  Coset methods are used to construct the action describing the dynamics
associated with the spontaneous breaking of the local symmetries of AdS_{d+1}
space due to the embedding of an AdS_d brane. The resulting action is an
SO(2,d) invariant AdS form of the Einstein-Hilbert action, which in addition to
the AdS_d gravitational vielbein, also includes a massive vector field
localized on the brane. Its long wavelength dynamics is the same as a massive
Abelian vector field coupled to gravity in AdS_d space.


  The atmospheric neutrino flux represents a continuous source that can be
exploited to infer properties about Cosmic Rays and neutrino oscillation
physics. The JUNO observatory, a 20 kt liquid scintillator currently under
construction in China, will be able to detect atmospheric neutrinos , given the
large fiducial volume and the excellent energy resolution. The light produced
in neutrino interactions will be collected by a double-system of photosensors:
about 18.000 20" PMTs and about 25.000 3" PMTs. The rock overburden above the
experimental hall is around 700 m and the experiment is expected to complete
construction in 2021. In this study, the JUNO performances in reconstructing
the atmospheric neutrino spectrum have been evaluated. The different time
evolution of scintillation light on the PMTs allows to discriminate the flavor
of the primary neutrinos. To reconstruct the time pattern of events, the
signals from 3" PMTs only have been used, because of the small time resolution.
A probabilistic unfolding method has been used, in order to infer the primary
neutrino energy spectrum by looking at the detector output. The simulated
spectrum has been reconstructed between 100 MeV and 10 GeV, showing a great
potential of the detector in the atmospheric low energy region. The
uncertainties on the final flux, including both statistic and the systematic
contributions, range between 10% and 25%, with the best performances obtained
at the GeV.


  Gender/ing guides how we view ourselves, the world around us, and each
other--including non-humans. Critical voices have raised the alarm about
stereotyped gendering in the design of socially embodied artificial agents like
voice assistants, conversational agents, and robots. Yet, little is known about
how this plays out in research and to what extent. As a first step, we
critically reviewed the case of Pepper, a gender-ambiguous humanoid robot. We
conducted a systematic review (n=75) involving meta-synthesis and content
analysis, examining how participants and researchers gendered Pepper through
stated and unstated signifiers and pronoun usage. We found that ascriptions of
Pepper's gender were inconsistent, limited, and at times discordant, with
little evidence of conscious gendering and some indication of researcher
influence on participant gendering. We offer six challenges driving the state
of affairs and a practical framework coupled with a critical checklist for
centering gender in research on artificial agents.


  We study the isotropic Heisenberg chain with nearest and next-nearest
neighbour interactions. The ground state phase diagram is constructed in
dependence on the additonal interactions and an external magnetic field. The
thermodynamics is studied by use of finite sets of non-linear integral
equations resulting from integrabiliy. The equations are solved numerically and
analytically in suitable limiting cases. We find second and first order
transition lines. The exponents of the low temperature asymptotics at the phase
transitions are determined.


  Orientation control of oxygen vacancy channel (OVC) is a highly desirable for
tailoring oxygen diffusion as it serves fast transport channel in ion
conductors, which is widespread exploited in solid-state fuel cells, catalysts,
and ion-batteries. Direct observation of oxygen-ions hopping towards
preferential vacant sites is a key to clarifying migration pathways. Here we
report the anisotropic oxygen-ion migration mediated by strain in ultrathin
cobaltites via in-situ thermal activation in an atomic-resolved transmission
electron microscopy. Oxygen migration pathways are constructed on the basis of
the atomic structure during the OVC switching, which is manifested as the
vertical-to-horizontal OVC switching under tensile strain, but the
horizontal-to-diagonal switching under compression. We evaluate the topotactic
structural changes to OVC, determine the crucial role of tolerance factor for
OVC stability and establish the strain-dependent phase diagram. Our work
provides a practical guide for engineering OVC orientation that is applicable
ionic-oxide electronics.


  We show theoretically that photonic crystal membranes cause large variations
in the spontaneous emission rate of dipole emitters, not only inside but also
in the near-field above the membranes. Our three-dimensional finite difference
time-domain calculations reveal an inhibition of more than five times and an
enhancement of more than ten times for the spontaneous emission rate of
emitters with select dipole orientations and frequencies. Furthermore we
demonstrate theoretically, the potential of a nanoscopic emitter attached to
the end of a glass fiber tip as a local probe for mapping the large spatial
variations of the photonic crystal local radiative density of states. This
arrangement is promising for on-command modification of the coupling between an
emitter and the photonic crystal in quantum optical experiments.


  In many global optimization problems motivated by engineering applications,
the number of function evaluations is severely limited by time or cost. To
ensure that each evaluation contributes to the localization of good candidates
for the role of global minimizer, a sequential choice of evaluation points is
usually carried out. In particular, when Kriging is used to interpolate past
evaluations, the uncertainty associated with the lack of information on the
function can be expressed and used to compute a number of criteria accounting
for the interest of an additional evaluation at any given point. This paper
introduces minimizer entropy as a new Kriging-based criterion for the
sequential choice of points at which the function should be evaluated. Based on
\emph{stepwise uncertainty reduction}, it accounts for the informational gain
on the minimizer expected from a new evaluation. The criterion is approximated
using conditional simulations of the Gaussian process model behind Kriging, and
then inserted into an algorithm similar in spirit to the \emph{Efficient Global
Optimization} (EGO) algorithm. An empirical comparison is carried out between
our criterion and \emph{expected improvement}, one of the reference criteria in
the literature. Experimental results indicate major evaluation savings over
EGO. Finally, the method, which we call IAGO (for Informational Approach to
Global Optimization) is extended to robust optimization problems, where both
the factors to be tuned and the function evaluations are corrupted by noise.


  Our main interest in this paper is to study some approximation problems for
classes of functions with mixed smoothness. We use technique, based on a
combination of results from hyperbolic cross approximation, which were obtained
in 1980s -- 1990s, and recent results on greedy approximation to obtain sharp
estimates for best $m$-term approximation with respect to the trigonometric
system. We give some observations on numerical integration and approximate
recovery of functions with mixed smoothness. We prove lower bounds, which show
that one cannot improve accuracy of sparse grids methods with $\asymp
2^nn^{d-1}$ points in the grid by adding $2^n$ arbitrary points. In case of
numerical integration these lower bounds provide best known lower bounds for
optimal cubature formulas and for sparse grids based cubature formulas.


  Electromagnetic fields possess zero point fluctuations (ZPF) which lead to
observable effects such as the Lamb shift and the Casimir effect. In the
traditional quantum optics domain, these corrections remain perturbative due to
the smallness of the fine structure constant. To provide a direct observation
of non-perturbative effects driven by ZPF in an open quantum system we wire a
highly non-linear Josephson junction to a high impedance transmission line,
allowing large phase fluctuations across the junction. Consequently, the
resonance of the former acquires a relative frequency shift that is orders of
magnitude larger than for natural atoms. Detailed modelling confirms that this
renormalization is non-linear and quantum. Remarkably, the junction transfers
its non-linearity to about 30 environmental modes, a striking back-action
effect that transcends the standard Caldeira-Leggett paradigm. This work opens
many exciting prospects for longstanding quests such as the tailoring of
many-body Hamiltonians in the strongly non-linear regime, the observation of
Bloch oscillations, or the development of high-impedance qubits.


  Speaker diarization based on bottom-up clustering of speech segments by
acoustic similarity is often highly sensitive to the choice of hyperparameters,
such as the initial number of clusters and feature weighting. Optimizing these
hyperparameters is difficult and often not robust across different data sets.
We recently proposed the DOVER algorithm for combining multiple diarization
hypotheses by voting. Here we propose to mitigate the robustness problem in
diarization by using DOVER to average across different parameter choices. We
also investigate the combination of diverse outputs obtained by following
different merge choices pseudo-randomly in the course of clustering, thereby
mitigating the greediness of best-first clustering. We show on two conference
meeting data sets drawn from NIST evaluations that the proposed methods indeed
yield more robust, and in several cases overall improved, results.


  There is an apparent tension between cosmological parameters obtained from
{\it Planck} cosmic microwave background radiation observations and that
derived from the observed magnitude-redshift relation for the type Ia supernova
(SNe Ia). Here, we show that the tension can be alleviated, if we first
calibrate, with the help of the distance-duality relation, the light-curve
fitting parameters in the distance estimation in SNe Ia observations with the
angular diameter distance data of the galaxy clusters and then re-estimate the
distances for the SNe Ia with the corrected fitting parameters. This was used
to explore their cosmological implications in the context of the spatially flat
cosmology. We find a higher value for the matter density parameter, $\Omega_m$,
as compared to that from the original SNLS3, which is in agreement with {\it
Planck} observations at $68.3\%$ confidence. Therefore, the tension between
{\it Planck} measurements and SNe Ia observations regarding $\Omega_m$ can be
effectively alleviated without invoking new physics or resorting to extensions
for the standard concordance model. Moreover, with the absolute magnitude of a
fiducial SNe Ia, $M$, determined first, we obtained a constraint on the Hubble
constant with SNLS3 alone, which is also consistent with {\it Planck}.


  In \cite{TY}, we consider the minimal paths in the path complex associated to
a digraph $G$ under the strongly regular condition. In this paper, first, based
on our new definitions of admissible pair and admissible relations among the
set of minimal paths, we will give the definitions of cellular chain complex
associated to $G$ and prove the well-definedness. Then we will study several
properties of such cellular homologies. Finally, we give several interesting
examples as well as some important observations.


  Quantum-optical coherence tomography (Q-OCT) provides a dispersion-canceled
axial-imaging method, but its practical use is limited by the weakness of the
light source and by artifacts in the images. A recent study using chirped-pulse
interferometry (CPI) has demonstrated dispersion-canceled and artifact-free OCT
with a classical system; however, unwanted background signals still remain
after removing the artifacts. Here, we propose a classical optical method that
realizes dispersion-canceled, artifact-free, and background-free OCT. We employ
a time-reversed system for Q-OCT with transform-limited input laser pulses to
achieve dispersion-canceled OCT with a classical system. We have also
introduced a subtraction method to remove artifacts and background signals.
With these methods, we experimentally demonstrated dispersion-canceled,
artifact-free, and background-free axial imaging of a coverglass and
cross-sectional imaging of the surface of a coin.


  Let $L$ be a holomorphic line bundle over a compact K\"ahler manifold $X$.
Motivated by mirror symmetry, we study the deformed Hermitian-Yang-Mills
equation on $L$, which is the line bundle analogue of the special Lagrangian
equation in the case that $X$ is Calabi-Yau. We show that this equation is the
Euler-Lagrange equation for a positive functional, and that solutions are
unique global minimizers. We provide a necessary and sufficient criterion for
existence in the case that $X$ is a K\"ahler surface. For the higher
dimensional cases, we introduce a line bundle version of the Lagrangian mean
curvature flow, and prove convergence when $L$ is ample and $X$ has
non-negative orthogonal bisectional curvature.


  The vehicle re-identification (ReID) plays a critical role in the perception
system of autonomous driving, which attracts more and more attention in recent
years. However, to our best knowledge, there is no existing complete solution
for the surround-view system mounted on the vehicle. In this paper, we argue
two main challenges in above scenario: i) In single camera view, it is
difficult to recognize the same vehicle from the past image frames due to the
fisheye distortion, occlusion, truncation, etc. ii) In multi-camera view, the
appearance of the same vehicle varies greatly from different camera's
viewpoints. Thus, we present an integral vehicle Re-ID solution to address
these problems. Specifically, we propose a novel quality evaluation mechanism
to balance the effect of tracking box's drift and target's consistency.
Besides, we take advantage of the Re-ID network based on attention mechanism,
then combined with a spatial constraint strategy to further boost the
performance between different cameras. The experiments demonstrate that our
solution achieves state-of-the-art accuracy while being real-time in practice.
Besides, we will release the code and annotated fisheye dataset for the benefit
of community.


  According to Mukai, any prime Fano threefold X of genus 7 is a linear section
of the spinor tenfold in the projectivized half-spinor space of Spin(10). The
orthogonal linear section of the spinor tenfold is a canonical genus-7 curve G,
and the intermediate Jacobian J(X) is isomorphic to the Jacobian of G. It is
proven that, for a generic X, the Abel-Jacobi map of the family of elliptic
sextics on X factors through the moduli space of rank-2 vector bundles with
c_1=-K_X and deg c_2=6 and that the latter is birational to the singular locus
of the theta divisor of J(X).


  We demonstrate a method that enables accurate timing jitter spectral density
characterization of free-running mode-locked laser oscillators over more than
10-decade of Fourier frequency from mHz to tens MHz range. The method is based
on analyzing both the input voltage noise to the slave laser and the output
voltage noise from the balanced optical cross- correlator (BOC), when two
mode-locked lasers are synchronized in repetition rate by the BOC. As a
demonstration experiment, timing jitter spectrum of a free-running mode-locked
Er-fiber laser with a dynamic range of >340 dB is measured over Fourier
frequency ranging from 1 mHz to 38.5 MHz (Nyquist frequency). The demonstrated
method can resolve different noise mechanisms that cause specific jitter
characteristics in free-running mode-locked laser oscillators for a vast range
of time scales from <100-ns to >1000-s.


  During a period of about two decades we have realized a programme of
systematic investigations of different aspects of neutrino propagation in
extreme external environments and have predicted and studied several new
phenomena that are engendered by the presence of external magnetic fields and
dense matter. The starting point that underlies the research is the fact that
the electromagnetic properties of neutrinos open a window to new physics
\cite{Giunti:2014ixa,Studenikin:2008bd, Studenikin:2018vnp}. In these brief
notes, we recall several new phenomena that have been proposed and investigated
earlier. In particular, we discuss: 1) the spin light of neutrino in matter, 2)
the neutrino energy quantization in rotating matter, and 3) neutrino start
turning mechanism. Then we dwell on results of recent studies: 4) the effects
of interplay of neutrino flavour and spin oscillations in a magnetic field, 5)
the quantum theory of neutrino spin and spin-flavour oscillations engendered by
the transversal mater currents, 6) the amplitude modulation of the flavour
neutrino oscillation probability by the transversal matter current. As for
references to the literature, only those papers are included in which a
particular effect was proposed and considered for the first time and in a
number of cases references are also be given to the most recent articles, which
contain detailed references to the available literature on the issue.


  The transition of many educational activities from in-presence to online, due
to the Covid-19 emergency, has caused various difficulties to students,
especially with regards to maintaining concentration. Even and especially in
online mode, it is thus important to pay attention to the interaction with
participants. In this context, the Department of Mathematics and Physics of
Roma Tre University has proposed a series of activities dedicated to schools
that have proven to be able to guarantee the engagement of the participants,
also thanks to the game-based learning platform Kahoot!.


  Current research on Deep Reinforcement Learning (DRL) for automated on-ramp
merging neglects vehicle powertrain and dynamics. This work considers automated
on-ramp merging for a power-split Plug-In Hybrid Electric Vehicle (PHEV), the
2015 Toyota Prius Plug-In, using DRL. The on-ramp merging control and the PHEV
energy management are co-optimized such that the DRL policy directly outputs
the power split between the engine and the electric motor. The testing results
show that DRL can be successfully used for co-optimization, leading to
collision-free on-ramp merging. When compared with sequential approaches
wherein the upper-level on-ramp merging control and the lower-level PHEV energy
management are performed independently and in sequence, we found that
co-optimization results in economic but jerky on-ramp merging while sequential
approaches may result in collisions due to neglecting powertrain power limit
constraints in designing the upper-level on-ramp merging controller.


  One of the main interest in quantum cosmology is to determine boundary
conditions for the wave function of the universe which can predict
observational data of our universe. For this purpose, we solve the
Wheeler-DeWitt equation for a closed universe with a scalar field numerically
and evaluate probabilities for boundary conditions of the wave function of the
universe. To impose boundary conditions of the wave function, we use exact
solutions of the Wheeler-DeWitt equation with a constant scalar field
potential. These exact solutions include wave functions with well known
boundary condition proposals, the no-boundary proposal and the tunneling
proposal. We specify the exact solutions by introducing two real parameters to
discriminate boundary conditions, and obtain the probability for these
parameters under the requirement of sufficient e-foldings of the inflation. The
probability distribution of boundary conditions prefers the tunneling boundary
condition to the no-boundary boundary condition. Furthermore, for large values
of a model parameter related to the inflaton mass and the cosmological
constant, the probability of boundary conditions selects an unique boundary
condition different from the tunneling type.


  Foundation models have exhibited unprecedented capabilities in tackling many
domains and tasks. Models such as CLIP are currently widely used to bridge
cross-modal representations, and text-to-image diffusion models are arguably
the leading models in terms of realistic image generation. Image generative
models are trained on massive datasets that provide them with powerful internal
spatial representations. In this work, we explore the potential benefits of
such representations, beyond image generation, in particular, for dense visual
prediction tasks. We focus on the task of image segmentation, which is
traditionally solved by training models on closed-vocabulary datasets, with
pixel-level annotations. To avoid the annotation cost or training large
diffusion models, we constraint our setup to be zero-shot and training-free. In
a nutshell, our pipeline leverages different and relatively small-sized,
open-source foundation models for zero-shot open-vocabulary segmentation. The
pipeline is as follows: the image is passed to both a captioner model (i.e.
BLIP) and a diffusion model (i.e., Stable Diffusion Model) to generate a text
description and visual representation, respectively. The features are clustered
and binarized to obtain class agnostic masks for each object. These masks are
then mapped to a textual class, using the CLIP model to support
open-vocabulary. Finally, we add a refinement step that allows to obtain a more
precise segmentation mask. Our approach (dubbed FreeSeg-Diff), which does not
rely on any training, outperforms many training-based approaches on both Pascal
VOC and COCO datasets. In addition, we show very competitive results compared
to the recent weakly-supervised segmentation approaches. We provide
comprehensive experiments showing the superiority of diffusion model features
compared to other pretrained models. Project page:
https://bcorrad.github.io/freesegdiff/


  We investigate the entanglement spectra of topological insulators which
manifest edge states on a lattice with spatial boundaries. In the physical
energy spectrum, a subset of the edge states that intersect the Fermi level
translates to discontinuities in the trace of the single-particle entanglement
spectrum, which we call a `trace index'. We find that any free-fermion
topological insulator that exhibits spectral flow has a non-vanishing trace
index, which provides us with a new description of topological invariants. In
addition, we identify the signatures of spectral flow in the single-particle
and many-body entanglement spectrum; in the process we present new methods to
extract topological invariants and establish a connection between entanglement
and quantum Hall physics.


  Electronic properties and lattice dynamics of bulk $\varepsilon$-GaSe and
mono-, bi- and tri-tetralayer GaSe are investigated by means of density
functional and density functional perturbation theory. The few-tetralayers
systems are semiconductors with an indirect nature of the fundamental band gap
and a Mexican-hat-shape is observed at the top of the valence band. The phonon
branches analysis reveals the dynamical stability for all systems considered
together with the LO-TO splitting breakdown in two-dimensional systems.
In-plane (E) and out-of-plane (A) zone-center lattice vibrations dominate the
Raman and IR spectra.


  Federated learning (FL) is an emerging technique for training machine
learning models using geographically dispersed data collected by local
entities. It includes local computation and synchronization steps. To reduce
the communication overhead and improve the overall efficiency of FL, gradient
sparsification (GS) can be applied, where instead of the full gradient, only a
small subset of important elements of the gradient is communicated. Existing
work on GS uses a fixed degree of gradient sparsity for i.i.d.-distributed data
within a datacenter. In this paper, we consider adaptive degree of sparsity and
non-i.i.d. local datasets. We first present a fairness-aware GS method which
ensures that different clients provide a similar amount of updates. Then, with
the goal of minimizing the overall training time, we propose a novel online
learning formulation and algorithm for automatically determining the
near-optimal communication and computation trade-off that is controlled by the
degree of gradient sparsity. The online learning algorithm uses an estimated
sign of the derivative of the objective function, which gives a regret bound
that is asymptotically equal to the case where exact derivative is available.
Experiments with real datasets confirm the benefits of our proposed approaches,
showing up to $40\%$ improvement in model accuracy for a finite training time.


  Recent research on temporal networks has highlighted the limitations of a
static network perspective for our understanding of complex systems with
dynamic topologies. In particular, recent works have shown that i) the specific
order in which links occur in real-world temporal networks affects causality
structures and thus the evolution of dynamical processes, and ii) higher-order
aggregate representations of temporal networks can be used to analytically
study the effect of these order correlations on dynamical processes. In this
article we analyze the effect of order correlations on path-based centrality
measures in real-world temporal networks. Analyzing temporal equivalents of
betweenness, closeness and reach centrality in six empirical temporal networks,
we first show that an analysis of the commonly used static, time-aggregated
representation can give misleading results about the actual importance of
nodes. We further study higher-order time-aggregated networks, a recently
proposed generalization of the commonly applied static, time-aggregated
representation of temporal networks. Here, we particularly define path-based
centrality measures based on second-order aggregate networks, empirically
validating that node centralities calculated in this way better capture the
true temporal centralities of nodes than node centralities calculated based on
the commonly used static (first-order) representation. Apart from providing a
simple and practical method for the approximation of path-based centralities in
temporal networks, our results highlight interesting perspectives for the use
of higher-order aggregate networks in the analysis of time-stamped network
data.


  We show that for any two linear homogenous equations
$\mathcal{E}_0,\mathcal{E}_1$, each with at least three variables and
coefficients not all the same sign, any 2-coloring of $\mathbb{Z}^+$ admits
monochromatic solutions of color 0 to $\mathcal{E}_0$ or monochromatic
solutions of color 1 to $\mathcal{E}_1$. We define the 2-color off-diagonal
Rado number $RR(\mathcal{E}_0,\mathcal{E}_1)$ to be the smallest $N$ such that
$[1,N]$ must admit such solutions. We determine a lower bound for
$RR(\mathcal{E}_0,\mathcal{E}_1)$ in certain cases when each $\mathcal{E}_i$ is
of the form $a_1x_1+...+a_nx_n=z$ as well as find the exact value of
$RR(\mathcal{E}_0,\mathcal{E}_1)$ when each is of the form
$x_1+a_2x_2+...+a_nx_n=z$. We then present a Maple package that determines
upper bounds for off-diagonal Rado numbers of a few particular types, and use
it to quickly prove two previous results for diagonal Rado numbers.


  Differential conservation laws in Lagrangian field theory are usually related
to symmetries of a Lagrangian density and are obtained if the Lie derivative of
a Lagrangian density by a certain class of vector fields on a fiber bundle
vanishes. However, only two field models meet this property in fact. In gauge
theory of exact internal symmetries, the Lie derivative by vertical vector
fields corresponding to gauge transformations is equal to zero. The
corresponding N\"oether current is reduced to a superpotential that provides
invariance of the N\"oether conservation law under gauge transformations. In
the gravitation theory, we meet the phenomenon of "hidden energy". Only the
superpotential part of energy-momentum of gravity and matter is observed when
the general covariant transformations are exact. Other parts of energy-momentum
display themselves if the invariance under general covariance transformations
is broken, e.g., by a background world metric. In this case, the Lie
derivatives of Lagrangian densities by vector fields which call into play the
stress-energy-momentum tensors fail to be equal to zero in general. We base our
analysis of differential conservation laws on the canonical decomposition of
the Lie derivative of a Lagrangian density $L$ by a projectable vector field on
a bundle and with respect to different Lepagian equivalents of $L$. Different
Lepagian equivalents lead to conserved quantities which differ from each other
in superpotential terms. We have different stress-energy-momentum tensors
depending on different lifts of vector fields on a base onto a bundle.
Moreover, different solutions of the same Euler-Lagrange equations may require
different energy-momentum tensors. We show that different
stress-energy-momentum tensors differ from each other in N\"oether currents. As


  The prevalent approach to sequence to sequence learning maps an input
sequence to a variable length output sequence via recurrent neural networks. We
introduce an architecture based entirely on convolutional neural networks.
Compared to recurrent models, computations over all elements can be fully
parallelized during training and optimization is easier since the number of
non-linearities is fixed and independent of the input length. Our use of gated
linear units eases gradient propagation and we equip each decoder layer with a
separate attention module. We outperform the accuracy of the deep LSTM setup of
Wu et al. (2016) on both WMT'14 English-German and WMT'14 English-French
translation at an order of magnitude faster speed, both on GPU and CPU.


  We study the exterior and interior Bernoulli problems for the half Laplacian
and the interior Bernoulli problem for the spectral half Laplacian. We
concentrate on the existence and geometric properties of solutions. Our main
results are the following. For the exterior Bernoulli problem for the half
Laplacian, we show that under starshapedness assumptions on the data the free
domain is starshaped. For the interior Bernoulli problem for the spectral half
Laplacian, we show that under convexity assumptions on the data the free domain
is convex and we prove a Brunn-Minkowski inequality for the Bernoulli constant.
For Bernoulli problems for the half Laplacian we use a variational approach,
whereas for Bernoulli problem for the spectral half Laplacian we use the
Beurling method based on subsolutions.


  The O'Connell effect - the presence of unequal maxima in eclipsing binaries -
remains an unsolved riddle in the study of close binary systems. The Kepler
space telescope produced high precision photometry of nearly 3,000 eclipsing
binary systems, providing a unique opportunity to study the O'Connell effect in
a large sample and in greater detail than in previous studies. We have
characterized the observational properties - including temperature, luminosity,
and eclipse depth - of a set of 212 systems (7.3% of Kepler eclipsing binaries)
that display a maxima flux difference of at least 1%, representing the largest
sample of O'Connell effect systems yet studied. We explored how these
characteristics correlate with each other to help understand the O'Connell
effect's underlying causes. We also describe some system classes with peculiar
light curve features aside from the O'Connell effect (~30% of our sample),
including temporal variation and asymmetric minima. We found that the O'Connell
effect size's correlations with period and temperature are inconsistent with
Kouzuma's starspot study. Up to 20% of systems display the parabolic eclipse
timing variation signal expected for binaries undergoing mass transfer. Most
systems displaying the O'Connell effect have the brighter maximum following the
primary eclipse, suggesting a fundamental link between which maximum is
brighter and the O'Connell effect's physical causes. Most importantly, we find
that the O'Connell effect occurs exclusively in systems where the components
are close enough to significantly affect each other, suggesting that the
interaction between the components is ultimately responsible for causing the
O'Connell effect.


  The occurrence of stripe domains in ferromagnetic Permalloy
(Py=Fe$_{20}$Ni$_{80}$) is a well known phenomenon which has been extensively
observed and characterized. This peculiar magnetic configuration appears only
in films with a thickness above a critical value ($d_{cr}$), which is strongly
determined by the sputtering conditions (i.e. deposition rate, temperature,
magnetic field). So far, $d_{cr}$ has usually been presented as the boundary
between the homogeneous (H) and stripe-domains (SD) regime, respectively below
and above $d_{cr}$. In this work we study the transition from the H to the SD
regime in thin films and microstructured bridges of Py with different
thicknesses. We find there is an intermediate regime, over a quite significant
thickness range below d$_{cr}$, which is signaled in confined structures by a
quickly changing domain-wall configuration and by a broadening of the
magnetoresistance dip at the coercive field. We call this the emerging
stripe-domains (ESD) regime. The transition from the ESD to the SD regime is
accompanied by a sharp increase of the magnetoresistance ratio at the thickness
where stripes appear in MFM.


  The large time behavior of the solutions to a multi-dimensional viscous
conservation law is considered in this paper. It is shown that the solution
time-asymptotically tends to the planar rarefaction wave if the initial
perturbations are multi-dimensional periodic. The time-decay rate is also
obtained. Moreover, a Gagliardo-Nirenberg type inequality is established in the
domain $ \mathbb R \times \mathbb T^{n-1} (n\geq2) $, where $\mathbb T^{n-1}$
is the $ n-1 $-dimensional torus.


  We enlarge the chiral model, the so-called extended Linear Sigma Model
(eLSM), by including the low-lying hybrid nonet with exotic quantum numbers
$J^{PC}=1^{-+}$ and the nonet of their chiral partners with $J^{PC}=1^{+-}$ to
a global $U(3)_r \times U(3)_l$ chiral symmetry. We use the assignment of the
$\pi_1^{hyb}= \pi_1(1600)$ as input to determine the unknown parameters. Then,
we compute the lightest vector and pseudovector hybrid masses that could guide
ongoing and upcoming experiments in searching for hybrids.


  This work develops a theoretical model for steady thermodynamic and kinematic
profiles for severe convective storm environments, building off of the
two-layer static energy framework developed in Agard and Emanuel (2017). The
model is phrased in terms of static energy, and it allows for independent
variation of the boundary layer and free troposphere separated by a capping
inversion. An algorithm is presented to apply the model to generate a sounding
for numerical simulations of severe convective storms, and the model is
compared and contrasted with that of Weisman and Klemp. The model is then fit
to a case-study sounding associated with the 3 May 1999 tornado outbreak, and
its potential utility is demonstrated via idealized numerical simulation
experiments. A long-lived supercell is successfully simulated with the
historical sounding but not the analogous theoretical sounding. Two types of
example experiments are then performed that do simulate a long-lived supercell:
1) a semi-theoretical experiment in which a portion of the theoretical sounding
is modified to match the real sounding (low-level moisture); 2) a
fully-theoretical experiment in which a model physical parameter is modified
(free-tropospheric relative humidity). Overall, the construction of this
minimal model is flexible and amenable to additional modifications as needed.
The model offers a novel framework that may be useful for testing how severe
convective storms depend on the vertical structure of the hydrostatic
environment, as well as for linking variability in these environments to the
physical processes that produce them within the climate system.


  Milky Way globular clusters (GCs) display chemical enrichment in a phenomenon
called multiple stellar populations (MSPs). While the enrichment mechanism is
not fully understood, there is a correlation between a cluster's mass and the
fraction of enriched stars found therein. However, present-day GC masses are
often smaller than their masses at the time of formation due to dynamical mass
loss. In this work, we explore the relationship between mass and MSPs using the
stellar stream 300S. We present the chemical abundances of eight red giant
branch member stars in 300S with high-resolution spectroscopy from
Magellan/MIKE. We identify one enriched star characteristic of MSPs and no
detectable metallicity dispersion, confirming that the progenitor of 300S was a
globular cluster. The fraction of enriched stars (12.5\%) observed in our 300S
stars is less than the 50\% of stars found enriched in Milky Way GCs of
comparable present-day mass ($\sim10^{4.5}$\msun). We calculate the mass of
300S's progenitor and compare it to the initial masses of intact GCs, finding
that 300S aligns well with the trend between the system mass at formation and
enrichment. 300S's progenitor may straddle the critical mass threshold for the
formation of MSPs and can therefore serve as a benchmark for the stellar
enrichment process. Additionally, we identify a CH star, with high abundances
of \textit{s}-process elements, probably accreted from a binary companion. The
rarity of such binaries in intact GCs may imply stellar streams permit the
survival of binaries that would otherwise be disrupted.


  Energy-based learning is a powerful learning paradigm that encapsulates
various discriminative and generative approaches. An energy-based model (EBM)
is typically formed of inner-model(s) that learn a combination of the different
features to generate an energy mapping for each input configuration. In this
paper, we focus on the diversity of the produced feature set. We extend the
probably approximately correct (PAC) theory of EBMs and analyze the effect of
redundancy reduction on the performance of EBMs. We derive generalization
bounds for various learning contexts, i.e., regression, classification, and
implicit regression, with different energy functions and we show that indeed
reducing redundancy of the feature set can consistently decrease the gap
between the true and empirical expectation of the energy and boosts the
performance of the model.


  A toy model of strongly correlated fermions is studied using Green function
and functional integration methods. The model exhibits a metal-insulator
transition as the interaction is varied. In the case of unrestricted hopping is
established the equivalence of the model with the Hubbard model with infinite
range hopping. The generalization to the case with $N$ components is made.


  For many decades now, Bayesian Model Averaging (BMA) has been a popular
framework to systematically account for model uncertainty that arises in
situations when multiple competing models are available to describe the same or
similar physical process. The implementation of this framework, however, comes
with a multitude of practical challenges including posterior approximation via
Markov Chain Monte Carlo and numerical integration. We present a Variational
Bayesian Inference approach to BMA as a viable alternative to the standard
solutions which avoids many of the aforementioned pitfalls. The proposed method
is "black box" in the sense that it can be readily applied to many models with
little to no model-specific derivation. We illustrate the utility of our
variational approach on a suite of examples and discuss all the necessary
implementation details. Fully documented Python code with all the examples is
provided as well.


  Component separation is the process with which emission sources in
astrophysical maps are generally extracted by taking multi-frequency
information into account. It is crucial to develop more reliable methods for
component separation for future CMB experiments. We aim to develop a new method
based on fully convolutional neural networks called the Cosmic microwave
background Extraction Neural Network (CENN) in order to extract the CMB signal
in total intensity. The frequencies used are the Planck channels 143, 217 and
353 GHz. We validate the network at all sky, and at three latitude intervals:
lat1=0^{\circ}<b<5^{\circ}, lat2=5^{\circ}<b<30^{\circ} and
lat3=30^{\circ}<b<90^{\circ}, without using any Galactic or point source masks.
For training, we make realistic simulations in the form of patches of area 256
pixels, which contain the CMB, Dust, CIB and PS emissions, Sunyaev-Zel'dovich
effect and the instrumental noise. After validate the network, we compare the
power spectrum from input and output maps. We analyse the power spectrum from
the residuals at each latitude interval and at all sky and we study the
performance of our model dealing with high contamination at small scales. We
obtain a power spectrum with an error of 13{\pm}113 {\mu}K^2 for multipoles up
to above 4000. For residuals, we obtain 700{\pm}60 {\mu}K^2 for lat1, 80{\pm}30
{\mu}K^2 for lat2 and 30{\pm}20 {\mu}K^2 for lat3. For all sky, we obtain
20{\pm}10 {\mu}K^2. We validate the network in a patch with strong
contamination at small scales, obtaining an error of 50{\pm}120 {\mu}K^2 and
residuals of 40{\pm}10 {\mu}K^2. Therefore, fully convolutional neural networks
are promising methods to perform component separation in future CMB
experiments. Particularly, CENN is reliable against different levels of
contamination from Galactic and point source foregrounds at both large and
small scales.


  We place functional constraints on the shape of the inflaton potential from
the cosmic microwave background through a variant of the generalized slow roll
approximation that allows large amplitude, rapidly changing deviations from
scale-free conditions. Employing a principal component decomposition of the
source function G'~3(V'/V)^2 - 2V''/V and keeping only those measured to better
than 10% results in 5 nearly independent Gaussian constraints that maybe used
to test any single-field inflationary model where such deviations are expected.
The first component implies < 3% variations at the 100 Mpc scale. One component
shows a 95% CL preference for deviations around the 300 Mpc scale at the ~10%
level but the global significance is reduced considering the 5 components
examined. This deviation also requires a change in the cold dark matter density
which in a flat LCDM model is disfavored by current supernova and Hubble
constant data and can be tested with future polarization or high multipole
temperature data. Its impact resembles a local running of the tilt from
multipoles 30-800 but is only marginally consistent with a constant running
beyond this range. For this analysis, we have implemented a ~40x faster WMAP7
likelihood method which we have made publicly available.


  Computational complexity is essential to understanding the properties of
black hole horizons. The problem of Alice creating a firewall behind the
horizon of Bob's black hole is a problem of computational complexity. In
general we find that while creating firewalls is possible, it is extremely
difficult and probably impossible for black holes that form in sudden collapse,
and then evaporate. On the other hand if the radiation is bottled up then after
an exponentially long period of time firewalls may be common. It is possible
that gravity will provide tools to study problems of complexity; especially the
range of complexity between scrambling and exponential complexity.


  We obtain the general conditions for the emergence of odd-frequency
superconducting pairing in a two-dimensional (2D) electronic system
proximity-coupled to a superconductor, making minimal assumptions about both
the 2D system and the superconductor. Using our general results we show that a
simple heterostructure formed by a monolayer of a group VI transition metal
dichalcogenide, such as molybdenum disulfide, and an s-wave superconductor with
Rashba spin-orbit coupling will exhibit odd-frequency superconducting pairing.
Furthermore, we show that in such a heterostructure the odd-frequency pairing
amplitude will be proportional to the product of the Rashba spin-orbit coupling
in the substrate and the spin-orbit coupling in the dichalcogenide layer.


  By performing estimates on the integral of the absolute value of vorticity
along a local vortex line segment, we establish a relatively sharp dynamic
growth estimate of maximum vorticity under some assumptions on the local
geometric regularity of the vorticity vector. Our analysis applies to both the
3D incompressible Euler equations and the surface quasi-geostrophic model
(SQG). As an application of our vorticity growth estimate, we apply our result
to the 3D Euler equation with the two anti-parallel vortex tubes initial data
considered by Hou-Li. Under some additional assumption on the vorticity field,
which seems to be consistent with the computational results of Hou-Li, we show
that the maximum vorticity can not grow faster than double exponential in time.
Our analysis extends the earlier results by Cordoba-Fefferman and Deng-Hou-Yu.


  We investigate the classical Renyi entropy S_n and the associated mutual
information I_n in the Sherrington-Kirkpatrick (S-K) model, which is the
paradigm model of mean-field spin glasses. Using classical Monte Carlo
simulations and analytical tools we investigate the S-K model on the n-sheets
booklet. This is obtained by gluing together n independent copies of the model,
and it is the main ingredient to construct the Renyi entanglement-related
quantities. We find a glassy phase at low temperature, whereas at high
temperature the model exhibits paramagnetic behavior, consistent with the
regular S-K model. The temperature of the paramagnetic-glassy transition
depends non-trivially on the geometry of the booklet. At high-temperatures we
provide the exact solution of the model by exploiting the replica symmetry.
This is the permutation symmetry among the fictitious replicas that are used to
perform disorder averages (via the replica trick). In the glassy phase the
replica symmetry has to be broken. Using a generalization of the Parisi
solution, we provide analytical results for S_n and I_n, and for standard
thermodynamic quantities. Both S_n and I_n exhibit a volume law in the whole
phase diagram. We characterize the behavior of the corresponding densities
S_n/N, I_n/N, in the thermodynamic limit. Interestingly, at the critical point
the mutual information does not exhibit any crossing for different system
sizes, in contrast with local spin models.


  Modern learning-based approaches to 3D-aware image synthesis achieve high
photorealism and 3D-consistent viewpoint changes for the generated images.
Existing approaches represent instances in a shared canonical space. However,
for in-the-wild datasets a shared canonical system can be difficult to define
or might not even exist. In this work, we instead model instances in view
space, alleviating the need for posed images and learned camera distributions.
We find that in this setting, existing GAN-based methods are prone to
generating flat geometry and struggle with distribution coverage. We hence
propose WildFusion, a new approach to 3D-aware image synthesis based on latent
diffusion models (LDMs). We first train an autoencoder that infers a compressed
latent representation, which additionally captures the images' underlying 3D
structure and enables not only reconstruction but also novel view synthesis. To
learn a faithful 3D representation, we leverage cues from monocular depth
prediction. Then, we train a diffusion model in the 3D-aware latent space,
thereby enabling synthesis of high-quality 3D-consistent image samples,
outperforming recent state-of-the-art GAN-based methods. Importantly, our
3D-aware LDM is trained without any direct supervision from multiview images or
3D geometry and does not require posed images or learned pose or camera
distributions. It directly learns a 3D representation without relying on
canonical camera coordinates. This opens up promising research avenues for
scalable 3D-aware image synthesis and 3D content creation from in-the-wild
image data. See https://katjaschwarz.github.io/wildfusion for videos of our 3D
results.


  In all domains and sectors, the demand for intelligent systems to support the
processing and generation of digital content is rapidly increasing. The
availability of vast amounts of content and the pressure to publish new content
quickly and in rapid succession requires faster, more efficient and smarter
processing and generation methods. With a consortium of ten partners from
research and industry and a broad range of expertise in AI, Machine Learning
and Language Technologies, the QURATOR project, funded by the German Federal
Ministry of Education and Research, develops a sustainable and innovative
technology platform that provides services to support knowledge workers in
various industries to address the challenges they face when curating digital
content. The project's vision and ambition is to establish an ecosystem for
content curation technologies that significantly pushes the current state of
the art and transforms its region, the metropolitan area Berlin-Brandenburg,
into a global centre of excellence for curation technologies.


  Synchrotron x-ray diffraction experiments have been carried out on Eu metal
at ambient temperature to pressures as high as 92 GPa (0.92 Mbar). Following
the well-known bcc-to-hcp transition at 12 GPa, a mixed phase region is
observed from 18 to 66 GPa until finally a single orthorhombic (Pnma) phase
persists from 66 to 92 GPa. These results are compared to predictions from
density functional theory calculations. Under pressure the relatively large
molar volume Vmol of divalent Eu is rapidly diminished, equaling or falling
below Vmol(P) for neighboring trivalent lanthanides above 15 GPa. The present
results suggest that above 15 GPa Eu is neither divalent nor fully trivalent to
pressures as high as 92 GPa.


  We provide the first experimental confirmation of a three-way quantum
coherence identity possessed by single pure-state photons. Our experimental
results demonstrate that traditional wave-particle duality is specifically
limited by this identity. As a new consequence, we show that quantum duality
itself can be amplified, attenuated, or turned completely off. In the Young
double-slit context this quantum coherence identity is found to be directly
relevant, and it supplies a rare quantitative backup for one of Bohr's
philosophical pronouncements.


  Saki and Kiani proved that the subrack lattice of a rack $R$ is necessarily
complemented if $R$ is finite but not necessarily complemented if $R$ is
infinite. In this paper, we investigate further avenues related to the
complementation of subquandles. Saki and Kiani's example of an infinite rack
without complements is a quandle, which is neither ind-finite nor profinite. We
provide an example of an ind-finite quandle whose subobject lattice is not
complemented, and conjecture that profinite quandles have complemented
subobject lattices. Additionally, we provide a complete classification of
subquandles whose set-theoretic complement is also a subquandle, which we call
\textit{strongly complemented}, and provide a partial transitivity criterion
for the complementation in chains of strongly complemented subquandles. One
technical lemma used in establishing this is of independent interest: the inner
automorphism group of a subquandle is always a subquotient of the inner
automorphism group of the ambient quandle.


  Shortcomings of experimental techniques are usually assumed to diminish
nonclassical properties of quantum systems. Here it is demonstrated that this
standard assumption is not true in general. It is theoretically shown that the
inability to resolve different photon numbers in photodetection may
pseudo-increase a measured Bell parameter. Under proper conditions one even
pseudo-violates the quantum Cirel'son bound of the Bell parameter, the
corresponding density operator fails to be positive semi-definite. This paradox
can be resolved by appropriate squash models.


  In a somewhat overlooked work by Seiberg, a definition of the topological
charge for SU(N) lattice fields was given. Here, it is shown that Seibergs and
L\"{u}schers charge definition are related up to the section of the bundle.
With the continued interest in baryon number violating processes, Seibergs
paper is useful since it allows for a Chern-Simons number also.


  It is shown that the excited states of hydrogen atom in a uniform electric
field (Stark States) posess magnetic charge whose magnitude is given by a
Dirac-Saha type relation: $$ {eg\over \hbar c} = \sqrt 3 n $$ An experiment is
proposed to fabricate such states and to detect their magnetic charge.


  We develop a detailed theory for spin transport in a one-dimensional quantum
wire described by Luttinger liquid theory. A hydrodynamic description for the
quantum wire is supplemented by boundary conditions taking into account the
exchange coupling between the magnetization of ferromagnetic reservoirs and the
boundary magnetization in the wire. Spin-charge separation is shown to imply
drastic and qualitative consequences for spin-dependent transport. In
particular, the spin accumulation effect is quenched except for fine-tuned
parameter regimes. We propose several feasible setups involving an external
magnetic field to detect this phenomenon in transport experiments on
single-wall carbon nanotubes. In addition, electron-electron backscattering
processes, which do not have an important effect on thermodynamic properties or
charge transport, are shown to modify spin-dependent transport through long
quantum wires in a crucial way.


  SO(2,1) is the symmetry algebra for a class of three-parameter problems that
includes the oscillator, Coulomb and Morse potentials as well as other problems
at zero energy. All of the potentials in this class can be mapped into the
oscillator potential by point canonical transformations. We call this class the
"oscillator class". A nontrivial graded extension of SO(2,1) is defined and its
realization by two-dimensional matrices of differential operators acting in
spinor space is given. It turns out that this graded algebra is the
supersymmetry algebra for a class of relativistic potentials that includes the
Dirac-Oscillator, Dirac-Coulomb and Dirac-Morse potentials. This class is, in
fact, the relativistic extension of the oscillator class. A new point canonical
transformation, which is compatible with the relativistic problem, is
formulated. It maps all of these relativistic potentials into the
Dirac-Oscillator potential.


  We study the flavor structure of 4D effective theories, which are derived
from extra dimensional theories with magnetic fluxes and non-Abelian Wilson
lines. We study zero-mode wavefunctions and compute Yukawa couplings as well as
four-point couplings. In our models, we also discuss non-Abelian discrete
flavor symmetries such as $D_4$, $\Delta(27)$ and $\Delta(54)$.


  We state and prove that a certain class of smooth functions said to be
BH-separable is a meagre subset for the Fr\'echet topology. Because these
functions are the only admissible Hamiltonians for Arnold-Liouville systems
admitting a bi-Hamiltonian structure, we get that, generically,
Arnold-Liouville systems cannot be bi-Hamiltonian. At the end of the paper, we
determine, both as a concrete representation of our general result and as an
illustrative list, which polynomial Hamiltonians $H$ of the form
$H(x,y)=xy+ax^3+bx^2y+cxy^2+dy^3$ are BH-separable.


  Curvilinear coordinates, first introduced by F. Gygi for valence-only
electronic systems within the local-density functional theory, can be used to
describe both core and valence electrons in electronic-structure calculations.
A simple and quite general coordinate transformation results in a large, yet
affordable plane-wave energy cutoff for full-core systems (e.g., about 120 Ryd
for carbon or silicon) within the local-density functional theory, and in a
reduced correlation time for full-core variational Monte Carlo calculations.
Numerical tests for isolated Li, C, and Si atoms are presented.


  The CANDECOMP/PARAFAC (CP) decomposition is a generalization of the spectral
decomposition of matrices to higher-order tensors. In this paper we use the CP
decomposition to study unitary equivalence of higher order tensors and
construct several invariants of local unitary equivalence for general higher
order tensors. Based on this new method, we study the coefficient tensors of
$3$-qubit states and obtain a necessary and sufficient criterion for local
unitary equivalence of general tripartite states in terms of the CP
decomposition. We also generalize this method to obtain some invariants of
local unitary equivalence for general multi-partite qudits.


  We consider relativistic collisions of heavy hydrogen-like ions with hydrogen
and helium atoms in which the ion-atom interaction causes both colliding
particles to undergo transitions between their internal states. Using an
approach enabling one, for the first time, to give a detailed description of
this important case of the relativistic quantum few-body problem we concentrate
on the study of the longitudinal momentum spectrum of the atomic recoil ions.
We discuss the role of relativistic and higher order effects, predict a
surprisingly strong influence of the projectile's electron on the momentum
transfer, draw the general picture of the recoil ion formation and show that
the important information about the doubly inelastic collisions could be
obtained in experiment merely by measuring the recoil momentum spectrum.


  The scaling laws and extraordinary performance of large foundation models
motivate the development and utilization of such models in biomedicine.
However, despite early promising results on some biomedical benchmarks, there
are still major challenges that need to be addressed before these models can be
used in real-world clinics. Frontier general-domain models such as GPT-4V still
have significant performance gaps in multimodal biomedical applications. More
importantly, less-acknowledged pragmatic issues, including accessibility, model
cost, and tedious manual evaluation make it hard for clinicians to use
state-of-the-art large models directly on private patient data. Here, we
explore training open-source small multimodal models (SMMs) to bridge
competency gaps for unmet clinical needs in radiology. To maximize data
efficiency, we adopt a modular approach by incorporating state-of-the-art
pre-trained models for image and text modalities, and focusing on training a
lightweight adapter to ground each modality to the text embedding space, as
exemplified by LLaVA-Med. For training, we assemble a large dataset of over 697
thousand radiology image-text pairs. For evaluation, we propose CheXprompt, a
GPT-4-based metric for factuality evaluation, and demonstrate its parity with
expert evaluation. For best practice, we conduct a systematic ablation study on
various choices in data engineering and multimodal training. The resulting
LlaVA-Rad (7B) model attains state-of-the-art results on standard radiology
tasks such as report generation and cross-modal retrieval, even outperforming
much larger models such as GPT-4V and Med-PaLM M (84B). The inference of
LlaVA-Rad is fast and can be performed on a single V100 GPU in private
settings, offering a promising state-of-the-art tool for real-world clinical
applications.


  Nature, a synthetic master, creates more than 300,000 natural products (NPs)
which are the major constituents of FDA-proved drugs owing to the vast chemical
space of NPs. To date, there are fewer than 30,000 validated NPs compounds
involved in about 33,000 known enzyme catalytic reactions, and even fewer
biosynthetic pathways are known with complete cascade-connected enzyme
catalysis. Therefore, it is valuable to make computer-aided bio-retrosynthesis
predictions. Here, we develop BioNavi-NP, a navigable and user-friendly
toolkit, which is capable of predicting the biosynthetic pathways for NPs and
NP-like compounds through a novel (AND-OR Tree)-based planning algorithm, an
enhanced molecular Transformer neural network, and a training set that combines
general organic transformations and biosynthetic steps. Extensive evaluations
reveal that BioNavi-NP generalizes well to identifying the reported
biosynthetic pathways for 90% of test compounds and recovering the verified
building blocks for 73%, significantly outperforming conventional rule-based
approaches. Moreover, BioNavi-NP also shows an outstanding capacity of
biologically plausible pathways enumeration. In this sense, BioNavi-NP is a
leading-edge toolkit to redesign complex biosynthetic pathways of natural
products with applications to total or semi-synthesis and pathway elucidation
or reconstruction.


  We report the two-dimensional propagation of photoinduced spin wave packets
in Bi-doped rare-earth iron garnet. Spin waves were excited nonthermally and
impulsively by a circularly polarized light pulse via the inverse Faraday
effect. Space- and time resolved spin waves were detected with a
magneto-optical pump-probe technique. We investigated propagation in two
directions, parallel and perpendicular to the magnetic field. Backward volume
magnetostatic waves (BVMSWs) were detected in both directions. The frequency of
BVMSWs depends on the propagation direction. The experimental results agreed
well with the dispersion relation of BVMSWs.


  Mahler's measure defines a dynamical system on the algebraic numbers. In this
paper, we study the problem of which number fields have points which wander
under the iteration of Mahler's measure. We completely solve the problem for
all abelian number fields, and more generally, for all extensions of the
rationals of degree at most five.


  It is shown that the linearized fields of causal variational principles give
rise to linear bosonic quantum field theories. The properties of these field
theories are studied and compared with the axioms of local quantum physics.
Distinguished quasi-free states are constructed.


  In this paper, the Boiti Leon Pempinelli system in (2+1)-dimensions is
revisited for Lie symmetries and invariant solutions. An infinite-dimensional
Lie algebra is obtained using the Lie invariance criterion and is further
classified into one, two and three-dimensional optimal list of subalgebra. We
obtain new explicit exact solutions involving arbitrary functions that have
never been documented in previous work.


  We define and study slider-pinning rigidity, giving a complete combinatorial
characterization. This is done via direction-slider networks, which are a
generalization of Whiteley's direction networks.


  Gamma-ray bursts (GRBs) and supernovae (SNe) bring new perspectives to the
study of neutron stars and white dwarfs, as well as opening new branches of
theoretical physics and astrophysics.


  This paper presents the concept of an equivalence relation between the set of
optimal control problems. By leveraging this concept, we show that the boundary
of the reachability set can be constructed by the solutions of time optimal
problems. Alongside, a more generalized equivalence theorem is presented
together. The findings facilitate the use of solution structures from a certain
class of optimal control problems to address problems in corresponding
equivalent classes. As a byproduct, we state and prove the construction methods
of the reachability sets of three-dimensional curves with prescribed curvature
bound. The findings are twofold: Firstly, we prove that any boundary point of
the reachability set, with the terminal direction taken into account, can be
accessed via curves of H, CSC, CCC, or their respective subsegments, where H
denotes a helicoidal arc, C a circular arc with maximum curvature, and S a
straight segment. Secondly, we show that any boundary point of the reachability
set, without considering the terminal direction, can be accessed by curves of
CC, CS, or their respective subsegments. These findings extend the developments
presented in literature regarding planar curves, or Dubins car dynamics, into
spatial curves in $\mathbb{R}^3$. For higher dimensions, we confirm that the
problem of identifying the reachability set of curvature bounded paths subsumes
the well-known Markov-Dubins problem. These advancements in understanding the
reachability of curvature bounded paths in $\mathbb{R}^3$ hold significant
practical implications, particularly in the contexts of mission planning
problems and time optimal guidance.


  There are at least two different putative steady state solutions for current
across noncollinear magnetic multilayers; one has a discontinuity in the spin
current at the interface the other is continuous. We compare the resistance of
the two and find the solution with the continuous spin currents is lower. By
using the entropic principle we can state that this solution is a better
estimate of the resistance for a noncollinear magnetic


  We report the synthesis, electronic properties, and electronic structure of
LaIrSi-type BaPtP with a noncentrosymmetric cubic crystal structure. Electrical
resistivity and heat capacity data taken by using polycrystalline samples
indicated that BaPtP is a metal, which was further supported by first
principles calculations. A polycrystalline sample of BaPtP showed a zero
resistivity below 0.2 K due to the superconducting transition. The first
principles calculation results indicated that the spin splitting at around the
Fermi energy is large in BaPtP. These results suggest that BaPtP is likely to
exhibit interesting physical properties caused by a strong spin-orbit coupling
of 5d electrons in the Pt atoms.


  We undertook searches for isolated galaxies based on automatic selection of
infrared sources from the Two Micron All-Sky Survey (2MASS) followed by a
visual inspection of their surrounding. Using a modified criterion by
Karachentseva (1973), we compiled a catalog of 3227 isolated galaxies (2MIG)
containing 6% of 2MASS Extended Sources (2MASX) brighter than $K_s = 12^m$ with
angular diameters $a_K \geq 30\arcsec$.
  The most isolated 2493 galaxies among them enter in the 2MASS Very Isolated
Galaxy Catalog, 2MVIG. Being situated in the regions of extremely low mass
density, the 2MVIG galaxies can serve as a reference sample for investigation
the influence of environment on structure and evolution of galaxies.


  Topological band structures can be designed by subjecting lattice systems to
time-periodic modulations, as was recently demonstrated in cold atoms and
photonic crystals. However, changing the topological nature of Floquet Bloch
bands from trivial to non-trivial, by progressively launching the
time-modulation, is necessarily accompanied with gap-closing processes: this
has important consequences for the loading of particles into a target Floquet
band with non-trivial topology, and hence, on the subsequent measurements. In
this work, we analyse how such loading sequences can be optimized in view of
probing the topology of Floquet bands through transport measurements. In
particular, we demonstrate the robustness of center-of-mass responses, as
compared to current responses, which present important irregularities due to an
interplay between the micro-motion of the drive and inter-band interference
effects. The results presented in this work illustrate how probing the
center-of-mass displacement of atomic clouds offers a reliable method to detect
the topology of Floquet bands, after realistic loading sequences.


  In previous work we developed a method of learning Bayesian Network models
from raw data. This method relies on the well known minimal description length
(MDL) principle. The MDL principle is particularly well suited to this task as
it allows us to tradeoff, in a principled way, the accuracy of the learned
network against its practical usefulness. In this paper we present some new
results that have arisen from our work. In particular, we present a new local
way of computing the description length. This allows us to make significant
improvements in our search algorithm. In addition, we modify our algorithm so
that it can take into account partial domain information that might be provided
by a domain expert. The local computation of description length also opens the
door for local refinement of an existent network. The feasibility of our
approach is demonstrated by experiments involving networks of a practical size.


  We have developed a new model that uses a cellular approach to calculate
radiative transfer of starlight through dusty media. The model is designed to
be user friendly enough to be distributed as a tool for use by the general
astronomical community. Its features include treatment of scattering,
absorption and far infrared emission; propagating many wavelengths
simultaneously; giving 26 views of the output from different direction; and the
ability to cope with arbitrary geometry.
  As an example of the model's use, we have simulated the propagation of
starlight through the edge-on galaxy NGC 891. As well as recovering the
familiar edge-on view, we have a prediction for what the galaxy may look like
if seen at other viewing angles.


  We extend f(R) theories via the addition of a fundamental scalar field. The
approach is reminiscent of the dilaton field of string theory and the
Brans-Dicke model. f(R) theories attracted much attention recently in view of
their potential to explain the acceleration of the universe. Extending f(R)
models to theories with scalars can be motivated from the low energy effective
action of string theory. There, a fundamental scalar (the dilaton), has a
non-minimal coupling to the Ricci scalar. Furthermore beyond tree level actions
will contain terms having higher (or lower) powers of R compared to the
canonical Einstein-Hilbert term. Theories with f(R) will contain an extra
scalar degree on top of the ad-hoc dilaton and mixing of these two modes around
a stable solution is a concern. In this work we show that no mixing condition
mandates the form $V_{1}(\phi)f(R)+V_{2}(\phi)R^{2}$ for the action.


  We present a systematic technique to expand the Einstein-Hilbert Lagrangian
in inverse powers of the speed of light squared. The corresponding result for
the non-relativistic gravity Lagrangian is given up to next-to-next-to-leading
order. The techniques are universal and can be used to expand any Lagrangian
theory whose fields are a function of a given parameter.


  It has been recently shown that $|| F_n(A) ||\leq 2$, where $A$ is a linear
continuous operator acting in a Hilbert space, and $F_n$ is the Faber
polynomial of degree $n$ corresponding to some convex compact $E\subset \mathbb
C$ containing the numerical range of $A$. Such an inequality is useful in
numerical linear algebra, it allows for instance to derive error bounds for
Krylov subspace methods. In the present paper we extend this result to not
necessary convex sets $E$.


  In the $\Lambda$-CDM paradigm, the dark halo governs the gravitational
potential within which a galaxy can form and evolve. In this Letter we show
that the present-day inner ($r<50\text{ kpc}$) dark halo can be significantly
misaligned with the stellar disk. To this end, we use the TNG50 run from the
cosmological magneto-hydrodynamic IllustrisTNG simulation suite. Such "tilted"
dark halos can arise from a variety of processes including major mergers,
massive fly-bys, or interactions with satellite companions. Furthermore, we
show that tilted dark halos: (1) are well traced by tilted stellar halos, (2)
can maintain their tilt for $>$ 5 Gyr in isolated evolution, and (3) can
generate warps in the outer disks that are stable over many Gyr. A tilted dark
halo holds clues to important events in the formation history of a galaxy, and
could help explain the abundance of warped disks in galaxy observations,
including the Milky Way.


  The study of unitarization of representations for non compact real forms of
simple Lie Algebras has been achieved in the past decade by Jakobsen (JA81,
JA83) and by Enright, Howe and Wallach (EH83) following different paths but
arriving at the same final results. In order to discuss unitarity we need to
introduce a scalar product. This is done in sections II and III introducing a
sesquilinear form on the universal enveloping algebra (GL90). Such a
sesquilinear form was introduced by Harish-Chandra (HC55), Gel'fand and
Kirillov (GK69) and Shapovalov (SH72). The new developments given to Jakobsen
method in GEL90 are contained in sections IV and V. In section VI we summarize
the principal results due to Enright Howe and Wallach (EHW method). In section
VII we give the possible places for unitarity including those for which the
reduction level can't be higher than one and that were not considered in GEL90.
We see also in this section and in a explicit way how the Jakobsen method and
the EHW method give the same final results. This type of representations have
found applications in physics for a long time (see GK75, 82; GL83, 89; LO86, 89
and references contained therein) In sections VIII and IX we consider the
conformal and de Sitter algebras. In particular the construction of wave
equations for conformal multispinors and the wave equations in de Sitter space
are reviewed in sections X and XI. In the Appendix we give the representations
of the classical algebras in the subspace Omega extending the results obtained
in LG84 for the algebra A_l.


  Weak decays in heavy nuclei with charge numbers Z=101-109 are studied within
a microscopic formalism based on deformed self-consistent Skyrme Hartree-Fock
mean-field calculations with pairing correlations. The half-lives of beta+
decay and electron capture are compared with alpha-decay half-lives obtained
from phenomenological formulas. Transfermium isotopes of Md, No, Lr, Rf, Db,
Sg, Bh, Hs, and Mt that can be produced in the frontier of cold and hot
fusion-evaporation channels are considered. Several isotopes are identified
whose beta+/EC- and alpha-decay half-lives are comparable. The competition
between these decay modes opens the possibility of new pathways towards the
islands of stability.


  A two-dimensional honeycomb lattice composed of gyrotropic rods is studied.
Beginning with Maxwell's equations, a perturbed Wannier method is introduced
which yields a tight-binding model with nearest and next-nearest neighbors. The
resulting discrete model leads to a Haldane model and as such, topologically
protected modes, associated with nonzero Chern numbers are supported. Changing
the radii of the rods allows for the breaking of inversion symmetry which can
change the topology of the system. This model describes experimental results
associated with topological waves in magneto-optical honeycomb lattices. This
method can also be applied to more general Chern insulator lattices. When
on-site Kerr type nonlinear effects are considered, coherent soliton-like modes
are found to propagate robustly through boundary defects.


  In [8], Fang-Lan-Xiao proved a formula about Lusztig's induction and
restriction functors which can induce Green's formula for the path algebra of a
quiver over a finite field via the trace map. In this paper, we generalize
their formula to that for the mixed semisimple perverse sheaves for a quiver
with an automorphism. By applying the trace map, we obtain Green's formula for
any finite-dimensional hereditary algebra over a finite field.


  We obtain the one-loop propagators in superstring theory for the general case
when the worldsheet fields satisfy non-trivial holonomy and/or boundary
conditions. Non-trivial holonomy arises in orbifold and orientifold backgrounds
whereas non-trivial boundary conditions arise in backgrounds containing
D-branes of different dimensionality or D-branes intersecting each other at an
angle. In our derivation, we use a generalized version of the method of images.
Dihedral groups play a crucial role in constructing the one-loop propagators.


  Federated learning (FL) is a general framework for learning across
heterogeneous clients while preserving data privacy, under the orchestration of
a central server. FL methods often compute gradients of loss functions purely
locally (ie. entirely at each client, or entirely at the server), typically
using automatic differentiation (AD) techniques. We propose a federated
automatic differentiation (FAD) framework that 1) enables computing derivatives
of functions involving client and server computation as well as communication
between them and 2) operates in a manner compatible with existing federated
technology. In other words, FAD computes derivatives across communication
boundaries. We show, in analogy with traditional AD, that FAD may be
implemented using various accumulation modes, which introduce distinct
computation-communication trade-offs and systems requirements. Further, we show
that a broad class of federated computations is closed under these various
modes of FAD, implying in particular that if the original computation can be
implemented using privacy-preserving primitives, its derivative may be computed
using only these same primitives. We then show how FAD can be used to create
algorithms that dynamically learn components of the algorithm itself. In
particular, we show that FedAvg-style algorithms can exhibit significantly
improved performance by using FAD to adjust the server optimization step
automatically, or by using FAD to learn weighting schemes for computing
weighted averages across clients.


  Proper characterization of the host star to a planet is a key element to the
understanding of its overall properties. The star has a direct impact through
the modification of the structure and evolution of the planet atmosphere by
being the overwhelmingly larger source of energy. The star plays a central role
in shaping the structure, evolution, and even determining the mere existence of
planetary atmospheres. The vast majority of the stellar flux is well understood
thanks to the impressive progress made in the modeling of stellar atmospheres.
At short wavelengths (X-rays to UV), however, the information is scarcer since
the stellar emission does not originate in the photosphere but in the
chromospheric and coronal regions, which are much less understood. The same can
be said about particle emissions, with a strong impact on planetary
atmospheres, because a detailed description of the time-evolution of stellar
wind is still lacking. Here we review our current understanding of the flux and
particle emissions of the Sun and low-mass stars and briefly address their
impact in the context of planetary atmospheres.


  Progressive Neural Network Learning is a class of algorithms that
incrementally construct the network's topology and optimize its parameters
based on the training data. While this approach exempts the users from the
manual task of designing and validating multiple network topologies, it often
requires an enormous number of computations. In this paper, we propose to speed
up this process by exploiting subsets of training data at each incremental
training step. Three different sampling strategies for selecting the training
samples according to different criteria are proposed and evaluated. We also
propose to perform online hyperparameter selection during the network
progression, which further reduces the overall training time. Experimental
results in object, scene and face recognition problems demonstrate that the
proposed approach speeds up the optimization procedure considerably while
operating on par with the baseline approach exploiting the entire training set
throughout the training process.


  We prove that the pleated hyperbolic paraboloid, a familiar origami model
known since 1927, in fact cannot be folded with the standard crease pattern in
the standard mathematical model of zero-thickness paper. In contrast, we show
that the model can be folded with additional creases, suggesting that real
paper "folds" into this model via small such creases. We conjecture that the
circular version of this model, consisting simply of concentric circular
creases, also folds without extra creases.
  At the heart of our results is a new structural theorem characterizing
uncreased intrinsically flat surfaces--the portions of paper between the
creases. Differential geometry has much to say about the local behavior of such
surfaces when they are sufficiently smooth, e.g., that they are torsal ruled.
But this classic result is simply false in the context of the whole surface.
Our structural characterization tells the whole story, and even applies to
surfaces with discontinuities in the second derivative. We use our theorem to
prove fundamental properties about how paper folds, for example, that straight
creases on the piece of paper must remain piecewise-straight (polygonal) by
folding.


  We re-investigate the old problem of the survival of the five globular
clusters orbiting the Fornax dwarf galaxy in both standard and modified
Newtonian dynamics. For the first time in the history of the topic, we use
accurate mass models for the Fornax dwarf, obtained through Jeans modelling of
the recently published line of sight velocity dispersion data, and we are also
not resigned to circular orbits for the globular clusters. Previously conceived
problems stem from fixing the starting distances of the globulars to be less
than half the tidal radius. We relax this constraint since there is absolutely
no evidence for it and show that the dark matter paradigm, with either cusped
or cored dark matter profiles, has no trouble sustaining the orbits of the two
least massive globular clusters for a Hubble time almost regardless of their
initial distance from Fornax. The three most massive globulars can remain in
orbit as long as their starting distances are marginally outside the tidal
radius. The outlook for modified Newtonian dynamics is also not nearly as bleak
as previously reported. Although dynamical friction inside the tidal radius is
far stronger in MOND, outside dynamical friction is negligible due to the
absence of stars. This allows highly radial orbits to survive, but more
importantly circular orbits at distances more than 85% of Fornax's tidal radius
to survive indefinitely. The probability of the globular clusters being on
circular orbits at this distance compared with their current projected
distances is discussed and shown to be plausible. Finally, if we ignore the
presence of the most massive globular (giving it a large line of sight
distance) we demonstrate that the remaining four globulars can survive within
the tidal radius for the Hubble time with perfectly sensible orbits.


  Let $\Gamma$ be a finitely generated group and $X$ be a minimal compact
$\Gamma$-space. We assume that the $\Gamma$-action is micro-supported, i.e. for
every non-empty open subset $U \subseteq X$, there is an element of $\Gamma$
acting non-trivially on $U$ and trivially on the complement $X \setminus U$. We
show that, under suitable assumptions, the existence of certain commensurated
subgroups in $\Gamma$ yields strong restrictions on the dynamics of the
$\Gamma$-action: the space $X$ has compressible open subsets, and it is an
almost $\Gamma$-boundary. Those properties yield in turn restrictions on the
structure of $\Gamma$: $\Gamma$ is neither amenable nor residually finite.
Among the applications, we show that the (alternating subgroup of the)
topological full group associated to a minimal and expansive Cantor action of a
finitely generated amenable group has no commensurated subgroups other than the
trivial ones. Similarly, every commensurated subgroup of a finitely generated
branch group is commensurate to a normal subgroup; the latter assertion relies
on an appendix by Dominik Francoeur, and generalizes a result of Phillip
Wesolek on finitely generated just-infinite branch groups. Other applications
concern discrete groups acting on the circle, and the centralizer lattice of
non-discrete totally disconnected locally compact (tdlc) groups. Our results
rely, in an essential way, on recent results on the structure of tdlc groups,
on the dynamics of their micro-supported actions, and on the notion of
uniformly recurrent subgroups.


  We present a self-consistent field approximation to the problem of the
genetic switch composed of two mutually repressing/activating genes. The
protein and DNA state dynamics are treated stochastically and on equal footing.
In this approach the mean influence of the proteomic cloud created by one gene
on the action of another is self-consistently computed. Within this
approximation a broad range of stochastic genetic switches may be solved
exactly in terms of finding the probability distribution and its moments. A
much larger class of problems, such as genetic networks and cascades also
remain exactly solvable with this approximation. We discuss in depth certain
specific types of basic switches, which are used by biological systems and
compare their behavior to the expectation for a deterministic switch.


  We provide an axiomatic framework for working with a wide variety of closure
operations on ideals and submodules in commutative algebra, including notions
of reduction, independence, spread, and special parts of closures. This
framework is applied to tight, Frobenius, and integral closures. Applications
are given to evolutions and special Brian\c{c}on-Skoda theorems.


  To address increasing compute demand from recent multi-model workloads with
heavy models like large language models, we propose to deploy heterogeneous
chiplet-based multi-chip module (MCM)-based accelerators. We develop an
advanced scheduling framework for heterogeneous MCM accelerators that
comprehensively consider complex heterogeneity and inter-chiplet pipelining.
Our experiments using our framework on GPT-2 and ResNet-50 models on a
4-chiplet system have shown upto 2.2x and 1.9x increase in throughput and
energy efficiency, compared to a monolithic accelerator with an optimized
output-stationary dataflow.


  In this paper, we consider the problem of estimating a conditional density in
moderately large dimensions. Much more informative than regression functions,
conditional densities are of main interest in recent methods, particularly in
the Bayesian framework (studying the posterior distribution, finding its
modes...). Considering a recently studied family of kernel estimators, we
select a pointwise multivariate bandwidth by revisiting the greedy algorithm
Rodeo (Regularisation Of Derivative Expectation Operator). The method addresses
several issues: being greedy and computationally efficient by an iterative
procedure, avoiding the curse of high dimensionality under some suitably
defined sparsity conditions by early variable selection during the procedure,
converging at a quasi-optimal minimax rate.


  A modified equation, the S-K equation, fits data that the current neural
conduction equation, the K-R equation, does not. The S-K equation is a modified
Heaviside equation, based on a new interpretation of cross terms. Elements of
neural anatomy and function are reviewed to put the S-K equation into context.
The fit between S-K and resonance-like neural data is then shown.
  Appendix 1: Derivation of crossterms that represent combinations of physical
laws for a line conductor of finite length.
  Appendix 2: Evaluation of crossterms that represent combinations of physical
laws according to consistency arguments.
  Appendix 3: Some background on resonance.
  Appendix 4: Web access to some brain modeling, correspondence with NATURE,
and discussion of the work in George Johnson's New York Times forums.


  We ``quantify'' the role of elastic as well as inelastic gg<->ggg pQCD
processes in kinetic equilibration within a pQCD inspired parton cascade. The
contributions of different processes to kinetic equilibration are manifested by
the transport collision rates. We find that in a central Au+Au collision at
RHIC energy pQCD Bremstrahlung processes are much more efficient for momentum
isotropization compared to elastic scatterings. For the parameters chosen the
ratio of their transport collision rates amounts to 5:1.


  We compare the conjecture of Buzzard-Gee on the association of Galois
representations to C-algebraic automorphic representations with the conjectural
description of the cohomology of Shimura varieties due to Kottwitz, and the
reciprocity law at infinity due to Arthur. This is done by extending
Langlands's representation of the L-group associated with a Shimura datum to a
representation of the C-group of Buzzard-Gee. The approach offers an
explanation of the explicit Tate twist appearing in Kottwitz's description.


  The Fermi-Pasta-Ulam (FPU) problem consists of the nonequipartition of energy
among normal modes of a weakly anharmonic atomic chain model. In the harmonic
limit each normal mode corresponds to a periodic orbit in phase space and is
characterized by its wave number q. We continue normal modes from the harmonic
limit into the FPU parameter regime and obtain persistence of these periodic
orbits, termed here q-Breathers (QB). They are characterized by time
periodicity, exponential localization in the q-space of normal modes and linear
stability up to a size-dependent threshold amplitude. Trajectories computed in
the original FPU setting are perturbations around these exact QB solutions. The
QB concept is applicable to other nonlinear lattices as well.


  The present paper deals with the Cauchy problem of a multi-dimensional
non-conservative viscous compressible two-fluid system. We first study the
well-posedness of the model in spaces with critical regularity indices with
respect to the scaling of the associated equations. In the functional setting
as close as possible to the physical energy spaces, we prove the unique global
solvability of strong solutions close to a stable equilibrium state.
Furthermore, under a mild additional decay assumption involving only the low
frequencies of the data, we establish the time decay rates for the constructed
global solutions. The proof relies on an application of Fourier analysis to a
complicated parabolic-hyperbolic system, and on a refined time-weighted
inequality.


  We formulate and solve the energy minimization problem for a clustered
device-to-device (D2D) network with cache-enabled mobile devices. Devices are
distributed according to a Poisson cluster process (PCP) and are assumed to
have a surplus memory which is exploited to proactively cache files from a
library. Devices can retrieve the requested files from their caches, from
neighboring devices in their proximity (cluster), or from the base station as a
last resort. We minimize the energy consumption of the proposed network under a
random prob- abilistic caching scheme, where files are independently cached
according to a specific probability distribution. A closed-form expression for
the D2D coverage probability is obtained. The energy consumption problem is
then formulated as a function of the caching distribution, and the optimal
probabilistic caching distribution is obtained. Results reveal that the
proposed caching distribution reduces energy consumption up to 33% as compared
to caching popular files scheme.


  We argue that a particular spacetime, a spherically symmetric spacetime with
hyper-surface orthogonal, radial, homothetic Killing vector, is a physically
meaningful spacetime that describes the problem of spherical gravitational
collapse in its full "physical" generality.


  We present a long (~76 ks) Chandra observation of IRAS 09104+4109, a
hyper-luminous galaxy, optically classified as a Type 2 AGN hosted in a cD
galaxy in a cluster at z=0.442. We also report on the results obtained by
fitting its broad-band spectral energy distribution. The Compton-thick nature
of this source (which has been often referred to as an "archetype" of
Compton-thick Type 2 quasars) was formerly claimed on the basis of its marginal
detection in the PDS instrument onboard BeppoSAX, being then disputed using
XMM-Newton data. Both Chandra analysis and optical/mid-IR spectral fitting are
consistent with the presence of heavy (~1-5 10^{23} cm^{-2}) but not extreme
(Compton-thick) obscuration. However, using the mid-IR and the [OIII] emission
as proxies of the nuclear hard X-ray luminosity suggests the presence of
heavier obscuration. The 54-month Swift BAT map shows excess hard X-ray
emission likely related to a nearby (z=0.009) Type 2 AGN, close enough to IRAS
09104+4109 to significantly enhance and contaminate its emission in the early
BeppoSAX PDS data.


  RISC-V is a promising open-source architecture primarily targeted for
embedded systems. Programs compiled using the RISC-V toolchain can run
bare-metal on the system, and, as such, can be vulnerable to several memory
corruption vulnerabilities. In this work, we present HeapSafe, a lightweight
hardware assisted heap-buffer protection scheme to mitigate heap overflow and
use-after-free vulnerabilities in a RISC-V SoC. The proposed scheme tags
pointers associated with heap buffers with metadata indices and enforces tag
propagation for commonly used pointer operations. The HeapSafe hardware is
decoupled from the core and is designed as a configurable coprocessor and is
responsible for validating the heap buffer accesses. Benchmark results show a
1.5X performance overhead and 1.59% area overhead, while being 22% faster than
a software protection. We further implemented a HeapSafe-nb, an asynchronous
validation design, which improves performance by 27% over the synchronous
HeapSafe.


  In this paper, we investigate spectrum-power trading between a small cell
(SC) and a macro cell (MC), where the SC consumes power to serve the macro cell
users (MUs) in exchange for some bandwidth from the MC. Our goal is to maximize
the system energy efficiency (EE) of the SC while guaranteeing the quality of
service of each MU as well as small cell users (SUs). Specifically, given the
minimum data rate requirement and the bandwidth provided by the MC, the SC
jointly optimizes MU selection, bandwidth allocation, and power allocation
while guaranteeing its own minimum required system data rate. The problem is
challenging due to the binary MU selection variables and the fractional- form
objective function. We first show that the bandwidth of an MU is shared with at
most one SU in the SC. Then, for a given MU selection, the optimal bandwidth
and power allocation is obtained by exploiting the fractional programming. To
perform MU selection, we first introduce the concept of the trading EE to
characterize the data rate obtained as well as the power consumed for serving
an MU. We then reveal a sufficient and necessary condition for serving an MU
without considering the total power constraint and the minimum data rate
constraint: the trading EE of the MU should be higher than the system EE of the
SC. Based on this insight, we propose a low complexity MU selection method and
also investigate the optimality condition. Simulation results verify our
theoretical findings and demonstrate that the proposed resource allocation
achieves near-optimal performance.


  With the measurement of the small parameter $\sin^{2}\theta_{13}$ experiments
on the study of neutrino oscillations enter into a high precision era. I
discuss here the problem of the definition of the atmospheric mass-squared
difference which will be important for analysis of data of future experiments.


  A connected dominating set is a widely adopted model for the virtual backbone
of a wireless sensor network. In this paper, we design an evolutionary
algorithm for the minimum connected dominating set problem (MinCDS), whose
performance is theoretically guaranteed in terms of both computation time and
approximation ratio. Given a connected graph $G=(V,E)$, a connected dominating
set (CDS) is a subset $C\subseteq V$ such that every vertex in $V\setminus C$
has a neighbor in $C$, and the subgraph of $G$ induced by $C$ is connected. The
goal of MinCDS is to find a CDS of $G$ with the minimum cardinality. We show
that our evolutionary algorithm can find a CDS in expected $O(n^3)$ time which
approximates the optimal value within factor $(2+\ln\Delta)$, where $n$ and
$\Delta$ are the number of vertices and the maximum degree of graph $G$,
respectively.


  Motivated both by considerations of the generation of large-scale
astrophysical magnetic fields and by potential problems with mean magnetic
field generation by turbulent convection, we investigate the mean electromotive
force (emf) resulting from the magnetic buoyancy instability of a rotating
layer of stratified magnetic field, considering both unidirectional and sheared
fields. We discuss why the traditional decomposition into $\alpha$ and $\beta$
effects is inappropriate in this case, and that it is only consideration of the
entire mean emf that is meaningful. By considering a weighted average of the
unstable linear eigenmodes, and averaging over the horizontal plane, we obtain
depth-dependent emfs. For the simplified case of isothermal, ideal MHD we are
able to obtain an analytic expression for the emf; more generally the emf has
to be determined numerically. We calculate how the emf depends on the various
parameters of the problem, particularly the rotation rate and the latitude of
the magnetic layer.


  We consider -- within QED(2) -- the backreaction to the Schwinger pair
creation in a time dependent, spatially homogeneous electric field. Our focus
is the depletion of the external field as a quench and the subsequent long-term
evolution of the resulting electric field. Our numerical solutions of the self
consistent, fully backreacted dynamical equations exhibit a self-sustaining
oscillation of both the electric field and the pair number depending on the
coupling strength.


  Strong pinning depends on the pinning force strength and number density of
effective defects. Using hydrostatic pressure method, we demonstrate that
hydrostatic pressure up to 1.2 GPa can significantly enhance flux pinning or Jc
by a factor of up to 5 especially in both low and high fields in optimally
doped Ba0.6K0.4Fe2As2 crystals. Our analysis on the flux pining mechanism
indicate that both pinning centre number density (Np) and pinning force (Fp)
are greatly increased by the pressure and contribute to strong pinning.