  This paper studies quantum Arthur-Merlin games, which are Arthur-Merlin games
in which Arthur and Merlin can perform quantum computations and Merlin can send
Arthur quantum information. As in the classical case, messages from Arthur to
Merlin are restricted to be strings of uniformly generated random bits. It is
proved that for one-message quantum Arthur-Merlin games, which correspond to
the complexity class QMA, completeness and soundness errors can be reduced
exponentially without increasing the length of Merlin's message. Previous
constructions for reducing error required a polynomial increase in the length
of Merlin's message. Applications of this fact include a proof that logarithmic
length quantum certificates yield no increase in power over BQP and a simple
proof that QMA is contained in PP. Other facts that are proved include the
equivalence of three (or more) message quantum Arthur-Merlin games with
ordinary quantum interactive proof systems and some basic properties concerning
two-message quantum Arthur-Merlin games.


  Recent work of [Dasgupta-Kumar-Sarlos, STOC 2010] gave a sparse
Johnson-Lindenstrauss transform and left as a main open question whether their
construction could be efficiently derandomized. We answer their question
affirmatively by giving an alternative proof of their result requiring only
bounded independence hash functions. Furthermore, the sparsity bound obtained
in our proof is improved. The main ingredient in our proof is a spectral moment
bound for quadratic forms that was recently used in [Diakonikolas-Kane-Nelson,
FOCS 2010].


  We prove that there exists $\alpha \in \mathbb{R}$ such that for any $N$ the
dicrepancy $D_N$ of the sequence $\{\alpha n !\} ,\, 1\le n \le N$ satisfies $
D_N = O(\log N)$.


  We discuss phenomenology of the vacuum condensate <(A_\mu)^2> in pure gauge
theories, where A_\mu is the gauge potential. Both Abelian and non-Abelian
cases are considered. In case of the compact U(1) the non-perturbative part of
the condensate <(A_\mu)^2> is saturated by monopoles. In the non-Abelian case,
a two-component picture for the condensate is presented according to which
finite values of order \Lambda_{QCD}^2 are associated both with large and short
distances. We obtain a lower bound on the <(A_\mu)^2> by considering its change
at the phase transition. Numerically, it produces an estimate similar to other
measurements. Possible physical manifestations of the condensate are discussed.


  We determine when a convex body in $\mathbb{R}^d$ is the closed unit ball of
a reasonable crossnorm on
$\mathbb{R}^{d_1}\otimes\cdots\otimes\mathbb{R}^{d_l},$ $d=d_1\cdots d_l.$ We
call these convex bodies "tensorial bodies". We prove that, among them, the
only ellipsoids are the closed unit balls of Hilbert tensor products of
Euclidean spaces. It is also proved that linear isomorphisms on
$\mathbb{R}^{d_1}\otimes\cdots \otimes \mathbb{R}^{d_l}$ preserving
decomposable vectors map tensorial bodies into tensorial bodies. This leads us
to define a Banach-Mazur type distance between them, and to prove that there
exists a Banach-Mazur type compactum of tensorial bodies.


  A celebrated result of Chv\'atal, R\"odl, Szemer\'edi and Trotter states (in
slightly weakened form) that, for every natural number $\Delta$, there is a
constant $r_\Delta$ such that, for any connected $n$-vertex graph $G$ with
maximum degree $\Delta$, the Ramsey number $R(G,G)$ is at most $r_\Delta n$,
provided $n$ is sufficiently large. In 1987, Burr made a strong conjecture
implying that one may take $r_\Delta = \Delta$. However, Graham, R\"odl and
Ruci\'nski showed, by taking $G$ to be a suitable expander graph, that
necessarily $r_\Delta > 2^{c\Delta}$ for some constant $c>0$. We show that the
use of expanders is essential: if we impose the additional restriction that the
bandwidth of $G$ be at most some function $\beta (n) = o(n)$, then $R(G,G) \le
(2\chi(G)+4)n\leq (2\Delta+6)n$, i.e., $r_\Delta = 2\Delta +6$ suffices. On the
other hand, we show that Burr's conjecture itself fails even for $P_n^k$, the
$k$th power of a path $P_n$. Brandt showed that for any $c$, if $\Delta$ is
sufficiently large, there are connected $n$-vertex graphs $G$ with
$\Delta(G)\leq\Delta$ but $R(G,K_3)>cn$. We show that, given $\Delta$ and $H$,
there are $\beta>0$ and $n_0$ such that, if $G$ is a connected graph on $n\ge
n_0$ vertices with maximum degree at most $\Delta$ and bandwidth at most $\beta
n$, then we have $R(G,H)=(\chi(H)-1)(n-1)+\sigma(H)$, where $\sigma(H)$ is the
smallest size of any part in any $\chi(H)$-partition of $H$. We also show that
the same conclusion holds without any restriction on the maximum degree of $G$
if the bandwidth of $G$ is at most $\epsilon(H) \log n/\log\log n$.


  Given a multipartite quantum system, what are the possible ways to impose
mutual independence among some subsystems, and the presence of correlations
among others, such that there exists a quantum state which satisfies these
demands? This question and the related notion of a \textit{pattern of marginal
independence} (PMI) were introduced in arXiv:1912.01041, and then argued in
arXiv:2204.00075 to be central in the derivation of the holographic entropy
cone. Here we continue the general information theoretic analysis of the PMIs
allowed by \textit{strong subadditivity} (SSA) initiated in arXiv:1912.01041.
We show how the computation of these PMIs simplifies when SSA is replaced by a
weaker constraint, dubbed \textit{Klein's condition} (KC), which follows from
the necessary condition for the saturation of subadditivity (SA). Formulating
KC in the language of partially ordered sets, we show that the set of PMIs
compatible with KC forms a lattice, and we investigate several of its
structural properties. One of our main results is the identification of a
specific lower dimensional face of the SA cone that contains on its boundary
all the extreme rays (beyond Bell pairs) that can possibly be realized by
quantum states. We verify that for four or more parties, KC is strictly weaker
than SSA, but nonetheless the PMIs compatible with SSA can easily be derived
from the KC-compatible ones. For the special case of 1-dimensional PMIs, we
conjecture that KC and SSA are in fact equivalent. To make the presentation
self-contained, we review the key ingredients from lattice theory as needed.


  In the framework of k_T-factorization QCD approach and the colour singlet
model we consider J/\psi inelastic photo- and leptoproduction processes at
HERA. We investigate the dependences of the single differential and double
differential cross section on different forms of the unintegrated gluon
distribution. The z and p_T dependences of the spin aligment parameter \alpha
are presented also. Our theoretical predictions agree well with recent data
taken by the H1 and ZEUS collaborations at HERA. It is shown that experimental
study of the polarization J/\psi mesons at low Q^2 < 1 GeV^2 is an additional
test of BFKL gluon dynamics.


  We will present exact solutions for three variations of stochastic Korteweg
de Vries-Burgers (KdV-Burgers) equation featuring variable coefficients. In
each variant, white noise exhibits spatial uniformity, and the three categories
include additive, multiplicative, and advection noise. Across all cases, the
coefficients are time-dependent functions. Our discovery indicates that solving
certain deterministic counterparts of KdV-Burgers equations and composing the
solution with a solution of stochastic differential equations leads to the
exact solution of the stochastic Korteweg de Vries-Burgers (KdV-Burgers)
equations.


  A variety of new physics models predict the existence of extra charged gauge
bosons ($W^\prime$). It is verified that $W^\prime$ and top quark associated
production is a promising process to search for $W^\prime$ signal at the LHC.
We study the collider signatures of multi-jets$+$lepton$+\met$ by
reconstructing the $tW'$ intermediate state through the decay modes of
$W^\prime \to tb$, $W^\prime \to q \bar q'$ and $W^\prime \to l \nu$
respectively. An angular distribution related to charged lepton and top quark
moving direction is provided to distinguish alternative left-handed or
right-handed chiral couplings of $W^\prime$ to quarks in the hadronic decay
modes. The superiority on the search of $W^\prime$ is demonstrated in the
leptonic decay channel for the left-handed type interaction, which is forbidden
for the right-handed type interaction in the most theories. To be more
realistic, the relevant standard model backgrounds are simulated. We adopt
various kinematic cuts to suppress the backgrounds and collect the integral
luminosity needed for the corresponding process detected at the LHC with
$3\sigma$ sensitivity. We also provide a forward-backward asymmetry which is
related to the chirality of $W^\prime$. The successive studies can shed light
on the potential searching for $W^\prime$ signal as well as distinguishing
typical new physics models.


  Learning the distance metric between pairs of examples is of great importance
for visual recognition, especially for person re-identification (Re-Id).
Recently, the contrastive and triplet loss are proposed to enhance the
discriminative power of the deeply learned features, and have achieved
remarkable success. As can be seen, either the contrastive or triplet loss is
just one special case of the Euclidean distance relationships among these
training samples. Therefore, we propose a structured graph Laplacian embedding
algorithm, which can formulate all these structured distance relationships into
the graph Laplacian form. The proposed method can take full advantages of the
structured distance relationships among these training samples, with the
constructed complete graph. Besides, this formulation makes our method
easy-to-implement and super-effective. When embedding the proposed algorithm
with the softmax loss for the CNN training, our method can obtain much more
robust and discriminative deep features with inter-personal dispersion and
intra-personal compactness, which is essential to person Re-Id. We illustrate
the effectiveness of our proposed method on top of three popular networks,
namely AlexNet, DGDNet and ResNet50, on recent four widely used Re-Id benchmark
datasets. Our proposed method achieves state-of-the-art performances.


  We review some recently established connections between the mathematics of
black hole entropy in string theory and that of multipartite entanglement in
quantum information theory. In the case of N=2 black holes and the entanglement
of three qubits, the quartic [SL(2)]^3 invariant, Cayley's hyperdeterminant,
provides both the black hole entropy and the measure of tripartite
entanglement. In the case of N=8 black holes and the entanglement of seven
qubits, the quartic E_7 invariant of Cartan provides both the black hole
entropy and the measure of a particular tripartite entanglement encoded in the
Fano plane.


  Large neural networks excel in many domains, but they are expensive to train
and fine-tune. A popular approach to reduce their compute or memory
requirements is to replace dense weight matrices with structured ones (e.g.,
sparse, low-rank, Fourier transform). These methods have not seen widespread
adoption (1) in end-to-end training due to unfavorable efficiency--quality
tradeoffs, and (2) in dense-to-sparse fine-tuning due to lack of tractable
algorithms to approximate a given dense weight matrix. To address these issues,
we propose a class of matrices (Monarch) that is hardware-efficient (they are
parameterized as products of two block-diagonal matrices for better hardware
utilization) and expressive (they can represent many commonly used transforms).
Surprisingly, the problem of approximating a dense weight matrix with a Monarch
matrix, though nonconvex, has an analytical optimal solution. These properties
of Monarch matrices unlock new ways to train and fine-tune sparse and dense
models. We empirically validate that Monarch can achieve favorable
accuracy-efficiency tradeoffs in several end-to-end sparse training
applications: speeding up ViT and GPT-2 training on ImageNet classification and
Wikitext-103 language modeling by 2x with comparable model quality, and
reducing the error on PDE solving and MRI reconstruction tasks by 40%. In
sparse-to-dense training, with a simple technique called "reverse
sparsification," Monarch matrices serve as a useful intermediate representation
to speed up GPT-2 pretraining on OpenWebText by 2x without quality drop. The
same technique brings 23% faster BERT pretraining than even the very optimized
implementation from Nvidia that set the MLPerf 1.1 record. In dense-to-sparse
fine-tuning, as a proof-of-concept, our Monarch approximation algorithm speeds
up BERT fine-tuning on GLUE by 1.7x with comparable accuracy.


  Skin cancer is a highly dangerous type of cancer that requires an accurate
diagnosis from experienced physicians. To help physicians diagnose skin cancer
more efficiently, a computer-aided diagnosis (CAD) system can be very helpful.
In this paper, we propose a novel model, which uses a novel attention mechanism
to pinpoint the differences in features across the spatial dimensions and
symmetry of the lesion, thereby focusing on the dissimilarities of various
classes based on symmetry, uniformity in texture and color, etc. Additionally,
to take into account the variations in the boundaries of the lesions for
different classes, we employ a gradient-based fusion of wavelet and soft
attention-aided features to extract boundary information of skin lesions. We
have tested our model on the multi-class and highly class-imbalanced dataset,
called HAM10000, and achieved promising results, with a 91.17\% F1-score and
90.75\% accuracy. The code is made available at:
https://github.com/AyushRoy2001/WAGF-Fusion.


  SNO+ inherits much of it's infrastructure from the Noble prize winning SNO
detector. However due to the two orders of magnitude increase in light output
in liquid scintillator many upgrades have been made. Details of these upgrades
and their commissioning status are presented, along with an update on the
current status of SNO+.


  Information extraction(IE) has always been one of the essential tasks of NLP.
Moreover, one of the most critical application scenarios of information
extraction is the information extraction of resumes. Constructed text is
obtained by classifying each part of the resume. It is convenient to store
these texts for later search and analysis. Furthermore, the constructed resume
data can also be used in the AI resume screening system. Significantly reduce
the labor cost of HR. This study aims to transform the information extraction
task of resumes into a simple sentence classification task. Based on the
English resume dataset produced by the prior study. The classification rules
are improved to create a larger and more fine-grained classification dataset of
resumes. This corpus is also used to test some current mainstream Pre-training
language models (PLMs) performance.Furthermore, in order to explore the
relationship between the number of training samples and the correctness rate of
the resume dataset, we also performed comparison experiments with training sets
of different train set sizes.The final multiple experimental results show that
the resume dataset with improved annotation rules and increased sample size of
the dataset improves the accuracy of the original resume dataset.


  We demonstrate that the peak in the density dependence of electron spin
relaxation time in $n$-type bulk GaAs in the metallic regime predicted by Jiang
and Wu [Phys. Rev. B {\bf 79}, 125206 (2009)] has been realized experimentally
in the latest work by Krau\ss {\em et al}. [arXiv:0902.0270].


  We generalize K\"ahler information manifolds of complex-valued signal
processing filters by introducing weighted Hardy spaces and smooth
transformations of transfer functions. We prove that the Riemannian geometry of
a linear filter induced from weighted Hardy norms for the smooth
transformations of its transfer function is a K\"ahler manifold. Additionally,
the K\"ahler potential of the linear system geometry corresponds to the square
of the weighted Hardy norms of its composite transfer functions. Based on
properties of K\"ahler manifolds, geometric objects on the manifolds of the
linear systems in weighted Hardy spaces are computed in much simpler ways.
Moreover, K\"ahler information manifolds of signal filters in weighted Hardy
spaces incorporate various well-known information manifolds under the unified
framework. We also cover several examples from time series models of which
metric tensor, Levi-Civita connection, and K\"ahler potentials are represented
with polylogarithms of poles and zeros from the transfer functions with weight
vectors in exponential forms.


  We process snapshots of trajectories of evolution equations with intrinsic
symmetries, and demonstrate the use of recently developed eigenvector-based
techniques to successfully quotient out the degrees of freedom associated with
the symmetries in the presence of noise. Our illustrative examples include a
one-dimensional evolutionary partial differential (the Kuramoto-Sivashinsky)
equation with periodic boundary conditions, as well as a stochastic simulation
of nematic liquid crystals which can be effectively modeled through a nonlinear
Smoluchowski equation on the surface of a sphere. This is a useful first step
towards data mining the "symmetry-adjusted" ensemble of snapshots in search of
an accurate low-dimensional parametrization (and the associated reduction of
the original dynamical system). We also demonstrate a technique ("vector
diffusion maps") that combines, in a single formulation, the symmetry removal
step and the dimensionality reduction step.


  The effect of pitch of the pillars and impact velocity are studied for the
impact dynamics of a microliter water droplet on a micropillared hydrophobic
surface. The results are presented qualitatively by the high-speed photography
and quantitatively by the temporal variation of wetted diameter and droplet
height. A characterization of the transient quantitative results is a novel
aspect of our work. Three distinct regimes, namely, non-bouncing, complete
bouncing and partial bouncing are presented. A critical pitch as well as impact
velocity exists for the transition from one regime to another. This is
explained with a demonstration of Cassie to Wenzel wetting transition in which
the liquid penetrates in the grooves between the pillars at larger pitch or
impact velocity. The regimes are demarcated on a map of pitch and impact
velocity. A good agreement is reported between the present measurements and
published analytical models.


  We investigated the evolution of a massive galactic nucleus hosting a
super-massive black hole (SMBH) with mass $M_\mathrm{SMBH}=10^8
\mathrm{M}_\odot$ surrounded by a population of 42 heavy star clusters (GCs).
Using direct $N$-body modelling, we show here that the assembly of an NSC
through GCs orbital decay and merger is efficiently inhibited by the tidal
forces exerted from the SMBH. The GCs mass loss induced by tidal forces causes
a significant modification of their mass function, leading to a population of
low-mass ($<10^4$) clusters. Nonetheless, the GCs debris accumulated around the
SMBH give rise to well-defined kinematical and morphological properties,
leading to the formation of a disk-like structure. Interestingly, the disk is
similar to the one observed in the M31 galaxy nucleus, which has properties
similar to our numerical model. The simulation produced a huge amount of data,
which we used to investigate whether the GC debris deposited around the SMBH
can enhance the rate of tidal disruption events (TDEs) in our galaxy inner
density distribution. Our results suggest that the GCs disruption shapes the
SMBH neighbourhoods leading to a TDE rate of $\sim 2 \times 10^{-4} $yr$^{-1}$,
a value slightly larger than what expected in previous theoretical modelling of
galaxies with similar density profiles and central SMBHs. The simulation
presented here is the first of its kind, representing a massive galactic
nucleus and its star cluster population on scales $\sim 100$ pc.


  A key prediction of the trap model for the new conducting state in 2D is that
the resistivity turns upwards below some characteristic temperature, $T_{\rm
min}$. Altshuler, Maslov, and Pudalov have argued that the reason why no upturn
has been observed for the low density conducting samples is that the
temperature was not low enough in the experiments. We show here that $T_{\rm
min}$ within the Altshuler, Maslov, and Pudalov trap model actually increases
with decreasing density, contrary to their claim. Consequently, the trap model
is not consistent with the experimental trends.


  Generalized complex geometry, as developed by Hitchin, contains complex and
symplectic geometry as its extremal special cases. In this thesis, we explore
novel phenomena exhibited by this geometry, such as the natural action of a
B-field. We provide new examples, including some on manifolds admitting no
known complex or symplectic structure. We prove a generalized Darboux theorem
which yields a local normal form for the geometry. We show that there is an
elliptic deformation theory and establish the existence of a Kuranishi moduli
space.
  We then define the concept of a generalized Kahler manifold. We prove that
generalized Kahler geometry is equivalent to a bi-Hermitian geometry with
torsion first discovered by physicists. We then use this result to solve an
outstanding problem in 4-dimensional bi-Hermitian geometry: we prove that there
exists a Riemannian metric on the complex projective plane which admits exactly
two distinct Hermitian complex structures with equal orientation.
  Finally, we introduce the concept of generalized complex submanifold, and
show that such sub-objects correspond to D-branes in the topological A- and
B-models of string theory.


  Millions of vehicles are transported every year, tightly parked in vessels or
boats. To reduce the risks of associated safety issues like fires, knowing the
location of vehicles is essential, since different vehicles may need different
mitigation measures, e.g. electric cars. This work is aimed at creating a
solution based on a nano-drone that navigates across rows of parked vehicles
and detects their license plates. We do so via a wall-following algorithm, and
a CNN trained to detect license plates. All computations are done in real-time
on the drone, which just sends position and detected images that allow the
creation of a 2D map with the position of the plates. Our solution is capable
of reading all plates across eight test cases (with several rows of plates,
different drone speeds, or low light) by aggregation of measurements across
several drone journeys.


  In the context of optimization approaches to engineering applications,
time-consuming simulations are often utilized which can be configured to
deliver solutions for various levels of accuracy, commonly referred to as
different fidelity levels. It is common practice to train hierarchical
surrogate models on the objective functions in order to speed-up the
optimization process. These operate under the assumption that there is a
correlation between the high- and low-fidelity versions of the problem that can
be exploited to cheaply gain information. In the practical scenario where the
computational budget has to be allocated between multiple fidelities, limited
guidelines are available to help make that division. In this paper we evaluate
a range of different choices for a two-fidelity setup that provide helpful
intuitions about the trade-off between evaluating in high- or low-fidelity. We
present a heuristic method based on subsampling from an initial Design of
Experiments (DoE) to find a suitable division of the computational budget
between the fidelity levels. This enables the setup of multi-fidelity
optimizations which utilize the available computational budget efficiently,
independent of the multi-fidelity model used.


  In this note, we investigate the maximal number of intersection points of a
line with the contour of hypersurface amoebas in $\mathbb{R}^n$. We define the
latter number to be the $\mathbb{R}$-degree of the contour. We also investigate
the $\mathbb{R}$-degree of related sets such as the boundary of amoebas and the
amoeba of the real part of hypersurfaces defined over $\mathbb{R}$. For all
these objects, we provide bounds for the respective $\mathbb{R}$-degrees.


  In this paper a new conjecture equivalent to Collatz conjecture is presented.
In particural, showing that (all) the solution(s) of newly introduced iterative
functional equation(s) have a given property is equivalent to prove Collatz
conjecture.


  The paper describes a formulation of discrete scalar wave propagation in an
inhomogeneous medium by the use of elementary processes obeying a discrete
Huygens' principle and satisfying fundamental symmetries such as time-reversal,
reciprocity and isotropy. Its novelty is the systematic derivation of a unified
equation which, properly tuned by a single parameter, leads to either the
Klein-Gordon equation or the Schr\"{o}dinger equation. The generality of this
method enables one to consider its extension to other types of discrete wave
equations on any kind of discrete lattice.


  In this paper, we introduce $\text{EVL}_{\text{Gen}}$, a streamlined
framework designed for the pre-training of visually conditioned language
generation models with high computational demands, utilizing frozen pre-trained
large language models (LLMs). The conventional approach in vision-language
pre-training (VLP) typically involves a two-stage optimization process: an
initial resource-intensive phase dedicated to general-purpose vision-language
representation learning, focused on extracting and consolidating relevant
visual features. This is followed by a subsequent phase that emphasizes
end-to-end alignment between visual and linguistic modalities. Our novel
one-stage, single-loss framework bypasses the computationally demanding first
training stage by gradually merging similar visual tokens during training,
while avoiding model collapse caused by single-stage training of BLIP-2 type
models. The gradual merging process effectively condenses visual information
while preserving semantic richness, resulting in rapid convergence without
compromising performance. Our experimental findings demonstrate that our
approach accelerates the training of vision-language models by a factor of 5
without a noticeable impact on overall performance. Furthermore, we illustrate
that our models significantly narrow the performance gap to current
vision-language models using only 1/10 of the data. Finally, we showcase how
our image-text models can seamlessly adapt to video-conditioned language
generation tasks through novel soft attentive temporal token contextualizing
modules. Code is available at \url{https://github.com/yiren-jian/EVLGen}.


  Function approximation is a powerful approach for structuring large decision
problems that has facilitated great achievements in the areas of reinforcement
learning and game playing. Regression counterfactual regret minimization (RCFR)
is a simple algorithm for approximately solving imperfect information games
with normalized rectified linear unit (ReLU) parameterized policies. In
contrast, the more conventional softmax parameterization is standard in the
field of reinforcement learning and yields a regret bound with a better
dependence on the number of actions. We derive approximation error-aware regret
bounds for $(\Phi, f)$-regret matching, which applies to a general class of
link functions and regret objectives. These bounds recover a tighter bound for
RCFR and provide a theoretical justification for RCFR implementations with
alternative policy parameterizations ($f$-RCFR), including softmax. We provide
exploitability bounds for $f$-RCFR with the polynomial and exponential link
functions in zero-sum imperfect information games and examine empirically how
the link function interacts with the severity of the approximation. We find
that the previously studied ReLU parameterization performs better when the
approximation error is small while the softmax parameterization can perform
better when the approximation error is large.


  We construct canonical integral transforms, analogous to the Fourier
transform, that have periods six and three. The existence of such transforms is
shown to arise naturally from the expectation that the Schwartz space on the
real line, viewed as the Heisenberg module of Rieffel and Connes over the
rotation C*-algebra, should extend to a module action over the crossed product
of the latter by the canonical automorphisms of orders three and six (which
does in fact happen and is shown here).


  Major data centre providers are introducing RDMA-based networks for their
tenants, as well as for operating the underlying infrastructure. In comparison
to traditional socket-based network stacks, RDMA-based networks offer higher
throughput, lower latency and reduced CPU overhead. However, transparent
checkpoint and migration operations become much more difficult. The key reason
is that the OS is removed from the critical path of communication. As a result,
some of the communication state itself resides in the NIC hardware and is no
more under the direct control of the OS. This control includes especially the
support for virtualisation of communication which is needed for live migration
of communication partners. In this paper, we propose the basic principles
required to implement a migration-capable RDMA-based network. We recommend some
changes at the software level and small changes at the hardware level. As a
proof of concept, we integrate the proposed changes into SoftRoCE, an
open-source kernel-level implementation of the RoCE protocol. We claim that
these changes introduce no runtime overhead when migration does not happen.
Finally, we develop a proof-of-concept implementation for migrating
containerised applications that use RDMA-based networks.


  Lyman alpha absorber correlations contain information about the underlying
density distribution associated with a particular class of absorbers. As such,
they provide an opportunity to independently measure the "bias" of the Lyman
alpha forest, i.e. the relationship between HI column density and underlying
dark matter density. In these proceedings we use hydrodynamic simulations to
investigate whether the evolution of this bias is measurable from observable
correlations. Unfortunately, the increasingly complex physics in the IGM at z<1
makes a direct measurement of the bias difficult. Nevertheless, current
simulations do make predictions for HI absorber correlations that are in broad
agreement with observations at both high and low redshift, thus reinforcing the
bias evolution predictions given by these models.


  The localization technique from convex geometry is generalized to the setting
of Riemannian manifolds whose Ricci curvature is bounded from below. In a
nutshell, our method is based on the following observation: When the Ricci
curvature is non-negative, log-concave measures are obtained when conditioning
the Riemannian volume measure with respect to an integrable geodesic foliation.
The Monge mass transfer problem plays an important role in our analysis.


  The pure spinor heterotic string in a generic super Yang-Mills and
supergravity background is considered. We determine the one-loop BRST anomaly
at the cohomological level. We prove that it can be absorbed by consistent
corrections of the classical constraints due to Berkovits and Howe, in
agreement with the Green-Schwarz cancelation mechanism.


  We prove the decidability of Ticket Entailment. Raised by Anderson and Belnap
within the framework of relevance logic, this question is equivalent to the
question of the decidability of type inhabitation in simply-typed combinatory
logic with the partial basis BB'IW. We solve the equivalent problem of type
inhabitation for the restriction of simply-typed lambda-calculus to
hereditarily right-maximal terms.


  Monotone determined spaces are natural topological extensions of dcpo. Its
main purpose is to build an extended framework for domain theory. In this
paper, we study the one-step closure and ideal convergence on monotone
determined space. Then we also introduce the equivalent characterizations of
c-spaces and locally hypercompact space. The main results are:1.Every c-space
has one-step closure and every locally hypercompact space has weak one-step
closure;2.A monotone determined space has one-step closure if and only if it is
d-meet continuous and has weak one-step closure. 3.IS-convergence(resp.
IGS-convergence) is topological iff X is a c-space (resp. locally hypercompact
space); 4.If X is a d-meet continuous space, then the following three
conditions are equivalent to each other: (i) X is c-space; (ii) The net (xj )
ISL-converges to x iff (xj ) I-converges to x with respect to Lawson topology;
(iii) The net (xj ) IGSL-converges to x iff (xj ) I-converges to x with respect
to Lawson topology.


  This paper continues a series of papers in which 2-by-2 matrix joint
solutions of two scalar evolutionary equations are constructed, which are
analogs of the Schrodinger time equations. These equations correspond to the
Hamiltonian system $H^{2+2+1}$, being one of the representatives of the
hierarchy of degenerations of the isomonodromic Garnier system. The mentioned
hierarchy was described by H. Kimura in 1986. In terms of solutions of linear
systems of ordinary differential equations of the method of isomnodromic
deformations, the compatibility condition of which are the Hamiltonian
equations of the system $H^{2+2+1}$, the constructed joint matrix solutions of
analogs of the time equations of the Schrodinger equations in this paper will
be written out explicitly.


  We report tight-binding (TB) calculations of magnetocrystalline anisotropy
energy (MAE) of Iron slabs and nanoclusters with a particuler focus on local
analysis. After clarifying various concepts and formulations for the
determination of MAE, we apply our realistic TB model to the analysis of the
magnetic anisotropy of Fe$(001)$, Fe$(110)$ slabs and of two large Fe clusters
with $(001)$ and $(110)$ facets only: a truncated pyramid and a truncated
bipyramid containg 620 and 1096 atoms, respectively. It is shown that the MAE
of slabs originates mainly from outer layers, a small contribution from the
bulk gives rise, however, to an oscillatory behavior for large thicknesses.
Interestingly, the MAE of the nanoclusters considered is almost solely due to
$(001)$ facets and the base perimeter of the pyramid. We believe that this fact
could be used to efficiently control the anisotropy of Iron nanoparticles and
could also have consequences on their spin dynamics.


  We prove an analytic version of the Kontsevich-Soibelman wall-crossing
formula describing how the number of finite-length trajectories of a quadratic
differential jumps as the differential is varied. We characterize certain
birational automorphisms of an algebraic torus appearing in this wall-crossing
formula using Fock-Goncharov coordinates. As an application, we compute the
Stokes automorphisms for the Voros symbols appearing in the exact WKB analysis
of Schr\"odinger's equation.


  (Abridged) Low-mass stars have been recognised as promising targets in the
search for rocky, small planets with the potential of supporting life. Doppler
search programmes using high-resolution spectrographs like HARPS or HARPS-N are
providing huge quantities of optical spectra of M dwarfs. We aim to calibrate
empirical relationships to determine stellar parameters for early M dwarfs
(spectral types M0-M4.5) using the same spectra that are used for the radial
velocity determinations. Our methodology consists in the use of ratios of
pseudo equivalent widths of spectral features as a temperature diagnostic.
Stars with effective temperatures obtained from interferometric estimates of
their radii are used as calibrators. Empirical calibrations for the spectral
type are also provided. Combinations of features and ratios of features are
used to derive calibrations for the stellar metallicity. Our methods are then
applied to a large sample of M dwarfs that are being observed in the framework
of the HARPS search for extrasolar planets.The derived temperatures and
metallicities are used together with photometric estimates of mass, radius, and
surface gravity to calibrate empirical relationships for these parameters. A
total of 112 temperature sensitive ratios have been calibrated over the range
3100-3950 K, providing Teff values with typical uncertainties of the order of
70 K. Eighty-two ratios of pseudo equivalent widths of features were calibrated
to derive spectral types. Regarding stellar metallicity, 696 combinations of
pseudo equivalent widths of individual features and temperature-sensitive
ratios have been calibrated, over the metallicity range from -0.54 to +0.24
dex, with estimated uncertainties in the range of 0.07-0.10 dex. We provide our
own empirical calibrations for stellar mass, radius, and surface gravity.


  The coolest dwarf stars targeted by the Kepler Mission constitute a
relatively small but scientifically valuable subset of the Kepler target stars,
and provide a high-fidelity and nearby sample of transiting planetary systems.
Using archival Kepler data spanning the entire primary mission we perform a
uniform analysis to extract, confirm and characterize the transit signals
discovered by the Kepler pipeline toward M-type dwarf stars. We recover all but
two of the signals reported in a recent listing from the Exoplanet Archive
resulting in 165 planet candidates associated with a sample of 106 low-mass
stars. We fitted the observed light curves to transit models using Markov Chain
Monte Carlo and we have made the posterior samples publicly available to
facilitate further studies. We fitted empirical transit times to individual
transit signals with significantly non-linear ephemerides for accurate recovery
of transit parameters and measuring precise transit timing variations. We also
provide the physical parameters for the stellar sample, including new
measurements of stellar rotation, allowing the conversion of transit parameters
into planet radii and orbital parameters.


  Dedekind's theorem connecting ideal theory and polynomial congruences appears
in all textbooks on algebraic number theory, but few books note its connection
to the problem of ``common index divisors.'' As part of a project to study the
history of this problem, we present an annotated translation of two of
Dedekind's papers on the subject: a notice about the first publication of
Dedekind's ideal theory in 1871 and a paper of 1878 giving proofs of the
results announced in 1871 and giving a necessary and sufficient condition for
the existence of common index divisors. A separate paper will analyze Hensel's
1894 paper containing the same theorem.


  The apparent times and positions of moving clocks as predicted by both
`non-local' and `local' Lorentz Transformations are considered. Only local
transformations respect translational invariance. Such transformations change
temporal but not spatial intervals, so breaking space-time exchange symmetry
and forbidding relativity of simultaneity and length contraction. Two
satellite-borne experiments to test these predictions are proposed.


  This paper reports the first simultaneous measurement of the double
differential muon neutrino charged-current cross section on oxygen and carbon
without pions in the final state as a function of the outgoing muon kinematics,
made at the ND280 off-axis near detector of the T2K experiment. The ratio of
the oxygen and carbon cross sections is also provided to help validate various
models' ability to extrapolate between carbon and oxygen nuclear targets, as is
required in T2K oscillation analyses. The data are taken using a neutrino beam
with an energy spectrum peaked at 0.6 GeV. The extracted measurement is
compared with the prediction from different Monte Carlo neutrino-nucleus
interaction event generators, showing particular model separation for very
forward-going muons. Overall, of the models tested, the result is best
described using Local Fermi Gas descriptions of the nuclear ground state with
RPA suppression.


  The existence of magnetostriction in bulk BiFeO3 is still a matter of
investigation and it is also an issue to investigate the magnetostriction
effect in nano BiFeO3. Present work demonstrates the existence of
magnetostrictive strain in superparamagnetic BiFeO3 nanoparticles at room
temperature and the magnetoelectric coupling properties in composite form with
P(VDFTrFE). Despite few reports on the magnetostriction effect in bulk BiFeO3
evidenced by the indirect method, the direct method (strain gauge) was employed
in this work to examine the magnetostriction of superparamagnetic BiFeO3. In
addition, a high magnetoelectric coupling coefficient was observed by the
lock-in technique for optimized BiFeO3_P(VDF-TrFE) nanocomposite film. These
nanocomposite films also exhibit room-temperature multiferroic properties.
These results provide aspects of material with immense potential for practical
applications in spintronics and magneto-electronics applications. We report a
magnetoelectric sensor using superparamagnetic BiFeO3_P(VDF-TrFE) nanocomposite
film for detection of ac magnetic field.


  We bring new insights into the long-standing Alekseevskii conjecture, namely
that any connected homogeneous Einstein manifold of negative scalar curvature
is diffeomorphic to a Euclidean space, by proving structural results which are
actually valid for any homogeneous expanding Ricci soliton, and generalize many
well-known results on Einstein solvmanifolds, solvsolitons and nilsolitons. We
obtain that any homogeneous expanding Ricci soliton M=G/K is diffeomorphic to a
product U/K x N, where U is a maximal reductive Lie subgroup of G and N is the
maximal nilpotent normal subgroup of G, such that the metric restricted to N is
a nilsoliton. Moreover, strong compatibility conditions between the metric and
the action of U on N by conjugation must hold, including a nice formula for the
Ricci operator of the metric restricted to U/K. Our main tools come from
geometric invariant theory. As an application, we give many Lie theoretical
characterizations of algebraic solitons, as well as a proof of the fact that
the following a priori much stronger result is actually equivalent to
Alekseevskii's conjecture: Any expanding algebraic soliton is diffeomorphic to
a Euclidean space.


  Starburst galaxies are primary feedback sources of mechanical energy and
metals, which are generally measured from associated X-ray emission lines
assuming that they are from the thermal emission of the outflowing hot gas.
Such line emission, however, can also arise from the charge exchange X-ray
emission (CXE) between highly ionized ions and neutral species. To understand
the feedback of energy and metals, it is crucial to determine the origin of the
X-ray emission lines and to distinguish the contributions from the CXE and the
thermal emission. The origin of the lines can be diagnosed by the K{\alpha}
triplets of He-like ions, because the CXE favors the inter-combination and
forbidden lines, while the thermal emission favors the resonance line. We
analyze the triplets of O VII, Ne IX, and Mg XI observed in the XMM- Newton
reflection grating spectra of the starburst galaxy M82. The flux contribution
of the CXE is 90%, 50%, and 30% to the O VII, Ne IX, and Mg XI triplet,
respectively. Averaged over all the three triplets, the contribution of the CXE
is \sim 50% of the total observed triplet flux. To correctly understand the hot
outflow of starburst galaxies, it is necessary to include the CXE. Based on the
measured CXE contributions to the O VII, Ne IX, and Mg XI triplets, we estimate
the relative abundances of O, Ne, and Mg of the outflow and find they are
similar to the solar ratios.


  In this work we present an analysis of a spatially non homogeneous ultimatum
game. By considering different underlying topologies as substrates on top of
which the game takes place we obtain nontrivial behaviors for the evolution of
the strategies of the players. We analyze separately the effect of the size of
the neighborhood and the spatial structure. Whereas this last effect is the
most significant one, we show that even for disordered networks and provided
the neighborhood of each site is small, the results can be significantly
different from those obtained in the case of fully connected networks.


  We integrate out the Higgs boson in the electroweak standard model at one
loop, assuming that it is very heavy. We construct a low-energy effective
Lagrangian, which parametrizes the one-loop effects of the heavy Higgs boson at
O(M_H^0). Instead of applying conventional diagrammatical techniques, we
integrate out the Higgs boson directly in the path integral.


  We present low resolution UV-blue spectroscopic observations of red giant
stars in the globular cluster M53 ([Fe/H]=-1.84), obtained to study primordial
abundance variations and deep mixing via the CN and CH absorption bands. The
metallicity of M53 makes it an attractive target: a bimodal distribution of
3883 angstrom CN bandstrength is common in moderate- and high-metallicity
globular clusters ([Fe/H] > -1.6) but unusual in those of lower metallicity
([Fe/H] < -2.0). We find that M53 is an intermediate case, and has a broad but
not strongly bimodal distribution of CN bandstrength, with CN and CH
bandstrengths anticorrelated in the less-evolved stars. Like many other
globular clusters, M53 also exhibits a general decline in CH bandstrength and
[C/Fe] abundance with rising luminosity on the red giant branch.


  To study the local Hubble flow, we have run constrained dark matter
  (DM) simulations of the Local Group (LG) in the concordance LCDM and OCDM
cosmologies, with identical cosmological parameters apart from the Lambda term.
The simulations were performed within a computational box of 64 h^{-1}Mpc
centred on the LG. The initial conditions were constrained by the observed
peculiar velocities of galaxies and positions of X-ray nearby clusters of
galaxies. The simulations faithfully reproduce the nearby large scale
structure, and in particular the Local Supercluster and the Virgo cluster.
LG-like objects have been selected from the DM halos so as to closely resemble
the dynamical properties of the LG. Both the LCDM and OCDM simulations show
very similar local Hubble flow around the LG-like objects. It follows that,
contrary to recent statements, the dark energy (DE) does not manifest itself in
the local dynamics.


  The six-quark instanton induced 't Hooft interaction, which breaks the
unwanted U_A(1) symmetry of QCD, is also a sourse of semi-classical corrections
to the low energy effective action. It is argued that there emerges a
dimensionless expansion parameter that introduces a new mass scale,
Lambda_E^2=6 GeV^2, in the 0^-, 0^+ channels. This scale plays a similar role
as the large critical mass M^2_crit > 4.2-6.6 GeV^2 discovered in the framework
of QCD sum rules in the 0^-, 0^+ gluonic channels. In particular, it allows to
resolve the eta' puzzle. To extract Lambda_E we calculate the masses of the
lightest pseudoscalar meson nonet by using the Nambu --Jona-Lasinio (NJL) type
U_L(3)X U_R(3) chiral symmetric Lagrangian together with the 't Hooft
determinant. The mechanism which leads to the large value of Lambda_E is
scrutinized.


  Magnetic skyrmions are localized swirls of magnetization with a non-trivial
topological winding number. This winding increases their robustness to
superparamagnetism and gives rise to a myriad of novel dynamical properties,
making them attractive as next-generation information carriers. Recently the
equation of motion for a skyrmion was derived using the approach pioneered by
Thiele, allowing for macroscopic skyrmion systems to be modeled efficiently.
This powerful technique suffers from the prerequisite that one must have a
priori knowledge of the functional form of the interaction between a skyrmion
and all other magnetic structures in its environment. Here we attempt to
alleviate this problem by providing a simple analytic expression which can
generate arbitrary repulsive interaction potentials from the micromagnetic
Hamiltonian. We also discuss a toy model of the radial profile of a skyrmion
which is accurate for a wide range of material parameters.


  In complex oxide materials, changes in electronic properties are often
associated with changes in crystal structure, raising the question of the
relative roles of the electronic and lattice effects in driving the
metal-insulator transition. This paper presents a combined theoretical and
experimental analysis of the dependence of the metal-insulator transition of
NdNiO$_3$ on crystal structure, specifically comparing properties of bulk
materials to one and two layer samples of NdNiO$_3$ grown between multiple
electronically inert NdAlO$_3$ counterlayers in a superlattice. The comparison
amplifies and validates a theoretical approach developed in previous papers and
disentangles the electronic and lattice contributions, through an independent
variation of each. In bulk NdNiO$_3$ the correlations are not strong enough to
drive a metal-insulator transition by themselves: a lattice distortion is
required. Ultra-thin films exhibit two additional electronic effects and one
lattice-related effect. The electronic effects are quantum confinement, leading
to dimensional reduction of the electronic Hamiltonian, and an increase in
electronic bandwidth due to counterlayer induced bond angle changes. We find
that the confinement effect is much more important. The lattice effect is an
increase in stiffness due to the cost of propagation of the lattice
disproportionation into the confining material.


  A simple estimator for the finite right endpoint of a distribution function
in the Gumbel max-domain of attraction is proposed. Large sample properties
such as consistency and the asymptotic distribution are derived. A simulation
study is also presented.


  The outline of the presentation is as follows: I. Nucleon Distribution in the
Deuteron from $e-D$ and $p-D$ Processes. II. Quark Distribution in Deuteron
from its Fragmentation to Pions and Deep Inelastic $e-D$ scattering.
III.Difference of These Two Distributions and Its Possible Understanding.


  Using cosmological simulations, we address the properties of high-redshift
star-forming galaxies (SFGs) across their main sequence (MS) in the plane of
star-formation rate (SFR) versus stellar mass. We relate them to the evolution
of galaxies through phases of gas compaction, depletion, possible
replenishment, and eventual quenching. We find that the high-SFR galaxies in
the upper envelope of the MS are compact, with high gas fractions and short
depletion times ("blue nuggets"), while the lower-SFR galaxies in the lower
envelope have lower central gas densities, lower gas fractions and longer
depletion times, consistent with observed gradients across the MS.
Stellar-structure gradients are negligible. The SFGs oscillate about the MS
ridge on timescales $\sim0.4~t_{\mathrm{Hubble}}$ ($\sim1$ Gyr at $z\sim3$).
The propagation upwards is due to gas compaction, triggered, e.g., by mergers,
counter-rotating streams, and/or violent disc instabilities. The downturn at
the upper envelope is due to central gas depletion by peak star formation and
outflows while inflow from the shrunken gas disc is suppressed. An upturn at
the lower envelope can occur once the extended disc has been replenished by
fresh gas and a new compaction can be triggered, namely as long as the
replenishment time is shorter than the depletion time. The mechanisms of gas
compaction, depletion and replenishment confine the SFGs to the narrow
($\pm0.3$ dex) MS. Full quenching occurs in massive haloes
($M_{\mathrm{vir}}>10^{11.5}~M_\odot$) and/or at low redshifts ($z<3$), where
the replenishment time is long compared to the depletion time, explaining the
observed bending down of the MS at the massive end.


  It is well known that individual beliefs cannot be identified using
traditional choice data, unless we exogenously assume state-independent
utilities. In this paper, I propose a novel methodology that solves this
long-standing identification problem in a simple way. This method relies on the
extending the state space by introducing a proxy, for which the agent has no
stakes conditional on the original state space. The latter allows us to
identify the agent's conditional beliefs about the proxy given each state
realization, which in turn suffices for indirectly identifying her beliefs
about the original state space. This approach is analogous to the one of
instrumental variables in econometrics. Similarly to instrumental variables,
the appeal of this method comes from the flexibility in selecting a proxy.


  Let A be finite set equipped with a probability distribution P, and let M be
a "mass" function on A. A characterization is given for the most efficient way
in which A^n can be covered using spheres of a fixed radius. A covering is a
subset C_n of A^n with the property that most of the elements of A^n are within
some fixed distance from at least one element of C_n, and "most of the
elements" means a set whose probability is exponentially close to one (with
respect to the product distribution P^n). An efficient covering is one with
small mass M^n(C_n). With different choices for the geometry on A, this
characterization gives various corollaries as special cases, including Marton's
error-exponents theorem in lossy data compression, Hoeffding's optimal
hypothesis testing exponents, and a new sharp converse to some measure
concentration inequalities on discrete spaces.


  In this contribution we briefly report on the progress and open problems in
parton distribution functions (PDFs), with emphasis on their implications for
LHC phenomenology. Then we study the impact of the recent ATLAS and CMS W
lepton asymmetry data on the NNPDF2.1 parton distributions. We show that these
data provide the first constrains on PDFs from LHC measurements.


  We review the properties of Majorana fermions in particle physics and point
out that Majorana modes in solid state systems are significantly different. The
key reason is the concept of anti-particle in solid state systems is different
from its counterpart in particle physics. We define Majorana modes as the
eigenstates of Majorana operators and find that they can exist both at edges
and in the bulk. According to our definition, only one single Majorana mode can
exist in a system no matter at edges or in the bulk. Kitaev's spinless $p$-wave
superconductor is used to illustrate our results and the dynamical behavior of
the Majorana modes.


  Many proposals in exploring topological quantum computation are based on
superconducting quantum devices constructed on materials with strong spin-orbit
coupling (SOC). For these devices, a full control on both the magnitude and the
spatial distribution of the supercurrent would be highly demanded, but has been
elusive up to now. We constructed proximity-type Josephson junction on
nanoplates of Bi2O2Se, a new emerging semiconductor with strong SOC. Through
electrical gating, we show that the supercurrent can be fully turned ON and
OFF, and its real-space pathways can be configured either through the bulk or
along the edges. Our work demonstrates Bi2O2Se as a promising platform for
constructing multifunctional hybrid superconducting devices as well as for
searching for topological superconductivity.


  We have measured the dayside spectrum of HD 189733b between 1.5 and 2.5
microns using the NICMOS instrument on the Hubble Space Telescope. The emergent
spectrum contains significant modulation, which we attribute to the presence of
molecular bands seen in absorption. We find that water (H2O), carbon monoxide
(CO), and carbon dioxide (CO2) are needed to explain the observations, and we
are able to estimate the mixing ratios for these molecules. We also find
temperature decreases with altitude in the ~0.01 < P < ~1 bar region of the
dayside near-infrared photosphere and set an upper limit to the dayside
abundance of methane (CH4) at these pressures.


  We have used a model of magnetic accretion to investigate the accretion flows
of magnetic cataclysmic variables. Numerical simulations demonstrate that four
types of flow are possible: discs, streams, rings and propellers. The
fundamental observable determining the accretion flow, for a given mass ratio,
is the spin-to-orbital period ratio of the system. If IPs are accreting at
their equilibrium spin rates, then for a mass ratio of 0.5, those with
Pspin/Porb < 0.1 will be disc-like, those with 0.1 < Pspin/Porb < 0.6 will be
stream-like, and those with Pspin/Porb ~ 0.6 will be ring-like. The spin to
orbital period ratio at which the systems transition between these flow types
increases as the mass ratio of the stellar components decreases.
  For the first time we present evolutionary tracks of mCVs which allow
investigation of how their accretion flow changes with time. As systems evolve
to shorter orbital periods and smaller mass ratios, in order to maintain spin
equilibrium, their spin-to-orbital period ratio will generally increase. As a
result, the relative occurrence of ring-like flows will increase, and the
occurrence of disc-like flows will decrease, at short orbital periods. The
growing number of systems observed at high spin-to-orbital period ratios with
orbital periods below 2h, and the observational evidence for ring-like
accretion in EX Hya, are fully consistent with this picture.


  We devise a distributed asynchronous stochastic epsilon-gradient-based
algorithm to enable a network of computing and communicating nodes to solve a
constrained discrete-time time-varying stochastic convex optimization problem.
Each node updates its own decision variable only once every discrete time step.
Under some assumptions (among which, strong convexity, Lipschitz continuity of
the gradient, persistent excitation), we prove the algorithm's asymptotic
convergence in expectation to an error bound whose size is related to the
constant stepsize choice alpha, the variability in time of the optimization
problem, and to the accuracy epsilon. Moreover, the convergence rate is linear.
Then, we show how to compute locally stochastic epsilon-gradients that depend
also on the time-varying noise probability density function (PDF) of the
neighboring nodes, without requiring the neighbors to send such PDFs at each
time step. We devise utility-based policies to allow each node to decide
whether to send or not the most up-to-date PDF, which guarantee a given
user-specified error level epsilon in the computation of the stochastic
epsilon-gradient. Numerical simulations display the added value of the proposed
approach and its relevance for estimation and control of time-varying processes
and networked systems.


  The observed redshifts and magnitudes of the host galaxies of gamma-ray
bursts (GRBs) are compared with the predictions of three basic GRB models, in
which the comoving rate density of GRBs is (1) proportional to the cosmic star
formation rate density, (2) proportional to the total integrated stellar
density and (3) constant. All three models make the assumption that at every
epoch the probability of a GRB occuring in a galaxy is proportional to that
galaxy's broad-band luminosity. No assumption is made that GRBs are standard
candles or even that their luminosity function is narrow. All three rate
density models are consistent with the observed GRB host galaxies to date,
although model (2) is slightly disfavored relative to the others. Models (1)
and (3) make very similar predictions for host galaxy magnitude and redshift
distributions; these models will be probably not be distinguished without
measurements of host-galaxy star-formation rates. The fraction of host galaxies
fainter than 28 mag may constrain the faint end of the galaxy luminosity
function at high redshift, or, if the fraction is observed to be low, may
suggest that the bursters are expelled from low-luminosity hosts. In all
models, the probability of finding a z<0.008 GRB among a sample of 11 GRBs is
less than 10^(-4), strongly suggesting that GRB 980425, if associated with
supernova 1998bw, represents a distinct class of GRBs.


  Distinct seed formation mechanisms are imprinted upon the fraction of dwarf
galaxies currently containing a central supermassive black hole. Seeding by Pop
III remnants is expected to produce a higher occupation fraction than is
generated with direct gas collapse precursors. Chandra observations of nearby
early-type galaxies can directly detect even low-level supermassive black hole
activity, and the active fraction immediately provides a firm lower limit to
the occupation fraction. Here, we use the volume-limited AMUSE surveys of ~200
optically-selected early-type galaxies to characterize simultaneously, for the
first time, the occupation fraction and the scaling of nuclear X-ray luminosity
with stellar mass, accounting for intrinsic scatter, measurement uncertainties,
and X-ray limits. For early-type galaxies with log(M_star/M_sun)<10, we obtain
a lower limit to the occupation fraction of >20% (at 95% confidence), but full
occupation cannot be excluded. The preferred dependence of log(L_X) upon
log(M_star) has a slope of about 0.7-0.8, consistent with the "downsizing"
trend previously identified from the AMUSE dataset, and a uniform Eddington
efficiency is disfavored at ~2 sigma. We provide guidelines for the future
precision with which these parameters may be refined with larger or more
sensitive samples.


  We suggest a new way of the determining abundances and electron temperatures
in HII regions from strong emission lines. Our approach is based on the
standard assumption that HII regions with similar intensities of strong
emission lines have similar physical properties and abundances. A "counterpart"
for a studied HII region may be chosen among HII regions with well-measured
abundances (reference HII regions) by comparison of carefully chosen
combinations of strong line intensities. Then the abundances in the
investigated HII region can be assumed to be the same as that in its
counterpart. In other words, we suggest to determine the abundances in HII
regions "by precedent". To get more reliable abundances for the considered HII
region, a number of reference HII regions is selected and then the abundances
in the target HII region is estimated through extra-/interpolation. We will
refer to this method of abundance determination as the counterpart method or,
for brevity, the C method. We define a sample of reference HII regions and
verify the validity of the C method. We find that this method produces reliable
abundances. Finally, the C method is used to obtain the radial abundance
distributions in the extended discs of the spiral galaxies M83, NGC4625 and NGC
628.


  The purpose of this paper is to answer the following question : is it
possible to find a gauge group G and a space-time dimension D such that
anomalies constrain the fermion content to be composed of the 3 known families
of quarks and leptons ? The answer is, in some way, unique and consists in
taking an SU(5) gauge group in 6 dimensions. This work has been done with the
collaboration of N. Borghini and M. H. Tytgat.


  We compute the magnetic response of hollow semimetal cylinders and rings to
the presence of an axial Aharonov-Bohm magnetic flux, in the absence of
interactions. We predict nullification of the Aharonov-Bohm effect for a class
of dispersion laws that includes "non-relativistic" dispersion and demonstrate
that at zero flux the ground-state of a very short "armchair" graphene tube
will exhibit a ferromagnetic broken symmetry. We also compute the diamagnetic
response of bulk semimetals to the presence of a uniform magnetic field,
specifically predicting that the susceptibility has a logarithmic dependence on
the size of the sample.


  We propose a Distributionally Robust Optimization (DRO) formulation with a
Wasserstein-based uncertainty set for selecting grouped variables under
perturbations on the data for both linear regression and classification
problems. The resulting model offers robustness explanations for Grouped Least
Absolute Shrinkage and Selection Operator (GLASSO) algorithms and highlights
the connection between robustness and regularization. We prove probabilistic
bounds on the out-of-sample loss and the estimation bias, and establish the
grouping effect of our estimator, showing that coefficients in the same group
converge to the same value as the sample correlation between covariates
approaches 1. Based on this result, we propose to use the spectral clustering
algorithm with the Gaussian similarity function to perform grouping on the
predictors, which makes our approach applicable without knowing the grouping
structure a priori. We compare our approach to an array of alternatives and
provide extensive numerical results on both synthetic data and a real large
dataset of surgery-related medical records, showing that our formulation
produces an interpretable and parsimonious model that encourages sparsity at a
group level and is able to achieve better prediction and estimation performance
in the presence of outliers.


  We study the magnetic relaxation rate Gamma of the single-molecule magnet
Mn_{12}-tBuAc as a function of magnetic field component H_T transverse to the
molecule's easy axis. When the spin is near a magnetic quantum tunneling
resonance, we find that Gamma increases abruptly at certain values of H_T.
These increases are observed just beyond values of H_T at which a
geometric-phase interference effect suppresses tunneling between two excited
energy levels. The effect is washed out by rotating H_T away from the spin's
hard axis, thereby suppressing the interference effect. Detailed numerical
calculations of Gamma using the known spin Hamiltonian accurately reproduce the
observed behavior. These results are the first experimental evidence for
geometric-phase interference in a single-molecule magnet with true four-fold
symmetry.


  This letter presents and analyzes orthogonal frequency-division multiplexing
(OFDM)-based multi-carrier transmission for cell-free massive multi-input
multi-output (CFmMIMO) over frequency-selective fading channels.
Frequency-domain conjugate beamforming, pilot assignment, and user-specific
resource allocation are proposed. CFmMIMO-OFDM is scalable to serve a massive
number of users and is flexible to offer diverse data rates for heterogeneous
applications.


  Radio-based vehicular simultaneous localization and mapping (SLAM) aims to
localize vehicles while mapping the landmarks in the environment. We propose a
sequence of three Poisson multi-Bernoulli mixture (PMBM) based SLAM filters,
which handle the entire SLAM problem in a theoretically optimal manner. The
complexity of the three proposed SLAM filters is progressively reduced while
sustaining high accuracy by deriving SLAM density approximation with the
marginalization of nuisance parameters (either vehicle state or data
association). Firstly, the PMBM SLAM filter serves as the foundation, for which
we provide the first complete description based on a Rao-Blackwellized particle
filter. Secondly, the Poisson multi-Bernoulli (PMB) SLAM filter is based on the
standard reduction from PMBM to PMB, but involves a novel interpretation based
on auxiliary variables and a relation to Bethe free energy. Finally, using the
same auxiliary variable argument, we derive a marginalized PMB SLAM filter,
which avoids particles and is instead implemented with a low-complexity
cubature Kalman filter. We evaluate the three proposed SLAM filters in
comparison with the probability hypothesis density (PHD) SLAM filter in 5G
mmWave vehicular networks and show the computation-performance trade-off
between them.


  The purpose of this work is to prove existence of a weak solution of the two
dimensional incompressible Euler equations on a noncylindrical domain
consisting of a smooth, bounded, connected and simply connected domain
undergoing a prescribed motion. We prove existence of a weak solution for
initial vorticity in $L^p$, for $p>1$. This work complements a similar result
by C. He and L. Hsiao, who proved existence assuming that the flow velocity is
tangent to the moving boundary, see [JDE v. 163 (2000) 265--291].


  We propose here a robust scheme to infer the physical parameters of compact
stars from their f-mode gravitational wave signals. We first show that the
frequency and the damping rate of f-mode oscillation of compact stars can be
expressed in terms of universal functions of stellar mass and moment of
inertia. By employing the universality in the f-mode one can then infer
accurate values of the mass, the moment of inertia and the radius of a compact
star. In addition, we demonstrate that our new scheme works well for both
realistic neutron stars and quark stars, and hence provides a unifying way to
infer the physical parameters of compact stars.


  (Abridged) We describe the results of the highest-resolution radio
observations yet made of four relic radio sources in the Abell clusters A13,
A85, A133 and A4038. Our VLA images at 1.4 GHz with 4" resolution show a
remarkable variety of fine structure in the form of spectacular arcs, wisps,
plumes and loops. Their integrated radio flux densities fall very rapidly with
frequency, with power-law slopes between 2.1 and 4.4 near 1.4 GHz The relics
possess linear polarization levels ranging between 2.3 % (A133) and 35 % (A85);
the higher polarization fractions imply a highly ordered magnetic field in the
fine structure and low differential Faraday rotation in the intervening cluster
gas. The optical identification of host galaxies remains problematic. In A85,
A133 and A4038 the travel times for the brightest cluster galaxies are
significantly longer than the modeled ages of the relics and nearby bright
ellipticals provide a better match. Excess X-ray emission in the 0.5 keV-to-2
keV band was found near the relics in A85 and A133. The surface brightness was
too high to be attributed to the inverse-Compton mechanism alone. We found
excellent fits to the broad-band radio spectra using the anisotropic (KGKP)
model of spectral ageing, and we have extended the model to include diffusion
of particles between regions of different field strength (the Murgia-JP, or
MJP, model). The steep radio spectra imply ages for the relics of ~ 10^8 yr, at
the start of which period their radio luminosities would have been ~ 10^25 W/Hz
at 1.4 GHz.


  Generative search engines have the potential to transform how people seek
information online, but generated responses from existing large language models
(LLMs)-backed generative search engines may not always be accurate.
Nonetheless, retrieval-augmented generation exacerbates safety concerns, since
adversaries may successfully evade the entire system by subtly manipulating the
most vulnerable part of a claim. To this end, we propose evaluating the
robustness of generative search engines in the realistic and high-risk setting,
where adversaries have only black-box system access and seek to deceive the
model into returning incorrect responses. Through a comprehensive human
evaluation of various generative search engines, such as Bing Chat,
PerplexityAI, and YouChat across diverse queries, we demonstrate the
effectiveness of adversarial factual questions in inducing incorrect responses.
Moreover, retrieval-augmented generation exhibits a higher susceptibility to
factual errors compared to LLMs without retrieval. These findings highlight the
potential security risks of these systems and emphasize the need for rigorous
evaluation before deployment.


  We discuss novel ways in which neutrino oscillation experiments can probe
dark matter. In particular, we focus on interactions between neutrinos and
ultra-light ("fuzzy") dark matter particles with masses of order $10^{-22}$ eV.
It has been shown previously that such dark matter candidates are
phenomenologically successful and might help ameliorate the tension between
predicted and observed small scale structures in the Universe. We argue that
coherent forward scattering of neutrinos on fuzzy dark matter particles can
significantly alter neutrino oscillation probabilities. These effects could be
observable in current and future experiments. We set new limits on fuzzy dark
matter interacting with neutrinos using T2K and solar neutrino data, and we
estimate the sensitivity of reactor neutrino experiments and of future
long-baseline accelerator experiments. These results are based on detailed
simulations in GLoBES. We allow the dark matter particle to be either a scalar
or a vector boson. In the latter case, we find potentially interesting
connections to models addressing various $B$ physics anomalies.


  We propose a latent space dynamics identification method, namely tLaSDI, that
embeds the first and second principles of thermodynamics. The latent variables
are learned through an autoencoder as a nonlinear dimension reduction model.
The latent dynamics are constructed by a neural network-based model that
precisely preserves certain structures for the thermodynamic laws through the
GENERIC formalism. An abstract error estimate is established, which provides a
new loss formulation involving the Jacobian computation of autoencoder. The
autoencoder and the latent dynamics are simultaneously trained to minimize the
new loss. Computational examples demonstrate the effectiveness of tLaSDI, which
exhibits robust generalization ability, even in extrapolation. In addition, an
intriguing correlation is empirically observed between a quantity from tLaSDI
in the latent space and the behaviors of the full-state solution.


  Liquid foam flows in a Hele-Shaw cell were investigated. The plug flow
obtained for a monodisperse foam is strongly perturbed in the presence of
bubbles whose size is larger than the average bubble size by an order of
magnitude at least. The large bubbles migrate faster than the mean flow above a
velocity threshold which depends on its size. We evidence experimentally this
new instability and, in case of a single large bubble, we compare the large
bubble velocity with the prediction deduced from scaling arguments. In case of
a bidisperse foam, an attractive interaction between large bubbles induces
segregation and the large bubbles organize themselves in columns oriented along
the flow. These results allow to identify the main ingredients governing 2D
polydisperse foam flows.


  In cosmological first-order phase transitions, the microscopic interaction of
the phase transition fronts with non-equilibrium plasma particles manifests
itself macroscopically as friction forces. In general, it is a nontrivial
problem to compute these forces, and only two limits have been studied, namely,
that of very slow walls and, more recently, ultra-relativistic walls which run
away. In this paper we consider ultra-relativistic velocities and show that
stationary solutions still exist when the parameters allow the existence of
runaway walls. Hence, we discuss the necessary and sufficient conditions for
the fronts to actually run away. We also propose a phenomenological model for
the friction, which interpolates between the non-relativistic and
ultra-relativistic values. Thus, the friction depends on two friction
coefficients which can be calculated for specific models. We then study the
velocity of phase transition fronts as a function of the friction parameters,
the thermodynamic parameters, and the amount of supercooling.


  The optical/near-infrared (OIR) region of the spectra of low-mass X-ray
binaries appears to lie at the intersection of a variety of different emission
processes. In this paper we present quasi-simultaneous OIR - X-ray observations
of 33 XBs in an attempt to estimate the contributions of various emission
processes in these sources, as a function of X-ray state and luminosity. A
global correlation is found between OIR and X-ray luminosity for low-mass black
hole candidate XBs (BHXBs) in the hard X-ray state, of the form L_OIR is
proportional to Lx^0.6. This correlation holds over 8 orders of magnitude in Lx
and includes data from BHXBs in quiescence and at large distances (LMC and
M31). A similar correlation is found in low-mass neutron star XBs (NSXBs) in
the hard state. For BHXBs in the soft state, all the near-infrared (NIR) and
some of the optical emission is suppressed below the correlation, a behaviour
indicative of the jet switching off/on in transition to/from the soft state. We
compare these relations to theoretical models of a number of emission
processes. We find that X-ray reprocessing in the disc and emission from the
jets both predict a slope close to 0.6 for BHXBs, and both contribute to the
OIR in BHXBs in the hard state, the jets producing ~90 percent of the NIR
emission at high luminosities. X-ray reprocessing dominates the OIR in NSXBs in
the hard state, with possible contributions from the jets (only at high
luminosity) and the viscously heated disc. We also show that the optically
thick jet spectrum of BHXBs extends to near the K-band. (abridged)


  Black holes and wormholes are solutions of Einstein's field equations, both
of which, from afar, look like a central mass. We show here that although at
large distances both behave like Newtonian objects, close to the event horizon
or to the throat, black holes and wormholes have different tidal effects on
stars, due to their respective geometries. We quantify this difference by a
numerical procedure in the Schwarzschild black hole and the exponential
wormhole backgrounds, and compare the peak fallback rates of tidal debris in
these geometries. The tidal disruption rates in these backgrounds are also
computed. It is shown that these quantities are a few times higher for
wormholes, compared to the black hole cases.


  A non-perturbative study on the quantum fluctuations of light ray propagation
through a quantum region of spacetime is long overdue. Within the theory of
Lorentzian simplicial quantum gravity, we compute the probabilities for a test
light ray to land at different locations after travelling through a
symmetry-reduced box region in 2,3 and 4 spacetime dimensions. It is found that
for fixed boundary conditions, light ray fluctuations are generically large
when all coupling constants are relatively small in absolute value. For fixed
coupling constants, as the boundary size is decreased light ray fluctuations
first increase and then decrease in a 2D theory with the cosmological constant,
Einstein-Hilbert and R-squared terms. While in 3D and 4D theories with the
cosmological constant and Einstein-Hilbert terms, as the boundary size is
decreased light ray fluctuations just increase. Incidentally, when studying 2D
quantum gravity we show that the global time-space duality with the
cosmological constant and Einstein-Hilbert terms noted previously also holds
when arbitrary even powers of the Ricci scalar are added. We close by
discussing how light ray fluctuations can be used in obtaining the continuum
limit of non-perturbative Lorentzian quantum gravity.


  We present results of the search for hard X-ray/soft $\gamma$-ray emission in
coincidence with publicly reported (via Transient Name Server, TNS;
http://www.wis-tns.org/) fast radio bursts (FRBs). The search was carried out
using continuous Konus-Wind data with 2.944 s time resolution. We perform a
targeted search for each individual burst from 581 FRBs, along with a stacking
analysis of the bursts from 8 repeating sources in our sample and a separate
stacking analysis of the bursts from the non-repeating FRBs. We find no
significant associations in either case. We report upper bounds on the hard
X-ray (20 - 1500 keV) flux assuming four spectral models, which generally
describe spectra of short and long GRBs, magnetar giant flares, and the short
burst, coincident with FRB 200428 from a Galactic magnetar. Depending on the
spectral model, our upper bounds are in the range of $(0.1 - 2) \times10^{-6}$
erg cm$^{-2}$. For 18 FRBs with known distances we present upper bounds on the
isotropic equivalent energy release and peak luminosity. For the nearest FRB
200120E, we derive the most stringent upper bounds of $E_{\text{iso}}\leq$2.0
$\times 10^{44}$ erg and $L_{\text{iso}}\leq$1.2 $\times 10^{44}$ erg s$^{-1}$.
Furthermore, we report lower bounds on radio-to-gamma-ray fluence ratio
$E_{\text{radio}}/E_{\text{iso}} \geq 10^{-11}-10^{-9}$ and compare our results
with previously reported searches and theoretical predictions for high-energy
counterparts to FRBs.


  Spain is the third-largest producer of pork meat in the world, and many farms
in several regions depend on the evolution of this market. However, the current
pricing system is unfair, as some actors have better market information than
others. In this context, historical pricing is an easy-to-find and affordable
data source that can help all agents to be better informed. However, the time
lag in data acquisition can affect their pricing decisions. In this paper, we
study the effect that data acquisition delay has on a price prediction system
using multiple prediction algorithms. We describe the integration of the best
proposal into a decision support system prototype and test it in a real-case
scenario. Specifically, we use public data from the most important regional
pork meat markets in Spain published by the Ministry of Agriculture with a
two-week delay and subscription-based data of the same markets obtained on the
same day. The results show that the error difference between the best public
and data subscription models is 0.6 Euro cents in favor of the data without
delay. The market dimension makes these differences significant in the supply
chain, giving pricing agents a better tool to negotiate market prices.


  Stimulated by Ma's idea which explains the tribimaximal neutrino mixing by
assuming an A_4 flavor symmetry, a lepton mass matrix model is investigated. A
Frogatt-Nielsen type model is assumed, and the flavor structures of the masses
and mixing are caused by the VEVs of SU(2)_L-singlet scalars \phi_i^u and
\phi_i^d (i=1,2,3), which are assigned to {\bf 3} and ({\bf 1}, {\bf 1}',{\bf
1}'') of A_4, respectively.


  Standard practice in training neural networks involves initializing the
weights in an independent fashion. The results of recent work suggest that
feature "diversity" at initialization plays an important role in training the
network. However, other initialization schemes with reduced feature diversity
have also been shown to be viable. In this work, we conduct a series of
experiments aimed at elucidating the importance of feature diversity at
initialization. We show that a complete lack of diversity is harmful to
training, but its effects can be counteracted by a relatively small addition of
noise - even the noise in standard non-deterministic GPU computations is
sufficient. Furthermore, we construct a deep convolutional network with
identical features at initialization and almost all of the weights initialized
at 0 that can be trained to reach accuracy matching its standard-initialized
counterpart.


  The notion of magnetic monopoles has puzzled physicists since the
introduction of Maxwell's Equations and famously Dirac had hypothesized them in
the context of quantum mechanics. While they have proved experimentally elusive
as elementary particles, the concept has come to describe excitations or
topological defects in various material systems, from liquid crystals, to Hall
systems, skyrmion lattices, and Bose-Einstein condensate. Perhaps the most
versatile manifestation of magnetic monopoles as quasiparticles in matter has
been in so-called spin ice materials. There, they represent violations of the
ice rule, carry a magnetic charge, and can move freely unbound. Spin ice
emergent magnetic monopoles appear at the atomic scale in rare earth
pyrochlores or at the nano-scale in artificial spin ices systems. Here we
demonstrate for the first time that the notion of magnetic monopoles can be
transported at the macroscopic scale. We have built a mechano-magnet realized
via 3D-printing, that consists of mechanical rotors on which macroscopic
magnets can pivot. By controlling the relative height of the rotors we can
achieve different regimes for magnetic monopoles, including the free monopole
state. We then explore their driven dynamics under field. In the future,
integration of our proof of principle in an elastic matrix can lead to novel
macroscopic mechano-magnetic materials, to explore unusual piezomagnetism and
magnetostriction, with applications to actuators and soft-robotics.


  The slow dynamics for a colloidal suspension of particles interacting with a
hard-core repulsion complemented by a short-ranged attraction is discussed
within the frame of mode-coupling theory for ideal glass transitions for
parameter points near a higher-order glass-transition singularity. The
solutions of the equations of motion for the density correlation functions are
solved for the square-well system in quantitative detail by asymptotic
expansion using the distance of the three control parameters packing fraction,
attraction strength and attraction range from their critical values as small
parameters. For given wave vectors, distinguished surfaces in parameter space
are identified where the next-to-leading order contributions for the expansion
vanish so that the decay functions exhibit a logarithmic decay over large time
intervals. For both coherent and tagged particle dynamics the leading-order
logarithmic decay is accessible in the liquid regime for wave vectors of
several times the principal peak in the structure factor. The logarithmic decay
in the correlation function is manifested in the mean-squared displacement as a
subdiffusive power law with an exponent varying sensitively with the control
parameters. Shifting parameters through the distinguished surfaces, the
correlation functions and the logarithm of the mean-squared displacement
considered as functions of the logarithm of the time exhibit a crossover from
concave to convex behavior, and a similar scenario is obtained when varying the
wave vector.


  Non-Contact sensing is an emerging technology with applications across many
industries from driver monitoring in vehicles to patient monitoring in
healthcare. Current state-of-the-art implementations focus on RGB video, but
this struggles in varying/noisy light conditions and is almost completely
unfeasible in the dark. Near Infra-Red (NIR) video, however, does not suffer
from these constraints. This paper aims to demonstrate the effectiveness of an
alternative Convolution Attention Network (CAN) architecture, to regress
photoplethysmography (PPG) signal from a sequence of NIR frames. A combination
of two publicly available datasets, which is split into train and test sets, is
used for training the CAN. This combined dataset is augmented to reduce
overfitting to the 'normal' 60 - 80 bpm heart rate range by providing the full
range of heart rates along with corresponding videos for each subject. This
CAN, when implemented over video cropped to the subject's head, achieved a Mean
Average Error (MAE) of just 0.99 bpm, proving its effectiveness on NIR video
and the architecture's feasibility to regress an accurate signal output.


  We demonstrate the scale up of a symmetric three-path contrast interferometer
to large momentum separation. The observed phase stability at separation of 112
photon recoil momenta ($112\hbar k$) exceeds the performance of earlier
free-space interferometers. In addition to the symmetric interferometer
geometry and Bose-Einstein condensate source, the robust scalability of our
approach relies crucially on the suppression of undesired diffraction phases
through a careful choice of atom optics parameters. The interferometer phase
evolution is quadratic with number of recoils, reaching a rate as high as
$7\times10^7$ radians/s. We discuss the applicability of our method towards a
new measurement of the fine-structure constant and a test of QED.


  The task of the session-based recommendation is to predict the next
interaction of the user based on the anonymized user's behavior pattern. And
personalized version of this system is a promising research field due to its
availability to deal with user information. However, there's a problem that the
user's preferences and historical sessions were not considered in the typical
session-based recommendation since it concentrates only on user-item
interaction. In addition, the existing personalized session-based
recommendation model has a limited capability in that it only considers the
preference of the current user without considering those of similar users. It
means there can be the loss of information included within the hierarchical
data structure of the user-session-item. To tackle with this problem, we
propose USP-SBR(abbr. of User Similarity Powered - Session Based Recommender).
To model global historical sessions of users, we propose UserGraph that has two
types of nodes - ItemNode and UserNode. We then connect the nodes with three
types of edges. The first type of edges connects ItemNode as chronological
order, and the second connects ItemNode to UserNode, and the last connects
UserNode to ItemNode. With these user embeddings, we propose additional
contrastive loss, that makes users with similar intention be close to each
other in the vector space. we apply graph neural network on these UserGraph and
update nodes. Experimental results on two real-world datasets demonstrate that
our method outperforms some state-of-the-art approaches.


  With the upgrade of the RPCs [1]-[2] and the increase of its performances,
the study and the optimization of the read-out panel is necessary in order to
maintain the signal integrity and to reduce the intrinsic crosstalk. Through
Electromagnetic Simulation, performed with CST Studio Suite, new panels design
are tested and their crosstalk property are studied. The behavior of different
type of panel is shown, in particular a panel with the decoupling strip
connected through their characteristic impedance to the ground plane is
simulated.


  We use angle-resolved photoemission spectroscopy to study non-trivial surface
state in psuedobinary Bi2Se0.6Te2.3 topological insulator. We show that unlike
previously studied binaries, this is an intrinsic topological insulator with
conduction bulk band residing well above the chemical potential. Our data
indicates that under good vacuum condition there are no significant aging
effects for more then two weeks after cleaving. We also demonstrate that shift
of the Kramers point at low temperature is caused by UV assisted absorption of
molecular hydrogen. Our findings pave the way for applications of these
materials in devices and present an easy scheme to tune their properties.


  Recent fMRI-to-image approaches mainly focused on associating fMRI signals
with specific conditions of pre-trained diffusion models. These approaches,
while producing high-quality images, capture only a limited aspect of the
complex information in fMRI signals and offer little detailed control over
image creation. In contrast, this paper proposes to directly modulate the
generation process of diffusion models using fMRI signals. Our approach,
NeuroPictor, divides the fMRI-to-image process into three steps: i) fMRI
calibrated-encoding, to tackle multi-individual pre-training for a shared
latent space to minimize individual difference and enable the subsequent
multi-subject training; ii) fMRI-to-image multi-subject pre-training,
perceptually learning to guide diffusion model with high- and low-level
conditions across different individuals; iii) fMRI-to-image single-subject
refining, similar with step ii but focus on adapting to particular individual.
NeuroPictor extracts high-level semantic features from fMRI signals that
characterizing the visual stimulus and incrementally fine-tunes the diffusion
model with a low-level manipulation network to provide precise structural
instructions. By training with about 67,000 fMRI-image pairs from various
individuals, our model enjoys superior fMRI-to-image decoding capacity,
particularly in the within-subject setting, as evidenced in benchmark datasets.
Our code and model are available at https://jingyanghuo.github.io/neuropictor/.


  We consider the problem of numerical integration for weighted anchored and
ANOVA Sobolev spaces of $s$-variate functions. Here $s$ is large including
$s=\infty$. Under the assumption of sufficiently fast decaying weights, we
prove in a constructive way that such integrals can be approximated by
quadratures for functions $f_k$ with only $k$ variables, where
$k=k(\varepsilon)$ depends solely on the error demand $\varepsilon$ and is
surprisingly small when $s$ is sufficiently large relative to $\varepsilon$.
This holds, in particular, for $s=\infty$ and arbitrary $\varepsilon$ since
then $k(\varepsilon)<\infty$ for all $\varepsilon$. Moreover $k(\varepsilon)$
does not depend on the function being integrated, i.e., is the same for all
functions from the unit ball of the space.


  Multilingual neural machine translation (NMT) has recently been investigated
from different aspects (e.g., pivot translation, zero-shot translation,
fine-tuning, or training from scratch) and in different settings (e.g., rich
resource and low resource, one-to-many, and many-to-one translation). This
paper concentrates on a deep understanding of multilingual NMT and conducts a
comprehensive study on a multilingual dataset with more than 20 languages. Our
results show that (1) low-resource language pairs benefit much from
multilingual training, while rich-resource language pairs may get hurt under
limited model capacity and training with similar languages benefits more than
dissimilar languages; (2) fine-tuning performs better than training from
scratch in the one-to-many setting while training from scratch performs better
in the many-to-one setting; (3) the bottom layers of the encoder and top layers
of the decoder capture more language-specific information, and just fine-tuning
these parts can achieve good accuracy for low-resource language pairs; (4)
direct translation is better than pivot translation when the source language is
similar to the target language (e.g., in the same language branch), even when
the size of direct training data is much smaller; (5) given a fixed training
data budget, it is better to introduce more languages into multilingual
training for zero-shot translation.


  Superfluid turbulence is governed by two dimensionless parameters. One of
them is the intrinsic parameter q which characterizes the relative value of the
friction force acting on a vortex with respect to the non-dissipative forces.
The inverse parameter 1/q plays the same role as the Reynolds number Re=UR/\nu
in classical hydrodynamics. It marks the transition between the "laminar" and
turbulent regimes of vortex dynamics. The developed turbulence, described by a
Kolmogorov cascade, occurs when Re >> 1 in classical hydrodynamics. In
superfluids, the developed turbulence occurs at q << 1. Another parameter of
superfluid turbulence is the superfluid Reynolds number
  Re_s=UR/\kappa, which contains the circulation quantum \kappa characterizing
quantized vorticity in superfluids. The two parameters q and Re_s control the
crossover or transition between two classes of superfluid turbulence: (i) the
classical regime, where the Kolmogorov cascade (probably modified by the
non-canonical dissipation due to mutual friction) is effective, vortices are
locally polarized, and the quantization of vorticity is not important; and (ii)
the Vinen quantum turbulence where the properties are determined by the
quantization of vorticity. The phase diagram of these dynamical vortex states
is suggested.


  We revisit the hadronization and decay of excited heavy mesons and heavy
baryons in Herwig 7 general-purpose event-generator, following four distinct
steps: (i) Passing through the polarization of heavy hadrons at the end of
parton shower through the application of heavy quark effective theory (HQET),
where the emergence of a spin-flavour symmetry allows for the determination of
the polarizations of the excited heavy mesons and heavy baryons from the
helicity states of the light and heavy quarks. (ii) Improving the strong and
radiative decay modes of the excited heavy mesons, where in the absence of
conclusive experimental data on many of the decays, one needs to rely on HQET
symmetries to determine the favoured decay modes, widths and branching ratios.
(iii) Re-examination of the production rates of heavy hadrons using all
available experimental data sources and (iv) performing a general tune for
Herwig's free parameters to reflect the implemented changes. We compare our
predictions against existing experimental data in the presence/absence of the
newly implemented updates. These improvements will be available with
Herwig-7.3.0 public release.


  The ground states of the Bernasconi model are binary +1/-1 sequences of
length N with low autocorrelations. We introduce the notion of perfect
sequences, binary sequences with one-valued off-peak correlations of minimum
amount. If they exist, they are ground states. Using results from the
mathematical theory of cyclic difference sets, we specify all values of N for
which perfect sequences do exist and how to construct them. For other values of
N, we investigate almost perfect sequences, i.e. sequences with two-valued
off-peak correlations of minimum amount. Numerical and analytical results
support the conjecture that almost perfect sequences do exist for all values of
N, but that they are not always ground states. We present a construction for
low-energy configurations that works if N is the product of two odd primes.


  Hittmeir recently presented a deterministic algorithm that provably computes
the prime factorisation of a positive integer $N$ in $N^{2/9+o(1)}$ bit
operations. Prior to this breakthrough, the best known complexity bound for
this problem was $N^{1/4+o(1)}$, a result going back to the 1970s. In this
paper we push Hittmeir's techniques further, obtaining a rigorous,
deterministic factoring algorithm with complexity $N^{1/5+o(1)}$.