title: Magnetometer Based On Spin Wave Interferometer

abstract:
  We describe magnetic field sensor based on spin wave interferometer. Its
sensing element consists of a magnetic cross junction with four micro-antennas
fabricated at the edges. Two of these antennas are used for spin wave
excitation and two others antennas are used for the detection of the inductive
voltage produced by the interfering spin waves. Two waves propagating in the
orthogonal arms of the cross may accumulate significantly different phase
shifts depending on the magnitude and the direction of the external magnetic
field. This phenomenon is utilized for magnetic field sensing. The sensitivity
has maximum at the destructive interference condition, where a small change of
the external magnetic field results in a drastic increase of the inductive
voltage as well as the change of the output phase. We report experimental data
obtained on a micrometer scale Y3Fe2(FeO4)3 cross structure. The change of the
inductive voltage near the destructive interference point exceeds 40 dB per 1
Oe. At the same time, the phase of the output exhibit a {\pi}-phase shift
within 1 Oe. The data are collected for three different orientations of the
sensor in magnetic field at room temperature. Taking into account low thermal
noise in ferrite structures, the maximum sensitivity of spin wave magnetometer
may exceed atta Tesla. Other appealing advantages include compactness, fast
data acquisition and wide temperature operating range. The physical limits of
spin wave interferometers are also discussed.


title: Widefield lensless endoscopy with a multicore fiber

abstract:
  We demonstrate pixelation-free real-time widefield endoscopic imaging through
an aperiodic multicore fiber (MCF) without any distal opto-mechanical elements
or proximal scanners. Exploiting the memory effect in MCFs the images in our
system are directly obtained without any post-processing using a static
wavefront correction obtained from a single calibration procedure. Our approach
allows for video-rate 3D widefield imaging of incoherently illuminated objects
with imaging speed not limited by the wavefront shaping device refresh rate.


title:
QCD analysis of light charged Higgs production through polarized top
  quark decay in two various frames

abstract:
  Light and heavy charged Higgs bosons are predicted by many models with an
extended Higgs sector such as the two-Higgs-doublet model (2HDM). Searches for
the charged Higgs bosons have been done by the ATLAS and the CMS experiments at
the Large Hadron Collider (LHC) in proton-proton collision. However, a
definitive search is a program that still has to be carried out so this belongs
to the LHC experiments. The experimental observation of charged Higgs bosons
would indicate physics beyond the Standard Model. In the present work we study
the ${\cal O}(\alpha_s)$ correction to the energy spectrum of the inclusive
bottom-flavored mesons $(X_b)$ in polarized top quark decays into a light
charged Higgs boson ($m_{H^+}<m_t$) and a massless bottom quark followed by the
hadronization process $b\to X_b$ in the 2HDM, i.e. $t(\uparrow)\to H^+b\to
H^+X_b+Jet$. This spin-dependent energy distribution is studied in two
different helicity coordinate systems. This study could be considered as a new
channel to search for the charged Higgs bosons. To present our phenomenological
predictions, we restrict ourselves to the unexcluded regions of the MSSM
$m_{H^+}-\tan\beta$ parameter space determined by the recent results of the CMS
and the ATLAS collaborations.


title: Relativity free of coordinates

abstract:
  The concept of a physical space, which actualizes Euclidean geometry, is not
confined to the statics of solids but extensible to the phenomena where
Newtonian mechanics is valid, defining its concept of time. The laws of
propagation of electromagnetic disturbances modify Newtonian formalism for
sufficiently fast free motions within each spatial domain of its validity for
slow motions and introduce the extended concept of time by uniting those of
Newtonian which can exist in different spatial domains of their validity.
  A boost direction for a pair of physical spaces is that spatial direction in
one of the spaces along which the other space moves. Free motions of point
particles make an instrumentation for identifying the boost direction as well
as events on a straight line along that direction. The concept of a boost
direction secures the physics-based formulation of the basic relativity
effects, which eventually results in the relation between two arbitrary spaces
in terms of their position vectors and time of a given event.
  The obtained transformation rules for the components of the position vector
differ from the vector-like relationship known in the literature because the
latter actually deals with column vectors made of Cartesian coordinates of true
vectors and appears identical to a coordinate transformation referred to as a
boost.
  Within the physics-based approach, the transformation of coordinates implies
specifying coordinate systems in each frame in terms of physical
objects/directions. This yields a logically consistent and physically
meaningful presentation of the coordinate transformations commonly exploited in
the special relativity theory, which makes manifestations of those
transformations evident. Specifically, for a Cartesian coordinate system
subjected to a boost, the coordinate-free technique of reasoning allows one to
evaluate its apparent distortion easily.


title: On a class of Rauzy fractals without the finiteness property

abstract:
  We present some topological and arithmetical aspects of a class of Rauzy
fractals $\mathcal{R}_{a,b}$ related to the polynomials of the form
$P_{a,b}(x)=x^{3}-ax^{2}-bx-1$, where $a$ and $b$ are integers satisfying $-a+1
\leq b \leq -2$. This class has the property that $0$ lies on the boundary of
$\mathcal{R}_{a,b}$. We construct explicit finite automata that recognize the
boundaries of these fractals, which allows to establish the number of neighbors
of $\mathcal{R}_{a,b}$. In particular, we prove that if $2a+3b+4 \leq 0$ then
$\mathcal{R}_{a,b}$ is not homeomorphic to a topological disk. We also show
that the boundary of the set $\mathcal{R}_{3,-2}$ is generated by two infinite
iterated function systems.


title: Marginal and non-commutative deformations via non-abelian T-duality

abstract:
  In this short article we develop recent proposals to relate Yang-Baxter
sigma-models and non-abelian T-duality. We demonstrate explicitly that the
holographic space-times associated to both
(multi-parameter)-$\beta$-deformations and non-commutative deformations of
${\cal N}=4$ super Yang-Mills gauge theory including the RR fluxes can be
obtained via the machinery of non-abelian T-duality in Type II supergravity.


title:
Evaluating the charged background rejection requirement in an experiment
  to measure $\rm BR(K_L \to \pi^0 \nu \bar{\nu})$ at the CERN SPS

abstract:
  Measuring the rate at which the long-lived, neutral kaon decays into a
neutral pion, neutrino, and anti-neutrino allows physicists an opportunity to
test precise predictions made by the Standard Model. Differences between
theoretical predictions and experimental measurements may point to new physics.
Not only does the Standard Model predict a very low probability at
approximately 3 $K_L \to \pi^0 \nu \bar{\nu}$ decays in 100 billion $K_L$
decays, but many of the common decays leave false signals in the detector that
look the same as the true signal. Charged decays have been studied to determine
the required detection efficiency necessary to eliminate them. The conclusion
of these studies is that a reduction by a factor of $1/(3\times10^9)$ will be
required to achieve the 10:1 signal to charged background ratio necessary for
the experiment.


title:
A Stronger Convergence Result on the Proximal Incremental Aggregated
  Gradient Method

abstract:
  We study the convergence rate of the proximal incremental aggregated gradient
(PIAG) method for minimizing the sum of a large number of smooth component
functions (where the sum is strongly convex) and a non-smooth convex function.
At each iteration, the PIAG method moves along an aggregated gradient formed by
incrementally updating gradients of component functions at least once in the
last $K$ iterations and takes a proximal step with respect to the non-smooth
function. We show that the PIAG algorithm attains an iteration complexity that
grows linear in the condition number of the problem and the delay parameter
$K$. This improves upon the previously best known global linear convergence
rate of the PIAG algorithm in the literature which has a quadratic dependence
on $K$.


title:
Equation of state dependence of directed flow in a microscopic transport
  model

abstract:
  We study the sensitivities of the directed flow in Au+Au collisions on the
equation of state (EoS), employing the transport theoretical model JAM. The EoS
is modified by introducing a new collision term in order to control the
pressure of a system by appropriately selecting an azimuthal angle in two-body
collisions according to a given EoS. It is shown that this approach is an
efficient method to modify the EoS in a transport model. The beam energy
dependence of the directed flow of protons is examined with two different EoS,
a first-order phase transition and crossover. It is found that our approach
yields quite similar results as hydrodynamical predictions on the beam energy
dependence of the directed flow; Transport theory predicts a minimum in the
excitation function of the slope of proton directed flow and does indeed yield
negative directed flow, if the EoS with a first-order phase transition is
employed. Our result strongly suggests that the highest sensitivity for the
critical point can be seen in the beam energy range of $4.7\leq\srtNN\leq11.5$
GeV.


title:
EEGNet: A Compact Convolutional Network for EEG-based Brain-Computer
  Interfaces

abstract:
  Brain computer interfaces (BCI) enable direct communication with a computer,
using neural activity as the control signal. This neural signal is generally
chosen from a variety of well-studied electroencephalogram (EEG) signals. For a
given BCI paradigm, feature extractors and classifiers are tailored to the
distinct characteristics of its expected EEG control signal, limiting its
application to that specific signal. Convolutional Neural Networks (CNNs),
which have been used in computer vision and speech recognition, have
successfully been applied to EEG-based BCIs; however, they have mainly been
applied to single BCI paradigms and thus it remains unclear how these
architectures generalize to other paradigms. Here, we ask if we can design a
single CNN architecture to accurately classify EEG signals from different BCI
paradigms, while simultaneously being as compact as possible. In this work we
introduce EEGNet, a compact convolutional network for EEG-based BCIs. We
introduce the use of depthwise and separable convolutions to construct an
EEG-specific model which encapsulates well-known EEG feature extraction
concepts for BCI. We compare EEGNet to current state-of-the-art approaches
across four BCI paradigms: P300 visual-evoked potentials, error-related
negativity responses (ERN), movement-related cortical potentials (MRCP), and
sensory motor rhythms (SMR). We show that EEGNet generalizes across paradigms
better than the reference algorithms when only limited training data is
available. We demonstrate three different approaches to visualize the contents
of a trained EEGNet model to enable interpretation of the learned features. Our
results suggest that EEGNet is robust enough to learn a wide variety of
interpretable features over a range of BCI tasks, suggesting that the observed
performances were not due to artifact or noise sources in the data.


title:
Phases of higher spin black holes: Hawking-Page, transitions between
  black holes and a critical point

abstract:
  We study the thermodynamic phase diagram of three-dimensional
$sl(N;\mathbb{R})$ higher spin black holes. By analyzing the semi-classical
partition function we uncover a rich structure that includes Hawking-Page
transitions to the AdS$_3$ vacuum, first order phase transitions among black
hole states, and a second order critical point. Our analysis is explicit for
$N=4$ but we extrapolate some of our conclusions to arbitrary $N$. In
particular, we argue that even $N$ is stable in the ensemble under
consideration but odd $N$ is not.


title: Metabelian groups with large return probability

abstract:
  We study the return probability of finitely generated metabelian groups. We
give a characterization of metabelian groups whose return probability is
equivalent to $\exp(-n^\frac1{3} )$ in purely algebraic terms, namely the Krull
dimension of the group. Along the way, we give lower bounds on the return
probability for metabelian groups with torsion derived subgroup, according to
the dimension. We also establish a variation of the famous embedding theorem of
Kaloujinine and Krasner for metabelian groups that respects the Krull
dimension.


title: Energy spectra and passive tracer cascades in turbulent flows

abstract:
  We study the influence of the energy spectrum on the extent of the cascade
range of a passive tracer in turbulent flows. The interesting cases are when
there are two different spectra over the potential range of the tracer cascade
(in 2D when the tracer forcing is in the inverse energy cascade range, and in
3D when the Schmidt number Sc is large). The extent of the tracer cascade range
is then limited by the width of the range for the shallower of the two energy
spectra. Nevertheless, we show that in dimension $d=2,3$ the tracer cascade
range extends (up to a logarithm) to $\kappa_{d\text{D}}^{p}$, where
$\kappa_{d\text{D}}$ is the wavenumber beyond which diffusion should dominate
and $p$ is arbitrarily close to 1, provided Sc is larger than a certain power
(depending on $p$) of the Grashof number. We also derive estimates which
suggest that in 2D, for Sc${}\sim1$ a wide tracer cascade can coexist with a
significant inverse energy cascade at Grashof numbers large enough to produce a
turbulent flow.


title:
A fast and spectrally convergent algorithm for rational-order fractional
  integral and differential equations

abstract:
  A fast algorithm (linear in the degrees of freedom) for the solution of
linear variable-coefficient rational-order fractional integral and differential
equations is described. The approach is related to the ultraspherical method
for ordinary differential equations [Olver & Townsend 2013], and involves
constructing two different bases, one for the domain of the operator and one
for the range of the operator. The bases are constructed from direct sums of
suitably weighted ultraspherical or Jacobi polynomial expansions, for which
explicit representations of fractional integrals and derivatives are known, and
are carefully chosen so that the resulting operators are banded or
almost-banded. Geometric convergence is demonstrated for numerous model
problems when the variable coefficients and right-hand side are sufficiently
smooth.


title:
General calculation of the cross section for dark matter annihilations
  into two photons

abstract:
  Assuming that the underlying model satisfies some general requirements such
as renormalizability and CP conservation, we calculate the non-relativistic
one-loop cross section for any self-conjugate dark matter particle annihilating
into two photons. We accomplish this by carefully classifying all possible
one-loop diagrams and, from them, reading off the dark matter interactions with
the particles running in the loop. Our approach is general and leads to the
same results found in the literature for popular dark matter candidates such as
the neutralinos of the MSSM, minimal dark matter, inert Higgs and Kaluza-Klein
dark matter.


title: 4-wave dynamics in kinetic wave turbulence

abstract:
  A general Hamiltonian wave system with quartic resonances is considered, in
the standard kinetic limit of a continuum of weakly interacting dispersive
waves with random phases. The evolution equation for the multimode
characteristic function $Z$ is obtained within an "interaction representation"
and a perturbation expansion in the small nonlinearity parameter. A frequency
renormalization is performed to remove linear terms that do not appear in the
3-wave case. Feynman-Wyld diagrams are used to average over phases, leading to
a first order differential evolution equation for $Z$. A hierarchy of
equations, analogous to the Boltzmann hierarchy for low density gases is
derived, which preserves in time the property of random phases and amplitudes.
This amounts to a general formalism for both the $N$-mode and the 1-mode PDF
equations for 4-wave turbulent systems, suitable for numerical simulations and
for investigating intermittency.


title: The Betelgeuse Project: Constraints from Rotation

abstract:
  In order to constrain the evolutionary state of the red supergiant
Betelgeuse, we have produced a suite of models with ZAMS masses from 15 to 25
Msun in intervals of 1 Msun including the effects of rotation. The models were
computed with the stellar evolutionary code MESA. For non-rotating models we
find results that are similar to other work. It is somewhat difficult to find
models that agree within 1 sigma of the observed values of R, Teff and L, but
modestly easy within 3 sigma uncertainty. Incorporating the nominal observed
rotational velocity, ~15 km/s, yields significantly different, and challenging,
constraints. This velocity constraint is only matched when the models first
approach the base of the red supergiant branch (RSB), having crossed the
Hertzsprung gap, but not yet having ascended the RSB and most violate even
generous error bars on R, Teff and L. Models at the tip of the RSB typically
rotate at only ~0.1 km/s, independent of any reasonable choice of initial
rotation. We discuss the possible uncertainties in our modeling and the
observations, including the distance to Betelgeuse, the rotation velocity, and
model parameters. We summarize various options to account for the rotational
velocity and suggest that one possibility is that Betelgeuse merged with a
companion star of about 1 Msun as it ascended the RSB, in the process producing
the ring structure observed at about 7' away. A past coalescence would
complicate attempts to understand the evolutionary history and future of
Betelgeuse.


title:
Functionality-directed Screening of Pb-free Hybrid Organic-inorganic
  Perovskites with Desired Intrinsic Photovoltaic Functionalities

abstract:
  The material class of hybrid organic-inorganic perovskites has risen rapidly
from a virtually unknown material in photovoltaic applications a short 7 years
ago into a ~20% efficient thin-film solar cell material. As promising as this
class of materials is, however, there are limitations associated with its poor
long-term stability, non-optimal band gap, presence of environmentally-toxic Pb
element, etc. We herein apply a functionality-directed theoretical materials
selection approach as a filter for initial screening of the compounds that
satisfy the desired intrinsic photovoltaic functionalities and might overcome
the above limitations. First-principles calculations are employed to
systemically study thermodynamic stability and photovoltaic-related properties
of hundred of candidate hybrid perovskites. We have identified in this
materials selection process fourteen Ge and Sn-based materials with potential
superior bulk-material-intrinsic photovoltaic performance. A distinct class of
compounds containing NH3COH$^+$ with the organic molecule derived states
intriguingly emerging at band-edges is found. Comparison of various candidate
materials offers insights on how composition variation and microscopic
structural changes affect key photovoltaic relevant properties in this family
of materials.


title: Trajectory analysis of high-harmonic generation from periodic crystals

abstract:
  We theoretically study high-harmonic generation (HHG) from solids driven by
intense laser pulses using a one-dimensional model periodic crystal. By
numerically solving the time-dependent Schr\"{o}dinger equation directly on a
real-space grid, we successfully reproduce experimentally observed unique
features of solid-state HHG such as the linear cutoff-energy scaling and the
sudden transition from a single- to multiple-plateau structure. Based on the
simulation results, we propose a simple model that incorporates
vector-potential-induced intraband displacement, interband tunneling, and
recombination with the valence-band hole. One key parameter is the
valley-to-peak amplitude of the pulse vector potential, which determines the
crystal momentum displacement during the half cycle. When the maximum
peak-to-valley amplitude $A_{\rm peak}$ reaches the half width $\frac{\pi}{a}$
of the Brillouin zone with $a$ being the lattice constant, the HHG spectrum
exhibits a transition from a single- to multiple-plateau structure, and even
further plateaus appear at $A_{\rm peak} = \frac{2\pi}{a}, \frac{3\pi}{a},
\cdots$. The multiple cutoff positions are given as functions of $A_{\rm peak}$
and the second maximum $A_{\rm peak}^{\prime}$, in terms of the energy
difference between different bands. Using our recipe, one can draw electron
trajectories in the momentum space, from which one can deduce, for example, the
time-frequency structure of HHG without elaborate quantum-mechanical
calculations. Finally, we reveal that the cutoff positions depend on not only
the intensity and wavelength of the pulse, but also its duration, in marked
contrast to the gas-phase case. Our model can be viewed as a solid-state and
momentum-space counterpart of the familiar three-step model, highly successful
for gas-phase HHG, and provide a unified basis to understand HHG from
solid-state materials and gaseous media.


title:
Scalable Bayesian Learning of Recurrent Neural Networks for Language
  Modeling

abstract:
  Recurrent neural networks (RNNs) have shown promising performance for
language modeling. However, traditional training of RNNs using back-propagation
through time often suffers from overfitting. One reason for this is that
stochastic optimization (used for large training sets) does not provide good
estimates of model uncertainty. This paper leverages recent advances in
stochastic gradient Markov Chain Monte Carlo (also appropriate for large
training sets) to learn weight uncertainty in RNNs. It yields a principled
Bayesian learning algorithm, adding gradient noise during training (enhancing
exploration of the model-parameter space) and model averaging when testing.
Extensive experiments on various RNN models and across a broad range of
applications demonstrate the superiority of the proposed approach over
stochastic optimization.


title: Automating the Last-Mile for High Performance Dense Linear Algebra

abstract:
  High performance dense linear algebra (DLA) libraries often rely on a general
matrix multiply (Gemm) kernel that is implemented using assembly or with vector
intrinsics. In particular, the real-valued Gemm kernels provide the
overwhelming fraction of performance for the complex-valued Gemm kernels, along
with the entire level-3 BLAS and many of the real and complex LAPACK routines.
Thus,achieving high performance for the Gemm kernel translates into a high
performance linear algebra stack above this kernel. However, it is a monumental
task for a domain expert to manually implement the kernel for every
library-supported architecture. This leads to the belief that the craft of a
Gemm kernel is more dark art than science. It is this premise that drives the
popularity of autotuning with code generation in the domain of DLA.
  This paper, instead, focuses on an analytical approach to code generation of
the Gemm kernel for different architecture, in order to shed light on the
details or voo-doo required for implementing a high performance Gemm kernel. We
distill the implementation of the kernel into an even smaller kernel, an
outer-product, and analytically determine how available SIMD instructions can
be used to compute the outer-product efficiently. We codify this approach into
a system to automatically generate a high performance SIMD implementation of
the Gemm kernel. Experimental results demonstrate that our approach yields
generated kernels with performance that is competitive with kernels implemented
manually or using empirical search.


title: Robotic Grasp Detection using Deep Convolutional Neural Networks

abstract:
  Deep learning has significantly advanced computer vision and natural language
processing. While there have been some successes in robotics using deep
learning, it has not been widely adopted. In this paper, we present a novel
robotic grasp detection system that predicts the best grasping pose of a
parallel-plate robotic gripper for novel objects using the RGB-D image of the
scene. The proposed model uses a deep convolutional neural network to extract
features from the scene and then uses a shallow convolutional neural network to
predict the grasp configuration for the object of interest. Our multi-modal
model achieved an accuracy of 89.21% on the standard Cornell Grasp Dataset and
runs at real-time speeds. This redefines the state-of-the-art for robotic grasp
detection.


title:
A Spatio-Temporal Representation for the Orienteering Problem with
  Time-Varying Profits

abstract:
  We consider an orienteering problem (OP) where an agent needs to visit a
series (possibly a subset) of depots, from which the maximal accumulated
profits are desired within given limited time budget. Different from most
existing works where the profits are assumed to be static, in this work we
investigate a variant that has arbitrary time-dependent profits. Specifically,
the profits to be collected change over time and they follow different (e.g.,
independent) time-varying functions. The problem is of inherent nonlinearity
and difficult to solve by existing methods. To tackle the challenge, we present
a simple and effective framework that incorporates time-variations into the
fundamental planning process. Specifically, we propose a deterministic
spatio-temporal representation where both spatial description and temporal
logic are unified into one routing topology. By employing existing basic
sorting and searching algorithms, the routing solutions can be computed in an
extremely efficient way. The proposed method is easy to implement and extensive
numerical results show that our approach is time efficient and generates
near-optimal solutions.


title:
A unified integral equation scheme for doubly-periodic Laplace and
  Stokes boundary value problems in two dimensions

abstract:
  We present a spectrally-accurate scheme to turn a boundary integral
formulation for an elliptic PDE on a single unit cell geometry into one for the
fully periodic problem. Applications include computing the effective
permeability of composite media (homogenization), and microfluidic chip design.
Our basic idea is to exploit a small least squares solve to apply periodicity
without ever handling periodic Green's functions. We exhibit fast solvers for
the two-dimensional (2D) doubly-periodic Neumann Laplace problem (flow around
insulators), and Stokes non-slip fluid flow problem, that for inclusions with
smooth boundaries achieve 12-digit accuracy, and can handle thousands of
inclusions per unit cell. We split the infinite sum over the lattice of images
into a directly-summed "near" part plus a small number of auxiliary sources
which represent the (smooth) remaining "far" contribution. Applying physical
boundary conditions on the unit cell walls gives an expanded linear system,
which, after a rank-1 or rank-3 correction and a Schur complement, leaves a
well-conditioned square system which can be solved iteratively using fast
multipole acceleration plus a low-rank term. We are rather explicit about the
consistency and nullspaces of both the continuous and discretized problems. The
scheme is simple (no lattice sums, Ewald methods, nor particle meshes are
required), allows adaptivity, and is essentially dimension- and
PDE-independent, so would generalize without fuss to 3D and to other
non-oscillatory elliptic problems such as elastostatics. We incorporate
recently developed spectral quadratures that accurately handle
close-to-touching geometries. We include many numerical examples, and provide a
software implementation.


title: On the Circuit Diameter Conjecture

abstract:
  From the point of view of optimization, a critical issue is relating the
combinatorial diameter of a polyhedron to its number of facets $f$ and
dimension $d$. In the seminal paper of Klee and Walkup [KW67], the Hirsch
conjecture of an upper bound of $f-d$ was shown to be equivalent to several
seemingly simpler statements, and was disproved for unbounded polyhedra through
the construction of a particular 4-dimensional polyhedron $U_4$ with 8 facets.
The Hirsch bound for bounded polyhedra was only recently disproved by Santos.
  We consider analogous properties for a variant of the combinatorial diameter
called the circuit diameter. In this variant, the walks are built from the
circuit directions of the polyhedron, which are the minimal non-trivial
solutions to the system defining the polyhedron.
  We are able to prove that circuit variants of the so-called non-revisiting
conjecture and $d$-step conjecture both imply the circuit analogue of the
Hirsch conjecture. For the equivalences in [KW67], the wedge construction was a
fundamental proof technique. We exhibit why it is not available in the circuit
setting, and what are the implications of losing it as a tool.
  Further, we show the circuit analogue of the non-revisiting conjecture
implies a linear bound on the circuit diameter of all unbounded polyhedra - in
contrast to what is known for the combinatorial diameter. Finally, we give two
proofs of a circuit version of the $4$-step conjecture. These results offer
some hope that the circuit version of the Hirsch conjecture may hold in
general.
  A challenge in the circuit setting is that different realizations of
polyhedra of the same combinatorial structure may have different diameters. We
adapt the notion of simplicity to work with circuits in the form of C-simple
and wedge-simple polyhedra. We show that it suffices to consider such
polyhedra.


title:
Measuring the 2D Baryon Acoustic Oscillation signal of galaxies in
  WiggleZ: Cosmological constraints

abstract:
  We present results from the 2D anisotropic Baryon Acoustic Oscillation (BAO)
signal present in the final dataset from the WiggleZ Dark Energy Survey. We
analyse the WiggleZ data in two ways: firstly using the full shape of the 2D
correlation function and secondly focussing only on the position of the BAO
peak in the reconstructed data set. When fitting for the full shape of the 2D
correlation function we use a multipole expansion to compare with theory. When
we use the reconstructed data we marginalise over the shape and just measure
the position of the BAO peak, analysing the data in wedges separating the
signal along the line of sight from that parallel to the line of sight. We
verify our method with mock data and find the results to be free of bias or
systematic offsets. We also redo the pre-reconstruction angle averaged (1D)
WiggleZ BAO analysis with an improved covariance and present an updated result.
The final results are presented in the form of $\Omega_c h^2$, $H(z)$, and
$D_A(z)$ for three redshift bins with effective redshifts $z = 0.44$, $0.60$,
and $0.73$. Within these bins and methodologies, we recover constraints between
5% and 22% error. Our cosmological constraints are consistent with Flat
$\Lambda$CDM cosmology and agree with results from the Baryon Oscillation
Spectroscopic Survey (BOSS).


title: Crystal nucleation as the ordering of multiple order parameters

abstract:
  Nucleation is an activated process in which the system has to overcome a free
energy barrier in order for a first-order phase transition between the
metastable and the stable phases to take place. In the liquid-to-solid
transition the process occurs between phases of different symmetry, and it is
thus inherently a multi-dimensional process, in which all symmetries are broken
at the transition. In this Focus Article, we consider some recent studies which
highlight the multi-dimensional nature of the nucleation process. Even for a
single-component system, the formation of solid crystals from the metastable
melt involves fluctuations of two (or more) order parameters, often associated
with the decoupling of positional and orientational symmetry breaking. In other
words, we need at least two order parameters to describe the free-energy of a
system including its liquid and crystalline states. This decoupling occurs
naturally for asymmetric particles or directional interactions, focusing here
on the case of water, but we will show that it also affects spherically
symmetric interacting particles, such as the hard-sphere system. We will show
how the treatment of nucleation as a multi-dimensional process has shed new
light on the process of polymorph selection, on the effect of external fields
on the nucleation process, and on glass-forming ability.


title: Longitudinal Stability Study for the FACET-II e+ Damping Ring

abstract:
  This is an initial study of the longitudinal, single-bunch stability in the
proposed FACET-II e+ damping ring. It is preliminary because many vacuum
chamber objects of the ring have not yet been designed.


title:
Generalized Kubo Formulas for the Transport Properties of Incommensurate
  2D Atomic Heterostructures

abstract:
  We give an exact formulation for the transport coefficients of incommensurate
two-dimensional atomic multilayer systems in the tight-binding approximation.
This formulation is based upon the C* algebra framework introduced by
Bellissard and collaborators to study aperiodic solids (disordered crystals,
quasicrystals, and amorphous materials), notably in the presence of magnetic
fields (quantum Hall effect). We also present numerical approximations and test
our methods on a one-dimensional incommensurate bilayer system.


title:
On the density of coprime tuples of the form $(n,\lfloor
  f_1(n)\rfloor,\ldots,\lfloor f_k(n)\rfloor)$, where $f_1,\ldots,f_k$ are
  functions from a Hardy field

abstract:
  Let $k\in\mathbb{N}$ and let $f_1,\ldots,f_k$ belong to a Hardy field. We
prove that under some natural conditions on the $k$-tuple $(f_1,\ldots,f_k)$
the density of the set $$ \big\{n\in \mathbb{N}: \text{gcd}(n,\lfloor
f_1(n)\rfloor,\ldots,\lfloor f_k(n)\rfloor)=1\big\} $$ exists and equals
$\frac{1}{\zeta(k+1)}$, where $\zeta$ is the Riemann zeta function.


title: Rational polynomials of simple type: a combinatorial proof

abstract:
  We determine the Newton trees of the rational polynomials of simple type,
thus filling a gap in the proof of the classification of these polynomials
given by Neumann and Norbury.


title: A Photo-Hadronic Model of the Large Scale Jet of PKS 0637-752

abstract:
  Strong X-ray emission from large scale jets of radio loud quasars still
remains an open problem. Models based on inverse Compton scattering off CMB
photons by relativistically beamed jets have recently been ruled out, since
Fermi LAT observations for 3C 273 and PKS 0637-752 give the upper limit far
below the model prediction. Synchrotron emission from a separate electron
population with multi-hundred TeV energies remains a possibility although its
origin is not well known. We examine a photo-hadronic origin of such high
energy electrons/positrons, assuming that protons are accelerated up to
$10^{19}$ eV and produce electrons/positrons through Bethe-Heitler process and
photo-pion production. These secondary electrons/positrons are injected at
sufficiently high energies and produce X-rays and $\gamma$-rays by synchrotron
radiation without conflicting with the Fermi LAT upper limits. We find that the
resultant spectrum well reproduces the X-ray observations from PKS 0637-752, if
the proton power is at least $10^{49} \text{erg} \, \text{s}^{-1}$, which is
highly super-Eddington. It is noted that the X-ray emission originates
primarily from leptons through Bethe-Heitler process, while leptons from
photo-pion origin lose energy directly through synchrotron emission of
multi-TeV photons rather than cascading. To avoid the overproduction of the
optical flux, optical emission is primarily due to synchrotron emission of
secondary leptons rather than primary electrons, or a mild degree of beaming of
the jet is needed, if it is owing to the primary electrons. Proton synchrotron
luminosity is a few orders of magnitude smaller.


title: Topological Aspects of Quantum Entanglement

abstract:
  Kauffman and Lomonaco explored the idea of understanding quantum entanglement
(the non-local correlation of certain properties of particles) topologically by
viewing unitary entangling operators as braiding operators. In the work of G.
Alagic, M. Jarret, and S. Jordan it is shown that entanglement is a necessary
condition for forming invariants of knots from braid closures via solutions to
the Yang-Baxter Equation. We show that the arguments used by these authors
generalize to essentially the same results for quantum invariant state
summation models of knots. We also given an example of an SU(2) representation
of the three-strand braid group that models the Jones polynomial for closures
of three-strand braids. This invariant is a quantum model for the Jones
polynomial restricted to three strand braids, and it does not involve quantum
entanglement. These relationships between topological braiding and quantum
entanglement can be used as a framework for future work in understanding the
properties of entangling gates in topological quantum computing.The paper ends
with a discussion of the Aravind hypothesis about the direct relationship of
knots and quantum entanglement, and the ER = EPR hypothesis about the
relationship of quantum entanglement with the connectivity of space. We
describe how, given a background space and a quantum tensor network, to
construct a new topological space, that welds the network and the background
space together. This construction embodies the principle that quantum
entanglement and topological connectivity are intimately related.


title:
Quantifying the role of thermal motion in free-space light-atom
  interaction

abstract:
  We demonstrate 17.7(1)% extinction of a weak coherent field by a single atom.
We observe a shift of the resonance frequency and a decrease in interaction
strength with the external field when the atom, initially at 21(1) $\mu$K, is
heated by the recoil of the scattered photons. Comparing to a simple model, we
conclude that the initial temperature reduces the interaction strength by less
than 10%.


title:
A new kernel estimator of hazard ratio and its asymptotic mean squared
  error

abstract:
  The hazard function is a ratio of a density and survival function, and it is
a basic tool of the survival analysis. In this paper we propose a kernel
estimator of the hazard ratio function, which are based on a modification of
\'{C}wik and Mielniczuk's method. We study nonparametric estimators of the
hazard function and compare those estimators by means of asymptotic mean
squared error ($AMSE$). We obtain asymptotic bias and variance of the new
estimator, and compare them with a naive estimator. The asymptotic variance of
the new estimator is always smaller than the naive estimator's, so we also
discuss an improvement of $AMSE$ using Terrell and Scott's bias reduction
method. The new modified estimator ensures the non-negativity, and we
demonstrate the numerical improvement.


title: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields

abstract:
  We present an approach to efficiently detect the 2D pose of multiple people
in an image. The approach uses a nonparametric representation, which we refer
to as Part Affinity Fields (PAFs), to learn to associate body parts with
individuals in the image. The architecture encodes global context, allowing a
greedy bottom-up parsing step that maintains high accuracy while achieving
realtime performance, irrespective of the number of people in the image. The
architecture is designed to jointly learn part locations and their association
via two branches of the same sequential prediction process. Our method placed
first in the inaugural COCO 2016 keypoints challenge, and significantly exceeds
the previous state-of-the-art result on the MPII Multi-Person benchmark, both
in performance and efficiency.


title:
Ground-state isolation and discrete flows in a rationally extended
  quantum harmonic oscillator

abstract:
  Ladder operators for the simplest version of a rationally extended quantum
harmonic oscillator (REQHO) are constructed by applying a Darboux
transformation to the quantum harmonic oscillator system. It is shown that the
physical spectrum of the REQHO carries a direct sum of a trivial and an
infinite-dimensional irreducible representation of the polynomially deformed
bosonized osp(1|2) superalgebra. In correspondence with this the ground state
of the system is isolated from other physical states but can be reached by
ladder operators via non-physical energy eigenstates, which belong to either an
infinite chain of similar eigenstates or to the chains with generalized Jordan
states. We show that the discrete chains of the states generated by ladder
operators and associated with physical energy levels include six basic
generalized Jordan states, in comparison with the two basic Jordan states
entering in analogous discrete chains for the quantum harmonic oscillator.


title: A Search for Kilonovae in the Dark Energy Survey

abstract:
  The coalescence of a binary neutron star (BNS) pair is expected to produce
gravitational waves (GW) and electromagnetic (EM) radiation, both of which may
be detectable with currently available instruments. We describe a search for a
theoretically predicted r-process optical transient from these mergers, dubbed
the kilonova (KN), using griz broadband data from the Dark Energy Survey
Supernova Program (DES-SN). Some models predict KNe to be redder,
shorter-lived, and dimmer than supernovae (SNe), but at present the event rate
of KNe is poorly constrained. We simulate observations of KN and SN light
curves with the Monte-Carlo simulation code SNANA to optimize selection
requirements, determine search efficiency, and predict SN backgrounds. We also
perform an analysis using fake point sources on images to account for anomalous
efficiency losses from difference-imaging on bright low-redshift galaxies. Our
analysis of the first two seasons of DES-SN data results in 0 events, and is
consistent with our prediction of 1.1 background events based on simulations of
SN. Given our simulation prediction, there is a 33 percent chance of finding 0
events in the data. Assuming no underlying galaxy flux, our search sets 90
percent upper limits on the KN volumetric rate of $1.0\times10^7$ Gpc$^{-3}$
yr$^{-1}$ for the dimmest KN model we consider (peak i-band absolute magnitude
$M_i=-11.4$ mag) and $2.4\times10^4$ Gpc$^{-3}$ yr$^{-1}$ for the brightest
($M_i=-16.2$ mag). Accounting for efficiency loss from host galaxy Poisson
noise, these limits are 1.1 times higher; accounting for anomalous subtraction
artifacts on bright galaxies, these limits are ~3 times higher. While previous
KN searches were based on triggered follow-up, this analysis is the first
untriggered optical KN search and informs selection requirements and strategies
for future KN searches and GW follow-up observations.


title: Computational Power of Symmetry-Protected Topological Phases

abstract:
  We consider ground states of quantum spin chains with symmetry-protected
topological (SPT) order as resources for measurement-based quantum computation
(MBQC). We show that, for a wide range of SPT phases, the computational power
of ground states is uniform throughout each phase. This computational power,
defined as the Lie group of executable gates in MBQC, is determined by the same
algebraic information that labels the SPT phase itself. We prove that these Lie
groups always contain a full set of single-qubit gates, thereby affirming the
long-standing conjecture that general SPT phases can serve as computationally
useful phases of matter.


title: Flexion in Abell 2744

abstract:
  We present the first flexion-focused gravitational lensing analysis of the
first of the strong-lensing "cosmic telescope" galaxy clusters, observed as
part of the Hubble Frontier Fields initiative. Using HST observations of Abell
2744 (z = 0.308), we apply a modified Analytic Image Model (AIM) technique to
measure source galaxy flexion and shear values at a final number density of 82
arcmin$^{-2}$. By using flexion data alone we are able to identify the primary
mass structure aligned along the heart of the cluster in addition to a major
substructure peak offset 1.43' from the cluster core. We generate two types of
nonparametric reconstructions: a flexion aperture mass map, which identifies
the central potential and substructure peak with mass signal-to-noise of
3.5$\sigma$ and 2.3$\sigma$ respectively; and a convergence map derived
directly from the smoothed flexion field. For the primary peak we find a mass
of $1.93\times10^{14}\,h^{-1}\,M_{\odot}$ within a 45" (145h$^{-1}$ kpc)
aperture, and for the western substructure we find a mass of
$7.12\times10^{13}\,h^{-1}\,M_{\odot}$ within a 25" (80h$^{-1}$ kpc) aperture.
The associated peak velocity dispersions were determined to be $\sigma_v$ =
1630 km/s and $\sigma_v$ = 766 km/s, respectively, by fitting nonsingular
isothermal sphere profiles to the flexion data. Additionally, we use
simultaneous shear measurements to independently reconstruct the broader
cluster mass structure, and find that it is unable to reproduce the small-scale
structure associated with the flexion reconstructions. Finally, we perform the
same analysis on the Abell 2744 parallel sky field, and find no strong phantom
signals in the noise reconstructions.


title: Optimal Scheduling of Multiple Sensors with Packet Length Constraint

abstract:
  This paper considers the problem of sensory data scheduling of multiple
processes. There are $n$ independent linear time-invariant processes and a
remote estimator monitoring all the processes. Each process is measured by a
sensor, which sends its local state estimate to the remote estimator. The sizes
of the packets are different due to different dimensions of each process, and
thus it may take different lengths of time steps for the sensors to send their
data. Because of bandwidth limitation, only a portion of all the sensors are
allowed to transmit. Our goal is to minimize the average of estimation error
covariance of the whole system at the remote estimator. The problem is
formulated as a Markov decision process (MDP) with average cost over an
infinite time horizon. We prove the existence of a deterministic and stationary
policy for the problem. We also find that the optimal policy has a consistent
behavior and threshold type structure. A numerical example is provided to
illustrate our main results.


title:
Optimal Control with Limited Sensing via Empirical Gramians and
  Piecewise Linear Feedback

abstract:
  This paper is concerned with the design of optimal control for
finite-dimensional control-affine nonlinear dynamical systems. We introduce an
optimal control problem that specifically optimizes nonlinear observability in
addition to ensuring stability of the closed loop system. A recursive algorithm
is then proposed to obtain an optimal state feedback controller to maximize the
resulting non-quadratic cost functional. The main contribution of the paper is
presenting a control synthesis procedure that provides closed loop asymptotic
stability, on one hand, and empirical observability of the system, as a
transient performance criteria, on the other.


title:
Algorithms based on DQM with new sets of base functions for solving
  parabolic partial differential equations in $(2+1)$ dimension

abstract:
  This paper deals with the numerical computations of two space dimensional
time dependent parabolic partial differential equations by adopting adopting an
optimal five stage fourth-order strong stability preserving Runge Kutta
(SSP-RK54) scheme for time discretization, and three methods of differential
quadrature with different sets of modified B-splines as base functions, for
space discretization: namely i) mECDQM: (DQM with modified extended cubic
B-splines); ii) mExp-DQM: DQM with modified exponential cubic B-splines, and
iii) MTB-DQM: DQM with modified trigonometric cubic B-splines. Specially, we
implement these methods on convection-diffusion equation to convert them into a
system of first order ordinary differential equations,in time which can be
solved using any time integration method, while we prefer SSP-RK54 scheme. All
the three methods are found stable for two space convection-diffusion equation
by employing matrix stability analysis method. The accuracy and validity of the
methods are confirmed by three test problems of two dimensional
convection-diffusion equation, which shows that the proposed approximate
solutions by any of the method are in good agreement with the exact solutions.


title: CMB spectral distortions as solutions to the Boltzmann equations

abstract:
  Distortions to the cosmic microwave background~(CMB) blackbody spectrum are
calculated in the framework of cosmological perturbation theory. The second
order Boltzmann equation is explicitly solved, with the spectral $y$ distortion
and the frequency independent second order temperature perturbation. We also
solve higher order Boltzmann equations systematically and find new type
spectral distortions in the low energy limit of electrons. As an example, we
concretely construct a solution to the cubic order Boltzmann equation and show
that it can be characterized by three parameters: a cubic order temperature
perturbation and two different types of cubic order spectral distortions. A new
linear Sunyaev-Zel'dovich effect whose frequency dependence is different from
the usual $y$ distortion is also discussed in the presence of the
next-to-leading order Kompaneets terms, and we show that higher order spectral
distortions are also generated as a result of the diffusion process in a
framework of the higher order cosmological perturbation theory. We also comment
that generation of the spectral $\mu$ distortion cannot be explained in this
framework even at second order.


title:
Direct measurement of the localized-itinerant transition, hybridization
  and antiferromagnetic transition of 5f electrons

abstract:
  In heavy-fermion compounds, f electrons show both itinerant and localized
behaviour depending on the external conditions, and the hybridization between
localized f electrons and itinerant conduction bands gives rise to their exotic
properties like heavy-fermions, magnetic orders and unconventional
superconductivity. Duo to the risk of handling radioactive actinide materials,
the direct experimental evidence of the band structure evolution across the
localized-itinerant and magnetic transitions for 5f electrons is lacking. Here,
by using angle-resolved photoelectron spectroscopy, we revealed the dual nature
(localized vs itinerant) and the development of two different kinds of heavy
quasi-particle bands of 5f electrons in antiferromagnetic (AFM) USb2. Partially
opened energy gaps were observed on one quasi-particle 5f band cross the AFM
transition around 203 K, indicating that the magnetic orders in USb2 are of
spin density wave (SDW) type similar to Cr. The localized 5f electrons and
itinerant conduction bands hybridize to form another heavy quasi-particle band
at about 120 K, and then open hybridization gaps at even lower temperature. Our
results provide direct spectral demonstration of the localized-itinerant
transition, hybridization and SDW transition of 5f electrons for uranium-based
materials.


title: On ($1$, $\epsilon$)-Restricted Max-Min Fair Allocation Problem

abstract:
  We study the max-min fair allocation problem in which a set of $m$
indivisible items are to be distributed among $n$ agents such that the minimum
utility among all agents is maximized. In the restricted setting, the utility
of each item $j$ on agent $i$ is either $0$ or some non-negative weight $w_j$.
For this setting, Asadpour et al. showed that a certain configuration-LP can be
used to estimate the optimal value within a factor of $4+\delta$, for any
$\delta>0$, which was recently extended by Annamalai et al. to give a
polynomial-time $13$-approximation algorithm for the problem. For hardness
results, Bezakova and Dani showed that it is \NP-hard to approximate the
problem within any ratio smaller than $2$.
  In this paper we consider the $(1,\epsilon)$-restricted max-min fair
allocation problem in which each item $j$ is either heavy $(w_j = 1)$ or light
$(w_j = \epsilon)$, for some parameter $\epsilon \in (0,1)$. We show that the
$(1,\epsilon)$-restricted case is also \NP-hard to approximate within any ratio
smaller than $2$. Hence, this simple special case is still algorithmically
interesting.
  Using the configuration-LP, we are able to estimate the optimal value of the
problem within a factor of $3+\delta$, for any $\delta>0$. Extending this idea,
we also obtain a quasi-polynomial time $(3+4\epsilon)$-approximation algorithm
and a polynomial time $9$-approximation algorithm. Moreover, we show that as
$\epsilon$ tends to $0$, the approximation ratio of our polynomial-time
algorithm approaches $3+2\sqrt{2}\approx 5.83$.


title: Recalling Holistic Information for Semantic Segmentation

abstract:
  Semantic segmentation requires a detailed labeling of image pixels by object
category. Information derived from local image patches is necessary to describe
the detailed shape of individual objects. However, this information is
ambiguous and can result in noisy labels. Global inference of image content can
instead capture the general semantic concepts present. We advocate that
high-recall holistic inference of image concepts provides valuable information
for detailed pixel labeling. We build a two-stream neural network architecture
that facilitates information flow from holistic information to local pixels,
while keeping common image features shared among the low-level layers of both
the holistic analysis and segmentation branches. We empirically evaluate our
network on four standard semantic segmentation datasets. Our network obtains
state-of-the-art performance on PASCAL-Context and NYUDv2, and ablation studies
verify its effectiveness on ADE20K and SIFT-Flow.


title: All Pure Bipartite Entangled States can be Self-Tested

abstract:
  Device-independent self-testing allows to uniquely characterize the quantum
state shared by untrusted parties (up to local isometries) by simply inspecting
their correlations, and requiring only minimal assumptions, namely a
no-signaling constraint on the untrusted parties and the validity of quantum
mechanics. The device-independent approach exploits the fact that certain
non-local correlations can be uniquely achieved by measurements on a particular
quantum state. We can think of these correlations as a "classical fingerprint"
of the self-tested quantum state. In this work, we answer affirmatively the
outstanding open question of whether all pure bipartite entangled states can be
self-tested, by providing explicit self-testing correlations for each.


title:
Parity- and Time Reversal-Violating Pion Nucleon Couplings: Higher Order
  Chiral Matching Relations

abstract:
  Parity- and time reversal-violating (PVTV) pion-nucleon couplings govern the
magnitude of long-range contributions to nucleon and atomic electric dipole
moments. When these couplings arise from chiral symmetry-breaking CP-violating
operators, such as the QCD $\theta$-term or quark chromoelectric dipole
moments, one may relate hadronic matrix elements entering the PVTV couplings to
nucleon and pion mass shifts by exploiting the corresponding chiral
transformation properties at leading order (LO) in the chiral expansion. We
compute the higher-order contributions to the lowest order relations arising
from chiral loops and next-to-next-to leading order (NNLO) operators. We find
that for the QCD $\theta$-term the higher order contributions are analytic in
the quark masses, while for the quark chromoelectric dipole moments and chiral
symmetry-breaking four-quark operators, the matching relations also receive
non-analytic corrections. Numerical estimates suggest that for the isoscalar
PVTV pion-nucleon coupling, the higher order corrections may be as large as
$\sim 20\%$, while for the isovector coupling, more substantial corrections are
possible.


title:
Two families of orthogonal polynomials on the unit circle from basic
  hypergeometric functions

abstract:
  The sequence $\{\,_2\phi_1(q^{-k},q^{b+1};\,q^{-\overline{b}-k+1};\, q,
q^{-\overline{b}+1/2} z)\}_{k \geq 0}$ of basic hypergeometric polynomials is
known to be orthogonal on the unit circle with respect to the weight function
$|(q^{1/2}e^{i\theta};\,q)_{\infty}/(q^{b+1/2}e^{i\theta};\,q)_{\infty}|^2$.
This result, where one must take the parameters $q$ and $b$ to be $0 < q < 1$
and $\Re(b) > -1/2$, is due to P.I. Pastro \cite{Pastro-1985}. In the present
manuscript we deal with the orthogonal polynomials $\hat{\Phi}_{n}(b;.)$ and
$\check{\Phi}_{n}(b;.)$ on the unit circle with respect to the two parametric
families of weight functions $\hat{\omega}(b; \theta) =
|(e^{i\theta};\,q)_{\infty}/(q^{b}e^{i\theta};\,q)_{\infty}|^2$ and
$\check{\omega}(b;\theta) =
|(qe^{i\theta};\,q)_{\infty}/(q^{b}e^{i\theta};\,q)_{\infty}|^2$, where $0 < q
< 1$ and $\Re(b) > 0$. With the use of the basic hypergeometric polynomials $
_2\phi_1(q^{-k},q^{b};\,q^{-\overline{b}-k+1};\, q, q^{-\overline{b}+1} z)$, $k
\geq 0$, which have zeros on the unit circle when $\Re(b) > 0$, simple
expressions for the (monic) polynomials $\hat{\Phi}_{n}(b;.)$ and
$\check{\Phi}_{n}(b;.)$, their norms, the associated Verblunsky coefficients
and also the respective Szeg\H{o} functions are found.


title: Quantum transport in graphene Hall bars: Effects of vacancy disorder

abstract:
  Using the tight-binding model, we investigate the influence of vacancy
disorder on electrical transport in graphene Hall bars in the presence of
quantizing magnetic fields. Disorder, induced by a random distribution of
monovacancies, breaks the graphene sublattice symmetry and creates states
localized on the vacancies. These states are observable in the bend resistance,
as well as in the total DOS. Their energy is proportional to the square root of
the magnetic field, while their localization length is proportional to the
cyclotron radius. At the energies of these localized states, the electron
current flows around the monovacancies and, as we show, it can follow
unexpected paths depending on the particular arrangement of vacancies. We study
how these localized states change with the vacancy concentration, and what are
the effects of including the next nearest neighbor hopping term. Our results
are also compared with the situation when double vacancies are present in the
system. Double vacancies also induce localized states, but their energy and
magnetic field dependences are different. Their localization energy scales
linearly with the magnetic field, and their localization length appears not to
depend on the field strength.


title: Structure and algorithms for (cap, even hole)-free graphs

abstract:
  A graph is even-hole-free if it has no induced even cycles of length 4 or
more. A cap is a cycle of length at least 5 with exactly one chord and that
chord creates a triangle with the cycle. In this paper, we consider (cap, even
hole)-free graphs, and more generally, (cap, 4-hole)-free odd-signable graphs.
We give an explicit construction of these graphs. We prove that every such
graph $G$ has a vertex of degree at most $\frac{3}{2}\omega (G) -1$, and hence
$\chi(G)\leq \frac{3}{2}\omega (G)$, where $\omega(G)$ denotes the size of a
largest clique in $G$ and $\chi(G)$ denotes the chromatic number of $G$. We
give an $O(nm)$ algorithm for $q$-coloring these graphs for fixed $q$ and an
$O(nm)$ algorithm for maximum weight stable set. We also give a polynomial-time
algorithm for minimum coloring.
  Our algorithms are based on our results that triangle-free odd-signable
graphs have treewidth at most 5 and thus have clique-width at most 48, and that
(cap, 4-hole)-free odd-signable graphs $G$ without clique cutsets have
treewidth at most $6\omega(G)-1$ and clique-width at most 48.


title:
Heterogeneous Cellular Networks with Spatio-Temporal Traffic: Delay
  Analysis and Scheduling

abstract:
  Emergence of new types of services has led to various traffic and diverse
delay requirements in fifth generation (5G) wireless networks. Meeting diverse
delay requirements is one of the most critical goals for the design of 5G
wireless networks. Though the delay of point-to-point communications has been
well investigated, the delay of multi-point to multi-point communications has
not been thoroughly studied since it is a complicated function of all links in
the network. In this work, we propose a novel tractable approach to analyze the
delay in the heterogenous cellular networks with spatio-temporal random arrival
of traffic. Specifically, we propose the notion of \emph{delay outage} and
evaluated the effect of different scheduling policies on the delay performance.
Our numerical analysis reveals that offloading policy based on cell range
expansion greatly reduces the macrocell traffic while bringing a small amount
of growth for the picocell traffic. Our results also show that the delay
performance of round-robin scheduling outperforms first in first out scheduling
for heavy traffic, and it is reversed for light traffic. In summary, this
analytical framework provides an understanding and a rule-of-thumb for the
practical deployment of 5G systems where delay requirement is increasingly
becoming a key concern.


title: Solutions for two conjectures on kaleidoscopic edge-colorings

abstract:
  For an $r$-regular graph $G$, we define an edge-coloring $c$ with colors from
$\{1,2,\cdots,$ $k\}$, in such a way that any vertex of $G$ is incident to at
least one edge of each color. The multiset-color $c_m(v)$ of a vertex $v$ is
defined as the ordered tuple $(a_1,a_2,\cdots ,a_k)$, where $a_i \ (1\leq i\leq
k)$ denotes the number of edges with color $i$ which are incident with $v$ in
$G$. Then this edge-coloring $c$ is called a {\it $k$-kaleidoscopic coloring}
of $G$ if every two distinct vertices in $G$ have different multiset-colors and
in this way the graph $G$ is defined as a {\it $k$-kaleidoscope}. In this
paper, we determine the integer $k$ for a complete graph $K_n$ to be a
$k$-kaleidoscope, and hence solve a conjecture in [P. Zhang, A Kaleidoscopic
View of Graph Colorings, Springer, New York, 2016] that for any integers $n$
and $k$ with $n\geq k+3 \geq 6$, the complete graph $K_n$ is a
$k$-kaleidoscope. Then, we construct an $r$-regular $3$-kaleidoscope of order
$\binom{r-1}{2}-1$ for each integer $r\geq 7$, where $r\equiv 3\ (\text{mod}\
4)$, which solves another conjecture in the same book on the maximum order for
$r$-regular $3$-kaleidoscopes.


title: 3D Fully Convolutional Network for Vehicle Detection in Point Cloud

abstract:
  2D fully convolutional network has been recently successfully applied to
object detection from images. In this paper, we extend the fully convolutional
network based detection techniques to 3D and apply it to point cloud data. The
proposed approach is verified on the task of vehicle detection from lidar point
cloud for autonomous driving. Experiments on the KITTI dataset shows a
significant performance improvement over the previous point cloud based
detection approaches.


title: Multiscale Inverse Reinforcement Learning using Diffusion Wavelets

abstract:
  This work presents a multiscale framework to solve an inverse reinforcement
learning (IRL) problem for continuous-time/state stochastic systems. We take
advantage of a diffusion wavelet representation of the associated Markov chain
to abstract the state space. This not only allows for effectively handling the
large (and geometrically complex) decision space but also provides more
interpretable representations of the demonstrated state trajectories and also
of the resulting policy of IRL. In the proposed framework, the problem is
divided into the global and local IRL, where the global approximation of the
optimal value functions are obtained using coarse features and the local
details are quantified using fine local features. An illustrative numerical
example on robot path control in a complex environment is presented to verify
the proposed method.


title:
A classical optical approach to the `non-local Pancharatnam-like phases'
  in Hanbury-Brown-Twiss correlations

abstract:
  We examine a recent proposal to show the presence of nonlocal Pancharatnam
type geometric phases in a quantum mechanical treatment of intensity
interferometry measurements upon inclusion of polarizing elements in the setup.
It is shown that a completely classical statistical treatment of such effects
is adequate for practical purposes. Further we show that the phase angles that
appear in the correlations, while at first sight appearing to resemble
Pancharatnam phases in their mathematical structure, cannot actually be
interpreted in that manner. We also describe a simpler Mach-Zehnder type setup
where similar effects can be observed without use of the paraxial
approximation.


title:
A fast topology optimisation for material- and geometry-independent
  cloaking devices with the BEM and the ${\mathcal H}$-matrix method

abstract:
  We show a design method of cloaking devices which work for target objects
with arbitrary shape and material by a topology optimisation with an accurate
and efficient sensitivity analysis. Most of past researches on topology
optimisation of cloaking devices intend to hide a circle-shaped perfect
electric conductor. In this case, the cloaking effect is highly dependent on
the shape and material of a target object. In this study, we consider to design
a cloaking device which work regardless of the property of target objects by
modifying the definition of the objective function. Also, we developed an
efficient and accurate sensitivity analysis with the boundary element method
and the ${\mathcal H}$-matrix method. We show that the proposed method can
successfully obtain desired cloaking devices with low computational cost.


title: Bulk-edge correspondence and the cobordism invariance of the index

abstract:
  We show that the bulk-edge correspondence for two-dimensional type A and type
AII topological insulators follows directly from the cobordism invariance of
the index.


title: Probing Yang-Lee Edge Singularity by Central Spin Decoherence

abstract:
  Yang-Lee edge singularities are the branch point of the free energy on the
complex plane of physical parameters and were shown to be the simplest
universality class of phase transitions. However, the Yang-Lee edge
singularities have not been regarded as experimentally observable since they
occur at complex physical parameters, which are unphysical. A recent discovery
about the relation between partition functions and probe spin coherence makes
it experimentally feasible to access the complex plane of physical parameters.
However, how to extract the critical point and the critical exponent of
Yang-Lee edge singularities in many-body systems, which occurs only at
thermodynamic limit, has still been elusive. Here we show that the quantum
coherence of a probe spin coupled to finite-size Ising-type spin systems
presents universal scaling behavior near the Yang-Lee edge singularity. The
finite-size scaling behavior of quantum coherence of the probe spin predicts
that one can extract the critical point and the critical exponent of the
Yang-Lee edge singularity of Ising-type spin system in the thermodynamic limit
from the spin coherence measurement of the probe spin coupled to finite
Ising-type spin systems. This finding provides a practical approach to studying
the nature of Yang-Lee edge singularities of many-body systems.


title:
Spontaneous mirror-symmetry breaking induces inverse energy cascade in
  3D active fluids

abstract:
  Classical turbulence theory assumes that energy transport in a 3D turbulent
flow proceeds through a Richardson cascade whereby larger vortices successively
decay into smaller ones. By contrast, an additional inverse cascade
characterized by vortex growth exists in 2D fluids and gases, with profound
implications for meteorological flows and fluid mixing. The possibility of a
helicity-driven inverse cascade in 3D fluids had been rejected in the 1970s
based on equilibrium-thermodynamic arguments. Recently, however, it was
proposed that certain symmetry-breaking processes could potentially trigger a
3D inverse cascade, but no physical system exhibiting this phenomenon has been
identified to date. Here, we present analytical and numerical evidence for the
existence of an inverse energy cascade in an experimentally validated 3D active
fluid model, describing microbial suspension flows that spontaneously break
mirror symmetry. We show analytically that self-organized scale selection, a
generic feature of many biological and engineered nonequilibrium fluids, can
generate parity-violating Beltrami flows. Our simulations further demonstrate
how active scale selection controls mirror-symmetry breaking and the emergence
of a 3D inverse cascade.


title: Lie algebra lattices and strings on T-folds

abstract:
  We study the world-sheet conformal field theories for T-folds systematically
based on the Lie algebra lattices representing the momenta of strings. The
fixed point condition required for the T-duality twist restricts the possible
Lie algebras. When the T-duality acts as a simple chiral reflection, one is
left with the four cases, $A_1, D_{2r}, E_7, E_8$, among the simple
simply-laced algebras. From the corresponding Englert-Neveu lattices, we
construct the modular invariant partition functions for the T-fold CFTs in
bosonic string theory. Similar construction is possible also by using Euclidean
even self-dual lattices. We then apply our formulation to the T-folds in the
$E_8 \times E_8$ heterotic string theory. Incorporating non-trivial phases for
the T-duality twist, we obtain, as simple examples, a class of modular
invariant partition functions parametrized by three integers. Our construction
includes the cases which are not reduced to the free fermion construction.


title:
Gauge cooling for the singular-drift problem in the complex Langevin
  method --- an application to finite density QCD

abstract:
  We study full QCD at finite density and low temperature with light quark mass
using the complex Langevin method. Since the singular drift problem turns out
to be mild on a $4^3 \times 8$ lattice we use, the gauge cooling is performed
only to control the unitarity norm in this exploratory study. We report on our
preliminary data obtained from the complex Langevin simulation up to certain
Langevin time. While the data are still noisy due to lack of statistics, the
onset of the baryon number density seems to occur at larger $\mu$ than half the
pion mass, which is the value for the phase quenched QCD. The validity of our
simulation is tested by the recently proposed criterion based on the
probability distribution of the drift term.


title: Constraining the mass of the Local Group

abstract:
  The mass of the Local Group (LG) is a crucial parameter for galaxy formation
theories. However, its observational determination is challenging - its mass
budget is dominated by dark matter which cannot be directly observed. To meet
this end the posterior distributions of the LG and its massive constituents
have been constructed by means of constrained and random cosmological
simulations. Two priors are assumed - the LCDM model that is used to set up the
simulations and a LG model,which encodes the observational knowledge of the LG
and is used to select LG-like objects from the simulations. The constrained
simulations are designed to reproduce the local cosmography as it is imprinted
onto the Cosmicflows-2 database of velocities. Several prescriptions are used
to define the LG model, focusing in particular on different recent estimates of
the tangential velocity of M31. It is found that (a) different $v_{tan}$
choices affect the peak mass values up to a factor of 2, and change mass ratios
of $M_{M31}$ to $M_{MW}$ by up to 20%; (b) constrained simulations yield more
sharply peaked posterior distributions compared with the random ones; (c) LG
mass estimates are found to be smaller than those found using the timing
argument; (d) preferred MW masses lie in the range of $(0.6 - 0.8)\times10^{12}
M_{\odot}$ whereas (e) $M_{M31}$ is found to vary between $(1.0 -
2.0)\times10^{12} M_{\odot}$, with a strong dependence on the $v_{tan}$ values
used.


title: DroidLeaks: Benchmarking Resource Leak Bugs for Android Applications

abstract:
  Resource leak bugs in Android apps are pervasive and can cause serious
performance degradation and system crashes. In recent years, several resource
leak detection techniques have been proposed to assist Android developers in
correctly managing system resources. Yet, there exist no common bug benchmarks
for effectively and reliably comparing such techniques and quantitatively
evaluating their strengths and weaknesses. This paper describes our initial
contribution towards constructing such a benchmark. To locate real resource
leak bugs, we mined 124,215 code revisions of 34 large-scale open-source
Android apps. We successfully found 298 fixed resource leaks, which cover a
diverse set of resource classes, from 32 out of the 34 apps. To understand the
characteristics of these bugs, we conducted an empirical study, which revealed
the root causes of frequent resource leaks in Android apps and common patterns
of faults made by developers. With our findings, we further implemented a
static checker to detect a common pattern of resource leaks in Android apps.
Experiments showed that the checker can effectively locate real resource leaks
in popular Android apps, confirming the usefulness of our work.


title:
Design of L2_1-type antiferromagnetic semiconducting full-Heusler
  compounds: A first principles DFT+GW study

abstract:
  Antiferromagnetic spintronics is an on-going growing field of research.
Employing both standard density functional theory and the $GW$ approximation
within the framework of the FLAPW method, we study the electronic and magnetic
properties of seven potential antiferromagnetic semiconducting Heusler
compounds with 18 (or 28 when Zn is present) valence electrons per unit cell.
We show that in these compounds G-type antiferromagnetism is the ground state
and that they are all either emiconductors (Cr$_2$ScP, Cr$_2$TiZn, V$_2$ScP,
V$_2$TiSi, and V$_3$Al) or semimetals (Mn$_2$MgZn and Mn$_2$NaAl). The
many-body corrections have a minimal effect on the electronic band structure
with respect to the standard electronic structure calculations.


title:
The LHC searches for heavy neutral Higgs bosons by jet substructure
  analysis

abstract:
  The two-Higgs-doublet model contains extra Higgs bosons, with mass ranges
spanning from several hundred GeV to about 1 TeV. We study the possible
experimental searches for the neutral Higgs bosons of $A$ and $H$ at the future
high-luminosity LHC runs. Besides of the conventional search modes that are
inspired by the supersymmetric models, we discuss two search modes which were
not quite addressed previously. They are the decay modes of $A\to hZ$ and $A/H
\to t \bar t$. Thanks to the technique of tagging boosted objects of SM-like
Higgs bosons and top quarks, we show the improved mass reaches for heavy
neutral Higgs bosons with masses up to $\sim{\cal O}(1)\,\TeV$. The modes
proposed here are complementary to the conventional experimental searches
motivated by the MSSM.


title: High and low mass Axion Haloscopes at UWA

abstract:
  We consider the design of a haloscope experiment (ORGAN) to probe for axions
at 26.6 GHz. The motivation for this search is to perform the first direct test
of a result which claims a possible axion signal at this frequency. There are
many technical issues and optimisations that must be considered in the design
of a high mass axion haloscope. We discuss the current status of the ORGAN
experiment, as well as its future. We also discuss low mass axion haloscopes
employing lumped 3D LC resonators.


title: Survey of Expressivity in Deep Neural Networks

abstract:
  We survey results on neural network expressivity described in "On the
Expressive Power of Deep Neural Networks". The paper motivates and develops
three natural measures of expressiveness, which all display an exponential
dependence on the depth of the network. In fact, all of these measures are
related to a fourth quantity, trajectory length. This quantity grows
exponentially in the depth of the network, and is responsible for the depth
sensitivity observed. These results translate to consequences for networks
during and after training. They suggest that parameters earlier in a network
have greater influence on its expressive power -- in particular, given a layer,
its influence on expressivity is determined by the remaining depth of the
network after that layer. This is verified with experiments on MNIST and
CIFAR-10. We also explore the effect of training on the input-output map, and
find that it trades off between the stability and expressivity.


title:
A New Class of High-Order Methods for Fluid Dynamics Simulations using
  Gaussian Process Modeling

abstract:
  We introduce an entirely new class of high-order methods for computational
fluid dynamics (CFD) based on the Gaussian Process (GP) family of stochastic
functions. Our approach is to use kernel-based GP prediction methods to
interpolate/reconstruct high-order approximations for solving hyperbolic PDEs.
We present the GP approach as a new formulation of high-order
(magneto)hydrodynamic state variable interpolation that furnishes an
alternative to conventional polynomial-based approaches.


title:
Stochastic study of information transmission and population stability in
  a generic bacterial two-component system

abstract:
  Studies on the role of fluctuations in signal propagation and on gene
regulation in monoclonal bacterial population have been extensively pursued
based on the machinery of two-component system. The bacterial two-component
system shows noise utilisation through its inherent plasticity. The
fluctuations propagation takes place using the phosphotransfer module and the
feedback mechanism during gene regulation. To delicately observe the noisy
kinetics the generic cascade needs stochastic investigation at the mRNA and
protein levels. To this end, we propose a theoretical framework to investigate
the noisy signal transduction in a generic two-component system. The model
shows reliability in information transmission through quantification of several
statistical measures. We further extend our analysis to observe the protein
distribution in a population of cells. Through numerical simulation, we
identify the regime of the kinetic parameter set that generates a stability
switch in the steady state distribution of proteins. The results of our
theoretical analysis show key features of the network. The noise permeation and
information propagation in the autoregulation module is feeble. However, the
phosphotransfer module compensates such weakness and plays a significant role
in information transmission. The bimodality due to fluctuations pampers the
emergence of persistence in an isogenic bacterial pool.


title: Online Scaling of NFV Service Chains across Geo-distributed Datacenters

abstract:
  Network Function Virtualization (NFV) is an emerging paradigm that turns
hardware-dependent implementation of network functions (i.e., middleboxes) into
software modules running on virtualized platforms, for significant cost
reduction and ease of management. Such virtual network functions (VNFs)
commonly constitute service chains, to provide network services that traffic
flows need to go through. Efficient deployment of VNFs for network service
provisioning is key to realize the NFV goals. Existing efforts on VNF placement
mostly deal with offline or one-time placement, ignoring the fundamental,
dynamic deployment and scaling need of VNFs to handle practical time-varying
traffic volumes. This work investigates dynamic placement of VNF service chains
across geo-distributed datacenters to serve flows between dispersed source and
destination pairs, for operational cost minimization of the service chain
provider over the entire system span. An efficient online algorithm is
proposed, which consists of two main components: (1) A regularization-based
approach from online learning literature to convert the offline optimal
deployment problem into a sequence of one-shot regularized problems, each to be
efficiently solved in one time slot; (2) An online dependent rounding scheme to
derive feasible integer solutions from the optimal fractional solutions of the
one-shot problems, and to guarantee a good competitive ratio of the online
algorithm over the entire time span. We verify our online algorithm with solid
theoretical analysis and trace-driven simulations under realistic settings.


title: On $p$-Dunford integrable functions with values in Banach spaces

abstract:
  Let $(\Omega,\Sigma,\mu)$ be a complete probability space, $X$ a Banach space
and $1\leq p<\infty$. In this paper we discuss several aspects of $p$-Dunford
integrable functions $f:\Omega \to X$. Special attention is paid to the
compactness of the Dunford operator of $f$. We also study the $p$-Bochner
integrability of the composition $u\circ f:\Omega \to Y$, where $u$ is a
$p$-summing operator from $X$ to another Banach space $Y$. Finally, we also
provide some tests of $p$-Dunford integrability by using $w^*$-thick subsets of
$X^*$.


title: Multiple Time Series Ising Model for Financial Market Simulations

abstract:
  In this paper we propose an Ising model which simulates multiple financial
time series. Our model introduces the interaction which couples to spins of
other systems. Simulations from our model show that time series exhibit the
volatility clustering that is often observed in the real financial markets.
Furthermore we also find non-zero cross correlations between the volatilities
from our model. Thus our model can simulate stock markets where volatilities of
stocks are mutually correlated.


title:
A note on the finite basis and finite rank properties for
  pseudovarieties of semigroups

abstract:
  The finite basis property is often connected with the finite rank property,
which it entails. Many examples have been produced of finite rank varieties
which are not finitely based. In this note, we establish a result on nilpotent
pseudovarieties which yields many similar examples in the realm of
pseudovarieties of semigroups.


title:
Rigid covariance as a natural extension of Painlev\'e--Gullstrand
  space-times: gravitational waves

abstract:
  The group of rigid motions is considered to guide the search for a natural
system of space-time coordinates in General Relativity. This search leads us to
a natural extension of the space-times that support Painlev\'{e}--Gullstrand
synchronization. As an interesting example, here we describe a system of rigid
coordinates for the cross mode of gravitational linear plane waves.


title: Deep Joint Face Hallucination and Recognition

abstract:
  Deep models have achieved impressive performance for face hallucination
tasks. However, we observe that directly feeding the hallucinated facial images
into recog- nition models can even degrade the recognition performance despite
the much better visualization quality. In this paper, we address this problem
by jointly learning a deep model for two tasks, i.e. face hallucination and
recognition. In particular, we design an end-to-end deep convolution network
with hallucination sub-network cascaded by recognition sub-network. The
recognition sub- network are responsible for producing discriminative feature
representations using the hallucinated images as inputs generated by
hallucination sub-network. During training, we feed LR facial images into the
network and optimize the parameters by minimizing two loss items, i.e. 1) face
hallucination loss measured by the pixel wise difference between the ground
truth HR images and network-generated images; and 2) verification loss which is
measured by the classification error and intra-class distance. We extensively
evaluate our method on LFW and YTF datasets. The experimental results show that
our method can achieve recognition accuracy 97.95% on 4x down-sampled LFW
testing set, outperforming the accuracy 96.35% of conventional face recognition
model. And on the more challenging YTF dataset, we achieve recognition accuracy
90.65%, a margin over the recognition accuracy 89.45% obtained by conventional
face recognition model on the 4x down-sampled version.


title:
Twisted 3D holograms for self-referencing interferometers in metrology
  and imaging

abstract:
  The interference between radiation fields superposed appropriately contains
all available information about the source. This will be recapitulated for
coherent and incoherent fields. We will further analyze a new kind of twisted
3D interferometer which allows us to generate interferograms with high
information content. The physical basis for these devices is the geometric
parallel transport of electric fields along a 3D path in space. This concept
enables us to build very compact 3D interferometers.


title: Sign problem in finite density lattice QCD

abstract:
  The canonical approach, which was developed for solving the sign problem, may
suffer from a new type of sign problem. In the canonical approach, the grand
partition function is written as a fugacity expansion: $Z_G(\mu,T) = \sum_n
Z_C(n,T) \xi^n$, where $\xi=\exp(\mu/T)$ is the fugacity, and $Z_C(n,T)$ are
given as averages over a Monte Carlo update, $\langle z_n\rangle$. We show that
the complex phase of $z_n$ is proportional to $n$ at each Monte Carlo step.
Although $\langle z_n\rangle$ take real positive values, the values of $z_n$
fluctuate rapidly when $n$ is large, especially in the confinement phase, which
gives a limit on $n$. We discuss possible remedies for this problem.


title:
Application of single walled carbon nanotubes for heating agent in
  photothermal therapy

abstract:
  We present the theoretical investigation of the single walled carbon
nanotubes (SWNTs) as the heating agent of photothermal therapy. In our model,
the SWNT is modeled by rigid tube surrounded by cancer cells. In this model, we
neglect the angle dependence of temperature and assume that the length of SWNT
is much longer than the radius of tube. We calculated the temperature rise of
the SWNT and its surrounding cancer cells during the laser heating by solving
one-dimensional heat conduction equation in steady state condition. We found
that the maximum temperature is located at the interface between SWNT and
cancer cells. This maximum temperature is proportional to the square of SWNTs
diameter and diameter of SWNTs depends on their chirality. These results extend
our understanding of the temperature distribution in SWNT during the laser
heating process and provide the suggested specification of SWNT for the
improvement the photothermal therapy in the future.


title:
Metallicity Calibration and Photometric Parallax Estimation: II. SDSS
  photometry

abstract:
  We used the updated [Fe/H] abundances of 168 F-G type dwarfs and calibrated
them to a third order polynomial in terms of reduced ultraviolet excess,
$\delta_{0.41}$ defined with $ugr$ data in the SDSS. We estimated the $M_g$
absolute magnitudes for the same stars via the re-reduced Hipparcos parallaxes
and calibrated the absolute magnitude offsets, $\Delta M_g$, relative to the
intrinsic sequence of Hyades to a third order polynomial in terms of
$\delta_{0.41}$. The ranges of the calibrations are $-2<$[Fe/H]$\leq$0.3 dex
and $4<M_g\leq6$ mag. The mean of the residuals and the corresponding standard
deviation for the metallicity calibration are 0 and 0.137 mag; while, for the
absolute magnitude calibration they are 0 and 0.179 mag, respectively. We
applied our procedures to 23,414 dwarf stars in the Galactic field with the
Galactic coordinates $85^{\circ}\leq b\leq90^{\circ}$, $0^{\circ}\leq
l\leq360^{\circ}$ and size 78 deg$^{2}$. We estimated absolute magnitude $M_g$
dependent vertical metallicity gradients as a function of vertical distance
$Z$. The gradients are deep in the range of $0<Z\leq5$ kpc, while they are very
small positive numbers beyond $Z=5$ kpc. All dwarfs with $5<M_g\leq6$ mag are
thin-disc stars and their distribution shows a mode at $(g-r)_0\approx 0.38$
mag, while the absolute magnitudes $4<M_g\leq5$ are dominated by thick disc and
halo stars, i.e. the apparently bright ones ($g_0\leq18$ mag) are thick-disc
stars with a mode at $(g-r)_0\sim0.38$ mag, while the halo population is
significant in the faint stars ($g_0>18$ mag).


title:
User Personalized Satisfaction Prediction via Multiple Instance Deep
  Learning

abstract:
  Community based question answering services have arisen as a popular
knowledge sharing pattern for netizens. With abundant interactions among users,
individuals are capable of obtaining satisfactory information. However, it is
not effective for users to attain answers within minutes. Users have to check
the progress over time until the satisfying answers submitted. We address this
problem as a user personalized satisfaction prediction task. Existing methods
usually exploit manual feature selection. It is not desirable as it requires
careful design and is labor intensive. In this paper, we settle this issue by
developing a new multiple instance deep learning framework. Specifically, in
our settings, each question follows a weakly supervised learning multiple
instance learning assumption, where its obtained answers can be regarded as
instance sets and we define the question resolved with at least one
satisfactory answer. We thus design an efficient framework exploiting multiple
instance learning property with deep learning to model the question answer
pairs. Extensive experiments on large scale datasets from Stack Exchange
demonstrate the feasibility of our proposed framework in predicting askers
personalized satisfaction. Our framework can be extended to numerous
applications such as UI satisfaction Prediction, multi armed bandit problem,
expert finding and so on.


title: Geometric deep learning: going beyond Euclidean data

abstract:
  Many scientific fields study data with an underlying structure that is a
non-Euclidean space. Some examples include social networks in computational
social sciences, sensor networks in communications, functional networks in
brain imaging, regulatory networks in genetics, and meshed surfaces in computer
graphics. In many applications, such geometric data are large and complex (in
the case of social networks, on the scale of billions), and are natural targets
for machine learning techniques. In particular, we would like to use deep
neural networks, which have recently proven to be powerful tools for a broad
range of problems from computer vision, natural language processing, and audio
analysis. However, these tools have been most successful on data with an
underlying Euclidean or grid-like structure, and in cases where the invariances
of these structures are built into networks used to model them. Geometric deep
learning is an umbrella term for emerging techniques attempting to generalize
(structured) deep neural models to non-Euclidean domains such as graphs and
manifolds. The purpose of this paper is to overview different examples of
geometric deep learning problems and present available solutions, key
difficulties, applications, and future research directions in this nascent
field.


title:
On the Feasibility of Attribute-Based Encryption on Internet of Things
  Devices

abstract:
  Attribute-Based Encryption (ABE) could be an effective cryptographic tool for
the secure management of Internet-of-Things (IoT) devices, but its feasibility
in the IoT has been under-investigated thus far. This article explores such
feasibility for well-known IoT platforms, namely, Intel Galileo Gen 2, Intel
Edison, Raspberry Pi 1 Model B, and Raspberry Pi Zero, and concludes that
adopting ABE in the IoT is indeed feasible.


title: Metamaterials with index ellipsoids at arbitrary k-points

abstract:
  We propose and investigate a new type of metamaterial structure composing of
several interpenetrating wire meshes. Calculated band structures show that they
exhibit index ellipsoids locating at nonzero k-point in long wavelength limit.
We can comprehend these quasistatic modes by Poison's equation and find these
modes do not rely on the detailed geometry of the wires but the connectivities
of the wires. We can engineer the locations of index ellipsoid by designing the
connectivities of the wire meshes.


title:
Stability and Hopf bifurcation analysis for the
  hypothalamic-pituitary-adrenal axis model with memory

abstract:
  This paper generalizes the existing minimal model of the
hypothalamic-pituitary-adrenal (HPA) axis in a realistic way, by including
memory terms: distributed time delays, on one hand and fractional-order
derivatives, on the other hand. The existence of a unique equilibrium point of
the mathematical models is proved and a local stability analysis is undertaken
for the system with general distributed delays. A thorough bifurcation analysis
for the distributed delay model with several types of delay kernels is
provided. Numerical simulations are carried out for the distributed delays
models and for the fractional-order model with discrete delays, which
substantiate the theoretical findings. It is shown that these models are able
to capture the vital mechanisms of the HPA system.


title:
Quantum Emulation of Molecular Force Fields: A Blueprint for a
  Superconducting Architecture

abstract:
  In this work, we propose a flexible architecture of microwave resonators with
tunable couplings to perform quantum simulations of problems from the field of
molecular chemistry. The architecture builds on the experience of the D-Wave
design, working with nearly harmonic circuits instead of qubits. This
architecture, or modifications of it, can be used to emulate molecular
processes such as vibronic transitions. Furthermore, we discuss several aspects
of these emulations, such as dynamical ranges of the physical parameters,
quenching times necessary for diabaticity, and, finally, the possibility of
implementing anharmonic corrections to the force fields by exploiting certain
nonlinear features of superconducting devices.


title: Complex Effective Action and Schwinger Effect

abstract:
  Spontaneous pair production from background fields or spacetimes is one of
the most prominent phenomena predicted by quantum field theory. The Schwinger
mechanism of production of charged pairs by a strong electric field and the
Hawking radiation of all species of particles from a black hole are the
consequence of nonperturbative quantum effects. In this review article, the
vacuum structure and pair production is reviewed in the in-out formalism, which
provides a consistent framework for quantum field theory in the sense that the
complex action explains not only the vacuum persistence but also pair
production. The current technology of intense lasers is still lower by a few
order than the Schwinger limit for electron-positron pair production, while
magnetic fields of magnetars on the surface are higher than the Schwinger limit
and even higher at the core. On the other hand, the zero effective mass of
electron and hole in graphene and Dirac or Weyl semimetals will open a window
for experimental test of quantum electrodynamics (QED) phenomena in strong
fields.


title:
Double-quantitative $\gamma^{\ast}-$fuzzy coverings approximation
  operators

abstract:
  In digital-based information boom, the fuzzy covering rough set model is an
important mathematical tool for artificial intelligence, and how to build the
bridge between the fuzzy covering rough set theory and Pawlak's model is
becoming a hot research topic. In this paper, we first present the
$\gamma-$fuzzy covering based probabilistic and grade approximation operators
and double-quantitative approximation operators. We also study the
relationships among the three types of $\gamma-$fuzzy covering based
approximation operators. Second, we propose the $\gamma^{\ast}-$fuzzy coverings
based multi-granulation probabilistic and grade lower and upper approximation
operators and multi-granulation double-quantitative lower and upper
approximation operators. We also investigate the relationships among these
types of $\gamma-$fuzzy coverings based approximation operators. Finally, we
employ several examples to illustrate how to construct the lower and upper
approximations of fuzzy sets with the absolute and relative quantitative
information.


title: Quantum Enhanced Inference in Markov Logic Networks

abstract:
  Markov logic networks (MLNs) reconcile two opposing schools in machine
learning and artificial intelligence: causal networks, which account for
uncertainty extremely well, and first-order logic, which allows for formal
deduction. An MLN is essentially a first-order logic template to generate
Markov networks. Inference in MLNs is probabilistic and it is often performed
by approximate methods such as Markov chain Monte Carlo (MCMC) Gibbs sampling.
An MLN has many regular, symmetric structures that can be exploited at both
first-order level and in the generated Markov network. We analyze the graph
structures that are produced by various lifting methods and investigate the
extent to which quantum protocols can be used to speed up Gibbs sampling with
state preparation and measurement schemes. We review different such approaches,
discuss their advantages, theoretical limitations, and their appeal to
implementations. We find that a straightforward application of a recent result
yields exponential speedup compared to classical heuristics in approximate
probabilistic inference, thereby demonstrating another example where advanced
quantum resources can potentially prove useful in machine learning.