  Given any genus-two, hyperbolic, fibered knot in $S^3$ with nonzero
fractional Dehn twist coefficient, we show that its pseudo-Anosov
representative has a fixed point. Combined with recent work of
Baldwin--Hu--Sivek, this proves that knot Floer homology detects the cinquefoil
knot $T(2,5)$, and that the cinquefoil is the only genus-two L-space knot in
$S^3$. Our results have applications to Floer homology of cyclic branched
covers over knots in $S^3$, to $\mathit{SU}(2)$-abelian Dehn surgeries, and to
Khovanov and annular Khovanov homology. Along the way to proving our fixed
point result, we describe a small list of train tracks carrying all
pseudo-Anosov homeomorphisms in most strata on the punctured disk. As a
consequence, we find a canonical track $\tau$ carrying all pseudo-Anosov
homeomorphisms in a particular stratum $\mathcal{Q}_0$ on the genus-two
surface, and describe every fixed-point-free pseudo-Anosov homeomorphism in
$\mathcal{Q}_0$.


  Broad Fe II emission is a prominent feature of the optical and ultraviolet
spectra of quasars. We report on a systematical investigation of optical Fe II
emission in a large sample of 4037 z < 0.8 quasars selected from the Sloan
Digital Sky Survey. We have developed and tested a detailed line-fitting
technique, taking into account the complex continuum and narrow and broad
emission-line spectrum. Our primary goal is to quantify the velocity broadening
and velocity shift of the Fe II spectrum in order to constrain the location of
the Fe II-emitting region and its relation to the broad-line region. We find
that the majority of quasars show Fe II emission that is redshifted, typically
by ~ 400 km/s but up to 2000 km/s, with respect to the systemic velocity of the
narrow-line region or of the conventional broad-line region as traced by the
Hbeta line. Moreover, the line width of Fe II is significantly narrower than
that of the broad component of Hbeta. We show that the magnitude of the Fe II
redshift correlates inversely with the Eddington ratio, and that there is a
tendency for sources with redshifted Fe II emission to show red asymmetry in
the Hbeta line. These characteristics strongly suggest that Fe II originates
from a location different from, and most likely exterior to, the region that
produces most of Hbeta. The Fe II-emitting zone traces a portion of the
broad-line region of intermediate velocities whose dynamics may be dominated by
infall.


  Atomic ions confined in multi-electrode traps have been proposed as a basis
for scalable quantum information processing. This scheme involves transporting
ions between spatially distinct locations by use of time-varying electric
potentials combined with laser or microwave pulses for quantum logic in
specific locations. We report the development of a fast multi-channel arbitrary
waveform generator for applying the time-varying electric potentials used for
transport and for shaping quantum logic pulses. The generator is based on a
field-programmable gate array controlled ensemble of 16-bit digital-to-analog
converters with an update frequency of 50 MHz and an output range of $\pm$10 V.
The update rate of the waveform generator is much faster than relevant motional
frequencies of the confined ions in our experiments, allowing diabatic control
of the ion motion. Numerous pre-loaded sets of time-varying voltages can be
selected with 40 ns latency conditioned on real-time signals. Here we describe
the device and demonstrate some of its uses in ion-based quantum information
experiments, including speed-up of ion transport and the shaping of laser and
microwave pulses.


  Lifted Kramers spin-degeneracy has been among the central topics of
condensed-matter physics since the dawn of the band theory of solids. It
underpins established practical applications as well as current frontier
research, ranging from magnetic-memory technology to topological quantum
matter. Traditionally, lifted Kramers spin-degeneracy has been considered to
originate from two possible internal symmetry-breaking mechanisms. The first
one refers to time-reversal symmetry breaking by magnetization of ferromagnets,
and tends to be strong due to the non-relativistic exchange-coupling origin.
The second mechanism applies to crystals with broken inversion symmetry, and
tends to be comparatively weaker as it originates from the relativistic
spin-orbit coupling. A recent theory work based on spin-symmetry classification
has identified an unconventional magnetic phase, dubbed altermagnetic, that
allows for lifting the Kramers spin degeneracy without net magnetization and
inversion-symmetry breaking. Here we provide the confirmation using
photoemission spectroscopy and ab initio calculations. We identify two distinct
unconventional mechanisms of lifted Kramers spin degeneracy generated by the
altermagnetic phase of centrosymmetric MnTe with vanishing net magnetization.
Our observation of the altermagnetic lifting of the Kramers spin degeneracy can
have broad consequences in magnetism. It motivates exploration and exploitation
of the unconventional nature of this magnetic phase in an extended family of
materials, ranging from insulators and semiconductors to metals and
superconductors, that have been either identified recently or perceived for
many decades as conventional antiferromagnets.


  Recent works in image captioning have shown very promising raw performance.
However, we realize that most of these encoder-decoder style networks with
attention do not scale naturally to large vocabulary size, making them
difficult to be deployed on embedded system with limited hardware resources.
This is because the size of word and output embedding matrices grow
proportionally with the size of vocabulary, adversely affecting the compactness
of these networks. To address this limitation, this paper introduces a brand
new idea in the domain of image captioning. That is, we tackle the problem of
compactness of image captioning models which is hitherto unexplored. We showed
that, our proposed model, named COMIC for COMpact Image Captioning, achieves
comparable results in five common evaluation metrics with state-of-the-art
approaches on both MS-COCO and InstaPIC-1.1M datasets despite having an
embedding vocabulary size that is 39x - 99x smaller. The source code and models
are available at:
https://github.com/jiahuei/COMIC-Compact-Image-Captioning-with-Attention


  In this paper, we obtain general conditions under which the wave equation is
well-posed in spacetimes with metrics of Lipschitz regularity. In particular,
the results can be applied to spacetimes where there is a loss of regularity on
a hypersurface such as shell-crossing singularities, thin shells of matter and
surface layers. This provides a framework for regarding gravitational
singularities, not as obstructions to the world lines of point-particles, but
rather as an obstruction to the dynamics of test fields.


  This paper is an update of the survey of AI accelerators and processors from
past four years, which is now called the Lincoln AI Computing Survey - LAICS
(pronounced "lace"). As in past years, this paper collects and summarizes the
current commercial accelerators that have been publicly announced with peak
performance and peak power consumption numbers. The performance and power
values are plotted on a scatter graph, and a number of dimensions and
observations from the trends on this plot are again discussed and analyzed.
Market segments are highlighted on the scatter plot, and zoomed plots of each
segment are also included. Finally, a brief description of each of the new
accelerators that have been added in the survey this year is included.


  We introduce a new graph problem, the token dropping game, and we show how to
solve it efficiently in a distributed setting. We use the token dropping game
as a tool to design an efficient distributed algorithm for stable orientations
and more generally for locally optimal semi-matchings. The prior work by
Czygrinow et al. (DISC 2012) finds a stable orientation in $O(\Delta^5)$ rounds
in graphs of maximum degree $\Delta$, while we improve it to $O(\Delta^4)$ and
also prove a lower bound of $\Omega(\Delta)$.


  We discuss current efforts behind the curation of observing proposals,
archive bibliographies, and data links in the NASA Astrophysics Data System
(ADS). The primary data in the ADS is the bibliographic content from scholarly
articles in Astronomy and Physics, which ADS aggregates from publishers, arXiv
and conference proceeding sites. This core bibliographic information is then
further enriched by ADS via the generation of citations and usage data, and
through the aggregation of external resources from astronomy data archives and
libraries. Important sources of such additional information are the metadata
describing observing proposals and high level data products, which, once
ingested in ADS, become easily discoverable and citeable by the science
community. Bibliographic studies have shown that the integration of links
between data archives and the ADS provides greater visibility to data products
and increased citations to the literature associated with them.


  This report gives a summary of two problems about graph convolutional
networks (GCNs): over-smoothing and heterophily challenges, and outlines future
directions to explore.


  We study the spectrum of Andreev bound states and Josephson currents across a
junction of $N$ superconducting wires which may have $s$- or $p$-wave pairing
symmetries and develop a scattering matrix based formalism which allows us to
address transport across such junctions. For $N \ge 3$, it is well known that
Berry curvature terms contribute to the Josephson currents; we chart out
situations where such terms can have relatively large effects. For a system of
three $s$- or three $p$-wave superconductors, we provide analytic expressions
for the Andreev bound state energies and study the Josephson currents in
response to a constant voltage applied across one of the wires; we find that
the integrated transconductance at zero temperature is quantized to integer
multiples of $4e^2/h$, where $e$ is the electron charge and $h = 2\pi \hbar$ is
Planck's constant. For a sinusoidal current with frequency $\omega$ applied
across one of the wires in the junction, we find that Shapiro plateaus appear
in the time-averaged voltage $\langle V_1 \rangle$ across that wire for any
rational fractional multiple (in contrast to only integer multiples in
junctions of two wires) of $2e \langle V_1 \rangle/(\hbar \omega)$. We also use
our formalism to study junctions of two $p$- and one $s$-wave wires. We find
that the corresponding Andreev bound state energies depend on the spin of the
Bogoliubov quasiparticles; this produces a net magnetic moment in such
junctions. The time variation of these magnetic moments may be controlled by an
external applied voltage across the junction. We discuss experiments which may
test our theory.


  We have designed a medium deep large area X-ray survey with XMM - the XMM
Large Scale Structure survey, XMM-LSS - with the scope of extending the
cosmological tests attempted using ROSAT cluster samples to two redshift bins
between 0<z<1 while maintaining the precision of earlier studies. Two main
goals have constrained the survey design: the evolutionary study of the
cluster-cluster correlation function and of the cluster number density. The
results are promising and, so far, in accordance with our predictions as to the
survey sensitivity and cluster number density. The feasibility of the programme
is demonstrated and further X-ray coverage is awaited in order to proceed with
a truly significant statistical analysis. (Abridged)


  We study the natural problem of Triplet Reconstruction (also Rooted Triplets
Consistency or Triplet Clustering), originally motivated in computational
biology and relational databases (Aho, Sagiv, Szymanski, and Ullman, 1981):
given $n$ points, we want to embed them onto the $n$ leaves of a rooted binary
tree (a hierarchical clustering or ultrametric embedding) such that a given set
of $m$ triplet constraints is satisfied. Triplet $ij|k$ indicates that ``$i, j$
are more closely related to each other than to $k$'' and a tree satisfies
$ij|k$ if $d(i,j)$ is the smallest among the 3 distances. Aho et al. (1981)
gave an elegant efficient algorithm to find a tree respecting all constraints
(if it exists) and it is easy to see that a random binary tree is a
1/3-approximation. Unfortunately, despite more than four decades of research,
no better approximation is known.
  Our main theorem--which captures Triplet Reconstruction as a special case--is
a general hardness of approximation result about Constraint Satisfaction
Problems (CSPs) over infinite domains (the variables are mapped to any of the
$n$ leaves of a tree). Specifically, we prove, under Unique Games (Khot, 2002),
that Triplet Reconstruction and more generally, every CSP over hierarchies is
approximation resistant (there is no polynomial-time algorithm that does
asymptotically better than a biased random assignment). This settles the
approximability for many interesting Subtree or Supertree Aggregation Problems.
More broadly, our result significantly extends the list of approximation
resistant predicates and is a generalization of Guruswami, Hastad, Manokaran,
Raghavendra, and Charikar (2011), who showed that ordering CSPs are
approximation resistant. The main challenge in our analyses stems from the fact
that trees have topology which is what determines whether a given triplet
constraint on the leaves is satisfied or not.


  We prove subsequential tightness of centered maxima of two-dimensional
Ginzburg-Landau fields with bounded elliptic contrast.


  In conversation, a person sometimes has to refer to an object that is not
previously known to the other participant. We present a plan-based model of how
agents collaborate on reference of this sort. In making a reference, an agent
uses the most salient attributes of the referent. In understanding a reference,
an agent determines his confidence in its adequacy as a means of identifying
the referent. To collaborate, the agents use judgment, suggestion, and
elaboration moves to refashion an inadequate referring expression.


  In this work, we have extracted the initial tempearture from the transverse
momentum spectra of charged particles in $Au+Au$ collisions using STAR data at
RHIC energies from $\sqrt{s_{NN}}$ = 7.7 to 200 GeV. The initial energy density
($\varepsilon$), shear viscosity to entropy density ratio ($\eta/s$), trace
anomaly ($\Delta$), the squared speed of sound ($C_s^2$), entropy density, and
bulk viscosity to entropy density ratio ($\zeta/s$) are obtained and compared
with the lattice QCD calculations for (2+1) flavor. The initial temperatures
obtained are compared with various hadronization and chemical freeze-out
temperatures. The analysis of the data shows that the deconfinement to
confinement transition possibly takes place between $\sqrt{s_{NN}}$ = 11.5 and
19.6 GeV.


  The segregation of plasmids in a bacterial population is investigated.
Hereby, a dynamical model is formulated in terms of a size-structured
population using a hyperbolic partial differential equation incorporating
non-local terms (the fragmentation equation). For a large class of parameter
functions this PDE can be re-written as an infinite system of ordinary
differential equations for the moments of its solution. We investigate the
influence of different plasmid production modes, kinetic parameters, and
plasmid segregation modes on the equilibrium plasmid distribution. In
particular, at small plasmid numbers the distribution is strongly influenced by
the production mode, while the kinetic parameters (cell growth rate resp. basic
plasmid reproduction rate) influence the distribution mainly at large plasmid
numbers. The plasmid transmission characteristics only gradually influence the
distribution, but may become of importance for biologically relevant cases. We
compare the theoretical findings with experimental results.


  The production of GWs during preheating in the Starobinsky model with a
nonminimally coupled auxiliary scalar field is studied through the lattice
simulation in this paper. We find that the GW spectrum $\Omega_{\rm gw}$ grows
fast with the increase of the absolute value of coupling parameter $\xi$. This
is because the resonant bands become broad with the increase of $|\xi|$. When
$\xi<0$, $\Omega_{\rm gw}$ begins to grow once the inflation ends and grows
faster than the case of $\xi>0$. $\Omega_{\rm gw}$ reaches the maximum at
$\xi=-20$ ($\xi=42$ for the case $\xi>0$) and then decreases with slight
oscillation. Furthermore we find that the GWs produced in the era of preheating
satisfy the limits from the Planck and next-generation CMB experiments.


  We study the following nonlinear Schr\"odinger equation with a forth order
dispersion term \[ \Delta^2u-\beta\Delta u=g(u) \quad \text{in } \mathbb{R}^N
\] in the positive and zero mass regimes: in the former, $N\geq 2$ and $\beta >
-2\sqrt{m}$, where $m>0$ depends on $g$; in the latter, $N\geq 3$ and
$\beta>0$. In either regimes, we find an infinite sequence of solutions under
rather generic assumptions about $g$; if $N=2$ in the positive mass case, or
$N=4$ in the zero mass case, we need to strengthen such assumptions. Our
approach is variational.


  The visual and audio information from movies can evoke a variety of emotions
in viewers. Towards a better understanding of viewer impact, we present our
methods for the MediaEval 2018 Emotional Impact of Movies Task to predict the
expected valence and arousal continuously in movies. This task, using the
LIRIS-ACCEDE dataset, enables researchers to compare different approaches for
predicting viewer impact from movies. Our approach leverages image, audio, and
face based features computed using pre-trained neural networks. These features
were computed over time and modeled using a gated recurrent unit (GRU) based
network followed by a mixture of experts model to compute multiclass
predictions. We smoothed these predictions using a Butterworth filter for our
final result. Our method enabled us to achieve top performance in three
evaluation metrics in the MediaEval 2018 task.


  In this work, we prove the strong Feller property and the exponential
ergodicity of stochastic Burgers equations driven by $\alpha/2$-subordinated
cylindrical Brownian motions with $\alpha\in(1,2)$. To prove the results, we
truncate the nonlinearity and use the derivative formula for SDEs driven by
$\alpha$-stable noises established in Zhang (arXiv:1204.2630v2).


  The Sommerfeld boundary conditions, imposed on hyperbolic differential
equations to obtain solutions in the form of outgoing waves, are formulated
here so as to make explicit the role of an appropriate null vector field. When
applied to the scalar and Maxwell equations, they lead to the asymptotic form
of the energy-momentum tensor representing radiation as a null, perfect dust.


  For $f(z) = \sum_{n=0}^{\infty} a_n z^n$ and a fixed $z$ in the unit disk,
$|z| = r,$ the Bohr operator $\mathcal{M}_r$ is given by \[\mathcal{M}_r (f) =
\sum_{n=0}^{\infty} |a_n| |z^n| = \sum_{n=0}^{\infty} |a_n| r^n.\] This papers
develops normed theoretic approaches on $\mathcal{M}_r$. Using earlier results
of Bohr and Rogosinski, the following results are readily established: if
$f(z)=\sum_{n=0}^{\infty} a_{n}z^{n}$ is subordinate (or quasi-subordinate) to
$h(z)=\sum_{n=0}^{\infty} b_{n}z^{n}$ in the unit disk, then
\[\mathcal{M}_{r}(f) \leq \mathcal{M}_{r}(h), \quad 0 \leq r \leq 1/3,\] that
is, \[\sum_{n=0}^{\infty} \ | a_{n}\ | |z|^{n} \leq \sum_{n=0}^{\infty} \ |
b_{n}\ |t |z|^{n}, \quad 0 \leq |z| \leq 1/3. \] Further, each $k$-th section
$s_k(f) = a_0 + a_1 z + \cdots + a_kz^k$ satisfies \[\ | s_k(f)\ | \leq
\mathcal{M}_r \ ( s_k(h)\ ), \quad 0 \leq r \leq 1/2,\] and \[\mathcal{M}_{r}\
( s_{k}(f) \ ) \leq \mathcal{M}_{r}(s_{k}(h)), \quad 0 \leq r \leq 1/3.\] A von
Neumann-type inequality is also obtained for the class consisting of Schwarz
functions in the unit disk.


  Many sulphur-bearing species have been detected in different astronomical
environments and have allowed to derive important information about the
chemical and physical composition of interstellar regions. In particular, these
species have also been showed to trace and probe hot-core environment time
evolution. Among the most prominent sulphur-bearing molecules, SO, sulphur
monoxide radical, is one of the more ubiquitous and abundant, observed also in
its isotopic substituted species such as $^{34}$SO and S$^{18}$O. Due to the
importance of this simple diatomic system and to face the challenge of modern
radioastronomical facilities, an extension to THz range of the rare
isotopologues of sulphur monoxide has been performed. High-resolution
rotational molecular spectroscopy has been employed to extend the available
dataset of four isotopic species, SO, $^{34}$SO, S$^{17}$O, and S$^{18}$O up to
the 1.5 THz region. The frequency coverage and the spectral resolution of our
measurements allowed a better constraint of the molecular constants of the four
species considered, focusing especially for the two oxygen substituted
isotopologues. Our measurements were also employed in an isotopically invariant
fit including all available pure rotational and ro-vibrational transitions for
all SO isotopologues, thus enabling accurate predictions for rotational
transitions at higher frequencies. Comparison with recent works performed on
the same system are also provided, showing the quality of our experiment and
the improvement of the datasets for all the species here considered. Transition
frequencies for this system can now be used with confidence by the astronomical
community well into the THz spectral region.


  Archaeological settlement systems are usually analysed in terms of the
relation between the rank of a settlement and its size (Zipf's law). We argue
that this approach is unreliable, and can be misleading, in application to
archaeological data where the recovery rate of settlements can be low and their
size estimates are often approximate at best. An alternative framework for the
settlement data interpretation, better connected with the theoretical concepts
of the stochastic evolution of settlement systems, is applied to the evolving
system of settlements of the Late Neolithic-Bronze Age Trypillia cultural
complex (5,400-2,800 BC) in modern Ukraine. The stochastic evolution model
provides a consistent and accurate explanation of the frequency of occurrence
of Trypillian settlement areas in the range from 0.05 to 500 ha. Thus
validated, the model leads to reliable estimates of the typical size of a newly
formed settlement as well as the growth rates of the total number of
settlements and their areas. The parameters of the settlement system thus
revealed are consistent with palaeoeconomy reconstructions for the Trypillia
area.


  Acoustic peaks in the spectrum of the cosmic microwave background in
spherically symmetric inhomogeneous cosmological models are studied. At the
photon-baryon decoupling epoch, the universe may be assumed to be dominated by
non-relativistic matter, and thus we may treat radiation as a test field in the
universe filled with dust which is described by the Lema\^itre-Tolman-Bondi
(LTB) solution. First, we give an LTB model whose distance-redshift relation
agrees with that of the concordance $\Lambda$CDM model in the whole redshift
domain and which is well approximated by the Einstein-de Sitter universe at and
before decoupling. We determine the decoupling epoch in this LTB universe by
Gamow's criterion and then calculate the positions of acoustic peaks. Thus
obtained results are not consistent with the WMAP data. However, we find that
one can fit the peak positions by appropriately modifying the LTB model,
namely, by allowing the deviation of the distance-redshift relation from that
of the concordance $\Lambda$CDM model at $z>2$ where no observational data are
available at present. Thus there is still a possibility of explaining the
apparent accelerated expansion of the universe by inhomogeneity without
resorting to dark energy if we abandon the Copernican principle. Even if we do
not take this extreme attitude, it also suggests that local, isotropic
inhomogeneities around us may seriously affect the determination of the density
contents of the universe unless the possible existence of such inhomogeneities
is properly taken into account.


  We report on the nearly simultaneous \nicer{} and \nustar{} observations of
the known X-ray transient XTE~J1739-285. These observations provide the first
sensitive hard X-ray spectrum of this neutron star X-ray transient. The source
was observed on 2020 February 19 in the hard spectral state with a luminosity
of $0.007$ of the Eddington limit. The broadband $1-70 \kev{}$ \nicer{} and
\nustar{} observation clearly detects a cutoff of the hard spectral component
around $34-40 \kev{}$ when the continuum is fitted by a soft thermal component
and a hard power-law component. This feature has been detected for the first
time in this source. Moreover, the spectrum shows evidence for disc reflection
-- a relativistically broadened Fe K$\alpha$ line around $5-8 \kev{}$ and a
Compton hump in the $10-20 \kev{}$ energy band. The accretion disc reflection
features have not been identified before from this source. Through accretion
disc reflection modeling, we constrain the radius of the inner disc to be
$R_{in}=3.1_{-0.5}^{+1.8}\;R_{ISCO}$ for the first time. In addition, we find a
low inclination, $i\sim 33^{0}$. Assuming the magnetosphere is responsible for
such truncation of the inner accretion disc above the stellar surface, we
establish an upper limit of $6.2\times 10^8$ G on the magnetic field at the
poles.


  The search for chemically unevolved galaxies remains prevalent in the nearby
Universe, mostly because these systems provide excellent proxies for exploring
in detail the physics of high-z systems. The most promising candidates are
extremely metal-poor galaxies (XMPs), i.e., galaxies with <1/10 solar
metallicity. However, due to the bright emission line based search criteria
traditionally used to find XMPs, we may not be sampling the full XMP
population. In 2014 we reoriented this search using only morphological
properties and uncovered a population of ~150 `blue diffuse dwarf (BDD)
galaxies', and published a sub-sample of 12 BDD spectra. Here we present
optical spectroscopic observations of a larger sample of 51 BDDs, along with
their SDSS photometric properties. With our improved statistics, we use
direct-method abundances to confirm that BDDs are chemically unevolved
(7.43<12+log(O/H)<8.01), with ~20% of our sample classified as being XMP
galaxies, and find they are actively forming stars at rates of 1-33x10^-2
M_sol/yr in HII regions randomly embedded in a blue, low-surface brightness
continuum. Stellar masses are calculated from population synthesis models and
estimated to be in the range log(M_star/M_sol) ~5-9. Unlike other
low-metallicity star-forming galaxies, BDDs are in agreement with the
mass-metallicity relation at low masses, suggesting they are not accreting
large amounts of pristine gas relative to their stellar mass. BDD galaxies
appear to be a population of actively star-forming dwarf irregular (dIrr)
galaxies who fall within the class of low-surface brightness dIrr galaxies.
Their ongoing star-formation and irregular morphology make them excellent
analogues for galaxies in the early Universe.


  Vision transformers (ViTs) have emerged as a prevalent architecture for
vision tasks owing to their impressive performance. However, when it comes to
handling long token sequences, especially in dense prediction tasks that
require high-resolution input, the complexity of ViTs increases significantly.
Notably, dense prediction tasks, such as semantic segmentation or object
detection, emphasize more on the contours or shapes of objects, while the
texture inside objects is less informative. Motivated by this observation, we
propose to apply adaptive resolution for different regions in the image
according to their importance. Specifically, at the intermediate layer of the
ViT, we utilize a spatial-aware density-based clustering algorithm to select
representative tokens from the token sequence. Once the representative tokens
are determined, we proceed to merge other tokens into their closest
representative token. Consequently, semantic similar tokens are merged together
to form low-resolution regions, while semantic irrelevant tokens are preserved
independently as high-resolution regions. This strategy effectively reduces the
number of tokens, allowing subsequent layers to handle a reduced token sequence
and achieve acceleration. We evaluate our proposed method on three different
datasets and observe promising performance. For example, the "Segmenter ViT-L"
model can be accelerated by 48% FPS without fine-tuning, while maintaining the
performance. Additionally, our method can be applied to accelerate fine-tuning
as well. Experimental results demonstrate that we can save 52% training time
while accelerating 2.46 times FPS with only a 0.09% performance drop. The code
is available at https://github.com/caddyless/ailurus/tree/main.


  $\mathrm{MoTe_2}$ has recently been shown to realize in its low-temperature
phase the type-II Weyl semimetal (WSM). We investigated by time- and angle-
resolved photoelectron spectroscopy (tr-ARPES) the possible influence of the
Weyl points in the electron dynamics above the Fermi level $\mathrm{E_F}$, by
comparing the ultrafast response of $\mathrm{MoTe_2}$ in the trivial and
topological phases. In the low-temperature WSM phase, we report an enhanced
relaxation rate of electrons optically excited to the conduction band, which we
interpret as a fingerprint of the local gap closure when Weyl points form. By
contrast, we find that the electron dynamics of the related compound
$\mathrm{WTe_2}$ is slower and temperature-independent, consistent with a
topologically trivial nature of this material. Our results shows that tr-ARPES
is sensitive to the small modifications of the unoccupied band structure
accompanying the structural and topological phase transition of
$\mathrm{MoTe_2}$.


  In this work, we investigate the computational complexity of Restless
Temporal $(s,z)$-Separation, where we are asked whether it is possible to
destroy all restless temporal paths between two distinct vertices $s$ and $z$
by deleting at most $k$ vertices from a temporal graph. A temporal graph has a
fixed vertex but the edges have (discrete) time stamps. A restless temporal
path uses edges with non-decreasing time stamps and the time spent at each
vertex must not exceed a given duration $\Delta$.
  Restless Temporal $(s,z)$-Separation naturally generalizes the NP-hard
Temporal $(s,z)$-Separation problem. We show that Restless Temporal
$(s,z)$-Separation is complete for $\Sigma_2^\text{P}$, a complexity class
located in the second level of the polynomial time hierarchy. We further
provide some insights in the parameterized complexity of Restless Temporal
$(s,z)$-Separation parameterized by the separator size $k$.


  In this paper asymptotic equalities are found for the least upper bounds of
deviations in the uniform metric of de la Vallee Poussin sums on classes of
2\pi-periodic (\psi,\beta)-differentiable functions admitting an analytic
continuation into the given strip of the complex plane. As a consequence,
asymptotic equalities are obtained on classes of convolutions of periodic
functions generated by the Neumann kernel and the polyharmonic Poisson kernel.


  The giant electro- and elasto-caloric effects in spin chain materials are
predicted. The theory is based on the exact quantum mechanical solution of the
problem. It is shown that the giant jumps in the entropy and the temperature
caused by the caloric effect are weakly affected by the initial temperature.
The effect can be used for the cooling of new quantum devices (like systems of
qubits in quantum computers). On the other hand, since large changes are
predicted in the narrow neighborhood of the critical point, the predicted
effect can be used in ultra-sensitive electric and stress sensors for modern
microelectronics.


  We study the parameterized problem of satisfying ``almost all'' constraints
of a given formula $F$ over a fixed, finite Boolean constraint language
$\Gamma$, with or without weights. More precisely, for each finite Boolean
constraint language $\Gamma$, we consider the following two problems. In Min
SAT$(\Gamma)$, the input is a formula $F$ over $\Gamma$ and an integer $k$, and
the task is to find an assignment $\alpha \colon V(F) \to \{0,1\}$ that
satisfies all but at most $k$ constraints of $F$, or determine that no such
assignment exists. In Weighted Min SAT$(\Gamma$), the input additionally
contains a weight function $w \colon F \to \mathbb{Z}_+$ and an integer $W$,
and the task is to find an assignment $\alpha$ such that (1) $\alpha$ satisfies
all but at most $k$ constraints of $F$, and (2) the total weight of the
violated constraints is at most $W$. We give a complete dichotomy for the
fixed-parameter tractability of these problems: We show that for every Boolean
constraint language $\Gamma$, either Weighted Min SAT$(\Gamma)$ is FPT; or
Weighted Min SAT$(\Gamma)$ is W[1]-hard but Min SAT$(\Gamma)$ is FPT; or Min
SAT$(\Gamma)$ is W[1]-hard. This generalizes recent work of Kim et al. (SODA
2021) which did not consider weighted problems, and only considered languages
$\Gamma$ that cannot express implications $(u \to v)$ (as is used to, e.g.,
model digraph cut problems). Our result generalizes and subsumes multiple
previous results, including the FPT algorithms for Weighted Almost 2-SAT,
weighted and unweighted $\ell$-Chain SAT, and Coupled Min-Cut, as well as
weighted and directed versions of the latter. The main tool used in our
algorithms is the recently developed method of directed flow-augmentation (Kim
et al., STOC 2022).


  (Abridged) We present the results of M31 globular cluster (GC) X-ray source
survey, based on the data of XMM-Newton and Chandra observations covering ~6100
sq.arcmin of M31. We detected 43 X-ray sources coincident with globular cluster
candidates from optical surveys. The estimated isotropic X-ray luminosities of
GC sources lie between ~10e35 and ~10e39 erg/s in the 0.3 - 10 keV energy band.
The spectral properties and variability of M31 GC X-ray sources are consistent
with that derived for the LMXBs in the bulges of M31 and Milky Way. We found
that ~80% of the M31 GC sources with multiple flux measurements available show
significant variability on a time scales from days to years. The X-ray
luminosity function of GC sources is found to be significantly different from
that of the point sources in the bulge and disk of M31 and that of the Galactic
GC X-ray sources. GC sources make dominant contribution to the bright source
counts in the areas of M31 covered by the survey: ~40% of the total number of
sources with luminosities above 10e37 ergs/s reside in GCs with fraction of GC
sources rising to 67-90% for the luminosities above 10e38 ergs/s. The
contribution of the GC sources to the total number of bright sources found in
M31 is much higher than in the Milky Way galaxy, but surprisingly close to that
of the early-type galaxies. The brightest M31 GC sources tend to reside at
large galactocentric distances outside the central bulge. We found that
globular clusters hosting bright X-ray sources are optically brighter and more
metal rich than the rest of M31 globular clusters. The brightest sources with
luminosities above ~10e38 ergs/s show tendency to reside in more metal poor
clusters.


  In this paper, a deep convolutional neural network architecture for galaxies
classification is presented. The galaxy can be classified based on its features
into main three categories Elliptical, Spiral, and Irregular. The proposed deep
galaxies architecture consists of 8 layers, one main convolutional layer for
features extraction with 96 filters, followed by two principles fully connected
layers for classification. It is trained over 1356 images and achieved 97.272%
in testing accuracy. A comparative result is made and the testing accuracy was
compared with other related works. The proposed architecture outperformed other
related works in terms of testing accuracy.


  The structural reorganization of the actin cytoskeleton is facilitated
through the action of motor proteins that crosslink the actin filaments and
transport them relative to each other. Here, we present a combined
experimental-computational study that probes the dynamic evolution of mixtures
of actin filaments and clusters of myosin motors. While on small spatial and
temporal scales the system behaves in a very noisy manner, on larger scales it
evolves into several well distinct patterns such as bundles, asters, and
networks. These patterns are characterized by junctions with high connectivity,
whose formation is possible due to the organization of the motors in
"oligoclusters" (intermediate-size aggregates). The simulations reveal that the
self-organization process proceeds through a series of hierarchical steps,
starting from local microscopic moves and ranging up to the macroscopic large
scales where the steady-state structures are formed. Our results shed light
into the mechanisms involved in processes like cytokinesis and cellular
contractility, where myosin motors organized in clusters operate cooperatively
to induce structural organization of cytoskeletal networks.


  We perform a qualitative analysis of the critical equation associated with a
stationary ergodic Hamiltonian through a stochastic version of the metric
method, where the notion of closed random stationary set, issued from
stochastic geometry, plays a major role. Our purpose is to give an appropriate
notion of random Aubry set, to single out characterizing conditions for the
existence of exact or approximate correctors, and write down representation
formulae for them. For the last task, we make use of a Lax--type formula,
adapted to the stochastic environment. This material can be regarded as a first
step of a long--term project to develop a random analog of Weak KAM Theory,
generalizing what done in the periodic case or, more generally, when the
underlying space is a compact manifold.


  We propose a novel Rayleigh quotient based sparse quadratic dimension
reduction method - named QUADRO (Quadratic Dimension Reduction via Rayleigh
Optimization) - for analyzing high- dimensional data. Unlike in the linear
setting where Rayleigh quotient optimization coincides with classification,
these two problems are very different under nonlinear settings. In this paper,
we clarify this difference and show that Rayleigh quotient optimization may be
of independent scientific interests. One major challenge of Rayleigh quotient
optimization is that the variance of quadratic statistics involves all fourth
cross-moments of predictors, which are infeasible to compute for
high-dimensional applications and may accumulate too many stochastic errors.
This issue is resolved by considering a family of elliptical models. Moreover,
for heavy-tail distributions, robust estimates of mean vectors and covariance
matrices are employed to guarantee uniform convergence in estimating
nonpolynomially many parameters, even though only the fourth moments are
assumed. Methodologically, QUADRO is based on elliptical models which allow us
to formulate the Rayleigh quotient maximization as a convex optimization
problem. Computationally, we propose an efficient linearized augmented
Lagrangian method to solve the constrained optimization problem. Theoretically,
we provide explicit rates of convergence in terms of Rayleigh quotient under
both Gaussian and general elliptical models. Thorough numerical results on both
synthetic and real datasets are also provided to back up our theoretical
results.


  We develop a rigid multiblob method for numerically solving the mobility
problem for suspensions of passive and active rigid particles of complex shape
in Stokes flow in unconfined, partially confined, and fully confined
geometries. As in a number of existing methods, we discretize rigid bodies
using a collection of minimally-resolved spherical blobs constrained to move as
a rigid body, to arrive at a potentially large linear system of equations for
the unknown Lagrange multipliers and rigid-body motions. Here we develop a
block-diagonal preconditioner for this linear system and show that a standard
Krylov solver converges in a modest number of iterations that is essentially
independent of the number of particles. For unbounded suspensions and
suspensions sedimented against a single no-slip boundary, we rely on existing
analytical expressions for the Rotne-Prager tensor combined with a fast
multipole method or a direct summation on a Graphical Processing Unit to obtain
an simple yet efficient and scalable implementation. For fully confined
domains, such as periodic suspensions or suspensions confined in slit and
square channels, we extend a recently-developed rigid-body immersed boundary
method to suspensions of freely-moving passive or active rigid particles at
zero Reynolds number. We demonstrate that the iterative solver for the coupled
fluid and rigid body equations converges in a bounded number of iterations
regardless of the system size. We optimize a number of parameters in the
iterative solvers and apply our method to a variety of benchmark problems to
carefully assess the accuracy of the rigid multiblob approach as a function of
the resolution. We also model the dynamics of colloidal particles studied in
recent experiments, such as passive boomerangs in a slit channel, as well as a
pair of non-Brownian active nanorods sedimented against a wall.


  Cognitive radio is a promising technology to improve spectral efficiency.
However, the secure performance of a secondary network achieved by using
physical layer security techniques is limited by its transmit power and channel
fading. In order to tackle this issue, a cognitive unmanned aerial vehicle
(UAV) communication network is studied by exploiting the high flexibility of a
UAV and the possibility of establishing line-of-sight links. The average
secrecy rate of the secondary network is maximized by robustly optimizing the
UAV's trajectory and transmit power. Our problem formulation takes into account
two practical inaccurate location estimation cases, namely, the worst case and
the outage-constrained case. In order to solve those challenging non-convex
problems, an iterative algorithm based on $\mathcal{S}$-Procedure is proposed
for the worst case while an iterative algorithm based on Bernstein-type
inequalities is proposed for the outage-constrained case. The proposed
algorithms can obtain effective suboptimal solutions of the corresponding
problems. Our simulation results demonstrate that the algorithm under the
outage-constrained case can achieve a higher average secrecy rate with a low
computational complexity compared to that of the algorithm under the worst
case. Moreover, the proposed schemes can improve the secure communication
performance significantly compared to other benchmark schemes.


  We consider the dynamics of interacting quantum and classical systems in the
Heisenberg representation. Unlike the usual construction in standard quantum
mechanics, mixed quantum-classical systems involve the interplay of unitary
operators acting on the quantum observables and the Lagrangian trajectories
sweeping the classical degrees of freedom. This interplay reflects an intricate
structure which is made particularly challenging by the backreaction excerpted
on the classical trajectories by the quantum degrees of freedom. While the
backreaction is underestimated in the common Ehrenfest model, more recent
methodologies succeed in capturing this important effect by resorting to
Koopman wavefunctions in classical mechanics. Luckily, both Ehrenfest and
Koopman models enjoy a variational framework which is exploited here to unfold
the geometric structure underlying quantum-classical coupling. A special role
is played by the action of the diffeomorphic Lagrangian paths on a non-Abelian
pure-gauge potential which comprises statistical correlations. After presenting
the treatment in the simple case of Ehrenfest dynamics, we move on to the
Koopman model and present the role of the backreaction terms therein. Finally,
we compare both models in the context of pure-dephasing systems.


  The well-known factorization theorem of Lozanovski{\u \i} may be written in
the form $L^{1}\equiv E\odot E^{\prime}$, where $\odot $ means the pointwise
product of Banach ideal spaces. A natural generalization of this problem would
be the question when one can factorize $F$ through $E$, i.e., when $F\equiv
E\odot M(E, F) \,$, where $M(E, F) $ is the space of pointwise multipliers from
$E$ to $F$. Properties of $M(E, F) $ were investigated in our earlier paper
[KLM12] and here we collect and prove some properties of the construction
$E\odot F$. The formulas for pointwise product of Calder\'{o}n-Lozanovski{\u
\i} $E_{\varphi}$ spaces, Lorentz spaces and Marcinkiewicz spaces are proved.
These results are then used to prove factorization theorems for these spaces.
Finally, it is proved in Theorem 11 that under some natural assumptions, a
rearrangement invariant Banach function space may be factorized through
Marcinkiewicz space.


  This work proposes a distance that combines Minkowski and Chebyshev distances
and can be seen as an intermediary distance. This combination not only achieves
efficient run times in neighbourhood iteration tasks in Z^2, but also obtains
good accuracies when coupled with the k-Nearest Neighbours (k-NN) classifier.
The proposed distance is approximately 1.3 times faster than Manhattan distance
and 329.5 times faster than Euclidean distance in discrete neighbourhood
iterations. An accuracy analysis of the k-NN classifier using a total of 33
datasets from the UCI repository, 15 distances and values assigned to k that
vary from 1 to 200 is presented. In this experiment, the proposed distance
obtained accuracies that were better than the average more often than its
counterparts (in 26 cases out of 33), and also obtained the best accuracy more
frequently (in 9 out of 33 cases).


  The Industrial Internet market is targeted to grow by trillions of US dollars
by the year 2030, driven by adoption, deployment and integration of billions of
intelligent devices and their associated data. This digital expansion faces a
number of significant challenges, including reliable data management, security
and privacy. Realizing the benefits from this evolution is made more difficult
because a typical industrial plant includes multiple vendors and legacy
technology stacks. Aggregating all the raw data to a single data center before
performing analysis increases response times, raising performance concerns in
traditional markets and requiring a compromise between data duplication and
data access performance. Similar to the way microservices can integrate
disparate information technologies without imposing monolithic cross-cutting
architecture impacts, we propose microdatabases to manage the data
heterogeneity of the Industrial Internet while allowing records to be captured
and secured close to the industrial processes, but also be made available near
the applications that can benefit from the data. A microdatabase is an
abstraction of a data store that standardizes and protects the interactions
between distributed data sources, providers and consumers. It integrates an
information model with discoverable object types that can be browsed
interactively and programmatically, and supports repository instances that
evolve with their own lifecycles. The microdatabase abstraction is independent
of technology choice and was designed based on solicitation and review of
industry stakeholder concerns.


  A Landau model is used to study the phase behavior of the surface layer for
magnetic and cholesteric liquid crystal systems that are at or near a Lifshitz
point marking the boundary between modulated and homogeneous bulk phases. The
model incorporates surface and bulk fields and includes a term in the free
energy proportional to the square of the second derivative of the order
parameter in addition to the usual term involving the square of the first
derivative. In the limit of vanishing bulk field, three distinct types of
surface ordering are possible: a wetting layer, a non-wet layer having a small
deviation from bulk order, and a different non-wet layer with a large deviation
from bulk order which decays non-monotonically as distance from the wall
increases. In particular the large deviation non-wet layer is a feature of
systems at the Lifshitz point and also those having only homogeneous bulk
phases.


  A recent publication by the NSA assessing the usability of quantum
cryptography has generated significant attention, concluding that this
technology is not recommended for use. Here, we reply to this criticism and
argue that some of the points raised are unjustified, whereas others are
problematic now but can be expected to be resolved in the foreseeable future.


  Event-by-event fluctuations (ebe) of hadronic patterns are investigated in
terms of voids by analyzing the experimental data on 4.5, 14.5 and 60A GeV/c
16O-AgBr collisions. The findings are compared with the predictions of a
multi-phase transport AMPT model. Dependence of voids on phase space bin width
is examined in terms of two lowest moments of event-by-event fluctuations of
voids, <Gq> and Sq. The findings reveal that scaling exponent estimated from
the observed power-law behavior of the voids may be used to characterize the
various properties of hadronic phase transition. The results also rule out
occurrence of 2nd order quark-hadron phase transition at the projectile
energies considered.


  Visual QA is a pivotal challenge for higher-level reasoning, requiring
understanding language, vision, and relationships between many objects in a
scene. Although datasets like CLEVR are designed to be unsolvable without such
complex relational reasoning, some surprisingly simple feed-forward, "holistic"
models have recently shown strong performance on this dataset. These models
lack any kind of explicit iterative, symbolic reasoning procedure, which are
hypothesized to be necessary for counting objects, narrowing down the set of
relevant objects based on several attributes, etc. The reason for this strong
performance is poorly understood. Hence, our work analyzes such models, and
finds that minor architectural elements are crucial to performance. In
particular, we find that \textit{early fusion} of language and vision provides
large performance improvements. This contrasts with the late fusion approaches
popular at the dawn of Visual QA. We propose a simple module we call Multimodal
Core, which we hypothesize performs the fundamental operations for multimodal
tasks. We believe that understanding why these elements are so important to
complex question answering will aid the design of better-performing algorithms
for Visual QA while minimizing hand-engineering effort.


  An efficient procedure for the computation of the coefficients of Legendre
expansions is here presented. We prove that the Legendre coefficients
associated with a function f(x) can be represented as the Fourier coefficients
of an Abel-type transform of f(x). The computation of N Legendre coefficients
can then be performed in O(N log N) operations with a single Fast Fourier
Transform of the Abel-type transform of f(x).


  We present a new 300 ks Chandra observation of M87 that limits pileup to only
a few per cent of photon events and maps the hot gas properties closer to the
nucleus than has previously been possible. Within the supermassive black hole's
gravitational sphere of influence, the hot gas is multiphase and spans
temperatures from 0.2 to 1 keV. The radiative cooling time of the lowest
temperature gas drops to only 0.1-0.5 Myr, which is comparable to its free fall
time. Whilst the temperature structure is remarkably symmetric about the
nucleus, the density gradient is steep in sectors to the N and S, with
$\rho{\propto}r^{-1.5\pm0.1}$, and significantly shallower along the jet axis
to the E, where $\rho{\propto}r^{-0.93\pm0.07}$. The density structure within
the Bondi radius is therefore consistent with steady inflows perpendicular to
the jet axis and an outflow directed E along the jet axis. By putting limits on
the radial flow speed, we rule out Bondi accretion on the scale resolved at the
Bondi radius. We show that deprojected spectra extracted within the Bondi
radius can be equivalently fit with only a single cooling flow model, where gas
cools from 1.5 keV down below 0.1 keV at a rate of 0.03 M$_{\odot}$/yr. For the
alternative multi-temperature spectral fits, the emission measures for each
temperature component are also consistent with a cooling flow model. The lowest
temperature and most rapidly cooling gas in M87 is therefore located at the
smallest radii at ~100 pc and may form a mini cooling flow. If this cooling gas
has some angular momentum, it will feed into the cold gas disk around the
nucleus, which has a radius of ~80 pc and therefore lies just inside the
observed transition in the hot gas structure.


  We review the enveloping algebra of the 10 dimensional chiral sigma matrices.
To facilitate the computation of the product of several chiral sigma matrices
we have developed a symbolic program. Using this program one can reduce the
multiplication of the sigma matrices down to linear combinations of irreducilbe
elements. We are able to quickly derive several identities that are not
restricted to traces. A copy of the program written in the Mathematica language
is provided for the community.


  Current out-of-distribution (OOD) detection benchmarks are commonly built by
defining one dataset as in-distribution (ID) and all others as OOD. However,
these benchmarks unfortunately introduce some unwanted and impractical goals,
e.g., to perfectly distinguish CIFAR dogs from ImageNet dogs, even though they
have the same semantics and negligible covariate shifts. These unrealistic
goals will result in an extremely narrow range of model capabilities, greatly
limiting their use in real applications. To overcome these drawbacks, we
re-design the benchmarks and propose the semantically coherent
out-of-distribution detection (SC-OOD). On the SC-OOD benchmarks, existing
methods suffer from large performance degradation, suggesting that they are
extremely sensitive to low-level discrepancy between data sources while
ignoring their inherent semantics. To develop an effective SC-OOD detection
approach, we leverage an external unlabeled set and design a concise framework
featured by unsupervised dual grouping (UDG) for the joint modeling of ID and
OOD data. The proposed UDG can not only enrich the semantic knowledge of the
model by exploiting unlabeled data in an unsupervised manner, but also
distinguish ID/OOD samples to enhance ID classification and OOD detection tasks
simultaneously. Extensive experiments demonstrate that our approach achieves
state-of-the-art performance on SC-OOD benchmarks. Code and benchmarks are
provided on our project page: https://jingkang50.github.io/projects/scood.


  Recent advances in spatial and temporal networks have enabled researchers to
more-accurately describe many real-world systems such as urban transport
networks. In this paper, we study the response of real-world spatio-temporal
networks to random error and systematic attack, taking a unified view of their
spatial and temporal performance. We propose a model of spatio-temporal paths
in time-varying spatially embedded networks which captures the property that,
as in many real-world systems, interaction between nodes is non-instantaneous
and governed by the space in which they are embedded. Through numerical
experiments on three real-world urban transport systems, we study the effect of
node failure on a network's topological, temporal and spatial structure. We
also demonstrate the broader applicability of this framework to three other
classes of network. To identify weaknesses specific to the behaviour of a
spatio-temporal system, we introduce centrality measures that evaluate the
importance of a node as a structural bridge and its role in supporting
spatio-temporally efficient flows through the network. This exposes the complex
nature of fragility in a spatio-temporal system, showing that there is a
variety of failure modes when a network is subject to systematic attacks.


  We approach the biexciton Schr\"{o}dinger equation not through the
free-carrier basis as usually done, but through the free-exciton basis,
exciton-exciton interactions being treated according to the recently developed
composite boson many-body formalism which allows an exact handling of carrier
exchange between excitons, as induced by the Pauli exclusion principle. We
numerically solve the resulting biexciton Schr\"{o}dinger equation with the
exciton levels restricted to the ground state and we derive the biexciton
ground state as well as the bound and unbound excited states as a function of
hole-to-electron mass ratio. The biexciton ground-state energy we find, agrees
reasonably well with variational results. Next, we use the obtained biexciton
wave functions to calculate optical absorption in the presence of a dilute
exciton gas in quantum well. We find a small asymmetric peak with a
characteristic low-energy tail, identified with the biexciton ground state, and
a set of large peaks associated with biexciton unbound states, i.e.,
exciton-exciton scattering states.


  Geometric phase plays a fundamental role in quantum theory and accounts for
wide phenomena ranging from the Aharanov-Bohm effect, the integer and
fractional quantum hall effects, and topological phases of matter, including
topological insulators, to name a few. In this thesis, we have proposed a fresh
perspective of geodesics and null phase curves, which are key ingredients in
understanding the geometric phase. We have also looked at a number of
applications of geometric phases in topological phases, quantum walks, and
non-inertial quantum systems.
  The shortest curve between any two points on a given surface is a (minimal)
geodesic. They are also the curves along which a system does not acquire any
geometric phase. In the same context, we can generalize geodesics to define a
larger class of curves, known as null phase curves (NPCs), along which also the
acquired geometric phase is zero; however, they need not be the shortest curves
between the two points. We have proposed a geometrical decomposition of
geodesics and null phase curves on the Bloch sphere, which is crucial in
improving our understanding of the geometry of the state space and the
intrinsic symmetries of geodesics and NPCs.
  We have also investigated the persistence of topological phases in quantum
walks in the presence of an external (lossy) environment. We show that the
topological order in one and two-dimensional quantum walks persist against
moderate losses. Further, we use the geometric phase to detect the non-inertial
modifications to the field correlators perceived by a circularly rotating
two-level atom placed inside a cavity.


  Most recently, both BaBar and Belle experiments found evidences of neutral
$D$ mixing. In this paper, we discuss the constraints on the strong phase
difference in $D^0 \to K\pi$ decay from the measurements of the mixing
parameters, $y^\prime$, $y_{CP}$ and $x$ at the $B$ factories. The sensitivity
of the measurement of the mixing parameter $y$ is estimated in BES-III
experiment at $\psi(3770)$ peak. We also make an estimate on the measurements
of the mixing rate $R_M$. Finally, the sensitivity of the strong phase
difference at BES-III are obtained by using data near the $D\bar{D}$ threshold
with CP tag technique at BES-III experiment.


  As an important type of dynamics on complex networks, spreading is widely
used to model many real processes such as the epidemic contagion and
information propagation. One of the most significant research questions in
spreading is to rank the spreading ability of nodes in the network. To this
end, substantial effort has been made and a variety of effective methods have
been proposed. These methods usually define the spreading ability of a node as
the number of finally infected nodes given that the spreading is initialized
from the node. However, in many real cases such as advertising and medicine
science the spreading only aims to cover a specific group of nodes. Therefore,
it is necessary to study the spreading ability of nodes towards localized
targets in complex networks. In this paper, we propose a reversed local path
algorithm for this problem. Simulation results show that our method outperforms
the existing methods in identifying the influential nodes with respect to these
localized targets. Moreover, the influential spreaders identified by our method
can effectively avoid infecting the non-target nodes in the spreading process.


  In this paper we prove theorems that describe how the representation theory
of the affine Hecke algebra of type A and of related algebras such as the group
algebra of the symmetric group are controlled by integrable highest weight
representations of the characteristic zero affine Lie algebra \hat{sl}_l. In
particular we parameterise the representations of these algebras by the nodes
of the crystal graph, and give various Hecke theoretic descriptions of the
edges.
  As a consequence we find for each prime p a basis of the integrable
representations of \hat{sl}_l which shares many of the remarkable properties,
such as positivity, of the global crystal basis/canonical basis of Lusztig and
Kashiwara. This {\it $p$-canonical basis} is the usual one when p = 0, and the
crystal of the p-canonical basis is always the usual one.
  The paper is self-contained, and our techniques are elementary (no perverse
sheaves or algebraic geometry is invoked).


  Two-dimensional gray solitons to the nonlinear Schroedinger equation are
numerically created by two processes to show its robustness. One is transverse
instability of a one-dimensional gray soliton, and another is a pair
annihilation of a vortex and an antivortex. The two-dimensional dark solitons
are anisotropic and propagate in a certain direction. The two-dimensional dark
soliton is stable against the head-on collision. The effective mass of the
two-dimensional dark soliton is evaluated from the motion in a harmonic
potential.


  With the tremendous growth in the information communication sector, the
mobile phones have become the prime information communication devices. The
convergence of traditional telephony with the modern web enabled communication
in the mobile devices has made the communication much effective and simpler. As
mobile phones are becoming the crucial source of accessing the contents of the
World Wide Web which was originally designed for personal computers, has opened
up a new challenge of accommodating the web contents in to the smaller mobile
devices. This paper proposes an approach towards building a model for rendering
the web pages in mobile devices. The proposed model is based on a
multi-dimensional web page segment evaluation model. The incorporation of
personalization in the proposed model makes the rendering user-centric. The
proposed model is validated with a prototype implementation.


  Hand pose estimation from a single depth image is an essential topic in
computer vision and human computer interaction. Despite recent advancements in
this area promoted by convolutional neural network, accurate hand pose
estimation is still a challenging problem. In this paper we propose a Pose
guided structured Region Ensemble Network (Pose-REN) to boost the performance
of hand pose estimation. The proposed method extracts regions from the feature
maps of convolutional neural network under the guide of an initially estimated
pose, generating more optimal and representative features for hand pose
estimation. The extracted feature regions are then integrated hierarchically
according to the topology of hand joints by employing tree-structured fully
connections. A refined estimation of hand pose is directly regressed by the
proposed network and the final hand pose is obtained by utilizing an iterative
cascaded method. Comprehensive experiments on public hand pose datasets
demonstrate that our proposed method outperforms state-of-the-art algorithms.


  We present the first public implementation of antenna-based QCD initial- and
final-state showers. The shower kernels are $2\to 3$ antenna functions, which
capture not only the collinear dynamics but also the leading soft (coherent)
singularities of QCD matrix elements. We define the evolution measure to be
inversely proportional to the leading poles, hence gluon emissions are evolved
in a $p_\perp$ measure inversely proportional to the eikonal, while processes
that only contain a single pole (e.g., $g\to q\bar{q}$) are evolved in
virtuality. Non-ordered emissions are allowed, suppressed by an additional
power of $1/Q^2$. Recoils and kinematics are governed by exact on-shell $2\to
3$ phase-space factorisations. This first implementation is limited to massless
QCD partons and colourless resonances. Tree-level matrix-element corrections
are included for QCD up to $\mathcal{O}(\alpha_s^4)$ (4 jets), and for
Drell-Yan and Higgs production up to $\mathcal{O}(\alpha_s^3)$ ($V/H$ + 3
jets). The resulting algorithm has been made publicly available in Vincia 2.0.


  A general multi-terminal source code and a general multi-terminal channel
code are presented. Constrained-random-number generators with sparse matrices,
which are building blocks for the code construction, are used in the
construction of both encoders and decoders. Achievable regions for source
coding and channel coding are derived in terms of entropy functions, where the
capacity region for channel coding provides an alternative to the region of
[Somekh-Baruch and Verd\'u, ISIT2006].


  Lag synchronization is a basic phenomenon in mismatched coupled systems,
delay coupled systems and time-delayed systems. It is characterized by a lag
configuration that establishes a unique time shift between all the state
variables of the coupled systems. In this report, an attempt is made how to
induce multiple lag configurations in coupled systems when different pairs of
state variables attain different time shift. A design of coupling is presented
to realize this multiple lag synchronization. Numerical illustration is given
using examples of the R\"ossler system and the slow-fast Hindmarsh-Rose neuron
model. The multiple lag scenario is physically realized in an electronic
circuit of two Sprott systems.


  We study the Landau damping of the surface plasmon resonance of metallic
nanoparticles embedded in different environments of experimental relevance.
Important oscillations of the plasmon linewidth as a function of the radius of
the nanoparticles are obtained from numerical calculations based on the time
dependent local density approximation. These size-oscillations are understood,
within a semiclassical approximation, as a consequence of correlations in the
spectral density of the nanoparticles. We treat inert matrices, as well as the
case with an unoccupied conduction band. In the latter case, the plasmon
lifetime is greatly reduced with respect to the inert case, but the
non-monotonous size-dependence persists.


  Pruning neural network parameters is often viewed as a means to compress
models, but pruning has also been motivated by the desire to prevent
overfitting. This motivation is particularly relevant given the perhaps
surprising observation that a wide variety of pruning approaches increase test
accuracy despite sometimes massive reductions in parameter counts. To better
understand this phenomenon, we analyze the behavior of pruning over the course
of training, finding that pruning's benefit to generalization increases with
pruning's instability (defined as the drop in test accuracy immediately
following pruning). We demonstrate that this "generalization-stability
tradeoff" is present across a wide variety of pruning settings and propose a
mechanism for its cause: pruning regularizes similarly to noise injection.
Supporting this, we find less pruning stability leads to more model flatness
and the benefits of pruning do not depend on permanent parameter removal. These
results explain the compatibility of pruning-based generalization improvements
and the high generalization recently observed in overparameterized networks.


  Reconfigurable intelligent surface (RIS) is an emerging paradigm able to
control the propagation environment in wireless systems. Most of the research
on RIS has been dedicated to system optimization and, with the advent of beyond
diagonal RIS (BD-RIS), to RIS architecture design. However, developing general
and unified electromagnetic (EM)-consistent models for RIS-aided systems
remains an open problem. In this study, we propose a universal framework for
the multiport network analysis of RIS-aided systems. With our framework, we
model RIS-aided systems and RIS architectures through impedance, admittance,
and scattering parameter analysis. Based on these analyses, three equivalent
models are derived accounting for the effects of impedance mismatching and
mutual coupling. The three models are then simplified by assuming large
transmission distances, perfect matching, and no mutual coupling to understand
the role of the RIS in the communication model. The derived simplified models
are consistent with the typical model used in related literature, although we
show that an additional approximation is commonly considered in the literature.
We discuss the benefits of each analysis in characterizing and optimizing the
RIS and how to select the most suitable parameters according to the needs.
Numerical results provide additional evidence of the equivalence of the three
analyses.


  The effectiveness of pain management relies on the choice and the correct use
of suitable pain assessment tools. In the case of newborns, some of the most
common tools are human-based and observational, thus affected by subjectivity
and methodological problems. Therefore, in the last years there has been an
increasing interest in developing an automatic machine-based pain assessment
tool.
  This research is a preliminary investigation towards the inclusion of a
scoring system for the vocal expression of the infant into an automatic tool.
To this aim we present a method to compute three correlated indicators which
measure three distress-related features of the cry: duration, dysphonantion and
fundamental frequency of the first cry. In particular, we propose a new method
to measure the dysphonantion of the cry via spectral entropy analysis,
resulting in an indicator that identifies three well separated levels of
distress in the vocal expression. These levels provide a classification that is
highly correlated with the human-based assessment of the cry.


  One source of beauty in mathematics is totally unexpected connections between
two fundamentally different objects. For instance, is it not surprising that
the time period of a real simple pendulum is linked with a function arising out
of finding the number of ways in which a positive integer could be decomposed
as a sum of two squares? Why should inherent properties and interrelations
among counting numbers should appear in the laws of nature that govern the
motion of a simple pendulum? In this article we will see some such surprising
and beautiful results coming from combinatorics, number theory and physics.


  We compute Teitelboim's causal propagator in the context of canonical loop
quantum gravity. For the Lorentzian signature, we find that the resultant power
series can be expressed as a sum over branched, colored two-surfaces with an
intrinsic causal structure. This leads us to define a general structure which
we call a ``causal spin foam''. We also demonstrate that the causal evolution
models for spin networks fall in the general class of causal spin foams.


  Criminal organizations exploit their presence on territories and local
communities to recruit new workforce in order to carry out their criminal
activities and business. The ability to attract individuals is crucial for
maintaining power and control over the territories in which these groups are
settled. This study proposes the formalization, development and analysis of an
agent-based model (ABM) that simulates a neighborhood of Palermo (Sicily) with
the aim to understand the pathways that lead individuals to recruitment into
organized crime groups (OCGs). Using empirical data on social, economic and
criminal conditions of the area under analysis, we use a multi-layer network
approach to simulate this scenario. As the final goal, we test different
policies to counter recruitment into OCGs. These scenarios are based on two
different dimensions of prevention and intervention: (i) primary and secondary
socialization and (ii) law enforcement targeting strategies.


  Diffusion models (DMs) are a class of generative machine learning methods
that sample a target distribution by transforming samples of a trivial (often
Gaussian) distribution using a learned stochastic differential equation. In
standard DMs, this is done by learning a ``score function'' that reverses the
effect of adding diffusive noise to the distribution of interest. Here we
consider the generalisation of DMs to lattice systems with discrete degrees of
freedom, and where noise is added via Markov chain jump dynamics. We show how
to use tensor networks (TNs) to efficiently define and sample such ``discrete
diffusion models'' (DDMs) without explicitly having to solve a stochastic
differential equation. We show the following: (i) by parametrising the data and
evolution operators as TNs, the denoising dynamics can be represented exactly;
(ii) the auto-regressive nature of TNs allows to generate samples efficiently
and without bias; (iii) for sampling Boltzmann-like distributions, TNs allow to
construct an efficient learning scheme that integrates well with Monte Carlo.
We illustrate this approach to study the equilibrium of two models with
non-trivial thermodynamics, the $d=1$ constrained Fredkin chain and the $d=2$
Ising model.


  A trapped ion transported along a periodic potential is studied as a
paradigmatic nanocontact frictional interface. The combination of the periodic
corrugation potential and a harmonic trapping potential creates a
one-dimensional energy landscape with multiple local minima, corresponding to
multistable stick-slip friction. We measure the probabilities of slipping to
the various minima for various corrugations and transport velocities. The
observed probabilities show that the multislip regime can be reached
dynamically at smaller corrugations than would be possible statically, and can
be described by an equilibrium Boltzmann model. While a clear microscopic
signature of multislip behavior is observed for the ion motion, the frictional
force and dissipation are only weakly affected by the transition to multistable
potentials.


  We derive upper and lower limits for the basic physical parameters
(mass-radius ratio, anisotropy, redshift and total energy) for arbitrary
anisotropic general relativistic matter distributions in the presence of a
cosmological constant. The values of these quantities are strongly dependent on
the value of the anisotropy parameter (the difference between the tangential
and radial pressure) at the surface of the star. In the presence of the
cosmological constant, a minimum mass configuration with given anisotropy does
exist. Anisotropic compact stellar type objects can be much more compact than
the isotropic ones, and their radii may be close to their corresponding
Schwarzschild radii. Upper bounds for the anisotropy parameter are also
obtained from the analysis of the curvature invariants. General restrictions
for the redshift and the total energy (including the gravitational
contribution) for anisotropic stars are obtained in terms of the anisotropy
parameter. Values of the surface redshift parameter greater than two could be
the main observational signature for anisotropic stellar type objects.


  Large Language Models (LLMs) inherently use autoregressive decoding, which
lacks parallelism in inference and results in significantly slow inference
speeds, especially when hardware parallel accelerators and memory bandwidth are
not fully utilized. In this work, we propose Amphista, a speculative decoding
algorithm that adheres to a non-autoregressive decoding paradigm. Owing to the
increased parallelism, our method demonstrates higher efficiency in inference
compared to autoregressive methods. Specifically, Amphista models an
Auto-embedding Block capable of parallel inference, incorporating
bi-directional attention to enable interaction between different drafting
heads. Additionally, Amphista implements Staged Adaptation Layers to facilitate
the transition of semantic information from the base model's autoregressive
inference to the drafting heads' non-autoregressive speculation, thereby
achieving paradigm transformation and feature fusion. We conduct a series of
experiments on a suite of Vicuna models using MT-Bench and Spec-Bench. For the
Vicuna 33B model, Amphista achieves up to 2.75$\times$ and 1.40$\times$
wall-clock acceleration compared to vanilla autoregressive decoding and Medusa,
respectively, while preserving lossless generation quality.


  FPSAC 2013 Extended Abstract. We introduce a new basis of the non-commutative
symmetric functions whose elements have Schur functions as their commutative
images. Dually, we build a basis of the quasi-symmetric functions which expand
positively in the fundamental quasi-symmetric functions and decompose Schur
functions according to a signed combinatorial formula.


  We study the resolved stellar populations of dwarf galaxies in the nearby
Centaurus A/M83 group of galaxies. Our goal is to characterize their
evolutionary history and to investigate eventual similarities or differences
with the dwarf population in other group environments. This work presents the
analysis of five late-type (irregular) dwarfs found in the vicinity of the
giant spiral M83. Using archival HST/ACS data, we perform synthetic
color-magnitude diagram modeling to derive the star formation histories of
these late-type dwarfs. The target objects show heterogeneous star formation
histories, with average star formation rates of 0.08 to 0.70x10^{-2} M_odot/yr.
Some of them present prolonged, global bursts of star formation (~300-500 Myr).
The studied galaxies are all metal-poor ([Fe/H] ~-1.4). We further investigate
the spatial extent of different stellar populations, finding that the young
stars show a clumpy distribution, as opposed to the smooth, broad extent of the
old ones. The actively star forming regions have sizes of ~100 pc and lifetimes
of >~100 Myr, thus suggesting a stochastic star formation mode for the target
dwarf irregular galaxies. The galaxies formed ~20% to 70% of their stars more
than ~7 Gyr ago. The studied dwarfs have average star formation rates slightly
higher than their analogues in the Local Group, but comparable to those in the
M81 group. Our preliminary sample indicates that the neutral gas content of the
target dwarfs does seem to be affected by the group environment: galaxies
within a denser region have a much lower M_HI/<SFR> than the isolated ones,
meaning that they will exhaust their gas reservoir more quickly.


  In this paper we propose a Deep Learning architecture to approximate
diffeomorphisms diffeotopic to the identity. We consider a control system of
the form $\dot x = \sum_{i=1}^lF_i(x)u_i$, with linear dependence in the
controls, and we use the corresponding flow to approximate the action of a
diffeomorphism on a compact ensemble of points. Despite the simplicity of the
control system, it has been recently shown that a Universal Approximation
Property holds. The problem of minimizing the sum of the training error and of
a regularizing term induces a gradient flow in the space of admissible
controls. A possible training procedure for the discrete-time neural network
consists in projecting the gradient flow onto a finite-dimensional subspace of
the admissible controls. An alternative approach relies on an iterative method
based on Pontryagin Maximum Principle for the numerical resolution of Optimal
Control problems. Here the maximization of the Hamiltonian can be carried out
with an extremely low computational effort, owing to the linear dependence of
the system in the control variables.


  We extend the discussion of the antipodal identification of black holes to
the Reissner-Nordstr\"om (RN) spacetime by developing the classical tools
necessary to define the corresponding quantum field theory (QFT). We solve the
massless Klein-Gordon equation in the RN background in terms of scattering
coefficients and provide a procedure for constructing a solution for an
arbitrary analytic extension of RN. The behavior of the maximally extended
solution is highly dependent upon the coefficients of scattering between the
inner and outer horizons, so we present the low-frequency behavior of, and
numerical solutions for, these quantities. We find that, for low enough
frequency, field amplitudes of solutions with purely positive or negative
frequency at each horizon will acquire only a phase after passing both the
inner and outer horizons, while at higher frequencies the amplitudes will tend
to grow exponentially either to the future or to the past, and decay
exponentially in the other direction. Regardless, we can always construct a
basis of globally antipodal symmetric and antisymmetric solutions for any
finite analytic extension of RN. We have characterized this basis in terms of
positive and negative frequency solutions for future use in constructing the
corresponding QFT.


  An analytical model is developed to study the spectra of electromagnetic
dissociation of two-neutron halo nuclei without precise knowledge about initial
and final states. Phenomenological three-cluster bound state wave functions,
reproducing the most relevant features of these nuclei, are used along with no
interaction final states. The 6-He nucleus is considered as a test case, and a
good agreement with experimental data concerning the shape of the spectrum and
the magnitude of the strength function is found.


  The metastable helium triplet in the near-infrared (10833{\AA}) is among the
most important probes of exoplanet atmospheres. It can trace their extended
outer layers and constrain mass-loss. We use the near-infrared high-resolution
spectropolarimeter SPIRou on the CFHT to search for the spectrally resolved
helium triplet in the atmospheres of eleven exoplanets, ranging from warm
mini-Neptunes to hot Jupiters and orbiting G, K, and M dwarfs. Observations
were obtained as part of the SPIRou Legacy Survey and complementary open-time
programs. We apply a homogeneous data reduction to all datasets and set
constraints on the presence of metastable helium, despite the presence of
systematics in the data. We confirm published detections for HAT-P-11b,
HD189733b, and WASP-69b and set upper limits for the other planets. We apply
the p-winds open source code to set upper limits on the mass-loss rate for the
non-detections and to constrain the thermosphere temperature, mass-loss rate,
line-of-sight velocity, and the altitude of the thermosphere for the
detections. We confirm that the presence of metastable helium correlates with
the stellar mass and the XUV flux received by the planets. We investigated the
correlation between the mass-loss rate and the presence of metastable helium,
but it remains difficult to draw definitive conclusions. Finally, some of our
results are in contradiction with previous results in the literature, therefore
we stress the importance of repeatable, homogeneous, and larger-scale analyses
of the helium triplet to obtain robust statistics, study temporal variability,
and better understand how the helium triplet can be used to explore the
evolution of exoplanets.


  In this paper, we study rank 2 (quasi) parabolic bundles over the Riemann
sphere with an effective divisor and these moduli spaces. First we consider a
criterium when a parabolic bundle admits a unramified irregular singular
parabolic connection. Second, to give a good compactification of the moduli
space of semistable parabolic bundles, we introduce a generalization of
parabolic bundles, which is called refined parabolic bundles. Third, we discuss
a stability condition of refined parabolic bundles and define elementary
transformations of the refined parabolic bundles. Finally, we describe the
moduli spaces of refined parabolic bundles when the dimensions of the moduli
spaces are two. These are related to geometry of some weak del Pezzo surfaces.


  We consider a discrete-continuum model of a biomembrane with embedded
particles. While the membrane is represented by a continuous surface, embedded
particles are described by rigid discrete objects which are free to move and
rotate in lateral direction. For the membrane we consider a linearized
Canham-Helfrich energy functional and height and slope boundary conditions
imposed on the particle boundaries resulting in a coupled minimization problem
for the membrane shape and particle positions.
  When considering the energetically optimal membrane shape for each particle
position we obtain a reduced energy functional that models the implicitly given
interaction potential for the membrane-mediated mechanical particle-particle
interactions. We show that this interaction potential is differentiable with
respect to the particle positions and orientations. Furthermore we derive a
fully practical representation of the derivative only in terms of well defined
derivatives of the membrane. This opens the door for the application of
minimization algorithms for the computation of minimizers of the coupled system
and for further investigation of the interaction potential of membrane-mediated
mechanical particle--particle interaction.
  The results are illustrated with numerical examples comparing the explicit
derivative formula with difference quotient approximations. We furthermore
demonstrate the application of the derived formula to implement a gradient flow
for the approximation of optimal particle configurations.


  In conventional solar cells, photogenerated carriers lose part of their
energy before they can be extracted to make electricity. The aim of hot-carrier
solar cells is to extract the carriers before this energy loss, thereby turning
more energy into electrical power. This requires extracting the carriers in a
nonequilibrium (nonthermal) energy distribution. Here, we investigate the
performance of hot-carrier solar cells for such nonequilibrium distributions.
We propose a quantum transport model in which each energy-loss process (carrier
thermalization, relaxation, and recombination) is simulated by a B\"uttiker
probe. We study charge and heat transport to analyze the hot-carrier solar
cell's power output and efficiency, introducing partial efficiencies for
different loss processes and the carrier extraction. We show that producing
electrical power from a nonequilibrium distribution has the potential to
improve the output power and efficiency. Furthermore, in the limit where the
distribution is thermal, we prove that a boxcar-shaped transmission for the
carrier extraction maximizes the efficiency at any given output power.


  We prove an inequality on the Kantorovich-Rubinstein distance --which can be
seen as a particular case of a Wasserstein metric-- between two solutions of
the spatially homogeneous Boltzmann equation without angular cutoff, but with a
moderate angular singularity. Our method is in the spirit of [7]. We deduce
some well-posedness and stability results in the physically relevant cases of
hard and moderately soft potentials. In the case of hard potentials, we relax
the regularity assumption of [6], but we need stronger assumptions on the tail
of the distribution (namely some exponential decay). We thus obtain the first
uniqueness result for measure initial data. In the case of moderately soft
potentials, we prove existence and uniqueness assuming only that the initial
datum has finite energy and entropy (for very moderately soft potentials), plus
sometimes an additionnal moment condition. We thus improve significantly on all
previous results, where weighted Sobolev spaces were involved.


  The Su-Schrieffer-Heeger model of polyacetylene is a paradigmatic Hamiltonian
exhibiting non-trivial edge states. By using Floquet theory we study how the
spectrum of this one-dimensional topological insulator is affected by a
time-dependent potential. In particular, we evidence the competition among
different photon-assisted processes and the native topology of the unperturbed
Hamiltonian to settle the resulting topology at different driving frequencies.
While some regions of the quasienergy spectrum develop new gaps hosting Floquet
edge states, the native gap can be dramatically reduced and the original edge
states may be destroyed or replaced by new Floquet edge states. Our study is
complemented by an analysis of Zak phase applied to the Floquet bands. Besides
serving as a simple example for understanding the physics of driven topological
phases, our results could find a promising test-ground in cold matter
experiments.


  In the upper layers of the solar atmosphere the temperature increases
sharply. We studied possibility of the transfer of neutrals motion energy into
the electrostatic waves.Electrostatic waves could damp in the upper layers of
the solar atmosphere and their energy could be transformed into the thermal
energy of the solar atmosphere plasma. When studying the plasma dynamics in the
low altitudes of the solar atmosphere, we investigated hydrodynamics of the
plasma which consists of thee components-electrons, ions and neutrals. In order
to study evolution of disturbances of high amplitudes the parametric resonance
technique is used. The dispersion relation for the electrostatic waves excited
due tot he motion of neutrals is derived. The frequencies of electromagnetic
waves which could be excited due to existence of the acoustic wave are found.
The increment of excited electrostatic waves are determined. The motion of the
neutrals in the lower solar atmosphere, where ionization rate is low, could
excite electrostatic waves. In the upper solar atmosphere the ionization rate
increases and motion of the neutrals could not support electrostatic waves and
these waves could damp due to the collision of the charged particles. The
energy of the damping waves could be transformed into the thermal energy of the
plasma in the upper atmosphere.


  Score based generative models are a new class of generative models that have
been shown to accurately generate high dimensional calorimeter datasets. Recent
advances in generative models have used images with 3D voxels to represent and
model complex calorimeter showers. Point clouds, however, are likely a more
natural representation of calorimeter showers, particularly in calorimeters
with high granularity. Point clouds preserve all of the information of the
original simulation, more naturally deal with sparse datasets, and can be
implemented with more compact models and data files. In this work, two
state-of-the-art score based models are trained on the same set of calorimeter
simulation and directly compared.


  The increase of available large clinical and experimental datasets has
contributed to a substantial amount of important contributions in the area of
biomedical image analysis. Image segmentation, which is crucial for any
quantitative analysis, has especially attracted attention. Recent hardware
advancement has led to the success of deep learning approaches. However,
although deep learning models are being trained on large datasets, existing
methods do not use the information from different learning epochs effectively.
In this work, we leverage the information of each training epoch to prune the
prediction maps of the subsequent epochs. We propose a novel architecture
called feedback attention network (FANet) that unifies the previous epoch mask
with the feature map of the current training epoch. The previous epoch mask is
then used to provide a hard attention to the learned feature maps at different
convolutional layers. The network also allows to rectify the predictions in an
iterative fashion during the test time. We show that our proposed
\textit{feedback attention} model provides a substantial improvement on most
segmentation metrics tested on seven publicly available biomedical imaging
datasets demonstrating the effectiveness of FANet. The source code is available
at \url{https://github.com/nikhilroxtomar/FANet}.


  Ultrasound imaging is caught between the quest for the highest image quality,
and the necessity for clinical usability. Our contribution is two-fold: First,
we propose a novel fully convolutional neural network for ultrasound
reconstruction. Second, a custom loss function tailored to the modality is
employed for end-to-end training of the network. We demonstrate that training a
network to map time-delayed raw data to a minimum variance ground truth offers
performance increases in a clinical environment. In doing so, a path is
explored towards improved clinically viable ultrasound reconstruction. The
proposed method displays both promising image reconstruction quality and
acquisition frequency when integrated for live ultrasound scanning. A clinical
evaluation is conducted to verify the diagnostic usefulness of the proposed
method in a clinical setting.


  We address the problem of finding the zeros of the sum of a maximally
monotone operator and a cocoercive operator. Our approach introduces a
modification to the forward-backward method by integrating an inertial/momentum
term alongside a correction term. We demonstrate that the sequence of
iterations thus generated converges weakly towards a solution for the monotone
inclusion problem. Furthermore, our analysis reveals an outstanding attribute
of our algorithm: it displays rates of convergence of the order $o(1/k)$ for
the discrete velocity and the tangent residual approaching zero. These rates
for tangent residuals can be extended to fixed-point residuals frequently
discussed in the existing literature. Specifically, when applied to minimize a
nonsmooth convex function subject to linear constraints, our method evolves
into a primal-dual full splitting algorithm. Notably, alongside the convergence
of iterates, this algorithm possesses a remarkable characteristic of
nonergodic/last iterate $o(1/k)$ convergence rates for both the function value
and the feasibility measure. Our algorithm showcases the most advanced
convergence and convergence rate outcomes among primal-dual full splitting
algorithms when minimizing nonsmooth convex functions with linear constraints.


  An optical microscopic examination of thinly cut stained tissue on glass
slides prepared from a FFPE tissue blocks is the gold standard for tissue
diagnostics. In addition, the diagnostic abilities and expertise of any
pathologist is dependent on their direct experience with common as well as
rarer variant morphologies. Recently, deep learning approaches have been used
to successfully show a high level of accuracy for such tasks. However,
obtaining expert-level annotated images is an expensive and time-consuming task
and artificially synthesized histological images can prove greatly beneficial.
Here, we present an approach to not only generate histological images that
reproduce the diagnostic morphologic features of common disease but also
provide a user ability to generate new and rare morphologies. Our approach
involves developing a generative adversarial network model that synthesizes
pathology images constrained by class labels. We investigated the ability of
this framework in synthesizing realistic prostate and colon tissue images and
assessed the utility of these images in augmenting diagnostic ability of
machine learning methods as well as their usability by a panel of experienced
anatomic pathologists. Synthetic data generated by our framework performed
similar to real data in training a deep learning model for diagnosis.
Pathologists were not able to distinguish between real and synthetic images and
showed a similar level of inter-observer agreement for prostate cancer grading.
We extended the approach to significantly more complex images from colon
biopsies and showed that the complex microenvironment in such tissues can also
be reproduced. Finally, we present the ability for a user to generate deepfake
histological images via a simple markup of sematic labels.


  We study the existence of gradient conformal Killing vectors (CKVs) in LRS
spacetimes, and investigate some implications for the evolutionary character of
marginally outer trapped surfaces. We first study existence of gradient CKVs
via the obtention of a relationship between the Ricci curvature and the
gradient of the divergence of the CKV. This provides an alternative set of
equations, for which the integrability condition is obtained, to analyze the
existence of gradient CKVs. A uniqueness result is obtained in the case of
perfect fluids, where it is demonstrated that the Robertson-Walker solution is
the unique perfect fluid solution with a nonvanishing pressure, admitting a
timelike gradient CKV. The constant mean curvature condition for LRS spacetimes
is also obtained, characterized by three distinct conditions which are
specified by a set of three scalars. Linear combinations of these scalars,
whose vanishing define the constant mean curvature condition, turn out to be
related to the evolutions of null expansions of 2-sphere along their null
normal directions. As such, some implications for the existence of black holes
and the character of the associated horizons are obtained. It is further shown
that dynamical black holes of increasing area, with a non-vanishing heat flux
across the horizon, will be in equilibrium, with respect to the frame of the
conformal observers.