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1807.02125 | Scalable Gaussian Processes with Grid-Structured Eigenfunctions
(GP-GRIEF) | We introduce a kernel approximation strategy that enables computation of the
Gaussian process log marginal likelihood and all hyperparameter derivatives in
$\mathcal{O}(p)$ time. Our GRIEF kernel consists of $p$ eigenfunctions found
using a Nystrom approximation from a dense Cartesian product grid of inducing
points. By exploiting algebraic properties of Kronecker and Khatri-Rao tensor
products, computational complexity of the training procedure can be practically
independent of the number of inducing points. This allows us to use arbitrarily
many inducing points to achieve a globally accurate kernel approximation, even
in high-dimensional problems. The fast likelihood evaluation enables type-I or
II Bayesian inference on large-scale datasets. We benchmark our algorithms on
real-world problems with up to two-million training points and $10^{33}$
inducing points.
| stat.ML cs.LG |
1807.02126 | Cognitive chimera states in human brain networks | The human brain is a complex dynamical system that gives rise to cognition
through spatiotemporal patterns of coherent and incoherent activity between
brain regions. As different regions dynamically interact to perform cognitive
tasks, variable patterns of partial synchrony can be observed, forming chimera
states. We propose that the emergence of such states plays a fundamental role
in the cognitive organization of the brain, and present a novel
cognitively-informed, chimera-based framework to explore how large-scale brain
architecture affects brain dynamics and function. Using personalized brain
network models, we systematically study how regional brain stimulation produces
different patterns of synchronization across predefined cognitive systems. We
then analyze these emergent patterns within our novel framework to understand
the impact of subject-specific and region-specific structural variability on
brain dynamics. Our results suggest a classification of cognitive systems into
four groups with differing levels of subject and regional variability that
reflect their different functional roles.
| q-bio.NC math.DS physics.data-an |
1807.02127 | Mixtures of blue phase liquid crystal with simple liquids: elastic
emulsions and cubic fluid cylinders | We investigate numerically the behaviour of a phase-separating mixture of a
blue phase I liquid crystal with an isotropic fluid. The resulting morphology
is primarily controlled by an inverse capillary number, $\chi$, setting the
balance between interfacial and elastic forces. When $\chi$ and the
concentration of the isotropic component are both low, the blue phase
disclination lattice templates a cubic array of fluid cylinders. For larger
$\chi$, the isotropic phase arranges primarily into liquid emulsion droplets
which coarsen very slowly, rewiring the blue phase disclination lines into an
amorphous elastic network. Our blue phase/simple fluid composites can be
externally manipulated: an electric field can trigger a morphological
transition between cubic fluid cylinder phases with different topologies.
| cond-mat.soft |
1807.02128 | Adaptive Path-Integral Autoencoder: Representation Learning and Planning
for Dynamical Systems | We present a representation learning algorithm that learns a low-dimensional
latent dynamical system from high-dimensional \textit{sequential} raw data,
e.g., video. The framework builds upon recent advances in amortized inference
methods that use both an inference network and a refinement procedure to output
samples from a variational distribution given an observation sequence, and
takes advantage of the duality between control and inference to approximately
solve the intractable inference problem using the path integral control
approach. The learned dynamical model can be used to predict and plan the
future states; we also present the efficient planning method that exploits the
learned low-dimensional latent dynamics. Numerical experiments show that the
proposed path-integral control based variational inference method leads to
tighter lower bounds in statistical model learning of sequential data. The
supplementary video: https://youtu.be/xCp35crUoLQ
| cs.LG cs.RO stat.ML |
1807.02129 | Operads and Maurer-Cartan spaces | This thesis is divided into two parts. The first one is composed of
recollections on operad theory, model categories, simplicial homotopy theory,
rational homotopy theory, Maurer-Cartan spaces, and deformation theory. The
second part deals with the theory of convolution algebras and some of their
applications, as explained below.
Suppose we are given a type of algebras, a type of coalgebras, and a
relationship between those types of algebraic structures (encoded by an operad,
a cooperad, and a twisting morphism respectively). Then, it is possible to
endow the space of linear maps from a coalgebra C and an algebra A with a
natural structure of Lie algebra up to homotopy. We call the resulting homotopy
Lie algebra the convolution algebra of A and C. We study the theory of
convolution algebras and their compatibility with the tools of homotopical
algebra: infinity morphisms and the homotopy transfer theorem. After doing
that, we apply this theory to various domains, such as derived deformation
theory and rational homotopy theory. In the first case, we use the tools we
developed to construct an universal Lie algebra representing the space of
Maurer-Cartan elements, a fundamental object of deformation theory. In the
second case, we generalize a result of Berglund on rational models for mapping
spaces between pointed topological spaces. In the last chapter of this thesis,
we give a new approach to two important theorems in deformation theory: the
Goldman-Millson theorem and the Dolgushev-Rogers theorem.
| math.AT math.QA |
1807.02130 | Learning to pinpoint effective operators at the LHC: a study of the
$t\bar{t}b\bar{b}$ signature | In the context of the Standard Model effective field theory (SMEFT), we study
the LHC sensitivity to four fermion operators involving heavy quarks by
employing cross section measurements in the $t\bar{t}b\bar{b}$ final state.
Starting from the measurement of total rates, we progressively exploit
kinematical information and machine learning techniques to optimize the
projected sensitivity at the end of Run III. Indeed, in final states with high
multiplicity containing inter-correlated kinematical information, multi-variate
methods provide a robust way of isolating the regions of phase space where the
SMEFT contribution is enhanced. We also show that training for multiple output
classes allows for the discrimination between operators mediating the
production of tops in different helicity states. Our projected sensitivities
not only constrain a host of new directions in the SMEFT parameter space but
also improve on existing limits demonstrating that, on one hand,
$t\bar{t}b\bar{b}$ production is an indispensable component in a future global
fit for top quark interactions in the SMEFT, and on the other, multi-class
machine learning algorithms can be a valuable tool for interpreting LHC data in
this framework.
| hep-ph |
1807.02131 | 3D Human Action Recognition with Siamese-LSTM Based Deep Metric Learning | This paper proposes a new 3D Human Action Recognition system as a two-phase
system: (1) Deep Metric Learning Module which learns a similarity metric
between two 3D joint sequences using Siamese-LSTM networks; (2) A Multiclass
Classification Module that uses the output of the first module to produce the
final recognition output. This model has several advantages: the first module
is trained with a larger set of data because it uses many combinations of
sequence pairs.Our deep metric learning module can also be trained
independently of the datasets, which makes our system modular and
generalizable. We tested the proposed system on standard and newly introduced
datasets that showed us that initial results are promising. We will continue
developing this system by adding more sophisticated LSTM blocks and by
cross-training between different datasets.
| cs.CV |
1807.02132 | Gradual Liquid Type Inference | Liquid typing provides a decidable refinement inference mechanism that is
convenient but subject to two major issues: (1) inference is global and
requires top-level annotations, making it unsuitable for inference of modular
code components and prohibiting its applicability to library code, and (2)
inference failure results in obscure error messages. These difficulties
seriously hamper the migration of existing code to use refinements. This paper
shows that gradual liquid type inference---a novel combination of liquid
inference and gradual refinement types---addresses both issues. Gradual
refinement types, which support imprecise predicates that are optimistically
interpreted, can be used in argument positions to constrain liquid inference so
that the global inference process e effectively infers modular specifications
usable for library components. Dually, when gradual refinements appear as the
result of inference, they signal an inconsistency in the use of static
refinements. Because liquid refinements are drawn from a nite set of
predicates, in gradual liquid type inference we can enumerate the safe
concretizations of each imprecise refinement, i.e. the static refinements that
justify why a program is gradually well-typed. This enumeration is useful for
static liquid type error explanation, since the safe concretizations exhibit
all the potential inconsistencies that lead to static type errors. We develop
the theory of gradual liquid type inference and explore its pragmatics in the
setting of Liquid Haskell.
| cs.PL |
1807.02133 | Prospects for axion searches with Advanced LIGO through binary mergers | The observation of gravitational waves from a binary neutron star merger by
LIGO/VIRGO and the associated electromagnetic counterpart provides a high
precision test of orbital dynamics, and therefore a new and sensitive probe of
extra forces and new radiative degrees of freedom. Axions are one particularly
well-motivated class of extensions to the Standard Model leading to new forces
and sources of radiation, which we focus on in this paper. Using an effective
field theory (EFT) approach, we calculate the first post-Newtonian corrections
to the orbital dynamics, radiated power, and gravitational waveform for binary
neutron star mergers in the presence of an axion. This result is applicable to
many theories which add an extra massive scalar degree of freedom to General
Relativity. We then perform a detailed forecast of the potential for Advanced
LIGO to constrain the free parameters of the EFT, and map these to the mass
$m_a$ and decay constant $f_a$ of the axion. At design sensitivity, we find
that Advanced LIGO can potentially exclude axions with $m_a \lesssim 10^{-11} \
{\rm eV}$ and $f_a \sim (10^{14} - 10^{17}) \ {\rm GeV}$. There are a variety
of complementary observational probes over this region of parameter space,
including the orbital decay of binary pulsars, black hole superradiance, and
laboratory searches. We comment on the synergies between these various
observables.
| hep-ph astro-ph.CO gr-qc hep-th |
1807.02134 | The Impact Of World War I On Relativity: Part III, The Aftermath | Neither the world nor science came to an end when the gunfire stopped on 11
November 1918 (close to 11 AM in some time zone), but neither would ever be the
same again. Part I of this inquiry (Observatory 138, 46-58, April 2018) looked
at the development of general relativity under the Rubric of Gerald Holton's
"Only Einstein, only there, only then." Part II (Observatory 138, 98 116, June,
2018) addressed the activities, relativistic, classical, and otherwise of many
(mostly) physicists who were interacting with Einstein, working on relativistic
gravity, or, sometimes, against it, and leaving tracks that can still be
followed. Part III considers some of what happened to Einstein, his theory of
gravity, and related science after the war and, perhaps, because of it. A
subset of the items will probably be familiar -- the 1919 eclipse expedition
and the founding of the International Astronomical Union the same year,
Einsteins 1921 Nobel Prize (for the discovery of the law of the photoelectric
effect). Others perhaps less so, including a flood of books about GR (pro and
con) with the end of paper rationing surely playing a role, AE's 1922 trip to
Paris, and the gory details, swings and roundabouts of gravitational
radiation/waves and the cosmological constant. It is left as an exercise for
the reader to decide which items are primarily scientific and which primarily
political. The long-range issues of "is general relativity the right theory of
gravity?" and "do we have better wars?" come at the end. And I am going to
start in a slightly improbable place.
| physics.hist-ph |
1807.02135 | Face Recognition Using Map Discriminant on YCbCr Color Space | This paper presents face recognition using maximum a posteriori (MAP)
discriminant on YCbCr color space. The YCbCr color space is considered in order
to cover the skin information of face image on the recognition process. The
proposed method is employed to improve the recognition rate and equal error
rate (EER) of the gray scale based face recognition. In this case, the face
features vector consisting of small part of dominant frequency elements which
is extracted by non-blocking DCT is implemented as dimensional reduction of the
raw face images. The matching process between the query face features and the
trained face features is performed using maximum a posteriori (MAP)
discriminant. From the experimental results on data from four face databases
containing 2268 images with 196 classes show that the face recognition YCbCr
color space provide better recognition rate and lesser EER than those of gray
scale based face recognition which improve the first rank of grayscale based
method result by about 4%. However, it requires three times more computation
time than that of grayscale based method.
| cs.CV |
1807.02136 | Detecting Visual Relationships Using Box Attention | We propose a new model for detecting visual relationships, such as "person
riding motorcycle" or "bottle on table". This task is an important step towards
comprehensive structured image understanding, going beyond detecting individual
objects. Our main novelty is a Box Attention mechanism that allows to model
pairwise interactions between objects using standard object detection
pipelines. The resulting model is conceptually clean, expressive and relies on
well-justified training and prediction procedures. Moreover, unlike previously
proposed approaches, our model does not introduce any additional complex
components or hyperparameters on top of those already required by the
underlying detection model. We conduct an experimental evaluation on three
challenging datasets, V-COCO, Visual Relationships and Open Images,
demonstrating strong quantitative and qualitative results.
| cs.CV |
1807.02137 | Multigrid Algorithm Based on Hybrid Smoothers for Variational and
Selective Segmentation Models | Automatic segmentation of an image to identify all meaningful parts is one of
the most challenging as well as useful tasks in a number of application areas.
This is widely studied. Selective segmentation, less studied, aims to use
limited user specified information to extract one or more interesting objects
(instead of all objects). Constructing a fast solver remains a challenge for
both classes of model. However our primary concern is on selective
segmentation. In this work, we develop an effective multigrid algorithm, based
on a new non-standard smoother to deal with non-smooth coefficients, to solve
the underlying partial differential equations (PDEs) of a class of variational
segmentation models in the level set formulation. For such models,
non-smoothness (or jumps) is typical as segmentation is only possible if edges
(jumps) are present. In comparison with previous multigrid methods which were
shown to produce an acceptable {\it mean} smoothing rate for related models,
the new algorithm can ensure a small and {\it global} smoothing rate that is a
sufficient condition for convergence. Our rate analysis is by Local Fourier
Analysis and, with it, we design the corresponding iterative solver, improving
on an ineffective line smoother. Numerical tests show that the new algorithm
outperforms multigrid methods based on competing smoothers.
| math.NA |
1807.02138 | The weak Lefschetz property of equigenerated monomial ideals | We determine a sharp lower bound for the Hilbert function in degree $d$ of a
monomial algebra failing the weak Lefschetz property over a polynomial ring
with $n$ variables and generated in degree $d$, for any $d\geq 2$ and $n\geq
3$. We consider artinian ideals in the polynomial ring with $n$ variables
generated by homogeneous polynomials of degree $d$ invariant under an action of
the cyclic group $\mathbb{Z}/d\mathbb{Z}$, for any $n\geq 3$ and any $d\geq 2$.
We give a complete classification of such ideals in terms of the weak Lefschetz
property depending on the action.
| math.AC |
1807.02139 | Fundamentally fastest optical processes at the surface of a topological
insulator | We predict that a single oscillation of a strong optical pulse can
significantly populate the surface conduction band of a three-dimensional
topological insulator, Bi2Se3. Both linearly- and circularly-polarized pulses
generate chiral textures of interference fringes of population in the surface
Brillouin zone. These fringes constitute a self-referenced electron hologram
carrying information on the topology of the surface Bloch bands, in particular,
on the effect of the warping term of the low-energy Hamiltonian. These
electron-interference phenomena are in a sharp contrast to graphene where there
are no chiral textures for a linearly-polarized pulse and no interference
fringes for circularly-polarized pulse. These predicted reciprocal space
electron-population textures can be measured experimentally by time resolved
angle resolved photoelectron spectroscopy (TR-ARPES) to gain direct access to
non-Abelian Berry curvature at topological insulator surfaces.
| cond-mat.mes-hall |
1807.02140 | Distances between zeroes and critical points for random polynomials with
i.i.d. zeroes | Consider a random polynomial $Q_n$ of degree $n+1$ whose zeroes are i.i.d.
random variables $\xi_0,\xi_1,\ldots,\xi_n$ in the complex plane. We study the
pairing between the zeroes of $Q_n$ and its critical points, i.e. the zeroes of
its derivative $Q_n'$. In the asymptotic regime when $n\to\infty$, with high
probability there is a critical point of $Q_n$ which is very close to $\xi_0$.
We localize the position of this critical point by proving that the difference
between $\xi_0$ and the critical point has approximately complex Gaussian
distribution with mean $1/(nf(\xi_0))$ and variance of order $\log n \cdot
n^{-3}$. Here, $f(z)= \mathbb E[1/(z-\xi_k)]$ is the Cauchy-Stieltjes transform
of the $\xi_k$'s. We also state some conjectures on critical points of
polynomials with dependent zeroes, for example the Weyl polynomials and
characteristic polynomials of random matrices.
| math.PR |
1807.02141 | Slow magnetoacoustic gravity waves in an equilibrium stratified solar
atmosphere: cut-off periods through the transition region | Assuming the thin flux tube approximation, we introduce an analytical model
that contemplates the presence of: a non-isothermal temperature; a varying
magnetic field and a non-uniform stratified medium in hydrostatic equilibrium
due to a constant gravity acceleration. This allows the study of slow
magnetoacoustic cut-off periods across the solar transition region, from the
base of the solar chromosphere to the lower corona. The used temperature
profile approaches the VAC solar atmospheric model. The periods obtained are
consistent with observations. Similar to the acoustic cut-off periods, the
resulting magnetoacoustic gravity ones follow the sharp temperature profile,
but shifted towards larger heights; in other words, at a given height the
magnetoacoustic cut-off period is significantly lower than the corresponding
acoustic one. Along a given longitude of an inclined thin magnetic tube, the
greater its inclination the softener the temperature gradient it crosses.
Changes in the magnetic field intensity do not significantly modify the periods
at the coronal level but modulate the values below the transition region within
periods between $\sim [2\,- 6]\,$min. Within the limitations of our model, we
show that monochromatic oscillations of the solar atmosphere are the
atmospheric response at its natural frequency to random or impulsive
perturbations, and not a consequence of the forcing from the photosphere.
| astro-ph.SR |
1807.02142 | Metallicity gradients in the globular cluster systems of early-type
galaxies: In-situ and accreted components? | Massive early-type galaxies typically have two subpopulations of globular
clusters (GCs) which often reveal radial colour (metallicity) gradients.
Collating gradients from the literature, we show that the gradients in the
metal-rich and metal-poor GC subpopulations are the same, within measurement
uncertainties, in a given galaxy. Furthermore, these GC gradients are similar
in strength to the {\it stellar} metallicity gradient of the host galaxy. At
the very largest radii (e.g. greater than 8 galaxy effective radii) there is
some evidence that the GC gradients become flat with near constant mean
metallicity. Using stellar metallicity gradients as a proxy, we probe the
assembly histories of massive early-type galaxies with hydrodynamical
simulations from the Magneticum suite of models. In particular, we measure the
stellar metallicity gradient for the in-situ and accreted components over a
similar radial range as those observed for GC subpopulations. We find that the
in-situ and accreted stellar metallicity gradients are similar but have a
larger scatter than the metal-rich and metal-poor GC subpopulations gradients
in a given galaxy. We conclude that although metal-rich GCs are predominately
formed during the in-situ phase and metal-poor GCs during the accretion phase
of massive galaxy formation, they do not have a strict one-to-one connection.
| astro-ph.GA astro-ph.CO |
1807.02143 | Spatiotemporal KSVD Dictionary Learning for Online Multi-target Tracking | In this paper, we present a new spatial discriminative KSVD dictionary
algorithm (STKSVD) for learning target appearance in online multi-target
tracking. Different from other classification/recognition tasks (e.g. face,
image recognition), learning target's appearance in online multi-target
tracking is impacted by factors such as posture/articulation changes, partial
occlusion by background scene or other targets, background changes (human
detection bounding box covers human parts and part of the scene), etc. However,
we observe that these variations occur gradually relative to spatial and
temporal dynamics. We characterize the spatial and temporal information between
target's samples through a new STKSVD appearance learning algorithm to better
discriminate sparse code, linear classifier parameters and minimize
reconstruction error in a single optimization system. Our appearance learning
algorithm and tracking framework employ two different methods of calculating
appearance similarity score in each stage of a two-stage association: a linear
classifier in the first stage, and minimum residual errors in the second stage.
The results tested using 2DMOT2015 dataset and its public Aggregated Channel
features (ACF) human detection for all comparisons show that our method
outperforms the existing related learning methods.
| cs.CV |
1807.02144 | Ergodic invariant measures on the space of geodesic currents | Let $S$ be a compact, connected, oriented surface, possibly with boundary, of
negative Euler characteristic. In this article we extend
Lindenstrauss-Mirzakhani's and Hamenst\"adt's classification of locally finite
mapping class group invariant ergodic measures on the space of measured
laminations $\mathcal{M}\mathcal{L}(S)$ to the space of geodesic currents
$\mathcal{C}(S)$, and we discuss the homogeneous case. Moreover, we extend
Lindenstrauss-Mirzakhani's classification of orbit closures to
$\mathcal{C}(S)$. Our argument relies on their results and on the decomposition
of a current into a sum of three currents with isotopically disjoint supports:
a measured lamination without closed leaves, a simple multi-curve and a current
that binds its hull.
| math.GT math.DS |
1807.02145 | Nature of the $\Omega$(2012) through its strong decays | We extend our previous analysis on the mass of the recently discovered
$\Omega(2012)$ state by investigation of its strong decays and calculation of
its width employing the method of light cone QCD sum rule. Considering two
possibilities for the quantum numbers of $\Omega(2012)$ state, namely $1P$
orbital excitation with $J^P=\frac{3}{2}^-$ and $2S$ radial excitation with
$J^P=\frac{3}{2}^+$, we obtain the strong coupling constants defining the
$\Omega(1P/2S)\rightarrow\Xi K$ decays. The results of the coupling constants
are then used to calculate the decay width corresponding to each possibility.
Comparison of the obtained results on the total widths in this work with the
experimental value and taking into account the results of our previous mass
prediction on the $\Omega(2012)$ state, we conclude that this state is $1P$
orbital excitation of the ground state $\Omega$ baryon, whose quantum numbers
are $J^P=\frac{3}{2}^-$.
| hep-ph hep-ex hep-lat |
1807.02146 | Absence of Criticality in the Phase Transitions of Open Floquet Systems | We address the nature of phase transitions in periodically driven systems
coupled to a bath. The latter enables a synchronized non-equilibrium Floquet
steady state at finite entropy, which we analyse for rapid drives within a
non-equilibrium RG approach. While the infinitely rapidly driven limit exhibits
a second order phase transition, here we reveal that fluctuations turn the
transition first order when the driving frequency is finite. This can be traced
back to a universal mechanism, which crucially hinges on the competition of
degenerate, near critical modes associated to higher Floquet Brillouin zones.
The critical exponents of the infinitely rapidly driven system -- including a
new, independent one -- can yet be probed experimentally upon smoothly tuning
towards that limit.
| cond-mat.stat-mech cond-mat.quant-gas hep-th |
1807.02147 | Theory for strained graphene beyond the Cauchy-Born rule | The low-energy electronic properties of strained graphene are usually
obtained by transforming the bond vectors according to the Cauchy-Born rule. In
this work, we derive a new effective Dirac Hamiltonian by assuming a more
general transformation rule for the bond vectors under uniform strain, which
takes into account the strain-induced relative displacement between the two
sublattices of graphene. Our analytical results show that the consideration of
such relative displacement yields a qualitatively different Fermi velocity with
respect to previous reports. Furthermore, from the derived Hamiltonian, we
analyze effects of this relative displacement on the local density of states
and the optical conductivity, as well as the implications on the scanning
tunneling spectroscopy, including external magnetic field, and optical
transmittance experiments of strained graphene.
| cond-mat.mes-hall |
1807.02148 | The twin paradox: the role of acceleration | The twin paradox, which evokes from the the idea that two twins may age
differently because of their relative motion, has been studied and explained
ever since it was first described in 1906, the year after special relativity
was invented. The question can be asked: "Is there anything more to say?" It
seems evident that acceleration has a role to play, however this role has
largely been brushed aside since it is not required in calculating, in a
preferred reference frame, the relative age difference of the twins. Indeed, if
one tries to calculate the age difference from the point of the view of the
twin that undergoes the acceleration, then the role of the acceleration is
crucial and cannot be dismissed. In the resolution of the twin paradox, the
role of the acceleration has been denigrated to the extent that it has been
treated as a red-herring. This is a mistake and shows a clear misunderstanding
of the twin paradox.
| gr-qc physics.class-ph |
1807.02149 | Large gaps of CUE and GUE | In this article, we study the largest gaps of the classical random matrices
of CUE and GUE, and we will derive the rescaling limit of the $k$-th largest
gap, which is given by the Gumbel distribution.
| math.PR |
1807.02150 | Scalable Recommender Systems through Recursive Evidence Chains | Recommender systems can be formulated as a matrix completion problem,
predicting ratings from user and item parameter vectors. Optimizing these
parameters by subsampling data becomes difficult as the number of users and
items grows. We develop a novel approach to generate all latent variables on
demand from the ratings matrix itself and a fixed pool of parameters. We
estimate missing ratings using chains of evidence that link them to a small set
of prototypical users and items. Our model automatically addresses the
cold-start and online learning problems by combining information across both
users and items. We investigate the scaling behavior of this model, and
demonstrate competitive results with respect to current matrix factorization
techniques in terms of accuracy and convergence speed.
| cs.IR cs.LG stat.ML |
1807.02151 | On Ergodic Capacity and Optimal Number of Tiers in UAV-Assisted
Communication Systems | In this paper, we consider unmanned aerial vehicle (UAV) assisted
communication systems where a number of UAVs are utilized as multi-tier relays
between a number of users and a base-transceiver station (BTS). We model the
wireless propagation channel between the users and the BTS as a Rayleigh
product channel, which is a product of a series of independent and identically
distributed (i.i.d.) Rayleigh multi-input multi-output (MIMO) channels. We put
a special interested in optimizing the number of tiers in such UAV-assisted
systems for a given total number of UAVs to maximize the ergodic capacity. To
achieve this goal, in a first part we derive a lower-bound in closed-form for
the ergodic capacity which is shown to be asymptotically tight as
signal-to-noise ratio (SNR) increases. With the derived bound, in a second part
we analyze the optimal number of UAV-tiers, and propose a low-complexity
procedure that significantly reduces the search-size and yields near-optimal
performance. Moreover, asymptotic properties both for the ergodic capacity of
Rayleigh product channel, and the optimal solutions on number of tiers are
extensively analyzed.
| cs.IT math.IT |
1807.02152 | Automatic deep learning-based normalization of breast dynamic
contrast-enhanced magnetic resonance images | Objective: To develop an automatic image normalization algorithm for
intensity correction of images from breast dynamic contrast-enhanced magnetic
resonance imaging (DCE-MRI) acquired by different MRI scanners with various
imaging parameters, using only image information. Methods: DCE-MR images of 460
subjects with breast cancer acquired by different scanners were used in this
study. Each subject had one T1-weighted pre-contrast image and three
T1-weighted post-contrast images available. Our normalization algorithm
operated under the assumption that the same type of tissue in different
patients should be represented by the same voxel value. We used four
tissue/material types as the anchors for the normalization: 1) air, 2) fat
tissue, 3) dense tissue, and 4) heart. The algorithm proceeded in the following
two steps: First, a state-of-the-art deep learning-based algorithm was applied
to perform tissue segmentation accurately and efficiently. Then, based on the
segmentation results, a subject-specific piecewise linear mapping function was
applied between the anchor points to normalize the same type of tissue in
different patients into the same intensity ranges. We evaluated the algorithm
with 300 subjects used for training and the rest used for testing. Results: The
application of our algorithm to images with different scanning parameters
resulted in highly improved consistency in pixel values and extracted radiomics
features. Conclusion: The proposed image normalization strategy based on tissue
segmentation can perform intensity correction fully automatically, without the
knowledge of the scanner parameters. Significance: We have thoroughly tested
our algorithm and showed that it successfully normalizes the intensity of
DCE-MR images. We made our software publicly available for others to apply in
their analyses.
| cs.CV |
1807.02153 | Measurement of D0 ->omega eta Branching Fraction with CLEO-c Data | Using CLEO-c data, we confirm the observation of D0 ->omega eta by BESIII. In
the Dalitz Plot of D0 -> Kshort eta pi0, we find a background in the
Kshort(->pipi)pi0 projection with a m(pipipi0) equal to the omega(782) mass. In
a direct search for D0 -> (omega eta) we find a clear signal and measure BF(D0
->omega eta) = (1.78+/-0.19+/-0.14) x 10**(-3), in good agreement with BESIII.
| hep-ex |
1807.02154 | Betti numbers of toric ideals of graphs: A case study | We compute the graded Betti numbers for the toric ideal of a family of graphs
constructed by adjoining a cycle to a complete bipartite graph. The key
observation is that this family admits an initial ideal which has linear
quotients. As a corollary, we compute the Hilbert series and $h$-vector for all
the toric ideals of graphs in this family.
| math.AC math.CO |
1807.02155 | Gridbot: An autonomous robot controlled by a Spiking Neural Network
mimicking the brain's navigational system | It is true that the "best" neural network is not necessarily the one with the
most "brain-like" behavior. Understanding biological intelligence, however, is
a fundamental goal for several distinct disciplines. Translating our
understanding of intelligence to machines is a fundamental problem in robotics.
Propelled by new advancements in Neuroscience, we developed a spiking neural
network (SNN) that draws from mounting experimental evidence that a number of
individual neurons is associated with spatial navigation. By following the
brain's structure, our model assumes no initial all-to-all connectivity, which
could inhibit its translation to a neuromorphic hardware, and learns an
uncharted territory by mapping its identified components into a limited number
of neural representations, through spike-timing dependent plasticity (STDP). In
our ongoing effort to employ a bioinspired SNN-controlled robot to real-world
spatial mapping applications, we demonstrate here how an SNN may robustly
control an autonomous robot in mapping and exploring an unknown environment,
while compensating for its own intrinsic hardware imperfections, such as
partial or total loss of visual input.
| q-bio.NC cs.AI |
1807.02156 | A Geometric Interpretation of the Intertwining Number | We exhibit a connection between two statistics on set partitions, the
intertwining number and the depth-index. In particular, results link the
intertwining number to the algebraic geometry of Borel orbits. Furthermore, by
studying the generating polynomials of our statistics, we determine the $q=-1$
specialization of a $q$-analogue of the Bell numbers. Finally, by using
Renner's $H$-polynomial of an algebraic monoid, we introduce and study a
$t$-analog of $q$-Stirling numbers.
| math.CO |
1807.02157 | Fluctuations and noise-limited sensing near the exceptional point of
$\mathcal{PT}$-symmetric resonator systems | We theoretically explore the role of mesoscopic fluctuations and noise on the
spectral and temporal properties of systems of $\mathcal{PT}$-symmetric coupled
gain-loss resonators operating near the exceptional point, where eigenvalues
and eigenvectors coalesce. We show that the inevitable detuning in the
frequencies of the uncoupled resonators leads to an unavoidable modification of
the conditions for reaching the exceptional point, while, as this point is
approached in ensembles of resonator pairs, statistical averaging significantly
smears the spectral features. We also discuss how these fluctuations affect the
sensitivity of sensors based on coupled $\mathcal{PT}$-symmetric resonators.
Finally, we show that temporal fluctuations in the detuning and gain of these
sensors lead to a quadratic growth of the optical power in time, thus implying
that maintaining operation at the exceptional point over a long period can be
rather challenging. Our theoretical analysis clarifies issues central to the
realization of $\mathcal{PT}$-symmetric devices, and should facilitate future
experimental work in the field.
| cond-mat.mes-hall physics.optics |
1807.02158 | Some results on affine Deligne-Lusztig varieties | The study of affine Deligne-Lusztig varieties originally arose from
arithmetic geometry, but many problems on affine Deligne-Lusztig varieties are
purely Lie-theoretic in nature. This survey deals with recent progress on
several important problems on affine Deligne-Lusztig varieties. The emphasis is
on the Lie-theoretic aspect, while some connections and applications to
arithmetic geometry will also be mentioned.
| math.AG math.NT math.RT |
1807.02159 | Entangled-path interferometer simpler, faster than LISA | Entangled light can provide a seminal improvement in resolution sensitivity
even without achieving Heisenberg limit in a single channel. In this paper,
based on the back-of-the-envelope type calculations, I demonstrate an
alternative path to space based long-arm interferometer. Its advantage with
respect to LISA is that it does not require complex satellites with many active
components to achieve similar resolution.
| quant-ph astro-ph.IM |
1807.02160 | Affine-Goldstone/quartet-metric gravity: emergent vs. existent | As a group-theoretic foundation of gravity, it is considered an
affine-Goldstone nonlinear model based upon the nonlinear realization of the
global affine symmetry spontaneously broken at the Planck scale to the Poincare
symmetry. It is shown that below this scale the model justifies and elaborates
an earlier introduced effective field theory of the quartet-metric gravity
incorporating the gravitational dark substances emerging in addition to the
tensor graviton. The prospects for subsequent going beyond the nonlinear model
above the Planck scale are indicated.
| gr-qc hep-ph |
1807.02161 | Minimizing Sensitivity to Model Misspecification | We propose a framework for estimation and inference when the model may be
misspecified. We rely on a local asymptotic approach where the degree of
misspecification is indexed by the sample size. We construct estimators whose
mean squared error is minimax in a neighborhood of the reference model, based
on one-step adjustments. In addition, we provide confidence intervals that
contain the true parameter under local misspecification. As a tool to interpret
the degree of misspecification, we map it to the local power of a specification
test of the reference model. Our approach allows for systematic sensitivity
analysis when the parameter of interest may be partially or irregularly
identified. As illustrations, we study three applications: an empirical
analysis of the impact of conditional cash transfers in Mexico where
misspecification stems from the presence of stigma effects of the program, a
cross-sectional binary choice model where the error distribution is
misspecified, and a dynamic panel data binary choice model where the number of
time periods is small and the distribution of individual effects is
misspecified.
| econ.EM stat.ME |
1807.02162 | Feature Assisted bi-directional LSTM Model for Protein-Protein
Interaction Identification from Biomedical Texts | Knowledge about protein-protein interactions is essential in understanding
the biological processes such as metabolic pathways, DNA replication, and
transcription etc. However, a majority of the existing Protein-Protein
Interaction (PPI) systems are dependent primarily on the scientific literature,
which is yet not accessible as a structured database. Thus, efficient
information extraction systems are required for identifying PPI information
from the large collection of biomedical texts. Most of the existing systems
model the PPI extraction task as a classification problem and are tailored to
the handcrafted feature set including domain dependent features. In this paper,
we present a novel method based on deep bidirectional long short-term memory
(B-LSTM) technique that exploits word sequences and dependency path related
information to identify PPI information from text. This model leverages joint
modeling of proteins and relations in a single unified framework, which we name
as Shortest Dependency Path B-LSTM (sdpLSTM) model. We perform experiments on
two popular benchmark PPI datasets, namely AiMed & BioInfer. The evaluation
shows the F1-score values of 86.45% and 77.35% on AiMed and BioInfer,
respectively. Comparisons with the existing systems show that our proposed
approach attains state-of-the-art performance.
| cs.IR cs.CL |
1807.02163 | Testing logarithmic corrections on $R^2$-exponential gravity by
observational data | This paper is devoted to the analysis of a class of $F(R)$ gravity, where
additional logarithmic corrections are assumed. The gravitational action
includes an exponential term and a $R^2$ inflationary term, both with
logarithmic corrections. This model can unify an early time inflationary era
and also the late time acceleration of the universe expansion. This model is
deeply analysed, confronting with recent observational data coming from the
largest Pantheon Type Ia supernovae sample, the latest measurements of the
Hubble parameter $H(z)$, manifestations of Baryon Acoustic Oscillations and
Cosmic Microwave Background radiation. The viability of the model is studied
and the corresponding constraints on the free parameters are obtained, leading
to an statistical analysis in comparison to $\Lambda$CDM model. The
inflationary era is also analysed within this model and its compatibility with
the latest observational data for the spectral index of primordial curvature
perturbations and the scalar-to-tensor ratio. Finally, possible corrections on
the Newton's law and constraints due to primordial nucleosynthesis are
analysed.
| gr-qc astro-ph.CO |
1807.02164 | V-CNN: When Convolutional Neural Network encounters Data Visualization | In recent years, deep learning poses a deep technical revolution in almost
every field and attracts great attentions from industry and academia.
Especially, the convolutional neural network (CNN), one representative model of
deep learning, achieves great successes in computer vision and natural language
processing. However, simply or blindly applying CNN to the other fields results
in lower training effects or makes it quite difficult to adjust the model
parameters. In this poster, we propose a general methodology named V-CNN by
introducing data visualizing for CNN. V-CNN introduces a data visualization
model prior to CNN modeling to make sure the data after processing is fit for
the features of images as well as CNN modeling. We apply V-CNN to the network
intrusion detection problem based on a famous practical dataset: AWID.
Simulation results confirm V-CNN significantly outperforms other studies and
the recall rate of each invasion category is more than 99.8%.
| cs.HC cs.LG stat.ML |
1807.02165 | On the determination of nonlinear terms appearing in semilinear
hyperbolic equations | We consider the inverse problem of determining a general nonlinear term
appearing in a semilinear hyperbolic equation on a Riemannian manifold with
boundary $(M,g)$ of dimension $n=2,3$. We prove results of unique recovery of
the nonlinear term $F(t,x,u)$, appearing in the equation
$\partial_t^2u-\Delta_gu+F(t,x,u)=0$ on $(0,T)\times M$ with $T>0$, from some
partial knowledge of the solutions $u$ on the boundary of the time-space
cylindrical manifold $(0,T)\times M$ or on the lateral boundary
$(0,T)\times\partial M$. We determine the expression $F(t,x,u)$ both on the
boundary $x\in\partial M$ and inside the manifold $x\in M$.
| math.AP |
1807.02166 | Oscillation modes of hybrid stars within the relativistic Cowling
approximation | The first direct detection of gravitational waves has opened a new window to
study the Universe and would probably start a new era: the gravitational wave
Astronomy. Gravitational waves emitted by compact objects like neutron stars
could provide significant information about their structure, composition and
evolution.
In this paper we calculate, using the relativistic Cowling approximation, the
oscillations of compact stars focusing on hybrid stars, with and without a
mixed phase in their cores. We study the existence of a possible hadron-quark
phase transition in the central regions of neutron stars and the changes it
produces on the gravitational modes frequencies emitted by these stars. We pay
particular attention to the $g$-modes, which are extremely important as they
could signal the existence of pure quark matter inside neutron stars. Our
results show a relationship between the frequency of the $g$-modes and the
constant speed of sound parametrization for the quark matter phase. We also
show that the inclusion of color superconductivity produces an increase on the
oscillation frequencies.
We propose that observations of $g$-modes with frequencies $f_{\rm g}$
between $1$ kHz and $1.5$ kHz should be interpreted as an evidence of a sharp
hadron-quark phase transition in the core of a compact object.
| astro-ph.HE |
1807.02167 | A $Z'$-model and the magnetism of a dark fermion candidate | Our contribution sets out to investigate the phenomenology of a gauge model
based on an $SU_{L}(2) \times U_{R}(1)_{Q} \times U(1)_{Q'}$-symmetry group.
The model can accommodate, through its symmetry-breaking pattern, a candidate
to a heavy $Z'$-boson at the TeV-scale. The extended Higgs sector introduces a
heavy scalar whose mass lies in the region $1.2-3.7 \, \mbox{TeV}$. The fermion
sector includes an exotic candidate to Dark Matter that mixes with the
right-handed neutrino component in the Higgs sector, so that the whole field
content ensures the cancellation of the $U(1)$-quiral anomaly. The masses are
fixed according to the particular way the symmetry breaking takes place. In
view of the possible symmetry breakdown pattern, we study the phenomenological
implications in a high-energy scenario. We worek out the magnetic dipole
momentum (MDM) of the exotic fermion and the transition MDM due to its mixing
with the right-neutrino.
| hep-ph hep-th |
1807.02168 | The halon: a quasiparticle featuring critical charge fractionalization | The halon is a special critical state of an impurity in a quantum-critical
environment. The hallmark of the halon physics is that a well-defined integer
charge gets fractionalized into two parts: a microscopic core with half-integer
charge and a critically large halo carrying a complementary charge of $\pm
1/2$. The halon phenomenon emerges when the impurity--environment interaction
is fine-tuned to the vicinity of a boundary quantum critical point (BQCP), at
which the energies of two quasiparticle states with adjacent integer charges
approach each other. The universality class of such BQCP is captured by a model
of pseudo-spin-$1/2$ impurity coupled to the quantum-critical environment, in
such a way that the rotational symmetry in the pseudo-spin $xy$-plane is
respected, with a small local "magnetic" field along the pseudo-spin $z$-axis
playing the role of control parameter driving the system away from the BQCP. On
the approach to BQCP, the half-integer projection of the pseudo-spin on its
$z$-axis gets delocalized into a halo of critically divergent radius, capturing
the essence of the phenomenon of charge fractionalization. With large-scale
Monte Carlo simulations, we confirm the existence of halons---and quantify
their universal features---in O(2) and O(3) quantum critical systems.
| cond-mat.quant-gas quant-ph |
1807.02169 | Quantum master equations for entangled qubit environments | We study the Markovian dynamics of a collection of n quantum systems coupled
to an irreversible environmental channel consisting of a stream of n entangled
qubits. Within the framework of repeated quantum interactions, we derive the
master equation that describes the dynamics of the composite quantum system. We
investigate the evolution of the joint system for two-qubit environments and
find that (1) the presence of antidiagonal coherences (in the local basis) in
the environment is a necessary condition for entangling two remote systems, and
(2) that maximally entangled two-qubit baths are an exceptional point without a
unique steady state. For the general case of n-qubit environments we show that
coherences in maximally entangled baths (when expressed in the local energy
basis), do not affect the system evolution in the weak coupling regime
| quant-ph |
1807.02170 | First Point-Spread Function and X-Ray Phase-Contrast Imaging Results
With an 88-mm Diameter Single Crystal | In this study, we report initial demonstrations of the use of single crystals
in indirect x-ray imaging with a benchtop implementation of propagation-based
(PB) x-ray phase contrast imaging. Based on single Gaussian peak fits to the
x-ray images, we observed a four times smaller system point-spread function
(PSF) with the 50-{\mu}m thick single crystal scintillators than with the
reference polycrystalline phosphor/scintillator. Fiber-optic plate
depth-of-focus and Al reflective-coating aspects are also elucidated. Guided by
the results from the 25-mm diameter crystal samples, we report additionally the
first results with a unique 88-mm diameter single crystal bonded to a fiber
optic plate and coupled to the large format CCD. Both PSF and x-ray phase
contrast imaging data are quantified and presented.
| physics.ins-det physics.acc-ph |
1807.02171 | Analysis of continuous and discrete Wigner approximations for spin
dynamics | We compare the continuous and discrete truncated Wigner approximations of
various spin models' dynamics to exact analytical and numerical solutions. We
account for all components of spin-spin correlations on equal footing,
facilitated by a recently introduced geometric correlation matrix visualization
technique [R. Mukherjee {\em et al.}, Phys. Rev. A {\bf 97}, 043606 (2018)]. We
find that at modestly short times, the dominant error in both approximations is
to substantially suppress spin correlations along one direction.
| quant-ph cond-mat.quant-gas |
1807.02172 | Curved detectors developments and characterization: application to
astronomical instruments | Many astronomical optical systems have the disadvantage of generating curved
focal planes requiring flattening optical elements to project the corrected
image on flat detectors. The use of these designs in combination with a
classical flat sensor implies an overall degradation of throughput and system
performances to obtain the proper corrected image. With the recent development
of curved sensor this can be avoided. This new technology has been gathering
more and more attention from a very broad community, as the potential
applications are multiple: from low-cost commercial to high impact scientific
systems, to mass-market and on board cameras, defense and security, and
astronomical community. We describe here the first concave curved CMOS detector
developed within a collaboration between CNRS- LAM and CEA-LETI. This
fully-functional detector 20 Mpix (CMOSIS CMV20000) has been curved down to a
radius of Rc = 150 mm over a size of 24x32 mm^2 . We present here the
methodology adopted for its characterization and describe in detail all the
results obtained. We also discuss the main components of noise, such as the
readout noise, the fixed pattern noise and the dark current. Finally we provide
a comparison with the flat version of the same sensor in order to establish the
impact of the curving process on the main characteristics of the sensor.
| astro-ph.IM |
1807.02173 | A survey on subjecting electronic product code and non-ID objects to IP
identification | Over the last decade, both research on the Internet of Things (IoT) and
real-world IoT applications have grown exponentially. The IoT provides us with
smarter cities, intelligent homes, and generally more comfortable lives.
However, the introduction of these devices has led to several new challenges
that must be addressed. One of the critical challenges facing interacting with
IoT devices is to address billions of devices (things) around the world,
including computers, tablets, smartphones, wearable devices, sensors, and
embedded computers, and so on. This article provides a survey on subjecting
Electronic Product Code and non-ID objects to IP identification for IoT
devices, including their advantages and disadvantages thereof. Different
metrics are here proposed and used for evaluating these methods. In particular,
the main methods are evaluated in terms of their: (i) computational overhead,
(ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether
applicable to already ID-based objects and presented in tabular format.
Finally, the article proves that this field of research will still be ongoing,
but any new technique must favorably offer the mentioned five evaluative
parameters.
| cs.NI |
1807.02174 | Locally $p$-admissible measures on $\mathbb{R}$ | In this note we show that locally $p$-admissible measures on $\mathbb{R}$
necessarily come from local Muckenhoupt $A_p$ weights. In the proof we employ
the corresponding characterization of global $p$-admissible measures on
$\mathbb{R}$ in terms of global $A_p$ weights due to Bj\"orn, Buckley and
Keith, together with tools from analysis in metric spaces, more specifically
preservation of the doubling condition and Poincar\'e inequalities under
flattening, due to Durand-Cartagena and Li. As a consequence, the class of
locally $p$-admissible weights on $\mathbb{R}$ is invariant under addition and
satisfies the lattice property. We also show that measures that are
$p$-admissible on an interval can be partially extended by periodical
reflections to global $p$-admissible measures. Surprisingly, the
$p$-admissibility has to hold on a larger interval than the reflected one, and
an example shows that this is necessary.
| math.MG math.FA |
1807.02175 | Adaptive Paired-Comparison Method for Subjective Video Quality
Assessment on Mobile Devices | To effectively evaluate subjective visual quality in weakly-controlled
environments, we propose an Adaptive Paired Comparison method based on particle
filtering. As our approach requires each sample to be rated only once, the test
time compared to regular paired comparison can be reduced. The method works
with non-experts and improves reliability compared to MOS and DS-MOS methods.
| stat.AP eess.IV |
1807.02176 | A stochastic Levenberg-Marquardt method using random models with
complexity results | Globally convergent variants of the Gauss-Newton algorithm are often the
methods of choice to tackle nonlinear least-squares problems. Among such
frameworks, Levenberg-Marquardt and trust-region methods are two
well-established, similar paradigms. Both schemes have been studied when the
Gauss-Newton model is replaced by a random model that is only accurate with a
given probability. Trust-region schemes have also been applied to problems
where the objective value is subject to noise: this setting is of particular
interest in fields such as data assimilation, where efficient methods that can
adapt to noise are needed to account for the intrinsic uncertainty in the input
data.
In this paper, we describe a stochastic Levenberg-Marquardt algorithm that
handles noisy objective function values and random models, provided sufficient
accuracy is achieved in probability. Our method relies on a specific scaling of
the regularization parameter, that allows us to leverage existing results for
trust-region algorithms. Moreover, we exploit the structure of our objective
through the use of a family of stationarity criteria tailored to least-squares
problems. Provided the probability of accurate function estimates and models is
sufficiently large, we bound the expected number of iterations needed to reach
an approximate stationary point, which generalizes results based on using
deterministic models or noiseless function values. We illustrate the link
between our approach and several applications related to inverse problems and
machine learning.
| math.OC |
1807.02177 | Higher Structures in Homotopy Type Theory | The intended model of the homotopy type theories used in Univalent
Foundations is the infinity-category of homotopy types, also known as
infinity-groupoids. The problem of higher structures is that of constructing
the homotopy types needed for mathematics, especially those that aren't sets.
The current repertoire of constructions, including the usual type formers and
higher inductive types, suffice for many but not all of these. We discuss the
problematic cases, typically those involving an infinite hierarchy of coherence
data such as semi-simplicial types, as well as the problem of developing the
meta-theory of homotopy type theories in Univalent Foundations. We also discuss
some proposed solutions.
| math.LO |
1807.02178 | A Cheeger-M\"uller theorem for manifolds with wedge singularities | We study the spectrum and heat kernel of the Hodge Laplacian with
coefficients in a flat bundle on a closed manifold degenerating to a manifold
with wedge singularities. Provided the Hodge Laplacians in the fibers of the
wedge have an appropriate spectral gap, we give uniform constructions of the
resolvent and heat kernel on suitable manifolds with corners. When the wedge
manifold and the base of the wedge are odd dimensional, this is used to obtain
a Cheeger-M\"uller theorem relating analytic torsion with the Reidemeister
torsion of the natural compactification by a manifold with boundary.
| math.DG math.AP math.SP |
1807.02179 | Interpolating factorizations for acyclic Donaldson--Thomas invariants | We prove a family of factorization formulas for the combinatorial
Donaldson--Thomas invariant for an acyclic quiver. A quantum dilogarithm
identity due to Reineke, later interpreted by Rimanyi by counting codimensions
of quiver loci, gives two extremal cases of our formulation in the Dynkin case.
We establish our interpolating factorizations explicitly with a dimension
counting argument by defining certain stratifications of the space of
representations for the quiver and calculating Betti numbers in the
corresponding equivariant cohomology algebras.
| math.RT math.AG math.AT |
1807.02180 | Engineered Chiral Skyrmion and Skyrmionium States by the Gradient of
Curvature | Curvilinear nanomagnets can support magnetic skyrmions stabilized at a local
curvature without any intrinsic chiral interactions. Here, we propose a new
mechanism to stabilize chiral N\'{e}el skyrmion states relying on the
\textit{gradient} of curvature. We illustrate our approach with an example of a
magnetic thin film with perpendicular magnetic anisotropy shaped as a circular
indentation. We show that in addition to the topologically trivial ground
state, there are two skyrmion states with winding numbers $\pm 1$ and a
skyrmionium state with a winding number $0$. These chiral states are formed due
to the pinning of a chiral magnetic domain wall at a bend of the
nanoindentation due to spatial inhomogeneity of the curvature-induced
Dzyaloshinskii--Moriya interaction. The latter emerges due to the gradient of
the local curvature at a bend. While the chirality of the skyrmion is
determined by the sign of the local curvature, its radius can be varied in a
broad range by engineering the position of the bend with respect to the center
of the nanoindentation. We propose a general method, which enables one to
reduce a magnetic problem for any surface of revolution to the common planar
problem by means of proper modification of constants of anisotropy and
Dzyaloshinskii--Moriya interaction.
| cond-mat.mes-hall cond-mat.str-el |
1807.02181 | The Conformal Anomaly and a new Exact RG | For scalar field theory, a new generalization of the Exact RG to curved space
is proposed, in which the conformal anomaly is explicitly present. Vacuum terms
require regularization beyond that present in the canonical formulation of the
Exact RG, which can be accomplished by adding certain free fields, each at a
non-critical fixed-point. Taking the Legendre transform, the sole effect of the
regulator fields is to remove a divergent vacuum term and they do not
explicitly appear in the effective average action. As an illustration, both the
integrated conformal anomaly and Polyakov action are recovered for the Gaussian
theory in d=2.
| hep-th cond-mat.stat-mech gr-qc |
1807.02182 | Detector setup of the VIP2 Underground Experiment at LNGS | The VIP2 experiment tests the Pauli Exclusion Principle with high
sensitivity, by searching for Pauli-forbidden atomic transitions from the 2p to
the 1s shell in copper at about 8keV. The transition energy of Pauli-forbidden
K X-rays is shifted by about 300 eV with respect to the normal allowed K line.
This energy difference can be resolved using Silicon Drift Detectors. The data
for this experiment is taken in the Gran Sasso underground laboratory (LNGS),
which provides shielding from cosmic radiation. An overview of the detection
system of the VIP2 experiment will be given. This includes the Silicon Drift
Detectors used as X-ray detectors which provide an energy resolution of around
150 eV at 6 keV and timing information for active shielding. Furthermore, the
low maintenance requirement makes them excellent X-ray detectors for the use in
an underground laboratory. The VIP2 setup will be discussed which consists of a
high current target system and a passive as well as an active shielding system
using plastic scintillators read out by Silicon Photomultipliers.
| physics.ins-det quant-ph |
1807.02183 | Application of the Complex Kohn Variational Method to Attosecond
Spectroscopy | The complex Kohn variational method is extended to compute light-driven
electronic transitions between continuum wavefunctions in atomic and molecular
systems. This development enables the study of multiphoton processes in the
perturbative regime for arbitrary light polarization. As a proof of principle,
we apply the method to compute the photoelectron spectrum arising from the
pump-probe two-photon ionization of helium induced by a sequence of extreme
ultraviolet and infrared-light pulses. We compare several two-photon ionization
pump-probe spectra, resonant with the (2s2p)1P1o Feshbach resonance, with
independent simulations based on the atomic B-spline close- coupling STOCK
code, and find good agreement between the two approaches. This new finite-pulse
perturbative approach is a step towards the ab initio study of weak-field
attosecond processes in poly-electronic molecules.
| physics.atom-ph |
1807.02184 | Slytherin: Dynamic, Network-assisted Prioritization of Tail Packets in
Datacenter Networks | Datacenter applications demand both low latency and high throughput; while
interactive applications (e.g., Web Search) demand low tail latency for their
short messages due to their partition-aggregate software architecture, many
data-intensive applications (e.g., Map-Reduce) require high throughput for long
flows as they move vast amounts of data across the network. Recent proposals
improve latency of short flows and throughput of long flows by addressing the
shortcomings of existing packet scheduling and congestion control algorithms,
respectively. We make the key observation that long tails in the Flow
Completion Times (FCT) of short flows result from packets that suffer
congestion at more than one switch along their paths in the network. Our
proposal, Slytherin, specifically targets packets that suffered from congestion
at multiple points and prioritizes them in the network. Slytherin leverages ECN
mechanism which is widely used in existing datacenters to identify such tail
packets and dynamically prioritizes them using existing priority queues. As
compared to existing state-of-the-art packet scheduling proposals, Slytherin
achieves 18.6% lower 99th percentile flow completion times for short flows
without any loss of throughput. Further, Slytherin drastically reduces 99th
percentile queue length in switches by a factor of about 2x on average.
| cs.NI |
1807.02185 | A new nonlocal nonlinear Schroedinger equation and its soliton solutions | A new integrable nonlocal nonlinear Schroedinger (NLS) equation with clear
physical motivations is proposed. This equation is obtained from a special
reduction of the Manakov system, and it describes Manakov solutions whose two
components are related by a parity symmetry. Since the Manakov system governs
wave propagation in a wide variety of physical systems, this new nonlocal
equation has clear physical meanings. Solitons and multi-solitons in this
nonlocal equation are also investigated in the framework of Riemann-Hilbert
formulations. Surprisingly, symmetry relations of discrete scattering data for
this equation are found to be very complicated, where constraints between
eigenvectors in the scattering data depend on the number and locations of the
underlying discrete eigenvalues in a very complex manner. As a consequence,
general $N$-solitons are difficult to obtain in the Riemann-Hilbert framework.
However, one- and two-solitons are derived, and their dynamics investigated. It
is found that two-solitons are generally not a nonlinear superposition of
one-solitons, and they exhibit interesting dynamics such as meandering and
sudden position shifts. As a generalization, other integrable and physically
meaningful nonlocal equations are also proposed, which include NLS equations of
reverse-time and reverse-space-time types as well as nonlocal Manakov equations
of reverse-space, reverse-time and reverse-space-time types.
| nlin.SI |
1807.02186 | Holographic Complexity and Volume | The previously proposed "Complexity=Volume" or CV-duality is probed and
developed in several directions. We show that the apparent lack of universality
for large and small black holes is removed if the volume is measured in units
of the maximal time from the horizon to the "final slice" (times Planck area).
This also works for spinning black holes. We make use of the conserved "volume
current", associated with a foliation of spacetime by maximal volume surfaces,
whose flux measures their volume. This flux picture suggests that there is a
transfer of the complexity from the UV to the IR in holographic CFTs, which is
reminiscent of thermalization behavior deduced using holography. It also
naturally gives a second law for the complexity when applied at a black hole
horizon. We further establish a result supporting the conjecture that a
boundary foliation determines a bulk maximal foliation without gaps, establish
a global inequality on maximal volumes that can be used to deduce the
monotonicity of the complexification rate on a boost-invariant background, and
probe CV duality in the settings of multiple quenches, spinning black holes,
and Rindler-AdS.
| hep-th gr-qc |
1807.02187 | Encoding Motion Primitives for Autonomous Vehicles using Virtual
Velocity Constraints and Neural Network Scheduling | Within the context of trajectory planning for autonomous vehicles this paper
proposes methods for efficient encoding of motion primitives in neural networks
on top of model-based and gradient-free reinforcement learning. It is
distinguished between 5 core aspects: system model, network architecture,
training algorithm, training tasks selection and hardware/software
implementation. For the system model, a kinematic (3-states-2-controls) and a
dynamic (16-states-2-controls) vehicle model are compared. For the network
architecture, 3 feedforward structures are compared including weighted skip
connections. For the training algorithm, virtual velocity constraints and
network scheduling are proposed. For the training tasks, different feature
vector selections are discussed. For the implementation, aspects of
gradient-free learning using 1 GPU and the handling of perturbation noise
therefore are discussed. The effects of proposed methods are illustrated in
experiments encoding up to 14625 motion primitives. The capabilities of tiny
neural networks with as few as 10 scalar parameters when scheduled on vehicle
velocity are emphasized.
| cs.RO cs.LG |
1807.02188 | Implicit Generative Modeling of Random Noise during Training for
Adversarial Robustness | We introduce a Noise-based prior Learning (NoL) approach for training neural
networks that are intrinsically robust to adversarial attacks. We find that the
implicit generative modeling of random noise with the same loss function used
during posterior maximization, improves a model's understanding of the data
manifold furthering adversarial robustness. We evaluate our approach's efficacy
and provide a simplistic visualization tool for understanding adversarial data,
using Principal Component Analysis. Our analysis reveals that adversarial
robustness, in general, manifests in models with higher variance along the
high-ranked principal components. We show that models learnt with our approach
perform remarkably well against a wide-range of attacks. Furthermore, combining
NoL with state-of-the-art adversarial training extends the robustness of a
model, even beyond what it is adversarially trained for, in both white-box and
black-box attack scenarios.
| cs.LG cs.CV stat.ML |
1807.02189 | Functional Object-Oriented Network: Construction & Expansion | We build upon the functional object-oriented network (FOON), a structured
knowledge representation which is constructed from observations of human
activities and manipulations. A FOON can be used for representing object-motion
affordances. Knowledge retrieval through graph search allows us to obtain novel
manipulation sequences using knowledge spanning across many video sources,
hence the novelty in our approach. However, we are limited to the sources
collected. To further improve the performance of knowledge retrieval as a
follow up to our previous work, we discuss generalizing knowledge to be applied
to objects which are similar to what we have in FOON without manually
annotating new sources of knowledge. We discuss two means of generalization: 1)
expanding our network through the use of object similarity to create new
functional units from those we already have, and 2) compressing the functional
units by object categories rather than specific objects. We discuss experiments
which compare the performance of our knowledge retrieval algorithm with both
expansion and compression by categories.
| cs.RO cs.AI |
1807.02190 | Strong Numerical Methods of Orders 2.0, 2.5, and 3.0 for Ito Stochastic
Differential Equations Based on the Unified Stochastic Taylor Expansions and
Multiple Fourier-Legendre Series | The article is devoted to the construction of explicit one-step numerical
methods with the strong orders of convergence 2.0, 2,5, and 3.0 for Ito
stochastic differential equations with multidimensional non-commutative noise.
We consider the numerical methods based on the unified Taylor-Ito and
Taylor-Stratonovich expansions. For numerical modeling of iterated Ito and
Stratonovich stochastic integrals of multiplicities 1 to 6 we appling the
method of multiple Fourier-Legendre series converging in the sense of norm in
Hilbert space $L_2([t, T]^k),$ $k=1,\ldots,6$. The article is addressed to
engineers who use numerical modeling in stochastic control and for solving the
non-linear filtering problem. The article can be interesting for the
mathematicians who working in the field of high-order strong numerical methods
for Ito stochastic differential equations.
| math.PR |
1807.02191 | An MCMC Approach to Empirical Bayes Inference and Bayesian Sensitivity
Analysis via Empirical Processes | Consider a Bayesian situation in which we observe $Y \sim p_{\theta}$, where
$\theta \in \Theta$, and we have a family $\{ \nu_h, \, h \in \mathcal{H} \}$
of potential prior distributions on $\Theta$. Let $g$ be a real-valued function
of $\theta$, and let $I_g(h)$ be the posterior expectation of $g(\theta)$ when
the prior is $\nu_h$. We are interested in two problems: (i) selecting a
particular value of $h$, and (ii) estimating the family of posterior
expectations $\{ I_g(h), \, h \in \mathcal{H} \}$. Let $m_y(h)$ be the marginal
likelihood of the hyperparameter $h$: $m_y(h) = \int p_{\theta}(y) \,
\nu_h(d\theta)$. The empirical Bayes estimate of $h$ is, by definition, the
value of $h$ that maximizes $m_y(h)$. It turns out that it is typically
possible to use Markov chain Monte Carlo to form point estimates for $m_y(h)$
and $I_g(h)$ for each individual $h$ in a continuum, and also confidence
intervals for $m_y(h)$ and $I_g(h)$ that are valid pointwise. However, we are
interested in forming estimates, with confidence statements, of the entire
families of integrals $\{ m_y(h), \, h \in \mathcal{H} \}$ and $\{ I_g(h), \, h
\in \mathcal{H} \}$: we need estimates of the first family in order to carry
out empirical Bayes inference, and we need estimates of the second family in
order to do Bayesian sensitivity analysis. We establish strong consistency and
functional central limit theorems for estimates of these families by using
tools from empirical process theory. We give two applications, one to Latent
Dirichlet Allocation, which is used in topic modelling, and the other is to a
model for Bayesian variable selection in linear regression.
| stat.ME |
1807.02192 | A Survey of Knowledge Representation in Service Robotics | Within the realm of service robotics, researchers have placed a great amount
of effort into learning, understanding, and representing motions as
manipulations for task execution by robots. The task of robot learning and
problem-solving is very broad, as it integrates a variety of tasks such as
object detection, activity recognition, task/motion planning, localization,
knowledge representation and retrieval, and the intertwining of
perception/vision and machine learning techniques. In this paper, we solely
focus on knowledge representations and notably how knowledge is typically
gathered, represented, and reproduced to solve problems as done by researchers
in the past decades. In accordance with the definition of knowledge
representations, we discuss the key distinction between such representations
and useful learning models that have extensively been introduced and studied in
recent years, such as machine learning, deep learning, probabilistic modelling,
and semantic graphical structures. Along with an overview of such tools, we
discuss the problems which have existed in robot learning and how they have
been built and used as solutions, technologies or developments (if any) which
have contributed to solving them. Finally, we discuss key principles that
should be considered when designing an effective knowledge representation.
| cs.RO cs.AI |
1807.02193 | Mesonic excited states of magnetic monopoles in quantum spin ice | Spin ice magnetic monopoles are fractionalized emergent excitations in a
class of frustrated magnets called spin ices. The classical spin ice model has
an extensive number of ground state spin configurations, whereas magnetic
monopoles can be thought of as the endpoints of string operators applied to
these ground states. Introducing quantum fluctuations into the model induces
monopoles with dynamics, which would normally lift the degeneracy of the
two-monopole energy level at the linear order of the perturbation. Contrary to
this expectation, we find that quantum fluctuations in the form of a locally
transverse field term partially preserve the extensive degeneracy of the
monopole pairs up to the much weaker splitting of the background monopole-free
spin ice configurations. Each of these approximately degenerate excited states,
termed mesons, can be represented as a bound monopole-antimonopole pair
delocalized in a classical spin ice background.
| cond-mat.str-el |
1807.02194 | An algorithm for enumerating difference sets | The DifSets package for GAP implements an algorithm for enumerating all
difference sets in a group up to equivalence and provides access to a library
of results. The algorithm functions by finding difference sums, which are
potential images of difference sets in quotient groups of the original group,
and searching their preimages. In this way, the search space can be
dramatically decreased, and searches of groups of relatively large order (such
as order 64 or order 96) can be completed.
| math.CO |
1807.02195 | Polynomials in Base $x$ and the Prime-Irreducible Affinity | Arthur Cohn's irreducibility criterion for polynomials with integer
coefficients and its generalization connect primes to irreducibles, and
integral bases to the variable $x$. As we follow this link, we find that these
polynomials are ready to spill two of their secrets: (i) There exists a unique
"base-$x$" representation of such polynomials that makes the ring
$\mathbb{Z}[x]$ into an ordered domain; and (ii) There is a 1-1 correspondence
between positive rational primes $p$ and certain infinite sets of irreducible
polynomials $f(x)$ that attain the value $p$ at sufficiently large $x$, each
generated in finitely many steps from the $p$th cyclotomic polynomial. The
base-$x$ representation provides practical conversion methods among numeric
bases (not to mention a polynomial factorization algorithm), while the
prime-irreducible correspondence puts a new angle on the Bouniakowsky
Conjecture, a generalization of Dirichlet's Theorem on Primes in Arithmetic
Progressions.
| math.NT |
1807.02196 | Pairing symmetry and spontaneous vortex-antivortex lattice in
superconducting twisted-bilayer graphene: Bogoliubov-de Gennes approach | We study the superconducting pairing symmetry in twisted bilayer graphene by
solving the Bogoliubov-de Gennes equation for all electrons in moir\'{e}
supercells. With increasing the pairing potential, the system evolves from the
mixed nontopological $d+id$ and $p+ip$ phase to the $s+p+d$ phase via the
first-order phase transition. In the time-reversal symmetry breaking $d+id$ and
$p+ip$ phase, vortex and antivortex lattices accompanying spontaneous
supercurrent are induced by the twist. The superconducting order parameter is
nonuniform in the moir\'{e} unit cell. Nevertheless, the superconducting gap in
the local density of states is identical in the unit cell. The twist-induced
vortices and nontopological nature of the mixed $d+id$ and $p+ip$ phase are not
captured by the existing effective models. Our results suggest the importance
of long-range pairing interaction for effective models.
| cond-mat.str-el cond-mat.supr-con |
1807.02197 | Assessment of the impact of two-dimensional wall deformations' shape on
high-speed boundary layer disturbances | Previous experimental and numerical studies showed that two-dimensional
roughness elements can stabilize disturbances inside a hypersonic boundary
layer, and eventually delay the transition onset. The objective of this paper
is to evaluate the response of disturbances propagating inside a high-speed
boundary layer to various two-dimensional surface deformations of different
shapes. We perform an assessment of the impact of various two-dimensional
surface non-uniformities, such as backward or forward steps, combinations of
backward and forward steps, wavy surfaces, surface dips, and surface humps.
Disturbances inside a Mach 5.92 flat-plate boundary layer are excited using
periodic wall blowing and suction at an upstream location. The numerical tools
consist of a high-accurate numerical algorithm solving for the unsteady,
compressible form of the Navier-Stokes equations in curvilinear coordinates.
Results show that all types of surface non-uniformities are able to reduce the
amplitude of boundary layer disturbances to a certain degree. The amount of
disturbance energy reduction is related to the type of pressure gradients that
are posed by the deformation (adverse or favorable). A possible cause (among
others) of the disturbance energy reduction inside the boundary layer is
presumed to be the result of a partial deviation of the kinetic energy to the
external flow, along the discontinuity that is generated by the wall
deformation.
| physics.flu-dyn |
1807.02198 | The Radius of Metric Subregularity | There is a basic paradigm, called here the radius of well-posedness, which
quantifies the "distance" from a given well-posed problem to the set of
ill-posed problems of the same kind. In variational analysis, well-posedness is
often understood as a regularity property, which is usually employed to measure
the effect of perturbations and approximations of a problem on its solutions.
In this paper we focus on evaluating the radius of the property of metric
subregularity which, in contrast to its siblings, metric regularity, strong
regularity and strong subregularity, exhibits a more complicated behavior under
various perturbations. We consider three kinds of perturbations: by Lipschitz
continuous functions, by semismooth functions, and by smooth functions,
obtaining different expressions/bounds for the radius of subregularity, which
involve generalized derivatives of set-valued mappings. We also obtain
different expressions when using either Frobenius or Euclidean norm to measure
the radius. As an application, we evaluate the radius of subregularity of a
general constraint system. Examples illustrate the theoretical findings.
| math.OC |
1807.02199 | Measurements of Degree-Scale B-mode Polarization with the BICEP/Keck
Experiments at South Pole | The BICEP and Keck Array experiments are a suite of small-aperture refracting
telescopes observing the microwave sky from the South Pole. They target the
degree-scale B-mode polarization signal imprinted in the Cosmic Microwave
Background (CMB) by primordial gravitational waves. Such a measurement would
shed light on the physics of the very early universe. While BICEP2 observed for
the first time a B-mode signal at 150 GHz, higher frequencies from the Planck
satellite showed that it could be entirely due to the polarized emission from
Galactic dust, though uncertainty remained high. Keck Array has been observing
the same region of the sky for several years, with an increased detector count,
producing the deepest polarized CMB maps to date. New detectors at 95 GHz were
installed in 2014, and at 220 GHz in 2015. These observations enable a better
constraint of galactic foreground emissions, as presented here. In 2015, BICEP2
was replaced by BICEP3, a 10 times higher throughput telescope observing at 95
GHz, while Keck Array is now focusing on higher frequencies. In the near
future, BICEP Array will replace Keck Array, and will allow unprecedented
sensitivity to the gravitational wave signal. High resolution observations from
the South Pole Telescope (SPT) will also be used to remove the lensing
contribution to B-modes.
| astro-ph.CO |
1807.02200 | Natural Language Processing for Music Knowledge Discovery | Today, a massive amount of musical knowledge is stored in written form, with
testimonies dated as far back as several centuries ago. In this work, we
present different Natural Language Processing (NLP) approaches to harness the
potential of these text collections for automatic music knowledge discovery,
covering different phases in a prototypical NLP pipeline, namely corpus
compilation, text-mining, information extraction, knowledge graph generation
and sentiment analysis. Each of these approaches is presented alongside
different use cases (i.e., flamenco, Renaissance and popular music) where large
collections of documents are processed, and conclusions stemming from
data-driven analyses are presented and discussed.
| cs.CL |
1807.02201 | Monte Carlo Methods for Insurance Risk Computation | In this paper we consider the problem of computing tail probabilities of the
distribution of a random sum of positive random variables. We assume that the
individual variables follow a reproducible natural exponential family (NEF)
distribution, and that the random number has a NEF counting distribution with a
cubic variance function. This specific modelling is supported by data of the
aggregated claim distribution of an insurance company. Large tail probabilities
are important as they reflect the risk of large losses, however, analytic or
numerical expressions are not available. We propose several simulation
algorithms which are based on an asymptotic analysis of the distribution of the
counting variable and on the reproducibility property of the claim
distribution. The aggregated sum is simulated efficiently by importancesampling
using an exponential cahnge of measure. We conclude by numerical experiments of
these algorithms.
| math.PR |
1807.02202 | The price of debiasing automatic metrics in natural language evaluation | For evaluating generation systems, automatic metrics such as BLEU cost
nothing to run but have been shown to correlate poorly with human judgment,
leading to systematic bias against certain model improvements. On the other
hand, averaging human judgments, the unbiased gold standard, is often too
expensive. In this paper, we use control variates to combine automatic metrics
with human evaluation to obtain an unbiased estimator with lower cost than
human evaluation alone. In practice, however, we obtain only a 7-13% cost
reduction on evaluating summarization and open-response question answering
systems. We then prove that our estimator is optimal: there is no unbiased
estimator with lower cost. Our theory further highlights the two fundamental
bottlenecks---the automatic metric and the prompt shown to human
evaluators---both of which need to be improved to obtain greater cost savings.
| cs.CL |
1807.02203 | Colloquium: Quantum skyrmionics | Skyrmions are topological solitons that emerge in many physical contexts. In
magnetism, they appear as textures of the spin-density field stabilized by
different competing interactions and characterized by a topological charge that
counts the number of times the order parameter wraps the sphere. They can
behave as classical objects, when the spin texture varies slowly on the scale
of the microscopic lattice of the magnet. However, the fast development of
experimental tools to create and stabilize skyrmions in thin magnetic films has
lead to a rich variety of textures, sometimes of atomistic sizes. In this
article, we discuss, in a pedagogical manner, how to introduce quantum
interference in the translational dynamics of skyrmion textures, starting from
the micromagnetic equations of motion for a classical soliton. We study how the
nontrivial topology of the spin texture manifests in the semiclassical regime,
when the microscopic lattice potential is treated quantum-mechanically, but the
external driving forces are taken as smooth classical perturbations. We
highlight close relations to the fields of noncommutative quantum mechanics,
Chern-Simons theories, and the quantum Hall effect.
| cond-mat.mes-hall |
1807.02204 | Neutrino masses, cosmological inflation and dark matter in a
$U(1)_{B-L}$ model with type II seesaw mechanism | In this work we implement the type II seesaw mechanism into the framework of
the $U(1)_{B-L}$ gauge model. As main gain, the right-handed neutrinos of the
model get free to play the role of the dark matter of the universe. As side
effect, the model realizes Higgs inflation without problem with loss of
unitarity.
| hep-ph |
1807.02205 | OSDF: An Intent-based Software Defined Network Programming Framework | Software Defined Networking (SDN) offers flexibility to program a network
based on a set of network requirements. Programming the networks using SDN is
not completely straightforward because a programmer must deal with low level
details. To solve the problem, researchers proposed a set of network
programming languages that provide a set of high level abstractions to hide low
level hardware details. Most of the proposed languages provide abstractions
related to packet processing and flows, and still require a programmer to
specify low-level match-action fields to configure and monitor a network.
Recently, in an attempt to raise the level at which programmers work,
researchers have begun to investigate Intent-based, descriptive northbound
interfaces. The work is still in early stages, and further investigation is
required before intent-based systems will be adopted by enterprise networks. To
help achieve the goal of moving to an intent-based design, we propose an
SDN-based network programming framework, the Open Software Defined Framework
(OSDF). OSDF provides a high level Application Programming Interface (API) that
can be used by managers and network administrators to express network
requirements for applications and policies for multiple domains. OSDF also
provides a set of high level network operation services that handle common
network configuration, monitoring, and Quality of Service (QoS) provisioning.
OSDF is equipped with a policy conflict management module to help a network
administrator detect and resolve policy conflicts. The paper shows how OSDF can
be used and explains application-based policies. Finally, the paper reports the
results of both testbed measurements and simulations that are used to evaluate
the framework from multiple perspectives, including functionality and
performance.
| cs.NI |
1807.02206 | On forcing projective generic absoluteness from strong cardinals | W.H. Woodin showed that if $\kappa_1 < \cdots < \kappa_n$ are strong
cardinals then two-step ${\bf\Sigma}^1_{n+3}$ generic absoluteness holds after
collapsing $2^{2^{\kappa_n}}$ to be countable. We show that this number can be
reduced to $2^{\kappa_n}$, and to $\kappa_n^+$ in the case $n = 1$, but cannot
be further reduced to $\kappa_n$.
| math.LO |
1807.02207 | Weakly remarkable cardinals, Erd\H{o}s cardinals, and the generic
Vop\v{e}nka principle | We consider a weak version of Schindler's remarkable cardinals that may fail
to be $\Sigma_2$-reflecting. We show that the $\Sigma_2$-reflecting weakly
remarkable cardinals are exactly the remarkable cardinals, and we show that the
existence of a non-$\Sigma_2$-reflecting weakly remarkable cardinal has higher
consistency strength: it is equiconsistent with the existence of an
$\omega$-Erd\H{o}s cardinal. We give an application involving gVP, the generic
Vop\v{e}nka principle defined by Bagaria, Gitman, and Schindler. Namely, we
show that gVP + "Ord is not $\Delta_2$-Mahlo" and $\text{gVP}({\bf\Pi}_1)$ +
"there is no proper class of remarkable cardinals" are both equiconsistent with
the existence of a proper class of $\omega$-Erd\H{o}s cardinals, extending
results of Bagaria, Gitman, Hamkins, and Schindler.
| math.LO |
1807.02208 | Generic Vop\v{e}nka cardinals and models of ZF with few
$\aleph_1$-Suslin sets | We define a generic Vop\v{e}nka cardinal to be an inaccessible cardinal
$\kappa$ such that for every first-order language $\mathcal{L}$ of cardinality
less than $\kappa$ and every set $\mathscr{B}$ of $\mathcal{L}$-structures, if
$|\mathscr{B}| = \kappa$ and every structure in $\mathscr{B}$ has cardinality
less than $\kappa$, then an elementary embedding between two structures in
$\mathscr{B}$ exists in some generic extension of $V$. We investigate
connections between generic Vop\v{e}nka cardinals in models of ZFC and the
number and complexity of $\aleph_1$-Suslin sets of reals in models of ZF. In
particular, we show that ZFC + (there is a generic Vop\v{e}nka cardinal) is
equiconsistent with ZF + $(2^{\aleph_1} \not\leq |S_{\aleph_1}|)$ where
$S_{\aleph_1}$ is the pointclass of all $\aleph_1$-Suslin sets of reals, and
also with ZF + $(S_{\aleph_1} = {\bf\Sigma}^1_2)$ + $(\Theta = \aleph_2)$ where
$\Theta$ is the least ordinal that is not a surjective image of the reals.
| math.LO |
1807.02209 | Strategic enhancement of anomalous Nernst effect in Co2MnAl1-xSix
Heusler compounds | The anomalous Nernst effect (ANE), a thermoelectric phenomenon in magnetic
materials, has potential for novel energy harvesting applications because its
orthogonal relationship between the temperature gradient and the electric field
enables us to utilize the large area of non-flat heat sources. In this study,
the required thermopower of ANE for practical energy harvesting applications is
evaluated in simulations of electric power obtainable from ANE using a
low-temperature heat source. A strategy for finding magnetic materials having
large ANEs is proposed, which suggests that a large ANE originates from the
constructive relationship between large Seebeck, anomalous Hall, and transverse
Peltier effects. This strategy leads us to investigate the electric and
thermoelectric properties in Co2MnAl1-xSix. As a result, it is found that
Co2MnAl0.63Si0.37 has the largest ANE thermopower ever reported, 6.2 uV/K. A
first principles calculation of the anomalous Hall conductivity and transverse
Peltier coefficient in B2 and L21-ordered Co2MnAl0.63Si0.37 shows close
agreement with the experimental results, indicating that the observed large ANE
arises from the intrinsic Berry phase curvature of Co2MnAl1-xSix. This study
can be a guide for developing materials for new thermoelectric applications
using ANE.
| cond-mat.mtrl-sci |
1807.02210 | Molecular Gas and Dark Neutral Medium in the Outskirts of Chamaeleon | %context More gas is inferred to be present in molecular cloud complexes than
can be accounted for by HI and CO emission, a phenomenon known as dark neutral
medium (DNM) or CO-dark gas for the molecules. %aims To see if molecular gas
can be detected in Chamaeleon when gas column densities in the DNM were
inferred and CO emission was not detected. % methods We took 3mm absorption
profiles of HCO+ and other molecules toward quasars across Chamaeleon, 1 of
which had detectable CO emission. We derived N(H2) assuming N(HC+)/N(H2) =
3x10^{-9}. %results With the possible exception of 1 weak continuum target HCO+
absorption was detected in all directions, \cch\ in 8 and HCN in 4 directions.
The sightlines divide in 2 groups according to their DNM content with 1 group
of 8 directions having N(DNM) \ga 2x10^{20} \pcc and another group of 5
directions having N(DNM) < .5x10^{20}\pcc. The groups have comparable <N(HI)>
in Chamaeleon 6-7 x 10^{20}\pcc and <N(H)/E(B-V) ~ 6-7x10^{21}\pcc/mag. They
differ in having quite different <E(B-V)> 0.33 vs 0.18 mag, <N(DNM)> 3.3 vs .14
x 10^{20}\pcc and <2N(H2)> = 5.6 vs 0.8 x 10^{20} \pcc. Gas at more positive
velocities is enriched in molecules and DNM. %conclusion Overall the quantity
of H2 inferred from HCO+ fully accounts for the previously-inferred DNM along
the studied sightlines. H2 is concentrated in the high-DNM group, where the
molecular fraction is 46% vs. 13% otherwise and 38% overall. Thus, neutral gas
in the outskirts of the complex is mostly atomic but the DNM is mostly
molecular. Saturation of the HI emission may occur along 3 of the 4 sightlines
having the largest DNM column densities but there is no substantial reservoir
of 'dark' atomic or molecular gas that remains undetected as part of the
inventory of dark neutral medium.
| astro-ph.GA |
1807.02211 | Scalar resonance in a top partner model | The phenomenology entailed by a scalar resonance in a top partner model is
analysed here in a $SO(5)$ Composite Higgs formalism. Heavy scalar resonances
production and their decays modes are explored along a benchmark resonance mass
range. The production of single-double partner final states has been scanned
along the partner mass scale. QCD drives such production, as well as the SM
gauge, Higgs, plus the intermediation of the scalar resonance. Non-zero
contributions are induced as long as extra fermion-resonance effects are
included. Finally, we have excluded regions of the parameter spaces underlying
our framework by imposing the recent LHC searches for vector-like quarks
production in $pp$-collisions at 13 TeV. Substantial reduction of the allowed
regions occurs if extra fermion-resonance effects are accounted for, leading us
to test the involved parametric dependence in the shed light of new matter
interactions.
| hep-ph |
1807.02212 | On the exact variance of Tsallis entropy in a random pure state | Tsallis entropy is a useful one-parameter generalization of the standard von
Neumann entropy in information theory. We study the variance of Tsallis entropy
of bipartite quantum systems in a random pure state. The main result is an
exact variance formula of Tsallis entropy that involves finite sums of some
terminating hypergeometric functions. In the special cases of quadratic entropy
and small subsystem dimensions, the main result is further simplified to
explicit variance expressions. As a byproduct, we find an independent proof of
the recently proved variance formula of von Neumann entropy based on the
derived moment relation to the Tsallis entropy.
| math-ph math.MP |
1807.02213 | The consistency strength of the perfect set property for universally
Baire sets of reals | We show that the statement "every universally Baire set of reals has the
perfect set property" is equiconsistent modulo ZFC with the existence of a
cardinal that we call a virtually Shelah cardinal. These cardinals resemble
Shelah cardinals but are much weaker: if $0^\sharp$ exists then every Silver
indiscernible is virtually Shelah in $L$. We also show that the statement
$\text{uB} = {\bf\Delta}^1_2$, where $\text{uB}$ is the pointclass of all
universally Baire sets of reals, is equiconsistent modulo ZFC with the
existence of a $\Sigma_2$-reflecting virtually Shelah cardinal.
| math.LO |
1807.02214 | Low-Frequency Raman Spectroscopy of Few-Layer 2H-SnS2 | We investigated interlayer phonon modes of mechanically exfoliated few-layer
2H-SnS2 samples by using room temperature low-frequency micro-Raman
spectroscopy. Raman measurements were performed using laser wavelength of
441.6, 514.4, 532 and 632.8 nm with power below 100 uW and inside a vacuum
chamber to avoid photo-oxidation. The intralayer Eg and A1g modes are observed
at ~206 cm-1 and ~314 cm-1, respectively, but the Eg mode is much weaker for
all excitation energies. The A1g mode exhibits strong resonant enhancement for
the 532 nm (2.33 eV) laser. In the low-frequency region, interlayer vibrational
modes of shear and breathing modes are observed. These modes show
characteristic dependence on the number of layers. The strengths of the
interlayer interactions are estimated by fitting the interlayer mode
frequencies using the linear chain model and are found to be 1.64 x10^19 N.m-3
and 5.03 x10^19 N.m-3 for the shear and breathing modes, respectively.
| cond-mat.mtrl-sci |
1807.02215 | Empirical distributions of the robustified $t$-test statistics | Based on the median and the median absolute deviation estimators, and the
Hodges-Lehmann and Shamos estimators, robustified analogues of the conventional
$t$-test statistic are proposed. The asymptotic distributions of these
statistics are recently provided. However, when the sample size is small, it is
not appropriate to use the asymptotic distribution of the robustified $t$-test
statistics for making a statistical inference including hypothesis testing,
confidence interval, p-value, etc.
In this article, through extensive Monte Carlo simulations, we obtain the
empirical distributions of the robustified $t$-test statistics and their
quantile values. Then these quantile values can be used for making a
statistical inference.
| stat.AP |
1807.02216 | On some novel features of the Kerr-Newman-NUT Spacetime | In this work we have presented a special class of Kerr-Newman-NUT black hole,
having its horizon located precisely at $r=2M$, for $Q^{2}=l^{2}-a^{2}$, where
$M$, $l$, $a$ and $Q$ are respectively mass, NUT, rotation and electric charge
parameters of the black hole. Clearly this choice radically alters the causal
structure as there exists no Cauchy horizon indicating spacelike nature of the
singularity when it exists. On the other hand, there is no curvature
singularity for $l^2 > a^2$, however it may have conical singularities.
Furthermore there is no upper bound on specific rotation parameter $a/M$, which
could exceed unity without risking destruction of the horizon. To bring out
various discerning features of this special member of the Kerr-Newman-NUT
family, we study timelike and null geodesics in the equatorial as well as off
the equatorial plane, energy extraction through super-radiance and Penrose
process, thermodynamical properties and also the quasi-periodic oscillations.
It turns out that the black hole under study radiates less energy through the
super-radiant modes and Penrose process than the other black holes in this
family.
| gr-qc hep-th |
1807.02217 | TTV-determined Masses for Warm Jupiters and their Close Planetary
Companions | Although the formation and the properties of hot Jupiters (with orbital
periods $P<10\,$d) have attracted a great deal of attention, the origins of
warm Jupiters ($10<P<100\,$d) are less well-studied. Using a transit timing
analysis, we present the orbital parameters of five planetary systems
containing warm Jupiters, Kepler 30, Kepler 117, Kepler 302, Kepler 487 and
Kepler 418. Three of them, Kepler-30 c($M_p=549.4{\pm{5.6}}M_{\oplus}$),
Kepler-117 c($M_p=702{\pm{63}}M_{\oplus}$) and Kepler 302 c($M_p=933\pm
527M_{\oplus}$), are confirmed to be real warm Jupiters based on their mass.
Insights drawn from the radius-temperature relationship lead to the inference
that hot Jupiters and warm Jupiters can be roughly separated by ${T_{\rm
eff,c}} =1123.7\pm3.3$ K. Also, ${T_{\rm eff,c}}$ provides a good separation
for Jupiters with companion fraction consistent with zero($T_{\rm eff}>T_{\rm
eff,c}$) and those with companion fraction significantly different from zero
($T_{\rm eff}<T_{\rm eff,c}$).
| astro-ph.EP |
1807.02218 | Sampling basis in reproducing kernel Banach spaces | We present necessary and sufficient conditions to hold true a Kramer type
sampling theorem over semi-inner product reproducing kernel Banach spaces.
Under some sampling-type hypotheses over a sequence of functions on these
Banach spaces it results necessary that such sequence must be a $X_d$-Riesz
basis and a sampling basis for the space. These results are a generalization of
some already known sampling theorems over reproducing kernel Hilbert spaces.
| math.FA |
1807.02219 | Analysis of Probabilistic and Parametric Reduced Order Models | Stochastic models share many characteristics with generic parametric models.
In some ways they can be regarded as a special case. But for stochastic models
there is a notion of weak distribution or generalised random variable, and the
same arguments can be used to analyse parametric models. Such models in vector
spaces are connected to a linear map, and in infinite dimensional spaces are a
true gener- alisation. Reproducing kernel Hilbert space and affine- / linear-
representations in terms of tensor products are directly related to this linear
operator. This linear map leads to a generalised correlation operator, and
representations are connected with factorisations of the correlation operator.
The fitting counterpart in the stochastic domain to make this point of view as
simple as possible are algebras of random variables with a distinguished linear
functional, the state, which is interpreted as expectation. The connections of
factorisations of the generalised correlation to the spectral decomposition, as
well as the associated Karhunen-Lo\`eve- or proper orthogonal decomposition
will be sketched. The purpose of this short note is to show the common
theoretical background and pull some lose ends together.
| math.NA |
1807.02220 | Arithmetic actions on cyclotomic function fields | We derive the group structure for cyclotomic function fields obtained by
applying the Carlitz action for extensions of an initial constant field. The
tame and wild structures are isolated to describe the Galois action on
differentials. We show that the associated invariant rings are not polynomial.
| math.NT |
1807.02221 | The Data Science of Hollywood: Using Emotional Arcs of Movies to Drive
Business Model Innovation in Entertainment Industries | Much of business literature addresses the issues of consumer-centric design:
how can businesses design customized services and products which accurately
reflect consumer preferences? This paper uses data science natural language
processing methodology to explore whether and to what extent emotions shape
consumer preferences for media and entertainment content. Using a unique
filtered dataset of 6,174 movie scripts, we generate a mapping of screen
content to capture the emotional trajectory of each motion picture. We then
combine the obtained mappings into clusters which represent groupings of
consumer emotional journeys. These clusters are used to predict overall success
parameters of the movies including box office revenues, viewer satisfaction
levels (captured by IMDb ratings), awards, as well as the number of viewers'
and critics' reviews. We find that like books all movie stories are dominated
by 6 basic shapes. The highest box offices are associated with the Man in a
Hole shape which is characterized by an emotional fall followed by an emotional
rise. This shape results in financially successful movies irrespective of genre
and production budget. Yet, Man in a Hole succeeds not because it produces most
"liked" movies but because it generates most "talked about" movies.
Interestingly, a carefully chosen combination of production budget and genre
may produce a financially successful movie with any emotional shape.
Implications of this analysis for generating on-demand content and for driving
business model innovation in entertainment industries are discussed.
| cs.CL cs.CY |
1807.02222 | Digital Geometry, a Survey | This paper provides an overview of modern digital geometry and topology
through mathematical principles, algorithms, and measurements. It also covers
recent developments in the applications of digital geometry and topology
including image processing, computer vision, and data science. Recent research
strongly showed that digital geometry has made considerable contributions to
modelings and algorithms in image segmentation, algorithmic analysis, and
BigData analytics.
| cs.DM cs.GR |
1807.02223 | Existence theory for non-separable mean field games in Sobolev spaces | The mean field games system is a coupled pair of nonlinear partial
differential equations arising in differential game theory, as a limit as the
number of agents tends to infinity. We prove existence and uniqueness of
classical solutions for time-dependent mean field games with Sobolev data. Many
works in the literature assume additive separability of the Hamiltonian, as
well as further structure such as convexity and monotonicity of the resulting
components. Problems arising in practice, however, may not have this separable
structure; we therefore consider the non-separable problem. For our existence
and uniqueness results, we introduce new smallness constraints which
simultaneously consider the size of the time horizon, the size of the data, and
the strength of the coupling in the system.
| math.AP |
1807.02224 | Cooperative Adaptive Cruise Control for a Platoon of Connected and
Autonomous Vehicles Considering Dynamic Information Flow Topology | Vehicle-to-vehicle communications can be unreliable as interference causes
communication failures. Thereby, the information flow topology for a platoon of
Connected Autonomous Vehicles (CAVs) can vary dynamically. This limits existing
Cooperative Adaptive Cruise Control (CACC) strategies as most of them assume a
fixed information flow topology (IFT). To address this problem, we introduce a
CACC design that considers a dynamic information flow topology (CACC-DIFT) for
CAV platoons. An adaptive Proportional-Derivative (PD) controller under a
two-predecessor-following IFT is proposed to reduce the negative effects when
communication failures occur. The PD controller parameters are determined to
ensure the string stability of the platoon. Further, the designed controller
also factors the performance of individual vehicles. Hence, when communication
failure occurs, the system will switch to a certain type of CACC instead of
degenerating to adaptive cruise control, which improves the control performance
considerably. The effectiveness of the proposed CACC-DIFT is validated through
numerical experiments based on NGSIM field data. Results indicate that the
proposed CACC-DIFT design outperforms a CACC with a predetermined information
flow topology.
| cs.SY |