  Some modal (or decoupled) transmission-line properties such as
per-unit-length impedance, admittance, or characteristic impedance have long
been held to be, in general, non-unique. This ambiguity arises from the nature
of the similarity transformations used to relate the terminal and modal
domains, for which the voltage transformation matrix has been shown to be only
loosely related to the corresponding current transformation matrix. Modern
methods have attempted to relate the two, but these relations typically rely on
arbitrary normalizations, leading to strictly incorrect and/or non-unique
results. This work introduces relations between the two transformations,
derived from the physical equivalence of total power and currents between the
two domains, by which the transformation matrices can be unambiguously related
to each other, and the modal properties uniquely solved. This technique allows
for the correct extraction of the modal transmission-line properties for any
arbitrary system of conductors. Multiple examples are studied to validate the
proposed solution process.


  A system of two dimensional photon gas has recently been realized
experimentally. It is pointed out that this setup can be used to observe a
universal breathing mode of photon gas. It is shown that a modification in the
experimental setup would open up a possibility of observing the
Berezinskii-Kosterlitz-Thouless (BKT) phase transition in such a system. It is
shown that the universal jump in the superfluid density of light in the output
channel can be used as an unambiguous signature for the experimental
verification of the BKT transition.


  We compare the effects of local features (LF) and branch features (BF) of the
inflaton potential on the spectrum of primordial perturbations. We show that LF
affect the spectrum in a narrow range of scales while BF produce a step between
large and small scales with respect to the featureless spectrum. We comment on
the possibility of distinguishing between these two types of feature models
from the analysis of the Cosmic Microwave Background (CMB) radiation data.
  We also show that there exists a quantitative similarity between the
primordial spectra predicted by two of the BF potentials considered. This could
lead to a degeneracy of their predicted CMB temperature spectra which could
make difficult to discriminate between the models from a CMB analysis. We
comment on the possibility that the degeneracy can be broken when higher order
terms in the perturbations are considered. In this sense non-Gaussianity may
play an important role in discerning between different inflationary models
which predict similar spectra.


  We demonstrate theoretically how photon number statistics of a driven, damped
oscillator at finite temperature can be extracted by measuring the dephasing
spectrum of a two-level system dispersively coupled to the oscillator; we thus
extend the work of Dykman (1987) and Gambetta et al. (2006). We carefully
consider the fidelity of this scheme-- to what extent does the measurement
reflect the initial number statistics of the mode? We also derive analytic
results for the dephasing of a qubit by a driven, thermal mode, and compare
results obtained at different levels of approximation. Our results have
relevance both to experiments in circuit cavity QED, as well as to
nano-electromechanical systems.


  Recently, Ref. \cite{Wang:2023tdz} investigated the model of Einstein-Bardeen
theory coupled to a free complex scalar field. The introduction of the scalar
field prevents the formation of the event horizon, and when the magnetic charge
exceeds a certain critical value, the frozen Bardeen-boson star can be obtained
with the frequency $\omega \rightarrow 0$. In this paper, we extend the
investigation of the Einstein-Bardeen model with a charged scalar field and
obtain two types of solutions: the small $q$ solution and the large $q$
solution. Specifically, for the small $q$ solution, we find that there exists a
maximum value for the charge $q$, the introduction of the charge makes it
possible to obtain solutions for frozen stars without the frequency to be
approached to zero. For the large $q$ solution, the charge can tend toward
infinity, and as $q \rightarrow \infty$, the large $q$ solution gradually
becomes the pure Bardeen solution. Similar to Ref. \cite{Wang:2023tdz}, the
event horizon is not found in our results.


  We are concerned with a nonstandard phase field model of Cahn-Hilliard type.
The model, which was introduced by Podio-Guidugli (Ric. Mat. 2006), describes
two-species phase segregation and consists of a system of two highly
nonlinearly coupled PDEs. It has been recently investigated by Colli, Gilardi,
Podio-Guidugli, and Sprekels in a series of papers: see, in particular, SIAM J.
Appl. Math. 2011 and Boll. Unione Mat. Ital. 2012. In the latter contribution,
the authors can treat the very general case in which the diffusivity
coefficient of the parabolic PDE is allowed to depend nonlinearly on both
variables. In the same framework, this paper investigates the asymptotic limit
of the solutions to the initial-boundary value problems as the diffusion
coefficient in the equation governing the evolution of the order parameter
tends to zero. We prove that such a limit actually exists and solves the limit
problem, which couples a nonlinear PDE of parabolic type with an ODE accounting
for the phase dynamics. In the case of a constant diffusivity, we are able to
show uniqueness and to improve the regularity of the solution.


  We study the shear mode in the gauge/gravity correspondence at finite
temperature. First, we confirm the general formula for the shear viscosity in
an arbitrary background metric which includes a black hole in the fifth
dimension. We then derive a general formula for the shear mode relaxation time
which appears in the theory of relativistic dissipative fluid dynamics; it
agrees with known expressions in the limit of conformal fields. These results
may be useful in relativistic viscous fluid descriptions of high energy nuclear
collisions at RHIC and LHC.


  Learning powerful feature representations for image retrieval has always been
a challenging task in the field of remote sensing. Traditional methods focus on
extracting low-level hand-crafted features which are not only time-consuming
but also tend to achieve unsatisfactory performance due to the content
complexity of remote sensing images. In this paper, we investigate how to
extract deep feature representations based on convolutional neural networks
(CNN) for high-resolution remote sensing image retrieval (HRRSIR). To this end,
two effective schemes are proposed to generate powerful feature representations
for HRRSIR. In the first scheme, the deep features are extracted from the
fully-connected and convolutional layers of the pre-trained CNN models,
respectively; in the second scheme, we propose a novel CNN architecture based
on conventional convolution layers and a three-layer perceptron. The novel CNN
model is then trained on a large remote sensing dataset to learn low
dimensional features. The two schemes are evaluated on several public and
challenging datasets, and the results indicate that the proposed schemes and in
particular the novel CNN are able to achieve state-of-the-art performance.


  We construct the first example of a finitely-presented, residually-finite
group that contains an infinite sequence of non-isomorphic finitely-presented
subgroups such that each of the inclusion maps induces an isomorphism of
profinite completions.


  Recently quantum walks have been considered as a possible fundamental
description of the dynamics of relativistic quantum fields. Within this
scenario we derive the analytical solution of the Weyl walk in 2+1 dimensions.
We present a discrete path-integral formulation of the Feynman propagator based
on the binary encoding of paths on the lattice. The derivation exploits a
special feature of the Weyl walk, that occurs also in other dimensions, that is
closure under multiplication of the set of the walk transition matrices. This
result opens the perspective of a similar solution in the 3+1 case.


  Two Higgs doublet models (2HDM) provide the low energy effective field theory
(EFT) description in many well motivated extensions of the Standard Model. It
is therefore relevant to study their properties, as well as the theoretical
constraints on these models. In this article we concentrate on three relevant
requirements for the validity of the 2HDM framework, namely the perturbative
unitarity bounds, the bounded from below constraints, and the vacuum stability
constraints. In this study, we concentrate on the most general renormalizable
version of the 2HDM -- without imposing any parity symmetry, which may be
violated in many UV extensions. We derive novel analytical expressions that
generalize those previously obtained in more restrictive scenarios to the most
general case. We also discuss the phenomenological implications of these
bounds, focusing on CP violation.


  Machine Learning (ML) has become ubiquitous, and its deployment in Network
Intrusion Detection Systems (NIDS) is inevitable due to its automated nature
and high accuracy compared to traditional models in processing and classifying
large volumes of data. However, ML has been found to have several flaws, most
importantly, adversarial attacks, which aim to trick ML models into producing
faulty predictions. While most adversarial attack research focuses on computer
vision datasets, recent studies have explored the suitability of these attacks
against ML-based network security entities, especially NIDS, due to the wide
difference between different domains regarding the generation of adversarial
attacks.
  To further explore the practicality of adversarial attacks against ML-based
NIDS in-depth, this paper presents three distinct contributions: identifying
numerous practicality issues for evasion adversarial attacks on ML-NIDS using
an attack tree threat model, introducing a taxonomy of practicality issues
associated with adversarial attacks against ML-based NIDS, and investigating
how the dynamicity of some real-world ML models affects adversarial attacks
against NIDS. Our experiments indicate that continuous re-training, even
without adversarial training, can reduce the effectiveness of adversarial
attacks. While adversarial attacks can compromise ML-based NIDSs, our aim is to
highlight the significant gap between research and real-world practicality in
this domain, warranting attention.


  In this paper, a novel approach, Inforence, is proposed to isolate the
suspicious codes that likely contain faults. Inforence employs a feature
selection method, based on mutual information, to identify those bug-related
statements that may cause the program to fail. Because the majority of a
program faults may be revealed as undesired joint effect of the program
statements on each other and on program termination state, unlike the
state-of-the-art methods, Inforence tries to identify and select groups of
interdependent statements which altogether may affect the program failure. The
interdependence amongst the statements is measured according to their mutual
effect on each other and on the program termination state. To provide the
context of failure, the selected bug-related statements are chained to each
other, considering the program static structure. Eventually, the resultant
cause-effect chains are ranked according to their combined causal effect on
program failure. To validate Inforence, the results of our experiments with
seven sets of programs include Siemens suite, gzip, grep, sed, space, make and
bash are presented. The experimental results are then compared with those
provided by different fault localization techniques for the both single-fault
and multi-fault programs. The experimental results prove the outperformance of
the proposed method compared to the state-of-the-art techniques.


  We present the results of our study of the long term X-ray variability
characteristics of the Narrow Line Seyfert 1 galaxy RE J1034+396. We use data
obtained from the AstroSat satellite along with the light curves obtained from
XMM-Newton and Swift-XRT. We use the 0.3 - 7.0 keV and 3 - 20 keV data,
respectively, from the SXT and the LAXPC of AstroSat. The X-ray spectra in the
0.3 - 20 keV region are well fit with a model consisting of a power-law and a
soft excess described by a thermal-Compton emission with a large optical depth,
consistent with the earlier reported results. We have examined the X-ray light
curves in the soft and hard X-ray bands of SXT and LAXPC, respectively, and
find that the variability is slightly larger in the hard band. To investigate
the variability characteristics of this source at different time scales, we
have used X-ray light curves obtained from XMM-Newton data (200 s to 100 ks
range) and Swift-XRT data (1 day to 100 day range) and find that there are
evidences to suggest that the variability sharply increases at longer time
scales. We argue that the mass of the black hole in RE J1034+396 is likely to
be $\sim$3 $\times$ 10$^6$ M$_\odot$, based on the similarity of the observed
QPO to the high frequency QPO seen in the Galactic black hole binary, GRS
1915+105.


  The correlation functions for models of minimal gravity are discussed. An
algorithm is proposed for calculations of invariant ratios from formulas of
residues that can be compared with the coefficients of expansion of the
partition function in Liouville theory. For (2,2K-1) models transition
coefficient from basis of quasiclassical hierarchy to basis Liouville theory is
obtained evidently, and the hypothesis about exact form of spectral curve has
been verified.


  Since the grand partition function $Z_q$ for the so-called $q$-particles
(i.e.,\ quons), $q\in(-1,1)$, cannot be computed by using the standard 2nd
quantisation technique involving the full Fock space construction for $q=0$,
and its $q$-deformations for the remaining cases, we determine such grand
partition functions in order to obtain the natural generalisation of the Plank
distribution to $q\in [-1,1]$. We also note the (non) surprising fact that the
right grand partition function concerning the Boltzmann case (i.e.,\ $q=0$) can
be easily obtained by using the full Fock space 2nd quantisation, by
considering the appropriate correction by the Gibbs factor $1/n!$ in the $n$
term of the power series expansion with respect to the fugacity $z$. As an
application, we briefly discuss the equations of the state for a gas of free
quons or the condensation phenomenon into the ground state, also occurring for
the Bose-like quons $q\in(0,1)$.


  We are settling a longstanding quarrel in quantitative finance by proving the
existence of trends in financial time series thanks to a theorem due to P.
Cartier and Y. Perrin, which is expressed in the language of nonstandard
analysis (Integration over finite sets, F. & M. Diener (Eds): Nonstandard
Analysis in Practice, Springer, 1995, pp. 195--204). Those trends, which might
coexist with some altered random walk paradigm and efficient market hypothesis,
seem nevertheless difficult to reconcile with the celebrated Black-Scholes
model. They are estimated via recent techniques stemming from control and
signal theory. Several quite convincing computer simulations on the forecast of
various financial quantities are depicted. We conclude by discussing the r\^ole
of probability theory.


  I review some basic facts about the chiral limit of QCD. This allows to
formulate an effective field theory below the chiral symmetry breaking scale,
chiral perturbation theory (CHPT). I show that for threshold reactions, the
spectrum of QCD is most economically encoded in a set of coupling constants of
operators of higher chiral dimension. A consistent scheme to incorporate the
$\Delta(1232)$ is also discussed and some examples are given. It is stressed
that more precise low--energy data are needed to further test and sharpen the
resonance saturation hypothesis in the presence of baryons.


  Semiconducting ferromagnet-nonmagnet interfaces in van der Waals
heterostructures present a unique opportunity to investigate magnetic proximity
interactions dependent upon a multitude of phenomena including valley and layer
pseudospins, moir\'e periodicity, or exceptionally strong Coulomb binding.
Here, we report a charge-state dependency of the magnetic proximity effects
between MoSe$_2$ and CrBr$_3$ in photoluminescence, whereby the valley
polarization of the MoSe$_2$ trion state conforms closely to the local CrBr$_3$
magnetization, while the neutral exciton state remains insensitive to the
ferromagnet. We attribute this to spin-dependent interlayer charge transfer
occurring on timescales between the exciton and trion radiative lifetimes.
Going further, we uncover by both the magneto-optical Kerr effect and
photoluminescence a domain-like spatial topography of contrasting valley
polarization, which we infer to be labyrinthine or otherwise highly intricate,
with features smaller than 400 nm corresponding to our optical resolution. Our
findings offer a unique insight into the interplay between short-lived valley
excitons and spin-dependent interlayer tunnelling, while also highlighting
MoSe$_2$ as a promising candidate to optically interface with exotic spin
textures in van der Waals structures.


  Background: At the forefront of the nuclear science, production of new
neutron-rich isotopes is continuously pursued at accelerator laboratories all
over the world. To explore the currently-unknown territories in the nuclear
chart far away from the stability, reliable theoretical predictions are
inevitable.
  Purpose: To provide a reliable prediction of production cross sections taking
into account secondary deexcitation processes, both particle evaporation and
fission, a new method called TDHF+GEMINI is proposed, which combines the
microscopic time-dependent Hartree-Fock (TDHF) theory with a sophisticated
statistical compound-nucleus deexcitation model, GEMINI++.
  Results: The method is applied for multinucleon transfer processes in
low-energy heavy ion reactions. It is shown that the inclusion of secondary
deexcitation processes, which are dominated by neutron evaporation in the
present systems, substantially improves agreement with the experimental data.
The magnitude of the evaporation effects is very similar to the one observed in
GRAZING calculations. TDHF+GEMINI provides better description of the absolute
value of the cross sections for channels involving transfer of more than one
protons, compared with the GRAZING results. However, there remain discrepancies
between the measurements and the calculated cross sections, indicating a limit
of the theoretical framework that works with a single mean-field potential.
Possible causes of the discrepancies are discussed.
  Conclusions: In order to perfectly reproduce experimental cross sections for
multinucleon transfer processes, one should go beyond the standard
self-consistent mean-field description. Nevertheless, the proposed method will
provide valuable information to optimize production mechanisms of new
neutron-rich nuclei through its microscopic, non-empirical predictions.
  (Shortened due to the word limit)


  After reviewing some of the mathematical foundations and numerical
difficulties facing lattice QCD, I review the status of several calculations
relevant to experimental high-energy physics. The topics considered are moments
of structure functions, which may prove relevant to search for new phenomena at
the LHC, and several aspects of flavor physics, which are relevant to
understanding CP and flavor violation.


  The spectrum of cyclotron radiation is calculated for anisotropically
distributed relativistic electrons with a nonrelativistic velocity scattering
across the magnetic field. It is shown that if such electrons are responsible
for a formation of the "cyclotron" line in the spectrum of Her X-1, then the
value of its magnetic field $(3-6)\cdot 10^{10}$ Gs resulting from this
interpretation is in a good agreement with some other observations and
theoretical estimations. Observations of a time dependence of the energy of
this "cyclotron" line in the spectra of several X-ray pulsars is explained by a
variability of the average longitude energy of the electrons, decreasing with
increasing liminocity due to radiational braking of the accretion flow.


  In this note, we show that for every simple game with n players the critical
threshold value is at most n/4. This verifies the conjecture of Freixas and
Kurz.


  Let $\varphi$ and $\psi$ be quadratic forms over a field $K$ of
characteristic different from 2. In this paper, we give a criterion for
isotropy of $\varphi$ over the function field of $\psi$ in terms of
representations and we apply it to stably birational equivalence of $\varphi$
and $\psi$. Then we use this criterion to investigate the case of stably
birational equivalence of multiples of Pfister forms. Finally, we give a a
criterion of stably birational equivalence of quadratic forms in terms of
isomorphisms of quotients of special Clifford groups by the kernel of the
spinor norm.


  Utilizing multiwavelength observations and magnetic field data from SDO/AIA,
SDO/HMI, GOES and RHESSI, we investigate a large-scale ejective solar eruption
of 2014 December 18 from active region NOAA 12241. This event produced a
distinctive three-ribbon flare, having two parallel ribbons corresponding to
the ribbons of a standard two-ribbon flare, and a larger-scale third
quasi-circular ribbon offset from the other two ribbons. There are two
components to this eruptive event. First, a flux rope forms above a
strong-field polarity-inversion line and erupts and grows as the parallel
ribbons turn on, grow, and spread part from that polarity-inversion line; this
evolution is consistent with the tether-cutting-reconnection mechanism for
eruptions. Second, the eruption of the arcade that has the erupting flux rope
in its core under goes magnetic reconnection at the null point of a fan dome
that envelops the erupting arcade, resulting in formation of the quasi-circular
ribbon; this is consistent with the breakout reconnection mechanism for
eruptions. We find that the parallel ribbons begin well before (12 min)
circular ribbon onset, indicating that tether-cutting reconnection (or a
non-ideal MHD instability) initiated this event, rather than breakout
reconnection. The overall setup for this large-scale (circular-ribbon diameter
100000 km) eruption is analogous to that of coronal jets (base size 10000 km),
many of which, according to recent findings, result from eruptions of
small-scale minifilaments. Thus these findings confirm that eruptions of
sheared-core magnetic arcades seated in fan-spine null-point magnetic topology
happen on a wide range of size scales on the Sun.


  The total number of fatalities of an epidemic outbreak is a dramatic but
extremely informative quantity. Knowledge of the statistics of this quantity
allows the calculation of the mean total number of fatalities conditioned to
the fact that the outbreak has surpassed a given number of fatalities, which is
very relevant for risk assessment. However, the fact that the total number of
fatalities seems to be characterized by a power-law tailed distribution with
exponent (of the survival function) smaller than one poses an important
theoretical difficulty, due to the non-existence of a mean value for such
distributions. Cirillo and Taleb [Nature Phys. 16, 606 (2020)] propose a
transformation from a so-called dual variable, which displays a power-law tail,
to the total number of fatalities, which becomes bounded by the total world
population. Here, we (i) show that such a transformation is ad hoc and
unphysical; (ii) propose alternative transformations and distributions (also ad
hoc); (iii) argue that the right framework for this problem is statistical
physics, through finite-size scaling; and (iv) demonstrate that the real
problem is not the non-existence of the mean value for power-law tailed
distributions but the fact that the tail of the different theoretical
distributions (which is what distinguishes one model from the other) is far
from being well sampled with the available number of empirical data. Our
results are also valid for many other hazards displaying (apparent) power-law
tails in their size.


  Data-Driven Inversion-Based Control (D$^{2}$-IBC) is a recently introduced
control design method for uncertain nonlinear systems, relying on a two
degree-of-freedom architecture, with a nonlinear controller and a linear
controller running in parallel. In this paper, extending to the MIMO case a
previous result holding for the SISO case, we derive a finite-gain stability
sufficient condition for a closed-loop system formed by a nonlinear MIMO plant,
connected in feedback with a D$^{2}$-IBC controller.


  The Filament Based Lamellipodium Model (FBLM) is a two-phase two-dimensional
continuum model, describing the dynamcis of two interacting families of locally
parallel actin filaments (C.Schmeiser and D.Oelz, How do cells move?
Mathematical modeling of cytoskeleton dynamics and cell migration. Cell
mechanics: from single scale-based models to multiscale modeling. Chapman and
Hall, 2010). It contains accounts of the filaments' bending stiffness, of
adhesion to the substrate, and of cross-links connecting the two families.
  An extension of the model is presented with contributions from nucleation of
filaments by branching, from capping, from contraction by actin-myosin
interaction, and from a pressure-like repulsion between parallel filaments due
to Coulomb interaction. The effect of a chemoattractant is described by a
simple signal transduction model influencing the polymerization speed.
Simulations with the extended model show its potential for describing various
moving cell shapes, depending on the signal transduction procedure, and for
predicting transients between nonmoving and moving states as well as changes of
direction.


  The chemical abundance patterns of the oldest stars in the Galaxy are
expected to contain residual signatures of the first stars in the early
universe. Numerous studies attempt to explain the intrinsic abundance scatter
observed in some metal-poor populations in terms of chemical inhomogeneities
dispersed throughout the early Galactic medium due to discrete enrichment
events. Just how the complex data and models are to be interpreted with respect
to "progenitor yields" remains an open question. Here we show that stochastic
chemical evolution models to date have overlooked a crucial fact. Essentially
all stars today are born in highly homogeneous star clusters and it is likely
that this was also true at early times. When this ingredient is included, the
overall scatter in the abundance plane [Fe/H] vs. [X/Fe] (C-space), where X is
a nucleosynthetic element, can be much less than derived from earlier models.
Moreover, for moderately flat cluster mass functions (gamma < 2), and/or for
mass functions with a high mass cut-off (M_max > 10^5 M_sun), stars exhibit a
high degree of clumping in C-space that can be identified even in relatively
small data samples. Since stellar abundances can be modified by mass transfer
in close binaries, clustered signatures are essential for deriving the yields
of the first supernovae. We present a statistical test to determine whether a
given set of observations exhibit such behaviour. Our initial work focusses on
two dimensions in C-space, but we show that the clustering signal can be
greatly enhanced by additional abundance axes. The proposed experiment will be
challenging on existing 8-10m telescopes, but relatively straightforward for a
multi-object echelle spectrograph mounted on a 25-40m telescope.


  We study word reconstruction problems. Improving a previous result by P.
Fleischmann, M. Lejeune, F. Manea, D. Nowotka and M. Rigo, we prove that, for
any unknown word $w$ of length $n$ over an alphabet of cardinality $k$, $w$ can
be reconstructed from the number of occurrences as subwords (or scattered
factors) of $O(k^2\sqrt{n\log_2(n)})$ words. Two previous upper bounds obtained
by S. S. Skiena and G. Sundaram are also slightly improved: one when
considering information on the existence of subwords instead of on the numbers
of their occurrences, and, the other when considering information on the
existence of factors.


  A game-theoretic model is proposed to study the cross-layer problem of joint
power and rate control with quality of service (QoS) constraints in
multiple-access networks. In the proposed game, each user seeks to choose its
transmit power and rate in a distributed manner in order to maximize its own
utility while satisfying its QoS requirements. The user's QoS constraints are
specified in terms of the average source rate and an upper bound on the average
delay where the delay includes both transmission and queuing delays. The
utility function considered here measures energy efficiency and is particularly
suitable for wireless networks with energy constraints. The Nash equilibrium
solution for the proposed non-cooperative game is derived and a closed-form
expression for the utility achieved at equilibrium is obtained. It is shown
that the QoS requirements of a user translate into a "size" for the user which
is an indication of the amount of network resources consumed by the user. Using
this competitive multiuser framework, the tradeoffs among throughput, delay,
network capacity and energy efficiency are studied. In addition, analytical
expressions are given for users' delay profiles and the delay performance of
the users at Nash equilibrium is quantified.


  We study the spatially resolved outflow properties of CSWA13, an intermediate
mass ($M_*=10^{9}~\mathrm{M}_{\odot}$), gravitationally lensed star-forming
galaxy at $z=1.87$. We use Keck/KCWI to map outflows in multiple rest-frame
ultraviolet ISM absorption lines, along with fluorescent Si II$^*$ emission,
and nebular emission from C III] tracing the local systemic velocity. The
spatial structure of outflow velocity mirrors that of the nebular kinematics,
which we interpret to be a signature of a young galactic wind that is
pressurizing the ISM of the galaxy but is yet to burst out. From the radial
extent of Si II$^*$ emission, we estimate that the outflow is largely
encapsulated within $3.5$ kpc. We explore the geometry (e.g., patchiness) of
the outflow by measuring the covering fraction at different velocities, finding
that the maximum covering fraction is at velocities $v\simeq-150$
km$\,$s$^{-1}$. Using the outflow velocity ($v_{out}$), radius ($R$), column
density ($N$), and solid angle ($\Omega$) based on the covering fraction, we
measure the mass loss rate
$\log\dot{m}_{out}/(\mathrm{M}_{\odot}\text{yr}^{-1}) = 1.73\pm0.23$ and mass
loading factor $\log\eta = 0.04\pm0.34$ for the low-ionization outflowing gas
in this galaxy. These values are relatively large and the bulk of the
outflowing gas is moving with speeds less than the escape velocity of the
galaxy halo, suggesting that the majority of outflowing mass will remain in the
circumgalactic medium and/or recycle back into the galaxy. The results support
a picture of high outflow rates transporting mass and metals into the inner
circumgalactic medium, providing the gas reservoir for future star formation.


  This paper studies an optimal consumption problem for a loss-averse agent
with reference to past consumption maximum. To account for loss aversion on
relative consumption, an S-shaped utility is adopted that measures the
difference between the non-negative consumption rate and a fraction of the
historical spending peak. We consider the concave envelope of the utility with
respect to consumption, allowing us to focus on an auxiliary HJB variational
inequality on the strength of concavification principle and dynamic programming
arguments. By applying the dual transform and smooth-fit conditions, the
auxiliary HJB variational inequality is solved in piecewise closed-form and
some thresholds of the wealth variable are obtained. The optimal consumption
and investment control can be derived in the piecewise feedback form. The
rigorous verification proofs on optimality and concavification principle are
provided. Some numerical sensitivity analysis and financial implications are
also presented.


  Magnetic tunnel junctions (MTJs) with partially oxidized 9 \AA
AlO$_x$-barriers were recently shown to have the necessary characteristics to
be used as magnetoresistive sensors in high-density storage devices. Here we
study dielectric breakdown in such underoxidized magnetic tunnel junctions,
focusing on its dependence on tunnel junction area and oxidation time. A clear
relation between breakdown mechanism and junction area is observed for the MTJs
with the highest studied oxidation time: samples with large areas fail usually
due to extrinsic causes (characterized by a smooth resistance decrease at
dielectric breakdown). Small area junctions fail mainly through an intrinsic
mechanism (sharp resistance decrease at breakdown). However, this dependence
changes for lower oxidation times, with extrinsic breakdown becoming dominant.
In fact, in the extremely underoxidized magnetic tunnel junctions, failure is
exclusively related with extrinsic causes, independently of MTJ-area. These
results are related with the presence of defects in the barrier (weak spots
that lead to intrinsic breakdown) and of metallic unoxidized Al
nanoconstrictions (leading to extrinsic breakdown).


  In this paper, we study the greybody factor for static spherically symmetric
black hole with non-linear electrodynamics. For this purpose, we assume minimal
coupling of the scalar field and find the radial equation by using the
Klein-Gordon equation. We then apply tortoise coordinate to convert this
equation into Schrodinger wave equation which helps to find the effective
potential. The behavior of effective potential is checked for different values
of the coupling and charge parameters. We find two solutions in two horizons
named as event and cosmological horizons by using the radial equation. We
consider the intermediate regime and match these two solutions to obtain the
greybody factor and examine its behavior graphically. It is found that the
greybody factor has an inverse relation with the coupling constant, mass,
charge as well as the radius of the black hole and has a direct relation with
angular momentum.


  A fundamental task in AI is to assess (in)dependence between mixed-type
variables (text, image, sound). We propose a Bayesian kernelised correlation
test of (in)dependence using a Dirichlet process model. The new measure of
(in)dependence allows us to answer some fundamental questions: Based on data,
are (mixed-type) variables independent? How likely is dependence/independence
to hold? How high is the probability that two mixed-type variables are more
than just weakly dependent? We theoretically show the properties of the
approach, as well as algorithms for fast computation with it. We empirically
demonstrate the effectiveness of the proposed method by analysing its
performance and by comparing it with other frequentist and Bayesian approaches
on a range of datasets and tasks with mixed-type variables.


  Varying environmental conditions affect relations between interacting
individuals in social dilemmas, thus affecting also the evolution of
cooperation. Oftentimes these environmental variations are seasonal and can
therefore be mathematically described as periodic changes. Accordingly, we here
study how periodic shifts between different manifestations of social dilemmas
affect cooperation. We observe a non-trivial interplay between the inherent
spatiotemporal dynamics that characterizes the spreading of cooperation in a
particular social dilemma type and the frequency of payoff changes. In
particular, we show that periodic changes between two available games with
global ordering best be fast, while periodic changes between global and local
ordering games best be slow for cooperation to thrive. We also show that the
frequency of periodic changes between two local ordering social dilemmas is
irrelevant, because then the process is fast and simply the average cooperation
level of the two is returned. The structure of the interaction network plays an
important role too in that lattices promote local ordering, whilst random
graphs hinder the formation of compact cooperative clusters. Conversely, for
local ordering the regular structure of the interaction network is only
marginally relevant as role-separating checkerboard patterns do not rely on
long-range order.


  In this paper, we deal with the $\mathcal{U}(\mathfrak{g})$-action on a
$\mathfrak{g}$-module on which a larger algebra $\mathcal{A}$ acts irreducibly.
Under a mild condition, we will show that the support of the
$\mathcal{Z}(\mathfrak{g})$-action is a union of affine subspaces in the dual
of a Cartan subalgebra modulo the Weyl group action. As a consequence, we
propose a definition of a Cartan subalgebra for such a $\mathfrak{g}$-module.
  The support of the $\mathcal{Z}(\mathfrak{g})$-module is an algebraic
counterpart of the support of the measure in the irreducible decomposition of a
unitary representation. This consideration is motivated by the theory of the
discrete decomposability initiated by T. Kobayashi. Defining a Cartan
subalgebra for a $\mathfrak{g}$-module is motivated by the study of I. Losev on
Poisson $G$-varieties. These are related each other through the associated
variety and the nilpotent orbit associated to a $\mathfrak{g}$-module.


  We consider the flow network model to solve the multiprocessor real-time task
scheduling problems. Using the flow network model or its generic form, linear
programming (LP) formulation, for the problems is not new. However, the
previous works have limitations, for example, that they are classified as
offline scheduling techniques since they establish a flow network model or an
LP problem considering a very long time interval. In this study, we propose how
to construct the flow network model for online scheduling periodic real-time
tasks on multiprocessors. Our key idea is to construct the flow network only
for the active instances of tasks at the current scheduling time, while
guaranteeing the existence of an optimal schedule for the future instances of
the tasks. The optimal scheduling is here defined to ensure that all real-time
tasks meet their deadlines when the total utilization demand of the given tasks
does not exceed the total processing capacity. We then propose the flow network
model-based polynomial-time scheduling algorithms. Advantageously, the flow
network model allows the task workload to be collected unfairly within a
certain time interval without losing the optimality. It thus leads us to
designing three unfair-but-optimal scheduling algorithms on both continuous and
discrete-time models. Especially, our unfair-but-optimal scheduling algorithm
on a discrete-time model is, to the best of our knowledge, the first in the
problem domain. We experimentally demonstrate that it significantly alleviates
the scheduling overheads, i.e., the reduced number of preemptions with the
comparable number of task migrations across processors.


  This paper has been withdrawn by the authors because the paper is largely
revised and improved.


  The methodology of deriving an adatom lattice-gas Hamiltonian (LGH) from
first principles (FP) calculations is revisited. Such LGH cluster expansions
compute a large set of lateral pair-, trio-, quarto interactions by solving a
set of linear equations modelling regular adatom configurations and their FP
energies. The basic assumption of truncating interaction terms beyond fifth
nearest neighbors does not hold when adatoms show longer range interactions,
e.g. substrate mediated elastic interactions. O-Pd(100) as a popular reference
is used to propose a long range elastic interaction alternative including
many-body trio- and quarto terms with just 3 parameters fitted to FP
calculations. A key feature of the interaction alternative is its analytic
nature, allowing statistical methods different from Monte Carlo simulations to
derive surface order. The assumptions made are discussed and ways to further
verify and apply the model are outlined.


  A hole in a 4d orbital of atomic xenon relaxes through Auger decay after a
lifetime of 3 fs. Adding electronegative fluorine ligands to form xenon
fluoride molecules, results in withdrawal of valence-electron density from Xe.
Thus, within the one-center picture of Auger decay, a lowered Xe 4d Auger width
would be expected, in contradiction, however, with experiment. Employing
extensive ab initio calculations within the framework of many-body Green's
functions, we determine all available decay channels in XeFn and characterize
these channels by means of a two-hole population analysis. We derive a relation
between two-hole population numbers and partial Auger widths. On this basis,
interatomic electronic decay processes are demonstrated to be so strong in the
xenon fluorides that they overcompensate the reduction in intra-atomic Auger
width and lead to the experimentally observed trend. The nature of the relevant
processes is discussed. These processes presumably underlie Auger decay in a
variety of systems.


  It is well-known that the speed $c_u=1/\sqrt{\epsilon_0\mu_0}$ is obtained in
the process of defining SI units via action-at-a-distance forces, like the
force between two static charges and the force between two long and parallel
currents. The speed $c_u$ is then physically different from the observed speed
of propagation $c$ associated with electromagnetic waves in vacuum. However,
repeated experiments have led to the numerical equality $c_u=c,$ which we have
called the $c$ equivalence principle. In this paper we point out that
$\nabla\times{\bf E}=-[1/(\epsilon_0\mu_0 c^2)]\partial{\bf B}/\partial t$ is
the correct form of writing Faraday's law when the $c$ equivalence principle is
not assumed. We also discuss the covariant form of Maxwell's equations without
assuming the $c$ equivalence principle.


  Based on published data, we have compiled a catalogue of fundamental
astrophysical parameters for 593 open clusters of the Galaxy. In particular,
the catalogue provides the Galactic orbital elements for 500 clusters, the
masses, central concentrations, and ellipticities for 424 clusters, the
metallicities for 264 clusters, and the relative magnesium abundances for 56
clusters. We describe the sources of initial data and estimate the errors in
the investigated parameters. The selection effects are discussed. The chemical
and kinematical properties of the open clusters and field thin-disk stars are
shown to differ. We provide evidence for the heterogeneity of the population of
open clusters.


  We show in this text how the most important homology equivalences of
fundamental Algebraic Topology can be obtained as reductions associated to
discrete vector fields. Mainly the homology equivalences whose existence --
most often non-constructive -- is proved by the main spectral sequences, the
Serre and Eilenberg-Moore spectral sequences. On the contrary, the constructive
existence is here systematically looked for and obtained.


  The Milky Way bulge has a boxy/peanut morphology and an X-shaped structure.
This X-shape has been revealed by the `split in the red clump' from star counts
along the line of sight toward the bulge, measured from photometric surveys.
This boxy, X-shaped bulge morphology is not unique to the Milky Way and such
bulges are observed in other barred spiral galaxies. N-body simulations show
that boxy and X-shaped bulges are formed from the disk via dynamical
instabilities. It has also been proposed that the Milky Way bulge is not
X-shaped, but rather, the apparent split in the red clump stars is a
consequence of different stellar populations, in an old classical spheroidal
bulge. We present a WISE image of the Milky Way bulge, produced by downsampling
the publicly available "unWISE" coadds. The WISE image of the Milky Way bulge
shows that the X-shaped nature of the Milky Way bulge is self-evident and
irrefutable. The X-shape morphology of the bulge in itself and the fraction of
bulge stars that comprise orbits within this structure has important
implications for the formation history of the Milky Way, and, given the
ubiquity of boxy X-shaped bulges, spiral galaxies in general.


  The semiclassical limit for Dirac particles interacting with a static
gravitational field is investigated. A Foldy-Wouthuysen transformation which
diagonalizes at the semiclassical order the Dirac equation for an arbitrary
static spacetime metric is realized. In this representation the Hamiltonian
provides for a coupling between spin and gravity through the torsion of the
gravitational field. In the specific case of a symmetric gravitational field we
retrieve the Hamiltonian previously found by other authors. But our formalism
provides for another effect, namely, the spin hall effect, which was not
predicted before in this context.


  Increasing energy efficiency in buildings can reduce costs and emissions
substantially. Historically, this has been treated as a local, or single-agent,
optimization problem. However, many buildings utilize the same types of thermal
equipment e.g. electric heaters and hot water vessels. During operation,
occupants in these buildings interact with the equipment differently thereby
driving them to diverse regions in the state-space. Reinforcement learning
agents can learn from these interactions, recorded as sensor data, to optimize
the overall energy efficiency. However, if these agents operate individually at
a household level, they can not exploit the replicated structure in the
problem. In this paper, we demonstrate that this problem can indeed benefit
from multi-agent collaboration by making use of targeted exploration of the
state-space allowing for better generalization. We also investigate trade-offs
between integrating human knowledge and additional sensors. Results show that
savings of over 40% are possible with collaborative multi-agent systems making
use of either expert knowledge or additional sensors with no loss of occupant
comfort. We find that such multi-agent systems comfortably outperform
comparable single agent systems.


  OpenMP is a shared memory programming model which supports the offloading of
target regions to accelerators such as NVIDIA GPUs. The implementation in
Clang/LLVM aims to deliver a generic GPU compilation toolchain that supports
both the native CUDA C/C++ and the OpenMP device offloading models. There are
situations where the semantics of OpenMP and those of CUDA diverge. One such
example is the policy for implicitly handling local variables. In CUDA, local
variables are implicitly mapped to thread local memory and thus become private
to a CUDA thread. In OpenMP, due to semantics that allow the nesting of regions
executed by different numbers of threads, variables need to be implicitly
\emph{shared} among the threads of a contention group. In this paper we
introduce a re-design of the OpenMP device data sharing infrastructure that is
responsible for the implicit sharing of local variables in the Clang/LLVM
toolchain. We introduce a new data sharing infrastructure that lowers
implicitly shared variables to the shared memory of the GPU. We measure the
amount of shared memory used by our scheme in cases that involve scalar
variables and statically allocated arrays. The evaluation is carried out by
offloading to K40 and P100 NVIDIA GPUs. For scalar variables the pressure on
shared memory is relatively low, under 26\% of shared memory utilization for
the K40, and does not negatively impact occupancy. The limiting occupancy
factor in that case is register pressure. The data sharing scheme offers the
users a simple memory model for controlling the implicit allocation of device
shared memory.


  Axisymmetric dust rings containing tens to hundreds of Earth masses of solids
have been observed in protoplanetary discs with (sub-)millimetre imaging. Here,
we investigate the growth of a planetary embryo in a massive (150M$_\oplus$)
axisymmetric dust trap through dust and gas hydrodynamics simulations. When
accounting for the accretion luminosity of the planetary embryo from pebble
accretion, the thermal feedback on the surrounding gas leads to the formation
of an anticyclonic vortex. Since the vortex forms at the location of the
planet, this has significant consequences for the planet's growth: as dust
drifts towards the pressure maximum at the centre of the vortex, which is
initially co-located with the planet, a rapid accretion rate is achieved, in a
distinct phase of ``vortex-assisted'' pebble accretion. Once the vortex
separates from the planet due to interactions with the disc, it accumulates
dust, shutting off accretion onto the planet. We find that this rapid
accretion, mediated by the vortex, results in a planet containing $\approx$
100M$_\oplus$ of solids. We follow the evolution of the vortex, as well as the
efficiency with which dust grains accumulate at its pressure maximum as a
function of their size, and investigate the consequences this has for the
growth of the planet as well as the morphology of the protoplanetary disc. We
speculate that this extreme formation scenario may be the origin of giant
planets which are identified to be significantly enhanced in heavy elements.


  We evaluate the non-Markovian finite-temperature two-time correlation
functions (CF's) of system operators of a pure-dephasing spin-boson model in
two different ways, one by the direct exact operator technique and the other by
the recently derived evolution equations, valid to second order in the
system-environment interaction Hamiltonian. This pure-dephasing spin-boson
model that is exactly solvable has been extensively studied as a simple
decoherence model. However, its exact non-Markovian finite-temperature two-time
system operator CF's, to our knowledge, have not been presented in the
literature. This may be mainly due to the fact, illustrated in this article,
that in contrast to the Markovian case, the time evolution of the reduced
density matrix of the system (or the reduced quantum master equation) alone is
not sufficient to calculate the two-time system operator CF's of non-Markovian
open systems. The two-time CF's obtained using the recently derived evolution
equations in the weak system-environment coupling case for this non-Markovian
pure-dephasing model happen to be the same as those obtained from the exact
evaluation. However, these results significantly differ from the non-Markovian
two-time CF's obtained by wrongly directly applying the quantum regression
theorem (QRT), a useful procedure to calculate the two-time CF's for
weak-coupling Markovian open systems. This demonstrates clearly that the
recently derived evolution equations generalize correctly the QRT to
non-Markovian finite-temperature cases. It is believed that these evolution
equations will have applications in many different branches of physics.


  In a kagome lattice, the time reversal symmetry can be broken by a staggered
magnetic flux emerging from ferromagnetic ordering and intrinsic spin-orbit
coupling, leading to several wellseparated nontrivial Chern bands and intrinsic
quantum anomalous Hall effect. Based on this idea and ab initio calculations,
we propose the realization of the intrinsic quantum anomalous Hall effect in
the single layer Cs2Mn3F12 kagome lattice and on the (001) surface of a
Cs2LiMn3F12 single crystal by modifying the carrier coverage on it, where the
band gap is around 20 meV. Moreover, a simplified tight binding model based on
the in-plane dd\sigma antibonding states is constructed to understand the
topological band structures of the system.


  A joint campaign of various space-borne and ground-based observatories,
comprising the Japanese Hinode mission (HOP~338, 20\,--\,30~September 2017),
the GREGOR solar telescope, and the \textit{Vacuum Tower Telescope} (VTT),
investigated numerous targets such as pores, sunspots, and coronal holes. In
this study, we focus on the coronal hole region target. On 24~September 2017, a
very extended non-polar coronal hole developed patches of flux emergence, which
contributed to the decrease of the overall area of the coronal hole. These flux
emergence patches erode the coronal hole and transform the area into a more
quiet-Sun-like area, whereby bipolar magnetic structures play an important
role. Conversely, flux cancellation leads to the reduction of opposite-polarity
magnetic fields and to an increase in the area of the coronal hole.
  Other global coronal hole characteristics, including the evolution of the
associated magnetic flux and the aforementioned area evolution in the EUV, are
studied using data of the \textit{Helioseismic and Magnetic Imager} (HMI) and
\textit{Atmospheric Imaging Assembly} (AIA) onboard the \textit{Solar Dynamics
Observatory} (SDO). The interplanetary medium parameters of the solar wind
display parameters compatible with the presence of the coronal hole.
Furthermore, a particular transient is found in those parameters.


  In this article we will review some notions of infiniteness that appear in
Hilbert space operators and operator algebras. These include proper
infiniteness, Murray von Neumann's classification into type I and type III
factors and the class of F{/o} lner C*-algebras that capture some aspects of
amenability. We will also mention how these notions reappear in the description
of certain mathematical aspects of quantum mechanics, quantum field theory and
the theory of superselection sectors. We also show that the algebra of the
canonical anti-commutation relations (CAR-algebra) is in the class of F{/o}
lner C*-algebras.


  We consider processing an n x d matrix A in a stream with row-wise updates
according to a recent algorithm called Frequent Directions (Liberty, KDD 2013).
This algorithm maintains an l x d matrix Q deterministically, processing each
row in O(d l^2) time; the processing time can be decreased to O(d l) with a
slight modification in the algorithm and a constant increase in space. We show
that if one sets l = k+ k/eps and returns Q_k, a k x d matrix that is the best
rank k approximation to Q, then we achieve the following properties: ||A -
A_k||_F^2 <= ||A||_F^2 - ||Q_k||_F^2 <= (1+eps) ||A - A_k||_F^2 and where
pi_{Q_k}(A) is the projection of A onto the rowspace of Q_k then ||A -
pi_{Q_k}(A)||_F^2 <= (1+eps) ||A - A_k||_F^2.
  We also show that Frequent Directions cannot be adapted to a sparse version
in an obvious way that retains the l original rows of the matrix, as opposed to
a linear combination or sketch of the rows.


  It was pointed out in a recent paper that the observed cooling rate of old,
cold neutron stars (NS) can provide an upper limit on the transition rate of
neutron to mirror neutron ($n-n'$). This limit is so stringent that it would
preclude any discovery of $n \to n'$ oscillation in the current round of
terrestrial searches for the process. Motivated by this crucially important
conclusion, we critically analyze this suggestion and note an interesting new
effect present in nearly exact mirror models for $n \to n'$ oscillation, which
significantly affect this bound. The new element is the $\beta$ decay $n' \to
p'+ e' +\bar{\nu}'_{e}$, which creates a cloud of mirror particles $n'$, $p'$,
$e'$ and $D'$ inside the NS core. The $e'$ can "rob" the energy generated by
the $n \to n'$ transition via $e-e'$ scattering enabled by the presence of a
(minute) milli-charge in mirror particles. This energy is emitted as unobserved
mirror photons via fast mirror bremsstrahlung leading to a relaxation of this
upper limit.


  Given a family of nodal curves, a semistable modification of it is another
family made up of curves obtained by inserting chains of rational curves of any
given length at certain nodes of certain curves of the original family. We give
comparison theorems between torsion-free, rank-1 sheaves in the former family
and invertible sheaves in the latter. We apply them to show that there are
functorial isomorphisms between the compactifications of relative Jacobians of
families of nodal curves constructed through Caporaso's approach and those
constructed through Pandharipande's approach.


  The presently available high-statistics data of the D0 --> K0S pi+ pi-
processes measured by the Belle and BABAR Collaborations are analyzed within a
quasi two-body QCD factorization framework. Starting from the weak effective
Hamiltonian, tree and annihilation amplitudes build up the D0 --> K0S pi+ pi-
decay amplitude. Two of the three final-state mesons are assumed to form a
single scalar, vector or tensor state originating from a quark-antiquark pair
so that the factorization hypothesis can be applied. The meson-meson final
state interactions are described by K pi and pi pi scalar and vector form
factors for the S and P waves and by relativistic Breit-Wigner formulae for the
D waves. A combined chi^2 fit to a Belle Dalitz plot density distribution, to
the total experimental branching fraction and to the tau^- --> K0S pi- nu_tau
decay data is carried out to fix the 33 free parameters. These are mainly
related to the strengths of the scalar form factors and to unknown meson to
meson transition form factors at a large momentum transfer squared equal to the
D0 mass squared. A good overall agreement to the Belle Dalitz plot density
distribution is achieved. Another set of parameters fits equally well the BABAR
Collaboration Dalitz plot model. The branching fractions of the dominant
channels compare well with those of the isobar Belle or BABAR models.The
lower-limit values of the branching fractions of the annihilation amplitudes
are significant. Built upon experimental data from other processes, the unitary
K pi and pi pi scalar form factors, entering our decay amplitude and satisfying
analyticity and chiral symmetry constraints, are furthermore constrained by the
present Dalitz plot analysis. Our decay amplitude could be a useful input for
determinations of D0-D0bar mixing parameters and of the CKM angle gamma (or
phi3).


  We study the weak-tunnelling limit for a system of cold 40K atoms trapped in
a one-dimensional optical lattice close to an s-wave Feshbach resonance. We
calculate the local spectrum for three atoms at one site of the lattice within
a two-channel model. Our results indicate that, for this one-dimensional
system, one- and two-channel models will differ close to the Feshbach
resonance, although the two theories would converge in the limit of strong
Feshbach coupling. We also find level crossings in the low-energy spectrum of a
single well with three atoms that may lead to quantum phase transition for an
optical lattice of many wells. We discuss the stability of the system to a
phase with non-uniform density.


  We select a sample of 10 radio-quiet quasars with confirmed intranight
optical variability and with available X-ray data. We compare the variability
properties and the broad band spectral constraints to the predictions of
intranight variability by three models: (i) irradiation of an accretion disk by
a variable X-ray flux (ii) an accretion disk instability (iii) the presence of
a weak blazar component. We concluded that the third model, e.g. the blazar
component model, is the most promising if we adopt a cannonball model for the
jet variable emission. In this case, the probability of detecting the
intranight variability is within 20-80%, depending on the ratio of the disk to
the jet optical luminosity. Variable X-ray irradiation mechanism is also
possible but only under additional requirement: either the source should have a
very narrow Hbeta line or occasional extremely strong flares should appear at
very large disk radii.


  We compare the thermal escape rates of a Brownian particle, initially trapped
into one of the two wells of an asymmetric double-well potential, for thermal
Markovian and non-Markovian noise. The Markovian treatment of this problem goes
originally back to the studies of Kramers in 1940 and is therefore often
referred to as "Kramers's escape rate problem". We solve the generalized
Langevin equation for the trajectories of the particles numerically and
analytically for both limiting cases, Markovian and non-Markovian thermal
noise. We compute the escape rate and work out the fundamental differences
arising from finite correlation times of the thermal noise.


  Artificial intelligence (AI) can improve human decision-making in various
application areas. Ideally, collaboration between humans and AI should lead to
complementary team performance (CTP) -- a level of performance that neither of
them can attain individually. So far, however, CTP has rarely been observed,
suggesting an insufficient understanding of the complementary constituents in
human-AI collaboration that can contribute to CTP in decision-making. This work
establishes a holistic theoretical foundation for understanding and developing
human-AI complementarity. We conceptualize complementarity by introducing and
formalizing the notion of complementarity potential and its realization.
Moreover, we identify and outline sources that explain CTP. We illustrate our
conceptualization by applying it in two empirical studies exploring two
different sources of complementarity potential. In the first study, we focus on
information asymmetry as a source and, in a real estate appraisal use case,
demonstrate that humans can leverage unique contextual information to achieve
CTP. In the second study, we focus on capability asymmetry as an alternative
source, demonstrating how heterogeneous capabilities can help achieve CTP. Our
work provides researchers with a theoretical foundation of complementarity in
human-AI decision-making and demonstrates that leveraging sources of
complementarity potential constitutes a viable pathway toward effective
human-AI collaboration.


  In the spirit of an earlier result of M\"uller on the Heisenberg group we
prove a restriction theorem on a certain class of two step nilpotent Lie
groups. Our result extends that of M\"uller also in the framework of the
Heisenberg group.


  We study the dependence of the dimensional character of the charge-density
wave (CDW) in TiSe$_2$ by a controlled variation of the number of available
charge carriers in the conduction band. A change of dimensionality is realised
by H2O exposure and monitored by angle-resolved photoelectron spectroscopy. The
CDW spanning vector changes from 2x2x1 towards 1x1x2 in a narrow population
range, just before a complete suppression of the CDW. Our findings enable a new
view on the excitonic origin of the CDW, the relation between CDW spanning
vector and periodic lattice distortion, and suggest modifications in the
picture of the recently discovered chirality of the CDW.


  In weak-lensing cosmological studies, peak statistics is sensitive to
nonlinear structures and thus complementary to cosmic shear two-point
correlations. In this paper, we explore a new approach, namely, the peak
steepness statistics, with the overall goal to understand the cosmological
information embedded there in comparison with the commonly used peak height
statistics. We perform the analyses with ray-tracing simulations considering
different sets of cosmological parameters $\Omega_{\rm m}$ and $\sigma_8$. A
theoretical model to calculate the abundance of high peaks based on steepness
is also presented, which can well describe the main trend of the peak
distribution from simulations. We employ $\Delta\chi^2$ and Fisher analyses to
study the cosmological dependence of the two peak statistics using our limited
sets of simulations as well as our theoretical model. Within our considerations
without including potential systematic effects, the results show that the
steepness statistics tends to have higher sensitivities to the cosmological
parameters than the peak height statistics and this advantage is diluted with
the increase of the shape noise. Using the theoretical model, we investigate
the physical reasons accounting for the different cosmological information
embedded in the two statistics. Our analyses indicate that the projection
effect from large-scale structures plays an important role to enhance the gain
from the steepness statistics. The redshift and cosmology dependence of dark
matter halo density profiles also contributes to the differences between the
two statistics.


  Why Bi2Sr2CaCu2Ox (Bi2212) allows high critical current density Jc in round
wires rather than only in the anisotropic tape form demanded by all other high
temperature superconductors is important for future magnet applications. Here
we compare the local texture of state-of-the-art Bi2212 and Bi2223
((Bi,Pb)2Sr2Ca2Cu3O10), finding that round wire Bi2212 generates a dominant
a-axis growth texture that also enforces a local biaxial texture (FWHM
<15{\deg}) while simultaneously allowing the c-axes of its polycrystals to
rotate azimuthally along and about the filament axis so as to generate
macroscopically isotropic behavior. By contrast Bi2223 shows only a uniaxial
(FWHM <15{\deg}) c-axis texture perpendicular to the tape plane without any
in-plane texture. Consistent with these observations, a marked,
field-increasing, field-decreasing Jc(H) hysteresis characteristic of
weak-linked systems appears in Bi2223 but is absent in Bi2212 round wire.
Growth-induced texture on cooling from the melt step of the Bi2212 Jc
optimization process appears to be the key step in generating this highly
desirable microstructure.


  When personal, assistive, and interactive robots make mistakes, humans
naturally and intuitively correct those mistakes through physical interaction.
In simple situations, one correction is sufficient to convey what the human
wants. But when humans are working with multiple robots or the robot is
performing an intricate task often the human must make several corrections to
fix the robot's behavior. Prior research assumes each of these physical
corrections are independent events, and learns from them one-at-a-time.
However, this misses out on crucial information: each of these interactions are
interconnected, and may only make sense if viewed together. Alternatively,
other work reasons over the final trajectory produced by all of the human's
corrections. But this method must wait until the end of the task to learn from
corrections, as opposed to inferring from the corrections in an online fashion.
In this paper we formalize an approach for learning from sequences of physical
corrections during the current task. To do this we introduce an auxiliary
reward that captures the human's trade-off between making corrections which
improve the robot's immediate reward and long-term performance. We evaluate the
resulting algorithm in remote and in-person human-robot experiments, and
compare to both independent and final baselines. Our results indicate that
users are best able to convey their objective when the robot reasons over their
sequence of corrections.


  The scientific process of earthquake forecasting involves estimating the
probability and intensity of earthquakes in a specific area within a certain
timeframe, based on seismic activity laws and observational data. Epidemic-Type
Aftershock Sequence (ETAS) models, which rely on seismic empirical laws, is one
of the most commonly used methods for earthquake forecasting. However, it
underestimates feature in short-term time scale and overestimates in long-term
time scale. Convolutional Long Short-Term Memory (ConvLSTM), has emerged as a
promising approach capable of extracting spatio-temporal features. Hence, we
propose a novel composite model named CL-ETAS model, which combines the
strengths of ConvLSTM and ETAS model. We conduct experimental verification on
real seismic data in Southern California. Our results show that CL-ETAS model
outperforms both ETAS model and ConvLstm in accurately forecasting the number
of earthquake events, their magnitude, and spatial distribution. Additionally,
CL-ETAS model demonstrates notable enhancements in forecast stability and
interpretability. These results offer valuable insights and recommendations for
future earthquake forecasting endeavors.


  We analyze the inverse spectral problem on the half line associated with
elastic surface waves. Here, we extend the treatment of Love waves [arXiv:
1908.10529] to Rayleigh waves. Under certain conditions, and assuming that the
Poisson ratio is constant, we establish uniqueness and present a reconstruction
scheme for the S-wave speed with multiple wells from the semiclassical spectrum
of these waves.


  We consider the problem of identifying any $k$ out of the best $m$ arms in an
$n$-armed stochastic multi-armed bandit. Framed in the PAC setting, this
particular problem generalises both the problem of `best subset selection' and
that of selecting `one out of the best m' arms [arcsk 2017]. In applications
such as crowd-sourcing and drug-designing, identifying a single good solution
is often not sufficient. Moreover, finding the best subset might be hard due to
the presence of many indistinguishably close solutions. Our generalisation of
identifying exactly $k$ arms out of the best $m$, where $1 \leq k \leq m$,
serves as a more effective alternative. We present a lower bound on the
worst-case sample complexity for general $k$, and a fully sequential PAC
algorithm, \GLUCB, which is more sample-efficient on easy instances. Also,
extending our analysis to infinite-armed bandits, we present a PAC algorithm
that is independent of $n$, which identifies an arm from the best $\rho$
fraction of arms using at most an additive poly-log number of samples than
compared to the lower bound, thereby improving over [arcsk 2017] and
[Aziz+AKA:2018]. The problem of identifying $k > 1$ distinct arms from the best
$\rho$ fraction is not always well-defined; for a special class of this
problem, we present lower and upper bounds. Finally, through a reduction, we
establish a relation between upper bounds for the `one out of the best $\rho$'
problem for infinite instances and the `one out of the best $m$' problem for
finite instances. We conjecture that it is more efficient to solve `small'
finite instances using the latter formulation, rather than going through the
former.


  The clustering coefficient, path length and average vertex degree of two
urban train line networks have been calculated. The results are compared with
theoretical predictions for appropriate random bipartite graphs. They have also
been compared with one another to investigate the effect of architecture on the
small-world properties.


  Given integers $ n \ge k >l \ge 1 $ and a $k$-graph $F$ with $|V(F)|$
divisible by $n$, define $t_l^k(n,F)$ to be the smallest integer $d$ such that
every $k$-graph $H$ of order $n$ with minimum $l$-degree $\delta_l(H) \ge d $
contains an $F$-factor. A classical theorem of Hajnal and Szemer\'{e}di implies
that $t^2_1(n,K_t) = (1-1/t)n$ for integers $t$. For $k \ge 3$,
$t^k_{k-1}(n,K_k^k)$ (the $\delta_{k-1}(H)$ threshold for perfect matchings)
has been determined by K\"{u}hn and Osthus (asymptotically) and R\"{o}dl,
Ruci\'{n}ski and Szemer\'{e}di (exactly) for large $n$.
  In this paper, we generalise the absorption technique of R\"{o}dl,
Ruci\'{n}ski and Szemer\'{e}di to $F$-factors. We determine the asymptotic
values of $t^k_1(n,K_k^k(m))$ for $k = 3,4$ and $m \ge 1$. In addition, we show
that for $t>k = 3$ and $\gamma >0$, $ t^3_{2}(n,K_t^3) \le (1-
\frac{2}{t^2-3t+4} + \gamma) n$ provided $n$ is large and $t | n$. We also
bound $t^3_{2}(n,K_t^3)$ from below. In particular, we deduce that
$t^3_2(n,K_4^3) = (3/4+o(1))n$ answering a question of Pikhurko. In addition,
we prove that $t^k_{k-1}(n,K_t^k) \le (1- \binom{t-1}{k-1}^{-1} + \gamma)n$ for
$\gamma >0$, $k \ge 6$ and $t \ge (3+ \sqrt5)k/2$ provided $n$ is large and $t
| n$.


  Privacy in form of anonymous communication could be comparably both faster
and harder to break in optical routers than in today's anonymous IP networks
based on The Onion Routing (Tor). Implementing the practical privacy
alloptically,however, is not straightforward, as it requires key generation in
each anonymization node to avoid distribution of long keys, and layered
encryption, both at the optical line rate. Due to the unavailability of
cryptographically strong optical key generation and encryption components, not
only a layered encryption is a challenge, but an optical encryption in general.
In this paper, we address the challenges of optical anonymous networking for
the first time from the system's perspective, and discuss options for practical
implementation of all-optical layered encryption. To this end, we propose an
optical anonymization component realized with the state-of-the-art optical XOR
logic and optical Linear Feedback Shift Registers (oLFSRs). Given that LFSR
alone is known for its weak cryptographic security due to its linear
properties, we propose an implementation with parallel oLFSRs and analyze the
resulting computational security. The results show that proposed optical
anonymization component is promising as it can be practically realized to
provide a high computational security against deanonymization (privacy) attack.


  Entropy dimension is an entropy-type quantity which takes values in $[0,1]$
and classifies different levels of intermediate growth rate of complexity for
dynamical systems. In this paper, we consider the complexity of skew products
of irrational rotations with Bernoulli systems, which can be viewed as
deterministic walks in random sceneries, and show that this class of models can
have any given entropy dimension by choosing suitable rotations for the base
system.


  We examine the sum of modified Bessel functions with argument depending
quadratically on the summation index given by \[S_\nu(a)=\sum_{n\geq 1}
(\frac{1}{2} an^2)^{-\nu} K_\nu(an^2)\qquad (|\arg\,a|<\pi/2)\] as the
parameter $|a|\to 0$. It is shown that the positive real $a$-axis is a Stokes
line, where an infinite number of increasingly subdominant exponentially small
terms present in the asymptotic expansion undergo a smooth, but rapid,
transition as this ray is crossed. Particular attention is devoted to the
details of the expansion on the Stokes line as $a\to 0$ through positive
values. Numerical results are presented to support the asymptotic theory.


  In this study we considered five generalizations of the standard Weibull
distribution to describe the lifetime of two important components of harvest
sugarcane machines. The harvesters considered in the analysis does the harvest
of an average of 20 tons of sugarcane per hour and their malfunction may lead
to major losses, therefore, an effective maintenance approach is of main
interesting for cost savings. For the considered distributions, the
mathematical background is presented. Maximum likelihood is used for parameter
estimation. Further, different discrimination procedures were used to obtain
the best fit for each component. At the end, we propose a maintenance
scheduling for the components of the harvesters using predictive analysis.


  The XMM-Newton X-ray observatory performed a pointed observation of the
bursting pulsar GRO J1744-28 in April 2001 for about 10 ks during a program
devoted to the scan of the Galactic center region. After the discovery of this
source by BATSE in December 1995 during a very active bursting phase, it has
been in quiescence since April 1997. We present here the first detection of GRO
J1744-28 in its quiescent state at a position which is consistent with previous
high-energy positions (but not consistent with a proposed IR counterpart). The
observed luminosity of the source in quiescence is about 6 orders of magnitude
weaker than the luminosity in outburst.


  Death benefits are generally the largest cash flow item that affects
financial statements of life insurers where some still do not have a systematic
process to track and monitor death claims experience. In this article, we
explore data clustering to examine and understand how actual death claims
differ from expected, an early stage of developing a monitoring system crucial
for risk management. We extend the $k$-prototypes clustering algorithm to draw
inference from a life insurance dataset using only the insured's
characteristics and policy information without regard to known mortality. This
clustering has the feature to efficiently handle categorical, numerical, and
spatial attributes. Using gap statistics, the optimal clusters obtained from
the algorithm are then used to compare actual to expected death claims
experience of the life insurance portfolio. Our empirical data contains
observations, during 2014, of approximately 1.14 million policies with a total
insured amount of over 650 billion dollars. For this portfolio, the algorithm
produced three natural clusters, with each cluster having a lower actual to
expected death claims but with differing variability. The analytical results
provide management a process to identify policyholders' attributes that
dominate significant mortality deviations, and thereby enhance decision making
for taking necessary actions.


  Unique to certain unconventional superconductors is the coexistence of
magnetism and superconductivity. We have previously found ferromagnetism and
superconductivity in hydrogenated graphitic materials. Herein we present
similar as well as completely new findings this time applicable to hydrogenated
graphite foils. As the strength of the magnetic field is increased, the
temperature-dependent magnetization shows several important transitions. From a
Neel paramagnetic-antiferromagnetic transition, to a ferromagnetic
superconductor state, to an orbital paramagnetic glass high-temperature
superconductor with critical temperature for the dominant phase at Tc = 50 to
60 K. The ferromagnetic state is observed up to room temperature. Thus, the
magnetism of hydrogenated low-density carbon graphite foils plays an important
role in establishing electronic correlations of which some are superconducting
in nature.


  We consider the one-dimensional Schroedinger equation on a ring, with the
cubic term, of either self-attractive or repulsive sign, confined to a narrow
segment. This setting can be realized in optics and Bose-Einstein condensates.
For the nonlinearity coefficient represented by the delta-function, all
stationary states are obtained in an exact analytical form. The states with
positive chemical potentials are found in alternating bands for the cases of
the self-repulsion and attraction, while solutions with negative chemical
potentials exist only in the latter case. These results provide a possibility
to obtain exact solutions for bandgap states in the nonlinear system.
Approximating the delta-function by a narrow Gaussian, stability of the
stationary modes is addressed through numerical computation of eigenvalues for
small perturbations, and verified by simulations of the perturbed evolution.
For positive chemical potentials, the stability is investigated in three lowest
bands. In the case of the self-attraction, each band contains a stable subband,
the transition to instability occurring with the increase of the total norm. As
a result, multi-peak states may be stable in higher bands. In the case of the
self-repulsion, a single-peak ground state is stable in the first band, while
the two higher ones are populated by weakly unstable two- and four-peak excited
states. In the case of the self-attraction and negative chemical potentials,
single-peak modes feature instability which transforms them into persistently
oscillating states.


  We introduce SELF-DISCOVER, a general framework for LLMs to self-discover the
task-intrinsic reasoning structures to tackle complex reasoning problems that
are challenging for typical prompting methods. Core to the framework is a
self-discovery process where LLMs select multiple atomic reasoning modules such
as critical thinking and step-by-step thinking, and compose them into an
explicit reasoning structure for LLMs to follow during decoding. SELF-DISCOVER
substantially improves GPT-4 and PaLM 2's performance on challenging reasoning
benchmarks such as BigBench-Hard, grounded agent reasoning, and MATH, by as
much as 32% compared to Chain of Thought (CoT). Furthermore, SELF-DISCOVER
outperforms inference-intensive methods such as CoT-Self-Consistency by more
than 20%, while requiring 10-40x fewer inference compute. Finally, we show that
the self-discovered reasoning structures are universally applicable across
model families: from PaLM 2-L to GPT-4, and from GPT-4 to Llama2, and share
commonalities with human reasoning patterns.


  The performance of sensor arrays in sensing and wireless communications
improves with more elements, but this comes at the cost of increased energy
consumption and hardware expense. This work addresses the challenge of
selecting $k$ sensor elements from a set of $m$ to optimize a generic
Quality-of-Service metric. Evaluating all $\binom{m}{k}$ possible sensor
subsets is impractical, leading to prior solutions using convex relaxations,
greedy algorithms, and supervised learning approaches. The current paper
proposes a new framework that employs deep generative modeling, treating sensor
selection as a deterministic Markov Decision Process where sensor subsets of
size $k$ arise as terminal states. Generative Flow Networks (GFlowNets) are
employed to model an action distribution conditioned on the state. Sampling
actions from the aforementioned distribution ensures that the probability of
arriving at a terminal state is proportional to the performance of the
corresponding subset. Applied to a standard sensor selection scenario, the
developed approach outperforms popular methods which are based on convex
optimization and greedy algorithms. Finally, a multiobjective formulation of
the proposed approach is adopted and applied on the sparse antenna array design
for Integrated Sensing and Communication (ISAC) systems. The multiobjective
variation is shown to perform well in managing the trade-off between radar and
communication performance.


  Traditional spectral analysis methods are increasingly challenged by the
exploding volumes of data produced by contemporary astronomical surveys. In
response, we develop deep-Regularized Ensemble-based Multi-task Learning with
Asymmetric Loss for Probabilistic Inference ($\rm{deep-REMAP}$), a novel
framework that utilizes the rich synthetic spectra from the PHOENIX library and
observational data from the MARVELS survey to accurately predict stellar
atmospheric parameters. By harnessing advanced machine learning techniques,
including multi-task learning and an innovative asymmetric loss function,
$\rm{deep-REMAP}$ demonstrates superior predictive capabilities in determining
effective temperature, surface gravity, and metallicity from observed spectra.
Our results reveal the framework's effectiveness in extending to other stellar
libraries and properties, paving the way for more sophisticated and automated
techniques in stellar characterization.


  Consider a stochastic matrix $P$ and diagonal matrix $D.$ In this work, we
introduce Tilted matrices. A Tilted matrix is the product $D'PD$, where $D'$ is
a diagonal normalization that makes the product stochastic. We then provide
several results on products of Tilted matrices, which can be desirable for
analyses of Markov Decision Processes. Lastly, we obtain a convergence rate
result for the product of Tilted reversible matrices.


  In this paper, we show that the Calabi flow exists as long as the Sobolev
constants and the $L^p$ scalar curvature are uniformly bounded for some $p>n$.


  The spatiotemporal structure of reactive media supporting a solitary spiral
wave is studied for systems where the local reaction law exhibits a
period-doubling cascade to chaos. This structure is considerably more complex
than that of simple period-1 oscillatory media. As one moves from the core of
the spiral wave the local dynamics takes the form of perturbed period-doubled
orbits whose character varies with spatial location relative to the core. An
important feature of these media is the existence of a curve where the local
dynamics is effectively period-1. This curve arises as a consequence of the
necessity to reconcile the conflict between the global topological organization
of the medium induced by the presence of a spiral wave and the topological
phase space structure of local orbits determined by the reaction rate law. Due
to their general topological nature, the phenomena described here should be
observable in a broad class of systems with complex periodic behavior.


  We consider integrals $\tau_{\rho}=\int_0^1\rho\xi^2\,dx$, where $\xi$ is
Wiener process and $\rho$ is generalized function from some class of
multipliers. In the case when multiplier $\rho$ belongs to the trace-class, it
is shown that $\tau_{\rho}$ has $\chi^2$-distribution (or analogous). An
example of multiplier $\rho$ not belonging to the trace-class is constructed.


  The joint density of states (JDOS) of Bi2Sr2CaCu2O8+x is calculated by
evaluating the autocorrelation of the single particle spectral function
A(k,omega) measured from angle resolved photoemission spectroscopy (ARPES).
These results are compared with Fourier transformed (FT) conductance
modulations measured by scanning tunneling microscopy (STM). Good agreement
between the two experimental probes is found for two different doping values
examined. In addition, by comparing the FT-STM results to the autocorrelated
ARPES spectra with different photon polarization, new insight on the form of
the STM matrix elements is obtained. This shines new light on unsolved
mysteries in the tunneling data.


  Given a finite field $\F_q$ and $n\in \N^*$, one could try to compute all
polynomial endomorphisms $\F_q^n\lp \F_q^n$ up to a certain degree with a
specific property. We consider the case $n=3$. If the degree is low (like 2,3,
or 4) and the finite field is small ($q\leq 7$) then some of the computations
are still feasible. In this article we study the following properties of
endomorphisms: being a bijection of $\F_q^n\lp \F_q^n$, being a polynomial
automorphism, being a {\em Mock automorphism}, and being a locally finite
polynomial automorphism. In the resulting tables, we point out a few
interesting objects, and pose some interesting conjectures which surfaced
through our computations.


  Human-Object Interaction (HOI) detection plays a vital role in scene
understanding, which aims to predict the HOI triplet in the form of <human,
object, action>. Existing methods mainly extract multi-modal features (e.g.,
appearance, object semantics, human pose) and then fuse them together to
directly predict HOI triplets. However, most of these methods focus on seeking
for self-triplet aggregation, but ignore the potential cross-triplet
dependencies, resulting in ambiguity of action prediction. In this work, we
propose to explore Self- and Cross-Triplet Correlations (SCTC) for HOI
detection. Specifically, we regard each triplet proposal as a graph where
Human, Object represent nodes and Action indicates edge, to aggregate
self-triplet correlation. Also, we try to explore cross-triplet dependencies by
jointly considering instance-level, semantic-level, and layout-level relations.
Besides, we leverage the CLIP model to assist our SCTC obtain interaction-aware
feature by knowledge distillation, which provides useful action clues for HOI
detection. Extensive experiments on HICO-DET and V-COCO datasets verify the
effectiveness of our proposed SCTC.


  We study the tropicalization of intersections of plane curves, under the
assumption that they have the same tropicalization. We show that the set of
tropical divisors that arise in this manner is a pure dimensional balanced
polyhedral complex and compute its dimension. When the genus is at most 1, we
show that all the tropical divisors that move in the expected dimension are
realizable. As part of the proof, we introduce a combinatorial tool for
explicitly constructing large families of realizable tropical divisors.


  Thermophysical properties of hydrogen, helium, and hydrogen-helium mixtures
have been investigated in the warm dense matter regime at electron number
densities ranging from $6.02\times10^{29}\sim2.41\times10^{30}$/m$^{3}$ and
temperatures from 4000 to 20000 K via quantum molecular dynamics simulations.
We focus on the dynamical properties such as the equation of states, diffusion
coefficients, and viscosity. Mixing rules (density matching, pressure matching,
and binary ionic mixing rules) have been validated by checking composite
properties of pure species against that of the fully interacting mixture
derived from QMD simulations. These mixing rules reproduce pressures within 10%
accuracy, while it is 75% and 50% for the diffusion and viscosity,
respectively. Binary ionic mixing rule moves the results into better agreement.
Predictions from one component plasma model are also provided and discussed.


  In many applications, we are constrained to learn classifiers from very
limited data (few-shot classification). The task becomes even more challenging
if it is also required to identify samples from unknown categories (open-set
classification). Learning a good abstraction for a class with very few samples
is extremely difficult, especially under open-set settings. As a result,
open-set recognition has received minimal attention in the few-shot setting.
However, it is a critical task in many applications like environmental
monitoring, where the number of labeled examples for each class is limited.
Existing few-shot open-set recognition (FSOSR) methods rely on thresholding
schemes, with some considering uniform probability for open-class samples.
However, this approach is often inaccurate, especially for fine-grained
categorization, and makes them highly sensitive to the choice of a threshold.
To address these concerns, we propose Reconstructing Exemplar-based Few-shot
Open-set ClaSsifier (ReFOCS). By using a novel exemplar reconstruction-based
meta-learning strategy ReFOCS streamlines FSOSR eliminating the need for a
carefully tuned threshold by learning to be self-aware of the openness of a
sample. The exemplars, act as class representatives and can be either provided
in the training dataset or estimated in the feature domain. By testing on a
wide variety of datasets, we show ReFOCS to outperform multiple
state-of-the-art methods.


  To make practical quantum algorithms work, large-scale quantum processors
protected by error-correcting codes are required to resist noise and ensure
reliable computational outcomes. However, a major challenge arises from defects
in processor fabrication, as well as occasional losses or cosmic rays during
the computing process, all of which can lead to qubit malfunctions and disrupt
error-correcting codes' normal operations. In this context, we introduce an
automatic adapter to implement the surface code on defective lattices. Unlike
previous approaches, this adapter leverages newly proposed bandage-like
super-stabilizers to save more qubits when defects are clustered, thus
enhancing the code distance and reducing super-stabilizer weight. For instance,
in comparison with earlier methods, with a code size of 27 and a random defect
rate of 2\%, the disabled qubits decrease by $1/3$, and the average preserved
code distance increases by 63\%. This demonstrates a significant reduction in
overhead when handling defects using our approach, and this advantage amplifies
with increasing processor size and defect rates. Our work presents a
low-overhead, automated solution to the challenge of adapting the surface code
to defects, an essential step towards scaling up the construction of
large-scale quantum computers for practical applications.


  The nonlinear Schr\"{o}dinger (NLS) equation can be derived as a formal
approximation equation describing the envelopes of slowly modulated spatially
and temporarily oscillating wave packet-like solutions to the ion Euler-Poisson
equation. In this paper, we rigorously justify such approximation by giving
error estimates in Sobolev norms between exact solutions of the ion
Euler-Poisson system and the formal approximation obtained via the NLS
equation. The justification consists of several difficulties such as the
resonances and loss of regularity, due to the quasilinearity of the problem.
These difficulties are overcome by introducing normal form transformation and
cutoff functions and carefully constructed energy functional of the equation.


  Blind Image Quality Assessment (BIQA) is essential for automatically
evaluating the perceptual quality of visual signals without access to the
references. In this survey, we provide a comprehensive analysis and discussion
of recent developments in the field of BIQA. We have covered various aspects,
including hand-crafted BIQAs that focus on distortion-specific and
general-purpose methods, as well as deep-learned BIQAs that employ supervised
and unsupervised learning techniques. Additionally, we have explored multimodal
quality assessment methods that consider interactions between visual and audio
modalities, as well as visual and text modalities. Finally, we have offered
insights into representative BIQA databases, including both synthetic and
authentic distortions. We believe this survey provides valuable understandings
into the latest developments and emerging trends for the visual quality
community.


  We consider the mixed $q$-Gaussian algebras introduced by Speicher which are
generated by the variables $X_i=l_i+l_i^*,i=1,\ldots,N$, where $l_i^*
l_j-q_{ij}l_j l_i^*=\delta_{i,j}$ and $-1<q_{ij}=q_{ji}<1$. Using the free
monotone transport theorem of Guionnet and Shlyakhtenko, we show that the mixed
$q$-Gaussian von Neumann algebras are isomorphic to the free group von Neumann
algebra $L(\mathbb{F}_N)$, provided that $\max_{i,j}|q_{ij}|$ is small enough.
The proof relies on some estimates which are generalizations of Dabrowski's
results for the special case $q_{ij}\equiv q$.


  We present a new method for generating robust guesses for unstable periodic
orbits (UPOs) by post-processing turbulent data using dynamic mode
decomposition (DMD). The approach relies on the identification of near-neutral,
repeated harmonics in the DMD eigenvalue spectrum from which both an estimate
for the period of a nearby UPO and a guess for the velocity field can be
constructed. In this way, the signature of a UPO can be identified in a short
time series without the need for a near recurrence to occur, which is a
considerable drawback to recurrent flow analysis, the current state-of-the-art.
We first demonstrate the method by applying it to a known (simple) UPO and find
that the period can be reliably extracted even for time windows of length one
quarter of the full period. We then turn to a long turbulent trajectory,
sliding an observation window through the time series and performing many DMD
computations. Our approach yields many more converged periodic orbits
(including multiple new solutions) than a standard recurrent flow analysis of
the same data. Furthermore, it also yields converged UPOs at points where the
recurrent flow analysis flagged a near recurrence but the Newton solver did not
converge, suggesting that the new approach can be used alongside the old to
generate improved initial guesses. Finally, we discuss some heuristics on what
constitutes a "good" time window for the DMD to identify a UPO.


  Violent stochastic collisional events have been invoked as a possible
explanation for some debris discs displaying pronounced asymmetries or having a
great luminosity excess. So far, no thorough modelling of the consequences of
such events has been carried out, mainly because of the extreme numerical
challenge of coupling the dynamical and collisional evolution of dust.
  We perform the first fully self-consistent modelling of the aftermath of
massive breakups in debris discs. We follow the collisional and dynamical
evolution of dust released after the breakup of a Ceres-sized body at 6 AU from
its central star. We investigate the duration, magnitude and spatial structure
of the signature left by such a violent event, as well as its observational
detectability.
  We use the recently developed LIDT-DD code (Kral et al., 2013), which handles
the coupled collisional and dynamical evolution of debris discs. The main focus
is placed on the complex interplay between destructive collisions, Keplerian
dynamics and radiation pressure forces. We use the GRaTer package to estimate
the system's luminosity at different wavelengths.
  The breakup of a Ceres-sized body at 6 AU creates an asymmetric dust disc
that is homogenized, by the coupled action of collisions and dynamics, on a
timescale of a few $10^5$ years. The luminosity excess in the breakup's
aftermath should be detectable by mid-IR photometry, from a 30 pc distance,
over a period of $\sim 10^6$ years that exceeds the duration of the asymmetric
phase of the disc (a few $10^5$ years). As for the asymmetric structures, we
derive synthetic images for the SPHERE/VLT and MIRI/JWST instruments, showing
that they should be clearly visible and resolved from a 10 pc distance. Images
at 1.6$\mu$m (marginally), 11.4 and 15.5$\mu$m would show the inner disc
structures while 23$\mu$m images would display the outer disc asymmetries.


  We introduce a new class of combinatorial markets in which agents have
covering constraints over resources required and are interested in delay
minimization. Our market model is applicable to several settings including
scheduling, cloud computing, and communicating over a network. This model is
quite different from the traditional models, to the extent that neither do the
classical equilibrium existence results seem to apply to it nor do any of the
efficient algorithmic techniques developed to compute equilibria seem to apply
directly. We give a proof of existence of equilibrium and a polynomial time
algorithm for finding one, drawing heavily on techniques from LP duality and
submodular minimization. We observe that in our market model, the set of
equilibrium prices could be a connected, non-convex set. To the best of our
knowledge, this is the first natural example of the phenomenon where the set of
solutions could have such complicated structure, yet there is a combinatorial
polynomial time algorithm to find one. Finally, we show that our model inherits
many of the fairness properties of traditional equilibrium models.


  We prove the following result:
  Let B be a smooth, irreducible, quasi-projective variety over the complex
numbers and assume that B has a projective compactification \bar{B} such that
\bar{B} - B is of codimension at least two in \bar{B}. Then there exists a
family of smooth ireducible curves {C_q}_{q \in Q} in B parametrised by an
irreducible variety Q such that if p: A \to B is an abelian scheme and q \in Q
is a generic point, then the restriction map on sections A(B) \to A(C_q) is an
isomorphism.
  This answers, in a special case, a question of Graber, Harris, Mazur and
Starr.