  We study the temperature dependence of the pseudoscalar meson properties in a
relativistic bound-state approach exhibiting the chiral behavior mandated by
QCD. Concretely, we adopt the Dyson-Schwinger approach with a rank-2 separable
model interaction. After extending the model to the strange sector and fixing
its parameters at zero temperature, T=0, we study the T-dependence of the
masses and decay constants of all ground-state mesons in the pseudoscalar
nonet. Of chief interest are $\eta$ and $\eta^\prime$. The influence of the QCD
axial anomaly on them is successfully obtained through the Witten-Veneziano
relation at T=0. The same approach is then extended to T>0, using lattice QCD
results for the topological susceptibility. The most conspicuous finding is an
increase of the $\eta^\prime$ mass around the chiral restoration temperature
$T_{\rm Ch}$, which would suggest a suppression of $\eta^\prime$ production in
relativistic heavy-ion collisions. The increase of the $\eta^\prime$ mass may
also indicate that the extension of the Witten-Veneziano relation to finite
temperatures becomes unreliable around and above $T_{\rm Ch}$. Possibilities of
an improved treatment are discussed.


  The dynamics of two mutually coupled chaotic diode lasers are investigated
experimentally and numerically. By adding self feedback to each laser, stable
isochronal synchronization is established. This stability, which can be
achieved for symmetric operation, is essential for constructing an optical
public-channel cryptographic system. The experimental results on diode lasers
are well described by rate equations of coupled single mode lasers.


  We examine faint infrared emission features detected in Spitzer Space
Telescope images of M51, which are associated with atomic hydrogen in the outer
disk and tidal tail at R greater than R_25 (4.9', ~14 kpc at d=9.6 Mpc). The
infrared colors of these features are consistent with the colors of dust
associated with star formation in the bright disk. However, the star formation
efficiency (as a ratio of star formation rate to neutral gas mass) implied in
the outer disk is lower than that in the bright disk of M51 by an order of
magnitude, assuming a similar relationship between infrared emission and star
formation rate in the inner and outer disks.


  We give an example of a class of distributions that is learnable in total
variation distance with a finite number of samples, but not learnable under
$(\varepsilon, \delta)$-differential privacy. This refutes a conjecture of
Ashtiani.


  We use holographic techniques to study meson quasiparticles moving through a
thermal plasma in N=2 super-Yang-Mills theory, with gauge group SU(N_c) and
coupled to N_f flavours of fundamental matter. This holographic approach
reliably describes the system at large N_c, large 't Hooft coupling and
N_f/N_c<<1. The meson states are destabilized by introducing a small quark
density n_q. Spectral functions are used to examine the dispersion relations of
these quasiparticles. In a low-momentum regime, the quasiparticles approach a
limiting velocity which can be significantly less than the speed of light. In
this regime, the widths of the quasiparticles also rise dramatically as their
momentum approaches a critical value q_crit. While the spectral functions do
not display isolated resonances for q>q_crit, the dispersion relations can be
extended into this high-momentum regime by studying the dual quasinormal modes.
A preliminary qualitative analysis of these modes suggests that the group
velocity rises to the speed of light for q>>q_crit.


  Non-orthogonal multiple-access (NOMA) and simultaneous wireless information
and power transfer (SWIPT) are promising techniques to improve spectral
efficiency and energy efficiency. However, the security of NOMA SWIPT systems
has not received much attention in the literature. In this paper, an artificial
noise-aided beamforming design problem is studied to enhance the security of a
multiple-input single-output NOMA SWIPT system where a practical non-linear
energy harvesting model is adopted. The problem is non-convex and challenging
to solve. Two algorithms are proposed to tackle this problem based on
semidefinite relaxation (SDR) and successive convex approximation. Simulation
results show that a performance gain can be obtained by using NOMA compared to
the conventional orthogonal multiple access. It is also shown that the
performance of the algorithm using a cost function is better than the algorithm
using SDR at the cost of a higher computation complexity.


  In this work we extend the recently proposed synchronous broadcast algorithm
amnesiac flooding to the case of intermittent communication channels. In
amnesiac flooding a node forwards a received message in the subsequent round.
There are several reasons that render an immediate forward of a message
impossible: Higher priority traffic, overloaded channels, etc. We show that
postponing the forwarding for one or more rounds prevents termination. Our
extension overcomes this shortcoming while retaining the advantages of the
algorithm: Nodes don't need to memorize the reception of a message to guarantee
termination and messages are sent at most twice per edge. This extension allows
to solve more general broadcast tasks such as multi-source broadcasts and
concurrent broadcasts for systems with bounded channel capacities.


  We prove a general rigorous lower bound for
$W(\Lambda,q)=\exp(S_0(\Lambda,q)/k_B)$, the exponent of the ground state
entropy of the $q$-state Potts antiferromagnet, on an arbitrary Archimedean
lattice $\Lambda$. We calculate large-$q$ series expansions for the exact
$W_r(\Lambda,q)=q^{-1}W(\Lambda,q)$ and compare these with our lower bounds on
this function on the various Archimedean lattices. It is shown that the lower
bounds coincide with a number of terms in the large-$q$ expansions and hence
serve not just as bounds but also as very good approximations to the respective
exact functions $W_r(\Lambda,q)$ for large $q$ on the various lattices
$\Lambda$. Plots of $W_r(\Lambda,q)$ are given, and the general dependence on
lattice coordination number is noted. Lower bounds and series are also
presented for the duals of Archimedean lattices. As part of the study, the
chromatic number is determined for all Archimedean lattices and their duals.
Finally, we report calculations of chromatic zeros for several lattices; these
provide further support for our earlier conjecture that a sufficient condition
for $W_r(\Lambda,q)$ to be analytic at $1/q=0$ is that $\Lambda$ is a regular
lattice.


  The NUGA project is the first high-resolution (0.5''-1'') CO survey of low
luminosity AGN including the full sequence of activity types (Seyfert 1--2 and
LINERs). NUGA aims to study systematically the different mechanisms for gas
fueling of the AGN. In order to reach the critical spatial scales for AGN
feeding (<100 pc), we are undertaking high-resolution observations, made at the
Plateau de Bure Interferometer, to achieve a sharp view of the distribution and
kinematics of molecular gas. In this talk we discuss the latest results of this
survey which now includes newly acquired subarcsec resolution observations for
5 targets of our sample. The large variety of circumnuclear disk morphologies
found in NUGA galaxies (m=1, m=2 and m=0-type gravitational instabilities) is a
challenging result that urges the refinement of current dynamical models.


  The theory of the effect of external fluctuation force on the stability and
spatial distribution of mutually interacting and slowly evaporating charged
drops, levitated in an electrodynamic balance, is presented using classical
pseudo-potential approach. The theory is supplemented with numerical
simulations where the non-homogeneous modified Mathieu equation is solved for
single droplet as well as many droplets. The transition from the well ordered
Coulombic crystal to randomly distributed liquid like structure is observed
above a threshold value of the order parameter. The theory and simulations are
found to be in fair agreement with each other. The simulation is aimed at
studying the stability of structures for capturing the pollutant particle form
the air streams using contactless membrane.


  Perovskite chalcogenides are gaining substantial interest as an emerging
class of semiconductors for optoelectronic applications. High quality samples
are of vital importance to examine their inherent physical properties. We
report the successful crystal growth of the model system, BaZrS$_3$ and its
Ruddlesden-Popper phase Ba$_3$Zr$_2$S$_7$ by flux method. X-ray diffraction
analyses showed space group of $Pnma$ with lattice constants of $a$ = 7.056(3)
\AA\/, $b$ = 9.962(4) \AA\/, $c$ = 6.996(3) \AA\/ for BaZrS$_3$ and $P4_2/mnm$
with $a$ = 7.071(2) \AA\/, $b$ = 7.071(2) \AA\/, $c$ = 25.418(5) \AA\/ for
Ba$_3$Zr$_2$S$_7$. Rocking curves with full-width-at-half-maximum of
0.011$^\circ$ for BaZrS$_3$ and 0.027$^\circ$ for Ba$_3$Zr$_2$S$_7$ were
observed. Pole figure analysis, scanning transmission electron microscopy
images and electron diffraction patterns also establish high quality of grown
crystals. The octahedra tilting in the corner-sharing octahedra network are
analyzed by extracting the torsion angles.


  We introduce a model of tree-rooted planar maps weighted by their number of
$2$-connected blocks. We study its enumerative properties and prove that it
undergoes a phase transition. We give the distribution of the size of the
largest $2$-connected blocks in the three regimes (subcritical, critical and
supercritical) and further establish that the scaling limit is the Brownian
Continuum Random Tree in the critical and supercritical regimes, with
respective rescalings $\sqrt{n/\log(n)}$ and $\sqrt{n}$.


  A combination of small-cluster exact-diagonalization calculations and a
well-controlled approximative method is used to study the ground-state phase
diagram of the spin-one-half Falicov-Kimball model extended by the
spin-dependent on-site interaction between localized ($f$) and itinerant ($d$)
electrons. Both the magnetic and charge ordering are analysed as functions of
the spin-dependent on-site interaction ($J$) and the total number of itinerant
($N_d$) and localized ($N_f$) electrons at selected $U$ (the spin-independent
interaction between the $f$ and $d$ electrons). It is shown that the
spin-dependent interaction (for $N_f=L$, where $L$ is the number of lattice
sites) stabilizes the ferromagnetic (F) and ferrimagnetic (FI) state, while the
stability region of the antiferromagnetic (AF) phase is gradually reduced. The
precisely opposite effect on the stability of F, FI and AF phases has a
reduction of $N_f$. Moreover, the strong coupling between the $f$ and
$d$-electron subsystems is found for both $N_f=L$ as well as $N_f < L$.


  We study bosonic atoms in small optical lattices by exact diagonalization and
observe a striking similarity to the superfluid to Mott insulator transition in
macroscopic systems. The momentum distribution, the formation of an energy gap,
and the pair correlation function show only a weak size dependence. For
noncommensurate filling we reveal in deep lattices a mixture of localized and
delocalized particles, which is sensitive to lattice imperfections. Breaking
the lattice symmetry causes a Bose-glass-like behavior. We discuss the nature
of excited states and orbital effects by using an exact diagonalization
technique that includes higher bands.


  Using a wide array of machinery from diverse fields across mathematics, we
provide a construction of a measure on the real line which is doubling on all
$n$-adic intervals for any finite list of $n\in\mathbb{N}$, yet not doubling
overall. In particular, we extend previous results in the area, where only two
coprime numbers $n$ were allowed, by using substantially new ideas. In
addition, we provide several nontrivial applications to reverse H\"older
weights, $A_p$ weights, Hardy spaces, BMO and VMO function classes, and connect
our results with key principles and conjectures across number theory.


  A (quasi-)Hamiltonian manifold is called multiplicity free if all of its
symplectic reductions are 0-dimensional. In this paper, we classify
multiplicity free Hamiltonian actions for (twisted) loop groups or,
equivalently, multiplicity free (twisted) quasi-Hamiltonian manifolds for
simply connected compact Lie groups. As a result we recover old and find new
examples of these structures.


  We give general classification and structure theorems for actions of groups
of homeomorphisms and diffeomorphisms on manifolds, reminiscent of classical
results for actions of (locally) compact groups. This gives a negative answer
to Ghys' "extension problem" for diffeomorphisms of manifolds with boundary, as
well as a classification of all homomorphisma $\mathrm{Homeo}_0(M) \to
\mathrm{Homeo}_0(N)$ when dim(M) = dim(N) (and related results for
diffeomorphisms), and a complete classification of actions of
$\mathrm{Homeo}_0(S^1)$ on surfaces. This resolves many problems in a program
initiated by Ghys, and gives definitive answers to conjectures of Militon and
Hurtado and a question of Rubin.


  The main result of this paper is a new exact algorithm computing the estimate
given by the Least Trimmed Squares (LTS). The algorithm works under very weak
assumptions. To prove that, we study the respective objective function using
basic techniques of analysis and linear algebra.


  In this article we consider variable coefficient, time dependent wave
equations in exterior domains. We prove localized energy estimates if the
domain is star-shaped and global in time Strichartz estimates if the domain is
strictly convex.


  If the fundamental Planck scale is near a TeV, then we should expect to see
TeV scale black holes at the LHC. Similarly, if the scale of supersymmetry
breaking is sufficiently low, then we might expect to see light supersymmetric
particles in the next generation of colliders. If the mass of the
supersymmetric particle is of order a TeV and is comparable to the temperature
of a typical TeV scale black hole, then such sparticles will be copiously
produced via Hawking radiation: The black hole will act as a resonance for
sparticles, among other things. In this paper we compared various signatures
for SUSY production at LHC, and we contrasted the situation where the
sparticles are produced directly via parton fusion processes with the situation
where they are produced indirectly through black hole resonances. We found that
black hole resonances provide a larger source for heavy mass SUSY (squark and
gluino) production than the direct pQCD-SUSY production via parton fusion
processes depending on the values of the Planck mass and blackhole mass. Hence
black hole production at LHC may indirectly act as a dominant channel for SUSY
production. We also found that the differential cross section d\sigma/dp_t for
SUSY production increases as a function of the p_t (up to p_t equal to about 1
TeV or more) of the SUSY particles (squarks and gluinos), which is in sharp
contrast with the pQCD predictions where the differential cross section
d\sigma/dp_t decreases as p_t increases for high p_t about 1 TeV or higher.
This is a feature for any particle emission from TeV scale blackhole as long as
the temperature of the blackhole is very high (~ TeV). Hence measurement of
increase of d\sigma/dp_t with p_t for p_t up to about 1 TeV or higher for final
state particles might be a useful signature for blackhole production at LHC.


  The Hayden-Preskill protocol probes the capability of information recovery
from local subsystems after unitary dynamics. As such it resolves the
capability of quantum many-body systems to dynamically implement a quantum
error-correcting code. The transition to coding behavior has been mostly
discussed using effective approaches, such as entanglement membrane theory.
Here, we present exact results on the use of Hayden-Preskill recovery as a
dynamical probe of scrambling in local quantum many-body systems. We
investigate certain classes of unitary circuit models, both structured Floquet
(dual-unitary) and Haar-random circuits. We discuss different dynamical
signatures corresponding to information transport or scrambling, respectively,
that go beyond effective approaches. Surprisingly, certain chaotic circuits
transport information with perfect fidelity. In integrable dual-unitary
circuits, we relate the information transmission to the propagation and
scattering of quasiparticles. Using numerical and analytical insights, we argue
that the qualitative features of information recovery extend away from these
solvable points. Our results suggest that information recovery protocols can
serve to distinguish chaotic and integrable behavior, and that they are
sensitive to characteristic dynamical features, such as long-lived
quasiparticles or dual-unitarity.


  In this article, we propose a new algorithm for supervised learning methods,
by which one can both capture the non-linearity in data and also find the best
subset model. To produce an enhanced subset of the original variables, an ideal
selection method should have the potential of adding a supplementary level of
regression analysis that would capture complex relationships in the data via
mathematical transformation of the predictors and exploration of synergistic
effects of combined variables. The method that we present here has the
potential to produce an optimal subset of variables, rendering the overall
process of model selection to be more efficient. The core objective of this
paper is to introduce a new estimation technique for the classical least square
regression framework. This new automatic variable transformation and model
selection method could offer an optimal and stable model that minimizes the
mean square error and variability, while combining all possible subset
selection methodology and including variable transformations and interaction.
Moreover, this novel method controls multicollinearity, leading to an optimal
set of explanatory variables.


  We use state-of-the-art radiation-MHD simulations and 3D non-LTE radiative
transfer computations to investigate \Halpha\ line formation in the solar
chromosphere and apply the results of this investigation to develop the
potential of \Halpha\ as diagnostic of the chromosphere.
  We show that one can accurately model \Halpha\ line formation assuming
statistical equilibrium and complete frequency redistribution provided the
computation of the model atmosphere included non-equilibrium ionization of
hydrogen, and the Lyman-$\alpha$ and Lyman-$\beta$ line profiles are described
by Doppler profiles.
  We find that 3D radiative transfer is essential in modeling hydrogen lines
due to the low photon destruction probability in \Halpha. The \Halpha\ opacity
in the upper chromosphere is mainly sensitive to the mass density and only
weakly sensitive to temperature.
  We find that the \Halpha\ line-core intensity is correlated with the average
formation height: the larger the average formation height, the lower the
intensity. The line-core width is a measure of the gas temperature in the
line-forming region. The fibril-like dark structures seen in \Halpha\ line-core
images computed from our model atmosphere are tracing magnetic field lines.
These structures are caused by field-aligned ridges of enhanced chromospheric
mass density that raise their average formation height, and therefore makes
them appear dark against their deeper-formed surroundings. We compare with
observations, and find that the simulated line-core widths are very similar to
the observed ones, without the need for additional microturbulence.


  Symmetry breaking ubiquitously occurs across complex systems, from phase
transition in statistical physics to self-organized lane formation in
pedestrian dynamics. Here, we uncover spontaneous symmetry breaking in a simple
model of ride-sharing adoption. We analyze how collective interactions among
ride-sharing users to avoid detours in shared rides give rise to spontaneous
symmetry breaking and pattern formation in the adoption dynamics. These
dynamics result in bistability of high homogeneous and partial heterogeneous
adoption states, potentially limiting the population-wide adoption of
ride-sharing. Our results provide a framework to understand real-world adoption
patterns of ride-sharing in complex urban settings and support the (re)design
of ride-sharing services and incentives for sustainable shared mobility.


  Domain generalization models aim to learn cross-domain knowledge from source
domain data, to improve performance on unknown target domains. Recent research
has demonstrated that diverse and rich source domain samples can enhance domain
generalization capability. This paper argues that the impact of each sample on
the model's generalization ability varies. Despite its small scale, a
high-quality dataset can still attain a certain level of generalization
ability. Motivated by this, we propose a domain-adversarial active learning
(DAAL) algorithm for classification tasks in domain generalization. First, we
analyze that the objective of tasks is to maximize the inter-class distance
within the same domain and minimize the intra-class distance across different
domains. To achieve this objective, we design a domain adversarial selection
method that prioritizes challenging samples. Second, we posit that even in a
converged model, there are subsets of features that lack discriminatory power
within each domain. We attempt to identify these feature subsets and optimize
them by a constraint loss. We validate and analyze our DAAL algorithm on
multiple domain generalization datasets, comparing it with various domain
generalization algorithms and active learning algorithms. Our results
demonstrate that the DAAL algorithm can achieve strong generalization ability
with fewer data resources, thereby reducing data annotation costs in domain
generalization tasks.


  A non-decimated wavelet transform (NDWT) is a popular version of wavelet
transforms because of its many advantages in applications. The inherent
redundancy of this transform proved beneficial in tasks of signal denoising and
scaling assessment. To facilitate the use of NDWT, we built a MATLAB package,
{\bf WavmatND}, which has three novel features: First, for signals of moderate
size the proposed method reduces computation time of the NDWT by replacing
repetitive convolutions with matrix multiplications. Second, submatrices of an
NDWT matrix can be rescaled, which enables a straightforward inverse transform.
Finally, the method has no constraints on a size of the input signal in one or
in two dimensions, so signals of non-dyadic length and rectangular
two-dimensional signals with non-dyadic sides can be readily transformed. We
provide illustrative examples and a tutorial to assist users in application of
this stand-alone package.


  Active matter systems are driven out of equilibrium by conversion of energy
into directed motion locally on the level of the individual constituents. In
the spirit of a minimal description, active matter is often modeled by
so-called active Ornstein-Uhlenbeck particles (AOUPs), an extension of passive
Brownian motion where activity is represented by an additional fluctuating
non-equilibrium "force" with simple statistical properties (Ornstein-Uhlenbeck
process). While in passive Brownian motion, entropy production along
trajectories is well-known to relate to irreversibility in terms of the
log-ratio of probabilities to observe a certain particle trajectory forward in
time in comparison to observing its time-reversed twin trajectory, the
connection between these concepts for active matter is less clear. It is
therefore of central importance to provide explicit expressions for the
irreversibility of active particle trajectories based on measurable quantities
alone, such as the particle positions. In this technical note, we derive a
general expression for the irreversibility of AOUPs in terms of path
probability ratios (forward versus backward path), extending recent results
from [PRX 9, 021009 (2019)] by allowing for arbitrary initial particle
distributions and states of the active driving.


  Exponential-family random graph models (ERGMs) are a family of network models
originating in social network analysis, which have also been applied to
biological networks. Advances in estimation algorithms have increased the
practical scope of these models to larger networks, however it is still not
always possible to estimate a model without encountering problems of model
near-degeneracy, particularly if it is desired to use only simple model
parameters, rather than more complex parameters designed to overcome the
problem of near-degeneracy. Two new network models related to the ERGM, the
Tapered ERGM, and the latent order logistic (LOLOG) model, have recently been
proposed to overcome this problem. In this work I illustrate the application of
the Tapered ERGM and the LOLOG to a set of biological networks, including
protein-protein interaction (PPI) networks, gene regulatory networks, and
neural networks. I find that the Tapered ERGM and the LOLOG are able to
estimate models for networks for which it was not possible to estimate a
conventional ERGM, and are able to do so using only simple model parameters. In
the case of two neural networks where data on the spatial position of neurons
is available, this allows the estimation of models including terms for spatial
distance and triangle structures, allowing triangle motif statistical
significance to be estimated while accounting for the effect of spatial
proximity on connection probability. For some larger networks, however, Tapered
ERGM and LOLOG estimation was not possible in practical time, while
conventional ERGM models were able to be estimated only by using the
Equilibrium Expectation (EE) algorithm.


  We study the properties of distinct dark matter halos (i.e., those that are
not subhalos) that have a final virial mass $M_{\mathrm{vir}}$ at $z = 0$ less
than their peak mass ($M_{\mathrm{peak}}$) in the Bolshoi-Planck cosmological
simulation. We identify two primary causes of halo mass loss: relaxation after
a major merger and tidal stripping by a massive neighbouring halo. Major
mergers initially boost $M_{\mathrm{vir}}$ and typically cause the final halo
to become more prolate and less relaxed and to have higher spin and lower NFW
concentration. As the halo relaxes, high energy material from the recent merger
gradually escapes beyond the virial radius, temporarily resulting in a net
negative accretion rate that reduces the halo mass by $5-15\%$ on average.
Halos that experience a major merger around $z = 0.4$ typically reach a minimum
mass near $z = 0$. Tidal stripping mainly occurs in dense regions, and it
causes halos to become less prolate and have lower spins and higher NFW
concentrations. Tidally stripped halos often lose a large fraction of their
peak mass ($> 20\%$) and most never recover (or even reattain a positive
accretion rate). Low mass halos can be strongly affected by both post-merger
mass loss and tidal stripping, while high mass halos are predominantly
influenced by post-merger mass loss and show few signs of significant tidal
stripping.


  In this paper, two different approaches fluid forces computation approaches
are compared in the frame of Volume Penalization - Lattice Boltzmann Method
(VP-LBM). The first method, the momentum exchange method, uses the variation of
the distribution functions near the fluid solid interface, while the second
one, the stress integration method, allows direct integration of fluid forces
onto this interface. Applied to the VP-LBM, which consists in penalizing the
solid in the LBM, these two methods lead to significantly different results.
The tests are performed to study on one hand the lift and drag coefficients of
a Naca 0012 airfoil at different angles of attack, at Reynolds number 1000, and
on the other hand, the particle sedimentation under gravity in a channel.


  The discovery of gravitational waves from merging compact objects has opened
up a new window to the Universe. Planned third-generation gravitational-wave
detectors such as Einstein Telescope will potentially deliver hundreds of such
events at redshifts below $z\sim0.1$. Finding electromagnetic counterparts to
these events will be a major observational challenge. We demonstrate how
Einstein Telescope will provide advance warning of such events on a timescale
of hours, based on the low frequency emission from the pre-merger system. In
addition, we suggest how this early warning enables prompt identification of
any electromagnetic counterpart using the Large Synoptic Survey Telescope.


  The newly released observational $H(z)$ data (OHD) is used to constrain
$\Lambda(t)$CDM models as holographic and agegraphic dark energy. By the use of
the length scale and time scale as the IR cut-off including Hubble horizon
(HH), future event horizon (FEH), age of the universe (AU), and conformal time
(CT), we achieve four different $\Lambda(t)$CDM models which can describe the
present cosmological acceleration respectively. In order to get a comparison
between such $\Lambda(t)$CDM models and standard $\Lambda$CDM model, we use the
information criteria (IC), $Om(z)$ diagnostic, and statefinder diagnostic to
measure the deviations. Furthermore, by simulating a larger Hubble parameter
data sample in the redshift range of $0.1<z<2.0$, we get the improved
constraints and more sufficient comparison. We show that OHD is not only able
to play almost the same role in constraining cosmological parameters as SNe Ia
does but also provides the effective measurement of the deviation of the DE
models from standard $\Lambda$CDM model. In the holographic and agegraphic
scenarios, the results indicate that the FEH is more preferable than HH
scenario. However, both two time scenarios show better approximations to
$\Lambda$CDM model than the length scenarios.


  Following on after three previous papers discussing the formation of
primordial black holes during the radiative era of the early universe, we
present here a further investigation of the critical nature of the process
involved, aimed at making contact with some of the basic underlying ideas from
the literature on critical collapse. We focus on the intermediate state, which
we have found appearing in cases with perturbations close to the critical
limit, and examine the connection between this and the similarity solutions
which play a fundamental role in the standard picture of critical collapse. We
have derived a set of self-similar equations for the null-slicing form of the
metric which we are using for our numerical calculations, and have then
compared the results obtained by integrating these with the ones coming from
our simulations for collapse of cosmological perturbations within an expanding
universe. We find that the similarity solution is asymptotically approached in
a region which grows to cover both the contracting matter and part of the
semi-void which forms outside it. Our main interest is in the situation
relevant for primordial black hole formation in the radiative era of the early
universe, where the relation between the pressure $p$ and the energy density
$e$ can be reasonably approximated by an expression of the form $p = we$ with
$w=1/3$. However, we have also looked at other values of $w$, both because
these have been considered in previous literature and also because they can be
helpful for giving further insight into situations relevant for primordial
black hole formation. As in our previous work, we have started our simulations
with initial supra-horizon scale perturbations of a type which could have come
from inflation.


  We study the possibility of the helium decoupling in the stellar wind of
sigma Ori E. To obtain reliable wind parameters for this star we first
calculate an NLTE wind model and derive wind mass-loss rate and terminal
velocity. Using corresponding force multipliers we study the possibility of
helium decoupling. We find that helium decoupling is not possible for realistic
values of helium charge (calculated from NLTE wind models). Helium decoupling
seems only possible for a very low helium charge. The reason for this behaviour
is the strong coupling between helium and hydrogen. We also find that
frictional heating becomes important in the outer parts of the wind of sigma
Ori E due to the collisions between some heavier elements and the passive
components -- hydrogen and helium. For a metallicity ten times lower than the
solar one both hydrogen and helium decouple from the metals and may fall back
onto the stellar surface. However, this does not explain the observed chemical
peculiarity since both these components decouple together from the absorbing
ions. Although we do not include the effects of the magnetic field into our
models, we argue that the presence of a magnetic field will likely not
significantly modify the derived results because in such case model equations
describe the motion parallel to the magnetic field.


  In this paper we consider a nonlocal evolution problem and obtain by a
scaling method the first term in the asymptotic behavior of the solutions. The
method employed treats in different way the smooth and the rough part of the
solution.


  The stochastic block model (SBM) provides a popular framework for modeling
community structures in networks. However, more attention has been devoted to
problems concerning estimating the latent node labels and the model parameters
than the issue of choosing the number of blocks. We consider an approach based
on the log likelihood ratio statistic and analyze its asymptotic properties
under model misspecification. We show the limiting distribution of the
statistic in the case of underfitting is normal and obtain its convergence rate
in the case of overfitting. These conclusions remain valid when the average
degree grows at a polylog rate. The results enable us to derive the correct
order of the penalty term for model complexity and arrive at a likelihood-based
model selection criterion that is asymptotically consistent. Our analysis can
also be extended to a degree-corrected block model (DCSBM). In practice, the
likelihood function can be estimated using more computationally efficient
variational methods or consistent label estimation algorithms, allowing the
criterion to be applied to large networks.


  Nonreciprocity, the defining characteristic of isolators, circulators and a
wealth of other applications in radio/microwave communications technologies, is
in general difficult to achieve as most physical systems incorporate symmetries
that prevent the effect. In particular, acoustic waves are an important medium
for information transport, but they are inherently symmetric in time. In this
work, we report giant nonreciprocity in the transmission of surface acoustic
waves (SAWs) on lithium niobate substrate coated with
ferromagnet/insulator/ferromagnet (FeGaB/Al2O3/FeGaB) multilayer structure. We
exploit this novel structure with a unique asymmetric band diagram, and expand
on magnetoelastic coupling theory to show how the magnetic bands couple with
acoustic waves only in a single direction. We measure 48.4 dB (ratio of
1:100,000) isolation which outperforms current state of the art microwave
isolator devices in a novel acoustic wave system that facilitates unprecedented
size, weight, and power reduction. Additionally, these results offer a
promising platform to study nonreciprocal SAW devices.


  We present a method for improving the performance of nested
  sampling as well as its accuracy. Building on previous work by
  Chen et al., we show that posterior repartitioning
  may be used to reduce the amount of time nested sampling spends in
  compressing from prior to posterior if a suitable ``proposal''
  distribution is supplied. We showcase this on a cosmological example
  with a Gaussian posterior, and release the code as an LGPL licensed,
  extensible Python package
  https://gitlab.com/a-p-petrosyan/sspr.


  The generalization ability of Convolutional neural networks (CNNs) for
biometrics drops greatly due to the adverse effects of various occlusions. To
this end, we propose a novel unified framework integrated the merits of both
CNNs and graphical models to learn dynamic graph representations for occlusion
problems in biometrics, called Dynamic Graph Representation (DGR).
Convolutional features onto certain regions are re-crafted by a graph generator
to establish the connections among the spatial parts of biometrics and build
Feature Graphs based on these node representations. Each node of Feature Graphs
corresponds to a specific part of the input image and the edges express the
spatial relationships between parts. By analyzing the similarities between the
nodes, the framework is able to adaptively remove the nodes representing the
occluded parts. During dynamic graph matching, we propose a novel strategy to
measure the distances of both nodes and adjacent matrixes. In this way, the
proposed method is more convincing than CNNs-based methods because the dynamic
graph method implies a more illustrative and reasonable inference of the
biometrics decision. Experiments conducted on iris and face demonstrate the
superiority of the proposed framework, which boosts the accuracy of occluded
biometrics recognition by a large margin comparing with baseline methods.The
code is avaliable at
https://github.com/RenMin1991/Dyamic\_Graph\_Representation


  We construct solutions of the Cahn-Hilliard equation whose nodal set
converges to a given constant mean curvature hypersurface in a Riemannian
manifold.


  We use elementary geometric techniques to exhibit an explicit equivalence
between certain sectors of the Gromov-Witten theories of blowups of P^1xP^1xP^1
and P^3. In particular, we prove that the all genus, virtual dimension zero
Gromov-Witten theory of the blowup of P^3 at points coincides with that of the
blowup at points of P^1xP^1xP^1, for non-exceptional classes. We observe a
toric symmetry of the Gromov-Witten theory of P^1xP^1xP^1 analogous and
intimately related to Cremona symmetry of P^3. Enumerative applications are
given.


  We study the injective envelope I(X) of an operator space X, showing amongst
other things that it is a self-dual C$^*-$module. We describe the diagonal
corners of the injective envelope of the canonical operator system associated
with X. We prove that if X is an operator $A-B$-bimodule, then A and B can be
represented completely contractively as subalgebras of these corners. Thus, the
operator algebras that can act on X are determined by these corners of I(X) and
consequently bimodules actions on X extend naturally to actions on I(X). These
results give another characterization of the multiplier algebra of an operator
space, which was introduced by the first author, and a short proof of a recent
characterization of operator modules, and a related result. As another
application, we extend Wittstock's module map extension theorem, by showing
that an operator $A-B$-bimodule is injective as an operator $A-B$-bimodule if
and only if it is injective as an operator space.


  We derive analytical expressions for the frequency and damping of the lowest
collective modes of a two-dimensional Fermi gas using kinetic theory. For
strong coupling, we furthermore show that pairing correlations overcompensate
the effects of Pauli blocking on the collision rate for a large range of
temperatures, resulting in a rate which is larger than that of a classical gas.
Our results agree well with experimental data, and they recover the observed
cross-over from collisionless to hydrodynamic behaviour with increasing
coupling for the quadruple mode. Finally, we show that a trap anisotropy within
the experimental bounds results in a damping of the breathing mode which is
comparable to what is observed, even for a scale invariant system.


  We develop an autonomous navigation algorithm for a robot operating in
two-dimensional environments containing obstacles, with arbitrary non-convex
shapes, which can be in close proximity with each other, as long as there
exists at least one safe path connecting the initial and the target location.
An instrumental transformation that modifies (virtually) the non-convex
obstacles, in a non-conservative manner, is introduced to facilitate the design
of the obstacle-avoidance strategy. The proposed navigation approach relies on
a hybrid feedback that guarantees global asymptotic stabilization of a target
location while ensuring the forward invariance of the modified obstacle-free
workspace. The proposed hybrid feedback controller guarantees Zeno-free
switching between the move-to-target mode and the obstacle-avoidance mode based
on the proximity of the robot with respect to the modified obstacle-occupied
workspace. Finally, we provide an algorithmic procedure for the sensor-based
implementation of the proposed hybrid controller and validate its effectiveness
via some numerical simulations.


  The fractal dimension of large-scale galaxy clustering has been demonstrated
to be roughly $D_F \sim 2$ from a wide range of redshift surveys. If correct,
this statistic is of interest for two main reasons: fractal scaling is an
implicit representation of information content, and also the value itself is a
geometric signature of area. It is proposed that the fractal distribution of
galaxies may thus be interpreted as a signature of holography (``fractal
holography''), providing more support for current theories of holographic
cosmologies. Implications for entropy bounds are addressed. In particular,
because of spatial scale invariance in the matter distribution, it is shown
that violations of the spherical entropy bound can be removed. This holographic
condition instead becomes a rigid constraint on the nature of the matter
density and distribution in the Universe. Inclusion of a dark matter
distribution is also discussed, based on theoretical considerations of possible
universal CDM density profiles.


  We investigate electron-phonon coupling in the molecular crystals CH$_4$,
NH$_3$, H$_2$O, and HF, using first-principles quantum mechanical calculations.
We find vibrational corrections to the electronic band gaps at zero temperature
of -1.97 eV, -1.01 eV, -1.52 eV, and -1.62 eV, respectively, which are
comparable in magnitude to those from electron-electron correlation effects.
Microscopically, the strong electron-phonon coupling arises in roughly equal
measure from the almost dispersionless high-frequency molecular modes and from
the lower frequency lattice modes. We also highlight the limitations of the
widely used Allen-Heine-Cardona theory, which gives significant discrepancies
compared to our more accurate treatment.


  We study the imprints of a cosmological redshift-dependent pseudoscalar field
$\phi$ on the rotation of cosmic microwave background (CMB) linear polarization
generated by a coupling $ \phi F^{\mu\nu} \tilde F_{\mu \nu}$. We show how
either phenomenological or theoretically motivated redshift dependence of the
pseudoscalar field, such as those in models of Early Dark Energy, Quintessence
or axion-like dark matter, lead to CMB polarization and
temperature-polarization power spectra which exhibit a multipole dependence
which goes beyond the widely adopted approximation in which the redshift
dependence of the linear polarization angle is neglected. Because of this
multipole dependence, the isotropic birefringence effect due to a general
coupling $\phi F^{\mu\nu} \tilde F_{\mu \nu}$ is not degenerate with a
systematic calibration angle uncertainty. By taking this multipole dependence
into account, we calculate the parameters of these phenomenological and
theoretical redshift dependence of the pseudoscalar field which can be detected
by future CMB polarization experiments on the basis of a $\chi^2$ analysis for
a Wishart likelihood. As a final example of our approach, we compute by Markov
Chain MonteCarlo (MCMC) the minimal coupling $g_\phi$ in Early Dark Energy
which could be detected by future experiments, with or without marginalizing on
a systematic rotation angle uncertainty.


  We examine the computational energy requirements of different systems driven
by the geometrical scaling law, and increasing use of Artificial Intelligence
or Machine Learning (AI-ML) over the last decade. With more scientific and
technology applications based on data-driven discovery, machine learning
methods, especially deep neural networks, have become widely used. In order to
enable such applications, both hardware accelerators and advanced AI-ML methods
have led to the introduction of new architectures, system designs, algorithms,
and software. Our analysis of energy trends indicates three important
observations: 1) Energy efficiency due to geometrical scaling is slowing down;
2) The energy efficiency at the bit-level does not translate into efficiency at
the instruction-level, or at the system-level for a variety of systems,
especially for large-scale AI-ML accelerators or supercomputers; 3) At the
application level, general-purpose AI-ML methods can be computationally energy
intensive, off-setting the gains in energy from geometrical scaling and special
purpose accelerators. Further, our analysis provides specific pointers for
integrating energy efficiency with performance analysis for enabling
high-performance and sustainable computing in the future.


  We consider five dimensional (5D) supersymmetric SO(10) compactified on the
orbifold $S^1/(Z_2\times Z_2')$ such that the SO(10) gauge symmetry is broken
on both fixed points (branes), and the residual gauge symmetry is
$SU(3)_c\times SU(2)_L\times U(1)_Y\times U(1)_X$. We explore one example in
which the gauge symmetries on the two branes are respectively $SU(5)\times
U(1)_X$ and $SU(4)_c\times SU(2)_L\times SU(2)_R$, and the MSSM gauge symmetry
is recovered by the usual Higgs mechanism. We discuss how fermion masses and
mixings can be understood in this framework by introducing a flavor $U(1)_F$
symmetry. Unification of the MSSM gauge couplings and proton stability are also
considered. An order of magnitude increase in sensitivity could reveal proton
decay.


  We demonstrate that chimera behavior can be observed in small networks
consisting of three identical oscillators, with mutual all-to-all coupling.
Three different types of chimeras, characterized by the coexistence of two
coherent oscillators and one incoherent oscillator (i.e. rotating with another
frequency) have been identified, where the oscillators show periodic (two
types) and chaotic (one type) behaviors. Typical bifurcations at the
transitions from full synchronization to chimera states and between different
types of chimeras have been described. Parameter regions for the chimera states
are obtained in the form of Arnold tongues, issued from a singular parameter
point. Our analysis suggests that chimera states can be observed in small
networks, relevant to various real-world systems.


  Most attempts to represent 3D shapes for deep learning have focused on
volumetric grids, multi-view images and point clouds. In this paper we look at
the most popular representation of 3D shapes in computer graphics - a
triangular mesh - and ask how it can be utilized within deep learning. The few
attempts to answer this question propose to adapt convolutions & pooling to
suit Convolutional Neural Networks (CNNs). This paper proposes a very different
approach, termed MeshWalker, to learn the shape directly from a given mesh. The
key idea is to represent the mesh by random walks along the surface, which
"explore" the mesh's geometry and topology. Each walk is organized as a list of
vertices, which in some manner imposes regularity on the mesh. The walk is fed
into a Recurrent Neural Network (RNN) that "remembers" the history of the walk.
We show that our approach achieves state-of-the-art results for two fundamental
shape analysis tasks: shape classification and semantic segmentation.
Furthermore, even a very small number of examples suffices for learning. This
is highly important, since large datasets of meshes are difficult to acquire.


  We concentrate on kinetic models for swarming with individuals interacting
through self-propelling and friction forces, alignment and noise. We assume
that the velocity of each individual relaxes to the mean velocity. In our
present case, the equilibria depend on the density and the orientation of the
mean velocity, whereas the mean speed is not anymore a free parameter and a
phase transition occurs in the homogeneous kinetic equation. We analyze the
profile of equilibria for general potentials identifying a family of potentials
leading to phase transitions. Finally, we derive the fluid equations when the
interaction frequency becomes very large.


  In muon scattering tomography, the investigated materials are discriminated
according to the scattering angle that mainly depends on the atomic number, the
density, and the thickness of the medium at a given energy value. The
scattering angles at different initial energies also provide the opportunity to
classify the incoming muons into a number of energy groups. In this study, by
employing the GEANT4 code, we show that the deflection angle exponentially
decays as a function of energy, and the numerical values for the current
configuration are below the detector accuracy except the initial energy bins
owing to the low-Z, low density, and low thickness of the current plastic
scintillators. This implies the necessity of additional components that provoke
the muon scattering. Therefore, we introduce stainless steel surfaces into the
top and bottom sections in order to amplify the deflection angle as well as to
reduce the uncertainty, thereby improving the detector performance.


  We study the determination of the top-quark mass using leptonic observables
in t-channel single top-quark production at the LHC. We demonstrate sensitivity
of transverse momentum of the charged lepton on the input top-quark mass. We
present predictions at next-to-next-to-leading order (NNLO) in QCD with narrow
width approximation and structure function approach. Further corrections due to
parton shower and hadronization, non-resonant and non-factorized contributions
are discussed. To reduce impact of SM backgrounds we propose to use the charge
weighted distribution for the measurement, i.e., differences between
distributions of charged lepton with positive and negative charges. By modeling
both signal and background processes, we found the projections for (HL-)LHC to
be promising, with a total theoretical uncertainty on the extracted top-quark
mass of about 1 $\sim$ 2 GeV.


  Let $C/\mathbb{Q}$ be a hyperelliptic curve with an affine model of the form
$y^2=x^p+a$. We explicitly determine the root number of the Jacobian of $C$,
with particular focus on the local root number at $p$ where $C$ has wild
ramification.


  The problem of signal detection using a flexible and general model is
considered. Due to applicability and flexibility of sparse signal
representation and approximation, it has attracted a lot of attention in many
signal processing areas. In this paper, we propose a new detection method based
on sparse decomposition in a union of subspaces (UoS) model. Our proposed
detector uses a dictionary that can be interpreted as a bank of matched
subspaces. This improves the performance of signal detection, as it is a
generalization for detectors. Low-rank assumption for the desired signals
implies that the representations of these signals in terms of some proper bases
would be sparse. Our proposed detector exploits sparsity in its decision rule.
We demonstrate the high efficiency of our method in the cases of voice activity
detection in speech processing.


  There is considerable evidence that action potentials are accompanied by
"intrinsic optical signals", such as a nanometer-scale motion of the cell
membrane. Here we present ChiSCAT, a technically simple imaging scheme that
detects such signals with interferometric sensitivity. ChiSCAT combines
illumination by a {\bf ch}aotic speckle pattern and interferometric scattering
microscopy ({\bf iSCAT}) to sensitively detect motion in any point and any
direction. The technique features reflective high-NA illumination, common-path
suppression of vibrations and a large field of view. This approach maximizes
sensitivity to motion, but does not produce a visually interpretable image. We
show that unsupervised learning based on matched filtering and motif discovery
can recover underlying motion patterns and detect action potentials. We
demonstrate these claims in an experiment on blebbistatin-paralyzed
cardiomyocytes. ChiSCAT promises to even work in scattering tissue, including a
living brain.


  The open radio access network (RAN) aims to bring openness and intelligence
to the traditional closed and proprietary RAN technology and offer flexibility,
performance improvement, and cost-efficiency in the RAN deployment and
operation. This paper provides a comprehensive survey of the open RAN
development. We briefly summarized the RAN evolution history and the
state-of-the-art technologies applied in open RAN. The open RAN-related
projects, activities, and standardization is then discussed. We then summarize
the challenges and future research directions required to support the open RAN.
Finally, we discuss some solutions to tackle these issues from the open
source's perspective.


  Let $F \in \mathbb{R}[x_1, \ldots, x_n]$ be a homogeneous form of degree $d >
1$ satisfying $(n - \dim V_{F}^*) > 4$, where $V_F^*$ is the singular locus of
$V(F) = \{ \mathbf{z} \in {\mathbb{C}}^n: F(\mathbf{z}) = 0 \}$. Suppose there
exists $\mathbf{x}_0 \in (0,1)^n \cap (V(F) \backslash V_F^*)$. Let $\mathbf{t}
= (t_1, \ldots, t_n) \in \mathbb{R}^n$. Then for a smooth function
$\varpi:\mathbb{R}^n \rightarrow \mathbb{R}$ with its support contained in a
small neighbourhood of $\mathbf{x}_0$, we prove $$ \Big{|} \int_{0}^{\infty}
\cdots \int_{0}^{\infty} \varpi(\mathbf{x}) x_1^{i t_1} \cdots x_n^{i t_n} e^{2
\pi i \tau F(\mathbf{x})} d \mathbf{x} \Big{|} \ll \min \{ 1, |\tau|^{-1} \},
$$ where the implicit constant is independent of $\tau$ and $\mathbf{t}$.


  We have entered an era where the importance of decentralized solutions has
become more obvious. Blockchain technology and its derivatives are distributed
ledger technologies that keep the registry of data between peers of a network.
This ledger is secured within a successive over looping cryptographic chain.
The accomplishment of the Bitcoin cryptocurrency proved that blockchain
technology and its derivatives could be used to eliminate intermediaries and
provide security for cyberspace. However, there are some challenges in the
implementation of blockchain technology. This chapter first explains the
concept of blockchain technology and the data that we can store therein. The
main advantage of blockchain is the security services that it provides. This
section continues by describing these services.. The challenges of blockchain;
blockchain anomalies, energy consumption, speed, scalability, interoperability,
privacy and cryptology in the age of quantum computing are described. Selected
solutions for these challenges are given. Remarkable derivatives of blockchain,
which use different solutions (directed acyclic graph, distributed hash table,
gossip consensus protocol) to solve some of these challenges are described.
Then the data storage in blockchain and evolving data solutions are explained.
The comparison of decentralized solutions with the lcentralized database
systems is given. A multi-platform interoperable scalable architecture (MPISA)
is proposed. In the conclusion we include the evolution assumptions of data
storage in a decentralized world.


  We derive the radiative transfer equation for arbitrary stationary
relativistic flows in stationary spacetimes, i.e. for steady-state transfer
problems. We show how the standard characteristics method of solution developed
by Mihalas and used throughout the radiative transfer community can be adapted
to multi-dimensional applications with isotropic sources. Because the
characteristics always coincide with geodesics and can always be specified by
constants, direct integration of the characteristics derived from the transfer
equation as commonly done in 1-D applications is not required. The
characteristics are known for a specified metric from the geodesics. We give
details in both flat and static spherically symmetric spacetimes. This work has
direct application in 3-dimensional simulations of supernovae, gamma-ray
bursts, and active galactic nuclei, as well as in modeling neutron star
atmospheres.


  The string corrections to the Riemann Curvature tensor are found to first
order in the string slope parameter, here proportional to $\g$. This is done
for D=10 supergravity, the presumed low energy limit of string theory. We
follow the perturbative approach. We also simplify a crucial result in our
previous solution.


  Let v be a rank m discrete valuation of k[[X1,...,Xn]] with dimension n-m. We
prove that there exists an inmediate extension L of K where the valuation is
monomial. Therefore we compute explicitly the residue field of the valuation.


  The SUperluminous Supernova Host galaxIES (SUSHIES) survey aims to provide
strong new constraints on the progenitors of superluminous supernovae (SLSNe)
by understanding the relationship to their host galaxies. We present the
photometric properties of 53 H-poor and 16 H-rich SLSN host galaxies out to
$z\sim4$. We model their spectral energy distributions to derive physical
properties, which we compare with other galaxy populations. At low redshift,
H-poor SLSNe are preferentially found in very blue, low-mass galaxies with high
average specific star-formation rates. As redshift increases, the host
population follows the general evolution of star-forming galaxies towards more
luminous galaxies. After accounting for secular evolution, we find evidence for
differential evolution in galaxy mass, but not in the $B$-band and the far UV
luminosity ($3\sigma$ confidence). Most remarkable is the scarcity of hosts
with stellar masses above $10^{10}~M_\odot$ for both classes of SLSNe. In the
case of H-poor SLSNe, we attribute this to a stifled production efficiency
above $\sim0.4$ solar metallicity. However, we argue that, in addition to low
metallicity, a short-lived stellar population is also required to regulate the
SLSN production. H-rich SLSNe are found in a very diverse population of
star-forming galaxies. Still, the scarcity of massive hosts suggests a stifled
production efficiency above $\sim0.8$ solar metallicity. The large dispersion
of the H-rich SLSNe host properties is in stark contrast to those of gamma-ray
burst, regular core-collapse SN, and H-poor SLSNe host galaxies. We propose
that multiple progenitor channels give rise to this sub-class.


  We discuss the Morse estimates for the curvature of several metrics on Semple
weighted projective bundle over a projective variety. Following Demailly works
on holomorphic Morse inequalities we show an analogue of his results along the
Green-Griffiths conjecture for invariant jets.


  We perform a complete analysis of $\Delta S=2$ processes in the kaon system
and evaluate $\Delta M_K$ and $\epsilon_K$ in the left-right supersymmetric
model. We include analytic expressions for the contributions of gluinos,
neutralinos and charginos. We obtain general constraints on off-diagonal mass
terms between the first two generations of both down-type and up-type squarks.
In the down-squark sector, we compare the results with gluino-only estimates.
In the up-squark sector, we find a complete set of bounds on all combinations
of chirality conserving or chirality flipping parameters. Finally, we comment
on the size of the bounds obtained by imposing left-right symmetry in the
squark sector.


  The head-on collision of identical neutron stars from rest at infinity
requires a numerical simulation in full general relativity for a complete
solution. Undaunted, we provide a relativistic, analytic argument to suggest
that during the collision, sufficient thermal pressure is always generated to
support the hot remnant in quasi-static stable equilibrium against collapse
prior to slow cooling via neutrino emission. Our conclusion is independent of
the total mass of the progenitors and holds even if the remnant greatly exceeds
the maximum mass of a cold neutron star.


  We study the impact of inherent mode coupling between clockwise (CW) and
counter-clockwise (CCW) modes on Kerr comb generation in a small
whispering-gallery mode microcavity. Our numerical analysis using a coupled
Lugiato-Lefever equation reveals the range of the coupling strength in which a
soliton pulse can be obtained in the CW direction. It also showed that CCW comb
power depends on the coupling strength between the CW and CCW modes. In
addition to the simulation, we conducted an experiment to confirm that the
power ratio between the CW and CCW comb modes depends on the coupling strength,
and the experimental results agree well with the simulation results. This study
helps us to understand the relationship between CW and CCW mode coupling and
Kerr comb generation, and the effect on soliton formation.


  Three-dimensional (3D) deep molecular generative models offer the advantage
of goal-directed generation based on 3D-dependent properties, such as binding
affinity for structure-based design within binding pockets. Traditional
benchmarks created to evaluate SMILES or molecular graphs generators, such as
GuacaMol or MOSES, are limited to evaluate 3D generators as they do not assess
the quality of the generated molecular conformation. In this work, we hence
developed GenBench3D, which implements a new benchmark for models producing
molecules within a binding pocket. Our main contribution is the Validity3D
metric, evaluating the conformation quality using the likelihood of bond
lengths and valence angles based on reference values observed in the Cambridge
Structural Database. The LiGAN, 3D-SBDD, Pocket2Mol, TargetDiff, DiffSBDD and
ResGen models were benchmarked. We show that only between 0% and 11% of
generated molecules have valid conformations. Performing local relaxation of
generated molecules in the pocket considerably improved the Validity3D for all
models by a minimum increase of 40%. For LiGAN, 3D-SBDD, or TargetDiff, the set
of valid relaxed molecules shows on average higher Vina score (i.e. worse) than
the set of raw generated molecules, indicating that the binding affinity of raw
generated molecules might be overestimated. Using the other scoring functions,
that give higher importance to ligand strain, only yield improved scores when
using valid relaxed molecules. Using valid relaxed molecules, TargetDiff and
Pocket2Mol show better median Vina, Glide and Gold PLP scores than other
models. We have publicly released GenBench3D on GitHub for broader use:
https://github.com/bbaillif/genbench3d


  We develop the theory of Hodge ideals for Q-divisors by means of log
resolutions, extending our previous work on reduced hypersurfaces. We prove
local (non-)triviality criteria and a global vanishing theorem, as well as
other analogues of standard results from the theory of multiplier ideals, and
we derive a new local vanishing theorem. The connection with the V-filtration
is analyzed in a sequel.


  For effective human-robot teaming, it is important for the robots to be able
to share their visual perception with the human operators. In a harsh remote
collaboration setting, data compression techniques such as autoencoder can be
utilized to obtain and transmit the data in terms of latent variables in a
compact form. In addition, to ensure real-time runtime performance even under
unstable environments, an anytime estimation approach is desired that can
reconstruct the full contents from incomplete information. In this context, we
propose a method for imputation of latent variables whose elements are
partially lost. To achieve the anytime property with only a few dimensions of
variables, exploiting prior information of the category-level is essential. A
prior distribution used in variational autoencoders is simply assumed to be
isotropic Gaussian regardless of the labels of each training datapoint. This
type of flattened prior makes it difficult to perform imputation from the
category-level distributions. We overcome this limitation by exploiting a
category-specific multi-modal prior distribution in the latent space. The
missing elements of the partially transferred data can be sampled, by finding a
specific modal according to the remaining elements. Since the method is
designed to use partial elements for anytime estimation, it can also be applied
for data over-compression. Based on the experiments on the ModelNet and
Pascal3D datasets, the proposed approach shows consistently superior
performance over autoencoder and variational autoencoder up to 70% data loss.


  This paper presents CARTOS, a charging-aware real-time operating system
designed to enhance the functionality of intermittently-powered batteryless
devices (IPDs) for various Internet of Things (IoT) applications. While IPDs
offer significant advantages such as extended lifespan and operability in
extreme environments, they pose unique challenges, including the need to ensure
forward progress of program execution amidst variable energy availability and
maintaining reliable real-time time behavior during power disruptions. To
address these challenges, CARTOS introduces a mixed-preemption scheduling model
that classifies tasks into computational and peripheral tasks, and ensures
their efficient and timely execution by adopting just-in-time checkpointing for
divisible computation tasks and uninterrupted execution for indivisible
peripheral tasks. CARTOS also supports processing chains of tasks with
precedence constraints and adapts its scheduling in response to environmental
changes to offer continuous execution under diverse conditions. CARTOS is
implemented with new APIs and components added to FreeRTOS but is designed for
portability to other embedded RTOSs. Through real hardware experiments and
simulations, CARTOS exhibits superior performance over state-of-the-art
methods, demonstrating that it can serve as a practical platform for developing
resilient, real-time sensing applications on IPDs.


  The slowdown of Moore's law and the power wall necessitates a shift towards
finely tunable precision (a.k.a. transprecision) computing to reduce energy
footprint. Hence, we need circuits capable of performing floating-point
operations on a wide range of precisions with high energy-proportionality. We
present FPnew, a highly configurable open-source transprecision floating-point
unit (TP-FPU) capable of supporting a wide range of standard and custom FP
formats. To demonstrate the flexibility and efficiency of FPnew in
general-purpose processor architectures, we extend the RISC-V ISA with
operations on half-precision, bfloat16, and an 8bit FP format, as well as SIMD
vectors and multi-format operations. Integrated into a 32-bit RISC-V core, our
TP-FPU can speed up execution of mixed-precision applications by 1.67x w.r.t.
an FP32 baseline, while maintaining end-to-end precision and reducing system
energy by 37%. We also integrate FPnew into a 64-bit RISC-V core, supporting
five FP formats on scalars or 2, 4, or 8-way SIMD vectors. For this core, we
measured the silicon manufactured in Globalfoundries 22FDX technology across a
wide voltage range from 0.45V to 1.2V. The unit achieves leading-edge measured
energy efficiencies between 178 Gflop/sW (on FP64) and 2.95 Tflop/sW (on 8-bit
mini-floats), and a performance between 3.2 Gflop/s and 25.3 Gflop/s.


  While Bayesian Optimization (BO) is a very popular method for optimizing
expensive black-box functions, it fails to leverage the experience of domain
experts. This causes BO to waste function evaluations on bad design choices
(e.g., machine learning hyperparameters) that the expert already knows to work
poorly. To address this issue, we introduce Bayesian Optimization with a Prior
for the Optimum (BOPrO). BOPrO allows users to inject their knowledge into the
optimization process in the form of priors about which parts of the input space
will yield the best performance, rather than BO's standard priors over
functions, which are much less intuitive for users. BOPrO then combines these
priors with BO's standard probabilistic model to form a pseudo-posterior used
to select which points to evaluate next. We show that BOPrO is around 6.67x
faster than state-of-the-art methods on a common suite of benchmarks, and
achieves a new state-of-the-art performance on a real-world hardware design
application. We also show that BOPrO converges faster even if the priors for
the optimum are not entirely accurate and that it robustly recovers from
misleading priors.


  We propose a simple and easy to implement neural network compression
algorithm that achieves results competitive with more complicated
state-of-the-art methods. The key idea is to modify the original optimization
problem by adding K independent Gaussian priors (corresponding to the k-means
objective) over the network parameters to achieve parameter quantization, as
well as an L1 penalty to achieve pruning. Unlike many existing
quantization-based methods, our method uses hard clustering assignments of
network parameters, which adds minimal change or overhead to standard network
training. We also demonstrate experimentally that tying neural network
parameters provides less gain in generalization performance than changing
network architecture and connectivity patterns entirely.


  The inhomogeneous distribution of matter in the non-linear regime of
galaxies, clusters of galaxies and voids is described by an exact, spherically
symmetric inhomogeneous solution of Einstein's gravitational field equations,
corresponding to an under-dense void. The solution becomes the homogeneous and
isotropic Einstein-de Sitter solution for a red shift $z > 10-20$, which
describes the matter dominated CMB data with small inhomogeneities. A spatial
volume averaging of physical quantities is introduced and the averaged time
evolution expansion parameter $\theta$ can give rise in the late-time universe
to a volume averaged deceleration parameter $<q>$ that is negative for a
positive matter density. This allows for a region of accelerated expansion
which does not require a cosmological constant. A negative deceleration
parameter can be derived by this volume averaging procedure from the
Lema\^{i}tre-Tolman-Bondi open void solution, which describes the late-time
non-linear regime associated with galaxies and under-dense voids and solves the
``coincidence'' problem.


  This expository note, written for the proceedings of ICCM 2023, presents
recent work [arXiv:2004.13894]. We particularly prove an Carleman estimate on
conic manifolds, using a multiple-weight Carleman argument.


  Ultra-wide triple black-holes (TBHs; with an outer orbit $>10^3$ AU) in the
field can be considerably perturbed by flyby encounters with field stars by the
excitation of the outer orbit eccentricities. We study the cumulative effect of
such flybys, and show them to be conductive for the production of
gravitational-wave (GW) sources. Flyby encounters with TBHs can turn the TBHs
unstable and follow chaotic evolution. This leads to a binary-single resonant
encounter between the outer BH and the inner-binary. These encounters can
result in either a prompt GW-merger of two of the TBH components during the
resonant phase, or the disruption of the TBH. In the latter case a more compact
binary is left behind, while the third BH escapes and is ejected. The compact
remnant binary may still inspiral through GW-emission, although on longer
timescales. A significant number of these would lead to a delayed GW-merger in
less than a Hubble time. We find a volumetric merger rate of $\sim3-10{\rm
Gpc^{-3}yr^{-1}}$ contributed by the (former) prompt-merger TBH channel and
$\sim100-250{\rm {\rm Gpc^{-3}yr^{-1}}}$ contributed by the (latter)
delayed-merger TBH channel. The prompt channel gives rise to eccentric mergers
in the aLIGO band, while the majority of the delayed-GW mergers are
circularized when enter the aLIGO band. We find the total {\rm eccentric}
volumetric merger rate to be $\sim1-10{\rm Gpc^{-3}yr^{-1}}$ from both
channels. We expect these mergers to show no significant spin-orbit alignment,
and uniform delay time distribution.


  Predicting future trajectories of surrounding agents is essential for
safety-critical autonomous driving. Most existing work focuses on predicting
marginal trajectories for each agent independently. However, it has rarely been
explored in predicting joint trajectories for interactive agents. In this work,
we propose Bi-level Future Fusion (BiFF) to explicitly capture future
interactions between interactive agents. Concretely, BiFF fuses the high-level
future intentions followed by low-level future behaviors. Then the
polyline-based coordinate is specifically designed for multi-agent prediction
to ensure data efficiency, frame robustness, and prediction accuracy.
Experiments show that BiFF achieves state-of-the-art performance on the
interactive prediction benchmark of Waymo Open Motion Dataset.


  Transport or kinetic equations are often derived assuming a quasi-particle
(on-shell) representation of the spectral function. We investigate this
assumption using a three-loop approximation of the 2PI effective action in real
time, without a gradient expansion or on-shell approximation. For a scalar
field in 1+1 dimensions the nonlinear evolution, including the integration over
memory kernels, can be solved numerically. We find that a spectral function
approximately described by a nonzero width emerges dynamically. During the
nonequilibrium time evolution the Wigner transformed spectral function is
slowly varying, even in presence of strong qualitative changes in the effective
particle distribution. These results may be used to make further analytical
progress towards a quantum Boltzmann equation including off-shell effects and a
nonzero width.


  In this paper a relation between iterated cyclings and iterated powers of
elements in a Garside group is shown. This yields a characterization of
elements in a Garside group having a rigid power, where 'rigid' means that the
left normal form changes only in the obvious way under cycling and decycling.
It is also shown that, given X in a Garside group, if some power X^m is
conjugate to a rigid element, then m can be bounded above by ||\Delta||^3. In
the particular case of braid groups, this implies that a pseudo-Anosov braid
has a small power whose ultra summit set consists of rigid elements. This
solves one of the problems in the way of a polynomial solution to the conjugacy
decision problem (CDP) and the conjugacy search problem (CSP) in braid groups.
In addition to proving the rigidity theorem, it will be shown how this paper
fits into the authors' program for finding a polynomial algorithm to the
CDP/CSP, and what remains to be done.


  We studied the changes in the electronic structure of V2O3 using a cluster
model. The calculations included fluctuations from the coherent band in the
metallic phase, and non-local Mott-Hubbard fluctuations in the insulating
phase. The incoherent structure is mostly related to the usual ligand screening
channel (3d2L). The coherent peak in the metallic phase corresponds to coherent
band fluctuations (3d2C). The non-local screened state in the insulating phase
(3d2D) appears at higher energies, opening the band gap. The photon energy
dependence of the spectra is mostly due to the relative V 3d and O 2p cross
sections. The present model reproduces also the observed changes in the V 1s
core-level spectra. The above results suggest that the Mott-Hubbard transition
in V2O3 requires a multi-band model.


  Concatenation of two quantum error correcting codes with complementary sets
of transversal gates can provide a means towards universal fault-tolerant
computation. We first show that it is generally preferable to choose the inner
code with the higher pseudo-threshold in order to achieve lower logical failure
rates. We then explore the threshold properties of a wide range of
concatenation schemes. Notably, we demonstrate that the concatenation of
complementary sets of Reed-Muller codes can increase the code capacity
threshold under depolarizing noise when compared to extensions of previously
proposed concatenation models. We also analyze the properties of logical errors
under circuit level noise, showing that smaller codes perform better for all
sampled physical error rates. Our work provides new insights into the
performance of universal concatenated quantum codes for both code capacity and
circuit level noise.


  Improved Phantom cell is a new scenario which has been introduced recently to
enhance the capacity of Heterogeneous Networks (HetNets). The main trait of
this scenario is that, besides maximizing the total network capacity in both
indoor and outdoor environments, it claims to reduce the handover number
compared to the conventional scenarios. In this paper, by a comprehensive
review of the Improved Phantom cells structure, an appropriate algorithm will
be introduced for the handover procedure of this scenario. To reduce the number
of handover in the proposed algorithm, various parameters such as the received
Signal to Interference plus Noise Ratio (SINR) at the user equipment (UE),
users access conditions to the phantom cells, and users staying time in the
target cell based on its velocity, has been considered. Theoretical analyses
and simulation results show that applying the suggested algorithm the improved
phantom cell structure has a much better performance than conventional HetNets
in terms of the number of handover.


  Globular clusters may host intermediate mass black holes (IMBHs) at their
centres. Here we propose a new method for their identification using
millisecond pulsars (MSPs) as probes. We show that measuring the first (jerk)
and second (jounce) derivatives of the accelerations of an ensemble of MSPs
will let us infer the presence of an IMBH in a globular cluster better than
measuring the sole accelerations. We test this concept by simulating a set of
star clusters with and without a central IMBH to extract the distributions of
the stellar jerks and jounces. We then apply this technique to the ensemble of
MSPs in the Galactic globular cluster 47 Tucanae. Current timing observations
are insufficient to constrain the presence of an IMBH and can only be used to
pose upper limits on its mass. But, with few more years of observations it will
be possible to test for the presence of a central IMBH with mass smaller than
$\sim$ 1000 M$_{\odot}$. We conclude that jerks and jounces help significantly
in reducing the upper limit of the mass of IMBHs in Galactic globular clusters.


  We report the results of density functional theory (DFT) based calculations
on monolayer and bilayer green phosphorene and their heterostructures with
MoSe2. Both monolayer and bilayer green phosphorene are direct band gap
semiconductors and possess anisotropic carrier mobility as high as 10^{4}
cm^{2}V^{-1}s^{-1}. In bilayers, pressure of about 9 GPa induces the
semiconductor-metal transition. Moreover, the band gap depends strongly on the
thickness of the films and the external electric field. By employing
strain-engineering under suitable solution conditions, monolayer and AC-stacked
bilayer green phosphorene offer the band edge alignments which can be used for
water splitting. The upper limit of the power conversion efficiencies for
monolayer, AB- and AC-stacked bilayer green phosphorene heterostructures with
MoSe_{2} is calculated to be 18-21 %. Our results show the possibility of green
phosphorene to be used as photocatalytic and photovoltaic material in the
energy-related applications.


  The recursion operators admitted by different operator Burgers equations, in
the framework of the study of nonlinear evolution equations, are here con-
sidered. Specifically, evolution equations wherein the unknown is an operator
acting on a Banach space are investigated. Here, the mirror non-Abelian Burgers
equation is considered: it can be written as $r_t = r_{xx} + 2r_x r$. The
structural properties of the admitted recursion operator are studied; thus, it
is proved to be a strong symmetry for the mirror non-Abelian Burgers equation
as well as to be the hereditary. These results are proved via direct
computations as well as via computer assisted manipulations; ad hoc routines
are needed to treat non-Abelian quantities and relations among them. The
obtained recursion operator generates the $mirror$ non-Abelian Burgers
hierarchy. The latter, when the unknown operator $r$ is replaced by a real
valued function reduces to the usual (commutative) Burgers hierarchy.
Accordingly, also the recursion operator reduces to the usual Burgers one.


  We calculate the momentum dependence of the $\rho-\omega$ mixing amplitude in
a purely hadronic model. The basic assumption of the model is that the mixing
amplitude is generated by $N{\bar{N}}$ loops and thus driven entirely by the
neutron-proton mass difference. The value of the amplitude at the
$\omega$-meson point is expressed in terms of only the $NN\omega$ and the
$NN\rho$ coupling constants. Using values for these couplings constrained by
empirical two-nucleon data we obtain a value for the mixing amplitude in
agreement with experiment. Extending these results to the spacelike region, we
find a $\rho-\omega$ contribution to the NN interaction that is strongly
suppressed and opposite in sign relative to the conventional contribution
obtained from using the constant on-shell value for the mixing amplitude.


  In this paper we study a gradient flow generated by the Landau-de Gennes free
energy that describes nematic liquid crystal configurations in the space of
$Q$-tensors. This free energy density functional is composed of three quadratic
terms as the elastic energy density part, and a singular potential in the bulk
part that is considered as a natural enforcement of a physical constraint on
the eigenvalues of $Q$. The system is a non-diagonal parabolic system with a
singular potential which trends to infinity logarithmically when the
eigenvalues of $Q$ approaches the physical boundary. We give a rigorous proof
that for rather general initial data with possibly infinite free energy, the
system has a unique strong solution after any positive time $t_0$. Furthermore,
this unique strong solution detaches from the physical boundary after a
sufficiently large time $T_0$. We also give estimate of the Hausdorff measure
of the set where the solution touches the physical boundary and thus prove a
partial regularity result of the solution in the intermediate stage $(0,T_0)$.


  Let $X$ be a locally compact Hausdorff space, let $A$ be a partially ordered
algebra, and let $\pi\colon \mathrm{C}_{\mathrm c}(X)\to A$ be a positive
algebra homomorphism. Under conditions on $A$ that are satisfied in a good
number of cases of practical interest, it is shown that $\pi$ is represented by
a unique regular spectral measure $\mu$ on the Borel $\sigma$-algebra of $X$,
taking its values in the positive idempotents in $A$. The measure $\mu$, which
is $\sigma$-additive in an ordered sense, represents $\pi$ via the order
integral (a generalisation of the Lebesgue integral) that goes back to J.D.M.
Wright and which was investigated earlier by the authors.
  The positive algebra homomorphism $\pi$ can be extended from
$\mathrm{C}_{\mathrm c}(X)$ to a positive linear map from the accompanying
$L^1$-space of $\mu$ into $A$. It is shown that, quite often, this $L^1$-space
is closed under multiplication, so that it is a vector lattice algebra, and
that the extended map from $L^1$ into $A$ is not only an algebra homomorphism
but, even when $A$ is not a vector lattice, also a vector lattice homomorphism
in a sense that is explained in the paper. When $ A$ has the countable sup
property, the image of $L^1$ (or of its positive cone) is described in terms of
consecutive ups and downs of the image of ${\mathrm C}_{\mathrm c}(X)$ (or of
its positive cone).
  The general results are applied in three different contexts, showing how
various spectral theorems have a common order-theoretical root: representations
on Banach lattices, on Hilbert spaces, and (the algebra need not consist of
operators) spectral theory for JBW-algebras.


  The Cherenkov Telescope Array (CTA) is the next generation of Imaging
Atmospheric Cherenkov Telescopes. It will reach a sensitivity and energy
resolution never obtained until now by any other high energy gamma-ray
experiment. Understanding the systematic uncertainties in general will be a
crucial issue for the performance of CTA. It is well known that atmospheric
conditions contribute particularly in this aspect.Within the CTA consortium
several groups are currently building Raman LIDARs to be installed on the two
sites. Raman LIDARs are devices composed of a powerful laser that shoots into
the atmosphere, a collector that gathers the backscattered light from molecules
and aerosols, a photo-sensor, an optical module that spectrally selects
wavelengths of interest, and a read--out system.Unlike currently used elastic
LIDARs, they can help reduce the systematic uncertainties of the molecular and
aerosol components of the atmosphere to <5% so that CTA can achieve its energy
resolution requirements of<10% uncertainty at 1 TeV.All the Raman LIDARs in
this work have design features that make them different than typical Raman
LIDARs used in atmospheric science and are characterized by large collecting
mirrors (2.5m2) and reduced acquisition time.They provide both multiple elastic
and Raman read-out channels and custom made optics design.In this paper, the
motivation for Raman LIDARs, the design and the status of advance of these
technologies are described.


  This note is intended to be a supplement to the bi-Lipschitz decomposition of
Lipschitz maps shown in [Sch]. We show that in the case of 1-Ahlfors-regular
sets, the condition of having `Big Pieces of bi-Lipschitz Images' (BPBI) is
equivalent to a Carleson condition.


  We investigate by numerical simulation and finite-size analysis the impact of
long-range shortcuts on a spatially embedded transportation network. Our
networks are built from two-dimensional ($d=2$) square lattices to be improved
by the addition of long-range shortcuts added with probability $P(r_{ij})\sim
r_{ij}^{-\alpha}$ [J. M. Kleinberg, Nature 406, 845 (2000)]. Considering those
improved networks, we performed numerical simulation of multiple discrete
package navigation and found a limit for the amount of packages flowing through
the network. Such limit is characterized by a critical probability of creating
packages $p_{c}$, where above this value a transition to a congested state
occurs. Moreover, $p_{c}$ is found to follow a power-law, $p_{c}\sim
L^{-\gamma}$, where $L$ is the network size. Our results indicate the presence
of an optimal value of $\alpha_{\rm min}\approx1.7$, where the parameter
$\gamma$ reaches its minimum value and the networks are more resilient to
congestion for larger system sizes.


  Relativistic quantum gravity with the action including terms quadratic in the
curvture tensor is analyzed. We derive new expressions for the corresponding
Lagrangian and the graviton propagator within dimensional regularization. We
argue that the considered model is a good candidate for the fundamental quantum
theory of gravitation.


  A methodology is proposed for freight traffic assignment in large-scale
road-rail intermodal networks. To obtain the user-equilibrium freight flows, a
path-based assignment algorithm (gradient projection) was proposed. The
developed methodology was tested on the U.S. intermodal network by using the
2007 freight demand for truck, rail, and road-rail intermodal from the Freight
Analysis Framework, Version 3 (FAF3). The results indicate that the proposed
methodology's projected flow pattern is similar to the FAF3 assignment. The
proposed methodology can be used by transportation planners and decision makers
to forecast freight flows and to evaluate strategic network expansion options.


  It is known that not only classical semantics but also intuitionistic Kripke
semantics can be generalized so that it can treat arbitrary propositional
connectives characterized by truth tables, or truth functions. In our previous
work, it has been shown that the set of Kripke-valid propositional sequents and
that of classically valid propositional sequents coincide if and only if all
available propositional connectives are monotonic. The present paper extend
this result to frst-order logic showing that, in the case of predicate logic,
the condition that all available propositional connectives are monotonic is a
necessary and sufficient condition for the set of sequents valid in all
constant domain Kripke models, not the set of Kripke-valid sequents, and the
set of classically valid sequents to coincide.


  Local binary descriptors are attracting increasingly attention due to their
great advantages in computational speed, which are able to achieve real-time
performance in numerous image/vision applications. Various methods have been
proposed to learn data-dependent binary descriptors. However, most existing
binary descriptors aim overly at computational simplicity at the expense of
significant information loss which causes ambiguity in similarity measure using
Hamming distance. In this paper, by considering multiple features might share
complementary information, we present a novel local binary descriptor, referred
as Ring-based Multi-Grouped Descriptor (RMGD), to successfully bridge the
performance gap between current binary and floated-point descriptors. Our
contributions are two-fold. Firstly, we introduce a new pooling configuration
based on spatial ring-region sampling, allowing for involving binary tests on
the full set of pairwise regions with different shapes, scales and distances.
This leads to a more meaningful description than existing methods which
normally apply a limited set of pooling configurations. Then, an extended
Adaboost is proposed for efficient bit selection by emphasizing high variance
and low correlation, achieving a highly compact representation. Secondly, the
RMGD is computed from multiple image properties where binary strings are
extracted. We cast multi-grouped features integration as rankSVM or sparse SVM
learning problem, so that different features can compensate strongly for each
other, which is the key to discriminativeness and robustness. The performance
of RMGD was evaluated on a number of publicly available benchmarks, where the
RMGD outperforms the state-of-the-art binary descriptors significantly.


  We report on updated precision predictions for total cross sections of
coloured supersymmetric particle production at the LHC with a centre-of-mass
energy of $\sqrt S$ = 13.6 TeV, computed with the modern PDF4LHC21 set. The
cross sections are calculated at an approximated NNLO accuracy in QCD and
contain corrections from the threshold resummation of soft-gluon emission up to
NNLL accuracy as well as Coulomb-gluon contributions including bound-state
terms. The corrections are found to increase the cross sections and reduce the
theoretical uncertainty as compared to the best available fixed-order
calculations. These predictions constitute the state-of-the-art calculations
and update the existing results for $\sqrt S$ = 13 TeV. We make our new results
publicly available in the version 2.0 update to the code package NNLL-fast.


  We apply the infinite time-evolving-block-decimation algorithm to calculate
the dynamical spin-structure factors of the quasi-one-dimensional (q1D) S=1
antiferromagnetic spin system with the single-ion anisotropy and the bond
alternation. We find that excitation continuum originating from magnons is
quantized, when the staggered field induced by the weak inter-chain interaction
is taken into account. The excitation energies of the quantized excitation
spectra are well explained by negative zeros of the Airy functions, when the
easy-axis anisotropy is strong and the ground state is located deep in the
N\'eel phase. This quantization of the magnon continuum is a counterpart of the
spinon confinement, which has been recently discussed in q1D S=1/2
antiferromagnets. We further show that, when the staggered field exists, the
quantized excitation spectra appear the phase boundary between the Haldane
phase and the N\'eel phase of the phase diagram without the staggered field.
However, the quantized excitation spectra disappear in the singlet dimer phase.


  In this paper, we demonstrate the applicability of the data-driven and
self-consistent solar energetic particle model, Solar-wind with FIeld-lines and
Energetic-particles (SOFIE), to simulate acceleration and transport processes
of solar energetic particles. SOFIE model is built upon the Space Weather
Modeling Framework (SWMF) developed at the University of Michigan. In SOFIE,
the background solar wind plasma in the solar corona and interplanetary space
is calculated by the Aflv\'en Wave Solar-atmosphere Model(-Realtime) (AWSoM-R)
driven by the near-real-time hourly updated Global Oscillation Network Group
(GONG) solar magnetograms. In the background solar wind, coronal mass ejections
(CMEs) are launched by placing an imbalanced magnetic flux rope on top of the
parent active region, using the Eruptive Event Generator using Gibson-Low model
(EEGGL). The acceleration and transport processes are modeled by the
Multiple-Field-Line Advection Model for Particle Acceleration (M-FLAMPA). In
this work, nine solar energetic particle events (Solar Heliospheric and
INterplanetary Environment (SHINE) challenge/campaign events) are modeled. The
three modules in SOFIE are validated and evaluated by comparing with
observations, including the steady-state background solar wind properties, the
white-light image of the CME, and the flux of solar energetic protons, at
energies of > 10 MeV.


  We study linear Batalin-Vilkovisky (BV) quantization, which is a derived and
shifted version of the Weyl quantization of symplectic vector spaces. Using a
variety of homotopical machinery, we implement this construction as a symmetric
monoidal functor of $\infty$-categories. We also show that this construction
has a number of pleasant properties: It has a natural extension to derived
algebraic geometry, it can be fed into the higher Morita category of
$E_n$-algebras to produce a "higher BV quantization" functor, and when
restricted to formal moduli problems, it behaves like a determinant. Along the
way we also use our machinery to give an algebraic construction of
$E_n$-enveloping algebras for shifted Lie algebras.


  Bauwens and Zimand [BZ 2019] have shown that lossless expanders have an
interesting online matching property. The result appears in an implicit form in
[BZ 2019]. We present an explicit version of this property which is directly
amenable to typical applications, prove it in a self-contained manner that
clarifies the role of some parameters, and give two applications.
  A $(K, \epsilon)$ lossless expander is a bipartite graph such that any subset
$S$ of size at most $K$ of nodes on the left side of the bipartition has at
least $(1-\epsilon) D |S|$ neighbors, where $D$ is the left degree.The main
result is that any such graph, after a slight modification, admits
$(1-O(\epsilon)D, 1)$ online matching up to size $K$. This means that for any
sequence $S=(x_1, \ldots, x_K)$ of nodes on the left side of the bipartition,
one can assign in an online manner to each node $x_i$ in $S$ a set $A_i$
consisting of $(1-O(\epsilon))$ fraction of its neighbors so that the sets
$A_1, \ldots, A_K$ are pairwise disjoint. "Online manner" refers to the fact
that, for every $i$, the set of nodes assigned to $x_i$ only depends on the
nodes assigned to $x_1, \ldots, x_{i-1}$.
  The first application concerns storage schemes for representing a set $S$, so
that a membership query "Is $x \in S$?" can be answered probabilistically by
reading a single bit. All the previous one-probe storage schemes were for a
static set $S$. We show that a lossless expander can be used to construct a
one-probe storage scheme for dynamic sets, i.e., sets in which elements can be
inserted and deleted without affecting the representation of other elements.
The second application is about non-blocking networks.


  The motivations for simulating QCD thermodynamics with Wilson fermions and a
twisted mass term are introduced. The twisted mass approach provides a natural
infrared cutoff and O(a) improvement at maximal twist, and can be extended to
finite temperature. Our strategy for exploring the QCD phase diagram at finite
temperature in this setup, while taking advantage of the results at T=0, is
explained. The first results for the order parameters and susceptibilities on a
16^3 x 8 lattice are presented. All dynamical simulations are carried out on
the apeNEXT facility in Rome.


  In this work, we study the propagation and absorption of plasma waves in the
context of the Maxwell-Carroll-Field-Jackiw (MCFJ) electrodynamics with a
purely spacelike background playing the role of the anomalous Hall
conductivity, concerning the anomalous Hall current. Such a current is also
found in an axion field which increases linearly with a space coordinate. The
Maxwell equations are rewritten for a cold, uniform, and collisionless fluid
plasma model, allowing us to determine the new refractive indices and
propagating modes. The analysis begins for propagation along the magnetic axis,
examined in the cases of chiral vectors parallel and orthogonal to the magnetic
field. Two distinct refractive indices (associated with right-handed circularly
polarized [RCP] and left-handed circularly polarized [LCP] waves) are obtained
and the associated propagation and absorption zones are determined. The
low-frequency regime is discussed and we obtain RCP and LCP helicons. We
scrutinize optical effects, such as birefringence and dichroism, and observe
rotatory power sign reversion, a property of chiral MCFJ plasmas. We also
examine the case of transversal propagation in the direction orthogonal to the
magnetic field, providing much more involved results.