  We present observations of the 5$_{1,5}\to4_{2,2}$ transition of water vapor
at 325.15 GHz taken with the CSO telescope towards Orion IRc2. The emission is
more extended than that of other molecular species such as CH$_3$OH. However,
it is much less extended than the emission of water vapor at 183.31 GHz
reported by Cernicharo et al (1994). A comparison of the line intensities at
325.15 GHz and 183.31 GHz puts useful constraints on the density and
temperature of the emitting regions and allows an estimate of H_2O abundance,
x(H_2O), of $\simeq10^{-4}$ in the Plateau and $\simeq10^{-6}-10^{-5}$ in the
Ridge.


  We construct an example of a hyperbolic group with a hyperbolic subgroup for
which the Cannon-Thurston map does not exist. That is, inclusion does not
induce a map of the boundaries.


  The Anshel-Anshel-Goldfeld-Lemieux (abbreviated AAGL) key agreement protocol
is proposed to be used on low-cost platforms which constraint the use of
computational resources. The core of the protocol is the concept of an
Algebraic Eraser (abbreviated AE) which is claimed to be a suitable primitive
for use within lightweight cryptography. The AE primitive is based on a new and
ingenious idea of using an action of a semidirect product on a (semi)group to
obscure involved algebraic structures. The underlying motivation for AAGL
protocol is the need to secure networks which deploy Radio Frequency
Identification (RFID) tags used for identification, authentication, tracing and
point-of-sale applications.
  In this paper we revisit the computational problem on which AE relies and
heuristically analyze its hardness. We show that for proposed parameter values
it is impossible to instantiate the secure protocol. To be more precise, in
100% of randomly generated instances of the protocol we were able to find a
secret conjugator z generated by TTP algorithm (part of AAGL protocol).


  In this short note we present several infinite dimensional theorems which
generalize corresponding facts from the finite dimensional differential
inclusions theory.


  We present a dynamical model for the formation and evolution of a massive
disk galaxy, within a growing dark halo whose mass evolves according to
cosmological simulations of structure formation. The galactic evolution is
simulated with a new 3D chemo-dynamical code, including dark matter, stars and
a multi-phase ISM. The simulations start at redshift z=4.85 with a small dark
halo in a LCDM universe and we follow the evolution until the present epoch.
The energy release by massive stars and SNe prevents a rapid collapse of the
baryonic matter and delays the maximum star formation until z=1. The galaxy
forms radially from inside-out and vertically from halo to disk. The first
galactic component that forms is the halo, followed by the bulge, the disk-halo
transition region, and the disk. At z=1, a bar begins to form which later turns
into a triaxial bulge. There is a pronounced deficiency of low-metallicity disk
stars due to pre-enrichment of the disk ISM with metal-rich gas from the bulge
and inner disk (G-dwarf problem). The mean rotation and the distribution of
orbital eccentricities for all stars as a function of metallicity are not very
different from those observed in the solar neighbourhood, showing that
homogeneous collapse models are oversimplified. The approach presented here
provides a detailed description of the formation and evolution of an isolated
disk galaxy in a LCDM universe, yielding new information about the kinematical
and chemical history of the stars and the ISM, but also about the evolution of
the luminosity, the colours and the morphology of disk galaxies.


  I recall the well-known sufficient conditions for the bound $r<16\epsilon$ on
the spectrum of the primordial tensor perturbation. Two recent papers claim a
violation of this bound, without stating explicitely any violation of the
sufficient conditions.


  We apply the recently developed extremely correlated Fermi liquid theory to
the Anderson impurity model, in the extreme correlation limit. We develop an
expansion in a parameter \lambda, related to n_d, the average occupation of the
localized orbital, and find analytic expressions for the Green's functions to
O(\lambda^2). These yield the impurity spectral function and also the
self-energy \Sigma(\omega) in terms of the two self energies of the ECFL
formalism. The imaginary parts of the latter, have roughly symmetric low energy
behaviour (~ \omega^2), as predicted by Fermi Liquid theory. However, the
inferred impurity self energy
  \Sigma"(\omega) develops asymmetric corrections near n_d ~ 1, leading in turn
to a strongly asymmetric impurity spectral function with a skew towards the
occupied states. Within this approximation the Friedel sum rule is satisfied
but we overestimate the quasiparticle weight z relative to the known exact
results, resulting in an over broadening of the Kondo peak. Upon scaling the
frequency by the quasiparticle weight z, the spectrum is found to be in
reasonable agreement with numerical renormalization group results over a wide
range of densities.


  The study of how spin interacts with lattice vibrations and relaxes to
equilibrium provides unique insights on its chemical environment and the
relation between electronic structure and molecular composition. Despite its
importance for several disciplines, ranging from magnetic resonance to quantum
technologies, a convincing interpretation of spin dynamics in crystals of
magnetic molecules is still lacking due to the challenging experimental
determination of the correct spin relaxation mechanism. We apply ab initio spin
dynamics to a series of twelve coordination complexes of Co(II) and Dy(III)
ions selected among $\sim$240 compounds that largely cover the literature on
single-molecule magnets and well represent different regimes of spin
relaxation. Simulations reveal that the Orbach spin relaxation rate of known
compounds mostly depends on the ions' zero-field splitting and little on the
details of molecular vibrations. Raman relaxation is instead found to be also
significantly affected by the features of low-energy phonons. These results
provide a complete understanding of the factors limiting spin lifetime in
single-molecule magnets and revisit years of experimental investigations by
making it possible to transparently distinguish Orbach and Raman relaxation
mechanisms.


  Compressible (full) potential flow is expressed as an equivalent first-order
system of conservation laws for density $\rho$ and velocity $v$. Energy $E$ is
shown to be the only nontrivial entropy for that system in multiple space
dimensions, and it is strictly convex in $\rho,v$ if and only if $|v|<c$. For
motivation some simple variations on the relative entropy theme of
Dafermos/DiPerna are given, for example that smooth regions of weak entropy
solutions shrink at finite speed, and that smooth solutions force solutions of
singular entropy-compatible perturbations to converge to them. We conjecture
that entropy weak solutions of compressible potential flow are unique, in
contrast to the known counterexamples for the Euler equations.


  Stress concentration due to flaws in any material are very dangerous. Its
understanding is thus very important before practical application of the
material. As Fiber Reinforced Composite (FRC) is gaining wide range of
application it is necessary to analyze it for stress concentration as one of
the parameter. Literature survey reveals that the failure of FRC due to
breakage of fiber is a cumulative process. If a fiber breaks stress
concentration develops near the failure which leads to failure of other fibers
in its vicinity. This process continues until the whole FRC gets failed. This
phenomenon is quantified by a parameter called Stress Transfer Coefficient
(STC). To analyze FRC generally it is practiced to analyze Representative
Volume Element (RVE) which is a representation of the complete FRC. Another
important aspect which is considered while analyzing FRC is the distribution of
the fiber. Ideally the distribution of fibers should be uniform but no
manufacturing process guarantees uniform distribution. Thus while analyzing FRC
it is a good practice to generate RVE with randomly distributed fibers. In this
paper an attempt is made to attain the relationship between volume fraction and
STC. FRC with unidirectional fiber orientation is considered. RVEs with
different volume fraction are analyzed. A new method is implemented to generate
RVE with randomly distributed fibers. RVEs are so generated that it contains a
broken fiber at its geometrical center and other fibers surrounding it. The RVE
is loaded along the fiber direction.


  We discuss the decay of accelerated protons and illustrate how the
Fulling-Davies-Unruh effect is indeed mandatory to maintain the consistency of
standard Quantum Field Theory. The confidence level of the Fulling-Davies-Unruh
effect must be the same as that of Quantum Field Theory itself.


  Guibert and Linusson introduced the family of doubly alternating Baxter
permutations, i.e. Baxter permutations $\sigma \in S_n$, such that $\sigma$ and
$\sigma^{-1}$ are alternating. They proved that the number of such permutations
in $S_{2n}$ and $S_{2n+1}$ is the Catalan number $C_n$. In this paper we
explore the expected limit shape of such permutations, following the approach
by Miner and Pak.


  This paper investigates the reduced attitude formation control problem for a
group of rigid-body agents using feedback based on relative attitude
information. Under both undirected and directed cycle graph topologies, it is
shown that reversing the sign of a classic consensus protocol yields
asymptotical convergence to formations whose shape depends on the parity of the
group size. Specifically, in the case of even parity the reduced attitudes
converge asymptotically to a pair of antipodal points and distribute
equidistantly on a great circle in the case of odd parity. Moreover, when the
inter-agent graph is an undirected ring, the desired formation is shown to be
achieved from almost all initial states.


  For a metric space $X$ with a compatible measure $\mu$, Genevois and Tessera
defined the Scaling Group of $(X,\mu)$ as the subgroup $\Gamma$ of
$\mathbb{R}_{>0}$ of positive real numbers $\gamma$ for which there are
quasi-isometries of $X$ coarsely scaling $\mu$ by a factor of $\gamma$. We show
that for any finitely generated subgroup $\Gamma$ of $\mathbb{R}_{>0}$ there
exists a space $N_\Gamma$, bi-Lipschitz equivalent to a graph of finite degree,
with scaling group $\Gamma$.


  We uncover the interaction-induced \emph{stable self-localization} of bosons
in disorder-free superlattices. In these nonthermalized multi-particle states,
one of the particles forms a superposition of multiple standing waves, so that
it provides a quasirandom potential to localize the other particles. We derive
effective Hamiltonians for self-localized states and find their energy level
spacings obeying the Poisson statistics for Anderson-like localization.
Surprisingly, we find that the correlated self-localization can be solely
induced by interaction in the well-studied nonintegrable Bose-Hubbard models,
which has been overlooked for a long time. We propose a dynamical scheme to
detect self-localization, where long-time quantum walks of a single particle
form a superposition of multiple standing waves for trapping the subsequently
loaded particles. Our work provides an experimentally feasible way to realize
stable Anderson-like localization in translation-invariant disorder-free
systems.


  In the foreseeable future, autonomous vehicles will require human assistance
in situations they can not resolve on their own. In such scenarios, remote
assistance from a human can provide the required input for the vehicle to
continue its operation. Typical sensors used in autonomous vehicles include
camera and lidar sensors. Due to the massive volume of sensor data that must be
sent in real-time, highly efficient data compression is elementary to prevent
an overload of network infrastructure. Sensor data compression using deep
generative neural networks has been shown to outperform traditional compression
approaches for both image and lidar data, regarding compression rate as well as
reconstruction quality. However, there is a lack of research about the
performance of generative-neural-network-based compression algorithms for
remote assistance. In order to gain insights into the feasibility of deep
generative models for usage in remote assistance, we evaluate state-of-the-art
algorithms regarding their applicability and identify potential weaknesses.
Further, we implement an online pipeline for processing sensor data and
demonstrate its performance for remote assistance using the CARLA simulator.


  We describe CARTOLABE, a web-based multi-scale system for visualizing and
exploring large textual corpora based on topics, introducing a novel mechanism
for the progressive visualization of filtering queries. Initially designed to
represent and navigate through scientific publications in different
disciplines, CARTOLABE has evolved to become a generic framework and
accommodate various corpora, ranging from Wikipedia (4.5M entries) to the
French National Debate (4.3M entries). CARTOLABE is made of two modules: the
first relies on Natural Language Processing methods, converting a corpus and
its entities (documents, authors, concepts) into high-dimensional vectors,
computing their projection on the 2D plane, and extracting meaningful labels
for regions of the plane. The second module is a web-based visualization,
displaying tiles computed from the multidimensional projection of the corpus
using the U MAP projection method. This visualization module aims at enabling
users with no expertise in visualization and data analysis to get an overview
of their corpus, and to interact with it: exploring, querying, filtering,
panning and zooming on regions of semantic interest. Three use cases are
discussed to illustrate CARTOLABE's versatility and ability to bring large
scale textual corpus visualization and exploration to a wide audience.


  Certain supersymmetric grand unified models predict that the coefficients of
the quadratic terms in the MSSM Higgs potential should be degenerate at the GUT
scale. We discuss some examples for such models, and we analyse the
implications of this peculiar condition of a GUT-scale degenerate Higgs mass
matrix for low-scale MSSM phenomenology. To this end we explore the parameter
space which is consistent with existing experimental constraints by means of a
Markov Chain Monte Carlo analysis.


  Previous evolutionary computations concerning stars with masses in the range
of the ``Red Giants Transition Phase'' are extended to lower metallicities.
Clusters isochrones for two values of the metallicity Z (Z=10E-4, 4E-4) and for
ages down to 1 billion years are presented, discussing selected evolutionary
features characterizing the structure of the stars during both H or He burning
phases. One finds that clusters with Z about equal to 1E-4 an age around 1-2
billion years could be characterized by the occurrence of anomalous He burning
variables at a luminosity of the order of LogL= 2.0-2.2 (in solar units).


  The Dualized Standard Model offers a {\it raison d'\^etre} for 3 fermion
generations and an explanation for their distinctive mass and mixing patterns,
reproducing to a reasonable accuracy the empirical mixing matrix and mass
spectrum for both quarks and leptons in terms of just a few parameters. With
its parameters thus fixed, the result is a highly predictive framework. In
particular, it is shown that it gives explicit parameter-free predictions for
neutrinoless double beta decays. For $^{76}Ge$, it predicts a half-life of
$10^{28}-10^{30}$ years, which satisfies the present experimental lower bound
of $1.8 \times 10^{25}$ years.


  We consider two conformal defects close to each other in a free theory, and
study what happens as the distance between them goes to zero. This limit is the
same as zooming out, and the two defects have fused to another defect. As we
zoom in we find a non-conformal effective action for the fused defect. Among
other things this means that we cannot in general decompose the two-point
correlator of two defects in terms of other conformal defects. We prove the
fusion using the path integral formalism by treating the defects as sources for
a scalar in the bulk.


  Internet Protocol (IP) addresses are frequently used as a method of locating
web users by researchers in several different fields. However, there are
competing reports concerning the accuracy of those locations, and little
research has been done in manually comparing the IP geolocation databases and
web page geographic information. This paper categorized web page from the Yahoo
search engine into twelve categories, ranging from 'Blog' and 'News' to
'Education' and 'Governmental'. Then we manually compared the mailing or street
address of the web page's content creator with the geolocation results by the
given IP address. We introduced a cartographic design method by creating kernel
density maps for visualizing the information landscape of web pages associated
with specific keywords.


  The asymptotic behavior of expressions of the form $%
\sum_{t=1}^{n}f(r_{n}x_{t})$ where $x_{t}$ is an integrated process, $r_{n}$ is
a sequence of norming constants, and $f$ is a measurable function has been the
subject of a number of articles in recent years. We mention Borodin and
Ibragimov (1995), Park and Phillips (1999), de Jong (2004), Jeganathan (2004),
P\"{o}tscher (2004), de Jong and Whang (2005), Berkes and Horvath (2006), and
Christopeit (2009) which study weak convergence results for such expressions
under various conditions on $x_{t}$ and the function $f$. Of course, these
results also provide information on the order of magnitude of $%
\sum_{t=1}^{n}f(r_{n}x_{t})$. However, to the best of our knowledge no result
is available for the case where $f$ is non-integrable with respect to
Lebesgue-measure in a neighborhood of a given point, say $x=0$. In this paper
we are interested in bounds on the order of magnitude of $%
\sum_{t=1}^{n}|x_{t}| ^{-\alpha}$ when $\alpha \geq 1$, a case where the
implied function $f$ is not integrable in any neighborhood of zero. More
generally, we shall also obtain bounds on the order of magnitude for
$\sum_{t=1}^{n}v_{t}|x_{t}| ^{-\alpha}$ where $v_{t}$ are random variables
satisfying certain conditions.


  In this note, we will compare the Garnier system in two variables with
four-dimensional partial differential system in two variables with
$W(D_6^{(1)})$-symmetry. Both systems are different in each compactification in
the variables $q_1,q_2$, however, has same five holomorphy conditions in the
variables $p_1,p_2$.


  In the present paper we investigate generalizations of O'Hara's M\"obius
energy on curves \cite{ohara_1991a}, to M\"obius-invariant energies on
non-smooth subsets of $\R^n$ of arbitrary dimension and co-dimension. In
particular, we show under mild assumptions on the local flatness of an
admissible possibly unbounded set $\Sigma\subset \R^n$ that locally finite
energy implies that $\Sigma$ is, in fact, an embedded Lipschitz submanifold of
$\R^n$ -- sometimes even smoother (depending on the a priorily given additional
regularity of the admissible set). We also prove, on the other hand, that a
local graph structure of low fractional Sobolev regularity on a set $\Sigma$ is
already sufficient to guarantee finite energy of $\Sigma$. This type of Sobolev
regularity is exactly what one would expect in view of Blatt's characterization
\cite{blatt_2012a} of the correct energy space for the M\"obius energy on
closed curves. Our results hold in particular for Kusner and Sullivan's cosine
energy $E_\textnormal{KS}$ \cite{kusner-sullivan_1997} since one of the
energies considered here is equivalent to $E_\textnormal{KS}$.


  An orthogonal time sequency multiplexing (OTSM) scheme using practical
signaling functions is proposed under strong phase noise (PHN) scenarios. By
utilizing the transform relationships between the delay-sequency (DS),
time-frequency (TF) and time-domains, we first conceive the DS-domain
input-output relationship of our OTSM system, where the conventional
zero-padding is discarded to increase the spectral efficiency. Then, the
unconditional pairwise error probability is derived, followed by deriving the
bit error ratio (BER) upper bound in closed-form. Moreover, we compare the BER
performance of our OTSM system based on several practical signaling functions.
Our simulation results demonstrate that the upper bound derived accurately
predicts the BER performance in the case of moderate to high signal-to-noise
ratios (SNRs), while harnessing practical window functions is capable of
attaining an attractive out-of-band emission (OOBE) vs. BER trade-off.


  Myoglobin modulates the binding of diatomic molecules to its heme group via
hydrogen-bonding and steric interactions with neighboring residues, and is an
important benchmark for computational studies of biomolecules. We have
performed calculations on the heme binding site and a significant proportion of
the protein environment (more than 1000 atoms) using linear-scaling density
functional theory and the DFT+U method to correct for self-interaction errors
associated with localized 3d states. We confirm both the hydrogen-bonding
nature of the discrimination effect (3.6 kcal/mol) and assumptions that the
relative strain energy stored in the protein is low (less than 1 kcal/mol). Our
calculations significantly widen the scope for tackling problems in drug design
and enzymology, especially in cases where electron localization, allostery or
long-ranged polarization influence ligand binding and reaction.


  Computer experiments that mirror the evolutionary dynamics of sexual and
asexual organisms as they occur in nature, tested features proposed to explain
the evolution of sexual recombination. Results show that this evolution is
better described as a network of interactions between possible sexual forms,
including diploidy, thelytoky, facultative sex, assortation, bisexuality, and
division of labor between the sexes, rather than a simple transition from
parthenogenesis to sexual recombination. Diploidy was shown to be fundamental
for the evolution of sex; bisexual reproduction emerged only among anisogamic
diploids with a synergistic division of reproductive labor; and facultative sex
was more likely to evolve among haploids practicing assortative mating. Looking
at the evolution of sex as a complex system through individual based
simulations, explains better the diversity of sexual strategies known to exist
in nature, compared to classical analytical models


  Let $Sh_K(G,\mu)$ be a Shimura variety of KHT type, as introduced in
Harris-Taylor book, associated to some similitude group $G/\mathbb Q$ and a
open compact subgroup $K$ of $G(\mathbb A)$. For any irreducible algebraic
$\overline{\mathbb Q}_l$-representation $\xi$ of $G$, let $V_\xi$ be the
$\mathbb Z_l$-local system on $Sh_K(G,\mu)$. From my paper about
p-stabilization, we know that if we allow the local component $K_l$ of $K$ to
be small enough, then there must exists some non trivial cohomology classes
with coefficient in $V_\xi$. The aim of this paper is then to construct
explicitly such torsion classes with the control of $K_l$. As an application we
obtain the construction of some new automorphic congruences between tempered
and non tempered automorphic representations of the same weight and same level
at $l$.


  We study the properties of the quantum states in the one-dimensional system
with a shifted periodic potential in both the discrete model and the continuous
model. With open boundary conditions, the edge states appear in the energy gaps
which indicate non-trivial topological structures. The Chern numbers with
respect to the Bloch vector and the potential shift angle are computed. In the
limit of the continuous model, the Chern number of each band is exactly one. We
demonstrate the particle number pumped by the adiabatically shift of the
potential is directly related to the topological invariants.


  In this paper we reconsider the notion of an optimal effective Hamiltonian
for the semiclassical propagation of the Wigner distribution in phase space. An
explicit expression for the optimal effective Hamiltonian is obtained in the
short time limit by minimizing the Hilbert-Schmidt distance between the
semiclassical approximation and the real state of the system. The method is
illustrated for the quartic oscillator.


  We present Twitmo, a package that provides a broad range of methods to
collect, pre-process, analyze and visualize geo-tagged Twitter data. Twitmo
enables the user to collect geo-tagged Tweets from Twitter and and provides a
comprehensive and user-friendly toolbox to generate topic distributions from
Latent Dirichlet Allocations (LDA), correlated topic models (CTM) and
structural topic models (STM). Functions are included for pre-processing of
text, model building and prediction. In addition, one of the innovations of the
package is the automatic pooling of Tweets into longer pseudo-documents using
hashtags and cosine similarities for better topic coherence. The package
additionally comes with functionality to visualize collected data sets and
fitted models in static as well as interactive ways and offers built-in support
for model visualizations via LDAvis providing great convenience for researchers
in this area. The Twitmo package is an innovative toolbox that can be used to
analyze public discourse of various topics, political parties or persons of
interest in space and time.


  Studies in robot teleoperation have been centered around action
specifications -- from continuous joint control to discrete end-effector pose
control. However, these robot-centric interfaces often require skilled
operators with extensive robotics expertise. To make teleoperation accessible
to non-expert users, we propose the framework "Scene Editing as Teleoperation"
(SEaT), where the key idea is to transform the traditional "robot-centric"
interface into a "scene-centric" interface -- instead of controlling the robot,
users focus on specifying the task's goal by manipulating digital twins of the
real-world objects. As a result, a user can perform teleoperation without any
expert knowledge of the robot hardware. To achieve this goal, we utilize a
category-agnostic scene-completion algorithm that translates the real-world
workspace (with unknown objects) into a manipulable virtual scene
representation and an action-snapping algorithm that refines the user input
before generating the robot's action plan. To train the algorithms, we
procedurally generated a large-scale, diverse kit-assembly dataset that
contains object-kit pairs that mimic real-world object-kitting tasks. Our
experiments in simulation and on a real-world system demonstrate that our
framework improves both the efficiency and success rate for 6DoF kit-assembly
tasks. A user study demonstrates that SEaT framework participants achieve a
higher task success rate and report a lower subjective workload compared to an
alternative robot-centric interface. Video can be found at
https://www.youtube.com/watch?v=-NdR3mkPbQQ .


  This paper aims to introduce a new statistical learning technique based on
sparsity promoting for data-driven modeling and control of solar photovoltaic
(PV) systems. Compared with conventional sparse regression techniques that
might introduce computational complexities when the number of candidate
functions increases, an innovative algorithm, named adaptive regulated sparse
regression (ARSR) is proposed that adaptively regulates the hyperparameter
weights of candidate functions to best represent the dynamics of PV systems.
Utilizing this algorithm, open-loop and closed-loop models of single-stage and
two-stage PV systems are obtained from measurements and are utilized for
control design purposes. Moreover, it is demonstrated that the proposed
data-driven approach can successfully be employed for fault analysis studies,
which distinguishes its capabilities compared with other data-driven
techniques. Finally, the proposed approach is validated through real-time
simulations.


  Many early order flow auction designs handle the payment for orders when they
execute on the chain rather than when they are won in the auction. Payments in
these auctions only take place when the orders are executed, creating a free
option for whoever wins the order. Bids in these auctions set the strike price
of this option rather than the option premium. This paper develops a simple
model of an order flow auction and compares contingent fees with upfront
payments as well as mixtures of the two. Results suggest that auctions with a
greater share of the payment contingent on execution have lower execution
probability, lower revenue, and increased effective spreads in equilibrium. A
Reputation system can act as a negative contingent fee, partially mitigating
the downsides; however, unless the system is calibrated perfectly, some of the
undesirable qualities of the contingent fees remain. Results suggest that
designers of order flow auctions should avoid contingent fees whenever
possible.


  The possible existence of stable black holes with entropies larger than the
corresponding Schwarzschild black hole has been discussed extensively. The
recently proposed "rough" black holes provide a concrete example of this. The
fear is that, in accordance with the Second Law of thermodynamics, the familiar
smooth-skinned black holes might spontaneously "wrinklify" into such an object.
We show that this fear is to some extent justified, in the sense that AdS black
holes with more entropy than the AdS-Schwarzschild black hole of the same mass
do exist.


  We theoretically investigate the possibility of lasing in an electromagnetic
resonator coupled to a voltage-biased hybrid double quantum dot comprised of a
double quantum dot tunnel coupled simultaneously to a normal metal and a
superconducting lead. Using a unitary transformation, we derive a
resonator-double quantum dot interaction Hamiltonian in the rotating-wave
approximation which reveals the fact that lasing in this system is mediated by
electron transitions between Andreev energy levels in the system's density of
states. Moreover, by employing a Markovian master equation incorporating
dissipation effects for the electronic and photonic degrees of freedom, we
numerically calculate the steady-state reduced density matrix of the system
from which we determine the average photon number and its statistics in the
resonator in various parameter regimes. We find that at some appropriate
parameter configurations, lasing can be considerably enhanced due to the
possibility of electron transitions between multiple Andreev levels in the
system.


  Given an integer $b\geqslant 2$ and a set $P$ of prime numbers, the set $T_P
$ of Toeplitz numbers comprises all elements of $[0,b[$ whose digits
$(a_n)_{n\geqslant 1}$ in the base-$b$ expansion satisfy $a_n=a_{pn}$ for all
$p\in P$ and $n\geqslant 1$. Using a completely additive arithmetical function,
we construct a number in~$T_P$ that is simply Borel normal if, and only if,
$\sum_{p\not \in P} 1/p=\infty$. We then provide an effective bound for the
discrepancy.


  Many complex phenomena occurring in physics,chemistry, biology, finance, etc.
can be reduced, by some projection process, to a 1-d stochastic Differential
Equation (SDE) for the variable of interest. Typically, this SDE is both
non-linear and non-markovian, so a Fokker Planck equation (FPE), for the
probability density function (PDF), is generally not obtainable. However, a FPE
is desirable because it is the main tool to obtain relevant analytical
statistical information such as stationary PDF and First Passage Time. This
problem has been addressed by many authors in the past, but due to an incorrect
use of the interaction picture (the standard tool to obtain a reduced FPE)
previous theoretical results were incorrect, as confirmed by direct numerical
simulation of the SDE. We will show, in general, how to address the problem and
we will derived the correct best FPE from a perturbation approach. The method
followed and the results obtained have a general validity beyond the simple
case of exponentially correlated Gaussian driving used here as an example; they
can be applied even to non Gaussian drivings with a generic time correlation.


  We perform an investigation of the MSSM parameter space at the Fermi scale
taking into account available accelerator, non-accelerator and cosmological
constraints. Extra assumptions about upper bounds for some of the SUSY
particles are also imposed. We show that a non-observation of the SUSY dark
matter candidates with a high-accuracy dark matter detector, such as Ge-73,
under above-mentioned assumptions can exclude large domains of the MSSM
parameter space and, for instance, can make especially desirable collider
search for light SUSY charged Higgs boson.


  Consider the binomial model $G^{d+1}(n,p)$ of the random $(d+1)$-uniform
hypergraph on $n$ vertices, where each edge is present, independently of one
another, with probability $p:\mathbb{N}\to[0,1]$. We prove that, for all
logarithmo-exponential $p\ll n^{-d+\epsilon}$, the probabilities of all
elementary properties of hypergraphs converge, with particular emphasis in the
ranges $p(n)\sim C/n^d$ and $p(n) \sim C\log(n)/n^d$. The exposition is unified
by constructing, for each such function $p$, the topological space of all
completions of its almost sure theory. This space turns out to be compact,
metrizable and totally disconnected, but further properties depend on the range
of $p$. The convergence of the probabilities of elementary properties is
associated with a borelian probability measure on the space.


  This work introduces a computational framework for applying absolute
electrical impedance tomography to head imaging without accurate information on
the head shape or the electrode positions. A library of fifty heads is employed
to build a principal component model for the typical variations in the shape of
the human head, which leads to a relatively accurate parametrization for head
shapes with only a few free parameters. The estimation of these shape
parameters and the electrode positions is incorporated in a regularized
Newton-type output least squares reconstruction algorithm. The presented
numerical experiments demonstrate that strong enough variations in the internal
conductivity of a human head can be detected by absolute electrical impedance
tomography even if the geometric information on the measurement configuration
is incomplete to an extent that is to be expected in practice.


  The projective space of order $n$ over a finite field $\F_q$ is a set of all
subspaces of the vector space $\F_q^{n}$. In this work, we consider
error-correcting codes in the projective space, focusing mainly on constant
dimension codes. We start with the different representations of subspaces in
the projective space. These representations involve matrices in reduced row
echelon form, associated binary vectors, and Ferrers diagrams. Based on these
representations, we provide a new formula for the computation of the distance
between any two subspaces in the projective space. We examine lifted maximum
rank distance (MRD) codes, which are nearly optimal constant dimension codes.
We prove that a lifted MRD code can be represented in such a way that it forms
a block design known as a transversal design. The incidence matrix of the
transversal design derived from a lifted MRD code can be viewed as a
parity-check matrix of a linear code in the Hamming space. We find the
properties of these codes which can be viewed also as LDPC codes. We present
new bounds and constructions for constant dimension codes. First, we present a
multilevel construction for constant dimension codes, which can be viewed as a
generalization of a lifted MRD codes construction. This construction is based
on a new type of rank-metric codes, called Ferrers diagram rank-metric codes.
Then we derive upper bounds on the size of constant dimension codes which
contain the lifted MRD code, and provide a construction for two families of
codes, that attain these upper bounds. We generalize the well-known concept of
a punctured code for a code in the projective space to obtain large codes which
are not constant dimension. We present efficient enumerative encoding and
decoding techniques for the Grassmannian. Finally we describe a search method
for constant dimension lexicodes.


  Small systems in a thermodynamic medium --- like colloids in a suspension or
the molecular machinery in living cells --- are strongly affected by the
thermal fluctuations of their environment. Physicists model such systems by
means of stochastic processes. Stochastic Thermodynamics (ST) defines entropy
changes and other thermodynamic notions for individual realizations of such
processes. It applies to situations far from equilibrium and provides a unified
approach to stochastic fluctuation relations. Its predictions have been studied
and verified experimentally.
  This thesis addresses the theoretical foundations of ST. Its focus is on the
following two aspects: (i) The stochastic nature of mesoscopic observations has
its origin in the molecular chaos on the microscopic level. Can one derive ST
from an underlying reversible deterministic dynamics? Can we interpret ST's
notions of entropy and entropy changes in a well-defined
information-theoretical framework? (ii) Markovian jump processes on finite
state spaces are common models for bio-chemical pathways. How does one quantify
and calculate fluctuations of physical observables in such models? What role
does the topology of the network of states play? How can we apply our abstract
results to the design of models for molecular motors?
  The thesis concludes with an outlook on dissipation as information written to
unobserved degrees of freedom --- a perspective that yields a consistency
criterion between dynamical models formulated on various levels of description.


  The quantum phase effects for induced electric and magnetic dipole moments
are investigated. It is shown that the phase shift received by induced electric
dipole has the same form with the one induced by magnetic dipole moment,
therefore the total phase is a hybrid of these two types of phase. This feature
indicates that in order to have a decisive measurement on either one of these
two phases, it is necessary to measure the velocity dependence of the observed
phase.


  Due to lowest possible quantum fluctuation, shear viscosity to entropy
density ratio never reach to zero, rather has some lower bound (0.08 approx).
Here, we have attempted to link our calculation, based on relaxation time
approximation for massless relativistic fluid, with that value and
interestingly found a lower and also an upper limit of relaxation time.


  Prediction algorithms that quantify the expected benefit of a given treatment
conditional on patient characteristics can critically inform medical decisions.
Quantifying the performance of treatment benefit prediction algorithms is an
active area of research. A recently proposed metric, the concordance statistic
for benefit (cfb), evaluates the discriminative ability of a treatment benefit
predictor by directly extending the concept of the concordance statistic from a
risk model with a binary outcome to a model for treatment benefit. In this
work, we scrutinize $cfb$ on multiple fronts. Through numerical examples and
theoretical developments, we show that cfb is not a proper scoring rule. We
also show that it is sensitive to the unestimable correlation between
counterfactual outcomes and to the definition of matched pairs. We argue that
measures of statistical dispersion applied to predicted benefits do not suffer
from these issues and can be an alternative metric for the discriminatory
performance of treatment benefit predictors.


  Two reverse inequalities for Young's inequality were shown by M. Tominaga,
using Specht ratio.
  In this short paper, we show alternative reverse inequalities for Young's
inequality without using Specht ratio.


  We investigate a calculation method for solving the Mukhanov-Sasaki equation
in slow-roll $k$-inflation based on the uniform approximation (UA) in
conjunction with an expansion scheme for slow-roll parameters with respect to
the number of $e$-folds about the so-called \textit{turning point}. Earlier
works on this method has so far gained some promising results derived from the
approximating expressions for the power spectra among others, up to second
order with respect to the Hubble and sound flow parameters, when compared to
other semi-analytical approaches (e.g., Green's function and WKB methods).
However, a closer inspection is suggestive that there is a problem when
higher-order parts of the power spectra are considered; residual logarithmic
divergences may come out that can render the prediction physically
inconsistent. Looking at this possibility, we map out up to what order with
respect to the mentioned parameters several physical quantities can be
calculated before hitting a logarithmically divergent result. It turns out that
the power spectra are limited up to second order, the tensor-to-scalar ratio up
to third order, and the spectral indices and running converge to all orders.
This indicates that the expansion scheme is incompatible with the working
equations derived from UA for the power spectra but compatible with that of the
spectral indices. For those quantities that involve logarithmically divergent
terms in the higher-order parts, existing results in the literature for the
convergent lower-order parts calculated in the equivalent fashion should be
viewed with some caution; they do not rest on solid mathematical ground.


  The Cherenkov Telescope Array (CTA) project aims to build the largest
ground-based gamma-ray observatory based on an array of Imaging Atmospheric
Cherenkov Telescopes (IACTs). The CTA will implement a multi-level trigger
system to distinguish between gamma ray-like induced showers and background
images induced by night sky background (NSB) light. The trigger system is based
on coincident detections among pixels (level 0 trigger), clusters of pixels
(level 1) or telescopes. In this article, the first version of the application
specific integrated circuit (ASIC) for Level 1 trigger system is presented,
capable of working with different Level 0 strategies and different trigger
region sizes. In addition, it complies with all the requirements specified by
the CTA project, specially the most critical ones as regards noise, bandwidth,
dynamic range and power consumption. All these features make the presented
system very suitable for use in the CTA cameras and improve the features of
discrete components prototypes of the L1 trigger circuit in terms of
compactness, noise, performance and power consumption.


  We obtain analytic formulas for the frequency-dependent spin-Hall
conductivity of a two-dimensional electron gas (2DEG) in the presence of
impurities, linear spin-orbit Rashba interaction, and external magnetic field
perpendicular to the 2DEG. We show how different mechanisms (skew-scattering,
side-jump, and spin precession) can be brought in or out of focus by changing
controllable parameters such as frequency, magnetic field, and temperature. We
find, in particular, that the d.c. spin Hall conductivity vanishes in the
absence of a magnetic field, while a magnetic field restores the
skew-scattering and side-jump contributions proportionally to the ratio of
magnetic and Rashba fields.


  Stellar obliquity, the angle between a planet's orbital axis and its host
star's spin axis, traces the formation and evolution of a planetary system. In
transiting exoplanet observations, only the sky-projected stellar obliquity can
be measured, but this can be de-projected using an estimate of the stellar
obliquity. In this paper, we introduce a flexible, hierarchical Bayesian
framework that can be used to infer the stellar obliquity distribution solely
from sky-projected stellar obliquities, including stellar inclination
measurements when available. We demonstrate that while a constraint on the
stellar inclination is crucial for measuring the obliquity of an individual
system, it is not required for robust determination of the population-level
stellar obliquity distribution. In practice, the constraints on the stellar
obliquity distribution are mainly driven by the sky-projected stellar
obliquities.
  When applying the framework to all systems with measured sky-projected
stellar obliquity, which are mostly Hot Jupiter systems, we find that the
inferred population-level obliquity distribution is unimodal and peaked at zero
degrees. The misaligned systems have nearly isotropic stellar obliquities with
no strong clustering near 90 degrees. The diverse range of stellar obliquities
prefers dynamic mechanisms, such as planet-planet scattering after a convergent
disk migration, which could produce both prograde and retrograde orbits of
close-in planets with no strong inclination concentrations other than 0
degrees.


  We study the chiral phase transition within the Linear Sigma Model with
quarks from its thermodynamical potential considering quantum corrections up to
ring diagrams in the high-temperature regime. Demanding a second order phase
transition as expected in the chiral limit at low baryon chemical potential,
that the curvature of the critical line matches the one obtained in lattice
simulations and that the value of the speed of sound at high temperature and
zero density has its measured value, we constrain the couplings and other free
parameters of the model. We set restrictions to locate the position of the
Critical End Point in the phase diagram from a fast drop-off of the critical
line reminiscent from the behavior of the speed of sound near criticality. Our
results set tight constrains in parameter space for the model to exhibit
realistic features.


  The paper addresses the homogenization of a family of micro-models for the
flow of a slightly compressible fluid in a poroelastic matrix containing
periodically distibuted poroelastic inclusions, with low permeabilities and
with imperfect contact on the interface. The micro-models are based on Biot's
system for consolidation processes in each phase, with interfacial barrier
formulation. Using the two-scale convergence technique, it is shown that the
derived system is a general model of that proposed by Aifantis, plus an extra
memory term.


  The notion of the Jacob's ladders, reversely iterated integrals and the
$\zeta$-factorization is used in this paper in order to obtain new results in
study of the function $\arg\zf$. Namely, we obtain new formulae for non-local
and non-linear interaction of the functions $|\zf|$ and $\arg\zf$, and also a
set of metamorphoses of the oscillating Q-system.


  We propose two dimensional x-ray coherent correlation spectroscopy (2DXCS)
for the study of interactions between core-electron and valence transitions.
This technique might find experimental applications in the future when very
high intensity x-ray sources become available. Spectra obtained by varying two
delay periods between pulses show off-diagonal cross-peaks induced by coupling
of core transitions of two different types. Calculations of the N1s and O1s
signals of aminophenol isomers illustrate how novel information about many-body
effects in electronic structure and excitations of molecules can be extracted
from these spectra.


  We investigate the limitations of statistical absorption measurements with
the SDSS optical spectroscopic surveys. We show that changes in the data
reduction strategy throughout different data releases have led to a better
accuracy at long wavelengths, in particular for sky line subtraction, but a
degradation at short wavelengths with the emergence of systematic spectral
features with an amplitude of about one percent. We show that these features
originate from inaccuracy in the fitting of modeled F-star spectra used for
flux calibration. The best-fit models for those stars are found to
systematically over-estimate the strength of metal lines and under-estimate
that of Lithium. We also identify the existence of artifacts due to masking and
interpolation procedures at the wavelengths of the hydrogen Balmer series
leading to the existence of artificial Balmer $\alpha$ absorption in all SDSS
optical spectra. All these effects occur in the rest-frame of the standard
stars and therefore present Galactic longitude variations due to the rotation
of the Galaxy. We demonstrate that the detection of certain weak absorption
lines reported in the literature are solely due to calibration effects.
Finally, we discuss new strategies to mitigate these issues.


  The scientific impact of current and upcoming photometric galaxy surveys is
contingent on our ability to obtain redshift estimates for large numbers of
faint galaxies. In the absence of spectroscopically confirmed redshifts,
broad-band photometric redshift point estimates (photo-$z$s) have been
superseded by photo-$z$ probability density functions (PDFs) that encapsulate
their nontrivial uncertainties. Initial applications of photo-$z$ PDFs in weak
gravitational lensing studies of cosmology have obtained the redshift
distribution function $\mathcal{N}(z)$ by employing computationally
straightforward stacking methodologies that violate the laws of probability. In
response, mathematically self-consistent models of varying complexity have been
proposed in an effort to answer the question, "What is the right way to obtain
the redshift distribution function $\mathcal{N}(z)$ from a catalog of photo-$z$
PDFs?" This letter aims to motivate adoption of such principled methods by
addressing the contrapositive of the more common presentation of such models,
answering the question, "Under what conditions do traditional stacking methods
successfully recover the true redshift distribution function $\mathcal{N}(z)$?"
By placing stacking in a rigorous mathematical environment, we identify two
such conditions: those of perfectly informative data and perfectly informative
prior information. Stacking has maintained its foothold in the astronomical
community for so long because the conditions in question were only weakly
violated in the past. These conditions, however, will be strongly violated by
future galaxy surveys. We therefore conclude that stacking must be abandoned in
favor of mathematically supported methods in order to advance observational
cosmology.


  Relaxation processes of dislocation systems are studied by two-dimensional
dynamical simulations. In order to capture generic features, three physically
different scenarios were studied and power-law decays found for various
physical quantities. Our main finding is that all these are the consequence of
the underlying scaling property of the dislocation velocity distribution.
Scaling is found to break down at some cut-off time increasing with system
size. The absence of intrinsic relaxation time indicates that criticality is
ubiquitous in all states studied. These features are reminiscent to glassy
systems, and can be attributed to the inherent quenched disorder in the
position of the slip planes.


  Isotopically resolved cross sections and velocity distributions have been
measured in charge-pickup reactions of 1 A GeV 208Pb with proton, deuterium and
titanium target. The total and partial charge-pickup cross sections in the
reactions 208Pb + 1H and 208Pb + 2H are measured to be the same in the limits
of the error bars. A weak increase in the total charge-pickup cross section is
seen in the reaction of 208Pb with the titanium target. The measured velocity
distributions show different contributions - quasi-elastic scattering and
Delta-resonance excitation - to the charge-pickup production. Data on total and
partial charge-pickup cross sections from these three reactions are compared
with other existing data and also with model calculations based on the coupling
of different intra-nuclear cascade codes and an evaporation code.


  In this paper, we study the performance of IPOP-saACM-ES, recently proposed
self-adaptive surrogate-assisted Covariance Matrix Adaptation Evolution
Strategy. The algorithm was tested using restarts till a total number of
function evaluations of $10^6D$ was reached, where $D$ is the dimension of the
function search space. The experiments show that the surrogate model control
allows IPOP-saACM-ES to be as robust as the original IPOP-aCMA-ES and
outperforms the latter by a factor from 2 to 3 on 6 benchmark problems with
moderate noise. On 15 out of 30 benchmark problems in dimension 20,
IPOP-saACM-ES exceeds the records observed during BBOB-2009 and BBOB-2010.


  In a delightful article that recently appeared in the American Mathematics
Monthly, Norbert Henze and Guenter Last discuss the "Absent-Minded Passengers"
Problem, but left open finding an explicit expression for the probability
generating function, of the random variable "Number of passengers occupying a
wrong seat", when the number of absent-minded passengers is larger than one.
This is accomplished in this note, using experimental mathematics and symbolic
computation. We also derive explicit expressions for the first 8 moments of the
original case of one absent-minded passenger, and indicate how to extend it to
the general case


  We present a hybrid algorithm for optimizing a convex, smooth function over
the cone of positive semidefinite matrices. Our algorithm converges to the
global optimal solution and can be used to solve general large-scale
semidefinite programs and hence can be readily applied to a variety of machine
learning problems. We show experimental results on three machine learning
problems (matrix completion, metric learning, and sparse PCA) . Our approach
outperforms state-of-the-art algorithms.


  We discuss features of the brane cosmological evolution that arise through
the presence of matter in the bulk. As these deviations from the conventional
evolution are not associated with some observable matter component on the
brane, we characterize them as mirage effects. We review an example of
expansion that can be attributed to mirage non-relativistic matter (mirage cold
dark matter) on the brane. The real source of the evolution is an anisotropic
bulk fluid with negative pressure along the extra dimension. We also study the
general problem of exchange of real non-relativistic matter between the brane
and the bulk, and discuss the related mirage effects. Finally, we derive the
brane cosmological evolution within a bulk that contains a global monopole
(hedgehog) configuration. This background induces a mirage curvature term in
the effective Friedmann equation, which can cause a brane Universe with
positive spatial curvature to expand forever.


  In this paper, we use tools from rate-distortion theory to establish new
upper bounds on the generalization error of statistical distributed learning
algorithms. Specifically, there are $K$ clients whose individually chosen
models are aggregated by a central server. The bounds depend on the
compressibility of each client's algorithm while keeping other clients'
algorithms un-compressed, and leverage the fact that small changes in each
local model change the aggregated model by a factor of only $1/K$. Adopting a
recently proposed approach by Sefidgaran et al., and extending it suitably to
the distributed setting, this enables smaller rate-distortion terms which are
shown to translate into tighter generalization bounds. The bounds are then
applied to the distributed support vector machines (SVM), suggesting that the
generalization error of the distributed setting decays faster than that of the
centralized one with a factor of $\mathcal{O}(\log(K)/\sqrt{K})$. This finding
is validated also experimentally. A similar conclusion is obtained for a
multiple-round federated learning setup where each client uses stochastic
gradient Langevin dynamics (SGLD).


  We study the periodic traveling wave solutions of the derivative nonlinear
Schr\"{o}dinger equation (DNLS). It is known that DNLS has two types of
solitons on the whole line; one has exponential decay and the other has
algebraic decay. The latter corresponds to the soliton for the massless case.
In the new global results recently obtained by Fukaya, Hayashi and Inui, the
properties of two-parameter of the solitons are essentially used in the proof,
and especially the soliton for the massless case plays an important role. To
investigate further properties of the solitons, we construct exact periodic
traveling wave solutions which yield the solitons on the whole line including
the massless case in the long-period limit. Moreover, we study the regularity
of the convergence of these exact solutions in the long-period limit.
Throughout the paper, the theory of elliptic functions and elliptic integrals
is used in the calculation.


  The extraction of detailed nuclear structure information from transfer
reactions requires reliable, well-normalized data as well as optical potentials
and a theoretical framework demonstrated to work well in the relevant mass and
beam energy ranges. It is rare that the theoretical ingredients can be tested
well for exotic nuclei owing to the paucity of data. The halo nucleus Be-11 has
been examined through the 10Be(d,p) reaction in inverse kinematics at
equivalent deuteron energies of 12,15,18, and 21.4 MeV. Elastic scattering of
Be-10 on protons was used to select optical potentials for the analysis of the
transfer data. Additionally, data from the elastic and inelastic scattering of
Be-10 on deuterons was used to fit optical potentials at the four measured
energies. Transfers to the two bound states and the first resonance in Be-11
were analyzed using the Finite Range ADiabatic Wave Approximation (FR-ADWA).
Consistent values of the spectroscopic factor of both the ground and first
excited states were extracted from the four measurements, with average values
of 0.71(5) and 0.62(4) respectively. The calculations for transfer to the first
resonance were found to be sensitive to the size of the energy bin used and
therefore could not be used to extract a spectroscopic factor.


  High-precision mass measurements of more than thirty neutron-rich nuclides
around the Z=28 closed proton shell were performed with the triple-trap mass
spectrometer ISOLTRAP at ISOLDE/CERN to address the question of a possible
neutron shell closure at N=40. The results, for 57,60,64-69Ni (Z=28),
65-74,76Cu (Z=29), and 63-65,68-78Ga (Z=31), have a relative uncertainty of the
order of 10^8. In particular, the masses of 72-74,76Cu have been measured for
the first time. We analyse the resulting mass surface for signs of magicity,
comparing the behavior of N=40 to that of known magic numbers and to mid-shell
behavior. Contrary to nuclear spectroscopy studies, no indications of a shell
or sub-shell closure are found for N=40.


  In this note, a brief review of the consistent state approach to systems
containing closed timelike curves or similar devices is given, and applied to
the well known thermodynamic problem of Maxwell's demon. The 'third party
paradox' for acausal systems is defined and applied to CTC censorship and black
hole evaporation. Some traditional arguments for chronology protection are
re-examined.


  We address the inverse problem of cosmic large-scale structure reconstruction
from a Bayesian perspective. For a linear data model, a number of known and
novel reconstruction schemes, which differ in terms of the underlying signal
prior, data likelihood, and numerical inverse extra-regularization schemes are
derived and classified. The Bayesian methodology presented in this paper tries
to unify and extend the following methods: Wiener-filtering, Tikhonov
regularization, Ridge regression, Maximum Entropy, and inverse regularization
techniques. The inverse techniques considered here are the asymptotic
regularization, the Jacobi, Steepest Descent, Newton-Raphson,
Landweber-Fridman, and both linear and non-linear Krylov methods based on
Fletcher-Reeves, Polak-Ribiere, and Hestenes-Stiefel Conjugate Gradients. The
structures of the up-to-date highest-performing algorithms are presented, based
on an operator scheme, which permits one to exploit the power of fast Fourier
transforms. Using such an implementation of the generalized Wiener-filter in
the novel ARGO-software package, the different numerical schemes are
benchmarked with 1-, 2-, and 3-dimensional problems including structured white
and Poissonian noise, data windowing and blurring effects. A novel numerical
Krylov scheme is shown to be superior in terms of performance and fidelity.
These fast inverse methods ultimately will enable the application of sampling
techniques to explore complex joint posterior distributions. We outline how the
space of the dark-matter density field, the peculiar velocity field, and the
power spectrum can jointly be investigated by a Gibbs-sampling process. Such a
method can be applied for the redshift distortions correction of the observed
galaxies and for time-reversal reconstructions of the initial density field.


  Recent empirical work on stochastic gradient descent (SGD) applied to
over-parameterized deep learning has shown that most gradient components over
epochs are quite small. Inspired by such observations, we rigorously study
properties of Truncated SGD (T-SGD), that truncates the majority of small
gradient components to zeros. Considering non-convex optimization problems, we
show that the convergence rate of T-SGD matches the order of vanilla SGD. We
also establish the generalization error bound for T-SGD. Further, we propose
Noisy Truncated SGD (NT-SGD), which adds Gaussian noise to the truncated
gradients. We prove that NT-SGD has the same convergence rate as T-SGD for
non-convex optimization problems. We demonstrate that with the help of noise,
NT-SGD can provably escape from saddle points and requires less noise compared
to previous related work. We also prove that NT-SGD achieves better
generalization error bound compared to T-SGD because of the noise. Our
generalization analysis is based on uniform stability and we show that
additional noise in the gradient update can boost the stability. Our
experiments on a variety of benchmark datasets (MNIST, Fashion-MNIST, CIFAR-10,
and CIFAR-100) with various networks (VGG and ResNet) validate the theoretical
properties of NT-SGD, i.e., NT-SGD matches the speed and accuracy of vanilla
SGD while effectively working with sparse gradients, and can successfully
escape poor local minima.


  With the rapid growth of handheld devices in the internet of things (IoT)
networks, mobile applications have become ubiquitous in everyday life. As
technology is developed, so do also the risks and threats associated with it,
especially in the forthcoming quantum era. Existing IoT networks, however, lack
a quantum-resistant secret key sharing scheme to meet confidential message
transmission demands in wide-area mobile applications. To address this issue,
this article proposes a new scheme, channel reciprocity (CR) based quantum key
distribution (QKD) CR-QKD, which accomplishes the goal of secret key sharing by
combining emerging techniques of QKD and CR-based key generation (CRKG).
Exploiting laws of quantum physics and properties of wireless channels, the
proposed scheme is able to ensure the secrecy of the key, even against
computationally unbounded adversaries. The basic mechanism is elaborated for a
single-user case and it is extended into a multi-user case by redesigning a
multi-user edge forwarding strategy. In addition, to make CR-QKD more
practical, some enhancement strategies are studied to reduce the time delay and
to improve the secret key generation rate in a secure manner. A prototype of
CR-QKD is demonstrated in a metropolitan area network, where secret keys are
shared between two remote IoT devices that are roughly fifteen kilometers apart
from each other. The experimental results have verified that CR-QKD allows a
secret key rate of 424 bits per second with a retransmission rate of 2.1%.


  In this paper we analyse the behaviour of a pile-up of vertically periodic
walls of edge dislocations at an obstacle, represented by a locked dislocation
wall. Starting from a continuum non-local energy $E_\gamma$ modelling the
interactions$-$at a typical length-scale of $1/\gamma$$-$of the walls subjected
to a constant shear stress, we derive a first-order approximation of the energy
$E_\gamma$ in powers of $1/\gamma$ by $\Gamma$-convergence, in the limit
$\gamma\to\infty$. While the zero-order term in the expansion, the
$\Gamma$-limit of $E_\gamma$, captures the `bulk' profile of the density of
dislocation walls in the pile-up domain, the first-order term in the expansion
is a `boundary-layer' energy that captures the profile of the density in the
proximity of the lock.
  This study is a first step towards a rigorous understanding of the behaviour
of dislocations at obstacles, defects, and grain boundaries.


  Mathematical learning environments help students in mastering mathematical
knowledge. Mature environments typically offer thousands of interactive
exercises. Providing feedback to students solving interactive exercises
requires domain reasoners for doing the exercise-specific calculations. Since a
domain reasoner has to solve an exercise in the same way a student should solve
it, the structure of domain reasoners should follow the layered structure of
the mathematical domains. Furthermore, learners, teachers, and environment
builders have different requirements for adapting domain reasoners, such as
providing more details, disallowing or enforcing certain solutions, and
combining multiple mathematical domains in a new domain. In previous work we
have shown how domain reasoners for solving interactive exercises can be
expressed in terms of rewrite strategies, rewrite rules, and views. This paper
shows how users can adapt and configure such domain reasoners to their own
needs. This is achieved by enabling users to explicitly communicate the
components that are used for solving an exercise.


  Disordered materials are attracting considerable attention because of their
enhanced properties compared to their ordered analogs, making them particularly
suitable for high-temperature applications. The feasibility of incorporating
these materials into new devices depends on a variety of thermophysical
properties. Among them, thermal expansion is critical to device stability,
especially in multi-component systems. Its calculation, however, is quite
challenging for materials with substitutional disorder, hindering computational
screenings. In this work, we introduce QH-POCC to leverage the local
tile-expansion of disorder. This method provides an effective partial partition
function to calculate thermomechanical properties of substitutionally
disordered compounds in the quasi-harmonic approximation. Two systems, AuCu3
and CdMg3, the latter a candidate for long-period superstructures at low
temperature, are used to validate the methodology by comparing the calculated
values of the coefficient of thermal expansion and isobaric heat capacity with
experiment, demonstrating that QH-POCC is a promising approach to study
thermomechanical properties of disordered systems.


  This work is motivated by the classical discrete elastic rod model by Audoly
et al. We derive a discrete version of the Kirchhoff elastic energy for rods
undergoing bending and torsion and prove $\Gamma$-convergence to the continuous
model. This discrete energy is given by the bending and torsion energy of an
interpolating conforming polynomial curve and provides a simple formula for the
bending energy depending in each discrete segment only on angle and adjacent
edge lengths. For the $\liminf$-inequality, we need to introduce penalty terms
to ensure arc-length parametrization in the limit. For the recovery sequence a
discretization with equal Euclidean distance between consecutive points is
constructed. Particular care is taken to treat the interaction between bending
and torsion by employing a discrete version of the Bishop frame.


  The precision enhancement is demonstrated in an optical spatial measurement
based on weak value amplification (WVA) system and split-like detection, by
injecting a TEM10 squeezed vacuum beam. It is the first time combining the WVA
technique and squeezed beam injection to experimentally realize high-precision
optical spatial measurement beyond the standard quantum limit. As a result, the
precision enhancement of 1.3 times can be achieved at 500kHz by adding a
squeezed beam in the vacuum input port of the Mach-Zehnder interferometer. The
minimum measurable displacement is reduced from 1.08pm to 0.85pm and the
corresponding minimum measurable tilt is reduced from 0.86prad to 0.67prad.
Moreover, the spatial measurement at low-frequency band is also implemented and
the SNR is improved 2dB at 4kHz. Our work provides an effective method to
accomplish higher precision in optical spatial measurement, which has potential
applications in gravitational wave interferometer calibration, super-resolution
quantum imaging, etc.


  Network programmability will be required to handle future increased network
traffic and constantly changing application needs. However, there is currently
no way of using a high-level, easy to use programming language to program Wi-Fi
firmware. This impedes rapid prototyping and deployment of novel network
services/applications and hinders continuous performance optimization in Wi-Fi
networks, since expert knowledge is required for both the used hardware
platforms and the Wi-Fi domain. In this paper, we present ReactiFi, a
high-level reactive programming language to program Wi-Fi chips on mobile
consumer devices. ReactiFi enables programmers to implement extensions of PHY,
MAC, and IP layer mechanisms without requiring expert knowledge of Wi-Fi chips,
allowing for novel applications and network protocols. ReactiFi programs are
executed directly on the Wi-Fi chip, improving performance and power
consumption compared to execution on the main CPU. ReactiFi is conceptually
similar to functional reactive languages, but is dedicated to the
domain-specific needs of Wi-Fi firmware. First, it handles low-level
platform-specific details without interfering with the core functionality of
Wi-Fi chips. Second, it supports static reasoning about memory usage of
applications, which is important for typically memory-constrained Wi-Fi chips.
Third, it limits dynamic changes of dependencies between computations to
dynamic branching, in order to enable static reasoning about the order of
computations. We evaluate ReactiFi empirically in two real-world case studies.
Our results show that throughput, latency, and power consumption are
significantly improved when executing applications on the Wi-Fi chip rather
than in the operating system kernel or in user space. Moreover, we show that
the high-level programming abstractions of ReactiFi have no performance
overhead compared to manually written C code.


  We establish a region of convergence for the proto-typical non-convex
Douglas-Rachford iteration which finds a point on the intersection of a line
and a circle. Previous work on the non-convex iteration [2] was only able to
establish local convergence, and was ineffective in that no explicit region of
convergence could be given.


  We study the impact of ultraviolet background (UVB) radiation field and the
local stellar radiation on the H_I column density distribution f(N_HI) of
damped Ly-alpha systems (DLAs) and sub-DLAs at z=3 using cosmological smoothed
particle hydrodynamics simulations. We find that, in the previous simulations
with an optically thin approximation, the UVB was sinking into the H_I cloud
too deeply, and therefore we underestimated the f(N_HI) at 19 < log(N_HI) <
21.2 compared to the observations. If the UVB is shut off in the high-density
regions with n_gas > 6 x 10^{-3} cm^{-3}, then we reproduce the observed
f(N_HI) at z=3 very well. We also investigate the effect of local stellar
radiation by post-processing our simulation with a radiative transfer code, and
find that the local stellar radiation does not change the f(N_HI) very much.
Our results show that the shape of f(N_HI) is determined primarily by the UVB
with a much weaker effect by the local stellar radiation and that the optically
thin approximation often used in cosmological simulation is inadequate to
properly treat the ionization structure of neutral gas in and out of DLAs. Our
result also indicates that the DLA gas is closely related to the transition
region from optically-thick neutral gas to optically-thin ionized gas within
dark matter halos.


  We report on the achievement of quantum degeneracy in both components of a
Bose-Fermi mixture of metastable helium atoms, $^4$He* and $^3$He*. Degeneracy
is achieved via Doppler cooling and forced evaporation for $^4$He*, and
sympathetically cooling $^3$He* with $^4$He*. We discuss our simplified
implementation, along with the high versatility of our system. This technique
is able to produce a degenerate Fermi gas with a minimum reduced temperature of
$T/T_F=0.14(1)$, consisting of $2.5 \times 10^4$ $^3$He* atoms. Due to the high
internal energy of both isotopes single atom detection is possible, opening the
possibility of a large number of experiments into Bose-Fermi mixtures.


  We report on R_c and K band observations of the optical counterpart to GRB
970508 with the Fred Lawrence Whipple Observatory (FLWO) 1.2m telescope. Eleven
R_c-band observations were obtained on 1997 May 12, and three on May14. The
counterpart clearly faded between the two nights. On May 12 there was no
evidence for variability (<9%) on 10-70 minute time scales based on 11 R_c-band
observations. On May 19 a one hour observation set a limit on the K magnitude
of K>18.2. Comparison of these data points with those obtained by other authors
shows that the decay of the optical counterpart can be well fitted by a power
law of the form f ~ t**-alpha where alpha = 1.22 +/- 0.03 with occasional
fluctuations superposed. We note that the decay of the optical counterpart to
another burst, GRB 970228, can also be well fitted with a power law with
exponent alpha = 1.0/+0.2/-0.5 with occasional fluctuations superposed. These
two decay light curves are remarkably similar in form to that predicted by
cosmic-fireball models.


  We calculate the shear viscosity $\eta$ of a quark plasma through the
two-flavor Nambu-Jona-Lasinio (NJL) model in the chiral limit, at finite
temperature $T$, and baryon number chemical potential $\mu_B$. We solve the
Boltzmann equation by using in the collision term cross sections that are
correct to leading order in the coupling constant. We find the ratio of shear
viscosity to entropy density above and slightly below the chiral transition
temperature to vary from 1.5 to 13 times the conjectured lower bound of
$(4\pi)^{-1}$ depending on the chemical potential to temperature ratio. Ratio
of shear viscosity to entropy density is found to be a monotonically increasing
function of the ratio of chemical potential to temperature for temperatures
between 185 and 300 MeV.


  This paper introduces a LArge-scale Video Interpolation Benchmark (LAVIB) for
the low-level video task of video frame interpolation (VFI). LAVIB comprises a
large collection of high-resolution videos sourced from the web through an
automated pipeline with minimal requirements for human verification. Metrics
are computed for each video's motion magnitudes, luminance conditions, frame
sharpness, and contrast. The collection of videos and the creation of
quantitative challenges based on these metrics are under-explored by current
low-level video task datasets. In total, LAVIB includes 283K clips from 17K
ultra-HD videos, covering 77.6 hours. Benchmark train, val, and test sets
maintain similar video metric distributions. Further splits are also created
for out-of-distribution (OOD) challenges, with train and test splits including
videos of dissimilar attributes.


  In recent years, reinforcement learning has achieved many remarkable
successes due to the growing adoption of deep learning techniques and the rapid
growth in computing power. Nevertheless, it is well-known that flat
reinforcement learning algorithms are often not able to learn well and
data-efficient in tasks having hierarchical structures, e.g. consisting of
multiple subtasks. Hierarchical reinforcement learning is a principled approach
that is able to tackle these challenging tasks. On the other hand, many
real-world tasks usually have only partial observability in which state
measurements are often imperfect and partially observable. The problems of RL
in such settings can be formulated as a partially observable Markov decision
process (POMDP). In this paper, we study hierarchical RL in POMDP in which the
tasks have only partial observability and possess hierarchical properties. We
propose a hierarchical deep reinforcement learning approach for learning in
hierarchical POMDP. The deep hierarchical RL algorithm is proposed to apply to
both MDP and POMDP learning. We evaluate the proposed algorithm on various
challenging hierarchical POMDP.


  We demonstrate cavity sideband cooling of a single collective motional mode
of an atomic ensemble down to a mean phonon occupation number of
2.0(-0.3/+0.9). Both this minimum occupation number and the observed cooling
rate are in good agreement with an optomechanical model. The cooling rate
constant is proportional to the total photon scattering rate by the ensemble,
demonstrating the cooperative character of the light-emission-induced cooling
process. We deduce fundamental limits to cavity-cooling either the collective
mode or, sympathetically, the single-atom degrees of freedom.


  We investigate the role of supermassive black holes in the global context of
galaxy evolution by measuring the host galaxy stellar mass function (HGMF) and
the specific accretion rate i.e., lambda_SAR, distribution function (SARDF) up
to z~2.5 with ~1000 X-ray selected AGN from XMM-COSMOS. Using a maximum
likelihood approach, we jointly fit the stellar mass function and specific
accretion rate distribution function, with the X-ray luminosity function as an
additional constraint. Our best fit model characterizes the SARDF as a double
power-law with mass dependent but redshift independent break whose low
lambda_SAR slope flattens with increasing redshift while the normalization
increases. This implies that, for a given stellar mass, higher lambda_SAR
objects have a peak in their space density at earlier epoch compared to the
lower lambda_SAR ones, following and mimicking the well known AGN cosmic
downsizing as observed in the AGN luminosity function. The mass function of
active galaxies is described by a Schechter function with a almost constant
Mstar* and a low mass slope alpha that flattens with redshift. Compared to the
stellar mass function, we find that the HGMF has a similar shape and that, up
to log((Mstar/Msun)~11.5 the ratio of AGN host galaxies to star forming
galaxies is basically constant (~10%). Finally, the comparison of the AGN HGMF
for different luminosity and specific accretion rate sub-classes with the
phenomenological model prediction by Peng et al. (2010) for the "transient"
population, i.e. galaxies in the process of being mass-quenched, reveals that
low-luminosity AGN do not appear to be able to contribute significantly to the
quenching and that at least at high masses, i.e. Mstar>10^(10.7) Msun ,
feedback from luminous AGN (log(Lbol)>~46 [erg/s]) may be responsible for the
quenching of star formation in the host galaxy.


  In the present talk diffraction in deep inelastic scattering is discussed in
the framework of the semiclassical approach. The main emphasis is on the
possibility of a consistent semiclassical description of both hard and soft
colour singlet exchange processes. This approach allows the comparison of hard
and soft colour neutralization in diffractive electroproduction of
high-$p_\perp$ jets or heavy quarks.


  The accessibility of both n-type and p-type MoS2 FET is necessary for
complementary device applications involving MoS2. However, MoS2 PFET is rarely
achieved due to pinning effect resulting high Rc at metal-MoS2 interface and
the inherently strong n-type property of the MoS2 material. In this study, we
realized a high-performance multi-layer MoS2 PFET via controllable chemical
doping, which has an excellent on/off ratio of 107 and a maximum hole mobility
of 72 cm2/Vs at room temperature, and these values are further exceeding to 109
and 132 cm2/Vs at 133K. In addition, we revealed that large Rc hindered the
polar transition of MoS2 FET from n-type to p-type, meanwhile channel Rs
limited Ion of PFET. Therefore it is suggested that reducing Rc at high work
function metal-MoS2 interface and p-type doping of channel were necessary for
achieving high performance MoS2 PFET. Based on the high performance PFET, we
successfully demonstrated a MoS2 CMOS inverter by integrating NFET and PFET.


  Statistical machine learning methods are increasingly used for neuroimaging
data analysis. Their main virtue is their ability to model high-dimensional
datasets, e.g. multivariate analysis of activation images or resting-state time
series. Supervised learning is typically used in decoding or encoding settings
to relate brain images to behavioral or clinical observations, while
unsupervised learning can uncover hidden structures in sets of images (e.g.
resting state functional MRI) or find sub-populations in large cohorts. By
considering different functional neuroimaging applications, we illustrate how
scikit-learn, a Python machine learning library, can be used to perform some
key analysis steps. Scikit-learn contains a very large set of statistical
learning algorithms, both supervised and unsupervised, and its application to
neuroimaging data provides a versatile tool to study the brain.


  We propose a numerical method to solve the Wigner equation in quantum systems
of spinless, non-relativistic particles. The method uses a spectral
decomposition into $L^2(\mathbb{R}^d)$ basis functions in momentum-space to
obtain a system of first-order advection-reaction equations. The resulting
equations are solved by splitting the reaction and advection steps so as to
allow the combination of numerical techniques from quantum mechanics and
computational fluid dynamics by identifying the skew-hermitian reaction matrix
as a generator of unitary rotations. The method is validated for the case of
particles subject to a one-dimensional (an-)harmonic potential using
finite-differences for the advection part. Thereby, we verify the second order
of convergence and observe non-classical behavior in the evolution of the
Wigner function.


  We introduce a novel sampler called the energy based diffusion generator for
generating samples from arbitrary target distributions. The sampling model
employs a structure similar to a variational autoencoder, utilizing a decoder
to transform latent variables from a simple distribution into random variables
approximating the target distribution, and we design an encoder based on the
diffusion model. Leveraging the powerful modeling capacity of the diffusion
model for complex distributions, we can obtain an accurate variational estimate
of the Kullback-Leibler divergence between the distributions of the generated
samples and the target. Moreover, we propose a decoder based on generalized
Hamiltonian dynamics to further enhance sampling performance. Through empirical
evaluation, we demonstrate the effectiveness of our method across various
complex distribution functions, showcasing its superiority compared to existing
methods.


  Following the work of Lal\'in and Mittal on the Mahler measure over arbitrary
tori, we investigate the definition of the generalized Mahler measure for all
Laurent polynomials in two variables when they do not vanish on the integration
torus. We establish certain relations between the standard Mahler measure and
the generalized Mahler measure of such polynomials. Later we focus our
investigation on a tempered family of polynomials originally studied by Boyd,
namely $Q_{r}(x, y) = x + \frac{1}{x} + y + \frac{1}{y} + r$ with $r \in
\mathbb{C},$ and apply our results to this family. For the $r = 4$ case, we
explicitly calculate the generalized Mahler measure of $Q_4$ over any arbitrary
torus in terms of special values of the Bloch-Wigner dilogarithm. Finally, we
extend our results to the several variable setting.


  We propose an efficient framework, called Simple Swap (SimSwap), aiming for
generalized and high fidelity face swapping. In contrast to previous approaches
that either lack the ability to generalize to arbitrary identity or fail to
preserve attributes like facial expression and gaze direction, our framework is
capable of transferring the identity of an arbitrary source face into an
arbitrary target face while preserving the attributes of the target face. We
overcome the above defects in the following two ways. First, we present the ID
Injection Module (IIM) which transfers the identity information of the source
face into the target face at feature level. By using this module, we extend the
architecture of an identity-specific face swapping algorithm to a framework for
arbitrary face swapping. Second, we propose the Weak Feature Matching Loss
which efficiently helps our framework to preserve the facial attributes in an
implicit way. Extensive experiments on wild faces demonstrate that our SimSwap
is able to achieve competitive identity performance while preserving attributes
better than previous state-of-the-art methods. The code is already available on
github: https://github.com/neuralchen/SimSwap.


  Polarized emission from dust is an important foreground that can hinder the
progress in polarized CMB studies unless carefully accounted for. We discuss
potential difficulties associated with the dust foreground, namely, the
existence of different grain populations with very different
emission/polarization properties and variations of the polarization yield with
grain temperature. In this context we appeal for systematic studies of
polarized dust emission as the means of dealing with this foreground.


  We consider stochastic multi-armed bandits where the expected reward is a
unimodal function over partially ordered arms. This important class of problems
has been recently investigated in (Cope 2009, Yu 2011). The set of arms is
either discrete, in which case arms correspond to the vertices of a finite
graph whose structure represents similarity in rewards, or continuous, in which
case arms belong to a bounded interval. For discrete unimodal bandits, we
derive asymptotic lower bounds for the regret achieved under any algorithm, and
propose OSUB, an algorithm whose regret matches this lower bound. Our algorithm
optimally exploits the unimodal structure of the problem, and surprisingly, its
asymptotic regret does not depend on the number of arms. We also provide a
regret upper bound for OSUB in non-stationary environments where the expected
rewards smoothly evolve over time. The analytical results are supported by
numerical experiments showing that OSUB performs significantly better than the
state-of-the-art algorithms. For continuous sets of arms, we provide a brief
discussion. We show that combining an appropriate discretization of the set of
arms with the UCB algorithm yields an order-optimal regret, and in practice,
outperforms recently proposed algorithms designed to exploit the unimodal
structure.


  Wordle is a very popular word game that is owned by the New York Times. We
can design parameterized strategies for solving Wordle, based on probabilistic,
statistical, and information-theoretical information about the games. The
strategies can handle a reasonably large family of Wordle-like games both
systematically and dynamically, meaning that we do not rely on precomputations
that may work for non-fixed games. More specifically, the answer set can be
arbitrary, not confining to the current 2315 words. The answer words may
include any specific number of letters (does not have to be five), and the set
of symbols that form the words does not have to be limited to only the English
alphabet.
  Exploring possible strategies for solving the Wordle-like games offers an
attractive learning challenges for students who are learning to design computer
games. This paper will provide the results of using two families of
parameterized strategies to solve the current Wordle, using the simulator that
abides by the hard-mode rules as the baseline. The baseline simulator used an
average of 4.078 guesses to find the 2315 answers, and needed more than six
trials to solve the game 1.77% of the time. The best performing strategy of
ours used an average of 3.674 guesses to find the 2315 answers, and failed
0.65% of the time.


  Particle Swarm Optimization (PSO) has demonstrated efficacy in addressing
static path planning problems. Nevertheless, such application on dynamic
scenarios has been severely precluded by PSO's low computational efficiency and
premature convergence downsides. To address these limitations, we proposed a
Tensor Operation Form (TOF) that converts particle-wise manipulations to tensor
operations, thereby enhancing computational efficiency. Harnessing the
computational advantage of TOF, a variant of PSO, designated as Self-Evolving
Particle Swarm Optimization (SEPSO) was developed. The SEPSO is underpinned by
a novel Hierarchical Self-Evolving Framework (HSEF) that enables autonomous
optimization of its own hyper-parameters to evade premature convergence.
Additionally, a Priori Initialization (PI) mechanism and an Auto Truncation
(AT) mechanism that substantially elevates the real-time performance of SEPSO
on dynamic path planning problems were introduced. Comprehensive experiments on
four widely used benchmark optimization functions have been initially conducted
to corroborate the validity of SEPSO. Following this, a dynamic simulation
environment that encompasses moving start/target points and dynamic/static
obstacles was employed to assess the effectiveness of SEPSO on the dynamic path
planning problem. Simulation results exhibit that the proposed SEPSO is capable
of generating superior paths with considerably better real-time performance (67
path planning computations per second in a regular desktop computer) in
contrast to alternative methods. The code and video of this paper can be
accessed here.


  Although Lorentz symmetry has been tested at low energy with extremely good
accuracy, its validity at very high energy is much less well established. If
Lorentz symmetry violation (LSV) is energy-dependent (e.g. $\propto E^2$), it
can be of order 1 at Planck scale and undetectable at GeV scale or below.
Similarly, superluminal particles with positive mass and energy (superbradyons)
can exist and be the ultimate building blocks of matter. We discuss a few
cosmological consequences of such a scenario, as well as possible experimental
tests.


  We present a numerical solution of a stationary 5-dimensional spinning cosmic
string in the Einstein-Yang-Mills (EYM) model, where the extra bulk coordinate
$\psi$ is periodic. It turns out that when $g_{\psi\psi}$ approaches zero,
i.e., a closed time-like curve (CTC) would appear, the solution becomes
singular. When a negative cosmological constant is incorporated in the model,
the solution becomes regular everywhere with angle deficit$<2\pi$. However, the
cosmic string-like object has not all the desired asymptotic properties of the
counterpart Abelian Nielsen-Olesen string. When we use a two point boundary
value routine with the correct cosmic string features far from the core, then
again a negative $\Lambda$ results in an acceptable string-like solution.
  We also investigated the possibility of a Gott space time structure of the
static 5D cosmic string. The matching condition yields no obstruction for an
effective angle deficit. Moreover, by considering the angular momentum in bulk
space, no helical structure of time is necessary. Two opposite moving 5D
strings could, in contrast with the 4D case, fulfil the Gott condition.


  The possibilities to measure lepton forward--backward asymmetries at the LHC
in the reaction pp(qqbar) --> l+l- are studied for dilepton events with masses
above 400 GeV. It is shown that such measurements allow accurate tests of the
neutral current interference structure up to about 2 TeV center of mass
energies. The sensitivity of asymmetries at the LHC to new physics is
demonstrated within the context of quark compositeness and exotic Z' scenarios.


  We show a priori bounds for solutions to $(\partial_t - \Delta) u = \sigma
(u) \xi$ in finite volume in the framework of Hairer's Regularity Structures
[Invent Math 198:269--504, 2014]. We assume $\sigma \in C_b^2 (\mathbb{R})$ and
that $\xi$ is of negative H\"older regularity of order $- 1 - \kappa$ where
$\kappa < \bar{\kappa}$ for an explicit $\bar{\kappa}< 1/3$, and that it can be
lifted to a model in the sense of Regularity Structures. Our main results
guarantee non-explosion of the solution in finite time and a growth which is at
most polynomial in $t > 0$. Our estimates imply global well-posedness for the
2-d generalised parabolic Anderson model on the torus, as well as for the
parabolic quantisation of the Sine-Gordon Euclidean Quantum Field Theory (EQFT)
on the torus in the regime $\beta^2 \in (4 \pi, (1 + \bar{\kappa}) 4 \pi)$. We
also consider the parabolic quantisation of a massive Sine-Gordon EQFT and
derive estimates that imply the existence of the measure for the same range of
$\beta$. Finally, our estimates apply to It\^o SPDEs in the sense of Da
Prato-Zabczyk [Stochastic Equations in Infinite Dimensions, Enc. Math. App.,
Cambridge Univ. Press, 1992] and imply existence of a stochastic flow beyond
the trace-class regime.


  Motivated by the potential similarities between the underlying mechanisms of
the enhanced memory storage capacity in black holes and in brain networks, we
construct an artificial quantum neural network based on gravity-like synaptic
connections and a symmetry structure that allows to describe the network in
terms of geometry of a d-dimensional space. We show that the network possesses
a critical state in which the gapless neurons emerge that appear to inhabit a
(d-1)-dimensional surface, with their number given by the surface area. In the
excitations of these neurons, the network can store and retrieve an
exponentially large number of patterns within an arbitrarily narrow energy gap.
The corresponding micro-state entropy of the brain network exhibits an area
law. The neural network can be described in terms of a quantum field, via
identifying the different neurons with the different momentum modes of the
field, while identifying the synaptic connections among the neurons with the
interactions among the corresponding momentum modes. Such a mapping allows to
attribute a well-defined sense of geometry to an intrinsically non-local
system, such as the neural network, and vice versa, it allows to represent the
quantum field model as a neural network.


  Important analyses at a future linear collider, including top-quark and
W-boson mass measurements will depend upon the precise determination of the
luminosity spectrum. This can be done, in principle,in the planned detectors.
We review the problems to be solved, both beam-related and detector-related.


  We show that coherent anti-Stokes Raman lineshapes do not follow known
spectral profiles if the time asymmetry of realistic laser pulses is taken into
account. Examples are given for nanosecond and picosecond laser pulses commonly
employed in frequency-resolved coherent anti-Stokes Raman scattering. More
remarkably, the analysis suggests an effect of line narrowing in comparison to
the customary approach, based primarily on the Voigt lineshape.


  We develop a 2D inclined rotating disc model, which we apply to the stellar
velocity maps of 1862 galaxies taken from the MaNGA survey (SDSS public Data
Release 15). We use a random forest classifier to identify the kinematic
parameters that are most connected to galaxy quenching. We find that kinematic
parameters that relate predominantly to the disc (such as the mean rotational
velocity) and parameters that characterise whether a galaxy is rotation- or
dispersion-dominated (such as the ratio of rotational velocity to velocity
dispersion) are not fundamentally linked to the quenching of star formation.
Instead, we find overwhelmingly that it is the absolute level of velocity
dispersion (a property that relates primarily to a galaxy's bulge/spheroidal
component) that is most important for separating star forming and quenched
galaxies. Furthermore, a partial correlation analysis shows that many commonly
discussed correlations between galaxy properties and quenching are spurious,
and that the fundamental correlation is between quenching and velocity
dispersion. In particular, we find that at fixed velocity dispersion, there is
only a very weak dependence of quenching on the disc properties, whereby more
discy galaxies are slightly more likely to be forming stars. By invoking the
tight relationship between black hole mass and velocity dispersion, and noting
that black hole mass traces the total energy released by AGN, we argue that
these data support a scenario in which quenching occurs by preventive feedback
from AGN. The kinematic measurements from this work are publicly available.


  Preservation of the chemical and structural integrity of samples that will be
brought back from Mars is paramount to achieving the scientific objectives of
MSR. Given our knowledge of the nature of the samples retrieved at Jezero by
Perseverance, at least two options need to be tested for opening the sample
tubes: (1) One or two radial cuts at the end of the tube to slide the sample
out. (2) Two radial cuts at the ends of the tube and two longitudinal cuts to
lift the upper half of the tube and access the sample. Strategy 1 will likely
minimize contamination but incurs the risk of affecting the physical integrity
of weakly consolidated samples. Strategy 2 will be optimal for preserving the
physical integrity of the samples but increases the risk of contamination and
mishandling of the sample as more manipulations and additional equipment will
be needed. A flexible approach to opening the sample tubes is therefore
required, and several options need to be available, depending on the nature of
the rock samples returned. Both opening strategies 1 and 2 may need to be
available when the samples are returned to handle different sample types (e.g.,
loosely bound sediments vs. indurated magmatic rocks). This question should be
revisited after engineering tests are performed on analogue samples. The MSR
sample tubes will have to be opened under stringent BSL4 conditions and this
aspect needs to be integrated into the planning.