  Surgical simulation is an increasingly important element of surgical
education. Using simulation can be a means to address some of the significant
challenges in developing surgical skills with limited time and resources. The
photo-realistic fidelity of simulations is a key feature that can improve the
experience and transfer ratio of trainees. In this paper, we demonstrate how we
can enhance the visual fidelity of existing surgical simulation by performing
style transfer of multi-class labels from real surgical video onto synthetic
content. We demonstrate our approach on simulations of cataract surgery using
real data labels from an existing public dataset. Our results highlight the
feasibility of the approach and also the powerful possibility to extend this
technique to incorporate additional temporal constraints and to different
applications.


  We propose the form of the Liouville action satisfying Polyakov conjecture on
the accessory parameters for the hyperbolic singularities on the Riemann
sphere.


  Polytomous categorical data are frequent in studies, that can be obtained
with an individual or grouped structure. In both structures, the generalized
logit model is commonly used to relate the covariates on the response variable.
After fitting a model, one of the challenges is the definition of an
appropriate residual and choosing diagnostic techniques. Since the polytomous
variable is multivariate, raw, Pearson, or deviance residuals are vectors and
their asymptotic distribution is generally unknown, which leads to difficulties
in graphical visualization and interpretation. Therefore, the definition of
appropriate residuals and the choice of the correct analysis in diagnostic
tools is important, especially for nominal data, where a restriction of methods
is observed. This paper proposes the use of randomized quantile residuals
associated with individual and grouped nominal data, as well as Euclidean and
Mahalanobis distance measures, as an alternative to reduce the dimension of the
residuals. We developed simulation studies with both data structures
associated. The half-normal plots with simulation envelopes were used to assess
model performance. These studies demonstrated a good performance of the
quantile residuals, and the distance measurements allowed a better
interpretation of the graphical techniques. We illustrate the proposed
procedures with two applications to real data.


  Let k be an algebraically closed field of characteristic zero, D a locally
nilpotent derivation on the polynomial ring k[X_1, X_2,X_3,X_4] and A the
kernel of D. A question of M. Miyanishi asks whether projective modules over A
are necessarily free. Implicit is a subquestion: whether the Grothendieck group
K_0(A) is trivial.
  In this paper we shall demonstrate an explicit k[X_1]-linear fixed point free
locally nilpotent derivation D of k[X_1,X_2, X_3, X_4] whose kernel A has an
isolated singularity and whose Grothendieck group K_0(A) is not finitely
generated; in particular, there exists an infinite family of pairwise
non-isomorphic projective modules over the kernel A.
  We shall also show that, although Miyanishi's original question does not have
an affirmative answer in general, suitably modified versions of the question do
have affirmative answers when D annihilates a variable. For instance, we shall
establish that in this case the groups G_0(A) and G_1(A) are indeed trivial.
Further, we shall see that if the above kernel A is a regular ring, then A is
actually a polynomial ring over k; in particular, by the Quillen-Suslin
theorem, Miyanishi's question has an affirmative answer.
  Our construction involves rings defined by the relation u^mv=F(z,t), where
F(Z,T) is an irreducible polynomial in k[Z,T]. We shall show that a necessary
and sufficient condition for such a ring to be the kernel of a k[X_1]-linear
locally nilpotent derivation D of a polynomial ring k[X_1,...,X_4] is that F
defines a polynomial curve.


  We study the weak decays of exotic tetraquark states ${b\bar c}{q\bar q}$
with two heavy quarks. Under the SU(3) symmetry for light quarks, these
tetraquarks can be classified into an octet plus a singlet: $3\bigotimes\bar
3=1\bigoplus8$. We will concentrate on the octet tetraquarks with
$J^{P}=0^{+}$, and study their weak decays, both semileptonic and nonleptonic.
Hadron-level effective Hamiltonian is constructed according to the irreducible
representations of the SU(3) group. Expanding the Hamiltonian, we obtain the
decay amplitudes parameterized in terms of a few irreducible quantities. Based
on these amplitudes, relations for decay widths are derived, which can be
tested in future. We also give a list of golden channels that can be used to
look for these states at various colliders.


  In this paper we prove a two-term asymptotic formula for for the spectral
counting function for a 2D magnetic Schr\"odinger operator on a domain (with
Dirichlet boundary conditions) in a semiclassical limit and with strong
magnetic field. By scaling, this is equivalent to a thermodynamic limit of a 2D
Fermi gas submitted to a constant external magnetic field.
  The original motivation comes from a paper by H. Kunz in which he studied,
among other things, the boundary correction for the grand-canonical pressure
and density of such a Fermi gas. Our main theorem yields a rigorous proof of
the formulas announced by Kunz. Moreover, the same theorem provides several
other results on the integrated density of states for operators of the type
$(-ih\nabla- \mu {\bf A})^2$ in $L^2({\Omega})$ with Dirichlet boundary
conditions.


  The collective behaviour of hadronic particles has been observed in high
multiplicity proton-lead collisions at the Large Hadron Collider (LHC), as well
as in deuteron-gold collisions at the Relativistic Heavy-Ion Collider (RHIC).
In this work we present the first calculation, in the hydrodynamic framework,
of thermal photon radiation from such small collision systems. Owing to their
compact size, these systems can reach temperatures comparable to those in
central nucleus-nucleus collisions. The thermal photons can thus shine over the
prompt background, and increase the low $p_T$ direct photon spectrum by a
factor of 2-3 in 0-1% p+Pb collisions at 5.02 TeV. This thermal photon
enhancement can therefore serve as a clean signature of the existence of a hot
quark-gluon plasma during the evolution of these small collision systems, as
well as validate hydrodynamic behavior in small systems.


  We report the discovery of a statistically significant radial alignment of
cluster galaxies in a sample of 85 X-ray selected clusters observed in the
Sloan Digital Sky Survey. The tendency for alignment is a robust feature of our
sample and does not vary significantly with individual cluster or galaxy
properties. We use dynamical arguments to show that a significant fraction of
cluster galaxies should be undergoing a parametric tidal resonance that can
cause their long axes to orient themselves towards the center of the cluster
potential, and therefore tentatively ascribe the observed radial alignment to
this dynamical effect.


  Dark Energy is the dominant component of the energy density of the universe.
In a previous paper, we have shown that the collapse of dark energy fields
leads to the formation of Super Massive Black Holes with masses comparable to
the masses of Black Holes at the centers of galaxies. Thus it becomes a
pressing issue to investigate the other physical consequences of the collapse
of Dark Energy fields. Given that the primary interactions of Dark Energy
fields with the rest of the Universe are gravitational, it is particularly
interesting to investigate the gravitational wave signals emitted during the
process of the collapse of Dark Energy fields. This is the focus of the current
work described in this paper. We describe and use the 3+1 BSSN formalism to
follow the evolution of the dark energy fields coupled with gravity and to
extract the gravitational wave signals. Finally, we describe the results of our
numerical computations and the gravitational wave signals produced as a result
of the collapse of the dark energy fields.


  The exotic Fulde-Ferrell-Larkin-Ovchinnikov (FFLO) states have been actively
searched for experimentally since the mean-field based FFLO theories were put
forward half a century ago. Here we investigate the stability of FFLO states
against unavoidable pairing fluctuations, and conclude that FFLO superfluids
cannot exist due to their intrinsic instability in three and two dimensions.
This explains their absence in experimental observations in both condensed
matter systems and the most recent, more promising ultracold atomic Fermi gases
with a population imbalance.


  One of the fundamental challenges towards building any intelligent tutoring
system is its ability to automatically grade short student answers. A typical
automatic short answer grading system (ASAG) grades student answers across
multiple domains (or subjects). Grading student answers requires building a
supervised machine learning model that evaluates the similarity of the student
answer with the reference answer(s). We observe that unlike typical textual
similarity or entailment tasks, the notion of similarity is not universal here.
On one hand, para-phrasal constructs of the language can indicate similarity
independent of the domain. On the other hand, two words, or phrases, that are
not strict synonyms of each other, might mean the same in certain domains.
Building on this observation, we propose JMD-ASAG, the first joint multidomain
deep learning architecture for automatic short answer grading that performs
domain adaptation by learning generic and domain-specific aspects from the
limited domain-wise training data. JMD-ASAG not only learns the domain-specific
characteristics but also overcomes the dependence on a large corpus by learning
the generic characteristics from the task-specific data itself. On a
large-scale industry dataset and a benchmarking dataset, we show that our model
performs significantly better than existing techniques which either learn
domain-specific models or adapt a generic similarity scoring model from a large
corpus. Further, on the benchmarking dataset, we report state-of-the-art
results against all existing non-neural and neural models.


  It is well known that the Dresselhaus spin-orbit coupling (SOC) in
semiconductor two dimensional electron gases (2DEGs) possesses both linear and
cubic in momentum contributions. Nevertheless, the latter is usually neglected
in most theoretical studies. However, recent Kerr rotation experiments have
revealed a significant enhancement of the cubic Dresselhaus interaction by
increasing the drift velocities in 2DEGs hosted in GaAs quantum wells. Here, we
present a study of the optical spin Hall conductivity in 2DEGs under the
simultaneous presence of Rashba and (linear plus cubic) Dresselhaus SOC. The
work was done within the Kubo formalism in linear response. We show that the
coexistence of the Rashba and cubic Dresselhaus SOC in 2DEGs promotes a strong
anisotropy of the band spin splitting which in turn leads to a very
characteristic frequency dependence of the spin Hall conductivity. We find that
the spin Hall conductivity response could be very sensible to sizeable
cubic-Dresselhaus coupling strength. This may be of relevance for the optical
control of spin currents in 2DEGs with non-negligible cubic-Dresselhaus SOC.


  Reinforcement learning with function approximation can be unstable and even
divergent, especially when combined with off-policy learning and Bellman
updates. In deep reinforcement learning, these issues have been dealt with
empirically by adapting and regularizing the representation, in particular with
auxiliary tasks. This suggests that representation learning may provide a means
to guarantee stability. In this paper, we formally show that there are indeed
nontrivial state representations under which the canonical TD algorithm is
stable, even when learning off-policy. We analyze representation learning
schemes that are based on the transition matrix of a policy, such as
proto-value functions, along three axes: approximation error, stability, and
ease of estimation. In the most general case, we show that a Schur basis
provides convergence guarantees, but is difficult to estimate from samples. For
a fixed reward function, we find that an orthogonal basis of the corresponding
Krylov subspace is an even better choice. We conclude by empirically
demonstrating that these stable representations can be learned using stochastic
gradient descent, opening the door to improved techniques for representation
learning with deep networks.


  We present direct evidence of a superconducting state existing in the title
compound below 300 mK under quasi-hydrostatic pressure. The superconducing
transition is observed in the whole pressure range studied, 0 < P < 4 kbar.
However, the character of the transition drastically changes with suppressing
the charge-density wave state.


  Recently, the existence of a candidate a-function for renormalisable theories
in three dimensions was demonstrated for a general theory at leading order and
for a scalar-fermion theory at next-to-leading order. Here we extend this work
by constructing the a-function at next-to-leading order for an N=2
supersymmetric Chern-Simons theory. This increase in precision for the
a-function necessitated the evaluation of the underlying renormalization-group
functions at four loops.


  Employing the method of mapping the spin problem onto a particle one, we have
derived the particle Hamiltonian for a biaxial spin system with a transverse or
longitudinal magnetic field. Using the Hamiltonian and introducing the
parameter $p (\equiv (U_{max}-E)/(U_{max}-U_{min}))$ where $U_{max}$ (U_{min})
corresponds to the top (bottom) of the potential and $E$ is the energy of the
particle, we have studied the first- or second-order transition around the
crossover temperature between thermal and quantum regimes for the escape rate,
depending on the anisotropy constant and the external magnetic field. It is
shown that the phase boundary separating the first- and second-order transition
and its crossover temperature are greatly influenced by the transverse
anisotropy constant as well as the transverse or longitudinal magnetic field.


  In this study, we implement a control method for stabilizing a ballbot that
simultaneously follows a reference. A ballbot is a robot balancing on a
spherical wheel where the single point of contact with the ground makes it
omnidirectional and highly maneuverable but with inherent instability. After
introducing the scheduling parameters, we start the analysis by embedding the
nonlinear dynamic model derived from first principles to a linear
parameter-varying (LPV) formulation. Continuously, and as an extension of a
past study, we refine the parameters of the nonlinear model that enhance
significantly its accuracy. The crucial advantages of the LPV formulation are
that it consists of a nonlinear predictor that can be used in model predictive
control (MPC) by retaining the convexity of the quadratic optimization problem
with linear constraints and further evades computational burdens that appear in
other nonlinear MPC methods with only a slight loss in performance. The LPVMPC
control method can be solved efficiently as a quadratic program (QP) that
provides timing that supports real-time implementation. Finally, to illustrate
the method, we test the control designs on a two-set point 1D non-smooth
reference with sudden changes, to a 2D nonstationary smooth reference known as
Lissajous curves, and to a single-set point 1D non-smooth reference where for
this case theoretical guarantees such as stability and recursive feasibility
are provided.


  This paper considers a general stochastic resource allocation problem that
arises widely in wireless networks, cognitive radio, networks, smart-grid
communications, and cross-layer design. The problem formulation involves
expectations with respect to a collection of random variables with unknown
distributions, representing exogenous quantities such as channel gain, user
density, or spectrum occupancy. We consider the constant step-size stochastic
dual subgradient descent (SDSD) method that has been widely used for online
resource allocation in networks. The problem is solved in dual domain which
results in a primal resource allocation subproblem at each time instant. The
goal here is to characterize the non-asymptotic behavior of such stochastic
resource allocations in an almost sure sense.
  It is well known that with a step size of $\epsilon$, {SDSD} converges to an
$\mathcal{O}(\epsilon)$-sized neighborhood of the optimum. In practice however,
there exists a trade-off between the rate of convergence and the choice of
$\epsilon$. This paper establishes a convergence rate result for the SDSD
algorithm that precisely characterizes this trade-off. {Towards this end, a
novel stochastic bound on the gap between the objective function and the
optimum is developed. The asymptotic behavior of the stochastic term is
characterized in an almost sure sense, thereby generalizing the existing
results for the {stochastic subgradient} methods.} For the stochastic resource
allocation problem at hand, the result explicates the rate with which the
allocated resources become near-optimal. As an application, the power and
user-allocation problem in device-to-device networks is formulated and solved
using the {SDSD} algorithm. Further intuition on the rate results is obtained
from the verification of the regularity conditions and accompanying simulation
results.


  Lattice vibrations of the wurtzite-type AlN have been studied by Raman
spectroscopy under high pressure up to the structural phase transition at 20
GPa. We have shown that the widely debated bond-bending E_2^1 mode of w-AlN has
an abnormal positive pressure shift up to the threshold of the phase
transition, whereas in many tetrahedral semiconductors the bond-bending modes
soften on compression. This finding disagrees with the results of ab initio
calculations, which give a "normal" negative pressure shift. Combination of
high dynamical and low thermodynamical stability of AlN breaks the correlation
between the mode Gruneisen parameters for the bond-bending modes and the
transition pressure, which holds for CdS, InP, ZnO, ZnTe, ZnSe, ZnS, Ge, Si,
GaP, GaN, SiC and BeO.


  Microstructure of reflection holographic grating fabricated via a
photo-isomerization process in an absorptive azopolymer film is analyzed. A
surface relief formation takes place on the film surface even in the reflection
holographic configuration. The polarization-dependent diffraction efficiency
and the polarization analysis reveal that the polarization grating structure
inside the film strongly depends on the amount of optical absorption
experienced by the two writing beams. Theoretical analysis shows that the
reflection polarization grating, while mimicking a cholesteric liquid crystal
structure, is composed of elliptic polarizations with the ellipticity going
through a periodic modulation.


  Spatio-temporal modeling is foundational for smart city applications, yet it
is often hindered by data scarcity in many cities and regions. To bridge this
gap, we propose a novel generative pre-training framework, GPD, for
spatio-temporal few-shot learning with urban knowledge transfer. Unlike
conventional approaches that heavily rely on common feature extraction or
intricate few-shot learning designs, our solution takes a novel approach by
performing generative pre-training on a collection of neural network parameters
optimized with data from source cities. We recast spatio-temporal few-shot
learning as pre-training a generative diffusion model, which generates tailored
neural networks guided by prompts, allowing for adaptability to diverse data
distributions and city-specific characteristics. GPD employs a
Transformer-based denoising diffusion model, which is model-agnostic to
integrate with powerful spatio-temporal neural networks. By addressing
challenges arising from data gaps and the complexity of generalizing knowledge
across cities, our framework consistently outperforms state-of-the-art
baselines on multiple real-world datasets for tasks such as traffic speed
prediction and crowd flow prediction. The implementation of our approach is
available: https://github.com/tsinghua-fib-lab/GPD.


  Theories of gravity extending or modifying general relativity typically allow
for black hole solutions different from the Schwarzschild/Kerr geometries.
Electromagnetic observations have been used to place constraints on
parametrized deviations from the Schwarzschild/Kerr metrics, in an effort to
gain insight on the underlying gravitational theory. In this work, we show that
observations of the gravitational quasi-normal modes by existing and future
interferometers can be used to bound the same parametrized black hole metrics
that are constrained by electromagnetic observations (e.g. by the Event Horizon
Telescope). We argue that our technique is most sensitive to changes in the
background black hole metric near the circular photon orbit, and that it is
robust against the changes that a gravitational theory differing from general
relativity necessarily introduces in the equations for the gravitational
perturbations. We demonstrate our approach by reconstructing the background
metric from a set of simulated observations using a Bayesian approach.


  For the linear baryon string model with three massive points (three quarks)
connected sequentially by the relativistic strings the initial-boundary value
problem is stated and solved in general. This problem implies defining a
classical motion of the system on the base of given initial position and
initial velocities of string points. The given solution work reduces the
initial-boundary value problem for the considered model to the system of
ordinary differential equations that can be integrated numerically in general.
The examples of numerical simulation of the system motion are considered,
which, in particular, allow to answer to the old question about stability of a
flat uniform rotation of the linear string configuration.


  We produce a quantum degenerate mixture composed by two Bose-Einstein
condensates of different atomic species, 41 K and 87 Rb. We study the dynamics
of the superfluid system in an elongated magnetic trap, where off-axis
collisions between the two interacting condensates induce scissors-like
oscillation.


  In this paper we show that two Lagrangian graphs over the torus in
$\mathbb{C}^n$ with large Lagrangian phase can be connected via Lipschitz
continuous geodesic with respect to the $L^2$ metric on the space of Lagrangian
submanifolds. In particular, the geodesic for Lagrangian graphs over the torus
in $\mathbb{C}^n$ can be formulated as a degenerate elliptic equation, and we
construct geodesic by solving the corresponding Dirichlet problem.


  By generalizing the Miura transformation for $\Ww_N$ to other classical $\Ww$
algebras obtained by hamiltonian reduction, we find realisations of these
algebras in terms of relatively simple non-abelian current algebras, e.g.
$\widehat{sl(2)}\times \widehat{u(1)}^N$, generalizing the free field
realisation of $\Ww_N$. As an example, we present the $\widehat{sl(2)}\times
\widehat{u(1)}$ realisation of $\Ww_3^2$, which we also quantize. By a specific
example, we also show how the realisation of $\Ww_N$ with the currents of
$\Ww_{N-1}$ and a free boson can be generalized to certain classes of
``extended'' $\Ww_N$ algebras.


  This paper describes a two-layer control and coordination framework for
distributed energy resources. The lower layer is a real-time model predictive
control (MPC) executed at 10 s resolution to achieve fine tuning of a given
energy set-point. The upper layer is a slower MPC coordination mechanism based
on distributed optimization, and solved with the alternating direction method
of multipliers (ADMM) at 5 minutes resolution. It is needed to coordinate the
power flow among the controllable resources such that enough power is available
in real-time to achieve a pre-established energy trajectory in the long term.
Although the formulation is generic, it is developed for the case of a battery
system and a curtailable PV facility to dispatch stochastic prosumption
according to a trajectory at 5 minutes resolution established the day before
the operation. The proposed method is experimentally validated in a real-life
setup to dispatch the operation of a building with rooftop PV generation (i.e.,
101 kW average load, 350 kW peak demand, 82 kW peak PV generation) by
controlling a 560 kWh/720 kVA battery and a 13 kW peak curtailable PV facility.


  The Golomb space $\mathbb N_\tau$ is the set $\mathbb N$ of positive integers
endowed with the topology $\tau$ generated by the base consisting of arithmetic
progressions $\{a+bn\}_{n=0}^\infty$ with coprime $a,b$. We prove that the
Golomb space $\mathbb N_\tau$ has continuum many continuous self-maps, contains
a countable disjoint family of infinite closed connected subsets, the set $\Pi$
of prime numbers is a dense metrizable subspace of $\mathbb N_\tau$, and each
homeomorphism $h$ of $\mathbb N_\tau$ has the following properties: $h(1)=1$,
$h(\Pi)=\Pi$ and $\Pi_{h(x)}=h(\Pi_x)$ for all $x\in\mathbb N$. Here by $\Pi_x$
we denote the set of prime divisors of $x$.


  The spreading dynamics of Newtonian liquids have been extensively studied in
hydrophilic and hydrophobic surfaces and its behavior has been extensively
explored over the last years. However, drop impact of Non-Newtonian liquids
still needs further study. Luu and Forterre (J. Fluid Mech., 632, 2009)
successfully found scaling laws for yield-stress fluids on hydrophilic
surfaces. They also uncovered interesting and yet unexplained regimes when the
impact was performed on a superhydrophobic surface. In this work, we perform
drop impact experiments on micro-patterned surfaces with two types of
non-Newtonian liquids: one showing shear-thickening behavior and another one
showing shear-thinning. Our results show that a typical shear-thickening liquid
as cornstarch -at least a the relatively low concentration of 30\%w/w- spreads
according to the scaling laws of Newtonian liquids, whereas visco-elastic
liquids as Carbopol behave as predicted by Luu and Forterre for impact on
hydrophilic surfaces, but show different scaling laws when they impact on
superhydrophobic surfaces.


  Recently we proposed the linguistic interpretation of quantum mechanics
(called quantum and classical measurement theory), which was characterized as a
kind of metaphysical and linguistic turn of the Copenhagen interpretation. This
turn from physics to language does not only extend quantum theory to classical
systems but also yield the quantum mechanical world view (i.e., quantum
philosophy or quantum language). The purpose of this paper is to formulate the
double-slit experiment, the quantum eraser experiment, Wheeler's delayed choice
experiment, Hardy's paradox and the three boxes paradox (the weak value
associated with a weak measurement due to Aharonov, et al.) in the linguistic
interpretation of quantum mechanics. Through these arguments, we assert that
the linguistic interpretation is just the final version of so called Copenhagen
interpretation. And therefore, we conclude that the Copenhagen interpretation
does not belong to physics (i.e., the realistic world view) but the linguistic
world view.


  The ratio of the measured $\bar B\to D^{(*)}\ell\bar{\nu}$ decay rates for
$\ell = \tau$ vs. $e,\mu$ deviate from the Standard Model (SM) by about
$4\sigma$. We show that the data are in tension with the SM, independent of
form factor calculations, and we update the SM prediction for $\mathcal{B}(B\to
X_c\tau\bar{\nu}) / \mathcal{B}(B\to X_c \ell\bar{\nu})$. We classify the
operators that can accommodate the measured central values, as well as their UV
completions. We identify models with leptoquark mediators that are minimally
flavor violating in the quark sector, and are minimally flavor violating or
$\tau$-aligned in the lepton sector. We explore experimental signatures of
these scenarios, which are observable in the future at ATLAS/CMS, LHCb, or
Belle II.


  Some recent publications on ferromagnetic resonance in amorphous wires
mention presumably new kind of anisotropy, called there circumferential
anisotropy, as an explanation of various spectral features. In this paper we
argue that there is no special reason to speak of the new kind of anisotropy,
since the observed spectra can be well described in terms of more traditional
uniaxial and surface anisotropies alone.


  In this paper, ensembles of quasi-cyclic moderate-density parity-check (MDPC)
codes based on protographs are introduced and analyzed in the context of a
McEliece-like cryptosystem. The proposed ensembles significantly improve the
error correction capability of the regular MDPC code ensembles that are
currently considered for post-quantum cryptosystems without increasing the
public key size. The proposed ensembles are analyzed in the asymptotic setting
via density evolution, both under the sum-product algorithm and a
low-complexity (error-and-erasure) message passing algorithm. The asymptotic
analysis is complemented at finite block lengths by Monte Carlo simulations.
The enhanced error correction capability remarkably improves the scheme
robustness with respect to (known) decoding attacks.


  Using $448.0 \times 10^6$~$\psi(3686)$ events collected with the BESIII
detector, an amplitude analysis is performed for
$\psi(3686)\to\gamma\chi_{c1}$, $\chi_{c1}\to\eta\pi^+\pi^-$ decays. The most
dominant two-body structure observed is $a_0(980)^{\pm}\pi^{\mp}$;
$a_0(980)^{\pm}\to\eta\pi^{\pm}$. The $a_0(980)$ line shape is modeled using a
dispersion relation, and a significant non-zero $a_0(980)$ coupling to the
$\eta^{\prime}\pi$ channel is measured. We observe $\chi_{c1}\to a_2(1700)\pi$
production for the first time, with a significance larger than 17$\sigma$. The
production of mesons with exotic quantum numbers, $J^{PC}=1^{-+}$, is
investigated, and upper limits for the branching fractions $\chi_{c1}\to
\pi_1(1400)^{\pm}\pi^{\mp}$, $\chi_{c1}\to \pi_1(1600)^{\pm}\pi^{\mp}$, and
$\chi_{c1}\to\pi_1(2015)^{\pm}\pi^{\mp}$, with subsequent $\pi_1(X)^{\pm} \to
\eta\pi^{\pm}$ decay, are determined.


  Oxygen reduction/evolution reaction (ORR/OER) is a basic process for fuel
cells or metal air batteries. However, ORR/OER generally requires noble metal
catalysts and suffers from low solubility (10-3 molar per liter) of O2, low
kinetics rate (10-6 cm2/s) and low reversibility. We report a manganese
reduction/oxidation reaction (MRR/MOR) on graphene/MnO2 composites, delivering
a high capacity (4200 mAh/g), fast kinetics (0.0024 cm2/s, three orders higher
than ORR/OER), high solubility (three orders than O2), and high reversibility
(100%). We further use MRR/MOR to invent a rechargeable manganese ion battery
(MIB), which delivers an energy density of 1200 Wh/Kg (several times of lithium
ion battery), a fast charge ability (3 minutes), and a long cycle life (10,000
cycles). MRR/MOR renders a new class of energy conversion or storage systems
with a very high energy density enabling electric vehicles run much more miles
at one charge.


  Neuromorphic computing (NC) architecture has shown its suitability for
energy-efficient computation. Amongst several systems, spin-orbit torque (SOT)
based domain wall (DW) devices are one of the most energy-efficient contenders
for NC. To realize spin-based NC architecture, the computing elements such as
synthetic neurons and synapses need to be developed. However, there are very
few experimental investigations on DW neurons and synapses. The present study
demonstrates the energy-efficient operations of neurons and synapses by using
novel reading and writing strategies. We have used a W/CoFeB-based
energy-efficient SOT mechanism to drive the DWs at low current densities. We
have used the concept of meander devices for achieving synaptic functions. By
doing this, we have achieved 9 different resistive states in experiments. We
have experimentally demonstrated the functional spike and step neurons.
Additionally, we have engineered the anomalous Hall bars by incorporating
several pairs, in comparison to conventional Hall crosses, to increase the
sensitivity as well as signal-to-noise ratio (SNR). We performed micromagnetic
simulations and transport measurements to demonstrate the above-mentioned
functionalities.


  We study the behavior of high-dimensional robust regression estimators in the
asymptotic regime where $p/n$ tends to a finite non-zero limit. More
specifically, we study ridge-regularized estimators, i.e
$\widehat{\beta}=\text{argmin}_{\beta \in \mathbb{R}^p} \frac{1}{n}\sum_{i=1}^n
\rho(\varepsilon_i-X_i' \beta)+\frac{\tau}{2}\lVert\beta\rVert^2$. In a
recently published paper, we had developed with collaborators probabilistic
heuristics to understand the asymptotic behavior of $\widehat{\beta}$. We give
here a rigorous proof, properly justifying all the arguments we had given in
that paper. Our proof is based on the probabilistic heuristics we had
developed, and hence ideas from random matrix theory, measure concentration and
convex analysis. While most the work is done for $\tau>0$, we show that under
some extra assumptions on $\rho$, it is possible to recover the case $\tau=0$
as a limiting case. We require that the $X_i$'s be i.i.d with independent
entries, but our proof handles the case where these entries are not Gaussian. A
2-week old paper of Donoho and Montanari [arXiv:1310.7320] studied a similar
problem by a different method and with a different point of view. At this
point, their interesting approach requires Gaussianity of the design matrix.


  A very recent observation on the membrane mediated attraction and ordered
aggregation of colloidal particles bound to giant phospholipid vesicles (I.
Koltover, J. O. R\"{a}dler, C. R. Safinya, Phys. Rev. Lett. {\bf 82},
1991(1999)) is investigated theoretically within the frame of Helfrich
curvature elasticity theory of lipid bilayer fluid membrane. Since the concave
or waist regions of the vesicle possess the highest local bending energy
density, the aggregation of colloidal beads on these places can reduce the
elastic energy in maximum. Our calculation shows that a bead in the concave
region lowers its energy $\sim 20 k_B T$. For an axisymmetrical dumbbell
vesicle, the local curvature energy density along the waist is equally of
maximum, the beads can thus be distributed freely with varying separation
distance.


  Recently thulium has been condensed to Bose-Einstein condensate. Machine
learning was used to avoid a detailed study of all obstacles making cooling
difficult. This paper analyses the atomic loss mechanism for the 532 nm optical
trap, used in the Bose-condensation experiment, and compares it with the
alternative and more traditional micron-range optical dipole trap. We also
measured the scalar and tensor polarizability of thulium at 1064 nm and was
found to be $167\pm 25$ a.u. ($275\pm 41\times {{10}^{-41}}\text{F }\cdot
\text{ }{{\text{m}}^{\text{2}}}$) and $-4\pm 1$ a.u. ($7\pm 2\times
{{10}^{-41}}\text{F }\cdot \text{ }{{\text{m}}^{\text{2}}}$).


  In previous papers the permutation group S_4 has been suggested as an
ordering scheme for elementary particles, and the appearance of this finite
symmetry group was taken as indication for the existence of a discrete inner
symmetry space underlying elementary particle interactions. Here it is pointed
out that a more suitable choice than the tetrahedral group S_4 is the
pyritohedral group A_4 x Z_2 because its vibrational spectrum exhibits exactly
the mass multiplet structure of the 3 fermion generations. Furthermore it is
noted that the same structure can also be obtained from a primordial symmetry
breaking S_4 --> A_4. Since A_4 is a chiral group, while S_4 is achiral, an
argument can be given why the chirality of the inner pyritohedral symmetry
leads to parity violation of the weak interactions.


  This paper investigates the decentralized stabilization problem for a class
of interconnected systems in the presence of non-triangular structural
uncertainties and time-varying parameters, where each subsystem exchanges
information only with its neighbors and only intermittent (rather than
continuous) states and input are to be utilized. Thus far to our best
knowledge, no solution exists priori to this work, despite its high prevalence
in practice. Two globally decentralized adaptive control schemes are presented
based on the backstepping technique, the first one is developed in a continuous
fashion by combining the philosophy of the modified congelation of variables
based approach with the special treatment of non-triangular structural
uncertainties, which avoids the derivative of time-varying parameters and
eliminates the limitation of the triangular condition, thus largely broadens
the scope of application. By making use of the important property that the
partial derivatives of the constructed virtual controllers in each subsystem
are all constant, the second scheme is developed through directly replacing the
states in the preceding scheme with the triggered ones. Consequently, the
non-differentiability of the virtual control stemming from intermittent state
feedback is completely obviated. The internal signals under both schemes are
rigorously shown to be globally uniformly bounded with the aid of several novel
lemmas, while the stabilization performance can be enhanced by appropriately
adjusting design parameters. Moreover, the inter-event intervals are ensured to
be lower-bounded by a positive constant. Finally, numerical simulation verifies
the benefits and efficiency of the proposed method.


  We consider the category of smooth $W(k)[GL_n(F)]$-modules, where F is a
p-adic field and k is an algebraically closed field of characteristic l
different from p. We describe a factorization of this category into blocks, and
show that the center of each block is a reduced, finite type, l-torsion free
W(k)-algebra. Moreover, the k-points of the center of each block are in
bijection with the possible "supercuspidal supports" of the smooth
$k[GL_n(F)]$-modules that lie in the block. Finally, we describe a large,
explicit subalgebra of the center of each block and give a description of the
action of this subalgebra on the simple objects of the block, in terms of the
description of the classical "characteristic zero" Bernstein center.


  We derive N-particle Bell-type inequalities under the assumption of partial
separability, i.e. that the N-particle system is composed of subsystems which
may be correlated in any way (e.g. entangled) but which are uncorrelated with
respect to each other. These inequalities provide, upon violation,
experimentally accessible sufficient conditions for full N-particle
entanglement, i.e. for N-particle entanglement that cannot be reduced to
mixtures of states in which a smaller number of particles are entangled. The
inequalities are shown to be maximally violated by the N-particle
Greenberger-Horne-Zeilinger (GHZ) states.


  We present the EpIC Monte Carlo event generator for exclusive processes
sensitive to generalised parton distributions. EpIC utilises the PARTONS
framework, which provides a flexible software architecture and a variety of
modelling options for the partonic description of the nucleon. The generator
offers a comprehensive set of features, including multi-channel capabilities
and radiative corrections. It may be used both in analyses of experimental
data, as well as in impact studies, especially for future electron-ion
colliders.


  We present two complementary analytical approaches for calculating the
distribution of shortest path lengths in Erdos-R\'enyi networks, based on
recursion equations for the shells around a reference node and for the paths
originating from it. The results are in agreement with numerical simulations
for a broad range of network sizes and connectivities. The average and standard
deviation of the distribution are also obtained. In the case that the mean
degree scales as $N^{\alpha}$ with the network size, the distribution becomes
extremely narrow in the asymptotic limit, namely almost all pairs of nodes are
equidistant, at distance $d=\lfloor 1/\alpha \rfloor$ from each other. The
distribution of shortest path lengths between nodes of degree $m$ and the rest
of the network is calculated. Its average is shown to be a monotonically
decreasing function of $m$, providing an interesting relation between a local
property and a global property of the network. The methodology presented here
can be applied to more general classes of networks.


  We present a lattice calculation of the masses and decay constants of
$D_{(s)}^*$ and $B_{(s)}^*$ mesons using the gauge configurations produced by
the European Twisted Mass Collaboration (ETMC) with $N_f = 2 + 1 + 1$ dynamical
quarks at three values of the lattice spacing $a \sim (0.06 - 0.09)$ fm. Pion
masses are simulated in the range $M_\pi \simeq (210 - 450)$ MeV, while the
strange and charm sea-quark masses are close to their physical values. We
compute the ratios of vector to pseudoscalar masses and decay constants for
various values of the heavy-quark mass $m_h$ in the range $0.7
m_c^{\mathrm{phys}} \lesssim m_h \lesssim 3 m_c^{\mathrm{phys}}$. In order to
reach the physical b-quark mass, we exploit the Heavy Quark Effective Theory
prediction that, in the static limit of infinite heavy-quark mass, the
considered ratios are equal to one. At the physical point our results are:
$M_{D^*} / M_{D} = 1.0769(79)$, $M_{D^*_{s}} / M_{D_{s}} = 1.0751(56)$, $
f_{D^*} / f_{D} = 1.078(36),$ $f_{D^*_{s}} / f_{D_{s}} = 1.087(20)$, $M_{B^*} /
M_{B} = 1.0078(15)$, $M_{B^*_{s}} / M_{B_{s}} = 1.0083(10)$, $f_{B^*} / f_{B} =
0.958(22)$ and $f_{B^*_{s}} / f_{B_{s}} = 0.974(10)$. Combining them with the
experimental values of the pseudoscalar meson masses (used as input to fix the
quark masses) and the values of the pseudoscalar decay constants calculated by
ETMC, we get: $M_{D^*} = 2013(14)~\mathrm{MeV}$, $ M_{D_s^*} =
2116(11)~\mathrm{MeV}$, $f_{D^*} = 223.5(8.4)~\mathrm{MeV}$, $f_{D_s^*} =
268.8(6.6)~\mathrm{MeV}$, $M_{B^*} = 5320.5(7.6)~\mathrm{MeV}$, $M_{B_s^*} =
5411.36(5.3)~\mathrm{MeV}$, $f_{B^*} = 185.9(7.2)~\mathrm{MeV}$ and $f_{B_s^*}
= 223.1(5.4)~\mathrm{MeV}$.


  We compute the lowest frequency non-radial oscillation modes of dilute axion
stars. The effective potential that enters into the Schr{\"o}dinger-like
equation, several associated eigenfunctions, and the large as well as the small
frequency separations are shown as well.


  To each tagged triangulation of a surface with marked points and non-empty
boundary we associate a quiver with potential, in such a way that whenever we
apply a flip to a tagged triangulation, the Jacobian algebra of the QP
associated to the resulting tagged triangulation is isomorphic to the Jacobian
algebra of the QP obtained by mutating the QP of the original one. Furthermore,
we show that any two tagged triangulations are related by a sequence of flips
compatible with QP-mutation. We also prove that for each of the QPs
constructed, the ideal of the non-completed path algebra generated by the
cyclic derivatives is admissible and the corresponding quotient is isomorphic
to the Jacobian algebra. These results, which generalize some of the second
author's previous work for ideal triangulations, are then applied to prove
properties of cluster monomials, like linear independence, in the cluster
algebra associated to the given surface by Fomin-Shapiro-Thurston (with an
arbitrary system of coefficients).


  We consider a metric which describes Ba$\tilde{\text{n}}$ados geometries and
show that the considered metric is a solution of generalized minimal massive
gravity (GMMG) model. We consider the Killing vector field which preserves the
form of considered metric. Using the off-shell quasi-local approach we obtain
the asymptotic conserved charges of given solution. Similar to the Einstein
gravity in the presence of negative cosmological constant, for the GMMG model
also, we show that the algebra among the asymptotic conserved charges is
isomorphic to two copies of the Virasoro algebra. Eventually, we find relation
between the algebra of the near horizon and the asymptotic conserved charges.
This relation show that the main part of the horizon fluffs proposal of
Refs.\cite{140,14} appear for generic black holes in the class of
Ba$\tilde{\text{n}}$ados geometries in the context of GMMG model.


  We present the main results of a deep timing analysis (in the 0.2-10 keV
energy band) of the bright Seyfert-1 galaxy MCG-6-30-15 performed on XMM-Newton
data. The light-curves and hardness ratios show that the source has large flux
and spectral variations on time-scales of a few kiloseconds at most. From the
analysis of both the power spectra and the structure function of the light
curves we detected a relevant source variability between time-scales of ~0.3
and ~10 ks. Based on this result, we extracted a characteristic size of the
X-ray emitting region of the order of 10^13 cm.


  In \cite[Section 5, p.32]{Arnold-1998}, Arnold writes: "Classification of
singularities of curves can be interpreted in dual terms as a description of
'co-artin' subalgebras of finite co-dimension in the algebra of formal series
in a single variable (up to isomorphism of the algebra of formal series)." In
the paper, such a description is obtained but up to isomorphism of algebraic
curves (i.e. this description is finer).
  Let $K$ be an algebraically closed field of arbitrary characteristic. The aim
of the paper is to give a classification (up to isomorphism) of the set of
subalgebras $\mathcal{A}$ of the polynomial algebra $K[x]$ that contains the
ideal $x^mK[x]$ for some $m\geq 1$. It is proven that the set $\mathcal{A} =
\coprod_{m, \Gamma }\mathcal{A} (m, \Gamma )$ is a disjoint union of affine
algebraic varieties (where $\Gamma \coprod \{0, m, m+1, \ldots \}$ is the
semigroup of the singularity and $m-1$ is the Frobenius number). It is proven
that each set $\mathcal{A} (m, \Gamma )$ is an affine algebraic variety and
explicit generators and defining relations are given for the algebra of regular
functions on $\mathcal{A} (m ,\Gamma )$. An isomorphism criterion is given for
the algebras in $\mathcal{A}$. For each algebra $A\in \mathcal{A} (m, \Gamma)$,
explicit sets of generators and defining relations are given and the
automorphism group ${\rm Aut}_K(A)$ is explicitly described. The automorphism
group of the algebra $A$ is finite iff the algebra $A$ is not isomorphic to a
monomial algebra, and in this case $|{\rm Aut}_K(A)|<{\rm
dim}_K(A/\mathfrak{c}_A)$ where $\mathfrak{c}_A$ is the conductor of $A$. The
set of orders of the automorphism groups of the algebras in $\mathcal{A} (m ,
\Gamma )$ is explicitly described.


  Convolution Neural Network (ConvNet) offers a high potential to generalize
input data. It has been widely used in many application areas, such as visual
imagery, where comprehensive learning datasets are available and a ConvNet
model can be well trained and perform the required function effectively.
ConvNet can also be applied to network intrusion detection. However, the
currently available datasets related to the network intrusion are often
inadequate, which makes the ConvNet learning deficient, hence the trained model
is not competent in detecting unknown intrusions. In this paper, we propose a
ConvNet model using transfer learning for network intrusion detection. The
model consists of two concatenated ConvNets and is built on a two-stage
learning process: learning a base dataset and transferring the learned
knowledge to the learning of the target dataset. Our experiments on the NSL-KDD
dataset show that the proposed model can improve the detection accuracy not
only on the test dataset containing mostly known attacks (KDDTest+) but also on
the test dataset featuring many novel attacks (KDDTest-21) -- about 2.68\%
improvement on KDDTest+ and 22.02\% on KDDTest-21 can be achieved, as compared
to the traditional ConvNet model.


  We prove long-time existence of the Ricci flow starting from complete
manifolds with bounded curvature and scale-invariant integral curvature
sufficiently pinched with respect to the inverse of its Sobolev constant.
Moreover, if the curvature is sub-critical $L^p$ integrable, this flow
converges locally smoothly to a limiting metric $g(\infty)$ on $M$ with
$(M,g(\infty))$ isometric to the standard flat $\mathbb{R}^n$, which implies
topological rigidity of $M$. This generalizes work of Chen, who proved
analogous results for asymptotically flat manifolds. We also prove a long-time
Ricci flow existence (and likewise topological rigidity) result for unbounded
curvature initial data, assuming the initial data is a locally smooth limit of
bounded curvature manifolds as described above.


  Improvements both in the photonic confinement and in the emitter design have
led to a steady increase in the strength of the light-matter coupling in cavity
quantum electrodynamics experiments. This has allowed to access
interaction-dominated regimes in which the state of the system can only be
described in terms of mixed light-matter excitations. Here we show that, when
the coupling between light and matter becomes strong enough, this picture
breaks down, and light and matter degrees of freedom totally decouple. A
striking consequence of such a counter-intuitive phenomenon is that the Purcell
effect is reversed and the spontaneous emission rate, usually thought to
increase with the light-matter coupling strength, plummets instead for large
enough couplings.


  The reconstruction of the initial conditions of the Universe is an important
topic in cosmology, particularly in the context of sharpening the measurement
of the baryon acoustic oscillation (BAO) peak. Nonlinear reconstruction
algorithms developed in recent years, when applied to late-time matter fields,
can recover to a substantial degree the initial density distribution, however,
when applied to sparse tracers of the matter field, the performance is poorer.
In this paper we apply the Shi et al. non-linear reconstruction method to
biased tracers in order to establish what factors affect the reconstruction
performance. We find that grid resolution, tracer number density and mass
assignment scheme all have a significant impact on the performance of our
reconstruction method, with triangular-shaped-cloud (TSC) mass assignment and a
grid resolution of ${\sim}1{-}2h^{-1}$ Mpc being the optimal choice. We also
show that our method can be easily adapted to include generic tracer biases up
to quadratic order in the reconstruction formalism. Applying the reconstruction
to halo and galaxy samples with a range of tracer number densities, we find
that the linear bias is by far the most important bias term, while including
nonlocal and nonlinear biases only leads to marginal improvements on the
reconstruction performance. Overall, including bias in the reconstruction
substantially improves the recovery of BAO wiggles, down to
$k\sim0.25~h\text{Mpc}^{-1}$ for tracer number densities between
$2\times10^{-4}$ and $2\times10^{-3}~(h^{-1}\text{Mpc})^{-3}$.


  Threadneedle is a multi-agent simulation framework, based on a full double
entry book keeping implementation of the banking system's fundamental
transactions. It is designed to serve as an experimental test bed for economic
simulations that can explore the banking system's influence on the
macro-economy under varying assumptions for its regulatory framework, mix of
financial instruments, and activities of borrowers and lenders. Support is
provided for Basel Capital and central bank reserve regulatory frameworks,
inter-bank lending and correct handling of loan defaults within the bank
accounting framework.
  In this paper we provide an overview of the design of Threadneedle, and the
rational for the double entry book keeping approach used in its implementation.
We then provide evidence from a series of experiments using the simulation that
the macro-economic behaviour of the banking system is in some cases sensitive
to double entry book keeping ledger definitions, and in particular that loss
provisions can be systemically affecting. We also show that credit and money
expansion in Basel regulated systems is now dominated by the Basel capital
requirements, rather than the older central bank reserve requirements. This
implies that bank profitability is now the main factor in providing new capital
to support lending, meaning that lowering interest rates can act to restrict
loan supply, rather than increasing borrowing as currently believed. We also
show that long term liquidity flows due to interest repayment act in favour of
the bank making the loan, and do not provide any long term throttling effect on
loan expansion and money expansion as has been claimed by Keynes and others.


  We present a semiclassical prediction of regular-to-chaotic tunneling in
systems with a mixed phase space, including the effect of a nonlinear resonance
chain. We identify complex paths for direct and resonance-assisted tunneling in
the phase space of an integrable approximation with one nonlinear resonance
chain. We evaluate the resonance-assisted contribution analytically and give a
prediction based on just a few properties of the classical phase space. For the
standard map excellent agreement with numerically determined tunneling rates is
observed. The results should similarly apply to ionization rates and quality
factors.


  Band selection plays a crucial role in hyperspectral image classification by
removing redundant and noisy bands and retaining discriminative ones. However,
most existing deep learning-based methods are aimed at dealing with a specific
band selection dataset, and need to retrain parameters for new datasets, which
significantly limits their generalizability.To address this issue, a novel
multi-teacher multi-objective meta-learning network (M$^3$BS) is proposed for
zero-shot hyperspectral band selection. In M$^3$BS, a generalizable graph
convolution network (GCN) is constructed to generate dataset-agnostic base, and
extract compatible meta-knowledge from multiple band selection tasks. To
enhance the ability of meta-knowledge extraction, multiple band selection
teachers are introduced to provide diverse high-quality experiences.strategy
Finally, subsequent classification tasks are attached and jointly optimized
with multi-teacher band selection tasks through multi-objective meta-learning
in an end-to-end trainable way. Multi-objective meta-learning guarantees to
coordinate diverse optimization objectives automatically and adapt to various
datasets simultaneously. Once the optimization is accomplished, the acquired
meta-knowledge can be directly transferred to unseen datasets without any
retraining or fine-tuning. Experimental results demonstrate the effectiveness
and efficiency of our proposed method on par with state-of-the-art baselines
for zero-shot hyperspectral band selection.


  We study the geodesic orbit property for nilpotent Lie groups $N$ when
endowed with a pseudo-Riemannian left-invariant metric. We consider this
property with respect to different groups acting by isometries. When $N$ acts
on itself by left-translations we show that it is a geodesic orbit space if and
only if the metric is bi-invariant. Assuming $N$ is 2-step nilpotent and with
non-degenerate center we give algebraic conditions on the Lie algebra
$\mathfrak n$ of $N$ in order to verify that every geodesic is the orbit of a
one-parameter subgroup of $N\rtimes\operatorname{Auto}(N)$. In addition we
present an example of an almost g.o. space such that for null homogeneous
geodesics, the natural parameter of the orbit is not always the affine
parameter of the geodesic.


  Most offline reinforcement learning (RL) algorithms return a target policy
maximizing a trade-off between (1) the expected performance gain over the
behavior policy that collected the dataset, and (2) the risk stemming from the
out-of-distribution-ness of the induced state-action occupancy. It follows that
the performance of the target policy is strongly related to the performance of
the behavior policy and, thus, the trajectory return distribution of the
dataset. We show that in mixed datasets consisting of mostly low-return
trajectories and minor high-return trajectories, state-of-the-art offline RL
algorithms are overly restrained by low-return trajectories and fail to exploit
high-performing trajectories to the fullest. To overcome this issue, we show
that, in deterministic MDPs with stochastic initial states, the dataset
sampling can be re-weighted to induce an artificial dataset whose behavior
policy has a higher return. This re-weighted sampling strategy may be combined
with any offline RL algorithm. We further analyze that the opportunity for
performance improvement over the behavior policy correlates with the
positive-sided variance of the returns of the trajectories in the dataset. We
empirically show that while CQL, IQL, and TD3+BC achieve only a part of this
potential policy improvement, these same algorithms combined with our
reweighted sampling strategy fully exploit the dataset. Furthermore, we
empirically demonstrate that, despite its theoretical limitation, the approach
may still be efficient in stochastic environments. The code is available at
https://github.com/Improbable-AI/harness-offline-rl.


  The level splitting formula of an asymmetric double well potential is
calculated taking into account the multi-instanton contributions (dilute gas
approximation). Results can be related with known semiclassical ones obtained
with a truncated hamiltonian, and the symmetric case is easily recovered.


  In the "Bits Through Queues" paper, it was hypothesized that full feedback
always increases the capacity of first-in-first-out queues, except when the
service time distribution is memoryless. More recently, a non-explicit
sufficient condition under which feedback increases capacity was provided,
along with simple examples of service times meeting this condition. While this
condition yields examples where feedback is beneficial, it does not offer
explicit structural properties of such service times.
  In this paper, we show that full feedback increases capacity whenever the
service time has bounded support. This is achieved by investigating a
generalized notion of feedback, with full feedback and weak feedback as
particular cases.


  The mean shift (MS) algorithm seeks a mode of the kernel density estimate
(KDE). This study presents a convergence guarantee of the mode estimate
sequence generated by the MS algorithm and an evaluation of the convergence
rate, under fairly mild conditions, with the help of the argument concerning
the {\L}ojasiewicz inequality. Our findings extend existing ones covering
analytic kernels and the Epanechnikov kernel. Those are significant in that
they cover the biweight kernel, which is optimal among non-negative kernels in
terms of the asymptotic statistical efficiency for the KDE-based mode
estimation.


  We introduce a low-order dynamical system to describe thermal convection in
an annular domain. The model derives systematically from a Fourier-Laurent
truncation of the governing Navier-Stokes Boussinesq equations and accounts for
spatial dependence of the flow and temperature fields. Comparison with
fully-resolved direct numerical simulations (DNS) shows that the model captures
parameter bifurcations and reversals of the large-scale circulation (LSC),
including states of (i) steady circulating flow, (ii) chaotic LSC reversals,
and (iii) periodic LSC reversals. Casting the system in terms of the fluid's
angular momentum and center of mass (CoM) reveals equivalence to a damped
pendulum with forcing that raises the CoM above the fulcrum. This formulation
offers a transparent mechanism for LSC reversals, namely the inertial overshoot
of a forced pendulum, and it yields an explicit formula for the frequency $f^*$
of regular LSC reversals in the high Rayleigh-number limit. This formula is
shown to be in excellent agreement with DNS and produces the scaling law $f^*
\sim Ra^{0.5}$.


  To resum large logarithms in multi-scale problems a generalization of $\MS$
is introduced allowing for as many renormalization scales as there are generic
scales in the problem. In the new \lq\lq minimal multi-scale subtraction
scheme'' standard perturbative boundary conditions become applicable. However,
the multi-loop beta functions depend on the various renormalization scale
ratios and a large logarithms resummation has to be performed on them. Using
these improved beta functions the \lq\lq partial'' renormalization group
equations corresponding to the renormalization point independence of physical
quantities allows one to resum the logarithms. As an application the leading
and next-to-leading order two-scale analysis of the effective potential in the
$O(N)$-symmetric $\phi^4$-theory is performed. This calculation indicates that
there is no stable vacuum in the broken phase of the theory for $1<N\leq4$.


  We present a safe-by-design approach to path planning and control for
nonlinear systems. The planner uses a low fidelity model of the plant to
compute reference trajectories by solving an MPC problem, while the plant being
controlled utilizes a feedback control law that tracks those trajectories with
an upper-bound on the tracking error. Our main goal is to allow for maximum
permissiveness (that is, room for constraint feasibility) of the planner, while
maintaining safety after accounting for the tracking error bound. We achieve
this by parametrizing the state and input constraints imposed on the planner
and deriving corresponding parametrized tracking control laws and tracking
error bounds, which are computed offline through Sum-of-Squares programming.
The parameters are then optimally chosen to maximize planner permissiveness,
while guaranteeing safety.


  We report the discovery of a quasar pair at z=5 separated by 21 arcsec. Both
objects were identified as quasar candidates using simple color selection
techniques applied to photometric catalogs from the CFHT Legacy Survey
(CFHTLS). Spectra obtained with the MMT present no discernible offset in
redshift between the two objects; on the other hand, there are clear
differences in the emission line profiles and in the multiwavelength spectral
energy distributions that strongly disfavor the hypothesis that they are
gravitationally lensed images of a single quasar. Both quasars are surprisingly
bright given their proximity (a projected separation of ~135 kpc), with i=19.4
and i=21.4. Previous measurements of the luminosity function demonstrate that
luminous quasars are extremely rare at z=5; the existence of this pair suggests
that quasars have strong small-scale clustering at high redshift. Assuming a
real-space correlation function of the form $\xi(r) \propto (r/r_0)^{-2}$, this
discovery implies a correlation length $r_0 > 20 h^{-1}$ Mpc, consistent with a
rapid strengthening of quasar clustering at high redshift as seen in previous
observations and predicted by theoretical models where feedback effects are
inefficient at shutting down black hole growth at high redshift.


  We review simulations of dynamical domain wall fermions at a fixed inverse
lattice spacing of 1.73GeV and with pion masses as light as 330MeV and spatial
dimensions as large as 2.7fm performed by the RBC and UKQCD collaborations.
These results include pseudoscalar masses and decay constants and low energy
constants of the chiral effective lagrangian. We also review results for the
neutral kaon mixing amplitude $B_K$, the Kl3 form factor, pseudoscalar meson
structure, and vector meson decay constants. In the baryon sector we review
results for the spectrum, and nucleon form factors and structure functions.
Highlights of our programme include preliminary quark masses, and
determinations of $V_{us}$ from both $f_K/f_\pi$ and from Kl3, and an updated
result for $B_K$. We find significant finite volume effects in the nucleon
axial charge $g_A$ for our $m_\pi=330$ MeV ensemble on a $(2.7 {\rm fm})^3$
lattice, and highlight the importance of large physical volumes for non-trivial
nucleon physics.


  Current machine learning has made great progress on computer vision and many
other fields attributed to the large amount of high-quality training samples,
while it does not work very well on genomic data analysis, since they are
notoriously known as small data. In our work, we focus on few-shot disease
subtype prediction problem, identifying subgroups of similar patients that can
guide treatment decisions for a specific individual through training on small
data. In fact, doctors and clinicians always address this problem by studying
several interrelated clinical variables simultaneously. We attempt to simulate
such clinical perspective, and introduce meta learning techniques to develop a
new model, which can extract the common experience or knowledge from
interrelated clinical tasks and transfer it to help address new tasks. Our new
model is built upon a carefully designed meta-learner, called Prototypical
Network, that is a simple yet effective meta learning machine for few-shot
image classification. Observing that gene expression data have specifically
high dimensionality and high noise properties compared with image data, we
proposed a new extension of it by appending two modules to address these
issues. Concretely, we append a feature selection layer to automatically filter
out the disease-irrelated genes and incorporate a sample reweighting strategy
to adaptively remove noisy data, and meanwhile the extended model is capable of
learning from a limited number of training examples and generalize well.
Simulations and real gene expression data experiments substantiate the
superiority of the proposed method for predicting the subtypes of disease and
identifying potential disease-related genes.


  Various approaches have emerged for multi-armed bandits in distributed
systems. The multiplayer dueling bandit problem, common in scenarios with only
preference-based information like human feedback, introduces challenges related
to controlling collaborative exploration of non-informative arm pairs, but has
received little attention. To fill this gap, we demonstrate that the direct use
of a Follow Your Leader black-box approach matches the lower bound for this
setting when utilizing known dueling bandit algorithms as a foundation.
Additionally, we analyze a message-passing fully distributed approach with a
novel Condorcet-winner recommendation protocol, resulting in expedited
exploration in many cases. Our experimental comparisons reveal that our
multiplayer algorithms surpass single-player benchmark algorithms, underscoring
their efficacy in addressing the nuanced challenges of the multiplayer dueling
bandit setting.


  We study diamagnetism of a gas of fermions moving in a nonhomogeneous
magnetic field $( {\bf B} =B( 0, 0, 1/cosh^{2}( \frac{x-x_{0} }{ \delta })))$
The gas magnetization, the static magnetic susceptibility, the chemical
potential and the gas compressibility are discussed and compared with the
uniform field case. General need to study dynamics of electrons in different
types of magnetic fields follows from a large number of experimental situations
in which its understanding enables physicists to obtain new information.


  We study a class of importance sampling methods for stochastic differential
equations (SDEs). A small-noise analysis is performed, and the results suggest
that a simple symmetrization procedure can significantly improve the
performance of our importance sampling schemes when the noise is not too large.
We demonstrate that this is indeed the case for a number of linear and
nonlinear examples. Potential applications, e.g., data assimilation, are
discussed.


  Let G be a torsion-free hyperbolic group and let n > 5 be an integer. We
prove that G is the fundamental group of a closed aspherical manifold if the
boundary of G is homeomorphic to an (n-1)-dimensional sphere.


  KEY WORDS suspensions, inertial focusing, particle-laden flows, high Reynolds
numbers SHORT SUMMARY The inertial migration of particles in square channel
flows at the micro-scale has been deeply investigated in the last two decades.
The well-known four equilibrium positions are located near the center of each
channel face at moderate Reynolds numbers [1]. More recently, Miura et al. [2]
revealed experimentally the presence of eight equilibrium positions in
millimetric square channels for Reynolds numbers higher than 250. The aim of
the present work is to extend these results obtained at millimeter scale to the
micrometer scale. To this end, in situ visualization of particles flowing in
square micro-channels at Reynolds numbers ranging from 5 to 300 have been
conducted and analyzed.


  We consider the novel task of learning disentangled representations of object
shape and appearance across multiple domains (e.g., dogs and cars). The goal is
to learn a generative model that learns an intermediate distribution, which
borrows a subset of properties from each domain, enabling the generation of
images that did not exist in any domain exclusively. This challenging problem
requires an accurate disentanglement of object shape, appearance, and
background from each domain, so that the appearance and shape factors from the
two domains can be interchanged. We augment an existing approach that can
disentangle factors within a single domain but struggles to do so across
domains. Our key technical contribution is to represent object appearance with
a differentiable histogram of visual features, and to optimize the generator so
that two images with the same latent appearance factor but different latent
shape factors produce similar histograms. On multiple multi-domain datasets, we
demonstrate our method leads to accurate and consistent appearance and shape
transfer across domains.


  In this paper, we present a Constraint Energy Minimizing Generalized
Multiscale Finite Element Method (CEM-GMsFEM) for parabolic equations with
multiscale coefficients, arising from applications in porous media. We will
present the construction of CEM-GMsFEM and rigorously analyze its convergence
for the parabolic equations. The convergence rate is characterized by the
coarse grid size and the eigenvalue decay of local spectral problems, but is
independent of the scale length and contrast of the media. The analysis shows
that the method has a first order convergence rate with respect to coarse grid
size in the energy norm and second order convergence rate with respect to
coarse grid size in $L^2$ norm under some appropriate assumptions. For the
temporal discretization, finite difference techniques are used and the
convergence analysis of full discrete scheme is given. Moreover, a posteriori
error estimator is derived and analyzed. A few numerical results for porous
media applications are presented to confirm the theoretical findings and
demonstrate the performance of the approach.


  The Bak--Sneppen model is an abstract representation of a biological system
that evolves according to the Darwinian principles of random mutation and
selection. The species in the system are characterized by a numerical fitness
value between zero and one. We show that in the case of five species the
steady-state fitness distribution can be obtained as a solution to a linear
differential equation of order five with hypergeometric coefficients. Similar
representations for the asymptotic fitness distribution in larger systems may
help pave the way towards a resolution of the question of whether or not, in
the limit of infinitely many species, the fitness is asymptotically uniformly
distributed on the interval [f,1] with f approximately equal to 2/3.


  Coupling photons to Rydberg excitations in a cold atomic gas yields
unprecedentedly large optical nonlinearities at the level of individual light
quanta, where the formation of nearby dark-state polaritons is blocked by the
strong interactions between Rydberg atoms. This blockade mechanism, however,
realizes an inherently dissipative nonlinearity, which limits the performance
of practical applications. In this work, we propose a new approach to strong
photon interactions via a largely coherent mechanism at drastically suppressed
photon losses. Rather than a polariton blockade, it is based on an interaction
induced conversion between distinct types of dark-state polaritons with
different propagation characteristics. We outline a specific implementation of
this approach and show that it permits to turn a single photon into an
effective mirror with a robust and continuously tuneable reflection phase. We
describe potential applications, including a detailed discussion of achievable
operational fidelities.


  Robustness of a distributed computing system is defined as the ability to
maintain its performance in the presence of uncertain parameters. Uncertainty
is a key problem in heterogeneous (and even homogeneous) distributed computing
systems that perturbs system robustness. Notably, the performance of these
systems is perturbed by uncertainty in both task execution time and arrival.
Accordingly, our goal is to make the system robust against these uncertainties.
Considering task execution time as a random variable, we use probabilistic
analysis to develop an autonomous proactive task dropping mechanism to attain
our robustness goal. Specifically, we provide a mathematical model that
identifies the optimality of a task dropping decision, so that the system
robustness is maximized. Then, we leverage the mathematical model to develop a
task dropping heuristic that achieves the system robustness within a feasible
time complexity. Although the proposed model is generic and can be applied to
any distributed system, we concentrate on heterogeneous computing (HC) systems
that have a higher degree of exposure to uncertainty than homogeneous systems.
Experimental results demonstrate that the autonomous proactive dropping
mechanism can improve the system robustness by up to 20%.


  Halo stars with unusually high radial velocity ("hypervelocity" stars, or
HVS) are thought to be stars unbound to the Milky Way that originate from the
gravitational interaction of stellar systems with the supermassive black hole
at the Galactic center. We examine the latest HVS compilation and find
peculiarities that are unexpected in this black hole-ejection scenario. For
example, a large fraction of HVS cluster around the constellation of Leo and
share a common travel time of $\sim 100$-200 Myr. Furthermore, their velocities
are not really extreme if, as suggested by recent galaxy formation models, the
Milky Way is embedded within a $2.5\times 10^{12} h^{-1} M_{\odot}$ dark halo
with virial velocity of $\sim 220$ km/s. In this case, the escape velocity at
$\sim 50$ kpc would be $\sim 600$ km/s and very few HVS would be truly unbound.
We use numerical simulations to show that disrupting dwarf galaxies may
contribute halo stars with velocities up to and sometimes exceeding the nominal
escape speed of the system. These stars are arranged in a thinly-collimated
outgoing ``tidal tail'' stripped from the dwarf during its latest pericentric
passage. We speculate that some HVS may therefore be tidal debris from a dwarf
recently disrupted near the center of the Galaxy. In this interpretation, the
angular clustering of HVS results because from our perspective the tail is seen
nearly ``end on'', whereas the common travel time simply reflects the fact that
these stars were stripped simultaneously from the dwarf during a single
pericentric passage. This proposal is eminently falsifiable, since it makes a
number of predictions that are distinct from the black-hole ejection mechanism
and that should be testable with improved HVS datasets.


  Generic $U(1)^2$ 4-d black holes with unbroken $N=1$ supersymmetry are shown
to tend to a Robinson-Bertotti type geometry with a linear dilaton and doubling
of unbroken supersymmetries near the horizon. Purely magnetic dilatonic black
holes, which have unbroken $N=2$ supersymmetry, behave near the horizon as a
2-d linear dilaton vacuum $\otimes \, S^2$. This geometry is invariant under 8
supersymmetries, i.e. half of the original $N=4$ supersymmetries are unbroken.
The supersymmetric positivity bound, which requires the mass of the 4-d dilaton
black holes to be greater than or equal to the central charge, corresponds to
positivity of mass for a class of stringy 2-d black holes.


  On 13 December 2012, Chang'e-2 completed a successful flyby of the near-Earth
asteroid 4179 Toutatis at a closest distance of 770 meters from the asteroid's
surface. The observations show that Toutatis has an irregular surface and its
shape resembles a ginger-root of a smaller lobe (head) and a larger lobe
(body). Such bilobate shape is indicative of a contact binary origin for
Toutatis. In addition, the high-resolution images better than 3 meters provide
a number of new discoveries about this asteroid, such as an 800-meter
depression at the end of the large lobe, a sharply perpendicular silhouette
near the neck region, boulders, indicating that Toutatis is probably a
rubble-pile asteroid. Chang'e-2 observations have significantly revealed new
insights into the geological features and the formation and evolution of this
asteroid. In final, we brief the future Chinese asteroid mission concept.


  In the presence of flavor oscillations, muon and tau neutrinos can contribute
to the Super-Kamiokande (SK) solar neutrino signal through the neutral current
process \nu_{\mu,\tau} e^{-}\to \nu_{\mu,\tau} e^{-}. We show how to separate
the \nu_e and \nu_{\mu,\tau} event rates in SK in a model independent way, by
using the rate of the charged current process \nu_e d \to p p e^{-} from the
Sudbury Neutrino Observatory (SNO) experiment, with an appropriate choice of
the SK and SNO energy thresholds. Under the additional hypothesis of no
oscillations into sterile states, we also show how to determine the absolute
^{8}B neutrino flux from the same data set, independently of the \nu_e survival
probability.


  We classify the Montesinos links up to mutation and 5-move equivalence, and
obtain from this a Jones and Kauffman polynomial test for a Montesinos link.


  Since the early days of Bardeen-Cooper-Schrieffer theory, it has been
predicted that a sufficiently large supercurrent can close the energy gap in a
superconductor and creates gapless Bogoliubov quasiparticles through the
Doppler shift of quasiparticle energy due to the Cooper pair momentum. In this
gapless superconducting state, zero-energy quasiparticles reside on a segment
of the normal state Fermi surface, while its remaining part is still gapped.
The finite density of states of field-induced quasiparticles, known as the
Volovik effect, has been observed in tunneling and specific heat measurements
on d- and s-wave superconductors. However, the segmented Fermi surface of a
finite-momentum state carrying a supercurrent has never been detected directly.
Here we use quasiparticle interference (QPI) technique to image
field-controlled Fermi surface of Bi$_2$Te$_3$ thin films proximitized by the
superconductor NbSe$_2$. By applying a small in-plane magnetic field, a
screening supercurrent is induced which leads to finite-momentum pairing on
topological surface states of Bi$_2$Te$_3$. Our measurements and analysis
reveal the strong impact of finite Cooper pair momentum on the quasiparticle
spectrum, and thus pave the way for STM study of pair density wave and FFLO
states in unconventional superconductors.


  Using images from the Helioseismic and Magnetic Imager aboard the
\textit{Solar Dynamics Observatory} (SDO/HMI), we extract the radial-velocity
(RV) signal arising from the suppression of convective blue-shift and from
bright faculae and dark sunspots transiting the rotating solar disc. We remove
these rotationally modulated magnetic-activity contributions from simultaneous
radial velocities observed by the HARPS-N solar feed to produce a
radial-velocity time series arising from the magnetically quiet solar surface
(the 'inactive-region radial velocities'). We find that the level of
variability in the inactive-region radial velocities remains constant over the
almost 7 year baseline and shows no correlation with well-known activity
indicators. With an RMS of roughly 1 m/s, the inactive-region radial-velocity
time series dominates the total RV variability budget during the decline of
solar cycle 24. Finally, we compare the variability amplitude and timescale of
the inactive-region radial velocities with simulations of supergranulation. We
find consistency between the inactive-region radial-velocity and simulated time
series, indicating that supergranulation is a significant contribution to the
overall solar radial velocity variability, and may be the main source of
variability towards solar minimum. This work highlights supergranulation as a
key barrier to detecting Earth twins.


  This paper studies the problem of finding typical entities when the concept
is given as a query. For a short concept such as university, this is a
well-studied problem of retrieving knowledge base such as Microsoft's Probase
and Google's isA database pre-materializing entities found for the concept in
Hearst patterns of the web corpus. However, we find most real-life queries are
long concept queries (LCQs), such as top American private university, which
cannot and should not be pre-materialized. Our goal is an online construction
of entity retrieval for LCQs. We argue a naive baseline of rewriting LCQs into
an intersection of an expanded set of composing short concepts leads to highly
precise results with extremely low recall. Instead, we propose to augment the
concept list, by identifying related concepts of the query concept. However, as
such increase of recall often invites false positives and decreases precision
in return, we propose the following two techniques: First, we identify concepts
with different relatedness to generate linear orderings and pairwise ordering
constraints. Second, we rank entities trying to avoid conflicts with these
constraints, to prune out lowly ranked one (likely false positives). With these
novel techniques, our approach significantly outperforms state-of-the-arts.


  C60 fullerides are uniquely flexible molecular materials that exhibit a rich
variety of behavior, including superconductivity and magnetism in bulk
compounds, novel electronic and orientational phases in thin films, and quantum
transport in a single-C60 transistor. The complexity of fulleride properties
stems from the existence of many competing interactions, such as
electron-electron correlations, electron-vibration coupling, and intermolecular
hopping. The exact role of each interaction is controversial due to the
difficulty of experimentally isolating the effects of a single interaction in
the intricate fulleride materials. Here we report a unique level of control of
the material properties of KxC60 ultra-thin films through well-controlled
atomic layer indexing and accurate doping concentrations. Using STM techniques,
we observe a series of electronic and structural phase transitions as the
fullerides evolve from two-dimensional monolayers to quasi-threedimensional
multilayers in the early stages of layer-by-layer growth. These results
demonstrate the systematic evolution of fulleride electronic structure and
molecular ordering with variable KxC60 film layer index, and shed new light on
creating novel molecular structures and devices.


  Generalizability is the ultimate goal of Machine Learning (ML) image
classifiers, for which noise and limited dataset size are among the major
concerns. We tackle these challenges through utilizing the framework of deep
Multitask Learning (dMTL) and incorporating image depth estimation as an
auxiliary task. On a customized and depth-augmented derivation of the MNIST
dataset, we show a) multitask loss functions are the most effective approach of
implementing dMTL, b) limited dataset size primarily contributes to
classification inaccuracy, and c) depth estimation is mostly impacted by noise.
In order to further validate the results, we manually labeled the NYU Depth V2
dataset for scene classification tasks. As a contribution to the field, we have
made the data in python native format publicly available as an open-source
dataset and provided the scene labels. Our experiments on MNIST and
NYU-Depth-V2 show dMTL improves generalizability of the classifiers when the
dataset is noisy and the number of examples is limited.


  The small energy anomaly in the single particle density of states of
disordered interacting systems is studied for the zero dimensional case. This
anomaly interpolates between the non--perturbative Coulomb blockade and the
perturbative limit, the latter being an extension of the Altshuler--Aronov zero
bias anomaly at d=0. Coupling of the zero dimensional system to a dissipative
environment leads to an effective screening of the interaction and a
modification of the density of states.


  Photonic crystals are periodic systems that consist of dielectrics with
different refractive indices. They are designed to act on photons in contrast
to semiconductor crystals whose periodicity affects the motion of electrons.
Here we consider the interaction of an atomic electron with its own radiation
field in the case when the atom is placed in air voids of a photonic crystal
and is not in mechanical contact with the vibrational degrees of freedom of the
dielectric host. A strong modification of this interaction from that in free
space is shown to change the rest mass of the electron, and this has a
significant effect on the shift of the atomic energy levels. This shift is
investigated by using the example of atomic hydrogen in a high-index-contrast
photonic crystal. The found effect may be of interest both from fundamental and
practical points of view.


  In this article we consider the bounds on the noncommutative nature of
space-time. We argue that these bounds are extremely model dependent. In the
only phenomenologically viable framework, i.e. when the fields are taken to be
in the enveloping of the Lie algebra, the constraints are fairly loose and only
of the order of a few TeV.


  The thermodynamic properties of the (2+1)-dimensional non-rotating black hole
of Ba\~nados, Teitelboim and Zanelli are discussed. The first quantum
correction to the Bekenstein-Hawking entropy is evaluated within the on-shell
Euclidean formalism, making use of the related Chern-Simons representation of
the 3-dimensional gravity. Horizon and ultraviolet divergences in the quantum
correction are dealt with a renormalization of the Newton constant. It is
argued that the quantum correction due to the gravitational field shrinks the
effective radius of a hole and becomes more and more important as soon as the
evaporation process goes on, while the area law is not violated.


  We design and realise a hybrid interferometer consisting of three paths based
on integrated as well as on bulk optical components. This hybrid construction
offers a good compromise between stability and footprint on one side and means
of intervention on the other. As experimentally verified by the absence of
higher-order interferences, amplitude and phase can be manipulated in all paths
independently. In conjunction with single photons, the setup can, therefore, be
applied for fundamental investigations on quantum mechanics.


  The paper presents an O(N log N)-implementation of t-SNE -- an embedding
technique that is commonly used for the visualization of high-dimensional data
in scatter plots and that normally runs in O(N^2). The new implementation uses
vantage-point trees to compute sparse pairwise similarities between the input
data objects, and it uses a variant of the Barnes-Hut algorithm - an algorithm
used by astronomers to perform N-body simulations - to approximate the forces
between the corresponding points in the embedding. Our experiments show that
the new algorithm, called Barnes-Hut-SNE, leads to substantial computational
advantages over standard t-SNE, and that it makes it possible to learn
embeddings of data sets with millions of objects.


  High-dynamic-range (HDR) imaging is crucial for many computer graphics and
vision applications. Yet, acquiring HDR images with a single shot remains a
challenging problem. Whereas modern deep learning approaches are successful at
hallucinating plausible HDR content from a single low-dynamic-range (LDR)
image, saturated scene details often cannot be faithfully recovered. Inspired
by recent deep optical imaging approaches, we interpret this problem as jointly
training an optical encoder and electronic decoder where the encoder is
parameterized by the point spread function (PSF) of the lens, the bottleneck is
the sensor with a limited dynamic range, and the decoder is a convolutional
neural network (CNN). The lens surface is then jointly optimized with the CNN
in a training phase; we fabricate this optimized optical element and attach it
as a hardware add-on to a conventional camera during inference. In extensive
simulations and with a physical prototype, we demonstrate that this end-to-end
deep optical imaging approach to single-shot HDR imaging outperforms both
purely CNN-based approaches and other PSF engineering approaches.


  In [1] a syndrome counting based upper bound on the minimum distance of
regular binary LDPC codes is given. In this paper we extend the bound to the
case of irregular and generalized LDPC codes over GF(q). The comparison to the
lower bound for LDPC codes over GF(q) and to the upper bound for non-binary
codes is done. The new bound is shown to lie under the Gilbert-Varshamov bound
at high rates.


  Tidal disruption events (TDEs) occur when a star gets torn apart by the
strong tidal forces of a supermassive black hole, which results in the
formation of a debris stream that partly falls back towards the compact object.
This gas moves along inclined orbital planes that intersect near pericenter,
resulting in a so-called "nozzle shock". We perform the first dedicated study
of this interaction, making use of a two-dimensional simulation that follows
the transverse gas evolution inside a given section of stream. This numerical
approach circumvents the lack of resolution encountered near pericenter passage
in global three-dimensional simulations using particle-based methods. As it
moves inward, we find that the gas motion is purely ballistic, which near
pericenter causes strong vertical compression that squeezes the stream into a
thin sheet. Dissipation takes place at the resulting nozzle shock, inducing a
rise in pressure that causes the collapsing gas to bounce back, although
without imparting significant net expansion. As it recedes to larger distances,
this matter continues to expand while remaining thin despite the influence of
pressure forces. This gas evolution specifies the strength of the subsequent
self-crossing shock, which we find to be more affected by black hole spin than
previously estimated. We also evaluate the impact of general-relativistic
effects, viscous dissipation, magnetic fields and radiative processes on the
nozzle shock. This study represents an important step forward in the
theoretical understanding of TDEs, bridging the gap between our robust
knowledge of the fallback rate and the more complex following stages, during
which most of the emission occurs.


  Low Reynolds number swimmers frequently move near boundaries, such as
spirochetes moving through porous tissues and sperm navigating the reproductive
tract. Furthermore, these microorganisms must often navigate non-Newtonian
fluids such as mucus, which are typically shear-thinning and viscoelastic.
Here, we experimentally investigate such a system using the model biological
organism \textit{C. elegans} swimming through microfluidic channels containing
viscous Newtonian fluids and viscoelastic fluids. Swimmer kinematics and
resulting flow fields are measured as a function of channel width and therefore
the strength of confinement. Results show that, for viscoelastic fluids, weak
or moderate confinement can lead to enhancement in propulsion speed but for
strong confinement this enhancement is lost and the swimming speed is slower
than for an unconfined nematode. We use theory developed for bending elastic
filaments in viscoelastic fluids to show that while (weak) confinement leads to
increases in swimming speed there is a, $De-$ dependent, $Wi$ (Weissenberg
number) number transition from a linear stress response regime to a nonlinear
(or exponential) stress response regime. The experimentally obtained velocity
fields are used to calculate a Weissenberg number to show that the decrease in
swimming speed with confinement is likely related to growth in elastic stresses
around the swimmer.


  We analyze thermal emission of radiation in homogeneous clouds. The clouds
have negligible horizontal variation, but the temperature can vary vertically.
The radiation at optical depth $\tau$ above the cloud bottom is characterized
by intensity values $I(\mu_i,\tau)$ at $2n$ Gauss-Legendre direction cosines
$\mu_i$, the roots of the $2n$th Legendre polynomial, $P_{2n}(\mu_i)=0$.
Scattering matrices describe the intensity fraction with incoming direction
cosine $\mu_{i'}$ that is scattered to intensity with outgoing direction cosine
$\mu_{i}$. Green's-function matrices describe radiation generated by
infinitesimally thin layers of cloud particulates, thermally emitting at the
source optical depth $\tau'$. For thin isothermal clouds of optical thickness
$\tau_c\le1$, thermal emission is mainly determined by the single scattering
albedo $\tilde \omega$. The emitted intensity is limb brightened and depends
little on the scattering phase function. For optically thick isothermal clouds,
with $\tau_c \gg 1$, purely absorbing clouds with $\tilde\omega = 0$ become
perfect blackbodies and emit isotropic Planck intensity. Thick isothermal
clouds with moderate single scattering albedos emit substantially less thermal
radiation than black bodies and the emission depends strongly on the anisotropy
of the scattering phase function. Clouds with strong forward scattering are
``blackest" and emit the most thermal radiation. There is limb darkening which
is most pronounced for strongly forward-scattering phase functions. The limb
darkening in thick, isothermal, scattering clouds is not due to temperature
gradients, as it is for the Sun. With scattering, nearly vertical radiation
produced by thermal emission escapes through the surface more efficiently than
nearly horizontal radiation. There is limb darkening even for purely absorbing
particulates for clouds with hot interiors.


  Although general relativistic cosmological solutions, even in the presence of
pressure, can be mimicked by using neo-Newtonian hydrodynamics, it is not clear
whether there exists the same Newtonian correspondence for spherical static
configurations. General relativity solutions for stars are known as the
Tolman-Oppenheimer-Volkoff (TOV) equations. On the other hand, the Newtonian
description does not take into account the total pressure effects and therefore
can not be used in strong field regimes. We discuss how to incorporate pressure
in the stellar equilibrium equations within the neo-Newtonian framework. We
compare the Newtonian, neo-Newtonian and the full relativistic theory by
solving the equilibrium equations for both three approaches and calculating the
mass-radius diagrams for some simple neutron stars equation of state.


  Video super-resolution (VSR) techniques, especially deep-learning-based
algorithms, have drastically improved over the last few years and shown
impressive performance on synthetic data. However, their performance on
real-world video data suffers because of the complexity of real-world
degradations and misaligned video frames. Since obtaining a synthetic dataset
consisting of low-resolution (LR) and high-resolution (HR) frames are easier
than obtaining real-world LR and HR images, in this paper, we propose
synthesizing real-world degradations on synthetic training datasets. The
proposed synthetic real-world degradations (SRWD) include a combination of the
blur, noise, downsampling, pixel binning, and image and video compression
artifacts. We then propose using a random shuffling-based strategy to simulate
these degradations on the training datasets and train a single end-to-end deep
neural network (DNN) on the proposed larger variation of realistic synthesized
training data. Our quantitative and qualitative comparative analysis shows that
the proposed training strategy using diverse realistic degradations improves
the performance by 7.1 % in terms of NRQM compared to RealBasicVSR and by 3.34
% compared to BSRGAN on the VideoLQ dataset. We also introduce a new dataset
that contains high-resolution real-world videos that can serve as a common
ground for bench-marking.


  The data from all solar neutrino experiments presented at the Neutrino 98
conference has been analyzed and a brief summary of the status of the two most
popular neutrino solutions of the solar neutrino problem, the MSW mechanism and
vacuum oscillations, is presented here. The inclusion of the recoil-electron
data and of the zenith angle distribution of events in the SuperKamiokande
detector, together with the routine analysis of the rates, into a global
$\chi^2$ fit impose stringent constraints on these neutrino oscillation
scenarios.


  The local void model has lately attracted considerable attention since it can
explain the present apparent accelerated expansion of the universe without
introducing dark energy. However, in order to justify this model as an
alternative cosmological model to the standard $\Lambda$CDM model (FLRW
universe plus dark energy), one has to test the model by various observations,
such as CMB temperature anisotropy, other than the distance-redshift relation
of SNIa. For this purpose, we derive some analytic formulae that can be used to
rigorously compare consequences of this model with observations of CMB
anisotropy and to place constraints on the position of observers in the void
model.