  We present a Bayesian approach for the Contamination Source Detection problem
in Water Distribution Networks. Given an observation of contaminants in one or
more nodes in the network, we try to give probable explanation for it assuming
that contamination is a rare event. We introduce extra variables to
characterize the place and pattern of the first contamination event. Then we
write down the posterior distribution for these extra variables given the
observation obtained by the sensors. Our method relies on Belief Propagation
for the evaluation of the marginals of this posterior distribution and the
determination of the most likely origin. The method is implemented on a
simplified binary forward-in-time dynamics. Simulations on data coming from the
realistic simulation software EPANET on two networks show that the simplified
model is nevertheless flexible enough to capture crucial information about
contaminant sources.


  The DArk Matter Particle Explorer (DAMPE) has reported a measurement of the
flux of high energy cosmic ray electrons plus positrons (CREs) in the energy
range between $25$ GeV and $4.6$ TeV. With unprecedented high energy
resolution, the DAMPE data exhibit an excess of the CREs flux at an energy of
around $1.4$ TeV. In this letter, we discuss how the observed excess can be
understood in a minimal framework where the Standard Model (SM) is supplemented
by a stable SM singlet scalar as dark matter (DM) and type II seesaw for
generating the neutrino mass matrix. In our framework, a pair of DM particles
annihilates into a pair of the SM SU(2) triplet scalars ($\Delta$s) in type II
seesaw, and the subsequent $\Delta$ decays create the primary source of the
excessive CREs around $1.4$ TeV. The lepton flavor structure of the primary
source of CREs has a direct relationship with the neutrino oscillation data. We
find that the DM interpretation of the DAMPE excess determines the pattern of
neutrino mass spectrum to be the inverted hierarchy type, taking into account
the constraints from the Fermi-LAT observations of dwarf spheroidal galaxies.


  In this thesis, we aim to understand the microscopic details and origin of
the Cosmological Horizon, produced by a static observer in four-dimensional de
Sitter (dS$_4$) spacetime. We consider a deformed extension of dS spacetime by
means of a single $\mathbb Z_q$ quotient, which resembles an Orbifold geometry.
The Orbifold parameter induces a pair of codimension two minimal surfaces given
by 2-spheres in the Euclidean geometry. Using dimensional reduction on the
two-dimensional plane where the minimal surfaces have support, we use the
Liouville field theory and the Kerr/CFT mechanism in order to describe the
underlying degrees of freedom of the Cosmological Horizon. We then show, that
in the large $q$-limit, this pair of codimensions two surfaces can be realized
as the conformal boundaries of dS$_3$. We notice that the central charge
obtained using Liouville theory, in the latter limit, corresponds to the
Strominger central charge obtained in the context of the dS/CFT correspondence.
In addition, a formulation of entanglement entropy for de Sitter spacetimes is
given in terms of dS holography and also a different approach in which the
entanglement between two disconnected bulk observers is described in terms of
the topology of the spacetime. Therefore, a quarter of the area formula is
proposed, in which the area corresponds to the are of the set of fixed points
of an $S^2/\mathbb Z_q$ orbifold.


  We show that, using the Coulomb fluid approach, we are able to derive a rate
function $\Psi(c,x)$ of two variables that captures: (i) the large deviations
of bulk eigenvalues; (ii) the large deviations of extreme eigenvalues (both
left and right large deviations); (iii) the statistics of the fraction $c$ of
eigenvalues to the left of a position $x$. Thus, $\Psi(c,x)$ explains the full
order statistics of the eigenvalues of large random Gaussian matrices as well
as the statistics of the shifted index number. All our analytical findings are
thoroughly compared with Monte Carlo simulations, obtaining excellent
agreement. A summary of preliminary results was already presented in [22] in
the context of one-dimensional trapped spinless fermions in a harmonic
potential.


  Intermediate-task training---fine-tuning a pretrained model on an
intermediate task before fine-tuning again on the target task---often improves
model performance substantially on language understanding tasks in monolingual
English settings. We investigate whether English intermediate-task training is
still helpful on non-English target tasks. Using nine intermediate
language-understanding tasks, we evaluate intermediate-task transfer in a
zero-shot cross-lingual setting on the XTREME benchmark. We see large
improvements from intermediate training on the BUCC and Tatoeba sentence
retrieval tasks and moderate improvements on question-answering target tasks.
MNLI, SQuAD and HellaSwag achieve the best overall results as intermediate
tasks, while multi-task intermediate offers small additional improvements.
Using our best intermediate-task models for each target task, we obtain a 5.4
point improvement over XLM-R Large on the XTREME benchmark, setting the state
of the art as of June 2020. We also investigate continuing multilingual MLM
during intermediate-task training and using machine-translated
intermediate-task data, but neither consistently outperforms simply performing
English intermediate-task training.


  Ulcerative colitis (UC) is a chronic inflammatory bowel disease characterized
by relapsing inflammation of the large intestine. The severity of UC is often
represented by the Mayo Endoscopic Subscore (MES) which quantifies mucosal
disease activity from endoscopy videos. In clinical trials, an endoscopy video
is assigned an MES based upon the most severe disease activity observed in the
video. For this reason, severe inflammation spread throughout the colon will
receive the same MES as an otherwise healthy colon with severe inflammation
restricted to a small, localized segment. Therefore, the extent of disease
activity throughout the large intestine, and overall response to treatment, may
not be completely captured by the MES. In this work, we aim to automatically
estimate UC severity for each frame in an endoscopy video to provide a higher
resolution assessment of disease activity throughout the colon. Because
annotating severity at the frame-level is expensive, labor-intensive, and
highly subjective, we propose a novel weakly supervised, ordinal classification
method to estimate frame severity from video MES labels alone. Using clinical
trial data, we first achieved 0.92 and 0.90 AUC for predicting mucosal healing
and remission of UC, respectively. Then, for severity estimation, we
demonstrate that our models achieve substantial Cohen's Kappa agreement with
ground truth MES labels, comparable to the inter-rater agreement of expert
clinicians. These findings indicate that our framework could serve as a
foundation for novel clinical endpoints, based on a more localized scoring
system, to better evaluate UC drug efficacy in clinical trials.


  We propose the first joint audio-video generation framework that brings
engaging watching and listening experiences simultaneously, towards
high-quality realistic videos. To generate joint audio-video pairs, we propose
a novel Multi-Modal Diffusion model (i.e., MM-Diffusion), with two-coupled
denoising autoencoders. In contrast to existing single-modal diffusion models,
MM-Diffusion consists of a sequential multi-modal U-Net for a joint denoising
process by design. Two subnets for audio and video learn to gradually generate
aligned audio-video pairs from Gaussian noises. To ensure semantic consistency
across modalities, we propose a novel random-shift based attention block
bridging over the two subnets, which enables efficient cross-modal alignment,
and thus reinforces the audio-video fidelity for each other. Extensive
experiments show superior results in unconditional audio-video generation, and
zero-shot conditional tasks (e.g., video-to-audio). In particular, we achieve
the best FVD and FAD on Landscape and AIST++ dancing datasets. Turing tests of
10k votes further demonstrate dominant preferences for our model. The code and
pre-trained models can be downloaded at
https://github.com/researchmm/MM-Diffusion.


  In this paper, an upper bound for the perfect Italian domination number of
the cartesian product of any two graphs is obtained and the exact value of this
parameter for cartesian product of some special graphs are obtained. We have
also proved that for any two positive integers $a$, $b$ there exists a graph
$G$ and an induced subgraph $H$ of $G$ such that $\gamma_I^p(G) = a$ and
$\gamma_I^p(H) = b$. Relationship of the perfect Italian domination number with
the Roman domination number and the perfect domination number of a graph $G$
are obtained and the corresponding realization problems are also solved. We
have also obtained the perfect Italian domination number of the Mycielskian of
a graph in terms of the perfect domination number of the graph. Some open
problems related to this parameters are also included.


  We present a method for combining multi-agent communication and traditional
data-driven approaches to natural language learning, with an end goal of
teaching agents to communicate with humans in natural language. Our starting
point is a language model that has been trained on generic, not task-specific
language data. We then place this model in a multi-agent self-play environment
that generates task-specific rewards used to adapt or modulate the model,
turning it into a task-conditional language model. We introduce a new way for
combining the two types of learning based on the idea of reranking language
model samples, and show that this method outperforms others in communicating
with humans in a visual referential communication task. Finally, we present a
taxonomy of different types of language drift that can occur alongside a set of
measures to detect them.


  Despite intense efforts it has remained unresolved whether and how
interfacial spin-orbit coupling (ISOC) affects spin transport across heavy
metal (HM)/ferromagnet (FM) interfaces. Here we report conclusive experiment
evidence that the ISOC at HM/FM interfaces is the dominant mechanism for "spin
memory loss". An increase in ISOC significantly reduces, in a linear manner,
the dampinglike spin-orbit torque (SOT) exerted on the FM layer via degradation
of the spin transparency of the interface for spin currents generated in the
HM. In addition, the fieldlike SOT is also dominated by the spin Hall
contribution of the HM and decreases with increasing ISOC. This work reveals
that ISOC at HM/FM interfaces should be minimized to advance efficient SOT
devices through atomic layer passivation of the HM/FM interface or other means.


  We recall several results in Auslander-Reiten theory for finite-dimensional
algebras over fields and orders over complete local rings. Then we introduce
$n$-cluster tilting subcategories and higher theory of almost split sequences
and Auslander algebras there. Several examples are explained.


  We investigate the efficiency of two very different spoken term detection
approaches for transcription when the available data is insufficient to train a
robust ASR system. This work is grounded in very low-resource language
documentation scenario where only few minutes of recording have been
transcribed for a given language so far.Experiments on two oral languages show
that a pretrained universal phone recognizer, fine-tuned with only a few
minutes of target language speech, can be used for spoken term detection with a
better overall performance than a dynamic time warping approach. In addition,
we show that representing phoneme recognition ambiguity in a graph structure
can further boost the recall while maintaining high precision in the low
resource spoken term detection task.


  We demonstrate a new technique for creating unique forms of pure sp2-bonded
carbon and unprecedented hetero-molecules. These new structures, which we refer
to as sculpturenes, are formed by sculpting selected shapes from bilayer
graphene, hetero-bilayers or multi-layered materials and allowing the shapes to
spontaneously reconstruct. The simplest sculpturene is topologically equivalent
to a torus, with dimensions comparable to those of fullerenes. The topology of
these new molecular structures is stable against atomic scale defects.


  We present four MIPS (24 \micron) and two IRAC (3.6, 4.5, 5.8, and 8.0
\micron) Spitzer observations of the newly discovered Tremendous Outburst
Amplitude Dwarf nova (TOAD) Var Her 04 during decline from super-outburst. The
four MIPS observations span 271 days and the two IRAC observations span 211
days. Along the line-of-sight to Var Her 04, there is a foreground M-star
within 1\arcsec of the variable; as a result, all of the Spitzer photometry
presented in this paper is a blend of the foreground M-star and Var Her 04. We
estimate the quiescent level of the TOAD to be $\Delta V=4-5$ magnitudes below
that of the M-star. Based upon the spectral energy distribution and the 2MASS
colors, we find the M-star to be an M3.5V dwarf at a distance of 80-130 pc.
Based upon its outburst amplitude and quiescent apparent magnitude, we estimate
the distance to Var Her 04 to be 200-400 pc, suggesting that the line-of-sight
foreground star is physically unrelated to the cataclysmic variable. All of the
Spitzer photometry is consistent with the photospheric emission of the
line-of-sight M3.5V star, except for one 24 \micron observation obtained after
the variable re-brightened. This 24 \micron flux density is 75 $\mu$Jy
($4\sigma$) above the preceding and following MIPS observations. We tentatively
suggest that the mid-infrared brightening of 75 $\mu$Jy may be associated with
a dust formation event in the super-outburst ejecta. Assuming a dust
temperature of 100-400 K, we have estimated the amount of dust required. We
find $10^{-13}-10^{-11}$ M$_\odot$ of dust is needed, consistent with amounts
of mass ejection in TOADs expected during super-outburst, and possibly making
TOADs important contributors to the recycling of the interstellar medium.


  Nonlinear relations among frequencies and phases in modulational instability
of circularly polarized Alfven waves are discussed, within the context of one
dimensional, dissipation-less, unforced fluid system. We show that generation
of phase coherence is a natural consequence of the modulational instability of
Alfven waves. Furthermore, we quantitatively evaluate intensity of wave-wave
interaction by using bi-coherence, and also by computing energy flow among wave
modes, and demonstrate that the energy flow is directly related to the phase
coherence generation.


  Purpose: Field monitoring measures field perturbations, which can be
accounted for during image reconstructions. In certain field monitoring
environments, significant phase deviations can arise far from isocenter due to
the finite extent of the gradient and/or main magnet. This can degrade the
accuracy of field dynamics when field probes are placed near or outside the
diameter spherical volume of the gradient coils and/or main magnet, leading to
corrupted image quality. The objective of this work was to develop a correction
algorithm that reduces errors from highly nonlinear phase variations at distant
field probes in field dynamic fits. Methods: The algorithm is split into three
components. Component one fits phase coefficients one spatial order at a time,
while the second implements a weighted least squares solution based on probe
distance. After initial fitting, component three calculates phase residuals and
removes the phase for distant probes before re-fitting. Two healthy volunteers
were scanned on a head-only 7T MRI using diffusion-weighted single-shot spiral
and EPI sequences and field monitoring was performed. Images were reconstructed
with and without phase coefficient correction and compared qualitatively.
Results: The algorithm was able to correct corrupted field dynamics, resulting
in image quality improvements. Significant artefact reduction was observed when
correcting higher order fits, especially for diffusion weighted images.
Stepwise fitting provided the most correction benefit, which was marginally
improved when adding weighted least squares and phase residual corrections.
Conclusion: The proposed algorithm can mitigate effects of phase errors in
field monitoring, providing improved reliability of field dynamic
characterization.


  The increasing statistical power of cosmic microwave background (CMB)
datasets requires a commensurate effort in understanding their noise
properties. The noise in maps from ground-based instruments is dominated by
large-scale correlations, which poses a modeling challenge. This paper develops
novel models of the complex noise covariance structure in the Atacama Cosmology
Telescope Data Release 6 (ACT DR6) maps. We first enumerate the noise
properties that arise from the combination of the atmosphere and the ACT scan
strategy. We then prescribe a class of Gaussian, map-based noise models,
including a new wavelet-based approach that uses directional wavelet kernels
for modeling correlated instrumental noise. The models are empirical, whose
only inputs are a small number of independent realizations of the same region
of sky. We evaluate the performance of these models against the ACT DR6 data by
drawing ensembles of noise realizations. Applying these simulations to the ACT
DR6 power spectrum pipeline reveals a $\sim 20\%$ excess in the covariance
matrix diagonal when compared to an analytic expression that assumes noise
properties are uniquely described by their power spectrum. Along with our
public code, $\mathtt{mnms}$, this work establishes a necessary element in the
science pipelines of both ACT DR6 and future ground-based CMB experiments such
as the Simons Observatory (SO).


  Autonomous agents are supposed to be able to finish tasks or achieve goals
that are assigned by their users through performing a sequence of actions.
Since there might exist multiple plans that an agent can follow and each plan
might promote or demote different values along each action, the agent should be
able to resolve the conflicts between them and evaluate which plan he should
follow. In this paper, we develop a logic-based framework that combines modal
logic and argumentation for value-based practical reasoning with plans. Modal
logic is used as a technique to represent and verify whether a plan with its
local properties of value promotion or demotion can be followed to achieve an
agent's goal. We then propose an argumentation-based approach that allows an
agent to reason about his plans in the form of supporting or objecting to a
plan using the verification results.


  We establish upper bounds for the complexity of Seifert fibered manifolds
with nonempty boundary. In particular, we obtain potentially sharp bounds on
the complexity of torus knot complements.


  In the context of Markov processes, both in discrete and continuous setting,
we show a general relation between duality functions and symmetries of the
generator. If the generator can be written in the form of a Hamiltonian of a
quantum spin system, then the "hidden" symmetries are easily derived. We
illustrate our approach in processes of symmetric exclusion type, in which the
symmetry is of SU(2) type, as well as for the Kipnis-Marchioro-Presutti (KMP)
model for which we unveil its SU(1,1) symmetry. The KMP model is in turn an
instantaneous thermalization limit of the energy process associated to a large
family of models of interacting diffusions, which we call Brownian energy
process (BEP) and which all possess the SU(1,1) symmetry. We treat in details
the case where the system is in contact with reservoirs and the dual process
becomes absorbing.


  The modulational instability of broadband optical pulses in a four-state
atomic system is investigated. In particular, starting from a recently derived
generalized nonlinear Schr\"odinger equation, a wave-kinetic equation is
derived. A comparison between coherent and random phase wave states is made. It
is found that the spatial spectral broadening can contribute to the nonlinear
stability of ultra-short optical pulses. In practical terms, this could be
achieved by using random phase plate techniques.


  We consider the problem of clustering functional data while jointly selecting
the most relevant features for classification. This problem has never been
tackled before in the functional data context, and it requires a proper
definition of the concept of sparsity for functional data. Functional sparse
clustering is here analytically defined as a variational problem with a hard
thresholding constraint ensuring the sparsity of the solution. First, a unique
solution to sparse clustering with hard thresholding in finite dimensions is
proved to exist. Then, the infinite dimensional generalization is given and
proved to have a unique solution. Both the multivariate and the functional
version of sparse clustering with hard thresholding exhibits improvements on
other standard and sparse clustering strategies on simulated data. A real
functional data application is also shown.


  In the recent decades of high-energy physics research, it was demonstrated
that strongly interacting quark-gluon plasma (sQGP) is created in
ultra-relativistic nucleus-nucleus collisions. Investigation and understanding
of the properties of the hadronic matter are among the most important goals of
the NA61/SHINE collaboration at CERN SPS. Mapping of the phase diagram is
achieved by varying the collision energy (5 GeV $\sqrt{s_{NN}}<17$ GeV) and by
changing the collision system ($p$+$p$, $p$+Pb, Be+Be, Ar+Sc, Xe+La, Pb+Pb).
Femtoscopic correlations reveal the space-time structure of the hadron emitting
source.
  In this article, we report on the measurement of femtoscopic correlations in
small to intermediate systems. Comparing the measurements to calculations based
on symmetric L\'evy sources, we discuss the results on L\'evy source parameters
as a function of average pair transverse mass. One of the physical parameters
is of particular importance, the L\'evy exponent $\alpha$, which describes the
shape of the source and may be related to the critical exponent $\eta$ in the
proximity of the critical point. Therefore, measuring it may shed light on the
location of the critical endpoint of the QCD phase diagram.


  We discuss the BRST cohomology and exhibit a connection between the Hodge
decomposition theorem and the topological properties of a two dimensional free
non-Abelian gauge theory having no interaction with matter fields. The
topological nature of this theory is encoded in the vanishing of the Laplacian
operator when equations of motion are exploited. We obtain two sets of
topological invariants with respect to BRST and co-BRST charges on the two
dimensional manifold and show that the Lagrangian density of the theory can be
expressed as the sum of terms that are BRST- and co-BRST invariants.


  Deep Neural Networks (DNNs) have achieved great success in many applications.
The architectures of DNNs play a crucial role in their performance, which is
usually manually designed with rich expertise. However, such a design process
is labour intensive because of the trial-and-error process, and also not easy
to realize due to the rare expertise in practice. Neural Architecture Search
(NAS) is a type of technology that can design the architectures automatically.
Among different methods to realize NAS, Evolutionary Computation (EC) methods
have recently gained much attention and success. Unfortunately, there has not
yet been a comprehensive summary of the EC-based NAS algorithms. This paper
reviews over 200 papers of most recent EC-based NAS methods in light of the
core components, to systematically discuss their design principles as well as
justifications on the design. Furthermore, current challenges and issues are
also discussed to identify future research in this emerging field.


  The small atomic mass of boron indicates strong electron-phonon coupling, so
it may have a brilliant performance in superconductivity. Recently, a new 2D
boride sheet with ordered metal vacancies and surface terminals (Mo4/3B2-x) was
realized in experiments (Science 2021, 373, 801). Here, the 2D monolayer
freestanding Mo4/3B2is evidenced to be thermodynamically stable. Through
electronic structure, phonon spectrum and electron-phonon coupling, monolayer
Mo4/3B2 is found to be an intrinsic phonon-mediated superconductor. The
superconducting transition temperature (Tc) is determined to be 4.06 K by the
McMillian-Allen-Dynes formula. Remarkably, the Tc of monolayer Mo4/3B2 can be
increased to 6.78 K with an appropriate biaxial tensile strain (+5%). Moreover,
we predict that other transition metal replacing Mo atoms is also stable and
retaining the superconductivity. Such as monolayer W4/3B2 is also a
superconductor with the Tc of 2.37 K. Our research results enrich the database
of 2D monolayer superconductors and boron-related formed materials science.


  Let {f_t} be any algebraic family of rational maps of a fixed degree, with a
marked critical point c(t). We first prove that the hypersurfaces of parameters
for which c(t) is periodic converge as a sequence of positive closed (1,1)
currents to the bifurcation current attached to c and defined by DeMarco. We
then turn our attention to the parameter space of polynomials of a fixed degree
d. By intersecting the d-1 currents attached to each critical point of a
polynomial, Bassaneli and Berteloot obtained a positive measure of finite mass
which is supported on the connectedness locus. They showed that its support is
included in the closure of the set of parameters admitting d-1 neutral cycles.
We show that the support of this measure is precisely the closure of the set of
strictly critically finite polynomials (i.e. of Misiurewicz points).


  Let B be an n by n doubly substochastic matrix. We show that B can be written
as a convex combination of no more than {\sigma}(B)+t subpermutation matrices,
where {\sigma}(B) is the number of nonzero elements in B and t is the number of
fully indecomposable components of B^{comp}, the minimal doubly stochastic
completion of B obtained by a specific way.


  A symmetric matrix $C$ is completely positive (CP) if there exists an
entrywise nonnegative matrix $B$ such that $C=BB^T$. The CP-completion problem
is to study whether we can assign values to the missing entries of a partial
matrix (i.e., a matrix having unknown entries) such that the completed matrix
is completely positive. We propose a semidefinite algorithm for solving general
CP-completion problems, and study its properties. When all the diagonal entries
are given, the algorithm can give a certificate if a partial matrix is not
CP-completable, and it almost always gives a CP-completion if it is
CP-completable. When diagonal entries are partially given, similar properties
hold. Computational experiments are also presented to show how CP-completion
problems can be solved.


  Large-scale atomistic computer simulations of materials heavily rely on
interatomic potentials predicting the potential energy and Newtonian forces on
atoms. Traditional interatomic potentials are based on physical intuition but
contain few adjustable parameters and are usually not accurate. The emerging
machine-learning (ML) potentials achieve highly accurate interpolation between
the energies in a large DFT database but, being purely mathematical
constructions, suffer from poor transferability to unknown structures. We
propose a new approach that can drastically improve the transferability of ML
potentials by informing them of the physical nature of interatomic bonding.
This is achieved by combining a rather general physics-based model (analytical
bond-order potential) with a neural-network regression. The network adjusts the
parameters of the physics-based model on the fly during the simulations
according to the local environments of individual atoms. This approach, called
the physically-informed neural network (PINN) potential, is demonstrated by
developing a general-purpose PINN potential for Al. The potential provides a
DFT-level accuracy of energy predictions and excellent agreement with
experimental and DFT data for a wide range of physical properties. We suggest
that the development of physics-based ML potentials is the most effective way
forward in the field of atomistic simulations.


  One noted issue of vector-quantized variational autoencoder (VQ-VAE) is that
the learned discrete representation uses only a fraction of the full capacity
of the codebook, also known as codebook collapse. We hypothesize that the
training scheme of VQ-VAE, which involves some carefully designed heuristics,
underlies this issue. In this paper, we propose a new training scheme that
extends the standard VAE via novel stochastic dequantization and quantization,
called stochastically quantized variational autoencoder (SQ-VAE). In SQ-VAE, we
observe a trend that the quantization is stochastic at the initial stage of the
training but gradually converges toward a deterministic quantization, which we
call self-annealing. Our experiments show that SQ-VAE improves codebook
utilization without using common heuristics. Furthermore, we empirically show
that SQ-VAE is superior to VAE and VQ-VAE in vision- and speech-related tasks.


  We analyze data from Hinode spacecraft taken over two 54-minute periods
during the emergence of AR 11024. We focus on small-scale portions within the
observed solar active region and discover the appearance of very distinctive
small-scale and short-lived dark features in Ca II H chromospheric filtergrams
and Stokes I images. The features appear in regions with close-to-zero
longitudinal magnetic field, and are observed to increase in length before they
eventually disappear. Energy release in the low chromospheric line is detected
while the dark features are fading. In time series of magnetograms a diverging
bipolar configuration is observed accompanying the appearance of the dark
features and the brightenings. The observed phenomena are explained as
evidencing elementary flux emergence in the solar atmosphere, i.e small-scale
arch filament systems rising up from the photosphere to the lower chromosphere
with a length scale of a few solar granules. Brightenings are explained as
being the signatures of chromospheric heating triggered by reconnection of the
rising loops (once they reached chromospheric heights) with pre-existing
magnetic fields as well as to reconnection/cancellation events in U-loop
segments of emerging serpentine fields. We study the temporal evolution and
dynamics of the events and compare them with the emergence of magnetic loops
detected in quiet sun regions and serpentine flux emergence signatures in
active regions. Incorporating the novel features of granular-scale flux
emergence presented in this study we advance the scenario for serpentine flux
emergence.


  The structure of $(\Omega\Omega)_{0^+}$ dibaryon with strangeness $s=-6$ is
studied in the extended chiral SU(3) quark model, in which vector meson
exchange dominates the short range interaction. The resonating group method
(RGM) is adopted, in which the $\Omega\Omega$ and $CC$ (hidden color) channels
are involved. The color screening effect and the effects of mixing of scalar
mesons on $(\Omega\Omega)_{0^+}$ are also investigated.


  We have implemented a new numerical method to obtain the low-energy
many-particle states of the Coulomb glass. First, this method creates an
initial set of low-energy states by a hybrid of local search and simulated
annealing approaches. Then, systematically investigating the surroundings of
the states found, this set is completed. The transition rates between these
states are calculated. The connectivity of the corresponding graph is analysed
in dependence on temperature and duration of measurement. We study how the
formation of clusters is reflected in the specific heat as non-ergodic effects.


  We discuss a numerical model for black hole growth and its associated
feedback processes that for the first time allows cosmological simulations of
structure formation to self-consistently follow the build up of the cosmic
population of galaxies and active galactic nuclei. Our model assumes that seed
black holes are present at early cosmic epochs at the centres of forming halos.
We then track their growth from gas accretion and mergers with other black
holes in the course of cosmic time. For black holes that are active, we
distinguish between two distinct modes of feedback, depending on the black hole
accretion rate itself. Black holes that accrete at high rates are assumed to be
in a `quasar regime', where we model their feedback by thermally coupling a
small fraction of their bolometric luminosity to the surrounding gas. For black
holes with low accretion rates, we conjecture that most of their feedback
occurs in mechanical form, where AGN-driven bubbles are injected into a gaseous
environment. Using our new model, we carry out TreeSPH cosmological simulations
on the scales of individual galaxies to those of massive galaxy clusters, both
for isolated systems and for cosmological boxes. We demonstrate that our model
produces results for the black hole and stellar mass densities in broad
agreement with observational constraints. We find that the black holes
significantly influence the evolution of their host galaxies, changing their
star formation history, their amount of cold gas, and their colours. Also, the
properties of intracluster gas are affected strongly by the presence of massive
black holes in the cores of galaxy clusters, leading to shallower metallicity
and entropy profiles, and to a suppression of strong cooling flows. [Abridged]


  It seems that the Nazca Lines, ancient geoglyphs of a Peruvian dry pampa, had
some astronomical orientations. Here we discuss a geoglyph representing a
frigatebird and its orientation towards the setting of Fomalhaut, using freely
available software.


  In this talk some of the theoretical aspects of $b \to s \gamma$ transitions
are discussed. The focus is on inclusive decays, since these can be computed
more reliably. Topics covered are (1) perturbative QCD corrections, (2)
non-perturbative contributions and (3) effects of ``new physics'' in these
decays.


  We investigate theoretically the effect of injection of plasmonic carriers
from an optically-excited metal nanocrystal to a semiconductor contact or to
attached molecules. The distributions of optically-excited hot carriers are
dramatically different in metal nanocrystals with large and small sizes. In
large nanocrystals, most carriers have very small energies and the hot carrier
distribution resembles the case of a plasmon wave in bulk. In nanocrystals
smaller than 20nm, the carrier distribution extends to larger energies and
occupies the whole region E_{F}<E<omega. The physical reason for the above
behaviors is non-conservation of momentum in a nanocrystal. Because of the
above properties, nanocrystals of small sizes are most suitable for designing
of opto-electronic and photosynthetic devices based on injection of plasmonic
electrons and holes. The central parameter of the problem is
DeltaN=omega/q_{L}*v_{F}, where q_{L} is the momentum transfer and v_{F} is the
Fermi velocity. In gold nanocrystals, when DeltaN<7, the high-energy
hot-electron generation is efficient. For larger parameters DeltaN, the number
of high-energy electrons is greatly reduced. Another important factor is the
polarization of the exciting light. For efficient excitation of carriers with
high energies, the electric-field polarization vector should be perpendicular
to a prism-like nanoantenna (slab or platelet) with a small width ~ 10-20 nm.
We also show the relation between our theory for injection in plasmonic
nanocrystals and the Fowler theory of injection from a bulk metal. Along with a
prism geometry (or platelet geometry), we consider cubes. The results can be
applied to design both purely solid-state opto-electronic devices and systems
for photo-catalysis and solar conversion.


  Let $ n, q $ be positive integers. We show that if $ G $ is a finitely
generated residually finite group satisfying the identity $ [x,_ny^q]\equiv 1,
$ then there exists a function $ f(n) $ such that $ G $ has a nilpotent
subgroup of finite index of class at most $ f(n) $. We also extend this result
to locally graded groups.


  In wavelength division multiplexed (WDM) optical networks, intraband and/or
interband crosstalk plays a major role in limiting practical implementation of
an OXC subsystem. Again FIBER BRAGG GRATINGS (FBGs), due to their properties,
are emerging as very important elements for both the optical fiber
communication and sensing fields. The crosstalk sources are related to the
different individual components of the OXC's. In this paper, an analytical
model is established to evaluate the performance of an FBG-OC-based optical
cross connect and proposed a novel scheme of transmission Fiber Bragg Grating
for different wavelength separation and determine the BER and power penalty
with optical wavelength division multiplexed cross-connect topologies at
different bit rate.


  In this paper we characterize the set of points where the lateral derivatives
of the Takagi-Van der Waerden functions are infinite. We also prove that the
set of points with infinite derivative has Hausdorff dimension one and Lebesgue
measure zero.


  We study microwave photoresistivity oscillations in a high mobility
two-dimensional electron system subject to strong dc electric fields. We find
that near the second subharmonic of the cyclotron resonance the frequency of
the resistivity oscillations with dc electric field is twice the frequency of
the oscillations at the cyclotron resonance, its harmonics, or in the absence
of microwave radiation. This observation is discussed in terms of the
microwave-induced sidebands in the density of states and the interplay between
different scattering processes in the separated Landau level regime.


  We investigate cross sections for neutrino-12C exclusive scattering and for
muon capture on 12C using wave functions obtained in the ab initio no-core
shell model. In our parameter-free calculations with basis spaces up to the 6
hbarOmega we show that realistic nucleon-nucleon interactions, like e.g. the
CD-Bonn, under predict the experimental cross sections by more than a factor of
two. By including a realistic three-body interaction, Tucson-Melbourne TM'(99),
the cross sections are enhanced significantly and a much better agreement with
experiment is achieved. At the same time,the TM'(99) interaction improves the
calculated level ordering in 12C. The comparison between the CD-Bonn and the
three-body calculations provides strong confirmation for the need to include a
realistic three-body interaction to account for the spin-orbit strength in
p-shell nuclei.


  The stability of strange matter depends on the implicit assumption that
baryon number is conserved. We examine the relevant effective operators which
allow strangelets to decay by violating the conservation of baryon number. From
the experimental lower limit of 10$^{25}$ years on the stability of nuclei, we
find a lower limit of the order 10$^6$ years on the stability of strangelets
against such exotic decays.


  The International Roadmap for Ferroelectric Memories requires
three-dimensional integration of high-dielectric materials onto metal
interconnects or bottom electrodes by 2010. We report the first integration of
high-dielectric oxide films onto carbon nanotube electrodes with an aim of
ultra-high integration density of FeRAMs (Tb/in2).


  Let X be a smooth projectibe curve over a finite field. We consider the Hall
algebra H whose basis is formed by isomorphism classes of coherent sheaves on X
and whose typical structure constant is the number of subsheaves in a given
sheaf belonging to a given isomorphism class and with given isomorphism class
of quotient. We study this algebra in detail. It turns out that its structure
is strikingly similar to that of quantum affine algebras in their loop
realization of Drinfeld. In this analogy the set of simple roots of a
semisimple Lie algebra g corresponds to the set of cusp forms on X, the entries
of the Cartan matrix of g to the values of Rankin-Selberg L-functions
associated to two cusp forms. For the simplest instances of both theories (the
curve P^1, the Lie algebra g=sl_2) the analogy is in fact an identity.


  A new, conceptual proof approach for establishing the existence of
regenerative space-time points for symmetric, translation invariant,
finite-range interaction contact processes on survival is shown. The proof is
elementary, complements the original one, and employs symmetry-based coupling
arguments and a new consequence of convergence to equilibrium of the process in
order to circumvent the original block construction.


  A data word is a sequence of pairs of a letter from a finite alphabet and an
element from an infinite set, where the latter can only be compared for
equality. Safety one-way alternating automata with one register on infinite
data words are considered, their nonemptiness is shown EXPSPACE-complete, and
their inclusion decidable but not primitive recursive. The same complexity
bounds are obtained for satisfiability and refinement, respectively, for the
safety fragment of linear temporal logic with freeze quantification. Dropping
the safety restriction, adding past temporal operators, or adding one more
register, each causes undecidability.


  Several different "hat games" have recently received a fair amount of
attention. Typically, in a hat game, one or more players are required to
correctly guess their hat colour when given some information about other
players' hat colours. Some versions of these games have been motivated by
research in complexity theory and have ties to well-known research problems in
coding theory, and some variations have led to interesting new research.
  In this paper, we review Ebert's Hat Game, which garnered a considerable
amount of publicity in the late 90's and early 00's, and the Hats-on-a-line
Game. Then we introduce a new hat game which is a "hybrid" of these two games
and provide an optimal strategy for playing the new game. The optimal strategy
is quite simple, but the proof involves an interesting combinatorial argument.


  We define a hierarchy of dynamic relaxed gas spheres as solutions of the
Poisson equation coupled to a hierarchy of approximations of the Liouville
equation leading, when this equation is satisfied, to the well-known isothermal
gas spheres in the static case, but also to a new form of dynamic maximum
relaxation. The two previous steps of the hierarchy correspond to an increasing
degree of local relaxation at the center of the configuration.


  In this paper we study Markov processes and related first passage problems on
a class of weighted, modular graphs which generalize the Dyson hierarchical
model. In these networks, the coupling strength between two nodes depends on
their distance and is modulated by a parameter $\sigma$. We find that, in the
thermodynamic limit, ergodicity is lost and the "distant" nodes can not be
reached. Moreover, for finite-sized systems, there exists a threshold value for
$\sigma$ such that, when $\sigma$ is relatively large, the inhomogeneity of the
coupling pattern prevails and "distant" nodes are hardly reached. The same
analysis is carried on also for generic hierarchical graphs, where interactions
are meant to involve $p$-plets ($p>2$) of nodes, finding that ergodicity is
still broken in the thermodynamic limit, but no threshold value for $\sigma$ is
evidenced, ultimately due to a slow growth of the network diameter with the
size.


  This article considers recovery of signals that are sparse or approximately
sparse in terms of a (possibly) highly overcomplete and coherent tight frame
from undersampled data corrupted with additive noise. We show that the properly
constrained $l_1$-analysis, called analysis Dantzig selector, stably recovers a
signal which is nearly sparse in terms of a tight frame provided that the
measurement matrix satisfies a restricted isometry property adapted to the
tight frame. As a special case, we consider the Gaussian noise. Further, under
a sparsity scenario, with high probability, the recovery error from noisy data
is within a log-like factor of the minimax risk over the class of vectors which
are at most $s$ sparse in terms of the tight frame. Similar results for the
analysis LASSO are showed.
  The above two algorithms provide guarantees only for noise that is bounded or
bounded with high probability (for example, Gaussian noise). However, when the
underlying measurements are corrupted by sparse noise, these algorithms perform
suboptimally. We demonstrate robust methods for reconstructing signals that are
nearly sparse in terms of a tight frame in the presence of bounded noise
combined with sparse noise. The analysis in this paper is based on the
restricted isometry property adapted to a tight frame, which is a natural
extension to the standard restricted isometry property.


  We demonstrate the Ramsey analogous experiment known as coherent control,
taking place along an electrically-driven semiconductor optical amplifier
operating at room temperature.


  In this paper we introduce fractional powers of quaternionic operators. Their
definition is based on the theory of slice-hyperholomorphic functions and on
the $S$-resolvent operators of the quaternionic functional calculus. The
integral representation formulas of the fractional powers and the quaternionic
version of Kato's formula are based on the notion of $S$-spectrum of a
quaternionic operator.
  The proofs of several properties of the fractional powers of quaternionic
operators rely on the $S$-resolvent equation. This equation, which is very
important and of independent interest, has already been introduced in the case
of bounded quaternionic operators, but for the case of unbounded operators some
additional considerations have to be taken into account. Moreover, we introduce
a new series expansion for the pseudo-resolvent, which is of independent
interest and allows to investigate the behavior of the $S$-resolvents close to
the $S$-spectrum.
  The paper is addressed to researchers working in operator theory and in
complex analysis.


  We analyze the quantum regime of the dynamical backaction cooling of a
mechanical resonator assisted by a driven harmonic oscillator (cavity). Our
treatment applies to both optomechanical and electromechanical realizations and
includes the effect of thermal noise in the driven oscillator. In the
perturbative case, we derive the corresponding motional master equation using
the Nakajima-Zwanzig formalism and calculate the corresponding output spectrum
for the optomechanical case. Then we analyze the strong optomechanical coupling
regime in the limit of small cavity linewidth. Finally we consider the steady
state covariance matrix of the two coupled oscillators for arbitrary input
power and obtain an analytical expression for the final mechanical occupancy.
This is used to optimize the drive's detuning and input power for an
experimentally relevant range of parameters that includes the "ground state
cooling" regime.


  The rare B decays Bs(d)-->\mu\mu, B-->K*\mu\mu and Bs-->\phi\gamma are
studied using up to \sim 0.41 fb^{-1} of pp collisions at \sqrt{s} = 7 TeV
collected by the \lhcb experiment in 2010 and 2011. A search for the decays
Bs(d)-->\mu\mu, is performed with 0.41 fb^{-1} . The absence of significant
signal leads to BR(Bs-->\mu\mu<1.4 x 10^{-8} and BR(Bd-->\mu\mu<3.2 x 10^{-9}
at 95% confidence level. The forward-backward asymmetry, fraction of
longitudinal polarization and differential branching fraction of B-->K*\mu\mu,
as a function of dimuon invariant mass, are measured in 0.31 fb^{-1}.
  The ratio of branching ratios of the radiative B decays B--> K*\gamma and
Bs-->\phi\gamma h as been measured using 0.34fb^{-1}. The obtained value for
the ratio is 1.52 \pm 0.14 (stat) \pm 0.10 (syst) \pm 0.12 (f_s/f_d). Using the
HFAG value for BR(Bd --> K^*\gamma), BR(Bs-->\phi\gamma) has been found to be
(2.8 \pm 0.5)\times 10^{-5}.


  In the present paper, we are going to study metric properties of
unconventional limit set of a semigroup $G$ generated by contractive functions
$\{f_{i}\}_{i=1}^N$ on the unit ball $\mathbb Z_p$ of $p$-adic numbers. Namely,
we prove that the unconventional limit set is compact, perfect and uniformly
disconnected. Moreover, we provide an example of two contractions for which the
corresponding unconventional limiting set is quasi-symmetrically equivalent to
the symbolic Cantor set.


  The questions of what represents space-time in GR, the status of
gravitational energy, the substantivalist-relationalist issue, and the
(non)exceptional status of gravity are interrelated. If space-time has
energy-momentum, then space-time is substantival. Two extant ways to avoid the
substantivalist conclusion deny that the energy-bearing metric is part of
space-time or deny that gravitational energy exists. Feynman linked doubts
about gravitational energy to GR-exceptionalism; particle physics
egalitarianism encourages realism about gravitational energy.
  This essay proposes a third view, involving a particle physics-inspired
non-perturbative split that characterizes space-time with a constant background
_matrix_ (not a metric), avoiding the inference from gravitational energy to
substantivalism: space-time is (M, eta), where eta=diag(-1,1,1,1) is a
spatio-temporally constant numerical signature matrix (already used in GR with
spinors). The gravitational potential, bearing any gravitational energy, is
g_(munu)(x)-eta (up to field redefinitions), an _affine_ geometric object with
a tensorial Lie derivative and a vanishing covariant derivative. This
non-perturbative split permits strong fields, arbitrary coordinates, and
arbitrary topology, and hence is pure GR by almost any standard. This
razor-thin background, unlike more familiar ones, involves no extra gauge
freedom and so lacks their obscurities and carpet lump-moving.
  After a discussion of Curiel's GR exceptionalist rejection of energy
conservation, the two traditional objections to pseudotensors, coordinate
dependence and nonuniqueness, are explored. Both objections are inconclusive
and getting weaker. A literal interpretation of Noether's theorem (infinitely
many energies) largely answers Schroedinger's false-negative coordinate
dependence problem. Bauer's nonuniqueness (false positive) objection has
several answers.


  The functional generalized additive model (FGAM) provides a more flexible
nonlinear functional regression model than the well-studied functional linear
regression model. This paper restricts attention to the FGAM with identity link
and additive errors, which we will call the additive functional model, a
generalization of the functional linear model. This paper studies the minimax
rate of convergence of predictions from the additive functional model in the
framework of reproducing kernel Hilbert space. It is shown that the optimal
rate is determined by the decay rate of the eigenvalues of a specific kernel
function, which in turn is determined by the reproducing kernel and the joint
distribution of any two points in the random predictor function. For the
special case of the functional linear model, this kernel function is jointly
determined by the covariance function of the predictor function and the
reproducing kernel. The easily implementable roughness-regularized predictor is
shown to achieve the optimal rate of convergence. Numerical studies are carried
out to illustrate the merits of the predictor. Our simulations and real data
examples demonstrate a competitive performance against the existing approach.


  Magnonic frequency combs have recently attracted particular attention due to
their potential impact on spin-wave science. Here, we demonstrate theoretically
the generation of ultra-wideband (UWB) magnonic frequency combs induced by
dissipative coupling in an open cavity magnomechanical system. A broadband comb
with gigahertz repetition rates is obtained in the magnonic spectrum and a
typical non-perturbation frequency-comb structure is also observed. The total
width of the magnonic comb in the robust plateau region can be up to 400 comb
lines, which is much broader and flatter than the reported in the previous
works. Furthermore, when the dissipative coupling strength is further
increased, the chaotic motion is predicted in the magnonic spectrum. Our
results provide an in-depth understanding of nonlinear magnomechanic dynamics
in open quantum systems and fundamentally broadens the research range of magnon
in new spectral regimes.


  Let $K$ be an algebraically closed field with an absolute value. This note
gives an elementary proof of the classical result that the roots of a
polynomial with coefficients in $K$ are continuous functions of the
coefficients of the polynomial.


  Graph learning models have been widely deployed in collaborative filtering
(CF) based recommendation systems. Due to the issue of data sparsity, the graph
structure of the original input lacks potential positive preference edges,
which significantly reduces the performance of recommendations. In this paper,
we study how to enhance the graph structure for CF more effectively, thereby
optimizing the representation of graph nodes. Previous works introduced matrix
completion techniques into CF, proposing the use of either stochastic
completion methods or superficial structure completion to address this issue.
However, most of these approaches employ random numerical filling that lack
control over noise perturbations and limit the in-depth exploration of
higher-order interaction features of nodes, resulting in biased graph
representations.
  In this paper, we propose an Amplify Graph Learning framework based on
Sparsity Completion (called AGL-SC). First, we utilize graph neural network to
mine direct interaction features between user and item nodes, which are used as
the inputs of the encoder. Second, we design a factorization-based method to
mine higher-order interaction features. These features serve as perturbation
factors in the latent space of the hidden layer to facilitate generative
enhancement. Finally, by employing the variational inference, the above
multi-order features are integrated to implement the completion and enhancement
of missing graph structures. We conducted benchmark and strategy experiments on
four real-world datasets related to recommendation tasks. The experimental
results demonstrate that AGL-SC significantly outperforms the state-of-the-art
methods.


  We determine a one-to-one correspondence between Milnor fibers and minimal
symplectic fillings of a quotient surface singularity (up to diffeomorphism
type) by giving an explicit algorithm to compare them mainly via techniques
from the minimal model program for 3-folds and Pinkham's negative weight
smoothing. As by-products, we show that:
  -- Milnor fibers associated to irreducible components of the reduced versal
deformation space of a quotient surface singularity are not diffeomorphic to
each other with a few obvious exceptions. For this, we classify minimal
symplectic fillings of a quotient surface singularity up to diffeomorphism.
  -- Any symplectic filling of a quotient surface singularity is obtained by a
sequence of rational blow-downs from a special resolution (so-called the
maximal resolution) of the singularity, which is an analogue of the one-to-one
correspondence between the irreducible components of the reduced versal
deformation space and the so-called $P$-resolutions of a quotient surface
singularity.


  Given the growing evidence for an exotic S = +1 resonance, seen in kaon,
photon and neutrino induced reactions, we reexamine the existing K+p and K+d
database in order to understand how such a state could have been missed in
previous studies. The lack of structure in this database implies a width of an
MeV or less, assuming a state exists near 1540 MeV.


  We investigate the system-size dependence as well as the temperature
dependence of the conductance in 1D electron systems, paying particular
attention to the effect of Umklapp scattering. By taking into account the
renormalization of the external potential due to electron-electron interaction,
the correction to the conductance, 2e^2/h, due to Umklapp scattering is
estimated perturbatively. The Tomonaga-Luttinger liquid parameter appears in
the conductance via the system-size and temperature dependence.


  We measure the temperature of a mesoscopic system consisting of an
ultra-dilute two dimensional electron gas at the $Si/SiO_2$ interface in a
metal-oxide-semiconductor field effect transistor (MOSFET) quantum dot by means
of the capture and emission of an electron in a point defect close to the
interface. Contrarily to previous reports, we show that the capture and
emission by point defects in Si n-MOSFETs can be temperature dependent down to
800 mK. As the finite quantum grand canonical ensemble model applies, the time
domain charge fluctuation in the defect is used to determine the temperature of
the few electron gas in the channel.


  A novel method for computing torus amplitudes in orbifold compactifications
is suggested. It applies universally for every Abelian $\mathbb{Z}_{N}$
orbifold without requiring the unfolding technique. This method follows from
the possibility of obtaining integrals over fundamental domains of every Hecke
congruence subgroup $\Gamma_{0}[N]$ by computing contour integrals over
one-dimensional curves uniformly distributed in these domains.


  We consider a one-dimensional mono-atomic lattice with random perturbations
of masses spread over a finite number of particles. Assuming Newtonian dynamics
and linear nearest-neighbour interactions and allowing for a provision of
pinning due to substrate interaction, we discuss a transient dynamics problem
and a time-harmonic transmission problem. By a stochastic, multiscale analysis
we provide asymptotic expressions for the displacement field that propagates
through the random perturbations and for the time-harmonic transmission
coefficients. These theoretical predictions are supported by illustrations of
their agreements with numerical simulations.


  We constrain the sky-projected obliquities of two low-density hot Neptune
planets HATS-38 b and WASP-139 b orbiting nearby G and K stars using
Rossiter-McLaughlin (RM) observations with VLT/ESPRESSO, yielding $\lambda =
-108_{-16}^{+11}$ deg and $-85.6_{-4.2}^{+7.7}$ deg, respectively. To model the
RM effect, we use a new publicly available code, \texttt{ironman}, which is
capable of jointly fitting transit photometry, Keplerian radial velocities, and
RM effects. The two planets have residual eccentricities ($e=
0.112_{-0.070}^{+0.072}$, and $0.103_{-0.041}^{+0.050}$, respectively), and
together with the obliquity constraints, we show that they join a growing group
of eccentric hot and low-density Neptunes on polar orbits. We use long-term
radial velocities to rule out companions with masses $\sim 0.3-50$ $M_J$ within
$\sim$10 au. We show that the orbital architectures of the two Neptunes
disfavor an origin from primordial disk misalignment and/or in-situ secular
interactions with distant companions and instead favor high-eccentricity
migration from $\gtrsim 2$ au driven by a distant companion. Finally, we
performed a hierarchical Bayesian modeling of the true obliquity distribution
of Neptunes and found suggestive evidence for a higher preponderance of polar
orbits of hot Neptunes compared to Jupiters. However, we note that the exact
distribution is sensitive to the choice of priors, highlighting the need for
additional obliquity measurements of Neptunes to robustly compare the hot
Neptune obliquity distribution to Jupiters.


  Let L be a finite dimensional simple Lie superalgebra over an algebraically
closed field of characteristic different from 2. In this paper, we prove that
each skew-supersymmtric super-biderivation of L is inner. Furthermore, we prove
that each linear super-commuting map on L is a scalar multiplication map.


  A novel three-fluid dynamical model for simulations of heavy-ion collisions
at RHIC Beam Energy Scan programme, called MUFFIN, has been developed. The
novelty consists of modular inclusion of the Equation of State, use of
hyperbolic coordinates that allow to simulate higher collision energies, and
fluctuating initial conditions. The model reproduces rapidity and $p_t$ spectra
of collisions from $\sqrt{s_{NN}}$=7.7 to 62.4 GeV. Ideal fluid is assumed, and
the elliptic flow is over-predicted, particularly at lower collision energies.


  Financial market predictions utilize historical data to anticipate future
stock prices and market trends. Traditionally, these predictions have focused
on the statistical analysis of quantitative factors, such as stock prices,
trading volumes, inflation rates, and changes in industrial production. Recent
advancements in large language models motivate the integrated financial
analysis of both sentiment data, particularly market news, and numerical
factors. Nonetheless, this methodology frequently encounters constraints due to
the paucity of extensive datasets that amalgamate both quantitative and
qualitative sentiment analyses. To address this challenge, we introduce a
large-scale financial dataset, namely, Financial News and Stock Price
Integration Dataset (FNSPID). It comprises 29.7 million stock prices and 15.7
million time-aligned financial news records for 4,775 S&P500 companies,
covering the period from 1999 to 2023, sourced from 4 stock market news
websites. We demonstrate that FNSPID excels existing stock market datasets in
scale and diversity while uniquely incorporating sentiment information. Through
financial analysis experiments on FNSPID, we propose: (1) the dataset's size
and quality significantly boost market prediction accuracy; (2) adding
sentiment scores modestly enhances performance on the transformer-based model;
(3) a reproducible procedure that can update the dataset. Completed work, code,
documentation, and examples are available at github.com/Zdong104/FNSPID. FNSPID
offers unprecedented opportunities for the financial research community to
advance predictive modeling and analysis.


  Deep networks have achieved great success in image rescaling (IR) task that
seeks to learn the optimal downscaled representations, i.e., low-resolution
(LR) images, to reconstruct the original high-resolution (HR) images. Compared
with super-resolution methods that consider a fixed downscaling scheme, e.g.,
bicubic, IR often achieves significantly better reconstruction performance
thanks to the learned downscaled representations. This highlights the
importance of a good downscaled representation in image reconstruction tasks.
Existing IR methods mainly learn the downscaled representation by jointly
optimizing the downscaling and upscaling models. Unlike them, we seek to
improve the downscaled representation through a different and more direct way:
optimizing the downscaled image itself instead of the down-/upscaling models.
Specifically, we propose a collaborative downscaling scheme that directly
generates the collaborative LR examples by descending the gradient w.r.t. the
reconstruction loss on them to benefit the IR process. Furthermore, since LR
images are downscaled from the corresponding HR images, one can also improve
the downscaled representation if we have a better representation in the HR
domain. Inspired by this, we propose a Hierarchical Collaborative Downscaling
(HCD) method that performs gradient descent in both HR and LR domains to
improve the downscaled representations. Extensive experiments show that our HCD
significantly improves the reconstruction performance both quantitatively and
qualitatively. Moreover, we also highlight the flexibility of our HCD since it
can generalize well across diverse IR models.


  This paper studies Hamilton-Jacobi equations of evolution type defined in a
general metric space. We give a notion of a solution through optimal principles
and establish a unique existence theorem of the solution for initial value
problems. We also note a relationship between the notion of a solution and
another notion based on characterization of the modulus of the gradient in the
sense of [13].


  The recent development on large multimodal models (LMMs), especially
GPT-4V(ision) and Gemini, has been quickly expanding the capability boundaries
of multimodal models beyond traditional tasks like image captioning and visual
question answering. In this work, we explore the potential of LMMs like GPT-4V
as a generalist web agent that can follow natural language instructions to
complete tasks on any given website. We propose SEEACT, a generalist web agent
that harnesses the power of LMMs for integrated visual understanding and acting
on the web. We evaluate on the recent MIND2WEB benchmark. In addition to
standard offline evaluation on cached websites, we enable a new online
evaluation setting by developing a tool that allows running web agents on live
websites. We show that GPT-4V presents a great potential for web agents -- it
can successfully complete 51.1 of the tasks on live websites if we manually
ground its textual plans into actions on the websites. This substantially
outperforms text-only LLMs like GPT-4 or smaller models (FLAN-T5 and BLIP-2)
specifically fine-tuned for web agents. However, grounding still remains a
major challenge. Existing LMM grounding strategies like set-of-mark prompting
turns out to be not effective for web agents, and the best grounding strategy
we develop in this paper leverages both the HTML structure and visuals. Yet,
there is still a substantial gap with oracle grounding, leaving ample room for
further improvement. All code, data, and evaluation tools are available at
https://github.com/OSU-NLP-Group/SeeAct.


  Dielectric nano-swithes made of the materials that exhibit piezoelectric
and/or flexoelectric properties with significant electro-mechanical coupling
are considered. In this case, a nonuniform strain field may locally break
inversion symmetry and induce polarization even in nonpiezoelectrics. At
reducing dimensions to the nanoscale, the flexoelectric effect demonstrates the
nonlocality of the dielectric materials and plays more significant role than
piezoelectric effect. The flexoelectric effect is included into consideration
via additional term coupling strain gradient and polarization in the electric
enthalpy density. The equations of motion of the improved Euler-Bernoulli and
Timoshenko beam models, and 2-D plate theory have been obtained.


  One of the tasks of law enforcement agencies is to find evidence of criminal
activity in the Darknet. However, visiting thousands of domains to locate
visual information containing illegal acts manually requires a considerable
amount of time and resources. Furthermore, the background of the images can
pose a challenge when performing classification. To solve this problem, in this
paper, we explore the automatic classification Tor Darknet images using
Semantic Attention Keypoint Filtering, a strategy that filters non-significant
features at a pixel level that do not belong to the object of interest, by
combining saliency maps with Bag of Visual Words (BoVW). We evaluated SAKF on a
custom Tor image dataset against CNN features: MobileNet v1 and Resnet50, and
BoVW using dense SIFT descriptors, achieving a result of 87.98% accuracy and
outperforming all other approaches.


  Cross-domain sequential recommendation is an important development direction
of recommender systems. It combines the characteristics of sequential
recommender systems and cross-domain recommender systems, which can capture the
dynamic preferences of users and alleviate the problem of cold-start users.
However, in recent years, people pay more and more attention to their privacy.
They do not want other people to know what they just bought, what videos they
just watched, and where they just came from. How to protect the users' privacy
has become an urgent problem to be solved. In this paper, we propose a novel
privacy-preserving cross-domain sequential recommender system (PriCDSR), which
can provide users with recommendation services while preserving their privacy
at the same time. Specifically, we define a new differential privacy on the
data, taking into account both the ID information and the order information.
Then, we design a random mechanism that satisfies this differential privacy and
provide its theoretical proof. Our PriCDSR is a non-invasive method that can
adopt any cross-domain sequential recommender system as a base model without
any modification to it. To the best of our knowledge, our PriCDSR is the first
work to investigate privacy issues in cross-domain sequential recommender
systems. We conduct experiments on three domains, and the results demonstrate
that our PriCDSR, despite introducing noise, still outperforms recommender
systems that only use data from a single domain.


  Complex Organic Molecules (COMs) have been detected in the interstellar
medium (ISM). However, it is not clear whether their synthesis occurs on the
icy surfaces of interstellar grains or via a series of gas-phase reactions. As
a test case of the COMs synthesis in the ISM, we present new quantum chemical
calculations on the formation of acetaldehyde (CH3CHO) from the coupling of the
HCO and CH3 radicals, both in gas phase and on water ice surfaces. The binding
energies of HCO and CH3 on the amorphous water ice were also computed (2333 and
734 K, respectively). Results indicate that, in gas phase, the products could
be either CH3CHO, CH4 + CO, or CH3OCH, depending on the relative orientation of
the two radicals. However, on the amorphous water ice, only the CH4 + CO
product is possible due to the geometrical constraints imposed by the water ice
surface. Therefore, acetaldehyde cannot be synthesized by the CH3 + HCO
coupling on the icy grains. We discuss the implications of these results and
other cases, such as ethylene glycol and dimethyl ether, in which similar
situations can occur, suggesting that formation of these molecules on the grain
surfaces might be unlikely.


  It is intuitive that semantic representations can be useful for machine
translation, mainly because they can help in enforcing meaning preservation and
handling data sparsity (many sentences correspond to one meaning) of machine
translation models. On the other hand, little work has been done on leveraging
semantics for neural machine translation (NMT). In this work, we study the
usefulness of AMR (short for abstract meaning representation) on NMT.
Experiments on a standard English-to-German dataset show that incorporating AMR
as additional knowledge can significantly improve a strong attention-based
sequence-to-sequence neural translation model.


  Daily engagement in life experiences is increasingly interwoven with mobile
device use. Screen capture at the scale of seconds is being used in behavioral
studies and to implement "just-in-time" health interventions. The increasing
psychological breadth of digital information will continue to make the actual
screens that people view a preferred if not required source of data about life
experiences. Effective and efficient Information Extraction and Retrieval from
digital screenshots is a crucial prerequisite to successful use of screen data.
In this paper, we present the experimental workflow we exploited to: (i)
pre-process a unique collection of screen captures, (ii) extract unstructured
text embedded in the images, (iii) organize image text and metadata based on a
structured schema, (iv) index the resulting document collection, and (v) allow
for Image Retrieval through a dedicated vertical search engine application. The
adopted procedure integrates different open source libraries for traditional
image processing, Optical Character Recognition (OCR), and Image Retrieval. Our
aim is to assess whether and how state-of-the-art methodologies can be applied
to this novel data set. We show how combining OpenCV-based pre-processing
modules with a Long short-term memory (LSTM) based release of Tesseract OCR,
without ad hoc training, led to a 74% character-level accuracy of the extracted
text. Further, we used the processed repository as baseline for a dedicated
Image Retrieval system, for the immediate use and application for behavioral
and prevention scientists. We discuss issues of Text Information Extraction and
Retrieval that are particular to the screenshot image case and suggest
important future work.


  The problem of density of $C^0$-stable mappings is a classical and venerable
subject in singularity theory. In 1973, Mather showed that the set of proper
$C^0$-stable mappings is dense in the set of all proper mappings, which implies
that the set of $C^0$-stable mappings is dense in the set of all mappings if
the source manifold is compact. The aim of this paper is to complement Mather's
result and to provide new information to the subject. Namely, we show that the
set of $C^0$-stable mappings is never dense in the set of all mappings if the
source manifold is non-compact. As a corollary of this result and Mather's
result, we can obtain a characterization of density of $C^0$-stable mappings,
i.e., the set of $C^0$-stable mappings is dense in the set of all mappings if
and only if the source manifold is compact. To prove the non-density result, we
provide a more essential result by using the notion of topologically critical
points.


  In this study, dependence on site dilution of critical and compensation
temperatures of a two dimensional mixed spin-1/2 and spin-1 system has been
investigated with Monte Carlo simulation. The dependence of the thermal and
magnetic behaviors on dilution of mixed spin system have been discussed. We
have shown that the critical and compensation temperatures of diluted mixed
spin system linearly decrease with increasing number of diluted sites.


  For the ultradifferentiable weight sequence setting it is known that the
Borel map which assigns to each function the infinite jet of derivatives (at 0)
is surjective onto the corresponding weighted sequence class if and only if the
sequence is strongly nonquasianalytic for both the Roumieu- and Beurling-type
classes. Sequences which are nonquasianalytic but not strongly nonquasianalytic
admit a controlled loss of regularity and we determine the maximal sequence for
which such a mixed setting is possible for both types, hence get information on
the controlled loss of surjectivity in this situation. Moreover, we compare the
optimal sequences for both mixed strong nonquasianalyticity conditions arising
in the literature.


  There are many research available on the study of real-valued fractal
interpolation function and fractal dimension of its graph. In this paper, our
main focus is to study the dimensional results for vector-valued fractal
interpolation function and its Riemann-Liouville fractional integral. Here, we
give some results which ensure that dimensional results for vector-valued
functions are quite different from real-valued functions. We determine
interesting bounds for the Hausdorff dimension of the graph of vector-valued
fractal interpolation function. We also obtain bounds for the Hausdorff
dimension of associated invariant measure supported on the graph of
vector-valued fractal interpolation function. Next, We discuss more efficient
upper bound for the Hausdorff dimension of measure in terms of probability
vector and contraction ratios. Furthermore, we determine some dimensional
results for the graph of the Riemann-Liouville fractional integral of a
vector-valued fractal interpolation function.


  These lectures were presented at the 2019 CERN Latin-American School of High
Energy Physics. They were centered on the experimental methods used in hadron
colliders to advance our understanding in the field of high energy particle
physics. From accelerators, to particle detector technologies, object
identification and data analyses techniques, the lectures did not attempt to
provide a comprehensive, in-depth technical background, but rather focused on
an overview of experimental techniques that enabled our advances in supporting
and challenging the predictions of the standard model. This document includes a
selection of the material presented in the lectures, focusing on how advances
in detector technologies and object identification enabled the development of
increasingly sophisticated data analysis techniques. This writeup also includes
an outlook to the future LHC program and beyond.


  We prove that the Pauli representation of the quantum permutation algebra
$A_s(4)$ is faithful. This provides the second known model for a free quantum
algebra. We use this model for performing some computations, with the main
result that at the level of laws of diagonal coordinates, the Lebesgue measure
appears between the Dirac mass and the free Poisson law.


  The interstellar medium (ISM) seems to have a significant surplus of oxygen
which was dubbed as the "O crisis": independent of the adopted interstellar
reference abundance, the total number of O atoms depleted from the gas phase
far exceeds that tied up in solids by as much as ~160ppm of O/H. Recently, it
has been hypothesized that the missing O could be hidden in micrometer-sized
H2O ice grains. We examine this hypothesis by comparing the infrared (IR)
extinction and far-IR emission arising from these grains with that observed in
the Galactic diffuse ISM. We find that it is possible for the diffuse ISM to
accommodate ~160ppm of O/H in micron-sized H2O ice grains without violating the
observational constraints including the absence of the 3.1micron O-H absorption
feature. More specifically, H2O ice grains of radii ~4micron and O/H = 160 ppm
are capable of accounting for the observed flat extinction at ~ 3-8 micron and
produce no excessive emission in the far-IR. These grains could be present in
the diffuse ISM through rapid exchange of material between dense molecular
clouds where they form and diffuse clouds where they are destroyed by
photosputtering.


  In this paper, we show that a complete embedded minimal surface in $\Real^3$
with finite topology and one end is conformal to a once-punctured compact
Riemann surface. Moreover, using the conformality and embeddedness, we examine
the Weierstrass data and conclude that every such surface has Weierstrass data
asymptotic to that of the helicoid. More precisely, if $g$ is the stereographic
projection of the Gauss map, then in a neighborhood of the puncture, $g(p) =
\exp(i\alpha z(p) + F(p))$, where $\alpha \in \Real$, $z=x_3+ix_3^*$ is a
holomorphic coordinate defined in this neighborhood and $F(p)$ is holomorphic
in the neighborhood and extends over the puncture with a zero there. This
further implies that the end is actually Hausdorff close to a helicoid.


  Geometric deep learning is increasingly important thanks to the popularity of
3D sensors. Inspired by the recent advances in NLP domain, the self-attention
transformer is introduced to consume the point clouds. We develop Point
Attention Transformers (PATs), using a parameter-efficient Group Shuffle
Attention (GSA) to replace the costly Multi-Head Attention. We demonstrate its
ability to process size-varying inputs, and prove its permutation equivariance.
Besides, prior work uses heuristics dependence on the input data (e.g.,
Furthest Point Sampling) to hierarchically select subsets of input points.
Thereby, we for the first time propose an end-to-end learnable and
task-agnostic sampling operation, named Gumbel Subset Sampling (GSS), to select
a representative subset of input points. Equipped with Gumbel-Softmax, it
produces a "soft" continuous subset in training phase, and a "hard" discrete
subset in test phase. By selecting representative subsets in a hierarchical
fashion, the networks learn a stronger representation of the input sets with
lower computation cost. Experiments on classification and segmentation
benchmarks show the effectiveness and efficiency of our methods. Furthermore,
we propose a novel application, to process event camera stream as point clouds,
and achieve a state-of-the-art performance on DVS128 Gesture Dataset.


  Ising superconductivity, observed experimentally in NbSe$_{2}$ and similar
materials, has generated tremendous interest. Recently, attention was called to
the possible role that spin fluctuations (SF) play in this phenomenon, in
addition to the dominant electron-phonon coupling (EPC); the possibility of a
predominantly-triplet state was discussed and led to a conjecture of viable
singlet-triplet Leggett oscillations. However, these hypotheses have not been
put to a quantitative test. In this paper, we report first principle
calculations of the EPC and also estimate coupling with SF, including full
momentum dependence. We find that: (1) EPC is strongly anisotropic, largely
coming from the K-K' scattering, and therefore excludes triplet symmetry even
as an excited state; (2) superconductivity is substantially weakened by SF, but
anisotropy remains as above; and, (3) we do find the possibility of a Leggett
mode, not in a singlet-triplet but in an $s_{++}$ - $s_\pm$ channel.


  Despite the ability of the cosmological concordance model ($\Lambda$CDM) to
describe the cosmological observations exceedingly well, power law expansion of
the Universe scale radius, $R(t)\propto t^n$, has been proposed as an
alternative framework. We examine here these models, analyzing their ability to
fit cosmological data using robust model comparison criteria. Type Ia
supernovae (SNIa), baryonic acoustic oscillations (BAO) and acoustic scale
information from the cosmic microwave background (CMB) have been used. We find
that SNIa data either alone or combined with BAO can be well reproduced by both
$\Lambda$CDM and power law expansion models with $n\sim 1.5$, while the
constant expansion rate model $(n=1)$ is clearly disfavored. Allowing for some
redshift evolution in the SNIa luminosity essentially removes any clear
preference for a specific model. The CMB data are well known to provide the
most stringent constraints on standard cosmological models, in particular,
through the position of the first peak of the temperature angular power
spectrum, corresponding to the sound horizon at recombination, a scale
physically related to the BAO scale. Models with $n\geq 1$ lead to a divergence
of the sound horizon and do not naturally provide the relevant scales for the
BAO and the CMB. We retain an empirical footing to overcome this issue: we let
the data choose the preferred values for these scales, while we recompute the
ionization history in power law models, to obtain the distance to the CMB. In
doing so, we find that the scale coming from the BAO data is not consistent
with the observed position of the first peak of the CMB temperature angular
power spectrum for any power law cosmology. Therefore, we conclude that when
the three standard probes are combined, the $\Lambda$CDM model is very strongly
favored over any of these alternative models, which are then essentially ruled
out.


  A bounded linear operator $U$ between Banach spaces is universal for the
complement of some operator ideal $\mathfrak{J}$ if it is a member of the
complement and it factors through every element of the complement of
$\mathfrak{J}$. In the first part of this paper, we produce new universal
operators for the complements of several ideals and give examples of ideals
whose complements do not admit such operators. In the second part of the paper,
we use Descriptive Set Theory to study operator ideals. After restricting
attention to operators between separable Banach spaces, we call an operator
ideal $\mathfrak{J}$ generic if anytime an operator $A$ has the property that
every operator in $\mathfrak{J}$ factors through a restriction of $A$, then
every operator between separable Banach spaces factors through a restriction of
$A$. We prove that many of classical operator ideals are generic (i.e. strictly
singular, weakly compact, Banach-Saks) and give a sufficient condition, based
on the complexity of the ideal, for when the complement does not admit a
universal operator. Another result is a new proof of a theorem of M. Girardi
and W.B. Johnson which states that there is no universal operator for the
complement of the ideal of completely continuous operators.


  We consider the electromagnetic propagation in two-dimensional photonic
crystals, formed by parallel dielectric cylinders embedded a uniform medium.
The frequency band structure is computed using the standard plane-wave
expansion method, and the corresponding eigne-modes are obtained subsequently.
The optical flows of the eigen-modes are calculated by a direct computation
approach, and several averaging schemes of the energy current are discussed.
The results are compared to those obtained by the usual approach that employs
the group velocity calculation. We consider both the case in which the
frequency lies within passing band and the situation in which the frequency is
in the range of a partial bandgap. The agreements and discrepancies between
various averaging schemes and the group velocity approach are discussed in
detail. The results indicate the group velocity can be obtained by appropriate
averaging method.


  We report a measurement of time-dependent $CP$ violation parameters in ${B^0
\to K_S^0 \eta \gamma}$ decays. The study is based on a data sample, containing
${772 \times 10^6 B\bar{B}}$ pairs, that was collected at the $\Upsilon(4S)$
resonance with the Belle detector at the KEKB asymmetric-energy $e^+ e^-$
collider. We obtain the $CP$ violation parameters of ${{\cal S} = -1.32 \pm
0.77 {\rm (stat.)} \pm 0.36{\rm (syst.)}}$ and ${{\cal A} = -0.48 \pm 0.41 {\rm
(stat.)} \pm 0.07{\rm (syst.)}}$ for the invariant mass of the $K_S^0 \eta$
system up to 2.1 GeV/$c^2$.


  Adaptive simulated annealing (ASA) is a global optimization algorithm based
on an associated proof that the parameter space can be sampled much more
efficiently than by using other previous simulated annealing algorithms. The
author's ASA code has been publicly available for over two years. During this
time the author has volunteered to help people via e-mail, and the feedback
obtained has been used to further develop the code. Some lessons learned, in
particular some which are relevant to other simulated annealing algorithms, are
described.


  The goal of the present paper is the investigation of the evolution of
anisotropic regular structures and turbulence at large Reynolds number in the
multi-dimensional Burgers equation. We show that we have local isotropization
of the velocity and potential fields at small scale inside cellular zones. For
periodic waves, we have simple decay inside of a frozen structure. The global
structure at large times is determined by the initial correlations, and for
short range correlated field, we have isotropization of turbulence. The other
limit we consider is the final behavior of the field, when the processes of
nonlinear and harmonic interactions are frozen, and the evolution of the field
is determined only by the linear dissipation.


  Ba$_8$CoNb$_6$O$_{24}$ presents a system whose Co$^{2+}$ ions have an
effective spin 1/2 and construct a regular triangular-lattice antiferromagnet
(TLAFM) with a very large interlayer spacing, ensuring purely two-dimensional
character. We exploit this ideal realization to perform a detailed experimental
analysis of the $S = 1/2$ TLAFM, which is one of the keystone models in
frustrated quantum magnetism. We find strong low-energy spin fluctuations and
no magnetic ordering, but a diverging correlation length down to 0.1 K,
indicating a Mermin-Wagner trend towards zero-temperature order. Below 0.1 K,
however, our low-field measurements show an nexpected magnetically disordered
state, which is a candidate quantum spin liquid. We establish the $(H,T)$ phase
diagram, mapping in detail the quantum fluctuation corrections to the available
theoretical analysis. These include a strong upshift in field of the maximum
ordering temperature, qualitative changes to both low- and high-field phase
boundaries, and an ordered regime apparently dominated by the collinear
"up-up-down" state. Ba$_8$CoNb$_6$O$_{24}$ therefore offers fresh input for the
development of theoretical approaches to the field-induced quantum phase
transitions of the $S = 1/2$ Heisenberg TLAFM.


  The divergent part of the one-loop Vilkovisky unique effective action for
quantum Einstein gravity is evaluated in the general parametrization of the
quantum field, including the separated conformal factor. The output of this
calculation explicitly demonstrates the parametrization and conformal gauge
independence of the unique effective action with the configuration space metric
chosen following Vilkovisky's prescription.


  A kind of spatial fractional diffusion equations in this paper are studied.
Firstly, an L1 formula is employed for the spatial discretization of the
equations. Then, a second order scheme is derived based on the resulting
semi-discrete ordinary differential system by using the implicit integration
factor method, which is a class of efficient semi-implicit temporal scheme.
Numerical results show that the proposed scheme is accurate even for the
discontinuous coefficients.


  In this paper, we establish the global in time hydrodynamic limit of
Boltzmann equation to the planar rarefaction wave of compressible Euler system
in three dimensional space $x\in\mathbb{R}^3$ for general collision kernels.
Our approch is based on a generalized Hilbert expansion, and a recent
$L^2-L^\infty$ framework. In particular, we improve the $L^2$-estimate to be a
localized version because the planar rarefaction wave is indeed a
one-dimensional wave which makes the source terms to be not integrable in the
$L^2$ energy estimate of three dimensional problem. We also point out that the
wave strength of rarefaction may be large.


  By considering corrections to the asymptotic scaling functions of the photon
and electron in quantum electrodynamics with $\Nf$ flavours, we solve the
skeleton Dyson equations at $O(1/\Nf)$ in the large $\Nf$ expansion at the
$d$-dimensional critical point of the theory and deduce the critical exponent
$\beta^\prime(g_c)$, in arbitrary dimensions, and subsequently present a method
for computing higher order corrections to $\beta(g)$.


  We study the quark-antiquark interaction in the large N limit of the
superconformal field theory on D-3branes at a Calabi-Yau conical singularity.
We compute the Wilson loop in the AdS_5xT^{11} supergravity background for the
SU(2N)x SU(2N) theory. We also calculate the Wilson loop for the Higgs phase
where the gauge group is broken to SU(N)x SU(N)x SU_D(N). This corresponds to a
two center configuration with some of the branes at the singularity and the
rest of them at a smooth point. The calculation exhibits the expected Coulomb
dependence for the interaction. The angular distribution of the BPS states is
different than the one for a spherical horizon.


  I present a Variational Autoencoder (VAE) trained on collider physics data
(specifically boosted $W$ jets), with reconstruction error given by an
approximation to the Earth Movers Distance (EMD) between input and output jets.
This VAE learns a concrete representation of the data manifold, with
semantically meaningful and interpretable latent space directions which are
hierarchically organized in terms of their relation to physical EMD scales in
the underlying physical generative process. The variation of the latent space
structure with a resolution hyperparameter provides insight into scale
dependent structure of the dataset and its information complexity. I introduce
two measures of the dimensionality of the learnt representation that are
calculated from this scaling.


  Clusters of galaxies at z>1 are expected to be increasingly active sites of
star formation. To test this, an 850um survey was undertaken of eight
high-redshift clusters at z=1.6-2.0 using SCUBA-2 on the James Clerk Maxwell
Telescope. Mid-infrared properties were used to identify 53 probable
counterparts to 45 SCUBA-2 sources with colours that suggested that they were
cluster members. This uncovered a modest overdensity of 850um sources with
far-infrared luminosities LIR>10^12Lo (SFR>100Mo/yr) and colours consistent
with being cluster members of a factor of 4+/-1 within the central 1Mpc radius
of the clusters. The submillimetre photometry of these galaxies was used to
estimate the total cluster star formation rates. These showed that the
mass-normalised rates in the clusters are two orders of magnitude higher than
in local systems, evolving as (1+z)^(5.5+/-0.6). This rapid evolution means
that the mass-normalised star formation rates in these clusters matched that of
average halos in the field at z~1.8+/-0.2 marking the epoch where the local
star formation-density relation reverses in massive halos. The estimated
stellar masses of the cluster submillimetre galaxies suggest that their
descendants will be amongst the most massive galaxies in z~0 clusters. This
reinforces the suggestion that the majority of the massive early-type galaxy
population in z~0 clusters were likely to have formed at z>1.5-2 through very
active, but dust-obscured, starburst events.


  We prove the optimal convergence estimate for first order interpolants used
in finite element methods based on three major approaches for generalizing
barycentric interpolation functions to convex planar polygonal domains. The
Wachspress approach explicitly constructs rational functions, the Sibson
approach uses Voronoi diagrams on the vertices of the polygon to define the
functions, and the Harmonic approach defines the functions as the solution of a
PDE. We show that given certain conditions on the geometry of the polygon, each
of these constructions can obtain the optimal convergence estimate. In
particular, we show that the well-known maximum interior angle condition
required for interpolants over triangles is still required for Wachspress
functions but not for Sibson functions.


  In this paper, we extend our study of the holographic R\'enyi entropy of
single interval on a torus to the CFT with W symmetry. To read the possible
corrections from W fields clearly, we compute the thermal correction to the
R\'enyi entropy up to the order $e^{-8\pi /TL}$. In the field theory, this
requires us to compute the contribution from all the level 4 states, from both
the vacuum module and W primaries. On the gravity side, after computing the
eigenvalue of single Schottky generators to the order $e^{-4 \pi/TL}$, we
obtain the 1-loop quantum correction to the holographic R\'enyi entropy. We
find complete agreement between the bulk and boundary theories.


  We present modeling of the COVID-19 epidemic in Illinois, USA, capturing the
implementation of a Stay-at-Home order and scenarios for its eventual release.
We use a non-Markovian age-of-infection model that is capable of handling long
and variable time delays without changing its model topology. Bayesian
estimation of model parameters is carried out using Markov Chain Monte Carlo
(MCMC) methods. This framework allows us to treat all available input
information, including both the previously published parameters of the epidemic
and available local data, in a uniform manner. To accurately model deaths as
well as demand on the healthcare system, we calibrate our predictions to total
and in-hospital deaths as well as hospital and ICU bed occupancy by COVID-19
patients. We apply this model not only to the state as a whole but also its
sub-regions in order to account for the wide disparities in population size and
density. Without prior information on non-pharmaceutical interventions (NPIs),
the model independently reproduces a mitigation trend closely matching mobility
data reported by Google and Unacast. Forward predictions of the model provide
robust estimates of the peak position and severity and also enable forecasting
the regional-dependent results of releasing Stay-at-Home orders. The resulting
highly constrained narrative of the epidemic is able to provide estimates of
its unseen progression and inform scenarios for sustainable monitoring and
control of the epidemic.


  We study the quantum phase transition in the two-dimensional random Ising
model in a transverse field by Monte Carlo simulations. We find results similar
to those known analytically in one-dimension. At the critical point, the
dynamical exponent is infinite and the typical correlation function decays with
a stretched exponential dependence on distance. Away from the critical point
there are Griffiths-McCoy singularities, characterized by a single,
continuously varying exponent, z', which diverges at the critical point, as in
one-dimension. Consequently, the zero temperature susceptibility diverges for a
RANGE of parameters about the transition.


  The one clean qubit model of quantum computation (DQC1) efficiently
implements a computational task that is not known to have a classical
alternative. During the computation, there is never more than a small but
finite amount of entanglement present, and it is typically vanishingly small in
the system size. In this paper, we demonstrate that there is nothing unexpected
hidden within the DQC1 model -- Grover's Search, when acting on a mixed state,
provably exhibits a speed-up over classical with guarantees as to the presence
of only vanishingly small amounts of quantum correlations (entanglement and
quantum discord) -- while arguing that this is not an artefact of the
oracle-based construction. We also present some important refinements in the
evaluation of how much entanglement may be present in DQC1, and how the typical
entanglement of the system must be evaluated.


  We discuss the effect of electromagnetic environment on laboratory
measurements of the nuclear fusion reactions of astrophysical interest. The
radiation field is eliminated using the path integral formalism in order to
obtain the influence functional, which we evaluate in the semi-classical
approximation. We show that enhancement of the tunneling probability due to the
radiation correction is extremely small and does not resolve the longstanding
problem that the observed electron screening effect is significantly larger
than theoretical predictions.