  A finite Hilbert space can be associated to a periodic phase space, that is,
a torus. A finite subgroup of operators corresponding to reflections and
translations on the torus form respectively the basis for the discrete Weyl
representation, including the Wigner function, and for its Fourier conjugate,
the chord representation. They are invariant under Clifford transformations and
obey analogous product rules to the continuous representations, so allowing for
the calculation of expectations and correlations for observables. We here
import new identities from the continuum for products of pure state Wigner and
chord functions, involving, for instance the inverse phase space participation
ratio and correlations of a state with its translate. New identities are
derived involving {\it transition} Wigner or chord functions of transition
operators $\ket{\psi_1}\bra{\psi_2}$. Extension of the reflection and
translation operators to a doubled torus phase space leads to the
representation of superoperators and so to the construction of the propagator
of Wigner functions from the Weyl representation of the evolution operator.


  Laser-induced femtosecond magnetism or femtomagnetism simultaneously relies
on two distinctive contributions: (a) the optical dipole interaction (ODI)
between a laser field and a magnetic system and (b) the spin expectation value
change (SEC) between two transition states. Surprisingly, up to now, no study
has taken both contributions into account simultaneously. Here we do so by
introducing a new concept of the optical spin generator, a product of SEC and
ODI between transition states. In ferromagnetic nickel, our first-principles
calculation demonstrates that the larger the value of optical spin generator
is, the larger the dynamic spin moment change is. This simple generator
directly links the time-dependent spin moment change {\Delta}Mk z (t) at every
crystal- momentum k point to its intrinsic electronic structure and magnetic
properties. Those hot spin spots are a direct manifestation of the optical spin
generator, and should be the focus of future research.


  Three dimensional, particle-in-cell, fully electromagnetic simulations of
electron plasma wake field acceleration in the blow out regime are presented.
Earlier results are extended by (i) studying the effect of longitudinal density
gradient; (ii) avoiding use of co-moving simulation box; (iii) inclusion of ion
motion; and (iv) studying fully electromagnetic plasma wake fields. It is
established that injecting driving and trailing electron bunches into a
positive density gradient of ten-fold increasing density over 10 cm long
Lithium vapor plasma, results in spatially more compact and three times larger,
compared to the uniform density case, electric fields ($-6.4 \times 10^{10}$
V/m), leading to acceleration of the trailing bunch up to 24.4 GeV (starting
from initial 20.4 GeV), with an energy transfer efficiencies from leading to
trailing bunch of 75 percent. In the uniform density case $-2.5 \times 10^{10}$
V/m wake is created leading to acceleration of the trailing bunch up to 22.4
GeV, with an energy transfer efficiencies of 65 percent. It is also established
that injecting the electron bunches into a negative density gradient of
ten-fold decreasing density over 10 cm long plasma, results in spatially more
spread and two-and-half smaller electric fields ($-1.0 \times 10^{10}$ V/m),
leading to a weaker acceleration of the trailing bunch up to 21.4 GeV, with an
energy transfer efficiencies of 45 percent. Inclusion of ion motions into
consideration shows that in the plasma wake ion number density can increase
over few times the background value. It is also shown that transverse
electromagnetic fields in plasma wake are of the same order as the longitudinal
(electrostatic) ones.


  We study the unitary relaxation dynamics of disordered spin chains following
a sudden quench of the Hamiltonian. We give analytical arguments, corroborated
by specific numerical examples, to show that the existence of a stationary
state depends crucially on the spectral and localization properties of the
final Hamiltonian, and not on the initial state. We test these ideas on
integrable one-dimensional models of the Ising or XY class, but argue more
generally on their validity for more complex (nonintegrable) models.


  During the last years, asymptotic (or sequential) constraint qualifications,
which postulate upper semicontinuity of certain set-valued mappings and provide
a natural companion of asymptotic stationarity conditions, have been shown to
be comparatively mild, on the one hand, while possessing inherent practical
relevance from the viewpoint of numerical solution methods, on the other one.
Based on recent developments, the theory in this paper enriches asymptotic
constraint qualifications for very general nonsmooth optimization problems over
inverse images of set-valued mappings by incorporating directional data. We
compare these new directional asymptotic regularity conditions with standard
constraint qualifications from nonsmooth optimization. Further, we introduce
directional concepts of pseudo- and quasi-normality which apply to set-valued
mappings. It is shown that these properties provide sufficient conditions for
the validity of directional asymptotic regularity. Finally, a novel
coderivative-like variational tool is introduced which allows to study the
presence of directional asymptotic regularity. For geometric constraints, it is
illustrated that all appearing objects can be calculated in terms of initial
problem data.


  Structures in circumstellar disks such as gaps and rings are often attributed
to planets. This connection has been difficult to show unequivocally, as other
processes may also produce these features. Particularly, a photoelectric
instability (PEI) has been proposed, operating in gas-rich optically thin
disks, that generates structures predicted by planet--disk interactions. We
examine the question of how to disentangle planetary effects on disk structure
from the effects of the PEI. We use the Pencil Code to perform 2D global
hydrodynamical models of the dynamics of gas and dust in a thin disk, with and
without planetary perturbers. Photoelectric heating is modeled with an equation
of state where pressure is proportional to dust surface density. The drag force
on grains and its backreaction on the gas are included. Analyzing the situation
without PEI, we find that gas--dust interactions alter the shape of the
planetary gap from the dust-free case when the local dust-to-gas ratio
$\varepsilon$ approaches unity. This result applies also to primordial disks,
because dust drifting inwards accumulates at the edge of the planetary gap, and
any initial dust-to-gas ratio eventually achieves $\varepsilon=1$ if the dust
reservoir is sufficient. We find a result particular to high dust-to-gas ratio
disks as well: as dust drifts inwards, the dust front becomes a sharp
transition, and the backreaction triggers the Rossby wave instability. When PEI
is included, we find that it obscures structures induced by planets unless the
planet's mass is sufficiently large to carve a noticeable gap. Specifically,
the instability generates arcs and rings of regular spacing: a planet is
discernible when it carves a dust gap wider than the wavelength of the PEI.


  Using CLEO data, we study the production of the anti-deuteron, d-bar, in
Upsilon(nS) resonance decays and the nearby continuum. The branching ratios
obtained are B^dir(Upsilon(1S) --> d-bar X) = (3.36 +- 0.23 +- 0.25) x 10^-5,
  B(Upsilon(1S) --> d-bar X) = (2.86 +- 0.19 +- 0.21) x 10^-5, and
  B(Upsilon(2S) --> d-bar X) = (3.37 +- 0.50 +- 0.25) x 10^-5, where the `dir'
superscript indicates that decays produced via re-annihilation of the b bbar
pair to a gamma* are removed from both the signal and the normalizing number of
Upsilon(1S) decays in order to isolate direct decays of the Upsilon(1S) to ggg,
gg gamma. Upper limits at 90% CL are given for B(Upsilon(4S) --> d-bar X) < 1.3
x 10^-5, and continuum production \sigma(e^+e^- --> d-bar X) < 0.031 pb. The
Upsilon(2S) data is also used to extract a limit on chi_bJ --> d-bar X. The
results indicate enhanced deuteron production in ggg, gg gamma hadronization
compared to gamma* --> q qbar. Baryon number compensation is also investigated
with the large Upsilon(1S) --> d-bar X sample.


  For a 3-manifold $M$ with $b_1(M)=1$ fibered over $S^1$ and the fiberwise
gradient $\xi$ of a fiberwise Morse function on $M$, we introduce the notion of
amidakuji-like path (AL-path) on $M$. An AL-path is a piecewise smooth path on
$M$ consisting of edges each of which is either a part of a critical locus of
$\xi$ or a flow line of $-\xi$. Counting closed AL-paths with signs gives the
Lefschetz zeta function of $M$. The "moduli space" of AL-paths on $M$ gives
explicitly Lescop's equivariant propagator, which can be used to define
$\mathbb{Z}$-equivariant version of Chern--Simons perturbation theory for $M$.


  Vision-language (VL) models often exhibit a limited understanding of complex
expressions of visual objects (e.g., attributes, shapes, and their relations),
given complex and diverse language queries. Traditional approaches attempt to
improve VL models using hard negative synthetic text, but their effectiveness
is limited. In this paper, we harness the exceptional compositional
understanding capabilities of generative foundational models. We introduce a
novel method for structured synthetic data generation aimed at enhancing the
compositional understanding of VL models in language-based object detection.
Our framework generates densely paired positive and negative triplets (image,
text descriptions, and bounding boxes) in both image and text domains. By
leveraging these synthetic triplets, we transform 'weaker' VL models into
'stronger' models in terms of compositional understanding, a process we call
"Weak-to-Strong Compositional Learning" (WSCL). To achieve this, we propose a
new compositional contrastive learning formulation that discovers semantics and
structures in complex descriptions from synthetic triplets. As a result, VL
models trained with our synthetic data generation exhibit a significant
performance boost in the Omnilabel benchmark by up to +5AP and the D3 benchmark
by +6.9AP upon existing baselines.


  We study the stochastic hydrodynamics of colonies of flagellated swimming
cells, typified by multicellular choanoflagellates, which can form both rosette
and chainlike shapes. The objective is to link cell-scale dynamics to
colony-scale dynamics for various colonial morphologies. Via autoregressive
stochastic models for the cycle-averaged flagellar force dynamics and
statistical models for demographic cell-to-cell variability in flagellar
properties and placement, we derive effective transport properties of the
colonies, including cell-to-cell variability. We provide the most quantitative
detail on disclike geometries to model rosettes, but also present formulas for
the dynamics of general planar colony morphologies, which includes planar
chain-like configurations.


  Archdeacon, in his seminal paper $[1]$, defined the concept of Heffter array
in order to provide explicit constructions of $\mathbb{Z}_{v}$-regular
biembeddings of complete graphs $K_v$ into orientable surfaces.
  In this paper, we first introduce the quasi-Heffter arrays as a
generalization of the concept of Heffer array and we show that, in this
context, we can define a $2$-colorable embedding of Archdeacon type of the
complete multipartite graph $K_{\frac{v}{t}\times t}$ into an orientable
surface. Then, our main goal is to study the full automorphism groups of these
embeddings: here we are able to prove, using a probabilistic approach, that,
almost always, this group is exactly $\mathbb{Z}_{v}$.
  As an application of this result, given a positive integer $t\not\equiv
0\pmod{4}$, we prove that there are, for infinitely many pairs of $v$ and $k$,
at least $(1-o(1)) \frac{(\frac{v-t}{2})!}{\phi(v)} $ non-isomorphic
biembeddings of $K_{\frac{v}{t}\times t}$ whose face lengths are multiples of
$k$. Here $\phi(\cdot)$ denotes the Euler's totient function. Moreover, in case
$t=1$ and $v$ is a prime, almost all these embeddings define faces that are all
of the same length $kv$, i.e. we have a more than exponential number of
non-isomorphic $kv$-gonal biembeddings of $K_{v}$.


  Several theories of early sensory processing suggest that it whitens sensory
stimuli. Here, we test three key predictions of the whitening theory using
recordings from 152 ganglion cells in salamander retina responding to natural
movies. We confirm the previous finding that firing rates of ganglion cells are
less correlated compared to natural scenes, although significant correlations
remain. We show that while the power spectrum of ganglion cells decays less
steeply than that of natural scenes, it is not completely flattened. Finally,
we find evidence that only the top principal components of the visual stimulus
are transmitted.


  Inspired by chaotic firing of neurons in the brain, we propose ChaosNet -- a
novel chaos based artificial neural network architecture for classification
tasks. ChaosNet is built using layers of neurons, each of which is a 1D chaotic
map known as the Generalized Luroth Series (GLS) which has been shown in
earlier works to possess very useful properties for compression, cryptography
and for computing XOR and other logical operations. In this work, we design a
novel learning algorithm on ChaosNet that exploits the topological transitivity
property of the chaotic GLS neurons. The proposed learning algorithm gives
consistently good performance accuracy in a number of classification tasks on
well known publicly available datasets with very limited training samples. Even
with as low as 7 (or fewer) training samples/class (which accounts for less
than 0.05% of the total available data), ChaosNet yields performance accuracies
in the range 73.89 % - 98.33 %. We demonstrate the robustness of ChaosNet to
additive parameter noise and also provide an example implementation of a
2-layer ChaosNet for enhancing classification accuracy. We envisage the
development of several other novel learning algorithms on ChaosNet in the near
future.


  We give an improved analysis of the best-of-many Christofides algorithm with
lonely edge deletion, which was proposed by Seb\H{o} and van Zuylen [2016].
This implies an improved upper bound on the integrality ratio of the standard
LP relaxation for the $s$-$t$-path TSP.


  A refined trilinear Strichartz estimate for solutions to the Schr\"odinger
equation on the flat rational torus T^3 is derived. By a suitable modification
of critical function space theory this is applied to prove a small data global
well-posedness result for the quintic Nonlinear Schr\"odinger Equation in
H^s(T^3) for all s \geq 1. This is the first energy-critical global
well-posedness result in the setting of compact manifolds.


  The detection of the GW170817/GRB170817A event improved the constraints on
the propagation speed of gravitational waves, thus placing possible variations
caused by dark energy under restraint. For models based on scalar fields
belonging to the family of Horndeski Lagrangians, non-minimal derivative
couplings are now severely constrained, entailing a substantially limited
phenomenology. In this work we want to stress that there is still a plethora of
dark energy models that get around this obstacle while still providing
interesting phenomenologies able to distinguish them from the standard
cosmology. We focus on a class involving vector fields as a proxy, but our
discussion is extensible to a broader class of models. In particular, we show
the possibility of having a non-minimal derivative coupling giving a
non-trivial effect on scalar modes without affecting gravitational waves and
the possibility of having a second tensor mode that can oscillate into
gravitational waves. We also present a novel class of configurations breaking
rotational invariance but with an energy-momentum tensor that is isotropic
on-shell. This peculiar feature makes the scalar and vector sectors of the
perturbations mix so that, even in a perfectly isotropic background cosmology,
preferred direction effects can appear in the perturbations. We also comment on
models that give rise to isotropic solutions when averaging over rapid
oscillations of the vector fields. The explored models are classified according
to distinctive field configurations that provide inequivalent realisations of
the Cosmological Principle.


  We prove the existence and uniqueness of solution of the obstacle problem for
quasilinear stochastic partial differential equations (OSPDEs for short) with
Neumann boundary condition. Our method is based on the analytical technics
coming from parabolic potential theory. The solution is expressed as a pair
$(u,\nu)$ where $u$ is a predictable continuous process which takes values in a
proper Sobolev space and $\nu$ is a random regular measure satisfying minimal
Skohorod condition.


  Inspired by classic generative adversarial networks (GAN), we propose a novel
end-to-end adversarial neural network, called SegAN, for the task of medical
image segmentation. Since image segmentation requires dense, pixel-level
labeling, the single scalar real/fake output of a classic GAN's discriminator
may be ineffective in producing stable and sufficient gradient feedback to the
networks. Instead, we use a fully convolutional neural network as the segmentor
to generate segmentation label maps, and propose a novel adversarial critic
network with a multi-scale $L_1$ loss function to force the critic and
segmentor to learn both global and local features that capture long- and
short-range spatial relationships between pixels. In our SegAN framework, the
segmentor and critic networks are trained in an alternating fashion in a
min-max game: The critic takes as input a pair of images, (original_image $*$
predicted_label_map, original_image $*$ ground_truth_label_map), and then is
trained by maximizing a multi-scale loss function; The segmentor is trained
with only gradients passed along by the critic, with the aim to minimize the
multi-scale loss function. We show that such a SegAN framework is more
effective and stable for the segmentation task, and it leads to better
performance than the state-of-the-art U-net segmentation method. We tested our
SegAN method using datasets from the MICCAI BRATS brain tumor segmentation
challenge. Extensive experimental results demonstrate the effectiveness of the
proposed SegAN with multi-scale loss: on BRATS 2013 SegAN gives performance
comparable to the state-of-the-art for whole tumor and tumor core segmentation
while achieves better precision and sensitivity for Gd-enhance tumor core
segmentation; on BRATS 2015 SegAN achieves better performance than the
state-of-the-art in both dice score and precision.


  We propose an accurate and convenient method to achieve 100\% discrimination
of chiral molecules with Lewis-Riesenfeld invariant. By reversely designing the
pulse scheme of handed resolution, we obtain the parameters of the three-level
Hamiltonians to achieve this goal. For the same initial state, we can
completely transfer its population to one energy level for left-handed
molecules, while transfer it to another energy level for right-handed
molecules. Moreover, this method can be further optimized when errors exist,
and it shows that the optimal method are more robust against these errors than
the counterdiabatic and original invariant-based shortcut schemes. This
provides an effective, accurate, and robust method to distinguish the
handedness of molecules.


  For every compact surface $S$ of finite type (possibly with boundary
components but without punctures), we show that when $n$ is sufficiently large
there is no lift $\sigma$ of the surface braid group $B_n(S)$ to
$\operatorname{Diff}(S,n)$, the group of $C^1$ diffeomorphisms preserving $n$
marked points and restricting to the identity on the boundary. Our methods are
applied to give a new proof of Morita's non-lifting theorem in the best
possible range. These techniques extend to the more general setting of spaces
of codimension-$2$ embeddings, and we obtain corresponding results for
spherical motion groups, including the string motion group.


  Quantum devices use qubits to represent information, which allows them to
exploit important properties from quantum physics, specifically superposition
and entanglement. As a result, quantum computers have the potential to
outperform the most advanced classical computers. In recent years, quantum
algorithms have shown hints of this promise, and many algorithms have been
proposed for the quantum domain. There are two key hurdles to solving difficult
real-world problems on quantum computers. The first is on the hardware front --
the number of qubits in the most advanced quantum systems is too small to make
the solution of large problems practical. The second involves the algorithms
themselves -- as quantum computers use qubits, the algorithms that work there
are fundamentally different from those that work on traditional computers. As a
result of these constraints, research has focused on developing approaches to
solve small versions of problems as proofs of concept -- recognizing that it
would be possible to scale these up once quantum devices with enough qubits
become available. Our objective in this paper is along the same lines. We
present a quantum approach to solve a well-studied problem in the context of
data sharing. This heuristic uses the well-known Quantum Approximate
Optimization Algorithm (QAOA). We present results on experiments involving
small datasets to illustrate how the problem could be solved using quantum
algorithms. The results show that the method has potential and provide answers
close to optimal. At the same time, we realize there are opportunities for
improving the method further.


  Consider elliptic curves $ E=E_\sigma: y^2 = x (x+\sigma p) (x+\sigma q), $
where$ \sigma =\pm 1, $ $p$ and $ q$ are prime numbers with $p+2=q$. (1) The
Selmer groups $ S^{(2)}(E/{\mathbf{Q}}), S^{(\phi)}(E/{\mathbf{Q})}$, and $\
S^{(\hat{\phi})}(E/{\mathbf{Q})} $ are explicitly determined, e.g., $\
S^{(2)}(E_{+1}/{\mathbf{Q}})= $ $({\mathbf{Z}}/2{\mathbf{Z}})^2; $ $
({\mathbf{Z}}/2{\mathbf{Z}})^3; $ or $ ({\mathbf{Z}}/2{\mathbf{Z}})^4 $ when
$p\equiv 5; 1 $ or $3; $ or $ 7 ({\mathrm{mod}} 8)$ respectively. (2) When
$p\equiv 5 (3, 5$ for $\sigma =-1) ({\mathrm{mod}} 8), $ it is proved that the
Mordell-Weil group $ E({\mathbf{Q})} \cong $ $ {\mathbf{Z}}/2{\mathbf{Z}}
\oplus{\mathbf{Z}}/2{\mathbf{Z}} $ having rank $0, $ and Shafarevich-Tate group
{\CC ':} $(E/{\mathbf{Q}})[2]=0. $ (3) In any case, the sum of
rank$E({\mathbf{Q})}$ and dimension of {\CC ':} $(E/{\mathbf{Q}})[2] $ is
given, e.g., $0; 1; 2 $ when $p\equiv 5; 1 $ or $3; 7 ({\mathrm{mod}} 8)$ for
$\sigma =1$. (4) The Kodaira symbol, the torsion subgroup $E(K)_{tors}$ for any
number field $K$, etc. are also obtained.
  This paper is a revised version of ANT-0229.


  We present a large suite of cosmological simulations, the FORGE (F-of-R
Gravity Emulator) simulation suite, which is designed to build accurate
emulators for cosmological observables in galaxy clustering, weak gravitational
lensing and galaxy clusters, for the $f(R)$ gravity model. The total of 200
simulations explore the cosmological parameter space around the Planck(2018)
cosmology with a Latin hypercube, for 50 combinations of $\bar{f}_{R0}$,
$\Omega_m$, $\sigma_8$ and $h$ with all other parameters fixed. For each
parameter combination, or node, we ran four independent simulations, one pair
using $1024^3$ particles in $500 h^{-1} Mpc$ simulation boxes to cover small
scales, and another pair using $512^3$ simulation particles in $1500 h^{-1}
Mpc$ boxes for larger scales. Each pair of initial conditions are selected such
that sample variance on large scales is minimised on average. In this work we
present an accurate emulator for the matter power spectrum in $f(R)$ gravity
trained on FORGE. We have verified, using the cross-validation technique, that
the emulator accuracy is better than $2.5\%$ for the majority of nodes,
particularly around the center of the explored parameter space, up to scales of
$k = 10 h Mpc^{-1}$. We have also checked the power spectrum emulator against
simulations which are not part of our training set and found excellent
agreement. Due to its high accuracy on small scales, the FORGE matter power
spectrum emulator is well suited for weak lensing analysis and can play a key
tool in constraining $f(R)$ gravity using current and future observational
data.


  We study the local structure of vector fields on $\mathbb{R}^3$ which
preserve the Martinet $1$-form $\alpha=(1+x)dy\pm zdz$. We present the
classification of their singularities, up to diffeomorphisms preserving the
form $\alpha$, as well as their transversal unfoldings. We are thus able to
provide a fairly complete list of the bifurcations such vector fields undergo.


  Telescopes for observing the Cosmic Microwave Background (CMB) usually have
shields and baffle structures in order to reduce the pickup from the ground.
These structures may introduce unwanted sidelobes. We present a method to
measure and model baffling structures of large aperture telescope optics to
predict the sidelobe pattern.


  We show that the U(1)-prime models linked with the seesaw mechanism at TeV
scale can lead to a successful baryogenesis through soft leptogenesis with a
resonant behavior in the B parameter. Such a consideration constrains the
Z-prime mass to be larger than 2-3 TeV depending on the seesaw scale and the
spharelon rate. Together with multi-TeV Z-prime, large sneutrino-antisneutrino
mixing and CP violating phenomena required by TeV leptogenesis could be
searched for in future colliders by observing the distinct same-sign
dilepton--dichargino as well as dislepton--diHiggs signatures.


  In this paper we develop constructive invertibility conditions for the
twisted convolution. Our approach is based on splitting the twisted convolution
with rational parameters into a finite number of weighted convolutions, which
can be interpreted as another twisted convolution on a finite cyclic group. In
analogy with the twisted convolution of finite discrete signals, we derive an
anti-homomorphism between the sequence space and a suitable matrix algebra
which preserves the algebraic structure. In this way, the problem reduces to
the analysis of finite matrices whose entries are sequences supported on
corresponding cosets. The invertibility condition then follows from Cramer's
rule and Wiener's lemma for this special class of matrices. The problem results
from a well known approach of studying the invertibility properties of the
Gabor frame operator in the rational case. The presented approach gives further
insights into Gabor frames. In particular, it can be applied for both the
continuous (on $\Rd$) and the finite discrete setting. In the latter case, we
obtain algorithmic schemes for directly computing the inverse of Gabor
frame-type matrices equivalent to those known in the literature.


  Using a simple model based on the knowledge of spherical and deformed
Woods-Saxon potentials, it is shown that the recent observation of halo
phenomena in $^{29}$F can be interpreted as an evidence for the prolate
deformation of the ground state of $^{29}$F. The prolate deformation is the
result of the shell structure, which is unique in one-neutron resonant levels,
in particular near degeneracy of the neutron 1$f_{7/2}$ and 2$p_{3/2}$ resonant
levels, together with the strong preference of prolate shape by the proton
number $Z$ = 9. On the other hand, in oxygen isotopes spherical shape is so
much favored by the proton number $Z$ = 8 that the presence of possible neutron
shell-structure may not make the system deformed. Thus, the strong preference
of particular shape by the proton numbers 8 and 9, respectively, together with
a considerable amount of the energy difference between the neutron $1d_{3/2}$
and $2s_{1/2}$ orbits in oxygen isotopes seems to play an important role in the
phenomena of oxygen neutron drip line anomaly, as was suggested by H. Sakurai
{\it et al.} in 1999.


  Methods such as non-intrusive polynomial chaos (NIPC), and stochastic
collocation are frequently used for uncertainty propagation problems.
Particularly for low-dimensional problems, these methods often use a
tensor-product grid for sampling the space of uncertain inputs. A limitation of
this approach is that it encounters a significant challenge: the number of
sample points grows exponentially with the increase of uncertain inputs.
Current strategies to mitigate computational costs abandon the tensor structure
of sampling points, with the aim of reducing their overall count.
Contrastingly, our investigation reveals that preserving the tensor structure
of sample points can offer distinct advantages in specific scenarios. Notably,
by manipulating the computational graph of the targeted model, it is feasible
to avoid redundant evaluations at the operation level to significantly reduce
the model evaluation cost on tensor-grid inputs. This paper presents a
pioneering method: Accelerated Model Evaluations on Tensor grids using
Computational graph transformations (AMTC). The core premise of AMTC lies in
the strategic modification of the computational graph of the target model to
algorithmically remove the repeated evaluations on the operation level. We
implemented the AMTC method within the compiler of a new modeling language
called the Computational System Design Language (CSDL). We demonstrate the
effectiveness of AMTC by using it with the full-grid NIPC method to solve four
low-dimensional UQ problems involving an analytical piston model, a
multidisciplinary unmanned aerial vehicle design model, a multi-point air taxi
mission analysis model, and a single-disciplinary rotor model, respectively.
For three of the four test problems, AMTC reduces the model evaluation cost by
between 50% and 90%, making the full-grid NIPC the most efficacious method to
use among the UQ methods implemented.


  Given a Banach space $X$, a $w^*$-compact subset of $X^*$, and $1<p<\infty$,
we provide an optimal relationship between the Szlenk index of $K$ and the
Szlenk index of an associated subset of $L_p(X)^*$. As an application, given a
Banach space $X$, we prove an optimal estimate of the Szlenk index of $L_p(X)$
in terms of the Szlenk index of $X$. This extends a result of H\'ajek and
Schlumprecht to uncountable ordinals. More generally, given an operator $A:X\to
Y$, we provide an estimate of the Szlenk index of the "pointwise $A$" operator
$A_p:L_p(X)\to L_p(Y)$ in terms of the Szlenk index of $A$.


  In the non-linear optical process of type-II spontaneous parametric
down-conversion, we present on an experiment showing that the two-photon
detection amplitude of the down-converted beams does not generally reproduce
the transverse profile of the pump beam that carries non-zero orbital angular
momentum. We explain this observation by that orbital angular momentum is not
conserved in the type-II non-linear process due to the broken rotational
symmetry of the Hamiltonian.


  Measurements of normalised cross sections for the production of photons and
neutrons at very small angles with respect to the proton beam direction in
deep-inelastic $ep$ scattering at HERA are presented as a function of the
Feynman variable $x_F$ and of the centre-of-mass energy of the virtual
photon-proton system $W$. The data are taken with the H1 detector in the years
2006 and 2007 and correspond to an integrated luminosity of $131
\mathrm{pb}^{-1}$. The measurement is restricted to photons and neutrons in the
pseudorapidity range $\eta>7.9$ and covers the range of negative four momentum
transfer squared at the positron vertex $6<Q^2<100$ GeV$^2$, of inelasticity
$0.05<y<0.6$ and of $70<W<245 $GeV. To test the Feynman scaling hypothesis the
$W$ dependence of the $x_F$ dependent cross sections is investigated.
Predictions of deep-inelastic scattering models and of models for hadronic
interactions of high energy cosmic rays are compared to the measured cross
sections.


  We have achieved (001) oriented L10 (Fe1-xCux)55Pt45 thin films, with
magnetic anisotropy up to 3.6x10^7 erg/cm^3, using atomic-scale multilayer
sputtering and post annealing at 400 {\deg}C for 10 seconds. By fixing the Pt
concentration, structure and magnetic properties are systematically tuned by
the Cu addition. Increasing Cu content results in an increase in the tetragonal
distortion of the L10 phase, significant changes to the film microstructure,
and lowering of the saturation magnetization and anisotropy. The relatively
convenient synthesis conditions, along with the tunable magnetic properties,
make such materials highly desirable for future magnetic recording
technologies.


  We investigate the problem of localization of gauge fields within the 5D
standing wave braneworld model and show that in the case of increasing warp
factor there exist normalizable vector field zero modes on the brane.


  We review the DPD sum rules and establish their validity to all orders in
QCD. This is done using a diagrammatic approach and light-front perturbation
theory. In the process we furthermore investigate the QCD evolution of double
parton distributions and obtain sum rules for $1\to2$ splitting kernels in
close analogy to the DPD sum rules themselves.


  Stacking fault energy (SFE) is an essential parameter for characterizing
mechanical properties. However, in high entropy alloys (HEAs), the local
chemical environment varies significantly across different stacking fault
planes, resulting in a substantial fluctuation of SFE values rather than a
unique value, which prohibits the prediction of the local SFE. Herein, we
proposed an effective descriptor based on the local concentration ratio near
stacking fault to quantitatively predict the local SFE of refractory HEAs. We
find that the role of a given element in determining SFE strongly depends on
its valence-electron number relative to other components and the contribution
of its s- and d-electrons to its cohesive properties, which can be understood
in the framework of the tight-binding model. Notably, the descriptor not only
unifies the local nature of SFE from simple alloys to HEAs but also helps to
quickly design HEAs as the involved parameters are easily accessible.


  It is shown that the two dimensional gravity, described either in the
conformal gauge (the Liouville theory) or in the light cone gauge, when coupled
to matter possesses an infinite number of twisted $N=2$ superconformal
symmetries. The central charges of the $N=2$ algebra for the two gauge choices
are in general different. Further, it is argued that the physical states in the
light cone gauge theory can be obtained from the Liouville theory by a field
redefinition.


  The enormous quantity of data produced every day together with advances in
data analytics has led to a proliferation of data management and analysis
systems. Typically, these systems are built around highly specialized
monolithic operators optimized for the underlying hardware. While effective in
the short term, such an approach makes the operators cumbersome to port and
adapt, which is increasingly required due to the speed at which algorithms and
hardware evolve. To address this limitation, we present Modularis, an execution
layer for data analytics based on sub-operators, i.e.,composable building
blocks resembling traditional database operators but at a finer granularity. To
demonstrate the advantages of our approach, we use Modularis to build a
distributed query processing system supporting relational queries running on an
RDMA cluster, a serverless cloud platform, and a smart storage engine.
Modularis requires minimal code changes to execute queries across these three
diverse hardware platforms, showing that the sub-operator approach reduces the
amount and complexity of the code. In fact, changes in the platform affect only
sub-operators that depend on the underlying hardware. We show the end-to-end
performance of Modularis by comparing it with a framework for SQL processing
(Presto), a commercial cluster database (SingleStore), as well as
Query-as-a-Service systems (Athena, BigQuery). Modularis outperforms all these
systems, proving that the design and architectural advantages of a modular
design can be achieved without degrading performance. We also compare Modularis
with a hand-optimized implementation of a join for RDMA clusters. We show that
Modularis has the advantage of being easily extensible to a wider range of join
variants and group by queries, all of which are not supported in the hand-tuned
join.


  We find a thermodynamic description of gas-liquid criticality that is
different from van der Waals and mean-field theories. At the critical
temperature there is no critical point; a liquid phase coexists with a vapor
phase with densities determined by an intersection of 2nd-order percolation
transition loci. There is a line of critical states of constant chemical
potential at temperatures above which there exists a supercritical mesophase,
and below which there is the familiar two-phase liquid-vapor coexistence
region.


  The charge transfer from an adatom to a semiconductor substrate of
one-dimensional quantum dot array is evaluated theoretically. Due to the Van
Hove singularity in the density of electron states at the band edges, the
charge transfer decay rate is enhanced nonanalytically in terms of the coupling
constant $g$ as $g^{4/3}$. The optical absorption spectrum for the ionization
of a core level electron of the adatom to the conduction band is also
calculated. The reversible non-Markovian process and irreversible Markovian
process in the time evolution of the adatom localized state manifest themselves
in the absorption spectrum through the branch point and pole contributions,
respectively.


  Consider the thin-film equation $h_t + \left(h h_{yyy}\right)_y = 0$ with a
zero contact angle at the free boundary, that is, at the triple junction where
liquid, gas, and solid meet. Previous results on stability and well-posedness
of this equation have focused on perturbations of equilibrium-stationary or
self-similar profiles, the latter eventually wetting the whole surface. These
solutions have their counterparts for the second-order porous-medium equation
$h_t - (h^m)_{yy} = 0$, where $m > 1$ is a free parameter. Both porous-medium
and thin-film equation degenerate as $h \searrow 0$, but the porous-medium
equation additionally fulfills a comparison principle while the thin-film
equation does not.
  In this note, we consider traveling waves $h = \frac V 6 x^3 + \nu x^2$ for
$x \ge 0$, where $x = y-V t$ and $V, \nu \ge 0$ are free parameters. These
traveling waves are receding and therefore describe de-wetting, a phenomenon
genuinely linked to the fourth-order nature of the thin-film equation and not
encountered in the porous-medium case as it violates the comparison principle.
The linear stability analysis leads to a linear fourth-order
degenerate-parabolic operator for which we prove maximal-regularity estimates
to arbitrary orders of the expansion in $x$ in a right-neighborhood of the
contact line $x = 0$. This leads to a well-posedness and stability result for
the corresponding nonlinear equation. As the linearized evolution has different
scaling as $x \searrow 0$ and $x \to \infty$, the analysis is more intricate
than in related previous works. We anticipate that our approach is a natural
step towards investigating other situations in which the comparison principle
is violated, such as droplet rupture.


  This short paper gives a model for and a proof of completeness of the NRB
verification logic for deterministic imperative programs, the logic having been
used in the past as the basis for automated semantic checks of large,
fast-changing, open source C code archives, such as that of the Linux kernel
source. The model is a colored state transitions model that approximates from
above the set of transitions possible for a program. Correspondingly, the logic
catches all traces that may trigger a particular defect at a given point in the
program, but may also flag false positives.


  Deep surveys conducted during the past decades have shown that galaxies in
the distant universe are generally of more irregular shapes, and are disky in
appearance and in their star formation rate, compared to galaxies in similar
environments in the nearby universe. Given that the merger rate between z=2 and
the local universe is far from adequate to account for this observed
morphological transformation rate, an internal mechanism for the morphological
transformation of galaxies is to be sought, whose operation can be further
aided by environmental factors. The secular evolution mechanism, especially
with the discovery of a collisionless dissipation mechanism for stars within
the secular evolution paradigm, has provided just such a framework for
understanding the morphological evolution of galaxies across the Hubble time.
In this paper we will summarize the past theoretical results on the dynamical
mechanisms for secular evolution, and highlight new results in the analysis of
the observational data, which confirmed that density waves in physical galaxies
possess the kind of characteristics which could produce the observed rates of
morphological transformation for both cluster and field galaxies.


  A new elementary proof for a theorem of D. Burns and S. Krantz on the
rigidity of the analytic self maps of the unit disc was recently discovered by
L. Baracco, D. Zaitsev, and G. Zampieri. We use their argument to generalize
Burns-Krantz theorems on the unit disc and on the unit ball of ${\mathbb C}^n$.


  We study a nonzero-sum game of two players which is a generalization of the
antagonistic noisy duel of discrete type. The game is considered from the point
of view of various criterions of optimality. We prove existence of
epsilon-equilibrium situations and show that the epsilon-equilibrium strategies
that we have found are epsilon-maxmin. Conditions under which the equilibrium
plays are Pareto-optimal are given.
  Keywords: noisy duel, payoff function, strategy, equilibrium situation,
Pareto optimality, the value of a game.


  We investigated travelling waves appearing as the primary pattern-forming
instability in the nematic Phase 5 (Merck) in the planar geometry in order to
test the recently developed weak electrolyte model of ac-driven
electroconvection [M. Treiber and L. Kramer, Mol. Cryst. Liq. Cryst 261, 311
(1995)]. Travelling waves are observed over the full conductive range of
applied frequencies for three cells of different layer thickness d. We also
measured the elastic constants, the electric conductivity, and the dielectric
constant. The other parameters of Phase 5 are known, apart from the (relatively
unimportant) viscosity $\alpha_1$ and the two parameters of the weak
electrolyte model that are proportional to the geometric mean of the
mobilities, and the recombination rate, respectively. Assuming a sufficiently
small recombination rate, the predicted dependence of the frequency of the
travelling waves at onset (Hopf frequency) on d and on the applied frequency
agreed quantitatively with the experiments, essentially without fit parameters.
The absolute value of the Hopf frequency implies that the geometric mean of the
mobilities amounts to $1.1 \times 10^{-10} m^2/(Vs)$.


  Iterative Proportional Fitting (IPF), combined with EM, is commonly used as
an algorithm for likelihood maximization in undirected graphical models. In
this paper, we present two iterative algorithms that generalize upon IPF. The
first one is for likelihood maximization in discrete chain factor graphs, which
we define as a wide class of discrete variable models including undirected
graphical models and Bayesian networks, but also chain graphs and sigmoid
belief networks. The second one is for conditional likelihood maximization in
standard undirected models and Bayesian networks. In both algorithms, the
iteration steps are expressed in closed form. Numerical simulations show that
the algorithms are competitive with state of the art methods.


  The density fluctuation spectrum in the solar wind reveals a Kolmogorov-like
scaling with a spectral slope of -5/3 in wavenumber space. The energy transfer
process in the magnetized solar wind, characterized typically by MHD
turbulence, over extended length-scales remains an unresolved paradox of modern
turbulence theories, raising the question of how a compressible magnetofluid
exhibits a turbulent spectrum that is characteristic of an incompressible
hydrodynamic fluid. To address these questions, we have undertaken
three-dimensional time dependent numerical simulations of a compressible
magnetohydrodynamic fluid describing super-Alfv\'enic, supersonic and strongly
magnetized plasma fluid. It is shown that a Kolmogorov-like density spectrum
can develop by plasma motions that are dominated by Alfv\'enic cascades whereas
compressive modes are dissipated.


  We show theoretically that the strong coupling of circularly polarized
photons to an exciton in ring-like semiconductor nanostructures results in
physical nonequivalence of clockwise and counterclockwise exciton rotations in
the ring. As a consequence, the stationary energy splitting of exciton states
corresponding to these mutually opposite rotations appears. This excitonic
Aharonov-Bohm effect depends on the intensity and frequency of the circularly
polarized field and can be detected in state-of-the-art optical experiments.


  Nuclei in the $^{135}$I region have been identified as being a possible
bottleneck for the \textit{i} process. Here we present an indirect measurement
for the Maxwellian-averaged cross section of $^{126}\text{Sb}(n,\gamma)$. The
nuclear level density and the $\gamma$-ray strength function of $^{127}$Sb have
been extracted from $^{124}$Sn$(\alpha,p\gamma)^{127}$Sb data using the Oslo
method. The level density in the low-excitation-energy region agrees well with
known discrete levels, and the higher-excitation-energy region follows an
exponential curve compatible with the constant-temperature model. The strength
function between $E_\gamma\approx$ 1.5-8.0 MeV presents several features, such
as an upbend and a possibly double-peaked pygmy-like structure. None of the
theoretical models included in the nuclear reaction code TALYS seem to
reproduce the experimental data. The Maxwellian-averaged cross section for the
$^{126}$Sb$(n,\gamma)^{127}$Sb reaction has been experimentally constrained by
using our level-density and strength-function data as input to TALYS. We
observe a good agreement with the JINA REACLIB, TENDL, and BRUSLIB libraries,
while the ENDF/B-VIII.0 library predicts a significantly higher rate than our
results.


  We show that in case a pushdown system is bisimulation equivalent to a finite
system, there is already a bisimulation equivalent finite system whose size is
elementarily bounded in the description size of the pushdown system. As a
consequence we obtain that it is elementarily decidable if a given pushdown
system is bisimulation equivalent to some finite system. This improves a
previously best-known ACKERMANN upper bound for this problem.


  We present Zar: a formally verified compiler pipeline from discrete
probabilistic programs with unbounded loops in the conditional probabilistic
guarded command language (cpGCL) to proved-correct executable samplers in the
random bit model. We exploit the key idea that all discrete probability
distributions can be reduced to unbiased coin-flipping schemes. The compiler
pipeline first translates a cpGCL program into choice-fix trees, an
intermediate representation suitable for reduction of biased probabilistic
choices. Choice-fix trees are then translated to coinductive interaction trees
for execution within the random bit model. The correctness of the composed
translations establishes the sampling equidistribution theorem: compiled
samplers are correct wrt. the conditional weakest pre-expectation semantics of
cpGCL source programs. Zar is implemented and fully verified in the Coq proof
assistant. We extract verified samplers to OCaml and Python and empirically
validate them on a number of illustrative examples.


  In nonrelativistic limits for states labeled by minimum packets with
constrained spatial spreads and over a short term, states of unconstrained
quantum field theories evolve on trajectories described by Newton's equations
for the $1/r^2$ force. These states include bound solutions in the attractive
force case.


  Real world datasets often contain entries with missing elements e.g. in a
medical dataset, a patient is unlikely to have taken all possible diagnostic
tests. Variational Autoencoders (VAEs) are popular generative models often used
for unsupervised learning. Despite their widespread use it is unclear how best
to apply VAEs to datasets with missing data. We develop a novel latent variable
model of a corruption process which generates missing data, and derive a
corresponding tractable evidence lower bound (ELBO). Our model is
straightforward to implement, can handle both missing completely at random
(MCAR) and missing not at random (MNAR) data, scales to high dimensional inputs
and gives both the VAE encoder and decoder principled access to indicator
variables for whether a data element is missing or not. On the MNIST and SVHN
datasets we demonstrate improved marginal log-likelihood of observed data and
better missing data imputation, compared to existing approaches.


  Accurate and reliable probabilistic forecasts of hydrological quantities like
runoff or water level are beneficial to various areas of society. Probabilistic
state-of-the-art hydrological ensemble prediction models are usually driven
with meteorological ensemble forecasts. Hence, biases and dispersion errors of
the meteorological forecasts cascade down to the hydrological predictions and
add to the errors of the hydrological models. The systematic parts of these
errors can be reduced by applying statistical post-processing. For a sound
estimation of predictive uncertainty and an optimal correction of systematic
errors, statistical post-processing methods should be tailored to the
particular forecast variable at hand. Former studies have shown that it can
make sense to treat hydrological quantities as bounded variables. In this
paper, a doubly truncated Bayesian model averaging (BMA) method, which allows
for flexible post-processing of (multi-model) ensemble forecasts of water
level, is introduced. A case study based on water level for a gauge of river
Rhine, reveals a good predictive skill of doubly truncated BMA compared both to
the raw ensemble and the reference ensemble model output statistics approach.


  This paper investigates the problem of online prediction learning, where
learning proceeds continuously as the agent interacts with an environment. The
predictions made by the agent are contingent on a particular way of behaving,
represented as a value function. However, the behavior used to select actions
and generate the behavior data might be different from the one used to define
the predictions, and thus the samples are generated off-policy. The ability to
learn behavior-contingent predictions online and off-policy has long been
advocated as a key capability of predictive-knowledge learning systems but
remained an open algorithmic challenge for decades. The issue lies with the
temporal difference (TD) learning update at the heart of most prediction
algorithms: combining bootstrapping, off-policy sampling and function
approximation may cause the value estimate to diverge. A breakthrough came with
the development of a new objective function that admitted stochastic gradient
descent variants of TD. Since then, many sound online off-policy prediction
algorithms have been developed, but there has been limited empirical work
investigating the relative merits of all the variants. This paper aims to fill
these empirical gaps and provide clarity on the key ideas behind each method.
We summarize the large body of literature on off-policy learning, focusing on
1- methods that use computation linear in the number of features and are
convergent under off-policy sampling, and 2- other methods which have proven
useful with non-fixed, nonlinear function approximation. We provide an
empirical study of off-policy prediction methods in two challenging
microworlds. We report each method's parameter sensitivity, empirical
convergence rate, and final performance, providing new insights that should
enable practitioners to successfully extend these new methods to large-scale
applications.[Abridged abstract]


  We construct a model of high energy heavy ion collisions as two
ultrarelativistic shock waves colliding in AdS_5. We point out that shock waves
corresponding to physical energy-momentum tensors of the nuclei completely stop
almost immediately after the collision in AdS_5, which, on the field theory
side, corresponds to complete nuclear stopping due to strong coupling effects,
likely leading to Landau hydrodynamics. Since in real-life heavy ion collisions
the large Bjorken x part of nuclear wave functions continues to move along the
light cone trajectories of the incoming nuclei leaving the small-x partons
behind, we conclude that a pure large coupling approach is not likely to
adequately model nuclear collisions. We show that to account for small-coupling
effects one can model the colliding nuclei by two (unphysical)
ultrarelativistic shock waves with zero net energy each (but with non-zero
energy density). We use this model to study the energy density of the
strongly-coupled matter created immediately after the collision. We argue that
expansion of the energy density in the powers of proper time squared
corresponds on the gravity side to a perturbative expansion of the metric in
graviton exchanges. Using such expansion we reproduce our earlier result that
the energy density of produced matter at mid-rapidity starts out as a constant
(of time) in heavy ion collisions at large coupling.


  We study the full counting statistics for interacting quantum many-body spin
systems weakly coupled to the environment. In the leading order in the
system-bath coupling we derive exact spin current statistics for a large class
of parity symmetric spin-1/2 systems driven by a pair of Markovian baths with
local coupling operators. Interestingly, in this class of systems the leading
order current statistics are universal and do not depend on details of the
Hamiltonian. Furthermore, in the specific case of symmetrically boundary driven
anisotropic Heisenberg ($XXZ$) spin 1/2 chain we derive explicitly the
third-order non-linear corrections to the current statistics.


  When a parameter quench is performed in an isolated quantum system with a
complete set of constants of motion, its out of equilibrium dynamics is
considered to be well captured by the Generalized Gibbs Ensemble (GGE),
characterized by a set $\{\lambda_\alpha\}$ of coefficients related to the
constants of motion. We determine the most elementary GGE deviation from the
equilibrium distribution that leads to detectable effects. By quenching a
suitable local attractive potential in a one-dimensional electron system, the
resulting GGE differs from equilibrium by only one single $\lambda_{\alpha}$,
corresponding to the emergence of an only partially occupied bound state lying
below a fully occupied continuum of states. The effect is shown to induce
optical gain, i.e., a negative peak in the absorption spectrum, indicating the
stimulated emission of radiation, enabling one to identify GGE signatures in
fermionic systems through optical measurements. We discuss the implementation
in realistic setups.


  We examine the case for Quark-Novae (QNe) as possible sources for the
reionization and early metal enrichment of the universe. Quark-Novae are
predicted to arise from the explosive collapse (and conversion) of sufficiently
massive neutron stars into quark stars. A Quark-Nova (QN) can occur over a
range of time scales following the supernova event. For QNe that arise days to
weeks after the supernovae, we show that dual-shock that arises as the QN
ejecta encounter the supernova ejecta can produce enough photons to reionize
hydrogen in most of the Inter-Galactic medium (IGM) by z ~ 6. Such events can
explain the large optical depth tau_e ~ 0.1 as measured by WMAP, if the
clumping factor, C, of the material being ionized is smaller than 10. We
suggest a way in which a normal initial mass function (IMF) for the oldest
stars can be reconciled with a large optical depth as well as the mean
metallicity of the early IGM post reionization. We find that QN also make a
contribution to r-process element abundances for atomic numbers A > 130. We
predict that the main cosmological signatures of Quark-Novae are the gamma-ray
bursts that announce their birth. These will be clustered at redshifts in the
range z ~ 7-8 in our model.


  Exploring the potential application of quantum computers in material design
and drug discovery has attracted a lot of interest in the age of quantum
computing. However, the quantum resource requirement for solving practical
electronic structure problems are far beyond the capacity of near-term quantum
devices. In this work, we integrate the divide-and-conquer (DC) approaches into
the variational quantum eigensolver (VQE) for large-scale quantum computational
chemistry simulations. Two popular divide-and-conquer schemes, including
many-body expansion~(MBE) fragmentation theory and density matrix embedding
theory~(DMET), are employed to divide complicated problems into many small
parts that are easy to implement on near-term quantum computers. Pilot
applications of these methods to systems consisting of tens of atoms are
performed with adaptive VQE algorithms. This work should encourage further
studies of using the philosophy of DC to solve electronic structure problems on
quantum computers.


  We study the transport coefficients, damping rates and mean free paths of
soft fermion collective excitations in a hot fermion-gauge-scalar plasma with
the goal of understanding the main physical mechanisms that determine transport
of chirality in scenarios of non-local electroweak baryogenesis. The focus is
on identifying the different transport coefficients for the different branches
of soft collective excitations of the fermion spectrum. These branches
correspond to collective excitations with opposite ratios of chirality to
helicity and different dispersion relations. By combining results from the hard
thermal loop (HTL) resummation program with a novel mechanism of fermion
damping through heavy scalar decay, we obtain a robust description of the
different damping rates and mean free paths for the soft collective excitations
to leading order in HTL and lowest order in the Yukawa coupling. The space-time
evolution of wave packets of collective excitations unambiguously reveals the
respective mean free paths. We find that whereas both the gauge and scalar
contribution to the damping rates are different for the different branches, the
difference of mean free paths for both branches is mainly determined by the
decay of the heavy scalar into a hard fermion and a soft collective excitation.
We argue that these mechanisms are robust and are therefore relevant for
non-local scenarios of baryogenesis either in the Standard Model or extensions
thereof.


  We study the impact of mass-transfer physics on the observable properties of
binary black hole populations formed through isolated binary evolution. We
investigate the impact of mass-accretion efficiency onto compact objects and
common-envelope efficiency on the observed distributions of $\chi_{eff}$,
$M_{chirp}$ and $q$. We find that low common envelope efficiency translates to
tighter orbits post common envelope and therefore more tidally spun up
second-born black holes. However, these systems have short merger timescales
and are only marginally detectable by current gravitational-waves detectors as
they form and merge at high redshifts ($z\sim 2$), outside current detector
horizons. Assuming Eddington-limited accretion efficiency and that the
first-born black hole is formed with a negligible spin, we find that all
non-zero $\chi_{eff}$ systems in the detectable population can come only from
the common envelope channel as the stable mass-transfer channel cannot shrink
the orbits enough for efficient tidal spin-up to take place. We find the local
rate density ($z\simeq 0.01$) for the common envelope channel is in the range
$\sim 17-113~Gpc^{-3}yr^{-1}$ considering a range of $\alpha_{CE} \in
[0.2,5.0]$ while for the stable mass transfer channel the rate density is $\sim
25~Gpc^{-3}yr^{-1}$. The latter drops by two orders of magnitude if the mass
accretion onto the black hole is not Eddington limited because conservative
mass transfer does not shrink the orbit as efficiently as non-conservative mass
transfer does. Finally, using GWTC-2 events, we constrain the lower bound of
branching fraction from other formation channels in the detected population to
be $\sim 0.2$. Assuming all remaining events to be formed through either stable
mass transfer or common envelope channels, we find moderate to strong evidence
in favour of models with inefficient common envelopes.


  Sequential recommendation systems aim to provide personalized recommendations
by analyzing dynamic preferences and dependencies within user behavior
sequences. Recently, Transformer models can effectively capture user
preferences. However, their quadratic computational complexity limits
recommendation performance on long interaction sequence data. Inspired by the
State Space Model (SSM)representative model, Mamba, which efficiently captures
user preferences in long interaction sequences with linear complexity, we find
that Mamba's recommendation effectiveness is limited in short interaction
sequences, with failing to recall items of actual interest to users and
exacerbating the data sparsity cold start problem. To address this issue, we
innovatively propose a new model, MaTrRec, which combines the strengths of
Mamba and Transformer. This model fully leverages Mamba's advantages in
handling long-term dependencies and Transformer's global attention advantages
in short-term dependencies, thereby enhances predictive capabilities on both
long and short interaction sequence datasets while balancing model efficiency.
Notably, our model significantly improves the data sparsity cold start problem,
with an improvement of up to 33% on the highly sparse Amazon Musical
Instruments dataset. We conducted extensive experimental evaluations on five
widely used public datasets. The experimental results show that our model
outperforms the current state-of-the-art sequential recommendation models on
all five datasets. The code is available at
https://github.com/Unintelligentmumu/MaTrRec.


  In this paper, we consider supervised learning problems such as logistic
regression and study the stochastic gradient method with averaging, in the
usual stochastic approximation setting where observations are used only once.
We show that after $N$ iterations, with a constant step-size proportional to
$1/R^2 \sqrt{N}$ where $N$ is the number of observations and $R$ is the maximum
norm of the observations, the convergence rate is always of order
$O(1/\sqrt{N})$, and improves to $O(R^2 / \mu N)$ where $\mu$ is the lowest
eigenvalue of the Hessian at the global optimum (when this eigenvalue is
greater than $R^2/\sqrt{N}$). Since $\mu$ does not need to be known in advance,
this shows that averaged stochastic gradient is adaptive to \emph{unknown
local} strong convexity of the objective function. Our proof relies on the
generalized self-concordance properties of the logistic loss and thus extends
to all generalized linear models with uniformly bounded features.


  The Atacama Cosmology Telescope (ACT) is currently observing the cosmic
microwave background with arcminute resolution at 148 GHz, 218 GHz, and 277
GHz. In this paper, we present ACT's first results. Data have been analyzed
using a maximum-likelihood map-making method which uses B-splines to model and
remove the atmospheric signal. It has been used to make high-precision beam
maps from which we determine the experiment's window functions. This beam
information directly impacts all subsequent analyses of the data. We also used
the method to map a sample of galaxy clusters via the Sunyaev-Zel'dovich (SZ)
effect, and show five clusters previously detected with X-ray or SZ
observations. We provide integrated Compton-y measurements for each cluster. Of
particular interest is our detection of the z = 0.44 component of A3128 and our
current non-detection of the low-redshift part, providing strong evidence that
the further cluster is more massive as suggested by X-ray measurements. This is
a compelling example of the redshift-independent mass selection of the SZ
effect.


  Recent years have witnessed the advancement of deep learning vision
technologies and applications in the medical industry. Intelligent devices for
special medication management are in great need of, which requires more precise
detection algorithms to identify the specifications and locations. In this
work, YOLO (You only look once) based object detectors are tailored for toxic
and narcotic medications detection tasks. Specifically, a more flexible
annotation with rotated degree ranging from $0^\circ$ to $90^\circ$ and a
mask-mapping-based non-maximum suppression method are proposed to achieve a
feasible and efficient medication detector aiming at arbitrarily oriented
bounding boxes. Extensive experiments demonstrate that the rotated YOLO
detectors are more suitable for identifying densely arranged drugs. The best
shot mean average precision of the proposed network reaches 0.811 while the
inference time is less than 300ms.


  In contrast to the water-poor inner solar system planets, stochasticity
during planetary formation and order of magnitude deviations in exoplanet
volatile contents suggest that rocky worlds engulfed in thick volatile ice
layers are the dominant family of terrestrial analogues among the extrasolar
planet population. However, the distribution of compositionally Earth-like
planets remains insufficiently constrained, and it is not clear whether the
solar system is a statistical outlier or can be explained by more general
planetary formation processes. Here we employ numerical models of planet
formation, evolution, and interior structure, to show that a planet's bulk
water fraction and radius are anti-correlated with initial $^{26}$Al levels in
the planetesimal-based accretion framework. The heat generated by this
short-lived radionuclide rapidly dehydrates planetesimals prior to accretion
onto larger protoplanets and yields a system-wide correlation of planet bulk
abundances, which, for instance, can explain the lack of a clear orbital trend
in the water budgets of the TRAPPIST-1 planets. Qualitatively, our models
suggest two main scenarios of planetary systems' formation: high-$^{26}$Al
systems, like our solar system, form small, water-depleted planets, whereas
those devoid of $^{26}$Al predominantly form ocean worlds, where the mean
planet radii between both scenarios deviate by up to about 10%.


  We present a deep UBI CCD survey using the Palomar 5-m telescope of a sample
of high X-ray luminosity, distant clusters selected from the ROSAT All-Sky
Survey. The 10 clusters lie at z=0.22-0.28, an era where evolutionary effects
have been reported in the properties of cluster galaxy populations. Our
clusters thus provide a well-defined sample of the most massive systems at
these redshifts to quantify the extent and variability of these evolutionary
effects. Moreover, by concentrating on a narrow redshift range, we can take
advantage of the homogeneity of our sample to combine the catalogues from all
the clusters to analyse the bulk properties of their populations. The core
regions of these clusters ontain only a small proportion of star-forming
galaxies, and they therefore do not exhibit a `Butcher-Oemler' effect. Focusing
on the redder cluster galaxies we find that their integrated luminosity is well
correlated with the cluster X-ray temperatures, and hence with cluster mass.
Furthermore, the typical UV-optical colours of the elliptical sequences in the
clusters exhibit a small cluster-to-cluster scatter, <=2%, indicating that
these galaxies are highly homogeneous between clusters. However, at fainter
magnitudes we observe an increase in the range of mid-UV colours of galaxies
possessing strong 4000A breaks. In the light of the apparent decline in the S0
populations of z>=0.4 clusters (Dressler et al. 1997), and in view of the
luminosities and colours of this population, we propose that they may be the
progenitors of the S0 population of local rich clusters, caught in the final
stage before they become completely quiescent. [abridged]


  An action for the ten-dimensional Green-Schwarz superstring with N=2
worldsheet superconformal invariance has recently been used to calculate
superstring scattering amplitudes and prove their finiteness. In this paper, it
is shown that the N=2 stress-energy tensor for this Green-Schwarz action can be
constructed out of the stress-energy tensor and ghosts of the Neveu-
Schwarz-Ramond action by the standard twisting procedure. In other words, a
field redefinition is found from the GS matter fields into the NSR matter and
ghost fields which transforms the matter part of the two fermionic GS super-
conformal generators into the $b$ ghost and shifted BRST current of the NSR
string. In light-cone gauge, this field redefinition reduces to the usual one
relating the light-cone GS and NSR fields.
  Although this proves the equivalence of physical vertex operators in the two
superstring formalisms, multiloop amplitudes are easier to calculate using the
Green-Schwarz formalism since manifest spacetime supersymmetry eliminates the
need for spin cuts, GSO projections, and cutoffs in moduli space.


  Usually, it's difficult for us to observe the Compton Scattering in an atom.
One way to overcome this difficult is using multi-photon collide with an atom,
which will come into being multi-photon Compton Scattering (MCS) phenomenon.
Thus, we can investigate the MCS process in visible light region. During the
MCS process, the cluster atoms moving as a whole, namely atomic Dicke states,
the multi-photon interacting with cluster atoms. We can observe a significant
Doppler shift of resonant fluorescence spectrum(RFS)in a room-temperature
two-levelatomic system. In this paper, we present a detail analysis of the
physics mechanism of the Doppler shift and propose a method to measure the
component of the Dicke states (the atomic polymers with different masses)by
using the Doppler shift of the RFS.


  This paper presents a bibliometric analysis that examines the works cited in,
as well as those citing, NIME papers; for brevity, we refer to these as
`references` and `citations`. Utilizing existing tools, we have computationally
extracted data from the NIME proceedings archive and retrieved metadata from an
academic database, including details of associated references and citations.
From this data, we computed a range of metrics and statistics, which we present
in this paper. We offer quantitative insights into NIME as a scholarly
publication venue, its connections to other venues, and its relationship with
various fields of study and authors. Based on our data interpretations, we
provide several recommendations for the community's future. In sharing the
software we developed for this study, and the summarized raw data, we enable
other NIME researchers to conduct more in-depth investigations and examine
specific trends.


  In this talk I briefly review the main ideas and challenges involved in the
computation of the baryon asymmetry of the Universe. (Invited talk given at
``The Birth of the Universe and Fundamental Physics'', Rome, May 18--21, 1994.)


  Evaluation of predictive deep learning (DL) models beyond conventional
performance metrics has become increasingly important for applications in
sensitive environments like healthcare. Such models might have the capability
to encode and analyse large sets of data but they often lack comprehensive
interpretability methods, preventing clinical trust in predictive outcomes.
Quantifying uncertainty of a prediction is one way to provide such
interpretability and promote trust. However, relatively little attention has
been paid to how to include such requirements into the training of the model.
In this paper we: (i) quantify the data (aleatoric) and model (epistemic)
uncertainty of a DL model for Cardiac Resynchronisation Therapy response
prediction from cardiac magnetic resonance images, and (ii) propose and perform
a preliminary investigation of an uncertainty-aware loss function that can be
used to retrain an existing DL image-based classification model to encourage
confidence in correct predictions and reduce confidence in incorrect
predictions. Our initial results are promising, showing a significant increase
in the (epistemic) confidence of true positive predictions, with some evidence
of a reduction in false negative confidence.


  We present multi-wavelength observations of stellar features in the HI tidal
bridge connecting M81 and M82 in the region called Arp's Loop. We identify
eight young star-forming regions from Galaxy Evolution Explorer ultraviolet
observations. Four of these objects are also detected at H\alpha. We determine
the basic star formation history of Arp's Loop using F475W and F814W images
obtained with the Advanced Camera for Surveys on board the Hubble Space
Telescope. We find both a young (< 10 Myr) and an old (>1 Gyr) stellar
population with a similar spatial distribution and a metallicity Z~0.004. We
suggest that the old stellar population was formed in the stellar disk of M82
and/or M81 and ejected into the intergalactic medium during a tidal passage (~
200-300 Myr ago), whereas the young UV-bright stars have formed in the tidal
debris. The UV luminosities of the eight objects are modest and typical of
small clusters or OB associations. The tidal bridge between M81-M82 therefore
appears to be intermediate between the very low levels of star formation seen
in the Magellanic bridge and actively star-forming tidal tails associated with
major galaxy mergers.


  Let $(G,\Omega)$ be a symplectic Lie group, i.e, a Lie group endowed with a
left invariant symplectic form. If $\G$ is the Lie algebra of $G$ then we call
$(\G,\omega=\Om(e))$ a symplectic Lie algebra. The product $\bullet$ on $\G$
defined by $3\omega\left(x\bullet
y,z\right)=\omega\left([x,y],z\right)+\omega\left([x,z],y\right)$ extends to a
left invariant connection $\na$ on $G$ which is torsion free and symplectic
($\na\Om=0)$. When $\na$ has vanishing curvature, we call $(G,\Omega)$ a flat
symplectic Lie group and $(\G,\om)$ a flat symplectic Lie algebra. In this
paper, we study flat symplectic Lie groups. We start by showing that the
derived ideal of a flat symplectic Lie algebra is degenerate with respect to
$\om$. We show that a flat symplectic Lie group must be nilpotent with
degenerate center. This implies that the connection $\na$ of a flat symplectic
Lie group is always complete. We prove that the double extension process can be
applied to characterize all flat symplectic Lie algebras. More precisely, we
show that every flat symplectic Lie algebra is obtained by a sequence of double
extension of flat symplectic Lie algebras starting from $\{0\}$. As examples in
low dimensions, we classify all flat symplectic Lie algebras of dimension
$\leq6$.


  We have investigated magnetic interactions between transition metal ions in
bismuthene topological insulator with protected edge states. We find that these
topological states have a crucial role on the magnetic interactions in 2D
topological insulators. Using first-principles and model Hamiltonian we make a
comparative study of transition metal doped bulk and nanoribbon bismuthene.
While direct overlap between the transition metal prevails in gapped bulk
bismuthene, at the borders of nanoribbons a long-range magnetism is present.
The exchange interactions are well described by a RKKY-like Hamiltonian
mediated by topological states. Our results show a dominance of
antiferromagnetism promoted by the topological states, preserving the
spin-locked Dirac crossing states due to a global time-reversal symmetry
preservation. This extended magnetic interactions mediated by massless
electrons can increase the spin diffusion length being promising for fast
dissipationless spintronic devices.


  We reexamine the production of J/Psi and other charmonium states for a
variety of target-projectile choices at the SPS, in particular for the
interesting comparison between S+U at 200 GeV/c and Pb+Pb at 158 GeV/c as
observed in the experiments NA38 and NA50 respectively. The result is a
description of the NA38 and NA50 data in terms of a conventional,
quasi-hadronic picture. The apparently anomalous suppression found in the most
massive Pb+Pb system arises in the present simulation from three sources:
destruction in the initial nucleon-nucleon cascade phase, use of coupled
channels to exploit the larger breakup in the less bound Chi and Psi' states,
and comover interaction in the final low energy phase.


  Homodyned K (HK) distribution has been widely used to describe the scattering
phenomena arising in various research fields, such as ultrasound imaging or
optics. In this work, we propose a machine learning based approach to the
estimation of the HK distribution parameters. We develop neural networks that
can estimate the HK distribution parameters based on the signal-to-noise ratio,
skewness and kurtosis calculated using fractional-order moments. Compared to
the previous approaches, we consider the orders of the moments as trainable
variables that can be optimized along with the network weights using the
back-propagation algorithm. Networks are trained based on samples generated
from the HK distribution. Obtained results demonstrate that the proposed method
can be used to accurately estimate the HK distribution parameters.


  For finite quantum many-particle systems modeled with say $m$ fermions in $N$
single particle states and interacting with $k$-body interactions ($k \leq m$),
the wavefunction structure is studied using random matrix theory. Hamiltonian
for the system is chosen to be $H=H_0(t) + \lambda V(k)$ with the unperturbed
$H_0(t)$ Hamiltonian being a $t$-body operator and $V(k)$ a $k$-body operator
with interaction strength $\lambda$. Representing $H_0(t)$ and $V(k)$ by
independent Gaussian orthogonal ensembles (GOE) of random matrices in $t$ and
$k$ fermion spaces respectively, first four moments, in $m$-fermion spaces, of
the strength functions $F_\kappa(E)$ are derived; strength functions contain
all the information about wavefunction structure. With $E$ denoting the $H$
energies or eigenvalues and $\kappa$ denoting unperturbed basis states with
energy $E_\kappa$, the $F_\kappa(E)$ give the spreading of the $\kappa$ states
over the eigenstates $E$. It is shown that the first four moments of
$F_\kappa(E)$ are essentially same as that of the conditional $q$-normal
distribution given in: P.J. Szabowski, Electronic Journal of Probability {\bf
15}, 1296 (2010). This naturally gives asymmetry in $F_\kappa(E)$ with respect
to $E$ as $E_\kappa$ increases and also the peak value changes with $E_\kappa$.
Thus, the wavefunction structure in quantum many-fermion systems with $k$-body
interactions follows in general the conditional $q$-normal distribution.


  We expand asymptotically mean-field solutions of the $p<4$ Potts glass with
various levels of replica-symmetry breaking below the transition temperature to
the glassy phase. We find that the ordered phase is degenerate and solutions
with one hierarchy of spin replicas and with the full continuous
replica-symmetry breaking coexist for $p> p^{*} \approx 2.82$. The latter
emerges immediately with the instability of the replica-symmetric one. Apart
from these two solutions there exists also a succession of unstable states
converging to the solution with the continuous replica-symmetry breaking that
is marginally stable and has the highest free energy.


  We construct an exact metric which at short distances is the metric of
massless particles in 5+1 spacetime (moving along a diameter of the sphere) and
is AdS_3\times S^3 at infinity. We also consider a set of a conical defect
spacetimes which are locally AdS_3\times S^3 and have the masses and charges of
a special set of chiral primaries of the dual orbifold CFT. We find that
excitation energies for a scalar field in the latter geometries agree exactly
with the excitations in the corresponding CFT state created by twist operators:
redshift in the geometry reproduces `long circle' physics in the CFT. We
propose a map of string states in AdS_3\times S^3\times T^4 to states in the
orbifold CFT, analogous to the recently discovered map for AdS_5\times S^5. The
vibrations of the string can be pictured as oscillations of a Fermi sea in the
CFT.


  We analytically calculate the transverse energy fluxes that would be
respectively induced in high-power Airy beams by the Kerr self-focusing and the
Airy profile itself if they were the only active process. In experimental
condition representative of laser filamentation experiments of high-power
ultrashort laser pulses in air and condensed media, the Kerr lens induces
transverse energy fluxes much larger than the Airy "prism" at the main peak. As
a consequence, the curved plasma channels in Airy beams are not only a plasma
spark on a curved focus, but indeed self-guided filaments, and their curved
trajectory appears as a perturbation due to the linear Airy propagation regime.


  Network alignment (NA) is the task of discovering node correspondences across
different networks. Although NA methods have achieved remarkable success in a
myriad of scenarios, their satisfactory performance is not without prior anchor
link information and/or node attributes, which may not always be available. In
this paper, we propose Grad-Align+, a novel NA method using node attribute
augmentation that is quite robust to the absence of such additional
information. Grad-Align+ is built upon a recent state-of-the-art NA method, the
so-called Grad-Align, that gradually discovers only a part of node pairs until
all node pairs are found. Specifically, Grad-Align+ is composed of the
following key components: 1) augmenting node attributes based on nodes'
centrality measures, 2) calculating an embedding similarity matrix extracted
from a graph neural network into which the augmented node attributes are fed,
and 3) gradually discovering node pairs by calculating similarities between
cross-network nodes with respect to the aligned cross-network neighbor-pair.
Experimental results demonstrate that Grad-Align+ exhibits (a) superiority over
benchmark NA methods, (b) empirical validation of our theoretical findings, and
(c) the effectiveness of our attribute augmentation module.


  The critical behaviour of statistical models with long-range interactions
exhibits distinct regimes as a function of $\rho$, the power of the interaction
strength decay. For $\rho$ large enough, $\rho>\rho_{\rm sr}$, the critical
behaviour is observed to coincide with that of the short-range model. However,
there are controversial aspects regarding this picture, one of which is the
value of the short-range threshold $\rho_{\rm sr}$ in the case of the
long-range XY model in two dimensions. We study the 2d XY model on the {\it
diluted} graph, a sparse graph obtained from the 2d lattice by rewiring links
with probability decaying with the Euclidean distance of the lattice as
$|r|^{-\rho}$, which is expected to feature the same critical behavior of the
long range model. Through Monte Carlo sampling and finite-size analysis of the
spontaneous magnetisation and of the Binder cumulant, we present numerical
evidence that $\rho_{\rm sr}=4$. According to such a result, one expects the
model to belong to the Berezinskii-Kosterlitz-Thouless (BKT) universality class
for $\rho\ge 4$, and to present a $2^{nd}$-order transition for $\rho<4$.


  Given a precovering (also called contravariantly finite) class F there are
three natural approaches to a homological dimension with respect to F: One
based on Ext functors relative to F, one based on F-resolutions, and one based
on Schanuel classes relative to F. In general these approaches do not give the
same result. In this paper we study relations between the three approaches
above, and we give necessary and sufficient conditions for them to agree.


  We describe methods to evaluate elementary logarithmic integrals. The
integrand is the product of a rational function and a linear polynomial in ln
x.


  In the layered iron-based superconductor YFe2Ge2, a high Sommerfeld ratio of
~100 mJ/molK^2 and a T^(3/2) temperature dependence of the electrical
resistivity at low temperature T indicate strong electronic correlations and
point towards an unconventional pairing state. We have investigated the role of
composition and annealing conditions in optimizing the growth of high-quality
YFe2Ge2. Our findings confirm that bulk superconductivity is observed in
samples with disorder scattering rates less than 2 k_B T_c/hbar. Fe deficiency
on the Fe site is identified as the dominant source of disorder, which can be
minimised by precipitating from a slightly iron-rich melt, following by
annealing.


  The SPI spectrometer aboard the INTEGRAL mission observes regularly the Crab
Nebula since 2003. We report on observations distributed over 5.5 years and
investigate the variability of the intensity and spectral shape of this
remarkable source in the hard X-rays domain up to a few MeV. While single power
law models give a good description in the X-ray domain (mean photon index ~
2.05) and MeV domain (photon index ~ 2.23), crucial information are contained
in the evolution of the slope with energy between these two values. This study
has been carried out trough individual observations and long duration (~ 400
ks) averaged spectra. The stability of the emission is remarkable and excludes
a single power law model. The slopes measured below and above 100 keV agree
perfectly with the last values reported in the X-ray and MeV regions
respectively, but without indication of a localized break point. This suggests
a gradual softening in the emission around 100 keV and thus a continuous
evolution rather than an actual change in the mechanism parameters. In the MeV
region, no significant deviation from the proposed power law model is visible
up to 5-6 MeV. Finally, we take advantage of the spectroscopic capability of
the instrument to seek for previously reported spectral features in the covered
energy range with negative results for any significant cyclotron or
annihilation emission on 400 ks timescales. Beyond the scientific results, the
performance and reliability of the SPI instrument is explicitly demonstrated,
with some details about the most appropriate analysis method.


  Hutchins, Yuan, M., and Santangelo (2015) proposed the Relative Citation
Ratio (RCR) as a new field-normalized impact indicator. This study investigates
the RCR by correlating it on the level of single publications with established
field-normalized indicators and assessments of the publications by peers. We
find that the RCR correlates highly with established field-normalized
indicators, but the correlation between RCR and peer assessments is only low to
medium.


  How should computer science and social science collaborate to build a common
model? How should they proceed to gather data that is really useful to the
modelling? How can they design a survey that is tailored to the target model?
This paper aims to answer those crucial questions in the framework of a
multidisciplinary research project. This research addresses the issue of
co-constructing a model when several disciplines are involved, and is applied
to modelling human behaviour immediately after an earthquake. The main
contribution of the work is to propose a tool dedicated to multidisciplinary
dialogue. It also proposes a reflexive analysis of the enriching intellectual
process carried out by the different disciplines involved. Finally, from
working with an anthropologist, a complementary view of the multidisciplinary
process is given.


  The number of potentially habitable planets continues to increase, but we
lack the time and resources to characterize all of them. With $\sim$30 known
potentially habitable planets and an ever-growing number of candidate and
confirmed planets, a robust statistical framework for prioritizing
characterization of these planets is desirable. Using the $\sim$2 Gy it took
life on Earth to make a detectable impact on the atmosphere as a benchmark, we
use a Bayesian statistical method to determine the probability that a given
radius around a star has been continuously habitable for 2 Gy. We perform this
analysis on 9 potentially habitable exoplanets with planetary radii $<$1.8
R$_\oplus$ and/or planetary masses $<$10 M$_\oplus$ around 9 low-mass host
stars ($\sim$0.5-1.1 M$_\odot$) with measured stellar mass and metallicity, as
well as Venus, Earth, and Mars. Ages for the host stars are generated by the
analysis. The technique is also used to provide age estimates for 2768 low-mass
stars (0.5-1.3 M$_\odot$) in the TESS Continuous Viewing Zones.


  We present a simple and efficient Finite-Difference Time-Domain (FDFD) scheme
for simulating dispersive (Lorentz-Debye) bianisotropic metasurfaces. This
scheme replaces the conventional FDTD update equations by augmented update
equations where the effect of the metasurface, positioned at a virtual node (or
node plane) in the Yee grid, is accounted for by judiciously selected auxiliary
polarization functions, based on the Generalized Sheet Transition Conditions
(GSTCs). This scheme is computationally -- time- and memory-wise -- more
efficient and easier to implement than a previously reported scheme for
dispersive metasurfaces. It is validated in three illustrative examples.


  In the article we made an attempt to reveal the contents and development of
the concept of economic clusters, to characterize the specificity of the
regional cluster as a project. We have identified features of an estimation of
efficiency of state participation in the cluster, where the state is an
institution representing the interests of society.


  Attribution scores can be applied in data management to quantify the
contribution of individual items to conclusions from the data, as part of the
explanation of what led to these conclusions. In Artificial Intelligence,
Machine Learning, and Data Management, some of the common scores are
deployments of the Shapley value, a formula for profit sharing in cooperative
game theory. Since its invention in the 1950s, the Shapley value has been used
for contribution measurement in many fields, from economics to law, with its
latest researched applications in modern machine learning. Recent studies
investigated the application of the Shapley value to database management. This
article gives an overview of recent results on the computational complexity of
the Shapley value for measuring the contribution of tuples to query answers and
to the extent of inconsistency with respect to integrity constraints. More
specifically, the article highlights lower and upper bounds on the complexity
of calculating the Shapley value, either exactly or approximately, as well as
solutions for realizing the calculation in practice.


  Image cropping aims to find visually appealing crops in an image, which is an
important yet challenging task. In this paper, we consider a specific and
practical application: human-centric image cropping, which focuses on the
depiction of a person. To this end, we propose a human-centric image cropping
method with two novel feature designs for the candidate crop: partition-aware
feature and content-preserving feature. For partition-aware feature, we divide
the whole image into nine partitions based on the human bounding box and treat
different partitions in a candidate crop differently conditioned on the human
information. For content-preserving feature, we predict a heatmap indicating
the important content to be included in a good crop, and extract the geometric
relation between the heatmap and a candidate crop. Extensive experiments
demonstrate that our method can perform favorably against state-of-the-art
image cropping methods on human-centric image cropping task. Code is available
at https://github.com/bcmi/Human-Centric-Image-Cropping.


  The niobium oxide polymorph T-Nb2O5 has been extensively investigated in its
bulk form especially for applications in fast-charging batteries and
electrochemical (pseudo)capacitors. Its crystal structure that has
two-dimensional (2D) layers with very low steric hindrance allows for fast
Li-ion migration. However, since its discovery in 1941, the growth of
single-crystalline thin films and its electronic applications have not yet been
realized, likely due to its large orthorhombic unit cell along with the
existence of many polymorphs. Here we demonstrate the epitaxial growth of
single-crystalline T-Nb2O5 thin films, critically with the ionic transport
channels oriented perpendicular to the film's surface. These vertical 2D
channels enable fast Li-ion migration which we show gives rise to a colossal
insulator-metal transition where the resistivity drops by eleven orders of
magnitude due to the population of the initially empty Nb 4d0 states by
electrons. Moreover, we reveal multiple unexplored phase transitions with
distinct crystal and electronic structures over a wide range of Li-ion
concentrations by comprehensive in situ experiments and theoretical
calculations, that allow for the reversible and repeatable manipulation of
these phases and their distinct electronic properties. This work paves the way
to the exploration of novel thin films with ionic channels and their potential
applications.


  The cyclic universe model is a modification of the ekpyrotic universe and the
pyrotechnic universe models. The cyclic universe goes through the six
transitions: the triplet universe, the inflation, the big bang, the
quintessence, the big crush, and the deflation transitions. The universe starts
with eleven dimensional space-time with two boundary 9-branes separated by a
finite gap spanning an intervening bulk volume. The triplet transition starts
when the bulk 9-brane is generated from the hidden boundary 9-brane, and
collides with the pre-observable 9-brane. The collision starts the inflation
transition. The collision is the brane dimensional interference mixing between
the pre-observable 9-brane and the bulk 9-brane. The results are the mixed
branes (combined brane dimensions), the internal space (cancelled brane
dimensions), the bulk space, 3-brane vacuum, and cosmic radiation. Cosmic
radiation generated during the inflation leads to the big bang. Meanwhile, the
hidden brane undergoes stepwise fractionalization, changing in stepwise manner
from 9-brane to 3-brane. The observable universe expands in a constant rate
until the quintessence transition. Afterward, there are the big crush
transition (the reverse of the big bang) and the deflation (the reverse of the
inflation). The cosmic cycle of the fractionalization and condensation starts
over again. The masses of all elementary particles and hadrons can be
calculated.


  We study stress relaxation in bi-disperse entangled polymer solutions.
Shorter chains embedded in a majority of longer ones are known to be oriented
by coupling to them. We analyze the mechanism for this both by computer
simulation and theoretically. We show that the results can be understood in
terms of stress fluctuations in a polymer melt and chain screening. Stress
fluctuations are frozen on the relaxation time of the longer chains, and these
will induce strong orientational couplings in the shorter chains.


  In this article, we study the decision-making process of chess players by
using a chess engine to evaluate the moves across different pools of games. We
quantify the decisiveness of each move during the games using a metric called
$\Delta$, which is derived from the engine's evaluation of the positions. We
then performed a comparative analysis across players of varying competitive
levels. Firstly, we observed that players face a wide spectrum of $\Delta$
values, evidencing the complexity of the process. By examining groups of
winning and losing players, we found evidence where a decrease in complexity
may be associated with a drop in player performance levels. Secondly, we
observed that players' accuracy increases in positions with high $\Delta$
values regardless of competitive level. Complementing this information with a
null model where players make completely random legal moves allowed us to
characterize the decision-making process under the simple strategy of making
moves that minimize $\Delta$ values. Finally, based on this idea, we proposed a
simple model that approximately replicates the global emergent properties of
the system.


  Inspired by the work of Backelin on non-commutative correspondences to
Macaulay's theorem of the growth of the Hilbert series of affine algebras, we
study embedding dimension dependant versions of his degree 2 to degree 3
result. In graph-theoretical terms, we study the following question: what is
the maximal number of directed walks of length 2 in a digraph with (k) edges
and (n) vertices? The problem can also be formulated as follows: maximize (<
\lambda, \lambda^T >) when (\lambda) is a partition of (k), contained in an (n
\times n) box. We show that for mild restrictions on (n), optimal digraphs are
the ``stars of saturated stars''.