  We present a model of an outburst of the soft X-ray transient A0620-003. A
two-dimensional time-dependent smoothed particle hydrodynamics scheme is used
to simulate the evolution of the accretion disc through a complete outburst.
The scheme includes the full tidal potential of the binary and a simple
treatment of the thermal-viscous disc instability.
  In the case where the mass accretion rate onto the primary determines the
fraction of the disc that can be kept in a hot, high viscosity state by the
resulting X-ray emission, we find that the shape of the X-ray light curve is
ultimately determined by the relative sizes of the irradiated and unirradiated
parts of the disc and the growth time-scale of the tidal instability.
  The model accounts for the rebrightening that has been observed in the light
curves of A0620-003 and several other transients. The primary maximum and
subsequent decline are due to the accretion of gas within the irradiated
portion of the disc, while the secondary maximum is caused by the accretion of
gas in the outer part of the disc that is initially shadowed from the central
X-rays, but subject to tidal forces. We propose that tidal effects at the disc
edge can be sufficient to drive accretion on a time-scale shorter than that
expected for a standard alpha-viscosity disc.
  The final decay is subsequently controlled by the gradual retreat of the
irradiated portion of the disc. If the entire disc is kept in the
high-viscosity state by the irradiation, no rebrightening is possible.


  Starting from a microscopic lattice model, we investigate clustering,
micellization and micelle ordering in semi-dilute solutions of AB diblock
copolymers in a selective solvent. To bridge the gap in length scales, from
monomers to ordered micellar structures, we implement a two-step coarse
graining strategy, whereby the AB copolymers are mapped onto ``ultrasoft''
dumbells with monomer-averaged effective interactions between the centres of
mass of the blocks. Monte Carlo simulations of this coarse-grained model yield
clear-cut evidence for self-assembly into micelles with a mean aggregation
number n of roughly 100 beyond a critical concentration. At a slightly higher
concentration the micelles spontaneously undergo a disorder-order transition to
a cubic phase. We determine the effective potential between these micelles from
first principles.


  The computational cost as well as the probabilistic skill of ensemble
forecasts depends on the spatial resolution of the numerical weather prediction
model and the ensemble size. Periodically, e.g. when more computational
resources become available, it is appropriate to reassess the balance between
resolution and ensemble size. Recently, it has been proposed to investigate
this balance in the context of dual-resolution ensembles, which use members
with two different resolutions to make probabilistic forecasts. This study
investigates whether statistical post-processing of such dual-resolution
ensemble forecasts changes the conclusions regarding the optimal
dual-resolution configuration.
  Medium-range dual-resolution ensemble forecasts of 2-metre temperature have
been calibrated using ensemble model output statistics. The forecasts are
produced with ECMWF's Integrated Forecast System and have horizontal
resolutions between 18 km and 45 km. The ensemble sizes range from 8 to 254
members. The forecasts are verified with SYNOP station data. Results show that
score differences between various single and dual-resolution configurations are
strongly reduced by statistical post-processing. Therefore, the benefit of some
dual-resolution configurations over single resolution configurations appears to
be less pronounced than for raw forecasts. Moreover, the ranking of the
ensemble configurations can be affected by the statistical post-processing.


  The detailed proof of cancellation of topologically unfactorized infrared
divergences in the inclusive production of lepton pair close to the threshold
of heavy quarkonia is presented. To make the effects of transition between
states containing heavy quark pairs, which is important in such cancellation,
the final detected states are constrained to be lepton pair near the threshold
of the heavy quarkonia instead of heavy quarkonia themselves. Such cancellation
is crucial for the NRQCD factorization of these processes.


  We present a condition for towers of fiber bundles which implies that the
fundamental group of the total space has a nilpotent subgroup of finite index
whose torsion is contained in its center. Moreover, the index of the subgroup
can be bounded in terms of the fibers of the tower.
  Our result is motivated by the conjecture that every almost nonnegatively
curved closed m-dimensional manifold M admits a finite cover M' for which the
number of leafs is bounded in terms of m such that the torsion of the
fundamental group of M' lies in its center.


  We present some results that show that bounds from classical coding theory
still work in many cases of quantum coding theory.


  Following recent fit of supernovae data to Brans-Dicke theory which favours
the model with $\omega = - 3/2$ \cite{fabris} we discuss the status of this
special case of Brans-Dicke cosmology in both isotropic and anisotropic
framework. It emerges that the limit $\omega = -3/2$ is consistent only with
the vacuum field equations and it makes such a Brans-Dicke theory conformally
invariant. Then it is an example of the conformal relativity theory which
allows the invariance with respect to conformal transformations of the metric.
Besides, Brans-Dicke theory with $\omega = -3/2$ gives a border between a
standard scalar field model and a ghost/phantom model.
  In this paper we show that in $\omega = -3/2$ Brans-Dicke theory, i.e., in
the conformal relativity there are no isotropic Friedmann solutions of non-zero
spatial curvature except for $k=-1$ case. Further we show that this $k=-1$
case, after the conformal transformation into the Einstein frame, is just the
Milne universe and, as such, it is equivalent to Minkowski spacetime. It
generally means that only flat models are fully consistent with the field
equations. On the other hand, it is shown explicitly that the anisotropic
non-zero spatial curvature models of Kantowski-Sachs type are admissible in
$\omega = -3/2$ Brans-Dicke theory. It then seems that an additional scale
factor which appears in anisotropic models gives an extra deegre of freedom and
makes it less restrictive than in an isotropic Friedmann case.


  Parity-time (PT) symmetry is a fundamental notion in quantum field theories.
It has opened a new paradigm for non-Hermitian Hamiltonians ranging from
quantum mechanics, electronics, to optics. In the realm of optics, optical loss
is responsible for power dissipation, therefore typically degrading device
performance such as attenuation of a laser beam. By carefully exploiting
optical loss in the complex dielectric permittivity, however, recent
exploration of PT symmetry revolutionizes our understandings in fundamental
physics and intriguing optical phenomena such as exceptional points and phase
transition that are critical for high-speed optical modulators. The interplay
between optical gain and loss in photonic PT synthetic matters offers a new
criterion of positively utilizing loss to efficiently manipulate gain and its
associated optical properties. Instead of simply compensating optical loss in
conventional lasers, for example, it is theoretically proposed that judiciously
designed delicate modulation of optical loss and gain can lead to PT synthetic
lasing that fundamentally broadens laser physics. Here, we report the first
experimental demonstration of PT synthetic lasers. By carefully exploiting the
interplay between gain and loss, we achieve degenerate eigen modes at the same
frequency but with complex conjugate gain and loss coefficients. In contrast to
conventional ring cavity lasers with multiple modes, the PT synthetic
micro-ring laser exhibits an intrinsic single mode lasing: the non-threshold PT
broken phase inherently associated in such a photonic system squeezes broadband
optical gain into a single lasing mode regardless of the gain spectral
bandwidth. This chip-scale semiconductor platform provides a unique route
towards fundamental explorations of PT physics and next generation of
optoelectronic devices for optical communications and computing.


  A brief overview of strangeness physics with the CLAS detector at JLab is
given, mainly covering the domain of nucleon resonances. Several excited states
predicted by the symmetric constituent quark model may have significant
couplings to the K-Lambda or K-Sigma channels. I will discuss data that are
relevant in the search for such states in the strangeness channel, and give an
outlook on the future prospects of the N* program at JLab with electromagnetic
probes.


  We develop a Newtonian model of a deep tidal disruption event (TDE), for
which the pericenter distance of the star, $r_{\rm p}$, is well within the
tidal radius of the black hole, $r_{\rm t}$, i.e., when $\beta \equiv r_{\rm
t}/r_{\rm p} \gg 1$. We find that shocks form for $\beta \gtrsim 3$, but they
are weak (with Mach numbers $\sim 1$) for all $\beta$, and that they reach the
center of the star prior to the time of maximum adiabatic compression for
$\beta \gtrsim 10$. The maximum density and temperature reached during the TDE
follow much shallower relations with $\beta$ than the previously predicted
$\rho_{\rm max} \propto \beta^3$ and $T_{\rm max} \propto \beta^2$ scalings.
Below $\beta \simeq 10$, this shallower dependence occurs because the pressure
gradient is dynamically significant before the pressure is comparable to the
ram pressure of the freefalling gas, while above $\beta \simeq 10$ we find that
shocks prematurely halt the compression and yield the scalings $\rho_{\rm max}
\propto \beta^{1.62}$ and $T_{\rm max} \propto \beta^{1.12}$. We find excellent
agreement between our results and high-resolution simulations. Our results
demonstrate that, in the Newtonian limit, the compression experienced by the
star is completely independent of the mass of the black hole. We discuss our
results in the context of existing (affine) models, polytropic
vs.~non-polytropic stars, and general relativistic effects, which become
important when the pericenter of the star nears the direct capture radius, at
$\beta \sim 12.5$ (2.7) for a solar-like star disrupted by a $10^6M_{\odot}$
($10^{7}M_{\odot}$) supermassive black hole.


  Gravitational theories invariant under transverse diffeomorphisms and Weyl
transformations have the same classical solutions as the corresponding fully
diffeomorphism invariant theories. However, they solve some of the problems
related to the cosmological constant and in principle allow local energy
non-conservation. In the present work, we obtain the Noether charge formalism
for these theories. We first derive expressions for the Noether currents and
charges corresponding to transverse diffeomorphisms and Weyl transformations,
showing that the latter vanish identically. We then use these results to obtain
an expression for a perturbation of a Hamiltonian corresponding to evolution
along a transverse diffeomorphism generator. From this expression, we derive
the first law of black hole mechanics, identifying the total energy, the total
angular momentum, the Wald entropy, and the contributions of the cosmological
constant perturbations and energy non-conservation. Lastly, we extend our
formalism to derive the first law of causal diamonds.


  Few-shot learning (FSL) aims to learn a classifier that can be easily adapted
to accommodate new tasks not seen during training, given only a few examples.
To handle the limited-data problem in few-shot regimes, recent methods tend to
collectively use a set of local features to densely represent an image instead
of using a mixed global feature. They generally explore a unidirectional
query-to-support paradigm in FSL, e.g., find the nearest/optimal support
feature for each query feature and aggregate these local matches for a joint
classification. In this paper, we propose a new method Mutual Centralized
Learning (MCL) to fully affiliate the two disjoint sets of dense features in a
bidirectional paradigm. We associate each local feature with a particle that
can bidirectionally random walk in a discrete feature space by the
affiliations. To estimate the class probability, we propose the features'
accessibility that measures the expected number of visits to the support
features of that class in a Markov process. We relate our method to learning a
centrality on an affiliation network and demonstrate its capability to be
plugged in existing methods by highlighting centralized local features.
Experiments show that our method achieves the state-of-the-art on both
miniImageNet and tieredImageNet.


  We examine the boundary conditions associated with extended supersymmetric
Maxwell theory in 5-dimensional anti-De Sitter space. Excitations on the
boundary are identical to those of ordinary 4-dimensional conformal invariant
super electrodynammics. Extrapolations of these excitations give rise to a
5-dimensional topological gauge theory of the singleton type. The possibility
of a connection of this phenomenon to the world volume theory of 3-branes in
IIB string theory is discussed.


  We present several infinite series of synchronizing automata for which the
minimum length of reset words is close to the square of the number of states.
These automata are closely related to primitive digraphs with large exponent.


  A new model for dark matter is put forward which consists of uniform droplets
of Bose Einstein condensate. In this model, structure forms rapidly, shortly
after the hot big bang plasma de-ionises. The model also produces modifications
to the expansion rate before droplet formation that affect the measurement of
cosmological parameters from Cosmic Microwave Background data. The model could
contribute to explaining why observations at high redshift see anomalously high
structure formation and predict low values for the Hubble constant.


  GraphRT is a graph based deep learning model that predicts the retention time
(RT) of peptides in liquid chromatography tandem mass spectrometry (LC MSMS)
experiments. Each amino acid is represented as a graph, capturing its atomic
and structural properties through a graph neural network. This enables the
model to understand not just the chemical composition of each amino acid, but
also the intricate relationships between its atoms. The sequential context of
the peptide the order and interaction of amino acids in the sequence is then
encoded using recurrent neural networks. This dual approach of graph based and
sequential modelling allows for a comprehensive understanding of both the
individual characteristics of amino acids and their collective behaviour in a
peptide sequence. GraphRT outperforms all current state of the art models and
can predict retention time for peptides containing unseen modifications.


  We observe that the continuity assumption on $f$ for the uniform estimates of
the canonical solution to $\bar\partial u = f$ on products of $C^2$ bounded
planar domains in \cite{DPZ} can be reduced to the boundedness assumption. This
completely answers the original question raised by Kerzman in 1971. Moreover,
the $L^p$ estimates of $\bar\partial$ is obtained for all $p \in [1, \infty]$.


  We recently proposed a new approach for the real-time monitoring of particle
therapy treatments with the goal of achieving high sensitivities on the
particle range measurement already at limited counting statistics. This method
extends the Prompt Gamma (PG) timing technique to obtain the PG vertex
distribution from the exclusive measurement of particle Time-Of-Flight (TOF).
It was previously shown, through Monte Carlo simulation, that an original data
reconstruction algorithm (Prompt Gamma Time Imaging) allows to combine the
response of multiple detectors placed around the target. In this work we focus
on the experimental feasibility of PGTI in Single Proton Regime (SPR) through
the development of a multi-channel, Cherenkov-based PG detector with a targeted
time resolution of 235 ps (FWHM): the TOF Imaging ARrAy (TIARA). The PG module
that we developed is composed of a small PbF$_{2}$ crystal coupled to a silicon
photoMultiplier to provide the time stamp of the PG. This prototype was tested
with 63 MeV protons delivered from a cyclotron: a time resolution of 276 ps
(FWHM) was obtained, resulting in a proton range sensitivity of 4 mm at
2$\sigma$ with the acquisition of only 600 PGs. A second prototype was also
evaluated with 148 MeV protons delivered from a synchro-cyclotron obtaining a
time resolution below 167 ps (FWHM) for the gamma detector. Moreover, using two
identical PG modules, it was shown that a uniform sensitivity on the PG
profiles would be achievable by combining the response of gamma detectors
uniformly distributed around the target. This work provides the experimental
proof-of-concept for the development of a high sensitivity detector that can be
used to monitor particle therapy treatments and potentially act in real-time if
the irradiation does not comply to treatment plan.


  For a family of minimal helicoids H_a in the hyperbolic 3-space, there exists
a constant a_c=2.17966 such that the following statements are true: (1) H_a is
a globally stable minimal surface if 0<=a<=a_c, and (2) H_a is an unstable
minimal surface with index one if a>a_c.


  Meteoroids impacting the Earth on a daily basis are fragments of asteroids
and comets. By studying fireballs produced during their disintegration in the
atmosphere, we can gain information about their source regions and the
properties of their parent bodies. In this work, data on 824 fireballs
presented in an accompanying paper and catalog are used. We propose a new
empirical parameter for the classification of the physical properties of
meteoroids, based on the maximum dynamic pressure suffered by the meteoroid in
the atmosphere. We then compare the physical and orbital properties of
meteoroids. We find that aphelion distance is a better indicator of asteroidal
origin than the Tisserand parameter. Meteoroids with aphelia lower than 4.9 AU
are mostly asteroidal, with the exception of the Taurids and alpha Capricornids
associated with the comets 2P/Encke and 169P/NEAT, respectively. We found
another population of strong meteoroids of probably asteroidal origin on orbits
with either high eccentricities or high inclinations, and aphelia up to ~ 7 AU.
Among the meteoroid streams, the Geminids and eta Virginids are the strongest,
and Leonids and alpha Capricornids the weakest. We found fine orbital
structures within the Geminid and Perseid streams. Four minor meteoroid streams
from the working list of the International Astronomical Union were confirmed.
No meteoroid with perihelion distance lower than 0.07 AU was detected. Spectra
are available for some of the fireballs, and they enabled us to identify
several iron meteoroids and meteoroids deficient in sodium. Recognition and
frequency of fireballs leading to meteorite falls is also discussed.


  In this work, we study two different quantum simulators composed of molecules
with dipole-dipole interaction through various theoretical and numerical tools.
Our first result provides knowledge upon the quantum order by disorder effect
of the $S=1/2$ system, which is programmable in a quantum simulator composed of
circular Rydberg atoms in the triangular optical lattice with a controllable
diagonal anisotropy. When the numbers of up spins and down spins are equal, a
set of sub-extensive degenerate ground states is present in the classical
limit, composed of continuous strings whose configuration enjoys a large degree
of freedom. Adopting the the real space perturbation theory, our calculation
demonstrates a lifting of the degeneracy, favoring the stripe configuration.
When $J$ becomes larger, we adopt the infinite projected entangled-pair
state~(iPEPS) and numerically check the effect of degeneracy lifting. The iPEPS
results show that even when the spin exchange coupling is strong the stripe
pattern is still favored. Next, we study the dipolar bosonic model with tilted
polar angle which can be realized through a quantum simulator composed of cold
atomic gas with dipole-dipole interaction in an optical lattice. By placing the
atoms in a triangular lattice and tilting the polar angle, the diagonal
anisotropy can also be realized in the bosonic system. With our cluster
mean-field theory calculation, we provide various phase diagrams with different
tilted angles, showing the abundant underlying phases including the supersolid.
Our proposal indicates realizable scenarios through quantum simulators in
studying the quantum effect as well as extraordinary phases. We believe that
our results indicated here can also become a good benchmark for the
two-dimensional quantum simulators.


  In this article mixed CuInP$_2$(S$_x$Se$_{1-x}$)$_6$ crystals were
investigated by broadband dielectric spectroscopy (20 Hz - 3 GHz). The complete
phase diagram has been obtained from these results. The phase diagram of
investigated crystals is strongly asymmetric - the decreasing of ferroelectric
phase transition temperatures in CuInP$_2$(S$_x$Se$_{1-x}$)$_6$ is much more
flat with small admixture of sulphur then with small admixture of selenium. In
the middle part of the phase diagram (x=0.4-0.9) the dipolar glass phase has
been observed. In boundary region between ferroelectric order and dipolar glass
disorder with small amount of sulphur (x=0.2-0.25) at low temperatures the
nonergodic relaxor phase appears. The phase diagram was discussed in terms of
random bonds and random fields.


  We extend the dimension and strong linearity results of generic vanishing
theory to bundles of holomorphic forms and rank one local systems, and more
generally to certain coherent sheaves of Hodge-theoretic origin associated to
irregular varieties. Our main tools are Saito's mixed Hodge modules, the
Fourier-Mukai transform for D-modules on abelian varieties introduced by Laumon
and Rothstein, and Simpson's harmonic theory for flat bundles. In the process,
we discover two natural categories of perverse coherent sheaves, one on the
Picard variety, and the other on the moduli space of Higgs line bundles or that
of line bundles with flat connection.


  Model Predictive Control (MPC) approaches are widely used in robotics, since
they guarantee feasibility and allow the computation of updated trajectories
while the robot is moving. They generally require heuristic references for the
tracking terms and proper tuning of the parameters of the cost function in
order to obtain good performance. For instance, when a legged robot has to
react to disturbances from the environment (e.g., recover after a push) or
track a specific goal with statically unstable gaits, the effectiveness of the
algorithm can degrade. In this work, we propose a novel optimization-based
Reference Generator which exploits a Linear Inverted Pendulum (LIP) model to
compute reference trajectories for the Center of Mass while taking into account
the possible under-actuation of a gait (e.g., in a trot). The obtained
trajectories are used as references for the cost function of the Nonlinear MPC
presented in our previous work. We also present a formulation that ensures
guarantees on the response time to reach a goal without the need to tune the
weights of the cost terms. In addition, footholds are corrected using the
optimized reference to drive the robot towards the goal. We demonstrate the
effectiveness of our approach both in simulations and experiments in different
scenarios with the Aliengo robot.


  By analyzing $e^+e^-$ annihilation data corresponding to an integrated
luminosity of 2.93 $\rm fb^{-1}$ collected at a center-of-mass energy of 3.773
GeV with the \text{BESIII} detector, the first observation of the semileptonic
decays $D^0\rightarrow K_S^0\pi^-\pi^0 e^+ \nu_e$ and $D^+\rightarrow
K_S^0\pi^+\pi^- e^+ \nu_e$ is reported. With a dominant hadronic contribution
from $K_1(1270)$, the branching fractions are measured to be
$\mathcal{B}(D^0\rightarrow {K}_1(1270)^-(\to
K^0_S\pi^-\pi^0)e^+\nu_e)=(1.69^{+0.53}_{-0.46}\pm0.15)\times10^{-4}$ and
$\mathcal{B}(D^+\to \bar{K}_1(1270)^0(\to
K^0_S\pi^+\pi^-)e^+\nu_e)=(1.47^{+0.45}_{-0.40}\pm0.20)\times10^{-4}$ with
statistical significance of 5.4$\sigma$ and 5.6$\sigma$, respectively. When
combined with measurements of the $K_1(1270)\to K^+\pi^-\pi$ decays, the
absolute branching fractions are determined to be $\mathcal{B}(D^0\to
K_1(1270)^-e^+\nu_e)=(1.05^{+0.33}_{-0.28}\pm0.12\pm0.12)\times10^{-3}$ and
$\mathcal{B}(D^+\to
\bar{K}_1(1270)^0e^+\nu_e)=(1.29^{+0.40}_{-0.35}\pm0.18\pm0.15)\times10^{-3}$.
The first and second uncertainties are statistical and systematic,
respectively, and the third uncertainties originate from the assumed branching
fractions of the $K_1(1270)\to K\pi\pi$ decays.


  Significant obstacles prevent large, university-level, introductory physics
courses from effectively teaching problem-solving skills. We describe our
program for integrating three internet-based "teaching-while-quizzing" tools to
address two of these barriers: students' poor math skills and instructors'
insufficient grading recourses. We outline our system of math remediation,
homework and after-homework quizzes, and mini-practice exams, and demonstrate
how it can be incorporated into courses with modest instructor effort.


  The dynamic behavior of the cylindrical shell can be predicted by more
simplified beam models for a wide range of applications. The present paper
deals with finding design conditions in which the cylindrical shell performs
like a beam.


  The Transition-Edge Sensor (TES) is an extremely sensitive device which is
used to measure the energy of individual X-ray photons. For astronomical
spectrometry applications, SRON develops a Frequency Domain Multiplexing (FDM)
read-out system for kilopixel arrays of such TESs. Each TES is voltage biased
at a specific frequency in the range 1 to 5 MHz. Isolation between the
individual pixels is obtained through very narrow-band (high-Q) lithographic LC
resonators. To prevent energy resolution degradation due to intermodulation
line noise, the bias frequencies are distributed on a regular grid. The
requirements on the accuracy of the LC resonance frequency are very high. The
deviation of the resonance frequencies due to production tolerances is
significant with respect to the bandwidth, and a controller is necessary to
compensate for the LC series impedance. We present two such controllers: a
simple orthogonal proportional-integrating (PI) controller and a more complex
impedance estimator. Both controllers operate in baseband and try to make the
TES current in-phase with the bias voltage, effectively operating as
phase-locked loops (PLL). They allow off-LC-resonance operation of the TES
pixels, while preserving TES thermal response and energy resolution. Extensive
experimental results -- published in a companion paper recently -- with the
proposed methods, show that these controllers allow the preservation of single
pixel energy resolution in multiplexed operation.


  Following the direction of 1712.09990 and 1712.09994, this article continues
to excavate more interesting aspects of the 4-particle amplituhedron for a
better understanding of the 4-particle integrand of planar N=4 SYM to all loop
orders, from the perspective of positive geometry. At 3-loop order, we
introduce a much more refined dissection of the amplituhedron to understand its
essential structure and maximally simplify its direct calculation, by fully
utilizing its symmetry as well as the efficient Mondrian way for reorganizing
all contributing pieces. Although significantly improved, this approach
immediately encounters its technical bottleneck at 4-loop. Still, we manage to
alleviate this difficulty by imitating the traditional (generalized) unitarity
cuts, which is to use the so-called positive cuts. Given a basis of dual
conformally invariant (DCI) loop integrals, we can figure out the coefficient
of each DCI topology using its dlog form via positivity conditions. Explicit
examples include all 2+5 non-rung-rule topologies at 4- and 5-loop
respectively. These results remarkably agree with previous knowledge, which
confirms the validity of amplituhedron up to 5-loop and develops a new approach
of determining the coefficient of each distinct DCI loop integral.


  We provide some new consequences on the Lipschitz numerical radius and index
which were introduced recently. More precisely, we give some renorming results
on the Lipschitz numerical index, introduce a concept of Lipschitz numerical
radius attaining functions in order to show that the denseness fails for an
arbitrary Banach space, and study a Lipschitz version of Daugavet centers.
Furthermore, we discuss the Lipschitz numerical index of vector-valued function
spaces, absolute sums of Banach spaces, the K\"othe-Bochner spaces, and Banach
spaces which contain a dense union of increasing family of one-complemented
subspaces.


  Recently, a method was presented for constructing self-energies within
many-body perturbation theory that are guaranteed to produce a positive
spectral function for equilibrium systems, by representing the self-energy as a
product of half-diagrams on the forward and backward branches of the Keldysh
contour. We derive an alternative half-diagram representation that is based on
products of retarded diagrams. Our approach extends the method to systems out
of equilibrium. When a steady-state limit exists, we show that our approach
yields a positive definite spectral function in the frequency domain.


  Showers of $\gamma$-rays and positrons are produced when a high-energy
electron beam collides with a super-intense laser pulse. We present scaling
laws for the electron beam energy loss, the $\gamma$-ray spectrum, and the
positron yield and energy that are valid in the non-linear,
radiation-reaction--dominated regime. As an application we demonstrate that by
employing the collision of a $>$GeV electron beam with a laser pulse of
intensity $>5\times10^{21}\,\text{Wcm}^{-2}$, today's high-intensity laser
facilities are capable of producing $O(10^4)$ positrons per shot via
light-by-light scattering.


  We show that the Kounterterms for pure AdS gravity in arbitrary even
dimensions coincide with the boundary counterterms obtained through holographic
renormalization if and only if the boundary Weyl tensor vanishes. In
particular, the Kounterterms lead to a well posed variational problem for
generic asymptotically locally AdS manifolds only in four dimensions. We
determine the exact form of the counterterms for conformally flat boundaries
and demonstrate that, in even dimensions, the Kounterterms take exactly the
same form. This agreement can be understood as a consequence of Anderson's
theorem for the renormalized volume of conformally compact Einstein 4-manifolds
and its higher dimensional generalizations by Albin and Chang, Qing and Yang.
For odd dimensional asymptotically locally AdS manifolds with a conformally
flat boundary, the Kounterterms coincide with the boundary counterterms except
for the logarithmic divergence associated with the holographic conformal
anomaly, and finite local terms.


  Cellular automata (CAs) are dynamical systems which exhibit complex global
behavior from simple local interaction and computation. Since the inception of
cellular automaton (CA) by von Neumann in 1950s, it has attracted the attention
of several researchers over various backgrounds and fields for modelling
different physical, natural as well as real-life phenomena. Classically, CAs
are uniform. However, non-uniformity has also been introduced in update
pattern, lattice structure, neighborhood dependency and local rule. In this
survey, we tour to the various types of CAs introduced till date, the different
characterization tools, the global behaviors of CAs, like universality,
reversibility, dynamics etc. Special attention is given to non-uniformity in
CAs and especially to non-uniform elementary CAs, which have been very useful
in solving several real-life problems.


  An experimentally inspired model is constructed and rigorously solved from
the Hamiltonian level where a dc circular spontaneous flow exists in absence of
a magnetic field, irrespective of presence of dissipation causing otherwise
proper relaxation. The flow causes a spontaneous unidirectional transfer of
heat from one bath to another one, even against temperature step. This is what
is explicitly forbidden by the Clausius form of the Second law of
thermodynamics. The unidirectionality of the flow is caused by that of
spontaneous processes known to bear this property since their introduction by
Einstein. The model slightly improves the previous one (\v{C}\'{a}pek & Sheehan
2002), describes a realistic plasma system for which experimental results
violating the second law were announced, and the result obtained fully supports
the experimental conclusions (Sheehan 1995). Analytical proof of the violation
is supported by numerical results. All mathematical details are exposed, two
fully independent types of mathematical arguments behind starting equations are
invoked, and no approximations that could be made responsible for the striking
conclusions are used. It shows how the physics beyond the Second law is still
little understood.


  This is a short manuscript which was initially submitted to Nature Physics as
a comment to the PBR (Pusey, M. F., Barrett, J., Rudolph, T) paper just after
its publication in 2012. The comment was not accepted. I however think that the
argumentation is correct: one is free to judge!


  The attosecond ultrafast ionization dynamics of correlated two- or
many-electron systems have, so far, been mainly addressed investigating atomic
systems. In the case of single ionization, it is well known that
electron-electron correlation modifies the ionization dynamics and observables
beyond the single active electron picture, resulting in effects such as the
Auger effect or shake-up/down and knock-up/down processes. Here, we extend
these works by investigating the attosecond ionization of a molecular system
involving correlated two-electron dynamics, as well as non-adiabatic nuclear
dynamics. Employing a charge-transfer molecular model system with two
differently bound electrons, a strongly and a weakly bound electron, we
distinguish different pathways leading to ionization, be it direct ionization
or ionization involving elastic and inelastic electron scattering processes. We
find that different pathways result in a difference in the electronic
population of the parent molecular ion, which, in turn, involves different
subsequent (non-adiabatic) postionization dynamics on different time scales.


  We construct N=8 supersymmetric mechanics with four bosonic end eight
fermionic physical degrees of freedom. Starting from the most general N=4
superspace action in harmonic superspace for the ({\bf 4,8,4}) supermultiplet
we find conditions which make it N=8 invariant. We introduce in the action
Fayet-Iliopoulos terms which give rise to potential terms. We present the
action in components and give explicit expressions for the Hamiltonian and
Poisson brackets. Finally we discuss the possibility of N=9 supersymmetric
mechanics.


  We consider a variant of the contextual bandit problem. In standard
contextual bandits, when a user arrives we get the user's complete feature
vector and then assign a treatment (arm) to that user. In a number of
applications (like healthcare), collecting features from users can be costly.
To address this issue, we propose algorithms that avoid needless feature
collection while maintaining strong regret guarantees.


  Cell detection is an essential task in cell image analysis. Recent deep
learning-based detection methods have achieved very promising results. In
general, these methods require exhaustively annotating the cells in an entire
image. If some of the cells are not annotated (imperfect annotation), the
detection performance significantly degrades due to noisy labels. This often
occurs in real collaborations with biologists and even in public data-sets. Our
proposed method takes a pseudo labeling approach for cell detection from
imperfect annotated data. A detection convolutional neural network (CNN)
trained using such missing labeled data often produces over-detection. We treat
partially labeled cells as positive samples and the detected positions except
for the labeled cell as unlabeled samples. Then we select reliable pseudo
labels from unlabeled data using recent machine learning techniques;
positive-and-unlabeled (PU) learning and P-classification. Experiments using
microscopy images for five different conditions demonstrate the effectiveness
of the proposed method.


  In their Letter[Phys. Rev. Lett. 126, 106803 (2021)], the authors found an
interesting reentrant localization phenomenon in a one-dimensional dimerized
lattice with quasiperiodic disorder, i.e., the system undergoes a second
localization transition at a higher disorder strength. They claimed that this
reentrant feature would appear in the case of staggered disorder, but not for
the uniform ones. In this Comment, we show that such reentrant feature can also
appear for the uniform disorder when larger system parameters are taken into
account.


  Recurrent Neural Networks (RNNs) have been widely used in natural language
processing and computer vision. Among them, the Hierarchical Multi-scale RNN
(HM-RNN), a kind of multi-scale hierarchical RNN proposed recently, can learn
the hierarchical temporal structure from data automatically. In this paper, we
extend the work to solve the computer vision task of action recognition.
However, in sequence-to-sequence models like RNN, it is normally very hard to
discover the relationships between inputs and outputs given static inputs. As a
solution, attention mechanism could be applied to extract the relevant
information from input thus facilitating the modeling of input-output
relationships. Based on these considerations, we propose a novel attention
network, namely Hierarchical Multi-scale Attention Network (HM-AN), by
combining the HM-RNN and the attention mechanism and apply it to action
recognition. A newly proposed gradient estimation method for stochastic
neurons, namely Gumbel-softmax, is exploited to implement the temporal boundary
detectors and the stochastic hard attention mechanism. To amealiate the
negative effect of sensitive temperature of the Gumbel-softmax, an adaptive
temperature training method is applied to better the system performance. The
experimental results demonstrate the improved effect of HM-AN over LSTM with
attention on the vision task. Through visualization of what have been learnt by
the networks, it can be observed that both the attention regions of images and
the hierarchical temporal structure can be captured by HM-AN.


  The theory of complex networks and of disordered systems is used to study the
stability and dynamical properties of a simple model of material flow networks
defined on random graphs. In particular we address instabilities that are
characteristic of flow networks in economic, ecological and biological systems.
Based on results from random matrix theory, we work out the phase diagram of
such systems defined on extensively connected random graphs, and study in
detail how the choice of control policies and the network structure affects
stability. We also present results for more complex topologies of the
underlying graph, focussing on finitely connected Erd\"os-R\'eyni graphs,
Small-World Networks and Barab\'asi-Albert scale-free networks. Results
indicate that variability of input-output matrix elements, and random
structures of the underlying graph tend to make the system less stable, while
fast price dynamics or strong responsiveness to stock accumulation promote
stability.


  Holistic understanding of multiphase reactive flow mechanisms such as CO$_2$
dissolution, multiphase displacement, and snap-off events are vital for
optimisation of large-scale industrial operations like CO$_2$ sequestration,
enhanced oil recovery, and geothermal energy. Recent advances in
three-dimensional (3D) printing allow for cheap and fast manufacturing of
complex porosity models, which enable investigation of specific flow processes
in a repeatable manner as well as sensitivity analysis for small geometry
alterations. However, there are concerns regarding dimensional fidelity, shape
conformity and surface quality, and therefore the printing quality and printer
limitations must be benchmarked. We present an experimental investigation into
the ability of 3D printing to generate custom-designed micromodels accurately
and repeatably down to a minimum pore throat size of 140 micrometers, which is
representative of the average pore-throat size in coarse sandstones.
Homogeneous and heterogeneous micromodel geometries are designed, then the 3D
printing process is optimised to achieve repeatable experiments with
single-phase fluid flow. Finally, Particle Image Velocimetry is used to compare
the velocity map obtained from flow experiments in 3D printed micromodels with
the map generated with direct numerical simulation (OpenFOAM software) and an
accurate match is obtained. This work indicates that 3D printed micromodels can
be used to accurately investigate pore-scale processes present in CO$_2$
sequestration, enhanced oil recovery and geothermal energy applications more
cheapely than traditional micromodel methods.


  We study the supersymmetric model with $D_4 \times Z_2$ lepton flavor
symmetry. We evaluate soft supersymmetry breaking terms, i.e. soft slepton
masses and A-terms, which are predicted in the $D_4$ flavor model. We consider
constraints due to experiments of flavor changing neutral current processes.


  Long-term pain conditions after surgery and patients' responses to pain
relief medications are not yet fully understood. While recent studies developed
an index for nociception level of patients under general anesthesia, based on
multiple physiological parameters, it remains unclear whether and how dynamics
of these parameters indicate long-term post-operative pain (POP). To extract
unbiased and interpretable descriptions of how physiological parameters
dynamics change over time and across patients in response to surgical
procedures, we employed a multivariate-temporal analysis. We demonstrate the
main features of intra-operative physiological responses can be used to predict
long-term POP. We propose to use a complex higher-order SVD method to
accurately decompose the patients' physiological responses into multivariate
structures evolving in time. We used intra-operative vital signs of 175
patients from a mixed surgical cohort to extract three interconnected,
low-dimensional complex-valued descriptions of patients' physiological
responses: multivariate factors, reflecting sub-physiological parameters;
temporal factors reflecting common intra-surgery temporal dynamics; and
patients factors, describing patient to patient changes in physiological
responses. Adoption of complex-HOSVD allowed us to clarify the dynamic
correlation structure included in intra-operative physiological responses.
Instantaneous phases of the complex-valued physiological responses within the
subspace of principal descriptors enabled us to discriminate between mild
versus severe levels of long-term POP. By abstracting patients into different
surgical groups, we identified significant surgery-related principal
descriptors: each of them potentially encodes different surgical stimulation.
The dynamics of patients' physiological responses to these surgical events are
linked to long-term post-operative pain development.


  The Green-Schwarz anomaly-cancelling mechanism in string theories requires a
Chern-Simons term in the Einstein-Hilbert action, which leads to an amplitude
birefringence of spacetime for the propagation of gravitational waves. While
the degree of birefringence may be intrinsically small, its effects on a
gravitational wave will accumulate as the wave propagates. The proposed Laser
Interferometer Space Antenna (LISA) will be sensitive enough to observe the
gravitational waves from sources at cosmological distances great enough that
interesting bounds on the Chern-Simons may be found. Here we evaluate the
effect of a Chern-Simons induced spacetime birefringence to the propagation of
gravitational waves from such systems. We find that gravitational waves from in
coalescing binary black hole system are imprinted with a signature of
Chern-Simons gravity. This signature appears as a time-dependent change in the
apparent orientation of the binary's orbital angular momentum with respect to
the observer line-of-sight, with the change magnitude reflecting the integrated
history of the Chern-Simons coupling over the worldline of a radiation
wavefront. While spin-orbit coupling in the binary system will also lead to an
evolution of the system's orbital angular momentum, the time dependence and
other details of this \emph{real} effect are different than the \emph{apparent}
effect produced by Chern-Simons birefringence, allowing the two effects to be
separately identified.


  Using ideas from Guth-Maldague-Wang and working over $\mathbb{Q}_p$, we show
that the discrete restriction constant for the parabola is
$O_{\varepsilon}((\log M)^{2 + \varepsilon})$.


  For dealing with the equal sphere packing problem, we propose a serial
symmetrical relocation algorithm, which is effective in terms of the quality of
the numerical results. We have densely packed up to 200 equal spheres in
spherical container and up to 150 equal spheres in cube container. All results
are rigorous because of a fake sphere trick. It was conjectured impossible to
pack 68 equal spheres of radius 1 into a sphere of radius 5. The serial
symmetrical relocation algorithm has proven wrong this conjecture by finding
one such packing.


  The optimized structure and electronic properties of neutral and singly
charged magnesium clusters have been investigated using ab initio theoretical
methods based on density-functional theory and systematic post-Hartree-Fock
many-body perturbation theory accounting for all electrons in the system. We
have systematically calculated the optimized geometries of neutral and singly
charged magnesium clusters consisting of up to 21 atoms, electronic shell
closures, binding energies per atom, ionization potentials and the gap between
the highest occupied and the lowest unoccupied molecular orbitals. We have
investigated the transition to the hcp structure and metallic evolution of the
magnesium clusters, as well as the stability of linear chains and rings of
magnesium atoms. The results obtained are compared with the available
experimental data and the results of other theoretical works.


  States in quantum field theory (QFT) are represented by many-particle wave
functions, such that a state describing n particles depends on n spacetime
positions. Since a general state is a superposition of states with different
numbers of particles, the wave function lives in the configuration space
identified with a product of an infinite number of 4-dimensional Minkowski
spacetimes. The squared absolute value of the wave function is interpreted as
the probability density in the configuration space, from which the standard
probabilistic predictions of QFT can be recovered. Such a formulation and
probabilistic interpretation of QFT allows to interpret the wave function as a
pilot wave that describes deterministic particle trajectories, which
automatically includes a deterministic and continuous description of particle
creation and destruction. In particular, when the conditional wave function
associated with a quantum measurement ceases to depend on one of the spacetime
coordinates, then the 4-velocity of the corresponding particle vanishes,
describing a trajectory that stops at a particular point in spacetime. In a
more general situation a dependence on this spacetime coordinate is negligibly
small but not strictly zero, in which case the trajectory does not stop but the
measuring apparatus still behaves as if this particle has been destroyed.


  We combine Chandra and XMM-Newton X-ray data from our previous papers with
new X-ray observations and with Spitzer mid-infrared data in order to study the
nature of the nuclei of radio galaxies and radio-loud quasars with z<1.0 from
the 3CRR sample. The significant increase in sample size over our previous
work, the reduction of bias in the sample as a result of new observations, and
the availability of more mid-infrared data allow us to show conclusively that
almost all objects classed as low-excitation radio galaxies in optical
spectroscopic studies lack a radiatively efficient active nucleus. We show that
the distribution of absorbing columns in the narrow-line radio galaxies differs
from the population of X-ray-selected radio-quiet type-2 quasars and from that
in local Seyfert 2s. We comment on the current evidence for the nature of the
soft X-ray component in radio-galaxy nuclear spectra, concluding that a jet
origin for this component is very hard to evade. Finally, we discuss the
recently discovered `fundamental plane' of black hole activity, showing that
care must be taken when placing radio-loud AGN on such diagnostic diagrams.


  Pursuing topological phases in natural and artificial materials is one of the
central topics in modern physical science and engineering. In classical
magnetic systems, spin waves (or magnons) and magnetic solitons (such as domain
wall, vortex, skyrmion, etc) represent two important excitations. Recently, the
topological insulator and semimetal states in magnon- and soliton-based
crystals (or metamaterials) have attracted growing attention owing to their
interesting dynamics and promising applications for designing robust spintronic
devices. Here, we give an overview of current progress of topological phases in
structured classical magnetism. We first provide a brief introduction to spin
wave, and discuss its topological properties including magnon Hall effects,
topological magnon insulators, and Dirac (Weyl) magnon semimetals. Appealing
proposal of topological magnonic devices is also highlighted. We then review
the collective-coordinate approach for describing the dynamics of magnetic
soliton lattice. Pedagogical topological models such as the
Su-Schrieffer-Heeger model and the Haldane model and their manifestation in
magnetic soliton crystals are elaborated. Then we focus on the topological
properties of magnetic solitons, by theoretically analyzing the first-order
topological insulating phases in low dimensional systems and higher-order
topological states in breathing crystals. Finally, we discuss the experimental
realization and detection of the edge states in both the magnonic and solitonic
crystals. We remark the challenges and future prospects before concluding this
article.


  Recently Chern insulators with Chern number $C=1$ and $C=2$ in zero (or very
small) magnetic field have been observed in two moire graphene systems: twisted
bilayer graphene and ABC trilayer graphene, both aligned with a hexagonal
Boron-Nitride (h-BN) substrate. These Chern insulator states arise due to many
body effects in the Chern bands of these systems when they are partially filled
to a total integer filling $\nu_T = 1,3$ (including spin and valley degrees of
freedom). A simple possible explanation is from Hartree-Fock mean field theory
which predicts valley and spin polarization in the zero bandwidth limit,
similar to the "quantum Hall ferromagnetism" in Landau levels. Though valley
polarization is implied by the existing experiments, the fate of the spin
degree of freedom is not presently clear. In this paper we propose alternative
valley polarized - but not spin polarized - candidates for the observed QAH
effect. For a valley polarized spinful Chern band at filling $\nu_T=1$, we
describe a class of exotic Chern insulator phases through spin-charge
separation: charge is in a conventional Chern insulator phase with quantized
Hall conductivity, while the spin forms disordered spin liquid phase with
fractionalization, which we dub quantum Hall spin liquids. We construct a
simple class of $Z_2$ quantum Hall spin liquid as analogs of the familiar $Z_2$
spin liquid through slave fermion-schwinger boson parton theory. Condensation
of the spinon from the $Z_2$ quantum Hall spin liquid can lead to a quantum
Hall antiferromagnet which is yet another, less exotic, candidate for the
experimentally observed Chern insulator. We offer several experimental
proposals to probe the quantum Hall spin liquid and the quantum Hall
anti-ferromagnetic phases.


  The electric polarizability of mesons, in particular, that of the charged
pion, is studied in the framework of a semirelativistic description of hadrons
as bound states of valence quarks in terms of a Hamiltonian composed of the
relativistic kinetic energy as well as a phenomenological potential describing
the strong interactions between the quarks. The quark-core contribution to the
electric polarizability obtainable in quark models of this kind turns out to be
in the semirelativistic approaches even smaller than in the nonrelativistic
limit.


  For decades the primary experimental goal in studies of hadronic parity
nonconservation (PNC) has been the isolation of the isovector weak
nucleon-nucleon interaction, expected to be dominated by long-range pion
exchange and enhanced by the neutral current. In meson-exchange descriptions
this interaction together with an isoscalar interaction generated by rho and
omega exchange dominate most observables. Consequently these two amplitudes
have been used to compare and check the consistency of the field's experiments.
Yet to date, despite sensitive searches like that performed with 18F, no
evidence for isovector hadronic PNC has been found. Here we argue, based on
recent large-Nc treatments and new global analyses, that the emphasis on
isovector hadronic PNC was misplaced. Large-Nc provides an alternative and
theoretically better motivated simplification of effective field theories
(EFTs) of hadronic PNC, separating the five low-energy constants (LECs) into
two of leading order (LO), and three others that are NNLO. This scheme pivots
the isospin coordinates we have traditionally used, placing one dominant axis
in the isoscalar plane, and a second along the isotensor direction. We show
that this large-Nc LEC hierarchy accurately describes all existing data on
hadronic PNC, and we discuss opportunities to further test the predicted
large-Nc hierarchy of LECs, illustrating the kind of analyses experimentalists
can use to better constrain the LO theory and to determine the size of NNLO
corrections.


  Intelligent transportation systems (ITS) are expected to effectively create a
stand-alone network for secure communication among autonomous agents. In such a
dynamic and fast-changing network with high-speed agents, verifying the
authenticity and integrity of messages while taking preventive action (e.g.,
applying brakes) within tens of milliseconds is one of the main challenges. In
such a brief moment after receiving a message, the agent not only must verify
the integrity and authenticity of the received message but also needs to
perform extra computations to localize the sender of the message for taking
appropriate action (e.g., an immediate stop warning from a vehicle in front vs.
rear). In this paper, we present an inherently location-aware and lightweight
authentication protocol by exploiting in situ visual localization (i.e., SLAM).
In this protocol, each agent displays its public key using visual
authentication beacons (e.g., QR codes). Thus, receiving agents not only can
verify and authenticate the messages but also can easily localize the sender by
keeping a shortlist of observed visual beacons within their visual localization
system with no additional computation cost. Compared to prior work, our
location-aware protocol is scalable, does not depend on any infrastructure,
removes the high cost of post-message-delivery localization, and provides
trustworthiness guarantees for information that are beyond the reach of each
agent sensors.


  We present a construction explaining the existence of (unexpected) curves of
degree $d+k$, passing through a set $Z$ of points on $\mathbb{P}^2$, and having
a generic point $P$ of multiplicity $d$. The construction is based on the
syzygies of the $k$-th powers of Jacobian of the product of lines dual to the
points of $Z$. We prove also a result characterizing the unexpectedness of the
curves via splitting type of the bundle of these syzygies retricted to the line
dual to $P$.


  Deep Neural Networks (DNNs) are known to be vulnerable to adversarial
attacks. Currently, there is no clear insight into how slight perturbations
cause such a large difference in classification results and how we can design a
more robust model architecture. In this work, we propose a novel
interpretability method, InterpretGAN, to generate explanations for features
used for classification in latent variables. Interpreting the classification
process of adversarial examples exposes how adversarial perturbations influence
features layer by layer as well as which features are modified by
perturbations. Moreover, we design the first diagnostic method to quantify the
vulnerability contributed by each layer, which can be used to identify
vulnerable parts of model architectures. The diagnostic results show that the
layers introducing more information loss tend to be more vulnerable than other
layers. Based on the findings, our evaluation results on MNIST and CIFAR10
datasets suggest that average pooling layers, with lower information loss, are
more robust than max pooling layers for the network architectures studied in
this paper.


  In this paper, we explore a forward-thinking question: Is GPT-4V effective at
low-level data analysis tasks on charts? To this end, we first curate a
large-scale dataset, named ChartInsights, consisting of 89,388 quartets (chart,
task, question, answer) and covering 10 widely-used low-level data analysis
tasks on 7 chart types. Firstly, we conduct systematic evaluations to
understand the capabilities and limitations of 18 advanced MLLMs, which include
12 open-source models and 6 closed-source models. Starting with a standard
textual prompt approach, the average accuracy rate across the 18 MLLMs is
36.17%. Among all the models, GPT-4V achieves the highest accuracy, reaching
56.13%. To understand the limitations of multimodal large models in low-level
data analysis tasks, we have designed various experiments to conduct an
in-depth test of capabilities of GPT-4V. We further investigate how visual
modifications to charts, such as altering visual elements (e.g. changing color
schemes) and introducing perturbations (e.g. adding image noise), affect
performance of GPT-4V. Secondly, we present 12 experimental findings. These
findings suggest potential of GPT-4V to revolutionize interaction with charts
and uncover the gap between human analytic needs and capabilities of GPT-4V.
Thirdly, we propose a novel textual prompt strategy, named Chain-of-Charts,
tailored for low-level analysis tasks, which boosts model performance by
24.36%, resulting in an accuracy of 80.49%. Furthermore, by incorporating a
visual prompt strategy that directs attention of GPT-4V to question-relevant
visual elements, we further improve accuracy to 83.83%. Our study not only
sheds light on the capabilities and limitations of GPT-4V in low-level data
analysis tasks but also offers valuable insights for future research.


  Computationally expensive training strategies make self-supervised learning
(SSL) impractical for resource constrained industrial settings. Techniques like
knowledge distillation (KD), dynamic computation (DC), and pruning are often
used to obtain a lightweightmodel, which usually involves multiple epochs of
fine-tuning (or distilling steps) of a large pre-trained model, making it more
computationally challenging. In this work we present a novel perspective on the
interplay between SSL and DC paradigms. In particular, we show that it is
feasible to simultaneously learn a dense and gated sub-network from scratch in
a SSL setting without any additional fine-tuning or pruning steps. The
co-evolution during pre-training of both dense and gated encoder offers a good
accuracy-efficiency trade-off and therefore yields a generic and multi-purpose
architecture for application specific industrial settings. Extensive
experiments on several image classification benchmarks including CIFAR-10/100,
STL-10 and ImageNet-100, demonstrate that the proposed training strategy
provides a dense and corresponding gated sub-network that achieves on-par
performance compared with the vanilla self-supervised setting, but at a
significant reduction in computation in terms of FLOPs, under a range of target
budgets (td ).


  This study aims to identify the leading of inflation indicators of monetary
policy in DRC. The results reveal that the most relevant inflation indicators
usually come from the monetary origin than the real sector. Variance
decomposition analyzes place in the foreground the rate of exchange, the money
supply and the public consumption like the most relevant indicators. In order
to achieve its goal of price stability and to support a strong economic growth,
the intermediate objective of the Central Bank baseded on the controle of the
money supply seems to be less relevant. Relates to a high level of the
dollarization, the central bank will be able to adopt either the strategy of
nominal anchoring of the rate of exchange, this calls the return of the fixed
exchange regime or to adopt a strategy of inflation targeting is to restore the
credibility of the monetary policy


  The characteristic functional is the infinite-dimensional generalization of
the Fourier transform for measures on function spaces. It characterizes the
statistical law of the associated stochastic process in the same way as a
characteristic function specifies the probability distribution of its
corresponding random variable. Our goal in this work is to lay the foundations
of the innovation model, a (possibly) non-Gaussian probabilistic model for
sparse signals. This is achieved by using the characteristic functional to
specify sparse stochastic processes that are defined as linear transformations
of general continuous-domain white noises (also called innovation processes).
We prove the existence of a broad class of sparse processes by using the
Minlos-Bochner theorem. This requires a careful study of the regularity
properties, especially the boundedness in Lp-spaces, of the characteristic
functional of the innovations. We are especially interested in the functionals
that are only defined for p<1 since they appear to be associated with the
sparser kind of processes. Finally, we apply our main theorem of existence to
two specific subclasses of processes with specific invariance properties.


  In this paper the lightface $\Pi^{1}_{1}$-Comprehension axiom is shown to be
proof-theoretically strong even over $\mbox{RCA}_{0}^{*}$, and we calibrate the
proof-theoretic ordinals of weak fragments of the theory $\mbox{ID}_{1}$ of
positive inductive definitions over natural numbers. Conjunctions of negative
and positive formulas in the transfinite induction axiom of $\mbox{ID}_{1}$ are
shown to be weak, and disjunctions are strong. Thus we draw a boundary line
between predicatively reducible and impredicative fragments of $\mbox{ID}_{1}$.


  There are experimental evidences for the existence of narrow states
$\Theta^+$ and $\Theta_c$ with the same quantum numbers of $uudd\bar s$ and
$uudd\bar c$ pentaquarks and also $NK^{(*)}$ and $ND^{(*)}$ molecular states.
Their masses deviate from many theoretical estimates of the pure pentaquark and
molecular states. In this work we study the possibility that the observed
$\Theta^+$ and $\Theta_c$ are mixtures of pure pentaquark and molecular states.
The mixing parameters are in general related to non-perturbative QCD which are
not calculable at present. We determine them by fitting data from known states
and then generalize the mechanism to $\Theta_b$ to predict its mass and width.
The mixing mechanism can also naturally explain the narrow width for $\Theta^+$
and $\Theta_c$ through destructive interferences, even if the pure pentaquark
and molecular states have much larger decay widths. We also briefly discuss the
properties of the partner eigenstates of $\Theta^+$ and $\Theta_c$ and the
possibility of experimentally observe them. Moreover, probable consequences of
multi-state mixing are also addressed.


  Legal judgment prediction (LJP) applies Natural Language Processing (NLP)
techniques to predict judgment results based on fact descriptions
automatically. Recently, large-scale public datasets and advances in NLP
research have led to increasing interest in LJP. Despite a clear gap between
machine and human performance, impressive results have been achieved in various
benchmark datasets. In this paper, to address the current lack of comprehensive
survey of existing LJP tasks, datasets, models and evaluations, (1) we analyze
31 LJP datasets in 6 languages, present their construction process and define a
classification method of LJP with 3 different attributes; (2) we summarize 14
evaluation metrics under four categories for different outputs of LJP tasks;
(3) we review 12 legal-domain pretrained models in 3 languages and highlight 3
major research directions for LJP; (4) we show the state-of-art results for 8
representative datasets from different court cases and discuss the open
challenges. This paper can provide up-to-date and comprehensive reviews to help
readers understand the status of LJP. We hope to facilitate both NLP
researchers and legal professionals for further joint efforts in this problem.


  In this paper we investigate the phase structure of a (1+1)-dimensional
schematic quark model with four-quark interaction and in the presence of baryon
($\mu_B$), isospin ($\mu_I$) and chiral isospin ($\mu_{I5}$) chemical
potentials. It is established that in the large-$N_c$ limit ($N_c$ is the
number of colored quarks) there exists a duality correspondence between the
chiral symmetry breaking phase and the charged pion condensation (PC) one. The
role and influence of this property on the phase structure of the model are
studied. Moreover, it is shown that the chemical potential $\mu_{I5}$ promotes
the appearance of the charged PC phase with nonzero baryon density.


  Recently the discovery of room-temperature superconductivity was announced
for a carbonaceous sulfur hydride (CSH) under high pressure. The evidence for
superconductivity was based on resistance and magnetic susceptibility
measurements. In the figures showing the susceptibility it was stated that "the
background signal, determined from a non-superconducting CSH sample at 108~GPa,
has been subtracted from the data". From a thorough data analysis we show that
the data are incompatible with the notion that the susceptibility data are
obtained from the "measured voltage" using a background correction. On the
other hand the data {\it are} compatible with the reverse procedure, namely the
"measured voltage" is obtained by adding a "background signal" containing noise
to what was reported as the background-corrected susceptibility. For all 6 of
the reported pressures our analysis leads to the conclusion that: (i) the
reported background-corrected susceptibility data are pathological, (ii) they
were not obtained by the method described in this paper nor by any one of the
alternative 3 methods that were subsequently provided by the authors and (iii)
the "measured voltage" data are not raw data.


  A generalized screened potential model (GSPM), recently developed to study
the bottomonium spectrum, is applied to the calculation of charmonium masses
and electromagnetic widths. The presence in the GSPM of more quark-antiquark
bound states than in conventional non screened potential models, allows for the
assignment of GSPM states to cataloged non conventional $J^{++}$ charmonium
resonances as well as for the prediction of new (non cataloged) $J^{++}$
states. The results obtained seem to indicate that a reasonable overall
description of $J^{++}$ charmonium resonances is feasible.


  Out-of-distribution (OOD) detection aims to identify test examples that do
not belong to the training distribution and are thus unlikely to be predicted
reliably. Despite a plethora of existing works, most of them focused only on
the scenario where OOD examples come from semantic shift (e.g., unseen
categories), ignoring other possible causes (e.g., covariate shift). In this
paper, we present a novel, unifying framework to study OOD detection in a
broader scope. Instead of detecting OOD examples from a particular cause, we
propose to detect examples that a deployed machine learning model (e.g., an
image classifier) is unable to predict correctly. That is, whether a test
example should be detected and rejected or not is ``model-specific''. We show
that this framework unifies the detection of OOD examples caused by semantic
shift and covariate shift, and closely addresses the concern of applying a
machine learning model to uncontrolled environments. We provide an extensive
analysis that involves a variety of models (e.g., different architectures and
training strategies), sources of OOD examples, and OOD detection approaches,
and reveal several insights into improving and understanding OOD detection in
uncontrolled environments.


  We construct a fully covariant theory of massive gravity which does not
require the introduction of an external reference metric, and overcomes the
usual problems of massive gravity theories (fatal ghosts instabilities,
acausality and/or vDVZ discontinuity). The equations of motion of the theory
are non-local, but respect causality. The starting point is the quadratic
action proposed in the context of the degravitation idea. We show that it is
possible to extended it to a fully non-linear covariant theory. This theory
describes the five degrees of freedom of a massive graviton plus a scalar
ghost. However, contrary to generic non-linear extensions of Fierz-Pauli
massive gravity, the ghost has the same mass m as the massive graviton,
independently of the background, and smoothly goes into a non-radiative degree
of freedom for m-> 0. As a consequence, for $m\sim H_0$ the vacuum instability
induced by the ghost is irrelevant even over cosmological time-scales. We
finally show that an extension of the model degravitates a vacuum energy
density of order $M_{Planck}^4$ down to a value of order $M_{Planck}^2 m^2$,
which for $m \sim H_0$ is of order of the observed value of the vacuum energy
density.


  We present simultaneous dual-frequency radio observations of Cygnus X-3
during a phase of low-level activity. We constrain the minimum variability
timescale to be 20 minutes at 43 GHz and 30 minutes at 15 GHz, implying source
sizes of 2 to 4 AU. We detect polarized emission at a level of a few per cent
at 43 GHz which varies with the total intensity. The delay of approximately 10
minutes between the peaks of the flares at the two frequencies is seen to
decrease with time, and we find that synchrotron self-absorption and free-free
absorption by entrained thermal material play a larger role in determining the
opacity than absorption in the stellar wind of the companion. A shock-in-jet
model gives a good fit to the lightcurves at all frequencies, demonstrating
that this mechanism, which has previously been used to explain the brighter,
longer-lived giant outbursts in this source, is also applicable to these
low-level flaring events. Assembling the data from outbursts spanning over two
orders of magnitude in flux density shows evidence for a strong correlation
between the peak brightness of an event, and the timescale and frequency at
which this is attained. Brighter flares evolve on longer timescales and peak at
lower frequencies. Analysis of the fitted model parameters suggests that
brighter outbursts are due to shocks forming further downstream in the jet,
with an increased electron normalisation and magnetic field strength both
playing a role in setting the strength of the outburst.


  Accretion onto SMBH is believed to occur mostly in obscured AGN. Such objects
are proving rather elusive in surveys of distant galaxies, including those at
X-ray energies. Our main goal is to determine whether the revised IRAC criteria
of Donley et al. (2012) (objects with an IR power-law spectral shape), are
effective at selecting X-ray type-2 AGN. We present the results from the X-ray
spectral analysis of 147 AGN selected by cross-correlating the highest spectral
quality ultra-deep XMM-Newton and the Spitzer/IRAC catalogues in the CDF-S.
Consequently it is biased towards sources with high S/N X-ray spectra. In order
to measure the amount of intrinsic absorption in these sources, we adopt a
simple X-ray spectral model that includes a power-law modified by intrinsic
absorption and a possible soft X-ray component. We find 21/147 sources to be
heavily absorbed but the uncertainties in their obscuring column densities do
not allow us to confirm their Compton-Thick nature without resorting to
additional criteria. Although IR power-law galaxies are less numerous in our
sample than IR non-power-law galaxies (60 versus 87 respectively), we find that
the fraction of absorbed (N_{H} > 10^{22} cm^{-2}) AGN is significantly higher
(at about 3 sigma level) for IR-power-law sources ($\sim$2/3) than for those
sources that do not meet this IR selection criteria ($\sim$1/2). This behaviour
is particularly notable at low luminosities, but it appears to be present,
although with a marginal significance, at all luminosities. We therefore
conclude that the IR power-law method is efficient in finding X-ray-absorbed
sources. We would then expect that the long-sought dominant population of
absorbed AGN is abundant among IR power-law spectral shape sources not detected
in X-rays.


  The Galaxy Evolution Explorer (GALEX) has performed the first surveys of the
sky in the Ultraviolet (UV). Its legacy is an unprecedented database with more
than 200 million source measurements in far-UV (FUV) and near-UV (NUV), as well
as wide-field imaging of extended objects, filling an important gap in our view
of the sky across the electromagnetic spectrum. The UV surveys offer unique
sensitivity for identifying and studying selected classes of astrophysical
objects, both stellar and extra-galactic. We examine the overall content and
distribution of UV sources over the sky, and with magnitude and color. For this
purpose, we have constructed final catalogs of UV sources with homogeneous
quality, eliminating duplicate measurements of the same source. Such catalogs
can facilitate a variety of investigations on UV-selected samples, as well as
planning of observations with future missions.
  We describe the criteria used to build the catalogs, their coverage and
completeness. We included observations in which both the far-UV and near-UV
detectors were exposed; 28,707 fields from the All-Sky Imaging survey (AIS)
cover a unique area of 22,080 square degrees (after we restrict the catalogs to
the central 1-degree diameter of the field), with a typical depth of about
20/21 mag (FUV/NUV, in the AB mag system), and 3,008 fields from the
Medium-depth Imaging Survey (MIS) cover a total of 2,251 square degrees at a
depth of about 22.7mag. The catalogs contain about 71 and 16.6 million sources
respectively. The density of hot stars reflects the Galactic structure, and the
number counts of both Galactic and extra-galactic sources are modulated by the
Milky Way dust extinction, to which the UV data are very sensitive.


  A relativistic constituent quark model is found to reproduce the recent data
regarding the ratio of proton form factors, $F_2(Q^2)/F_1(Q^2)$. We show that
imposing Poincare invariance leads to substantial violation of the helicity
conservation rule, as well as an analytic result that the ratio
$F_2(Q^2)/F_1(Q^2)\sim 1/Q$ for intermediate values of $Q^2$.


  The method of biomass estimation based on a volume-to-biomass relationship
has been applied in estimating forest biomass conventionally through the mean
volume (m3 ha-1). However, few studies have been reported concerning the
verification of the volume-biomass equations regressed using field data. The
possible bias may result from the volume measurements and extrapolations from
sample plots to stands or a unit area. This paper addresses (i) how to verify
the volume-biomass equations, and (ii) how to reduce the bias while building
these equations. This paper presents an applicable method for verifying the
field data using reasonable wood densities, restricting the error in field data
processing based on limited field plots, and achieving a better understanding
of the uncertainty in building those equations. The verified and improved
volume-biomass equations are more reliable and will help to estimate forest
carbon sequestration and carbon balance at any large scale.


  Approximate symmetries of geodesic equations on 2-spheres are studied. These
are the symmetries of the perturbed geodesic equations which represent
approximate path of a particle rather than exact path. After giving the exact
symmetries of the geodesic equations, two different approaches to study the
approximate symmetries of the approximate geodesic equations show that no
non-trivial approximate symmetry for these spaces exists.


  It was recently shown that when a drop of Glenlivet whiskey evaporates, it
leaves behind a uniform deposit [PRL 116, 124501 (2016)]. We utilize this
fascinating finding in the fabrication of electrochemical metallization memory
(ECM) cells. The top (Ag) and bottom (Co) electrodes in our structure are
separated by a layer of Glenlivet whiskey deposit (an insulator). Measurements
show the device response is typical of ECM cells that involve threshold-type
switching, pinched hysteresis loops, and a large difference between the high-
and low-resistance states. The surface coating process used in our experiments
simplifies the device fabrication and results in a biodegradable insulating
layer, which may facilitate the recovery of recyclable materials at the end of
the device's use.


  We analyze a 3D hydrodynamic simulation of common envelope evolution to
understand how energy is transferred between various forms and whether theory
and simulation are mutually consistent given the setup. Virtually all of the
envelope unbinding in the simulation occurs before the end of the rapid
plunge-in phase, here defined to coincide with the first periastron passage. In
contrast, the total envelope energy is nearly constant during this time because
positive energy transferred to the gas from the core particles is
counterbalanced by the negative binding energy from the closer proximity of the
inner layers to the plunged-in secondary. During the subsequent slow spiral-in
phase, energy continues to transfer to the envelope from the red giant core and
secondary core particles. We also propose that relative motion between the
centre of mass of the envelope and the centre of mass of the particles could
account for the offsets of planetary nebula central stars from the nebula's
geometric centre.


  Statistical uncertainties complicate engineering design -- confounding
regulated design approaches, and degrading the performance of reliability
efforts. The simplest means to tackle this uncertainty is double loop
simulation; a nested Monte Carlo method that, for practical problems, is
intractable. In this work, we introduce a flexible, general approximation
technique that obviates the double loop. This approximation is constructed in
the context of a novel theory of reliability design under statistical
uncertainty: We introduce metrics for measuring the efficacy of RBDO strategies
(effective margin and effective reliability), minimal conditions for
controlling uncertain reliability (precision margin), and stricter conditions
that guarantee the desired reliability at a designed confidence level. We
provide a number of examples with open-source code to demonstrate our
approaches in a reproducible fashion.


  Context. Most observational studies so far point towards brown dwarfs sharing
a similar formation mechanism as the one accepted for low mass stars. However,
larger databases and more systematic studies are needed before strong
conclusions can be reached. Aims. In this second paper of a series devoted to
the study of the spectroscopic properties of the members of the Lambda Orionis
Star Forming Region, we study accretion, activity and rotation for a wide set
of spectroscopically confirmed members of the central star cluster Collinder 69
to draw analogies and/or differences between the brown dwarf and stellar
populations of this cluster. Moreover, we present comparisons with other star
forming regions of similar and different ages to address environmental effects
on our conclusions. Methods. We study prominent photospheric lines to derive
rotational velocities and emission lines to distinguish between accretion
processes and chromospheric activity. In addition, we include information about
disk presence and X-ray emission. Results. We report very large differences in
the disk fractions of low mass stars and brown dwarfs (~58%) when compared to
higher mass stars (26+4-3%) with 0.6 Msun being the critical mass we find for
this dichotomy. As a byproduct, we address the implications of the spatial
distribution of disk and diskless members in the formation scenario of the
cluster itself. We have used the Halpha emission to discriminate among
accreting and non-accreting sources finding that 38+8-7% of sources harboring
disks undergo active accretion and that his percentage stays similar in the
substellar regime. For those sources we have estimated accretion rates.
Finally, regarding rotational velocities, we find a high dispersion in vsin(i)
which is even larger among the diskless population.


  For an odd prime $p$ satisfying Vandiver's conjecture, we give explicit
formulae for the action of the absolute Galois group $G_{\mathbb{Q}(\zeta_p)}$
on the homology of the degree $p$ Fermat curve, building on work of Anderson.
Further, we study the invariants and the first Galois cohomology group which
are associated with obstructions to rational points on the Fermat curve.


  We report results of both Diffusion Quantum Monte Carlo(DMC) method and
Reptation Quantum Monte Carlo(RMC) method on the potential energy curve of the
helium dimer. We show that it is possible to obtain a highly accurate
description of the helium dimer. An improved stochastic reconfiguration
technique is employed to optimize the many-body wave function, which is the
starting point for highly accurate simulations based on the Diffusion Quantum
Monte Carlo(DMC) and Reptation Quantum Monte Carlo (RMC) methods. We find that
the results of these methods are in excellent agreement with the best
theoretical results at short range, especially recently developed Reptation
Quantum Monte Carlo(RMC) method, yield practically accurate results with
reduced statistical error, which gives very excellent agreement across the
whole potential. For the equilibrium internuclear distance of 5.6 bohr, the
calculated electronic energy with Reptation Quantum Monte Carlo(RMC) method is
5.807483599$\pm$0.000000015 hartrees and the corresponding well depth is
-11.003$\pm$0.005 K.


  Decoherence originates from the leakage of quantum information into external
degrees of freedom. For a qubit the two main decoherence channels are
relaxation and dephasing. Here, we report an experiment on a superconducting
qubit where we retrieve part of the lost information in both of these channels.
We demonstrate that raw averaging the corresponding measurement records
provides a full quantum tomography of the qubit state where all three
components of the effective spin-1/2 are simultaneously measured. From single
realizations of the experiment, it is possible to infer the quantum
trajectories followed by the qubit state conditioned on relaxation and/or
dephasing channels. The incompatibility between these quantum measurements of
the qubit leads to observable consequences in the statistics of quantum states.
The high level of controllability of superconducting circuits enables us to
explore many regimes from the Zeno effect to underdamped Rabi oscillations
depending on the relative strengths of driving, dephasing and relaxation.


  We present a novel modular object detection convolutional neural network that
significantly improves the accuracy of object detection. The network consists
of two stages in a hierarchical structure. The first stage is a network that
detects general classes. The second stage consists of separate networks to
refine the classification and localization of each of the general classes
objects. Compared to a state of the art object detection networks the
classification error in the modular network is improved by approximately 3-5
times, from 12% to 2.5 %-4.5%. This network is easy to implement and has a 0.94
mAP. The network architecture can be a platform to improve the accuracy of
widespread state of the art object detection networks and other kinds of deep
learning networks. We show that a deep learning network initialized by transfer
learning becomes more accurate as the number of classes it later trained to
detect becomes smaller.


  Graph Neural Networks (GNNs) have achieved notable success in various
applications over graph data. However, recent research has revealed that
real-world graphs often contain noise, and GNNs are susceptible to noise in the
graph. To address this issue, several Graph Structure Learning (GSL) models
have been introduced. While GSL models are tailored to enhance robustness
against edge noise through edge reconstruction, a significant limitation
surfaces: their high reliance on node features. This inherent dependence
amplifies their susceptibility to noise within node features. Recognizing this
vulnerability, we present DEGNN, a novel GNN model designed to adeptly mitigate
noise in both edges and node features. The core idea of DEGNN is to design two
separate experts: an edge expert and a node feature expert. These experts
utilize self-supervised learning techniques to produce modified edges and node
features. Leveraging these modified representations, DEGNN subsequently
addresses downstream tasks, ensuring robustness against noise present in both
edges and node features of real-world graphs. Notably, the modification process
can be trained end-to-end, empowering DEGNN to adjust dynamically and achieves
optimal edge and node representations for specific tasks. Comprehensive
experiments demonstrate DEGNN's efficacy in managing noise, both in original
real-world graphs and in graphs with synthetic noise.


  IFOSMONDI iterative algorithm for implicit co-simulation of coupled physical
systems (introduced by the authors in july 2019 during the Simultech
conference, p.176-186) enables us to solve the nonlinear coupling function
while keeping the smoothness of interfaces without introducing a delay.
Moreover, it automatically adapts the size of the steps between data exchanges
among the systems according to the difficulty of the solving of the coupling
constraint. The latter was solved by a fixed-point algorithm in the original
implementation whereas this paper introduces the JFM version (standing for
Jacobian-Free Methods). Most implementations of Newton-like methods require a
jacobian matrix which can be difficult to compute in the co-simulation context,
except in the case where the interfaces are represented by a Zero-Order-Hold
(ZOH). As far as IFOSMONDI coupling algorithm uses Hermite interpolation for
smoothness enhancement (up to Third-Order-Hold), we propose hereafter a new
formulation of the non-linear coupling function including both the values and
the time-derivatives of the coupling variables. This formulation is well
designed for solving the coupling through jacobian-free Newton type methods.
Consequently, successive function evaluations consist in multiple simulations
of the systems on a co-simulation time step using rollback. The
orchestrator-workers structure of the algorithm enables us to combine the PETSc
framework on the orchestrator side for the non-linear Newton-type solvers with
the parallel integrations of the systems on the workers side thanks to MPI
processes. Different nonlinear methods will be compared to one another and to
the original fixed-point implementation on a newly proposed 2-systems academic
test-case (mass-spring-damper type) with direct feedthrough on both sides.


  A possible mean to stabilize the LEO debris population is to remove each year
5 heavy debris like spent satellites or launchers stages from that space
region. This paper investigates the DeltaV requirement for such a Space Debris
Collecting mission. The optimization problem is intrinsically hard since it
mixes combinatorial optimization to select the debris among a list of
candidates and functional optimization to define the orbital maneuvers. The
solving methodology proceeds in two steps : firstly a generic transfer strategy
with impulsive maneuvers is defined so that the problem becomes of finite
dimension, secondly the problem is linearized around an initial reference
solution. A Branch and Bound algorithm is then applied to optimize
simultaneously the debris selection and the orbital maneuvers, yielding a new
reference solution. The process is iterated until the solution stabilizes on
the optimal path. The trajectory controls and dates are finally re-optimized in
order to refine the solution. The method is applicable whatever the numbers of
debris (candidate and to deorbit) and whatever the mission duration. It is
exemplified on an application case consisting in selecting 5 SSO debris among a
list of 11.


  Redshift surveys are one of the prime tools of observational cosmology.
Imaging surveys of the whole sky are now available at a wide range of
wavelengths, and provide a basis for the new generation of massive redshift
surveys currently in progress. The very large datasets produced by these
surveys call for new and sophisticated approaches to the analysis of
large-scale structure and the galaxy population. These issues, and some
preliminary results from the new redshift surveys, were discussed at the second
Coral Sea Cosmology Conference, held at Dunk Island on 24-28 August 1999. This
is a summary of the conference; the full conference proceedings are on the WWW
at http://www.mso.anu.edu.au/DunkIsland/Proceedings .


  Gravitational waves from binary black hole pairs have emerged as an important
observational tool in current times. The energy of the BH - BH binary pair is
radiated in the form of gravitational waves and to compensate for that energy,
kinetic energy of the system decreases gradually. Consequently the mutual
separation of the objects decreases with time and tends to merge. The whole
process may require a very long time comparable or longer than the age of the
universe, specially in the case of low mass mergers. We have examined the case
in which a massive object compared to the individual masses comprising the
binary pair is present nearby such a system. We have found that in this case
the merging process takes place much rapidly than that of the conventional
BH-BH merging process. Scenarios with both an Intermediate Mass Black Hole
(IBMH) ($10^{5}\:M_{\odot}$) as well as a Super Massive Black Hole (SMBH) have
been studied and the latter has been found to provide a much higher overall
rate for the BH-BH merger process.


  We introduce and analyze a system of two coupled partial differential
equations with external noise. The equations are constructed to model
transitions of monovalent metallic nanowires with non-axisymmetric intermediate
or end states, but also have more general applicability. They provide a rare
example of a system for which an exact solution of nonuniform stationary states
can be found. We find a transition in activation behavior as the interval
length on which the fields are defined is varied. We discuss several
applications to physical problems.


  We present a one-shot method for compressing large labeled graphs called
Random Edge Coding. When paired with a parameter-free model based on P\'olya's
Urn, the worst-case computational and memory complexities scale quasi-linearly
and linearly with the number of observed edges, making it efficient on sparse
graphs, and requires only integer arithmetic. Key to our method is bits-back
coding, which is used to sample edges and vertices without replacement from the
edge-list in a way that preserves the structure of the graph. Optimality is
proven under a class of random graph models that are invariant to permutations
of the edges and of vertices within an edge. Experiments indicate Random Edge
Coding can achieve competitive compression performance on real-world network
datasets and scales to graphs with millions of nodes and edges.


  We calculate the characteristic classes for flat SL(n,R) and Sp(2m,R)-bundles
over a compact surface as functions of the spectral data in the Higgs bundle
description, which consists of the points of order 2 in an abelian variety.
Using similar methods we produce a conjectural mirror for the moduli space of
flat U(m,m)-bundles with a fixed characteristic class. This is a
hyperholomorphic bundle over the Sp(2m,C)-moduli space.


  We review the construction of a low-energy effective field theory and its
state space for "abelian" quantum Hall fluids. The scaling limit of the
incompressible fluid is described by a Chern-Simons theory in 2+1 dimensions on
a manifold with boundary. In such a field theory, gauge invariance implies the
presence of anomalous chiral modes localized on the edge of the sample. We
assume a simple boundary structure, i.e., the absence of a reconstructed edge.
For the bulk, we consider a multiply connected planar geometry. We study
tunneling processes between two boundary components of the fluid and calculate
the tunneling current to lowest order in perturbation theory as a function of
dc bias voltage. Particular attention is paid to the special cases when the
edge modes propagate at the same speed, and when they exhibit two significantly
distinct propagation speeds. We distinguish between two "geometries" of
interference contours corresponding to the (electronic) Fabry-Perot and
Mach-Zehnder interferometers, respectively. We find that the interference term
in the current is absent when exactly one hole in the fluid corresponding to
one of the two edge components involved in the tunneling processes lies inside
the interference contour (i.e., in the case of a Mach-Zehnder interferometer).
We analyze the dependence of the tunneling current on the state of the quantum
Hall fluid and on the external magnetic flux through the sample.


  A new amplification method based on the optical Kerr instability is suggested
and theoretically analyzed, with emphasis on the near to mid-infrared
wavelength regime. Our analysis for CaF2 and KBr crystals shows that one to two
cycle pulse amplification by 3-4 orders of magnitude in the wavelength range
from 1-14 microns is feasible with currently available laser sources. At 14
microns final output energies in the 0.05 mJ range are achievable corresponding
to about 0.2-0.25% of the pump energy. The Kerr instability presents a
promising process for the amplification of ultrashort mid-infrared pulses.


  The description of a conducting medium in thermal equilibrium, such as an
electrolyte solution or a plasma, involves nonlinear electrostatics, a subject
rarely discussed in the standard electricity and magnetism textbooks. We
consider in detail the case of the electrostatic double layer formed by an
electrolyte solution near a uniformly charged wall, and we use mean-field or
Poisson-Boltzmann (PB) theory to calculate the mean electrostatic potential and
the mean ion concentrations, as functions of distance from the wall. PB theory
is developed from the Gibbs variational principle for thermal equilibrium of
minimizing the system free energy. We clarify the key issue of which free
energy (Helmholtz, Gibbs, grand,...) should be used in the Gibbs principle;
this turns out to depend not only on the specified conditions in the bulk
electrolyte solution (e.g., fixed volume or fixed pressure), but also on the
specified surface conditions, such as fixed surface charge or fixed surface
potential. Despite its nonlinearity the PB equation for the mean electrostatic
potential can be solved analytically for planar or wall geometry, and we
present analytic solutions for both a full electrolyte, and for an ionic
solution which contains only counterions, i.e. ions of sign opposite to that of
the wall charge. This latter case has some novel features. We also use the free
energy to discuss the inter-wall forces which arise when the two parallel
charged walls are sufficiently close to permit their double layers to overlap.
We consider situations where the two walls carry equal charges, and where they
carry equal and opposite charges.


  The sixth-generation (6G) network is envisioned to shift its focus from the
service requirements of human beings' to those of Internet-of-Things (IoT)
devices'. Satellite communications are indispensable in 6G to support IoT
devices operating in rural or disastrous areas. However, satellite networks
face the inherent challenges of low data rate and large latency, which may not
support computation-intensive and delay-sensitive IoT applications. Mobile Edge
Computing (MEC) is a burgeoning paradigm by extending cloud computing
capabilities to the network edge. By utilizing MEC technologies, the
resource-limited IoT devices can access abundant computation resources with low
latency, which enables the highly demanding applications while meeting strict
delay requirements. Therefore, an integration of satellite communications and
MEC technologies is necessary to better enable 6G IoT. In this survey, we
provide a holistic overview of satellite-MEC integration. We first discuss the
main challenges of the integrated satellite-MEC network and propose three
minimal integrating structures. For each minimal structure, we summarize the
current advances in terms of their research topics, after which we discuss the
lessons learned and future directions of the minimal structure. Finally, we
outline potential research issues to envision a more intelligent, more secure,
and greener integrated satellite-MEC network.