  In this paper, we explore the possibility of accreting primordial black holes
as the source of heating for the collapsing gas in the context of the direct
collapse black hole scenario for the formation of super-massive black holes
(SMBHs) at high redshifts, $z\sim 6-7$. One of the essential requirements for
the direct collapse model to work is to maintain the temperature of the in
falling gas at $\approx 10^4$ K. We show that even under the existing abundance
limits, the primordial black holes of masses $\gtrsim 10^{-2} \ {\rm M}_\odot$,
can heat the collapsing gas to an extent that the ${\rm H}_2$ formation is
inhibited. The collapsing gas can maintain its temperature at $10^4$ K till the
gas reaches a critical density $n_{crit} \approx 10^3$ cm$^{-3}$, at which the
roto-vibrational states of ${\rm H}_2$ approaches local thermodynamic
equilibrium and ${\rm H}_2$ cooling becomes inefficient. In the absence of
${\rm H}_2$ cooling the temperature of the collapsing gas stays at $\approx
10^4$ K even as it collapses further. We discuss scenarios of subsequent
angular momentum removal and the route to find collapse through either a
supermassive star or a supermassive disk.


  In this paper, we proved decay properties of solutions to the Stokes
equations with surface tension and gravity in the half space
$\mathbf{R}_{+}^{N}=\{(x',x_N)\mid x'\in\mathbf{R}^{N-1},\ x_N>0\}$ $(N\geq
2)$. In order to prove the decay properties, we first show that the zero points
$\lambda_\pm$ of Lopatinskii determinant for some resolvent problem associated
with the Stokes equations have the asymptotics: $\lambda_\pm=\pm i
c_g^{1/2}|\xi'|^{1/2} -2|\xi'|^2+O(|\xi'|^{5/2})$ as $|\xi'|\to0$, where
$c_g>0$ is the gravitational acceleration and $\xi'\in\mathbf{R}^{N-1}$ is the
tangential variable in the Fourier space. We next shift the integral path in
the representation formula of the Stokes semi-group to the complex left
half-plane by Cauchy's integral theorem, and then it is decomposed into closed
curves enclosing $\lambda_\pm$ and the remainder part. We finally see, by the
residue theorem, that the low frequency part of the solution to the Stokes
equations behaves like the convolution of the $(N-1)$-dimensional heat kernel
and $\mathcal{F}_{\xi'}^{-1}[e^{\pm i c_g^{1/2}|\xi'|^{1/2}t}](x')$ formally,
where $\mathcal{F}_{\xi'}^{-1}$ is the inverse Fourier transform with respect
to $\xi'$. However, main task in our approach is to show that the remainder
part in the above decomposition decay faster than the residue part.


  Adiabatic mode evolution waveguides (AMEWs) are widely utilized in integrated
photonics, including tapered waveguides, edge couplers, mode converters,
splitters, etc. An analytical theory and a novel AMEW design algorithm are
developed to create shortcuts to adiabaticity (STA). This new algorithm is
effective in shortening the total length of the AMEW while maintaining the
desired wavelength range. Moreover, this analytical algorithm requires much
fewer computing resources than traditional numerical algorithms. With the new
algorithm, we demonstrate a broadband and highly efficient polarization
splitter-rotator (PSR) on a lithium-niobate-on-insulator (LNOI) platform with
an LN thickness of 500 nm. According to our simulation, the length of the PSR
is shortened by 3.5 times compared to the linear design. The fabricated PSR,
with a total length of 2 mm, exhibits an insertion loss (IL) of 0.8 dB and a
polarization extinction ratio (ER) of 12.2 dB over a wavelength range exceeding
76 nm.


  Insightful findings in political science often require researchers to analyze
documents of a certain subject or type, yet these documents are usually
contained in large corpora that do not distinguish between pertinent and
non-pertinent documents. In contrast, we can find corpora that label relevant
documents but have limitations (e.g., from a single source or era), preventing
their use for political science research. To bridge this gap, we present
\textit{adaptive ensembling}, an unsupervised domain adaptation framework,
equipped with a novel text classification model and time-aware training to
ensure our methods work well with diachronic corpora. Experiments on an
expert-annotated dataset show that our framework outperforms strong benchmarks.
Further analysis indicates that our methods are more stable, learn better
representations, and extract cleaner corpora for fine-grained analysis.


  Coding Theory where the alphabet is identified with the elements of a ring or
a module has become an important research topic over the last 30 years. Such
codes over rings had important applications and many interesting mathematical
problems are related to this line of research.
  It has been well established, that with the generalization of the algebraic
structure to rings there is a need to also generalize the underlying metric
beyond the usual Hamming weight used in traditional coding theory over finite
fields.
  This paper introduces a new weight, called the overweight, which can be seen
as a generalization of the Lee weight on the integers modulo $4$. For this new
weight we provide a number of well-known bounds, like a Plotkin bound, a
sphere-packing bound, and a Gilbert-Varshamov bound. A further highlight is the
proof of a Johnson bound for the homogeneous weight on a general finite
Frobenius ring.


  In this paper we consider a large class of many-variable polynomials which
contains generalisations of the classical Hermite, Laguerre, Jacobi and Bessel
polynomials as special cases, and which occur as the polynomial part in the
eigenfunctions of Calogero-Sutherland type operators and their deformations
recently found and studied by Chalykh, Feigin, Sergeev, and Veselov. We present
a unified and explicit construction of all these polynomials.


  The Majorana transformation makes it possible to reduce the Thomas-Fermi
equation to a first-order differential equation. This reduction is possible due
to the special scaling property of the Thomas-Fermi equation under homology
transformations. Such reductions are well known in the context of stellar
astrophysics, where the use of homology-invariant variables has long proved
useful. We use homology-invariant variables in the context of the Thomas-Fermi
equation to demystify the origin of the otherwise mysterious Majorana
transformation.


  We define the Witt coindex of a link with non-trivial Alexander polynomial,
as a concordance invariant from the Seifert form. We show that it provides an
upper bound for the (locally flat) slice Euler characteristic of the link,
extending the work of Levine on algebraically slice knots and Taylor on the
genera of knots. Then we extend the techniques by Levine on isometric
structures and characterize completely the forms of coindex $1$ under the
condition that the symmetrized Seifert form is non-degenerate. We illustrate
our results with examples where the coindex is used to show that a
two-component link does not bound a locally flat cylinder in the four-ball,
whereas any other known restriction does not show it.


  Hydrostatic equilibrium and energy conservation determine the conditions in
the gravitationally stabilized solar fusion reactor. We assume a matter density
distribution varying non-linearly through the central region of the Sun. The
analytic solutions of the differential equations of mass conservation,
hydrostatic equilibrium, and energy conservation, together with the equation of
state of the perfect gas and a nuclear energy generation rate
$\epsilon=\epsilon_0 \rho^nT^m$, are given in terms of Gauss' hypergeometric
function. This model for the structure of the Sun gives the run of density,
mass, pressure, temperature, and nuclear energy generation through the central
region of the Sun. Because of the assumption of a matter density distribution,
the conditions of hydrostatic equilibrium and energy conservation are separated
from the mode of energy transport in the Sun.


  This paper considers a joint multi-graph inference and clustering problem for
simultaneous inference of node centrality and association of graph signals with
their graphs. We study a mixture model of filtered low pass graph signals with
possibly non-white and low-rank excitation. While the mixture model is
motivated from practical scenarios, it presents significant challenges to prior
graph learning methods. As a remedy, we consider an inference problem focusing
on the node centrality of graphs. We design an expectation-maximization (EM)
algorithm with a unique low-rank plus sparse prior derived from low pass signal
property. We propose a novel online EM algorithm for inference from streaming
data. As an example, we extend the online algorithm to detect if the signals
are generated from an abnormal graph. We show that the proposed algorithms
converge to a stationary point of the maximum-a-posterior (MAP) problem.
Numerical experiments support our analysis.


  Dynamical instabilities in fluid mechanics are responsible of a variety of
important common phenomena, such as waves on the sea surface or Taylor vorteces
in Couette flow. In granular media dynamical instabilities has just begun to be
discovered. Here we show by means of molecular dynamics simulation the
existence of a new dynamical instability of a granular mixture under
oscillating horizontal shear, which leads to the formation of a striped pattern
where the components are segregated. We investigate the properties of such a
Kelvin-Helmholtz like instability and show how it is connected to pattern
formation in granular flow and segregation.


  We study a topological aspect of rank-1 double affine Hecke algebra (DAHA).
Clarified is a relationship between the DAHA of A1-type (resp. CC1-type) and
the skein algebra on a once-punctured torus (resp. a 4-punctured sphere), and
the SL(2;Z) actions of DAHAs are identified with the Dehn twists on the
surfaces. Combining these two types of DAHA, we construct the DAHA
representation for the skein algebra on a genus-two surface, and we propose a
DAHA polynomial for a double-torus knot, which is a simple closed curve on a
genus two Heegaard surface in S3. Discussed is a relationship between the DAHA
polynomial and the colored Jones polynomial.


  The Kassiopeia particle tracking framework is an object-oriented software
package using modern C++ techniques, written originally to meet the needs of
the KATRIN collaboration. Kassiopeia features a new algorithmic paradigm for
particle tracking simulations which targets experiments containing complex
geometries and electromagnetic fields, with high priority put on calculation
efficiency, customizability, extensibility, and ease of use for novice
programmers. To solve Kassiopeia's target physics problem the software is
capable of simulating particle trajectories governed by arbitrarily complex
differential equations of motion, continuous physics processes that may in part
be modeled as terms perturbing that equation of motion, stochastic processes
that occur in flight such as bulk scattering and decay, and stochastic surface
processes occuring at interfaces, including transmission and reflection
effects. This entire set of computations takes place against the backdrop of a
rich geometry package which serves a variety of roles, including initialization
of electromagnetic field simulations and the support of state-dependent
algorithm-swapping and behavioral changes as a particle's state evolves. Thanks
to the very general approach taken by Kassiopeia it can be used by other
experiments facing similar challenges when calculating particle trajectories in
electromagnetic fields. It is publicly available at
https://github.com/KATRIN-Experiment/Kassiopeia


  We study a model for macroions in an electrolyte solution confined by a
semipermeable membrane. The membrane finite thickness is considered and both
membrane surfaces are uniformly charged. The model explicitly includes
electrostatic and size particles correlations. Our study is focused on the
adsorption of macroions on the membrane surface and on the osmotic pressure.
The theoretical prediction for the osmotic pressure shows a good agreement with
experimental results.


  Online algorithms with predictions is a popular and elegant framework for
bypassing pessimistic lower bounds in competitive analysis. In this model,
online algorithms are supplied with future predictions, and the goal is for the
competitive ratio to smoothly interpolate between the best offline and online
bounds as a function of the prediction error. In this paper, we study online
graph problems with predictions. Our contributions are the following:
  * The first question is defining prediction error. For graph/metric problems,
there can be two types of error, locations that are not predicted, and
locations that are predicted but the predicted and actual locations do not
coincide exactly. We design a novel definition of prediction error called
metric error with outliers to simultaneously capture both types of errors,
which thereby generalizes previous definitions of error that only capture one
of the two error types.
  * We give a general framework for obtaining online algorithms with
predictions that combines, in a "black box" fashion, existing online and
offline algorithms, under certain technical conditions. To the best of our
knowledge, this is the first general-purpose tool for obtaining online
algorithms with predictions.
  * Using our framework, we obtain tight bounds on the competitive ratio of
several classical graph problems as a function of metric error with outliers:
Steiner tree, Steiner forest, priority Steiner tree/forest, and
uncapacitated/capacitated facility location.
  Both the definition of metric error with outliers and the general framework
for combining offline and online algorithms are not specific to the problems
that we consider in this paper. We hope that these will be useful for future
work in this domain.


  The strongly correlated bosons in flat band systems are an excellent platform
to study a wide range of quantum phenomena. Such systems can be realized in
optical lattices filled with ultracold atomic gases. In this paper we study the
Bose-Hubbard model in the Lieb lattice by means of the time-dependent
Gutzwiller mean-field approach. We find that in the Mott insulator phase the
excitation modes are gapped and display purely particle or purely hole
character, while in the superfluid phase the excitation spectrum is gapless.
The geometry of the Lieb lattice leads to a non-uniform order parameter and
non-uniform oscillation energy in the ground state. This results in additional
anti-crossings between dispersive bands in the excitation spectra, while the
flat bands remain insensitive to this effect. We analyze the oscillations of
the order parameter on the sublattices as well as the particle-hole character
of the excitations. For certain model parameters we find simultaneous pure
phase and pure amplitude oscillations within the same mode, separated between
the sublattices. Also, we propose a simple method to differentiate between the
hole- and particle superfluid regions in the Lieb lattice by in-situ
measurement of the atom population on the sublattices.


  Recent high precision measurements of deep inelastic diffractive scattering
at HERA are presented in an increased region of phase space. Current models for
diffractive photon dissociation are compared to the data.


  We study the multiferroic properties in the distorted tetrahedral quasi-one
dimensional spin system Cu$_3$Mo$_2$O$_9$, in which the effects of the low
dimensionality and the magnetic frustration are expected to appear
simultaneously. We clarify that the antiferromagnetic order is formed together
with ferroelectric properties at $T_{\rm N}=7.9$ K under zero magnetic field
and obtain the magnetic-field-temperature phase diagram by measuring dielectric
constant and spontaneous electric polarization. It is found that the
antiferromagnetic phase possesses a spontaneous electric polarization parallel
to the c axis when the magnetic field $H$ is applied parallel to the a axis. On
the other hand, there are three different ferroelectric phases in the
antiferromagnetic phase for $H$ parallel to the c axis.


  Three-dimensional complete photonic bandgap materials or photonic crystals
block light propagation in all directions. The rod-connected diamond structure
exhibits the largest photonic bandgap known to date and supports a complete
bandgap for the lowest refractive index contrast ratio down to
$n_{high}/n_{low} \sim 1.9$. We confirm this threshold by measuring a complete
photonic bandgap in the infrared region in Sn--S--O $(n\sim1.9)$ and
Ge--Sb--S--O $(n\sim2)$ inverse rod-connected diamond structures. The
structures were fabricated using a low-temperature chemical vapor deposition
process via a single-inversion technique. This provides a reliable fabrication
technique of complete photonic bandgap materials and expands the library of
backfilling materials, leading to a wide range of future photonic applications.


  We describe SR-POEM, a Galilean test of the weak equivalence principle that
is to be conducted during the free fall portion of the flight of a sounding
rocket payload. This test of a single pair of substances will have a
measurement uncertainty of {\sigma}({\eta}) < 2 10^17 after averaging the
results of eight separate drops, each of 120 s duration. The entire payload is
inverted between successive drops to cancel potential sources of systematic
error. The weak equivalence principle measurement is made with a set of four of
the SAO laser gauges, which have achieved an Allan deviation of 0.04 pm for an
averaging time of 30 s. We discuss aspects of the current design with an
emphasis on those that bear on the accuracy of the determination of {\eta}. The
discovery of a violation ({\eta} \neq 0) would have profound implications for
physics, astrophysics and cosmology.


  Rigorous assessment of the uncertainty is crucial to the utility of numerical
simulation of Turbulent flow. The Turbulent flows are often stationary and
ergodic, after some initial transient time. Therefore, the time averaged of a
quantity (velocity, TKE (turbulence kinetic energy), total drag, etc) converges
to a constant as the averaging interval increases. This infinite-time-average
statistic is of particular interest in many problems, such as aerodynamic shape
optimization. Since taking an average over the infinite time horizon is not
possible, some finite-time approximation of the infinite-time-average statistic
of interest is used in practice. However, because of the initial transient
behavior of the turbulence simulations, this estimate is biased. This issue is
solved by deleting the initial transient part of the simulation. The other
important issue is the error of this approximation decreases slowly, like the
reciprocal of the square roots of the averaging time. In this paper, we develop
a framework to first automatically deleted the transient part of a turbulence
simulation, then, quantify precisely the uncertainty of such a
finite-time-average approximation of an infinite-time-average statistic of a
stationary and ergodic process.


  We compare Particle-in-Cell simulation results of relativistic electron-ion
shear flows with different bulk Lorentz factors, and discuss their implications
for spine-sheath models of blazar versus gamma-ray burst (GRB) jets.
Specifically, we find that most properties of the shear boundary layer scale
with the bulk Lorentz factor: the lower the Lorentz factor, the thinner the
boundary layer, and the weaker the self-generated fields. Similarly, the
energized electron spectrum peaks at an energy near the ion drift energy, which
increases with bulk Lorentz factor, and the beaming of the accelerated
electrons gets narrower with increasing Lorentz factor. This predicts a strong
correlation between emitted photon energy, angular beaming and temporal
variability with the bulk Lorentz factor. Observationally, we expect systematic
differences between the high-energy emissions of blazars and GRB jets.


  Applying the method of light-cone sum rules with photon distribution
amplitudes, we compute the subleading-power correction to the radiative
leptonic $B \to \gamma \ell \nu$ decay, at next-to-leading order in QCD for the
twist-two contribution and at leading order in $\alpha_s$ for the higher-twist
contributions, induced by the hadronic component of the collinear photon. The
leading-twist hadronic photon effect turns out to preserve the symmetry
relation between the two $B \to \gamma$ form factors due to the helicity
conservation, however, the higher-twist hadronic photon corrections can yield
symmetry-breaking effect already at tree level in QCD. Using the conformal
expansion of photon distribution amplitudes with the non-perturbative
parameters estimated from QCD sum rules, the twist-two hadronic photon
contribution can give rise to approximately 30\% correction to the
leading-power "direct photon" effect computed from the perturbative QCD
factorization approach. In contrast, the subleading-power corrections from the
higher-twist two-particle and three-particle photon distribution amplitudes are
estimated to be of ${\cal O} (3 \sim 5\%)$ with the light-cone sum rule
approach. We further predict the partial branching fractions of $B \to \gamma
\ell \nu $ with a photon-energy cut $E_{\gamma} \geq E_{\rm cut}$, which are of
interest for determining the inverse moment of the leading-twist $B$-meson
distribution amplitude thanks to the forthcoming high-luminosity Belle II
experiment at KEK.


  Suspensions of rear- and front-actuated microswimmers immersed in a fluid,
known respectively as ``pushers'' and ``pullers'', display qualitatively
different collective behaviours: beyond a characteristic density, pusher
suspensions exhibit a hydrodynamic instability leading to collective motion
known as active turbulence, a phenomenon which is absent for pullers. In this
Letter, we describe the collective dynamics of a binary pusher--puller mixture
using kinetic theory and large-scale particle-resolved simulations. We derive
and verify an instability criterion, showing that the critical density for
active turbulence moves to higher values as the fraction $\chi$ of pullers is
increased and disappears for $\chi \geq 0.5$. We then show analytically and
numerically that the two-point hydrodynamic correlations of the 1:1 mixture are
equal to those of a suspension of noninteracting swimmers. Strikingly, our
numerical analysis furthermore shows that the full probability distribution of
the fluid velocity fluctuations collapses onto the one of a noninteracting
system at the same density, where swimmer--swimmer correlations are strictly
absent. Our results thus indicate that the fluid velocity fluctuations in 1:1
pusher--puller mixtures are exactly equal to those of the corresponding
noninteracting suspension at any density, a surprising cancellation with no
counterpart in equilibrium long-range interacting systems.


  We introduce two additive invariants of output quantum channels. If the value
of one these invariants is less than 1 then the logarithm of the inverse of its
value is a positive lower bound for the regularized minimum entropy of an
output quantum channel. We give a few examples in which one of these invariants
is less than 1. We also study the special cases where the above both invariants
are equal to 1.


  Aims: Chemical compositions and other properties of planetary nebulae around
central stars of spectral types [WC], [WO], and wels are compared with those of
`normal' central stars, in order to clarify the evolutionary status of each
type and their interrelation. Methods: We use plasma diagnostics to derive from
optical spectra the plasma parameters and chemical compositions of 48 planetary
nebulae. We also reanalyze the published spectra of a sample of 167 non-WR PN.
The results as well as the observational data are compared in detail with those
from other studies of the objects in common. Results: The central star's
spectral type is clearly correlated with electron density, temperature and
excitation class of the nebula, [WC] nebulae tend to be smaller than the other
types. All this corroborates the view of an evolutionary sequence from cool [WC
11] central stars inside dense, low excitation nebulae towards hot [WO 1] stars
with low density, high excitation nebulae. The wels PN, however, appear to be a
separate class of objects, not linked to WRPN by evolution, --abridged--


  Propagation channel characteristics are substantially different in sub-6 GHz
and millimeter-wave (mmWave) bands. A typical mmWave link experiences more than
an order-of-magnitude larger path loss and is more susceptible to blockages
than a traditional sub-6 GHz link. Therefore, extensive measurement campaigns
with efficient channel sounders are needed for a complete understanding of the
mmWave propagation channel characteristics. In addition, solutions should be
sought to overcome the outage problems associated with the mmWave bands and to
achieve acceptable communication performance. In this paper, our 28 GHz channel
sounder is introduced that can be used with horn antennas as well as phased
array antennas. The two antenna types are then compared in terms of speed they
switch from one direction to another and extracted multipath component (MPC)
properties, such as path gain. We then propose the use of passive reflectors
and an active repeater for coverage enhancement by improving the received
signal strength. In particular, ECHO reflector and TURBO repeater are
introduced, and measurement results using them are presented.


  In this paper, we propose a data representation model that demonstrates
hierarchical feature learning using nsNMF. We extend unit algorithm into
several layers. Experiments with document and image data successfully
discovered feature hierarchies. We also prove that proposed method results in
much better classification and reconstruction performance, especially for small
number of features. feature hierarchies.


  Evolution of coherent states is considered for a particle confined to a
cylinder moving in a harmonic oscillator potential. Because of the
discontinuous changes as time goes by of the phase representing the position of
a particle on a parallel (circle) the trajectory pattern of quantum averages
specifying coordinates on a cylinder is very complex and in some aspects
resembles chaotic one.


  We propose to use the High Momentum Spectrometer of Hall C combined with the
Neutral Particle Spectrometer (NPS) to perform high precision measurements of
the Deeply Virtual Compton Scattering (DVCS) cross section using a beam of
positrons. The combination of measurements with oppositely charged incident
beams is the only unambiguous way to disentangle the contribution of the
DVCS$^2$ term in the photon electroproduction cross section from its
interference with the Bethe-Heitler amplitude. This provides a stronger way to
constrain the Generalized Parton Distributions of the nucleon. A wide range of
kinematics accessible with an 11 GeV beam off an unpolarized proton target will
be covered. The $Q^2-$dependence of each contribution will be measured
independently.


  Rapid mass assembly, likely from mergers or smooth accretion, has been
predicted to play a vital role in star-formation in high-redshift Lyman-alpha
(Lya) emitters. Here we predict the major merger, minor merger, and smooth
accreting Lya emitter fraction from z~3 to z~7 using a large dark matter
simulation, and a simple physical model that is successful in reproducing many
observations over this large redshift range. The central tenet of this model,
different from many of the earlier models, is that the star-formation in Lya
emitters is proportional to the mass accretion rate rather than the total halo
mass. We find that at z~3, nearly 35% of the Lya emitters accrete their mass
through major (3:1) mergers, and this fraction increases to about 50% at z~7.
This imply that the star-formation in a large fraction of high-redshift Lya
emitters is driven by mergers. While there is discrepancy between the model
predictions and observed merger fractions, some of this difference (~15%) can
be attributed to the mass-ratio used to define a merger in the simulation. We
predict that future, deeper observations which use a 3:1 definition of major
mergers will find >30% major merger fraction of Lya emitters at redshifts >3.


  Chronic exposure to inorganic arsenic is a potential cause of carcinogenesis.
It elicits its potential by generation of ROS, leading to DNA, protein and
lipid damage. Therefore, the deleterious effect of arsenic can be mitigated by
quenching ROS using antioxidants. There is a homology between the protein
coding regions of mice and human. Effect of these alterations in human can be
mimicked in mice. Therefore to understand the underlying mechanism of arsenic
toxicity and its amelioration by black tea, studies have been conducted in mice
model. Long term exposure to iAs leads to tumour growth, which has been found
to be alleviated by black tea. Observations reveal that black tea has two
salutary effects on the growth of tumour: the rate of growth of damaged cells
was appreciably reduced and an early saturation of the level of damage is
achieved. To take the experimental findings further, the experimental data have
been modelled with simple dynamical equations. The curves obtained from
\textit{in vivo} studies have been fitted with the data obtained from the
model. The corresponding steady states and their stabilities are analyzed.


  Recently, the transductive graph-based methods have achieved great success in
the few-shot classification task. However, most existing methods ignore
exploring the class-level knowledge that can be easily learned by humans from
just a handful of samples. In this paper, we propose an Explicit Class
Knowledge Propagation Network (ECKPN), which is composed of the comparison,
squeeze and calibration modules, to address this problem. Specifically, we
first employ the comparison module to explore the pairwise sample relations to
learn rich sample representations in the instance-level graph. Then, we squeeze
the instance-level graph to generate the class-level graph, which can help
obtain the class-level visual knowledge and facilitate modeling the relations
of different classes. Next, the calibration module is adopted to characterize
the relations of the classes explicitly to obtain the more discriminative
class-level knowledge representations. Finally, we combine the class-level
knowledge with the instance-level sample representations to guide the inference
of the query samples. We conduct extensive experiments on four few-shot
classification benchmarks, and the experimental results show that the proposed
ECKPN significantly outperforms the state-of-the-art methods.


  In this paper we define and study self-similar ranked fragmentations. We
first show that any ranked fragmentation is the image of some partition-valued
fragmentation, and that there is in fact a one-to-one correspondence between
the laws of these two types of fragmentations. We then give an explicit
construction of homogeneous ranked fragmentations in terms of Poisson point
processes. Finally we use this construction and classical results on records of
Poisson point processes to study the small-time behavior of a ranked
fragmentation.


  Results are presented for a Hubble Space Telescope Advanced Camera for
Surveys high-resolution imaging campaign of 90 white dwarfs with known or
suspected low mass stellar and substellar companions. Of the 72 targets which
remain candidate and confirmed white dwarfs with near-infrared excess, 43 are
spatially resolved into two or more components, and a total of 12 systems are
potentially triples. There is a possible, slight deficit of earlier spectral
types (bluer colors) among the spatially unresolved companions, exactly the
opposite of expectations if significant mass is transferred to the companion
during the common envelope phase. Using the best available distance estimates,
the low mass companions to white dwarfs exhibit a bimodal distribution in
projected separation. This result supports the hypothesis that during the giant
phases of the white dwarf progenitor, any unevolved companions either migrate
inward to short periods of hours to days, or outward to periods of hundreds to
thousands of years. No intermediate projected separations of a few to several
AU are found among these pairs. However, a few double M dwarfs (within triples)
are spatially resolved in this range, empirically demonstrating that such
separations were readily detectable among the binaries with white dwarfs. A
straightforward and testable prediction emerges: all spatially unresolved, low
mass stellar and substellar companions to white dwarfs should be in short
period orbits. This result has implications for substellar companion and
planetary orbital evolution during the post-main sequence lifetime of their
stellar hosts.


  We point out the idea that, at small scales, gravity can be described by the
standard degrees of freedom of general relativity, plus a scalar particle and a
degree of freedom of a new type: the fakeon. This possibility leads to
fundamental implications in understanding gravitational force at quantum level
as well as phenomenological consequences in the corresponding classical theory.


  In a recent paper, Bacher and de la Harpe study conjugacy growth series of
infinite permutation groups and their relationships with $p(n)$, the partition
function, and $p(n)_{\textbf{e}}$, a generalized partition function. They prove
identities for the conjugacy growth series of the finitary symmetric group and
the finitary alternating group. The group theory also motivates an
investigation into congruence relationships between the finitary symmetric
group and the finitary alternating group. Using the Ramanujan congruences for
the partition function $p(n)$ and Atkin's generalization to the $k$-colored
partition function $p_{k}(n)$, we prove the existence of congruence relations
between these two series modulo arbitrary powers of 5 and 7, which we
systematically describe. Furthermore, we prove that such relationships exist
modulo powers of all primes $\ell\geq 5$.


  NGC 7538 IRS1 is a high-mass (approx. 30 M_sun) protostar with a CO outflow,
an associated UCHII region, and a linear methanol maser structure, which might
trace a Keplerian-rotating circumstellar disk. The directions of the various
associated axes are misaligned with each other. We investigate the
near-infrared morphology of the source to clarify the relations among the
various axes. K'-band bispectrum speckle interferometry was performed at two
6-meter-class telescopes -- the BTA 6m telescope and the 6.5m MMT.
Complementary IRAC images from the Spitzer Space Telescope Archive were used to
relate the structures detected with the outflow at larger scales. High-dynamic
range images show fan-shaped outflow structure in which we detect 18 stars and
several blobs of diffuse emission. We interpret the misalignment of various
outflow axes in the context of a disk precession model, including numerical
hydrodynamic simulations of the molecular emission. The precession period is
approx. 280 years and its half-opening angle is 40 degrees. A possible
triggering mechanism is non-coplanar tidal interaction of an (undiscovered)
close companion with the circumbinary protostellar disk. Our observations
resolve the nearby massive protostar NGC 7538 IRS2 as a close binary with
separation of 195 mas. We find indications for shock interaction between the
outflow activities in IRS1 and IRS2. Indications of outflow precession have
been discovered to date in a number of massive protostars, all with large
precession angles 20--45 degrees. This might explain the difference between the
outflow widths in low- and high-mass stars and add support to a common
collimation mechanism.


  An opaque set (or a barrier) for $U \subseteq \mathbb{R}^2$ is a set $B$ of
finite-length curves such that any line intersecting $U$ also intersects $B$.
In this paper, we consider the lower bound for the shortest barrier when $U$ is
the unit equilateral triangle. The known best lower bound for triangles is the
classic one by Jones [Jones,1964], which exhibits that the length of the
shortest barrier for any convex polygon is at least the half of its perimeter.
That is, for the unit equilateral triangle, it must be at least $3/2$. Very
recently, this lower bounds are improved for convex $k$-gons for any $k\geq 4$
[Kawamura et al. 2014], but the case of triangles still lack the bound better
than Jones' one. The main result of this paper is to fill this missing piece:
We give the lower bound of $3/2 + 5 \cdot 10^{-13}$ for the unit-size
equilateral triangle. The proof is based on two new ideas, angle-restricted
barriers and a weighted sum of projection-cover conditions, which may be of
independently interest.


  Many-body spin systems represent a paradigmatic platform for the realization
of emergent states of matter in a strongly interacting regime. Spin models are
commonly studied in one-dimensional periodic chains, whose lattice constant is
on the order of the interatomic distance. However, in cold atomic setups or
functionalized twisted van der Waals heterostructures, long-range modulations
of the spin physics can be engineered. Here we show that such superlattice
modulations in a many-body spin Hamiltonian can give rise to observable
topological boundary modes in the excitation spectrum of the spin chain. In the
case of an XY spin-$1/2$ chain, these boundary modes stem from a mathematical
correspondence with the chiral edge modes of a two-dimensional quantum Hall
state. Our results show that the addition of many-body interactions does not
close some of the topological gaps in the excitation spectrum, and the
topological boundary modes visibly persist in the isotropic Heisenberg limit.
These observations carry through when the spin moment is increased and a
large-spin limit of the phenomenon is established. Our results show that such
spin superlattices provide a promising route to observe many-body topological
boundary effects in cold atomic setups and functionalized twisted van der Waals
materials.


  Generative Adversarial Networks have shown remarkable success in learning a
distribution that faithfully recovers a reference distribution in its entirety.
However, in some cases, we may want to only learn some aspects (e.g., cluster
or manifold structure), while modifying others (e.g., style, orientation or
dimension). In this work, we propose an approach to learn generative models
across such incomparable spaces, and demonstrate how to steer the learned
distribution towards target properties. A key component of our model is the
Gromov-Wasserstein distance, a notion of discrepancy that compares
distributions relationally rather than absolutely. While this framework
subsumes current generative models in identically reproducing distributions,
its inherent flexibility allows application to tasks in manifold learning,
relational learning and cross-domain learning.


  The Fundamental Plane (FP) describes the relation between the stellar mass,
size, and velocity dispersion of elliptical galaxies; the Faber-Jackson
relation (FJR) is its projection onto {mass, velocity} space. In this work we
redeploy and expand the framework of Desmond & Wechsler (2015) to ask whether
abundance matching-based LCDM models that have shown success in matching the
spatial distribution of galaxies are also capable of explaining key properties
of the FJR and FP, including their scatter. Within our framework, agreement
with the normalisation of the FJR requires haloes to expand in response to disc
formation. We find that the tilt of the FP may be explained by a combination of
the observed non-homology in galaxy structure and the variation in
mass-to-light ratio produced by abundance matching with a universal initial
mass function (IMF), provided that the anisotropy of stellar motions is taken
into account. However, the predicted scatter around the FP is considerably
increased by situating galaxies in cosmologically-motivated haloes due to
variations in halo properties at fixed stellar mass, and appears to exceed that
of the data. This implies that additional correlations between galaxy and halo
variables may be required to fully reconcile these models with elliptical
galaxy scaling relations.


  This paper is part of a project to search the inner Milky Way for hidden
massive clusters and to address the question of whether our Galaxy still forms
clusters similar to the progenitors of the present-day globular clusters.
  We report high angular resolution deep near-infrared imaging of 21 cluster
candidates selected from the catalogues of Bica et al. (2003) and Dutra et
al.(2003) in a region around the Galactic Center. These catalogues were created
from visual inspection of the 2MASS images. Seven objects appear to be genuine
clusters, and for these objects we present estimates of extinction, distance
and in some cases age and mass.
  Our estimated masses range from 1200 to 5500 solar masses. These clusters are
thus significantly smaller than any Galactic globular cluster, and indicate
that the formation of massive young clusters such as Arches and Quintuplet is
not common in the present-day Milky Way.
  The remaining 14 objects are either not clusters or cannot be classified
based on our data.


  PURPOSE: To correct line-to-line delays and phase errors in echo-planar
imaging (EPI). THEORY AND METHODS: EPI- trajectory auto-corrected image
reconstruction (EPI-TrACR) is an iterative maximum-likelihood technique that
exploits data redundancy provided by multiple receive coils between nearby
lines of k-space to determine and correct line-to-line trajectory delays and
phase errors that cause ghosting artifacts. EPI-TrACR was applied to in vivo
data acquired at 7 Tesla across acceleration and multishot factors, and in a
dynamic time series. The method was efficiently implemented using a segmented
FFT and compared to a conventional calibrated reconstruction. RESULTS: Compared
to conventional calibrated reconstructions, EPI-TrACR reduced ghosting up to
moderate acceleration factors and across multishot factors. It also maintained
low ghosting in a dynamic time series. Averaged over all cases, EPI-TrACR
reduced root-mean-square ghosted signal outside the brain by 27% compared to
calibrated reconstruction. CONCLUSION: EPI-TrACR is effective in automatically
correcting line-to-line delays and phase errors in multishot, accelerated, and
dynamic EPI. While the method benefits from additional calibration data, it is
not a requirement.


  We obtain order-exact estimates for uniform approximations by using Zygmund
sums $Z^{s}_{n}$ of classes $C^{\psi}_{\beta,p}$ of $2\pi$-periodic continuous
functions $f$ representable by convolutions of functions from unit balls of the
space $L_{p}$, $1< p<\infty$, with a fixed kernels $\Psi_{\beta}\in L_{p'}$,
$\frac{1}{p}+\frac{1}{p'}=1$. In addition, we find a set of allowed values of
parameters (that define the class $C^{\psi}_{\beta,p}$ and the linear method
$Z^{s}_{n}$) for which Zygmund sums and Fejer sums realize the order of the
best uniform approximations by trigonometric polynomials of those classes.


  In the paper we introduce the new approach how to use an orthonormality
relation of coefficients of Dirichlet series defining given L-functions from
the Selberg class to prove joint universality.


  Utilizing the dataset corresponding to an integrated luminosity of $2.93$
fb$^{-1}$ at $\sqrt{s}=3.773$ GeV collected by the BESIII detector, we report
the first amplitude analysis and branching fraction measurement of the
$D^0\rightarrow K^-\pi^+\pi^0\pi^0$ decay. We investigate the sub-structures
and determine the relative fractions and the phases among the different
intermediate processes. Our results are used to provide an accurate detection
efficiency and allow measurement of ${\cal B}(D^0\rightarrow
K^-\pi^+\pi^0\pi^0) \,=\, (8.86 \pm 0.13(\text{stat}) \pm
0.19(\text{syst}))\%$.


  Recently, Li et al. (Int J Theor Phys: DOI: 10.1007/s10773-020-04588-w, 2020)
proposed a multiparty quantum key agreement protocol via non-maximally
entangled cluster states. They claimed that the proposed protocol can help all
the involved participants have equal influence on the final shared key.
However, this study points out a loophole that makes Li et al.'s protocol
suffer from a collusion attack, i.e. several dishonest participants can
conspire to manipulate the final shared key without being detected by others.
To avoid this loophole, an improvement is proposed here.


  The size-dependent phase stability of gamma-Al2O3 was studied by large-scale
molecular dynamics simulations over a wide temperature range from 300 to 900 K.
For the gamma-Al2O3 crystal, a bulk transformation to alpha-Al2O3 by an
FCC-to-HCP transition of the O sublattice is still kinetically hindered at 900
K. However, local distortions of the FCC O-sublattice by the formation of
quasi-octahedral Al local coordination spheres become thermally activated, as
driven by the partial covalency of the Al-O bond. On the contrary, spherical
gamma-Al2O3 NPs (with sizes of 6 and 10 nm) undergo a crystalline-to-amorphous
transformation at 900 K, which starts at the reconstructed surface and
propagates into the core through collective displacements of anions and
cations, resulting in the formation of 7- and 8-fold local coordination spheres
of Al. In parallel, the reconstructed Al-enriched surface is separated from the
stoichiometric core by a diffuse Al-depleted transition region. This
compositional heterogeneity creates a disbalance of charges inside the NP,
which induces a net attractive Coulombic force that is strong enough to reverse
the initial stress state in the NP core from compressive to tensile. These
findings disclose the delicate interplay between lattice distortions, stresses,
and space-charge regions in oxide nanosystems. A fundamental explanation for
the reported expansion of metal-oxide NPs with decreasing size is provided,
which has significant implications for e.g. heterogeneous catalysis, NP
sintering, and additive manufacturing of NP-reinforced metal matrix composites.


  The goal of this chapter is to support teachers in holistically introducing
graduate students to literature reviews, with a particular focus on secondary
research. It provides an overview of the overall literature review process and
the different types of literature review before diving into guidelines for
selecting and conducting different types of literature review. The chapter also
provides recommendations for evaluating the quality of existing literature
reviews and concludes with a summary of our learning goals and how the chapter
supports teachers in addressing them.


  Gyroscopic systems in classical and quantum field theory are characterized by
the presence of at least two scalar degrees of freedom and by terms that mix
fields and their time derivatives in the quadratic Lagrangian. In Minkowski
spacetime, they naturally appear in the presence of a coupling among fields
with time-dependent vacuum expectation values and fields with space-dependent
vacuum expectation values, breaking spontaneously Lorentz symmetry; this is the
case for a supersolid. In a cosmological background a gyroscopic system can
also arise from the time dependence of non-diagonal kinetic and mass matrices.
We study the classical and quantum dynamics computing the correlation functions
on the vacuum state that minimizes the energy. Two regions of stability in
parameter space are found: in one region, dubbed normal, the Hamiltonian is
positive defined, while in the second region, dubbed anomalous, it has no
definite sign. Interestingly, in the anomalous region the 2-point correlation
function exhibits a resonant behaviour in a certain region of parameter space.
We show that dynamical dark energy models (with exact equation of state $w=-1$)
can be realised as a gyroscopic system.


  In this paper the methodology and the results of a contactless thermal
characterization of a high temperature test chamber will be introduced. The
test chamber is used for fatigue testing of different MEMS devices where the
homogenous temperature distribution within the close proximity from the heating
filaments is very important. Our aim was to characterize the evolving
temperature distribution inside the test chamber. In order to achieve smaller
time constant a new contactless sensor card was developed. The contactless
thermal characterization method introduced in this paper enables in situ heat
distribution measurement inside the test chamber during operation, with the
detection of potentially uneven heat distribution.


  Learning representations of data is an important problem in statistics and
machine learning. While the origin of learning representations can be traced
back to factor analysis and multidimensional scaling in statistics, it has
become a central theme in deep learning with important applications in computer
vision and computational neuroscience. In this article, we review recent
advances in learning representations from a statistical perspective. In
particular, we review the following two themes: (a) unsupervised learning of
vector representations and (b) learning of both vector and matrix
representations.


  A major uncertainty in the spectroscopic dating of extragalactic globular
clusters concerns the degenerate effect that age and horizontal branch
morphology have on the strength of Balmer lines. In this Letter we show that
the ratio between the equivalent widths of Hdelta and Hbeta is far more
sensitive to horizontal branch morphology than to age, thus making it possible
to break the degeneracy. We show that it is possible to distinguish
intermediate-age globular clusters from those whose Balmer lines are
strengthened by the presence of blue horizontal branch stars, purely on the
basis of the clusters' integrated spectra. The degeneracy between age and
horizontal branch morphology can be lifted with Hbeta and Hdelta line strengths
from spectra with S/N >= 30 per Angstrom, which is typical of current studies
of integrated spectroscopy of extragalactic globular clusters.


  The Gauss Markov theorem states that the weighted least squares estimator is
a linear minimum variance unbiased estimation (MVUE) in linear models. In this
paper, we take a first step towards extending this result to non linear
settings via deep learning with bias constraints. The classical approach to
designing non-linear MVUEs is through maximum likelihood estimation (MLE) which
often involves computationally challenging optimizations. On the other hand,
deep learning methods allow for non-linear estimators with fixed computational
complexity. Learning based estimators perform optimally on average with respect
to their training set but may suffer from significant bias in other parameters.
To avoid this, we propose to add a simple bias constraint to the loss function,
resulting in an estimator we refer to as Bias Constrained Estimator (BCE). We
prove that this yields asymptotic MVUEs that behave similarly to the classical
MLEs and asymptotically attain the Cramer Rao bound. We demonstrate the
advantages of our approach in the context of signal to noise ratio estimation
as well as covariance estimation. A second motivation to BCE is in applications
where multiple estimates of the same unknown are averaged for improved
performance. Examples include distributed sensor networks and data augmentation
in test-time. In such applications, we show that BCE leads to asymptotically
consistent estimators.


  Continuous gravitational waves are long-lasting forms of gravitational
radiation produced by persistent quadrupolar variations of matter. Standard
expected sources for ground-based interferometric detectors are neutron stars
presenting non-axisymmetries such as crustal deformations, r-modes or free
precession. More exotic sources could include decaying ultralight boson clouds
around spinning black holes. A rich suite of data-analysis methods spanning a
wide bracket of thresholds between sensitivity and computational efficiency has
been developed during the last decades to search for these signals. In this
work, we review the current state of searches for continuous gravitational
waves using ground-based interferometer data, focusing on searches for unknown
sources. These searches typically consist of a main stage followed by several
post-processing steps to rule out outliers produced by detector noise. So far,
no continuous gravitational wave signal has been confidently detected, although
tighter upper limits are placed as detectors and search methods are further
developed.


  In this paper, we propose a multiphysics finite element method for a
quasi-static thermo-poroelasticity model with a nonlinear convective transport
term. To design some stable numerical methods and reveal the multi-physical
processes of deformation, diffusion and heat, we introduce three new variables
to reformulate the original model into a fluid coupled problem. Then, we
introduce an Newton's iterative algorithm by replacing the convective transport
term with $\nabla T^{i}\cdot(\bm{K}\nabla p^{i-1})$, $\nabla
T^{i-1}\cdot(\bm{K}\nabla p^{i})$ and $\nabla T^{i-1}\cdot(\bm{K}\nabla
p^{i-1})$, and apply the Banach fixed point theorem to prove the convergence of
the proposed method. Then, we propose a multiphysics finite element method with
Newton's iterative algorithm, which is equivalent to a stabilized method, can
effectively overcome the numerical oscillation caused by the nonlinear thermal
convection term. Also, we prove that the fully discrete multiphysics finite
element method has an optimal convergence order. Finally, we draw conclusions
to summarize the main results of this paper.


  Having in mind present uncertainty of the experimental situation in respect
to exotic hadrons, it is important to discuss any possible theoretical
arguments, pro and contra. Up to now, there are no theoretical ideas which
could forbid existence of the exotic states. Theoretical proofs for their
existence are also absent. However, there are some indirect arguments for the
latter case. It will be shown here, by using the complex angular momenta
approach, that the standard assumptions of analyticity and unitarity for
hadronic amplitudes lead to a non-trivial conclusion: the S-matrix has
infinitely many poles in the energy plane (accounting for all its Riemann
sheets). This is true for any arbitrary quantum numbers of the poles, exotic or
non-exotic. Whether some of the poles may provide physical (stable or
resonance) states, should be determined by some more detailed dynamics.


  Magnetic semiconductors are attracting high interest because of their
potential use for spintronics, a new technology which merges electronics and
manipulation of conduction electron spins. (GaMn)As and (GaMn)N have recently
emerged as the most popular materials for this new technology. While Curie
temperatures are rising towards room temperature, these materials can only be
fabricated in thin film form, are heavily defective, and are not obviously
compatible with Si. We show here that it is productive to consider transition
metal monosilicides as potential alternatives. In particular, we report the
discovery that the bulk metallic magnets derived from doping the narrow gap
insulator FeSi with Co share the very high anomalous Hall conductance of
(GaMn)As, while displaying Curie temperatures as high as 53 K. Our work opens
up a new arena for spintronics, involving a bulk material based only on
transition metals and Si, and which we have proven to display a variety of
large magnetic field effects on easily measured electrical properties.


  We study rational modules over complete path and monomial algebras, and the
problem of when rational modules over the dual $C^*$ of a coalgebra $C$ are
closed under extensions, equivalently, when is the functor $Rat$ a torsion
functor. We show that coreflexivity, closure under extensions of finite
dimensional rational modules and of arbitrary modules are Morita invariant, and
that they are preserved by subcoalgebras. We obtain new large classes of
examples of coalgebras with torsion functor, coming from monomial coalgebras,
and answer some questions in the literature.


  We investigate the parameter space of the Inert Doublet Model, which is a
straightforward extension of the SM in the scalar sector. We apply a set of
constraints both from the theoretical and experimental side to extract and
determine allowed regions of parameter space. These constraints put strong
limits on both masses and couplings of the new particles. We also present a set
of benchmarks for the current LHC run. This work is based on [1, 2].


  For a set of graphs $\mathcal{F}$, the extremal number $ex(n;\mathcal{F})$ is
the maximum number of edges in a graph of order $n$ not containing any subgraph
isomorphic to some graph in $\mathcal{F}$. If $\mathcal{F}$ contains a graph on
$n$ vertices, then we often call the problem a spanning Tur\'{a}n problem. A
linear forest is a graph whose connected components are all paths and isolated
vertices. In this paper, we let $\mathcal{L}_n^k$ be the set of all linear
forests of order $n$ with at least $n-k+1$ edges. We prove that when $n\geq 3k$
and $k\geq 2$, \[ ex(n;\mathcal{L}_n^k)=\binom{n-k+1}{2}+ O(k^2). \] Clearly,
the result is interesting when $k=o(n)$.


  Analog to the classical result of Kazdan-Warner for the existence of
solutions to the prescribed Gaussian curvature equation on compact 2-manifolds
without boundary, it is widely known that if $(M,g_0)$ is a closed 4-manifold
with zero $Q$-curvature and if $f$ is any non-constant, smooth, sign-changing
function with $\int_M f d\mu_{{\it g}_0} <0$, then there exists at least one
solution $u$ to the prescribed $Q$-curvature equation \[ \mathbf{P}_{g_0} u = f
e^{4u}, \] where $\mathbf{P}_{g_0}$ is the Paneitz operator which is positive
with kernel consisting of constant functions. In this paper, we fix a
non-constant smooth function $f_0$ with \[ \max_{x\in M}f_0(x)=0, \quad \int_M
f_0 d\mu_{{\it g}_0} <0 \] and consider a family of prescribed $Q$-curvature
equations \[ \mathbf{P}_{g_0} u=(f_0+\lambda)e^{4u}, \] where $\lambda>0$ is a
suitably small constant. A solution to the equation above can be obtained from
a minimizer $u_\lambda$ of certain energy functional associated to the
equation. Firstly, we prove that the minimizer $u_\lambda$ exhibits bubbling
phenomenon in a certain limit regime as $\lambda \searrow 0$. Then, we show
that the analogous phenomenon occurs in the context of $Q$-curvature flow.


  The search for direct interactions of dark matter particles remains one of
the most pressing challenges of contemporary experimental physics. A variety of
different approaches is required to probe the available parameter space and to
meet the technological challenges. Here, we review the experimental efforts
towards the detection of direct dark matter interactions using scintillating
crystals at cryogenic temperatures. We outline the ideas behind these detectors
and describe the principles of their operation. Recent developments are
summarized and various results from the search for rare processes are
presented. In the search for direct dark matter interactions, the CRESST-II
experiment delivers competitive limits, with a sensitivity below 5x10^(-7) pb
on the coherent WIMP-nucleon cross section.


  The Forelem framework was first introduced as a means to optimize database
queries using optimization techniques developed for compilers. Since its
introduction, Forelem has proven to be more versatile and to be applicable
beyond database applications. In this paper we show that the original Forelem
framework can be used to express and optimize Big Data applications, more
specifically: k-Means clustering and PageRank, resulting in automatically
generated implementations of these applications. These implementations are more
efficient than state-of-the-art, hand-written MPI C/C++ implementations of
k-Means and PageRank, as well as significantly outperform state-of-the-art
Hadoop implementations.


  We have reexamined the possibility of explaining the solar neutrino problem
through long-wavelength neutrino oscillations induced by a tiny breakdown of
the weak equivalence principle of general relativity. We found that such
gravitationally induce oscillations can provide a viable solution to the solar
neutrino problem.


  We present a hybrid numerical-asymptotic (HNA) boundary element method (BEM)
for high frequency scattering by two-dimensional screens and apertures, whose
computational cost to achieve any prescribed accuracy remains bounded with
increasing frequency. Our method is a collocation implementation of the high
order hp HNA approximation space of Hewett et al. IMA J. Numer. Anal. 35
(2015), pp.1698- 1728, where a Galerkin implementation was studied.
  An advantage of the current collocation scheme is that the one-dimensional
highly oscillatory singular integrals appearing in the BEM matrix entries are
significantly easier to evaluate than the two-dimensional integrals appearing
in the Galerkin case, which leads to much faster computation times. Here we
compute the required integrals at frequency-independent cost using the
numerical method of steepest descent, which involves complex contour
deformation.
  The change from Galerkin to collocation is nontrivial because naive
collocation implementations based on square linear systems suffer from severe
numerical instabilities associated with the numerical redundancy of the HNA
basis, which produces highly ill-conditioned BEM matrices. In this paper we
show how these instabilities can be removed by oversampling, and solving the
resulting overdetermined collocation system in a weighted least-squares sense
using a truncated singular value decomposition. On the basis of our numerical
experiments, the amount of oversampling required to stabilise the method is
modest (around 25% typically suffices) and independent of frequency. As an
application of our method we present numerical results for high frequency
scattering by prefractal approximations to the middle-third Cantor set.


  We investigate the single source shortest distance (SSSD) and all pairs
shortest distance (APSD) problems as enumeration problems (on unweighted and
integer weighted graphs), meaning that the elements $(u, v, d(u, v))$ -- where
$u$ and $v$ are vertices with shortest distance $d(u, v)$ -- are produced and
listed one by one without repetition. The performance is measured in the RAM
model of computation with respect to preprocessing time and delay, i.e., the
maximum time that elapses between two consecutive outputs. This point of view
reveals that specific types of output (e.g., excluding the non-reachable pairs
$(u, v, \infty)$, or excluding the self-distances $(u, u, 0)$) and the order of
enumeration (e.g., sorted by distance, sorted row-wise with respect to the
distance matrix) have a huge impact on the complexity of APSD while they appear
to have no effect on SSSD.
  In particular, we show for APSD that enumeration without output restrictions
is possible with delay in the order of the average degree. Excluding
non-reachable pairs, or requesting the output to be sorted by distance,
increases this delay to the order of the maximum degree. Further, for weighted
graphs, a delay in the order of the average degree is also not possible without
preprocessing or considering self-distances as output. In contrast, for SSSD we
find that a delay in the order of the maximum degree without preprocessing is
attainable and unavoidable for any of these requirements.


  Introduced as a notion of algorithmic fairness, multicalibration has proved
to be a powerful and versatile concept with implications far beyond its
original intent. This stringent notion -- that predictions be well-calibrated
across a rich class of intersecting subpopulations -- provides its strong
guarantees at a cost: the computational and sample complexity of learning
multicalibrated predictors are high, and grow exponentially with the number of
class labels. In contrast, the relaxed notion of multiaccuracy can be achieved
more efficiently, yet many of the most desirable properties of multicalibration
cannot be guaranteed assuming multiaccuracy alone. This tension raises a key
question: Can we learn predictors with multicalibration-style guarantees at a
cost commensurate with multiaccuracy?
  In this work, we define and initiate the study of Low-Degree
Multicalibration. Low-Degree Multicalibration defines a hierarchy of
increasingly-powerful multi-group fairness notions that spans multiaccuracy and
the original formulation of multicalibration at the extremes. Our main
technical contribution demonstrates that key properties of multicalibration,
related to fairness and accuracy, actually manifest as low-degree properties.
Importantly, we show that low-degree multicalibration can be significantly more
efficient than full multicalibration. In the multi-class setting, the sample
complexity to achieve low-degree multicalibration improves exponentially (in
the number of classes) over full multicalibration. Our work presents compelling
evidence that low-degree multicalibration represents a sweet spot, pairing
computational and sample efficiency with strong fairness and accuracy
guarantees.


  We propose a new class of mathematical structures called (m,n)-semirings}
(which generalize the usual semirings), and describe their basic properties. We
also define partial ordering, and generalize the concepts of congruence,
homomorphism, ideals, etc., for (m,n)-semirings. Following earlier work by Rao,
we consider a system as made up of several components whose failures may cause
it to fail, and represent the set of systems algebraically as an
(m,n)-semiring. Based on the characteristics of these components we present a
formalism to compare the fault tolerance behaviour of two systems using our
framework of a partially ordered (m,n)-semiring.


  For a general $k$-dimensional Brakke flow in $\mathbb{R}^n$ locally close to
a $k$-dimensional plane in the sense of measure, it is proved that the flow is
represented locally as a smooth graph over the plane with estimates on all the
derivatives up to the end-time. Moreover, at any point in space-time where the
Gaussian density is close to $1$, the flow can be extended smoothly as a mean
curvature flow up to that time in a neighborhood: this extends White's local
regularity theorem to general Brakke flows. The regularity result is in fact
obtained for more general Brakke-like flows, driven by the mean curvature plus
an additional forcing term in a dimensionally sharp integrability class or in a
H\"{o}lder class.


  Infant motility assessment using intelligent wearables is a promising new
approach for assessment of infant neurophysiological development, and where
efficient signal analysis plays a central role. This study investigates the use
of different end-to-end neural network architectures for processing infant
motility data from wearable sensors. We focus on the performance and
computational burden of alternative sensor encoder and time-series modelling
modules and their combinations. In addition, we explore the benefits of data
augmentation methods in ideal and non-ideal recording conditions. The
experiments are conducted using a data-set of multi-sensor movement recordings
from 7-month-old infants, as captured by a recently proposed smart jumpsuit for
infant motility assessment. Our results indicate that the choice of the encoder
module has a major impact on classifier performance. For sensor encoders, the
best performance was obtained with parallel 2-dimensional convolutions for
intra-sensor channel fusion with shared weights for all sensors. The results
also indicate that a relatively compact feature representation is obtainable
for within-sensor feature extraction without a drastic loss to classifier
performance. Comparison of time-series models revealed that feed-forward
dilated convolutions with residual and skip connections outperformed all
RNN-based models in performance, training time, and training stability. The
experiments also indicate that data augmentation improves model robustness in
simulated packet loss or sensor dropout scenarios. In particular, signal- and
sensor-dropout-based augmentation strategies provided considerable boosts to
performance without negatively affecting the baseline performance. Overall the
results provide tangible suggestions on how to optimize end-to-end neural
network training for multi-channel movement sensor data.


  This paper is aimed at presenting a simple vibronic model for describing the
dipolar reorientation in crystals by means of reaction rate theory. The
Hamiltonian of an isolated dipole is simplified so as to render the problem
solvable. Depending on the crossover splitting the dipoles may reorientate
adiabatically with a high electron-transfer expectancy or exhibit low
reorientation rates due to low expectancy. An important quantity to distinguish
between adiabatic dipoles behaving classically and ones reorientating by means
of quantum-mechanical tunneling is Christov's characteristic temperature which
is found to relate to the barrier height and crossover splitting. ITC data on
impurity-vacancy dipoles in Eu-doped alkali halides are reanalyzed.


  We characterize countable dimensionality and strong countable dimensionality
by means of an infinite game.


  The concept of photon added two-mode Schr\"odinger cat states in which both
modes are independent is introduced, their non-classical properties and
entanglement are studied. The introduced states emerge as the eigenstates of
$f_1f_2a_1a_2$, where $f_1, f_2$ are nonlinear functions of the number operator
and $a_1, a_2$ are annihilation operators. We study the evolution of these
states under the canonical transformation using the parity operator for the
case of standard coherent states of the harmonic oscillator. The non-classical
properties of these states are evaluated especially by considering
sub-Poissonian photon statistics and photon number distribution. Interestingly,
the addition of photons leads to shifting the region in which photon number
distribution shows oscillatory behavior. In addition, the entanglement of
introduced states has been quantitatively analyzed using concurrence. We
observe that the state approaches the maximum entanglement more rapidly after
the addition of photons.


  The ability to manipulate quantum information encoded in microwave fields has
led to a renewed interest in Josephson parametric amplifiers (JPAs). For these
applications the ability of JPAs to amplify signals with the least amount of
added noise is critical. Unfortunately JPAs are typically narrow band
amplifiers with small dynamic range. It is therefore important to understand
the bandwidth and dynamic range of any particular JPA in order to determine if
it is appropriate for these applications. We recently introduced a new kind of
JPA. Although it is still narrow band, the amplified band can be tuned over a
full octave. We have shown that it has good noise performance and can squeeze
the vacuum noise by 10 dB. Here we characterize other important parameters of
this amplifier, specifically the signal-bandwidth, dynamic range and saturation
power.


  Wireless links using massive MIMO transceivers are vital for next generation
wireless communications networks networks. Precoding in Massive MIMO
transmission requires accurate downlink channel state information (CSI). Many
recent works have effectively applied deep learning (DL) to jointly train
UE-side compression networks for delay domain CSI and a BS-side decoding
scheme. Vitally, these works assume that the full delay domain CSI is available
at the UE, but in reality, the UE must estimate the delay domain based on a
limited number of frequency domain pilots. In this work, we propose a linear
pilot-to-delay (P2D) estimator that transforms sparse frequency pilots to the
truncated delay CSI. We show that the P2D estimator is accurate under frequency
downsampling, and we demonstrate that the P2D estimate can be effectively
utilized with existing autoencoder-based CSI estimation networks. In addition
to accounting for pilot-based estimates of downlink CSI, we apply unrolled
optimization networks to emulate iterative solutions to compressed sensing
(CS), and we demonstrate better estimation performance than prior
autoencoder-based DL networks. Finally, we investigate the efficacy of
trainable CS networks for in a differential encoding network for time-varying
CSI estimation, and we propose a new network, MarkovNet-ISTA-ENet, comprised of
both a CS network for initial CSI estimation and multiple autoencoders to
estimate the error terms. We demonstrate that this heterogeneous network has
better asymptotic performance than networks comprised of only one type of
network.


  We estimate the covariance in counts of almost-primes in $\mathbb{F}_q[T]$,
weighted by higher-order von Mangoldt functions. The answer takes a pleasant
algebraic form. This generalizes recent work of Keating and Rudnick that
estimates the variance of primes, and makes use, as theirs, of a recent
equidistribution result of Katz.
  In an appendix we prove some related identities for random matrix statistics,
which allows us to give a quick proof of a $2\times2$ ratio theorem for the
characteristic polynomial of the unitary group. We additionally identify
arithmetic functions whose statistics mimic those of hook Schur functions.


  In this note, we shortly survey some recent approaches on the approximation
of the Bayes factor used in Bayesian hypothesis testing and in Bayesian model
choice. In particular, we reassess importance sampling, harmonic mean sampling,
and nested sampling from a unified perspective.


  Here we report an ensemble study of 214 A- and F-type stars observed by
\textit{Kepler}, exhibiting the so-called \textit{hump and spike} periodic
signal, explained by Rossby modes (r~modes) -- the \textit{hump} -- and
magnetic stellar spots or overstable convective (OsC) modes -- the
\textit{spike} -- respectively. We determine the power confined in the
non-resolved hump features and find additional gravity~modes (g~modes) humps
always occurring at higher frequencies than the spike. Furthermore, we derive
projected rotational velocities from FIES, SONG and HERMES spectra for 28 stars
and the stellar inclination angle for 89 stars. We find a strong correlation
between the spike amplitude and the power in the r and g~modes, which suggests
that both types of oscillations are mechanically excited by either stellar
spots or OsC modes. Our analysis suggests that stars with a higher power in
$m=1$ r~modes humps are more likely to also exhibit humps at higher azimuthal
orders ($m$ = 2, 3, or 4). Interestingly, all stars that show g~modes humps are
hotter and more luminous than the observed red edge of the $\delta$ Scuti
instability strip, suggesting that either magnetic fields or convection in the
outer layers could play an important role.


  We perform a detailed and comprehensive study of several flavor physics
observables in both lepton and quark sectors within the framework of an
extended 2HDM theory where the inverse seesaw mechanism is implemented to
generate the SM fermion mass hierarchy. In that theory, the SM gauge symmetry
is supplemented by the local $U(1)_X$ and discrete $Z_4\times Z_2$ groups. In
particular, we find that the leptonic flavor observables specifically, the
branching ratios of LFV decays $\mu\to e\gamma, \tau\to e(\mu)\gamma$ and the
anomalous magnetic moments $\Delta a_{e(\mu)}$ strongly depend on the couplings
of the neutral CP even(odd) Higgses with exotic charged lepton $E_1$, whereas
other observables involving BR($l\to 3l'$), Mu-$\overline{\text{Mu}}$
transition and coherent conversion $\mu \to e $ in a muonic atom are predicted
to be less than several orders of magnitude compared to the corresponding
experimental limits. Regarding the quark sector, the most stringent limits
arising from the FCNC process involving the down-type quark $d_a\to d_b$
($a=1,2,3$) transitions such as BR($\bar{B}\to X_s \gamma$), BR$(B_s\to
\mu^+\mu^-)$, and meson mixing $ \Delta m_{K,B_s, B_d}$. Considering the
obtained constraints from these observables, the new physics contributions to
other observables namely BR$(B_s\to \tau^+\mu^-)$, BR$(B^+\to
K^+\tau^+\tau^-)$, BR$(B^+\to K^+\tau^+\mu^-)$, and FCCC $b\to c$ transition
LFUV ratios $R_{D^{(*)}}$ are shown to be remarkably small. Regarding the
observables in the up-type quark transitions, the FCNC top quark processes
$t\to u(c)\gamma$ and $t\to u(c)h$ have branching ratios consistent with the
experimental limits. Additionally, observables related to SM-like Higgs boson
decays BR$(h\to \bar{l}'l)$ and modified couplings $a_{h\bar{f}f}$ are also
discussed.


  We find that in the kinematic limit the ensemble averaged square of the
curvature of magnetic field lines is exponentially amplified in time by the
turbulent motions in a highly conductive plasma. At the same time, the ensemble
averaged curvature vector exponentially decays to zero. Thus, independently of
the initial conditions, the fluctuation field becomes very curved, and the
curvature vector becomes highly isotropic.
  Keywords: ISM: magnetic fields, MHD, turbulence, methods: analytical


  Existing approaches to depth or disparity estimation output a distribution
over a set of pre-defined discrete values. This leads to inaccurate results
when the true depth or disparity does not match any of these values. The fact
that this distribution is usually learned indirectly through a regression loss
causes further problems in ambiguous regions around object boundaries. We
address these issues using a new neural network architecture that is capable of
outputting arbitrary depth values, and a new loss function that is derived from
the Wasserstein distance between the true and the predicted distributions. We
validate our approach on a variety of tasks, including stereo disparity and
depth estimation, and the downstream 3D object detection. Our approach
drastically reduces the error in ambiguous regions, especially around object
boundaries that greatly affect the localization of objects in 3D, achieving the
state-of-the-art in 3D object detection for autonomous driving. Our code will
be available at https://github.com/Div99/W-Stereo-Disp.


  We study operators of the form $$ Tf(x)= \psi(x) \int f(\gamma_t(x))K(t)\,dt,
$$ where $\gamma_t(x)$ is a real analytic function of $(t,x)$ mapping from a
neighborhood of $(0,0)$ in $\mathbb{R}^N \times \mathbb{R}^n$ into
$\mathbb{R}^n$ satisfying $\gamma_0(x)\equiv x$, $\psi(x) \in
C_c^\infty(\mathbb{R}^n)$, and $K(t)$ is a "multi-parameter singular kernel"
with compact support in $\mathbb{R}^N$; for example when $K(t)$ is a product
singular kernel. The celebrated work of Christ, Nagel, Stein, and Wainger
studied such operators with smooth $\gamma_t(x)$, in the single-parameter case
when $K(t)$ is a Calder\'on-Zygmund kernel. Street and Stein generalized their
work to the multi-parameter case, and gave sufficient conditions for the
$L^p$-boundedness of such operators. This paper shows that when $\gamma_t(x)$
is real analytic, the sufficient conditions of Street and Stein are also
necessary for the $L^p$-boundedness of $T$, for all such kernels $K$.


  Many existing thermal management techniques focus on reducing the overall
power consumption of the chip, and do not address location-specific temperature
problems referred to as hotspots. We propose the use of dynamic runtime
reconfiguration to shift the hotspot-inducing computation periodically and make
the thermal profile more uniform. Our analysis shows that dynamic
reconfiguration is an effective technique in reducing hotspots for NoCs.


  Convergence properties of the variational cluster approach with respect to
the variational parameter space, cluster size, and boundary conditions of the
reference system are investigated and discussed for bosonic many-body systems.
Specifically, the variational cluster approach is applied to the
one-dimensional Bose-Hubbard model, which exhibits a quantum phase transition
from Mott to superfluid phase. In order to benchmark the variational cluster
approach, results for the phase boundary delimiting the first Mott lobe are
compared with essentially exact density matrix renormalization group data.
Furthermore, static quantities, such as the ground state energy and the
one-particle density matrix are compared with high-order strong coupling
perturbation theory results. For reference systems with open boundary
conditions the variational parameter space is extended by an additional
variational parameter which allows for a more uniform particle density on the
reference system and thus drastically improves the results. It turns out that
the variational cluster approach yields accurate results with relatively low
computational effort for both spectral as well as static properties of the
one-dimensional Bose-Hubbard model, even at the tip of the first Mott lobe
where correlation effects are most pronounced.


  A generalization of the free energy perturbation identity is derived, and a
computational strategy based on this result is presented. A simple example
illustrates the efficiency gains that can be achieved with this method.


  We first introduce and study two new classes of subsets in $T_0$ spaces -
$\omega$-Rudin sets and $\omega$-well-filtered determined sets lying between
the class of all closures of countable directed subsets and that of irreducible
closed subsets, and two new types of spaces - $\omega$-$d$ spaces and
$\omega$-well-filtered spaces. We prove that an $\omega$-well-filtered $T_0$
space is locally compact iff it is core compact. One immediate corollary is
that every core compact well-filtered space is sober, answering Jia-Jung
problem with a new method. We also prove that all irreducible closed subsets in
a first countable $\omega$-well-filtered $T_0$ space are directed. Therefore, a
first countable $T_0$ space $X$ is sober iff $X$ is well-filtered iff $X$ is an
$\omega$-well-filtered $d$-space. Using $\omega$-well-filtered determined sets,
we present a direct construction of the $\omega$-well-filtered reflections of
$T_0$ spaces, and show that products of $\omega$-well-filtered spaces are
$\omega$-well-filtered.


  In this paper, we will get the analytical expression of the number of real
zeros of a random equation in a interval. First, we present some proprieties of
this expectation. Then we discuss a special case that the random function is
linear in x, and promote the analytical expression of the expectation.
Especially, when the parameter obeys some special distributions, e.g. the
uniform distribution in a sup-sphere, the norm distribution, more concise
results are got. Finally, we use our results to some classical problems, e.g.
random polynomials, random trigonometric equations and etc, and all get the
same result existed, which means that all existed results with proper density
functions are our corollaries.


  Information theoretic quantities play a central role in machine learning. The
recent surge in the complexity of data and models has increased the demand for
accurate estimation of these quantities. However, as the dimension grows the
estimation presents significant challenges, with existing methods struggling
already in relatively low dimensions. To address this issue, in this work, we
introduce $\texttt{REMEDI}$ for efficient and accurate estimation of
differential entropy, a fundamental information theoretic quantity. The
approach combines the minimization of the cross-entropy for simple, adaptive
base models and the estimation of their deviation, in terms of the relative
entropy, from the data density. Our approach demonstrates improvement across a
broad spectrum of estimation tasks, encompassing entropy estimation on both
synthetic and natural data. Further, we extend important theoretical
consistency results to a more generalized setting required by our approach. We
illustrate how the framework can be naturally extended to information theoretic
supervised learning models, with a specific focus on the Information Bottleneck
approach. It is demonstrated that the method delivers better accuracy compared
to the existing methods in Information Bottleneck. In addition, we explore a
natural connection between $\texttt{REMEDI}$ and generative modeling using
rejection sampling and Langevin dynamics.


  The growing threat of personal data breach in data trading pinpoints an
urgent need to develop countermeasures for preserving individual privacy. The
state-of-the-art work either endows the data collector with the responsibility
of data privacy or reports only a privacy-preserving version of the data. The
basic assumption of the former approach that the data collector is trustworthy
does not always hold true in reality, whereas the latter approach reduces the
value of data. In this paper, we investigate the privacy leakage issue from the
root source. Specifically, we take a fresh look to reverse the inferior
position of the data provider by making her dominate the game with the
collector to solve the dilemma in data trading. To that aim, we propose the
noisy-sequentially zero-determinant (NSZD) strategies by tailoring the
classical zero-determinant strategies, originally designed for the
simultaneous-move game, to adapt to the noisy sequential game. NSZD strategies
can empower the data provider to unilaterally set the expected payoff of the
data collector or enforce a positive relationship between her and the data
collector's expected payoffs. Both strategies can stimulate a rational data
collector to behave honestly, boosting a healthy data trading market. Numerical
simulations are used to examine the impacts of key parameters and the feasible
region where the data provider can be an NSZD player. Finally, we prove that
the data collector cannot employ NSZD to further dominate the data market for
deteriorating privacy leakage.


  We use the dynamics of a galaxy, set up initially at a constant proper
distance from an observer, to derive and illustrate two counter-intuitive
general relativistic results. Although the galaxy does gradually join the
expansion of the universe (Hubble flow), it does not necessarily recede from
us. In particular, in the currently favored cosmological model, which includes
a cosmological constant, the galaxy recedes from the observer as it joins the
Hubble flow, but in the previously favored cold dark matter model, the galaxy
approaches, passes through the observer, and joins the Hubble flow on the
opposite side of the sky. We show that this behavior is consistent with the
general relativistic idea that space is expanding and is determined by the
acceleration of the expansion of the universe -- not a force or drag associated
with the expansion itself. We also show that objects at a constant proper
distance will have a nonzero redshift; receding galaxies can be blueshifted and
approaching galaxies can be redshifted.


  We compute numerically small window overlaps in the three dimensional Edwards
Anderson spin glass. We show that they behave in the way implied by the Replica
Symmetry Breaking Ansatz, that they do not qualitatively differ from the full
volume overlap and do not tend to a trivial function when increasing the
lattice volume. On the contrary we show they are affected by small finite
volume effects, and are interesting tools for the study of the features of the
spin glass phase.


  Recently the long-standing puzzle about counting the Witten index in N=1
supersymmetric gauge theories was resolved. The resolution was based on
existence (for higher orthogonal $SO(N), N \geq 7$ and exceptional gauge
groups) of flat connections on $T^{3}$ which have commuting holonomies but
cannot be gauged to a Cartan torus. A number of papers has been published which
studied moduli spaces and some topological characteristics of those flat
connections. In the present letter an explicit description of such flat
connection for the basic case of $Spin(7)$ is given.


  We study the production of gravitational waves during oscillations of the
inflaton around the minimum of a cuspy potential after inflation. We find that
a cusp in the potential can trigger copious oscillon formation, which sources a
characteristic energy spectrum of gravitational waves with double peaks. The
discovery of such a double-peak spectrum could test the underlying inflationary
physics.


  Linguistic analysis of language models is one of the ways to explain and
describe their reasoning, weaknesses, and limitations. In the probing part of
the model interpretability research, studies concern individual languages as
well as individual linguistic structures. The question arises: are the detected
regularities linguistically coherent, or on the contrary, do they dissonate at
the typological scale? Moreover, the majority of studies address the inherent
set of languages and linguistic structures, leaving the actual typological
diversity knowledge out of scope. In this paper, we present and apply the
GUI-assisted framework allowing us to easily probe a massive number of
languages for all the morphosyntactic features present in the Universal
Dependencies data. We show that reflecting the anglo-centric trend in NLP over
the past years, most of the regularities revealed in the mBERT model are
typical for the western-European languages. Our framework can be integrated
with the existing probing toolboxes, model cards, and leaderboards, allowing
practitioners to use and share their standard probing methods to interpret
multilingual models. Thus we propose a toolkit to systematize the multilingual
flaws in multilingual models, providing a reproducible experimental setup for
104 languages and 80 morphosyntactic features.
https://github.com/AIRI-Institute/Probing_framework


  This Letter presents the first experimental evidence of the attractive strong
interaction between a proton and a $\phi$ meson. The result is obtained from
two-particle correlations of combined p-$\phi \oplus \overline{\rm {p}}$-$\phi$
pairs measured in high-multiplicity pp collisions at $\sqrt{s}~=~13$ TeV by the
ALICE collaboration. The spin-averaged scattering length and effective range of
the p-$\phi$ interaction are extracted from the fully corrected correlation
function employing the Lednick\'y-Lyuboshits approach. In particular, the
imaginary part of the scattering length vanishes within uncertainties,
indicating that inelastic processes do not play a prominent role for the
p-$\phi$ interaction. These data demonstrate that the interaction is dominated
by elastic p-$\phi$ scattering. Furthermore, an analysis employing
phenomenological Gaussian- and Yukawa-type potentials is conducted. Under the
assumption of the latter, the N-$\phi$ coupling constant is found to be
$g_{\rm{N}-\phi} = 0.14\pm 0.03\,(\mathrm{stat.})\pm 0.02\,(\mathrm{syst.})$.
This work provides valuable experimental input to accomplish a self-consistent
description of the N-$\phi$ interaction, which is particularly relevant for the
more fundamental studies on partial restoration of chiral symmetry in nuclear
medium.


  We review the history of the ghost problem in quantum field theory from the
Pauli-Villars regulator theory to currently popular fourth-order derivative
quantum gravity theories. While these theories all appear to have
unitarity-violating ghost states with negative norm, we show that in fact these
ghost states only appear because the theories are being formulated in the wrong
Hilbert space. In these theories the Hamiltonians are not Hermitian but instead
possess an antilinear symmetry. Consequently, one cannot use inner products
that are built out of states and their Hermitian conjugates. Rather, one must
use inner products built out of states and their conjugates with respect to the
antilinear symmetry, and these latter inner products are positive. In this way
one can build quantum theories of gravity in four spacetime dimensions that are
unitary.


  Numerical simulations have become an important tool to understand and predict
non-perturbative phenomena in particle physics. In this article we attempt to
present a general overview over the field. First, the basic concepts of lattice
gauge theories are described, including a discussion of currently used
algorithms and the reconstruction of continuum physics from lattice results. We
then proceed to present some results for QCD, both at low energies and at high
temperatures, as well as for the electro-weak sector of the standard model.


  We give new linear time globally explicit constructions for perfect hash
families, cover-free families and separating hash functions.


  The well-known ponderomotive force, arising from the interaction of matter
and light, has critical implications across a broad range of fields from laser
fusion and astrophysics to laser diagnostics and even pulsed-power experiments.
This pseudo-potential pushes electrons, which through coulomb forces causes ion
density modulations that can steepen with profound implications. When used
intentionally, density modulations can be used for plasma gratings, which are
essential for optical components operating in extreme conditions for next
generation lasers. They can also be important for plasma confinement and
particle trapping, which can even impact magnetic confinement in fusion
devices. The ponderomotive potential also leads to laser self-focusing,
complicating laser diagnostics. In laser fusion, the force exacerbates
challenges posed by stimulated Brillouin scattering (SBS) and crossed beam
energy transfer (CBET), both of which destabilize the fusion process. It even
plays an astrophysical role in the filamentation of fast radio bursts in the
relativistic winds of magnetars. Since the ponderomotive force primarily
effects electron dynamics, multi-fluid/particle codes or additional ansatz are
required to include its effects. This paper demonstrates that by including
electron effects on an ion timescale with a 1-fluid, 2-energy extended
magnetohydrodynamics (XMHD) model, ponderomotive effects are also naturally
present. We introduce the theory for these dynamics and demonstrate their
presence with 1-D pencil-like simulations.


  We investigate two types of query games played on a graph, pair queries and
edge queries. We concentrate on investigating the two associated graph
parameters for binomial random graphs, and showing that determining any of the
two parameters is NP-hard for bounded degree graphs.


  We report a sample of 463 high-mass starless clump (HMSC) candidates within
$-60\deg<l<60\deg$ and $-1\deg<b<1\deg$. This sample has been singled out from
10861 ATLASGAL clumps. All of these sources are not associated with any known
star-forming activities collected in SIMBAD and young stellar objects
identified using color-based criteria. We also make sure that the HMSC
candidates have neither point sources at 24 and 70 \micron~nor strong extended
emission at 24 $\mu$m. Most of the identified HMSCs are infrared ($\le24$
$\mu$m) dark and some are even dark at 70 $\mu$m. Their distribution shows
crowding in Galactic spiral arms and toward the Galactic center and some
well-known star-forming complexes. Many HMSCs are associated with large-scale
filaments. Some basic parameters were attained from column density and dust
temperature maps constructed via fitting far-infrared and submillimeter
continuum data to modified blackbodies. The HMSC candidates have sizes, masses,
and densities similar to clumps associated with Class II methanol masers and
HII regions, suggesting they will evolve into star-forming clumps. More than
90% of the HMSC candidates have densities above some proposed thresholds for
forming high-mass stars. With dust temperatures and luminosity-to-mass ratios
significantly lower than that for star-forming sources, the HMSC candidates are
externally heated and genuinely at very early stages of high-mass star
formation. Twenty sources with equivalent radius $r_\mathrm{eq}<0.15$ pc and
mass surface density $\Sigma>0.08$ g cm$^{-2}$ could be possible high-mass
starless cores. Further investigations toward these HMSCs would undoubtedly
shed light on comprehensively understanding the birth of high-mass stars.


  A standard objective in computer experiments is to approximate the behaviour
of an unknown function on a compact domain from a few evaluations inside the
domain. When little is known about the function, space-filling design is
advisable: typically, points of evaluation spread out across the available
space are obtained by minimizing a geometrical (for instance, covering radius)
or a discrepancy criterion measuring distance to uniformity. The paper
investigates connections between design for integration (quadrature design),
construction of the (continuous) BLUE for the location model, space-filling
design, and minimization of energy (kernel discrepancy) for signed measures.
Integrally strictly positive definite kernels define strictly convex energy
functionals, with an equivalence between the notions of potential and
directional derivative, showing the strong relation between discrepancy
minimization and more traditional design of optimal experiments. In particular,
kernel herding algorithms, which are special instances of vertex-direction
methods used in optimal design, can be applied to the construction of point
sequences with suitable space-filling properties.


  We report quantum Monte Carlo evidence of the existence of large gap
superfluidity in electron-hole double layers over wide density ranges. The
superfluid parameters evolve from normal state to BEC with decreasing density,
with the BCS state restricted to a tiny range of densities due to the strong
screening of Coulomb interactions, which causes the gap to rapidly become large
near the onset of superfluidity. The superfluid properties exhibit similarities
to ultracold fermions and iron-based superconductors, suggesting an underlying
universal behavior of BCS-BEC crossovers in pairing systems.