  We have studied the FIR/{\it mm} spectrum of IR galaxies by combining IRAS
photometry with new {\it mm} data on a complete southern IRAS galaxy sample.
The observed spectra and a dust model emphasize a dicothomy in the galaxy
population: half of the objects with a lot of warm dust are characterized by
higher values of the bolometric (UV-FIR) luminosity, of the dust-to-gas mass
ratio, of the dust optical depths and extinction, while those dominated by cold
({\it cirrus}) dust show opposite trends. From these data we derive the {\it
mm} luminosity function of galaxies and estimate their contribution to the
sub-{\it mm} background (BKG).


  We study the properties of a spin-polarized Fermi gas in a harmonic trap,
using the semiclassical (Thomas-Fermi) approximation. Universal forms for the
spatial and momentum distributions are calculated, and the results compared
with the corresponding properties of a dilute Bose gas.


  The Ar XVII X-ray line group principally due to transitions 1s2 - 1s2l (l=s,
p) near 4 Anstroms was observed in numerous flares by the RESIK bent crystal
spectrometer aboard CORONAS-F between 2001 and 2003. The three line features
include the Ar XVII w (resonance line), a blend of x and y (intercombination
lines), and z (forbidden line), all of which are blended with Ar XVI
dielectronic satellites. The ratio G, equal to [I(x+y) + I(z)]/I(w), varies
with electron temperature Te mostly because of unresolved dielectronic
satellites. With temperatures estimated from GOES X-ray emission, the observed
G ratios agree fairly well with those calculated from CHIANTI and other data.
With a two-component emission measure, better agreement is achieved. Some S XV
and S XVI lines blend with the Ar lines, the effect of which occurs at
temperatures greater than 8MK, allowing the S/Ar abundance ratio to be
determined. This is found to agree with coronal values. A nonthermal
contribution is indicated for some spectra in the repeating-pulse flare of 2003
February 6.


  The generalized Lotka-Volterra (gLV) equations are a mathematical proxy for
ecological dynamics. We focus on a gLV model of the gut microbiome, in which
the evolution of the gut microbial state is determined in part by pairwise
inter-species interaction parameters that encode environmentally-mediated
resource competition between microbes. We develop an in silico method that
controls the steady-state outcome of the system by adjusting these interaction
parameters. This approach is confined to a bistable region of the gLV model.
The two steady states of interest are idealized as either a "healthy" or
"diseased" steady state of the gut microbiome. In this method, a dimensionality
reduction technique called steady-state reduction (SSR) is first used to
generate a two-dimensional (2D) gLV model that approximates the
high-dimensional dynamics on the 2D subspace spanned by the two steady states.
Then a bifurcation analysis of the 2D model analytically determines parameter
modifications that drive a disease-prone initial condition to the healthy
steady state. This parameter modification of the reduced 2D model guides
parameter modifications of the original high-dimensional model, resulting in a
change of steady-state outcome in the high-dimensional model. This control
method, called SPARC (SSR-guided parameter change), bypasses the computational
challenge of directly determining parameter modifications in the original
high-dimensional system. SPARC could guide the development of indirect
bacteriotherapies, which seek to change microbial compositions by deliberately
modifying gut environmental variables such as gut acidity or macronutrient
availability.


  We report anistropy in superconducting and normal state of NiBi3 single
crystals with Tc = 4.06 K. The magnetoresistance results indicate the absence
of scattering usually associated with ferromagnetic metals, suggesting the
absence of bulk long range magnetic order below 300 K. However, the electron
spin resonance results demonstrate that ferromagnetism fluctuations exist on
the surface of the crystal below 150K.


  We study the Einstein-Dirac equation as well as the weak Killing equation on
Riemannian spin manifolds with codimension one foliation. We prove that, for
any manifold $M^n$ admitting real Killing spinors (resp. parallel spinors),
there exist warped product metrics $\bar{\eta}$ on $M^n \times {\mathbb R}$
such that $(M^n \times {\mathbb R}, \bar{\eta})$ admit Einstein spinors (resp.
weak Killing spinors). To prove the result we split the Einstein-Dirac equation
into evolution equations and constraints, by means of Cartan's frame formalism,
and apply the local preservation property of constraints.


  Solenoids are ``inverse limits'' of the circle, and the classical knot theory
is the theory of tame embeddings of the circle into the 3-space. We give some
general study, including certain classification results, of tame embeddings of
solenoids into the 3-space as the ``inverse limits'' of the tame embeddings of
the circle.
  Some applications are discussed. In particular, there are ``tamely'' embedded
solenoids $\Sigma\subset \R^3$ which are strictly achiral. Since solenoids are
non-planar, this contrasts sharply with the known fact that if there is a
strictly achiral embedding $Y\subset \R^3$ of a compact polyhedron $Y$, then
$Y$ must be planar.


  In spite of the rich phenomenology of the polarization properties of radio
pulsars, the rotating vector model (RVM) created 50 years ago remains the best
method to determine the beam geometry of a pulsar. We apply the RVM to a sample
of 854 radio pulsars observed with the MeerKAT telescope in order to draw
conclusions about the population of pulsars as a whole. The main results are
that (i) the geometrical interpretation of the position angle traverse is valid
in the majority of the population, (ii) the pulsars for which the RVM fails
tend to have a high fraction of circular polarization compared to linear
polarization, (iii) emission heights obtained through both geometrical and
relativistic methods show that the majority of pulsars must have emission
heights less than 1000~km independent of spin period, (iv) orthogonal mode
jumps are seen in the position angle traverse in about one third of the
population. All these results are weakly dependent on the pulsar spin-down
energy.


  We introduce and analyze a spatial Lotka-Volterra competition model with
local and nonlocal interactions. We study two alternative classes of nonlocal
competition that differ in how each species' characteristics determine the
range of the nonlocal interactions. In both cases, nonlocal interactions can
create spatial patterns of population densities in which highly populated
clumps alternate with unpopulated regions. This non-populated regions provide
spatial niches for a weaker competitor to establish in the community and
persist in conditions in which local models predict competitive exclusion.
Moreover, depending on the balance between local and nonlocal competition
intensity, the clumps of the weaker competitor vary from M-like structures with
higher densities of individuals accumulating at the edges of each clump to
triangular structures with most individuals occupying their centers. These
results suggest that long-range competition, through the creation of spatial
patterns in population densities, might be an important driving force behind
the rich diversity of species observed in real ecological communities.


  In numerical computations, precision of floating-point computations is a key
factor to determine the performance (speed and energy-efficiency) as well as
the reliability (accuracy and reproducibility). However, precision generally
plays a contrary role for both. Therefore, the ultimate concept for maximizing
both at the same time is the minimal-precision computing through
precision-tuning, which adjusts the optimal precision for each operation and
data. Several studies have been already conducted for it so far (e.g.
Precimoniuos and Verrou), but the scope of those studies is limited to the
precision-tuning alone. Hence, we aim to propose a broader concept of the
minimal-precision computing system with precision-tuning, involving both
hardware and software stack.
  In 2019, we have started the Minimal-Precision Computing project to propose a
more broad concept of the minimal-precision computing system with
precision-tuning, involving both hardware and software stack. Specifically, our
system combines (1) a precision-tuning method based on Discrete Stochastic
Arithmetic (DSA), (2) arbitrary-precision arithmetic libraries, (3) fast and
accurate numerical libraries, and (4) Field-Programmable Gate Array (FPGA) with
High-Level Synthesis (HLS).
  In this white paper, we aim to provide an overview of various technologies
related to minimal- and mixed-precision, to outline the future direction of the
project, as well as to discuss current challenges together with our project
members and guest speakers at the LSPANC 2020 workshop;
https://www.r-ccs.riken.jp/labs/lpnctrt/lspanc2020jan/.


  First-order predicate logic extended with linear arithmetic is undecidable,
in general. We show that the Bernays-Sch\"onfinkel-Ramsey (BSR) fragment
extended with linear arithmetic restricted to simple bounds (SB) is decidable
through finite ground instantiation. The identified ground instances can be
employed to restrict the search space of existing automated reasoning
procedures for BSR(SB). Satisfiability of BSR(SB) compared to BSR remains
NEXPTIME-complete. The decidability result is almost tight because BSR is
undecidable if extended with linear difference inequations, simple additive
inequations, quotient inequations and multiplicative inequations.


  Cubic boron phosphide BP has been studied in situ by X-ray diffraction and
Raman scattering up to 55 GPa at 300 K in a diamond anvil cell. The bulk
modulus of B0 = 174(2) GPa has been established, which is in excellent
agreement with our ab initio calculations. The data on Raman shift as a
function of pressure, combined with equation-of-state data, allowed us to
estimate the Gr\"uneisen parameters of the TO and LO modes of zinc-blende
structure, {\gamma}GTO = 1.16 and {\gamma}GLO = 1.04, just like in the case of
other AIIIBV diamond-like phases, for which {\gamma}GTO > {\gamma}GLO = 1. We
also established that the pressure dependence of the effective electro-optical
constant {\alpha} is responsible for a strong change in relative intensities of
the TO and LO modes from ITO/ILO ~0.25 at 0.1 MPa to ITO/ILO ~2.5 at 45 GPa,
for which we also find excellent agreement between experiment and theory.


  We consider the situation when an elliptic problem in a subdomain $\Omega_1$
of an $n$-dimensional bounded domain $\Omega$ is coupled via inhomogeneous
canonical transmission conditions to a parabolic problem in
$\Omega\setminus\Omega_1$. In particular, we can treat elliptic-parabolic
equations in bounded domains with discontinuous coefficients. Using Fourier
multiplier techniques, we prove an a priori estimate for strong solutions to
the equations in $L^p$-Sobolev spaces.


  We revisit the so-called compressed oracle technique, introduced by Zhandry
for analyzing quantum algorithms in the quantum random oracle model (QROM). To
start off with, we offer a concise exposition of the technique, which easily
extends to the parallel-query QROM, where in each query-round the considered
algorithm may make several queries to the QROM in parallel. This variant of the
QROM allows for a more fine-grained query-complexity analysis.
  Our main technical contribution is a framework that simplifies the use of
(the parallel-query generalization of) the compressed oracle technique for
proving query complexity results. With our framework in place, whenever
applicable, it is possible to prove quantum query complexity lower bounds by
means of purely classical reasoning. More than that, for typical examples the
crucial classical observations that give rise to the classical bounds are
sufficient to conclude the corresponding quantum bounds.
  We demonstrate this on a few examples, recovering known results (like the
optimality of parallel Grover), but also obtaining new results (like the
optimality of parallel BHT collision search). Our main target is the hardness
of finding a $q$-chain with fewer than $q$ parallel queries, i.e., a sequence
$x_0, x_1,\ldots, x_q$ with $x_i = H(x_{i-1})$ for all $1 \leq i \leq q$.
  The above problem of finding a hash chain is of fundamental importance in the
context of proofs of sequential work. Indeed, as a concrete cryptographic
application of our techniques, we prove that the "Simple Proofs of Sequential
Work" proposed by Cohen and Pietrzak remains secure against quantum attacks.
Such an analysis is not simply a matter of plugging in our new bound; the
entire protocol needs to be analyzed in the light of a quantum attack. Thanks
to our framework, this can now be done with purely classical reasoning.


  Blind quantum computation is a secure delegated quantum computing protocol
where Alice who does not have sufficient quantum technology at her disposal
delegates her computation to Bob who has a fully-fledged quantum computer in
such a way that Bob cannot learn anything about Alice's input, output, and
algorithm. Protocols of blind quantum computation have been proposed for
several qubit measurement-based computation models, such as the graph state
model, the Affleck-Kennedy-Lieb-Tasaki model, and the
Raussendorf-Harrington-Goyal topological model. Here, we consider blind quantum
computation for the continuous-variable measurement-based model. We show that
blind quantum computation is possible for the infinite squeezing case. We also
show that the finite squeezing causes no additional problem in the blind setup
apart from the one inherent to the continuous-variable measurement-based
quantum computation.


  In this paper, we compute the Standard Model polarized amplitudes and cross
sections of the processes $\gamma\nu\to\gamma\gamma \nu$, $\gamma\gamma \to
\gamma\nu\bar\nu$ and $\nu\bar\nu \to \gamma\gamma\gamma$, for centre-of-mass
energies $\omega$ within the range of validity of the Fermi theory. By using a
large electron-mass expansion of the exact result, we also derive the first
correction term to the effective, low-energy ($\omega < m_e$) formula for
$\gamma\nu\to\gamma\gamma \nu$. Finally, we discuss possible astrophysical
implications of our results and provide simple fits to the exact expressions.


  We formulate abstract conditions under which a suspension flow satisfies the
local central limit theorem. We check the validity of these conditions for
several systems including reward renewal processes, Axiom A flows, as well as
the systems admitting Young tower, such as Sinai billiard with finite horizon,
suspensions over Pomeau-Manneville maps, and geometric Lorenz attractors.


  Turning the skein relation for HOMFLY into a Fibonacci recurrence, we prove
that there are only three rational specializations of HOMFLY polynomial:
Alexander-Conway, Jones, and a new one. Using the recurrence relation, we find
general and relative expansion formulae and rational generating functions for
Alexander-Conway polynomial and the new polynomial, which reduce the
computations to closure of simple braids, a subset of square free braids;
HOMFLY polynomials of these simple braids are also computed. Algebraic
independence of these three polynomials is proved.


  We cut and paste two Banados-Teitelboim-Zanelli (BTZ) spacetimes at a throat
by the Darmois-Israel method to construct a rotating wormhole with a thin shell
filled with a barotropic fluid. The thin shell at the throat and both sides of
the throat corotate. We investigate the linear stability of the thin shell of
the rotating wormhole against radial perturbations. We show that the wormhole
becomes more and more stable the larger its angular momentum is until the
angular momentum reaches a critical value and that the behavior of a condition
for stability significantly changes when the angular momentum exceeds the
critical value. We find that the overcritical rotating wormhole has the radius
of the thin shell, which is stable regardless of the equation of state for the
barotropic fluid.


  We present the first cross-correlation measurement between Sloan Digital Sky
Survey (SDSS) Type 1 quasars and the cosmic infrared background (CIB) measured
by Herschel. The distribution of the quasars at 0.15<z<3.5 covers the redshift
range where we expect most of the CIB to originate. We detect the sub-mm
emission of the quasars, which dominates on small scales, as well as correlated
emission from dusty star-forming galaxies (DSFGs) dominant on larger scales.
The mean sub-mm flux densities of the DR7 quasars (median redshift <z>=1.4) is
$11.1^{+1.6}_{-1.4}$, $7.1^{+1.6}_{-1.3}$ and $3.6^{+1.4}_{-1.0}$ mJy at 250,
350 and 500 microns, respectively, while the mean sub-mm flux densities of the
DR9 quasars (<z>=2.5) is $5.7^{+0.7}_{-0.6}$, $5.0^{+0.8}_{-0.7}$ and
$1.8^{+0.5}_{-0.4}$ mJy. We find that the correlated sub-mm emission includes
both the emission from satellite DSFGs in the same halo as the central quasar
and the emission from DSFGs in separate halos (correlated with the
quasar-hosting halo). The amplitude of the one-halo term is ~10 times smaller
than the sub-mm emission of the quasars, implying the the satellites have a
lower star-formation rate than the quasars. The satellite fraction for the DR7
quasars is $0.008^{+0.008}_{-0.005}$ and the host halo mass scale for the
central and satellite quasars is $10^{12.36\pm0.87}$ M$_{\odot}$ and
$10^{13.60\pm0.38}$ M$_{\odot}$, respectively. The satellite fraction of the
DR9 quasars is $0.065^{+0.021}_{-0.031}$ and the host halo mass scale for the
central and satellite quasars is $10^{12.29\pm0.62}$ M$_{\odot}$ and
$10^{12.82\pm0.39}$ M$_{\odot}$, respectively. Thus, the typical halo
environment of the SDSS Type 1 quasars is found to be similar to that of DSFGs,
which supports the generally accepted view that dusty starburst and quasar
activity are evolutionarily linked.


  We consider dynamic pricing schemes in online settings where selfish agents
generate online events. Previous work on online mechanisms has dealt almost
entirely with the goal of maximizing social welfare or revenue in an auction
settings. This paper deals with quite general settings and minimizing social
costs. We show that appropriately computed posted prices allow one to achieve
essentially the same performance as the best online algorithm. This holds in a
wide variety of settings. Unlike online algorithms that learn about the event,
and then make enforceable decisions, prices are posted without knowing the
future events or even the current event, and are thus inherently dominant
strategy incentive compatible.
  In particular we show that one can give efficient posted price mechanisms for
metrical task systems, some instances of the $k$-server problem, and metrical
matching problems. We give both deterministic and randomized algorithms. Such
posted price mechanisms decrease the social cost dramatically over selfish
behavior where no decision incurs a charge. One alluring application of this is
reducing the social cost of free parking exponentially.


  We calculate the Riemann curvature tensor and sectional curvature for the Lie
group of volume-preserving diffeomorphisms of the Klein bottle and projective
plane. In particular, we investigate the sign of the sectional curvature, and
find a possible disagreement with a theorem of Lukatskii. We suggest an
amendment to this theorem.


Discussion of ``Least angle regression'' by Efron et al. [math.ST/0406456]


  A mechanism of radiative generation of realistic neutrino mixing at one-loop
level with $D5\times Z_2$ is presented in this paper. The process is
demonstrated in two set-ups using $D5\times Z_2$ symmetry viz. Model 1 and
Model 2. Two right-handed neutrinos are present in both the models. In both
Model 1 and Model 2, when mixing between these two right-handed neutrinos are
maximal, one can produce the form of the left-handed Majorana neutrino mass
matrix corresponding to $\theta_{13}=0$, $\theta_{23}=\pi/4$ and any value of
$\theta_{12}^0$ associated with Tribimaximal (TBM), Bimaximal (BM), Golden
Ratio (GR) or other mixings. Small shift from maximal mixing between the two
right-handed neutrino states can generate non-zero $\theta_{13}$, deviation of
$\theta_{23}$ from $\pi/4$ and corrections to the solar mixing $\theta_{12}$ in
one step for both Model 1 and Model 2. In both the models, two $Z_2$ odd inert
$SU(2)_L$ doublet scalars are present. The lightest between these two scalars
can be a viable dark matter candidate for both Model 1 and Model 2.


  Markov Logic Networks (MLN) and Probabilistic Soft Logic (PSL) are widely
applied formalisms in Statistical Relational Learning, an emerging area in
Artificial Intelligence that is concerned with combining logical and
statistical AI. Despite their resemblance, the relationship has not been
formally stated. In this paper, we describe the precise semantic relationship
between them from a logical perspective. This is facilitated by first extending
fuzzy logic to allow weights, which can be also viewed as a generalization of
PSL, and then relate that generalization to MLN. We observe that the
relationship between PSL and MLN is analogous to the known relationship between
fuzzy logic and Boolean logic, and furthermore the weight scheme of PSL is
essentially a generalization of the weight scheme of MLN for the many-valued
setting.


  Distributed quantum applications impose requirements on the quality of the
quantum states that they consume. When analyzing architecture implementations
of quantum hardware, characterizing this quality forms an important factor in
understanding their performance. Fundamental characteristics of quantum
hardware lead to inherent tradeoffs between the quality of states and
traditional performance metrics such as throughput. Furthermore, any real-world
implementation of quantum hardware exhibits time-dependent noise that degrades
the quality of quantum states over time. Here, we study the performance of two
possible architectures for interfacing a quantum processor with a quantum
network. The first corresponds to the current experimental state of the art in
which the same device functions both as a processor and a network device. The
second corresponds to a future architecture that separates these two functions
over two distinct devices. We model these architectures as Markov chains and
compare their quality of executing quantum operations and producing entangled
quantum states as functions of their memory lifetimes, as well as the time that
it takes to perform various operations within each architecture. As an
illustrative example, we apply our analysis to architectures based on
Nitrogen-Vacancy centers in diamond, where we find that for present-day device
parameters one architecture is more suited to computation-heavy applications,
and the other for network-heavy ones. Besides the detailed study of these
architectures, a novel contribution of our work are several formulas that
connect an understanding of waiting time distributions to the decay of quantum
quality over time for the most common noise models employed in quantum
technologies. This provides a valuable new tool for performance evaluation
experts, and its applications extend beyond the two architectures studied in
this work.


  Background: Chronic rhinosinusitis (CRS) is a prevalent and disruptive
disease. Medical management including nasal steroid sprays is the primary
treatment modality. Computational fluid dynamics (CFD) has been used to
characterize sinonasal airflow and intranasal drug delivery; however, variation
in simulation methods indicates a need for large scale CFD model validation.
  Methods: Anatomic reconstructions of pre and post-operative CT scans of 3
functional endoscopic sinus surgery patients were created in Mimics(TM). Fluid
analysis and drug particle deposition modeling were conducted using CFD methods
with Fluent(TM) in 18 cases. Models were 3D printed and in vitro studies were
performed using Tc99-labeled Nasacort(TM). Gamma scintigraphy signals and
CFD-modeled spray mass were post-processed in a superimposed grid and compared.
Statistical analysis using overlap coefficients (OCs) evaluated similarities
between computational and experimental distributions and Kendall's tau rank
correlation coefficient was employed to test independence.
  Results: OCs revealed strong agreement in percent deposition and grid
profiles between CFD models and experimental results (mean [range] for
sagittal, axial, and coronal grids were 0.69 [0.57], 0.61 [0.49], and 0.78
[0.44], respectively). Kendall's tau values showed strong agreement (average
0.73) between distributions, which were statistically significant (p < 0.05)
apart from a single coronal grid in one model and two sagittal grids of
another.
  Conclusions: CFD modeling demonstrates statistical agreement with in vitro
experimental results. This validation study is one of the largest of its kind
and supports the applicability of CFD in accurately modeling nasal spray drug
delivery and using computational methods to investigate means of improving
clinical drug delivery.


  Magnetic clouds (MCs) are transient magnetic structures giving the strongest
southward magnetic field (Bz south) in the solar wind. The sheath regions of
MCs may also carry southward magnetic field. Southward magnetic field is
responsible for causing space-weather disturbances. We report a comprehensive
analysis of MCs and Bz components in their sheath regions during 1995 to 2017.
Eighty-five percent of 303 MCs contain a south Bz up to 50 nT. Sheath Bz during
the 23 years may reach as high as 40 nT. The MCs of strongest magnetic
magnitude and Bz south occur in the declining phase of the solar cycle. The
bipolar MCs have solar-cycle dependence in their polarity, but not in the
occurrence frequency. Unipolar MCs show solar-cycle dependence in their
occurrence frequency but not in their polarity. MCs with the highest speeds,
largest total B magnitudes and sheath Bz south are from source regions closer
to the solar disk center. About 80% of large Dst storms are caused by MC
events. The combinations of south Bz in the sheath and the south-first MCs in
close succession have given the largest storms. The solar-cycle dependence of
bipolar MCs is extended to 2017, spanning 42 years. We find that the bipolar MC
Bz polarity solar-cycle dependence is given by MCs originated from quiescent
filaments in decayed active regions and a group of weak MCs of unclear sources,
while the polarity of bipolar MCs with active-region flares always has mixed Bz
polarity without solar-cycle dependence and is therefore the least predictable
for Bz forecasting.


  We consider the multi-particle Anderson tight-binding model and prove that
its lower spectral edge is non-random under some mild assumptions on the
inter-particle interaction and the random external potential. We also adapt to
the low energy regime the multi-particle multi-scale analysis initially
developed by Chulaevsky and Suhov in the high disorder limit, if the marginal
probability distribution of the i.i.d. random variables is log-H\"older
continuous and obtain the spectral exponential and strong dynamical
localization near the bottom of the spectrum.


  We examine the deSitter entropy in the braneworld model with the
Gauss-Bonnet/Lovelock terms. Then, we can see that the deSitter entropy
computed through the Euclidean action exactly coincides with the holographic
entanglement entropy.


  Charged lepton pairs are produced copiously in high-energy hadron collisions
via electroweak gauge boson exchange, and are one of the most precisely
measured final states in proton-proton collisions at the Large Hadron Collider
(LHC). We propose that measurements of lepton angular distributions can be used
to improve the accuracy of theoretical predictions for Higgs boson production
cross sections at the LHC. To this end, we exploit the sensitivity of the
lepton angular coefficient associated with the longitudinal Z-boson
polarization to the parton density function (PDF) for gluons resolved from the
incoming protons, in order to constrain the Higgs boson cross section from
gluon fusion processes. By a detailed numerical analysis using the open-source
platform xFitter, we find that high-statistics determinations of the
longitudinally polarized angular coefficient at the LHC Run III and
high-luminosity HL-LHC improve the PDF systematic uncertainties of the Higgs
boson cross section predictions by 50% over a broad range of Higgs boson
rapidities.


  We show that birational smooth complex projective varieties with numerically
effective canonical bundles along the exceptional loci have the same Betti
numbers. In particular, birational smooth minimal models share the same Betti
numbers. Our methods indicate a link between $p$-adic measure and the minimal
model theory.


  Emergence of new protein structures has proved difficult to trace in nature
and engineer in the laboratory. However, one aspect of structure evolution has
proved immensely helpful for determining the three-dimensional structure of
proteins from their sequences: in the vast majority of cases, proteins that
share more than 30% sequence identity have similar structures. Below this mark
is the "twilight zone" where proteins may have identical or very different
structures. These observations form the foundational intuition behind structure
homology modeling. Despite their importance, however, they have never received
a comprehensive biophysical justification. Here we show that the onset of the
twilight zone is more gradual for proteins with low contact density, a proxy
for low thermodynamic stability, than proteins with high contact density. Then
we present an analytical model that treats divergent fold evolution as an
activated process, in analogy to chemical kinetics, where sequence evolution
must overcome thermodynamically unstable evolutionary intermediates to discover
new folds. This model explains the existence of a twilight zone and explains
why its onset is more abrupt for some classes of proteins than for others. We
test the assumptions of the model and characterize the dynamics of fold
evolution using evolutionary simulations of model proteins and cell
populations. Overall these results show how fundamental biophysical constraints
directed evolutionary dynamics leading to the Universe of modern protein
structures and sequences.


  In 4 spacetime dimensions there is a well known proof that for any
asymptotically flat, stationary, and axisymmetric vacuum solution of Einstein's
equation there exists a "$t$-$\phi$" reflection isometry that reverses the
direction of the timelike Killing vector field and the direction of the axial
Killing vector field. However, this proof does not generalize to higher
spacetime dimensions. Here we consider asymptotically flat, stationary, and
axisymmetric (i.e., having one or more commuting rotational isometries) black
hole spacetimes in vacuum general relativity in $d \geq 4$ spacetime dimensions
such that the action of the isometry group is trivial. (Here "trivial" means
that if the "axes"---i.e., the points where the axial Killing fields are
linearly dependent---are removed, the action of the isometry group is that of a
trivial principal fiber bundle. This excludes actions like that found in the
Sorkin monopole.) We prove that there exists a "$t$-$\phi$" reflection isometry
that reverses the direction of the timelike Killing vector field and the
direction of each axial Killing vector field. The proof relies in an essential
way on the first law of black hole mechanics.


  We study the resummation of large logarithmic perturbative corrections to the
partonic cross sections relevant for the process pp->h X at high transverse
momentum of the hadron h. These corrections arise near the threshold for the
partonic reaction and are associated with soft-gluon emission. We perform the
resummation to next-to-leading logarithmic accuracy. We present numerical
results for the fixed-target regime and find enhancements over the
next-to-leading order cross section, which significantly improve the agreement
between theoretical predictions and data. We also apply the resummation for
RHIC kinematics and find that subleading terms appear to play a rather
important role here.


  Stochastic processes play a key role for modeling a huge variety of transport
problems out of equilibrium, with manifold applications throughout the natural
and social sciences. To formulate models of stochastic dynamics the
conventional approach consists in superimposing random fluctuations on a
suitable deterministic evolution. These fluctuations are sampled from
probability distributions that are prescribed a priori, most commonly as
Gaussian or L\'evy. While these distributions are motivated by (generalised)
central limit theorems they are nevertheless \textit{unbounded}, meaning that
arbitrarily large fluctuations can be obtained with finite probability. This
property implies the violation of fundamental physical principles such as
special relativity and may yield divergencies for basic physical quantities
like energy. Here we solve the fundamental problem of unbounded random
fluctuations by constructing a comprehensive theoretical framework of
stochastic processes possessing physically realistic finite propagation
velocity. Our approach is motivated by the theory of L\'evy walks, which we
embed into an extension of conventional Poisson-Kac processes. The resulting
extended theory employs generalised transition rates to model subtle
microscopic dynamics, which reproduces non-trivial spatio-temporal correlations
on macroscopic scales. It thus enables the modelling of many different kinds of
dynamical features, as we demonstrate by three physically and biologically
motivated examples. The corresponding stochastic models capture the whole
spectrum of diffusive dynamics from normal to anomalous diffusion, including
the striking `Brownian yet non Gaussian' diffusion, and more sophisticated
phenomena such as senescence. Extended Poisson-Kac theory can therefore be used
to model a wide range of finite velocity dynamical phenomena that are observed
experimentally.


  We have constructed a four-fermion theory coupled to a
Yang-Mills-Chern-Simons gauge field which admits static multi-vortex solutions.
This is achieved through the introduction of an anomalous magnetic interation
term in addition to the usual minimal coupling, and the appropriate choice of
the fermion quartic coupling constant.


  The infamous exploration-exploitation dilemma is one of the oldest and most
important problems in reinforcement learning (RL). Deliberate and effective
exploration is necessary for RL agents to succeed in most environments.
However, until very recently even very sophisticated RL algorithms employed
simple, undirected exploration strategies in large-scale RL tasks.
  We introduce a new optimistic count-based exploration algorithm for RL that
is feasible in high-dimensional MDPs. The success of RL algorithms in these
domains depends crucially on generalization from limited training experience.
Function approximation techniques enable RL agents to generalize in order to
estimate the value of unvisited states, but at present few methods have
achieved generalization about the agent's uncertainty regarding unvisited
states. We present a new method for computing a generalized state visit-count,
which allows the agent to estimate the uncertainty associated with any state.
  In contrast to existing exploration techniques, our
$\phi$-$\textit{pseudocount}$ achieves generalization by exploiting the feature
representation of the state space that is used for value function
approximation. States that have less frequently observed features are deemed
more uncertain. The resulting $\phi$-$\textit{Exploration-Bonus}$ algorithm
rewards the agent for exploring in feature space rather than in the original
state space. This method is simpler and less computationally expensive than
some previous proposals, and achieves near state-of-the-art results on
high-dimensional RL benchmarks. In particular, we report world-class results on
several notoriously difficult Atari 2600 video games, including Montezuma's
Revenge.


  Despite significant progress over more than 100 years, no accelerator has
been unambiguously identified as the source of the locally measured flux of
cosmic rays. High-energy electrons and positrons are of particular importance
in the search for nearby sources as radiative energy losses constrain their
propagation to distances of about 1 kpc around 1 TeV. At the highest energies,
the spectrum is therefore dominated and shaped by only a few sources whose
properties can be inferred from the fine structure of the spectrum at energies
currently accessed by experiments like AMS-02, CALET, DAMPE, Fermi-LAT,
H.E.S.S. and ISS-CREAM. We present a stochastic model of the Galactic
all-electron flux and evaluate its compatibility with the measurement recently
presented by the H.E.S.S. collaboration. To this end, we have MC generated a
large sample of the all-electron flux from an ensemble of random distributions
of sources. We confirm the non-Gaussian nature of the probability density of
fluxes at individual energies previously reported in analytical computations.
For the first time, we also consider the correlations between the fluxes at
different energies, treating the binned spectrum as a random vector and
parametrising its joint distribution with the help of a pair-copula
construction. We show that the spectral break observed in the all-electron
spectrum by H.E.S.S. and DAMPE is statistically compatible with a distribution
of astrophysical sources like supernova remnants or pulsars, but requires a
rate smaller than the canonical supernova rate. This important result provides
an astrophysical interpretation of the spectrum at TeV energies and allows
differentiating astrophysical source models from exotic explanations, like dark
matter annihilation. We also critically assess the reliability of using
catalogues of known sources to model the electron-positron flux.


  We study the time-resolved reflectivity spectrum of a switched planar
GaAs-AlAs microcavity. Between 5 and 40 ps after the switching (pump) pulse we
observe a strong excess probe reflectivity and a change of the frequency of
light trapped in the cavity up to 5 linewidths away from the cavity resonance.
This frequency change does not adiabatically follow the fast-changing cavity
resonance. The frequency change is attributed to an accumulated phase change
due to the time-dependent refractive index. An analytical model predicts
dynamics in qualitative agreement with the experiments, and points to crucial
parameters that control future applications.


  Existing person re-identification (re-id) methods rely mostly on either
localised or global feature representation alone. This ignores their joint
benefit and mutual complementary effects. In this work, we show the advantages
of jointly learning local and global features in a Convolutional Neural Network
(CNN) by aiming to discover correlated local and global features in different
context. Specifically, we formulate a method for joint learning of local and
global feature selection losses designed to optimise person re-id when using
only generic matching metrics such as the L2 distance. We design a novel CNN
architecture for Jointly Learning Multi-Loss (JLML) of local and global
discriminative feature optimisation subject concurrently to the same re-id
labelled information. Extensive comparative evaluations demonstrate the
advantages of this new JLML model for person re-id over a wide range of
state-of-the-art re-id methods on five benchmarks (VIPeR, GRID, CUHK01, CUHK03,
Market-1501).


  Light transport in a highly multimode fiber exhibits complex behavior in
space, time, frequency and polarization, especially in the presence of mode
coupling. The newly developed techniques of spatial wavefront shaping turn out
to be highly suitable to harness such enormous complexity: a spatial light
modulator enables precise characterization of field propagation through a
multimode fiber, and by adjusting the incident wavefront it can accurately
tailor the transmitted spatial pattern, temporal profile and polarization
state. This unprecedented control leads to multimode fiber applications in
imaging, endoscopy, optical trapping and microfabrication. Furthermore, the
output speckle pattern from a multimode fiber encodes spatial, temporal,
spectral and polarization properties of the input light, allowing such
information to be retrieved from spatial measurements only. This article
provides an overview of recent advances and breakthroughs in controlling light
propagation in multimode fibers, and discusses newly emerging applications.


  The BIR workshop brings together experts in Bibliometrics and Information
Retrieval. While sometimes perceived as rather loosely related, these research
areas share various interests and face similar challenges. Our motivation as
organizers of the BIR workshop stemmed from a twofold observation. First, both
communities only partly overlap, albeit sharing various interests. Second, it
will be profitable for both sides to tackle some of the emerging problems that
scholars face today when they have to identify relevant and high quality
literature in the fast growing number of electronic publications available
worldwide. Bibliometric techniques are not yet used widely to enhance retrieval
processes in digital libraries, although they offer value-added effects for
users. Information professionals working in libraries and archives, however,
are increasingly confronted with applying bibliometric techniques in their
services. The first BIR workshop in 2014 set the research agenda by introducing
each group to the other, illustrating state-of-the-art methods, reporting on
current research problems, and brainstorming about common interests. The second
workshop in 2015 further elaborated these themes. This third BIR workshop aims
to foster a common ground for the incorporation of bibliometric-enhanced
services into scholarly search engine interfaces. In particular we will address
specific communities, as well as studies on large, cross-domain collections
like Mendeley and ResearchGate. This third BIR workshop addresses explicitly
both scholarly and industrial researchers.


  Using Vovk's outer measure, which corresponds to a minimal superhedging
price, the existence of quadratic variation is shown for "typical price paths"
in the space of c\`adl\`ag functions possessing a mild restriction on the jumps
directed downwards. In particular, this result includes the existence of
quadratic variation of "typical price paths" in the space of non-negative
c\`adl\`ag paths and implies the existence of quadratic variation in the sense
of F\"ollmer quasi surely under all martingale measures. Based on the robust
existence of the quadratic variation, a model-free It\^o integration is
developed.


  When surface states (SSs) form in topological insulators (TIs), they inherit
the properties of bulk bands, including the electron-hole (e-h) asymmetry but
with much more profound impacts. Here, via combining magneto-infrared
spectroscopy with theoretical analysis, we show that e-h asymmetry
significantly modifies the SS electronic structures when interplaying with the
quantum confinement effect. Compared to the case without e-h asymmetry, the SSs
now bear not only a band asymmetry as that in the bulk but also a shift of the
Dirac point relative to the bulk bands and a reduction of the hybridization gap
up to 70%. Our results signify the importance of e-h asymmetry in band
engineering of TIs in the thin film limit.


  We estimate the energy and Hausdorff dimensions of the Riesz products on the
unit sphere of $\mathbb{C}^n$, $n\ge 2$. Also, we obtain similar results for
the pluriharmonic measures on the torus.


  Supernova remnants (SNRs) are the most attractive candidates for the
acceleration sites of Galactic cosmic rays. We report the detection of GeV
$\gamma$-ray emission with the Pass 8 events recorded by Fermi Large Area
Telescope (Fermi-LAT) in the vicinity of the shell type SNR CTB 37B that is
likely associated with the TeV $\gamma-$ray source HESS J1713-381. The photon
spectrum of CTB 37B is consistent with a power-law with an index of
$1.89\pm0.08$ in the energy range of $0.5-500$ GeV, and the measured flux
connects smoothly with that of HESS J1713-381 at a few hundred GeV. No
significant spatial extension and time variation are detected. The
multi-wavelength data can be well fitted with either a leptonic model or a
hadronic one. However, parameters of both models suggest more efficient
particle acceleration than typical SNRs. Meanwhile, the X-ray and $\gamma$-ray
spectral properties of CTB 37B show that it is an interesting source bridging
young SNRs dominated by non-thermal emission and old SNRs interacting with
molecular clouds.


  We tackle the question of whether an agent can, by suitable choice of
prompts, control an AI bot to any state. To that end, we first introduce a
formal definition of ``meaning'' that is amenable to analysis. Then, we
characterize ``meaningful data'' on which large language models (LLMs) are
ostensibly trained, and ``well-trained LLMs'' through conditions that are
largely met by today's LLMs. While a well-trained LLM constructs an embedding
space of meanings that is Euclidean, meanings themselves do not form a vector
(linear) subspace, but rather a quotient space within. We then characterize the
subset of meanings that can be reached by the state of the LLMs for some input
prompt, and show that a well-trained bot can reach any meaning albeit with
small probability. We then introduce a stronger notion of controllability as
{\em almost certain reachability}, and show that, when restricted to the space
of meanings, an AI bot is controllable. We do so after introducing a functional
characterization of attentive AI bots, and finally derive necessary and
sufficient conditions for controllability. The fact that AI bots are
controllable means that an adversary could steer them towards any state.
However, the sampling process can be designed to counteract adverse actions and
avoid reaching undesirable regions of state space before their boundary is
crossed.


  The updated CLEO measurement of the electromagnetic penguin process $B \to
X_s \gamma$ is presented and compared to the ALEPH result. Implications on new
physics are discussed and the status of recent searches for $B \to X_s l^+ l^-$
modes is given.


  Although deep convolutional networks have been widely studied for head and
neck (HN) organs at risk (OAR) segmentation, their use for routine clinical
treatment planning is limited by a lack of robustness to imaging artifacts, low
soft tissue contrast on CT, and the presence of abnormal anatomy. In order to
address these challenges, we developed a computationally efficient nested block
self-attention (NBSA) method that can be combined with any convolutional
network. Our method achieves computational efficiency by performing non-local
calculations within memory blocks of fixed spatial extent. Contextual
dependencies are captured by passing information in a raster scan order between
blocks, as well as through a second attention layer that causes bi-directional
attention flow. We implemented our approach on three different networks to
demonstrate feasibility. Following training using 200 cases, we performed
comprehensive evaluations using conventional and clinical metrics on a separate
set of 172 test scans sourced from external and internal institution datasets
without any exclusion criteria. NBSA required a similar number of computations
(15.7 gflops) as the most efficient criss-cross attention (CCA) method and
generated significantly more accurate segmentations for brain stem (Dice of
0.89 vs. 0.86) and parotid glands (0.86 vs. 0.84) than CCA. NBSA's
segmentations were less variable than multiple 3D methods, including for small
organs with low soft-tissue contrast such as the submandibular glands (surface
Dice of 0.90).


  We use the Sloan-Digital Sky Survey quasar catalog to statistically infer the
local abundance of black holes heavier than $10^8M_\odot$, which allows us to
estimate the detection prospect of super-massive black holes by future
observational campaigns. We find that the upcoming James Webb Space Telescope
(JWST) and the Extremely Large Telescope (ELT) should be able to resolve, with
integral field spectroscopy techniques, the gravitational influence of
$\sim10^3$ black holes within a sphere of $\sim50\;\rm Mpc$. A Very-Long
Baseline (VLB) observatory with one receiver placed in a geostationary orbit,
is predicted to capture $\sim10$ images of the silhouette of a black hole,
similar to the image of $\rm M87^*$ recently performed by the Event Horizon
Telescope.


  Electronic nematicity has been found in a wide range of strongly correlated
electron materials, resulting in the electronic states having a symmetry that
is lower than that of the crystal that hosts them. One of the most astonishing
examples is Sr$_3$Ru$_2$O$_7$, in which a small in-plane component of a
magnetic field induces significant resistivity anisotropy. The direction of
this anisotropy follows the direction of the in-plane field. The microscopic
origin of this field-induced nematicity has been a long-standing puzzle, with
recent experiments suggesting a field-induced spin density wave driving the
anisotropy. Here, we report spectroscopic imaging of a field-controlled
anisotropy of the electronic structure at the surface of Sr$_3$Ru$_2$O$_7$. We
track the electronic structure as a function of the direction of the field,
revealing a continuous change with the angle. This continuous evolution
suggests a mechanism based on spin-orbit coupling resulting in compass-like
control of the electronic bands. The anisotropy of the electronic structure
persists to temperatures about an order of magnitude higher compared to the
bulk, demonstrating novel routes to stabilize such phases over a wider
temperature range.


  A difference matrix over a group is a discrete structure that is intimately
related to many other combinatorial designs, including mutually orthogonal
Latin squares, orthogonal arrays, and transversal designs. Interest in
constructing difference matrices over $2$-groups has been renewed by the recent
discovery that these matrices can be used to construct large linking systems of
difference sets, which in turn provide examples of systems of linked symmetric
designs and association schemes. We survey the main constructive and
nonexistence results for difference matrices, beginning with a classical
construction based on the properties of a finite field. We then introduce the
concept of a contracted difference matrix, which generates a much larger
difference matrix. We show that several of the main constructive results for
difference matrices over abelian $p$-groups can be substantially simplified and
extended using contracted difference matrices. In particular, we obtain new
linking systems of difference sets of size $7$ in infinite families of abelian
$2$-groups, whereas previously the largest known size was $3$.


  We prove that in a strongly pseudoconvex domain with smooth boundary, then
the length of a geodesic for the Kobayashi-Royden infinitesimal metric between
two points is bounded by a constant multiple of the Euclidean distance between
the points.


  A city's critical infrastructure such as gas, water, and power systems, are
largely interdependent since they share energy, computing, and communication
resources. This, in turn, makes it challenging to endow them with fool-proof
security solutions. In this paper, a unified model for interdependent
gas-power-water infrastructure is presented and the security of this model is
studied using a novel game-theoretic framework. In particular, a zero-sum
noncooperative game is formulated between a malicious attacker who seeks to
simultaneously alter the states of the gas-power-water critical infrastructure
to increase the power generation cost and a defender who allocates
communication resources over its attack detection filters in local areas to
monitor the infrastructure. At the mixed strategy Nash equilibrium of this
game, numerical results show that the expected power generation cost deviation
is 35\% lower than the one resulting from an equal allocation of resources over
the local filters. The results also show that, at equilibrium, the
interdependence of the power system on the natural gas and water systems can
motivate the attacker to target the states of the water and natural gas systems
to change the operational states of the power grid. Conversely, the defender
allocates a portion of its resources to the water and natural gas states of the
interdependent system to protect the grid from state deviations.


  White dwarfs with log g lower than 7.0 are called Extremely Low Mass white
dwarfs (ELMs). They were first found as companions to pulsars, then to other
white dwarfs and main sequence stars (The ELM Survey: 2010 to 2016), and can
only be formed in interacting binaries in the age of the Universe. In our SDSS
DR12 white dwarf catalog (Kepler et al. 2016), we found a few thousand stars in
the effective temperature and surface gravity ranges attributed to ELMs. We
have called these objects sdAs, alluding to their narrow hydrogen line spectra
showing sub-main sequence log g. One possible explanation for the sdAs is that
they are ELMs. Increasing the ELMs sample would help constrain the number of
close binaries in the Galaxy. Interestingly, if they turn out to be A stars
with an overestimated log g, the distance modulus would put these young stars
in the Galaxy's halo.


  We discuss the synergies between heliospheric and dust science, the open
science questions, the technological endeavors and programmatic aspects that
are important to maintain or develop in the decade to come. In particular, we
illustrate how we can use interstellar dust in the solar system as a tracer for
the (dynamic) heliosphere properties, and emphasize the fairly unexplored, but
potentially important science question of the role of cosmic dust in
heliospheric and astrospheric physics. We show that an Interstellar Probe
mission with a dedicated dust suite would bring unprecedented advances to
interstellar dust research, and can also contribute-through measuring dust - to
heliospheric science. This can, in particular, be done well if we work in
synergy with other missions inside the solar system, thereby using multiple
vantage points in space to measure the dust as it `rolls' into the heliosphere.
Such synergies between missions inside the solar system and far out are crucial
for disentangling the spatially and temporally varying dust flow. Finally, we
highlight the relevant instrumentation and its suitability for contributing to
finding answers to the research questions.


  Observations are reported of different sources of $CP$ violation from an
amplitude analysis of $B^+ \to \pi^+ \pi^+ \pi^-$ decays, based on a data
sample corresponding to an integrated luminosity of $3 \; {\rm fb}^{-1}$ of
$pp$ collisions recorded with the LHCb detector. A large $CP$ asymmetry is
observed in the decay amplitude involving the tensor $f_2(1270)$ resonance, and
in addition significant $CP$ violation is found in the $\pi^+ \pi^-$ S-wave at
low invariant mass. The presence of $CP$ violation related to interference
between the $\pi^+ \pi^-$ S-wave and the P-wave $B^+ \to \rho(770)^0 \pi^+$
amplitude is also established; this causes large local asymmetries but cancels
when integrated over the phase space of the decay. The results provide both
qualitative and quantitative new insights into $CP$-violation effects in
hadronic $B$ decays.


  Skin cancer is a serious worldwide health issue, precise and early detection
is essential for better patient outcomes and effective treatment. In this
research, we use modern deep learning methods and explainable artificial
intelligence (XAI) approaches to address the problem of skin cancer detection.
To categorize skin lesions, we employ four cutting-edge pre-trained models:
XceptionNet, EfficientNetV2S, InceptionResNetV2, and EfficientNetV2M. Image
augmentation approaches are used to reduce class imbalance and improve the
generalization capabilities of our models. Our models decision-making process
can be clarified because of the implementation of explainable artificial
intelligence (XAI). In the medical field, interpretability is essential to
establish credibility and make it easier to implement AI driven diagnostic
technologies into clinical workflows. We determined the XceptionNet
architecture to be the best performing model, achieving an accuracy of 88.72%.
Our study shows how deep learning and explainable artificial intelligence (XAI)
can improve skin cancer diagnosis, laying the groundwork for future
developments in medical image analysis. These technologies ability to allow for
early and accurate detection could enhance patient care, lower healthcare
costs, and raise the survival rates for those with skin cancer. Source Code:
https://github.com/Faysal-MD/An-Interpretable-Deep-Learning?Approach-for-Skin-Cancer-Categorization-IEEE2023


  New string models in D=4 space-time extended by tensor central charge
coordinates $z_{mn}$ are constructed. We use the $z_{mn}$ coordinates to
generate string tension using a minimally extended string action linear in
$dz^{mn}$. It is shown that the presence of $z_{mn}$ lifts the light-like
character of the tensionless string worldsheet and the degeneracy of its
induced metric. We analyse the equations of motion and find a solution of the
string equations in the generalized D=(4+6)-dimensional space $X^{\cal
M}=(x^{m},z^{mn})$ with $z_{mn}$ describing a spin wave process. A
supersymmetric version of the proposed model is formulated.


  We report experimental and theoretical results on the extremely large Lamb
shift in a multimode circuit quantum electrodynamics (QED) system in the
deep-strong coupling (DSC) regime, where the qubit-resonator coupling strength
is comparable to or larger than the qubit and resonator frequencies. The system
comprises a superconducting flux qubit (FQ) and a quarter-wavelength coplanar
waveguide resonator ($\lambda/4$ CPWR) that are coupled inductively through a
shared edge that contains a Josephson junction to achieve the DSC regime.
Spectroscopy is performed around the frequency of the fundamental mode of the
CPWR, and the spectrum is fitted by the single-mode quantum Rabi Hamiltonian to
obtain the system parameters. Since the qubit is also coupled to a large number
of higher modes in the resonator, the single-mode fitting does not provide the
bare qubit energy but a value that incorporates the renormalization from all
the other modes. We derive theoretical formulas for the Lamb shift in the
multimode resonator system. As shown in previous studies, there is a cut-off
frequency $\omega_{\rm{cutoff}}$ for the coupling between the FQ and the modes
in the CPWR, where the coupling grows as $\sqrt{\omega_n}$ for
$\omega_n/\omega_{\rm{cutoff}}\ll 1$ and decreases as $1/\sqrt{\omega_n}$ for
$\omega_n/\omega_{\rm{cutoff}}\gg 1$. Here $\omega_n$ is the frequency of the
$n$th mode. The cut-off effect occurs because the qubit acts as an obstacle for
the current in the resonator, which suppresses the current of the modes above
$\omega_{\rm{cutoff}}$ at the location of the qubit and results in a reduced
coupling strength. Using our observed spectrum and theoretical formulas, we
estimate that the Lamb shift from the fundamental mode is 82.3\% and the total
Lamb shift from all the modes is 96.5\%.


  Previously it has been shown that imposing a Petrov-like boundary condition
on a hypersurface may reduce the Einstein equation to the incompressible
Navier-Stokes equation, but all these correspondences are established in the
near horizon limit. In this note, we remark that this strategy can be extended
to an arbitrary finite cutoff surface which is spatially flat, and the
Navier-Stokes equation is obtained by employing a non-relativistic
long-wavelength limit.


  We use far-UV absorption spectra obtained with FUSE towards three late B
stars to study the formation and excitation of H2 in the diffuse ISM. The data
interpretation relies on a model of the chemical and thermal balance in
photon-illuminated gas. The data constrain well the nR product between gas
density and H2 formation rate on dust grains: nR = 1 to 2.2 e-15 s-1. For each
line of sight the mean effective H2 density n, assumed uniform, is obtained by
the best fit of the model to the observed N(J=1)/N(J=0) ratio, since the
radiation field is known. Combining n with the nR values, we find similar H2
formation rates for the three stars of about R = 4 e-17 cm3/s.
  Because the target stars do not interact with the absorbing matter we can
show that the H2 excitation in the J>2 levels cannot be accounted for by the UV
pumping of the cold H2 but implies collisional excitation in regions where the
gas is much warmer. The existence of warm H2 is corroborated by the fact that
the star with the largest column density of CH+ has the largest amount of warm
H2.


  We study hypersurfaces either in the sphere \s{n+1} or in the hyperbolic
space \h{n+1} whose position vector $x$ satisfies the condition $L_kx=Ax+b$,
where $L_k$ is the linearized operator of the $(k+1)$-th mean curvature of the
hypersurface for a fixed $k=0,...,n-1$, $A\in\R{(n+2)\times (n+2)}$ is a
constant matrix and $b\in\R{n+2}$ is a constant vector. For every $k$, we prove
that when $A$ is self-adjoint and $b=0$, the only hypersurfaces satisfying that
condition are hypersurfaces with zero $(k+1)$-th mean curvature and constant
$k$-th mean curvature, and open pieces of standard Riemannian products of the
form $\s{m}(\sqrt{1-r^2})\times\s{n-m}(r)\subset\s{n+1}$, with $0<r<1$, and
$\h{m}(-\sqrt{1+r^2})\times\s{n-m}(r)\subset\h{n+1}$, with $r>0$. If $H_k$ is
constant, we also obtain a classification result for the case where $b\neq 0$.


  We present a new Self-Supervised Learning (SSL) approach to pre-train
encoders on unlabeled audio data that reduces the need for large amounts of
labeled data for audio and speech classification. Our primary aim is to learn
audio representations that can generalize across a large variety of speech and
non-speech tasks in a low-resource un-labeled audio pre-training setting.
Inspired by the recent success of clustering and contrasting learning paradigms
for SSL-based speech representation learning, we propose SLICER (Symmetrical
Learning of Instance and Cluster-level Efficient Representations), which brings
together the best of both clustering and contrasting learning paradigms. We use
a symmetric loss between latent representations from student and teacher
encoders and simultaneously solve instance and cluster-level contrastive
learning tasks. We obtain cluster representations online by just projecting the
input spectrogram into an output subspace with dimensions equal to the number
of clusters. In addition, we propose a novel mel-spectrogram augmentation
procedure, k-mix, based on mixup, which does not require labels and aids
unsupervised representation learning for audio. Overall, SLICER achieves
state-of-the-art results on the LAPE Benchmark \cite{9868132}, significantly
outperforming DeLoRes-M and other prior approaches, which are pre-trained on
$10\times$ larger of unsupervised data. We will make all our codes available on
GitHub.


  Multifractal analysis studies level sets of asymptotically defined quantities
in a topological dynamical system. We consider the topological pressure
function on such level sets, relating it both to the pressure on the entire
phase space and to a conditional variational principle. We use this to recover
information on the topological entropy and Hausdorff dimension of the level
sets.
  Our approach is thermodynamic in nature, requiring only existence and
uniqueness of equilibrium states for a dense subspace of potential functions.
Using an idea of Hofbauer, we obtain results for all continuous potentials by
approximating them with functions from this subspace.
  This technique allows us to extend a number of previous multifractal results
from the $C^{1+\epsilon}$ case to the $C^1$ case. We consider ergodic ratios
$S_n \phi/S_n \psi$ where the function $\psi$ need not be uniformly positive,
which lets us study dimension spectra for non-uniformly expanding maps. Our
results also cover coarse spectra and level sets corresponding to more general
limiting behaviour.


  We present data from simultaneous Chandra, XMM-Newton and BeppoSAX
observations of the Seyfert 1 galaxy NGC 3516, taken during 2001 April and Nov.
We have investigated the nature of the very flat observed X-ray spectrum.
Chandra grating data show the presence of X-ray absorption lines, revealing two
distinct components of the absorbing gas, one which is consistent with our
previous model of the UV/X-ray absorber while the other, which is outflowing at
a velocity of ~1100 km/s has a larger column density and is much more highly
ionized. The broad-band spectral characteristics of the X-ray continuum
observed with XMM during 2001 April, reveal the presence of a third layer of
absorption consisting of a very large column (~2.5 x 10E23 cm^-2) of highly
ionized gas with a covering fraction ~50%. This low covering fraction suggests
that the absorber lies within a few lt-days of the X-ray source and/or is
filamentary in structure. Interestingly, these absorbers are not in thermal
equilibrium with one another. The two new components are too highly ionized to
be radiatively accelerated, which we suggest is evidence for a hydromagnetic
origin for the outflow. Applying our model to the Nov dataset, we can account
for the spectral variability primarily by a drop in the ionization states of
the absorbers, as expected by the change in the continuum flux. When this
complex absorption is accounted for we find the underlying continuum to be
typical of Seyfert 1 galaxies. The spectral curvature attributed to the high
column absorber, in turn, reduces estimates of the flux and extent of any broad
Fe emission line from the accretion disk.


  We introduce and study a Maker-Breaker type game in which the issue is to
create or avoid two disjoint dominating sets in graphs without isolated
vertices. We prove that the maker has a winning strategy on all connected
graphs if the game is started by the breaker. This implies the same in the
$(2:1)$ biased game also in the maker-start game. It remains open to
characterize the maker-win graphs in the maker-start non-biased game, and to
analyze the $(a:b)$ biased game for $(a:b)\neq (2:1)$. For a more restricted
variant of the non-biased game we prove that the maker can win on every graph
without isolated vertices.


  In coupled space-division multiplexing (SDM) transmission systems,
imperfections in optical amplifiers and passive devices introduce
mode-dependent loss (MDL) and gain (MDG). These effects render the channel
capacity stochastic and result in a decrease in average capacity. Several
previous studies employ multi-section simulations to model the capacity of
these systems. Additionally, relevant works derive analytically the capacity
distribution for a single-mode system with polarization-dependent gain and loss
(mode count D = 2). However, to the best of our knowledge, analytic expressions
of the capacity distribution for systems with D > 2 have not been presented. In
this paper, we provide analytic expressions for the capacity of optical systems
with arbitrary mode counts. The expressions rely on Gaussian approximations for
the per-mode capacity distributions and for the overall capacity distribution,
as well as on fitting parameters for the capacity cross-correlation among
different modes. Compared to simulations, the derived analytical expressions
exhibit a suitable level of accuracy across a wide range of practical
scenarios.


  We study the AC electrical conductivity at zero temperature in a holographic
model for a Weyl semimetal. At small frequencies we observe a linear dependence
in the frequency. The model shows a quantum phase transition between a
topological semimetal (Weyl semimetal phase) with a non vanishing anomalous
Hall conductivity and a trivial semimetal. The AC conductivity has an
intermediate scaling due to the presence of a quantum critical region in the
phase diagram of the system. The phase diagram is reconstructed using the
scaling properties of the conductivity. We compare with the experimental data
of [1502.03807] obtaining qualitative agreement.


  Marine pollution is a growing worldwide concern, affecting health of marine
ecosystems, human health, climate change, and weather patterns. To reduce
underwater pollution, it is critical to have access to accurate information
about the extent of marine pollutants as otherwise appropriate countermeasures
and cleaning measures cannot be chosen. Currently such information is difficult
to acquire as existing monitoring solutions are highly laborious or costly,
limited to specific pollutants, and have limited spatial and temporal
resolution. In this article, we present a research vision of large-scale
autonomous marine pollution monitoring that uses coordinated groups of
autonomous underwater vehicles (AUV)s to monitor extent and characteristics of
marine pollutants. We highlight key requirements and reference technologies to
establish a research roadmap for realizing this vision. We also address the
feasibility of our vision, carrying out controlled experiments that address
classification of pollutants and collaborative underwater processing, two key
research challenges for our vision.


  Partially molten rock is a densely packed, melt-saturated, granular medium,
but it has seldom been considered in these terms. In this manuscript, we extend
the continuum theory of partially molten rock to incorporate the physics of
granular media. Our formulation includes dilatancy in a viscous constitutive
law and introduces a non-local fluidity. We analyse the resulting
poro-viscous--granular theory in terms of two modes of liquid--solid
segregation that are observed in published torsion experiments: localisation of
liquid into high-porosity sheets and radially inward liquid flow. We show that
the newly incorporated granular physics brings the theory into agreement with
experiments. We discuss these results in the context of grain-scale physics
across the nominal jamming fraction at the high homologous temperatures
relevant in geological systems.


  Under categorial grammars that have powerful rules like composition, a simple
n-word sentence can have exponentially many parses. Generating all parses is
inefficient and obscures whatever true semantic ambiguities are in the input.
This paper addresses the problem for a fairly general form of Combinatory
Categorial Grammar, by means of an efficient, correct, and easy to implement
normal-form parsing technique. The parser is proved to find exactly one parse
in each semantic equivalence class of allowable parses; that is, spurious
ambiguity (as carefully defined) is shown to be both safely and completely
eliminated.


  Formal methods for guaranteeing that a protocol satisfies a cryptographic
security definition have advanced substantially, but such methods are still
labor intensive and the need remains for an automated tool that can positively
identify an insecure protocol. In this work, we demonstrate that property-based
testing, "run it a bunch of times and see if it breaks", is effective for
detecting security bugs in secure protocols. We specifically target Secure
Multi-Party Computation (MPC), because formal methods targeting this security
definition for bit-model implementations are particularly difficult. Using
results from the literature for Probabilistic Programming Languages and
statistical inference, we devise a test that can detect various flaws in a
bit-level implementation of an MPC protocol. The test is grey-box; it requires
only transcripts of randomness consumed by the protocol and of the inputs,
outputs, and messages. It successfully detects several different mistakes and
biases introduced into two different implementations of the classic GMW
protocol. Applied to hundreds of randomly generated protocols, it identifies
nearly all of them as insecure. We also include an analysis of the parameters
of the test, and discussion of what makes detection of MPC (in)security
difficult.


  We study the irreducible components of special loci of curves whose group of
symmetries is given as certain group extension. We introduce some relative
Hurwitz data, which we show by using mixed \'etale cohomology theory,
identifies some irreducible components for rational and normal non-abelian
special loci and Hurwitz spaces. A heuristic, that is supported by three
classes of examples, provides an additional context for building further
irreducible loci.


  We formulate and prove a generalized Albanese property for families of maps
from a smooth curve over an arbitrary field into a commutative group stack. Our
proof, which is mostly self-contained, employs local-to-global techniques and
some new Ext-vanishing results to reduce to the local Cartier self-duality
theorem of Contou-Carrere. As a corollary, we reprove local and global
geometric class field theory with arbitrary ramification.


  We examine the disc--jet connection in stellar mass and supermassive black
holes by investigating the properties of their compact emission in the X-ray
and radio bands. We compile a sample of ~100 active galactic nuclei with
measured mass, 5 GHz core emission, and 2-10 keV luminosity, together with 8
galactic black holes with a total of ~50 simultaneous observations in the radio
and X-ray bands. Using this sample, we study the correlations between the radio
(L_{R}) and the X-ray (L_{X}) luminosity and the black hole mass (M). We find
that the radio luminosity is correlated with {\em both} M and L_{X}, at a
highly significant level. In particular, we show that the sources define a
``fundamental plane'' in the three-dimensional (log L_{R},log L_{X},log M)
space, given by log L_{R}=(0.60^{+0.11}_{-0.11}) log L_{X}
+(0.78^{+0.11}_{-0.09}) log M + 7.33^{+4.05}_{-4.07}, with a substantial
scatter of \sigma_{R}=0.88. We compare our results to the theoretical relations
between radio flux, black hole mass, and accretion rate derived by Heinz and
Sunyaev (2003). Such relations depend only on the assumed accretion model and
on the observed radio spectral index. Therefore, we are able to show that the
X-ray emission from black holes accreting at less than a few per cent of the
Eddington rate is unlikely to be produced by radiatively efficient accretion,
and is marginally consistent with optically thin synchrotron emission from the
jet. On the other hand, models for radiatively inefficient accretion flows seem
to agree well with the data.


  We investigate the Gaussian small ball probabilities with random centers,
find their deterministic a.s.-equivalents and establish a relation to
infinite-dimensional high-resolution quantization.


  Recently deep neural networks, which require a large amount of annotated
samples, have been widely applied in nuclei instance segmentation of H\&E
stained pathology images. However, it is inefficient and unnecessary to label
all pixels for a dataset of nuclei images which usually contain similar and
redundant patterns. Although unsupervised and semi-supervised learning methods
have been studied for nuclei segmentation, very few works have delved into the
selective labeling of samples to reduce the workload of annotation. Thus, in
this paper, we propose a novel full nuclei segmentation framework that chooses
only a few image patches to be annotated, augments the training set from the
selected samples, and achieves nuclei segmentation in a semi-supervised manner.
In the proposed framework, we first develop a novel consistency-based patch
selection method to determine which image patches are the most beneficial to
the training. Then we introduce a conditional single-image GAN with a
component-wise discriminator, to synthesize more training samples. Lastly, our
proposed framework trains an existing segmentation model with the above
augmented samples. The experimental results show that our proposed method could
obtain the same-level performance as a fully-supervised baseline by annotating
less than 5% pixels on some benchmarks.


  In this paper, we compute the $q$-adic slopes of the L-functions of an
important class of exponential sums arising from analytic number theory. Our
main tools include Adolphson-Sperber's work on toric exponential sums and Wan's
decomposition theorems.


  FIREBall-2 is a stratospheric balloon-borne 1-m telescope coupled to a UV
multi-object slit spectrograph designed to map the faint UV emission
surrounding z~0.7 galaxies and quasars through their Lyman-alpha line emission.
This spectro-imager had its first launch on September 22nd 2018 out of Ft.
Sumner, NM, USA. Because the balloon was punctured, the flight was abruptly
interrupted. Instead of the nominal 8 hours above 32 km altitude, the
instrument could only perform science acquisition for 45 minutes at this
altitude. In addition, the shape of the deflated balloon, combined with a full
Moon, revealed a severe off-axis scattered light path, directly into the UV
science detector and about 100 times larger than expected. In preparation for
the next flight, and in addition to describing FIREBall-2's upgrade, this paper
discusses the exposure time calculator (ETC) that has been designed to analyze
the instrument's optimal performance (explore the instrument's limitations and
subtle trade-offs).


  We report on infrared studies of the c-axis electrodynamics of Tl-Ba-Cu-O
(Tl-2201) crystals. A sum rule analysis reveals spectral weight shifts that can
be interpreted as a kinetic energy change at the superconducting transistion.
In optimally doped crystals, showing an incoherent normal state response, the
kinetic energy is lowered at T < Tc, but no significant change is found in the
over-doped samples, which have more coherent conductivity at T > Tc.


  Despite its theoretical and practical importance, the pion structure is still
badly constrained, particularly at low $x_{\pi}$ and in the sea-quark and gluon
sectors. Recently ZEUS have presented data on dijet photoproduction with a
leading neutron, which is dominated by slightly off-shell pion exchange and can
be used to constrain the pion densities down to $x_{\pi}\simeq 0.01$. We
compare a recent NLO calculation to the ZEUS data and find that the lower gluon
densities of SMRS seem to be preferred by the data. Theoretical uncertainties,
in particular from the pion flux, are discussed in some detail.


  Voltage underscaling below the nominal level is an effective solution for
improving energy efficiency in digital circuits, e.g., Field Programmable Gate
Arrays (FPGAs). However, further undervolting below a safe voltage level and
without accompanying frequency scaling leads to timing related faults,
potentially undermining the energy savings. Through experimental voltage
underscaling studies on commercial FPGAs, we observed that the rate of these
faults exponentially increases for on-chip memories, or Block RAMs (BRAMs). To
mitigate these faults, we evaluated the efficiency of the built-in
Error-Correction Code (ECC) and observed that more than 90% of the faults are
correctable and further 7% are detectable (but not correctable). This
efficiency is the result of the single-bit type of these faults, which are then
effectively covered by the Single-Error Correction and Double-Error Detection
(SECDED) design of the built-in ECC. Finally, motivated by the above
experimental observations, we evaluated an FPGA-based Neural Network (NN)
accelerator under low-voltage operations, while built-in ECC is leveraged to
mitigate undervolting faults and thus, prevent NN significant accuracy loss. In
consequence, we achieve 40% of the BRAM power saving through undervolting below
the minimum safe voltage level, with a negligible NN accuracy loss, thanks to
the substantial fault coverage by the built-in ECC.


  The first experience of virtual free-radical copolymerization (FRCP) of vinyl
monomers with stable radicals in the framework of the digital twins (DTs)
concept (arXiv:2309.11616 [physics.chem-ph] and arXiv:2311.02752
[cond-mat.mtrl-sci]) is extended to N-isopropylacrylamide (NIPA). The
virtualization of the chemical process is based on the concept of a chain
reaction that covers a set of elementary reactions (ERs) and is the most
suitable for quantum chemical treatment. The calculations were performed using
a semi-empirical version of the unrestricted Hartree-Fock approximation. Once
input in the chemical reactor, providing free-radical polymerization of NIPA,
the fullerene C60 inhibits capturing the formed monomer-radicals and terminates
the polymerization. The obtained virtual kinetic data, providing the appearance
of an induction period at the initial stage of the NIPA polymerization, are in
a full agreement with experimental reality.


  Magnetic and magnetocaloric properties of high-purity, giant magnetocaloric
polycrystalline and single-crystalline Fe2P are investigated. Fe2P displays a
moderate magnetic entropy change which spans over 70 K and the presence of
strong magnetization anisotropy proves this system is not fully itinerant but
displays a mix of itinerant and localized magnetism. The properties of pure
Fe2P are compared to those of giant magnetocaloric (Fe,Mn)2(P,A) compounds
helping understand the exceptional characteristics shown by the latter which
are so promising for heat pump and energy conversion applications.


  Some bounds on the entropic informational quantities related to a quantum
continual measurement are obtained and the time dependencies of these
quantities are studied.


  Dispersive effects during long wave run-up on a plane beach are studied. We
take an advantage of experimental data collection of different wave types
(single pulses, sinusoidal waves, bi-harmonic waves, and frequency modulated
wave trains) and simulate their run-up using two models: (i) non-dispersive
nonlinear shallow water theory and (ii) dispersive Boussinesq type model based
on the modified Peregrine system. It is shown, that for long positive pulses,
dispersive effects are not so important and nonlinear shallow water theory can
be used. However, for periodic sinusoidal and bi-harmonic pulses of the same
period, the dispersive effects result in significant wave transformation during
its propagation, but do not have a strong impact on its maximal run-up height.
Overall, for maximum wave run-up height, we could not find a preference of
dispersive model against the nondispersive one, and, therefore, suggest using
nonlinear shallow water model for long wave run-up height estimation.


  We derive the quantization of magnetic helicity in the solid-state and
demonstrate tunable macroscopic quantum tunneling, coherence, and oscillation
for a skyrmion spin texture stabilized in frustrated magnets. We also discuss
the parameter space for the experimental realization of quantum effects.
Typically, for a skyrmion of 5 nm radius, quantum tunneling between two
macroscopic states with distinct helicities occurs with an inverse escape rate
within seconds below 100 mK, and an energy splitting in the MHz regime.
Feasibility of quantum tunneling of an ensemble of magnetic spins inspires new
platforms for quantum operations utilizing topologically protected chiral spin
configurations.


  In the probe limit, we numerically build a holographic $p$-wave superfluid
model in the four-dimensional Lifshitz black hole coupled to a Maxwell-complex
vector field. We observe the rich phase structure and find that the Lifshitz
dynamical exponent $z$ contributes evidently to the effective mass of the
matter field and dimension of the gravitational background. Concretely, we
obtain the Cave of Winds appeared only in the five-dimensional anti-de
Sitter~(AdS) spacetime, and the increasing $z$ hinders not only the condensate
but also the appearance of the first-order phase transition. Furthermore, our
results agree with the Ginzburg-Landau results near the critical temperature.
In addition, the previous AdS superfluid model is generalized to the Lifshitz
spacetime.


  In this paper, we investigate the energy decay of hyperbolic systems of
wave-wave, wave-Euler- Bernoulli beam and beam-beam types. The two equations
are coupled through boundary connection with only one localized non-smooth
fractional Kelvin-Voigt damping. First, we reformulate each system into an
augmented model and using a general criteria of Arendt-Batty, we prove that our
models are strongly stable. Next, by using frequency domain approach, combined
with multiplier technique and some interpolation inequalities, we establish
different types of polynomial energy decay rate which depends on the order of
the fractional derivative and the type of the damped equation in the system.


  We have recently introduced an approach for studying perturbatively classical
and quantum canonical general relativity. The perturbative technique appears to
preserve many of the attractive features of the non-perturbative quantization
approach based on Ashtekar's new variables and spin networks. With this
approach one can find perturbatively classical observables (quantities that
have vanishing Poisson brackets with the constraints) and quantum states
(states that are annihilated by the quantum constraints). The relative ease
with which the technique appears to deal with these traditionally hard problems
opens several questions about how relevant the results produced can possibly
be. Among the questions is the issue of how useful are results for large values
of the cosmological constant and how the approach can deal with several
pathologies that are expected to be present in the canonical approach to
quantum gravity. With the aim of clarifying these points, and to make our
construction as explicit as possible, we study its application in several
simple models. We consider Bianchi cosmologies, the asymmetric top, the coupled
harmonic oscillators with constant energy density and a simple quantum
mechanical system with two Hamiltonian constraints. We find that the technique
satisfactorily deals with the pathologies of these models and offers promise
for finding (at least some) results even for small values of the cosmological
constant. Finally, we briefly sketch how the method would operate in the full
four dimensional quantum general relativity case.


  This PhD thesis is devoted to show that differential renormalization is a
simple and useful renormalization method that we can use when dealing with
gauge theories. In this work, it is shown how the one-loop results of
Constraint Differential Renormalization can be fruitfully applied when
renormalizing two-loop amplitudes. As an example of this procedure, the
two-loop beta functions of various relevant gauge theories are obtained (QED,
SuperQED, Yang-Mills and N=1 SuperYM) without making use of the Ward
identities, which are mandatory in the standard differential renormalization
procedure. Also, we study how to deal with expressions that have IR and UV
divergences, showing that both are renormalized with independent scales. This
result allow us to give new insight on the origin of the higher order
corrections to the beta function of the N=1 SuperYM theory, as in this case we
have both divergences due to the form of the gauge propagator. This is an
advantage over usual dimensional regularization methods, where both divergences
become mixed.


  We introduce exponential numerical integration methods for stiff stochastic
dynamical systems of the form $d\mathbf{z}_t = L(t)\mathbf{z}_tdt +
\mathbf{f}(t)dt + Q(t)d\mathbf{W}_t$. We consider the setting of time-varying
operators $L(t), Q(t)$ where they may not commute $L(t_1)L(t_2) \neq
L(t_2)L(t_1)$, raising challenges for exponentiation. We develop stochastic
numerical integration methods using Mangus expansions for preserving
statistical structures and for maintaining fluctuation-dissipation balance for
physical systems. For computing the contributions of the fluctuation terms, our
methods provide alternative approaches without needing directly to evaluate
stochastic integrals. We present results for our methods for a class of SDEs
arising in particle simulations and for SPDEs for fluctuations of concentration
fields in spatially-extended systems. For time-varying stochastic dynamical
systems, our introduced discretization approaches provide general exponential
numerical integrators for preserving statistical structures while handling
stiffness.


  We present a new set of high-resolution hydrodynamic cosmological zoom-in
simulations that apply the Feedback In Realistic Environments (FIRE) physics to
both Local Group (LG)-like and isolated Milky Way (MW)-like volumes (ten host
systems in total with baryonic particle mass $\simeq 3,500-7,000\,M_\odot$). We
study the stellar mass functions, circular velocity or mass profiles, and
velocity dispersions of the dwarf galaxy populations. The simulations reproduce
the stellar mass function and central densities of MW satellite dwarfs for
$M_\ast \geq10^{5.5}\,M_\odot$ and predict the existence of $\sim3$
unidentified galaxies with $M_\ast\sim10^5\,M_\odot$ within $300$ kpc of the
MW. Overall, we find no evidence for the classical missing satellites or
too-big-to-fail (TBTF) problems for satellite galaxies in our sample. Among the
satellites, TBTF is resolved primarily by subhalo disruption and overall mass
loss; central density profiles of subhalos are of secondary importance. For
non-satellite galaxies, our LG-like simulations predict as many as $\sim10$
as-of-yet unseen galaxies at distances $0.3-1$ Mpc from both hosts, with
$M_\ast\simeq10^{5-6}\,M_\odot$ (in halos with $V_\mathrm{max}\sim
20~\mathrm{km\,s}^{-1}$), albeit with large halo-to-halo variance. None of our
simulations produces a compact, baryon-dominated, high-density dwarf
elliptical-type galaxy (with $V_\mathrm{circ} \gtrsim 35~\mathrm{km\,s}^{-1}$
at $r<1\,$kpc), of which six may appear in the LG (but none in the MW). It may
therefore remain a challenge to reproduce the full diversity of the dwarf
population, including both the highest and lowest density systems.


  A Gaussian Process (GP) is a prominent mathematical framework for stochastic
function approximation in science and engineering applications. This success is
largely attributed to the GP's analytical tractability, robustness,
non-parametric structure, and natural inclusion of uncertainty quantification.
Unfortunately, the use of exact GPs is prohibitively expensive for large
datasets due to their unfavorable numerical complexity of $O(N^3)$ in
computation and $O(N^2)$ in storage. All existing methods addressing this issue
utilize some form of approximation -- usually considering subsets of the full
dataset or finding representative pseudo-points that render the covariance
matrix well-structured and sparse. These approximate methods can lead to
inaccuracies in function approximations and often limit the user's flexibility
in designing expressive kernels. Instead of inducing sparsity via data-point
geometry and structure, we propose to take advantage of naturally-occurring
sparsity by allowing the kernel to discover -- instead of induce -- sparse
structure. The premise of this paper is that GPs, in their most native form,
are often naturally sparse, but commonly-used kernels do not allow us to
exploit this sparsity. The core concept of exact, and at the same time sparse
GPs relies on kernel definitions that provide enough flexibility to learn and
encode not only non-zero but also zero covariances. This principle of
ultra-flexible, compactly-supported, and non-stationary kernels, combined with
HPC and constrained optimization, lets us scale exact GPs well beyond 5 million
data points.


  We propose an unsupervised solution to the Authorship Verification task that
utilizes pre-trained deep language models to compute a new metric called
DV-Distance. The proposed metric is a measure of the difference between the two
authors comparing against pre-trained language models. Our design addresses the
problem of non-comparability in authorship verification, frequently encountered
in small or cross-domain corpora. To the best of our knowledge, this paper is
the first one to introduce a method designed with non-comparability in mind
from the ground up, rather than indirectly. It is also one of the first to use
Deep Language Models in this setting. The approach is intuitive, and it is easy
to understand and interpret through visualization. Experiments on four datasets
show our methods matching or surpassing current state-of-the-art and strong
baselines in most tasks.


  In these lectures, the status of baryon chiral perturbation theory is
reviewed. Particular emphasis is put on the two--flavor sector and the physics
related to electromagnetic probes. I discuss in some detail the structure of
the effective Lagrangian at next--to--leading order, the meaning of low--energy
theorems in Compton scattering and pion photoproduction and confront the chiral
predictions with the existing data. Some remaining problems and challenges are
outlined.


  For $d\geq 3$, we study the Ising model on $\mathbb Z^d$ with random field
given by $\{\epsilon h_v: v\in \mathbb Z^d\}$ where $h_v$'s are independent
normal variables with mean 0 and variance 1. We show that for any $T < T_c$
(here $T_c$ is the critical temperature without disorder), long range order
exists as long as $\epsilon$ is sufficiently small depending on $T$. Our work
extends previous results of Imbrie (1985) and Bricmont--Kupiainen (1988) from
the very low temperature regime to the entire low temperature regime.


  Final state phases \delta_f and \delta_f' in B-> D pi, barD pi decays are
shown to be equal i.e. \delta =\delta_f-\delta_f' = 0. Thus CP-violating
asymmetry A(t) is independent of final state phases. The estimate for the
phases \delta_f and \delta_f' is also given.


  Data science workers increasingly collaborate on large-scale projects before
communicating insights to a broader audience in the form of visualization.
While prior work has modeled how data science teams, oftentimes with distinct
roles and work processes, communicate knowledge to outside stakeholders, we
have little knowledge of how data science workers communicate intermediately
before delivering the final products. In this work, we contribute a nuanced
description of the intermediate communication process within data science
teams. By analyzing interview data with 8 self-identified data science workers,
we characterized the data science intermediate communication process with four
factors, including the types of audience, communication goals, shared
artifacts, and mode of communication. We also identified overarching challenges
in the current communication process. We also discussed design implications
that might inform better tools that facilitate intermediate communication
within data science teams.


  Infectious epidemics can be simulated by employing dynamical processes as
interactions on network structures. Here, we introduce techniques from the
Multi-Agent System (MAS) domain in order to account for individual level
characterization of societal dynamics for the SARS-CoV-2 pandemic. We
hypothesize that a MAS model which considers rich spatial demographics, hourly
mobility data and daily contagion information from the metropolitan area of
Toronto can explain significant emerging behavior. To investigate this
hypothesis we designed, with our modeling framework of choice, GAMA, an
accurate environment which can be tuned to reproduce mobility and healthcare
data, in our case coming from TomTom's API and Toronto's Open Data. We observed
that some interesting contagion phenomena are directly influenced by mobility
restrictions and curfew policies. We conclude that while our model is able to
reproduce non-trivial emerging properties, large-scale simulation are needed to
further investigate the role of different parameters. Finally, providing such
an end-to-end model can be critical for policy-makers to compare their outcomes
with past strategies in order to devise better plans for future measures.


  By tracking tracer particles at high speeds and for long times, we study the
geometric statistics of Lagrangian trajectories in an intensely turbulent
laboratory flow. In particular, we consider the distinction between the
displacement of particles from their initial positions and the total distance
they travel. The difference of these two quantities shows power-law scaling in
the inertial range. By comparing them with simulations of a chaotic but
non-turbulent flow and a Lagrangian Stochastic model, we suggest that our
results are a signature of turbulence.


  We investigate the quantum thermodynamic cycle of a quantum heat engine
carrying out an Otto thermodynamic cycle. We use the thermal properties of a
moving heat bath with relativistic velocity with respect to the cold bath. As a
working medium, we use a two-level system and a harmonic oscillator that
interact with a moving heat bath and a static cold bath. In the current work,
the quantum heat engine is studied in the high and low temperatures regime.
Using quantum thermodynamics and the theory of open quantum system we obtain
the total produced work, the efficiency and the efficiency at maximum power.
The maximum efficiency of the Otto quantum heat engine depends only on the
ratio of the minimum and maximum energy gaps. On the contrary, the efficiency
at maximum power and the extracted work decreases with the velocity since the
motion of the heat bath has an energy cost for the quantum heat engine.
Furthermore, the efficiency at maximum power depends on the nature of the
working medium.


  A particularly attractive feature of inflation is that quantum fluctuations
in the inflaton field may have seeded inhomogeneities in the cosmic microwave
background (CMB) and the formation of large-scale structure. In this paper, we
demonstrate that a scalar field with zero active mass, i.e., with an equation
of state rho+3p=0, where rho and p are its energy density and pressure,
respectively, could also have produced an essentially scale-free fluctuation
spectrum, though without inflation. This alternative mechanism is based on the
Hollands-Wald concept of a minimum wavelength for the emergence of quantum
fluctuations into the semi-classical universe. A cosmology with zero active
mass does not have a horizon problem, so it does not need inflation to solve
this particular (non) issue. In this picture, the 1-10 degree fluctuations in
the CMB correspond almost exactly to the Planck length at the Planck time,
firmly supporting the view that CMB observations may already be probing
trans-Planckian physics.