  We conducted an analysis of the distribution of elements from lithium to
europium in 200 dwarfs in the solar neighbourhood ~20 pc with temperatures in
the range 4800-6200 K and metallicities [Fe/H] higher than -0.5 dex.
Determinations of atmospheric parameters and the chemical composition of the
dwarfs were taken from our previous studies. We found that the lithium
abundances in the planet-hosting solar-analog stars of our sample were lower
than those in the stars without planetary systems. Our results reveal no
significant differences exceeding the determination errors for the abundances
of investigated elements, except for aluminium and barium, which are more and
less abundant in the planet-hosting stars, respectively. We did not find
confident dependences of the lithium, aluminium and barium abundances on the
ages of our target stars (which is probable because of the small number of
stars). Furthermore, we found no correlation between the abundance differences
in [El/Fe] and the condensation temperature (Tcond) for stars in the 16 Cyg
binary system, unlike the case for 51 Peg (HD 217014), for which a slight
excess of volatile elements and a deficit of refractories were obtained
relative to those of solar twins. We found that one of the components of 16 Cyg
exhibits a slightly higher average abundance than its counterpart
(<[El/H](A-B)> = 0.08+/-0.02 dex); however, no significant abundance trend
versus Tcond was observed. Owing to the relatively large errors, we cannot
provide further constraints for this system.


  We present some statistics of turbulence monitoring at the Plateau de Calern
(France), with the Generalised Differential Image Motion Monitor (GDIMM). This
instrument allows to measure integrated parameters of the atmospheric
turbulence, i.e. seeing, isoplanatic angle, coherence time and outer scale,
with 2 minutes time resolution. It is running routinely since November 2015 and
is now fully automatic. A large dataset has been collected, leading to the
first statistics of turbulence above the Plateau de Calern.


  Fold maps are smooth maps at each singular point of which it is represented
as the product map of a Morse function and the identity map.
  Round fold maps are, in short, such maps the sets of all singular points of
which are embedded concentrically. They are, as Morse functions, important in
understanding the topologies and the differentiable structures in geometric
ways.
  In the present paper, we study cohomology rings of $3$-dimensional manifolds
admitting round fold maps into the plane and see that difference of the
coefficient rings and topological types of round fold maps are closely related.
This is an explicit precise new study on our previous study, showing that a
$3$-dimensional closed and orientable manifold is a so-called {\it graph
manifold}, or a manifold obtained by gluing so-called circle bundles over
surfaces along tori, if and only if it admits a round fold map into the plane.
We also show another exposition on classifications of graph manifolds admitting
such maps whose topological types are of a certain simplest class.


  Flows over time enable a mathematical modeling of traffic that changes as
time progresses. In order to evaluate these dynamic flows from a game
theoretical perspective we consider the price of anarchy (PoA). In this paper
we study the impact of spillback effects on the PoA, which turn out to be
substantial. It is known that, in general, the PoA is unbounded in the
spillback setting. We extend this by showing that it is still unbounded even
when considering networks with unit edge capacities and that the Braess ratio
can be arbitrarily large. In contrast to that, we show that on a fixed network
the PoA as a function of the flow amount is bounded by a constant and also
upper bound the PoA for the set of networks where the outflow capacities
satisfy certain constraints depending on the quickest flow. This upper bound
only depends on the worst spillback factor of the Nash flows over time of the
given network. It therefore provides a way to quantify the impact of spillback
to the quality of the dynamic equilibria. In addition, we show the surprising
fact that the introduction of spillback behavior can actually speed up dynamic
equilibria in some networks.


  We propose a new model for the emergence of blood capillary networks. We
assimilate the tissue and extra cellular matrix as a porous medium, using
Darcy's law for describing both blood and intersticial fluid flows. Oxygen
obeys a convection-diffusion-reaction equation describing advection by the
blood, diffusion and consumption by the tissue. Discrete agents named capillary
elements and modelling groups of endothelial cells are created or deleted
according to different rules involving the oxygen concentration gradient, the
blood velocity, the sheer stress or the capillary element density. Once
created, a capillary element locally enhances the hydraulic conductivity
matrix, contributing to a local increase of the blood velocity and oxygen flow.
No connectivity between the capillary elements is imposed. The coupling between
blood, oxygen flow and capillary elements provides a positive feedback
mechanism which triggers the emergence of a network of channels of high
hydraulic conductivity which we identify as new blood capillaries. We provide
two different, biologically relevant geometrical settings and numerically
analyze the influence of each of the capillary creation mechanism in detail.
All mechanisms seem to concur towards a harmonious network but the most
important ones are those involving oxygen gradient and sheer stress. A detailed
discussion of this model with respect to the literature and its potential
future developments concludes the paper.


  Radio frequency (RF) communications offer reliable but low data rates and
energy-inefficient satellite links, while free-space optical (FSO) promises
high bandwidth but struggles with disturbances imposed by atmospheric effects.
A hybrid RF/FSO architecture aims to achieve optimal reliability along with
high data rates for space communications. Accurate prediction of dynamic
ground-to-satellite FSO link availability is critical for routing decisions in
low-earth orbit constellations. In this paper, we propose a system leveraging
ubiquitous RF links to proactively forecast FSO link degradation prior to
signal drops below threshold levels. This enables pre-calculation of rerouting
to maximally maintain high data rate FSO links throughout the duration of
weather effects. We implement a supervised learning model to anticipate FSO
attenuation based on the analysis of RF patterns. Through the simulation of a
dense lower earth orbit (LEO) satellite constellation, we demonstrate the
efficacy of our approach in a simulated satellite network, highlighting the
balance between predictive accuracy and prediction duration. An emulated cloud
attenuation model is proposed which provides insight into the temporal profiles
of RF signals and their correlation to FSO channel dynamics. Our investigation
sheds light on the trade-offs between prediction horizon and accuracy arising
from RF beacon proximity, achieving a prediction accuracy of 86\% with 16 RF
beacons.


  Asteroid (162173) Ryugu was the first spinning-top-shaped asteroid to be
closely approached by a probe, the Hayabusa2 spacecraft, which sent numerous
high-resolution images of Ryugu to the Earth and revealed the nature of this
type of asteroid. One of the notable features of Ryugu is the equatorial ridge,
which is considered the result of rapid spin in the past. Despite the advanced
age of the ridge, indicated by the presence of numerous craters, the ridge
exhibits a bluish color, indicating that it is covered with fresh material. In
addition to Ryugu, many other asteroids have similar blue areas, which are
considered the result of ejecta emplacement. We examined the distribution of
ejecta blankets from actual craters on Ryugu to assess ejecta emplacement as a
possible origin of Ryugu's bluer units. We determined that when Ryugu's
rotation was fast, ejecta from craters formed at lower latitudes accumulated
along the equator, which may explain the bluish color of the equatorial ridge.
On the other hand, ejecta emplacement does not fully explain the bluish color
of Tokoyo Fossa, although we attempted to find the corresponding ejecta
blankets.


  We present an alternative technique for evaluating multiloop Feynman
diagrams, using the integration by fractional expansion method. Here we
consider generic diagrams that contain propagators with radiative corrections
which topologically correspond to recursive constructions of bubble type
diagrams. The main idea is to reduce these subgraphs, replacing them by their
equivalent multiregion expansion. One of the main advantages of this
integration technique is that it allows to reduce massive cases with the same
degree of difficulty as in the massless case.


  Weakly supervised object detection (WSOD) is a challenging task when provided
with image category supervision but required to simultaneously learn object
locations and object detectors. Many WSOD approaches adopt multiple instance
learning (MIL) and have non-convex loss functions which are prone to get stuck
into local minima (falsely localize object parts) while missing full object
extent during training. In this paper, we introduce a continuation optimization
method into MIL and thereby creating continuation multiple instance learning
(C-MIL), with the intention of alleviating the non-convexity problem in a
systematic way. We partition instances into spatially related and class related
subsets, and approximate the original loss function with a series of smoothed
loss functions defined within the subsets. Optimizing smoothed loss functions
prevents the training procedure falling prematurely into local minima and
facilitates the discovery of Stable Semantic Extremal Regions (SSERs) which
indicate full object extent. On the PASCAL VOC 2007 and 2012 datasets, C-MIL
improves the state-of-the-art of weakly supervised object detection and weakly
supervised object localization with large margins.


  The average multicast rate (AMR) is analyzed in a multicast channel utilizing
analog beamforming with finite-alphabet inputs, considering statistical channel
state information (CSI). New expressions for the AMR are derived for
non-cooperative and cooperative multicasting scenarios. Asymptotic analyses are
conducted in the high signal-to-noise ratio regime to derive the array gain and
diversity order. It is proved that the analog beamformer influences the AMR
through its array gain, leading to the proposal of efficient beamforming
algorithms aimed at maximizing the array gain to enhance the AMR.


  We present a numerical framework for approximating unknown governing
equations using observation data and deep neural networks (DNN). In particular,
we propose to use residual network (ResNet) as the basic building block for
equation approximation. We demonstrate that the ResNet block can be considered
as a one-step method that is exact in temporal integration. We then present two
multi-step methods, recurrent ResNet (RT-ResNet) method and recursive ReNet
(RS-ResNet) method. The RT-ResNet is a multi-step method on uniform time steps,
whereas the RS-ResNet is an adaptive multi-step method using variable time
steps. All three methods presented here are based on integral form of the
underlying dynamical system. As a result, they do not require time derivative
data for equation recovery and can cope with relatively coarsely distributed
trajectory data. Several numerical examples are presented to demonstrate the
performance of the methods.


  The exclusive rare radiative B meson decay to the orbitally excited tensor
K_2^*(1430) meson is investigated in the framework of the relativistic quark
model based on the quasipotential approach in quantum field theory. The
calculated branching ratio BR(B --> K_2^*(1430)\gamma)=(1.7\pm 0.6)\times
10^{-5} as well as the ratio BR(B --> K_2^*(1430)\gamma)/BR(B -->
K^*(892)\gamma)=0.38\pm 0.08 is found in a good agreement with recent
experimental data from CLEO.


  Possible mixing and its consequences of heavy cascade baryons \Xi-\Xi^\prime
is analyzed and its importance in the analysis of their characteristics is
shown within the non-relativistic quark model and QCD sum rules.


  We demonstrate a systematic approach to Heisenberg-limited lithographic image
formation using four-mode reciprocal binominal states. By controlling the
exposure pattern with a simple bank of birefringent plates, any pixel pattern
on a $(N+1) \times (N+1)$ grid, occupying a square with the side half a
wavelength long, can be generated from a $2 N$-photon state.


  It is well-known that the LIE(Locally Induction Equation) admit soliton-type
solutions and same soliton solutions arise from different and apparently
irrelevant physical models. By comparing the solitons of LIE and Killing
magnetic geodesics, we observe that these solitons are essentially decided by
two families of isometries of the domain and the target space respectively.
With this insight, we propose the new concept of geometric solitons of
Hamiltonian flows on manifolds, such as geometric Schr\"odinger flows and KdV
flows for maps. Moreover, we give several examples of geometric solitons of the
Schr\"odinger flow and geometric KdV flow, including magnetic curves as
geometric Schr\"odinger solitons and explicit geometric KdV solitons on
surfaces of revolution.


  The classical problem of optimal transportation can be formulated as a linear
optimization problem on a convex domain: among all joint measures with fixed
marginals find the optimal one, where optimality is measured against a cost
function. Here we consider a natural but largely unexplored variant of this
problem by imposing a pointwise constraint on the joint (absolutely continuous)
measures: among all joint densities with fixed marginals and which are
dominated by a given density, find the optimal one. For this variant, we show
local non-degeneracy of the cost function implies every minimizer is extremal
in the convex set of competitors, hence unique. An appendix develops rudiments
of a duality theory for this problem, which allows us to compute several
suggestive examples.


  Humans are experts in making decisions for challenging driving tasks with
uncertainties. Many efforts have been made to model the decision-making process
of human drivers at the behavior level. However, limited studies explain how
human drivers actively make reliable sequential decisions to complete
interactive driving tasks in an uncertain environment. This paper argues that
human drivers intently search for actions to reduce the uncertainty of their
perception of the environment, i.e., perceptual uncertainty, to a low level
that allows them to make a trustworthy decision easily. This paper provides a
proof of concept framework to empirically reveal that human drivers' perceptual
uncertainty decreases when executing interactive tasks with uncertainties. We
first introduce an explainable-artificial intelligence approach (i.e., SHapley
Additive exPlanation, SHAP) to determine the salient features on which human
drivers make decisions. Then, we use entropy-based measures to quantify the
drivers' perceptual changes in these ranked salient features across the
decision-making process, reflecting the changes in uncertainties. The
validation and verification of our proposed method are conducted in the highway
on-ramp merging scenario with congested traffic using the INTERACTION dataset.
Experimental results support that human drivers intentionally seek information
to reduce their perceptual uncertainties in the number and rank of salient
features of their perception of environments to make a trustworthy decision.


  We compare various concepts of attractor in the context of non-autonomous
dynamical systems. Then, we prove an appropriate version of the Pliss reduction
principle for non-autonomous differential systems with rapidly oscillating
coefficients.


  Negative reflection occurs when light is reflected towards the same side of
the normal to the boundary from which it is incident. This exotic optical
phenomenon, which provides a new avenue towards light manipulation, is not only
yet to be visualized in real space but remains largely unexplored both at the
nanoscale and in natural media. Here, we directly visualize nanoscale-confined
polaritons negatively reflecting on subwavelength mirrors fabricated in a
low-loss van der Waals crystal. Our near-field nanoimaging results unveil an
unconventional and broad tunability of both the polaritonic wavelength and
direction of propagation upon negative reflection. Based on these findings, we
introduce a novel device in nano-optics: a hyperbolic nanoresonator, in which
hyperbolic polaritons with different momenta reflect back to a common point
source, enhancing its intensity. These results pave the way to realize
nanophotonics in low-loss natural media, providing a novel and efficient route
to confine and control the flow of light at the nanoscale, key for future
optical on-chip nanotechnologies.


  Fundamental differences between fermions and bosons are revealed in their
spin and distribution statistics as well as the discrete symmetries they obey
(charge, parity and time). While significant progress has been made on
fermionic topological phases of matter with time-reversal symmetry, the bosonic
counterpart still remains elusive. We present here a spin-1 bosonic topological
insulator for light by utilizing a Dirac-Maxwell correspondence. Departing from
structural photonic approaches which mimic the pseudo-spin-\textonehalf{}
behavior of electrons, we exploit the integer spin and discrete symmetries of
the photon to formulate a distinct bosonic topological phase of matter. We
introduce a bosonic Kramers theorem and the photonic equivalent of topological
quantization, which arises solely from photon spin. Our continuum field theory
predicts that photons acquire a mass in the presence of a spatio-temporally
dispersive degenerate chirality, a unique form of magneto-electric coupling
inside matter fundamentally different from well-known chirality,
magneto-electricity, gyrotropy or bi-anisotropy. We predict that this unique
dispersive (non-local) degenerate chiral medium has anomalous parity and
time-reversal symmetries and if found in nature will exhibit a gapped Quantum
spin-1 Hall bosonic phase. Photons do not possess a conductivity transport
parameter which can be quantized (unlike electronic systems), but we predict
that photon spin quantization of symmetry-protected edge states is amenable to
experimental isolation leading to a new bosonic phase of matter.


  The recent detections of gravitational waves by the advanced LIGO and Virgo
detectors open up new tests of modified gravity theories in the strong-field
and dynamical, extreme gravity regime. Such tests rely sensitively on the phase
evolution of the gravitational waves, which is controlled by the
energy-momentum carried by such waves out of the system. We here study four
different methods for finding the gravitational wave stress-energy
pseudo-tensor in gravity theories with any combination of scalar, vector, or
tensor degrees of freedom. These methods rely on the second variation of the
action under short-wavelength averaging, the second perturbation of the field
equations in the short-wavelength approximation, the construction of an energy
complex leading to a Landau-Lifshitz tensor, and the use of Noether's theorem
in field theories about a flat background. We apply these methods in General
Relativity, scalar-tensor theories and Einstein-\AE{}ther theory to find the
gravitational wave stress-energy pseudo-tensor and calculate the rate at which
energy and linear momentum is carried away from the system. The stress-energy
tensor and the rate of linear momentum loss in Einstein-\AE{}ther theory are
presented here for the first time. We find that all methods yield the same rate
of energy loss, although the stress-energy pseudo-tensor can be functionally
different. We also find that the Noether method yields a stress-energy tensor
that is not symmetric or gauge-invariant, and symmetrization via the Belinfante
procedure does not fix these problems because this procedure relies on Lorentz
invariance, which is spontaneously broken in Einstein-\AE{}ther theory. The
methods and results found here will be useful for the calculation of
predictions in modified gravity theories that can then be contrasted with
observations.


  Type Iax supernovae (SN Iax) are the largest known class of peculiar white
dwarf supernovae, distinct from normal Type Ia supernovae (SN Ia). The unique
properties of SN Iax, especially their strong photospheric lines out to
extremely late times, allow us to model their optical spectra and derive
physical parameters for the long-lasting photosphere. We present an extensive
spectral timeseries, including 21 new spectra, of SN Iax 2014dt from +11 to
+562 days after maximum light. We are able to reproduce the entire timeseries
with a self-consistent, nearly unaltered deflagration explosion model from Fink
et al. (2014) using TARDIS, an open-source radiative transfer code (Kerzendorf
& Sim 2014; Kerzendorf et al. 2023). We find that the photospheric velocity of
SN 2014dt slows its evolution between +64 and +148 days, which closely overlaps
the phase when we see SN 2014dt diverge from the normal spectral evolution of
SN Ia (+90 to +150 days). The photospheric velocity at these epochs,
~400$-$1000 km s$^{-1}$, may demarcate a boundary within the ejecta below which
the physics of SN Iax and normal SN Ia differ. Our results suggest that SN
2014dt is consistent with a weak deflagration explosion model that leaves
behind a bound remnant and drives an optically thick, quasi-steady-state wind
creating the photospheric lines at late times. The data also suggest that this
wind may weaken at epochs past +450 days, perhaps indicating a radioactive
power source that has decayed away.


  The paper is devoted to the characterization of the geometry of Prony curves
arising from spike-train signals. We give a sufficient condition which
guarantees the blowing up of the amplitudes of a Prony curve S in case where
some of its nodes tend to collide. We also give sufficient conditions on S
which guarantee a certain asymptotic behavior of its nodes near infinity.


  We present the results of Chandra and Suzaku X-ray observations of nine
moderate-redshift (0.16 < z < 0.42) clusters discovered via the Red-sequence
Cluster Survey (RCS). Surface brightness profiles are fitted to beta models,
gas masses are determined, integrated spectra are extracted within R2500, and
X-ray temperatures and luminosities are inferred. The Lx-Tx relationship
expected from self-similar evolution is tested by comparing this sample to our
previous X-ray investigation of nine high-redshift (0.6 < z < 1.0) optically
selected clusters. We find that optically selected clusters are systematically
less luminous than X-ray selected clusters of similar X-ray temperature at both
moderate and high-z. We are unable to constrain evolution in the Lx-Tx relation
with these data, but find it consistent with no evolution, within relatively
large uncertainties. To investigate selection effects, we compare the X-ray
properties of our sample to those of clusters in the representative X-ray
selected REXCESS sample, also determined within R2500. We find that while RCS
cluster X-ray properties span the entire range of those of massive clusters
selected by other methods, their average X-ray properties are most similar to
those of dynamically disturbed X-ray selected clusters. This similarity
suggests that the true cluster distribution might contain a higher fraction of
disturbed objects than are typically detected in X-ray selected surveys.


  We propose a scheme for dispersive readout of stored energy in one mode of a
nonlinear superconducting microwave ring resonator by detection of the
frequency shift of a second mode coupled to the first via a Kerr nonlinearity.
Symmetry is used to enhance the device responsivity while minimizing self
nonlinearity of each mode. Assessment of the signal to noise ratio indicates
that the scheme will function at the single photon level, allowing quantum
non-demolition measurement of the photon number state of one mode. Experimental
data from a simplified version of the device demonstrating the principle of
operation are presented.


  This paper proposes novel approaches to design hierarchical decentralized
robust controllers for homogeneous linear multi-agent systems (MASs) perturbed
by disturbances/noise. Firstly, based on LQR method, we present a systematic
procedure to design hierarchical decentralized optimal stabilizing controllers
for MASs without disturbances/noise. Next, a method for deriving reduced-order
hierarchical decentralized stabilizing controllers is presented by suitable
selections of the weighting matrices in the LQR performance index. Secondly,
the hierarchical decentralized robust controller designs in terms of
$H_{\infty}$ and $H_{2}$ norms are introduced, which include two different
scenarios namely general and LQR-based synthesis. For the general synthesis,
the robust controller gains are computed as solutions of a distributed convex
optimization problem with LMI constraints. On the other hand, for the LQR-based
design, the robust controller gains obtained from the general synthesis are
further verified as LQR stabilizing gains to be unified with the LQR-based
design when there are no disturbances/noise. This results in a hierarchical
decentralized inverse optimal control problem, for which we will propose a new
method to resolve it. Finally, several numerical examples are presented to
illustrate the effectiveness of the proposed approaches.


  For the representation-theoretic study of domestic string algebras,
Schr\"{o}er introduced a version of hammocks that are bounded discrete linear
orders. He introduced a finite combinatorial gadget called the bridge quiver,
which we modified in the prequel of this paper to get a variation called the
arch bridge quiver. Here we use it as a tool to provide an algorithm to compute
the order type of an arbitrary closed interval in such hammocks. Moreover, we
characterize the class of order types of these hammocks as the bounded discrete
ones amongst the class of finitely presented linear orders--the smallest class
of linear orders containing finite linear orders as well as $\omega$, and that
is closed under isomorphisms, order reversal, finite order sums and
lexicographic products.


  Motivated by the possibility of explaining the 3.5 keV line through dark
matter decaying to axion-like particles that subsequently convert to photons,
we study ALP-photon conversion for sightlines passing within 50 pc of the
galactic centre. Conversion depends on the galactic centre magnetic field which
is highly uncertain. For fields at low or mid-range of observational estimates
(10--100 $\mu$G), no observable signal is possible. For fields at the high
range of observational estimates (a pervasive poloidal mG field over the
central 150 pc) it is possible to generate sufficient signal to explain recent
observations of a 3.5 keV line in the galactic centre. In this scenario, the
galactic centre line signal comes predominantly from the region with $z > 20$
pc, reconciling the results from the Chandra and XMM-Newton X-ray telescopes.
The dark matter to ALP to photon scenario also naturally predicts the
non-observation of the 3.5 keV line in stacked galaxy spectra. We further
explore predictions for the line flux in galaxies and suggest a set of galaxies
that is optimised for observing the 3.5 keV line in this model.


  In this paper we prove the existence and uniqueness of the solution of Young
differential delay equations under weaker conditions than it is known in the
literature. We also prove the continuity and differentiability of the solution
with respect to the initial function and give an estimate for the growth of the
solution. The proofs use techniques of stopping times, Shauder-Tychonoff fixed
point theorem and a Gronwall-type lemma.


  We investigate Whitehead's asphericity question from a new perspective, using
results and techniques of the homotopy theory of finite topological spaces. We
also introduce a method of reduction to investigate asphericity based on the
interaction between the combinatorics and the topology of finite spaces.


  Let $X$ be a Banach space and $(\Omega,\Sigma)$ be a measure space. We
provide a characterization of sequences in the space of $X$-valued countably
additive measures on $\Omega,\Sigma)$ of bounded variation that generate
complemented copies of $\ell_1$. As application, we prove that if a dual Banach
space $E^*$ has Pe\l czy\'nski's property (V*) then so does the space of
$E^*$-valued countably additive measures with bounded variation. Another
application, we show that for a Banach space $X$, the space $\ell_\infty(X)$
contains a complemented copy of $\ell_1$ if and only if $X$ contains all
$\ell_1^n$ uniformly complemented.


  This thesis is a theoretical analysis of sample two- and one-dimensional
systems. The two-dimensional examples are the quantum Hall liquid and anomalous
paired states. The most widely accepted effective theory of the quantum Hall
liquid is based on the so-called Chern Simons Lagrangian, but it is not
entirely satisfactory. We obtain the first derivation of an alternative
effective theory from microscopic principles. Our formulation allows for a
first principles derivation of physical quantities such as the effective mass
and compressibility and contains the first analytical observation of the
magnetoroton. The formalism developed along the way is also applied to paired
states in anomalous supeconductors, a topic of much recent interest. The
one-dimenisonal system is the carbon nanotube. Gas uptake in nanotube bundles
is currently attracting a wealth of research with both applied and fundamental
implications. We propose adsorption of gases on the surface of a single tube,
finding strong correlations and symmetries that have not been observed yet. The
properties of these states are directly relevant to other one-dimensional
structures such as spin ladders and stripes and raise interesting and open
questions.


  Among the multiple 5D thick braneworld models that have been proposed in the
last years, in order to address several open problems in modern physics, there
is a specific one involving a tachyonic bulk scalar field. Delving into this
framework, a thick braneworld with a cosmological background induced on the
brane is here investigated. The respective field equations --- derived from the
model with a warped 5D geometry --- are highly non-linear equations, admitting
a non-trivial solution for the warp factor and the tachyon scalar field as
well, in a de Sitter 4D cosmological background. Moreover, the non-linear
tachyonic scalar field, that generates the brane in complicity with warped
gravity, has the form of a kink-like configuration. Notwithstanding, the
non-linear field equations restricting character does not allow one to easily
find thick brane solutions with a decaying warp factor which leads to the
localization of 4D gravity and other matter fields. We derive such a thick
brane configuration altogether in this tachyon-gravity setup. When analyzing
the spectrum of gravity fluctuations in the transverse traceless sector, the 4D
gravity is shown to be localized due to the presence of a {\it single} zero
mode bound state, separated by a continuum of massive Kaluza-Klein (KK) modes
by a mass gap. It contrasts with previous results, where there is a KK massive
bound excitation providing no clear physical interpretation. The mass gap is
determined by the scale of the metric parameter $H$. Finally, the corrections
to Newton's law in this model are computed and shown to decay exponentially. It
is in full compliance to corrections reported in previous results (up to a
constant factor) within similar braneworlds with induced 4D de Sitter metric,
despite the fact that the warp factor and the massive modes have a different
form.


  A phase reference has been a standard requirement in continuous-variable
quantum sensing and communication protocols. However, maintaining a phase
reference is challenging due to environmental fluctuations, preventing quantum
phenomena such as entanglement and coherence from being utilized in many
scenarios. We show that quantum communication and entanglement-assisted
communication without a phase reference are possible, when a short-time memory
effect is present. The degradation in the communication rate of classical or
quantum information transmission decreases inversely with the correlation time.
An exact solution of the quantum capacity and entanglement-assisted
classical/quantum capacity for pure dephasing channels is derived, where
non-Gaussian multipartite-entangled states show strict advantages over usual
Gaussian sources. For thermal-loss dephasing channels, lower bounds of the
capacities are derived. The lower bounds also extend to scenarios with fading
effect in the channel. In addition, for entanglement-assisted communication,
the lower bounds can be achieved by a simple phase-encoding scheme on two-mode
squeezed vacuum sources, when the noise is large.


  The discovery of diffuse sub-PeV gamma-rays by the Tibet AS$_\gamma$
Collaboration promises to revolutionize our understanding of the high-energy
astrophysical universe. It has been shown that these data broadly agree with
prior theoretical expectations. We study the impact of this discovery on a
well-motivated new physics scenario: PeV-scale decaying dark matter (DM).
Considering a wide range of final states in DM decay, a number of DM density
profiles, and numerous astrophysical background models, we find that these data
provide the most stringent limit on DM lifetime for various Standard Model
final states. In particular, we find that the strongest constraints are derived
for DM masses in between a few PeV to a few tens of PeV. Near-future data of
these high-energy gamma-rays can be used to discover PeV-scale decaying DM.


  The "scenario approach" provides an intuitive method to address chance
constrained problems arising in control design for uncertain systems. It
addresses these problems by replacing the chance constraint with a finite
number of sampled constraints (scenarios). The sample size critically depends
on Helly's dimension, a quantity always upper bounded by the number of decision
variables. However, this standard bound can lead to computationally expensive
programs whose solutions are conservative in terms of cost and violation
probability. We derive improved bounds of Helly's dimension for problems where
the chance constraint has certain structural properties. The improved bounds
lower the number of scenarios required for these problems, leading both to
improved objective value and reduced computational complexity. Our results are
generally applicable to Randomized Model Predictive Control of chance
constrained linear systems with additive uncertainty and affine disturbance
feedback. The efficacy of the proposed bound is demonstrated on an inventory
management example.


  In this paper we consider the problem of decomposing tensor products of
certain singular unitary representations of a semisimple Lie group G. Using
explicit models for these representations (constructed earlier by one of us) we
show that the decomposition is controlled by a reductive homogeneous space
G'/H'. Our procedure establishes a correspondence between certain unitary
representations of G and those of G'. This extends the usual
theta--correspondence for dual reductive pairs. As a special case we obtain a
correspondence between certain representations of real forms of E_7 and F_4.


  We study exact vacuum solutions to quadratic gravity (QG) of the Weyl types N
and III. We show that in an arbitrary dimension all Einstein spacetimes of the
Weyl type N with an appropriately chosen effective cosmological constant
$\Lambda$ are exact solutions to QG and we refer to explicitly known metrics
within this class.
  For type III Einstein spacetimes, an additional constraint follows from the
field equations of QG and examples of spacetimes obeying such constraint are
given. However, type III pp-waves do not satisfy this constraint and thus do
not solve QG.
  For type N, we also study a wider class of spacetimes admitting a pure
radiation term in the Ricci tensor. In contrast to the Einstein case, the field
equations of generic QG determine optical properties of the geometry and
restrict such exact solutions to the Kundt class. We provide examples of these
metrics.


  The experimental highlights from PHENIX are summarized from the point of view
of probing the properties of dense partonic matter produced at RHIC


  With the advent and recent ubiquity of foundation models, continual learning
(CL) has recently shifted from continual training from scratch to the continual
adaptation of pretrained models, seeing particular success on rehearsal-free CL
benchmarks (RFCL). To achieve this, most proposed methods adapt and restructure
parameter-efficient finetuning techniques (PEFT) to suit the continual nature
of the problem. Based most often on input-conditional query-mechanisms or
regularizations on top of prompt- or adapter-based PEFT, these PEFT-style RFCL
(P-RFCL) approaches report peak performances; often convincingly outperforming
existing CL techniques. However, on the other end, critical studies have
recently highlighted competitive results by training on just the first task or
via simple non-parametric baselines. Consequently, questions arise about the
relationship between methodological choices in P-RFCL and their reported high
benchmark scores. In this work, we tackle these questions to better understand
the true drivers behind strong P-RFCL performances, their placement w.r.t.
recent first-task adaptation studies, and their relation to preceding CL
standards such as EWC or SI. In particular, we show: (1) P-RFCL techniques
relying on input-conditional query mechanisms work not because, but rather
despite them by collapsing towards standard PEFT shortcut solutions. (2)
Indeed, we show how most often, P-RFCL techniques can be matched by a simple
and lightweight PEFT baseline. (3) Using this baseline, we identify the
implicit bound on tunable parameters when deriving RFCL approaches from PEFT
methods as a potential denominator behind P-RFCL efficacy. Finally, we (4)
better disentangle continual versus first-task adaptation, and (5) motivate
standard RFCL techniques s.a. EWC or SI in light of recent P-RFCL methods.


  We simulate the assembly dynamics of icosahedral capsids from subunits that
interconvert between different conformations (or quasi-equivalent states). The
simulations identify mechanisms by which subunits form empty capsids with only
one morphology but adaptively assemble into different icosahedral morphologies
around nanoparticle cargoes with varying sizes, as seen in recent experiments
with brome mosaic virus (BMV) capsid proteins. Adaptive cargo encapsidation
requires moderate cargo-subunit interaction strengths; stronger interactions
frustrate assembly by stabilizing intermediates with incommensurate curvature.
We compare simulation results to experiments with cowpea chlorotic mottle virus
empty capsids and BMV capsids assembled on functionalized nanoparticles and
suggest new cargo encapsidation experiments. Finally, we find that both empty
and templated capsids maintain the precise spatial ordering of subunit
conformations seen in the crystal structure even if interactions that preserve
this arrangement are favored by as little as the thermal energy, consistent
with experimental observations that different subunit conformations are highly
similar.


  We study the constraints of supersymmetry on the non-Abelian holonomy given
by U=P exp(i\int A), the path-ordered exponential of a connection A. For
theories with four supercharges, we show that A satisfies the tt* equations if
it is a function of chiral multiplets. In contrast, when A is a function of
vector multiplets, it satisfies the Bogomolnyi monopole equations. We describe
applications of these results to the Berry connection in supersymmetric quantum
mechanics.


  It is shown that the temperature of the resistive transition $T_r$ of a
superconducting film can be increased by a thin superconducting or normal
overlayer. For instance, deposition of a highly conductive thin overlayer onto
a dirty superconducting film can give rise to an "anti-proximity effect" which
manifests itself in an initial increase of $T_r(d_2)$ with the overlayer
thickness $d_2$ followed by a decrease of $T_r(d_2)$ at larger $d_2$. Such a
nonmonotonic thickness dependence of $T_r(d_2)$ results from the interplay of
the increase of a net superfluid density mitigating phase fluctuations and the
suppression of the critical temperature $T_c$ due to the conventional proximity
effect. This behavior of $T_r(d_2)$ is obtained by solving the Usadel equations
to calculate the temperature of the Berezinskii-Kosterletz-Thouless transition,
and the temperature of the resistive transition due to thermally-activated
hopping of single vortices in dirty bilayers. The theory incorporates relevant
materials parameters such as thicknesses and conductivities of the layers,
interface contact resistance between them and the subgap quasiparticle states
which affect both phase fluctuations and the proximity effect suppression of
$T_c$. The transition temperature $T_r$ can be optimized by tuning the
overlayer parameters, which can significantly weaken vortex fluctuations and
nearly restore the mean-field critical temperature. The calculated behavior of
$T_r(d_2)$ may explain the nonmonotonic dependence of $T_r(d_2)$ observed on
(Ag, Au, Mg, Zn)-coated Bi films, Ag-coated Ga and Pb films or NbN and NbTiN
films on AlN buffer layers. These results suggest that bilayers can be used as
model systems for systematic investigations of optimization of fluctuations in
superconductors.


  Magnetars are a unique class of neutron stars characterized by their
incredibly strong magnetic fields. Unlike normal pulsars whose X-ray emission
was driven by rotational energy loss, magnetars exhibit distinct X-ray
emissions thought to be driven by their strong magnetic fields. Here we present
the results of magnetar X-ray spectra analysis in their quiescent state. Most
of the spectra of magnetars can be fitted with a model consisting of a
power-law and a black body component. We found that the luminosity of the
power-law component can be described by a function of black-body temperature
and emission-region radius. The same relation was seen in pulsars whose X-ray
emission mechanism is thought to be different. The fact that magnetars and
pulsars share a common fundamental plane in the space spanned by non-thermal
X-ray luminosity, surface temperature and the radius of the thermally emitting
region presents both challenges and hints to theoretical models for a complete
comprehension of the magnetospheric emissions from these two classes of neutron
stars.


  We present results of integral field spectroscopy of Balmer-dominated shocks
in the LMC supernova remnant (SNR) N103B, carried out using the Wide Field
Integral Spectrograph (WiFeS) on the 2.3 m telescope at Siding Spring
Observatory in Australia. Existing X-ray studies of N103B have indicated a Type
Ia supernova origin. Radiative shock emission from clumpy material surrounding
the SNR may result from interaction of the forward shock with relic stellar
wind material, possibly implicating a thermonuclear explosion in a
single-degenerate binary system. The recently discovered Balmer-dominated
shocks mark the impact of the forward shock with low density, partially neutral
CSM gas, and form a partial shell encircling clumps of material exhibiting
radiative shocks. The WiFeS spectra of N103B cover the range 3500 - 7000
Angstroms and reveal broad Halpha profiles up to 2360 km/s in width along the
northern rim, and both Halpha and Hbeta broad profiles approximately 1300 km/s
in width along the southern rim. Our fits to the Halpha line profiles indicate
that in addition to from the usual broad and narrow emission components, a
third component of intermediate width exists in the Balmer-dominated shocks,
ranging from around 125 km/s up to 225 km/s in width. Recent Balmer-dominated
shock models have predicted such an intermediate-width component will be
generated in a fast neutral precursor. We derive a Sedov age of approximately
685 years for N103B from the Balmer-dominated spectra, consistent with the
young age of 380 - 860 years estimated from light echo studies.


  We propose a cut-free cyclic system for Transitive Closure Logic (TCL) based
on a form of hypersequents, suitable for automated reasoning via proof search.
We show that previously proposed sequent systems are cut-free incomplete for
basic validities from Kleene Algebra (KA) and Propositional Dynamic Logic
(PDL), over standard translations. On the other hand, our system faithfully
simulates known cyclic systems for KA and PDL, thereby inheriting their
completeness results. A peculiarity of our system is its richer correctness
criterion, exhibiting 'alternating traces' and necessitating a more intricate
soundness argument than for traditional cyclic proofs.


  The free propagation of acoustic plane waves through cellular periodic
materials is generally accompanied by a flow of mechanical energy across the
adjacent cells. The paper focuses on the energy transport related to dispersive
waves propagating through nondissipative microstructured materials. The generic
microstructure of the periodic cell is described by a beam lattice model,
suitably reduced to the minimal space of dynamic degrees-of-freedom. The linear
eigenproblem governing the wave propagation is stated and the complete
eigensolution is considered to study both the real-valued dispersion functions
and the complex-valued waveforms of the propagating elastic waves. First, a
complete family of nondimensional quantities (polarization factors) is proposed
to quantify the linear polarization or quasi-polarization, according to a
proper energetic criterion. Second, a vector variable related to the periodic
cell is introduced to assess the directional flux of mechanical energy, in
analogy to the Umov-Poynting vector related to the material point in solid
mechanics. The physical-mathematical relation between the energy flux and the
velocity of the energy transport is recognized. The formal equivalence between
the energy and the group velocity is pointed out, according to the mechanical
assumptions. Finally, all the theoretical developments are successfully applied
to the prototypical beam lattice material characterized by a periodic
tetrachiral microstructure.


  We present new, ab initio calculations of the electronic structure of
one-dimensional infinite chains and three-dimensional condensed matter in
strong magnetic fields ranging from B=10^12 G to 2x10^15 G, appropriate for
observed magnetic neutron stars. At these field strengths, the magnetic forces
on the electrons dominate over the Coulomb forces, and to a good approximation
the electrons are confined to the ground Landau level. Our calculations are
based on the density functional theory, and use a local magnetic
exchange-correlation function appropriate in the strong field regime. The band
structures of electrons in different Landau orbitals are computed
self-consistently. Numerical results of the ground-state energies and electron
work functions are given for one-dimensional chains of H, He, C, and Fe.
Fitting formulae for the B-dependence of the energies are also provided. For
all the field strengths considered in this paper, hydrogen, helium, and carbon
chains are found to be bound relative to individual atoms (although for B less
than a few x 10^12 G, the relative binding between C and C_infinity is small).
Iron chains are significantly bound for B>10^14 G and are weakly bound if at
all at B<10^13 G. We also study the cohesive property of three-dimensional
condensed matter of H, He, C, and Fe at zero pressure, constructed from
interacting chains in a body-centered tetragonal lattice. Such
three-dimensional condensed matter is found to be bound relative to individual
atoms, with the cohesive energy increasing rapidly with increasing B.


  In distributed optimization and distributed numerical linear algebra, we
often encounter an inversion bias: if we want to compute a quantity that
depends on the inverse of a sum of distributed matrices, then the sum of the
inverses does not equal the inverse of the sum. An example of this occurs in
distributed Newton's method, where we wish to compute (or implicitly work with)
the inverse Hessian multiplied by the gradient. In this case, locally computed
estimates are biased, and so taking a uniform average will not recover the
correct solution. To address this, we propose determinantal averaging, a new
approach for correcting the inversion bias. This approach involves reweighting
the local estimates of the Newton's step proportionally to the determinant of
the local Hessian estimate, and then averaging them together to obtain an
improved global estimate. This method provides the first known distributed
Newton step that is asymptotically consistent, i.e., it recovers the exact step
in the limit as the number of distributed partitions grows to infinity. To show
this, we develop new expectation identities and moment bounds for the
determinant and adjugate of a random matrix. Determinantal averaging can be
applied not only to Newton's method, but to computing any quantity that is a
linear tranformation of a matrix inverse, e.g., taking a trace of the inverse
covariance matrix, which is used in data uncertainty quantification.


  We consider Gell-Mann and Hartle's consistent histories formulation of
quantum cosmology in the interpretation in which one history, chosen randomly
according to the decoherence functional probabilities, is realised from each
consistent set. We show that in this interpretation, if one assumes that an
observed quasiclassical structure will continue to be quasiclassical, one
cannot infer that it will obey the predictions of classical or Copenhagen
quantum mechanics.


  We propose a new smoothing method for obtaining surface densities from
discrete particle positions from numerical simulations. This is an essential
step for many applications in gravitational lensing. This method is based on
the ``scatter'' interpretation of the discrete density field in the Smoothed
Particle Hydrodynamics. We use Monte Carlo simulations of uniform density
fields and one isothermal ellipsoid to empirically derive the noise properties,
and best smoothing parameters (such as the number of nearest neighbors used). A
cluster from high-resolution simulations is then used to assess the reality of
high-order singularities such as swallowtails and butterflies in caustics,
which are important for the interpretation of substructures in gravitational
lenses. We also compare our method with the Delaunay tesselation field
estimator using the galaxy studied by Bradac et al. (2004), and find good
agreements. We show that higher order singularities are not only connected with
bound subhaloes but also with the satellite streams. However, the presence of
high-order singularities are sensitive to not only the fluctuation amplitude of
the surface density, but also the detailed form of the underlying smooth
lensing potential (such as ellipticity and external shear).


  We find a dark gauge symmetry $U(1)_D$ that transforms nontrivially only for
three right-handed neutrinos $\nu_{1,2,3R}$. The anomaly cancellation demands
that they have a dark charge $D=0,-1,+1$ assigned to $\nu_{1,2,3R}$,
respectively. The dark charge is broken by two units down to a dark parity,
i.e. $U(1)_D\to P_D=(-1)^D$, which stabilizes a dark matter candidate.
Interestingly, the model manifestly supplies neutrino masses via joint seesaw
and scotogenic mechanisms, called scotoseesaw.


  For many recommender systems the primary data source is a historical record
of user clicks. The associated click matrix which is often very sparse,
however, as the number of users x products can be far larger than the number of
clicks, and such sparsity is accentuated in cold-start settings. The sparsity
of the click matrix is the reason matrix factorization and autoencoders
techniques remain highly competitive across collaborative filtering datasets.
In this work, we propose a simple approach to address cold-start
recommendations by leveraging content metadata, Metadata Alignment for
cold-start Recommendation. we show that this approach can readily augment
existing matrix factorization and autoencoder approaches, enabling a smooth
transition to top performing algorithms in warmer set-ups. Our experimental
results indicate three separate contributions: first, we show that our proposed
framework largely beats SOTA results on 4 cold-start datasets with different
sparsity and scale characteristics, with gains ranging from +8.4% to +53.8% on
reported ranking metrics; second, we provide an ablation study on the utility
of semantic features, and proves the additional gain obtained by leveraging
such features ranges between +46.8% and +105.5%; and third, our approach is by
construction highly competitive in warm set-ups, and we propose a closed-form
solution outperformed by SOTA results by only 0.8% on average.


  We present a combined analytical and numerical study on double-vortex
spin-torque nano-oscillators and describe a mechanism that suppresses the
windmill modes. The magnetization dynamics is dominated by the gyrotropic
precession of the vortex in one of the ferromagnetic layers. In the other layer
the vortex gyration is strongly damped. The dominating layer for the
magnetization dynamics is determined by the current polarity. Measurements on
Fe/Ag/Fe nano-pillars support these findings. The results open up a new
perspective for building high quality-factor spin-torque oscillators operating
at selectable, well-separated frequency bands.


  We present a summary of a recent workshop held at Duke University on Partonic
Transverse Momentum in Hadrons: Quark Spin-Orbit Correlations and Quark-Gluon
Interactions. The transverse momentum dependent parton distribution functions
(TMDs), parton-to-hadron fragmentation functions, and multi-parton correlation
functions, were discussed extensively at the Duke workshop. In this paper, we
summarize first the theoretical issues concerning the study of partonic
structure of hadrons at a future electron-ion collider (EIC) with emphasis on
the TMDs. We then present simulation results on experimental studies of TMDs
through measurements of single spin asymmetries (SSA) from semi-inclusive
deep-inelastic scattering (SIDIS) processes with an EIC, and discuss the
requirement of the detector for SIDIS measurements. The dynamics of parton
correlations in the nucleon is further explored via a study of SSA in D (`D)
production at large transverse momenta with the aim of accessing the unexplored
tri-gluon correlation functions. The workshop participants identified the SSA
measurements in SIDIS as a golden program to study TMDs in both the sea and
valence quark regions and to study the role of gluons, with the Sivers
asymmetry measurements as examples. Such measurements will lead to major
advancement in our understanding of TMDs in the valence quark region, and more
importantly also allow for the investigation of TMDs in the sea quark region
along with a study of their evolution.


  We study a system of weakly interacting electrons described by the energy
dispersion $\xi(\mathbf{k}) = k_x^2 - k_y^2 - \mu$ in two dimensions within a
renormalization group approach. This energy dispersion exhibits a
neck-narrowing Lifshitz transition at the critical chemical potential $\mu_c=0$
where a van Hove singularity develops. Implementing a systematic
renormalization group analysis of this system has long been hampered by the
appearance of nonlocal terms in the Wilsonian effective action. We demonstrate
that non-locality at the critical point is intrinsic, and the locality of the
effective action can be maintained only away from the critical point. We also
point out that it is crucial to introduce a large momentum cutoff to keep
locality even away from the critical point. Based on a local renormalization
group scheme employed near the critical point, we show that, as the energy
scale $E$ is lowered, an attractive four-fermion interaction grows as $\log^2
E$ for $E > \mu$, whereas it retains the usual BCS growth, $-\log E$, for $E <
\mu$. Starting away from the critical point, this fast growth of the pairing
interaction suggests that the system becomes unstable toward a superconducting
state well before the critical point is reached.


  Let f and g two rational functions having the same Julia set J_f. Lets
suppose that f has a rational indifferent periodic point and that the critical
set of f is disjoint of J_f. Then or J_f has to be equal to P^1, a circle, an
arc of a circle for some cordinate or f and g has to verify an equation of the
type: $$f^{m_1}\circ g\circ f^{m_2}\circ\cdotc\circ f^{m_n}\circ g=f^m.$$


  In a robust statistical way, we quantify the uncertainty that affects the
calibration of the overshooting efficiency parameter $\beta$ that is owing to
the uncertainty on the observational data in double-lined eclipsing binary
systems. We also quantify the bias that is caused by the lack of constraints on
the initial helium content and on the efficiencies of the superadiabatic
convection and microscopic diffusion. We adopted a modified grid-based SCEPtER
pipeline using as observational constraints the effective temperatures, [Fe/H],
masses, and radii of the two stars. In a reference scenario of mild
overshooting $\beta = 0.2$ for the synthetic data, we found both large
statistical uncertainties and biases on the estimated $\beta$. For the first
80% of the MS evolution, $\beta$ is biased and practically unconstrained in the
whole explored range [0.0; 0.4]. In the last 5% of the MS the bias vanishes and
the $1 \sigma$ error is about 0.05. For synthetic data computed with $\beta =
0.0$, the estimated $\beta$ is biased by about 0.12 in the first 80% of the MS
evolution, and by 0.05 afterwards. Assuming an uncertainty of $\pm 1$ in the
helium-to-metal enrichment ratio $\Delta Y/\Delta Z$, we found that in the
terminal part of the MS evolution the error on the estimated $\beta$ values
ranges from -0.05 to +0.10, while $\beta$ is basically unconstrained throughout
the explored range at earlier evolutionary stages. A uniform variation of $\pm
0.24$ in the mixing-length parameter around the solar-calibrated value causes
in last 5% of the MS an uncertainty from -0.09 to +0.15. A complete neglect of
diffusion in the stellar evolution computations produces a $1 \sigma$
uncertainty of $\pm 0.08$ in the last 5% of the MS, while $\beta$ is
practically unconstrained in the first 80% of the MS. Overall, the calibration
appears poorly reliable.


  A sample of Lambda's produced in 2 A*GeV Ni + Cu collisions has been obtained
with the EOS Time Projection Chamber at the Bevalac. Low background in the
invariant mass distribution allows for the unambiguous demonstration of Lambda
directed flow. The transverse mass spectrum at mid-rapidity has the
characteristic shoulder-arm shape of particles undergoing radial transverse
expansion. A linear dependence of Lambda multiplicity on impact parameter is
observed, from which a total Lambda + Sigma^0 production cross section of $112
+/- 24 mb is deduced. Detailed comparisons with the ARC and RVUU models are
made.


  We discuss the expected amplitude of a cosmic background of massive,
non-relativistic dilatons, and we report recent results about its possible
detection. This paper is a contracted version of a talk given at the 15th
SIGRAV Conference on "General Relativity and Gravitational Physics" (Villa
Mondragone, Roma, September 2002).


  A Relational Dependency Network (RDN) is a directed graphical model widely
used for multi-relational data. These networks allow cyclic dependencies,
necessary to represent relational autocorrelations. We describe an approach for
learning both the RDN's structure and its parameters, given an input relational
database: First learn a Bayesian network (BN), then transform the Bayesian
network to an RDN. Thus fast Bayes net learning can provide fast RDN learning.
The BN-to-RDN transform comprises a simple, local adjustment of the Bayes net
structure and a closed-form transform of the Bayes net parameters. This method
can learn an RDN for a dataset with a million tuples in minutes. We empirically
compare our approach to state-of-the art RDN learning methods that use
functional gradient boosting, on five benchmark datasets. Learning RDNs via BNs
scales much better to large datasets than learning RDNs with boosting, and
provides competitive accuracy in predictions.


  As the real-world impact of Artificial Intelligence (AI) systems has been
steadily growing, so too have these systems come under increasing scrutiny. In
response, the study of AI fairness has rapidly developed into a rich field of
research with links to computer science, social science, law, and philosophy.
Many technical solutions for measuring and achieving AI fairness have been
proposed, yet their approach has been criticized in recent years for being
misleading, unrealistic and harmful.
  In our paper, we survey these criticisms of AI fairness and identify key
limitations that are inherent to the prototypical paradigm of AI fairness. By
carefully outlining the extent to which technical solutions can realistically
help in achieving AI fairness, we aim to provide the background necessary to
form a nuanced opinion on developments in fair AI. This delineation also
provides research opportunities for non-AI solutions peripheral to AI systems
in supporting fair decision processes.


  Generating an image from a provided descriptive text is quite a challenging
task because of the difficulty in incorporating perceptual information (object
shapes, colors, and their interactions) along with providing high relevancy
related to the provided text. Current methods first generate an initial
low-resolution image, which typically has irregular object shapes, colors, and
interaction between objects. This initial image is then improved by
conditioning on the text. However, these methods mainly address the problem of
using text representation efficiently in the refinement of the initially
generated image, while the success of this refinement process depends heavily
on the quality of the initially generated image, as pointed out in the DM-GAN
paper. Hence, we propose a method to provide good initialized images by
incorporating perceptual understanding in the discriminator module. We improve
the perceptual information at the first stage itself, which results in
significant improvement in the final generated image. In this paper, we have
applied our approach to the novel StackGAN architecture. We then show that the
perceptual information included in the initial image is improved while modeling
image distribution at multiple stages. Finally, we generated realistic
multi-colored images conditioned by text. These images have good quality along
with containing improved basic perceptual information. More importantly, the
proposed method can be integrated into the pipeline of other state-of-the-art
text-based-image-generation models to generate initial low-resolution images.
We also worked on improving the refinement process in StackGAN by augmenting
the third stage of the generator-discriminator pair in the StackGAN
architecture. Our experimental analysis and comparison with the
state-of-the-art on a large but sparse dataset MS COCO further validate the
usefulness of our proposed approach.


  Satellite observations of acoustic-gravity waves in the polar regions of the
atmosphere indicate a close connection of these waves with wind flows. The
paper investigates the peculiarities of the propagation of AGWs in spatially
inhomogeneous flows, where the wind speed slowly changes in the horizontal
direction. A system of hydrodynamic equations is used for the analysis, which
takes into account the wind flow with spatial inhomogeneity. Unlike the system
of equations written for a stationary medium (or a medium moving at a uniform
speed), the resulting system contains components that describe the interaction
of the waves with the medium. It is shown that the influence of inhomogeneous
background parameters of the medium can be separated from the effects of
inertial forces by means of the special variable substitution. The analytical
expression is obtained that describes the changes in the wave amplitude in a
medium moving with a non-uniform speed. This expression contains two functional
dependencies: 1) the linear part caused by changes in the background parameters
of the medium, it does not depend on the direction of the wave propagation
relative to the flow; 2) the exponential part associated with the inertia
forces, which determines the dependence of the amplitudes of AGWs on the
direction of their propagation. The exponential part shows an increase in the
amplitudes of the waves in the headwind and a decrease in their amplitudes in
the downwind. The obtained theoretical dependence of the amplitudes of AGWs on
the wind speed is in good agreement with the data of satellite observations of
these waves in the polar thermosphere.


  The relative importance of atomic defects and electron transfer in explaining
conductivity at the crystalline LaAlO3/SrTiO3 interface has been a topic of
debate. Metallic interfaces with similar electronic properties produced by
amorphous oxide overlayers on SrTiO3 have called in question the original
polarization catastrophe model. We resolve the issue by a comprehensive
comparison of (100)-oriented SrTiO3 substrates with crystalline and amorphous
overlayers of LaAlO3 of different thicknesses prepared under different oxygen
pressures. For both types of overlayers, there is a critical thickness for the
appearance of conductivity, but its value is always 4 unit cells (around 1.6
nm) for the oxygen-annealed crystalline case, whereas in the amorphous case,
the critical thickness could be varied in the range 0.5 to 6 nm according to
the deposition conditions. Subsequent ion milling of the overlayer restores the
insulating state for the oxygen-annealed crystalline heterostructures but not
for the amorphous ones. Oxygen post-annealing removes the oxygen vacancies, and
the interfaces become insulating in the amorphous case. However, the interfaces
with a crystalline overlayer remain conducting with reduced carrier density.
These results demonstrate that oxygen vacancies are the dominant source of
mobile carriers when the LaAlO3 overlayer is amorphous, while both oxygen
vacancies and polarization catastrophe contribute to the interface conductivity
in unannealed crystalline LaAlO3/SrTiO3 heterostructures, and the polarization
catastrophe alone accounts for the conductivity in oxygen-annealed crystalline
LaAlO3/SrTiO3 heterostructures. Furthermore, we find that the crystallinity of
the LaAlO3 layer is crucial for the polarization catastrophe mechanism in the
case of crystalline LaAlO3 overlayers.


  The spectral singularity (SS) and coherent perfect absorption (CPA) have been
extensively studied over the last one and half decade for different
non-Hermitian potentials in non-Hermitian standard quantum mechanics (SQM)
governed by Schrodinger equation. In the present work we explore these
scattering features in the domain of non-Hermitian space fractional quantum
mechanics (SFQM) governed by fractional Schrodinger equation which is
characterized by Levy index $\alpha$ ($ 1< \alpha \leq 2$). We observe that
non-Hermitian SFQM systems have more flexibility for SS and CPA and display
some new features of scattering. For the delta potential $V(x)=-i\rho \delta
(x-x_{0})$, $\rho > 0$, the SS energy, $E_{ss}$, is blue or red shifted with
decreasing $\alpha$ depending the strength of the potential. For complex
rectangular barrier in non-Hermitian SQM, it is known that the reflection and
transmission amplitudes are oscillatory near the spectral singular point. It is
found that these oscillations eventually develop SS in non-Hermitian SFQM. The
similar features is also reported for the case of CPA phenomena from complex
rectangular barrier in non-Hermitian SFQM. These observations suggest a deeper
relation between scattering features of non-Hermitian SQM and non-Hermitian
SFQM.


  Three solid solutions of [CH$_3$NH$_3$]Co$_x$Ni$_{1-x}$(HCOO)$_3$, with $x$ =
0.25 (1), 0.50 (2) and 0.75 (3), were synthesized and their nuclear structures
and magnetic properties were characterized using single crystal neutron
diffraction and magnetization measurements. At room temperature, all three
compounds crystallize in the Pnma orthorhombic space group, akin to the cobalt
and nickel end series members. Upon cooling, each compound undergoes distinct
series of structural transitions to modulated structures. Compound 1 exhibits a
phase transition to a modulated structure analogous to the pure nickel
compound, while compound 3 maintains the behaviour observed in the pure cobalt
compound, although in both cases the temperatures at which the phase
transitions occur differ slightly from the pure phases. Monochromatic neutron
diffraction measurements showed that the structural evolution of 2 diverges
from that of either parent compound, with the competing hydrogen bond
interactions which drive the modulation throughout the series producing a
unique sequence of phases. It involves two modulated phases below 96(3) K and
59(3) K, with different q vectors, similar to the pure cobalt compound (with
modulated phases below 128 K and 96 K), however it maintains the modulated
phase below magnetic order (at 22.5(7) K), resembling the pure nickel compound
(which present magnetic order below 34 K), resulting in an improper modulated
magnetic structure. Despite these large scale structural changes, magnetometry
data reveal that the bulk magnetic properties of these solid solutions form a
linear continuum between the end members. Notably, doping of the metal site in
these solid solutions allows for tuning of bulk magnetic properties, including
magnetic ordering temperature, transition temperatures, and the nature of
nuclear phase transitions, through adjustment of metal ratios.


  Over the past few years, various domain-specific pretrained language models
(PLMs) have been proposed and have outperformed general-domain PLMs in
specialized areas such as biomedical, scientific, and clinical domains. In
addition, financial PLMs have been studied because of the high economic impact
of financial data analysis. However, we found that financial PLMs were not
pretrained on sufficiently diverse financial data. This lack of diverse
training data leads to a subpar generalization performance, resulting in
general-purpose PLMs, including BERT, often outperforming financial PLMs on
many downstream tasks. To address this issue, we collected a broad range of
financial corpus and trained the Financial Language Model (FiLM) on these
diverse datasets. Our experimental results confirm that FiLM outperforms not
only existing financial PLMs but also general domain PLMs. Furthermore, we
provide empirical evidence that this improvement can be achieved even for
unseen corpus groups.


  The previous proved-bound is $C(1+\frac{H^2}{\delta^2})$ for the condition
number of the overlapping domain decomposition
$\mathrm{H}(\mathrm{curl};\Omega)$ and $\mathrm{H}(\mathrm{div};\Omega)$
methods, where $H$ and $\delta$ are the sizes of subdomains and overlaps
respectively. But all numerical results indicate that the best bound is
$C(1+\frac{H}{\delta})$. In this work, we solve this long-standing open problem
by proving that $C(1+\frac{H}{\delta})$ is indeed the best bound.


  Given an $\infty$-harmonic function $u_\infty$ on a domain $\Omega \subseteq
\mathbb{R}^2$, consider the function $w = -\log |\nabla u_\infty|$. If
$u_\infty \in C^2(\Omega)$ with $\nabla u_\infty \neq 0$ and $\nabla |\nabla
u_\infty| \neq 0$, then it is easy to check that (1) the streamlines of
$u_\infty$ are the level sets of $w$ and (2) $w$ solves the level set
formulation of the inverse mean curvature flow.
  For less regular solutions, neither statement is true in general, but even
so, $w$ is still a weak solution of the inverse mean curvature flow under far
weaker assumptions. This is proved through an approximation of $u_\infty$ by
$p$-harmonic functions, the use of conjugate $p'$-harmonic functions, and the
known connection of the latter with the inverse mean curvature flow. A
statement about the regularity of $|\nabla u_\infty|$ arises as a by-product.


  The necessity of accurately taking into account the existence of
nonequivalent operator representations, associated with canonical
transformations, is discussed. It is demonstrated that Bose systems in the
presence of the Bose-Einstein condensate and without it correspond to different
Fock spaces, orthogonal to each other. A composite representation for the field
operators is constructed, allowing for a self-consistent description of
Bose-condensed systems. Equations of motion are derived from the given
Hamiltonian, which guarantees the validity of conservation laws and
thermodynamic self-consistency. At the same time, the particle spectrum,
obtained either from diagonalizing this Hamiltonian or from linearizing the
field-operator equations of motion, has no gap. The condition of the condensate
existence assures the absence of the gap in the spectrum, irrespectively to the
approximation involved. The suggested self-consistent theory is both conserving
and gapless.


  We present measurements of the thermal fluctuations of the free surface of an
aging colloidal suspension, Laponite. The technique consists in measuring the
fluctuations of the position of a laser beam that reflects from the free
surface. Analysing the data statistics, we show that, as the fluid ages, the
dynamics becomes intermittent. The intermittent events correspond to large
changes in the local slope of the free surface over a few milliseconds. We show
that those quakes are uncorrelated, although they are kept in memory by the
surface over short time scales.


  We recently found that the energy contribution to the linear elasticity of
polymer gels in the as-prepared state can be a significant negative value; the
shear modulus is not proportional to the absolute temperature [Y. Yoshikawa et
al., Phys. Rev. X 11, 011045 (2021) (arXiv:1912.13191)]. Our finding challenges
the conventional notion that the polymer-gel elasticity is mainly determined by
the entropy contribution. Existing molecular models of classical rubber
elasticity theories, including the affine, phantom, and junction affine network
models, cannot be used to estimate the structural parameters of polymer gels.
In this focus review, we summarize the experimental studies on the linear
elasticity of polymer gels in the as-prepared state using tetra-arm
poly(ethylene glycol) (PEG) hydrogels with a homogenous polymer network. We
also provide a unified formula for the linear elasticity of polymer gels with
various network topologies and densities. Using the unified formula, we
reconcile the past experimental results that seemed to be inconsistent with
each other. Finally, we mention that there are still fundamental unresolved
problems involving the linear elasticity of polymer gels.


  Let $R$ be a commutative ring with identity. The small finitistic dimension
$\fPD(R)$ of $R$ is defined to be the supremum of projective dimensions of
$R$-modules with finite projective resolutions. In this paper, we characterize
a ring $R$ with $\fPD(R)\leq n$ using finitely generated semi-regular ideals,
tilting modules, cotilting modules of cofinite type or vaguely associated prime
ideals. As an application, we obtain that if $R$ is a Noetherian ring, then
$\fPD(R)= \sup\{\grade(\m,R)|\m\in \Max(R)\}$ where $\grade(\m,R)$ is the grade
of $\m$ on $R$ . We also show that a ring $R$ satisfies $\fPD(R)\leq 1$ if and
only if $R$ is a $\DW$ ring. As applications, we show that the small finitistic
dimensions of strong \Prufer\ rings and $\LPVD$s are at most one. Moreover, for
any given $n\in \mathbb{N}$, we obtain examples of total rings of quotients $R$
with $\fPD(R)=n$.


  We consider quasilinear elliptic systems in divergence form. In general, we
cannot expect that weak solutions are locally bounded because of De Giorgi's
counterexample. Here we assume a condition on the support of off-diagonal
coefficients that "keeps away" the counterexample and allows us to prove local
boundedness of weak solutions.


  Recent studies exposed many remarkable properties of layered cobaltates
NaxCoO2. Surprisingly, many-body effects have been found to increase at
sodium-rich compositions of NaxCoO2 where one expects a simple, nearly free
motion of the dilute S=1/2 holes doped into a band insulator NaCoO2. Here we
discuss the origin of enigmatic correlations that turn a doped NaCoO2 into a
strongly correlated electronic system. A minimal model including orbital
degeneracy is proposed and its predictions are discussed. The model is based on
a key property of cobalt oxides - the spin-state quasidegeneracy of CoO6
octahedral complex - which has been known, e.g., in the context of an unusual
physics of LaCoO3 compound. Another important ingredient of the model is the
90-degree Co-O-Co bonding in NaxCoO2 which allows nearest-neighbor $t_{2g}-e_g$
hopping. This hopping introduces a dynamical mixture of electronic
configurations $t_{2g}^6, S=0$ and $t_{2g}^5e_g^1, S=1$ of neighboring cobalt
ions. We show that scattering of charge carriers on spin-state fluctuations
suppresses their coherent motion and leads to the spin-polaron physics at
$x\sim 1$. At larger doping when coherent fermionic bands are formed, the model
predicts singlet superconductivity of extended s-wave symmetry. The presence of
low-lying spin states of Co$^{3+}$ is essential for the pairing mechanism.
Implications of the model for magnetic orderings are also discussed.


  Under the constraints of HQET the equations of motion of heavy meson
distribution amplitudes of definite geometric twist, using the knowledge of
their off-cone structure, are reformulated as a set of algebraic equations.
Together with equations due to various Dirac structures various relations
between the (sets of) independent two- and three particle distribution
amplitudes of definite geometric twist are derived and presented using both the
notion of (double) Mellin moments and re-summed non-local distribution
amplitudes. Resolving these relations for the independent two-particle moments
in terms of three-particle double moments we confirmed the representation of
$\Phi_{\pm|n}$ by Kawamura et al. (Phys. Lett. B \bf{523} (2001) 111).


  Let G be a connected reductive algebraic group and let G'=[G,G] be its
derived subgroup. Let (G,V) be a multiplicity free representation with a one
dimensional quotient (see definition below). We prove that the algebra
D(V)^{G'} of G'-invariant differential operators with polynomial coefficients
on V, is a quotient of a so-called Smith algebra over its center. Over C this
class of algebras was introduced by S.P. Smith as a class of algebras similar
to the enveloping algebra U(sl(2)) of sl(2). Our result generalizes the case of
the Weil representation, where the associative algebra generated by Q(x) and
Q(?) (Q being a non degenerate quadratic form on V) is a quotient of U(sl(2))
Other structure results are obtained when (G,V) is a regular prehomogeneous
vector space of commutative parabolic type.


  The behaviors of the holographic superconductors/insulator transition are
studied by introducing a charged scalar field coupled with a logarithmic
electromagnetic field in both the Einstein-Gauss-Bonnet AdS black hole and
soliton. For the Einstein-Gauss-Bonnet AdS black hole, we find that: i) the
larger coupling parameter of logarithmic electrodynamic field $b$ makes it
easier for the scalar hair to be condensated; ii) the ratio of the gap
frequency in conductivity $\omega_g$ to the critical temperature $T_c$ depends
on both $b$ and the Gauss-Bonnet constant $\alpha$; and iii) the critical
exponents are independent of the $b$ and $\alpha$. For the
Einstein-Gauss-Bonnet AdS Soliton, we show that the system is the insulator
phase when the chemical potential $\mu$ is small, but there is a phase
transition and the AdS soliton reaches the superconductor (or superfluid) phase
when $\mu$ larger than critical chemical potential. A special property should
be noted is that the critical chemical potential is not changed by the coupling
parameter $b$ but depends on $\alpha$.


  Probabilistic graphical models are traditionally known for their successes in
generative modeling. In this work, we advocate layered graphical models (LGMs)
for probabilistic discriminative learning. To this end, we design LGMs in close
analogy to neural networks (NNs), that is, they have deep hierarchical
structures and convolutional or local connections between layers. Equipped with
tensorized truncated variational inference, our LGMs can be efficiently trained
via backpropagation on mainstream deep learning frameworks such as PyTorch. To
deal with continuous valued inputs, we use a simple yet effective soft-clamping
strategy for efficient inference. Through extensive experiments on image
classification over MNIST and FashionMNIST datasets, we demonstrate that LGMs
are capable of achieving competitive results comparable to NNs of similar
architectures, while preserving transparent probabilistic modeling.


  We consider the relationship between the total HI mass in late-type galaxies
and the kinematic properties of their disks. The mass $M_HI$ for galaxies with
a wide variety of properties, from dwarf dIrr galaxies with active star
formation to giant low-brightness galaxies, is shown to correlate with the
product $V_c R_0$ ($V_c$ is the rotational velocity, and $R_0$ is the radial
photometric disks scale length), which characterizes the specific angular
momentum of the disk. This relationship, along with the anticorrelation between
the relative mass of HI in a galaxy and $V_c$, can be explained in terms of the
previously made assumption that the gas density in the disks of most galaxies
is maintained at a level close to the threshold (marginal) stability of a
gaseous layer to local gravitational perturbations. In this case, the
regulation mechanism of the star formation rate associated with the growth of
local gravitational instability in the gaseous layer must play a crucial role
in the evolution of the gas content in the galactic disk.


  A significant performance reduction is often observed in speech recognition
when the rate of speech (ROS) is too low or too high. Most of present
approaches to addressing the ROS variation focus on the change of speech
signals in dynamic properties caused by ROS, and accordingly modify the dynamic
model, e.g., the transition probabilities of the hidden Markov model (HMM).
However, an abnormal ROS changes not only the dynamic but also the static
property of speech signals, and thus can not be compensated for purely by
modifying the dynamic model. This paper proposes an ROS learning approach based
on deep neural networks (DNN), which involves an ROS feature as the input of
the DNN model and so the spectrum distortion caused by ROS can be learned and
compensated for. The experimental results show that this approach can deliver
better performance for too slow and too fast utterances, demonstrating our
conjecture that ROS impacts both the dynamic and the static property of speech.
In addition, the proposed approach can be combined with the conventional HMM
transition adaptation method, offering additional performance gains.


  Three dimensional (3D) Dirac semimetals which can be seen as 3D analogues of
graphene have attracted enormous interests in research recently. In order to
apply these ultrahigh-mobility materials in future electronic/optoelectronic
devices, it is crucial to understand the relaxation dynamics of photoexcited
carriers and their coupling with lattice. In this work, we report ultrafast
transient reflection measurements of the photoexcited carrier dynamics in
cadmium arsenide (Cd3As2), which is one of the most stable Dirac semimetals
that have been confirmed experimentally. By using low energy probe photon of
0.3 eV, we probed the dynamics of the photoexcited carriers that are
Dirac-Fermi-like approaching the Dirac point. We systematically studied the
transient reflection on bulk and nanoplate samples that have different doping
intensities by tuning the probe wavelength, pump power and lattice temperature,
and find that the dynamical evolution of carrier distributions can be retrieved
qualitatively by using a two-temperature model. This result is very similar to
that of graphene, but the carrier cooling through the optical phonon couplings
is slower and lasts over larger electron temperature range because the optical
phonon energies in Cd3As2 are much lower than those in graphene.


  Deep learning techniques have been successfully applied to predict unplanned
readmissions of patients in medical centers. The training data for these models
is usually based on historical medical records that contain a significant
amount of free-text from admission reports, referrals, exam notes, etc. Most of
the models proposed so far are tailored to English text data and assume that
electronic medical records follow standards common in developed countries.
These two characteristics make them difficult to apply in developing countries
that do not necessarily follow international standards for registering patient
information, or that store text information in languages other than English.
  In this paper we propose a deep learning architecture for predicting
unplanned readmissions that consumes data that is significantly less structured
compared with previous models in the literature. We use it to present the first
results for this task in a large clinical dataset that mainly contains Spanish
text data. The dataset is composed of almost 10 years of records in a Chilean
medical center. On this dataset, our model achieves results that are comparable
to some of the most recent results obtained in US medical centers for the same
task (0.76 AUROC).


  The results of 3,989 intensified CCD observations of double stars, made with
the 26-inch refractor of the U.S. Naval Observatory, are presented. Each
observation of a system represents a combination of over two thousand
short-exposure images. These observations are averaged into 1,911 mean relative
positions and range in separation from 0.289 to 128.638, with a median
separation of 8.669. Four orbits are improved. This is the 23rd in this series
of papers and covers the period 4 January 2017 through 13 September 2017.


  In this article, we define a generalisation of microlocal defect measures
(also known as H-measures) to the setting of graded nilpotent Lie groups. This
requires to develop the notions of homogeneous symbols and classical
pseudo-differential calculus adapted to this setting and defined via the
representations of the groups. Our method relies on the study of the C
*-algebra of 0-homogeneous symbols. Then, we compute microlocal defect measures
for concentrating and oscillating sequences, which also requires to investigate
the notion of oscillating sequences in graded Lie groups. Finally, we discuss
compacity compactness approaches in the context of graded nilpotent Lie groups.


  We review some methods recently used in the literature to detect the
existence of a certain degree of common behavior of stock returns belonging to
the same economic sector. Specifically, we discuss methods based on random
matrix theory and hierarchical clustering techniques. We apply these methods to
a set of stocks traded at the New York Stock Exchange. The investigated time
series are recorded at a daily time horizon.
  All the considered methods are able to detect economic information and the
presence of clusters characterized by the economic sector of stocks. However,
different methodologies provide different information about the considered set.
Our comparative analysis suggests that the application of just a single method
could not be able to extract all the economic information present in the
correlation coefficient matrix of a set of stocks.


  In this paper, we tackle the problem of relational behavior forecasting from
sensor data. Towards this goal, we propose a novel spatially-aware graph neural
network (SpAGNN) that models the interactions between agents in the scene.
Specifically, we exploit a convolutional neural network to detect the actors
and compute their initial states. A graph neural network then iteratively
updates the actor states via a message passing process. Inspired by Gaussian
belief propagation, we design the messages to be spatially-transformed
parameters of the output distributions from neighboring agents. Our model is
fully differentiable, thus enabling end-to-end training. Importantly, our
probabilistic predictions can model uncertainty at the trajectory level. We
demonstrate the effectiveness of our approach by achieving significant
improvements over the state-of-the-art on two real-world self-driving datasets:
ATG4D and nuScenes.


  There has been great interest in identifying a Kitaev quantum spin liquid
state in frustrated magnets with bond-dependent interactions. In particular,
the experimental report of a half-quantized thermal Hall conductivity in
$\alpha$-RuCl$_3$ in the presence of a magnetic field has generated excitement
as it could be strong evidence for a field-induced chiral spin liquid. More
recent experiments, however, provide a conflicting interpretation advocating
for topological magnons in the field-polarized state as the origin of the
non-quantized thermal Hall conductivity observed in their experiments. An
inherent difficulty in distinguishing between the two scenarios is the phase
transition between a putative two-dimensional spin liquid and the
field-polarized state exists only at zero temperature, while the behaviour at
finite temperature is mostly crossover phenomena. In this work, we provide
insights into the finite temperature crossover behavior between the spin
excitation continuum in a quantum spin liquid and topological magnons in the
field-polarized state in three different theoretical models with large Kitaev
interactions. These models allow for a field-induced phase transition from a
spin liquid (or an intermediate field-induced spin liquid) to the
field-polarized state in the quantum model. We obtain the dynamical spin
structure factor as a function of magnetic field using molecular dynamics
simulations and compute thermal Hall conductivity in the field-polarized
regime. We demonstrate the gradual evolution of the dynamical spin structure
factor exhibiting crossover behaviour near magnetic fields where
zero-temperature phase transitions occur in the quantum model. We also examine
nonlinear effects on topological magnons and the validity of thermal Hall
conductivity computed using linear spin wave theory. We discuss the
implications of our results to existing and future experiments.


  Magnetization dynamics in a ferromagnet can induce a spin-dependent electric
field through spin motive force. Spin current generated by the spin-dependent
electric field can in turn modify the magnetization dynamics through
spin-transfer torque. While this feedback effect is usually weak and thus
ignored, we predict that in Rashba spin-orbit coupling systems with large
Rashba parameter $\alpha_{\rm R}$, the coupling generates the spin-dependent
electric field [$\pm(\alpha_{\rm R}m_e/e\hbar) (\vhat{z}\times \partial
\vec{m}/\partial t)]$, which can be large enough to modify the magnetization
dynamics significantly. This effect should be relevant for device applications
based on ultrathin magnetic layers with strong Rashba spin-orbit coupling.


  For any number field K, it is unknown which finite groups appear as Galois
groups of extensions L/K such that L is a maximal subfield of a division
algebra with center K (a K-division algebra). For K=Q, the answer is described
by the long standing Q-admissibility conjecture.
  We extend a theorem of Neukirch on embedding problems with local constraints
in order to determine for every number field K, what finite solvable groups G
appear as Galois groups of tame maximal subfields of K-division algebras,
generalizing Liedahl's theorem for metacyclic G and Sonn's solution of the
Q-admissibility conjecture for solvable groups.


  Parallel driving is a novel framework to synthesize vehicle intelligence and
transport automation. This article aims to define digital quadruplets in
parallel driving. In the cyber-physical-social systems (CPSS), based on the ACP
method, the names of the digital quadruplets are first given, which are
descriptive, predictive, prescriptive and real vehicles. The objectives of the
three virtual digital vehicles are interacting, guiding, simulating and
improving with the real vehicles. Then, the three virtual components of the
digital quadruplets are introduced in detail and their applications are also
illustrated. Finally, the real vehicles in the parallel driving system and the
research process of the digital quadruplets are depicted. The presented digital
quadruplets in parallel driving are expected to make the future connected
automated driving safety, efficiently and synergistically.


  In a ghost-condensate model of dark energy the combined dynamics of the
scalar field and gravitation is shown to impose non-trivial restriction on the
self-interaction of the scalar field. Using this restriction we show that the
choice of a zero self-interaction leads to a situation too restrictive for the
general evolution of the universe. This restriction, obtained in the form of a
quadratic equation of the scalar potential, is demonstrated to admit real
solutions. Also, in the appropriate limit it reproduces the potential in the
phantom cosmology.


  The magnetic dipole, the electric quadrupole and the Coulomb quadrupole
amplitudes for the transition $\gamma N\to \Delta$ are evaluated both in
quenched lattice QCD at $\beta=6.0$ and using two dynamical Wilson fermions
simulated at $\beta=5.6$. The dipole transition form factor is accurately
determined at several values of momentum transfer. On the lattices studied in
this work, the electric quadrupole amplitude is found to be non-zero yielding a
negative value for the ratio, $ R_{EM}$, of electric quadrupole to magnetic
dipole amplitudes at three values of momentum transfer.


  We investigate dimensional reduction, the property that the critical behavior
of a system in the presence of quenched disorder in dimension d is the same as
that of its pure counterpart in d-2, and its breakdown in the case of the
random-field Ising model in which both the interactions and the correlations of
the disorder are long-ranged, i.e. power-law decaying. To some extent the
power-law exponents play the role of spatial dimension in a short-range model,
which allows us to probe the theoretically predicted existence of a nontrivial
critical value separating a region where dimensional reduction holds from one
where it is broken, while still considering the physical dimension d=3. By
extending our recently developed approach based on a nonperturbative functional
renormalization group combined with a supersymmetric formalism, we find that
such a critical value indeed exists, provided one chooses a specific relation
between the decay exponents of the interactions and of the disorder
correlations. This transition from dimensional reduction to its breakdown
should therefore be observable in simulations and numerical analyses, if not
experimentally.


  Generally, to apply the MUltiple SIgnal Classification (MUSIC) algorithm for
the rapid imaging of small inhomogeneities, the complete elements of the
multi-static response (MSR) matrix must be collected. However, in real-world
applications such as microwave imaging or bistatic measurement configuration,
diagonal elements of the MSR matrix are unknown. Nevertheless, it is possible
to obtain imaging results using a traditional approach but theoretical reason
of the applicability has not been investigated yet. In this paper, we establish
mathematical structures of the imaging function of MUSIC from an MSR matrix
without diagonal elements in both transverse magnetic (TM) and transverse
electric (TE) polarizations. The established structures demonstrate why the
shape of the location of small inhomogeneities can be retrieved via MUSIC
without the diagonal elements of the MSR matrix. In addition, they reveal the
intrinsic properties of imaging and the fundamental limitations. Results of
numerical simulations are also provided to support the identified structures.


  Almost all robotic systems in use have hard shells, which is limiting in many
ways their full potential of physical interaction with humans or their
surrounding environment. Robots with soft-shell covers offer an alternative
morphology which is more pleasant in both appearance and for haptic human
interaction. A persisting challenge in such soft-shell robotic covers is the
simultaneous realization of softness and heat-conducting properties. Such
heat-conducting properties are important for enabling temperature-control of
robotic covers in the range that is comfortable for human touch. The presented
soft-shell robotic cover is composed of a linked two-layer structure: (i) the
inner layer, with built-in pipes for water circulation, is soft and acts as a
thermal-isolation layer between the cover and the robot structure, whereas (ii)
the outer layer, which can be patterned with a given desired texture and color,
allows heat transfer from the circulating water of the inner part to the
surface. Moreover, we demonstrate the ability to integrate our prototype cover
with a humanoid robot equipped with capacitance sensors. This fabrication
technique enables robotic cover possibilities, including tunable color, surface
texture, and size, that are likely to have applications in a variety of robotic
systems.