  Status of lattice calculations of hadron matrix elements along with CP
violation in B and in K systems is reviewed. Lattice has provided useful input
which, in conjunction with experimenatl data, leads to the conclusion that
CP-odd phase in the CKM matrix plays the dominant role in the observed
asymmetry in $B \to \psi K_s$. It is now quite likely that any beyond the SM,
CP-odd, phase will cause only small deviations in B-physics. Search for the
effects of the new phase(s) will consequently require very large data samples
as well as very precise theoretical predictions. Clean determination of {\it
all} the angles of the unitarity triangle therefore becomes essential. In this
regard $B \to K D^0$ processes play a unique role. Regarding K-decays,
remarkable progress made by theory with regard to maintenance of chiral
symmetry on the lattice is briefly discussed. First application already provide
quantitaive information on $B_K$ and the $\Delta I=1/2$ rule. The enhancement
in $Re A_0$ appears to arise solely from tree operators, esp. $Q_2$; penguin
contribution to $Re A_0$ appears to be very small. However, improved
calculations are necessary for $\epsilon^'/epsilon$ as there the contributions
of QCD penguins and electroweak penguins largely seem to cancel. There are good
reasons, though, to believe that these cancellations will not survive
improvements that are now underway. Importance of determining the unitarity
triangle purely from K-decays is also emphasized.


  We formulate a method for incorporating quantum fluctuations into molecular-
dynamics simulations of many-body systems, such as those employed for energetic
nuclear collision processes. Based on Fermi's Golden Rule, we allow spontaneous
transitions to occur between the wave packets which are not energy eigenstates.
The ensuing diffusive evolution in the space of the wave packet parameters
exhibits appealing physical properties, including relaxation towards quantum-
statistical equilibrium.


  The potential existence of a fifth fundamental force, mediated by the X17
boson, has generated significant interest. This force can manifest itself as
either a vector or pseudoscalar particle. In order to gain insight into the
effective potentials produced by the X17 boson for hyperfine interactions in
muonic systems, we conduct calculations for both the pseudoscalar and vector
hypotheses. Our study reveals that, for muonic atoms with nuclear charge
numbers ranging from 10 to 15, the energy shift associated with the fifth force
can be as high as 0.61 eV. These effects have the potential to be detected
through the utilization of high-precision X-ray detectors that are used to
analyze the energy spectrum of muonic characteristic X-rays.


  Anisotropy is one factor that appears to be significantly important in the
studies of relativistic compact stars. In this paper, we make a generalization
of the Buchdahl limit by incorporating an anisotropic effect for a selected
class of exact solutions describing anisotropic stellar objects. In the
isotropic case of a homogeneous distribution, we regain the Buchdahl limit
$2M/R \leq 8/9$. Our investigation shows a direct link between the maximum
allowed compactness and pressure anisotropy vi-a-vis geometry of the associated
$3$-space.


  Motivated to understand the behavior of biological filaments interacting with
membranes of various types, we study a theoretical model for the shape and
thermodynamics of intrinsically-helical filaments bound to curved membranes. We
show filament-surface interactions lead to a host of non-uniform shape
equilibria, in which filaments progressively unwind from their native twist
with increasing surface interaction and surface curvature, ultimately adopting
uniform-contact curved shapes. The latter effect is due to non-linear coupling
between elastic twist and bending of filaments on anisotropically-curved
surfaces, such as the cylindrical surfaces considered here. Via a combination
of numerical solutions and asymptotic analysis of shape equilibria we show that
filament conformations are critically sensitive to the surface curvature in
both the strong- and weak-binding limits. These results suggest that local
structure of membrane-bound chiral filaments is generically sensitive to the
curvature-radius of the surface to which it is bound, even when that radius is
much larger than the filament intrinsic pitch. Typical values of elastic
parameters and interaction energies for several prokaryotic and eukaryotic
filaments indicate that biopolymers are inherently very sensitive to the
coupling between twist, interactions and geometry and that this could be
exploited for regulation of a variety of processes such as the targeted
exertion of forces, signaling and self-assembly in response to geometric cues
including the local mean and Gaussian curvatures.


  Given two metric spaces $\mathcal N \subseteq \mathcal M$ in inclusion and
$0<p\leq 1$, we wish to determine the smallest constant $\mathfrak{t}_p
(\mathcal N, \mathcal M)$ such that any Lipschitz map $f: \mathcal N \to Z$
into any $p$-Banach space $Z$ can be extended to a Lipschitz map $f' : \mathcal
M \to Z$ satisfying $\operatorname{Lip} f' \leq \mathfrak{t}_p (\mathcal N,
\mathcal M)\cdot \operatorname{Lip} f$. In this article, we prove that if
$\mathcal N$ has finite Nagata dimension at most $d$ with constant $\gamma$,
then $\mathfrak{t}_p (\mathcal N, \mathcal M) \lesssim_p \gamma \cdot
(d+1)^{1/p -1} \cdot \log (d+2)$ for all $0<p\leq 1$. We show that examples of
spaces with finite Nagata dimension include doubling spaces, as well as
minor-excluded metric graphs. We also establish that the constant
$\mathfrak{t}_p (\mathcal N, \mathcal M)$ generally increases as $p$ approaches
zero.


  We study the dynamical instability against bar-mode deformation of
differentially rotating stars. We performed numerical simulation and linear
perturbation analysis adopting polytropic equations of state with the
polytropic index $n=1$. It is found that rotating stars of a high degree of
differential rotation are dynamically unstable even for the ratio of the
kinetic energy to the gravitational potential energy of $O(0.01)$.
Gravitational waves from the final nonaxisymmetric quasistationary states are
calculated in the quadrupole formula. For rotating stars of mass $1.4M_{\odot}$
and radius several 10 km, gravitational waves have frequency several 100 Hz and
effective amplitude $\sim 5 \times 10^{-22}$ at a distance of $\sim 100$ Mpc.


  A previously unknown bright N-soliton solution for an intermediate nonlinear
Schr\"{o}dinger equation of focusing type is presented. This equation is
constructed as a reduction of an integrable system related to a Sato equation
of a 2-component KP hierarchy for certain differential--difference dispersion
relations. Bright soliton solutions are obtained in the form of double
Wronskian determinants.


  Comprehending the radio--infrared (IR) relations of the faint extragalactic
radio sources is important for using radio emission as a tracer of
star-formation in high redshift ($z$) star-forming galaxies (SFGs). Using deep
uGMRT observations of the ELAIS-N1 field in the 0.3--0.5\,GHz range, we study
the statistical properties of the radio--IR relations and the variation of the
`$q$-parameter' up to $z=2$ after broadly classifying the faint sources as SFGs
and AGN. We find the dust temperature ($\tdust$) to increase with $z$. This
gives rise to $\qmir$, measured at $24\,\upmu$m, to increase with $z$ as the
peak of IR emission shifts towards shorter wavelengths, resulting in the
largest scatter among different measures of $q$-parameters. $\qfir$ measured at
$70\,\upmu$m, and $q_{\rm TIR}$ using total-IR (TIR) emission are largely
unaffected by $\tdust$. We observe strong, non-linear correlations between the
radio luminosities at 0.4 and 1.4\,GHz with $70\,\upmu$m luminosity and TIR
luminosity($\ltir$). To assess the possible role of the radio-continuum
spectrum in making the relations non-linear, for the first time we study them
at high $z$ using integrated radio luminosity ($\lrc$) in the range
0.1--2\,GHz. In SFGs, the $\lrc$--$\ltir$ relation remains non-linear with a
slope of $1.07\pm0.02$, has a factor of 2 lower scatter compared to
monochromatic radio luminosities, and $\qtirbol$ decreases with $z$ as
$\qtirbol = (2.27 \pm 0.03)\,(1+z)^{-0.12 \pm 0.03}$. A redshift variation of
$q$ is a natural consequence of non-linearity. We suggest that a redshift
evolution of magnetic field strengths and/or cosmic ray acceleration efficiency
in high-$z$ SFGs could give rise to non-linear radio--IR relations.


  Neutron-Transformer Reflectometry and Advanced Computation Engine (N-TRACE ),
a neural network model using transformer architecture, is introduced for
neutron reflectometry data analysis. It offers fast, accurate initial parameter
estimations and efficient refinements, improving efficiency and precision for
real-time data analysis of lithium-mediated nitrogen reduction for
electrochemical ammonia synthesis, with relevance to other chemical
transformations and batteries. Despite limitations in generalizing across
systems, it shows promises for the use of transformers as the basis for models
that could replace trial-and-error approaches to modeling reflectometry data.


  [Note: After the first version of this manuscript was uploaded, the authors
of [Berta, Brand\~ao, Gour, Lami, Plenio, Regula, and Tomamichel, Quantum 7,
1103 (2023)] pointed out an issue about a part of the claims in the previous
version of [Bluhm, Capel, Gondolf, P\'erez-Hern\'andez, IEEE Trans. Inf. Theory
69, 5869 (2023)] used in our analysis. Due to this issue, the analysis in the
previous version of this manuscript can no longer be considered complete proof
of the generalized quantum Stein's lemma. This version is a temporal update to
add this note. We are planning to update the manuscript further to explain the
issue and what conditions we will additionally need to complete the proof of
the generalized quantum Stein's lemma.]


  In this paper, we study the existence of solutions to the scalar additive
Jump problem and the Riemann boundary value problems in the context of
vectorial Clifford analysis on domains with fractal boundaries. A reduction
procedure is applied with great effectiveness to find the solution of the
problems.


  This paper focuses on building a blog search engine which doesn't focus only
on keyword search but includes extended search capabilities. It also
incorporates the blog-post concept clustering which is based on the category
extracted from the blog post semantic content analysis. The proposed approach
is titled as "BloSen (Blog Search Engine)". It involves in extracting the posts
from blogs and parsing them to extract the blog elements and store them as
fields in a document format. Inverted index is being built on the fields of the
documents. Search is induced on the index and requested query is processed
based on the documents so far made from blog posts. It currently focuses on
Blogger and Wordpress hosted blogs since both these hosting services are the
most popular ones in the blogosphere. The proposed BloSen model is experimented
with a prototype implementation and the results of the experiments with the
user's relevance cumulative metric value of 95.44% confirms the efficiency of
the proposed model.


  Recent progress in numerical relativity now allows computation of the binary
black hole merger, whereas post-Newtonian and perturbative techniques can be
used to model the inspiral and ringdown phases. So far, most gravitational-wave
searches have made use of various post-Newtonian-inspired templates to search
for signals arising from the coalescence of compact binary objects. Ajith et al
have produced hybrid waveforms for non-spinning binary black-hole systems which
include the three stages of the coalescence process, and constructed from them
phenomenological templates which capture the features of these waveforms in a
parametrized form. As a first step towards extending the present inspiral
searches to higher-mass binary black-hole systems, we have used these
phenomenological waveforms in a search for numerically-simulated signals
injected into synthetic LIGO data as part of the NINJA project.


  The hypothesis that Dark Matter is one electroweak multiplet leads to
predictive candidates with multi-TeV masses that can form electroweak bound
states. Bound states with the same quantum numbers as electroweak vectors are
found to be especially interesting, as they can be produced resonantly with
large cross sections at lepton colliders. Such bound states exist e.g. if DM is
an automatically stable fermionic weak 5-plet with mass $M \approx$ 14 TeV such
that the DM abundance is reproduced thermally. In this model, a muon collider
could resolve three such bound states. Production rates are so large that
details of DM spectroscopy can be probed with larger statistics: we compute the
characteristic pattern of single and multiple $\gamma$ lines.


  In finite many-body quantum systems such as nuclei, atoms, mesoscopic systems
like quantum dots and small metallic grains, interacting spin systems modeling
quantum computing core and BEC, the interparticle interactions are essentially
two-body in nature. Therefore, it is more appropriate to represent the complex
Hamiltonian of these systems by random ensembles that incorporate the two-body
nature of interactions. These ensembles are generically called embedded
Gaussian ensembles (EGEs). The aim of the present thesis is to identify and
systematically analyze many different physically relevant EGEs with symmetries
by considering a variety of quantities and measures that are important for
isolated finite interacting quantum systems.


  This paper examines several computer algorithms designed to assess mortality
and longevity risk.


  Whether we are alone in the universe is one of the greatest mysteries facing
humankind. Given the >100 billion stars in our galaxy, many have argued that it
is statistically unlikely that life, including intelligent life, has not
emerged anywhere else. The lack of any sign of extraterrestrial intelligence,
even though on a cosmic timescale extraterrestrial civilizations would have
enough time to cross the galaxy, is known as Fermi's Paradox. One possible
explanation for Fermi's Paradox is the Zoo Hypothesis which states that one or
more extraterrestrial civilizations know of our existence and can reach us, but
have chosen not to disturb us or even make their existence known to us. I
propose here a proactive test of the Zoo Hypothesis. Specifically, I propose to
send a message using television and radio channels to any extraterrestrial
civilization(s) that might be listening and inviting them to respond. Even
though I accept this is unlikely to be successful in the sense of resulting in
a response from extraterrestrial intelligences, the possibility that
extraterrestrial civilizations are monitoring us cannot be dismissed and my
proposal is consistent with current scientific knowledge. Besides, issuing an
invitation is technically feasible, cheap and safe, and few would deny the
profound importance of establishing contact with one or more extraterrestrial
intelligences. A website has been set up (http://active-seti.info) to encourage
discussion of this proposal and for drafting the invitation message.


  The Glashow resonance at E_\nu=6.3 PeV is a measure of the \bar\nu_e content
of the astrophysical neutrino flux. The fractional \bar\nu_e content depends on
the neutrino production model at the cosmic neutrino source, and the
environment at the source. Thus, the strength of the Glashow resonance event
rate is a potential window into astrophysical sources. We quantify the "Glashow
resonometer" and comment on the significance that no Glashow events are
observed in the IceCube three-year data.


  The rapid growth of e-commerce increases the need for larger warehouses and
their automation, thus using robots as assistants to human workers becomes a
priority. In order to operate efficiently and safely, robot assistants or the
supervising system should recognize human intentions. Theory of mind (ToM) is
an intuitive conception of other agents' mental state, i.e., beliefs and
desires, and how they cause behavior. In this paper we present a ToM-based
algorithm for human intention recognition in flexible robotized warehouses. We
have placed the warehouse worker in a simulated 2D environment with three
potential goals. We observe agent's actions and validate them with respect to
the goal locations using a Markov decision process framework. Those
observations are then processed by the proposed hidden Markov model framework
which estimated agent's desires. We demonstrate that the proposed framework
predicts human warehouse worker's desires in an intuitive manner and in the end
we discuss the simulation results.


  We present a method for obtaining quantum transport properties in graphene
that uniquely combines three crucial features: microscopic treatment of charge
disorder, fully quantum mechanical analysis of transport, and the ability to
model experimentally relevant system sizes. As a pertinent application we study
the disorder dependence of Klein tunneling dominated transport in p-n-p
junctions. Both the resistance and the Fano factor show broad resonance peaks
due to the presence of quasi bound states. This feature is washed out by the
disorder when the mean free path becomes of the order of the distance between
the two p-n interfaces.


  Local and global gravitational effects induced by eternal vacuum domain walls
are studied. We concentrate on thin walls between non-equal and non-positive
cosmological constants on each side of the wall. These vacuum domain walls fall
in three classes depending on the value of their energy density $\sigma$: (1)\
extreme walls with $\sigma = \sigma_{{\text{ext}}}$ are planar, static walls
corresponding to supersymmetric configurations, (2)\ non-extreme walls with
$\sigma = \sigma_{{\text{non}}} > \sigma_{{\text{ext}}}$ correspond to
expanding bubbles with observers on either side of the wall being {\em
inside\/} the bubble, and (3)\ ultra-extreme walls with $\sigma =
\sigma_{{\text{ultra}}} < \sigma_{{\text{ext}}}$ represent the bubbles of false
vacuum decay. On the sides with less negative cosmological constant, the
extreme, non-extreme, and ultra-extreme walls exhibit no, repulsive, and
attractive effective ``gravitational forces,'' respectively. These
``gravitational forces'' are global effects not caused by local curvature.
Since the non-extreme wall encloses observers on both sides, the supersymmetric
system has the lowest gravitational mass accessable to outside observers. It is
conjectured that similar positive mass protection occurs in all physical
systems and that no finite negative mass object can exist inside the universe.
We also discuss the global space-time structure of these singularity free
space-times and point out intriguing analogies with the causal structure of
black holes.


  Considering a general input distribution, using Gel'fand-Pinsker full binning
scheme and the Han- Kobayashi (HK) jointly decoding strategy, we obtain a new
achievable rate region for the cognitive radio channel (CRC) and then derive a
simplified description for the region, by a combination of Cover superposition
coding, binning scheme and the HK decoding technique. Our rate region (i) has
an interesting interpretation, i.e., any rate in the region, as expected, has
generally three additional terms in comparison with the KH region for the
interference channel (IC): one term due to the input correlation, the other
term due to binning scheme and the third term due to the interference dependent
on the inputs, (ii) is really a generalization of the HK region for the IC to
the CRC by the use of binning scheme, and as a result of this generalization we
see that different versions of our region for the CRC are reduced to different
versions of the previous results for the IC, and (iii) is a generalized and
improved version of previous results ,i.g., the Devroye-Mitran-Tarokh (DMT)
region.


  Semiconductor lasers have great potential for space laser communication.
However, excessive radiation in space can cause laser failure. Quantum dot (QD)
lasers are more resistant to radiation compared to quantum well (QW) and bulk
lasers due to better carrier confinement and a smaller active region.
Therefore, it is crucial to find the most radiation-tolerant QD structures and
compare the radiation tolerance of QD and QW structures at different radiation
fluences where the QDs can show their advantages in the best way. Proton and
60Co {\gamma}-ray radiation tests were conducted on different InAs/GaAs QD and
InGaAs/GaAs QW materials and devices. The results show that the QD samples were
more radiation-tolerant than QW samples within a certain fluence range, and
more radiation-tolerant QD structures were identified. Dislocations were found
near the QWs but not the QDs after 1 x 1011 cm-2 radiation. Defects were
created in all samples after 7 x 1013 cm-2 proton radiation. Additionally, 60Co
{\gamma}-rays radiation tests ranging from 10 to 12000 Gy were conducted, and
all the samples exhibited good tolerance to total radiation dose effects.


  Given a coloring of group elements, a rainbow solution to an equation is a
solution whose every element is assigned a different color. The rainbow number
of $\mathbb{Z}_n$ for an equation $eq$, denoted $rb(\mathbb{Z}_n,eq)$, is the
smallest number of colors $r$ such that every exact $r$-coloring of
$\mathbb{Z}_n$ admits a rainbow solution to the equation $eq$. We prove that
for every exact $4$-coloring of $\mathbb{Z}_p$, where $p\geq 3$ is prime, there
exists a rainbow solution to the Sidon equation $x_1+x_2=x_3+x_4$. Furthermore,
we determine the rainbow number of $\mathbb{Z}_n$ for the Sidon equation.


  This work, shows how propositional resolution can be generalized to obtain a
resolution proof system for constrained pseudo-propositional logic (CPPL),
which is an extension resulted from inserting the natural numbers with few
constraints symbols into the alphabet of propositional logic and adjusting the
underling language accordingly. Unlike the construction of CNF formulas which
are restricted to a finite set of clauses, the extended CPPL does not require
the corresponding set to be finite.
  Although this restriction is made dispensable, this work presents a
constructive proof showing that the generalized resolution for CPPL is sound
and complete. As a marginal result, this implies that propositional resolution
is also sound and complete for formulas with even infinite set of clauses.


  Ultrafast imaging of molecular chirality is a key step towards the dream of
imaging and interpreting electronic dynamics in complex and biologically
relevant molecules. Here, we propose a new ultrafast chiral phenomenon
exploiting recent advances in electron optics allowing access to the orbital
angular momentum of free electrons. We show that strong-field ionization of a
chiral target with a few-cycle linearly polarized 800 nm laser pulse yields
photoelectron vortices, whose chirality reveals that of the target, and we
discuss the mechanism underlying this phenomenon. Our work opens new
perspectives in recollision-based chiral imaging.


  In [Commun Math Phys 348(1), 129-143, 2016], Cheskidov et al. proved that
physically realizable weak solutions of the incompressible 2D Euler equations
on a torus conserve kinetic energy. Physically realizable weak solutions are
those that can be obtained as limits of vanishing viscosity. The key hypothesis
was boundedness of the initial vorticity in $L^p$, $p>1$. In this work we
extend their result, by adding forcing to the flow.


  As Natural Language Processing (NLP) systems become increasingly integrated
into human social life, these technologies will need to increasingly rely on
social intelligence. Although there are many valuable datasets that benchmark
isolated dimensions of social intelligence, there does not yet exist any body
of work to join these threads into a cohesive subfield in which researchers can
quickly identify research gaps and future directions. Towards this goal, we
build a Social AI Data Infrastructure, which consists of a comprehensive social
AI taxonomy and a data library of 480 NLP datasets. Our infrastructure allows
us to analyze existing dataset efforts, and also evaluate language models'
performance in different social intelligence aspects. Our analyses demonstrate
its utility in enabling a thorough understanding of current data landscape and
providing a holistic perspective on potential directions for future dataset
development. We show there is a need for multifaceted datasets, increased
diversity in language and culture, more long-tailed social situations, and more
interactive data in future social intelligence data efforts.


  In the realm of machine learning and statistical modeling, practitioners
often work under the assumption of accessible, static, labeled data for
evaluation and training. However, this assumption often deviates from reality
where data may be private, encrypted, difficult- to-measure, or unlabeled. In
this paper, we bridge this gap by adapting the Hui-Walter paradigm, a method
traditionally applied in epidemiology and medicine, to the field of machine
learning. This approach enables us to estimate key performance metrics such as
false positive rate, false negative rate, and priors in scenarios where no
ground truth is available. We further extend this paradigm for handling online
data, opening up new possibilities for dynamic data environments. Our
methodology involves partitioning data into latent classes to simulate multiple
data populations (if natural populations are unavailable) and independently
training models to replicate multiple tests. By cross-tabulating binary
outcomes across ensemble categorizers and multiple populations, we are able to
estimate unknown parameters through Gibbs sampling, eliminating the need for
ground-truth or labeled data. This paper showcases the potential of our
methodology to transform machine learning practices by allowing for accurate
model assessment under dynamic and uncertain data conditions.


  Recent works in image inpainting have shown that structural information plays
an important role in recovering visually pleasing results. In this paper, we
propose an end-to-end architecture composed of two parallel UNet-based streams:
a main stream (MS) and a structure stream (SS). With the assistance of SS, MS
can produce plausible results with reasonable structures and realistic details.
Specifically, MS reconstructs detailed images by inferring missing structures
and textures simultaneously, and SS restores only missing structures by
processing the hierarchical information from the encoder of MS. By interacting
with SS in the training process, MS can be implicitly encouraged to exploit
structural cues. In order to help SS focus on structures and prevent textures
in MS from being affected, a gated unit is proposed to depress
structure-irrelevant activations in the information flow between MS and SS.
Furthermore, the multi-scale structure feature maps in SS are utilized to
explicitly guide the structure-reasonable image reconstruction in the decoder
of MS through the fusion block. Extensive experiments on CelebA, Paris
StreetView and Places2 datasets demonstrate that our proposed method
outperforms state-of-the-art methods.


  With a better understanding of the loss surfaces for multilayer networks, we
can build more robust and accurate training procedures. Recently it was
discovered that independently trained SGD solutions can be connected along
one-dimensional paths of near-constant training loss. In this paper, we show
that there are mode-connecting simplicial complexes that form multi-dimensional
manifolds of low loss, connecting many independently trained models. Inspired
by this discovery, we show how to efficiently build simplicial complexes for
fast ensembling, outperforming independently trained deep ensembles in
accuracy, calibration, and robustness to dataset shift. Notably, our approach
only requires a few training epochs to discover a low-loss simplex, starting
from a pre-trained solution. Code is available at
https://github.com/g-benton/loss-surface-simplexes.


  A memory window of ferroelectric field-effect transistors (FeFETs), defined
as a separation of the HIGH-state and the LOW-state threshold voltages, is an
important measure of the FeFET memory characteristics. In this study, we
theoretically investigate the relation between the FeFET memory window and the
P-E hysteresis loop of the ferroelectric gate insulator, and derive a compact
model explicitly described by material parameters. It is found that the memory
window is linearly proportional to the ferroelectric polarization for the small
polarization regime, and converges to the limit value of 2 x coercive field x
thickness when the remanent polarization is much larger than permittivity x
coercive field. We discuss additional factors that possibly influence the
memory window in actual devices such as the existence of interlayer (no direct
impact), interface charges (invalidity of linear superposition between the
ferroelectric and charge-trapping hysteresis), and minor-loop operation
(behavior equivalent to the generation of interface charges).


  Events with a large rapidity gap and total transverse energy greater than 5
GeV have been observed in quasi-real photoproduction at HERA with the ZEUS
detector. The distribution of these events as a function of the $\gamma p$
centre of mass energy is consistent with diffractive scattering. For total
transverse energies above 12 GeV, the hadronic final states show predominantly
a two-jet structure with each jet having a transverse energy greater than 4
GeV. For the two-jet events, little energy flow is found outside the jets. This
observation is consistent with the hard scattering of a quasi-real photon with
a colourless object in the proton.


  We describe fivebrane configurations in M theory whose 4-d spacetime contains
N=1 supersymmetric Sp or SO gauge fields and fundamentals of these groups. We
show how field-theory dualities for Sp and SO groups can be derived using these
fivebrane configurations in M theory.


  We analyze the CP asymmetries of $B\to \phi K$ and $B\to \eta^{(\prime)} K$
modes in the QCD improved factorization framework. For our calculation we use
the phenomenological parameters predetermined from the global fit for the
available $B\to PP$ and $VP$ modes (without the quark-level subprocess $b\to
s\bar s s$). We show that the large negative $\sin (2\phi_1)_{\phi K_s}$ and
the large branching ratio for $B^{\pm}\to \eta' K^{\pm}$ can be simultaneously
explained in the context of supersymmetry (SUSY). The R-parity conserving SUGRA
models are used and their parameter space is constrained with the observed dark
matter relic density along with other experimental constraints. The R-parity
violating SUSY models are also used to show that they can provide solutions. We
calculate the CP asymmetries for different $B^{\pm (0)} \to \phi K^{\pm (0)}$
and $B^{\pm (0)} \to \eta^{(')} K^{\pm (0)}$ modes and show that the SUSY model
predictions are consistent with the available experimental data.


  We define the oscillator and Coulomb systems on four-dimensional spaces with
U(2)-invariant Kahler metric and perform their Hamiltonian reduction to the
three-dimensional oscillator and Coulomb systems specified by the presence of
Dirac monopoles. We find the Kahler spaces with conic singularity, where the
oscillator and Coulomb systems on three-dimensional sphere and two-sheet
hyperboloid are originated. Then we construct the superintegrable oscillator
system on three-dimensional sphere and hyperboloid, coupled to monopole, and
find their four-dimensional origins. In the latter case the metric of
configuration space is non-Kahler one. Finally, we extend these results to the
family of Kahler spaces with conic singularities.


  We show that ripples on the surface of deep water which are driven
parametrically by monochromatic vertical vibration represent ensembles of
oscillating solitons, or quasi-particles, rather than waves. Horizontal
mobility of oscillons determines the broadening of spectral lines and
transitions from chaos to regular patterns. It is found that microscopic
additions of proteins to water dramatically affect the oscillon mobility and
drive transitions from chaos to order. The shape of the oscillons in physical
space determines the shape of the frequency spectra of the surface ripple.


  We construct a functor from the category of $(\mathbb{Z},X)$-modules of
Ranicki (cf. \cite{Ra92}) to the category of homotopy cosheaves of chain
complexes of Ranicki-Weiss (cf. \cite{RaWei10}) inducing an equivalence on
$L$-theory. The $L$-theory of $(\mathbb{Z},X)$-modules is central in the
algebraic formulation of the surgery exact sequence and in the construction of
the total surgery obstruction by Ranicki, as described in \cite{Ra79}. The
symmetric $L$-theory of homotopy cosheaf complexes is used by Ranicki-Weiss in
\cite{RaWei10}, to reprove the topological invariance of rational Pontryagin
classes. The work presented here may be considered as an addendum to the latter
article and suggests some translation of ideas of Ranicki into the language of
homotopy chain complexes of cosheaves.


  It is emphasized that compactified little string theories have compact moduli
spaces of vacua, which globally probe compact string geometry. Compactifying
various little string theories on T^3 leads to 3d theories with exact, quantum
Coulomb branch given by: an arbitrary T^4 of volume M_s^2, an arbitrary K3 of
volume M_s^2, and moduli spaces of G=SU(N), SO(2N), or E_{6,7,8} instantons on
an arbitrary T^4 or K3 of fixed volume. Compactifying instead on a T^2 leads to
4d theories with a compact Coulomb branch base which, when combined with the
exact photon gauge coupling fiber, is a compact, elliptically-fibered space
related to the above spaces.


  We report on the microscopic magnetic model of a spin-1/2 magnet
BaV$_3$O$_8$. In contrast to earlier phenomenological analysis, our
density-functional band-structure calculations combined with quantum
Monte-Carlo simulations establish a relatively simple and non-frustrated model
of weakly coupled spin chains with the intrachain coupling of $J\sim$ 38 K and
the Neel temperature of $T_N\sim$ 6 K, both in excellent agreement with the
experiment. The intrachain coupling between the spin-1/2 V$^{+4}$ ions takes
place via two contiguous V$^{+5}$O$_4$ tetrahedra forming an extended
superexchange pathway with the V$^{+4}$--V$^{+4}$ distance of 7.44 A.
Surprisingly, this pathway is preferred over shorter V$^{+4}$--V$^{+4}$
connections, owing to peculiarities in the interacting orbitals of the magnetic
V$^{+4}$ ions and V$^{+5}$ ions that are non-magnetic, but feature low-lying
$3d$ states contributing to the superexchange process. We also note that the
crystal structure of BaV$_3$O$_8$ supports the long-sought uniform arrangement
of Dzyaloshinsky-Moriya (DM) couplings on a spin-1/2 chain. While our
calculations yield only a weak DM anisotropy in BaV$_3$O$_8$, the crystal
structure of this compound provides a suitable framework for the search of spin
chains with the uniform DM anisotropy in other compounds of the vanadate
family.


  Entangled photon pairs are essential for quantum communication technology.
They can be generated on-demand by semiconductor quantum dots, but several
mechanisms are known to reduce the degree of entanglement. While some obstacles
like the finite fine-structure splitting can be overcome by now, the excitation
scheme itself can impair the entanglement fidelity. Here, we demonstrate that
the swing-up of quantum emitter population (SUPER) scheme applied to a quantum
dot in a cavity yields almost perfectly entangled photons. The entanglement
degree remains robust against phonon influences even at elevated temperatures,
due to decoupling of the excitation and emission process. With this
achievement, quantum dots are ready to be used as entangled photon pair sources
in applications requiring high degrees of entanglement up to temperatures of
about $80\,$K.


  We review three solutions for low-cost data center interconnects with a
target reach of up to 80 km. Directly detected DMT, PAM-4 and multi-band CAP
are promising modulation schemes, enabling 400 Gbit/s by combining eight
channels of 56 Gbit/s.


  We revisit the low-energy $K^+N$ elastic scatterings in the context of the
in-medium quark condensate with strange quarks. The chiral ward identity
connects the in-medium quark condensate to the soft limit value of the
pseudoscalar correlation function evaluated in nuclear matter. The in-medium
correlation function of the psuedoscalar fields with strangeness describes
in-medium kaon propagation and is obtained by kaon-nucleon scattering
amplitudes in the low density approximation. We construct the kaon-nucleon
scattering amplitudes in chiral perturbation theory up to the next-to-leading
order and add some terms of the next-to-next-to-leading order with the strange
quark mass to improve expansion of the strange quark sector. We also consider
the effect of a possible broad resonance state around $P_\mathrm{lab} = 600$
MeV/c for $I=0$ reported in the previous study. The low energy constants are
determined by existent $K^+N$ scattering data. We obtain good reproduction of
the $K^+p$ scattering amplitude by chiral perturbation theory, while the
description of the $KN$ amplitude with $I=0$ is not so satisfactory due to the
lack of low energy data. Performing analytic continuation of the scattering
amplitudes obtained by chiral perturbation theory to the soft limit, we
estimate the in-medium strange quark condensate.


  We present subarcsecond resolution polarimetric observations of the 878 mum
thermal dust continuum emission obtained with the Submillimeter Array (SMA)
towards the IRAS 16293-2422 protostellar binary system. We report the detection
of linearly polarized dust emission arising from the circumstellar disk
associated with the IRAS 16293-2422 B protostar. The fractional polarization of
~1.4$% is only slightly lower than that expected from theoretical calculations
in such disks. The magnetic field structure on the plane of the sky derived
from the dust polarization suggests a complex magnetic field geometry in the
disk, possibly associated with a rotating disk that is wrapping the field lines
as expected from the simulations. The polarization around IRAS 16293-2422 A at
subarcsecond angular resolution is only marginally detected.


  We study the branching ratios, the direct CP asymmetries in $B\to
K^{(*)}\bar{K}^{(*)}$ decays and the polarization fractions of $B\to
K^{*}\bar{K}^{*}$ decays by employing the QCD factorization in the minimal
supersymmetric standard model with R-parity violation. We derive the new upper
bounds on the relevant R-parity violating couplings from the latest
experimental data of $B\to K^{(*)}\bar{K}^{(*)}$, and some of these constraints
are stronger than the existing bounds. Using the constrained parameter spaces,
we predict the R-parity violating effects on the other quantities in $B\to
K^{(*)}\bar{K}^{(*)}$ decays which have not been measured yet. We find that the
R-parity violating effects on the branching ratios and the direct $CP$
asymmetries could be large, nevertheless their effects on the longitudinal
polarizations of $B\to K^{*}\bar{K}^{*}$ decays are small. Near future
experiments can test these predictions and shrink the parameter spaces.


  Let $X^4$ and $Y^4$ be smooth manifolds and $f: X\to Y$ a branched cover with
branching set $B$. Classically, if $B$ is smoothly embedded in $Y$, the
signature $\sigma(X)$ can be computed from data about $Y$, $B$ and the local
degrees of $f$. When $f$ is an irregular dihedral cover and $B\subset Y$
smoothly embedded away from a cone singularity whose link is $K$, the second
author gave a formula for the contribution $\Xi(K)$ to $\sigma(X)$ resulting
from the non-smooth point. We extend the above results to the case where $Y$ is
a {\it topological} four-manifold and $B$ is locally flat, away from the
possible singularity. Owing to the presence of non-locally-flat points on $B$,
$X$ in this setting is a stratified pseudomanifold, and we use the Intersection
Homology signature of $X$, $\sigma_{IH}(X)$. For any knot $K$ whose determinant
is not $\pm 1$, a homotopy ribbon obstruction is derived from $\Xi(K)$,
providing a new technique to potentially detect slice knots that are not
ribbon.


  The intimate link between complex geometry and the problem of the pre-metric
formulation of electromagnetism is explored. In particular, the relationship
between 3+1 decompositions of R4 and the decompositions of the vector space of
bivectors over R4 into real and imaginary subspaces relative to a choice of
complex structure is emphasized. The role of the various scalar products on the
space of bivectors that are defined in terms of a volume element on R4 and a
complex structure on the space of bivectors that makes it C-linear isomorphic
to C3 is discussed in the context of formulation of a theory of
electromagnetism in which the Lorentzian metric on spacetime follows as a
consequence of the existence of electromagnetic waves, not a prior assumption.


  One-shot face recognition measures the ability to identify persons with only
seeing them at one glance, and is a hallmark of human visual intelligence. It
is challenging for conventional machine learning approaches to mimic this way,
since limited data are hard to effectively represent the data variance. The
goal of one-shot face recognition is to learn a large-scale face recognizer,
which is capable to fight off the data imbalance challenge. In this paper, we
propose a novel generative adversarial one-shot face recognizer, attempting to
synthesize meaningful data for one-shot classes by adapting the data variances
from other normal classes. Specifically, we target at building a more effective
general face classifier for both normal persons and one-shot persons.
Technically, we design a new loss function by formulating knowledge transfer
generator and a general classifier into a unified framework. Such a two-player
minimax optimization can guide the generation of more effective data, which
effectively promote the underrepresented classes in the learned model and lead
to a remarkable improvement in face recognition performance. We evaluate our
proposed model on the MS-Celeb-1M one-shot learning benchmark task, where we
could recognize 94.98% of the test images at the precision of 99% for the
one-shot classes, keeping an overall Top1 accuracy at $99.80\%$ for the normal
classes. To the best of our knowledge, this is the best performance among all
the published methods using this benchmark task with the same setup, including
all the participants in the recent MS-Celeb-1M challenge at ICCV
2017\footnote{http://www.msceleb.org/challenge2/2017}.


  We describe an algorithm for computing the convex hull of a finite collection
of points in the affine building of SL_d(K), for K a field with discrete
valuation. These convex hulls describe the relations among a finite collection
of invertible matrices over K. As a consequence, we bound the dimension of the
tropical projective space needed to realize the convex hull as a tropical
polytope.


  Sparsely-activated Mixture-of-experts (MoE) models allow the number of
parameters to greatly increase while keeping the amount of computation for a
given token or a given sample unchanged. However, a poor expert routing
strategy (e.g. one resulting in load imbalance) can cause certain experts to be
under-trained, leading to an expert being under or over-specialized. Prior work
allocates a fixed number of experts to each token using a top-k function
regardless of the relative importance of different tokens. To address this, we
propose a heterogeneous mixture-of-experts employing an expert choice method.
Instead of letting tokens select the top-k experts, we have experts selecting
the top-k tokens. As a result, each token can be routed to a variable number of
experts and each expert can have a fixed bucket size. We systematically study
pre-training speedups using the same computational resources of the Switch
Transformer top-1 and GShard top-2 gating of prior work and find that our
method improves training convergence time by more than 2x. For the same
computational cost, our method demonstrates higher performance in fine-tuning
11 selected tasks in the GLUE and SuperGLUE benchmarks. For a smaller
activation cost, our method outperforms the T5 dense model in 7 out of the 11
tasks.


  Recent data from experiment E97-006 at TJNAF using the 12C(e,e'p) reaction at
very large missing energies and momenta are compared to a calculation of
two-step rescattering.
  A comparison between parallel and perpendicular kinematics suggests that the
effects of final state interactions can be strongly reduced in the former case.


  Joint communication and sensing is expected to be one of the features
introduced by the sixth-generation (6G) wireless systems. This will enable a
huge variety of new applications, hence, it is important to find suitable
approaches to secure the exchanged information. Conventional security
mechanisms may not be able to meet the stringent delay, power, and complexity
requirements which opens the challenge of finding new lightweight security
solutions. A promising approach coming from the physical layer is the secret
key generation (SKG) from channel fading. While SKG has been investigated for
several decades, practical implementations of its full protocol are still
scarce. The aim of this chapter is to evaluate the SKG rates in real-life
setups under a set of different scenarios. We consider a typical radar waveform
and present a full implementation of the SKG protocol. Each step is evaluated
to demonstrate that generating keys from the physical layer can be a viable
solution for future networks. However, we show that there is not a single
solution that can be generalized for all cases, instead, parameters should be
chosen according to the context.


  We have conducted a deep radio survey with the Very Large Array at 1.4 GHz of
a region containing the Hubble Deep Field. This survey overlaps previous
observations at 8.5 GHz allowing us to investigate the radio spectral
properties of microjansky sources to flux densities greater than 40 $\mu$Jy at
1.4 GHz and greater than 8 $\mu$Jy at 8.5 GHz. A total of 371 sources have been
catalogued at 1.4 GHz as part of a complete sample within 20\arcmin ~of the
HDF. The differential source count for this region is only marginally
sub-Euclidean and is given by $n(S) = (8.3 \pm 0.4) S^{-2.4 \pm 0.1}$
sr$^{-1}$Jy$^{-1}$. Above about 100 $\mu$Jy the radio source count is
systematically lower in the HDF as compared to other fields. We conclude that
there is clustering in our radio sample on size scales of 1\arcmin - 40\arcmin
\.
  The 1.4 GHz selected sample shows that the radio spectral indices are
preferentially steep ($\bar{\alpha}_{1.4} = 0.85 $) and the sources are
moderately extended with average angular size $\theta$ = 1.8\arcsec . Optical
identification with disk-type systems at $z \sim $ 0.5-0.8 suggests that
synchrotron emission, produced by supernovae remnants, is powering the radio
emission in the majority of sources. The 8.5 GHz sample contains primarily
moderately flat spectrum sources ($\bar{\alpha}_{8.5} = 0.35$), with less than
15% inverted. We argue that we may be observing an increased fraction of
optically thin bremsstrahlung over synchrotron radiation in these distant
star-forming galaxies.


  Previous work on learning physical systems from data has focused on
high-resolution grid-structured measurements. However, real-world knowledge of
such systems (e.g. weather data) relies on sparsely scattered measuring
stations. In this paper, we introduce a novel simulated benchmark dataset,
DynaBench, for learning dynamical systems directly from sparsely scattered data
without prior knowledge of the equations. The dataset focuses on predicting the
evolution of a dynamical system from low-resolution, unstructured measurements.
We simulate six different partial differential equations covering a variety of
physical systems commonly used in the literature and evaluate several machine
learning models, including traditional graph neural networks and point cloud
processing models, with the task of predicting the evolution of the system. The
proposed benchmark dataset is expected to advance the state of art as an
out-of-the-box easy-to-use tool for evaluating models in a setting where only
unstructured low-resolution observations are available. The benchmark is
available at https://anonymous.4open.science/r/code-2022-dynabench/.


  Detecting the objects in dense and rotated scenes is a challenging task.
Recent works on this topic are mostly based on Faster RCNN or Retinanet. As
they are highly dependent on the pre-set dense anchors and the NMS operation,
the approach is indirect and suboptimal.The end-to-end DETR-based detectors
have achieved great success in horizontal object detection and many other areas
like segmentation, tracking, action recognition and etc.However, the DETR-based
detectors perform poorly on dense rotated target tasks and perform worse than
most modern CNN-based detectors. In this paper, we find the most significant
reason for the poor performance is that the original attention can not
accurately focus on the oriented targets. Accordingly, we propose Rotated
object detection TRansformer (RotaTR) as an extension of DETR to oriented
detection. Specifically, we design Rotation Sensitive deformable (RSDeform)
attention to enhance the DETR's ability to detect oriented targets. It is used
to build the feature alignment module and rotation-sensitive decoder for our
model. We test RotaTR on four challenging-oriented benchmarks. It shows a great
advantage in detecting dense and oriented objects compared to the original
DETR. It also achieves competitive results when compared to the
state-of-the-art.


  First passage models, where corporate assets undergo correlated random walks
and a company defaults if its assets fall below a threshold provide an
attractive framework for modeling the default process. Typical one year default
correlations are small, i.e., of order a few percent, but nonetheless including
correlations is very important, for managing portfolio credit risk and pricing
some credit derivatives (e.g. first to default baskets). In first passage
models the exact dependence of the joint survival probability of more than two
firms on their asset correlations is not known. We derive an expression for the
dependence of the joint survival probability of $n$ firms on their asset
correlations using first order perturbation theory in the correlations. It
includes all terms that are linear in the correlations but neglects effects of
quadratic and higher order. For constant time independent correlations we
compare the first passage model expression for the joint survival probability
with what a multivariate normal Copula function gives. As a practical
application of our results we calculate the dependence of the five year joint
survival probability for five basic industrials on their asset correlations.


  In this paper, the production of Axion-Like Particles (ALPs) at $B$-factories
via the process $e^+e^- \to \gamma a$ is revisited. To this purpose, the
relevant cross-section is computed via an effective Lagrangian with
simultaneous ALP couplings to $b$-quarks and photons. The interplay between
resonant and non-resonant contributions is shown to be relevant for experiments
operating at $\sqrt{s}=m_{\Upsilon(nS)}$, with $n=1,2,3$, while the
non-resonant one dominates at $\Upsilon(4S)$. These effects imply that the
experimental searches performed at different quarkonia resonances are sensitive
to complementary combinations of ALP couplings. To illustrate these results,
constraints from existing BaBar and Belle data on ALPs decaying into invisible
final states are derived, and the prospects for the Belle-II experiment are
discussed.


  This paper highlights an unexpected connection between expansions of real
numbers to noninteger bases (so-called {\em $\beta$-expansions}) and the
infinite derivatives of a class of self-affine functions. Precisely, we extend
Okamoto's function (itself a generalization of the well-known functions of
Perkins and Katsuura) to a two-parameter family $\{F_{N,a}: N\in\mathbb{N},
a\in(0,1)\}$. We first show that for each $x$, $F_{N,a}'(x)$ is either $0$,
$\pm\infty$, or undefined. We then extend Okamoto's theorem by proving that for
each $N$, depending on the value of $a$ relative to a pair of thresholds, the
set $\{x: F_{N,a}'(x)=0\}$ is either empty, uncountable but Lebesgue null, or
of full Lebesgue measure. We compute its Hausdorff dimension in the second
case.
  The second result is a characterization of the set
$\mathcal{D}_\infty(a):=\{x:F_{N,a}'(x)=\pm\infty\}$, which enables us to
closely relate this set to the set of points which have a unique expansion in
the (typically noninteger) base $\beta=1/a$. Recent advances in the theory of
$\beta$-expansions are then used to determine the cardinality and Hausdorff
dimension of $\mathcal{D}_\infty(a)$, which depends qualitatively on the value
of $a$ relative to a second pair of thresholds.


  We determine the rational Khovanov bigraded homology groups of all Kanenobu
knots. Also, we determine the crossing number for all Kanenobu knots $K(p,q)$
with $pq > 0$ or $|pq|\leq \max \{|p|, |q|\}$. In the case where $pq < 0$ and
$|pq| > \max \{|p|, |q|\}$, we conjecture that the crossing number is $|p| +
|q| + 8$.


  We show that a large contribution to the inertial mass of a moving
superconducting vortex comes from transversal displacements of the crystal
lattice. The corresponding part of the mass per unit length of the vortex line
is $M_{l} = ({\rm
m}_e^2c^{2}/64{\pi}{\alpha}^{2}{\mu}{\lambda}_{L}^{4})\ln({\lambda}_{L}/{\xi})$
, where ${\rm m}_{e}$ is the the bare electron mass, $c$ is the speed of light,
${\alpha}=e^{2}/{\hbar}c {\approx} 1/137$ is the fine structure constant,
${\mu}$ is the shear modulus of the solid, ${\lambda}_{L}$ is the London
penetration length and ${\xi}$ is the coherence length. In conventional
superconductors, this mass can be comparable to or even greater than the vortex
core mass computed by Suhl.


  We study the impact of predictions in online Linear Quadratic Regulator
control with both stochastic and adversarial disturbances in the dynamics. In
both settings, we characterize the optimal policy and derive tight bounds on
the minimum cost and dynamic regret. Perhaps surprisingly, our analysis shows
that the conventional greedy MPC approach is a near-optimal policy in both
stochastic and adversarial settings. Specifically, for length-$T$ problems, MPC
requires only $O(\log T)$ predictions to reach $O(1)$ dynamic regret, which
matches (up to lower-order terms) our lower bound on the required prediction
horizon for constant regret.


  By means of variational methods and systematic numerical analysis, we
demonstrate the existence of stable solitons in three-dimensional (3D) free
space, in the context of binary atomic condensates combining contact
self-attraction and spin-orbit coupling, which can be engineered by available
experimental techniques. Depending on the relative strength of the intra- and
inter-component attraction, the stable solitons feature a semi-vortex or
mixed-mode structure. In spite of the fact that the local cubic self-attraction
gives rise to the supercritical collapse in 3D, the solitons are stable against
random perturbations, motion, and collisions.


  Let there be given a contaminated list of n R^d-valued observations coming
from g different, normally distributed populations with a common covariance
matrix. We compute the ML-estimator with respect to a certain statistical model
with n-r outliers for the parameters of the g populations; it detects outliers
and simultaneously partitions their complement into g clusters. It turns out
that the estimator unites both the minimum-covariance-determinant rejection
method and the well-known pooled determinant criterion of cluster analysis. We
also propose an efficient algorithm for approximating this estimator and study
its breakdown points for mean values and pooled SSP matrix.


  We prove that the trace of the Hecke operator $T_2$ acting on the vector
space of cusp forms of level one takes no repeated values, except for 0, which
only occurs when the space is trivial.


  In tokamak-confined plasmas, particle transport can be reduced by modifying
the radial electric field. In this paper, we investigate the influence of both
a well-like and a hill-like shaped radial electric field profile on the
creation of shearless transport barriers (STBs) at the plasma edge, which are a
type of barrier that can prevent chaotic transport and are related to the
presence of extreme values in the rotation number profile. For that, we apply
an ExB drift model to describe test particle orbits in large aspect-ratio
tokamaks. We show how these barriers depend on the electrostatic fluctuation
amplitudes and on the width and depth (height) of the radial electric field
well-like (hill-like) profile. We find that, as the depth (height) increases,
the STB at the plasma edge becomes more resistant to fluctuations, enabling
access to an improved confinement regime that prevents chaotic transport. We
also present parameter spaces with the radial electric field parameters,
indicating the STB existence for several electric field configurations at the
plasma edge, for which we obtain a fractal structure at the barrier/non-barrier
frontier, typical of quasi-integrable Hamiltonian systems.


  In this thesis, we present optimization tools for different problems in
quantum information theory. First, we introduce an algorithm for quantum estate
estimation. The algorithm consists of orthogonal projections on intersecting
hyperplanes, which are determined by the probability distributions and the
measurement operators. We show its performance, in both runtime and fidelity,
considering realistic errors. Second, we present a technique for certifying
quantum non-locality. Given a set of bipartite measurement frequencies, this
technique finds a Bell inequality that maximizes the gap between the local
hidden variable and the quantum value of a Bell inequality. Lastly, to study
the quantum marginal problem, we introduce an operator and develop an
algorithm, which takes as inputs a set of quantum marginals and eigenvalues,
and outputs a density matrix, if exists, compatible with the prescribed data.


  We present GW based self-energy calculations for the state of coexisting
spin-density wave and d-wave superconductivity in a series of cuprate
superconductors. In these systems, the spin resonance spectrum exhibits the
typical `hour-glass' form, whose upward and downward dispersion branches come
from the gapped spin-wave and magnetic scattering of Cooper pairs,
respectively. We show that the crossover between these two different dispersion
features leads to an abrupt change in slope in the quasiparticle self-energy,
and hence the low-energy kink commences in the single-particle quasiparticle
spectrum. The calculated electron-bosonic coupling strength agrees well with
experimental data as a function of temperature, doping and material. The
results demonstrate that the electronic correlations dominate the quasiparticle
spectra of cuprates near the low-energy kink, suggesting a relatively smaller
role for phonons in this energy range.


  We develop Polaris, the first safety-focused LLM constellation for real-time
patient-AI healthcare conversations. Unlike prior LLM works in healthcare
focusing on tasks like question answering, our work specifically focuses on
long multi-turn voice conversations. Our one-trillion parameter constellation
system is composed of several multibillion parameter LLMs as co-operative
agents: a stateful primary agent that focuses on driving an engaging
conversation and several specialist support agents focused on healthcare tasks
performed by nurses to increase safety and reduce hallucinations. We develop a
sophisticated training protocol for iterative co-training of the agents that
optimize for diverse objectives. We train our models on proprietary data,
clinical care plans, healthcare regulatory documents, medical manuals, and
other medical reasoning documents. We align our models to speak like medical
professionals, using organic healthcare conversations and simulated ones
between patient actors and experienced nurses. This allows our system to
express unique capabilities such as rapport building, trust building, empathy
and bedside manner. Finally, we present the first comprehensive clinician
evaluation of an LLM system for healthcare. We recruited over 1100 U.S.
licensed nurses and over 130 U.S. licensed physicians to perform end-to-end
conversational evaluations of our system by posing as patients and rating the
system on several measures. We demonstrate Polaris performs on par with human
nurses on aggregate across dimensions such as medical safety, clinical
readiness, conversational quality, and bedside manner. Additionally, we conduct
a challenging task-based evaluation of the individual specialist support
agents, where we demonstrate our LLM agents significantly outperform a much
larger general-purpose LLM (GPT-4) as well as from its own medium-size class
(LLaMA-2 70B).


  The continuous confinement of quantum systems can be described by means of
the $d$-method, where the dimension $d$ is taken as a continuous parameter. In
this work we describe in detail how this method can be used to obtain the root
mean square radii for a squeezed three-body system. These observables are used
to investigate the disappearance of the Efimov states around the two-body
threshold during a progressive confinement of the system from three to two
dimensions. We illustrate how the disappearance takes place through the loss of
one of the particles, whereas the other two remain bound.


  Federated representation learning (FRL) is a popular personalized federated
learning (FL) framework where clients work together to train a common
representation while retaining their personalized heads. Existing studies,
however, largely focus on the over-parameterized regime. In this paper, we make
the initial efforts to investigate FRL in the under-parameterized regime, where
the FL model is insufficient to express the variations in all ground-truth
models. We propose a novel FRL algorithm FLUTE, and theoretically characterize
its sample complexity and convergence rate for linear models in the
under-parameterized regime. To the best of our knowledge, this is the first FRL
algorithm with provable performance guarantees in this regime. FLUTE features a
data-independent random initialization and a carefully designed objective
function that aids the distillation of subspace spanned by the global optimal
representation from the misaligned local representations. On the technical
side, we bridge low-rank matrix approximation techniques with the FL analysis,
which may be of broad interest. We also extend FLUTE beyond linear
representations. Experimental results demonstrate that FLUTE outperforms
state-of-the-art FRL solutions in both synthetic and real-world tasks.


  The bright star 55 Cancri is known to host five planets, including a
transiting super-Earth. We use the CHARA Array to directly determine the
following of 55 Cnc's stellar astrophysical parameters: $R=0.943 \pm 0.010
R_{\odot}$, $T_{\rm EFF} = 5196 \pm 24$ K. Planet 55 Cnc f ($M \sin i = 0.155
M_{Jupiter}$) spends the majority of the duration of its elliptical orbit in
the circumstellar habitable zone (0.67--1.32 AU) where, with moderate
greenhouse heating, it could harbor liquid water. Our determination of 55
Cancri's stellar radius allows for a model-independent calculation of the
physical diameter of the transiting super-Earth 55 Cnc e ($\simeq 2.1
R_{\earth}$), which, depending on the assumed literature value of planetary
mass, implies a bulk density of 0.76 $\rho_{\earth}$ or 1.07 $\rho_{\earth}$.


  Most existing pruning works are resource-intensive, requiring retraining or
fine-tuning of the pruned models for accuracy. We propose a retraining-free
pruning method based on hyperspherical learning and loss penalty terms. The
proposed loss penalty term pushes some of the model weights far from zero,
while the rest weight values are pushed near zero and can be safely pruned with
no need for retraining and a negligible accuracy drop. In addition, our
proposed method can instantly recover the accuracy of a pruned model by
replacing the pruned values with their mean value. Our method obtains
state-of-the-art results in retraining-free pruning and is evaluated on
ResNet-18/50 and MobileNetV2 with ImageNet dataset. One can easily get a 50\%
pruned ResNet18 model with a 0.47\% accuracy drop. With fine-tuning, the
experiment results show that our method can significantly boost the accuracy of
the pruned models compared with existing works. For example, the accuracy of a
70\% pruned (except the first convolutional layer) MobileNetV2 model only drops
3.5\%, much less than the 7\% $\sim$ 10\% accuracy drop with conventional
methods.


  64 years ago, I. M. James raised two fundamental questions about octonionic
Stiefel spaces. The prime objective of this paper is to figure out partial
answers to both of them.


  We record a general asymptotic formula for colon of ideals and proceed to
give some applications regarding $m$-full, weakly $m$-full, and full ideals.


  For non-equilibrium systems described by finite Markov processes, we consider
the number of times that a system traverses a cyclic sequence of states (a
cycle). The joint distribution of the number of forward and backward instances
of any given cycle is described by universal formulae which depend on the cycle
affinity, but are otherwise independent of system details. We discuss the
similarities and differences of this result to fluctuation theorems, and
generalize the result to families of cycles, relevant under coarse-graining.
Finally, we describe the application of large deviation theory to this cycle
counting problem.


  Dynamic arrest is a general phenomenon across a wide range of dynamic
systems, but the universality of dynamic arrest phenomena remains unclear. We
relate the emergence of traffic jams in a simple traffic flow model to the
dynamic slow down in kinetically constrained models for glasses. In kinetically
constrained models, the formation of glass becomes a true (singular) phase
transition in the limit $T\to 0$. Similarly, using the Nagel-Schreckenberg
model to simulate traffic flow, we show that the emergence of jammed traffic
acquires the signature of a sharp transition in the deterministic limit $\pp\to
1$, corresponding to overcautious driving. We identify a true dynamical
critical point marking the onset of coexistence between free flowing and jammed
traffic, and demonstrate its analogy to the kinetically constrained glass
models. We find diverging correlations analogous to those at a critical point
of thermodynamic phase transitions.


  This study provides evidence that personality can be reliably predicted from
activity data collected through mobile phone sensors. Employing a set of well
informed indicators calculable from accelerometer records and movement
patterns, we were able to predict users' personality up to a 0.78 F1 score on a
two class problem. Given the fast growing number of data collected from mobile
phones, our novel personality indicators open the door to exciting avenues for
future research in social sciences. Our results reveal distinct behavioral
patterns that proved to be differentially predictive of big five personality
traits. They potentially enable cost effective, questionnaire free
investigation of personality related questions at an unprecedented scale. We
show how a combination of rich behavioral data obtained with smartphone sensing
and the use of machine learning techniques can help to advance personality
research and can inform both practitioners and researchers about the different
behavioral patterns of personality. These findings have practical implications
for organizations harnessing mobile sensor data for personality assessment,
guiding the refinement of more precise and efficient prediction models in the
future.


  We investigate the neutrino-process in an energetic Type Ic supernova (SN Ic)
and resultant productions of the light elements including boron and its stable
isotopes. SN Ic is a very unique boron source because it can produce boron
through not only spallation reactions as discussed in Nakamura & Shigeyama
(2004) but also the neutrino-process. The neutrino-process is considered to
occur in core-collapse supernovae and previous studies were limited to Type II
supernovae (SNe II). Although the progenitor star of an SN Ic does not posses a
He envelope so that 7Li production via the neutrino-process is unlikely, 11B
can be produced in the C-rich layers. We demonstrate a hydrodynamic simulation
of SN Ic explosion and estimate the amounts of the light elements produced via
the neutrino-process for the first time, and also the subsequent spallation
reactions between the outermost layers of compact SN Ic progenitor and the
ambient medium. We find that the neutrino-process in the current SN Ic model
produces a significant amount of 11B, which is diluted by 10B from spallation
reactions to get closer to B isotopic ratios observed in meteorites. We also
confirm that high-temperature mu- and tau-neutrinos and their anti-neutrinos,
reasonably suggested from the compact structure of SN Ic progenitors, enhance
the light element production through the neutral-current reactions, which may
imply an important role of SNe Ic in the Galactic chemical evolution.


  The operation of quantum dots at highest possible temperatures is desirable
for many applications. Capacitance-voltage spectroscopy (C(V)-spectroscopy)
measurements are an established instrument to analyze the electronic structure
and energy levels of self-assembled quantum dots (QDs). We perform C(V) in the
dark and C(V) under the influence of non-resonant illumination, probing exciton
states up to $X^{4+}$ on InAs QDs embedded in a GaAs matrix for temperatures
ranging from 2.5 K to 120 K. While a small shift in the charging spectra
resonance is observed for the two pure spin degenerate electron s-state
charging voltages with increasing temperature, a huge shift is visible for the
electron-hole excitonic states resonance voltages. The $s_2$-peak moves to
slightly higher, the $s_1$-peak to slightly lower charging voltages. In
contrast, the excitonic states are surprisingly charged at much lower voltages
upon increasing temperature. We derive a rate-model allowing to attribute and
value different contributions to these shifts. Resonant tunnelling, state
degeneracy and hole generation rate in combination with the Fermi distribution
function turn out to be of great importance for the observed effects. The
differences in the shifting behavior is connected to different equilibria
schemes for the peaks; s-peaks arise when tunneling-in- and out-rates become
equal, while excitonic peaks occur, when electron tunneling-in- and
hole-generation rates are balanced.


  Apart from the coherence and fluency of responses, an empathetic chatbot
emphasizes more on people's feelings. By considering altruistic behaviors
between human interaction, empathetic chatbots enable people to get a better
interactive and supportive experience. This study presents a framework whereby
several empathetic chatbots are based on understanding users' implied feelings
and replying empathetically for multiple dialogue turns. We call these chatbots
CheerBots. CheerBots can be retrieval-based or generative-based and were
finetuned by deep reinforcement learning. To respond in an empathetic way, we
develop a simulating agent, a Conceptual Human Model, as aids for CheerBots in
training with considerations on changes in user's emotional states in the
future to arouse sympathy. Finally, automatic metrics and human rating results
demonstrate that CheerBots outperform other baseline chatbots and achieves
reciprocal altruism. The code and the pre-trained models will be made
available.


  The effects of retardation in the Coulomb excitation of radioactive nuclei in
intermediate energy collisions (Elab ~100 MeV/nucleon) are investigated. We
show that the excitation cross sections of low-lying states in 11Be,
{38,40,42}S and {44,46}Ar projectiles incident on gold and lead targets are
modified by as much as 20% due to these effects. The angular distributions of
decaying gamma-rays are also appreciably modified.


  Chest computed tomography (CT) becomes an effective tool to assist the
diagnosis of coronavirus disease-19 (COVID-19). Due to the outbreak of COVID-19
worldwide, using the computed-aided diagnosis technique for COVID-19
classification based on CT images could largely alleviate the burden of
clinicians. In this paper, we propose an Adaptive Feature Selection guided Deep
Forest (AFS-DF) for COVID-19 classification based on chest CT images.
Specifically, we first extract location-specific features from CT images. Then,
in order to capture the high-level representation of these features with the
relatively small-scale data, we leverage a deep forest model to learn
high-level representation of the features. Moreover, we propose a feature
selection method based on the trained deep forest model to reduce the
redundancy of features, where the feature selection could be adaptively
incorporated with the COVID-19 classification model. We evaluated our proposed
AFS-DF on COVID-19 dataset with 1495 patients of COVID-19 and 1027 patients of
community acquired pneumonia (CAP). The accuracy (ACC), sensitivity (SEN),
specificity (SPE) and AUC achieved by our method are 91.79%, 93.05%, 89.95% and
96.35%, respectively. Experimental results on the COVID-19 dataset suggest that
the proposed AFS-DF achieves superior performance in COVID-19 vs. CAP
classification, compared with 4 widely used machine learning methods.


  This paper constructs a persistence module of Floer cohomology groups
associated to a contactomorphism of the ideal boundary of a Liouville manifold.
The barcode (or, bottleneck) distance between the persistence modules is
bounded from above by Shelukhin's Hofer distance. Moreover, the barcode is
supported (i.e., has spectrum) on the lengths of translated points of the
contactomorphism. We use this structure to prove various existence results for
translated points and to construct spectral invariants for contactomorphisms
which are monotone with respect to positive paths and continuous with respect
to Shelukhin's Hofer distance. While this paper was nearing completion, the
author was made aware of similar upcoming work by Djordjevi\'c, Uljarevi\'c,
Zhang.


  In this paper, we propose an operation procedure for our previously developed
in-pipe robotic system that is used for water quality monitoring in water
distribution systems (WDS). The proposed operation procedure synchronizes a
developed wireless communication system that is suitable for harsh environments
of soil, water, and rock with a multi-phase control algorithm. The new wireless
control algorithm facilitates smart navigation and near real-time wireless data
transmission during operation for our in-pipe robot in WDS. The smart
navigation enables the robot to pass through different configurations of the
pipeline with long inspection capability with a battery in which is mounted on
the robot. To this end, we have divided the operation procedure into five steps
that assign a specific motion control phase and wireless communication task to
the robot. We describe each step and the algorithm associated with that step in
this paper. The proposed robotic system defines the configuration type in each
pipeline with the pre-programmed pipeline map that is given to the robot before
the operation and the wireless communication system. The wireless communication
system includes some relay nodes that perform bi-directional communication in
the operation procedure. The developed wireless robotic system along with
operation procedure facilitates localization and navigation for the robot
toward long-distance inspection in WDS.


  We point out a natural mechanism for quenching of star formation in
early-type galaxies. It automatically links the color of a galaxy with its
morphology and does not require gas consumption, removal or termination of gas
supply. Given that star formation takes place in gravitationally unstable gas
disks, it can be quenched when a disk becomes stable against fragmentation to
bound clumps. This can result from the growth of a stellar spheroid, for
instance by mergers. We present the concept of morphological quenching (MQ)
using standard disk instability analysis, and demonstrate its natural
occurrence in a cosmological simulation using an efficient zoom-in technique.
We show that the transition from a stellar disk to a spheroid can be sufficient
to stabilize the gas disk, quench star formation, and turn an early-type galaxy
red and dead while gas accretion continues. The turbulence necessary for disk
stability can be stirred up by sheared perturbations within the disk in the
absence of bound star-forming clumps. While gas stripping processes are limited
to dense groups and clusters, and other quenching mechanisms like AGN feedback,
virial shock heating and gravitational heating, are limited to halos more
massive than 10^12 Mo, the MQ can explain the appearance of red ellipticals
even in less massive halos and in the field. The dense gas disks observed in
some of today's red ellipticals may be the relics of this mechanism, whereas
red galaxies with quenched gas disks are expected to be more frequent at high
redshift.


  We present wide-field near-infrared J and Ks images of the Andromeda Galaxy
taken with WIRCam on the Canada-France-Hawaii Telescope (CFHT) as part of the
Andromeda Optical and Infrared Disk Survey (ANDROIDS). This data set allows
simultaneous observations of resolved stars and NIR surface brightness across
M31's entire bulge and disk (within R=22 kpc). The primary concern of this work
is the development of NIR observation and reduction methods to recover a
uniform surface brightness map across the 3x1 degree disk of M31. This
necessitates sky-target nodding across 27 WIRCam fields. Two sky-target nodding
strategies were tested, and we find that strictly minimizing sky sampling
latency does not maximize sky subtraction accuracy, which is at best 2% of the
sky level. The mean surface brightness difference between blocks in our mosaic
can be reduced from 1% to 0.1% of the sky brightness by introducing scalar sky
offsets to each image. The true surface brightness of M31 can be known to
within a statistical zeropoint of 0.15% of the sky level (0.2 mag arcsec sq.
uncertainty at R=15 kpc). Surface brightness stability across individual WIRCam
frames is limited by both WIRCam flat field evolution and residual sky
background shapes. To overcome flat field variability of order 1% over 30
minutes, we find that WIRCam data should be calibrated with real-time sky
flats. Due either to atmospheric or instrumental variations, the individual
WIRCam frames have typical residual shapes with amplitudes of 0.2% of the sky
after real-time flat fielding and median sky subtraction. We present our WIRCam
reduction pipeline and performance analysis here as a template for future
near-infrared observers needing wide-area surface brightness maps with
sky-target nodding, and give specific recommendations for improving photometry
of all CFHT/WIRCam programs. (Abridged)


  Cryptompress, a new 128-bit (initial) private-key cryptography algorithm is
proposed. It uses a block size of at least 30 bits and increments prior key
size to additional 32 bits on each unsuccessful attempt of any means, including
bruteforcing, further changing a specific portion of the cyphertext using the
reformed Feistel network. Encryption process results from a proposed
compression sequence developed using lookup table and shift operations followed
by key generation. Eventually, four matrixes named add-sub matrix, reduced
matrix, sequence matrix and term matrix are obtained which ultimately forms a
cyphertext.


The M-theory origin of brane creation processes is discussed.


  An experimental proposal is presented in which dark port post-selection
together with weak measurements are used to enlarge the radiation pressure
effect of a single photon on a mechanical oscillator placed in the middle of a
Fabry-Perot cavity and initialized in the ground state. By preparing and
post-selecting the photon (the system) in two quasi orthogonal states, the weak
value of the radiation force operator can lie outside the eigenvalue spectrum,
producing a large shift on the wave function of the mechanical oscillator (the
measuring device) in the position representation. Consequently, the effect of a
single photon on the average position of the oscillator in its final state can
be amplified as compared to the effect caused by a photon without
post-selection, i.e. only pre-selected. The strong measurement scenario is also
analyzed. In this case, a higher amplification effect is achieved and the mean
position of the oscillator reaches the level of the zero-point fluctuation, but
the back-action on the system is increased and the post-selection probabilities
are smaller.


  The Gould and Fernandez local brokerage measure defines brokering roles based
on the group membership of the nodes from the incoming and outgoing edges. This
paper extends on this brokerage measure to account for weighted edges and
introduces the Weighted-Normalized Gould-Fernandez measure (WNGF). The value
added of this new measure is demonstrated empirically with both a macro level
trade network and a micro level organization network. The measure is first
applied to the EUREGIO inter-regional trade dataset and then to an
organizational network in a research and development group. The results gained
from the WNGF measure are compared to those from two dichotomized networks: a
threshold and a multiscale backbone network. The results show that the WNGF
generates valid results, consistent with those of the dichotomized network. In
addition, it provides the following advantages: (i) it ensures information
retention, (ii) since no alterations and decisions have to be made on how to
dichotomize the network, the WNGF frees the user from the burden of making
assumptions, (iii) it provides a nuanced understanding of each node's brokerage
role. These advantages are of special importance when the role of less
connected nodes is considered. The two empirical networks used here are for
illustrative purposes. Possible applications of WNGF span beyond regional and
organizational studies, and into all those contexts where retaining weights is
important, for example by accounting for persisting or repeating edges compared
to one-time interactions. WNGF can also be used to further analyze networks
that measure how often people meet, talk, text, like, or retweet. WNGF makes a
relevant methodological contribution as it offers a way to analyze brokerage in
weighted, directed, and even complete graphs without information loss that can
be used across disciplines and different type of networks.


  The standard electroweak interaction is here re-assessed to accommodate two
different situations in Particle Physics. The first one is a $Z'$-model at the
TeV-scale physics. The second one tackles the recent discussion of a possible
fifth force mediated by a $17$-MeV X-boson associated with an electron-positron
emission in the transition of an excited 8-Beryllium to its ground state. The
anomaly-free model that provides these two scenarios is based on an $SU_{L}(2)
\times U_{R}(1)_{J} \times U(1)_{K}$-symmetry. It yields a new massive neutral
boson, an exotic massive neutral fermion, right-neutrinos and an additional
neutral Higgs particle, which stems from a supplementary Higgs field,
introduced along with the usual Higgs doublet responsible for the electroweak
breaking and the masses of $W^{\pm}$ and $Z^{0}$. Yukawa interactions of the
two scalars generate the masses of the Standard Model leptons, neutrinos and a
new exotic fermion of the model. The vacuum expectation values of the Higgses
fix up two independent energy scales. One of them is the well-confirmed
electroweak scale, $246 \, \mbox{GeV}$, whereas the other one is set up by
adopting an experimental estimate for the $Z'$-mass.


  We report results of a deep wide-field narrowband survey for redshift z~5.7
Ly alpha emitters carried out with SuprimeCam on Subaru 8.3-m telescope. Deep
narrowband imaging of the SSA22 field through a 120 A bandpass filter centered
at 8150 A was combined with deep multicolor RIz' SuprimeCam broadband imaging,
and BVRZ imaging taken with CFHT's CFH12K camera to select high-redshift galaxy
candidates. Spectroscopic observations were made using the new wide-field
multi-object DEIMOS spectrograph on Keck for 22 of the 26 candidate objects.
Eighteen objects were identified as z~5.7 Lyman alpha emitters, and a further
nineteenth candidate was identified based on an LRIS spectrum. At the 3.3 A
resolution of the DEIMOS spectra the asymmetric profile for Ly alpha emission
with its steep blue fall-off can be clearly seen. We use this to describe the
distribution of equivalent widths and the continuum color break properties for
z~5.7 Ly alpha galaxies compared with foreground objects. The large majority
(>75%) of Ly alpha lines have rest frame equivalent widths less than 240 A and
can be understood in terms of young star forming galaxies with a Salpeter
initial mass function for the stars. With narrowband selection criteria of I-N
> 0.7 and N<25.05 (AB mags) we find a surface density of Ly alpha emitters of
0.03 per square arcminute per (deltaz=0.1) to a limiting flux just under 2e-17
erg/cm2/s. The luminosity function of the Ly alpha emitters is similar to that
at lower redshifts to the lowest measurable luminosity of 1e43 ergs/s as is the
universal star formation rate based on their continuum properties. We note that
the objects are highly structured in both spatial and spectral properties on
the angular scale of the fields (~60 Mpc), and that multiple fields will have
to be averaged to accurately measure their ensemble properties.


  The understanding of the physics of lasermatter interactions in the strongly
relativistic regime is of fundamental importance. In this article, a new
mechanism of fast electron generation at the vacuum-solid boundary of intense
laser pulse interaction with overdense plasma is described. It is one that has
no analogue in classical, non-relativistic laser-plasma interactions. Here,
conclusive proof is provided that the key contribution to the fast electron
generation is given by the zero points of the vector potential. We demonstrate
that the new mechanism leads to scalings for the fast electron energy, which
explicitly depend on the plasma density, thus providing a new insight into
relativistic laser-matter interaction. Furthermore, it is shown that this new
mechanism provides the dominant contribution to the interaction by the
injection of energy into the overdense plasma delivered by attosecondduration
electron bunches. This new understanding will allow the future generation of a
single ultra-bright attosecond X-ray pulse by suitable control of the laser
pulse polarization [1]-[7]. This process will also allow single pulse
attosecond electron bunches to be generated that can be further accelerated in
laser wakefield accelerators [8]-[10]. Other applications that will benefit
from this new insight include laser driven ion accelerators [11]-[15], fast
ignition inertial confinement fusion [16]-[18] as well as fundamental studies
at the intensity frontier [19]-[20].


  We calculate the asymptotic merit factor, under all cyclic rotations of rows
and columns, of two families of binary two-dimensional arrays derived from the
quadratic character. The arrays in these families have size p x q, where p and
q are not necessarily distinct odd primes, and can be considered as
two-dimensional generalisations of a Legendre sequence. The asymptotic values
of the merit factor of the two families are generally different, although the
maximum asymptotic merit factor, taken over all cyclic rotations of rows and
columns, equals 36/13 for both families. These are the first non-trivial
theoretical results for the asymptotic merit factor of families of truly
two-dimensional binary arrays.


  The Monte Carlo calculation of R\'enyi entanglement entropies $S^{}_n$ of
interacting fermions suffers from a well-known signal-to-noise problem, even
for a large number of situations in which the infamous sign problem is absent.
A few methods have been proposed to overcome this issue, such as ensemble
switching and the use of auxiliary partition-function ratios. Here, we present
an approach that builds on the recently proposed free-fermion decomposition
method; it incorporates entanglement in the probability measure in a natural
way; it takes advantage of the hybrid Monte Carlo algorithm (an essential tool
in lattice quantum chromodynamics and other gauge theories with dynamical
fermions); and it does not suffer from noise problems. This method displays no
sign problem for the same cases as other approaches and is therefore useful for
a wide variety of systems. As a proof of principle, we calculate $S_2^{}$ for
the one-dimensional, half-filled Hubbard model and compare with results from
exact diagonalization and the free-fermion decomposition method.


  Ensemble Kalman Inversion (EKI) has been proposed as an efficient method for
solving inverse problems with expensive forward models. However, the method is
based on the assumption that we proceed through a sequence of Gaussian measures
in moving from the prior to the posterior, and that the forward model is
linear. In this work, we introduce Sequential Kalman Monte Carlo (SKMC)
samplers, where we exploit EKI and Flow Annealed Kalman Inversion (FAKI) within
a Sequential Monte Carlo (SMC) sampling scheme to perform efficient
gradient-free inference in Bayesian inverse problems. FAKI employs normalizing
flows (NF) to relax the Gaussian ansatz of the target measures in EKI. NFs are
able to learn invertible maps between a Gaussian latent space and the original
data space, allowing us to perform EKI updates in the Gaussianized NF latent
space. However, FAKI alone is not able to correct for the model linearity
assumptions in EKI. Errors in the particle distribution as we move through the
sequence of target measures can therefore compound to give incorrect posterior
moment estimates. In this work we consider the use of EKI and FAKI to
initialize the particle distribution for each target in an adaptive SMC
annealing scheme, before performing t-preconditioned Crank-Nicolson (tpCN)
updates to distribute particles according to the target. We demonstrate the
performance of these SKMC samplers on three challenging numerical benchmarks,
showing significant improvements in the rate of convergence compared to
standard SMC with importance weighted resampling at each temperature level.
Code implementing the SKMC samplers is available at
https://github.com/RichardGrumitt/KalmanMC.


  Unintentional actions are rare occurrences that are difficult to define
precisely and that are highly dependent on the temporal context of the action.
In this work, we explore such actions and seek to identify the points in videos
where the actions transition from intentional to unintentional. We propose a
multi-stage framework that exploits inherent biases such as motion speed,
motion direction, and order to recognize unintentional actions. To enhance
representations via self-supervised training for the task of unintentional
action recognition we propose temporal transformations, called Temporal
Transformations of Inherent Biases of Unintentional Actions (T2IBUA). The
multi-stage approach models the temporal information on both the level of
individual frames and full clips. These enhanced representations show strong
performance for unintentional action recognition tasks. We provide an extensive
ablation study of our framework and report results that significantly improve
over the state-of-the-art.


  Electrostatic velocity filtering is a technique for the production of
continuous guided beams of slow polar molecules from a thermal gas. We extended
this technique to produce pulses of slow molecules with a narrow velocity
distribution around a tunable velocity. The pulses are generated by
sequentially switching the voltages on adjacent segments of an electric
quadrupole guide synchronously with the molecules propagating at the desired
velocity. This technique is demonstrated for deuterated ammonia (ND$_{3}$),
delivering pulses with a velocity in the range of $20-100\,\rm{m/s}$ and a
relative velocity spread of $(16\pm 2)\,%$ at FWHM. At velocities around
$60\,\rm{m/s}$, the pulses contain up to $10^6$ molecules each. The data are
well reproduced by Monte-Carlo simulations, which provide useful insight into
the mechanisms of velocity selection.


  At the fully discrete setting, stability of the discontinuous
Petrov--Galerkin (DPG) method with optimal test functions requires local test
spaces that ensure the existence of Fortin operators. We construct such
operators for $H^1$ and $\boldsymbol{H}(\mathrm{div})$ on simplices in any
space dimension and arbitrary polynomial degree. The resulting test spaces are
smaller than previously analyzed cases. For parameter-dependent norms, we
achieve uniform boundedness by the inclusion of exponential layers. As an
example, we consider a canonical DPG setting for reaction-dominated diffusion.
Our test spaces guarantee uniform stability and quasi-optimal convergence of
the scheme. We present numerical experiments that illustrate the loss of
stability and error control by the residual for small diffusion coefficient
when using standard polynomial test spaces, whereas we observe uniform
stability and error control with our construction.


  In this short note we begin the analysis of deformed integrable Chern-Simons
theories. We construct the two loop dilatation operator for the scalar sector
of the ABJM theory with $k1 \neq -k2$ and we compute the anomalous dimension of
some operators.


  We propose that the enigmatic pseudogap phase of cuprate superconductors is
characterized by a hidden broken symmetry of d(x^2-y^2)-type. The transition to
this state is rounded by disorder, but in the limit that the disorder is made
sufficiently small, the pseudogap crossover should reveal itself to be such a
transition. The ordered state breaks time-reversal, translational, and
rotational symmetries, but it is invariant under the combination of any two. We
discuss these ideas in the context of ten specific experimental properties of
the cuprates, and make several predictions, including the existence of an
as-yet undetected metal-metal transition under the superconducting dome.


  We consider a weak adversarial network approach to numerically solve a class
of inverse problems, including electrical impedance tomography and dynamic
electrical impedance tomography problems. We leverage the weak formulation of
PDE in the given inverse problem, and parameterize the solution and the test
function as deep neural networks. The weak formulation and the boundary
conditions induce a minimax problem of a saddle function of the network
parameters. As the parameters are alternatively updated, the network gradually
approximates the solution of the inverse problem. We provide theoretical
justifications on the convergence of the proposed algorithm. Our method is
completely mesh-free without any spatial discretization, and is particularly
suitable for problems with high dimensionality and low regularity on solutions.
Numerical experiments on a variety of test inverse problems demonstrate the
promising accuracy and efficiency of our approach.


  We study the generating function for the number of involutions on $n$ letters
containing exactly $r\gs0$ occurrences of 3412. It is shown that finding this
function for a given $r$ amounts to a routine check of all involutions on
$2r+1$ letters.


  We present the Infrared spectrometer of SuperCam Instrument Suite that
enables the Mars 2020 Perseverance Rover to study remotely the Martian
mineralogy within the Jezero crater. The SuperCam IR spectrometer is designed
to acquire spectra in the 1.3-2.6 $\mu$m domain at a spectral resolution
ranging from 5 to 20~nm. The field-of-view of 1.15 mrad, is coaligned with the
boresights of the other remote-sensing techniques provided by SuperCam:
laser-induced breakdown spectroscopy, remote time-resolved Raman and
luminescence spectroscopies, and visible reflectance spectroscopy, and
micro-imaging. The IR spectra can be acquired from the robotic-arm workspace to
long-distances, in order to explore the mineralogical diversity of the Jezero
crater, guide the Perseverance Rover in its sampling task, and to document the
samples' environment. We present the design, the performance, the radiometric
calibration, and the anticipated operations at the surface of Mars.


  Let $f:A\longrightarrow B, g:A\longrightarrow C$ be ring homomorphisms and
let $\mathfrak{b}$ (resp., $\mathfrak{c}$) be an ideal of $B$ (resp., $C$)
satisfying $f^{-1}(\mathfrak{b})=g^{-1}(\mathfrak{c})$. Recently Kabbaj,
Louartiti and Tamekkante defined and studied the following subring
$$A\bowtie^{f,g}(\mathfrak{b},\mathfrak{c}) :=\{(f(a)+b, g(a)+c)\mid a\in A,
b\in\mathfrak{b}, c\in \mathfrak{c} \}$$ of $B\times C$, called the
bi-amalgamation of $A$ with $(B,C)$ along $(\mathfrak{b}, \mathfrak{c})$, with
respect to $(f,g)$. This ring construction is a natural generalization of the
amalgamated algebras, introduced and studied by D'Anna, Finocchiaro and
Fontana. The aim of this paper is to continue the investigation started by
Kabbaj, Louartiti and Tamekkante, by providing a deeper insigt on the
ideal-theoretic structure of bi-amalgamations.