  We explore links between the thin concurrent games of Castellan, Clairambault
and Winskel, and the weighted relational models of linear logic studied by
Laird, Manzonetto, McCusker and Pagani. More precisely, we show that there is
an interpretationpreserving "collapse" functor from the former to the latter.
On objects, the functor defines for each game a set of possible execution
states. Defining the action on morphisms is more subtle, and this is the main
contribution of the paper. Given a strategy and an execution state, our functor
needs to count the witnesses for this state within the strategy. Strategies in
thin concurrent games describe non-linear behaviour explicitly, so in general
each witness exists in countably many symmetric copies. The challenge is to
define the right notion of witnesses, factoring out this infinity while
matching the weighted relational model. Understanding how witnesses compose is
particularly subtle and requires a delve into the combinatorics of witnesses
and their symmetries. In its basic form, this functor connects thin concurrent
games and a relational model weighted by N $\cup$ {+$\infty$}. We will
additionally consider a generalised setting where both models are weighted by
elements of an arbitrary continuous semiring; this covers the probabilistic
case, among others. Witnesses now additionally carry a value from the semiring,
and our interpretation-preserving collapse functor extends to this setting.


  Thermalization in the D1D5 CFT should occur via interactions caused by the
twist operator, which deforms the theory off its free orbifold point. Earlier
studies investigating this deformation at first order did not show any definite
evidence of thermalization. In this paper we study the deformation to second
order, where we do expect to see the effects that should give thermalization.
We compute the effect of two twist operators on an initial vacuum state, which
generates a squeezed state analogous to the case for a single twist. We obtain
expressions for the Bogoliubov coefficients in this 2-twist case.


  We revisit processes generated by iterated random functions driven by a
stationary and ergodic sequence. Such a process is called strongly stable if a
random initialization exists, for which the process is stationary and ergodic,
and for any other initialization, the difference between the two processes
converges to zero almost surely. Under some mild conditions on the
corresponding recursive map, without any condition on the driving sequence, we
show the strong stability of iterations. Several applications are surveyed such
as generalized autoregression and queuing. Furthermore, new results are deduced
for Langevin-type iterations with dependent noise and for multitype branching
processes.


  A new S-type singular value inclusion set for rectangular tensors is given
and proved to be tighter than that in [Sang C.L., An S-type singular value
inclusion set for rectangular tensors, J. Inequal. Appl. 2017: 141, 2017].
Based on this set, new bounds for the largest singular value of nonnegative
rectangular tensors are obtained and proved to be better than some existing
results. Compared with the results in the paper mentioned above, the advantage
of the new results is that, under the same computations, we can obtain a
tighter singular value inclusion set for rectangular tensors and sharper bounds
for the largest singular value of nonnegative rectangular tensors. Finally, a
numerical example is given to verify the theoretical results.


  The possibility to observe transiting exoplanets from Dome C in Antarctica
provides immense benefits: stable weather conditions, limited atmospheric
turbulence, and a night that lasts almost three months due to the austral
winter. However, this site also presents significant limitations, such as
limited access for maintenance and internet speeds of only a few KB/s. This
latter factor means that the approximately 6 TB of data collected annually must
be processed on site automatically, with only final data products being sent
once a day to Europe. In this context, we present the current state of
operations of ASTEP+, a 40 cm optical telescope located at Concordia Station in
Antarctica. Following a successful summer campaign, ASTEP+ has begun the 2022
observing season with a brand-new two-colour photometer with increased
sensitivity. A new Python data analysis pipeline installed on a dedicated
server in Concordia will significantly improve the precision of the extracted
photometry, enabling us to get higher signal-to-noise transit detections. The
new pipeline additionally incorporates automatic transit modelling to reduce
the amount of manual post-processing required. It also handles the automatic
daily transfer of the photometric lightcurves and control data to Europe.
Additionally, we present the Python and web-based systems used for selection
and scheduling of transit observations; these systems have wide applicability
for the scheduling of other astronomical observations with strong time
constraints. We also review the type of science that ASTEP+ will be conducting
and analyse how unique ASTEP+ is to exoplanet transit research.


  By tracking small particles in the bulk of an intensely turbulent flow, we
show that even a very small concentration of long-chain polymers disrupts the
usual turbulent energy cascade. The polymers affect scales much larger than
their physical size, from the dissipation range to the inertial range. The
effect depends strongly on the polymer concentration. While the
dissipative-scale statistics change continuously as the polymer concentration
is increased, the inertial-range energy transfer rate is only altered by the
polymer additives when the concentration is above a threshold (approximately 5
parts per million by weight for the polymer we used).


  Quantifying a society's value system is important because it suggests what
people deeply care about -- it reflects who they actually are and, more
importantly, who they will like to be. This cultural quantification has been
typically done by studying literary production. However, a society's value
system might well be implicitly quantified based on the decisions that people
took in the past and that were mediated by what they care about. It turns out
that one class of these decisions is visible in ordinary settings: it is
visible in street names. We studied the names of 4,932 honorific streets in the
cities of Paris, Vienna, London and New York. We chose these four cities
because they were important centers of cultural influence for the Western world
in the 20th century. We found that street names greatly reflect the extent to
which a society is gender biased, which professions are considered elite ones,
and the extent to which a city is influenced by the rest of the world. This way
of quantifying a society's value system promises to inform new methodologies in
Digital Humanities; makes it possible for municipalities to reflect on their
past to inform their future; and informs the design of everyday's educational
tools that promote historical awareness in a playful way.


  Recent studies have revealed the vulnerability of deep neural networks (DNNs)
to various backdoor attacks, where the behavior of DNNs can be compromised by
utilizing certain types of triggers or poisoning mechanisms. State-of-the-art
(SOTA) defenses employ too-sophisticated mechanisms that require either a
computationally expensive adversarial search module for reverse-engineering the
trigger distribution or an over-sensitive hyper-parameter selection module.
Moreover, they offer sub-par performance in challenging scenarios, e.g.,
limited validation data and strong attacks. In this paper, we propose Neural
mask Fine-Tuning (NFT) with an aim to optimally re-organize the neuron
activities in a way that the effect of the backdoor is removed. Utilizing a
simple data augmentation like MixUp, NFT relaxes the trigger synthesis process
and eliminates the requirement of the adversarial search module. Our study
further reveals that direct weight fine-tuning under limited validation data
results in poor post-purification clean test accuracy, primarily due to
overfitting issue. To overcome this, we propose to fine-tune neural masks
instead of model weights. In addition, a mask regularizer has been devised to
further mitigate the model drift during the purification process. The distinct
characteristics of NFT render it highly efficient in both runtime and sample
usage, as it can remove the backdoor even when a single sample is available
from each class. We validate the effectiveness of NFT through extensive
experiments covering the tasks of image classification, object detection, video
action recognition, 3D point cloud, and natural language processing. We
evaluate our method against 14 different attacks (LIRA, WaNet, etc.) on 11
benchmark data sets such as ImageNet, UCF101, Pascal VOC, ModelNet,
OpenSubtitles2012, etc.


  We introduce a new property of tile self-assembly systems that we call
size-separability. A system is size-separable if every terminal assembly is a
constant factor larger than any intermediate assembly. Size-separability is
motivated by the practical problem of filtering completed assemblies from a
variety of incomplete "garbage" assemblies using gel electrophoresis or other
mass-based filtering techniques.
  Here we prove that any system without cooperative bonding assembling a unique
mismatch-free terminal assembly can be used to construct a size-separable
system uniquely assembling the same shape. The proof achieves optimal scale
factor and temperature for the size-separable system. As part of the proof, we
obtain two results of independent interest on mismatch-free temperature-1
two-handed systems.


  Distribution matching transforms independent and Bernoulli(1/2) distributed
input bits into a sequence of output symbols with a desired distribution.
Fixed-to-fixed length, invertible, and low complexity encoders and decoders
based on constant composition and arithmetic coding are presented.
Asymptotically in the blocklength, the encoder achieves the maximum rate,
namely the entropy of the desired distribution. Furthermore, the normalized
divergence of the encoder output and the desired distribution goes to zero in
the blocklength.


  We study charged and radially excited boson stars in both asymptotically flat
as well as asymptotically Anti-de Sitter space-time. We demonstrate that two
different types of radially excited solutions exist~: one that persists in the
linear limit of small scalar fields, in which analytical arguments suggest the
existence of these solutions, and one that appears only in the highly
non-linear regime of the model. We also demonstrate that the formation of wavy
scalar hair discussed previously for black holes and boson stars in
asymptotically flat space-time persists for asymptotically Anti-de Sitter
space-time.


  In this paper we study the well-posedness for the inhomogeneous nonlinear
Schr\"odinger equation $i\partial_{t}u+\Delta
u=\lambda|x|^{-\alpha}|u|^{\beta}u$ in Sobolev spaces $H^s$, $s\geq0$. The
well-posedness theory for this model has been intensively studied in recent
years, but much less is understood compared to the classical NLS model where
$\alpha=0$. The conventional approach does not work particularly for the
critical cases $\beta=\frac{4-2\alpha}{d-2s}$. It is still an open problem. The
main contribution of this paper is to develop the well-posedness theory in this
critical case (as well as non-critical cases). To this end, we approach to the
matter in a new way based on a weighted $L^p$ setting which seems to be more
suitable to perform a finer analysis for this model. This is because it makes
it possible to handle the singularity $|x|^{-\alpha}$ in the nonlinearity more
effectively. This observation is a core of our approach that covers the
critical case successfully.


  We report on a new measurement of the luminosity function (LF) and mass
function (MF) of field low-mass dwarfs using Sloan Digital Sky Survey (SDSS)
photometry. The final catalog is composed of ~15 million low-mass stars (0.1
Msun < M < 0.8 Msun), spread over 8,400 square degrees. Distances to the stars
are estimated using new photometric parallax relations, constructed from ugriz
photometry of nearby low-mass stars with trigonometric parallaxes. The LF is
measured with a novel technique, which simultaneously measures Galactic
structure and the stellar LF. The resulting LF is compared to previous studies
and converted to a MF. The MF is well-described by a log-normal distribution,
with Mo = 0.27 Msun.


  We develop a hydrodynamic representation of the Klein-Gordon-Maxwell-Einstein
equations. These equations combine quantum mechanics, electromagnetism, and
general relativity. We consider the case of an arbitrary curved spacetime, the
case of weak gravitational fields in a static or expanding background, and the
nonrelativistic (Newtonian) limit. The Klein-Gordon-Maxwell-Einstein equations
govern the evolution of a complex scalar field, possibly describing
self-gravitating Bose-Einstein condensates, coupled to an electromagnetic
field. They may find applications in the context of dark matter, boson stars,
and neutron stars with a superfluid core.


  We consider the online search problem in which a server starting at the
origin of a $d$-dimensional Euclidean space has to find an arbitrary
hyperplane. The best-possible competitive ratio and the length of the shortest
curve from which each point on the $d$-dimensional unit sphere can be seen are
within a constant factor of each other. We show that this length is in
$\Omega(d)\cap O(d^{3/2})$.


  We study the partially wrapped Fukaya category of a surface with boundary
with an action of a group of order two. Inspired by skew-group algebras and
categories, we define the notion of a skew-group $A_\infty$-category and let it
play the role of the partially wrapped Fukaya category of an orbifold surface.
We classify indecomposable objects in terms of graded curves with signs, or
taggings, at orbifold points. We compute morphisms between a class of objects,
and we use this to describe tilting objects and find algebras
derived-equivalent to skew-gentle algebras.


  A general method of quantum-to-classical reduction of quantum dynamics is
described. The key aspect of our method is the similarity transformation of the
Liouvillian, which provides a new perspective. In conventional studies of
quantum energy transport, the rotating wave approximation has been frequently
regarded as an inappropriate approach because it causes the energy flow through
the system to vanish. Our formulation elucidates as to why this unphysical
result occurs and provides a solution for the problem. That is, not only the
density matrix but also the physical quantity is to be transformed. Moreover,
we show that quantum dynamics can be "exactly" replaced with classical
equations for the calculation of the transport efficiency.


  The epoxy/magnetite nanocomposites express superparamagnetism under a static
or low-frequency electromagnetic field. At the microwave frequency, said the
X-band, the nanocomposites reveal an unexpected diamagnetism. To explain the
intriguing phenomenon, we revisit the Debye relaxation law with the memory
effect. The magnetization vector of the magnetite is unable to synchronize with
the rapidly changing magnetic field, and it contributes to diamagnetism, a
negative magnetic susceptibility for nanoparticles. The model just developed
and the fitting result can not only be used to explain the experimental data in
the X-band but also can be used to estimate the transition frequency between
paramagnetism and diamagnetism.


  The main contribution of this paper is the introduction of a dynamic logic
formalism for reasoning about information flow in composite quantum systems.
This builds on our previous work on a complete quantum dynamic logic for single
systems. Here we extend that work to a sound (but not necessarily complete)
logic for composite systems, which brings together ideas from the quantum logic
tradition with concepts from (dynamic) modal logic and from quantum
computation. This Logic of Quantum Programs (LQP) is capable of expressing
important features of quantum measurements and unitary evolutions of
multi-partite states, as well as giving logical characterisations to various
forms of entanglement (for example, the Bell states, the GHZ states etc.). We
present a finitary syntax, a relational semantics and a sound proof system for
this logic. As applications, we use our system to give formal correctness
proofs for the Teleportation protocol and for a standard Quantum Secret Sharing
protocol; a whole range of other quantum circuits and programs, including other
well-known protocols (for example, superdense coding, entanglement swapping,
logic-gate teleportation etc.), can be similarly verified using our logic.


  We study the position estimation of a mechanical oscillator undergoing both
detuned parametric amplification and continuous quantum measurement. This
model, which can be utilised to produce squeezed states, is applied to a
general optoelectromechanical system. Using a stochastic master equation
formalism, we derive general formulae for the reduction in position uncertainty
of one quadrature of motion. The filter for extracting the optimal position
estimate from the measurement record is derived. We also find that since this
scheme does not work far into the back-action dominated regime, implementing
resolved-sideband cooling improves the squeezing only marginally.


  The upcoming long baseline neutrino experiments aim to enhance proton beam
power to multi-MW scale and utilize large-scale detectors to address the
challenge of limited event statistics. The DUNE experiment at LBNF will test
the three neutrino flavor paradigm and directly search for CP violation by
studying oscillation signatures in the high intensity $\nu_{\mu}$
(anti-$\nu_{\mu}$) beam to $\nu_{e}$ (anti-$\nu_{e}$) measured over a long
baseline. Higher beam power and improved accelerator up-time will enhance
neutrino flux for the neutrino program by increasing the number of protons on
target. LBNF/DUNE, as well as PIP-II upgrade and Accelerator Complex Evolution
(ACE) plan, play a vital role in this effort. The scientific potential of ACE
plan extends beyond neutrino physics, encompassing endeavors such as the Muon
Collider, Charged Lepton Flavor Violation (CLFV), Dark Sectors, and exploration
of neutrinos beyond DUNE.\par In the era of higher-power accelerator operation
, research in target materials and beam instrumentation is crucial for
optimizing design modifications. This abstract discusses Fermilab ACE, the
science opportunities it provides, and how Fermilab is pushing the limits of
proton beam power and accelerator infrastructure. By tackling neutrino beam
challenges and exploring research and development ideas, we are advancing our
understanding of fundamental particles and their interactions.


  We analyze the memory capacity of a delay based reservoir computer with a
Hopf normal form as nonlinearity and numerically compute the linear as well as
the higher order recall capabilities. A possible physical realisation could be
a laser with external cavity, for which the information is fed via electrical
injection. A task independent quantification of the computational capability of
the reservoir system is done via a complete orthonormal set of basis functions.
Our results suggest that even for constant readout dimension the total memory
capacity is dependent on the ratio between the information input period, also
called the clock cycle, and the time delay in the system. Optimal performance
is found for a time delay about 1.6 times the clock cycle


  Thermonuclear flashes of hydrogen and helium accreted onto neutron stars
produce the frequently observed Type I X-ray bursts. It is the current paradigm
that almost all material burns in a burst, after which it takes hours to
accumulate fresh fuel for the next burst. In rare cases, however, bursts are
observed with recurrence times as short as minutes. We present the first
one-dimensional multi-zone simulations that reproduce this phenomenon. Bursts
that ignite in a relatively hot neutron star envelope leave a substantial
fraction of the fuel unburned at shallow depths. In the wake of the burst,
convective mixing events driven by opacity bring this fuel down to the ignition
depth on the observed timescale of minutes. There, unburned hydrogen mixes with
the metal-rich ashes, igniting to produce a subsequent burst. We find burst
pairs and triplets, similar to the observed instances. Our simulations
reproduce the observed fraction of bursts with short waiting times of ~30%, and
demonstrate that short recurrence time bursts are typically less bright and of
shorter duration.


  We show that the sheaf of $\mathbb A^1$-connected components of a Nisnevich
sheaf of sets and its universal $\mathbb A^1$-invariant quotient (obtained by
iterating the $\mathbb A^1$-chain connected components construction and taking
the direct limit) agree on field-valued points. This establishes an explicit
formula for the field-valued points of the sheaf of $\mathbb A^1$-connected
components of any space. Given any natural number $n$, we construct an $\mathbb
A^1$-connected space on which the iterations of the naive $\mathbb
A^1$-connected components construction do not stabilize before the $n$th stage.


  Extrasolar planetary transits are powerful tools to probe their atmosphere
and to extract key physical properties of planets, like their mean densities,
chemical compositions, or atmospheric structures. Every 3.5 days, the transits
of the gaseous planet orbiting HD209458 offer the opportunity to investigate
the spectral features of its atmosphere. We present here NUV transmission
spectroscopy of the transiting extrasolar planet HD209458b using HST/ACS. We
show the data analysis of the seven HST orbits which were used to observe two
transits of HD209458b. Due to various remaining systematics, the radius of the
planet in the NUV could not be extracted with a high precison. However, we
derived a radius of Rp=1.4Rjup+/-0.08 between 2800 and 3100 AA which is
consistent with previous measurements in the visible.


  Undoubtedly, social media are brainstormed by a tremendous volume of stories,
feedback, reviews, and reactions expressed in various languages and idioms,
even though some are factually incorrect. These motifs make assessing such data
challenging, time-consuming, and vulnerable to misinterpretation. This paper
describes a classification model for movie reviews founded on deep learning
approaches. Almost 500KB pairs of balanced data from the IMDb movie review
databases are employed to train the model. People's perspectives regarding
movies were classified using both the long short-term memory (LSTM) and
convolutional neural network (CNN) strategies. According to the findings, the
CNN algorithm's prediction accuracy rate would be almost 97.4%. Furthermore,
the model trained by LSTM resulted in accuracies of around and applying 99.2%
within the Keras library. The model is investigated more by modification of
model parameters. According to the outcomes, LTSM outperforms CNN in assessing
IMDb movie reviews and is computationally less costly than LSTM.


  We consider systems under uncertainty whose dynamics are partially unknown.
Our aim is to study satisfaction of temporal logic properties by trajectories
of such systems. We express these properties as signal temporal logic formulas
and check if the probability of satisfying the property is at least a given
threshold. Since the dynamics are parameterized and partially unknown, we
collect data from the system and employ Bayesian inference techniques to
associate a confidence value to the satisfaction of the property. The main
novelty of our approach is to combine both data-driven and model-based
techniques in order to have a two-layer probabilistic reasoning over the
behavior of the system: one layer is related to the stochastic noise inside the
system and the next layer is related to the noisy data collected from the
system. We provide approximate algorithms for computing the confidence for
linear dynamical systems.


  Heavy long-lived multi-charged leptons (MCLs) are predicted by various new
physics models. These hypothetical MCLs can form bound states, due to their
high electric charges and long life times. In this work, we propose a novel
strategy of searching for MCLs through their bound state productions and
decays. By utilizing LHC-8 TeV data in searching for resonances in the diphoton
channel, we exclude the masses of isospin singlet heavy leptons with electric
charge $|q|\geq 6$ (in units of electron charge) lower than $\sim$1.2 TeV,
which are much stronger than the corresponding 8 TeV LHC bounds from analysing
the high ionisation and the long time-of-flight of MCLs. By utilising the
current 13 TeV LHC diphoton channel measurements the bound can further exclude
MCL masses up to $\sim$1.6 TeV for $|q|\geq 6$. Also, we demonstrate that the
conventional LHC limits from searching for MCLs produced via Drell-Yan
processes can be enhanced by including the contribution of photon fusion
processes.


  An improved version of the ``optical bar'' intracavity readout scheme for
gravitational-wave antennae is considered. We propose to call this scheme
``optical lever'' because it can provide significant gain in the signal
displacement of the local mirror similar to the gain which can be obtained
using ordinary mechanical lever with unequal arms. In this scheme displacement
of the local mirror can be close to the signal displacement of the end mirrors
of hypothetical gravitational-wave antenna with arm lengths equal to the
half-wavelength of the gravitational wave.


  High sensitivity observations of Halpha polarization of 30 flares of
different sizes and disk positions are reported. Both filter and spectrographic
techniques have been used. The ZIMPOL system eliminates spurious polarizations
due to seeing and flat-field effects. We didn't find any clear linear
polarization signature above our sensitivity level which was usually better
than 0.1%. The observations include an X17.1 flare with gamma-ray lines
reported by the RHESSI satellite. These results cast serious doubts on previous
claims of linear polarization at the one percent level and more, attributed to
impact polarization. The absence of linear polarization limits the anisotropy
of energetic protons in the H$\alpha$ emitting region. The likely causes are
isotropization by collisions with neutrals in the chromosphere and defocusing
by the converging magnetic field.


  We report a study about the electrical response from a sliding contact made
of a silver-graphite brush and a brass ring. This study focuses specifically on
the voltage variations due to the mechanical interactions across the contact
according to the rotational speed. This study is part of the research and the
development about the monitoring of dynamical interfaces.


  The one-dimensional parabolic potential barrier dealt with in an earlier
paper is re-examined from the point of view of operator methods, for the
purpose of getting generalized Fock spaces.


  Can recurrent neural nets, inspired by human sequential data processing,
learn to understand language? We construct simplified datasets reflecting core
properties of natural language as modeled in formal syntax and semantics:
recursive syntactic structure and compositionality. We find LSTM and GRU
networks to generalise to compositional interpretation well, but only in the
most favorable learning settings, with a well-paced curriculum, extensive
training data, and left-to-right (but not right-to-left) composition.


  The project was funded in 2021-2023 by the National Programme of Estonian
Language Technology. Its main aim was to develop spelling and grammar
correction tools for the Estonian language. The main challenge was the very
small amount of available error correction data needed for such development. To
mitigate this, (1) we annotated more correction data for model training and
testing, (2) we tested transfer-learning, i.e. retraining machine learning
models created for other tasks, so as not to depend solely on correction data,
(3) we compared the developed method and model with alternatives, including
large language models. We also developed automatic evaluation, which can
calculate the accuracy and yield of corrections by error category, so that the
effectiveness of different methods can be compared in detail.
  There has been a breakthrough in large language models during the project:
GPT4, a commercial language model with Estonian-language support, has been
created. We took into account the existence of the model when adjusting plans
and in the report we present a comparison with the ability of GPT4 to improve
the Estonian language text.
  The final results show that the approach we have developed provides better
scores than GPT4 and the result is usable but not entirely reliable yet. The
report also contains ideas on how GPT4 and other major language models can be
implemented in the future, focusing on open-source solutions.
  All results of this project are open-data/open-source, with licenses that
allow them to be used for purposes including commercial ones.


  Let $\cX$ be a family of subsets of a finite set $E$. A matroid on $E$ is
called an $\cX$-matroid if each set in $\cX$ is a circuit. We consider the
problem of determining when there exists a unique maximal $\cX$-matroid in the
weak order poset of all $\cX$-matroids on $E$, and characterizing its rank
function when it exists.


  The worldline formalism has previously been used for deriving compact master
formulas for the QED $N$ - photon amplitudes in vacuum, in a constant field and
in a plane-wave field. Here we carry this program one step further by deriving
master formulas for the scalar and spinor QED $N$-photon amplitudes in the
background of the "parallel" special case of a combined constant and plane-wave
field.


  In the Tutor Allocation Problem, the objective is to assign a set of tutors
to a set of workshops in order to maximize tutors' preferences. The problem is
solved every year by many universities, each having its own specific set of
constraints. In this work, we study the tutor allocation in the School of
Mathematics at the University of Edinburgh, and solve it with an integer linear
programming model. We tested the model on the 2019/2020 case, obtaining a
significant improvement with respect to the manual assignment in use. Further
tests on randomly created instances show that the model can be used to address
cases of broad interest. We also provide meaningful insights on how input
parameters, such as the number of workshop locations and the length of the
tutors' preference list, might affect the performance of the model and the
average number of preferences satisfied.


  We have investigated the influence of the superconducting layer thickness, d,
on the structural and transport properties of Co-doped BaFe2As2 films deposited
on Fe-buffered MgO substrates by pulsed laser deposition. The superconducting
transition temperature and the texture quality of Co-doped BaFe2As2 films
improve with increasing d due to a gradual relief of the tensile strain. For
d>90 nm an additional 110 textured component of Co-doped BaFe2As2 was observed,
which leads to an upward shift in the angular dependent critical current
density at H // c. These results indicate that the grain boundaries created by
the 110 textured component may contribute to the c-axis pinning.


  Approximate Bayesian computation (ABC) has gained popularity over the past
few years for the analysis of complex models arising in population genetic,
epidemiology and system biology. Sequential Monte Carlo (SMC) approaches have
become work horses in ABC. Here we discuss how to construct the perturbation
kernels that are required in ABC SMC approaches, in order to construct a set of
distributions that start out from a suitably defined prior and converge towards
the unknown posterior. We derive optimality criteria for different kernels,
which are based on the Kullback-Leibler divergence between a distribution and
the distribution of the perturbed particles. We will show that for many
complicated posterior distributions, locally adapted kernels tend to show the
best performance. In cases where it is possible to estimate the Fisher
information we can construct particularly efficient perturbation kernels. We
find that the added moderate cost of adapting kernel functions is easily
regained in terms of the higher acceptance rate. We demonstrate the
computational efficiency gains in a range of toy-examples which illustrate some
of the challenges faced in real-world applications of ABC, before turning to
two demanding parameter inference problem in molecular biology, which highlight
the huge increases in efficiency that can be gained from choice of optimal
models. We conclude with a general discussion of rational choice of
perturbation kernels in ABC SMC settings.


  In a supersymmetry model with an axino as the lightest supersymmetric
particle (LSP) and a Bino as the next LSP (NLSP), supersymmetry particles
produced in pair at a high energy collider end up with including two Binos,
followed by each Bino's decay into a photon and an axino. Final states are
diphoton with large missing energy. We have comprehensively studied the
implication of $\gamma\gamma+$MET data from the ALEPH, CDF II, and recent ATLAS
and CMS experiments. No excess over the standard model backgrounds can be
explained in this model if the NLSP Bino decays outside the detector, which
happens when the axino decay constant $f_a$ is large enough. The ALEPH and CDF
II data put a very strong bound on $f_a$ for light Bino case with
$m_{\tilde{B}} < 150$ GeV: the narrow hadronic axion window around $f_a \sim
10^6$ GeV is completely closed. In the case where the gluino mass is smaller
than about 776 GeV, the recent ATLAS data limit $f_a > 10^5$ GeV for the Bino
mass below 700 GeV. This is already stronger than the previous laboratory
bounds.


  In this paper we enhance Generalized Self-Adapting Particle Swarm
Optimization algorithm (GAPSO), initially introduced at the Parallel Problem
Solving from Nature 2018 conference, and to investigate its properties. The
research on GAPSO is underlined by the two following assumptions: (1) it is
possible to achieve good performance of an optimization algorithm through
utilization of all of the gathered samples, (2) the best performance can be
accomplished by means of a combination of specialized sampling behaviors
(Particle Swarm Optimization, Differential Evolution, and locally fitted square
functions). From a software engineering point of view, GAPSO considers a
standard Particle Swarm Optimization algorithm as an ideal starting point for
creating a generalpurpose global optimization framework. Within this framework
hybrid optimization algorithms are developed, and various additional techniques
(like algorithm restart management or adaptation schemes) are tested. The paper
introduces a new version of the algorithm, abbreviated as M-GAPSO. In
comparison with the original GAPSO formulation it includes the following four
features: a global restart management scheme, samples gathering within an
R-Tree based index (archive/memory of samples), adaptation of a sampling
behavior based on a global particle performance, and a specific approach to
local search. The above-mentioned enhancements resulted in improved performance
of M-GAPSO over GAPSO, observed on both COCO BBOB testbed and in the black-box
optimization competition BBComp. Also, for lower dimensionality functions (up
to 5D) results of M-GAPSO are better or comparable to the state-of-the art
version of CMA-ES (namely the KL-BIPOP-CMA-ES algorithm presented at the GECCO
2017 conference).


  We present the exact time-dependent solutions on inhomogeneous spherically
symmetric space-time in the conformal invariant Weyl gravity. For this purpose,
the subclass of the Lemaitre-Tolman metric which is supported by an anisotropic
fluid is used. For the first time, the exact solutions of the dynamical
equations are obtained for two special cases. One of the exact solutions is a
de Sitter space-time and other solution is a class of time-dependent wormhole
geometries which can be supported by exotic matter in similar to the general
relativistic solutions.


  We develop an effective framework for the $\bar\mu$ scheme of holonomy
corrections motivated by loop quantum gravity for vacuum spherically symmetric
space-times. This is done by imposing the areal gauge in the classical theory,
and then expressing the remaining components of the Ashtekar-Barbero connection
in the Hamiltonian constraint in terms of holonomies of physical length
$\ell_{\rm Pl}$. The stationary solutions to the effective Hamiltonian
constraint can be found exactly, and we give the explicit form of the effective
metric in Painlev\'e-Gullstrand coordinates. This solution has the correct
classical limit, the quantum gravity corrections decay rapidly at large
distances, and curvature scalars are bounded by the Planck scale, independently
of the black hole mass $M$. In addition, the solution is valid for radii $x \ge
x_{\rm min} \sim (\ell_{\rm Pl}^2 M)^{1/3}$ indicating the need for a matter
field, with an energy density bounded by the Planck scale, to provide a source
for the curvature in the space-time. Finally, for $M \gg m_{\rm Pl}$, the
space-time has an outer and also an inner horizon, within which the expansion
for outgoing radial null geodesics becomes positive again. On the other hand,
for sufficiently small $M \sim m_{\rm Pl}$, there are no horizons at all in the
effective metric.


  Optical spectroscopy study of the recent AG Peg outburst observed during the
second half of 2015 is presented. Considerable variations of the intensity and
the shape of the spectral features as well as the changes of the hot component
parameters, caused by the outburst, are discussed and certain similarities
between the outburst of AG Peg and the outburst of a classical symbiotic stars
are shown. It seems that after the end of the symbiotic nova phase, AG Peg
became a member of the classical symbiotic stars group.


  As an indicator of human attention gaze is a subtle behavioral cue which can
be exploited in many applications. However, inferring 3D gaze direction is
challenging even for deep neural networks given the lack of large amount of
data (groundtruthing gaze is expensive and existing datasets use different
setups) and the inherent presence of gaze biases due to person-specific
difference. In this work, we address the problem of person-specific gaze model
adaptation from only a few reference training samples. The main and novel idea
is to improve gaze adaptation by generating additional training samples through
the synthesis of gaze-redirected eye images from existing reference samples. In
doing so, our contributions are threefold: (i) we design our gaze redirection
framework from synthetic data, allowing us to benefit from aligned training
sample pairs to predict accurate inverse mapping fields; (ii) we proposed a
self-supervised approach for domain adaptation; (iii) we exploit the gaze
redirection to improve the performance of person-specific gaze estimation.
Extensive experiments on two public datasets demonstrate the validity of our
gaze retargeting and gaze estimation framework.


  Accurate and reliable brain tumor segmentation is a critical component in
cancer diagnosis, treatment planning, and treatment outcome evaluation. Build
upon successful deep learning techniques, a novel brain tumor segmentation
method is developed by integrating fully convolutional neural networks (FCNNs)
and Conditional Random Fields (CRFs) in a unified framework to obtain
segmentation results with appearance and spatial consistency. We train a deep
learning based segmentation model using 2D image patches and image slices in
following steps: 1) training FCNNs using image patches; 2) training CRFs as
Recurrent Neural Networks (CRF-RNN) using image slices with parameters of FCNNs
fixed; and 3) fine-tuning the FCNNs and the CRF-RNN using image slices.
Particularly, we train 3 segmentation models using 2D image patches and slices
obtained in axial, coronal and sagittal views respectively, and combine them to
segment brain tumors using a voting based fusion strategy. Our method could
segment brain images slice-by-slice, much faster than those based on image
patches. We have evaluated our method based on imaging data provided by the
Multimodal Brain Tumor Image Segmentation Challenge (BRATS) 2013, BRATS 2015
and BRATS 2016. The experimental results have demonstrated that our method
could build a segmentation model with Flair, T1c, and T2 scans and achieve
competitive performance as those built with Flair, T1, T1c, and T2 scans.


  Rutile TiO2 is a paradigmatic transition metal oxide with applications in
optics, electronics, photocatalysis, etc., that are subject to pervasive
electron-phonon interaction. To understand how energies of its electronic
bands, and in general semiconductors or metals where the frontier orbitals have
a strong d-band character, depend on temperature, we perform a comprehensive
theoretical and experimental study of the effects of electron-phonon (e-p)
interactions. In a two-photon photoemission (2PP) spectroscopy study we observe
an unusual temperature dependence of electronic band energies within the
conduction band of reduced rutile TiO2, which is contrary to the well
understood sp-band semiconductors and points to a so far unexplained dichotomy
in how the e-p interactions affect differently the materials where the frontier
orbitals are derived from the sp- and d-orbitals. To develop a broadly
applicable model, we employ state-of-the-art first-principles calculations that
explain how phonons promote interactions between the Ti-3d orbitals of the
conduction band within the octahedral crystal field. The characteristics
differences in e-p interactions experienced by the Ti 3d-orbitals of rutile
TiO2 crystal lattice are contrasted with the more familiar behavior of the Si
2s-orbitals of stishovite SiO2 polymorph, in which the frontier 2s-orbital
experience a similar crystal field with the opposite effect...


  Many vector-borne disease epidemic models neglect the fact that in modern
human civilization, social awareness as well as self-defence system are
overwhelming against advanced propagation of the disease. News are becoming
more effortlessly accessible through social media and mobile apps, while
apparatuses for disease prevention are inclined to be more abundant and
affordable. Here we study a simple host-vector model in which media-triggered
social awareness and seasonality in vector breeding are taken into account.
There appears a certain threshold indicating the alarming outbreak; the number
of infective human individuals above which shall actuate the self-defence
system for the susceptible subpopulation. A model where the infection rate
revolves in the likelihood of poverty, reluctancy, tiresomeness, perceiving the
disease as being easily curable, absence of medical access, and overwhelming
hungrier vectors is proposed. Further discoveries are made from undertaking
disparate time scales between human and vector population dynamics. The
resulting slow-fast system discloses notable dynamics in which solution
trajectories confine to the slow manifold and critical manifold, before finally
ending up at equilibria. How coinciding the slow manifold with the critical
manifold enhances periodic forcing is also studied. The finding on hysteresis
loops gives insights of how defining alarming outbreak critically perturbs the
basic reproductive number, which later helps keep the incidence cycle on small
magnitudes.


  We study the spin fluctuation dynamics of Cu-O chains in the oxygen deficient
planes of YBa(2)Cu(3)O(6+x). The chains are described by a model including
antiferromagnetic interactions between the spins and Kondo-like scattering of
the oxygen holes by the copper spins. There are incommensurate spin
fluctuations along the direction of the chains. The dynamic structure factor of
this system is qualitatively different from that of a quasi one-dimensional
localized antiferromagnet due to the presence of itinerant holes. We compute
the dynamic structure factor that could be measured in neutron scattering
experiments.


  Existence of global weak solutions to the continuous Oort-Hulst-Safronov
(OHS) coagulation equation is investigated for coagulation kernels capturing a
singularity near zero and growing linearly at infinity. The proof mainly relies
on a relation, between classical Smoluchowski coagulation equation (SCE) and
OHS coagulation equation, which is introduced in [16] as generalized
coagulation equation. Moreover, all weak solutions formulated in a suitable
sense are demonstrated to be mass-conserving. We obtain here a similar result
for OHS coagulation equation as the one in [6] for SCE.


  These lectures address the dynamics of phase ordering out of equilibrium in
condensed matter and in quantum field theory in cosmological settings,
emphasizing their similarities and differences. In condensed matter we describe
the phenomenological approach based on the Time Dependent Ginzburg-Landau
(TDGL) description. After a general discussion of the main experimental and
theoretical features of phase ordering kinetics and the description of linear
(spinodal) instabilities we introduce the scaling hypothesis and show how a
dynamical correlation length emerges in the large N limit in condensed matter
systems. The large N approximation is a powerful tool in quantum field theory
that allows the study of non-perturbative phenomena in a consistent manner. We
study the exact solution to the dynamics after a quench in this limit in
Minkowski space time and in radiation dominated Friedman-Robertson-Walker
Cosmology. There are some remarkable similarities between these very different
settings such as the emergence of a scaling regime and of a dynamical
correlation length at late times that describe the formation and growth of
ordered regions. In quantum field theory and cosmology this length scale is
constrained by causality and its growth in time is also associated with
coarsening and the onset of a condensate. We provide a density matrix
interpretation of the formation of defects and the classicalization of quantum
fluctuations.


  The search for new interactions and particles in high-energy collider physics
relies on precise background predictions. This has led to many advances in
combining precise fixed-order cross-section calculations with detailed event
generator simulations. In recent years, fixed-order QCD calculations of
inclusive cross sections at N3LO precision have emerged, followed by an
impressive progress at producing differential results. Once differential
results become publicly available, it would be prudent to embed these into
event generators to allow the community to leverage these advances. This note
offers some concrete thoughts on ME+PS matching at third order in QCD. As a
method for testing these thoughts, a toy calculation of $e^+e^-\rightarrow u
\bar u$ at $\mathcal{O}(\alpha_s^3)$ is constructed, and combined with an event
generator through unitary matching. The toy implementation may serve also as
blueprint for high-precision QCD predictions at future lepton colliders. As a
byproduct of the N3LO matching formula, a new NNLO+PS formula for processes
with "additional" jets is obtained.


  We give a new proof of logarithmic bounds for Roth's theorem on arithmetic
progressions, namely that if $A \subset \{1,2,\ldots,N\}$ is free of three-term
progressions, then $\lvert A\rvert \leq N/(\log N)^{1-o(1)}$. Unlike previous
proofs, this is almost entirely done in physical space using
almost-periodicity.


  The classical Halpern-L\"auchli theorem states that for any finite coloring
of a finite product of finitely branching perfect trees of height $\omega$,
there exist strong subtrees sharing the same level set such that tuples
consisting of elements lying on the same level get the same color. Relative to
large cardinals, we establish the consistency of a tail cone version of the
Halpern-L\"auchli theorem at large cardinal, which, roughly speaking, deals
with many colorings simultaneously and diagonally. Among other applications, we
generalize a polarized partition relation on rational numbers due to Laver and
Galvin to one on linear orders of larger saturation.


  We analyze the modulation characteristics of the uncooled terahertz (THz) and
infrared (IR) detectors using the variation of the density and effective
temperature of the two-dimensional electron-hole plasma in uniform graphene
layers (GLs) and perforated graphene layers (PGLs) due to the absorption of THz
and IR radiation. The performance of the photodetectors (both the
GL-photoresistor and the PGL-based barrier photodiodes) are compared. Their
characteristics are also compared with the GL reverse-biased photodiodes. The
obtained results allow to evaluate the ultimate modulation frequencies of these
photodetectors and can be used for their optimization.


  Azimuthal distributions of radial velocities of charged hadrons produced in
nucleus-nucleus $(AB)$ collisions are compared with the corresponding azimuthal
distribution of charged hadron multiplicity in the framework of a multiphase
transport (AMPT) model at two different collision energies. The mean radial
velocity seems to be a good probe for studying radial expansion. While the
anisotropic part of the distributions indicates a kind of collective nature of
radial expansion, the isotropic part characterizes a thermal motion. The
present investigation is carried out keeping the upcoming Compressed Baryonic
Matter (CBM) experiment to be held at the Facility for Anti-proton Ion Research
(FAIR) in mind. As far as high-energy heavy-ion interactions are concerned, CBM
will supplement the Relativistic Heavy Ion Collider (RHIC) and Large Hadron
Collider (LHC) experiments. In this context our simulation results at high
baryochemical potential would be interesting, when scrutinized from the
perspective of almost a baryon free environment achieved at RHIC and LHC.


  Over the past three years we have determined the basic features of our
Universe. It is spatially flat; accelerating; comprised of 1/3 a new form of
matter, 2/3 a new form of energy, with some ordinary matter and a dash of
massive neutrinos; and it apparently began from a great burst of expansion
(inflation) during which quantum noise was stretched to astrophysical size
seeding cosmic structure. This ``New Cosmology'' greatly extends the highly
successful hot big-bang model. Now we have to make sense of it. What is the
dark matter particle? What is the nature of the dark energy? Why this mixture?
How did the matter -- antimatter asymmetry arise? What is the underlying cause
of inflation (if it indeed occurred)?


  Most collimated supersonic protostellar jets show a collimated wiggling, and
knotty structure (e.g., the Haro 6-5B jet) and frequently reveal a long gap
between this structure and the terminal bow shock. In a few cases, there is no
evidence of such a terminal feature. We present three-dimensional smoothed
particle hydrodynamical simulations which suggest that this morphology may be
due to the interaction of the propagating cooling jet with a non-homogeneous
ambient medium. In regions where the ambient gas has an increasing density (and
pressure) gradient, we find that it tends to compress the cold, low-pressure
cocoon of shocked material that surrounds the beam, destroy the bow shock-like
structure at the head, and enhance beam focusing, wiggling, and internal
traveling shocks. In ambient regions of decreasing density (and pressure), the
flow widens and relaxes, becoming very faint. This could explain ``invisible''
segments in systems like the Haro 6-5B jet. The bow shock in these cases could
be a relic of an earlier outflow episode, as previously suggested, or the place
where the jet reappears after striking a denser portion of the ambient medium.


  Given a closed Riemannian manifold of dimenion less than eight, we prove a
compactness result for the space of closed, embedded minimal hypersurfaces
satisfying a volume bound and a uniform lower bound on the first eigenvalue of
the stability operator. When the latter assumption is replaced by a uniform
lower bound on the p-th Jacobi eigenvalue for p greater or equal than 2 one
gains strong convergence to a smooth limit submanifold away from at most p-1
points.


  A square trisection is a problem of assembling three identical squares from a
larger square, using a minimal number of pieces. This paper presents an
historical overview of the square trisection problem starting with its origins
in the third century. We detail the reasoning behind some of the main known
solutions. Finally, we give a new solution and three ruler-and-compass
constructions. We conclude with a conjecture of optimality of the proposed
solution.


  This paper presents GestureMap, a visual analytics tool for gesture
elicitation which directly visualises the space of gestures. Concretely, a
Variational Autoencoder embeds gestures recorded as 3D skeletons on an
interactive 2D map. GestureMap further integrates three computational
capabilities to connect exploration to quantitative measures: Leveraging DTW
Barycenter Averaging (DBA), we compute average gestures to 1) represent gesture
groups at a glance; 2) compute a new consensus measure (variance around average
gesture); and 3) cluster gestures with k-means. We evaluate GestureMap and its
concepts with eight experts and an in-depth analysis of published data. Our
findings show how GestureMap facilitates exploring large datasets and helps
researchers to gain a visual understanding of elicited gesture spaces. It
further opens new directions, such as comparing elicitations across studies. We
discuss implications for elicitation studies and research, and opportunities to
extend our approach to additional tasks in gesture elicitation.


  A localised particle in Quantum Mechanics is described by a wave packet in
position space, regardless of its energy. However, from the point of view of
General Relativity, if the particle's energy density exceeds a certain
threshold, it should be a black hole. In order to combine these two pictures,
we introduce a horizon wave-function determined by the position wave-function,
which yields the probability that the particle is a black hole. The existence
of a (fuzzy) minimum mass for black holes naturally follows, and we also show
that our construction entails an effective Generalised Uncertainty Principle
simply obtained by adding the uncertainties coming from the two wave-functions.


  We systematically study the spectrum of excitations and the one-loop
determinant of holographic Wilson loop operators in antisymmetric
representations of $\mathcal{N}=4$ supersymmetric Yang-Mills theory.
Holographically, these operators are described by D5-branes carrying electric
flux and wrapping an $S^4 \subset S^5$ in the $AdS_5\times S^5$ bulk
background. We derive the dynamics of both bosonic and fermionic excitations
for such D5-branes. A particularly important configuration in this class is the
D5-brane with $AdS_2\times S^4$ worldvolume and $k$ units of electric flux,
which is dual to the circular Wilson loop in the totally antisymmetric
representation of rank $k$. For this Wilson loop, we obtain the spectrum, show
explicitly that it is supersymmetric and calculate the one-loop effective
action using heat kernel techniques.


  We do not know why there are three fermion families in the Standard Model
(SM), nor can we explain the observed pattern of fermion masses and mixing
angles. Standard grand unified theories based on the SU(5) and SO(10) groups
fail to shed light on this issue, since they also contain three copies of
fermion representations of an enlarged gauge group. However, it does not need
to be so: the Standard Model families might be distributed over distinct
representations of a grand unified model, in which case the gauge symmetry
itself might discriminate the various families and explain (at least partially)
the flavor puzzle. The most ambitious version of this idea consists on
embedding all SM fermions in a single irreducible representation of the gauge
group.


  We investigate the J/psi polarization in photoproduction at the Hadron
Electron Ring Accelerator(HERA) up to the next-to-leading order of QCD. The
results show that the transverse momentum p_t and energy fraction z
distributions of J/psi production do not agree with the observed ones very
well. The theoretical uncertainties for the z distributions of the J/psi
polarization parameters with respect to various choices of the renormalization
and factorization scales are too large to give an accurate prediction. The
uncertainties for the p_t distributions of these parameters are small when
p_t>3GeV and the obtained p_t distributions can not describe the experimental
data even in this region.


  Two puzzles associated with open clusters have attracted a lot of attention
-- their formation, with densities and velocity dispersions that are not too
different from those of the star forming regions in the Galaxy, given that the
observed Star Formation Efficiencies (SFE) are low and, the mass segregation
observed / inferred in some of them, at ages significantly less than the
dynamical relaxation times in them. Gas dynamical friction has been considered
before as a mechanism for contracting embedded stellar clusters, by dissipating
their energy. This would locally raise the SFE which might then allow bound
clusters to form. Noticing that dynamical friction is inherently capable of
producing mass segregation, since here, the dissipation rate is proportional to
the mass of the body experiencing the force, we explore further, some of the
details and implications of such a scenario, vis-a-vis observations. Making
analytical approximations, we obtain a boundary value for the density of a star
forming clump of given mass, such that, stellar clusters born in clumps which
have densities higher than this, could emerge bound after gas loss, and for a
clump of given mass and density, we find a critical mass such that,
subcondensations with larger masses than this could suffer significant
segregation within the clump.


  The structural correlation functions of a weakly disordered Abrikosov lattice
are calculated in a functional RG-expansion in $d=4-\epsilon$ dimensions. It is
shown, that in the asymptotic limit the Abrikosov lattice exhibits still
quasi-long-range translational order described by a {\it nonuniversal} exponent
$\eta_{\bf G}$ which depends on the ratio of the renormalized elastic constants
$\kappa ={c}_{66}/ {c}_{11}$ of the flux line (FL) lattice. Our calculations
clearly demonstrate three distinct scaling regimes corresponding to the Larkin,
the random manifold and the asymptotic Bragg-glass regime. On a wide range of
{\it intermediate} length scales the FL displacement correlation function
increases as a power law with twice the manifold roughness exponent $\zeta_{\rm
RM}(\kappa) $, which is also {\it nonuniversal}. Correlation functions in the
asymptotic regime are calculated in their full anisotropic dependencies and
various order parameters are examined. Our results, in particular the
$\kappa$-dependency of the exponents, are in variance with those of the
variational treatment with replica symmetry breaking which allows in principle
an experimental discrimination between the two approaches.


  Geometric deep learning (GDL), which is based on neural network architectures
that incorporate and process symmetry information, has emerged as a recent
paradigm in artificial intelligence. GDL bears particular promise in molecular
modeling applications, in which various molecular representations with
different symmetry properties and levels of abstraction exist. This review
provides a structured and harmonized overview of molecular GDL, highlighting
its applications in drug discovery, chemical synthesis prediction, and quantum
chemistry. Emphasis is placed on the relevance of the learned molecular
features and their complementarity to well-established molecular descriptors.
This review provides an overview of current challenges and opportunities, and
presents a forecast of the future of GDL for molecular sciences.


  Boundary value problems for operators of Dirac type arise naturally in
connection with the conformal geometry of surfaces immersed in Euclidean
3--space. Recently such boundary value problems have been successfully applied
to a variety of problems from computer graphics. Here we investigate under
which conditions these boundary value problems are elliptic and self--adjoint.
We show that under certain periodic deformations of the boundary data our
operators exhibit non-trivial spectral flow.


  Thermotropic biaxial nematic phases seem to be rare, but biaxial smectic A
phases less so. Here we use molecular field theory to study a simple
two-parameter model, with one parameter promoting a biaxial phase and the
second promoting smecticity. The theory combines the biaxial Maier-Saupe and
McMillan models. We use alternatively the Sonnet-Virga-Durand (SVD) and
geometric mean approximations (GMA) to characterize molecular biaxiality by a
single parameter. For non-zero smecticity and biaxiality, the model always
predicts a ground state biaxial smectic A phase. For a low degree of smectic
order, the phase diagram is very rich, predicting uniaxial and biaxial nematic
and smectic phases, with in addition a variety of tricritical and tetracritical
points. For higher degrees of smecticity, the region of stability of the
biaxial nematic phase is restricted and eventually disappears, yielding to the
biaxial smectic phase. Phase diagrams from the two alternative approximations
for molecular biaxiality are similar, except inasmuch that SVD allows for a
first order isotropic-nematic biaxial transition, whereas GMA predicts a Landau
point separating isotropic and biaxial nematic phases. We speculate that the
rarity of thermotropic biaxial nematic phases is partly a consequence of the
presence of stabler analogous smectic phases.


  We theoretically study charge noise generated by excited neutral modes, which
impinge on the quantum point contact of a quantum Hall bar with filling
fraction v=2/3. The noise is computed for thermally excited neutral modes as
well as for biased neutral modes with dipole-fermion excitations. Within the
dipole-fermion picture, we show that the noise arising from two colliding modes
can be suppressed due to Pauli-blocking and be non-universal due to random edge
disorder, but becomes universal upon disorder-averaging. The ratio of noise due
to two colliding neutral modes and noise due to only one such mode is smaller
for dipole-fermions than for thermal excitations, thus providing evidence for
the different quantum statistics of the two types of excitations.


  We show tunable strain-induced perpendicular magnetic anisotropy (PMA) over a
wide range of thicknesses in epitaxial ferrimagnetic insulator Eu3Fe5O12 (EuIG)
and Tb3Fe5O12 (TbIG) thin films grown by pulsed-laser deposition on Gd3Ga5O12
with (001) and (111) orientations, respectively. The PMA field is determined by
measuring the induced anomalous Hall loops in Pt deposited on the garnet films.
Due to positive magnetostriction constants, compressive in-plane strain induces
a PMA field as large as 32.9 kOe for 4 nm thick EuIG and 66.7 kOe for 5 nm
thick TbIG at 300 K, and relaxes extremely slowly as the garnet film thickness
increases. In bilayers consisting of Pt and EuIG or Pt and TbIG, robust PMA is
revealed by squared anomalous Hall hysteresis loops in Pt, the magnitude of
which appears to be only related to the net magnetic moment of iron
sublattices. Furthermore, the magnetostriction constant is found to be
2.7x10^(-5) for EuIG and 1.35x10^(-5) for TbIG, comparable with the values for
bulk crystals. Our results demonstrate a general approach of tailoring magnetic
anisotropy of rare earth iron garnets by utilizing modulated strain via
epitaxial growth.


  This paper studies several aspects of symbolic factors of $\mathcal{S}$-adic
subshifts of finite alphabet rank. First, we address a problem raised in
[DDPM20] about the topological rank of symbolic factors of $\mathcal{S}$-adic
subshifts and prove that this rank is at most the one of the extension system,
improving results from [E20] and [GH2020]. As a consequence of our methods, we
prove that finite topological rank systems are coalescent. Second, we
investigate the structure of fibers $\pi^{-1}(y)$ of factor maps
$\pi\colon(X,T)\to(Y,T)$ between minimal $\mathcal{S}$-adic subshifts of finite
alphabet rank and show that they have the same finite cardinality for all $y$
in a residual subset of $Y$. Finally, we prove that the number of symbolic
factors (up to conjugacy) of a fixed subshift of finite topological rank is
finite, thus extending Durand's similar theorem on linearly recurrent
subshifts.


  In this paper, we give some interesting and new identities of q-Bernoulli
numbers which are derived from convolutions on the ring of p-adic integers.


  We describe a method for learning word embeddings with data-dependent
dimensionality. Our Stochastic Dimensionality Skip-Gram (SD-SG) and Stochastic
Dimensionality Continuous Bag-of-Words (SD-CBOW) are nonparametric analogs of
Mikolov et al.'s (2013) well-known 'word2vec' models. Vector dimensionality is
made dynamic by employing techniques used by Cote & Larochelle (2016) to define
an RBM with an infinite number of hidden units. We show qualitatively and
quantitatively that SD-SG and SD-CBOW are competitive with their
fixed-dimension counterparts while providing a distribution over embedding
dimensionalities, which offers a window into how semantics distribute across
dimensions.


  This paper studies the design of wireless federated learning (FL) for
simultaneously training multiple machine learning models. We consider round
robin device-model assignment and downlink beamforming for concurrent multiple
model updates. After formulating the joint downlink-uplink transmission
process, we derive the per-model global update expression over communication
rounds, capturing the effect of beamforming and noisy reception. To maximize
the multi-model training convergence rate, we derive an upper bound on the
optimality gap of the global model update and use it to formulate a multi-group
multicast beamforming problem. We show that this problem can be converted to
minimizing the sum of inverse received signal-to-interference-plus-noise
ratios, which can be solved efficiently by projected gradient descent.
Simulation shows that our proposed multi-model FL solution outperforms other
alternatives, including conventional single-model sequential training and
multi-model zero-forcing beamforming.


  We report the detection of a weak X-ray point source coincident with the
nucleus of the bulgeless disk galaxy NGC 3621, recently discovered by Spitzer
to display high ionization mid-infrared lines typically associated with AGN.
These Chandra observations provide confirmation for the presence of an AGN in
this galaxy, adding to the growing evidence that black holes do form and grow
in isolated bulgeless disk galaxies. Although the low signal-to-noise ratio of
the X-ray spectrum prevents us from carrying out a detailed spectral analysis
of the nuclear source, the X-ray results, combined with the IR and optical
spectroscopic results, suggests that NGC 3621 harbors a heavily absorbed AGN,
with a supermassive black hole of relatively small mass accreting at a high
rate. Chandra also reveals the presence of two bright sources straddling the
nucleus located almost symmetrically at 20" from the center. Both sources have
X-ray spectra that are well-fitted by an absorbed power-law model. Assuming
they are at the distance of NGC 3621, these two sources have luminosities of
the order of 1.e39 erg/s, which make them ULXs and suggest that they are black
hole systems. Estimates of the black hole mass based on the X-ray spectral
analysis and scaling laws of black hole systems suggest that the 2 bright
sources might be intermediate mass black holes with M_BH of the order of a few
thousand solar masses. However, higher quality X-ray data combined with
multi-wavelength observations are necessary to confirm these conclusions.


  In the graph database literature the term "join" does not refer to an
operator used to merge two graphs. In particular, a counterpart of the
relational join is not present in existing graph query languages, and
consequently no efficient algorithms have been developed for this operator.
  This paper provides two main contributions. First, we define a binary graph
join operator that acts on the vertices as a standard relational join and
combines the edges according to a user-defined semantics. Then we propose the
"CoGrouped Graph Conjunctive $\theta$-Join" algorithm running over data indexed
in secondary memory. Our implementation outperforms the execution of the same
operation in Cypher and SPARQL on major existing graph database management
systems by at least one order of magnitude, also including indexing and loading
time.


  The CAT Imaging Telescope has observed the BL Lac object Markarian 501
between March and August 1997. We report here on the variability over this time
including several large flares. We present also preliminary spectra for all
these data, for the low emission state, and for the largest flare.


  The OPERA experiment has reported neutrinos, from the CNGS beam, that arrived
to Gran Sasso Laboratory 60ns earlier that expected for light, within a
statistical error margin of {\S}6:9 and a systemic error of {\S}7:4. Therefore,
these neutrinos are faster than known velocity of the light in vacuum. These
puzzling result could be explained by stimulated emission of neutrinos in the
decay tunnel, in close analogy with the amplification of a LASER pulse.


  We discuss the problem of characterizing "quantum disordered" ground states,
obtained upon loss of antiferromagnetic order on general lattices in two
spatial dimensions, with arbitrary electronic band structure. A key result is
the response in electron bilinears to the skyrmion density in the local
antiferromagnetic order, induced by geometric phases. We also discuss the
connection to topological terms obtained under situations where the electronic
spectrum has a Dirac form.


  We give an explicit combinatorial description of the multiplicity as well as
the Hilbert function of the tangent cone at any point on a Schubert variety in
the symplectic Grassmannian.


  The physics teaching particularly the optics teaching always have faced
motivational problems, mostly due to the loss of the link between the social
practice and the daily life of the student. Moreover, the laboratory practices
have lost space in high school attributable to a lack of resources or caused by
the fact that the main purpose of the high school is being no more than the
access to the University. This work shows how an extension activity called
"Holographic Exhibit" tries to motivate high school students by means of
experimentation, observation and the application of physics concepts in daily
life, awakening their interests to the general physics.
  La ensenanza de la fisica y en particular de la optica siempre ha enfrentado
problemas de aspecto motivacional principalmente por la perdida del vinculo con
la practica social y con la vida cotidiana del estudiante. Ademas, las
practicas de laboratorio han perdido mucho espacio en la ensenanza media por
carencias de las escuelas o debido a que tiene apenas como objeto el examen de
ingreso a la universidad. El objetivo de este trabajo es mostrar como una
actividad de extensi\'on universitaria llamada 'Exposicion de Holografia'
intenta motivar a estudiantes de ense\~nanza media a traves de la
experimentacion, observacion y aplicacion de conceptos fisicos en la vida
cotidiana, despertando sus intereses por la f\'isica general.


  With the fast growing number of wireless devices and demand of user data, the
backhaul load becomes a bottleneck in wireless networks. Physical layer network
coding (PNC) allows Access Points (APs) to relay compressed, network coded user
data, therefore reducing the backhaul traffic. In this paper, an implementation
of uplink Network Coded Modulation (NetCoM) with PNC is presented. A 5-node
prototype NetCoM system is established using Universal Software Radio
Peripherals (USRPs) and a practical PNC scheme designed for binary systems is
utilised. An orthogonal frequency division multiplexing (OFDM) waveform
implementation and the practical challenges (e.g. device synchronisation and
clock drift) of applying OFDM to NetCoM are discussed. To the best of our
knowledge this is the first PNC implementation in an uplink scenario in radio
access networks and our prototype provides an industrially-applicable
implementation of the proposed NetCoM with PNC approach.


  An index theorem for the anti-self-dual deformation complex on anti-self-dual
orbifolds with singularities conjugate to ADE-type is proved. In 1988, Claude
Lebrun gave examples of scalar-flat K\"ahler ALE metrics with negative mass, on
the total space of the bundle $\mathcal{O}(-n)$ over $S^2$. A corollary of this
index theorem is that the moduli space of anti-self-dual ALE metrics near each
of these metrics has dimension at least $4n-12$, and thus for $n \geq 4$ the
LeBrun metrics admit a plethora of non-trivial anti-self-dual deformations.


  Decoherence effects on the traditional N vs. M photon coherent control of a
two-level system are investigated, with 1 vs. 3 used as a specific example. The
problem reduces to that of a two-level system interacting with a single mode
field, but with an effective Rabi frequency that depends upon the fundamental
and third harmonic fields. The resultant analytic control solution is explored
for a variety of parameters, with emphasis on the dependence of control on the
relative phase of the lasers. The generalization to off-resonant cases is
noted.


  This is a review paper for the "Current Developments in Mathematics 2014"
conference.


  Simulation of spiking neural networks has been traditionally done on
high-performance supercomputers or large-scale clusters. Utilizing the parallel
nature of neural network computation algorithms, GeNN (GPU Enhanced Neural
Network) provides a simulation environment that performs on General Purpose
NVIDIA GPUs with a code generation based approach. GeNN allows the users to
design and simulate neural networks by specifying the populations of neurons at
different stages, their synapse connection densities and the model of
individual neurons. In this report we describe work on how to scale synaptic
weights based on the configuration of the user-defined network to ensure
sufficient spiking and subsequent effective learning. We also discuss
optimization strategies particular to GPU computing: sparse representation of
synapse connections and occupancy based block-size determination.


  Analyzing ideology and polarization is of critical importance in advancing
our grasp of modern politics. Recent research has made great strides towards
understanding the ideological bias (i.e., stance) of news media along the
left-right spectrum. In this work, we instead take a novel and more nuanced
approach for the study of ideology based on its left or right positions on the
issue being discussed. Aligned with the theoretical accounts in political
science, we treat ideology as a multi-dimensional construct, and introduce the
first diachronic dataset of news articles whose ideological positions are
annotated by trained political scientists and linguists at the paragraph level.
We showcase that, by controlling for the author's stance, our method allows for
the quantitative and temporal measurement and analysis of polarization as a
multidimensional ideological distance. We further present baseline models for
ideology prediction, outlining a challenging task distinct from stance
detection.


  Let $u$ be a harmonic function in a $C^1$ domain $D\subset \mathbb{R}^d$,
which vanishes on an open subset of the boundary. In this note we study its
critical set $\{x \in \overline{D}: \nabla u(x) = 0 \}$. When $D$ is a
$C^{1,\alpha}$ domain for some $\alpha \in (0,1]$, we give an upper bound on
the $(d-2)$-dimensional Hausdorff measure of the critical set by the frequency
function. We also discuss possible ways to extend such estimate to all
$C^1$-Dini domains, the optimal class of domains for which analogous estimates
have been shown to hold for the singular set $\{x \in \overline{D}: u(x) = 0 =
|\nabla u(x)| \}$ (see [KZ1, KZ2]).


  Prony mapping provides the global solution of the Prony system of equations
\[ \Sigma_{i=1}^{n}A_{i}x_{i}^{k}=m_{k},\ k=0,1,...,2n-1. \] This system
appears in numerous theoretical and applied problems arising in Signal
Reconstruction. The simplest example is the problem of reconstruction of linear
combination of $\delta$-functions of the form
$g(x)=\sum_{i=1}^{n}a_{i}\delta(x-x_{i})$, with the unknown parameters $a_{i},\
x_{i},\ i=1,...,n,$ from the "moment measurements" $m_{k}=\int x^{k}g(x)dx.$
  Global solution of the Prony system, i.e. inversion of the Prony mapping,
encounters several types of singularities. One of the most important ones is a
collision of some of the points $x_{i}.$ The investigation of this type of
singularities has been started in \cite{yom2009Singularities} where the role of
finite differences was demonstrated.
  In the present paper we study this and other types of singularities of the
Prony mapping, and describe its global geometry. We show, in particular, close
connections of the Prony mapping with the "Vieta mapping" expressing the
coefficients of a polynomial through its roots, and with hyperbolic polynomials
and "Vandermonde mapping" studied by V. Arnold.


  The recently developed stochastic gradient method combined with Monte Carlo
sampling techniques [PRB {\bf 95}, 195154 (2017)] offers a low scaling and
accurate method to optimize the projected entangled pair states (PEPS). We
extended this method to the fermionic PEPS (fPEPS). To simplify the
implementation, we introduce a fermi arrow notation to specify the order of the
fermion operators in the virtual entangled EPR pairs. By defining some local
operation rules associated with the fermi arrows, one can implement fPEPS
algorithms very similar to that of standard PEPS. We benchmark the method for
the interacting spinless fermion models, and the t-J models. The numerical
calculations show that the gradient optimization greatly improves the results
of simple update method. Furthermore, much larger virtual bond dimensions ($D$)
and truncation dimensions ($D_c$) than those of boson and spin systems are
necessary to converge the results. The method therefore offer a powerful tool
to simulate fermion systems because it has much lower scaling than the direct
contraction methods.


  This work investigates the use of Neural implicit representations,
specifically Neural Radiance Fields (NeRF), for geometrical queries and motion
planning. We show that by adding the capacity to infer occupancy in a radius to
a pre-trained NeRF, we are effectively learning an approximation to a Euclidean
Signed Distance Field (ESDF). Using backward differentiation of the augmented
network, we obtain an obstacle gradient that is integrated into an obstacle
avoidance policy based on the Riemannian Motion Policies (RMP) framework. Thus,
our findings allow for very fast sampling-free obstacle avoidance planning in
the implicit representation.


  This paper presents a flexible standalone, low-cost smart home system, which
is based on the Android app communicating with the micro-web server providing
more than the switching functionalities. The Arduino Ethernet is used to
eliminate the use of a personal computer (PC) keeping the cost of the overall
system to a minimum while voice activation is incorporated for switching
functionalities. Devices such as light switches, power plugs, temperature
sensors, humidity sensors, current sensors, intrusion detection sensors,
smoke/gas sensors and sirens have been integrated in the system to demonstrate
the feasibility and effectiveness of the proposed smart home system. The smart
home app is tested and it is able to successfully perform the smart home
operations such as switching functionalities, automatic environmental control
and intrusion detection, in the later case where an email is generated and the
siren goes on.


  We describe the periodic orbits of the prefractal Koch snowflake billiard
(the nth inner rational polygonal approximation of the Koch snowflake
billiard). In the case of the finite (prefractal) billiard table, we focus on
the direction given by an initial angle of pi/3, and define 1) a compatible
sequence of piecewise Fagnano orbits, 2) an eventually constant compatible
sequence of orbits and 3) a compatible sequence of generalized piecewise
Fagnano orbits. In the case of the infinite (fractal) billiard table, we will
describe what we call stabilizing periodic orbits of the Koch snowflake fractal
billiard. In a sense, we show that it is possible to define billiard dynamics
on a Cantor set. In addition, we will show that the inverse limit of the
footprints of orbits of the prefractal approximations exists in a specific
situation and provide a plausibility argument as to why such an inverse limit
of footprints should constitute the footprint of a well-defined periodic orbit
of the fractal billiard. Using known results for the inverse limit of a
sequence of finite spaces, we deduce that the footprint (i.e., the intersection
of the orbit with the boundary) of a piecewise Fagnano orbit is a topological
Cantor set and a self-similar Cantor set. We allude to a possible
characterization of orbits with an initial direction of pi/3. Such a
characterization would allow one to describe an orbit with an initial direction
of pi/3 of the Koch snowflake billiard as either a piecewise Fagnano orbit, a
stabilizing orbit or a generalized piecewise Fagnano orbit. We then close the
paper by discussing several outstanding open problems and conjectures about the
Koch snowflake fractal billiard, the associated 'fractal flat surface', and
possible connections with the associated fractal drum. In the long-term, the
present work may help lay the foundations for a general theory of fractal
billiards.


  We give a bound on the order of the Schur multiplier of $p$-groups refining
earlier bounds. As an application we complete the classification of groups
having Schur multiplier of maximum order. Finally we prove that the order of
the Schur multiplier of a finite $p$-group of maximal class and order $p^n$ is
at most $p^{\frac{n}{2}}$.


  The Chermak-Delgado lattice of a finite group is a dual, modular sublattice
of the subgroup lattice of the group. This paper considers groups with a
quasi-antichain interval in the Chermak-Delgado lattice, ultimately proving
that if there is a quasi-antichain interval between $L$ and $H$ with $L \leq H$
then there exists a prime $p$ such that the quotient $H / L$ is an elementary
abelian $p$-group and the number of atoms in the quasi-antichain is one more
than a power of $p$. In the case where the Chermak-Delgado lattice of the
entire group is a quasi-antichain, the relationship between the number of
abelian atoms and the prime $p$ is examined; additionally several examples of
group with a quasi-antichain Chermak-Delgado lattice are constructed.


  In this report, we describe our Transformers for euphemism detection baseline
(TEDB) submissions to a shared task on euphemism detection 2022. We cast the
task of predicting euphemism as text classification. We considered
Transformer-based models which are the current state-of-the-art methods for
text classification. We explored different training schemes, pretrained models,
and model architectures. Our best result of 0.816 F1-score (0.818 precision and
0.814 recall) consists of a euphemism-detection-finetuned
TweetEval/TimeLMs-pretrained RoBERTa model as a feature extractor frontend with
a KimCNN classifier backend trained end-to-end using a cosine annealing
scheduler. We observed pretrained models on sentiment analysis and
offensiveness detection to correlate with more F1-score while pretraining on
other tasks, such as sarcasm detection, produces less F1-scores. Also, putting
more word vector channels does not improve the performance in our experiments.


  The present work proposes a new approach to energy effiency for filtering of
a system interconnected by a Multi-Hop network. The minimization of the energy
cost per time unit is obtained through limiting the number of packets
retransmission in the Hop-by-Hop mechanism. We explore a trade-Off between
system performance, measured by estimation error H-inf norm and energy
consumption. The proposal is validated using a theoretical model for energy
consumption of MICA2 transceivers.


  Many nearby stars are surrounded by a bright ring or disk of cold dust. Our
calculations show that these disks and rings of dust are signposts of recent
planet formation. Bright rings appear because dust associated with the
formation of a planet absorbs and scatters light from the central star. The
calculations explain the rings observed so far and predict that all nascent
solar systems have dusty rings.


  Deconvolution of large survey images with millions of galaxies requires to
develop a new generation of methods which can take into account a space variant
Point Spread Function (PSF) and have to be at the same time accurate and fast.
We investigate in this paper how Deep Learning (DL) could be used to perform
this task. We employ a U-Net Deep Neural Network (DNN) architecture to learn in
a supervised setting parameters adapted for galaxy image processing and study
two strategies for deconvolution. The first approach is a post-processing of a
mere Tikhonov deconvolution with closed form solution and the second one is an
iterative deconvolution framework based on the Alternating Direction Method of
Multipliers (ADMM). Our numerical results based on GREAT3 simulations with
realistic galaxy images and PSFs show that our two approaches outperforms
standard techniques based on convex optimization, whether assessed in galaxy
image reconstruction or shape recovery. The approach based on Tikhonov
deconvolution leads to the most accurate results except for ellipticity errors
at high signal to noise ratio where the ADMM approach performs slightly better,
is also more computation-time efficient to process a large number of galaxies,
and is therefore recommended in this scenario.


  To support the understanding of declarative probabilistic programming
languages, we introduce a lambda-calculus with a fair binary probabilistic
choice that chooses between its arguments with equal probability. The reduction
strategy of the calculus is a call-by-need strategy that performs lazy
evaluation and implements sharing by recursive let-expressions. Expected
convergence of expressions is the limit of the sum of all successful reduction
outputs weighted by their probability. We use contextual equivalence as program
semantics: two expressions are contextually equivalent if and only if the
expected convergence of the expressions plugged into any program context is
always the same. We develop and illustrate techniques to prove equivalences
including a context lemma, two derived criteria to show equivalences and a
syntactic diagram-based method. This finally enables us to show correctness of
a large set of program transformations with respect to the contextual
equivalence.


  The hierarchy of commuting maps related to a set-theoretical solution of the
quantum Yang-Baxter equation (Yang-Baxter map) is introduced. They can be
considered as dynamical analogues of the monodromy and/or transfer-matrices.
The general scheme of producing Yang-Baxter maps based on matrix factorisation
is discussed in the context of the integrability problem for the corresponding
dynamical systems. Some examples of birational Yang-Baxter maps coming from the
theory of the periodic dressing chain and matrix KdV equation are discussed.


  Low latency and accuracy are fundamental requirements when vision is
integrated in robots for high-speed interaction with targets, since they affect
system reliability and stability. In such a scenario, the choice of the sensor
and algorithms is important for the entire control loop. The technology of
event-cameras can guarantee fast visual sensing in dynamic environments, but
requires a tracking algorithm that can keep up with the high data rate induced
by the robot ego-motion while maintaining accuracy and robustness to
distractors. In this paper, we introduce a novel tracking method that leverages
the Exponential Reduced Ordinal Surface (EROS) data representation to decouple
event-by-event processing and tracking computation. The latter is performed
using convolution kernels to detect and follow a circular target moving on a
plane. To benchmark state-of-the-art event-based tracking, we propose the task
of tracking the air hockey puck sliding on a surface, with the future aim of
controlling the iCub robot to reach the target precisely and on time.
Experimental results demonstrate that our algorithm achieves the best
compromise between low latency and tracking accuracy both when the robot is
still and when moving.


  We introduce a non-parametric method to recover physical probability
distributions of asset returns based on their European option prices and some
other sparse parametric information. Thus the main problem is similar to the
one considered foir instance in the Recovery Theorem by Ross (2015), except
that here we consider a non-dynamical setting. The recovery of the distribution
is complete, instead of estimating merely a finite number of its parameters,
such as implied volatility, skew or kurtosis. The technique is based on a
reverse application of recently introduced Distribution Matching by the author
and is related to the ideas in Distribution Pricing by Dybvig (1988) as well as
comonotonicity.


  Following two dictums roadmap of Einstein (one, for incorporation of maximum
of empirical facts, and the other, on long continued experimental verifications
for perfecting a scientific theory) for future generations to make his General
Relativity Theory (GRT) evolve to perfection, it is necessary to experimentally
confirm his concept on General relativistic nature of speed of light, c, which
relates to the variation of c under the influence of gravitational field, and
whose experimental confirmation is long overdue.
  This paper gives the Execution and some Additional Details for the Space
Experiment Proposed for GRT, so that any of the Space research organizations
(viz., NASA, ESA, ASI, ISRO, etc.) would conduct this low cost experiment,
during Space missions to Mercury, Venus, or the sun, or may choose to conduct
it as an independent space mission as the cost may be brought down by sending
micro satellites using the launch sharing facility of any other lending
country. Even an advanced country may conduct this experiment at low cost by
sending a micro satellite (called a co-passenger satellite) by arranging with
the Space research organization of any lending country, which is sending a
primary satellite for a space mission to any of the desired locations.
  At present, even a small country interested in making a historic contribution
for making GRT of Einstein evolve, but not having a Space research
organization, may contract with an experienced organization, or hire the
services of an experienced project director who
  * can organize the planning, procurement, and launching of a micro satellite
carrying the laser device, from launch pad of another country (adopting the
piggy back launching method), and
  * can guide (else, can hire the services of a Principal Investigator, from
some renowned institute) remote operation of the laser device for a few days.


  A glance at recent research on magnetism turns up a curious set of articles
discussing, or claiming evidence for, a state of matter called a quantum spin
liquid (QSL). These articles are notable in their invocation of exotic notions
of topological physics, quantum entanglement, fractional quantum numbers, anyon
statistics and gauge field theories. So what is a QSL and why do we need this
complicated technical vocabulary to describe it? Our aim in this article is to
introduce some of these concepts and provide a discussion of what a QSL is,
where it might occur in Nature and why it is of interest. As we'll see, this is
a rich subject which is still in development, and unambiguous evidence for the
realisation of the QSL state in a magnetic material remains hotly debated.
However, the payoff in terms of the special nature of quantum entanglement in
the QSL, and its diverse spectrum of unusual excitations and topological status
will (at least to some extent) justify the need to engage with some powerful,
occasionally abstract, technical material.


  If the cosine of a rational multiple of $\pi$ is a rational number then it is
an integral multiple of $\frac12$. For this fact, we give a proof accessible to
an interested school student. We then discuss which quadratic and cubic
irrationalities are values of cosine at ratinal multiples of $\pi$.


  A reported weakness of C4.5 in domains with continuous attributes is
addressed by modifying the formation and evaluation of tests on continuous
attributes. An MDL-inspired penalty is applied to such tests, eliminating some
of them from consideration and altering the relative desirability of all tests.
Empirical trials show that the modifications lead to smaller decision trees
with higher predictive accuracies. Results also confirm that a new version of
C4.5 incorporating these changes is superior to recent approaches that use
global discretization and that construct small trees with multi-interval
splits.


  We introduce a novel approach to investigate CP violation in the neutrino
sector, based on the simultaneous detection of $\nu_e$ and $\bar{\nu}_e$
stemming from the oscillation of $\nu_{\mu}$ and $\bar{\nu}_{\mu}$ produced in
the decay at rest of $\pi$s and $\mu$s at a beam dump. This approach relies on
a novel liquid scintillator detector technology expected to yield unprecedented
identification of $\nu_e$ and $\bar{\nu}_e$ charged-current interactions, which
we investigate by means of Montecarlo simulations. Here we report preliminary
results concerning both the detection technique and its physics reach.


  Various modified quantum teleportation schemes are proposed to overcome
experimental constraints or to meet specific application requirements for
quantum communication. Hence, most schemes are developed and studied with
unique methodologies, each with its inherent challenges. Our research focuses
on interconnecting these schemes appearing to be unrelated to each other, based
on the idea that the unique advantages of one scheme can compensate for the
limitations of another. In this paper, we introduce an asymptotic teleportation
scheme requiring the receiver to perform a classical selection task followed by
a quantum correction. This scheme bridges standard teleportation with
port-based teleportation through the transformation of joint measurements.
Specifically, we categorize and analytically investigate protocols within this
scheme for qubit systems. Given that linear optics teleportation protocol
without ancilla qubits is contained in the two non-trivial groups, we provide a
novel perspective on its expansion. Furthermore, we discuss the potential
application of a protocol from one of these groups as a universal programmable
processor and extend these protocols to higher-dimensional systems while
maintaining the same properties and potential, providing the analytic form of
the joint measurement and its performance. These results thereby propose new
avenues for developing a quantum network in higher-dimensional systems.


  In spin chains with local unitary evolution preserving the magnetization
$S^{\rm z}$, the domain-wall state $\left| \dots \uparrow \uparrow \uparrow
\uparrow \uparrow \downarrow \downarrow \downarrow \downarrow \downarrow \dots
\right>$ typically "melts". At large times, a non-trivial magnetization profile
develops in an expanding region around the initial position of the domain-wall.
For non-integrable dynamics the melting is diffusive, with entropy production
within a melted region of size $\sqrt{t}$. In contrast, when the evolution is
integrable, ballistic transport dominates and results in a melted region
growing linearly in time, with no extensive entropy production: the spin chain
remains locally in states of zero entropy at any time. Here we show that, for
the integrable spin-$1/2$ XXZ chain, low-energy quantum fluctuations in the
melted region give rise to an emergent Luttinger liquid which, remarkably,
differs from the equilibrium one. The striking feature of this emergent
Luttinger liquid is its quasi-particle charge (or Luttinger parameter $K$)
which acquires a fractal dependence on the XXZ chain anisotropy parameter
$\Delta$.


  In light of the cosmological observations, we investigate dark energy models
from the Horndeski theory of gravity. In particular, we consider cosmological
models with the derivative self-interaction of the scalar field and the
derivative coupling between the scalar field and gravity. We choose the
self-interaction term to have an exponential function of the scalar field with
both positive and negative exponents. For the function that has a positive
exponent, our result shows that the derivative self-interaction term plays an
important role in the late-time universe. On the other hand, to reproduce the
right cosmic history, the derivative coupling between the scalar field and
gravity must dominate during the radiation-dominated phase. However, the
importance of such a coupling in the present universe found to be negligible
due to its drastic decrease over time. Moreover, the propagation speed of
gravitational waves estimated for our model is within the observational bounds,
and our model satisfies the observational constraints on the dark energy
equation of state.


  We perform a lattice Monte-Carlo calculation of the trace-anomaly two-point
function at finite temperature in the SU(3) gauge theory. We obtain the
long-distance properties of the correlator in the continuum limit and extract
the bulk viscosity zeta via a Kubo formula. Unlike the tensor correlator
relevant to the shear viscosity, the scalar correlator depends strongly on
temperature. If s is the entropy density, we find that zeta/s becomes rapidly
small at high T, zeta/s<0.15 at 1.65T_c and zeta/s<0.015 at 3.2T_c. However
zeta/s rises dramatically just above T_c, with 0.5<zeta/s<2.0 at 1.02T_c.