title: Direct Sparse Odometry

abstract:
  We propose a novel direct sparse visual odometry formulation. It combines a
fully direct probabilistic model (minimizing a photometric error) with
consistent, joint optimization of all model parameters, including geometry --
represented as inverse depth in a reference frame -- and camera motion. This is
achieved in real time by omitting the smoothness prior used in other direct
methods and instead sampling pixels evenly throughout the images. Since our
method does not depend on keypoint detectors or descriptors, it can naturally
sample pixels from across all image regions that have intensity gradient,
including edges or smooth intensity variations on mostly white walls. The
proposed model integrates a full photometric calibration, accounting for
exposure time, lens vignetting, and non-linear response functions. We
thoroughly evaluate our method on three different datasets comprising several
hours of video. The experiments show that the presented approach significantly
outperforms state-of-the-art direct and indirect methods in a variety of
real-world settings, both in terms of tracking accuracy and robustness.


title:
Robust causal inference with continuous instruments using the local
  instrumental variable curve

abstract:
  Instrumental variables are commonly used to estimate effects of a treatment
afflicted by unmeasured confounding, and in practice instruments are often
continuous (e.g., measures of distance, or treatment preference). However,
available methods for continuous instruments have important limitations: they
either require restrictive parametric assumptions for identification, or else
rely on modeling both the outcome and treatment process well (and require
modeling effect modification by all adjustment covariates). In this work we
develop the first semiparametric doubly robust estimators of the local
instrumental variable effect curve, i.e., the effect among those who would take
treatment for instrument values above some threshold and not below. In addition
to being robust to misspecification of either the instrument or
treatment/outcome processes, our approach also incorporates information about
the instrument mechanism and allows for flexible data-adaptive estimation of
effect modification. We discuss asymptotic properties under weak conditions,
and use the methods to study infant mortality effects of neonatal intensive
care units with high versus low technical capacity, using travel time as an
instrument.


title: Running cosmological constant with observational tests

abstract:
  We investigate the running cosmological constant model with dark energy
linearly proportional to the Hubble parameter, $\Lambda = \sigma H +
\Lambda_0$, in which the $\Lambda$CDM limit is recovered by taking $\sigma=0$.
We derive the linear perturbation equations of gravity under the
Friedmann-Lema\"itre-Robertson-Walker cosmology, and show the power spectra of
the CMB temperature and matter density distribution. By using the Markov chain
Monte Carlo method, we fit the model to the current observational data and find
that $\sigma H_0/ \Lambda_0 \lesssim 2.63 \times 10^{-2}$ and $6.74 \times
10^{-2}$ for $\Lambda(t)$ coupled to matter and radiation-matter, respectively,
along with constraints on other cosmological parameters.


title: Deep Learning of Appearance Models for Online Object Tracking

abstract:
  This paper introduces a novel deep learning based approach for vision based
single target tracking. We address this problem by proposing a network
architecture which takes the input video frames and directly computes the
tracking score for any candidate target location by estimating the probability
distributions of the positive and negative examples. This is achieved by
combining a deep convolutional neural network with a Bayesian loss layer in a
unified framework. In order to deal with the limited number of positive
training examples, the network is pre-trained offline for a generic image
feature representation and then is fine-tuned in multiple steps. An online
fine-tuning step is carried out at every frame to learn the appearance of the
target. We adopt a two-stage iterative algorithm to adaptively update the
network parameters and maintain a probability density for target/non-target
regions. The tracker has been tested on the standard tracking benchmark and the
results indicate that the proposed solution achieves state-of-the-art tracking
results.


title:
Novel Quaternary Dilute Magnetic Semiconductor (Ga,Mn)(Bi,As): Magnetic
  and Magneto-Transport Investigations

abstract:
  Magnetic and magneto-transport properties of thin layers of the
(Ga,Mn)(Bi,As) quaternary dilute magnetic semiconductor grown by the
low-temperature molecular-beam epitaxy technique on GaAs substrates have been
investigated. Ferromagnetic Curie temperature and magneto-crystalline
anisotropy of the layers have been examined by using magneto-optical Kerr
effect magnetometry and low-temperature magneto-transport measurements.
Postgrowth annealing treatment has been shown to enhance the hole concentration
and Curie temperature in the layers. Significant increase in the magnitude of
magnetotransport effects caused by incorporation of a small amount of Bi into
the (Ga,Mn)As layers revealed in the planar Hall effect (PHE) measurements, is
interpreted as a result of enhanced spin-orbit coupling in the (Ga,Mn)(Bi,As)
layers. Two-state behaviour of the planar Hall resistance at zero magnetic
field provides its usefulness for applications in nonvolatile memory devices.


title:
Theoretical and numerical investigation of diffusive instabilities in
  multi-component alloys

abstract:
  Mechanical properties of engineering alloys are strongly correlated to their
microstructural length scale. Diffusive insta- bilities of the Mullins-Sekerka
type is one of the principal mechanisms through which the scale of the
microstructural features are determined during solidification. In contrast to
binary systems, in multicomponent alloys with arbitrary interdiffusivities, the
growth rate as well as the maximally growing wavelengths characterizing these
instabilities depend on the the dynamically selected equilibrium tie-lines and
the steady state growth velocity. In this study, we derive analytical
expressions to characterize the dispersion behavior in isothermally solidified
multicomponent (quaternary) alloys for different choices of the
inter-diffusivity matrices and confirm our calculations using phase-field
simulations. Thereafter, we perform controlled studies to capture and isolate
the dependence of instability length scales on solute diffusivities and steady
state planar front velocities, which leads to an understanding of the process
of length scale selection during the onset of instability for any alloy
composition with arbitrary diffusivities, comprising of both independent and
coupled diffusion of solutes.


title:
Comments on various extensions of the Riemann-Liouville fractional
  derivatives : about the Leibniz and chain rule properties

abstract:
  Starting from the Riemann-Liouville derivative, many authors have built their
own notion of fractional derivative in order to avoid some classical
difficulties like a non zero derivative for a constant function or a rather
complicated analogue of the Leibniz relation. Discussing in full generality the
existence of such operator over continuous functions, we derive some
obstruction Lemma which can be used to prove the triviality of some operators
as long as the linearity and the Leibniz property are preserved. As an
application, we discuss some properties of the Jumarie's fractional derivative
as well as the local fractional derivative. We also discuss the chain rule
property in the same perspective.


title:
Anisotropic emission of direct photons and thermal dileptons from Au+Au
  collisions at $\sqrt{s_{NN}}=200$~GeV with EPOS3

abstract:
  Electromagnetic probes such as direct photons and dileptons are crucial to
study the properties of a Quark-Gluon Plasma (QGP) created in heavy ion
collisions. Based on the (3+1)-dimensional event-by-event viscous hydrodynamic
model EPOS 3.102, we calculated the anisotropic emission of thermal photons and
dileptons in Au+Au collisions at the Relativistic Heavy Ion Collider (RHIC)
energy $\sqrt{s_{NN}}=200$~GeV. Thermal emissions from both QGP phase and
hadronic gas phase are considered, with AMY rate for photons and Lattice QCD
based rates for dileptons in QGP phase. For emission from hadron gas phase,
rates based vector meson dominant model are used for both photons and
dileptons. Non-thermal contribution to direct photons is calculated with next
to leading order QCD. STAR cocktail data are directly used for non-thermal
contribution to dileptons. With the same space-time evolution of the collision
systems, the two penetrating probes, photons and dileptonsshow some
consistency, ie, the emission of both thermal photons and dileptons are
underestimated, compared with the transverse momentum spectra of direct photons
measured by PHENIX collaboration and the invariant mass spectra of dileptons
measured by STAR collaboration, for all centrality classes. With a good
constraint of anisotropy of the plasma via the elliptic flow and triangular
flow of charged hadrons, the resulted elliptic flow and triangular flow of
direct photons agree with PHENIX measurements reasonably well. Thus we made
predictions to the flows of thermal dileptons. The elliptic flow of thermal
dileptons is predicted larger than the available results from other models, and
comparable to the STAR measurement referring to all dileptons (thermal +
cocktail) for minimal bias collisions.


title:
Microwave Tomographic Imaging of Cerebrovascular Accidents by Using
  High-Performance Computing

abstract:
  The motivation of this work is the detection of cerebrovascular accidents by
microwave tomographic imaging. This requires the solution of an inverse problem
relying on a minimization algorithm (for example, gradient-based), where
successive iterations consist in repeated solutions of a direct problem. The
reconstruction algorithm is extremely computationally intensive and makes use
of efficient parallel algorithms and high-performance computing. The
feasibility of this type of imaging is conditioned on one hand by an accurate
reconstruction of the material properties of the propagation medium and on the
other hand by a considerable reduction in simulation time. Fulfilling these two
requirements will enable a very rapid and accurate diagnosis. From the
mathematical and numerical point of view, this means solving Maxwell's
equations in time-harmonic regime by appropriate domain decomposition methods,
which are naturally adapted to parallel architectures.


title:
The Miracle of Peer Review and Development in Science: An Agent-Based
  Model

abstract:
  It is not easy to rationalize how peer review, as the current grassroots of
science, can work based on voluntary contributions of reviewers. There is no
rationale to write impartial and thorough evaluations. Consequently, there is
no risk in submitting low-quality work by authors. As a result, scientists face
a social dilemma: if everyone acts according to his or her own self-interest,
low scientific quality is produced. Still, in practice, reviewers as well as
authors invest high effort in reviews and submissions.
  We examine how the increased relevance of public good benefits (journal
impact factor), the editorial policy of handling incoming reviews, and the
acceptance decisions that take into account reputational information can help
the evolution of high-quality contributions from authors. High effort from the
side of reviewers is problematic even if authors cooperate: reviewers are still
best off by producing low-quality reviews, which does not hinder scientific
development, just adds random noise and unnecessary costs to it. We show with
agent-based simulations that tacit agreements between authors that are based on
reciprocity might decrease these costs, but does not result in superior
scientific quality. Our study underlines why certain self-emerged current
practices, such as the increased importance of journal metrics, the
reputation-based selection of reviewers, and the reputation bias in acceptance
work efficiently for scientific development. Our results find no answers,
however, how the system of peer review with impartial and thorough evaluations
could be sustainable jointly with rapid scientific development.


title: Approximate invariance for ergodic actions of amenable groups

abstract:
  We develop in this paper some general techniques to analyze action sets of
small doubling for probability measure-preserving actions of amenable groups.
  As an application of these techniques, we prove a dynamical generalization of
Kneser's celebrated density theorem for subsets in $(\bZ,+)$, valid for any
countable amenable group, and we show how it can be used to establish a
plethora of new inverse product set theorems for upper and lower asymptotic
densities. We provide several examples demonstrating that our results are
optimal for the settings under study.


title: Analysis of opinionated text for opinion mining

abstract:
  In sentiment analysis, the polarities of the opinions expressed on an
object/feature are determined to assess the sentiment of a sentence or document
whether it is positive/negative/neutral. Naturally, the object/feature is a
noun representation which refers to a product or a component of a product, let
us say, the "lens" in a camera and opinions emanating on it are captured in
adjectives, verbs, adverbs and noun words themselves. Apart from such words,
other meta-information and diverse effective features are also going to play an
important role in influencing the sentiment polarity and contribute
significantly to the performance of the system. In this paper, some of the
associated information/meta-data are explored and investigated in the sentiment
text. Based on the analysis results presented here, there is scope for further
assessment and utilization of the meta-information as features in text
categorization, ranking text document, identification of spam documents and
polarity classification problems.


title:
Extensive photometry of the intermediate polar MU Cam: detection of a
  spin period change

abstract:
  Intermediate polars with known rates of spin period changes are not numerous
because such tasks require measurements performed for a long time. To measure a
spin period change, MU Cam is a good candidate because it has a spin
oscillation with a large amplitude enabling measurements with high precision.
Fortunately, in the past the spin period of MU Cam was measured with high
precision. To measure the spin period anew, in 2014-2015 we performed extensive
photometric observations of MU Cam, spanning a total duration of 208 h within
46 nights. We found that the spin, sideband and orbital periods are equal to
1187.16245+/-0.00047 s, 1276.3424+/-0.0022 s and 4.71942+/-0.00016 h,
respectively. Comparing the measured spin period with the spin period of MU Cam
in the past, we detected the spin period change with dP/dt=-(2.17+/-0.10) X
10^(-10). This rate of the spin period change was not stable and varied in a
time scale of years. During four nights in 2014 April-May MU Cam was fainter
than usual by 0.8 mag, and the amplitude of the sideband oscillation was five
times larger, denoting significant fraction of disc-overflow accretion. The
sideband oscillation showed a double-peaked pulse profile in the normal
brightness state. When the star brightness was decreased by 0.8 mag, the
sideband oscillation showed a single-peaked pulse profile. In contrast, the
spin pulse, which was quasi-sinusoidal, remained remarkably stable both in
profile and in amplitude. Moreover, the spin pulse was also remarkably stable
in a time scale of years and even decades. MU Cam is of great interest because
it represents a distinctive object with a large and unstable rate of the spin
period change and exhibits a distinctive behaviour of the pulse profiles.


title:
Quantum entanglement in the spatial symmetry breaking phase transition
  of a driven-dissipative Bose-Hubbard dimer

abstract:
  We theoretically explore quantum correlation properties of a dissipative
Bose-Hubbard dimer in presence of a coherent drive. In particular, we focus on
the regime where the semiclassical theory predicts a bifurcation with a
spontaneous spatial symmetry breaking. The critical behavior in a well defined
thermodynamical limit of large excitation numbers is considered and analyzed
within a Gaussian approach. The case of a finite boson density is also examined
by numerically integrating the Lindblad master equation for the density matrix.
We predict the critical behavior around the bifurcation points accompanied with
large quantum correlations of the mixed steady-state, in particular exhibiting
a peak in the logarithmic entanglement negativity.


title: Foliated Quantum Codes

abstract:
  We show how to construct a large class of quantum error correcting codes,
known as CSS codes, from highly entangled cluster states. This becomes a
primitive in a protocol that foliates a series of such cluster states into a
much larger cluster state, implementing foliated quantum error correction. We
exemplify this construction with several familiar quantum error correction
codes, and propose a generic method for decoding foliated codes. We numerically
evaluate the error-correction performance of a family of finite-rate CSS codes
known as turbo codes, finding that it performs well over moderate depth
foliations. Foliated codes have applications for quantum repeaters and
fault-tolerant measurement-based quantum computation.


title: CAT(-1) metrics on small cancellation groups

abstract:
  We give a proof that groups satisfying the "uniform C'(1/6)" small
cancellation condition admit a geometric action on a CAT(-1) space. It follows
that random groups at density <1/12 are CAT(-1). The proof consists of a direct
construction of a piecewise hyperbolic structure on the presentation complex of
such a group, together with folding moves to make the complex negatively
curved. The argument was originally suggested by Gromov.


title:
A Potential Correlation Between the Temperature of the Pacific Ocean and
  Data from Google Trends May Yield a Warning Sign for the Outbreak of Zika

abstract:
  There has been a large number of reported cases of the occurrence of Zika in
different countries in 2016 and it is necessary to develop an early warning
system to initiate preventive campaigns against the disease. A potential early
warning system based on the rise in ocean temperature of the Pacific Ni\~no
Index is proposed. The efficacy is verified using data for the outbreak in
Colombia as obtained from Google Trends.


title:
The impact of bars on the radial distribution of supernovae in disc
  galaxies

abstract:
  We present an analysis of the impact of bars on the radial distributions of
the different types of supernovae (SNe) in the stellar discs of host galaxies
with various morphologies. We find that in Sa-Sbc galaxies, the radial
distribution of core-collapse (CC) SNe in barred hosts is inconsistent with
that in unbarred ones, while the distributions of SNe Ia are not significantly
different. At the same time, the radial distributions of both types of SNe in
Sc-Sm galaxies are not affected by bars. We propose that the additional
mechanism shaping the distributions of Type Ia and CC SNe can be explained
within the framework of substantial suppression of massive star formation in
the radial range swept by strong bars, particularly in early-type spirals. The
radial distribution of CC SNe in unbarred Sa-Sbc galaxies is more centrally
peaked and inconsistent with that in unbarred Sc-Sm hosts, while the
distribution of SNe Ia in unbarred galaxies is not affected by host morphology.
These results can be explained by the distinct distributions of massive stars
in the discs of early-and late-type spirals.


title: Quasi-periodic solutions for quasi-linear generalized KdV equations

abstract:
  We prove the existence of Cantor families of small amplitude, linearly
stable, quasi-periodic solutions of quasi-linear autonomous Hamiltonian
generalized KdV equations. We consider the most general quasi-linear quadratic
nonlinearity. The proof is based on an iterative Nash-Moser algorithm. To
initialize this scheme, we need to perform a bifurcation analysis taking into
account the strongly perturbative effects of the nonlinearity near the origin.
In particular, we implement a weak version of the Birkhoff normal form method.
The inversion of the linearized operators at each step of the iteration is
achieved by pseudo-differential techniques, linear Birkhoff normal form
algorithms and a linear KAM reducibility scheme.


title:
A Unified Alternating Direction Method of Multipliers by Majorization
  Minimization

abstract:
  Accompanied with the rising popularity of compressed sensing, the Alternating
Direction Method of Multipliers (ADMM) has become the most widely used solver
for linearly constrained convex problems with separable objectives. In this
work, we observe that many previous variants of ADMM update the primal variable
by minimizing different majorant functions with their convergence proofs given
case by case. Inspired by the principle of majorization minimization, we
respectively present the unified frameworks and convergence analysis for the
Gauss-Seidel ADMMs and Jacobian ADMMs, which use different historical
information for the current updating. Our frameworks further generalize
previous ADMMs to the ones capable of solving the problems with non-separable
objectives by minimizing their separable majorant surrogates. We also show that
the bound which measures the convergence speed of ADMMs depends on the
tightness of the used majorant function. Then several techniques are introduced
to improve the efficiency of ADMMs by tightening the majorant functions. In
particular, we propose the Mixed Gauss-Seidel and Jacobian ADMM (M-ADMM) which
alleviates the slow convergence issue of Jacobian ADMMs by absorbing merits of
the Gauss-Seidel ADMMs. M-ADMM can be further improved by using backtracking,
wise variable partition and fully exploiting the structure of the constraint.
Beyond the guarantee in theory, numerical experiments on both synthesized and
real-world data further demonstrate the superiority of our new ADMMs in
practice. Finally, we release a toolbox at https://github.com/canyilu/LibADMM
that implements efficient ADMMs for many problems in compressed sensing.


title: Algebraic construction of spherical harmonics

abstract:
  The angular wave functions for a hydrogen atom are well known to be spherical
harmonics, and are obtained as the solutions of a partial differential
equation. However, the differential operator is given by the Casimir operator
of the $SU(2)$ algebra and its eigenvalue $l(l+1) \hbar^2$, where $l$ is
non-negative integer, is easily obtained by an algebraic method. Therefore the
shape of the wave function may also be obtained by extending the algebraic
method. In this paper, we describe the method and show that wave functions with
different quantum numbers are connected by a rotational group in the cases of
$l=0$, 1 and 2.


title:
Visual Dynamics: Probabilistic Future Frame Synthesis via Cross
  Convolutional Networks

abstract:
  We study the problem of synthesizing a number of likely future frames from a
single input image. In contrast to traditional methods, which have tackled this
problem in a deterministic or non-parametric way, we propose a novel approach
that models future frames in a probabilistic manner. Our probabilistic model
makes it possible for us to sample and synthesize many possible future frames
from a single input image. Future frame synthesis is challenging, as it
involves low- and high-level image and motion understanding. We propose a novel
network structure, namely a Cross Convolutional Network to aid in synthesizing
future frames; this network structure encodes image and motion information as
feature maps and convolutional kernels, respectively. In experiments, our model
performs well on synthetic data, such as 2D shapes and animated game sprites,
as well as on real-wold videos. We also show that our model can be applied to
tasks such as visual analogy-making, and present an analysis of the learned
network representations.


title:
In-beam evaluation of a medium-size Resistive-Plate WELL gaseous
  particle detector

abstract:
  In-beam evaluation of a fully-equipped medium-size 30$\times$30 cm$^2$
Resistive Plate WELL (RPWELL) detector is presented. It consists here of a
single element gas-avalanche multiplier with Semitron ESD225 resistive plate, 1
cm$^2$ readout pads and APV25/SRS electronics. Similarly to previous results
with small detector prototypes, stable operation at high detection efficiency
(>98%) and low average pad multiplicity (~1.2) were recorded with 150 GeV muon
and high-rate pion beams, in Ne/(5%CH$_4$), Ar/(5%CH$_4$) and Ar/(7%CO$_2$).
This is an important step towards the realization of robust detectors suitable
for applications requiring large-area coverage; among them Digital Hadron
Calorimetry.


title:
Influence of temporal aspects and age-correlations on the process of
  opinion formation based on Polish contact survey

abstract:
  On the basis of the experimental data concerning interactions between humans
the process of Ising-based model of opinion formation in a social network was
investigated. In the paper the data concerning human social activity, i.e.
frequency and duration time of interpersonal interactions as well as age
correlations - homophily are presented in comparison to base line homogeneous,
static and uniform mixing. It is known from previous studies that number of
contact and average age of nearest neighbors are highly correlated with age of
an individual. Such real, assortative patterns usually speed up processes (like
epidemic spread) on the networks, but here it only plays a role for small
social temperature values (by reducing `freezing by heating' effect). A real
structure of contacts affects processes in many various studies in different
way, however here it causes stronger (dynamic) and smoother (durations)
susceptibility on external field. Moreover, our research shows that the cross
interactions between contact frequency and its duration impose the significant
increase in critical temperature.


title: Quaternionic (super)twistors extensions and general superspaces

abstract:
  In a attempt to treat a supergravity as a tensor representation, the
4-dimensional N-extended quaternionic superspaces are constructed from the
(diffeomorphyc)graded extension of the ordinary Penrose-twistor formulation,
performed in a previous work of the authors[14], with N = p + k: These
quaternionic superspaces have 4 + k (N - k) even-quaternionic coordinates and
4N odd- quaternionic coordinates where each coordinate is a quaternion composed
by four C-felds (bosons and fermions respectively). The fields content as the
dimensionality (even and odd sectors) of these superspaces are given and
exemplified by selected physical cases. In this case the number of felds of the
supergravity is determined by the number of components of the tensor
representation of the 4-dimensional N-extended quaternionic superspaces. The
role of tensorial central charges for any N even USp (N) = Sp (N;HC) \ U (N;HC)
is elucidated from this theoretical context.


title: Applications of the Wall form to unipotent isometries of index two

abstract:
  We investigate the Wall form of unipotent elements of index two in the
orthogonal group and obtain a decomposition for these elements. Also, in
characteristic two, the relation between the Wall form and some invariants of
the induced involution on the Clifford algebra is studied.


title: On the decomposition of metabolic involutions

abstract:
  The problem of whether a metabolic idempotent of a central simple algebra
with involution is contained in an invariant quaternion subalgebra is
investigated. As an application, the similar problem is studied for
skew-symmetric elements whose squares lie in the square of the underlying
field.


title:
Variation of the physical properties of four transition metal oxides
  SrTMO3 (TM = Rh, Ti, Mo, Zr) under pressure: An ab initio study

abstract:
  Using first principles calculations, we have studied the structural and
elastic properties of SrTMO3 (TM = Rh, Ti, Mo, Zr) under pressure by the plane
wave pseudopotential method based on the density functional theory (DFT) within
the generalized gradient approximation (GGA). The optical properties have been
investigated under zero pressure. It is observed that the calculated lattice
parameters are in good agreement with the available experimental result and
previous theoretical results.


title: More about the Instanton/Soliton/Kink correspondence

abstract:
  We demonstrate that all gauge instantons in a $d=3+1$ Yang-Mills theory, with
generic topological vacuum charge K, correspond to soliton solutions and kink
scalar fields in $d=4+1$ space-time.


title:
Gauge dependence and self-force from Galilean to Einsteinian free fall,
  compact stars falling into black holes, Hawking radiation and the Pisa tower
  at the general relativity centennial

abstract:
  (Short abstract). In Galilean physics, the universality of free fall implies
an inertial frame, which in turns implies that the mass m of the falling body
is omitted. Otherwise, an additional acceleration proportional to m/M would
rise either for an observer at the centre of mass of the system, or for an
observer at a fixed distance from the centre of mass of M. These elementary,
but overlooked, considerations fully respect the equivalence principle and the
identity of an inertial or a gravitational pull for an observer in the Einstein
cabin. They value as fore-runners of the self-force and gauge dependency in
general relativity. The approximate nature of Galilei's law of free fall is
explored herein. When stepping into general relativity, we report how the
geodesic free fall into a black hole was the subject of an intense debate again
centred on coordinate choice. Later, we describe how the infalling mass and the
emitted gravitational radiation affect the free fall motion of a body. The
general relativistic self-force might be dealt with to perfectly fit into a
geodesic conception of motion. Then, embracing quantum mechanics, real black
holes are not classical static objects any longer. Free fall has to handle the
Hawking radiation, and leads us to new perspectives on the varying mass of the
evaporating black hole and on the varying energy of the falling mass. Along the
paper, we also estimate our findings for ordinary masses being dropped from a
Galilean or Einsteinian Pisa-like tower with respect to the current state of
the art drawn from precise measurements in ground and space laboratories, and
to the constraints posed by quantum measurements. The appendix describes how
education physics and high impact factor journals discuss the free fall.
Finally, case studies conducted on undergraduate students and teachers are
reviewed.


title: Non-Abelian black string solutions of N=(2,0),d=6 supergravity

abstract:
  We show that, when compactified on a circle, N=(2,0),d=6 supergravity coupled
to 1 tensor multiplet and nV vector multiplets is dual to N=(2,0),d=6
supergravity coupled to just nT=nV+1 tensor multiplets and no vector
multiplets. Both theories reduce to the same models of N=2,d=5 supergravity
coupled to nV5=nV+2 vector fields. We derive Buscher rules that relate
solutions of these theories (and of the theory that one obtains by dualizing
the 3-form field strength) admitting an isometry. Since the relations between
the fields of N=2,d=5 supergravity and those of the 6-dimensional theories are
the same with or without gaugings, we construct supersymmetric non-Abelian
solutions of the 6-dimensional gauged theories by uplifting the recently found
5-dimensional supersymmetric non-Abelian black-hole solutions. The solutions
describe the usual superpositions of strings and waves supplemented by a BPST
instanton in the transverse directions. One of the solutions obtained
interpolates smoothly between two AdS3xS3 geometries with different radii.


title:
Large-Scale Fluctuations in the Number Density of Galaxies in
  Independent Surveys of Deep Fields

abstract:
  New arguments supporting the reality of large-scale fluctuations in the
density of the visible matter in deep galaxy surveys are presented. A
statistical analysis of the radial distributions of galaxies in the COSMOS and
HDF-N deep fields is presented. Independent spectral and photometric surveys
exist for each field, carried out in different wavelength ranges and using
different observing methods. Catalogs of photometric redshifts in the optical
(COSMOS-Zphot) and infrared (UltraVISTA) were used for the COSMOS field in the
redshift interval $0.1 < z < 3.5$, as well as the zCOSMOS (10kZ) spectroscopic
survey and the XMM-COSMOS and ALHAMBRA-F4 photometric redshift surveys. The
HDFN-Zphot and ALHAMBRA-F5 catalogs of photometric redshifts were used for the
HDF-N field. The Pearson correlation coefficient for the fluctuations in the
numbers of galaxies obtained for independent surveys of the same deep field
reaches $R = 0.70 \pm 0.16$. The presence of this positive correlation supports
the reality of fluctuations in the density of visible matter with sizes of up
to 1 000 Mpc and amplitudes of up to 20% at redshifts $z \sim 2$. The absence
of correlations between the fluctuations in different fields (the correlation
coefficient between COSMOS and HDF-N is $R = -0.20 \pm 0.31$) testifies to the
independence of structures visible in different directions on the celestial
sphere. This also indicates an absence of any influence from universal
systematic errors (such as "spectral voids"), which could imitate the detection
of correlated structures.


title:
Background Stratospheric Aerosol Investigations Using Multi-Color
  Wide-Field Measurements of the Twilight Sky

abstract:
  First results of multi-wavelength measurements of the twilight sky background
using all-sky camera with RGB-color CCD conducted in spring and summer of 2016
in central Russia (55.2 deg N, 37.5 deg E) are discussed. They show the effect
of aerosol scattering at altitudes up to 35 km which significantly increases to
the long-wave range (624 nm, R channel). Analysis of sky color behavior during
the light period of twilight with account of ozone Chappuis absorption allows
retrieving the angle dependencies of scattering on the stratospheric aerosol
particles. This is used to find the parameters of lognormal size distribution:
median radius about 0.08 microns and width 1.5-1.6 for stratospheric altitude
range.


title:
Security Pricing as an Enabler of Cyber-Insurance: A First Look at
  Differentiated Pricing Markets

abstract:
  Despite the promising potential of network risk management services (e.g.,
cyber-insurance) to improve information security, their deployment is
relatively scarce, primarily due to such service companies being unable to
guarantee profitability. As a novel approach to making cyber-insurance services
more viable, we explore a symbiotic relationship between security vendors
(e.g., Symantec) capable of price differentiating their clients, and
cyber-insurance agencies having possession of information related to the
security investments of their clients. The goal of this relationship is to (i)
allow security vendors to price differentiate their clients based on security
investment information from insurance agencies, (ii) allow the vendors to make
more profit than in homogeneous pricing settings, and (iii) subsequently
transfer some of the extra profit to cyber-insurance agencies to make insurance
services more viable. \noindent In this paper, we perform a theoretical study
of a market for differentiated security product pricing, primarily with a view
to ensuring that security vendors (SVs) make more profit in the differentiated
pricing case as compared to the case of non-differentiated pricing. In order to
practically realize such pricing markets, we propose novel and
\emph{computationally efficient} consumer differentiated pricing mechanisms for
SVs based on (i) the market structure, (ii) the communication network structure
of SV consumers captured via a consumer's \emph{Bonacich centrality} in the
network, and (iii) security investment amounts made by SV consumers.


title:
Phase tunable Josephson junction and spontaneous mass current in a
  spin-orbit coupled Fermi superfluid

abstract:
  Atomtronics has the potential for engineering new types of functional
devices, such as Josephson junctions (JJs). Previous studies have mainly
focused on JJs whose ground states have 0 or $\pi $ superconducting phase
difference across the junctions, while arbitrarily tunable phase JJs may have
important applications in superconducting electronics and quantum computation.
Here we show that a phase tunable JJ can be implemented in a spin-orbit coupled
cold atomic gas with the magnetic tunneling barrier generated by a
spin-dependent focused laser beam. We consider the JJ confined in either a
linear harmonic trap or a circular ring trap. In the ring trap, the magnetic
barrier induces a spontaneous mass current for the ground state of the JJ,
demonstrating the magnetoelectric effects of cold atoms.


title:
Cosmic Tsunamis in Modified Gravity: Disruption of Screening Mechanisms
  from Scalar Waves

abstract:
  Extending general relativity by adding extra degrees of freedom is a popular
approach for explaining the accelerated expansion of the Universe and to build
high energy completions of the theory of gravity. The presence of such new
degrees of freedom is, however, tightly constrained from several observations
and experiments that aim to test general relativity in a wide range of scales.
The viability of a given modified theory of gravity, therefore, strongly
depends on the existence of a screening mechanism that suppresses the extra
degrees of freedom. We perform simulations, and find that waves propagating in
the new degrees of freedom can significantly impact the efficiency of some
screening mechanisms, thereby threatening the viability of these modified
gravity theories. Specifically, we show that the waves produced in the
symmetron model can increase the amplitude of the fifth force and the
parametrized post-Newtonian parameters by several orders of magnitude.


title:
Orientation of the electric field gradient and ellipticity of the
  magnetic cycloid in multiferroic BiFeO3

abstract:
  The paper deals with the hyperfine interactions observed on the 57Fe nucleus
in multiferroic BiFeO3 by means of the 14.41-keV resonant transition in 57Fe,
and for transmission geometry applied to the random powder sample. Spectra were
obtained at 80 K, 190 K and at room temperature. It was found that iron occurs
in the high spin trivalent state. Hyperfine magnetic field follows distribution
due to the elliptic-like distortion of the magnetic cycloid. The long axis of
the ellipse is oriented along <111> direction of the rhombohedral unit cell.
The hyperfine magnetic field in this direction is about 1.013 of the field in
the perpendicular direction at room temperature. This ratio diminishes to 1.010
at 80 K. Axially symmetric electric field gradient (EFG) on the iron atoms has
the principal axis oriented in the same direction and the main component of the
EFG is positive. Our results are consistent with the finding that iron magnetic
moments are confined to the [1-21] crystal plane.


title: Deformation rings and parabolic induction

abstract:
  We study deformations of smooth mod $p$ representations (and their duals) of
a $p$-adic reductive group $G$. Under some mild genericity condition, we prove
that parabolic induction with respect to a parabolic subgroup $P=LN$ defines an
isomorphism between the universal deformation rings of a supersingular
representation $\bar{\sigma}$ of $L$ and of its parabolic induction
$\bar{\pi}$. As a consequence, we show that every Banach lift of $\bar{\pi}$ is
induced from a unique Banach lift of $\bar{\sigma}$.


title: On the MIT bag model: self-adjointness and non-relativistic limit

abstract:
  This paper is devoted to the mathematical investigation of the MIT bag model,
that is the Dirac operator on a smooth and bounded domain with certain boundary
conditions. We prove that the operator is self-adjoint and, when the mass goes
to infinity, we provide spectral asymptotic results.


title: Convergence of Multivariate Quantile Surfaces

abstract:
  We define the quantile set of order $\alpha \in \left[ 1/2,1\right) $
associated to a law $P$ on $\mathbb{R}^{d}$ to be the collection of its
directional quantiles seen from an observer $O\in \mathbb{R}^{d}$. Under
minimal assumptions these star-shaped sets are closed surfaces, continuous in
$(O,\alpha )$ and the collection of empirical quantile surfaces is uniformly
consistent.\ Under mild assumptions -- no density or symmetry is required for
$P$ -- our uniform central limit theorem reveals the correlations between
quantile points and a non asymptotic Gaussian approximation provides joint
confident enlarged quantile surfaces. Our main result is a dimension free rate
$n^{-1/4} (\log n)^{1/2}(\log\log n) ^{1/4} $ of Bahadur-Kiefer embedding by
the empirical process indexed by half-spaces. These limit theorems sharply
generalize the univariate quantile convergences and fully characterize the
joint behavior of Tukey half-spaces.


title:
P,T-odd Faraday effect as a tool for observation of CP violation in
  Standard Model

abstract:
  It is proposed to employ the P,T-odd Faraday effect, i.e. rotation of the
polarization plane of the light propagating through a medium in presence of the
electric field, as a tool for observation of P,T-odd effects caused by CP
violation within the Standard Model. For this purpose the vapors of heavy atoms
like Tl, Pb, Bi are most suitable. Estimates within the Standard Model show:
provided that applied field is about 10^5 V/cm and the optical length can be as
large as 70000 km, the rotation angle may reach the value corresponding to the
recently observable values (10^{-9} rad). These estimates demonstrate that the
P,T-odd Faraday effect observations may effectively compete with the recent
measurements of the electron spin rotation in an external electric field,
performed with diatomic molecules. These measurements exclude the P,T-odd
effects at the level 9 orders of magnitude higher than the predictions of the
Standard Model.


title: No need for dark matter in galaxy clusters within Galileon theory

abstract:
  Modified gravity theories with a screening mechanism have acquired much
interest recently in the quest for a viable alternative to General Relativity
on cosmological scales, given their intrinsic property of being able to pass
Solar System scale tests and, at the same time, to possibly drive universe
acceleration on much larger scales. Here, we explore the possibility that the
same screening mechanism, or its breaking at a certain astrophysical scale,
might be responsible of those gravitational effects which, in the context of
general relativity, are generally attributed to Dark Matter. We consider a
recently proposed extension of covariant Galileon models in the so-called
"beyond Horndeski" scenario, where a breaking of the Vainshtein mechanism is
possible and, thus, some peculiar observational signatures should be detectable
and make it distinguishable from general relativity. We apply this model to a
sample of clusters of galaxies observed under the \textit{CLASH} survey, using
both new data from gravitational lensing events and archival data from X-ray
intra-cluster hot gas observations. In particular, we use the latter to model
the gas density, and then use it as the only ingredient in the matter clusters'
budget to calculate the expected lensing convergence map. Results show that, in
the context of this extended Galileon, the assumption of having only gas and no
Dark Matter at all in the clusters is able to match observations. We also
obtain narrow and very interesting bounds on the parameters which characterize
this model. In particular, we find that, at least for one of them, the general
relativity limit is excluded at $2\sigma$ confidence level, thus making this
model clearly statistically different and competitive with respect to general
relativity.


title: Data Set From Molisan Regional Seismic Network Events

abstract:
  After the earthquake occurred in Molise (Central Italy) on 31st October 2002
(Ml 5.4, 29 people dead), the local Servizio Regionale per la Protezione Civile
to ensure a better analysis of local seismic data, through a convention with
the Istituto Nazionale di Geofisica e Vulcanologia (INGV), promoted the design
of the Regional Seismic Network (RMSM) and funded its implementation. The 5
stations of RMSM worked since 2007 to 2013 collecting a large amount of seismic
data and giving an important contribution to the study of seismic sources
present in the region and the surrounding territory. This work reports about
the dataset containing all triggers collected by RMSM since July 2007 to March
2009, including actual seismic events; among them, all earthquakes events
recorded in coincidence to Rete Sismica Nazionale Centralizzata (RSNC) of INGV
have been marked with S and P arrival timestamps. Every trigger has been
associated to a spectrogram defined into a recorded time vs. frequency domain.
The main aim of this structured dataset is to be used for further analysis with
data mining and machine learning techniques on image patterns associated to the
waveforms.


title:
The parabolic Monge-Amp\`ere equation on compact almost Hermitian
  manifolds

abstract:
  We prove the long time existence and uniqueness of solutions to the parabolic
Monge-Amp\`ere equation on compact almost Hermitian manifolds. We also show
that the normalization of solution converges to a smooth function in
$C^{\infty}$ topology as $t\rightarrow\infty$. Up to scaling, the limit
function is a solution of the Monge-Amp\`ere equation. This gives a parabolic
proof of existence of solutions to the Monge-Amp\`ere equation on almost
Hermitian manifolds.


title: Dualizable and semi-flat objects in abstract module categories

abstract:
  In this paper, we define what it means for an object in an abstract module
category to be dualizable and we give a homological description of the direct
limit closure of the dualizable objects. Our description recovers existing
results of Govorov and Lazard, Oberst and R{\"o}hrl, and Christensen and Holm.
When applied to differential graded modules over a differential graded algebra,
our description yields that a DG-module is semi-flat if and only if it can be
obtained as a direct limit of finitely generated semi-free DG-modules. We
obtain similar results for graded modules over graded rings and for
quasi-coherent sheaves over nice schemes.


title: Pair Production in Near Extremal Kerr-Newman Black Holes

abstract:
  The spontaneous pair production of charged scalars in a near extremal
Kerr-Newman (KN) black hole is analytically studied. It is shown that the
existence condition for the pair production is equivalent to the violation of
the Breitenlohner-Freedman bound in an AdS$_2$ space. The mean number of
produced pairs in the extremal black hole has a thermal interpretation, in
which the effective temperature for the Schwinger effect in the AdS$_2$ space
persistently holds, while the mean number in the near extremal black hole has
an additional factor of the Schwinger effect in the Rindler space. In addition,
the holographic dual conformal field theory (CFT) descriptions of the charged
scalar pair production are respectively realized both in the $J$ and $Q$
pictures in terms of the KN/CFTs correspondence.


title: Hyperbolicity and Averaging for the Srzednicki-W\'ojcik equation

abstract:
  For the Srzednicki-W\'ojcik equation, the planar nonautonomous ODE
parameterized by $\kappa \in \mathbb{R}$, $$ z'=\overline{z}(1+ |z|^2 \exp(i
\kappa t)), \qquad z(t) \in \mathbb{C} $$ using averaging we show how the
region of hyperbolicty grows with $|\kappa|$. Based on this we give bounds on
the sizes of bounded orbits.


title: Resonant optical gating of suspended carbon nanotube transistor

abstract:
  Building smaller transistors with enhanced functionality is critical in
extending the limits of Moores law and meeting the demands of the electronics
industry. Here we demonstrate transistor operation in a suspended single carbon
nanotube (CNT) using feedback-enabled radiation pressure of a near-field
focused laser that enabled significant changes in conductivity of the CNT.
Further, using in-situ tip-enhanced Raman spectroscopy, we show that the change
in conductivity of over five orders in magnitude is accompanied by self-induced
defect states within the CNT. The entire structure is less than 10 nm in
dimension and shows promise of scalability. This is a novel method for
achieving logic operations at the nanoscale.


title: New approach to Bayesian high-dimensional linear regression

abstract:
  Consider the problem of estimating parameters $X^n \in \mathbb{R}^n $,
generated by a stationary process, from $m$ response variables $Y^m =
AX^n+Z^m$, under the assumption that the distribution of $X^n$ is known. This
is the most general version of the Bayesian linear regression problem. The lack
of computationally feasible algorithms that can employ generic prior
distributions and provide a good estimate of $X^n$ has limited the set of
distributions researchers use to model the data. In this paper, a new scheme
called Q-MAP is proposed. The new method has the following properties: (i) It
has similarities to the popular MAP estimation under the noiseless setting.
(ii) In the noiseless setting, it achieves the "asymptotically optimal
performance" when $X^n$ has independent and identically distributed components.
(iii) It scales favorably with the dimensions of the problem and therefore is
applicable to high-dimensional setups. (iv) The solution of the Q-MAP
optimization can be found via a proposed iterative algorithm which is provably
robust to the error (noise) in the response variables.


title: Sums of two squares and a power

abstract:
  We extend results of Jagy and Kaplansky and the present authors and show that
for all $k\geq 3$ there are infinitely many positive integers $n$, which cannot
be written as $x^2+y^2+z^k=n$ for positive integers $x,y,z$, where for
$k\not\equiv 0 \bmod 4$ a congruence condition is imposed on $z$. These
examples are of interest as there is no congruence obstruction itself for the
representation of these $n$. This way we provide a new family of
counterexamples to the Hasse principle or strong approximation.


title:
Evidence for a spinon Fermi surface in a triangular lattice quantum spin
  liquid candidate

abstract:
  A quantum spin liquid is an exotic quantum state of matter in which spins are
highly entangled and remain disordered down to zero temperature. Such a state
of matter is potentially relevant to high-temperature superconductivity and
quantum-information applications, and experimental identification of a quantum
spin liquid state is of fundamental importance for our understanding of quantum
matter. Theoretical studies have proposed various quantum-spin-liquid ground
states, most of which are characterized by exotic spin excitations with
fractional quantum numbers (termed `spinon'). Here, we report neutron
scattering measurements that reveal broad spin excitations covering a wide
region of the Brillouin zone in a triangular antiferromagnet YbMgGaO4. The
observed diffusive spin excitation persists at the lowest measured energy and
shows a clear upper excitation edge, which is consistent with the particle-hole
excitation of a spinon Fermi surface. Our results therefore point to a QSL
state with a spinon Fermi surface in YbMgGaO4 that has a perfect spin-1/2
triangular lattice as in the original proposal of quantum spin liquids.


title:
Gravitational wave observations may constrain gamma-ray burst models:
  the case of GW 150914 - GBM

abstract:
  The possible short gamma-ray burst (GRB) observed by {\it Fermi}/GBM in
coincidence with the first gravitational wave (GW) detection, offers new ways
to test GRB prompt emission models. Gravitational wave observations provide
previously unaccessible physical parameters for the black hole central engine
such as its horizon radius and rotation parameter. Using a minimum jet
launching radius from the Advanced LIGO measurement of GW~150914, we calculate
photospheric and internal shock models and find that they are marginally
inconsistent with the GBM data, but cannot be definitely ruled out. Dissipative
photosphere models, however have no problem explaining the observations. Based
on the peak energy and the observed flux, we find that the external shock model
gives a natural explanation, suggesting a low interstellar density ($\sim
10^{-3}$ cm$^{-3}$) and a high Lorentz factor ($\sim 2000$). We only speculate
on the exact nature of the system producing the gamma-rays, and study the
parameter space of a generic Blandford Znajek model. If future joint
observations confirm the GW-short GRB association we can provide similar but
more detailed tests for prompt emission models.


title:
The H\"ormander Multiplier Theorem III: The complete bilinear case via
  interpolation

abstract:
  We develop a special multilinear complex interpolation theorem that allows us
to prove an optimal version of the bilinear H\"ormander multiplier theorem
concerning symbols that lie in the Sobolev space $L^r_s(\mathbb R^{2n})$, $2\le
r<\infty$, $rs>2n$, uniformly over all annuli. More precisely, given a
smoothness index $s$, we find the largest open set of indices $(1/p_1,1/p_2 )$
for which we have boundedness for the associated bilinear multiplier operator
from $L^{p_1}(\mathbb R^{ n})\times L^{p_2} (\mathbb R^{ n})$ to $ L^p(\mathbb
R^{ n})$ when $1/p=1/p_1+1/p_2$, $1<p_1,p_2<\infty$.


title: On cubic symmetric non-Cayley graphs with solvable automorphism groups

abstract:
  It was proved in [Y.-Q. Feng, C. H. Li and J.-X. Zhou, Symmetric cubic graphs
with solvable automorphism groups, {\em European J. Combin.} {\bf 45} (2015),
1-11] that a cubic symmetric graph with a solvable automorphism group is either
a Cayley graph or a $2$-regular graph of type $2^2$, that is, a graph with no
automorphism of order $2$ interchanging two adjacent vertices. In this paper an
infinite family of non-Cayley cubic $2$-regular graphs of type $2^2$ with a
solvable automorphism group is constructed. The smallest graph in this family
has order 6174.


title: Conditional and unconditional Gaussian quantum dynamics

abstract:
  This article focuses on the general theory of open quantum systems in the
Gaussian regime and explores a number of diverse ramifications and consequences
of the theory. We shall first introduce the Gaussian framework in its full
generality, including a classification of Gaussian (also known as
"general-dyne") quantum measurements. In doing so, we will give a compact proof
for the parametrisation of the most general Gaussian completely positive map,
which we believe to be missing in the existing literature. We will then move on
to consider the linear coupling with a white noise bath, and derive the
diffusion equations that describe the evolution of Gaussian states under such
circumstances. Starting from these equations, we outline a constructive method
to derive general master equations that apply outside the Gaussian regime.
Next, we include the general-dyne monitoring of the environmental degrees of
freedom and recover the Riccati equation for the conditional evolution of
Gaussian states. Our derivation relies exclusively on the standard quantum
mechanical update of the system state, through the evaluation of Gaussian
overlaps. The parametrisation of the conditional dynamics we obtain is novel
and, at variance with existing alternatives, directly ties in to physical
detection schemes. We conclude our study with two examples of conditional
dynamics that can be dealt with conveniently through our formalism,
demonstrating how monitoring can suppress the noise in optical parametric
processes as well as stabilise systems subject to diffusive scattering.


title: The H\"ormander multiplier theorem I: The Linear Case

abstract:
  We discuss $L^p(\mathbb R^n)$ boundedness for Fourier multiplier operators
that satisfy the hypotheses of the H\"ormander multiplier theorem in terms of
an optimal condition that relates the distance $|\frac 1p-\frac12|$ to the
smoothness $s$ of the associated multiplier measured in some Sobolev norm. We
provide new counterexamples to justify the optimality of the condition $|\frac
1p-\frac12|<\frac sn$ and we discuss the endpoint case $|\frac
1p-\frac12|=\frac sn$.


title: The Aleksandrov-Bakelman-Pucci estimate and the Calabi-Yau equation

abstract:
  We give two applications of the Aleksandrov-Bakelman-Pucci estimate to the
Calabi-Yau equation on symplectic four-manifolds. The first is solvability of
the equation on the Kodaira-Thurston manifold for certain almost-Kahler
structures assuming $S^1$-invariance, extending a result of
Buzano-Fino-Vezzoni. The second is to reduce the general case of Donaldson's
conjecture to a bound on the measure of a superlevel set of a scalar function.


title: The H\"ormander multiplier theorem, II: The bilinear local $L^2$ case

abstract:
  We use wavelets of tensor product type to obtain the boundedness of bilinear
multiplier operators on $\mathbb R^n\times \mathbb R^n$ associated with
H\"ormander multipliers on $\mathbb R^{2n}$ with minimal smoothness. We focus
on the local $L^2$ case and we obtain boundedness under the minimal smoothness
assumption of $n/2$ derivatives. We also provide counterexamples to obtain
necessary conditions for all sets of indices.


title:
Beyond the Pearson correlation: heavy-tailed risks, weighted Gini
  correlations, and a Gini-type weighted insurance pricing model

abstract:
  Gini-type correlation coefficients have become increasingly important in a
variety of research areas, including economics, insurance and finance, where
modelling with heavy-tailed distributions is of pivotal importance. In such
situations, naturally, the classical Pearson correlation coefficient is of
little use. On the other hand, it has been observed that when light-tailed
situations are of interest, and hence when both the Gini-type and Pearson
correlation coefficients are well-defined and finite, then these coefficients
are related and sometimes even coincide. In general, understanding how the
correlation coefficients above are related has been an illusive task. In this
paper we put forward arguments that establish such a connection via certain
regression-type equations. This, in turn, allows us to introduce a Gini-type
Weighted Insurance Pricing Model that works in heavy-tailed situation and thus
provides a natural alternative to the classical Capital Asset Pricing Model. We
illustrate our theoretical considerations using several bivariate
distributions, such as elliptical and those with heavy-tailed Pareto margins.


title:
Beating level-set methods for 3D seismic data interpolation: a
  primal-dual alternating approach

abstract:
  Acquisition cost is a crucial bottleneck for seismic workflows, and low-rank
formulations for data interpolation allow practitioners to `fill in' data
volumes from critically subsampled data acquired in the field. Tremendous size
of seismic data volumes required for seismic processing remains a major
challenge for these techniques.
  We propose a new approach to solve residual constrained formulations for
interpolation. We represent the data volume using matrix factors, and build a
block-coordinate algorithm with constrained convex subproblems that are solved
with a primal-dual splitting scheme. The new approach is competitive with state
of the art level-set algorithms that interchange the role of objectives with
constraints. We use the new algorithm to successfully interpolate a large scale
5D seismic data volume, generated from the geologically complex synthetic 3D
Compass velocity model, where 80% of the data has been removed.


title:
Theoretical modelling of the AGN iron-line vs continuum time-lags in the
  lamp-post geometry

abstract:
  Context: Theoretical modelling of time-lags between variations in the Fe
K$\alpha$ emission and the X-ray continuum might shed light on the physics and
geometry of the X-ray emitting region in active galaxies (AGN) and X-ray
binaries. We here present the results from a systematic analysis of time-lags
between variations in two energy bands ($5-7$ vs $2-4\,\mathrm{keV}$) for seven
X-ray bright and variable AGN.
  Aims: We estimate time-lags as accurately as possible and fit them with
theoretical models in the context of the lamp-post geometry. We also constrain
the geometry of the X-ray emitting region in AGN.
  Methods: We used all available archival \textit{XMM-Newton} data for the
sources in our sample and extracted light curves in the $5-7$ and
$2-4\,\mathrm{keV}$ energy bands. We used these light curves and applied a
thoroughly tested (through extensive numerical simulations) recipe to estimate
time-lags that have minimal bias, approximately follow a Gaussian distribution,
and have known errors. Using traditional $\chi^2$ minimisation techniques, we
then fitted the observed time-lags with two different models: a
phenomenological model where the time-lags have a power-law dependence on
frequency, and a physical model, using the reverberation time-lags expected in
the lamp-post geometry. The latter were computed assuming a point-like primary
X-ray source above a black hole surrounded by a neutral and prograde accretion
disc with solar iron abundance. We took all relativistic effects into account
for various X-ray source heights, inclination angles, and black hole spin
values.


title:
A hybrid superconducting quantum dot acting as an efficient charge and
  spin Seebeck diode

abstract:
  We propose a highly efficient thermoelectric diode device built from the
coupling of a quantum dot with a normal or ferromagnetic electrode and a
superconducting reservoir. The current shows a strongly nonlinear behavior in
the forward direction (positive thermal gradients) while it almost vanishes in
the backward direction (negative thermal gradients). Our discussion is
supported by a gauge-invariant current-conserving transport theory accounting
for electron-electron interactions inside the dot. We find that the diode
behavior is greatly tuned with external gate potentials, Zeeman splittings or
lead magnetizations. Our results are thus relevant for the search of novel
thermoelectric devices with enhanced functionalities.


title: Finding merit in dividing neighbors

abstract:
  The IV-VI binary semiconductors and and column V elements crystalize in one
of the three varieties derived from the cubic rocksalt structure. The rocksalt
structure can be seen as a network of interpenetrating octahedra with an atom
at the center of each octahedron and its six nearest neighbors at the vertices.
What drives lower symmetry is the problem of placing ten electrons along three
perpendicular axes with six equivalent neighbors. Rhombohedral and orthorhombic
distortions divide the six immediate neighbors in two distinct sets of first
neighbors and second neighbors. This structural competition is at the origin of
the the remarkable thermoelectric figure of merit in SnSe and PbTe.


title: DDO 68: A flea with smaller fleas that on him prey

abstract:
  We present new photometry of the dwarf irregular galaxy DDO 68, one of the
most metal-poor and least massive dwarfs, located in the Lynx-Cancer Void. The
images were acquired with the Large Binocular Telescope in the g and r
passbands, and show unequivocally that DDO 68 has previously unknown stellar
streams related to the accretion of at least two smaller companions: a flea
with smaller fleas biting it, to put it in Jonathan Swift's words. Our data
provide direct observational evidence of multiple merging occurring at very low
galactic mass scales. We present the results of an N-body simulation of the
interaction of three dwarf galaxies which reproduces well the main
morphological features of DDO 68.


title:
Ensemble X-ray variability of Active Galactic Nuclei. II. Excess
  Variance and updated Structure Function

abstract:
  Most investigations of the X-ray variability of active galactic nuclei (AGN)
have been concentrated on the detailed analyses of individual, nearby sources.
A relatively small number of studies have treated the ensemble behaviour of the
more general AGN population in wider regions of the luminosity-redshift plane.
We want to determine the ensemble variability properties of a rich AGN sample,
called Multi-Epoch XMM Serendipitous AGN Sample (MEXSAS), extracted from the
fifth release of the XMM-Newton Serendipitous Source Catalogue (XMMSSC-DR5),
with redshift between 0.1 and 5, and X-ray luminosities in the 0.5-4.5 keV band
between 10^42 and 10^47 erg/s. We urge caution on the use of the normalised
excess variance (NXS), noting that it may lead to underestimate variability if
used improperly. We use the structure function (SF), updating our previous
analysis for a smaller sample. We propose a correction to the NXS variability
estimator, accounting for the light curve duration in the rest frame on the
basis of the knowledge of the variability behaviour gained by SF studies. We
find an ensemble increase of the X-ray variability with the rest-frame time lag
tau, given by tau^0.12. We confirm an inverse dependence on the X-ray
luminosity, approximately as L_X^-0.19. We analyse the SF in different X-ray
bands, finding a dependence of the variability on the frequency as nu^-0.15,
corresponding to a softer when brighter trend. In turn, this dependence allows
us to parametrically correct the variability estimated in observer-frame bands
to that in the rest frame, resulting in a moderate shift upwards
(V-correction). Ensemble X-ray variability of AGNs is best described by the
structure function. An improper use of the normalised excess variance may lead
to an underestimate of the intrinsic variability, so that appropriate
corrections to the data or the models must be applied to prevent these effects.


title: MAGIC: a general, powerful and tractable method for selective inference

abstract:
  Selective inference is a recent research topic that tries to perform valid
inference after using the data to select a reasonable statistical model. We
propose MAGIC, a new method for selective inference that is general, powerful
and tractable. MAGIC is a method for selective inference after solving a convex
optimization problem with smooth loss and $\ell_1$ penalty. Randomization is
incorporated into the optimization problem to boost statistical power. Through
reparametrization, MAGIC reduces the problem into a sampling problem with
simple constraints. MAGIC applies to many $\ell_1$ penalized optimization
problem including the Lasso, logistic Lasso and neighborhood selection in
graphical models, all of which we consider in this paper.


title:
Discrete Choice Models for Nonmonotone Nonignorable Missing Data:
  Identification and Inference

abstract:
  Nonmonotone missing data arise routinely in empirical studies of social and
health sciences, and when ignored, can induce selection bias and loss of
efficiency. In practice, it is common to account for nonresponse under a
missing-at-random assumption which although convenient, is rarely appropriate
when nonresponse is nonmonotone. Likelihood and Bayesian missing data
methodologies often require specification of a parametric model for the full
data law, thus a priori ruling out any prospect for semiparametric inference.
In this paper, we propose an all-purpose approach which delivers semiparametric
inferences when missing data are nonmonotone and not at random. The approach is
based on a discrete choice model (DCM) as a means to generate a large class of
nonmonotone nonresponse mechanisms that are nonignorable. Sufficient conditions
for nonparametric identification are given, and a general framework for fully
parametric and semiparametric inference under an arbitrary DCM is proposed.
Special consideration is given to the case of logit discrete choice nonresponse
model (LDCM) for which we describe generalizations of inverse-probability
weighting, pattern-mixture estimation, doubly robust estimation and multiply
robust estimation.


title:
Decentralized, Self-organizing, Potential field-based Control for
  Individuallymotivated, Mobile Agents in a Cluttered Environment: A
  Vector-Harmonic Potential Field Approach

abstract:
  Spatial multi-agency has been receiving growing attention from researchers
exploring many of the aspects and modalities of this phenomenon. The aim is to
develop the theoretical background needed for a multitude of applications
involving the sharing of resources by more than one agent. A traffic management
system is one of these applications. Here, a large group of mobile robots that
are operating in communication-limited, and sensory-limited modes are required
to cope with each others presence as well as the contents of their environment
while preserving their ability to reach their preset, independent goals. This
work explores the construction of a decentralized traffic controller for a
large group of agents sharing a workspace with stationary forbidden regions.
The suggested multi-agent motion controller is complete provided that a lenient
condition on the geometry of the workspace is upheld. It has a low
computational effort that linearly increases with the number of agents. The
controller is also self-organizing; therefore, it is able to deal, on its own,
with incomplete information and unexpected situations. In addition to the
above, the controller has an open structure to enable any agent to join or
leave the group without the remaining agents having to adjust the manner in
which they function. To meet these requirements, a definition of
decentralization is suggested. This definition equates decentralization to
self-organization in a group of agents operating in an artificial life mode.
The definition is used to provide guidelines for the construction of the
multi-agent controller. The controller is realized using the potential field
approach. Theoretical developments, as well as simulation results, are
provided.


title:
Bayesian inference for stochastic differential equation mixed effects
  models of a tumor xenography study

abstract:
  We consider Bayesian inference for stochastic differential equation mixed
effects models (SDEMEMs) exemplifying tumor response to treatment and regrowth
in mice. We produce an extensive study on how a SDEMEM can be fitted using both
exact inference based on pseudo-marginal MCMC and approximate inference via
Bayesian synthetic likelihoods (BSL). We investigate a two-compartments SDEMEM,
these corresponding to the fractions of tumor cells killed by and survived to a
treatment, respectively. Case study data considers a tumor xenography study
with two treatment groups and one control, each containing 5-8 mice. Results
from the case study and from simulations indicate that the SDEMEM is able to
reproduce the observed growth patterns and that BSL is a robust tool for
inference in SDEMEMs. Finally, we compare the fit of the SDEMEM to a similar
ordinary differential equation model. Due to small sample sizes, strong prior
information is needed to identify all model parameters in the SDEMEM and it
cannot be determined which of the two models is the better in terms of
predicting tumor growth curves. In a simulation study we find that with a
sample of 17 mice per group BSL is able to identify all model parameters and
distinguish treatment groups.


title:
New Finite Volume Method for rotating channel flows involving boundary
  layers

abstract:
  We investigate in this article the boundary layers appearing for a fluid
under moderate rotation when the viscosity is small. The fluid is modeled by
rotating type Stokes equations known also as the Barotropric mode equations in
the primitive equations theory. First we derive the correctors that describe
the sharp variations at large Reynolds number (i.e., small viscosity). Second,
thanks to a new finite volume method (NFVM) we give numerical solutions of the
rotating Stokes system at small viscosity. The NFVM can be applied to a large
class of singular perturbation problems.


title:
On the reality of broad iron L lines from the narrow line Seyfert 1
  galaxies 1H0707-495 and IRAS 13224-3809

abstract:
  We performed time resolved spectroscopy of 1H0707-495 and IRAS 13224-3809
using long XMM-Newton observations. These are strongly variable narrow line
Seyfert 1 galaxies and show broad features around 1 keV that has been
interpreted as relativistically broad Fe L$\alpha$ lines. Such features are not
clearly observed in other AGN despite sometimes having high iron abundance
required by the best fitted blurred reflection models. Given the importance of
these lines, we explore the possibility if rapid variability of spectral
parameters may introduce broad bumps/dips artificially in the time averaged
spectrum, which may then be mistaken as broadened lines. We tested this
hypothesis by performing time resolved spectroscopy using long (> 100 ks)
XMM-Newton observations and by dividing it into segments with typical exposure
of few ks. We extracted spectra from each such segment and modelled using a two
component phenomenological model consisting of a power law to represent hard
component and a black body to represent the soft emission. As expected both the
sources showed variations in the spectral parameters. Using these variation
trends, we simulated model spectra for each segment and then co-added to get a
combined simulated spectrum. In the simulated spectra, we found no broad
features below 1 keV and in particular no deviation near 0.9 keV as seen in the
real average spectra. This implies that the broad Fe L? line that is seen in
the spectra of these sources is not an artifact of the variation of spectral
components and hence providing evidence that the line is indeed genuine.


title:
On the differential geometry of numerical schemes and weak solutions of
  functional equations

abstract:
  We exhibit differential geometric structures that arise in numerical methods,
based on the construction of Cauchy sequences, that are currently used to prove
explicitly the existence of weak solutions to functional equations. We describe
the geometric framework, highlight several examples and describe how two
well-known proofs fit with our setting. The first one is a re-interpretation of
the classical proof of an implicit functions theorem in an ILB setting, for
which our setting enables us to state an implicit functions theorem without
additional norm estimates, and the second one is the finite element method of
the Dirichlet problem where the set of triangulations appear as a smooth set of
parameters. In both case, smooth dependence on the set of parameters is
established. Before that, we develop the necessary theoretical tools, namely
the notion of Cauchy diffeology on spaces of Cauchy sequences and a new
generalization of the notion of tangent space to a diffeological space.


title: Network Flows Under Thermal Restrictions

abstract:
  We define a \emph{thermal network}, which is a network where the flow
functionality of a node depends upon its temperature. This model is inspired by
several types of real-life networks, and generalizes some conventional network
models wherein nodes have fixed capacities and the problem is to maximize the
flow through the network. In a thermal network, the temperature of a node
increases as traffic moves through it, and nodes may also cool spontaneously
over time, or by employing cooling packets. We analyze the problems of
maximizing the flow from a source to a sink for both these cases, for a
holistic view with respect to the single-source-single-sink dynamic flow
problem in a thermal network. We have studied certain properties such a thermal
network exhibits, and give closed-form solutions for the maximum flow that can
be achieved through such a network.


title:
Observation of the decay B+ to psi(2S) phi(1020) K+ in pp collisions at
  sqrt(s) = 8 TeV

abstract:
  The decay B+ to psi(2S) phi(1020) K+ is observed for the first time using
data collected from pp collisions at sqrt(s) = 8 TeV by the CMS experiment at
the LHC, corresponding to an integrated luminosity of 19.6 inverse femtobarns.
The branching fraction of this decay is measured, using the mode B+ to psi(2S)
K+ as normalization, to be (4.0 +/- 0.4 (stat) +/- 0.6 (syst) +/- 0.2 (B)) x
E-6, where the third uncertainty is from the measured branching fraction of the
normalization channel.


title:
Analytic next-to-nearest neighbour XX models with perfect state transfer
  and fractional revival

abstract:
  Certain non-uniformly coupled spin chains can exhibit perfect transfer of
quantum states from end to end. Motivated by recent experimental
implementations, we extend the simplest such chain to next-to-nearest neighbour
(NNN) couplings. It is shown analytically that perfect state transfer can be
maintained under the extension and that end-to-end entanglement generation
(fractional revival) can occur.


title:
Three-Dimensional Imaging of Individual Point Defects Using Selective
  Detection Angles in Annular Dark Field Scanning Transmission Electron
  Microscopy

abstract:
  We propose a new scanning transmission electron microscopy (STEM) technique
that can realize the three-dimensional (3D) characterization of vacancies,
lighter and heavier dopants with high precision. Using multislice STEM imaging
and diffraction simulations of beta-Ga2O3 and SrTiO3, we show that selecting a
small range of low scattering angles can make the contrast of the
defect-containing atomic columns substantially more depth-dependent. The origin
of the depth-dependence is the de-channeling of electrons due to the existence
of a point defect in the atomic column, which creates extra ripples at low
scattering angles. We show that, by capturing the de-channeling signal with
narrowly selected annular dark field angles (e.g. 20-40 mrad), the contrast of
a column containing a point defect in the image can be significantly enhanced.
The effect of sample thickness, crystal orientation, probe convergence angle,
and experimental uncertainty will also be discussed. Our new technique can
therefore create new opportunities for highly precise 3D structural
characterization of individual point defects in functional materials.


title: Randomised Relevance Model

abstract:
  Relevance Models are well-known retrieval models and capable of producing
competitive results. However, because they use query expansion they can be very
slow. We address this slowness by incorporating two variants of locality
sensitive hashing (LSH) into the query expansion process. Results on two
document collections suggest that we can obtain large reductions in the amount
of work, with a small reduction in effectiveness. Our approach is shown to be
additive when pruning query terms.


title:
SANA: Simulated Annealing Network Alignment Applied to Biological
  Networks

abstract:
  The alignment of biological networks has the potential to teach us as much
about biology and disease as has sequence alignment. Sequence alignment can be
optimally solved in polynomial time. In contrast, network alignment is
$NP$-hard, meaning optimal solutions are impossible to find, and the quality of
found alignments depend strongly upon the algorithm used to create them. Every
network alignment algorithm consists of two orthogonal components: first, an
objective function or measure $M$ that is used to evaluate the quality of any
proposed alignment, and second, a search algorithm used to explore the
exponentially large set of possible alignments in an effort to find "good" ones
according to $M$. Objective functions fall into many categories, including
biological measures such as sequence similarity, as well as topological
measures like graphlet similarity and edge coverage (possibly weighted).
Algorithms to search the space of all possible alignments can be deterministic
or stochastic, and many possibilities have been offered over the past decade.
In this paper we introduce a new stochastic search algorithm called SANA:
Simulated Annealing Network Aligner. We test it on several popular objective
functions and demonstrate that it almost universally optimizes each one
significantly better than existing search algorithms. Finally, we compare
several topological objective functions using SANA. Software available at
http://sana.ics.uci.edu.


title: Hierarchical Deep Temporal Models for Group Activity Recognition

abstract:
  In this paper we present an approach for classifying the activity performed
by a group of people in a video sequence. This problem of group activity
recognition can be addressed by examining individual person actions and their
relations. Temporal dynamics exist both at the level of individual person
actions as well as at the level of group activity. Given a video sequence as
input, methods can be developed to capture these dynamics at both person-level
and group-level detail. We build a deep model to capture these dynamics based
on LSTM (long short-term memory) models. In order to model both person-level
and group-level dynamics, we present a 2-stage deep temporal model for the
group activity recognition problem. In our approach, one LSTM model is designed
to represent action dynamics of individual people in a video sequence and
another LSTM model is designed to aggregate person-level information for group
activity recognition. We collected a new dataset consisting of volleyball
videos labeled with individual and group activities in order to evaluate our
method. Experimental results on this new Volleyball Dataset and the standard
benchmark Collective Activity Dataset demonstrate the efficacy of the proposed
models.


title: Continuous $\times p,\times q$-invariant measures on the unit circle

abstract:
  We express continuous $\times p,\times q$-invariant measures on the unit
circle via some simple forms. On one hand, a continuous $\times p,\times
q$-invariant measure is the weak-$*$ limit of average of Dirac measures along
an irrational orbit. On the other hand, a continuous $\times p,\times
q$-invariant measure is a continuous function on $[0,1]$ satisfying certain
function equations.


title: Intrinsic unpredictability of strong El Ni\~no events

abstract:
  The El Ni\~no-Southern Oscillation (ENSO) is a mode of interannual
variability in the coupled equatorial ocean/atmosphere Pacific. El Ni\~no
describes a state in which sea surface temperatures in the eastern Pacific
increase and upwelling of colder, deep waters diminishes. El Ni\~no events
typically peak in boreal winter, but their strength varies irregularly on
decadal time scales. There were exceptionally strong El Ni\~no events in
1982-83, 1997-98 and 2015-16 that affected weather on a global scale. Widely
publicized forecasts in 2014 predicted that the 2015-16 event would occur a
year earlier. Predicting the strength of El Ni\~no is a matter of practical
concern due to its effects on hydroclimate and agriculture around the world.
This paper presents a new robust mechanism limiting the predictability of
strong ENSO events: the existence of an irregular switching between an
oscillatory state that has strong El Ni\~no events and a chaotic state that
lacks strong events, which can be induced by very weak seasonal forcing or
noise.


title: High-Level Programming Abstractions for Distributed Graph Processing

abstract:
  Efficient processing of large-scale graphs in distributed environments has
been an increasingly popular topic of research in recent years. Inter-connected
data that can be modeled as graphs arise in application domains such as machine
learning, recommendation, web search, and social network analysis. Writing
distributed graph applications is inherently hard and requires programming
models that can cover a diverse set of problem domains, including iterative
refinement algorithms, graph transformations, graph aggregations, pattern
matching, ego-network analysis, and graph traversals. Several high-level
programming abstractions have been proposed and adopted by distributed graph
processing systems and big data platforms. Even though significant work has
been done to experimentally compare distributed graph processing frameworks, no
qualitative study and comparison of graph programming abstractions has been
conducted yet. In this survey, we review and analyze the most prevalent
high-level programming models for distributed graph processing, in terms of
their semantics and applicability. We identify the classes of graph
applications that can be naturally expressed by each abstraction and we also
give examples of applications that are hard or impossible to express. We review
34 distributed graph processing systems with respect to their programming
abstractions, execution models, and communication mechanisms. Finally, we
discuss trends and open research questions in the area of distributed graph
processing.


title: Fluid transport and mixing by an unsteady microswimmer

abstract:
  We study the fluid drift due to a time-dependent dumbbell model of a
microswimmer. The model captures important aspects of real microswimmers such
as a time-dependent flagellar motion and a no-slip body. The model consists of
a rigid sphere for the body and a time-dependent moving Stokeslet representing
the flagella. We analyze the paths of idealized fluid particles displaced by
the swimmer. The simplicity of the model allows some asymptotic calculations
very near and far away from the swimmer. The displacements of particles near
the swimmer diverge in a manner similar to an isolated no-slip sphere, but with
a smaller coefficient due to the action of the flagellum. Far from the swimmer,
the time dependence becomes negligible due to both being very fast and decaying
with distance. Finally, we compute the probability distribution of particle
displacements, and find that our model has fatter tails than previous steady
models, due to the presence of a no-slip surface that drags particles along.


title: Active dry granular flows: rheology and rigidity transitions

abstract:
  The constitutive relations of a dense granular flow composed of
self-propelling frictional hard particles are investigated by means of DEM
numerical simulations. We show that the rheology, which relates the dynamical
friction $\mu$ and the volume fraction $\phi$ to the inertial number $I$,
depends on a dimensionless number $\mathcal{A}$, which compares the active
force to the confining pressure. Two liquid/solid transitions -- in the Maxwell
rigidity sense -- are observed. As soon as the activity is turned on, the
packing becomes an `active solid' with a mean number of particle contacts
larger than the isostatic value. The quasi-static values of $\mu$ and $\phi$
decrease with $\mathcal{A}$. At a finite value of the activity $\mathcal{A}_t$,
corresponding to the isostatic condition, a second `active rigidity transition'
is observed beyond which the quasi-static values of the friction vanishes and
the rheology becomes Newtonian. For $\mathcal{A}>\mathcal{A}_t$, we provide
evidence for a highly intermittent dynamics of this 'active fluid'.


title:
Linear signal recovery from $b$-bit-quantized linear measurements:
  precise analysis of the trade-off between bit depth and number of
  measurements

abstract:
  We consider the problem of recovering a high-dimensional structured signal
from independent Gaussian linear measurements each of which is quantized to $b$
bits. Our interest is in linear approaches to signal recovery, where "linear"
means that non-linearity resulting from quantization is ignored and the
observations are treated as if they arose from a linear measurement model.
Specifically, the focus is on a generalization of a method for one-bit
observations due to Plan and Vershynin [\emph{IEEE~Trans. Inform. Theory,
\textbf{59} (2013), 482--494}]. At the heart of the present paper is a precise
characterization of the optimal trade-off between the number of measurements
$m$ and the bit depth per measurement $b$ given a total budget of $B = m \cdot
b$ bits when the goal is to minimize the $\ell_2$-error in estimating the
signal. It turns out that the choice $b = 1$ is optimal for estimating the unit
vector (direction) corresponding to the signal for any level of additive
Gaussian noise before quantization as well as for a specific model of
adversarial noise, while the choice $b = 2$ is optimal for estimating the
direction and the norm (scale) of the signal. Moreover, Lloyd-Max quantization
is shown to be an optimal quantization scheme w.r.t. $\ell_2$-estimation error.
Our analysis is corroborated by numerical experiments showing nearly perfect
agreement with our theoretical predictions. The paper is complemented by an
empirical comparison to alternative methods of signal recovery taking the
non-linearity resulting from quantization into account. The results of that
comparison point to a regime change depending on the noise level: in a
low-noise setting, linear signal recovery falls short of more sophisticated
competitors while being competitive in moderate- and high-noise settings.


title:
Ab-initio tensorial electronic friction for molecules on metal surfaces:
  nonadiabatic vibrational relaxation

abstract:
  Molecular adsorbates on metal surfaces exchange energy with substrate phonons
and low-lying electron-hole pair excitations. In the limit of weak coupling,
electron-hole pair excitations can be seen as exerting frictional forces on
adsorbates that enhance energy transfer and facilitate vibrational relaxation
or hot-electron mediated chemistry. We have recently reported on the relevance
of tensorial properties of electronic friction [Phys. Rev. Lett. 116, 217601
(2016)] in dynamics at surfaces. Here we present the underlying implementation
of tensorial electronic friction based on Kohn-Sham Density Functional Theory
for condensed phase and cluster systems. Using local atomic-orbital basis sets,
we calculate nonadiabatic coupling matrix elements and evaluate the full
electronic friction tensor in the classical limit. Our approach is numerically
stable and robust as shown by a detailed convergence analysis. We furthermore
benchmark the accuracy of our approach by calculation of vibrational relaxation
rates and lifetimes for a number of diatomic molecules at metal surfaces. We
find friction-induced mode-coupling between neighboring CO adsorbates on
Cu(100) in a c(2x2) overlayer to be important to understand experimental
findings.


title:
Electrical spin injection into graphene from a topological insulator in
  a van der Waals heterostructure

abstract:
  All-electrical (magnetic-material-free) spin injection is one of the
outstanding goals in spintronics. Topological insulators (TIs) have been
recognized as a promising electrically controlled spin source thanks to the
strong spin-orbit coupling and in particular, the spin-momentum locked
topological surface states (TSS) supporting helically spin polarized currents.
Many TI materials such as Bi-based chalcogenides are also layered 2D materials
and can be incorporated into van der Waals (vdW) coupled heterostructures,
opening the possibility of the utilization of TIs for electrical spin injection
into other 2D materials. Here, we demonstrate electrical injection of helically
spin-polarized current into graphene through a 3D TI in a mechanically stacked
heterostructure between Bi2Te2Se (a TI) and chemical vapor deposition
(CVD)-grown graphene, using the spin potentiometric measurement. When a dc
current is flowing from the TI to graphene, we detect a striking step-like
voltage change (spin signal) in both the TI and graphene using ferromagnetic
(FM) probes. The sign of the spin signal can be reversed by reversing the
direction of the dc bias current, and the corresponding amplitude of the spin
signal increases linearly with the bias current, indicative of a
current-induced helical spin polarization in both TI and graphene. In contrast,
the graphene itself exhibits usual nonlocal spin valve signal when the spins
are injected using an FM electrode. We discuss possible origins of the helical
spin polarization injected into the graphene in our TI/graphene heterostructure
that may include TSS as well as the spin-orbit coupled Rashba states. Our
findings show electrical injection of a spin helical current into graphene
through a TI and demonstrate TIs as potential spin sources for future
spintronic devices wherein spin manipulation is achieved electrically.


title: Multimodal Affect Recognition using Kinect

abstract:
  Affect (emotion) recognition has gained significant attention from
researchers in the past decade. Emotion-aware computer systems and devices have
many applications ranging from interactive robots, intelligent online tutor to
emotion based navigation assistant. In this research data from multiple
modalities such as face, head, hand, body and speech was utilized for affect
recognition. The research used color and depth sensing device such as Kinect
for facial feature extraction and tracking human body joints. Temporal features
across multiple frames were used for affect recognition. Event driven decision
level fusion was used to combine the results from each individual modality
using majority voting to recognize the emotions. The study also implemented
affect recognition by matching the features to the rule based emotion templates
per modality. Experiments showed that multimodal affect recognition rates using
combination of emotion templates and supervised learning were better compared
to recognition rates based on supervised learning alone. Recognition rates
obtained using temporal feature were higher compared to recognition rates
obtained using position based features only.


title: Estimation of KL Divergence: Optimal Minimax Rate

abstract:
  The problem of estimating the Kullback-Leibler divergence $D(P\|Q)$ between
two unknown distributions $P$ and $Q$ is studied, under the assumption that the
alphabet size $k$ of the distributions can scale to infinity. The estimation is
based on $m$ independent samples drawn from $P$ and $n$ independent samples
drawn from $Q$. It is first shown that there does not exist any consistent
estimator that guarantees asymptotically small worst-case quadratic risk over
the set of all pairs of distributions. A restricted set that contains pairs of
distributions, with density ratio bounded by a function $f(k)$ is further
considered. {An augmented plug-in estimator is proposed, and its worst-case
quadratic risk is shown to be within a constant factor of
$(\frac{k}{m}+\frac{kf(k)}{n})^2+\frac{\log ^2 f(k)}{m}+\frac{f(k)}{n}$, if $m$
and $n$ exceed a constant factor of $k$ and $kf(k)$, respectively.} Moreover,
the minimax quadratic risk is characterized to be within a constant factor of
$(\frac{k}{m\log k}+\frac{kf(k)}{n\log k})^2+\frac{\log ^2
f(k)}{m}+\frac{f(k)}{n}$, if $m$ and $n$ exceed a constant factor of
$k/\log(k)$ and $kf(k)/\log k$, respectively. The lower bound on the minimax
quadratic risk is characterized by employing a generalized Le Cam's method. A
minimax optimal estimator is then constructed by employing both the polynomial
approximation and the plug-in approaches.


title:
Combining multiple resolutions into hierarchical representations for
  kernel-based image classification

abstract:
  Geographic object-based image analysis (GEOBIA) framework has gained
increasing interest recently. Following this popular paradigm, we propose a
novel multiscale classification approach operating on a hierarchical image
representation built from two images at different resolutions. They capture the
same scene with different sensors and are naturally fused together through the
hierarchical representation, where coarser levels are built from a Low Spatial
Resolution (LSR) or Medium Spatial Resolution (MSR) image while finer levels
are generated from a High Spatial Resolution (HSR) or Very High Spatial
Resolution (VHSR) image. Such a representation allows one to benefit from the
context information thanks to the coarser levels, and subregions spatial
arrangement information thanks to the finer levels. Two dedicated structured
kernels are then used to perform machine learning directly on the constructed
hierarchical representation. This strategy overcomes the limits of conventional
GEOBIA classification procedures that can handle only one or very few
pre-selected scales. Experiments run on an urban classification task show that
the proposed approach can highly improve the classification accuracy w.r.t.
conventional approaches working on a single scale.


title:
Scalable Bayesian modeling, monitoring and analysis of dynamic network
  flow data

abstract:
  Traffic flow count data in networks arise in many applications, such as
automobile or aviation transportation, certain directed social network
contexts, and Internet studies. Using an example of Internet browser traffic
flow through site-segments of an international news website, we present
Bayesian analyses of two linked classes of models which, in tandem, allow fast,
scalable and interpretable Bayesian inference. We first develop flexible
state-space models for streaming count data, able to adaptively characterize
and quantify network dynamics efficiently in real-time. We then use these
models as emulators of more structured, time-varying gravity models that allow
formal dissection of network dynamics. This yields interpretable inferences on
traffic flow characteristics, and on dynamics in interactions among network
nodes. Bayesian monitoring theory defines a strategy for sequential model
assessment and adaptation in cases when network flow data deviates from
model-based predictions. Exploratory and sequential monitoring analyses of
evolving traffic on a network of web site-segments in e-commerce demonstrate
the utility of this coupled Bayesian emulation approach to analysis of
streaming network count data.


title:
Detection System for Neutron $\beta$ Decay Correlations in the UCNB and
  Nab experiments

abstract:
  We describe a detection system designed for precise measurements of angular
correlations in neutron $\beta$ decay. The system is based on thick, large
area, highly segmented silicon detectors developed in collaboration with Micron
Semiconductor, Ltd. The prototype system meets specifications for $\beta$
electron detection with energy thresholds below 10 keV, energy resolution of
$\sim$3 keV FWHM, and rise time of $\sim$50 ns with 19 of the 127 detector
pixels instrumented. Using ultracold neutrons at the Los Alamos Neutron Science
Center, we have demonstrated the coincident detection of $\beta$ particles and
recoil protons from neutron $\beta$ decay. The fully instrumented detection
system will be implemented in the UCNB and Nab experiments, to determine the
neutron $\beta$ decay parameters $B$, $a$, and $b$.