title: Coherent population trapping with polarization modulation

abstract:
  Coherent population trapping (CPT) is extensively studied for future vapor
cell clocks of high frequency stability. In the constructive polarization
modulation CPT scheme, a bichromatic laser field with polarization and phase
synchronously modulated is applied on an atomic medium. A high contrast CPT
signal is observed in this so-called double-modulation configuration, due to
the fact that the atomic population does not leak to the extreme Zeeman states,
and that the two CPT dark states, which are produced successively by the
alternate polarizations, add constructively. Here we experimentally investigate
CPT signal dynamics first in the usual configuration, a single circular
polarization. The double-modulation scheme is then addressed in both cases: one
pulse Rabi interaction and two pulses Ramsey interaction. The impact and the
optimization of the experimental parameters involved in the time sequence are
reviewed. We show that a simple sevenlevel model explains the experimental
observations. The double-modulation scheme yields a high contrast similar to
the one of other high contrast configurations like push-pull optical pumping or
crossed linear polarization scheme, with a setup allowing a higher compactness.
The constructive polarization modulation is attractive for atomic clock, atomic
magnetometer and high precision spectroscopy applications.


title:
Mahler measures of polynomials that are sums of a bounded number of
  monomials

abstract:
  We study Laurent polynomials in any number of variables that are sums of at
most $k$ monomials. We first show that the Mahler measure of such a polynomial
is at least $h/2^{k-2}$, where $h$ is the height of the polynomial. Next,
restricting to such polynomials having integer coefficients, we show that the
set of logarithmic Mahler measures of the elements of this restricted set is a
closed subset of the nonnegative real line, with $0$ being an isolated point of
the set.
  In the final section, we discuss the extent to which such an integer
polynomial of Mahler measure $1$ is determined by its $k$ coefficients.


title: A Generalized Krein-Rutman Theorem

abstract:
  A generalized Krein-Rutman theorem for a strongly positive bounded linear
operator whose spectral radius is larger than essential spectral radius is
established: the spectral radius of the operator is an algebraically simple
eigenvalue with strongly positive eigenvector and other eigenvalues are less
than the spectral radius.


title: Bantay's trace in Unitary Modular Tensor Categories

abstract:
  We give a proof of a formula for the trace of self-braidings (in an arbitrary
channel) in UMTCs which first appeared in the context of rational conformal
field theories (CFTs). The trace is another invariant for UMTCs which depends
only on modular data, and contains the expression of the Frobenius-Schur
indicator as a special case. Furthermore, we discuss some applications of the
trace formula to the realizability problem of modular data and to the
classification of UMTCs.


title:
Nuclear in-medium effects on $\eta$ dynamics in proton-nucleus
  collisions

abstract:
  The dynamics of $\eta$ meson produced in proton-induced nuclear reactions via
the decay of N$^{\ast}(1535)$ has been investigated within the Lanzhou quantum
molecular dynamics transport model (LQMD). The in-medium modifications of the
$\eta$ production in dense nuclear matter are included in the model, in which
an attractive $\eta$-nucleon potential is implemented. The impact of the $\eta$
optical potential on the $\eta$ dynamics is investigated. It is found that the
attractive potential leads to the reduction of high-momentum (kinetic energy)
production from the spectra of momentum distributions and inclusive cross
sections and increasing the reabsorption process by surrounding nucleons.


title:
On the generators of the canonical module of a Hibi ring: a criterion of
  level property and the degrees of generators

abstract:
  In this paper, we study the minimal generating system of the canonical module
of a Hibi ring. Using the results, we state a characterization of a Hibi ring
to be level. We also give a characterization of a Hibi ring to be of type 2.
Further, we show that the degrees of the elements of the minimal generating
system of the canonical module of a Hibi ring form a set of consecutive
integers.


title:
A combined study for turning CO$_2$ and H$_2$O into value-added products
  in a dielectric barrier discharge

abstract:
  A combination of experiments and extensive modelling, including a chemical
kinetics analysis, was performed for a CO$_2$/H$_2$O plasma in a dielectric
barrier discharge. This provides a better understanding of the mechanisms
related to the reactivity of the plasma and of the conversions into value-added
products, such as methanol.


title:
Modeling Fractal Structure of Systems of Cities Using Spatial
  Correlation Function

abstract:
  This paper proposes a new method to analyze the spatial structure of urban
systems using ideas from fractals. Regarding a system of cities as a set of
"particles" distributed randomly on a triangular lattice, we construct a
spatial correlation function of cities. Suppose that the spatial correlation
follows the power law. It can be proved that the correlation exponent is the
second order generalized dimension. The spatial correlation model is applied to
the system of cities in China. The results show that the Chinese urban system
can be described by the correlation dimension ranging from 1.3 to 1.6. The
fractality of self-organized network of cities in both the conventional
geographic space and the "time" space is revealed with the empirical evidence.
The spatial correlation analysis is significant in that it is applicable to
both large and small sizes of samples and can be used to link different fractal
dimensions in urban study, including box dimension and radial dimension.


title:
The Parameterized Complexity of Fixing Number and Vertex
  Individualization in Graphs

abstract:
  In this paper we study the complexity of the following problems:
  Given a colored graph X=(V,E,c), compute a minimum cardinality set S of
vertices such that no nontrivial automorphism of X fixes all vertices in S. A
closely related problem is computing a minimum base S for a permutation group G
on [n] given by generators, i.e., a minimum cardinality subset S of [n] such
that no nontrivial permutation in G fixes all elements of S. Our focus is
mainly on the parameterized complexity of these problems. We show that when
k=|S| is treated as parameter, then both problems are MINI[1]-hard. For the
dual problems, where k=n-|S| is the parameter, we give FPT algorithms.
  A notion closely related to fixing is called individualization.
Individualization combined with the Weisfeiler-Leman procedure is a fundamental
technique in algorithms for Graph Isomorphism. Motivated by the power of
individualization, in the present paper we explore the complexity of
individualization: what is the minimum number of vertices we need to
individualize in a given graph such that color refinement "succeeds" on it.
Here "succeeds" could have different interpretations, and we consider the
following: It could mean the individualized graph becomes: (a) discrete, (b)
amenable, (c) compact, or (d) refinable. In particular, we study the
parameterized versions of these problems where the parameter is the number of
vertices individualized. We show a dichotomy: For graphs with color classes of
size at most 3 these problems can be solved in polynomial time (even in
logspace), while starting from color class size 4 they become W[P]-hard.


title:
Direct probe of anisotropy in atom-molecule collisions via quantum
  scattering resonances

abstract:
  Anisotropy is a fundamental property of particle interactions. It occupies a
central role in cold and ultra-cold molecular processes, where long range
forces have been found to significantly depend on orientation in ultra-cold
polar molecule collisions. Recent experiments have demonstrated the emergence
of quantum phenomena such as scattering resonances in the cold collisions
regime due to quantization of the intermolecular degrees of freedom. Although
these states have been shown to be sensitive to interaction details, the effect
of anisotropy on quantum resonances has eluded experimental observation so far.
Here, we directly measure the anisotropy in atom-molecule interactions via
quantum resonances by changing the quantum state of the internal molecular
rotor. We observe that a quantum scattering resonance at a collision energy of
$k_B$ x 270 mK appears in the Penning ionization of molecular hydrogen with
metastable helium only if the molecule is rotationally excited. We use state of
the art ab initio and multichannel quantum molecular dynamics calculations to
show that the anisotropy contributes to the effective interaction only for
$H_2$ molecules in the first excited rotational state, whereas rotationally
ground state $H_2$ interacts purely isotropically with metastable helium.
Control over the quantum state of the internal molecular rotation allows us to
switch the anisotropy on or off and thus disentangle the isotropic and
anisotropic parts of the interaction. These quantum phenomena provide a
challenging benchmark for even the most advanced theoretical descriptions,
highlighting the advantage of using cold collisions to advance the microscopic
understanding of particle interactions.


title:
Fractal-Based Exponential Distribution of Urban Density and Self-Affine
  Fractal Forms of Cities

abstract:
  Urban population density always follows the exponential distribution and can
be described with Clark's model. Because of this, the spatial distribution of
urban population used to be regarded as non-fractal pattern. However, Clark's
model differs from the exponential function in mathematics because that urban
population is distributed on the fractal support of landform and land-use form.
By using mathematical transform and empirical evidence, we argue that there are
self-affine scaling relations and local power laws behind the exponential
distribution of urban density. The scale parameter of Clark's model indicating
the characteristic radius of cities is not a real constant, but depends on the
urban field we defined. So the exponential model suggests local fractal
structure with two kinds of fractal parameters. The parameters can be used to
characterize urban space filling, spatial correlation, self-affine properties,
and self-organized evolution. The case study of the city of Hangzhou, China, is
employed to verify the theoretical inference. Based on the empirical analysis,
a three-ring model of cities is presented and a city is conceptually divided
into three layers from core to periphery. The scaling region and non-scaling
region appear alternately in the city. This model may be helpful for future
urban studies and city planning.


title: A Note on the Period Enforcer Algorithm for Self-Suspending Tasks

abstract:
  The period enforcer algorithm for self-suspending real-time tasks is a
technique for suppressing the "back-to-back" scheduling penalty associated with
deferred execution. Originally proposed in 1991, the algorithm has attracted
renewed interest in recent years. This note revisits the algorithm in the light
of recent developments in the analysis of self-suspending tasks, carefully
re-examines and explains its underlying assumptions and limitations, and points
out three observations that have not been made in the literature to date: (i)
period enforcement is not strictly superior (compared to the base case without
enforcement) as it can cause deadline misses in self-suspending task sets that
are schedulable without enforcement; (ii) to match the assumptions underlying
the analysis of the period enforcer, a schedulability analysis of
self-suspending tasks subject to period enforcement requires a task set
transformation for which no solution is known in the general case, and which is
subject to exponential time complexity (with current techniques) in the limited
case of a single self-suspending task; and (iii) the period enforcer algorithm
is incompatible with all existing analyses of suspension-based locking
protocols, and can in fact cause ever-increasing suspension times until a
deadline is missed.


title: Low-Rank Sum-of-Squares Representations on Varieties of Minimal Degree

abstract:
  A celebrated result by Hilbert says that every real nonnegative ternary
quartic is a sum of three squares. We show more generally that every
nonnegative quadratic form on a real projective variety $X$ of minimal degree
is a sum of $\dim(X)+1$ squares of linear forms. This strengthens one direction
of a recent result due to Blekherman, Smith, and Velasco. Our upper bound is
the best possible, and it implies the existence of low-rank factorizations of
positive semidefinite bivariate matrix polynomials and representations of
biforms as sums of few squares. We determine the number of equivalence classes
of sum-of-squares representations of general quadratic forms on surfaces of
minimal degree, generalizing the count for ternary quartics by Powers, Reznick,
Scheiderer, and Sottile.


title:
Formation of Selfbound States in a One-Dimensional Nuclear Model -- A
  Renormalization Group based Density Functional Study

abstract:
  In nuclear physics, Density Functional Theory (DFT) provides the basis for
state-of-the art studies of ground-state properties of heavy nuclei. However,
the direct relation of the density functional underlying these calculations and
the microscopic nuclear forces is not yet fully understood. We present a
combination of DFT and Renormalization Group (RG) techniques which allows to
study selfbound many-body systems from microscopic interactions. We discuss its
application with the aid of systems of identical fermions interacting via a
long-range attractive and short-range repulsive two-body force in one
dimension. We compute ground-state energies, intrinsic densities, and density
correlation functions of these systems and compare our results to those
obtained from other methods. In particular, we show how energies of excited
states as well as the absolute square of the ground-state wave function can be
extracted from the correlation functions within our approach. The relation
between many-body perturbation theory and our DFT-RG approach is discussed and
illustrated with the aid of the calculation of the second-order energy
correction for a system of $N$ identical fermions interacting via a general
two-body interaction. Moreover, we discuss the control of spuriously emerging
fermion self-interactions in DFT studies within our framework. In general, our
approach may help to guide the development of energy functionals for future
quantitative DFT studies of heavy nuclei from microscopic interactions.


title:
Power Installations based on Activated Nuclear Reactions of Fission and
  Synthesis

abstract:
  The general scheme of power installations based on nuclear reactions of
fission and synthesis activated by external sources is analyzed. The external
activation makes possible to support nuclear reactions at temperatures and
pressures lower than needed for chain reactions, so simplifies considerably
practical realization of power installations. The possibility of operation on
subcritical masses allows making installations compact and safe at emergency
situations. Installations are suitable for transmutation of radioactive
nuclides, what solves the problem of utilization of nuclear waste products. It
is proposed and considered schemes of power installations based on nuclear
reactions of fission and fusion, activated by external sources, different from
ADS systems. Variants of activation of nuclear reactions of fission (U-235,
238, Pu-239) and fusion (Li-6,7, B-10,11) are considered.


title: Numerical modeling of material points evolution in a system with gravity

abstract:
  The evolution of material points interacting via gravitational force in 3D
space was investigated. At initial moment points with masses of 2.48 Sun masses
are randomly distributed inside a cube with an edge of 5 light-years. The
modeling was conducted at different initial distributions of velocities and
different ratios between potential and kinetic energy of the points. As a
result of modeling the time dependence of velocity distribution function of
points was obtained. Dependence of particles fraction which had evaporated from
initial cluster on time for different initial conditions is obtained. In
particular, it was obtained that the fraction of evaporated particles varies
between 0,45 and 0,63. Mutual diffusion of two classes of particles at
different initial conditions in the case when at initial moment of time both
classes of particles occupy equal parts of cube was investigated. The maximum
Lyapunov exponent of the system with different initial conditions was
calculated. The obtained value weakly depends on the ratio between initial
kinetic and potential energies and amounts approximately 10^-5. Corresponding
time of the particle trajectories divergence turned out to be 40-50 thousand
years.


title: New Limits on Heavier Electroweakinos and their LHC Signatures

abstract:
  We investigate the heavier electroweakino sectors in several versions of the
MSSM, which has not been explored so far in the light of the LHC data, and
obtain new bounds using the ATLAS Run I constraints in the $3l +
{E\!\!\!\!/_T}$ channel. We also venture beyond the trilepton events and
predict several novel multilepton + ${E\!\!\!\!/_T}$ signatures of these
electroweakinos which may show up before the next shutdown of the LHC.


title: The relative units-Picard complex and the Brauer group of a product

abstract:
  We introduce the relative units-Picard complex of an arbitrary morphism of
schemes and apply it to the problem of describing the (cohomological) Brauer
group of a (fiber) product of schemes in terms of the Brauer groups of the
factors. Under certain hypotheses, we obtain a five-term exact sequence
involving the preceding groups which enables us to solve the indicated problem
in the case of, e.g., (certain types of) ruled varieties over a field of
characteristic zero.


title:
Deep Learning with Darwin: Evolutionary Synthesis of Deep Neural
  Networks

abstract:
  Taking inspiration from biological evolution, we explore the idea of "Can
deep neural networks evolve naturally over successive generations into highly
efficient deep neural networks?" by introducing the notion of synthesizing new
highly efficient, yet powerful deep neural networks over successive generations
via an evolutionary process from ancestor deep neural networks. The
architectural traits of ancestor deep neural networks are encoded using
synaptic probability models, which can be viewed as the `DNA' of these
networks. New descendant networks with differing network architectures are
synthesized based on these synaptic probability models from the ancestor
networks and computational environmental factor models, in a random manner to
mimic heredity, natural selection, and random mutation. These offspring
networks are then trained into fully functional networks, like one would train
a newborn, and have more efficient, more diverse network architectures than
their ancestor networks, while achieving powerful modeling capabilities.
Experimental results for the task of visual saliency demonstrated that the
synthesized `evolved' offspring networks can achieve state-of-the-art
performance while having network architectures that are significantly more
efficient (with a staggering $\sim$48-fold decrease in synapses by the fourth
generation) compared to the original ancestor network.


title:
Partitioning sparse graphs into an independent set and a forest of
  bounded degree

abstract:
  An $({\cal I},{\cal F}_d)$-partition of a graph is a partition of the
vertices of the graph into two sets $I$ and $F$, such that $I$ is an
independent set and $F$ induces a forest of maximum degree at most $d$. We show
that for all $M<3$ and $d \ge \frac{2}{3-M} - 2$, if a graph has maximum
average degree less than $M$, then it has an $({\cal I},{\cal F}_d)$-partition.
Additionally, we prove that for all $\frac{8}{3} \le M < 3$ and $d \ge
\frac{1}{3-M}$, if a graph has maximum average degree less than $M$ then it has
an $({\cal I},{\cal F}_d)$-partition.


title:
Kinetic effects observed in dynamic FORCs of magnetic wires: Experiment
  and theoretical description

abstract:
  This study is focused on the possibility to extend the use of the first-order
reversal curve (FORC) diagram method to rate-dependent hysteresis. The FORCs
for an amorphous magnetic wire was measured with an inductometric experimental
setup in which the field-rate was maintained constant. The FORC experiment was
performed for four different field-rates. As it is known, to obtain
quantitative information on the magnetization process during the FORC process
we need a model able to simulate as close as possible the experimental FORC
diagrams. In this case, we have developed and implemented a model based on the
hypothesis that the magnetization processes in this kind of materials are
mainly due to the movement of a domain wall between the central domains of the
wire. The differential equation of the domain wall movement is able to give a
remarkably accurate description of the experimental FORC diagrams. The
experimental FORCs, the FORC susceptibility diagram and the classical FORC
diagram show however a number of details that the model is not able to
describe. In each such case one discuss the possible physical cause of the
observed behavior. As the magnetic wires are analyzed in many laboratories
around the world for a wide variety of applications (essentially involving the
control of the domain wall movement) we consider that our study offers to these
researchers a valuable new tool.


title: Spin and charge fluctuations in the Hubbard model

abstract:
  Using the strong coupling diagram technique for calculating the electron
Green's function of the two-dimensional Hubbard model we have summed infinite
sequences of ladder diagrams, which describe interactions of electrons with
spin and charge fluctuations. For sufficiently low temperatures and doping a
pronounced four-band structure is observed in spectral functions. Its
appearance is related to the proximity of the transition to the long-range
antiferromagnetic order.


title:
Relating Strong Spatial Cognition to Symbolic Problem Solving --- An
  Example

abstract:
  In this note, we discuss and analyse a shortest path finding approach using
strong spatial cognition. It is compared with a symbolic graph-based algorithm
and it is shown that both approaches are similar with respect to structure and
complexity. Nevertheless, the strong spatial cognition solution is easy to
understand and even pops up immediately when one has to solve the problem.


title: Test of the cosmic evolution using Gaussian processes

abstract:
  Much focus was on the possible slowing down of cosmic acceleration under the
dark energy parametrization. In the present paper, we investigate this subject
using the Gaussian processes (GP), without resorting to a particular template
of dark energy. The reconstruction is carried out by abundant data including
luminosity distance from Union2, Union2.1 compilation and gamma-ray burst, and
dynamical Hubble parameter. It suggests that slowing down of cosmic
acceleration cannot be presented within 95\% C.L., in considering the influence
of spatial curvature and Hubble constant. In order to reveal the reason of
tension between our reconstruction and previous parametrization constraint for
Union2 data, we compare them and find that slowing down of acceleration in some
parametrization is only a "mirage". Although these parameterizations fits well
with the observational data, their tension can be revealed by high order
derivative of distance $D$. Instead, GP method is able to faithfully model the
cosmic expansion history.


title:
Double-step truncation procedure for large-scale shell-model
  calculations

abstract:
  We present a procedure that is helpful to reduce the computational complexity
of large-scale shell-model calculations, by preserving as much as possible the
role of the rejected degrees of freedom in an effective approach. Our
truncation is driven first by the analysis of the effective single-particle
energies of the original large-scale shell-model hamiltonian, so to locate the
relevant degrees of freedom to describe a class of isotopes or isotones, namely
the single-particle orbitals that will constitute a new truncated model space.
The second step is to perform an unitary transformation of the original
hamiltonian from its model space into the truncated one. This transformation
generates a new shell-model hamiltonian, defined in a smaller model space, that
retains effectively the role of the excluded single-particle orbitals. As an
application of this procedure, we have chosen a realistic shell-model
hamiltonian defined in a large model space, set up by seven and five proton and
neutron single-particle orbitals outside 88Sr, respectively. We study the
dependence of shell-model results upon different truncations of the original
model space for the Zr, Mo, Ru, Pd, Cd, and Sn isotopic chains, showing the
reliability of this truncation procedure.


title: Demonstration of a Chip-based Nonlinear Optical Isolator

abstract:
  Despite fundamentally challenging in integrated (nano)photonics, achieving
chip-based light nonreciprocity becomes increasingly urgent in signal
processing and optical communications. Because of material incompatibilities in
conventional approaches based on Faraday effects, alternative solutions have
resorted to nonlinear processes to obtain one-way transmission. However,
revealed dynamic reciprocity in a recent theoretical analysis has pinned down
the functionalities of these nonlinear isolators. To overcome this dynamic
reciprocity, we here report the first demonstration of a nonlinear optical
isolator on a silicon chip enforced by phase-matched parametric amplification.
Using a high-Q microtoroid resonator, we realize highly nonreciprocal transport
at the 1,550 nm wavelength when waves are simultaneously launched in both
forward and backward directions. Our design, compatible with current CMOS
technique, yields convincing isolation performance with sufficiently low
insertion loss for a wide range of input power levels. Moreover, our work
evidences the possibility of designing chip-based real nonlinear isolators for
information processing and laser protection.


title:
Conformal Field Theory for Inhomogeneous One-dimensional Quantum
  Systems: the Example of Non-Interacting Fermi Gases

abstract:
  Conformal field theory (CFT) has been extremely successful in describing
large-scale universal effects in one-dimensional (1D) systems at quantum
critical points. Unfortunately, its applicability in condensed matter physics
has been limited to situations in which the bulk is uniform because CFT
describes low-energy excitations around some energy scale, taken to be constant
throughout the system. However, in many experimental contexts, such as quantum
gases in trapping potentials and in several out-of-equilibrium situations,
systems are strongly inhomogeneous. We show here that the powerful CFT methods
can be extended to deal with such 1D situations, providing a few concrete
examples for non-interacting Fermi gases. The system's inhomogeneity enters the
field theory action through parameters that vary with position; in particular,
the metric itself varies, resulting in a CFT in curved space. This approach
allows us to derive exact formulas for entanglement entropies which were not
known by other means.


title:
Warm ISM in the Sgr A Complex. I: Mid-J CO, atomic carbon, ionized
  atomic carbon,and ionized nitrogen sub-mm/FIR line observations with the
  Herschel-HIFI and NANTEN2/SMART telescopes

abstract:
  We present large-scale submm observations towards the Sgr A Complex covering
~300 arcmin2. These data were obtained in the frame of the HEXGAL Program with
the Herschel-HIFI satellite and are complemented with submm observations
obtained with the NANTEN2/SMART telescope as part of the NANTEN2/SMART Central
Nuclear Zone Survey. The observed species are CO(4-3) observed with the
NANTEN2/SMART telescope, and [CI](1-0), [CI](2-1), [NII](1-0), and
[CII](3/2-1/2) observed with the Herschel-HIFI satellite. The observations are
presented in a 1 km/s spectral resolution and a spatial resolution ranging from
46" to 28". The spectral coverage of the three lower frequency lines is +-200
km/s, while in the two high frequency lines, the upper LSR velocity limit is
+94 km/s and +145 km/s for the [NII] and [CII] lines, respectively. The spatial
distribution of the emission in all lines is very widespread. The bulk of the
CO emission is found towards Galactic latitudes below the Galactic plane, and
all the known molecular clouds are identified. Both neutral atomic carbon lines
have their brightest emission associated with the +50 km/s cloud. Their spatial
distribution at this LSR velocity describes a crescent-shape structure, which
is probably the result of interaction with the energetic event (one or several
supernovae explosions) that gave origin to the non-thermal Sgr A-East source.
The [CII] and [NII] emissions have most of their flux associated with the
thermal Arched-Filaments and the H Region and bright spots in [CII] emission
towards the Central Nuclear Disk (CND) are detected. Warm Gas at very high
(|Vlsr| > 100 km/s) LSR velocities is also detected towards the line of sight
to the Sgr A Complex, and it is most probably located outside the region, in
the X1 orbits.


title:
Theoretical predictions of transverse kinematic imbalance in
  neutrino-nucleus interactions

abstract:
  Distributions of transverse kinematic imbalance in neutrino-nucleus
interactions in the few GeV regime are sensitive to nuclear effects. We present
a study comparing the latest predictions of transverse kinematic imbalance from
the interaction simulations, NuWro and GENIE. We dis- cuss the differences
between the model predictions.


title: End-to-End Comparative Attention Networks for Person Re-identification

abstract:
  Person re-identification across disjoint camera views has been widely applied
in video surveillance yet it is still a challenging problem. One of the major
challenges lies in the lack of spatial and temporal cues, which makes it
difficult to deal with large variations of lighting conditions, viewing angles,
body poses and occlusions. Recently, several deep learning based person
re-identification approaches have been proposed and achieved remarkable
performance. However, most of those approaches extract discriminative features
from the whole frame at one glimpse without differentiating various parts of
the persons to identify. It is essentially important to examine multiple highly
discriminative local regions of the person images in details through multiple
glimpses for dealing with the large appearance variance. In this paper, we
propose a new soft attention based model, i.e., the end to-end Comparative
Attention Network (CAN), specifically tailored for the task of person
re-identification. The end-to-end CAN learns to selectively focus on parts of
pairs of person images after taking a few glimpses of them and adaptively
comparing their appearance. The CAN model is able to learn which parts of
images are relevant for discerning persons and automatically integrates
information from different parts to determine whether a pair of images belongs
to the same person. In other words, our proposed CAN model simulates the human
perception process to verify whether two images are from the same person.
Extensive experiments on three benchmark person re-identification datasets,
including CUHK01, CHUHK03 and Market-1501, clearly demonstrate that our
proposed end-to-end CAN for person re-identification outperforms well
established baselines significantly and offer new state-of-the-art performance.


title:
Fundamentals of Modeling Finite Wireless Networks using Binomial Point
  Process

abstract:
  Modeling the locations of nodes as a uniform binomial point process (BPP), we
present a generic mathematical framework to characterize the performance of an
arbitrarily-located reference receiver in a finite wireless network. Different
from most of the prior works where the serving transmitter (TX) node is located
at the fixed distance from the reference receiver, we consider two general
TX-selection policies: i) uniform TX-selection: the serving node is chosen
uniformly at random amongst transmitting nodes, and ii) k-closest TX-selection:
the serving node is the k-th closest node out of transmitting nodes to the
reference receiver. The key intermediate step in our analysis is the derivation
of a new set of distance distributions that lead not only to the tractable
analysis of coverage probability but also enable the analyses of wide range of
classical and currently trending problems in wireless networks. Using this new
set of distance distributions, we first investigate the diversity loss due to
SIR correlation in a finite network. We then obtain the optimal number of links
that can be simultaneously activated to maximize network spectral efficiency.
Finally, we evaluate optimal caching probability to maximize the total hit
probability in cache-enabled finite networks.


title:
Fast derivatives of likelihood functionals for ODE based models using
  adjoint-state method

abstract:
  We consider time series data modeled by ordinary differential equations
(ODEs), widespread models in physics, chemistry, biology and science in
general. The sensitivity analysis of such dynamical systems usually requires
calculation of various derivatives with respect to the model parameters.
  We employ the adjoint state method (ASM) for efficient computation of the
first and the second derivatives of likelihood functionals constrained by ODEs
with respect to the parameters of the underlying ODE model. Essentially, the
gradient can be computed with a cost (measured by model evaluations) that is
independent of the number of the ODE model parameters and the Hessian with a
linear cost in the number of the parameters instead of the quadratic one. The
sensitivity analysis becomes feasible even if the parametric space is
high-dimensional.
  The main contributions are derivation and rigorous analysis of the ASM in the
statistical context, when the discrete data are coupled with the continuous ODE
model. Further, we present a highly optimized implementation of the results and
its benchmarks on a number of problems.
  The results are directly applicable in (e.g.) maximum-likelihood estimation
or Bayesian sampling of ODE based statistical models, allowing for faster, more
stable estimation of parameters of the underlying ODE model.


title:
Integrated Silicon Photonic Transmitter for Polarization-Encoded Quantum
  Key Distribution

abstract:
  We present a silicon optical transmitter for polarization-encoded quantum key
distribution (QKD). The chip was fabricated in a standard silicon photonic
foundry process and integrated a pulse generator, intensity modulator, variable
optical attenuator, and polarization modulator in a 1.3 mm $\times$ 3 mm die
area. The devices in the photonic circuit meet the requirements for QKD. The
transmitter was used in a proof-of-concept demonstration of the BB84 QKD
protocol over a 5 km long fiber link.


title:
$h\to\mu\tau$ and muon g-2 in the alignment limit of two-Higgs-doublet
  model

abstract:
  We examine the $h\to \mu\tau$ and muon g-2 in the exact alignment limit of
two-Higgs-doublet model. In this case, the couplings of the SM-like Higgs to
the SM particles are the same as the Higgs couplings in the SM at the tree
level, and the tree-level lepton-flavor-violating coupling $h\mu\tau$ is
absent. We assume the lepton-flavor-violating $\mu\tau$ excess observed by CMS
to be respectively from the other neutral Higgses, $H$ and $A$, which almost
degenerates with the SM-like Higgs at the 125 GeV. After imposing the relevant
theoretical constraints and experimental constraints from the precision
electroweak data, $B$-meson decays, $\tau$ decays and Higgs searches, we find
that the muon g-2 anomaly and $\mu\tau$ excess favor the small lepton Yukawa
coupling and top Yukawa coupling of the non-SM-like Higgs around 125 GeV, and
the lepton-flavor-violating coupling is sensitive to another heavy neutral
Higgs mass. In addition, if the $\mu\tau$ excess is from $H$ around 125 GeV,
the experimental data of the heavy Higgs decaying into $\mu\tau$ favor
$m_A>230$ GeV for a relatively large $H\bar{t}t$ coupling.


title:
An advection-diffusion model for cross-field runaway electron transport
  in perturbed magnetic fields

abstract:
  Disruption-generated runaway electrons (RE) present an outstanding issue for
ITER. The predictive computational studies of RE generation rely on
orbit-averaged computations and, as such, they lack the effects from the
magnetic field stochasticity. Since stochasiticity is naturally present in
post-disruption plasma, and externally induced stochastization offers a
prominent mechanism to mitigate RE avalanche, we present an advection-diffusion
model that can be used to couple an orbit-following code to an orbit-averaged
tool in order to capture the cross-field transport and to overcome the latter's
limitation. The transport coefficients are evaluated via a Monte Carlo method.
We show that the diffusion coefficient differs significantly from the
well-known Rechester-Rosenbluth result. We also demonstrate the importance of
including the advection: it has a two-fold role both in modelling transport
barriers created by magnetic islands and in amplifying losses in regions where
the islands are not present.


title: Braneworld scenarios from deformed defect chains

abstract:
  Novel braneworld scenarios supported by warp factors driven by a single extra
dimension are obtained from deformed one-dimensional lump-like solutions known
{\em a priori}. Through a novel {\em ansatz}, the internal energy structure,
the braneworld warp factor, and the quantum mechanical analogue problem, as
well as the associated zero mode solutions, are straightforwardly derived by
means of an analytical procedure. The results allow one to identify thick brane
solutions that support internal structures and that can hold the
($3+1$)-dimensional gravity.


title:
Ab-initio perspective on structural and electronic properties of
  iron-based superconductors

abstract:
  The discovery of iron pnictides and iron chalcogenides as a new class of
unconventional superconductors in 2008 has generated an enourmous amount of
experimental and theoretical work that identifies these materials as correlated
metals with multiorbital physics, where magnetism, nematicity and
superconductivity are competing phases that appear as a function of pressure
and doping. A microscopic understanding of the appearance of these phases is
crucial in order to determine the nature of superconductivity in these systems.
Here we review our recent theoretical efforts to describe and understand from
first principles the properties of iron pnictides and chalcogenides with
special focus on (i) pressure dependence, (ii) effects of electronic
correlation and (iii) origin of magnetism and superconductivity.


title:
The Infinity Mirror Test for Analyzing the Robustness of Graph
  Generators

abstract:
  Graph generators learn a model from a source graph in order to generate a new
graph that has many of the same properties. The learned models each have
implicit and explicit biases built in, and its important to understand the
assumptions that are made when generating a new graph. Of course, the
differences between the new graph and the original graph, as compared by any
number of graph properties, are important indicators of the biases inherent in
any modelling task. But these critical differences are subtle and not
immediately apparent using standard performance metrics. Therefore, we
introduce the infinity mirror test for the analysis of graph generator
performance and robustness. This stress test operates by repeatedly,
recursively fitting a model to itself. A perfect graph generator would have no
deviation from the original or ideal graph, however the implicit biases and
assumptions that are cooked into the various models are exaggerated by the
infinity mirror test allowing for new insights that were not available before.
We show, via hundreds of experiments on 6 real world graphs, that several
common graph generators do degenerate in interesting and informative ways. We
believe that the observed degenerative patterns are clues to future development
of better graph models.


title:
EXPRES: A Next Generation RV Spectrograph in the Search for Earth-like
  Worlds

abstract:
  The EXtreme PREcision Spectrograph (EXPRES) is an optical fiber fed echelle
instrument being designed and built at the Yale Exoplanet Laboratory to be
installed on the 4.3-meter Discovery Channel Telescope operated by Lowell
Observatory. The primary science driver for EXPRES is to detect Earth-like
worlds around Sun-like stars. With this in mind, we are designing the
spectrograph to have an instrumental precision of 15 cm/s so that the on-sky
measurement precision (that includes modeling for RV noise from the star) can
reach to better than 30 cm/s. This goal places challenging requirements on
every aspect of the instrument development, including optomechanical design,
environmental control, image stabilization, wavelength calibration, and data
analysis. In this paper we describe our error budget, and instrument
optomechanical design.


title: The Parallel Knowledge Gradient Method for Batch Bayesian Optimization

abstract:
  In many applications of black-box optimization, one can evaluate multiple
points simultaneously, e.g. when evaluating the performances of several
different neural network architectures in a parallel computing environment. In
this paper, we develop a novel batch Bayesian optimization algorithm --- the
parallel knowledge gradient method. By construction, this method provides the
one-step Bayes-optimal batch of points to sample. We provide an efficient
strategy for computing this Bayes-optimal batch of points, and we demonstrate
that the parallel knowledge gradient method finds global optima significantly
faster than previous batch Bayesian optimization algorithms on both synthetic
test functions and when tuning hyperparameters of practical machine learning
algorithms, especially when function evaluations are noisy.


title:
Existence of cylindrically symmetric ground states to a nonlinear
  curl-curl equation with non-constant coefficients

abstract:
  We consider the nonlinear curl-curl problem $\nabla\times\nabla\times U +
V(x) U=f(x,|U|^2)U$ in $\mathbb{R}^3$ related to the nonlinear Maxwell
equations with Kerr-type nonlinear material laws. We prove the existence of a
symmetric ground-state type solution for a bounded, cylindrically symmetric
coefficient $V$ and subcritical cylindrically symmetric nonlinearity $f$. The
new existence result extends the class of problems for which ground-state type
solutions are known. It is based on compactness properties of symmetric
functions due to Lions, new rearrangement type inequalities from Brock and the
recent extension of the Nehari-manifold technique by Szulkin and Weth.


title:
Natural NMSSM after LHC Run I and the Higgsino dominated dark matter
  scenario

abstract:
  We investigate the impact of the direct searches for SUSY at LHC Run I on the
naturalness of the Next-to-Minimal Supersymmetric Standard Model (NMSSM). For
this end, we first scan the vast parameter space of the NMSSM to get the region
where the fine tuning measures $\Delta_Z$ and $\Delta_h$ at the electroweak
scale are less than about 50, then we implement by simulations the constraints
of the direct searches on the parameter points in the region. Our results
indicate that although the direct search experiments are effective in excluding
the points, the parameter intervals for the region and also the minimum reaches
of $\Delta_Z$ and $\Delta_h$ are scarcely changed by the constraints, which
implies that the fine tuning of the NMSSM does not get worse after LHC Run I.
Moreover, based on the results we propose a natural NMSSM scenario where the
lightest neutralino $\tilde{\chi}_1^0$ as the dark matter (DM) candidate is
Higgsino-dominated. In this scenario, $\Delta_Z$ and $\Delta_h$ may be as low
as 2 without conflicting with any experimental constraints, and intriguingly
$\tilde{\chi}_1^0$ can easily reach the measured DM relic density due to its
significant Singlino component. We exhibit the features of the scenario which
distinguish it from the other natural SUSY scenario, including the properties
of its neutralino-chargino sector and scalar top quark sector. We emphasize
that the scenario can be tested either through searching for $3 l + E_T^{miss}$
signal at 14 TeV LHC or through future DM direct detection experiments.


title:
A unified matrix model including both CCA and F matrices in multivariate
  analysis: the largest eigenvalue and its applications

abstract:
  Let $\bbZ_{M_1\times N}=\bbT^{\frac{1}{2}}\bbX$ where
$(\bbT^{\frac{1}{2}})^2=\bbT$ is a positive definite matrix and $\bbX$ consists
of independent random variables with mean zero and variance one. This paper
proposes a unified matrix model
$$\bold{\bbom}=(\bbZ\bbU_2\bbU_2^T\bbZ^T)^{-1}\bbZ\bbU_1\bbU_1^T\bbZ^T,$$ where
$\bbU_1$ and $\bbU_2$ are isometric with dimensions $N\times N_1$ and $N\times
(N-N_2)$ respectively such that $\bbU_1^T\bbU_1=\bbI_{N_1}$,
$\bbU_2^T\bbU_2=\bbI_{N-N_2}$ and $\bbU_1^T\bbU_2=0$. Moreover, $\bbU_1$ and
$\bbU_2$ (random or non-random) are independent of $\bbZ_{M_1\times N}$ and
with probability tending to one, $rank(\bbU_1)=N_1$ and $rank(\bbU_2)=N-N_2$.
  We establish the asymptotic Tracy-Widom distribution for its largest
eigenvalue under moment assumptions on $\bbX$ when $N_1,N_2$ and $M_1$ are
comparable.
  By selecting appropriate matrices $\bbU_1$ and $\bbU_2$, the asymptotic
distributions of the maximum eigenvalues of the matrices used in Canonical
Correlation Analysis (CCA) and of F matrices (including centered and
non-centered versions) can be both obtained from that of $\bold{\bbom}$. %In
particular, $\bbom$ can also cover nonzero mean by appropriate matrices
$\bbU_1$ and $\bbU_2$. %relax the zero mean value restriction for F matrix in
\cite{WY} to allow for any nonzero mean vetors. %thus a direct application of
our proposed Tracy-Widom distribution is the independence testing via CCA.
Moreover, via appropriate matrices $\bbU_1$ and $\bbU_2$, this matrix
$\bold{\bbom}$ can be applied to some multivariate testing problems that cannot
be done by the traditional CCA matrix.


title:
Entangled pure state transformations via local operations assisted by
  finitely many rounds of classical communication

abstract:
  We consider generic pure $n$-qubit states and a general class of pure states
of arbitrary dimensions and arbitrarily many subsystems. We characterize those
states which can be reached from some other state via Local Operations assisted
by finitely many rounds of Classical Communication ($LOCC_{\mathbb{N}}$). For
$n$ qubits with $n>3$ we show that this set of states is of measure zero, which
implies that the maximally entangled set is generically of full measure if
restricted to the practical scenario of $LOCC_{\mathbb{N}}$. Moreover, we
identify a class of states for which any $LOCC_{\mathbb{N}}$ protocol can be
realized via a concatenation of deterministic steps. We show, however, that in
general there exist state transformations which require a probabilistic step
within the protocol, which highlights the difference between bipartite and
multipartite LOCC.


title: Small feedback vertex sets in planar digraphs

abstract:
  Let $G$ be a directed planar graph on $n$ vertices, with no directed cycle of
length less than $g\ge 4$. We prove that $G$ contains a set $X$ of vertices
such that $G-X$ has no directed cycle, and $|X|\le \tfrac{5n-5}9$ if $g=4$,
$|X|\le \tfrac{2n-5}4$ if $g=5$, and $|X|\le \tfrac{2n-6}{g}$ if $g\ge 6$. This
improves recent results of Golowich and Rolnick.


title:
Angular correlation between IceCube high-energy starting events and
  starburst sources

abstract:
  Starburst galaxies and star-forming regions in the Milkyway, with high rate
of supernova activities, are candidate sources of high-energy neutrinos. Using
a gamma-ray selected sample of these sources we perform statistical analysis of
their angular correlation with the four-year sample of high-energy starting
events (HESE), detected by the IceCube Neutrino Observatory. We find that the
two samples (starburst galaxies and local star-forming regions) are correlated
with cosmic neutrinos at $\sim (2-3)\sigma$ (pre-trial) significance level,
when the full HESE sample with deposited energy $\gtrsim 20$~TeV is considered.
However when we consider the HESE sample with deposited energy $\gtrsim
60$~TeV, which is almost free of atmospheric neutrino and muon backgrounds, the
significance of correlation decreased drastically. We perform a similar study
for Galactic sources in the 2nd Catalog of Hard {\em Fermi}-LAT Sources (2FHL,
$>50$~ GeV) catalog as well, obtaining $\sim (2-3)\sigma$ (pre-trial)
correlation, however the significance of correlation increases with higher
cutoff energy in the HESE sample for this case. We also fit available gamma-ray
data from these sources using a $pp$ interaction model and calculate expected
neutrino fluxes. We find that the expected neutrino fluxes for most of the
sources are at least an order of magnitude lower than the fluxes required to
produce the HESE neutrinos from these sources. This puts the starburst sources
being the origin of the IceCube HESE neutrinos in question.


title: Analysis of Conditions favorable for Ball Lightning Creation

abstract:
  This report uses a few well documented cases of Ball Lightning (or BL for
short) observations to demonstrate a correlation between BL and positive
lightning, especially strong positive lightning. This allows to draw
conclusions and predictions about future BL observations and the pro- duction
of these objects in the laboratory. Contrary to many current BL theories, these
objects can be created without direct contact to a lightning channel. Very high
electric fields appear to be essential for the creation, together with the
proper temporal structure of the field. So far no experiments have been
performed along the ideas presented in this report.


title:
Logic Tensor Networks: Deep Learning and Logical Reasoning from Data and
  Knowledge

abstract:
  We propose Logic Tensor Networks: a uniform framework for integrating
automatic learning and reasoning. A logic formalism called Real Logic is
defined on a first-order language whereby formulas have truth-value in the
interval [0,1] and semantics defined concretely on the domain of real numbers.
Logical constants are interpreted as feature vectors of real numbers. Real
Logic promotes a well-founded integration of deductive reasoning on a
knowledge-base and efficient data-driven relational machine learning. We show
how Real Logic can be implemented in deep Tensor Neural Networks with the use
of Google's tensorflow primitives. The paper concludes with experiments
applying Logic Tensor Networks on a simple but representative example of
knowledge completion.


title:
Regularity and a priori error analysis of a Ventcel problem in
  polyhedral domains

abstract:
  We consider the regularity of a mixed boundary value problem for the Laplace
operator on a polyhedral domain, where Ventcel boundary conditions are imposed
on one face of the polyhedron and Dirichlet boundary conditions are imposed on
the complement of that face in the boundary. We establish improved regularity
estimates for the trace of the variational solution on the Ventcel face, and
use them to derive a decomposition of the solution into a regular and a
singular part that belongs to suitable weighted Sobolev spaces. This
decomposition, in turn, via interpolation estimates both in the interior as
well as on the Ventcel face, allows us to perform an a priori error analysis
for the Finite Element approximation of the solution on anisotropic graded
meshes. Numerical tests support the theoretical analysis.


title: Comparison of Gelfand-Tsetlin Bases for Alternating and Symmetric Groups

abstract:
  Young's orthogonal basis is a classical basis for an irreducible
representation of a symmetric group. This basis happens to be a Gelfand-Tsetlin
basis for the chain of symmetric groups. It is well-known that the chain of
alternating groups, just like the chain of symmetric groups, has
multiplicity-free restrictions for irreducible representations. Therefore each
irreducible representation of an alternating group also admits Gelfand-Tsetlin
bases. Moreover, each such representation is either the restriction of, or a
subrepresentation of, the restriction of an irreducible representation of a
symmetric group. In this article, we describe a recursive algorithm to write
down the expansion of each Gelfand-Tsetlin basis vector for an irreducible
representation of an alternating group in terms of Young's orthogonal basis of
the ambient representation of the symmetric group. This algorithm is
implemented with the Sage Mathematical Software.


title: Exponential Growth Series and Benford's Law

abstract:
  Exponential growth occurs when the growth rate of a given quantity is
proportional to the quantity's current value. Surprisingly, when exponential
growth data is plotted as a simple histogram disregarding the time dimension, a
remarkable fit to the positively skewed k/x distribution is found, where the
small is numerous and the big is rare. Such quantitative preference for the
small has a corresponding digital preference known as Benford's Law which
predicts that the first significant digit on the left-most side of numbers in
typical real-life data is proportioned between all possible 1 to 9 digits
approximately as in LOG(1 + 1/digit), so that low digits occur much more
frequently than high digits in the first place. Exponential growth series with
high growth rate are nearly perfectly Benford given that plenty of elements are
considered. An additional constraint is that the logarithm of the growth factor
must be an irrational number. Since the irrationals vastly outnumber the
rationals, on the face of it, this constraint seems to constitute the
explanation of why almost all growth series are Benford, yet, in reality this
is all too simplistic, and the real and more complex explanation is provided in
this article. Empirical examinations of close to a half a million growth series
via computerized programs almost perfectly match the prediction of the
theoretical study on rational versus irrational occurrences, thus in a sense
confirming both, the empirical work as well as the theoretical study. In
addition, a rigorous mathematical proof is provided in the continuous growth
case showing that it exactly obeys Benford's Law. A non-rigorous proof is given
in the discrete case via uniformity of mantissa argument. Finally cases of
discrete series embedded within continuous series are studied, detailing the
degree of deviation from the ideal Benford configuration.


title:
Modulation instability in quasi two-dimensional spin-orbit coupled
  Bose-Einstein condensates

abstract:
  We theoretically investigate the dynamics of modulation instability (MI) in
two-dimensional spin-orbit coupled Bose-Einstein condensates (BECs). The
analysis is performed for equal densities of pseudo-spin components. Different
combination of the signs of intra- and inter-component interaction strengths
are considered, with a particular emphasize on repulsive interactions. We
observe that the unstable modulation builds from originally miscible
condensates, depending on the combination of the signs of the intra- and
inter-component interaction strengths. The repulsive intra- and inter-component
interactions admit instability and the MI immiscibility condition is no longer
significant. Influence of interaction parameters such as spin-orbit and Rabi
coupling on MI are also investigated. The spin-orbit coupling (SOC) inevitably
contributes to instability regardless of the nature of the interaction. In the
case of attractive interaction, SOC manifest in enhancing the MI. Thus, a
comprehensive study of MI in two-dimensional spin-orbit coupled binary BECs of
pseudo-spin components is presented.


title: Splotch: porting and optimizing for the Xeon Phi

abstract:
  With the increasing size and complexity of data produced by large scale
numerical simulations, it is of primary importance for scientists to be able to
exploit all available hardware in heterogenous High Performance Computing
environments for increased throughput and efficiency. We focus on the porting
and optimization of Splotch, a scalable visualization algorithm, to utilize the
Xeon Phi, Intel's coprocessor based upon the new Many Integrated Core
architecture. We discuss steps taken to offload data to the coprocessor and
algorithmic modifications to aid faster processing on the many-core
architecture and make use of the uniquely wide vector capabilities of the
device, with accompanying performance results using multiple Xeon Phi. Finally
performance is compared against results achieved with the GPU implementation of
Splotch.


title: Ultrafast Spin-Transfer-Torque Switching of Synthetic Ferrimagnets

abstract:
  The switching speed and the write current required for spin-transfer-torque
reversal of spintronic devices such as magnetic tunnel junctions (MTJ)
currently hinder their wide implementation into memory and logic devices. This
problem is further exacerbated as the dimensions of MTJ nanostructures are
scaled down to tens of nanometers in diameter, as higher magnetic anisotropy
materials are required to meet thermal stability requirements that demand
higher switching current densities. Here, we propose a simple solution to these
issues based on synthetic ferrimagnet (SFM) structures. It is commonly assumed
that to achieve a given switching delay, the current has to exceed the critical
current by a certain factor and so a higher critical current implies a higher
switching current. We show that this is not the case for SFM structures which
can provide significantly reduced switching delay for a given current density,
even though the critical current is increased. This non-intuitive result can be
understood from the requirements of angular momentum conservation. We conclude
that a 20 nm diameter MTJ incorporating the proposed SFM free layer structure
can be switched in tens of picosecond time scales. This remarkable switching
speed can be attained by employing current perpendicular magnetic anisotropy
materials with experimentally demonstrated exchange coupling strengths.


title: Using Fuzzy Logic to Leverage HTML Markup for Web Page Representation

abstract:
  The selection of a suitable document representation approach plays a crucial
role in the performance of a document clustering task. Being able to pick out
representative words within a document can lead to substantial improvements in
document clustering. In the case of web documents, the HTML markup that defines
the layout of the content provides additional structural information that can
be further exploited to identify representative words. In this paper we
introduce a fuzzy term weighing approach that makes the most of the HTML
structure for document clustering. We set forth and build on the hypothesis
that a good representation can take advantage of how humans skim through
documents to extract the most representative words. The authors of web pages
make use of HTML tags to convey the most important message of a web page
through page elements that attract the readers' attention, such as page titles
or emphasized elements. We define a set of criteria to exploit the information
provided by these page elements, and introduce a fuzzy combination of these
criteria that we evaluate within the context of a web page clustering task. Our
proposed approach, called Abstract Fuzzy Combination of Criteria (AFCC), can
adapt to datasets whose features are distributed differently, achieving good
results compared to other similar fuzzy logic based approaches and TF-IDF
across different datasets.


title: An Interpolating Family of Size Distributions

abstract:
  We introduce a new five-parameter family of size distributions on the
semi-finite interval $[x_0, \infty), x_0 \geqslant 0$, with two attractive
features. First, it interpolates between power laws, such as the Pareto
distribution, and power laws with exponential cut-off, such as the Weibull
distribution. The proposed family is thus very flexible and spans over a broad
range of well-known size distributions which are special cases of our family.
Second, it has important tractability advantages over the popular
five-parameter Generalized Beta distribution. We derive the hazard function,
survival function, modes and quantiles, propose a random number generation
procedure and discuss maximum likelihood estimation issues. Finally, we
illustrate the wide applicability and fitting capacities of our new model on
basis of three real data sets from very diverse domains, namely actuarial
science, environmental science and survival analysis.


title:
Nonparametric causal inference from observational time series through
  marginal integration

abstract:
  Causal inference from observational data is an ambitious but highly relevant
task, with diverse applications ranging from natural to social sciences. Within
the scope of nonparametric time series, causal inference defined through
interventions (cf. Pearl (2000)) is largely unexplored, although time order
simplifies the problem substantially. We consider a marginal integration scheme
for inferring causal effects from observational time series data, MINT-T
(marginal integration in time series), which is an adaptation for time series
of a method proposed by Ernest and B\"{u}hlmann (Electron. J. Statist, pp.
3155-3194, vol. 9, 2015) for the case of independent data. Our approach for
stationary stochastic processes is fully nonparametric and, assuming no
instantaneous effects consistently recovers the total causal effect of a single
intervention with optimal one-dimensional nonparametric convergence rate
$n^{-2/5}$ assuming regularity conditions and twice differentiability of a
certain corresponding regression function. Therefore, MINT-T remains largely
unaffected by the curse of dimensionality as long as smoothness conditions hold
in higher dimensions and it is feasible for a large class of stationary time
series, including nonlinear and multivariate processes. For the case with
instantaneous effects, we provide a procedure which guards against false
positive causal statements.


title:
Decentralized Simultaneous Information and Energy Transmission in K-User
  Multiple Access Channels

abstract:
  In this paper, the fundamental limits of decentralized simultaneous
information and energy transmission in the $K$-user Gaussian multiple access
channel (G-MAC), with an arbitrary $K \geqslant 2$ and one non-colocated energy
harvester (EH), are fully characterized.
  The objective of the transmitters is twofold. First, they aim to reliably
communicate their message indices to the receiver; and second, to harvest
energy at the EH at a rate not less than a minimum rate requirement $b$. The
information rates $R_1,\dots,R_K$, in bits per channel use, are measured at the
receiver and the energy rate $B$ is measured at an EH.
  Stability is considered in the sense of an $\eta$-Nash equilibrium
($\eta$-NE), with $\eta > 0$.
  The main result is a full characterization of the $\eta$-NE
information-energy region, i.e., the set of information-energy rate tuples
$(R_1,\dots,R_K,B)$ that are achievable and stable in the G-MAC when:
  $(a)$ all the transmitters autonomously and independently tune their own
transmit configurations seeking to maximize their own information transmission
rates $R_1,\dots, R_K$; and
  $(b)$ all the transmitters jointly guarantee an energy transmission rate $B$
at the EH, such that $B \geqslant b$.
  Therefore, any rate tuple outside the $\eta$-NE region is not stable as there
always exists at least one transmitter able to increase by at least $\eta$ bits
per channel use its own information transmission rate by updating its own
transmit configuration.


title:
Search for anomalous quartic $ZZ\gamma\gamma$ couplings in photon-photon
  collisions

abstract:
  The self-couplings of the electroweak gauge bosons are completely specified
by the non-Abelian gauge nature of the Standard Model (SM). The direct study of
these couplings provides a significant opportunity to test the validity of the
SM and the existence of new physics beyond the SM up to the high energy scale.
For this reason, we investigate the potential of the processes
$\gamma\gamma\rightarrow ZZ$, $e^{-}\gamma\rightarrow e^{-}\gamma^{*}\gamma
\rightarrow e^{-}Z\, Z$ and $e^{+}e^{-} \rightarrow e^{+}\gamma^{*} \gamma^{*}
e^{-} \rightarrow e^{+}\, Z\, Z\, e^{-}$ to examine the anomalous quartic
couplings of $ZZ\gamma\gamma$ vertex at the Compact Linear Collider (CLIC) with
center-of-mass energy $3$ TeV. We calculate $95\%$ confidence level
sensitivities on the dimension-8 parameters with various values of the
integrated luminosity. We show that the best bounds on the anomalous
$\frac{f_{M2}}{\Lambda^{4}}$, $\frac{f_{M3}}{\Lambda^{4}}$,
$\frac{f_{T0}}{\Lambda^4}$ and $\frac{f_{T9}}{\Lambda^4}$ couplings arise from
$\gamma\gamma\rightarrow ZZ$ process among those three processes at
center-of-mass energy of 3 TeV and integrated luminosity of $L_{int}=2000$
fb$^{-1}$ are found to be $[-3.30;3.30]\times 10 ^{-3}$ TeV$^{-4}$,
$[-1.20;1.20]\times 10 ^{-2}$ TeV$^{-4}$, $[-3.40;3.40]\times 10 ^{-3}$
TeV$^{-4}$ and $[-1.80;1.80]\times 10 ^{-3}$ TeV$^{-4}$, respectively.


title: Survey of Distributed Decision

abstract:
  We survey the recent distributed computing literature on checking whether a
given distributed system configuration satisfies a given boolean predicate,
i.e., whether the configuration is legal or illegal w.r.t. that predicate. We
consider classical distributed computing environments, including mostly
synchronous fault-free network computing (LOCAL and CONGEST models), but also
asynchronous crash-prone shared-memory computing (WAIT-FREE model), and mobile
computing (FSYNC model).


title:
Adversarial Perturbations Against Deep Neural Networks for Malware
  Classification

abstract:
  Deep neural networks, like many other machine learning models, have recently
been shown to lack robustness against adversarially crafted inputs. These
inputs are derived from regular inputs by minor yet carefully selected
perturbations that deceive machine learning models into desired
misclassifications. Existing work in this emerging field was largely specific
to the domain of image classification, since the high-entropy of images can be
conveniently manipulated without changing the images' overall visual
appearance. Yet, it remains unclear how such attacks translate to more
security-sensitive applications such as malware detection - which may pose
significant challenges in sample generation and arguably grave consequences for
failure.
  In this paper, we show how to construct highly-effective adversarial sample
crafting attacks for neural networks used as malware classifiers. The
application domain of malware classification introduces additional constraints
in the adversarial sample crafting problem when compared to the computer vision
domain: (i) continuous, differentiable input domains are replaced by discrete,
often binary inputs; and (ii) the loose condition of leaving visual appearance
unchanged is replaced by requiring equivalent functional behavior. We
demonstrate the feasibility of these attacks on many different instances of
malware classifiers that we trained using the DREBIN Android malware data set.
We furthermore evaluate to which extent potential defensive mechanisms against
adversarial crafting can be leveraged to the setting of malware classification.
While feature reduction did not prove to have a positive impact, distillation
and re-training on adversarially crafted samples show promising results.


title:
Theoretical description of circular dichroism in photoelectron angular
  distributions of randomly oriented chiral molecules after multi-photon
  photoionization

abstract:
  Photoelectron circular dichroism refers to the forward/backward asymmetry in
the photoelectron angular distribution with respect to the propagation axis of
circularly polarized light. It has recently been demonstrated in femtosecond
multi-photon photoionization experiments with randomly oriented camphor and
fenchone molecules [C. Lux et al., Angew. Chem. Int. Ed. 51, 5001 (2012);C. S.
Lehmann et al., J. Chem. Phys. 139, 234307 (2013)]. A theoretical framework
describing this process as (2+1) resonantly enhanced multi-photon ionization is
constructed, which consists of two-photon photoselection from randomly oriented
molecules and successive one-photon ionisation of the photoselected molecules.
It combines perturbation theory for the light-matter interaction with ab initio
calculations for the two-photon absorption and a single-center expansion of the
photoelectron wavefunction in terms of hydrogenic continuum functions. It is
verified that the model correctly reproduces the basic symmetry behavior
expected under exchange of handedness and light helicity. When applied it to
fenchone and camphor, semi-quantitative agreement with the experimental data is
found, for which a sufficient d wave character of the electronically excited
intermediate state is crucial.


title:
Influence of incoherent scattering on stochastic deflection of
  high-energy negative particle beams in bent crystals

abstract:
  An investigation on stochastic deflection of high-energy negatively charged
particles in a bent crystal was carried out. On the basis of analytical
calculation and numerical simulation it was shown that it exists a maximum
angle at which most of the beam is deflected. The existence of a maximum, which
is taken in the correspondence of the optimal radius of curvature, is a novelty
with respect to the case of positively charged particles, for which the
deflection angle can be freely increased by increasing the crystal length. This
difference has to be ascribed to the stronger contribution of incoherent
scattering affecting the dynamics of negative particles that move closer to
atomic nuclei and electrons. We therefore identified the ideal parameters for
the exploitation of axial confinement for negatively charged particle beam
manipulation in future high-energy accelerators, e.g., ILC or muon colliders.


title: Distributed chaos in turbulent wakes

abstract:
  Soft and hard spontaneous breaking of space translational symmetry
(homogeneity) have been studied in turbulent wakes by means of distributed
chaos. In the case of the soft translational symmetry breaking the vorticity
correlation integral $\int_{V} \langle {\boldsymbol \omega} ({\bf x},t) \cdot
{\boldsymbol \omega} ({\bf x} + {\bf r},t) \rangle_{V} d{\bf r}$ dominates the
distributed chaos and the chaotic spectra $\exp-(k/k_{\beta})^{\beta }$ have
$\beta =1/2$. In the case of the hard translational symmetry breaking, control
on the distributed chaos is switched from one type of fundamental symmetry to
another (in this case to Lagrangian relabeling symmetry). Due to the Noether's
theorem the relabeling symmetry results in the inviscid helicity conservation
and helicity correlation integral $I=\int \langle h({\bf x},t)~h({\bf x}+{\bf
r}, t)\rangle d{\bf r}$ (Levich-Tsinober invariant) dominates the distributed
chaos with $\beta =1/3$. Good agreement with the experimental data has been
established for turbulent wakes behind a cylinder, behind grids (for normal and
super-fluids) and for bubbling flows. In the last case even small concentration
of bubbles leads to a drastic change of the turbulent velocity spectra due to
the hard spontaneous symmetry breaking in the bubbles' wakes.


title: Atlases for Ineffective Orbifolds

abstract:
  We give a definition of atlases for ineffective orbifolds, and prove that
this definition leads to the same notion of orbifold as that defined via
topological groupoids.


title:
Stability Analysis of C-band 500-kW Klystron with Multi-cell Output
  cavity

abstract:
  A progogype 5-GHz 500-kW CW klystron (model E3762 provided by Toshiba
Electron Tubes & Devices Co. Ltd.) has been operating as the RF source for the
lower hybrid current drive (LHCD) system in the KSTAR tokamak. In order to
investigate how the efficiency of the 5-GHz 500-kW CW klystron prototype could
be enhanced, the cavity design study is being carried out with simulation code
based on the main klystron operation parameters. This is being done by
simulating klystron performances for various cavity parameters including the
number of cavities, inter-cavity distance, and cavity tuning frequencies. The
simulation has been done with the FCI (field charge interaction) code aided by
a matlab script for scanning input parameters. Initial set of scan parameters
was obtained by benchmarking the E3762 klystron. It was possible to obtain
optimized design parameters with better efficiency for a cavity system adopting
a multi-cell output cavity. However, the multi-cell output cavity is prone to
produce a self-oscillation due to the prolonged (several half RF periods)
beam-field interaction along its multiple gaps. We have checked the feasibility
of the optimization by evaluating the stability of output cavity system. The
stability is given by the ratio of a beam-loading conductance to the circuit
conductance.


title: Coleman Map in Coleman Families

abstract:
  In this paper, we aimed at constructing a two-variable Coleman map for a
given $p$-adic family of eigen cuspforms with a fixed non-zero slope (Coleman
family). A Coleman map is a machinary which transforms a hypothetical $p$-adic
family of zeta elements to a $p$-adic $L$-function. The result would be a
non-ordinary generalization of a two-variable Coleman map for a given Hida
deformation obtained by the second-named author.


title: DeepMath - Deep Sequence Models for Premise Selection

abstract:
  We study the effectiveness of neural sequence models for premise selection in
automated theorem proving, one of the main bottlenecks in the formalization of
mathematics. We propose a two stage approach for this task that yields good
results for the premise selection task on the Mizar corpus while avoiding the
hand-engineered features of existing state-of-the-art models. To our knowledge,
this is the first time deep learning has been applied to theorem proving on a
large scale.


title:
A scalable end-to-end Gaussian process adapter for irregularly sampled
  time series classification

abstract:
  We present a general framework for classification of sparse and
irregularly-sampled time series. The properties of such time series can result
in substantial uncertainty about the values of the underlying temporal
processes, while making the data difficult to deal with using standard
classification methods that assume fixed-dimensional feature spaces. To address
these challenges, we propose an uncertainty-aware classification framework
based on a special computational layer we refer to as the Gaussian process
adapter that can connect irregularly sampled time series data to any black-box
classifier learnable using gradient descent. We show how to scale up the
required computations based on combining the structured kernel interpolation
framework and the Lanczos approximation method, and how to discriminatively
train the Gaussian process adapter in combination with a number of classifiers
end-to-end using backpropagation.


title: Statistical mechanics of covariant systems with multi-fingered time

abstract:
  Recently, in [Class. Quantum Grav. 33 (2016) 045005], the authors proposed a
new approach extending the framework of statistical mechanics to
reparametrization-invariant systems with no additional gauges. In this work,
the approach is generalized to systems defined by more than one Hamiltonian
constraints (multi-fingered time). We show how well known features as the
Ehrenfest- Tolman effect and the J\"uttner distribution for the relativistic
gas can be consistently recovered from a covariant approach in the
multi-fingered framework. Eventually, the crucial role played by the
interaction in the definition of a global notion of equilibrium is discussed.


title: A consistent model for leptogenesis, dark matter and the IceCube signal

abstract:
  We discuss a left-right symmetric extension of the Standard Model in which
the three additional right-handed neutrinos play a central role in explaining
the baryon asymmetry of the Universe, the dark matter abundance and the ultra
energetic signal detected by the IceCube experiment. The energy spectrum and
neutrino flux measured by IceCube are ascribed to the decays of the lightest
right-handed neutrino $N_1$, thus fixing its mass and lifetime, while the
production of $N_1$ in the primordial thermal bath occurs via a freeze-in
mechanism driven by the additional $SU(2)_R$ interactions. The constraints
imposed by IceCube and the dark matter abundance allow nonetheless the heavier
right-handed neutrinos to realize a standard type-I seesaw leptogenesis, with
the $B-L$ asymmetry dominantly produced by the next-to-lightest neutrino $N_2$.
Further consequences and predictions of the model are that: the $N_1$
production implies a specific power-law relation between the reheating
temperature of the Universe and the vacuum expectation value of the $SU(2)_R$
triplet; leptogenesis imposes a lower bound on the reheating temperature of the
Universe at $7\times10^9\,\mbox{GeV}$. Additionally, the model requires a
vanishing absolute neutrino mass scale $m_1\simeq0$.


title:
Attend Refine Repeat: Active Box Proposal Generation via In-Out
  Localization

abstract:
  The problem of computing category agnostic bounding box proposals is utilized
as a core component in many computer vision tasks and thus has lately attracted
a lot of attention. In this work we propose a new approach to tackle this
problem that is based on an active strategy for generating box proposals that
starts from a set of seed boxes, which are uniformly distributed on the image,
and then progressively moves its attention on the promising image areas where
it is more likely to discover well localized bounding box proposals. We call
our approach AttractioNet and a core component of it is a CNN-based category
agnostic object location refinement module that is capable of yielding accurate
and robust bounding box predictions regardless of the object category.
  We extensively evaluate our AttractioNet approach on several image datasets
(i.e. COCO, PASCAL, ImageNet detection and NYU-Depth V2 datasets) reporting on
all of them state-of-the-art results that surpass the previous work in the
field by a significant margin and also providing strong empirical evidence that
our approach is capable to generalize to unseen categories. Furthermore, we
evaluate our AttractioNet proposals in the context of the object detection task
using a VGG16-Net based detector and the achieved detection performance on COCO
manages to significantly surpass all other VGG16-Net based detectors while even
being competitive with a heavily tuned ResNet-101 based detector. Code as well
as box proposals computed for several datasets are available at::
https://github.com/gidariss/AttractioNet.


title: Shedding vertices of vertex decomposable graphs

abstract:
  We focus our attention on well-covered graphs that are vertex decomposable.
We show that for many known families of these vertex decomposable graphs, the
set of shedding vertices forms a dominating set. We then construct three new
infinite families of well-covered graphs, none of which have this property. We
use these results to provide a minimal counterexample to a conjecture of
Villarreal regarding Cohen-Macaulay graphs.


title: Abelian tensor hierarchy in 4D ${\cal N}=1$ conformal supergravity

abstract:
  We consider Abelian tensor hierarchy in four-dimensional ${\cal N}=1$
supergravity in the conformal superspace formalism, where the so-called
covariant approach is used to antisymmetric tensor fields. We introduce
$p$-form gauge superfields as superforms in the conformal superspace. We solve
the Bianchi identities under the constraints for the superforms. As a result,
each of form fields is expressed by a single gauge invariant superfield. The
action of superforms is shown with the invariant superfields. We also show the
relation between the superspace formalism and the superconformal tensor
calculus.


title:
Recurrent neural network training with preconditioned stochastic
  gradient descent

abstract:
  This paper studies the performance of a recently proposed preconditioned
stochastic gradient descent (PSGD) algorithm on recurrent neural network (RNN)
training. PSGD adaptively estimates a preconditioner to accelerate gradient
descent, and is designed to be simple, general and easy to use, as stochastic
gradient descent (SGD). RNNs, especially the ones requiring extremely long term
memories, are difficult to train. We have tested PSGD on a set of synthetic
pathological RNN learning problems and the real world MNIST handwritten digit
recognition task. Experimental results suggest that PSGD is able to achieve
highly competitive performance without using any trick like preprocessing,
pretraining or parameter tweaking.


title: Multiple Human Tracking in RGB-D Data: A Survey

abstract:
  Multiple human tracking (MHT) is a fundamental task in many computer vision
applications. Appearance-based approaches, primarily formulated on RGB data,
are constrained and affected by problems arising from occlusions and/or
illumination variations. In recent years, the arrival of cheap RGB-Depth
(RGB-D) devices has {led} to many new approaches to MHT, and many of these
integrate color and depth cues to improve each and every stage of the process.
In this survey, we present the common processing pipeline of these methods and
review their methodology based (a) on how they implement this pipeline and (b)
on what role depth plays within each stage of it. We identify and introduce
existing, publicly available, benchmark datasets and software resources that
fuse color and depth data for MHT. Finally, we present a brief comparative
evaluation of the performance of those works that have applied their methods to
these datasets.


title: Metal-insulator transition in films of doped semiconductor nanocrystals

abstract:
  To fully deploy the potential of semiconductor nanocrystal films as low-cost
electronic materials, a better understanding of the amount of dopants required
to make their conductivity metallic is needed. In bulk semiconductors, the
critical concentration of electrons at the metal-insulator transition is
described by the Mott criterion. Here, we theoretically derive the critical
concentration $n_c$ for films of heavily doped nanocrystals devoid of ligands
at their surface and in direct contact with each other. In the accompanying
experiments, we investigate the conduction mechanism in films of
phosphorus-doped, ligand-free silicon nanocrystals. At the largest electron
concentration achieved in our samples, which is half the predicted $n_c$, we
find that the localization length of hopping electrons is close to three times
the nanocrystals diameter, indicating that the film approaches the
metal-insulator transition.


title: On the bifurcation for fractional Laplace equations

abstract:
  In this paper, we consider the bifurcation problem for fractional Laplace
equation \begin{eqnarray*} \begin{array}{ll} (-\Delta)^{s} u = \lambda u +
f(\lambda,\,x,\,u)& \mbox{in }\Omega, u = 0 &\mbox{in }\mathbb{R}^n\backslash
\Omega, \end{array} \end{eqnarray*} where $\Omega\subset \mathbb{R}^n,\,n> 2s
(0<s<1)$ is an open bounded subset with smooth boundary, $(-\Delta)^{s}$ stands
for the fractional Laplacian. We show that a continuum of solutions bifurcates
out from the principal eigenvalue $\lambda_1$ of the eigenvalue problem
\begin{eqnarray*} \begin{gathered} (-\Delta)^{s} v = \lambda
v\,\,\,\mbox{in}\,\,\Omega, v = 0 \,\,\,\,\mbox{in}\,\,\,\,\mathbb{R}^n
\backslash\Omega, \end{gathered} \end{eqnarray*} and, conversely.


title:
Langevin Equation for a Dissipative Macroscopic Quantum System: Bohmian
  Theory versus Quantum Mechanics

abstract:
  In this study, we solve analytically the Schrodinger equation for a
macroscopic quantum oscillator as a central system coupled to a large number of
environmental micro-oscillating particles. Then, the Langevin equation is
obtained for the system using two approaches: Quantum Mechanics and Bohmian
Theory. Our results show that the predictions of the two theories are
inherently different in real conditions. Nevertheless, the Langevin equation
obtained by Bohmian approach could be reduced to the quantum one, when the
vibrational frequency of the central system is high enough compared to the
maximum frequency of the environmental particles.


title:
Simulation of incompressible two-phase flow in porous media with large
  timesteps

abstract:
  Multiphase flow in porous media occurs in several disciplines including
petroleum reservoir engineering, petroleum systems' analysis, and CO$_2$
sequestration. While simulations often use a fully implicit discretization to
increase the time step size, restrictions on the time step often exist due to
non-convergence of the nonlinear solver (e.g. Newton's method). Here this
problem is addressed for the Buckley-Leverett equations, which model
incompressible, immiscible, two-phase flow with no capillary potential. The
equations are recast as a gradient flow using the phase-field method, and a
convex energy splitting scheme is applied to enable large timesteps, even for
high degrees of heterogeneity in permeability and viscosity. By using the
phase-field formulation as a homotopy map, the underlying hyperbolic flow
equations can be solved with large timesteps. For a heterogeneous test problem,
the new homotopy method allows the timestep to be increased by more than six
orders of magnitude relative to the unmodified equations while maintaining
convergence.


title: A Generalization of Lifting Non-proper Tropical Intersections

abstract:
  Let X and X' be closed subschemes of an algebraic torus T over a
non-archimedean field. We prove the rational equivalence as tropical cycles, in
the sense of Henning Meyer's graduate thesis, between the tropicalization of
the intersection product of X and X' and the stable intersection of trop(X) and
trop(X'), when restricted to (the inverse image under the tropicalization map
of) a connected component C of the intersection of trop(X) and trop(X'). This
requires possibly passing to a (partial) compactification of T with respect to
a suitable fan. We define the compactified stable intersection in a toric
tropical variety, and check that this definition is compatible with the
intersection product in loc.cit.. As a result we get a numerical equivalence
(after a compactification and restricting to C) between the intersection
product of X and X' and the stable intersection of trop(X) and trop(X') via the
compactified stable intersection. In particular, when X and X' have
complementary codimensions, this equivalence generalizes the work of Osserman
and Rabinoff, in the sense that the intersection of X and X' is allowed to be
of positive dimension. Moreover, if the intersection of the closures of X and
X' has finitely many points which tropicalize to the closure of C, we prove a
similar equation as in Theorem 6.4 of the paper of Osserman and Rabinoff when
the ambient space is a reduced closed subscheme of T (instead of T itself).


title:
Towards Operator-less Data Centers Through Data-Driven, Predictive,
  Proactive Autonomics

abstract:
  Continued reliance on human operators for managing data centers is a major
impediment for them from ever reaching extreme dimensions. Large computer
systems in general, and data centers in particular, will ultimately be managed
using predictive computational and executable models obtained through
data-science tools, and at that point, the intervention of humans will be
limited to setting high-level goals and policies rather than performing
low-level operations. Data-driven autonomics, where management and control are
based on holistic predictive models that are built and updated using live data,
opens one possible path towards limiting the role of operators in data centers.
In this paper, we present a data-science study of a public Google dataset
collected in a 12K-node cluster with the goal of building and evaluating
predictive models for node failures. Our results support the practicality of a
data-driven approach by showing the effectiveness of predictive models based on
data found in typical data center logs. We use BigQuery, the big data SQL
platform from the Google Cloud suite, to process massive amounts of data and
generate a rich feature set characterizing node state over time. We describe
how an ensemble classifier can be built out of many Random Forest classifiers
each trained on these features, to predict if nodes will fail in a future
24-hour window. Our evaluation reveals that if we limit false positive rates to
5%, we can achieve true positive rates between 27% and 88% with precision
varying between 50% and 72%.This level of performance allows us to recover
large fraction of jobs' executions (by redirecting them to other nodes when a
failure of the present node is predicted) that would otherwise have been wasted
due to failures. [...]


title: Bayesian mixture modeling for multivariate conditional distributions

abstract:
  We present a Bayesian mixture model for estimating the joint distribution of
mixed ordinal, nominal, and continuous data conditional on a set of fixed
variables. The model uses multivariate normal and categorical mixture kernels
for the random variables. It induces dependence between the random and fixed
variables through the means of the multivariate normal mixture kernels and via
a truncated local Dirichlet process. The latter encourages observations with
similar values of the fixed variables to share mixture components. Using a
simulation of data fusion, we illustrate that the model can estimate underlying
relationships in the data and the distributions of the missing values more
accurately than a mixture model applied to the random and fixed variables
jointly. We use the model to analyze consumers' reading behaviors using a quota
sample, i.e., a sample where the empirical distribution of some variables is
fixed by design and so should not be modeled as random, conducted by the book
publisher HarperCollins.


title:
Secure Compute-and-Forward Transmission With Artificial Noise and
  Full-Duplex Devices

abstract:
  We consider a wiretap channel with an eavesdropper (Eve) and an honest but
curious relay (Ray). Ray and the destination (Bob) are full-duplex (FD)
devices. Since we aim at not revealing information on the secret message to the
relay, we consider the scaled compute-and-forward (SCF) where scaled lattice
coding is used in the transmission by both the source (Alice) and Bob in order
to allow Ray to decode only a linear combination of the two messages. At the
same time Ray transmits artificial noise (AN) to confuse Eve. When Ray relays
the decoded linear combination, Alice and Bob are transmitting AN against Eve.
This can be a 5G cellular communication scenario where a mobile terminal (MT)
aims at transmitting a secret message to a FD base station (BS), with the
assistance of a network FD relay. With respect to existing literature the
innovations of this paper are: a) Bob and Ray are FD devices; b) Alice, Ray and
Bob transmit also AN; and c) the channel to Eve is not known to Alice, Bob and
Ray. For this scenario we derive bounds on both the secrecy outage probability
under Rayleigh fading conditions of the channels to Eve, and the achievable
secrecy-outage rates.


title: Tessellations

abstract:
  A survey of tessellations, which appeared in Italian in La Matematica vol 3
in 2010. The Tiling Lemma appears for the first time.


title: Model-Free Episodic Control

abstract:
  State of the art deep reinforcement learning algorithms take many millions of
interactions to attain human-level performance. Humans, on the other hand, can
very quickly exploit highly rewarding nuances of an environment upon first
discovery. In the brain, such rapid learning is thought to depend on the
hippocampus and its capacity for episodic memory. Here we investigate whether a
simple model of hippocampal episodic control can learn to solve difficult
sequential decision-making tasks. We demonstrate that it not only attains a
highly rewarding strategy significantly faster than state-of-the-art deep
reinforcement learning algorithms, but also achieves a higher overall reward on
some of the more challenging domains.


title: Characterization of Completely $k$-Magic Regular Graphs

abstract:
  Let $k \in \mathbb{N}$ and $c \in \mathbb{Z}_k$, where
$\mathbb{Z}_1=\mathbb{Z}$. A graph $G=(V(G),E(G))$ is said to be $c$-sum
$k$-magic if there is a labeling $\ell:E(G) \rightarrow \mathbb{Z}_k \setminus
\{0\}$ such that $\sum_{u \in N(v)} \ell(uv) \equiv c \pmod{k}$ for every
vertex $v$ of $G$, where $N(v)$ is the neighborhood of $v$ in $G$. We say that
$G$ is completely $k$-magic whenever it is $c$-sum $k$-magic for every $c \in
\mathbb{Z}_k$. In this paper, we characterize all completely $k$-magic regular
graphs.


title: Double-Slit Interference Pattern for a Macroscopic Quantum System

abstract:
  In this study, we solve analytically the Schrodinger equation for a
macroscopic quantum oscillator as a central system coupled to two environmental
micro-oscillating particles. Then, the double-slit interference patterns are
investigated in two limiting cases, considering the limits of uncertainty in
the position probability distribution. Moreover, we analyze the interference
patterns based on a recent proposal called stochastic electrodynamics with
spin. Our results show that when the quantum character of the macro-system is
decreased, the diffraction pattern becomes more similar to a classical one. We
also show that, depending on the size of the slits, the predictions of quantum
approach could be apparently different with those of the aforementioned
stochastic description


title: Adinkras, Dessins, Origami, and Supersymmetry Spectral Triples

abstract:
  We investigate the spectral geometry and spectral action functionals
associated to 1D Supersymmetry Algebras, using the classification of these
superalgebras in terms of Adinkra graphs and the construction of associated
dessin d'enfant and origami curves. The resulting spectral action functionals
are computed in terms of the Selberg (super) trace formula.


title:
Sequential geophysical and flow inversion to characterize fracture
  networks in subsurface systems

abstract:
  Subsurface applications including geothermal, geological carbon
sequestration, oil and gas, etc., typically involve maximizing either the
extraction of energy or the storage of fluids. Characterizing the subsurface is
extremely complex due to heterogeneity and anisotropy. Due to this complexity,
there are uncertainties in the subsurface parameters, which need to be
estimated from multiple diverse as well as fragmented data streams. In this
paper, we present a non-intrusive sequential inversion framework, for
integrating data from geophysical and flow sources to constraint subsurface
Discrete Fracture Networks (DFN). In this approach, we first estimate bounds on
the statistics for the DFN fracture orientations using microseismic data. These
bounds are estimated through a combination of a focal mechanism (physics-based
approach) and clustering analysis (statistical approach) of seismic data. Then,
the fracture lengths are constrained based on the flow data. The efficacy of
this multi-physics based sequential inversion is demonstrated through a
representative synthetic example.

categories: cs.CE math.NA physics.comp-ph physics.geo-ph stat.ML


title: Vainshtein mechanism in general purely disformal gravity theory

abstract:
  We study a theory of gravity in which the action is a result from the general
purely disformal transformation on the Einstein-Hilbert action. This theory is
a sub-class of GLPV theory which is the the generalization of covariant
Galileon. Nevertheless, we find that the self accelerating solution for the
background universe disappears in this theory. We also find that, for this
theory, the Vainshtein mechanism is absent. However, the Vainshtein mechanism
is not necessary for this theory, because this theory can nearly mimic the
Einstein theory of gravity at all scales inside the Huble radius without this
mechanism.


title: Neural Networks and Continuous Time

abstract:
  The fields of neural computation and artificial neural networks have
developed much in the last decades. Most of the works in these fields focus on
implementing and/or learning discrete functions or behavior. However,
technical, physical, and also cognitive processes evolve continuously in time.
This cannot be described directly with standard architectures of artificial
neural networks such as multi-layer feed-forward perceptrons. Therefore, in
this paper, we will argue that neural networks modeling continuous time are
needed explicitly for this purpose, because with them the synthesis and
analysis of continuous and possibly periodic processes in time are possible
(e.g. for robot behavior) besides computing discrete classification functions
(e.g. for logical reasoning). We will relate possible neural network
architectures with (hybrid) automata models that allow to express continuous
processes.


title:
Outer Bounds on the Storage-Repair Bandwidth Tradeoff of Exact-Repair
  Regenerating Codes

abstract:
  In this paper, three outer bounds on the normalized storage-repair bandwidth
(S-RB) tradeoff of regenerating codes having parameter set
$\{(n,k,d),(\alpha,\beta)\}$ under the exact-repair (ER) setting are presented.
The first outer bound is applicable for every parameter set $(n,k,d)$ and in
conjunction with a code construction known as {\em improved layered codes}, it
characterizes the normalized ER tradeoff for the case $(n,k=3,d=n-1)$. It
establishes a non-vanishing gap between the ER and functional-repair (FR)
tradeoffs for every $(n,k,d)$. The second bound is an improvement upon an
existing bound due to Mohajer et al. and is tighter than the first bound, in a
regime away from the Minimum Storage Regeneraing (MSR) point. The third bound
is for the case of $k=d$, under the linear setting. This outer bound matches
with the achievable region of {\em layered codes} thereby characterizing the
normalized ER tradeoff of linear ER codes when $k=d=n-1$.