title: A Traversable Fixed Size Small Object Allocator in C++

abstract:
  At the allocation and deallocation of small objects with fixed size, the
standard allocator of the runtime system has commonly a worse time performance
compared to allocators adapted for a special application field. We propose a
memory allocator, originally developed for mesh primitives but also usable for
any other small equally sized objects. For a large amount of objects it leads
to better results than allocating data with the C ++new instruction and behaves
nowhere worse. The proposed synchronization approach for this allocator behaves
lock-free in practical scenarios without using machine instructions, such as
compare-and-swap. A traversal structure is integrated requiring less memory
than using containers such as STL-vectors or lists, but with comparable time
performance.


title: Relative Currents

abstract:
  In this paper we define currents relative to a free factor system. We prove
that a fully irreducible outer automorphism relative to a free factor system
acts with uniform north-south dynamics on a subspace of the space of projective
relative currents.


title:
Spaces with $\mathbb{G}_m$-action, hyperbolic localization and nearby
  cycles

abstract:
  We study families of algebraic spaces with a fiberwise $\mathbb{G}_m$-action
and prove Braden's theorem on hyperbolic localization for arbitrary base
schemes. As an application, we obtain that hyperbolic localization commutes
with nearby cycles.


title:
Berry phase, Berry Connection, and Chern Number for a Continuum
  Bianisotropic Material from a Classical Electromagnetics Perspective

abstract:
  The properties that quantify photonic topological insulators (PTIs), Berry
phase, Berry connection, and Chern number, are typically obtained by making
analogies between classical Maxwell's equations and the quantum mechanical
Schr\"{o}dinger equation, writing both in Hamiltonian form. However, the
aforementioned quantities are not necessarily quantum in nature, and for
photonic systems they can be explained using only classical concepts. Here we
provide a derivation and description of PTI quantities using classical
Maxwell's equations, we demonstrate how an electromagnetic mode can acquire
Berry phase, and we discuss the ramifications of this effect. We consider
several examples, including wave propagation in a biased plasma, and radiation
by a rotating isotropic emitter. These concepts are discussed without invoking
quantum mechanics, and can be easily understood from an engineering
electromagnetics perspective.


title:
A New Track Reconstruction Algorithm suitable for Parallel Processing
  based on Hit Triplets and Broken Lines

abstract:
  Track reconstruction in high track multiplicity environments at current and
future high rate particle physics experiments is a big challenge and very time
consuming. The search for track seeds and the fitting of track candidates are
usually the most time consuming steps in the track reconstruction. Here, a new
and fast track reconstruction method based on hit triplets is proposed which
exploits a three-dimensional fit model including multiple scattering and hit
uncertainties from the very start, including the search for track seeds. The
hit triplet based reconstruction method assumes a homogeneous magnetic field
which allows to give an analytical solutions for the triplet fit result. This
method is highly parallelizable, needs fewer operations than other standard
track reconstruction methods and is therefore ideal for the implementation on
parallel computing architectures. The proposed track reconstruction algorithm
has been studied in the context of the Mu3e-experiment and a typical LHC
experiment.


title:
Oscillating magnetoresistance due to fragile spin structure in metallic
  GdPd$_3$

abstract:
  Studies on the phenomenon of magnetoresistance (MR) have produced intriguing
and application-oriented outcomes for decades--colossal MR, giant MR and
recently discovered extremely large MR of millions of percents in semimetals
can be taken as examples. We report here the investigation of oscillating MR in
a cubic intermetallic compound GdPd$_3$, which is the only compound that
exhibits MR oscillations between positive and negative values. Our study shows
that a very strong correlation between magnetic, electrical and
magnetotransport properties is present in this compound. The magnetic structure
in GdPd$_3$ is highly fragile since applied magnetic fields of moderate
strength significantly alter the spin arrangement within the system--a behavior
that manifests itself in the oscillating MR. Intriguing magnetotransport
characteristics of GdPd$_3$ are appealing for field-sensitive device
applications, especially if the MR oscillation could materialize at higher
temperature by manipulating the magnetic interaction through perturbations
caused by chemical substitutions.


title: Generative Multi-Adversarial Networks

abstract:
  Generative adversarial networks (GANs) are a framework for producing a
generative model by way of a two-player minimax game. In this paper, we propose
the \emph{Generative Multi-Adversarial Network} (GMAN), a framework that
extends GANs to multiple discriminators. In previous work, the successful
training of GANs requires modifying the minimax objective to accelerate
training early on. In contrast, GMAN can be reliably trained with the original,
untampered objective. We explore a number of design perspectives with the
discriminator role ranging from formidable adversary to forgiving teacher.
Image generation tasks comparing the proposed framework to standard GANs
demonstrate GMAN produces higher quality samples in a fraction of the
iterations when measured by a pairwise GAM-type metric.


title: On non-secant defectivity of Segre-Veronese varieties

abstract:
  Let $SV^{\pmb n}_{\pmb d}$ be the Segre-Veronese given as the image of the
embedding induced by the line bundle
$\mathcal{O}_{\mathbb{P}^{n_1}\times\dots\times\mathbb{P}^{n_r}}(d_1,\dots,
d_r)$. We prove that asymptotically $SV^{\pmb n}_{\pmb d}$ is not $h$-defective
for $h\leq n_1^{\lfloor \log_2(d-1)\rfloor}$.


title: A simple method for implementing Monte Carlo tests

abstract:
  We consider a statistical test whose p-value can only be approximated using
Monte Carlo simulations. We are interested in deciding whether the p-value for
an observed data set lies above or below a given threshold such as 5%. We want
to ensure that the resampling risk, the probability of the (Monte Carlo)
decision being different from the true decision, is uniformly bounded. This
article introduces a simple open-ended method with this property, the
confidence sequence method (CSM). We compare our approach to another algorithm,
SIMCTEST, which also guarantees an (asymptotic) uniform bound on the resampling
risk, as well as to other Monte Carlo procedures without a uniform bound. CSM
is free of tuning parameters and conservative. It has the same theoretical
guarantee as SIMCTEST and, in many settings, similar stopping boundaries. As it
is much simpler than other methods, CSM is a useful method for practical
applications.


title: Symmetry, stability, and computation of degenerate lasing modes

abstract:
  We present a general method to obtain the stable lasing solutions for the
steady-state ab-initio lasing theory (SALT) for the case of a degenerate
symmetric laser in two dimensions (2d). We find that under most regimes (with
one pathological exception), the stable solutions are clockwise and
counterclockwise circulating modes, generalizing previously known results of
ring lasers to all 2d rotational symmetry groups. Our method uses a combination
of semi-analytical solutions close to lasing threshold and numerical solvers to
track the lasing modes far above threshold. Near threshold, we find closed-form
expressions for both circulating modes and other types of lasing solutions as
well as for their linearized Maxwell--Bloch eigenvalues, providing a simple way
to determine their stability without having to do a full nonlinear numerical
calculation. Above threshold, we show that a key feature of the circulating
mode is its "chiral" intensity pattern, which arises from spontaneous
symmetry-breaking of mirror symmetry, and whose symmetry group requires that
the degeneracy persists even when nonlinear effects become important. Finally,
we introduce a numerical technique to solve the degenerate SALT equations far
above threshold even when spatial discretization artificially breaks the
degeneracy.


title: Number of Wavevectors for Each Frequency in a Periodic Structure

abstract:
  Periodic structures have interesting acoustic and vibration properties making
them suitable for a wide variety of applications. In a periodic structure, the
number of frequencies for each wavevector depends on the degree of freedom of
the unit cell. In this paper, we investigate the number of wavevectors for each
frequency. This analysis defines the upper bound for the maximum number of
wavevectors for each frequency in a general periodic structure which might
include damping. Investigation presented in this paper can also provide an
insight for designing materials in which the interaction between unit cells is
not limited to the closest neighbor. As an example application of this work, we
investigate phonon dispersion curves in hexagonal form of Boron Nitride to show
that first neighbor interaction is not sufficient to model dispersion curves
with force-constant-model.


title:
Comparing learning algorithms in neural network for diagnosing
  cardiovascular disease

abstract:
  Today data mining techniques are exploited in medical science for diagnosing,
overcoming and treating diseases. Neural network is one of the techniques which
are widely used for diagnosis in medical field. In this article efficiency of
nine algorithms, which are basis of neural network learning in diagnosing
cardiovascular diseases, will be assessed. Algorithms are assessed in terms of
accuracy, sensitivity, transparency, AROC and convergence rate by means of 10
fold cross validation. The results suggest that in training phase, Lonberg-M
algorithm has the best efficiency in terms of all metrics, algorithm OSS has
maximum accuracy in testing phase, algorithm SCG has the maximum transparency
and algorithm CGB has the maximum sensitivity.


title:
Improved measurement of the hyperfine structure of the laser cooling
  level $4f^{12}(^3 H_6)5d_{5/2}6s^2$ $(J=9/2)$ in $^{169}$Tm

abstract:
  We report on the improved measurement of the hyperfine structure of
$4f^{12}(^3 H_6)5d_{5/2}6s^2$ $(J=9/2)$ excited state in Tm-169 which is
involved in the second-stage laser cooling of Tm. To measure the absolute value
of the hyperfine splitting interval we used Doppler-free frequency modulation
saturated absorption spectroscopy of Tm atoms in a vapor cell. The sign of the
hyperfine constant was determined independently by spectroscopy of laser cooled
Tm atoms. The hyperfine constant of the level equals $A_J=-422.112(32)$ MHz
that corresponds to the energy difference between two hyperfine sublevels of
$-2110.56(16)$~MHz. In relation to the saturated absorption measurement we
quantitatively treat contributions of various mechanisms into the line
broadening and shift. We consider power broadening in the case when Zeeman
sublevels of atomic levels are taken into account. We also discuss the line
broadening due to frequency modulation and relative intensities of transitions
in saturated-absorption experiments.


title: Monte Carlo methods in continuous time for lattice Hamiltonians

abstract:
  We solve a variety of sign problems for models in lattice field theory using
the Hamiltonian formulation, including Yukawa models and simple lattice gauge
theories. The solutions emerge naturally in continuous time and use the dual
representation for the bosonic fields. These solutions allow us to construct
quantum Monte Carlo methods for these problems. The methods could provide an
alternative approach to understanding non-perturbative dynamics of some lattice
field theories.


title: Excited Random Walk in a Markovian Environment

abstract:
  One dimensional excited random walk has been extensively studied for bounded,
i.i.d. cookie environments. In this case, many important properties of the walk
including transience or recurrence, positivity or non-positivity of the speed,
and the limiting distribution of the position of the walker are all
characterized by a single parameter $\delta$, the total expected drift per
site. In the more general case of stationary ergodic environments, things are
not so well understood. If all cookies are positive then the same threshold for
transience vs. recurrence holds, even if the cookie stacks are unbounded.
However, it is unknown if the threshold for transience vs. recurrence extends
to the case when cookies may be negative (even for bounded stacks), and
moreover there are simple counterexamples to show that the threshold for
positivity of the speed does not. It is thus natural to study the behavior of
the model in the case of Markovian environments, which are intermediate between
the i.i.d. and stationary ergodic cases. We show here that many of the
important results from the i.i.d. setting, including the thresholds for
transience and positivity of the speed, as well as the limiting distribution of
the position of the walker, extend to a large class of Markovian environments.
No assumptions are made about the positivity of the cookies.


title: Network model of human aging: frailty limits and information measures

abstract:
  Aging is associated with the accumulation of damage throughout a persons
life. Individual health can be assessed by the Frailty Index (FI). The FI is
calculated simply as the proportion $f$ of accumulated age related deficits
relative to the total, leading to a theoretical maximum of $f \leq 1$.
Observational studies have generally reported a much more stringent bound, with
$f \leq f_{max} <1$. The value of $f_{max}$ in observational studies appears to
be non-universal, but $f_{max} \approx 0.7$ is often reported. A previously
developed network model of individual aging was unable to recover $f_{max}<1$
while retaining the other observed phenomenology of increasing $f$ and
mortality rates with age. We have developed a computationally accelerated
network model that also allows us to tune the scale-free network exponent
$\alpha$. The network exponent $\alpha$ significantly affects the growth of
mortality rates with age. However, we are only able to recover $f_{max}$ by
also introducing a deficit sensitivity parameter $1-q$, which is equivalent to
a false-negative rate $q$. Our value of $q=0.3$ is comparable to finite
sensitivities of age-related deficits with respect to mortality that are often
reported in the literature. In light of non-zero $q$, we use mutual information
$I$ to provide a non-parametric measure of the predictive value of the FI with
respect to individual mortality. We find that $I$ is only modestly degraded by
$q<1$, and this degradation is mitigated when increasing number of deficits are
included in the FI. We also find that the information spectrum, i.e. the mutual
information of individual deficits vs connectivity, has an approximately
power-law dependence that depends on the network exponent $\alpha$. Mutual
information $I$ is therefore a useful tool for characterizing the network
topology of aging populations.


title: Simulations for Deep Random Secrecy Protocol

abstract:
  We present numerical simulations measuring secrecy and efficiency rate of
Perfect Secrecy protocol presented in former article named Perfect Secrecy
under Deep Random assumption. Those simulations specifically measure the
respective error rates of both legitimate partner and eavesdropper experimented
during the exchange of a data flow through the protocol. Those measured error
rates also enable us to estimate a lower bound of the Crytpologic Limit
introduced in article named Perfect Secrecy under Deep Random assumption. We
discuss the variation of the protocol parameters and their impact on the
measured performance.


title: Chromospherically Active Low-Mass Close Binary: KIC 9761199

abstract:
  In this study, we present the results obtained from KIC 9761199's the
photometrical data acquired by the Kepler Mission. The light curve of the
system, the sinusoidal variation out-of-eclipses and instant-short term flare
events in the entire light curves were analyzed. The temperature of the
secondary component was found to be 3891+-1 K, while the mass ratio of the
components (q) was found to be 0.69+-0.01, and the orbital inclination (i) was
computed as 77.4+-0.1 degrees. The sinusoidal variation is caused by the
stellar spots of two active regions separated by about 180 degrees
longitudinally located around the latitudes of +47 and +30 degrees. In
addition, 94 flares were detected and their parameters were computed. The OPEA
model was derived for these flares and its parameters were computed. The
Plateau value as saturation level for the active component was found to be
1.951+-0.069 s, while the half-life value was found to be 1014 s. The flare
frequency N1 was found to be 0.01351 per hour, while the flare frequency N2 was
found to be 0.00006. Maximum flare rise time (Tr) was found to be 1118.098 s,
while maximum flare total time (Tt) was found to be 6767.72 s. Comparing its
analogue it is seen that the chromospheric activity level of KIC 9761199, which
is a low-mass close binary system according to the light curve analyses, is an
expected level according to the (B-V) color index of 1.303 mag for the active
component.


title: A conceptual breakthrough in sphere packing

abstract:
  This expository paper describes Viazovska's breakthrough solution of the
sphere packing problem in eight dimensions, as well as its extension to
twenty-four dimensions by Cohn, Kumar, Miller, Radchenko, and Viazovska.


title: On the fractional probabilistic Taylor's and mean value theorems

abstract:
  In order to develop certain fractional probabilistic analogues of Taylor's
theorem and mean value theorem, we introduce the nth-order fractional
equilibrium distribution in terms of the Weyl fractional integral and
investigate its main properties. Specifically, we show a characterization
result by which the nth-order fractional equilibrium distribution is identical
to the starting distribution if and only if it is exponential. The nth-order
fractional equilibrium density is then used to prove a fractional probabilistic
Taylor's theorem based on derivatives of Riemann-Liouville type. A fractional
analogue of the probabilistic mean value theorem is thus developed for pairs of
nonnegative random variables ordered according to the survival bounded
stochastic order. We also provide some related results, both involving the
normalized moments and a fractional extension of the variance, and a formula of
interest to actuarial science. In conclusion we discuss the probabilistic
Taylor's theorem based on fractional Caputo derivatives.


title: One-particle density matrix characterization of many-body localization

abstract:
  We study a model of interacting fermions in one dimension subject to random,
uncorrelated onsite disorder. The model realizes an interaction-driven quantum
phase transition between an ergodic and a many-body localized phase (MBL). We
propose a single-particle framework to characterize these phases by the
eigenstates (the natural orbitals) and the eigenvalues (the occupation
spectrum) of the one-particle density matrix (OPDM) in many-body eigenstates.
As a main result, we find that the natural orbitals are localized in the MBL
phase, but delocalized in the ergodic phase. This qualitative change in these
single-particle states is a many-body effect, since without interactions the
single-particle energy eigenstates are all localized. The occupation spectrum
in the ergodic phase is thermal in agreement with the eigenstate thermalization
hypothesis, while in the MBL phase the occupations preserve a discontinuity at
an emergent Fermi edge. This suggests that the MBL eigenstates are weakly
dressed Slater determinants, with the eigenstates of the underlying Anderson
problem as reference states. We discuss the statistical properties of the
natural orbitals and of the occupation spectrum in the two phases and as the
transition is approached. Our results are consistent with the existing picture
of emergent integrability and localized integrals of motion, or quasiparticles,
in the MBL phase. We emphasize the close analogy of the MBL phase to a
zero-temperature Fermi liquid: in the studied model, the MBL phase is
adiabatically connected to the Anderson insulator and the occupation-spectrum
discontinuity directly indicates the presence of quasiparticles localized in
real space. Finally, we show that the same picture emerges for interacting
fermions in the presence of an experimentally-relevant bichromatic lattice and
thereby demonstrate that our findings are not limited to a specific model.


title: Oracle-Efficient Online Learning and Auction Design

abstract:
  We consider the design of computationally efficient online learning
algorithms in an adversarial setting in which the learner has access to an
offline optimization oracle. We present an algorithm called Generalized
Follow-the-Perturbed-Leader and provide conditions under which it is
oracle-efficient while achieving vanishing regret. Our results make significant
progress on an open problem raised by Hazan and Koren, who showed that
oracle-efficient algorithms do not exist in general and asked whether one can
identify properties under which oracle-efficient online learning may be
possible.
  Our auction-design framework considers an auctioneer learning an optimal
auction for a sequence of adversarially selected valuations with the goal of
achieving revenue that is almost as good as the optimal auction in hindsight,
among a class of auctions. We give oracle-efficient learning results for: (1)
VCG auctions with bidder-specific reserves in single-parameter settings, (2)
envy-free item pricing in multi-item auctions, and (3) s-level auctions of
Morgenstern and Roughgarden for single-item settings. The last result leads to
an approximation of the overall optimal Myerson auction when bidders'
valuations are drawn according to a fast-mixing Markov process, extending prior
work that only gave such guarantees for the i.i.d. setting.
  Finally, we derive various extensions, including: (1) oracle-efficient
algorithms for the contextual learning setting in which the learner has access
to side information (such as bidder demographics), (2) learning with
approximate oracles such as those based on Maximal-in-Range algorithms, and (3)
no-regret bidding in simultaneous auctions, resolving an open problem of
Daskalakis and Syrgkanis.


title: Reduced functions and Jensen measures

abstract:
  Let $\varphi$ be a locally upper bounded Borel measurable function on a
Greenian open set $\Omega$ in $R^d$ and, for every $x\in \Omega$, let
$v_\varphi(x)$ denote the infimum of the integrals of $\varphi$ with respect to
Jensen measures for $x$ on $\Omega$. Twenty years ago, B.J. Cole and T.J.
Ransford proved that $v_\varphi$ is the supremum of all subharmonic minorants
of $\varphi$ on $X$ and that the sets $\{v_\varphi<t\}$, $t\in R$, are
analytic. In this paper, a different method leading to the inf-sup-result
establishes at the same time that, in fact, $v_\varphi$ is the minimum of
$\varphi$ and a subharmonic function, and hence Borel measurable. This is
presented in the generality of harmonic spaces, where semipolar sets are polar,
and the key are measurability results for reduced functions on balayage spaces
which are of independent interest.


title: A Fault-tolerance Linguistic Structure for Distributed Applications

abstract:
  The structures for the expression of fault-tolerance provisions into the
application software are the central topic of this dissertation. Structuring
techniques provide means to control complexity, the latter being a relevant
factor for the introduction of design faults. This fact and the ever increasing
complexity of today's distributed software justify the need for simple,
coherent, and effective structures for the expression of fault-tolerance in the
application software. A first contribution of this dissertation is the
definition of a base of structural attributes with which application-level
fault-tolerance structures can be qualitatively assessed and compared with each
other and with respect to the above mentioned need. This result is then used to
provide an elaborated survey of the state-of-the-art of software
fault-tolerance structures. The key contribution of this work is a novel
structuring technique for the expression of the fault-tolerance design concerns
in the application layer of those distributed software systems that are
characterized by soft real-time requirements and with a number of processing
nodes known at compile-time. The main thesis of this dissertation is that this
new structuring technique is capable of exhibiting satisfactory values of the
structural attributes in the domain of soft real-time, distributed and parallel
applications. Following this novel approach, beside the conventional
programming language addressing the functional design concerns, a
special-purpose linguistic structure (the so-called "recovery language") is
available to address error recovery and reconfiguration. This recovery language
comes into play as soon as an error is detected by an underlying error
detection layer, or when some erroneous condition is signaled by the
application processes.


title:
Vortex reconnections and rebounds in trapped atomic Bose--Einstein
  condensates

abstract:
  Reconnections and interactions of filamentary coherent structures play a
fundamental role in the dynamics of fluids, plasmas and nematic liquid
crystals. In fluids, vortex reconnections redistribute energy and helicity
among the length scales and induce fine-scale turbulent mixing. Unlike ordinary
fluids where vorticity is a continuous field, in quantum fluids vorticity is
concentrated into discrete (quantized) vortex lines turning vortex
reconnections into isolated events, making it conceptually easier to study.
Here we report experimental and numerical observations of three-dimensional
quantum vortex interactions in a cigar-shaped atomic Bose-Einstein Condensate
(BEC). In addition to standard reconnections, already numerically and
experimentally observed in homogeneous systems away from boundaries, we show
that double reconnections, rebounds and ejections can also occur as a
consequence of the non-homogeneous, confined nature of the system.


title: Reverse vaccinology in Plasmodium falciparum 3D7

abstract:
  A timely immunization can be effective against certain diseases and can save
thousands of lives. However, for some diseases it has been difficult, so far,
to develop an efficient vaccine. Malaria, a tropical disease caused by a
parasite of the genus Plasmodium, is one example. Bioinformatics has opened the
way to new lines of experimental investigation One example is reverse
vaccinology that aims to identify antigens that are capable of generating an
immune response in a given organism using in silico studies. In this study we
applied a reverse vaccinology methodology using a bioinformatics pipeline. We
obtained 45 potential linear B cells consensus epitopes from the whole genome
of P. falciparum 3D7 that can be used as candidates for malaria vaccines. The
direct implication of the results obtained is to open the way to experimentally
validate more epitopes to increase the efficiency of the available treatments
against malaria and to explore the methodology in other diseases.


title: Infinite and Giant Components in the Layers Percolation Model

abstract:
  In this work we continue the investigation launched in [FHR16] of the
structural properties of the structural properties of the Layers model, a
dependent percolation model. Given an undirected graph $G=(V,E)$ and an integer
$k$, let $T_k(G)$ denote the random vertex-induced subgraph of $G$, generated
by ordering $V$ according to Uniform$[0,1]$ $\mathrm{i.i.d.}$ clocks and
including in $T_k(G)$ those vertices with at most $k-1$ of their neighbors
having a faster clock. The distribution of subgraphs sampled in this manner is
called the layers model with parameter $k$. The layers model has found
applications in the study of $\ell$-degenerate subgraphs, the design of
algorithms for the maximum independent set problem and in the study of
bootstrap percolation.
  We prove that every infinite locally finite tree $T$ with no leaves,
satisfying that the degree of the vertices grow sub-exponentially in their
distance from the root, $T_3(T)$ $\mathrm{a.s.}$ has an infinite connected
component. In contrast, we show that for any locally finite graph $G$,
$\mathrm{a.s.}$ every connected component of $T_2(G)$ is finite.
  We also consider random graphs with a given degree sequence and show that if
the minimal degree is at least 3 and the maximal degree is bounded, then
$\mathrm{w.h.p.}$ $T_3$ has a giant component. Finally, we also consider
${\mathbb{Z}}^{d}$ and show that if $d$ is sufficiently large, then
$\mathrm{a.s.}$ $T_4(\mathbb{Z}^d)$ contains an infinite cluster.


title: On the conservative pasting lemma

abstract:
  Several perturbation tools are established in the volume preserving setting
allowing for the pasting, extension, localized smoothing and local
linearization of vector fields. The pasting and local linearization hold in all
classes of regularity ranging from $C^{1}$ to $C^{\infty}$ (H\"older included).
For diffeomorphisms, a conservative linearized version of Franks lemma is
proved in the $C^{r,\alpha}$ ($r\in\mathbb{Z}^+$, $0<\alpha <1$) and
$C^{\infty}$ settings, the resulting diffeomorphism having the same regularity
as the original one.


title:
Application of the fractional conservation of mass to Gas Flow
  diffusivity equation in heterogeneous porous media

abstract:
  In this paper we reconsider the classical nonlinear diffusivity equation of
real gas in an heterogenous porous medium in light of the recent studies about
the generalized fractional equation of conservation of mass. We first recall
the physical meaning of the fractional conservation of mass recently studied by
Wheatcraft and Meerschaert (2008) and then consider the implications in the
classical model of diffusion of a real gas in a porous medium. Then we show
that the obtained equation can be simply linearized into a classical
space-fractional diffusion equation, widely studied in the literature. We also
consider the case of a power-law pressure-dependence of the permeability
coefficient. In this case we provide some useful exact analytical results. In
particular, we are able to find a Barenblatt-type solution for a
space-fractional Boussinesq equation, arising in this context.


title: Closure and Nonclosure Properties of the Compressible and Rankable Sets

abstract:
  The rankable and compressible sets have been studied for more than a quarter
of a century, ever since Allender [1] and Goldberg and Sipser [6] introduced
the formal study of polynomial-time ranking. Yet even after all that time,
whether the rankable and compressible sets are closed under the most important
boolean and other operations remains essentially unexplored. The present paper
studies these questions for both polynomial-time and recursion-theoretic
compression and ranking, and for almost every case arrives at a Closed, a
Not-Closed, or a Closed-Iff-Well-Known-Complexity-Classes-Collapse result for
the given operation. Even though compression and ranking classes are capturing
something quite natural about the structure of sets, it turns out that they are
quite fragile with respect to closure properties, and many fail to possess even
the most basic of closure properties. For example, we show that with respect to
the join (aka disjoint union) operation: the P-rankable sets are not closed,
whether the semistrongly P-rankable sets are closed is closely linked to
whether P = UP $\cap$ coUP, and the strongly P-rankable sets are closed.


title:
Dislocations as a boundary between charge density wave and oxygen rich
  phases in a cuprate high temperature superconductor

abstract:
  Multiple functional ionic and electronic orders are observed in high
temperature superconducting cuprates. The charge density wave order is one of
them and it is spatially localized in spatial regions of the material. It is
also known that the oxygen interstitials introduced by chemical intercalation
self-organize in different oxygen rich regions corresponding with hole rich
regions in the Cu$O_2$ layers left empty by the charge density wave order
domains. However, what happens in between these two order is not known, and
neither there is a method to control this spatial separation. Here we
demonstrate by using scanning nano X-ray diffraction, that dislocations or
grain boundaries in the material can act as boundary between charge density
wave and oxygen rich phases in a optimally doped La$_2$CuO$_4$$_+$$_y$ high
temperature superconductor. Dislocations can be used therefore to control the
anti-correlation of the charge density wave order with the oxygen interstitials
in specific portion of the material.


title: Semantic Information Encoding in One Dimensional Time Domain Signals

abstract:
  A one dimensional time domain analog signal s(t) can be visualized as a
trajectory of a moving particle in a force field with one degree of freedom.
Then the power of the particle at point t is P(s(t)) = s"(t)s'(t), which is the
rate at which kinetic energy is dissipated (assuming the mass of the particle
is unit) by the particle in order to create the trajectory or give shape to the
signal. Assuming meaning of the signal or the semantic information is in its
shape, we can say that P(s(t)) is the rate at which kinetic energy of the
particle is dissipated to encode semantic information in s(t) at t. After s(t)
is digitized (to make it s[n]) the discrete form P(s[n]) is valid. Considering
the sign changes of P(s[n]) it has been shown that in the smallest neighborhood
of n, in which n is the middle point, semantic information in s[n] can be
encoded in 13 distinct ways. This list is exhaustive. A deterministic finite
automaton (DFA) has been designed which can accept any finite length digital
signal and therefore collection of all finite length digital signals forms a
regular language. The DFA has been generalized to a weighted finite state
transducer (WFST), which has been used to identify action potentials in a spike
train and also to distinguish two speakers when uttering the same phoneme. It
has been shown that in any analog signal semantic information can be encoded at
a point in the form of the shape of its infinitesimal neighborhood in 17
distinct ways. The list is exhaustive. A new entropy measure called semantic
entropy has been introduced. It has been shown that a signal s(t) is traceable
on a piece of paper or in an oscilloscope, only if s"(t) exists on all but at
most a finite number of points within any finite interval. This is an essential
condition for a signal to be the trajectory of a moving particle.


title: Maximum nonlocality in the (3,2,2) scenario

abstract:
  We identify the simplest combinations of entanglement and incompatibility
giving the maximum quantum violation for each of the 46 classes of tight Bell
inequalities for the (3,2,2) scenario, i.e., three parties, two measurements
per party, and two outcomes per measurement. This allows us to classify the
maximum quantum nonlocality according to the simplest resources needed to
achieve it. We show that entanglement and incompatibility only produce maximum
nonlocality when they are combined in specific ways. For each entanglement
class there is, in most cases, just one incompatibility class leading to
maximum nonlocality. We also identify two interesting cases. We show that the
maximum quantum violation of \'Sliwa inequality 23 only occurs when the third
party measures the identity, so nonlocality cannot increase when we add a third
party to the bipartite case. Almost quantum correlations predict that adding a
new party increases nonlocality. This points out that either almost quantum
correlations violate a fundamental principle or that there is a form of
tripartite entanglement which quantum theory cannot account for. The other
interesting case is the maximum quantum violation of \'Sliwa inequality 26,
which, like the Mermin inequality, requires maximum incompatibility for all
parties. In contrast, it requires a specific entangled state which has the same
tripartite negativity as the W state.


title: WW + jet at 14 and 100 TeV

abstract:
  In the current LHC run, an accurate understanding of Standard Model processes
is extremely important. Processes including electroweak gauge bosons serve as
standard candles for SM measurements, and equally constitute important
backgrounds for Beyond-the-Standard Model (BSM) searches. We present here the
next-to-leading order (NLO) QCD virtual contributions to W+W- + jet in an
analytic format obtained through unitarity methods. We present results for the
full process using the Monte Carlo event generator MCFM, and discuss total as
well as differential cross-sections for the LHC with 14 TeV center-of-mass
energy, as well as a future 100 TeV proton-proton machine.


title:
Direct measurement of sub-10 fs relativistic electron beams with
  ultralow emittance

abstract:
  Ultralow emittance ($\leq20$ nm, normalized) electron beams with $10^5$
electrons per bunch are obtained by tightly focusing an ultrafast ($\sim$ 100
fs) laser pulse on the cathode of a 1.6 cell radiofrequency photoinjector.
Taking advantage of the small initial longitudinal emittance, a downstream
velocity bunching cavity is used to compress the beam to $<10$ fs rms bunch
length. The measurement is performed using a thick high voltage deflecting
cavity which is shown to be well-suited to measure ultrashort durations of
bunching beams, provided that the beam reaches a ballistic longitudinal focus
at the cavity center.


title: TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency

abstract:
  In this paper, we propose TopicRNN, a recurrent neural network (RNN)-based
language model designed to directly capture the global semantic meaning
relating words in a document via latent topics. Because of their sequential
nature, RNNs are good at capturing the local structure of a word sequence -
both semantic and syntactic - but might face difficulty remembering long-range
dependencies. Intuitively, these long-range dependencies are of semantic
nature. In contrast, latent topic models are able to capture the global
underlying semantic structure of a document but do not account for word
ordering. The proposed TopicRNN model integrates the merits of RNNs and latent
topic models: it captures local (syntactic) dependencies using an RNN and
global (semantic) dependencies using latent topics. Unlike previous work on
contextual RNN language modeling, our model is learned end-to-end. Empirical
results on word prediction show that TopicRNN outperforms existing contextual
RNN baselines. In addition, TopicRNN can be used as an unsupervised feature
extractor for documents. We do this for sentiment analysis on the IMDB movie
review dataset and report an error rate of $6.28\%$. This is comparable to the
state-of-the-art $5.91\%$ resulting from a semi-supervised approach. Finally,
TopicRNN also yields sensible topics, making it a useful alternative to
document models such as latent Dirichlet allocation.


title: Unraveling the hardness of a borophene-based compound

abstract:
  Two-dimensional systems have strengthened their position as one of the key
materials for novel applications. Very recently, boron joined the distinguished
group of elements that are confirmed to possess 2D allotropes, named
borophenes. In this work, we explore the stability and hardness of the highest
boride of tungsten, which is regarded as built of borophenes separated by metal
atoms. We show that WB$_{3+x}$ has Vickers hardnesses approaching 40 GPa only
for small values of $x$. The insertion of extra boron atoms is, in general,
detrimental for WB$_{3}$ in terms of hardness since leads to the formation of
quasi-planar boron sheets that are less tightly connected with the adjacent W
layers. Very high concentrations of boron ($x \approx 1$), give rise to a soft
(Vickers hardness of about 8 GPa) and unstable $hP$20-WB$_{4}$ structure that
can be considered as built of quasi-planar boron $\alpha$-sheets separated by
graphitic W layers. On the other hand, we show that the formation of tungsten
vacancies brings on structures, e.g. W$_{0.75}$B$_{3+x}$, with Vickers
hardnesses that are less sensitive to variations in the boron content and are
close in value to the experimentally reported load-independent values above 20
GPa.


title: End-to-end Optimized Image Compression

abstract:
  We describe an image compression method, consisting of a nonlinear analysis
transformation, a uniform quantizer, and a nonlinear synthesis transformation.
The transforms are constructed in three successive stages of convolutional
linear filters and nonlinear activation functions. Unlike most convolutional
neural networks, the joint nonlinearity is chosen to implement a form of local
gain control, inspired by those used to model biological neurons. Using a
variant of stochastic gradient descent, we jointly optimize the entire model
for rate-distortion performance over a database of training images, introducing
a continuous proxy for the discontinuous loss function arising from the
quantizer. Under certain conditions, the relaxed loss function may be
interpreted as the log likelihood of a generative model, as implemented by a
variational autoencoder. Unlike these models, however, the compression model
must operate at any given point along the rate-distortion curve, as specified
by a trade-off parameter. Across an independent set of test images, we find
that the optimized method generally exhibits better rate-distortion performance
than the standard JPEG and JPEG 2000 compression methods. More importantly, we
observe a dramatic improvement in visual quality for all images at all bit
rates, which is supported by objective quality estimates using MS-SSIM.


title:
The Radio Spectral Energy Distribution and Star Formation Rate
  Calibration in Galaxies

abstract:
  We study the spectral energy distribution (SED) of the radio continuum
emission from the KINGFISH sample of nearby galaxies to understand the
energetics and origin of this emission. Effelsberg multi-wavelength
observations at 1.4GHz, 4.8GHz, 8.5GHz, and 10.5GHz combined with archive data
allow us, for the first time, to determine the mid-radio continuum (1-10 GHz,
MRC) bolometric luminosities and further present calibration relations vs. the
monochromatic radio luminosities. The 1-10 GHz radio SED is fitted using a
Bayesian Markov Chain Monte Carlo (MCMC) technique leading to measurements for
the nonthermal spectral index and the thermal fraction f_th with mean values of
alpha_nt=0.97+-0.16 (0.79+-0.15 for the total spectral index) and f_th= 10% +-
9% at 1.4 GHz. The MRC luminosity changes over ~3 orders of magnitude in the
sample. The thermal emission is responsible for ~23% of the MRC on average. We
also compare the extinction-corrected diagnostics of star formation rate with
the thermal and nonthermal radio tracers and derive the first star formation
calibration relations using the MRC radio luminosity. The nonthermal spectral
index flattens with increasing star formation rate surface density, indicating
the effect of the star formation feedback on the cosmic ray electron population
in galaxies. Comparing the radio and IR SEDs, we find that the FIR-to-MRC ratio
could decrease with star formation rate, due to the amplification of the
magnetic fields in star forming regions. This particularly implies a decrease
in the ratio at high redshifts, where mostly luminous/star forming galaxies are
detected.


title:
Self-reducible with easy decision version counting problems admit
  additive error approximation. Connections to counting complexity, exponential
  time complexity, and circuit lower bounds

abstract:
  We consider the class of counting problems,i.e. functions in $\#$P, which are
self reducible, and have easy decision version, i.e. for every input it is easy
to decide if the value of the function $f(x)$ is zero. For example,
$\#$independent-sets of all sizes, is such a problem, and one of the hardest of
this class, since it is equivalent to $\#$SAT under multiplicative
approximation preserving reductions.
  Using these two powerful properties, self reducibility and easy decision, we
prove that all problems/ functions $f$ in this class can be approximated in
probabilistic polynomial time within an absolute exponential error
$\epsilon\cdot 2^{n'}, \forall\epsilon>0$, which for many of those problems
(when $n'=n+$constant) implies additive approximation to the fraction
$f(x)/2^n$. (Where $n'$ is the amount of non-determinism of some associated
NPTM).
  Moreover we show that for all these problems we can have multiplicative error
to the value $f(x)$, of any desired accuracy (i.e. a RAS), in time of order
$2^{2n'/3}poly(n)$, which is strictly smaller than exhaustive search. We also
show that $f(x)<g(x)$ can be decided deterministically in time $g(x)poly(n),
\forall g$.
  Finally we show that the Circuit Acceptance Probability Problem, which is
related to derandomization and circuit lower bounds, can be solved with high
probability and in polynomial time, for the family of all circuits for which
the problems of counting either satisfying or unsatisfying assignments belong
to TotP (which is the Karp-closure of self reducible problems with easy
decision version).


title: On toric locally conformally K\"ahler manifolds

abstract:
  We study compact toric strict locally conformally K\"ahler manifolds. We show
that the Kodaira dimension of the underlying complex manifold is $-\infty$ and
that the only compact complex surfaces admitting toric strict locally
conformally K\"ahler metrics are the diagonal Hopf surfaces. We also show that
every toric Vaisman manifold has lcK rank 1 and is isomorphic to the mapping
torus of an automorphism of a toric compact Sasakian manifold.


title:
Detecting Dependencies in Sparse, Multivariate Databases Using
  Probabilistic Programming and Non-parametric Bayes

abstract:
  Datasets with hundreds of variables and many missing values are commonplace.
In this setting, it is both statistically and computationally challenging to
detect true predictive relationships between variables and also to suppress
false positives. This paper proposes an approach that combines probabilistic
programming, information theory, and non-parametric Bayes. It shows how to use
Bayesian non-parametric modeling to (i) build an ensemble of joint probability
models for all the variables; (ii) efficiently detect marginal independencies;
and (iii) estimate the conditional mutual information between arbitrary subsets
of variables, subject to a broad class of constraints. Users can access these
capabilities using BayesDB, a probabilistic programming platform for
probabilistic data analysis, by writing queries in a simple, SQL-like language.
This paper demonstrates empirically that the method can (i) detect
context-specific (in)dependencies on challenging synthetic problems and (ii)
yield improved sensitivity and specificity over baselines from statistics and
machine learning, on a real-world database of over 300 sparsely observed
indicators of macroeconomic development and public health.


title:
Uncovering star formation feedback and magnetism in galaxies with radio
  continuum surveys

abstract:
  Recent studies show the importance of the star formation feedback in changing
the energetic and structure of galaxies. Dissecting the physics of the feedback
is hence crucial to understand the evolution of galaxies. Full polarization
radio continuum surveys can be ideally performed to trace not only star
formation but also the energetic components of the interstellar medium (ISM),
the magnetic fields and cosmic ray electrons. Using the SKA precursors, we
investigate the effect of the massive star formation on the ISM energy balance
in nearby galaxies. Our multi-scale and multi-frequency surveys show that
cosmic rays are injected in star forming regions and lose energy propagating
away from their birth place. Due to the star formation feedback, cosmic ray
electron population becomes younger and more energetic. Star formation also
amplifies the turbulent magnetic field inserting a high pressure which is
important in energy balance in the ISM and structure formation in the host
galaxy.


title: Deciding Graph non-Hamiltonicity via a Closure Algorithm

abstract:
  We present a matching and LP based heuristic algorithm that decides graph
non-Hamiltonicity. Each of the $n!$ Hamilton cycles in a complete directed
graph on $n+1$ vertices corresponds with each of the $n!$ $n$-permutation
matrices $P$, such that $p_{u,i}=1$ if and only if the $i^{th}$ arc in a cycle
enters vertex $u$, starting and ending at vertex $n+1$. A graph instance ($G$)
is initially coded as exclusion set $E$, whose members are pairs of components
of $P$, $\{p_{u,i} ,p_{v,i+1}\}, i=1,n-1$, for each arc $(u,v)$ not in $G$. For
each $\{p_{u,i} ,p_{v,i+1}\}\in E$, the set of $P$ satisfying
$p_{u,i}=p_{v,i+1}=1$ correspond with a set of cycles not in $G$. Accounting
for all arcs not in $G$, $E$ codes precisely the set of cycles not in $G$. A
doubly stochastic-like $\mathcal{O}$($n^4$) formulation of the Hamilton cycle
decision problem is then constructed. Each $\{p_{u,i} ,p_{v,j}\}$ is coded as
variable $q_{u,i,v,j}$ such that the set of integer extrema is the set of all
permutations. We model $G$ by setting each $q_{u,i,v,j}=0$ in correspondence
with each $\{p_{u,i} ,p_{v,j}\}\in E$ such that for non-Hamiltonian $G$,
integer solutions cannot exist. We recognize non-Hamiltonicity by iteratively
deducing additional $q_{u,i,v,j}$ that can be set zero and expanding $E$ until
the formulation becomes infeasible, in which case we recognize that no integer
solutions exists i.e. $G$ is decided non-Hamiltonian. Over 100 non-Hamiltonian
graphs (10 through 104 vertices) and 2000 randomized 31 vertex non-Hamiltonian
graphs are tested and correctly decided non-Hamiltonian. For Hamiltonian $G$,
the complement of $E$ provides information about covers of matchings, perhaps
useful in searching for cycles. We also present an example where the algorithm
fails to deduce any integral value for any $q_{u,i,v,j}$ i.e. $G$ is undecided.


title:
Causes for Query Answers from Databases: Datalog Abduction,
  View-Updates, and Integrity Constraints

abstract:
  Causality has been recently introduced in databases, to model, characterize,
and possibly compute causes for query answers. Connections between QA-causality
and consistency-based diagnosis and database repairs (wrt. integrity constraint
violations) have already been established. In this work we establish precise
connections between QA-causality and both abductive diagnosis and the
view-update problem in databases, allowing us to obtain new algorithmic and
complexity results for QA-causality. We also obtain new results on the
complexity of view-conditioned causality, and investigate the notion of
QA-causality in the presence of integrity constraints, obtaining complexity
results from a connection with view-conditioned causality. The abduction
connection under integrity constraints allows us to obtain algorithmic tools
for QA-causality.


title: Singularly perturbed critical Choquard equations

abstract:
  In this paper we study the semiclassical limit for the singularly perturbed
Choquard equation
  $$
  -\vr^2\Delta u +V(x)u =\vr^{\mu-3}\Big(\int_{\R^3}
\frac{Q(y)G(u(y))}{|x-y|^\mu}dy\Big)Q(x)g(u) \quad \mbox{in $\R^3$},
  $$ where $0<\mu<3$, $\vr$ is a positive parameter, $V,Q$ are two continuous
real function on $\R^3$ and $G$ is the primitive of $g$ which is of critical
growth due to the Hardy-Littlewood-Sobolev inequality. Under suitable
assumptions on the nonlinearity $g$, we first establish the existence of ground
states for the critical Choquard equation with constant coefficients in $\R^3$.
Next we establish existence and multiplicity of semi-classical solutions and
characterize the concentration behavior by variational methods.


title: PID Techniques: Alternatives to RICH Methods

abstract:
  In this review article we discuss new updates on PID techniques, other than
the Cherenkov method. In particular, we discuss recent efforts to develop high
resolution timing, placing an emphasis on small scale test results.


title: Beyond Fine Tuning: A Modular Approach to Learning on Small Data

abstract:
  In this paper we present a technique to train neural network models on small
amounts of data. Current methods for training neural networks on small amounts
of rich data typically rely on strategies such as fine-tuning a pre-trained
neural network or the use of domain-specific hand-engineered features. Here we
take the approach of treating network layers, or entire networks, as modules
and combine pre-trained modules with untrained modules, to learn the shift in
distributions between data sets. The central impact of using a modular approach
comes from adding new representations to a network, as opposed to replacing
representations via fine-tuning. Using this technique, we are able surpass
results using standard fine-tuning transfer learning approaches, and we are
also able to significantly increase performance over such approaches when using
smaller amounts of data.


title: Recover Subjective Quality Scores from Noisy Measurements

abstract:
  Simple quality metrics such as PSNR are known to not correlate well with
subjective quality when tested across a wide spectrum of video content or
quality regime. Recently, efforts have been made in designing objective quality
metrics trained on subjective data (e.g. VMAF), demonstrating better
correlation with video quality perceived by human. Clearly, the accuracy of
such a metric heavily depends on the quality of the subjective data that it is
trained on. In this paper, we propose a new approach to recover subjective
quality scores from noisy raw measurements, using maximum likelihood
estimation, by jointly estimating the subjective quality of impaired videos,
the bias and consistency of test subjects, and the ambiguity of video contents
all together. We also derive closed-from expression for the confidence interval
of each estimate. Compared to previous methods which partially exploit the
subjective information, our approach is able to exploit the information in
full, yielding tighter confidence interval and better handling of outliers
without the need for z-scoring or subject rejection. It also handles missing
data more gracefully. Finally, as side information, it provides interesting
insights on the test subjects and video contents.


title:
Convergence of density expansions of correlation functions and the
  Ornstein-Zernike equation

abstract:
  We prove convergence of the multi-body correlation function as a power series
in the density. We work in the context of the cluster expansion in the
canonical ensemble and we obtain bounds uniform in the volume and the number of
particles. In the thermodynamic limit, the coefficients are characterized by
sums over some class of two-connected graphs. We introduce the "direct
correlation function" in the canonical ensemble and we prove that in the
thermodynamic limit it is given by a convergent power series in the density
with coefficients given by sums over some other class of two-connected graphs.
Furthermore, it satisfies the Ornstein-Zernike equation from which quantified
approximations can be derived.


title:
Methane bursts as a trigger for intermittent lake-forming climates on
  post-Noachian Mars

abstract:
  Lakes existed on Mars later than 3.6 billion years ago, according to
sedimentary evidence for deltaic deposition. The observed fluvio-lacustrine
deposits suggest that individual lake-forming climates persisted for at least
several thousand years (assuming dilute flow). But the lake watersheds' little
weathered soils indicate a largely dry climate history, with intermittent
runoff events. Here we show that these observational constraints, while
inconsistent with many previously-proposed triggers for lake-forming climates,
are consistent with a methane burst scenario. In this scenario, chaotic
transitions in mean obliquity drive latitudinal shifts in temperature and ice
loading that destabilize methane clathrate. Using numerical simulations, we
find that outgassed methane can build up to atmospheric levels sufficient for
lake forming climates, for past clathrate hydrate stability zone occupancy
fractions >0.04. Such occupancy fractions are consistent with methane
production by water-rock reactions due to hydrothermal circulation on early
Mars. We further estimate that photochemical destruction of atmospheric methane
curtails the duration of individual lake-forming climates to less than a
million years, consistent with observations. We conclude that methane bursts
represent a potential pathway for intermittent excursions to a warm, wet
climate state on early Mars.


title: A Formula For the S-Class Number of an Algebraic Torus

abstract:
  We obtain a formula for the S-class number of an algebraic torus defined over
a number field in terms of the etale and Galois cohomology groups of its
character module. As applications, we give different proofs of some classical
class number formulas of Shyr, Ono, Katayama and Morishita.


title: Toughness and damage tolerance of fractal hierarchical metamaterials

abstract:
  We present a theory for the toughness, damage tolerance, and tensile strength
of a class of hierarchical, fractal, metamaterials. We show that the even
though the absolute toughness and damage tolerance decrease with increasing
number of hierarchical scales, the specific toughness (toughness per-unit
density) grows with increasing number of hierarchical scales in the material,
while the specific tensile strength and damage tolerance remain constant.


title: Weil-etale Cohomology and Special Values of L-functions

abstract:
  We construct the Weil-\'etale cohomology and Euler characteristics for a
subclass of the class of $\mathbb{Z}$-constructible sheaves on an open
subscheme of the spectrum of the ring of integers of a number field. Then we
show that the special value of an Artin L-function of toric type at zero is
given by the Weil-\'etale Euler characteristic of an appropriate
$\mathbb{Z}$-constructible sheaf up to signs. As applications of our result, we
will prove a formula for the special value of the L-function of an algebraic
torus at zero which is similar to Ono's Tamagawa Number Formula.


title: Longitudinal RF capture simulation and BPM signal estimation

abstract:
  In this paper, the theoretical aspects behind longitudinal RF capture are
reviewed and the capture process is simulated via a program based on this
theory. Four kinds of cases with different initial distribution and capture
curve are considered, i.e. uniform distribution with adiabatic capture, uniform
distribution with non-adiabatic capture, Gaussian distribution with adiabatic
capture and Gaussian distribution with non-adiabatic capture. The simulation
results are compared each other and discussed, and Gaussian distribution with
adiabatic capture is demonstrated having a higher capture efficiency and
leading to a shorter bunch length. In addition, the BPM induced signal is
simulated with high input impendence, i.e. $1M\Omega$, and low input
impendence, i.e. $50\Omega$, respectively. Finally, the BPM signal of Heavy Ion
Medical Machine (HIMM) is estimated and compared with measured one, and a good
agreement is achieved.


title:
Learning to Draw Samples: With Application to Amortized MLE for
  Generative Adversarial Learning

abstract:
  We propose a simple algorithm to train stochastic neural networks to draw
samples from given target distributions for probabilistic inference. Our method
is based on iteratively adjusting the neural network parameters so that the
output changes along a Stein variational gradient that maximumly decreases the
KL divergence with the target distribution. Our method works for any target
distribution specified by their unnormalized density function, and can train
any black-box architectures that are differentiable in terms of the parameters
we want to adapt. As an application of our method, we propose an amortized MLE
algorithm for training deep energy model, where a neural sampler is adaptively
trained to approximate the likelihood function. Our method mimics an
adversarial game between the deep energy model and the neural sampler, and
obtains realistic-looking images competitive with the state-of-the-art results.


title: A Gaussian small deviation inequality for convex functions

abstract:
  Let $Z$ be an $n$-dimensional Gaussian vector and let $f: \mathbb R^n \to
\mathbb R$ be a convex function. We show that: $$\mathbb P \left( f(Z) \leq
\mathbb E f(Z) -t\sqrt{ {\rm Var} f(Z)} \right) \leq \exp(-ct^2),$$ for all
$t>1$, where $c>0$ is an absolute constant. As an application we derive
variance-sensitive small ball probabilities for Gaussian processes.


title: Words or Characters? Fine-grained Gating for Reading Comprehension

abstract:
  Previous work combines word-level and character-level representations using
concatenation or scalar weighting, which is suboptimal for high-level tasks
like reading comprehension. We present a fine-grained gating mechanism to
dynamically combine word-level and character-level representations based on
properties of the words. We also extend the idea of fine-grained gating to
modeling the interaction between questions and paragraphs for reading
comprehension. Experiments show that our approach can improve the performance
on reading comprehension tasks, achieving new state-of-the-art results on the
Children's Book Test dataset. To demonstrate the generality of our gating
mechanism, we also show improved results on a social media tag prediction task.


title:
Extended Nuclear Quadrupole Resonance Study of the Heavy-Fermion
  Superconductor PuCoGa$_5$

abstract:
  PuCoGa$_5$ has emerged as a prototypical heavy-fermion superconductor, with
its transition temperature ($T_c\simeq18.5$ K) being the highest amongst such
materials. Nonetheless, a clear description as to what drives the
superconducting pairing is still lacking, rendered complicated by the
notoriously intricate nature of plutonium's 5$f$ valence electrons. Here, we
present a detailed $^{69,71}$Ga nuclear quadrupole resonance (NQR) study of
PuCoGa$_5$, concentrating on the system's normal state properties near to $T_c$
and aiming to detect distinct signatures of possible pairing mechanisms. In
particular, the quadrupole frequency and spin-lattice relaxation rate were
measured for the two crystallographically inequivalent Ga sites and for both Ga
isotopes, in the temperature range 1.6 K - 300 K. No evidence of significant
charge fluctuations is found from the NQR observables. On the contrary, the
low-energy dynamics is dominated by anisotropic spin fluctuations with strong,
nearly critical, in-plane character, which are effectively identical to the
case of the sister compound PuCoIn$_5$. These findings are discussed within the
context of different theoretical proposals for the unconventional pairing
mechanism in heavy-fermion superconductors.


title:
LSTM-Based System-Call Language Modeling and Robust Ensemble Method for
  Designing Host-Based Intrusion Detection Systems

abstract:
  In computer security, designing a robust intrusion detection system is one of
the most fundamental and important problems. In this paper, we propose a
system-call language-modeling approach for designing anomaly-based host
intrusion detection systems. To remedy the issue of high false-alarm rates
commonly arising in conventional methods, we employ a novel ensemble method
that blends multiple thresholding classifiers into a single one, making it
possible to accumulate 'highly normal' sequences. The proposed system-call
language model has various advantages leveraged by the fact that it can learn
the semantic meaning and interactions of each system call that existing methods
cannot effectively consider. Through diverse experiments on public benchmark
datasets, we demonstrate the validity and effectiveness of the proposed method.
Moreover, we show that our model possesses high portability, which is one of
the key aspects of realizing successful intrusion detection systems.


title:
Non equilibrium stationary states of a dissipative kicked linear chain
  of spins

abstract:
  We consider a linear chain made of spins of one half in contact with a
dissipative environment for which periodic delta-kicks are applied to the
qubits of the linear chain in two different configurations: kicks applied to a
single qubit and simultaneous kicks applied to two qubits of the linear chain.
In both cases the system reaches a non-equilibrium stationary condition in the
long time limit. We study the transient to the quasi stationary states and
their properties as function of the kick parameters in the single kicked qubit
case and report the emergence of stationary entanglement between the kicked
qubits when simultaneous kicks are applied. For doing our study we have derived
an approximation to a master equation which serves us to analyze the effects of
a finite temperature and the zero temperature environment.


title: Jets and high-$p_{T}$ probes measured in the STAR experiment

abstract:
  Hard probes created through large momentum transfers are used to study the
properties of QCD matter created in heavy-ion collisions, by comparing the
measurements to those in p+p collisions. Jets, and the "quenching" or
suppression of jets in the medium created in heavy-ion collisions, are studied
through various different observables. We present the most recent measurements
from $\sqrt{s_{NN}}$ = 200 GeV Au+Au collisions, with p+p collisions as the
reference, by the STAR Collaboration. The observables are semi-inclusive
charged jets and di-jet transverse momentum imbalance. Additionally,
correlation measurements of direct photon-hadron and neutral pion-hadron are
presented and discussed.


title:
A Survey on Replica Server Placement Algorithms for Content Delivery
  Networks

abstract:
  Content Delivery Networks (CDNs) have gained immense popularity over the
years. Replica server placement is a key design issue in CDNs. It entails
placing replica servers at meticulous locations, such that cost is minimized
and Quality of Service (QoS) of end-users is satisfied. Many replica server
placement models have been proposed in the literature of traditional CDN. As
the CDN architecture is evolving through the adoption of emerging paradigms,
such as, cloud computing and Network Functions Virtualization (NFV), new
algorithms are being proposed. In this paper, we present a comprehensive survey
of replica server placement algorithms in traditional and emerging paradigm
based CDNs. We categorize the algorithms and provide a summary of their
characteristics. Besides, we identify requirements for an efficient replica
server placement algorithm and perform a comparison in the light of the
requirements. Finally, we discuss potential avenues for further research in
replica server placement in CDNs.


title: Validation of Tsallis Entropy In Inter-Modality Neuroimage Registration

abstract:
  Medical image registration plays an important role in determining topographic
and morphological changes for functional diagnostic and therapeutic purposes.
Manual alignment and semi-automated software still have been used; however they
are subjective and make specialists spend precious time. Fully automated
methods are faster and user-independent, but the critical point is registration
reliability. Similarity measurement using Mutual Information (MI) with Shannon
entropy (MIS) is the most common automated method that is being currently
applied in medical images, although more reliable algorithms have been proposed
over the last decade, suggesting improvements and different entropies; such as
Studholme et al, (1999), who demonstrated that the normalization of Mutual
Information (NMI) provides an invariant entropy measure for 3D medical image
registration. In this paper, we described a set of experiments to evaluate the
applicability of Tsallis entropy in the Mutual Information (MIT) and in the
Normalized Mutual Information (NMIT) as cost functions for Magnetic Resonance
Imaging (MRI), Positron Emission Tomography (PET) and Computed Tomography (CT)
exams registration. The effect of changing overlap in a simple image model and
clinical experiments on current entropies (Entropy Correlation Coefficient -
ECC, MIS and NMI) and the proposed ones (MIT and NMT) showed NMI and NMIT with
Tsallis parameter close to 1 as the best options (confidence and accuracy) for
CT to MRI and PET to MRI automatic neuroimaging registration.


title: Deep Label Distribution Learning with Label Ambiguity

abstract:
  Convolutional Neural Networks (ConvNets) have achieved excellent recognition
performance in various visual recognition tasks. A large labeled training set
is one of the most important factors for its success. However, it is difficult
to collect sufficient training images with precise labels in some domains such
as apparent age estimation, head pose estimation, multi-label classification
and semantic segmentation. Fortunately, there is ambiguous information among
labels, which makes these tasks different from traditional classification.
Based on this observation, we convert the label of each image into a discrete
label distribution, and learn the label distribution by minimizing a
Kullback-Leibler divergence between the predicted and ground-truth label
distributions using deep ConvNets. The proposed DLDL (Deep Label Distribution
Learning) method effectively utilizes the label ambiguity in both feature
learning and classifier learning, which help prevent the network from
over-fitting even when the training set is small. Experimental results show
that the proposed approach produces significantly better results than
state-of-the-art methods for age estimation and head pose estimation. At the
same time, it also improves recognition performance for multi-label
classification and semantic segmentation tasks.


title:
Finite-Time Elimination of Disagreement of Opinion Dynamics via Covert
  Noise

abstract:
  Eliminating disagreement in a group is usually beneficial to the social
stability. In this paper, using the well-known Hegselmann-Krause (HK) model, we
design a quite simple strategy that could resolve the opinion difference of the
system in finite time and induce the opinions synchronized to a targeted value.
To be specific, we intentionally introduce weak random noise to only one agent
to affect its opinion in the evolution and also a leader agent with fixed
opinion in a divisive group, then strictly prove that the disagreement is
finally eliminated and the opinions get synchronized to the leader's opinion in
finite time. Other than that, we calculate the finite stopping time when the
opinions synchronously reach the objective opinion value, which could provide
further guide for designing more efficient noise intervention strategy.


title:
A sensitive search for unknown spectral emission lines in the diffuse
  X-ray background with XMM-Newton

abstract:
  The Standard Model of particle physics can be extended to include sterile
(right-handed) neutrinos or axions to solve the dark matter problem. Depending
upon the mixing angle between active and sterile neutrinos, the latter have the
possibility to decay into monoenergetic active neutrinos and photons in the
keV-range while axions can couple to two photons. We have used data taken with
X-ray telescopes like e.g. XMM-Newton for the search of line emissions. We used
pointings with high exposures and expected dark matter column densities with
respect to the dark matter halo of the Milky Way. The posterior predictive
p-value analysis has been applied to locate parameter space regions which
favour additional emission lines. In addition, upper limits of the parameter
space of the models have been generated such that the preexisting limits have
been significantly improved.


title: Deep Biaffine Attention for Neural Dependency Parsing

abstract:
  This paper builds off recent work from Kiperwasser & Goldberg (2016) using
neural attention in a simple graph-based dependency parser. We use a larger but
more thoroughly regularized parser than other recent BiLSTM-based approaches,
with biaffine classifiers to predict arcs and labels. Our parser gets state of
the art or near state of the art performance on standard treebanks for six
different languages, achieving 95.7% UAS and 94.1% LAS on the most popular
English PTB dataset. This makes it the highest-performing graph-based parser on
this benchmark---outperforming Kiperwasser Goldberg (2016) by 1.8% and
2.2%---and comparable to the highest performing transition-based parser
(Kuncoro et al., 2016), which achieves 95.8% UAS and 94.6% LAS. We also show
which hyperparameter choices had a significant effect on parsing accuracy,
allowing us to achieve large gains over other graph-based approaches.


title: On rainbow matchings for hypergraphs

abstract:
  For any posotive integer $m$, let $[m]:=\{1,\ldots,m\}$. Let $n,k,t$ be
positive integers. Aharoni and Howard conjectured that if, for $i\in [t]$,
$\mathcal{F}_i\subset[n]^k:= \{(a_1,\ldots,a_k): a_j\in [n] \mbox{ for } j\in
[k]\}$ and $|\mathcal{F}_i|>(t-1)n^{k-1}$, then there exist $M\subseteq [n]^k$
such that $|M|=t$ and $|M\cap \mathcal{F}_i|=1$ for $i\in [t]$ We show that
this conjecture holds when $n\geq 3(k-1)(t-1)$.
  Let $n, t, k_1\ge k_2\geq \ldots\geq k_t $ be positive integers. Huang, Loh
and Sudakov asked for the maximum $\Pi_{i=1}^t |{\cal
  R}_i|$ over all ${\cal R}=\{{\cal R}_1, \ldots ,{\cal R}_t\}$ such that each
${\cal R}_i$ is a collection of $k_i$-subsets of $[n]$ for which there does not
exist a collection $M$ of subsets of $[n]$ such that $|M|=t$ and $|M\cap
\mathcal{R}_i|=1$ for $i\in [t]$ %and ${\cal R}$ does not admit a rainbow
matching. We show that for sufficiently large $n$ with $\sum_{i=1}^t k_i\leq
n(1-(4k\ln n/n)^{1/k}) $, $\prod_{i=1}^t |\mathcal{R}_i|\leq {n-1\choose
k_1-1}{n-1\choose
  k_2-1}\prod_{i=3}^{t}{n\choose k_i}$. This bound is tight.


title: Block type Lie algebras and their representations

abstract:
  Block type Lie algebras have been studied by many authors in the latest
twenty years. In this paper, we will study a class of more general Block type
Lie algebra $\mathcal{B}(p,q)$, which is a class of infinite-dimensional Lie
algebra by using the generalized Balinskii-Novikov's construction method to
Witt type Novikov algebra. We study the representation theory for
$\mathcal{B}(p,q)$. We classify quasifinite irreducible highest weight
$\mathcal{B}(p,q)$-module. We also prove that any quasifinite irreducible
module of Block type Lie algebras $\mathcal{B}(p,q)$ is either a highest or
lowest weight module, or else a uniformly bounded module. This paper can be
considered as a generalization of the related literatures.


title:
Quasiclassical theory of magnetoelectric effects in superconducting
  heterostructures in the presence of the spin-orbit coupling

abstract:
  The quasiclassical theory in terms of equations for the Green's functions
(Eilenberger equations) is generalized in order to allow for quantitative
description of the magneto-electric effects and proximity-induced triplet
correlations in the presence of spin-orbit coupling in hybrid superconducting
systems. The formalism is valid under the condition that the spin-orbit
coupling is weak with respect to the Fermi energy, but exceeds the
superconducting energy scale considerably. On the basis of the derived
formalism it is shown that the triplet correlations in the spin-orbit coupled
normal metal can be induced by proximity to a singlet superconductor without
any exchange or external magnetic field. They contain an odd-frequency
even-momentum component, which is stable against disorder. The value of the
proximity-induced triplet correlations is of the order of
$\Delta_{so}/\varepsilon_F$, that is absent in the framework of the standard
quasiclassical approximation, but can be described by our theory. The spin
polarization, induced by the Josephson current flowing through the
superconductor/Rashba metal/superconductor junction, is also calculated.


title:
Einstein-Yang-Mills-Dirac systems from the discretized Kaluza-Klein
  theory

abstract:
  A unified theory of the non-Abelian gauge interactions with gravity in the
framework of a discretized Kaluaza-Kleine theory is constructed with a modified
Dirac operator and wedge product. All the couplings of chiral spinors to the
non-Abelian gauge fields emerge naturally as components of the couplings of the
chiral spinors to the generalized gravity together with some new interactions.
In particular, the currently prevalent gravity-QCD-quark and
gravity-electroweak-quark-lepton models are shown to follow as special cases of
the general framework.


title:
Quantitative aspects of the Beurling--Helson theorem: Phase functions of
  a special form

abstract:
  We consider the space $A(\mathbb{T}^d)$ of absolutely convergent Fourier
series on the torus $\mathbb{T}^d$. The norm on $A(\mathbb{T}^d)$ is naturally
defined by $\|f\|_{A}=\|\widehat{f}\|_{l^1}$, where $\widehat{f}$ is the
Fourier transform of a function $f$. For real functions $\varphi$ of a certain
special form on $\mathbb T^d, \,d\geq 2,$ we obtain lower bounds for the norms
$\|e^{i\lambda\varphi}\|_A$ as $\lambda\rightarrow\infty$. In particular, we
show that if $\varphi(x, y)=a(x)|y|$ for $|y|\leq\pi$, where $a\in
A(\mathbb{T})$ is an arbitrary nonconstant real function, then
$\|e^{i\lambda\varphi}\|_{A(\mathbb{T}^2)}\gtrsim |\lambda|$.


title: Maximal coherence in generic basis

abstract:
  Since quantum coherence is an undoubted characteristic trait of quantum
physics, the quantification and application of quantum coherence has been one
of the long-standing central topics in quantum information science. Within the
framework of a resource theory of quantum coherence proposed recently, a
\textit{fiducial basis} should be pre-selected for characterizing the quantum
coherence in specific circumstances, namely, the quantum coherence is a
\textit{basis-dependent} quantity. Therefore, a natural question is raised:
what are the maximum and minimum coherences contained in a certain quantum
state with respect to a generic basis? While the minimum case is trivial, it is
not so intuitive to verify in which basis the quantum coherence is maximal.
Based on the coherence measure of relative entropy, we indicate the particular
basis in which the quantum coherence is maximal for a given state, where the
Fourier matrix (or more generally, \textit{complex Hadamard matrices}) plays a
critical role in determining the basis. Intriguingly, though we can prove that
the basis associated with the Fourier matrix is a stationary point for
optimizing the $l_1$ norm of coherence, numerical simulation shows that it is
not a global optimal choice.


title:
On commensurability of right-angled Artin groups I: RAAGs defined by
  trees of diameter 4

abstract:
  In this paper we study the classification of right-angled Artin groups up to
commensurability. We characterise the commensurability classes of RAAGs defined
by trees of diameter 4. In particular, we prove a conjecture of Behrstock and
Neumann that there are infinitely many commensurability classes. Hence, we give
first examples of RAAGs that are quasi-isometric but not commensurable.


title:
Analytical Derivation of Downlink Data Rate Distribution for 5G HetNets
  with Cell-Edge Located Small Cells

abstract:
  In HetNets, time/frequency resources should be partitioned intelligently in
order to minimize the interference among the users. In this paper, the
probability distributions of per user downlink Data Rate, Spectral Efficiency
(SE) and Energy Efficiency (EE) are analytically derived for a HetNet model
with cell-edge located small cells. The high accuracy of analytically derived
CDFs have been verified by the distributions obtained via simulations. CDF
expressions have then been employed in order to optimize Key Parameter
Indicators (KPI) which are selected here as $10^{th}$ percentile downlink user
Data Rate ($R_{10}$), Spectral Efficiency ($SE_{10}$) and Energy Efficiency
($EE_{10}$).
  In addition to optimizing KPIs separately, employing the analytically derived
distributions, we have also investigated the variation of the KPIs with respect
to each other. The results have shown that the resource allocation parameter
values maximizing $R_{10}$ is very close to the values that maximize $SE_{10}$.
However, the values that are optimal for $SE_{10}$ and $R_{10}$, are not
optimal for $EE_{10}$, which demonstrates the EE and SE trade-off in HetNets.
We have also proposed a metric, $\theta$, aiming to jointly optimize SE and EE.
The results have shown the value of resource sharing parameter optimizing
$\theta$ is closer to the value that maximizes SE. This result shows that SE is
more critical in SE-EE trade-off.


title:
The Quantile Based Flattened Logistic Distribution: Some properties and
  Application

abstract:
  In this paper, the quantile based flattened logistic distribution introduced
by Gilchrist has been studied. Some classical and quantile based properties of
the distribution have been obtained. Closed form expression of L-moments and
L-ratios of the distribution have been obtained. A quantile based analysis
based on the methods of matching L-moments estimation is employed to estimate
the parameters of the proposed model. We further derive the asymptotic
variance-covariance matrix of the L-Moments estimator of the proposed model.
Finally, we apply the proposed model to a real data set and perform some
goodness of fit tests.


title:
Stellar electron capture rates on neutron-rich nuclei and their impact
  on core-collapse

abstract:
  During the late stages of gravitational core-collapse of massive stars,
extreme isospin asymmetries are reached within the core. Due to the lack of
microscopic calculations of electron capture (EC) rates for all relevant
nuclei, in general simple analytic parameterizations are employed. We study
here several extensions of these parameterizations, allowing for a temperature,
electron density and isospin dependence as well as for odd-even effects. The
latter extra degrees of freedom considerably improve the agreement with large
scale microscopic rate calculations. We find, in particular, that the isospin
dependence leads to a significant reduction of the global EC rates during core
collapse with respect to fiducial results, where rates optimized on
calculations of stable $fp$-shell nuclei are used. Our results indicate that
systematic microscopic calculations and experimental measurements in the
$N\approx 50$ neutron rich region are desirable for realistic simulations of
the core-collapse.


title: Ultrarelativistic bound states in the shallow spherical well

abstract:
  We determine approximate eigenvalues and eigenfunctions shapes for bound
states in the $3D$ shallow spherical ultrarelativistic well. Existence
thresholds for the ground state and first excited states are identified, both
in the purely radial and orbitally nontrivial cases. This contributes to an
understanding of how energy may be stored or accumulated in the form of bound
states of Schr\"odinger - type quantum systems that are devoid of any mass.


title:
Heating mechanisms in the low solar atmosphere through magnetic
  reconnection in current sheets

abstract:
  We simulate several magnetic reconnection processes in the low solar
chromosphere/photosphere, the radiation cooling, heat conduction and ambipolar
diffusion are all included. Our numerical results indicate that both the high
temperature($ \gtrsim 8\times10^4$~K) and low temperature($\sim 10^4$~K)
magnetic reconnection events can happen in the low solar atmosphere
($100\sim600$~km above the solar surface). The plasma $\beta$ controlled by
plasma density and magnetic fields is one important factor to decide how much
the plasma can be heated up. The low temperature event is formed in a high
$\beta$ magnetic reconnection process, Joule heating is the main mechanism to
heat plasma and the maximum temperature increase is only several thousand
Kelvin. The high temperature explosions can be generated in a low $\beta$
magnetic reconnection process, slow and fast-mode shocks attached at the edges
of the well developed plasmoids are the main physical mechanisms to heat the
plasma from several thousand Kelvin to over $8\times10^4$~K. Gravity in the low
chromosphere can strongly hinder the plasmoind instability and the formation of
slow-mode shocks in a vertical current sheet. Only small secondary islands are
formed; these islands, however, are not well developed as those in the
horizontal current sheets. This work can be applied for understanding the
heating mechanism in the low solar atmosphere and could possibly be extended to
explain the formation of common low temperature EBs ($\sim10^4$~K) and the high
tenperature IRIS bombs ($\gtrsim 8\times10^4$) in the future.


title: A Compare-Aggregate Model for Matching Text Sequences

abstract:
  Many NLP tasks including machine comprehension, answer selection and text
entailment require the comparison between sequences. Matching the important
units between sequences is a key to solve these problems. In this paper, we
present a general "compare-aggregate" framework that performs word-level
matching followed by aggregation using Convolutional Neural Networks. We
particularly focus on the different comparison functions we can use to match
two vectors. We use four different datasets to evaluate the model. We find that
some simple comparison functions based on element-wise operations can work
better than standard neural network and neural tensor network.


title:
Connection between fragility, mean-squared displacement and shear
  modulus in two van der Waals bonded glass-forming liquids

abstract:
  The temperature dependence of the high-frequency shear modulus measured in
the kHz range is compared to the mean-squared displacement measured in the
nanosecond range for the two van der Waals bonded glass-forming liquids cumene
and 5PPE. This provides an experimental test for the assumption connecting two
versions of the shoving model for the non-Arrhenius temperature dependence of
the relaxation time in glass formers. The two versions of the model are also
tested directly and both are shown to work well for these liquids.


title:
Amenability and subexponential spectral growth rate of Dirichlet forms
  on von Neumann algebras

abstract:
  In this work we apply Noncommutative Potential Theory to prove (relative)
amenability and the (relative) Haagerup Property $(H)$ of von Neumann algebras
in terms of the spectral growth of Dirichlet forms. Examples deal with
(inclusions of) countable discrete groups and free orthogonal compact quantum
groups.


title:
Inverted dipole feature in directional detection of exothermic dark
  matter

abstract:
  Directional dark matter detection attempts to measure the direction of motion
of nuclei recoiling after having interacted with dark matter particles in the
halo of our Galaxy. Due to Earth's motion with respect to the Galaxy, the dark
matter flux is concentrated around a preferential direction. An anisotropy in
the recoil direction rate is expected as an unmistakable signature of dark
matter. The average nuclear recoil direction is expected to coincide with the
average direction of dark matter particles arriving to Earth. Here we point out
that for a particular type of dark matter, inelastic exothermic dark matter,
the mean recoil direction as well as a secondary feature, a ring of maximum
recoil rate around the mean recoil direction, could instead be opposite to the
average dark matter arrival direction. Thus, the detection of an average
nuclear recoil direction opposite to the usually expected direction would
constitute a spectacular experimental confirmation of this type of dark matter.


title: Deep Convolutional Neural Network Features and the Original Image

abstract:
  Face recognition algorithms based on deep convolutional neural networks
(DCNNs) have made progress on the task of recognizing faces in unconstrained
viewing conditions. These networks operate with compact feature-based face
representations derived from learning a very large number of face images. While
the learned features produced by DCNNs can be highly robust to changes in
viewpoint, illumination, and appearance, little is known about the nature of
the face code that emerges at the top level of such networks. We analyzed the
DCNN features produced by two face recognition algorithms. In the first set of
experiments we used the top-level features from the DCNNs as input into linear
classifiers aimed at predicting metadata about the images. The results show
that the DCNN features contain surprisingly accurate information about the yaw
and pitch of a face, and about whether the face came from a still image or a
video frame. In the second set of experiments, we measured the extent to which
individual DCNN features operated in a view-dependent or view-invariant manner.
We found that view-dependent coding was a characteristic of the identities
rather than the DCNN features - with some identities coded consistently in a
view-dependent way and others in a view-independent way. In our third analysis,
we visualized the DCNN feature space for over 24,000 images of 500 identities.
Images in the center of the space were uniformly of low quality (e.g., extreme
views, face occlusion, low resolution). Image quality increased monotonically
as a function of distance from the origin. This result suggests that image
quality information is available in the DCNN features, such that consistently
average feature values reflect coding failures that reliably indicate poor or
unusable images. Combined, the results offer insight into the coding mechanisms
that support robust representation of faces in DCNNs.


title: Learning a Static Analyzer from Data

abstract:
  To be practically useful, modern static analyzers must precisely model the
effect of both, statements in the programming language as well as frameworks
used by the program under analysis. While important, manually addressing these
challenges is difficult for at least two reasons: (i) the effects on the
overall analysis can be non-trivial, and (ii) as the size and complexity of
modern libraries increase, so is the number of cases the analysis must handle.
  In this paper we present a new, automated approach for creating static
analyzers: instead of manually providing the various inference rules of the
analyzer, the key idea is to learn these rules from a dataset of programs. Our
method consists of two ingredients: (i) a synthesis algorithm capable of
learning a candidate analyzer from a given dataset, and (ii) a counter-example
guided learning procedure which generates new programs beyond those in the
initial dataset, critical for discovering corner cases and ensuring the learned
analysis generalizes to unseen programs.
  We implemented and instantiated our approach to the task of learning
JavaScript static analysis rules for a subset of points-to analysis and for
allocation sites analysis. These are challenging yet important problems that
have received significant research attention. We show that our approach is
effective: our system automatically discovered practical and useful inference
rules for many cases that are tricky to manually identify and are missed by
state-of-the-art, manually tuned analyzers.


title: Universe opacity and EBL

abstract:
  The observed extragalactic background light (EBL) is affected by light
attenuation due to absorption of light by galactic and intergalactic dust in
the Universe. Even galactic opacity of 10-20 percent and minute universe
intergalactic opacity of $0.01\,\mathrm{mag}\,h\,\mathrm{Gpc}^{-1}$ at the
local Universe have a significant impact on the EBL because obscuration of
galaxies and density of intergalactic dust increase with redshift as
$\left(1+z\right)^3$. Consequently, intergalactic opacity increases and the
Universe becomes considerably opaque at $z > 3$. Adopting realistic values for
galactic and intergalactic opacity, the estimates of the EBL for the expanding
dusty universe are close to observations. The luminosity density evolution fits
well measurements. The model reproduces a steep increase of the luminosity
density at $z<2$, its maximum at $z=2-3$, and its decrease at higher redshifts.
The increase of the luminosity density at low $z$ is not produced by the
evolution of the star formation rate but by the fact that the Universe occupied
a smaller volume in previous epochs. The decline of the luminosity density at
high $z$ originates in the opacity of the Universe. The calculated bolometric
EBL ranges from 100 to 200 $\mathrm{n W m}^{-2}\mathrm{sr}^{-1}$ and is within
the limits of 40 and 200 $\mathrm{n W m}^{-2}\mathrm{sr}^{-1}$ of current EBL
observations. The model predicts 98\% of the EBL coming from radiation of
galaxies at $z<3.5$. Accounting for light extinction by intergalactic dust
implies that the Universe was probably more opaque than dark for $z>3.5$.


title: Forensics in Industrial Control System: A Case Study

abstract:
  Industrial Control Systems (ICS) are used worldwide in critical
infrastructures. An ICS system can be a single embedded system working
stand-alone for controlling a simple process or ICS can also be a very complex
Distributed Control System (DCS) connected to Supervisory Control And Data
Acquisition (SCADA) system(s) in a nuclear power plant. Although ICS are widely
used to-day, there are very little research on the forensic acquisition and
analyze ICS artefacts. In this paper we present a case study of forensics in
ICS where we de-scribe a method of safeguarding important volatile artefacts
from an embedded industrial control system and several other sources


title: Large Fixed-Diameter Graphs are Good Expanders

abstract:
  We revisit the classical question of the relationship between the diameter of
a graph and its expansion properties. One direction is well understood:
expander graphs exhibit essentially the lowest possible diameter. We focus on
the reverse direction, showing that "sufficiently large" graphs of fixed
diameter and degree must be "good" expanders. We prove this statement for
various definitions of "sufficiently large" (multiplicative/additive factor
from the largest possible size), for different forms of expansion (edge,
vertex, and spectral expansion), and for both directed and undirected graphs. A
recurring theme is that the lower the diameter of the graph and (more
importantly) the larger its size, the better the expansion guarantees. Aside
from inherent theoretical interest, our motivation stems from the domain of
network design. Both low-diameter networks and expanders are prominent
approaches to designing high-performance networks in parallel computing, HPC,
datacenter networking, and beyond. Our results establish that these two
approaches are, in fact, inextricably intertwined. We leave the reader with
many intriguing questions for future research.


title: Amenable colorings

abstract:
  Let $\kappa$ be any regular cardinal. Assuming the existence of a huge
cardinal above $\kappa$, we prove the consistency of
$\binom{\kappa^{++}}{\kappa^+}\rightarrow\binom{\tau}{\kappa^+}$ for every
ordinal $\tau<\kappa^{++}$. Likewise, we prove a full amenable relation for
$(\aleph_2,\aleph_1)$ with respect to collections which are strongly closed
under countable intersections.


title:
Lattice thermal conductivity of Ti$_x$Zr$_y$Hf$_{1-x-y}$NiSn
  half-Heusler alloys calculated from first principles: Key role of nature of
  phonon modes

abstract:
  In spite of their relatively high lattice thermal conductivity
$\kappa_{\ell}$, the XNiSn (X=Ti, Zr or Hf) half-Heusler compounds are good
thermoelectric materials. Previous studies have shown that $\kappa_{\ell}$ can
be reduced by sublattice-alloying on the X-site. To cast light on how the alloy
composition affects $\kappa_\ell$, we study this system using the phonon
Boltzmann-transport equation within the relaxation time approximation in
conjunction with density functional theory.The effect of alloying through
mass-disorder scattering is explored using the virtual crystal approximation to
screen the entire ternary Ti$_x$Zr$_{y}$Hf$_{1-x-y}$NiSn phase diagram. The
lowest lattice thermal conductivity is found for the Ti$_x$Hf$_{1-x}$NiSn
compositions; in particular, there is a shallow minimum centered at
Ti$_{0.5}$Hf$_{0.5}$NiSn with $\kappa_l$ taking values between 3.2 and 4.1 W/mK
when the Ti content varies between 20 and 80\%. Interestingly, the overall
behavior of mass-disorder scattering in this system can only be understood from
a combination of the nature of the phonon modes and the magnitude of the mass
variance. Mass-disorder scattering is not effective at scattering acoustic
phonons of low energy. By using a simple model of grain boundary scattering, we
find that nanostructuring these compounds can scatter such phonons effectively
and thus further reduce the lattice thermal conductivity; for instance,
Ti$_{0.5}$Hf$_{0.5}$NiSn with a grain size of $L= 100$ nm experiences a 42\%
reduction of $\kappa_{\ell}$ compared to that of the single crystal.


title: Black hole mining in the RST model

abstract:
  We consider the possibility of mining black holes in the 1+1-dimensional
dilaton gravity model of Russo, Susskind and Thorlacius. The model correctly
incorporates Hawking radiation and back-reaction in a semiclassical expansion
in 1/N, where N is the number of matter species. It is shown that the lifetime
of a perturbed black hole is independent of the addition of any extra apparatus
when realized by an arbitrary positive energy matter source. We conclude that
mining does not occur in the RST model and comment on the implications of this
for the black hole information paradox.