  Magnetic field lines in interstellar media have a rich morphology, which
could be characterized by geometrical parameters such as curvature and torsion.
In this paper, we explore the statistical properties of magnetic field line
curvature $\kappa$ in compressible magnetized turbulence. We see that both the
mean and standard deviation of magnetic field line curvature obey power-law
relations to the magnetization. Moreover, the power-law tail of the curvature
probability distribution function is also proportional to the Alfvenic Mach
number. We also explore whether the curvature method could be used in the
field-tracing Velocity Gradient Technique. In particular, we observe that there
is a relation between the mean and standard deviation of the curvature probed
by velocity gradients to $M_A$. Finally we discuss how curvature is contributed
by different MHD modes in interstellar turbulence, and suggests that the
eigenvectors of MHD modes could be possibly represented by the natural
Fernet-Serrat frame of the magnetic field lines. We discuss possible
theoretical and observational applications of the curvature technique,
including the extended understanding on a special length scale that
characterize the importance of magnetic field curvature in driving MHD
turbulence, and how it could be potentially used to study self-gravitating
system.


  The modelling of neutrino nucleus interactions is one of the limiting
systematic errors in long base line neutrino oscillation experiments. The
accurate modelling of the neutrino interactions requires more experimental
observables to determine its accuracy. Adler Angles are observables carrying
information about the polarization of the ?{\Delta} resonance and the
interference with the non-resonant single pion production. These observables
were measured with limited statistics in bubble chamber experiments. We discuss
the possibility of measuring the angles in neutrino interactions with nucleus.


  We present spatially resolved kinematics of the interstellar NaI D 5890,5896
doublet absorption and 12CO(1-0) emission across the inner ~2x1 kpc of the disk
of M82. These data were obtained with the DensePak IFU on the WIYN telescope
and the Caltech Owens Valley Radio Observatory (OVRO) millimetre array. By
measuring the NaI and CO (and Halpha kinematics from a previous study) at the
same spatial resolution, and employing the same line fitting method, we have
been able to make meaningful comparisons between the ionized, neutral and
molecular gas phases. We detect a component of the NaI line throughout the
inner disk with velocities that are forbidden by the known galactic rotation.
We interpret this as originating in counter-rotating or perhaps inflowing
material. In the southern plume, we find clear evidence of entrained CO gas
with kinematics consistent with that of Halpha. On the northern side, the CO
kinematics appear to trace more static clouds in the inner halo that could be
pre-existing or tidal in origin. We find no evidence that NaI absorption is
kinematically associated with the outflow. We conclude that a combination of
lack of velocity resolution and confusion of due to the high inclination of the
system is acting to prevent detection. Thus, in the search for neutral outflows
from galaxies, the signature high velocity components may easily be missed in
observations at low spectral resolution and/or sensitivity, and particularly so
in highly inclined systems.


  One of the big challenges of the industry today is how to produce quality
products, one of which is in the knit fabric industry. The improvement of the
evaluation and quality control processes of non woven production has been
widely developed to support the improvement of the quality of production. The
use of information and computational technology is now widely applied to the
quality control process of textile material production, one of which is the use
of image processing technology in the evaluation process of knit fabric. This
chapter will explain various methods of applying image processing technology in
the field of evaluation and quality control of textile production.


  We present a systematic construction of bulk solutions that are dual to CFT
excited states. The bulk solution is constructed perturbatively in bulk fields.
The linearised solution is universal and depends only on the conformal
dimension of the primary operator that is associated with the state via the
operator-state correspondence, while higher order terms depend on detailed
properties of the operator, such as its OPE with itself and generally involve
many bulk fields. We illustrate the discussion with the holographic
construction of the universal part of the solution for states of two
dimensional CFTs, either on $R \times S^1$ or on $R^{1,1}$. We compute the
1-point function both in the CFT and in the bulk, finding exact agreement. We
comment on the relation with other reconstruction approaches.


  We examine how various types of noise in the parallel training data impact
the quality of neural machine translation systems. We create five types of
artificial noise and analyze how they degrade performance in neural and
statistical machine translation. We find that neural models are generally more
harmed by noise than statistical models. For one especially egregious type of
noise they learn to just copy the input sentence.


  Higher-order nonclassical properties of r photon added and t photon
subtracted qudit states (referred to as rPAQS and tPSQS, respectively) are
investigated here to answer: How addition and subtraction of photon can be used
engineer higher-order nonclassical properties of qudit states? To obtain the
answer higher-order moment of relevant bosonic field operators are first
obtained for rPAQS and tPSQS, and subsequently the same is used to study the
higher-order nonclassical properties of the corresponding states. A few
witnesses of higher-order nonclassicality (e.g. Higher-Order Antibunching,
Higher-Order Squeezing of Hillery type, Higher-Order sub-Poissonian Photon
statistics) are first used to establish that rPAQS and tPSQS are highly
nonclassical. These witnesses are found to indicate that the amount of
nonclassicality enhances with the number of photon added (r). To quantitatively
establish this observation and to make a comparison between rPAQS and tPSQS,
volumes of the negative part of Wigner function (nonclassical volume) of rPAQS
and tPSQS are computed as a quantitative measure of nonclassicality. Finally,
for the sake of verifiablity of the obtained results, optical tomograms are
also reported which can be obtained experimentally and used to produce Wigner
function (which is not directly measurable in general) by the Radon transform.
Throughout the study, a particular type of qudit state named as a new
generalized binomial state is used as an example.


  Relativistic positron beams are required for fundamental research in
nonlinear strong field QED, plasma physics, and laboratory astrophysics.
Positrons are difficult to create and manipulate due to their short lifetime,
and their energy gain is limited by the accelerator size in conventional
facilities. Alternative compact accelerator concepts in plasmas are becoming
more and more mature for electrons, but positron generation and acceleration
remain an outstanding challenge. Here we propose a new setup where we can
generate, inject and accelerate them in a single stage during the propagation
of an intense laser in a plasma channel. The positrons are created from a
laser-electron collision at 90 degrees, where the injection and guiding are
made possible by an 800 nC electron beam loading which reverses the sign of the
background electrostatic field. We obtain a 20 fC positron beam, with GeV-level
central energy within 0.5 mm of plasma.


  We show that the generalized Bell-type inequality, explicitly involving
rotational symmetry of physical laws, is very efficient in distinguishing
between true N-particle quantum correlations and correlations involving less
particles. This applies to various types of generalized partial separabilities.
We also give a rigorous proof that the new Bell inequalities are maximally
violated by the GHZ states, and find a very handy description of the N-qubit
correlation function.


  Most of the JavaScript code deployed in the wild has been minified, a process
in which identifier names are replaced with short, arbitrary and meaningless
names. Minified code occupies less space, but also makes the code extremely
difficult to manually inspect and understand. This paper presents Context2Name,
a deep learningbased technique that partially reverses the effect of
minification by predicting natural identifier names for minified names. The
core idea is to predict from the usage context of a variable a name that
captures the meaning of the variable. The approach combines a lightweight,
token-based static analysis with an auto-encoder neural network that summarizes
usage contexts and a recurrent neural network that predict natural names for a
given usage context. We evaluate Context2Name with a large corpus of real-world
JavaScript code and show that it successfully predicts 47.5% of all minified
identifiers while taking only 2.9 milliseconds on average to predict a name. A
comparison with the state-of-the-art tools JSNice and JSNaughty shows that our
approach performs comparably in terms of accuracy while improving in terms of
efficiency. Moreover, Context2Name complements the state-of-the-art by
predicting 5.3% additional identifiers that are missed by both existing tools.


  We study the mechanisms of the non properness of the action of the group of
diffeomorphisms on the space of Lorentzian metrics of a compact manifold. In
particular, we prove that nonproperness entails the presence of lightlike
geodesic foliations of codimension 1. On the 2-torus, we prove that a metric
with constant curvature along one of its lightlike foliation is actually flat.
This allows us to show that the restriction of the action to the set of
non-flat metrics is proper and that on the set of flat metrics of volume 1 the
action is ergodic. Finally, we show that, contrarily to the Riemannian case,
the space of metrics without isometries is not always open.


  The critical-state in a thin strip of YBaCuO is studied by magneto-optical
imaging. The distribution of magnetic flux density is shown to have a specific
symmetry in the remanent state after a large applied field. The symmetry was
predicted [PRL 82, 2947 (1999)] for any Jc(B), and is therefore suggested as a
simple tool to verify the applicability of the critical-state model. At large
temperatures we find deviations from this symmetry, which demonstrates
departure from the critical-state behavior. The observed deviations can be
attributed to an explicit coordinate dependence of $j_c$ since both a surface
barrier, and flux creep would break the symmetry in a different way.


  The last few years has seen a dramatic increase in the number of exoplanets
known and in the range of methods for characterising their atmospheric
properties. At the same time, new discoveries of increasingly cooler brown
dwarfs have pushed down their temperature range which now extends down to
Y-dwarfs of <300 K. Modelling of these atmospheres has required the development
of new techniques to deal with the molecular chemistry and clouds in these
objects. The atmospheres of brown dwarfs are relatively well understood, but
some problems remain, in particular the behavior of clouds at the L/T
transition. Observational data for exoplanet atmosphere characterization is
largely limited to giant exoplanets that are hot because they are near to their
star (hot Jupiters) or because they are young and still cooling. For these
planets there is good evidence for the presence of CO and H2O absorptions in
the IR. Sodium absorption is observed in a number of objects. Reflected light
measurements show that some giant exoplanets are very dark, indicating a cloud
free atmosphere. However, there is also good evidence for clouds and haze in
some other planets. It is also well established that some highly irradiated
planets have inflated radii, though the mechanism for this inflation is not yet
clear. Some other issues in the composition and structure of giant exoplanet
atmospheres such as the occurence of inverted temperature structures, the
presence or absence of CO2 and CH4, and the occurrence of high C/O ratios are
still the subject of investigation and debate.


  $k-$means Clustering requires as input the exact value of $k$, the number of
clusters. Two challenges are open: (i) Is there a data-determined definition of
$k$ which is provably correct and (ii) Is there a polynomial time algorithm to
find $k$ from data ? This paper provides the first affirmative answers to both
these questions. As common in the literature, we assume that the data admits an
unknown Ground Truth (GT) clustering with cluster centers separated. This
assumption alone is not sufficient to answer Yes to (i). We assume a novel, but
natural second constraint called no tight sub-cluster (NTSC) which stipulates
that no substantially large subset of a GT cluster can be "tighter" (in a sense
we define) than the cluster. Our yes answer to (i) and (ii) are under these two
deterministic assumptions. We also give polynomial time algorithm to identify
$k$. Our algorithm relies on NTSC to peel off one cluster at a time by
identifying points which are tightly packed. We are also able to show that our
algorithm(s) apply to data generated by mixtures of Gaussians and more
generally to mixtures of sub-Gaussian pdf's and hence are able to find the
number of components of the mixture from data. To our knowledge, previous
results for these specialized settings as well, assume generally that $k$ is
given besides the data.


  We present a new difference equation with two parameters c in [0,1] and A in
[1,4]. This equation is equivalent to the logistic mapping if c=1 and the
Morishita mapping if c=0, which are the well-known chaotic and integrable
mappings, respectively. We first consider the case A=4 and investigate the time
evolution by changing the parameter c in [0,1]. We next change both two
parameters A in [3,4] and c in [0,1] and present the corresponding 3D
bifurcation diagram.


  The big freeze is a singularity that shows up in some dark energy models. We
address here its possible avoidance in quantum cosmology, more precisely in the
framework of quantum geometrodynamics.


  We develop a general diagrammatic theory of welded graphs, and provide an
extension of Satoh's Tube map from welded graphs to ribbon surface-links. As a
topological application, we obtain a complete link-homotopy classification of
so-called \emph{knotted punctured spheres} in $4$--space, by means of the
$4$--dimensional Milnor invariants introduced by the authors in \cite{cutAMY}.
On the algebraic side, we show that the theory of welded graphs can be
reinterpreted as a theory of Wirtinger group presentations, up to a natural set
of transformations; these groups arise as the fundamental group of the exterior
of the surface-link obtained from the given welded graph by the extended Tube
map. Finally, we address the injectivity question for the Tube map, identifying
a new family of local moves on welded links, called $\Upsilon$ moves, under
which the (non extended) Tube map is invariant.


  Neural networks have demonstrated their outstanding performance in a wide
range of tasks. Specifically recurrent architectures based on long-short term
memory (LSTM) cells have manifested excellent capability to model time
dependencies in real-world data. However, standard recurrent architectures
cannot estimate their uncertainty which is essential for safety-critical
applications such as in medicine. In contrast, Bayesian recurrent neural
networks (RNNs) are able to provide uncertainty estimation with improved
accuracy. Nonetheless, Bayesian RNNs are computationally and memory demanding,
which limits their practicality despite their advantages. To address this
issue, we propose an FPGA-based hardware design to accelerate Bayesian
LSTM-based RNNs. To further improve the overall algorithmic-hardware
performance, a co-design framework is proposed to explore the most fitting
algorithmic-hardware configurations for Bayesian RNNs. We conduct extensive
experiments on healthcare applications to demonstrate the improvement of our
design and the effectiveness of our framework. Compared with GPU
implementation, our FPGA-based design can achieve up to 10 times speedup with
nearly 106 times higher energy efficiency. To the best of our knowledge, this
is the first work targeting acceleration of Bayesian RNNs on FPGAs.


  The theory of heavy ion single charge exchange reactions is reformulated. In
momentum space the reaction amplitude factorizes into a product of projectile
and target transition form factors, folded with the nucleon-nucleon isovector
interaction and a distortion coefficient which accounts for initial and final
state ion-ion elastic interactions. The multipole structure of the transition
form factors is studied in detail for Fermi-type non-spin flip and
Gamow-Teller-type spin flip transitions, also serving to establish the
connection to nuclear beta decay. The reaction kernel is evaluated for central
and rank-2 tensor interactions. Initial and final state elastic ion-ion
interaction are shown to be dominated by the imaginary part of the optical
potential allowing to evaluate the reaction coefficients in the strong
absorption limit, realized by the black disk approximation. In that limit the
distortion coefficient is evaluated in closed form, revealing the relation to
the total reaction cross section and the geometry of the transition form
factors. It is shown that at small momentum transfer distortion effects reduce
to a simple scaling factor, allowing to define reduced forward-angle cross
section which is given by nuclear matrix elements of beta decay-type. The
response function formalism is used to describe nuclear charge changing
transitions. Spectral distributions obtained by a self-consistent HFB and QRPA
approach are discussed for $\tau_\pm$ excitations of $^{18}O$ and $^{40}Ca$,
respectively, and compared to spectroscopic data. The interplay of nuclear
structure and reaction dynamics is illustrated for the single charge exchange
reaction $^{18}O+^{40}Ca \to ^{18}F+^{40}K$ at $T_{lab}=270$ MeV.


  We present results from the fastsum collaboration's programme to determine
the spectrum of the bottomonium system as a function of temperature. Three
different methods of extracting spectral information are discussed: a Maximum
Likelihood approach using a Gaussian spectral function for the ground state,
the Backus Gilbert method, and the Kernel Ridge Regression machine learning
procedure. We employ the fastsum anisotropic lattices with 2+1 dynamical quark
flavours, with temperatures ranging from 47 to 375 MeV.


  We demonstrate super-resolution optical sensing of the size of the wave
packet of a single trapped ion. Our method extends the well known ground state
depletion (GSD) technique to the coherent regime. Here, we use a hollow beam to
strongly saturate a coherently driven dipole-forbidden transition around a
sub-diffraction limited area at its center and observe state dependent
fluorescence. By spatially scanning this laser beam over a single trapped
$^{40}\mathrm{Ca}^+$ ion, we are able to measure the wave packet sizes of
cooled ions. Using a depletion beam waist of $4.2(1)\,\mu$m we reach a spatial
resolution which allows us to determine a wave packet size of $39(9)\,$nm for a
near ground state cooled ion. This value matches an independently deduced value
of $32(2)\,$nm, calculated from resolved sideband spectroscopy measurements.
Finally, we discuss the ultimate resolution limits of our adapted GSD imaging
technique in view of applications to direct quantum wave packet imaging.


  We consider similarity transformations of a perturbed linear operator $A-B$
in a complex Banach space $\mathcal{X}$, where the unperturbed operator $A$ is
a generator of a Banach $L_1(\mathbb{R})$-module and the perturbation operator
$B$ is a bounded linear operator. The result of the transformation is a simpler
operator $A-B_0$. For example, if $A$ is a differentiation operator and $B$ is
an operator of multiplication by an operator-valued function, then $B_0$ is an
operator of multiplication by a function that is a restriction of an entire
function of exponential type and could be $0$ in some cases. As a consequence,
we derive the spectral invariance of the operator $A-B$ in a large class of
spaces. The study is based on a widely applicable modification of the method of
similar operators that is also presented in the paper. This non-traditional
modification is rooted in the spectral theory of Banach
$L_1(\mathbb{R})$-modules.


  We develop the mutation theory in the exact WKB analysis using the framework
of cluster algebras. Under a continuous deformation of the potential of the
Schr\"odinger equation on a compact Riemann surface, the Stokes graph may
change the topology. We call this phenomenon the mutation of Stokes graphs.
Along the mutation of Stokes graphs, the Voros symbols, which are monodromy
data of the equation, also mutate due to the Stokes phenomenon. We show that
the Voros symbols mutate as variables of a cluster algebra with surface
realization. As an application, we obtain the identities of Stokes
automorphisms associated with periods of cluster algebras. The paper also
includes an extensive introduction of the exact WKB analysis and the surface
realization of cluster algebras for nonexperts.


  Recurrent events arise frequently in biomedical research, where the subject
may experience the same type of events more than once. The Andersen-Gill (AG)
model has become increasingly popular in the analysis of recurrent events
particularly when the event rate is not constant over time. We propose a
procedure for calculating the power and sample size for the robust Wald test
from the AG model in superiority, noninferiority, and equivalence clinical
trials. Its performance is demonstrated by numerical examples. Sample SAS code
is provided in the Supplementary Material.


  Many kinds of convolution identities have been considered about several
numbers, including Bernoulli, Euler, Genocchi, Cauchy, Stirling, and Fibonacci
numbers. The well-known basic result about Bernoulli numbers is due to Euler.
The convolution identities have been studied.
  In this paper, we give convolution identities for Tribonacci numbers without
binomial coefficients and with binomial coefficients. Convolution identities of
Fiboancci numbers or Lucas numbers can be expressed in the form of linear
combinations of Fibonacci numbers and Lucas numbers only. Fibonacci numbers and
Lucas numbers are in pairs with different values. Covolution identities of
Tribonacci numbers can be expressed in the linear combination of several
Tribonacci numbers with different values. Symmetric formulas are basic tools
for these expressions.


  Minimal cellular resolutions of the edge ideals of cointerval hypergraphs are
constructed. This class of d-uniform hypergraphs coincides with the complements
of interval graphs (for the case d=2), and strictly contains the class of
`strongly stable' hypergraphs corresponding to pure shifted simplicial
complexes. The polyhedral complexes supporting the resolutions are described as
certain spaces of directed graph homomorphisms, and are realized as
subcomplexes of mixed subdivisions of the Minkowski sums of simplices.
Resolutions of more general hypergraphs are obtained by considering
decompositions into cointerval hypergraphs.


  A search for the $K^+\to\mu^-\nu e^+e^+$ decay, forbidden within the Standard
Model by either lepton number or lepton flavour conservation depending on the
flavour of the emitted neutrino, has been performed using the dataset collected
by the NA62 experiment at CERN in 2016--2018. An upper limit of $8.1\times
10^{-11}$ is obtained for the decay branching fraction at 90% CL, improving by
a factor of 250 over the previous search.


  Problems with artificial neural networks originate from their deterministic
nature and inevitable prior learnings, resulting in inadequate adaptability
against unpredictable, abrupt environmental change. Here we show that a
stochastically excitable threshold unit can be utilized by these systems to
partially overcome the environmental change. Using an excitable threshold
system, attractors were created that represent quasi-equilibrium states into
which a system settles until disrupted by environmental change. Furthermore,
noise-driven attractor stabilization and switching were embodied by inhibitory
connections. Noise works as a power source to stabilize and switch attractors,
and endows the system with hysteresis behavior that resembles that of
stereopsis and binocular rivalry in the human visual cortex. A canonical model
of the ring network with inhibitory connections composed of class 1 neurons
also shows properties that are similar to the simple threshold system.


  A central problem in the theory of the dynamics of open quantum systems is
the derivation of a rigorous and computationally tractable master equation for
the reduced system density matrix. Most generally, the evolution of an open
quantum system is described by a completely positive linear map. We show how to
derive a completely positive Markovian master equation (the Lindblad equation)
from such a map by a coarse graining procedure. We provide a novel and explicit
recipe for calculating the coefficients of the master equation, using
perturbation theory in the weak-coupling limit. The only parameter external to
our theory is the coarse-graining time-scale. We illustrate the method by
explicitly deriving the master equation for the spin-boson model. The results
are evaluated for the exactly solvable case of pure dephasing, and an excellent
agreement is found within the timescale where the Markovian approximation is
expected to be valid. The method can be extended in principle to include
non-Markovian effects.


  Sources of entangled photon pairs are a key component in both fundamental
tests of quantum theory and practical applications such as quantum key
distribution and quantum computing. In this work, we describe and characterize
a source of polarization entangled photon pairs based on two spontaneous
parametric down-conversion (SPDC) crystals in a Sagnac interferometer. Our
source is compact and produces high-quality entangled states in a very flexible
manner. The wavelengths of the photon pairs, around 810 and 1550 nm, the phase
between orthogonal components of the entangled state, and the tangle of the
state are all independently adjustable. In addition to presenting basic
characterization data, we present experimental violations of CHSH and Leggett
inequalities, as well as an instance of the "beautiful" Bell inequality, which
has not previously been tested experimentally.


  The celebration of Allan Kaufman's 80th birthday was an occasion to reflect
on a career that has stimulated the mutual exchange of ideas (or memes in the
terminology of Richard Dawkins) between many researchers. This paper will
revisit a meme Allan encountered in his early career in magnetohydrodynamics,
the continuation of a magnetohydrodynamic mode through a singularity, and will
also mention other problems where Allan's work has had a powerful
cross-fertilizing effect in plasma physics and other areas of physics and
mathematics.


  Let $E = \Bbb C/\Lambda$ be a flat torus and $G$ be its Green function with
singularity at $0$. Consider the multiple Green function $G_n$ on $E^n$:
$$G_{n}(z_1,\cdots,z_n) := \sum_{i < j} G(z_{i} - z_{j}) - n \sum_{i = 1} ^{n}
G(z_{i}).$$ A critical point $a = (a_1, \cdots, a_n)$ of $G_n$ is called
trivial if $\{a_1, \cdots, a_n\} = \{-a_1, \cdots, -a_n\}$. For such a point
$a$, two geometric quantities $D(a)$ and $H(a)$ arising from bubbling analysis
of mean field equations are introduced. $D(a)$ is a global quantity measuring
asymptotic expansion and $H(a)$ is the Hessian of $G_n$ at $a$. By way of
geometry of Lam\'e curves developed in our previous paper (Cambridge J. Math 3,
2015), we derive precise formulas to relate these two quantities.


  We use local mirror symmetry to study a class of local Calabi-Yau
super-manifolds with bosonic sub-variety V_b having a vanishing first Chern
class. Solving the usual super- CY condition, requiring the equality of the
total U(1) gauge charges of bosons \Phi_{b} and the ghost like fields \Psi_{f}
one \sum_{b}q_{b}=\sum_{f}Q_{f}, as \sum_{b}q_{b}=0 and \sum_{f}Q_{f}=0,
several examples are studied and explicit results are given for local A_{r}
super-geometries. A comment on purely fermionic super-CY manifolds
corresponding to the special case where q_{b}=0, \forall b and \sum_{f}Q_{f}=0
is also made.\bigskip


  The recurrent nova and symbiotic binary RS Oph erupted again in August 2021
for its eighth known outburst. As part of a multi-epoch and frequency campaign,
we observed RS Oph 34 days after the outburst at 5 GHz with the European VLBI
Network (EVN). The radio image is elongated over the east-west direction for a
total extension of about 90 mas (or about 240 AU at the Gaia DR3 distance
d=2.68 [-0.15/+0.17] kpc), and shows a bright and compact central component
coincident with the Gaia astrometric position, and two lobes east and west of
it, expanding perpendicular to the orbital plane. By comparing with the
evolution of emission-line profiles on optical spectra, we found the leading
edge of the lobes to be expanding at 7550 km/s, and i=54 deg as the orbital
inclination of the binary. The 2021 radio structure is remarkably similar to
that observed following the 2006 eruption. The obscuring role of the density
enhancement on the orbital plane (DEOP) is discussed in connection to the
time-dependent visibility of the receding lobe in the background to the DEOP,
and the origin of the triple-peaked profiles is traced to the ring structure
formed by the nova ejecta impacting the DEOP.


  We consider the issue of strategic behaviour in various peer-assessment
tasks, including peer grading of exams or homeworks and peer review in hiring
or promotions. When a peer-assessment task is competitive (e.g., when students
are graded on a curve), agents may be incentivized to misreport evaluations in
order to improve their own final standing. Our focus is on designing methods
for detection of such manipulations. Specifically, we consider a setting in
which agents evaluate a subset of their peers and output rankings that are
later aggregated to form a final ordering. In this paper, we investigate a
statistical framework for this problem and design a principled test for
detecting strategic behaviour. We prove that our test has strong false alarm
guarantees and evaluate its detection ability in practical settings. For this,
we design and execute an experiment that elicits strategic behaviour from
subjects and release a dataset of patterns of strategic behaviour that may be
of independent interest. We then use the collected data to conduct a series of
real and semi-synthetic evaluations that demonstrate a strong detection power
of our test.


  The quantum dimensions and the fusion rules for the parafermion vertex
operator algebra associated to the irreducible highest weight module for the
affine Kac-Moody algebra A_1^{(1)} of level k are determined.


  The intermediate quantum states of multiple qubits, generated during the
operation of Shor's factoring algorithm are analyzed. Their entanglement is
evaluated using the Groverian measure. It is found that the entanglement is
generated during the pre-processing stage of the algorithm and remains nearly
constant during the quantum Fourier transform stage. The entanglement is found
to be correlated with the speedup achieved by the quantum algorithm compared to
classical algorithms.


  We report the first experimental observation of noise-free stochastic
resonance by utilizing the intrinsic chaotic dynamics of the system. To this
end we have investigated the effect of an external periodic modulation on
intermittent signals observed by high power ferromagnetic resonance in yttrium
iron garnet spheres. Both the signal-to-noise ratio and the residence time
distributions show the characteristic features of stochastic resonance. The
phenomena can be explained by means of a one-dimensional intermittent map. We
present analytical results as well as computer simulations.


  We have investigated 52 RXTE pointed observations of GRO J1655-40 spanning
the X-ray outburst that commenced on 1996 April 25 and lasted for 16 months.
Our X-ray timing analyses reveal four types of QPOs: three with relatively
stable central frequencies at 300 Hz, 9 Hz, and 0.1 Hz, and a fourth that
varied over the range 14-28 Hz. The 300 Hz and 0.1 Hz QPOs appear only at the
highest observed luminosities (Lx > 0.15 Ledd), where the power-law component
dominates the X-ray spectrum. At lower luminosity, the disk flux exceeds the
power-law flux and only two of the QPOs are observed: the spectrally "soft" 9
Hz QPO, and the narrow, "hard" QPO that varies from 14-28 Hz as the hard flux
decreases. The 300 Hz QPO is likely to be analogous to the stationary QPO at 67
Hz seen in the microquasar GRS1915+105. We discuss models of these
high-frequency QPOs which depend on effects due to general relativity. The 9 Hz
QPO displays a spectrum consistent with a thermal origin, but this frequency
does not appear to be consistent with any of the natural time scales associated
with the disk, or with the inferred values of the mass and rapid spin of the
black hole. The mechanism for the 14-28 Hz QPOs appears to be linked to the
power-law component, as do the 1-10 Hz QPOs in GRS1915+105. Finally, we show
data for GRO J1655-40 and GRS1915+105 as each source teeters between relative
stability and a state of intense oscillations at 0.1 Hz. A comparison of the
sources' spectral parameters allows us to speculate that the black hole mass in
GRS1915+105 is very large, possibly in the range 39-70 Msun.


  We give a geometric invariant theory (GIT) construction of the log canonical
model $\bar M_g(\alpha)$ of the pairs $(\bar M_g, \alpha \delta)$ for $\alpha
\in (7/10 - \epsilon, 7/10]$ for small $\epsilon \in \mathbb Q_+$. We show that
$\bar M_g(7/10)$ is isomorphic to the GIT quotient of the Chow variety
bicanonical curves; $\bar M_g(7/10-\epsilon)$ is isomorphic to the GIT quotient
of the asymptotically-linearized Hilbert scheme of bicanonical curves. In each
case, we completely classify the (semi)stable curves and their orbit closures.
Chow semistable curves have ordinary cusps and tacnodes as singularities but do
not admit elliptic tails. Hilbert semistable curves satisfy further conditions,
e.g., they do not contain elliptic bridges. We show that there is a small
contraction $\Psi: \bar M_g(7/10+\epsilon) \to \bar M_g(7/10)$ that contracts
the locus of elliptic bridges. Moreover, by using the GIT interpretation of the
log canonical models, we construct a small contraction $\Psi^+ : \bar
M_g(7/10-\epsilon) \to \bar M_g(7/10)$ that is the Mori flip of $\Psi$.


  We introduce DeepDIVA: an infrastructure designed to enable quick and
intuitive setup of reproducible experiments with a large range of useful
analysis functionality. Reproducing scientific results can be a frustrating
experience, not only in document image analysis but in machine learning in
general. Using DeepDIVA a researcher can either reproduce a given experiment
with a very limited amount of information or share their own experiments with
others. Moreover, the framework offers a large range of functions, such as
boilerplate code, keeping track of experiments, hyper-parameter optimization,
and visualization of data and results. To demonstrate the effectiveness of this
framework, this paper presents case studies in the area of handwritten document
analysis where researchers benefit from the integrated functionality. DeepDIVA
is implemented in Python and uses the deep learning framework PyTorch. It is
completely open source, and accessible as Web Service through DIVAServices.


  A path integral approach is used to derive a closed analytical expression for
the Kondo temperature of the SU(4) symmetrical Anderson model. In contrast to
the SU(2) case, the prefactor of the Kondo temperature is found to display a
peculiar orbital energy (gate voltage) dependence, reflecting the presence of
various SU(4) mixed valence fixed points. Our analytical expressions are tested
against and confirmed by numerical renormalization group computations.


  When using a Groebner basis to solve the highly symmetric system of algebraic
equations defining the cyclic p-roots, one has the feeling that much of the
advantage of computerized symbolic algebra over hand calculation is lost
through the fact that the symmetry is immediately ``thrown out'' by the
calculations. In this paper, the problem of finding (for all relevant primes p)
all cyclic p-roots of index 3 is treated with the symmetry preserved through
the calculations. Once we had found the relevant formulas, using MAPLE and
MATHEMATICA, the calculations could even be made by hand. On the other hand,
with respect to a straightforward attack with Groebner basis, it is not even
clear how this could be organized for a general p.
  In other terminologies, our results involve listings of all bi-unimodular
sequences constant on the cosets of the group G_0 of cubic residues, or
equivalently all circulant complex Hadamard matrices related to G_0.
  The corresponding problem for bi-unimodular sequences of index 2 was solved
by the first named author in 1989 and shortly after solved independently by de
la Harpe and Jones in the case p = 1 (mod 4) and by Munemasa and Watatani in
the case p = 3 (mod 4).


  The decay width, forward-backward asymmetry and tau lepton longitudinal and
transversal polarization for the exclusive (B -> K tau^+ tau^-) decay in a two
Higgs doublet model are computed. It is shown that the forward-backward
asymmetry and longitudinal polarization of the tau lepton are very effective
tools for establishing new physics.


  We present a kind of model of quantum electrodynamics with nonlocal
interaction, all the action and the equations of motion of charged particle and
electromagnetic field are given. The main characteristics of the theory are:
the model obeys the action principle; free charged particle and free
electromagnetic field obey the Dirac equation and the Maxwell equation of free
fields, respectively; for the case of interaction, both the equations of motion
of charged particle and electromagnetic field lead to the normal current
conservation naturally; the theory is Lorentz invariant and gauge invariant,
and returns to the conventional local QED under appropriate limit conditions.
Taking advantage of the Yang-Feldman equations and the Lehmann-Symanzik-
Zimmermann formalism, we establish the corresponding quantum theory.


  Climate Change (CC) is a pressing topic of global importance, attracting
increasing attention across research fields, from social sciences to Natural
Language Processing (NLP). CC is also discussed in various settings and
communication platforms, from academic publications to social media forums.
Understanding who and what is mentioned in such data is a first critical step
to gaining new insights into CC. We present CLIMATELI (CLIMATe Entity LInking),
the first manually annotated CC dataset that links 3,087 entity spans to
Wikipedia. Using CLIMATELI (CLIMATe Entity LInking), we evaluate existing
entity linking (EL) systems on the CC topic across various genres and propose
automated filtering methods for CC entities. We find that the performance of EL
models notably lags behind humans at both token and entity levels. Testing
within the scope of retaining or excluding non-nominal and/or non-CC entities
particularly impacts the models' performances.


  Dimensionality reduction is a first step of many machine learning pipelines.
Two popular approaches are principal component analysis, which projects onto a
small number of well chosen but non-interpretable directions, and feature
selection, which selects a small number of the original features. Feature
selection can be abstracted as a numerical linear algebra problem called the
column subset selection problem (CSSP). CSSP corresponds to selecting the best
subset of columns of a matrix $X \in \mathbb{R}^{N \times d}$, where
\emph{best} is often meant in the sense of minimizing the approximation error,
i.e., the norm of the residual after projection of $X$ onto the space spanned
by the selected columns. Such an optimization over subsets of $\{1,\dots,d\}$
is usually impractical. One workaround that has been vastly explored is to
resort to polynomial-cost, random subset selection algorithms that favor small
values of this approximation error. We propose such a randomized algorithm,
based on sampling from a projection determinantal point process (DPP), a
repulsive distribution over a fixed number $k$ of indices $\{1,\dots,d\}$ that
favors diversity among the selected columns. We give bounds on the ratio of the
expected approximation error for this DPP over the optimal error of PCA. These
bounds improve over the state-of-the-art bounds of \emph{volume sampling} when
some realistic structural assumptions are satisfied for $X$. Numerical
experiments suggest that our bounds are tight, and that our algorithms have
comparable performance with the \emph{double phase} algorithm, often considered
to be the practical state-of-the-art. Column subset selection with DPPs thus
inherits the best of both worlds: good empirical performance and tight error
bounds.


  Star formation rates (SFR) larger than 1000 Msun/ yr are observed in extreme
star bursts. This leads to the formation of star clusters with masses > 10^6
Msun in which crowding of the pre-stellar cores may lead to a change of the
stellar initial mass function (IMF). Indeed, the large mass-to-light ratios of
ultra-compact dwarf galaxies and recent results on globular clusters suggest
the IMF to become top-heavy with increasing star-forming density. We explore
the implications of top-heavy IMFs in these very massive and compact systems
for the integrated galactic initial mass function (IGIMF), which is the
galaxy-wide IMF, in dependence of the star-formation rate of galaxies. The
resulting IGIMFs can have slopes, alpha_3, for stars more massive than about 1
Msun between 1.5 and the Salpeter slope of 2.3 for an embedded cluster mass
function (ECMF) slope (beta) of 2.0, but only if the ECMF has no low-mass
clusters in galaxies with major starbursts. Alternatively, beta would have to
decrease with increasing SFR >10 Msun/ yr such that galaxies with major
starbursts have a top-heavy ECMF. The resulting IGIMFs are within the range of
observationally deduced IMF variations with redshift.


  We give a new proof of the result that if f and g are transcendental entire
functions, then the composite function f(g) has infinitely many fixed points.
The method yields a number of generalization of this result. In particular, it
extends to quasiregular maps in space.


  We present supersymmetric positive definite scalar products together with
natural Krein structures of supersymmetries.


  We report on the stellar core collapse, bounce, and postbounce evolution of a
13 solar mass star in a self-consistent general relativistic spherically
symmetric simulation based on Boltzmann neutrino transport. We conclude that
approximations to exact neutrino transport and omission of general relativistic
effects were not alone responsible for the failure of numerous preceding
attempts to model supernova explosions in spherical symmetry. Compared to
simulations in Newtonian gravity, the general relativistic simulation results
in a smaller shock radius. We however argue that the higher neutrino
luminosities and rms energies in the general relativistic case could lead to a
larger supernova explosion energy.


  The gauge variance of wave functionals for a gauge theory quantized in the
momentum (curvature) representation is described. It is shown that a gauge
transformation gives rise to a cocycle, which for theories in two space-time
dimensions is related to the Kirillov-Kostant form. Various derivations are
presented, including one based on geometric (pre-) quantization. The formalism
is applied to two dimensional gravity models that are equivalently described by
"B-F" gauge theories.


  Following excitation by a strong ultra-short laser pulse, molecules develop
coordinated rotational motion, exhibiting transient alignment along the
direction of the laser electric field, followed by periodic full and fractional
revivals that depend on the molecular rotational constants. In mixtures, the
different species undergo similar rotational dynamics, all starting together
but evolving differently with each demonstrating its own periodic revival
cycles. For a bimolecular mixture of linear molecules, at predetermined times,
one species may attain a maximally aligned state while the other is
anti-aligned (i.e. molecular axes are confined in a plane perpendicular to the
laser electric field direction). By a properly timed second laser pulse, the
rotational excitation of the undesired species may be almost completely removed
leaving only the desired species to rotate and periodically realign, thus
facilitating further selective manipulations by polarized light. In this paper,
such double excitation schemes are demonstrated for mixtures of molecular
isotopes (isotopologues) and for nuclear spin isomers.


  We present a new reconstruction of the distribution of atomic hydrogen in the
inner Galaxy that is based on explicit radiation-transport modelling of line
and continuum emission and a gas-flow model in the barred Galaxy that provides
distance resolution for lines of sight toward the Galactic Center. The main
benefits of the new gas model are, a), the ability to reproduce the negative
line signals seen with the H$I$4PI survey and, b), the accounting for gas that
primarily manifests itself through absorption.
  We apply the new model of Galactic atomic hydrogen to an analysis of the
diffuse gamma-ray emission from the inner Galaxy, for which an excess at a few
GeV was reported that may be related to dark matter. We find with high
significance an improved fit to the diffuse gamma-ray emission observed with
the Fermi-LAT, if our new H$I$ model is used to estimate the cosmic-ray induced
diffuse gamma-ray emission. The fit still requires a nuclear bulge at high
significance. Once this is included there is no evidence for a dark-matter
signal, be it cuspy or cored. But an additional so-called boxy bulge is still
favoured by the data. This finding is robust under the variation of various
parameters, for example the excitation temperature of atomic hydrogen, and a
number of tests for systematic issues.


  We consider the distributed SGD problem, where a main node distributes
gradient calculations among $n$ workers. By assigning tasks to all the workers
and waiting only for the $k$ fastest ones, the main node can trade-off the
algorithm's error with its runtime by gradually increasing $k$ as the algorithm
evolves. However, this strategy, referred to as adaptive $k$-sync, neglects the
cost of unused computations and of communicating models to workers that reveal
a straggling behavior. We propose a cost-efficient scheme that assigns tasks
only to $k$ workers, and gradually increases $k$. We introduce the use of a
combinatorial multi-armed bandit model to learn which workers are the fastest
while assigning gradient calculations. Assuming workers with exponentially
distributed response times parameterized by different means, we give empirical
and theoretical guarantees on the regret of our strategy, i.e., the extra time
spent to learn the mean response times of the workers. Furthermore, we propose
and analyze a strategy applicable to a large class of response time
distributions. Compared to adaptive $k$-sync, our scheme achieves significantly
lower errors with the same computational efforts and less downlink
communication while being inferior in terms of speed.


  We study the RG flow of two dimensional (fluid) membranes embedded in
Euclidean D-dimensional space using functional RG methods based on the
effective average action. By considering a truncation ansatz for the effective
average action with both extrinsic and intrinsic curvature terms we derive a
system of beta functions for the running surface tension, bending rigidity and
Gaussian rigidity. We look for non-trivial fixed points but we find no evidence
for a crumpling transition at $T\neq0$. Finally, we propose to identify the
$D\rightarrow 0$ limit of the theory with two dimensional quantum gravity. In
this limit we derive new beta functions for both cosmological and Newton's
constants.


  It is well known that, for a wide class of spacetimes with horizons, Einstein
equations near the horizon can be written as a thermodynamic identity. It is
also known that the Einstein tensor acquires a highly symmetric form near
static, as well as stationary, horizons. We show that, for generic static
spacetimes, this highly symmetric form of the Einstein tensor leads quite
naturally and generically to the interpretation of the near-horizon field
equations as a thermodynamic identity. We further extend this result to generic
static spacetimes in Lanczos-Lovelock gravity, and show that the near-horizon
field equations again represent a thermodynamic identity in all these models.
These results confirm the conjecture that this thermodynamic perspective of
gravity extends far beyond Einstein's theory.


  Since its conception, smart app market has grown exponentially. Success in
the app market depends on many factors among which the quality of the app is a
significant contributor, such as energy use. Nevertheless, smartphones, as a
subset of mobile computing devices. inherit the limited power resource
constraint. Therefore, there is a challenge of maintaining the resource while
increasing the target app quality. This paper introduces Learning Automata (LA)
as an online learning method to learn and predict the app usage routines of the
users. Such prediction can leverage the app cache functionality of the
operating system and thus (i) decreases app launch time and (ii) preserve
battery. Our algorithm, which is an online learning approach, temporally
updates and improves the internal states of itself. In particular, it learns
the transition probabilities between app launching. Each App launching instance
updates the transition probabilities related to that App, and this will result
in improving the prediction. We benefit from a real-world lifelogging dataset
and our experimental results show considerable success with respect to the two
baseline methods that are used currently for smartphone app prediction
approaches.


  We construct cosmological spacetimes with a self-dual Weyl tensor whose
dynamics are described by conformally coupled scalars with only cubic
self-interactions. Similar to the previously discovered cases in flat and
(Anti) de Sitter backgrounds, the interactions are characterized by a bracket
that encodes a kinematic algebra. We discuss how the color-kinematics duality
and double copy are realized in these cosmological backgrounds. If we further
impose that the Ricci scalar is that of an FLRW spacetime, we find two new
self-dual metrics corresponding to radiation-dominated and coasting
(non-accelerating) FLRW backgrounds. Relaxing this requirement, we find an
infinite family of solutions given by three different conformal classes of
cosmological self-dual metrics. These solutions approximate those of FLRW as
long as we impose a simple additional constraint on the scalar theory.


  For sequences $\alpha \equiv \{\alpha_n\}_{n=0}^{\infty}$ of positive real
numbers, called weights, we study the weighted shift operators $W_{\alpha}$
having the property of moment infinite divisibility ($\mathcal{MID}$); that is,
for any $p > 0$, the Schur power $W_{\alpha}^p$ is subnormal. We first prove
that $W_{\alpha}$ is $\mathcal{MID}$ if and only if certain infinite matrices
$\log M_{\gamma}(0)$ and $\log M_{\gamma}(1)$ are conditionally positive
definite (CPD). Here $\gamma$ is the sequence of moments associated with
$\alpha$, $M_{\gamma}(0),M_{\gamma}(1)$ are the canonical Hankel matrices whose
positive semi-definiteness determines the subnormality of $W_{\alpha}$, and
$\log$ is calculated entry-wise (i.e., in the sense of Schur or Hadamard).
Next, we use conditional positive definiteness to establish a new bridge
between $k$--hyponormality and $n$--contractivity, which sheds significant new
light on how the two well known staircases from hyponormality to subnormality
interact. As a consequence, we prove that a contractive weighted shift
$W_{\alpha}$ is $\mathcal{MID}$ if and only if for all $p>0$, $M_{\gamma}^p(0)$
and $M_{\gamma}^p(1)$ are CPD.


  Conventional unsupervised domain adaptation (UDA) methods need to access both
labeled source samples and unlabeled target samples simultaneously to train the
model. While in some scenarios, the source samples are not available for the
target domain due to data privacy and safety. To overcome this challenge,
recently, source-free domain adaptation (SFDA) has attracted the attention of
researchers, where both a trained source model and unlabeled target samples are
given. Existing SFDA methods either adopt a pseudo-label based strategy or
generate more samples. However, these methods do not explicitly reduce the
distribution shift across domains, which is the key to a good adaptation.
Although there are no source samples available, fortunately, we find that some
target samples are very similar to the source domain and can be used to
approximate the source domain. This approximated domain is denoted as the
pseudo-source domain. In this paper, inspired by this observation, we propose a
novel method based on the pseudo-source domain. The proposed method firstly
generates and augments the pseudo-source domain, and then employs distribution
alignment with four novel losses based on pseudo-label based strategy. Among
them, a domain adversarial loss is introduced between the pseudo-source domain
the remaining target domain to reduce the distribution shift. The results on
three real-world datasets verify the effectiveness of the proposed method.


  A transfer function approach has recently proven effective for calibrating
deep learning (DL) algorithms in quantitative ultrasound (QUS), addressing data
shifts at both the acquisition and machine levels. Expanding on this approach,
we develop a strategy to 'steal' the functionality of a DL model from one
ultrasound machine and implement it on another, in the context of QUS. This
demonstrates the ease with which the functionality of a DL model can be
transferred between machines, highlighting the security risks associated with
deploying such models in a commercial scanner for clinical use. The proposed
method is a black-box unsupervised domain adaptation technique that integrates
the transfer function approach with an iterative schema. It does not utilize
any information related to model internals of the victim machine but it solely
relies on the availability of input-output interface. Additionally, we assume
the availability of unlabelled data from the testing machine, i.e., the
perpetrator machine. This scenario could become commonplace as companies begin
deploying their DL functionalities for clinical use. Competing companies might
acquire the victim machine and, through the input-output interface, replicate
the functionality onto their own machines. In the experiments, we used a
SonixOne and a Verasonics machine. The victim model was trained on SonixOne
data, and its functionality was then transferred to the Verasonics machine. The
proposed method successfully transferred the functionality to the Verasonics
machine, achieving a remarkable 98\% classification accuracy in a binary
decision task. This study underscores the need to establish security measures
prior to deploying DL models in clinical settings.


  Deployment of sensor network in hostile environment makes it mainly
vulnerable to battery drainage attacks because it is impossible to recharge or
replace the battery power of sensor nodes. Among different types of security
threats, low power sensor nodes are immensely affected by the attacks which
cause random drainage of the energy level of sensors, leading to death of the
nodes. The most dangerous type of attack in this category is sleep deprivation,
where target of the intruder is to maximize the power consumption of sensor
nodes, so that their lifetime is minimized. Most of the existing works on sleep
deprivation attack detection involve a lot of overhead, leading to poor
throughput. The need of the day is to design a model for detecting intrusions
accurately in an energy efficient manner. This paper proposes a hierarchical
framework based on distributed collaborative mechanism for detecting sleep
deprivation torture in wireless sensor network efficiently. Proposed model uses
anomaly detection technique in two steps to reduce the probability of false
intrusion.


  A misunderstanding of entangled states has spawned decades of concern about
quantum measurements and a plethora of quantum interpretations. The
"measurement state" or "Schrodinger's cat state" of a superposed quantum system
and its detector is nonlocally entangled, suggesting that we turn to
nonlocality experiments for insight into measurements. By studying the full
range of superposition phases, these experiments show precisely what the
measurement state does and does not superpose. These experiments reveal that
the measurement state is not, as had been supposed, a paradoxical superposition
of detector states. It is instead a nonparadoxical superposition of two
correlations between detector states and system states. In this way, the
experimental results resolve the problem of definite outcomes ("Schrodinger's
cat"), leading to a resolution of the measurement problem. However, this
argument does not yet resolve the measurement problem because it is based on
the results of experiments, while measurement is a theoretical problem: How can
standard quantum theory explain the definite outcomes seen experimentally?
Thus, we summarize the nonlocality experiments' supporting theory, which
rigorously predicts the experimental results directly from optical paths.
Several previous theoretical analyses of the measurement problem have relied on
the reduced density operators derived from the measurement state, but these
solutions have been rejected due to criticism of reduced density operators.
Because it avoids reduced density operators, the optical-path analysis is
immune to such criticism.


  We developed an efficient numerical approach to compute the different
components of the orbital Hall responses in disordered materials from the Berry
phase theory of magnetization. We propose a theoretical framework based on the
Chebyshev expansion of Green's functions and the position operator for systems
under arbitrary boundary conditions. The capability of this scheme is
illustrated by computing the orbital Hall conductivity for gapped graphene and
Haldane model in the presence of nonperturbative disorder effects. This
methodology opens the door to realistic simulations of orbital Hall responses
in arbitrary complex models of disordered materials.


  Social media data can be a very salient source of information during crises.
User-generated messages provide a window into people's minds during such times,
allowing us insights about their moods and opinions. Due to the vast amounts of
such messages, a large-scale analysis of population-wide developments becomes
possible. In this paper, we analyze Twitter messages (tweets) collected during
the first months of the COVID-19 pandemic in Europe with regard to their
sentiment. This is implemented with a neural network for sentiment analysis
using multilingual sentence embeddings. We separate the results by country of
origin, and correlate their temporal development with events in those
countries. This allows us to study the effect of the situation on people's
moods. We see, for example, that lockdown announcements correlate with a
deterioration of mood in almost all surveyed countries, which recovers within a
short time span.


  We address the problem of detecting and erasing furniture from a wide angle
photograph of a room. Inpainting large regions of an indoor scene often results
in geometric inconsistencies of background elements within the inpaint mask. To
address this problem, we utilize perceptual information (e.g. instance
segmentation, and room layout) to produce a geometrically consistent empty
version of a room. We share important details to make this system viable, such
as per-plane inpainting, automatic rectification, and texture refinement. We
provide detailed ablation along with qualitative examples, justifying our
design choices. We show an application of our system by removing real furniture
from a room and redecorating it with virtual furniture.


  The practice of applying several local updates before aggregation across
clients has been empirically shown to be a successful approach to overcoming
the communication bottleneck in Federated Learning (FL). Such methods are
usually implemented by having clients perform one or more epochs of local
training per round while randomly reshuffling their finite dataset in each
epoch. Data imbalance, where clients have different numbers of local training
samples, is ubiquitous in FL applications, resulting in different clients
performing different numbers of local updates in each round. In this work, we
propose a general recipe, FedShuffle, that better utilizes the local updates in
FL, especially in this regime encompassing random reshuffling and
heterogeneity. FedShuffle is the first local update method with theoretical
convergence guarantees that incorporates random reshuffling, data imbalance,
and client sampling - features that are essential in large-scale cross-device
FL. We present a comprehensive theoretical analysis of FedShuffle and show,
both theoretically and empirically, that it does not suffer from the objective
function mismatch that is present in FL methods that assume homogeneous updates
in heterogeneous FL setups, such as FedAvg (McMahan et al., 2017). In addition,
by combining the ingredients above, FedShuffle improves upon FedNova (Wang et
al., 2020), which was previously proposed to solve this mismatch. Similar to
Mime (Karimireddy et al., 2020), we show that FedShuffle with momentum variance
reduction (Cutkosky & Orabona, 2019) improves upon non-local methods under a
Hessian similarity assumption.


  The coordinate-free solutions of the multivector equation $ax+xb=c$ are
discussed and presented for the Clifford algebras $Cl_{p,q}$ when $p+q\le 3$.


  Recent advances in photonic integrated circuits (PICs) have enabled a new
generation of "programmable many-mode interferometers" (PMMIs) realized by
cascaded Mach Zehnder Interferometers (MZIs) capable of universal
linear-optical transformations on N input-output optical modes. PMMIs serve
critical functions in photonic quantum information processing, quantum-enhanced
sensor networks, machine learning and other applications. However, PMMI
implementations reported to date rely on thermo-optic phase shifters, which
limit applications due to slow response times and high power consumption. Here,
we introduce a large-scale PMMI platform, based on a 200 mm CMOS process, that
uses aluminum nitride (AlN) piezo-optomechanical actuators coupled to silicon
nitride (SiN) waveguides, enabling low-loss propagation with phase modulation
at greater than 100 MHz in the visible to near-infrared wavelengths. Moreover,
the vanishingly low holding-power consumption of the piezo-actuators enables
these PICs to operate at cryogenic temperatures, paving the way for a fully
integrated device architecture for a range of quantum applications.


  In this work, we investigate the prospects for detecting the Inert Doublet
Model via the trilepton channel at the LHC. We present a set of representative
benchmark scenarios in which all applicable constraints are satisfied, and show
that in some of these scenarios, it is possible to obtain a signal at the 5
sigma significance level or better with integrated luminosity of 300 fb^{-1}.


  The coming quantum computation is forcing us to reexamine the cryptosystems
people use. We are applying graph colorings of topological coding to modern
information security and future cryptography against supercomputer and quantum
computer attacks in the near future. Many of techniques introduced here are
associated with many mathematical conjecture and NP-problems. We will introduce
a group of W-constraint (k,d)-total colorings and algorithms for realizing
these colorings in some kinds of graphs, which are used to make quickly
public-keys and private-keys with anti-quantum computing, these (k,d)-total
colorings are: graceful (k,d)-total colorings, harmonious (k,d)-total
colorings, (k,d)-edge-magic total colorings, (k,d)-graceful-difference total
colorings and (k,d)-felicitous-difference total colorings. One of useful tools
we used is called Topcode-matrix with elements can be all sorts of things, for
example, sets, graphs, number-based strings. Most of parameterized graphic
colorings/labelings are defined by Topcode-matrix algebra here. From the
application point of view, many of our coloring techniques are given by
algorithms and easily converted into programs.


  Motivated by the recent report of a high Li6 ``plateau'' extending to low
metallicities in Galactic halo stars, we study the energetics of an early
production of Li6 through the interaction of energetic particles with the
interstellar medium. We then explore the potential of various candidate sources
of pre-galactic energetic particles and show that, in general, they fail to
satisfy the observational and theoretical requirements (especially if the Li6
plateau is at a considerably higher level than observed). Succesful candidates
appear to be: supernova explosions with abnormally low metal yield; the massive
black hole in the Galactic center (provided that it was formed early on and
that it was then radiating much more efficiently than today); and, perhaps, an
early accretion phase of supermassive black holes in galaxies. Assuming that
Li6 is indeed pre-galactic, we study the galactic evolution of the light
isotopes Li7, Li6, and Be in a self-consistent way. We find that the existence
of a Li6 plateau is hard to justify, unless a fine-tuned and
metallicity-dependent depletion mechanism of Li6 in stellar envelopes is
invoked. The depletion of Li6 should be different, both in magnitude and in its
metallicity dependence, than the depletion required to explain current
observations of Li (mostly Li7) in halo stars. If the recently reported Li6
``plateau'' is confirmed, our analysis suggests important implications for our
understanding of the production, evolution, and stellar depletion of the Li
isotopes.


  Recent advances in our understanding of the higher-wave quarkonia have
generated much interests in quarkonium physics. However most are devoted to
inclusive decays and productions. Experimental data of several two-body
exclusive decay channels of P-wave charmonia such as \pi \pi and p \bar p are
available and some have recently been re-measured by the BES collaboration. It
is not clear from the outset that color octet is needed for these exclusive
channels. Indeed only color singlet has been used in the past and reasonable
agreement with data was found. Contrary to these old results, we provide
theoretical arguments for the inclusion of color octet and perform explicit
calculations to back this up.


  We show that there exists a strong connection between the generic formal
neighborhood at a rational arc lying in the Nash set associated with a toric
divisorial valuation on a toric variety and the formal neighborhood at the
generic point of the same Nash set. This may be interpreted as the fact that,
analytically along such a Nash set, the arc scheme of a toric variety is a
product of a finite dimensional singularity and an infinite dimensional affine
space.


  Large language models (LLMs) are increasingly used to meet user information
needs, but their effectiveness in dealing with user queries that contain
various types of ambiguity remains unknown, ultimately risking user trust and
satisfaction. To this end, we introduce CLAMBER, a benchmark for evaluating
LLMs using a well-organized taxonomy. Building upon the taxonomy, we construct
~12K high-quality data to assess the strengths, weaknesses, and potential risks
of various off-the-shelf LLMs. Our findings indicate the limited practical
utility of current LLMs in identifying and clarifying ambiguous user queries,
even enhanced by chain-of-thought (CoT) and few-shot prompting. These
techniques may result in overconfidence in LLMs and yield only marginal
enhancements in identifying ambiguity. Furthermore, current LLMs fall short in
generating high-quality clarifying questions due to a lack of conflict
resolution and inaccurate utilization of inherent knowledge. In this paper,
CLAMBER presents a guidance and promotes further research on proactive and
trustworthy LLMs. Our dataset is available at
https://github.com/zt991211/CLAMBER


  The insulating magnetic pyrochlore Ce$_2$Zr$_2$O$_7$ has attracted much
attention as a quantum spin ice candidate with dipole-octupole character that
permits spin ice phases based not only on magnetic dipole moments but also
allows for even-more-exotic octupole-based spin ice phases. This work reports
low-temperature neutron diffraction measurements on single crystal
Ce$_2$Zr$_2$O$_7$ with $Q$-coverage both at low $Q$ where the magnetic form
factor for dipoles is near maximal and at high $Q$ covering the region where
the magnetic form factor for Ce$^{3+}$ octupoles is near maximal. This study
was motivated by recent powder neutron diffraction studies of other Ce-based
dipole-octupole pyrochlores, Ce$_2$Sn$_2$O$_7$ and Ce$_2$Hf$_2$O$_7$, which
each showed temperature-dependent diffuse diffraction at high $Q$ that was
interpreted as arising from octupolar correlations. Our measurements use an
optimized single crystal diffuse scattering instrument that allows us to screen
against strong single crystal Bragg scattering in Ce$_2$Zr$_2$O$_7$. The
temperature-difference neutron diffraction reveals a low-$Q$ peak consistent
with dipolar spin ice correlations. For larger $Q$, the temperature-difference
neutron diffraction shows an alternation between positive and negative net
intensity. These features are qualitatively consistent with the corresponding
numerical-linked-cluster (NLC) calculations using pseudospin interaction
parameters reported for Ce$_2$Zr$_2$O$_7$, Ce$_2$Sn$_2$O$_7$, or
Ce$_2$Hf$_2$O$_7$. Importantly, neither the measured data nor any of the NLC
calculations show increased scattering at high $Q$ resulting from octupolar
correlations. We conclude that at the lowest attainable temperatures for our
measurement ($T = 0.05$ K), octupolar correlations are not present in
Ce$_2$Zr$_2$O$_7$ on the level of our observation threshold of $\sim$ 0.1$\%$
of the low-$Q$ dipole scattering.


  A systematic nonperturbative scheme is implemented to calculate the ground
state energy for a wide class of strongly correlated fermion models. The scheme
includes: (a) method of automatic calculations of the cumulants of the model
Hamiltonian; (b) method of the ground state energy calculation from these
cumulants using the $t$-expansion proposed by Horn and Weinstein [Phys. Rev. D
\textbf{30}, 1256 (1984)] with new procedure of its extrapolation to
$t\rightarrow\infty$. As an example of application of the method all cumulants
up to the 8-th order for spinless fermion model are calculated exactly, and
converging sequences of approximations to the ground state energy are obtained
for one-, two- and three-dimensional versions of the model.


  Gene essentiality, the necessity of a specific gene for the survival of an
organism, is crucial to our understanding of cellular processes and identifying
drug targets. Experimental determination of gene essentiality requires large
growth screens that are time-consuming and expensive, motivating the
development of in-silico approaches. Existing methods predominantly utilise
flux balance analysis (FBA), a constraint-based optimisation algorithm;
however, they are fundamentally limited by the necessity of a predefined
cellular objective function. This requirement introduces an element of observer
bias, as the objective function often reflects the researcher's assumptions
rather than the cell's biological goals. Here, we present FluxGAT, a graph
neural network (GNN) model capable of predicting gene essentiality directly
from graphical representations of flux sampling data. Flux sampling removes the
need for objective functions, thereby eliminating observer bias. FluxGAT
leverages the unique strengths of GNNs in learning representations of complex
relationships within metabolic reaction networks. The success of our approach
in predicting experimentally determined gene essentiality, with almost double
the sensitivity of FBA, explores the possibility of predicting cellular
phenotypes in cases when objectives are less understood. Thus, we demonstrate a
method for more general gene essentiality predictions across a broader spectrum
of biological systems and environments.


  Point clouds and high-resolution 3D data have become increasingly important
in various fields, including surveying, construction, and virtual reality.
However, simply having this data is not enough; to extract useful information,
semantic labeling is crucial. In this context, we propose a method to transfer
annotations from a labeled to an unlabeled point cloud using an octree
structure. The structure also analyses changes between the point clouds. Our
experiments confirm that our method effectively transfers annotations while
addressing changes. The primary contribution of this project is the development
of the method for automatic label transfer between two different point clouds
that represent the same real-world object. The proposed method can be of great
importance for data-driven deep learning algorithms as it can also allow
circumventing stochastic transfer learning by deterministic label transfer
between datasets depicting the same objects.


  We show that states on tensor products of matrix algebras whose ranks are
relatively small are {\em almost surely} entangled, but that states of maximum
rank are not. More precisely, let $M=M_m(\mathbb C)$ and $N=M_n(\mathbb C)$ be
full matrix algebras with $m\geq n$, fix an arbitrary state $\omega$ of $N$,
and let $E(\omega)$ be the set of all states of $M\otimes N$ that extend
$\omega$. The space $E(\omega)$ contains states of rank $r$ for every
$r=1,2,...,m\cdot\rank\omega$, and it has a filtration into compact subspaces
$$ E^1(\omega)\subseteq E^2(\omega)\subseteq ...\subseteq
E^{m\cdot\rank\omega}=E(\omega), $$ where $E^r(\omega)$ is the set of all
states of $E(\omega)$ having rank $\leq r$.
  We show first that for every $r$, there is a real-analytic manifold $V^r$,
homogeneous under a transitive action of a compact group $G^r$, which
parameterizes $E^r(\omega)$. The unique $G^r$-invariant probability measure on
$V^r$ promotes to a probability measure $P^{r,\omega}$ on $E^r(\omega)$, and
$P^{r,\omega}$ assigns probability 1 to states of rank $r$. The resulting
probability space $(E^r(\omega),P^{r,\omega})$ represents ``choosing a rank $r$
extension of $\omega$ at random".
  Main result: For every $r=1,2,...,[\rank \omega/2]$, states of
$(E^r(\omega),P^{r,\omega})$ are almost surely entangled.


  Context. Gaia has been in operations since 2014. The third Gaia data release
expands from the early data release (EDR3) in 2020 by providing 34 months of
multi-epoch observations that allowed us to probe, characterise and classify
systematically celestial variable phenomena.
  Aims. We present a summary of the variability processing and analysis of the
photometric and spectroscopic time series of 1.8 billion sources done for Gaia
DR3.
  Methods. We used statistical and Machine Learning methods to characterise and
classify the variable sources. Training sets were built from a global revision
of major published variable star catalogues. For a subset of classes, specific
detailed studies were conducted to confirm their class membership and to derive
parameters that are adapted to the peculiarity of the considered class.
  Results. In total, 10.5 million objects are identified as variable in Gaia
DR3 and have associated time series in G, GBP, and GRP and, in some cases,
radial velocity time series. The DR3 variable sources subdivide into 9.5
million variable stars and 1 million Active Galactic Nuclei/Quasars. In
addition, supervised classification identified 2.5 million galaxies thanks to
spurious variability induced by the extent of these objects. The variability
analysis output in the DR3 archive amounts to 17 tables containing a total of
365 parameters. We publish 35 types and sub-types of variable objects. For 11
variable types, additional specific object parameters are published. An
overview of the estimated completeness and contamination of most variability
classes is provided.
  Conclusions. Thanks to Gaia we present the largest whole-sky variability
analysis based on coherent photometric, astrometric, and spectroscopic data.
Later Gaia data releases will more than double the span of time series and the
number of observations, thus allowing for an even richer catalogue in the
future.


  We perform a Monte-Carlo simulation of scalar leptoquark pair production at
the Tevatron (energy =1.8 TeV and luminosity =100 pb^{-1}) with ISAJET. We also
investigate the dominant sources of Standard Model background: Z*jj, ZZ
production and heavy quark top-antitop. We find that the top-antitop background
is the most important except near the Z pole where the Z*jj background is
peaked. We also evaluate the signal-to-background ratio and find a discovery
reach of 130 GeV (170 GeV) for a branching ratio of B(LQ-> eq)=0.5 (B=1).


  Extra-galactic X-ray absorption and optical extinction are often found in
gamma-ray burst (GRB) afterglows and they could be tracers of both circumburst
and host galaxy environments. By performing spectral analyses for spectral
energy distribution of 9 short GRB (SGRB) afterglows with known redshift, we
investigated a ratio of the equivalent hydrogen column density to the dust
extinction, N^{rest}_{H}/A^{rest}_{V}, in the rest frame of each SGRB. We found
that the distribution of N^{rest}_{H}/A^{rest}_{V} is systematically smaller
than the one for long GRBs, and is roughly consistent with the gas-to-dust
ratio in the Milky Way. This result means that the measured gas-to-dust ratio
of SGRBs would originate from the interstellar medium in each host galaxy. This
scenario supports the prediction that SGRBs occur in non star-forming regions
in the host galaxies.


  With the rapid advancement of large models and mobile edge computing,
transfer learning, particularly through fine-tuning, has become crucial for
adapting models to downstream tasks. Traditionally, this requires users to
share their data with model owners for fine-tuning, which is not only costly
but also raises significant privacy concerns. Furthermore, fine-tuning
large-scale models is computationally intensive and often impractical for many
users. To tackle these challenges, we introduce a system that combines
offsite-tuning with physical-layer security, which provides local data owners
with a lightweight adapter and a compressed emulator. Data owners then
fine-tune the adapter locally and securely send it back to the model owners
through a confidential channel for integration, ensuring privacy and resource
conservation. Our paper focuses on optimizing computational resource allocation
among data owners and the large model owner deployed on edge, and on the
compression ratio of adapters. We incorporate a secrecy uplink channel to
maximize the utility that we defined while minimizing system costs like energy
consumption and delay. The optimization uses the Dinkelbach algorithm,
fractional programming, successive convex approximation and alternating
optimization. Experiments demonstrate our algorithm's superiority over existing
methods.


  Diatomic nitrogen is an archetypal molecular system known for its exceptional
stability and complex behavior at high pressures and temperatures, including
rich solid polymorphism, formation of energetic states, and an
insulator-to-metal transformation coupled to a change in chemical bonding.
However, the thermobaric conditions of the fluid molecular-polymer phase
boundary and associated metallization have not been experimentally established.
Here, by applying dynamic laser heating of compressed nitrogen and using fast
optical spectroscopy to study electronic properties, we observe a
transformation from insulating (molecular) to conducting dense fluid nitrogen
at temperatures that decrease with pressure, and establish that metallization,
and presumably fluid polymerization, occurs above 125 GPa at 2500 K. Our
observations create a better understanding of the interplay between molecular
dissociation, melting, and metallization revealing features that are common in
simple molecular systems.


  Auns. The aim of our paper is to investigate the low-amplitude and
long-period variations in evolved stars with a precise radial velocity (RV)
survey. Methods. The high-resolution, the fiber-fed Bohyunsan Observatory
Echelle Spectrograph (BOES) was used from 2003 to 2013 for a radial velocity
survey of giant stars as part of the exoplanet search program at Bohyunsan
Optical Astronomy Observatory (BOAO). Results. We report the detection of three
new planetary companions orbiting the K giants beta Cnc, mu Leo, and beta UMi.
The planetary nature of the radial velocity variations is supported by analyzes
of ancillary data. The HIPPARCOS photometry shows no variations with periods
close to those in RV variations and there is no strong correlation between the
bisector velocity span (BVS) and the radial velocities for each star.
Furthermore, the stars show weak or no core reversal in Ca II H lines
indicating that they are inactive stars. The companion to beta Cnc has a
minimum mass of 7.8 M_Jup in a 605-day orbit with an eccentricity of 0.08. The
giant mu Leo is orbited by a companion of minimum mass of 2.4 M_Jup having a
period of 357 days and an eccentricity of 0.09. The giant beta UMi is a known
barium star and is suspected of harboring a white dwarf or substellar mass
companion. Its companion has a minimum mass of 6.1 M_Jup, a period of 522 days,
and an eccentricity e = 0.19.


  When a linear order has an order preserving surjection onto each of its
suborders we say that it is strongly surjective. We prove that the set of
countable strongly surjective linear orders is complete for the class of sets
which are the union of an analytic and a coanalytic set. Using hypotheses
beyond ZFC, we prove the existence of uncountable strongly surjective orders.


  Current understanding of neuronal growth is mostly qualitative, as the
staggering number of physical and chemical guidance cues involved prohibit a
fully quantitative description of axonal dynamics. We report on a general
approach that describes axonal growth in vitro, on poly-D-lysine coated glass
substrates, as diffusion in an effective external potential, representing the
collective contribution of all causal influences on the growth cone. We use
this approach to obtain effective growth rules that reveal an emergent
regulatory mechanism for axonal pathfinding on these substrates.


  Classic calculations of the magnetic moments mu_p and mu_n of the nucleons
using the traditional exponential kernel show instability with respect to
variations of the Borel mass as well as arbitrariness with respect to the
choice of the onset of perturbative QCD. The use of a polynomial kernel, the
coefficients of which are determined by the masses of the nucleon resonances
stabilizes the calculation and provides much better damping of the unknown
contribution of the nucleon continuum. The method is also applied to the
evaluation of the coupling gA of proton to the axial current and to the strong
part of the neutron-proton mass difference Delta M_np. All these quantities
depend sensitively on the value of the 4-quark condensate < 0 | qqqq | 0 > and
the value < 0 | qqqq | 0 > ~ 1.5< 0 | qq | 0 >^2 reproduces the experimental
results.


  Central to most applications involving monolayer graphene is its mechanical
response under various stress states. To date most of the work reported is of
theoretical nature and refers to tension and compression loading of model
graphene. Most of the experimental work is indeed limited to bending of single
flakes in air and the stretching of flakes up to typically ~1% using plastic
substrates. Recently we have shown that by employing a cantilever beam we can
subject single graphene into various degrees of axial compression. Here we
extend this work much further by measuring in detail both stress uptake and
compression buckling strain in single flakes of different geometries. In all
cases the mechanical response is monitored by simultaneous Raman measurements
through the shift of either the G or 2D phonons of graphene. In spite of the
infinitely small thickness of the monolayers, the results show that graphene
embedded in plastic beams exhibit remarkable compression buckling strains. For
large length (l)-to-width (w) ratios (> 0.2) the buckling strain is of the
order of -0.5% to -0.6%. However, for l/w <0.2 no failure is observed for
strains even higher than -1%. Calculations based on classical Euler analysis
show that the buckling strain enhancement provided by the polymer lateral
support is more than six orders of magnitude compared to suspended graphene in
air.


  Multi-braneworld universe is at the heart of many scenarios of physics beyond
the Standard Model and the cosmological model $\Lambda CDM$. It is thus an
important concern to constrain these scenarios which also allow for experiments
below the GeV scale. MURMUR is a new neutron-passing-through-walls experiment
designed to constrain neutron-hidden neutron transitions in the context of
braneworlds scenarios. As our visible universe could be a 3-brane embedded in a
multidimensional bulk, adjacent hidden 3-branes are often expected. Their
existence can be constrained as matter exchange between braneworlds must occur
with a swapping probability $p$. A neutron $n$ can convert into a hidden
neutron $n'$ when scattered by a nucleus with cross section $\sigma (n \to n')$
$\propto$ $\sigma_E (n \to n)\ p$, where $\sigma_E$ is the usual elastic
cross-section. Hidden neutrons could therefore be generated in the moderator
medium of a nuclear reactor, where high-flux neutrons undergo many elastic
collisions. All the theoretical and technological keys of this experiment soon
to be installed at the nuclear research reactor BR2 (SCK.CEN, Mol, Belgium) are
introduced.


  We use the approach used by Eguchi-Hanson in constructing four-dimensional
instanton metrics and construct a class of regular six-dimensional instantons
which are nothing but $S^2\times S^2$ resolved conifolds. We then also obtain
D3-brane solutions on these EH-resolved conifolds.


  We investigate the solutions of Nambu-Goto-type actions associated with
calibrations. We determine the supersymmetry preserved by these solutions using
the contact set of the calibration and examine their bulk interpretation as
intersecting branes. We show that the supersymmetry preserved by such solutions
is closely related to the spinor singlets of the subgroup $G$ of $Spin (9,1)$
or $Spin (10,1)$ that rotates the tangent spaces of the brane. We find that the
supersymmetry projections of the worldvolume solutions are precisely those of
the associated bulk configurations. We also investigate the supersymmetric
solutions of a Born-Infeld action. We show that in some cases this problem also
reduces to counting spinor singlets of a subgroup of $Spin (9,1)$ acting on the
associated spinor representations. We also find new worldvolume solutions which
preserve 1/8 of the supersymmetry of the bulk and give their bulk
interpretation.


  A few new N=2 superintegrable mappings in the (1|2) superspace are proposed
and their origin is analyzed. Using one of them, acting like the discrete
symmetry transformation of the N=2 supersymmetric modified NLS hierarchy, the
recursion operator and hamiltonian structures of the hierarchy are constructed.


  Markov categories are a recent categorical approach to the mathematical
foundations of probability and statistics. Here, this approach is advanced by
stating and proving equivalent conditions for second-order stochastic
dominance, a widely used way of comparing probability distributions by their
spread. Furthermore, we lay foundation for the theory of comparing statistical
experiments within Markov categories by stating and proving the classical
Blackwell-Sherman-Stein Theorem. Our version not only offers new insight into
the proof, but its abstract nature also makes the result more general,
automatically specializing to the standard Blackwell-Sherman-Stein Theorem in
measure-theoretic probability as well as a Bayesian version that involves
prior-dependent garbling. Along the way, we define and characterize
representable Markov categories, within which one can talk about Markov kernels
to or from spaces of distributions. We do so by exploring the relation between
Markov categories and Kleisli categories of probability monads.


  Multi-antenna technologies such as massive Multiple-Input Multiple-Output
(massive MIMO) and beamforming are key features to enhance performance, in
terms of capacity and coverage, by using a large number of antennas
intelligently. With the upcoming 5G New Radio (NR), FD-MIMO (Full Dimension
MIMO) will play a major key role. FD-MIMO consists in arranging a large number
of antennas in a 2D array, which enables to use 3D beamforming i.e.,
beamforming in both horizontal and vertical dimensions. The present paper
provides a 3D beamforming model where beam steering depends on the random
spatial distribution of users. We attempt to derive some analytical results
regarding the probability distribution of antenna beamforming radiation
pattern. Also, through system level simulations, we show how 3D beamforming can
reduce interference impact, compared to the traditional 2D beamforming, and
enhances system performance in terms of the coverage probability and users
throughput.


  In this article we show that there are branching systems (which induce
representations of the graph algebra $C^*(E)$) associated to each row-countable
graph $E$. For row-countable graphs, we characterize the condition $(L)$ via
branching systems. Moreover, we show that each permutative representation in
Hilbert spaces operators is unitarily equivalent to one induced by a branching
system, even the spaces being not separable. Furthermore, under some hypothesis
on the graph, we show that each representation of the graph C*-algebra is
permutative.


  One key challenge in the field of topological superconductivity (Tsc) has
been the rareness of material realization. This is true not only for the
first-order Tsc featuring Majorana surface modes, but also for the higher-order
Tsc, which host Majorana hinge and corner modes. Here, we propose a four-step
strategy that mathematically derives comprehensive guiding principles for the
search and design for materials of general higher-order Tsc phases.
Specifically, such recipes consist of conditions on the normal state and
pairing symmetry that can lead to a given higher-order Tsc state. We
demonstrate this strategy by obtaining recipes for achieving three-dimensional
higher-order Tsc phases protected by the inversion symmetry. Following our
recipe, we predict that the observed superconductivity in centrosymmetric
MoTe$_2$ is a candidate for higher-order Tsc with corner modes. Our proposed
strategy enables systematic materials search and design for higher-order Tsc,
which can mobilize the experimental efforts and accelerate the material
discovery for higher-order Tsc phases.


  In this short note we construct a spectral, non-tiling set of size $2p$ in
$(\mathbb{Z}/p\mathbb{Z})^4$, $p$ odd prime. This example complements a
previous counterexample in [arXiv:1509.01090], which existed only for $p \equiv
3 \pmod{4}$. On the contrary we show that the conjecture does hold in
$(\mathbb{Z}/2\mathbb{Z})^4$.


  This is the second paper of a series devoted to study the stellar content of
early-type galaxies. The goal of the series is to set constraints on the
evolutionary status of these objects. We use a new set of models which include
an improved stellar library (MILES) to derive simple stellar population
(SSP)-equivalent parameters in a sample of 98 early-type galaxies. The sample
contains galaxies in the field, poor groups, and galaxies in the Virgo and Coma
clusters.We find that low-density environment galaxies span a larger range in
SSP age and metallicity than their counterparts in high density environments,
with a tendency for lower sigma galaxies to be younger. Early-type galaxies in
low-density environments appear on average ~1.5 Gyr younger and more metal rich
than their counterparts in high density environments. The sample of low-density
environment galaxies shows an age metallicity relation in which younger
galaxies are found to be more metal rich, but only when metallicity is measured
with a Fe-sensitive index. Conversely, there is no age-metallicity relation
when the metallicity is measured with a Mg sensitive index. The
mass-metallicity relation is only appreciable for the low-density environment
galaxies when the metallicity is measured with a Mg-sensitive index and not
when the metallicity is measured with other indicators. On the contrary, this
relation exists for the high-density environment galaxies independently of the
indicator used to measure the metallicity. This suggests a dependence of the
mass-metallicity relation on the environment of the galaxies. Our data favour a
scenario in which galaxies in low density environments have suffered a more
extended star formation history than the galaxies in the Coma cluster, which
appear to host more homogenous stellar populations.


  We propose three different lattice operators to measure the intrinsic width
\xi_I of the chromoelectric flux tube in pure lattice gauge theories. In order
to test these proposals we evaluate them for SU(2) and Ising LGTs in (2+1)
dimensions in the vicinity of the deconfinement transition. Using dimensional
reduction, we could perform the calculation in the effective 2d spin model
using standard S-matrix techniques. We consistently found the same result for
the three lattice operators. This result can be expressed in terms of the
finite temperature string tension as follows \xi_I=\frac{T}{2\sigma(T)} and
implies that the intrinsic width of the flux tube diverges as the deconfinement
transition is approached.


  Current virtual reality (VR) training simulators of liver punctures often
rely on static 3D patient data and use an unrealistic (sinusoidal) periodic
animation of the respiratory movement. Existing methods for the animation of
breathing motion support simple mathematical or patient-specific, estimated
breathing models. However with personalized breathing models for each new
patient, a heavily dose relevant or expensive 4D data acquisition is mandatory
for keyframe-based motion modeling. Given the reference 4D data, first a model
building stage using linear regression motion field modeling takes place. Then
the methodology shown here allows the transfer of existing reference
respiratory motion models of a 4D reference patient to a new static 3D patient.
This goal is achieved by using non-linear inter-patient registration to warp
one personalized 4D motion field model to new 3D patient data. This cost- and
dose-saving new method is shown here visually in a qualitative proof-of-concept
study.


  Over 200 years ago, Gauss discovered a composition law on the $SL_2({\mathbb
Z})$-equivalence classes of primitive binary quadratic forms. Since then,
bijections of classes of binary forms have been found with ideal class groups
of quadratic rings. This paper uses one such bijection given by Bhargava,
relating classes of projective binary cubic forms to the $3$-torsion of an
ideal class group, to find an explicit form for a cubic analogue of Gaussian
composition.


  We use a Chandra X-ray observation of the gravitationally lensed system
MGB2016+112 at z=3.273 to elucidate presence of at least two X-ray sources. We
find that these sources are consistent with the VLBI components measured by
\citet{Spingola19}, which are separated by $\sim 200$ pc. Their intrinsic 0.5
-- 7 keV source frame luminosities are 2.6$\times$10$^{43}$ and
4.2$\times$10$^{44}$ erg s$^{-1}$. Most likely this system contains a dual
active galactic nucleus (AGN), but we possibly are detecting an AGN plus a
pc-scale X-ray jet, the latter lying in a region at very high magnification.
The quadruply lensed X-ray source is within $\pm$40 pc (1$\sigma$) of its VLBI
counterpart. Using a gravitational lens as a telescope, and a novel statistical
application, we have achieved unprecedented accuracy for measuring metric
distances at such large redshifts in X-ray astronomy, which is tens of mas if
the source is located close to the caustics, while it is of hundreds of mas if
the source is in a region at lower amplification. The present demonstration of
this approach has implications for future X-ray investigations of large numbers
of lensed systems.


  In this paper, we report the first quantum key-recovery attack on a symmetric
block cipher design, using classical queries only, with a more than quadratic
time speedup compared to the best classical attack.
  We study the 2XOR-Cascade construction of Ga\v{z}i and Tessaro
(EUROCRYPT~2012). It is a key length extension technique which provides an
n-bit block cipher with 5n/2 bits of security out of an n-bit block cipher with
2n bits of key, with a security proof in the ideal model. We show that the
offline-Simon algorithm of Bonnetain et al. (ASIACRYPT~2019) can be extended
to, in particular, attack this construction in quantum time \~O($2^n$),
providing a 2.5 quantum speedup over the best classical attack.
  Regarding post-quantum security of symmetric ciphers, it is commonly assumed
that doubling the key sizes is a sufficient precaution. This is because
Grover's quantum search algorithm, and its derivatives, can only reach a
quadratic speedup at most. Our attack shows that the structure of some
symmetric constructions can be exploited to overcome this limit. In particular,
the 2XOR-Cascade cannot be used to generically strengthen block ciphers against
quantum adversaries, as it would offer only the same security as the block
cipher itself.