  The 2009 November outburst of the neutron star X-ray binary Aquila X-1 was
observed with unprecedented radio coverage and simultaneous pointed X-ray
observations, tracing the radio emission around the full X-ray hysteresis loop
of the outburst for the first time. We use these data to discuss the disc-jet
coupling, finding the radio emission to be consistent with being triggered at
state transitions, both from the hard to the soft spectral state and vice
versa. Our data appear to confirm previous suggestions of radio quenching in
the soft state above a threshold X-ray luminosity of about 10% of the Eddington
luminosity. We also present the first detections of Aql X-1 with Very Long
Baseline Interferometry (VLBI), showing that any extended emission is
relatively diffuse, and consistent with steady jets rather than arising from
discrete, compact knots. In all cases where multi-frequency data were
available, the source radio spectrum is consistent with being flat or slightly
inverted, suggesting that the internal shock mechanism that is believed to
produce optically thin transient radio ejecta in black hole X-ray binaries is
not active in Aql X-1.


  The Event Horizon Telescope (EHT) is a very long baseline interferometry
(VLBI) array that comprises millimeter- and submillimeter-wavelength telescopes
separated by distances comparable to the diameter of the Earth. At a nominal
operating wavelength of ~1.3 mm, EHT angular resolution (lambda/D) is ~25
micro-as, which is sufficient to resolve nearby supermassive black hole
candidates on spatial and temporal scales that correspond to their event
horizons. With this capability, the EHT scientific goals are to probe general
relativistic effects in the strong-field regime and to study accretion and
relativistic jet formation near the black hole boundary. In this Letter we
describe the system design of the EHT, detail the technology and
instrumentation that enable observations, and provide measures of its
performance. Meeting the EHT science objectives has required several key
developments that have facilitated the robust extension of the VLBI technique
to EHT observing wavelengths and the production of instrumentation that can be
deployed on a heterogeneous array of existing telescopes and facilities. To
meet sensitivity requirements, high-bandwidth digital systems were developed
that process data at rates of 64 gigabit/s, exceeding those of currently
operating cm-wavelength VLBI arrays by more than an order of magnitude.
Associated improvements include the development of phasing systems at array
facilities, new receiver installation at several sites, and the deployment of
hydrogen maser frequency standards to ensure coherent data capture across the
array. These efforts led to the coordination and execution of the first Global
EHT observations in 2017 April, and to event-horizon-scale imaging of the
supermassive black hole candidate in M87.


  The growth and development of the mobile phone network has led to an
increased demand for energy by the telecommunications sector, with a noticeable
impact on the environment. Monitoring of energy consumption is a great tool for
understanding how to better manage this consumption and find the best strategy
to adopt in order to maximize reduction of unnecessary usage of electricity.
This paper reports on a monitoring campaign performed on six Base Transceiver
Stations (BSs) located central Italy, with different technology, typology and
technical characteristics. The study focuses on monitoring energy consumption
and environmental parameters (temperature, noise, and global radiation),
linking energy consumption with the load of telephone traffic and with the air
conditioning functions used to cool the transmission equipment. Moreover, using
experimental data collected, it is shown, with a Monte Carlo simulation based
on power saving features, how the BS monitored could save energy.


  The future apparent horizon of a black hole develops large stress energy due
to quantum effects, unless the outgoing modes are in a thermal density matrix
at the local Hawking temperature. It is shown for generic pure states that the
deviation from thermality is so small that an infalling observer will see no
drama on their way to the stretched horizon, providing a derivation of black
hole complementarity after the Page time. Atypical pure states, and atypical
observers, may of course see surprises, but that is not surprising.


  This talk outlines some results for gravitational theories with local Lorentz
violation in the context of the Lorentz- and CPT-violating Standard-Model
Extension.


  Convergence failure and slow convergence rate are among the biggest
challenges with solving the system of non-linear equations numerically. While
using strictly small time steps sizes and unconditionally stable fully implicit
scheme mitigate the problem, the computational load becomes enormous. We
introduce a sequential local refinement scheme in space-time domain that
improves convergence rate and prevents convergence failure while not
restricting to small time step, thus boosting computational efficiency. We rely
on the non-linear two-phase flow model. The algorithm starts by solving the
coarsest mesh. Then regions with certain features such as saturation front is
refined to the finest resolution sequentially. Such process prevents
convergence failure. After each refinement, the solution from the previous mesh
is used to estimate initial guess of the current mesh for faster convergence.
Numerical results are presented to confirm accuracy of our algorithm as
compared to the traditional fine time step approach. We also observe 5 times
speedup in the runtime by using our algorithm.


  The formation of a $2.7\ \rm M_{\odot}$ supermassive neutron star is
explored, as the possible companion of PSR J0514--4002E. Magnetars may
experience super-Eddington accretion. Observationally they may manifest
themselves as ultraluminous X-ray pulsars. We propose that supermassive neutron
stars may be formed through ultraluminous X-ray pulsar phase, if the
ultraluminous X-ray pulsar phase can last for $10^{5}$--$10^6 \ \rm yr$. The
accreted material will also bury the magnetic field of the neutron star.
Assuming accretion equilibrium, the final output may be a millisecond
supermassive neutron star. In order for the ultraluminous X-ray pulsar phase to
last long enough, a magnetic field configuration of the low magnetic field
magnetar is required. The mass, magnetic field and rotational evolution of
super-Eddington accreting neutron stars are rather robust against different
assumptions, although many of the model details are yet to be determined.


  We provide an open source framework to experiment with evolutionary
algorithms which we call "Experimenting and Learning toolkit for Evolutionary
Algorithms (ELEA)". ELEA is browser-based and allows to assemble evolutionary
algorithms using drag-and-drop, starting from a number of simple pre-designed
examples, making the startup costs for employing the toolkit minimal. The
designed examples can be executed and collected data can be displayed
graphically. Further features include export of algorithm designs and
experimental results as well as multi-threading. With the very intuitive user
interface and the short time to get initial experiments going, this tool is
especially suitable for explorative analyses of algorithms as well as for the
use in classrooms.


  We address the problem of novel view video prediction; given a set of input
video clips from a single/multiple views, our network is able to predict the
video from a novel view. The proposed approach does not require any priors and
is able to predict the video from wider angular distances, upto 45 degree, as
compared to the recent studies predicting small variations in viewpoint.
Moreover, our method relies only onRGB frames to learn a dual representation
which is used to generate the video from a novel viewpoint. The dual
representation encompasses a view-dependent and a global representation which
incorporates complementary details to enable novel view video prediction. We
demonstrate the effectiveness of our framework on two real world datasets:
NTU-RGB+D and CMU Panoptic. A comparison with the State-of-the-art novel view
video prediction methods shows an improvement of 26.1% in SSIM, 13.6% in PSNR,
and 60% inFVD scores without using explicit priors from target views.


  We determine the dynamical black hole mass in NGC404 including modeling of
the nuclear stellar populations. We combine \hst/STIS spectroscopy with WFC3
images to create a local color-\ml~relation derived from stellar population
modeling of the STIS data. We then use this to create a mass model for the
nuclear region. We use Jeans modeling to fit this mass model to adaptive optics
stellar kinematic observations from Gemini/NIFS. From our stellar dynamical
modeling, we find a 3$\sigma$ upper limit on the black hole mass of
$1.5\times10^5$\Msun.


  The autonomous quadrotor's flying speed has kept increasing in the past 5
years, especially in the field of autonomous drone racing. However, the
majority of the research mainly focuses on the aggressive flight of a single
quadrotor. In this letter, we propose a novel method called Pairwise Model
Predictive Control (PMPC) that can guide two quadrotors online to fly through
the waypoints with minimum time without collisions. The flight task is first
modeled as a nonlinear optimization problem and then an efficient two-step mass
point velocity search method is used to provide initial values and references
to improve the solving efficiency so that the method can run online with a
frequency of 50 Hz and can handle dynamic waypoints. The simulation and
real-world experiments validate the feasibility of the proposed method and in
the real-world experiments, the two quadrotors can achieve a top speed of
8.1m/s in a 6-waypoint racing track in a compact flying arena of 6m*4m*2m.


  Backbone members are recognized as essential parts of an organization, yet
their role and mechanisms of functioning in networks are not fully understood.
In this paper, we propose a new framework called Twotier to analyze the
evolution of community sports organizations (CSOs) and the role of backbone
members. Tier-one establishes a dynamic user interaction network based on
grouping relationships, and weighted k-shell decomposition is used to select
backbone members. We perform community detection and capture the evolution of
two separate sub-networks: one formed by backbone members and the other formed
by other members. In Tier-two, the sub-networks are abstracted, revealing a
core-periphery structure in the organization where backbone members serve as
bridges connecting all parts of the network. Our findings suggest that relying
on backbone members can keep newcomers actively involved in rewarding
activities, while non-rewarding activities solidify relations between backbone
members.


  We present a new many body formalism for BCS-BEC crossover, which represents
a modification of the BCS-Leggett ground state to include 4-fermion, and higher
correlations. In the BEC regime, we show how our approach contains the
\textit{Petrov et al} 4-fermion behavior and associated scattering length
$a_{dd}$ at short distances, and secondly reduces to composite-boson Bogoliubov
physics at long distances. It reproduces the Lee-Yang term, whose numerical
value is also fixed by $a_{dd}$. We have also examined the next term beyond the
Lee-Yang correction in a phenomenological fashion, building on cloud size data
and collective mode experiments. However, one has to view this phenomenological
analysis with some caution since experiments are in a state of flux and are
performed close to unitarity.


  In Ref. [1] we presented the JIMWLK Hamiltonian for high energy evolution of
QCD amplitudes at the next-to-leading order accuracy in $\alpha_s$. In the
present paper we provide details of our original derivation, which was not
reported in [1], and provide the Hamiltonian in the form appropriate for action
on color singlet as well as color nonsinglet states. The rapidity evolution of
the quark dipole generated by this Hamiltonian is computed and compared with
the corresponding result of Balitsky and Chirilli [2]. We then establish the
equivalence between the NLO JIMWLK Hamiltonian and the NLO version of the
Balitsky's hierarchy [3], which includes action on nonsinglet combinations of
Wilson lines. Finally, we present complete evolution equation for three-quark
Wilson loop operator, thus extending the results of Grabovsky [4].


  Artistic style transfer is an image synthesis problem where the content of an
image is reproduced with the style of another. Recent works show that a
visually appealing style transfer can be achieved by using the hidden
activations of a pretrained convolutional neural network. However, existing
methods either apply (i) an optimization procedure that works for any style
image but is very expensive, or (ii) an efficient feedforward network that only
allows a limited number of trained styles. In this work we propose a simpler
optimization objective based on local matching that combines the content
structure and style textures in a single layer of the pretrained network. We
show that our objective has desirable properties such as a simpler optimization
landscape, intuitive parameter tuning, and consistent frame-by-frame
performance on video. Furthermore, we use 80,000 natural images and 80,000
paintings to train an inverse network that approximates the result of the
optimization. This results in a procedure for artistic style transfer that is
efficient but also allows arbitrary content and style images.


  Many problems in machine learning can be formulated as solving
entropy-regularized optimal transport on the space of probability measures. The
canonical approach involves the Sinkhorn iterates, renowned for their rich
mathematical properties. Recently, the Sinkhorn algorithm has been recast
within the mirror descent framework, thus benefiting from classical
optimization theory insights. Here, we build upon this result by introducing a
continuous-time analogue of the Sinkhorn algorithm. This perspective allows us
to derive novel variants of Sinkhorn schemes that are robust to noise and bias.
Moreover, our continuous-time dynamics not only generalize but also offer a
unified perspective on several recently discovered dynamics in machine learning
and mathematics, such as the "Wasserstein mirror flow" of (Deb et al. 2023) or
the "mean-field Schr\"odinger equation" of (Claisse et al. 2023).


  Motion under stochastic resetting serves to model a myriad of processes in
physics and beyond, but in most cases studied to date resetting to the origin
was assumed to take zero time or a time decoupled from the spatial position at
the resetting moment. However, in our world, getting from one place to another
always takes time and places that are further away take more time to be
reached. We thus set off to extend the theory of stochastic resetting such that
it would account for this inherent spatio-temporal coupling. We consider a
particle that starts at the origin and follows a certain law of stochastic
motion until it is interrupted at some random time. The particle then returns
to the origin via a prescribed protocol. We study this model and surprisingly
discover that the shape of the steady-state distribution which governs the
stochastic motion phase does not depend on the return protocol. This shape
invariance then gives rise to a simple, and generic, recipe for the computation
of the full steady-state distribution. Several case studies are analyzed and a
class of processes whose steady-state is completely invariant with respect to
the speed of return is highlighted. For processes in this class we recover the
same steady-state obtained for resetting with instantaneous
returns---irrespective of whether the actual return speed is high or low. Our
work significantly extends previous results on motion with stochastic resetting
and is expected to find various applications in statistical, chemical, and
biological physics.


  The pseudoscalar sum rules of the heavy-light quark systems are used for
extracting simultaneously the c,b quark masses and the decay constants
f_D_(s),f_B_(s) of the D_(s),B_(s) mesons. To order alpha_s^2, one obtains the
running quark masses: m_c(m_c)=(1.10 \pm 0.04) GeV, m_b(m_b)=(4.05\pm 0.06)
GeV, the perturbative pole masses: M_c=(1.46\pm 0.04) GeV, M_b=(4.69\pm 0.06)
GeV, and the decay constants: f_D=(205\pm 20) MeV, f_B=(203\pm 23) MeV and
f_D_s=(235\pm 24) MeV, f_B_s=(236\pm 30) MeV, in the normalization where f_\pi=
130.56 MeV. The fitted values of the pole and running masses satisfy quite well
their three-loop perturbative relation. The value f_D = f_B confirms earlier
findings from the sum rule that the 1/M_P^1/2 heavy quark symmetry scaling law
is affected by large 1/M_P corrections.


  We are communicating with computers on two different levels. On upper level
we have a very flexible system of windows: we can move them, resize, overlap or
put side by side. At any moment we decide what would be the best view and
reorganize the whole view easily. Then we start any application, go to the
inner level, and everything changes. Here we are stripped of all the
flexibility and can work only inside the scenario, developed by the designer of
the program. Interface will allow us to change some tiny details, but in
general everything is fixed: graphics is neither moveable, nor resizable, and
the same with controls. Author designed an extremely powerful mechanism of
turning graphical objects and controls into moveable and resizable. This can
not only significantly improve the existing applications, but this will bring
the applications to another level. (To estimate the possible difference, try to
imagine the Windows system without its flexibility and compare it with the
current one.) This article explains in details the construction and use of
moveable and resizable graphical objects.


  We aim at studying the effect of a cosmologically motivated gas infall law
for the formation of a massive elliptical galaxy in order to understand its
impact on the formation of the spheroids. We replace the empirical infall law
of the model by Pipino & Matteucci with a cosmologically derived infall law for
the formation of an elliptical galaxy. We constrast our predictions with
observations. We also compare the obtained results with those of Pipino &
Matteucci. We computed models with and without galactic winds: we found that
models without wind predict a too large current SNIa rate. In particular, the
cosmological model produces a current SNIa which is about ten times higher than
the observed values. Moreover models without wind predict a large current SNII
rate, too large even if compared with the recent GALEX data. The predicted SNII
rate for the model with wind, on the other hand, is too low if compared with
the star formation histories given by GALEX. Last but not least, the mean value
for the [Mg/Fe] ratio in the dominant stellar population of the simulated
galaxy, as predicted by the cosmological model, is too low if compared to
observations. This is, a very important result indicating that the cosmological
infall law is in contrast with the chemical evolution. A cosmologically derived
infall law for an elliptical galaxy cannot reproduce all the chemical
constraints given by the observations. The problem resides in the fact that the
cosmologically derived infall law implies a slow gas accretion with consequent
star formation rate active for a long period. In this situation low [Mg/Fe]
ratios are produced for the dominant stellar population in a typical
elliptical, at variance with observations.


  Air traffic control is an example of a highly challenging operational problem
that is readily amenable to human expertise augmentation via decision support
technologies. In this paper, we propose a new intelligent decision making
framework that leverages multi-agent reinforcement learning (MARL) to
dynamically suggest adjustments of aircraft speeds in real-time. The goal of
the system is to enhance the ability of an air traffic controller to provide
effective guidance to aircraft to avoid air traffic congestion, near-miss
situations, and to improve arrival timeliness. We develop a novel deep ensemble
MARL method that can concisely capture the complexity of the air traffic
control problem by learning to efficiently arbitrate between the decisions of a
local kernel-based RL model and a wider-reaching deep MARL model. The proposed
method is trained and evaluated on an open-source air traffic management
simulator developed by Eurocontrol. Extensive empirical results on a real-world
dataset including thousands of aircraft demonstrate the feasibility of using
multi-agent RL for the problem of en-route air traffic control and show that
our proposed deep ensemble MARL method significantly outperforms three
state-of-the-art benchmark approaches.


  In recent years, remarkable advances in photonic computing have highlighted
the need for photonic memory, particularly high-speed and coherent
random-access memory. Addressing the ongoing challenge of implementing photonic
memories is required to fully harness the potential of photonic computing. A
photonic-phononic memory based on stimulated Brillouin scattering is a possible
solution as it coherently transfers optical information into sound waves at
high-speed access times. Such an optoacoustic memory has shown great potential
as it fulfils key requirements for high-performance optical random-access
memory due to its coherence, on-chip compatibility, frequency selectivity, and
high bandwidth. However, the storage time has so far been limited to a few
nanoseconds due to the nanosecond decay of the acoustic wave. In this work, we
experimentally enhance the intrinsic storage time of an optoacoustic memory by
more than one order of magnitude and coherently retrieve optical information
after a storage time of 120 ns. This is achieved by employing the optoacoustic
memory in a highly nonlinear fiber at 4.2 K, increasing the intrinsic phonon
lifetime by a factor of six. We demonstrate the capability of our scheme by
measuring the initial and readout optical data pulse with a direct and double
homodyne detection scheme. Finally, we analyze the dynamics of the optoacoustic
memory at different cryogenic temperatures in the range of 4.2 K to 20 K and
compare the findings to continuous wave measurements. The extended storage time
is not only beneficial for photonic computing, but also for Brillouin
applications that require long phonon lifetimes, such as optoacoustic filters,
true-time delay networks, and synthesizers in microwave photonics.


  Range-aggregate query is an important type of queries with numerous
applications. It aims to obtain some structural information (defined by an
aggregate function $F(\cdot)$) of the points (from a point set $P$) inside a
given query range $B$. In this paper, we study the range-aggregate query
problem in high dimensional space for two aggregate functions: (1) $F(P \cap
B)$ is the farthest point in $P \cap B$ to a query point $q$ in $\mathbb{R}^d$
and (2) $F(P \cap B)$ is the minimum enclosing ball (MEB) of $P \cap B$. For
problem (1), called In-Range Farthest Point (IFP) Query, we develop a
bi-criteria approximation scheme: For any $\epsilon>0$ that specifies the
approximation ratio of the farthest distance and any $\gamma>0$ that measures
the "fuzziness" of the query range, we show that it is possible to pre-process
$P$ into a data structure of size $\tilde{O}_{\epsilon,\gamma}(dn^{1+\rho})$ in
$\tilde{O}_{\epsilon,\gamma}(dn^{1+\rho})$ time such that given any
$\mathbb{R}^d$ query ball $B$ and query point $q$, it outputs in
$\tilde{O}_{\epsilon,\gamma}(dn^{\rho})$ time a point $p$ that is a
$(1-\epsilon)$-approximation of the farthest point to $q$ among all points
lying in a $(1+\gamma)$-expansion $B(1+\gamma)$ of $B$, where $0<\rho<1$ is a
constant depending on $\epsilon$ and $\gamma$ and the hidden constants in big-O
notations depend only on $\epsilon$, $\gamma$ and $\text{Polylog}(nd)$. For
problem (2), we show that the IFP result can be applied to develop query scheme
with similar time and space complexities to achieve a
$(1+\epsilon)$-approximation for MEB.


  Table detection, a pivotal task in document analysis, aims to precisely
recognize and locate tables within document images. Although deep learning has
shown remarkable progress in this realm, it typically requires an extensive
dataset of labeled data for proficient training. Current CNN-based
semi-supervised table detection approaches use the anchor generation process
and Non-Maximum Suppression (NMS) in their detection process, limiting training
efficiency. Meanwhile, transformer-based semi-supervised techniques adopted a
one-to-one match strategy that provides noisy pseudo-labels, limiting overall
efficiency. This study presents an innovative transformer-based semi-supervised
table detector. It improves the quality of pseudo-labels through a novel
matching strategy combining one-to-one and one-to-many assignment techniques.
This approach significantly enhances training efficiency during the early
stages, ensuring superior pseudo-labels for further training. Our
semi-supervised approach is comprehensively evaluated on benchmark datasets,
including PubLayNet, ICADR-19, and TableBank. It achieves new state-of-the-art
results, with a mAP of 95.7% and 97.9% on TableBank (word) and PubLaynet with
30% label data, marking a 7.4 and 7.6 point improvement over previous
semi-supervised table detection approach, respectively. The results clearly
show the superiority of our semi-supervised approach, surpassing all existing
state-of-the-art methods by substantial margins. This research represents a
significant advancement in semi-supervised table detection methods, offering a
more efficient and accurate solution for practical document analysis tasks.


  Recently, Kristensen, Ge and Hughes have compared [Phys. Rev. A 92, 053810
(2015)] three different methods for normalization of quasinormal modes in open
optical systems, and concluded that they all provide the same result. We show
here that this conclusion is incorrect and illustrate that the normalization of
[Opt. Lett. 37, 1649 (2012)] is divergent for any optical mode having a finite
quality factor, and that the Silver-Mueller radiation condition is not
fulfilled for quasinormal modes.


  A semiempirical shell model mass equation based on magic number Z=126 and
applicable to translead elements with N smaller or equal to 126 is presented.
For alpha decay energies the equation is shown to have a high predictive power
and an rms deviation from the data of about 100 keV. The rms deviations for
masses and other mass differences are between about 200 and 300 keV.


  Our findings indicated that brain stimulation exerted no effect on the
patients cognitive functions. The study outcome suggest that tDCS over primary
motor cortex may be considered as a potential nonpharmochological treatment
add-on in MG. Larger-sized studies need to evaluate the significance of this
approach is real-life practice.


  This paper is devoted to the presentation and the analysis of a new nonlinear
subdivision scheme eliminating the Gibbs oscillations close to discontinuities.
Its convergence, stability and order of approximation are analyzed. It is
proved that this schemes converges towards limit functions of H\"older
regularity index larger than 1.192. Numerical estimates provide an H\"older
regularity index of 2.438. Up to our knowledge, this scheme is the first one
that achieves simultaneously the control of the Gibbs phenomenon and regularity
index larger than 1 for its limit functions.


  The relativistic quantum decay laws of moving unstable particles are analyzed
for a general class of mass distribution densities which behave as power laws
near the (non-vanishing) lower bound $\mu_0$ of the mass spectrum. The survival
probability $\mathcal{P}_p(t)$, the instantaneous mass $M_p(t)$ and the
instantaneous decay rate $\Gamma_p(t)$ of the moving unstable particle are
evaluated over short and long times for an arbitrary value $p$ of the
(constant) linear momentum. The ultrarelativistic and non-relativistic limits
are studied. Over long times, the survival probability $\mathcal{P}_p(t)$ is
approximately related to the survival probability at rest $\mathcal{P}_0(t)$ by
a scaling law. The scaling law can be interpreted as the effect of the
relativistic time dilation if the asymptotic value $M_p\left(\infty\right)$ of
the instantaneous mass is considered as the effective mass of the unstable
particle over long times. The effective mass has magnitude $\mu_0$ at rest and
moves with linear momentum $p$ or, equivalently, with constant velocity
$1\Big/\sqrt{1+\mu_0^2\big/p^2}$. The instantaneous decay rate $\Gamma_p(t)$ is
approximately independent of the linear momentum $p$, over long times, and,
consequently, is approximately invariant by changing reference frame.


  A novel method for increasing the extinction ratio of plasmonic waveguide
polarizer has been investigated in this work. Aluminum was coated in a 20
microns multi-strips pattern on the top of a SU-8 waveguide to excite the
surface plasmons. Simulation and experimental results have been shown the
extinction ratio of the multi-strip polarizer is more than the single strip
ones with the same total aluminum-coated length due to the coupling loss
between Al coated and uncoated region and also the scattering at the edge of
metal. This polarizer was characterized over a wide range of wavelengths and
showed a high extinction ratio of 46 dB at 1550 nm and 26.8 dB at 980 nm
wavelengths.


  A (fully) dynamic graph algorithm is a data structure that supports edge
insertions, edge deletions, and answers specific queries pertinent to the
problem at hand. In this work, we address the fully dynamic edge orientation
problem, also known as the fully dynamic $\Delta$-orientation problem. The
objective is to maintain an orientation of the edges in an undirected graph
such that the out-degree of any vertex remains low. When edges are inserted or
deleted, it may be necessary to reorient some edges to prevent vertices from
having excessively high out-degrees. In this paper, we introduce the first
algorithm that maintains an optimal edge orientation during both insertions and
deletions. In experiments comparing with recent nearly exact algorithms, we
achieve a 32% lower running time. The update time of our algorithm is up to 6
orders of magnitude faster than static exact algorithms.


  In this article, we study the distribution of index of Farey fractions which
was first introduced and studied by Hall and Shiu. We provide asymptotic
formulas for moments of index of Farey fractions twisted by Dirichlet
characters for Farey fractions with $\mathcal{B}$-free denominators.
Additionally, we reconsider the squarefree case earlier done in [ALVZ08], and
obtain new results for moments of indices with square-free denominators. We
also study higher level correlations of the index function generalizing earlier
known results on two level correlations.


  The focusing performance of X-ray optics (conveniently expressed in terms of
HEW, Half Energy Width) strongly depend on both mirrors deformations and photon
scattering caused by the microroughness of reflecting surfaces. In particular,
the contribution of X-ray Scattering (XRS) to the HEW of the optic is usually
an increasing function H(E) of the photon energy E. Therefore, in future hard
X-ray imaging telescopes of the future (SIMBOL-X, NeXT, Constellation-X, XEUS),
the X-ray scattering could be the dominant problem since they will operate also
in the hard X-ray band (i.e. beyond 10 keV). [...]
  Several methods were proposed in the past years to estimate the scattering
contribution to the HEW, dealing with the surface microroughness expressed in
terms of its Power Spectral Density (PSD), on the basis of the well-established
theory of X-ray scattering from rough surfaces. We faced that problem on the
basis on the same theory, but we tried a new approach: the direct, analytical
translation of a given surface roughness PSD into a H(E) trend, and - vice
versa - the direct translation of a H(E) requirement into a surface PSD. This
PSD represents the maximum tolerable microroughness level in order to meet the
H(E) requirement in the energy band of a given X-ray telescope.
  We have thereby found a new, analytical and widely applicable formalism to
compute the XRS contribution to the HEW from the surface PSD, provided that the
PSD had been measured in a wide range of spatial frequencies. The inverse
problem was also solved, allowing the immediate evaluation of the mirror
surface PSD from a measured function H(E). The same formalism allows
establishing the maximum allowed PSD of the mirror in order to fulfill a given
H(E) requirement. [...]


  This paper investigates the capacity of general multiple-input single-output
(MISO) optical intensity channels (OICs) under per-antenna peak- and
average-intensity constraints. We first consider the MISO equal-cost
constrained OIC (EC-OIC), where, apart from the peak-intensity constraint,
average intensities of inputs are equal to arbitrarily preassigned constants.
The second model of our interest is the MISO bounded-cost constrained OIC
(BC-OIC), where, as compared with the EC-OIC, average intensities of inputs are
no larger than arbitrarily preassigned constants. By leveraging tools from
quantile functions, stop-loss transform and convex ordering of nonnegative
random variables, we prove two decomposition theorems for bounded and
nonnegative random variables, based on which we equivalently transform both the
EC-OIC and the BC-OIC into respective single-input single-output channels under
a peak-intensity and several stop-loss mean constraints. Capacity lower and
upper bounds for both channels are established, based on which the asymptotic
capacity at high and low signal-to-noise-ratio are determined.


  Exploration is a key problem in reinforcement learning, since agents can only
learn from data they acquire in the environment. With that in mind, maintaining
a population of agents is an attractive method, as it allows data be collected
with a diverse set of behaviors. This behavioral diversity is often boosted via
multi-objective loss functions. However, those approaches typically leverage
mean field updates based on pairwise distances, which makes them susceptible to
cycling behaviors and increased redundancy. In addition, explicitly boosting
diversity often has a detrimental impact on optimizing already fruitful
behaviors for rewards. As such, the reward-diversity trade off typically relies
on heuristics. Finally, such methods require behavioral representations, often
handcrafted and domain specific. In this paper, we introduce an approach to
optimize all members of a population simultaneously. Rather than using pairwise
distance, we measure the volume of the entire population in a behavioral
manifold, defined by task-agnostic behavioral embeddings. In addition, our
algorithm Diversity via Determinants (DvD), adapts the degree of diversity
during training using online learning techniques. We introduce both
evolutionary and gradient-based instantiations of DvD and show they effectively
improve exploration without reducing performance when better exploration is not
required.


  We prove that the moduli space of solutions to the PU(2) monopole equations
is a smooth manifold of the expected dimension for simple, generic parameters
such as (and including) the Riemannian metric on the given four-manifold. In a
previous article, dg-ga/9710032, we proved transversality using an extension of
the holonomy-perturbation methods of Donaldson, Floer, and Taubes, together
with the existence of an Uhlenbeck compactification for the perturbed moduli
space. However, it remained an important and interesting question to see
whether there were simpler, more intrinsic alternatives to the holonomy
perturbations and this is the issue we settle here. The idea that PU(2)
monopoles might lead to a proof of Witten's conjecture (hep-th/9411102,
hep-th/9709193) concerning the relation between the two types of four-manifold
invariants was first proposed by Pidstrigach and Tyurin in 1994
(dg-ga/9507004): the space of PU(2) monopoles contains the moduli space of
anti-self-dual connections together with copies of the various Seiberg-Witten
moduli spaces, these forming singular loci in the higher-dimensional space of
PU(2) monopoles. Results in this direction, due to the author and Leness, are
surveyed in dg-ga/9709022, with a detailed account appearing in dg-ga/9712005.
Our transversality theorem ensures that the anti-self-dual and Seiberg-Witten
loci are the only singularities and that the PU(2) monopole moduli space forms
a smooth - though non-compact, because of bubbling - cobordism between the
links of the singularities.


  We consider general fermi-phobic scenarios in which excess events in diphoton
or WW/ZZ resonances may be seen at LHC. These Higgs like signals do not
necessarily suggest that the new resonance is a particle with Yukawa couplings
nor do we know that it is responsible for electroweak symmetry breaking. We
can, however, extract two facts from it, this particle couples to pairs of
SU(2) and U(1) gauge bosons and it must be a scalar, pseudoscalar, or tensor.
We consider the signals of general operators up to effective dimension 5 in
which a new scalar, psuedo-scalar, or tensor particle may couple to pairs of
standard model gauge bosons. This particle may or may not be charged under the
standard model gauge groups, and may be produced via gluon fusion or EW vector
boson fusion.


  In some models of quantum gravity, space-time is thought to have a foamy
structure with non-trivial optical properties. We probe the possibility that
photons propagating in vacuum may exhibit a non-trivial refractive index, by
analyzing the times of flight of radiation from gamma-ray bursters (GRBs) with
known redshifts. We use a wavelet shrinkage procedure for noise removal and a
wavelet `zoom' technique to define with high accuracy the timings of sharp
transitions in GRB light curves, thereby optimizing the sensitivity of
experimental probes of any energy dependence of the velocity of light. We apply
these wavelet techniques to 64 ms and TTE data from BATSE, and also to OSSE
data. A search for time lags between sharp transients in GRB light curves in
different energy bands yields the lower limit $M \ge 6.9 \cdot 10^{15}$ GeV on
the quantum-gravity scale in any model with a linear dependence of the velocity
of light $~ E/M$. We also present a limit on any quadratic dependence.


  Multifractal analysis refers to the study of the local properties of measures
and functions, and consists of two parts: the fine multifractal theory and the
coarse multifractal theory. The fine and the coarse theory are linked by a web
of conjectures known collectively as the Multifractal Formalism. Very roughly
speaking the Multifractal Formalism says that the multifractal spectrum from
fine theory equals the Legendre transform of the Renyi dimensions from the
coarse theory.
  Recently {\it fine} multifractal zeta-functions, i.e. multifractal
zeta-functions designed to produce detailed information about the fine
multifractal theory, have been introduced and investigated. The purpose of this
work is to complement and expand this study by introducing and investigating
{\it coarse} multifractal zeta-functions, i.e. multifractal zeta-functions
designed to produce information about the coarse multifractal theory, and, in
particular, to establish a {\it Multifractal Fortmalism for Zeta-Functions}
linking fine multifractal zeta-functions and coarse multifractal zeta-functions
via the Legendre transform.
  Several applications are given, including applications to multifractal
analysis of graph-directed self-conformal measures and multifractal analysis of
ergodic Birkhoff averages of continuous functions on graph-directed
self-conformal sets.


  Despite impressive performance on numerous visual tasks, Convolutional Neural
Networks (CNNs) --- unlike brains --- are often highly sensitive to small
perturbations of their input, e.g. adversarial noise leading to erroneous
decisions. We propose to regularize CNNs using large-scale neuroscience data to
learn more robust neural features in terms of representational similarity. We
presented natural images to mice and measured the responses of thousands of
neurons from cortical visual areas. Next, we denoised the notoriously variable
neural activity using strong predictive models trained on this large corpus of
responses from the mouse visual system, and calculated the representational
similarity for millions of pairs of images from the model's predictions. We
then used the neural representation similarity to regularize CNNs trained on
image classification by penalizing intermediate representations that deviated
from neural ones. This preserved performance of baseline models when
classifying images under standard benchmarks, while maintaining substantially
higher performance compared to baseline or control models when classifying
noisy images. Moreover, the models regularized with cortical representations
also improved model robustness in terms of adversarial attacks. This
demonstrates that regularizing with neural data can be an effective tool to
create an inductive bias towards more robust inference.


  Due to shortage of water resources and increasing water demands, the joint
operation of multireservoir systems for balancing power generation, ecological
protection, and the residential water supply has become a critical issue in
hydropower management. However, the numerous constraints and nonlinearity of
multiple reservoirs make solving this problem time-consuming. To address this
challenge, a deep reinforcement learning approach that incorporates a
transformer framework is proposed. The multihead attention mechanism of the
encoder effectively extracts information from reservoirs and residential areas,
and the multireservoir attention network of the decoder generates suitable
operational decisions. The proposed method is applied to Lake Mead and Lake
Powell in the Colorado River Basin. The experimental results demonstrate that
the transformer-based deep reinforcement learning approach can produce
appropriate operational outcomes. Compared to a state-of-the-art method, the
operation strategies produced by the proposed approach generate 10.11% more
electricity, reduce the amended annual proportional flow deviation by 39.69%,
and increase water supply revenue by 4.10%. Consequently, the proposed approach
offers an effective method for the multiobjective operation of multihydropower
reservoir systems.


  We construct atmosphere models for strongly magnetized neutron stars with
surface fields $B\sim 10^{12}-10^{15}$ G and effective temperatures $T_{\rm
eff}\sim 10^6-10^7$ K. The atmospheres directly determine the characteristics
of thermal emission from isolated neutron stars, including radio pulsars, soft
gamma-ray repeaters, and anomalous X-ray pulsars. In our models, the atmosphere
is composed of pure hydrogen or helium and is assumed to be fully ionized. The
radiative opacities include free-free absorption and scattering by both
electrons and ions computed for the two photon polarization modes in the
magnetized electron-ion plasma. Since the radiation emerges from deep layers in
the atmosphere with $\rho\ga 10^2$ g/cm$^3$, plasma effects can significantly
modify the photon opacities by changing the properties of the polarization
modes. In the case where the magnetic field and the surface normal are
parallel, we solve the full, angle-dependent, coupled radiative transfer
equations for both polarization modes. We also construct atmosphere models for
general field orientations based on the diffusion approximation of the
transport equations and compare the results with models based on full radiative
transport. In general, the emergent thermal radiation exhibits significant
deviation from blackbody, with harder spectra at high energies. The spectra
also show a broad feature ($\Delta E/\Ebi\sim 1$) around the ion cyclotron
resonance $\Ebi=0.63 (Z/A)(B/10^{14}{G})$ keV, where $Z$ and $A$ are the atomic
charge and atomic mass of the ion, respectively; this feature is particularly
pronounced when $\Ebi\ga 3k\Teff$. Detection of the resonance feature would
provide a direct measurement of the surface magnetic fields on magnetars.


  In the paper, the authors verify the complete monotonicity of the difference
$e^{1/t}-\psi'(t)$ on $(0,\infty)$, compute the completely monotonic degree and
establish integral representations of the remainder of the Laurent series
expansion of $e^{1/z}$, and derive an inequality which gives a lower bound for
the first order modified Bessel function of the first kind.


  Consistent interactions that can be added to a free, Abelian gauge theory
comprising a collection of BF models and a set of three-form gauge fields are
constructed from the deformation of the solution to the master equation based
on specific cohomological techniques. Under the hypotheses of smooth, local, PT
invariant, Lorentz covariant, and Poincare invariant interactions, supplemented
with the requirement on the preservation of the number of derivatives on each
field with respect to the free theory, we obtain that the deformation procedure
modifies the Lagrangian action, the gauge transformations as well as the
accompanying algebra.


  While considerable advance has been made to account for statistical
uncertainties in astronomical analyses, systematic instrumental uncertainties
have been generally ignored. This can be crucial to a proper interpretation of
analysis results because instrumental calibration uncertainty is a form of
systematic uncertainty. Ignoring it can underestimate error bars and introduce
bias into the fitted values of model parameters. Accounting for such
uncertainties currently requires extensive case-specific simulations if using
existing analysis packages. Here we present general statistical methods that
incorporate calibration uncertainties into spectral analysis of high-energy
data. We first present a method based on multiple imputation that can be
applied with any fitting method, but is necessarily approximate. We then
describe a more exact Bayesian approach that works in conjunction with a Markov
chain Monte Carlo based fitting. We explore methods for improving computational
efficiency, and in particular detail a method of summarizing calibration
uncertainties with a principal component analysis of samples of plausible
calibration files. This method is implemented using recently codified Chandra
effective area uncertainties for low-resolution spectral analysis and is
verified using both simulated and actual Chandra data. Our procedure for
incorporating effective area uncertainty is easily generalized to other types
of calibration uncertainties.


  For a general class of gas models ---which includes discrete and continuous
Gibbsian models as well as contour or polymer ensembles--- we determine a
\emph{diluteness condition} that implies: (1) Uniqueness of the infinite-volume
equilibrium measure; (2) stability of this measure under perturbations of
parameters and discretization schemes, and (3) existence of a coupled
perfect-simulation scheme for the infinite-volume measure together with its
perturbations and discretizations. Some of these results have previously been
obtained through methods based on cluster expansions. In contrast, our
treatment is purely probabilistic and its diluteness condition is weaker than
existing convergence conditions for cluster expansions.


  The emergence of a compressible insulator phase, known as the Bose glass, is
characteristic of the interplay of interactions and disorder in correlated Bose
fluids. While widely studied in tight-binding models, its observation remains
elusive owing to stringent temperature effects. Here we show that this issue
may be overcome by using Lieb-Liniger bosons in shallow quasiperiodic
potentials. A Bose glass, surrounded by superfluid and Mott phases, is found
above a critical potential and for finite interactions. At finite temperature,
we show that the melting of the Mott lobes is characteristic of a fractal
structure and find that the Bose glass is robust against thermal fluctuations
up to temperatures accessible in quantum gases. Our results raise questions
about the universality of the Bose glass transition in such shallow
quasiperiodic potentials.


  A redshift tomography of the Pantheon type Ia supernovae (SnIa) data focusing
on the best fit value of the absolute magnitude $M$ and/or Hubble constant
$H_0$ in the context of $\Lambda$CDM indicates a local variation ($z\lesssim
0.2$) at $2\sigma$ level, with respect to the best fit of the full dataset. If
this variation is physical, it can be interpreted either as a locally higher
value of $H_0$, corresponding to a local matter underdensity $\delta
\rho_0/\rho_0 \simeq -0.10 \pm 0.04$ or as a time variation of Newton's
constant which implies an evolving Chandrasekhar mass and thus an evolving
absolute magnitude $M$ of SnIa. The local void scenario would predict an
anisotropy in the best fit value of $H_0$ since it is unlikely that we are
located at the center of a local spherical underdensity. Using a hemisphere
comparison method we find an anisotropy level consistent with simulated
isotropic datasets. We show however, that the anisotropic sky distribution of
the Pantheon SnIa data induces a preferred range of directions even in
simulated Pantheon data obtained in the context of isotropic $\Lambda$CDM. We
thus construct a more isotropically distributed subset of the Pantheon SnIa and
show that the preferred range of directions disappears. Using this subset we
again find no evidence for anisotropy using either the hemisphere comparison
method or the dipole fit method. In the context of the modified gravity
scenario, we allow for an evolving normalized Newton's constant consistent with
General Relativity (GR) at early and late times $\mu(z)=1+g_a z^2/(1+z)^2-g_a
z^4/(1+z)^4$ and fit for $g_a$ assuming $L\sim G_{\rm{eff}}^b$. For $b=-3/2$
indicated by previous studies we find $g_a=-0.47 \pm 0.36$ which is more than
$1.5\sigma$ away from the GR value of $g_a=0$. This weak hint for weaker
gravity at low $z$ is consistent with similar evidence from growth and weak
lensing data.


  In this paper a class of asymmetrical operators of generalised translation is
introduced, for each of them generalised moduli of smoothness are introduced,
and Jackson's and its converse theorems are proved for those moduli.
  -----
  V eto\v{i} rabote rassmatrivaetsya klass sesimmetrichnykh operatorov
obobshchenogo sdviga, dlya kazhdogo iz nikh vvoditsya obobshchennye moduli
gladkosti i dlya nikh dokazybaetsya teorma Dzheksona i teorema, obratnaya
e\v{i}.


  Transitions between the ground singlet state to the excited triplet state has
been observed in CuGeO3 by means of submillimeter wave electron spin resonance.
The strong absorption intensity shows the break down of the selection rule. The
energy gap at zero field is evaluated to be 570 GHz(2.36 meV) and this value is
nearly identical to the gap at the zone center observed by inelastic neutron
scattering. The absorption intensity shows strong field orientation dependence
but shows no significant dependence on magnetic field intensity. These features
have been explained by considering the existence of Dzyaloshinsky-Moriya (DM)
antisymmetric exchange interaction. The doping effect on this singlet-triplet
excitation has been also studied. A drastic broadening of the absorption line
is observed by the doping of only 0.5 % of Si.


  Evolution of inhomogeneities in the axion field around the QCD epoch is
studied numerically, including for the first time important non-linear effects.
It is found that perturbations on scales corresponding to causally disconnected
regions at $T \sim 1 \, {\rm GeV}$ can lead to very dense axion clumps, with
present density $\rho_a \ga 10^{-8}\,{\rm g \, cm^{-3}}$. This is high enough
for the collisional $2a \rightarrow 2a$ process to lead to Bose--Einstein
relaxation in the gravitationally bound clumps of axions, forming Bose stars.


  Intelligent reflecting surface (IRS) is envisioned as a promising solution
for controlling radio propagation environments in future wireless systems. In
this paper, we propose a distributed intelligent reflecting surface (IRS)
assisted multi-user millimeter wave (mmWave) system, where IRSs are exploited
to enhance the mmWave signal coverage when direct links between base station
and users are unavailable. First, a joint active and passive beamforming
problem is established for weighted sum-rate maximization. Then, an alternating
iterative algorithm with closed-form expressions is proposed to tackle the
challenging non-convex problem, thereby decoupling the active and passive
beamforming variables. Moreover, we design a constraint relaxation technique to
address the unit modulus constraints pertaining to the IRS. Numerical results
demonstrate that the distributed IRS can potentially enhance the communication
performance of existing wireless systems.


  We establish an expression of the entropy-from-work theorem that is
complementary to the one originally proposed in [P. Talkner, P. Hanggi and M.
Morillo, arXiv:0707.2307]. In the original expression the final energy is fixed
whereas in the present expression the initial energy is fixed.


  Periodically modulated nonlinear oscillators often display bistability of
forced vibrations. This bistability can be used for new types of quantum
measurements. They are based on switching between coexisting vibrational
states. Since switching is accompanied by a large change of the amplitude and
phase of forced vibrations, the measurements are highly sensitive. Quantum and
classical noise plays dual role. It imposes a limitation on sensitivity in the
familiar regime of a bifurcation amplifier. On the other hand, it makes it
possible to use a bistable modulated oscillator in a new regime of a balanced
dynamical bridge. We discuss the switching probabilities and show that they
display scaling with control parameters. The critical exponents are found for
different types of bifurcations and for different types of noise.


  We consider the "homotopy coniveau tower" for an arbitrary cohomology theory
on smooth varieties over a field or a Dedekind domain. This tower is a
generalization of the construction used by Bloch-Lichtenbaum and
Friedlander-Suslin in their studies of the spectral sequence from motivic
cohomology to K-theory. Our main result is that an application of the classical
Chow's moving lemma and some categorical constructions make the homotopy
coniveau tower strictly functorial when the base is a field, and functorial in
the homotopy category when the base is a Dedekind domain.


  Conveying complex objectives to reinforcement learning (RL) agents often
requires meticulous reward engineering. Preference-based RL methods are able to
learn a more flexible reward model based on human preferences by actively
incorporating human feedback, i.e. teacher's preferences between two clips of
behaviors. However, poor feedback-efficiency still remains a problem in current
preference-based RL algorithms, as tailored human feedback is very expensive.
To handle this issue, previous methods have mainly focused on improving query
selection and policy initialization. At the same time, recent exploration
methods have proven to be a recipe for improving sample-efficiency in RL. We
present an exploration method specifically for preference-based RL algorithms.
Our main idea is to design an intrinsic reward by measuring the novelty based
on learned reward. Specifically, we utilize disagreement across ensemble of
learned reward models. Our intuition is that disagreement in learned reward
model reflects uncertainty in tailored human feedback and could be useful for
exploration. Our experiments show that exploration bonus from uncertainty in
learned reward improves both feedback- and sample-efficiency of
preference-based RL algorithms on complex robot manipulation tasks from
MetaWorld benchmarks, compared with other existing exploration methods that
measure the novelty of state visitation.


  We consider the rational potentials of the one-dimensional mechanical
systems, which have a family of periodic solutions with the same period
(isochronous potentials). We prove that up to a shift and adding a constant all
such potentials have the form $U(x) = 1/2 \omega^2 x^2$ or $U(x) = 1/8 \omega^2
x ^2 + c^2 x^{-2}.$


  We present long-slit optical spectra of 12 edge-on low surface brightness
galaxies (LSBGs) positioned along their major axes. After performing reddening
corrections for the emission-line fluxes measured from the extracted integrated
spectra, we measured the gas-phase metallicities of our LSBG sample using both
the [NII]/Ha and the R_23 diagnostics. Both sets of oxygen abundances show good
agreement with each other, giving a median value of 12 + log(O/H) = 8.26 dex.
In the luminosity-metallicity plot, our LSBG sample is consistent with the
behavior of normal galaxies. In the mass-metallicity diagram, our LSBG sample
has lower metallicities for lower stellar mass, similar to normal galaxies. The
stellar masses estimated from z-band luminosities are comparable to those of
prominent spirals. In a plot of the gas mass fraction versus metallicity, our
LSBG sample generally agrees with other samples in the high gas mass fraction
space. Additionally, we have studied stellar populations of 3 LSBGs which have
relatively reliable spectral continua and high signal-to-noise ratios, and
qualitatively conclude that they have a potential dearth of stars with ages <1
Gyr instead of being dominated by stellar populations with ages >1Gyr.
Regarding the chemical evolution of our sample, the LSBG data appear to allow
for up to 30 % metal loss, but we cannot completely rule out the closed-box
model. Additionally, we find evidence that our galaxies retain up to about 3
times as much of their metals compared with dwarfs, consistent with metal
retention being related to galaxy mass. In conclusion, our data support the
view that LSBGs are probably just normal disk galaxies continuously extending
to the low end of surface brightness.


  Domain-specific accelerators are used in various computing systems ranging
from edge devices to data centers. Coarse-grained reconfigurable arrays (CGRAs)
represent an architectural midpoint between the flexibility of an FPGA and the
efficiency of an ASIC and are a promising candidate for servicing multi-tasked
workloads within an application domain. Unfortunately, scheduling multiple
tasks onto a CGRA is challenging. CGRAs lack abstractions that capture hardware
resources, leaving workload schedulers unable to reason about performance,
energy, and utilization for different schedules. This work first proposes a
CGRA architecture that can flexibly partition key resources, including the
global buffer memory capacity, the global buffer memory bandwidth, and the
compute resources. Partitioned resources serve as hardware abstractions that
decouple compilation and resource allocation. The compiler uses these
abstractions for coarse-grained resource mapping, and the scheduler uses them
for flexible resource allocation at run time. We then propose two hardware
mechanisms to support multi-task execution. A flexible-shape execution region
increases the overall resource utilization by mapping multiple tasks with
different resource requirements. Dynamic partial reconfiguration (DPR) enables
a CGRA to update the hardware configuration as the scheduler makes decisions
rapidly. We show that our abstraction can help automatic and efficient
scheduling of multi-tasked workloads onto our target CGRA with high
utilization, resulting in 1.05x-1.24x higher throughput and a 23-28% lower
latency in a multi-tasked cloud workload and 60.8% reduced latency in an
autonomous system workload when compared to a baseline CGRA running single
tasks at a time.


  While existing mathematical descriptions can accurately account for phenomena
at microscopic scales (e.g. molecular dynamics), these are often
high-dimensional, stochastic and their applicability over macroscopic time
scales of physical interest is computationally infeasible or impractical. In
complex systems, with limited physical insight on the coherent behavior of
their constituents, the only available information is data obtained from
simulations of the trajectories of huge numbers of degrees of freedom over
microscopic time scales. This paper discusses a Bayesian approach to deriving
probabilistic coarse-grained models that simultaneously address the problems of
identifying appropriate reduced coordinates and the effective dynamics in this
lower-dimensional representation. At the core of the models proposed lie
simple, low-dimensional dynamical systems which serve as the building blocks of
the global model. These approximate the latent, generating sources and
parameterize the reduced-order dynamics. We discuss parallelizable, online
inference and learning algorithms that employ Sequential Monte Carlo samplers
and scale linearly with the dimensionality of the observed dynamics. We propose
a Bayesian adaptive time-integration scheme that utilizes probabilistic
predictive estimates and enables rigorous concurrent s imulation over
macroscopic time scales. The data-driven perspective advocated assimilates
computational and experimental data and thus can materialize data-model fusion.
It can deal with applications that lack a mathematical description and where
only observational data is available. Furthermore, it makes non-intrusive use
of existing computational models.


  The plasma sheath sets a stage for a strongly nonlinear coupling of the
thermal, kinetic, and electric energies of plasma in a non-equilibrium, open
environment. The pressure, velocity, and electrostatic potential profiles
depend strongly on the boundary condition given on the internal side
(pre-sheath). By controlling the boundary values of the heat flux and the ion
Mach number, we solve a set of equations for the ion temperature and the
electrostatic potential. The boundary values of the ion velocity and the
electrostatic potential vary due to the change of the boundary ion temperature.
When the heat flux exceeds a threshold value (determined by the ion Mach
number), the temperature contrast is enhanced, resulting in a large entropy
production.


  We give families of examples where sharp rates of convergence to stationarity
of the widely used Gibbs sampler are available. The examples involve standard
exponential families and their conjugate priors. In each case, the transition
operator is explicitly diagonalizable with classical orthogonal polynomials as
eigenfunctions.


  We systematically investigate the possible molecular states composed of (1)
two spin-$\frac{3}{2}$ doubly charmed baryons, and (2) a pair of
spin-$\frac{3}{2}$ and spin-$\frac{1}{2}$ doubly charmed baryons. The
one-boson-exchange (OBE) model is used to describe the potential between two
baryons. The channel mixing effect is considered for the systems with the same
quantum number $(I(J^P))$ but different total spin ($S$) and orbital angular
momenta ($L$). We also study the channel mixing effect among the systems
composed of various doubly charmed baryons if they have the same quantum
number. Many of the systems are good candidates of molecular states.


  In the past years, there have been tremendous advances in the field of planar
N=4 super Yang-Mills scattering amplitudes. At tree-level they were formulated
as Grassmannian integrals and were shown to be invariant under the Yangian of
the superconformal algebra psu(2,2|4). Recently, Yangian invariant deformations
of these integrals were introduced as a step towards regulated loop-amplitudes.
However, in most cases it is still unclear how to evaluate these deformed
integrals. In this work, we propose that changing variables to oscillator
representations of psu(2,2|4) turns the deformed Grassmannian integrals into
certain matrix models. We exemplify our proposal by formulating Yangian
invariants with oscillator representations of the non-compact algebra u(p,q) as
Grassmannian integrals. These generalize the Brezin-Gross-Witten and
Leutwyler-Smilga matrix models. This approach might make elaborate matrix model
technology available for the evaluation of Grassmannian integrals. Our
invariants also include a matrix model formulation of the u(p,q) R-matrix,
which generates non-compact integrable spin chains.


  We argue for the use of active learning methods for player modelling. In
active learning, the learning algorithm chooses where to sample the search
space so as to optimise learning progress. We hypothesise that player modelling
based on active learning could result in vastly more efficient learning, but
will require big changes in how data is collected. Some example active player
modelling scenarios are described. A particular form of active learning is also
equivalent to an influential formalisation of (human and machine) curiosity,
and games with active learning could therefore be seen as being curious about
the player. We further hypothesise that this form of curiosity is symmetric,
and therefore that games that explore their players based on the principles of
active learning will turn out to select game configurations that are
interesting to the player that is being explored.


  Through detailed radiative transfer modeling, we present a disk+cavity model
to simultaneously explain both the SED and Subaru H-band polarized light
imaging for the pre-transitional protoplanetary disk PDS 70. Particularly, we
are able to match not only the radial dependence, but also the absolute scale,
of the surface brightness of the scattered light. Our disk model has a cavity
65 AU in radius, which is heavily depleted of sub-micron-sized dust grains, and
a small residual inner disk which produces a weak but still optically thick NIR
excess in the SED. To explain the contrast of the cavity edge in the Subaru
image, a factor of ~1000 depletion for the sub-micron-sized dust inside the
cavity is required. The total dust mass of the disk may be on the order of 1e-4
M_sun, only weakly constrained due to the lack of long wavelength observations
and the uncertainties in the dust model. The scale height of the
sub-micron-sized dust is ~6 AU at the cavity edge, and the cavity wall is
optically thick in the vertical direction at H-band. PDS 70 is not a member of
the class of (pre-)transitional disks identified by Dong et al. (2012), whose
members only show evidence of the cavity in the millimeter-sized dust but not
the sub-micron-sized dust in resolved images. The two classes of
(pre-)transitional disks may form through different mechanisms, or they may
just be at different evolution stages in the disk clearing process.


  We study inflation in a supersymmetric Pati-Salam model driven by a potential
generated in the context of no-scale supergravity. The Pati-Salam gauge group
$SU(4)_{c}\times{SU(2)_{L}\times{SU(2)_{R}}}$ , is supplemented with a $Z_{2} $
symmetry. Spontaneous breaking via the $SU(4)$ adjoint leads to the left-right
symmetric group. Then the $SU(2)_{R}$ breaks at an intermediate scale and the
inflaton is a combination of the neutral components of the $SU(2)_{R}$
doublets. We discuss various limits of the parameter space and we show that
consistent solutions with the cosmological data for the a spectral index
$n_{s}$ and the tensor-to-scalar ratio r are found for a wide range of the
parameter space of the model. Regarding the latter, which is a canonical
measure of primordial gravity waves, we find that $r\sim{10^{-3}-10^{-2}}$. An
alternative possibility where the adjoint scalar field $S$ has the role of the
inflaton is also discussed.


  We give the connections among the Fekete sets, the zeros of orthogonal
polynomials, $1(w)$-normal point systems, and the nodes of a stable and most
economical interpolatory process via the Fej\'er contants. Finally the
convergence of a weighted Gr\"unwald interpolation is proved.


  The Cattle Tracing System database is an online recording system for cattle
births, deaths and between--herd movements in the United Kingdom. Although it
has been thoroughly examined, the most recently reported movement analysis is
from 2009. This article uses the database to construct weighted directed
monthly movement networks for two distinct periods of time, 2004--2006 and
2015--2017, to quantify by how much the underlying structure of the network has
changed. Substantial changes in network structure may influence policy--makers
directly or may influence models built upon the network data, and these in turn
could impact policy--makers and their assessment of risk. Four general network
measures are used (total number of nodes with movements, movements, births and
deaths), in conjunction with network metrics to describe each monthly network.
Two updates of the database were examined to determine by how much the movement
data stored for a particular time period had been cleansed between updates.
Statistical models show that there is a statistically significant effect of the
time period (2004--2006 vs 2015--2017) in the values of all network measures
and six of nine network metrics. Changes in the sizes of both the Giant and
Weakly Strongly Connected components predict reductions in the upper and lower
bounds of the maximum epidemic size. Examination of the updates of the database
show that there are differences in records between updates and therefore
evidence of historical data changing between updates. Accurate modelling of
disease spread through a network requires representative descriptions of the
network. The authors recommend that where possible the most recent available
data always be used for network modelling and that methods of network
prediction be examined to mitigate for the time required for data to become
available.


  We present resistivity and thermal-conductivity measurements of
superconducting FeSe in intense magnetic fields up to 35 T applied parallel to
the $ab$ plane. At low temperatures, the upper critical field $\mu_0
H_{c2}^{ab}$ shows an anomalous upturn, while thermal conductivity exhibits a
discontinuous jump at $\mu_0 H^{\ast}\approx 24$ T well below $\mu_0
H_{c2}^{ab}$, indicating a first-order phase transition in the superconducting
state. This demonstrates the emergence of a distinct field-induced
superconducting phase. Moreover, the broad resistive transition at high
temperatures abruptly becomes sharp upon entering the high-field phase,
indicating a dramatic change of the magnetic-flux properties. We attribute the
high-field phase to the Fulde-Ferrel-Larkin-Ovchinnikov (FFLO) state, where the
formation of planar nodes gives rise to a segmentation of the flux-line
lattice. We point out that strongly orbital-dependent pairing as well as
spin-orbit interactions, the multiband nature, and the extremely small Fermi
energy are important for the formation of the FFLO state in FeSe.


  Following the success of Large Language Models (LLMs), Large Multimodal
Models (LMMs), such as the Flamingo model and its subsequent competitors, have
started to emerge as natural steps towards generalist agents. However,
interacting with recent LMMs reveals major limitations that are hardly captured
by the current evaluation benchmarks. Indeed, task performances (e.g., VQA
accuracy) alone do not provide enough clues to understand their real
capabilities, limitations, and to which extent such models are aligned to human
expectations. To refine our understanding of those flaws, we deviate from the
current evaluation paradigm, and (1) evaluate 10 recent open-source LMMs from
3B up to 80B parameter scale, on 5 different axes; hallucinations, abstention,
compositionality, explainability and instruction following. Our evaluation on
these axes reveals major flaws in LMMs. While the current go-to solution to
align these models is based on training, such as instruction tuning or RLHF, we
rather (2) explore the training-free in-context learning (ICL) as a solution,
and study how it affects these limitations. Based on our ICL study, (3) we push
ICL further and propose new multimodal ICL variants such as; Multitask-ICL,
Chain-of-Hindsight-ICL, and Self-Correcting-ICL. Our findings are as follows.
(1) Despite their success, LMMs have flaws that remain unsolved with scaling
alone. (2) The effect of ICL on LMMs flaws is nuanced; despite its
effectiveness for improved explainability, answer abstention, ICL only slightly
improves instruction following, does not improve compositional abilities, and
actually even amplifies hallucinations. (3) The proposed ICL variants are
promising as post-hoc approaches to efficiently tackle some of those flaws. The
code is available here: https://github.com/mshukor/EvALign-ICL.


  In this short note we want to give a definition of a generalized Deligne
pairing for modules over an Azumaya algebra on an arithmetic surface $X$. We do
this by defining Hermitian metrics on the Azumaya algebra and on the modules in
question. Then we go on and define the determinant of the cohomology for a pair
of modules over an Azumaya algebra. Using this we give the definition of a
generalized Deligne pairing and study some of its properties.


  General relativity and its Newtonian weak field limit are not sufficient to
explain the observed phenomenology in the Universe, from the formation of
large-scale structures to the dynamics of galaxies, with the only presence of
baryonic matter. The most investigated cosmological model, the $\Lambda$CDM,
accounts for the majority of observations by introducing two dark components,
dark energy and dark matter, which represent $\sim$95% of the mass-energy
budget of the Universe. Nevertheless, the $\Lambda$CDM model faces important
challenges on the scale of galaxies. For example, some very tight relations
between the properties of dark and baryonic matters in disk galaxies, such as
the baryonic Tully-Fisher relation (BTFR), the mass discrepancy-acceleration
relation (MDAR), and the radial acceleration relation (RAR), which see the
emergence of the acceleration scale $a_0 \simeq 1.2 \times 10^{-10}$ m
s$^{-2}$, cannot be intuitively explained by the CDM paradigm, where cosmic
structures form through a stochastic merging process. An even more outstanding
coincidence is due to the fact that the acceleration scale $a_0$, emerging from
galaxy dynamics, also seems to be related to the cosmological constant
$\Lambda$. Another challenge is provided by dwarf galaxies, which are darker
than what is expected in their innermost regions. These pieces of evidence can
be more naturally explained, or sometimes even predicted, by modified theories
of gravity, that do not introduce any dark fluid. I illustrate possible
solutions to these problems with the modified theory of gravity MOND, which
departs from Newtonian gravity for accelerations smaller than $a_0$, and with
Refracted Gravity, a novel classical theory of gravity introduced in 2016,
where the modification of the law of gravity is instead regulated by a density
scale.


  The specific heat of liquid helium confined under pressure in nanoporous
material and the formation, in these conditions, of a glass phase accompanied
by latent heat are known. These properties are in good agreement with a recent
model predicting, in liquid elements, the formation of ultrastable glass having
universal thermodynamic properties. The third law of thermodynamics involves
that the specific heat decreases at low temperatures and consequently the
effective transition temperature of the glass increases up to the temperature
where the frozen enthalpy becomes equal to the predicted value. The glass
residual entropy is about 23.6% of the melting entropy.


  In this work we try to use the Monte Carlo algorithm, metropolis, to study
the behavior of 2D magnetic systems; honeycomb, hexagonal and square lattices.
In this study we use Ising Model of magnetism, with considering only nearest
neighbors in the Hamiltonian and with the Ferromagnetic correlation constant.
The code was written in Payton. In this calculation, by comparing the results
obtained for all lattices, we will show that the paramagnetic to ferromagnetic
phase transition depends on the number of neighbor and it is a direct
dependence.


This a biographical essay about Edsger Wybe Dijkstra.


  We study neutrinoless double beta decay in left-right symmetric extension of
the standard model with type I and type II seesaw origin of neutrino masses.
Due to the enhanced gauge symmetry as well as extended scalar sector, there are
several new physics sources of neutrinoless double beta decay in this model.
Ignoring the left-right gauge boson mixing and heavy-light neutrino mixing, we
first compute the contributions to neutrinoless double beta decay for type I
and type II dominant seesaw separately and compare with the standard light
neutrino contributions. We then repeat the exercise by considering the presence
of both type I and type II seesaw, having non-negligible contributions to light
neutrino masses and show the difference in results from individual seesaw
cases. Assuming the new gauge bosons and scalars to be around a TeV, we
constrain different parameters of the model including both heavy and light
neutrino masses from the requirement of keeping the new physics contribution to
neutrinoless double beta decay amplitude below the upper limit set by the GERDA
experiment and also satisfying bounds from lepton flavor violation, cosmology
and colliders.


  We present an in-depth study of the reflectance spectra of 39 equilibrated
and 41 unequilibrated ordinary chondrites. We demonstrate that consistent
measuring conditions are vital for the direct comparison of spectral features
between chondrites, otherwise hampering any conclusions. We include a
comparison with a total of 466 S-type asteroid reflectance spectra. We analyze
(i) if a difference between EOCs and UOCs as well as between H, L and LL can be
seen, (ii) if it is possible to identify unequilibrated and equilibrated S-type
asteroid surfaces and (iii) if we can further constrain the match between OCs
and S-type asteroids all based on reflectance spectra. We checked the
classification of the 31 Antarctic UOCs analyzed in the present work, using
petrography and magnetic measurements, and evidenced that 74% of them were
misclassified. Reflectance spectra were compared between EOCs and UOCs as well
as between H, L and LL chondrites using a set of spectral features including
band depths and positions, peak reflectance values, spectral slopes and the
Ol/(Ol + Px) ratio. UOCs and EOCs reflectance spectra show no clear-cut
dichotomy, but a continuum with some EOCs showing stronger absorption bands and
peak reflectance values, while others are comparable to UOCs. We show by the
example of 6 EOCs that their band depths decrease with decreasing grain size.
Based on reflectance spectra alone, it is thus highly challenging to
objectively identify an unequilibrated from an equilibrated S-type surface.
There is no clear distinction of the chemical groups: only LL EOCs of
petrographic type > 4 can be distinguished from H and L through less deep 2-mic
band depths and 1-mic band positions at longer wavelengths. Lastly, an
anti-correlation between the diameter of the asteroids and their 1000 nm band
depth is found indicating that larger sized S-type asteroids show finer grained
surfaces.


  We study turn-based quantitative games of infinite duration opposing two
antagonistic players and played over graphs. This model is widely accepted as
providing the adequate framework for formalizing the synthesis question for
reactive systems. This important application motivates the question of strategy
complexity: which valuations (or payoff functions) admit optimal positional
strategies (without memory)? Valuations for which both players have optimal
positional strategies have been characterized by Gimbert and Zielonka for
finite graphs and by Colcombet and Niwi\'nski for infinite graphs. However, for
reactive synthesis, existence of optimal positional strategies for the opponent
(which models an antagonistic environment) is irrelevant. Despite this fact,
not much is known about valuations for which the protagonist admits optimal
positional strategies, regardless of the opponent. In this work, we
characterize valuations which admit such strategies over infinite game graphs.
Our characterization uses the vocabulary of universal graphs, which has also
proved useful in understanding recent breakthrough results regarding the
complexity of parity games. More precisely, we show that a valuation admitting
universal graphs which are monotone and well-ordered is positional over all
game graphs, and -- more surprisingly -- that the converse is also true for
valuations admitting neutral colors. We prove the applicability and elegance of
the framework by unifying a number of known positionality results, proving new
ones, and establishing closure under lexicographical products. Finally, we
discuss a class of prefix-independent positional objectives which is closed
under countable unions.


  We prove that the homology of the Swiss-cheese operad is a Koszul operad. As
a consequence, we obtain that the spectral sequence associated to the
stratification of the compactification of points on the upper half plane
collapses at the second stage, proving a conjecture by A. Voronov. However, we
prove that the operad obtained at the second stage differs from the homology of
the Swiss-cheese operad.


  The WT scheme, a piecewise polynomial force interpolation scheme with
time-step dependency, is proposed in this paper for relativistic
particle-in-cell (PIC) simulations. The WT scheme removes the lowest order
numerical Cherenkov instability (NCI) growth rate for arbitrary time steps
allowed by the Courant condition. While NCI from higher order resonances is
still present, the numerical tests show that for smaller time steps, the
numerical instability grows much slower than using the optimal time step found
in previous studies. The WT scheme is efficient for improving the quality and
flexibility of relativistic PIC simulations.


  A simple contactless method suitable to discern between the intergrain
(circular) current, which flows in the thin superconducting ring, and the
intragrain current, which does not cross the weakest link, has been proposed.
At first, we show that the intergrain current may directly be estimated from
the magnetic flux density $B(\pm z_0)$ measured by the Hall sensor positioned
in the special points $\pm z_0$ above/below the ring center. The experimental
and the numerical techniques to determine the value $z_0$ are discussed. Being
very promising for characterization of a current flowing across the joints in
welded YBaCuO rings (its dependencies on the temperature and the external
magnetic field as well as the time dissipation), the approach has been applied
to study corresponding properties of the intra- and intergrain currents flowing
across the $a$-twisted grain boundaries which are frequent in bulk
melt-textured YBaCuO samples. We present experimental data related to the flux
penetration inside a bore of MT YBaCuO rings both in the non-magnetized, virgin
state and during the field reversal. The shielding properties and their
dependence on external magnetic fields are also studied. Besides, we consider
the flux creep effects and their influence on the current re-distribution
during a dwell.


  InGaAs/InP single-photon avalanche diodes (SPADs) are widely used in
practical applications requiring near-infrared photon counting such as quantum
key distribution (QKD). Photon detection efficiency and dark count rate are the
intrinsic parameters of InGaAs/InP SPADs, due to the fact that their
performances cannot be improved using different quenching electronics given the
same operation conditions. After modeling these parameters and developing a
simulation platform for InGaAs/InP SPADs, we investigate the semiconductor
structure design and optimization. The parameters of photon detection
efficiency and dark count rate highly depend on the variables of absorption
layer thickness, multiplication layer thickness, excess bias voltage and
temperature. By evaluating the decoy-state QKD performance, the variables for
SPAD design and operation can be globally optimized. Such optimization from the
perspective of specific applications can provide an effective approach to
design high-performance InGaAs/InP SPADs.


  Advances in technology have provided ways to monitor and measure driving
behavior. Recently, this technology has been applied to usage-based automotive
insurance policies that offer reduced insurance premiums to policy holders who
opt-in to automotive monitoring. Several companies claim to measure only speed
data, which they further claim preserves privacy. However, we have developed an
algorithm - elastic pathing - that successfully tracks drivers' locations from
speed data. The algorithm tracks drivers by assuming a start position, such as
the driver's home address (which is typically known to insurance companies),
and then estimates the possible routes by fitting the speed data to map data.
To demonstrate the algorithm's real-world applicability, we evaluated its
performance with driving datasets from central New Jersey and Seattle,
Washington, representing suburban and urban areas. We are able to estimate
destinations with error within 250 meters for 17% of the traces and within 500
meters for 24% of the traces in the New Jersey dataset, and with error within
250 and 500 meters for 15.5% and 27.5% of the traces, respectively, in the
Seattle dataset. Our work shows that these insurance schemes enable a
substantial breach of privacy.


  In 2009 the cross artform group, Last Man to Die, presented a series of
performances using new interfaces and networked performance to integrate the
three artforms of its members (actor, Hanna Cormick, visual artist, Benjamin
Forster and percussionist, Charles Martin). This paper explains our artistic
motivations and design for a computer vision surface and networked heartbeat
sensor as well as the experience of mounting our first major work, Vital LMTD.


  Quasar damped Ly-alpha (DLA) absorption line systems with redshifts z<1.65
are used to trace neutral gas over approximately 70 per cent of the most recent
history of the Universe. However, such systems fall in the UV and are rarely
found in blind UV spectroscopic surveys. Therefore, it has been difficult to
compile a moderate-sized sample of UV DLAs in any narrow cosmic time interval.
However, DLAs are easy to identify in low-resolution spectra because they have
large absorption rest equivalent widths. We have performed an efficient
strong-MgII-selected survey for UV DLAs at redshifts z=[0.42,0.70] using HST's
low-resolution ACS-HRC-PR200L prism. This redshift interval covers ~1.8 Gyr in
cosmic time, i.e., t~[7.2,9.0] Gyrs after the Big Bang. A total of 96 strong
MgII absorption-line systems identified in SDSS spectra were successfully
observed with the prism at the predicted UV wavelengths of Ly-alpha absorption.
We found that 35 of the 96 systems had a significant probability of being DLAs.
One additional observed system could be a very high N(HI) DLA (N(HI)~2x10^22
atoms cm^-2 or possibly higher), but since very high N(HI) systems are
extremely rare, it would be unusual for this system to be a DLA given the size
of our sample. Here we present information on our prism sample, including our
best estimates of N(HI) and errors for the 36 systems fitted with damped
Ly-alpha profiles. This list is valuable for future follow-up studies of
low-redshift DLAs in a small redshift interval, although such work would
clearly benefit from improved UV spectroscopy to more accurately determine
their neutral hydrogen column densities.


  We investigate the energetics of the jet and X-ray corona of Cyg X-1. We show
that the current estimates of the jet power obtained from Halpha and [O III]
measurements of the optical nebula surrounding the X-ray source allow one to
constrain the bulk velocity of the jet. It is definitely relativistic (v >0.1c)
and most probably in the range (0.3-0.8)c. The exact value of the velocity
depends on the accretion efficiency. These constraints are obtained
independently of, and are consistent with, previous estimates of the jet bulk
velocity based on radio measurements. We then show that the X-ray emission does
not originate in the jet. Indeed, the energy budget does not allow the corona
to be ejected to infinity at relativistic speed. Rather, either a small
fraction of the corona escapes to infinity, or the ejection velocity of the
corona is vanishingly low. Although the corona could constitute the jet
launching region, it cannot be identified with the jet itself. We discuss the
consequences for various X-ray emission models.


  In this work we present the study of $p\Lambda$ and $pp\Lambda$ scattering
processes using femtoscopic correlation functions. This observable has been
recently used to access the low-energy interaction of hadrons emitted in the
final state of high-energy collisions, delivering unprecedented precision
information of the interaction among strange hadrons. The formalism for
particle pairs is well established and it relates the measured correlation
functions with the scattering wave function and the emission source. In the
present work we analyze the $NN\Lambda$ scattering in free space and relate the
corresponding wave function to the $pp\Lambda$ correlation measurement
performed by the ALICE collaboration. The three-body problem is solved using
the hyperspherical adiabatic basis. Regarding the $p\Lambda$ and $pp\Lambda$
interactions, different models are used and their impact on the correlation
function is studied. The three body force considered in this work is anchored
to describe the binding energy of the hypertriton and to give a good
description of the two four-body hypernuclei. As a main result we have observed
a huge, low-energy peak in the $pp\Lambda$ correlation function, mainly
produced by the $J^\pi=1/2^+$ three-body state. The study of this peak from an
experimental as well as a theoretical point of view will provide important
constraints to the two- and three-body interactions.


  The interaction of electrons with quantized phonons and photons underlies the
ultrafast dynamics of systems ranging from molecules to solids, giving rise to
a plethora of physical phenomena experimentally accessible using time-resolved
techniques. Green's function methods offer an invaluable interpretation tool
since scattering mechanisms of growing complexity can be selectively
incorporated in the theory. cheers is a general-purpose nonequilibrium Green's
function code that implements virtually all known many-body approximations and
is designed for first principles studies of ultrafast processes in molecular
and model solid state systems. The aims of generality, extensibility,
efficiency, and user friendliness of the code are achieved through the
underlying theory development and the use of modern software design practices.
Here, we motivate the necessity for the creation of such a code and overview
its design and capabilities.


  Delayed-acceptance Metropolis-Hastings and delayed-acceptance pseudo-marginal
Metropolis-Hastings algorithms can be applied when it is computationally
expensive to calculate the true posterior or an unbiased stochastic
approximation thereof, but a computationally cheap deterministic approximation
is available. An initial accept-reject stage uses the cheap approximation for
computing the Metropolis-Hastings ratio; proposals which are accepted at this
stage are then subjected to a further accept-reject step which corrects for the
error in the approximation. Since the expensive posterior, or the approximation
thereof, is only evaluated for proposals which are accepted at the first stage,
the cost of the algorithm is reduced and larger scalings may be used.
  We focus on the random walk Metropolis (RWM) and consider the
delayed-acceptance RWM and the delayed-acceptance pseudo-marginal RWM. We
provide a framework for incorporating relatively general deterministic
approximations into the theoretical analysis of high-dimensional targets.
Justified by diffusion approximation arguments, we derive expressions for the
limiting efficiency and acceptance rates in high-dimensional settings. These
theoretical insights are finally leveraged to formulate practical guidelines
for the efficient tuning of the algorithms. The robustness of these guidelines
and predicted properties are verified against simulation studies, all of which
are strictly outside of the domain of validity of our limit results.


  In this paper, we study distributed storage problems over unidirectional ring
networks. A lower bound on the reconstructing bandwidth to recover total
original data for each user is proposed, and it is achievable for arbitrary
parameters. If a distributed storage scheme can achieve this lower bound with
equality for each user, we say it an optimal reconstructing distributed storage
scheme (ORDSS). Furthermore, the repair problem for a failed storage node in
ORDSSes is under consideration and a tight lower bound on the repair bandwidth
for each storage node is obtained. Particularly, we indicate the fact that for
any ORDSS, every storage node can be repaired with repair bandwidth achieving
the lower bound with equality. In addition, we present an efficient approach to
construct ORDSSes for arbitrary parameters by using the concept of Euclidean
division. Finally, we take an example to characterize the above approach.


  Large Language Models (LLMs) have demonstrated remarkable performance across
various information-seeking and reasoning tasks. These computational systems
drive state-of-the-art dialogue systems, such as ChatGPT and Bard. They also
carry substantial promise in meeting the growing demands of mental health care,
albeit relatively unexplored. As such, this study sought to examine LLMs'
capability to generate empathetic responses in conversations that emulate those
in a mental health counselling setting. We selected five LLMs: version 3.5 and
version 4 of the Generative Pre-training (GPT), Vicuna FastChat-T5, Pathways
Language Model (PaLM) version 2, and Falcon-7B-Instruct. Based on a simple
instructional prompt, these models responded to utterances derived from the
EmpatheticDialogues (ED) dataset. Using three empathy-related metrics, we
compared their responses to those from traditional response generation dialogue
systems, which were fine-tuned on the ED dataset, along with human-generated
responses. Notably, we discovered that responses from the LLMs were remarkably
more empathetic in most scenarios. We position our findings in light of
catapulting advancements in creating empathetic conversational systems.


  We report analysis of high microlensing event MOA-2008-BLG-379, which has a
strong microlensing anomaly at its peak, due to a massive planet with a mass
ratio of q = 6.9 x 10^{-3}. Because the faint source star crosses the large
resonant caustic, the planetary signal dominates the light curve. This is
unusual for planetary microlensing events, and as a result, the planetary
nature of this light curve was not immediately noticed. The planetary nature of
the event was found when the MOA Collaboration conducted a systematic study of
binary microlensing events previously identified by the MOA alert system. We
have conducted a Bayesian analysis based on a standard Galactic model to
estimate the physical parameters of the lens system. This yields a host star
mass of M_L = 0.66_{-0.33}^{+0.29} M_Sun orbited by a planet of mass m_P =
4.8_{-2.4}^{+2.1} M_Jup at an orbital separation of a = 4.1_{-1.5}^{+1.9} AU at
a distance of D_L = 3.6 +/- 1.3 kpc. The faint source magnitude of I_S = 21.30
and relatively high lens-source relative proper motion of mu_rel = 7.6 +/- 1.6
mas/yr implies that high angular resolution adaptive optics or Hubble Space
Telescope observations are likely to be able to detect the source star, which
would determine the masses and distance of the planet and its host star.


  Recently, a series of papers proposed deep learning-based approaches to
sample from target distributions using controlled diffusion processes, being
trained only on the unnormalized target densities without access to samples.
Building on previous work, we identify these approaches as special cases of a
generalized Schr\"odinger bridge problem, seeking a stochastic evolution
between a given prior distribution and the specified target. We further
generalize this framework by introducing a variational formulation based on
divergences between path space measures of time-reversed diffusion processes.
This abstract perspective leads to practical losses that can be optimized by
gradient-based algorithms and includes previous objectives as special cases. At
the same time, it allows us to consider divergences other than the reverse
Kullback-Leibler divergence that is known to suffer from mode collapse. In
particular, we propose the so-called log-variance loss, which exhibits
favorable numerical properties and leads to significantly improved performance
across all considered approaches.


  We present DINAR, an approach for creating realistic rigged fullbody avatars
from single RGB images. Similarly to previous works, our method uses neural
textures combined with the SMPL-X body model to achieve photo-realistic quality
of avatars while keeping them easy to animate and fast to infer. To restore the
texture, we use a latent diffusion model and show how such model can be trained
in the neural texture space. The use of the diffusion model allows us to
realistically reconstruct large unseen regions such as the back of a person
given the frontal view. The models in our pipeline are trained using 2D images
and videos only. In the experiments, our approach achieves state-of-the-art
rendering quality and good generalization to new poses and viewpoints. In
particular, the approach improves state-of-the-art on the SnapshotPeople public
benchmark.


  Some q-analogues of classical integral transforms have recently been
investigated by many authors in diverse citations. The q-analogues of the
Natural transform are not known nor used. In the present paper, we are
concerned with definitions and investigations of the q-theory of the Natural
transform and some applications. We present two types of q-analogues of the
cited transform on given sets and get results of the nominated analogues for
certain class of functions of special type. We declare here that given results
are new and they complement recent known results related to q-Laplace and
q-Sumudu transforms. Over and above, we present some supporting examples to
illustrate effectiveness of the given results .