  For a hyperk\"{a}hler manifold $X$ of dimension $2n$, Huybrechts showed that
there are constants $a_0, a_2, \dots, a_{2n}$ such that $$\chi(L)
=\sum_{i=0}^n\frac{a_{2i}}{(2i)!}q_X(c_1(L))^{i}$$ for any line bundle $L$ on
$X$, where $q_X$ is the Beauville-Bogomolov-Fujiki quadratic form of $X$. Here
the polynomial $\sum_{i=0}^n\frac{a_{2i}}{(2i)!}q^{i}$ is called the
Riemann-Roch polynomial of $X$.
  In this paper, we show that all coefficients of the Riemann-Roch polynomial
of $X$ are positive. This confirms a conjecture proposed by Cao and the author,
which implies Kawamata's effective non-vanishing conjecture for projective
hyperk\"{a}hler manifolds. It also confirms a question of Riess on strict
monotonicity of Riemann-Roch polynomials.
  In order to estimate the coefficients of the Riemann-Roch polynomial, we
produce a Lefschetz-type decomposition of $\text{td}^{1/2}(X)$, the root of the
Todd genus of $X$, via the Rozansky-Witten theory following the ideas of
Hitchin, Sawon, and Nieper-Wi{\ss}kirchen.


  Results are presented from a search for the electroweak production of
supersymmetric particles in pp collisions in final states with two tau leptons.
The data sample corresponds to an integrated luminosity between 18.1 inverse
femtobarns and 19.6 inverse femtobarns depending on the final state of tau
lepton decays, at sqrt(s) = 8 TeV, collected by the CMS experiment at the LHC.
The observed event yields in the signal regions are consistent with the
expected standard model backgrounds. The results are interpreted using
simplified models describing the pair production and decays of charginos or tau
sleptons. For models describing the pair production of the lightest chargino,
exclusion limits are obtained in the plane of chargino mass vs. neutralino mass
under the following assumptions: the chargino decays into third-generation
sleptons, which are taken as the lightest sleptons, and the slepton masses lie
midway between those of the chargino and the neutralino. Chargino masses below
420 GeV are excluded at a 95% confidence level in the limit of a massless
neutralino, and for neutralino masses up to 100 GeV, chargino masses up to 325
GeV are excluded at 95% confidence level. Constraints are also placed on the
cross section for pair production of tau sleptons as a function of mass,
assuming a massless neutralino.


  The regulation of angular momentum is one of the key processes for our
understanding of stellar evolution. The rotational evolution of solar-mass
stars is mainly determined by the magnetic interaction with their circumstellar
disk and angular momentum loss through stellar winds, and In contrast to
solar-mass stars, very low mass (VLM) objects and brown dwarfs are believed to
be fully convective. This may lead to major differences of rotation and
activity, since fully convective objects may not host a solar-type dynamo.
Here, we report on our observational efforts to understand the rotational
evolution of VLM objects. By means of photometric monitoring, we determined 62
rotation periods for targets in three clusters, which form an age sequence from
3 to 125 Myr. We find that VLM objects rotate faster than their solar-mass
siblings in all evolutionary stages. Their rotational evolution seems to be
determined by hydrostatic contraction and exponential angular momentum loss.
The photometric amplitudes of the light curves are much lower than for
solar-mass stars. This may be explained as a consequence of smaller spot
coverage, more symmetric spot distributions, or lower contrast between spots
and their environment. Most of these results can be explained with a change of
the magnetic field properties with decreasing mass. VLM objects possibly
possess only small-scale, turbulent magnetic fields.


  The European Space Agency's Planck satellite was launched on 14 May 2009, and
has been surveying the sky stably and continuously since 13 August 2009. Its
performance is well in line with expectations, and it will continue to gather
scientific data until the end of its cryogenic lifetime. We give an overview of
the history of Planck in its first year of operations, and describe some of the
key performance aspects of the satellite. This paper is part of a package
submitted in conjunction with Planck's Early Release Compact Source Catalogue,
the first data product based on Planck to be released publicly. The package
describes the scientific performance of the Planck payload, and presents
results on a variety of astrophysical topics related to the sources included in
the Catalogue, as well as selected topics on diffuse emission.


  We show that the norm of the vector of Riesz transforms as operator in the
weighted Lebesgue space L^2(w) is bounded by a constant multiple of the first
power of the Poisson-A_2 characteristic of w. The bound is free of dimension.
Our argument requires an extension of Wittwer's linear estimate for martingale
transforms to the vector valued setting with scalar weights, for which we
indicate a proof. Extensions to L^p(w) for 1<p<\infty are discussed. Our proof
for sharpness requires a martingale extrapolation lemma for which we sketch a
proof. We also show that for n>1, the Poisson-A_2 class is properly included in
the classical A_2 class.


  We investigate thermodynamics of general nonequilibrium processes stopped at
stochastic times. We propose a systematic strategy for constructing
fluctuation-theorem-like martingales for each thermodynamic functional,
yielding a family of stopping-time fluctuation theorems. We derive
second-law-like thermodynamic inequalities for the mean thermodynamic
functional at stochastic stopping times, the bounds of which are stronger than
the thermodynamic inequalities resulting from the traditional fluctuation
theorems when the stopping time is reduced to a deterministic one. Numerical
verification is carried out for three well-known thermodynamic functionals,
namely, entropy production, free energy dissipation and dissipative work. These
universal equalities and inequalities are valid for arbitrary stopping
strategies, and thus provide a comprehensive framework with new insights into
the fundamental principles governing nonequilibrium systems.


  We propose a method for scaling trapped ions for large-scale quantum
computation and communication based on a probabilistic ion-photon mapping.
Deterministic quantum gates between remotely located trapped ions can be
achieved through detection of spontaneously-emitted photons, accompanied by the
local Coulomb interaction between neighboring ions. We discuss gate speeds and
tolerance to experimental noise for different probabilistic entanglement
schemes.


  Approaches for kinship verification often rely on cosine distances between
face identification features. However, due to gender bias inherent in these
features, it is hard to reliably predict whether two opposite-gender pairs are
related. Instead of fine tuning the feature extractor network on kinship
verification, we propose a comparator network to cope with this bias. After
concatenating both features, cascaded local expert networks extract the
information most relevant for their corresponding kinship relation. We
demonstrate that our framework is robust against this gender bias and achieves
comparable results on two tracks of the RFIW Challenge 2020. Moreover, we show
how our framework can be further extended to handle partially known or unknown
kinship relations.


  We propose a novel heterostructure to achieve chiral topological
superconductivity in 2D. A substrate with a large Rashba spin-orbit coupling
energy is brought in proximity to a twisted bilayer of thin films exfoliated
from a high-temperature cuprate superconductor. The combined system is then
exposed to an out-of-plane magnetic field. The rare $d + id$ pairing symmetry
expected to occur in such a system allows for nontrivial topology;
specifically, in contrast to the case of the twisted bilayer in isolation, the
substrate induces an odd Chern number. The resulting phase is characterized by
the presence of a Majorana zero mode in each vortex.


  Grid-based magnetohydrodynamic (MHD) simulations have proven invaluable for
the study of astrophysical accretion disks. However, the fact that angular
momentum transport in disks is mediated by MHD turbulence (with structure down
to very small scales) raises the concern that the properties of the modeled
accretion disks are affected by the finite numerical resolution of the
simulation. By implementing an orbital advection algorithm into the Athena code
in cylindrical geometry, we have performed a set of global (but unstratified)
Newtonian disk simulations extending up to resolutions previously unattained.
We study the convergence of these models as a function of spatial resolution
and initial magnetic field geometry. The usual viscosity parameter ($\alpha$)
or the ratio of thermal-to-magnetic pressure ($\beta$) are found to be poor
diagnostics of convergence, whereas the average tilt angle of the magnetic
field in the $(r,\phi)$-plane is a very good diagnostic of convergence. We
suggest that this is related to the saturation of the MHD turbulence via
parasitic modes of the magnetorotational instability. Even in the case of
zero-net magnetic flux, we conclude that our highest resolution simulations
(with 32-zones and 64-zones per vertical scale height) have achieved
convergence.
  Our global simulations reach resolutions comparable to those used in local,
shearing box models of MHD disk turbulence. We find that the saturation
predictors derived from local simulations correspond well to the instantaneous
correlations between local flux and stress found in our global simulations.
However, the conservation of magnetic flux implicit in local models is not
realized in our global disks. Thus, the magnetic connectivity of an accretion
disk represents physics that is truly global and cannot be captured in any
ab-initio local model.


  In this talk we report work on the matching of the next-to-leading
logarithmic approximation (NLLA) onto the fixed next-to-next-to-leading order
(NNLO) calculations for event shape distributions in electron-positron
annihilation. Furthermore we present preliminary results on the determination
of the strong coupling constant obtained using NLLA+NNLO predictions and ALEPH
data.


  Inverse Uncertainty Quantification (UQ), or Bayesian calibration, is the
process to quantify the uncertainties of random input parameters based on
experimental data. The introduction of model discrepancy term is significant
because "over-fitting" can theoretically be avoided. But it also poses
challenges in the practical applications. One of the mostly concerned and
unresolved problem is the "lack of identifiability" issue. With the presence of
model discrepancy, inverse UQ becomes "non-identifiable" in the sense that it
is difficult to precisely distinguish between the parameter uncertainties and
model discrepancy when estimating the calibration parameters. Previous research
to alleviate the non-identifiability issue focused on using informative priors
for the calibration parameters and the model discrepancy, which is usually not
a viable solution because one rarely has such accurate and informative prior
knowledge. In this work, we show that identifiability is largely related to the
sensitivity of the calibration parameters with regards to the chosen responses.
We adopted an improved modular Bayesian approach for inverse UQ that does not
require priors for the model discrepancy term. The relationship between
sensitivity and identifiability was demonstrated with a practical example in
nuclear engineering. It was shown that, in order for a certain calibration
parameter to be statistically identifiable, it should be significant to at
least one of the responses whose data are used for inverse UQ. Good
identifiability cannot be achieved for a certain calibration parameter if it is
not significant to any of the responses. It is also demonstrated that "fake
identifiability" is possible if model responses are not appropriately chosen,
or inaccurate but informative priors are specified.


  We present the first high spatial resolution near-infrared direct and
polarimetric observations of Parsamian 21, obtained with the VLT/NACO
instrument. We complemented these measurements with archival infrared
observations, such as HST/WFPC2 imaging, HST/NICMOS polarimetry, Spitzer IRAC
and MIPS photometry, Spitzer IRS spectroscopy as well as ISO photometry. Our
main conclusions are the following: (1) we argue that Parsamian 21 is probably
an FU Orionis-type object; (2) Parsamian 21 is not associated with any rich
cluster of young stars; (3) our measurements reveal a circumstellar envelope, a
polar cavity and an edge-on disc; the disc seems to be geometrically flat and
extends from approximately 48 to 360 AU from the star; (4) the SED can be
reproduced with a simple model of a circumstellar disc and an envelope; (5)
within the framework of an evolutionary sequence of FUors proposed by Green et
al. (2006) and Quanz et al. (2007), Parsamian 21 can be classified as an
intermediate-aged object.


Lefschetz formulae for torus actions on p-adic groups are proven.


  G. Walker and R. Wood proved that in degree $2^n-1-n$, the space of
indecomposable elements of $\Bbb F_2[x_1,\ldots,x_n]$, considered as a module
over the mod 2 Steenrod algebra, is isomorphic to the Steinberg representation
of $GL_n(\Bbb F_2)$. We generalize this result to all finite fields by
analyzing certain finite quotients of $\Bbb F_q[x_1,\ldots,x_n]$ which come
from the Stanley-Reisner rings of some matroid complexes. Our method also shows
that the space of indecomposable elements in degree $q^{n-1}-n$ has the
dimension equal to that of a complex cuspidal representation of $GL_n(\Bbb
F_q)$. As a by product, over the prime field $\Bbb F_2$, we give a
decomposition of the Steinberg summand of one of these quotients into a direct
sum of suspensions of Brown-Gitler modules. This decomposition suggests the
existence of a stable decomposition derived from the Steinberg module of a
certain topological space into a wedge of suspensions of Brown-Gitler spectra.


  Recommending the right products is the central problem in recommender
systems, but the right products should also be recommended at the right time to
meet the demands of users, so as to maximize their values. Users' demands,
implying strong purchase intents, can be the most useful way to promote
products sales if well utilized. Previous recommendation models mainly focused
on user's general interests to find the right products. However, the aspect of
meeting users' demands at the right time has been much less explored. To
address this problem, we propose a novel Long-Short Demands-aware Model (LSDM),
in which both user's interests towards items and user's demands over time are
incorporated. We summarize two aspects: termed as long-time demands (e.g.,
purchasing the same product repetitively showing a long-time persistent
interest) and short-time demands (e.g., co-purchase like buying paintbrushes
after pigments). To utilize such long-short demands of users, we create
different clusters to group the successive product purchases together according
to different time spans, and use recurrent neural networks to model each
sequence of clusters at a time scale. The long-short purchase demands with
multi-time scales are finally aggregated by joint learning strategies.
Experimental results on three real-world commerce datasets demonstrate the
effectiveness of our model for next-item recommendation, showing the usefulness
of modeling users' long-short purchase demands of items with multi-time scales.


  We revisit the decay of the orbital period in binary systems that occurs due
to the emission of gravitational waves in the context of modified gravity
models where the coupling $G_{gw}$ between matter and on-shell gravitons is
allowed to differ from the Newton constant $G_N$. Using the most precise
orbital parameters of binary pulsars, those of the Double Pulsar, we constrain
the ratio $G_{gw}/G_N$ to the level of $10^{-4}$, improving by two orders of
magnitude the present bound on this quantity.


  It is well known that the Lie-algebra structure on quantum algebras gives
rise to a Poisson-algebra structure on classical algebras as the Planck
constant goes to 0. We show that this correspondance still holds in the
generalization of super- algebra introduced by Scheunert, called
epsilon-algebra. We illustrate this with the example of Number Operator
Algebras, a new kind of object that we have defined and classified under some
assumptions.


  We conducted multi-epoch VLBA phase reference observations of LS I +61 303 in
order to study its precessing radio jet. Compared to similar observations in
2006, we find that the observed elliptical trajectory of emission at 8.4 GHz
repeats after the 9-year gap. The accurate alignment of the emission patterns
yields a precession period of 26.926 +- 0.005 d, which is consistent with that
determined by Lomb-Scargle analysis of the radio light curve. We analytically
model the projection on the sky plane of the peak position of a precessing,
synchrotron-emitting jet, which traces an elliptical trajectory on the sky.
Comparing the simulation with the VLBA astrometry we improve our knowledge of
the geometry of the system.We measure the LS I +61 303 absolute proper motion
to be -0.150 +- 0.006 mas/yr eastward and -0.264 +- 0.006 mas/yr northward.
Removing Galactic rotation, this reveals a small, < 20 km/s, non-circular
motion, which indicates a very low kick velocity when the black hole was
formed.


  Quantization of the magneto-thermoelectric transport is studied when an
external d.c. magnetic field is applied to the C/N-knot formed as crossing
between a narrow stripe of conducting atomic monolayer C on the one hand and
metal stripe N on the other hand. The temperature gradient in C is created by
injecting the non-equilibrium electrons, holes and phonons from the heater H
thereby directing them toward the C/N-knot. A non-linear coupling between
electron states of the C/N-knot counter electrodes causes splitting of the heat
flow into several fractions owing to the Lorentz force acting in the C/N-knot
vicinity, thereby inducing the magneto-thermoelectric current in N whereas the
phonons pass and propagate along C further ahead. The heat flow along C
generates a transversal electric current in N showing a series of maximums when
dimensions of the Landau orbits and the C/N-knot match each other. It allows
observing the interplay between the quantum Hall effect and the spatial
quantization.


  We review recent work of the authors on the non-relativistic Schr\"odinger
equation with a honeycomb lattice potential, $V$. In particular, we summarize
results on (i) the existence of Dirac points, conical singularities in
dispersion surfaces of $H_V=-\Delta+V$ and (ii) the two-dimensional Dirac
equations, as a large, but finite time, effective description of
$e^{-iH_Vt}\psi_0$, for data $\psi_0$, which is spectrally localized at a Dirac
point. We conclude with a formal derivation and discussion of the effective
large time evolution for the nonlinear Schr\"odinger - Gross Pitaevskii
equation for small amplitude initial conditions, $\psi_0$. The effective
dynamics are governed by a nonlinear Dirac system.


  In this article we consider a closed Riemannian manifold (M,g) and A a subset
of M. The purpose of this article is the comparison between the eigenvalues of
a Schrodinger operator on the manifold (M,g) and the eigenvalues on the
manifold (M-A,g) with Dirichlet boundary conditions.


  This article introduces SatHyS (SAT HYbrid Solver), a novel hybrid approach
for propositional satisfiability. It combines local search and conflict driven
clause learning (CDCL) scheme. Each time the local search part reaches a local
minimum, the CDCL is launched. For SAT problems it behaves like a tabu list,
whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable
sub-formula (MUS). Experimental results show good performances on many classes
of SAT instances from the last SAT competitions.


  We show how scale-free degree distributions can emerge naturally from growing
networks by using random walks for selecting vertices for attachment. This
result holds for several variants of the walk algorithm and for a wide range of
parameters. The growth mechanism is based on using local graph information
only, so this is a process of self-organisation. The standard mean-field
equations are an excellent approximation for network growth using these rules.
We discuss the effects of finite size on the degree distribution, and compare
analytical results to simulated networks. Finally, we generalise the random
walk algorithm to produce weighted networks with power-law distributions of
both weight and degree.


  While originally designed for natural language processing tasks, the
self-attention mechanism has recently taken various computer vision areas by
storm. However, the 2D nature of images brings three challenges for applying
self-attention in computer vision. (1) Treating images as 1D sequences neglects
their 2D structures. (2) The quadratic complexity is too expensive for
high-resolution images. (3) It only captures spatial adaptability but ignores
channel adaptability. In this paper, we propose a novel linear attention named
large kernel attention (LKA) to enable self-adaptive and long-range
correlations in self-attention while avoiding its shortcomings. Furthermore, we
present a neural network based on LKA, namely Visual Attention Network (VAN).
While extremely simple, VAN surpasses similar size vision transformers(ViTs)
and convolutional neural networks(CNNs) in various tasks, including image
classification, object detection, semantic segmentation, panoptic segmentation,
pose estimation, etc. For example, VAN-B6 achieves 87.8% accuracy on ImageNet
benchmark and set new state-of-the-art performance (58.2 PQ) for panoptic
segmentation. Besides, VAN-B2 surpasses Swin-T 4% mIoU (50.1 vs. 46.1) for
semantic segmentation on ADE20K benchmark, 2.6% AP (48.8 vs. 46.2) for object
detection on COCO dataset. It provides a novel method and a simple yet strong
baseline for the community. Code is available at
https://github.com/Visual-Attention-Network.


  We present a flexible density-matrix renormalization group approach to
calculate finite-temperature spectral functions of one-dimensional strongly
correlated quantum systems. The method combines the purification of the
finite-temperature density operator with a moment expansion of the Green's
function. Using this approach, we study finite-temperature properties of
dynamical spectral functions of spin-1/2 XXZ chains with Dzyaloshinskii-Moriya
interactions in magnetic fields and analyze the effect of these symmetry
breaking interactions on the nature of the finite-temperature dynamic spin
structure factor.


  Using the $SU(3)$ flavour symmetry of strong interactions, we propose
strategies for extracting both the CKM-angle $\gamma$ and the $\bar b\to\bar
uu\bar s$ tree-level amplitude $T'$. We present also an approximate approach
using the branching ratios for the modes $B^+\to\pi^+ K^0$, $B^0_d\to\pi^-
K^+$, $\bar B^0_d\to\pi^+ K^-$ and $B^+\to\pi^+\pi^0$ which should be rather
promising from the experimental point of view. The quantities $\gamma$ and $T'$
determined this way may well be used as an input to control electroweak
penguins in nonleptonic $B$-decays as has been discussed in previous work.
Following these lines, we propose strategies for obtaining quantitative
insights into the physics of the electroweak penguin operators and performing
some consistency checks. As a by-product, we derive an upper bound of $6^\circ$
for the uncertainty originating from electroweak penguins in the
$\alpha$-determination by means of $B\to\pi\pi$ decays.


  Upcoming many core processors are expected to employ a distributed memory
architecture similar to currently available supercomputers, but parallel
pattern mining algorithms amenable to the architecture are not comprehensively
studied. We present a novel closed pattern mining algorithm with a
well-engineered communication protocol, and generalize it to find statistically
significant patterns from personal genome data. For distributing communication
evenly, it employs global load balancing with multiple stacks distributed on a
set of cores organized as a hypercube with random edges. Our algorithm achieved
up to 1175-fold speedup by using 1200 cores for solving a problem with 11,914
items and 697 transactions, while the naive approach of separating the search
space failed completely.


  The rotations, boosts, and translations in an N^2-dimensional spacetime are
shown to be related to the fundamental commutators, anticommutators, and
Clebsch-Gordan coefficients, respectively, of SU(N).


  The streaming instability is a promising mechanism to induce the formation of
planetesimals. Nonetheless, this process has been found in previous studies to
require either a dust-to-gas surface density ratio or a dust size that is
enhanced compared to observed values. Employing two-dimensional global
simulations of protoplanetary disks, we show that the vertical shear
instability and the streaming instability in concert can cause dust
concentration that is sufficient for planetesimal formation for lower surface
density ratios and smaller dust sizes than the streaming instability in
isolation, and in particular under conditions that are consistent with
observational constraints. This is because dust overdensities forming in
pressure bumps induced by the vertical shear instability act as seeds for the
streaming instability and are enhanced by it. While our two-dimensional model
does not include self-gravity, we find that strong dust clumping and the
formation (and dissolution) of gravitationally unstable overdensities can be
robustly inferred from the evolution of the maximum or the mean dust-to-gas
volume density ratio. The vertical shear instability puffs up the dust layer to
an average mid-plane dust-to-gas density ratio that is significantly below
unity. We therefore find that reaching a mid-plane density ratio of one is not
necessary to trigger planetesimal formation via the streaming instability when
it acts in unison with the vertical shear instability.


  In this paper, we define two particular forms of non-termination, namely
loops and binary chains, in an abstract framework that encompasses term
rewriting and logic programming. The definition of loops relies on the notion
of compatibility of binary relations. We also present a syntactic criterion for
the detection of a special case of binary chains. Moreover, we describe our
implementation NTI and compare its results at the Termination Competition 2023
with those of leading analyzers.


  We review experimental and theoretical developments in inflation and its
application to structure formation, including the curvaton idea. We then
discuss a particle physics model of supersymmetric hybrid inflation at the
intermediate scale in which the Higgs scalar field is responsible for large
scale structure, and show how such a theory is completely natural in the
framework extra dimensions with an intermediate string scale.


  Recent studies have suggested that the Nuclear Pore Complex (NPC) plays a
significant role in mechanotransduction. When a force is exerted, the NPC's
diameter widens, leading to an increased molecular flux into the nucleus. In
this study, we sought to further explore this phenomenon and quantitativelly
assess the impact of pore dilation on molecular transport through the NPC.
Utilizing the scaling theory of polymers, we developed a theoretical model to
examine the relationship between pore size and the molecular transport rate.
Our model posits that the mesh structure inside the pore, formed by FG-Nups,
significantly influences the transport rate. Consequently, we propose that the
transport rate is exponentially related to the pore size. To validate our
model, we conducted extensive Brownian dynamics simulations. Our results
demonstrated that the model accurately represents the transport dynamics except
for exceptionally small molecules. For these molecules, the local mesh
structure becomes less significant, and instead, they perceive the global
structure of the pore. We also identified a critical threshold value, which
allows for an estimation of whether a given molecule falls within the scope of
our model. Our findings provide valuable insights into the dynamics of
molecular transport in the NPC and pave the way for future research on the
NPC's role in mechanotransduction.


  Solitons are known to occur in the context of atom-light interaction via the
well-known semi-classical phenomenon of self-induced transparency (SIT).
Separately, in the regime where both light and atoms are fully treated quantum
mechanically, quantum few-photon bound states are known to be a ubiquitous
phenomenon that arises in different systems such as atoms coupled to chiral or
bidirectional waveguides, and in Rydberg atomic media. In the specific case of
two-level atoms coupled to a chiral waveguide, a recent analysis based on Bethe
ansatz has established that SIT emerges from the quantum realm as a
superposition of quantum many-photon bound states. Beyond this case, however,
the nature of any connection between the full quantum many-body regime and
semi-classical behavior has not been established. Here, we employ a general
spin-model formulation of quantum atom-light interfaces to numerically
investigate this problem, taking advantage of the fact that this approach
readily allows for powerful many-body simulations based on matrix product
states (MPS). We first analytically derive the two-photon bound state
dispersion relation for a variety of atom-light interfaces, and then proceed to
numerically investigate the multi-excitation bound states dynamics.
Interestingly, for all the specific systems studied, we find that the
large-photon number limit always coincides with the soliton phenomenon of
self-induced transparency or immediate generalizations thereof.


  The original and amplitude permutations are two basic ordinal patterns;
however, their relationship has received little attention. This paper compares
the original and amplitude permutations used to characterize vector structures.
To accurately convey the vector structure, we modify indexes of equal values in
the permutations to be the same ones in each group of equalities. Comparative
analysis suggests that the amplitude permutation, comprising the positions of
the original values in the reordered vector, directly reflects the vector's
temporal structure, whereas the original permutation, consisting of the indexes
of reorganized values in the original vector, conveys the structural pattern of
the reorganized vector. Moreover, we clarify the association of the original
and amplitude permutations with timeand amplitude-symmetric vectors, thus
contributing to the fields of symbolic analysis, topological data analysis, and
so on.


  We review recent theoretical progress in the understanding and prediction of
novel topological semimetals. Topological semimetals define a class of gapless
electronic phases exhibiting topologically stable crossings of energy bands.
Different types of topological semimetals can be distinguished based on the
degeneracy of the band crossings, their codimension (e.g., point or line
nodes), as well as the crystal space group symmetries on which the protection
of stable band crossings relies. The dispersion near the band crossing is a
further discriminating characteristic. These properties give rise to a wide
range of distinct semimetal phases such as Dirac or Weyl semimetals, point or
line node semimetals, and type-I or type-II semimetals. In this review we give
a general description of various families of topological semimetals with an
emphasis on proposed material realizations from first-principles calculations.
The conceptual framework for studying topological gapless electronic phases is
reviewed, with a particular focus on the symmetry requirements of energy band
crossings, and the relation between the different families of topological
semimetals is elucidated. In addition to the paradigmatic Dirac and Weyl
semimetals, we pay particular attention to more recent examples of topological
semimetals, which include nodal line semimetals, multifold fermion semimetals,
triple-point semimetals. Less emphasis is placed on their surface state
properties, responses to external probes, and recent experimental developments.


  We studied electromagnetic wave propagation in a system that is periodic in
both space and time, namely a discrete 2D transmission line (TL) with
capacitors modulated in tandem externally. Kirchhoff's laws lead to an
eigenvalue equation whose solutions yield a band structure (BS) for the
circular frequency $\omega$ as function of the phase advances $k_{x}a$ and
$k_{y}a$ in the plane of the TL. The surfaces $\omega(k_{x}a, k_{y}a)$ display
exotic behavior like forbidden $\omega$ bands, forbidden $k$ bands, both, or
neither. Certain critical combinations of the modulation strength $m_{c}$ and
the modulation frequency $\Omega$ mark transitions from $\omega$ stop bands to
forbidden $k$ bands, corresponding to phase transitions from no propagation to
propagation of waves. Such behavior is found invariably at the high symmetry
$\mathbf{X}$ and $\mathbf{M}$ points of the spatial Brillouin zone (BZ) and at
the boundary $\omega=(1/2)\Omega$ of the temporal BZ. At such boundaries the
$\omega(k_{x}a, k_{y}a)$ surfaces in neighboring BZs assume conical forms that
just touch, resembling a South American toy "di\'abolo"; the point of contact
is thus called a "diabolic point". Our investigation reveals interesting
interplay between geometry, critical points, and phase transitions.


  Research on the construction of traditional information science methodology
taxonomy is mostly conducted manually. From the limited corpus, researchers
have attempted to summarize some of the research methodology entities into
several abstract levels (generally three levels); however, they have been
unable to provide a more granular hierarchy. Moreover, updating the methodology
taxonomy is traditionally a slow process. In this study, we collected full-text
academic papers related to information science. First, we constructed a basic
methodology taxonomy with three levels by manual annotation. Then, the word
vectors of the research methodology entities were trained using the full-text
data. Accordingly, the research methodology entities were clustered and the
basic methodology taxonomy was expanded using the clustering results to obtain
a methodology taxonomy with more levels. This study provides new concepts for
constructing a methodology taxonomy of information science. The proposed
methodology taxonomy is semi-automated; it is more detailed than conventional
schemes and the speed of taxonomy renewal has been enhanced.


  We propose a new type of cooling mechanism for ultra-cold fermionic atom
ensembles, which capitalizes on the energy dependence of inelastic collisions
in the presence of a Feshbach resonance. We first discuss the case of a single
magnetic resonance, and find that the final temperature and the cooling rate is
limited by the width of the resonance. A concrete example, based on a p-wave
resonance of $^{40}$K, is given. We then improve upon this setup by using both
a very sharp optical or radio-frequency induced resonance and a very broad
magnetic resonance and show that one can improve upon temperatures reached with
current technologies.


  The Compact Linear Accelerator for Research and Applications (CLARA) is a 250
MeV ultrabright electron beam test facility at STFC Daresbury Laboratory. A
user beam line has been designed to maximise exploitation of CLARA in a variety
of fields, including novel acceleration and new modalities of radiotherapy. In
this paper we present the specification and design of this beam line for Full
Energy Beam Exploitation (FEBE). We outline the key elements which provide
users to access ultrashort, low emittance electron bunches in two large
experiment chambers. The results of start-to-end simulations are reported which
verify the expected beam parameters delivered to these chambers. Key technical
systems are detailed, including those which facilitate combination of electron
bunches with high power laser pulses.


  We discuss calculations of the inclusive total cross section for heavy quark
production at hadron collider energies within the context of perturbative
quantum chromodynamics, including resummation of the effects of initial-state
soft gluon radiation to all orders in the strong coupling strength. We resum
the universal leading-logarithm contributions, and we restrict our integrations
to the region of phase space that is demonstrably perturbative. We include a
detailed comparison of the differences between ours and other methods. We
provide predictions of the physical cross section as a function of the heavy
quark mass in proton-antiproton reactions at center-of-mass energies of 1.8 and
2.0 TeV, and we discuss estimated uncertainties.


  In this article, a biophysically realistic model of a soft octopus arm with
internal musculature is presented. The modeling is motivated by experimental
observations of sensorimotor control where an arm localizes and reaches a
target. Major contributions of this article are: (i) development of models to
capture the mechanical properties of arm musculature, the electrical properties
of the arm peripheral nervous system (PNS), and the coupling of PNS with
muscular contractions; (ii) modeling the arm sensory system, including
chemosensing and proprioception; and (iii) algorithms for sensorimotor control,
which include a novel feedback neural motor control law for mimicking
target-oriented arm reaching motions, and a novel consensus algorithm for
solving sensing problems such as locating a food source from local chemical
sensory information (exogenous) and arm deformation information (endogenous).
Several analytical results, including rest-state characterization and stability
properties of the proposed sensing and motor control algorithms, are provided.
Numerical simulations demonstrate the efficacy of our approach. Qualitative
comparisons against observed arm rest shapes and target-oriented reaching
motions are also reported.


  We obtain in closed form the probability distribution for individual
measurements of the stress-energy tensor of two-dimensional conformal field
theory in the vacuum state, smeared in time against a Gaussian test function.
The result is a shifted Gamma distribution with the shift given by the
previously known optimal quantum inequality bound. For small values of the
central charge it is overwhelmingly likely that individual measurements of the
sampled energy density in the vacuum give negative results. For the case of a
single massless scalar field, the probability of finding a negative value is
84%. We also report on computations for four-dimensional massless scalar fields
showing that the probability distribution of the smeared square field is also a
shifted Gamma distribution, but that the distribution of the energy density is
not.


  Human brain dynamics can be profitably viewed through the lens of statistical
mechanics, where neurophysiological activity evolves around and between local
attractors representing preferred mental states. Many physically-inspired
models of these dynamics define the state of the brain based on instantaneous
measurements of regional activity. Yet, recent work in network neuroscience has
provided initial evidence that the brain might also be well-characterized by
time-varying states composed of locally coherent activity or functional
modules. Here we study this network-based notion of brain state to understand
how functional modules dynamically interact with one another to perform
cognitive functions. We estimate the functional relationships between regions
of interest (ROIs) by fitting a pair-wise maximum entropy model to each ROI's
pattern of allegiance to functional modules. Local minima in this model
represent attractor states characterized by specific patterns of modular
structure. The clustering of local minima highlights three classes of ROIs with
similar patterns of allegiance to community states. Visual, attention,
sensorimotor, and subcortical ROIs tend to form a single functional community.
The remaining ROIs tend to form a putative executive control community or a
putative default mode and salience community. We simulate the brain's dynamic
transitions between these community states using a Markov Chain Monte Carlo
random walk. We observe that simulated transition probabilities between basins
resemble empirically observed transitions between community allegiance states
in resting state fMRI data. These results collectively offer a view of the
brain as a dynamical system that transitions between basins of attraction
characterized by coherent activity in small groups of brain regions, and that
the strength of these attractors depends on the cognitive computations being
performed.


  This work on spin-0 amplitudes in black-hole evaporation is based on the
underlying results and methods outlined in our first paper, "I. Complex
Approach". The main result here, and the model calculation for work on all
higher spins, as described in several further papers, is the computation of the
quantum amplitude (rather than merely the probability) for a given slightly
anisotropic configuration of a scalar field $\phi$ on a space-like hypersurface
$\Sigma_F$ at a very late time $T$. For simplicity, one may take the initial
data for gravity and the massless scalar field at an initial surface $\Sigma_I$
to be spherically symmetric. This applies to perturbations of
spherically-symmetric collapse to a black hole, starting from a diffuse,
nearly-stationary configuration, where the bosonic part of the Lagrangian
consists of Einstein gravity and the massless scalar field. As in Paper I,
Feynman's $+i\epsilon$ approach is taken; this involves a rotation into the
complex: $T\to {\mid}T{\mid} \exp (-i\theta)$, with $0<\theta\leq\pi/2$. A
complex solution of the classical boundary-value problem is expected to exist,
provided $\theta>0$; although for $\theta =0$ (Lorentzian time-separation), the
classical boundary-value problem is badly posed. Once the amplitude is found
for $\theta>0$, one can take the limit $\theta\to 0_+$ to find the Lorentzian
amplitude. The paper also includes a discussion of adiabatic solutions of the
scalar wave equation, needed for the spin-0 calculation.


  We investigate the properties of spontaneous currents generated at surfaces
and interfaces of d-wave superconductors using the self-consistent
quasiclassical Eilenberger equations. The influence of the roughness and
reflectivity of the boundaries on the spontaneous current are studied. We show
that these have very different effects at the surfaces compared to the
interfaces, which reflects the different nature of the time reversal symmetry
breaking states in these two systems. We find a signature of the ``anomalous
proximity effect'' at rough d-wave interfaces. We also show that the existence
of a subdominant order parameter, which is necessary for time reversal symmetry
breaking at the surface, suppresses the spontaneous current generation due to
proximity effect at the interface between two superconductors. We associate
orbital moments to the spontaneous currents to explain the ``superscreening''
effect, which seems to be present at all ideal d-wave surfaces and interfaces,
where d_{xy} is the favorite subdominant symmetry.


  When solving inverse problems in geophysical imaging, deep generative models
(DGMs) may be used to enforce the solution to display highly structured spatial
patterns which are supported by independent information (e.g. the geological
setting) of the subsurface. In such case, inversion may be formulated in a
latent space where a low-dimensional parameterization of the patterns is
defined and where Markov chain Monte Carlo or gradient-based methods may be
applied. However, the generative mapping between the latent and the original
(pixel) representations is usually highly nonlinear which may cause some
difficulties for inversion, especially for gradient-based methods. In this
contribution we review the conceptual framework of inversion with DGMs and
study the principal causes of the nonlinearity of the generative mapping. As a
result, we identify a conflict between two goals: the accuracy of the generated
patterns and the feasibility of gradient-based inversion. In addition, we show
how some of the training parameters of a variational autoencoder, which is a
particular instance of a DGM, may be chosen so that a tradeoff between these
two goals is achieved and acceptable inversion results are obtained with a
stochastic gradient-descent scheme. A test case using truth models with channel
patterns of different complexity and cross-borehole traveltime tomographic data
involving both a linear and a nonlinear forward operator is used to assess the
performance of the proposed approach.


  We calculate the exact values of the F{\o}lner function $\mathrm{F{\o}l}$ of
the lamplighter group $\mathbb{Z}\wr\mathbb{Z}/2\mathbb{Z}$ for the standard
generating set. More generally, for any finite group $D$ and $n\geq|D|$, we
obtain the exact value of $\mathrm{F{\o}l}(n)$ on the wreath product
$\mathbb{Z}\wr D$, for a generating set induced by a generator on $\mathbb{Z}$
and the entire group being taken as generators for $D$. We also describe the
F{\o}lner sets that give rise to it. F{\o}lner functions encode the
isoperimetric properties of amenable groups and have previously been studied up
to asymptotic equivalence (that is to say, independently of the choice of
finite generating set). What is more, we prove an isoperimetric result
concerning the edge boundary on the Baumslag-Solitar group $BS(1,2)$ for the
standard generating set.


  This paper develops an unified framework to study finite-sample convergence
guarantees of a large class of value-based asynchronous reinforcement learning
(RL) algorithms. We do this by first reformulating the RL algorithms as
\textit{Markovian Stochastic Approximation} (SA) algorithms to solve
fixed-point equations. We then develop a Lyapunov analysis and derive
mean-square error bounds on the convergence of the Markovian SA. Based on this
result, we establish finite-sample mean-square convergence bounds for
asynchronous RL algorithms such as $Q$-learning, $n$-step TD, TD$(\lambda)$,
and off-policy TD algorithms including V-trace. As a by-product, by analyzing
the convergence bounds of $n$-step TD and TD$(\lambda)$, we provide theoretical
insights into the bias-variance trade-off, i.e., efficiency of bootstrapping in
RL. This was first posed as an open problem in (Sutton, 1999).


  Conjugate pairs of distributions over infinite dimensional spaces are
prominent in statistical learning theory, particularly due to the widespread
adoption of Bayesian nonparametric methodologies for a host of models and
applications. Much of the existing literature in the learning community focuses
on processes possessing some form of computationally tractable conjugacy as is
the case for the beta and gamma processes (and, via normalization, the
Dirichlet process). For these processes, proofs of conjugacy and requisite
derivation of explicit computational formulae for posterior density parameters
are idiosyncratic to the stochastic process in question. As such, Bayesian
Nonparametric models are currently available for a limited number of conjugate
pairs, e.g. the Dirichlet-multinomial and beta-Bernoulli process pairs. In each
of these above cases the likelihood process belongs to the class of discrete
exponential family distributions. The exclusion of continuous likelihood
distributions from the known cases of Bayesian Nonparametric Conjugate models
stands as a disparity in the researcher's toolbox.
  In this paper we first address the problem of obtaining a general
construction of prior distributions over infinite dimensional spaces possessing
distributional properties amenable to conjugacy. Second, we bridge the divide
between the discrete and continuous likelihoods by illustrating a canonical
construction for stochastic processes whose Levy measure densities are from
positive exponential families, and then demonstrate that these processes in
fact form the prior, likelihood, and posterior in a conjugate family. Our
canonical construction subsumes known computational formulae for posterior
density parameters in the cases where the likelihood is from a discrete
distribution belonging to an exponential family.


  The third named author has been developing a theory of "higher" symplectic
capacities. These capacities are invariant under taking products, and so are
well-suited for studying the stabilized embedding problem. The aim of this note
is to apply this theory, assuming its expected properties, to solve the
stabilized embedding problem for integral ellipsoids, when the eccentricity of
the domain has the opposite parity of the eccentricity of the target and the
target is not a ball. For the other parity, the embedding we construct is
definitely not always optimal; also, in the ball case, our methods recover
previous results of McDuff, and of the second named author and Kerman.
  There is a similar story, with no condition on the eccentricity of the
target, when the target is a polydisc: a special case of this implies a
conjecture of the first named author, Frenkel, and Schlenk concerning the
rescaled polydisc limit function. Some related aspects of the stabilized
embedding problem and some open questions are also discussed.


  The parameters estimation of a system using indirect measurements over the
same system is a problem that occurs in many fields of engineering, known as
the inverse problem. It also happens in the field of underwater acoustic,
especially in mediums that are not transparent enough. In those cases, shape
identification of objects using only acoustic signals is a challenge because it
is carried out with information of echoes that are produced by objects with
different densities from that of the medium. In general, these echoes are
difficult to understand since their information is usually noisy and redundant.
In this paper, we propose a model of convolutional neural network with an
Encoder-Decoder configuration to estimate both localization and shape of
objects, which produce reflected signals. This model allows us to obtain a 2D
velocity model. The model was trained with data generated by the
finite-difference method, and it achieved a value of 98.58% in the intersection
over union metric 75.88% in precision and 64.69% in sensibility.


  We consider fractional diffusion equations and study the stability of the
inverse problem of determining the time-dependent parameter in a source term or
a coefficient of zero-th order term from observations of the solution at one
point in a bounded domain.


  We examine the normal-state temperature and doping dependence of the Hall
coefficient in the context of a pair-fluctuation scenario, based on a model
where itinerant electrons are hybridized with localized electron pairs via a
charge exchange term. We show that an anomalous behavior of the Hall effect,
qualitatively similar to that observed in high-Tc superconductors, can be
attributed to the non-Fermi liquid properties of the single-particle spectral
function which exhibits pseudogap features. Our calculations are based on a
dynamical mean-field procedure which relates the transport coefficients to the
single-particle spectral function in an exact way.


  Time series anomaly detection is a critical machine learning task for
numerous applications, such as finance, healthcare, and industrial systems.
However, even high-performed models may exhibit potential issues such as
biases, leading to unreliable outcomes and misplaced confidence. While model
explanation techniques, particularly visual explanations, offer valuable
insights to detect such issues by elucidating model attributions of their
decision, many limitations still exist -- They are primarily instance-based and
not scalable across dataset, and they provide one-directional information from
the model to the human side, lacking a mechanism for users to address detected
issues. To fulfill these gaps, we introduce HILAD, a novel framework designed
to foster a dynamic and bidirectional collaboration between humans and AI for
enhancing anomaly detection models in time series. Through our visual
interface, HILAD empowers domain experts to detect, interpret, and correct
unexpected model behaviors at scale. Our evaluation with two time series
datasets and user studies demonstrates the effectiveness of HILAD in fostering
a deeper human understanding, immediate corrective actions, and the reliability
enhancement of models.


  HD 49798/RX J0648.0--4418 is a peculiar X-ray binary with a hot subdwarf
(sdO) mass donor. The nature of the accreting compact object is not known, but
its spin period $P=13.2$~s and $\dot P =-2.15 \times 10^{-15}$s~s$^{-1}$, prove
that it can be only either a white dwarf or a neutron star. The spin-up has
been very stable for more than 20 years. We demonstrate that the continuous
stable spin-up of the compact companion of HD 49798 can be best explained by
contraction of a young white dwarf with an age $\sim 2$~Myrs. This allows us to
interpret all the basic parameters of the system in the framework of an
accreting white dwarf. We present examples of binary evolution which result in
such systems. If correct, this is the first direct evidence for a white dwarf
contraction on early evolutionary stages.


  A search for matched circle pairs of similar temperature fluctuations in the
final WMAP 9yr data is carried out. Such a signature is expected if the space
of the Universe is multiply connected. We investigate the relation between the
pixel resolution of cosmic microwave background (CMB) maps and a Gaussian
smoothing in order to lower the probability for missing matched circle pairs.
CMB maps having the 3-torus topology are generated with the characteristics of
the WMAP satellite in order to determine how large the smoothing should be
chosen in CMB maps disturbed by detector noise. The V- and W-band data are
analysed with respect to matched circle pairs and a tentatively signal is found
for a circle pair, which lies, however, close to the plane of the Galaxy. It
is, however, inconclusive whether this signal is generated by chance, is due to
residual foregrounds contained in the V- and W-band maps, or is due to a
genuine topology.


  We analyze fulleride superconductivity at experimental doping levels,
treating the electron-electron and electron-phonon interactions on an equal
footing, and establish the existence of novel physics which helps explain the
unusually high superconducting transition temperatures in these systems. The
Jahn-Teller phonons create a local (intramolecular) pairing that is
surprisingly resistant to the Coulomb repulsion, despite the weakness of
retardation in these low-bandwidth systems. The requirement for coherence
throughout the solid to establish superconductivity then yields a very strong
doping dependence to Tc, one consistent with experiment and much stronger than
expected from standard Eliashberg theory.


  We investigate possible interactions between neutrinos and massive scalar
bosons via $g^{}_{\phi} \overline{\nu} \nu \phi$ (or massive vector bosons via
$g^{}_V \overline{\nu} \gamma^\mu \nu V^{}_\mu$) and explore the allowed
parameter space of the coupling constant $g^{}_{\phi}$ (or $g^{}_V$) and the
scalar (or vector) boson mass $m^{}_\phi$ (or $m^{}_V$) by requiring that these
secret neutrino interactions (SNIs) should not spoil the success of Big Bang
nucleosynthesis (BBN). Incorporating the SNIs into the evolution of the early
Universe in the BBN era, we numerically solve the Boltzmann equations and
compare the predictions for the abundances of light elements with observations.
It turns out that the constraint on $g^{}_{\phi}$ and $m^{}_\phi$ in the
scalar-boson case is rather weak, due to a small number of degrees of freedom.
However, in the vector-boson case, the most stringent bound on the coupling
$g^{}_V \lesssim 6\times 10^{-10}$ at $95~\%$ confidence level is obtained for
$m^{}_V \simeq 1~{\rm MeV}$, while the bound becomes much weaker $g^{}_V
\lesssim 8\times 10^{-6}$ for smaller masses $m^{}_V \lesssim 10^{-4}~{\rm
MeV}$. Moreover, we discuss in some detail how the SNIs affect the cosmological
evolution and the abundances of the lightest elements.


  We present spin transfer switching results for MgO based magnetic tunneling
junctions (MTJs)with large tunneling magnetoresistance (TMR) ratio of up to
150% and low intrinsic switching current density of 2-3 x 10 MA/cm2. The
switching data are compared to those obtained on similar MTJ nanostructures
with AlOx barrier. It is observed that the switching current density for MgO
based MTJs is 3-4 times smaller than that for AlOx based MTJs, and that can be
attributed to higher tunneling spin polarization (TSP) in MgO based MTJs. In
addition, we report a qualitative study of TSP for a set of samples, ranging
from 0.22 for AlOx to 0.46 for MgO based MTJs, and that shows the TSP (at
finite bias) responsible for the current-driven magnetization switching is
suppressed as compared to zero-bias tunneling spin polarization determined from
TMR.


  Recently a version of Lorentz-conserving noncommutative field theory (NCFT)
has been suggested. The underlying Lie algebra of the theory is the same as
that of Doplicher, Fredenhagen, and Roberts. In Lorentz-conserving NCFT the
matrix parameter {theta}^{mu nu} which characterizes the canonical NCFT's is
promoted to an operator {theta hat}^{mu nu} that transforms as a Lorentz
tensor. In this paper, we calculate phenomenological consequences of the QED
version of this theory by looking at various collider processes. In particular
we calculate modifications to Moller scattering, Bhabha scattering, e^+e^- -->
mu^+ mu^- and e^+e^- --> gamma gamma. We obtain bounds on the noncommutativity
scale from the existing experiments at LEP and make predictions for what may be
seen in future collider experiments.


  Several recent high-impact studies leverage large hospital-owned
electrocardiographic (ECG) databases to model and predict patient mortality.
MIMIC-IV, released September 2023, is the first comparable public dataset and
includes 800,000 ECGs from a U.S. hospital system. Previously, the largest
public ECG dataset was Code-15, containing 345,000 ECGs collected during
routine care in Brazil. These datasets now provide an excellent resource for a
broader audience to explore ECG survival modeling. Here, we benchmark survival
model performance on Code-15 and MIMIC-IV with two neural network
architectures, compare four deep survival modeling approaches to Cox
regressions trained on classifier outputs, and evaluate performance at one to
ten years. Our results yield AUROC and concordance scores comparable to past
work (circa 0.8) and reasonable AUPRC scores (MIMIC-IV: 0.4-0.5, Code-15:
0.05-0.13) considering the fraction of ECG samples linked to a mortality
(MIMIC-IV: 27\%, Code-15: 4\%). When evaluating models on the opposite dataset,
AUROC and concordance values drop by 0.1-0.15, which may be due to cohort
differences. All code and results are made public.


  One of the key open problems in network information theory is to obtain the
capacity region for the two-user Interference Channel (IC). In this paper, new
results are derived for this channel. As a first result, a noisy interference
regime is given for the general IC where the sum-rate capacity is achieved by
treating interference as noise at the receivers. To obtain this result, a
single-letter outer bound in terms of some auxiliary random variables is first
established for the sum-rate capacity of the general IC and then those
conditions under which this outer bound is reduced to the achievable sum-rate
given by the simple treating interference as noise strategy are specified. The
main benefit of this approach is that it is applicable for any two-user IC
(potentially non-Gaussian). For the special case of Gaussian channel, our
result is reduced to the noisy interference regime that was previously
obtained. Next, some results are given on the Han-Kobayashi (HK) achievable
rate region. The evaluation of this rate region is in general difficult. In
this paper, a simple characterization of the HK rate region is derived for some
special cases, specifically, for a novel very weak interference regime. As a
remarkable characteristic, it is shown that for this very weak interference
regime, the achievable sum-rate due to the HK region is identical to the one
given by the simple treating interference as noise strategy.


  Traditional image processing is a field of science and technology developed
to facilitate human-centered image management. But today, when huge volumes of
visual data inundate our surroundings (due to the explosive growth of
image-capturing devices, proliferation of Internet communication means and
video sharing services over the World Wide Web), human-centered handling of
Big-data flows is impossible anymore. Therefore, it has to be replaced with a
machine (computer) supported counterpart. Of course, such an artificial
counterpart must be equipped with some cognitive abilities, usually
characteristic for a human being. Indeed, in the past decade, a new computer
design trend - Cognitive Computer development - is become visible. Cognitive
image processing definitely will be one of its main duties. It must be
specially mentioned that this trend is a particular case of a much more general
movement - the transition from a "computational data-processing paradigm" to a
"cognitive information-processing paradigm", which affects today many fields of
science, technology, and engineering. This transition is a blessed novelty, but
its success is hampered by the lack of a clear delimitation between the notion
of data and the notion of information. Elaborating the case of cognitive image
processing, the paper intends to clarify these important research issues.


  Attenuation of high-energy gamma rays by pair-production with UV, optical and
IR extragalactic background light (EBL) photons provides a link between the
history of galaxy formation and high-energy astrophysics. We present results
from our latest semi-analytic models (SAMs), which employ the main ingredients
thought to be important to galaxy formation and evolution, as well as an
improved model for reprocessing of starlight by dust to mid- and far-IR
wavelengths. These SAMs are based upon a Lambda-CDM hierarchical structural
formation scenario, and are successful in reproducing a large variety of
observational constraints such as number counts, luminosity and mass functions,
and color bimodality. Our fiducial model is based upon a WMAP5 cosmology, and
treats dust emission using empirical templates. This model predicts a
background flux considerably lower than optical and near-IR measurements that
rely on subtraction of zodiacal and galactic foregrounds, and near the lower
bounds set by number counts of resolvable sources at a large number of
wavelengths. We also show the results of varying cosmological parameters and
dust attenuation model used in our SAM. For each EBL prediction, we show how
the optical depth due to electron-positron pair-production is affected by
redshift and gamma-ray energy, and the effect of gamma-ray absorption on the
spectra of a variety of extragalactic sources. We conclude with a discussion of
the implications of our work, comparisons to other models and key measurements
of the EBL and a discussion of how the burgeoning science of gamma-ray
astronomy will continue to help constrain cosmology. The low EBL flux predicted
by our fiducial model suggests an optimistic future for further studies of
distant gamma-ray sources.


  We carry out first-principles density-functional calculations of the
antiferrodistortive (AFD) and ferroelectric (FE) soft-mode instabilities in
tetragonal SrTiO3, with the structural degrees of freedom treated in a
classical, zero-temperature framework. In particular, we use frozen-phonon
calculations to make a careful study of the anisotropy of the AFD and FE mode
frequencies in the tetragonal ground state, in which an R-point AFD soft phonon
has condensed. Because of the anharmonic couplings, the presence of this AFD
distortion substantially affects both the AFD and FE mode frequencies. The AFD
mode is found to be softer for rotations around a perpendicular axis (Eg mode)
than for rotations about the tetragonal axis (A1g mode), in agreement with
experimental results. The FE mode, on the other hand, is found to be softer
when polarized perpendicular to the tetragonal axis (Eu mode) than parallel to
it (A2u mode). The sign of this frequency splitting is consistent with the
experimentally reported anisotropy of the dielectric susceptibility and other
evidence. Finally, we present a discussion of the influence of various types of
structural distortions on the FE instability and its anisotropy.


  The Affordable Care Act introduced a revenue transfer formula that requires
insurance plans with generally healthier enrollees to pay funds into a revenue
transfer pool for to reimburse plans with generally less healthy enrollees. For
a given plan, the issue arises of whether the plan will be a payer into or a
receiver from the pool in a chosen future year. To examine that issue, we
analyze data from The Actuary Magazine on transfer payments for 2014-2015, and
we infer strong evidence of a statistical relationship between year-to-year
transfer payments. We also apply to the data a Markov transition model to study
annual changes in the payer-receiver statuses of insurance plans. We estimate
that the limiting conditional probability that an insurance plan will pay into
the pool, given that the plan had paid into the pool in 2014, is 55.6 percent.
Further, that limiting probability is attained quickly because the conditional
probability that an insurance plan will pay into the pool in 2024, given that
the plan had paid into the pool in 2014, is estimated to be 55.7 percent. We
also find the revenue transfer system to have the disturbing feature that once
a plan enters the "state" of paying into the pool then it will stay in that
state for an average period of 4.87 years; moreover, once a plan has received
funds from the pool then it will stay in that state for an average period of
3.89 years.


  Narrow-band intensity-difference squeezing beams have important applications
in quantum metrology and gravitational wave detection. The best way to generate
narrow-band intensity-difference squeezing is to employ
parametrically-amplified four-wave mixing process in high-gain atomic media.
Such IDS can be further enhanced by cascading multiple parametrically-amplified
four-wave mixing processes in separate atomic media. The complicated
experimental setup, added losses and required high-power pump laser with the
increase of number of stages can limit the wide uses of such scheme in
practical applications. Here, we show that by modulating the internal energy
level(s) with additional laser(s), the degree of original intensity-difference
squeezing can be substantially increased. With an initial intensity-difference
squeezing of $-8.5\pm0.4$ dB using parametrically-amplified-non-degenerate
four-wave mixing process in a three-level $\Lambda$-type configuration, the
degree of intensity-difference squeezing can be enhanced to $-11.9\pm0.4$
dB/$-13.9\pm0.4$ dB (corrected for losses) when we use one/two laser beam(s) to
modulate the involved ground/excited state(s). More importantly, a maximal
noise reduction of $-9.7\pm0.4$ dB (only corrected for electronic noise) is
observed below the standard quantum limit, which is the strongest reported to
date in phase insensitive amplification in four-wave mixing. Applying the model
to quantum metrology, the signal-to-noise ratio is improved by 23 dB compared
to the conventional Mach-Zehnder interferometer under the same phase-sensing
intensity, which is a 14-fold enhancement in rms phase measurement sensitivity
beyond the shot noise limit. Our results show a low-loss, robust and efficient
way to produce high degree of IDS and facilitate its potential applications.


  This is an introduction to an algebraic construction of a gravity theory on
noncommutative spaces which is based on a deformed algebra of (infinitesimal)
diffeomorphisms. We start with some fundamental ideas and concepts of
noncommutative spaces. Then the $\theta$-deformation of diffeomorphisms is
studied and a tensor calculus is defined. A deformed Einstein-Hilbert action
invariant with respect to deformed diffeomorphisms is given. Finally, all
noncommutative fields are expressed in terms of their commutative counterparts
up to second order of the deformation parameter using the $\star$-product. This
allows to study explicitly deviations to Einstein's gravity theory in orders of
$\theta$.


  When running at scale, modern scientific workflows require middleware to
handle allocated resources, distribute computing payloads and guarantee a
resilient execution. While individual steps might not require sophisticated
control methods, bringing them together as a whole workflow requires advanced
management mechanisms. In this work, we used RADICAL-EnTK (Ensemble Toolkit) -
one of the SDK components of the ECP ExaWorks project - to implement and
execute the novel Exascale Additive Manufacturing (ExaAM) workflows on up to
8000 compute nodes of the Frontier supercomputer at the Oak Ridge Leadership
Computing Facility. EnTK allowed us to address challenges such as varying
resource requirements (e.g., heterogeneity, size, and runtime), different
execution environment per workflow, and fault tolerance. And a native
portability feature of the developed EnTK applications allowed us to adjust
these applications for Frontier runs promptly, while ensuring an expected level
of resource utilization (up to 90%).


  Excitation-energy spectra of $^{11}$C nuclei near the $\eta^\prime$-meson
production threshold have been measured by missing-mass spectroscopy using the
$^{12}$C($p$,$d$) reaction. A carbon target has been irradiated with a 2.5 GeV
proton beam supplied by the synchrotron SIS-18 at GSI to produce $\eta^\prime$
meson bound states in $^{11}$C nuclei. Deuterons emitted at $0^\circ$ in the
reaction have been momentum-analyzed by the fragment separator (FRS) used as a
high-resolution spectrometer. No distinct structure due to the formation of
$\eta^\prime$-mesic states is observed although a high statistical sensitivity
is achieved in the experimental spectra. Upper limits on the formation cross
sections of $\eta^\prime$-mesic states are determined, and thereby a constraint
imposed on the $\eta^\prime$-nucleus interaction is discussed.


  We propose a new phenomenological approach to establish QCD factorization of
jet cross sections in the heavy-ion environment. Starting from a factorization
formalism in proton-proton collisions, we introduce medium modified jet
functions to capture the leading interaction of jets with the hot and dense QCD
medium. A global analysis using a Monte Carlo sampling approach is performed in
order to reliably determine the new jet functions from the nuclear modification
factor of inclusive jets at the LHC. We find that gluon jets are significantly
more suppressed due to the presence of the medium than quark jets. In addition,
we observe that the jet radius dependence is directly related to the relative
suppression of quark and gluon jets. Our approach may help to improve the
extraction of medium properties from data.


  In this work, we consider the problem of steering the first two moments of
the uncertain state of a discrete time nonlinear stochastic system to
prescribed goal quantities at a given final time. In principle, the latter
problem can be formulated as a density tracking problem, which seeks for a
feedback policy that will keep the probability density function of the state of
the system close, in terms of an appropriate metric, to the goal density. The
solution to the latter infinite-dimensional problem can be, however, a complex
and computationally expensive task. Instead, we propose a more tractable and
intuitive approach which relies on a greedy control policy. The latter control
policy is comprised of the first elements of the control policies that solve a
sequence of corresponding linearized covariance steering problems. Each of
these covariance steering problems relies only on information available about
the state mean and state covariance at the current stage and can be formulated
as a tractable (finite-dimensional) convex program. At each stage, the
information on the state statistics is updated by computing approximations of
the predicted state mean and covariance of the resulting closed-loop nonlinear
system at the next stage by utilizing the (scaled) unscented transform.
Numerical simulations that illustrate the key ideas of our approach are also
presented.


  In frequency-division duplexing (FDD) massive multiple-input multiple-output
(MIMO) systems, 1-bit compressed sensing (CS)-based superimposed channel state
information (CSI) feedback has shown many advantages, while still faces many
challenges, such as low accuracy of the downlink CSI recovery and large
processing delays. To overcome these drawbacks, this paper proposes a deep
learning (DL) scheme to improve the 1-bit compressed sensing-based superimposed
CSI feedback. On the user side, the downlink CSI is compressed with the 1-bit
CS technique, superimposed on the uplink user data sequences (UL-US), and then
sent back to the base station (BS). At the BS, based on the model-driven
approach and assisted by the superimposition-interference cancellation
technology, a multi-task detection network is first constructed for detecting
both the UL-US and downlink CSI. In particular, this detection network is
jointly trained to detect the UL-US and downlink CSI simultaneously, capturing
a globally optimized network parameter. Then, with the recovered bits for the
downlink CSI, a lightweight reconstruction scheme, which consists of an initial
feature extraction of the downlink CSI with the simplified traditional method
and a single hidden layer network, is utilized to reconstruct the downlink CSI
with low processing delay. Compared with the 1-bit CS-based superimposed CSI
feedback scheme, the proposed scheme improves the recovery accuracy of the
UL-US and downlink CSI with lower processing delay and possesses robustness
against parameter variations.


  Mirror universe is a fundamental way to restore parity symmetry in weak
interactions. It naturally provides the lightest mirror nucleon as a unique
GeV-scale asymmetric dark matter particle candidate. We conjecture that the
mirror parity is respected by the fundamental interaction Lagrangian, and its
possible soft breaking arises only from non-interaction terms in the
gauge-singlet sector. We realize the spontaneous mirror parity violation by
minimizing the vacuum Higgs potential, and derive the corresponding Higgs
spectrum. We demonstrate that the common origin of CP violation in the visible
and mirror neutrino seesaws can generate the right amount of matter and mirror
dark matter via leptogenesis. We analyze the direct detections of GeV-scale
mirror dark matter by TEXONO and CDEX experiments. We further study the
predicted distinctive Higgs signatures at the LHC.


  Hybrid free space optical (FSO)/radio frequency (RF) systems have been proved
to be reliable links for high-data-rate wireless backhauls. In this paper, we
present a unified performance analysis of the hybrid FSO/RF transmission system
which transmits the identical data in both links and implements two popular
diversity combining schemes, namely, selection combining (SC) and maximal ratio
combining (MRC), in the receiver. Specially, for the FSO link, the Gamma-Gamma
turbulence with pointing errors under heterodyne detection (HD) and intensity
modulation/direction detection (IM/DD) is considered in our analysis while the
general \k{appa}-{\mu} shadowed fading which unifies popular RF fading models
is employed for the analysis of the RF link. As a result, unified closed-form
expressions of outage probabilities and average bit error rates for different
modulation schemes are derived. Analytical and Monte Carlo simulation results
are provided to characterize the performance of the hybrid FSO/RF link which is
compared to the single FSO link and the single RF link. The agreement between
the analytical and simulation results confirms the unification of various FSO
channels and RF fading scenarios into a single closed-form expression.


  This paper studies theoretically the ultraslow light phenomenon in
Bose-Einstein condensates of alkali-metal atoms. The description is based on
the linear approach that is developed in the framework of the Green function
formalism. It is pointed out that the group velocity of light pulses that are
tuned up close to resonant lines of the alkali atoms' spectrum may strongly
depend on the intensity of the external static magnetic field. The possibility
of filtering optical pulses using the ultraslow light phenomenon in Bose
condensates is discussed.


  By calculating the non-equilibrium parameter of the probability distribution
function and the singularity spectrum of multifractal we have quantified the
dynamical heterogeneity in strongly correlated many-body systems.


  We live in a universe filled with galaxies with an amazing variety of sizes
and shapes. One of the biggest challenges for astronomers working in this field
is to understand how all these types relate to each other in the background of
an expanding universe. Modern astronomical surveys (like the Sloan Digital Sky
Survey) have revolutionised this field of astronomy, by providing vast numbers
of galaxies to study. The sheer size of the these databases made traditional
visual classification of the types galaxies impossible and in 2007 inspired the
Galaxy Zoo project (www.galaxyzoo.org); starting the largest ever scientific
collaboration by asking members of the public to help classify galaxies by type
and shape. Galaxy Zoo has since shown itself, in a series of now more than 30
scientific papers, to be a fantastic database for the study of galaxy
evolution. In this Invited Discourse I spoke a little about the historical
background of our understanding of what galaxies are, of galaxy classification,
about our modern view of galaxies in the era of large surveys. I finish with
showcasing some of the contributions galaxy classifications from the Galaxy Zoo
project are making to our understanding of galaxy evolution.
  This publication has been made possible by the participation of more than
200,000 volunteers in the Galaxy Zoo project. Their contributions are
individually acknowledged at http://www.galaxyzoo.org/volunteers. KLM
acknowledges funding from the Peter and Patricia Gruber Foundation as the 2008
Peter and Patricia Gruber Foundation IAU Fellow, and from a 2010 Leverhulme
Trust Early Career Fellowship, as well as support from the Royal Astronomical
Society to attend the 28th GA of the IAU.


  Effects on the spectra of the quantum bouncer due to dissipation are given
when a linear or quadratic dissipation is taken into account. Classical
constant of motions and Hamiltonians are deduced for these systems and their
quantized eigenvalues are estimated through perturbation theory. we found some
differences when we compare the eigenvalues of these two quantities.


  In the last 50 years, equilibrium density functional theory (DFT) has been
proven to be a powerful, versatile and predictive approach for the statics and
structure of classical particles. This theory can be extended to the
nonequilibrium dynamics of completely overdamped Brownian colloidal particles
towards so-called dynamical density functional theory (DDFT). The success of
DDFT makes it a promising candidate for a first-principle description of active
matter. In this lecture, we shall first recapitulate classical DDFT for passive
colloidal particles typically described by Smoluchowski equation. After a basic
derivation of DDFT from the Smoluchowski equation, we discuss orientational
degrees of freedom and the effect of hydrodynamic interactions for passive
particles. This brings us into an ideal position to generalize DDFT towards
active matter. In particular we distinguish between "dry active matter" which
is composed of self-propelled particles that contain no hydrodynamic flow
effects of a surrounding solvent and "wet active matter" where the hydrodynamic
flow fields generated by the microswimmers are taken into account. For the
latter, DDFT is a tool which unifies thermal fluctuations, direct particle
interactions, external driving fields and hydrodynamic effects arising from
internal self-propulsion discriminating between "pushers" and "pullers". A
number of recent applications is discussed including transient clustering of
self-propelled rods and the spontaneous formation of a hydrodynamic pump in
confined microswimmers.


  We present the Dirichlet-Neumann (DN) and Neumann-Neumann (NN) methods
applied to the optimal control problems arising from elliptic partial
differential equations (PDEs) under the $H^{-1}$ regularization. We use the
Lagrange multiplier approach to derive a forward-backward optimality system
with the $L^2$ regularization, and a singular perturbed Poisson equation with
the $H^{-1}$ regularization. The $H^{-1}$ regularization thus avoids solving a
coupled bi-Laplacian problem, yet the solutions are less regular. The singular
perturbed Poisson equation is then solved by using the DN and NN methods, and a
detailed analysis is given both in the one-dimensional and two-dimensional
case. Finally, we provide some numerical experiments with conclusions.


  VERITAS observed the supernova remnants Cassiopeia A (Cas A) and IC 443
during 2007, resulting in strong TeV detections of both sources. Cas A is a
young remnant, and bright in both the radio and nonthermal X-rays, both tracers
of cosmic-ray electrons. IC 443 is a middle-aged composite remnant interacting
with a molecular cloud; the molecular cloud provides an enhanced density of
target material for hadronic cosmic rays to produce TeV gamma rays via pion
decay. The TeV morphology - point-like for Cas A and extended for IC 443 - will
be discussed in the context of existing multiwavelength data on the remnants.


  There exists a two parameter action, the variation of which produces both the
geodesic equation and the geodesic deviation equation. In this paper it is
shown that this action can be quantized by the canonical method, resulting in
equations which generalize the Klein-Gordon equation. The resulting equations
might have applications, and also show that entirely unexpected systems can be
quantized. The possible applications of quantized geodesic deviation are to:
i)the spreading wave packet in quantum theory, ii)and also to the one particle
to many particle problem in second quantized quantum field theory.


  We report the detection of numerous far-infrared emission lines of water
vapor toward the supergiant star VY Canis Majoris. A 29.5 - 45 micron grating
scan of VY CMa, obtained using the Short Wavelength Spectrometer (SWS) of the
Infrared Space Observatory (ISO) at a spectral resolving power of approximately
2000, reveals at least 41 spectral features due to water vapor that together
radiate a total luminosity ~ 25 solar luminosities. In addition to pure
rotational transitions within the ground vibrational state, these features
include rotational transitions within the (010) excited vibrational state. The
spectrum also shows the doublet Pi 1/2 (J=5/2) <-- doublet Pi 3/2 (J=3/2) OH
feature near 34.6 micron in absorption. Additional SWS observations of VY CMa
were carried out in the instrument's Fabry-Perot mode for three water
transitions: the 7(25)-6(16) line at 29.8367 micron, the 4(41)-3(12) line
31.7721 micron, and the 4(32)-3(03) line at 40.6909 micron. The higher spectral
resolving power of approximately 30,000 thereby obtained permits the line
profiles to be resolved spectrally for the first time and reveals the "P Cygni"
profiles that are characteristic of emission from an outflowing envelope.


  The common-envelope (CE) phase is an important stage in the evolution of
binary stellar populations. The most common way to compute the change in
orbital period during a CE is to relate the binding energy of the envelope of
the Roche-lobe filling giant to the change in orbital energy. Especially in
population-synthesis codes, where the evolution of millions of stars must be
computed and detailed evolutionary models are too expensive computationally,
simple approximations are made for the envelope binding energy. In this study,
we present accurate analytic prescriptions based on detailed stellar-evolution
models that provide the envelope binding energy for giants with metallicities
between Z = 10-4 and Z = 0.03 and masses between 0.8 Msun and 100 Msun, as a
function of the metallicity, mass, radius and evolutionary phase of the star.
Our results are also presented in the form of electronic data tables and
Fortran routines that use them. We find that the accuracy of our fits is better
than 15% for 90% of our model data points in all cases, and better than 10% for
90% of our data points in all cases except the asymptotic giant branches for
three of the six metallicities we consider. For very massive stars (M > 50
Msun), when stars lose more than ~20% of their initial mass due to stellar
winds, our fits do not describe the models as accurately. Our results are more
widely applicable - covering wider ranges of metallicity and mass - and are of
higher accuracy than those of previous studies.


  In this note, we construct a minimal surface of general type with geometric
genus p g = 4, self-intersection of the canonical divisor K^2 = 32 and
irregularity q = 1 such that its canonical map is an abelian cover of degree 16
of P^1 x P^1.


  GeoAI has emerged as an exciting interdisciplinary research area that
combines spatial theories and data with cutting-edge AI models to address
geospatial problems in a novel, data-driven manner. While GeoAI research has
flourished in the GIScience literature, its reproducibility and replicability
(R&R), fundamental principles that determine the reusability, reliability, and
scientific rigor of research findings, have rarely been discussed. This paper
aims to provide an in-depth analysis of this topic from both computational and
spatial perspectives. We first categorize the major goals for reproducing GeoAI
research, namely, validation (repeatability), learning and adapting the method
for solving a similar or new problem (reproducibility), and examining the
generalizability of the research findings (replicability). Each of these goals
requires different levels of understanding of GeoAI, as well as different
methods to ensure its success. We then discuss the factors that may cause the
lack of R&R in GeoAI research, with an emphasis on (1) the selection and use of
training data; (2) the uncertainty that resides in the GeoAI model design,
training, deployment, and inference processes; and more importantly (3) the
inherent spatial heterogeneity of geospatial data and processes. We use a deep
learning-based image analysis task as an example to demonstrate the results'
uncertainty and spatial variance caused by different factors. The findings
reiterate the importance of knowledge sharing, as well as the generation of a
"replicability map" that incorporates spatial autocorrelation and spatial
heterogeneity into consideration in quantifying the spatial replicability of
GeoAI research.


  Autonomous flight in unknown environments requires precise planning for both
the spatial and temporal profiles of trajectories, which generally involves
nonconvex optimization, leading to high time costs and susceptibility to local
optima. To address these limitations, we introduce the Learning-Initialized
Trajectory Planner (LIT-Planner), a novel approach that guides optimization
using a Neural Network (NN) Planner to provide initial values. We first
leverage the spatial-temporal optimization with batch sampling to generate
training cases, aiming to capture multimodality in trajectories. Based on these
data, the NN-Planner maps visual and inertial observations to trajectory
parameters for handling unknown environments. The network outputs are then
optimized to enhance both reliability and explainability, ensuring robust
performance. Furthermore, we propose a framework that supports robust online
replanning with tolerance to planning latency. Comprehensive simulations
validate the LIT-Planner's time efficiency without compromising trajectory
quality compared to optimization-based methods. Real-world experiments further
demonstrate its practical suitability for autonomous drone navigation.


  Let $G$ be an unramified group over a $p$-adic field. This article introduces
a base change homomorphism for Bernstein centers of depth-zero principal series
blocks for $G$ and proves the corresponding base change fundamental lemma. This
result is used in the approach to Shimura varieties with $\Gamma_1(p)$-level
structure initiated by M. Rapoport and the author in [HR2].


  We introduce algorithms for online, full-information prediction that are
competitive with contextual tree experts of unknown complexity, in both
probabilistic and adversarial settings. We show that by incorporating a
probabilistic framework of structural risk minimization into existing adaptive
algorithms, we can robustly learn not only the presence of stochastic structure
when it exists (leading to constant as opposed to $\mathcal{O}(\sqrt{T})$
regret), but also the correct model order. We thus obtain regret bounds that
are competitive with the regret of an optimal algorithm that possesses strong
side information about both the complexity of the optimal contextual tree
expert and whether the process generating the data is stochastic or
adversarial. These are the first constructive guarantees on simultaneous
adaptivity to the model and the presence of stochasticity.


  We show that the set of Heisenberg polynomials furnishes a simple non-trivial
example in the uniform treatment of Darboux's method.


  We analyze spin-dependent energetics and conductance for one dimensional (1D)
atomic carbon wires consisting of terminal magnetic (Co) and interior
nonmagnetic (C) atoms sandwiched between gold electrodes, obtained employing
first-principles gradient corrected density functional theory and Landauer's
formalism for conductance. Wires containing an even number of interior carbon
atoms are found to be acetylenic with sigma-pi bonding patterns, while cumulene
structures are seen in wires containing odd number of interior carbon atoms, as
a result of strong pi-conjugation. Ground states of carbon wires containing up
to 13 C atoms are found to have anti-parallel spin configurations of the two
terminal Co atoms, while the 14 C wire has a parallel Co spin configuration in
the ground state. The stability of the anti-ferromagnetic state in the wires is
ascribed to a super-exchange effect. For the cumulenic wires this effect is
constant for all wire lengths. For the acetylenic wires, the super-exchange
effect diminishes as the wire length increases, going to zero for the atomic
wire containing 14 carbon atoms. Conductance calculations at the zero bias
limit show spin-valve behavior, with the parallel Co spin configuration state
giving higher conductance than the corresponding anti-parallel state, and a
non-monotonic variation of conductance with the length of the wires for both
spin configurations.


  We discuss how properties of Hecke symmetry (i.e., Hecke type R-matrix)
influence the algebraic structure of the corresponding Reflection Equation (RE)
algebra. Analogues of the Newton relations and Cayley-Hamilton theorem for the
matrix of generators of the RE algebra related to a finite rank even Hecke
symmetry are derived.


  Quick Shift is a popular mode-seeking and clustering algorithm. We present
finite sample statistical consistency guarantees for Quick Shift on mode and
cluster recovery under mild distributional assumptions. We then apply our
results to construct a consistent modal regression algorithm.


  In this paper we are interested in unraveling the mathematical connections
between the stochastic derivation of Schr\"odinger equation and ours. It will
be shown that these connections are given by means of the time-energy
dispersion relation and will allow us to interpret this relation on more
sounded grounds. We also discuss the underlying epistemology.


  Among confirmed central compact objects (CCOs), only three sources have
measured period and period derivatives. We have investigated possible
evolutionary paths of these three CCOs in the fallback disc model. The model
can account for the individual X-ray luminosities and rotational properties of
the sources consistently with their estimated supernova ages. For these
sources, reasonable model curves can be obtained with dipole field strengths
$\sim$ a few $\times 10^9$ G on the surface of the star. The model curves
indicate that these CCOs were in the spin-up state in the early phase of
evolution. The spin-down starts, while accretion is going on, at a time $t \sim
10^3 - 10^4$ yr depending on the current accretion rate, period and the
magnetic dipole moment of the star. This implies that some of the CCOs with
relatively long periods, weak dipole fields and high X-ray luminosities could
be strong candidates to show spin-up behavior if they indeed evolve with
fallback discs.


  A substantial number of algorithms exists for the simulation of moving
particles suspended in fluids. However, finding the best method to address a
particular physical problem is often highly non-trivial and depends on the
properties of the particles and the involved fluid(s) together. In this report
we provide a short overview on a number of existing simulation methods and
provide two state of the art examples in more detail. In both cases, the
particles are described using a Discrete Element Method (DEM). The DEM solver
is usually coupled to a fluid-solver, which can be classified as grid-based or
mesh-free (one example for each is given). Fluid solvers feature different
resolutions relative to the particle size and separation. First, a
multicomponent lattice Boltzmann algorithm (mesh-based and with rather fine
resolution) is presented to study the behavior of particle stabilized fluid
interfaces and second, a Smoothed Particle Hydrodynamics implementation
(mesh-free, meso-scale resolution, similar to the particle size) is introduced
to highlight a new player in the field, which is expected to be particularly
suited for flows including free surfaces.


  Opinion summarisation synthesises opinions expressed in a group of documents
discussing the same topic to produce a single summary. Recent work has looked
at opinion summarisation of clusters of social media posts. Such posts are
noisy and have unpredictable structure, posing additional challenges for the
construction of the summary distribution and the preservation of meaning
compared to online reviews, which has been so far the focus of opinion
summarisation. To address these challenges we present \textit{WassOS}, an
unsupervised abstractive summarization model which makes use of the Wasserstein
distance. A Variational Autoencoder is used to get the distribution of
documents/posts, and the distributions are disentangled into separate semantic
and syntactic spaces. The summary distribution is obtained using the
Wasserstein barycenter of the semantic and syntactic distributions. A latent
variable sampled from the summary distribution is fed into a GRU decoder with a
transformer layer to produce the final summary. Our experiments on multiple
datasets including Twitter clusters, Reddit threads, and reviews show that
WassOS almost always outperforms the state-of-the-art on ROUGE metrics and
consistently produces the best summaries with respect to meaning preservation
according to human evaluations.


  We consider the problem of optimizing locations of distribution centers (DCs)
and plans for distributing resources such as test kits and vaccines, under
spatiotemporal uncertainties of disease spread and demand for the resources. We
aim to balance the operational cost (including costs of deploying facilities,
shipping, and storage) and quality of service (reflected by demand coverage),
while ensuring equity and fairness of resource distribution across multiple
populations. We compare a sample-based stochastic programming (SP) approach
with a distributionally robust optimization (DRO) approach using a moment-based
ambiguity set. Numerical studies are conducted on instances of distributing
COVID-19 vaccines in the United States and test kits, to compare SP and DRO
models with a deterministic formulation using estimated demand and with the
current resource distribution plans implemented in the US. We demonstrate the
results over distinct phases of the pandemic to estimate the cost and speed of
resource distribution depending on scale and coverage, and show the
``demand-driven'' properties of the SP and DRO solutions. Our results further
indicate that if the worst-case unmet demand is prioritized, then the DRO
approach is preferred despite of its higher overall cost. Nevertheless, the SP
approach can provide an intermediate plan under budgetary restrictions without
significant compromises in demand coverage.


  We demonstrate a quantum dot single photon source at 900 nm triggered at 300
MHz by a continuous wave telecommunications wavelength laser followed by an
electro-optic modulator. The quantum dot is excited by on-chip-generated second
harmonic radiation, resonantly enhanced by a GaAs photonic crystal cavity
surrounding the InAs quantum dot. Our result suggests a path toward the
realization of telecommunications-wavelength-compatible quantum dot single
photon sources with speeds exceeding 1 GHz.