title
stringlengths 7
239
| abstract
stringlengths 7
2.76k
| cs
int64 0
1
| phy
int64 0
1
| math
int64 0
1
| stat
int64 0
1
| quantitative biology
int64 0
1
| quantitative finance
int64 0
1
|
|---|---|---|---|---|---|---|---|
A Conic Integer Programming Approach to Constrained Assortment Optimization under the Mixed Multinomial Logit Model | We consider the constrained assortment optimization problem under the mixed
multinomial logit model. Even moderately sized instances of this problem are
challenging to solve directly using standard mixed-integer linear optimization
formulations. This has motivated recent research exploring customized
optimization strategies and approximation techniques. In contrast, we develop a
novel conic quadratic mixed-integer formulation. This new formulation, together
with McCormick inequalities exploiting the capacity constraints, enables the
solution of large instances using commercial optimization software.
| 0 | 0 | 1 | 0 | 0 | 0 |
Voyager 1 Measurements Beyond the Heliopause of Galactic Cosmic Ray Helium, Boron, Carbon, Oxygen, Magnesium, Silicon and Iron Nuclei with Energies 0.5 to >1.5 GeV/nuc | We have obtained the energy spectra of cosmic ray He, B, C, O, Mg, S and Fe
nuclei in the range 0.5-1.5 GeV/nuc and above using the penetrating particle
mode of the High Energy Telescope, part of the Cosmic Ray Science (CRS)
experiment on Voyagers 1 and 2. The data analysis procedures are the same as
those used to obtain similar spectra from the identical V2 HET telescope while
it was in the heliosphere between about 23 and 54 AU. The time period of
analysis includes 4 years of data beyond the heliopause (HP). These new
interstellar spectra are compared with various earlier experiments at the same
energies at the Earth to determine the solar modulation parameter, phi. These
new spectra are also compared with recent measurements of the spectra of the
same nuclei measured by the same telescope at low energies. It is found that
the ratio of intensities at 100 MeV/nuc to those at 1.0 GeV/nuc are
significantly Z dependent. Some of this Z dependence can be explained by the Z2
dependence of energy loss by ionization in the 7-10 g/cm2 of interstellar H and
He traversed by cosmic rays of these energies in the galaxy; some by the Z
dependent loss due to nuclear interactions in this same material; some by
possible differences in the source spectra of these nuclei and some by the
non-uniformity of the source distribution and propagation conditions. The
observed features of the spectra, also including a Z dependence of the peak
intensities of the various nuclei, pose interesting problems related to the
propagation and source distribution of these cosmic rays.
| 0 | 1 | 0 | 0 | 0 | 0 |
Block Mean Approximation for Efficient Second Order Optimization | Advanced optimization algorithms such as Newton method and AdaGrad benefit
from second order derivative or second order statistics to achieve better
descent directions and faster convergence rates. At their heart, such
algorithms need to compute the inverse or inverse square root of a matrix whose
size is quadratic of the dimensionality of the search space. For high
dimensional search spaces, the matrix inversion or inversion of square root
becomes overwhelming which in turn demands for approximate methods. In this
work, we propose a new matrix approximation method which divides a matrix into
blocks and represents each block by one or two numbers. The method allows
efficient computation of matrix inverse and inverse square root. We apply our
method to AdaGrad in training deep neural networks. Experiments show
encouraging results compared to the diagonal approximation.
| 0 | 0 | 0 | 1 | 0 | 0 |
A Minimum Discounted Reward Hamilton-Jacobi Formulation for Computing Reachable Sets | We propose a novel formulation for approximating reachable sets through a
minimum discounted reward optimal control problem. The formulation yields a
continuous solution that can be obtained by solving a Hamilton-Jacobi equation.
Furthermore, the numerical approximation to this solution can be obtained as
the unique fixed-point to a contraction mapping. This allows for more efficient
solution methods that could not be applied under traditional formulations for
solving reachable sets. In addition, this formulation provides a link between
reinforcement learning and learning reachable sets for systems with unknown
dynamics, allowing algorithms from the former to be applied to the latter. We
use two benchmark examples, double integrator, and pursuit-evasion games, to
show the correctness of the formulation as well as its strengths in comparison
to previous work.
| 1 | 0 | 0 | 0 | 0 | 0 |
Imbedding results in Musielak-Orlicz spaces with an application to anisotropic nonlinear Neumann problems | We prove a continuous embedding that allows us to obtain a boundary trace
imbedding result for anisotropic Musielak-Orlicz spaces, which we then apply to
obtain an existence result for Neumann problems with nonlinearities on the
boundary associated to some anisotropic nonlinear elliptic equations in
Musielak-Orlicz spaces constructed from Musielak-Orlicz functions on which and
on their conjugates we do not assume the $\Delta_2$-condition. The uniqueness
is also studied.
| 0 | 0 | 1 | 0 | 0 | 0 |
Defend against advanced persistent threats: An optimal control approach | The new cyber attack pattern of advanced persistent threat (APT) has posed a
serious threat to modern society. This paper addresses the APT defense problem,
i.e., the problem of how to effectively defend against an APT campaign. Based
on a novel APT attack-defense model, the effectiveness of an APT defense
strategy is quantified. Thereby, the APT defense problem is modeled as an
optimal control problem, in which an optimal control stands for a most
effective APT defense strategy. The existence of an optimal control is proved,
and an optimality system is derived. Consequently, an optimal control can be
figured out by solving the optimality system. Some examples of the optimal
control are given. Finally, the influence of some factors on the effectiveness
of an optimal control is examined through computer experiments. These findings
help organizations to work out policies of defending against APTs.
| 1 | 0 | 0 | 0 | 0 | 0 |
Challenges in Designing Datasets and Validation for Autonomous Driving | Autonomous driving is getting a lot of attention in the last decade and will
be the hot topic at least until the first successful certification of a car
with Level 5 autonomy. There are many public datasets in the academic
community. However, they are far away from what a robust industrial production
system needs. There is a large gap between academic and industrial setting and
a substantial way from a research prototype, built on public datasets, to a
deployable solution which is a challenging task. In this paper, we focus on bad
practices that often happen in the autonomous driving from an industrial
deployment perspective. Data design deserves at least the same amount of
attention as the model design. There is very little attention paid to these
issues in the scientific community, and we hope this paper encourages better
formalization of dataset design. More specifically, we focus on the datasets
design and validation scheme for autonomous driving, where we would like to
highlight the common problems, wrong assumptions, and steps towards avoiding
them, as well as some open problems.
| 1 | 0 | 0 | 1 | 0 | 0 |
Improving Adversarial Robustness via Promoting Ensemble Diversity | Though deep neural networks have achieved significant progress on various
tasks, often enhanced by model ensemble, existing high-performance models can
be vulnerable to adversarial attacks. Many efforts have been devoted to
enhancing the robustness of individual networks and then constructing a
straightforward ensemble, e.g., by directly averaging the outputs, which
ignores the interaction among networks. This paper presents a new method that
explores the interaction among individual networks to improve robustness for
ensemble models. Technically, we define a new notion of ensemble diversity in
the adversarial setting as the diversity among non-maximal predictions of
individual members, and present an adaptive diversity promoting (ADP)
regularizer to encourage the diversity, which leads to globally better
robustness for the ensemble by making adversarial examples difficult to
transfer among individual members. Our method is computationally efficient and
compatible with the defense methods acting on individual networks. Empirical
results on various datasets verify that our method can improve adversarial
robustness while maintaining state-of-the-art accuracy on normal examples.
| 1 | 0 | 0 | 1 | 0 | 0 |
Majorana stripe order on the surface of a three-dimensional topological insulator | The issue on the effect of interactions in topological states concerns not
only interacting topological phases but also novel symmetry-breaking phases and
phase transitions. Here we study the interaction effect on Majorana zero modes
(MZMs) bound to a square vortex lattice in two-dimensional (2D) topological
superconductors. Under the neutrality condition, where single-body
hybridization between MZMs is prohibited by an emergent symmetry, a minimal
square-lattice model for MZMs can be faithfully mapped to a quantum spin model,
which has no sign problem in the world-line quantum Monte Carlo simulation.
Guided by an insight from a further duality mapping, we demonstrate that the
interaction induces a Majorana stripe state, a gapped state spontaneously
breaking lattice translational and rotational symmetries, as opposed to the
previously conjectured topological quantum criticality. Away from neutrality, a
mean-field theory suggests a quantum critical point induced by hybridization.
| 0 | 1 | 0 | 0 | 0 | 0 |
Academic Engagement and Commercialization in an Institutional Transition Environment: Evidence from Shanghai Maritime University | Does academic engagement accelerate or crowd out the commercialization of
university knowledge? Research on this topic seldom considers the impact of the
institutional environment, especially when a formal institution for encouraging
the commercial activities of scholars has not yet been established. This study
investigates this question in the context of China, which is in the
institutional transition stage. Based on a survey of scholars from Shanghai
Maritime University, we demonstrate that academic engagement has a positive
impact on commercialization and that this impact is greater for risk-averse
scholars than for other risk-seeking scholars. Our results suggest that in an
institutional transition environment, the government should consider
encouraging academic engagement to stimulate the commercialization activities
of conservative scholars.
| 0 | 0 | 0 | 0 | 0 | 1 |
Affine-Gradient Based Local Binary Pattern Descriptor for Texture Classiffication | We present a novel Affine-Gradient based Local Binary Pattern (AGLBP)
descriptor for texture classification. It is very hard to describe complicated
texture using single type information, such as Local Binary Pattern (LBP),
which just utilizes the sign information of the difference between the pixel
and its local neighbors. Our descriptor has three characteristics: 1) In order
to make full use of the information contained in the texture, the
Affine-Gradient, which is different from Euclidean-Gradient and invariant to
affine transformation is incorporated into AGLBP. 2) An improved method is
proposed for rotation invariance, which depends on the reference direction
calculating respect to local neighbors. 3) Feature selection method,
considering both the statistical frequency and the intraclass variance of the
training dataset, is also applied to reduce the dimensionality of descriptors.
Experiments on three standard texture datasets, Outex12, Outex10 and KTH-TIPS2,
are conducted to evaluate the performance of AGLBP. The results show that our
proposed descriptor gets better performance comparing to some state-of-the-art
rotation texture descriptors in texture classification.
| 1 | 0 | 0 | 0 | 0 | 0 |
Decomposition theorems for asymptotic property C and property A | We combine aspects of the notions of finite decomposition complexity and
asymptotic property C into a notion that we call finite APC-decomposition
complexity. Any space with finite decomposition complexity has finite
APC-decomposition complexity and any space with asymptotic property C has
finite APC-decomposition complexity. Moreover, finite APC-decomposition
complexity implies property A for metric spaces. We also show that finite
APC-decomposition complexity is preserved by direct products of groups and
spaces, amalgamated products of groups, and group extensions, among other
constructions.
| 0 | 0 | 1 | 0 | 0 | 0 |
Three dimensional free-surface flow over arbitrary bottom topography | We consider steady nonlinear free surface flow past an arbitrary bottom
topography in three dimensions, concentrating on the shape of the wave pattern
that forms on the surface of the fluid. Assuming ideal fluid flow, the problem
is formulated using a boundary integral method and discretised to produce a
nonlinear system of algebraic equations. The Jacobian of this system is dense
due to integrals being evaluated over the entire free surface. To overcome the
computational difficulty and large memory requirements, a Jacobian-free Newton
Krylov (JFNK) method is utilised. Using a block-banded approximation of the
Jacobian from the linearised system as a preconditioner for the JFNK scheme, we
find significant reductions in computational time and memory required for
generating numerical solutions. These improvements also allow for a larger
number of mesh points over the free surface and the bottom topography. We
present a range of numerical solutions for both subcritical and supercritical
regimes, and for a variety of bottom configurations. We discuss nonlinear
features of the wave patterns as well as their relationship to ship wakes.
| 0 | 1 | 0 | 0 | 0 | 0 |
Spin-polaron formation and magnetic state diagram in La doped $CaMnO_3$ | $La_xCa_{1-x}MnO_3$ (LCMO) has been studied in the framework of density
functional theory (DFT) using Hubbard-U correction. We show that the formation
of spin-polarons of different configurations is possible in the G-type
antiferromagentic phase. We also show that the spin-polaron (SP) solutions are
stabilized due to an interplay of magnetic and lattice effects at lower La
concentrations and mostly due to the lattice contribution at larger
concentrations. Our results indicate that the development of SPs is unfavorable
in the C- and A-type antiferromagnetic phases. The theoretically obtained
magnetic state diagram is in good agreement with previously reported
experimental results
| 0 | 1 | 0 | 0 | 0 | 0 |
Power-law citation distributions are not scale-free | We analyze time evolution of statistical distributions of citations to
scientific papers published in one year. While these distributions can be
fitted by a power-law dependence we find that they are nonstationary and the
exponent of the power law fit decreases with time and does not come to
saturation. We attribute the nonstationarity of citation distributions to
different longevity of the low-cited and highly-cited papers. By measuring
citation trajectories of papers we found that citation careers of the low-cited
papers come to saturation after 10-15 years while those of the highly-cited
papers continue to increase indefinitely: the papers that exceed some citation
threshold become runaways. Thus, we show that although citation distribution
can look as a power-law, it is not scale-free and there is a hidden dynamic
scale associated with the onset of runaways. We compare our measurements to our
recently developed model of citation dynamics based on
copying/redirection/triadic closure and find explanations to our empirical
observations.
| 1 | 0 | 0 | 0 | 0 | 0 |
Atmospheric stellar parameters for large surveys using FASMA, a new spectral synthesis package | In the era of vast spectroscopic surveys focusing on Galactic stellar
populations, astronomers want to exploit the large quantity and good quality of
data to derive their atmospheric parameters without losing precision from
automatic procedures. In this work, we developed a new spectral package, FASMA,
to estimate the stellar atmospheric parameters (namely effective temperature,
surface gravity, and metallicity) in a fast and robust way. This method is
suitable for spectra of FGK-type stars in medium and high resolution. The
spectroscopic analysis is based on the spectral synthesis technique using the
radiative transfer code, MOOG. The line list is comprised of mainly iron lines
in the optical spectrum. The atomic data are calibrated after the Sun and
Arcturus. We use two comparison samples to test our method, i) a sample of 451
FGK-type dwarfs from the high resolution HARPS spectrograph, and ii) the
Gaia-ESO benchmark stars using both high and medium resolution spectra. We
explore biases in our method from the analysis of synthetic spectra covering
the parameter space of our interest. We show that our spectral package is able
to provide reliable results for a wide range of stellar parameters, different
rotational velocities, different instrumental resolutions, and for different
spectral regions of the VLT-GIRAFFE spectrographs, used among others for the
Gaia-ESO survey. FASMA estimates stellar parameters in less than 15 min for
high resolution and 3 min for medium resolution spectra. The complete package
is publicly available to the community.
| 0 | 1 | 0 | 0 | 0 | 0 |
Bingham flow in porous media with obstacles of different size | By using the unfolding operators for periodic homogenization, we give a
general compactness result for a class of functions defined on bounded domains
presenting perforations of two different size. Then we apply this result to the
homogenization of the flow of a Bingham fluid in a porous medium with solid
obstacles of different size. Next we give the interpretation of the limit
problem in term of a non linear Darcy law.
| 0 | 0 | 1 | 0 | 0 | 0 |
Eigenstate entanglement in the Sachdev-Ye-Kitaev model | In the Sachdev-Ye-Kitaev model, we argue that the entanglement entropy of any
eigenstate (including the ground state) obeys a volume law, whose coefficient
can be calculated analytically from the energy and subsystem size. We expect
that the argument applies to a broader class of chaotic models with all-to-all
interactions.
| 0 | 1 | 0 | 0 | 0 | 0 |
Finite presheaves and $A$-finite generation of unstable algebras mod nilpotents | Inspired by the work of Henn, Lannes and Schwartz on unstable algebras over
the Steenrod algebra modulo nilpotents, a characterization of unstable algebras
that are $A$-finitely generated up to nilpotents is given in terms of the
associated presheaf, by introducing the notion of a finite presheaf. In
particular, this gives the natural characterization of the (co)analytic
presheaves that are important in the theory of Henn, Lannes and Schwartz.
However, finite presheaves remain imperfectly understood, as illustrated by
examples. One important class of examples is shown to be provided by unstable
algebras of finite transcendence degree (under a necessary weak finiteness
condition).
For unstable Hopf algebras, it is shown that the situation is much better:
the associated presheaf is finite if and only if its growth function is
polynomial. This leads to a description of unstable Hopf algebras modulo
nilpotents in the spirit of Henn, Lannes and Schwartz.
| 0 | 0 | 1 | 0 | 0 | 0 |
Ejection of rocky and icy material from binary star systems: Implications for the origin and composition of 1I/`Oumuamua | In single star systems like our own Solar system, comets dominate the mass
budget of bodies that are ejected into interstellar space, since they form
further away and are less tightly bound. However 1I/`Oumuamua, the first
interstellar object detected, appears asteroidal in its spectra and in its lack
of detectable activity. We argue that the galactic budget of interstellar
objects like 1I/`Oumuamua should be dominated by planetesimal material ejected
during planet formation in circumbinary systems, rather than in single star
systems or widely separated binaries. We further show that in circumbinary
systems, rocky bodies should be ejected in comparable numbers to icy ones. This
suggests that a substantial fraction of additional interstellar objects
discovered in the future should display an active coma. We find that the rocky
population, of which 1I/`Oumuamua seems to be a member, should be predominantly
sourced from A-type and late B-star binaries.
| 0 | 1 | 0 | 0 | 0 | 0 |
Two-photon excitation of rubidium atoms inside porous glass | We study the two-photon laser excitation to the 5D$_{5/2}$ energy level of
$^{85}$Rb atoms contained in the interstices of a porous material made from
sintered ground glass with typical pore dimensions in the 10 - 100 $\mu$m
range. The excitation spectra show unusual flat-top lineshapes which are shown
to be the consequence of wave-vector randomization of the laser light in the
porous material. For large atomic densities, the spectra are affected by
radiation trapping around the D2 transitions. The effect of the transient
atomic response limited by time of flight between pores walls appears to have a
minor influence in the excitation spectra. It is however revealed by the
shortening of the temporal evolution of the emitted blue light following a
sudden switch-off of the laser excitation.
| 0 | 1 | 0 | 0 | 0 | 0 |
Readout of the atomtronic quantum interference device | A Bose-Einstein condensate confined in ring shaped lattices interrupted by a
weak link and pierced by an effective magnetic flux defines the atomic
counterpart of the superconducting quantum interference device: the atomtronic
quantum interference device (AQUID). In this paper, we report on the detection
of current states in the system through a self-heterodyne protocol. Following
the original proposal of the NIST and Paris groups, the ring-condensate
many-body wave function interferes with a reference condensate expanding from
the center of the ring. We focus on the rf-AQUID which realizes effective qubit
dynamics. Both the Bose-Hubbard and Gross-Pitaevskii dynamics are studied. For
the Bose-Hubbard dynamics, we demonstrate that the self-heterodyne protocol can
be applied, but higher-order correlations in the evolution of the interfering
condensates are measured to readout of the current states of the system. We
study how states with macroscopic quantum coherence can be told apart analyzing
the noise in the time of flight of the ring condensate.
| 0 | 1 | 0 | 0 | 0 | 0 |
Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy | Deep learning networks have achieved state-of-the-art accuracies on computer
vision workloads like image classification and object detection. The performant
systems, however, typically involve big models with numerous parameters. Once
trained, a challenging aspect for such top performing models is deployment on
resource constrained inference systems - the models (often deep networks or
wide networks or both) are compute and memory intensive. Low-precision numerics
and model compression using knowledge distillation are popular techniques to
lower both the compute requirements and memory footprint of these deployed
models. In this paper, we study the combination of these two techniques and
show that the performance of low-precision networks can be significantly
improved by using knowledge distillation techniques. Our approach, Apprentice,
achieves state-of-the-art accuracies using ternary precision and 4-bit
precision for variants of ResNet architecture on ImageNet dataset. We present
three schemes using which one can apply knowledge distillation techniques to
various stages of the train-and-deploy pipeline.
| 1 | 0 | 0 | 0 | 0 | 0 |
An IDE-Based Context-Aware Meta Search Engine | Traditional web search forces the developers to leave their working
environments and look for solutions in the web browsers. It often does not
consider the context of their programming problems. The context-switching
between the web browser and the working environment is time-consuming and
distracting, and the keyword-based traditional search often does not help much
in problem solving. In this paper, we propose an Eclipse IDE-based web search
solution that collects the data from three web search APIs-- Google, Yahoo,
Bing and a programming Q & A site-- Stack Overflow. It then provides search
results within IDE taking not only the content of the selected error into
account but also the problem context, popularity and search engine
recommendation of the result links. Experiments with 25 run time errors and
exceptions show that the proposed approach outperforms the keyword-based search
approaches with a recommendation accuracy of 96%. We also validate the results
with a user study involving five prospective participants where we get a result
agreement of 64.28%. While the preliminary results are promising, the approach
needs to be further validated with more errors and exceptions followed by a
user study with more participants to establish itself as a complete IDE-based
web search solution.
| 1 | 0 | 0 | 0 | 0 | 0 |
Sharing Data Homomorphically Encrypted with Different Encryption Keys | In this paper, we propose the first homomorphic based proxy re-encryption
(HPRE) solution that allows different users to share data they outsourced
homomorphically encrypted using their respective public keys with the
possibility to process such data remotely. More clearly, this scheme makes
possible to switch the public encryption key to another one without the help of
a trusted third party. Its originality stands on a method we propose so as to
compute the difference between two encrypted data without decrypting them and
with no extra communications. Basically, in our HPRE scheme, the two users, the
delegator and the delegate, ask the cloud server to generate an encrypted noise
based on a secret key, both users previously agreed on. Based on our solution
for comparing encrypted data, the cloud computes in clear the differences
in-between the encrypted noise and the encrypted data of the delegator,
obtaining thus blinded data. By next the cloud encrypts these differences with
the public key of the delegate. As the noise is also known of the delegate,
this one just has to remove it to get access to the data encrypted with his
public key. This solution has been experimented in the case of the sharing of
images outsourced into a semihonest cloud server.
| 1 | 0 | 0 | 0 | 0 | 0 |
Low temperature features in the heat capacity of unary metals and intermetallics for the example of bulk aluminum and Al$_3$Sc | We explore the competition and coupling of vibrational and electronic
contributions to the heat capacity of Al and Al$_3$Sc at temperatures below 50
K combining experimental calorimetry with highly converged finite temperature
density functional theory calculations. We find that semilocal exchange
correlation functionals accurately describe the rich feature set observed for
these temperatures, including electron-phonon coupling. Using different
representations of the heat capacity, we are therefore able to identify and
explain deviations from the Debye behaviour in the low-temperature limit and in
the temperature regime 30 - 50 K as well as the reduction of these features due
to the addition of Sc.
| 0 | 1 | 0 | 0 | 0 | 0 |
Designing spin and orbital exchange Hamiltonians with ultrashort electric field transients | We demonstrate how electric fields with arbitrary time profile can be used to
control the time-dependent parameters of spin and orbital exchange
Hamiltonians. Analytic expressions for the exchange constants are derived from
a time-dependent Schrieffer-Wolff transformation, and the validity of the
resulting effective Hamiltonian is verified for the case of a quarter-filled
two-orbital Hubbard model, by comparing to the results of a full nonequilibrium
dynamical mean-field theory simulation. The ability to manipulate Hamiltonians
with arbitrary time-dependent fields, beyond the paradigm of Floquet
engineering, opens the possibility to control intertwined spin and orbital
order using laser or THz pulses which are tailored to minimize electronic
excitations.
| 0 | 1 | 0 | 0 | 0 | 0 |
A Novel Comprehensive Approach for Estimating Concept Semantic Similarity in WordNet | Computation of semantic similarity between concepts is an important
foundation for many research works. This paper focuses on IC computing methods
and IC measures, which estimate the semantic similarities between concepts by
exploiting the topological parameters of the taxonomy. Based on analyzing
representative IC computing methods and typical semantic similarity measures,
we propose a new hybrid IC computing method. Through adopting the parameter
dhyp and lch, we utilize the new IC computing method and propose a novel
comprehensive measure of semantic similarity between concepts. An experiment
based on WordNet "is a" taxonomy has been designed to test representative
measures and our measure on benchmark dataset R&G, and the results show that
our measure can obviously improve the similarity accuracy. We evaluate the
proposed approach by comparing the correlation coefficients between five
measures and the artificial data. The results show that our proposal
outperforms the previous measures.
| 1 | 0 | 0 | 0 | 0 | 0 |
Tannakian duality for affine homogeneous spaces | Associated to any closed quantum subgroup $G\subset U_N^+$ and any index set
$I\subset\{1,\ldots,N\}$ is a certain homogeneous space $X_{G,I}\subset
S^{N-1}_{\mathbb C,+}$, called affine homogeneous space. We discuss here the
abstract axiomatization of the algebraic manifolds $X\subset S^{N-1}_{\mathbb
C,+}$ which can appear in this way, by using Tannakian duality methods.
| 0 | 0 | 1 | 0 | 0 | 0 |
Strong comparison principle for the fractional $p$-Laplacian and applications to starshaped rings | In the following we show the strong comparison principle for the fractional
$p$-Laplacian, i.e. we analyze functions $v,w$ which satisfy $v\geq w$ in
$\mathbb{R}^N$ and
\[
(-\Delta)^s_pv+q(x)|v|^{p-2}v\geq (-\Delta)^s_pw+q(x)|w|^{p-2}w \quad
\text{in $D$,}
\] where $s\in(0,1)$, $p>1$, $D\subset \mathbb{R}^N$ is an open set, and
$q\in L^{\infty}(\mathbb{R}^N)$ is a nonnegative function. Under suitable
conditions on $s,p$ and some regularity assumptions on $v,w$ we show that
either $v\equiv w$ in $\mathbb{R}^N$ or $v>w$ in $D$. Moreover, we apply this
result to analyze the geometry of nonnegative solutions in starshaped rings and
in the half space.
| 0 | 0 | 1 | 0 | 0 | 0 |
The uniformity and time-invariance of the intra-cluster metal distribution in galaxy clusters from the IllustrisTNG simulations | The distribution of metals in the intra-cluster medium encodes important
information about the enrichment history and formation of galaxy clusters. Here
we explore the metal content of clusters in IllustrisTNG - a new suite of
galaxy formation simulations building on the Illustris project. Our cluster
sample contains 20 objects in TNG100 - a ~(100 Mpc)^3 volume simulation with
2x1820^3 resolution elements, and 370 objects in TNG300 - a ~(300 Mpc)^3 volume
simulation with 2x2500^3 resolution elements. The z=0 metallicity profiles
agree with observations, and the enrichment history is consistent with
observational data going beyond z~1, showing nearly no metallicity evolution.
The abundance profiles vary only minimally within the cluster samples,
especially in the outskirts with a relative scatter of ~15%. The average
metallicity profile flattens towards the center, where we find a logarithmic
slope of -0.1 compared to -0.5 in the outskirts. Cool core clusters have more
centrally peaked metallicity profiles (~0.8 solar) compared to non-cool core
systems (~0.5 solar), similar to observational trends. Si/Fe and O/Fe radial
profiles follow positive gradients. The outer abundance profiles do not evolve
below z~2, whereas the inner profiles flatten towards z=0. More than ~80% of
the metals in the intra-cluster medium have been accreted from the
proto-cluster environment, which has been enriched to ~0.1 solar already at
z~2. We conclude that the intra-cluster metal distribution is uniform among our
cluster sample, nearly time-invariant in the outskirts for more than 10 Gyr,
and forms through a universal enrichment history.
| 0 | 1 | 0 | 0 | 0 | 0 |
Improving Native Ads CTR Prediction by Large Scale Event Embedding and Recurrent Networks | Click through rate (CTR) prediction is very important for Native
advertisement but also hard as there is no direct query intent. In this paper
we propose a large-scale event embedding scheme to encode the each user
browsing event by training a Siamese network with weak supervision on the
users' consecutive events. The CTR prediction problem is modeled as a
supervised recurrent neural network, which naturally model the user history as
a sequence of events. Our proposed recurrent models utilizing pretrained event
embedding vectors and an attention layer to model the user history. Our
experiments demonstrate that our model significantly outperforms the baseline
and some variants.
| 0 | 0 | 0 | 1 | 0 | 0 |
On the Communication Cost of Determining an Approximate Nearest Lattice Point | We consider the closest lattice point problem in a distributed network
setting and study the communication cost and the error probability for
computing an approximate nearest lattice point, using the nearest-plane
algorithm, due to Babai. Two distinct communication models, centralized and
interactive, are considered. The importance of proper basis selection is
addressed. Assuming a reduced basis for a two-dimensional lattice, we determine
the approximation error of the nearest plane algorithm. The communication cost
for determining the Babai point, or equivalently, for constructing the
rectangular nearest-plane partition, is calculated in the interactive setting.
For the centralized model, an algorithm is presented for reducing the
communication cost of the nearest plane algorithm in an arbitrary number of
dimensions.
| 1 | 0 | 0 | 0 | 0 | 0 |
One shot entanglement assisted classical and quantum communication over noisy quantum channels: A hypothesis testing and convex split approach | Capacity of a quantum channel characterizes the limits of reliable
communication through a noisy quantum channel. This fundamental information
theoretic question is very well studied specially in the setting of many
independent uses of the channel. An important scenario, both from practical and
conceptual point of view, is when the channel can be used only once. This is
known as the one-shot channel coding problem. We provide a tight
characterization of the one-shot entanglement assisted classical capacity of a
quantum channel. We arrive at our result by introducing a simple decoding
technique which we refer to as position-based decoding. We also consider two
other important quantum network scenarios: quantum channel with a jammer and
quantum broadcast channel. For these problems, we use the recently introduced
convex split technique [Anshu, Devabathini and Jain 2014] in addition to
position based decoding. Our approach exhibits that the simultaneous use of
these two techniques provides a uniform and conceptually simple framework for
designing communication protocols for quantum networks.
| 1 | 0 | 0 | 0 | 0 | 0 |
Conformally variational Riemannian invariants | Conformally variational Riemannian invariants (CVIs), such as the scalar
curvature, are homogeneous scalar invariants which arise as the gradient of a
Riemannian functional. We establish a wide range of stability and rigidity
results involving CVIs, generalizing many such results for the scalar
curvature.
| 0 | 0 | 1 | 0 | 0 | 0 |
Caching Meets Millimeter Wave Communications for Enhanced Mobility Management in 5G Networks | One of the most promising approaches to overcome the uncertainty and dynamic
channel variations of millimeter wave (mmW) communications is to deploy
dual-mode base stations that integrate both mmW and microwave ($\mu$W)
frequencies. If properly designed, such dual-mode base stations can enhance
mobility and handover in highly mobile wireless environments. In this paper, a
novel approach for analyzing and managing mobility in joint $\mu$W-mmW networks
is proposed. The proposed approach leverages device-level caching along with
the capabilities of dual-mode base stations to minimize handover failures,
reduce inter-frequency measurement energy consumption, and provide seamless
mobility in emerging dense heterogeneous networks. First, fundamental results
on the caching capabilities, including caching probability and cache duration
are derived for the proposed dual-mode network scenario. Second, the average
achievable rate of caching is derived for mobile users. Third, the proposed
cache-enabled mobility management problem is formulated as a dynamic matching
game between mobile user equipments (MUEs) and small base stations (SBSs). The
goal of this game is to find a distributed handover mechanism that subject to
the network constraints on HOFs and limited cache sizes, allows each MUE to
choose between executing an HO to a target SBS, being connected to the
macrocell base station (MBS), or perform a transparent HO by using the cached
content. The formulated matching game allows capturing the dynamics of the
mobility management problem caused by HOFs. To solve this dynamic matching
problem, a novel algorithm is proposed and its convergence to a two-sided
dynamically stable HO policy is proved. Numerical results corroborate the
analytical derivations and show that the proposed solution will provides
significant reductions in both the HOF and energy consumption by MUEs.
| 1 | 0 | 0 | 0 | 0 | 0 |
Poison Frogs! Targeted Clean-Label Poisoning Attacks on Neural Networks | Data poisoning is an attack on machine learning models wherein the attacker
adds examples to the training set to manipulate the behavior of the model at
test time. This paper explores poisoning attacks on neural nets. The proposed
attacks use "clean-labels"; they don't require the attacker to have any control
over the labeling of training data. They are also targeted; they control the
behavior of the classifier on a $\textit{specific}$ test instance without
degrading overall classifier performance. For example, an attacker could add a
seemingly innocuous image (that is properly labeled) to a training set for a
face recognition engine, and control the identity of a chosen person at test
time. Because the attacker does not need to control the labeling function,
poisons could be entered into the training set simply by leaving them on the
web and waiting for them to be scraped by a data collection bot.
We present an optimization-based method for crafting poisons, and show that
just one single poison image can control classifier behavior when transfer
learning is used. For full end-to-end training, we present a "watermarking"
strategy that makes poisoning reliable using multiple ($\approx$50) poisoned
training instances. We demonstrate our method by generating poisoned frog
images from the CIFAR dataset and using them to manipulate image classifiers.
| 0 | 0 | 0 | 1 | 0 | 0 |
Sorting Phenomena in a Mathematical Model For Two Mutually Attracting/Repelling Species | Macroscopic models for systems involving diffusion, short-range repulsion,
and long-range attraction have been studied extensively in the last decades. In
this paper we extend the analysis to a system for two species interacting with
each other according to different inner- and intra-species attractions. Under
suitable conditions on this self- and crosswise attraction an interesting
effect can be observed, namely phase separation into neighbouring regions, each
of which contains only one of the species. We prove that the intersection of
the support of the stationary solutions of the continuum model for the two
species has zero Lebesgue measure, while the support of the sum of the two
densities is simply connected.
Preliminary results indicate the existence of phase separation, i.e. spatial
sorting of the different species. A detailed analysis in one spatial dimension
follows. The existence and shape of segregated stationary solutions is shown
via the Krein-Rutman theorem. Moreover, for small repulsion/nonlinear
diffusion, also uniqueness of these stationary states is proved.
| 0 | 0 | 1 | 0 | 0 | 0 |
Ab initio design of drug carriers for zoledronate guest molecule using phosphonated and sulfonated calix[4]arene and calix[4]resorcinarene host molecules | Monomolecular drug carriers based on calix[n]-arenes and -resorcinarenes
containing the interior cavity can enhance the affinity and specificity of the
osteoporosis inhibitor drug zoledronate (ZOD). In this work we investigate the
suitability of nine different calix[4]-arenes and -resorcinarenes based
macrocycles as hosts for the ZOD guest molecule by conducting {\it ab initio}
density functional theory calculations for structures and energetics of
eighteen different host-guest complexes. For the optimized molecular structures
of the free, phosphonated, sulfonated calix[4]-arenes and -resorcinarenes, the
geometric sizes of their interior cavities are measured and compared with those
of the host-guest complexes in order to check the appropriateness for
host-guest complex formation. Our calculations of binding energies indicate
that in gaseous states some of the complexes might be unstable but in aqueous
states almost all of the complexes can be formed spontaneously. Of the two
different docking ways, the insertion of ZOD with the \ce{P-C-P} branch into
the cavity of host is easier than that with the nitrogen containing heterocycle
of ZOD. The work will open a way for developing effective drug delivering
systems for the ZOD drug and promote experimentalists to synthesize them.
| 0 | 1 | 0 | 0 | 0 | 0 |
Skeleton-based Action Recognition of People Handling Objects | In visual surveillance systems, it is necessary to recognize the behavior of
people handling objects such as a phone, a cup, or a plastic bag. In this
paper, to address this problem, we propose a new framework for recognizing
object-related human actions by graph convolutional networks using human and
object poses. In this framework, we construct skeletal graphs of reliable human
poses by selectively sampling the informative frames in a video, which include
human joints with high confidence scores obtained in pose estimation. The
skeletal graphs generated from the sampled frames represent human poses related
to the object position in both the spatial and temporal domains, and these
graphs are used as inputs to the graph convolutional networks. Through
experiments over an open benchmark and our own data sets, we verify the
validity of our framework in that our method outperforms the state-of-the-art
method for skeleton-based action recognition.
| 1 | 0 | 0 | 0 | 0 | 0 |
Active classification with comparison queries | We study an extension of active learning in which the learning algorithm may
ask the annotator to compare the distances of two examples from the boundary of
their label-class. For example, in a recommendation system application (say for
restaurants), the annotator may be asked whether she liked or disliked a
specific restaurant (a label query); or which one of two restaurants did she
like more (a comparison query).
We focus on the class of half spaces, and show that under natural
assumptions, such as large margin or bounded bit-description of the input
examples, it is possible to reveal all the labels of a sample of size $n$ using
approximately $O(\log n)$ queries. This implies an exponential improvement over
classical active learning, where only label queries are allowed. We complement
these results by showing that if any of these assumptions is removed then, in
the worst case, $\Omega(n)$ queries are required.
Our results follow from a new general framework of active learning with
additional queries. We identify a combinatorial dimension, called the
\emph{inference dimension}, that captures the query complexity when each
additional query is determined by $O(1)$ examples (such as comparison queries,
each of which is determined by the two compared examples). Our results for half
spaces follow by bounding the inference dimension in the cases discussed above.
| 1 | 0 | 0 | 0 | 0 | 0 |
Behavior of digital sequences through exotic numeration systems | Many digital functions studied in the literature, e.g., the summatory
function of the base-$k$ sum-of-digits function, have a behavior showing some
periodic fluctuation. Such functions are usually studied using techniques from
analytic number theory or linear algebra. In this paper we develop a method
based on exotic numeration systems and we apply it on two examples motivated by
the study of generalized Pascal triangles and binomial coefficients of words.
| 1 | 0 | 0 | 0 | 0 | 0 |
Quantum cognition goes beyond-quantum: modeling the collective participant in psychological measurements | In psychological measurements, two levels should be distinguished: the
'individual level', relative to the different participants in a given cognitive
situation, and the 'collective level', relative to the overall statistics of
their outcomes, which we propose to associate with a notion of 'collective
participant'. When the distinction between these two levels is properly
formalized, it reveals why the modeling of the collective participant generally
requires beyond-quantum - non-Bornian - probabilistic models, when sequential
measurements at the individual level are considered, and this though a pure
quantum description remains valid for single measurement situations.
| 0 | 0 | 0 | 0 | 1 | 0 |
Geometry of Projective Perfectoid and Integer Partitions | Line bundles of rational degree are defined using Perfectoid spaces, and
their co-homology computed via standard Čech complex along with Kunneth
formula. A new concept of `braided dimension' is introduced, which helps
convert the curse of infinite dimensionality into a boon, which is then used to
do Bezout type computations, define euler characters, describe ampleness and
link integer partitions with geometry. This new concept of 'Braided dimension'
gives a space within a space within a space an infinite tower of spaces, all
intricately braided into each other. Finally, the concept of Blow Up over
perfectoid space is introduced.
| 0 | 0 | 1 | 0 | 0 | 0 |
Determinantal Generalizations of Instrumental Variables | Linear structural equation models relate the components of a random vector
using linear interdependencies and Gaussian noise. Each such model can be
naturally associated with a mixed graph whose vertices correspond to the
components of the random vector. The graph contains directed edges that
represent the linear relationships between components, and bidirected edges
that encode unobserved confounding. We study the problem of generic
identifiability, that is, whether a generic choice of linear and confounding
effects can be uniquely recovered from the joint covariance matrix of the
observed random vector. An existing combinatorial criterion for establishing
generic identifiability is the half-trek criterion (HTC), which uses the
existence of trek systems in the mixed graph to iteratively discover
generically invertible linear equation systems in polynomial time. By focusing
on edges one at a time, we establish new sufficient and necessary conditions
for generic identifiability of edge effects extending those of the HTC. In
particular, we show how edge coefficients can be recovered as quotients of
subdeterminants of the covariance matrix, which constitutes a determinantal
generalization of formulas obtained when using instrumental variables for
identification.
| 0 | 0 | 1 | 1 | 0 | 0 |
Computational insights and the observation of SiC nanograin assembly: towards 2D silicon carbide | While an increasing number of two-dimensional (2D) materials, including
graphene and silicene, have already been realized, others have only been
predicted. An interesting example is the two-dimensional form of silicon
carbide (2D-SiC). Here, we present an observation of atomically thin and
hexagonally bonded nanosized grains of SiC assembling temporarily in graphene
oxide pores during an atomic resolution scanning transmission electron
microscopy experiment. Even though these small grains do not fully represent
the bulk crystal, simulations indicate that their electronic structure already
approaches that of 2D-SiC. This is predicted to be flat, but some doubts have
remained regarding the preference of Si for sp$^{3}$ hybridization. Exploring a
number of corrugated morphologies, we find completely flat 2D-SiC to have the
lowest energy. We further compute its phonon dispersion, with a Raman-active
transverse optical mode, and estimate the core level binding energies. Finally,
we study the chemical reactivity of 2D-SiC, suggesting it is like silicene
unstable against molecular absorption or interlayer linking. Nonetheless, it
can form stable van der Waals-bonded bilayers with either graphene or hexagonal
boron nitride, promising to further enrich the family of two-dimensional
materials once bulk synthesis is achieved.
| 0 | 1 | 0 | 0 | 0 | 0 |
Non-Homogeneous Hydrodynamic Systems and Quasi-Stäckel Hamiltonians | In this paper we present a novel construction of non-homogeneous hydrodynamic
equations from what we call quasi-Stäckel systems, that is non-commutatively
integrable systems constructed from appropriate maximally superintegrable
Stäckel systems. We describe the relations between Poisson algebras generated
by quasi-Stäckel Hamiltonians and the corresponding Lie algebras of vector
fields of non-homogeneous hydrodynamic systems. We also apply Stäckel
transform to obtain new non-homogeneous equations of considered type.
| 0 | 1 | 0 | 0 | 0 | 0 |
Latest results of the Tunka Radio Extension (ISVHECRI2016) | The Tunka Radio Extension (Tunka-Rex) is an antenna array consisting of 63
antennas at the location of the TAIGA facility (Tunka Advanced Instrument for
cosmic ray physics and Gamma Astronomy) in Eastern Siberia, nearby Lake Baikal.
Tunka-Rex is triggered by the air-Cherenkov array Tunka-133 during clear and
moonless winter nights and by the scintillator array Tunka-Grande during the
remaining time. Tunka-Rex measures the radio emission from the same air-showers
as Tunka-133 and Tunka-Grande, but with a higher threshold of about 100 PeV.
During the first stages of its operation, Tunka-Rex has proven, that sparse
radio arrays can measure air-showers with an energy resolution of better than
15\% and the depth of the shower maximum with a resolution of better than 40
g/cm\textsuperscript{2}. To improve and interpret our measurements as well as
to study systematic uncertainties due to interaction models, we perform radio
simulations with CORSIKA and CoREAS. In this overview we present the setup of
Tunka-Rex, discuss the achieved results and the prospects of mass-composition
studies with radio arrays.
| 0 | 1 | 0 | 0 | 0 | 0 |
The Rabi frequency on the $H^3Δ_1$ to $C^1Π$ transition in ThO: influence of interaction with electric and magnetic fields | Calculations of the correlations between the Rabi frequency on the
$H^3\Delta_1$ to $C^1\Pi$ transition in ThO molecule and experimental setup
parameters in the electron electric dipole moment (eEDM) search experiment is
performed. Calculations are required for estimations of systematic errors in
the experiment due to imperfections in laser beams used to prepare the molecule
and read out the eEDM signal.
| 0 | 1 | 0 | 0 | 0 | 0 |
Deriving mesoscopic models of collective behaviour for finite populations | Animal groups exhibit emergent properties that are a consequence of local
interactions. Linking individual-level behaviour to coarse-grained descriptions
of animal groups has been a question of fundamental interest. Here, we present
two complementary approaches to deriving coarse-grained descriptions of
collective behaviour at so-called mesoscopic scales, which account for the
stochasticity arising from the finite sizes of animal groups. We construct
stochastic differential equations (SDEs) for a coarse-grained variable that
describes the order/consensus within a group. The first method of construction
is based on van Kampen's system-size expansion of transition rates. The second
method employs Gillespie's chemical Langevin equations. We apply these two
methods to two microscopic models from the literature, in which organisms
stochastically interact and choose between two directions/choices of foraging.
These `binary-choice' models differ only in the types of interactions between
individuals, with one assuming simple pair-wise interactions, and the other
incorporating higher-order effects. In both cases, the derived mesoscopic SDEs
have multiplicative, or state-dependent, noise. However, the different models
demonstrate the contrasting effects of noise: increasing order in the pair-wise
interaction model, whilst reducing order in the higher-order interaction model.
Although both methods yield identical SDEs for such binary-choice, or
one-dimensional, systems, the relative tractability of the chemical Langevin
approach is beneficial in generalizations to higher-dimensions. In summary,
this book chapter provides a pedagogical review of two complementary methods to
construct mesoscopic descriptions from microscopic rules and demonstrates how
resultant multiplicative noise can have counter-intuitive effects on shaping
collective behaviour.
| 0 | 0 | 0 | 0 | 1 | 0 |
First Indirect X-Ray Imaging Tests With An 88-mm Diameter Single Crystal | Using the 1-BM-C beamline at the Advanced Photon Source (APS), we have
performed the initial indirect x-ray imaging point-spread-function (PSF) test
of a unique 88-mm diameter YAG:Ce single crystal of only 100-micron thickness.
The crystal was bonded to a fiber optic plate (FOP) for mechanical support and
to allow the option for FO coupling to a large format camera. This
configuration resolution was compared to that of self-supported 25-mm diameter
crystals, with and without an Al reflective coating. An upstream monochromator
was used to select 17-keV x-rays from the broadband APS bending magnet source
of synchrotron radiation. The upstream, adjustable Mo collimators were then
used to provide a series of x-ray source transverse sizes from 200 microns down
to about 15-20 microns (FWHM) at the crystal surface. The emitted scintillator
radiation was in this case lens coupled to the ANDOR Neo sCMOS camera, and the
indirect x-ray images were processed offline by a MATLAB-based image processing
program. Based on single Gaussian peak fits to the x-ray image projected
profiles, we observed a 10.5 micron PSF. This sample thus exhibited superior
spatial resolution to standard P43 polycrystalline phosphors of the same
thickness which would have about a 100-micron PSF. This single crystal
resolution combined with the 88-mm diameter makes it a candidate to support
future x-ray diffraction or wafer topography experiments.
| 0 | 1 | 0 | 0 | 0 | 0 |
A randomized Halton algorithm in R | Randomized quasi-Monte Carlo (RQMC) sampling can bring orders of magnitude
reduction in variance compared to plain Monte Carlo (MC) sampling. The extent
of the efficiency gain varies from problem to problem and can be hard to
predict. This article presents an R function rhalton that produces scrambled
versions of Halton sequences. On some problems it brings efficiency gains of
several thousand fold. On other problems, the efficiency gain is minor. The
code is designed to make it easy to determine whether a given integrand will
benefit from RQMC sampling. An RQMC sample of n points in $[0,1]^d$ can be
extended later to a larger n and/or d.
| 1 | 0 | 0 | 1 | 0 | 0 |
Leveraging Node Attributes for Incomplete Relational Data | Relational data are usually highly incomplete in practice, which inspires us
to leverage side information to improve the performance of community detection
and link prediction. This paper presents a Bayesian probabilistic approach that
incorporates various kinds of node attributes encoded in binary form in
relational models with Poisson likelihood. Our method works flexibly with both
directed and undirected relational networks. The inference can be done by
efficient Gibbs sampling which leverages sparsity of both networks and node
attributes. Extensive experiments show that our models achieve the
state-of-the-art link prediction results, especially with highly incomplete
relational data.
| 1 | 0 | 0 | 1 | 0 | 0 |
pMR: A high-performance communication library | On many parallel machines, the time LQCD applications spent in communication
is a significant contribution to the total wall-clock time, especially in the
strong-scaling limit. We present a novel high-performance communication library
that can be used as a de facto drop-in replacement for MPI in existing
software. Its lightweight nature that avoids some of the unnecessary overhead
introduced by MPI allows us to improve the communication performance of
applications without any algorithmic or complicated implementation changes. As
a first real-world benchmark, we make use of the pMR library in the coarse-grid
solve of the Regensburg implementation of the DD-$\alpha$AMG algorithm. On
realistic lattices, we see an improvement of a factor 2x in pure communication
time and total execution time savings of up to 20%.
| 1 | 1 | 0 | 0 | 0 | 0 |
Extending a Function Just by Multiplying and Dividing Function Values: Smoothness and Prime Identities | We describe a purely-multiplicative method for extending an analytic
function. It calculates the value of an analytic function at a point, merely by
multiplying together function values and reciprocals of function values at
other points closer to the origin. The function values are taken at the points
of geometric sequences, independent of the function, whose geometric ratios are
arbitrary. The method exposes an "elastic invariance" property of all analytic
functions. We show how to simplify and truncate multiplicative function
extensions for practical calculations. If we choose each geometric ratio to be
the reciprocal of a power of a prime number, we obtain a prime functional
identity, which contains a generalization of the Möbius function (with the
same denominator as the Rieman zeta function), and generates prime number
identities.
| 0 | 0 | 1 | 0 | 0 | 0 |
Towards Modeling the Interaction of Spatial-Associative Neural Network Representations for Multisensory Perception | Our daily perceptual experience is driven by different neural mechanisms that
yield multisensory interaction as the interplay between exogenous stimuli and
endogenous expectations. While the interaction of multisensory cues according
to their spatiotemporal properties and the formation of multisensory
feature-based representations have been widely studied, the interaction of
spatial-associative neural representations has received considerably less
attention. In this paper, we propose a neural network architecture that models
the interaction of spatial-associative representations to perform causal
inference of audiovisual stimuli. We investigate the spatial alignment of
exogenous audiovisual stimuli modulated by associative congruence. In the
spatial layer, topographically arranged networks account for the interaction of
audiovisual input in terms of population codes. In the associative layer,
congruent audiovisual representations are obtained via the experience-driven
development of feature-based associations. Levels of congruency are obtained as
a by-product of the neurodynamics of self-organizing networks, where the amount
of neural activation triggered by the input can be expressed via a nonlinear
distance function. Our novel proposal is that activity-driven levels of
congruency can be used as top-down modulatory projections to spatially
distributed representations of sensory input, e.g. semantically related
audiovisual pairs will yield a higher level of integration than unrelated
pairs. Furthermore, levels of neural response in unimodal layers may be seen as
sensory reliability for the dynamic weighting of crossmodal cues. We describe a
series of planned experiments to validate our model in the tasks of
multisensory interaction on the basis of semantic congruence and unimodal cue
reliability.
| 0 | 0 | 0 | 0 | 1 | 0 |
Dex-Net 2.0: Deep Learning to Plan Robust Grasps with Synthetic Point Clouds and Analytic Grasp Metrics | To reduce data collection time for deep learning of robust robotic grasp
plans, we explore training from a synthetic dataset of 6.7 million point
clouds, grasps, and analytic grasp metrics generated from thousands of 3D
models from Dex-Net 1.0 in randomized poses on a table. We use the resulting
dataset, Dex-Net 2.0, to train a Grasp Quality Convolutional Neural Network
(GQ-CNN) model that rapidly predicts the probability of success of grasps from
depth images, where grasps are specified as the planar position, angle, and
depth of a gripper relative to an RGB-D sensor. Experiments with over 1,000
trials on an ABB YuMi comparing grasp planning methods on singulated objects
suggest that a GQ-CNN trained with only synthetic data from Dex-Net 2.0 can be
used to plan grasps in 0.8sec with a success rate of 93% on eight known objects
with adversarial geometry and is 3x faster than registering point clouds to a
precomputed dataset of objects and indexing grasps. The Dex-Net 2.0 grasp
planner also has the highest success rate on a dataset of 10 novel rigid
objects and achieves 99% precision (one false positive out of 69 grasps
classified as robust) on a dataset of 40 novel household objects, some of which
are articulated or deformable. Code, datasets, videos, and supplementary
material are available at this http URL .
| 1 | 0 | 0 | 0 | 0 | 0 |
Effects of temperature and strain rate on mechanical behaviors of Stone-Wales defective monolayer black phosphorene | The mechanical behaviors of monolayer black phosphorene (MBP) are explored by
molecular dynamics (MD) simulations using reactive force field. It is revealed
that the temperature and strain rate have significant influence on mechanical
behaviors of MBP, and they are further weakened by SW (Stone-Wales) defects. In
general, the tensile strength for both of the pristine and SW defective MBP
decreases with the increase of temperature or decreasing of strain rate.
Surprisingly, for relatively high temperature and low strain rate, phase
transition from the black phosphorene to a mixture of {\beta}-phase ({\beta}-P)
and {\gamma}-phase ({\gamma}-P) is observed for the SW-2 defective MBP under
armchair tension, while self-healing of the SW-2 defect is observed under
zigzag tension. A deformation map of SW-2 defective MBP under armchair tension
at different temperature and strain rate is established, which is useful for
the design of phosphorene allotropes by strain. The results presented herein
yield useful insights for designing and tuning the structure, and the
mechanical and physical properties of phosphorene.
| 0 | 1 | 0 | 0 | 0 | 0 |
Ward identities for charge and heat currents of particle-particle and particle-hole pairs | The Ward identities for the charge and heat currents are derived for
particle-particle and particle-hole pairs. They are the exact constraints on
the current-vertex functions imposed by conservation laws and should be
satisfied by consistent theories. While the Ward identity for the charge
current of electrons is well established, that for the heat current is not
understood correctly. Thus the correct interpretation is presented. On this
firm basis the Ward identities for pairs are discussed. As the application of
the identity we criticize some inconsistent results in the studies of the
superconducting fluctuation transport and the transport anomaly in the normal
state of high-Tc superconductors.
| 0 | 1 | 0 | 0 | 0 | 0 |
Ultrafast imprinting of topologically protected magnetic textures via pulsed electrons | Short electron pulses are demonstrated to trigger and control magnetic
excitations, even at low electron current densities.
We show that the tangential magnetic field surrounding a picosecond electron
pulse can imprint topologically protected magnetic textures such as skyrmions
in a sample with a residual Dzyaloshinskii-Moriya spin-orbital coupling.
Characteristics of the created excitations such as the topological charge can
be steered via the duration and the strength of the electron pulses. The study
points to a possible way for a spatio-temporally controlled generation of
skyrmionic excitations.
| 0 | 1 | 0 | 0 | 0 | 0 |
Recurrent Environment Simulators | Models that can simulate how environments change in response to actions can
be used by agents to plan and act efficiently. We improve on previous
environment simulators from high-dimensional pixel observations by introducing
recurrent neural networks that are able to make temporally and spatially
coherent predictions for hundreds of time-steps into the future. We present an
in-depth analysis of the factors affecting performance, providing the most
extensive attempt to advance the understanding of the properties of these
models. We address the issue of computationally inefficiency with a model that
does not need to generate a high-dimensional image at each time-step. We show
that our approach can be used to improve exploration and is adaptable to many
diverse environments, namely 10 Atari games, a 3D car racing environment, and
complex 3D mazes.
| 1 | 0 | 0 | 1 | 0 | 0 |
Exceeding the Shockley-Queisser limit within the detailed balance framework | The Shockley-Queisser limit is one of the most fundamental results in the
field of photovoltaics. Based on the principle of detailed balance, it defines
an upper limit for a single junction solar cell that uses an absorber material
with a specific band gap. Although methods exist that allow a solar cell to
exceed the Shockley-Queisser limit, here we show that it is possible to exceed
the Shockley-Queisser limit without considering any of these additions. Merely
by introducing an absorptivity that does not assume that every photon with an
energy above the band gap is absorbed, efficiencies above the Shockley-Queisser
limit are obtained. This is related to the fact that assuming optimal
absorption properties also maximizes the recombination current within the
detailed balance approach. We conclude that considering a finite thickness for
the absorber layer allows the efficiency to exceed the Shockley-Queisser limit,
and that this is more likely to occur for materials with small band gaps.
| 0 | 1 | 0 | 0 | 0 | 0 |
Effect of disorder on the optical response of NiPt and Ni$_3$Pt alloys | In this communication we present a detailed study of the effect of chemical
disorder on the optical response of Ni$_{1-x}$Pt$_x$ (0.1$\leq$ x $\leq$0.75)
and Ni$_{3(1-x)/3}$Pt$_x$ (0.1$\leq$ x $\leq$0.3). We shall propose a formalism
which will combine a Kubo-Greenwood approach with a DFT based tight-binding
linear muffin-tin orbitals (TB-LMTO) basis and augmented space recursion (ASR)
technique to explicitly incorporate the effect of disorder. We show that
chemical disorder has a large impact on optical response of Ni-Pt systems. In
ordered Ni-Pt alloys, the optical conductivity peaks are sharp. But as we
switch on chemical disorder, the UV peak becomes broadened and its position as
a function of composition and disorder carries the signature of a phase
transition from NiPt to Ni$_3$Pt with decreasing Pt concentration.
Quantitatively this agrees well with Massalski's Ni-Pt phase diagram
\cite{massal}. Both ordered NiPt and Ni$_3$Pt have an optical conductivity
transition at 4.12 eV. But disordered NiPt has an optical conductivity
transition at 3.93 eV. If we decrease the Pt content, it results a chemical
phase transition from NiPt to Ni$_3$Pt and shifts the peak position by 1.67 eV
to the ultraviolet range at 5.6 eV. There is a significant broadening of UV
peak with increasing Pt content due to enhancement of 3d(Ni)-5d(Pt) bonding.
Chemical disorder enhances the optical response of NiPt alloys nearly one order
of magnitude. Our study also shows the fragile magnetic effect on optical
response of disordered Ni$_{1-x}$Pt$_x$ (0.4$<$ x $<$0.6) binary alloys. Our
theoretical predictions agree more than reasonably well with both earlier
experimental as well as theoretical investigations.
| 0 | 1 | 0 | 0 | 0 | 0 |
Train on Validation: Squeezing the Data Lemon | Model selection on validation data is an essential step in machine learning.
While the mixing of data between training and validation is considered taboo,
practitioners often violate it to increase performance. Here, we offer a
simple, practical method for using the validation set for training, which
allows for a continuous, controlled trade-off between performance and
overfitting of model selection. We define the notion of
on-average-validation-stable algorithms as one in which using small portions of
validation data for training does not overfit the model selection process. We
then prove that stable algorithms are also validation stable. Finally, we
demonstrate our method on the MNIST and CIFAR-10 datasets using stable
algorithms as well as state-of-the-art neural networks. Our results show
significant increase in test performance with a minor trade-off in bias
admitted to the model selection process.
| 0 | 0 | 0 | 1 | 0 | 0 |
Local migration quantification method for scratch assays | Motivation: The scratch assay is a standard experimental protocol used to
characterize cell migration. It can be used to identify genes that regulate
migration and evaluate the efficacy of potential drugs that inhibit cancer
invasion. In these experiments, a scratch is made on a cell monolayer and
recolonisation of the scratched region is imaged to quantify cell migration
rates. A drawback of this methodology is the lack of its reproducibility
resulting in irregular cell-free areas with crooked leading edges. Existing
quantification methods deal poorly with such resulting irregularities present
in the data. Results: We introduce a new quantification method that can analyse
low quality experimental data. By considering in-silico and in-vitro data, we
show that the method provides a more accurate statistical classification of the
migration rates than two established quantification methods. The application of
this method will enable the quantification of migration rates of scratch assay
data previously unsuitable for analysis. Availability and Implementation: The
source code and the implementation of the algorithm as a GUI along with an
example dataset and user instructions, are available in
this https URL.
The datasets are available in
this https URL.
| 0 | 0 | 0 | 0 | 1 | 0 |
Assessing the level of merging errors for coauthorship data: a Bayesian model | Robust analysis of coauthorship networks is based on high quality data.
However, ground-truth data are usually unavailable. Empirical data suffer
several types of errors, a typical one of which is called merging error,
identifying different persons as one entity. Specific features of authors have
been used to reduce these errors. We proposed a Bayesian model to calculate the
information of any given features of authors. Based on the features, the model
can be utilized to calculate the rate of merging errors for entities.
Therefore, the model helps to find informative features for detecting heavily
compromised entities. It has potential contributions to improving the quality
of empirical data.
| 1 | 0 | 0 | 0 | 0 | 0 |
Blood-based metabolic signatures in Alzheimer's disease | Introduction: Identification of blood-based metabolic changes might provide
early and easy-to-obtain biomarkers.
Methods: We included 127 AD patients and 121 controls with
CSF-biomarker-confirmed diagnosis (cut-off tau/A$\beta_{42}$: 0.52). Mass
spectrometry platforms determined the concentrations of 53 amine, 22 organic
acid, 120 lipid, and 40 oxidative stress compounds. Multiple signatures were
assessed: differential expression (nested linear models), classification
(logistic regression), and regulatory (network extraction).
Results: Twenty-six metabolites were differentially expressed. Metabolites
improved the classification performance of clinical variables from 74% to 79%.
Network models identified 5 hubs of metabolic dysregulation: Tyrosine,
glycylglycine, glutamine, lysophosphatic acid C18:2 and platelet activating
factor C16:0. The metabolite network for APOE $\epsilon$4 negative AD patients
was less cohesive compared to the network for APOE $\epsilon$4 positive AD
patients.
Discussion: Multiple signatures point to various promising peripheral markers
for further validation. The network differences in AD patients according to
APOE genotype may reflect different pathways to AD.
| 0 | 0 | 0 | 1 | 0 | 0 |
The Indecomposable Solutions of Linear Congruences | This article considers the minimal non-zero (= indecomposable) solutions of
the linear congruence $1\cdot x_1 + \cdots + (m-1)\cdot x_{m-1} \equiv 0 \pmod
m$ for unknown non-negative integers $x_1, \ldots, x_n$, and characterizes the
solutions that attain the Eggleton-Erdős bound. Furthermore it discusses
the asymptotic behaviour of the number of indecomposable solutions. The results
have direct interpretations in terms of zero-sum sequences and invariant
theory.
| 0 | 0 | 1 | 0 | 0 | 0 |
Weak multiplier Hopf algebras III. Integrals and duality | Let $(A,\Delta)$ be a weak multiplier Hopf algebra. It is a pair of a
non-degenerate algebra $A$, with or without identity, and a coproduct $\Delta$
on $A$, satisfying certain properties. The main difference with multiplier Hopf
algebras is that now, the canonical maps $T_1$ and $T_2$ on $A\otimes A$,
defined by $$T_1(a\otimes b)=\Delta(a)(1\otimes b)
\qquad\quad\text{and}\qquad\quad T_2(c\otimes a)=(c\otimes 1)\Delta(a),$$ are
no longer assumed to be bijective. Also recall that a weak multiplier Hopf
algebra is called regular if its antipode is a bijective map from $A$ to
itself.
In this paper, we introduce and study the notion of integrals on such regular
weak multiplier Hopf algebras. A left integral is a non-zero linear functional
on $A$ that is left invariant (in an appropriate sense). Similarly for a right
integral. For a regular weak multiplier Hopf algebra $(A,\Delta)$ with
(sufficiently many) integrals, we construct the dual $(\widehat
A,\widehat\Delta)$. It is again a regular weak multiplier Hopf algebra with
(sufficiently many) integrals. This duality extends the known duality of
finite-dimensional weak Hopf algebras to this more general case. It also
extends the duality of multiplier Hopf algebras with integrals, the so-called
algebraic quantum groups. For this reason, we will sometimes call a regular
weak multiplier Hopf algebra with enough integrals an algebraic quantum
groupoid.
We discuss the relation of our work with the work on duality for algebraic
quantum groupoids by Timmermann.
We also illustrate this duality with a particular example in a separate
paper. In this paper, we only mention the main definitions and results for this
example. However, we do consider the two natural weak multiplier Hopf algebras
associated with a groupoid in detail and show that they are dual to each other
in the sense of the above duality.
| 0 | 0 | 1 | 0 | 0 | 0 |
Monte-Carlo Tree Search by Best Arm Identification | Recent advances in bandit tools and techniques for sequential learning are
steadily enabling new applications and are promising the resolution of a range
of challenging related problems. We study the game tree search problem, where
the goal is to quickly identify the optimal move in a given game tree by
sequentially sampling its stochastic payoffs. We develop new algorithms for
trees of arbitrary depth, that operate by summarizing all deeper levels of the
tree into confidence intervals at depth one, and applying a best arm
identification procedure at the root. We prove new sample complexity guarantees
with a refined dependence on the problem instance. We show experimentally that
our algorithms outperform existing elimination-based algorithms and match
previous special-purpose methods for depth-two trees.
| 1 | 0 | 0 | 1 | 0 | 0 |
Efficient Model-Based Deep Reinforcement Learning with Variational State Tabulation | Modern reinforcement learning algorithms reach super-human performance on
many board and video games, but they are sample inefficient, i.e. they
typically require significantly more playing experience than humans to reach an
equal performance level. To improve sample efficiency, an agent may build a
model of the environment and use planning methods to update its policy. In this
article we introduce Variational State Tabulation (VaST), which maps an
environment with a high-dimensional state space (e.g. the space of visual
inputs) to an abstract tabular model. Prioritized sweeping with small backups,
a highly efficient planning method, can then be used to update state-action
values. We show how VaST can rapidly learn to maximize reward in tasks like 3D
navigation and efficiently adapt to sudden changes in rewards or transition
probabilities.
| 0 | 0 | 0 | 1 | 0 | 0 |
Griffiths Singularities in the Random Quantum Ising Antiferromagnet: A Tree Tensor Network Renormalization Group Study | The antiferromagnetic Ising chain in both transverse and longitudinal
magnetic fields is one of the paradigmatic models of a quantum phase
transition. The antiferromagnetic system exhibits a zero-temperature critical
line separating an antiferromagnetic phase and a paramagnetic phase; the
critical line connects an integrable quantum critical point at zero
longitudinal field and a classical first-order transition point at zero
transverse field. Using a strong-disorder renormalization group method
formulated as a tree tensor network, we study the zero-temperature phase of the
quantum Ising chain with bond randomness. We introduce a new matrix product
operator representation of high-order moments, which provides an efficient and
accurate tool for determining quantum phase transitions via the Binder cumulant
of the order parameter. Our results demonstrate an infinite-randomness quantum
critical point in zero longitudinal field accompanied by pronounced quantum
Griffiths singularities, arising from rare ordered regions with anomalously
slow fluctuations inside the paramagnetic phase. The strong Griffiths effects
are signaled by a large dynamical exponent $z>1$, which characterizes a
power-law density of low-energy states of the localized rare regions and
becomes infinite at the quantum critical point. Upon application of a
longitudinal field, the quantum phase transition between the paramagnetic phase
and the antiferromagnetic phase is completely destroyed. Furthermore, quantum
Griffiths effects are suppressed, showing $z<1$, when the dynamics of the rare
regions is hampered by the longitudinal field.
| 0 | 1 | 0 | 0 | 0 | 0 |
Which Neural Net Architectures Give Rise To Exploding and Vanishing Gradients? | We give a rigorous analysis of the statistical behavior of gradients in a
randomly initialized fully connected network N with ReLU activations. Our
results show that the empirical variance of the squares of the entries in the
input-output Jacobian of N is exponential in a simple architecture-dependent
constant beta, given by the sum of the reciprocals of the hidden layer widths.
When beta is large, the gradients computed by N at initialization vary wildly.
Our approach complements the mean field theory analysis of random networks.
From this point of view, we rigorously compute finite width corrections to the
statistics of gradients at the edge of chaos.
| 0 | 0 | 0 | 1 | 0 | 0 |
Curriculum-Based Neighborhood Sampling For Sequence Prediction | The task of multi-step ahead prediction in language models is challenging
considering the discrepancy between training and testing. At test time, a
language model is required to make predictions given past predictions as input,
instead of the past targets that are provided during training. This difference,
known as exposure bias, can lead to the compounding of errors along a generated
sequence at test time.
In order to improve generalization in neural language models and address
compounding errors, we propose a curriculum learning based method that
gradually changes an initially deterministic teacher policy to a gradually more
stochastic policy, which we refer to as \textit{Nearest-Neighbor Replacement
Sampling}. A chosen input at a given timestep is replaced with a sampled
nearest neighbor of the past target with a truncated probability proportional
to the cosine similarity between the original word and its top $k$ most similar
words. This allows the teacher to explore alternatives when the teacher
provides a sub-optimal policy or when the initial policy is difficult for the
learner to model. The proposed strategy is straightforward, online and requires
little additional memory requirements. We report our main findings on two
language modelling benchmarks and find that the proposed approach performs
particularly well when used in conjunction with scheduled sampling, that too
attempts to mitigate compounding errors in language models.
| 0 | 0 | 0 | 1 | 0 | 0 |
Randomized Composable Coresets for Matching and Vertex Cover | A common approach for designing scalable algorithms for massive data sets is
to distribute the computation across, say $k$, machines and process the data
using limited communication between them. A particularly appealing framework
here is the simultaneous communication model whereby each machine constructs a
small representative summary of its own data and one obtains an
approximate/exact solution from the union of the representative summaries. If
the representative summaries needed for a problem are small, then this results
in a communication-efficient and round-optimal protocol. While many fundamental
graph problems admit efficient solutions in this model, two prominent problems
are notably absent from the list of successes, namely, the maximum matching
problem and the minimum vertex cover problem. Indeed, it was shown recently
that for both these problems, even achieving a polylog$(n)$ approximation
requires essentially sending the entire input graph from each machine.
The main insight of our work is that the intractability of matching and
vertex cover in the simultaneous communication model is inherently connected to
an adversarial partitioning of the underlying graph across machines. We show
that when the underlying graph is randomly partitioned across machines, both
these problems admit randomized composable coresets of size $\widetilde{O}(n)$
that yield an $\widetilde{O}(1)$-approximate solution. This results in an
$\widetilde{O}(1)$-approximation simultaneous protocol for these problems with
$\widetilde{O}(nk)$ total communication when the input is randomly partitioned
across $k$ machines. We further prove the optimality of our results. Finally,
by a standard application of composable coresets, our results also imply
MapReduce algorithms with the same approximation guarantee in one or two rounds
of communication
| 1 | 0 | 0 | 0 | 0 | 0 |
simode: R Package for statistical inference of ordinary differential equations using separable integral-matching | In this paper we describe simode: Separable Integral Matching for Ordinary
Differential Equations. The statistical methodologies applied in the package
focus on several minimization procedures of an integral-matching criterion
function, taking advantage of the mathematical structure of the differential
equations like separability of parameters from equations. Application of
integral based methods to parameter estimation of ordinary differential
equations was shown to yield more accurate and stable results comparing to
derivative based ones. Linear features such as separability were shown to ease
optimization and inference. We demonstrate the functionalities of the package
using various systems of ordinary differential equations.
| 0 | 0 | 0 | 1 | 0 | 0 |
Positive scalar curvature and the Euler class | We prove the following generalization of the classical Lichnerowicz vanishing
theorem: if $F$ is an oriented flat vector bundle over a closed spin manifold
$M$ such that $TM$ carries a metric of positive scalar curvature, then
$<\widehat A(TM)e(F),[M]>=0$, where $e(F)$ is the Euler class of $F$.
| 0 | 0 | 1 | 0 | 0 | 0 |
Online Service with Delay | In this paper, we introduce the online service with delay problem. In this
problem, there are $n$ points in a metric space that issue service requests
over time, and a server that serves these requests. The goal is to minimize the
sum of distance traveled by the server and the total delay in serving the
requests. This problem models the fundamental tradeoff between batching
requests to improve locality and reducing delay to improve response time, that
has many applications in operations management, operating systems, logistics,
supply chain management, and scheduling.
Our main result is to show a poly-logarithmic competitive ratio for the
online service with delay problem. This result is obtained by an algorithm that
we call the preemptive service algorithm. The salient feature of this algorithm
is a process called preemptive service, which uses a novel combination of
(recursive) time forwarding and spatial exploration on a metric space. We hope
this technique will be useful for related problems such as reordering buffer
management, online TSP, vehicle routing, etc. We also generalize our results to
$k > 1$ servers.
| 1 | 0 | 0 | 0 | 0 | 0 |
Comparison of dynamic mechanical properties of non-superheated and superheated A357 alloys | The influence of superheat treatment on the microstructure and dynamic
mechanical properties of A357 alloys has been investigated. The study of
microstructure was performed by the optical microscope. Dynamic mechanical
properties (storage modulus, loss modulus, and damping capacity) were measured
by the dynamic mechanical analyzer (DMA). Microstructure showed coarser and
angular eutectic Si particles with larger {\alpha}-Al dendrites in the
non-superheated A357 alloy. In contrast, finer and rounded eutectic Si
particles together with smaller and preferred oriented {\alpha}-Al dendrites
have been observed in the superheated A357 alloy. Dynamic mechanical properties
showed an increasing trend of loss modulus and damping capacity meanwhile a
decreasing trend of storage modulus at elevated temperatures for superheated
and non-superheated A357 alloys. The high damping capacity of superheated A357
has been ascribed to the grain boundary damping at elevated temperatures.
| 0 | 1 | 0 | 0 | 0 | 0 |
On the accuracy and usefulness of analytic energy models for contemporary multicore processors | This paper presents refinements to the execution-cache-memory performance
model and a previously published power model for multicore processors. The
combination of both enables a very accurate prediction of performance and
energy consumption of contemporary multicore processors as a function of
relevant parameters such as number of active cores as well as core and Uncore
frequencies. Model validation is performed on the Sandy Bridge-EP and
Broadwell-EP microarchitectures. Production-related variations in chip quality
are demonstrated through a statistical analysis of the fit parameters obtained
on one hundred Broadwell-EP CPUs of the same model. Insights from the models
are used to explain the performance- and energy-related behavior of the
processors for scalable as well as saturating (i.e., memory-bound) codes. In
the process we demonstrate the models' capability to identify optimal operating
points with respect to highest performance, lowest energy-to-solution, and
lowest energy-delay product and identify a set of best practices for
energy-efficient execution.
| 1 | 0 | 0 | 0 | 0 | 0 |
A Simple Solution for Maximum Range Flight | Within the standard framework of quasi-steady flight, this paper derives a
speed that realizes the maximal obtainable range per unit of fuel. If this
speed is chosen at each instant of a flight plan $h(x)$ giving altitude $h$ as
a function of distance $x$, a variational problem for finding an optimal $h(x)$
can be formulated and solved. It yields flight plans with maximal range, and
these turn out to consist of mainly three phases using the optimal speed:
starting with a climb at maximal continuous admissible thrust, ending with a
continuous descent at idle thrust, and in between with a transition based on a
solution of the Euler-Lagrange equation for the variational problem. A similar
variational problem is derived and solved for speed-restricted flights, e.g. at
250 KIAS below 10000 ft. In contrast to the literature, the approach of this
paper does not need more than standard ordinary differential equations solving
variational problems to derive range-optimal trajectories. Various numerical
examplesbased on a Standard Business Jet are added for illustration.
| 0 | 0 | 1 | 0 | 0 | 0 |
Multiscale Residual Mixture of PCA: Dynamic Dictionaries for Optimal Basis Learning | In this paper we are interested in the problem of learning an over-complete
basis and a methodology such that the reconstruction or inverse problem does
not need optimization. We analyze the optimality of the presented approaches,
their link to popular already known techniques s.a. Artificial Neural
Networks,k-means or Oja's learning rule. Finally, we will see that one approach
to reach the optimal dictionary is a factorial and hierarchical approach. The
derived approach lead to a formulation of a Deep Oja Network. We present
results on different tasks and present the resulting very efficient learning
algorithm which brings a new vision on the training of deep nets. Finally, the
theoretical work shows that deep frameworks are one way to efficiently have
over-complete (combinatorially large) dictionary yet allowing easy
reconstruction. We thus present the Deep Residual Oja Network (DRON). We
demonstrate that a recursive deep approach working on the residuals allow
exponential decrease of the error w.r.t. the depth.
| 1 | 0 | 0 | 1 | 0 | 0 |
On factorizations of graphical maps | We study the categories governing infinity (wheeled) properads. The graphical
category, which was already known to be generalized Reedy, is in fact an
Eilenberg-Zilber category. A minor alteration to the definition of the wheeled
graphical category allows us to show that it is a generalized Reedy category.
Finally, we present model structures for Segal properads and Segal wheeled
properads.
| 0 | 0 | 1 | 0 | 0 | 0 |
Raking-ratio empirical process with auxiliary information learning | The raking-ratio method is a statistical and computational method which
adjusts the empirical measure to match the true probability of sets in a finite
partition. We study the asymptotic behavior of the raking-ratio empirical
process indexed by a class of functions when the auxiliary information is given
by the learning of the probability of sets in partitions from another sample
larger than the sample of the statistician. Under some metric entropy
hypothesis and conditions on the size of the independent samples, we establish
the strong approximation of this process with estimated auxiliary information
and show in particular that weak convergence is the same as the classical
raking-ratio empirical process. We also give possible statistical applications
of these results like strengthening the $Z$-test and the chi-square goodness of
fit test.
| 0 | 0 | 1 | 1 | 0 | 0 |
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation | Predicting the efficacy of a drug for a given individual, using
high-dimensional genomic measurements, is at the core of precision medicine.
However, identifying features on which to base the predictions remains a
challenge, especially when the sample size is small. Incorporating expert
knowledge offers a promising alternative to improve a prediction model, but
collecting such knowledge is laborious to the expert if the number of candidate
features is very large. We introduce a probabilistic model that can incorporate
expert feedback about the impact of genomic measurements on the sensitivity of
a cancer cell for a given drug. We also present two methods to intelligently
collect this feedback from the expert, using experimental design and
multi-armed bandit models. In a multiple myeloma blood cancer data set (n=51),
expert knowledge decreased the prediction error by 8%. Furthermore, the
intelligent approaches can be used to reduce the workload of feedback
collection to less than 30% on average compared to a naive approach.
| 1 | 0 | 0 | 1 | 0 | 0 |
On Vague Computers | Vagueness is something everyone is familiar with. In fact, most people think
that vagueness is closely related to language and exists only there. However,
vagueness is a property of the physical world. Quantum computers harness
superposition and entanglement to perform their computational tasks. Both
superposition and entanglement are vague processes. Thus quantum computers,
which process exact data without "exploiting" vagueness, are actually vague
computers.
| 1 | 0 | 0 | 0 | 0 | 0 |
Exploiting OxRAM Resistive Switching for Dynamic Range Improvement of CMOS Image Sensors | We present a unique application of OxRAM devices in CMOS Image Sensors (CIS)
for dynamic range (DR) improvement. We propose a modified 3T-APS (Active Pixel
Sensor) circuit that incorporates OxRAM in 1T-1R configuration. DR improvement
is achieved by resistive compression of the pixel output signal through
autonomous programming of OxRAM device resistance during exposure. We show that
by carefully preconditioning the OxRAM resistance, pixel DR can be enhanced.
Detailed impact of OxRAM SET-to-RESET and RESET-to-SET transitions on pixel DR
is discussed. For experimental validation with specific OxRAM preprogrammed
states, a 4 Kb 10 nm thick HfOx (1T-1R) matrix was fabricated and
characterized. Best case, relative pixel DR improvement of ~ 50 dB was obtained
for our design.
| 1 | 0 | 0 | 0 | 0 | 0 |
Magnetic control of Goos-Hanchen shifts in a yttrium-iron-garnet film | We investigate the Goos-Hanchen (G-H) shifts reflected and transmitted by a
yttrium-iron-garnet (YIG) film for both normal and oblique incidence. It is
found that the nonreciprocity effect of the MO material does not only result in
a nonvanishing reflected shift at normal incidence, but also leads to a
slab-thickness-independent term which breaks the symmetry between the reflected
and transmitted shifts at oblique incidence. The asymptotic behaviors of the
normal-incidence reflected shift are obtained in the vicinity of two
characteristic frequencies corresponding to a minimum reflectivity and a total
reflection, respectively. Moreover, the coexistence of two types of
negative-reflected-shift (NRS) at oblique incidence is discussed. We show that
the reversal of the shifts from positive to negative values can be realized by
tuning the magnitude of applied magnetic field, the frequency of incident wave
and the slab thickness as well as the incident angle. In addition, we further
investigate two special cases for practical purposes: the reflected shift with
a total reflection and the transmitted shift with a total transmission.
Numerical simulations are also performed to verify our analytical results.
| 0 | 1 | 0 | 0 | 0 | 0 |
Effective mass of quasiparticles from thermodynamics | We discuss the potential advantages of calculating the effective mass of
quasiparticles in the interacting electron liquid from the low-temperature free
energy vis-a-vis the conventional approach, in which the effective mass is
obtained from approximate calculations of the self-energy, or from a quantum
Monte Carlo evaluation of the energy of a variational "quasiparticle wave
function". While raw quantum Monte Carlo data are presently too sparse to allow
for an accurate determination of the effective mass, the values estimated by
this method are numerically close to the ones obtained in previous calculations
using diagrammatic many-body theory. In contrast to this, a recently published
parametrization of quantum Monte Carlo data for the free energy of the
homogeneous electron liquid yields effective masses that considerably deviate
from previous calculations and even change sign for low densities, reflecting
an unphysical negative entropy. We suggest that this anomaly is related to the
treatment of the exchange energy at finite temperature.
| 0 | 1 | 0 | 0 | 0 | 0 |
Dynamics over Signed Networks | A signed network is a network with each link associated with a positive or
negative sign. Models for nodes interacting over such signed networks, where
two different types of interactions take place along the positive and negative
links, respectively, arise from various biological, social, political, and
economic systems. As modifications to the conventional DeGroot dynamics for
positive links, two basic types of negative interactions along negative links,
namely the opposing rule and the repelling rule, have been proposed and studied
in the literature. This paper reviews a few fundamental convergence results for
such dynamics over deterministic or random signed networks under a unified
algebraic-graphical method. We show that a systematic tool of studying node
state evolution over signed networks can be obtained utilizing generalized
Perron-Frobenius theory, graph theory, and elementary algebraic recursions.
| 1 | 0 | 0 | 0 | 0 | 0 |
On the Estimation of Entropy in the FastICA Algorithm | The fastICA algorithm is a popular dimension reduction technique used to
reveal patterns in data. Here we show that the approximations used in fastICA
can result in patterns not being successfully recognised. We demonstrate this
problem using a two-dimensional example where a clear structure is immediately
visible to the naked eye, but where the projection chosen by fastICA fails to
reveal this structure. This implies that care is needed when applying fastICA.
We discuss how the problem arises and how it is intrinsically connected to the
approximations that form the basis of the computational efficiency of fastICA.
| 0 | 0 | 0 | 1 | 0 | 0 |
Spatial-Temporal Imaging of Anisotropic Photocarrier Dynamics in Black Phosphorus | As an emerging single elemental layered material with a low symmetry in-plane
crystal lattice, black phosphorus (BP) has attracted significant research
interest owing to its unique electronic and optoelectronic properties,
including its widely tunable bandgap, polarization dependent photoresponse and
highly anisotropic in-plane charge transport. Despite extensive study of the
steady-state charge transport in BP, there has not been direct characterization
and visualization of the hot carriers dynamics in BP immediately after
photoexcitation, which is crucial to understanding the performance of BP-based
optoelectronic devices. Here we use the newly developed scanning ultrafast
electron microscopy (SUEM) to directly visualize the motion of photo-excited
hot carriers on the surface of BP in both space and time. We observe highly
anisotropic in-plane diffusion of hot holes, with a 15-times higher diffusivity
along the armchair (x-) direction than that along the zigzag (y-) direction.
Our results provide direct evidence of anisotropic hot carrier transport in BP
and demonstrate the capability of SUEM to resolve ultrafast hot carrier
dynamics in layered two-dimensional materials.
| 0 | 1 | 0 | 0 | 0 | 0 |
The maximal order of iterated multiplicative functions | Following Wigert, a great number of authors including Ramanujan, Gronwall,
Erdős, Ivić, Heppner, J. Knopfmacher, Nicolas, Schwarz, Wirsing,
Freiman, Shiu et al. determined the maximal order of several multiplicative
functions, generalizing Wigert's result \[\max_{n\leq x} \log d(n)= (\log
2+o(1))\frac{\log x}{\log \log x}.\]
On the contrary, for many multiplicative functions, the maximal order of
iterations of the functions remains wide open. The case of the iterated divisor
function was only recently solved, answering a question of Ramanujan (1915).
Here, we determine the maximal order of $\log f(f(n))$ for a class of
multiplicative functions $f$ which are related to the divisor function. As a
corollary, we apply this to the function counting representations as sums of
two squares of non-negative integers, also known as $r_2(n)/4$, and obtain an
asymptotic formula: \[\max_{n\leq x} \log f(f(n))= (c+o(1))\frac{\sqrt{\log
x}}{\log \log x},\] with some explicitly given positive constant $c$.
| 0 | 0 | 1 | 0 | 0 | 0 |
Extending applicability of bimetric theory: chameleon bigravity | This article extends bimetric formulations of massive gravity to make the
mass of the graviton to depend on its environment. This minimal extension
offers a novel way to reconcile massive gravity with local tests of general
relativity without invoking the Vainshtein mechanism. On cosmological scales,
it is argued that the model is stable and that it circumvents the Higuchi
bound, hence relaxing the constraints on the parameter space. Moreover, with
this extension the strong coupling scale is also environmentally dependent in
such a way that it is kept sufficiently higher than the expansion rate all the
way up to the very early universe, while the present graviton mass is low
enough to be phenomenologically interesting. In this sense the extended
bigravity theory serves as a partial UV completion of the standard bigravity
theory. This extension is very generic and robust and a simple specific example
is described.
| 0 | 1 | 0 | 0 | 0 | 0 |
The Scaling Limit of High-Dimensional Online Independent Component Analysis | We analyze the dynamics of an online algorithm for independent component
analysis in the high-dimensional scaling limit. As the ambient dimension tends
to infinity, and with proper time scaling, we show that the time-varying joint
empirical measure of the target feature vector and the estimates provided by
the algorithm will converge weakly to a deterministic measured-valued process
that can be characterized as the unique solution of a nonlinear PDE. Numerical
solutions of this PDE, which involves two spatial variables and one time
variable, can be efficiently obtained. These solutions provide detailed
information about the performance of the ICA algorithm, as many practical
performance metrics are functionals of the joint empirical measures. Numerical
simulations show that our asymptotic analysis is accurate even for moderate
dimensions. In addition to providing a tool for understanding the performance
of the algorithm, our PDE analysis also provides useful insight. In particular,
in the high-dimensional limit, the original coupled dynamics associated with
the algorithm will be asymptotically "decoupled", with each coordinate
independently solving a 1-D effective minimization problem via stochastic
gradient descent. Exploiting this insight to design new algorithms for
achieving optimal trade-offs between computational and statistical efficiency
may prove an interesting line of future research.
| 1 | 1 | 0 | 1 | 0 | 0 |
Direct characterization of a nonlinear photonic circuit's wave function with laser light | Integrated photonics is a leading platform for quantum technologies including
nonclassical state generation \cite{Vergyris:2016-35975:SRP,
Solntsev:2014-31007:PRX, Silverstone:2014-104:NPHOT, Solntsev:2016:RPH},
demonstration of quantum computational complexity \cite{Lamitral_NJP2016} and
secure quantum communications \cite{Zhang:2014-130501:PRL}. As photonic
circuits grow in complexity, full quantum tomography becomes impractical, and
therefore an efficient method for their characterization
\cite{Lobino:2008-563:SCI, Rahimi-Keshari:2011-13006:NJP} is essential. Here we
propose and demonstrate a fast, reliable method for reconstructing the
two-photon state produced by an arbitrary quadratically nonlinear optical
circuit. By establishing a rigorous correspondence between the generated
quantum state and classical sum-frequency generation measurements from laser
light, we overcome the limitations of previous approaches for lossy multimode
devices \cite{Liscidini:2013-193602:PRL, Helt:2015-1460:OL}. We applied this
protocol to a multi-channel nonlinear waveguide network, and measured a
99.28$\pm$0.31\% fidelity between classical and quantum characterization. This
technique enables fast and precise evaluation of nonlinear quantum photonic
networks, a crucial step towards complex, large-scale, device production.
| 0 | 1 | 0 | 0 | 0 | 0 |
The Accuracy of Confidence Intervals for Field Normalised Indicators | When comparing the average citation impact of research groups, universities
and countries, field normalisation reduces the influence of discipline and
time. Confidence intervals for these indicators can help with attempts to infer
whether differences between sets of publications are due to chance factors.
Although both bootstrapping and formulae have been proposed for these, their
accuracy is unknown. In response, this article uses simulated data to
systematically compare the accuracy of confidence limits in the simplest
possible case, a single field and year. The results suggest that the MNLCS
(Mean Normalised Log-transformed Citation Score) confidence interval formula is
conservative for large groups but almost always safe, whereas bootstrap MNLCS
confidence intervals tend to be accurate but can be unsafe for smaller world or
group sample sizes. In contrast, bootstrap MNCS (Mean Normalised Citation
Score) confidence intervals can be very unsafe, although their accuracy
increases with sample sizes.
| 1 | 0 | 0 | 0 | 0 | 0 |
Generalized Theta Functions. I | Generalizations of classical theta functions are proposed that include any
even number of analytic parameters for which conditions of quasi-periodicity
are fulfilled and that are representations of extended Heisenberg group.
Differential equations for generalized theta functions and finite non-unitary
representations of extended Heisenberg group are presented so as other
properties and possible applications are pointed out such as a projective
embedding of tori by means of generalized theta functions.
| 0 | 1 | 0 | 0 | 0 | 0 |
Constructing grids for molecular quantum dynamics using an autoencoder | A challenge for molecular quantum dynamics (QD) calculations is the curse of
dimensionality with respect to the nuclear degrees of freedom. A common
approach that works especially well for fast reactive processes is to reduce
the dimensionality of the system to a few most relevant coordinates.
Identifying these can become a very difficult task, since they often are highly
unintuitive. We present a machine learning approach that utilizes an
autoencoder that is trained to find a low-dimensional representation of a set
of molecular configurations. These configurations are generated by trajectory
calculations performed on the reactive molecular systems of interest. The
resulting low-dimensional representation can be used to generate a potential
energy surface grid in the desired subspace. Using the G-matrix formalism to
calculate the kinetic energy operator, QD calculations can be carried out on
this grid. In addition to step-by-step instructions for the grid construction,
we present the application to a test system.
| 0 | 1 | 0 | 0 | 0 | 0 |
3D Pursuit-Evasion for AUVs | In this paper, we consider the problem of pursuit-evasion using multiple
Autonomous Underwater Vehicles (AUVs) in a 3D water volume, with and without
simple obstacles. Pursuit-evasion is a well studied topic in robotics, but the
results are mostly set in 2D environments, using unlimited line of sight
sensing. We propose an algorithm for range limited sensing in 3D environments
that captures a finite speed evader based on one single previous observation of
its location. The pursuers are first moved to form a maximal cage formation,
based on their number and sensor ranges, containing all of the possible evader
locations. The cage is then shrunk until every part of that volume is sensed,
thereby capturing the evader. The pursuers need only limited sensing range and
low bandwidth communication, making the algorithm well suited for an underwater
environment.
| 1 | 0 | 0 | 0 | 0 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.