  We propose a four-neutrino model which can reconcile the existing data coming
from underground experiments in terms of neutrino oscillations, together with
the hint from the LSND experiment and a possible neutrino contribution to the
hot dark matter of the Universe. It applies the idea that extra compact
dimensions, probed only by gravity and possibly gauge-singlet fields, can lower
the fundamental scales such as the Planck, string or unification scales. Our
fourth light neutrino $\nu_s$ ($s$ for sterile) is identified with the zero
mode of the Kaluza-Klein states. To first approximation \nu_sterile combines
with the nu_mu in order to form a Dirac neutrino with mass in the eV range
leaving the other two neutrinos massless. The smallness of this mass scale
(suitable for LSND and Hot Dark Matter) arises without appealing neither to a
see-saw mechanism nor to a radiative mechanism, but from the volume factor
associated with the canonical normalization of the wave-function of the bulk
field in the compactified dimensions. % On the other hand the splitting between
\nm and \nu_sterile (atmospheric scale) as well as the mass of the two other
neutrinos (solar mass scale) arise from the violation of the fermion number on
distant branes. We also discuss alternative scenarios involving
flavour-changing interactions. In one of them \ne can be in the electron-volt
range and therefore be probed in beta decay studies.


  The next-to-next-to-leading order (NNLO) corrections in massless perturbative
QCD are derived for the parton distributions of the photon and the deep
inelastic structure functions F_1^gamma and F_2^gamma. We present the full
photonic coefficient functions at order alpha alpha_s and calculate the first
six even-integer moments of the corresponding O(alpha alpha_s^2) photon-quark
and photon-gluon splitting functions together with the moments of the alpha
alpha_s^2 coefficient functions which enter only beyond NNLO. These results are
employed to construct parametrizations of the splitting functions which prove
to be sufficiently accurate at least for momentum fractions x >= 0.05. We also
present explicit expressions for the transformation from the MS_bar to the
DIS_gamma factorization scheme and write down the solution of the evolution
equations. The numerical impact of the NNLO corrections is discussed in both
schemes.


  We present new and explicit formulae for the one-loop integrands of
scattering amplitudes in non-supersymmetric gauge theory and gravity, valid for
any number of particles. The results exhibit the colour-kinematics duality in
gauge theory and the double-copy relation to gravity, in a form that was
recently observed in supersymmetric theories. The new formulae are expressed in
a particular representation of the loop integrand, with only one quadratic
propagator, which arises naturally from the framework of the loop-level
scattering equations. The starting point in our work are the expressions based
on the scattering equations that were recently derived from ambitwistor string
theory. We turn these expressions into explicit formulae depending only on the
loop momentum, the external momenta and the external polarisations. These
formulae are valid in any number of spacetime dimensions for pure Yang-Mills
theory (gluon) and its natural double copy, NS-NS gravity (graviton, dilaton,
B-field), and we also present formulae in four spacetime dimensions for pure
gravity (graviton). We perform several tests of our results, such as checking
gauge invariance and directly matching our four-particle formulae to previously
known expressions. While these tests would be elaborate in a Feynman-type
representation of the loop integrand, they become straightforward in the
representation we use.


  The expansive globalization of the semiconductor supply chain has introduced
numerous untrusted entities into different stages of a device's lifecycle. To
make matters worse, the increase complexity in the design as well as aggressive
time to market requirements of the newer generation of integrated circuits can
lead either designers to unintentionally introduce security vulnerabilities or
verification engineers to fail in detecting them earlier in the design
lifecycle. These overlooked or undetected vulnerabilities can be exploited by
malicious entities in subsequent stages of the lifecycle through an ever
widening variety of hardware attacks. The ability to ascertain the provenance
of these vulnerabilities, therefore, becomes a pressing issue when the security
assurance across the whole lifecycle is required to be ensured. We posit that
if there is a malicious or unintentional breach of security policies of a
device, it will be reflected in the form of anomalies in the traditional
design, verification and testing activities throughout the lifecycle. With
that, a digital simulacrum of a device's lifecycle, called a digital twin (DT),
can be formed by the data gathered from different stages to secure the
lifecycle of the device. In this paper, we put forward a realization of
intertwined relationships of security vulnerabilities with data available from
the silicon lifecycle and formulate different components of an AI driven DT
framework. The proposed DT framework leverages these relationships and
relational learning to achieve Forward and Backward Trust Analysis
functionalities enabling security aware management of the entire lifecycle.
Finally, we provide potential future research avenues and challenges for
realization of the digital twin framework to enable secure semiconductor
lifecycle management.


  We investigate the properties of Fe-rich knots on the east limb of the
Cassiopeia A supernova remnant using observations with Chandra/ACIS and
analysis methods developed in a companion paper. We use the fitted ionization
age and electron temperature of the knots to constrain the ejecta density
profile and the Lagrangian mass coordinates of the knots. Fe-rich knots which
also have strong emission from Si, S, Ar, and Ca are clustered around mass
coordinates q~0.35-0.4 in the shocked ejecta; for ejecta mass 2M_sun, this
places the knots 0.7-0.8 M_sun out from the center (or 2-2.1 M_sun, allowing
for a 1.3 M_sun compact object). We also find an Fe clump that is evidently
devoid of line emission from lower mass elements, as would be expected if it
were the product of alpha-rich freeze out; the mass coordinate of this clump is
similar to those of the other Fe knots.


  We give a precise description of how the class group of a number field
measures the failure of unique factorization in its ring of integers.
Specifically, following ideas of Kummer, we determine the structure of all
irreducible factorizations of an element in the ring of integers of a number
field, and give a combinatorial description for the number of such
factorizations. In certain cases, we show how quadratic forms can explicitly
provide all such factorizations.


  In an external magnetic field, the energy of the electroweak
sphaleron---representing the energy barrier to baryon and lepton number
violation---decreases but remains nonzero until the upper Ambjorn-Olesen
critical field strength set by the Higgs mass and the electric charge, where it
vanishes. We demonstrate this by numerically computing the sphaleron
configuration in the presence of an external magnetic field, over the full
range of field strengths until the energy barrier vanishes. We discuss the
implications for baryogenesis in the early universe, and the possibility of
observing of baryon and lepton number violation in heavy-ion collisions.


  We report the first experimental generation and observation of Airy beams of
free electrons. The electron Airy beams are generated by diffraction of
electrons through a nanoscale hologram, that imprints a cubic phase modulation
on the beams' transverse plane. We observed the spatial evolution dynamics of
an arc-shaped, self accelerating and shape preserving electron Airy beams. We
directly observed the ability of electrons to self-heal, restoring their
original shape after passing an obstacle. This electromagnetic method opens up
new avenues for steering electrons, like their photonic counterparts, since
their wave packets can be imprinted with arbitrary shapes or trajectories.
Furthermore, these beams can be easily manipulated using magnetic or electric
potentials. It is also possible to efficiently self mix narrow beams having
opposite signs of acceleration, hence obtaining a new type of electron
interferometer.


  Recent determination of the distance to HDE 226868/Cyg X-1 binary system
(Reid et al., 2011) and more precise determination of the effective temperature
of HDE 226868 (Caballero- Nieves et al., 2009) permit a more accurate estimate
of the masses of both components. Using up to date evolutionary models, I
obtain a mass range of between 25 to 35 Msun for the mass of the supergiant and
between 13 to 23 Msun for the mass of the black hole. Accepting more liberal
estimates of uncertainties in both the distance and the effective temperature,
one may extend these ranges to 21 to 35 Msun and 10 to 23 Msun for both masses,
respectively. The most likely values within these ranges are, respectively, 27
Msun and 16 Msun. The obtained mass of black hole agrees with the value 15 +- 1
Msun suggested by Orosz et al. (2011). However, the value suggested by them for
the mass of the supergiant of 19 +- 2 Msun should not be used as such a star
violates the mass-luminosity relation for the the massive core hydrogen burning
stars. This consideration was not incorporated into the iterative process of
Orosz et al. To resolve this violation I consider the possibility that the
hydrogen content of HDE 222268 might be lowered as a result of the mass
transfer and the induced fast rotation of the mass gainer. I analyzed the
evolutionary effects of such situation and found that, while important, they do
not invalidate the conclusions listed above. If, as a result of the rotation
induced mixing, the present hydrogen content of HDE 226868 is equal about 0.6
(as suggested by some observational data), then its present mass may be
somewhat lower: about 24 Msun rather than about 27 Msun.


  These notes have been prepared as reading material for the mini-course given
by the author at the "2019 Graduate Summer School" at Park City Mathematics
Institute - Institute for Advanced Study. We begin by introducing Higgs bundles
and their main properties (Lecture 1), and then we discuss the Hitchin
fibration and its different uses (Lecture 2). The second half of the course is
dedicated to studying different types of subspaces (branes) of the moduli space
of complex Higgs bundles, their appearances in terms of flat connections and
representations (Lecture 3), as well as correspondences between them (Lecture
4).


  The two-dimensional relativistic configurational $\vec r$-space is proposed
and the exactly solvable finite-difference model of the harmonic oscillator in
this space is constructed. The wave functions of the stationary states and the
corresponding energy spectrum are found for the model under consideration. It
is shown that, they have correct non-relativistic limit. Explicit form of the
plane momentum operator is determined.


  We present interferometric observations of HI in nine slow rotator early-type
galaxies of the Atlas3D sample. With these data, we now have sensitive HI
searches in 34 of the 36 slow rotators. The aggregate detection rate is 32\%
$\pm$ 8\%, consistent with previous work; however, we find two detections with
extremely high HI masses, whose gas kinematics are substantially different from
what was previously known about HI in slow rotators. These two cases (NGC 1222
and NGC 4191) broaden the known diversity of HI properties in slow rotators.
NGC 1222 is a merger remnant with prolate-like rotation and, if it is indeed
prolate in shape, an equatorial gas disc; NGC 4191 has two counterrotating
stellar discs and an unusually large HI disc. We comment on the implications of
this disc for the formation of $2\sigma$ galaxies. In general, the HI detection
rate, the incidence of relaxed HI discs, and the HI/stellar mass ratios of slow
rotators are indistinguishable from those of fast rotators. These broad
similarities suggest that the HI we are detecting now is unrelated to the
galaxies' formation processes and was often acquired after their stars were
mostly in place. We also discuss the HI nondetections; some of these galaxies
that are undetected in HI or CO are detected in other tracers (e.g. FIR fine
structure lines and dust). The question of whether there is cold gas in massive
galaxies' scoured nuclear cores still needs work. Finally, we discuss an
unusual isolated HI cloud with a surprisingly faint (undetected) optical
counterpart.


  Electromagnetically induced transparency (EIT) is observed in a three-level
system composed of an excited state and two coherent superpositions of the two
ground-state levels. This peculiar ground state basis is composed of the
so-called bright and dark states of the same atomic system in a standard
coherent population trapping configuration. The characteristics of EIT, namely,
width of the transmission window and reduced group velocity of light, in this
unusual basis, are theoretically and experimentally investigated and are shown
to be essentially identical to those of standard EIT in the same system.


  The facile chemical precipitation method and subsequent thermal treatment
were shown to be suitable for preparation of crystalline ThO2
nanoparticles(NPs) in a wide range of particle sizes (from 2.5 to 34.3 nm). The
obtained NPs were investigated with X-ray diffraction, high-resolution
transmission electron microscopy, and X-ray absorption techniques to find out
the possible size effects associated with nanocrystalline thoria.


  In the present work, the evolution of damage in periodic composite materials
is investigated through a novel finite element-based multiscale computational
approach. The methodology is developed by means of the original combination of
homogenization methods with the phase field approach of fracture. This last is
applied at the macroscale level on the equivalent homogeneous continuum, whose
constitutive properties are obtained in closed form via a two-scale asymptotic
homogenization scheme. The formulation allows considering different assumptions
on the evolution of damage at the microscale (e.g., damage in the matrix and
not in the inclusion/fiber), as well as the role played by the microstructural
topology. Numerical results show that the proposed formulation leads to an
apparent tensile strength and a post-peak branch of unnotched and notched
specimens dependent not only on the internal length scale of the phase field
approach, as for homogeneous materials, but also on the inclusion volumetric
content and its shape. Down-scaling relations allow the full reconstruction of
the microscopic fields at any point of the macroscopic model, as a simple
post-processing operation.


  In past years, the world has switched to many-core and multi-core shared
memory architectures. As a result, there is a growing need to utilize these
architectures by introducing shared memory parallelization schemes to software
applications. OpenMP is the most comprehensive API that implements such
schemes, characterized by a readable interface. Nevertheless, introducing
OpenMP into code is challenging due to pervasive pitfalls in management of
parallel shared memory. To facilitate the performance of this task, many
source-to-source (S2S) compilers have been created over the years, tasked with
inserting OpenMP directives into code automatically. In addition to having
limited robustness to their input format, these compilers still do not achieve
satisfactory coverage and precision in locating parallelizable code and
generating appropriate directives. In this work, we propose leveraging recent
advances in ML techniques, specifically in natural language processing (NLP),
to replace S2S compilers altogether. We create a database (corpus), Open-OMP,
specifically for this goal. Open-OMP contains over 28,000 code snippets, half
of which contain OpenMP directives while the other half do not need
parallelization at all with high probability. We use the corpus to train
systems to automatically classify code segments in need of parallelization, as
well as suggest individual OpenMP clauses. We train several transformer models,
named PragFormer, for these tasks, and show that they outperform
statistically-trained baselines and automatic S2S parallelization compilers in
both classifying the overall need for an OpenMP directive and the introduction
of private and reduction clauses.
  Our source code and database are available at:
https://github.com/Scientific-Computing-Lab-NRCN/PragFormer.


  In this paper, we describe the approach and results for our participation in
the task 1 (multilingual information extraction) of the CLEF eHealth 2018
challenge. We addressed the task of automatically assigning ICD-10 codes to
French death certificates. We used a dictionary-based approach using materials
provided by the task organizers. The terms of the ICD-10 terminology were
normalized, tokenized and stored in a tree data structure. The Levenshtein
distance was used to detect typos. Frequent abbreviations were detected by
manually creating a small set of them. Our system achieved an F-score of 0.786
(precision: 0.794, recall: 0.779). These scores were substantially higher than
the average score of the systems that participated in the challenge.


  We present a c-function for spherically symmetric, static and asymptotically
flat solutions in theories of four-dimensional gravity coupled to gauge fields
and moduli. The c-function is valid for both extremal and non-extremal black
holes. It monotonically decreases from infinity and in the static region
acquires its minimum value at the horizon, where it equals the entropy of the
black hole. Higher dimensional cases, involving $p$-form gauge fields, and
other generalisations are also discussed.


  We report experiments on thermally driven convection in an inclined layer of
large aspect ratio in a fluid of Prandtl number $\sigma \approx 1$. We observed
a number of new nonlinear, mostly spatio-temporally chaotic, states. At small
angles of inclination we found longitudinal rolls, subharmonic oscillations,
Busse oscillations, undulation chaos, and crawling rolls. At larger angles, in
the vicinity of the transition from buoyancy- to shear-driven instability, we
observed drifting transverse rolls, localized bursts, and drifting bimodals.
For angles past vertical, when heated from above, we found drifting transverse
rolls and switching diamond panes.


  Is there any theoretical guarantee for the approximation ability of neural
networks? The answer to this question is the "Universal Approximation Theorem
for Neural Networks". This theorem states that a neural network is dense in a
certain function space under an appropriate setting. This paper is a
comprehensive explanation of the universal approximation theorem for
feedforward neural networks, its approximation rate problem (the relation
between the number of intermediate units and the approximation error), and
Barron space in Japanese.


  Monitoring chromospheric and photospheric indexes of magnetic activity can
provide valuable information, especially the interaction between different
parts of the atmosphere and their response to magnetic fields. We extract
chromospheric indexes, S and Rhk+, for 59,816 stars from LAMOST spectra in the
LAMOST-Kepler program, and photospheric index, Reff, for 5575 stars from Kepler
light curves. The log Reff shows positive correlation with log Rhk+. We
estimate the power-law indexes between Reff and Rhk+ for F-, G-, and K-type
stars, respectively. We also confirm the dependence of both chromospheric and
photospheric activity on stellar rotation. Ca II H and K emissions and
photospheric variations generally decrease with increasing rotation periods for
stars with rotation periods exceeding a few days. The power-law indexes in
exponential decay regimes show different characteristics in the two
activity-rotation relations. The updated largest sample including the activity
proxies and reported rotation periods provides more information to understand
the magnetic activity for cool stars.


  Price-based demand response (DR) of heating, ventilating, and
air-conditioning (HVAC) systems is a challenging task, requiring comprehensive
models to represent the building thermal dynamics and game theoretic
interactions among participants. This paper proposes an online learning-based
strategy for a distribution system operator (DSO) to determine optimal
electricity prices, considering the optimal DR of HVAC systems in commercial
buildings. An artificial neural network (ANN) is trained with building energy
data and represented using an explicit set of linear and nonlinear equations,
without physics-based model parameters. An optimization problem for price-based
DR is then formulated using this equation set and repeatedly solved offline,
producing data on optimal DR schedules for various conditions of electricity
prices and building thermal environments. Another ANN is then trained online to
directly predict DR schedules for day-ahead electricity prices, which is
referred to as meta-prediction (MP). By replacing the DR optimization problem
with the MP-enabled ANN, an optimal electricity pricing strategy can be
implemented using a single-level decision-making structure, which is simpler
and more practical than a bi-level one. In simulation case studies, the
proposed single-level strategy is verified to successfully reflect the game
theoretic relations between the DSO and commercial building operators, so that
they effectively exploit the operational flexibility of the HVAC systems to
make the DR application profitable, while ensuring the grid voltage stability
and occupants thermal comfort.


  This paper develops a quasispecies model that incorporates the SOS response.
We consider a unicellular, asexually replicating population of organisms, whose
genomes consist of a single, double-stranded DNA molecule, i.e. one chromosome.
We assume that repair of post-replication mismatched base-pairs occurs with
probability $ \lambda $, and that the SOS response is triggered when the total
number of mismatched base-pairs exceeds $ l_S $. We further assume that the
per-mismatch SOS elimination rate is characterized by a first-order rate
constant $ \kappa_{SOS} $. For a single fitness peak landscape where the master
genome can sustain up to $ l $ mismatches and remain viable, this model is
analytically solvable in the limit of infinite sequence length. The results,
which are confirmed by stochastic simulations, indicate that the SOS response
does indeed confer a fitness advantage to a population, provided that it is
only activated when DNA damage is so extensive that a cell will die if it does
not attempt to repair its DNA.


  In this paper, the coupled fractional Ginzburg-Landau equations are first
time investigated numerically. A linearized implicit finite difference scheme
is proposed. The scheme involves three time levels, is unconditionally stable
and second-order accurate in both time and space variables. The unique
solvability, the unconditional stability and optimal pointwise error estimates
are obtained by using the energy method and mathematical induction. Moreover,
the proposed second-order method can be easily extended into the fourth-order
method by using an average finite difference operator for spatial fractional
derivatives and Richardson extrapolation for time variable. Finally, numerical
results are presented to confirm the theoretical results.


  We argue that the Witten's loop mechanism for the right-handed Majorana
neutrino mass generation identified originally in the SO(10) grand unification
context can be successfully adopted to the class of the simplest flipped SU(5)
models. In such a framework, the main drawback of the SO(10) prototype, in
particular, the generic tension among the gauge unification constraints and the
absolute neutrino mass scale is alleviated and a simple yet potentially
realistic and testable scenario emerges.


  NGST offers unprecedented opportunities for charting the `dark ages' beyond
the limits of the deep optical surveys conducted with HST. An equally important
motivation, however, is a detailed physical understanding of the later stages
of cosmic history including the period 2<z<5 when most galaxies are thought to
assemble and undergo dramatic changes in their star formation rate, chemical
content and, ultimately, their morphological characteristics. An important
question we need to resolve is the extent to which established massive systems
might exist at moderate redshifts. In the context of recent observational and
theoretical progress in this area, I review the role NGST could play in this
redshift range taking into account the likely progress made in the next decade
with the new generation of 8-m class ground-based telescopes


  In this paper, the authors propose a new framework under which a theory of
generalized Besov-type and Triebel-Lizorkin-type function spaces is developed.
Many function spaces appearing in harmonic analysis fall under the scope of
this new framework. Among others, the boundedness of the Hardy-Littlewood
maximal operator or the related vector-valued maximal function on any of these
function spaces is not required to construct these generalized scales of
smoothness spaces. Instead of this, a key idea used in this framework is an
application of the Peetre maximal function. This idea originates from recent
findings in the abstract coorbit space theory obtained by Holger Rauhut and
Tino Ullrich. Under this new setting, the authors establish the boundedness of
pseudo-differential operators based on atomic and molecular characterizations
and also the boundedness of the Fourier multipliers. The characterizations of
these function spaces by means of differences and oscillations are also
established. As further applications of this new framework, the authors
reexamine and polish some existing results for many different scales of
function spaces.


  In this talk I consider forward-jet production at HERA and at the Tevatron as
a probe of the multiple gluon radiation induced by the BFKL evolution.


  Annual luminance maps provide meaningful evaluations for occupants' visual
comfort, preferences, and perception. However, acquiring long-term luminance
maps require labor-intensive and time-consuming simulations or impracticable
long-term field measurements. This paper presents a novel data-driven machine
learning approach that makes annual luminance-based evaluations more efficient
and accessible. The methodology is based on predicting the annual luminance
maps from a limited number of point-in-time high dynamic range imagery by
utilizing a deep neural network (DNN). Panoramic views are utilized, as they
can be post-processed to study multiple view directions. The proposed DNN model
can faithfully predict high-quality annual panoramic luminance maps from one of
the three options within 30 minutes training time: a) point-in-time luminance
imagery spanning 5% of the year, when evenly distributed during daylight hours,
b) one-month hourly imagery generated or collected continuously during daylight
hours around the equinoxes (8% of the year); or c) 9 days of hourly data
collected around the spring equinox, summer and winter solstices (2.5% of the
year) all suffice to predict the luminance maps for the rest of the year. The
DNN predicted high-quality panoramas are validated against Radiance (RPICT)
renderings using a series of quantitative and qualitative metrics. The most
efficient predictions are achieved with 9 days of hourly data collected around
the spring equinox, summer and winter solstices. The results clearly show that
practitioners and researchers can efficiently incorporate long-term
luminance-based metrics over multiple view directions into the design and
research processes using the proposed DNN workflow.


  The majority of solar-type stars reside in multiple systems, especially
binaries. They form in dense cores of molecular clouds that are observed to be
significantly magnetized. Our previous study shows that magnetic braking can
tighten the binary separation during the protostellar mass accretion phase by
removing the angular momentum of the accreting material. Recent numerical
calculations of single star formation have shown that misalignment between the
magnetic field and rotation axis may weaken both magnetic braking and the
associated magnetically driven outflows. These two effects allow for disk
formation even in strongly magnetized cores. Here we investigate the effects of
magnetic field misalignment on the properties of protobinaries. Somewhat
surprisingly, the misaligned magnetic field is more efficient at tightening the
binary orbit compared to the aligned field. The main reason is that the
misalignment weakens the magnetically-driven outflow, which allows more
material to accrete onto the binary. Even though the specific angular momentum
of this inner material is higher than in the aligned case, it is insufficient
to compensate for the additional mass. A corollary of this result is that a
weaker field is required to achieve the same degree of inward migration when
the field is tilted relative to the rotation axis. Large field misalignment
also helps to produce rotationally-supported circumbinary disks even for
relatively strong magnetic fields, by weakening the magnetically-dominated
structure close to the binary. Our result may provide an explanation for the
circumbinary disks detected in recent SMA and ALMA observations.


  Haemorrhaging of the brain is the leading cause of death in people between
the ages of 15 and 24 and the third leading cause of death in people older than
that. Computed tomography (CT) is an imaging modality used to diagnose
neurological emergencies, including stroke and traumatic brain injury. Recent
advances in Deep Learning and Image Processing have utilised different
modalities like CT scans to help automate the detection and segmentation of
brain haemorrhage occurrences. In this paper, we propose a novel implementation
of an architecture consisting of traditional Convolutional Neural Networks(CNN)
along with Graph Neural Networks(GNN) to produce a holistic model for the task
of brain haemorrhage segmentation.GNNs work on the principle of neighbourhood
aggregation thus providing a reliable estimate of global structures present in
images. GNNs work with few layers thus in turn requiring fewer parameters to
work with. We were able to achieve a dice coefficient score of around 0.81 with
limited data with our implementation.


  We simulate a finite system of $N$ confined electrons with inclusion of the
Darwin magnetic interaction in two- and three-dimensions. The lowest energy
states are located using the steepest descent quenching adapted for velocity
dependent potentials. Below a critical density the ground state is a static
Wigner lattice. For supercritical density the ground state has a non-zero
kinetic energy. The critical density decreases with $N$ for exponential
confinement but not for harmonic confinement. The lowest energy state also
depends on the confinement and dimension: an antiferromagnetic cluster forms
for harmonic confinement in two dimensions.


  Motivated by questions in modular representation theory, Carlson,
Friedlander, and the first author introduced the varieties E(r, g) of
r-dimensional abelian p-nilpotent subalgebras of a p-restricted Lie algebra g.
In this paper, we identify the varieties E(r, g) for a reductive restricted Lie
algebra g and r the maximal dimension of an abelian p-nilpotent subalgebra of
g.


  This paper is concerned with the existence of metrics of constant Hermitian
scalar curvature on almost-K\"ahler manifolds obtained as smoothings of a
constant scalar curvature K\"ahler orbifold, with $A_1$ singularities. More
precisely, given such an orbifold that does not admit nontrivial holomorphic
vector fields, we show that an almost-K\"ahler smoothing $(M_\varepsilon,
\omega_\varepsilon)$ admits an almost-K\"ahler structure $(\hat J_\varepsilon,
\hat g_\varepsilon)$ of constant Hermitian curvature. Moreover, we show that
for $\varepsilon>0$ small enough, the $(M_\varepsilon, \omega_\varepsilon)$ are
all symplectically equivalent to a fixed symplectic manifold $(\hat M, \hat
\omega)$ in which there is a surface $S$ homologous to a 2-sphere, such that
$[S]$ is a vanishing cycle that admits a representant that is Hamiltonian
stationary for $\hat g_\varepsilon$.


  We report the discovery of twelve faint Herbig-Haro (HH) objects in LDN 673
found using a novel color-composite imaging method that reveals faint H{\alpha}
emission in complex environments. Follow-up observations in [S II] confirmed
their classification as HH objects. Potential driving sources are identified
from the Spitzer c2d Legacy Program catalog and other infrared observations.
The twelve new HH objects can be divided into three groups: Four are likely
associated with a cluster of eight YSO class I/II IR sources that lie between
them; five are colinear with the T Tauri multiple star system AS 353, and are
likely driven by the same source as HH 32 and HH 332; three are bisected by a
very red source that coincides with an infrared dark cloud. We also provide
updated coordinates for the three components of HH 332. Inaccurate numbers were
given for this object in the discovery paper. The discovery of HH objects and
associated driving sources in this region provides new evidence for star
formation in the Aquila clouds, implying a much larger T Tauri population in a
seldom-studied region.


  When predictions are performative, the choice of which predictor to deploy
influences the distribution of future observations. The overarching goal in
learning under performativity is to find a predictor that has low
\emph{performative risk}, that is, good performance on its induced
distribution. One family of solutions for optimizing the performative risk,
including bandits and other derivative-free methods, is agnostic to any
structure in the performative feedback, leading to exceedingly slow convergence
rates. A complementary family of solutions makes use of explicit \emph{models}
for the feedback, such as best-response models in strategic classification,
enabling faster rates. However, these rates critically rely on the feedback
model being correct. In this work we study a general protocol for making use of
possibly misspecified models in performative prediction, called \emph{plug-in
performative optimization}. We show this solution can be far superior to
model-agnostic strategies, as long as the misspecification is not too extreme.
Our results support the hypothesis that models, even if misspecified, can
indeed help with learning in performative settings.


  In this paper, Hamiltonian and energy preserving reduced-order models are
developed for the rotating thermal shallow water equation (RTSWE) in the
non-canonical Hamiltonian form with the state-dependent Poisson matrix. The
high fidelity full solutions are obtained by discretizing the RTSWE in space
with skew-symmetric finite-differences, that preserve the Hamiltonian
structure. The resulting skew-gradient system is integrated in time with the
energy preserving average vector field (AVF) method. The reduced-order model
(ROM) is constructed in the same way as the full order model (FOM), preserving
the reduced skew-symmetric structure and integrating in time with the AVF
method. Relying on structure-preserving discretizations in space and time and
applying proper orthogonal decomposition (POD) with the Galerkin projection, an
energy preserving reduced order model (ROM) is constructed. The nonlinearities
in the ROM are computed by applying the discrete empirical interpolation (DEIM)
method to reduce the computational cost. The computation of the reduced-order
solutions is accelerated further by the use of tensor techniques. The overall
procedure yields a clear separation of the offline and online computational
cost of the reduced solutions. The accuracy and computational efficiency of the
ROMs are demonstrated for a numerical test problem. Preservation of the energy
(Hamiltonian), and other conserved quantities, i.e. mass, buoyancy, and total
vorticity show that the reduced-order solutions ensure the long-term stability
of the solutions while exhibiting several orders of magnitude computational
speedup over the FOM.


  This paper presents an exact solution to the long wavelength perturbations
for the scalar modes and for a scalar field theory with arbitrary potential.
Locally these modes are coordinate transformations of the homogeneous
background solutions (although non-locally they are not). These solutions are
then used to discuss a couple of recent papers in which such perturbations play
a role.
  Abramo, Brandenberger, and Mukhanov have recently argued that long wavelength
perturbations have the effect of driving the cosmological constant to zero if
the higher order perturbation equation are examined. I argue that this effect
is invisible to any local observer, and thus does not constitute a relaxation
of the cosmological constant in the normal sense of the term.
  Grishchuk has argued that the standard lore on the strength of the
perturbations at the end of inflation is wrong. I discuss the disagreement in
light of the exact long wavelength solutions, and emphasize the importance of
the initial conditions in resolving the disagreement.


  We aim to improve the performance of multi-agent flocking behavior by
quantifying the structural significance of each agent. We designed a confidence
score(ConfScore) to measure the spatial significance of each agent. The score
will be used by an auxiliary controller to refine the velocity of agents. The
agents will be enforced to follow the motion of the leader agents whose
ConfScores are high. We demonstrate the efficacy of the auxiliary controller by
applying it to several existing algorithms including learning-based and
non-learning-based methods. Furthermore, we examined how the auxiliary
controller can help improve the performance under different settings of
communication radius, number of agents and maximum initial velocity.


  A nitrogen-vacancy (NV) center in diamond is a promising sensor for nanoscale
magnetic sensing. Here we report electron spin resonance (ESR) spectroscopy
using a single NV center in diamond. First, using a 230 GHz ESR spectrometer,
we performed ensemble ESR of a type-Ib sample crystal and identified a
substitutional single nitrogen impurity as a major paramagnetic center in the
sample crystal. Then, we carried out free-induction decay and spin echo
measurements of the single NV center to study static and dynamic properties of
nanoscale bath spins surrounding the NV center. We also measured ESR spectrum
of the bath spins using double electron-electron resonance spectroscopy with
the single NV center. The spectrum analysis of the NV-based ESR measurement
identified that the detected spins are the nitrogen impurity spins. The
experiment was also performed with several other single NV centers in the
diamond sample and demonstrated that the properties of the bath spins are
unique to the NV centers indicating the probe of spins in the microscopic
volume using NV-based ESR. Finally, we discussed the number of spins detected
by the NV-based ESR spectroscopy. By comparing the experimental result with
simulation, we estimated the number of the detected spins to be $\leq$ 50
spins.


  Digital forensic evidence acquisition speed is traditionally limited by two
main factors: the read speed of the storage device being investigated, i.e.,
the read speed of the disk, memory, remote storage, mobile device, etc.), and
the write speed of the system used for storing the acquired data. Digital
forensic investigators can somewhat mitigate the latter issue through the use
of high-speed storage options, such as networked RAID storage, in the
controlled environment of the forensic laboratory. However, traditionally,
little can be done to improve the acquisition speed past its physical read
speed from the target device itself. The protracted time taken for data
acquisition wastes digital forensic experts' time, contributes to digital
forensic investigation backlogs worldwide, and delays pertinent information
from potentially influencing the direction of an investigation. In a remote
acquisition scenario, a third contributing factor can also become a detriment
to the overall acquisition time - typically the Internet upload speed of the
acquisition system. This paper explores an alternative to the traditional
evidence acquisition model through the leveraging of a forensic data
deduplication system. The advantages that a deduplicated approach can provide
over the current digital forensic evidence acquisition process are outlined and
some preliminary results of a prototype implementation are discussed.


  Machine Learning (ML) techniques are becoming an invaluable support for
network intrusion detection, especially in revealing anomalous flows, which
often hide cyber-threats. Typically, ML algorithms are exploited to
classify/recognize data traffic on the basis of statistical features such as
inter-arrival times, packets length distribution, mean number of flows, etc.
Dealing with the vast diversity and number of features that typically
characterize data traffic is a hard problem. This results in the following
issues: i) the presence of so many features leads to lengthy training processes
(particularly when features are highly correlated), while prediction accuracy
does not proportionally improve; ii) some of the features may introduce bias
during the classification process, particularly those that have scarce relation
with the data traffic to be classified. To this end, by reducing the feature
space and retaining only the most significant features, Feature Selection (FS)
becomes a crucial pre-processing step in network management and, specifically,
for the purposes of network intrusion detection. In this review paper, we
complement other surveys in multiple ways: i) evaluating more recent datasets
(updated w.r.t. obsolete KDD 99) by means of a designed-from-scratch
Python-based procedure; ii) providing a synopsis of most credited FS approaches
in the field of intrusion detection, including Multi-Objective Evolutionary
techniques; iii) assessing various experimental analyses such as feature
correlation, time complexity, and performance. Our comparisons offer useful
guidelines to network/security managers who are considering the incorporation
of ML concepts into network intrusion detection, where trade-offs between
performance and resource consumption are crucial.


  Several algorithms have been developed over the years to perform join
operation which is executed frequently and affects the efficiency of the
database system. Some of these efforts prove that join performance mainly
depends on the sequences of execution of relations in addition to the hardware
architecture. In this paper, we present a method that processes a many-to-many
multi join operation by using a non-recursive reverse polish notation tree for
sort-merge join. Precisely, this paper sheds more light on main memory join
operation of two types of sort-merge join sequences: sequential join sequences
(linear tree) and general join sequences (wide bushy tree, also known as
composite inner) and also tests their performance and functionality. We will
also provide the algorithm of the proposed system that shows the implementation
steps.


  We consider a recent proposal [1] to redefine the kilogram in terms of
natural constants. In our opinion, the main objective of the redefinition
should be to build such a version of the SI system in which the electric
measurements are possible with the highest accuracy in SI units, and not in
practical units as now. We emphasize that this objective can be achieved only
with a simultaneous redefinition of the kilogram and ampere. This redefinition
must be in terms of fixed values of the Planck constant h and the elementary
charge e. Certain details of the possible redefinition are considered.


  In this paper we consider an ergodic diffusion process with jumps whose drift
coefficient depends on an unknown parameter $\theta$. We suppose that the
process is discretely observed at the instants (t n i)i=0,...,n with $\Delta$n
= sup i=0,...,n--1 (t n i+1 -- t n i) $\rightarrow$ 0. We introduce an
estimator of $\theta$, based on a contrast function, which is efficient without
requiring any conditions on the rate at which $\Delta$n $\rightarrow$ 0, and
where we allow the observed process to have non summable jumps. This extends
earlier results where the condition n$\Delta$ 3 n $\rightarrow$ 0 was needed
(see [10],[24]) and where the process was supposed to have summable jumps.
Moreover, in the case of a finite jump activity, we propose explicit
approximations of the contrast function, such that the efficient estimation of
$\theta$ is feasible under the condition that n$\Delta$ k n $\rightarrow$ 0
where k > 0 can be arbitrarily large. This extends the results obtained by
Kessler [15] in the case of continuous processes. L{\'e}vy-driven SDE,
efficient drift estimation, high frequency data, ergodic properties,
thresholding methods.


  We study a novel set of gravitational field configurations, called "dipolar
zero modes", which give an exactly null contribution to the Einstein action and
are thus candidates to become large fluctuations in the quantized theory. They
are generated by static unphysical sources satisfying (up to terms of order
G^2) the simple condition Int d^3x T_00(x) = 0. We give two explicit examples
of virtual sources: (i) a "mass dipole" consisting of two separated mass
distributions with different signs; (ii) two concentric "+/- shells". The field
fluctuations can be large even at macroscopic scale. There are some, for
instance, which last ~ 1 s or more and correspond to the field generated by a
virtual source with size ~ 1 cm and mass ~ 10^6 g. This appears paradoxical,
for several reasons, both theoretical and phenomenological. We also give an
estimate of possible suppression effects following the addition to the pure
Einstein action of cosmological or R^2 terms.


  The possibility of non-s-wave superconductivity induced by phonons is
investigated using a simple model that is inspired by Sr$_2$RuO$_4$. The model
assumes a two-dimensional electronic structure, a two-dimensional
spin-fluctuation spectrum, and three-dimensional electron-phonon coupling.
Taken separately, each interaction favors formation of spin-singlet pairs (of s
symmetry for the phonon interaction and d$_{x^2-y^2}$ symmetry for the spin
interaction), but in combination, a variety of more unusual singlet and triplet
states are found, depending on the interaction parameters. This may have
important implications for Sr$_2$RuO$_4$, providing a plausible explanation of
how the observed spin fluctuations, which clearly favor d$_{x^2-y^2}$ pairing,
may still be instrumental in creating a superconducting state with a different
(e.g., p-wave) symmetry. It also suggests an interpretation of the large
isotope effect observed in Sr$_2$RuO$_4$. These results indicate that phonons
could play a key role in establishing the order-parameter symmetry in
Sr$_2$RuO$_4$, and possibly in other unconventional superconductors.


  In this survey paper we discuss some tools and methods which are of use in
quasi-Monte Carlo (QMC) theory. We group them in chapters on Numerical
Analysis, Harmonic Analysis, Algebra and Number Theory, and Probability Theory.
We do not provide a comprehensive survey of all tools, but focus on a few of
them, including reproducing and covariance kernels, Littlewood-Paley theory,
Riesz products, Minkowski's fundamental theorem, exponential sums, diophantine
approximation, Hoeffding's inequality and empirical processes, as well as other
tools. We illustrate the use of these methods in QMC using examples.


  In the present paper we introduce a new generating function for outer
billiards in the plane. Using this generating function, we prove the following
rigidity result: if the vicinity of the smooth convex plane curve $\gamma$ of
positive curvature is foliated by continuous curves which are invariant under
outer billiard map, then the curve $\gamma$ must be an ellipse.
  In addition to the new generating function used in the proof, we also
overcome the noncompactness of the phase space by finding suitable weights in
the integral-geometric part of the proof. Thus, we reduce the result to the
Blaschke-Santalo inequality.


  Following our previous paper in the radial case, we consider blow-up type II
solutions to the energy-critical focusing wave equation. Let W be the unique
radial positive stationary solution of the equation. Up to the symmetries of
the equation, under an appropriate smallness assumption, any type II blow-up
solution is asymptotically a regular solution plus a rescaled Lorentz transform
of W concentrating at the origin.


  Many Active Galactic Nuclei (AGN) are surrounded by gas which absorbs the
radiation produced by accretion onto the central black hole and obscures the
nucleus from direct view. The dust component of the gas greatly enhances the
effect of radiation pressure above that for Thomson scattering so that an AGN
which is sub-Eddington for ionized gas in the usual sense can appear
super-Eddington for cold dusty gas. The radiation-pressure enhancement factor
depends on the AGN spectrum but ranges between unity and about 500, depending
on the column density. It means that an AGN for which the absorption is
long-lived should have a column density N_H>5x10^23 lambda cm^-2, where lambda
is its Eddington fraction L_bol/L_Edd, provided that N_H}>5x10^21 cm^-2. We
have compared the distribution of several samples of AGN - local, CDFS and
Lockman Hole - with this expectation and find good agreement. We show that the
limiting enhancement factor can explain the black hole mass - bulge mass
relation and note that the effect of radiation pressure on dusty gas may be a
key component in the feedback of momentum and energy from a central black hole
to a galaxy.


  Let $\mathfrak{L}_1$, $\mathfrak{L}_2$, $\mathfrak{L}_3$ be finite
collections of $L_1$, $L_2$, $L_3$, respectively, lines in $\mathbb{R}^3$, and
$J(\mathfrak{L}_1, \mathfrak{L}_2,\mathfrak{L}_3)$ the set of multijoints
formed by them, i.e. the set of points $x \in \mathbb{R}^3$, each of which lies
in at least one line $l_i \in \mathfrak{L}_i$, for all $i=1,2,3$, such that the
directions of $l_1$, $l_2$ and $l_3$ span $\mathbb{R}^3$. We prove here that
$|J(\mathfrak{L}_1, \mathfrak{L}_2,\mathfrak{L}_3)|\lesssim (L_1L_2L_3)^{1/2}$,
and we extend our results to multijoints formed by real algebraic curves in
$\mathbb{R}^3$ of uniformly bounded degree, as well as by curves in
$\mathbb{R}^3$ parametrised by real univariate polynomials of uniformly bounded
degree. The multijoints problem is a variant of the joints problem, as well as
a discrete analogue of the endpoint multilinear Kakeya problem.


  In this study we analyze the dynamics of the contact list evolution of
millions of users of the Skype communication network. We find that egocentric
networks evolve heterogeneously in time as events of edge additions and
deletions of individuals are grouped in long bursty clusters, which are
separated by long inactive periods. We classify users by their link creation
dynamics and show that bursty peaks of contact additions are likely to appear
shortly after user account creation. We also study possible relations between
bursty contact addition activity and other user-initiated actions like free and
paid service adoption events. We show that bursts of contact additions are
associated with increases in activity and adoption - an observation that can
inform the design of targeted marketing tactics.


  We study the existence of eigenvalues of the generalized Friedrichs model
$H_\mu(p)$, with a rank-one perturbation, depending on parameters $\mu>0$ and
$p\in\mathbb{T}^2$, and found an absolutely convergent expansions for
eigenvalues at $\mu(p)$, the coupling constant threshold. The expansions are
highly dependent on that, whether the threshold $m(p)$ of the essential
spectrum is: $(i)$ neither an threshold eigenvalue nor a threshold resonance;
$(ii)$ a threshold resonance; $(iii)$ an threshold eigenvalue.


  Recently, observations of compact stars have provided new data of high
accuracy which put strong constraints on the high-density behaviour of the
equation of state of strongly interacting matter otherwise not accessible in
terrestrial laboratories. The evidence for neutron stars with high mass (M =2.1
+/- 0.2 M_sun for PSR J0751+1807) and large radii (R > 12 km for RX J1856-3754)
rules out soft equations of state and has provoked a debate whether the
occurence of quark matter in compact stars can be excluded as well. In this
contribution it is shown that modern quantum field theoretical approaches to
quark matter including color superconductivity and a vector meanfield allow a
microscopic description of hybrid stars which fulfill the new, strong
constraints. The deconfinement transition in the resulting stiff hybrid
equation of state is weakly first order so that signals of it have to be
expected due to specific changes in transport properties governing the
rotational and cooling evolution caused by the color superconductivity of quark
matter. A similar conclusion holds for the investigation of quark deconfinement
in future generations of nucleus-nucleus collision experiments at low
temperatures and high baryon densities such as CBM @ FAIR.


  This paper studies the capacity of a class of discrete memoryless
interference channels where interference is defined analogous to that of
Gaussian interference channel with one-sided weak interference. The sum-rate
capacity of this class of channels is determined. As with the Gaussian case,
the sum-rate capacity is achieved by letting the transceiver pair subject to
interference communicate at a rate such that its message can be decoded at the
unintended receiver using single user detection. It is also established that
this class of discrete memoryless interference channels is equivalent in
capacity region to certain degraded interference channels. This allows the
construction of capacity outer-bounds using the capacity regions of associated
degraded broadcast channels. The same technique is then used to determine the
sum-rate capacity of discrete memoryless interference channels with mixed
interference as defined in the paper. The obtained capacity bounds and sum-rate
capacities are used to resolve the capacities of several new discrete
memoryless interference channels.


  This paper introduces a dual input-output parameterization (dual IOP) for the
identification of linear time-invariant systems from closed-loop data. It draws
inspiration from the recent input-output parameterization developed to
synthesize a stabilizing controller. The controller is parameterized in terms
of closed-loop transfer functions, from the external disturbances to the input
and output of the system, constrained to lie in a given subspace. Analogously,
the dual IOP method parameterizes the unknown plant with analogous closed-loop
transfer functions, also referred to as dual parameters. In this case, these
closed-loop transfer functions are constrained to lie in an affine subspace
guaranteeing that the identified plant is \emph{stabilized} by the known
controller. Compared with existing closed-loop identification techniques
guaranteeing closed-loop stability, such as the dual Youla parameterization,
the dual IOP neither requires a doubly-coprime factorization of the controller
nor a nominal plant that is stabilized by the controller. The dual IOP does not
depend on the order and the state-space realization of the controller either,
as in the dual system-level parameterization. Simulation shows that the dual
IOP outperforms the existing benchmark methods.


  Clustering is one of the most common tasks of Machine Learning. In this paper
we examine how ideas from topology can be used to improve clustering
techniques.


  Two-jet event shape distributions, traditionally studied in the language of
perturbative QCD, can be described naturally in soft-collinear effective
theory. In this language, we demonstrate factorization of event shape
distributions into perturbatively-calculable hard and jet functions and
nonperturbative soft functions, and show how the latter contribute universal
shifts to the mean values of various event shape distributions. Violations of
universality in shifts of higher moments can give information on correlations
of energy flow in soft radiation.


  Recently, the Event Horizon Telescope collaboration has reported the first
image of the supermassive black hole Sagittarius in the Galactic Center. We
attempt to test the validity of the no-hair theorem of black holes using this
new shadow observation. Considering the Einstein-Maxwell-klein-Gordon theory
with a minimally-coupled scalar field, we find that our numerical result is
consistent with the prediction of the no-hair theorem. However, we can not rule
out the possibility that black holes with scalar hair may exist in some special
cases.


  Instant-runoff voting (IRV) is used in several countries around the world. It
requires voters to rank candidates in order of preference, and uses a counting
algorithm that is more complex than systems such as first-past-the-post or
scoring rules. An even more complex system, the single transferable vote (STV),
is used when multiple candidates need to be elected. The complexity of these
systems has made it difficult to audit the election outcomes. There is
currently no known risk-limiting audit (RLA) method for STV, other than a full
manual count of the ballots.
  A new approach to auditing these systems was recently proposed, based on a
Dirichlet-tree model. We present a detailed analysis of this approach for
ballot-polling Bayesian audits of IRV elections. We compared several choices
for the prior distribution, including some approaches using a Bayesian
bootstrap (equivalent to an improper prior). Our findings include that the
bootstrap-based approaches can be adapted to perform similarly to a full
Bayesian model in practice, and that an overly informative prior can give
counter-intuitive results. Via carefully chosen examples, we show why creating
an RLA with this model is challenging, but we also suggest ways to overcome
this.
  As well as providing a practical and computationally feasible implementation
of a Bayesian IRV audit, our work is important in laying the foundation for an
RLA for STV elections.


  Motivated by the works of Wang [Y. Wang, \textit{Lie (Jordan) derivations of
arbitrary triangular algebras,} Aequationes Mathematicae, \textbf{93} (2019),
1221-1229] and Moafian et al. [F. Moafian and H. R. Ebrahimi Vishki,
\textit{Lie higher derivations on triangular algebras revisited,} Filomat,
\textbf{30}(12) (2016), 3187-3194.], we shall study Lie higher derivations of
arbitrary triangular algebras. In fact, it is shown that every Lie higher
derivation on an arbitrary triangular algebra is proper, using the notion of
maximal left (right) ring of quotients.


  The PAMELA satellite has observed an excess in the positron to electron ratio
above theoretical predictions in the range 10 - 100 GeV that increases with
energy. We propose that the excess is not due to a change in the local
interstellar spectrum, but is due to heliospheric modulation. We motivate this
from the known form of the heliospheric magnetic field and predict that the
excess will disappear when we enter a period of solar maximum activity.


  The partition algebras are algebras of diagrams (which contain the group
algebra of the symmetric group and the Brauer algebra) such that the
multiplication is given by a combinatorial rule and such that the structure
constants of the algebra depend polynomially on a parameter. This is a survey
paper which proves the primary results in the theory of partition algebras.
Some of the results in this paper are new. This paper gives: (a) a presentation
of the partition algebras by generators and relations, (b) shows that each
partition algebra has an ideal which is isomorphic to a basic construction and
such that the quotient is isomorphic to the group algebra of the symmetric
gropup, (c) shows that partition algebras are in "Schur-Weyl duality" with the
symmetric groups on tensor space, (d) provides a construction of "Specht
modules" for the partition algebras (integral lattices in the generic
irreducible modules), (e) determines (with a couple of exceptions) the values
of the parameter where the partition algebras are semisimple, (f) provides
"Murphy elements" for the partition algebras that play exactly analogous roles
to the classical Murphy elements for the group algebra of the symmetric group.
The primary new results in this paper are (a) and (f).


  We prove that in the Heisenberg group $\mathbb{H}^1$ with a sub-Finsler
structure, an $(X,Y)$-Lipschitz surface which is complete, oriented, connected
and stable must be a vertical plane. In particular, the result holds for entire
intrinsic graphs of Euclidean Lipschitz functions.


  We discuss supersymmetry breaking induced by simultaneous presence of a
Wilson-line type superpotential and boundary-localized Fayet-Iliopoulos terms
in a four dimensional theory based on deconstruction of five-dimensional
abelian gauge theories on orbifolds. Large hierarchy between the scale of
supersymmetry breaking and the fundamental scale can be generated dynamically.
The model has several potentially interesting phenomenological applications. We
also discuss the conditions that are necessary for interpreting our $U(1)^N$
model as an ultra-violet completion of some 5d theory. In particular, the
corresponding 5d theory contains Chern-Simons couplings.


  It is shown that, if the loss of entanglement along a quantum channel is
sufficiently small, then approximate quantum error correction is possible,
thereby generalizing what happens for coherent information. Explicit bounds are
obtained for the entanglement of formation and the distillable entanglement,
and their validity naturally extends to other bipartite entanglement measures
in between. Robustness of derived criteria is analyzed and their tightness
compared. Finally, as a byproduct, we prove a bound quantifying how large the
gap between entanglement of formation and distillable entanglement can be for
any given finite dimensional bipartite system, thus providing a sufficient
condition for distillability in terms of entanglement of formation.


  Generative Autoregressive Neural Networks (ARNNs) have recently demonstrated
exceptional results in image and language generation tasks, contributing to the
growing popularity of generative models in both scientific and commercial
applications. This work presents an exact mapping of the Boltzmann distribution
of binary pairwise interacting systems into autoregressive form. The resulting
ARNN architecture has weights and biases of its first layer corresponding to
the Hamiltonian's couplings and external fields, featuring widely used
structures such as the residual connections and a recurrent architecture with
clear physical meanings. Moreover, its architecture's explicit formulation
enables the use of statistical physics techniques to derive new ARNNs for
specific systems. As examples, new effective ARNN architectures are derived
from two well-known mean-field systems, the Curie-Weiss and
Sherrington-Kirkpatrick models, showing superior performance in approximating
the Boltzmann distributions of the corresponding physics model compared to
other commonly used architectures. The connection established between the
physics of the system and the neural network architecture provides a means to
derive new architectures for different interacting systems and interpret
existing ones from a physical perspective.


  We report the automatic detection of a new sample of very low surface
brightness (LSB) galaxies, likely members of the Virgo cluster. We introduce
our new software, {\tt DeepScan}, that has been designed specifically to detect
extended LSB features automatically using the DBSCAN algorithm. We demonstrate
the technique by applying it over a 5 degree$^2$ portion of the Next-Generation
Virgo Survey (NGVS) data to reveal 53 low surface brightness galaxies that are
candidate cluster members based on their sizes and colours. 30 of these sources
are new detections despite the region being searched specifically for LSB
galaxies previously. Our final sample contains galaxies with $26.0\leq\langle
\mu_{e}\rangle\leq28.5$ and $19\leq m_{g}\leq21$, making them some of the
faintest known in Virgo. The majority of them have colours consistent with the
red sequence, and have a mean stellar mass of $10^{6.3\pm0.5} M_{\odot}$
assuming cluster membership. After using {\tt ProFit} to fit S\'ersic profiles
to our detections, none of the new sources have effective radii larger than 1.5
Kpc and do not meet the criteria for ultra-diffuse galaxy (UDG) classification,
so we classify them as ultra-faint dwarfs.


  Chart question answering (CQA) is a task used for assessing chart
comprehension, which is fundamentally different from understanding natural
images. CQA requires analyzing the relationships between the textual and the
visual components of a chart, in order to answer general questions or infer
numerical values. Most existing CQA datasets and models are based on
simplifying assumptions that often enable surpassing human performance. In this
work, we address this outcome and propose a new model that jointly learns
classification and regression. Our language-vision setup uses co-attention
transformers to capture the complex real-world interactions between the
question and the textual elements. We validate our design with extensive
experiments on the realistic PlotQA dataset, outperforming previous approaches
by a large margin, while showing competitive performance on FigureQA. Our model
is particularly well suited for realistic questions with out-of-vocabulary
answers that require regression.


  Deep gated convolutional networks have been proved to be very effective in
single channel speech separation. However current state-of-the-art framework
often considers training the gated convolutional networks in time-frequency
(TF) domain. Such an approach will result in limited perceptual score, such as
signal-to-distortion ratio (SDR) upper bound of separated utterances and also
fail to exploit an end-to-end framework. In this paper we present an integrated
simple and effective end-to-end approach to monaural speech separation, which
consists of deep gated convolutional neural networks (GCNN) that takes the
mixed utterance of two speakers and maps it to two separated utterances, where
each utterance contains only one speaker's voice. In addition long short-term
memory (LSTM) is employed for long term temporal modeling. For the objective,
we propose to train the network by directly optimizing utterance level SDR in a
permutation invariant training (PIT) style. Our experiments on the public
WSJ0-2mix data corpus demonstrate that this new scheme can produce more
discriminative separated utterances and leading to performance improvement on
the speaker separation task.


  We study a coupled dark energy scenario in which a massive vector field
$A_{\mu}$ with broken $U(1)$ gauge symmetry interacts with the four-velocity
$u_c^{\mu}$ of cold dark matter (CDM) through the scalar product $Z=-u_c^{\mu}
A_{\mu}$. This new coupling corresponds to the momentum transfer, so that the
background vector and CDM continuity equations do not have explicit interacting
terms analogous to the energy exchange. Hence the observational preference of
uncoupled generalized Proca theories over the $\Lambda$CDM model can be still
maintained at the background level. Meanwhile, the same coupling strongly
affects the evolution of cosmological perturbations. While the effective sound
speed of CDM vanishes, the propagation speed and no-ghost condition of a
longitudinal scalar of $A_{\mu}$ and the CDM no-ghost condition are subject to
nontrivial modifications by the $Z$ dependence in the Lagrangian. We propose a
concrete dark energy model and show that the gravitational interaction on
scales relevant to the linear growth of large-scale structures can be smaller
than the Newton constant at low redshifts. This leads to the suppression of
growth rates of both CDM and total matter density perturbations, so our model
allows an interesting possibility for reducing the tension of matter density
contrast $\sigma_8$ between high- and low-redshift measurements.


  The bar of the Large Magellanic Cloud (LMC) is one of the prominent, but
controversial feature regarding its location with respect to the disk of the
LMC. In order to study the relative location of the bar with respect to the
disk, we present the high resolution map of the structure across the LMC. We
used the reddening corrected mean magnitudes ($I_0$) of red clump (RC) stars
from the OGLE III catalogue to map the relative variation in distance (vertical
structure) or variation in RC population across the LMC. The bar does not
appear as an identifiable vertical feature in the map, as there is no
difference in $I_0$ values between the bar and the disk regions. We conclude
that the LMC bar is very much part of the disk, located in the plane of the
disk (within 0.02 mag) and it is not a separate component. We identify warps or
variation in RC population with increase in radial distance. %The structure map
also suggests a %warp or a different RC population in the eastern part of the
LMC disk.


  The simplest unified extension of the Minimal Supersymmetric Standard Model
with bi-linear R-parity violation naturally predicts a hierarchical neutrino
mass spectrum, suitable to explain atmospheric and solar neutrino fluxes. We
study whether the individual violation of the lepton numbers L_{e,mu,tau} in
the charged sector can lead to measurable rates for BR(mu->e gamma)and
$BR(tau-> mu gamma). We find that some of the R-parity violating terms that are
compatible with the observed atmospheric neutrino oscillations could lead to
rates for mu->e gamma measurable in projected experiments. However, the Delta
m^2_{12} obtained for those parameters is too high to be compatible with the
solar neutrino data, excluding therefore the possibility of having measurable
rates for mu->e gamma in the model.


  Iosevich and Senger (2008) showed that if a subset of the d-dimensional
vector space over a finite field is large enough, then it contains many
k-tuples of mutually orthogonal vectors. In this note, we provide a graph
theoretic proof of this result.


  Superconductivity in small metallic specimens is studied with regard to the
size dependence of the "parity gap" (Delta_P), a parameter distinguishing
between the energy of even and odd number of electrons in the granule. Delta_P
is shown to be an increasing function of level spacing delta. The energy gap of
superconductor Delta, on the other hand, decreases with increasing delta and
vanishes at delta=delta_c which is of the order of Delta. However, nonzero
value of Delta_P persists above delta_c in a "gapless"
superconducting-insulating state. Level degeneracy in small specimens having
perfect geometry changes the size dependence of the parity gap, the Josephson
effect, and flux quantization. Parity gap is evaluated using an interpolation
procedure between the continuum limit (delta<<Delta), the moderate mesoscopic
regime (delta ~ Delta), and the nanoscopic scale (delta>>Delta), for which an
exact solution to the pairing problem is provided with the numeric
diagonalization of system Hamiltonian in a small metallic cluster.


  We derive a formula for the $\bar\mu$-invariant of a Seifert fibered homology
sphere in terms of the eta-invariant of its Dirac operator. As a consequence,
we obtain a vanishing result for the index of certain Dirac operators on
plumbed 4-manifolds bounding such spheres.


  We report the observation of tens of minor lines of the combinational
spin-flip Raman scattering in a CdTe:Mn quantum well by means of the
high-resolution optical spectroscopy. Classification of this manifold leads to
four characteristic values of energy, that correspond to four different types
of pair clusters of Mn ions: the nearest, second, third etc. neighbors. All the
four energies show up in a single experiment with a very high precision,
providing experimental grounds for a deeper understanding of the d-d exchange
interactions in a diluted magnetic semiconductor and demonstrating the capacity
of the employed method. The major (nearest-neighbor) exchange constant J_1 =
6.15 K was found to consent with its previously reported value. Other detected
characteristic energies are as follows: J_{(2)} = 1.80 K, J_{(3)} = 1.39 K,
J_{(4)} = 0.81 K.


  Quantitative information flow (QIF) is traditionally defined as the expected
value of information leakage over all feasible program runs and it fails to
identify vulnerable programs where only limited number of runs leak large
amount of information. As discussed in Bielova (2016), a good notion for
dynamic leakage and an efficient way of computing the leakage are needed. To
address this problem, the authors have already proposed two notions for dynamic
leakage and a method of quantifying dynamic leakage based on model counting.
Inspired by the work of Kawamoto et. al. (2017), this paper proposes two
efficient methods for computing dynamic leakage, a compositional method along
with the sequential structure of a program and a parallel computation based on
the value domain decomposition. For the former, we also investigate both exact
and approximated calculations. From the perspective of implementation, we
utilize binary decision diagrams (BDDs) and deterministic decomposable negation
normal forms (d-DNNFs) to represent Boolean formulas in model counting.
Finally, we show experimental results on several examples.


  Here we present a physically transparent generalization of the multicomponent
Van der Waals equation of state in the grand canonical ensemble. For the
one-component case the third and fourth virial coefficients are calculated
analytically. It is shown that an adjustment of a single model parameter allows
us to reproduce the third and fourth virial coefficients of the gas of hard
spheres with small deviations from their exact values. A thorough comparison of
the compressibility factor and speed of sound of the developed model with the
one and two component Carnahan-Starling equation of state is made. It is shown
that the model with the induced surface tension is able to reproduce the
results of the Carnahan-Starling equation of state up to the packing fractions
0.2-0.22 at which the usual Van der Waals equation of state is inapplicable. At
higher packing fractions the developed equation of state is softer than the gas
of hard spheres and, hence, it breaks causality in the domain where the
hadronic description is expected to be inapplicable. Using this equation of
state we develop an entirely new hadron resonance gas model and apply it to a
description of the hadron yield ratios measured at AGS, SPS, RHIC and ALICE
energies of nuclear collisions. The achieved quality of the fit per degree of
freedom is about 1.08. We confirm that the strangeness enhancement factor has a
peak at low AGS energies, while at and above the highest SPS energy of
collisions the chemical equilibrium of strangeness is observed. We argue that
the chemical equilibrium of strangeness, i.e. $\gamma_s \simeq 1$, observed
above the center of mass collision energy 4.3 GeV may be related to the
hadronization of quark gluon bags which have the Hagedorn mass spectrum, and,
hence, it may be a new signal for the onset of deconfinement.


  The increasing adoption of WebAssembly (Wasm) for performance-critical and
security-sensitive tasks drives the demand for WebAssembly program
comprehension and reverse engineering. Recent studies have introduced machine
learning (ML)-based WebAssembly reverse engineering tools. Yet, the
generalization of task-specific ML solutions remains challenging, because their
effectiveness hinges on the availability of an ample supply of high-quality
task-specific labeled data. Moreover, previous works overlook the high-level
semantics present in source code and its documentation. Acknowledging the
abundance of available source code with documentation, which can be compiled
into WebAssembly, we propose to learn representations of them concurrently and
harness their mutual relationships for effective WebAssembly reverse
engineering.
  In this paper, we present WasmRev, the first multi-modal pre-trained language
model for WebAssembly reverse engineering. WasmRev is pre-trained using
self-supervised learning on a large-scale multi-modal corpus encompassing
source code, code documentation and the compiled WebAssembly, without requiring
labeled data. WasmRev incorporates three tailored multi-modal pre-training
tasks to capture various characteristics of WebAssembly and cross-modal
relationships. WasmRev is only trained once to produce general-purpose
representations that can broadly support WebAssembly reverse engineering tasks
through few-shot fine-tuning with much less labeled data, improving data
efficiency. We fine-tune WasmRev onto three important reverse engineering
tasks: type recovery, function purpose identification and WebAssembly
summarization. Our results show that WasmRev pre-trained on the corpus of
multi-modal samples establishes a robust foundation for these tasks, achieving
high task accuracy and outperforming the state-of-the-art ML methods for
WebAssembly reverse engineering.


  The magnetic properties of dilute Li$_2$(Li$_{1-x}$Fe$_x$)N with $x \sim
0.001$ are dominated by the spin of single, isolated Fe atoms. Below $T = 10$ K
the spin-relaxation times become temperature-independent indicating a crossover
from thermal excitations to the quantum tunneling regime. We report on a strong
increase of the spin-flip probability in $\textit{transverse}$ magnetic fields
that proves the resonant character of this tunneling process.
$\textit{Longitudinal}$ fields, on the other hand, lift the ground-state
degeneracy and destroy the tunneling condition. An increase of the relaxation
time by four orders of magnitude in applied fields of only a few milliTesla
reveals exceptionally sharp tunneling resonances. Li$_2$(Li$_{1-x}$Fe$_x$)N
represents a comparatively simple and clean model system that opens the
possibility to study quantum tunneling of the magnetization at liquid helium
temperatures.


  We perform systematic simulation experiments on model systems with
soft-sphere repulsive interactions to test the predicted dynamic equivalence
between soft-sphere liquids with similar static structure. For this we compare
the simulated dynamics (mean squared displacement, intermediate scattering
function, {\alpha}-relaxation time, etc.) of different soft-sphere systems,
between them and with the hard-sphere liquid. We then show that the referred
dynamic equivalence does not depend on the (Newtonian or Brownian) nature of
the microscopic laws of motion of the constituent particles, and hence, applies
independently to colloidal and to atomic simple liquids. In addition, we verify
another more recently-proposed dynamic equivalence, this time between the
long-time dynamics of a Brownian fluid and its corresponding atomic liquid
(i.e., the atomic system with the same interaction potential).


  We report on sytematic measurements of the low frequency conductivity in
aequous supensions of highly charged colloidal spheres. System preparation in a
closed tubing system results in precisely controlled number densities between
1E16/m3 and 1E19/m^3 (packing fractions between 1E-7 and 1E-2) and electrolyte
concentrations between 1E-7 and 1E-3 mol/l. Due to long ranged Coulomb
repulsion some of the systems show a pronounced fluid or crystalline order.
Under deionized conditions we find s to depend linearily on the packing
fraction with no detectable influence of the phase transitions. Further at
constant packing fraction s increases sublinearily with increasing number of
dissociable surface groups N. As a function of c the conductivity shows
pronounced differences depending on the kind of electrolyte used. We propose a
simple yet powerful model based on independent migration of all species present
and additivity of the respective conductivity contributions. It takes account
of small ion macro-ion interactions in terms of an effectivly transported
charge. The model successfully describes our qualitatively complex experimental
observations. It further facilitates quantitative estimates of conductivity
over a wide range of particle and experimental parameters.


  In emergency situations, the high-speed movement of an ambulance through the
city streets can be hindered by vehicular traffic. This work presents a method
for detecting emergency vehicle sirens in real time. To obtain the audio
fingerprint of a Hi-Lo siren, DSP and signal symbolization techniques were
applied, which were contrasted against an audio classifier based on a deep
neural network, using the same 280 audios of ambient sounds and 52 Hi-Lo siren
audios dataset. In both methods, some classification accuracy metrics were
evaluated based on its confusion matrix, resulting in the DSP algorithm having
a slightly lower accuracy than the DNN model, however, it offers a
self-explanatory, adjustable, portable, high performance and lower energy and
consumption that makes it a more viable lower cost ADAS implementation to
identify Hi-Lo sirens in real time.


  We prove that the free uniform spanning forest of any bounded degree proper
plane graph is connected almost surely, answering a question of Benjamini,
Lyons, Peres and Schramm.
  We provide a quantitative form of this result, calculating the critical
exponents governing the geometry of the uniform spanning forests of transient
proper plane graphs with bounded degrees and codegrees. We find that the same
exponents hold universally over this entire class of graphs provided that
measurements are made using the hyperbolic geometry of their circle packings
rather than their usual combinatorial geometry.


  This paper addresses the trajectory-tracking problem for a class of
electromechanical systems. To this end, the dynamics of the plants are modeled
in the so-called port-Hamiltonian framework. Then, the notion of contraction is
exploited to design the desired closed-loop dynamics and the corresponding
tracking controller. Notably, the proposed control design method does not
require solving partial differential equations or changing the coordinates of
the plant, which permits preserving the physical interpretation of the
controller. The applicability of the proposed approach is illustrated in
several electromechanical systems via simulations.


  Understanding dissipative and decohering processes is fundamental to the
study of quantum systems. An accurate and generic method for investigating
these processes is to simulate both the system and environment, which, however,
is computationally very demanding. We develop a novel approach to constructing
finite representations of the environment based on the influence of different
frequency scales on the system's dynamics. As an illustration, we analyze a
solvable model of an optical mode decaying into a reservoir. The influence of
the environment modes is constant for small frequencies, but drops off rapidly
for large frequencies, allowing for a very sparse representation at high
frequencies that gives a significant computational speedup in simulating the
environment. This approach provides a general framework for simulating open
quantum systems.


  The binary many-step Markov chain with the step-like memory function is
considered as a model for the analysis of rank distributions of words in
stochastic symbolic dynamical systems. We prove that the envelope curve for
this distribution obeys the power law with the exponent of the order of unity
in the case of rather strong persistent correlations. The Zipf law is shown to
be valid for the rank distribution of words with lengths about and shorter than
the correlation length in the Markov sequence. A self-similarity in the rank
distribution with respect to the decimation procedure is observed.


  We propose a post-selection technique, based on quantum error detection, for
quantum key distribution (QKD) systems that run over quantum repeaters with
encoding. In such repeaters, quantum error correction techniques are used for
entanglement distillation. By developing an analytical approach to study such
quantum repeaters, we show that, in the context of QKD, it is often more
efficient to use the error detection, rather than the error correction,
capability of the underlying code to sift out cases where an error has been
detected. We implement our technique for three-qubit repetition codes by
modelling different sources of error in crucial components of the system. We
then investigate in detail the impact of such imperfections on the secret key
generation rate of the QKD system, and how one can use the information obtained
during entanglement swapping and decoding stages to maximize the rate. For
benchmarking purposes, we specify the maximum allowed error rates in different
components of the setup below which positive key rates can be obtained.


  In this paper, we make a detailed study on the production of the $B_c$,
$B_c^*$, $B_c(2\,^1S_0)$, and $B^*_c(2\,^3S_1)$ mesons via the three planned
running modes ($Z$, $W$, and $H$) at the future Circular Electron-Positron
Collider (CEPC). The fragmentation-function and full nonrelativistic QCD
approaches are adopted to calculate the production cross sections. Considering
the excited states shall decay to the ground $B_c$ state (e.g. $1^1S_0$-state)
with almost $100\%$ probability, our numerical results show that up to
next-to-leading order QCD corrections, there are about $1.4\times 10^8$ $B_c$
events to be accumulated via the $Z$ mode ($\sqrt{s}=m_{_Z}$) of the CEPC, but
only about $1.6\times 10^4$ and $1.1\times 10^4$ $B_c$ events to be accumulated
via the $W$ ($\sqrt{s}=160\,{\rm GeV}$) and $H$ ($\sqrt{s}=240\,{\rm GeV}$)
modes, respectively. Since the $Z$ mode is the best mode among the three
planned modes of the CEPC for studying the production of the $B_c$, $B_c^*$,
$B_c(2\,^1S_0)$, and $B^*_c(2\,^3S_1)$ mesons and the differential
distributions of these mesons may be measured precisely at this mode, we
further present the differential cross sections $d\sigma/(dz\,d{\rm
cos}\theta)$ and $d\sigma/dz$ via the $Z$ mode of the CEPC.


  Determining how galactic environment, especially the high gas densities and
complex dynamics in bar-fed galaxy centers, alters the star formation
efficiency (SFE) of molecular gas is critical to understanding galaxy
evolution. However, these same physical or dynamical effects also alter the
emissivity properties of CO, leading to variations in the CO-to-H$_2$
conversion factor ($\alpha_\rm{CO}$) that impact the assessment of the gas
column densities and thus of the SFE. To address such issues, we investigate
the dependence of $\alpha_\rm{CO}$ on local CO velocity dispersion at 150-pc
scales using a new set of dust-based $\alpha_\rm{CO}$ measurements, and propose
a new $\alpha_\rm{CO}$ prescription that accounts for CO emissivity variations
across galaxies. Based on this prescription, we estimate the SFE in a sample of
65 galaxies from the PHANGS-ALMA survey. We find increasing SFE towards high
surface density regions like galaxy centers, while using a constant or
metallicity-based $\alpha_\rm{CO}$ results in a more homogeneous SFE throughout
the centers and disks. Our prescription further reveals a mean molecular gas
depletion time of 700 Myr in the centers of barred galaxies, which is overall
3-4 times shorter than in non-barred galaxy centers or the disks. Across the
galaxy disks, the depletion time is consistently around 2-3 Gyr regardless of
the choice of $\alpha_\rm{CO}$ prescription. All together, our results suggest
that the high level of star formation activity in barred centers is not simply
due to an increased amount of molecular gas but also an enhanced SFE compared
to non-barred centers or disk regions.


  We consider the degenerate parabolic equation with nonlocal source given by
\[ u_t=u\Delta u + u \int_{\mathbb{R}^n} |\nabla u|^2, \] which has been
proposed as model for the evolution of the density distribution of frequencies
with which different strategies are pursued in a population obeying the rules
of replicator dynamics in a continuous infinite-dimensional setting. Firstly,
for all positive initial data $u_0\in C^0(\mathbb{R}^n)$ satisfying $u_0\in
L^p(\mathbb{R}^n)$ for some $p\in (0,1)$ as well as $\int_{\mathbb{R}^n}
u_0=1$, the corresponding Cauchy problem in $\mathbb{R}^n$ is seen to possess a
global positive classical solution with the property that $\int_{\mathbb{R}^n}
u(\cdot,t)=1$ for all $t>0$. Thereafter, the main purpose of this work consists
in revealing a dependence of the large time behavior of these solutions on the
spatial decay of the initial data in a direction that seems unexpected when
viewed against the background of known behavior in large classes of scalar
parabolic problems. In fact, it is shown that all considered solutions
asymptotically decay with respect to their spatial $H^1$ norm, so that \[
\mathcal{E}(t):=\int_0^t \int_{\mathbb{R}^n} |\nabla u(\cdot,t)|^2, \qquad t>0,
\] always grows in a significantly sublinear manner in that \begin{equation}
\frac{\mathcal{E}(t)}{t} \to 0 \qquad \mbox{as } t\to\infty; \qquad (*)
\end{equation} the precise growth rate of $\mathcal{E}$, however, depends on
the initial data in such a way that fast decay rates of $u_0$ enforce rapid
growth of $\mathcal{E}$. To this end, examples of algebraical and certain
exponential types of initial decay are detailed, inter alia generating
logarithmic and arbitrary sublinear algebraic growth rates of $\mathcal{E}$,
and moreover indicating that (*) is essentially optimal.


  The observed radial and transverse velocities of individual stars in M15 are
implemented as inputs to a fully non-parametric code (CHASSIS) in order to
estimate the equilibrium stellar distribution function and the
three-dimensional mass density profile. In particular, the paper explores the
possibility of the existence of a central black hole in M15 via several runs
that utilize the radial velocity data set which offers kinematic measurements
closer to the centre of the cluster than the proper motion data. These runs are
distinguished from each other in the choice of the initial seed for the cluster
characteristics; however, the profiles identified by the algorithm at the end
of each run concur with each other, within error bars, thus confirming the
robustness of CHASSIS. The recovered density profiles are noted to exhibit
unequivocal flattening, inner to about 0.0525pc. Also, the enclosed mass
profile is very close to being a power-law function of radius inside 0.1pc and
is not horizontal. Simplistically speaking, these trends negate the possibility
of the central mass to be concentrated in a black hole, the lower bound on the
radius of the sphere of influence of which would be $\gtrsim$0.041pc, had it
existed. However, proper analysis suggests that the mass enclosed within the
inner 0.01pc could be in the form of a black hole of mass
$\sim{10^3}$M$_{\odot}$, under two different scenarios, which are discussed.
The line-of-sight velocity dispersion is visually found to be very similar to
the observed dispersion profile. The enclosed mass and velocity dispersion
profiles calculated from runs done with the proper motion data are found to be
consistent with the profiles obtained with the radial velocity data.


  With the shrinking of technology nodes and the use of parallel processor
clusters in hostile and critical environments, such as space, run-time faults
caused by radiation are a serious cross-cutting concern, also impacting
architectural design. This paper introduces an architectural approach to
run-time configurable soft-error tolerance at the core level, augmenting a
six-core open-source RISC-V cluster with a novel On-Demand Redundancy Grouping
(ODRG) scheme. ODRG allows the cluster to operate either as two fault-tolerant
cores, or six individual cores for high-performance, with limited overhead to
switch between these modes during run-time. The ODRG unit adds less than 11% of
a core's area for a three-core group, or a total of 1% of the cluster area, and
shows negligible timing increase, which compares favorably to a commercial
state-of-the-art implementation, and is 2.5$\times$ faster in fault recovery
re-synchronization. Furthermore, when redundancy is not necessary, the ODRG
approach allows the redundant cores to be used for independent computation,
allowing up to 2.96$\times$ increase in performance for selected applications.


  We determine the Dehn functions of central products of two families of
filiform nilpotent Lie groups of arbitrary dimension with all simply connected
nilpotent Lie groups with cyclic centre and strictly lower nilpotency class. We
also determine the Dehn functions of all central products of nilpotent Lie
groups of dimension at most $5$ with one-dimensional centre. This confirms a
conjecture of Llosa Isenrich, Pallier and Tessera for these cases, providing
further evidence that the Dehn functions of central products are often strictly
lower than those of the factors. Our work generalises previous results of Llosa
Isenrich, Pallier and Tessera and produces an uncountable family of nilpotent
Lie groups without lattices whose Dehn functions are strictly lower than the
ones of the associated Carnot-graded groups. A consequence of our main result
is the existence of an infinite family of groups such that Cornulier's bounds
on the $e$ for which there is an $O(r^e)$-bilipschitz equivalence between them
and their Carnot-graded groups are asymptotically optimal, as the nilpotency
class goes to infinity.


  We propose a robust and efficient approach for tripartite-to-bipartite
entanglement localization. By using weak measurements and quantum measurement
reversal, an almost maximal entangled state shared by two parties can be
generated with the assistance of the third party by local quantum operations
and classical communication from a W-like state. We show that this approach
works well in the presence of losses and phase diffusion. Our method provides
an active way to fight against decoherence, and might help for quantum
communication and distributed quantum computation.


  The Indyk-Motwani Locality-Sensitive Hashing (LSH) framework (STOC 1998) is a
general technique for constructing a data structure to answer approximate near
neighbor queries by using a distribution $\mathcal{H}$ over locality-sensitive
hash functions that partition space. For a collection of $n$ points, after
preprocessing, the query time is dominated by $O(n^{\rho} \log n)$ evaluations
of hash functions from $\mathcal{H}$ and $O(n^{\rho})$ hash table lookups and
distance computations where $\rho \in (0,1)$ is determined by the
locality-sensitivity properties of $\mathcal{H}$. It follows from a recent
result by Dahlgaard et al. (FOCS 2017) that the number of locality-sensitive
hash functions can be reduced to $O(\log^2 n)$, leaving the query time to be
dominated by $O(n^{\rho})$ distance computations and $O(n^{\rho} \log n)$
additional word-RAM operations. We state this result as a general framework and
provide a simpler analysis showing that the number of lookups and distance
computations closely match the Indyk-Motwani framework, making it a viable
replacement in practice. Using ideas from another locality-sensitive hashing
framework by Andoni and Indyk (SODA 2006) we are able to reduce the number of
additional word-RAM operations to $O(n^\rho)$.


  The electronic structure and intrinsic anomalous Hall conductivity of nickel
have been calculated based on the generalized gradient approximation (GGA) plus
on-site Coulomb interaction (GGA+U) scheme. It is found that the intrinsic
anomalous Hall conductivity ($\sigma_{xy}^H$) obtained from the GGA+U
calculations with $U = 1.9$ eV and $J=1.2$ eV, is in nearly perfect agreement
with that measured recently at low temperatures while, in contrast, the
$\sigma_{xy}^H$ from the GGA calculations is about 100% larger than the
measured one. This indicates that, as for the other spin-orbit interaction
(SOI)-induced phenomena in 3$d$ itinerant magnets such as the orbital magnetic
magnetization and magnetocrystalline anisotropy, the on-site electron-electron
correlation, though moderate only, should be taken into account properly in
order to get the correct anomalous Hall conductivity. The intrinsic
$\sigma_{xy}^H$ and the number of valence electrons ($N_e$) have also been
calculated as a function of the Fermi energy ($E_F$). A sign change is
predicted at $E_F = -0.38$ eV ($N_e = 9.57$), and this explain qualitatively
why the theoretical and experimental $\sigma_{xy}^H$ values for Fe and Co are
positive. It is also predicted that fcc Ni$_{(1-x)}$Co(Fe,Cu)$_x$ alloys with
$x$ being small, would also have the negative $\sigma_{xy}^H$ with the
magnitude being in the range of $500\sim 1400$ $\Omega^{-1}$cm$^{-1}$. The most
pronounced effect of including the on-site Coulomb interaction is that all the
$d$-dominant bands are lowered in energy relative to the $E_F$ by about 0.3 eV,
and consequently, the small minority spin X$_2$ hole pocket disappears. The
presence of the small X$_2$ hole pocket in the GGA calculations is attributed
to be responsible for the large discrepancy in the $\sigma_{xy}^H$ between
theory and experiment.


  Using a Markov duality satisfied by ASEP on the integer line, we deduce a
similar Markov duality for half-line open ASEP and open ASEP on a segment. This
leads to closed systems of ODEs characterizing observables of the models. In
the half-line case, we solve the system of ODEs using Bethe ansatz and prove an
integral formula for $q$-moments of the current at $n$ distinct spatial
locations. We then use this formula to confirm predictions for the moments of
the multiplicative noise stochastic heat equation on $\mathbb R_{>0}$ with
Robin type boundary condition and we obtain new formulas in the case of a
Dirichlet boundary condition.


  Expressions for Sudakov form factors for heavy quarks are presented. They are
used to construct resummed jet rates in electron-positron annihilation.
Predictions are given for production of bottom quarks at LEP and top quarks at
the Linear Collider.


  We explain some simple methods to establish the property of Rapid Decay for a
number of groups arising geometrically. We also give new examples of groups
with the property of Rapid Decay. In particular we establish the property of
Rapid Decay for all lattices in rank one Lie groups.