title: Majorana Landau Level Raman Spectroscopy

abstract:
  The unambiguous experimental detection of quantum spin liquids and, in
particular, of the long-sought Kitaev quantum spin liquid (KQSL) with its
Majorana fermion excitations remains an outstanding challenge. One of the major
obstacles is the absence of signatures that definitively characterize this
phase. Here we propose the Landau levels known to form in the Majorana
excitation spectrum of the KQSL when certain strain fields are applied as a
direct signature of Majorana fermions with Dirac-like dispersion. In
particular, we show that the Majorana Landau level quantization of strained
films of the KQSL can be directly probed by Raman spectroscopy. Such
experiments are feasible in thin films of $\alpha$-RuCl$_3$, which are a
promising place to search for the KQSL.


title:
Continuous-wave operation and 10-Gb/s direct modulation of InAsP/InP
  sub-wavelength nanowire laser on silicon photonic crystal

abstract:
  We demonstrated sub-wavelength (~111 nm diameter) single nanowire (NW)
continuous wave (CW) lasers on silicon photonic crystal in the telecom-band
with direct modulation at 10 Gb/s by optical pumping at cryogenic temperatures.
To estimate the small signal response and pseudo-random bit sequence (PRBS)
modulation of our CW lasers, we employed a new signal detection technique that
employs a superconducting single photon detector and a time-correlated single
photon counting module. The results showed that our NW laser was unambiguously
modulated at above 10 Gb/s and an open eye pattern was obtained. This is the
first demonstration of a telecom-band CW NW laser with high-speed PRBS
modulation.


title: Iterative control strategies for non-linear systems

abstract:
  In this paper, we focus on the control of the mean field equilibrium of non
linear networks of the Langevin type in the limit of small noise. Using
iterative linear approximations, we derive a formula that prescribes a control
strategy in order to displace the equilibrium state of a given system, and
remarkably find that the control function has a "universal" form under certain
physical conditions. This result can be employed to define universal protocols
useful, for example, in the optimal work extraction from a given reservoir.
Generalizations and limits of application of the method are discussed.


title:
Statistics of the maximal distance and momentum in a trapped Fermi gas
  at low temperature

abstract:
  We consider $N$ non-interacting fermions in an isotropic $d$-dimensional
harmonic trap. We compute analytically the cumulative distribution of the
maximal radial distance of the fermions from the trap center at zero
temperature. While in $d=1$ the limiting distribution (in the large $N$ limit),
properly centered and scaled, converges to the squared Tracy-Widom distribution
of the Gaussian Unitary Ensemble in Random Matrix Theory, we show that for all
$d>1$, the limiting distribution converges to the Gumbel law. These limiting
forms turn out to be universal, i.e., independent of the details of the
trapping potential for a large class of isotropic trapping potentials. We also
study the position of the right-most fermion in a given direction in $d$
dimensions and, in the case of a harmonic trap, the maximum momentum, and show
that they obey similar Gumbel statistics. Finally, we generalize these results
to low but finite temperature.

categories: cond-mat.stat-mech cond-mat.quant-gas math-ph math.MP math.PR


title: General Two-variable Functions on the Slide-rule

abstract:
  We discuss the general theory of realizing two-variable fuctions on slide
rules (based on our paper 1977) and offer some new scales for practical use.


title:
Eigenmode orthogonality breaking and deviation from the fluctuation
  dissipation relation in rotationally dressed nanomechanical oscillators

abstract:
  The ultimate sensitivities achieved in force or mass sensing are limited by
the employed nanomechanical probes thermal noise. Its proper understanding is
critical for ultimate operation and any deviation from the underlying
fluctuation dissipation theorem should be carefully inspected. Here we
investigate an ultrasensitive vectorial force-field sensor, a singly clamped
nanowire oscillating along two quasi frequency degenerated transverse
directions. Immersing the nanowire in a non-conservative optical force field
causes dramatic modifications of its thermal noise and driven dynamics. In
regions of strong vorticity, eigenmodes orientations are distorted and lose
their initial orthogonality. Thermal noise spectra strongly deviate from the
normal mode expansion and presents an anomalous excess of noise violating the
fluctuation dissipation theorem. Our model quantitatively accounts for all
observations and underlines the role of non-axial response when patching the
fluctuation dissipation relation. These results reveal the intriguing
properties of thermal fluctuations in multimode nano-optomechanical systems and
the subtleties appearing when performing thermal noise thermometry in such
systems. They are also valid in any non-symmetrically coupled dual systems.


title: Monte Carlo Structured SVI for Two-Level Non-Conjugate Models

abstract:
  The stochastic variational inference (SVI) paradigm, which combines
variational inference, natural gradients, and stochastic updates, was recently
proposed for large-scale data analysis in conjugate Bayesian models and
demonstrated to be effective in several problems. This paper studies a family
of Bayesian latent variable models with two levels of hidden variables but
without any conjugacy requirements, making several contributions in this
context. The first is observing that SVI, with an improved structured
variational approximation, is applicable under more general conditions than
previously thought with the only requirement being that the approximating
variational distribution be in the same family as the prior. The resulting
approach, Monte Carlo Structured SVI (MC-SSVI), significantly extends the scope
of SVI, enabling large-scale learning in non-conjugate models. For models with
latent Gaussian variables we propose a hybrid algorithm, using both standard
and natural gradients, which is shown to improve stability and convergence.
Applications in mixed effects models, sparse Gaussian processes, probabilistic
matrix factorization and correlated topic models demonstrate the generality of
the approach and the advantages of the proposed algorithms.


title: On weak weighted estimates of martingale transform

abstract:
  We consider several weak type estimates for singular operators using the
Bellman function approach. We disprove the $A_1$ conjecture of Muckenhoupt,
which stayed open after Muckenhoupt--Wheeden's conjecture was disproved by
Reguera--Thiele.


title: Autoencoder-based holographic image restoration

abstract:
  We propose a holographic image restoration method using an autoencoder, which
is an artificial neural network. Because holographic reconstructed images are
often contaminated by direct light, conjugate light, and speckle noise, the
discrimination of reconstructed images may be difficult. In this paper, we
demonstrate the restoration of reconstructed images from holograms that record
page data in holographic memory and QR codes by using the proposed method.


title: Inflation in random Gaussian landscapes

abstract:
  We develop analytic and numerical techniques for studying the statistics of
slow-roll inflation in random Gaussian landscapes. As an illustration of these
techniques, we analyze small-field inflation in a one-dimensional landscape. We
calculate the probability distributions for the maximal number of e-folds and
for the spectral index of density fluctuations $n_s$ and its running
$\alpha_s$. These distributions have a universal form, insensitive to the
correlation function of the Gaussian ensemble. We outline possible extensions
of our methods to a large number of fields and to models of large-field
inflation. These methods do not suffer from potential inconsistencies inherent
in the Brownian motion technique, which has been used in most of the earlier
treatments.


title:
Neural Networks with Manifold Learning for Diabetic Retinopathy
  Detection

abstract:
  Widespread outreach programs using remote retinal imaging have proven to
decrease the risk from diabetic retinopathy, the leading cause of blindness in
the US. However, this process still requires manual verification of image
quality and grading of images for level of disease by a trained human grader
and will continue to be limited by the lack of such scarce resources.
Computer-aided diagnosis of retinal images have recently gained increasing
attention in the machine learning community. In this paper, we introduce a set
of neural networks for diabetic retinopathy classification of fundus retinal
images. We evaluate the efficiency of the proposed classifiers in combination
with preprocessing and augmentation steps on a sample dataset. Our experimental
results show that neural networks in combination with preprocessing on the
images can boost the classification accuracy on this dataset. Moreover the
proposed models are scalable and can be used in large scale datasets for
diabetic retinopathy detection. The models introduced in this paper can be used
to facilitate the diagnosis and speed up the detection process.


title: Quantifying perceived impact of scientific publications

abstract:
  Citations are commonly held to represent scientific impact. To date, however,
there is no empirical evidence in support of this postulate that is central to
research assessment exercises and Science of Science studies. Here, we report
on the first empirical verification of the degree to which citation numbers
represent scientific impact as it is actually perceived by experts in their
respective field. We run a large-scale survey of about 2000 corresponding
authors who performed a pairwise impact assessment task across more than 20000
scientific articles. Results of the survey show that citation data and
perceived impact do not align well, unless one properly accounts for strong
psychological biases that affect the opinions of experts with respect to their
own papers vs. those of others. First, researchers tend to largely prefer their
own publications to the most cited papers in their field of research. Second,
there is only a mild positive correlation between the number of citations of
top-cited papers in given research areas and expert preference in pairwise
comparisons. This also applies to pairs of papers with several orders of
magnitude differences in their total number of accumulated citations. However,
when researchers were asked to choose among pairs of their own papers, thus
eliminating the bias favouring one's own papers over those of others, they did
systematically prefer the most cited article. We conclude that, when scientists
have full information and are making unbiased choices, expert opinion on impact
is congruent with citation numbers.


title:
Trends and Progress in Nuclear and Hadron Physics: a straight or winding
  road

abstract:
  Quantitative calculations of the properties of hadrons and nuclei, with
assessed uncertainties, have emerged as competitive with experimental
measurements in a number of major cases. We may well be entering an era where
theoretical predictions are critical for experimental progress.
Cross-fertilization between the fields of relativistic hadronic structure and
non-relativistic nuclear structure is readily apparent. Non-perturbative
renormalization methods such as Similarity Renormalization Group and
Okubo-Lee-Suzuki schemes as well as many-body methods such as Coupled Cluster,
Configuration Interaction and Lattice Simulation methods are now employed and
advancing in both major areas of physics. New algorithms to apply these
approaches on supercomputers are shared among these areas of physics. The roads
to success have intertwined with each community taking the lead at various
times in the recent past. I briefly sketch these fascinating paths and comment
on some symbiotic relationships. I also overview some recent results from the
Hamiltonian Basis Light-Front Quantization approach.


title:
Probabilistic Bisection Converges Almost as Quickly as Stochastic
  Approximation

abstract:
  The probabilistic bisection algorithm (PBA) solves a class of stochastic
root-finding problems in one dimension by successively updating a prior belief
on the location of the root based on noisy responses to queries at chosen
points. The responses indicate the direction of the root from the queried
point, and are incorrect with a fixed probability. The fixed-probability
assumption is problematic in applications, and so we extend the PBA to apply
when this assumption is relaxed. The extension involves the use of a power-one
test at each queried point. We explore the convergence behavior of the extended
PBA, showing that it converges at a rate arbitrarily close to, but slower than,
the canonical "square root" rate of stochastic approximation.


title:
A construction of a finitely presented semigroup containing nonnilpotent
  nil ideal

abstract:
  This work presents an example of a finitely presented semigroup $S$
containing an infinite nonnilpotent nil ideal $LS$, whose elements do not have
a square (i.e. any word of the type $LXYYZ$ equals zero.)


title: On Background Independence and Duality Invariance in String Theory

abstract:
  Closed string theory exhibits an O(D,D) duality symmetry on tori, which in
double field theory is manifest before compactification. I prove that to first
order in $\alpha'$ there is no manifestly background independent and duality
invariant formulation of bosonic string theory in terms of metric, b-field and
dilaton. To this end I use O(D,D) invariant second order perturbation theory
around flat space to show that the unique background independent candidate
expression for the gauge algebra at order $\alpha'$ is inconsistent with the
Jacobi identity. A background independent formulation exists instead for frame
variables subject to $\alpha'$-deformed frame transformations (generalized
Green-Schwarz transformations). Potential applications for curved backgrounds,
as in cosmology, are discussed.


title: Fast Instability Caused by Electron Cloud in Combined Function Magnets

abstract:
  One of the factors which may limit the intensity in the Fermilab Recycler is
a fast transverse instability. It develops within a hundred turns and, in
certain conditions, may lead to a beam loss. The high rate of the instability
suggest that its cause is electron cloud. We studied the phenomena by observing
the dynamics of stable and unstable beam, simulating numerically the build-up
of the electron cloud, and developed an analytical model of an electron cloud
driven instability with the electrons trapped in combined function di-poles. We
found that beam motion can be stabilized by a clearing bunch, which confirms
the electron cloud nature of the instability. The clearing suggest electron
cloud trapping in Recycler combined function mag-nets. Numerical simulations
show that up to 1% of the particles can be trapped by the magnetic field. Since
the process of electron cloud build-up is exponential, once trapped this amount
of electrons significantly increases the density of the cloud on the next
revolution. In a Recycler combined function dipole this multi-turn accumulation
allows the electron cloud reaching final intensities orders of magnitude
greater than in a pure dipole. The estimated resulting instability growth rate
of about 30 revolutions and the mode fre-quency of 0.4 MHz are consistent with
experimental observations and agree with the simulation in the PEI code. The
created instability model allows investigating the beam stability for the
future intensity upgrades.


title:
The structure of mode-locking regions of piecewise-linear continuous
  maps: II. Skew sawtooth maps

abstract:
  In two-parameter bifurcation diagrams of piecewise-linear continuous maps on
$\mathbb{R}^N$, mode-locking regions typically have points of zero width known
as shrinking points. Near any shrinking point, but outside the associated
mode-locking region, a significant proportion of parameter space can be
usefully partitioned into a two-dimensional array of nearly-hyperbolic annular
sectors. The purpose of this paper is to show that in these sectors the
dynamics is well-approximated by a three-parameter family of skew sawtooth
circle maps, where the relationship between the skew sawtooth maps and the
$N$-dimensional map is fixed within each sector. The skew sawtooth maps are
continuous, degree-one, and piecewise-linear, with two different slopes. They
approximate the stable dynamics of the $N$-dimensional map with an error that
goes to zero with the distance from the shrinking point. The results explain
the complicated radial pattern of periodic, quasi-periodic, and chaotic
dynamics that occurs near shrinking points.


title: Tracking the World State with Recurrent Entity Networks

abstract:
  We introduce a new model, the Recurrent Entity Network (EntNet). It is
equipped with a dynamic long-term memory which allows it to maintain and update
a representation of the state of the world as it receives new data. For
language understanding tasks, it can reason on-the-fly as it reads text, not
just when it is required to answer a question or respond as is the case for a
Memory Network (Sukhbaatar et al., 2015). Like a Neural Turing Machine or
Differentiable Neural Computer (Graves et al., 2014; 2016) it maintains a fixed
size memory and can learn to perform location and content-based read and write
operations. However, unlike those models it has a simple parallel architecture
in which several memory locations can be updated simultaneously. The EntNet
sets a new state-of-the-art on the bAbI tasks, and is the first method to solve
all the tasks in the 10k training examples setting. We also demonstrate that it
can solve a reasoning task which requires a large number of supporting facts,
which other methods are not able to solve, and can generalize past its training
horizon. It can also be practically used on large scale datasets such as
Children's Book Test, where it obtains competitive performance, reading the
story in a single pass.


title:
Singular values of weighted composition operators and second
  quantization

abstract:
  We study a semigroup of weighted composition operators on the Hardy space of
the disk $H^2(\mathbb{D})$, and more generally on the Hardy space $H^2(U)$
attached to a simply connected domain $U$ with smooth boundary. Motivated by
conformal field theory, we establish bounds on the singular values
(approximation numbers) of these weighted composition operators. As a byproduct
we obtain estimates on the singular values of the restriction operator
(embedding operator) $H^2(V) \to H^2(U)$ when $U \subset V$ and the boundary of
$U$ touches that of $V$. Moreover, using the connection between the weighted
composition operators and restriction operators, we show that these operators
exhibit an analog of the Fisher-Micchelli phenomenon for non-compact operators.


title: An In Situ Measurement System for Characterizing Orbital Debris

abstract:
  This paper presents the development of an in situ measurement system known as
the Debris Resistive Acoustic Grid Orbital Navy/NASA Sensor (DRAGONS). The
DRAGONS system is designed to detect impacts caused by particles ranging from
50 micrometers to 1 mm at both low-earth and geostationary orbits. DRAGONS
utilizes a combination of low-cost sensor technologies to facilitate accurate
measurements and approximations of the size, velocity, and angle of impacting
micrometeoroids and orbital debris (MMOD). Two thin layers of kapton sheets
with resistive traces are used to detect the changes in resistance that are
directly proportional to the impacting force caused by the fast traveling
particles. Four polyvinylidene fluoride-based sensors are positioned in the
back of each kapton sheet to measure acoustic strain caused by an impact. The
electronic hardware module that controls all operations employs a low-power,
modular, and compact design that enables it to be installed as a low-resource
load on a host satellite. Laboratory results demonstrate that in addition to
having the ability to detect an impact event, the DRAGONS system can determine
impact location, speed, and angle of impact with a mean error of 1.4 cm, 0.2
km/s, and 5{\deg}. The DRAGONS system could be deployed as an add-on subsystem
of a payload to enable a real-time, in-depth study of the properties of MMOD.


title: Kondo Insulator to Semimetal Transformation Tuned by Spin-Orbit Coupling

abstract:
  Recent theoretical studies of topologically nontrivial electronic states in
Kondo insulators have pointed to the importance of spin-orbit coupling (SOC)
for stabilizing these states. However, systematic experimental studies that
tune the SOC parameter $\lambda_{\rm{SOC}}$ in Kondo insulators remain elusive.
The main reason is that variations of (chemical) pressure or doping strongly
influence the Kondo coupling $J_{\text{K}}$ and the chemical potential $\mu$ --
both essential parameters determining the ground state of the material -- and
thus possible $\lambda_{\rm{SOC}}$ tuning effects have remained unnoticed. Here
we present the successful growth of the substitution series
Ce$_3$Bi$_4$(Pt$_{1-x}$Pd$_x$)$_3$ ($0 \le x \le 1$) of the archetypal
(noncentrosymmetric) Kondo insulator Ce$_3$Bi$_4$Pt$_3$. The Pt-Pd substitution
is isostructural, isoelectronic, and isosize, and therefore likely to leave
$J_{\text{K}}$ and $\mu$ essentially unchanged. By contrast, the large mass
difference between the $5d$ element Pt and the $4d$ element Pd leads to a large
difference in $\lambda_{\rm{SOC}}$, which thus is the dominating tuning
parameter in the series. Surprisingly, with increasing $x$ (decreasing
$\lambda_{\rm{SOC}}$), we observe a Kondo insulator to semimetal transition,
demonstrating an unprecedented drastic influence of the SOC. The fully
substituted end compound Ce$_3$Bi$_4$Pd$_3$ shows thermodynamic signatures of a
recently predicted Weyl-Kondo semimetal.


title: Desingularization of bounded-rank matrix sets

abstract:
  Conventional ways to solve optimization problems on low-rank matrix sets
which appear in great number of applications ignore its underlying structure of
an algebraic variety and existence of singular points. This leads to appearance
of inverses of singular values in algorithms and since they could be close to
$0$ it causes certain problems. We tackle this problem by utilizing ideas from
the algebraic geometry and show how to desingularize these sets. Our main
result is algorithm which uses only bounded functions of singular values and
hence does not suffer from the issue described above.


title:
A self-calibrating method for heavy tailed data modelling. Application
  in neuroscience and finance

abstract:
  Modelling non-homogeneous and multi-component data is a problem that
challenges scientific researchers in several fields. In general, it is not
possible to find a simple and closed form probabilistic model to describe such
data. That is why one often resorts to non-parametric approaches. However, when
the multiple components are separable, parametric modelling becomes again
tractable. In this study, we propose a self-calibrating method to model
multi-component data that exhibit heavy tails. We introduce a three-component
hybrid distribution: a Gaussian distribution is linked to a Generalized Pareto
one via an exponential distribution that bridges the gap between mean and tail
behaviors. An unsupervised algorithm is then developed for estimating the
parameters of this model. We study analytically and numerically its
convergence. The effectiveness of the self-calibrating method is tested on
simulated data, before applying it to real data from neuroscience and finance,
respectively. A comparison with other standard Extreme Value Theory approaches
confirms the relevance and the practical advantage of this new method.


title: ConceptNet 5.5: An Open Multilingual Graph of General Knowledge

abstract:
  Machine learning about language can be improved by supplying it with specific
knowledge and sources of external information. We present here a new version of
the linked open data resource ConceptNet that is particularly well suited to be
used with modern NLP techniques such as word embeddings.
  ConceptNet is a knowledge graph that connects words and phrases of natural
language with labeled edges. Its knowledge is collected from many sources that
include expert-created resources, crowd-sourcing, and games with a purpose. It
is designed to represent the general knowledge involved in understanding
language, improving natural language applications by allowing the application
to better understand the meanings behind the words people use.
  When ConceptNet is combined with word embeddings acquired from distributional
semantics (such as word2vec), it provides applications with understanding that
they would not acquire from distributional semantics alone, nor from narrower
resources such as WordNet or DBPedia. We demonstrate this with state-of-the-art
results on intrinsic evaluations of word relatedness that translate into
improvements on applications of word vectors, including solving SAT-style
analogies.


title: Simulations of populations of Sapajus robustus in a fragmented landscape

abstract:
  The study of populations subject to the phenomenon of loss and fragmentation
of habitat, transforming continuous areas into small ones, usually surrounded
by anthropogenic matrices, has been the focus of many researches within the
scope of conservation. The objective of this study was to develop a computer
model by introducing modifications to the renowned Penna Model for biological
aging, in order to evaluate the behavior of populations subjected to the
effects of fragmented environments. As an object of study, it was used
biological data of the robust tufted capuchin (Sapajus robustus), an endangered
primate species whose geographical distribution within the Atlantic Rain Forest
is part of the backdrop of intense habitat fragmentation. The simulations
showed the expected behavior based on the three main aspects that affects
populations under intense habitat fragmentation: the population density, area
and conformation of the fragments and deleterious effects due the low genetic
variability in small and isolated populations. The model showed itself suitable
to describe changes in viability and population dynamics of the species crested
capuchin considering critical levels of survival in a fragmented environment
and also, actions in order to preserve the species should be focused not only
on increasing available area but also in dispersion dynamics.


title: Nonlinear Coherent Structures in Granular Crystals

abstract:
  The study of granular crystals, metamaterials that consist of closely packed
arrays of particles that interact elastically, is a vibrant area of research
that combines ideas from disciplines such as materials science, nonlinear
dynamics, and condensed-matter physics. Granular crystals, a type of nonlinear
metamaterial, exploit geometrical nonlinearities in their constitutive
microstructure to produce properties (such as tunability and energy
localization) that are not conventional to engineering materials and linear
devices. In this topical review, we focus on recent experimental,
computational, and theoretical results on nonlinear coherent structures in
granular crystals. Such structures --- which include traveling solitary waves,
dispersive shock waves, and discrete breathers --- have fascinating dynamics,
including a diversity of both transient features and robust, long-lived
patterns that emerge from broad classes of initial data. In our review, we
primarily discuss phenomena in one-dimensional crystals, as most research has
focused on such scenarios, but we also present some extensions to
two-dimensional settings. Throughout the review, we highlight open problems and
discuss a variety of potential engineering applications that arise from the
rich dynamic response of granular crystals.


title:
Probing the two Higgs doublet wedge region with charged Higgs boson
  decays to boosted jets

abstract:
  Two Higgs doublet extensions of the standard model, such as supersymmetry,
predict the existence of charged Higgs bosons. We explore the reach for
TeV-scale charged Higgs bosons through their associated production with top
quarks, and their decay to boosted top jets and $\mu_x$ tagged boosted bottom
jets, at a 14 TeV CERN Large Hadron Collider and at a 100 TeV Future Circular
Collider. In particular, we show the moderate $\tan\beta$ "wedge" region of
parameter space cannot be probed at the Large Hadron Collider for TeV-scale
$H^\pm$ because the cross section is too small. However, a 100 TeV future
proton collider can close the wedge region below 2 TeV, and search for $H^\pm$
up to 6 TeV.


title:
On the Formal Development of Behavioral Reactive Agents: A Systematic
  Braitenberg-Vehicle Approach

abstract:
  In this paper, a novel process has been developed to realize high-level
complex cognitive behaviors into reactive agents, efficiently. This method
paves the way for deducting high-level reactive behaviors from low-level
perceptive information by autonomous robots. The aforementioned process lets us
actualize different generations of Braitenberg vehicles, are which able to
mimic desired behaviors to survive in complex environments with high degrees of
flexibility in perception and emergence of high-level cognitive actions. The
approach has been used to engineer a Braitenberg vehicle with a wide range of
perception-action capabilities. Verification would be realized within this
framework, due to the efficient traceability between each sequential pair of
process phases. The applied simulations demonstrate the efficiency of the
established development process, based on the Braitenberg vehicle's behavior.


title: Carbon monoxide in an extremely metal-poor galaxy

abstract:
  Extremely metal-poor galaxies with metallicity below 10% of the solar value
in the local universe are the best analogues to investigating the interstellar
medium at a quasi-primitive environment in the early universe. In spite of the
ongoing formation of stars in these galaxies, the presence of molecular gas
(which is known to provide the material reservoir for star formation in
galaxies, such as our Milky Way) remains unclear. Here, we report the detection
of carbon monoxide (CO), the primary tracer of molecular gas, in a galaxy with
7% solar metallicity, with additional detections in two galaxies at higher
metallicities. Such detections offer direct evidence for the existence of
molecular gas in these galaxies that contain few metals. Using archived
infrared data, it is shown that the molecular gas mass per CO luminosity at
extremely low metallicity is approximately one-thousand times the Milky Way
value.


title:
Hybrid Repeat/Multi-point Sampling for Highly Volatile Objective
  Functions

abstract:
  A key drawback of the current generation of artificial decision-makers is
that they do not adapt well to changes in unexpected situations. This paper
addresses the situation in which an AI for aerial dog fighting, with tunable
parameters that govern its behavior, will optimize behavior with respect to an
objective function that must be evaluated and learned through simulations. Once
this objective function has been modeled, the agent can then choose its desired
behavior in different situations. Bayesian optimization with a Gaussian Process
surrogate is used as the method for investigating the objective function. One
key benefit is that during optimization the Gaussian Process learns a global
estimate of the true objective function, with predicted outcomes and a
statistical measure of confidence in areas that haven't been investigated yet.
However, standard Bayesian optimization does not perform consistently or
provide an accurate Gaussian Process surrogate function for highly volatile
objective functions. We treat these problems by introducing a novel sampling
technique called Hybrid Repeat/Multi-point Sampling. This technique gives the
AI ability to learn optimum behaviors in a highly uncertain environment. More
importantly, it not only improves the reliability of the optimization, but also
creates a better model of the entire objective surface. With this improved
model the agent is equipped to better adapt behaviors.


title:
Deep Convolutional Poses for Human Interaction Recognition in Monocular
  Videos

abstract:
  Human interaction recognition is a challenging problem in computer vision and
has been researched over the years due to its important applications. With the
development of deep models for the human pose estimation problem, this work
aims to verify the effectiveness of using the human pose in order to recognize
the human interaction in monocular videos. This paper developed a method based
on 5 steps: detect each person in the scene, track them, retrieve the human
pose, extract features based on the pose and finally recognize the interaction
using a classifier. The Two-Person interaction dataset was used for the
development of this methodology. Using a whole sequence evaluation approach it
achieved 87.56% of average accuracy of all interaction. Yun, et at achieved
91.10% using the same dataset, however their methodology used the depth sensor
to recognize the interaction. The methodology developed in this paper shows
that an RGB camera can be as effective as depth cameras to recognize the
interaction between two persons using the recent development of deep models to
estimate the human pose.


title: Path-Complete Graphs and Common Lyapunov Functions

abstract:
  A Path-Complete Lyapunov Function is an algebraic criterion composed of a
finite number of functions, called its pieces, and a directed, labeled graph
defining Lyapunov inequalities between these pieces. It provides a stability
certificate for discrete-time switching systems under arbitrary switching.
  In this paper, we prove that the satisfiability of such a criterion implies
the existence of a Common Lyapunov Function, expressed as the composition of
minima and maxima of the pieces of the Path-Complete Lyapunov function. The
converse, however, is not true even for discrete-time linear systems: we
present such a system where a max-of-2 quadratics Lyapunov function exists
while no corresponding Path-Complete Lyapunov function with 2 quadratic pieces
exists.
  In light of this, we investigate when it is possible to decide if a
Path-Complete Lyapunov function is less conservative than another. By analyzing
the combinatorial and algebraic structure of the graph and the pieces
respectively, we provide simple tools to decide when the existence of such a
Lyapunov function implies that of another.


title: Electrical Double Layer Properties of Spherical Oxide Nanoparticles

abstract:
  The accurate characterization of electrical double layer properties of
nanoparticles is of fundamental importance for optimizing their physicochemical
properties for specific biotechnological and biomedical applications. In this
article, we use classical solvation density functional theory and a surface
complexation model to investigate the effects of pH and nanoparticle size on
the structural and electrostatic properties of an electrolyte solution
surrounding a spherical silica oxide nanoparticle. The formulation has been
particularly useful for identifying dominant interactions governing the ionic
driving force under a variety of pH levels and nanoparticle sizes. As a result
of the energetic interplay displayed between electrostatic potential, ion-ion
correlation and particle crowding effects on the nanoparticle surface
titration, rich, non-trivial ion density profiles and mean electrostatic
potential behavior have been found.


title:
Restless Video Bandits: Optimal SVC Streaming in a Multi-user Wireless
  Network

abstract:
  In this paper, we consider the problem of optimal scalable video delivery to
mobile users in wireless networks given arbitrary Quality Adaptation (QA)
mechanisms. In current practical systems, QA and scheduling are performed
independently by the content provider and network operator, respectively. While
most research has been focused on jointly optimizing these two tasks, the high
complexity that comes with a joint approach makes the implementation
impractical. Therefore, we present a scheduling mechanism that takes the QA
logic of each user as input and optimizes the scheduling accordingly. Hence,
there is no need for centralized QA and cross-layer interactions are minimized.
We model the QA-adaptive scheduling and the jointly optimal problem as a
Restless Bandit and a Multi-user Semi Markov Decision Process, respectively in
order to compare the loss incurred by not employing a jointly optimal scheme.
We then present heuristic algorithms in order to achieve the optimal outcome of
the Restless Bandit solution assuming the base station has knowledge of the
underlying quality adaptation of each user (QA-Aware). We also present a
simplified heuristic without the need for any higher layer knowledge at the
base station (QA-Blind). We show that our QA-Aware strategy can achieve up to
two times improvement in user network utilization compared to popular baseline
algorithms such as Proportional Fairness. We also provide a testbed
implementation of the QA-Blind scheme in order to compare it with baseline
algorithms in a real network setting.


title:
Large phase relaxation length in the topological surface states of
  epitaxial Bi2-xSnxTe3 thin films

abstract:
  A topological insulator (TI), a new quantum state featured with the
topologically-protected surface state (TSS) originating from its peculiar
topology in band structure, has attracted much interest due to academic and
practical importance. Nonetheless, a large contribution of the bulk conduction,
induced by unintended doping by defects, has hindered the characterization of
the unique surface state and the utilization of it into a device. To resolve
this problem, we have investigated the transport properties of epitaxial
Bi2-xSnxTe3 thin films with varying x. With the bulk conduction being strongly
suppressed, the TSS is separately characterized, resulting in a large phase
relaxation length of ~250 nm at 1.8 K, a record-high value in TIs. In addition,
the magnetoresistance ratio (MR) has shown a non-monotonic temperature
dependence with a maximum value at an elevated temperature depending on x.
These results are associated with the compensation of carriers and, we believe,
provide an important step for the application of topological insulators for
developing novel functional devices based on the topological surface states.


title:
Morphology of clusters of attractive dry and wet self-propelled
  spherical particle suspensions

abstract:
  In order to asses the effect of hydrodynamics in the assembly of active
attractive spheres, we simulate a semi-dilute suspension of attractive
self-propelled spherical particles in a quasi two dimensional geometry
comparing the case with and without hydrodynamics interactions. To start with,
independently on the presence of hydrodynamics, we observe that depending on
the ratio between attraction and propulsion, particles either coarsen or
aggregate forming finite-size clusters. Focusing on the clustering regime, we
characterize two different clusters parameters, i.e. their morphology and
orientational order, and compare the case when active particles behave either
as pushers or pullers (always in the regime where inter-particles attractions
competes with self-propulsion). Studying cluster phases for squirmers with
respect to those obtained for active Brownian disks (indicated as ABP), we have
shown that hydrodynamics alone can sustain a cluster phase of active swimmers
(pullers), while ABP form cluster phases due to the competition between
attraction and self propulsion. The structural properties of the cluster phases
of squirmers and ABP are similar, although squirmers show sensitivity to active
stresses. Active Brownian disks resemble weakly pusher squirmer suspensions in
terms of cluster size distribution, structure of the radius of gyration on
cluster size and degree of cluster polarity.


title: Inherently trap-free convex landscapes for full quantum optimal control

abstract:
  We present a comprehensive analysis of the landscape for full quantum-quantum
control associated with the expectation value of an arbitrary observable of one
quantum system controlled by another quantum system. It is shown that such full
quantum-quantum control landscapes are convex, and hence devoid of local
suboptima and saddle points that may exist in landscapes for quantum systems
controlled by time-dependent classical fields. There is no controllability
requirement for the full quantum-quantum landscape to be trap-free, although
the forms of Hamiltonians, the flexibility in choosing initial state of the
controller, as well as the control duration, can infulence the reachable
optimal value on the landscape. All level sets of the full quantum-quantum
landscape are connected convex sets. Finally, we show that the optimal solution
of the full quantum-quantum control landscape can be readily determined
numerically, which is demonstrated using the Jaynes-Cummings model depicting a
two-level atom interacting with a quantized radiation field.


title: A Fast Keypoint Based Hybrid Method for Copy Move Forgery Detection

abstract:
  Copy move forgery detection in digital images has become a very popular
research topic in the area of image forensics. Due to the availability of
sophisticated image editing tools and ever increasing hardware capabilities, it
has become an easy task to manipulate the digital images. Passive forgery
detection techniques are more relevant as they can be applied without the prior
information about the image in question. Block based techniques are used to
detect copy move forgery, but have limitations of large time complexity and
sensitivity against affine operations like rotation and scaling. Keypoint based
approaches are used to detect forgery in large images where the possibility of
significant post processing operations like rotation and scaling is more. A
hybrid approach is proposed using different methods for keypoint detection and
description. Speeded Up Robust Features (SURF) are used to detect the keypoints
in the image and Binary Robust Invariant Scalable Keypoints (BRISK) features
are used to describe features at these keypoints. The proposed method has
performed better than the existing forgery detection method using SURF
significantly in terms of detection speed and is invariant to post processing
operations like rotation and scaling. The proposed method is also invariant to
other commonly applied post processing operations like adding Gaussian noise
and JPEG compression


title:
Evaluating Automatic Speech Recognition Systems in Comparison With Human
  Perception Results Using Distinctive Feature Measures

abstract:
  This paper describes methods for evaluating automatic speech recognition
(ASR) systems in comparison with human perception results, using measures
derived from linguistic distinctive features. Error patterns in terms of
manner, place and voicing are presented, along with an examination of confusion
matrices via a distinctive-feature-distance metric. These evaluation methods
contrast with conventional performance criteria that focus on the phone or word
level, and are intended to provide a more detailed profile of ASR system
performance,as well as a means for direct comparison with human perception
results at the sub-phonemic level.


title:
Performance Improvements of Probabilistic Transcript-adapted ASR with
  Recurrent Neural Network and Language-specific Constraints

abstract:
  Mismatched transcriptions have been proposed as a mean to acquire
probabilistic transcriptions from non-native speakers of a language.Prior work
has demonstrated the value of these transcriptions by successfully adapting
cross-lingual ASR systems for different tar-get languages. In this work, we
describe two techniques to refine these probabilistic transcriptions: a
noisy-channel model of non-native phone misperception is trained using a
recurrent neural net-work, and decoded using minimally-resourced
language-dependent pronunciation constraints. Both innovations improve quality
of the transcript, and both innovations reduce phone error rate of a
trainedASR, by 7% and 9% respectively


title:
Polarization Gradient Study of Interstellar Medium Turbulence Using The
  Canadian Galactic Plane Survey

abstract:
  We have investigated the magneto-ionic turbulence in the interstellar medium
through spatial gradients of the complex radio polarization vector in the
Canadian Galactic Plane Survey (CGPS). The CGPS data cover 1300 square-degrees,
over the range ${53^{\circ}}\leq{\ell}\leq{192^{\circ}}$,
${-3^{\circ}}\leq{b}\leq{5^{\circ}}$ with an extension to ${b}={17.5^{\circ}}$
in the range ${101^{\circ}}\leq{\ell}\leq{116^{\circ}}$, and arcminute
resolution at 1420 MHz. Previous studies found a correlation between the
skewness and kurtosis of the polarization gradient and the Mach number of the
turbulence, or assumed this correlation to deduce the Mach number of an
observed turbulent region. We present polarization gradient images of the
entire CGPS dataset, and analyze the dependence of these images on angular
resolution. The polarization gradients are filamentary, and the length of these
filaments is largest towards the Galactic anti-center, and smallest towards the
inner Galaxy. This may imply that small-scale turbulence is stronger in the
inner Galaxy, or that we observe more distant features at low Galactic
longitudes. For every resolution studied, the skewness of the polarization
gradient is influenced by the edges of bright polarization gradient regions,
which are not related to the turbulence revealed by the polarization gradients.
We also find that the skewness of the polarization gradient is sensitive to the
size of the box used to calculate the skewness, but insensitive to Galactic
longitude, implying that the skewness only probes the number and magnitude of
the inhomogeneities within the box. We conclude that the skewness and kurtosis
of the polarization gradient are not ideal statistics for probing natural
magneto-ionic turbulence.


title: Design of 5G Full Dimension Massive MIMO Systems

abstract:
  Massive multiple-input-multiple-output (MIMO) transmission is a promising
technology to improve the capacity and reliability of wireless systems.
However, the number of antennas that can be equipped at a base station (BS) is
limited by the BS form factor, posing a challenge to the deployment of massive
linear arrays. To cope with this limitation, this work discusses Full Dimension
MIMO (FD-MIMO), which is currently an active area of research and
standardization in the 3rd Generation Partnership Project (3GPP) for evolution
towards fifth generation (5G) cellular systems. FD-MIMO utilizes an active
antenna system (AAS) with a 2D planar array structure, which provides the
ability of adaptive electronic beamforming in the 3D space. This paper presents
the design of the AAS and the ongoing efforts in the 3GPP to develop the
corresponding 3D channel model. Compact structure of large-scale antenna arrays
drastically increases the spatial correlation in FD-MIMO systems. In order to
account for its effects, the generalized spatial correlation functions for
channels constituted by individual antenna elements and overall antenna ports
in the AAS are derived. Exploiting the quasi-static channel covariance matrices
of the users, the problem of determining the optimal downtilt weight vector for
antenna ports, which maximizes the minimum signal-to-interference ratio of a
multi-user multiple-input-single-output system, is formulated as a fractional
optimization problem. A quasi-optimal solution is obtained through the
application of semi-definite relaxation and Dinkelbach's method. Finally, the
user-group specific elevation beamforming scenario is devised, which offers
significant performance gains as confirmed through simulations. These results
have direct application in the analysis of 5G FD-MIMO systems.


title: Data Compression for the Tomo-e Gozen with Low-rank Matrix Approximation

abstract:
  Optical wide-field surveys with a high cadence are expected to create a new
field of astronomy, so-called "movie astronomy," in the near future. The amount
of data of the observations will be huge, and hence efficient data compression
will be indispensable. Here we propose a low-rank matrix approximation with
sparse matrix decomposition as a promising solution to reduce the data size
effectively, while preserving sufficient scientific information. We apply one
of the methods to the movie data obtained with the prototype model of the
Tomo-e Gozen mounted on the 1.0-m Schmidt telescope of Kiso Observatory. Once
the full-scale observation of the Tomo-e Gozen commences, it will generate ~30
TB of data per night. We demonstrate that the data are compressed by a factor
of about 10 in size without losing transient events like optical short
transient point-sources and meteors. The intensity of point sources can be
recovered from the compressed data. The processing runs sufficiently fast,
compared with the expected data-acquisition rate in the actual observing runs.


title:
Magnetic Bloch Skyrmion Transport by Electric Fields in a Composite
  Bilayer

abstract:
  We investigate a mechanical method to manipulate magnetic Bloch Skyrmions by
applying an electric field in a composite chiral-magnetic (CM)/ferroelectric
(FE) bilayer. The magnetoelectric coupling at the interface allows the electric
field to stimulate magnetic ordering. Therefore it offers the possibility to
generate Skyrmions [Phys. Rev. B 94, 014311 (2016)]. Here, we design a movable
and localized electric field source to drive skyrmion transport along the
bilayer. A traveling velocity of the electric field source must be carefully
chosen to show the stability and effciency of this process. The effects of high
speed operation will be discussed.


title:
Continuous-variable entanglement generated with a hybrid PT-symmetric
  system

abstract:
  We study a proposal of generating macroscopic continuous-variable
entanglement with two coupled waveguides respectively carrying optical damping
and optical gain. Moreover, a squeezing element is added into one or both
waveguides. We show that quantum noise effect existing in the process is
essential to the degree of the generated entanglement. It will totally
eliminate the entanglement in the setup of adding the squeezing element into
the waveguide filled with optical damping material, but will not completely
damp the entanglement to zero in the other configurations of having the
squeezing element in the gain medium or in both gain and damping medium. The
degree of the generated continuous-variable entanglement is irrelevant to the
intensities of the input light in coherent states. Moreover, the relations
between the entanglement and system parameters are illustrated in terms of the
dynamical evolutions of the created continuous-variable entanglement.


title: L\'{e}vy robotics

abstract:
  Two the most common tasks for autonomous mobile robots is to explore the
environment and locate a target. %In the last case, the objective is either to
find a target in the shortest time possible or, alternatively, to find %as many
targets as possible for a given amount of time. Targets could range from
sources of chemical contamination to people needing assistance in a disaster
area. From the very beginning, the quest for most efficient search algorithms
was strongly influenced by behavioral science and ecology, where researchers
try to figure out the strategies used by leaving beings, from bacteria to
mammals. Since then, bio-inspired random search algorithms remain one the most
important directions in autonomous robotics. Recently a new wave arrived
bringing a specific type of random walks as a universal search strategy
exploited by immune cells, insects, mussels, albatrosses, sharks, deers, and a
dozen of other animals including humans. These \textit{L\'{e}vy} walks combine
two key features, the ability of walkers to spread anomalously fast while
moving with a finite velocity. The latter is especially valuable in the context
of robotics because it respects the reality autonomous robots live in. There is
already an impressive body of publications on L\'{e}vy robotics; yet research
in this field is unfolding further, constantly bringing new results, ideas,
hypothesis and speculations. In this mini-review we survey the current state of
the field, list latest advances, discuss the prevailing trends, and outline
further perspectives.


title:
Invariants of the special orthogonal group and an enhanced Brauer
  category

abstract:
  We first give a short intrinsic, diagrammatic proof of the First Fundamental
Theorem of invariant theory (FFT) for the special orthogonal group
$\text{SO}_m(\mathbb{C})$, given the FFT for $\text{O}_m(\mathbb{C})$. We then
define, by means of a presentation with generators and relations, an enhanced
Brauer category $\widetilde{\mathcal{B}}(m)$ by adding a single generator to
the usual Brauer category $\mathcal{B}(m)$, together with four relations. We
prove that our category $\widetilde{\mathcal{B}}(m)$ is actually (and
remarkably) {\em equivalent} to the category of representations of
$\text{SO}_m$ generated by the natural representation. The FFT for
$\text{SO}_m$ amounts to the surjectivity of a certain functor $\mathcal{F}$ on
$\text{Hom}$ spaces, while the Second Fundamental Theorem for $\text{SO}_m$
says simply that $\mathcal{F}$ is injective on $\text{Hom}$ spaces. This
theorem provides a diagrammatic means of computing the dimensions of spaces of
homomorphisms between tensor modules for $\text{SO}_m$ (for any $m$). These
methods will be applied to the case of the orthosymplectic Lie algebras
$\text{osp}(m|2n)$, where the super-Pfaffian enters, in a future work.


title: Electron Dynamics in Relativistic Strophotron

abstract:
  Relativistic strophotron is a system in which fast electrons move along a
potential trough produced by quadrupole electric lenses. Equations of motion in
the strophotron field are investigated and electron trajectories are found. It
is shown, that electrons are harmonically oscillating in transverse direction
and do complex motion in longitudinal direction.


title:
Structural analysis of star-forming blue early-type galaxies:
  Merger-driven star formation in elliptical galaxies

abstract:
  Star-forming blue early-type galaxies at low redshift can give insight to the
stellar mass growth of L$*$ elliptical galaxies in the local Universe. We wish
to understand the reason for star formation in these otherwise passively
evolving red and dead stellar systems. The fuel for star formation can be
acquired through recent accretion events such as mergers or flyby. The
signatures of such events should be evident from a structural analysis of the
galaxy image. We carried out structural analysis on SDSS $r$-band imaging data
of 55 star-forming blue elliptical galaxies, derived the structural parameters,
analysed the residuals from best-fit to surface brightness distribution, and
constructed the galaxy scaling relations. We found that star-forming blue
early-type galaxies are bulge-dominated systems with axial ratio $>$ 0.5 and
surface brightness profiles fitted by Sersic profiles with index ($n$) mostly
$>$ 2. Twenty-three galaxies are found to have $n$ $<$ 2; these could be
hosting a disc component. The residual images of the 32 galaxy surface
brightness profile fits show structural features indicative of recent
interactions. The star-forming blue elliptical galaxies follow the Kormendy
relation and show the characteristics of normal elliptical galaxies as far as
structural analysis is concerned. There is a general trend for high-luminosity
galaxies to display interaction signatures and high star formation rates. The
star-forming population of blue early-type galaxies at low redshifts could be
normal ellipticals that might have undergone a recent gas-rich minor merger
event. The star formation in these galaxies will shut down once the recently
acquired fuel is consumed, following which the galaxy will evolve to a normal
early-type galaxy.


title: A systematic study on the cosmic ray antiproton flux

abstract:
  Recently the AMS-02 collaboration has published the measurement of the cosmic
antiproton to proton ratio $\bar{p}/p$ and the $\bar{p}$ flux with a high
precision up to $\sim 450\,\mathrm{GeV}$. In this work, we perform a systematic
analysis of the secondary antiproton flux generated by the cosmic ray
interaction with the interstellar gas. The uncertainty of the prediction
originates from the cosmic ray propagation process and the hadronic interaction
models. Although the cosmic ray propagation parameters have been well
controlled by the AMS-02 $B/C$ ratio data for a specified model, different
propagation models can not be discriminated by the $B/C$ data. The $\bar{p}$
flux is also calculated for several hadronic interaction models, which are
generally adopted by the cosmic ray community. However, the results for
different hadronic models do not converge. We find the EPOS LHC model, which
seems to fit the collider data very well, predicts a slightly lower $\bar{p}/p$
ratio than the AMS-02 data at the high energy end. Finally we derive the
constraints on the dark matter annihilation cross section from the AMS-02
$\bar{p}/p$ ratio for different propagation and hadronic interaction models.


title: Self-Dual Gravity and the Immirzi parameter

abstract:
  Working in the first order formalism of gravity, we propose an action that
combines the self and anti-self-dual parts of the curvature and comprises all
the diffeomorphism invariant Lagrangians that one can consider in this
formalism. The action that we propose is motivated by (A)dS gauge theories of
gravity. We use this action to derive the (2+1)-dimensional version of the
Immirzi parameter. Our derivation relates explicitly the Immirzi parameter to
the existence of two classically equivalent actions for the description of
gravity in (2+1) dimensions, namely the standard and exotic actions introduced
by Witten in the description of (2+1) gravity as a gauge theory. This relation
had been conjectured previously in the literature, but not derived.


title:
Avoiding communication in primal and dual block coordinate descent
  methods

abstract:
  Primal and dual block coordinate descent methods are iterative methods for
solving regularized and unregularized optimization problems. Distributed-memory
parallel implementations of these methods have become popular in analyzing
large machine learning datasets. However, existing implementations communicate
at every iteration which, on modern data center and supercomputing
architectures, often dominates the cost of floating-point computation. Recent
results on communication-avoiding Krylov subspace methods suggest that large
speedups are possible by re-organizing iterative algorithms to avoid
communication. We show how applying similar algorithmic transformations can
lead to primal and dual block coordinate descent methods that only communicate
every $s$ iterations--where $s$ is a tuning parameter--instead of every
iteration for the \textit{regularized least-squares problem}. We show that the
communication-avoiding variants reduce the number of synchronizations by a
factor of $s$ on distributed-memory parallel machines without altering the
convergence rate and attains strong scaling speedups of up to $6.1\times$ on a
Cray XC30 supercomputer.


title:
Galactic structure in the outer disk: the field in the line of sight to
  the intermediate-age open cluster Tombaugh 1

abstract:
  We employ optical photometry and high-resolution spectroscopy to study a
field toward the open cluster Tombaugh 1, where we identify a complex
population mixture, that we describe in terms of young and old Galactic thin
disk. Of particular interest is the spatial distribution of the young
population, which consists of dwarfs with spectral type as early as B6, and
distribute in a {\it blue plume} feature in the colour-magnitude diagram. For
the first time we confirm spectroscopically that most of these stars are early
type stars, and not blue stragglers nor halo/thick disk sub-dwarfs. Moreover,
they are not evenly distributed along the line of sight, but crowd at
heliocentric distances between 6.6 and 8.2 kpc. We compare these results with
present-day understanding of the spiral structure of the Galaxy and suggest
that they traces the outer arm. This range in distances challenges current
Galactic models adopting a disk cut-off at 14 kpc from the Galactic center. The
young dwarfs overlap in space with an older component which identifies the old
Galactic thin disk. Both young and old populations are confined in space since
the disk is warped at the latitude and longitude of Tombaugh~1. The main
effects of the warp are that the line of sight intersects the disk and entirely
crosses it at the outer arm distance, and that there are no traces of the
closer Perseus arm, which would then be either un-important in this sector, or
located much closer to the formal Galactic plane. We finally analysed a group
of giant stars, which turn out to be located at very different distances, and
to possess very different chemical properties, with no obvious relation with
the other populations.


title:
Rate-Achieving Policy in Finite-Horizon Throughput Region for Multi-User
  Interference Channels

abstract:
  This paper studies a wireless network consisting of multiple
transmitter-receiver pairs sharing the same spectrum where interference is
regarded as noise. Previously, the throughput region of such a network was
characterized for either one time slot or an infinite time horizon. This work
aims to close the gap by investigating the throughput region for transmissions
over a finite time horizon. We derive an efficient algorithm to examine the
achievability of any given rate in the finite-horizon throughput region and
provide the rate-achieving policy. The computational efficiency of our
algorithm comes from the use of A* search with a carefully chosen heuristic
function and a tree pruning strategy. We also show that the celebrated
max-weight algorithm which finds all achievable rates in the infinite-horizon
throughput region fails to work for the finite-horizon throughput region.


title: Weak lensing from self-ordering scalar fields

abstract:
  Cosmological defects result from cosmological phase transitions in the early
Universe and the dynamics reflects their symmetry-breaking mechanisms. These
cosmological defects may be probed through weak lensing effects because they
interact with ordinary matters only through the gravitational force. In this
paper, we investigate global textures by using weak lensing curl and B modes.
Non-topological textures are modeled by the non-linear sigma model (NLSM), and
induce not only the scalar perturbation but also vector and tensor
perturbations in the primordial plasma due to the nonlinearity in the
anisotropic stress of scalar fields. We show angular power spectra of curl and
B modes from both vector and tensor modes based on the NLSM. Furthermore, we
give the analytic estimations for curl and B mode power spectra. The amplitude
of weak lensing signals depends on a combined parameter $\epsilon^{2}_{v} =
N^{-1}\left( v/m_{\rm pl} \right)^{4}$ where $N$ and $v$ are the number of the
scalar fields and the vacuum expectation value, respectively. We discuss the
detectability of the curl and B modes with several observation specifications.
In the case of the CMB lensing observation without including the instrumental
noise, we can reach $\epsilon_{v} \approx 2.7\times 10^{-6}$. This constraint
is about 10 times stronger than the current one determined from the Planck. For
the cosmic shear observation, we find that the signal-to-noise ratio depends on
the mean redshift and the observing number of galaxies as $\propto z^{0.7}_{\rm
m}$ and $\propto N^{0.2}_{\rm g}$, respectively. In the study of textures using
cosmic shear observations, the mean redshift would be one of the key design
parameters.


title: A Video-Based Method for Objectively Rating Ataxia

abstract:
  For many movement disorders, such as Parkinson's disease and ataxia, disease
progression is visually assessed by a clinician using a numerical disease
rating scale. These tests are subjective, time-consuming, and must be
administered by a professional. This can be problematic where specialists are
not available, or when a patient is not consistently evaluated by the same
clinician. We present an automated method for quantifying the severity of
motion impairment in patients with ataxia, using only video recordings. We
consider videos of the finger-to-nose test, a common movement task used as part
of the assessment of ataxia progression during the course of routine clinical
checkups.
  Our method uses neural network-based pose estimation and optical flow
techniques to track the motion of the patient's hand in a video recording. We
extract features that describe qualities of the motion such as speed and
variation in performance. Using labels provided by an expert clinician, we
train a supervised learning model that predicts severity according to the Brief
Ataxia Rating Scale (BARS). The performance of our system is comparable to that
of a group of ataxia specialists in terms of mean error and correlation, and
our system's predictions were consistently within the range of inter-rater
variability. This work demonstrates the feasibility of using computer vision
and machine learning to produce consistent and clinically useful measures of
motor impairment.


title: Multi-bump solutions for fractional Nirenberg problem

abstract:
  We consider the multi-bump solutions of the following fractional Nirenberg
problem \begin{equation}\label{01} (-\Delta)^s u=K(x)u^{\frac{n+2s}{n-2s}},
\;\;\;\;u>0\;\;\text{ in }\mathbb{R}^n, \end{equation} where $s\in (0,1)$ and
$n>2+2s$. If $K$ is a periodic function in some $k$ variables with $1\leq
k<\frac{n-2s}2$, we proved that \eqref{01} has multi-bump solutions with bumps
clustered on some lattice points in $\mathbb{R}^k$ via Lyapunov-Schmidt
reduction. It is also established that the equation \eqref{01} has an
infinite-many-bump solutions with bumps clustered on some lattice points in
$\mathbb{R}^n$ which is isomorphic to $\mathbb{Z}_+^k$.


title: Wigner distributions of quarks for different polarizations

abstract:
  We calculate quark Wigner distributions using the light-front wave functions
in a dressed quark model. In this model, a proton target is replaced by a
simplified spin-1/2 state, namely a quark dressed with a gluon. We calculate
the Wigner distributions for different polarization configuration of quark and
the target state in this model.


title: An empirical analysis of the optimization of deep network loss surfaces

abstract:
  The success of deep neural networks hinges on our ability to accurately and
efficiently optimize high-dimensional, non-convex functions. In this paper, we
empirically investigate the loss functions of state-of-the-art networks, and
how commonly-used stochastic gradient descent variants optimize these loss
functions. To do this, we visualize the loss function by projecting them down
to low-dimensional spaces chosen based on the convergence points of different
optimization algorithms. Our observations suggest that optimization algorithms
encounter and choose different descent directions at many saddle points to find
different final weights. Based on consistency we observe across re-runs of the
same stochastic optimization algorithm, we hypothesize that each optimization
algorithm makes characteristic choices at these saddle points.


title: Clockwork Goldstone Bosons

abstract:
  The clockwork mechanism has recently been proposed as a natural way to
generate hierarchies among parameters in quantum field theories. The mechanism
is characterized by a very specific pattern of spontaneous and explicit
symmetry breaking, and the presence of new light states referred to as `gears'.
In this paper we begin by investigating the self-interactions of these gears in
a scalar clockwork model and find a parity-like selection rule at all orders in
the fields. We then proceed to investigate how the clockwork mechanism can be
realized in 5D linear dilaton models from the spontaneous symmetry breaking of
a complex bulk scalar field. We also discuss how the clockwork mechanism is
manifest in the scalar components of 5D gauge theories in the linear dilaton
model, and build their 4D deconstructed analogue. Finally we discuss attempts
at building both 4D and 5D realizations of a non-abelian scalar clockwork
mechanism, where in the latter we consider scenarios in which the Goldstone
bosons arise from 5D scalar and 5D gauge fields.


title: Fubini theorem in noncommutative geometry

abstract:
  We discuss the Fubini formula in Alain Connes' noncommutative geometry. We
present a sufficient condition on spectral triples for which a Fubini formula
holds true. The condition is natural and related to heat semigroup asymptotics.
We provide examples of spectral triples for which the Fubini formula fails.


title: Direct image of parabolic line bundles

abstract:
  Given a vector bundle $E$ on an irreducible projective variety $X$ we give a
necessary and sufficient criterion for $E$ to be a direct image of a line
bundle under an \'etale morphism. The criterion in question is the existence of
a Cartan subalgebra bundle of the endomorphism bundle $\text{End}(E)$. As a
corollary, a criterion is obtained for $E$ to be the direct image of the
structure sheaf under an \'etale morphism. The direct image of a parabolic line
bundle under any ramified covering map has a natural parabolic structure. Given
a parabolic vector bundle, we give a similar criterion for it to be a direct
image of a parabolic line bundle under a ramified covering map.


title:
A globally convergent numerical method for a 3D coefficient inverse
  problem with a single measurement of multi-frequency data

abstract:
  The goal of this paper is to reconstruct spatially distributed dielectric
constants from complex-valued scattered wave field by solving a 3D coefficient
inverse problem for the Helmholtz equation at multi-frequencies. The data are
generated by only a single direction of the incident plane wave. To solve this
inverse problem, a globally convergent algorithm is analytically developed. We
prove that this algorithm provides a good approximation for the exact
coefficient without any \textit{a priori} knowledge of any point in a small
neighborhood of that coefficient. This is the main advantage of our method,
compared with classical approaches using optimization schemes. Numerical
results are presented for both computationally simulated data and experimental
data. Potential applications of this problem are in detection and
identification of explosive-like targets.


title:
Existence results for the fractional Q-curvature problem on three
  dimensional CR sphere

abstract:
  In this paper the fractional Q-curvature problem on three dimensional CR
sphere is considered. By using the critical points theory at infinity, an
existence result is obtained.


title: Precoding under Instantaneous Per-Antenna Peak Power Constraint

abstract:
  We consider a multi-user (MU) multiple-input-single-output (MISO) downlink
system with M single-antenna users and N transmit antennas with a nonlinear
power amplifier (PA) at each antenna. Instead of emitting constant envelope
(CE) signals from the antennas to have highly power efficient PAs, we relax the
CE constraint and allow the transmit signals to have instantaneous power less
than or equal to the available power at each PA. The PA power efficiency
decreases but simulation results show that the same performance in terms of
bit-error-ratio (BER) can be achieved with less transmitted power and less PA
power consumption. We propose a linear and a nonlinear precoder design to
mitigate the multi-user interference (MUI) under the constraint of a maximal
instantaneous per-antenna peak power.


title:
Globular Clusters As Tracers of Fine Structure in the Dramatic Shell
  Galaxy NGC 474

abstract:
  Globular clusters (GCs) are some of the most visible tracers of the merging
and accretion history of galaxy halos. Metal-poor GCs, in particular, are
thought to arrive in massive galaxies largely through dry, minor merging
events, but it is rare to see a direct connection between GCs and visible
stellar streams. NGC 474 is a post-merger early-type galaxy with dramatic fine
structures made of concentric shells and radial streams that have been more
clearly revealed by deep imaging. We present a study of GCs in NGC 474 to
better establish the relationship between merger-induced fine structure and the
GC system. We find that many GCs are superimposed on visible streams and
shells, and about 35% of GCs outside $3R_{\rm e,galaxy}$ are located in regions
of fine structure. The spatial correlation between the GCs and fine structure
is significant at the 99.9% level, showing that this correlation is not
coincidental. The colors of the GCs on the fine structures are mostly blue, and
we also find an intermediate-color population that is dominant in the central
region, and which will likely passively evolve to have colors consistent with a
traditional metal-rich GC population. The association of the blue GCs with fine
structures is direct confirmation that many metal-poor GCs are accreted onto
massive galaxy halos through merging events, and that progenitors of these
mergers are sub-L* galaxies.


title: Trigonometric Interpolation and Quadrature in Perturbed Points

abstract:
  The trigonometric interpolants to a periodic function $f$ in equispaced
points converge if $f$ is Dini-continuous, and the associated quadrature
formula, the trapezoidal rule, converges if $f$ is continuous. What if the
points are perturbed? With equispaced grid spacing $h$, let each point be
perturbed by an arbitrary amount $\le \alpha h$, where $\alpha\in [\kern .5pt
0,1/2)$ is a fixed constant. The Kadec 1/4 theorem of sampling theory suggests
there may be be trouble for $\alpha\ge 1/4$. We show that convergence of both
the interpolants and the quadrature estimates is guaranteed for all
$\alpha<1/2$ if $f$ is twice continuously differentiable, with the convergence
rate depending on the smoothness of $f$. More precisely it is enough for $f$ to
have $4\alpha$ derivatives in a certain sense, and we conjecture that $2\alpha$
derivatives is enough. Connections with the Fej\'er--Kalm\'ar theorem are
discussed.


title: Graphene mechanical oscillators with tunable frequency

abstract:
  Oscillators, which produce continuous periodic signals from direct current
power, are central to modern communications systems, with versatile
applications such as timing references and frequency modulators. However,
conventional oscillators typically consist of macroscopic mechanical resonators
such as quartz crystals, which require excessive off-chip space. Here we report
oscillators built on micron-size, atomically-thin graphene nanomechanical
resonators, whose frequencies can be electrostatically tuned by as much as
14\%. The self-sustaining mechanical motion of the oscillators is generated and
transduced at room temperature by simple electrical circuitry. The prototype
graphene voltage controlled oscillators exhibit frequency stability and
modulation bandwidth sufficient for modulation of radio-frequency carrier
signals. As a demonstration, we employ a graphene oscillator as the active
element for frequency modulated signal generation, and achieve efficient audio
signal transmission.


title:
Constraining the Stellar Populations and Star Formation Histories of
  Blue Compact Dwarf Galaxies with SED Fits

abstract:
  We discuss and test possible evolutionary connections between Blue Compact
Dwarf galaxies (BCDs) and other types of dwarf galaxies. BCDs provide ideal
laboratories to study intense star formation episodes in low mass dwarf
galaxies, and have sometimes been considered a short-lived evolutionary stage
between types of dwarf galaxies. To test these connections, we consider a
sample of BCDs as well as a comparison sample of nearby galaxies from the Local
Volume Legacy (LVL) survey for context. We fit the multi-wavelength spectral
energy distributions (SED, far-ultra-violet to far-infrared) of each galaxy
with a grid of theoretical models to determine their stellar masses and star
formation properties. We compare our results for BCDs with the LVL galaxies to
put BCDs in the context of normal galaxy evolution. The SED fits demonstrate
that the star formation events currently underway in BCDs are at the extreme of
the continuum of normal dwarf galaxies, both in terms of the relative mass
involved and in the relative increase over previous star formation rates.
Today's BCDs are distinctive objects in a state of extreme star formation which
is rapidly transforming them. This study also suggests ways to identify former
BCDs whose star formation episodes have since faded.


title: Generative Adversarial Parallelization

abstract:
  Generative Adversarial Networks have become one of the most studied
frameworks for unsupervised learning due to their intuitive formulation. They
have also been shown to be capable of generating convincing examples in limited
domains, such as low-resolution images. However, they still prove difficult to
train in practice and tend to ignore modes of the data generating distribution.
Quantitatively capturing effects such as mode coverage and more generally the
quality of the generative model still remain elusive. We propose Generative
Adversarial Parallelization, a framework in which many GANs or their variants
are trained simultaneously, exchanging their discriminators. This eliminates
the tight coupling between a generator and discriminator, leading to improved
convergence and improved coverage of modes. We also propose an improved variant
of the recently proposed Generative Adversarial Metric and show how it can
score individual GANs or their collections under the GAP model.


title: Distributed Multi-Task Relationship Learning

abstract:
  Multi-task learning aims to learn multiple tasks jointly by exploiting their
relatedness to improve the generalization performance for each task.
Traditionally, to perform multi-task learning, one needs to centralize data
from all the tasks to a single machine. However, in many real-world
applications, data of different tasks may be geo-distributed over different
local machines. Due to heavy communication caused by transmitting the data and
the issue of data privacy and security, it is impossible to send data of
different task to a master machine to perform multi-task learning. Therefore,
in this paper, we propose a distributed multi-task learning framework that
simultaneously learns predictive models for each task as well as task
relationships between tasks alternatingly in the parameter server paradigm. In
our framework, we first offer a general dual form for a family of regularized
multi-task relationship learning methods. Subsequently, we propose a
communication-efficient primal-dual distributed optimization algorithm to solve
the dual problem by carefully designing local subproblems to make the dual
problem decomposable. Moreover, we provide a theoretical convergence analysis
for the proposed algorithm, which is specific for distributed multi-task
relationship learning. We conduct extensive experiments on both synthetic and
real-world datasets to evaluate our proposed framework in terms of
effectiveness and convergence.


title:
Proceedings of the The First Workshop on Verification and Validation of
  Cyber-Physical Systems

abstract:
  The first International Workshop on Verification and Validation of
Cyber-Physical Systems (V2CPS-16) was held in conjunction with the 12th
International Conference on integration of Formal Methods (iFM 2016) in
Reykjavik, Iceland. The purpose of V2CPS-16 was to bring together researchers
and experts of the fields of formal verification and cyber-physical systems
(CPS) to cover the theme of this workshop, namely a wide spectrum of
verification and validation methods including (but not limited to) control,
simulation, formal methods, etc.
  A CPS is an integration of networked computational and physical processes
with meaningful inter-effects; the former monitors, controls, and affects the
latter, while the latter also impacts the former. CPSs have applications in a
wide-range of systems spanning robotics, transportation, communication,
infrastructure, energy, and manufacturing. Many safety-critical systems such as
chemical processes, medical devices, aircraft flight control, and automotive
systems, are indeed CPS. The advanced capabilities of CPS require complex
software and synthesis algorithms, which are hard to verify. In fact, many
problems in this area are undecidable. Thus, a major step is to find particular
abstractions of such systems which might be algorithmically verifiable
regarding specific properties of such systems, describing the partial/overall
behaviors of CPSs.


title: Towards a second law for Lovelock theories

abstract:
  In classical general relativity described by Einstein-Hilbert gravity, black
holes behave as thermodynamic objects. In particular, the laws of black hole
mechanics can be interpreted as laws of thermodynamics. The first law of black
hole mechanics extends to higher derivative theories via the Noether charge
construction of Wald. One also expects the statement of the second law, which
in Einstein-Hilbert theory owes to Hawking's area theorem, to extend to higher
derivative theories. To argue for this however one needs a notion of entropy
for dynamical black holes, which the Noether charge construction does not
provide. We propose such an entropy function for the family of Lovelock
theories, treating the higher derivative terms as perturbations to the
Einstein-Hilbert theory. Working around a dynamical black hole solution, and
making no assumptions about the amplitude of departure from equilibrium, we
construct a candidate entropy functional valid to all orders in the low energy
effective field theory. This entropy functional satisfies a second law, modulo
a certain subtle boundary term, which deserves further investigation in
non-spherically symmetric situations.


title:
Second-order unbiased naive estimator of mean squared error for EBLUP in
  small-area estimation

abstract:
  An empirical best linear unbiased prediction (EBLUP) estimator is utilized
for efficient inference in small-area estimation. To measure its uncertainty,
we need to estimate its mean squared error (MSE) since the true MSE cannot
generally be derived in a closed form. The "naive MSE estimator", one of the
estimators available for small-area inference, is unlikely to be chosen, since
it does not achieve the desired asymptotic property, namely second-order
unbiasedness, although it maintains strict positivity and tractability.
Therefore, users tend to choose the second-order unbiased MSE estimator. In
this paper, we seek a new adjusted maximum-likelihood method to obtain a naive
MSE estimator that achieves the required asymptotic property. To obtain the
result, we also reveal the relationship between the general adjusted
maximum-likelihood method for the model variance parameter and the general
functional form of the second-order unbiased, and strictly positive, MSE
estimator. We also compare the performance of the new method with that of the
existing naive estimator through a Monte Carlo simulation study. The results
show that the new method remedies the underestimation associated with the
existing naive estimator.


title:
Ground-state thermodynamic quantities of homogeneous spin-$1/2$ fermions
  from the BCS region to the unitarity limit

abstract:
  We experimentally determined various thermodynamic quantities of interacting
two-component fermions at the zero-temperature limit from the
Bardeen-Cooper-Schrieffer (BCS) region to the unitarity limit. The obtained
results are very accurate in the sense that the systematic error is within 4%
around the unitarity limit. Using this advantage, we can compare our data with
various many-body theories. We found that an extended ${\it T}$-matrix
approximation, which is a strong-coupling theory involving fluctuations in the
Cooper channel, well reproduces our experimental results. We also found that
the superfluid order parameter ${\it \Delta}$ calculated by solving the
ordinary BCS gap equation with the chemical potential of interacting fermions
is close to the binding energy of the paired fermions directly observed in a
spectroscopic experiment and that obtained using a quantum Monte Carlo method.
Since understanding the strong-coupling properties of a superfluid Fermi gas in
the BCS-BEC (Bose-Einstein condensation) crossover region is a crucial issue in
condensed matter physics and nuclear physics, the results of the present study
are expected to be useful in the further development of these fields.


title:
Intrinsic Phonon Bands in High-Quality Monolayer T' Molybdenum
  Ditelluride

abstract:
  The topologically nontrivial and chemically functional distorted octahedral
(T') transition metal dichalcogenides (TMDCs) are a type of layered semimetal
that has attracted significant recent attention. However, the properties of
monolayer (1L) T'-TMDC, a fundamental unit of the system, is still largely
unknown due to rapid sample degradation in air. Here we report that
well-protected 1L CVD T'-MoTe2 exhibits sharp and robust intrinsic Raman bands,
with intensities about one order of magnitude stronger than those from bulk
T'-MoTe2. The high-quality samples enabled us to reveal the set of all nine
even-parity zone-center optical phonons, providing reliable fingerprints for
the previously elusive crystal. By performing light polarization and crystal
orientation resolved scattering analysis, we can effectively distinguish the
intrinsic modes from Te-metalloid-like modes A (~122 cm-1) and B (~141 cm-1)
which are related to the sample degradation. Our studies offer a powerful
non-destructive method for assessing sample quality and for monitoring sample
degradation in situ, representing a solid advance in understanding the
fundamental properties of 1L-T'-TMDCs.


title: Adaptive DCTNet for Audio Signal Classification

abstract:
  In this paper, we investigate DCTNet for audio signal classification. Its
output feature is related to Cohen's class of time-frequency distributions. We
introduce the use of adaptive DCTNet (A-DCTNet) for audio signals feature
extraction. The A-DCTNet applies the idea of constant-Q transform, with its
center frequencies of filterbanks geometrically spaced. The A-DCTNet is
adaptive to different acoustic scales, and it can better capture low frequency
acoustic information that is sensitive to human audio perception than features
such as Mel-frequency spectral coefficients (MFSC). We use features extracted
by the A-DCTNet as input for classifiers. Experimental results show that the
A-DCTNet and Recurrent Neural Networks (RNN) achieve state-of-the-art
performance in bird song classification rate, and improve artist identification
accuracy in music data. They demonstrate A-DCTNet's applicability to signal
processing problems.


title: Faster and Simpler Algorithm for Optimal Strategies of Blotto Game

abstract:
  In the Colonel Blotto game, which was initially introduced by Borel in 1921,
two colonels simultaneously distribute their troops across different
battlefields. The winner of each battlefield is determined independently by a
winner-take-all rule. The ultimate payoff of each colonel is the number of
battlefields he wins. This game is commonly used for analyzing a wide range of
applications such as the U.S presidential election, innovative technology
competitions, advertisements, etc. There have been persistent efforts for
finding the optimal strategies for the Colonel Blotto game. After almost a
century Ahmadinejad, Dehghani, Hajiaghayi, Lucier, Mahini, and Seddighin
provided a poly-time algorithm for finding the optimal strategies. They first
model the problem by a Linear Program (LP) and use Ellipsoid method to solve
it. However, despite the theoretical importance of their algorithm, it is
highly impractical. In general, even Simplex method (despite its exponential
running-time) performs better than Ellipsoid method in practice. In this paper,
we provide the first polynomial-size LP formulation of the optimal strategies
for the Colonel Blotto game. We use linear extension techniques. Roughly
speaking, we project the strategy space polytope to a higher dimensional space,
which results in a lower number of facets for the polytope. We use this
polynomial-size LP to provide a novel, simpler and significantly faster
algorithm for finding the optimal strategies for the Colonel Blotto game. We
further show this representation is asymptotically tight in terms of the number
of constraints. We also extend our approach to multi-dimensional Colonel Blotto
games, and implement our algorithm to observe interesting properties of Colonel
Blotto; for example, we observe the behavior of players in the discrete model
is very similar to the previously studied continuous model.


title:
Optimization and Analysis of Probabilistic Caching in $N$-tier
  Heterogeneous Networks

abstract:
  In this paper, we study the probabilistic caching for an $N$-tier wireless
heterogeneous network (HetNet) using stochastic geometry. A general and
tractable expression of the successful delivery probability (SDP) is first
derived. We then optimize the caching probabilities for maximizing the SDP in
the high signal-to-noise ratio (SNR) regime. The problem is proved to be convex
and solved efficiently. We next establish an interesting connection between
$N$-tier HetNets and single-tier networks. Unlike the single-tier network where
the optimal performance only depends on the cache size, the optimal performance
of $N$-tier HetNets depends also on the BS densities. The performance upper
bound is, however, determined by an equivalent single-tier network. We further
show that with uniform caching probabilities regardless of content
popularities, to achieve a target SDP, the BS density of a tier can be reduced
by increasing the cache size of the tier when the cache size is larger than a
threshold; otherwise the BS density and BS cache size can be increased
simultaneously. It is also found analytically that the BS density of a tier is
inverse to the BS cache size of the same tier and is linear to BS cache sizes
of other tiers.


title:
Negative Magnetoresistance in Weyl semimetals NbAs and NbP: Intrinsic
  Chiral Anomaly and Extrinsic Effects

abstract:
  Chiral anomaly induced negative magnetoresistance (NMR) has been widely used
as a critical transport evidence on the existence of Weyl fermions in
topological semimetals. In this mini review, we discuss the general observation
of the NMR phenomena in non-centrosymmetric NbP and NbAs. We show that NMR can
be contributed by intrinsic chiral anomaly of Weyl fermions and/or extrinsic
effects, such as superimposition of Hall signals, field-dependent inhomogeneous
current flow in the bulk, i.e. current jetting, and weak localization (WL) of
coexistent trivial carriers. Such WL controlled NMR is heavily dependent on
sample quality, and is characterized by pronounced crossover from positive to
negative MR growth at elevated temperatures, as a result of the competition
between the phase coherence time and the spin-orbital scattering constant of
the bulk trivial pockets. Thus, the correlation of NMR and chiral anomaly needs
to be scrutinized, without the support of other complimentary techniques. Due
to the lifting of spin degeneracy, the spin orientations of Weyl fermions are
either parallel or antiparallel to the momentum, a unique physical property
known as helicity. The conservation of helicity provides strong protection for
the transport of Weyl fermions, which can only be effectively scattered by
magnetic impurities. Chemical doping of magnetic and non-magnetic impurities
are thus more convincing in probing the existence of Weyl fermions than the NMR
method.


title:
Subharmonic Solutions and Minimal Periodic Solutions of First-order
  Hamiltonian Systems with Anisotropic Growth

abstract:
  Using a homologically link theorem in variational theory and iteration
inequalities of Maslov-type index, we show the existence of a sequence of
subharmonic solutions of non-autonomous Hamiltonian systems with the
Hamiltonian functions satisfying some anisotropic growth conditions, i.e., the
Hamiltonian functions may have simultaneously, in different components,
superquadratic, subquadratic and quadratic behaviors. Moreover, we also
consider the minimal period problem of some autonomous Hamiltonian systems with
anisotropic growth.


title:
Minimal $P$-symmetric period problem of first-order autonomous
  Hamiltonian Systems

abstract:
  Let $P\in Sp(2n)$ satisfying $P^{k}=I_{2n}$, we consider the minimal
$P$-symmetric period problem of the autonomous nonlinear Hamiltonian system
  \begin{equation*} \dot x(t) = JH^{\prime}(x(t)). \end{equation*} For some
symplectic matrices $P$, we show that for any $\tau>0$ the above Hamiltonian
system possesses a $k\tau$ periodic solution $x$ with $k\tau$ being its minimal
$P$-symmetric period provided $H$ satisfies the Rabinowitz's conditions on the
minimal period conjecture, together with that $H$ is convex and $H(Px)=H(x)$.


title: Counting Independent Sets in Graphs of Hyperplane Arrangements

abstract:
  In this paper, we count the number of independent sets of a type of graph
$G(\mathcal{A},q)$ associated to some hyperplane arrangement $\mathcal{A}$,
which is a generalization of the construction of graphical arrangements. We
show that when the parameters of $\mathcal{A}$ satisfy certain conditions, the
number of independent sets of the disjoint union
$G(\mathcal{A},q_1)\cup\cdots\cup G(\mathcal{A},q_s)$ depends only on the
coefficients of $\mathcal{A}$ and the total number of vertices $\sum_i q_i$
when $q_i$'s are powers of large enough prime numbers. In addition it is
independent of the coefficients as long as $\mathcal{A}$ is central and the
coefficients are multiplicatively independent.


title:
DizzyRNN: Reparameterizing Recurrent Neural Networks for Norm-Preserving
  Backpropagation

abstract:
  The vanishing and exploding gradient problems are well-studied obstacles that
make it difficult for recurrent neural networks to learn long-term time
dependencies. We propose a reparameterization of standard recurrent neural
networks to update linear transformations in a provably norm-preserving way
through Givens rotations. Additionally, we use the absolute value function as
an element-wise non-linearity to preserve the norm of backpropagated signals
over the entire network. We show that this reparameterization reduces the
number of parameters and maintains the same algorithmic complexity as a
standard recurrent neural network, while outperforming standard recurrent
neural networks with orthogonal initializations and Long Short-Term Memory
networks on the copy problem.


title:
Solution enthalpies of barium cerates co-doped by rare-earth elements
  and indium

abstract:
  The dissolution enthalpies of BaCe0.7Ho0.2In0.1O2.85 and
BaCe0.7Sm0.2In0.1O2.85 were measured by method of solution calorimetry in 1M
hydrochloric acid with adding 0.1 M KI. The obtained data were compared with
earlier measured data on dissolution enthalpies of BaCe0.7Nd0.2In0.1O2.85,
BaCe0.7Gd0.2In0.1O2.85. The dependence of dissolution enthalpies from
lanthanide radius was constructed. As was shown the relationship is not linear.


title:
Proceedings 11th Doctoral Workshop on Mathematical and Engineering
  Methods in Computer Science

abstract:
  MEMICS provides a forum for doctoral students interested in applications of
mathematical and engineering methods in computer science. Besides a rich
technical programme (including invited talks, regular papers, and
presentations), MEMICS also offers friendly social activities and exciting
opportunities for meeting like-minded people. MEMICS submissions traditionally
cover all areas of computer science (such as parallel and distributed
computing, computer networks, modern hardware and its design, non-traditional
computing architectures, information systems and databases, multimedia and
graphics, verification and testing, computer security, as well as all related
areas of theoretical computer science).


title:
Tridiagonal representations of the q-oscillator algebra and Askey-Wilson
  polynomials

abstract:
  A construction is given of the most general representations of the
q-oscillator algebra where both generators are tridiagonal. It is shown to be
connected to the Askey-Wilson polynomials.


title: Construction of Full-Diversity LDPC Lattices for Block-Fading Channels

abstract:
  LDPC lattices were the first family of lattices which have an efficient
decoding algorithm in high dimensions over an AWGN channel. Considering
Construction D' of lattices with one binary LDPC code as underlying code gives
the well known Construction A LDPC lattices or 1-level LDPC lattices.
Block-fading channel (BF) is a useful model for various wireless communication
channels in both indoor and outdoor environments. Frequency-hopping schemes and
orthogonal frequency division multiplexing (OFDM) can conveniently be modelled
as block-fading channels. Applying lattices in this type of channel entails
dividing a lattice point into multiple blocks such that fading is constant
within a block but changes, independently, across blocks. The design of
lattices for BF channels offers a challenging problem, which differs greatly
from its counterparts like AWGN channels. Recently, the original binary
Construction A for lattices, due to Forney, have been generalized to a lattice
construction from totally real and complex multiplication fields. This
generalized Construction A of lattices provides signal space diversity
intrinsically, which is the main requirement for the signal sets designed for
fading channels. In this paper we construct full diversity LDPC lattices for
block-fading channels using Construction A over totally real number fields. We
propose a new iterative decoding method for these family of lattices which has
complexity that grows linearly in the dimension of the lattice. In order to
implement our decoding algorithm, we propose the definition of a parity check
matrix and Tanner graph for full diversity Construction A lattices. We also
prove that the constructed LDPC lattices together with the proposed decoding
method admit diversity order n-1 over an n-block-fading channel.