title: {\Delta}{\mu} Binaries among Stars with Large Proper Motions

abstract:
  Based on observations performed with the Pulkovo normal astrograph in
2008-2015 and data from sky surveys (DSS, 2MASS, SDSS DR12, WISE), we have
investigated the motions of 1308 stars with proper motions larger than 300
mas/yr down to magnitude 17. The main idea of our search for binary stars based
on this material is reduced to comparing the quasi-mean (POSS2-POSS1; an epoch
difference of $\approx$50 yr) and quasi-instantaneous (2MASS, SDSS, WISE,
Pulkovo; an epoch difference of $\approx$10 yr) proper motions. If the
difference is statistically significant compared to the proper motion errors,
then the object may be considered as a {\Delta}{\mu}-binary candidate. One
hundred and twenty one stars from among those included in the observational
program satisfy this requirement. Additional confirmations of binarity for a
number of stars have been obtained by comparing the calculated proper motions
with the data from several programs of stellar trigonometric parallax
determinations and by analyzing the asymmetry of stellar images on sky-survey
CCD frames. Analysis of the highly accurate SDSS photometric data for four
stars (J0656+3827, J0838+3940, J1229+5332, J2330+4639) allows us to reach a
conclusion about the probability that these {\Delta}{\mu} binaries are white
dwarf + M dwarf pairs.


title: Evaluation of explicit and implicit LES closures for Burgers turbulence

abstract:
  In this work, we perform an aposteriori error analysis on implicit and
explicit large eddy simulation closure models for solving the Burgers
turbulence problem. Our closure modeling efforts include both functional and
structural models equipped with various low-pass filters. We introduce discrete
binomial smoothing filters and an enhanced version of the Van Cittert algorithm
to accelerate the convergence of approximate deconvolution processes including
regularization and relaxation filtering approaches. Our implicit modeling
efforts consist of various high-order schemes including compact and non-compact
fifth-order upwind schemes as well as weighted essential non-oscillatory (WENO)
and compact reconstructed WENO (CRWENO) schemes, and the resulting schemes are
shown to effectively converge to the direct numerical simulation (DNS) for
increasing resolutions. Comparing with DNS and underresolved DNS computations,
our numerical assessments illustrate the ability of these methods to capture
the energy content near grid cut-off scale.


title:
Petrov-Galerkin and Spectral Collocation Methods for distributed Order
  Differential Equations

abstract:
  Distributed order fractional operators offer a rigorous tool for mathematical
modelling of multi-physics phenomena, where the differential orders are
distributed over a range of values rather than being just a fixed
integer/fraction as it is in standard/fractional ODEs/PDEs. We develop two
spectrally-accurate schemes, namely a Petrov-Galerkin spectral method and a
spectral collocation method for distributed order fractional differential
equations. These schemes are developed based on the fractional Sturm-Liouville
eigen-problems (FSLPs). In the Petrov-Galerkin method, we employ fractional
(non-polynomial) basis functions, called \textit{Jacobi poly-fractonomials},
which are the eigenfunctions of the FSLP of first kind, while, we employ
another space of test functions as the span of poly-fractonomial eigenfunctions
of the FSLP of second kind. We define the underlying \textit{distributed
Sobolev space} and the associated norms, where we carry out the corresponding
discrete stability and error analyses of the proposed scheme. In the
collocation scheme, we employ fractional (non-polynomial) Lagrange interpolants
satisfying the Kronecker delta property at the collocation points.
Subsequently, we obtain the corresponding distributed differentiation matrices
to be employed in the discretization of the strong problem. We perform
systematic numerical tests to demonstrate the efficiency and conditioning of
each method.


title: Robustness of Leader-Follower Networked Dynamical Systems

abstract:
  We present a graph-theoretic approach to analyzing the robustness of
leader-follower consensus dynamics to disturbances and time delays. Robustness
to disturbances is captured via the system $\mathcal{H}_2$ and
$\mathcal{H}_{\infty}$ norms and robustness to time delay is defined as the
maximum allowable delay for the system to remain asymptotically stable. Our
analysis is built on understanding certain spectral properties of the grounded
Laplacian matrix that play a key role in such dynamics. Specifically, we give
graph-theoretic bounds on the extreme eigenvalues of the grounded Laplacian
matrix which quantify the impact of disturbances and time-delays on the
leader-follower dynamics. We then provide tight characterizations of these
robustness metrics in Erdos-Renyi random graphs and random regular graphs.
Finally, we view robustness to disturbances and time delay as network
centrality metrics, and provide conditions under which a leader in a network
optimizes each robustness objective. Furthermore, we propose a sufficient
condition under which a single leader optimizes both robustness objectives
simultaneously.


title: Dynamical model of the kinesin protein motor

abstract:
  We model and simulate the stepping dynamics of the kinesin motor including
electric and mechanical forces, environmental noise, and the complicated
potentials produced by tracking and neighboring protofilaments. Our dynamical
model supports the hand-over-hand mechanism of the kinesin stepping. Our
theoretical predictions and numerical simulations include the off-axis
displacements of the kinesin heads while the steps are performed. The results
obtained are in a good agreement with recent experiments on the kinesin
dynamics.


title: How to resum perturbative series in 3d N=2 Chern-Simons matter theories

abstract:
  Continuing the work arXiv:1603.06207, we study perturbative series in general
3d $\mathcal{N}=2$ supersymmetric Chern-Simons matter theory with $U(1)_R$
symmetry, which is given by a power series expansion of inverse Chern-Simons
levels. We find that the perturbative series are usually non-Borel summable
along positive real axis for various observables. Alternatively we prove that
the perturbative series are always Borel summable along negative (positive)
imaginary axis for positive (negative) Chern-Simons levels. It turns out that
the Borel resummations along this direction are the same as exact results and
therefore correct ways of resumming the perturbative series.


title:
Bayesian Genome- and Epigenome-wide Association Studies with Gene Level
  Dependence

abstract:
  High-throughput genetic and epigenetic data are often screened for
associations with an observed phenotype. For example, one may wish to test
hundreds of thousands of genetic variants, or DNA methylation sites, for an
association with disease status. These genomic variables can naturally be
grouped by the gene they encode, among other criteria. However, standard
practice in such applications is independent screening with a universal
correction for multiplicity. We propose a Bayesian approach in which the prior
probability of an association for a given genomic variable depends on its gene,
and the gene-specific probabilities are modeled nonparametrically. This
hierarchical model allows for appropriate gene and genome-wide multiplicity
adjustments, and can be incorporated into a variety of Bayesian association
screening methodologies with negligible increase in computational complexity.
We describe an application to screening for differences in DNA methylation
between lower grade glioma and glioblastoma multiforme tumor samples from The
Cancer Genome Atlas. Software is available via the package BayesianScreening
for R at https://github.com/lockEF/BayesianScreening .


title: Five-term relation and Macdonald polynomials

abstract:
  The non-commutative five-term relation $T_{1,0} T_{0,1} = T_{0,1} T_{1,1}
T_{1,0}$ is shown to hold for certain operators acting on symmetric functions.
The "generalized recursion" conjecture of Bergeron and Haiman is a corollary of
this result.


title: A bilayer Double Semion Model with Symmetry-Enriched Topological Order

abstract:
  We construct a new model of two-dimensional quantum spin systems that
combines intrinsic topo- logical orders and a global symmetry called flavour
symmetry. It is referred as the bilayer Doubled Semion model (bDS) and is an
instance of symmetry-enriched topological order. A honeycomb bi- layer lattice
is introduced to combine a Double Semion Topolgical Order with a global
spin-flavour symmetry to get the fractionalization of its quasiparticles. The
bDS model exhibits non-trival braid- ing self-statistics of excitations and its
dual model constitutes a Symmetry-Protected Topological Order with novel edge
states. This dual model gives rise to a bilayer Non-Trivial Paramagnet that is
invariant under the flavour symmetry and the well-known spin flip symmetry.


title: On the Erdos-Szekeres convex polygon problem

abstract:
  Let $ES(n)$ be the smallest integer such that any set of $ES(n)$ points in
the plane in general position contains $n$ points in convex position. In their
seminal 1935 paper, Erdos and Szekeres showed that $ES(n) \leq {2n - 4\choose
n-2} + 1 = 4^{n -o(n)}$. In 1960, they showed that $ES(n) \geq 2^{n-2} + 1$ and
conjectured this to be optimal. In this paper, we nearly settle the
Erdos-Szekeres conjecture by showing that $ES(n) =2^{n +o(n)}$.


title: Dependence between External Path-Length and Size in Random Tries

abstract:
  We study the size and the external path length of random tries and show that
they are asymptotically independent in the asymmetric case but strongly
dependent with small periodic fluctuations in the symmetric case. Such an
unexpected behavior is in sharp contrast to the previously known results that
the internal path length is totally positively correlated to the size and that
both tend to the same normal limit law. These two examples provide concrete
instances of bivariate normal distributions (as limit laws) whose correlation
is $0$, $1$ and periodically oscillating.


title: Spin Seebeck effect through antiferromagnetic NiO

abstract:
  We report temperature-dependent spin-Seebeck measurements on Pt/YIG bilayers
and Pt/NiO/YIG trilayers, where YIG (Yttrium iron garnet, Y$_3$Fe$_5$O$_{12}$)
is an insulating ferrimagnet and NiO is an antiferromagnet at low temperatures.
The thickness of the NiO layer is varied from 0 to 10 nm. In the Pt/YIG
bilayers, the temperature gradient applied to the YIG stimulates dynamic spin
injection into the Pt, which generates an inverse spin Hall voltage in the Pt.
The presence of a NiO layer dampens the spin injection exponentially with a
decay length of $2 \pm 0.6$ nm at 180 K. The decay length increases with
temperature and shows a maximum of $5.5 \pm 0.8$ nm at 360 K. The temperature
dependence of the amplitude of the spin-Seebeck signal without NiO shows a
broad maximum of $6.5 \pm 0.5$ $\mu$V/K at 20 K. In the presence of NiO, the
maximum shifts sharply to higher temperatures, likely correlated to the
increase in decay length. This implies that NiO is most transparent to magnon
propagation near the paramagnet-antiferromagnet transition. We do not see the
enhancement in spin current driven into Pt reported in other papers when 1-2 nm
NiO layers are sandwiched between Pt and YIG.


title: Crowd Counting via Weighted VLAD on Dense Attribute Feature Maps

abstract:
  Crowd counting is an important task in computer vision, which has many
applications in video surveillance. Although the regression-based framework has
achieved great improvements for crowd counting, how to improve the
discriminative power of image representation is still an open problem.
Conventional holistic features used in crowd counting often fail to capture
semantic attributes and spatial cues of the image. In this paper, we propose
integrating semantic information into learning locality-aware feature sets for
accurate crowd counting. First, with the help of convolutional neural network
(CNN), the original pixel space is mapped onto a dense attribute feature map,
where each dimension of the pixel-wise feature indicates the probabilistic
strength of a certain semantic class. Then, locality-aware features (LAF) built
on the idea of spatial pyramids on neighboring patches are proposed to explore
more spatial context and local information. Finally, the traditional VLAD
encoding method is extended to a more generalized form in which diverse
coefficient weights are taken into consideration. Experimental results validate
the effectiveness of our presented method.


title: Asymptotic structure and coarse Lipschitz geometry of Banach spaces

abstract:
  In this paper, we study the coarse Lipschitz geometry of Banach spaces with
several asymptotic properties. Specifically, we look at asymptotically
uniformly smoothness and convexity, and several distinct Banach-Saks-like
properties. Among other results, we characterize the Banach spaces which are
either coarsely or uniformly homeomorphic to $T^{p_1}\oplus \ldots \oplus
T^{p_n}$, where each $T^{p_j}$ denotes the $p_j$-convexification of the
Tsirelson space, for $p_1,\ldots,p_n\in (1,\ldots, \infty)$, and
$2\not\in\{p_1,\ldots ,p_n\}$. We obtain applications to the coarse Lipschitz
geometry of the $p$-convexifications of the Schlumprecht space, and some
hereditarily indecomposable Banach spaces. We also obtain some new results on
the linear theory of Banach spaces.


title:
Triangulated endofunctors of the derived category of coherent sheaves
  which do not admit DG liftings

abstract:
  Recently, Rizzardo and Van den Bergh constructed an example of a triangulated
functor between the derived categories of coherent sheaves on smooth projective
varieties over a field $k$ of characteristic $0$ which is not of the
Fourier-Mukai type. The purpose of this note is to show that if $char \, k =p$
then there are very simple examples of such functors. Namely, for a smooth
projective $Y$ over $\mathbb Z_p$ with the special fiber $i: X\hookrightarrow
Y$, we consider the functor $L i^* \circ i_*: D^b(X) \to D^b(X)$ from the
derived categories of coherent sheaves on $X$ to itself. We show that if $Y$ is
a flag variety which is not isomorphic to $\mathbb P^1$ then $L i^* \circ i_*$
is not of the Fourier-Mukai type. Note that by a theorem of Toen (\cite{t},
Theorem 8.15) the latter assertion is equivalent to saying that $L i^* \circ
i_*$ does not admit a lifting to a $\mathbb F_p$-linear DG quasi-functor
$D^b_{dg}(X) \to D^b_{dg}(X)$, where $D^b_{dg}(X)$ is a (unique) DG enhancement
of $D^b(X)$. However, essentially by definition, $L i^* \circ i_*$ lifts to a
$\mathbb Z_p$-linear DG quasi-functor.


title: Relative controllability of linear difference equations

abstract:
  In this paper, we study the relative controllability of linear difference
equations with multiple delays in the state by using a suitable formula for the
solutions of such systems in terms of their initial conditions, their control
inputs, and some matrix-valued coefficients obtained recursively from the
matrices defining the system. Thanks to such formula, we characterize relative
controllability in time $T$ in terms of an algebraic property of the
matrix-valued coefficients, which reduces to the usual Kalman controllability
criterion in the case of a single delay. Relative controllability is studied
for solutions in the set of all functions and in the function spaces $L^p$ and
$\mathcal C^k$. We also compare the relative controllability of the system for
different delays in terms of their rational dependence structure, proving that
relative controllability for some delays implies relative controllability for
all delays that are "less rationally dependent" than the original ones, in a
sense that we make precise. Finally, we provide an upper bound on the minimal
controllability time for a system depending only on its dimension and on its
largest delay.


title: Semiclassical approach to Dynamics of Interacting Fermions

abstract:
  Understanding the behavior of interacting fermions is of fundamental interest
in many fields ranging from condensed matter to high energy physics. Developing
numerically efficient and accurate simulation methods is an indispensable part
of this. Already in equilibrium, fermions are notoriously hard to handle due to
the sign problem. Out of equilibrium, an important outstanding problem is the
efficient numerical simulation of the dynamics of these systems. In this work
we develop a new semiclassical phase-space approach (a.k.a. the truncated
Wigner approximation) for simulating the dynamics of interacting fermions in
arbitrary dimensions. As fermions are essentially non-classical objects, a
phase-space is constructed out of all fermionic bilinears. Classical
phase-space is thus comprised of highly non-local (hidden) variables
representing these bilinears, and the cost of the method is that it scales
quadratic rather than linear with system size. We demonstrate the strength of
the method by comparing the results to the exact quantum dynamics of fermion
expansion in the Hubbard model and quantum thermalization in the
Sachdev-Ye-Kitaev (SYK) model for small systems, where the semiclassics nearly
perfectly reproduces correct results. We furthermore analyze fermion expansion
in a larger, intractable by exact methods, 2D Hubbard model, which is directly
relevant to recent cold atom experiments.


title:
Connecting the UMEB in $\mathbb{C}^{d}\bigotimes\mathbb{C}^{d}$ with
  partial Hadamard matrices

abstract:
  We study the unextendible maximally entangled bases (UMEB) in
$\mathbb{C}^{d}\bigotimes\mathbb{C}^{d}$ and connect it with the partial
Hadamard matrix. Firstly, we show that for a given special UMEB in
$\mathbb{C}^{d}\bigotimes\mathbb{C}^{d}$, there is a partial Hadamard matrix
can not extend to a complete Hadamard matrix in $\mathbb{C}^{d}$. As a
corollary, any $(d-1)\times d$ partial Hadamard matrix can extend to a complete
Hadamard matrix. Then we obtain that for any $d$ there is an UMEB except $d=p\
\text{or}\ 2p$, where $p\equiv 3\mod 4$ and $p$ is a prime. Finally, we argue
that there exist different kinds of constructions of UMEB in
$\mathbb{C}^{nd}\bigotimes\mathbb{C}^{nd}$ for any $n\in \mathbb{N}$ and
$d=3\times5 \times7$.


title: On the twisted quadratic moment for Dirichlet L-functions

abstract:
  Given $c,$ a positive integer, we give an explicit formula and an asymptotic
formula for \[ \sum\chi(c)|L(1,\,\chi)|^{2}, \] where $\chi$ is the non-trivial
Dirichlet character mod $f$ with $f>c.$


title:
A Bio-Inspired Tensegrity Manipulator with Multi-DOF, Structurally
  Compliant Joints

abstract:
  Most traditional robotic mechanisms feature inelastic joints that are unable
to robustly handle large deformations and off-axis moments. As a result, the
applied loads are transferred rigidly throughout the entire structure. The
disadvantage of this approach is that the exerted leverage is magnified at each
subsequent joint possibly damaging the mechanism. In this paper, we present two
lightweight, elastic, bio-inspired tensegrity robotics arms which mitigate this
danger while improving their mechanism's functionality. Our solutions feature
modular tensegrity structures that function similarly to the human elbow and
the human shoulder when connected. Like their biological counterparts, the
proposed robotic joints are flexible and comply with unanticipated forces. Both
proposed structures have multiple passive degrees of freedom and four active
degrees of freedom (two from the shoulder and two from the elbow). The
structural advantages demonstrated by the joints in these manipulators
illustrate a solution to the fundamental issue of elegantly handling off-axis
compliance.


title:
Uniform in Time Interacting Particle Approximations for Nonlinear
  Equations of Patlak-Keller-Segel type

abstract:
  We study a system of interacting diffusions that models chemotaxis of
biological cells or microorganisms (referred to as particles) in a chemical
field that is dynamically modified through the collective contributions from
the particles. Such systems of reinforced diffusions have been widely studied
and their hydrodynamic limits that are nonlinear non-local partial differential
equations are usually referred to as Patlak-Keller-Segel (PKS) equations. Under
the so-called "quasi-stationary hypothesis" on the chemical field the limit PDE
is closely related to granular media equations that have been extensively
studied probabilistically in recent years. Solutions of classical PKS solutions
may blow up in finite time and much of the PDE literature has been focused on
understanding this blow-up phenomenon. In this work we study a modified form of
the PKS equation for which global existence and uniqueness of solutions holds.
Our goal is to analyze the long-time behavior of the particle system
approximating the equation. We establish, under suitable conditions, uniform in
time convergence of the empirical measure of particle states to the solution of
the PDE. We also provide uniform in time exponential concentration bounds for
rate of the above convergence under additional integrability conditions.
Finally, we introduce an Euler discretization scheme for the simulation of the
interacting particle system and give error bounds that show that the scheme
converges uniformly in time and in the size of the particle system as the
discretization parameter approaches zero.


title:
Polarization of thermal bremsstrahlung emission due to electron pressure
  anisotropy

abstract:
  Astrophysical plasmas are typically magnetized, with the Larmor radii of the
charged particles many orders of magnitude smaller than their collisional mean
free paths. The fundamental properties of such plasmas, e.g., conduction and
viscosity, may depend on the instabilities driven by the anisotropy of the
particle distribution functions and operating at scales comparable to the
Larmor scales. We discuss a possibility that the pressure anisotropy of thermal
electrons could produce polarization of thermal bremsstrahlung emission. In
particular, we consider coherent large-scale motions in galaxy clusters to
estimate the level of anisotropy driven by stretching of the magnetic-field
lines by plasma flow and by heat fluxes associated with thermal gradients. Our
estimate of the degree of polarization is $\sim 0.1 \%$ at energies $\gtrsim
kT$. While this value is too low for the forthcoming generation of X-ray
polarimeters, it is potentially an important proxy for the processes taking
place at extremely small scales, which are impossible to resolve spatially. The
absence of the effect at the predicted level may set a lower limit on the
electron collisionality in the ICM. At the same time, the small value of the
effect implies that it does not preclude the use of clusters as (unpolarized)
calibration sources for X-ray polarimeters at this level of accuracy.


title: A Characteristic Function for the Primes

abstract:
  I develop a function that, for any integer $n \geq 2$, takes a value of 1 if
$n$ is prime, 0 if $n$ is composite. I also discuss two applications: First,
the characteristic function provides a new expression for the prime counting
function. Second, the components of the characteristic function point to a new
expression that gives the number of distinct prime factors for any integer
greater than one.


title: Deep Edge Guided Recurrent Residual Learning for Image Super-Resolution

abstract:
  In this work, we consider the image super-resolution (SR) problem. The main
challenge of image SR is to recover high-frequency details of a low-resolution
(LR) image that are important for human perception. To address this essentially
ill-posed problem, we introduce a Deep Edge Guided REcurrent rEsidual~(DEGREE)
network to progressively recover the high-frequency details. Different from
most of existing methods that aim at predicting high-resolution (HR) images
directly, DEGREE investigates an alternative route to recover the difference
between a pair of LR and HR images by recurrent residual learning. DEGREE
further augments the SR process with edge-preserving capability, namely the LR
image and its edge map can jointly infer the sharp edge details of the HR image
during the recurrent recovery process. To speed up its training convergence
rate, by-pass connections across multiple layers of DEGREE are constructed. In
addition, we offer an understanding on DEGREE from the view-point of sub-band
frequency decomposition on image signal and experimentally demonstrate how
DEGREE can recover different frequency bands separately. Extensive experiments
on three benchmark datasets clearly demonstrate the superiority of DEGREE over
well-established baselines and DEGREE also provides new state-of-the-arts on
these datasets.


title: Distance Metric Learning for Aspect Phrase Grouping

abstract:
  Aspect phrase grouping is an important task in aspect-level sentiment
analysis. It is a challenging problem due to polysemy and context dependency.
We propose an Attention-based Deep Distance Metric Learning (ADDML) method, by
considering aspect phrase representation as well as context representation.
First, leveraging the characteristics of the review text, we automatically
generate aspect phrase sample pairs for distant supervision. Second, we feed
word embeddings of aspect phrases and their contexts into an attention-based
neural network to learn feature representation of contexts. Both aspect phrase
embedding and context embedding are used to learn a deep feature subspace for
measure the distances between aspect phrases for K-means clustering.
Experiments on four review datasets show that the proposed method outperforms
state-of-the-art strong baseline methods.


title:
High Performance WSe2 Field-Effect Transistors via Controlled Formation
  of In-Plane Heterojunctions

abstract:
  Monolayer WSe2 is a two dimensional (2D) semiconductor with a direct bandgap,
and it has been recently explored as a promising material for electronics and
optoelectronics. Low field effect mobility is the main constraint preventing
WSe2 from becoming one of the competing channel materials for field-effect
transistors (FETs). Recent results have demonstrated that chemical treatments
can modify the electrical properties of transition metal dichalcogenides
(TMDCs) including MoS2 and WSe2. Here, we report that controlled heating in air
significantly improves device performance of WSe2 FETs in terms of on-state
currents and field-effect mobilities. Specifically, after heating at optimized
conditions, chemical vapor deposition grown monolayer WSe2 FETs showed an
average FET mobility of 31 cm2/Vs and on/off current ratios up to 5*108. For
few-layer WSe2 FETs, after the same treatment applied, we achieved a high
mobility up to 92 cm2/Vs. These values are significantly higher than FETs
fabricated using as-grown WSe2 flakes without heating treatment, demonstrating
the effectiveness of air heating on the performance improvements of WSe2 FETs.
The underlying chemical processes involved during air heating and the formation
of in-plane heterojunctions of WSe2 and WO3-x, which is believed to be the
reason for the improved FET performance, were studied by spectroscopy and
transmission electron microscopy. We further demonstrated that by combining air
heating method developed in this work with supporting 2D materials on BN
substrate, we achieved a noteworthy field effect mobility of 83 cm2/Vs for
monolayer WSe2 FETs. This work is a step towards controlled modification of the
properties of WSe2 and potentially other TMDCs, and may greatly improve device
performance for future applications of 2D materials in electronics and
optoelectronics.


title:
Geometric Scattering for Schr\"odinger Operators with Asymptotically
  Homogeneous Potentials of Order Zero

abstract:
  In this paper we consider Schr\"oodinger operators with potentials of order
zero on asymptotically conic manifolds. We prove the existence and the
completeness of the wave operators with a naturally defined free Hamiltonian.


title:
A Modest Proposal for Open Market Risk Assessment to Solve the
  Cyber-Security Problem

abstract:
  We introduce a model for a market based economic system of cyber-risk
valuation to correct fundamental problems of incentives within the information
technology and information processing industries. We assess the makeup of the
current day marketplace, identify incentives, identify economic reasons for
current failings, and explain how a market based risk valuation system could
improve these incentives to form a secure and robust information marketplace
for all consumers by providing visibility into open, consensus based risk
pricing and allowing all parties to make well informed decisions.


title: SGR-like behaviour of the repeating FRB 121102

abstract:
  Fast radio bursts (FRBs) are millisecond-duration radio signals occurring at
cosmological distances. However the physical model of FRBs is mystery, many
models have been proposed. Here we study the frequency distributions of peak
flux, fluence, duration and waiting time for the repeating FRB 121102. The
cumulative distributions of peak flux, fluence and duration show power-law
forms. The waiting time distribution also shows power-law distribution, and is
consistent with a non-stationary Poisson process. These distributions are
similar as those of soft gamma repeaters (SGRs). We also use the statistical
results to test the proposed models for FRBs. These distributions are
consistent with the predictions from avalanche models of slowly driven
nonlinear dissipative systems.


title:
An Explicit Formula for Likelihood Function for Gaussian Vector
  Autoregressive Moving-Average Model Conditioned on Initial Observables with
  Application to Model Calibration

abstract:
  We derive an explicit formula for likelihood function for Gaussian VARMA
model conditioned on initial observables where the moving-average (MA)
coefficients are scalar. For fixed MA coefficients the likelihood function is
optimized in the autoregressive variables $\Phi$'s by a closed form formula
generalizing regression calculation of the VAR model with the introduction of
an inner product defined by MA coefficients. We show the assumption of scalar
MA coefficients is not restrictive and this formulation of the VARMA model
shares many nice features of VAR and MA model. The gradient and Hessian could
be computed analytically. The likelihood function is preserved under the root
invertion maps of the MA coefficients. We discuss constraints on the gradient
of the likelihood function with moving average unit roots. With the help of FFT
the likelihood function could be computed in $O((kp+1)^2T +ckT\log(T))$ time.
Numerical calibration is required for the scalar MA variables only. The
approach can be generalized to include additional drifts as well as integrated
components. We discuss a relationship with the Borodin-Okounkov formula and the
case of infinite MA components.


title:
Chiral Symmetry Breaking in Micro-Ring Optical Cavity By Engineered
  Dissipation

abstract:
  We propose a method to break the chiral symmetry of light in traveling wave
resonators by coupling the optical modes to a lossy channel. Through the
engineered dissipation, an indirect dissipative coupling between two oppositely
propagating modes can be realized. Combining with reactive coupling, it can
break the chiral symmetry of the resonator, allowing light propagating only in
one direction. The chiral symmetry breaking is numerically verified by the
simulation of an electromagnetic field in a micro-ring cavity, with proper
refractive index distributions. This work provokes us to emphasize the
dissipation engineering in photonics, and the generalized idea can also be
applied to other systems.


title: On Approximating Functions of the Singular Values in a Stream

abstract:
  For any real number $p > 0$, we nearly completely characterize the space
complexity of estimating $\|A\|_p^p = \sum_{i=1}^n \sigma_i^p$ for $n \times n$
matrices $A$ in which each row and each column has $O(1)$ non-zero entries and
whose entries are presented one at a time in a data stream model. Here the
$\sigma_i$ are the singular values of $A$, and when $p \geq 1$, $\|A\|_p^p$ is
the $p$-th power of the Schatten $p$-norm. We show that when $p$ is not an even
integer, to obtain a $(1+\epsilon)$-approximation to $\|A\|_p^p$ with constant
probability, any $1$-pass algorithm requires $n^{1-g(\epsilon)}$ bits of space,
where $g(\epsilon) \rightarrow 0$ as $\epsilon \rightarrow 0$ and $\epsilon >
0$ is a constant independent of $n$. However, when $p$ is an even integer, we
give an upper bound of $n^{1-2/p} \textrm{poly}(\epsilon^{-1}\log n)$ bits of
space, which holds even in the turnstile data stream model. The latter is
optimal up to $\textrm{poly}(\epsilon^{-1} \log n)$ factors.
  Our results considerably strengthen lower bounds in previous work for
arbitrary (not necessarily sparse) matrices $A$: the previous best lower bound
was $\Omega(\log n)$ for $p\in (0,1)$, $\Omega(n^{1/p-1/2}/\log n)$ for $p\in
[1,2)$ and $\Omega(n^{1-2/p})$ for $p\in (2,\infty)$. We note for $p \in (2,
\infty)$, while our lower bound for even integers is the same, for other $p$ in
this range our lower bound is $n^{1-g(\epsilon)}$, which is considerably
stronger than the previous $n^{1-2/p}$ for small enough constant $\epsilon >
0$. We obtain similar near-linear lower bounds for Ky-Fan norms, SVD entropy,
eigenvalue shrinkers, and M-estimators, many of which could have been solvable
in logarithmic space prior to our work.


title:
Infinite Horizon Optimal Transmission Power Control for Remote State
  Estimation over Fading Channels

abstract:
  Jointly optimal transmission power control and remote estimation over an
infinite horizon is studied. A sensor observes a dynamic process and sends its
observations to a remote estimator over a wireless fading channel characterized
by a time-homogeneous Markov chain. The successful transmission probability
depends on both the channel gains and the transmission power used by the
sensor. The transmission power control rule and the remote estimator should be
jointly designed, aiming to minimize an infinite-horizon cost consisting of the
power usage and the remote estimation error. A first question one may ask is:
Does this joint optimization problem have a solution? We formulate the joint
optimization problem as an average cost belief-state Markov decision process
and answer the question by proving that there exists an optimal deterministic
and stationary policy. We then show that when the monitored dynamic process is
scalar, the optimal remote estimates depend only on the most recently received
sensor observation, and the optimal transmission power is symmetric and
monotonically increasing with respect to the innovation error.


title: Approximate amenability of tensor products of Banach algebras

abstract:
  We show that the tensor product of approximately amenable algebras need not
be approximately amenable, and investigate conditions under which $A$ and $B$
being approximately amenable implies, or is implied by, $A\hat{\otimes}B$ or
$A^{\#}\hat{\otimes} B^{\#}$ being approximately amenable. Our methods also
enable us to prove that if $A\hat{\otimes}B$ is amenable, then so are $A$ and
$B$, a result proved by Barry Johnson in 1996 under an additional assumption.


title:
Entropic uncertainty relations for successive measurements of
  canonically conjugate observables

abstract:
  Uncertainties in successive measurements of general canonically conjugate
variables are examined. Such operators are approached within a limiting
procedure of the Pegg-Barnett type. Dealing with unbounded observables, we
should take into account a finiteness of detector resolution. An appropriate
reformulation of two scenarios of successive measurements is proposed and
motivated. Uncertainties are characterized by means of generalized entropies of
both the R\'{e}nyi and Tsallis types. The R\'{e}nyi and Tsallis formulations of
uncertainty relations are obtained for both the scenarios of successive
measurements of canonically conjugate operators. Entropic uncertainty relations
for the case of position and momentum are separately discussed.


title: Top-push Video-based Person Re-identification

abstract:
  Most existing person re-identification (re-id) models focus on matching still
person images across disjoint camera views. Since only limited information can
be exploited from still images, it is hard (if not impossible) to overcome the
occlusion, pose and camera-view change, and lighting variation problems. In
comparison, video-based re-id methods can utilize extra space-time information,
which contains much more rich cues for matching to overcome the mentioned
problems. However, we find that when using video-based representation, some
inter-class difference can be much more obscure than the one when using
still-image based representation, because different people could not only have
similar appearance but also have similar motions and actions which are hard to
align. To solve this problem, we propose a top-push distance learning model
(TDL), in which we integrate a top-push constrain for matching video features
of persons. The top-push constraint enforces the optimization on top-rank
matching in re-id, so as to make the matching model more effective towards
selecting more discriminative features to distinguish different persons. Our
experiments show that the proposed video-based re-id framework outperforms the
state-of-the-art video-based re-id methods.


title: Topological Orbit Dimension of MF $C^*$-algebras

abstract:
  This paper is a continuation of our work on D. Voiculescu's topological free
entropy dimension in unital C*-algebras. In this paper we first prove the
topological free entropy dimension of a MF-nuclear and inner QD algebra is
irrelevant to its generating family. Then we give the relation between the
topological orbit dimension $K_{top}^2$ and the modified free orbit dimension$
K_2^2$ by using MF-traces. We also introduce a new invariant $K_{top}^3$ which
is a modification of the topological orbit dimension $K_{top}^2$ when$
K_{top}^2$ is defined. As the applications of $K_{top}^3$, We prove that$
K_{top}^3(A)=0$ if A has property $ c^*-{\Gamma}$ and has no finite-dimensional
representations. We also give the definition of property MF-c^*-{\Gamma}. We
then conclude that, for the unital MF $ C^*$-algebra with no finite-dimensional
representations, if A has property MF-c*-{\Gamma}, then $K_{top}^3(A)=0$.


title: Single Image 3D Interpreter Network

abstract:
  Understanding 3D object structure from a single image is an important but
difficult task in computer vision, mostly due to the lack of 3D object
annotations in real images. Previous work tackles this problem by either
solving an optimization task given 2D keypoint positions, or training on
synthetic data with ground truth 3D information. In this work, we propose 3D
INterpreter Network (3D-INN), an end-to-end framework which sequentially
estimates 2D keypoint heatmaps and 3D object structure, trained on both real
2D-annotated images and synthetic 3D data. This is made possible mainly by two
technical innovations. First, we propose a Projection Layer, which projects
estimated 3D structure to 2D space, so that 3D-INN can be trained to predict 3D
structural parameters supervised by 2D annotations on real images. Second,
heatmaps of keypoints serve as an intermediate representation connecting real
and synthetic data, enabling 3D-INN to benefit from the variation and abundance
of synthetic 3D objects, without suffering from the difference between the
statistics of real and synthesized images due to imperfect rendering. The
network achieves state-of-the-art performance on both 2D keypoint estimation
and 3D structure recovery. We also show that the recovered 3D information can
be used in other vision applications, such as 3D rendering and image retrieval.


title:
Superconductivity and abnormal pressure effect in Sr0.5La0.5FBiSe2
  superconductor

abstract:
  Through the solid state reaction method, we synthesized a new BiSe2-based
superconductor Sr0:5La0:5FBiSe2 with superconducting transition temperature
Tc?3.8 K. A strong diamagnetic signal below Tc in susceptibility ?(T) is
observed indicating the bulk nature of superconductivity. Different to most
BiS2-based compounds where superconductivity develops from a
semiconducting-like normal state, the present compound exhibits a metallic
behavior down to Tc. Under weak magnetic field or pressure, however, a
remarkable crossover from metallic to insulating behaviors takes place around
Tmin where the resistivity picks up a local minimum. With increasing pressure,
Tc decreases monotonously and Tmin shifts to high temperatures, while the
absolute value of the normal state resistivity at low temperatures first
decreases and then increases with pressure up to 2.5 GPa. These results imply
that the electronic structure of Sr0:5La0:5FBiSe2 may be different to those in
the other BiS2-based systems.


title: Hagedorn legacy

abstract:
  These remarks open the one-day session "50 years of Hagedorn's Temperature
and the Statistical Bootstrap Model". These developments set the path at CERN
towards the discovery of Quark-Gluon Plasma in the year 2000.


title: Implementing the Deutsch-Jozsa algorithm with macroscopic ensembles

abstract:
  Quantum computing implementations under consideration today typically deal
with systems with microscopic degrees of freedom such as photons, ions, cold
atoms, and superconducting circuits. The quantum information is stored
typically in low-dimensional Hilbert spaces such as qubits, as quantum effects
are strongest in such systems. It has however been demonstrated that quantum
effects can be observed in mesoscopic and macroscopic systems, such as
nanomechanical systems and gas ensembles. While few-qubit quantum information
demonstrations have been performed with such macroscopic systems, a quantum
algorithm showing exponential speedup over classical algorithms is yet to be
shown. Here we show that the Deutsch-Jozsa algorithm can be implemented with
macroscopic ensembles. The encoding that we use avoids the detrimental effects
of decoherence that normally plagues macroscopic implementations. We discuss
two mapping procedures which can be chosen depending upon the constraints of
the oracle and the experiment. Both methods have an exponential speedup over
the classical case, and only require control of the ensembles at the level of
the total spin of the ensembles. It is shown that both approaches reproduce the
qubit Deutsch-Jozsa algorithm, and are robust under decoherence.


title: The hot Hagedorn Universe

abstract:
  In the context of the half-centenary of Hagedorn temperature and the
statistical bootstrap model (SBM) we present a short account of how these
insights coincided with the establishment of the hot big-bang model (BBM) and
helped resolve some of the early philosophical difficulties. We then turn
attention to the present day context and show the dominance of strong
interaction quark and gluon degrees of freedom in the early stage, helping to
characterize the properties of the hot Universe. We focus attention on the
current experimental insights about cosmic microwave background (CMB)
temperature fluctuation, and develop a much improved understanding of the
neutrino freeze-out, in this way paving the path to the opening of a direct
connection of quark-gluon plasma (QGP) physics in the early Universe with the
QCD-lattice, and the study of the properties of QGP formed in the laboratory.


title: Probing QED Vacuum with Heavy Ions

abstract:
  We recall how nearly half a century ago the proposal was made to explore the
structure of the quantum vacuum using slow heavy-ion collisions. Pursuing this
topic we review the foundational concept of spontaneous vacuum decay
accompanied by observable positron emission in heavy-ion collisions and
describe the related theoretical developments in strong fields QED.


title:
A Fast Sampling Method of Exploring Graphlet Degrees of Large Directed
  and Undirected Graphs

abstract:
  Exploring small connected and induced subgraph patterns (CIS patterns, or
graphlets) has recently attracted considerable attention. Despite recent
efforts on computing the number of instances a specific graphlet appears in a
large graph (i.e., the total number of CISes isomorphic to the graphlet),
little attention has been paid to characterizing a node's graphlet degree,
i.e., the number of CISes isomorphic to the graphlet that include the node,
which is an important metric for analyzing complex networks such as social and
biological networks. Similar to global graphlet counting, it is challenging to
compute node graphlet degrees for a large graph due to the combinatorial nature
of the problem. Unfortunately, previous methods of computing global graphlet
counts are not suited to solve this problem. In this paper we propose sampling
methods to estimate node graphlet degrees for undirected and directed graphs,
and analyze the error of our estimates. To the best of our knowledge, we are
the first to study this problem and give a fast scalable solution. We conduct
experiments on a variety of real-word datasets that demonstrate that our
methods accurately and efficiently estimate node graphlet degrees for graphs
with millions of edges.


title: Optimal data recovery and forecasting with dummy long-horizon forecasts

abstract:
  The paper suggests a method of recovering missing values for sequences,
including sequences with a multidimensional index, based on optimal
approximation by processes featuring spectrum degeneracy. The problem is
considered in the pathwise setting, without using probabilistic assumptions on
the ensemble. The method requires to solve a closed linear equation connecting
the available observations of the underlying process with the values of the
approximating process with degenerate spectrum outside the observation
range.Some robustness with respect to noise contamination is established for
the suggested recovering algorithm. It is suggested to apply this data recovery
algorithm to forecasting with a preselected dummy long-horizon forecast that
helps to regularize the solution.


title:
LMS Moodle: Distance international education in cooperation of higher
  education institutions of different countries

abstract:
  The development of international cooperation requires cooperation in the
sphere of education. An enhanced sharing of experience in the sphere of
practical teaching activities implies the increase of the quality of teaching
process and of scientific cooperation. Sharing of experience in educational
activities implies understanding among representatives of different nations
anywhere in the world. It means that through LSM teaching the principle of
social constructivism is realized, when participants together create a narrow
culture of common objects and senses. The article presents an example of
practical application of electronic media to the process of a real lesson. The
article describes the process of teaching students from different countries
using the system of LMS MOODLE, beginning with preparing study materials,
giving lectures by foreign lecturers, practical tasks and ending with passing
an examination. Training has included some full-time students from the Slovak
Republic, the Republic of Dagestan and the Republic of Kazakhstan, and has been
realized by applying the method of distance learning (LMS).


title:
Paradoxical signaling regulates structural plasticity in dendritic
  spines

abstract:
  Transient spine enlargement (3-5 min timescale) is an important event
associated with the structural plasticity of dendritic spines. Many of the
molecular mechanisms associated with transient spine enlargement have been
identified experimentally. Here, we use a systems biology approach to construct
a mathematical model of biochemical signaling and actin-mediated transient
spine expansion in response to calcium-influx due to NMDA receptor activation.
We have identified that a key feature of this signaling network is the
paradoxical signaling loop. Paradoxical components act bifunctionally in
signaling networks and their role is to control both the activation and
inhibition of a desired response function (protein activity or spine volume).
Using ordinary differential equation (ODE)-based modeling, we show that the
dynamics of different regulators of transient spine expansion including CaMKII,
RhoA, and Cdc42 and the spine volume can be described using paradoxical
signaling loops. Our model is able to capture the experimentally observed
dynamics of transient spine volume. Furthermore, we show that actin remodeling
events provide a robustness to spine volume dynamics. We also generate
experimentally testable predictions about the role of different components and
parameters of the network on spine dynamics.


title: A Discrete Carleson Theorem Along the Primes with a Restricted Supremum

abstract:
  Consider the discrete maximal function acting on finitely supported functions
on the integers, \[ \mathcal{C}_\Lambda f(n) := \sup_{\lambda \in \Lambda} |
\sum_{p \in \pm \mathbb{P}} f(n-p) \log |p| \frac{e^{2\pi i \lambda p}}{p} |,\]
where $\pm \mathbb{P} := \{ \pm p : p \text{ is a prime} \}$, and $\Lambda
\subset [0,1]$. We give sufficient conditions on $\Lambda$, met by (finite
unions of) lacunary sets, for this to be a bounded sublinear operator on
$\ell^p(\mathbb{Z})$ for $\frac{3}{2} < p < 4$.


title:
Gompertzian population growth under some deterministic and stochastic
  jump schedules

abstract:
  Many cell populations, exemplified by certain tumors, grow approximately
according to a Gompertzian growth model which has a slower approach to an upper
limit than that of logistic growth. Certain populations of animals and other
organisms have also recently been analyzed with the Gompertz model. This
article addresses the question of how long it takes to reduce the population
from one level to a lower one under a schedule of sudden decrements, each of
which removes a given fraction of the cell mass or population. A deterministic
periodic schedule is first examined and yields exact results for the
eradication or extinction time which is defined as that required to reduce the
number of cells to less than unity. The decrements in cell mass at each hit
could correspond to an approximation to reduction of a tumor by external beam
radiation therapy. The effects of variations in magnitude of successive
decrements, the time interval between them, the initial population size and the
intrinsic growth rate are calculated and results presented graphically.
  With a schedule governed by a Poisson process, the number of organisms or
cells satisfies a stochastic differential equation whose solution sample paths
have downward jumps as random times. The moments of the exit time then satisfy
a system of recurrent differential-difference equations. A simple
transformation results in a simpler system which has been studied both
analytically and numerically in the context of interspike intervals of a model
neuron. Results are presented for the mean eradication time for various
frequencies and magnitudes of hits and for various eventual and initial
population sizes. The standard deviation of the eradication time is also
investigated.


title:
Sparse Generalized Eigenvalue Problem: Optimal Statistical Rates via
  Truncated Rayleigh Flow

abstract:
  Sparse generalized eigenvalue problem (GEP) plays a pivotal role in a large
family of high-dimensional statistical models, including sparse Fisher's
discriminant analysis, canonical correlation analysis, and sufficient dimension
reduction. Sparse GEP involves solving a non-convex optimization problem. Most
existing methods and theory in the context of specific statistical models that
are special cases of the sparse GEP require restrictive structural assumptions
on the input matrices. In this paper, we propose a two-stage computational
framework to solve the sparse GEP. At the first stage, we solve a convex
relaxation of the sparse GEP. Taking the solution as an initial value, we then
exploit a nonconvex optimization perspective and propose the truncated Rayleigh
flow method (Rifle) to estimate the leading generalized eigenvector. We show
that Rifle converges linearly to a solution with the optimal statistical rate
of convergence for many statistical models. Theoretically, our method
significantly improves upon the existing literature by eliminating structural
assumptions on the input matrices for both stages. To achieve this, our
analysis involves two key ingredients: (i) a new analysis of the gradient based
method on nonconvex objective functions, and (ii) a fine-grained
characterization of the evolution of sparsity patterns along the solution path.
Thorough numerical studies are provided to validate the theoretical results.


title: Relative Convex Hull Determination from Convex Hulls in the Plane

abstract:
  A new algorithm for the determination of the relative convex hull in the
plane of a simple polygon A with respect to another simple polygon B which
contains A, is proposed. The relative convex hull is also known as geodesic
convex hull, and the problem of its determination in the plane is equivalent to
find the shortest curve among all Jordan curves lying in the difference set of
B and A and encircling A. Algorithms solving this problem known from
Computational Geometry are based on the triangulation or similar decomposition
of that difference set. The algorithm presented here does not use such
decomposition, but it supposes that A and B are given as ordered sequences of
vertices. The algorithm is based on convex hull calculations of A and B and of
smaller polygons and polylines, it produces the output list of vertices of the
relative convex hull from the sequence of vertices of the convex hull of A.


title:
Universality class of site and bond percolation on multi-multifractal
  scale-free planar stochastic lattice

abstract:
  In this article, we investigate both site and bond percolation on a weighted
planar stochastic lattice (WPSL) which is a multi-multifractal and whose dual
is a scale-free network. The characteristic properties of percolation is that
it exhibits threshold phenomena as we find sudden or abrupt jump in spanning
probability across $p_c$ accompanied by the divergence of some other observable
quantities which is reminiscent of continuous phase transition. Indeed,
percolation is characterized by the critical behavior of percolation strength
$P(p)\sim (p_c-p)^\beta$, mean cluster size $S\sim (p_c-p)^{-\gamma}$ and the
system size $L\sim (p_c-p)^{-\nu}$ which are known as the equivalent
counterpart of the order parameter, susceptibility and correlation length
respectively. Moreover, the cluster size distribution function $n_s(p_c)\sim
s^{-\tau}$ and the mass-length relation $M\sim L^{d_f}$ of the spanning cluster
also provide useful characterization of the percolation process. We obtain an
exact value for $p_c$ and for all the exponents such as $\beta, \nu, \gamma,
\tau$ and $d_f$. We find that, except $p_c$, all the exponents are exactly the
same in both bond and site percolation despite the significant difference in
the definition of cluster and other quantities. Our results suggest that the
percolation on WPSL belongs to a new universality class as its exponents do not
share the same value as for all the existing planar lattices and like other
cases its site and bond belong to the same universality class.


title: Bound-bound transitions in the emission spectra of Ba$^{+}$--He excimer

abstract:
  We present an experimental and theoretical study of the emission and
absorption spectra of the Ba$^{+}$ ions and Ba$^{+\ast}$He excimer
quasimolecules in the cryogenic Ba--He plasma. We observe several new spectral
features in the emission spectrum which we assign to the electronic transitions
between bound states of the excimer correlating to the 6$^{2}P_{3/2}$ and
5$^{2}D_{3/2,5/2}$ states of Ba$^{+}$. The resulting Ba$^{+}$(5$^{2}D_{J}$)He
is a metastable electronically excited complex with orbital angular momentum
$L$=2, thus expanding the family of known metal--helium quasimolecules. It
might be suitable for high-resolution spectroscopic studies and for the search
for new polyatomic exciplex structures.


title: Polarimetric Detection of Exoplanets Transiting T- and L- Brown Dwarfs

abstract:
  While scattering of light by atoms and molecules yields large amount of
polarization at the B-band of both T- and L-dwarfs, scattering by dust grains
in cloudy atmosphere of L-dwarfs gives rise to significant polarization at the
far-optical and infra-red wavelengths where these objects are much brighter.
However, the observable disk averaged polarization should be zero if the clouds
are uniformly distributed and the object is spherically symmetric. Therefore,
in order to explain the observed large polarization of several L-dwarfs,
rotation-induced oblateness or horizontally inhomogeneous cloud distribution in
the atmosphere is invoked. On the other hand, when an extra-solar planet of
Earth-size or larger transits the brown dwarf along the line of sight, the
asymmetry induced during the transit gives rise to a net non-zero, time
dependent polarization. Employing atmospheric models for a range of effective
temperature and surface gravity appropriate for T- and L-dwarfs, I derive the
time dependent polarization profiles of these objects during transit phase and
estimate the peak amplitude of polarization that occurs during the inner
contact points of the transit ingress/egress phase. It is found that peak
polarization in the range of 0.2-1.0 % at I- and J-band may arise of cloudy L
dwarfs occulted by Earth-size or larger exoplanets. Such an amount of
polarization is higher than that can be produced by rotation-induced oblateness
of even the rapidly rotating L-dwarfs. Hence, I suggest that time resolved
imaging polarization should be a potential technique to detect transiting
exoplanets around L-dwarfs.


title:
Renormalization of domain-wall bilinear operators with short-distance
  current correlators

abstract:
  We determine the renormalization constants for flavor non-singlet fermion
bilinear operators of M\"obius domain-wall fermions. The renormalization
condition is imposed on the correlation functions in the coordinate space, such
that the non-perturbative lattice calculation reproduces the perturbatively
calculated counterpart at short distances. The perturbative expansion is
precise as the coefficients are available up to $O(\alpha_s^4)$. We employ
$2+1$-flavor lattice ensembles at three lattice spacings in the range
0.044--0.080~fm.


title:
The regularizing properties of multistep methods for first kind Volterra
  integral equations with smooth kernels

abstract:
  We study quadrature methods for solving Volterra integral equations of the
first kind with smooth kernels under the presence of noise in the right-hand
sides, with the quadrature methods being generated by linear multistep methods.
The regularizing properties of an a priori choice of the step size are
analyzed, with the smoothness of the involved functions carefully taken into
consideration. The balancing principle as an adaptive choice of the step size
is also studied. It is considered in a version which sometimes requires less
amount of computational work than the standard version of this principle.
Numerical results are included.


title:
Current induced magnetization dynamics and magnetization switching in
  superconducting ferromagnetic hybrid (F$|$S$|$F) structures

abstract:
  We investigate the current induced magnetization dynamics and magnetization
switching in an unconventional p-wave superconductor sandwiched between two
misaligned ferromagnetic layers by numerically solving Landau-Lifshitz-Gilbert
equation modified with current induced Slonczewski's spin torque term. A
modified form of Ginzburg-Landau free energy functional has been used for this
purpose. We demonstrated the possibility of current induced magnetization
switching in the spin-triplet ferromagnetic superconducting hybrid structures
with strong easy axis anisotropy and the condition for magnetization reversal.
The switching time for such arrangement is calculated and is found to be highly
dependent on the magnetic configuration along with the biasing current. This
study would be useful in designing practical superconducting-spintronic
devices.


title: The logic of Turing progressions

abstract:
  Turing progressions arise by iteratedly adding consistency statements to a
base theory. Different notions of consistency give rise to different Turing
progressions. In this paper we present a logic that generates exactly all
relations that hold between these different Turing progressions given a
particular set of natural consistency notions. Thus, the presented logic is
proven to arithmetically sound and complete for a natural interpretation, named
the \emph{Formalized Turing progressions} (FTP) interpretation.


title: Comment on Quantum Massive Conformal Gravity

abstract:
  In a recent paper in EPJC March 2016, Faria has shown that quantum massive
conformal gravity is renormalizable but has ghost states. We comment this paper
on the aspect of renormalizability.


title:
Deterministic remote preparation of an arbitrary qubit state using a
  partially entangled state and finite classical communication

abstract:
  We propose a deterministic remote state preparation (RSP) scheme for
preparing an arbitrary (including pure and mixed) qubit, where a partially
entangled state and finite classical communication are used. To our knowledge,
our scheme is the first RSP scheme that fits into this category. One other RSP
scheme proposed by Berry shares close features, but can only be used to prepare
an arbitrary pure qubit. Even so, our scheme saves classical communication by
approximate 1 bit per prepared qubit under equal conditions. When using a
maximally entangled state, the classical communication for our scheme is 2
bits, which agrees with Lo's conjecture on the resource cost. Furthermore Alice
can switch between our RSP scheme and a standard teleportation scheme without
letting Bob know, which makes the quantum channel multipurpose.


title:
Mobile Robot Navigation on Partially Known Maps using a Fast A Star
  Algorithm Version

abstract:
  Mobile robot navigation in total or partially unknown environments is still
an open problem. The path planning algorithms lack completeness and/or
performance. Thus, there is the need for complete (i.e., the algorithm
determines in finite time either a solution or correctly reports that there is
none) and performance (i.e., with low computational complexity) oriented
algorithms which need to perform efficiently in real scenarios. In this paper
we evaluate the efficiency of two versions of the A star algorithm for mobile
robot navigation inside indoor environments with the help of two software
applications and the Pioneer 2DX robot. We demonstrate that an improved version
of the A star algorithm (we call this the fast A star algorithm) which (a
different version of this algorithm is widely used in video games) can be
successfully used for indoor mobile robot navigation. We evaluated the two
versions of the A star algorithm first, by implementing the algorithms in
source code and by testing them on a simulator and second, by comparing two
operation modes of the fast A star algorithm w.r.t. path planning efficiency
(i.e., completness) and performance (i.e., time need to complete the path
traversing) for indoor navigation with the Pioneer 2DX robot. The results
obtained with the fast A star algorithm are promising and we think that this
results can be further improved by tweaking the algorithm and by using an
advanced sensor fusion approach (i.e., combine the inputs of multiple robot
sensors) for better dealing with partially known environments.


title: "Knowing value" logic as a normal modal logic

abstract:
  Recent years witness a growing interest in nonstandard epistemic logics of
"knowing whether", "knowing what", "knowing how", and so on. These logics are
usually not normal, i.e., the standard axioms and reasoning rules for modal
logic may be invalid. In this paper, we show that the conditional "knowing
value" logic proposed by Wang and Fan \cite{WF13} can be viewed as a disguised
normal modal logic by treating the negation of the Kv operator as a special
diamond. Under this perspective, it turns out that the original first-order
Kripke semantics can be greatly simplified by introducing a ternary relation
$R_i^c$ in standard Kripke models, which associates one world with two
$i$-accessible worlds that do not agree on the value of constant $c$. Under
intuitive constraints, the modal logic based on such Kripke models is exactly
the one studied by Wang and Fan (2013,2014}. Moreover, there is a very natural
binary generalization of the "knowing value" diamond, which, surprisingly, does
not increase the expressive power of the logic. The resulting logic with the
binary diamond has a transparent normal modal system, which sharpens our
understanding of the "knowing value" logic and simplifies some previously hard
problems.


title:
Fermi Study of gamma-ray Millisecond Pulsars: the Spectral Shape and
  Pulsed 25--200 GeV Emission from J0614-3329

abstract:
  We report our analysis of the Fermi Large Area Telescope data for 39
millisecond pulsars (MSPs) listed in the second $\gamma$-ray pulsar catalog.
Spectra of the pulsars are obtained. We fit the spectra with a function of a
power law with exponential cutoff, and find the best-fit parameters of photon
index $\Gamma = 1.54^{+0.10}_{-0.11}$ and cutoff energy $E_{c} =
3.70^{+0.95}_{-0.70}$ GeV. This spectral shape, which includes the intrinsic
differences in the spectra of the MSPs, can be used for finding candidate MSPs
and unidentified types of sources detected by Fermi at high Galactic latitudes.
In one of the MSPs PSR J0614-3329, we find significant pulsed emission upto 200
GeV. The result has thus added this MSP to the group of the Crab and Vela
pulsars that have been detected with >50 GeV pulsed emission. Comparing the
$\gamma$-ray spectrum of PSR J0614-3329 with those of the Crab and Vela
pulsars, we discuss possible emission mechanisms for the very high-energy
component.


title:
On the question of symmetries in non-relativistic diffeomorphism
  invariant theories

abstract:
  A novel algorithm is provided to couple a Galilean invariant model with
curved spatial background by taking nonrelativistic limit of a unique minimally
coupled relativistic theory, which ensures Galilean symmetry in the flat limit
and canonical transformation of the original fields. That the twin requirements
are fulfilled is ensured by a new field, the existence of which was
demonstrated recently from Galilean gauge theory. The ambiguities and anomalies
concerning the recovery of Galilean symmetry in the flat limit of spatial non
relativistic diffeomorphic theories, reported in the literature, are focused
and resolved from a new angle.


title: Renormalization of Generalized KPZ equation

abstract:
  We use Renormalization Group to prove local well posedness for a generalized
KPZ equation introduced by H. Spohn in the context of stochastic hydrodynamics.
The equation requires the addition of counter terms diverging with a cutoff
$\epsilon$ as $\epsilon^{-1}$ and $\log\epsilon^{-1}$.


title:
Discrepancy of second order digital sequences in function spaces with
  dominating mixed smoothness

abstract:
  The discrepancy function measures the deviation of the empirical distribution
of a point set in $[0,1]^d$ from the uniform distribution. In this paper, we
study the classical discrepancy function with respect to the BMO and
exponential Orlicz norms, as well as Sobolev, Besov and Triebel-Lizorkin norms
with dominating mixed smoothness. We give sharp bounds for the discrepancy
function under such norms with respect to infinite sequences.


title: Iterative Multiplicative Filters for Data Labeling

abstract:
  Based on an idea in [4] we propose a new iterative multiplicative filtering
algorithm for label assignment matrices which can be used for the supervised
partitioning of data. Starting with a row-normalized matrix containing the
averaged distances between prior features and the observed ones the method
assigns in a very efficient way labels to the data. We interpret the algorithm
as a gradient ascent method with respect to a certain function on the product
manifold of positive numbers followed by a reprojection onto a subset of the
probability simplex consisting of vectors whose components are bounded away
from zero by a small constant. While such boundedness away from zero is
necessary to avoid an arithmetic underflow, our convergence results imply that
they are also necessary for theoretical reasons. Numerical examples show that
the proposed simple and fast algorithm leads to very good results. In
particular we apply the method for the partitioning of manifold-valued images.


title: On the joint spectral radius of a nilpotent Lie algebra of matrices

abstract:
  For a complex nilpotent finite dimensional Lie algebra of matrices,and a
Jordan-H\"older basis of it, we prove a spectral radius formula which extends a
well-known result for commuting matrices.


title:
Learning Compact Structural Representations for Audio Events Using
  Regressor Banks

abstract:
  We introduce a new learned descriptor for audio signals which is efficient
for event representation. The entries of the descriptor are produced by
evaluating a set of regressors on the input signal. The regressors are
class-specific and trained using the random regression forests framework. Given
an input signal, each regressor estimates the onset and offset positions of the
target event. The estimation confidence scores output by a regressor are then
used to quantify how the target event aligns with the temporal structure of the
corresponding category. Our proposed descriptor has two advantages. First, it
is compact, i.e. the dimensionality of the descriptor is equal to the number of
event classes. Second, we show that even simple linear classification models,
trained on our descriptor, yield better accuracies on audio event
classification task than not only the nonlinear baselines but also the
state-of-the-art results.


title: On Two Diophantine Inequalities Over Primes

abstract:
  Let $1<c<37/18,\,c\neq2$ and $N$ be a sufficiently large real number. In this
paper, we prove that, for almost all $R\in(N,2N],$ the Diophantine inequality
$|p_1^c+p_2^c+p_3^c-R|<\log^{-1}N$ is solvable in primes $p_1,\,p_2,\,p_3.$
Moreover, we also investigate the problem of six primes and prove that the
Diophantine inequality $|p_1^c+p_2^c+p_3^c+p_4^c+p_5^c+p_6^c-N|<\log^{-1}N$ is
solvable in primes $p_1,\,p_2,\,p_3,\,p_4,\,p_5,\,p_6$ for sufficiently large
real number $N$.


title:
Sharing of Nonlocality of a single member of an Entangled Pair Is Not
  Possible by More Than Two Unbiased Observers on the other wing

abstract:
  We address the recently posed question as to whether the nonlocality of a
single member of an entangled pair of spin $1/2$ particles can be shared among
multiple observers on the other wing who act sequentially and independently of
each other [1]. We first show that the optimality condition for the trade-off
between information gain and disturbance in the context of weak or non-ideal
measurements emerges naturally when one employs a one-parameter class of
positive operator valued measures (POVMs). Using this formalism we then prove
analytically that it is impossible to obtain violation of the
Clauser-Horne-Shimony-Holt (CHSH) inequality by more than two Bobs in one of
the two wings using unbiased input settings with an Alice in the other wing.


title:
The number of representations of squares by integral ternary quadratic
  forms (II)

abstract:
  Let $f$ be a positive definite ternary quadratic form. We assume that $f$ is
non-classic integral, that is, the norm ideal of $f$ is $\z$. We say $f$ is
{\it strongly $s$-regular } if the number of representations of squares of
integers by $f$ satisfies the condition in Cooper and Lam's conjecture in \cite
{cl}. In this article, we prove that there are only finitely many strongly
$s$-regular ternary forms up to equivalence if the minimum of the non zero
squares that are represented by the form is fixed. In particular, we show that
there are exactly $207$ non-classic integral strongly $s$-regular ternary forms
that represent one (see Tables 1 and 2). This result might be considered as a
complete answer to a natural extension of Cooper and Lam's conjecture.


title: Individual Treatment Effect Prediction for ALS Patients

abstract:
  A treatment for a complicated disease may be helpful for some but not all
patients, which makes predicting the treatment effect for new patients
important yet challenging. Here we develop a method for predicting the
treatment effect based on patient char- acteristics and use it for predicting
the effect of the only drug (Riluzole) approved for treating Amyotrophic
Lateral Sclerosis (ALS). Our proposed method of model-based ran- dom forests
detects similarities in the treatment effect among patients and on this basis
computes personalised models for new patients. The entire procedure focuses on
a base model, which usually contains the treatment indicator as a single
covariate and takes the survival time or a health or treatment success
measurement as primary outcome. This base model is used both to grow the
model-based trees within the forest, in which the patient characteristics that
interact with the treatment are split variables, and to com- pute the
personalised models, in which the similarity measurements enter as weights. We
applied the personalised models using data from several clinical trials for ALS
from the PRO-ACT database. Our results indicate that some ALS patients benefit
more from the drug Riluzole than others. Our method allows shifting from
stratified medicine to person- alised medicine and can also be used in
assessing the treatment effect for other diseases studied in a clinical trial.


title: Dynamics under Geometric Dissipation

abstract:
  We give sufficient conditions for asymptotic stabilization of equilibrium
points and periodic orbits of a dynamical system when we add a geometric
dissipation of gradient type. We also describe the domain of attraction in the
case of asymptotic stability.


title: The 2X-HI disks of spiral galaxies

abstract:
  The outskirts of galaxies - especially the very extended HI disks of galaxies
- are strongly affected by their local environment. I highlight the giant 2X-HI
disks of nearby galaxies (M 83, NGC 3621, and NGC 1512), studied as part of the
Local Volume HI Survey (LVHIS), their kinematics and relation to XUV disks,
signatures of tidal interactions and accretion events, the MHI - DHI relation
as well as the formation of tidal dwarf galaxies. - Using multi-wavelength
data, I create 3D visualisations of the gas and stars in galaxies, with the
shape of their warped disks obtained through kinematic modelling of their HI
velocity fields.


title: Music transcription modelling and composition using deep learning

abstract:
  We apply deep learning methods, specifically long short-term memory (LSTM)
networks, to music transcription modelling and composition. We build and train
LSTM networks using approximately 23,000 music transcriptions expressed with a
high-level vocabulary (ABC notation), and use them to generate new
transcriptions. Our practical aim is to create music transcription models
useful in particular contexts of music composition. We present results from
three perspectives: 1) at the population level, comparing descriptive
statistics of the set of training transcriptions and generated transcriptions;
2) at the individual level, examining how a generated transcription reflects
the conventions of a music practice in the training transcriptions (Celtic
folk); 3) at the application level, using the system for idea generation in
music composition. We make our datasets, software and sound examples open and
available: \url{https://github.com/IraKorshunova/folk-rnn}.


title: Adaptive strategy for joint measurements

abstract:
  We develop a technique to find simultaneous measurements for noisy quantum
observables in finite-dimensional Hilbert spaces. We use the method to derive
lower bounds for the noise needed to make incompatible measurements jointly
measurable. Using our strategy together with recent devel- opments in the field
of one-sided quantum information processing we show that the attained lower
bounds are tight for various symmetric sets of quantum measurements. We use
this characterisation to prove the existence of so called 4-Specker sets in the
qubit case.


title:
Influence of external temperature gradient on acoustoelectric current in
  graphene

abstract:
  Recent analyses of thermoelectric amplification of acoustic phonons in
Free-Standing Graphene (FSG) $\Gamma_q^{grap}$ have prompted the theoretical
study of the influence of external temperature gradient ($\nabla T$) on the
acoustoelectric current $j_T^{(grap)}$ in FSG. Here, we calculated thermal
field on open circuit ($j_T^{(grap)} = 0$) to be $(\nabla T)^g = 746.8Km^{-1}$.
We then calculated acoustoelectric current ($j_T^{(grap)}$)to be $1.1mA\mu
m^{-2}$ for $\nabla T = 750.0 Km^{-1}$, which is comparable to that obtained in
semiconductors ($1.0mA\mu m^{-2}$), the thermal-voltage $(V_T)_0^g$ to be
$6.6\mu V$ and the Seebeck coefficient $S$ as $8.8\mu V/K$. Graphs of the
normalized $j_T^{(grap)}/j_0$ versus $\omega_q$, $T$ and $\nabla T/T$ were
sketched. For $j_T^{(grap)}$ on $T$ for varying $\omega_q$, Negative Difference
Conductivity (NDC) ($| \frac{\partial j}{\partial T}| < 0$) was observed in the
material. This indicates graphene is a suitable material for developing thermal
amplifiers and logic gates.


title: On the complete integrability of the periodic quantum Toda lattice

abstract:
  We prove that the periodic quantum Toda lattice corresponding to any extended
Dynkin diagram is completely integrable. This has been conjectured and proved
in all classical cases and $E_6$ by Goodman and Wallach at the beginning of the
1980's. As a direct application, in the context of quantum cohomology of affine
flag manifolds, results that were known to hold only for some particular Lie
types can now be extended to all types.


title:
Exploring Social Networks for Optimized User Association in Wireless
  Small Cell Networks with Device-to-Device Communications

abstract:
  In this paper, we propose a novel social network aware approach for user
association in wireless small cell networks. The proposed approach exploits
social relationships between user equipments (UEs) and their physical proximity
to optimize the network throughput. We formulate the problem as a matching game
between UEs and their serving nodes (SNs). In our proposed game, the serving
node can be a small cell base station (SCBS) or an important node with
device-to-device capabilities. In this game, the SCBSs and UEs maximize their
respective utility functions capturing both the spatial and social structures
of the network. We show that the proposed game belongs to the class of matching
games with externalities. Subsequently, we propose a distributed algorithm
using which the SCBSs and UEs interact and reach a stable matching. We show the
convergence of the proposed algorithm and study the properties of the resulting
matching. Simulation results show that the proposed socially-aware user
association approach can efficiently offload traffic while yielding a
significant gain reaching up to 63% in terms of data rates as compared to the
classical (social-unaware) approach.


title: Magnetically ordered phase near transition to Bose-glass phase

abstract:
  We discuss magnetically ordered ("superfluid") phase near quantum transition
to Bose-glass phase in a simple modeling system, Heisenberg antiferromagnet in
spatial dimension $d>2$ in external magnetic field with disorder in exchange
coupling constants. Our analytical consideration is based on hydrodynamic
description of long-wavelength excitations. Results obtained are valid in the
entire critical region near the quantum critical point (QCP) allowing to
describe a possible crossover from one critical behavior to another. We
demonstrate that the system behaves in full agreement with predictions by
Fisher et al.\ (Phys.\ Rev.\ B {\bf 40}, 546 (1989)) in close vicinity of QCP.
We find as an extension to that analysis that the anomalous dimension
$\eta=2-d$ and $\beta=\nu d/2$, where $\beta$ and $\nu$ are critical exponents
of the order parameter and the correlation length, respectively. The density of
states per spin of low-energy localized excitations are found to be independent
of $d$ ("superuniversal"). We show that many recent experimental and numerical
results obtained in various 3D systems can be described by our formulas using
percolation critical exponents. Then, it is a possibility that a percolation
critical regime arises in the ordered phase in some 3D systems not very close
to QCP.


title:
Low-Complexity Hybrid Linear/Tomlinson-Harashima Precoding for Downlink
  Large-Scale MU-MIMO Systems

abstract:
  In this paper, we propose a novel low-complexity hybrid
linear/Tomlinson-Harashima precoder (H-L-THP) for downlink large-scale
multiuser multiple-input multiple-output (MU-MIMO) systems. The proposed
precoder comprises an inner linear precoder which utilizes only the second
order statistics of the channel state information (CSI) and outer THPs which
use the instantaneous overall CSI of the cascade of the actual channel and the
inner precoder. The user terminals are divided into groups, where for each
group a THP successively mitigates the intra-group interference, whereas the
inter-group interference is canceled by the inner linear precoder. Our
simulation results show that the bit error rate (BER) of the proposed H-L-THP
precoder is close to that of the conventional THP precoder, and is
substantially lower than the BER of the commonly used regularized zero-forcing
(RZF) precoder. Moreover, we derive exact expressions for the computational
complexity of the proposed H-L-THP precoder in terms of the required numbers of
floating-point operations. These results reveal that the proposed H-L-THP
precoder has a much lower computational complexity than the conventional THP
and RZF precoders, and is thus an excellent candidate for practical
implementations.


title: Observability of Higgs Mode in a system without Lorentz invariance

abstract:
  We study the observability of the Higgs mode in BEC-BCS crossover. The
observability of Higgs mode is investigated by calculating the spectral weight
functions of the amplitude fluctuation below the critical transition
temperature. At zero temperature, we find that there are two sharp peaks on the
spectral function of the amplitude fluctuation attributed to Goldstone and
Higgs modes respectively. As the system goes from BCS to BEC side, there is
strong enhancement of spectral weight transfer from the Higgs to Goldstone
mode. However, even at the unitary regime where the Lorentz invariance is lost,
the sharp feature of Higgs mode still exists. We specifically calculate the
finite temperature spectral function of amplitude fluctuation at the unitary
regime and show that the Higgs mode is observable at the temperature that
present experiments can reach.


title:
The Dirichlet problem for p-harmonic functions with respect to arbitrary
  compactifications

abstract:
  We study the Dirichlet problem for p-harmonic functions on metric spaces with
respect to arbitrary compactifications. A particular focus is on the Perron
method, and as a new approach to the invariance problem we introduce
Sobolev-Perron solutions. We obtain various resolutivity and invariance
results, and also show that most functions that have earlier been proved to be
resolutive are in fact Sobolev-resolutive. We also introduce (Sobolev)-Wiener
solutions and harmonizability in this nonlinear context, and study their
connections to (Sobolev)-Perron solutions, partly using Q-compactifications.


title: Quantum Thermal Machines Fuelled by Vacuum Forces

abstract:
  We propose a quantum thermal machine composed of two nanomechanical
resonators (NMR) (two membranes suspended over a trench in a substrate), placed
a few $\mu$m from each other. The quantum thermodynamical cycle is powered by
the Casimir interaction between the resonators and the working fluid is the
polariton resulting from the mixture of the flexural (out-of-plane) vibrations.
With the help of piezoelectric cells, we select and sweep the polariton
frequency cyclically. We calculate the performance of the proposed quantum
thermal machines and show that high efficiencies are achieved thanks to (i) the
strong coupling between the resonators and (ii) the large difference between
the membrane stiffnesses. Our findings can be of particular importance for
applications in nanomechanical technologies where a sensitive control of
temperature is needed.


title: Sufficient conditions for Hamiltonian cycles in bipartite digraphs

abstract:
  We prove two sharp sufficient conditions for hamiltonian cycles in balanced
bipartite directed graph. Let $D$ be a strongly connected balanced bipartite
directed graph of order $2a$. Let $x,y$ be distinct vertices in $D$. $\{x,y\}$
dominates a vertex $z$ if $x\rightarrow z$ and $y\rightarrow z$; in this case,
we call the pair $\{x,y\}$ dominating.
  (i) {\it If $a\geq 4$ and $max \{d(x), d(y)\}\geq 2a-1$ for every dominating
pair of vertices $\{x,y\}$, then either $D$ is hamiltonian or $D$ is isomorphic
to one exceptional digraph of order eight.}
  (ii) {\it If $a\geq 5$ and $d(x)+d(y)\geq 4a-3$ for every dominating pair of
vertices $\{x,y\}$, then $D$ is hamiltonian.}
  The first result improves a theorem of R. Wang (arXiv:1506.07949 [math.CO]),
the second result, in particular, establishes a conjecture due to Bang-Jensen,
Gutin and Li (J. Graph Theory , 22(2), 1996) for strongly connected balanced
bipartite digraphs of order at least ten.


title: System Level Performance Evaluation of LTE-V2X Network

abstract:
  Vehicles are among the fastest growing type of connected devices. Therefore,
there is a need for Vehicle-to-Everything (V2X) communication i.e. passing of
information from a Vehicle-to-Vehicle (V2V) or Vehicle-to-Infrastructure (V2I)
and vice versa. In this paper, the main focus is on the communication between
vehicles and road side units (RSUs) commonly referred to as V2I communication
in a multi-lane freeway scenario. Moreover, we analyze network related
bottlenecks such as the maximum number of vehicles that can be supported when
coverage is provided by the Long Term Evolution Advanced (LTE-A) network. The
performance evaluation is assessed through extensive system-level simulations.
Results show that new resource allocation and interference mitigation
techniques are needed in order to achieve the required high reliability
requirements, especially when network load is high.


title: Pricing Bermudan options under local L\'evy models with default

abstract:
  We consider a defaultable asset whose risk-neutral pricing dynamics are
described by an exponential L\'evy-type martingale. This class of models allows
for a local volatility, local default intensity and a locally dependent L\'evy
measure. We present a pricing method for Bermudan options based on an
analytical approximation of the characteristic function combined with the COS
method. Due to a special form of the obtained characteristic function the price
can be computed using a Fast Fourier Transform-based algorithm resulting in a
fast and accurate calculation. The Greeks can be computed at almost no
additional computational cost. Error bounds for the approximation of the
characteristic function as well as for the total option price are given.


title: Verifying Buchberger's Algorithm in Reduction Rings

abstract:
  In this paper we present the formal, computer-supported verification of a
functional implementation of Buchberger's critical-pair/completion algorithm
for computing Gr\"obner bases in reduction rings. We describe how the algorithm
can be implemented and verified within one single software system, which in our
case is the Theorema system.
  In contrast to existing formal correctness proofs of Buchberger's algorithm
in other systems, e. g. Coq and ACL2, our work is not confined to the classical
setting of polynomial rings over fields, but considers the much more general
setting of reduction rings; this, naturally, makes the algorithm more
complicated and the verification more difficult.
  The correctness proof is essentially based on some non-trivial results from
the theory of reduction rings, which we formalized and formally proved as well.
This formalization already consists of more than 800 interactively proved
lemmas and theorems, making the elaboration an extensive example of
higher-order theory exploration in Theorema.


title: Regularisation effects of nonlinear semigroups

abstract:
  One introduces natural and simple methods to deduce
$L^{s}$-$L^{\infty}$-re\-gularisation estimates for $1\le s< \infty$ of
nonlinear semigroups holding uniformly for all time with sharp exponents from
natural Gagliardo-Nirenberg inequalities. From $L^{q}$-$L^{r}$
Gagliardo-Nirenberg inequalities, $1\le q, r\le \infty$, one deduces
$L^{q}$-$L^{r}$ estimates for the semigroup. New nonlinear interpolation
techniques of independent interest are introduced in order to extrapolate such
estimates to $L^{\tilde{q}}$-$L^{\infty}$ estimates for some $\tilde{q}$, $1\le
\tilde{q}<\infty$. Finally one is able to extrapolate to $L^{s}$-$L^{\infty}$
estimates for $1\le s<q$. The theory developed in this monograph allows to work
with minimal regularity assumptions on solutions of nonlinear parabolic
boundary value problems as illustrated in a plethora of examples including
nonlocal diffusion processes.


title: I/O-Efficient Generation of Massive Graphs Following the LFR Benchmark

abstract:
  LFR is a popular benchmark graph generator used to evaluate community
detection algorithms. We present EM-LFR, the first external memory algorithm
able to generate massive complex networks following the LFR benchmark. Its most
expensive component is the generation of random graphs with prescribed degree
sequences which can be divided into two steps: the graphs are first
materialized deterministically using the Havel-Hakimi algorithm, and then
randomized. Our main contributions are EM-HH and EM-ES, two I/O-efficient
external memory algorithms for these two steps. We also propose EM-CM/ES, an
alternative sampling scheme using the Configuration Model and rewiring steps to
obtain a random simple graph. In an experimental evaluation we demonstrate
their performance; our implementation is able to handle graphs with more than
37 billion edges on a single machine, is competitive with a massive parallel
distributed algorithm, and is faster than a state-of-the-art internal memory
implementation even on instances fitting in main memory. EM-LFR's
implementation is capable of generating large graph instances orders of
magnitude faster than the original implementation. We give evidence that both
implementations yield graphs with matching properties by applying clustering
algorithms to generated instances. Similarly, we analyse the evolution of graph
properties as EM-ES is executed on networks obtained with EM-CM/ES and find
that the alternative approach can accelerate the sampling process.


title: Information Theory and Statistical Mechanics Revisited

abstract:
  We derive Bose-Einstein statistics and Fermi-Dirac statistics by Principle of
Maximum Entropy applied to two families of entropy functions different from the
Boltzmann-Gibbs-Shannon entropy. These entropy functions are identified with
special cases of modified Naudts' $\phi$-entropy.


title: MetaGrad: Multiple Learning Rates in Online Learning

abstract:
  In online convex optimization it is well known that certain subclasses of
objective functions are much easier than arbitrary convex functions. We are
interested in designing adaptive methods that can automatically get fast rates
in as many such subclasses as possible, without any manual tuning. Previous
adaptive methods are able to interpolate between strongly convex and general
convex functions. We present a new method, MetaGrad, that adapts to a much
broader class of functions, including exp-concave and strongly convex
functions, but also various types of stochastic and non-stochastic functions
without any curvature. For instance, MetaGrad can achieve logarithmic regret on
the unregularized hinge loss, even though it has no curvature, if the data come
from a favourable probability distribution. MetaGrad's main feature is that it
simultaneously considers multiple learning rates. Unlike previous methods with
provable regret guarantees, however, its learning rates are not monotonically
decreasing over time and are not tuned based on a theoretically derived bound
on the regret. Instead, they are weighted directly proportional to their
empirical performance on the data using a tilted exponential weights master
algorithm.


title: Vertex Operators for Irregular Conformal Blocks: Supersymmetric Case

abstract:
  We construct supersymmetric irregular vertex operators of arbitrary rank,
appearing in the colliding limit of primary fields. We find that the structure
of the supersymmetric irregular vertices differs significantly from the bosonic
case: upon supersymmetrization, the irregular operators are no longer the
eigenstates of positive Virasoro and $W_N$ generators but block-diagonalize
them. We relate the block-diagonal structure of the irregular vertices to
contributions of the Ramond sector to the colliding limit.


title: Hidden cusps

abstract:
  This paper investigates a situation pointed out in a recent paper, in which a
non-singular change of assembly mode of a planar 2-RPR-PR parallel manipulator
was realized by encircling a point of multiplicity 4. It is shown that this
situation is, in fact, a non-generic one and gives rise to cusps under a small
perturbation. Furthermore , we show that, for a large class of singularities of
multiplicity 4, there are only two types of stable singularities occurring in a
small perturbation: these two types are given by the complex square mapping and
the quarto mapping. Incidentally , this paper confirms the fact that,
generically, a local non-singular change of solution must be accomplished by
encircling a cusp point.


title: Factor Models for Cancer Signatures

abstract:
  We present a novel method for extracting cancer signatures by applying
statistical risk models (http://ssrn.com/abstract=2732453) from quantitative
finance to cancer genome data. Using 1389 whole genome sequenced samples from
14 cancers, we identify an "overall" mode of somatic mutational noise. We give
a prescription for factoring out this noise and source code for fixing the
number of signatures. We apply nonnegative matrix factorization (NMF) to genome
data aggregated by cancer subtype and filtered using our method. The resultant
signatures have substantially lower variability than those from unfiltered
data. Also, the computational cost of signature extraction is cut by about a
factor of 10. We find 3 novel cancer signatures, including a liver cancer
dominant signature (96% contribution) and a renal cell carcinoma signature (70%
contribution). Our method accelerates finding new cancer signatures and
improves their overall stability. Reciprocally, the methods for extracting
cancer signatures could have interesting applications in quantitative finance.


title:
Enabling Relaying Over Heterogeneous Backhauls in the Uplink of Wireless
  Femtocell Networks

abstract:
  In this paper, we develop novel two-tier interference management strategies
that enable macrocell users (MUEs) to improve their performance, with the help
of open-access femtocells. To this end, we propose a rate-splitting technique
using which the MUEs optimize their uplink transmissions by dividing their
signals into two types: a coarse message that is intended for direct
transmission to the macrocell base station and a fine message that is decoded
by a neighboring femtocell and subsequently relayed over a heterogeneous
(wireless/wired) backhaul. For deploying the proposed technique, we formulate a
non-cooperative game between the MUEs in which each MUE can decide on its
relaying femtocell while maximizing a utility function that captures both the
achieved throughput and the expected backhaul delay. Simulation results show
that the proposed approach yields up to 125% rate improvement and up to 2 times
delay reduction with wired backhaul and, 150% rate improvement and up to 10
times delay reduction with wireless backhaul, relative to classical
interference management approaches, with no cross-tier cooperation.


title: Magneto-Elastic Coupling in a potential ferromagnetic 2D Atomic Crystal

abstract:
  Cr2Ge2Te6 has been of interest for decades, as it is one of only a few
naturally forming ferromagnetic semiconductors. Recently, this material has
been revisited due to its potential as a 2 dimensional semiconducting
ferromagnet and a substrate to induce anomalous quantum Hall states in
topological insulators. However, many relevant properties of Cr2Ge2Te6 still
remain poorly understood, especially the spin-phonon coupling crucial to
spintronic, multiferrioc, thermal conductivity, magnetic proximity and the
establishment of long range order on the nanoscale. We explore the interplay
between the lattice and magnetism through high resolution micro-Raman
scattering measurements over the temperature range from 10 K to 325 K. Strong
spin-phonon coupling effects are confirmed from multiple aspects: two low
energy modes splits in the ferromagnetic phase, magnetic quasielastic
scattering in paramagnetic phase, the phonon energies of three modes show clear
upturn below Tc, and the phonon linewidths change dramatically below Tc as
well. Our results provide the first demonstration of spin-phonon coupling in a
potential 2 dimensional atomic crystal.