title:
The mitotic spindle in the one-cell C. elegans embryo is positioned with
  high precision and stability

abstract:
  Precise positioning of the mitotic spindle is important for specifying the
plane of cell division, which in turn determines how the cytoplasmic contents
are partitioned into the daughter cells, and how the daughters are positioned
within the tissue. During metaphase in the early C. elegans embryo, the spindle
is aligned and centered on the anterior-posterior axis by a
microtubule-dependent machinery that exerts restoring forces when the spindle
is displaced from the center. To investigate the accuracy and stability of
centering, we tracked the position and orientation of the mitotic spindle
during the first cell division with high temporal and spatial resolution. We
found that the precision is remarkably high: the cell-to-cell variation in the
transverse position of the center of the spindle during metaphase, as measured
by the standard deviation, was only 1.5% of the length of the short axis of the
cell. Spindle position is also very stable: the standard deviation of the
fluctuations in transverse spindle position during metaphase was only 0.5% of
the short axis of the cell. Assuming that stability is limited by fluctuations
in the number of independent motor elements such as microtubules or dyneins
underlying the centering machinery, we infer that the number is on the order of
one thousand, consistent with the several thousand of astral microtubules in
these cells. Astral microtubules grow out from the two spindle poles, make
contact with the cell cortex, and then shrink back shortly thereafter. The high
stability of centering can be accounted for quantitatively if, while making
contact with the cortex, the astral microtubules buckle as they exert
compressive, pushing forces. We thus propose that the large number of
microtubules in the asters provides a highly precise mechanism for positioning
the spindle during metaphase while assembly is completed prior to the onset of
anaphase.


title: On a theta lift related to the Shintani lift

abstract:
  We study a certain theta lift which maps weight $-2k$ to weight $1/2-k$
harmonic weak Maass forms for $k \in \mathbb{Z}, k \geq 0$, and which is
closely related to the classical Shintani lift from weight $2k+2$ to weight
$k+3/2$ cusp forms. We compute the Fourier expansion of the theta lift and show
that it involves twisted traces of CM values and geodesic cycle integrals of
the input function. As an application, we obtain a criterion for the
non-vanishing of the central $L$-value of an integral weight newform $G$ in
terms of the holomorphicity of the theta lift of a certain harmonic weak Maass
form associated to $G$. Moreover, we derive interesting identities between
cycle integrals of different kinds of modular forms.


title: Community Detection Using Multilayer Edge Mixture Model

abstract:
  A wide range of complex systems can be modeled as networks with corresponding
constraints on the edges and nodes, which have been extensively studied in
recent years. Nowadays, with the progress of information technology, systems
that contain the information collected from multiple perspectives have been
generated. The conventional models designed for single perspective networks
fail to depict the diverse topological properties of such systems, so
multilayer network models aiming at describing the structure of these networks
emerge. As a major concern in network science, decomposing the networks into
communities, which usually refers to closely interconnected node groups,
extracts valuable information about the structure and interactions of the
network. Unlike the contention of dozens of models and methods in conventional
single-layer networks, methods aiming at discovering the communities in the
multilayer networks are still limited. In order to help explore the community
structure in multilayer networks, we propose the multilayer edge mixture model,
which explores a relatively general form of a community structure evaluator
from an edge combination view. As an example, we demonstrate that the
multilayer modularity and stochastic blockmodels can be derived from the
proposed model. We also explore the decomposition of community structure
evaluators with specific forms to the multilayer edge mixture model
representation, which turns out to reveal some new interpretation of the
evaluators. The flexibility and performance on different networks of the
proposed model are illustrated with applications on a series of benchmark
networks.


title:
A note on central limit theorems for quadratic variation in case of
  endogenous observation times

abstract:
  This paper is concerned with a central limit theorem for quadratic variation
when observations come as exit times from a regular grid. We discuss the
special case of a semimartingale with deterministic characteristics and finite
activity jumps in detail and illustrate technical issues in more general
situations.


title: Bayesian Model Selection of Stochastic Block Models

abstract:
  A central problem in analyzing networks is partitioning them into modules or
communities. One of the best tools for this is the stochastic block model,
which clusters vertices into blocks with statistically homogeneous pattern of
links. Despite its flexibility and popularity, there has been a lack of
principled statistical model selection criteria for the stochastic block model.
Here we propose a Bayesian framework for choosing the number of blocks as well
as comparing it to the more elaborate degree- corrected block models,
ultimately leading to a universal model selection framework capable of
comparing multiple modeling combinations. We will also investigate its
connection to the minimum description length principle.


title:
Simplified DM models with the full SM gauge symmetry : the case of
  $t$-channel colored scalar mediators

abstract:
  The general strategy for dark matter (DM) searches at colliders currently
relies on simplified models. In this paper, we propose a new $t$-channel
UV-complete simplified model that improves the existing simplified DM models in
two important respects: (i) we impose the full SM gauge symmetry including the
fact that the left-handed and the right-handed fermions have two independent
mediators with two independent couplings, and (ii) we include the
renormalization group evolution when we derive the effective Lagrangian for
DM-nucleon scattering from the underlying UV complete models by integrating out
the $t$-channel mediators. The first improvement will introduce a few more new
parameters compared with the existing simplified DM models. In this study we
look at the effect this broader set of free parameters has on direct detection
and the mono-$X$ + MET ($X$=jet,$W,Z$) signatures at 13 TeV LHC while
maintaining gauge invariance of the simplified model under the full SM gauge
group. We find that the direct detection constraints require DM masses less
than 10 GeV in order to produce phenomenologically interesting collider
signatures. Additionally, for a fixed mono-W cross section it is possible to
see very large differences in the mono-jet cross section when the usual
simplified model assumptions are loosened and isospin violation between RH and
LH DM-SM quark couplings are allowed.


title: Absolute parameters for AI Phoenicis using WASP photometry

abstract:
  AI Phe is a double-lined, detached binary, in which a K-type sub-giant star
totally eclipses its main-sequence companion every 24.6 days. This
configuration makes AI Phe ideal for testing stellar evolutionary models.
Difficulties in obtaining a complete lightcurve mean the precision of existing
radii measurements could be improved. Our aim is to improve the precision of
the radius measurements for the stars in AI Phe using high-precision photometry
from WASP, and use these improved radius measurements together with estimates
of the masses, temperatures and composition of the stars to place constraints
on the mixing length, helium abundance and age of the system. A best-fit ebop
model is used to obtain lightcurve parameters, with their standard errors
calculated using a prayer-bead algorithm. These were combined with previously
published spectroscopic orbit results, to obtain masses and radii. A Bayesian
method is used to estimate the age of the system for model grids with different
mixing lengths and helium abundances. The radii are found to be
$R_1=1.835\pm0.014$ R$_{\odot}$, $R_2=2.912\pm0.014$ R$_{\odot}$ and the masses
$M_1=1.1973\pm0.0037$ M$_{\odot}$, $M_2=1.2473\pm0.0039$ M$_{\odot}$. From the
best-fit stellar models we infer a mixing length of 1.78, a helium abundance of
$Y_{AI}=0.26^{+0.02}_{-0.01}$ and an age of $4.39\pm0.32$ Gyr. Times of primary
minimum show the period of AI Phe is not constant. Currently, there are
insufficient data to determine the cause of this variation. Improved precision
in the masses and radii have improved the age estimate, and allowed the mixing
length and helium abundance to be constrained. The eccentricity is now the
largest source of uncertainty in calculating the masses. More binaries with
parameters measured to a similar level of precision would allow us to test for
relationships between helium abundance and mixing length.


title: Magnetic confinement and the Linde problem

abstract:
  Perturbation theory of thermodynamic potentials in QCD at $T>T_c$ is
considered with the nonperturbative background vacuum taken into account. It is
shown that the magnetic confinement in the QCD vacuum prevents the infrared
catastrophe of the perturbation theory present in the case of the free vacuum
(the "Linde problem"). A short discussion is given of the applicability of the
nonperturbative formalism at large $T$ and of the relation with the HTL
theory.The observation of A.D.Linde, that the terms $O(g^n), n>6$ contribute to
the order $O(g^6)$ is confirmed also with the account of the colormagnetic
confinement, and it is shown that the latter makes these terms IR convergent,
and summable. As a result one obtains the selfconsistent theory of the gluon
plasma.


title: On Restricted Nonnegative Matrix Factorization

abstract:
  Nonnegative matrix factorization (NMF) is the problem of decomposing a given
nonnegative $n \times m$ matrix $M$ into a product of a nonnegative $n \times
d$ matrix $W$ and a nonnegative $d \times m$ matrix $H$. Restricted NMF
requires in addition that the column spaces of $M$ and $W$ coincide. Finding
the minimal inner dimension $d$ is known to be NP-hard, both for NMF and
restricted NMF. We show that restricted NMF is closely related to a question
about the nature of minimal probabilistic automata, posed by Paz in his seminal
1971 textbook. We use this connection to answer Paz's question negatively, thus
falsifying a positive answer claimed in 1974. Furthermore, we investigate
whether a rational matrix $M$ always has a restricted NMF of minimal inner
dimension whose factors $W$ and $H$ are also rational. We show that this holds
for matrices $M$ of rank at most $3$ and we exhibit a rank-$4$ matrix for which
$W$ and $H$ require irrational entries.


title: On Clifford Algebras and binary integers

abstract:
  We show that the binary representation of the integers has a role to play in
many aspects of Clifford algebras.


title:
Stimulated low-frequency Raman scattering in tobacco mosaic virus
  suspension

abstract:
  Laser pulses interaction with tobacco mosaic virus (TMV) in Tris-HCl pH7.5
buffer and in water has been investigated. 20 ns ruby laser pulses have been
used for excitation. Spectrum of the light passing through the sample was
registered with the help of Fabri-Perot interferometer. In the case of TMV in
water we observed in the spectrum only one line of the exciting laser light,
for TMV in Tris-HCl pH7.5 buffer second line appeared, corresponding to the
stimulated low-frequency Raman scattering (SLFRS) on the breathing radial mode
of TMV. SLFRS frequency shift by 2 cm-1, (60 GHz), conversion efficiency and
threshold are measured for the first time to the best of our knowledge.


title:
A real-time lattice simulation of the thermalization of a gluon plasma:
  first results

abstract:
  To achieve an understanding of the thermalization of a quark-gluon plasma,
starting from QCD without using model assumptions, is a formidable task. We
study the early stage dynamics of a relativistic heavy ion collision in the
framework of real time simulations of classical Yang-Mills theory in a static
box with the color glass condensate as initial condition. Our study generalizes
a previous one by Fukushima and Gelis from SU(2) to the realistic case of
SU(3). We calculate the chromo-electric and chromo-magnetic energy densities as
well as the ratio of longitudinal and transverse pressure as a function of time
as probes for thermalization. Our preliminary results on coarse lattices show
the occurrence of Weibel instabilities prior to thermalization.


title:
Assessment of Multireference Approaches to Explicitly Correlated Full
  Configuration Interaction Quantum Monte Carlo

abstract:
  The Full Configuration Interaction Quantum Monte Carlo (FCIQMC) method has
proved able to provide near-exact solutions to the electronic Schr\"odinger
equation within a finite orbital basis set, without relying on an expansion
about a reference state. However, a drawback to the approach is that being
based on an expansion of Slater determinants, the FCIQMC method suffers from a
basis set incompleteness error that decays very slowly with the size of the
employed single particle basis. The FCIQMC results obtained in a small basis
set can be improved significantly with explicitly correlated techniques. Here,
we present a study that assesses and compares two contrasting `universal'
explicitly correlated approaches that fit into the FCIQMC framework; the
$[2]_{R12}$ method of Valeev {\em et al.}, and the explicitly correlated
canonical transcorrelation approach of Yanai {\em et al}. The former is an {\em
a posteriori} internally-contracted perturbative approach, while the latter
transforms the Hamiltonian prior to the FCIQMC simulation. These comparisons
are made across the 55 molecules of the G1 standard set. We found that both
methods consistently reduce the basis set incompleteness, for accurate
atomization energies in small basis sets, reducing the error from 28~mE$_{\text
h}$ to 3-4~mE$_{\text h}$. While many of the conclusions hold in general for
any combination of multireference approaches with these methodologies, we also
consider FCIQMC-specific advantages of each approach.


title:
A Unifying Framework for Gaussian Process Pseudo-Point Approximations
  using Power Expectation Propagation

abstract:
  Gaussian processes (GPs) are flexible distributions over functions that
enable high-level assumptions about unknown functions to be encoded in a
parsimonious, flexible and general way. Although elegant, the application of
GPs is limited by computational and analytical intractabilities that arise when
data are sufficiently numerous or when employing non-Gaussian models.
Consequently, a wealth of GP approximation schemes have been developed over the
last 15 years to address these key limitations. Many of these schemes employ a
small set of pseudo data points to summarise the actual data. In this paper, we
develop a new pseudo-point approximation framework using Power Expectation
Propagation (Power EP) that unifies a large number of these pseudo-point
approximations. Unlike much of the previous venerable work in this area, the
new framework is built on standard methods for approximate inference
(variational free-energy, EP and Power EP methods) rather than employing
approximations to the probabilistic generative model itself. In this way, all
of approximation is performed at `inference time' rather than at `modelling
time' resolving awkward philosophical and empirical questions that trouble
previous approaches. Crucially, we demonstrate that the new framework includes
new pseudo-point approximation methods that outperform current approaches on
regression and classification tasks.


title:
Thermal expansion and transport in van der Waals solids from
  first-principles calculations

abstract:
  The lattice thermal expansion and conductivity in bulk Mo and W-based
transition metal dichalcogenides are investigated by means of density
functional and Boltzmann transport theory calculations. To this end, a recent
van der Waals density functional (vdW-DF-CX) is employed, which is shown to
yield excellent agreement with reference data for the structural parameters.
The calculated in-plane thermal conductivity compares well with experimental
room temperature values, when phonon-phonon and isotopic scattering are
included. To explain the behavior over the entire available temperature range
one must, however, include additional (temperature independent) scattering
mechanisms that limit the mean free path. Generally, the primary heat carrying
modes have mean free paths of $1\,\mu\text{m}$ or more, which makes these
materials very susceptible to structural defects. The conductivity of Mo and
W-based TMDs is primarily determined by the chalcogenide species and increases
in the order Te-Se-S. While for the tellurides and selenides the transition
metal element has a negligible effect, the conductivity of WS$_2$ is notably
higher than for MoS$_2$, which can be traced to the much larger phonon band gap
of the former. Overall the present study provides a consistent set of thermal
conductivities that reveal chemical trends and constitute the basis for future
investigations of van der Waals solids.


title:
Incorporating Quotation and Evaluation into Church's Type Theory: Syntax
  and Semantics

abstract:
  ${\rm \small CTT}_{\rm qe}$ is a version of Church's type theory that
includes quotation and evaluation operators that are similar to quote and eval
in the Lisp programming language. With quotation and evaluation it is possible
to reason in ${\rm \small CTT}_{\rm qe}$ about the interplay of the syntax and
semantics of expressions and, as a result, to formalize syntax-based
mathematical algorithms. We present the syntax and semantics of ${\rm \small
CTT}_{\rm qe}$ and give several examples that illustrate the usefulness of
having quotation and evaluation in ${\rm \small CTT}_{\rm qe}$. We do not give
a proof system for ${\rm \small CTT}_{\rm qe}$, but we do sketch what a proof
system could look like.


title:
On the Degrees of Freedom of SISO X-networks with Synergistic
  Alternating Channel State Information at transmitters

abstract:
  In this paper, we consider the two-user single-input single-output (SISO)
X-channel and $K$-user SISO X-network in fast fading environment. It is assumed
that the transmitters have access to synergistic alternating channel state
information (CSI). Specifically, the CSIT alternates between three states,
namely, perfect, delayed and no-CSIT, in a certain manner to enable these
states to work together cooperatively. These states are associated with
fractions of time denoted by $\lambda_P$, $\lambda_D$ \text{and} $\lambda_N$,
respectively. For the two-user $X$-channel, simple upper bound is developed to
prove the tightness of the achievability result of $4/3$ DoF under a certain
distribution of the availability of three CSIT states for
$\Lambda(\lambda_P=1/3, \lambda_D= 1/3, \lambda_N=1/3)$. For the $K$-user
$X$-network, it is shown that the sum Degrees of freedom (DoF) is at least
$2K/(K + 1)$, using two-phase transmission schemes over finite symbols channel
extension and under the same distribution of the availability of
$\Lambda(\lambda_P=1/3, \lambda_D= 1/3, \lambda_N=1/3)$.This achievability
result, can be considered as a tight lower bound, coincides with the best lower
bound known for the same network but with partial output feedback in stead of
alternating CSIT. Hence, we show that the role of synergistic alternating CSIT
with distribution $\Lambda(1/3,1/3,1/3)$ is equivalent to the partial output
feedback. Also, this lower bound is strictly better than the best lower bound
known for the case of delayed CSI assumption for all values of $K$. All the
proposed transmission schemes are based on two phases transmission strategy,
namely, interference creation and interference resurrection, which exploit the
synergy of instantaneous CSI and delay CSIT to retrospectively align
interference in the subsequent channel uses.


title: Conformal reference frames for Lorentzian manifolds

abstract:
  We define a conformal reference frame, i.e., a special projection of the
six-dimensional sky bundle of a Lorentzian manifold (or the five-dimensional
twistor space) to a three-dimensional manifold. We construct an example, a
conformal compactification, for Minkowski space. Based on the complex structure
on the skies, we define the celestial transform of Lorentzian vectors, a kind
of spinor correspondence. We express a 1-form generating the contact structure
explicitly as a (line bundle)-valued form. We prove a theorem on the projection
of this 1-form to the fiberwise normal bundle of a reference frame; its
corollary is an equation for the flow of time.
  The Appendix is less mathematical than the main body and discusses the causal
relation in context of the FLRW cosmology and its natural conformal reference
frame.


title:
Strict positive definiteness on a product of compact two-point
  homogeneous spaces

abstract:
  We present an explicit characterization for the real, continuous, isotropic
and strictly positive definite kernels on a product of compact two-point
homogeneous spaces, in the cases in which at least one of the spaces is a
sphere of dimension greater than 1 and the other is not a circle. The result
complements similar characterizations previously obtained for products of high
dimensional spheres.


title: Generalized Stability Approach for Regularized Graphical Models

abstract:
  Selecting regularization parameters in penalized high-dimensional graphical
models in a principled, data-driven, and computationally efficient manner
continues to be one of the key challenges in high-dimensional statistics. We
present substantial computational gains and conceptual generalizations of the
Stability Approach to Regularization Selection (StARS), a state-of-the-art
graphical model selection scheme. Using properties of the Poisson-Binomial
distribution and convex non-asymptotic distributional modeling we propose lower
and upper bounds on the StARS graph regularization path which results in
greatly reduced computational cost without compromising regularization
selection. We also generalize the StARS criterion from single edge to induced
subgraph (graphlet) stability. We show that simultaneously requiring edge and
graphlet stability leads to superior graph recovery performance independent of
graph topology. These novel insights render Gaussian graphical model selection
a routine task on standard multi-core computers.


title:
An effective mean field theory for the coexistence of
  anti-ferromagnetism and superconductivity: Applications to iron-based
  superconductors and cold Bose-Fermi atomic mixtures

abstract:
  We study an effective fermion model on a square lattice to investigate the
cooperation and competition of superconductivity and anti-ferromagnetism. In
addition to particle tunneling and on-site interaction, a bosonic excitation
mediated attractive interaction is also included in the model. We assume that
the attractive interaction is mediated by spin fluctuations and excitations of
Bose-Einstein condensation (BEC) in electronic systems and Bose-Fermi mixtures
on optical lattices, respectively. Using an effective mean-field theory to
treat both superconductivity and anti-ferromagnetism at equal footing, we study
the model within the Landau energy functional approach and a linearized theory.
Within our approaches, we find possible co-existence of superconductivity and
anti-ferromagnetism for both electronic and cold-atomic models. Our linearized
theory shows while spin fluctuations favor d-wave superconductivity and BEC
excitations favor s-wave superconductivity.


title: Initial conditions in the neural field model

abstract:
  In spite of the large amount of existing neural models in the literature,
there is a lack of a systematic review of the possible effect of choosing
different initial conditions on the dynamic evolution of neural systems. In
this short review we intend to give insights into this topic by discussing some
published examples. First, we briefly introduce the different ingredients of a
neural dynamical model. Secondly, we introduce some concepts used to describe
the dynamic behavior of neural models, namely phase space and its portraits,
time series, spectra, multistability and bifurcations. We end with an analysis
of the irreversibility of processes and its implications on the functioning of
normal and pathological brains.


title: Rare decays at LHCb

abstract:
  Rare decays are flavour changing neutral current processes that are
loop-suppressed in the Standard Model (SM). New particles in SM extensions can
therefore give significant contributions, modifying branching fractions and
angular distributions. Consequently, rare decays are particularly sensitive
probes for New Physics (NP). These proceedings summarize the latest results
from the LHCb experiment on rare decays. While most results are in good
agreement with SM predictions, some tensions that recently appeared in rare
semileptonic $b\to s\ell^+\ell^-$ decays are also discussed.


title: Int\'egrales orbitales sur $GL(N,{\Bbb F}_q((t)))$

abstract:
  Let $F$ be a non--Archimedean local field of characteristic $\geq 0$, and let
$G=GL(N,F)$, $N\geq 1$. An element $\gamma\in G$ is said to be quasi--regular
if the centralizer of $\gamma$ in $M(N,F)$ is a product of field extensions of
$F$. Let $G_{\rm qr}$ be the set of quasi--regular elements of $G$. For
$\gamma\in G_{\rm qr}$, we denote by $\mathcal{O}_\gamma$ the ordinary orbital
integral on $G$ associated with $\gamma$. In this paper, we replace the Weyl
discriminant $\vert D_G\vert$ by a normalization factor $\eta_G: G_{\rm
qr}\rightarrow {\Bbb R}_{>0}$ which allows us to obtain the same results as
proven by Harish--Chandra in characteristic zero: for $f\in C^\infty_{\rm
c}(G)$, the normalized orbital integral $I^G(\gamma,f)=\eta_G^{1\over
2}(\gamma)\mathcal{O}_\gamma(f)$ is bounded on $G$, and for $\epsilon>0$ such
that $N(N-1)\epsilon <1$, the function $\eta_G^{-{1\over 2}-\epsilon}$ is
locally integrable on $G$.


title: Resonant impurities states-driven topological transition in quantum well

abstract:
  We demonstrate theoretically that a new system quantum well can realize the
topological transition based on the 16-band kp model. Utilizing the strain
introduced by the doped impurities, the band anti crossing induced by the doped
nitrogen and valence band anti crossing induced by the doped bismuth, the band
gap of the quantum well is rapidly decreased and even becomes negative. As a
result, the topological transitions arise. Furthermore, the band gap as a
function of the concentration of nitrogen and bismuth is calculated, where the
negative gap corresponds to the topological phase. Noting the cancel of strain
resulting from the combination of tensile strain introduced by N and strain
introduced by Bi, we can easily tune the ratio of the N and Bi to meet the
requirement of strain in the crystal growth procedure. Our proposal provides a
promising approach for topological insulator in traditional semiconductor
system utilizing the semiconductor fabrication technologies.


title: Learning Sensor Multiplexing Design through Back-propagation

abstract:
  Recent progress on many imaging and vision tasks has been driven by the use
of deep feed-forward neural networks, which are trained by propagating
gradients of a loss defined on the final output, back through the network up to
the first layer that operates directly on the image. We propose
back-propagating one step further---to learn camera sensor designs jointly with
networks that carry out inference on the images they capture. In this paper, we
specifically consider the design and inference problems in a typical color
camera---where the sensor is able to measure only one color channel at each
pixel location, and computational inference is required to reconstruct a full
color image. We learn the camera sensor's color multiplexing pattern by
encoding it as layer whose learnable weights determine which color channel,
from among a fixed set, will be measured at each location. These weights are
jointly trained with those of a reconstruction network that operates on the
corresponding sensor measurements to produce a full color image. Our network
achieves significant improvements in accuracy over the traditional Bayer
pattern used in most color cameras. It automatically learns to employ a sparse
color measurement approach similar to that of a recent design, and moreover,
improves upon that design by learning an optimal layout for these measurements.


title:
Fast Bayesian Optimization of Machine Learning Hyperparameters on Large
  Datasets

abstract:
  Bayesian optimization has become a successful tool for hyperparameter
optimization of machine learning algorithms, such as support vector machines or
deep neural networks. Despite its success, for large datasets, training and
validating a single configuration often takes hours, days, or even weeks, which
limits the achievable performance. To accelerate hyperparameter optimization,
we propose a generative model for the validation error as a function of
training set size, which is learned during the optimization process and allows
exploration of preliminary configurations on small subsets, by extrapolating to
the full dataset. We construct a Bayesian optimization procedure, dubbed
Fabolas, which models loss and training time as a function of dataset size and
automatically trades off high information gain about the global optimum against
computational cost. Experiments optimizing support vector machines and deep
neural networks show that Fabolas often finds high-quality solutions 10 to 100
times faster than other state-of-the-art Bayesian optimization methods or the
recently proposed bandit strategy Hyperband.


title: BCS theory with the external pair potential

abstract:
  We consider a hypothetical substance, where interaction between (within)
structural elements of condensed matter (molecules, nanoparticles, clusters,
layers, wires etc.) depends on state of Cooper pairs: an additional work must
be made against this interaction to break a pair. Such a system can be
described by BCS Hamiltonian with the external pair potential term. In this
model the potential essentially renormalizes the order parameter: if the
pairing lowers energy of the structure the energy gap is slightly enlarged at
zero temperature and asymptotically tends to zero as temperature rises. Thus
the critical temperature of such a superconductor is equal to infinity
formally. For this case the effective Ginzburg-Landau theory is formulated,
where the coherence length decreases as temperature rises, the GL parameter and
the second critical field are increasing functions of temperature unlike the
standard theory. If the pairing enlarges energy of the structure then
suppression of superconductivity and the first order phase transition occur.


title:
Depth from a Single Image by Harmonizing Overcomplete Local Network
  Predictions

abstract:
  A single color image can contain many cues informative towards different
aspects of local geometric structure. We approach the problem of monocular
depth estimation by using a neural network to produce a mid-level
representation that summarizes these cues. This network is trained to
characterize local scene geometry by predicting, at every image location, depth
derivatives of different orders, orientations and scales. However, instead of a
single estimate for each derivative, the network outputs probability
distributions that allow it to express confidence about some coefficients, and
ambiguity about others. Scene depth is then estimated by harmonizing this
overcomplete set of network predictions, using a globalization procedure that
finds a single consistent depth map that best matches all the local derivative
distributions. We demonstrate the efficacy of this approach through evaluation
on the NYU v2 depth data set.


title: A unified Erd\H{o}s-P\'osa theorem for constrained cycles

abstract:
  A doubly group-labeled graph is an oriented graph with its edges labeled by
elements of the direct sum of two groups $\Gamma_1,\Gamma_2$. A cycle in a
doubly group-labeled graph is $(\Gamma_1,\Gamma_2)$-non-zero if it is non-zero
in both coordinates. Our main result is a generalization of the Flat Wall
Theorem of Robertson and Seymour to doubly group-labeled graphs. As an
application, we determine all canonical obstructions to the Erd\H{o}s-P\'osa
property for $(\Gamma_1,\Gamma_2)$-non-zero cycles in doubly group-labeled
graphs. The obstructions imply that the half-integral Erd\H{o}s-P\'osa property
always holds for $(\Gamma_1,\Gamma_2)$-non-zero cycles.
  Moreover, our approach gives a unified framework for proving packing results
for constrained cycles in graphs. For example, as immediate corollaries we
recover the Erd\H{o}s-P\'osa property for cycles and $S$-cycles and the
half-integral Erd\H{o}s-P\'osa property for odd cycles and odd $S$-cycles.
Furthermore, we recover Reed's Escher-wall Theorem.
  We also prove many new packing results as immediate corollaries. For example,
we show that the half-integral Erd\H{o}s-P\'osa property holds for cycles not
homologous to zero, odd cycles not homologous to zero, and $S$-cycles not
homologous to zero. Moreover, the (full) Erd\H{o}s-P\'osa property holds for
$S_1$-$S_2$-cycles and cycles not homologous to zero on an orientable surface.
Finally, we also describe the canonical obstructions to the Erd\H{o}s-P\'osa
property for cycles not homologous to zero and for odd $S$-cycles.


title: D-SPACE4Cloud: A Design Tool for Big Data Applications

abstract:
  The last years have seen a steep rise in data generation worldwide, with the
development and widespread adoption of several software projects targeting the
Big Data paradigm. Many companies currently engage in Big Data analytics as
part of their core business activities, nonetheless there are no tools and
techniques to support the design of the underlying hardware configuration
backing such systems. In particular, the focus in this report is set on Cloud
deployed clusters, which represent a cost-effective alternative to on premises
installations. We propose a novel tool implementing a battery of optimization
and prediction techniques integrated so as to efficiently assess several
alternative resource configurations, in order to determine the minimum cost
cluster deployment satisfying QoS constraints. Further, the experimental
campaign conducted on real systems shows the validity and relevance of the
proposed method.


title: Low-Sensitivity Functions from Unambiguous Certificates

abstract:
  We provide new query complexity separations against sensitivity for total
Boolean functions: a power $3$ separation between deterministic (and even
randomized or quantum) query complexity and sensitivity, and a power $2.22$
separation between certificate complexity and sensitivity. We get these
separations by using a new connection between sensitivity and a seemingly
unrelated measure called one-sided unambiguous certificate complexity
($UC_{min}$). We also show that $UC_{min}$ is lower-bounded by fractional block
sensitivity, which means we cannot use these techniques to get a
super-quadratic separation between $bs(f)$ and $s(f)$. We also provide a
quadratic separation between the tree-sensitivity and decision tree complexity
of Boolean functions, disproving a conjecture of Gopalan, Servedio, Tal, and
Wigderson (CCC 2016).
  Along the way, we give a power $1.22$ separation between certificate
complexity and one-sided unambiguous certificate complexity, improving the
power $1.128$ separation due to G\"o\"os (FOCS 2015). As a consequence, we
obtain an improved $\Omega(\log^{1.22} n)$ lower-bound on the
co-nondeterministic communication complexity of the Clique vs. Independent Set
problem.


title:
The entanglement spectrum and R\'enyi entropies of non-relativistic
  conformal fermions

abstract:
  We characterize non-perturbatively the R\'enyi entropies of degree n=2,3,4,
and 5 of three-dimensional, strongly coupled many-fermion systems in the
scale-invariant regime of short interaction range and large scattering length,
i.e. in the unitary limit. We carry out our calculations using lattice methods
devised recently by us. Our results show the effect of strong pairing
correlations on the entanglement entropy, which modify the sub-leading behavior
for large subsystem sizes (as characterized by the dimensionless parameter x=kF
L_A, where kF is the Fermi momentum and L_A the linear subsystem size), but
leave the leading order unchanged relative to the non-interacting case.
Moreover, we find that the onset of the sub-leading asymptotic regime is at
surprisingly small x=2-4. We provide further insight into the entanglement
properties of this system by analyzing the spectrum of the entanglement
Hamiltonian of the two-body problem from weak to strong coupling. The low-lying
entanglement spectrum displays clear features as the strength of the coupling
is varied, such as eigenvalue crossing, a sharp change in the Schmidt gap, and
scale invariance at unitarity. Beyond the low-lying component, the spectrum
appears as a quasi-continuum distribution, for which we present a statistical
characterization; we find, in particular, that the mean shifts to infinity as
the coupling is turned off, which indicates that that part of the spectrum
represents non-perturbative contributions to the entanglement Hamiltonian. In
contrast, the low-lying entanglement spectrum evolves to finite values in the
noninteracting limit. The scale invariance of the unitary regime guarantees
that our results are universal features intrinsic to 3D quantum mechanics and
represent a well-defined prediction for ultracold atom experiments, which were
recently shown to have direct access to the entanglement entropy.

categories: cond-mat.quant-gas hep-lat hep-th nucl-th quant-ph


title:
On Lp -theory for parabolic and elliptic integro-differential equations
  with scalable operators in the whole space

abstract:
  Elliptic and parabolic integro-differential model problems are considered in
the whole space. By verifying H\"ormander condition, the existence and
uniqueness is proved in L_{p}-spaces of functions whose regularity is defined
by a scalable, possibly nonsymmetric, Levy measure. Some rough probability
density function estimates of the associated Levy process are used as well.


title: Direct evidence for charge stripes in a layered cobalt oxide

abstract:
  Recent experiments indicate that static stripe-like charge order is generic
to the hole-doped copper oxide superconductors and competes with
superconductivity. Here we show that a similar type of charge order is present
in La$_{5/3}$Sr$_{1/3}$CoO$_4$, an insulating analogue of the copper oxide
superconductors containing cobalt in place of copper. The stripe phase we have
detected is accompanied by short-range, quasi-one-dimensional,
antiferromagnetic order, and provides a natural explanation for the distinctive
hourglass shape of the magnetic spectrum previously observed in neutron
scattering measurements of La$_{5/3}$Sr$_{1/3}$CoO$_4$ and many hole-doped
copper oxide superconductors. The results establish a solid empirical basis for
theories of the hourglass spectrum built on short-range, quasi-static, stripe
correlations.


title: Non-local fractional derivatives. Discrete and continuous

abstract:
  We prove maximum and comparison principles for fractional discrete
derivatives in the integers. Regularity results when the space is a mesh of
length $h$, and approximation theorems to the continuous fractional derivatives
are shown. When the functions are good enough, these approximation procedures
give a measure of the order of approximation. These results also allows us to
prove the coincidence, for good enough functions, of the Marchaud and
Gr\"unwald-Letnikov derivatives in every point and the speed of convergence to
the Gr\"unwald-Letnikov derivative. The fractional discrete derivative will be
also described as a Neumann-Dirichlet operator defined by a semi-discrete
extension problem. Some operators related to the Harmonic Analysis associated
to the discrete derivative will be also considered, in particular their
behavior in the Lebesgue spaces $\ell^p(\mathbb{Z}).$


title: Thin-shell wormholes with a double layer in quadratic F(R) gravity

abstract:
  We present a family of spherically symmetric Lorentzian wormholes in
quadratic F(R) gravity, with a thin shell of matter corresponding to the
throat. At each side of the shell the geometry has a different constant value
of the curvature scalar R. The junction conditions determine the equation of
state between the pressure and energy density at the throat, where a double
layer is also located. We analyze the stability of the configurations under
perturbations preserving the spherical symmetry. In particular, we study
thin-shell wormholes with mass and charge. We find that there exist values of
the parameters for which stable static solutions are possible.


title: How wet should be the reaction coordinate for ligand unbinding?

abstract:
  We use a recently proposed method called Spectral Gap Optimization of Order
Parameters (SGOOP) (Tiwary and Berne, Proc. Natl. Acad. Sci 2016, 113, 2839
(2016)), to determine an optimal 1-dimensional reaction coordinate (RC) for the
unbinding of a bucky-ball from a pocket in explicit water. This RC is estimated
as a linear combination of the multiple available order parameters that
collectively can be used to distinguish the various stable states relevant for
unbinding. We pay special attention to determining and quantifying the degree
to which water molecules should be included in the RC. Using SGOOP with
under-sampled biased simulations, we predict that water plays a distinct role
in the reaction coordinate for unbinding in the case when the ligand is
sterically constrained to move along an axis of symmetry. This prediction is
validated through extensive calculations of the unbinding times through
metadynamics, and by comparison through detailed balance with unbiased
molecular dynamics estimate of the binding time. However when the steric
constraint is removed, we find that the role of water in the reaction
coordinate diminishes. Here instead SGOOP identifies a good one-dimensional RC
involving various motional degrees of freedom.


title: Stable and accurate interface capturing advection schemes

abstract:
  In this paper, stable and "low-diffusive" multidimensional interface
capturing (IC) schemes using slope limiters are discussed. It is known that
direction-by-direction slope-limited MUSCL schemes create geometrical artifacts
and thus return a poor accuracy. We here focus on this particular issue and
show that the reconstruction of gradient directions are an important factor of
accuracy. The use of a multidimensional limiting process (MLP) added with an
adequate time integration scheme leads to an artifact-free and instability-free
interface capturing (IC) approach. Numerical experiments like the reference
Kothe-Rider forward-backward advection case show the accuracy of the approach.
We also show that the approach can be extended to the more complex compressible
multimaterial hydrodynamics case, with potentially an arbitrary number of
fluids. We also believe that this approach is appropriate for
multicore/manycore architecture because of its SIMD feature, which may be
another asset compared to interface reconstruction approaches.


title: Zeros of quadratic Dirichlet $L$-functions in the hyperelliptic ensemble

abstract:
  We study the $1$-level density and the pair correlation of zeros of quadratic
Dirichlet $L$-functions in function fields, as we average over the ensemble
$\mathcal{H}_{2g+1}$ of monic, square-free polynomials with coefficients in
$\mathbb{F}_q[x]$. In the case of the $1$-level density, when the Fourier
transform of the test function is supported in the restricted interval
$(\frac{1}{3},1)$, we compute a secondary term of size $q^{-\frac{4g}{3}}/g$,
which is not predicted by the Ratios Conjecture. Moreover, when the support is
even more restricted, we obtain several lower order terms. For example, if the
Fourier transform is supported in $(\frac{1}{3}, \frac{1}{2})$, we identify
another lower order term of size $q^{-\frac{8g}{5}}/g$. We also compute the
pair correlation, and as for the $1$-level density, we detect lower order terms
under certain restrictions; for example, we see a term of size $q^{-g}/g^2$
when the Fourier transform is supported in $(\frac{1}{4},\frac{1}{2})$. The
$1$-level density and the pair correlation allow us to obtain non-vanishing
results for $L(\frac12,\chi_D)$, as well as lower bounds for the proportion of
simple zeros of this family of $L$-functions.


title: Maps of Degree 1 and Lusternik--Schnirelmann Category

abstract:
  Given a map $f: M \to N$ of degree 1 of closed manifolds. Is it true that the
Lusternik--Schnirelmann category of the range of the map is not more that the
category of the domain? We discuss this and some related questions.


title:
A note on the expected minimum error probability in equientropic
  channels

abstract:
  While the channel capacity reflects a theoretical upper bound on the
achievable information transmission rate in the limit of infinitely many bits,
it does not characterise the information transfer of a given encoding routine
with finitely many bits. In this note, we characterise the quality of a code
(i. e. a given encoding routine) by an upper bound on the expected minimum
error probability that can be achieved when using this code. We show that for
equientropic channels this upper bound is minimal for codes with maximal
marginal entropy. As an instructive example we show for the additive white
Gaussian noise (AWGN) channel that random coding---also a capacity achieving
code---indeed maximises the marginal entropy in the limit of infinite messages.


title:
Gibbs measures of nonlinear Schr\"odinger equations as limits of
  many-body quantum states in dimensions $d \leq 3$

abstract:
  We prove that Gibbs measures of nonlinear Schr\"odinger equations arise as
high-temperature limits of thermal states in many-body quantum mechanics. Our
results hold for defocusing interactions in dimensions $d =1,2,3$. The
many-body quantum thermal states that we consider are the grand canonical
ensemble for $d = 1$ and an appropriate modification of the grand canonical
ensemble for $d =2,3$. In dimensions $d =2,3$, the Gibbs measures are supported
on singular distributions, and a renormalization of the chemical potential is
necessary. On the many-body quantum side, the need for renormalization is
manifested by a rapid growth of the number of particles. We relate the original
many-body quantum problem to a renormalized version obtained by solving a
counterterm problem. Our proof is based on ideas from field theory, using a
perturbative expansion in the interaction, organized by using a diagrammatic
representation, and on Borel resummation of the resulting series.


title:
Bayes' theorem and early solar short-lived radionuclides: the case for
  an unexceptional origin for the solar system

abstract:
  The presence of excesses of short-lived radionuclides in the early solar
system evidenced in meteorites has been taken as testament to close encounters
with exotic nucleosynthetic sources, including supernovae or AGB stars. An
analysis of the likelihoods associated with different sources of these extinct
nuclides in the early solar system indicates that rather than being exotic,
their abundances were typical of star-forming regions like those observed today
in the Galaxy. The radiochemistry of the early solar system is therefore
unexceptional, being the consequence of extensive averaging of molecular cloud
solids.


title: Double centralizers in Artin-Tits groups

abstract:
  We prove an analogue of the Centralizer Theorem in the context of Artin-Tits
groups.


title:
Free Deterministic Equivalents for the Analysis of MIMO Multiple Access
  Channel

abstract:
  In this paper, a free deterministic equivalent is proposed for the capacity
analysis of the multi-input multi-output (MIMO) multiple access channel (MAC)
with a more general channel model compared to previous works. Specifically, a
MIMO MAC with one base station (BS) equipped with several distributed antenna
sets is considered. Each link between a user and a BS antenna set forms a
jointly correlated Rician fading channel. The analysis is based on
operator-valued free probability theory, which broadens the range of
applicability of free probability techniques tremendously. By replacing
independent Gaussian random matrices with operator-valued random variables
satisfying certain operator-valued freeness relations, the free deterministic
equivalent of the considered channel Gram matrix is obtained. The Shannon
transform of the free deterministic equivalent is derived, which provides an
approximate expression for the ergodic input-output mutual information of the
channel. The sum-rate capacity achieving input covariance matrices are also
derived based on the approximate ergodic input-output mutual information. The
free deterministic equivalent results are easy to compute, and simulation
results show that these approximations are numerically accurate and
computationally efficient.


title: The Jacobi Stochastic Volatility Model

abstract:
  We introduce a novel stochastic volatility model where the squared volatility
of the asset return follows a Jacobi process. It contains the Heston model as a
limit case. We show that the joint density of any finite sequence of log
returns admits a Gram-Charlier A expansion with closed-form coefficients. We
derive closed-form series representations for option prices whose discounted
payoffs are functions of the asset price trajectory at finitely many time
points. This includes European call, put, and digital options, forward start
options, and can be applied to discretely monitored Asian options. In a
numerical analysis we show that option prices can be accurately and efficiently
approximated by truncating their series representations.


title: A Highly Magnetized Twin-Jet Base Pinpoints a Supermassive Black Hole

abstract:
  Supermassive black holes (SMBH) are essential for the production of jets in
radio-loud active galactic nuclei (AGN). Theoretical models based on Blandford
& Znajek extract the rotational energy from a Kerr black hole, which could be
the case for NGC1052, to launch these jets. This requires magnetic fields of
the order of $10^3\,$G to $10^4\,$G. We imaged the vicinity of the SMBH of the
AGN NGC1052 with the Global Millimetre VLBI Array and found a bright and
compact central feature, smaller than 1.9 light days (100 Schwarzschild radii)
in radius. Interpreting this as a blend of the unresolved jet bases, we derive
the magnetic field at 1 Schwarzschild radius to lie between 200 G and ~80000 G
consistent with Blandford & Znajek models.


title: Unitaries in Ultraproduct of Matrices

abstract:
  We study various conditions under which a unitary in an ultraproduct of
matrices is conjugated to an ultraproduct of permutations.


title: Fluctuations of TASEP on a ring in relaxation time scale

abstract:
  We consider the totally asymmetric simple exclusion process on a ring with
flat and step initial conditions. We assume that the size of the ring and the
number of particles tend to infinity proportionally and evaluate the
fluctuations of tagged particles and currents. The crossover from the KPZ
dynamics to the equilibrium dynamics occurs when the time is proportional to
the 3/2 power of the ring size. We compute the limiting distributions in this
relaxation time scale. The analysis is based on an explicit formula of the
finite-time one-point distribution obtained from the coordinate Bethe ansatz
method.


title: Decomposing Real Square Matrices via Unitary Diagonalization

abstract:
  Diagonalization, or eigenvalue decomposition, is very useful in many areas of
applied mathematics, including signal processing and quantum physics. Matrix
decomposition is also a useful tool for approximating matrices as the product
of a matrix and its transpose, which relates to unitary diagonalization. As
stated by the spectral theorem, only normal matrices are unitarily
diagonalizable. However we show that all real square matrices are the real part
of some unitarily diagonalizable matrix.


title:
Generic Instance Search and Re-identification from One Example via
  Attributes and Categories

abstract:
  This paper aims for generic instance search from one example where the
instance can be an arbitrary object like shoes, not just near-planar and
one-sided instances like buildings and logos. First, we evaluate
state-of-the-art instance search methods on this problem. We observe that what
works for buildings loses its generality on shoes. Second, we propose to use
automatically learned category-specific attributes to address the large
appearance variations present in generic instance search. Searching among
instances from the same category as the query, the category-specific attributes
outperform existing approaches by a large margin on shoes and cars and perform
on par with the state-of-the-art on buildings. Third, we treat person
re-identification as a special case of generic instance search. On the popular
VIPeR dataset, we reach state-of-the-art performance with the same method.
Fourth, we extend our method to search objects without restriction to the
specifically known category. We show that the combination of category-level
information and the category-specific attributes is superior to the alternative
method combining category-level information with low-level features such as
Fisher vector.


title:
Practitioners' Perspectives on Change Impact Analysis for
  Safety-Critical Software - A Preliminary Analysis

abstract:
  Safety standards prescribe change impact analysis (CIA) during evolution of
safety-critical software systems. Although CIA is a fundamental activity, there
is a lack of empirical studies about how it is performed in practice. We
present a case study on CIA in the context of an evolving automation system,
based on 14 interviews in Sweden and India. Our analysis suggests that
engineers on average spend 50-100 hours on CIA per year, but the effort varies
considerably with the phases of projects. Also, the respondents presented
different connotations to CIA and perceived the importance of CIA differently.
We report the most pressing CIA challenges, and several ideas on how to support
future CIA. However, we show that measuring the effect of such improvement
solutions is non-trivial, as CIA is intertwined with other development
activities. While this paper only reports preliminary results, our work
contributes empirical insights into practical CIA.


title: Van der Waals pressure and its effect on trapped interlayer molecules

abstract:
  Van der Waals assembly of two-dimensional (2D) crystals continue attract
intense interest due to the prospect of designing novel materials with
on-demand properties. One of the unique features of this technology is the
possibility of trapping molecules or compounds between 2D crystals. The trapped
molecules are predicted to experience pressures as high as 1 GPa. Here we
report measurements of this interfacial pressure by capturing
pressure-sensitive molecules and studying their structural and conformational
changes. Pressures of 1.2 +/- 0.3 GPa are found using Raman spectrometry for
molecular layers of one nanometer in thickness. We further show that this
pressure can induce chemical reactions and several trapped salts or compounds
are found to react with water at room temperature, leading to 2D crystals of
the corresponding oxides. This pressure and its effect should be taken into
account in studies of van der Waals heterostructures and can also be exploited
to modify materials confined at the atomic interfaces.


title: Revenue Maximization in Service Systems with Heterogeneous Customers

abstract:
  In this paper, we consider revenue maximization problem for a two server
system in the presence of heterogeneous customers. We assume that the customers
differ in their cost for unit delay and this is modeled as a continuous random
variable with a distribution $F.$ We also assume that each server charges an
admission price to each customer that decide to join its queue. We first
consider the monopoly problem where both the servers belong to a single
operator. The heterogeneity of the customer makes the analysis of the problem
difficult. The difficulty lies in the inability to characterize the equilibrium
queue arrival rates as a function of the admission prices. We provide an
equivalent formulation with the queue arrival rates as the optimization
variable simplifying the analysis for revenue rate maximization for the
monopoly. We then consider the duopoly problem where each server competes with
the other server to maximize its revenue rate. For the duopoly problem, the
interest is to obtain the set of admission prices satisfying the Nash
equilibrium conditions. While the problem is in general difficult to analyze,
we consider the special case when the two servers are identical. For such a
duopoly system, we obtain the necessary condition for existence of symmetric
Nash equilibrium of the admission prices. The knowledge of the distribution $F$
characterizing the heterogeneity of the customers is necessary to solve the
monopoly and the duopoly problem. However, for most practical scenarios, the
functional form of $F$ may not be known to the system operator and in such
cases, the revenue maximizing prices cannot be determined. In the last part of
the paper, we provide a simple method to estimate the distribution $F$ by
suitably varying the admission prices. We illustrate the method with some
numerical examples.


title: Stochastic Phase Segregation on Surfaces

abstract:
  Phase separation and coarsening is a phenomenon commonly seen in binary
physical and chemical systems that occur in nature. Often times, thermal
fluctuations, modeled as stochastic noise, are present in the system and the
phase segregation process occurs on a surface. In this work, the segregation
process is modeled via the Cahn-Hilliard-Cook model, which is a fourth-order
parabolic stochastic system. Coarsening is analyzed on two sample surfaces: a
unit sphere and a dumbbell using a variety and a statistical analysis of the
growth rate is performed. The influence of noise level and mobility is also
investigated. It is also shown that a log-normal distribution fits the results
well.


title:
Implications of the pulsar wind nebula scenario for a TeV gamma-ray
  source VER J2016+371

abstract:
  We present multiwavelength studies of a TeV gamma-ray source VER J2016+371
suggested to be associated with a supernova remnant CTB 87 (G74.9+1.2) and
based on X-ray and radio morphologies, CTB 87 is identified as an evolved
pulsar wind nebula. A source in the vicinity of VER J2016+371 is also detected
at GeV energies by Fermi Gamma Ray Space Telescope suggesting a likely
counterpart at GeV energies. We find that a broken power-law (BPL) distribution
of electrons can explain the observed data at radio, X-ray and TeV energies,
however, is not sufficient to explain the data at MeV--GeV energies. A
Maxwellian distribution of electrons along with the BPL distribution of
electrons in low magnetic fields can explain the observed multiwavelength data
spanned from radio to TeV energies suggesting this as the most likely scenario
for this source. We also find that although the hadronic model can explain the
observed GeV--TeV data for the ambient matter density of $\sim 20~ \rm
cm^{-3}$, no observational support for such high ambient density makes this
hadronic scenario unlikely for this source.


title: Deep Learning without Poor Local Minima

abstract:
  In this paper, we prove a conjecture published in 1989 and also partially
address an open problem announced at the Conference on Learning Theory (COLT)
2015. With no unrealistic assumption, we first prove the following statements
for the squared loss function of deep linear neural networks with any depth and
any widths: 1) the function is non-convex and non-concave, 2) every local
minimum is a global minimum, 3) every critical point that is not a global
minimum is a saddle point, and 4) there exist "bad" saddle points (where the
Hessian has no negative eigenvalue) for the deeper networks (with more than
three layers), whereas there is no bad saddle point for the shallow networks
(with three layers). Moreover, for deep nonlinear neural networks, we prove the
same four statements via a reduction to a deep linear model under the
independence assumption adopted from recent work. As a result, we present an
instance, for which we can answer the following question: how difficult is it
to directly train a deep model in theory? It is more difficult than the
classical machine learning models (because of the non-convexity), but not too
difficult (because of the nonexistence of poor local minima). Furthermore, the
mathematically proven existence of bad saddle points for deeper models would
suggest a possible open problem. We note that even though we have advanced the
theoretical foundations of deep learning and non-convex optimization, there is
still a gap between theory and practice.


title:
The descent of twisted perfect complexes on a space with soft structure
  sheaf

abstract:
  In this paper we study the dg-category of twisted perfect complexes on a
ringed space with soft structure sheaf. We prove that this dg-category is
quasi-equivalent to the dg-category of complexes of vector bundles on that
space. This result could be considered as a dg-enhancement of the classic
result on soft sheaves in SGA6.


title: Harnessing Smoothness to Accelerate Distributed Optimization

abstract:
  There has been a growing effort in studying the distributed optimization
problem over a network. The objective is to optimize a global function formed
by a sum of local functions, using only local computation and communication.
Literature has developed consensus-based distributed (sub)gradient descent
(DGD) methods and has shown that they have the same convergence rate
$O(\frac{\log t}{\sqrt{t}})$ as the centralized (sub)gradient methods (CGD)
when the function is convex but possibly nonsmooth. However, when the function
is convex and smooth, under the framework of DGD, it is unclear how to harness
the smoothness to obtain a faster convergence rate comparable to CGD's
convergence rate. In this paper, we propose a distributed algorithm that,
despite using the same amount of communication per iteration as DGD, can
effectively harnesses the function smoothness and converge to the optimum with
a rate of $O(\frac{1}{t})$. If the objective function is further strongly
convex, our algorithm has a linear convergence rate. Both rates match the
convergence rate of CGD. The key step in our algorithm is a novel gradient
estimation scheme that uses history information to achieve fast and accurate
estimation of the average gradient. To motivate the necessity of history
information, we also show that it is impossible for a class of distributed
algorithms like DGD to achieve a linear convergence rate without using history
information even if the objective function is strongly convex and smooth.


title:
Global Existence for a Nonlinear System with Fractional Laplacian in
  Banach Space

abstract:
  We consider the cauchy problem for the fractional power dissipative equation
$u_t+(-\Delta )^{\beta/2} u=F(u)$, where $\beta>0$ and $F(u)=B(u, ...,u)$ and
$B$ is a multilinear form on a Banach space $E$. We show a global existence
result assuming some properties of scaling degree of the multilinear form and
the norm of the space $E$. We extend the ideas used for the treating of the
equation to determine the global existence for the system
$u_t+(-\Delta)^{\beta/2}= F(v)$, $v_t+(-\Delta )^{\beta/2}v=G(u)$ where
$F(u)=B_1(u,...,u), G(v)=B_2(v,...,v)$


title:
Global Effective-Field-Theory analysis of New-Physics effects in
  (semi)leptonic kaon decays

abstract:
  We analyze the decays $K\to\pi\ell\nu$ and $P\to\ell\nu$ ($P=K,\pi$,
$\ell=e,\,\mu$) using a low-energy Effective-Field-Theory approach to
parametrize New Physics and study the complementarity with baryon $\beta$
decays. We then provide a road map for a global analysis of the experimental
data, with all the Wilson coefficients simultaneously, and perform a fit
leading to numerical bounds for them and for $V_{us}$. A prominent result of
our analysis is a reinterpretation of the well-known $V_{ud}-V_{us}$ diagram as
a strong constraint on new physics. Finally, we reinterpret our bounds in terms
of the $SU(2)_L\times~U(1)_Y$-invariant operators, provide bounds to the
corresponding Wilson coefficients at the TeV scale and compare our results with
collider searches at the LHC.


title: Differential calculus over N-graded commutative rings

abstract:
  The Chevalley-Eilenberg differential calculus and differential operators over
N-graded commutative rings are constructed. This is a straightforward
generalization of the differential calculus over commutative rings, and it is
the most general case of the differential calculus over rings that is not the
non-commutative geometry. Since any N-graded ring possesses the associated
Z_2-graded structure, this also is the case of the graded differential calculus
over Grassmann algebras and the supergeometry and field theory on graded
manifolds.


title:
A Formal Evaluation of PSNR as Quality Measurement Parameter for Image
  Segmentation Algorithms

abstract:
  Quality evaluation of image segmentation algorithms are still subject of
debate and research. Currently, there is no generic metric that could be
applied to any algorithm reliably. This article contains an evaluation for the
PSRN (Peak Signal-To-Noise Ratio) as a metric which has been used to evaluate
threshold level selection as well as the number of thresholds in the case of
multi-level segmentation. The results obtained in this study suggest that the
PSNR is not an adequate quality measurement for segmentation algorithms.


title: Quaternionic Bott-Chern cohomology and existence of HKT metrics

abstract:
  We study quaternionic Bott-Chern cohomology on compact hypercomplex manifolds
and adapt some results from complex geometry to the quaternionic setting. For
instance, we prove a criterion for the existence of HKT metrics on compact
hypercomplex manifolds of real dimension 8 analogous to the one given by
Teleman [35] and Angella-Dloussky-Tomassini [3] for compact complex surfaces.


title:
Two-letter words and a fundamental homomorphism ruling geometric
  contextuality

abstract:
  It has recently been recognized by the author that the quantum contextuality
paradigm may be formulated in terms of the properties of some subgroups of the
two-letter free group $G$ and their corresponding point-line incidence geometry
$\mathcal{G}$. I introduce a fundamental homomorphism $f$ mapping the
(infinitely many) words of G to the permutations ruling the symmetries of
$\mathcal{G}$. The substructure of $f$ is revealing the essence of geometric
contextuality in a straightforward way.


title: Superconducting phase diagram of the paramagnetic one-band Hubbard model

abstract:
  We study spin-fluctuation-mediated superconductivity in the one-band Hubbard
model. Higher order effective interactions in $U$ give rise to a
superconducting instability which is very sensitive to changes in the Fermi
surface topology arising as a function of doping and changes in the band
structure. We show the superconducting phase diagram as a function of doping
and next-nearest neighbor hopping in the limit of very small Coulomb
interaction strength and discuss peculiarities arising at the phase boundaries
separating different superconducting domains.


title: Assembly of open clusters of colloidal dumbbells via droplet evaporation

abstract:
  We investigate the behavior of a mixture of asymmetric colloidal dumbbells
and emulsion droplets by means of kinetic Monte Carlo simulations. The
evaporation of the droplets and the competition between droplet-colloid
attraction and colloid-colloid interactions leads to the formation of clusters
built up of colloid aggregates with both closed and open structures. We find
that stable packings and hence complex colloidal structures can be obtained by
changing the relative size of the colloidal spheres and/or their interfacial
tension with the droplets.


title:
Estimation of CD4+ T Cell Count Parameters in HIV/AIDS Patients Based on
  Real-time Nonlinear Receding Horizon Control

abstract:
  An increasing number of control techniques are introduced to HIV infection
problem to explore the options of helping clinical testing, optimizing drug
treatments and to study the drug resistance situations. In such cases,
complete/accurate knowledge of the HIV model and/or parameters is critical not
only to monitor the dynamics of the system, but also to adjust the therapy
accordingly. In those studies, existence of any type of unknown parameters
imposes severe set-backs and becomes problematic for the treatment of the
patients. In this work, we develop a real-time adaptive nonlinear receding
horizon control approach to aid such scenarios and to estimate unknown
constant/time-varying parameters of nonlinear HIV system models. For this
purpose, the problem of estimation is updated by a series of finite-time
optimization problem which can be solved by backwards sweep Riccati method in
real time without employing any iteration techniques. The simulation results
demonstrates the fact that proposed algorithm is able to estimate unknown
constant/time-varying parameters of HIV/AIDS model effectively and provide a
unique, adaptive solution methodology to an important open problem.


title:
Efficient fluorescence quenching in electrochemically exfoliated
  graphene decorated with gold nanoparticles

abstract:
  High surface area graphene sheets were obtained by electrochemical
exfoliation of graphite in an acid media under constant potential conditions.
Filtration and centrifugation processes played an important role in order to
obtain stable dispersions in water. Scanning electron microscopy (SEM) and
transmission electron microscopy (TEM) imaging revealed highly exfoliated
crystalline samples of ~5(\mum). Raman, FT-IR and XPS spectroscopy further
confirmed the high quality of the exfoliated material. The electrochemically
exfoliated graphene (EEG) was decorated with gold nanoparticles (AuNP) using
sodium cholate (SC) as a buffer layer. This approach allowed for a non-covalent
functionalization without altering the desirable electronic properties of the
EEG. The AuNP-EEG samples were characterized with various techniques including
absorbance and fluorescence spectroscopy. These samples displayed a
fluorescence signal using an excitation wavelength of 290nm. The calculated
quantum yield (?) for these samples was 40.04%, a high efficiency compared to
previous studies using solution processable graphene.


title: A Borel maximal eventually different family

abstract: We construct a Borel maximal eventually different family.


title:
Stochastic models of gene transcription with upstream drives: exact
  solution and sample path characterization

abstract:
  Gene transcription is a highly stochastic and dynamic process. As a result,
the mRNA copy number of a given gene is heterogeneous both between cells and
across time. We present a framework to model gene transcription in populations
of cells with time-varying (stochastic or deterministic) transcription and
degradation rates. Such rates can be understood as upstream cellular drives
representing the effect of different aspects of the cellular environment. We
show that the full solution of the master equation contains two components: a
model-specific, upstream effective drive, which encapsulates the effect of
cellular drives (e.g., entrainment, periodicity or promoter randomness), and a
downstream transcriptional Poissonian part, which is common to all models. Our
analytical framework treats cell-to-cell and dynamic variability consistently,
unifying several approaches in the literature. We apply the obtained solution
to characterise different models of experimental relevance, and to explain the
influence on gene transcription of synchrony, stationarity, ergodicity, as well
as the effect of time-scales and other dynamic characteristics of drives. We
also show how the solution can be applied to the analysis of noise sources in
single-cell data, and to reduce the computational cost of stochastic
simulations.


title: Dynamical model for spindown of solar-type stars

abstract:
  Since their formation, stars slow down their rotation rates by the removal of
angular momentum from their surfaces, e.g. via stellar winds. Despite the
complexity of the processes involved, a traditional model, where the removal of
angular momentum loss by magnetic fields is prescribed, has provided a useful
framework to understand observational relations between stellar rotation and
age and magnetic field strength. Here, a spindown model is proposed where loss
of angular momentum by magnetic fields is evolved dynamically, instead of being
kinematically prescribed. To this end, we evolve the stellar rotation and
magnetic field simultaneously over stellar evolution time by extending our
previous work on a dynamo model which incorporates the nonlinear feedback
mechanisms on rotation and magnetic fields. Our extended model reproduces key
observations and explains the presence of the two branches of (fast and slow
rotating) stars which have different relations between rotation rate $\Omega$
vs. time (age), magnetic field strength $|B|$ vs. rotation rate, and frequency
of magnetic field $\omega_{cyc}$ vs. rotation rate. For fast rotating stars we
find: (i) an exponential spindown $\Omega \propto e^{-1.35t}$, with $t$
measured in Gyrs, (ii) $|B|$ saturates for higher rotation rate, (iii)
$\omega_{cyc} \propto \Omega^{0.85}$. For slow rotating stars we obtain: (i) a
power law spindown $\Omega \propto t^{-0.52}$, (ii) $|B|$ scales almost
linearly with rotation rate, (iii) $\omega_{cyc} \propto \Omega^{1.16}$. The
results obtained are in good agreement with observations. The Vaughan-Preston
gap is consistently explained in our model by the shortest spindown timescale
in this transition from fast to slow rotators. Our results highlight the
importance of self-regulation of magnetic fields and rotation by direct and
indirect interactions involving nonlinear feedback in stellar evolution.


title: Small doubling in ordered nilpotent groups of class 2

abstract:
  The aim of this paper is to present a complete description of the structure
of finite subsets with small doubling property in ordered nilpotent groups of
class 2.


title:
Learning and Policy Search in Stochastic Dynamical Systems with Bayesian
  Neural Networks

abstract:
  We present an algorithm for model-based reinforcement learning that combines
Bayesian neural networks (BNNs) with random roll-outs and stochastic
optimization for policy learning. The BNNs are trained by minimizing
$\alpha$-divergences, allowing us to capture complicated statistical patterns
in the transition dynamics, e.g. multi-modality and heteroskedasticity, which
are usually missed by other common modeling approaches. We illustrate the
performance of our method by solving a challenging benchmark where model-based
approaches usually fail and by obtaining promising results in a real-world
scenario for controlling a gas turbine.


title: Noether theorems and higher derivatives

abstract:
  A simple proof of Noether's first theorem involves the promotion of a
constant symmetry parameter $\epsilon$ to an arbitrary function of time, the
Noether charge $Q$ is then the coefficient of $\dot\epsilon$ in the variation
of the action. Here we examine the validity of this proof for Lagrangian
mechanics with arbitrarily-high time derivatives, in which context
"higher-level" analogs of Noether's theorem can be similarly proved, and
"Noetherian charges" read off from, e.g. the coefficient of $\ddot \epsilon$ in
the variation of the action. While $Q=0$ implies a restricted gauge invariance,
unrestricted gauge invariance requires zero Noetherian charges too. Some
illustrative examples are considered and the extension to field theory
discussed.


title:
Sub-Gaussian estimators of the mean of a random matrix with heavy-tailed
  entries

abstract:
  Estimation of the covariance matrix has attracted a lot of attention of the
statistical research community over the years, partially due to important
applications such as Principal Component Analysis. However, frequently used
empirical covariance estimator (and its modifications) is very sensitive to
outliers in the data. As P. J. Huber wrote in 1964, "...This raises a question
which could have been asked already by Gauss, but which was, as far as I know,
only raised a few years ago (notably by Tukey): what happens if the true
distribution deviates slightly from the assumed normal one? As is now well
known, the sample mean then may have a catastrophically bad performance..."
Motivated by this question, we develop a new estimator of the (element-wise)
mean of a random matrix, which includes covariance estimation problem as a
special case. Assuming that the entries of a matrix possess only finite second
moment, this new estimator admits sub-Gaussian or sub-exponential concentration
around the unknown mean in the operator norm. We will explain the key ideas
behind our construction, as well as applications to covariance estimation and
matrix completion problems.


title: Limit cycles can reduce the width of the habitable zone

abstract:
  The liquid water habitable zone (HZ) describes the orbital distance at which
a terrestrial planet can maintain above-freezing conditions through regulation
by the carbonate-silicate cycle. Recent calculations have suggested that
planets in the outer regions of the habitable zone cannot maintain stable, warm
climates, but rather should oscillate between long, globally glaciated states
and shorter periods of climatic warmth. Such conditions, similar to 'Snowball
Earth' episodes experienced on Earth, would be inimical to the development of
complex land life, including intelligent life. Here, we build upon previous
studies with an updated an energy balance climate model to calculate this
'limit cycle' region of the habitable zone where such cycling would occur. We
argue that an abiotic Earth would have a greater CO$_2$ partial pressure than
today because plants and other biota help to enhance the storage of CO$_2$ in
soil. When we tune our abiotic model accordingly, we find that limit cycles can
occur but that previous calculations have overestimated their importance. For G
stars like the Sun, limit cycles occur only for planets with CO$_2$ outgassing
rates less than that on modern Earth. For K and M star planets, limit cycles
should not occur; however, M-star planets may be inhospitable to life for other
reasons. Planets orbiting late G-type and early K-type stars retain the
greatest potential for maintaining warm, stable conditions. Our results suggest
that host star type, planetary volcanic activity, and seafloor weathering are
all important factors in determining whether planets will be prone to limit
cycling.


title:
Cooling a Mechanical Resonator with a Nitrogen-Vacancy Center Ensemble
  Using a Room Temperature Excited State Spin-Strain Interaction

abstract:
  We propose a protocol to dissipatively cool a room temperature mechanical
resonator using a nitrogen-vacancy (NV) center ensemble. The spin ensemble is
coupled to the resonator through its orbitally-averaged excited state, which
has a spin-strain interaction that has not been previously characterized. We
experimentally demonstrate that the spin-strain coupling in the excited state
is $13.5\pm0.5$ times stronger than the ground state spin-strain coupling. We
then theoretically show that this interaction combined with a high-density spin
ensemble enables the cooling of a mechanical resonator from room temperature to
a fraction of its thermal phonon occupancy.


title: An irradiated brown-dwarf companion to an accreting white dwarf

abstract:
  Brown dwarfs and giant planets orbiting close to a host star are subjected to
significant irradiation that can modify the properties of their atmospheres. In
order to test the atmospheric models that are used to describe these systems,
it is necessary to obtain accurate observational estimates of their physical
properties (masses, radii, temperatures, albedos). Interacting compact binary
systems provide a natural laboratory for studying strongly irradiated
sub-stellar objects. As the mass-losing secondary in these systems makes a
critical, but poorly understood transition from the stellar to the sub-stellar
regime, it is also strongly irradiated by the compact accretor. In fact, the
internal and external energy fluxes are both expected to be comparable in these
objects, providing access to an unexplored irradiation regime. However, the
atmospheric properties of such donors have so far remained largely unknown.
Here, we report the direct spectroscopic detection and characterisation of an
irradiated sub-stellar donor in an accreting white dwarf binary system. Our
near-infrared observations allow us to determine a model-independent mass
estimate for the donor of $M_2=0.055\pm0.008M_{\odot}$ and an average spectral
type of ${\rm L1}\pm{\rm1}$, supporting both theoretical predictions and
model-dependent observational constraints. Our time-resolved data also allow us
to estimate the average irradiation-induced temperature difference between the
day and night sides on the sub-stellar donor, $\Delta{\rm T}\simeq57$~K, and
the maximum difference between the hottest and coolest parts of its surface, of
$\Delta{\rm T}_{max}\simeq200$~K. The observations are well described by a
simple geometric reprocessing model with a bolometric (Bond) albedo of
$A_B<0.54$ at 2-$\sigma$ confidence level, consistent with high reprocessing
efficiency, but poor lateral heat redistribution in the donor's atmosphere.


title: Towards Multi-Agent Communication-Based Language Learning

abstract:
  We propose an interactive multimodal framework for language learning. Instead
of being passively exposed to large amounts of natural text, our learners
(implemented as feed-forward neural networks) engage in cooperative referential
games starting from a tabula rasa setup, and thus develop their own language
from the need to communicate in order to succeed at the game. Preliminary
experiments provide promising results, but also suggest that it is important to
ensure that agents trained in this way do not develop an adhoc communication
code only effective for the game they are playing


title:
Electric polarizability in the three dimensional problem and the
  solution of an inhomogeneous differential equation

abstract:
  In previous publications, we illustrated the effectiveness of the method of
the inhomogeneous differential equation in calculating the electric
polarizability in the one-dimensional problem. In this paper we extend our
effort to apply the method to the three-dimensional problem.


title:
On a conjecture by Naito-Sagaki: Littelmann paths and
  Littlewood-Richardson Sundaram tableaux

abstract:
  We prove a special case of a conjecture of Naito-Sagaki about a branching
rule for the restriction of irreducible representations of
$\mathfrak{sl}(2n,\mathbb{C})$ to $\mathfrak{sp}(2n,\mathbb{C})$. The
conjecture is in terms of certain Littelmann paths, with the embedding given by
the folding of the type $A_{2n-1}$ Dynkin diagram. We propose and motivate an
approach to the conjecture in general, in terms of Littlewood-Richardson
Sundaram tableaux.


title: The reproducible radio outbursts of SS Cygni

abstract:
  We present the results of our intensive radio observing campaign of the dwarf
nova SS Cyg during its 2010 April outburst. We argue that the observed radio
emission was produced by synchrotron emission from a transient radio jet.
Comparing the radio light curves from previous and subsequent outbursts of this
system (including high-resolution observations from outbursts in 2011 and 2012)
shows that the typical long and short outbursts of this system exhibit
reproducible radio outbursts that do not vary significantly between outbursts,
which is consistent with the similarity of the observed optical, ultraviolet
and X-ray light curves. Contemporaneous optical and X-ray observations show
that the radio emission appears to have been triggered at the same time as the
initial X-ray flare, which occurs as disk material first reaches the boundary
layer. This raises the possibility that the boundary region may be involved in
jet production in accreting white dwarf systems. Our high spatial resolution
monitoring shows that the compact jet remained active throughout the outburst
with no radio quenching.


title:
Physical Study by Surface Characterizations of Sarin Sensor on the Basis
  of Chemically Functionalized Silicon Nanoribbon Field Effect Transistor

abstract:
  Surface characterizations of an organophosphorus (OP) gas detector based on
chemically functionalized silicon nanoribbon field-effect transistor (SiNR-FET)
were performed by Kelvin Probe Force Microscopy (KPFM) and ToF-SIMS, and
correlated with changes in the current-voltage characteristics of the devices.
KPFM measurements on FETs allow (i) to investigate the contact potential
difference (CPD) distribution of the polarized device as function of the gate
voltage and the exposure to OP traces and, (ii) to analyze the CPD hysteresis
associated to the presence of mobile ions on the surface. The CPD measured by
KPFM on the silicon nanoribbon was corrected due to side capacitance effects in
order to determine the real quantitative surface potential. Comparison with
macroscopic Kelvin probe (KP) experiments on larger surfaces was carried out.
These two approaches were quantitatively consistent. An important increase of
the CPD values (between + 399 mV and + 302 mV) was observed after the OP sensor
grafting, corresponding to a decrease of the work function, and a weaker
variation after exposure to OP (between - 14 mV and - 61 mV) was measured.
Molecular imaging by ToF-SIMS revealed OP presence after SiNR-FET exposure. The
OP molecules were essentially localized on the Si-NR confirming effectiveness
and selectivity of the OP sensor. A prototype was exposed to Sarin vapors and
succeeded in the detection of low vapor concentrations (40 ppm).


title: Fractional Hofstadter States in Graphene on Hexagonal Boron Nitride

abstract:
  In fractionally filled Landau levels there is only a small energy difference
between broken translational symmetry electron-crystal states and exotic
correlated quantum fluid states. We show that the spatially periodic substrate
interaction associated with the long period moir\'{e} patterns present in
graphene on nearly aligned hexagonal boron nitride (hBN) tilts this close
competition in favor of the former, explaining surprising recent experimental
findings.


title: Fairness in Learning: Classic and Contextual Bandits

abstract:
  We introduce the study of fairness in multi-armed bandit problems. Our
fairness definition can be interpreted as demanding that given a pool of
applicants (say, for college admission or mortgages), a worse applicant is
never favored over a better one, despite a learning algorithm's uncertainty
over the true payoffs. We prove results of two types.
  First, in the important special case of the classic stochastic bandits
problem (i.e., in which there are no contexts), we provide a provably fair
algorithm based on "chained" confidence intervals, and provide a cumulative
regret bound with a cubic dependence on the number of arms. We further show
that any fair algorithm must have such a dependence. When combined with regret
bounds for standard non-fair algorithms such as UCB, this proves a strong
separation between fair and unfair learning, which extends to the general
contextual case.
  In the general contextual case, we prove a tight connection between fairness
and the KWIK (Knows What It Knows) learning model: a KWIK algorithm for a class
of functions can be transformed into a provably fair contextual bandit
algorithm, and conversely any fair contextual bandit algorithm can be
transformed into a KWIK learning algorithm. This tight connection allows us to
provide a provably fair algorithm for the linear contextual bandit problem with
a polynomial dependence on the dimension, and to show (for a different class of
functions) a worst-case exponential gap in regret between fair and non-fair
learning algorithms


title:
Optimization of p+-ZnTe layer for Back Contacts of ZnTe Thin Film Solar
  Cells

abstract:
  We have studied performance of ZnTe-based heterojunction diodes grown on
p-GaAs substrates by pulsed laser deposition (PLD).


title: Large magnetic anisotropy in Fe_{0.25}TaS_2

abstract:
  We present a first-principles study of the large magneto-crystalline
anisotropy in the intercalated di-chalcogenide material \ce{Fe_{0.25}TaS_2},
investigated with the DFT+U approach. We verify a uniaxial magnetocrystalline
anisotropy energy(MAE) of 15meV/Fe. in the material. We further analyze the
dependence of MAE on the constituent elements and the effect of spin-orbit
coupling. Contrary to conventional intuition, we find a small contribution to
MAE due to strong spin-orbit coupling in the heavier element, Ta. We show that
the electronic configuration, crystal field environment and correlational
effects of the magnetic ion are more important.


title:
Stability of Solid Electrolyte Interphase Components on Lithium Metal
  and Reactive Anode Material Surfaces

abstract:
  Lithium ion batteries (LIB) can feature reactive anodes that operate at low
potentials, such as lithium metal or silicon, passivated by solid electrolyte
interphase (SEI) films. SEI is known to evolve over time as cycling proceeds.
In this modeling work, we focus on the stability of two main SEI components,
lithium carbonate (Li2CO3) and lithium ethylene dicarbonate (LEDC). Both
components are electrochemically stable but thermodynamically unstable near the
equilibrium Li+/Li(s) potential. Interfacial reactions represent one way to
trigger the intrinsic thermodynamic instability. Both Li(2)CO(3) and LEDC are
predicted to exhibit exothermic reactions on lithium metal surfaces, and the
barriers are sufficiently low to permit reactions on battery operation time
scales. LEDC also readily decomposes on high Li-content Li(x)Si surfaces. Our
studies suggest that the innermost SEI layer on lithium metal surfaces should
be a thin layer of Li(2)O -- the only thermodynamically and kinetically stable
component (in the absence of a fluoride source). This work should also be
relevant to inadvertant lithium plating during battery cycling, and SEI
evolution on Li(x)Si surfaces.


title:
Collisionless Isotropization of the Solar-Wind Protons by Compressive
  Fluctuations and Plasma Instabilities

abstract:
  Compressive fluctuations are a minor yet significant component of
astrophysical plasma turbulence. In the solar wind, long-wavelength compressive
slow-mode fluctuations lead to changes in $\beta_{\parallel \mathrm p}\equiv
8\pi n_{\mathrm p}k_{\mathrm B}T_{\parallel \mathrm p}/B^2$ and in $R_{\mathrm
p}\equiv T_{\perp \mathrm p}/T_{\parallel \mathrm p}$, where $T_{\perp \mathrm
p}$ and $T_{\parallel \mathrm p}$ are the perpendicular and parallel
temperatures of the protons, $B$ is the magnetic field strength, and
$n_{\mathrm p}$ is the proton density. If the amplitude of the compressive
fluctuations is large enough, $R_{\mathrm p}$ crosses one or more instability
thresholds for anisotropy-driven microinstabilities. The enhanced field
fluctuations from these microinstabilities scatter the protons so as to reduce
the anisotropy of the pressure tensor. We propose that this scattering drives
the average value of $R_{\mathrm p}$ away from the marginal stability boundary
until the fluctuating value of $R_{\mathrm p}$ stops crossing the boundary. We
model this "fluctuating-anisotropy effect" using linear Vlasov--Maxwell theory
to describe the large-scale compressive fluctuations. We argue that this effect
can explain why, in the nearly collisionless solar wind, the average value of
$R_{\mathrm p}$ is close to unity.


title:
Actively Learning Hemimetrics with Applications to Eliciting User
  Preferences

abstract:
  Motivated by an application of eliciting users' preferences, we investigate
the problem of learning hemimetrics, i.e., pairwise distances among a set of
$n$ items that satisfy triangle inequalities and non-negativity constraints. In
our application, the (asymmetric) distances quantify private costs a user
incurs when substituting one item by another. We aim to learn these distances
(costs) by asking the users whether they are willing to switch from one item to
another for a given incentive offer. Without exploiting structural constraints
of the hemimetric polytope, learning the distances between each pair of items
requires $\Theta(n^2)$ queries. We propose an active learning algorithm that
substantially reduces this sample complexity by exploiting the structural
constraints on the version space of hemimetrics. Our proposed algorithm
achieves provably-optimal sample complexity for various instances of the task.
For example, when the items are embedded into $K$ tight clusters, the sample
complexity of our algorithm reduces to $O(n K)$. Extensive experiments on a
restaurant recommendation data set support the conclusions of our theoretical
analysis.


title: On Optimality Conditions for Auto-Encoder Signal Recovery

abstract:
  Auto-Encoders are unsupervised models that aim to learn patterns from
observed data by minimizing a reconstruction cost. The useful representations
learned are often found to be sparse and distributed. On the other hand,
compressed sensing and sparse coding assume a data generating process, where
the observed data is generated from some true latent signal source, and try to
recover the corresponding signal from measurements. Looking at auto-encoders
from this \textit{signal recovery perspective} enables us to have a more
coherent view of these techniques. In this paper, in particular, we show that
the \textit{true} hidden representation can be approximately recovered if the
weight matrices are highly incoherent with unit $ \ell^{2} $ row length and the
bias vectors takes the value (approximately) equal to the negative of the data
mean. The recovery also becomes more and more accurate as the sparsity in
hidden signals increases. Additionally, we empirically demonstrate that
auto-encoders are capable of recovering the data generating dictionary when
only data samples are given.


title: Wide Residual Networks

abstract:
  Deep residual networks were shown to be able to scale up to thousands of
layers and still have improving performance. However, each fraction of a
percent of improved accuracy costs nearly doubling the number of layers, and so
training very deep residual networks has a problem of diminishing feature
reuse, which makes these networks very slow to train. To tackle these problems,
in this paper we conduct a detailed experimental study on the architecture of
ResNet blocks, based on which we propose a novel architecture where we decrease
depth and increase width of residual networks. We call the resulting network
structures wide residual networks (WRNs) and show that these are far superior
over their commonly used thin and very deep counterparts. For example, we
demonstrate that even a simple 16-layer-deep wide residual network outperforms
in accuracy and efficiency all previous deep residual networks, including
thousand-layer-deep networks, achieving new state-of-the-art results on CIFAR,
SVHN, COCO, and significant improvements on ImageNet. Our code and models are
available at https://github.com/szagoruyko/wide-residual-networks


title: Riemannian SVRG: Fast Stochastic Optimization on Riemannian Manifolds

abstract:
  We study optimization of finite sums of geodesically smooth functions on
Riemannian manifolds. Although variance reduction techniques for optimizing
finite-sums have witnessed tremendous attention in the recent years, existing
work is limited to vector space problems. We introduce Riemannian SVRG (RSVRG),
a new variance reduced Riemannian optimization method. We analyze RSVRG for
both geodesically convex and nonconvex (smooth) functions. Our analysis reveals
that RSVRG inherits advantages of the usual SVRG method, but with factors
depending on curvature of the manifold that influence its convergence. To our
knowledge, RSVRG is the first provably fast stochastic Riemannian method.
Moreover, our paper presents the first non-asymptotic complexity analysis
(novel even for the batch setting) for nonconvex Riemannian optimization. Our
results have several implications; for instance, they offer a Riemannian
perspective on variance reduced PCA, which promises a short, transparent
convergence analysis.


title: Backprop KF: Learning Discriminative Deterministic State Estimators

abstract:
  Generative state estimators based on probabilistic filters and smoothers are
one of the most popular classes of state estimators for robots and autonomous
vehicles. However, generative models have limited capacity to handle rich
sensory observations, such as camera images, since they must model the entire
distribution over sensor readings. Discriminative models do not suffer from
this limitation, but are typically more complex to train as latent variable
models for state estimation. We present an alternative approach where the
parameters of the latent state distribution are directly optimized as a
deterministic computation graph, resulting in a simple and effective gradient
descent algorithm for training discriminative state estimators. We show that
this procedure can be used to train state estimators that use complex input,
such as raw camera images, which must be processed using expressive nonlinear
function approximators such as convolutional neural networks. Our model can be
viewed as a type of recurrent neural network, and the connection to
probabilistic filtering allows us to design a network architecture that is
particularly well suited for state estimation. We evaluate our approach on
synthetic tracking task with raw image inputs and on the visual odometry task
in the KITTI dataset. The results show significant improvement over both
standard generative approaches and regular recurrent neural networks.