  A key element in transfer learning is representation learning; if
representations can be developed that expose the relevant factors underlying
the data, then new tasks and domains can be learned readily based on mappings
of these salient factors. We propose that an important aim for these
representations are to be unbiased. Different forms of representation learning
can be derived from alternative definitions of unwanted bias, e.g., bias to
particular tasks, domains, or irrelevant underlying data dimensions. One very
useful approach to estimating the amount of bias in a representation comes from
maximum mean discrepancy (MMD) [5], a measure of distance between probability
distributions. We are not the first to suggest that MMD can be a useful
criterion in developing representations that apply across multiple domains or
tasks [1]. However, in this paper we describe a number of novel applications of
this criterion that we have devised, all based on the idea of developing
unbiased representations. These formulations include: a standard domain
adaptation framework; a method of learning invariant representations; an
approach based on noise-insensitive autoencoders; and a novel form of
generative model.


  Unlike the previous theoretical results based on standard quantum mechanics
that has established the nearly elliptical shapes for the centre-of-mass motion
using numerical simulations, we show analytically that the Bohmian trajectories
in Rydberg atoms are nearly elliptical.


  In this study, we propose a modulation decoupling based single channel speech
enhancement subspace framework, in which the spectrogram of noisy speech is
decoupled as the product of a spectral envelop subspace and a spectral details
subspace. This decoupling approach provides a method to specifically work on
elimination of those noises that greatly affect the intelligibility. Two
supervised low-rank and sparse decomposition schemes are developed in the
spectral envelop subspace to obtain a robust recovery of speech components. A
Bayesian formulation of non-negative factorization is used to learn the speech
dictionary from the spectral envelop subspace of clean speech samples. In the
spectral details subspace, a standard robust principal component analysis is
implemented to extract the speech components. The validation results show that
compared with four speech enhancement algorithms, including MMSE-SPP, NMF-RPCA,
RPCA, and LARC, the proposed MS based algorithms achieve satisfactory
performance on improving perceptual quality, and especially speech
intelligibility.


  We consider a basic one-dimensional model of diffusion which allows to obtain
a diversity of diffusive regimes whose speed depends on the moments of the
per-site trapping time. This model is closely related to the continuous time
random walks widely studied in the literature. The model we consider lends
itself to a detailed treatment, making it possible to study deviations from
normality due to finite time effects.


  In some particular cases we give criteria for morphic sequences to be almost
periodic (=uniformly recurrent). Namely, we deal with fixed points of
non-erasing morphisms and with automatic sequences. In both cases a
polynomial-time algorithm solving the problem is found. A result more or less
supporting the conjecture of decidability of the general problem is given.


  Effective potential of a charged dusty particle moving in homogeneous plasma
has a negative part that provides attraction between similarly charged dusty
particles. A depth of this potential well is great enough to ensure both
stability of crystal structure of dusty plasma and sizable value of surface
tension of a boundary surface of dusty region. The latter depends on the
orientation of the surface relative to the counter-ion flow, namely, it is
maximal and positive for the surface normal to the flow and minimal and
negative for the surface along the flow. For the most cases of dusty plasma in
a gas discharge, a value of the first of them is more than sufficient to ensure
stability of lenticular dusty phase void oriented across the counter-ion flow.


  We study the spectral properties of sparse random graphs with different
topologies and type of interactions, and their implications on the stability of
complex systems, with particular attention to ecosystems. Specifically, we
focus on the behaviour of the leading eigenvalue in different type of random
matrices (including interaction matrices and Jacobian-like matrices), relevant
for the assessment of different types of dynamical stability. By comparing the
results on Erdos-Renyi and Husimi graphs with sign-antisymmetric interactions
or mixed sign patterns, we introduce a sufficient criterion, called strong
local sign stability, for stability not to be affected by system size, as
traditionally implied by the complexity-stability trade-off in conventional
models of random matrices. The criterion requires sign-antisymmetric or
unidirectional interactions and a local structure of the graph such that the
number of cycles of finite length do not increase with the system size. Note
that the last requirement is stronger than the classical local tree-like
condition, which we associate to the less stringent definition of local sign
stability, also defined in the paper. In addition, for strong local sign stable
graphs which show stability to linear perturbations irrespectively of system
size, we observe that the leading eigenvalue can undergo a transition from
being real to acquiring a nonnull imaginary part, which implies a dynamical
transition from nonoscillatory to oscillatory linear response to perturbations.
Lastly, we ascertain the discontinuous nature of this transition.


  We define some notions of the decentralization of a deterministic
input-output machine. This opens the possibility for introducing game-theoretic
elements -- such as strategic players -- inside the machine, as part of its
design.


  The $n$-queens problem is to determine $\mathcal{Q}(n)$, the number of ways
to place $n$ mutually non-threatening queens on an $n \times n$ board. We show
that there exists a constant $\alpha = 1.942 \pm 3 \times 10^{-3}$ such that
$\mathcal{Q}(n) = ((1 \pm o(1))ne^{-\alpha})^n$. The constant $\alpha$ is
characterized as the solution to a convex optimization problem in
$\mathcal{P}([-1/2,1/2]^2)$, the space of Borel probability measures on the
square.
  The chief innovation is the introduction of limit objects for $n$-queens
configurations, which we call queenons. These form a convex set in
$\mathcal{P}([-1/2,1/2]^2)$. We define an entropy function that counts the
number of $n$-queens configurations that approximate a given queenon. The upper
bound uses the entropy method of Radhakrishnan and Linial--Luria. For the lower
bound we describe a randomized algorithm that constructs a configuration near a
prespecified queenon and whose entropy matches that found in the upper bound.
The enumeration of $n$-queens configurations is then obtained by maximizing the
(concave) entropy function in the space of queenons.
  Along the way we prove a large deviations principle for $n$-queens
configurations that can be used to study their typical structure.


  Context: This paper investigates the effectiveness of phase mixing as a
coronal heating mechanism. A key quantity is the wave damping rate, $\gamma$,
defined as the ratio of the heating rate to the wave energy.
  Aims: We investigate whether or not laminar phase-mixed Alfv\'en waves can
have a large enough value of $\gamma$ to heat the corona. We also investigate
the degree to which the $\gamma$ of standing Alfv\'en waves which have reached
steady-state can be approximated with a relatively simple equation. Further
foci of this study are the cause of the reduction of $\gamma$ in response to
leakage of waves out of a loop, the quantity of this reduction, and how
increasing the number of excited harmonics affects $\gamma$.
  Results: We find that at observed frequencies $\gamma$ is too small to heat
the corona by approximately three orders of magnitude. Therefore, we believe
that laminar phase mixing is not a viable stand-alone heating mechanism for
coronal loops. We show that $\gamma$ is largest at resonance. We find our
simple equation provides a good estimate for the damping rate (within
approximately 10% accuracy) for resonant field lines. However, away from
resonance, the equation provides a poor estimate, predicting $\gamma$ to be
orders of magnitude too large. We find that leakage acts to reduce $\gamma$ but
plays a negligible role if $\gamma$ is of the order required to heat the
corona. If the wave energy follows a power spectrum with slope -5/3 then
$\gamma$ grows logarithmically with the number of excited harmonics. If the
number of excited harmonics is increased by much more than 100, then the
heating is mainly caused by gradients that are parallel to the field rather
than perpendicular to it. Therefore, in this case, the system is not heated
mainly by phase mixing.


  We test the validity of Hanle measurements in three-terminal devices by using
aluminum (Al) and gold (Au). The obtained Hanle and inverted Hanle-like curves
show an anomalous behavior. First, we measure Hanle signals 8 orders of
magnitude larger than those predicted by standard theory. Second, the
temperature and voltage dependences of the signal do not match with the
tunneling spin polarization of the ferromagnetic contact. Finally, the spin
relaxation times obtained with this method are independent of the choice of the
metallic channel. These results are not compatible with spin accumulation in
the metal. Furthermore, a scaling of the Hanle signal with the interface
resistance of the devices suggests that the measured signal is originated in
the tunnel junction.


  We present a method for symbolic calculation of Feynman amplitudes for
processes involving both massless and massive fermions. With this approach
fermion strings in a specific amplitude can be easily evaluated and expressed
as basic Lorentz scalars. The new approach renders the symbolic calculation of
some complicated physical processes more feasible and easier, especially with
the assistance of algebra manipulating codes for computer.


  It is classical that uniform stabilization of solutions to the autonomous
damped wave equation is equivalent to every geodesic meeting the positive set
of the damping, which is called the geometric control condition. In this paper,
it is shown that for time-dependent damping, a generalization of the geometric
control condition is equivalent to uniform stabilization at an exponential
rate. Additionally, non-exponential uniform stabilization rates are computed
for damping which do not satisfy this geometric control condition. Decay rates
are guaranteed via an observability argument, including a new uniform
time-dependent observability inequality. Bounds on decay rates are proved via a
Gaussian beam construction.


  So far different studies have tackled the sentiment analysis in several
domains such as restaurant and movie reviews. But, this problem has not been
studied in scholarly book reviews which is different in terms of review style
and size. In this paper, we propose to combine different features in order to
be presented to a supervised classifiers which extract the opinion target
expressions and detect their polarities in scholarly book reviews. We construct
a labeled corpus for training and evaluating our methods in French book
reviews. We also evaluate them on English restaurant reviews in order to
measure their robustness across the domains and languages. The evaluation shows
that our methods are enough robust for English restaurant reviews and French
book reviews.


  Cartograms are maps that rescale geographic regions (e.g., countries,
districts) such that their areas are proportional to quantitative demographic
data (e.g., population size, gross domestic product). Unlike conventional bar
or pie charts, cartograms can represent correctly which regions share common
borders, resulting in insightful visualizations that can be the basis for
further spatial statistical analysis. Computer programs can assist data
scientists in preparing cartograms, but developing an algorithm that can
quickly transform every coordinate on the map (including points that are not
exactly on a border) while generating recognizable images has remained a
challenge. Methods that translate the cartographic deformations into
physics-inspired equations of motion have become popular, but solving these
equations with sufficient accuracy can still take several minutes on current
hardware. Here we introduce a flow-based algorithm whose equations of motion
are numerically easier to solve compared with previous methods. The equations
allow straightforward parallelization so that the calculation takes only a few
seconds even for complex and detailed input. Despite the speedup, the proposed
algorithm still keeps the advantages of previous techniques: with comparable
quantitative measures of shape distortion, it accurately scales all areas,
correctly fits the regions together and generates a map projection for every
point. We demonstrate the use of our algorithm with applications to the 2016 US
election results, the gross domestic products of Indian states and Chinese
provinces, and the spatial distribution of deaths in the London borough of
Kensington and Chelsea between 2011 and 2014.


  We release a realistic, diverse, and challenging dataset for object detection
on images. The data was recorded at a beer tent in Germany and consists of 15
different categories of food and drink items. We created more than 2,500 object
annotations by hand for 1,110 images captured by a video camera above the
checkout. We further make available the remaining 600GB of (unlabeled) data
containing days of footage. Additionally, we provide our trained models as a
benchmark. Possible applications include automated checkout systems which could
significantly speed up the process.


  We present a QCD analysis of the neutral current neutrino-nucleus interaction
at the small-x region using the color dipole formalism. This phenomenological
approach is quite successful in describing experimental results in deep
inelastic ep scattering and charged current neutrino-nucleus interactions at
high energies. We present theoretical predictions for the relevant structure
functions and the corresponding implications for the total NC neutrino cross
section.


  We present a new self-regulating methodology for coordinating distributed
team work called Algorithmic Autoregulation (AA), based on recent social
networking concepts and individual merit. Team members take on an egalitarian
role, and stay voluntarily logged into so-called AA sessions for part of their
time (e.g. 2 hours per day), during which they create periodical logs - short
text sentences - they wish to share about their activity with the team. These
logs are publicly aggregated in a website and are peer-validated after the end
of a session, as in code review. A short screencast is ideally recorded at the
end of each session to make AA logs more understandable. This methodology has
shown to be well-suited for increasing the efficiency of distributed teams
working on Global Software Development (GSD), as observed in our reported
experience in actual real-world situations. This efficiency boost is mainly
achieved through 1) built-in asynchronous on-demand communication in
conjunction with documentation of work, products, and processes, and 2) reduced
need for central management, meetings or time-consuming reports. Hence, the AA
methodology legitimizes and facilitates the activities of a distributed
software team. It thus enables other entities to have a solid means to fund
these activities, allowing for new and concrete business models to emerge for
very distributed software development. AA has been proposed, at its core, as a
way of sustaining self-replicating hacker initiatives. These claims are
discussed in a real case-study of running a distributed free software hacker
team called Lab Macambira.


  We present a framework for modeling astrophysical pulses from radio pulsars
and fast radio bursts (FRBs). This framework, called fitburst, generates
synthetic representations of dynamic spectra that are functions of several
physical and heuristic parameters; the heuristic parameters can nonetheless
accommodate a vast range of distributions in spectral energy. fitburst is
designed to optimize the modeling of features induced by effects that are
intrinsic and extrinsic to the emission mechanism, including the magnitude and
frequency dependence of pulse dispersion and scatter-broadening. fitburst
removes intra-channel smearing through two-dimensional upsampling, and can
account for phase wrapping of "folded" signals that are typically acquired
during pulsar-timing observations. We demonstrate the effectiveness of fitburst
in modeling data containing pulsars and FRBs observed with the Canadian
Hydrogen Intensity Mapping Experiment (CHIME) telescope.


  In the course of seeking the microscopic mechanism of superconductivity in
cuprate high temperature superconductors, the pseudogap phase\textemdash the
very abnormal 'normal' state on the hole-doped side\textemdash has proven to be
as big of a quandary as superconductivity itself. Angle-resolved photoemission
spectroscopy (ARPES) is a powerful tool for assessing the momentum-dependent
phenomenology of the pseudogap, and recent technological developments have
permitted a more detailed understanding. This report reviews recent progress in
understanding the relationship between superconductivity and the pseudogap, the
Fermi arc phenomena, and the relationship between charge order and pseudogap
from the perspective of ARPES measurements.


  In this paper we show irreducibility and the strong Feller property for
transition probabilities of stochastic differential equations with jumps and
monotone coefficients. Thus, exponential ergodicity and the spectral gap for
the corresponding transition semigroups are obtained.


  The rise of big data has revolutionized data exploitation practices and led
to the emergence of new concepts. Among them, data lakes have emerged as large
heterogeneous data repositories that can be analyzed by various methods. An
efficient data lake requires a metadata system that addresses the many problems
arising when dealing with big data. In consequence, the study of data lake
metadata models is currently an active research topic and many proposals have
been made in this regard. However, existing metadata models are either tailored
for a specific use case or insufficiently generic to manage different types of
data lakes, including our previous model MEDAL. In this paper, we generalize
MEDAL's concepts in a new metadata model called goldMEDAL. Moreover, we compare
goldMEDAL with the most recent state-of-the-art metadata models aiming at
genericity and show that we can reproduce these metadata models with
goldMEDAL's concepts. As a proof of concept, we also illustrate that goldMEDAL
allows the design of various data lakes by presenting three different use
cases.


  We explore constraints on various new physics resonances from four top-quark
production based on current experimental data. Both light and heavy resonances
are studied in the work. A comparison of full width effect and narrow width
approximation is also made.


  Microstate geometries are proposed microstates of black holes which can be
described within supergravity. Even though their number may not reproduce the
full entropy of black holes with finite-sized horizons, they still offer a
glimpse into the microscopic structure of black holes. In this paper we
construct a new set of microstate geometries of the supersymmetric D1-D5-P
black hole, where the momentum charge is carried by a vector field, as seen
from the perspective of six-dimensional supergravity. To aid our construction,
we develop an algorithm which solves a complicated partial differential
equation using the regularity of the geometries. The new solutions are
asymptotically AdS$_3\times S^3$, and have a long, but finite AdS$_2$ throat
that caps off without ever developing a horizon. These microstate geometries
have a holographic interpretation as coherent superpositions of heavy states in
the boundary D1-D5 CFT. We identify the states which are dual to our newly
constructed solutions and carry out some basic consistency checks to support
our identification.


  The Integral Fluctuation Theorem for entropy production (IFT) is among the
few equalities that are known to be valid for physical systems arbitrarily
driven far from equilibrium. Microscopically, it can be understood as an
inherent symmetry for the fluctuating entropy production rate implying the
second law of thermodynamics. Here, we examine an IFT statistical estimator
based on regular sampling and discuss its limitations for nonequilibrium
systems, when sampling rare events becomes pivotal. Furthermore, via a large
deviation study, we discuss a method to carefully setup an experiment in the
parameter region where the IFT estimator safely converges and also show how to
improve the convergence region for Markov chains with finite correlation time.
We corroborate our arguments with two illustrative examples.


  Economics does not need a scientific revolution. Economics needs accurate
measurements according to high standards of natural sciences and meticulous
work on revealing empirical relationships between measured variables.


  In this work we study three exterior extension problems for strongly elliptic
partial equations: the Cauchy problem (in a special statement), the
"analytical" continuation problem and the so called "inner" Dirichlet problem
in the scale of the Sobolev spaces over a domain with relatively smooth
boundaries. We consider the existence of solutions to these problems, the dense
solvability and conditional well-posedness of these problems for a wide class
of strongly elliptic systems. We also consider the approximation of solutions
to these problems by a single layer potential and by a linear combination of
"discrete" fundamental solutions in relation to a narrower class of strongly
elliptic operators of the second order. The obtained results justify the
applicability of the indirect method of boundary integral equations and for
numerical solving the exterior extension problems.


  We introduce the active exploration problem in Markov decision processes
(MDPs). Each state of the MDP is characterized by a random value and the
learner should gather samples to estimate the mean value of each state as
accurately as possible. Similarly to active exploration in multi-armed bandit
(MAB), states may have different levels of noise, so that the higher the noise,
the more samples are needed. As the noise level is initially unknown, we need
to trade off the exploration of the environment to estimate the noise and the
exploitation of these estimates to compute a policy maximizing the accuracy of
the mean predictions. We introduce a novel learning algorithm to solve this
problem showing that active exploration in MDPs may be significantly more
difficult than in MAB. We also derive a heuristic procedure to mitigate the
negative effect of slowly mixing policies. Finally, we validate our findings on
simple numerical simulations.


  Employing a sapphire whispering gallery mode resonator, we demonstrate
features of the spin-photon interaction in cavities with broken time-reflection
symmetry. The broken symmetry leads to a lifting of the degeneracy between
left-handed and right-handed polarised cavity photons, which results in an
observable gyrotropic effect. In the high-$Q$ cavity limit, such a situation
requires a modification of the Tavis-Cummings Hamiltonian to take into account
conservation of spin angular momentum and the corresponding selection rules. As
a result, the system is represented by a system of two linearly coupled bosonic
modes, with each one coupled to its own sub-ensemble of two-level systems with
different energy splittings. In the experimental example, these sub-ensembles
originate from Fe$^{3+}$ impurity ions effectively seen as a two level systems
at the interaction frequency. The temperature dependence of the population of
each sub-ensemble (in terms of effective susceptibility of the medium) is
determined experimentally in accordance with the theoretical predictions
revealing various paramagnetic impurity types in the solid. The regimes of
backscatterer and spin ensemble domination are discussed and compared.


  The quantum charged rigid membrane model, which is a higher derivative theory
has been considered to explore its gauge symmetries using a recently developed
first order formalism \cite{BMP}. Hamiltonian analysis has been performed and
the gauge symmetry of the model is identified as reparametrisation symmetry.
First class constraints are shown to have a truncated Virasoro algebraic
structure. An exact correspondence between the higher derivative theory and the
first order formalism has been shown from the point of view of equations of
motion.


  We show that for an orientable non-spin manifold with fundamental group
$\mathbb{Z}_2$ and universal cover $S^2\times S^3,$ the moduli space of metrics
of nonnegative sectional curvature has infinitely many path components. The
representatives of the components are quotients of the standard metric on
$S^3\times S^3$ or metrics on Brieskorn varieties previously constructed using
cohomogeneity one actions. The components are distinguished using the relative
$\eta$ invariant of the spin$^c$ Dirac operator computed by means of a
Lefschetz fixed point theorem.


  The mass of an electroweakly charged lepton consists of the two components of
electric and weak nature, and regardless of the difference in masses, all
leptons have an equal charge, the same charge radius as well as an identical
magnetic moment. Between these currents there appear the most diverse
connections, for example, in their interactions with an electroweak field of
spinless nuclei. We derive the united equations which relate the structural
parts of mass to charge, charge radius and magnetic moment of each lepton as a
consequence of the ideas of flavor symmetry laws. Therefore, these ideas
require the verification of the lepton universality from the point of view of a
constancy of the size implied from the multiplication of a weak mass of lepton
by its electric mass. Such a principle gives the possibility to define the
lepton weak masses. If this picture does not change, leptons universally
interact not only with the photon or the weak boson but also with any of the
corresponding types of gauge fields.


  Recent theoretical efforts aimed at understanding the nature of
antiferromagnetic ordering in GdNi2B2C predicted double-q ordering. Here we
employ resonant elastic x-ray scattering to test this theory against the
formerly proposed, single-q ordering scenario. Our study reveals a satellite
reflection associated with a mixed-order component propagation wave vector,
viz., (q_a,2q_b,0) with q_b = q_a approx= 0.55 reciprocal lattice units, the
presence of which is incompatible with single-q ordering but is expected from
the double-q model. A (3q_a,0,0) wave vector (i.e., third-order) satellite is
also observed, again in line with the double-q model. The temperature
dependencies of these along with that of a first-order satellite are compared
with calculations based on the double-q model and reasonable qualitative
agreement is found. By examining the azimuthal dependence of first-order
satellite scattering, we show the magnetic order to be, as predicted,
elliptically polarized at base temperature and find the temperature dependence
of the "out of a-b plane" moment component to be in fairly good agreement with
calculation. Our results provide qualitative support for the double-q model and
thus in turn corroborate the explanation for the "magnetoelastic paradox"
offered by this model.


  The influence of mechanical strain on the critical current (Ic) is
investigated for MgB2/stainless steel (SUS316) superconducting tapes. The tapes
are fabricated by using 'powder in tube' method and deformation process without
any heat treatment. The tensile axial strain along tape length is successfully
induced to the sample by using a U-shape holder made of stainless steel
(SUS304). Two samples are examined at 4.2 K in 5 T (B is applied perpendicular
to the tape surface). While the initial Ic at zero external strain state (Ic0)
varies (30.4 and 33.3 A), normalized Ic (Ic/Ic0) vs. external strain relations
fall on the same curve. Linear increase of Ic is observed from zero external
strain state to 0.5% strain (107% of Ic0). Rapid and large degradation occurs
at the strain exceeding 0.4-0.5%. High durability against stress can be
expected for MgB2/stainless steel superconducting tapes.


  We present results on spectroscopic observations of the fast-rotating active
giant FK Comae, obtained mainly with the ESA-MUSICOS spectrograph at the Isaac
Newton Telescope (INT) in 1996 and 1997 and also with the Aurelie spectrograph
at the Observatoire de Haute Provence (OHP) in 1997. The profiles analysed are
those of the Balmer, Halpha and Hbeta, and He I D3 (5876 A) lines. We analyse
the Balmer line variability and phase behaviour. We confirm these lines as
highly variable, with excess emission that originates from extended structures
and exhibits clear signs of rotational modulation. We have described the line
profiles for two distinct states of activity, using different modelling
approaches. Similar techniques were applied to the He I D3 spectra. A large
flare event lasting several days was detected in both Balmer lines and in the
He I D3 line. The energy released during this flare in H alpha is of the order
of 10^37 erg, making it the largest Halpha flare reported on a cool star. Our
results confirm the extreme complexity of the circumstellar environment of FK
Comae. The activity level of this star is quite variable demanding different
approaches to the line profile analysis.


  In the original version of the minimal SU(3)_C x SU(3)_L x U(1)_N model the
masses of all quarks are correctly obtained by introducing three scalar
triplets into the model, meanwhile the lepton mass generation requires the
introduction of at least one scalar sextet. In this work we show that this
scalar sextet is unable to yield the correct neutrino masses and mixing. In
order to solve this puzzle in the most economical way, we evoke an additional
Z_3 discrete symmetry, without including this sextet in the scalar spectrum,
and propose a truly minimal 3-3-1 model capable of generating the correct
masses and mixing of all fermions. Moreover, we show that our proposal leads to
naturally light neutrinos with masses in the eV range, obtained with three
scalar triplets only. Finally, the so called minimal 3-3-1 model is also in
danger due to the presence of undesirable effective operators that lead to
proton decay unless they are suppressed by extremely small couplings or, as we
choose to employ in this work, are eliminated by some discrete symmetry.


  We show that two commonly used definitions for the heat current give
different results--through the Kubo formula--for the heat conductivity of
oscillator chains. The difference exists for finite chains, and is expected to
be important more generally for small structures. For a chain of N particles
that are tethered at the ends, the ratio of the heat conductivities calculated
with the two currents differs from unity by O(1/N). For a chain held at
constant pressure, the difference from unity decays more slowly, and is
consistent with O(1/N^eta) with 1 > eta > 0.5.


  The leading nonadiabatic corrections to rovibrational levels of a diatomic
molecule are expressed in terms of three functions of internuclear distance:
corrections to the adiabatic potential, the effective nuclear mass, and the
effective moment of inertia. The resulting radial Schr\"odinger equation for
nuclear motion is solved numerically yielding accurate nonadiabatic energies
for all rovibrational levels of H$_2$ molecule in excellent agreement with
previous calculations by Wolniewicz.


  Terahertz (THz) band communications and integrated sensing and communications
(ISAC) are two main facets of the sixth generation wireless networks. In order
to compensate the severe attenuation, the THz wireless systems employ large
arrays, wherein the near-field beam-squint severely degrades the beamforming
accuracy. Contrary to prior works that examine only either narrowband ISAC
beamforming or far-field models, we introduce an alternating optimization
technique for hybrid beamforming design in near-field THz-ISAC scenario. We
also propose an efficient approach to compensate near-field beam-squint via
baseband beamformers. Via numerical simulations, we show that the proposed
approach achieves satisfactory spectral efficiency performance while accurately
estimating the near-field beamformers and mitigating the beam-squint without
additional hardware components.


  This paper proves that the functor $C(*)$ that sends pointed,
simply-connected CW-complexes to their chain-complexes equipped with diagonals
and iterated higher diagonals, determines their integral homotopy type --- even
inducing an equivalence of categories between the category of CW-complexes up
to homotopy equivalence and a certain category of chain-complexes equipped with
higher diagonals. Consequently, $C(*)$ is an algebraic model for integral
homotopy types similar to Quillen's model of rational homotopy types. For
finite CW complexes, our model is finitely generated. Our result implies that
the geometrically induced diagonal map with all ``higher diagonal'' maps (like
those used to define Steenrod operations) collectively determine integral
homotopy type.


  The model of cognition developed in (Smolensky and Legendre, 2006) seeks to
unify two levels of description of the cognitive process: the connectionist and
the symbolic. The theory developed brings together these two levels into the
Integrated Connectionist/Symbolic Cognitive architecture (ICS). Clark and
Pulman (2007) draw a parallel with semantics where meaning may be modelled on
both distributional and symbolic levels, developed by Coecke et al, 2010 into
the Distributional Compositional (DisCo) model of meaning. In the current work,
we revisit Smolensky and Legendre (S&L)'s model. We describe the DisCo
framework, summarise the key ideas in S&L's architecture, and describe how
their description of harmony as a graded measure of grammaticality may be
applied in the DisCo model.


  This paper proposes Multi-modAl Retrieval model via Visual modulE pLugin
(MARVEL), which learns an embedding space for queries and multi-modal documents
to conduct retrieval. MARVEL encodes queries and multi-modal documents with a
unified encoder model, which helps to alleviate the modality gap between images
and texts. Specifically, we enable the image understanding ability of the
well-trained dense retriever, T5-ANCE, by incorporating the visual module's
encoded image features as its inputs. To facilitate the multi-modal retrieval
tasks, we build the ClueWeb22-MM dataset based on the ClueWeb22 dataset, which
regards anchor texts as queries, and extracts the related text and image
documents from anchor-linked web pages. Our experiments show that MARVEL
significantly outperforms the state-of-the-art methods on the multi-modal
retrieval dataset WebQA and ClueWeb22-MM. MARVEL provides an opportunity to
broaden the advantages of text retrieval to the multi-modal scenario. Besides,
we also illustrate that the language model has the ability to extract image
semantics and partly map the image features to the input word embedding space.
All codes are available at https://github.com/OpenMatch/MARVEL.


  In this paper, we consider the problem of piecewise affine abstraction of
nonlinear systems, i.e., the overapproximation of its nonlinear dynamics by a
pair of piecewise affine functions that "includes" the dynamical
characteristics of the original system. As such, guarantees for controllers or
estimators based on the affine abstraction also apply to the original nonlinear
system. Our approach consists of solving a linear programming (LP) problem that
over-approximates the nonlinear function at only the grid points of a mesh with
a given resolution and then accounting for the entire domain via an appropriate
correction term. To achieve a desired approximation accuracy, we also
iteratively subdivide the domain into subregions. Our method applies to
nonlinear functions with different degrees of smoothness, including Lipschitz
continuous functions, and improves on existing approaches by enabling the use
of tighter bounds. Finally, we compare the effectiveness of our approach with
existing optimization-based methods in simulation and illustrate its
applicability for estimator design.


  A permutation is called smooth if the corresponding Schubert variety is
smooth. Gilboa and Lapid prove that in the symmetric group, multiplying the
reflections below a smooth element $w$ in Bruhat order in a compatible order
yields back the element $w$. We strengthen this result by showing that such a
product in fact determines a saturated chain $e \to w$ in Bruhat order, and
that this property characterizes smooth elements.


  In 1971 Zel'dovich predicted that quantum fluctuations and classical waves
reflected from a rotating absorbing cylinder will gain energy and be amplified.
This key conceptual step towards the understanding that black holes may also
amplify quantum fluctuations, has not been verified experimentally due to the
challenging experimental requirements on the cylinder rotation rate that must
be larger than the incoming wave frequency. Here we experimentally demonstrate
that these conditions can be satisfied with acoustic waves. We show that
low-frequency acoustic modes with orbital angular momentum are transmitted
through an absorbing rotating disk and amplified by up to 30% or more when the
disk rotation rate satisfies the Zel'dovich condition. These experiments
address an outstanding problem in fundamental physics and have implications for
future research into the extraction of energy from rotating systems.


  We report a first attempt (i) to derive constraints on the energy loss of
charm quarks in a deconfined medium from the recent PHENIX data of
single-electron transverse momentum spectra and (ii) to estimate the resulting
suppression of dileptons from correlated semi-leptonic decays of open charmed
mesons. The momentum imbalance of photon-tagged light-quark jets is also
considered.


  We present a new optical polarimetric catalog for the Small Magellanic Cloud
(SMC). It contains a total of 7207 stars, located in the Northeast (NE) and
Wing sections of the SMC and part of the Magellanic Bridge. This new catalog is
a significant improvement compared to previous polarimetric catalogs for the
SMC. We used it to study the sky-projected interstellar magnetic field
structure of the SMC. Three trends were observed for the ordered magnetic field
direction at position angles of $(65 \pm 10)$ deg, $(115 \pm 10)$ deg, and
$(150 \pm 10)$ deg. Our results suggest the existence of an ordered magnetic
field aligned with the Magellanic Bridge direction and SMC's Bar in the NE
region, which have position angles roughly at $115.4$ deg and $45$ deg,
respectively. However, the overall magnetic field structure is fairly complex.
The trends at $115$ deg and $150$ deg may be correlated with the SMC's bimodal
structure, observed in Cepheids' distances and HI velocities. We derived a
value of $B_{sky} = (0.947 \pm 0.079)~\mu G$ for the ordered sky-projected
magnetic field, and $\delta B = (1.465 \pm 0.069)~\mu G$ for the turbulent
magnetic field. This estimate of $B_{sky}$ is significantly larger (by a factor
of $\sim10$) than the line-of-sight field derived from Faraday rotation
observations, suggesting that most of the ordered field component is on the
plane of the sky. A turbulent magnetic field stronger than the ordered field
agrees with observed estimates for other irregular and spiral galaxies. For the
SMC the $B_{sky}/\delta B$ ratio is closer to what is observed for our Galaxy
than other irregular dwarf galaxies.


  When the coupling between light and matter becomes comparable to the energy
gap between different excited states they hybridize, leading to the appearance
of a rich and complex phenomenology which attracted remarkable interest in
recent years. While the mixing between states with different number of
excitations, so-called ultrastrong coupling regime, has been observed in
various implementations, the effect of the hybridization between different
single excitation states, referred to as very strong coupling regime, has
remained elusive. In semiconductor quantum wells such a regime is predicted to
manifest as a photon-mediated electron-hole coupling leading to different
excitonic wavefunctions for the two polaritonic branches when the ratio of the
coupling strength to exciton binding energy approaches unity. Here, we verify
experimentally the existence of this regime in magneto-optical measurements on
a microcavity with 28 GaAs quantum wells, showing that the average
electron-hole separation of the upper polariton is significantly increased
compared to the bare quantum well exciton Bohr radius. This manifests in a
diamagnetic shift around zero detuning that exceeds the shift of the lower
polariton by one order of magnitude and the bare quantum well exciton
diamagnetic shift by a factor of two. The lower polariton exhibits a
diamagnetic shift smaller than expected from the coupling of a rigid exciton to
the cavity mode which suggests more tightly bound electron-hole pairs than in
the bare quantum well.


  The Stable Roommates problem (SR) is characterized by the preferences of
agents over other agents as roommates: each agent ranks all others in strict
order of preference. A solution to SR is then a partition of the agents into
pairs so that each pair shares a room, and there is no pair of agents that
would block this matching (i.e., who prefers the other to their roommate in the
matching). There are interesting variations of SR that are motivated by
applications (e.g., the preference lists may be incomplete (SRI) and involve
ties (SRTI)), and that try to find a more fair solution (e.g., Egalitarian SR).
Unlike the Stable Marriage problem, every SR instance is not guaranteed to have
a solution. For that reason, there are also variations of SR that try to find a
good-enough solution (e.g., Almost SR). Most of these variations are NP-hard.
We introduce a formal framework, called SRTI-ASP, utilizing the logic
programming paradigm Answer Set Programming, that is provable and general
enough to solve many of such variations of SR. Our empirical analysis shows
that SRTI-ASP is also promising for applications. This paper is under
consideration for acceptance in TPLP.


  Approximation only by derivative (or more generally momentum) expansions,
combined with reparametrization invariance, turns the continuous
renormalization group for quantum field theory into a set of partial
differential equations which at fixed points become non-linear eigenvalue
equations for the anomalous scaling dimension $\eta$. We review how these
equations provide a powerful and robust means of discovering and approximating
non-perturbative continuum limits. Gauge fields are briefly discussed.
Particular emphasis is placed on the r\^ole of reparametrization invariance,
and the convergence of the derivative expansion is addressed.


  We discuss slepton mass matrices in the $S_4$ flavor model with SUSY SU(5)
GUT. By considering the gravity mediation within the framework of supergravity
theory, we estimate the SUSY breaking terms in the slepton mass matrices, which
contribute to the $\mu \rightarrow e + \gamma$ decay.
  We obtain a lower bound for the ratio of $\mu\rightarrow e\gamma$ as
$10^{-13}$ if $m_{\text{SUSY}}$ and $m_{1/2}$ are below 500GeV. The off
diagonal terms of slepton mass matrices also contribute to EDM of leptons. The
predicted electron EDM is around $10^{-29}-10^{-28}$cm. Our predictions are
expected to be tested in the near future experiment.


  In this work, we present, for the first time, a numerical study of the
Bondi-Hoyle accretion with density gradients in the fully relativistic regime.
In this context, we consider accretion onto a Kerr Black Hole (BH) of a
supersonic ideal gas, which has density gradients perpendicular to the relative
motion. The set of parameters of interest in this study are the Mach number, M,
the spin of the BH, a, and the density-gradient parameter of the gas, {\rho} .
We show that, unlike in the Newtonian case, all the studied cases, especially
those with density gradient, approach a stationary flow pattern. To illustrate
that the system reaches steady state we calculate the mass and angular momentum
accretion rates on a spherical surface located almost at the event horizon. In
the particular case of M = 1, {\rho} = 0.5 and BH spin a = 0.5, we observe a
disk-like configuration surrounding the BH. Finally, we present the gas
morphology and some of its properties.


  We consider extensions of the Standard Model by a hidden sector consisting of
a gauge field coupled with a scalar field. Assuming the absence of dimensionful
parameters in the tree level potential, radiative symmetry breaking will make
the hidden sector gauge field massive and induce the electroweak scale of the
Standard Model. We consider separately dark sector gauge groups $U(1)_{\rm{D}}$
and $SU(2)_{\rm{D}}$, and focus on probing the models with a combination of
direct detection experiments and gravitational wave observatories. We find that
recent dark matter direct detection results significantly constrain the
parameter space of the models where they can account for the observed dark
matter relic density via freeze-out. The gravitational wave signals originating
from strongly first order electroweak phase transition in these models can be
probed in future gravitational wave observatories such as the Laser
Interferometer Space Antenna. We show how the projected results compliment
direct detection experiments and can help probe parameter space near the
neutrino floor of direct detection.


  Despite the success of sequence-to-sequence approaches in automatic speech
recognition (ASR) systems, the models still suffer from several problems,
mainly due to the mismatch between the training and inference conditions. In
the sequence-to-sequence architecture, the model is trained to predict the
grapheme of the current time-step given the input of speech signal and the
ground-truth grapheme history of the previous time-steps. However, it remains
unclear how well the model approximates real-world speech during inference.
Thus, generating the whole transcription from scratch based on previous
predictions is complicated and errors can propagate over time. Furthermore, the
model is optimized to maximize the likelihood of training data instead of error
rate evaluation metrics that actually quantify recognition quality. This paper
presents an alternative strategy for training sequence-to-sequence ASR models
by adopting the idea of reinforcement learning (RL). Unlike the standard
training scheme with maximum likelihood estimation, our proposed approach
utilizes the policy gradient algorithm. We can (1) sample the whole
transcription based on the model's prediction in the training process and (2)
directly optimize the model with negative Levenshtein distance as the reward.
Experimental results demonstrate that we significantly improved the performance
compared to a model trained only with maximum likelihood estimation.


  This paper is concerned with identification, estimation, and specification
testing in causal evaluation problems when data is selective and/or missing. We
leverage recent advances in the literature on graphical methods to provide a
unifying framework for guiding empirical practice. The approach integrates and
connects to prominent identification and testing strategies in the literature
on missing data, causal machine learning, panel data analysis, and more. We
demonstrate its utility in the context of identification and specification
testing in sample selection models and field experiments with attrition. We
provide a novel analysis of a large-scale cluster-randomized controlled
teacher's aide trial in Danish schools at grade 6. Even with detailed
administrative data, the handling of missing data crucially affects broader
conclusions about effects on mental health. Results suggest that teaching
assistants provide an effective way of improving internalizing behavior for
large parts of the student population.


  Lyman-$\alpha$ spheres, i.e. regions around the first stars which are
illuminated by Lyman-$\alpha$ photons and show 21cm absorption feature against
the CMB, are smoking guns at the dawn of the reionization epoch. Though
overwhelming radio foreground makes their detections extremely difficult, we
pointed out that, strong gravitational lensing can significantly improve their
observational feasibility. Since Lyman-$\alpha$ spheres have ~10" sizes,
comparable to the caustic size of galaxy clusters, individual images of each
strongly lensed Lyman-$\alpha$ sphere often merge together and form single
structures in the 21cm sky with irregular shapes. Using high-resolution N-body
LCDM simulations, we found that the lensing probability to have magnification
bigger than 10 is ~10^{-5}. This results in $\ga 10^6$ strongly lensed
Lyman-$\alpha$ spheres across the sky, which should be the primary targets for
first detections of Lyman-$\alpha$ spheres. Although the required total radio
array collecting area for their detection is large (~100 km^2), the design of
long fixed cylindrical reflectors can significantly reduce the total cost of
such array to the level of the square kilometer array (SKA) and makes the
detection of these very first objects feasible.


  We formulate the Schiffer's conjecture in spectral geometry in the context of
scattering theory. The problem is equivalent to finding a non-trivial solution
in an interior transmission problem. We compare the back-scattering data of the
perturbation along all incident angles. The uniqueness of the inverse
scattering problem along each incident direction proves the Schiffer's
conjecture.


  We have theoretically and experimentally address the possible tandem
electro-optical modulator configurations that can be employed to implement
Frequency Coded Quantum Key Distribution systems (FC-QKD). A closed and general
formulation of the end to end field propagation in a dispersion compensated
FC-QKD optical fiber system under the low modulation index regime is presented
which accounts for all the possible tandem combinations. The properties and the
parameter selection of the modulators to achieve each one are summarized. We
also address which protocol (B92, BB84 or either) is feasible to be implemented
with each configuration. The results confirm those reported for the
configurations previously reported in the literature and, at the same time,
show the existence of four novel tandem modulator configurations that can also
be employed. We have also provided experimental evidence of the successful
operation of the novel configurations that confirm the behavior predicted by
the theoretical results.


  In this work we intend to discuss the solitonic solutions of Einstein's field
equations in vacuum by constructing the solution to N solitons and studying
some aspects of it. In conclusion, it will be shown how the Kerr black hole can
be interpreted as a soliton solution in the case of axial symmetry.


  This paper presents a novel application of multiparameter spectral theory to
the study of structural stability, with particular emphasis on aeroelastic
flutter. Methods of multiparameter analysis allow the development of new
solution algorithms for aeroelastic flutter problems; most significantly, a
direct solver for polynomial problems of arbitrary order and size, something
which has not before been achieved. Two major variants of this direct solver
are presented, and their computational characteristics are compared. Both are
effective for smaller problems arising in reduced-order modelling and
preliminary design optimization. Extensions and improvements to this new
conceptual framework and solution method are then discussed.


  We compare experiments and direct numerical simulations to evaluate the
accuracy of the Stokes-drag model, which is used widely in studies of inertial
particles in turbulence. We focus on statistics at the dissipation scale and on
extreme values of relative particle velocities for moderately inertial
particles (St < 1). The probability distributions of relative velocities in the
simulations were qualitatively similar to those in the experiments. The
agreement improved with increasing Stokes number and decreasing relative
velocity. Simulations underestimated the probability of extreme events, which
suggests that the Stokes drag model misses important dynamics. Nevertheless,
the scaling behavior of the extreme events in both the experiments and the
simulations can be captured by the same multi-fractal model.


  Large-scale recommender systems often face severe latency and storage
constraints at prediction time. These are particularly acute when the number of
items that could be recommended is large, and calculating predictions for the
full set is computationally intensive. In an attempt to relax these
constraints, we train recommendation models that use binary rather than
real-valued user and item representations, and show that while they are
substantially faster to evaluate, the gains in speed come at a large cost in
accuracy. In our Movielens 1M experiments, we show that reducing the latent
dimensionality of traditional models offers a more attractive accuracy/speed
trade-off than using binary representations.


  Smart tourism (ST) stems from the concepts of e-tourism - focused on the
digitalization of processes within the tourism industry, and digital tourism -
also considering the digitalization within the tourist experience. The earlier
ST references found regard ST Destinations and emerge from the development of
Smart Cities.
  Our initial literature review on the ST concept and Smart Tourism Tools (STT)
revealed significant research uncertainties: ST is poorly defined and
frequently linked to the concept of Smart Cities; different authors have
different, sometimes contradictory, views on the goals of ST; STT claims are
often only based on technological aspects, and their "smartness" is difficult
to evaluate; often the term "Smart" describes developments fueled by
cutting-edge technologies, which lose that status after a few years.
  This chapter is part of the ongoing initiative to build an online observatory
that provides a comprehensive view of STTs' offerings in Europe, known as the
European STT Observatory. To achieve this, the observatory requires
methodologies and tools to evaluate "smartness" based on a sound definition of
ST and STT, while also being able to adapt to technological advancements. In
this chapter, we present the results of a participatory approach where we
invited ST experts from around the world to help us achieve this level of
soundness. Our goal is to make a valuable contribution to the discussion on the
definition of ST and STT.


  While significant progress has been made in deep video denoising, it remains
very challenging for exploiting historical and future frames. Bidirectional
recurrent networks (BiRNN) have exhibited appealing performance in several
video restoration tasks. However, BiRNN is intrinsically offline because it
uses backward recurrent modules to propagate from the last to current frames,
which causes high latency and large memory consumption. To address the offline
issue of BiRNN, we present a novel recurrent network consisting of forward and
look-ahead recurrent modules for unidirectional video denoising. Particularly,
look-ahead module is an elaborate forward module for leveraging information
from near-future frames. When denoising the current frame, the hidden features
by forward and look-ahead recurrent modules are combined, thereby making it
feasible to exploit both historical and near-future frames. Due to the scene
motion between non-neighboring frames, border pixels missing may occur when
warping look-ahead feature from near-future frame to current frame, which can
be largely alleviated by incorporating forward warping and proposed border
enlargement. Experiments show that our method achieves state-of-the-art
performance with constant latency and memory consumption. Code is avaliable at
https://github.com/nagejacob/FloRNN.


  This paper presents an efficient parallel direct algorithm with near-optimal
complexity for the compact fourth and sixth-order approximation of the
three-dimensional Helmholtz equations [1] with the problem coefficient
depending on only one of the coordinate directions. The developed method is
based on a combination of the separation of variables technique and a Fast
Fourier Transform (FFT) type method. Similar direct solvers for the lower-order
approximations of the two and three-dimensional Helmholtz equation were
considered in several previous publications by the authors and other
researchers (see e.g. [2,3,4,5]). The authors also consider a generalization of
the presented algorithm to the solution of a wide class of linear systems
obtained from approximation on the compact 27-point three-dimensional stencils
on the rectangular grids with similar requirements on the stencil coefficients.
The general restrictions on the coefficients in the considered class of compact
schemes are developed and presented. This class includes the second, fourth and
sixth-order compact approximation schemes for the three-dimensional Helmholtz
equation considered in this paper and our previous publications [2,3,6]. As an
example of the diversity of applications of the developed general method, the
direct parallel implementation of a compact fourth-order approximation scheme
for a convection-diffusion equation is considered. The results of the
implementation of this method in OpenMP, MPI and hybrid programming
environments on the multicore computers and multiple node clusters are
presented and discussed. The results demonstrate the high efficiency of the
proposed direct solvers for many important applications on the structured grid
with the corresponding 27-diagonal matrices.


  Reversible jump MCMC (RJ-MCMC) sampling techniques, which allow to jointly
tackle model selection and parameter estimation problems in a coherent Bayesian
framework, have become increasingly popular in the signal processing literature
since the seminal paper of Andrieu and Doucet (IEEE Trans. Signal Process.,
47(10), 1999). Crucial to the implementation of any RJ-MCMC sampler is the
computation of the so-called Metropolis-Hastings-Green (MHG) ratio, which
determines the acceptance probability for the proposed moves.
  It turns out that the expression of the MHG ratio that was given in the paper
of Andrieu and Doucet for "Birth-or-Death" moves---the simplest kind of
trans-dimensional move, used in virtually all applications of RJ-MCMC to signal
decomposition problems---was erroneous. Unfortunately, this mistake has been
reproduced in many subsequent papers dealing with RJ-MCMC sampling in the
signal processing literature.
  This note discusses the computation of the MHG ratio, with a focus on the
case where the proposal kernel can be decomposed as a mixture of simpler
kernels, for which the MHG ratio is easy to compute. We provide sufficient
conditions under which the MHG ratio of the mixture can be deduced from the MHG
ratios of the elementary kernels of which it is composed. As an application, we
consider the case of Birth-or-Death moves, and provide a corrected expression
for the erroneous ratio in the paper of Andrieu and Doucet.


  In order to perceive the behavior presented by the multiphase chemical
reactors, the ant colony optimization algorithm was combined with computational
fluid dynamics (CFD) data. This intelligent algorithm creates a probabilistic
technique for computing flow and it can predict various levels of
three-dimensional bubble column reactor (BCR). This artificial ant algorithm is
mimicking real ant behavior. This method can anticipate the flow
characteristics in the reactor using almost 30 % of the whole data in the
domain. Following discovering the suitable parameters, the method is used for
predicting the points not being simulated with CFD, which represent mesh
refinement of Ant colony method. In addition, it is possible to anticipate the
bubble-column reactors in the absence of numerical results or training of exact
values of evaluated data. The major benefits include reduced computational
costs and time savings. The results show a great agreement between ant colony
prediction and CFD outputs in different sections of the BCR. The combination of
ant colony system and neural network framework can provide the smart structure
to estimate biological and nature physics base phenomena. The ant colony
optimization algorithm (ACO) framework based on ant behavior can solve all
local mathematical answers throughout 3D bubble column reactor. The integration
of all local answers can provide the overall solution in the reactor for
different characteristics. This new overview of modelling can illustrate new
sight into biological behavior in nature.


  We establish long-time stability of multi-dimensional viscous shocks of a
general class of symmetric hyperbolic--parabolic systems with variable
multiplicities, notably including the equations of compressible
magnetohydrodynamics (MHD) in dimensions $d\ge 2$. This extends the existing
result established by K. Zumbrun for systems with characteristics of constant
multiplicity to the ones with variable multiplicity, yielding the first such a
stability result for (fast) MHD shocks. At the same time, we are able to drop a
technical assumption on structure of the so--called glancing set that was
necessarily used in previous analyses. The key idea to the improvements is to
introduce a new simple argument for obtaining a $L^1\to L^p$ resolvent bound in
low--frequency regimes by employing the recent construction of degenerate
Kreiss' symmetrizers by O. Gu\`es, G. M\'etivier, M. Williams, and K. Zumbrun.
Thus, at the low-frequency resolvent bound level, our analysis gives an
alternative to the earlier pointwise Green's function approach of K. Zumbrun.
High--frequency solution operator bounds have been previously established
entirely by nonlinear energy estimates.


  We consider a load balancing model where a Poisson stream of jobs arrive at a
system of many servers whose service time distribution possesses a finite
second moment. A small fraction of arrivals pass through the so called
power-of-choice algorithm, which assigns a job to the shortest among $\ell$,
$\ell\ge 2$, randomly chosen queues, and the remaining jobs are assigned to
queues chosen uniformly at random. The system is analyzed at critical load in
an asymptotic regime where both the number of servers and the usual heavy
traffic parameter associated with individual queue lengths grow to infinity.
The first main result is a hydrodynamic limit, where the empirical measure of
the diffusively normalized queue lengths is shown to converge to a path in
measure space whose density is given by the unique solution of a parabolic PDE
with nonlocal coefficients.
  Further, two forms of an invariance principle are proved, corresponding to
two different assumptions on the initial distribution, where individual
normalized queue lengths converge weakly to solutions of SDE. In one of these
results, the limit is given by a McKean-Vlasov SDE, and propagation of chaos
holds. The McKean-Vlasov limit is closely related to limit results for Brownian
particles on $\mathbb{R}_+$ interacting through their rank (with a specific
interaction). However, an entirely different set of tools is required, as the
collection of $n$ prelimit particles does not obey a Markovian evolution on
$\mathbb{R}_+^n$.


  In the present work we show robust indications of the existence of g modes in
the Sun using 10 years of GOLF data. The present analysis is based on the
exploitation of the collective properties of the predicted low-frequency (25 to
140 microHz) g modes: their asymptotic nature, which implies a quasi
equidistant separation of their periods for a given angular degree (l). The
Power Spectrum (PS) of the Power Spectrum Density (PSD), reveals a significant
structure indicating the presence of features (peaks) in the PSD with near
equidistant periods corresponding to l=1 modes in the range n=-4 to n=-26. The
study of its statistical significance of this feature was fully undertaken and
complemented with Monte Carlo simulations. This structure has a confidence
level better than 99.86% not to be due to pure noise. Furthermore, a detailed
study of this structure suggests that the gravity modes have a much more
complex structure than the one initially expected (line-widths, magnetic
splittings...). Compared to the latest solar models, the obtained results tend
to favor a solar core rotating significantly faster than the rest of the
radiative zone. In the framework of the Phoebus group, we have also applied the
same methodology to other helioseismology instruments on board SoHO and ground
based networks.


  We consider the impedance of a structure with rectangular, periodic
corrugations on two opposing sides of a rectangular beam tube. Using the method
of field matching, we find the modes in such a structure. We then limit
ourselves to the the case of small corrugations, but where the depth of
corrugation is not small compared to the period. For such a structure we
generate analytical approximate solutions for the wave number $k$, group
velocity $v_g$, and loss factor $\kappa$ for the lowest (the dominant) mode
which, when compared with the results of the complete numerical solution,
agreed well. We find: if $w\sim a$, where $w$ is the beam pipe width and $a$ is
the beam pipe half-height, then one mode dominates the impedance, with
$k\sim1/\sqrt{w\delta}$ ($\delta$ is the depth of corrugation),
$(1-v_g/c)\sim\delta$, and $\kappa\sim1/(aw)$, which (when replacing $w$ by
$a$) is the same scaling as was found for small corrugations in a {\it round}
beam pipe. Our results disagree in an important way with a recent paper of
Mostacci {\it et al.} [A. Mostacci {\it et al.}, Phys. Rev. ST-AB, {\bf 5},
044401 (2002)], where, for the rectangular structure, the authors obtained a
synchronous mode with the same frequency $k$, but with $\kappa\sim\delta$.
Finally, we find that if $w$ is large compared to $a$ then many nearby modes
contribute to the impedance, resulting in a wakefield that Landau damps.


  In the era of Internet of Things (IoT), Digital Twin (DT) is envisioned to
empower various areas as a bridge between physical objects and the digital
world. Through virtualization and simulation techniques, multiple functions can
be achieved by leveraging computing resources. In this process, Mobile Cloud
Computing (MCC) and Mobile Edge Computing (MEC) have become two of the key
factors to achieve real-time feedback. However, current works only considered
edge servers or cloud servers in the DT system models. Besides, The models
ignore the DT with not only one data resource. In this paper, we propose a new
DT system model considering a heterogeneous MEC/MCC environment. Each DT in the
model is maintained in one of the servers via multiple data collection devices.
The offloading decision-making problem is also considered and a new offloading
scheme is proposed based on Distributed Deep Learning (DDL). Simulation results
demonstrate that our proposed algorithm can effectively and efficiently
decrease the system's average latency and energy consumption. Significant
improvement is achieved compared with the baselines under the dynamic
environment of DTs.


  Monolayer Transition Metal Dichalcogenides (TMDCs) are promising candidates
for quantum technologies, such as quantum dots, because they are truly
two-dimensional semiconductors with a direct band gap. In this work, we analyse
theoretically the behaviour of a double quantum dot (DQD) system created in the
conduction band of these materials, with two electrons in the (1,1) charge
configuration. Motivated by recent experimental progress, we consider several
scenarios, including different spin-orbit splittings in the two dots and
including the case when the valley degeneracy is lifted due to an insulating
ferromagnetic substrate. Finally, we discuss in which cases it is possible to
reduce the low energy subspace to the lowest Kramers pairs. We find that in
this case the low energy model is formally identical to the Heisenberg exchange
Hamiltonian.


  Weak gravitational lensing of distant galaxies can probe the total projected
mass distribution of foreground gravitational structures on all scales and has
been used successfully to map the projected mass distribution of rich
intermediate redshift clusters. This paper reviews the general concepts of the
lensing analysis. We focus on the relation between the observable (shapes and
fluxes) and physical (mass, redshift) quantities and discuss some observational
issues and recent developments on data analysis which appear promising for a
better measurement of the lensing signatures (distortion and magnification) at
very large scales.


  Change point testing for high-dimensional data has attracted a lot of
attention in statistics and machine learning owing to the emergence of
high-dimensional data with structural breaks from many fields. In practice,
when the dimension is less than the sample size but is not small, it is often
unclear whether a method that is tailored to high-dimensional data or simply a
classical method that is developed and justified for low-dimensional data is
preferred. In addition, the methods designed for low-dimensional data may not
work well in the high-dimensional environment and vice versa. In this paper, we
propose a dimension-agnostic testing procedure targeting a single change point
in the mean of a multivariate time series. Specifically, we can show that the
limiting null distribution for our test statistic is the same regardless of the
dimensionality and the magnitude of cross-sectional dependence. The power
analysis is also conducted to understand the large sample behavior of the
proposed test. Through Monte Carlo simulations and a real data illustration, we
demonstrate that the finite sample results strongly corroborate the theory and
suggest that the proposed test can be used as a benchmark for change-point
detection of time series of low, medium, and high dimensions.


  Graph games provide the foundation for modeling and synthesizing reactive
processes. In the synthesis of stochastic reactive processes, the traditional
model is perfect-information stochastic games, where some transitions of the
game graph are controlled by two adversarial players, and the other transitions
are executed probabilistically. We consider such games where the objective is
the conjunction of several quantitative objectives (specified as mean-payoff
conditions), which we refer to as generalized mean-payoff objectives. The basic
decision problem asks for the existence of a finite-memory strategy for a
player that ensures the generalized mean-payoff objective be satisfied with a
desired probability against all strategies of the opponent. A special case of
the decision problem is the almost-sure problem where the desired probability
is 1. Previous results presented a semi-decision procedure for
epsilon-approximations of the almost-sure problem. In this work, we show that
both the almost-sure problem as well as the general basic decision problem are
coNP-complete, significantly improving the previous results. Moreover, we show
that in the case of 1-player stochastic games, randomized memoryless strategies
are sufficient and the problem can be solved in polynomial time. In contrast,
in two-player stochastic games, we show that even with randomized strategies
exponential memory is required in general, and present a matching exponential
upper bound. We also study the basic decision problem with infinite-memory
strategies and present computational complexity results for the problem. Our
results are relevant in the synthesis of stochastic reactive systems with
multiple quantitative requirements.


  In this work we first introduce quasi-infinitely divisible (QID) random
measures and formulate spectral representations. Then, we introduce QID
stochastic integrals and present integrability conditions and continuity
properties. Further, we introduce QID stochastic processes, i.e. stochastic
processes with QID finite dimensional distributions. For example, a process $X$
is QID if there exist two ID processes $Y$ and $Z$ such that
$X+Y\stackrel{d}{=}Z$ with $Y$ independent of $X$. The class of QID processes
is strictly larger than the class of ID processes. We provide spectral
representations and L\'{e}vy-Khintchine formulations for potentially all QID
processes. Finally, we prove that QID random measures are dense in the space of
random measures under convergence in distribution. Throughout this work we
present many examples.


  We say that a bipartite graph $G(A, B)$ with fixed parts $A$, $B$ is
proximinal if there is a semimetric space $(X, d)$ such that $A$ and $B$ are
disjoint proximinal subsets of $X$ and all edges $\{a, b\}$ satisfy the
equality $d(a, b) = \operatorname{dist}(A, B)$. It is proved that a bipartite
graph $G$ is not isomorphic to any proximinal graph iff $G$ is finite and
empty. It is also shown that the subgraph induced by all non-isolated vertices
of a nonempty bipartite graph $G$ is a disjoint union of complete bipartite
graphs iff $G$ is isomorphic to a nonempty proximinal graph for an ultrametric
space.


  Whilst adversarial attack detection has received considerable attention, it
remains a fundamentally challenging problem from two perspectives. First, while
threat models can be well-defined, attacker strategies may still vary widely
within those constraints. Therefore, detection should be considered as an
open-set problem, standing in contrast to most current detection approaches.
These methods take a closed-set view and train binary detectors, thus biasing
detection toward attacks seen during detector training. Second, limited
information is available at test time and typically confounded by nuisance
factors including the label and underlying content of the image. We address
these challenges via a novel strategy based on random subspace analysis. We
present a technique that utilizes properties of random projections to
characterize the behavior of clean and adversarial examples across a diverse
set of subspaces. The self-consistency (or inconsistency) of model activations
is leveraged to discern clean from adversarial examples. Performance
evaluations demonstrate that our technique ($AUC\in[0.92, 0.98]$) outperforms
competing detection strategies ($AUC\in[0.30,0.79]$), while remaining truly
agnostic to the attack strategy (for both targeted/untargeted attacks). It also
requires significantly less calibration data (composed only of clean examples)
than competing approaches to achieve this performance.


  We construct $\Delta$-operators $F[\Delta]$ on the space of almost symmetric
functions $\mathscr{P}_{as}^{+}$. These operators extend the usual
$\Delta$-operators on the space of symmetric functions $\Lambda \subset
\mathscr{P}_{as}^{+}$ central to Macdonald theory. The $F[\Delta]$ operators
are constructed as certain limits of symmetric functions in the Cherednik
operators $Y_i$ and act diagonally on the stable-limit non-symmetric Macdonald
functions $\widetilde{E}_{(\mu|\lambda)}(x_1,x_2,\ldots;q,t).$ Using properties
of Ion-Wu limits, we are able to compute commutation relations for the
$\Delta$-operators $F[\Delta]$ and many of the other operators on
$\mathscr{P}_{as}^{+}$ introduced by Ion-Wu. Using these relations we show that
there is an action of $\mathbb{B}_{q,t}^{\text{ext}}$ on almost symmetric
functions which we show is isomorphic to the polynomial representation of
$\mathbb{B}_{q,t}^{\text{ext}}$ constructed by Gonz\'{a}lez-Gorsky-Simental.


  We present a new realization of scalar integrable hierarchies in terms of the
Toda lattice hierarchy. In other words, we show on a large number of examples
that an integrable hierarchy, defined by a pseudodifferential Lax operator, can
be embedded in the Toda lattice hierarchy. Such a realization in terms the Toda
lattice hierarchy seems to be as general as the Drinfeld--Sokolov realization.


  Why is the manifold topology in a spacetime taken for granted? Why do we
prefer to use Riemann open balls as basic-open sets, while there also exists a
Lorentz metric? Which topology is a best candidate for a spacetime; a topology
sufficient for the description of spacetime singularities or a topology which
incorporates the causal structure? Or both? Is it more preferable to have a
topology with as many physical properties as possible, whose description might
be complicated and counterintuitive, or a topology which can be described via a
countable basis but misses some important information? These are just a few
from the questions that we ask in this Chapter, which serves as a critical
review of the terrain and contains a survey with remarks, corrections and open
questions.


  In the set of all patterns in $S_n$, it is clear that each k-pattern occurs
equally often. If we instead restrict to the class of permutations avoiding a
specific pattern, the situation quickly becomes more interesting. Mikl\'os
B\'ona recently proved that, surprisingly, if we consider the class of
permutations avoiding the pattern 132, all other non-monotone patterns of
length 3 are equally common. In this paper we examine the class $\Av (123)$,
and give exact formula for the occurrences of each length 3 pattern. While this
class does not break down as nicely as $\Av (132)$, we find some interesting
similarities between the two and prove that the number of 231 patterns is the
same in each.


  The effective operator tr(G^3) is the only dimension-6 gluonic operator that
cannot be related to four-quark operators. A peculiar property of this operator
is that it does not contribute to two-jet production at hadron colliders, at
the level of one operator insertion and leading-order in alpha_s; therefore we
study its effects on three jet events. To calculate the helicity amplitudes
induced by this operator we make extensive use of collinear factorization. We
propose several ways of detecting the tr(G^3) signal, one of which exploits its
non-trivial behavior under azimuthal rotations of two almost collinear jets.


  The classical Einstein--Maxwell field equations admit static horizonless
wormhole solutions with only a circular cosmic string singularity. We show how
to extend these static solutions to exact rotating asymptotically flat
solutions. For a suitable range of parameter values, these solutions describe
charged or neutral rotating closed cosmic strings, with a perimeter of the
order of their Schwarzschild radius.


  The detection of the quantum dot charge state using a quantum point contact
charge detector has opened a new exciting route for the investigation of
quantum dot devices in recent years. In particular, time-resolved charge
detection allowed the precise measurement of quantum dot shot noise at
sub-femtoampere current levels, and the full counting statistics of the
current. The technique can be applied to different material systems and holds
promise for the future application in quantum dot based quantum information
processing implementations. We review recent experiments employing this charge
detection technique, including the self-interference of individual electrons
and back-action phenomena.


  We investigate the electronic structure of Sr$_2$FeMoO$_6$ combining
photoemission spectroscopy with a wide range of photon energies and electronic
structure calculations based on first-principle as well as model Hamiltonian
approaches to reveal several interesting aspects. We find evidence for
unusually strong Coulomb correlation effects both in the Fe 3$d$ and O 2$p$
states, with an enhanced manifestation in the majority spin channel.
Additionally, O 2$p$ states exhibit a spin-splitting of nonmagnetic origin,
which nevertheless is likely to have subtle influence on the stability of novel
ferromagnetism of this compound.


  Reimplementing solutions to previously solved software engineering problems
is not only inefficient but also introduces inadequate and error-prone code.
Many existing methods achieve impressive performance on this issue by using
autoregressive text-generation models trained on code. However, these methods
are not without their flaws. The generated code from these models can be buggy,
lack documentation, and introduce vulnerabilities that may go unnoticed by
developers. An alternative to code generation -- neural code search -- is a
field of machine learning where a model takes natural language queries as input
and, in turn, relevant code samples from a database are returned. Due to the
nature of this pre-existing database, code samples can be documented, tested,
licensed, and checked for vulnerabilities before being used by developers in
production. In this work, we present CodeDSI, an end-to-end unified approach to
code search. CodeDSI is trained to directly map natural language queries to
their respective code samples, which can be retrieved later. In an effort to
improve the performance of code search, we have investigated docid
representation strategies, impact of tokenization on docid structure, and
dataset sizes on overall code search performance. Our results demonstrate
CodeDSI strong performance, exceeding conventional robust baselines by 2-6%
across varying dataset sizes.


  We report the results of an in-depth analysis of the parameter estimation
capabilities of BayesWave, an algorithm for the reconstruction of
gravitational-wave signals without reference to a specific signal model. Using
binary black hole signals, we compare BayesWave's performance to the
theoretical best achievable performance in three key areas: sky localisation
accuracy, signal/noise discrimination, and waveform reconstruction accuracy.
BayesWave is most effective for signals that have very compact time-frequency
representations. For binaries, where the signal time-frequency volume decreases
with mass, we find that BayesWave's performance reaches or approaches
theoretical optimal limits for system masses above approximately 50 M_sun. For
such systems BayesWave is able to localise the source on the sky as well as
templated Bayesian analyses that rely on a precise signal model, and it is
better than timing-only triangulation in all cases. We also show that the
discrimination of signals against glitches and noise closely follow analytical
predictions, and that only a small fraction of signals are discarded as
glitches at a false alarm rate of 1/100 y. Finally, the match between
BayesWave- reconstructed signals and injected signals is broadly consistent
with first-principles estimates of the maximum possible accuracy, peaking at
about 0.95 for high mass systems and decreasing for lower-mass systems. These
results demonstrate the potential of unmodelled signal reconstruction
techniques for gravitational-wave astronomy.


  In this paper, we propose a method to generate personalized filled pauses
(FPs) with group-wise prediction models. Compared with fluent text generation,
disfluent text generation has not been widely explored. To generate more
human-like texts, we addressed disfluent text generation. The usage of
disfluency, such as FPs, rephrases, and word fragments, differs from speaker to
speaker, and thus, the generation of personalized FPs is required. However, it
is difficult to predict them because of the sparsity of position and the
frequency difference between more and less frequently used FPs. Moreover, it is
sometimes difficult to adapt FP prediction models to each speaker because of
the large variation of the tendency within each speaker. To address these
issues, we propose a method to build group-dependent prediction models by
grouping speakers on the basis of their tendency to use FPs. This method does
not require a large amount of data and time to train each speaker model. We
further introduce a loss function and a word embedding model suitable for FP
prediction. Our experimental results demonstrate that group-dependent models
can predict FPs with higher scores than a non-personalized one and the
introduced loss function and word embedding model improve the prediction
performance.


  We deal with families of probability distributions satisfying non-signalling
condition, called non-signalling boxes and consider class of operations that
transform local boxes into local ones (the one that admit LHV model). We prove
that any operation from this class can not broadcast a nonlocal box in 2x2
case. We consider a function called anti-Robustness which can not decrease
under these operations. The proof reduces to showing that anti-Robustness would
decrease after broadcasting.


  Hyperspectral image (HSI) classification is one of the most active research
topics and has achieved promising results boosted by the recent development of
deep learning. However, most state-of-the-art approaches tend to perform poorly
when the training and testing images are on different domains, e.g., source
domain and target domain, respectively, due to the spectral variability caused
by different acquisition conditions. Transfer learning-based methods address
this problem by pre-training in the source domain and fine-tuning on the target
domain. Nonetheless, a considerable amount of data on the target domain has to
be labeled and non-negligible computational resources are required to retrain
the whole network. In this paper, we propose a new transfer learning scheme to
bridge the gap between the source and target domains by projecting the HSI data
from the source and target domains into a shared abundance space based on their
own physical characteristics. In this way, the domain discrepancy would be
largely reduced such that the model trained on the source domain could be
applied on the target domain without extra efforts for data labeling or network
retraining. The proposed method is referred to as physically-constrained
transfer learning through shared abundance space (PCTL-SAS). Extensive
experimental results demonstrate the superiority of the proposed method as
compared to the state-of-the-art. The success of this endeavor would largely
facilitate the deployment of HSI classification for real-world sensing
scenarios.


  Autocomplete is a task where the user inputs a piece of text, termed prompt,
which is conditioned by the model to generate semantically coherent
continuation. Existing works for this task have primarily focused on datasets
(e.g., email, chat) with high frequency user prompt patterns (or focused
prompts) where word-based language models have been quite effective. In this
work, we study the more challenging open-domain setting consisting of low
frequency user prompt patterns (or broad prompts, e.g., prompt about 93rd
academy awards) and demonstrate the effectiveness of character-based language
models. We study this problem under memory-constrained settings (e.g., edge
devices and smartphones), where character-based representation is effective in
reducing the overall model size (in terms of parameters). We use WikiText-103
benchmark to simulate broad prompts and demonstrate that character models rival
word models in exact match accuracy for the autocomplete task, when controlled
for the model size. For instance, we show that a 20M parameter character model
performs similar to an 80M parameter word model in the vanilla setting. We
further propose novel methods to improve character models by incorporating
inductive bias in the form of compositional information and representation
transfer from large word models. Datasets and code used in this work are
available at https://github.com/UBC-NLP/char_autocomplete.


  In order to understand the relative expressive power of larger concurrent
programming languages, we analyze translations of small process calculi which
model the communication and synchronization of concurrent processes. The source
language SYNCSIMPLE is a minimalistic model for message passing concurrency
while the target language LOCKSIMPLE is a minimalistic model for shared memory
concurrency. The former is a calculus with synchronous communication of
processes, while the latter has synchronizing mutable locations - called locks
- that behave similarly to binary semaphores. The criteria for correctness of
translations is that they preserve and reflect may-termination and
must-termination of the processes. We show that there is no correct
compositional translation from SYNCSIMPLE to LOCKSIMPLE that uses one or two
locks, independent from the initialisation of the locks. We also show that
there is a correct translation that uses three locks. Also variants of the
locks are taken into account with different blocking behavior.


  Zoom metalens doublet exhibits unprecedented advantages over the traditional
zoom lens in many aspects, like ultra-compactness, CMOS compatibility, and
miniaturization. However, most of them can only work in a narrow band due to
chromatic aberration. Here, we numerically demonstrate a broadband achromatic
zoom metalens doublet inspired by the Moir\'e lens principle. This design is
achieved by globally optimizing the multi-wavelength phase profiles of the
metalens doublet in the visible. The doublet can achieve achromatic continuous
1-10 zoom range at wavelengths of 440 nm, 540 nm, and 640 nm, featuring high
focusing efficiency up to 86.5% and polarization insensitivity.


  Recommender systems, medical diagnosis, network security, etc., require
on-going learning and decision-making in real time. These -- and many others --
represent perfect examples of the opportunities and difficulties presented by
Big Data: the available information often arrives from a variety of sources and
has diverse features so that learning from all the sources may be valuable but
integrating what is learned is subject to the curse of dimensionality. This
paper develops and analyzes algorithms that allow efficient learning and
decision-making while avoiding the curse of dimensionality. We formalize the
information available to the learner/decision-maker at a particular time as a
context vector which the learner should consider when taking actions. In
general the context vector is very high dimensional, but in many settings, the
most relevant information is embedded into only a few relevant dimensions. If
these relevant dimensions were known in advance, the problem would be simple --
but they are not. Moreover, the relevant dimensions may be different for
different actions. Our algorithm learns the relevant dimensions for each
action, and makes decisions based in what it has learned. Formally, we build on
the structure of a contextual multi-armed bandit by adding and exploiting a
relevance relation. We prove a general regret bound for our algorithm whose
time order depends only on the maximum number of relevant dimensions among all
the actions, which in the special case where the relevance relation is
single-valued (a function), reduces to $\tilde{O}(T^{2(\sqrt{2}-1)})$; in the
absence of a relevance relation, the best known contextual bandit algorithms
achieve regret $\tilde{O}(T^{(D+1)/(D+2)})$, where $D$ is the full dimension of
the context vector.


  Occluded person re-identification (Re-ID), the task of searching for the same
person's images in occluded environments, has attracted lots of attention in
the past decades. Recent approaches concentrate on improving performance on
occluded data by data/feature augmentation or using extra models to predict
occlusions. However, they ignore the imbalance problem in this task and can not
fully utilize the information from the training data. To alleviate these two
issues, we propose a simple yet effective method with Parallel Augmentation and
Dual Enhancement (PADE), which is robust on both occluded and non-occluded data
and does not require any auxiliary clues. First, we design a parallel
augmentation mechanism (PAM) to generate more suitable occluded data to
mitigate the negative effects of unbalanced data. Second, we propose the global
and local dual enhancement strategy (DES) to promote the context information
and details. Experimental results on three widely used occluded datasets and
two non-occluded datasets validate the effectiveness of our method. The code is
available at
https://github.com/littleprince1121/PADE_Parallel_Augmentation_and_Dual_Enhancement_for_Occluded_Person_ReID


  V1432 Aquilae is the only known eclipsing asynchronous polar. In this respect
it is unique and therefore merits our attention. We report the results of a
15-year campaign by the globally distributed Center for Backyard Astrophysics
to observe V1432 Aql and investigate its return to synchronism. Originally
knocked out of synchrony by a nova explosion before observing records began,
the magnetic white dwarf in V1432 Aql is currently rotating slower than the
orbital period but is gradually catching up. The fortuitously high inclination
of the binary orbit affords us the bonus of eclipses providing a regular clock
against which these temporal changes can be assessed. At the present rate,
synchronism should be achieved around 2100. The continually changing trajectory
of the accretion stream as it follows the magnetic field lines of the rotating
white dwarf produces a complex pattern of light emission which we have measured
and documented, providing comprehensive observational evidence against which
physical models of the system can be tested.


  The transport of angular momentum by magnetic fields is a crucial physical
process in formation and evolution of stars and disks. Because the ionization
degree in star forming clouds is extremely low, non-ideal magnetohydrodynamic
(MHD) effects such as ambipolar diffusion and Ohmic dissipation work strongly
during protostellar collapse. These effects have significant impacts in the
early phase of star formation as they redistribute magnetic flux and suppress
angular momentum transport by magnetic fields. We perform three-dimensional
nested-grid radiation magnetohydrodynamic (RMHD) simulations including Ohmic
dissipation and ambipolar diffusion. Without these effects, magnetic fields
transport angular momentum so efficiently that no rotationally supported disk
is formed even after the second collapse. Ohmic dissipation works only in a
relatively high density region within the first core and suppresses angular
momentum transport, enabling formation of a very small rotationally supported
disk after the second collapse. With both Ohmic dissipation and ambipolar
diffusion, these effects work effectively in almost the entire region within
the first core and significant magnetic flux loss occurs. As a result, a
rotationally supported disk is formed even before a protostellar core forms.
The size of the disk is still small, about 5 AU at the end of the first core
phase, but this disk will grow later as gas accretion continues. Thus the
non-ideal MHD effects can resolve the so-called magnetic braking catastrophe
while maintaining the disk size small in the early phase, which is implied from
recent interferometric observations.


  We present results for the QCD Equation of State at non-zero chemical
potentials corresponding to the conserved charges in QCD using Taylor expansion
upto sixth order in the baryon number, electric charge and strangeness chemical
potentials. The latter two are constrained by the strangeness neutrality and a
fixed electric charge to baryon number ratio. In our calculations, we use the
Highly Improved Staggered Quarks (HISQ) discretization scheme at physical quark
masses and at different values of the lattice spacings to control lattice
cut-off effects. Furthermore we calculate the pressure along lines of constant
energy density, which serve as proxies for the freeze-out conditions and
discuss their dependence on $\mu_B$ , which is necessary for hydrodynamic
modelling near freezeout. We also provide an estimate of the radius of
convergence of the Taylor series from the 6th order coefficients which provides
a new constraint on the location of the critical end-point in the T-$\mu_B$
plane of the QCD phase diagram.


  We study the origin of non-thermal emissions from the Galactic black hole
X-ray binary Cygnus X--1 which is a confirmed high mass microquasar. By analogy
with those methods used in studies of active galactic nuclei, we propose a
two-dimensional, time-dependent radiation model from the microquasar Cygnus
X--1. In this model, the evolution equation for relativistic electrons in a
conical jet are numerically solved by including escape, adiabatic and various
radiative losses. The radiative processes involved are synchrotron emission,
its self-Compton scattering, and inverse Compton scatterings of an accretion
disk and its surrounding stellar companion. This model also includes an
electromagnetic cascade process of an anisotropic $\gamma$-$\gamma$
interaction. We study the spectral properties of electron evolution and its
emission spectral characteristic at different heights of the emission region
located in the jet. We find that radio data from Cygnus X--1 are reproduced by
the synchrotron emission, the \emph{Fermi} LAT measurements by the synchrotron
emission and Comptonization of photons of the stellar companion, the TeV band
emission fluxes by the Comptonization of the stellar photons. Our results show
that: (1) Radio emission region extends from the binary system scales to the
termination of the jet. (2) The GeV band emissions should originate from the
distance close to the binary system scales. (3) The TeV band emissions could be
inside the binary system, and these emissions could be probed by the upcoming
CTA telescope. (4) The MeV tail emissions, which produces a strongly linearly
polarized signal, are emitted inside the binary system. The location of the
emissions is very close to the inner region of the jet.


  We prove that the near-horizon geometries of minimal gauged five-dimensional
supergravity preserve at least half of the supersymmetry. If the near-horizon
geometries preserve a larger fraction, then they are locally isometric to
$AdS_5$. Our proof is based on Lichnerowicz type theorems for two horizon Dirac
operators constructed from the supercovariant connection restricted to the
horizon sections, and on an application of the index theorem. An application is
that all half-supersymmetric five-dimensional horizons admit an
$\mathfrak{sl}(2, {\mathbb{R}})$ symmetry subalgebra.