  Ising machines are dedicated hardware solvers of NP-hard optimization
problems. However, they do not always find the most optimal solution. The
probability of finding this optimal solution depends on the problem at hand.
Using continuation methods, we show that this is closely linked to the
bifurcation sequence of the optimal solution. From this bifurcation analysis,
we can determine the effectiveness of solution schemes. Moreover, we find that
the proper choice of implementation of the Ising machine can drastically change
this bifurcation sequence and therefore vastly increase the probability of
finding the optimal solution.


  We present results on rapidity and transverse momentum distributions of
inclusive charm quark production in heavy-ion collisions at RHIC, including the
next-to-leading order, $O(\alpha_s^3)$, radiative corrections and the nuclear
shadowing effect. We find the effective, nuclear K-factor to be $K(y)\approx
1.4$ for $\mid y\mid \leq 3$ in the rapidity distribution, while $1\leq
K(p_{T}) \leq 3$ for $1GeV\leq p_T \leq 6GeV$ in the $p_T$ distribution. We
incorporate multiple parton scatterings in our calculation of the fraction of
all central events that contain at least one charm quark pair. We obtain the
effective $A$-dependence of the charm cross sections. Finally, we comment on
the possibility of detecting the quark-gluon plasma signal as an enhanced charm
production in heavy-ion collisions at RHIC.


  Modern observations of the interstellar medium (ISM) in galaxies detect a
variety of atomic and molecular species. The goal is to connect these
observations to the astrochemical properties of the ISM. 3D hydro-chemical
simulations attempt this but due to extreme computational cost, they have to
rely on simplified chemical networks and are bound to individual case studies.
We present an alternative approach which models the ISM at larger scales by an
ensemble of pre-calculated 1D thermo-chemical photodissociation region (PDR)
calculations that determine the abundance and excitation of atomic and
molecular species. We adopt lognormal distributions of column density (\avpdf
s) for which each column density is linked to a volume density as derived by
hydrodynamical simulations. We consider two lognormal {\avpdf}s: a diffuse, low
density medium with average visual extinction of $\overline{{\rm
A}_V}=0.75\,{\rm mag}$ and dispersion of $\sigma=0.5$ and a denser giant
molecular cloud with $\overline{{\rm A}_V}=4\,{\rm mag}$ and $\sigma=0.8$. We
treat the UV radiation field, cosmic-ray ionization rate and metallicity as
free parameters. We find that the low density medium remains fully HI- and
CII-dominated under all explored conditions. The denser cloud remains almost
always molecular (i.e. H$_2$-dominated) while its carbon phase (CO, CI and CII)
is sensitive to the above free parameters, implying that existing methods of
tracing H$_2$-rich gas may require adjustments depending on environment. Our
numerical framework can be used to estimate the PDR properties of large ISM
regions and quantify trends with different environmental parameters as it is
fast, covers wide parameter space, and is flexible for extensions.


  We present a study of the escape time from a metastable state of an
overdamped Brownian particle, in the presence of colored noise generated by
Ornstein-Uhlenbeck process. We analyze the role of the correlation time on the
enhancement of the mean first passage time through a potential barrier and on
the behavior of the mean growth rate coefficient as a function of the noise
intensity. We observe the noise enhanced stability effect for all the initial
unstable states used, and for all values of the correlation time $\tau_c$
investigated. We can distinguish two dynamical regimes characterized by weak
and strong correlated noise respectively, depending on the value of $\tau_c$
with respect to the relaxation time of the system.


  We prove a global Torelli theorem for pairs (Y,D), where Y is a smooth
projective rational surface and D is an effective anti-canonical divisor which
is a cycle of rational curves. This Torelli theorem was conjectured by Friedman
in 1984. In addition, we construct natural universal families for such pairs.


  The need for consistent treatment of uncertainty has recently triggered
increased interest in probabilistic deep learning methods. However, most
current approaches have severe limitations when it comes to inference, since
many of these models do not even permit to evaluate exact data likelihoods.
Sum-product networks (SPNs), on the other hand, are an excellent architecture
in that regard, as they allow to efficiently evaluate likelihoods, as well as
arbitrary marginalization and conditioning tasks. Nevertheless, SPNs have not
been fully explored as serious deep learning models, likely due to their
special structural requirements, which complicate learning. In this paper, we
make a drastic simplification and use random SPN structures which are trained
in a "classical deep learning manner", i.e. employing automatic
differentiation, SGD, and GPU support. The resulting models, called RAT-SPNs,
yield prediction results comparable to deep neural networks, while still being
interpretable as generative model and maintaining well-calibrated
uncertainties. This property makes them highly robust under missing input
features and enables them to naturally detect outliers and peculiar samples.


  Content moderation (removing or limiting the distribution of posts based on
their contents) is one tool social networks use to fight problems such as
harassment and disinformation. Manually screening all content is usually
impractical given the scale of social media data, and the need for nuanced
human interpretations makes fully automated approaches infeasible. We consider
content moderation from the perspective of technology-assisted review (TAR): a
human-in-the-loop active learning approach developed for high recall retrieval
problems in civil litigation and other fields. We show how TAR workflows, and a
TAR cost model, can be adapted to the content moderation problem. We then
demonstrate on two publicly available content moderation data sets that a TAR
workflow can reduce moderation costs by 20% to 55% across a variety of
conditions.


  Misinformation has disruptive effects on our lives. Many researchers have
looked into means to identify and combat misinformation in text or data
visualization. However, there is still a lack of understanding of how
misinformation can be introduced when text and visualization are combined to
tell data stories, not to mention how to improve the lay public's awareness of
possible misperceptions about facts in narrative visualization. In this paper,
we first analyze where misinformation could possibly be injected into the
production-consumption process of data stories through a literature survey.
Then, as a first step towards combating misinformation in data stories, we
explore possible defensive design methods to enhance the reader's awareness of
information misalignment when data facts are scripted and visualized. More
specifically, we conduct a between-subjects crowdsourcing study to investigate
the impact of two design methods enhancing text-visualization integration,
i.e., explanatory annotation and interactive linking, on users' awareness of
misinformation in data stories. The study results show that although most
participants still can not find misinformation, the two design methods can
significantly lower the perceived credibility of the text or visualizations.
Our work informs the possibility of fighting an infodemic through defensive
design methods.


  The number of atoms in the four ribonucleotides uridine monophosphate,
cytidine monophosphate, adenine monophosphate and guanine monophosphate is
taken as a key parameter. A mathematical relation describing the condensation
of the three basic subunits a nucleobase, a ribose and a phosphate group, to
form a ribonucleotide, is first obtained from this parameter. Next, the use of
the latter and Euler totient function is shown to lead to the atom number
content of the 64 codons and also to Rakocevic pattern. Finally, selected
finite sums of Fibonacci numbers are shown to lead to the nucleon number
content of the amino acids in various degeneracy patterns, and also to the
multiplet structure of the 20 amino acids as well as to the degeneracy.


  The Kerr-Taub-NUT spacetime in the Kaluza-Klein theory represents a localized
stationary and axisymmetric object in four dimensions from the Kaluza-Klein
viewpoint. That is, it harbors companion electromagnetic and dilaton fields,
thereby showing up the signature of the extra fifth dimension. We explore the
separability structure of this spacetime and show that the Hamilton-Jacobi
equation for geodesics admits the complete separation of variables only for
massless geodesics. This implies the existence of the hidden symmetries in the
spacetime, which are generated by the conformal Killing tensor. Using a simple
trick built up on a conformally related metric (an "effective" metric) with the
Killing tensor, we construct the explicit expression for the conformal Killing
tensor.


  Given an image and a target modification (e.g an image of the Eiffel tower
and the text "without people and at night-time"), Compositional Image Retrieval
(CIR) aims to retrieve the relevant target image in a database. While
supervised approaches rely on annotating triplets that is costly (i.e. query
image, textual modification, and target image), recent research sidesteps this
need by using large-scale vision-language models (VLMs), performing Zero-Shot
CIR (ZS-CIR). However, state-of-the-art approaches in ZS-CIR still require
training task-specific, customized models over large amounts of image-text
pairs. In this work, we propose to tackle CIR in a training-free manner via our
Compositional Image Retrieval through Vision-by-Language (CIReVL), a simple,
yet human-understandable and scalable pipeline that effectively recombines
large-scale VLMs with large language models (LLMs). By captioning the reference
image using a pre-trained generative VLM and asking a LLM to recompose the
caption based on the textual target modification for subsequent retrieval via
e.g. CLIP, we achieve modular language reasoning. In four ZS-CIR benchmarks, we
find competitive, in-part state-of-the-art performance - improving over
supervised methods. Moreover, the modularity of CIReVL offers simple
scalability without re-training, allowing us to both investigate scaling laws
and bottlenecks for ZS-CIR while easily scaling up to in parts more than double
of previously reported results. Finally, we show that CIReVL makes CIR
human-understandable by composing image and text in a modular fashion in the
language domain, thereby making it intervenable, allowing to post-hoc re-align
failure cases. Code will be released upon acceptance.


  Thermodynamic and electronic properties are obtained for a lattice-gas model
fluid with self-consistent, partial, occupation of its sites; the self
consistency consists in obtaining ionic configurations from grand-canonical
Monte Carlo simulations based on fits to the exact, electronic, tight-binding
energies of isothermal ensembles of those same ionic configurations. The energy
of an ion is found to be a concave-up function of its local coordination.
Liquid-vapor coexistence densities and the electrical conductivity, which shows
a metal-nonmetal transition, have been obtained.


  We introduce a circuit-QED architecture combining fixed-frequency qubits and
microwave-driven couplers. In the appropriate frame, the drive parameters
appear as tunable knobs enabling selective two-qubit coupling and
coherent-error suppression. We moreover introduce a set of controlled-phase
gates based on drive-amplitude and drive-frequency modulation. We develop a
theoretical framework based on Floquet theory to model microwave-activated
interactions with time-dependent drive parameters, which we also use for pulse
shaping. We perform numerical simulations of the gate fidelity for realistic
circuit parameters, and discuss the impact of drive-induced decoherence. We
estimate average gate fidelities beyond $99.9\%$ for all-microwave
controlled-phase operations with gate times in the range $50-120\,\mathrm{ns}$.
These two-qubit gates can operate over a large drive-frequency bandwidth and in
a broad range of circuit parameters, thereby improving extensibility. We
address the frequency allocation problem for this architecture using
perturbation theory, demonstrating that qubit, coupler and drive frequencies
can be chosen such that undesired static and driven interactions remain bounded
in a multi-qubit device. Our numerical methods are useful for describing the
time-evolution of driven systems in the adiabatic limit, and are applicable to
a wide variety of circuit-QED setups.


  In this work we study the predominantly orbital and radial excitations of
hadrons containing a single heavy quark. We present meson and baryon mass
splittings and ratios of meson decay constants (e.g., $f_{B_s}/f_B$ and
$f_{B_s'}/f_{B_s}$) resulting from quenched and dynamical two-flavor
configurations. Light quarks are simulated using the chirally improved (CI)
lattice Dirac operator at valence masses as light as $M_\pi \approx 350$ MeV.
The heavy quark is approximated by a static propagator, appropriate for the $b$
quark on our lattices ($1/a \sim 1-2$ GeV). We also include some preliminary
calculations of the $O(1/m_Q^{})$ kinetic corrections to the states, showing,
in the process, a viable way of applying the variational method to three-point
functions involving excited states. We compare our results with recent
experimental findings.


  Framed in positive terms, this report examines how technical AI research
might be steered in a manner that is more attentive to humanity's long-term
prospects for survival as a species. In negative terms, we ask what existential
risks humanity might face from AI development in the next century, and by what
principles contemporary technical research might be directed to address those
risks.
  A key property of hypothetical AI technologies is introduced, called
\emph{prepotence}, which is useful for delineating a variety of potential
existential risks from artificial intelligence, even as AI paradigms might
shift. A set of \auxref{dirtot} contemporary research \directions are then
examined for their potential benefit to existential safety. Each research
direction is explained with a scenario-driven motivation, and examples of
existing work from which to build. The research directions present their own
risks and benefits to society that could occur at various scales of impact, and
in particular are not guaranteed to benefit existential safety if major
developments in them are deployed without adequate forethought and oversight.
As such, each direction is accompanied by a consideration of potentially
negative side effects.


  In the last few years, the amount of collected data, in various computer
science applications, has grown considerably. These large volumes of data need
to be analyzed in order to extract useful hidden knowledge. This work focuses
on association rule extraction. This technique is one of the most popular in
data mining. Nevertheless, the number of extracted association rules is often
very high, and many of them are redundant. In this paper, we propose a new
algorithm, called PRINCE. Its main feature is the construction of a partially
ordered structure for extracting subsets of association rules, called generic
bases. Without loss of information these subsets form representation of the
whole association rule set. To reduce the cost of such a construction, the
partially ordered structure is built thanks to the minimal generators
associated to frequent closed patterns. The closed ones are simultaneously
derived with generic bases thanks to a simple bottom-up traversal of the
obtained structure. The experimentations we carried out in benchmark and "worst
case" contexts showed the efficiency of the proposed algorithm, compared to
algorithms like CLOSE, A-CLOSE and TITANIC.


  Renormalization group transformations as discussed recently in deriving fixed
point actions are used to analyse the vacuum structure near to the
deconfinement temperature. Monte Carlo configurations are generated using the
fixed point action. We compare equilibrium configurations with configurations
obtained by inverse blocking from a coarser lattice. The absence of short range
vacuum fluctuations in the latter does not influence the string tension. For
the inversely blocked configurations we find the following: (i) the topological
susceptibility chi_top is consistent with the phenomenological value in the
confinement phase, (ii) chi_top drops across the deconfinement transition,
(iii) density and size of instantons are estimated, (iv) the topological
density is found to be correlated to Abelian monopole currents and (v) the
density of spacelike monopole currents becomes a confinement order parameter.


  Given a countable Borel equivalence relation E and a countable group G, we
study the problem of when a Borel action of G on X/E can be lifted to a Borel
action of G on X.


  We study the network reconstruction problem for an epidemic
reaction-diffusion. These models are an extension of deterministic,
compartmental models to a graph setting, where the reactions within the nodes
are coupled by a diffusion. We study the influence of the diffusion rate, and
the network topology, on the reconstruction and prediction problems, both from
a theoretical and experimental standpoint.Results first show that for almost
every network, the reconstruction problem is identifiable. Then, we show that
the faster the diffusion, the harder the reconstruction, but that increasing
the sampling rate may help in this respect.Second, we demonstrate that it is
possible to classify symmetrical networks generating the same trajectories, and
that the prediction problem can still be solved satisfyingly, even when the
network topology makes exact reconstruction difficult.


  We study the long-term evolution of ejecta formed in a binary neutron star
(BNS) merger that results in a long-lived remnant NS by performing a
hydrodynamics simulation with the outflow data of a numerical relativity
simulation as the initial condition. At the homologously expanding phase, the
total ejecta mass reaches $\approx0.1\,M_\odot$ with an average velocity of
$\approx0.1\,c$ and lanthanide fraction of $\approx 0.005$. We further perform
the radiative transfer simulation employing the obtained ejecta profile. We
find that, contrary to a naive expectation from the large ejecta mass and low
lanthanide fraction, the optical emission is not as bright as that in
GW170817/AT2017gfo, while the infrared emission can be brighter. This light
curve property is attributed to preferential diffusion of photons toward the
equatorial direction due to the prolate ejecta morphology, large opacity
contribution of Zr, Y, and lanthanides, and low specific heating rate of the
ejecta. Our results suggest that these light curve features could be used as an
indicator for the presence of a long-lived remnant NS. We also found that the
bright optical emission broadly consistent with GW170817/AT2017gfo is realized
for the case that the high-velocity ejecta components in the polar region are
suppressed. These results suggest that the remnant in GW170817/AT2017gfo is
unlikely to be a long-lived NS, but might have collapsed to a black hole within
${\cal O}(0.1)$ s.


  For a prime number $p\ge 5$, we consider three classical cusp eigenforms
$f_j(z)$ of weights $k_1, k_2, k_3$, of conductors $N_1, N_2, N_3$, and of
nebentypus characters $\psi_j \bmod N_j$. According to H.Hida and R.Coleman,
one can include each $f_j$ into a {$p$-adic analytic family} $k_j \mapsto
\{f_{j,k_j}\}$ of cusp eigenforms $f_{j,k_j}$ of weights $k_j$ in such a way
that $f_{j,k_j}=f_j$, and that all their Fourier coefficients $a_n(f_{j, k_j})$
are given by certain $p$-adic analytic functions $k_j{}\mapsto a_{n,
j}(k_j{})$. The purpose of this paper is to describe a four variable $p$-adic
$L$-function attached to Garrett's triple product of three Coleman's families
$k_j \mapsto \{f_{j,k_j}\}$ of cusp eigenforms of three fixed slopes
$\sigma_j=v_p(\alpha_{p, j}^{(1)}(k_j{}))\ge 0$ where $\alpha_{p,j}^{(1)} =
\al_{p,j}^{(1)}(k_j{})$ is an eigenvalue (which depends on $k_j{}$) of Atkin's
operator $U=U_p$ acting on Fourier expansions by $U(\sum_{n\ge 0}^\infty
a_{n}q^n) = \sum_{n \ge 0}^\infty a_{np} q^n$. We consider the $p$-adic weight
space $X$ containing all $(k{}_j, \psi_j)$. Our $p$-adic $L$-functions are
Mellin transforms of certain measures with values in $\Ar$, where
$\Ar=\Ar({\cal B})$ denotes an affinoid algebra associated with an affinoid
space ${\cal B}$ as in \cite{CoPB}, where ${\cal B}={\cal B}_1\times{\cal
B}_2\times{\cal B}_3$, is an affinoid neighbourhood around $(k_1, k_2, k_3)\in
X^3$ (with a given integers $k_j$ and fixed Dirichlet characters $\psi_j \bmod
N$). We construct such a measure from higher twists of classical
Siegel-Eisenstein series, which produce distributions with values in certain
Banach $\Ar$-modules $\Mr = \Mr(N;\Ar)$ of triple modular forms with
coefficients in the algebra $\Ar$.


  We study the influence of a fast noise on Landau-Zener transitions. We
demonstrate that a fast colored noise much weaker than the conventional white
noise can produce transitions itself or can change substantially the
Landau-Zener transition probabilities. In the limit of fast colored or strong
white noise we derive asymptotically exact formulae for transition
probabilities and study the time evolution of a spin coupled to the noise and a
sweeping magnetic field.


  Direct integration of ferroelectric Hf0.5Zr0.5O2 (HZO) on the inert surface
of graphene is challenging. Here, using nucleation layers to promote atomic
layer deposition of HZO was investigated. Different metals were deposited as
nucleation layers via dc sputtering. Ta, which oxidizes in air to form a
sub-stoichiometric oxide, was compared to Pt, which offers a more stable
electrode. For thicker interlayers, Ta leads to unstable switching behavior of
the HZO film. Conversely, at smaller thicknesses, a higher Pr can be achieved
with an oxidized Ta interlayer. In both cases, Pt offers higher endurance. The
choice of interlayer may strongly depend on the required application.


  The robust tracking and model following problem of linear discrete-time
systems is investigated in this paper. An approach to design robust tracking
controllers is proposed. The system is controlled to track dynamic inputs
generated from a reference model. By using the solution of the Lyapunov
equation, the convergence of the tracking error to the origin, is proved. The
proposed approach employs linear controllers rather than nonlinear ones.
Therefore, the designing method is simple for use and the resulting controller
is easy to implement. An application of the proposed approach for a class of
perturbed systems is also considered. Finally, numerical examples are given to
demonstrate the validity of the results.


  We study Calabi-Yau 3-folds M_0 with a conical singularity x modelled on a
Calabi-Yau cone V. We construct desingularizations of M_0, obtaining a
1-parameter family of compact, nonsingular Calabi-Yau 3-folds which has M_0 as
the limit. The way we do is to choose an Asymptotically Conical Calabi-Yau
3-fold Y modelled on the same cone V, and then glue into M_0 at x after
applying a homothety to Y. We then get a 1-parameter family of nearly
Calabi-Yau 3-folds M_t depending on a small real variable t. For sufficiently
small t, we show that the nearly Calabi-Yau structures on M_t can be deformed
to genuine Calabi-Yau structures, and therefore obtaining the
desingularizations of M_0. Our result can be applied to resolving orbifold
singularities and hence provides a quantitative description of the Calabi-Yau
metrics on the crepant resolutions.


  Cognitive Autonomous Networks (CAN) are promoted to advance Self Organizing
Network (SON), replacing rule-based SON Functions (SFs) with Cognitive
Functions (CFs), which learn optimal behavior by interacting with the network.
As in SON, CFs do encounter conflicts due to overlap in parameters or
objectives. However, owing to the non-deterministic behavior of CFs, these
conflicts cannot be resolved using rulebased methods and new solutions are
required. This paper investigates the CF deployments with and without a
coordination mechanism, and proves both heuristically and mathematically that a
coordination mechanism is required. Using a two-CF Multi-Agent-System model
with the possible types of conflicts, we show that the challenge is a typical
bargaining problem, for which the optimal response is the Nash bargaining
Solution (NBS). We use NBS to propose a coordination mechanism design that is
capable of resolving the conflicts and show via simulations how implementation
of the proposed solution is feasible in real life scenario.


  Multimodal magnetic resonance imaging (MRI) can reveal different patterns of
human tissue and is crucial for clinical diagnosis. However, limited by cost,
noise and manual labeling, obtaining diverse and reliable multimodal MR images
remains a challenge. For the same lesion, different MRI manifestations have
great differences in background information, coarse positioning and fine
structure. In order to obtain better generation and segmentation performance, a
coordination-spatial attention generation adversarial network (CASP-GAN) based
on the cycle-consistent generative adversarial network (CycleGAN) is proposed.
The performance of the generator is optimized by introducing the Coordinate
Attention (CA) module and the Spatial Attention (SA) module. The two modules
can make full use of the captured location information, accurately locating the
interested region, and enhancing the generator model network structure. The
ability to extract the structure information and the detailed information of
the original medical image can help generate the desired image with higher
quality. There exist some problems in the original CycleGAN that the training
time is long, the parameter amount is too large, and it is difficult to
converge. In response to this problem, we introduce the Coordinate Attention
(CA) module to replace the Res Block to reduce the number of parameters, and
cooperate with the spatial information extraction network above to strengthen
the information extraction ability. On the basis of CASP-GAN, an attentional
generative cross-modality segmentation (AGCMS) method is further proposed. This
method inputs the modalities generated by CASP-GAN and the real modalities into
the segmentation network for brain tumor segmentation. Experimental results
show that CASP-GAN outperforms CycleGAN and some state-of-the-art methods in
PSNR, SSMI and RMSE in most tasks.


  In this short note we prove that there is a constant $c$ such that every
k-edge-coloring of the complete graph K_n with n > 2^{ck} contains a K_4 whose
edges receive at most two colors. This improves on a result of Kostochka and
Mubayi, and is the first exponential bound for this problem.


  In this paper we define the module extension dual Banach algebras and we use
this Banach algebras to finding the relationship between $weak^*-$continuous
homomorphisms of dual Banach algebras and Connes-amenability. So we study the
$weak^*-$continuous derivations on module extension dual Banach algebras.


  We study dynamical surface gravity in a general spherically symmetric setting
using Painlev\'{e}-Gullstrand (PG) coordinates. Our analysis includes several
definitions that have been proposed in the past as well as two new definitions
adapted to PG coordinates. Various properties are considered, including general
covariance, value at extremality, locality and static limit. We illustrate with
specific examples of "dirty" black holes that even for spacetimes possessing a
global timelike Killing vector, local definitions of surface gravity can differ
substantially from "non-local" ones that require an asymptotic normalization
condition. Finally, we present numerical calculations of dynamical surface
gravity for black hole formation via spherically symmetric scalar field
collapse. Our results highlight the differences between the various definitions
in a dynamical setting and provide further insight into the distinction between
local and non-local definitions of surface gravity.


  We investigate the effect of a spin-density wave (SDW) on $s_{\pm}$
superconductivity in Fe-based superconductors. We show that, contrary to the
common wisdom, no nodes open at the new, reconnected Fermi surfaces when the
hole and electron pockets fold down in the SDW state, despite the fact that the
$s_{\pm}$ gap changes sign between the two pockets. Instead, the order
parameter preserves its sign along the newly formed Fermi surfaces. The
familiar experimental signatures of an $s_{\pm}$ symmetry are still preserved,
although they appear in a mathematically different way. For a regular $s$ case
($s_{++})$ the nodes do appear in the SDW state. This distinction suggests a
novel simple way to experimentally separate an $s_{\pm}$ state from a regular
$s$ in the pnictides. We argue that recently published thermal conductivity
data in the coexisting state are consistent with the $s_{\pm},$ but not the
$s_{++}$ state.


  The circumcentered Douglas--Rachford method (C--DRM), introduced by Behling,
Bello Cruz and Santos, is an acceleration of the well-known Douglas-Rachford
method (DRM) for finding the best approximation onto the intersection of
finitely many affine subspaces. Inspired by the C--DRM, we introduced the more
flexible circumcentered reflection method (CRM) and circumcentered isometry
method (CIM). The CIM essentially chooses the closest point to the solution
among all of the points in an associated affine hull as its iterate and is a
generalization of the CRM. The circumcentered--reflection method introduced by
Behling et al. to generalize the C--DRM is a special class of our CRM.
  We consider the CIM induced by a set of finitely many isometries for finding
the best approximation onto the intersection of fixed point sets of the
isometries which turns out to be an intersection of finitely many affine
subspaces. We extend our previous linear convergence results on CRMs in
finite-dimensional spaces from reflections to isometries. In order to better
accelerate the symmetric method of alternating projections (MAP), the
accelerated symmetric MAP first applies another operator to the initial point.
(Similarly, to accelerate the DRM, the C--DRM first applies another operator to
the initial point as well.) Motivated by these facts, we show results on the
linear convergence of CIMs in Hilbert spaces with first applying another
operator to the initial point. In particular, under some restrictions, our
results imply that some CRMs attain the known linear convergence rate of the
accelerated symmetric MAP in Hilbert spaces. We also exhibit a class of CRMs
converging to the best approximation in Hilbert spaces with a convergence rate
no worse than the sharp convergence rate of MAP. The fact that some CRMs attain
the linear convergence rate of MAP or accelerated symmetric MAP is entirely
new.


  The main result is that a quasi-projective surface has negative log Kodaira
dimension (i.e. no log pluricanonical sections) iff it is dominated by images
of the affine line. This follows from our main intermediate result, that the
smooth locus of a log Fano surface is rationally connected. We also give a
classification of all but a bounded family of rank one log del Pezzo surfaces.


  We present an explicit analytical computation of the quantum corrections, at
next-to-leading order, to the critical exponents. We employ for that the
Unconventional minimal subtraction, recently proposed, and the Callan-Symanzik
methods to probe the universality hypothesis by comparing the outcomes for the
critical exponents evaluated in both methods and the ones calculated previously
in massless theories renormalized at different renormalization schemes.
Furthermore, the consistency of the former method is investigated for the first
time in literature, to our knowledge. At the end, we compute the critical
exponents at any loop level by an induction process and furnish the physical
interpretation of the results.


  Feedback from the central black hole in active galactic nuclei (AGN) may be
responsible for establishing the observed MBH-sigma relation and limiting the
bulge stellar mass of the host galaxy. Here we explore the possibility of AGN
feedback triggering star formation in the host galaxy. We consider a shell of
dusty gas, driven outwards by radiation pressure, and analyse its
escape/trapping condition in the galactic halo for different underlying dark
matter potentials. In the isothermal potential, we obtain that the standard
condition setting the observed MBH-sigma relation is not sufficient to clear
gas out of the entire galaxy; whereas the same condition is formally sufficient
in the case of the Hernquist and Navarro-Frenk-White profiles. The squeezing
and compression of the inhomogeneous interstellar medium during the ejection
process can trigger star formation within the feedback-driven shell. We
estimate the resulting star formation rate and total additional stellar mass.
In this picture, new stars are formed at increasingly larger radii and
successively populate the outer regions of the host galaxy. This characteristic
pattern may be compared with the observed 'inside-out' growth of massive
galaxies.


  In compressive fracture of dry plexiform bone, we examine the individual
roles of overall mean porosity, the connectivity of the porosity network, and
the elastic as well as the failure properties of the non-porous matrix, using a
random spring network model. Porosity network structure is shown to reduce the
compressive strength by upto 30%. However, the load bearing capacity increases
with increase in either of the matrix properties - elastic modulus or failure
strain threshold. To validate the porosity-based RSNM model with available
experimental data, bone-specific failure strain thresholds for the ideal matrix
of similar elastic properties were estimated to be within 60% of each other.
Further, we observe the avalanche size exponents to be independent of the
bone-dependent parameters as well as the structure of the porosity network.


  Radial migration is defined as the change in guiding centre radius of stars
and gas caused by gains or losses of angular momentum that result from
gravitational interaction with non-axisymmetric structure. This has been shown
to have significant impact on the metallicity distribution in galactic discs,
and therefore affects the interpretation of Galactic archeology. We use a
simulation of a Milky Way-sized galaxy to examine the effect of radial
migration on the star and gas radial metallicity distribution. We find that
both the star and gas component show significant radial migration. The stellar
radial metallicity gradient remains almost unchanged but the radial metallicity
distribution of the stars is broadened to produce a greater dispersion at all
radii. However, the metallicity dispersion of the gas remains narrow. We find
that the main drivers of the gas metallicity distribution evolution are metal
enrichment and mixing: more efficient metal enrichment in the inner region
maintains a negative slope in the radial metallicity distribution, and the
metal mixing ensures the tight relationship of the gas metallicity with the
radius. The metallicity distribution function reproduces the trend in the
age-metallicity relation found from observations for stars younger than 1.0 Gyr
in the Milky Way.


  This paper delves into the formidable challenge of cross-domain
generalization in multimodal hate meme detection, presenting compelling
findings. We provide enough pieces of evidence supporting the hypothesis that
only the textual component of hateful memes enables the existing multimodal
classifier to generalize across different domains, while the image component
proves highly sensitive to a specific training dataset. The evidence includes
demonstrations showing that hate-text classifiers perform similarly to
hate-meme classifiers in a zero-shot setting. Simultaneously, the introduction
of captions generated from images of memes to the hate-meme classifier worsens
performance by an average F1 of 0.02. Through blackbox explanations, we
identify a substantial contribution of the text modality (average of 83%),
which diminishes with the introduction of meme's image captions (52%).
Additionally, our evaluation on a newly created confounder dataset reveals
higher performance on text confounders as compared to image confounders with an
average $\Delta$F1 of 0.18.


  Due to the limited availability of data, existing few-shot learning methods
trained from scratch fail to achieve satisfactory performance. In contrast,
large-scale pre-trained models such as CLIP demonstrate remarkable few-shot and
zero-shot capabilities. To enhance the performance of pre-trained models for
downstream tasks, fine-tuning the model on downstream data is frequently
necessary. However, fine-tuning the pre-trained model leads to a decrease in
its generalizability in the presence of distribution shift, while the limited
number of samples in few-shot learning makes the model highly susceptible to
overfitting. Consequently, existing methods for fine-tuning few-shot learning
primarily focus on fine-tuning the model's classification head or introducing
additional structure. In this paper, we introduce a fine-tuning approach termed
Feature Discrimination Alignment (FD-Align). Our method aims to bolster the
model's generalizability by preserving the consistency of spurious features
across the fine-tuning process. Extensive experimental results validate the
efficacy of our approach for both ID and OOD tasks. Once fine-tuned, the model
can seamlessly integrate with existing methods, leading to performance
improvements. Our code can be found in https://github.com/skingorz/FD-Align.


  We consider the galactic evolutionary history of \he3 in models which deplete
deuterium by as much as a factor of 2 to $\sim$ 15 from its primordial value to
its present day observed value in the ISM. We show that when \he3 production in
low mass stars (1 -- 3 $M_\odot$) is included over the history of the galaxy,
\he3 is greatly over-produced and exceeds the inferred solar values and the
abundances determined in galactic \hii regions. Furthermore, the ISM abundances
show a disturbing dispersion which is difficult to understand from the point of
view of standard chemical evolution models. In principle, resolution of the
problem may lie in either 1) the calculated \he3 production in low mass stars;
2) the observations of the \he3 abundance; or 3) an observational bias towards
regions of depleted \he3. Since \he3 observations in planetary nebula support
the calculated \he3 production in low mass stars, option (1) is unlikely. We
will argue for option (3) since the \he3 interstellar observations are indeed
made in regions dominated by massive stars in which \he3 is destroyed. In
conclusion, we note that the problem with \he3 seems to be galactic and not
cosmological.


  In this paper, we consolidate and expand upon the current theory and
potential applications of the set of $k$ best \emph{cascading via-paths} (CVPs)
and the \emph{reciprocal pointer chain} (RPC) method for identifying them. CVPs
are a collection of up to $|V|$ paths between a source and a target node in a
graph $G = (V,E)$, computed using two shortest path trees, that have
distinctive properties relative to other path sets. They have been shown to be
particularly useful in geospatial applications, where they are an intuitive and
efficient means for identifying a set of spatially diverse alternatives to the
single shortest path between the source and target. However, spatial diversity
is not intrinsic to paths in a graph, and little theory has been developed
outside of application to describe the nature of these paths and the RPC method
in general. Here we divorce the RPC method from its typical geospatial
applications and develop a comprehensive theory of CVPs from an abstract
graph-theoretic perspective. Restricting ourselves to properties of the CVPs
and of the entire set of $k$-best CVPs that can be computed in $O(|E| + |V|
\log |V|)$, we are able to then propose, among other things, new and efficient
approaches to problems such as generating a diverse set of paths and to
computing the $k$ shortest loopless paths between two nodes in a graph. We
conclude by demonstrating the new theory in practice, first for a typical
application of finding alternative routes in road networks and then for a novel
application of identifying layer-boundaries in ground-penetrating radar (GPR)
data. It is our hope that by generalizing the RPC method, providing a sound
theoretical foundation, and demonstrating novel uses, we are able to broaden
its perceived applicability and stimulate new research in this area, both
applied and theoretical.


  Reformulation of the Dirac equation in terms of the real Spacetime Algebra
(STA) reveals hidden geometric structure, including a geometric role for the
unit imaginary as generator of rotations in a spacelike plane. The STA and the
real Dirac equation play essential roles in a new Gauge Theory Gravity (GTG)
version of General Relativity (GR). Besides clarifying the conceptual
foundations of GR and facilitating complex computations, GTG opens up new
possibilities for a unified gauge theory of gravity and quantum mechanics,
including spacetime geometry of electroweak interactions. The Weinberg-Salam
model fits perfectly into this geometric framework, and a promising variant
that replaces chiral states with Majorana states is formulated to incorporate
zitterbewegung in electron states.


  CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a
key technology for security in smart city environments. This paper creates a
case where the UAVs with CCTV-cameras fly over the city area for flexible and
reliable surveillance services. UAVs should be deployed to cover a large area
while minimize overlapping and shadow areas for a reliable surveillance system.
However, the operation of UAVs is subject to high uncertainty, necessitating
autonomous recovery systems. This work develops a multi-agent deep
reinforcement learning-based management scheme for reliable industry
surveillance in smart city applications. The core idea this paper employs is
autonomously replenishing the UAV's deficient network requirements with
communications. Via intensive simulations, our proposed algorithm outperforms
the state-of-the-art algorithms in terms of surveillance coverage, user support
capability, and computational costs.


  Formulation of physical theories typically assumes a definite causal
structure -- either static or dynamic -- among the set of physical events.
Recent studies, however, suggest the possibility of indefiniteness in causal
structure, which emerges as a novel information primitive offering advantages
in various protocols. In this work, we explore utilities of this new primitive
in cryptographic applications. To this aim, we propose a task called
local-data-hiding, where a referee distributes encrypted messages among distant
parties in such a way that the parties individually remain completely ignorant
about the messages, and thus try to decrypt their respective messages through
mutual collaboration. As we demonstrate, agents embedded in an indefinite
causal structure can outperform their counterparts operating in a definite
causal background. Considering the bipartite local-bit-hiding (LBH) task, we
establish a strict duality between its optimal success probability and the
optimal violation of a causal inequality obtained from the
guess-your-neighbour's-input game. This, in turn, provides a way forward to
obtain Tsirelson-type bounds for causal inequalities. Furthermore, similar to
Peres's separability criterion, we derive a necessary criterion for quantum
processes to be useful in the LBH task. We then report an intriguing
super-activation phenomenon, where two quantum processes, each individually not
useful for the LBH task, become useful when used together. We also analyze the
utility of causal indefiniteness arising in classical setups and show its
advantages in multipartite variants of the local-data-hiding task. Along with
establishing new cryptographic applications our study illuminates various
unexplored aspects of causal indefiniteness, and welcomes further studies on
this new information primitive.


  Geometrically complex masonry structures (e.g., arches, domes, vaults) are
traditionally built with expensive scaffolding or falsework to provide
stability during construction. The process of building such structures can
potentially be improved through the use of multiple robots working together in
a cooperative assembly framework. Here a robot is envisioned as both a
placement and external support agent during fabrication - the unfinished
structure is supported in such a way that scaffolding is not required. The goal
of this paper is to present and validate the efficacy of three cooperative
fabrication approaches using two or three robots, for the scaffold-free
construction of a stable masonry arch from which a medium-span vault is built.
A simplified numerical method to represent a masonry structure is first
presented and validated to analyse systems composed of discrete volumetric
elements. This method is then used to evaluate the effect of the three
cooperative robotic fabrication strategies on the stability performance of the
central arch. The sequential method and cantilever method, which utilize two
robotic arms, are shown to be viable methods, but have challenges related to
scalability and robustness. By adding a third robotic agent, it becomes
possible to determine a structurally optimal fabrication sequence through a
multi-objective optimization process. The optimized three robot method is shown
to significantly improve the structural behavior over all fabrication steps.
The modeling approaches presented in this paper are broadly formulated and
widely applicable for the analysis of cooperative robotic fabrication sequences
for the construction of discrete element structures across scales and
materials.


  We investigate adversarial-sample generation methods from a frequency domain
perspective and extend standard $l_{\infty}$ Projected Gradient Descent (PGD)
to the frequency domain. The resulting method, which we call Spectral Projected
Gradient Descent (SPGD), has better success rate compared to PGD during early
steps of the method. Adversarially training models using SPGD achieves greater
adversarial accuracy compared to PGD when holding the number of attack steps
constant. The use of SPGD can, therefore, reduce the overhead of adversarial
training when utilizing adversarial generation with a smaller number of steps.
However, we also prove that SPGD is equivalent to a variant of the PGD
ordinarily used for the $l_{\infty}$ threat model. This PGD variant omits the
sign function which is ordinarily applied to the gradient. SPGD can, therefore,
be performed without explicitly transforming into the frequency domain.
Finally, we visualize the perturbations SPGD generates and find they use both
high and low-frequency components, which suggests that removing either
high-frequency components or low-frequency components is not an effective
defense.


  Simulation of conditional master equations is important to describe systems
under continuous measurement and for the design of control strategies in
quantum systems. For large bosonic systems, such as BEC and atom lasers, full
quantum field simulations must rely on scalable stochastic methods whose
convergence time is restricted by the use of representations based on coherent
states. Here we show that typical measurements on atom-optical systems have a
common form that allows for an efficient simulation using the number-phase
Wigner (NPW) phase-space representation. We demonstrate that a stochastic
method based on the NPW can converge over an order of magnitude longer and more
precisely than its coherent equivalent. This opens the possibility of realistic
simulations of controlled multi-mode quantum systems.


  We investigate the bounce solution in the holographic QCD and electroweak
models with first-order phase transition. The strength parameter $\alpha$,
inverse duration time $\beta/H$, and bubble wall velocity $v_w$ in the
gravitational wave power spectra are calculated by holographic bounce solution.
In contrast to the results of field theory, we find the parameter $\alpha$ is
about $\mathcal{O}(1)$ and $\beta/H$ is about $10^4$, which imply that the
phase transition is fast and strong. The critical, nucleation and percolation
temperatures of the phase transition are close to each other in the holographic
model. In addition, the velocity $v_w$ is found to be less than the sound speed
of the plasma $c_{s}=1/\sqrt{3}$, which corresponds to the deflagration
scenario. For QCD phase transition, the gravitational wave power spectrum can
reach $10^{-13}-10^{-14}$ around the peak frequency of 0.01 Hz, which can be
detected by BBO and Ultimate-DECIGO. For electroweak phase transition, the
gravitational wave power spectrum can reach $10^{-12}-10^{-16}$ around the peak
frequency $1-10$ Hz. Moreover, the primordial black hole is not favorable for
formation due to the large parameter $\beta/H$ and small velocity $v_w$.


  We investigate the first order implicit linear difference equation over
residue class rings modulo m. We prove an existence criterion and establish the
amount of solutions for this equation. We obtain analogous results for the
initial problem of the considered equation. The examples which illustrate the
developed theory are given.


  We propose a new symbolic algorithm and a C++ program for generating and
calculating supersymmetric Feynman diagrams for ${\cal N}=1$ supersymmetric
electrodynamics regularized by higher derivatives in four dimensions. According
to standard rules, the program generates all diagrams that are necessary to
calculate a specific contribution to the two-point Green function of matter
superfields in the needed order, and then reduces the answer to the sum of
Euclidean momentum integrals. At the moment, the program was used to calculate
the anomalous dimension in ${\cal N}=1$ supersymmetric quantum electrodynamics,
regularized by higher derivatives, in the three-loop approximation.


  Recent studies strive to incorporate various human rationales into neural
networks to improve model performance, but few pay attention to the quality of
the rationales. Most existing methods distribute their models' focus to
distantly-labeled rationale words entirely and equally, while ignoring the
potential important non-rationale words and not distinguishing the importance
of different rationale words. In this paper, we propose two novel auxiliary
loss functions to make better use of distantly-labeled rationales, which
encourage models to maintain their focus on important words beyond labeled
rationales (PINs) and alleviate redundant training on non-helpful rationales
(NoIRs). Experiments on two representative classification tasks show that our
proposed methods can push a classification model to effectively learn crucial
clues from non-perfect rationales while maintaining the ability to spread its
focus to other unlabeled important words, thus significantly outperform
existing methods.


  A unified scheme using the R-matrix method has been developed for
electron-ion recombination subsuming heretofore separate treatments of
radiative and dielectronic recombination (RR and DR). The ab initio coupled
channel approach unifies resonant and non-resonant phenomena, and enables a
general and self-consistent treatment of photoionization and electron-ion
recombination employing idential wavefunction expansion. Detailed balance takes
account of interference effects due to resonances in cross sections, calculated
explicitly for a large number of recombined (e+ion) bound levels over extended
energy regions. The theory of DR by Bell and Seaton is adapted for high-n
resonances in the region below series limits. The R-matrix method is employed
for (A) partial and total photoionization and photorecombination cross sections
of (e+ion) bound levels, and (B) DR and (e+ion) scattering cross sections.
Relativistic effects and fine structure are considered in the Breit-Pauli
approximation. Effects such as radiation damping may be taken into account
where necessary. Unfiied recombination cross sections are in excellent
agreement with measurements on ion storage rings to about 10-20%. In addition
to high accuracy, the strengths of the method are: (I) both total and
level-specific cross sections and rate coefficients are obtained, and (II) a
single (e+ion) recombination rate coefficient for any given atom or ion is
obtained over the entire temperature range of practical importance in
laboratory and astrophysical plasmas, (III) self-consistent results are
obtained for photoionization and recombination; comprehensive datasets have
been computed for over 50 atoms and ions. Selected data are presented for iron
ions.


  In this paper, we extend the Brown-Halmos theorems to the Fock space and
investigate the range of the Berezin transform. We observe that there are
non-pluriharmonic functions $u$ that can be written as a finite sum
$B(u)=\sum_lf_l\overline{g_l}$, where $f_l,g_l$ are holomorphic functions
belonging to the class $\mathrm{Sym}(\mathbb{C}^n)$. In addition, we solve an
open question about the zero product of Toeplitz operators, which was posed by
Bauer et al. in 2015. Our results reveal that the Brown-Halmos theorems on the
Fock space are more complicated than that on the classical Bergman space.


  Deeply Virtual Compton Scattering in the near forward kinematic region is the
golden access to Generalized Parton Distributions. We studied the O(alphaS)
corrections to the scattering amplitude for both spacelike and timelike
kinematics relevant respectively to the leptoproduction of a real photon and to
the photoproduction of a lepton pair. It turns out that these corrections are
phenomenologically important and that the gluonic contributions are by no means
negligible, even in the moderate energy range of JLab12 and of the COMPASS-II
experiment at CERN.


  We study Hilbert generated versions of nonseparable Banach spaces $\mathcal
X$ considered by Shelah, Stepr\=ans and Wark where the behavior of the norm on
nonseparable subsets is so irregular that it does not allow any linear bounded
operator on $\mathcal X$ other than a diagonal operator (or a scalar multiple
of the identity) plus a separable range operator. We address the questions if
these spaces admit uncountable equilateral sets and if their unit spheres admit
uncountable $(1+)$-separated or $(1+\varepsilon)$-separated sets. We resolve
some of the above questions for two types of these spaces by showing both
absolute and undecidability results.
  The corollaries are that the continuum hypothesis (in fact: the existence of
a nonmeager set of reals of the first uncountable cardinality) implies the
existence of an equivalent renorming of the nonsepareble Hilbert space
$\ell_2(\omega_1)$ which does not admit any uncountable equilateral set and it
implies the existence of a nonseparable Hilbert generated Banach space
containing an isomorphic copy of $\ell_2$ in each nonseparable subspace, whose
unit sphere does not admit an uncountable equilateral set and does not admit an
uncountable $(1+\varepsilon)$-separated set for any $\varepsilon>0$. This could
be compared with a recent result by H\'ajek, Kania and Russo saying that all
nonseparable reflexive Banach spaces admit uncountable
$(1+\varepsilon)$-separated sets in their unit spheres.


  The aim of this paper is twofold. The first is to study the asymptotics of a
parabolically scaled, continuous and space-time stationary in time version of
the well-known Funaki-Spohn model in Statistical Physics. After a change of
unknowns requiring the existence of a space-time stationary eternal solution of
a stochastically perturbed heat equation, the problem transforms to the
qualitative homogenization of a uniformly elliptic, space-time stationary,
divergence form, nonlinear partial differential equation, the study of which is
the second aim of the paper. An important step is the construction of
correctors with the appropriate behavior at infinity.


  In this article, we aim at obtaining the analytical expressions ({\bf not
previously found and not recorded in the literature}) for the exact curved
surface area of a hemiellpsoid in terms of Appell's double hypergeometric
function of first kind. The derivation is based on Mellin-Barnes type contour
integral representations of generalized hypergeometric function$~_pF_q(z)$,
Meijer's $G$-function and analytic continuation formula for Gauss function.
Moreover, we obtain some special cases related to ellipsoid, Prolate spheroid
and Oblate spheroid. The closed forms for the exact curved surface area of a
hemiellpsoid are also verified numerically by using {\it Mathematica Program}.


  We construct an expression for the Green function of a differential operator
satisfying nonlocal, homogeneous boundary conditions starting from the
fundamental solution of the differential operator. This also provides the
solution to the boundary value problem of an inhomogeneous partial differential
equation with inhomogeneous, nonlocal, and linear boundary conditions. The
construction generally applies for all types of linear partial differential
equations and linear boundary conditions.


  Conventional circulators are made of magnetic ferrites and suffer from a
cumbersome architecture, incompatibility with integrated circuit technology and
inability for high frequency applications. To overcome these limitations, here
we propose a lightweight low-profile non-magnetic circulator comprising a
nonreciprocal time-varying phase shifter. This circulator is composing a
nonreciprocal temporal phase shifter and two reciprocal delay-line-based phase
shifters. The proposed nonreciprocal temporal phase shifter is based on the
generation of time-harmonic signals, enforcing destructive interference for
undesired time harmonics and constructive interference for desired time
harmonics at different locations of the structure. Such a unique task is
accomplished through two phase-engineered temporal loops. The phase and
frequency of these two loops are governed by external signals with different
phases, imparting an effective electronic angular momentum to the system. We
observe large isolation level of greater than 32 dB, a P1dB of +31.7 dBm and
IIP3 of +42.4 dBm. Furthermore, this circulator is endowed with a
reconfigurable architecture and can be directly embedded in a conventional
integrated circuit (IC) technology to realize a class of high power handling
and linear IC circulators.


  Previous research in $2D$ object detection focuses on various tasks,
including detecting objects in generic and camouflaged images. These works are
regarded as passive works for object detection as they take the input image as
is. However, convergence to global minima is not guaranteed to be optimal in
neural networks; therefore, we argue that the trained weights in the object
detector are not optimal. To rectify this problem, we propose a wrapper based
on proactive schemes, PrObeD, which enhances the performance of these object
detectors by learning a signal. PrObeD consists of an encoder-decoder
architecture, where the encoder network generates an image-dependent signal
termed templates to encrypt the input images, and the decoder recovers this
template from the encrypted images. We propose that learning the optimum
template results in an object detector with an improved detection performance.
The template acts as a mask to the input images to highlight semantics useful
for the object detector. Finetuning the object detector with these encrypted
images enhances the detection performance for both generic and camouflaged. Our
experiments on MS-COCO, CAMO, COD$10$K, and NC$4$K datasets show improvement
over different detectors after applying PrObeD. Our models/codes are available
at https://github.com/vishal3477/Proactive-Object-Detection.


  Quantum and quantum-inspired optimisation algorithms are designed to solve
problems represented in binary, quadratic and unconstrained form. Combinatorial
optimisation problems are therefore often formulated as Quadratic Unconstrained
Binary Optimisation Problems (QUBO) to solve them with these algorithms.
Moreover, these QUBO solvers are often implemented using specialised hardware
to achieve enormous speedups, e.g. Fujitsu's Digital Annealer (DA) and D-Wave's
Quantum Annealer. However, these are single-objective solvers, while many
real-world problems feature multiple conflicting objectives. Thus, a common
practice when using these QUBO solvers is to scalarise such multi-objective
problems into a sequence of single-objective problems. Due to design trade-offs
of these solvers, formulating each scalarisation may require more time than
finding a local optimum. We present the first attempt to extend the algorithm
supporting a commercial QUBO solver as a multi-objective solver that is not
based on scalarisation. The proposed multi-objective DA algorithm is validated
on the bi-objective Quadratic Assignment Problem. We observe that algorithm
performance significantly depends on the archiving strategy adopted, and that
combining DA with non-scalarisation methods to optimise multiple objectives
outperforms the current scalarised version of the DA in terms of final solution
quality.


  The cross sections of $\Upsilon $\ absorption by nucleons are calculated in
meson-baryon exchange model using an effective hadronic Lagrangian. Calculated
cross sections are found to peak near threshold followed by an increase which
tends to settle at large center of mass energy. Peak values are found in range
about 1.8 to 4 mb when cutoff parameter of monopole form factor is varied from
1.2 to 1.8 GeV. The results disagree with pQCD calculations but are consistent
with the effective value of the absorption cross section extracted from p-A
scattering data in E772 experiment at $\sqrt{s_{NN}}=39$ GeV. We use this data
value to find a best fit of the cutoff parameter which enables us provide
definite predictions for the values of $\Upsilon $ absorption cross sections by
nucleons for upcoming p-A scattering experiments at RHIC and LHC energies for
zero rapidity $b\bar{b}$ states. The results could be useful in studying the
effect of $\Upsilon $ absorption by nucleons at its production stage in
relativistic heavy-ion collision experiments. We also find that thermal
averaged values of total absorption cross sections are small enough to rule out
the effect of absorption of $\Upsilon $ by the comovers in the hadronic matter.


  Modifications of spatial distributions of dynamic magnetization corresponding
to spinwave eigenmodes of magnetic squares subjected to a strong microwave
excitation field have been studied experimentally and theoretically. We show
that an increase of the excitation power leads to a nonlinear generation of
long-wavelength spatial harmonics caused by the nonlinear cross coupling
between the eigenmodes. The analysis of the experimental data shows that this
process is mainly governed by the action of the nonlinear spin-wave damping.
This conclusion is further supported by the numerical calculations based on the
complex Ginzburg-Landau equation phenomenologically taking into account the
nonlinear damping.


  We study grooming for two-period optical networks, a variation of the traffic
grooming problem for WDM ring networks introduced by Colbourn, Quattrocchi, and
Syrotiuk. In the two-period grooming problem, during the first period of time,
there is all-to-all uniform traffic among $n$ nodes, each request using $1/C$
of the bandwidth; and during the second period, there is all-to-all uniform
traffic only among a subset $V$ of $v$ nodes, each request now being allowed to
use $1/C'$ of the bandwidth, where $C' < C$. We determine the minimum drop cost
(minimum number of ADMs) for any $n,v$ and C=4 and $C' \in \{1,2,3\}$. To do
this, we use tools of graph decompositions. Indeed the two-period grooming
problem corresponds to minimizing the total number of vertices in a partition
of the edges of the complete graph $K_n$ into subgraphs, where each subgraph
has at most $C$ edges and where furthermore it contains at most $C'$ edges of
the complete graph on $v$ specified vertices. Subject to the condition that the
two-period grooming has the least drop cost, the minimum number of wavelengths
required is also determined in each case.


  This report describes our submission to BHI 2023 Data Competition: Sensor
challenge. Our Audio Alchemists team designed an acoustic-based COVID-19
diagnosis system, Cough to COVID-19 (C2C), and won the 1st place in the
challenge. C2C involves three key contributions: pre-processing of input
signals, cough-related representation extraction leveraging Wav2vec2.0, and
data augmentation. Through experimental findings, we demonstrate C2C's
promising potential to enhance the diagnostic accuracy of COVID-19 via cough
signals. Our proposed model achieves a ROC-AUC value of 0.7810 in the context
of COVID-19 diagnosis. The implementation details and the python code can be
found in the following link:
https://github.com/Woo-jin-Chung/BHI_2023_challenge_Audio_Alchemists


  An explicit expression for the temperature dependence of the specific heat of
clean anisotropic-gap superconductors is derived within the weak-coupling BCS
approximation. The specific heat is presented as a functional of the
superconducting gap on the Fermi surface. The obtained formula interpolates
between the correct low coupling jump at T_c and the low temperature behavior
for T<<T_c. For isotropic superconductors the formula gives a relation between
the specific heat and the superconducting gap. For anisotropic superconductors,
the interpolation formula incorporates averaging of powers of the gap
anisotropy function over the Fermi surface and provides a suitable set for
fitting model Hamiltonians to experimental data. The work of the interpolation
formula is illustrated by (i) the Pokrovsky formula for the specific heat jump,
(ii) Gor'kov and Melik-Barkhudarov formulas for the Ginzburg-Landau
coefficients, (iii) the Moskalenko two-band formula for the specific heat jump,
(iv) the temperature dependence of the specific heat for the two-band model,
applicable to MgB_2, (v) the two-dimensional d-wave model, applicable for
YBa_2Cu_3O_{7-delta}, and (vi) the Zhitomirsky and Rice triplet p-wave model
with horizontal line nodes for Sr_2RuO_4. The temperature dependence of the
penetration depth is illustrated by fitting the general theoretical formula to
the experimental data for MgB_2, YBa_2Cu_3O_{7-delta}, and the triplet
superconductor Sr_2RuO_4.


  n this work we consider a multilayered heat-wave system where a 3-D heat
equation is coupled with a 3-D wave equation via a 2-D interface whose dynamics
is described by a 2-D wave equation. This system can be viewed as a
simplification of a certain fluid-structure interaction (FSI) PDE model where
the structure is of composite-type; namely it consists of a \textquotedblleft
thin\textquotedblright\ layer and a \textquotedblleft thick\textquotedblright\
layer. We associate the wellposedness of the system with a strongly continuous
semigroup and establish its asymptotic decay.
  Our first result is semigroup well-posedness for the (FSI) PDE dynamics.
Utilizing here a Lumer-Phillips approach, we show that the fluid-structure
system generates a $C_0$-semigroup on a chosen finite energy space of data. As
our second result, we prove that the solution to the (FSI) dynamics generated
by the $C_0$-semigroup tends asymptotically to the zero state for all initial
data. That is, the semigroup of the (FSI) system is strongly stable. For this
stability work, we analyze the spectrum of the generator $\mathbf A$ and show
that the spectrum of $\mathbf A$ does not intersect the imaginary axis.
\vskip.3cm \noindent \textbf{Key terms:} Fluid-structure interaction, heat-wave
system, well-posedness, semigroup, strong stability.


  Carrier Aggregation (CA) is one of the Long Term Evolution Advanced (LTE-A)
features that allow mobile network operators (MNO) to combine multiple
component carriers (CCs) across the available spectrum to create a wider
bandwidth channel for increasing the network data throughput and overall
capacity. CA has a potential to enhance data rates and network performance in
the downlink, uplink, or both, and it can support aggregation of frequency
division duplexing (FDD) as well as time division duplexing (TDD). The
technique enables the MNO to exploit fragmented spectrum allocations and can be
utilized to aggregate licensed and unlicensed carrier spectrum as well. This
paper analyzes the performance gains and complexity level that arises from the
aggregation of three inter-band component carriers (3CC) as compared to the
aggregation of 2CC using a Vienna LTE System Level simulator. The results show
a considerable growth in the average cell throughput when 3CC aggregations are
implemented over the 2CC aggregation, at the expense of reduction in the
fairness index. The reduction in the fairness index implies that, the scheduler
has an increased task in resource allocations due to the added component
carrier. Compensating for such decrease in the fairness index could result into
scheduler design complexity. The proposed scheme can be adopted in combining
various component carriers, to increase the bandwidth and hence the data rates.


  We discuss central exclusive diffractive dihadron production in proton-proton
collisions at high energies. The calculation is based on a tensor pomeron model
and the amplitudes for the processes are formulated in an effective
field-theoretic approach. We include a purely diffractive dipion continuum, and
the scalar and tensor resonances decaying into the $\pi^{+} \pi^{-}$ pairs as
well as the photoproduction contributions ($\rho^{0}$, Drell-S\"oding). We
discuss how two pomerons couple to tensor meson $f_{2}(1270)$ and the
interference effects of the scalar and tensor resonances and the dipion
continuum. The theoretical results are compared with existing CDF and CMS
experimental data. We discuss also the Drell-Hiida-Deck type mechanism with
centrally produced $\rho^{0}$ meson associated with a very forward/backward
$\pi N$ system. For the $pp \to pp \pi^{+} \pi^{-} \pi^{+} \pi^{-}$ reaction we
consider both the $\sigma \sigma$ and $\rho \rho$ contributions as well as the
triple Regge exchange mechanism. Predictions for planned or being carried out
experiments (STAR, ALICE, ATLAS, CMS) are presented. We show the influence of
the experimental cuts on the integrated cross section and on various
differential distributions for outgoing particles.


  We consider the trace map associated with the silver ratio Schrodinger
operator as a diffeomorphism on the invariant surface associated with a given
coupling constant and prove that the non-wandering set of this map is
hyperbolic if the coupling is sufficiently large. As a consequence, for this
values of the coupling constant, the local and global Hausdorff dimension and
the local and global box counting dimension of the spectrum of this operator
all coincide and are smooth functions of the coupling constant.


  We define some Nehari-type constraints using an orthogonal decomposition of
the Sobolev space $H^1_0$ and prove the existence of multibump nodal solutions
for an indefinite superlinear elliptic problem.


  In the present work, the gravitational field of superconducting cosmic string
has been investigated in the context of Brans-Dicke theory of gravity. We have
presented two kind of solutions for the spacetime in the far field zone of the
string. When the B-D scalar field is switched off, one of the solutions reduces
to the solution earlier obtained by Moss and Poletti in General Relativity.


  The strata of the moduli spaces of Abelian differentials are non-homogenous
spaces carrying natural bi-algebraic structures. Partly inspired by the case of
homogenous spaces carrying bi-algebraic structures (such as torii, Abelian
varieties and Shimura varieties), Klingler and Lerer recently showed that any
bi-algebraic curve in a stratum of the moduli space of Abelian differentials is
linear provided that the so-called condition $(\star)$ is fulfilled.
  In this note, we construct a non-linear bi-algebraic curve, resp. surface, of
Abelian differentials of genus $7$, resp. $10$.


  Aims. Recent studies showed that time--distance inversions for flows start to
be dominated by a random noise at a depth of only a few Mm. It was proposed
that the ensemble averaging might be a solution to learn about the structure of
the convective flows, e.g., about the depth structure of supergranulation.
Methods. Time--distance inversion is applied to the statistical sample of
~$10^4$ supergranules, which allows to regularise weakly about the random-noise
term of the inversion cost function and hence to have a much better
localisation in space. We compare these inversions at four depths (1.9, 2.9,
4.3, and 6.2 Mm) when using different spatio-temporal filtering schemes in
order to gain confidence about these inferences. Results. The flows inferred by
using different spatio-temporal filtering schemes are different (even by the
sign) even-though the formal averaging kernels and the random-noise levels are
very similar. The inverted flows alterates its sign several times with depth.
It is suggested that this is due to the inaccuracies in the forward problem
that are possibly amplified by the inversion. It is possible that also other
time--distance inversions are affected by this issue.


  Starting from microscopic interaction rules we derive kinetic models of
Fokker--Planck type for vehicular traffic flow. The derivation is based on
taking a suitable asymptotic limit of the corresponding Boltzmann model. As
particular cases, the derived models comprise existing models.
  New Fokker--Planck models are also given and their differences to existing
models are highlighted. Finally, we report on numerical experiments.


  We study the effect of a Rashba spin-orbit coupling on the nodal
superconducting phase of an Ising superconductor. Such nodal phase was
predicted to occur when applying an in-plane field beyond the Pauli limit to a
superconducting monolayer transition metal dichalcogenides (TMD). Generically,
Rashba spin-orbit is known to lift the chiral symmetry that protects the nodal
points, resulting in a fully gapped phase. However, when the magnetic field is
applied along the $\Gamma -K $ line, a residual vertical mirror symmetry
protects a nodal crystalline phase. We study a single-band tight-binding model
that captures the low energy physics around the $\Gamma $ pocket of monolayer
TMD. We calculate the topological properties, the edge state structure, and the
current phase relation in a Josephson junction geometry of the nodal
crystalline phase. We show that while the nodal crystalline phase is
characterized by localized edge modes on non-self-reflecting boundaries, the
current phase relation exhibits a trivial $2\pi $ periodicity in the presence
of Rashba spin-orbit coupling.


  In this paper we present a method to derive classical solutions of the
Navier-Stokes equations for non-stationary initial value problems in domain
$\mathbb{R}^n$ ($n=2,3$ or higher). Exact solutions in $\mathbb{R}^2$ and
$\mathbb{R}^3$ in the presence of an externally specified force are obtained by
imposing certain restrictions on the initial data.


  We compute next-to-next-to-leading order QCD corrections to the gluon-induced
production cross section of Higgs boson pairs in the large top quark mass limit
using the soft-virtual approximation. In the limit of infinitely-heavy top
quark we confirm the results in the literature. We add two more expansion terms
in the inverse top quark mass to the $M_t\to\infty$ result. Since the $1/M_t$
expansion converges poorly, we try to improve on it by factorizing the exact
leading order cross section. We discuss two ways of doing that and conclude
that the finite top quark mass effects shift the cross section at most by about
10\% at next-to-leading order and by about 5\% at next-to-next-to-leading
order.


  In this paper we study weighted estimates for the multi-frequency
$\omega-$Calder\'{o}n-Zygmund operators $T$ associated with the frequency set
$\Theta=\{\xi_1,\xi_2,\dots,\xi_N\}$ and modulus of continuity $\omega$
satisfying the usual Dini condition. We use the modern method of domination by
sparse operators and obtain bounds $\|T\|_{L^p(w)\rightarrow L^p(w)}\lesssim
N^{|\frac{1}{r}-\frac{1}{2}|}[w]_{\mathbb{A}_{p/r}}^{max(1,\frac{1}{p-r})},~1\leq
r<p<\infty,$ for the exponents of $N$ and $\mathbb{A}_{p/r}$ characteristic
$[w]_{\mathbb{A}_{p/r}}$.


  Linear subspace models are pervasive in computational sciences and
particularly used for large datasets which are often incomplete due to privacy
issues or sampling constraints. Therefore, a critical problem is developing an
efficient algorithm for detecting low-dimensional linear structure from
incomplete data efficiently, in terms of both computational complexity and
storage.
  In this paper we propose a streaming subspace estimation algorithm called
Subspace Navigation via Interpolation from Partial Entries (SNIPE) that
efficiently processes blocks of incomplete data to estimate the underlying
subspace model. In every iteration, SNIPE finds the subspace that best fits the
new data block but remains close to the previous estimate. We show that SNIPE
is a streaming solver for the underlying nonconvex matrix completion problem,
that it converges globally to a stationary point of this program regardless of
initialization, and that the convergence is locally linear with high
probability. We also find that SNIPE shows state-of-the-art performance in our
numerical simulations.


  Given a fibered link, consider the characteristic polynomial of the monodromy
restricted to first homology. This generalizes the notion of the Alexander
polynomial of a knot. We define a construction, called iterated plumbing, to
create a sequence of fibered links from a given one. The resulting sequence of
characteristic polynomials has the same form as those arising in work of Salem
and Boyd in their study of distributions of Salem and P-V numbers. From this we
deduce information about the asymptotic behavior of the large roots of the
generalized Alexander polynomials, and define a new poset structure for Salem
fibered links.


  We propose an additional term in the classical gravitational force law, which
is repelling in nature, and which may solve the dark matter problem. As an
inverse cube field interaction, it operates over 4 real spatial dimensions and
its effect on our observable 3-D space may account both for flat rotation
curves and standard Newtonian dynamics at small radial distances. By utilizing
cosmological clustering scales, we can derive the universal interaction
strength, and show that this naturally leads to an altered Planck mass that
becomes the neutron/proton rest mass. Moreover, the correct value for the
electron rest mass can be predicted using only classical electrostatics coupled
with the current theory. On cosmological scales, the interaction easily
accounts for the acceleration of the Hubble flow.


  We address three genuine phantom dark energy models where each of them
induces the particular future events known as Big Rip, Little Rip and Little
Sibling of the Big Rip. The background models are fully determined by a given
dark energy equation of state. We first observationally constrain the
corresponding model parameters that characterise each paradigm using the
available data of supernova type Ia, Cosmic Microwave Background and Baryonic
Acoustic Oscillations by using a Markov Chain Monte Carlo method. The obtained
fits are used to solve numerically the first order cosmological perturbations.
We compute the evolution of the density contrast of (dark) matter and DE, from
the radiation dominated era till a totally DE dominated universe. Then, the
obtained results are compared with respect to $\Lambda$CDM. We obtain the
predicted current matter power spectrum and the evolution of $f\sigma_8$ given
by the models studied in this work. Finally, the models are tested by computing
the reduced $\chi^2$ for the `Gold2017' $f\sigma_8$ dataset.


  Visible light communications (VLC) is gaining interest as one of the enablers
of short-distance, high-data-rate applications, in future beyond 5G networks.
Moreover, non-orthogonal multiple-access (NOMA)-enabled schemes have recently
emerged as a promising multiple-access scheme for these networks that would
allow realization of the target spectral efficiency and user fairness
requirements. The integration of NOMA in the widely adopted orthogonal
frequency-division multiplexing (OFDM)-based VLC networks would require an
optimal resource allocation for the pair or the cluster of users sharing the
same subcarrier(s). In this paper, the max-min rate of a multi-cell indoor
centralized VLC network is maximized through optimizing user pairing,
subcarrier allocation, and power allocation. The joint complex optimization
problem is tackled using a low-complexity solution. At first, the user pairing
is assumed to follow the divide-and-next-largest-difference user-pairing
algorithm (D-NLUPA) that can ensure fairness among the different clusters.
Then, subcarrier allocation and power allocation are solved iteratively through
both the Simulated Annealing (SA) meta-heuristic algorithm and the bisection
method. The obtained results quantify the achievable max-min user rates for the
different relevant variants of NOMA-enabled schemes and shed new light on both
the performance and design of multi-user multi-carrier NOMA-enabled centralized
VLC networks.


  The phenomena of odd-parity magnetoresistance and the planar Hall effect are
deeply entwined with ferromagnetism. The intrinsic magnetization of the ordered
state permits these unusual and rarely observed manifestations of Onsager's
theorem when time reversal symmetry is broken at zero applied field. Here we
study two classes of ferromagnetic materials, rare-earth magnets with high
intrinsic coercivity and antiferromagnetic pyrochlores with strongly-pinned
ferromagnetic layers at domain walls, which both exhibit odd-parity
magnetoresistive behavior. The peculiar angular variation of the response with
respect to the relative alignments of the magnetization, magnetic field, and
current reveal the two underlying microscopic mechanisms:
spin-polarization-dependent scattering of a Zeeman-shifted Fermi surface and
magnetoresistance driven by the anomalous velocity physics usually associated
with the anomalous Hall effect.


  Fault diagnosis has attracted extensive attention for its importance in the
exceedingly fault management framework for cloud virtualization, despite the
fact that fault diagnosis becomes more difficult due to the increasing
scalability and complexity in a heterogeneous environment for a virtualization
technique. Most existing fault diagnoses methods are based on active probing
techniques which can be used to detect the faults rapidly and precisely.
However, most of those methods suffer from the limitation of traffic overhead
and diagnosis of faults, which leads to a reduction in system performance. In
this paper, we propose a new hybrid model named accelerated fault diagnosis
invention (AFDI) to monitor various system metrics for VMs and physical server
hosting, such as CPU, memory, and network usages based on the severity of fault
levels and anomalies. The proposed method takes the advantages of the
multi-valued decision diagram (MDD), A Naive Bayes Classifier (NBC) models and
virtual sensors cloud to achieve high availability for cloud services.


  We report dissipative magnon-photon coupling caused by cavity Lenz effect,
where the magnons in a magnet induce a rf current in the cavity, leading to a
cavity back action that impedes the magnetization dynamics. This effect is
revealed in our experiment as level attraction with a coalescence of hybridized
magnon-photon modes, which is distinctly different from level repulsion with
mode anticrossing caused by coherent magnon-photon coupling. We develop a
method to control the in- terpolation of coherent and dissipative magnon-photon
coupling, and observe a matching condition where the two effects cancel. Our
work sheds light on the so-far hidden side of magnon-photon coupling, opening a
new avenue for controlling and utilizing light-matter interactions.


  We present several expected properties of the holomorphic Floer theory of a
holomorphic symplectic manifold. In particular, we propose a conjecture
relating holomorphic Floer theory of Hitchin integrable systems and
Donaldson-Thomas invariants of non-compact Calabi-Yau 3-folds. More generally,
we conjecture that the BPS spectrum of a $\mathcal{N}=2$ 4-dimensional quantum
field theory can be recovered from the holomorphic Floer theory of the
corresponding Seiberg-Witten integrable system.


  The ability in experiments to control the relative twist angle between
successive layers in two-dimensional (2D) materials offers a new approach to
manipulating their electronic properties; we refer to this approach as
"twistronics". A major challenge to theory is that, for arbitrary twist angles,
the resulting structure involves incommensurate (aperiodic) 2D lattices. Here,
we present a general method for the calculation of the electronic density of
states of aperiodic 2D layered materials, using parameter-free hamiltonians
derived from ab initio density-functional theory. We use graphene, a semimetal,
and MoS$_2$, a representative of the transition metal dichalcogenide (TMDC)
family of 2D semiconductors, to illustrate the application of our method, which
enables fast and efficient simulation of multi-layered stacks in the presence
of local disorder and external fields. We comment on the interesting features
of their Density of States (DoS) as a function of twist-angle and local
configuration and on how these features can be experimentally observed.


  Discretizing a solution in the Fourier domain rather than the time domain
presents a significant advantage in solving transport problems that vary
smoothly and periodically in time, such as cardiorespiratory flows. The finite
element solution of the resulting time-spectral formulation is investigated
here for the convection-diffusion equations. In addition to the baseline
Galerkin's method, we consider stabilized approaches inspired by the streamline
upwind Petrov/Galerkin (SUPG), Galerkin/least square (GLS), and variational
multiscale (VMS) methods. We also introduce a new augmented SUPG (ASU) method
that, by design, produces a nodally exact solution in one dimension for
piecewise linear interpolation functions. Comparing these five methods using
1D, 2D, and 3D canonical test cases shows while the ASU is most accurate
overall, it exhibits stability issues in extremely oscillatory flows with a
high Womersley number in 3D. The GLS method, which is identical to the VMS for
this problem, presents an attractive alternative due to its excellent stability
and reasonable accuracy.


  The observation of a compact object with a mass of $2.50-2.67M_{\odot}$ on
August 14, 2019, by the LIGO Scientific and Virgo collaborations (LVC) has the
potential to improve our understanding of the supranuclear equation of state.
While the gravitational-wave analysis of the LVC suggests that GW190814 likely
was a binary black hole system, the secondary component could also have been
the heaviest neutron star observed to date. We use our previously derived
nuclear-physics-multimessenger astrophysics framework to address the nature of
this object. Based on our findings, we determine GW190814 to be a binary black
hole merger with a probability of $>99.9\%$. Even if we weaken previously
employed constraints on the maximum mass of neutron stars, the probability of a
binary black hole origin is still $\sim 81\%$. Furthermore, we study the impact
that this observation has on our understanding of the nuclear equation of state
by analyzing the allowed region in the mass-radius diagram of neutron stars for
both a binary black hole or neutron star--black hole scenario. We find that the
unlikely scenario in which the secondary object was a neutron star requires
rather stiff equations of state with a maximum speed of sound $c_s\geq
\sqrt{0.6}$ times the speed of light, while the binary black hole scenario does
not offer any new insight.


  Three types of nonlinear Schrodinger models with multiple length scales are
considered. It is shown that the length-scale competition universally results
into arising of new localized stationary states. Multistability phenomena with
a controlled switching between stable states become possible.


  In this work, we characterize a class of nonlinear monotone dynamical systems
that have a certain translation invariance property which goes by the name of
plus-homogeneity; usually called "topical" systems. Such systems need not be
asymptotically stable, since they are merely nonexpansive but not contractive.
Thus, we introduce a stricter version of monotonicity, termed "type-K" in honor
of Kamke, and we prove the asymptotic stability of the equilibrium points, as
well as the convergence of all trajectories to such equilibria for type-K
monotone and plus-homogeneous systems: we call them "K-topical". Since topical
maps are the natural nonlinear counterpart of linear maps defined by
row-stochastic matrices, which are a cornerstone in the convergence analysis of
linear multi-agent systems (MASs), we exploit our results for solving the
consensus problem over nonlinear K-topical MASs. We first provide necessary and
sufficient conditions on the local interaction rules of the agents ensuring the
K-topicality of a MAS. Then, we prove that the agents achieve consensus
asymptotically if the graph describing their interactions contains a globally
reachable node. Finally, several examples for continuous-time and discrete-time
systems are discussed to corroborate the enforceability of our results in
different applications.


  Tensegrity robots, composed of rigid rods and flexible cables, exhibit high
strength-to-weight ratios and significant deformations, which enable them to
navigate unstructured terrains and survive harsh impacts. They are hard to
control, however, due to high dimensionality, complex dynamics, and a coupled
architecture. Physics-based simulation is a promising avenue for developing
locomotion policies that can be transferred to real robots. Nevertheless,
modeling tensegrity robots is a complex task due to a substantial sim2real gap.
To address this issue, this paper describes a Real2Sim2Real (R2S2R) strategy
for tensegrity robots. This strategy is based on a differentiable physics
engine that can be trained given limited data from a real robot. These data
include offline measurements of physical properties, such as mass and geometry
for various robot components, and the observation of a trajectory using a
random control policy. With the data from the real robot, the engine can be
iteratively refined and used to discover locomotion policies that are directly
transferable to the real robot. Beyond the R2S2R pipeline, key contributions of
this work include computing non-zero gradients at contact points, a loss
function for matching tensegrity locomotion gaits, and a trajectory
segmentation technique that avoids conflicts in gradient evaluation during
training. Multiple iterations of the R2S2R process are demonstrated and
evaluated on a real 3-bar tensegrity robot.


  Estimating the temperature and metal abundance of the intracluster and the
intragroup media is crucial to determine their global metal content and to
determine fundamental cosmological parameters. When a spatially resolved
temperature or abundance profile cannot be recovered from observations (e.g.,
for distant objects), or deprojection is difficult (e.g., due to a significant
non-spherical shape), only global average temperature and abundance are
derived. After introducing a general technique to build hydrostatic gaseous
distributions of prescribed density profile in potential wells of any shape, we
compute the global mass weighted and emission weighted temperature and
abundance for a large set of barotropic equilibria and an observationally
motivated abundance gradient. We also compute the spectroscopic-like
temperature that is recovered from a single temperature fit of observed
spectra. The derived emission weighted abundance and temperatures are higher by
50% to 100% than the corresponding mass weighted quantities, with overestimates
that increase with the gas mean temperature. Spectroscopic temperatures are
intermediate between mass and luminosity weighted temperatures. Dark matter
flattening does not lead to significant differences in the values of the
average temperatures or abundances with respect to the corresponding spherical
case (except for extreme cases).


  We combine small angle scattering experiments and simulations to investigate
the internal structure and interactions of composite
Poly(N-isopropylacrylamide)-Poly(ethylene glycol) (PNIPAM-PEG) microgels. At
low temperatures the experimentally determined form factors and the simulated
density profiles indicate a loose internal particle structure with an extended
corona, that can be modeled as a star-like object. Increasing temperature
across the volumetric phase transition, the form factor develops an inflection
which, using simulations, is interpreted as arising from a configuration in
which PEG chains are incorporated in the interior of the PNIPAM network. In
this configuration a peculiar density profile characterized by two dense,
separate regions is observed, at odds with configurations in which the PEG
chains reside on the surface of the PNIPAM core. The conformation of the PEG
chains have also profound effects on the interparticle interactions: While
chains on the surface reduce the solvophobic attractions typically experienced
by PNIPAM particles at high temperatures, PEG chains inside the PNIPAM network
shift the onset of attractive interaction at even lower temperatures. Our
results show that by tuning the morphology of the composite microgels we can
qualitatively change both their structure and their mutual interactions,
opening the way to explore new collective behaviors of these objects.


  In this article we demonstrate the injection locking of recently demonstrated
spintronic feedback nano oscillator to microwave magnetic fields at integers as
well fractional multiples of its auto oscillation frequency. Feedback
oscillators have delay as a new degree of freedom which is absent for
spin-transfer torque based oscillators, which gives rise to side peaks along
with a main peak. We show that it is also possible to lock the oscillator on
its side band peaks, which opens a new avenue to phase locked oscillators with
large frequency differences. We observe that for low driving fields, side band
locking improves the quality factor of the main peak, whereas for higher
driving fields the main peak is suppressed. Further, measurements at two field
angles provide some insight into the role of symmetry of oscillation orbit in
determining the fractional locking.


  Pre-main sequence (PMS) stars are known to produce powerful X-ray flares
which resemble magnetic reconnection solar flares scaled by factors up to 10^4.
However, numerous puzzles are present including the structure of X-ray emitting
coronae and magnetospheres, effects of protoplanetary disks, and effects of
stellar rotation. To investigate these issues in detail, we examine 216 of the
brightest flares from 161 PMS stars observed in the Chandra Orion Ultradeep
Project (COUP). These constitute the largest homogeneous dataset of PMS, or
indeed stellar flares at any stellar age, ever acquired. Our effort is based on
a new flare spectral analysis technique that avoids nonlinear parametric
modeling. It can be applied to much weaker flares and is more sensitive than
standard methods. We provide a catalog with >30 derived flare properties and an
electronic atlas for this unique collection of stellar X-ray flares. The
current study (Paper I) examines the flare morphologies, and provides general
comparison of COUP flare characteristics with those of other active X-ray stars
and the Sun. Paper II will concentrate on relationships between flare behavior,
protoplanetary disks, and other stellar properties. Several results are
obtained. First, the COUP flares studied here are among the most powerful,
longest, and hottest stellar X-ray flares ever studied. Second, no significant
statistical differences in peak flare luminosity or temperature distributions
are found among different morphological flare classes, suggesting a common
underlying mechanism for all flares. Third, comparison with the general
solar-scaling laws indicates that COUP flares may not fit adequately proposed
power-temperature and duration-temperature solar-stellar fits. Fourth, COUP
super-hot flares are found to be brighter but shorter than ... ABRIDGED


  We have studied the resistivity, $\rho$, of a two-dimensional electron system
in silicon in the temperature range 200 mK < T < 7.5 K at zero magnetic field
at low electron densities, when the electron system is in the insulating
regime. Our results show that at an intermediate temperature range $\rho=\rho_0
exp[(T_0/T)^{1/2}]$ for at least four orders of magnitude up to 3x10^9 Ohms.
This behavior is consistent with the existence of a Coulomb gap. Near the
metal/insulator transition, the prefactor was found to be close to $h/e^2$, and
resistivity scales with temperature. For very low electron densities, $n_s$,
the prefactor diminishes with diminishing $n_s$. A comparison with the theory
shows that a specific set of conditions are necessary to observe the behavior
of resistivity consistent with the existence of the Coulomb gap.


  We show that extremal Kerr black holes are sensitive probes of new physics.
Stringy or quantum corrections to general relativity are expected to generate
higher-curvature terms in the gravitational action. We show that in the
presence of these terms, asymptotically flat extremal rotating black holes have
curvature singularities on their horizon. Furthermore, near-extremal black
holes can have large yet finite tidal forces for infalling observers. In
addition, we consider five-dimensional extremal charged black holes and show
that higher-curvature terms can have a large effect on the horizon geometry.