  In this paper, we study the problem of learning probabilistic logical rules
for inductive and interpretable link prediction. Despite the importance of
inductive link prediction, most previous works focused on transductive link
prediction and cannot manage previously unseen entities. Moreover, they are
black-box models that are not easily explainable for humans. We propose DRUM, a
scalable and differentiable approach for mining first-order logical rules from
knowledge graphs which resolves these problems. We motivate our method by
making a connection between learning confidence scores for each rule and
low-rank tensor approximation. DRUM uses bidirectional RNNs to share useful
information across the tasks of learning rules for different relations. We also
empirically demonstrate the efficiency of DRUM over existing rule mining
methods for inductive link prediction on a variety of benchmark datasets.


  Suzuki's split-step quantum walk on the one-dimensional integer lattice can
be naturally viewed as a chirally symmetric quantum walk. Given the unitary
time-evolution of such a chirally symmetric quantum walk, we can separately
introduce well-defined indices for the eigenvalues $\pm 1.$ The bulk-edge
correspondence for Suzuki's split-step quantum walk is twofold. Firstly, we
show that the multiplicities of the eigenvalues $\pm 1$ coincide with the
absolute values of the associated indices. Note that this can be viewed as the
symmetry protection of bound states, and that the indices we consider are
robust in the sense that these depend only on the asymptotic behaviour of the
parameters of the given model. Secondly, we show that that such bound states
exhibit exponential decay at spatial infinity.


  Strong coupling between a single resonator mode and a single quantum emitter
is key to a plethora of experiments and applications in quantum science and
technology and is commonly described by means of the Jaynes-Cummings model.
Here, we show that the Jaynes-Cummings model only applies when the cavity does
not significantly change the emitter's emission rate into free-space. Most
notably, the predictions made by the Jaynes-Cummings model become increasingly
wrong when approaching the ideal emitter-resonator systems with no free-space
decay channels. We present a Hamiltonian that provides, within the validity
range of the rotating wave approximation, a correct theoretical description
that applies to all regimes. As minimizing the coupling to free-space modes is
paramount for many cavity-based applications, a correct description of strong
light-matter interaction is therefore crucial for developing and optimizing
quantum protocols.


  A simultaneous arithmetic progression (s.a.p.) of length k consists of k
points (x_i, y_\sigma(i)), where x_i and y_i are arithmetic progressions and
\sigma is a permutation. Garcia-Selfa and Tornero asked whether there is a
bound on the length of an s.a.p. on an elliptic curve in Weierstrass form over
Q. We show that 4319 is such a bound for curves over R. This is done by
considering translates of the curve in a grid as a graph. A simple upper bound
is found for the number of crossings and the 'crossing inequality' gives a
lower bound. Together these bound the length of an s.a.p. on the curve. We then
use a similar method to extend the result to arbitrary real algebraic curves.
Instead of considering s.a.p.'s we consider k^2/3 points in a grid. The number
of crossings is bounded by Bezout's Theorem. We then give another proof using a
result of Jarnik bounding the number of grid points on a convex curve. This
result applies as any real algebraic curve can be broken up into convex and
concave parts, the number of which depend on the degree. Lastly, these results
are extended to complex algebraic curves.


  We derive the solution representation for a large class of nonlocal boundary
value problems for linear evolution PDEs with constant coefficients in one
space variable. The prototypical such PDE is the heat equation, for which
problems of this form model physical phenomena in chemistry and for which we
formulate and prove a full result. We also consider the third order case, which
is much less studied and has been shown by the authors to have very different
structural properties in general.
  The nonlocal conditions we consider can be reformulated as \emph{multipoint
conditions}, and then an explicit representation for the solution of the
problem is obtained by an application of the Fokas transform method. The
analysis is carried out under the assumption that the problem being solved is
well posed, i.e.\ that it admits a unique solution. For the second order case,
we also give criteria that guarantee well-posedness.


  We present a protocol based on continuous-variable quantum teleportation and
Gaussian post- selection that can be used to correct errors introduced by a
lossy channel. We first show that the global transformation enacted by the
protocol is equivalent to an effective system composed of a noiseless
amplification (or attenuation), and an effective quantum channel, which can in
theory have no loss and an amount of thermal noise arbitrarily small, hence
tending to an identity channel. An application of our protocol is the
probabilistic purification of quantum non-Gaussian states using only Gaussian
operations.


  As a key indicator of unsafe driving, driving volatility characterizes the
variations in microscopic driving decisions. This study characterizes
volatility in longitudinal and lateral driving decisions and examines the links
between driving volatility in time to collision and crash injury severity. By
using a unique real-world naturalistic driving database from the 2nd Strategic
Highway Research Program (SHRP), a test set of 671 crash events featuring
around 0.2 million temporal samples of real world driving are analyzed. Based
on different driving performance measures, 16 different volatility indices are
created. To explore the relationships between crash-injury severity outcomes
and driving volatility, the volatility indices are then linked with individual
crash events including information on crash severity, drivers' pre crash
maneuvers and behaviors, secondary tasks and durations, and other factors. As
driving volatility prior to crash involvement can have different components, an
indepth analysis is conducted using the aggregate as well as segmented (based
on time to collision) real world driving data. To account for the issues of
observed and unobserved heterogeneity, fixed and random parameter logit models
with heterogeneity in parameter means and variances are estimated. The
empirical results offer important insights regarding how driving volatility in
time to collision relates to crash severity outcomes. Overall, statistically
significant positive correlations are found between the aggregate (as well as
segmented) volatility measures and crash severity outcomes. The findings
suggest that greater driving volatility (both in longitudinal and lateral
direction) in time to collision increases the likelihood of police reportable
or most severe crash events... ...


  We derive analytical formulas for the wake and wave drag of a disturbance
moving arbitrarily at the air-water interface. We show that, provided a
constant velocity is reached in finite time, the unsteady surface displacement
converges to its well-known steady counterpart as given by Havelock's famous
formula. Finally we assess, in a specific situation, to which extent one can
rightfully use Havelock's steady wave drag formula for non-uniform motion
(quasi-static). Such an approach can be used to legitimize or discredit a
number of studies which used steady wave drag formulas in unsteady situations.


  We generalize protective measurement for protective joint measurement of
several observables. The merit of joint protective measurement is the
determination of the eigenstates of an unknown Hamiltonian rather than the
determination of features of an unknown quantum state. As an example, we
precisely determine the two eigenstates of an unknown Hamiltonian by a single
joint protective measurement of the three Pauli matrices on a qubit state.


  This paper describes a CNN where all CNN style 2D convolution operations that
lower to matrix matrix multiplication are fully binary. The network is derived
from a common building block structure that is consistent with a constructive
proof outline showing that binary neural networks are universal function
approximators. 71.24% top 1 accuracy on the 2012 ImageNet validation set was
achieved with a 2 step training procedure and implementation strategies
optimized for binary operands are provided.


  We report the observation of the $B$ meson decay $B^\pm\to J/\psi \eta K^\pm$
and evidence for the decay $B^0\to J/\psi \eta K^0_S$, using {90} million
$BBbar$ events collected at the $\ensuremath{\Upsilon{(4S)}}\xspace$ resonance
with the $BaBar$ detector at the PEP-II $e^+ e^-$ asymmetric-energy storage
ring. We obtain branching fractions of $\cal{B}$$(B^\pm\to J/\psi \eta
K^{\pm}$)=$(10.8\pm 2.3(\rm{stat.})\pm 2.4(\rm{syst.}))\times 10^{-5}$ and
$\cal{B}$$(B^0\to J/\psi\eta K_{\rm{S}}^{0}$)=$(8.4\pm 2.6(\rm{stat.})\pm
2.7(\rm{syst.}))\times 10^{-5}$. We search for the new narrow mass state, the
X(3872), recently reported by the Belle Collaboration, in the decay $B^\pm\to
X(3872)K^\pm, X(3872)\to \jpsi \eta$ and determine an upper limit of
$\cal{B}$$(B^\pm \to X(3872) K^\pm \to \jpsi \eta K^\pm$) $<7.7\times 10^{-6}$
at 90% C.L.


  The existence of three smooth solutions, one negative, one positive, and one
nodal, to a homogeneous Robin problem with $p$-Laplacian and Carath\'eodory
reaction is established. No sub-critical growth condition is taken on. Proofs
exploit variational as well as truncation techniques. The case $p=2$ is
separately examined, obtaining a further nodal solution via Morse's theory.


  We present the results of a multi-wavelength follow up campaign for the
luminous nuclear transient Gaia16aax, which was first identified in January
2016. The transient is spatially consistent with the nucleus of an active
galaxy at z=0.25, hosting a black hole of mass $\rm \sim6\times10^8M_\odot$.
The nucleus brightened by more than 1 magnitude in the Gaia G-band over a
timescale of less than one year, before fading back to its pre-outburst state
over the following three years. The optical spectra of the source show broad
Balmer lines similar to the ones present in a pre-outburst spectrum. During the
outburst, the $\rm H\alpha$ and $\rm H\beta$ emission lines develop a secondary
peak. We also report on the discovery of two transients with similar light
curve evolution and spectra: Gaia16aka and Gaia16ajq. We consider possible
scenarios to explain the observed outbursts. We exclude that the transient
event could be caused by a microlensing event, variable dust absorption or a
tidal encounter between a neutron star and a stellar mass black hole in the
accretion disk. We consider variability in the accretion flow in the inner part
of the disk, or a tidal disruption event of a star $\geq 1 M_{\odot}$ by a
rapidly spinning supermassive black hole as the most plausible scenarios. We
note that the similarity between the light curves of the three Gaia transients
may be a function of the Gaia alerts selection criteria.


  Pnictogens have multiple allotropic forms resulting from their ns2 np3
valence electronic configuration, making them the only elemental materials to
crystallize in layered van der Waals (vdW) and quasi-vdW structures throughout
the group. Light group VA elements are found in the layered orthorhombic A17
phase such as black phosphorus, and can transition to the layered rhombohedral
A7 phase at high pressure. On the other hand, bulk heavier elements are only
stable in the A7 phase. Herein, we demonstrate that these two phases not only
co-exist during the vdW growth of antimony on weakly interacting surfaces, but
also undertake a spontaneous transformation from the A17 phase to the
thermodynamically stable A7 phase. This metastability of the A17 phase is
revealed by real-time studies unraveling its thickness-driven transition to the
A7 phase and the concomitant evolution of its electronic properties. At a
critical thickness of ~4 nm, A17 antimony undergoes a diffusionless shuffle
transition from AB to AA stacked alpha-antimonene followed by a gradual
relaxation to the A7 bulk-like phase. Furthermore, the electronic structure of
this intermediate phase is found to be determined by surface self-passivation
and the associated competition between A7- and A17-like bonding in the bulk.
These results highlight the critical role of the atomic structure and
interfacial interactions in shaping the stability and electronic
characteristics of vdW layered materials, thus enabling a new degree of freedom
to engineer their properties using scalable processes.


  The production of prompt $D^+_{s}$ and $D^+$ mesons is measured by the LHCb
experiment in proton-lead ($p\mathrm{Pb}$) collisions in both the forward
($1.5<y^*<4.0$) and backward ($-5.0<y^*<-2.5$) rapidity regions at a
nucleon-nucleon center-of-mass energy of $\sqrt {s_{\mathrm{NN}}}=8.16\,$TeV.
The nuclear modification factors of both $D^+_{s}$ and $D^+$ mesons are
determined as a function of transverse momentum, $p_{\mathrm{T}}$, and
rapidity. In addition, the $D^+_{s}$ to $D^+$ cross-section ratio is measured
as a function of the charged particle multiplicity in the event. An enhanced
$D^+_{s}$ to $D^+$ production in high-multiplicity events is observed for the
whole measured $p_{\mathrm{T}}$ range, in particular at low $p_{\mathrm{T}}$
and backward rapidity, where the significance exceeds six standard deviations.
This constitutes the first observation of strangeness enhancement in charm
quark hadronization in high-multiplicity $p\mathrm{Pb}$ collisions. The results
are also qualitatively consistent with the presence of quark coalescence as an
additional charm quark hadronization mechanism in high-multiplicity proton-lead
collisions.


  A family of quantum fields is said to be strongly local if it generates a
local net of von Neumann algebras. There are few methods of showing directly
strong locality of a quantum field. Among them, linear energy bounds are the
most widely used, yet a chiral conformal field of conformal weight $d>2$ cannot
admit linear energy bounds. In this paper we give a new direct method to prove
strong locality in two-dimensional conformal field theory. We prove that if a
chiral conformal field satisfies an energy bound of degree $d-1$, then it also
satisfies a certain local version of the energy bound, and this in turn implies
strong locality. A central role in our proof is played by diffeomorphism
symmetry. As a concrete application, we show that the vertex operator algebra
given by a unitary vacuum representation of the $\mathcal{W}_3$-algebra is
strongly local. For central charge $c > 2$, this yields a new conformal net. We
further prove that these nets do not satisfy strong additivity, and hence are
not completely rational.


  We show that a hybrid inflation model with multiple waterfall fields can
result in the formation of primordial black hole (PBH) with an astrophysical
size, by using an advanced algorithm to follow the stochastic dynamics of the
waterfall fields. This is in contrast to the case with a single waterfall
field, where the wavelength of density perturbations is usually too short to
form PBHs of the astrophysical scale (or otherwise PBH are overproduced and the
model is ruled out) unless the inflaton potential is tuned. In particular, we
demonstrate that PBHs with masses of order $10^{20}\, {\rm g}$ can form after
hybrid inflation consistently with other cosmological observations if the
number of waterfall fields is about 5 for the case of instantaneous reheating.
Observable gravitational waves are produced from the second-order effect of
large curvature perturbations as well as from the dynamics of texture or global
defects that form after the waterfall phase transition.


  The well-known theorem of Shalom--Vaserstein and Ershov--Jaikin-Zapirain
states that the group $\mathrm{EL}_n(\mathcal{R})$, generated by elementary
matrices over a finitely generated commutative ring $\mathcal{R}$, has
Kazhdan's property (T) as soon as $n\geq3$. This is no longer true if the ring
$\mathcal{R}$ is replaced by a commutative rng (a ring but without the
identity) due to nilpotent quotients
$\mathrm{EL}_n(\mathcal{R}/\mathcal{R}^k)$. In this paper, we prove that even
in such a case the group $\mathrm{EL}_n(\mathcal{R})$ satisfies a certain
property that can substitute property (T), provided that $n$ is large enough.


  Negative longitudinal magnetoresistance (NLMR) has been reported in a variety
of materials and has attracted extensive attention as an electrotransport
hallmark of topological Weyl semimetals. However, its origin is still under
debate. Here, we demonstrate that the NLMR in a two dimensional electron gas
can be influenced by the measurement current. While the NLMR persists up to 130
K, its magnitude and magnetic field response become dependent on the applied
current below 60 K. The tunable NLMR at low and high currents can be best
attributed to quantum interference and disorder scattering effects,
respectively. This work uncovers non-Ohmic NLMR in a non-Weyl material and
highlights potential effects of the measurement current in elucidating
electrotransport phenomena. We also demonstrate that NLMRs can be a valuable
phenomenon in revealing the origins of other properties, such as negative MRs
in perpendicular magnetic fields.


  It has been shown in (Gaidashev et al, 2010) and (Gaidashev et al, 2011) that
infinitely renormalizable area-preserving maps admit invariant Cantor sets with
a maximal Lyapunov exponent equal to zero. Furthermore, the dynamics on these
Cantor sets for any two infinitely renormalizable maps is conjugated by a
transformation that extends to a differentiable function whose derivative is
Holder continuous of exponent alpha>0.
  In this paper we investigate numerically the specific value of alpha. We also
present numerical evidence that the normalized derivative cocycle with the base
dynamics in the Cantor set is ergodic. Finally, we compute renormalization
eigenvalues to a high accuracy to support a conjecture that the renormalization
spectrum is real.


  This paper presents an emotion-regularized conditional variational
autoencoder (Emo-CVAE) model for generating emotional conversation responses.
In conventional CVAE-based emotional response generation, emotion labels are
simply used as additional conditions in prior, posterior and decoder networks.
Considering that emotion styles are naturally entangled with semantic contents
in the language space, the Emo-CVAE model utilizes emotion labels to regularize
the CVAE latent space by introducing an extra emotion prediction network. In
the training stage, the estimated latent variables are required to predict the
emotion labels and token sequences of the input responses simultaneously.
Experimental results show that our Emo-CVAE model can learn a more informative
and structured latent space than a conventional CVAE model and output responses
with better content and emotion performance than baseline CVAE and
sequence-to-sequence (Seq2Seq) models.


  Using the powerful language of geometric algebra, we present an
observationally symmetric derivation of the strong correlations predicted by
the entangled singlet state in a deterministic and locally causal model,
usually also referred to as a local-realistic model, in which the physical
space is assumed to be a quaternionic 3-sphere, or $S^3$, available as the
spatial part of a solution of Einstein's field equations of general relativity,
and compare it in quantitative detail with Bell's local-realistic model for the
singlet correlations set within a flat Euclidean space ${\mathrm{I\!R}^3}$.
Since the quantitatively detailed expressions of relative-angle-dependent
probabilities of observing measurement outcomes for Bell's local model do not
seem to have been fully articulated before, our novel analysis exploiting the
non-commutative properties of quaternions, in addition to allowing the
comparison with the quaternionic 3-sphere model, may also provide useful
comparisons for other less compelling local-realistic models, such as those
relying on retrocausality or superdeterminism. Apart from the conservation of
zero spin angular momentum, the key attribute underlying the strong singlet
correlations within $S^3$ in comparison with Bell's local model turns out to be
the spinorial sign changes intrinsic to quaternions that constitute the
3-sphere. In addition, we also discuss anew a macroscopic experiment that can,
in principle, test our 3-sphere hypothesis.


  We propose local symplectic surgery, a two-timescale procedure for finding
local Nash equilibria in two-player zero-sum games. We first show that previous
gradient-based algorithms cannot guarantee convergence to local Nash equilibria
due to the existence of non-Nash stationary points. By taking advantage of the
differential structure of the game, we construct an algorithm for which the
local Nash equilibria are the only attracting fixed points. We also show that
the algorithm exhibits no oscillatory behaviors in neighborhoods of equilibria
and show that it has the same per-iteration complexity as other recently
proposed algorithms. We conclude by validating the algorithm on two numerical
examples: a toy example with multiple Nash equilibria and a non-Nash
equilibrium, and the training of a small generative adversarial network (GAN).


  We extend various recent results regarding the derivation of effective
cosmological Friedmann equations from the dynamics of group field theory (GFT).
Restricting ourselves to a single GFT field mode (or fixed values of Peter-Weyl
representation labels), we first consider dynamics given by a quadratic
Hamiltonian, which takes the form of a squeezing operator, and then add a
quartic interaction that can be seen as a toy model for interactions in full
GFT. Our derivation of effective Friedmann equations does not require a
mean-field approximation; we mostly follow a general approach in which these
equations in fact hold for any state. The resulting cosmological equations
exhibit corrections to classical Friedmann dynamics similar to those of loop
quantum cosmology, leading to generic singularity resolution, but also involve
further state-dependent terms. We then specify these equations to various types
of coherent states, such as Fock coherent states or Perelomov-Gilmore states
based on the su(1,1) structure of harmonic quantum cosmology. We compute
relative uncertainties of volume and energy in these states, clarifying whether
they can be interpreted as semiclassical. In the interacting case, both
analytical and numerical approximations are used to obtain modified
cosmological dynamics. Our results clarify how effective cosmological equations
derived from GFT can provide reliable approximations to the full dynamics.


  Effects of possible orbital order in magnetic properties of two-dimensional
spin gap system for CaV$_4$O$_9$ are investigated theoretically. After
analyzing experimental data, we show that single orbital models assumed in the
literature are insufficient to reproduce the data. To understand the origin of
the discrepancy, we assume that in $d^1$ state of V, $d_{xz}$ and $d_{yz}$
orbitals have substantial contributions in the lowest-energy atomic level which
leads to a double-degeneracy. We study possible configurations of the orbital
order. By exact diagonalization and perturbation expansion, we calculate the
susceptibility, wavenumber dependence of low-lying excitations and equal-time
spin-spin correlations which is related to integrated intensity of the neutron
inelastic scattering. These quantities sensitively depend on the configuration
of the orbital order. The calculated results for some configurations of the
orbital order reproduce many experimental results much better than the previous
single-orbital models. However some discrepancy still remains to completely
reproduce all of the reported experimental results. To understand the origin of
these discrepancies, we point out the possible importance of the partially
occupied $d_{xy}$ orbital in addition to orbital order of partially filled
$d_{xz}$ and $d_{yz}$ orbitals.


  We determine an absolute calibration of stellar mass-to-light ratios for the
densest \simeq 3% of early-type galaxies in the local universe (redshift
z\simeq 0.08) from SDSS DR7. This sample of \sim 4000 galaxies has, assuming a
Chabrier IMF, effective stellar surface densities, Sigma_e > 2500 M_sun/pc^2,
stellar population synthesis (SPS) stellar masses log_10(M_sps/M_sun)<10.8, and
aperture velocity dispersions of sigma_ap=168^{+37}_{-34} km/s (68% range). In
contrast to typical early-type galaxies, we show that these dense early-type
galaxies follow the virial fundamental plane, which suggests that
mass-follows-light. With the additional assumption that any dark matter does
not follow the light, the dynamical masses of dense galaxies provide a direct
measurement of stellar masses. Our dynamical masses (M_dyn), obtained from the
spherical Jeans equations, are only weakly sensitive to the choice of
anisotropy (\beta) due to the relatively large aperture of the SDSS fiber for
these galaxies: R_ap \simeq 1.5 R_e. Assuming isotropic orbits (\beta=0) we
find a median log_{10} (M_dyn/M_sps) = 0.233 \pm 0.003, consistent with a
Salpeter IMF, while more bottom heavy IMFs and standard Milky-Way IMFs are
strongly disfavored. Our results are consistent with, but do not require, a
dependence of the IMF on dynamical mass or velocity dispersion. We find
evidence for a color dependence to the IMF such that redder galaxies have
heavier IMFs with M_dyn/M_sps \propto (g-r)^{1.13\pm0.09}. This may reflect a
more fundamental dependence of the IMF on the age or metallicity of a stellar
population, or the density at which the stars formed.


  Here we consider scale invariant dynamical systems within a classical
particle description of Lagrangian mechanics. We begin by showing the condition
under which a spatial and temporal scale transformation of such a system can
lead to a symmetry by leaving the action unchanged. We then derive the form of
all analytic Lagrangians that possess such a symmetry under change of scale.
Finally, we write down the Noether charges of all analytic Lagrangians that are
associated with a scale invariant action.


  Electron resonant scattering by high-frequency electromagnetic whistler-mode
waves has been proposed as a mechanism for solar wind electron scattering and
pre-acceleration to energies that enable them to participate in shock drift
acceleration around the Earth's bow shock. However, observed whistler-mode
waves are often sufficiently intense to resonate with electrons nonlinearly,
which prohibits the application of quasi-linear diffusion theory. This is the
second of two accompanying papers devoted to developing a new theoretical
approach for quantifying the electron distribution evolution subject to
multiple resonant interactions with intense whistler-mode wave-packets. In the
first paper, we described a probabilistic approach, applicable to systems with
short wave-packets. For such systems, nonlinear resonant effects can be treated
by diffusion theory, but with diffusion rates different from those of
quasi-linear diffusion. In this paper we generalize this approach by merging it
with a mapping technique. This technique can be used to model the electron
distribution evolution in the presence of significantly non-diffusive resonant
scattering by intense long wave-packets. We verify our technique by comparing
its predictions with results from a numerical integration approach.


  In this paper, we firstly consider view-dependent effects into single
image-based novel view synthesis (NVS) problems. For this, we propose to
exploit the camera motion priors in NVS to model view-dependent appearance or
effects (VDE) as the negative disparity in the scene. By recognizing
specularities "follow" the camera motion, we infuse VDEs into the input images
by aggregating input pixel colors along the negative depth region of the
epipolar lines. Also, we propose a `relaxed volumetric rendering' approximation
that allows computing the densities in a single pass, improving efficiency for
NVS from single images. Our method can learn single-image NVS from image
sequences only, which is a completely self-supervised learning method, for the
first time requiring neither depth nor camera pose annotations. We present
extensive experiment results and show that our proposed method can learn NVS
with VDEs, outperforming the SOTA single-view NVS methods on the RealEstate10k
and MannequinChallenge datasets.


  We derive a class of equations of state for a multi-phase thermodynamic
system associated with a finite set of order parameters that satisfy an
integrable system of hydrodynamic type. As particular examples, we discuss
one-phase systems such as the van der Waals gas and the effective molecular
field model. The case of N-phase systems is also discussed in detail in
connection with entropies depending on the order parameter according to
Tsallis' composition rule.


  The goal of session-based recommendation (SR) models is to utilize the
information from past actions (e.g. item/product clicks) in a session to
recommend items that a user is likely to click next. Recently it has been shown
that the sequence of item interactions in a session can be modeled as
graph-structured data to better account for complex item transitions. Graph
neural networks (GNNs) can learn useful representations for such
session-graphs, and have been shown to improve over sequential models such as
recurrent neural networks [14]. However, we note that these GNN-based
recommendation models suffer from popularity bias: the models are biased
towards recommending popular items, and fail to recommend relevant long-tail
items (less popular or less frequent items). Therefore, these models perform
poorly for the less popular new items arriving daily in a practical online
setting. We demonstrate that this issue is, in part, related to the magnitude
or norm of the learned item and session-graph representations (embedding
vectors). We propose a training procedure that mitigates this issue by using
normalized representations. The models using normalized item and session-graph
representations perform significantly better: i. for the less popular long-tail
items in the offline setting, and ii. for the less popular newly introduced
items in the online setting. Furthermore, our approach significantly improves
upon existing state-of-the-art on three benchmark datasets.


  It is shown that finite groups in which the order of the product of every
pair of elements of co-prime order is the product of the orders, is nilpotent.


  In this paper, we show that the $L^2$-optimal condition implies the
$L^2$-divisibility of $L^2$-integrable holomorphic functions. As an
application, we offer a new characterization of bounded $L^2$-domains of
holomorphy with null thin complements using the $L^2$-optimal condition, which
appears to be advantageous in addressing a problem proposed by Deng-Ning-Wang.
Through this characterization, we show that a domain in a Stein manifold with a
null thin complement, admitting an exhaustion of complete K\"ahler domains,
remains Stein. By the way, we construct an $L^2$-optimal domain that does not
admit any complete K\"ahler metric.


  The extension of ab initio quantum many-body theory to higher accuracy and
larger systems is intrinsically limited by the handling of large data objects
in form of wave-function expansions and/or many-body operators. In this work we
present matrix factorization techniques as a systematically improvable and
robust tool to significantly reduce the computational cost in many-body
applications at the price of introducing a moderate decomposition error. We
demonstrate the power of this approach for the nuclear two-body systems, for
many-body perturbation theory calculations of symmetric nuclear matter, and for
non-perturbative in-medium similarity renormalization group simulations of
finite nuclei. Establishing low-rank expansions of chiral nuclear interactions
offers possibilities to reformulate many-body methods in ways that take
advantage of tensor factorization strategies.


  We discuss the determination of the parameters of the pp and ppbar amplitudes
for the description of scattering in the Coulomb interference region. We put
enphasis on the possibility that the effective slope observed in the
differential cross section is formed by different exponential slopes in the
real and imaginary amplitudes (called B_R and B_I). For this purpose we develop
a more general treatment of the Coulomb phase. We analyse the differential
cross section data in the range from 19 to 1800 GeV with four parameters (sigma
, rho, B_I, B_R), and observe that we cannot obtain from the data a unique
determination of the parameters. We investigate correlations in pairs of the
four quantities, showing ranges leading to the smaller chi2 values. In the
specific case of p-pbar scattering at 541 GeV, we investigate the measurements
of event rate dN/dt at low |t| in terms of the Coulomb interference with
exponentially decreasing nuclear amplitudes. The analysis allows a
determination of the normalization factor connecting the event rate with the
absolute cross section.


  In these notes, using the method of differential constraints, novel exact
kink-like solutions are obtained for certain classes of complex
Ginzburg--Landau equations with cubic-quintic nonlinearity. The foregoing
solutions are presented in terms of the Lambert W function.


  Starting with a manifold $M$ and a semi-free action of $S^3$ on it, we have
the Smith-Gysin sequence: $$ \cdots \to H^{*}( M) \to
  H^{*-3}(M/S^3, M^{S^3}) \oplus H^{*} (M^{S^3}) \to H^{*+1}(M/S^3, M^{S^3})
\to
  H^{*+1}(M) \to \cdots $$ In this paper, we construct a Smith-Gysin sequence
that does not require the semi-free condition. This sequence includes a new
term, referred to as the "exotic term," which depends on the subset $M^{S^1}$:
$$ \cdots \to H^{*}(M) \to H^{*-3} (M/S^3, \Sigma/S^3) \oplus H^{*}(M^{S^3})
\oplus \left( H^{*-2}(M^{S^1})\right)^{-\mathbb{Z}_2} \to
H^{*+1}(M/S^3,M^{S^3}) \to H^{*+1}(M) \to \cdots $$
  Here, $\Sigma \subset M$ is the subset of points in $M$ whose isotropy groups
are infinite. The group $\mathbb{Z}_2$ acts on $M^{S^1}$ by $j \in S^3$.


  We generate inverse Compton scattered X-rays in both linear and nonlinear
regimes with a 250 MeV laser wakefield electron accelerator and plasma mirror
by retro-reflecting the unused drive laser light to scatter from the
accelerated electrons. We characterize the X-rays using a CsI(Tl) voxelated
scintillator that measures their total energy and divergence as a function of
plasma mirror distance from the accelerator exit. At each plasma mirror
position, these X-ray properties are correlated with the measured fluence and
inferred intensity of the laser pulse after driving the accelerator to
determine the laser strength parameter $a_0$. The results show that ICS X-rays
are generated at $a_0$ ranging from $0.3\pm0.1$ to $1.65\pm0.25$, and exceed
the strength of co-propagating bremsstrahlung and betatron X-rays at least
ten-fold throughout this range of $a_0$.


  Visual Question Answering (VQA) is the task of answering questions about an
image. Some VQA models often exploit unimodal biases to provide the correct
answer without using the image information. As a result, they suffer from a
huge drop in performance when evaluated on data outside their training set
distribution. This critical issue makes them unsuitable for real-world
settings.
  We propose RUBi, a new learning strategy to reduce biases in any VQA model.
It reduces the importance of the most biased examples, i.e. examples that can
be correctly classified without looking at the image. It implicitly forces the
VQA model to use the two input modalities instead of relying on statistical
regularities between the question and the answer. We leverage a question-only
model that captures the language biases by identifying when these unwanted
regularities are used. It prevents the base VQA model from learning them by
influencing its predictions. This leads to dynamically adjusting the loss in
order to compensate for biases. We validate our contributions by surpassing the
current state-of-the-art results on VQA-CP v2. This dataset is specifically
designed to assess the robustness of VQA models when exposed to different
question biases at test time than what was seen during training.
  Our code is available: github.com/cdancette/rubi.bootstrap.pytorch


  We give an efficient algorithm for learning a binary function in a given
class C of bounded VC dimension, with training data distributed according to P
and test data according to Q, where P and Q may be arbitrary distributions over
X. This is the generic form of what is called covariate shift, which is
impossible in general as arbitrary P and Q may not even overlap. However,
recently guarantees were given in a model called PQ-learning (Goldwasser et
al., 2020) where the learner has: (a) access to unlabeled test examples from Q
(in addition to labeled samples from P, i.e., semi-supervised learning); and
(b) the option to reject any example and abstain from classifying it (i.e.,
selective classification). The algorithm of Goldwasser et al. (2020) requires
an (agnostic) noise tolerant learner for C. The present work gives a
polynomial-time PQ-learning algorithm that uses an oracle to a "reliable"
learner for C, where reliable learning (Kalai et al., 2012) is a model of
learning with one-sided noise. Furthermore, our reduction is optimal in the
sense that we show the equivalence of reliable and PQ learning.


  We examine ADHM multi-instantons in the conformal N=2 supersymmetric Sp(N)
gauge theory with one anti-symmetric tensor and four fundamental
hypermultiplets. We argue that the ADHM construction and measure can also be
deduced from purely field theoretic considerations and also from the dynamics
of D-instantons in the presence of D3-branes, D7-branes and an orientifold
O7-plane. The measure then admits a large-N saddle-point approximation where
the D3-branes disappear but the background is changed to AdS_5 x S^5/Z_2, as
expected on the basis of the AdS/CFT correspondence. The large-N measure
displays the fractionation of D-instantons at the singularity S^3 in S^5/Z_2
and is described for instanton number k by a certain O(k) matrix model.


  Urea at sufficiently high concentration unfolds the secondary structure of
proteins leading to denaturation. In contrast, Choline Chloride (ChCl) and
urea, in 1:2 molar ratio form a deep eutectic mixture, a liquid at room
temperature and protect proteins from denaturation. In order to get a
microscopic picture of this phenomenon, we perform extensive all-atom molecular
dynamics simulations on a model protein HP-36. Based on our calculation of
Kirkwood-Buff integrals, we analyze the relative accumulation of these
osmolytes around the protein. Additional insights are drawn from the analyses
of the translational and rotational dynamics of solvent molecules and also from
the hydrogen bond auto-correlation functions. In the presence of urea, water
shows slow subdiffusive dynamics around the protein backbone as a consequence
of stronger interaction of water molecules with the backbone atoms. Urea also
shows subdiffusive motion. Addition of choline further slows down the dynamics
of urea restricting its inclusion around the protein backbone. Adding to this,
choline molecules in the first solvation shell of the protein shows the
strongest subdiffusive behavior. In other words, ChCl behaves as a nano-crowder
by excluding urea from the protein backbone and thereby slowing down the
dynamics of the water layer around the protein. This prevents the protein from
denaturation and makes it structurally rigid which in turn is supported by the
smaller radius of gyration and root mean square deviation values of HP-36 when
ChCl is present in the system.


  Casimir effect is the attractive force which acts between two plane parallel,
closely spaced, uncharged, metallic plates in vacuum. This phenomenon was
predicted theoretically in 1948 and reliably investigated experimentally only
in recent years. In fact, the Casimir force is similar to the familiar van der
Waals force in the case of relatively large separations when the relativistic
effects come into play. We review the most important experiments on measuring
the Casimir force by means of torsion pendulum, atomic force microscope and
micromechanical torsional oscillator. Special attention is paid to the puzzle
of the thermal Casimir force, i.e., to the apparent violation of the third law
of thermodynamics when the Lifshitz theory of dispersion forces is applied to
real metals. Thereafter we discuss the role of the Casimir force in nanosystems
including the stiction phenomenon, actuators, and interaction of hydrogen atoms
with carbon nanotubes. The applications of the Casimir effect for constraining
predictions of extra-dimensional unification schemes and other physics beyond
the standard model are also considered.


  We consider the first-passage problem for $N$ identical independent particles
that are initially released uniformly in a finite domain $\Omega$ and then
diffuse toward a reactive area $\Gamma$, which can be part of the outer
boundary of $\Omega$ or a reaction centre in the interior of $\Omega$. For both
cases of perfect and partial reactions, we obtain the explicit formulas for the
first two moments of the fastest first-passage time (fFPT), i.e., the time when
the first out of the $N$ particles reacts with $\Gamma$. Moreover, we
investigate the full probability density of the fFPT. We discuss a significant
role of the initial condition in the scaling of the average fastest
first-passage time with the particle number $N$, namely, a much stronger
dependence ($1/N$ and $1/N^2$ for partially and perfectly reactive targets,
respectively), in contrast to the well known inverse-logarithmic behaviour
found when all particles are released from the same fixed point. We combine
analytic solutions with scaling arguments and stochastic simulations to
rationalise our results, which open new perspectives for studying the relevance
of multiple searchers in various situations of molecular reactions, in
particular, in living cells.


  The role of torsion and a scalar field $\phi$ in gravitation, especially, in
the presence of a Dirac field in the background of a particular class of the
Riemann-Cartan geometry is considered here. Recently, a Lagrangian density with
Lagrange multipliers has been proposed by the author which has been obtained by
picking some particular terms from the SO(4,1) Pontryagin density, where the
scalar field $\phi$ causes the de Sitter connection to have the proper
dimension of a gauge field. In this article the scalar field has been linked to
the dimension of the Dirac field. Here we get the field equations for the Dirac
field and the scalar field in such a way that both of them appear to be
mutually non-interacting. In this scenario the scalar field appears to be a
natural candidate for the dark matter and the dark radiation.


  We observe critical phenomena in spherical collapse of radiation fluid. A
sequence of spacetimes $\cal{S}[\eta]$ is numerically computed, containing
models ($\eta\ll 1$) that adiabatically disperse and models ($\eta\gg 1$) that
form a black hole. Near the critical point ($\eta_c$), evolutions develop a
self-similar region within which collapse is balanced by a strong,
inward-moving rarefaction wave that holds $m(r)/r$ constant as a function of a
self-similar coordinate $\xi$. The self-similar solution is known and we show
near-critical evolutions asymptotically approaching it. A critical exponent
$\beta \simeq 0.36$ is found for supercritical ($\eta>\eta_c$) models.


  Measurements are presented of $K^0$ meson and $\Lambda$ baryon production in
deep-inelastic positron-proton scattering (DIS) in the kinematic range $10 <
Q^2 < 70 $GeV$^2$ and $10^{-4} < x < 10^{-2}$. The measurements, obtained using
the H1 detector at the HERA collider, are discussed in the light of possible
mechanisms for increased strangeness production at low Bjorken-$x$. Comparisons
of the $x_F$ spectra, where $x_F$ is the fractional longitudinal momentum in
the hadronic centre-of-mass frame, with results from electron-positron
annihilation are made. The $x_F$ spectra and the $K^0$ ``seagull'' plot are
compared with previous DIS results. The mean $K^0$ and $\Lambda$ multiplicities
are studied as a function of the centre-of-mass energy $W$ and are observed to
be consistent with a logarithmic increase with $W$ when compared with previous
measurements. A comparison of the levels of strangeness production in
diffractive and non-diffractive DIS is made. An upper limit of $0.9 $nb, at the
95% confidence level, is placed on the cross-section for QCD instanton induced
events.


  We explore a web of connections between quantum entanglement and knot theory
by examining how topological entanglement entropy probes the braiding data of
quasi-particles in Chern-Simons theory, mainly using $SU(2)$ gauge group as our
working example. The problem of determining the Renyi entropy is mapped to
computing the expectation value of an auxiliary Wilson loop in $S^3$ for each
braid. We study various properties of this auxiliary Wilson loop for some
2-strand and 3-strand braids, and demonstrate how they reflect some geometrical
properties of the underlying braids.


  The same but different: That might describe two metrics. On the surface
CLASSI may show two metrics are locally equivalent, but buried beneath one may
be a wealth of further structure. This was beautifully described in a paper by
M.A.H. MacCallum in 1998. Here I will illustrate the effect with two flat
metrics -- one describing ordinary Minkowski spacetime and the other describing
a three-parameter family of Gal'tsov-Letelier-Tod spacetimes. I will dig out
the beautiful hidden classical singularity structure of the latter (a structure
first noticed by Tod in 1994) and then show how quantum considerations can
illuminate the riches. I will then discuss how quantum structure can help us
understand classical singularities and metric parameters in a variety of exact
solutions mined from the Exact Solutions book.


  Effects of dynamical activity spillover in a noisy binary choice game (Ising
game) on a complete graph are studied. Binary choice games are very important
for both economics and statistical physics playing a role of the bridge between
these two fields. In this paper we investigate the effects of self-excited
activity induced by activity spillover on relaxation to equilibria and
transitions between metastable equilibria at finite times. Using the formalism
of master equations we show that both relaxation and interequilibria
transitions at finite time are accelerated by the effects of activity
spillover.


  We show that the phase sensitivity $\Delta \theta$ of a Mach-Zehnder
interferometer fed by a coherent state in one input port and squeezed-vacuum in
the other one is i) independent from the true value of the phase shift and ii)
can reach the Heisenberg limit $\Delta \theta \sim 1/N_T$, where $N_T$ is the
average number of particles of the input states. We also show that the
Cramer-Rao lower bound, $\Delta \theta \propto 1/ \sqrt{|\alpha|^2 e^{2r} +
\sinh^2r}$, can be saturated for arbitrary values of the squeezing parameter
$r$ and the amplitude of the coherent mode $|\alpha|$ by a Bayesian phase
inference protocol.


  Linux container technologies such as Docker and Singularity offer
encapsulated environments for easy execution of software. In high performance
computing, this is especially important for evolving and complex software
stacks with conflicting dependencies that must co-exist. Singularity Registry
HPC ("shpc") was created as an effort to install containers in this environment
as modules, seamlessly allowing for typically hidden executables inside
containers to be presented to the user as commands, and as such significantly
simplifying the user experience. A remaining challenge, however, is deriving
the list of important executables in the container. In this work, we present
new automation and methods that allow for not only discovering new containers
in large community sets, but also deriving container entries with important
executables. With this work we have added over 8,000 containers from the
BioContainers community that can be maintained and updated by the software
automation over time. All software is publicly available on the GitHub
platform, and can be beneficial to container registries and infrastructure
providers for automatically generating container modules to lower the usage
entry barrier and improve user experience.


  The \textit{square} of a graph $G$, denoted by $G^2$, is obtained from $G$ by
adding an edge to connect every pair of vertices with a common neighbor in $G$.
In this paper we prove that for every planar graph $G$ with maximum degree at
most $5$, $G^2$ admits a proper vertex coloring using at most $17$ colors,
which improves the upper bound $18$ recently obtained by Hou, Jin, Miao, and
Zhao.


  A neutron star in binary orbit with a low-mass non-degenerate companion
becomes a source of x-rays with millisecond variability when mass accretion
spins it up. Centrifugally driven changes in density profile may initiate a
phase transition in a growing region of the core parallel to what may take
place in an isolated millisecond pulsar, but in reverse. Such a star will spend
a longer time in the spin frequency range over which the transition occurs than
elsewhere because the change of phase, paced by the spinup rate, is accompanied
by a growth in the moment of inertia. The population of accreters will exhibit
a clustering in the critical frequency range. A phase change triggered by
changing spin and the accompanying adjustment of moment of inertia has its
analogue in rotating nuclei.


  Traditional cryptography-based security mechanisms such as authentication and
authorization are not effective against insider attacks like wormhole,
sinkhole, selective forwarding attacks, etc., Trust based approaches have been
widely used to counter insider attacks in wireless sensor networks. It provides
a quantitative way to evaluate the trustworthiness of sensor nodes. An
untrustworthy node can wreak considerable damage and adversely affect the
quality and reliability of data. Therefore, analysing the trust level of a node
is important. In this paper we focused about indirect trust mechanism, in which
each node monitors the forwarding behavior of its neighbors in order to detect
any node that behaves selfishly and does not forward the packets it receives.
For this, we used a link state routing protocol based indirect trusts which
forms the shortest route and finds the best trustworthy route among them by
comparing the values of all the calculated route trusts as for each route
present in the network. And finally, we compare our work with similar routing
protocols and show its advantages over them.


  We study the surface magnetization of aperiodic Ising quantum chains. Using
fermion techniques, exact results are obtained in the critical region for
quasiperiodic sequences generated through an irrational number as well as for
the automatic binary Thue-Morse sequence and its generalizations modulo p. The
surface magnetization exponent keeps its Ising value, beta_s=1/2, for all the
sequences studied. The critical amplitude of the surface magnetization depends
on the strength of the modulation and also on the starting point of the chain
along the aperiodic sequence.


  Let $f$ be a modular form which is non-ordinary at $p$. Kim and Loeffler have
recently constructed two-variable $p$-adic $L$-functions associated to $f$. In
the case where $a_p=0$, they showed that, as in the one-variable case,
Pollack's plus and minus splitting applies to these new objects. In this short
note, we show that such a splitting can be generalised to the case where
$a_p\ne0$ using Sprung's logarithmic matrix.


  Programs with high levels of complexity often face challenges in adjusting
execution parameters, particularly when these parameters vary based on the
execution context. These dynamic parameters significantly impact the program's
performance, such as loop granularity, which can vary depending on factors like
the execution environment, program input, or the choice of compiler. Given the
expensive nature of testing each case individually, one viable solution is to
automate parameter adjustments using optimization methods. This article
introduces PATSMA, a parameter auto-tuning tool that leverages Coupled
Simulated Annealing (CSA) and Nelder-Mead (NM) optimization methods to
fine-tune existing parameters in an application. We demonstrate how auto-tuning
can contribute to the real-time optimization of parallel algorithms designed
for shared memory systems. PATSMA is a C++ library readily available under the
MIT license.


  We present a calculation of defect--defect correlation functions in the
defect turbulence regime of the complex Ginzburg--Landau equation. Our results
do not agree with the predictions of generic scale invariance. Using the
topological nature of the defects, we prove that defect--defect correlations
cannot decay as slowly as predicted by generic scale invariance


  The fundamental metallicity relation (FMR) states that galaxies of the same
stellar mass but larger star formation rate (SFR) tend to have smaller
gas-phase metallicity (<Zg>). It is thought to be fundamental because it
naturally arises from the stochastic feeding of star-formation from external
metal-poor gas accretion, a process extremely elusive to observe but essential
according the cosmological simulations of galaxy formation. In this letter, we
show how the FMR emerges from the local anti-correlation between SFR surface
density and Zg recently observed to exist in disk galaxies. We analytically
derive the global FMR from the local law, and then show that both relations
agree quantitatively when considering the star-forming galaxies of the MaNGA
survey. Thus, understanding the FMR becomes equivalent to understanding the
origin of the anti-correlation between SFR and metallicity followed by the set
of star-forming regions of any typical galaxy. The correspondence between local
and global laws is not specific of the FMR, so that a number of local relations
should exist associated with known global relations.


  This paper presents the OmniRace approach to controlling a racing drone with
6-degree of freedom (DoF) hand pose estimation and gesture recognition. To our
knowledge, it is the first-ever technology that allows for low-level control of
high-speed drones using gestures. OmniRace employs a gesture interface based on
computer vision and a deep neural network to estimate a 6-DoF hand pose. The
advanced machine learning algorithm robustly interprets human gestures,
allowing users to control drone motion intuitively. Real-time control of a
racing drone demonstrates the effectiveness of the system, validating its
potential to revolutionize drone racing and other applications. Experimental
results conducted in the Gazebo simulation environment revealed that OmniRace
allows the users to complite the UAV race track significantly (by 25.1%) faster
and to decrease the length of the test drone path (from 102.9 to 83.7 m). Users
preferred the gesture interface for attractiveness (1.57 UEQ score), hedonic
quality (1.56 UEQ score), and lower perceived temporal demand (32.0 score in
NASA-TLX), while noting the high efficiency (0.75 UEQ score) and low physical
demand (19.0 score in NASA-TLX) of the baseline remote controller. The deep
neural network attains an average accuracy of 99.75% when applied to both
normalized datasets and raw datasets. OmniRace can potentially change the way
humans interact with and navigate racing drones in dynamic and complex
environments. The source code is available at
https://github.com/SerValera/OmniRace.git.


  This paper introduces a class of rings called left nil zero semicommutative
rings ( LNZS rings ), wherein a ring R is said to be LNZS if the left
annihilator of every nilpotent element of R is an ideal of R. It is observed
that reduced rings are LNZS but not the other way around. So, this paper
provides some conditions for an LNZS ring to be reduced, and among other
results, it is proved that R is reduced if and only if the ring of upper
triangular matrices of order 2x2 over R is LNZS. Furthermore, it is shown
through examples that neither the polynomial ring nor the skew polynomial ring
over an LNZS is LNZS. Therefore, this paper investigates the LNZS property of
the polynomial extension and skew polynomial extension of an LNZS ring with
some additional conditions.


  We consider the uplink of a multicell multiuser multiple-input
multiple-output system where the channel experiences both small and large-scale
fading. The data detection is done by using the linear zero-forcing technique,
assuming the base station (BS) has perfect channel state information. We derive
new, exact closed-form expressions for the uplink rate, symbol error rate, and
outage probability per user, as well as a lower bound on the achievable rate.
This bound is very tight and becomes exact in the large-number-of-antennas
limit. We further study the asymptotic system performance in the regimes of
high signal-to-noise ratio (SNR), large number of antennas, and large number of
users per cell. We show that at high SNRs, the system is interference-limited
and hence, we cannot improve the system performance by increasing the transmit
power of each user. Instead, by increasing the number of BS antennas, the
effects of interference and noise can be reduced, thereby improving the system
performance. We demonstrate that, with very large antenna arrays at the BS, the
transmit power of each user can be made inversely proportional to the number of
BS antennas while maintaining a desired quality-of-service. Numerical results
are presented to verify our analysis.


  The Murchison Widefield Array (MWA) is a new low frequency radio telescope
operating on the Square Kilometre Array site in Western Australia. MWA is
generating tens of terabytes of data daily. The size of the required data
storage has become a significant operational limitation and cost. We present a
simple binary compression technique and a system for the floating point
visibility data developed MWA. We present the statistics of the impact of such
compression on the data with the typical compression ratio up to 1:3.1.


  We present radio, optical/NIR, and X-ray observations of the afterglow of the
short-duration 130603B, and uncover a break in the radio and optical bands at
0.5 d after the burst, best explained as a jet break with an inferred jet
opening angle of 4-8 deg. GRB 130603B is only the third short GRB with a radio
afterglow detection to date, and the first time that a jet break is evident in
the radio band. We model the temporal evolution of the spectral energy
distribution to determine the burst explosion properties and find an
isotropic-equivalent kinetic energy of (0.6-1.7) x 10^51 erg and a circumburst
density of 5 x 10^-3-30 cm^-3. From the inferred opening angle of GRB 130603B,
we calculate beaming-corrected energies of Egamma (0.5-2) x 10^49 erg and EK
(0.1-1.6) x 10^49 erg. Along with previous measurements and lower limits we
find a median short GRB opening angle of 10 deg. Using the all-sky observed
rate of 10 Gpc^-3 yr^-1, this implies a true short GRB rate of 20 yr^-1 within
200 Mpc, the Advanced LIGO/VIRGO sensitivity range for neutron star binary
mergers. Finally, we uncover evidence for significant excess emission in the
X-ray afterglow of GRB 130603B at >1 d and conclude that the additional energy
component could be due to fall-back accretion or spin-down energy from a
magnetar formed following the merger.


  Predictions for angular distributions of top quark decay products that are
sensitive to t tbar spin correlations are presented at next-to-leading order in
alpha_s for the Tevatron and the LHC.


  Gravitational waves offer a potent mean to test the underlying theory of
gravity. In general theories of gravity, such as scalar-tensor theories, one
expects modifications in the friction term and the sound speed in the
gravitational wave equation. In that case, rapid oscillations in such
coefficients, e.g. due to an oscillating scalar field, may lead to narrow
parametric resonances in the gravitational wave strain. We perform a general
analysis of such possibility within DHOST theories. We use disformal
transformations to find the theory space with larger resonances, within an
effective field theory approach. We then apply our formalism to a non-minimally
coupled ultra-light dark matter scalar field, assuming the presence of a
primordial gravitational wave background, e.g., from inflation. We find that
the resonant peaks in the spectral density may be detectable by forthcoming
detectors such as LISA, Taiji, Einstein Telescope and Cosmic Explorer.


  In the context of a comprehensive Microsoft Academic (MA) study, we explored
in an initial step the quality of linked references data in MA in comparison
with Web of Science (WoS). Linked references are the backbone of bibliometrics,
because they are the basis of the times cited information in citation indexes.
We found that the concordance of linked references between MA and WoS ranges
from weak to non-existent for the full sample (publications of the University
of Zurich with less than 50 linked references in MA). An analysis with a sample
restricted to less than 50 linked references in WoS showed a strong agreement
between linked references in MA and WoS.


  Using the supergravity solution of $N_1$ D3-branes probing $A_{N_2-1}$
singularities we study the pp-wave limit of $AdS_5\times S^5/Z_{N_2}$. We show
that there are two different pp-wave limits. One is the orbifold of the pp-wave
limit of $AdS_5\times S^5$. In this case there is no symmetry enhancement. The
other case is the same as the pp-wave limit of $AdS_5\times S^5$ and therefore
we again see the maximal supersymmetry. We will also identify operators in the
four dimensional ${\cal N}=2$ $SU(N_1)^{N_2}$ gauge theory which correspond to
stringy excitations in the orbifolded pp-wave geometry. The existence of the
maximal pp-wave geometry indicates that there is a subsector of the
corresponding ${\cal N}=2$ gauge theories which has enhanced ${\cal N}=4$
supersymmetry. We also study the pp-wave limits of $AdS_{7,4}\times
S^{4,7}/Z_{N}$.


  We consider the coloring of certain distance graphs on the Euclidean plane.
Namely, we ask for the minimal number of colors needed to color all points of
the plane in such a way that pairs of points at distance in the interval
$[1,b]$ get different colors. The classic Hadwiger-Nelson problem is a special
case of this question -- obtained by taking $b=1$. The main results of the
paper are improved lower and upper bounds on the number of colors for some
values of $b$. In particular, we determine the minimal number of colors for two
ranges of values of $b$ - one of which is enlarging an interval presented by
Exoo and the second is completely new. Up to our knowledge, these are the only
known families of distance graphs on the plane with a determined nontrivial
chromatic number. Moreover, we present the first $8$-coloring for $b$ larger
than values of $b$ for the known $7$-colorings. As a byproduct, we give some
bounds and exact values for bounded parts of the plane, specifically by
coloring certain annuli.


  The aim of this work is to make available to the community a large collection
of mass-action reaction networks of a given size for further research. The set
is limited to what can be computed on a modern multi-core desktop in reasonable
time (< 20 days). We have currently generated over 47 million unique reaction
networks. All currently generated sets of networks are available and as new
sets are completed they will also be made available. Also provided are programs
for translating them into different formats, along with documentation and
examples. Source code and binaries for all the programs are included. These can
be downloaded from (http://www.sys-bio.org/networkenumeration). This library of
networks will allow for thorough studies of the reaction network space.
Additionally, these methods serve as an example for future work on enumerating
other types of biological networks, such as genetic regulatory networks and
mass-action networks that include regulation.


  The assumption of anarchic quark flavor puts serious stress on composite
Higgs models: flavor bounds imply a tuning of a few per-mille (at best) in the
Higgs potential. Composite twin Higgs (CTH) models significantly reduce this
tension by opening up a new region of parameter space, obtained by raising the
coupling among the composites close to the strong coupling limit $g_* \sim
4\pi$, thereby raising the scale of composites to around 10 TeV. This does not
lead to large tuning in the Higgs potential since the leading quantum
corrections are canceled by the twin partners (rather than the composites). We
survey the leading flavor bounds on the CTH, which correspond to tree-level
$\Delta F=2$ four-Fermi operators from Kaluza-Klein (KK) Z exchange in the kaon
system and 1-loop corrections from KK fermions to the electric dipole moment of
the neutron. We provide a parametric estimate for these bounds and also perform
a numeric scan of the parameter space using the complete calculation for both
quantities. The results confirm our expectation that CTH models accommodate
anarchic flavor significantly better than regular composite Higgs (CH) models.
Our conclusions apply both to the identical and fraternal twin cases.


  The goal of this research is to develop agents that are adaptive and
predictable and timely. At first blush, these three requirements seem
contradictory. For example, adaptation risks introducing undesirable side
effects, thereby making agents' behavior less predictable. Furthermore,
although formal verification can assist in ensuring behavioral predictability,
it is known to be time-consuming. Our solution to the challenge of satisfying
all three requirements is the following. Agents have finite-state automaton
plans, which are adapted online via evolutionary learning (perturbation)
operators. To ensure that critical behavioral constraints are always satisfied,
agents' plans are first formally verified. They are then reverified after every
adaptation. If reverification concludes that constraints are violated, the
plans are repaired. The main objective of this paper is to improve the
efficiency of reverification after learning, so that agents have a sufficiently
rapid response time. We present two solutions: positive results that certain
learning operators are a priori guaranteed to preserve useful classes of
behavioral assurance constraints (which implies that no reverification is
needed for these operators), and efficient incremental reverification
algorithms for those learning operators that have negative a priori results.


  BRST quantization is carried out for a model of p-branes with second class
constraints. After extension of the phase space the constraint algebra
coincides with the one of null string when p=1. It is shown that in this case
one can or can not obtain critical dimension for the null string, depending on
the choice of the operator ordering and corresponding vacuum states. When p>1,
operator orderings leading to critical dimension in the p=1 case are not
allowed. Admissable orderings give no restrictions on the dimension of the
embedding space-time. Finally, a generalization to supersymmetric null branes
is proposed.


  Near-Earth objects (NEOs) moving in resonant, Earth-like orbits are
potentially important. On the positive side, they are the ideal targets for
robotic and human low-cost sample return missions and a much cheaper
alternative to using the Moon as an astronomical observatory. On the negative
side and even if small in size (2-50 m), they have an enhanced probability of
colliding with the Earth causing local but still significant property damage
and loss of life. Here, we show that the recently discovered asteroid 2013 BS45
is an Earth co-orbital, the sixth horseshoe librator to our planet. In contrast
with other Earth's co-orbitals, its orbit is strikingly similar to that of the
Earth yet at an absolute magnitude of 25.8, an artificial origin seems
implausible. The study of the dynamics of 2013 BS45 coupled with the analysis
of NEO data show that it is one of the largest and most stable members of a
previously undiscussed dynamically cold group of small NEOs experiencing
repeated trappings in the 1:1 commensurability with the Earth. This new
resonant family is well constrained in orbital parameter space and it includes
at least 10 other transient members: 2003 YN107, 2006 JY26, 2009 SH2 and 2012
FC71 among them. 2012 FC71 represents the best of both worlds as it is locked
in a Kozai resonance and is unlikely to impact the Earth. Objects in this group
could be responsible for the production of Earth's transient irregular natural
satellites.


  Humans have a natural ability to perform semantic associations with the
surrounding objects in the environment. This allows them to create a mental map
of the environment, allowing them to navigate on-demand when given linguistic
instructions. A natural goal in Vision Language Navigation (VLN) research is to
impart autonomous agents with similar capabilities. Recent works take a step
towards this goal by creating a semantic spatial map representation of the
environment without any labeled data. However, their representations are
limited for practical applicability as they do not distinguish between
different instances of the same object. In this work, we address this
limitation by integrating instance-level information into spatial map
representation using a community detection algorithm and utilizing word
ontology learned by large language models (LLMs) to perform open-set semantic
associations in the mapping representation. The resulting map representation
improves the navigation performance by two-fold (233%) on realistic language
commands with instance-specific descriptions compared to the baseline. We
validate the practicality and effectiveness of our approach through extensive
qualitative and quantitative experiments.


  We calculate thermodynamic quantities of HP lattice proteins by means of a
multicanonical chain growth algorithm that connects the new variants of the
Pruned-Enriched Rosenbluth Method (nPERM) and flat histogram sampling of the
entire energy space. Since our method directly simulates the density of states,
we obtain results for thermodynamic quantities of the system for all
temperatures. In particular, this algorithm enables us to accurately simulate
the usually difficult accessible low-temperature region. Therefore, it becomes
possible to perform detailed analyses of the low-temperature transition between
ground states and compact globules.


  Let M be an n-dimensional K\"ahler manifold with numerically effective Ricci
class. In this note we prove that, if the first Betti number b_1(M)=2n, then M
is biholomorphic to the complex torus T^n_C.


  Automatic analyses and comparisons of different stages of embryonic
development largely depend on a highly accurate spatiotemporal alignment of the
investigated data sets. In this contribution, we assess multiple approaches for
automatic staging of developing embryos that were imaged with time-resolved 3D
light-sheet microscopy. The methods comprise image-based convolutional neural
networks as well as an approach based on the PointNet architecture that
directly operates on 3D point clouds of detected cell nuclei centroids. The
experiments with four wild-type zebrafish embryos render both approaches
suitable for automatic staging with average deviations of 21 - 34 minutes.
Moreover, a proof-of-concept evaluation based on simulated 3D+t point cloud
data sets shows that average deviations of less than 7 minutes are possible.


  Text-based Visual Question Answering~(TextVQA) aims to produce correct
answers for given questions about the images with multiple scene texts. In most
cases, the texts naturally attach to the surface of the objects. Therefore,
spatial reasoning between texts and objects is crucial in TextVQA. However,
existing approaches are constrained within 2D spatial information learned from
the input images and rely on transformer-based architectures to reason
implicitly during the fusion process. Under this setting, these 2D spatial
reasoning approaches cannot distinguish the fine-grain spatial relations
between visual objects and scene texts on the same image plane, thereby
impairing the interpretability and performance of TextVQA models. In this
paper, we introduce 3D geometric information into a human-like spatial
reasoning process to capture the contextual knowledge of key objects
step-by-step. %we formulate a human-like spatial reasoning process by
introducing 3D geometric information for capturing key objects' contextual
knowledge. To enhance the model's understanding of 3D spatial relationships,
Specifically, (i)~we propose a relation prediction module for accurately
locating the region of interest of critical objects; (ii)~we design a
depth-aware attention calibration module for calibrating the OCR tokens'
attention according to critical objects. Extensive experiments show that our
method achieves state-of-the-art performance on TextVQA and ST-VQA datasets.
More encouragingly, our model surpasses others by clear margins of 5.7\% and
12.1\% on questions that involve spatial reasoning in TextVQA and ST-VQA valid
split. Besides, we also verify the generalizability of our model on the
text-based image captioning task.


  Independent Component Analysis (ICA) is a statistical method often used to
decompose a complex dataset in its independent sub-parts. It is a powerful
technique to solve a typical Blind Source Separation problem. A fast
calculation of the gamma ray sky observed by GLAST, assuming the expected
instrumental response, has been implemented. The simulated images were used to
test the capability of the ICA method in identifying the sources.


  Dipolar (or spatially indirect) excitons (IXs) in semiconductor double
quantum well (DQW) subjected to an electric field are neutral species with a
dipole moment oriented perpendicular to the DQW plane. Here, we theoretically
study interactions between IXs in stacked DQW bilayers, where the dipolar
coupling can be either attractive or repulsive depending on the relative
positions of the particles. By using microscopic band structure calculations to
determine the electronic states forming the excitons, we show that the
attractive dipolar interaction between stacked IXs deforms their electronic
wave function, thereby increasing the inter-DQW interaction energy and making
the IX electrically polarizable. Many-particle effects interaction are
addressed by considering the coupling between a single IX in one of the DQWs to
a cloud of IXs in the other DQW, which is modeled either as a closed-packed
lattice or as a continuum IX fluid. We find that the lattice model yields IX
interlayer binding energies decreasing with increasing lattice density. This
behavior is due to the dominating role of the intra-DQW dipolar repulsion,
which prevents more than one exciton from entering the attractive region of the
inter-DQW coupling. Finally, both models shows that the single IX distorts the
distribution of IXs in the adjacent DQW, thus inducing the formation of an IX
polaron. While the interlayer binding energy reduces with IX density for
lattice polarons, the continuous polaron model predicts a non-monotonous
dependence on density in semi-quantitative agreement with a recent experimental
study [cf. Hubert {\it et al.}, Phys. Rev. {\bf X}9, 021026 (2019)].


  Here we generate finite bipartite body-centred cubic lattices up to 32
vertices. We have studied the spin one half Heisenberg antiferromagnet by
diagonalizing its Hamiltonian on each of the finite lattices and hence
computing its ground state properties. By extrapolation of these data we obtain
estimates of the T = 0 properties on the infinite bcc lattice. Our estimate of
the T = 0 energy agrees to five parts in ten thousand with third order spin
wave and series expansion method estimates, while our estimate of the staggered
magnetization agrees with the spin wave estimate to within a quarter of one
percent.


  We present full expressions for the surface part of polarization tensor of a
Dirac fermion confined in a half-space in $3+1$ dimensions. We compare this
tensor to the polarization tensor of eventual surface mode (which is a $2+1$
dimensional Dirac fermion) and find essential differences in the conductivities
in both Hall and normal sectors. Thus, the interaction with electromagnetic
field near the boundary differs significantly in the full model and in the
effective theory for the surface mode.


  The statistical study of the parsec scale properties of radio sources is
crucial to get information on the nature of the central engine and to provide
the foundations of the current unified theories, suggesting that the appearance
of active galactic nuclei depends strongly on orientation. We started a project
to observe at sub-arcsec resolution a complete sample of 94 nearby (z<0.1)
radio galaxies, the Bologna Complete Sample, which is not affected by any
selection effect on the jet velocity and orientation with respect to the line
of sight. Up to now, we published our parsec scale analysis of 77/94 sources.
Here, we describe the last VLBA observations at 5 GHz and EVN data at 18 cm
obtained for the 17 remaining faintest radio core (<5 mJy at 5 GHz in VLA
images) BCS sources and we report our preliminary results on the whole complete
sample.


  We present measurements of the electron-recoil (ER) response of the LUX dark
matter detector based upon 170,000 highly pure and spatially-uniform tritium
decays. We reconstruct the tritium energy spectrum using the combined energy
model and find good agreement with expectations. We report the average charge
and light yields of ER events in liquid xenon at 180 V/cm and 105 V/cm and
compare the results to the NEST model. We also measure the mean charge
recombination fraction and its fluctuations, and we investigate the location
and width of the LUX ER band. These results provide input to a re-analysis of
the LUX Run3 WIMP search.


  We consider online wireless network virtualization (WNV) in a multi-cell
multiple-input multiple output (MIMO) system with delayed feedback of channel
state information (CSI). Multiple service providers (SPs) simultaneously share
the base station resources of an infrastructure provider (InP). We aim at
minimizing the accumulated precoding deviation of the InP's actual precoder
from the SPs' virtualization demands via managing both inter-SP and inter-cell
interference, subject to both long-term and short-term per-cell transmit power
constraints. We develop an online coordinated precoding solution and show that
it provides provable performance bounds. Our precoding solution is fully
distributed at each cell, based only on delayed local CSI. Furthermore, it has
a closed-form expression with low computational complexity. Finally, simulation
results demonstrate the substantial performance gain of our precoding solution
over the current best alternative.


  For over a decade now we have been witnessing the success of {\em massive
parallel computation} (MPC) frameworks, such as MapReduce, Hadoop, Dryad, or
Spark. One of the reasons for their success is the fact that these frameworks
are able to accurately capture the nature of large-scale computation. In
particular, compared to the classic distributed algorithms or PRAM models,
these frameworks allow for much more local computation. The fundamental
question that arises in this context is though: can we leverage this additional
power to obtain even faster parallel algorithms?
  A prominent example here is the {\em maximum matching} problem---one of the
most classic graph problems. It is well known that in the PRAM model one can
compute a 2-approximate maximum matching in $O(\log{n})$ rounds. However, the
exact complexity of this problem in the MPC framework is still far from
understood. Lattanzi et al. showed that if each machine has $n^{1+\Omega(1)}$
memory, this problem can also be solved $2$-approximately in a constant number
of rounds. These techniques, as well as the approaches developed in the follow
up work, seem though to get stuck in a fundamental way at roughly $O(\log{n})$
rounds once we enter the near-linear memory regime. It is thus entirely
possible that in this regime, which captures in particular the case of sparse
graph computations, the best MPC round complexity matches what one can already
get in the PRAM model, without the need to take advantage of the extra local
computation power.
  In this paper, we finally refute that perplexing possibility. That is, we
break the above $O(\log n)$ round complexity bound even in the case of {\em
slightly sublinear} memory per machine. In fact, our improvement here is {\em
almost exponential}: we are able to deliver a $(2+\epsilon)$-approximation to
maximum matching, for any fixed constant $\epsilon>0$, in $O((\log \log n)^2)$
rounds.


  Assume we are given a set of parallel line segments in the plane, and we wish
to place a point on each line segment such that the resulting point set
maximizes or minimizes the area of the largest or smallest triangle in the set.
We analyze the complexity of the four resulting computational problems, and we
show that three of them admit polynomial-time algorithms, while the fourth is
NP-hard. Specifically, we show that maximizing the largest triangle can be done
in $O(n^2)$ time (or in $O(n \log n)$ time for unit segments); minimizing the
largest triangle can be done in $O(n^2 \log n)$ time; maximizing the smallest
triangle is NP-hard; but minimizing the smallest triangle can be done in
$O(n^2)$ time. We also discuss to what extent our results can be generalized to
polygons with $k>3$ sides.


  Much human and computational effort has aimed to improve how deep
reinforcement learning algorithms perform on benchmarks such as the Atari
Learning Environment. Comparatively less effort has focused on understanding
what has been learned by such methods, and investigating and comparing the
representations learned by different families of reinforcement learning (RL)
algorithms. Sources of friction include the onerous computational requirements,
and general logistical and architectural complications for running Deep RL
algorithms at scale. We lessen this friction, by (1) training several
algorithms at scale and releasing trained models, (2) integrating with a
previous Deep RL model release, and (3) releasing code that makes it easy for
anyone to load, visualize, and analyze such models. This paper introduces the
Atari Zoo framework, which contains models trained across benchmark Atari
games, in an easy-to-use format, as well as code that implements common modes
of analysis and connects such models to a popular neural network visualization
library. Further, to demonstrate the potential of this dataset and software
package, we show initial quantitative and qualitative comparisons between the
performance and representations of several deep RL algorithms, highlighting
interesting and previously unknown distinctions between them.


  It is well known that the proportion of pairs of elements of
$\operatorname{SL}(n,q)$ which generate the group tends to $1$ as $q^n\to
\infty$. This was proved by Kantor and Lubotzky using the classification of
finite simple groups. We give a proof of this theorem which does not depend on
the classification.
  An essential step in our proof is an estimate for the average of
$1/\operatorname{ord} g$ when $g$ ranges over $\operatorname{GL}(n,q)$, which
may be of independent interest. We prove that this average is \[
  \exp(-(2-o(1)) \sqrt{n \log n \log q}). \]


  A healthy human brain is perfused with blood flowing laminarly through
cerebral vessels, providing brain tissue with substrates such as oxygen and
glucose. Under normal conditions, cerebral blood flow is controlled by
autoregulation as well as metabolic, chemical and neurogenic regulation.
Physiological complexity of these mechanisms invariably leads to a question as
to what are the relations between the statistical properties of arterial and
intracranial pressure fluctuations. To shed new light on cerebral hemodynamics,
we employ a complex continuous wavelet transform to determine the instantaneous
phase difference between the arterial blood pressure (ABP) and intracranial
pressure (ICP) in patients with traumatic brain injuries or spontaneous
cerebral hemorrhage. For patients with mild to moderate injury, the phase
difference slowly evolves in time. However, severe neurological injury with
elevated ICP are herein associated with synchronization of arterial and
intracranial pressure. We use Shannon entropy to quantify the stability of
ABP-ICP phase difference and discuss the clinical applicability of such measure
to assessment of cerebrovascular reactivity and autoregulation integrity.


  Large language models (LLMs) such as ChatGPT have shown remarkable
capabilities in code generation. Despite the great achievement, they rely on
enormous training data to acquire a broad spectrum of open-domain knowledge.
Besides, their evaluation revolves around open-domain benchmarks like
HumanEval, which primarily consist of programming contests. Therefore, it is
hard to fully characterize the intricacies and challenges associated with
particular domains (e.g., web, game, and math). In this paper, we conduct an
in-depth study of the LLMs in domain-specific code generation. Our results
demonstrate that LLMs exhibit sub-optimal performance in generating
domain-specific code, due to their limited proficiency in utilizing
domain-specific libraries. We further observe that incorporating API knowledge
as prompts can empower LLMs to generate more professional code. Based on these
findings, we further investigate how to efficiently incorporate API knowledge
into the code generation process. We experiment with three strategies for
incorporating domain knowledge, namely, external knowledge inquirer,
chain-of-thought prompting, and chain-of-thought fine-tuning. We refer to these
strategies as a new code generation approach called DomCoder. Experimental
results show that all strategies of DomCoder lead to improvement in the
effectiveness of domain-specific code generation under certain settings. The
results also show that there is still ample room for further improvement, based
on which we suggest possible future works.


  We study the almost sure behaviour of suitably normalised multivariate Levy
processes as t goes to zero. Among other results we find necessary and
sufficient conditions for a law of a very slowly varying function which
includes a general law of the iterated logarithm in this setting. We also look
at the corresponding cluster set problem.


  We find an analog of Zamolodchikov's c-theorem for disordered two dimensional
noninteracting systems in their supersymmetric representation. For this purpose
we introduce a new parameter b which flows along the renormalization group
trajectories much like the central charge for unitary two dimensional field
theories. However, it is not known yet if this flow is irreversible. b turns
out to be related to the central extension of a certain algebra, a
generalization of the Virasoro algebra, which we show may be present at the
critical points of these theories. b is also related to the physical free
energy of the disordered system defined on a cylinder. We discuss possible
applications by computing b for two dimensional Dirac fermions with random
gauge potential.


  Machine learning (ML) methods have been developing rapidly, but configuring
and selecting proper methods to achieve a desired performance is increasingly
difficult and tedious. To address this challenge, automated machine learning
(AutoML) has emerged, which aims to generate satisfactory ML configurations for
given tasks in a data-driven way. In this paper, we provide a comprehensive
survey on this topic. We begin with the formal definition of AutoML and then
introduce its principles, including the bi-level learning objective, the
learning strategy, and the theoretical interpretation. Then, we summarize the
AutoML practices by setting up the taxonomy of existing works based on three
main factors: the search space, the search algorithm, and the evaluation
strategy. Each category is also explained with the representative methods.
Then, we illustrate the principles and practices with exemplary applications
from configuring ML pipeline, one-shot neural architecture search, and
integration with foundation models. Finally, we highlight the emerging
directions of AutoML and conclude the survey.


  We experimentally investigate the response of a sheared granular medium in a
Couette geometry. The apparatus exhibits the expected stick-slip motion and we
probe it in the very intermittent regime resulting from low driving.
Statistical analysis of the dynamic fluctuations reveals notable regularities.
We observe a possible stability property for the torque distribution,
reminiscent of the stability of Gaussian independent variables. In this case,
however, the variables are correlated and the distribution is skewed. Moreover,
the whole dynamical intermittent regime can be described with a simple
stochastic model, finding good quantitative agreement with the experimental
data. Interestingly, a similar model has been previously introduced in the
study of magnetic domain wall motion, a source of Barkhausen noise. Our study
suggests interesting connections between different complex phenomena and
reveals some unexpected features that remain to be explained.


  Magnetohydrodynamic(MHD) turbulence displays velocity anisotropies which
reflect the direction of the magnetic field. This anisotropy has led to the
development of a number of statistical techniques for studying magnetic fields
in the interstellar medium. In this paper, we review and compare three
techniques that use radio position-position-velocity data for determining
magnetic field strength and morphology : the correlation function anisotropy
(CFA), Principal Component Analysis of Anisotropies (PCAA), and the more recent
Velocity Gradient Technique (VGT). We compare these three techniques and
suggest improvements to the CFA and PCAA techniques to increase their accuracy
and versatility. In particular, we suggest and successfully implement a much
faster way of calculating non-periodic correlation functions for the CFA. We
discuss possible improvements to the current implementation of the PCAA. We
show the advantages of the VGT in terms of magnetic field tracing and stress
the complementary nature with the other two techniques.


  We study the problem on the weak-star decomposability of a topological
$\mathbb{N}_{0}$-dynamical system $(\Omega,\varphi)$, where $\varphi$ is an
endomorphism of a metric compact set $\Omega$, into ergodic components in terms
of the associated enveloping semigroups. In the tame case (where the Ellis
semigroup $E(\Omega,\varphi)$ consists of $B_{1}$-transformations
$\Omega\rightarrow \Omega$), we show that (i) the desired decomposition exists
for an appropriate choice of the generalized sequential averaging method; (ii)
every sequence of weighted ergodic means for the shift operator $x\rightarrow
x\circ\varphi$, $x\in C(\Omega)$, contains a pointwise convergent subsequence.
We also discuss the relationship between the statistical properties of
$(\Omega,\varphi)$ and the mutual structure of minimal sets and ergodic
measures.


  We present the implementation of a spectral kurtosis based Radio Frequency
Interference detection system on the CHIME instrument and its reduced-scale
pathfinder. Our implementation extends single-receiver formulations to the case
of a compact array, combining samples from multiple receivers to improve the
confidence with which RFI is detected. Through comparison between on-sky data
and simulations, we show that the statistical properties of the canonical
spectral kurtosis estimator are functionally unchanged by cross-array
integration. Moreover, by comparison of simultaneous data from CHIME and the
Pathfinder, we evaluate our implementation's capacity for interference
discrimination for compact arrays of various size. We conclude that a spectral
kurtosis based implementation provides a scalable, high cadence RFI
discriminator for compact multi-receiver arrays.


  We present systematic construction of probability and probability current
densities operators for one-band single particle Pauli equations starting from
the operators in Dirac electron model within Second Quantized Approach. These
operators are of importance as in probability interpretation of experimental
data, so in establishing of boundary conditions. It is shown that derived
operators differ significally from their convential Schrodinger-type
counterparts. The generalization of continuity equation for probability density
under external perturbations and physical meaning of additional source terms is
discussed. The presented approach can be useful in analysis of carriers
dynamics described within generic multicomponent $\vec{k} \cdot \vec{p}$
Hamiltonians in Envelope Function Approximation (EFA).


  Denote $\Sigma_n$ and $Q_n$ the set of all $n \times n$ symmetric and
skew-symmetric matrices over a field $\mathbb{F}$, respectively, where
$char(\mathbb{F})\neq 2$ and $\lvert \mathbb{F} \rvert \geq n^2+1$. A
characterization of $\phi,\psi:\Sigma_n \rightarrow \Sigma_n$, for which at
least one of them is surjective, satisfying
$$\det(\phi(x)+\psi(y))=\det(x+y)\qquad(x,y\in \Sigma_n)$$ is given.
Furthermore, if $n$ is even and $\phi,\psi:Q_n \rightarrow Q_n$, for which
$\psi$ is surjective and $\psi(0)=0$, satisfy
$$\det(\phi(x)+\psi(y))=\det(x+y)\qquad(x,y\in Q_n),$$ then $\phi=\psi$ and
$\psi$ must be a bijective linear map preserving the determinant.


  Most deep learning methods for video frame interpolation consist of three
main components: feature extraction, motion estimation, and image synthesis.
Existing approaches are mainly distinguishable in terms of how these modules
are designed. However, when interpolating high-resolution images, e.g. at 4K,
the design choices for achieving high accuracy within reasonable memory
requirements are limited. The feature extraction layers help to compress the
input and extract relevant information for the latter stages, such as motion
estimation. However, these layers are often costly in parameters, computation
time, and memory. We show how ideas from dimensionality reduction combined with
a lightweight optimization can be used to compress the input representation
while keeping the extracted information suitable for frame interpolation.
Further, we require neither a pretrained flow network nor a synthesis network,
additionally reducing the number of trainable parameters and required memory.
When evaluating on three 4K benchmarks, we achieve state-of-the-art image
quality among the methods without pretrained flow while having the lowest
network complexity and memory requirements overall.


  We use the dynamical density matrix renormalization group technique to show
that the high-energy part of the spectrum of a S=1 Haldane chain, placed in a
strong external magnetic field $H$ exceeding the Haldane gap $\Delta$, contains
edge singularities, similar to those known to exist in the low-energy spectral
response. It is demonstrated that in the frequency range $\omega\gtrsim \Delta$
the longitudinal (with respect to the applied field) dynamical structure factor
is dominated by the power-law singularity
$S^{\parallel}(q=\pi,\omega)\propto(\omega-\omega_{0})^{-\alpha'}$. We study
the behavior of the high-energy edge exponent $\alpha'$ and the edge
$\omega_{0}$ as functions of the magnetic field. The existence of edge
singularities at high energies is directly related to the Tomonaga-Luttinger
liquid character of the ground state at $H>\Delta$ and is expected to be a
general feature of one-dimensional gapped spin systems in high magnetic fields.


  A classical spin network consists of a ribbon graph (i.e., an abstract graph
with a cyclic ordering of the vertices around each edge) and an admissible
coloring of its edges by natural numbers. The standard evaluation of a spin
network is an integer number. In a previous paper, we proved an existence
theorem for the asymptotics of the standard evaluation of an arbitrary
classical spin network when the coloring of its edges are scaled by a large
natural number. In the present paper, we extend the results to the case of an
evaluation of quantum spin networks of arbitrary valency at a fixed root of
unity. As in the classical case, our proofs use the theory of $G$-functions of
Andr\'e, together with some new results concerning holonomic and $q$-holonomic
sequences of Wilf-Zeilberger.


  The cosmological principle assumes that the universe is homogeneous and
isotropic on cosmic scales. There exist many works testing the cosmic
homogeneity and/or the cosmic isotropy of the universe in the literature. In
fact, some observational hints of the cosmic anisotropy have been claimed.
However, we note that the paucity of the data considered in the literature
might be responsible for the `found' cosmic anisotropy. So, it might disappear
in a large enough sample. Very recently, the Pantheon sample consisting of 1048
type Ia supernovae (SNIa) has been released, which is the largest
spectroscopically confirmed SNIa sample to date. In the present work, we test
the cosmic anisotropy in the Pantheon SNIa sample by using three methods, and
hence the results from different methods can be cross-checked. All the results
obtained by using the hemisphere comparison (HC) method, the dipole fitting
(DF) method and HEALPix suggest that no evidence for the cosmic anisotropy is
found in the Pantheon SNIa sample.


  Despite their apparent simplicity, random Boolean networks display a rich
variety of dynamical behaviors. Much work has been focused on the properties
and abundance of attractors. We here derive an expression for the number of
attractors in the special case of one input per node. Approximating some other
non-chaotic networks to be of this class, we apply the analytic results to
them. For this approximation, we observe a strikingly good agreement on the
numbers of attractors of various lengths. Furthermore, we find that for long
cycle lengths, there are some properties that seem strange in comparison to
real dynamical systems. However, those properties can be interesting from the
viewpoint of constraint satisfaction problems.