title:
Second-harmonic focusing by nonlinear turbid medium via feedback-based
  wavefront shaping

abstract:
  Scattering has usually be considered as detrimental for optical focusing or
imaging. Recently, more and more research has shown that strongly scattering
materials can be utilized to focus coherent light by controlling or shaping the
incident light. Here, purposeful focusing of second-harmonic waves, which are
generated and scattered from nonlinear turbid media via feedback-based
wavefront shaping is presented. This work shows a flexible manipulation of both
disordered linear and nonlinear scattering signals, indicating more
controllable degrees of freedom for the description of turbid media. This
technique also provides a possible way to an efficient transmission of
nonlinear signal at a desired location in the form of a focal point or other
patterns. With the combination of random nonlinear optics and wavefront shaping
methods, more interesting applications are expected in the future, such as
nonlinear transmission matrix, multi-frequency imaging and phase-matching-free
nonlinear optics.


title: Shift-Reduce Constituent Parsing with Neural Lookahead Features

abstract:
  Transition-based models can be fast and accurate for constituent parsing.
Compared with chart-based models, they leverage richer features by extracting
history information from a parser stack, which spans over non-local
constituents. On the other hand, during incremental parsing, constituent
information on the right hand side of the current word is not utilized, which
is a relative weakness of shift-reduce parsing. To address this limitation, we
leverage a fast neural model to extract lookahead features. In particular, we
build a bidirectional LSTM model, which leverages the full sentence information
to predict the hierarchy of constituents that each word starts and ends. The
results are then passed to a strong transition-based constituent parser as
lookahead features. The resulting parser gives 1.3% absolute improvement in WSJ
and 2.3% in CTB compared to the baseline, given the highest reported accuracies
for fully-supervised parsing.


title: Pulse sequences for suppressing leakage in single-qubit gate operations

abstract:
  Many realizations of solid-state qubits involve couplings to leakage states
lying outside the computational subspace, posing a threat to high-fidelity
quantum gate operations. Mitigating leakage errors is especially challenging
when the coupling strength is unknown, e.g., when it is caused by noise. Here
we show that simple pulse sequences can be used to strongly suppress leakage
errors for a qubit embedded in a three-level system. As an example, we apply
our scheme to the recently proposed charge quadrupole (CQ) qubit for quantum
dots. These results provide a solution to a key challenge for fault-tolerant
quantum computing with solid-state elements.


title: Ab initio calculation of energy levels for phosphorus donors in silicon

abstract:
  The s manifold energy levels for phosphorus donors in silicon are important
input parameters for the design and modelling of electronic devices on the
nanoscale. In this paper we calculate these energy levels from first principles
using density functional theory. The wavefunction of the donor electron's
ground state is found to have a form that is similar to an atomic s orbital,
with an effective Bohr radius of 1.8 nm. The corresponding binding energy of
this state is found to be 41 meV, which is in good agreement with the currently
accepted value of 45.59 meV. We also calculate the energies of the excited
1s(T) and 1s(E) states, finding them to be 32 and 31 meV respectively. These
results constitute the first ab initio confirmation of the s manifold energy
levels for phosphorus donors in silicon.


title: Application of Microgrids in Supporting Distribution Grid Flexibility

abstract:
  Distributed renewable energy resources have attracted significant attention
in recent years due to the falling cost of the renewable energy technology,
extensive federal and state incentives, and the application in improving
load-point reliability. This growing proliferation, however, is changing the
traditional consumption load curves by adding considerable levels of
variability and further challenging the electricity supply-demand balance. In
this paper, the application of microgrids in effectively capturing the
distribution network net load variability, caused primarily by the prosumers,
is investigated. Microgrids provide a viable and localized solution to this
challenge while removing the need for costly investments by the electric
utility on reinforcing the existing electricity infrastructure. A
flexibility-oriented microgrid optimal scheduling model is proposed and
developed to coordinate the microgrid net load with the aggregated
consumers/prosumers net load in the distribution network with a focus on
ramping issues. The proposed coordination is performed to capture both
inter-hour and intra-hour net load variabilities. Numerical simulations on a
test distribution feeder with one microgrid and several consumers and prosumers
exhibit the effectiveness of the proposed model.


title:
Reliability study of series and parallel systems of heterogeneous
  component lifetimes under proportional odds model

abstract:
  In this paper, we investigate various stochastic orderings for series and
parallel systems with independent and heterogeneous components having lifetimes
following the proportional odds model. We also investigate comparisons between
system with heterogeneous components and that with homogeneous components. This
paper also studies relative ageing orders for two systems in the framework of
components having lifetimes following the proportional odds model.


title:
Mechanisms for strong anisotropy of in-plane g-factors in hole based
  quantum point contacts

abstract:
  In-plane hole g-factors measured in quantum point contacts based on p-type
heterostructures strongly depend on the orientation of the magnetic field with
respect to the electric current. This effect, first reported a decade ago and
confirmed in a number of publications, has remained an open problem. In this
work, we present systematic experimental studies to disentangle different
mechanisms contributing to the effect and develop the theory which describes it
successfully. We show that there is a new mechanism for the anisotropy related
to the existence of an additional $B_+k_-^4\sigma_+$ effective Zeeman
interaction for holes, which is kinematically different from the standard
single Zeeman term $B_-k_-^2\sigma_+$ considered until now.


title: Quantum friction: environment engineering perspectives

abstract:
  We prove a generalization of the Lindblad's fundamental no-go result: A
quantum system cannot be completely frozen and, in some cases, even thermalized
via translationally invariant dissipation -- the quantum friction.
Nevertheless, a practical methodology is proposed for engineering nearly
perfect quantum analogs of classical friction within the Doppler cooling
framework. These findings pave the way for hallmark dissipative engineering
(e.g. nonreciprocal couplings) with atoms and molecules.


title: Equilibrium and dynamic pleating of a crystalline bonded network

abstract:
  We describe a phase transition that gives rise to structurally non-trivial
states in a two-dimensional ordered network of particles connected by harmonic
bonds. Monte Carlo simulations reveal that the network supports, apart from the
homogeneous phase, a number of heterogeneous "pleated" phases, which can be
stabilised by an external field. This field is conjugate to a global collective
variable quantifying "non-affineness", i.e.~the deviation of local particle
displacements from local affine deformation. In the pleated phase, stress is
localised in ordered rows of pleats and eliminated from the rest of the
lattice. The {\em kinetics} of the phase transition is unobservably slow in
molecular dynamics simulation near coexistence, due to very large free energy
barriers. When the external field is increased further to lower these barriers,
the network exhibits rich dynamic behaviour: it transforms into a {\em
metastable} phase with the stress now localised in a {\em disordered}
arrangement of pleats. The pattern of pleats shows ageing dynamics and slow
relaxation to equilibrium. Our predictions may be checked by experiments on
tethered colloidal solids in dynamic laser traps.


title:
Not Call Me Cellular Any More: The Emergence of Scaling Law, Fractal
  Patterns and Small-World in Wireless Networks

abstract:
  In conventional cellular networks, for base stations (BSs) that are deployed
far away from each other, it is general to assume them to be mutually
independent. Nevertheless, after long-term evolution of cellular networks in
various generations, this assumption no longer holds. Instead, the BSs, which
seem to be gradually deployed by operators in a service-oriented manner, have
embedded many fundamentally distinctive features in their locations, coverage
and traffic loading. These features can be leveraged to analyze the intrinsic
pattern in BSs and even human community. In this paper, according to
large-scale measurement datasets, we build up a correlation model of BSs by
utilizing one of the most important features, ie., spatial traffic. Coupling
with the theory of complex networks, we make further analysis on the structure
and characteristics of this traffic load correlation model. Numerical results
show that the degree distribution follows scale-free property. Also the
datasets unveil the characteristics of fractality and small-world. Furthermore,
we apply collective influence (CI) algorithm to localize the influential base
stations and demonstrate that some low-degree BSs may outrank BSs with larger
degree.


title: Guided Open Vocabulary Image Captioning with Constrained Beam Search

abstract:
  Existing image captioning models do not generalize well to out-of-domain
images containing novel scenes or objects. This limitation severely hinders the
use of these models in real world applications dealing with images in the wild.
We address this problem using a flexible approach that enables existing deep
captioning architectures to take advantage of image taggers at test time,
without re-training. Our method uses constrained beam search to force the
inclusion of selected tag words in the output, and fixed, pretrained word
embeddings to facilitate vocabulary expansion to previously unseen tag words.
Using this approach we achieve state of the art results for out-of-domain
captioning on MSCOCO (and improved results for in-domain captioning). Perhaps
surprisingly, our results significantly outperform approaches that incorporate
the same tag predictions into the learning algorithm. We also show that we can
significantly improve the quality of generated ImageNet captions by leveraging
ground-truth labels.


title: Principal curvatures and parallel surfaces of wave fronts

abstract:
  We give criteria for which a principal curvature becomes a bounded
$C^\infty$-function at non-degenerate singular points of wave fronts by using
geometric invariants. As applications, we study singularities of parallel
surfaces and extended distance squared functions of wave fronts. Moreover, we
relate these singularities to some geometric invariants of fronts.


title: Most Boson quantum states are almost maximally entangled

abstract:
  The geometric measure of entanglement $E$ of an $m$ qubit quantum state takes
maximal possible value $m$. In previous work of Gross, Flammia, and Eisert, it
was shown that $E \ge m-O(\log m)$ with high probability as $m\to\infty$. They
showed, as a consequence, that the vast majority of states are too entangled to
be computationally useful. In this paper, we show that for $m$ qubit {\em
Boson} quantum states (those that are actually available in current designs for
quantum computers), the maximal possible geometric measure of entanglement is
$\log_2 m$, opening the door to many computationally universal states. We
further show the corresponding concentration result that $E \ge \log_2 m -
O(\log \log m)$ with high probability as $m\to\infty$. We extend these results
also to $m$-mode $n$-bit Boson quantum states.


title:
Production of neutron-rich isotopes around N=126 in multinucleon
  transfer reactions

abstract:
  The multinucleon transfer reactions has been investigated within the
dinuclear system model. The nucleon transfer is coupled to the dissipation of
relative motion energy and angular momentum by solving a set of microscopically
derived master equations. A barrier distribution approach is implemented in the
model in order to including the contributions of different orientations and
dynamical effects. The available data of fragment production via multinucleon
transfer reactions could be understood with the model for the reactions of
$^{136}$Xe + $^{198}$Pt/$^{208}$Pb near Coulomb barrier energies. It is found
that the production of heavy neutron-rich nuclei weakly depends on the incident
energy. However, the yields of proton-rich nuclei increase with the incident
energy.


title: A Generalization of APN Functions for Odd Characteristic

abstract:
  Almost perfect nonlinear (APN) functions on finite fields of characteristic
two have been studied by many researchers. Such functions have useful
properties and applications in cryptography, finite geometries and so on.
However APN functions on finite fields of odd characteristic do not satisfy
desired properties. In this paper, we modify the definition of APN function in
the case of odd characteristic, and study its properties.


title:
Adaptive estimation of a time-varying phase with a power-law spectrum
  via continuous squeezed states

abstract:
  When measuring a time-varying phase, the standard quantum limit and
Heisenberg limit as usually defined, for a constant phase, do not apply. If the
phase has Gaussian statistics and a power-law spectrum $1/|\omega|^p$ with
$p>1$, then the generalized standard quantum limit and Heisenberg limit have
recently been found to have scalings of $1/{\cal N}^{(p-1)/p}$ and $1/{\cal
N}^{2(p-1)/(p+1)}$, respectively, where ${\cal N}$ is the mean photon flux. We
show that this Heisenberg scaling can be achieved via adaptive measurements on
squeezed states. We predict the experimental parameters analytically, and test
them with numerical simulations. Previous work had considered the special case
of $p=2$.


title: Predicting Changes in Affective States using Neural Networks

abstract:
  Knowledge of patients affective state could prove to be crucial for
health-care professionals in both diagnosis and treatment, however, this
requires patients to report how they feel. In practice the sampling rate of
affective states needs to be kept low, in order to ensure that the patients can
rest. Furthermore using traditional methods of measuring affective states, is
not always possible, e.g. patients can be incapable of verbal communications.
In this study we explore the prediction of peoples self-reported affective
state by measuring multiple physiological signals. We use different Neural
networks (NN) setups and compare with different multiple linear regression
(MLR) setups for prediction of changes in affective states. The results showed
that NN and MLR predicted the change in affective states with accuracies of
91.88% and 89.10%, respectively.


title: Active Search for Sparse Signals with Region Sensing

abstract:
  Autonomous systems can be used to search for sparse signals in a large space;
e.g., aerial robots can be deployed to localize threats, detect gas leaks, or
respond to distress calls. Intuitively, search algorithms may increase
efficiency by collecting aggregate measurements summarizing large contiguous
regions. However, most existing search methods either ignore the possibility of
such region observations (e.g., Bayesian optimization and multi-armed bandits)
or make strong assumptions about the sensing mechanism that allow each
measurement to arbitrarily encode all signals in the entire environment (e.g.,
compressive sensing). We propose an algorithm that actively collects data to
search for sparse signals using only noisy measurements of the average values
on rectangular regions (including single points), based on the greedy
maximization of information gain. We analyze our algorithm in 1d and show that
it requires $\tilde{O}(\frac{n}{\mu^2}+k^2)$ measurements to recover all of $k$
signal locations with small Bayes error, where $\mu$ and $n$ are the signal
strength and the size of the search space, respectively. We also show that
active designs can be fundamentally more efficient than passive designs with
region sensing, contrasting with the results of Arias-Castro, Candes, and
Davenport (2013). We demonstrate the empirical performance of our algorithm on
a search problem using satellite image data and in high dimensions.


title:
Alleviating Overfitting for Polysemous Words for Word Representation
  Estimation Using Lexicons

abstract:
  Though there are some works on improving distributed word representations
using lexicons, the improper overfitting of the words that have multiple
meanings is a remaining issue deteriorating the learning when lexicons are
used, which needs to be solved. An alternative method is to allocate a vector
per sense instead of a vector per word. However, the word representations
estimated in the former way are not as easy to use as the latter one. Our
previous work uses a probabilistic method to alleviate the overfitting, but it
is not robust with a small corpus. In this paper, we propose a new neural
network to estimate distributed word representations using a lexicon and a
corpus. We add a lexicon layer in the continuous bag-of-words model and a
threshold node after the output of the lexicon layer. The threshold rejects the
unreliable outputs of the lexicon layer that are less likely to be the same
with their inputs. In this way, it alleviates the overfitting of the polysemous
words. The proposed neural network can be trained using negative sampling,
which maximizing the log probabilities of target words given the context words,
by distinguishing the target words from random noises. We compare the proposed
neural network with the continuous bag-of-words model, the other works
improving it, and the previous works estimating distributed word
representations using both a lexicon and a corpus. The experimental results
show that the proposed neural network is more efficient and balanced for both
semantic tasks and syntactic tasks than the previous works, and robust to the
size of the corpus.


title:
Development of a hybrid learning system based on SVM, ANFIS and domain
  knowledge: DKFIS

abstract:
  This paper presents the development of a hybrid learning system based on
Support Vector Machines (SVM), Adaptive Neuro-Fuzzy Inference System (ANFIS)
and domain knowledge to solve prediction problem. The proposed two-stage Domain
Knowledge based Fuzzy Information System (DKFIS) improves the prediction
accuracy attained by ANFIS alone. The proposed framework has been implemented
on a noisy and incomplete dataset acquired from a hydrocarbon field located at
western part of India. Here, oil saturation has been predicted from four
different well logs i.e. gamma ray, resistivity, density, and clay volume. In
the first stage, depending on zero or near zero and non-zero oil saturation
levels the input vector is classified into two classes (Class 0 and Class 1)
using SVM. The classification results have been further fine-tuned applying
expert knowledge based on the relationship among predictor variables i.e. well
logs and target variable - oil saturation. Second, an ANFIS is designed to
predict non-zero (Class 1) oil saturation values from predictor logs. The
predicted output has been further refined based on expert knowledge. It is
apparent from the experimental results that the expert intervention with
qualitative judgment at each stage has rendered the prediction into the
feasible and realistic ranges. The performance analysis of the prediction in
terms of four performance metrics such as correlation coefficient (CC), root
mean square error (RMSE), and absolute error mean (AEM), scatter index (SI) has
established DKFIS as a useful tool for reservoir characterization.


title: Some remarks on log surfaces

abstract:
  Fujino and Tanaka established the minimal model theory for $\mathbb
Q$-factorial log surfaces in characteristic $0$ and $p$, respectively. We prove
that every intermediate surface has only log terminal singularities if we run
the minimal model program starting with a pair consisting of a smooth surface
and a boundary $\mathbb R$-divisor. We further show that such a property does
not hold if the initial surface is singular.


title:
On fluctuation theory for spectrally negative Levy processes with
  Parisian reflection below, and applications

abstract:
  As well known, all functionals of a Markov process may be expressed in terms
of the generator operator, modulo some analytic work. In the case of spectrally
negative Markov processes however, it is conjectured that everything can be
expressed in a more direct way using the $W$ scale function which intervenes in
the two-sided first passage problem, modulo performing various integrals. This
conjecture arises from work on Levy processes \cite{AKP,Pispot,APP,Iva,IP,
ivanovs2013potential,AIZ,APY}, where the $W$ scale function has explicit
Laplace transform, and is therefore easily computable; furthermore it was found
in the papers above that a second scale function $Z$ introduced in \cite{AKP}
greatly simplifies first passage laws, especially for reflected processes.
  This paper gathers a collection of first passage formulas for spectrally
negative Parisian L\'evy processes, expressed in terms of $W,Z$ which may serve
as an "instruction kit" for computing quantities of interest in applications,
for example in risk theory and mathematical finance.
  To illustrate the usefulness of our list, we construct a new index for the
valuation of financial companies modeled by spectrally negative L\'evy
processes, based on a Dickson-Waters modifications of the de Finetti optimal
expected discounted dividends objective. We offer as well an index for the
valuation of conglomerates of financial companies.
  An implicit question arising is to investigate analog results for other
classes of spectrally negative Markovian processes.


title: Krawtchouk-Griffiths Systems II: As Bernoulli Systems

abstract:
  We call Krawtchouk-Griffiths systems, KG-systems, systems of multivariate
polynomials orthogonal with respect to corresponding multinomial distributions.
The original Krawtchouk polynomials are orthogonal with respect to a binomial
distribution. Here we present a Fock space construction with raising and
lowering operators. The operators of "multiplication by X" are found in terms
of boson operators and corresponding recurrence relations presented. The
Riccati partial differential equations for the differentiation operators,
Berezin transform and associated partial differential equations are found.
These features provide the specifications for a Bernoulli system as a
quantization formulation of multivariate Krawtchouk polynomials.


title: Graphs with two main and two plain eigenvalues

abstract:
  In this paper, we introduce the concepts of the plain eigenvalue, the
main-plain index and the refined spectrum of graphs. We focus on the graphs
with two main and two plain eigenvalues and give some characterizations of
them.


title:
Two-fluid model of the pulsar magnetosphere represented as an
  axisymmetric force-free dipole

abstract:
  Based on the exact dipolar solution of the pulsar equation the
self-consistent two-fluid model of the pulsar magnetosphere is developed. We
concentrate on the low-mass limit of the model, taking into account the
radiation damping. As a result, we obtain the particle distributions sustaining
the dipolar force-free configuration of the pulsar magnetosphere in case of a
slight velocity shear of the electron and positron components. Over most part
of the force-free region, the particles follow the poloidal magnetic field
lines, with the azimuthal velocities being small. Close to the Y-point,
however, the particle motion is chiefly azimuthal and the Lorentz-factor grows
unrestrictedly. This may result in the very-high-energy emission from the
vicinity of the Y-point and may also imply the magnetocentrifugal formation of
a jet. As for the first-order quantities, the longitudinal accelerating
electric field is found to change the sign, hinting at coexistence of the polar
and outer gaps. Besides that, the components of the plasma conductivity tensor
are derived and the low-mass analogue of the pulsar equation is formulated as
well.


title: The Effect of Galactic Feedback on Gas Accretion and Wind Recycling

abstract:
  In the absence of galactic winds, the rate at which gas accretes onto
galaxies is determined by the gravitational potential and by radiative cooling.
However, outflows driven by supernovae and active galactic nuclei not only
eject gas from galaxies, but also prevent gas from accreting in the first
place. Furthermore, gas previously ejected from a galaxy can re-accrete onto
(the same or a different) galaxy. Because this gas has a high metallicity, its
cooling rate is relatively high, which will increase its chances to re-accrete.
This complex interplay between gas inflows and outflows is discussed in this
chapter. Wind recycling is found to be an important process that fuels galaxies
at late times and the recycled gas has different properties than gas accreting
for the first time. Quantitative conclusions, however, vary between studies,
because the amount of wind recycling is dependent on the details of the
feedback model. We discuss these differences, known caveats, and ways to make
progress in understanding how galaxies are fed at low redshift.


title:
Temporal characteristics and energy deposition of pulsating auroral
  patches

abstract:
  We present a careful statistical analysis of pulsating aurora (PA) using
all-sky green line (557.7 nm) images obtained at 3.3 Hz. Six well-defined
individual PA patches are identified and extracted using a contouring
technique. Quantitative parameters such as the patch duration (on-time and
off-time), peak intensity, and integrated intensity are determined for each
patch and each pulsation. The resulting characteristics serve as strict
observational constraints that any of the many competing theories attempting to
explain PA must predict. The purpose of this paper is to determine the
characteristics of PA patches in order to provide better observational
constraints on the suggested mechanisms. All aspects of the temporal behavior
of the individual patches appear to be erratic. Historically, PA has been
defined very loosely and we argue that the use of the term "pulsating" is
inappropriate since our findings and other published results are not regularly
periodic and thus a more appropriate term may be fluctuating aurora. Further,
we find that the observational constraints do not fit well with the flow
cyclotron maser theory, which in particular is suggested to create PA patches.
There is no clear candidate of the suggested mechanisms and drivers to explain
the observational constraints set by the PA patches in a satisfactory manner.


title:
PointNet: Deep Learning on Point Sets for 3D Classification and
  Segmentation

abstract:
  Point cloud is an important type of geometric data structure. Due to its
irregular format, most researchers transform such data to regular 3D voxel
grids or collections of images. This, however, renders data unnecessarily
voluminous and causes issues. In this paper, we design a novel type of neural
network that directly consumes point clouds and well respects the permutation
invariance of points in the input. Our network, named PointNet, provides a
unified architecture for applications ranging from object classification, part
segmentation, to scene semantic parsing. Though simple, PointNet is highly
efficient and effective. Empirically, it shows strong performance on par or
even better than state of the art. Theoretically, we provide analysis towards
understanding of what the network has learnt and why the network is robust with
respect to input perturbation and corruption.


title:
Realization of high-Q/V bichromatic photonic crystal cavities defined by
  an effective Aubry-Andr\'e-Harper potential

abstract:
  We report on the design, fabrication and optical characterization of
bichromatic photonic crystal cavities in thin silicon membranes, with
resonances around 1550 nm wavelength. The cavity designs are based on a
recently proposed photonic crystal implementation of the Aubry-Andr\'e-Harper
bichromatic potential, which relies on the superposition of two one-dimensional
lattices with non-integer ratio between the periodicity constants. In photonic
crystal nanocavities, this confinement mechanism is such that optimized figures
of merit can be straightforwardly achieved, in particular an ultra-high-Q
factor and diffraction-limited mode volume. Several silicon membrane photonic
crystal nanocavities with Q-factors in the 1 million range have been realized,
as evidenced by resonant scattering. The generality of these designs and their
easy implementation and scalability make these results particularly interesting
for realizing highly performing photonic nanocavities on different materials
platforms and operational wavelengths.


title: Parallel Chromatic MCMC with Spatial Partitioning

abstract:
  We introduce a novel approach for parallelizing MCMC inference in models with
spatially determined conditional independence relationships, for which existing
techniques exploiting graphical model structure are not applicable. Our
approach is motivated by a model of seismic events and signals, where events
detected in distant regions are approximately independent given those in
intermediate regions. We perform parallel inference by coloring a factor graph
defined over regions of latent space, rather than individual model variables.
Evaluating on a model of seismic event detection, we achieve significant
speedups over serial MCMC with no degradation in inference quality.


title:
Learning to Search on Manifolds for 3D Pose Estimation of Articulated
  Objects

abstract:
  This paper focuses on the challenging problem of 3D pose estimation of a
diverse spectrum of articulated objects from single depth images. A novel
structured prediction approach is considered, where 3D poses are represented as
skeletal models that naturally operate on manifolds. Given an input depth
image, the problem of predicting the most proper articulation of underlying
skeletal model is thus formulated as sequentially searching for the optimal
skeletal configuration. This is subsequently addressed by convolutional neural
nets trained end-to-end to render sequential prediction of the joint locations
as regressing a set of tangent vectors of the underlying manifolds. Our
approach is examined on various articulated objects including human hand,
mouse, and fish benchmark datasets. Empirically it is shown to deliver highly
competitive performance with respect to the state-of-the-arts, while operating
in real-time (over 30 FPS).


title: On the Bohr inequality

abstract:
  The Bohr inequality, first introduced by Harald Bohr in 1914, deals with
finding the largest radius $r$, $0<r<1$, such that $\sum_{n=0}^\infty |a_n|r^n
\leq 1$ holds whenever $|\sum_{n=0}^\infty a_nz^n|\leq 1$ in the unit disk
$\mathbb{D}$ of the complex plane. The exact value of this largest radius,
known as the \emph{Bohr radius}, has been established to be $1/3.$ This paper
surveys recent advances and generalizations on the Bohr inequality. It
discusses the Bohr radius for certain power series in $\mathbb{D},$ as well as
for analytic functions from $\mathbb{D}$ into particular domains. These domains
include the punctured unit disk, the exterior of the closed unit disk, and
concave wedge-domains. The analogous Bohr radius is also studied for harmonic
and starlike logharmonic mappings in $\mathbb{D}.$ The Bohr phenomenon which is
described in terms of the Euclidean distance is further investigated using the
spherical chordal metric and the hyperbolic metric. The exposition concludes
with a discussion on the $n$-dimensional Bohr radius.


title:
Spontaneous symmetry breaking induced by complex fermion determinant ---
  yet another success of the complex Langevin method

abstract:
  In many interesting systems, the fermion determinant becomes complex and its
phase plays a crucial role in the determination of the vacuum. For instance, in
finite density QCD at low temperature and high density, exotic fermion
condensates are conjectured to form due to such effects. When one applies the
complex Langevin method to such a complex action system naively, one cannot
obtain the correct results because of the singular-drift problem associated
with the appearance of small eigenvalues of the Dirac operator. Here we propose
to avoid this problem by adding a fermion bilinear term to the action and
extrapolating its coefficient to zero. We test this idea in an SO(4)-invariant
matrix model with a Gaussian action and a complex fermion determinant, whose
phase is expected to induce the spontaneous breaking of the SO(4) symmetry. Our
results agree well with the previous results obtained by the Gaussian expansion
method.


title:
Communication Lower Bounds for Distributed Convex Optimization:
  Partition Data on Features

abstract:
  Recently, there has been an increasing interest in designing distributed
convex optimization algorithms under the setting where the data matrix is
partitioned on features. Algorithms under this setting sometimes have many
advantages over those under the setting where data is partitioned on samples,
especially when the number of features is huge. Therefore, it is important to
understand the inherent limitations of these optimization problems. In this
paper, with certain restrictions on the communication allowed in the
procedures, we develop tight lower bounds on communication rounds for a broad
class of non-incremental algorithms under this setting. We also provide a lower
bound on communication rounds for a class of (randomized) incremental
algorithms.


title:
Comment on Influence of induced interactions on superfluid properties of
  quasi-two-dimensional dilute Fermi gases with spin-orbit coupling

abstract:
  In an article in 2013, Caldas et al. [Phys. Rev. A 88, 023615 (2013)] derived
analytical expressions of the induced interaction within the scheme of Gorkov
and Melik-Barkhudrov in quasi-two-dimensional Fermi gases with Rashba
spin-orbit coupling (SOC). They claimed that the induced interaction is exactly
the same as the one for the case without SOC when the SOC is weak, and in the
region of strong SOC, it starts from a reduced value and then recovers the
value for the zero SOC in the limit of large SOC. We point out that their
calculations contain the critical errors and inconsistencies that significantly
affect the basis of these claims.


title: Products and tensor products of graphs and homomorphisms

abstract:
  We introduce and study, for a process P delivering edges on the Cartesian
product of the vertex sets of a given set of graphs, the P-product of these
graphs, thereby generalizing many types of product graph. Analogous to the
notion of a multilinear map (from linear algebra), a P-morphism is introduced
and utilised to define a P-tensor product of graphs, after which its uniqueness
is demonstrated.
  Congruences of graphs are utilised to show a way to handle projections (being
weak homomorphisms) in this context. Finally, the graph of a homomorphism and a
P-tensor product of homomorphisms are introduced, studied, and linked to the
P-tensor product of graphs.


title:
Variable phase propagation velocity for long-range lightning location
  system

abstract:
  The electromagnetic wave propagation velocity at low radio frequencies is an
important input parameter for lightning location systems that use time of
arrival (TOA) method. This velocity is normally fixed at or near the speed of
light. However, this study finds that the radio waves from two submarine
communication transmitters at 20.9 kHz and 23.4 kHz exhibit phase propagation
velocities that are $\sim$0.51% slower and $\sim$0.64% faster than the speed of
light as a result of sky wave contributions and ground effects. Therefore, a
novel technique with a variable phase propagation velocity is implemented for
the first time in the TOA method and applied to electric field recordings with
a long-baseline lightning location system that consists of four radio receivers
in western Europe. The lightning locations inferred from variable velocities
improve the accuracy of locations inferred from a fixed velocity by
$\sim$0.89-1.06 km when compared to the lightning locations reported by the UK
MetOffice. The normal distributions of the observed phase propagation
velocities in small geographic areas are not centered at the speed of light.
Consequently, representative velocities can be calculated for many small
geographic areas to produce a velocity map over central France where numerous
lightning discharges occurred. This map reflects the impact of sky waves and
ground effects on the calculation of lightning locations as a result of the
network configuration. It is concluded that the use of variable phase
propagation velocities mitigates the influence of sky waves and ground effects
in long-range lightning location networks.


title:
A Point Set Generation Network for 3D Object Reconstruction from a
  Single Image

abstract:
  Generation of 3D data by deep neural network has been attracting increasing
attention in the research community. The majority of extant works resort to
regular representations such as volumetric grids or collection of images;
however, these representations obscure the natural invariance of 3D shapes
under geometric transformations and also suffer from a number of other issues.
In this paper we address the problem of 3D reconstruction from a single image,
generating a straight-forward form of output -- point cloud coordinates. Along
with this problem arises a unique and interesting issue, that the groundtruth
shape for an input image may be ambiguous. Driven by this unorthodox output
form and the inherent ambiguity in groundtruth, we design architecture, loss
function and learning paradigm that are novel and effective. Our final solution
is a conditional shape sampler, capable of predicting multiple plausible 3D
point clouds from an input image. In experiments not only can our system
outperform state-of-the-art methods on single image based 3d reconstruction
benchmarks; but it also shows a strong performance for 3d shape completion and
promising ability in making multiple plausible predictions.


title: Globally Consistent Multi-People Tracking using Motion Patterns

abstract:
  Many state-of-the-art approaches to people tracking rely on detecting them in
each frame independently, grouping detections into short but reliable
trajectory segments, and then further grouping them into full trajectories.
This grouping typically relies on imposing local smoothness constraints but
almost never on enforcing more global constraints on the trajectories. In this
paper, we propose an approach to imposing global consistency by first inferring
behavioral patterns from the ground truth and then using them to guide the
tracking algorithm. When used in conjunction with several state-of-the-art
algorithms, this further increases their already good performance. Furthermore,
we propose an unsupervised scheme that yields almost similar improvements
without the need for ground truth.


title: Anyonic Haldane insulator in one dimension

abstract:
  We demonstrate numerically the existence of a nontrivial topological Haldane
phase for the one-dimensional extended ($U$-$V$) Hubbard model with a mean
density of one particle per site, not only for bosons but also for anyons,
despite a broken reflection parity symmetry. The Haldane insulator, surrounded
by superfluid, Mott insulator and density-wave phases in the $V$-$U$ parameter
plane, is protected by combined (modified) spatial-inversion and time-reversal
symmetries, which is verified within our matrix-product-state based infinite
density-matrix renormalization group scheme by analyzing generalized transfer
matrices. With regard to an experimental verification of the anyonic Haldane
insulator state the calculated asymmetry of the dynamical density structure
factor should be of particular importance.


title: SyncSpecCNN: Synchronized Spectral CNN for 3D Shape Segmentation

abstract:
  In this paper, we study the problem of semantic annotation on 3D models that
are represented as shape graphs. A functional view is taken to represent
localized information on graphs, so that annotations such as part segment or
keypoint are nothing but 0-1 indicator vertex functions. Compared with images
that are 2D grids, shape graphs are irregular and non-isomorphic data
structures. To enable the prediction of vertex functions on them by
convolutional neural networks, we resort to spectral CNN method that enables
weight sharing by parameterizing kernels in the spectral domain spanned by
graph laplacian eigenbases. Under this setting, our network, named SyncSpecCNN,
strive to overcome two key challenges: how to share coefficients and conduct
multi-scale analysis in different parts of the graph for a single shape, and
how to share information across related but different shapes that may be
represented by very different graphs. Towards these goals, we introduce a
spectral parameterization of dilated convolutional kernels and a spectral
transformer network. Experimentally we tested our SyncSpecCNN on various tasks,
including 3D shape part segmentation and 3D keypoint prediction.
State-of-the-art performance has been achieved on all benchmark datasets.


title:
Deciphering Majorana nature of sub-eV neutrinos by using their quantum
  statistical property

abstract:
  Neutrinos are the only known elementary fermions that can exhibit Majorana
nature. As per the "practical Dirac-Majorana confusion theorem" it is
impossible to distinguish between Dirac and Majorana neutrinos via any
kinematic tests when their masses are very small. However, it is also well
known that Majorana neutrino and anti-neutrino present in the final state must
obey the Fermi-Dirac statistics, irrespective of how small the mass of neutrino
is. We propose a new method to search for Majorana neutrinos by exploiting
their quantum statistical property. We analyse `effective' three-body decays of
the kind $X \to Y \nu \overline{\nu}$ (e.g.\ $X \left[ B^0 \right] \to \pi^+
\big( \to \mu^+ \nu_{\mu} \big) \mu^- \overline{\nu}_{\mu} \equiv Y \left[
\mu^+ \mu^-\right] \nu_{\mu} \overline{\nu}_{\mu}$), with 4-momenta of $X$ and
$Y$ experimentally known, such that the 4-momenta of both neutrino and
anti-neutrino can be deduced. For Majorana neutrinos the distribution of events
in the `effective' Dalitz plot for such a well chosen process would be fully
symmetric under exchange of the neutrino and anti-neutrino. Unlike the
neutrinoless double-beta decay or other lepton-number violating modes, this
distinction between Majorana and Dirac neutrinos survives even in the almost
massless neutrino limit due to the quantum statistical property.


title: Development of New 3D Pixel Sensors for Phase 2 Upgrades at LHC

abstract:
  We report on the development of new 3D pixel sensors for the Phase 2 Upgrades
at the High-Luminosity LHC (HL-LHC). To cope with the requirements of increased
pixel granularity (e.g., 50x50 or 25x100 um2 pixel size) and extreme radiation
hardness (up to a fluence of 2e16 neq cm-2), thinner 3D sensors (~100 um) with
electrodes having narrower size (~ 5 um) and reduced spacing (~ 30 um) are
considered. The paper covers TCAD simulations, as well as technological and
design aspects relevant to the first batch of these 3D sensors, that is
currently being fabricated at FBK on 6-inch wafers.


title: Spectral sum rules for conformal field theories in arbitrary dimensions

abstract:
  We derive spectral sum rules in the shear channel for conformal field
theories at finite temperature in general $d\geq 3$ dimensions. The sum rules
result from the OPE of the stress tensor at high frequency as well as the
hydrodynamic behaviour of the theory at low frequencies. The sum rule states
that a weighted integral of the spectral density over frequencies is
proportional to the energy density of the theory. We show that the
proportionality constant can be written in terms the Hofman-Maldacena variables
$t_2, t_4$ which determine the three point function of the stress tensor. For
theories which admit a two derivative gravity dual this proportionality
constant is given by $\frac{d}{2(d+1)}$. We then use causality constraints and
obtain bounds on the sum rule which are valid in any conformal field theory.
Finally we demonstrate that the high frequency behaviour of the spectral
function in the vector and the tensor channel are also determined by the
Hofman-Maldacena variables.


title:
Fast recovery of the stripe magnetic order by Mn/Fe substitution in
  F-doped LaFeAsO superconductors

abstract:
  $^{75}$As Nuclear Magnetic (NMR) and Quadrupolar (NQR) Resonance were used,
together with M\"{o}ssbauer spectroscopy, to investigate the magnetic state
induced by Mn for Fe substitutions in F-doped LaFe$_{1-x}$Mn$_{x}$AsO
superconductors. The results show that $0.5$% of Mn doping is enough to
suppress the superconducting transition temperature $T_c$ from 27 K to zero and
to recover the magnetic structure observed in the parent undoped LaFeAsO. Also
the tetragonal to orthorhombic transition of the parent compound is recovered
by introducing Mn, as evidenced by a sharp drop of the NQR frequency. The NQR
spectra also show that a charge localization process is at play in the system.
Theoretical calculations using a realistic five-band model show that
correlation-enhanced RKKY exchange interactions between nearby Mn ions
stabilize the observed magnetic order, dominated by $Q_1=(\pi,0)$ and
$Q_2=(0,\pi)$ ordering vectors. These results give compelling evidence that
F-doped LaFeAsO is a strongly correlated electron system at the verge of an
electronic instability.


title:
Predictive Clinical Decision Support System with RNN Encoding and Tensor
  Decoding

abstract:
  With the introduction of the Electric Health Records, large amounts of
digital data become available for analysis and decision support. When
physicians are prescribing treatments to a patient, they need to consider a
large range of data variety and volume, making decisions increasingly complex.
Machine learning based Clinical Decision Support systems can be a solution to
the data challenges. In this work we focus on a class of decision support in
which the physicians' decision is directly predicted. Concretely, the model
would assign higher probabilities to decisions that it presumes the physician
are more likely to make. Thus the CDS system can provide physicians with
rational recommendations. We also address the problem of correlation in target
features: Often a physician is required to make multiple (sub-)decisions in a
block, and that these decisions are mutually dependent. We propose a solution
to the target correlation problem using a tensor factorization model. In order
to handle the patients' historical information as sequential data, we apply the
so-called Encoder-Decoder-Framework which is based on Recurrent Neural Networks
(RNN) as encoders and a tensor factorization model as a decoder, a combination
which is novel in machine learning. With experiments with real-world datasets
we show that the proposed model does achieve better prediction performances.


title: In-orbit Performance of UVIT and First Results

abstract:
  The performance of the ultraviolet telescope (UVIT) on-board ASTROSAT is
reported. The performance in orbit is also compared with estimates made from
the calibrations done on the ground. The sensitivity is found to be within ~15%
of the estimates, and the spatial resolution in the NUV is found to exceed
significantly the design value of 1.8 arcsec and it is marginally better in the
FUV. Images obtained from UVIT are presented to illustrate the details revealed
by the high spatial resolution. The potential of multi-band observations in the
ultraviolet with high spatial resolution is illustrated by some results.


title: Heat capacity for systems with excited-state quantum phase transitions

abstract:
  Heat capacities of model systems with finite numbers of effective degrees of
freedom are evaluated using canonical and microcanonical thermodynamics.
Discrepancies between both approaches, which are observed even in the
infinite-size limit, are particularly large in systems that exhibit an
excited-state quantum phase transition. The corresponding irregularity of the
spectrum generates a singularity in the microcanonical heat capacity and
affects smoothly the canonical heat capacity.


title: Out-of-time-ordered density correlators in Luttinger liquids

abstract:
  Information scrambling and the butterfly effect in chaotic quantum systems
can be diagnosed by out-of-time-ordered (OTO) commutators through an
exponential growth and large late time value. We show that the latter feature
shows up in a strongly correlated many-body system, a Luttinger liquid, whose
density fluctuations we study at long and short wavelengths, both in
equilibrium and after a quantum quench. We find rich behaviour combining
robustly universal and non-universal features. The OTO commutators display
temperature and initial state independent behaviour, and grow as $t^2$ for
short times. For the short wavelength density operator, they reach a sizeable
value after the light cone only in an interacting Luttinger liquid, where the
bare excitations break up into collective modes. We benchmark our findings
numerically on an interacting spinless fermion model in 1D, and find
persistence of central features even in the non-integrable case. As a
non-universal feature, the short time growth exhibits a distance dependent
power.


title: A temporal model for multiple sclerosis course evolution

abstract:
  Multiple Sclerosis is a degenerative condition of the central nervous system
that affects nearly 2.5 million of individuals in terms of their physical,
cognitive, psychological and social capabilities. Researchers are currently
investigating on the use of patient reported outcome measures for the
assessment of impact and evolution of the disease on the life of the patients.
To date, a clear understanding on the use of such measures to predict the
evolution of the disease is still lacking. In this work we resort to
regularized machine learning methods for binary classification and multiple
output regression. We propose a pipeline that can be used to predict the
disease progression from patient reported measures. The obtained model is
tested on a data set collected from an ongoing clinical research project.


title:
Charged pions tagged with polarized photons probing strong CP violation
  in a chiral-imbalance medium

abstract:
  It is expected that in a hot QCD system, a local parity-odd domain can be
produced due to nonzero chirality, which is induced from the difference of
winding numbers carried by the gluon topological configuration (QCD sphaleron).
This local domain is called the chiral-imbalance medium characterized by
nonzero chiral chemical potential, which can be interpreted as the time
variation of the strong CP phase. We find that the chiral chemical potential
generates the parity breaking term in the electromagnetic form factor of
charged pions. Heavy ion collision experiments could observe the
phenomenological consequence of this parity-odd form factor through the elastic
scattering of a pion and a photon in the medium. Then we quantify the asymmetry
rate of the parity violation by measuring the polarization of the photon
associated with the pion, and discuss how it could be measured in a definite
lab frame. We roughly estimate the typical size of the asymmetry, just by
picking up the pion resonant process, and find that the signal can be
sufficiently larger than possible background events from parity-breaking
electroweak process. Our findings might provide a novel possibility to make a
manifest detection for the remnant of the strong CP violation.


title:
Irregularities of distributions and extremal sets in combinatorial
  complexity theory

abstract:
  In 2004 the second author of the present paper proved that a point set in
$[0,1]^d$ which has star-discrepancy at most $\varepsilon$ must necessarily
consist of at least $c_{abs} d \varepsilon^{-1}$ points. Equivalently, every
set of $n$ points in $[0,1]^d$ must have star-discrepancy at least $c_{abs} d
n^{-1}$. The original proof of this result uses methods from
Vapnik--Chervonenkis theory and from metric entropy theory. In the present
paper we give an elementary combinatorial proof for the same result, which is
based on identifying a sub-box of $[0,1]^d$ which has approximately $d$
elements of the point set on its boundary. Furthermore, we show that a point
set for which no such box exists is rather irregular, and must necessarily have
a large star-discrepancy.


title: Gamma Ray Burst Prompt correlations

abstract:
  The mechanism responsible for the prompt emission of gamma-ray bursts (GRBs)
is still a debated issue. The prompt phase-related GRB correlations can allow
to discriminate among the most plausible theoretical models explaining this
emission. We present an overview of the observational two-parameter
correlations, their physical interpretations, their use as redshift estimators
and possibly as cosmological tools. The nowadays challenge is to make GRBs, the
farthest stellar-scaled objects observed (up to redshift $z=9.4$), standard
candles through well established and robust correlations. However, GRBs
spanning several orders of magnitude in their energetics are far from being
standard candles. We describe the advances in the prompt correlation research
in the past decades, with particular focus paid to the discoveries in the last
20 years.


title:
Decay of Superconducting Correlations for Gauged Electrons in Dimensions
  $D\le 4$

abstract:
  We study lattice superconductors coupled to gauge fields, such as an
attractive Hubbard model in electromagnetic fields, with a standard gauge
fixing. We prove upper bounds for a two-point Cooper pair correlation at finite
temperatures in spatial dimensions $D\le 4$. The upper bounds decay
exponentially in three dimensions, and by power law in four dimensions. These
imply absence of the superconducting long-range order for the Cooper pair
amplitude as a consequence of fluctuations of the gauge fields. Since our
results hold for the gauge fixing Hamiltonian, they cannot be obtained as a
corollary of Elitzur's theorem.

categories: math-ph cond-mat.str-el cond-mat.supr-con hep-lat math.MP


title:
Final COMPASS results on the deuteron spin-dependent structure function
  $g_1^{\rm d}$ and the Bjorken sum rule

abstract:
  Final results are presented from the inclusive measurement of deep-inelastic
polarised-muon scattering on longitudinally polarised deuterons using a $^6$LiD
target. The data were taken at $160~{\rm GeV}$ beam energy and the results are
shown for the kinematic range $1~({\rm GeV}/c)^2 < Q^2 < 100~({\rm GeV}/c)^2$
in photon virtuality, $0.004<x<0.7$ in the Bjorken scaling variable and $W >
4~{\rm GeV}/c^2$ in the mass of the hadronic final state. The deuteron
double-spin asymmetry $A_1^{\rm d}$ and the deuteron longitudinal-spin
structure function $g_1^{\rm d}$ are presented in bins of $x$ and $Q^2$.
Towards lowest accessible values of $x$, $g_1^{\rm d}$ decreases and becomes
consistent with zero within uncertainties. The presented final $g_1^{\rm d}$
values together with the recently published final $g_1^{\rm p}$ values of
COMPASS are used to again evaluate the Bjorken sum rule and perform the QCD fit
to the $g_1$ world data at next-to-leading order of the strong coupling
constant. In both cases, changes in central values of the resulting numbers are
well within statistical uncertainties. The flavour-singlet axial charge $a_0$,
{which is identified in the $\overline{\rm MS}$ renormalisation scheme with the
total contribution of quark helicities to the nucleon spin}, is extracted from
only the COMPASS deuteron data with negligible extrapolation uncertainty: $a_0
(Q^2 = 3~({\rm GeV}/c)^2) = 0.32 \pm 0.02_{\rm stat} \pm0.04_{\rm syst} \pm
0.05_{\rm evol}$. Together with the recent results on the proton spin structure
function $g_1^{\rm p}$, the results on $g_1^{\rm d}$ constitute the COMPASS
legacy on the measurements of $g_1$ through inclusive spin-dependent deep
inelastic scattering.


title: O(3) model with Nienhuis action

abstract:
  We study the O(3) sigma model in $D=2$ on the lattice with a Boltzmann weight
linearized in $\beta$ on each link. While the spin formulation now suffers from
a sign-problem the equivalent loop model remains positive and becomes
particularly simple. By studying the transfer matrix and by performing Monte
Carlo simulations in the loop form we study the mass gap coupling in a step
scaling analysis. The question addressed is, whether or not such a simplified
action still has the right universal continuum limit. If the answer is
affirmative this would be helpful in widening the applicability of worm
algorithm methods.


title: Blow-up lemmas for sparse graphs

abstract:
  The blow-up lemma states that a system of super-regular pairs contains all
bounded degree spanning graphs as subgraphs that embed into a corresponding
system of complete pairs. This lemma has far-reaching applications in extremal
combinatorics.
  We prove sparse analogues of the blow-up lemma for subgraphs of random and of
pseudorandom graphs. Our main results are the following three sparse versions
of the blow-up lemma: one for embedding spanning graphs with maximum degree
$\Delta$ in subgraphs of $G(n,p)$ with $p=C(\log n/n)^{1/\Delta}$; one for
embedding spanning graphs with maximum degree $\Delta$ and degeneracy $D$ in
subgraphs of $G(n,p)$ with $p=C_\Delta\big(\log n/n\big)^{1/(2D+1)}$; and one
for embedding spanning graphs with maximum degree $\Delta$ in
$(p,cp^{\max(4,(3\Delta+1)/2)}n)$-bijumbled graphs.
  We also consider various applications of these lemmas.


title: Density Based Algorithm With Automatic Parameters Generation

abstract:
  The traditional algorithms do not meet the latest multiple requirements
simultaneously for objects. Density-based method is one of the methodologies,
which can detect arbitrary shaped clusters where clusters are defined as dense
regions separated by low density regions. In this paper, we present a new
clustering algorithm to enhance the density-based algorithm DBSCAN. This
enables an automatic parameter generation strategy to create clusters with
different densities and enables noises recognition, and generates arbitrary
shaped clusters. The kdtree is used for increasing the memory efficiency.
Experimental result shows that proposed algorithm is capable of handling
complex objects with good memory efficiency and accuracy.


title: Development of a new generation of 3D pixel sensors for HL-LHC

abstract:
  This paper covers the main technological and design aspects relevant to the
development of a new generation of thin 3D pixel sensors with small pixel size
aimed at the High-Luminosity LHC upgrades.


title: Recognition of Text Image Using Multilayer Perceptron

abstract:
  The biggest challenge in the field of image processing is to recognize
documents both in printed and handwritten format. Optical Character Recognition
OCR is a type of document image analysis where scanned digital image that
contains either machine printed or handwritten script input into an OCR
software engine and translating it into an editable machine readable digital
text format. A Neural network is designed to model the way in which the brain
performs a particular task or function of interest: The neural network is
simulated in software on a digital computer. Character Recognition refers to
the process of converting printed Text documents into translated Unicode Text.
The printed documents available in the form of books, papers, magazines, etc.
are scanned using standard scanners which produce an image of the scanned
document. Lines are identifying by an algorithm where we identify top and
bottom of line. Then in each line character boundaries are calculated by an
algorithm then using these calculation, characters is isolated from the image
and then we classify each character by basic back propagation. Each image
character is comprised of 30*20 pixels. We have used the Back propagation
Neural Network for efficient recognition where the errors were corrected
through back propagation and rectified neuron values were transmitted by
feed-forward method in the neural network of multiple layers.


title: The INFN-FBK Phase-2 R{\&}D Program

abstract:
  We report on the 3-year INFN ATLAS-CMS joint research activity in
collaboration with FBK, started in 2014, and aimed at the development of new
thin pixel detectors for the High Luminosity LHC Phase-2 upgrades. The program
is concerned with both 3D and planar active-edge pixel sensors to be made on
6-inch p-type wafers. The technology and the design will be optimized and
qualified for extreme radiation hardness (2e16 neq cm-2). Pixel layouts
compatible with present (for testing) and future (RD53 65nm) front-end chips of
ATLAS and CMS are considered. The paper covers the main aspects of the research
program, from the sensor design and fabrication technology, to the results of
initial tests performed on the first prototypes.


title:
Bochner type formulas for the Weyl tensor on four dimensional Einstein
  manifolds

abstract:
  The very definition of an Einstein metric implies that all its geometry is
encoded in the Weyl tensor. With this in mind, in this paper we derive
higher-order Bochner type formulas for the Weyl tensor on a four dimensional
Einstein manifold. In particular, we prove a second Bochner type formula which,
formally, extends to the covariant derivative level the classical one for the
Weyl tensor obtained by Derdzinski in 1983. As a consequence, we deduce some
integral identities involving the Weyl tensor and its derivatives on a compact
four dimensional Einstein manifold.


title: Overloaded Multiuser MISO Transmission with Imperfect CSIT

abstract:
  A required feature for the next generation of wireless communication networks
will be the capability to serve simultaneously a large number of devices with
heterogeneous CSIT qualities and demands. In this paper, we consider the
overloaded MISO BC with two groups of CSIT qualities. We propose a transmission
scheme where degraded symbols are superimposed on top of spatially-multiplexed
symbols. The developed strategy allows to serve all users in a non-orthogonal
manner and the analysis shows an enhanced perfomance compared to existing
schemes. Moreover, optimality in a DoF sense is shown.


title: Steady-state generation of negative-Wigner-function light using feedback

abstract:
  We propose a method of producing steady-state coherent light with negative
Wigner functions in nonlinear media combined with feedback control. While the
nonlinearities are essential to produce the Wigner negativities, this alone is
insufficient to stabilize steady-state light with negativities. Using feedback
control to control the phase in the cavity, we find that this produces
significant total negativities for reasonable experimental parameters. The
negative Wigner function is produced continuously and does not appear to be
restricted to low-amplitude light. The technique is applicable to systems such
as exciton-polaritons, where strong natural nonlinearities are present.


title:
Attractors of sequences of function systems and their relation to
  non-stationary subdivision

abstract:
  Iterated Function Systems (IFSs) have been at the heart of fractal geometry
almost from its origin, and several generalizations for the notion of IFS have
been suggested. Subdivision schemes are widely used in computer graphics and
attempts have been made to link fractals generated by IFSs to limits generated
by subdivision schemes. With an eye towards establishing connection between
non-stationary subdivision schemes and fractals, this paper introduces the
notion of "trajectories of maps defined by function systems" which may be
considered as a new generalization of the traditional IFS. The significance and
the convergence properties of 'forward' and 'backward' trajectories are
studied. In contrast to the ordinary fractals which are self-similar at
different scales, the attractors of these trajectories may have different
structures at different scales.


title: Design Automation and Design Space Exploration for Quantum Computers

abstract:
  A major hurdle to the deployment of quantum linear systems algorithms and
recent quantum simulation algorithms lies in the difficulty to find inexpensive
reversible circuits for arithmetic using existing hand coded methods. Motivated
by recent advances in reversible logic synthesis, we synthesize arithmetic
circuits using classical design automation flows and tools. The combination of
classical and reversible logic synthesis enables the automatic design of large
components in reversible logic starting from well-known hardware description
languages such as Verilog. As a prototype example for our approach we
automatically generate high quality networks for the reciprocal $1/x$, which is
necessary for quantum linear systems algorithms.


title: Dark matter and baryogenesis in the Fermi-bounce curvaton mechanism

abstract:
  We elaborate on a toy-model of matter bounce, in which the matter content is
constituted by two fermion species endowed with four fermion interaction term.
We describe the curvaton mechanism that is forth generated, and then argue that
one of the two fermionic species may realize baryogenesis, while the other
(lighter) one is compatible with constrains on extra hot dark matter particles.


title:
Enhancing Light Emission in Interface Engineered Spin-OLEDs Through
  Spin-Polarized Injection at High Voltages

abstract:
  The quest for a spin-polarized organic light emitting diode (spin-OLED) is a
common goal in the emerging fields of molecular electronics and spintronics. In
this device two ferromagnetic electrodes are used to enhance the
electroluminescence intensity of the OLED through a magnetic control of the
spin polarization of the injected carriers. The major difficulty is that the
driving voltage of an OLED device exceeds of a few volts, while spin injection
in organic materials is only efficient at low voltages. We report here the
fabrication of a spin-OLED that uses a conjugated polymer as bipolar spin
collector layer and ferromagnetic electrodes. Through a careful engineering of
the organic/inorganic interfaces we have succeeded in obtaining a
light-emitting device showing spin-valve effects at high voltages (up to 14 V).
This has allowed us to detect a magneto-electroluminescence enhancement on the
order of a 2.4 % at 9 V for the antiparallel configuration of the magnetic
electrodes. This observation provides evidence for the long-standing
fundamental issue of injecting spins from magnetic electrodes into the frontier
levels of a molecular semiconductor. Our finding opens the way for the design
of multifunctional devices coupling the light and the spin degrees of freedom.


title: The giant radio flare of Cygnus X-3 in September 2016

abstract:
  In the long-term multi-frequency monitoring program of the microquasars with
RATAN-600 we discovered the giant flare from the X-ray binary Cygnus X-3 on 13
September 2016. It happened after 2000 days of the 'quiescent state' of the
source passed after the former giant flare (~18 Jy) in March 2011. We have
found that during this quiet period the hard X-ray flux (Swift/BAT, 15-50 keV)
and radio flux (RATAN-600, 11 GHz) have been strongly anti-correlated. Both
radio flares occurred after transitions of the microquasar to a 'hypersoft'
X-ray state that occurred in February 2011 and in the end of August 2016. The
giant flare was predicted by us in the first ATel #9416. Indeed after dramatic
decrease of the hard X-ray Swift 15-50 keV flux and RATAN 4-11 GHz fluxes (a
'quenched state') a small flare (0.7 Jy at 4-11 GHz) developed on MJD 57632 and
then on MJD 57644.5 almost simultaneously with X-rays radio flux rose from 0.01
to 15 Jy at 4.6 GHz during few days. The rise of the flaring flux is well
fitted by a exponential law that could be a initial phase of the relativistic
electrons generation by internal shock waves in the jets. Initially spectra
were optically thick at frequencies lower 2 GHz and optically thin at
frequencies higher 8 GHz with typical spectral index about -0.5. After maximum
of the flare radio fluxes at all frequencies faded out with the exponential law
(~ exp(-(t-t0)/2d) for 21.7 GHz).


title:
Critical Schwinger pair production II - universality in the deeply
  critical regime

abstract:
  We study electron-positron pair production by spatially inhomogeneous
electric fields. Depending on the localization of the field, a critical point
(critical surface) exists in the space of field configurations where the pair
production probability vanishes. Near criticality, pair production exhibits
universal properties similar to those of continuous phase transitions. We
extend results previously obtained in the semi-classical (weak-field) critical
regime to the deeply critical regime for arbitrary peak field strength. In this
regime, we find an enhanced universality, featuring a unique critical exponent
$\beta=3$ for all sufficiently localized fields. For a large class of field
profiles, we also compute the non-universal amplitudes.


title:
Families of irreducible singular Gelfand-Tsetlin modules of
  $\mathfrak{gl}(n)$

abstract:
  We prove a conjecture for the irreducibility of singular Gelfand-Tsetlin
modules. We describe explicitly the irreducible subquotients of certain classes
of singular Gelfand-Tsetlin modules.


title:
A General Framework for Density Based Time Series Clustering Exploiting
  a Novel Admissible Pruning Strategy

abstract:
  Time Series Clustering is an important subroutine in many higher-level data
mining analyses, including data editing for classifiers, summarization, and
outlier detection. It is well known that for similarity search the superiority
of Dynamic Time Warping (DTW) over Euclidean distance gradually diminishes as
we consider ever larger datasets. However, as we shall show, the same is not
true for clustering. Clustering time series under DTW remains a computationally
expensive operation. In this work, we address this issue in two ways. We
propose a novel pruning strategy that exploits both the upper and lower bounds
to prune off a very large fraction of the expensive distance calculations. This
pruning strategy is admissible and gives us provably identical results to the
brute force algorithm, but is at least an order of magnitude faster. For
datasets where even this level of speedup is inadequate, we show that we can
use a simple heuristic to order the unavoidable calculations in a
most-useful-first ordering, thus casting the clustering into an anytime
framework. We demonstrate the utility of our ideas with both single and
multidimensional case studies in the domains of astronomy, speech physiology,
medicine and entomology. In addition, we show the generality of our clustering
framework to other domains by efficiently obtaining semantically significant
clusters in protein sequences using the Edit Distance, the discrete data
analogue of DTW.


title: First Production of New Thin 3D Sensors for HL-LHC at FBK

abstract:
  Owing to their intrinsic (geometry dependent) radiation hardness, 3D pixel
sensors are promising candidates for the innermost tracking layers of the
forthcoming experiment upgrades at the Phase 2 High-Luminosity LHC (HL-LHC). To
this purpose, extreme radiation hardness up to the expected maximum fluence of
2e16 neq.cm-2 must come along with several technological improvements in a new
generation of 3D pixels, i.e., increased pixel granularity (50x50 or 25x100 um2
cell size), thinner active region (~100 um), narrower columnar electrodes (~5
um diameter) with reduced inter-electrode spacing (~30 um), and very slim edges
(~100 um). The fabrication of the first batch of these new 3D sensors was
recently completed at FBK on Si-Si direct wafer bonded 6-inch substrates.
Initial electrical test results, performed at wafer level on sensors and test
structures, highlighted very promising performance, in good agreement with TCAD
simulations: low leakage current (<1 pA/column), intrinsic breakdown voltage of
more than 150 V, capacitance of about 50 fF/column, thus assessing the validity
of the design approach. A large variety of pixel sensors compatible with both
existing (e.g., ATLAS FEI4 and CMS PSI46) and future (e.g., RD53) read-out
chips were fabricated, that were also electrically tested on wafer using a
temporary metal layer patterned as strips shorting rows of pixels together.
This allowed a statistically significant distribution of the relevant
electrical quantities to be obtained, thus gaining insight into the impact of
process-induced defects. A few 3D strip test structures were irradiated with
X-rays, showing inter-strip resistance of at least several GOhm even after 50
Mrad(Si) dose, thus proving the p-spray robustness. We present the most
important design and technological aspects, and results obtained from the
initial investigations.


title:
Unusual mixed valence of Eu in two new materials EuSr2Bi2S4F4 and
  Eu2SrBi2S4F4: M\"ossbauer and X-ray photoemission Spectroscopy investigations

abstract:
  We have synthesized two new Eu-based compounds, EuSr2Bi2S4F4 and Eu2SrBi2S4F4
which are derivatives of Eu3Bi2S4F4, an intrinsic superconductor with Tc = 1.5
K. They belong to a tetragonal structure (SG: I4/mmm, Z = 2), similar to the
parent compound Eu3Bi2S4F4. Our structural and 151Eu M\"ossbauer spectroscopy
studies show that in EuSr2Bi2S4F4, Eu-atoms exclusively occupy the
crystallographic 2a-sites. In Eu2SrBi2S4F4, 2a-sites are fully occupied by
Eu-atoms and the other half of Eu-atoms and Sr-atoms together fully occupy
4e-sites in a statistical distribution. In both compounds Eu atoms occupying
the crystallographic 2a-sites are in a homogeneous mixed valent state ~ 2.6 -
2.7. From our magnetization studies in an applied H = 9 Tesla, we infer that
the valence of Eu-atoms in Eu2SrBi2S4F4 at the 2a-sites exhibits a shift
towards 2+. Our XPS studies corroborate the occurrence of valence fluctuations
of Eu and after Ar-ion sputtering show evidence of enhanced population of
Eu2+-states. Resistivity measurements, down to 2 K suggest a semi-metallic
nature for both compounds.


title: I-factorial quantum torsors

abstract:
  In an earlier paper of the author, locally compact quantum torsors were
defined for locally compact quantum groups, putting into the analytic framework
the theory of Galois objects for Hopf algebras. Such quantum torsors allow to
deform the given quantum group, providing a generalization of the 2-cocycle
twisting procedure. It was also shown that a quantum torsor can be constructed
from an action of the dual quantum group on a type I-factor. In this paper, we
study quantum torsors which are themselves type I-factors. These I-factorial
quantum torsors turn out to have a nice duality theory. We illustrate the
general theory with the example of the Heisenberg double.


title: Linking particle dynamics to local connectivity in colloidal gels

abstract:
  Colloidal gels are a prototypical example of a heterogeneous network solid
whose complex properties are governed by thermally-activated dynamics. In this
Letter we experimentally establish the connection between the intermittent
dynamics of individual particles and their local connectivity. We interpret our
experiments with a model that describes single-particle dynamics based on
highly cooperative thermal debonding. The model, in quantitative agreement with
experiments, provides a microscopic picture for the structural origin of
dynamical heterogeneity in colloidal gels and sheds new light on the link
between structure and the complex mechanics of these heterogeneous solids.


title:
Riemann integrability under weaker forms of continuity in infinite
  dimensional spaces

abstract:
  In classical analysis, the relationship between continuity and Riemann
integrability is an intimate one: a continuous function on a closed and bounded
interval is always Riemann integrable whereas a Riemann integrable function is
continuous almost everywhere. In the setting of functions taking values in
infinite dimensional spaces that include quasi Banach spaces, one encounters
certain curious situations involving the breakdown of the above stated
phenomena, besides the failure of the fundamental theorem of calculus and the
non-existence of primitives for continuous functions! While some of these
properties can surely be salvaged within the class of Banach spaces, it turns
out that certain important properties involving vector integration that include
Riemann integration no longer hold in an infinite dimensional setting. This
will be seen to be the case, for example, in situations when it is required to
integrate functions which are continuous with respect to certain well known (
generally compatible) linear topologies on X (resp. its dual) weaker than the
norm topology. As we shall see in Section 3(a), such a requirement imposes
rather severe restrictions on the space in question. The present paper is
devoted to a discussion of these issues which will be examined in the setting
of Banach and Frechet spaces on the one hand and of quasi Banach spaces on the
other. The paper concludes with a brief (but non-technical) description on
recent developments and the current of art involving various other aspects of
vector integration


title: Searching for New Physics in Scalar Top-Pair Resonance

abstract:
  We consider the effects in the production via gluon fusion in LHC collisions
of one or two spin-zero new resonant particles $\Phi$ that decay into a top
quark pair. We revisit previous analyses of the interferences between the
heavy-fermion loop-induced $gg \rightarrow \Phi \rightarrow t\bar{t}$ signal
and the continuum QCD background $gg \rightarrow t\bar{t}$. We show that in the
presence of standard model fermions only in the $gg \rightarrow \Phi$ loops,
the interference effect is destructive causing a dip in the $t \bar t$ mass
distribution. Including New Physics such as additional vector-like quarks leads
to a totally different picture as the line-shape can be distorted by peaks and
dips. For the time being, the absence of such effects in ATLAS and CMS data
constrain models of the production and decays of the $\Phi$ state(s).


title: Bayesian Population Receptive Field Modelling

abstract:
  We introduce a probabilistic (Bayesian) framework and associated software
toolbox for mapping population receptive fields (pRFs) based on fMRI data. This
generic approach is intended to work with stimuli of any dimension and is
demonstrated and validated in the context of 2D retinotopic mapping. The
framework enables the experimenter to specify generative (encoding) models of
fMRI timeseries, in which experimental manipulations enter a pRF model of
neural activity, which in turns drives a nonlinear model of neurovascular
coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuronal
and haemodynamic parameters are estimated together on a voxel-by-voxel or
region-of-interest basis using a Bayesian estimation algorithm (variational
Laplace). This offers several novel contributions to receptive field modelling.
The variance / covariance of parameters are estimated, enabling receptive
fields to be plotted while properly representing uncertainty about pRF size and
location. Variability in the haemodynamic response across the brain is
accounted for. Furthermore, the framework introduces formal hypothesis testing
to pRF analysis, enabling competing models to be evaluated based on their model
evidence (approximated by the variational free energy), which represents the
optimal tradeoff between accuracy and complexity. Using simulations and
empirical data, we found that parameters typically used to represent pRF size
and neuronal scaling are strongly correlated, which should be taken into
account when making inferences. We used the framework to compare the evidence
for six variants of pRF model using 7T functional MRI data and we found a
circular Difference of Gaussians (DoG) model to be the best explanation for our
data overall. We hope this framework will prove useful for mapping stimulus
spaces with any number of dimensions onto the anatomy of the brain.


title:
Centrog Feature technique for vehicle type recognition at day and night
  times

abstract:
  This work proposes a feature-based technique to recognize vehicle types
within day and night times. Support vector machine (SVM) classifier is applied
on image histogram and CENsus Transformed histogRam Oriented Gradient (CENTROG)
features in order to classify vehicle types during the day and night. Thermal
images were used for the night time experiments. Although thermal images suffer
from low image resolution, lack of colour and poor texture information, they
offer the advantage of being unaffected by high intensity light sources such as
vehicle headlights which tend to render normal images unsuitable for night time
image capturing and subsequent analysis. Since contour is useful in shape based
categorisation and the most distinctive feature within thermal images, CENTROG
is used to capture this feature information and is used within the experiments.
The experimental results so obtained were compared with those obtained by
employing the CENsus TRansformed hISTogram (CENTRIST). Experimental results
revealed that CENTROG offers better recognition accuracies for both day and
night times vehicle types recognition.


title: A Fra\"iss\'e theoretic approach to the Jiang--Su algebra

abstract:
  In this paper, we give a Fra\"iss\'e theoretic proof of the result of X.
Jiang and H. Su that the Jiang--Su algebra is the unique monotracial simple
C*-algebra among all inductive limits of prime dimension drop algebras. We also
partially recover the fact that every unital endomorphism of the Jiang--Su
algebra is approximately inner.


title: Stability of topological properties of bismuth (111) bilayer

abstract:
  We investigate electronic and transport properties of bismuth (111) bilayer
in the context of stability of its topological properties against different
perturbations. The effects of spin-orbit coupling variations, geometry
relaxation and an interaction with a substrate are considered. Transport
properties are studied in the presence of Anderson disorder. Band structure
calculations are performed within multi-orbital tight-binding model and density
functional theory methods. A band inversion process in bismuth (111) infinite
bilayer and an evolution of edge states dispersion in ribbons as a function of
spin-orbit coupling strength are analyzed. A significant change of orbital
composition of the conduction and valence bands during a topological phase
transition is observed. A topological phase is shown to be robust when the
effect of geometry relaxation is taken into account. An interaction with a
substrate has similar effect to an external perpendicular electric field. The
robust quantized conductance is observed when the Fermi energy lies within the
bulk energy gap, where only two counter-propagating edge states are present.
For energies where the Fermi level crosses more in-gap states, a scattering is
possible between channels lying close in $k-$space. When the energy of edge
states overlaps with bulk states, no topological protection is observed.


title: Spectrum of a class of matrices and its applications

abstract:
  In this paper, we give the spectrum of a matrix by using the quotient matrix,
then we apply this result to various matrices associated to a graph and a
digraph, including adjacency matrix, (signless) Laplacian matrix, distance
matrix, distance (signless) Laplacian matrix, to obtain some known and new
results. Moreover, we propose some problems for further research.


title: Storage Management in Modern Electricity Power Grids

abstract:
  This letter introduces a method to manage energy storage in electricity
grids. Starting from the stochastic characterization of electricity generation
and demand, we propose an equation that relates the storage level for every
time-step as a function of its previous state and the realized surplus/deficit
of electricity. Therefrom, we can obtain the probability that, in the next
time-step: (i) there is a generation surplus that cannot be stored, or (ii)
there is a demand need that cannot be supplied by the available storage. We
expect this simple procedure can be used as the basis of electricity
self-management algorithms in micro-level (e.g. individual households) or in
meso-level (e.g. groups of houses).


title: Heavy-tailed configuration models at criticality

abstract:
  We study the critical behavior of the component sizes for the configuration
model when the tail of the degree distribution of a randomly chosen vertex is a
regularly-varying function with exponent $\tau-1$, where $\tau\in (3,4)$. The
component sizes are shown to be of the order $n^{(\tau-2)/(\tau-1)}L(n)^{-1}$
for some slowly-varying function $L(\cdot)$. We show that the re-scaled ordered
component sizes converge in distribution to the ordered excursions of a thinned
L\'evy process. This proves that the scaling limits for the component sizes for
these heavy-tailed configuration models are in a different universality class
compared to the Erd\H{o}s-R\'enyi random graphs. Also the joint re-scaled
vector of ordered component sizes and their surplus edges is shown to have a
distributional limit under a strong topology. Our proof resolves a conjecture
by Joseph, Ann. Appl. Probab. (2014) about the scaling limits of uniform simple
graphs with i.i.d degrees in the critical window, and sheds light on the
relation between the scaling limits obtained by Joseph and in this paper, which
appear to be quite different. Further, we use percolation to study the
evolution of the component sizes and the surplus edges within the critical
scaling window, which is shown to converge in finite dimension to the augmented
multiplicative coalescent process introduced by Bhamidi et. al., Probab. Theory
Related Fields (2014). The main results of this paper are proved under rather
general assumptions on the vertex degrees. We also discuss how these
assumptions are satisfied by some of the frameworks that have been studied
previously.


title:
Sampling Theorems for Shift-invariant Spaces, Gabor Frames, and Totally
  Positive Functions

abstract:
  We study nonuniform sampling in shift-invariant spaces and the construction
of Gabor frames with respect to the class of totally positive functions whose
Fourier transform factors as $ \hat g(\xi)= \prod_{j=1}^n (1+2\pi
i\delta_j\xi)^{-1} \, e^{-c \xi^2}$ for $\delta_1,\ldots,\delta_n\in
\mathbb{R}, c >0$ (in which case $g$ is called totally positive of Gaussian
type).
  In analogy to Beurling's sampling theorem for the Paley-Wiener space of
entire functions, we prove that every separated set with lower Beurling density
$>1$ is a sampling set for the shift-invariant space generated by such a $g$.
In view of the known necessary density conditions, this result is optimal and
validates the heuristic reasonings in the engineering literature.
  Using a subtle connection between sampling in shift-invariant spaces and the
theory of Gabor frames, we show that the set of phase-space shifts of $g$ with
respect to a rectangular lattice $\alpha \mathbb{Z} \times \beta \mathbb{Z}$
forms a frame, if and only if $\alpha \beta <1$. This solves an open problem
going back to Daubechies in 1990 for the class of totally positive functions of
Gaussian type.
  The proof strategy involves the connection between sampling in
shift-invariant spaces and Gabor frames, a new characterization of sampling
sets "without inequalities" in the style of Beurling, new properties of totally
positive functions, and the interplay between zero sets of functions in a
shift-invariant space and functions in the Bargmann-Fock space.


title:
Gromov--Witten theory of $[\mathbb{C}^2/\mathbb{Z}_{n+1}]\times
  \mathbb{P}^1$

abstract:
  We compute the relative orbifold Gromov-Witten invariants of
$[\mathbb{C}^2/\mathbb{Z}_{n+1}]\times \mathbb{P}^1$, with respect to vertical
fibers. Via a vanishing property of the Hurwitz-Hodge bundle, 2-point rubber
invariants are calculated explicitly using Pixton's formula for the double
ramification cycle, and the orbifold quantum Riemann-Roch. As a result parallel
to its crepant resolution counterpart for $\mathcal{A}_n$, the GW/DT/Hilb/Sym
correspondence is established for $[\mathbb{C}^2/\mathbb{Z}_{n+1}]$. The
computation also implies the crepant resolution conjecture for relative
orbifold Gromov-Witten theory of $[\mathbb{C}^2/\mathbb{Z}_{n+1}]\times
\mathbb{P}^1$.


title:
Inferring Cognitive Models from Data using Approximate Bayesian
  Computation

abstract:
  An important problem for HCI researchers is to estimate the parameter values
of a cognitive model from behavioral data. This is a difficult problem, because
of the substantial complexity and variety in human behavioral strategies. We
report an investigation into a new approach using approximate Bayesian
computation (ABC) to condition model parameters to data and prior knowledge. As
the case study we examine menu interaction, where we have click time data only
to infer a cognitive model that implements a search behaviour with parameters
such as fixation duration and recall probability. Our results demonstrate that
ABC (i) improves estimates of model parameter values, (ii) enables meaningful
comparisons between model variants, and (iii) supports fitting models to
individual users. ABC provides ample opportunities for theoretical HCI research
by allowing principled inference of model parameter values and their
uncertainty.


title:
Realization of electron vortices with large orbital angular momentum
  using miniature holograms fabricated by electron beam lithography

abstract:
  Free electron beams that carry high values of orbital angular momentum (OAM)
possess large magnetic moments along the propagation direction. This makes them
an ideal probe for measuring the electronic and magnetic properties of
materials, and for fundamental experiments in magnetism. However, their
generation requires the use of complex diffractive elements, which usually take
the form of nano-fabricated holograms. Here, we show how the limitations of
focused ion beam milling in the fabrication of such holograms can be overcome
by using electron beam lithography. We demonstrate experimentally the
realization of an electron vortex beam with the largest OAM value that has yet
been reported (L = 1000h\bar), paving the way for even more demanding
demonstrations and applications of electron beam shaping.


title:
Multi-wavelength observations of the Be/X-ray binary IGR J01217-7257
  (=SXP 2.16) during outburst

abstract:
  We present simultaneous, multi-wavelength observations of the Small
Magellanic Cloud Be/XRB IGR J01217-7257 (=SXP 2.16) during outbursts in 2014,
2015 and 2016. We also present the results of RXTE observations of the Small
Magellanic Cloud during which the source was initially discovered with a
periodicity of 2.1652$\pm$0.0001 seconds which we associate with the spin
period of the neutron star. A systematic temporal analysis of long term
Swift/BAT data reveals a periodic signal of 82.5$\pm$0.7 days, in contrast with
a similar analysis of long base line OGLE I-band light curves which reveals an
83.67$\pm$0.05 days also found in this work. Interpreting the longer X-ray
periodicity as indicative of binary motion of the neutron star, we find that
outbursts detected by INTEGRAL and Swift between 2014 and 2016 are consistent
with Type I outbursts seen in Be/XRBs, occurring around periastron. Comparing
these outbursts with the OGLE data, we see a clear correlation between outburst
occurrence and increasing I-band flux. A periodic analysis of subdivisions of
OGLE data reveals three epochs during which short periodicities of $\sim$1 day
are significantly detected which we suggest are non-radial pulsations (NRPs) of
the companion star. These seasons immediately precede those exhibiting clear
outburst behaviour, supporting the suggested association between the NRPs,
decretion disk growth and the onset of Type I outbursts.


title: A simple tensor network algorithm for two-dimensional steady states

abstract:
  Understanding dissipation in 2D quantum many-body systems is a remarkably
difficult open challenge. Here we show how numerical simulations for this
problem are possible by means of a tensor network algorithm that approximates
steady-states of 2D quantum lattice dissipative systems in the thermodynamic
limit. Our method is based on the intuition that strong dissipation kills
quantum entanglement before it gets too large to handle. We test its validity
by simulating a dissipative quantum Ising model, relevant for dissipative
systems of interacting Rydberg atoms, and benchmark our simulations with a
variational algorithm based on product and correlated states. Our results
support the existence of a first order transition in this model, with no
bistable region. We also simulate a dissipative spin-1/2 XYZ model, showing
that there is no re-entrance of the ferromagnetic phase. Our method enables the
computation of steady states in 2D quantum lattice systems.


title:
A Stable and High-Order Accurate Discontinuous Galerkin Based Splitting
  Method for the Incompressible Navier-Stokes Equations

abstract:
  In this paper we consider discontinuous Galerkin (DG) methods for the
incompressible Navier-Stokes equations in the framework of projection methods.
In particular we employ symmetric interior penalty DG methods within the
second-order rotational incremental pressure correction scheme. The major focus
of the paper is threefold: i) We propose a modified upwind scheme based on the
Vijayasundaram numerical flux that has favourable properties in the context of
DG. ii) We present a novel postprocessing technique in the Helmholtz projection
step based on $H(\text{div})$ reconstruction of the pressure correction that is
computed locally, is a projection in the discrete setting and ensures that the
projected velocity satisfies the discrete continuity equation exactly. As a
consequence it also provides local mass conservation of the projected velocity.
iii) Numerical results demonstrate the properties of the scheme for different
polynomial degrees applied to two-dimensional problems with known solution as
well as large-scale three-dimensional problems. In particular we address
second-order convergence in time of the splitting scheme as well as its
long-time stability.


title: Remote synchronization in networks of coupled oscillators

abstract:
  We study under which conditions systems of coupled oscillators on complex
networks display remote synchronization, a situation where pairs of vertices,
not necessarily physically linked, but with the same network symmetry, are
synchronized.


title:
Relative Entanglement Entropies in 1+1-dimensional conformal field
  theories

abstract:
  We study the relative entanglement entropies of one interval between excited
states of a 1+1 dimensional conformal field theory (CFT). To compute the
relative entropy $S(\rho_1 \| \rho_0)$ between two given reduced density
matrices $\rho_1$ and $\rho_0$ of a quantum field theory, we employ the replica
trick which relies on the path integral representation of ${\rm Tr} ( \rho_1
\rho_0^{n-1} )$ and define a set of R\'enyi relative entropies $S_n(\rho_1 \|
\rho_0)$. We compute these quantities for integer values of the parameter $n$
and derive via the replica limit, the relative entropy between excited states
generated by primary fields of a free massless bosonic field. In particular, we
provide the relative entanglement entropy of the state described by the primary
operator $i \partial\phi$, both with respect to the ground state and to the
state generated by chiral vertex operators. These predictions are tested
against exact numerical calculations in the XX spin-chain finding perfect
agreement.


title: On the $b$-quark running mass in QCD and the SM

abstract:
  We consider electroweak corrections to the relation between the running
$\overline{\mathrm{MS}}$ mass $m_b$ of the $b$ quark in the five-flavor
QCD$\times$QED effective theory and its counterpart in the Standard Model (SM).
As a bridge between the two parameters, we use the pole mass $M_b$ of the $b$
quark, which can be calculated in both models. The running mass is not a
fundamental parameter of the SM Lagrangian, but the product of the running
Yukawa coupling $y_b$ and the Higgs vacuum expectation value. Since there exist
different prescriptions to define the latter, the relations considered in the
paper involve a certain amount of freedom. All the definitions can be related
to each other in perturbation theory. Nevertheless, we argue in favor of a
certain gauge-independent prescription and provide a relation which can be
directly used to deduce the value of the Yukawa coupling of the $b$ quark at
the electroweak scale from its effective QCD running mass. This approach allows
one to resum large logarithms $\ln(m_b/M_t)$ systematically. Numerical analysis
shows that, indeed, the corrections to the proposed relation are much smaller
than those between $y_b$ and $M_b$.


title: The Bandwidth Theorem in Sparse Graphs

abstract:
  The bandwidth theorem [Mathematische Annalen, 343(1):175--205, 2009] states
that any $n$-vertex graph $G$ with minimum degree
$\big(\tfrac{k-1}{k}+o(1)\big)n$ contains all $n$-vertex $k$-colourable graphs
$H$ with bounded maximum degree and bandwidth $o(n)$. We provide sparse
analogues of this statement in random graphs as well as pseudorandom graphs.
  More precisely, we show that for $p\gg \big(\tfrac{\log
n}{n}\big)^{1/\Delta}$ asymptotically almost surely each spanning subgraph $G$
of $G(n,p)$ with minimum degree $\big(\tfrac{k-1}{k}+o(1)\big)pn$ contains all
$n$-vertex $k$-colourable graphs $H$ with maximum degree $\Delta$, bandwidth
$o(n)$, and at least $C p^{-2}$ vertices not contained in any triangle. A
similar result is shown for sufficiently bijumbled graphs, which, to the best
of our knowledge, is the first resilience result in pseudorandom graphs for a
rich class of spanning subgraphs. Finally, we provide improved results for $H$
with small degeneracy, which in particular imply a resilience result in
$G(n,p)$ with respect to the containment of spanning bounded degree trees for
$p\gg \big(\tfrac{\log n}{n}\big)^{1/3}$.