  We give a partial answer to the question whether the Schrodinger equation can
be derived from the Newtonian mechanics of a particle in a potential subject to
a random force. We show that the fluctuations around the classical motion of a
one dimensional harmonic oscillator subject to a random force can be described
by the Schrodinger equation for a period of time depending on the frequency and
the energy of the oscillator. We achieve this by deriving the postulates of
Nelson's stochastic formulation of quantum mechanics for a random force
depending on a small parameter. We show that the same result applies to small
potential perturbations around the harmonic oscillator as long as the total
potential preserves the periodicity of motion with a small shift in frequency.
We also show that the noise spectrum can be chosen to obtain the result for all
oscillator frequencies for fixed mass. We discuss heuristics to generalize the
result for a particle in one dimension in a potential where the motion can be
described using action-angle variables.


  The recent result from the DESI (Dark Energy Spectroscopic Instrument) data
release 1 (DR1) combined with the cosmic microwave background and supernova
data shows a preference for the dynamical dark energy over the cosmological
constant [1]. For this analysis, the Chevallier-Polarski-Linder (CPL)
parameterization of the dark energy equation of state has been used. Though CPL
parametrization is the most popular parametrization of dark energy equation of
state (EoS) recent studies have questioned its choice of prior and degeneracy.
In this work, we propose a new parametrization of the dark energy equation of
state motivated by its ability to cross the phantom barrier crossing. At a high
redshift limit, this parametrization takes the form of CPL parametrization. We
have used the Bayesian model selection criteria in which this parametrisation
shows a moderate positive preference over the $\Lambda$CDM model. Contrary to
the DESI2024 results our model suggests the current value of the dark energy
equation of state to be phantom today with two phantom barrier crossings one at
$z\simeq 0.4$ from deep phantom to quintessence which matches with the finding
from the DESI2024 result and another phantom barrier crossing very recently at
$z\simeq0.1$ from quintessence to phantom. The proposed model also weakens the
Hubble tension significantly to $\approx 2 \sigma$ while comparing with the
result from [2] and to $\approx 1.4 \sigma$ while comparing with [3].


  Given a smooth, projective variety $X$ and an effective divisor
$D\,\subseteq\, X$, it is well-known that the (topological) obstruction to the
deformation of the fundamental class of $D$ as a Hodge class, lies in
$H^2(\mathcal{O}_X)$. In this article, we replace $H^2(\mathcal{O}_X)$ by
$H^2_D(\mathcal{O}_X)$ and give an analogous topological obstruction theory. We
compare the resulting local topological obstruction theory with the geometric
obstruction theory (i.e., the obstruction to the deformation of $D$ as an
effective Cartier divisor of a first order infinitesimal deformations of $X$).
We apply this to study the jumping locus of families of linear systems and the
Noether-Lefschetz locus. Finally, we give examples of first order deformations
$X_t$ of $X$ for which the cohomology class $[D]$ deforms as a Hodge class but
$D$ does not lift as an effective Cartier divisor of $X_t$.


  Understanding the generation of mechanical stress in drying, particle-laden
films is important for a wide range of industrial processes. The cantilever
experiment allows the stress in a drying film that has been deposited onto a
thin plate to be quantified. Mechanical stresses in the film are transmitted to
the plate and drive bending. Mathematical modelling enables the film stress to
be inferred from measurements of the plate deflection. The aim of this paper is
to present simplified models of the cantilever experiment that have been
derived from the time-dependent equations of continuum mechanics using
asymptotic methods. The film is described using nonlinear poroelasticity and
the plate using nonlinear elasticity. In contrast to Stoney-like formulae, the
simplified models account for films with non-uniform thickness and stress. The
film model reduces to a single differential equation that can be solved
independently of the plate equations. The plate model reduces to an extended
form of the Foppl-von Karman (FvK) equations that accounts for gradients in the
longitudinal traction acting on the plate surface. Consistent boundary
conditions for the FvK equations are derived by resolving the Saint-Venant
boundary layers at the free edges of the plate. The asymptotically reduced
models are in excellent agreement with finite element solutions of the full
governing equations. As the P\'eclet number increases, the time evolution of
the plate deflection changes from $t$ to $t^{1/2}$, in agreement with
experiments.


  The large arrays of magnetic dots are the building blocks of magnonic
crystals and the emerging bit patterned media for future recording technology.
In order to fully utilize the functionalities of high density magnetic
nanodots, a method for the selective reversal of a single nanodot in a matrix
of dots is desired. We have proposed a method for magnetization reversal of a
single nanodot with microwave excitation in a matrix of magneto-statically
interacting dots. The method is based on the excitation of collective modes and
the spatial anomaly in the microwave power absorption. We perform numerical
simulations to demonstrate the possibility of switching a single dot from any
initial state of a 3 by 3 matrix of dots, and develop a theoretical model for
the phenomena. We discuss the applicability of the proposed method for
introducing defect modes in magnonic crystals as well as for future magnetic
recording.


  An improved Quantum Molecular Dynamics model is proposed. By using this
model, the properties of ground state of nuclei from $^{6}$Li to $^{208}$Pb can
be described very well with one set of parameters. The fusion reactions for
$^{40}$Ca+$^{90}$Zr, $^{40}$Ca+$^{96}$Zr and $^{48}$Ca+$^{90}$Zr at energy near
barrier are studied by this model. The experimental data of the fusion cross
sections for $^{40}$Ca+$^{90,96}$Zr at the energy near barrier can be
reproduced remarkably well without introducing any new parameters. The
mechanism for the enhancement of fusion probability for fusion reactions with
neutron-rich projectile or target is analyzed.


  This review of the book "The Challenge of Financial Stability: A New Model
and its Applications" by Goodhart C.A.E. and Tsomocos D.P. highlights the
potential of the framework of strategic partial default of banks with credit
chain on the interbank market for further theoretical and applied research on
financial stability.


  Bayesian maxent lets one integrate thermal physics and information theory
points of view in the quantitative study of complex systems. Since net
surprisal (a free energy analog for measuring "departures from expected")
allows one to place second law constraints on mutual information (a
multi-moment measure of correlations), it makes a quantitative case for the
role of reversible thermalization in the natural history of invention, and
suggests multiscale strategies to monitor standing crop as well. It prompts one
to track evolved complexity starting from live astrophysically-observed
processes, rather than only from evidence of past events. Various gradients and
boundaries that play a role in availability flow, ranging from the edge of a
wave-packet to the boundary between idea-pools, allow one to frame wide-ranging
correlations (including that between a phenomenon and its explanation) as
delocalized {\em physical} structures.


  In this paper, we investigate the existence of weak solution for a Kirchhoff
type problem driven by a nonlocal operator of elliptic type in a fractional
Orlicz-Sobolev space, with homogeneous Dirichlet boundary conditions
  {\small$$
  (D_{K,A}) \hspace*{0.5cm} \left\{
  \begin{array}{clclc}
  M\left( \displaystyle \int_{\R^{2N}}A\left( [u(x)-u(y)] K(x,y)\right)
dxdy\right) \mathcal{L}^K_A u & = & f(x,u) & \text{ in }& \Omega,
  \hspace*{7cm} u & = & 0 \hspace*{0.2cm} \hspace*{0.2cm} & \text{ in } &
\R^N\setminus \Omega.
  \label{eq1}
  \end{array}
  \right. $$ } Where $\mathcal{L}^K_A$ is a nonlocal operator with singular
kernel $K$ and $A$ is an $N$-function, $\Omega$ is an open bounded subset in
$\R^N$ with Lipschitz boundary $\partial \Omega$.


  Holistic 3D scene understanding entails estimation of both layout
configuration and object geometry in a 3D environment. Recent works have shown
advances in 3D scene estimation from various input modalities (e.g., images, 3D
scans), by leveraging 3D supervision (e.g., 3D bounding boxes or CAD models),
for which collection at scale is expensive and often intractable. To address
this shortcoming, we propose a new method to learn 3D scene priors of layout
and shape without requiring any 3D ground truth. Instead, we rely on 2D
supervision from multi-view RGB images. Our method represents a 3D scene as a
latent vector, from which we can progressively decode to a sequence of objects
characterized by their class categories, 3D bounding boxes, and meshes. With
our trained autoregressive decoder representing the scene prior, our method
facilitates many downstream applications, including scene synthesis,
interpolation, and single-view reconstruction. Experiments on 3D-FRONT and
ScanNet show that our method outperforms state of the art in single-view
reconstruction, and achieves state-of-the-art results in scene synthesis
against baselines which require for 3D supervision.


  We calculate the scattering lenths A(K-,3He) and A(K-,4He) using the multiple
scattering approach and different parameters sets for the elementary a(Kbar,N).
Within the zero-range approximation, we find for both systems loosely bound
states with binding energies in the range 2-7 MeV and widths 11-18 MeV. It is
demonstrated that the existence of deeply bound K-,4He states, which have been
predicted in literature, can be tested by measuring the reaction dd -> 4He K-K+
at COSY.


  We define Dirac pairs on Jacobi algebroids, which is a generalization of
Dirac pairs on Lie algebroids introduced by Kosmann-Schwarzbach. We show the
relationship between Dirac pairs on Lie and on Jacobi algebroids, and that
Dirac pairs on Jacobi algebroids characterize several compatible structures on
manifolds or on Jacobi algebroids.


  Compressing deep neural networks while maintaining accuracy is important when
we want to deploy large, powerful models in production and/or edge devices. One
common technique used to achieve this goal is knowledge distillation.
Typically, the output of a static pre-defined teacher (a large base network) is
used as soft labels to train and transfer information to a student (or smaller)
network. In this paper, we introduce Adjoined Networks, or AN, a learning
paradigm that trains both the original base network and the smaller compressed
network together. In our training approach, the parameters of the smaller
network are shared across both the base and the compressed networks. Using our
training paradigm, we can simultaneously compress (the student network) and
regularize (the teacher network) any architecture. In this paper, we focus on
popular CNN-based architectures used for computer vision tasks. We conduct an
extensive experimental evaluation of our training paradigm on various
large-scale datasets. Using ResNet-50 as the base network, AN achieves 71.8%
top-1 accuracy with only 1.8M parameters and 1.6 GFLOPs on the ImageNet
data-set. We further propose Differentiable Adjoined Networks (DAN), a training
paradigm that augments AN by using neural architecture search to jointly learn
both the width and the weights for each layer of the smaller network. DAN
achieves ResNet-50 level accuracy on ImageNet with $3.8\times$ fewer parameters
and $2.2\times$ fewer FLOPs.


  Earth Observation (EO) mining aims at supporting efficient access and
exploration of petabyte-scale space- and airborne remote sensing archives that
are currently expanding at rates of terabytes per day. A significant challenge
is performing the analysis required by envisaged applications --- like for
instance process mapping for environmental risk management --- in reasonable
time. In this work, we address the problem of content-based image retrieval via
example-based queries from EO data archives. In particular, we focus on the
analysis of polarimetric SAR data, for which target decomposition theorems have
proved fundamental in discovering patterns in data and characterize the ground
scattering properties. To this end, we propose an interactive region-oriented
content-based image mining system in which 1) unsupervised ingestion processes
are distributed onto virtual machines in elastic, on-demand computing
infrastructures 2) archive-scale content hierarchical indexing is implemented
in terms of a "big data" analytics cluster-computing framework 3) query
processing amounts to traversing the generated binary tree index, computing
distances that correspond to descriptor-based similarity measures between image
groups and a query image tile. We describe in depth both the strategies and the
actual implementations for the ingestion and indexing components, and verify
the approach by experiments carried out on the NASA/JPL UAVSAR full
polarimetric data archive. We report the results of the tests performed on
computer clusters by using a public Infrastructure-as-a-Service and evaluating
the impact of cluster configuration on system performance. Results are
promising for data mapping and information retrieval applications.


  The paper aims to point out a novel geometric characterisation of the WDVV
equations of 2D topological field theory.


  We investigate superfield formulation of the minimal
$\mathbb{Z}_2^2$-supersymmetry. It is shown that the integrability on
$\mathbb{Z}_2^2$-superspace guarantees the invariance of action. Then we
present two superfields which carry distinct irreducible representations of the
$\mathbb{Z}_2^2$-supersymmetry algebra. One of them gives integrable Lagrangian
and the other does not. We also show that integrable superfields with different
$\mathbb{Z}_2^2$-degree also carry irreducible representations and they give
invariant actions. To perform this analysis, the representation theory of the
minimal $\mathbb{Z}_2^2$-supersymmetry algebra is studied in some detail.


  We discuss the evolution of the eight leading twist transverse momentum
dependent parton distribution functions, which turns out to be universal and
spin independent. By using the highest order perturbatively calculable
ingredients at our disposal, we perform the resummation of the large logarithms
that appear in the evolution kernel of transverse momentum distributions up to
next-to-next-to-leading logarithms (NNLL), thus obtaining an expression for the
kernel with highly reduced model dependence. Our results can also be obtained
using the standard CSS approach when a particular choice of the $b^*$
prescription is used. In this sense, and while restricted to the perturbative
domain of applicability, we consider our results as a "prediction" of the
correct value of $b_{\rm max}$ which is very close to $1.5 {\rm GeV}^{-1}$. We
explore under which kinematical conditions the effects of the non-perturbative
region are negligible, and hence the evolution of transverse momentum
distributions can be applied in a model independent way. The application of the
kernel is illustrated by considering the unpolarized transverse momentum
dependent parton distribution function and the Sivers function.


  This article concerns the time growth of Sobolev norms of classical solutions
to the 3D incompressible isotropic elastodynamics with small initial
displacements.


  GdN is a ferromagnetic semiconductor which has seen increasing interest in
the preceding decades particularly in the areas of spin- and superconducting-
based electronics. Here we report a detailed computational study and optical
spectroscopy study of the electronic structure of stoichiometric and nitrogen
vacancy doped GdN. Based on our calculations we provide the effective mass
tensor for undoped GdN, and some indicative values for electron doped GdN. Such
a property is valuable as it can directly affect device design, and be directly
measured experimentally to validate the existing computation results.


  Given smooth manifolds $M$ and $N$, manifold calculus studies the space of
embeddings $\operatorname{Emb}(M,N)$ via the "embedding tower", which is
constructed using the homotopy theory of presheaves on $M$. The same theory
allows us to study the stable homotopy type of $\operatorname{Emb}(M,N)$ via
the "stable embedding tower". By analyzing cubes of framed configuration
spaces, we prove that the layers of the stable embedding tower are tangential
homotopy invariants of $N$.
  If $M$ is framed, the moduli space of disks $E_M$ is intimately connected to
both the stable and unstable embedding towers through the $E_n$ operad. The
action of $E_n$ on $E_M$ induces an action of the Poisson operad
$\mathrm{pois}_n$ on the homology of configuration spaces $H_*(F(M,-))$.
  In order to study this action, we introduce the notion of Poincare-Koszul
operads and modules and show that $E_n$ and $E_M$ are examples. As an
application, we compute the induced action of the Lie operad on $H_*(F(M,-))$
and show it is a homotopy invariant of $M^+$.


  This article reports a measurement of the proper motion of Leo II, a dwarf
galaxy that is a likely satellite of the Milky Way, based on imaging with the
Hubble Space Telescope and Wide Field Camera 3. The measurement uses compact
background galaxies as standards of rest in both channels of the camera for two
distinct pointings of the telescope and a QSO in one channel for each pointing,
resulting in the weighted average of six measurements. The measured proper
motion in the the equatorial coordinate system is (mu_alpha, mu_delta) = (-6.9
+- 3.7, -8.7 +- 3.9) mas/century and in the Galactic coordinate system is
(mu_l, mu_b) = (6.2 +- 3.9, -9.2 +- 3.7) mas/century. The implied space
velocity with respect to the Galactic center is (Pi, Theta, Z) = (-37 +- 38,
117 +- 43, 40 +- 16) km/s or, expressed in Galactocentric radial and tangential
components, (V_r, V_tan) = (21.9 +- 1.5, 127 +- 42) km/s. The space velocity
implies that the instantaneous orbital inclination is 68 degrees, with a 95%
confidence interval of (66 deg, 80 deg). The measured motion supports the
hypothesis that Leo II, Leo IV, Leo V, Crater 2, and the globular cluster
Crater fell into the Milky Way as a group.


  Based on the result in our previous work, we calculate the polarization of
quarks from parton scatterings in high energy heavy ion collisions. The result
is compared with the STAR data at $\sqrt{s_{NN}}=200$ GeV.


  For each adjointable idempotent $Q$ on a Hilbert $C^*$-module $H$, a specific
projection $m(Q)$ called the matched projection of $Q$ was introduced recently
due to the characterization of the minimum value among all the distances from
projections to $Q$. Inspired by the relationship between $m(Q)$ and $Q$,
another term called the quasi-projection pair $(P,Q)$ was also introduced
recently, where $P$ is a projection on $H$ satisfying $Q^*=(2P-I)Q(2P-I)$, in
which $Q^*$ is the adjoint operator of the idempotent $Q$ and $I$ is the
identity operator on $H$. Some fundamental issues on quasi-projection pairs,
such as the block matrix representations for quasi-projection pairs and the
$C^*$-morphisms associated with quasi-projection pairs, are worthwhile to be
investigated. This paper aims to make some detailed preparations. Two objects
called the semi-harmonious quasi-projection pair and the harmonious
quasi-projection pair are introduced and are systematically studied in the
general setting of the adjointable operators on Hilbert $C^*$-modules. Some
applications concerning the common similarity of operators and a norm equation
associated with the Friedrichs angle are also dealt with. Furthermore, many
examples are provided to illustrate the non-triviality of the associated
characterizations.


  The density functional approach is used to study the gas-to-liquid and
liquid-to-gas nucleation phenomena in a fluid of two-level atoms in an external
electrical field. The influence of the field on the surface tension and
nucleation and cavitation barriers is discussed.


  The cross-media retrieval problem has received much attention in recent years
due to the rapid increasing of multimedia data on the Internet. A new approach
to the problem has been raised which intends to match features of different
modalities directly. In this research, there are two critical issues: how to
get rid of the heterogeneity between different modalities and how to match the
cross-modal features of different dimensions. Recently metric learning methods
show a good capability in learning a distance metric to explore the
relationship between data points. However, the traditional metric learning
algorithms only focus on single-modal features, which suffer difficulties in
addressing the cross-modal features of different dimensions. In this paper, we
propose a cross-modal similarity learning algorithm for the cross-modal feature
matching. The proposed method takes a bilinear formulation, and with the
nuclear-norm penalization, it achieves low-rank representation. Accordingly,
the accelerated proximal gradient algorithm is successfully imported to find
the optimal solution with a fast convergence rate O(1/t^2). Experiments on
three well known image-text cross-media retrieval databases show that the
proposed method achieves the best performance compared to the state-of-the-art
algorithms.


  Active regions (ARs) are typical magnetic structures found in the solar
atmosphere. We calculate several magnetohydrostatic (MHS) equilibrium models
that include the effect of a finite plasma-$\beta$ and gravity and that are
representative of these structures in three dimensions. The construction of the
models is based on the use of two Euler potentials, $\alpha$ and $\beta$, that
represent the magnetic field as ${\bf B}=\nabla \alpha \times \nabla \beta$.
The ideal MHS nonlinear partial differential equations are solved numerically
using finite elements in a fixed 3D rectangular domain. The boundary conditions
are initially chosen to correspond to a potential magnetic field (current-free)
with known analytical expressions for the corresponding Euler potentials. The
distinctive feature is that we incorporate the effect of shear by progressively
deforming the initial potential magnetic field. This procedure is quite generic
and allows us to generate a vast variety of MHS models. The thermal structure
of the ARs is incorporated through the dependence of gas pressure and
temperature on the Euler potentials. Using this method we achieve the
characteristic hot and over-dense plasma found in ARs, but we demonstrate that
the method can also be applied to study configurations with open magnetic field
lines. Furthermore, we investigate basic topologies that include neutral lines.
Our focus is on the force balance of the structures and we do not consider the
energy balance in the constructed models. In addition, we address the difficult
question of the stability of the calculated 3D models. We find that if the
plasma is convectively stable, then the system is not prone in general to
develop magnetic Rayleigh-Taylor instabilities.


  We give some discussions to the relations between canonical left cells and
the lowest two-sided cell of an affine Weyl group. In particular, we use the
relations to construct irreducible modules attached to the lowest two-sided
cell and some one dimensional representations of an affine Hecke algebra.


  We prove a sufficient condition for the vanishing of the modified diagonal
cycle in the Chow group (with $\mathbb{Q}$-coefficients) of the triple product
of a curve over $\mathbb{C}$. We exhibit infinitely many non-hyperelliptic
curves, including the Fricke--Macbeath curve, the Bring curve, and two
1-dimensional families parameterized by certain Hurwitz spaces, for which our
condition is satisfied.


  Whether a file is accepted by a single parser is not a reliable indication of
whether a file complies with its stated format. Bugs within both the parser and
the format specification mean that a compliant file may fail to parse, or that
a non-compliant file might be read without any apparent trouble. The latter
situation presents a significant security risk, and should be avoided. This
article suggests that a better way to assess format specification compliance is
to examine the set of error messages produced by a set of parsers rather than a
single parser. If both a sample of compliant files and a sample of
non-compliant files are available, then we show how a statistical test based on
a pseudo-likelihood ratio can be very effective at determining a file's
compliance. Our method is format agnostic, and does not directly rely upon a
formal specification of the format. Although this article focuses upon the case
of the PDF format (ISO 32000-2), we make no attempt to use any specific details
of the format. Furthermore, we show how principal components analysis can be
useful for a format specification designer to assess the quality and structure
of these samples of files and parsers. While these tests are absolutely
rudimentary, it appears that their use to measure file format variability and
to identify non-compliant files is both novel and surprisingly effective.


  The presentation is concerned with higher twist corrections of nonpartonic
origin to semi-inclusive observables in the kinematical region relevant for the
HERMES experiment. We demonstrate a strong impact of the VDM-like interaction
and the exclusive production of $\rho^0$ meson on the extraction of the $\bar d
- \bar u$ asymmetry from charged pion DIS multiplicities. We also show that it
is the exclusive-$\rho^0$ channel which accounts for the experimentally
observed effect of the excess of charged over neutral pions produced at large
$z$.


  Within the mode-coupling theory (MCT) for glassy dynamics, the asymptotic
low-frequency expansions for the dynamical susceptibilities at critical points
are compared to the expansions for the dynamic moduli; this shows that the
convergence properties of the two expansions can be quite different. In some
parameter regions, the leading-order expansion formula for the modulus
describes the solutions of the MCT equations of motion outside the transient
regime successfully; at the same time, the leading- and next-to-leading order
expansion formulas for the susceptibility fail. In these cases, one can derive
a Cole-Cole law for the susceptibilities; and this law accounts for the
dynamics for frequencies below the band of microscopic excitations and above
the high-frequency part of the alpha-peak. It is shown that this scenario
explains the optical-Kerr-effect data measured for salol and benzophenone
(BZP). For BZP it is inferred that the depolarized light-scattering spectra
exhibit a wing for the alpha-peak within the Gigahertz band. This wing results
from the crossover of the von Schweidler-law part of the alpha-peak to the
high-frequency part of the Cole-Cole peak; and this crossover can be described
quantitatively by the leading-order formulas of MCT for the modulus.


  By defining a spatially varying replica overlap parameter for a supercooled
liquid referenced to an ensemble of fiducial liquid state configurations we
explicitly construct a constrained replica free energy functional that maps
directly onto an Ising Hamiltonian with both random fields and random
interactions whose statistics depend on liquid structure. Renormalization group
results for random magnets when combined with these statistics for the
Lennard-Jones glass suggest that discontinuous replica symmetry breaking would
occur if a liquid with short range interactions could be equilibrated at a
sufficiently low temperature where its mean field configurational entropy would
vanish, even though the system strictly retains a finite configurational
entropy.


  This paper proposes to maximize the accuracy of a distributed machine
learning (ML) model trained on learners connected via the resource-constrained
wireless edge. We jointly optimize the number of local/global updates and the
task size allocation to minimize the loss while taking into account
heterogeneous communication and computation capabilities of each learner. By
leveraging existing bounds on the difference between the training loss at any
given iteration and the theoretically optimal loss, we derive an expression for
the objective function in terms of the number of local updates. The resulting
convex program is solved to obtain the optimal number of local updates which is
used to obtain the total updates and batch sizes for each learner. The merits
of the proposed solution, which is heterogeneity aware (HA), are exhibited by
comparing its performance to the heterogeneity unaware (HU) approach.


  Very recent experiments have reported the tunneling between Yu-Shiba-Rusinov
(YSR) bound states at the atomic scale. These experiments have been realized
with the help of a scanning tunneling microscope where a superconducting tip is
functionalized with a magnetic impurity and is used to probe another magnetic
impurity deposited on a superconducting substrate. In this way it has become
possible to study for the first time the spin-dependent transport between
individual superconducting bound states. Motivated by these experiments, we
present here a comprehensive theoretical study of the tunneling processes
between YSR bound states in a system in which two magnetic impurities are
coupled to superconducting leads. Our theory is based on a combination of an
Anderson model with broken spin degeneracy to describe the impurities and
nonequilibrium Green's function techniques to compute the current-voltage
characteristics. This combination allows us to describe the spin-dependent
transport for an arbitrary strength of the tunnel coupling between the
impurities. We first focus on the tunnel regime and show that our theory
naturally explains the experimental observations of the appearance of current
peaks in the subgap region due to both the direct and thermal tunneling between
the YSR states in both impurities. Then, we study in detail the case of
junctions with increasing transparency, which has not been experimentally
explored yet, and predict the occurrence of a large variety of (multiple)
Andreev reflections mediated by YSR states that give rise to a very rich
structure in the subgap current. In particular, we predict the occurrence of
multiple Andreev reflections that involve YSR states in different impurities.
These processes have no analogue in single-impurity junctions and they are
manifested as current peaks with negative differential conductance for subgap
voltages.


  Quadrilateral layouts on surfaces are valuable in texture mapping, and
essential in generation of quadrilateral meshes and in fitting splines.
Previous work has characterized such layouts as a special metric on a surface
or as a meromorphic quartic differential with finite trajectories. In this
work, a surface quadrilateral layout is alternatively characterized as a
special immersion of a cut representation of the surface into the Euclidean
plane. We call this a quad layout immersion. This characterization, while posed
in smooth topology, naturally generalizes to piecewise-linear representations.
As such, it mathematically describes and generalizes integer grid maps, which
are common in computer graphics settings. Finally, the utility of the
representation is demonstrated by computationally extracting quadrilateral
layouts on surfaces of interest.


  This research continues to focus on the idea using cyclotronic antineutrino
source for purposes of neutrino physics. Long baseline experiments suffer from
degeneracies and correlations between $\Theta_{23}$, $\delta_{\rm CP}$ and the
mass hierarchy (MH). However the combination of a superconductive cyclotron and
a big liquid scintillator detector like JUNO in a medium baseline experiment,
which does not depend on the MH, may allow us to determine whether the position
of the mixing angle $\Theta_{23}$ is in the lower octant (LO) or upper octant
(UO). Such an experiment would improve the precision of the $\Theta_{23}$
measurement to a degree which depends on the CP-phase.


  We study, within the Ginzburg-Landau (GL) theory of phase transitions, how
elastic deformations in a supersolid lead to local changes in the supersolid
transition temperature. The GL theory is mapped onto a Schrodinger-type
equation with an effective potential that depends on local dilatory strain. The
effective potential is attractive for local contractions and repulsive for
local expansion. Different types of elastic deformations are studied. We find
that a contraction (expansion) of the medium that may be brought about by,
e.g., applied stress leads to a higher (lower) transition temperature as
compared to the unstrained medium. In addition, we investigate edge
dislocations and illustrate that the local transition temperature may be
increased in the immediate vicinity of the dislocation core. Our analysis is
not limited to supersolidity. Similar strain effects should also play a role in
superconductors.


  Forty years after their discovery, and in spite of a very large body of
observations, the operation of the 'engine' responsible for long-duration
Gamma-Ray Bursts (GRBs) and X-ray flashes --as well as the mechanisms
generating their radiation-- are still the subject of debate and study. In this
respect a recent event, XRF 060218, associated with SN 2006aj, is particularly
significant. It has been argued that, for the first time, the break-out of the
shock involved in the supernova explosion has been observed, thanks to the
detection of a thermal component in the event's radiation; that this XRF was
not a GRB seen 'off-axis', but a member of a new class of energetically feeble
GRBs; and that its 'continued engine activity' may have been driven by a
remnant highly-magnetized neutron star, a magnetar. I argue, on grounds based
on observations and on limpid verified hypothesis, that there is a common,
simpler alternative to these views, with no thermal component, no new feeble
GRBs, and no steady engine activity.


  We explore AdS/CFT correspondence between geodesic Witten diagrams and
conformal blocks (conformal partial waves) with an external symmetric traceless
tensor field. We derive an expression for the conformal partial wave with an
external spin-1 field and show that this expression is equivalent to the
amplitude of the geodesic Witten diagram. We also show the equivalence by using
conformal Casimir equation in embedding formalism. Furthermore, we extend the
construction of the amplitude of the geodesic Witten diagram to an external
arbitrary symmetric traceless tensor field. We show our construction agrees
with the known result of the conformal partial waves.


  Coriolis effect is an important error source in the weak equivalence
principle (WEP) test using atom interferometer. In this paper, the problem of
Coriolis error in WEP test is studied theoretically and experimentally. In
theoretical simulation, Coriolis effect is analyzed by establishing an error
model. The measurement errors of Eotvos coefficient (eta) in WEP test related
to experimental parameters, such as horizontal-velocity difference and
horizontal-position difference of atomic clouds, horizontal-position difference
of detectors and rotation compensation of Raman laser's mirror are calculated.
In experimental investigation, the position difference between Rb-85 and Rb-87
atomic clouds is reduced to 0.1 mm by optimizing the experimental parameters,
an alternating detection method is used to suppress the error caused by
detection position difference, thus the Coriolis error related to atomic clouds
and detectors is eliminated to 1.1E-9. This Coriolis error is further corrected
by compensating the rotation of Raman laser's mirror, and the total uncertainty
of eta measurement related to Coriolis effect is reduced as 4.4E-11.


  We review the recent developements in the stability problem and phase diagram
for asymptotically locally $AdS$ black strings. First, we quickly review the
case of locally flat black string before turning to the case of locally $AdS$
spacetimes.


  Symmetry-induced vortex-antivortex configurations in superconducting squares
and triangles were predicted earlier; yet, they have not been resolved in
experiment up to date. Namely, with vortex-antivortex states being highly
unstable with respect to defects and temperature fluctuations, it is very
unlikely that samples can be fabricated with the needed quality. Here we show
how these drawbacks can be overcome by strategically placed nanoholes in the
sample. As a result, (i) the actual shape of the sample becomes far less
important, (ii) the stability of the vortex-antivortex configurations in
general is substantially enhanced, and (iii) states comprising novel
giant-antivortices (with higher winding numbers) become energetically favorable
in perforated disks. In the analysis, we stress the potent of strong screening
to destabilize the vortex-antivortex states. In turn, the screening-symmetry
competition favors stabilization of new asymmetric ground states, which arise
for small values of the effective Ginzburg-Landau parameter kappa.


  Fine-grained financial sentiment analysis on news headlines is a challenging
task requiring human-annotated datasets to achieve high performance. Limited
studies have tried to address the sentiment extraction task in a setting where
multiple entities are present in a news headline. In an effort to further
research in this area, we make publicly available SEntFiN 1.0, a
human-annotated dataset of 10,753 news headlines with entity-sentiment
annotations, of which 2,847 headlines contain multiple entities, often with
conflicting sentiments. We augment our dataset with a database of over 1,000
financial entities and their various representations in news media amounting to
over 5,000 phrases. We propose a framework that enables the extraction of
entity-relevant sentiments using a feature-based approach rather than an
expression-based approach. For sentiment extraction, we utilize 12 different
learning schemes utilizing lexicon-based and pre-trained sentence
representations and five classification approaches. Our experiments indicate
that lexicon-based n-gram ensembles are above par with pre-trained word
embedding schemes such as GloVe. Overall, RoBERTa and finBERT (domain-specific
BERT) achieve the highest average accuracy of 94.29% and F1-score of 93.27%.
Further, using over 210,000 entity-sentiment predictions, we validate the
economic effect of sentiments on aggregate market movements over a long
duration.


  An explicit form of the generators of quantum and ordinary semisimple
algebras for an arbitrary finite-dimensional representation is found. The
generators corresponding to the simple roots are obtained in terms of a
solution of a system of matrix equations. The result is presented in the form
of $N_l\times N_l$ matrices, where $N_l$ is the dimension of the corresponding
representation, determined by the invariant Weyl formula.


  Based on experimental evidences supporting the hypothesis that neutrinos
might be tachyonic fermions, a new Dirac-type equation is proposed and a
spin-1/2 tachyonic quantum theory is developed. The new Dirac-type equation
provides a solution for the puzzle of negative mass-square of neutrinos. This
equation can be written in two spinor equations coupled together via nonzero
mass while respecting the maximum parity violation, and it reduces to one Weyl
equation in the massless limit. Some peculiar features of tachyonic neutrino
are discussed in this theoretical framework.


  By drilling periodic thru-holes in a suspended film, the phonon system can be
modified. Being motivated by the BCS theory, the technique, so-called phonon
engineering, was applied to a niobium sheet. The newly emergent high-$T_{c}$
superconductivity, however, cannot be accounted for by the BCS theory. Rather,
its exposed configuration, namely a square-lattice oxygen network, is
reminiscent of the copper-oxygen plane in cuprate high-$T_c$ superconductors.
It turns out that its magnetic result is consistent with the principle of giant
atom, which was developed by another heroes of superconductivity, Fritz London
and John Slater, in the 1930s, several decades earlier than the propagation of
BCS theory. The superconducting transition feature is discussed on the basis of
a comprehensive theory of the giant atom -- the theory of hole
superconductivity.


  We furnish any category of a universal (co)homology theory. Universal
(co)homologies and universal relative (co)homologies are obtained by showing
representability of certain functors and take values in $R$-linear abelian
categories of motivic nature, where $R$ is any commutative unitary ring.
Universal homology theory on the one point category yields "hieratic"
$R$-modules, i.e. the indization of Freyd's free abelian category on $R$.
Grothendieck $\partial$-functors and satellite functors are recovered as
certain additive relative homologies on an abelian category for which we also
show the existence of universal ones.


  Emotional Voice Conversion (EVC) aims to convert the emotional style of a
source speech signal to a target style while preserving its content and speaker
identity information. Previous emotional conversion studies do not disentangle
emotional information from emotion-independent information that should be
preserved, thus transforming it all in a monolithic manner and generating audio
of low quality, with linguistic distortions. To address this distortion
problem, we propose a novel StarGAN framework along with a two-stage training
process that separates emotional features from those independent of emotion by
using an autoencoder with two encoders as the generator of the Generative
Adversarial Network (GAN). The proposed model achieves favourable results in
both the objective evaluation and the subjective evaluation in terms of
distortion, which reveals that the proposed model can effectively reduce
distortion. Furthermore, in data augmentation experiments for end-to-end speech
emotion recognition, the proposed StarGAN model achieves an increase of 2% in
Micro-F1 and 5% in Macro-F1 compared to the baseline StarGAN model, which
indicates that the proposed model is more valuable for data augmentation.


  Robotic exploration under uncertain environments is challenging when optical
information is not available. In this paper, we propose an autonomous solution
of exploring an unknown task space based on tactile sensing alone. We first
designed a whisker sensor based on MEMS barometer devices. This sensor can
acquire contact information by interacting with the environment
non-intrusively. This sensor is accompanied by a planning technique to generate
exploration trajectories by using mere tactile perception. This technique
relies on a hybrid policy for tactile exploration, which includes a proactive
informative path planner for object searching, and a reactive Hopf oscillator
for contour tracing. Results indicate that the hybrid exploration policy can
increase the efficiency of object discovery. Last, scene understanding was
facilitated by segmenting objects and classification. A classifier was
developed to recognize the object categories based on the geometric features
collected by the whisker sensor. Such an approach demonstrates the whisker
sensor, together with the tactile intelligence, can provide sufficiently
discriminative features to distinguish objects.


  A flow approach to community detection in complex network and multilayer
network systems is proposed. Two methods have been developed to search for
communities in a network system (NS). The first of them is based on the
calculation of flow influence parameters of NS's subsystems, selected according
to the principle of nesting hierarchy. The second method uses the concept of
flow core of network system. Two methods are also proposed for community
detection in multilayer network system (MLNS). The first of them is based on
the concept of MLNS aggregate-network and subsequent allocation of its flow
core. The second method uses the concept of flow core of the process of
intersystem interactions in general. All developed methods are based on the use
of flow criterion that the selected group of nodes really forms a community.
The results of application of developed approaches are illustrated by examples
for which known methods are ineffective.


  Large language models (LLMs) have emerged as a promising alternative to
expensive human evaluations. However, the alignment and coverage of LLM-based
evaluations are often limited by the scope and potential bias of the evaluation
prompts and criteria. To address this challenge, we propose HD-Eval, a novel
framework that iteratively aligns LLM-based evaluators with human preference
via Hierarchical Criteria Decomposition. HD-Eval inherits the essence from the
evaluation mindset of human experts and enhances the alignment of LLM-based
evaluators by decomposing a given evaluation task into finer-grained criteria,
aggregating them according to estimated human preferences, pruning
insignificant criteria with attribution, and further decomposing significant
criteria. By integrating these steps within an iterative alignment training
process, we obtain a hierarchical decomposition of criteria that
comprehensively captures aspects of natural language at multiple levels of
granularity. Implemented as a white box, the human preference-guided aggregator
is efficient to train and more explainable than relying solely on prompting,
and its independence from model parameters makes it applicable to closed-source
LLMs. Extensive experiments on three evaluation domains demonstrate the
superiority of HD-Eval in further aligning state-of-the-art evaluators and
providing deeper insights into the explanation of evaluation results and the
task itself.


  Mode surfaces are the generalization of degenerate curves and neutral
surfaces, which constitute 3D symmetric tensor field topology. Efficient
analysis and visualization of mode surfaces can provide additional insight into
not only degenerate curves and neutral surfaces, but also how these features
transition into each other. Moreover, the geometry and topology of mode
surfaces can help domain scientists better understand the tensor fields in
their applications. Existing mode surface extraction methods can miss features
in the surfaces. Moreover, the mode surfaces extracted from neighboring cells
have gaps, which make their subsequent analysis difficult. In this paper, we
provide novel analysis on the topological structures of mode surfaces,
including a common parameterization of all mode surfaces of a tensor field
using 2D asymmetric tensors. This allows us to not only better understand the
structures in mode surfaces and their interactions with degenerate curves and
neutral surfaces, but also develop an efficient algorithm to seamlessly extract
mode surfaces, including neutral surfaces. The seamless mode surfaces enable
efficient analysis of their geometric structures, such as the principal
curvature directions. We apply our analysis and visualization to a number of
solid mechanics data sets.


  We compare the performances of symplectic and non-symplectic integrators for
the computation of normal geodesics and conjugate points in sub-Riemannian
geometry at the example of the Martinet case. For this case study we consider
first the flat metric, and then a one parameter perturbation leading to non
integrable geodesics. From our computations we deduce that near the abnormal
directions a symplectic method is much more efficient for this optimal control
problem. The explanation relies on the theory of backward error analysis in
geometric numerical integration.


  We prove that the periodic initial value problem for the modified
Hunter-Saxton equation is locally well-posed for continuously differentiable
initial data. We also study the analytic regularity of this problem and prove a
Cauchy-Kowalevski type theorem.


  We present improved point-source catalogs for the 2 Ms Chandra Deep
Field-North (CDF-N) and the 250 ks Extended Chandra Deep Field-South (E-CDF-S),
implementing a number of recent improvements in Chandra source-cataloging
methodology. For the CDF-N/E-CDF-S, we provide a main catalog that contains
683/1003 X-ray sources detected with wavdetect at a false-positive probability
threshold of $10^{-5}$ that also satisfy a binomial-probability
source-selection criterion of $P<0.004$/$P<0.002$. Such an approach maximizes
the number of reliable sources detected: a total of 196/275 main-catalog
sources are new compared to the Alexander et al. (2003) CDF-N/Lehmer et al.
(2005) E-CDF-S main catalogs. We also provide CDF-N/E-CDF-S supplementary
catalogs that consist of 72/56 sources detected at the same wavdetect threshold
and having $P$ of $0.004-0.1$/$0.002-0.1$ and $K_s\le22.9/K_s\le22.3$ mag
counterparts. For all $\approx1800$ CDF-N and E-CDF-S sources, including the
$\approx500$ newly detected ones (these being generally fainter and more
obscured), we determine X-ray source positions utilizing centroid and
matched-filter techniques; we also provide multiwavelength identifications,
apparent magnitudes of counterparts, spectroscopic and/or photometric
redshifts, basic source classifications, and estimates of observed AGN and
galaxy source densities around respective field centers. Simulations show that
both the CDF-N and E-CDF-S main catalogs are highly reliable and reasonably
complete. Background and sensitivity analyses indicate that the on-axis mean
flux limits reached represent a factor of $\approx1.5-2.0$ improvement over the
previous CDF-N and E-CDF-S limits. We make our data products publicly
available.


  Building on a previous proposal for the entanglement of electron-hole pairs
in the Fermi sea, we show how 3 qubits can be entangled without using
electron-electron interactions. As in the 2-qubit case, this electronic scheme
works even if the sources are in (local) thermal equilibrium -- in contrast to
the photonic analogue. The 3 qubits are represented by 4 edge-channel
excitations in the quantum Hall effect (2 hole excitations plus 2 electron
excitations with identical channel index). The entangler consists of an
adiabatic point contact flanked by a pair of tunneling point contacts. The
irreducible 3-qubit entanglement is characterized by the tangle, which is
expressed in terms of the transmission matrices of the tunneling point
contacts. The maximally entangled Greenberger-Horne-Zeilinger (GHZ) state is
obtained for channel-independent tunnel probabilities. We show how
low-frequency noise measurements can be used to determine an upper and lower
bound to the tangle. The bounds become tighter the closer the electron-hole
state is to the GHZ state.


  Probabilistic shaping is a pragmatic approach to improve the performance of
coherent optical fiber communication systems. In the nonlinear regime, the
advantages offered by probabilistic shaping might increase thanks to the
opportunity to obtain an additional nonlinear shaping gain. Unfortunately, the
optimization of conventional shaping techniques, such as probabilistic
amplitude shaping (PAS), yields a relevant nonlinear shaping gain only in
scenarios of limited practical interest. In this manuscript we use sequence
selection to investigate the potential, opportunities, and challenges offered
by probabilistic shaping for nonlinear channels. First, we show that ideal
sequence selection is able to provide up to 0.13 bit/s/Hz gain with respect to
PAS with an optimized blocklength. However, this additional gain is obtained
only if the selection metric accounts for the signs of the symbols: they must
be known to compute the selection metric, but there is no need to shape them.
Furthermore, we show that the selection depends in a non-critical way on the
symbol rate and link length: the sequences selected for a certain scenario
still provide a relevant gain if these are modified. Then, we analyze and
compare several practical implementations of sequence selection by taking into
account interaction with forward error correction (FEC) and complexity.
Overall, the single block and the multi block FEC-independent bit scrambling
are the best options, with a gain up to 0.08 bit/s/Hz. The main challenge and
limitation to their practical implementation remains the evaluation of the
metric, whose complexity is currently too high. Finally, we show that the
nonlinear shaping gain provided by sequence selection persists when carrier
phase recovery is included.


  We study the dynamics of a quantum two state system driven through an avoided
crossing under the influence of a super Ohmic environment, i.e. a longitudinal
as well as a transversal one. The crossing time window, in which relaxation
influences the dynamics, is centered around the avoided crossing. We determine
the dynamics and the Landau-Zener probability employing the numerical exact
quasi-adiabatic path integral. At weak coupling we show that the numerically
less demanding nonequilibrium Bloch equations provide an accurate description.
The crossing time depends strongly not only on the system-bath coupling
strength but also on the bath spectral cut-off frequency in contrast to the
situation in an Ohmic bath. Our results enable to design quantitative protocols
which drive quantum systems out of the influence range of relaxation.


  We discuss the radiative corrections to charged and neutral current
deep-inelastic neutrino--nucleon scattering in the minimal supersymmetric
standard model (MSSM). In particular, we study deviations, delta_R^nu(nu-bar),
from the Standard Model prediction for the ratios of neutral- to
charged-current cross sections, taking into account all sources for deviations
in the MSSM, i.e. different contributions from virtual Higgs bosons and virtual
superpartners. Our calculation includes the full q^2 dependence of the one-loop
amplitudes, parton distribution functions and a NuTeV-inspired process
kinematics. We present results of a scan of delta_R^nu(nu-bar) over the
relevant MSSM parameter space.


  Blazars, a class of active galaxies whose jets are relativistic and
collimated flows of plasma directed along the line of sight and are prone to a
slew of magneto-hydrodynamic (MHD) instabilities. We aim to study the interplay
of radiation and particle acceleration processes in regulating the multi-band
emission and variability signatures from blazars. In particular, the goal is to
decipher the impact of shocks arising due to MHD instabilities in driving the
longterm variable emission signatures from blazars. In this regard, we have
performed RMHD simulations of a representative section of blazar jet. The jet
is evolved using a hybrid Eulerian-Lagrangian framework to account for
radiative losses due to synchrotron process and particle acceleration due to
shocks. Additionally, we have incorporated and validated radiative losses due
to the external Compton (EC) process that are relevant for blazars. We have
further compared the effects of different radiation mechanisms through
numerical simulation of 2D slab jet as a validation test. Finally, we have
carried out a parametric study to quantify the effect of magnetic fields and
external radiation field characteristics by performing 3D simulations of a
plasma column. The synthetic light curves and spectral energy distribution
(SEDs) are analysed to qualitatively understand the impact of instability
driven shocks. We observe that shocks produced with the evolution of
instabilities give rise to flaring signatures in the high energy band. The
impact of such shocks is also evident from the instantaneous flattening of the
synchrotron component of the SEDs. At later stages, we observe the transition
in X-ray emission from the synchrotron process to that dominated by EC. The
inclusion of the EC process also gives rise to gamma-ray emission and shows
signatures of mild Compton dominance as typically seen in Low Synchrotron
Peaked blazars.


  It is of increasing importance to develop learning methods for ranking. In
contrast to many learning objectives, however, the ranking problem presents
difficulties due to the fact that the space of permutations is not smooth. In
this paper, we examine the class of rank-linear objective functions, which
includes popular metrics such as precision and discounted cumulative gain. In
particular, we observe that expectations of these gains are completely
characterized by the marginals of the corresponding distribution over
permutation matrices. Thus, the expectations of rank-linear objectives can
always be described through locations in the Birkhoff polytope, i.e.,
doubly-stochastic matrices (DSMs). We propose a technique for learning
DSM-based ranking functions using an iterative projection operator known as
Sinkhorn normalization. Gradients of this operator can be computed via
backpropagation, resulting in an algorithm we call Sinkhorn propagation, or
SinkProp. This approach can be combined with a wide range of gradient-based
approaches to rank learning. We demonstrate the utility of SinkProp on several
information retrieval data sets.


  In reply to hep-ph/0701204 we demonstrate why the arguments made therein do
not address the criticism exposed in hep-ph/0607246 on the fundamental
shortcomings of the Bayesian approach when it comes to the extraction of
parameters of Nature from experimental data. As for the isospin analysis and
the CKM angle alpha it is shown that the use of uniform priors for the observed
quantities in the Explicit Solution parametrization is equivalent to a
frequentist construction resulting from a change of variables, and thus relies
neither on prior PDFs nor on Bayes' theorem. This procedure provides in this
particular case results that are similar to the Confidence Level approach, but
the treatment of mirror solutions remains incorrect and it is far from being
general. In a second part it is shown that important differences subsist
between the Bayesian and frequentist approaches, when following the proposal of
hep-ph/0701204 and inserting additional information on the hadronic amplitudes
beyond isospin invariance. In particular the frequentist result preserves the
exact degeneracy that is expected from the remaining symmetries of the problem
while the Bayesian procedure does not. Moreover, in the Bayesian approach
reducing inference to the 68% or 95% credible interval is a misconception of
the meaning of the posterior PDF, which in turn implies that the significant
dependence of the latter to the chosen parametrization cannot be viewed as a
minor effect, contrary to the claim in hep-ph/0701204.


  Sensitivity of future far infrared 10m class space telescopes will be limited
by a confusion noise created by distant galaxies. Our primary goal is to create
a model that will allow us to estimate the confusion noise parameters of the
Millimetron mission. We construct a model of the Cosmic Infrared Background
(CIB) aimed at exploring the methods of prediction and reduction of the
confusion noise. The model is based on the publicly available eGALICS
simulation. For each simulated galaxy we construct a spectral energy
distribution with the help of the GRASIL code. To put our model in the context
of the current CIB investigations, we compare the outputs of the model with the
available observational data and with three other models. One is a well known
"backwards evolution" model of Bethermin et al. 2011 and two others are based
on a simple mass-luminosity (M-L) relation applied to simulated dark matter
halo catalogs. We conclude that our model reproduces the observational data
reasonably well. All four models show significant differences in the
predictions of the distribution of sources on the flux-redshift plane,
especially at high redshifts. We give estimations of the confusion noise based
on number counts (source density criterion, probability of deflection criterion
etc.) and based on the analysis of the simulated maps. We show that resolution
effects influence the number counts curves and noise estimations.


  Inferring parameters related to the aggregation pattern of parasites and to
their dispersal propensity is important for predicting their ecological
consequences and evolutionary potential. Nonetheless, it is notoriously
difficult to infer these parameters from wildlife parasites given the
difficulty in tracking these organisms. Molecular-based inferences constitute a
promising approach that has yet rarely been applied in the wild.Here, we
combinedseveral population genetic analyses including sibship reconstruction to
documentthe genetic structure, patterns of sibship aggregation and the
dispersal dynamics of a non-native parasite of fish, the freshwater copepod
ectoparasiteTracheliastespolycolpus. We collected parasites according to a
hierarchical sampling design,withthe sampling of all parasites from all host
individualscapturedineight sites spread along an upstream-downstream river
gradient. Individual multilocus genotypes were obtained from 14 microsatellite
markers, and used to assign parasites to full-sib families and to investigate
the genetic structure of T.polycolpus among both hosts and sampling sites. The
distribution of full-sibs obtainedamong the sampling sites was used to estimate
individual dispersal distances within families. Our results showed that T.
polycolpus sibs tend to be aggregated within sites but not withinhost
individuals. We detected important upstream-to-downstream dispersal events of
T.polycolpusbetween sites (modal distance: 25.4 km; 95% CI [22.9, 27.7]),
becoming scarcer as the geographic distance from their family core location
increases. Such a dispersal pattern likely contributes to the strong
isolation-by-distance observed at the river scale. We also detected some
downstream-to-upstream dispersal events (modal distance: 2.6 km; 95% CI
[2.2-23.3]) that likely result from movementsof infected hosts.Within each
site, the dispersal of free-living infective larvae among hosts likely
contributes to increasing genetic diversity on hosts, possibly fostering the
evolutionary potential of T. polycolpus.


  We propose a general frame work for deriving the OPEs within a logarithmic
conformal field theory (LCFT). This naturally leads to the emergence of a
logarithmic partner of the energy momentum tensor within an LCFT, and implies
that the current algebra associated with an LCFT is expanded. We derive this
algebra for a generic LCFT and discuss some of its implications. We observe
that two constants arise in the OPE of the energy-momentum tensor with itself.
One of these is the usual central charge.


  We derive analytical results for the large-time relaxation of the Sherrington
- Kirkpatrick model in the thermodynamic limit, starting from a random
configuration. The system never achieves local equilibrium in any fixed sector
of phase-space, but remains in an asymptotic out of equilibrium regime. We
propose as a tool, both numerical and analytical, for the study of the out of
equilibrium dynamics of spin-glass models the use of `triangle relations' which
describe the geometry of the configurations at three (long) different times.


  The Schwinger model describes quantum electrodynamics in 1+1-dimensions, it
is a prototype for quantum chromodynamics, and its lattice version allows for a
quantum link model description that can be simulated using modern quantum
devices. In this work, we devise quantum simulations to investigate the
dynamics of this model in its low dimensional form, where the gauge field
degrees of freedom are described by spin 1/2 operators. We apply trotterization
to write quantum circuits that effectively generate the evolution under the
Schwinger model Hamiltonian. We consider both sequential circuits, with a fixed
gate sequence, and randomized ones. Utilizing the correspondence between the
Schwinger model and the PXP model, known for its quantum scars, we investigate
the presence of quantum scar states in the Schwinger model by identifying
states exhibiting extended thermalization times in our circuit evolutions. Our
comparison of sequential and randomized circuit dynamics shows that the
non-thermal sector of the Hilbert space, including the scars, are more
sensitive to randomization.


  The turbulent boundary layer over a Gaussian shaped bump is computed by
direct numerical simulation (DNS) of the incompressible Navier-Stokes
equations. The two-dimensional bump causes a series of strong pressure
gradients alternating in rapid succession. At the inflow, the momentum
thickness Reynolds number is approximately 1,000 and the boundary layer
thickness is 1/8 of the bump height. DNS results show that the strong favorable
pressure gradient (FPG) causes the boundary layer to enter a relaminarization
process. The near-wall turbulence is significantly weakened and becomes
intermittent, however relaminarization does not complete. The streamwise
velocity profiles deviate above the standard logarithmic law and the Reynolds
shear stress is reduced. The strong acceleration also suppresses the wall-shear
normalized turbulent kinetic energy production rate. At the bump peak, where
the FPG switches to an adverse gradient (APG), the near-wall turbulence is
suddenly enhanced through a partial retransition process. This results in a new
highly energized internal layer which is more resilient to the strong APG and
only produces incipient flow separation on the downstream side. In the strong
FPG and APG regions, the inner and outer layers become largely independent of
each other. The near-wall region responds to the pressure gradients and
determines the skin friction. The outer layer behaves similarly to a free-shear
layer subject to pressure gradients and mean streamline curvature effects.
Results from a RANS simulation of the bump are also discussed and clearly show
the lack of predictive capacity of the near-wall pressure gradient effects on
the mean flow.


  The norm resolvent convergence of a family of one-dimensional Schroedinger
operators with singular magnetic and electric potentials of small support is
studied.


  We consider first order cosmological phase transitions (PT) happening at late
times, below Standard Model (SM) temperatures $T_{\rm PT} \lesssim$ GeV. The
inherently stochastic nature of bubble nucleation and the finite number of
bubbles associated with a late-time PT lead to superhorizon fluctuations in the
PT completion time. We compute how such fluctuations eventually source
curvature fluctuations with universal properties, independent of the
microphysics of the PT dynamics. Using Cosmic Microwave Background (CMB) and
Large Scale Structure (LSS) measurements, we constrain the energy released in a
dark-sector PT. For 0.1 eV $\lesssim T_{\rm PT} \lesssim$ keV this constraint
is stronger than both the current bound from additional neutrino species
$\Delta N_{\rm eff}$, and in some cases, even CMB-S4 projections. Future
measurements of CMB spectral distortions and pulsar timing arrays will also
provide competitive sensitivity for keV $\lesssim T_{\rm PT} \lesssim$ GeV.


  This paper studies the Hankel determinant generated by a perturbed Jacobi
weight, which is closely related to the largest and smallest eigenvalue
distribution of the degenerate Jacobi unitary ensemble. By using the ladder
operator approach for the orthogonal polynomials, we find that the logarithmic
derivative of the Hankel determinant satisfies a nonlinear second-order
differential equation, which turns out to be the Jimbo-Miwa-Okamoto
$\sigma$-form of the Painlev\'{e} VI equation by a translation transformation.
We also show that, after a suitable double scaling, the differential equation
is reduced to the Jimbo-Miwa-Okamoto $\sigma$-form of the Painlev\'{e} III. In
the end, we obtain the asymptotic behavior of the Hankel determinant as
$t\rightarrow1^{-}$ and $t\rightarrow0^{+}$ in two important cases,
respectively.


  Groundwater is a crucial source of drinking water, but it is often
contaminated with water-soluble pollutants that can pose significant health
risks. Among these pollutants, nitrate has been extensively studied and found
to be harmful to human health in high concentrations. However, the impact of
nitrate pollution in groundwater on crime rates and social problems remains
unexplored. This study aims to investigate the correlation between nitrate
contamination in groundwater and crime rates in US states. The results suggest
a potential link between nitrate pollution and increased crime rates, leading
to the proposal of the "Nitrate-Crime Hypothesis." These findings highlight the
importance of environmental factors in public health and safety policies and
call for further research in this area.


  One of the use cases for 5G systems and beyond is ultra-reliability
low-latency communication (URLLC). An enabling technology for URLLC is massive
multiple-input multiple-output (MIMO), which can increase reliability due to
improved user separation, array gain and the channel hardening effect.
Measurements have been performed in an operating factory environment at 3.7 GHz
with a co-located massive MIMO array and a unique randomly distributed array.
Channel hardening can appear when the number of antennas is increased such that
the variations of channel gain (small-scale fading) is decreased and it is here
quantified. The cumulative distribution function (CDF) of the channel gains
then becomes steeper and its tail is reduced. This CDF is modeled and the
required fading margins are quantified. By deploying a distributed array, the
large-scale power variations can also be reduced, further improving
reliability. The large array in this rich scattering environment, creates a
more reliable channel as it approaches an independent identically distributed
(i.i.d.) complex Gaussian channel, indicating that one can rethink the system
design in terms of e.g. channel coding and re-transmission strategies, in order
to reduce latency. To conclude, massive MIMO is a highly interesting technology
for reliable connectivity in reflective and heavily shadowed industrial
environments.


  Radiative nucleon-deuteron capture and two- and three-body photo
disintegration of the three-nucleon bound state are described. The description
uses the purely nucleonic charge-dependent CD-Bonn potential and its
coupled-channel extension CD Bonn + $\Delta$. The $\Delta$-isobar excitation
yields an effective three-nucleon force and effective two- and three-nucleon
currents besides other $\Delta$-isobar effects; they are mutually consistent.
Exact solutions of three-particle equations are employed for the initial and
final states of the reactions. The current has one-baryon and two-baryon
contributions and couples nucleonic with $\Delta$-isobar channels.
$\Delta$-isobar effects on the observables are isolated. Shortcomings of the
theoretical description are discussed and their consequence for the calculation
of observables is estimated.


  The 2-m robotic Liverpool Telescope reacted promptly to the gamma-ray burst
GRB 050502a discovered by INTEGRAL and started observing 3 min after the onset
of the GRB. The automatic identification of a bright afterglow of r'~15.8
triggered for the first time an observation sequence in the BVr'i' filters
during the first hour after a GRB. Observations continued for ~1 day using the
RoboNet-1.0 network of 2-m robotic telescopes. The light curve in all filters
can be described by a simple power law with index of 1.2 +/- 0.1. We find
evidence for a bump rising at t~0.02 days in all filters. From the spectrum and
the light curve we investigate different interpretative scenarios and we find
possible evidence for a uniform circumburst medium with clumps in density, as
in the case of GRB 021004. Other interpretations of such bumps, such as the
effect of energy injection through refreshed shocks or the result of a variable
energy profile, are less favored. The optical afterglow of GRB 050502a is
likely to be the result of slow electron cooling with the optical bands lying
between the synchrotron peak frequency and the cooling frequency.


  We show that every nonzero integer occurs in the denominator of a boundary
slope for infinitely many (1,1)-knots and that infinitely many (1,1)-knots have
boundary slopes of arbitrarily small difference. Specifically, we prove that
for any integers m, n > 1 with n odd the exterior of the Montesinos knot
K(-1/2, m/(2m \pm 1), 1/n) in S^3 contains an essential surface with boundary
slope r = 2(n-1)^2/n if m is even and 2(n+1)^2/n if m is odd. If n > 4m, we
prove that K(-1/2, m/(2m+1), 1/n) also has a boundary slope whose difference
with r is (8m-2)/(n^2-4mn+n), which decreases to 0 as n increases. All of these
knots are (1,1)-knots.


  In this paper we explore the performance of deep hidden physics model (M.
Raissi 2018) for autonomous systems. These systems are described by set of
ordinary differential equations which do not explicitly depend on time. Such
systems can be found in nature and have applications in modeling chemical
concentrations, population dynamics, n-body problems in physics etc. In this
work we consider dynamics of states, which explain how the states will evolve
are unknown to us. We approximate state and dynamics both using neural
networks. We have considered examples of 2D linear/nonlinear and Lorenz
systems. We observe that even without knowing all the states information, we
can estimate dynamics of certain states whose state information are known.


  In this paper we continue our study on the canonical metrics on the
Teichm\"uller and the moduli space of Riemman surfaces. We first prove the
equivalence of the Bergman metric and the Carath\'eodory metric to the
K\"ahler-Einstein metric, solving another old conjecture of Yau. We then prove
that the Ricci curvature of the perturbed Ricci metric has negative upper and
lower bounds, and it also has bounded geometry. Then we study in detail the
boundary behaviors of the K\"ahler-Einstein metric and prove that it has
bounded geometry, and all of the covariant derivatives of its curvature are
uniformly bounded on the Teichm\"uller space. As an application of our detailed
understanding of these metrics, we prove that the logarithmic cotangent bundle
of the moduli space is stable in the sense of Mumford.


  We introduce a new paradigm for constructing accurate analytic waveforms (and
fluxes) for eccentric compact binaries. Our recipe builds on the standard
Post-Newtonian (PN) approach but (i) retains implicit time-derivatives of the
phase space variables in the instantaneous part of the noncircular waveform,
and then (ii) suitably factorizes and resums this partly PN-implicit waveform
using effective-one-body (EOB) procedures. We test our prescription against the
exact results obtained by solving the Teukolsky equation with a test-mass
source orbiting a Kerr black hole, and compare the use of the exact vs PN
equations of motion for the time derivatives computation. Focusing only on the
quadrupole contribution, we find that the use of the exact equations of motion
yields an analytical/numerical agreement of the (averaged) angular momentum
fluxes that is improved by $40\%$ with respect to previous work, with $4.5\%$
fractional difference for eccentricity $e=0.9$ and black hole dimensionless
spin $-0.9\leq \hat{a}\leq +0.9$. We also find a remarkable convergence trend
between Newtonian, 1PN and 2PN results. Our approach carries over to the
comparable mass case using the resummed EOB equations of motion and paves the
way to faithful EOB-based waveform model for long-inspiral eccentric binaries
for current and future gravitational wave detectors.


  Symptom phenotypes are one of the key types of manifestations for diagnosis
and treatment of various disease conditions. However, the diversity of symptom
terminologies is one of the major obstacles hindering the analysis and
knowledge sharing of various types of symptom-related medical data particularly
in the fields of Traditional Chinese Medicine (TCM). Objective: This study
aimed to construct an Integrated Ontology of symptom phenotypes (ISPO) to
support the data mining of Chinese EMRs and real-world study in TCM field.
Methods: To construct an integrated ontology of symptom phenotypes (ISPO), we
manually annotated classical TCM textbooks and large-scale Chinese electronic
medical records (EMRs) to collect symptom terms with support from a medical
text annotation system. Furthermore, to facilitate the semantic
interoperability between different terminologies, we incorporated public
available biomedical vocabularies by manual mapping between Chinese terms and
English terms with cross-references to source vocabularies. In addition, we
evaluated the ISPO using independent clinical EMRs to provide a high-usable
medical ontology for clinical data analysis. Results: By integrating 78,696
inpatient cases of EMRs, 5 biomedical vocabularies, 21 TCM books and
dictionaries, ISPO provides 3,147 concepts, 23,475 terms, and 55,552 definition
or contextual texts. Adhering to the taxonomical structure of the related
anatomical systems of symptom phenotypes, ISPO provides 12 top-level categories
and 79 middle-level sub-categories. The validation of data analysis showed the
ISPO has a coverage rate of 95.35%, 98.53% and 92.66% for symptom terms with
occurrence rates of 0.5% in additional three independent curated clinical
datasets, which can demonstrate the significant value of ISPO in mapping
clinical terms to ontologies.


  The reliable estimation of forecast uncertainties is crucial for
risk-sensitive optimal decision making. In this paper, we propose implicit
generative ensemble post-processing, a novel framework for multivariate
probabilistic electricity price forecasting. We use a likelihood-free implicit
generative model based on an ensemble of point forecasting models to generate
multivariate electricity price scenarios with a coherent dependency structure
as a representation of the joint predictive distribution. Our ensemble
post-processing method outperforms well-established model combination
benchmarks. This is demonstrated on a data set from the German day-ahead
market. As our method works on top of an ensemble of domain-specific expert
models, it can readily be deployed to other forecasting tasks.


  This work aims to characterize ultra high dose rate pulses (UHDpulse)
electron beams using the hybrid semiconductor pixel detector. The Timepix3
(TPX3) ASIC chip was used to measure the composition, spatial, time, and
spectral characteristics of the secondary radiation fields from pulsed 15 to 23
MeV electron beams. The challenge is to develop a single compact detector that
could extract spectrometric and dosimetric information on such high flux short
pulsed fields. For secondary beam measurements, PMMA plates of 1 and 8 cm
thickness were placed in front of the electron beam, with a pulse duration of
3.5 microseconds. Timepix3 detectors with silicon sensors of 100 and 500
micrometers thickness were placed on a shifting stage allowing for data
acquisition at various lateral positions to the beam axis. The use of the
detector in FLEXI configuration enables suitable measurements in situ and
minimal self shielding. Preliminary results highlight both the technique and
the detector's ability to measure individual UHDpulses of electron beams
delivered in short pulses. In addition, the use of the two signal chains per
pixel enables the estimation of particle flux and the scattered dose rates
(DRs) at various distances from the beam core, in mixed radiation fields.


  A recent study pointed out that macroscopic dark matter (macros) traversing
through the earth's atmosphere can give rise to hot and ionized channels
similar to those associated with lightning leaders. The authors of the study
investigated the possibility that when such channels created by macros pass
through a thundercloud, lightning leaders may locked into these ionized
channels creating lightning discharges with perfectly straight channels. They
suggested the possibility of detecting such channels as a means of detecting
the passage of macros through the atmosphere. In this paper, we show that
macros crossing the atmosphere under fair weather conditions could also give
rise to mini lightning flashes with current amplitudes in the order of few
hundreds of Amperes. These mini lightning flashes would generate a thunder
signature similar to or stronger than those of long laboratory sparks and they
could also be detected by optical means. As in the case of thunderstorm
assisted macro lightning, these mini-lightning flashes are also associated with
straight channels. Moreover, since the frequency of mini lightning flashes are
about three hundred times more frequent than the macro generated lightning
flashes which were assisted by thunderstorms, they could be used as a means to
look for the paths of macroscopic dark matter crossing the atmosphere.


  The realism of digital avatars is crucial in enabling telepresence
applications with self-expression and customization. While physical simulations
can produce realistic motions for clothed humans, they require high-quality
garment assets with associated physical parameters for cloth simulations.
However, manually creating these assets and calibrating their parameters is
labor-intensive and requires specialized expertise. Current methods focus on
reconstructing geometry, but don't generate complete assets for physics-based
applications. To address this gap, we propose \papername,~a novel approach that
performs body and garment co-optimization using differentiable simulation. By
integrating physical simulation into the optimization loop and accounting for
the complex nonlinear behavior of cloth and its intricate interaction with the
body, our framework recovers body and garment geometry and extracts important
material parameters in a physically plausible way. Our experiments demonstrate
that our approach generates realistic clothing and body shape suitable for
downstream applications. We provide additional insights and results on our
webpage: https://people.csail.mit.edu/liyifei/publication/diffavatar/


  We prove that, for any finite set $A \subset \mathbb Q$ with $|AA| \leq K|A|$
and any positive integer $k$, the $k$-fold product set of the shift $A+1$
satisfies the bound $$| \{(a_1+1)(a_2+1) \cdots (a_k+1) : a_i \in A \}| \geq
\frac{|A|^k}{(8k^4)^{kK}}. $$ This result is essentially optimal when $K$ is of
the order $c\log|A|$, for a sufficiently small constant $c=c(k)$.
  Our main tool is a multiplicative variant of the $\Lambda$-constants used in
harmonic analysis, applied to Dirichlet polynomials.


  In recent years, several convergent multi-block variants of the alternating
direction method of multipliers (ADMM) have been proposed for solving the
convex quadratic semidefinite programming via its dual, which is naturally a
3-block separable convex optimization problem with one coupled linear equality
constraint. Among of these ADMM-type algorithms, the modified 3-block ADMM in
[Chang et al., Neurocomput. 214: 575--586 (2016)] bears a peculiar feature that
the augmented Lagrangian function is not necessarily to be minimized with
respect to the block-variable corresponding to the quadratic term of the
objective function. In this paper, we lay the theoretical foundation of this
phenomena by interpreting this modified 3-block ADMM as a realization of a
3-operator splitting framework. Based on this perspective, we are able to
extend this modified 3-block ADMM to a generalized 3-block ADMM, which not only
applies to the more general convex composite quadratic programming setting but
also admits the potential of achieving even a better numerical performance.


  We prove that there is a knot $K$ transverse to $\xi_{std}$, the tight
contact structure of $S^3$, such that every contact 3-manifold $(M, \xi)$ can
be obtained as a contact covering branched along $K$. By contact covering we
mean a map $\varphi: M \to S^3$ branched along $K$ such that $\xi$ is contact
isotopic to the lifting of $\xi_{std}$ under $\varphi$.


  We present a classification of non-hermitian random matrices based on
implementing commuting discrete symmetries. It contains 38 classes. This
generalizes the classification of hermitian random matrices due to
Altland-Zirnbauer and it also extends the Ginibre ensembles of non-hermitian
matrices.


  For the first time, an approach is suggested for the quantitative description
of the electronic structure of single-walled carbon nanotubes and the
prediction of active sites for the tube controlled functionalization in view of
the tube length and ends structure. The approach is based on the tube
characteristic feature connected with odd electrons and is illustrated for a
family involving fragments of arm-chair configured (4,4) single-walled
nanotubes differing by length and end structure. Short and long tubes as well
as tubes with cap end and open end, in the latter case, both hydrogen
terminated and empty, are considered. Algorithms of the quantitative
description of the tubes of any length are suggested. Calculations were
performed in the framework of the single-determinant unrestricted Hartree-Fock
approach.


  Recent years have seen a significant increase in the use of machine
intelligence for predicting electronic structure, molecular force fields, and
the physicochemical properties of various condensed systems. However,
substantial challenges remain in developing a comprehensive framework capable
of handling a wide range of atomic compositions and thermodynamic conditions.
This perspective discusses potential future developments in liquid-state
theories leveraging on recent advancements of functional machine learning. By
harnessing the strengths of theoretical analysis and machine learning
techniques including surrogate models, dimension reduction and uncertainty
quantification, we envision that liquid-state theories will gain significant
improvements in accuracy, scalability and computational efficiency, enabling
their broader applications across diverse materials and chemical systems.


  We propose an operator learning approach to accelerate geometric Markov chain
Monte Carlo (MCMC) for solving infinite-dimensional Bayesian inverse problems
(BIPs). While geometric MCMC employs high-quality proposals that adapt to
posterior local geometry, it requires repeated computations of gradients and
Hessians of the log-likelihood, which becomes prohibitive when the
parameter-to-observable (PtO) map is defined through expensive-to-solve
parametric partial differential equations (PDEs). We consider a
delayed-acceptance geometric MCMC method driven by a neural operator surrogate
of the PtO map, where the proposal exploits fast surrogate predictions of the
log-likelihood and, simultaneously, its gradient and Hessian. To achieve a
substantial speedup, the surrogate must accurately approximate the PtO map and
its Jacobian, which often demands a prohibitively large number of PtO map
samples via conventional operator learning methods. In this work, we present an
extension of derivative-informed operator learning [O'Leary-Roseberry et al.,
J. Comput. Phys., 496 (2024)] that uses joint samples of the PtO map and its
Jacobian. This leads to derivative-informed neural operator (DINO) surrogates
that accurately predict the observables and posterior local geometry at a
significantly lower training cost than conventional methods. Cost and error
analysis for reduced basis DINO surrogates are provided. Numerical studies
demonstrate that DINO-driven MCMC generates effective posterior samples 3--9
times faster than geometric MCMC and 60--97 times faster than prior
geometry-based MCMC. Furthermore, the training cost of DINO surrogates breaks
even compared to geometric MCMC after just 10--25 effective posterior samples.


  In this work we study the Plancherel-Rotach type asymptotics for
Ismail-Masson orthogonal polynomials with complex scaling. The main term of the
asymptotics contains Ramanujan function $A_{q}(z)$ for the scaling parameter on
the vertical line $\Re(s)={1/2}$, while the main term of the asymptotics
involves the theta functions for the scaling parameter in the strip
$0<\Re(s)<{1/2}$. In the latter case the number theoretical property of the
scaling parameter completely determines the order of the error term. $ $These
asymptotic formulas may provide insights to some new random matrix models and
also add a new link between special functions and number theory.


  Due to its empirical success in few-shot classification and reinforcement
learning, meta-learning has recently received significant interest.
Meta-learning methods leverage data from previous tasks to learn a new task in
a sample-efficient manner. In particular, model-agnostic methods look for
initialization points from which gradient descent quickly adapts to any new
task. Although it has been empirically suggested that such methods perform well
by learning shared representations during pretraining, there is limited
theoretical evidence of such behavior. More importantly, it has not been shown
that these methods still learn a shared structure, despite architectural
misspecifications. In this direction, this work shows, in the limit of an
infinite number of tasks, that first-order ANIL with a linear two-layer network
architecture successfully learns linear shared representations. This result
even holds with overparametrization; having a width larger than the dimension
of the shared representations results in an asymptotically low-rank solution.
The learned solution then yields a good adaptation performance on any new task
after a single gradient step. Overall, this illustrates how well model-agnostic
methods such as first-order ANIL can learn shared representations.


  XY Ari is one of the few known eclipsing intermediate polars. We present
results from a detailed analysis of an unpublished archival observation using
XMM-Newton EPIC pn and MOS data in a quiescent state of XY Ari. The X-ray
orbital modulation and spin pulse variations were investigated for energy
dependent modulations in different energy bands. The broad orbital modulation
observed with various observations was confirmed with XMM-Newton at hard X-ray
(>1.6 keV). The EPIC light curves folded at the spin phases show a double peak
profile as expected from two pole accretion. The pulse profile is found to be
energy dependent. Hardness ratio variations and energy modulation depth during
spin modulation can be explained by photoelectric absorption. The
simultaneously fitted EPIC spectra with CEVMKL model yield maximum plasma
temperature of $28^{+3.1}_{-2.9}$ keV with an iron abundance
$\mathrm{Fe}/\mathrm{Fe}_\odot=0.37^{+0.06}_{-0.05}$. We find two intrinsic
partial covering absorption columns of $6.2^{+1.0}_{-0.9} \times 10^{22}$ and
$105.3^{+35.4}_{-30.4} \times 10^{22} \,\mathrm{cm^{-2}}$ with covering
fractions of $0.53^{+0.05}_{-0.04}$, $0.41^{+0.14}_{-0.13}$ respectively. In
addition, a Gaussian emission line at $6.43^{+0.01}_{-0.02}$ keV with an
equivalent width of $51^{+12}_{-10}$ eV is required to account for fluorescent
emission from neutral iron. The X-ray luminosity of the source is $4.2 \times
10^{32} \,\mathrm{erg \,s^{-1}}$ in the 0.2-10.0 keV energy band.


  We provide a criterion for when Hilbert schemes of points on K3 surfaces are
birational. In particular, this allows us to generate a plethora of examples of
non-birational Hilbert schemes which are derived equivalent.


  We report new measurements on sup-gap energy structure originating from
multiple Andreev reflections in mesoscopic SNS junctions. The junctions were
fabricated in a planar geometry with high transparency superconducting contacts
of Al deposited on highly diffusive and surface d-doped n++-GaAs. For samples
with a normal GaAs region of active length 0.3um the Josephson effect with a
maximal supercurrent Ic=3mA at T=237mK was observed. The sub-gap structure was
observed as a series of local minima in the differential resistance at dc bias
voltages V=2D/ne with n=1,2,4 i.e. only the even sub-gap positions. While at
V=2D/e (n=1) only one dip is observed, the n=2, and the n=4 sub-gap structures
each consists of two separate dips in the differential resistance. The mutual
spacing of these two dips is independent of temperature, and the mutual spacing
of the n=4 dips is half of the spacing of the n=2 dips. The voltage bias
positions of the sub-gap differential resistance minima coincide with the
maxima in the oscillation amplitude when a magnetic field is applied in an
interferometer configuration, where one of the superconducting electrodes has
been replaced by a flux sensitive open loop.


  In this work, we have investigated the interaction of a high-power Ar$^+$
laser beam, in a continuous multi-line regime, with Ag$^+$-doped glass samples.
The samples were subjected to the irradiation after the ion-exchange step. As a
result of the irradiation, a peak appears in the absorption spectrum; its
evolution depends on both the exposure time and the laser beam power.
Interaction of the beam with the clusters causes them break into smaller ones
which has been confirmed by optical absorption spectroscopy. Depending on the
increment steps of the laser-beam power, different results are obtained. It is
found that, in addition to the fragmentations of the nano-clusters, clusters of
micro-meter size ($d\sim 3\mu m$) are formed in the sample, if the laser power
is increased in a fast regime. The fragmentation processes have been explained
in the framework of the density-functional theory with stabilized jellium
model.


  Let C/Q be a curve of genus three, given as a double cover of a plane conic.
Such a curve is hyperelliptic over the algebraic closure of Q, but may not have
a hyperelliptic model of the usual form over Q. We describe an algorithm that
computes the local zeta functions of C at all odd primes of good reduction up
to a prescribed bound N. The algorithm relies on an adaptation of the
"accumulating remainder tree" to matrices with entries in a quadratic field. We
report on an implementation, and compare its performance to previous algorithms
for the ordinary hyperelliptic case.


  In this paper, we show that there are instances where eavesdropping causes
noise reduction for a quantum key distribution (QKD) protocol. To witness these
phenomena, we investigate a fault-tolerant six-state QKD protocol over a
collective unitary noise channel. In this protocol, legitimate users send and
receive two-qubit states that belong to the noiseless subspace being robust
against collective unitary errors. We examine eavesdropper's intercept/resend
and entangling probe attacks on this protocol. In general, the collective
unitary noises lessen the probability that legitimate users share a random bit
with the QKD protocol. However, we show that eavesdropping enlarges that
probability in some specific scenarios although the effects of the collective
unitary noise channel are strong enough. These phenomena make the legitimate
users difficult to distinguish between noises and eavesdropper's malicious acts
by monitoring the probability that they share the same random key.


  Quasi-periodic oscillations inferred during rare magnetar giant flare tails
were initially interpreted as torsional oscillations of the neutron star (NS)
crust, and have been more recently described as global core+crust
perturbations. Similar frequencies are also present in high signal-to-noise
magnetar short bursts. In magnetars, disturbances of the field are strongly
coupled to the NS crust regardless of the triggering mechanism of short bursts.
For low-altitude magnetospheric magnetar models of fast radio bursts (FRBs)
associated with magnetar short bursts, such as the low-twist model, crustal
oscillations may be associated with additional radio bursts in the encompassing
short burst event (as recently suggested for SGR 1935+2154). Given the large
extragalactic volume probed by wide-field radio transient facilities, this
offers the prospect of studying NS crusts leveraging samples far more numerous
than galactic high-energy magnetar bursts by studying statistics of sub-burst
structure or clustered trains of FRBs. We explore the prospects for
distinguishing NS equation of state models with increasingly larger future sets
of FRB observations. Lower $l$-number eigenmodes (corresponding to FRB time
intervals of $\sim5-50$ ms) are likely less susceptible than high-$l$ modes to
confusion by systematic effects associated with the NS crust physics, magnetic
field, and damping. They may be more promising in their utility, and also may
corroborate models where FRBs arise from mature magnetars. Future observational
characterization of such signals can also determine whether they can be
employed as cosmological "standard oscillators" to constrain redshift, or can
be used to constrain the mass of FRB-producing magnetars when reliable
redshifts are available.


  We consider $N$ interacting dipolar bosonic atoms at zero temperature in a
double-well potential. This system is described by the two-space-mode extended
Bose-Hubbard (EBH) Hamiltonian which includes (in addition to the familiar BH
terms) the nearest-neighbor interaction, correlated hopping and bosonic-pair
hopping. For systems with $N=2$ and $N=3$ particles we calculate analytically
both the ground state and the Fisher information, the coherence visibility, and
the entanglement entropy that characterize the correlations of the lowest
energy state. The structure of the ground state crucially depends on the
correlated hopping $K_c$. On one hand we find that this process makes possible
the occurrence of Schr\"odinger-cat states even if the onsite interatomic
attraction is not strong enough to guarantee the formation of such states. On
the other hand, in the presence of a strong onsite attraction, sufficiently
large values of $|K_c|$ destroys the cat-like state in favor of a delocalized
atomic coherent state.


  We extend the formulae of classical invariant theory for the Jacobian of a
genus one curve of degree $n \le 4$ to curves of arbitrary degree. To do this,
we associate to each genus one normal curve of degree $n$, an $n \times n$
alternating matrix of quadratic forms in $n$ variables, that represents the
invariant differential. We then exhibit the invariants we need as homogeneous
polynomials of degrees $4$ and $6$ in the coefficients of the entries of this
matrix.