  This paper summarises the design of the candidate ED for the Challenge on
Learned Image Compression 2024. This candidate aims at providing an anchor
based on conventional coding technologies to the learning-based approaches
mostly targeted in the challenge.
  The proposed candidate is based on the Enhanced Compression Model (ECM)
developed at JVET, the Joint Video Experts Team of ITU-T VCEG and ISO/IEC MPEG.
  Here, ECM is adapted to the challenge objective: to maximise the perceived
quality, the encoding is performed according to a perceptual metric, also the
sequence selection is performed in a perceptual manner to fit the target bit
per pixel objectives.
  The primary objective of this candidate is to assess the recent developments
in video coding standardisation and in parallel to evaluate the progress made
by learning-based techniques. To this end, this paper explains how to generate
coded images fulfilling the challenge requirements, in a reproducible way,
targeting the maximum performance.


  Recent developments on three body systems have revealed that dynamics of
trajectories passing through collinear configurations can be easily adopted. We
analyse the reduction procedure in order to detect the points where collinear
configurations are deviating. Then we show that the value of the reduced
Hamiltonian can be computed at these points.


  We devise deep nearest centroids (DNC), a conceptually elegant yet
surprisingly effective network for large-scale visual recognition, by
revisiting Nearest Centroids, one of the most classic and simple classifiers.
Current deep models learn the classifier in a fully parametric manner, ignoring
the latent data structure and lacking simplicity and explainability. DNC
instead conducts nonparametric, case-based reasoning; it utilizes sub-centroids
of training samples to describe class distributions and clearly explains the
classification as the proximity of test data and the class sub-centroids in the
feature space. Due to the distance-based nature, the network output
dimensionality is flexible, and all the learnable parameters are only for data
embedding. That means all the knowledge learnt for ImageNet classification can
be completely transferred for pixel recognition learning, under the
"pre-training and fine-tuning" paradigm. Apart from its nested simplicity and
intuitive decision-making mechanism, DNC can even possess ad-hoc explainability
when the sub-centroids are selected as actual training images that humans can
view and inspect. Compared with parametric counterparts, DNC performs better on
image classification (CIFAR-10, ImageNet) and greatly boots pixel recognition
(ADE20K, Cityscapes), with improved transparency and fewer learnable
parameters, using various network architectures (ResNet, Swin) and segmentation
models (FCN, DeepLabV3, Swin). We feel this work brings fundamental insights
into related fields.


  We provide a field-theoretic algorithm of obtaining energy momentum tensor
(EMT) for gravitationally coupled theories. The method is based on an auxiliary
field theory and equally applicable to both minimal and non-minimal coupling.
The algorithm illuminates the connection between the EMT, obtained by
functional variation of the metric, and local balance of energy and momentum.
Our method is of cardinal value for the proper identification of the EMT in
context of non-minimally coupled gravity theories.


  We study fundamental graph parameters such as the Diameter and Radius in
directed graphs, when distances are measured using a somewhat unorthodox but
natural measure: the distance between $u$ and $v$ is the minimum of the
shortest path distances from $u$ to $v$ and from $v$ to $u$. The center node in
a graph under this measure can for instance represent the optimal location for
a hospital to ensure the fastest medical care for everyone, as one can either
go to the hospital, or a doctor can be sent to help.
  By computing All-Pairs Shortest Paths, all pairwise distances and thus the
parameters we study can be computed exactly in $\tilde{O}(mn)$ time for
directed graphs on $n$ vertices, $m$ edges and nonnegative edge weights.
Furthermore, this time bound is tight under the Strong Exponential Time
Hypothesis [Roditty-Vassilevska W. STOC 2013] so it is natural to study how
well these parameters can be approximated in $O(mn^{1-\epsilon})$ time for
constant $\epsilon>0$. Abboud, Vassilevska Williams, and Wang [SODA 2016] gave
a polynomial factor approximation for Diameter and Radius, as well as a
constant factor approximation for both problems in the special case where the
graph is a DAG. We greatly improve upon these bounds by providing the first
constant factor approximations for Diameter, Radius and the related
Eccentricities problem in general graphs. Additionally, we provide a hierarchy
of algorithms for Diameter that gives a time/accuracy trade-off.


  A self-propelled artificial microswimmer is often modeled as a ballistic
Brownian particle moving with constant speed aligned along one of its axis, but
changing direction due to random collisions with the environment. Similarly to
thermal noise, its angular randomization is described as a memoryless
stochastic process. Here, we speculate that finite-time correlations in the
orientational dynamics can affect the swimmer's diffusivity. To this purpose we
propose and solve two alternative models. In the first one we simply assume
that the environmental fluctuations governing the swimmer's propulsion are
exponentially correlated in time, whereas in the second one we account for
possible damped fluctuations of the propulsion velocity around the swimmer's
axis. The corresponding swimmer's diffusion constants are predicted to get,
respectively, enhanced or suppressed upon increasing the model memory time.
Possible consequences of this effect on the interpretation of the experimental
data are discussed.


  Several methods are constructed for large-scale electronic structure
calculations. Test calculations are carried out with up to 10^7 atoms. As an
application, cleavage process of silicon is investigated by molecular dynamics
simulation with 10-nm-scale systems. As well as the elementary formation
process of the (111)-(2 x 1) surface, we obtain nanoscale defects, that is,
step formation and bending of cleavage path into favorite (experimentally
observed) planes. These results are consistent to experiments. Moreover, the
simulation result predicts an explicit step structure on the cleaved surface,
which shows a bias-dependent STM image.


  Exclusive and kinematically complete high-statistics measurements of the
double pionic fusion reaction $dd \to ^4$He$\pi^0\pi^0$ have been performed in
the energy range 0.8 - 1.4 GeV covering thus the region of the ABC effect,
which denotes a pronounced low-mass enhancement in the $\pi\pi$-invariant mass
spectrum. The experiments were carried out with the WASA detector setup at
COSY. Similar to the observation in the basic $pn \to d \pi^0\pi^0$ reaction,
the data reveal a correlation between the ABC effect and a resonance-like
energy dependence in the total cross section. The maximum occurs at m=2.37 GeV
+ 2$m_N$, i.e. at the same position as in the basic reaction. The observed
resonance width $\Gamma \approx$ 160 MeV can be understood from broadening due
to Fermi motion of the nucleons in initial and final nuclei together with
collision damping. Differential cross sections are described equally well by
the hypothesis of a $pn$ resonance formation during the reaction process.


  In this chapter we review concepts and theories of polymer dynamics. We think
of it as an introduction to the topic for scientists specializing in other
subfields of statistical mechanics and condensed matter theory, so, for the
readers reference, we start with a short review of the equilibrium static
properties of polymer systems. Most attention is paid to the dynamics of
unentangled polymer systems, where apart from classical Rouse and Zimm models
we review some recent scaling and analytical generalizations. The dynamics of
systems with entanglements is also briefly reviewed. Special attention is paid
to the discussion of comparatively weakly understood topological states of
polymer systems and possible approaches to the description of their dynamics.


  The polarity of the toroidal magnetic field in the solar convection zone
periodically reverses in the course of the 11/22-year solar cycle. Among the
various processes that contribute to the removal of `old-polarity' toroidal
magnetic flux is the emergence of flux loops forming bipolar regions at the
solar surface. We quantify the loss of subsurface net toroidal flux by this
process. To this end, we determine the contribution of an individual emerging
bipolar loop and show that it is unaffected by surface flux transport after
emergence. Together with the linearity of the diffusion process this means that
the total flux loss can be obtained by adding the contributions of all emerging
bipolar magnetic regions. The resulting total loss rate of net toroidal flux
amounts to 1.3 X 10^{15} Mx/s during activity maxima and 6.1 X 10^{14} Mx/s
during activity minima, to which ephemeral regions contribute about 90% and
97%, respectively. This rate is consistent with the observationally inferred
loss rate of toroidal flux into interplanetary space and corresponds to a decay
time of the subsurface toroidal flux of about 12 years, also consistent with a
simple estimate based on turbulent diffusivity. Consequently, toroidal flux
loss by flux emergence is a relevant contribution to the budget of net toroidal
flux in the solar convection zone. That the toroidal flux loss rate due to flux
emergence is consistent with what is expected from turbulent diffusion, and
that the corresponding decay time is similar to the length of the solar cycle
are important constraints for understanding the solar cycle and the Sun's
internal dynamics.


  We present a detailed temperature-dependent spectroscopic study of DyMnO3
single crystals with distorted perovskite structure. Energies of 36
crystal-field levels of Dy3+ in paramagnetic DyMnO3 were determined. The Dy3+
ground Kramers doublet does not split at T_N^Mn = 39 K and splits below Tlock =
18 K. The splitting grows fast at temperatures near T_N^Dy = 6.5 K and reaches
{\Delta}0 = 11 cm-1 at 4 K. Using the experimental temperature dependence
{\Delta}0(T), we calculate the dysprosium magnetic moment mDy(T) and the
dysprosium contribution into specific heat and magnetic susceptibility.
Analysing all the experimental data, we conclude that the Dy-Mn interaction is
of the Dzyaloshinskii-Moriya type.


  We offer a short and elementary proof that, for a Z-set A in a
finite-dimensional ANR Y, dimA<dimY. This result is relevant to the study of
group boundaries. The original proof by Bestvina and Mess relied on
cohomological dimension theory.


  Emerging Compute Express Link (CXL) enables cost-efficient memory expansion
beyond the local DRAM of processors. While its CXL.mem protocol provides
minimal latency overhead through an optimized protocol stack, frequent CXL
memory accesses can result in significant slowdowns for memory-bound
applications whether they are latency-sensitive or bandwidth-intensive. The
near-data processing (NDP) in the CXL controller promises to overcome such
limitations of passive CXL memory. However, prior work on NDP in CXL memory
proposes application-specific units that are not suitable for practical CXL
memory-based systems that should support various applications. On the other
hand, existing CPU or GPU cores are not cost-effective for NDP because they are
not optimized for memory-bound applications. In addition, the communication
between the host processor and CXL controller for NDP offloading should achieve
low latency, but existing CXL$.$io/PCIe-based mechanisms incur $\mu$s-scale
latency and are not suitable for fine-grained NDP.
  To achieve high-performance NDP end-to-end, we propose a low-overhead
general-purpose NDP architecture for CXL memory referred to as Memory-Mapped
NDP (M$^2$NDP), which comprises memory-mapped functions (M$^2$func) and
memory-mapped $\mu$threading (M$^2\mu$thr). M$^2$func is a CXL.mem-compatible
low-overhead communication mechanism between the host processor and NDP
controller in CXL memory. M$^2\mu$thr enables low-cost, general-purpose NDP
unit design by introducing lightweight $\mu$threads that support highly
concurrent execution of kernels with minimal resource wastage. Combining them,
M$^2$NDP achieves significant speedups for various workloads by up to 128x
(14.5x overall) and reduces energy by up to 87.9% (80.3% overall) compared to
baseline CPU/GPU hosts with passive CXL memory.


  The COVID-19 pandemic has driven ever-greater demand for tools which enable
efficient exploration of biomedical literature. Although semi-structured
information resulting from concept recognition and detection of the defining
elements of clinical trials (e.g. PICO criteria) has been commonly used to
support literature search, the contributions of this abstraction remain poorly
understood, especially in relation to text-based retrieval. In this study, we
compare the results retrieved by a standard search engine with those filtered
using clinically-relevant concepts and their relations. With analysis based on
the annotations from the TREC-COVID shared task, we obtain quantitative as well
as qualitative insights into characteristics of relational and concept-based
literature exploration. Most importantly, we find that the relational concept
selection filters the original retrieved collection in a way that decreases the
proportion of unjudged documents and increases the precision, which means that
the user is likely to be exposed to a larger number of relevant documents.


  This paper presents the methods that have participated in the SHREC 2022
track on the fitting and recognition of simple geometric primitives on point
clouds. As simple primitives we mean the classical surface primitives derived
from constructive solid geometry, i.e., planes, spheres, cylinders, cones and
tori. The aim of the track is to evaluate the quality of automatic algorithms
for fitting and recognising geometric primitives on point clouds. Specifically,
the goal is to identify, for each point cloud, its primitive type and some
geometric descriptors. For this purpose, we created a synthetic dataset,
divided into a training set and a test set, containing segments perturbed with
different kinds of point cloud artifacts. Among the six participants to this
track, two are based on direct methods, while four are either fully based on
deep learning or combine direct and neural approaches. The performance of the
methods is evaluated using various classification and approximation measures.


  The Owens Valley Radio Observatory (OVRO) millimeter array was used to make
observations of the CS(2-1) line (at 97.981 GHz) arising from the G0.07+0.04
region of the ``-30 km/s'' molecular cloud near the Galactic center with a
spatial resolution of ~8". The ionized edges of this cloud forms the Arched
Filament HII regions which are ionized by the adjacent Arches stellar cluster.
The OVRO data were combined with single-dish data obtained at the 30-m IRAM
telescope by Serabyn & Guesten (1987). A comparison of this CS(2-1) data and
the H92alpha recombination line data of Lang, Goss & Morris (2001) reveals that
the ionized and molecular gas are physically related, but that their velocities
in this region differ by up to 35 km/s. This difference in velocity can be
understood if the gas that gave rise to the G0.07+0.04 HII region has been
fully ionized. An overall comparison of the molecular and ionized gas across
the entire -30 km/s cloud based on the single dish CS(2-1) data and the
H92alpha line data illustrates that such differences in velocity between the
ionized and molecular gas are common and that the geometrical arrangement of
these components is complicated. Much of the ionized gas resides on the near
side (to the observer) of the molecular cloud; however, in several regions,
some molecular material must lie in front of the HII region. The Arches stellar
cluster therefore appears to be located in the midst of the molecular clouds
such that some of the near-side cloud surfaces along our line of sight have not
been exposed to the ionizing radiation.


  We report Stark shift measurements for 121Sb donor electron spins in silicon
using pulsed electron spin resonance. Interdigitated metal gates on top of a
Sb-implanted 28Si epi-layer are used to apply electric fields. Two Stark
effects are resolved: a decrease of the hyperfine coupling between electron and
nuclear spins of the donor and a decrease in electron Zeeman g-factor. The
hyperfine term prevails at X-band magnetic fields of 0.35T, while the g-factor
term is expected to dominate at higher magnetic fields. A significant linear
Stark effect is also resolved presumably arising from strain.


  When inverting solar spectra, image degradation effects that are present in
the data are usually approximated or not considered. We develop a data
reduction method that takes these issues into account and minimizes the
resulting errors. By accounting for the diffraction PSF of the telescope during
the inversions, we can produce a self-consistent solution that best fits the
observed data, while simultaneously requiring fewer free parameters than
conventional approaches. Simulations using realistic MHD data indicate that the
method is stable for all resolutions, including those with pixel scales well
beyond those that can be resolved with a 0.5m telescope, such as the Hinode
SOT. Application of the presented method to reduce full Stokes data from the
Hinode spectro-polarimeter results in dramatically increased image contrast and
an increase in the resolution of the data to the diffraction limit of the
telescope in almost all Stokes and fit parameters. The resulting data allow for
detecting and interpreting solar features that have so far only been observed
with 1m class ground-based telescopes. The new inversion method allows for
accurate fitting of solar spectro-polarimetric imaging data over a large field
of view, while simultaneously improving the noise statistics and spatial
resolution of the results significantly.


  The paper presents the graph signal processing (GSP) companion model that
naturally replicates the basic tenets of classical signal processing (DSP) for
GSP. The companion model shows that GSP can be made equivalent to DSP 'plus'
appropriate boundary conditions (bc) - this is shown under broad conditions and
holds for arbitrary undirected or directed graphs. This equivalence suggests
how to broaden GSP - extend naturally a DSP concept to the GSP companion model
and then transfer it back to the common graph vertex and graph Fourier domains.
The paper shows that GSP unrolls as two distinct models that coincide in DSP,
the companion model based on (Hadamard or pointwise) powers of what we will
introduce as the spectral frequency vector $\lambda$, and the traditional graph
vertex model, based on the adjacency matrix and its eigenvectors. The paper
expands GSP in several directions, including showing that convolution in the
graph companion model can be achieved with the FFT and that GSP modulation with
appropriate choice of carriers exhibits the DSP translation effect that enables
multiplexing by modulation of graph signals.


  All the boundary conditions compatible with the reduction of a five
dimensional spinor field of bulk mass $M$ in a compactified warped space to a
four dimensional brane are derived from the hermiticity conditions of the
relevant operator. The possible presence of metric singularities is taken into
account. Examples of resulting Kaluza-Klein spinor towers are given for a
representative set of values for the basic parameters of the model and of the
parameters describing the allowed boundary conditions, within the hypothesis
that there exists one-mass-scale-only, the Planck mass. In many cases, the
lowest mass in the tower is small and very sensitive to the parameters while
the other masses are much higher and become more regularly spaced. In these
cases, if a basic fermion of the standard model (lepton or quark) happens to be
the lowest mass of a Kaluza-Klein tower, the other masses would be much larger
and weakly dependent on the fermion which defines the tower.


  This work completes the construction of purely algebraic version of the
theory of non-linear quantum chemistry methods. It is shown that at the heart
of these methods there lie certain algebras close in their definition to the
well-known Clifford algebra but quite different in their properties. The most
important for quantum chemistry property of these algebras is the following :
for a fixed number of electrons the corresponding sector of the Fock space
becomes a commutative algebra and its ideals are determined by the order of
excitations from the Hartree-Fock reference state. Quotients of this algebra
can also be endowed with commutative algebra structures and quotient
Schr{\"o}dinger equations are exactly the couple cluster type equations.
Possible computer implementation of multiplication in the aforementioned
algebras is described. Quality of different polynomial approximations of
configuration interaction wave functions is illustrated with concrete examples.
Embedding of algebras of infinitely separated subsystems in algebra of the
united system is discussed


  The new generation of VLTI instruments (GRAVITY, MATISSE) aims to produce
routinely interferometric images to uncover the morphological complexity of
different objects at high angular resolution. Image reconstruction is, however,
not a fully automated process. Here we focus on a specific science case, namely
the complex circumbinary environments of a subset of evolved binaries, for
which interferometric imaging provides the spatial resolution required to
resolve the immediate circumbinary environment.
  Indeed, many binaries where the main star is in the post-asymptotic giant
branch (post-AGB) phase are surrounded by circumbinary disks. Those disks were
first inferred from the infrared excess produced by dust. Snapshot
interferometric observations in the infrared confirmed disk-like morphology and
revealed high spatial complexity of the emission that the use of geometrical
models could not recover without being strongly biased. Arguably, the most
convincing proof of the disk-like shape of the circumbinary environment came
from the first interferometric image of such a system (IRAS08544-4431) using
the PIONIER instrument at the VLTI. This image was obtained using the SPARCO
image reconstruction approach that enables to subtract a model of a component
of the image and reconstruct an image of its environment only. In the case of
IRAS08544-4431, the model involved a binary and the image of the remaining
signal revealed several unexpected features. Then, a second image revealed a
different but also complex circumstellar morphology around HD101584 that was
well studied by ALMA. To exploit the VLTI imaging capability to understand
these targets, we started a large program at the VLTI to image post-AGB binary
systems using both PIONIER and GRAVITY instruments.


  We present moderate-resolution spectroscopy of globular clusters (GCs) around
the Sa/Sb spiral galaxy M81 (NGC 3031). Sixteen candidate clusters were
observed with the Low Resolution Imaging Spectrograph on the Keck I telescope.
All are confirmed as bona fide GCs, although one of the clusters appears to
have been undergoing a transient event during our observations. In general, the
M81 globular cluster system (GCS) is found to be very similar to the Milky Way
(MW) and M31 systems, both chemically and kinematically. A kinematic analysis
of the velocities of 44 M81 GCS, (the 16 presented here and 28 from previous
work) strongly suggests that the red, metal-rich clusters are rotating in the
same sense as the gas in the disk of M81. The blue, metal-poor clusters have
halo-like kinematics, showing no evidence for rotation. The kinematics of
clusters whose projected galactocentric radii lie between 4 and 8 kpc suggest
that they are rotating much more than those which lie outside these bounds. We
suggest that these rotating, intermediate-distance clusters are analogous to
the kinematic sub-population in the metal-rich, disk GCs observed in the MW and
we present evidence for the existence of a similar sub-population in the
metal-rich clusters of M31. With one exception, all of the M81 clusters in our
sample have ages that are consistent with MW and M31 GCs. One cluster may be as
young as a few Gyrs. The correlations between absorption-line indices
established for MW and M31 GCs also hold in the M81 cluster system, at least at
the upper end of the metallicity distribution (which our sample probes). On the
whole, the mean metallicity of the M81 GCS is similar to the metallicity of the
MW and M31 GCSs. The projected mass of M81 is similar to the masses of the MW
and M31. Its mass profile indicates the presence of a dark matter halo.


  We propose that gaugino condensation in the hidden sector may dynamically
induce intermediate gauge symmetry breaking and specify the compactification
scale. We also show that this scheme makes possible affine level one grand
unified string models with gauge breaking scale $M_{\rm GUT} \sim 10^{16}$ GeV.
$T$-duality plays a crucial role in making this scheme possible, even though it
is spontaneously broken. We also discuss the generation of the large mass
hierarchy between the string scale and the electroweak scale and the solution
of the dilaton runaway problem in this scheme.


  We prove the existence of a solution to a singular anisotropic elliptic
equation in a bounded open subset $\Omega$ of $\mathbb R^N$ with $N\ge 2$,
subject to a homogeneous boundary condition: \begin{equation} \label{eq0}
\left\{ \begin{array}{ll} \mathcal A u+ \Phi(u,\nabla u)=\Psi(u,\nabla u)+
\mathfrak{B} u \quad& \mbox{in } \Omega,\\ u=0 & \mbox{on } \partial\Omega.
\end{array} \right. \end{equation} Here $ \mathcal A u=-\sum_{j=1}^N
|\partial_j u|^{p_j-2}\partial_j u$ is the anisotropic
$\overrightarrow{p}$-Laplace operator, while $\mathfrak B$ is an operator from
$W_0^{1,\overrightarrow{p}}(\Omega)$ into $W^{-1,\overrightarrow{p}'}(\Omega)$
satisfying suitable, but general, structural assumptions. $\Phi$ and $\Psi$ are
gradient-dependent nonlinearities whose models are the following:
\begin{equation*} \label{phi}\Phi(u,\nabla u):=\left(\sum_{j=1}^N
\mathfrak{a}_j |\partial_j u|^{p_j}+1\right)|u|^{m-2}u, \quad \Psi(u,\nabla
u):=\frac{1}{u}\sum_{j=1}^N |u|^{\theta_j} |\partial_j u|^{q_j}.
\end{equation*} We suppose throughout that, for every $1\leq j\leq N$,
\begin{equation*}\label{ass} \mathfrak{a}_j\geq 0, \quad \theta_j>0, \quad
0\leq q_j<p_j, \quad 1<p_j,m\quad \mbox{and}\quad p<N, \end{equation*} and we
distinguish two cases: 1) for every $1\leq j\leq N$, we have $\theta_j\geq 1$;
2) there exists $1\leq j\leq N$ such that $\theta_j<1$. In this last situation,
we look for non-negative solutions of \eqref{eq0}.


  Using 2D particle-in-cell (PIC) plasma simulations we study electron
acceleration by temperature anisotropy instabilities, assuming conditions
typical of above-the-loop-top (ALT) sources in solar flares. We focus on the
long-term effect of $T_{e,\perp} > T_{e,\parallel}$ instabilities by driving
the anisotropy growth during the entire simulation time, through imposing a
shearing or a compressing plasma velocity ($T_{e,\perp}$ and $T_{e,\parallel}$
are the temperatures perpendicular and parallel to the magnetic field). This
magnetic growth makes $T_{e,\perp}/T_{e,\parallel}$ grow due to electron
magnetic moment conservation, and amplifies the ratio $\omega_{ce}/\omega_{pe}$
from $\sim 0.53$ to $\sim 2$ ($\omega_{ce}$ and $\omega_{pe}$ are the electron
cyclotron and plasma frequencies, respectively). In the regime
$\omega_{ce}/\omega_{pe}\lesssim 1.2-1.7$ the instability is dominated by
oblique, quasi-electrostatic (OQES) modes, and the acceleration is inefficient.
When $\omega_{ce}/\omega_{pe}$ has grown to $\omega_{ce}/\omega_{pe}\gtrsim
1.2-1.7$, electrons are efficiently accelerated by the inelastic scattering
provided by unstable parallel, electromagnetic z (PEMZ) modes. After
$\omega_{ce}/\omega_{pe}$ reaches $\sim 2$, the electron energy spectra show
nonthermal tails that differ between the shearing and compressing cases. In the
shearing case, the tail resembles a power-law of index $\alpha_s \sim$ 2.9 plus
a high-energy bump reaching $\sim 300$ keV. In the compressing runs, $\alpha_s
\sim$ 3.7 with a spectral break above $\sim 500$ keV. This difference can be
explained by the different temperature evolutions in these two types of
simulations, suggesting a critical role played by the type of anisotropy
driving, $\omega_{ce}/\omega_{pe}$ and the electron temperature in the
efficiency of the acceleration.


  The combination of high frequency vibrations and metallic transport in
graphene makes it a unique material for nano-electromechanical devices. In this
letter, we show that graphene-based nano-electromechanical devices are
extremely well suited for charge pumping, due to the sensitivity of its
transport coefficients to perturbations in electrostatic potential and
mechanical deformations, with the potential for novel small scale devices with
useful applications.


  Any graded restricted simple Lie algebra of Cartan type contains a subalgebra
isomorphic to the Witt algebra over a field of prime characteristic. As some
analogue of study on branching rules for restricted non-classical Lie algebras,
it is shown that each graded restricted simple Lie algebra of Cartan type can
be decomposed into a direct sum of restricted baby Verma modules and simple
modules as an adjoint module over the Witt algebra. In particular, the
composition factors are precisely determined.


  The structure of $k$-diametral point configurations in Minkowski $d$-space is
shown to be closely related to the properties of $k$-antipodal point
configurations in $\mathbb{R}^d$. In particular, the maximum size of
$k$-diametral point configurations of Minkowski $d$-spaces is obtained for
given $k\geq 2$ and $d\geq 2$ generalizing Petty's results (Proc. Am. Math.
Soc. 29: 369-374, 1971) on equilateral sets in Minkowski spaces. Furthermore,
bounds are derived for the maximum size of $k$-diametral point configurations
in Euclidean $d$-space. In the proofs convexity methods are combined with
volumetric estimates and combinatorial properties of diameter graphs.


  The treatment of the $\Delta$-current and its contribution in the exclusive
$^{16}$O$(e,e'pp)^{14}$C and $^{16}$O$(\gamma,pp)^{14}$C knockout reactions are
investigated in combination with the effects of correlations.
  Different parametrizations of the effective $\Delta$-current and different
treatments of correlations in the two-nucleon overlap function are considered.
The results are presented and discussed for a suitable choice of kinematics. It
is found that the investigation of different mutually supplementing kinematics
is necessary to resolve the uncertainties in the theoretical ingredients and
extract clear and unambiguous information on correlations.


  This paper is the first in a series of papers which will address, on a case
by case basis, the special cases of the following rational system in the plane,
labeled system #11. $$x_{n+1}=\frac{\alpha_{1}}{A_{1}+y_{n}},\quad
y_{n+1}=\frac{\alpha_{2}+\beta_{2}x_{n}+\gamma_{2}y_{n}}{A_{2}+B_{2}x_{n}+C_{2}y_{n}},\quad
n=0,1,2,...,$$ with $\alpha_{1},A_{1}>0$ and $\alpha_{2}, \beta_{2},
\gamma_{2}, A_{2}, B_{2}, C_{2}\geq 0$ and $\alpha_{2}+\beta_{2}+\gamma_{2}>0$
and $A_{2}+B_{2}+C_{2}>0$ and nonnegative initial conditions $x_{0}$ and
$y_{0}$ so that the denominator is never zero. In this article we focus on the
special cases which are reducible to the Riccati difference equation.


  In this paper, we advance in investigating a specific set of eigenvectors of
a linearly-independent square root of the identity matrix to obtain a new class
of spin-half mass-dimension one fermions. Such eigenvectors, after an
appropriated dual structure examination, may serve as expansion coefficients of
a local field.


  To make AI systems broadly useful for challenging real-world tasks, we need
them to learn complex human goals and preferences. One approach to specifying
complex goals asks humans to judge during training which agent behaviors are
safe and useful, but this approach can fail if the task is too complicated for
a human to directly judge. To help address this concern, we propose training
agents via self play on a zero sum debate game. Given a question or proposed
action, two agents take turns making short statements up to a limit, then a
human judges which of the agents gave the most true, useful information. In an
analogy to complexity theory, debate with optimal play can answer any question
in PSPACE given polynomial time judges (direct judging answers only NP
questions). In practice, whether debate works involves empirical questions
about humans and the tasks we want AIs to perform, plus theoretical questions
about the meaning of AI alignment. We report results on an initial MNIST
experiment where agents compete to convince a sparse classifier, boosting the
classifier's accuracy from 59.4% to 88.9% given 6 pixels and from 48.2% to
85.2% given 4 pixels. Finally, we discuss theoretical and practical aspects of
the debate model, focusing on potential weaknesses as the model scales up, and
we propose future human and computer experiments to test these properties.


  We consider the problem of maximizing expected utility from consumption in a
constrained incomplete semimartingale market with a random endowment process,
and establish a general existence and uniqueness result using techniques from
convex duality. The notion of asymptotic elasticity of Kramkov and
Schachermayer is extended to the time-dependent case. By imposing no smoothness
requirements on the utility function in the temporal argument, we can treat
both pure consumption and combined consumption/terminal wealth problems, in a
common framework. To make the duality approach possible, we provide a detailed
characterization of the enlarged dual domain which is reminiscent of the
enlargement of $L^1$ to its topological bidual $(L^{\infty})^*$, a space of
finitely-additive measures. As an application, we treat the case of a
constrained It\^ o-process market-model.


  Trusted Execution Environments (TEEs), such as Intel Software Guard
Extensions (SGX), ensure the confidentiality and integrity of user applications
when using cloud computing resources. However, in the multi-party cloud
computing scenario, how to select a Relying Party to verify the TEE of each
party and avoid leaking sensitive data to each other remains an open question.
In this paper, we propose SRAS, an open self-governed remote attestation scheme
with attestation and verification functions for verifying the trustworthiness
of TEEs and computing assets, achieving decentralized unified trusted
attestation and verification platform for multi-party cloud users. In SRAS, we
design a Relying Party enclave, which can form a virtual verifiable network,
capable of local verification on behalf of other participants relying parties
without leaking sensitive data to others. We provide an open-source prototype
implementation of SRAS to facilitate the adoption of this technology by cloud
users or developers.


  We present HST/ACS images and color-magnitude diagrams for 24 nearby galaxies
in and near the constellation of Centaurus with radial velocities V_LG < 550
km/s. Distances are determined based on the luminosities of stars at the tip of
the red giant branch that range from 3.0 Mpc to 6.5 Mpc. The galaxies are
concentrated in two spatially separated groups around Cen A (NGC 5128) and M 83
(NGC 5236). The Cen A group itself has a mean distance of 3.76 +/-0.05 Mpc, a
velocity dispersion of 136 km/s, a mean harmonic radius of 192 kpc, and an
estimated orbital/virial mass of (6.4 - 8.1) x 10^12 M_sun. This elliptical
dominated group is found to have a relatively high mass-to-light ratio: M/L_B =
125 M_sun/L_sun. For the M 83 group we derived a mean distance of 4.79 +/-0.10
Mpc, a velocity dispersion of 61 km/s, a mean harmonic radius of 89 kpc, and
estimated orbital/virial mass of (0.8 - 0.9) x 10^12 M_sun. This spiral
dominated group is found to have a relatively low M/L_B = 34 M_sun/L_sun. The
radius of the zero-velocity surface around Cen A lies at R_0 = 1.40 +/-0.11
Mpc, implying a total mass within R_0 of M_T = (6.0 +/-1.4) x 10^12 M_sun. This
value is in good agreement with the Cen A virial/orbital mass estimates and
provides confirmation of the relatively high M/L_B of this elliptical-dominated
group. The centroids of both the groups, as well as surrounding field galaxies,
have very small peculiar velocities, < 25 km/s, with respect to the local
Hubble flow with H_0 = 68 km/s/Mpc.


  Ne atoms with energies up to 3 keV are diffracted under grazing angles of
incidence from a LiF(001) surface. For a small momentum component of the
incident beam perpendicular to the surface, we observe an increase of the
elastic rainbow angle together with a broadening of the inelastic scattering
profile. We interpret these two effects as the refraction of the atomic wave in
the attractive part of the surface potential. We use a fast, rigorous dynamical
diffraction calculation to find a projectile-surface potential model that
enables a quantitative reproduction of the experimental data for up to ten
diffraction orders. This allows us to extract an attractive potential well
depth of 10.4 meV. Our results set a benchmark for more refined surface
potential models which include the weak Van der Waals region, a long-standing
challenge in the study of atom-surface interactions.


  The solution of the many-body statistical mechanical theory of elasticity
formulated by James and Guth in the 1940s is presented. The remarkable aspect
of the solution is that it gives an elastic free energy that is essentially
equivalent to that developed by Flory over a period of several decades.


  Recent financial disasters have emphasised the need to accurately predict
extreme financial losses and their consequences for the institutions belonging
to a given financial market. The ability of econometric models to predict
extreme events strongly relies on their flexibility to account for the highly
nonlinear and asymmetric dependence observed in financial returns. We develop a
new class of flexible Copula models where the evolution of the dependence
parameters follow a Markov-Switching Generalised Autoregressive Score (SGASC)
dynamics. Maximum Likelihood estimation is consistently performed using the
Inference Functions for Margins (IFM) approach and a version of the
Expectation-Maximisation (EM) algorithm specifically tailored to this class of
models. The SGASC models are then used to estimate the Conditional
Value-at-Risk (CoVaR), which is defined as the VaR of a given asset conditional
on another asset (or portfolio) being in financial distress, and the
Conditional Expected Shortfall (CoES). Our empirical investigation shows that
the proposed SGASC models are able to explain and predict the systemic risk
contribution of several European countries. Moreover, we also find that the
SGASC models outperform competitors using several CoVaR backtesting procedures.


  Talaia is a platform for monitoring social media and digital press. A
configurable crawler gathers content with respect to user defined domains or
topics. Crawled data is processed by means of the EliXa Sentiment Analysis
system. A Django powered interface provides data visualization for a user-based
analysis of the data. This paper presents the architecture of the system and
describes in detail its different components. To prove the validity of the
approach, two real use cases are accounted for: one in the cultural domain and
one in the political domain. Evaluation for the sentiment analysis task in both
scenarios is also provided, showing the capacity for domain adaptation.


  Since 2002, the number of detected blazars at gamma-ray energies above 100
GeV has more than doubled. I study 17 blazars currently known to emit E>100 GeV
gamma rays. Their intrinsic energy spectra are reconstructed by removing
extragalactic background light attenuation effects. Luminosity and spectral
slope in the E>100 GeV region are then compared and correlated among each
other, with X-ray, optical and radio data, and with the estimated black hole
(BH) masses of the respective host galaxies.
  According to expectations from synchrotron self-Compton emission models, a
correlation on the 3.6-sigma significance level between gamma-ray and X-ray
fluxes is found, while correlations between gamma-ray and optical/radio fluxes
are less pronounced. Further, a general hardening of the E>100 GeV spectra with
increasing gamma-ray luminosity is observed. This goes in line with a
correlation of the gamma-ray luminosity and the synchrotron peak frequency,
which is also seen. Tests for possible selection effects reveal a hardening of
the spectra with increasing redshift. The gamma-ray emission might depend on
the mass of the central BH. The studied blazars show no correlation of the BH
masses with the spectral index and the luminosity in the E>100 GeV region.
  Also temporal properties of the X-ray and E>100 GeV gamma-ray flux are
considered. No general trends are found, except that the blazars with the most
massive BHs do not show particularly high duty cycles. In general, VHE flare
time-scales are not found to scale with the BH mass.
  As a specific application of the luminosity study, a constraint for the still
undetermined redshift of the blazar PG 1553+113 is discussed.


  We adopt the integral definition of the fractional Laplace operator and study
an optimal control problem on Lipschitz domains that involves a fractional
elliptic partial differential equation (PDE) as state equation and a control
variable that enters the state equation as a coefficient; pointwise constraints
on the control variable are considered as well. We establish the existence of
optimal solutions and analyze first and, necessary and sufficient, second order
optimality conditions. Regularity estimates for optimal variables are also
analyzed. We develop two finite element discretization strategies: a
semidiscrete scheme in which the control variable is not discretized, and a
fully discrete scheme in which the control variable is discretized with
piecewise constant functions. For both schemes, we analyze the convergence
properties of discretizations and derive error estimates.


  At high temperatures a four dimensional field theory is reduced to a three
dimensional field theory. In this letter we consider the $\phi^4$ theory whose
parameters are chosen so that a thermal phase transition occurs at a high
temperature. Using the known properties of the three dimensional theory, we
derive a non-trivial correction to the critical temperature.


  This paper presents how techniques from natural language processing can be
used to examine the sentiment trajectories of gang-related drill music in the
United Kingdom (UK). This work is important because key public figures are
loosely making controversial linkages between drill music and recent
escalations in youth violence in London. Thus, this paper examines the dynamic
use of sentiment in gang-related drill music lyrics. The findings suggest two
distinct sentiment use patterns and statistical analyses revealed that lyrics
with a markedly positive tone attract more views and engagement on YouTube than
negative ones. Our work provides the first empirical insights into the language
use of London drill music, and it can, therefore, be used in future studies and
by policymakers to help understand the alleged drill-gang nexus.


  We present JWST/NIRCam F187N, F200W, F405N and F410M direct imaging data of
the disk surrounding SAO 206462. Previous images show a very structured disk,
with a pair of spiral arms thought to be launched by one or more external
perturbers. The spiral features are visible in three of the four filters, with
the non-detection in F410M due to the large detector saturation radius. We
detect with a signal-to-noise ratio of 4.4 a companion candidate (CC1) that, if
on a coplanar circular orbit, would orbit SAO 206462 at a separation of
$\sim300$ au, $2.25\sigma$ away from the predicted separation for the driver of
the eastern spiral. According to the BEX models, CC1 has a mass of
$M_\mathrm{CC1}=0.8\pm0.3~M_\mathrm{J}$. No other companion candidates were
detected. At the location predicted by simulations of both spirals generated by
a single massive companion, the NIRCam data exclude objects more massive than
$\sim2.2~M_\mathrm{J}$ assuming the BEX evolutionary models. In terms of
temperatures, the data are sensitive to objects with
$T_{\text{eff}}\sim650-850$ K, when assuming planets emit like blackbodies
($R_\mathrm{p}$ between 1 and $3 R_\mathrm{J}$). From these results, we
conclude that if the spirals are driven by gas giants, these must be either
cold or embedded in circumplanetary material. In addition, the NIRCam data
provide tight constraints on ongoing accretion processes. In the low extinction
scenario we are sensitive to mass accretion rates of the order
$\dot{M}\sim10^{-9} M_\mathrm{J}$ yr$^{-1}$. Thanks to the longer wavelengths
used to search for emission lines, we reach unprecedented sensitivities to
processes with $\dot{M}\sim10^{-7} M_\mathrm{J}$ yr$^{-1}$ even towards highly
extincted environments ($A_\mathrm{V}\approx50$~mag).


  The dynamics of the $\eta\to 3\pi^0$ decay have been studied with the Crystal
Ball multiphoton spectrometer and the TAPS calorimeter. Bremsstrahlung photons
produced by the 1.5-GeV electron beam of the Mainz microtron MAMI-C and tagged
by the Glasgow photon spectrometer were used for $\eta$-meson production. The
analysis of $3 \times 10^6$ $\gamma p \to \eta p \to 3\pi^0 p \to 6\gamma p$
events yields the value $\alpha=-0.032\pm0.003$ for the $\eta\to 3\pi^0$ slope
parameter, which agrees with the majority of recent experimental results and
has the smallest uncertainty. The $\pi^0\pi^0$ invariant-mass spectrum was
investigated for the occurrence of a cusplike structure in the vicinity of the
$\pi^+\pi^-$ threshold. The observed effect is small and does not affect our
measured value for the slope parameter.


  The causal structure of a unitary transformation is the set of relations of
possible influence between any input subsystem and any output subsystem. We
study whether such causal structure can be understood in terms of compositional
structure of the unitary. Given a quantum circuit with no path from input
system $A$ to output system $B$, system $A$ cannot influence system $B$.
Conversely, given a unitary $U$ with a no-influence relation from input $A$ to
output $B$, it follows from [B. Schumacher and M. D. Westmoreland, Quantum
Information Processing 4 no. 1, (Feb, 2005)] that there exists a circuit
decomposition of $U$ with no path from $A$ to $B$. However, as we argue, there
are unitaries for which there does not exist a circuit decomposition that makes
all causal constraints evident simultaneously. To address this, we introduce a
new formalism of `extended circuit diagrams', which goes beyond what is
expressible with quantum circuits, with the core new feature being the ability
to represent direct sum structures in addition to sequential and tensor product
composition. A causally faithful extended circuit decomposition, representing a
unitary $U$, is then one for which there is a path from an input $A$ to an
output $B$ if and only if there actually is influence from $A$ to $B$ in $U$.
We derive causally faithful extended circuit decompositions for a large class
of unitaries, where in each case, the decomposition is implied by the unitary's
respective causal structure. We hypothesize that every finite-dimensional
unitary transformation has a causally faithful extended circuit decomposition.


  We present F775W-F850LP (rest-frame UV-U) and F850LP-F160W (rest-frame U-R)
colour gradients for a sample of 17 elliptical galaxies morphologically
selected in the cluster XMMU J2235.3-2557 at $z$=1.39. We detected significant
negative (redder inwards) U-R colour gradients in $\sim$70 per cent of the
galaxies and flat gradients for the remaining ones. On the other hand, the UV-U
gradients are significant positive (bluer inwards) for $\sim$80 per cent of the
galaxies and flat for the remaining ones. Using stellar population synthesis
models, we found that the behaviour of the two colour gradients cannot be
simultaneously explained by a radial variation of age, metallicity and/or dust.
The observed U-R gradients are consistent with a metallicity gradient (mean
value $\nabla_{Z} =-0.4$) in agreement with the one observed in the local
elliptical galaxies. The positive UV-U gradients cannot be explained with age
or metallicity variations and imply an excess of UV emission towards the
galaxies' central regions.This excess calls into question mechanisms able to
efficiently produce UV emission. The data require either steady weak star
formation (< 1 M$_\odot$ yr$^{-1}$) or an He-rich population in the cores of
these galaxies in order to simultaneously reproduce both the colour gradients.
On the contrary, the presence of a QSO cannot account for the observed UV
excess on its own. We discuss these hypotheses on the basis of current
observations and available models.


  Wide binaries, particularly in large numbers and as free from selection
biases as possible, constitute a largely overlooked tool for studying the
Galaxy. The goal of this review is to highlight the potential inherent to large
samples of field wide binaries for research on problems as varied as star
formation in the early Galaxy, the nature of halo dark matter, the evolution of
the stellar halo, new geometric distances, metallicities, masses, and ages of
field stars and white dwarfs, and much more. Using the Revised NLTT as an
illustrative example, I review the main steps in the assembly of a large
catalog of wide binaries useful for multiple applications. The capability of
cleanly separating between the Galactic disk and halo populations using good
colors and proper motions is emphasized. The critical role of large surveys for
research on wide binaries as well as for the better understanding of the Galaxy
in general is stressed throughout. Finally, I point out the potential for
assembling new samples of wide binaries from available proper-motion surveys,
and report on current efforts of using the SDSS towards this goal.


  Since 1996, the CAT experiment, operating at the THEMIS site (French
Pyrenees), has been collecting Very High Energy (VHE) gamma-ray data from the
Crab. The temporal analysis of photon arrival times folded with the pulsar
parameters did not reveal any significant pulsation. The upper limit of a
steady pulsed flux over the 102.7 hours of observation is 1.5 10^-12
cm^-2.s^-1, 3.0 10^-13 cm^-2.s^-1 and 5.4 10^-14 cm^-2.s^-1 above 250 GeV, 1
TeV and 5 TeV, respectively. These results put stringent constraints on the
models of high energy pulsar electrodynamics.


  We report the growth of $\alpha-Ga_2O_3$ on $m$-plane $Al_2O_3$ by
conventional plasma-assisted molecular-beam epitaxy (MBE) and In-mediated
metal-oxide-catalyzed epitaxy (MOCATAXY). We report a growth-rate-diagram for
$\alpha-Ga_2O_3$ (10-10), and observe (i) a growth rate increase, (ii) an
expanded growth window, and (iii) reduced out-of-lane mosaic spread when
MOCATAXY is employed for the growth of $\alpha-Ga_2O_3$. Through the use of
In-mediated catalysis, growth rates over $0.2\,\mu\text{m}\,\text{hr}^{-1}$ and
rocking curves with full width at half maxima of $\Delta\omega \approx
0.45^{\circ}$ are achieved. Faceting is observed along the $\alpha-Ga_2O_3$
film surface and is explored through scanning transmission electron microscopy.


  In this work we consider theoretically the problem of a Newtonian droplet
moving in an otherwise quiescent infinite viscoelastic fluid under the
influence of an externally applied temperature gradient. The outer fluid is
modelled by the Oldroyd-B equation, and the problem is solved for small
Weissenberg and Capillary numbers in terms of a double perturbation expansion.
  We assume microgravity conditions and neglect the convective transport of
energy and momentum. We derive expressions for the droplet migration speed and
its shape in terms of the properties of both fluids. In the absence of shape
deformation, the droplet speed decreases monotonically for sufficiently viscous
inner fluids, while for fluids with a smaller inner-to-outer viscosity ratio,
the droplet speed first increases and then decreases as a function of the
Weissenberg number. For small but finite values of the Capillary number, the
droplet speed behaves monotonically as a function of the applied temperature
gradient for a fixed ratio of the Capillary and Weissenberg numbers. We
demonstrate that this behaviour is related to the polymeric stresses deforming
the droplet in the direction of its migration, while the associated changes in
its speed are Newtonian in nature, being related to a change in the droplet's
hydrodynamic resistance and its internal temperature distribution. When
compared to the results of numerical simulations, our theory exhibits a good
predictive power for sufficiently small values of the Capillary and Weissenberg
numbers.


  We develop a conformal-field theory approach for investigation of the quantum
charge-, heat- and thermoelectric- transport through a quantum impurity fine
tuned to a non-Fermi liquid regime. The non-Fermi-liquid operational mode is
associated with the overscreened spin Kondo effect and controlled by the number
of orbital channels. The universal low-temperature scaling and critical
exponents for Seebeck and Peltier coefficients are investigated for the
multichannel geometry. We derive and analyze the universal dependence of the
thermoelectric coefficients on the number of orbital channels. We discuss the
universality of Lorenz ratio and power factor beyond the Fermi Liquid paradigm.
Different methods of verifying our findings based on the recent experiments are
proposed.


  The Sorites paradox is the name of a class of paradoxes that arise when vague
predicates are considered. Vague predicates lack sharp boundaries in extension
and is therefore not clear exactly when such predicates apply.
  Several approaches to this class of paradoxes have been made since its first
formulation by Eubulides of Miletus in the IV century BCE. In this paper I
survey some of these approaches and point out some of the criticism that these
approaches have received. A new approach that uses tools from nonstandard
analysis to model the paradox is proposed.


  In supersymmetric models, the well-known tension between naturalness and
experimental constraints is relieved if the squarks and sleptons of the first
two generations are superheavy, with masses of order 10 TeV, and all other
superpartners are light, with masses of order 1 TeV. We show that even if all
scalar masses and trilinear A parameters are of order 10 TeV at some high
scale, a mass-squared hierarchy of order 400 may be generated dynamically
through renormalization group evolution. The required high energy relations are
consistent with grand unification, or, alternatively, may be realized in
moduli-dominated supersymmetry-breaking scenarios.


  Enhancing sampling and analyzing simulations are central issues in molecular
simulation. Recently, we introduced PLUMED, an open-source plug-in that
provides some of the most popular molecular dynamics (MD) codes with
implementations of a variety of different enhanced sampling algorithms and
collective variables (CVs). The rapid changes in this field, in particular new
directions in enhanced sampling and dimensionality reduction together with new
hardwares, require a code that is more flexible and more efficient. We
therefore present PLUMED 2 here - a complete rewrite of the code in an
object-oriented programming language (C++). This new version introduces greater
flexibility and greater modularity, which both extends its core capabilities
and makes it far easier to add new methods and CVs. It also has a simpler
interface with the MD engines and provides a single software library containing
both tools and core facilities. Ultimately, the new code better serves the
ever-growing community of users and contributors in coping with the new
challenges arising in the field.


  Multivariate Functional Principal Component Analysis (MFPCA) is a valuable
tool for exploring relationships and identifying shared patterns of variation
in multivariate functional data. However, controlling the roughness of the
extracted Principal Components (PCs) can be challenging. This paper introduces
a novel approach called regularized MFPCA (ReMFPCA) to address this issue and
enhance the smoothness and interpretability of the multivariate functional PCs.
ReMFPCA incorporates a roughness penalty within a penalized framework, using a
parameter vector to regulate the smoothness of each functional variable. The
proposed method generates smoothed multivariate functional PCs, providing a
concise and interpretable representation of the data. Extensive simulations and
real data examples demonstrate the effectiveness of ReMFPCA and its superiority
over alternative methods. The proposed approach opens new avenues for analyzing
and uncovering relationships in complex multivariate functional datasets.


  In this paper, we consider an unconstrained optimization model where the
objective is a sum of a large number of possibly nonconvex functions, though
overall the objective is assumed to be smooth and convex. Our bid to solving
such model uses the framework of cubic regularization of Newton's method. As
well known, the crux in cubic regularization is its utilization of the Hessian
information, which may be computationally expensive for large-scale problems.
To tackle this, we resort to approximating the Hessian matrix via sub-sampling.
In particular, we propose to compute an approximated Hessian matrix by either
\textit{uniformly}\/ or \textit{non-uniformly}\/ sub-sampling the components of
the objective. Based upon such sampling strategy, we develop accelerated
adaptive cubic regularization approaches and provide theoretical guarantees on
global iteration complexity of $O(\epsilon^{-1/3})$ with high probability,
which matches that of the original accelerated cubic regularization methods
\cite{Jiang-2017-Unified} using the \textit{full}\/ Hessian information.
Interestingly, we show that in the worst case scenario our algorithm still
achieves an $O\left(\log(\epsilon^{-1})\epsilon^{-5/6}\right)$ iteration
complexity bound. The performances of the proposed methods on the regularized
logistic regression problems show a clear effect of acceleration in terms of
the epoch counts on several real data sets.


  A new approach to bosonization in relativistic field theories and many-body
systems, based on the use of fermionic composites as integration variables in
the Berezin integral defining the partition function of the system, is tested.
The method is applied to the study of a simplified version of the BCS model.


  Data management systems have traditionally been designed to support either
long-running analytics queries or short-lived transactions, but an increasing
number of applications need both. For example, online games, socio-mobile apps,
and e-commerce sites need to not only maintain operational state, but also
analyze that data quickly to make predictions and recommendations that improve
user experience. In this paper, we present Minuet, a distributed, main-memory
B-tree that supports both transactions and copy-on-write snapshots for in-situ
analytics. Minuet uses main-memory storage to enable low-latency transactional
operations as well as analytics queries without compromising transaction
performance. In addition to supporting read-only analytics queries on
snapshots, Minuet supports writable clones, so that users can create branching
versions of the data. This feature can be quite useful, e.g. to support complex
"what-if" analysis or to facilitate wide-area replication. Our experiments show
that Minuet outperforms a commercial main-memory database in many ways. It
scales to hundreds of cores and TBs of memory, and can process hundreds of
thousands of B-tree operations per second while executing long-running scans.


  This paper presents a grammar and style checker demonstrator for Spanish and
Greek native writers developed within the project GramCheck. Besides a brief
grammar error typology for Spanish, a linguistically motivated approach to
detection and diagnosis is presented, based on the generalized use of PROLOG
extensions to highly typed unification-based grammars. The demonstrator,
currently including full coverage for agreement errors and certain
head-argument relation issues, also provides correction by means of an
analysis-transfer-synthesis cycle. Finally, future extensions to the current
system are discussed.


  Flooding is a destructive and dangerous hazard and climate change appears to
be increasing the frequency of catastrophic flooding events around the world.
Physics-based flood models are costly to calibrate and are rarely generalizable
across different river basins, as model outputs are sensitive to site-specific
parameters and human-regulated infrastructure. In contrast, statistical models
implicitly account for such factors through the data on which they are trained.
Such models trained primarily from remotely-sensed Earth observation data could
reduce the need for extensive in-situ measurements. In this work, we develop
generalizable, multi-basin models of river flooding susceptibility using
geographically-distributed data from the USGS stream gauge network. Machine
learning models are trained in a supervised framework to predict two measures
of flood susceptibility from a mix of river basin attributes, impervious
surface cover information derived from satellite imagery, and historical
records of rainfall and stream height. We report prediction performance of
multiple models using precision-recall curves, and compare with performance of
naive baselines. This work on multi-basin flood prediction represents a step in
the direction of making flood prediction accessible to all at-risk communities.


  Global models are trained to be as generalizable as possible, with user
invariance considered desirable since the models are shared across multitudes
of users. As such, these models are often unable to produce personalized
responses for individual users, based on their data. Contrary to widely-used
personalization techniques based on few-shot learning, we propose
UserIdentifier, a novel scheme for training a single shared model for all
users. Our approach produces personalized responses by adding fixed,
non-trainable user identifiers to the input data. We empirically demonstrate
that this proposed method outperforms the prefix-tuning based state-of-the-art
approach by up to 13%, on a suite of sentiment analysis datasets. We also show
that, unlike prior work, this method needs neither any additional model
parameters nor any extra rounds of few-shot fine-tuning.


  The circuit arrangement of the proposed coaxial ring cyclotron (CRC) is
described, and its main advantages, such as simple injection technique, several
injected beams summation option, high efficiency, are considered. The proposed
proton accelerator is a perspective machine for the solution of the main
problems of the present day nuclear power engineering as well as for the
next-generation nuclear power plants, representing a combination of subcritical
reactors and particle accelerators. The possibility of installation of CRCs
into ring accelerators with an average diameter from 60 to $100m$, e.g., the
Yerevan electron synchrotron, is considered.


  Gaussian random fields over infinite-dimensional Hilbert spaces require the
definition of appropriate covariance operators. The use of elliptic PDE
operators to construct covariance operators allows to build on fast PDE solvers
for manipulations with the resulting covariance and precision operators.
However, PDE operators require a choice of boundary conditions, and this choice
can have a strong and usually undesired influence on the Gaussian random field.
We propose two techniques that allow to ameliorate these boundary effects for
large-scale problems. The first approach combines the elliptic PDE operator
with a Robin boundary condition, where a varying Robin coefficient is computed
from an optimization problem. The second approach normalizes the pointwise
variance by rescaling the covariance operator. These approaches can be used
individually or can be combined. We study properties of these approaches, and
discuss their computational complexity. The performance of our approaches is
studied for random fields defined over simple and complex two- and
three-dimensional domains.


  Nano structures, namely, nano rings and nanoparticles, comprising two
dimensional, crystalline gold atomic discs were produced on a sapphire
substrate. Nano rings revealed several remarkable properties, namely, an
apparent spatial orientation memory register, an apparent programmed homing
instinct and action based on that instinct, usually observed only in living,
biological systems. Momentary application of 100 nN force on a nanostructure,
mother led every mother within the entire scanner area to increase its volume
and create several daughter replicas. Over time, without the influence of any
applied external force or stimulus, each daughter, of its own volition,
transported itself back to its mother and recreated its original form. The
results strongly implied temporal and spatial synchronization between the
daughters and their respective mothers. The targeted movement of the daughters
towards their mothers implied the existence of a special, yet unidentified new
force. Momentary application of a weak force on a gold nanoparticle resulted in
the spontaneous transformation of each nanoparticle into a complex and robot
like Dalek 3dimensional form. Without the application of any additional
external force or stimulus, we observed a remarkable display of oscillatory
transformation between the robot-like forms and their mother nanoparticles
lasting over 26 hours. The robot-like structures seem to replicate identical
copies of themselves.


  In \cite{WeiWu22-3} (J.Geom.Anal.32, 199(2022)), we classified HCMU surfaces
in 3-dimensional Euclidean space as Weingarten surfaces by holomorphic
functions. In this paper, using a totally different method from
\cite{WeiWu22-3}, we will classify HCMU surfaces in 3-dimensional space forms
as Weingarten surfaces. Moreover we will give a criteria of a Weingarten
surface which is also an HCMU surface.


  High-spatial resolution near-infrared (NIR) images of the central 24 x 24
arcsec^2 (~ 2 x 2 kpc^2) of the elliptical galaxy NGC 1052 reveal a total of 25
compact sources randomly distributed in the region. Fifteen of them exhibit
Halpha luminosities an order of magnitude above the estimate for an evolved
population of extreme horizontal branch stars. Their Halpha equivalent widths
and optical-to-NIR spectral energy distributions are consistent with them being
young stellar clusters aged < 7 Myr. We consider this to be the first direct
observation of spatially resolved star-forming regions in the central
kiloparsecs of an elliptical galaxy. The sizes of these regions are ~< 11 pc
and their median reddening is E(B - V) ~ 1 mag. According to previous works,
NGC 1052 may have experienced a merger event about 1 Gyr ago. On the assumption
that these clusters are spreaded with similar density over the whole galaxy,
the fraction of galaxy mass (5 x 10^{-5}) and rate of star formation (0.01
Msun/yr) involved, suggest the merger event as the possible cause for the star
formation we see today.


  A class of (1+2)-dimensional diffusion-convection equations (nonlinear
Kolmogorov equations) with time-dependent coefficients is studied with Lie
symmetry point of view. The complete group classification is achieved using a
gauging of arbitrary elements (i.e. via reducing the number of variable
coefficients) with the application of equivalence transformations. Two possible
gaugings are discussed in detail in order to show how equivalence groups serve
in making the optimal choice.


  This work tackles a significant challenge in dynamo theory: the possibility
of long-term amplification and maintenance of an axisymmetric magnetic field.
We introduce a novel model that allows for non-trivial axially-symmetric
steady-state solutions for the magnetic field, particularly when the dynamo
operates primarily within a "nearly-spherical" toroidal volume inside a fluid
shell surrounding a solid core. In this model, Ohm's law is generalized to
include the restoring friction force, which aligns the velocity of the shell
with the rotational speed of the inner core and outer mantle. Our findings
reveal that, in this context, Cowling's theorem and the neutral point argument
are modified, leading to magnetic energy growth for a suitable choice of
toroidal flow. The global equilibrium magnetic field that emerges from our
model exhibits a dipolar character.


  A molecular level understanding of the properties of electroactive vanadium
species in aqueous solution is crucial for enhancing the performance of
vanadium redox flow batteries (RFB). Here, we employ Car-Parrinello molecular
dynamics (CPMD) simulations based on density functional theory to investigate
the hydration structures, first hydrolysis reaction and diffusion of aqueous
V$^{2+}$, V$^{3+}$, VO$^{2+}$, and VO$_2^+$ ions at 300 K. The results indicate
that the first hydration shell of both V$^{2+}$ and V$^{3+}$ contains six water
molecules, while VO$^{2+}$ is coordinated to five and VO$_2^+$ to three water
ligands. The first acidity constants (p$K_\mathrm{a}$) estimated using
metadynamics simulations are 2.47, 3.06 and 5.38 for aqueous V$^{3+}$, VO$_2^+$
and VO$^{2+}$, respectively, while V$^{2+}$ is predicted to be a fairly weak
acid in aqueous solution with a p$K_\mathrm{a}$ value of 6.22. We also show
that the presence of chloride ions in the first coordination sphere of the
aqueous VO$_2^+$ ion has a significant impact on water hydrolysis leading to a
much higher p$K_\mathrm{a}$ value of 4.8. This should result in a lower
propensity of aqueous VO$_2^+$ for oxide precipitation reaction in agreement
with experimental observations for chloride-based electrolyte solutions. The
computed diffusion coefficients of vanadium species in water at room
temperature are found to increase as V$^{3+}$ $<$ VO$_2^+$ $<$ VO$^{2+}$ $<$
V$^{2+}$ and thus correlate with the simulated hydrolysis constants, namely,
the higher the p$K_\mathrm{a}$ value, the greater the diffusion coefficient.


  Though many compilation and runtime systems have been developed for DNNs in
recent years, the focus has largely been on static DNNs. Dynamic DNNs, where
tensor shapes and sizes and even the set of operators used are dependent upon
the input and/or execution, are becoming common. This paper presents SoD$^2$, a
comprehensive framework for optimizing Dynamic DNNs. The basis of our approach
is a classification of common operators that form DNNs, and the use of this
classification towards a Rank and Dimension Propagation (RDP) method. This
framework statically determines the shapes of operators as known constants,
symbolic constants, or operations on these. Next, using RDP we enable a series
of optimizations, like fused code generation, execution (order) planning, and
even runtime memory allocation plan generation. By evaluating the framework on
10 emerging Dynamic DNNs and comparing it against several existing systems, we
demonstrate both reductions in execution latency and memory requirements, with
RDP-enabled key optimizations responsible for much of the gains. Our evaluation
results show that SoD$^2$ runs up to $3.9\times$ faster than these systems
while saving up to $88\%$ peak memory consumption.


  We discuss various topics in the theory of heavy baryon decays. Among these
are recent applications of the Relativistic Three Quark Model to semileptonic,
nonleptonic, one-pion and one-photon transitions among heavy baryons, new
higher order perturbative results on the correlator of two heavy baryon
currents and on the semi-inclusive decay $\Lambda_b \to X_c + D_s^{(*)-}$.


  We introduce a novel method for analyzing person-to-person content influence
on Twitter. Using an Ego-Alter framework and Granger Causality, we examine
President Donald Trump (the Ego) and the people he retweets (Alters) as a case
study. We find that each Alter has a different scope of influence across
multiple topics, different magnitude of influence on a given topic, and the
magnitude of a single Alter's influence can vary across topics. This work is
novel in its focus on person-to-person influence and content-based influence.
Its impact is two-fold: (1) identifying "canaries in the coal mine" who could
be observed by misinformation researchers or platforms to identify
misinformation narratives before super-influencers spread them to large
audiences, and (2) enabling digital marketing targeted toward upstream Alters
of super-influencers.


  We study the regularity of the free boundary in the obstacle problem for the
fractional Laplacian under the assumption that the obstacle $\varphi$ satisfies
$\Delta \varphi\leq 0$ near the contact region. Our main result establishes
that the free boundary consists of a set of regular points, which is known to
be a $(n-1)$-dimensional $C^{1,\alpha}$ manifold by the results in \cite{CSS},
and a set of singular points, which we prove to be contained in a union of
$k$-dimensional $C^1$-submanifold, $k=0,\ldots,n-1$.
  Such a complete result on the structure of the free boundary was known only
in the case of the classical Laplacian \cite{C-obst1,C-obst2}, and it is new
even for the Signorini problem (which corresponds to the particular case of the
$\frac12$-fractional Laplacian). A key ingredient behind our results is the
validity of a new non-degeneracy condition $\sup_{B_r(x_0)}(u-\varphi)\geq
c\,r^2$, valid at all free boundary points $x_0$.


  Context. Bubble N107 was discovered in the infrared emission of dust in the
Galactic Plane observed by the Spitzer Space Telescope (GLIMPSE survey: l ~
51.0 deg, b ~ 0.1 deg). The bubble represents an example of shell-like
structures found all over the Milky Way Galaxy.
  Aims. We aim to analyse the atomic and molecular components of N107, as well
as its radio continuum emission. With the help of numerical simulations, we aim
to estimate the bubble age and other parameters which cannot be derived
directly from observations.
  Methods. From the observations of the HI (I-GALFA) and 13CO (GRS) lines we
derive the bubble's kinematical distance and masses of the atomic and molecular
components. With the algorithm DENDROFIND, we decompose molecular material into
individual clumps. From the continuum observations at 1420 MHz (VGPS) and 327
MHz (WSRT), we derive the radio flux density and the spectral index. With the
numerical code ring, we simulate the evolution of stellar-blown bubbles similar
to N107.
  Results. The total HI mass associated with N107 is 5.4E3 Msun. The total mass
of the molecular component (a mixture of cold gasses of H2, CO, He and heavier
elements) is 1.3E5 Msun, from which 4.0E4 Msun is found along the bubble
border. We identified 49 molecular clumps distributed along the bubble border,
with the slope of the clump mass function of -1.1. The spectral index of -0.30
of a strong radio source located apparently within the bubble indicates
nonthermal emission, hence part of the flux likely originates in a supernova
remnant, not yet catalogued. The numerical simulations suggest N107 is likely
less than 2.25 Myr old. Since first supernovae explode only after 3 Myr or
later, no supernova remnant should be present within the bubble. It may be
explained if there is a supernova remnant in the direction towards the bubble,
however not associated with it.


  We generalise the Karrass-Pietrowski-Solitar and the Nielsen realisation
theorems from the setting of free groups to that of free products. As a result,
we obtain a fixed point theorem for finite groups of outer automorphisms acting
on the relative free splitting complex of Handel--Mosher and on the outer space
of a free product of Guirardel--Levitt, as well as a relative version of the
Nielsen realisation theorem, which in the case of free groups answers a
question of Karen Vogtmann. We also prove Nielsen realisation for limit groups,
and as a byproduct obtain a new proof that limit groups are CAT($0$). The
proofs rely on a new version of Stallings' theorem on groups with at least two
ends, in which some control over the behaviour of virtual free factors is
gained.


  We show that reasonably well behaved 3d and 4D TQFts must contain certain
algebraic structures. In 4D, we find both Hopf categories and trialgebras.


  We analyse high-field current fluctuations in metallic systems by direct
mapping of the Fermi-liquid correlations to the semiclassical nonequilibrium
state. We give three applications. First, for bulk conductors, we show that
there is a unique nonequilibrium analogue to the fluctuation-dissipation
theorem for thermal noise. With it, we calculate suppression of the excess
hot-electron term by Pauli exclusion. Second, in the degenerate regime, we
argue that shot noise and thermal noise are incommensurate. They cannot be
connected by a smooth, universal interpolation formula. This follows from their
contrasting responses to Coulomb screening. We propose an experiment to test
this mismatch. Third, we carry out an exact model calculation of high-field
shot noise in narrow mesoscopic wires. We show that a distinctive mode of
suppression arises from the structure of the semiclassical Boltzmann equation
in two and three dimensions. In one dimension such a mode does not exist.


  Low-frequency Alfven-wave turbulence causes ion trajectories to become
chaotic, or "stochastic," when the turbulence amplitude is sufficiently large.
Stochastic orbits enable ions to absorb energy from the turbulence, increasing
the perpendicular ion temperature even when the fluctuation frequencies are too
small for a cyclotron resonance to occur. In this paper, an analytic expression
for the stochastic heating rate is used in conjunction with an observationally
constrained turbulence model to obtain an analytic formula for the
perpendicular ion temperature as a function of heliocentric distance r, ion
mass, and ion charge in coronal holes for values of r between 2 and 15 solar
radii (Rs). The resulting temperature profiles provide a good fit to
observations of protons and OVI ions at 2Rs < r < 3Rs from the Ultraviolet
Coronagraph Spectrometer (UVCS). Stochastic heating also offers a natural
explanation for several detailed features of the UVCS observations, including
the preferential and anisotropic heating of minor ions, the rapid radial
increase in the OVI temperature between 1.6Rs and 1.9Rs, and the abrupt
flattening of the OVI temperature profile as r increases above 1.9Rs.


  In this paper the problem of information dissemination in Mobile Ad-hoc
Networks (MANET) is studied. The problem is to disseminate a piece of
information, initially held by a distinguished source node, to all nodes in a
set defined by some predicate. We use a model of MANETs that is well suited for
dynamic networks and opportunistic communication. In this model nodes are
placed in a plane, in which they can move with bounded speed, and communication
between nodes occurs over a collision-prone single channel. In this setup
informed and uninformed nodes can be disconnected for some time (bounded by a
parameter alpha), but eventually some uninformed node must become neighbor of
an informed node and remain so for some time (bounded by a parameter beta). In
addition, nodes can start at different times, and they can crash and recover.
Under the above framework, we show negative and positive results for different
types of randomized protocols, and we put those results in perspective with
respect to previous deterministic results.


  LiteBIRD, a forthcoming JAXA mission, aims to accurately study the microwave
sky within the 40-400 GHz frequency range divided into 15 distinct nominal
bands. The primary objective is to constrain the CMB inflationary signal,
specifically the primordial B-modes. LiteBIRD targets the CMB B-mode signal on
large angular scales, where the primordial inflationary signal is expected to
dominate, with the goal of reaching a tensor-to-scalar ratio sensitivity of
$\sigma_r\sim0.001$. LiteBIRD frequency bands will be split among three
telescopes, with some overlap between telescopes for better control of
systematic effects. Here we report on the development status of the detector
arrays for the Low Frequency Telescope (LFT), which spans the 34-161 GHz range,
with 12 bands subdivided between four types of trichroic pixels consisting of
lenslet-coupled sinuous antennas. The signal from the antenna is bandpass
filtered and sensed by AlMn Transition-Edge Sensors (TES). We provide an update
on the status of the design and development of LiteBIRD's LFT LF1 (40-60-78
GHz), LF2 (50-68-89 GHz) pixels. We discuss design choices motivated by
LiteBIRD scientific goals. In particular we focus on the details of the
optimization of the design parameters of the sinuous antenna, on-chip bandpass
filters, cross-under and impedance transformers and all the RF components that
define the LF1 and LF2 pixel detection chain. We present this work in the
context of the technical challenges and physical constraints imposed by the
finite size of the instrument.


  Using 3D N-body simulations we analyse an onset of the bar in cuspy models,
and argue that role of swing amplification is twofold. Amplified shot noise due
to disc discreteness hampers bar formation, while induced resonance
perturbations allow bar amplitude to overcome shots. A bar pattern speed and a
growth rate obtained in N-body simulations agree well with global mode
analysis.


  We show how the Shannon entropy function H(p,q)is expressible as a linear
combination of other Shannon entropy functions involving quotients of
polynomials in p,q of degree n for any given positive integer n. An application
to cryptographic keys is presented.


  We study the integral representation of $\Gamma$-limits of $p$-coercive
integral functionals of the calculus of variations in the spirit of
\cite{dalmaso-modica86}. We use infima of local Dirichlet problems to
characterize the limit integrands. Applications to homogenization and
relaxation are given.


  We investigate the theoretical stability of the predictions of tri-bimaximal
neutrino mixing with respect to third family wave-function corrections. Such
third family wave-function corrections can arise from either the canonical
normalisation of the kinetic terms or renormalisation group running effects. At
leading order both sorts of corrections can be subsumed into a single universal
parameter. For hierarchical neutrinos, this leads to a new testable lepton
mixing sum rule 's = r cos delta + 2/3 a' (where s, r, a describe the
deviations of solar, reactor and atmospheric mixing angles from their
tri-bimaximal values, and 'delta' is the observable Dirac CP phase) which is
stable under all leading order third family wave-function corrections, as well
as Cabibbo-like charged lepton mixing effects.


  A discarded motherboard based eco-friendly copper catalyst has been
programmed to replace the industrially used tin based catalyst DBTDL. The
catalyst has been characterized by UV-Vis spectroscopy, FT-IR and TEM. Using
the catalyst reaction conditions is optimized and under the optimized
condition, both polyurethane and polyurethane foam are prepared, thus proving
the generality of the catalyst to be used in industries. A possible mechanism
has also been proposed.


  We present a diagrammatic technique for calculating the free energy of the
Hermitian one-matrix model to all orders of 1/N expansion in the case where the
limiting eigenvalue distribution spans arbitrary (but fixed) number of disjoint
intervals (curves).


  Embedding methods have demonstrated robust performance on the task of link
prediction in knowledge graphs, by mostly encoding entity relationships. Recent
methods propose to enhance the loss function with a literal-aware term. In this
paper, we propose KGA: a knowledge graph augmentation method that incorporates
literals in an embedding model without modifying its loss function. KGA
discretizes quantity and year values into bins, and chains these bins both
horizontally, modeling neighboring values, and vertically, modeling multiple
levels of granularity. KGA is scalable and can be used as a pre-processing step
for any existing knowledge graph embedding model. Experiments on legacy
benchmarks and a new large benchmark, DWD, show that augmenting the knowledge
graph with quantities and years is beneficial for predicting both entities and
numbers, as KGA outperforms the vanilla models and other relevant baselines.
Our ablation studies confirm that both quantities and years contribute to KGA's
performance, and that its performance depends on the discretization and binning
settings. We make the code, models, and the DWD benchmark publicly available to
facilitate reproducibility and future research.


  In a previous paper, we have constructed, for an arbitrary Lie group G and
any of the fields F=R or C, a good equivariant cohomology theory KF_G^*(-) on
the category of proper $G$-CW-complex and have justified why it deserved the
label ``equivariant K-theory". It was shown in particular how this theory was a
logical extension of the construction of L\"uck and Oliver for discrete groups
and coincided with Segal's classical K-theory when G is a compact group and
only finite G-CW-complexes are considered. Here, we compare our new equivariant
K-theory with that of N.C. Phillips: it is shown how a natural transformation
from ours to his may be constructed which gives rises to an isomorphism when G
is second-countable and only finite proper G-CW-complexes are considered. This
solves the long-standing issue of the existence of a classifying space for
Phillips' equivariant K-theory.


  We construct the spin foam model for N=2 supergravity in three dimensions.
Classically, it is a BF theory with gauge algebra osp(2|2). This algebra has
representations which are not completely reducible. This complicates the
procedure when building a state sum. Fortunately, one can and should excise
these representations. We show that the restricted subset of representations
form a subcategory closed under tensor product. The resulting state-sum is once
again a topological invariant. Furthermore, within this framework one can
identify positively and negatively charged fermions propagating on the spin
foam. These results on osp(2|2) representations and intertwiners apply more
generally to spin network states for N=2 loop quantum supergravity (in 3+1
dimensions) where it allows to define a notion of BPS states.


  Active Brownian particles are capable of taking up energy from their
environment and converting it into directed motion; examples range from
chemotactic cells and bacteria to artificial micro-swimmers. We have recently
demonstrated that Janus particles, i.e. gold-capped colloidal spheres,
suspended in a critical binary liquid mixture perform active Brownian motion
when illuminated by light. In this article, we investigate in some more details
their swimming mechanism leading to active Brownian motion. We show that the
illumination-borne heating induces a local asymmetric demixing of the binary
mixture generating a spatial chemical concentration gradient, which is
responsible for the particle's self-diffusiophoretic motion. We study this
effect as a function of the functionalization of the gold cap, the particle
size and the illumination intensity: the functionalization determines what
component of the binary mixture is preferentially adsorbed at the cap and the
swimming direction (towards or away from the cap); the particle size determines
the rotational diffusion and, therefore, the random reorientation of the
particle; and the intensity tunes the strength of the heating and, therefore,
of the motion. Finally, we harness this dependence of the swimming strength on
the illumination intensity to investigate the behaviour of a micro-swimmer in a
spatial light gradient, where its swimming properties are space-dependent.


  The hadronic vacuum polarization (HVP) contributions to the muon $g$$-$$2$
are the crucial quantity to resolve whether new physics is present or not in
the comparison between the Standard Model (SM) prediction and experimental
measurements at Fermilab. They are commonly and historically determined via
dispersion relations using a vast catalogue of experimentally measured,
low-energy $e^+e^-\to \,\rm{hadrons}$ cross section data as input. These
dispersive estimates result in a SM prediction that exhibits a muon $g$$-$$2$
discrepancy of more than $5\sigma$ when compared to experiment. However, recent
lattice QCD evaluations of the HVP and a new hadronic cross section measurement
from the CMD-3 experiment favor a no-new-physics scenario and, therefore,
exhibit a common tension with the previous $e^+e^-\to \,\rm{hadrons}$ data.
This study explores the current and future implications of these two scenarios
on other observables that are also sensitive to the HVP contributions in the
hope that they may provide independent tests of the current tensions observed
in the muon $g$$-$$2$.


  In many public health settings, it is important for patients to adhere to
health programs, such as taking medications and periodic health checks.
Unfortunately, beneficiaries may gradually disengage from such programs, which
is detrimental to their health. A concrete example of gradual disengagement has
been observed by an organization that carries out a free automated call-based
program for spreading preventive care information among pregnant women. Many
women stop picking up calls after being enrolled for a few months. To avoid
such disengagements, it is important to provide timely interventions. Such
interventions are often expensive and can be provided to only a small fraction
of the beneficiaries. We model this scenario as a restless multi-armed bandit
(RMAB) problem, where each beneficiary is assumed to transition from one state
to another depending on the intervention. Moreover, since the transition
probabilities are unknown a priori, we propose a Whittle index based Q-Learning
mechanism and show that it converges to the optimal solution. Our method
improves over existing learning-based methods for RMABs on multiple benchmarks
from literature and also on the maternal healthcare dataset.


  Deep generative models allow for photorealistic image synthesis at high
resolutions. But for many applications, this is not enough: content creation
also needs to be controllable. While several recent works investigate how to
disentangle underlying factors of variation in the data, most of them operate
in 2D and hence ignore that our world is three-dimensional. Further, only few
works consider the compositional nature of scenes. Our key hypothesis is that
incorporating a compositional 3D scene representation into the generative model
leads to more controllable image synthesis. Representing scenes as
compositional generative neural feature fields allows us to disentangle one or
multiple objects from the background as well as individual objects' shapes and
appearances while learning from unstructured and unposed image collections
without any additional supervision. Combining this scene representation with a
neural rendering pipeline yields a fast and realistic image synthesis model. As
evidenced by our experiments, our model is able to disentangle individual
objects and allows for translating and rotating them in the scene as well as
changing the camera pose.


  Velocity estimation plays a central role in driverless vehicles, but standard
and affordable methods struggle to cope with extreme scenarios like aggressive
maneuvers due to the presence of high sideslip. To solve this, autonomous race
cars are usually equipped with expensive external velocity sensors. In this
paper, we present an end-to-end recurrent neural network that takes available
raw sensors as input (IMU, wheel odometry, and motor currents) and outputs
velocity estimates. The results are compared to two state-of-the-art Kalman
filters, which respectively include and exclude expensive velocity sensors. All
methods have been extensively tested on a formula student driverless race car
with very high sideslip (10{\deg} at the rear axle) and slip ratio (~20%),
operating close to the limits of handling. The proposed network is able to
estimate lateral velocity up to 15x better than the Kalman filter with the
equivalent sensor input and matches (0.06 m/s RMSE) the Kalman filter with the
expensive velocity sensor setup.


  We investigate thermodynamic properties of a two-dimensional photon gas
confined by a dye-filled optical microcavity. A thermally equilibrated state of
the photon gas is achieved by radiative coupling to a heat bath that is
realized with dye molecules embedded in a polymer at room temperature. The
chemical potential of the gas is freely adjustable. The optical microcavity
consisting of two curved mirrors induces both a non-vanishing effective photon
mass and a harmonic trapping potential for the photons. While previous
experiments of our group have used liquid dye solutions, the measurements
described here are based on dye molecules incorporated into a polymer host
matrix. We describe studies of fluorescence properties of dye-doped polymers,
and discuss the applicability of Kennard-Stepanov theory in this system. We
observe a thermalized two-dimensional photon gas in the solid state based
microresonator system. In the future, dye-based solid state systems hold
promise for the realization of single-mode light sources in thermal equilibrium
based on Bose-Einstein condensation of photons, as well as for solar energy
concentrators.


  The Weil restriction functor, introduced in the late fifties, was recently
extended by Karpenko to the category of Chow motives with integral
coefficients. In this article we introduce the noncommutative (=NC) analogue of
the Weil restriction functor, where schemes are replaced by dg algebras, and
extend it to Kontsevich's categories of NC Chow motives and NC numerical
motives. Instead of integer coefficients, we work more generally with
coefficients in a binomial ring. Along the way, we extend Karpenko's functor to
the classical category of numerical motives, and compare this extension with
its NC analogue. As an application, we compute the (NC) Chow motive of the Weil
restriction of every smooth projective scheme whose category of perfect
complexes admits a full exceptional collection. Finally, in the case of central
simple algebras, we describe explicitly the NC analogue of the Weil restriction
functor using solely the degree of the field extension. This leads to a
"categorification" of the classical corestriction homomorphism between Brauer
groups.


  We describe a 3d analog of the Jordan-Wigner transformation which maps an
arbitrary fermionic system on a 3d spatial lattice to a 2-form $\mathbb{Z}_2$
gauge theory with an unusual Gauss law. An important property of this map is
that it preserves the locality of the Hamiltonian. The map depends explicitly
on the choice of a spin structure of the spatial manifold. We give examples of
3d bosonic systems dual to free fermions. We also describe the corresponding
Euclidean lattice models, which is analogous to the generalized Steenrod square
term in (3+1)D (compared to the Chern-Simon term in (2+1)D).


  Let R be an unramified regular local ring of mixed characteristic, D an
Azumaya R-algebra, K the fraction field of R, Nrd the reduced norm homomorphism
for the Azumaya R-algebra D. Let a be a unit in R. It is proved the following:
suppose the equation Nrd=a has a solution over K, then it has a solution over
R.
  Similar results are proved for regular local rings, which are geometrically
regular over a discrete valuation ring of mixed characteristic. These results
extend result proven by A.Sulin and the author in the middle of 90's.


  The DISL dataset features a collection of $514,506$ unique Solidity files
that have been deployed to Ethereum mainnet. It caters to the need for a large
and diverse dataset of real-world smart contracts. DISL serves as a resource
for developing machine learning systems and for benchmarking software
engineering tools designed for smart contracts. By aggregating every verified
smart contract from Etherscan up to January 15, 2024, DISL surpasses existing
datasets in size and recency.


  We study the problem of topic modeling in corpora whose documents are
organized in a multi-level hierarchy. We explore a parametric approach to this
problem, assuming that the number of topics is known or can be estimated by
cross-validation. The models we consider can be viewed as special
(finite-dimensional) instances of hierarchical Dirichlet processes (HDPs). For
these models we show that there exists a simple variational approximation for
probabilistic inference. The approximation relies on a previously unexploited
inequality that handles the conditional dependence between Dirichlet latent
variables in adjacent levels of the model's hierarchy. We compare our approach
to existing implementations of nonparametric HDPs. On several benchmarks we
find that our approach is faster than Gibbs sampling and able to learn more
predictive models than existing variational methods. Finally, we demonstrate
the large-scale viability of our approach on two newly available corpora from
researchers in computer security---one with 350,000 documents and over 6,000
internal subcategories, the other with a five-level deep hierarchy.