  The identification of phases of matter is a challenging task, especially in
quantum mechanics, where the complexity of the ground state appears to grow
exponentially with the size of the system. We address this problem with
state-of-the-art deep learning techniques: adversarial domain adaptation. We
derive the phase diagram of the whole parameter space starting from a fixed and
known subspace using unsupervised learning. The input data set contains both
labeled and unlabeled data instances. The first kind is a system that admits an
accurate analytical or numerical solution, and one can recover its phase
diagram. The second type is the physical system with an unknown phase diagram.
Adversarial domain adaptation uses both types of data to create invariant
feature extracting layers in a deep learning architecture. Once these layers
are trained, we can attach an unsupervised learner to the network to find phase
transitions. We show the success of this technique by applying it on several
paradigmatic models: the Ising model with different temperatures, the
Bose-Hubbard model, and the SSH model with disorder. The input is the ground
state without any manual feature engineering, and the dimension of the
parameter space is unrestricted. The method finds unknown transitions
successfully and predicts transition points in close agreement with standard
methods. This study opens the door to the classification of physical systems
where the phases boundaries are complex such as the many-body localization
problem or the Bose glass phase.


  A quantum-field approach for describing many-particle Fermi systems at finite
temperatures and with spontaneously broken symmetry has been proposed. A
generalized model of self-consistent field (SCF), which allows one to describe
the states eligible for this system with various symmetries, is used as the
initial approximation. A perturbation theory has been developed, and a diagram
technique for temperature Green's functions (GFs) has been constructed. The
Dyson's equation for the self-energy and vertex parts has been deduced.


  Given graphs $G, H_1, H_2$, we write $G \rightarrow ({H}_1, H_2)$ if every
$\{$red, blue$\}$-coloring of the edges of $G$ contains a red copy of $H_1$ or
a blue copy of $H_2$. A non-complete graph $G$ is $(H_1, H_2)$-co-critical if
$G \nrightarrow ({H}_1, H_2)$, but $G+e\rightarrow ({H}_1, H_2)$ for every edge
$e$ in $\overline{G}$. Motivated by a conjecture of Hanson and Toft from 1987,
we study the minimum number of edges over all $(K_t, K_{1,k})$-co-critical
graphs on $n$ vertices. We prove that for all $t\ge3$ and $k\ge 3$, there
exists a constant $\ell(t, k)$ such that, for all $n \ge (t-1)k+1$, if $G$ is a
$(K_t, K_{1,k})$-co-critical graph on $n$ vertices, then $$ e(G)\ge
\left(2t-4+\frac{k-1}{2}\right)n-\ell(t, k).$$ Furthermore, this linear bound
is asymptotically best possible when $t\in\{3, 4,5\}$ and all $k\ge3$ and $n\ge
(2t-2)k+1$. It seems non-trivial to construct extremal $(K_t,
K_{1,k})$-co-critical graphs for $t\ge6$. We also obtain the sharp bound for
the size of $(K_3, K_{1,3})$-co-critical graphs on $n\ge13$ vertices by showing
that all such graphs have at least $3n-4$ edges.


  The cosmological equations suggested by the non-relativistic renormalizable
gravitational theory proposed by Ho\v{r}ava are considered. It is pointed out
that the early universe cosmology has features that may give an alternative to
inflation and the theory may be able to escape singularities.


  Color-octet contributions to quarkonia production at LEP are studied herein.
The short distance formation of heavy quark-antiquark pairs in color-octet
configurations via gluon fragmentation processes is significantly enhanced
relative to the creation of color-singlet pairs via heavy quark fragmentation.
But the subsequent long distance hadronization of these colored pairs into
physical quarkonium bound states is suppressed compared to the nonperturbative
evolution of their colorless counterparts. We find that the overall LEP rates
for gluon fragmentation into prompt Upsilon and Psi vector bosons exceed those
from heavy quark fragmentation. Inclusion of the dominant color-octet
quarkonium production channel eliminates sizable discrepancies between previous
predictions and recent measurements of prompt $Z \to \Jpsi+X$, $Z \to \psi'+X$
and $Z \to \Upsilon+X$ branching fractions.


  The quantum separability problem consists in deciding whether a bipartite
density matrix is entangled or separable. In this work, we propose a machine
learning pipeline for finding approximate solutions for this NP-hard problem in
large-scale scenarios. We provide an efficient Frank-Wolfe-based algorithm to
approximately seek the nearest separable density matrix and derive a systematic
way for labeling density matrices as separable or entangled, allowing us to
treat quantum separability as a classification problem. Our method is
applicable to any two-qudit mixed states. Numerical experiments with quantum
states of 3- and 7-dimensional qudits validate the efficiency of the proposed
procedure, and demonstrate that it scales up to thousands of density matrices
with a high quantum entanglement detection accuracy. This takes a step towards
benchmarking quantum separability to support the development of more powerful
entanglement detection techniques.


  Standard stellar evolution models predict that black holes in the range of
approximately $50 - 140 M_\odot$ should not exist directly from stellar
evolution. This gap appears because stars with masses between 100 and 240
$M_\odot$ are expected to undergo a pair instability supernova and leave behind
no remnant, or a pulsational pair instability supernova and leave behind a
remnant much smaller than their initial stellar mass. However, black holes have
been discovered by the LIGO/Virgo collaboration within this mass range. In
previous work (arXiv:2010.00254), we used the stellar evolution code MESA to
show that the addition of non-nuclear energy (such as from annihilation of dark
matter) could alter the evolution of a 180 $M_\odot$ star so that the observed
black holes could be produced from isolated stars. In this paper, we extend
this analysis to stars of other masses, and find that sufficient amounts of
non-nuclear energy can allow any star to avoid pair instability, and could
produce a black hole of mass comparable to the initial stellar mass. In
addition, we produce examples of the type of black hole initial mass function
that can be produced from this mechanism. These illustrative examples suggest
that adding non-nuclear energy to stars offers a way to fully close the mass
gap.


  We analyse the quantization procedure of the spinor field in the Rindler
spacetime, showing the boundary conditions that should be imposed to the field,
in order to have a well posed theory. We then investigate the relationship
between this construction and the usual one in Minkowski spacetime. This leads
to the concept of "Unruh effect", that is the thermal nature of the Minkowski
vacuum state from the point of view of an accelerated observer. It is
demostrated that the two constructions are qualitatively different and can not
be compared and consequently the conventional interpretation of the Unruh
effect is questionable.


  Alzheimer's disease (AD) is the most common cause of dementia. An early
detection is crucial for slowing down the disease and mitigating risks related
to the progression. While the combination of MRI and FDG-PET is the best
image-based tool for diagnosis, FDG-PET is not always available. The reliable
detection of Alzheimer's disease with only MRI could be beneficial, especially
in regions where FDG-PET might not be affordable for all patients. To this end,
we propose a multi-task method based on U-Net that takes T1-weighted MR images
as an input to generate synthetic FDG-PET images and classifies the dementia
progression of the patient into cognitive normal (CN), cognitive impairment
(MCI), and AD. The attention gates used in both task heads can visualize the
most relevant parts of the brain, guiding the examiner and adding
interpretability. Results show the successful generation of synthetic FDG-PET
images and a performance increase in disease classification over the naive
single-task baseline.


  We derive several expressions for the quantum Fisher information matrix
(QFIM) for the multi-parameter estimation of multi-mode Gaussian quantum
states, the corresponding symmetric logarithmic derivatives, and conditions for
saturability of the quantum Cram\'{e}r-Rao bound. This bound determines the
ultimate precision with which parameters encoded into quantum states can be
estimated. We include expressions for mixed states, for the case when the
Williamson decomposition of the covariance matrix is known, expressions in
terms of infinite series, and expressions for pure states. We also discuss
problematic behavior when some modes are pure, and present a method that allows
the use of expressions that are defined only for mixed states, to compute QFIM
for states with any number of pure modes.


  The article is devoted to the construction of explicit one-step strong
numerical methods with the orders 2.0 and 2.5 of convergence for Ito stochastic
differential equations with multidimensional non-commutative noise. We consider
the numerical methods based on the unified Taylor-Ito and Taylor-Stratonovich
expansions. For the numerical modeling of iterated Ito and Stratonovich
stochastic integrals of multiplicities 1 to 5 we apply the method of multiple
Fourier-Legendre series converging in the sense of norm in Hilbert space
$L_2([t, T]^k),$ $k=1,\ldots,5$. The article is addressed to engineers who use
numerical modeling in stochastic control and for solving the non-linear
filtering problem. The article will be interesting to scientists who working in
the field of numerical integration of stochastic differential equations.


  After the recent advancement of sequencing strategies, mirror repeats have
been found to be present in the gene sequence of many organisms and species.
This presence of mirror repeats in most of the sequences indicates towards some
important functional role of these repeats. However, a simple and quick
strategy to search these repeats in a given sequence is not available. We in
this manuscript have proposed a simple and swift strategy named as FPCB
strategy to identify mirror repeats in a give sequence. The strategy includes
three simple steps of downloading sequencing in FASTA format (F), making its
parallel complement (PC) and finally performing a homology search with the
original sequence (B). At least twenty genes were analyzed using the proposed
study. A number and types of mirror repeats were observed. We have also tried
to give nomenclature to these repeats. We hope that the proposed FPCB strategy
will be quite helpful for the identification of mirror repeats in DNA or mRNA
sequence. Also the strategy may help in unraveling the functional role of
mirror repeats in various processes including evolution.


  Sports are spontaneous generators of stories. Through skill and chance, the
script of each game is dynamically written in real time by players acting out
possible trajectories allowed by a sport's rules. By properly characterizing a
given sport's ecology of `game stories', we are able to capture the sport's
capacity for unfolding interesting narratives, in part by contrasting them with
random walks. Here, we explore the game story space afforded by a data set of
1,310 Australian Football League (AFL) score lines. We find that AFL games
exhibit a continuous spectrum of stories rather than distinct clusters. We show
how coarse-graining reveals identifiable motifs ranging from last minute
comeback wins to one-sided blowouts. Through an extensive comparison with
biased random walks, we show that real AFL games deliver a broader array of
motifs than null models, and we provide consequent insights into the narrative
appeal of real games.


  The degradation of sewer pipes poses significant economical, environmental
and health concerns. The maintenance of such assets requires structured plans
to perform inspections, which are more efficient when structural and
environmental features are considered along with the results of previous
inspection reports. The development of such plans requires degradation models
that can be based on statistical and machine learning methods. This work
proposes a methodology to assess their suitability to plan inspections
considering three dimensions: accuracy metrics, ability to produce long-term
degradation curves and explainability. Results suggest that although ensemble
models yield the highest accuracy, they are unable to infer the long-term
degradation of the pipes, whereas the Logistic Regression offers a slightly
less accurate model that is able to produce consistent degradation curves with
a high explainability. A use case is presented to demonstrate this methodology
and the efficiency of model-based planning compared to the current inspection
plan.


  The computation of determinants or their signs is the core procedure in many
important geometric algorithms, such as convex hull, volume and point location.
As the dimension of the computation space grows, a higher percentage of the
total computation time is consumed by these computations. In this paper we
study the sequences of determinants that appear in geometric algorithms. The
computation of a single determinant is accelerated by using the information
from the previous computations in that sequence.
  We propose two dynamic determinant algorithms with quadratic arithmetic
complexity when employed in convex hull and volume computations, and with
linear arithmetic complexity when used in point location problems. We implement
the proposed algorithms and perform an extensive experimental analysis. On one
hand, our analysis serves as a performance study of state-of-the-art
determinant algorithms and implementations. On the other hand, we demonstrate
the supremacy of our methods over state-of-the-art implementations of
determinant and geometric algorithms. Our experimental results include a 20 and
78 times speed-up in volume and point location computations in dimension 6 and
11 respectively.


  Recent results from HERA and TevaTron on precision tests of QCD with jets, W
and Z bosons and photons associated with jets and heavy flavours are presented.
The measurements were used to probe QCD at the highest energies, to provide
experimental constraints on SM processes that constitute background to new
physics, to extract values of the coupling of the strong interaction and to
constrain the proton parton distribution functions. The implications of the
results on LHC physics are discussed.


  We introduce an expressive probabilistic temporal epistemic logic PTEL
suitable to reason about uncertain knowledge of a non-rigid set of agents that
can be changed during time. We define semantics for PTEL as Kripke models with
epistemic accessibility relations for agents' knowledge, linear temporal
relations describing possible runs of the system, and probability functions
defined on sets of runs. We give an axiomatization of PTEL and sketch the proof
of strong completeness.


  The excitation spectrum of the t-J model is studied on a square lattice in
the large $N$ limit in a doping range where a $d$-$density$-$wave$ (DDW) forms
below a transition temperature $T^\star$. Characteristic features of the DDW
ground state are circulating currents which fluctuate above and condense into a
staggered flux state below $T^\star$ and density fluctuations where the
electron and the hole are localized at different sites. General expressions for
the density response are given both above and below $T^\star$ and applied to
Raman, X-ray, and neutron scattering. Numerical results show that the density
response is mainly collective in nature consisting of broad, dispersive
structures which transform into well-defined peaks mainly at small momentum
transfers. One way to detect these excitations is by inelastic neutron
scattering at small momentum transfers where the cross section (typically a few
per cents of that for spin scattering) is substantially enhanced, exhibits a
strong dependence on the direction of the transferred momentum and a
well-pronounced peak somewhat below twice the DDW gap. Scattering from the
DDW-induced Bragg peak is found to be weaker by two orders of magnitude
compared with the momentum-integrated inelastic part.


  We present an extension of the MSSM where the dominant decay channel of the
Higgs boson is a cascade decay into a four-gluon final state. In this model the
Higgs is a pseudo-Goldstone boson of a broken global symmetry SU(3)-> SU(2).
Both the global symmetry breaking and electroweak symmetry breaking are
radiatively induced. The global symmetry breaking pattern also implies the
existence of a light (few GeV) pseudo-Goldstone boson eta which is a singlet
under the standard model gauge group. The h -> eta eta branching fraction is
large, and typically dominates over the standard h -> b b decay. The dominant
decay of eta is into two gluons, while the decays to photons, taus or lighter
standard model flavors are suppressed at the level of 10^(-4) or more. With h->
4 jets as the dominant decay, the Higgs could be as light as 78 GeV without
being detected at LEP, while detection at the LHC is extremely challenging.
However many of the super- and global symmetry partners of the standard model
particles should be easily observable at the LHC. Furthermore, the LHC should
be able to observe a "wrong Higgs" that is a 300-400 GeV heavy Higgs-like
particle with suppressed couplings to W and Z that by itself does not account
for electroweak precision observables and the unitarity of WW scattering. At
the same time, the true Higgs is deeply buried in the QCD background.


  We adopt CUDA-capable Graphic Processing Units (GPUs) for Coulomb, Landau and
maximally Abelian gauge fixing in 3+1 dimensional SU(3) lattice gauge field
theories. The local overrelaxation algorithm is perfectly suited for highly
parallel architectures. Simulated annealing preconditioning strongly increases
the probability to reach the global maximum of the gauge functional. We give
performance results for single and double precision. To obtain our maximum
performance of ~300 GFlops on NVIDIA's GTX 580 a very fine grained degree of
parallelism is required due to the register limits of NVIDIA's Fermi GPUs: we
use eight threads per lattice site, i.e., one thread per SU(3) matrix that is
involved in the computation of a site update.


  Our simultaneous three-colour ($BVR$) polarimetric observations of the
low-mass black hole X-ray binary V404 Cyg show a small but statistically
significant change of polarization degree ($\Delta p \sim 1$ per cent) between
the outburst in June 2015 and the quiescence. The polarization of V404 Cyg in
the quiescent state agrees within the errors with that of the visually close
(1\farcs4) companion ($p_{R} = 7.3\pm 0.1$ per cent), indicating that it is
predominantly of interstellar origin. The polarization pattern of the
surrounding field stars supports this conclusion. From the observed variable
polarization during the outburst we show that polarization degree of the
intrinsic component peaks in the $V$-band, $p_{V} = 1.1\pm 0.1$ per cent, at
the polarization position angle of $\theta_{V}= -7\deg\pm 2\deg$, which is
consistent in all three passbands. We detect significant variations in the
position angle of the intrinsic polarization in $R$ band from $-30\deg$ to
$\sim 0\deg$ during the outburst peak. The observed wavelength dependence of
the intrinsic polarization does not support non-thermal synchrotron emission
from a jet as a plausible mechanism, but is in better agreement with the
combined effect of electron (Thomson) scattering and absorption in a flattened
plasma envelope or outflow surrounding the illuminating source. Alternatively,
the polarization signal can be produced by scattering of the disc radiation in
a mildly relativistic polar outflow. The position angle of the intrinsic
polarization, nearly parallel to the jet direction (i.e. perpendicular to the
accretion disc plane), is in agreement with these interpretations.


  In this article a group-theoretical aspect of the method of dimensional
reduction is presented. Then, on the base of symmetry analysis of an
anisotropic space geometrical description of dimensional reduction of equations
for vector massless field is given. Formula for calculating components of the
energy-momentum tensor from the variables of the field factor-equations is
derived.


We construct curves with many points over finite fields using the class group


  Based on a large spectroscopic sample of $\sim$ 4,300 RR Lyrae stars with
metallicity, systemic radial velocity and distance measurements, we present a
detailed analysis of the chemical and kinematic properties of the Galactic
halo. Using this sample, the metallicity distribution function (MDF) as a
function of $r$ and the velocity anisotropy parameter $\beta$ profiles (for
different metallicity populations) are derived for the stellar halo. Both the
chemical and kinematic results suggest that the Galactic halo is composed of
two distinct parts, the inner halo and outer halo. The cutoff radius ($\sim$ 30
kpc) is similar to the previous break radius found in the density distribution
of the stellar halo. We find that the inner part is dominated by a metal-rich
population with extremely radial anisotropy ($\beta \sim 0.9$). These features
are in accordance with those of ``{\it Gaia}-Enceladus-Sausage'' (GES) and we
attribute this inner halo component as being dominantly composed of stars
deposited from this ancient merged satellite. We find that GES probably has a
slightly negative metallicity gradient. The metal-poor populations in the inner
halo are characterized as a long-tail in MDF with an anisotropy of $\beta \sim
0.5$, which is similar to that of the outer part. The MDF for the outer halo is
very broad with several weak peaks and the value of $\beta$ is around 0.5 for
all metallicities.


  We consider all connected and simply connected 7-dimensional Lie groups whose
Lie algebras have nilradical $\g_{5,2} = \s \{X_1, X_2, X_3, X_4, X_5 \colon
[X_1, X_2] = X_4, [X_1, X_3] = X_5\}$ of Dixmier. First, we give a geometric
description of the maximal-dimensional orbits in the coadjoint representation
of all considered Lie groups. Next, we prove that, for each considered group,
the family of the generic coadjoint orbits forms a measurable foliation in the
sense of Connes. Finally, the topological classification of all these
foliations is also provided.


  Symbolic Mathematical tasks such as integration often require multiple
well-defined steps and understanding of sub-tasks to reach a solution. To
understand Transformers' abilities in such tasks in a fine-grained manner, we
deviate from traditional end-to-end settings, and explore a step-wise
polynomial simplification task. Polynomials can be written in a simple normal
form as a sum of monomials which are ordered in a lexicographic order. For a
polynomial which is not necessarily in this normal form, a sequence of
simplification steps is applied to reach the fully simplified (i.e., in the
normal form) polynomial. We propose a synthetic Polynomial dataset generation
algorithm that generates polynomials with unique proof steps. Through varying
coefficient configurations, input representation, proof granularity, and
extensive hyper-parameter tuning, we observe that Transformers consistently
struggle with numeric multiplication. We explore two ways to mitigate this:
Curriculum Learning and a Symbolic Calculator approach (where the numeric
operations are offloaded to a calculator). Both approaches provide significant
gains over the vanilla Transformers-based baseline.


  Many efforts have been dedicated to identifying restrictions on ontologies
expressed as tuple-generating dependencies (tgds), a.k.a. existential rules,
that lead to the decidability for the problem of answering ontology-mediated
queries (OMQs). This has given rise to three families of formalisms: guarded,
non-recursive, and sticky sets of tgds. In this work, we study the containment
problem for OMQs expressed in such formalisms, which is a key ingredient for
solving static analysis tasks associated with them. Our main contribution is
the development of specially tailored techniques for OMQ containment under the
classes of tgds stated above. This enables us to obtain sharp complexity bounds
for the problems at hand, which in turn allow us to delimitate its practical
applicability. We also apply our techniques to pinpoint the complexity of
problems associated with two emerging applications of OMQ containment:
distribution over components and UCQ rewritability of OMQs.


  The shortcomings of the popular Black-Scholes-Merton (BSM) model have led to
models which could more accurately model the behavior of the underlying assets
in energy markets, particularly in electricity and future oil prices. In this
paper we consider a class of regime switching time-changed Levy processes,
which builds upon the BSM model by incorporating jumps through a random clock,
as well as randomly varying parameters according to a two-state continuous-time
Markov chain. We implement pricing methods based on expansions of the
characteristic function as in \cite{Fourier}. Finally, we estimate the
parameters of the model by incorporating historic energy data and option quotes
using a variety of methods.


  We study the problem of empirical coordination subject to a fidelity
criterion for a general set-up. We prove a result which indicates a strong
connection between our framework and the framework of empirical coordination
developed in [1]. It turns out that when we design codes that achieve empirical
coordination according to a given distribution and subject to the fidelity
criterion, it is sufficient to consider codes that produce actions of the same
joint type for a class of types which is close enough to our desired
distribution is some sense.


  Modern GPUs support special protocols to exchange data directly across the
PCI Express bus. While these protocols could be used to reduce GPU data
transmission times, basically by avoiding staging to host memory, they require
specific hardware features which are not available on current generation
network adapters. In this paper we describe the architectural modifications
required to implement peer-to-peer access to NVIDIA Fermi- and Kepler-class
GPUs on an FPGA-based cluster interconnect. Besides, the current software
implementation, which integrates this feature by minimally extending the RDMA
programming model, is discussed, as well as some issues raised while employing
it in a higher level API like MPI. Finally, the current limits of the technique
are studied by analyzing the performance improvements on low-level benchmarks
and on two GPU-accelerated applications, showing when and how they seem to
benefit from the GPU peer-to-peer method.


  For a fixed family of $r$-uniform hypergraphs $\mathcal{F}$, the anti-Ramsey
number of $\mathcal{F}$, denoted by $ ar(n,r,\mathcal{F})$, is the minimum
number $c$ of colors such that for any edge-coloring of the complete
$r$-uniform hypergraph on $n$ vertices with at least $c$ colors, there is a
rainbow copy of some hypergraph in $\mathcal{F}$. Here, a rainbow hypergraph is
an edge-colored hypergraph with all edges colored differently. Let
$\mathcal{P}_k$ and $\mathcal{C}_k$ be the families of loose paths and loose
cycles with $k$ edges in an $r$-uniform hypergraph, respectively. In this
paper, we determine the exact values of $ ar(n,r,\mathcal{P}_k)$ and $
ar(n,r,\mathcal{C}_k)$ for all $k\geq 4$ and $r\geq 3$.


  We report on the discovery of Cepheids in the Virgo spiral galaxy NGC 4535,
based on observations made with the Wide Field and Planetary Camera 2 on board
the Hubble Space Telescope. NGC 4535 is one of 18 galaxies observed as a part
of The HST Key Project on the Extragalactic Distance Scale which aims to
measure the Hubble constant to 10% accuracy. NGC 4535 was observed over 13
epochs using the F555W filter, and over 9 epochs using the F814W filter. The
HST F555W and F814W data were transformed to the Johnson V and Kron-Cousins I
magnitude systems, respectively. Photometry was performed using two independent
programs, DoPHOT and DAOPHOT II/ALLFRAME.
  Period-luminosity relations in the V and I bands were constructed using 39
high-quality Cepheids present in our set of 50 variable candidates. We obtain a
distance modulus of 31.02+/-0.26 mag, corresponding to a distance of 16.0+/-1.9
Mpc. Our distance estimate is based on values of mu = 18.50 +/- 0.10 mag and
E(V-I) = 0.13 mag for the distance modulus and reddening of the LMC,
respectively.


  The nuclear electric polarizability is theoretically analyzed using a sum
rule derived from the longitudinal part of the forward Compton amplitude.
Beyond the leading dipole contribution, this approach leads to the presence of
potential-dependent terms that do not show up in previous analyses. The
significance of these new contributions is illustrated by performing an
explicit calculation for a proton-neutron system interacting via a separable
potential.


  With the rapid development of the Internet of Things, there are many
interacting devices and applications. One crucial challenge is how to provide
security. Our proposal for a new direction is to create "smart buttons" and
collections of them called "smart blankets" as hardware/software security
patches rather than software-only patches.


  The discovery of the topological nature of free-space light and its quantum
chiral behavior has recently raised large attention. This important scientific
endeavor features spin-based integrated quantum technologies. Herein, we
discuss a novel phenomenon based on a resonantly-enhanced quantum spin-Hall
transport of light observed in a dielectric resonator operating near the
bound-state-in-continuum (BIC) regime. The BIC mode is characterized by a
transverse photonic spin angular momentum density extended on a macroscopic
area. As such, the experimental excited mode in near-BIC regime generates
resonant surface waves characterized by spin-momentum locking and that
propagate along the symmetry axes of the structure. In addition, the generated
side waves are interpreted as an abrupt nonparaxial redirection of the exciting
far field light, which is responsible for the spin-to-orbital angular momentum
conversion evidenced in the spin-orbit asymmetry measured in the intensity of
the side waves. The experimental results are in excellent agreement with a
model that combines geometric parallel transport of light polarization and
spin-momentum locking. In addition, breaking the excitation symmetry leads to a
total spin-directive coupling. Our results reveal the possibility of a
BIC-enhanced macroscopic spin-directive coupling, a novel fundamental mechanism
of light-spin manipulation that will have strong impact on emerging quantum
technologies.


  One of the greatest challenges of theoretical physics today is to unveil the
quantum information theory concerning what happens when one bit of information
enters the black hole (BH) horizon. The Landauer principle showed that a
certain amount of energy is generated when one-bit of information is erased as
it enters the event horizon system. In this paper we used the recently
developed Barrow BH model to calculate the addition to the area of the event
horizon of his toy model by using the Landauer concept. Besides we make this
computation considering $\Delta$ as a constant and a variable parameter. We
formulate the Barrow parameter ($\Delta$) as a function of the energy/mass,
which is new in the Barrow BH literature. We will investigate the differences
between the Bekenstein-Hawking entropy ($\Delta=0$) and the fractal
($\Delta=1$) cases concerning the addition in the area of the BH. The
asymptotical analysis is also mentioned and we will see that it affects only
the fractal case. All the results accomplished here are new concerning BHs in
general and the Barrow model literature in particular.


  There are strong suggestions that the disk-like accretion flow onto massive
black hole in AGN is disrupted in its innermost part (10-100 Rg), possibly due
to the radiation pressure instability. It may form a hot optically thin quasi
spherical (ADAF) flow surrounded by or containing denser clouds due to the
disruption of the disk. Such clouds might be optically thick, with a Thompson
depth of order of 10 or more. Within the frame of this cloud scenario
(Collin-Souffrin et al. 1996, Czerny & Dumont 1998), obscuration events are
expected and the effect would be seen as a variability. We consider expected
random variability due to statistical dispersion in location of clouds along
the line of sight for a constant covering factor. We discuss a simple
analytical toy model which provides us with the estimates of the mean spectral
properties and variability amplitude of AGN, and we support them with radiative
transfer computations done with the use of TITAN code of Dumont, Abrassart &
Collin (1999) and NOAR code of Abrassart (1999).


  Distant luminous quasars provide important information on the growth of the
first supermassive black holes, their host galaxies and the epoch of
reionization. The identification of quasars is usually performed through
detection of their Lyman-$\alpha$ line redshifted to $\sim$ 0.9 microns at
z>6.5. Here, we report the discovery of a very Lyman-$\alpha$ luminous quasar,
PSO J006.1240+39.2219 at redshift z=6.618, selected based on its red colour and
multi-epoch detection of the Lyman-$\alpha$ emission in a single near-infrared
band. The Lyman-$\alpha$-line luminosity of PSO J006.1240+39.2219 is unusually
high and estimated to be 0.8$\times$10$^{12}$ Solar luminosities (about 3% of
the total quasar luminosity). The Lyman-$\alpha$ emission of PSO
J006.1240+39.2219 shows fast variability on timescales of days in the quasar
rest frame, which has never been detected in any of the known high-redshift
quasars. The high luminosity of the Lyman-$\alpha$ line, its narrow width and
fast variability resemble properties of local Narrow-Line Seyfert 1 galaxies
which suggests that the quasar is likely at the active phase of the black hole
growth accreting close or even beyond the Eddington limit.


  This report provides a first design for H2+ accelerators as the DAEdALUS
neutrino sources. A description of all aspects of the system, from the ion
source to the extracted beam, is provided. The analysis provides a first proof
of principle of a full cyclotron system which can provide the necessary beam
power for the CP violation search proposed by the DAEdALUS Collaboration.


  We introduce the notion of a logical model category which is a Quillen model
category satisfying some additional conditions. Those conditions provide enough
expressive power that one can soundly interpret dependent products and sums in
it. On the other hand, those conditions are easy to check and provide a wide
class of models some of which are listed in the paper.


  We introduce an idempotent analogue of the exterior algebra for which the
theory of tropical linear spaces (and valuated matroids) can be seen in close
analogy with the classical Grassmann algebra formalism for linear spaces. The
top wedge power of a tropical linear space is its Plucker vector, which we view
as a tensor, and a tropical linear space is recovered from its Plucker vector
as the kernel of the corresponding wedge multiplication map. We prove that an
arbitrary d-tensor satisfies the tropical Plucker relations (valuated exchange
axiom) if and only if the d-th wedge power of the kernel of
wedge-multiplication is free of rank one. This provides a new cryptomorphism
for valuated matroids, including ordinary matroids as a special case.


  As artificial intelligence systems grow more powerful, there has been
increasing interest in "AI safety" research to address emerging and future
risks. However, the field of AI safety remains poorly defined and
inconsistently measured, leading to confusion about how researchers can
contribute. This lack of clarity is compounded by the unclear relationship
between AI safety benchmarks and upstream general capabilities (e.g., general
knowledge and reasoning). To address these issues, we conduct a comprehensive
meta-analysis of AI safety benchmarks, empirically analyzing their correlation
with general capabilities across dozens of models and providing a survey of
existing directions in AI safety. Our findings reveal that many safety
benchmarks highly correlate with upstream model capabilities, potentially
enabling "safetywashing" -- where capability improvements are misrepresented as
safety advancements. Based on these findings, we propose an empirical
foundation for developing more meaningful safety metrics and define AI safety
in a machine learning research context as a set of clearly delineated research
goals that are empirically separable from generic capabilities advancements. In
doing so, we aim to provide a more rigorous framework for AI safety research,
advancing the science of safety evaluations and clarifying the path towards
measurable progress.


  The lack of power anomaly is an unexpected feature observed at large angular
scales in the CMB maps by the COBE, WMAP and Planck satellites. This signature,
which consists in a missing of power with respect to that predicted by the
$\Lambda$CDM model, might hint at a new cosmological phase before the standard
inflationary era. The main point of this paper is taking the latest Planck
polarisation data into account to investigate how CMB polarisation improves the
understanding of this feature. With this aim, we apply to the last Planck data,
both PR3 (2018) and PR4 (2020) releases, a new class of estimators able to
evaluate this anomaly considering temperature and polarisation data both
separately and in a jointly way. This is the first time that the PR4 dataset is
used to study this anomaly. In order to critically evaluate this feature,
taking into account the residuals of known systematic effects present in the
Planck datasets, we analyse the cleaned CMB maps using different combinations
of sky masks, harmonic range and binning on the CMB multipoles. Our analysis
shows that the estimator based only on temperature data confirms the presence
of a lack of power with a lower-tail-probability (LTP), depending on the
component separation method, $\leq 0.33\%$ and $\leq 1.76\%$, for PR3 and PR4
respectively. To our knowledge the $LTP \leq 0.33\%$ for the PR3 dataset is the
lowest one present in the literature obtained from Planck 2018 data considering
the Planck confidence mask. We find significant differences between these two
datasets when polarisation is taken into account. However, we also show that
for the PR3 dataset the inclusion of the subdominant polarisation information
provides estimates which are less likely accepted in a $\Lambda$CDM
cosmological model than the only-temperature analysis on the whole
harmonic-range considered.


  Despite the huge improvements guaranteed by future GRAVITY observations of
the S0-2 star, these will not be able to unveil the fundamental nature, whether
black hole or wormhole, of the central supermassive object. Nevertheless,
observing stars orbiting closer to the central gravitational source could allow
to distinguish between the black hole and wormhole nature of this object at
more than 5$\sigma$. Firstly, we have used publicly available astrometric and
spectroscopic measurements of the S0-2 star to constrain the metric around the
supermassive object without finding any evidence either favouring or ruling out
the wormhole nature. Secondly, we have designed a mock catalogue of future
observations of the S0-2 star mirroring the accuracy and precision of GRAVITY.
Afterwards, we firstly tested our methodology showing that our procedure
recovers the input model, and subsequently we demonstrated that the
constraining power of such a dataset is not enough to distinguish between black
hole and wormhole. Finally, we built some toy models representing stars
orbiting much closer the central object than S0-2. We used these toy models to
investigate which are the ideal orbital features and observational strategies
to achieve our aim of unveiling the fundamental nature of the central
supermassive object, demonstrating that a star with a period of the order of
$\sim 5$ years and a pericentre distance of $\sim 5$ AU could identify the
nature of the central object at almost 5$\sigma$ accuracy.


  I present a dynamical analysis of the measured redshifts and distances of 64
dwarf galaxies at distances between 50 kpc and 2.6 Mpc. These dwarfs are
assumed to move as test particles in the gravitational field of 12 massive
actors---galaxies and groups of galaxies---under the mixed boundary conditions
imposed by cosmology. The model fits most of the measured dwarf distances and
redshifts. But more work, perhaps on the gravitational interaction among dwarf
galaxies, is required to account for the motions of six galaxies in the NGC
3109 association and two in the DDO 210 association. The sample of dwarfs is
large enough to constrain the halo mass run in the Milky Way. The evidence
points to a sharper break from a nearly flat inner rotation curve than
predicted by the NFW profile.


  The ANTARES detector is an undersea neutrino telescope in the Mediterranean
Sea. The search for point-like neutrino sources is one of the main goals of the
ANTARES telescope, requiring a reliable method to evaluate the detector angular
resolution and pointing accuracy. This work describes the study of the Sun
"shadow" effect with the ANTARES detector. The shadow is the deficit in the
atmospheric muon flux in the direction of the Sun caused by the absorption of
the primary cosmic rays. This analysis is based on the data collected between
2008 and 2017 by the ANTARES telescope. The observed statistical significance
of the Sun shadow detection is $3.7\sigma$, with an estimated angular
resolution of $0.59^\circ\pm0.10^\circ$ for downward-going muons. The pointing
accuracy is found to be consistent with the expectations and no evidence of
systematic pointing shifts is observed.


  In this paper, we investigate constant breadth curves on a surface according
to Darboux frame and give some characterizations of these curves.


  Deciding the existence of an $l\times m\times n$ integer threeway table with
given line-sums is NP-complete already for fixed $l=3$, but is in P with both
$l,m$ fixed. Here we consider {\em huge} tables, where the variable dimension
$n$ is encoded in {\em binary}. Combining recent results on integer cones and
Graver bases, we show that if the number of {\em layer types} is fixed, then
the problem is in P, whereas if it is variable, then the problem is in NP
intersect coNP. Our treatment goes through the more general class of $n$-fold
integer programming problems.


  In recent years it has been realized that in string/$M$ theories compactified
to four dimensions which satisfy cosmological constraints, it is possible to
make some generic predictions for particle physics and dark matter: a
non-thermal cosmological history before primordial nucleosynthesis, a scale of
supersymmetry breaking which is "high" as in gravity mediation, scalar
superpartners too heavy to be produced at the LHC (although gluino production
is expected in many cases), and a significant fraction of dark matter in the
form of axions. When the matter and gauge spectrum below the compactification
scale is that of the MSSM, a robust prediction of about 125 GeV for the Higgs
boson mass, predictions for various aspects of dark matter physics, as well as
predictions for future precision measurements, can be made. As a prototypical
example, $M$ theory compactified on a manifold of $G_2$ holonomy leads to a
good candidate for our "string vacuum", with the TeV scale emerging from the
Planck scale, a de Sitter vacuum, robust electroweak symmetry breaking, and
solutions of the weak and strong CP problems. In this article we review how
these and other results were derived, from the key theoretical ideas to the
final phenomenological predictions.


  Semantic reasoning and dynamic planning capabilities are crucial for an
autonomous agent to perform complex navigation tasks in unknown environments.
It requires a large amount of common-sense knowledge, that humans possess, to
succeed in these tasks. We present SayNav, a new approach that leverages human
knowledge from Large Language Models (LLMs) for efficient generalization to
complex navigation tasks in unknown large-scale environments. SayNav uses a
novel grounding mechanism, that incrementally builds a 3D scene graph of the
explored environment as inputs to LLMs, for generating feasible and
contextually appropriate high-level plans for navigation. The LLM-generated
plan is then executed by a pre-trained low-level planner, that treats each
planned step as a short-distance point-goal navigation sub-task. SayNav
dynamically generates step-by-step instructions during navigation and
continuously refines future steps based on newly perceived information. We
evaluate SayNav on multi-object navigation (MultiON) task, that requires the
agent to utilize a massive amount of human knowledge to efficiently search
multiple different objects in an unknown environment. We also introduce a
benchmark dataset for MultiON task employing ProcTHOR framework that provides
large photo-realistic indoor environments with variety of objects. SayNav
achieves state-of-the-art results and even outperforms an oracle based baseline
with strong ground-truth assumptions by more than 8% in terms of success rate,
highlighting its ability to generate dynamic plans for successfully locating
objects in large-scale new environments. The code, benchmark dataset and
demonstration videos are accessible at
https://www.sri.com/ics/computer-vision/saynav.


  The compound 2-mercaptobenzothizaole (MBT) has been frequently detected in
wastewater and surface water and is a potential threat to both aquatic
organisms and human health (its mutagenic potential has been demonstrated).
This study investigated the degradation routes of MBT in the anode of a
microbial electrolysis cell (MEC) and the involved microbial communities. The
results indicated that graphene-modified anodes promoted the presence of more
enriched, developed, and specific communities compared to bare anodes.
Moreover, consecutive additions of the OH substituent to the benzene ring of
MBT were only detected in the reactor equipped with the graphene-treated
electrode. Both phenomena, together with the application of an external
voltage, may be related to the larger reduction of biotoxicity observed in the
MEC equipped with graphene-modified anodes (46.2 eqtox/m3 to 27.9 eqtox/m3).


  We consider inference for the mean and covariance functions of covariate
adjusted functional data using Local Linear Kernel (LLK) estimators. By means
of a double asymptotic, we differentiate between sparse and dense covariate
adjusted functional data - depending on the relative order of m (the
discretization points per function) and n (the number of functions). Our
simulation results demonstrate that the existing asymptotic normality results
can lead to severely misleading inferences in finite samples. We explain this
phenomenon based on our theoretical results and propose finite-sample
corrections which provide practically useful approximations for inference in
sparse and dense data scenarios. The relevance of our theoretical results is
showcased using a real-data application.


  Previous observations have shown that the $\lesssim$10 au, $\gtrsim$400 K hot
inner disk of the archetypal accretion outburst young stellar object, FU Ori,
is dominated by viscous heating. To constrain dust properties in this region,
we have performed radio observations toward this disk using the Karl G. Jansky
Very Large Array (JVLA) in 2020 June-July, September, and November. We also
performed complementary optical photometric monitoring observations. We found
that the dust thermal emission from the hot inner disk mid-plane of FU Ori has
been approximately stationary and the maximum dust grain size is $\gtrsim$1.6
mm in this region. If the hot inner disk of FU Ori which is inward of the
150-170 K water snowline is turbulent (e.g., corresponding to a Sunyaev &
Shakura viscous $\alpha_{t}\gtrsim$0.1), or if the actual maximum grain size is
still larger than the lower limit we presently constrain, then as suggested by
the recent analytical calculations and the laboratory measurements, water-ice
free dust grains may be stickier than water-ice coated dust grains in
protoplanetary disks. Additionally, we find that the free-free emission and the
Johnson B and V bands magnitudes of these binary stars are brightening in
2016-2020. The optical and radio variability might be related to the
dynamically evolving protostellar or disk accretion activities. Our results
highlight that hot inner disks of outbursting objects are important
laboratories for testing models of dust grain growth. Given the active nature
of such systems, to robustly diagnose the maximum dust grain sizes, it is
important to carry out coordinated multi-wavelength radio observations.


  We consider the slight variation of the adversarial queuing theory model, in
which an adversary injects packets with routes into the network subject to the
following constraint: For any link $e$, the total number of packets injected in
any time window $[t,t')$ and whose route contains $e$, is at most
$\rho(t'-t)+\sigma$, where $\rho$ and $\sigma$ are non-negative parameters.
Informally, $\rho$ bounds the long-term rate of injections and $\sigma$ bounds
the "burstiness" of injection: $\sigma=0$ means that the injection is as smooth
as it can be.
  It is known that greedy scheduling of the packets (under which a link is not
idle if there is any packet ready to be sent over it) may result in $\Omega(n)$
buffer size even on an $n$-line network and very smooth injections
($\sigma=0$). In this paper we propose a simple non-greedy scheduling policy
and show that, in a tree where all packets are destined at the root, no buffer
needs to be larger than $\sigma+2\rho$ to ensure that no overflows occur, which
is optimal in our model. The rule of our algorithm is to forward a packet only
if its next buffer is completely empty. The policy is centralized: in a single
step, a long "train" of packets may progress together. We show that in some
sense central coordination is required, by presenting an injection pattern with
$\sigma=0$ for the $n$-node line that results in $\Omega(n)$ packets in a
buffer if local control is used, even for the more sophisticated "downhill"
algorithm, which forwards a packet only if its next buffer is less occupied
than its current one.


  Safe lock-free memory reclamation is a difficult problem. Existing solutions
follow three basic methods (or their combinations): epoch based reclamation,
hazard pointers, and optimistic reclamation. Epoch-based methods are fast, but
do not guarantee lock-freedom. Hazard pointer solutions are lock-free but
typically do not provide high performance. Optimistic methods are lock-free and
fast, but previous optimistic methods did not go all the way. While reads were
executed optimistically, writes were protected by hazard pointers. In this work
we present a new reclamation scheme called version based reclamation (VBR),
which provides a full optimistic solution to lock-free memory reclamation,
obtaining lock-freedom and high efficiency. Speculative execution is known as a
fundamental tool for improving performance in various areas of computer
science, and indeed evaluation with a lock-free linked-list, hash-table and
skip-list shows that VBR outperforms state-of-the-art existing solutions.


  We report an experimental refinement of the local charge density at the Si
(111) 7x7 surface utilizing a combination of x-ray and high energy electron
diffraction. By perturbing about a bond-centered pseudoatom model, we find
experimentally that the adatoms are in an anti-bonding state with the atoms
directly below. We are also able to experimentally refine a charge transfer of
0.26(4) e- from each adatom site to the underlying layers. These results are
compared with a full-potential all-electron density functional DFT calculation.


  We investigate base change and automorphic induction $\mathbb{C}/\mathbb{R}$
at the level of K-theory for the general linear group $GL_n(\mathbb{R})$. In
the course of this study, we compute in detail the C*-algebra K-theory of this
disconnected group. We investigate the interaction of base change with the
Baum-Connes correspondence for $GL_n(\mathbb{R})$ and $GL_n(\mathbb{C})$. This
article is the archimedean companion of our previous article in the Journal of
Noncommutative Geometry.


  This preprint contains the English translation of the paper "Relaxation
dynamics of a quantum chain of harmonic oscillators", which was published by
the author in 1980 in the Ukrainian Physical Journal. Comments describing its
motivations, background ideas and results are presented as well. This paper
addressed to the problem of approach to the thermal equilibrium in an isolated
macroscopic quantum system, which was studied on the example of the quantum
chain of weakly interacting harmonic oscillators. In the initial state,
macroscopic energy was supplied to one oscillator (atom) in the chain.
Subsequent evolution of the quantum state of the whole chain was determined due
to the model integrability. The main subject of interest was the time evolution
of the reduced density operators characterizing the quantum state of a
particular atom. On the short time-scale, the energy perturbation expands along
the chain with the velocity of the fastest phonon mode. On the long-time scale,
the single-atom density operators display strong fluctuations around the
canonical Gibbs distribution. These fluctuations are caused by the degeneracy
of the energy level differences (presence of resonances) in the model of
coupled harmonic oscillators. After lifting this degeneracy, fluctuations are
suppressed providing, that the reduced density operator of each atom in the
chain becomes very close to the Gibbs distribution at almost any time moment.


  Contribution from new gauge bosons in the 3 - 3 - 1 models to the anomalous
magnetic moment of the muon, mass difference of the kaon system and rare kaon
decay are calculated and numerically estimated. Bounds on masses of new gauge
bosons: bileptons and Z' are derived.


  In the present paper, an expansion of the transition density of Hyperbolic
Brownian motion with drift is given, which is potentially useful for pricing
and hedging of options under stochastic volatility models. We work on a
condition on the drift which dramatically simplifies the proof.


  We present extensive radio and X-ray observations of the nearby Type Ic SN
2007gr in NGC 1058 obtained with the Very Large Array and the Chandra X-ray
Observatory and spanning 5 to 150 days after explosion. Through our detailed
modeling of these data, we estimate the properties of the blastwave and the
circumstellar environment. We find evidence for a freely-expanding and
non-relativistic explosion with an average blastwave velocity, v~0.2c, and a
total internal energy for the radio emitting material of E ~ 2 x 10^46 erg
assuming equipartition of energy between electrons and magnetic fields
(epsilon_e=epsilon_B=0.1). The temporal and spectral evolution of the radio
emission points to a stellar wind-blown environment shaped by a steady
progenitor mass loss rate of Mdot ~ 6 x 10^-7 solar masses per year (wind
velocity, v_w=10^3 km/s). These parameters are fully consistent with those
inferred for other SNe Ibc and are in line with the expectations for an
ordinary, homologous SN explosion. Our results are at odds with those of Paragi
et al. (2010) who recently reported evidence for a relativistic blastwave in SN
2007gr based on their claim that the radio emission was resolved away in a low
signal-to-noise Very Long Baseline Interferometry (VLBI) observation. Here we
show that the exotic physical scenarios required to explain the claimed
relativistic velocity -- extreme departures from equipartition and/or a highly
collimated outflow -- are excluded by our detailed Very Large Array radio
observations. Moreover, we present an independent analysis of the VLBI data and
propose that a modest loss of phase coherence provides a more natural
explanation for the apparent flux density loss which is evident on both short
and long baselines. We conclude that SN 2007gr is an ordinary Type Ibc
supernova.


  Erik Verlinde recently proposed an idea about the thermodynamic origin of
gravity. Though this is a beautiful idea which may resolve many long standing
problems in the theories of gravity, it also raises many other problems. In
this article I will comment on some of the problems of Verlinde's proposal with
special emphasis on the thermodynamical origin of the principle of relativity.
It is found that there is a large group of hidden symmetries of thermodynamics
which contains the Poincare group of the spacetime for which space is emergent.
This explains the thermodynamic origin of the principle of relativity.


  Solving large-scale multistage stochastic programming (MSP) problems poses a
significant challenge as commonly used stagewise decomposition algorithms,
including stochastic dual dynamic programming (SDDP), face growing time
complexity as the subproblem size and problem count increase. Traditional
approaches approximate the value functions as piecewise linear convex functions
by incrementally accumulating subgradient cutting planes from the primal and
dual solutions of stagewise subproblems. Recognizing these limitations, we
introduce TranSDDP, a novel Transformer-based stagewise decomposition
algorithm. This innovative approach leverages the structural advantages of the
Transformer model, implementing a sequential method for integrating subgradient
cutting planes to approximate the value function. Through our numerical
experiments, we affirm TranSDDP's effectiveness in addressing MSP problems. It
efficiently generates a piecewise linear approximation for the value function,
significantly reducing computation time while preserving solution quality, thus
marking a promising progression in the treatment of large-scale multistage
stochastic programming problems.


  In this Letter we report the LDA+DMFT (method combining Local Density
Approximation with Dynamical Mean-Field Theory) results for magnetic properties
of parent superconductor LaFeAsO in paramagnetic phase. Calculated uniform
magnetic susceptibility shows linear dependence at intermediate temperatures in
agreement with experimental data. For high temperatures ($>$1000 K)
calculations show saturation and then susceptibility decreases with
temperature. Contributions to temperature dependence of the uniform
susceptibility are strongly orbitally dependent. It is related to the form of
the orbitally-resolved spectral functions near the Fermi energy with strong
temperature dependent narrow peaks for some of the orbitals. Our results
demonstrate that linear-temperature dependence of static magnetic
susceptibility in pnictide superconductors can be reproduced without invoking
antiferromagnetic fluctuations.


  Adaptive traffic signal control (ATSC) in urban traffic networks poses a
challenging task due to the complicated dynamics arising in traffic systems. In
recent years, several approaches based on multi-agent deep reinforcement
learning (MARL) have been studied experimentally. These approaches propose
distributed techniques in which each signalized intersection is seen as an
agent in a stochastic game whose purpose is to optimize the flow of vehicles in
its vicinity. In this setting, the systems evolves towards an equilibrium among
the agents that shows beneficial for the whole traffic network. A recently
developed multi-agent variant of the well-established advantage actor-critic
(A2C) algorithm, called MA2C (multi-agent A2C) exploits the promising idea of
some communication among the agents. In this view,the agents share their
strategies with other neighbor agents, thereby stabilizing the learning process
even when the agents grow in number and variety. We experimented MA2C in two
traffic networks located in Bologna (Italy) and found that its action
translates into a significant decrease of the amount of pollutants released
into the environment.


  We present experimental results on the single file motion of a group of
robots interacting with each other through position sensors. We successfully
replicate the fundamental diagram typical of these systems, with a transition
from free flow to congested traffic as the density of the system increases. In
the latter scenario we also observe the characteristic stop-and-go waves. The
unique advantages of this novel system, such as experimental stability and
repeatability, allow for extended experimental runs, facilitating a
comprehensive statistical analysis of the global dynamics. Above a certain
density, we observe a divergence of the average jam duration and the average
number of robots involved in it. This discovery enables us to precisely
identify another transition: from congested intermittent flow (for intermediate
densities) to a totally congested scenario for high densities. Beyond this
finding, the present work demonstrates the suitability of robot swarms to model
complex behaviors in many particle systems.


  This is an expository article describing recent results of the authors and
David Nadler on microlocalization, the Fukaya category, and coherent sheaves on
toric varieties. The original papers are arXiv:math/0604379, arXiv:math/0612399
and arXiv:0811.1228v1.


  Numerical calculations of the sensitivity coefficients, Q_mu, of microwave
molecular transitions in the ground torsion-rotation state of deuterated
methanol (CH3OD, CD3OH, and CD3OD) to small variations in the fundamental
physical constant mu = me/mp - the electron-to-proton mass ratio - are
reported. Theoretical motivation for changes in mu comes from a variety of
models beyond the Standard Model of particle physics which are invoked to
explain the nature of dark matter and dark energy that dominate the Universe.
The calculated values of Q_mu range from -300 to +73 and, thus, make deuterated
methanol promising for searches for small space-time changes in mu. It is also
shown that among the calculated sensitivity coefficients Q_mu using different
Hamiltonians in the present and previous works, there are several pronounced
outliers of unclear nature.


  Even if the unification and supersymmetry breaking scales are around $10^6$
to $10^{9}$ TeV, a large $A_t$ coupling may be entirely generated at low
energies through RGE evolution in the 5D MSSM. Independent of the precise
details of supersymmetry breaking, we take advantage of power law running in
five dimensions and a compactification scale in the $10-10^3$ TeV range to show
how the gluino mass may drive a large enough $A_t$ to achieve the required
$125.5$ GeV Higgs mass. This also allows for sub-TeV stops, possibly observable
at the LHC, and preserving GUT unification, thereby resulting in improved
naturalness properties with respect to the four dimensional MSSM. The results
apply also to models of "split families" in which the first and second
generation matter fields are in the bulk and the third is on the boundary,
which may assist in the generation of light stops whilst satisfying collider
constraints on the first two generations of squarks.


  Despite the great success of two-stage detectors, single-stage detector is
still a more elegant and efficient way, yet suffers from the two well-known
disharmonies during training, i.e. the huge difference in quantity between
positive and negative examples as well as between easy and hard examples. In
this work, we first point out that the essential effect of the two disharmonies
can be summarized in term of the gradient. Further, we propose a novel gradient
harmonizing mechanism (GHM) to be a hedging for the disharmonies. The
philosophy behind GHM can be easily embedded into both classification loss
function like cross-entropy (CE) and regression loss function like smooth-$L_1$
($SL_1$) loss. To this end, two novel loss functions called GHM-C and GHM-R are
designed to balancing the gradient flow for anchor classification and bounding
box refinement, respectively. Ablation study on MS COCO demonstrates that
without laborious hyper-parameter tuning, both GHM-C and GHM-R can bring
substantial improvement for single-stage detector. Without any whistles and
bells, our model achieves 41.6 mAP on COCO test-dev set which surpasses the
state-of-the-art method, Focal Loss (FL) + $SL_1$, by 0.8.


  We have carried out optical spectroscopic measurements of emission lines for
a sample of Galactic planetary nebulae with Wolf-Rayet (WR) stars and weak
emission-line stars (wels). The plasma diagnostics and elemental abundance
analysis have been done using both collisionally excited lines (CELs) and
optical recombination lines (ORLs). It is found that the abundance discrepancy
factors (ADF=ORL/CEL) are closely correlated with the dichotomy between
temperatures derived from forbidden lines and those from He I recombination
lines, implying the existence of H-deficient materials embedded in the nebula.
The H$\beta$ surface brightness correlations suggest that they might be also
related to the nebular evolution.


  In this paper we develop the theory of Artin-Wraith glueings for topological
spaces. As an application, we show that some categories of compactifications of
coarse spaces that agree with the coarse structures are invariant under coarse
equivalences. As a consequence, if X and Y are some well behaved metric spaces
that are coarse equivalent, then they have the same space of ends (generalizing
the well known fact that works on quasi-isometric proper geodesic metric
spaces). As another application, we show that for every compact metrizable
space $Y$, there exists only one, up to homeomorphisms, compactification of the
Cantor set minus one point such that the remainder is homeomorphic to $Y$.


  Supercurrents in superconducting flux threaded loops are expected to
oscillate with the magnetic flux with a period of hc/2e. This is indeed true
for s-wave superconductors larger than the coherence length xi_0. Here we show
that for superconductors with gap nodes, there is no such strict condition for
the supercurrent to be hc/2e rather than hc/e periodic. For nodal
superconductors, the flux induced Doppler shift of the near nodal states leads
to a flux dependent occupation probability of quasi-particles circulating
clockwise and counter clockwise around the loop, which leads to an hc/e
periodic component of the supercurrent, even at zero temperature. We analyze
this phenomenon on a cylinder in an approximative analytic approach and also
numerically within the framework of the BCS theory. Specifically for d-wave
pairing, we show that the hc/e periodic current component decreases with the
inverse radius of the loop and investigate its temperature dependence.


  Understanding event and event-centered commonsense reasoning are crucial for
natural language processing (NLP). Given an observed event, it is trivial for
human to infer its intents and effects, while this type of If-Then reasoning
still remains challenging for NLP systems. To facilitate this, a If-Then
commonsense reasoning dataset Atomic is proposed, together with an RNN-based
Seq2Seq model to conduct such reasoning. However, two fundamental problems
still need to be addressed: first, the intents of an event may be multiple,
while the generations of RNN-based Seq2Seq models are always semantically
close; second, external knowledge of the event background may be necessary for
understanding events and conducting the If-Then reasoning. To address these
issues, we propose a novel context-aware variational autoencoder effectively
learning event background information to guide the If-Then reasoning.
Experimental results show that our approach improves the accuracy and diversity
of inferences compared with state-of-the-art baseline methods.


  We have developed a new method for spectral analysis of binaries. Our method
successfully identifies SB2 candidates from high-resolution Gaia-ESO spectra.
Compared to the commonly used cross-correlation function analysis, it works for
binaries with rapidly rotating components. We test our method on synthetic and
observational spectra of BAFG-stars in the open cluster M 11. We confirm five
previously detected SB2 candidates and find 19 new ones. For three SB2
candidates we find circular orbits and obtain dynamical mass ratios.


  In this work, our goals are two fold: large-vocabulary continuous sign
language recognition (CSLR), and sign language retrieval. To this end, we
introduce a multi-task Transformer model, CSLR2, that is able to ingest a
signing sequence and output in a joint embedding space between signed language
and spoken language text. To enable CSLR evaluation in the large-vocabulary
setting, we introduce new dataset annotations that have been manually
collected. These provide continuous sign-level annotations for six hours of
test videos, and will be made publicly available. We demonstrate that by a
careful choice of loss functions, training the model for both the CSLR and
retrieval tasks is mutually beneficial in terms of performance -- retrieval
improves CSLR performance by providing context, while CSLR improves retrieval
with more fine-grained supervision. We further show the benefits of leveraging
weak and noisy supervision from large-vocabulary datasets such as BOBSL, namely
sign-level pseudo-labels, and English subtitles. Our model significantly
outperforms the previous state of the art on both tasks.


  Branched rough paths, used to solve ODEs on $\mathbb{R}$, have been
generalised in two different directions. In one direction, there are regularity
structures aimed at solving SPDEs on $\mathbb{R}$. In the other direction,
there are planarly branched rough paths to solve ODEs on homogeneous spaces.
This paper combines these two directions to construct planar regularity
structures, for (S)PDEs on homogeneous spaces.


  Community detection has been an active research area for decades. Among all
probabilistic models, Stochastic Block Model has been the most popular one.
This paper introduces a novel probabilistic model: RW-HDP, based on random
walks and Hierarchical Dirichlet Process, for community extraction. In RW-HDP,
random walks conducted in a social network are treated as documents; nodes are
treated as words. By using Hierarchical Dirichlet Process, a nonparametric
Bayesian model, we are not only able to cluster nodes into different
communities, but also determine the number of communities automatically. We use
Stochastic Variational Inference for our model inference, which makes our
method time efficient and can be easily extended to an online learning
algorithm.


  Data Science and Machine Learning have become fundamental assets for
companies and research institutions alike. As one of its fields, supervised
classification allows for class prediction of new samples, learning from given
training data. However, some properties can cause datasets to be problematic to
classify.
  In order to evaluate a dataset a priori, data complexity metrics have been
used extensively. They provide information regarding different intrinsic
characteristics of the data, which serve to evaluate classifier compatibility
and a course of action that improves performance. However, most complexity
metrics focus on just one characteristic of the data, which can be insufficient
to properly evaluate the dataset towards the classifiers' performance. In fact,
class overlap, a very detrimental feature for the classification process
(especially when imbalance among class labels is also present) is hard to
assess.
  This research work focuses on revisiting complexity metrics based on data
morphology. In accordance to their nature, the premise is that they provide
both good estimates for class overlap, and great correlations with the
classification performance. For that purpose, a novel family of metrics have
been developed. Being based on ball coverage by classes, they are named after
Overlap Number of Balls. Finally, some prospects for the adaptation of the
former family of metrics to singular (more complex) problems are discussed.


  Reduced basis methods for approximating the solutions of parameter-dependant
partial differential equations (PDEs) are based on learning the structure of
the set of solutions - seen as a manifold ${\mathcal S}$ in some functional
space - when the parameters vary. This involves investigating the manifold and,
in particular, understanding whether it is close to a low-dimensional affine
space. This leads to the notion of Kolmogorov $N$-width that consists of
evaluating to which extent the best choice of a vectorial space of dimension
$N$ approximates ${\mathcal S}$ well enough. If a good approximation of
elements in ${\mathcal S}$ can be done with some well-chosen vectorial space of
dimension $N$ -- provided $N$ is not too large -- then a ``reduced'' basis can
be proposed that leads to a Galerkin type method for the approximation of any
element in ${\mathcal S}$. In many cases, however, the Kolmogorov $N$-width is
not so small, even if the parameter set lies in a space of small dimension
yielding a manifold with small dimension. In terms of complexity reduction,
this gap between the small dimension of the manifold and the large Kolmogorov
$N$-width can be explained by the fact that the Kolmogorov $N$-width is linear
while, in contrast, the dependency in the parameter is, most often, non-linear.
There have been many contributions aiming at reconciling these two statements,
either based on deterministic or AI approaches. We investigate here further a
new paradigm that, in some sense, merges these two aspects: the nonlinear
compressive reduced basisapproximation. We focus on a simple multiparameter
problem and illustrate rigorously that the complexity associated with the
approximation of the solution to the parameter dependant PDE is directly
related to the number of parameters rather than the Kolmogorov $N$-width.


  New crystal technique - array of bent strips and a fan-type reflector, based
on thin straight plates - have been used for research of extraction and
collimation a circulating beam in the U-70 accelerator at the energy 50 GeV and
1.3 GeV. It is shown, that new devices can effectively steer a beam in a wide
energy range. For protons with energy 50 GeV efficiency of extraction and
collimation about 90 % has been achieved which is record for this method.
Reduction of particle losses in 2-3 times was observed also in accelerator at
application of different crystals in comparison with the usual one-stage
collimation scheme of beam with a steel absorber.


  The conformal transformation in the Einstein - Hilbert action leads to a new
frame where an extra scalar degree of freedom is compensated by the local
conformal-like symmetry. We write down a most general action resulting from
such transformation and show that it covers both general relativity and
conformally coupled to gravity scalar field as the particular cases. On quantum
level the equivalence between the different frames is disturbed by the loop
corrections. New conformal-like symmetry in anomalous and, as a result, the
theory is not finite on shell at the one-loop order.


  The dynamics of Vlasov kinetic moments is shown to be Lie-Poisson on the dual
Lie algebra of symmetric contravariant tensor fields. The corresponding Lie
bracket is identified with the symmetric Schouten bracket and the moment Lie
algebra is related with a bundle of bosonic Fock spaces, where creation and
annihilation operators are used to construct the cold plasma closure. Kinetic
moments are also shown to define a momentum map, which is infinitesimally
equivariant. This momentum map is the dual of a Lie algebra homomorphism,
defined through the Schouten bracket. Finally the moment Lie-Poisson bracket is
extended to anisotropic interactions.


  This work presents a technique to estimate on-line the global momentum of an
electric power system. It exploits the footprint of the principal frequency
system dynamics. Probing tones are injected by a grid-forming
converter-interfaced generator and the speed of its virtual rotor is exploited
to extrapolate the footprint. The proposed technique is entirely data driven
and thus it does not need any model of the power system. We show that the
proposed technique is adequate to accurately estimate the actual global
momentum contributed by synchronous machines and provided by the controllers of
converter-interfaced generators that emulate the behavior of synchronous
machines. The technique is comprehensively tested on a modified version of the
IEEE 39-BUS system and a dynamic version of the IEEE 118-BUS system, containing
grid forming converter interfaced generators.


  Major mergers of galaxies are considered to be an efficient way to trigger
Active Galactic Nuclei and are thought to be responsible for the phenomenon of
quasars. This has however recently been challenged by observations of a large
number of low luminosity Active Galactic Nuclei at low redshift ($z\lesssim1$)
without obvious major merger signatures. Minor mergers are frequently proposed
to explain the existence of these Active Galactic Nuclei. In this paper, we
perform nine high resolution hydrodynamical simulations of minor galaxy mergers
and investigate whether nuclear activities can be efficiently triggered by
minor mergers, by setting various properties for the progenitor galaxies of
those mergers. We find that minor galaxy merger scan activate the massive black
hole in the primary galaxy with an Eddington ratio of $f_{\rm Edd}>0.01$ and
$>0.05$ (or a bolometric luminosity $>10^{43}$ and $>10^{44}\mathrm{erg\,
s^{-1}}$) with a duration of $2.71$ and $0.49$ Gyr (or $2.69$ and $0.19$ Gyr),
respectively. The nuclear activity of primary galaxy strongly depends on the
nucleus separation, the nucleus is more active as the two nuclei approach to
each other. Dual Active Galactic Nuclei systems can still possibly form by
minor mergers of galaxies, the time period for dual Active Galactic Nuclei is
only $\sim 0.011$ Gyr and $\sim 0.017$ Gyr with Eddington ratio of $f_{\rm
Edd}>0.05$ and bolometric luminosity $>10^{44}\mathrm{erg\, s^{-1}}$. This time
period is typically shorter than that of dual Active Galactic Nuclei induced by
galaxy major mergers.


  Let $p$ and $l$ be rational primes such that $l$ is odd and the order of $p$
modulo $l$ is even. For such primes $p$ and $l$, and for $e=l, 2l$, we consider
the non-singular projective curves $aY^e = bX^e + cZ^e$ ($abc \neq 0$) defined
over finite fields $\mathbf{F}_q$ such that $q=p^\alpha \equiv 1(\bmod {e})$.
We see that the Fermat curves correspond precisely to those curves among each
class (for $e=l,2l$), that are maximal or minimal over $\mathbf{F}_q$. We
observe that each Fermat prime gives rise to explicit maximal and minimal
curves over finite fields of characteristic 2. For $e=2l$, we explicitly
determine the $\zeta$-function(s) for this class of curves, over
$\mathbf{F}_q$, as rational functions in the variable $t$, for distinct cases
of $a,b$, and $c$, in $\mathbf{F}_q^*$. The $\zeta$-function in each case is
seen to satisfy the Weil conjectures (now theorems) for this concrete class of
curves.


  Collaborative Simultaneous Localization and Mapping (CSLAM) is a critical
capability for enabling multiple robots to operate in complex environments.
Most CSLAM techniques rely on the transmission of low-level features for visual
and LiDAR-based approaches, which are used for pose graph optimization.
However, these low-level features can lead to incorrect loop closures,
negatively impacting map generation.Recent approaches have proposed the use of
high-level semantic information in the form of Hierarchical Semantic Graphs to
improve the loop closure procedures and overall precision of SLAM algorithms.
In this work, we present Multi S-Graphs, an S-graphs [1] based distributed
CSLAM algorithm that utilizes high-level semantic information for cooperative
map generation while minimizing the amount of information exchanged between
robots. Experimental results demonstrate the promising performance of the
proposed algorithm in map generation tasks.


  With the increasing role of Natural Language Processing (NLP) in various
applications, challenges concerning bias and stereotype perpetuation are
accentuated, which often leads to hate speech and harm. Despite existing
studies on sexism and misogyny, issues like homophobia and transphobia remain
underexplored and often adopt binary perspectives, putting the safety of
LGBTQIA+ individuals at high risk in online spaces. In this paper, we assess
the potential harm caused by sentence completions generated by English large
language models (LLMs) concerning LGBTQIA+ individuals. This is achieved using
QueerBench, our new assessment framework, which employs a template-based
approach and a Masked Language Modeling (MLM) task. The analysis indicates that
large language models tend to exhibit discriminatory behaviour more frequently
towards individuals within the LGBTQIA+ community, reaching a difference gap of
7.2% in the QueerBench score of harmfulness.


  Cloud computing is bringing a revolution in computing environment replacing
traditional software installations, licensing issues into complete on-demand
services through internet. Microsoft office 365 a cloud based office
application is available to clients online hence no need to buy and install the
software. On Facebook a social networking website, users upload videos which
uses cloud provider's storage service so less hardware cost for
clients.Virtualization technology has great contribution in advent of cloud
computing. Paper describes implementation of Private Cloud using open source
operating system Ubuntu 10.04 server edition, installation of Ubuntu Enterprise
Cloud with Eucalyptus 1.6.2 and providing CentOS 5.3 operating system through
cloud.


  We have developed a consistent analytical model to describe the observed
evolution of the quasar luminosity function. Our model combines black hole mass
distributions based on the Press - Schechter theory of the structure formation
in the Universe with quasar luminosity functions resulting from a physics-based
emission model that takes into account the time-dependent phenomena occurring
in the accretion disks. Quasar evolution and CDM models are mutually
constraining, therefore our model gives an estimation of the exponent, n, of
the power spectrum, P(k), which is found to be -1.8 < n < -1.6. We were able to
reject a generally assumed hypothesis of a constant ratio between Dark Matter
Halo and the Black Hole mass, since the observed data could not be fitted under
this assumption. We found that the relation between the Dark Matter Halos and
Black Hole masses is better described by M_{BH}=M_{DMH}^{0.668}. This model
provides a reasonable fit to the observed quasar luminosity function at
redshifts higher than ~2.0. We suggest that the disagreement at lower redshift
is due to mergers. Based on the agreement at high redshift, we estimated the
merger rate at lower redshift, and argue that this rate should depend on the
redshift, like (1+z)^3.


  We investigate the origin of exoticity in Fe-based systems via studying the
Fermiology of CaFe2As2 employing Angle Resolved Photoemission spectroscopy
(ARPES). While the Fermi surfaces (FSs) at 200 K and 31 K are observed to
exhibit two dimensional (2D) and three dimensional (3D) topology, respectively,
the FSs at intermediate temperatures reveal emergence of the 3D topology at
much lower temperature than the structural & magnetic phase transition
temperature (170 K, for the sample under scrutiny). This leads to the
conclusion that the evolution of FS topology is not directly driven by the
structural transition. In addition, we discover the existence in ambient
conditions of energy bands related to the collapsed tetragonal (cT) phase.
These bands are distinctly resolved in the high-photon energy spectra
exhibiting strong Fe 3d character. They gradually move to higher binding
energies due to thermal compression with cooling, leading to the emergence of
3D topology in the Fermi surface. These results reveal the so-far hidden
existence of a cT phase in ambient conditions, which is argued to lead to
quantum fluctuations responsible for the exotic electronic properties in
Fe-pnictide superconductors.


  In this work, new theoretical results on functional type a posteriori
estimates for elliptic optimal control problems with control constraints are
presented. More precisely, we derive new, sharp, guaranteed and fully
computable lower bounds for the cost functional in addition to the already
existing upper bounds. Using both, the lower and the upper bounds, we arrive at
two-sided estimates for the cost functional. We prove that these bounds finally
lead to sharp, guaranteed and fully computable upper estimates for the
discretization error in the state and the control of the optimal control
problem. First numerical tests are presented confirming the efficiency of the a
posteriori estimates derived.


  Agents' heterogeneity is recognized as a driver mechanism for the persistence
of financial volatility. We focus on the multiplicity of investment strategies'
horizons, we embed this concept in a continuous time stochastic volatility
framework and prove that a parsimonious, two-scale version effectively captures
the long memory as measured from the real data. Since estimating parameters in
a stochastic volatility model is challenging, we introduce a robust methodology
based on the Generalized Method of Moments supported by a heuristic selection
of the orthogonal conditions. In addition to the volatility clustering, the
estimated model also captures other relevant stylized facts, emerging as a
minimal but realistic and complete framework for modelling financial time
series.


  Using quantum information geometry, I derive quantum generalizations of the
Onsager rate equations, which model the dynamics of an open system near a
steady state. The generalized equations hold for a flexible definition of the
forces as well as a large class of statistical divergence measures and
quantum-Fisher-information metrics beyond the conventional definition of
entropy production. I also derive quantum Onsager-Casimir relations for the
transport tensors by proposing a general concept of time reversal and detailed
balance for open quantum systems. The results establish a remarkable connection
between statistical mechanics and parameter estimation theory.


  We report the first systematic survey of molecular lines (including HCO+
(1-0) and 12CO, 13CO, C18O (1-0) lines at 3 mm band) towards a new sample of 88
massive young stellar object (MYSO) candidates associated with ongoing outflows
(known as extended green objects or EGOs) identified from the Spitzer GLIMPSE
survey in the northern hemisphere with the PMO-13.7 m radio telescope. By
analyzing the asymmetries of the optically thick line HCO+ for 69 of 72 EGOs
with HCO+ detection, we found 29 sources with blue asymmetric profiles and 19
sources with red asymmetric profiles. This results in a blue excess of 0.14,
seen as a signature of collapsing cores in the observed EGO sample. The
relatively small blue excess measured in our full sample due to that the
observed EGOs are mostly dominated by outflows and at an earlier evolutionary
phase associated with IRDCs and 6.7 GHz methanol masers. The physical
properties of clouds surrounding EGOs derived from CO lines are similar to
those of massive clumps wherein the massive star forming cores associated with
EGOs possibly embedded. The infall velocities and mass infall rates derived for
20 infall candidates are also consistent with the typical values found in
MYSOs. Thus our observations further support the speculation of Cyganowski et
al. (2008) that EGOs trace a population with ongoing outflow activity and
active rapid accretion stage of massive protostellar evolution from a
statistical view, although there maybe have limitations due to single-pointing
survey with a large beam.


  The weak charge $Q_W$ measured in atomic parity violation experiments can
receive compensating contributions from more than one new physics source. We
show explicitly that the $\Delta Q_W$ contribution from the exchange of an
extra Z-boson can cancel that from the $s$-channel scalar top or scalar charm
exchange in R-parity violating SUSY models proposed to explain the HERA
high-$Q^2$ anomaly.


  We show that the Continuum Hypothesis implies that for every $0<d_1\leq
d_2<n$ the measure spaces $(\RR^n,\iM_{\iH^{d_1}},\iH^{d_1})$ and
$(\RR^n,\iM_{\iH^{d_2}},\iH^{d_2})$ are isomorphic, where $\iH^d$ is
$d$-dimensional Hausdorff measure and $\iM_{\Hd}$ is the $\sigma$-algebra of
measurable sets with respect to $\Hd$. This is motivated by the well-known
question (circulated by D. Preiss) whether such an isomorphism exists if we
replace measurable sets by Borel sets.
  We also investigate the related question whether every continuous function
(or the typical continuous function) is H\"older continuous (or is of bounded
variation) on a set of positive Hausdorff dimension.


  Random matrix models generalize to Group Field Theories (GFT) whose Feynman
graphs are dual to gluings of higher dimensional simplices. It is generally
assumed that GFT graphs are always dual to pseudo manifolds. In this paper we
prove that already in dimension three (and in all higher dimensions), this is
not true due to subtle differences between simplicial complexes and gluings
dual to GFT graphs. We prove however that, fortunately, the recently introduced
"colored" GFT models [1] do not suffer from this problem and only generate
graphs dual to pseudo manifolds in any dimension.


  Recent work on one-shot permutation-based model merging has shown impressive
low- or zero-barrier mode connectivity between models from completely different
initializations. However, this line of work has not yet extended to the
Transformer architecture, despite its dominant popularity in the language
domain. Therefore, in this work, we investigate the extent to which separate
Transformer minima learn similar features, and propose a model merging
technique to investigate the relationship between these minima in the loss
landscape. The specifics of the architecture, like its residual connections,
multi-headed attention, and discrete, sequential input, require specific
interventions in order to compute model permutations that remain within the
same functional equivalence class. In merging these models with our method, we
consistently find lower loss barriers between minima compared to model
averaging for several models trained on a masked-language modeling task or
fine-tuned on a language understanding benchmark. Our results show that the
minima of these models are less sharp and isolated than previously understood,
and provide a basis for future work on merging separately trained Transformer
models.


  The Ronkin function plays a fundamental role in the theory of amoebas. We
introduce an analogue of the Ronkin function in the setting of coamoebas. It
turns out to be closely related to a certain toric arrangement known as the
shell of the coamoeba and we use our Ronkin type function to obtain some
properties of it.


  The multiplication of architecture description languages, component models
and platforms implies a serious dilemma for component based software
architects. On the one hand, they have to choose a language to describe
concrete configurations which will be automatically deployed on execution
platforms. On the other hand, they wish to capitalize their software
architectures independently of any description languages or platforms. To solve
this problem, we propose a multi personalities environment for the
configuration and the deployment of component based applications. This
environment is composed of a core capturing a canonical model of configuration
and deployment, and a set of personalities tailored to languages and platforms.
This paper details the architecture of such an environment and describes the
personalities for the CORBA and Fractal component models.


  Optical neuroimaging is a vital tool for understanding the brain structure
and the connection between regions and nuclei. However, the image noise
introduced in the sample preparation and the imaging system hinders the
extraction of the possible knowlege from the dataset, thus denoising for the
optical neuroimaging is usually necessary. The supervised denoisng methods
often outperform the unsupervised ones, but the training of the supervised
denoising models needs the corresponding clean labels, which is not always
avaiable due to the high labeling cost. On the other hand, those semantic
labels, such as the located soma positions, the reconstructed neuronal fibers,
and the nuclei segmentation result, are generally available and accumulated
from everyday neuroscience research. This work connects a supervised denoising
and a semantic segmentation model together to form a end-to-end model, which
can make use of the semantic labels while still provides a denoised image as an
intermediate product. We use both the supervised and the self-supervised models
for the denoising and introduce a new cost term for the joint denoising and the
segmentation setup. We test the proposed approach on both the synthetic data
and the real-world data, including the optical neuroimaing dataset and the
electron microscope dataset. The result shows that the joint denoising result
outperforms the one using the denoising method alone and the joint model
benefits the segmentation and other downstream task as well.


  We assemble a statistical set of global mass models for ~2,000 nearly
spherical SDSS galaxies at a mean redshift of 0.12 based on their aperture
velocity dispersions and newly derived luminosity profiles in conjunction with
published velocity dispersion profiles and empirical properties and relations
of galaxy and halo parameters. When two-component (i.e. stellar plus dark) mass
models are fitted to the SDSS aperture velocity dispersions, the predicted
velocity dispersion profile (VP) slopes within the effective radius R_eff match
well the distribution in observed elliptical galaxies. In contrast, the
single-component models cannot reproduce the VP slope distribution. From a
number of input variations the models exhibit for the radial range 0.1 R_eff <
r < R_eff a tight correlation <gamma_e>=(1.865+/-0.008)+(-4.93+/-0.15)<eta>
where <gamma_e> is the mean slope absolute value of the total mass density and
<eta> is the mean slope of the velocity dispersion profile, which leads to a
super-isothermal <gamma_e> = 2.15+/-0.04 for <eta>=-0.058+/-0.008 in observed
elliptical galaxies. Furthermore, the successful two-component models appear to
imply a typical slope curvature pattern in the total mass profile because for
the observed steep luminosity (stellar mass) profile and the weak lensing
inferred halo profile at large radii a total mass profile with monotonically
varying slope would require too high DM density in the optical region giving
rise to too large aperture velocity dispersion and too shallow VP.


  Three bodies moving in a periodic orbit under the influence of Newtonian
gravity ought to emit gravitational waves. We have calculated the gravitational
radiation quadrupolar waveforms and the corresponding luminosities for the
13+11 recently discovered three-body periodic orbits in Newtonian gravity.
These waves clearly allow one to distinguish between their sources: all 13+11
orbits have different waveforms and their luminosities (evaluated at the same
orbit energy and body mass) vary by up to 13 orders of magnitude in the mean,
and up to 20 orders of magnitude for the peak values.


  We define and study the interpolated finite multiple harmonic $q$-series. A
generating function of the sums of the interpolated finite multiple harmonic
$q$-series with fixed weight, depth and $i$-height is computed. Some
Ohno-Zagier type relation with corollaries and some evaluation formulas of the
interpolated finite multiple harmonic $q$-series at roots of unity are given.


  We introduce the Leavitt path algebras of ultragraphs and we characterize
their ideal structures. We then use this notion to introduce and study the
algebraic analogous of Exel-Laca algebras.


  Events describe the state changes of entities. In a document, multiple events
are connected by various relations (e.g., Coreference, Temporal, Causal, and
Subevent). Therefore, obtaining the connections between events through
Event-Event Relation Extraction (ERE) is critical to understand natural
language. There are two main problems in the current ERE works: a. Only
embeddings of the event triggers are used for event feature representation,
ignoring event arguments (e.g., time, place, person, etc.) and their structure
within the event. b. The interconnection between relations (e.g., temporal and
causal relations usually interact with each other ) is ignored. To solve the
above problems, this paper proposes a jointly multiple ERE framework called
GraphERE based on Graph-enhanced Event Embeddings. First, we enrich the event
embeddings with event argument and structure features by using static AMR
graphs and IE graphs; Then, to jointly extract multiple event relations, we use
Node Transformer and construct Task-specific Dynamic Event Graphs for each type
of relation. Finally, we used a multi-task learning strategy to train the whole
framework. Experimental results on the latest MAVEN-ERE dataset validate that
GraphERE significantly outperforms existing methods. Further analyses indicate
the effectiveness of the graph-enhanced event embeddings and the joint
extraction strategy.


  This is a master's thesis concerning the theoretical ideas of geometric deep
learning. Geometric deep learning aims to provide a structured characterization
of neural network architectures, specifically focused on the ideas of
invariance and equivariance of data with respect to given transformations.
  This thesis aims to provide a theoretical evaluation of geometric deep
learning, compiling theoretical results that characterize the properties of
invariant neural networks with respect to learning performance.