  Recent advances in associative memory design through strutured pattern sets
and graph-based inference algorithms have allowed the reliable learning and
retrieval of an exponential number of patterns. Both these and classical
associative memories, however, have assumed internally noiseless computational
nodes. This paper considers the setting when internal computations are also
noisy. Even if all components are noisy, the final error probability in recall
can often be made exceedingly small, as we characterize. There is a threshold
phenomenon. We also show how to optimize inference algorithm parameters when
knowing statistical properties of internal noise.


  Electron hydrodynamics is an emerging framework that describes dynamics of
interacting electron systems as conventional fluids. While evidence for
hydrodynamic-like transport is reported in a variety of two-dimensional
materials, precise quantitative measurement of the core parameter, electron
viscosity, remains challenging. In this work, we demonstrate that
magnetoresistance in Corbino-shaped graphene devices offers a simultaneous
Ohmmeter/viscosometer, allowing us to disentangle the individual Ohmic and
viscous contributions to the transport response, even in the mixed flow regime.
Most surprising, we find that in both monolayer and bilayer graphene, the
effective electron-electron scattering rate scales linearly with temperature,
at odds with the expected $T$-squared dependence expected from conventional
Fermi liquid theory, but consistent with a recently identified tomographic flow
regime, which was theoretically conjectured to be generic for two-dimensional
charged fluids.


  Glitches, spin-up events in neutron stars, are of prime interest as they
reveal properties of nuclear matter at subnuclear densities. We numerically
investigate the glitch mechanism due to vortex unpinning using analogies
between neutron stars and dipolar supersolids. We explore the vortex and
crystal dynamics during a glitch and its dependence on the supersolid quality,
providing a tool to study glitches from different radial depths of a neutron
star. Benchmarking our theory against neutron star observations, our work will
open a new avenue for the quantum simulation of stellar objects from Earth.


  We have calculated the topological charge of U(N) instantons on
non-degenerate noncommutative space time to be exactly the instanton number k
in a previous paper [Mod.Phys.Lett. A18 1691]. This paper, which deals with the
degenerate R^2_{NC}*R^2 case, is the continuation of that one. We find that the
same conclusion holds in this case, thus complete the answer to the problem of
topological charge of noncommutative U(N) instantons.


  Very recent experiments have discovered that localized light in strongly
absorbing media displays intriguing diffusive phenomena. Here we develop a
first-principles theory of light propagation in open media with arbitrary
absorption strength and sample length. We show analytically that photons in
localized open absorbing media exhibit unusual Brownian motion. Specifically,
wave transport follows the diffusion equation with the diffusion coefficient
exhibiting spatial resolution. Most strikingly, despite that the system is
controlled by two parameters -- the ratio of the localization (absorption)
length to the sample length -- the spatially resolved diffusion coefficient
displays novel single parameter scaling: it depends on the space via the
returning probability. Our analytic predictions for this diffusion coefficient
are confirmed by numerical simulations. In the strong absorption limit they
agree well with the experimental results.


  We propose in this paper an original technique to predict global radiation
using a hybrid ARMA/ANN model and data issued from a numerical weather
prediction model (ALADIN). We particularly look at the Multi-Layer Perceptron.
After optimizing our architecture with ALADIN and endogenous data previously
made stationary and using an innovative pre-input layer selection method, we
combined it to an ARMA model from a rule based on the analysis of hourly data
series. This model has been used to forecast the hourly global radiation for
five places in Mediterranean area. Our technique outperforms classical models
for all the places. The nRMSE for our hybrid model ANN/ARMA is 14.9% compared
to 26.2% for the na\"ive persistence predictor. Note that in the stand alone
ANN case the nRMSE is 18.4%. Finally, in order to discuss the reliability of
the forecaster outputs, a complementary study concerning the confidence
interval of each prediction is proposed


  This work introduces into the Interacting Boson Model, which was created in
1974 by F. Iachello and A. Arima and then extended by numerous papers.
Many-body configurations with s- and d-boson states are described and creation-
and annihilation-operators for bosons are introduced. States with defined total
angular momentum are dealt with and the Hamilton operator of the IBM1-model is
expressed in terms of Casimir operators. Level energies and electromagnetic
transition probabilities are compared with measured data. A short introduction
to Lie algebras and their application to the IBM1-model are given. In the IBM2-
model protons and neutrons are treated separately and in IBFM single nucleons
are added to the boson model. Comparison with experimental results.


  We present a new method for neutrino-matter coupling in multi-dimensional
radiation-hydrodynamic simulations of core-collapse supernova (CCSN) with the
full Boltzmann neutrino transport. The development is motivated by the fact
that the accurate conservation of momentum is required for reliable numerical
modelings of CCSN dynamics including a recoil of proto-neutron star (PNS). The
new method is built on a hybrid approach, in which we use the energy-momentum
tensor of neutrinos to compute the momentum feedback from neutrino to matter in
the optically thick region while we employ the collision term in the optically
thin region. In this method we utilize a general relativistic description of
radiation-hydrodynamics with angular moments, which allows us to evaluate the
momentum feedback from neutrino to matter without inconsistency with our
Boltzmann solver. We demonstrate that the new method substantially improves the
accuracy of linear momentum conservation in our CCSN simulations under
reasonable angular resolutions in momentum space, alleviating the difficulty in
giving the diffusion limit precisely with the discrete ordinate (Sn) method. It
is the first-ever demonstration that the PNS kick can be handled directly and
properly in multi-dimensional radiation-hydrodynamic simulations with the full
Boltzmann neutrino transport.


  Earth and orbital-based radar observations of asteroids provide a unique
opportunity to characterize surface roughness and the dielectric properties of
their surfaces, as well as potentially explore some of their shallow subsurface
physical properties. If the dielectric and topographic properties of asteroid's
surfaces are defined, one can constrain their surface textural characteristics
as well as potential subsurface volatile enrichment using the observed radar
backscatter. To achieve this objective, we establish the first dielectric model
of asteroid Vesta for the case of a dry, volatile-poor regolith--employing an
analogy to the dielectric properties of lunar soil, and adjusted for the
surface densities and temperatures deduced from Dawn's Visible and InfraRed
mapping spectrometer (VIR). Our model suggests that the real part of the
dielectric constant at the surface of Vesta is relatively constant, ranging
from 2.3 to 2.5 from the night- to day-side of Vesta, while the loss tangent
shows slight variation as a function of diurnal temperature, ranging from 0.006
to 0.008. We estimate the surface porosity to be ~55% in the upper meter of the
regolith, as derived from VIR observations. This is ~12% higher than previous
estimation of porosity derived from previous Earth-based X- and S-band radar
observation. We suggest that the radar backscattering properties of asteroid
Vesta will be mainly driven by the changes in surface roughness rather than
potential dielectric variations in the upper regolith in the X- and S-band.


  The dependence of transverse momentum spectra of neutral pions and eta mesons
with p_T <16 GeV/c and p_T < 12 GeV/c, respectively, on the centrality of the
collision has been measured at mid-rapidity by the PHENIX experiment at RHIC in
d+Au collisions at sqrt(s_(NN)) = 200 GeV. The measured yields are compared to
those in p + p collisions at the same sqrt(s_(NN)) scaled by the number of
underlying nucleon-nucleon collisions in d+Au. At all centralities the yield
ratios show no suppression, in contrast to the strong suppression seen for
central Au+Au collisions at RHIC. Only a weak p_T and centrality dependence can
be observed.


  Majorana fermions were envisioned by E. Majorana in 1935 to describe
neutrinos. Recently it has been shown that they can be realized even in a class
of electron-doped semiconductors, on which ordinary s-wave superconductivity is
proximity induced, provided the time reversal symmetry is broken by an external
Zeeman field above a threshold. Here we show that in a hole-doped semiconductor
nanowire the threshold Zeeman field for Majorana fermions can be very small for
some magic values of the hole density. In contrast to the electron-doped
systems, smaller Zeeman fields and much stronger spin-orbit coupling and
effective mass of holes allow the hole-doped systems to support Majorana
fermions in a parameter regime which is routinely realized in current
experiments.


  We present 190 galaxy cluster candidates (most at high redshift) based on
galaxy overdensity measurements in the \spitzer/IRAC imaging of the fields
surrounding 646 bent, double-lobed radio sources drawn from the Clusters
Occupied by Bent Radio AGN (COBRA) Survey. The COBRA sources were chosen as
objects in the VLA FIRST survey that lack optical counterparts in the Sloan
Digital Sky Survey (SDSS) to a limit of $m_r=22$, making them likely to lie at
high redshift. This is confirmed by our observations: the redshift distribution
of COBRA sources with estimated redshifts peaks near $z=1$, and extends out to
$z\approx3$. Cluster candidates were identified by comparing our target fields
to a background field and searching for statistically significant
($\ge2\sigma$) excesses in the galaxy number counts surrounding the radio
sources; 190 fields satisfy the $\ge2\sigma$ limit. We find that 530 fields
(82.0\%) have a net positive excess of galaxies surrounding the radio source.
Many of the fields with positive excesses but below the $2\sigma$ cutoff are
likely to be galaxy groups. Forty-one COBRA sources are quasars with known
spectroscopic redshifts, which may be tracers of some of the most distant
clusters known.


  Under noisy conditions, automatic speech recognition (ASR) can greatly
benefit from the addition of visual signals coming from a video of the
speaker's face. However, when multiple candidate speakers are visible this
traditionally requires solving a separate problem, namely active speaker
detection (ASD), which entails selecting at each moment in time which of the
visible faces corresponds to the audio. Recent work has shown that we can solve
both problems simultaneously by employing an attention mechanism over the
competing video tracks of the speakers' faces, at the cost of sacrificing some
accuracy on active speaker detection. This work closes this gap in active
speaker detection accuracy by presenting a single model that can be jointly
trained with a multi-task loss. By combining the two tasks during training we
reduce the ASD classification accuracy by approximately 25%, while
simultaneously improving the ASR performance when compared to the multi-person
baseline trained exclusively for ASR.


  We theoretically and numerically analyze x-ray scattering from asymmetric-top
molecules three-dimensionally aligned using elliptically polarized laser light.
A rigid-rotor model is assumed. The principal axes of the polarizability tensor
are assumed to coincide with the principal axes of the moment of inertia
tensor. Several symmetries in the Hamiltonian are identified and exploited to
enhance the efficiency of solving the time-dependent Schr\"odinger equation for
each rotational state initially populated in a thermal ensemble. Using a
phase-retrieval algorithm, the feasibility of structure reconstruction from a
quasi-adiabatically-aligned sample is illustrated for the organic molecule
naphthalene. The spatial resolution achievable strongly depends on the laser
parameters, the initial rotational temperature, and the x-ray pulse duration.
We demonstrate that for a laser peak intensity of 5 TW/cm^2, a laser pulse
duration of 100 ps, a rotational temperature of 10 mK, and an x-ray pulse
duration of 1 ps, the molecular structure may be probed at a resolution of 1
\AA.


  This letter reports proof-of-principle demonstration of 3D printable,
low-cost, and compact THz spectral splitters based on diffractive optical
elements (DOEs) designed to disperse the incident collimated broadband THz
radiation (0.5 THz - 0.7 THz) at a pre-specified distance. Via inverse design,
we show that it is possible to design such a diffractive optic, which can split
the broadband incident spectrum in any desired fashion, as is evidenced from
both FDTD simulations and measured intensity profiles using a 500-750 GHz VNA.
Due to its straightforward construction without the usage of any movable parts,
our approach, in principle, can have various applications such as in portable,
low-cost spectroscopy as well as in wireless THz communication systems as a THz
demultiplexer.


  Simulation based inference (SBI) methods enable the estimation of posterior
distributions when the likelihood function is intractable, but where model
simulation is feasible. Popular neural approaches to SBI are the neural
posterior estimator (NPE) and its sequential version (SNPE). These methods can
outperform statistical SBI approaches such as approximate Bayesian computation
(ABC), particularly for relatively small numbers of model simulations. However,
we show in this paper that the NPE methods are not guaranteed to be highly
accurate, even on problems with low dimension. In such settings the posterior
cannot be accurately trained over the prior predictive space, and even the
sequential extension remains sub-optimal. To overcome this, we propose
preconditioned NPE (PNPE) and its sequential version (PSNPE), which uses a
short run of ABC to effectively eliminate regions of parameter space that
produce large discrepancy between simulations and data and allow the posterior
emulator to be more accurately trained. We present comprehensive empirical
evidence that this melding of neural and statistical SBI methods improves
performance over a range of examples, including a motivating example involving
a complex agent-based model applied to real tumour growth data.


  Lecture notes for a master-level mathematics course on martingales and
stochastic calculus, held at the University of Orl\'eans, France. With
corrected exercises.
  Contents: Discrete-time martingales, stopping times, convergence theorems.
Brownian motion, It\^o integrals, stochastic differential equations,
diffusions.
  -----
  Notes d'un cours de Master 2 en math\'ematiques, donn\'e \`a l'Universit\'e
d'Orl\'eans. Avec exercices corrig\'es.
  Contenu: Martingales \`a temps discret, temps d'arr\^et, th\'eor\`emes de
convergence. Mouvement Brownien, int\'egrale d'It\^o, \'equations
diff\'erentielles stochastiques, diffusions.


  In this work the robustness of a simple cellular automaton developed by
Bassler and Paczuski to describe the critical state in type-II superconductors
is studied. Two different configurations of pinning centers are introduced and
a new universality class is found. The numerical values of the critical
exponents were calculated following two scaling techniques to ensure the
validity of our results.


  We analyze an experimentally realizable model of bosons in a zig-zag optical
lattice, showing that by rapidly modulating the magnetic field one can tune
interaction parameters and realize an analog of the Haldane phase. We explain
how quantum gas microscopy can be used to detect this phase's non-local string
order and its topological edge states. We model the detection process. We also
find that this model can display supersolid correlations, but argue that they
only occur at parameter values which would be challenging to realize in an
experiment.


  We present optical and near-infrared photometric and spectroscopic
observations of the fast-declining Type Ia Supernova (SN) 2015bo. SN 2015bo is
under-luminous (M$_B$ = -17.67 $\pm$ 0.15 mag) and has a fast-evolving light
curve ($\Delta \mathrm{m}_{15}\mathrm{(B)}$ = 1.91 $\pm$ 0.01 mag and $s_{BV}$
= 0.48 $\pm$ 0.01). It has a unique morphology in the $V-r$ color curve, where
it is bluer than all other SNe in the comparison sample. A $^{56}$Ni mass of
0.17 $\pm$ 0.03 $M_{\odot}$ was derived from the peak bolometric luminosity,
which is consistent with its location on the luminosity-width relation.
Spectroscopically, SN 2015bo is a Cool SN in the Branch classification scheme.
The velocity evolution measured from spectral features is consistent with
1991bg-like SNe. SN 2015bo has a SN twin (similar spectra) and sibling (same
host galaxy), SN 1997cn. Distance moduli of $\mu$ = 34.33 $\pm$ 0.01 (stat)
$\pm$0.11 (sys) mag and $\mu$ = 34.34 $\pm$ 0.04 (stat) $\pm$ 0.12 (sys) mag
were derived for SN 2015bo and SN 1997cn, respectively. These distances are
consistent at the 0.06-$\sigma$ level with each other, and are also consistent
with distances derived using surface-brightness fluctuations and
redshift-corrected cosmology. This suggests that fast-declining SNe could be
accurate distance indicators which should not be excluded from future
cosmological analyses.


  The quantum delayed-choice experiment of Tang et al. [Nature Photonics 6
(2012) 600] is simulated on the level of individual events without making
reference to concepts of quantum theory or without solving a wave equation. The
simulation results are in excellent agreement with the quantum theoretical
predictions of this experiment. The implication of the work presented in the
present paper is that the experiment of Tang et al. can be explained in terms
of cause-and-effect processes in an event-by-event manner.


  We show a purely electronic cooling scheme to cool a charged mechanical
resonator (MR) down to nearly the vibrational ground state by elaborately
tuning bias gate voltages on the electrodes, which couple the MR by Coulomb
interaction. The key step is the modification of time-dependent effective
eigen-frequency of the MR based on the Lewis-Riesenfeld invariant. With respect
to a relevant idea proposed previously [Li et al., Phys. Rev. A 83, 043803
(2011)], our scheme is simpler, more practical and completely within the reach
of current technology.


  The projection filter is a technique for approximating the solutions of
optimal filtering problems. In projection filters, the Kushner--Stratonovich
stochastic partial differential equation that governs the propagation of the
optimal filtering density is projected to a manifold of parametric densities,
resulting in a finite-dimensional stochastic differential equation. Despite the
fact that projection filters are capable of representing complicated
probability densities, their current implementations are limited to Gaussian
family or unidimensional filtering applications. This work considers a
combination of numerical integration and automatic differentiation to construct
projection filter algorithms for more generic problems. Specifically, we
provide a detailed exposition of this combination for the manifold of the
exponential family, and show how to apply the projection filter to
multidimensional cases. We demonstrate numerically that based on comparison to
a finite-difference solution to the Kushner--Stratonovich equation and a
bootstrap particle filter with systematic resampling, the proposed algorithm
retains an accurate approximation of the filtering density while requiring a
comparatively low number of quadrature points. Due to the sparse-grid
integration and automatic differentiation used to calculate the expected values
of the natural statistics and the Fisher metric, the proposed filtering
algorithms are highly scalable. They therefore are suitable to many
applications in which the number of dimensions exceeds the practical limit of
particle filters, but where the Gaussian-approximations are deemed
unsatisfactory.


  We propose a dynamic encoder transducer (DET) for on-device speech
recognition. One DET model scales to multiple devices with different
computation capacities without retraining or finetuning. To trading off
accuracy and latency, DET assigns different encoders to decode different parts
of an utterance. We apply and compare the layer dropout and the collaborative
learning for DET training. The layer dropout method that randomly drops out
encoder layers in the training phase, can do on-demand layer dropout in
decoding. Collaborative learning jointly trains multiple encoders with
different depths in one single model. Experiment results on Librispeech and
in-house data show that DET provides a flexible accuracy and latency trade-off.
Results on Librispeech show that the full-size encoder in DET relatively
reduces the word error rate of the same size baseline by over 8%. The
lightweight encoder in DET trained with collaborative learning reduces the
model size by 25% but still gets similar WER as the full-size baseline. DET
gets similar accuracy as a baseline model with better latency on a large
in-house data set by assigning a lightweight encoder for the beginning part of
one utterance and a full-size encoder for the rest.


  The purpose of this paper is the study of the roots in the mapping class
groups. Let $\Sigma$ be a compact oriented surface, possibly with boundary, let
$\PP$ be a finite set of punctures in the interior of $\Sigma$, and let $\MM
(\Sigma, \PP)$ denote the mapping class group of $(\Sigma, \PP)$. We prove
that, if $\Sigma$ is of genus 0, then each $f \in \MM (\Sigma)$ has at most one
$m$-root for all $m \ge 1$. We prove that, if $\Sigma$ is of genus 1 and has
non-empty boundary, then each $f \in \MM (\Sigma)$ has at most one $m$-root up
to conjugation for all $m \ge 1$. We prove that, however, if $\Sigma$ is of
genus $\ge 2$, then there exist $f,g \in \MM (\Sigma, \PP)$ such that
$f^2=g^2$, $f$ is not conjugate to $g$, and none of the conjugates of $f$
commutes with $g$. Afterwards, we focus our study on the roots of the
pseudo-Anosov elements. We prove that, if $\partial \Sigma \neq \emptyset$,
then each pseudo-Anosov element $f \in \MM(\Sigma, \PP)$ has at most one
$m$-root for all $m \ge 1$. We prove that, however, if $\partial \Sigma =
\emptyset$ and the genus of $\Sigma$ is $\ge 2$, then there exist two
pseudo-Anosov elements $f,g \in \MM (\Sigma)$ (explicitely constructed) such
that $f^m=g^m$ for some $m\ge 2$, $f$ is not conjugate to $g$, and none of the
conjugates of $f$ commutes with $g$. Furthermore, if the genus of $\Sigma$ is
$\equiv 0 (\mod 4)$, then we can take $m=2$. Finally, we show that, if $\Gamma$
is a pure subgroup of $\MM (\Sigma, \PP)$ and $f \in \Gamma$, then $f$ has at
most one $m$-root in $\Gamma$ for all $m \ge 1$. Note that there are finite
index pure subgroups in $\MM (\Sigma, \PP)$.


  We consider basic conceptual questions concerning the relationship between
statistical estimation and causal inference. Firstly, we show how to translate
causal inference problems into an abstract statistical formalism without
requiring any structure beyond an arbitrarily-indexed family of probability
models. The formalism is simple but can incorporate a variety of causal
modelling frameworks, including 'structural causal models', but also models
expressed in terms of, e.g., differential equations. We focus primarily on the
structural/graphical causal modelling literature, however. Secondly, we
consider the extent to which causal and statistical concerns can be cleanly
separated, examining the fundamental question: 'What can be estimated from
data?'. We call this the problem of estimability. We approach this by analysing
a standard formal definition of 'can be estimated' commonly adopted in the
causal inference literature -- identifiability -- in our abstract statistical
formalism. We use elementary category theory to show that identifiability
implies the existence of a Fisher-consistent estimator, but also show that this
estimator may be discontinuous, and thus unstable, in general. This difficulty
arises because the causal inference problem is, in general, an ill-posed
inverse problem. Inverse problems have three conditions which must be satisfied
to be considered well-posed: existence, uniqueness, and stability of solutions.
Here identifiability corresponds to the question of uniqueness; in contrast, we
take estimability to mean satisfaction of all three conditions, i.e.
well-posedness. Lack of stability implies that naive translation of a causally
identifiable quantity into an achievable statistical estimation target may
prove impossible. Our article is primarily expository and aimed at unifying
ideas from multiple fields, though we provide new constructions and proofs.


  We define and study structural properties of hypergraphs of models of a
theory including lattice ones. Characterizations for the lattice properties of
hypergraphs of models of a theory, as well as for structures on sets of
isomorphism types of models of a theory, are given.


  Despite much recent work, detecting out-of-distribution (OOD) inputs and
adversarial attacks (AA) for computer vision models remains a challenge. In
this work, we introduce a novel technique, DAAIN, to detect OOD inputs and AA
for image segmentation in a unified setting. Our approach monitors the inner
workings of a neural network and learns a density estimator of the activation
distribution. We equip the density estimator with a classification head to
discriminate between regular and anomalous inputs. To deal with the
high-dimensional activation-space of typical segmentation networks, we
subsample them to obtain a homogeneous spatial and layer-wise coverage. The
subsampling pattern is chosen once per monitored model and kept fixed for all
inputs. Since the attacker has access to neither the detection model nor the
sampling key, it becomes harder for them to attack the segmentation network, as
the attack cannot be backpropagated through the detector. We demonstrate the
effectiveness of our approach using an ESPNet trained on the Cityscapes dataset
as segmentation model, an affine Normalizing Flow as density estimator and use
blue noise to ensure homogeneous sampling. Our model can be trained on a single
GPU making it compute efficient and deployable without requiring specialized
accelerators.


  We revisit the duality between ALE singularities in M-theory and 7-branes on
a circle in F-theory. We see that a frozen M-theory singularity maps to a
circle compactification involving a rotation of the plane transverse to the
7-brane, showing an interesting correspondence between commuting triples in
simply-laced groups and Kodaira's classification of singular elliptic
fibrations. Our analysis strongly suggests that the O7+ plane is the only
completely frozen F-theory singularity.


  Light scalar fields present during inflation can lead to interesting
observable signatures, especially in models with non-equilibrium reheating
dynamics. We study a supersymmetric hybrid inflation model with a third scalar
whose lightness is protected by symmetry, using analytical and numerical
techniques, and demonstrate that the amplitude, the spectral index and the
non-Gaussianity parameter fNL of the primordial curvature perturbation are
within the Planck observational bounds for suitable parameter values.


  A non-Boolean extension of the classical probability model is proposed. The
non-Boolean probabilities reproduce typical quantum phenomena. The proposed
model is more general and more abstract, but easier to interpret, than the
quantum mechanical Hilbert space formalism and exhibits a particular phenomenon
(state-independent conditional probabilities) which may provide new
opportunities for an understanding of the quantum measurement process. Examples
of the proposed model are provided, using Jordan operator algebras.


  We investigate the possibility of obtaining inflationary solutions of the
slow roll type from a low energy Lagrangian coming from superstrings. The
advantage of such an approach is that in these theories the scalar potential
has only one free parameter (the Planck scale) and therefore no unnatural fine
tuning may be accommodated. We find that in any viable scheme the dilaton and
the moduli fields have to be stabilized and that before this happens, no other
field may be used as the inflaton. Then inflation may occur due to chiral
matter fields. Demanding that the potential terms associated with the chiral
fields do not spoil the dilaton and moduli minimization leads to severe
constraints on the magnitude of the density fluctuations.


  When a hot system cools down faster than an equivalent cold one, it exhibits
the Mpemba Effect. This counterintuitive phenomenon was observed in several
systems including water, magnetic alloys and polymers. In most experiments the
system is coupled to the bath through its boundaries, but all theories so far
assumed bulk coupling. Here we build a general framework for boundary coupling
relaxation and show that the Mpemba effect persists in these cases.
Surprisingly, it can survive even an arbitrarily weak couplings. An example is
given in the Ising antiferromagnetic chain.


  Artificial Intelligence (AI) is envisioned to play a pivotal role in
empowering intelligent, adaptive and autonomous security management in 5G and
beyond networks, thanks to its potential to uncover hidden patterns from a
large set of time-varying multi-dimensional data, and deliver faster and
accurate decisions. Unfortunately, AI's capabilities and vulnerabilities make
it a double-edged sword that may jeopardize the security of future networks.
This paper sheds light on how AI may impact the security of 5G and its
successive from its posture of defender, offender or victim, and recommends
potential defenses to safeguard from malevolent AI while pointing out their
limitations and adoption challenges.


  This is an introductory account of the emergence of conformal invariance in
the scaling limit of planar critical percolation. We give an exposition of
Smirnov's theorem (2001) on the conformal invariance of crossing probabilities
in site percolation on the triangular lattice. We also give an introductory
account of Schramm-Loewner evolutions (SLE(k)), a one-parameter family of
conformally invariant random curves discovered by Schramm (2000). The article
is organized around the aim of proving the result, due to Smirnov (2001) and to
Camia and Newman (2007), that the percolation exploration path converges in the
scaling limit to chordal SLE(6). No prior knowledge is assumed beyond some
general complex analysis and probability theory.


  Let $M$ be a Riemannian 3-manifold of nonnegative Ricci curvature, Ric $\geq
0.$ We suppose that $M$ is conformally flat and simply connected or more
generally that it admits a conformal immersion into the standard 3-sphere. Let
$\Sigma$ be a compact connected and orientable surface immersed in $M$ which is
a stable constant mean curvature (CMC) surface or an index one minimal surface.
We prove that $\Sigma$ is homeomorphic either to a sphere or to a torus.
Moreover, in case $\Sigma$ is homeomorphic to a torus, then it is embedded,
minimal, conformal to a flat square torus and Ric$(N)=0$ where $N$ is a unit
field normal to $\Sigma.$ The result is sharp, we can perturb the standard
metric on the 3-sphere in its conformal class to obtain metrics of nonnegative
Ricci curvature admitting minimal tori which are stable as CMC surfaces.
  As a consequence, in any 3-sphere of positive Ricci curvature which is
conformally flat, the isoperimetric domains are topologically 3-balls. This
proves a special case of a conjecture of A. Ros.


  We report here on a survey of N-body simulations of encounters between
spherical galaxies. Initial systems are isotropic Jaffe models. Different sets
of mass ratios, impact parameters and orbital energies are studied. Both merger
remnants and systems perturbed after a non-merging encounter are analysed and
compared to real-life elliptical galaxies. The properties of merger remnants
show a large variety. Merger remnants resulting from head-on encounters are
mainly non-rotating prolate spheroids. Merger remnants from models with angular
momentum different from zero are triaxial or mildly oblate spheroids supported
in part by rotation. The velocity distributions are biased towards the radial
direction in the prolate case and the tangential direction in the oblate case.
Non-mergers are affected in various ways, depending on the orbital
characteristics. We conclude that many of the global properties of real-life
ellipticals can in principle be attributed to a merger of spherical
progenitors.


  We present low-resolution ($R\sim 90$) and medium-resolution ($R\sim 2500$)
spectropolarimetry of Nova V475 Sct with the HBS instrument, mounted on the
0.91-m telescope at the Okayama Astrophysical Observatory, and with FOCAS,
mounted on the 8.2-m Subaru telescope. We estimated the interstellar
polarization toward the nova from the steady continuum polarization components
and H$\alpha$ line emission components. After subtracting the interstellar
polarization component from the observations, we found that the H$\alpha$
emission seen on 2003 October 7 was clearly polarized. In the polarized flux
spectrum, the H$\alpha$ emission had a distinct red wing extending to $\sim
+4900$ km s$^{-1}$ and a shoulder around $+3500$ km s$^{-1}$, showing a
constant position angle of linear polarization $\theta_{\rm *}\simeq
155\arcdeg\pm 15\arcdeg$. This suggests that the nova had an asymmetric outflow
with a velocity of $v_{\rm wind}\simeq 3500$ km s$^{-1}$ or more, which is six
times higher than the expansion velocity of the ionized shell at the same
epoch. Such a high-velocity component has not previously been reported for a
nova in the `moderately fast' speed class. Our observations suggest the
occurrence of violent mass-loss activity in the nova binary system even during
the common-envelope phase. The position angle of the polarization in the
H$\alpha$ wing is in good agreement with that of the continuum polarization
found on 2003 September 26 ($p_{\rm *}\simeq 0.4$--0.6 %), which disappeared
within the following 2 d. The uniformity of the PA between the continuum
polarization and the wing polarization on October 7 suggests that the axis of
the circumstellar asymmetry remained nearly constant during the period of our
observations.


  Intelligent interaction with the physical world requires perceptual abilities
beyond vision and hearing; vibrant tactile sensing is essential for autonomous
robots to dexterously manipulate unfamiliar objects or safely contact humans.
Therefore, robotic manipulators need high-resolution touch sensors that are
compact, robust, inexpensive, and efficient. The soft vision-based haptic
sensor presented herein is a miniaturized and optimized version of the
previously published sensor Insight. Minsight has the size and shape of a human
fingertip and uses machine learning methods to output high-resolution maps of
3D contact force vectors at 60 Hz. Experiments confirm its excellent sensing
performance, with a mean absolute force error of 0.07 N and contact location
error of 0.6 mm across its surface area. Minsight's utility is shown in two
robotic tasks on a 3-DoF manipulator. First, closed-loop force control enables
the robot to track the movements of a human finger based only on tactile data.
Second, the informative value of the sensor output is shown by detecting
whether a hard lump is embedded within a soft elastomer with an accuracy of
98%. These findings indicate that Minsight can give robots the detailed
fingertip touch sensing needed for dexterous manipulation and physical
human-robot interaction.


  In this paper we prove the Lipschitz regularity for local minimizers of
convex variational integrals of the form \[ \mathfrak{F}( v, \Omega )=
\int_{\Omega} \! F(x, Dv(x)) \, dx, \] where, for ${n > 2}$ and $N\ge 1$,
$\Omega$ is a bounded open set in $\mathbb{R}^n$, $u \in W^{1,1}(\Omega ,
\mathbb{R}^N)$ and the energy density $F:\Omega\times \mathbb{R}^{N \times
n}\to \mathbb{R}$ satisfies the so called variable growth conditions. The main
novelty of the paper is that we assume an almost critical regularity in the
Orlicz Sobolev setting for the energy density as a function of the $x$
variable.


  In this paper we introduce a simple method of searching for the prime pairs
in the famous Goldbach Conjecture. The method, which is based on certain
integer identities as well as an observation related to the remainder property,
enables us to cut the search length by half and therefore can be considered as
a short cut in searching for the prime pairs in the Goldbach Conjecture.


  We compute the next-to-next-to-leading order (NNLO) QCD corrections to b \to
c l \bar \nu_l decay rate at a fully differential level. Arbitrary cuts on
kinematic variables of the decay products can be imposed. Our computation can
be used to study the NNLO QCD corrections to the total decay rate as well as to
the lepton energy, hadronic invariant mass and hadronic energy moments and to
incorporate those corrections into global fits of inclusive semileptonic
B-decays.


  The entanglement entropy corresponding to a smooth region in general
three-dimensional CFTs contains a constant universal term, $-F \subset
S_{\text{EE}}$. For a disk region, $F|_{\rm disk}\equiv F_0$ coincides with the
free energy on $\mathbb{S}^3$ and provides an RG-monotone for general theories.
As opposed to the analogous quantity in four dimensions, the value of $F$
generally depends in a complicated (and non-local) way on the geometry of the
region and the theory under consideration. For small geometric deformations of
the disk in general CFTs as well as for arbitrary regions in holographic
theories, it has been argued that $F$ is precisely minimized by disks. Here, we
argue that $F$ is globally minimized by disks with respect to arbitrary regions
and for general theories. The proof makes use of the strong subadditivity of
entanglement entropy and the geometric fact that one can always place an
osculating circle within a given smooth entangling region. For topologically
non-trivial entangling regions with $n_B$ boundaries, the general bound can be
improved to $F \geq n_B F_0$. In addition, we provide accurate approximations
to $F$ valid for general CFTs in the case of elliptic regions for arbitrary
values of the eccentricity which we check against lattice calculations for free
fields. We also evaluate $F$ numerically for more general shapes in the
so-called "Extensive Mutual Information model", verifying the general bound.


  Hyperspectral signal reconstruction aims at recovering the original spectral
input that produced a certain trichromatic (RGB) response from a capturing
device or observer. Given the heavily underconstrained, non-linear nature of
the problem, traditional techniques leverage different statistical properties
of the spectral signal in order to build informative priors from real world
object reflectances for constructing such RGB to spectral signal mapping.
However, most of them treat each sample independently, and thus do not benefit
from the contextual information that the spatial dimensions can provide. We
pose hyperspectral natural image reconstruction as an image to image mapping
learning problem, and apply a conditional generative adversarial framework to
help capture spatial semantics. This is the first time Convolutional Neural
Networks -and, particularly, Generative Adversarial Networks- are used to solve
this task. Quantitative evaluation shows a Root Mean Squared Error (RMSE) drop
of 33.2% and a Relative RMSE drop of 54.0% on the ICVL natural hyperspectral
image dataset.


  In this paper, we develop new methods for estimating average treatment
effects in observational studies, focusing on settings with more than two
treatment levels under unconfoundedness given pre-treatment variables. We
emphasize subclassification and matching methods which have been found to be
effective in the binary treatment literature and which are among the most
popular methods in that setting. Whereas the literature has suggested that
these particular propensity-based methods do not naturally extend to the
multi-level treatment case, we show, using the concept of weak
unconfoundedness, that adjusting for or matching on a scalar function of the
pre-treatment variables removes all biases associated with observed
pre-treatment variables. We apply the proposed methods to an analysis of the
effect of treatments for fibromyalgia. We also carry out a simulation study to
assess the finite sample performance of the methods relative to previously
proposed methods.


  We present a list of datasets and their best models with the goal of
advancing the state-of-the-art in object detection by placing the question of
object recognition in the context of the two types of state-of-the-art methods:
one-stage methods and two stage-methods. We provided an in-depth statistical
analysis of the five top datasets in the light of recent developments in
granulated Deep Learning models - COCO minival, COCO test, Pascal VOC 2007,
ADE20K, and ImageNet. The datasets are handpicked after closely comparing them
with the rest in terms of diversity, quality of data, minimal bias, labeling
quality etc. More importantly, our work extends to provide the best combination
of these datasets with the emerging models in the last two years. It lists the
top models and their optimal use cases for each of the respective datasets. We
have provided a comprehensive overview of a variety of both generic and
specific object detection models, enlisting comparative results like inference
time and average precision of box (AP) fixed at different Intersection Over
Union (IoUs) and for different sized objects. The qualitative and quantitative
analysis will allow experts to achieve new performance records using the best
combination of datasets and models.


  We show that unconventional boundary phenomena occur in the $3Q$ charge bond
orders on the hexagonal lattices. At the Van Hove singularity with three
nesting momenta, $3Q$ orders can trigger a $\text{C}_6$-symmetric insulator
under bond modulations. On the kagome lattice, in-gap corner states appear in
the energy spectrum and carry fractional corner charge $-2e/3$. Such corner
phenomena originate from the corner filling anomaly and indicate a higher-order
topological insulator. The in-gap corner states are also observed on the
triangular lattice. The honeycomb lattice does not support fractional corner
charges, while in-gap edge states are observed. We discuss possible indications
to the experimentally uncovered charge bond orders in the kagome metals
$\text{AV}_3\text{Sb}_5$ with $\text{A}=\text{K},\text{Rb},\text{Cs}$. With
layer stacking along the out-of-plane direction, the corner states can
constitute the hinge states with fractional charge densities.


  We find a family of planar bipartite graphs all of whose Lombardi drawings
(drawings with circular arcs for edges, meeting at equal angles at the
vertices) are nonplanar. We also find families of embedded series-parallel
graphs and apex-trees (graphs formed by adding one vertex to a tree) for which
there is no planar Lombardi drawing consistent with the given embedding.


  Moduli spaces of Abelian and quadratic differentials are stratified by
multiplicities of zeroes; connected components of the strata correspond to
ergodic components of the Teichmuller geodesic flow. It is known that the
strata are not necessarily connected; the connected components were recently
classified by M. Kontsevich and the author and by E. Lanneau. The strata can be
also viewed as families of flat metrics with conical singularities and with
Z/2Z-holonomy.
  For every connected component of each stratum of Abelian and quadratic
differentials we construct an explicit representative which is a
Jenkins-Strebel differential with a single cylinder. By an elementary variation
of this construction we represent almost every Abelian (quadratic) differential
in the corresponding connected component of the stratum as a polygon with
identified pairs of edges, where combinatorics of identifications is explicitly
described.
  Specifically, the combinatorics is expressed in terms of a generalized
permutation. For any component of any stratum of Abelian and quadratic
differentials we construct a generalized permutation (linear involution) in the
corresponding extended Rauzy class.


  We consider the constrained sampling problem where the goal is to sample from
a target distribution $\pi(x)\propto e^{-f(x)}$ when $x$ is constrained to lie
on a convex body $\mathcal{C}$. Motivated by penalty methods from continuous
optimization, we propose penalized Langevin Dynamics (PLD) and penalized
underdamped Langevin Monte Carlo (PULMC) methods that convert the constrained
sampling problem into an unconstrained sampling problem by introducing a
penalty function for constraint violations. When $f$ is smooth and gradients
are available, we get $\tilde{\mathcal{O}}(d/\varepsilon^{10})$ iteration
complexity for PLD to sample the target up to an $\varepsilon$-error where the
error is measured in the TV distance and $\tilde{\mathcal{O}}(\cdot)$ hides
logarithmic factors. For PULMC, we improve the result to
$\tilde{\mathcal{O}}(\sqrt{d}/\varepsilon^{7})$ when the Hessian of $f$ is
Lipschitz and the boundary of $\mathcal{C}$ is sufficiently smooth. To our
knowledge, these are the first convergence results for underdamped Langevin
Monte Carlo methods in the constrained sampling that handle non-convex $f$ and
provide guarantees with the best dimension dependency among existing methods
with deterministic gradient. If unbiased stochastic estimates of the gradient
of $f$ are available, we propose PSGLD and PSGULMC methods that can handle
stochastic gradients and are scaleable to large datasets without requiring
Metropolis-Hasting correction steps. For PSGLD and PSGULMC, when $f$ is
strongly convex and smooth, we obtain $\tilde{\mathcal{O}}(d/\varepsilon^{18})$
and $\tilde{\mathcal{O}}(d\sqrt{d}/\varepsilon^{39})$ iteration complexity in
W2 distance. When $f$ is smooth and can be non-convex, we provide finite-time
performance bounds and iteration complexity results. Finally, we illustrate the
performance on Bayesian LASSO regression and Bayesian constrained deep learning
problems.


  The dynamics of a one dimensional Ising spin system is investigated using
three families of local update rules, the Galam majority rules, Glauber inflow
influences and Sznadj outflow drives. Given an initial density p of up spins
the probability to reach a final state with all spins up is calculated exactly
for each choice. The various formulas are compared to a series of previous
calculations obtained analytically using the Kirkwood approximation. They turn
out to be identical. The apparent discrepancy with the Galam unifying frame is
addressed. The difference in the results seems to stem directly from the
implementation of the local update rule used to perform the associated
numerical simulations. The findings lead to view the non stepwise exit
probability as an artifact of the one dimensional finite size system with fixed
spins. The suitability and the significance to perform numerical simulations to
model social behavior without solid constraints is discussed and the question
of what it means to have a mean field result in this context is addressed.


  Given a $1$-cohomology class $u$ on a closed manifold $M$, we define a
Novikov fundamental group associated to $u$, generalizing the usual fundamental
group in the same spirit as Novikov homology generalizes Morse homology to the
case of non exact $1$-forms.
  As an application, lower bounds for the minimal number of index $1$ and $2$
critical points of Morse closed $1$-forms are obtained, that are different in
nature from those derived from the Novikov homology.


  We prove that the pure state space is homogeneous under the action of the
automorphism group (or the subgroup of asymptotically inner automorphisms) for
all the separable simple C*-algebras. The first result of this kind was shown
by Powers for the UHF algebras some 30 years ago.


  We introduce the \textit{generalized join the shortest queue model with
retrials} and two infinite capacity orbit queues. Three independent Poisson
streams of jobs, namely a \textit{smart}, and two \textit{dedicated} streams,
flow into a single server system, which can hold at most one job. Arriving jobs
that find the server occupied are routed to the orbits as follows: Blocked jobs
from the \textit{smart} stream are routed to the shortest orbit queue, and in
case of a tie, they choose an orbit randomly. Blocked jobs from the
\textit{dedicated} streams are routed directly to their orbits. Orbiting jobs
retry to connect with the server at different retrial rates, i.e.,
heterogeneous orbit queues. Applications of such a system are found in the
modelling of wireless cooperative networks. We are interested in the asymptotic
behaviour of the stationary distribution of this model, provided that the
system is stable. More precisely, we investigate the conditions under which the
tail asymptotic of the minimum orbit queue length is exactly geometric.
Moreover, we apply a heuristic asymptotic approach to obtain approximations of
the steady-state joint orbit queue-length distribution. Useful numerical
examples are presented, and shown that the results obtained through the
asymptotic analysis and the heuristic approach agreed.


  A Content Delivery Network (CDN) is a dynamic and complex service system. It
causes a huge amount of traffic on the network infrastructure of Internet
Service Providers (ISPs). Oftentimes, CDN providers and ISPs struggle to find
an efficient and appropriate way to cooperate for mutual benefits. This
challenge is key to push the quality of service (QoS) for the end-user. We
model, simulate, and optimize the behavior of a CDN to provide cooperative
solutions and to improve the QoS. Therefor, we determine reasonable server
locations, balance the amount of servers and improve the user assignments to
the servers. These aspects influence run time effects like caching at the
server, response time and network load at specific links. Especially, user
request history and profiles are considered to improve the overall performance.
Since we consider multiple objectives, we aim to provide a diverse set of
pareto optimal solutions using simulation based optimization.


  Our ability to explore the cosmos by direct contact has been limited to a
small number of lunar and interplanetary missions. However, the NASA Starlight
program points a path forward to send small, relativistic spacecraft far
outside our solar system via standoff directed-energy propulsion. These
miniaturized spacecraft are capable of robotic exploration but can also
transport seeds and organisms, marking a profound change in our ability to both
characterize and expand the reach of known life. Here we explore the biological
and technological challenges of interstellar space biology, focusing on
radiation-tolerant microorganisms capable of cryptobiosis. Additionally, we
discuss planetary protection concerns and other ethical considerations of
sending life to the stars.


  Our talk is intended for the session in memory of Mitya Diakonov. The problem
is considered of existence of flavor multiplets consisting of multi-quark
baryons. We have argued that the S-matrix should have poles, at least Regge
ones, with any quantum numbers, including exotic. This is a novel argument for
possible a proof, yet there are no theoretical arguments to forbid exotics.
Then we apply the partial-wave analysis (PWA) with addressing mainly to the
non-strange exotic members of the anti-decuplet or even of higher multiplets.
It suggested new N(1680) as a possible partner of Theta+. Later independent
measurements of several collaborations seem to support our finding for N(1680),
though its quantum numbers still wait for investigation. Similar approach to
pi+ - proton scattering, in combination with K+ - proton scattering, suggests a
number of candidates for 27-plets. Their interesting feature is possible
existence of both very wide and very narrow baryon states. This phenomenon may
be analogous to recent Weinberg's suggestion for tetra-quark mesons. The
situation is worth of further theoretical and experimental studies.


  Level statistics is discussed for XXZ spin chains with discrete symmetries
for some values of the next-nearest-neighbor (NNN) coupling parameter. We show
how the level statistics of the finite-size systems depends on the NNN coupling
and the XXZ anisotropy, which should reflect competition among quantum chaos,
integrability and finite-size effects. Here discrete symmetries play a central
role in our analysis. Evaluating the level-spacing distribution, the spectral
rigidity and the number variance, we confirm the correspondence between
non-integrability and Wigner behavior in the spectrum. We also show that
non-Wigner behavior appears due to mixed symmetries and finite-size effects in
some nonintegrable cases.


  We present a systematic study of the 2nd order scalar, vector and tensor
metric perturbations in the Einstein-de Sitter Universe in synchronous
coordinates. For the scalar-scalar coupling between 1st order perturbations, we
decompose the 2nd order perturbed Einstein equation into the respective field
equations of 2nd order scalar, vector, and tensor perturbations, and obtain
their solutions with general initial conditions. In particular, the decaying
modes of solution are included, the 2nd order vector is generated even the 1st
order vector is absent, and the solution of 2nd order tensor corrects that in
literature. We perform general synchronous-to-synchronous gauge transformations
up to 2nd order generated by a 1st order vector field $\xi^{(1)\mu}$ and a 2nd
order $\xi^{(2)\mu}$. All the residual gauge modes of 2nd order metric
perturbations and density contrast are found, and their number is substantially
reduced when the transformed 3-velocity of dust is set be zero. Moreover, we
show that only $\xi^{(2)\mu}$ is effective in carrying out 2nd order
transformations that we consider, because $\xi^{(1)\mu}$ has been used in
obtaining the 1st order perturbations. Holding the 1st order perturbations
fixed, the transformations by $\xi^{(2)\mu}$ on the 2nd order perturbations
have the same structure as those by $\xi^{(1)\mu}$ on the 1st order
perturbations.


  This paper presents a human-robot trust integrated task allocation and motion
planning framework for multi-robot systems (MRS) in performing a set of tasks
concurrently. A set of task specifications in parallel are conjuncted with MRS
to synthesize a task allocation automaton. Each transition of the task
allocation automaton is associated with the total trust value of human in
corresponding robots. Here, the human-robot trust model is constructed with a
dynamic Bayesian network (DBN) by considering individual robot performance,
safety coefficient, human cognitive workload and overall evaluation of task
allocation. Hence, a task allocation path with maximum encoded human-robot
trust can be searched based on the current trust value of each robot in the
task allocation automaton. Symbolic motion planning (SMP) is implemented for
each robot after they obtain the sequence of actions. The task allocation path
can be intermittently updated with this DBN based trust model. The overall
strategy is demonstrated by a simulation with 5 robots and 3 parallel subtask
automata.


  Current development of micro-scale technologies increases the interest to
viscous flows with low and moderate Reynolds numbers. This work theoretically
studies the entrainment flow of a viscous jet emerging from a plane wall into a
half space. Methods are developed to find physically meaningful similarity
solutions of the Navier-Stokes equations with finite values of mass and
momentum fluxes and having no characteristic size. Two models are considered:
flow dominated by momentum flux and flow dominated by mass flux. A new
one-parameter set of momentum-dominated similarity solutions is found. Two
linearly independent mass-dominated similarity solutions are found. Algorithms
are proposed to evaluate the parameters of the similarity models from the mass
and momentum balances. Distributions of flow parameters and stresses at the
wall are calculated for the similarity models. They are compared with the
corresponding distributions obtained by computational fluid dynamics for a more
realistic model with a finite size of the jet origin and competitive influence
of the mass and momentum fluxes. Such comparison validates the mass-dominated
similarity model at the jet Reynolds number Re <= 10 and the momentum-dominated
similarity model at Re >= 30. The obtained results are applied to the problem
of evaporation at selective laser melting. It is shown that the theoretically
estimated flow velocity corresponds to the experimentally observed one. The
theory explains formation of the experimentally observed denuded zone and its
widening with decreasing the pressure of the ambient gas.


  We calculate the "naive non-abelianization" (NNA) contributions of the
higher-twist Feynman diagrams to the large-$p_T$ inclusive pion production
cross section in proton-proton collisions in the case of the running coupling
and frozen coupling approaches. We compare the resummed "naive
non-abelianization" higher-twist cross sections with the ones obtained in the
framework of the frozen coupling approach and leading-twist cross section. The
structure of infrared renormalon singularities of the higher twist subprocess
cross section and it's resummed expression are found. We discuss the
phenomenological consequences of possible higher-twist contributions to the
pion production in proton-proton collisions in within NNA.


  The interplay between the collective dynamics of the quadrupole and octupole
deformation degree of freedom is discussed in a series of Sm and Gd isotopes
both at the mean field level and beyond, including parity symmetry restoration
and configuration mixing. Physical properties like negative parity excitation
energies, E1 and E3 transition probabilities are discussed and compared to
experimental data. Other relevant intrinsic quantities like dipole moments,
ground state quadrupole moments or correlation energies associated to symmetry
restoration and configuration mixing are discussed. For the considered
isotopes, the quadrupole-octupole coupling is found to be weak and most of the
properties of negative parity states can be described in terms of the octupole
degree of freedom alone.


  The screening of impurities in plasma with Bose-Einstein condensate of
electrically charged bosons is considered. It is shown that the screened
potential is drastically different from the usual Debye one. The polarization
operator of photons in plasma acquires infrared singular terms at small photon
momentum and the screened potential drops down as a power of distance and even
has an oscillating behavior, similar to the Friedel oscillations in plasma with
degenerate fermions. The magnetic properties of the cosmological plasma with
condensed W-bosons are also discussed. It is shown that W-bosons condense in
the ferromagnetic state. It could lead to spontaneous magnetization of the
primeval plasma. The created magnetic fields may seed galactic and
intergalactic magnetic fields observed in the present-day universe.


  Let Z be an algebraic space of finite type over a field, equipped with an
action of the multiplicative group $G_m$. In this situation we define and study
a certain algebraic space equipped with an unramified morphism to $A^1\times
Z\times Z$, where $A^1$ is the affine line. (If Z is affine and smooth this is
just the closure of the graph of the action map $G_m\times Z\to Z$.)
  In articles joint with D.Gaitsgory we use this set-up to prove a new result
in the geometric theory of automorphic forms and to give a new proof of a very
important theorem of T. Braden.


  The nonclassicality of a macroscopic single-mode optical superposition state
is potentially convertible into entanglement, when the state is mixed with the
vacuum on a beam splitter. Considering light beams with polarization degree of
freedom in Euclidean space as coherent product states in a bipartite Hilbert
space, we propose a method to convert the two orthogonal polarizations into
simultaneous entanglement and classical nonseparability through nonclassicality
in the superpositions of coherent and displaced Fock states. Equivalent Bell
state emerges from the resulted superpositions and the proportion of mixed
entanglement and nonseparablity is determined by the displacement amplitudes
along the polarization directions. We characterize the state nonclassicality
via features in Wigner distributions and propose an experimental method for
generating these states and measuring them via homodyne tomography.


  Entangled photons play a pivotal role in the distribution of quantum
information in quantum networks. However, the frequency bands for optimal
transmission and storage of photons are not necessarily the same. Here we
experimentally demonstrate the coherent frequency conversion of photons
entangled in their polarization, a widely used degree of freedom in photonic
quantum information processing. We verify the successful entanglement
conversion by violating a Clauser-Horne-Shimony-Holt (CHSH) Bell inequality and
fully confirm that our characterised fidelity of entanglement transfer is close
to unity using both state and process tomography. Our implementation is robust
and flexible, making it a practical building block for future quantum networks.


  Frameworks, such as MapReduce and Hadoop are abundant nowadays. They seek to
reap benefits of parallelization, albeit subject to a synchronization
constraint at the output. Fork-Join (FJ) queuing models are used to analyze
such systems. Arriving jobs are split into tasks each of which is mapped to
exactly one server. A job leaves the system when all of its tasks are executed.
  As a metric of performance, we consider waiting times for both
work-conserving and non-work conserving server systems under a mathematical
set-up general enough to take into account possible phase-type behavior of the
servers, and as suggested by recent evidences, bursty arrivals.
  To this end, we present a Markov-additive process framework for an FJ system
and provide computable bounds on tail probabilities of steady-state waiting
times, for both types of servers separately. We apply our results to three
scenarios, namely, non-renewal (Markov-modulated) arrivals, servers showing
phase-type behavior, and Markov-modulated arrivals and services. We compare our
bounds against estimates obtained through simulations and also provide a
theoretical conceptualization of provisions in FJ systems. Finally, we
calibrate our model with real data traces, and illustrate how our bounds can be
used to devise provisions.


  While the Hubble constant can be derived from observable time delays between
images of lensed quasars, the result is often highly sensitive to assumptions
and systematic uncertainties in the lensing model. Unlike most previous authors
we explore a broad class of models with non-parametric lens radial profile and
allow for non-elliptical lens potentials. The axis ratio and position angle of
the lens can be determined from the image positions of quadruple gravitational
lensed systems by solving the lens equation semi-analytically, independent of
the radial profile. We give simple equations for estimating the power-law slope
of the lens density directly from the image positions and for estimating the
time delay ratios. Our method greatly simplifies the numerics for fitting
observations and is fast in exploring the model parameter space. As an
illustration we apply the model to PG1115+080. We show that the measured image
positions and time delays do not uniquely determine the Hubble constant. The
mass-to-light ratio of the lens galaxy increases with radius, higher at image C
than at image B.


  The Giornata Sesta about the Force of Percussion is a relatively less known
Chapter from the Galileo's masterpiece "Discourse about Two New Sciences". It
was first published lately (1718), long after the first edition of the Two New
Sciences (1638) and Galileo's death (1642). The Giornata Sesta focuses on how
to quantify the percussion force caused by a body in movement, and describes a
very interesting experiment known as "the two-bucket experiment". In this
paper, we review this experiment reported by Galileo, develop a steady-state
theoretical model, and solve its transient form numerically; additionally, we
report the results from one real simplified analogous experiment. Finally, we
discuss the conclusions drawn by Galileo -- correct, despite a probably
unnoticeable imbalance --, showing that he did not report the thrust force
component in his setup -- which would be fundamental for the correct
calculation of the percussion force.


  Magnetic activity in the atmospheres of stars produces a number of
spectroscopic signatures that are visible in the shape and strength of spectral
lines. These signatures can be used to access, among other things, the
variability of the magnetic activity, or its infuence on other parameters such
as the measured radial velocity (RV). This latter is of utmost importance for
the detection and characterization of planets orbiting other stars. ACTIN is a
Python program to calculate stellar activity indices. The program reads input
data either from .fits files returned by the pipelines of spectrographs, or
from .rdb tables. It extracts automatically the spectral data required to
calculate spectral activity indices. The output is an .rdb table, with the
calculated stellar activity indices for each date (Julian Date), as well as the
RV and Cross-Correlation Function profile parameters, if available. It also
outputs timeseries plots of the activity indices and plots the spectral lines
used to compute the indices.


  Single crystals of A2Cr3As3 (A = K, Rb) were successfully grown using a
self-flux method and studied via structural, transport and thermodynamic
measurement techniques. The superconducting state properties between the two
species are similar, with critical temperatures of 6.1 K and 4.8 K in K2Cr3As3
and Rb2Cr3As3, respectively. However, the emergence of a strong normal state
electronic anisotropy in Rb2Cr3As3 suggests a unique electronic tuning
parameter is coupled to the inter-chain spacing in the A2Cr3As3 structure,
which increases with alkali metal ionic size while the one-dimensional
[(Cr3As3)^{2-}]_{\infty} chain structure itself remains essentially unchanged.
Together with dramatic enhancements in both conductivity and magnetoresistance
(MR), the appearance of a strong anisotropy in the MR of Rb2Cr3As3 is
consistent with the proposed quasi-one-dimensional character of band structure
and its evolution with alkali metal species in this new family of
superconductors.


  We present high angular resolution ($\sim$ 3$''$) and sensitive 1.3 mm
continuum, cyanogen (CN) and vinyl cyanide (C$_2$H$_3$CN) line observations
made with the Submillimeter Array (SMA) toward one of most highly obscured
objects of the W51 IRS2 region, W51 North. We find that the CN line exhibits a
pronounced inverse P-Cygni profile indicating that the molecular gas is
infalling inwards this object with a mass accretion rate between 4 and 7
$\times$ 10$^{-2}$ M$_\odot$ yr$^{-1}$. The C$_2$H$_3$CN traces an east-west
rotating molecular envelope that surrounds either a single obscured (proto)star
with a kinematic mass of 40 M$_{\odot}$ or a small central cluster of B-type
stars and that is associated with a compact high velocity bipolar outflow
traced by H$_2$O masers and SiO molecular emission. We thus confirm that the
W51 North region is part of the growing list of young massive star forming
regions that have been associated with infalling motions and with large mass
accretion rates ($\sim$ 10$^{-2}$ -- 10$^{-4}$), strengthening the evidence for
massive stars forming with very high accretion rates sufficient to quench the
formation of an UCHII region.


  WEST (Tungsten Environment in Steady-State Tokamak) will be operating by the
end of 2016 as a test bed for the ITER divertor components in long pulse
operation. In this context, radiative cooling of highly ionized impurities like
tungsten (W) sputtered from Plasma Facing Components (PFC) into the plasma core
is a critical issue since even small impurity concentrations below 10-4 degrade
significantly plasma performances and can lead to radiative collapse. In the
plasma core, tungsten emission is dominant in the Soft X-ray (SXR) range 0.1
keV -- 15 keV with complex contributions from line transition, radiative
recombination and Bremsstrahlung emission.This paper presents the recent
development of a synthetic SXR diagnostic using GEM (Gas Electron Multiplier)
detectors. This diagnostic will be used on WEST for W transport studies and
will be equipped with two new GEM based poloidal cameras allowing 2D
tomographic reconstructions with spectral resolution in energy bands. Thus once
GEM response to plasma emissivity is characterized thanks to synthetic
diagnostic, it offers new possibilities to disentangle the different SXR
contributions in harsh fusion environments like e.g. WEST or ITER with respect
to conventional semiconductor diodes working in current mode. Emitted SXR
spectrum from the plasma is modelled thanks to ADAS database from given WEST
scenario. The synthetic diagnostic includes Lines of Sight (LoS) etendues of
the two cameras as well as probability of photoabsorption through filters,
photoionization in the detection gas mixture (Ar-CO2), and transport of
electron avalanches in the gas through GEM foils as computed with Magboltz.
Local SXR emissivity is then retrieved from tomographic inversion using a
Minimum Fisher Information (MFI) algorithm.


  The IP matrix model is a simple large $N$ quantum mechanical model made up of
an adjoint harmonic oscillator plus a fundamental harmonic oscillator. It is a
model introduced previously as a toy model of the gauge theory dual of an AdS
black hole. In the large $N$ limit, one can solve the Schwinger-Dyson equation
for the fundamental correlator, and at sufficiently high temperature, this
model shows key signatures of thermalization and information loss; the
correlator decay exponentially in time, and the spectral density becomes
continuous and gapless. We study the Lanczos coefficients $b_n$ in this model
and at sufficiently high temperature, it grows linearly in $n$ with logarithmic
corrections, which is one of the fastest growth under certain conditions. As a
result, the Krylov complexity grows exponentially in time as $\sim
\exp\left({{\cal{O}}{\left(\sqrt{t}\right) }}\right)$. These results indicate
that the IP model at sufficiently high temperature is chaotic.


  We address the problem of separating stars from galaxies in future large
photometric surveys. We focus our analysis on simulations of the Dark Energy
Survey (DES). In the first part of the paper, we derive the science
requirements on star/galaxy separation, for measurement of the cosmological
parameters with the Gravitational Weak Lensing and Large Scale Structure
probes. These requirements are dictated by the need to control both the
statistical and systematic errors on the cosmological parameters, and by Point
Spread Function calibration. We formulate the requirements in terms of the
completeness and purity provided by a given star/galaxy classifier. In order to
achieve these requirements at faint magnitudes, we propose a new method for
star/galaxy separation in the second part of the paper. We first use Principal
Component Analysis to outline the correlations between the objects parameters
and extract from it the most relevant information. We then use the reduced set
of parameters as input to an Artificial Neural Network. This multi-parameter
approach improves upon purely morphometric classifiers (such as the classifier
implemented in SExtractor), especially at faint magnitudes: it increases the
purity by up to 20% for stars and by up to 12% for galaxies, at i-magnitude
fainter than 23.


  We prove some upper bounds for the Dirichlet eigenvalues of a class of fully
nonlinear elliptic equations, namely the Hessian equations


  We consider the one-dimensional Lieb-Liniger model (bosons interacting via
2-body delta potentials) in the infinite coupling constant limit (the so-called
Tonks-Girardeau model). This model might be relevant as a description of atomic
Bose gases confined in a one-dimensional geometry. It is known to have a
fermionic spectrum since the N-body wavefunctions have to vanish at coinciding
points, and therefore be symmetrizations of fermionic Slater wavefunctions. We
argue that in the infinite coupling constant limit the model is
indistinguishable from free fermions, i.e., all physically accessible
observables are the same as those of free fermions. Therefore, Bose-Einstein
condensate experiments at finite energy that preserve the one-dimensional
geometry cannot test any bosonic characteristic of such a model.


  Gibbs-type priors are widely used as key components in several Bayesian
nonparametric models. By virtue of their flexibility and mathematical
tractability, they turn out to be predominant priors in species sampling
problems, clustering and mixture modelling. We introduce a new family of
processes which extend the Gibbs-type one, by including a contaminant component
in the model to account for the presence of anomalies (outliers) or an excess
of observations with frequency one. We first investigate the induced random
partition, the associated predictive distribution and we characterize the
asymptotic behaviour of the number of clusters. All the results we obtain are
in closed form and easily interpretable, as a noteworthy example we focus on
the contaminated version of the Pitman-Yor process. Finally we pinpoint the
advantage of our construction in different applied problems: we show how the
contaminant component helps to perform outlier detection for an astronomical
clustering problem and to improve predictive inference in a species-related
dataset, exhibiting a high number of species with frequency one.


  We study a class $\widehat{\mathfrak{F}}$ of one-dimensional full branch maps
introduced in [Doubly Intermittent Full Branch Maps with Critical Points and
Singularities; D. Coates, S. Luzzatto, M. Mubarak, 2022], admitting two
indifferent fixed points as well as critical points and/or singularities with
unbounded derivative. We show that $\widehat{\mathfrak{F}}$ can be partitioned
into 3 pairwise disjoint subfamilies $$\widehat{\mathfrak{F}} = \mathfrak{F}
\cup \mathfrak{F}_\pm \cup \mathfrak{F}_*$$ such that all $g \in \mathfrak{F}$
have a unique physical measure equivalent to Lebesgue, all $g \in
\mathfrak{F}_{\pm}$ have a physical measure which is a Dirac-$\delta$ measure
on one of the (repelling) fixed points, and all $g \in \mathfrak{F}_{*}$ are
non-statistical and in particular have no physical measure. Moreover we show
that these subfamilies are intermingled: they can all be approximated by maps
in the other subfamilies in natural topologies.


  Let g be the finite dimensional Witt algebra W(1,1) over an algebraically
closed field of characteristic p > 3. It is well known that all simple
W(1,1)-modules are finite dimensional. Each simple module admits a character
\chi in g^*. Given such a \chi one can form the (finite dimensional) reduced
enveloping algebra u(g,\chi). The simple modules for u(g,\chi) are precisely
those simple W(1,1)-modules admitting the character \chi. In this paper the
authors compute Ext^1 between pairs of simple modules for u(g,\chi).


  Decreasing the time required for accurate thermodynamic property measurements
is extremely desirable for model development that can respond to the needs of
science and industry within a short time frame. Here, we demonstrate the
application of optimal experimental design to measurements of thermodynamic
properties. The technique is exemplified using the fitting of a Schilling-type
equation from published $(p, \rho, T)$-measurements of ethylene gylcol and
propylene gylcol. The analysis shows that a fixed-exponent fit using
$(p,T)$-measurements along the five most informative isotherms produces models
of relative density errors comparable to those obtained using the data along
all investigated isotherms, \ie, eight or nine. It is also argued that a
calculation of optimal isotherms prior to the measurement series can further
increase the precision at no additional experimental effort.


  The height probabilities for the recurrent configurations in the Abelian
Sandpile Model on the square lattice have analytic expressions, in terms of
multidimensional quadratures. At first, these quantities have been evaluated
numerically with high accuracy, and conjectured to be certain cubic
rational-coefficient polynomials in 1/pi. Later their values have been
determined by different methods.
  We revert to the direct derivation of these probabilities, by computing
analytically the corresponding integrals. Yet another time, we confirm the
predictions on the probabilities, and thus, as a corollary, the conjecture on
the average height.


  We present a novel approach for digitizing real-world objects by estimating
their geometry, material properties, and environmental lighting from a set of
posed images with fixed lighting. Our method incorporates into Neural Radiance
Field (NeRF) pipelines the split sum approximation used with image-based
lighting for real-time physical-based rendering. We propose modeling the
scene's lighting with a single scene-specific MLP representing pre-integrated
image-based lighting at arbitrary resolutions. We achieve accurate modeling of
pre-integrated lighting by exploiting a novel regularizer based on efficient
Monte Carlo sampling. Additionally, we propose a new method of supervising
self-occlusion predictions by exploiting a similar regularizer based on Monte
Carlo sampling. Experimental results demonstrate the efficiency and
effectiveness of our approach in estimating scene geometry, material
properties, and lighting. Our method is capable of attaining state-of-the-art
relighting quality after only ${\sim}1$ hour of training in a single NVIDIA
A100 GPU.


  Let $K$ denote a field and let $V$ denote a vector space over $K$ with finite
positive dimension. We consider an ordered pair of linear transformations
$A:V\to V$ and $A^*:V\to V$ that satisfy conditions (i), (ii) below.
  (i) There exists a basis for $V$ with respect to which the matrix
representing $A$ is irreducible tridiagonal and the matrix representing $A^*$
is diagonal.
  (ii) There exists a basis for $V$ with respect to which the matrix
representing $A$ is diagonal and the matrix representing $A^*$ is irreducible
tridiagonal.
  We call such a pair a {\it Leonard pair} on $V$. The structure of any given
Leonard pair is deterined by a certain sequence of scalars called its {\it
parameter array}. The set of parameter arrays is an affine algebraic variety.
We give two characterizations of this variety. One involves bidiagonal matrices
and the other involves orthogonal polynomials.


  Split cuts are cutting planes for mixed integer programs whose validity is
derived from maximal lattice point free polyhedra of the form $S:=\{x : \pi_0
\leq \pi^T x \leq \pi_0+1 \}$ called split sets. The set obtained by adding all
split cuts is called the split closure, and the split closure is known to be a
polyhedron. A split set $S$ has max-facet-width equal to one in the sense that
$\max\{\pi^T x : x \in S \}-\min\{\pi^T x : x \in S \} \leq 1$. In this paper
we consider using general lattice point free rational polyhedra to derive valid
cuts for mixed integer linear sets. We say that lattice point free polyhedra
with max-facet-width equal to $w$ have width size $w$. A split cut of width
size $w$ is then a valid inequality whose validity follows from a lattice point
free rational polyhedron of width size $w$. The $w$-th split closure is the set
obtained by adding all valid inequalities of width size at most $w$. Our main
result is a sufficient condition for the addition of a family of rational
inequalities to result in a polyhedral relaxation. We then show that a
corollary is that the $w$-th split closure is a polyhedron. Given this result,
a natural question is which width size $w^*$ is required to design a finite
cutting plane proof for the validity of an inequality. Specifically, for this
value $w^*$, a finite cutting plane proof exists that uses lattice point free
rational polyhedra of width size at most $w^*$, but no finite cutting plane
proof that only uses lattice point free rational polyhedra of width size
smaller than $w^*$. We characterize $w^*$ based on the faces of the linear
relaxation.


  Previous contrastive deep clustering methods mostly focus on instance-level
information while overlooking the member relationship within groups/clusters,
which may significantly undermine their representation learning and clustering
capability. Recently, some group-contrastive methods have been developed,
which, however, typically rely on the samples of the entire dataset to obtain
pseudo labels and lack the ability to efficiently update the group assignments
in a batch-wise manner. To tackle these critical issues, we present a novel
end-to-end deep clustering framework with dynamic grouping and prototype
aggregation, termed as DigPro. Specifically, the proposed dynamic grouping
extends contrastive learning from instance-level to group-level, which is
effective and efficient for timely updating groups. Meanwhile, we perform
contrastive learning on prototypes in a spherical feature space, termed as
prototype aggregation, which aims to maximize the inter-cluster distance.
Notably, with an expectation-maximization framework, DigPro simultaneously
takes advantage of compact intra-cluster connections, well-separated clusters,
and efficient group updating during the self-supervised training. Extensive
experiments on six image benchmarks demonstrate the superior performance of our
approach over the state-of-the-art. Code is available at
https://github.com/Regan-Zhang/DigPro.


  These workshop notes present an introduction to the concepts and mathematical
foundations of polarimetry. One of the main goals of this workshop is to
develop an understanding of the relationships between a physical description of
the signal path (e.g. gain, delay, rotation, coupling, etc.), the corresponding
transformations of the electric field vector, and the equivalent
transformations of the Stokes parameters. The adopted algebraic/geometric
approach is either directly copied from or heavily inspired by the work of
Britton (2000) and Hamaker (2000), and some justification is provided for
preferring these over other approaches and parameterizations.


  Image de-blurring is important in many cases of imaging a real scene or
object by a camera. This project focuses on de-blurring an image distorted by
an out-of-focus blur through a simulation study. A pseudo-inverse filter is
first explored but it fails because of severe noise amplification. Then
Tikhonov regularization methods are employed, which produce greatly improved
results compared to the pseudo-inverse filter. In Tikhonov regularization, the
choice of the regularization parameter plays a critical rule in obtaining a
high-quality image, and the regularized solutions possess a semi-convergence
property. The best result, with the relative restoration error of 8.49%, is
achieved when the prescribed discrepancy principle is used to decide an optimal
value. Furthermore, an iterative method, Conjugated Gradient, is employed for
image de-blurring, which is fast in computation and leads to an even better
result with the relative restoration error of 8.22%. The number of iteration in
CG acts as a regularization parameter, and the iterates have a semi-convergence
property as well.


  In this paper, we introduce Harmonics Virtual Lights (HVL), to model indirect
light sources for interactive global illumination of dynamic 3D scenes. Virtual
Point Lights (VPL) are an efficient approach to define indirect light sources
and to evaluate the resulting indirect lighting. Nonetheless, VPL suffer from
disturbing artifacts, especially with high frequency materials. Virtual
Spherical Lights (VSL) avoid these artifacts by considering spheres instead of
points but estimates the lighting integral using Monte Carlo which results to
noise in the final image. We define HVL as an extension of VSL in a Spherical
Harmonics (SH) framework, defining a closed form of the lighting integral
evaluation. We propose an efficient SH projection of spherical lights
contribution faster than existing methods. Computing the outgoing luminance
requires $\mathcal{O}(n)$ operations when using materials with circular
symmetric lobes, and $\mathcal{O}(n^2)$ operations for the general case, where
$n$ is the number of SH bands. HVL can be used with either parametric or
measured BRDF without extra cost and offers control over rendering time and
image quality, by either decreasing or increasing the band limit used for SH
projection. Our approach is particularly well designed to render
medium-frequency one-bounce global illumination with arbitrary BRDF in
interactive time.


  Water is one of the most abundant substances on Earth, and ice, i.e., solid
water, has more than 18 known phases. Normally ice in nature exists only as Ice
Ih, Ice Ic, or a stacking disordered mixture of both. Although many theoretical
efforts have been devoted to understanding the thermodynamics of different ice
phases at ambient temperature and pressure, there still remains many puzzles.
We simulated the reversible transitions between water and different ice phases
by performing full atom molecular dynamics simulations. Using the enhanced
sampling method MetaITS with the two selected X-ray diffraction peak
intensities as collective variables, the ternary phase diagrams of liquid
water, ice Ih, ice Ic at multiple were obtained. We also present a simple
physical model which successfully explains the thermodynamic stability of ice.
Our results agree with experiments and leads to a deeper understanding of the
ice nucleation mechanism.


  This paper studies the associativity of gluing of trajectories in Morse
theory. We show that the associativity of gluing follows from of the existence
of compatible manifold with face structures on the compactified moduli spaces.
Using our previous work, we obtain the associativity of gluing in certain
cases.
  In particular, associativity holds when the ambient manifold is compact and
the vector field is Morse-Smale.


  Recently bipartite graphs have been widely used to represent the relationship
two sets of items for information retrieval applications. The Web offers a wide
range of data which can be represented by bipartite graphs, such us movies and
reviewers in recomender systems, queries and URLs in search engines, users and
posts in social networks. The size and the dynamic nature of such graphs
generate the need for more efficient ranking methods.
  In this thesis, at first we present the fundamental mathematical backround
that we use subsequently and we describe the basic principles of the
Perron-Frobebius theory for non negative matrices as well as the the basic
principles of the Markov chain theory. Then, we propose a novel algorithm named
BipartiteRank, which is suitable to rank scenarios, that can be represented as
a bipartite graph. This algorithm is based on the random surfer model and
inherits the basic mathematical characteristics of PageRank. What makes it
different, is the fact that it introduces an alternative type of teleportation,
based on the block structure of the bipartite graph in order to achieve more
efficient ranking. Finally, we support this opinion with mathematical arguments
and then we confirm it experimentally through a series of tests on real data.


  We introduce a machine learning method in which energy solutions from the
Schrodinger equation are predicted using symmetry adapted atomic orbitals
features and a graph neural-network architecture. \textsc{OrbNet} is shown to
outperform existing methods in terms of learning efficiency and transferability
for the prediction of density functional theory results while employing
low-cost features that are obtained from semi-empirical electronic structure
calculations. For applications to datasets of drug-like molecules, including
QM7b-T, QM9, GDB-13-T, DrugBank, and the conformer benchmark dataset of
Folmsbee and Hutchison, \textsc{OrbNet} predicts energies within chemical
accuracy of DFT at a computational cost that is thousand-fold or more reduced.


  We prove that the infinite half-spin representations are topologically
Noetherian with respect to the infinite spin group. As a consequence we obtain
that half-spin varieties, which we introduce, are defined by the pullback of
equations at a finite level. The main example for such varieties is the
infinite isotropic Grassmannian in its spinor embedding, for which we
explicitly determine its defining equations.


  Maintaining a high quality of life through physical activities (PA) to
prevent health decline is crucial. However, the relationship between
individuals health status, PA preferences, and motion factors is complex. PA
discussions consistently show a positive correlation with healthy aging
experiences, but no explicit relation to specific types of musculoskeletal
exercises. Taking advantage of the increasingly widespread existence of
smartphones, especially in Indonesia, this research utilizes embedded sensors
for Human Activity Recognition (HAR). Based on 25 participants data, performing
nine types of selected motion, this study has successfully identified important
sensor attributes that play important roles in the right and left hands for
muscle strength motions as the basis for developing machine learning models
with the LSTM algorithm.


  Bounded Model Checking is one the most successful techniques for finding bugs
in program. However, for programs with loops iterating over large-sized arrays,
bounded model checkers often exceed the limit of resources available to them.
We present a transformation that enables bounded model checkers to verify a
certain class of array properties. Our technique transforms an
array-manipulating program in ANSI-C to an array-free and loop-free program.
The transformed program can efficiently be verified by an off-the-shelf bounded
model checker. Though the transformed program is, in general, an abstraction of
the original program, we formally characterize the properties for which the
transformation is precise. We demonstrate the applicability and usefulness of
our technique on both industry code as well as academic benchmarks.


  We have studied the dependence of the superconducting (SC) transition
temperature on the mutual orientation of magnetizations of Fe1 and Fe2 layers
in the spin valve system CoO_x/Fe1/Cu/Fe2/Pb. We find that this dependence is
nonmonotonic when passing from the parallel to the antiparallel case and
reveals a distinct minimum near the orthogonal configuration. The analysis of
the data in the framework of the SC triplet spin valve theory gives direct
evidence for the long-range triplet superconductivity arising due to
noncollinearity of the two magnetizations.


  Let R be a non-commutative field. We prove that generic triples of flags in
an m-dimensional R-vector space are described by flat R-line bundles on the
honeycomb graph with (m-1)(m-2)/2 holes.
  Generalising this, we prove that non-commutative stacks X(m,S) of framed rank
m flat R-vector bundles of on decorated surfaces S are birationally identified
with the moduli spaces of flat line bundles on a spectral surface assigned to
certain bipartite graphs on S.
  We introduce non-commutative cluster Poisson varieties related to bipartite
ribbon graphs. They carry canonical non-commutative Poisson structure. The
space X(m,S) has a structure of a non-commutative cluster Poisson variety,
equivariant under the action of the mapping class group.
  For bipartite graphs on a torus, we get the non-commutative dimer cluster
integrable system.
  We define non-commutative cluster A-varieties related to bipartite ribbon
graphs. They carry canonical non-commutative 2-form. The non-commutative stack
A(m,S) of twisted decorated local systems on S carries a cluster A-variety
structure, equivariant under the action of the mapping class group. The
non-commutative cluster A-coordinates on the space A(m,S) are ratios of
Gelfand-Retakh quasideterminants. In the case m=2 this recovers the
Berenstein-Retakh non-commutative cluster algebras related to surfaces.
  We introduce stacks of admissible dg-sheaves, and use them to give an
alternative proof of main results. We show that any stack of Stokes data is a
stack of admissible dg-sheaves of certain type. Using this we prove that all
stacks of framed Stokes data carry a cluster Poisson structure, equivariant
under the wild mapping class group. Therefore they can be equivariantly
quantized. Similar stacks of decorated Stokes data carry an equivariant cluster
A-variety structure.


  Ultralight bosons can form clouds around rotating black holes if their
Compton wavelength is comparable to the black hole size. The boson cloud spins
down the black hole through a process called superradiance, lowering the black
hole spin to a characteristic value. It has been suggested that spin
measurements of the black holes detected by ground-based gravitational-wave
detectors can be used to constrain the mass of ultralight bosons.
Unfortunately, a measurement of the individual black hole spins is often
uncertain, resulting in inconclusive results. Instead, we use hierarchical
Bayesian inference to combine information from multiple gravitational-wave
sources and obtain stronger constraints. We show that hundreds of high
signal-to-noise ratio gravitational-wave detections are enough to exclude
(confirm) the existence of non-interacting bosons in the mass range
$\left[10^{-13},3\times 10^{-12}\right]~\rm{eV}$
$\left([10^{-13},10^{-12}]~\rm{eV}\right)$. The precise number depends on the
distribution of black hole spins at formation and the mass of the boson. From
the few uninformative spin measurements of binary black hole mergers detected
by LIGO and Virgo in their first two observing runs, we cannot draw
statistically significant conclusions.


  This paper investigates unmanned aerial vehicle (UAV)-aided backscatter
communication (BackCom) networks, where the UAV is leveraged to help the
backscatter device (BD) forward signals to the receiver. Based on the presence
or absence of a direct link between BD and receiver, two protocols, namely
transmit-backscatter (TB) protocol and transmit-backscatter-relay (TBR)
protocol, are proposed to utilize the UAV to assist the BD. In particular, we
formulate the system throughput maximization problems for the two protocols by
jointly optimizing the time allocation, reflection coefficient and UAV
trajectory. Different static/dynamic circuit power consumption models for the
two protocols are analyzed. The resulting optimization problems are shown to be
non-convex, which are challenging to solve. We first consider the dynamic
circuit power consumption model, and decompose the original problems into three
sub-problems, namely time allocation optimization with fixed UAV trajectory and
reflection coefficient, reflection coefficient optimization with fixed UAV
trajectory and time allocation, and UAV trajectory optimization with fixed
reflection coefficient and time allocation. Then, an efficient iterative
algorithm is proposed for both protocols by leveraging the block coordinate
descent method and successive convex approximation (SCA) techniques. In
addition, for the static circuit power consumption model, we obtain the optimal
time allocation with a given reflection coefficient and UAV trajectory and the
optimal reflection coefficient with low computational complexity by using the
Lagrangian dual method. Simulation results show that the proposed protocols are
able to achieve significant throughput gains over the compared benchmarks.


  We have observed the middle-aged pulsar PSR B0656+14 with the prism and the
NUV MAMA detector of the Space Telescope Imaging Spectrograph (STIS) to measure
the pulsar spectrum and periodic pulsations in the near-ultraviolet (NUV). The
pulsations are clearly detected, double-peaked and very similar to the optical
pulse profile. The NUV pulsed fraction is 70 +/- 12%. The spectral slope of the
dereddened phase-integrated spectrum in the 1800 - 3200 A range is 0.35 +/- 0.5
which together with the high pulse fraction indicates a non-thermal origin for
the NUV emission. The total flux in the range 1700-3400 A is estimated to be
3.4 +/- 0.3e-15 erg/s/cm2 when corrected for E(B-V)=0.03. At a distance of 288
pc this corresponds to a luminosity 3.4e28 erg/s assuming isotropy of the
emission. We compare the NUV pulse profile with observations from radio to
gamma-rays. The first NUV sub-pulse is in phase with the gamma-ray pulse
marginally detected with the EGRET, while the second NUV sub-pulse is similar
both in shape and in phase with the non- thermal pulse in hard X-rays. This
indicates a single origin of the non-thermal emission in the optical-NUV and in
the X-rays. This is also supported by the observed NUV spectral slope, which is
compatible with a blackbody plus power-law fit extended from the X-ray range,
but dominated by the power-law component in most of the NUV range.


  I present a class of objects called gravitational strings (GS) for their
similarity to the conventional cosmic strings: even though the former are just
singularities in flat spacetime, both varieties are equally "realistic", they
may play equally important cosmological r\^ole and their lensing properties are
akin. I argue that the enigmatic object CSL-1 is an evidence in favor of the
existence of GS.