  This paper proposes a resilient-backpropagation-neural-network-(Rprop-NN)
based algorithm for Photovoltaic (PV) maximum power point tracking (MPPT). A
supervision mechanism is proposed to calibrate the Rprop-NN-MPPT reference and
limit short-circuit current caused by incorrect prediction. Conventional MPPT
algorithms (e.g., perturb and observe (P&O), hill climbing, and incremental
conductance (Inc-Cond) etc.) are trial-and-error-based, which may result in
steady-state oscillations and loss of tracking direction under fast-changing
ambient environment. In addition, partial shading is also a challenge due to
the difficulty of finding the global maximum power point on a multi-peak
characteristic curve. As an attempt to address the aforementioned issues, a
novel Rprop-NN MPPT algorithm is developed and elaborated in this work.
Multiple case studies are carried out to verify the effectiveness of the
proposed algorithm.


  A formula for the cross section and event rate constant describing
recombination of N particles are derived in terms of general S-matrix elements.
Our result immediately yields the generalized Wigner threshold scaling for the
recombination of N bosons. A semi-analytic formula encapsulates the overall
scaling with energy and scattering length, as well as resonant modifications by
the presence of borromean N-body states near the threshold collision energy in
the entrance channel. We then apply our model to the case of four-boson
recombination into an Efimov trimer and a free atom.


  The microscopic mechanism governing the zero-resistance flow of current in
some iron-based, high-temperature superconducting materials is not well
understood up to now. A central issue concerning the investigation of these
materials is their superconducting gap symmetry and structure. Here we present
a combined study of low-temperature specific heat and scanning tunnelling
microscopy measurements on single crystalline FeSe. The results reveal the
existence of at least two superconducting gaps which can be represented by a
phenomenological two-band model. The analysis of the specific heat suggests
significant anisotropy in the gap magnitude with deep gap minima. The tunneling
spectra display an overall "U"-shaped gap close to the Fermi level away as well
as on top of twin boundaries. These results are compatible with the anisotropic
nodeless models describing superconductivity in FeSe.


  The Lyman-alpha forest is a unique probe of large-scale matter density
fluctuations at high redshift (z > 2). It is possible to obtain 3D maps of the
matter distribution from Lyman-alpha data, using tomographic reconstruction
methods. Here, we present the largest tomographic map of matter fluctuations at
z > 2, over the Gpc^3 volume covered by Lyman-alpha forest from SDSS-IV quasar
spectra in the Stripe 82 field. We present a catalog of high-redshift voids
constructed from this map. The measurement of the cross-correlation between
these voids and the Lyman-alpha forest provides the first observation of the
matter velocity flow around voids, through the RSD effect, at such high
redshift. The data is in good agreement with simulations and is well adjusted
with a linear, Kaiser velocity model.


  A method for calculating the pressure tensor in constant-volume Monte Carlo
simulations of convex bodies is presented. In contrast to other approaches, the
method requires only an isotropic scaling of the simulation box, and the
counting of simple geometric quantities characterizing overlapping pairs.
Non-sphericity presents no special difficulties. The result is expressed as a
sum of pairwise contributions, and can therefore be used to compute pressure
tensor profiles in a conventional way.


  This is a course on Random Matrix Theory which includes traditional as well
as advanced topics presented with an extensive use of classical logarithmic
plasma analogy and that of the quantum systems of one-dimensional interacting
fermions with inverse square interaction (Calogero-Sutherland model). Certain
non-invariant random matrix ensembles are also considered with the emphasis on
the eigenfunction statistics in them. The course can also be viewed as
introduction to theory of localization where the (non-invariant) random matrix
ensembles play a role of the toy models to illustrate functional methods based
on super-vector/super-matrix representations.


  This paper introduces a partial order on the maximal chains of any finite
bounded poset $P$ which has a CL-labeling $\lambda$. We call this the maximal
chain descent order induced by $\lambda$, denoted $P_{\lambda}(2)$. As a first
example, letting $P$ be the Boolean lattice and $\lambda$ its standard
EL-labeling gives $P_{\lambda}(2)$ isomorphic to the weak order of type A. We
discuss in depth other seemingly well-structured examples: the max-min
EL-labeling of the partition lattice gives maximal chain descent order
isomorphic to a partial order on certain labeled trees, and particular cases of
the linear extension EL-labelings of finite distributive lattices produce
maximal chain descent orders isomorphic to partial orders on standard Young
tableaux. We observe that the order relations which one might expect to be the
cover relations, those given by the "polygon moves" whose transitive closure
defines the maximal chain descent order, are not always cover relations.
Several examples illustrate this fact. Nonetheless, we characterize the
EL-labelings for which every polygon move gives a cover relation, and we prove
many well known EL-labelings do have the expected cover relations. One
motivation for $P_{\lambda}(2)$ is that its linear extensions give all of the
shellings of the order complex of $P$ whose restriction maps are defined by the
descents with respect to $\lambda$. This yields strictly more shellings of $P$
than the lexicographic ones induced by $\lambda$. Thus, the maximal chain
descent order $P_{\lambda}(2)$ might be thought of as encoding the structure of
the set of shellings induced by $\lambda$.


  The problem of time is a deep paradox in our physical description of the
world. According to Aristotle's relational theory, time is a measure of change
and does not exist on its own. In contrast, quantum mechanics, just like
Newtonian mechanics, is equipped with a master clock that dictates the
evolution of a system. This clock is infinitely precise and tacitly supplied
free of charge from outside physics. Not only does this absolute time make it
notoriously difficult to make a consistent theory of quantum gravity, it is
also the underlying problem in establishing the second law. Indeed, contrary to
our experience, the Wheeler-deWitt equation --a canonical quantization of
general relativity-- predicts a static universe. Similarly, when simply
concerned with the dynamics of a closed quantum system, there is no second law
because the Von Neumann entropy is invariant under unitary transformations.
Here we are mainly concerned with the latter problem and we show that it can be
resolved by attributing a minimal amount of resources to the measurement of
time. Although there is an absolute time in quantum mechanics, an observer can
only establish a time by measuring a clock. For a local measurement, the
minimal entropy production is equal to the number of ticks. This lower bound is
attained by a black hole.


  Combinatorial auctions (CA) are a well-studied area in algorithmic mechanism
design. However, contrary to the standard model, empirical studies suggest that
a bidder's valuation often does not depend solely on the goods assigned to him.
For instance, in adwords auctions an advertiser might not want his ads to be
displayed next to his competitors' ads. In this paper, we propose and analyze
several natural graph-theoretic models that incorporate such negative
externalities, in which bidders form a directed conflict graph with maximum
out-degree $\Delta$. We design algorithms and truthful mechanisms for social
welfare maximization that attain approximation ratios depending on $\Delta$.
  For CA, our results are twofold: (1) A lottery that eliminates conflicts by
discarding bidders/items independent of the bids. It allows to apply any
truthful $\alpha$-approximation mechanism for conflict-free valuations and
yields an $\mathcal{O}(\alpha\Delta)$-approximation mechanism. (2) For
fractionally sub-additive valuations, we design a rounding algorithm via a
novel combination of a semi-definite program and a linear program, resulting in
a cone program; the approximation ratio is $\mathcal{O}((\Delta \log \log
\Delta)/\log \Delta)$. The ratios are almost optimal given existing hardness
results.
  For the prominent application of adwords auctions, we present several
algorithms for the most relevant scenario when the number of items is small. In
particular, we design a truthful mechanism with approximation ratio $o(\Delta)$
when the number of items is only logarithmic in the number of bidders.


  I present a brief review of the properties of jets from X-ray binaries,
highlighting the disk-jet connection, in which there are strong correlations
between X-ray and radio power for black holes and for neutron star in low/hard
spectral states, and reduced emission in soft states. I discuss how some of the
new "deviant" black hole systems which follow the relation normally found for
neutron stars might fit into such a picture. I close by highlighting a few open
questions which might be best addressed with soft gamma-ray observations.


  The matching coefficients for the four-quark operators in NRQCD (NRQED) are
calculated at one loop using dimensional regularization for ultraviolet and
infrared divergences. The matching for the electromagnetic current follows
easily from our results. Both the unequal and equal mass cases are considered.
The role played by the Coulomb infrared singularities is explained in detail.


  We propose an optimization method for the automatic design of approximate
multipliers, which minimizes the average error according to the operand
distributions. Our multiplier achieves up to 50.24% higher accuracy than the
best reproduced approximate multiplier in DNNs, with 15.76% smaller area,
25.05% less power consumption, and 3.50% shorter delay. Compared with an exact
multiplier, our multiplier reduces the area, power consumption, and delay by
44.94%, 47.63%, and 16.78%, respectively, with negligible accuracy losses. The
tested DNN accelerator modules with our multiplier obtain up to 18.70% smaller
area and 9.99% less power consumption than the original modules.


  Medical imaging plays a significant role in clinical practice of medical
diagnosis, where the text reports of the images are essential in understanding
them and facilitating later treatments. By generating the reports
automatically, it is beneficial to help lighten the burden of radiologists and
significantly promote clinical automation, which already attracts much
attention in applying artificial intelligence to medical domain. Previous
studies mainly follow the encoder-decoder paradigm and focus on the aspect of
text generation, with few studies considering the importance of cross-modal
mappings and explicitly exploit such mappings to facilitate radiology report
generation. In this paper, we propose a cross-modal memory networks (CMN) to
enhance the encoder-decoder framework for radiology report generation, where a
shared memory is designed to record the alignment between images and texts so
as to facilitate the interaction and generation across modalities. Experimental
results illustrate the effectiveness of our proposed model, where
state-of-the-art performance is achieved on two widely used benchmark datasets,
i.e., IU X-Ray and MIMIC-CXR. Further analyses also prove that our model is
able to better align information from radiology images and texts so as to help
generating more accurate reports in terms of clinical indicators.


  A heuristic model procedure for determining satisfiability of CNF-formulae is
set up and described by nonlinear recursion relations for m (number of
clauses), n (number of variables) and clause filling k. The system mimicked by
the recursion undergoes a sharp transition from bounded running times (easy) to
uncontrolled runaway behaviour (hard). Thus the parameter space turns out to be
separated into regions with qualitatively different efficiency of the model
procedure. The transition results from a competition of exponential blow up by
branching versus growing number of orthogonal clauses.


  We show that B-model topological strings on local Calabi-Yau threefolds are
large N duals of matrix models, which in the planar limit naturally give rise
to special geometry. These matrix models directly compute F-terms in an
associated N=1 supersymmetric gauge theory, obtained by deforming N=2 theories
by a superpotential term that can be directly identified with the potential of
the matrix model. Moreover by tuning some of the parameters of the geometry in
a double scaling limit we recover (p,q) conformal minimal models coupled to 2d
gravity, thereby relating non-critical string theories to type II superstrings
on Calabi-Yau backgrounds.


  Diffraction of coherent x-ray beams is treated through the Fractionnal
Fourier transform. The transformation allow us to deal with coherent
diffraction experiments from the Fresnel to the Fraunhofer regime. The analogy
with the Huygens-Fresnel theory is first discussed and a generalized
uncertainty principle is introduced.


  The implications of the physical theory of quantum mechanics on the question
of realism is much a subject of sustaining interest, while the background
questions among physicists on how to think about all the theoretical notion and
`interpretation' of the theory remains controversial. Through a careful
analysis of the theoretical notions with the help of modern mathematical
perspectives, we give here a picture of quantum mechanics, as the basic theory
for `nonrelativistic' particle dynamics, that can be seen as being as much
about the physical reality as classical mechanics itself. The key is to fully
embrace the noncommutativity of the theory and see it as a notion about the
reality of physical quantities. Quantum reality is then just a noncommutative
version of the classical reality.


  Dataset bias is a significant challenge in machine learning, where specific
attributes, such as texture or color of the images are unintentionally learned
resulting in detrimental performance. To address this, previous efforts have
focused on debiasing models either by developing novel debiasing algorithms or
by generating synthetic data to mitigate the prevalent dataset biases. However,
generative approaches to date have largely relied on using bias-specific
samples from the dataset, which are typically too scarce. In this work, we
propose, DiffInject, a straightforward yet powerful method to augment synthetic
bias-conflict samples using a pretrained diffusion model. This approach
significantly advances the use of diffusion models for debiasing purposes by
manipulating the latent space. Our framework does not require any explicit
knowledge of the bias types or labelling, making it a fully unsupervised
setting for debiasing. Our methodology demonstrates substantial result in
effectively reducing dataset bias.


  Invariance under time translation (or stationarity) is probably one of the
most important assumptions made when investigating electromagnetic phenomena.
Breaking this assumption is expected to open up novel possibilities and result
in exceeding conventional limitations. However, to explore the field of
time-varying electromagnetic structures, we primarily need to contemplate the
fundamental principles and concepts from a nonstationarity perspective. Here,
we revisit one of those key concepts: The polarizability of a small particle,
assuming that its properties vary in time. We describe the creation of induced
dipole moment by external fields in a nonstationary, causal way, and introduce
a complex-valued function, called temporal complex polarizability, for
elucidating a nonstationary Hertzian dipole under time-harmonic illumination.
This approach can be extended to any subwavelength particle exhibiting electric
response. In addition, we also study the classical model of the polarizability
of an oscillating electron using the equation of motion whose damping
coefficient and natural frequency are changing in time. Next, we theoretically
derive the effective permittivity corresponding to time-varying media
(comprising free or bound electrons, or dipolar meta-atoms) and explicitly show
the differences with the conventional macroscopic Drude-Lorentz model. This
paper will hopefully pave the road towards better understanding of
nonstationary scattering from small particles and homogenization of
time-varying materials, metamaterials, and metasurfaces.


  We show in this paper that the roots $x_1$ and $x_2$ of a scalar quadratic
polynomial $ax^2+bx+c=0$ with real or complex coefficients $a$, $b$ $c$ can be
computed in a element-wise mixed stable manner, measured in a relative sense.
We also show that this is a stronger property than norm-wise backward
stability, but weaker than element-wise backward stability. We finally show
that there does not exist any method that can compute the roots in an
element-wise backward stable sense, which is also illustrated by some numerical
experiments.


  In this paper we show that an effective Hamiltonian fit with first principles
calculations predicts an order/disorder transition occurs in the high entropy
alloy MoNbTaW. Using the Alloy Theoretic Automated Toolset, we find T=0K
enthalpies of formation for all binaries containing Mo, Nb, Ta, and W, and in
particular we find the stable structures for binaries at equiatomic
concentrations are close in energy to the associated B2 structure, suggesting
that at intermediate temperatures a B2 phase is stabilized in MoNbTaW. Our
previously published hybrid Monte Carlo/molecular dynamics results for the
MoNbTaW system are analyzed to identify certain preferred chemical bonding
types. A mean field free energy model incorporating nearest neighbor bonds is
derived, allowing us to predict the mechanism of the order/disorder transition.
We find the temperature evolution of the system is driven by strong Mo-Ta
bonding. Comparison of the free energy model and our hybrid Monte
Carlo/molecular dynamics results suggest the existence of additional
low-temperature phase transitions in the system likely ending with phase
segregation into binary phases.


  The accelerated expansion of the universe can be interpreted as a quest for
satisfying holographic equipartition. It can be expressed by a simple law,
$\Delta V = \Delta t\left(N_{surf}- N_{bulk}\right)$ which leads to the
standard Friedmann equation. This novel idea suggested by Padmanabhan in the
context of general relativity has been generalized by Cai and Yang et al. to
Gauss-Bonnet and Lovelock gravities for a spatially flat universe in different
methods. We investigate the consistency of these generalizations with the
constraints imposed by the maximum entropy principle. Interestingly, both these
generalizations imply entropy maximization even if their basic assumptions are
different. Further, we analyze the consistency of Verlinde's emergent gravity
with the maximum entropy principle in the cosmological context. In particular,
we consider the generalization suggested by Shu and Gong, in which an energy
flux through the horizon is assumed, in addition. Even though the conceptual
formulations are different, these two emergent perspectives of gravity
describes a universe which behaves as an ordinary macroscopic system. Our
results provide further support to the emergent gravity paradigm.


  We refine the implementation of ensemble fermions for the electroweak sector
of the Standard Model, introduced previously. We consider the behavior of
different observables as the size of the ensemble is increased and show that
the dynamics converges for ensemble sizes small enough that simulations of the
entire electroweak sector become numerically tractable. We apply the method to
the computation of the effective preheating temperature during a fast
electroweak transition, relevant for Cold Electroweak Baryogenesis. We find
that this temperature is never below 20 GeV, and this in combination with the
early results convincingly rules out Standard Model CP-violation as the origin
of the baryon asymmetry of the Universe.


  Let $A_H$ be the Aronsson operator associated with a Hamiltonian $H(x,z,p).$
Aronsson operators arise from $L^\infty$ variational problems, two person game
theory, control problems, etc. In this paper, we prove, under suitable
conditions, that if $u\in W^{1,\infty}_{\rm loc}(\Omega)$ is simultaneously a
viscosity solution of both of the equations $A_H(u)=f(x)$ and $A_H(u)=g(x)$ in
$\Omega$, where $f, g\in C(\Omega),$ then $f=g.$ The assumption $u\in
W_{loc}^{1,\infty}(\Omega)$ can be relaxed to $u\in C(\Omega)$ in many
interesting situations. Also, we prove that if $f,g,u\in C(\Omega)$ and $u$ is
simultaneously a viscosity solution of the equations ${\Delta_\infty u\over
|Du|^2}=-f(x)$ and ${\Delta_{\infty}u\over |Du|^2}=-g(x)$ in $\Omega$ then
$f=g.$ This answers a question posed in Peres, Schramm, Scheffield and Wilson
[PSSW] concerning whether or not the value function uniquely determines the
running cost in the "tug-of-war" game.


  The growth rate of large scale structure can probe whether dark matter
clusters at gravitational strength or deviates from this, e.g. due to self
interactions. Measurement of the growth rate through redshift space distortions
in galaxy redshift surveys constrains the clustering strength, and its redshift
dependence. We compare such effects on growth to those from high redshift
deviations (e.g. early dark energy) or modified gravity, and give a simple,
highly accurate analytic prescription. Current observations can constrain the
dark matter clustering strength to F_{cl}=0.99\pm0.02 of standard, if all other
parameters are held fixed, but substantial covariances exist. Future galaxy
redshift surveys may constrain an evolving clustering strength to 28%,
marginalizing over the other parameters, or 4% if the dark energy parameters
are held fixed while fitting for dark matter growth. Tighter constraints on the
nature of dark matter could be obtained by combining cosmological and
astrophysical probes.


  We study the best-arm identification problem with fixed confidence when
contextual (covariate) information is available in stochastic bandits. Although
we can use contextual information in each round, we are interested in the
marginalized mean reward over the contextual distribution. Our goal is to
identify the best arm with a minimal number of samplings under a given value of
the error rate. We show the instance-specific sample complexity lower bounds
for the problem. Then, we propose a context-aware version of the
"Track-and-Stop" strategy, wherein the proportion of the arm draws tracks the
set of optimal allocations and prove that the expected number of arm draws
matches the lower bound asymptotically. We demonstrate that contextual
information can be used to improve the efficiency of the identification of the
best marginalized mean reward compared with the results of Garivier & Kaufmann
(2016). We experimentally confirm that context information contributes to
faster best-arm identification.


  We present a combined experimental and theoretical study on the role of
copolymer architecture in the self-assembly of binary PEO-PCL mixtures in
water-THF, and show that altering the chain geometry and composition of the
copolymers can control the form of the self-assembled structures and lead to
the formation of novel aggregates. First, using transmission electron
microscopy and turbidity measurements, we study a mixture of sphere-forming and
lamella-forming PEO-PCL copolymers, and show that increasing the molecular
weight of the lamella-former at a constant ratio of its hydrophilic and
hydrophobic components leads to the formation of highly-curved structures even
at low sphere-former concentrations. This result is explained using a simple
argument based on the effective volumes of the two sections of the diblock and
is reproduced in a coarse-grained mean-field model: self-consistent field
theory (SCFT). Using further SCFT calculations, we study the distribution of
the two copolymer species within the individual aggregates and discuss how this
affects the self-assembled structures. We also investigate a binary mixture of
lamella-formers of different molecular weights, and find that this system forms
vesicles with a wall thickness intermediate to those of the vesicles formed by
the two copolymers individually. This result is also reproduced using SCFT.
Finally, a mixture of sphere-former and a copolymer with a large hydrophobic
block is shown to form a range of structures, including novel elongated
vesicles.


  The unique capabilities of Swift that make it ideal for discovery and
follow-up of Gamma-Ray bursts also makes it the idea mission for discovery and
monitoring of X-ray Transients in the Milky Way and the Large and Small
Magellanic Clouds. The Burst Alert Telescope allows for detection of new
transient outbursts, the automated follow-up capabilities of Swift allow for
rapid observation and localization of the new transient in X-rays and
optical/UV bands, and Swift's rapid slewing capabilities allows for
low-overhead short observations to be obtained, opening up the possibility of
regular, sensitive, long term monitoring of transient outbursts that are not
possible with other currently operational X-ray missions. In this paper I
describe the methods of discovery of X-ray transients utilizing Swift's BAT and
also collaboration with the MAXI telescope. I also detail two examples of X-ray
transient science enabled by Swift: Swift discovery and monitoring observations
of MAXI J1659-152, a Black Hole candidate Low Mass X-ray Binary in the Galactic
Halo, which has the shortest known orbital period of any such system; and Swift
monitoring of IGR J00569-7226, an edge on Be/X-ray binary that displayed a
outburst in 2013 and 2014, and which monitoring by Swift allowed for detection
of dips, eclipses and the determination of the orbital parameters, utilizing a
measurement of doppler shifts in the pulsar period.


  In this work we re-analyze the data of GW170817, the first binary neutron
star (BNS) merger event, in two ways, including the parameterized equation of
state (EoS) method and gravitational wave (GW) parameter estimation analysis.
Three sets of data, including the combined LIGO/Virgo (HLV) data, the
LIGO-Hanford (H1) data and the LIGO-Livingston (L1) data, have been analyzed,
respectively. We confirm the bimodal probability distribution of the tidal
deformability of GW170817 with the HLV data and resolve the different
contributions of H1 and L1 detectors. Our simulation reveals a tendency of
``overestimating" the tidal parameter with the decreasing signal-to-noise ratio
(SNR). Such a tendency is likely caused by the dependence of the result on the
prior (which is not well understood and has been assumed to be
widely-distributed) in the low SNR case. Though this effect is interesting, the
slightly higher SNR of H1 than L1 at frequencies above $\sim 100$ Hz is
most-likely not the main reason for the lower tidal parameter region favored by
H1. In view of the large fluctuation of the expected tide parameter in the case
of low SNR, the different probability distributions favored by the L1 and H1
data of GW170817 are reasonable. We have also explored the dependence of
expected difference of SNRs of H1 and L1 detectors on the source locations in
the O3 and full sensitivity runs. Such maps are helpful in evaluating the
relative powers of individual detectors on measuring the tidal deformabilities
for the new double neutron star merger events.


  Time-resolved X-ray absorption spectroscopy (TR-XAS), based on
laser-pump/X-ray probe method, is powerful in capturing the change of
geometrical and electronic structure of the absorbing atom upon excitation.
TR-XAS data analysis is generally performed on the laser-on minus laser-off
difference spectrum. Here we present a new analysis scheme for the TR-XAS
difference fitting in both the Extended X-Ray Absorption Fine Structure (EXAFS)
and the X-ray Absorption Near Edge Structure (XANES) region. R-space EXAFS
difference fitting could quickly give main quantitative structure change of the
first shell and provide reliable constraint on the range of the variables in
XANES fit. XANES fitting part introduces global non-derivative optimization
algorithm and optimizes the local structure change in a flexible way where both
the core XAS calculation package and the search method in the fitting shell are
changeable. The scheme was applied to the TR-XAS difference analysis of
Fe(phen)3 spin crossover complex and yielded the reliable distance change and
the excitation population.


  We study weakly coupled antiferromagnetic spin chains in their ordered phase
by combinining an exact solution of the single-chain problem with an RPA
analysis of the interchain interaction. A single chain is described by a
quantum Sine-Gordon model and dynamical staggered susceptibilities are
determined by employing the formfactor approach to quantum correlation
functions. We consider both antiferromagnetic order encountered in quasi-1D
materials like $KCuF_3$ and spin-Peierls order as found in $CuGeO_3$.


  The generation and control of entanglement in a quantum mechanical system is
a critical element of nearly all quantum applications. Molecular systems are a
promising candidate, with numerous degrees of freedom able to be targeted.
However, knowledge of inter-system entanglement mechanisms in such systems is
limited. In this work, we demonstrate the generation of entanglement between
vibrational degrees of freedom in molecules via strong coupling to a cavity
mode driven by a weak coherent field. In a bi-molecular system, we show
entanglement can not only be generated between the cavity and molecular system,
but also between molecules. This process also results in the generation of
non-classical states of light, providing potential pathways for harnessing
entanglement in molecular systems.


  The ground-state electronic, structural, and magnetic properties of small
silver clusters, Ag$_n$ (2$\le$n$\le$22), have been studied using a linear
combination of atomic Gaussian-type orbitals within the density functional
theory. The results show that the silver atoms, which are diamagnetic in bulk
environment, can be magnetic when they are grouped together in clusters. The
Ag$_{13}$ cluster with icosahedral symmetry has the highest magnetic moment per
atom among the studied silver clusters. The cluster symmetry and the reduced
coordination number specific of small clusters reveal as a fundamental factor
for the onset of the magnetism.


  In this paper we determine the velocity, the energy and estimate writhe and
twist helicity contributions of vortex filaments in the shape of torus knots
and unknots (toroidal and poloidal coils) in a perfect fluid. Calculations are
performed by numerical integration of the Biot-Savart law. Vortex complexity is
parametrized by the winding number $w$, given by the ratio of the number of
meridian wraps to that of the longitudinal wraps. We find that for $w<1$ vortex
knots and toroidal coils move faster and carry more energy than a reference
vortex ring of same size and circulation, whereas for $w>1$ knots and poloidal
coils have approximately same speed and energy of the reference vortex ring.
Helicity is dominated by the writhe contribution. Finally, we confirm the
stabilizing effect of the Biot-Savart law for all knots and unknots tested,
that are found to be structurally stable over a distance of several diameters.
Our results also apply to quantized vortices in superfluid $^4$He.


  Due to its unique long-term coverage and high photometric precision,
observations from the Kepler asteroseismic investigation will provide us with
the possibility to sound stellar cycles in a number of solar-type stars with
asteroseismology. By comparing these measurements with conventional
ground-based chromospheric activity measurements we might be able to increase
our understanding of the relation between the chromospheric changes and the
changes in the eigenmodes.
  In parallel with the Kepler observations we have therefore started a
programme at the Nordic Optical Telescope to observe and monitor chromospheric
activity in the stars that are most likely to be selected for observations for
the whole satellite mission. The ground-based observations presented here can
be used both to guide the selection of the special Kepler targets and as the
first step in a monitoring programme for stellar cycles. Also, the
chromospheric activity measurements obtained from the ground-based observations
can be compared with stellar parameters such as ages and rotation in order to
improve stellar evolution models.


  The use of Unmanned Ground Vehicles (UGVs) and Unmanned Aerial Vehicles
(UAVs) has seen significant growth in the research community, industry, and
society. Many of these agents are equipped with communication systems that are
essential for completing certain tasks successfully. This has led to the
emergence of a new interdisciplinary field at the intersection of robotics and
communications, which has been further driven by the integration of UAVs into
5G and 6G communication networks. However, one of the main challenges in this
research area is how many researchers tend to oversimplify either the robotics
or the communications aspects, hindering the full potential of this new
interdisciplinary field. In this paper, we present some of the necessary
modeling tools for addressing these problems from both a robotics and
communications perspective, using the UAV communications relay as an example.


  Discrete-time quantum walks (DTQWs) provide a convenient platform for a
realisation of many topological phases in noninteracting systems. They often
offer more possibilities than systems with a static Hamiltonian. Nevertheless,
researchers are still looking for DTQW symmetries protecting topological phases
and for definitions of appropriate topological invariants. Although majority of
DTQW studies on this topic focus on the so called split-step quantum walk, two
distinct topological phases can be observed in more basic models. Here we infer
topological properties of the basic DTQWs directly from the mapping of the
Brillouin zone to the Bloch Hamiltonian. We show that for translation symmetric
systems they can be characterized by a homotopy relative to special points. We
also propose a new topological invariant corresponding to this concept. This
invariant indicates the number of edge states at the interface between two
distinct phases.


  We study learning problems involving arbitrary classes of functions $F$,
distributions $X$ and targets $Y$. Because proper learning procedures, i.e.,
procedures that are only allowed to select functions in $F$, tend to perform
poorly unless the problem satisfies some additional structural property (e.g.,
that $F$ is convex), we consider unrestricted learning procedures that are free
to choose functions outside the given class.
  We present a new unrestricted procedure that is optimal in a very strong
sense: the required sample complexity is essentially the best one can hope for,
and the estimate holds for (almost) any problem, including heavy-tailed
situations. Moreover, the sample complexity coincides with the what one would
expect if $F$ were convex, even when $F$ is not. And if $F$ is convex, the
procedure turns out to be proper. Thus, the unrestricted procedure is actually
optimal in both realms, for convex classes as a proper procedure and for
arbitrary classes as an unrestricted procedure.


  Galaxy redshift surveys are subject to incompleteness and inhomogeneous
sampling due to the various constraints inherent to spectroscopic observations.
This can introduce systematic errors on the summary statistics of interest,
which need to be mitigated in cosmological analysis to achieve high accuracy.
Standard practices involve applying weighting schemes based on completeness
estimates across the survey footprint, possibly supplemented with additional
weighting schemes accounting for density-dependent effects. In this work, we
concentrate on pure angular systematics and describe an alternative approach
consisting in analysing the galaxy two-point correlation function where angular
modes are nulled. By construction, this procedure removes all possible known
and unknown sources of angular observational systematics, but also part of the
cosmological signal.We use a modified Landy-Szalay estimator for the two-point
correlation function that relies on an additional random catalogue where
angular positions are randomly drawn from the galaxy catalogue, and provide an
analytical model to describe this modified statistic. We test the model by
performing an analysis of the full anisotropic clustering in mock catalogues of
luminous red and emission-line galaxies at 0.43 < z < 1.1. We find that the
model fully accounts for the modified correlation function in redshift space,
without introducing new nuisance parameters. The derived cosmological
parameters from the analysis of baryon acoustic oscillations and redshift-space
distortions display slightly larger statistical uncertainties, mostly for the
growth rate of structure parameter fs8 that exhibits a 50% statistical error
increase, but free from angular systematic error.


  Control of systems where the information between the controller, actuator,
and sensor can be lost or delayed can be challenging with respect to stability
and performance. One way to overcome the resulting problems is the use of
prediction based compensation schemes. Instead of a single input, a sequence of
(predicted) future controls is submitted and implemented at the actuator. If
suitable, so-called prediction consistent compensation and control schemes,
such as certain predictive control approaches, are used, stability of the
closed loop in the presence of delays and packet losses can be guaranteed. In
this paper, we show that control schemes employing prediction based delay
compensation approaches do posses inherent robustness properties. Specifically,
if the nominal closed loop system without delay compensation is ISS with
respect to perturbation and measurement errors, then the closed loop system
employing prediction based delay compensation techniques is robustly stable. We
analyze the influence of the prediction horizon on the robustness gains and
illustrate the results in simulation.


  The theory for nonlinear three-wave interaction in magnetized plasmas is
reconsidered using quantum hydrodynamics. The general coupling coefficients are
calculated for a generalized Bohm de Broglie term. It is found that the
Manley-Rowe relations are fulfilled only if the form of the particle dispersive
term coincides with the standard expression. The implications of our results
are discussed.


  The Susceptible-Infected-Recovered (SIR) epidemic model is extensively used
for the study of the spread of infectious diseases. Even that the exact
solution of the model can be obtained in an exact parametric form, in order to
perform the comparison with the epidemiological data a simple but highly
accurate representation of the time evolution of the SIR compartments would be
very useful. In the present paper we obtain a series representation of the
solution of the SIR model by using the Laplace-Adomian Decomposition Method to
solve the basic evolution equation of the model. The solutions are expressed in
the form of infinite series. The series representations of the time evolution
of the SIR compartments are compared with the exact numerical solutions of the
model. We find that there is a good agreement between the Laplace-Adomian
semianalytical solutions containing only three terms, and the numerical
results.


  One key metric for physical layer security is the secrecy capacity. This is
the maximum rate that a system can transmit with perfect secrecy. For a
Multiple Input Multiple Output (MIMO) system (a newer technology for 5G, 6G and
beyond) the secrecy capacity is not fully understood. For a Gaussian MIMO
channel, the secrecy capacity is a non-convex optimisation problem for which a
general solution is not available.
  Previous work by the authors showed that the secrecy capacity of a MIMO
system with a single eavesdrop antenna is concave to a cut off point. In this
work, which extends the previous paper, results are given for the region beyond
this cut off point. It is shown that, for certain parameters, the presented
scheme is concave to a point, and convex beyond it, and can therefore be solved
efficiently using existing convex optimisation software.


  In this paper, we are concerned with the stochastic SIS
(susceptible-infected-susceptible) and SIR (susceptible-infected-recovered)
models on high-dimensional lattices with random edge weights, where a
susceptible vertex is infected by an infectious neighbor at rate proportional
to the weight on the edge connecting them. All the edge weights are assumed to
be i.i.d.. Our main result gives mean field limits for survival probabilities
of the two models as the dimension grows to infinity, which extends the main
conclusion given in \cite{Xue2017} for classic stochastic SIS model.


  Let X be a variety of maximal Albanese dimension. In this paper we prove that
if \chi (\omega_X)=1 then the q(X)<=2dim X and if q(X)=2dim X, then X is
birational to a product of curves of genus 2.


  In this paper, we develop a system identification algorithm to identify a
model for unknown linear quantum systems driven by time-varying coherent
states, based on empirical single-shot continuous homodyne measurement data of
the system's output. The proposed algorithm identifies a model that satisfies
the physical realizability conditions for linear quantum systems, challenging
constraints not encountered in classical (non-quantum) linear system
identification. Numerical examples on a multiple-input multiple-output optical
cavity model are presented to illustrate an application of the identification
algorithm.


  The first measurement of the charged component of the underlying event using
the novel "jet-area/median" approach is presented for proton-proton collisions
at centre-of-mass energies of 0.9 and 7 TeV. The data were recorded in 2010
with the CMS experiment at the LHC. A new observable, sensitive to soft
particle production, is introduced and investigated inclusively and as a
function of the event scale defined by the transverse momentum of the leading
jet. Various phenomenological models are compared to data, with and without
corrections for detector effects. None of the examined models describe the data
satisfactorily.


  Trace norm regularization is a popular method of multitask learning. We give
excess risk bounds with explicit dependence on the number of tasks, the number
of examples per task and properties of the data distribution. The bounds are
independent of the dimension of the input space, which may be infinite as in
the case of reproducing kernel Hilbert spaces. A byproduct of the proof are
bounds on the expected norm of sums of random positive semidefinite matrices
with subexponential moments.


  We introduce the Free Music Archive (FMA), an open and easily accessible
dataset suitable for evaluating several tasks in MIR, a field concerned with
browsing, searching, and organizing large music collections. The community's
growing interest in feature and end-to-end learning is however restrained by
the limited availability of large audio datasets. The FMA aims to overcome this
hurdle by providing 917 GiB and 343 days of Creative Commons-licensed audio
from 106,574 tracks from 16,341 artists and 14,854 albums, arranged in a
hierarchical taxonomy of 161 genres. It provides full-length and high-quality
audio, pre-computed features, together with track- and user-level metadata,
tags, and free-form text such as biographies. We here describe the dataset and
how it was created, propose a train/validation/test split and three subsets,
discuss some suitable MIR tasks, and evaluate some baselines for genre
recognition. Code, data, and usage examples are available at
https://github.com/mdeff/fma


  We develop a unified approach for establishing rates of decay for the Fourier
transform of a wide class of dynamically defined measures. Among the key
features of the method is the systematic use of the $L^2$-flattening theorem
obtained in \cite{Khalil-Mixing}, coupled with non-concentration estimates for
the derivatives of the underlying dynamical system. This method yields
polylogarithmic Fourier decay for Diophantine self-similar measures, and
polynomial decay for Patterson-Sullivan measures of convex cocompact hyperbolic
manifolds, Gibbs measures associated to non-integrable $C^2$ conformal systems,
as well as stationary measures for carpet-like non-conformal iterated function
systems. Applications include essential spectral gaps on convex cocompact
hyperbolic manifolds, fractal uncertainty principles, and equidistribution
properties of typical vectors in fractal sets.


  This paper explores object detection in the small data regime, where only a
limited number of annotated bounding boxes are available due to data rarity and
annotation expense. This is a common challenge today with machine learning
being applied to many new tasks where obtaining training data is more
challenging, e.g. in medical images with rare diseases that doctors sometimes
only see once in their life-time. In this work we explore this problem from a
generative modeling perspective by learning to generate new images with
associated bounding boxes, and using these for training an object detector. We
show that simply training previously proposed generative models does not yield
satisfactory performance due to them optimizing for image realism rather than
object detection accuracy. To this end we develop a new model with a novel
unrolling mechanism that jointly optimizes the generative model and a detector
such that the generated images improve the performance of the detector. We show
this method outperforms the state of the art on two challenging datasets,
disease detection and small data pedestrian detection, improving the average
precision on NIH Chest X-ray by a relative 20% and localization accuracy by a
relative 50%.


  We present a thermodynamically consistent model describing the dynamics of a
multi-component mixture where one enzyme component catalyzes a reaction between
other components. We find that the catalytic activity alone can induce phase
separation for sufficiently active systems and large enzymes, without any
equilibrium interactions between components. In the limit of fast reaction
rates, binodal lines can be calculated using a mapping to an effective free
energy. We also explain how this catalysis-induced phase separation (CIPS) can
act to autoregulate the enzymatic activity, which points at the biological
relevance of this phenomenon.


  We present a simple and efficient auxiliary loss function for automatic
speech recognition (ASR) based on the connectionist temporal classification
(CTC) objective. The proposed objective, an intermediate CTC loss, is attached
to an intermediate layer in the CTC encoder network. This intermediate CTC loss
well regularizes CTC training and improves the performance requiring only small
modification of the code and small and no overhead during training and
inference, respectively. In addition, we propose to combine this intermediate
CTC loss with stochastic depth training, and apply this combination to a
recently proposed Conformer network. We evaluate the proposed method on various
corpora, reaching word error rate (WER) 9.9% on the WSJ corpus and character
error rate (CER) 5.2% on the AISHELL-1 corpus respectively, based on CTC greedy
search without a language model. Especially, the AISHELL-1 task is comparable
to other state-of-the-art ASR systems based on auto-regressive decoder with
beam search.


  RF pulse compressor is a device to convert a long RF pulse to a short one
with much higher peak RF magnitude. SLED can be regarded as the earliest RF
pulse compressor used in large scale linear accelerators. It is widely studied
around the world and applied in the BEPC and BEPCII linac for many years.
During the routine operation, the error and jitter effects will deteriorate the
SLED performance either on the output electromagnetic wave amplitude or phase.
The error effects mainly include the frequency drift induced by cooling water
temperature variation and the frequency/Q0/{\beta} unbalances between the two
energy storage cavities caused by mechanical fabrication or microwave tuning.
The jitter effects refer to the PSK switching phase and time jitters. In this
paper, we re-derived the generalized formulae for the conventional SLED used in
the BEPCII linac. At last, the error and jitter effects on the SLED performance
are investigated.


  The Cremona group is connected in any dimension and, endowed with its
topology, it is simple in dimension 2.
  -----
  Le groupe de Cremona est connexe en toute dimension et, muni de sa topologie,
il est simple en dimension 2.


  We address the problem of convex optimization with preference feedback, where
the goal is to minimize a convex function given a weaker form of comparison
queries. Each query consists of two points and the dueling feedback returns a
(noisy) single-bit binary comparison of the function values of the two queried
points. Here we consider the sign-function-based comparison feedback model and
analyze the convergence rates with batched and multiway (argmin of a set
queried points) comparisons. Our main goal is to understand the improved
convergence rates owing to parallelization in sign-feedback-based optimization
problems. Our work is the first to study the problem of convex optimization
with multiway preferences and analyze the optimal convergence rates. Our first
contribution lies in designing efficient algorithms with a convergence rate of
$\smash{\widetilde O}(\frac{d}{\min\{m,d\} \epsilon})$ for $m$-batched
preference feedback where the learner can query $m$-pairs in parallel. We next
study a $m$-multiway comparison (`battling') feedback, where the learner can
get to see the argmin feedback of $m$-subset of queried points and show a
convergence rate of $\smash{\widetilde O}(\frac{d}{ \min\{\log m,d\}\epsilon
})$. We show further improved convergence rates with an additional assumption
of strong convexity. Finally, we also study the convergence lower bounds for
batched preferences and multiway feedback optimization showing the optimality
of our convergence rates w.r.t. $m$.


  We investigate the environmental dependence of the gas-phase metallicity for
galaxies at $z=0$ to $z\gtrsim 2$ and the underlying physical mechanisms
driving this dependence using state-of-the-art cosmological hydrodynamical
simulations. We find that, at fixed stellar mass, central galaxies in massive
halos have lower gas-phase metallicity than those in low-mass halos. On the
contrary, satellite galaxies residing in more massive halos are more
metal-rich. The combined effect is that massive galaxies are more metal-poor in
massive halos, and low-mass galaxies are more metal-rich in massive halos. By
inspecting the environmental dependence of other galaxy properties, we identify
that the accretion of low-metallicity gas is responsible for the environmental
dependence of central galaxies at high $z$, whereas the AGN feedback processes
play a crucial role at low $z$. For satellite galaxies, we find that both the
suppression of gas accretion and the stripping of existing gas are responsible
for their environmental dependence, with negligible effect from the AGN
feedback. Finally, we show that the difference of gas-phase metallicity as a
function of stellar mass between protocluster and field galaxies agrees with
recent observational results, for example from the MAMMOTH-Grism survey.


  An innovative method based on the traversal of rays, originating from
detected particles, through a three-dimensional grid of voxels is presented.
The methodology has as main advantage that the outcome of the method is
independent of the order of the input; the order of the cameras and the order
of the rays presented as input to the algorithm does not influence the outcome.
The algorithm finds matches in decreasing value of match quality, ensuring that
globally best matches are matched before worse matches. The time complexity of
the algorithm is found to scale efficiently with the number of cameras and
particles. A variety of show-cases are given to exemplify the algorithm for
different geometries and different number of cameras. The method is designed
for the tracking of tracer or inertial particles in fluid mechanics, for which
the particle size generally ranges from O({\mu}m)--O(cm). The method, however,
does not impose a size limit on the particles.


  We synthesize and spectroscopically investigate monolayer C$_{60}$ on the
topological insulator (TI) Bi$_4$Te$_3$. This C$_{60}$/Bi$_4$Te$_3$
heterostructure is characterized by excellent translational order in a novel (4
x 4) C$_{60}$ superstructure on a (9 x 9) unit of Bi$_4$Te$_3$. We measure the
full two-dimensional energy band structure of C$_{60}$/Bi$_4$Te$_3$ using
angle-resolved photoemission spectroscopy (ARPES). We find that C$_{60}$
accepts electrons from the TI at room temperature but no charge transfer occurs
at low temperatures. We unravel this peculiar behaviour by Raman spectroscopy
of C$_{60}$/Bi$_4$Te$_3$ and density functional theory (DFT) calculations of
the electronegativity of C$_{60}$. Both methods are sensitive to orientational
order of C$_{60}$. At low temperatures, Raman spectroscopy shows a dramatic
intensity increase of the C$_{60}$ Raman signal, evidencing a transition to a
rotationally ordered state. DFT reveals that the orientational order of
C$_{60}$ at low temperatures has a higher electron affinity than at high
temperatures. These results neatly explain the temperature-dependent charge
transfer observed in ARPES. Our conclusions are supported by the appearance of
a strong photoluminescence from C$_{60}$/Bi$_4$Te$_3$ at low temperatures.


  Let $G$ be a finite group and $cd(G)$ denote the set of complex irreducible
character degrees of $G$. In this paper, we prove that if $G$ is a finite group
and $H$ is an almost simple group whose socle is Mathieu group such that $cd(G)
=cd(H)$, then there exists an Abelian subgroup $A$ of $G$ such that $G/A$ is
isomorphic to $H$. This study is heading towards the study of an extension of
Huppert's conjecture (2000) for almost simple groups.


  Advertising becomes one of the most popular ways of monetizing an online
transaction platform. Usually, sponsored advertisements are posted on the most
attractive positions to enhance the number of clicks. However, multiple
e-commerce platforms are aware that this action may hurt the search experience
of users, even though it can bring more incomes. To balance the advertising
revenue and the user experience loss caused by advertisements, most e-commerce
platforms choose fixing some areas for advertisements and adopting some simple
restrictions on the number of ads, such as a fixed number K of ads on the top
positions or one advertisement for every N organic searched results. Different
from these common rules of treating the allocation of ads separately (from the
arrangements of the organic searched items), in this work we build up an
integrated system with mixed arrangements of advertisements and organic items.
We focus on the design of truthful mechanisms to properly list the
advertisements and organic items and optimally trade off the instant revenue
and the user experience. Furthermore, for different settings and practical
requirements, we extend our optimal truthful allocation mechanisms to cater for
these realistic conditions. Finally, we exert several experiments to verify the
improvement of our mechanism compared to the common-used advertising mechanism.


  A Majorana-based qubit can form within the fermion parity subspace of a
two-island topological superconductor setup consisting of four Majorana zero
modes. We study the relaxation time of this Majorana qubit induced by the
intrinsic Majorana-phonon interaction in combination with single electron
tunneling between the two islands. The theory is developed for both the
spinless p-wave Kitaev chain model and the spin-orbit-coupled semiconductor
nanowire with induced superconductivity and Zeeman splitting. We systematically
discuss the dependence of the relaxation rate on Majorana charge distribution
(varying with the chemical potential, magnetic field, superconducting paring,
spin-orbit coupling and island length) as well as on phonon wavelength and the
length of the tunnel barrier. Importantly, the accompanied phonon energy can be
tuned by the voltage bias over the tunnel barrier, leading to relatively easy
manipulation and suppression of the relaxation rate.


  Taking a rigorous formal approach, we consider sequential decision problems
involving observable variables, unobservable variables, and action variables.
We can typically assume the property of extended stability, which allows
identification (by means of G-computation) of the consequence of a specified
treatment strategy if the unobserved variables are, in fact, observed - but not
generally otherwise. However, under certain additional special conditions we
can infer simple stability (or sequential ignorability), which supports
G-computation based on the observed variables alone. One such additional
condition is sequential randomization, where the unobserved variables
essentially behave as random noise in their effects on the actions. Another is
sequential irrelevance, where the unobserved variables do not influence future
observed variables. In the latter case, to deduce sequential ignorability in
full generality requires additional positivity conditions. We show here that
these positivity conditions are not required when all variables are discrete.


  Trapped atomic ion crystals are a leading platform for quantum simulations of
spin systems, with programmable and long-range spin-spin interactions mediated
by excitations of phonons in the crystal. We describe a complementary approach
for quantum simulations of bosonic systems using phonons in trapped-ion
crystals, here mediated by excitations of the trapped ion spins. The scheme
features a high degree of programability over a dense graph of bosonic
couplings and is suitable for hard problems such as boson sampling and
simulations of long range bosonic and spin-boson Hamiltonians.


  We study the chiral phase transition in (2+1)d strongly coupled U(N) lattice
gauge theories with staggered fermions. We show with high precision simulations
performed directly in the chiral limit that these models undergo a
Berezinski-Kosterlitz-Thouless (BKT) transition. We also show that this
universality class is unaffected even in the large N limit.


  I report on a study of finite temperature QCD by the CP-PACS Collaboration
toward a precise determination of the equation of state with dynamical u,d
quarks. Based on a systematic simulation using improved Wilson-type quarks on
lattices with temporal size $N_t=4$ and 6, the energy density and pressure are
calculated as functions of temperature and renormalized light quark mass in the
range $T/T_c \approx 0.7$--2.5 and $m_{\rm PS}/m_{\rm V} = 0.65$--0.95. Results
for $N_t=4$ are found to contain significant scaling violations, while results
for $N_t=6$ are suggested to be not far from the continuum limit. On the other
hand, the quark mass dependence in the EOS turned out to be small for $m_{\rm
PS}/m_{\rm V} \simlt 0.8$.


  We argue that the recently proposed principle of relative locality offers a
new way to resolve the black hole information puzzle.


  The GAPS experiment is foreseen to carry out a dark matter search by
measuring low-energy cosmic-ray antideuterons and antiprotons with a novel
detection approach. It will provide a new avenue to access a wide range of
different dark matter models and masses from about 10GeV to 1TeV. The
theoretically predicted antideuteron flux resulting from secondary interactions
of primary cosmic rays is very low. Well-motivated theories beyond the Standard
Model contain viable dark matter candidates, which could lead to a significant
enhancement of the antideuteron flux due to annihilation or decay of dark
matter particles. This flux contribution is believed to be especially large at
low energies, which leads to a high discovery potential for GAPS. The GAPS
low-energy antiproton search will provide some of the most stringent
constraints on ~30GeV dark matter, will provide the best limits on primordial
black hole evaporation on galactic length scales, and explore new discovery
space in cosmic-ray physics.
  GAPS is designed to achieve its goals via long duration balloon flights at
high altitude in Antarctica. The detector itself will consist of 10 planes of
Si(Li) solid state detectors and a surrounding time-of-flight system.
Antideuterons and antiprotons will be slowed down in the Si(Li) material,
replace a shell electron and form an excited exotic atom. The atom will be
deexcited by characteristic X-ray transitions and will end its life by the
formation of an annihilation pion/proton star. This unique event structure will
deliver a nearly background free detection possibility.


  Recent studies have demonstrated the potential of antiferromagnets as the
active component in spintronic devices. This is in contrast to their current
passive role as pinning layers in hard disk read heads and magnetic memories.
Here we report the epitaxial growth of a new high-temperature antiferromagnetic
material, tetragonal CuMnAs, which exhibits excellent crystal quality, chemical
order and compatibility with existing semiconductor technologies. We
demonstrate its growth on the III-V semiconductors GaAs and GaP, and show that
the structure is also lattice matched to Si. Neutron diffraction shows
collinear antiferromagnetic order with a high Ne\'el temperature. Combined with
our demonstration of room-temperature exchange coupling in a CuMnAs/Fe bilayer,
we conclude that tetragonal CuMnAs films are suitable candidate materials for
antiferromagnetic spintronics.


  Gossip algorithms are widely used to solve the distributed consensus problem,
but issues can arise when nodes receive multiple signals either at the same
time or before they are able to finish processing their current work load.
Specifically, a node may assume a new state that represents a linear
combination of all received signals; even if such a state makes no sense in the
problem domain. As a solution to this problem, we introduce the notion of
conflict resolution for gossip algorithms and prove that their application
leads to a valid consensus state when the underlying communication network
possesses certain properties. We also introduce a methodology based on
absorbing Markov chains for analyzing gossip algorithms that make use of these
conflict resolution algorithms. This technique allows us to calculate both the
probabilities of converging to a specific consensus state and the time that
such convergence is expected to take. Finally, we make use of simulation to
validate our methodology and explore the temporal behavior of gossip algorithms
as the size of the network, the number of states per node, and the network
density increase.


  In this paper, we present a control framework that allows magnetic microrobot
teams to accomplish complex micromanipulation tasks captured by global Linear
Temporal Logic (LTL) formulas. To address this problem, we propose an optimal
control synthesis method that constructs discrete plans for the robots that
satisfy both the assigned tasks as well as proximity constraints between the
robots due to the physics of the problem. Our proposed algorithm relies on an
existing optimal control synthesis approach combined with a novel
sampling-based technique to reduce the state-space of the product automaton
that is associated with the LTL specifications. The synthesized discrete plans
are executed by the microrobots independently using local magnetic fields.
Simulation studies show that the proposed algorithm can address large-scale
planning problems that cannot be solved using existing optimal control
synthesis approaches. Moreover, we present experimental results that also
illustrate the potential of our method in practice. To the best of our
knowledge, this is the first control framework that allows independent control
of teams of magnetic microrobots for temporal micromanipulation tasks.


  We extend the ideas of (Barbour 1990) and use Stein's method to obtain a
bound on the distance between a scaled time-changed random walk and a
time-changed Brownian Motion. We then apply this result to bound the distance
between a time-changed compensated scaled Poisson process and a time-changed
Brownian Motion. This allows us to bound the distance between a process whose
dynamics resemble those of the Moran model with mutation and a process whose
dynamics resemble those of the Wright-Fisher diffusion with mutation upon
noting that the former may be expressed as a difference of two time-changed
Poisson processes and the diffusive part of the latter may be expressed as a
time-changed Brownian Motion. The method is applicable to a much wider class of
examples satisfying the Stroock-Varadhan theory of diffusion approximation.


  We performed a systematic search for broad-velocity-width molecular features
(BVFs) in the disk part of our Galaxy by using the CO J = 1-0 survey data
obtained with the Nobeyama Radio Observatory 45 m telescope. From this search,
58 BVFs were identified. In comparisons with the infrared and radio continuum
images, 36 BVFs appeared to have both infrared and radio continuum
counterparts, and 15 of them are described as molecular outflows from young
stellar objects in the literature. In addition, 21 BVFs have infrared
counterparts only, and eight of them are described as molecular outflows in the
literature. One BVF (CO 16.134-0.553) does not have any luminous counterpart in
the other wavelengths, which suggests that it may be an analog of high-velocity
compact clouds in the Galactic center.


  We provide combinatorial arguments based on a two-dimensional extension of a
locally-free semigroup allowing us to compute the growth rate, $\Lambda$, of
the partition function $Z_N=N^{\theta}\Lambda^N$ of the $N$-particle directed
animals ($N\gg 1$) on a simple cubic lattice in a three-dimensional space.
Establishing the bijection between the particular configuration of the lattice
animal and a class of equivalences of words in the 2D projective locally-free
semigroup, we find we find $\ln \Lambda = \lim_{N\to\infty} \ln Z_N / N$ with
$\Lambda= 2(\sqrt{2}+1) \approx 4.8284$.


  Learning from synthetic images plays an important role in facial expression
recognition task due to the difficulties of labeling the real images, and it is
challenging because of the gap between the synthetic images and real images.
The fourth Affective Behavior Analysis in-the-wild Competition raises the
challenge and provides the synthetic images generated from Aff-Wild2 dataset.
In this paper, we propose a hand-assisted expression recognition method to
reduce the gap between the synthetic data and real data. Our method consists of
two parts: expression recognition module and hand prediction module. Expression
recognition module extracts expression information and hand prediction module
predicts whether the image contains hands. Decision mode is used to combine the
results of two modules, and post-pruning is used to improve the result. F1
score is used to verify the effectiveness of our method.


  We describe a novel, "focusable", scalable, distributed web crawler based on
GNU/Linux and PostgreSQL that we designed to be easily extendible and which we
have released under a GNU public licence. We also report a first use case
related to an analysis of Twitter's streams about the french 2012 presidential
elections and the URL's it contains.


  In this paper we introduce two new DSm fusion conditioning rules with
example, and as a generalization of them a class of DSm fusion conditioning
rules, and then extend them to a class of DSm conditioning rules.


  We investigate here the confluence of singularities of Mathieu differential
equation by means of the Lie algebra contraction of the Lie algebra of the
motion group M(2) on the Heisenberg Lie algebra H(3). A similar approach for
the Lam\'e equation in terms of the Lie algebra contraction of $SO_0(2,1)$ on
the Lie algebra of the motion group M(2) is outlined.


  Extended guiding-center Vlasov-Maxwell equations are derived under the
assumption of time-dependent and inhomogeneous electric and magnetic fields
that obey the standard guiding-center space-time-scale orderings. The
guiding-center Vlasov-Maxwell equations are derived to second order, which
contain dipole and quadrupole contributions to the guiding-center polarization
and magnetization that include finite-Larmor-radius corrections. Exact
energy-momentum conservation laws are derived from the variational formulation
of these higher-order guiding-center Vlasov-Maxwell equations.


  Live Action Role-Playing (LARP) games and similar experiences are becoming a
popular game genre. Here, we discuss how artificial intelligence techniques,
particularly those commonly used in AI for Games, could be applied to LARP. We
discuss the specific properties of LARP that make it a surprisingly suitable
application field, and provide a brief overview of some existing approaches. We
then outline several directions where utilizing AI seems beneficial, by both
making LARPs easier to organize, and by enhancing the player experience with
elements not possible without AI.


  Pattern recognition in neuroimaging distinguishes between two types of
models: encoding- and decoding models. This distinction is based on the insight
that brain state features, that are found to be relevant in an experimental
paradigm, carry a different meaning in encoding- than in decoding models. In
this paper, we argue that this distinction is not sufficient: Relevant features
in encoding- and decoding models carry a different meaning depending on whether
they represent causal- or anti-causal relations. We provide a theoretical
justification for this argument and conclude that causal inference is essential
for interpretation in neuroimaging.


  In a parallel discrete-event simulation (PDES) scheme, tasks are distributed
among processing elements (PEs), whose progress is controlled by a
synchronization scheme. For lattice systems with short-range interactions, the
progress of the conservative PDES scheme is governed by the Kardar-Parisi-Zhang
equation from the theory of non-equilibrium surface growth. Although the
simulated (virtual) times of the PEs progress at a nonzero rate, their standard
deviation (spread) diverges with the number of PEs, hindering efficient data
collection. We show that weak random interactions among the PEs can make this
spread nondivergent. The PEs then progress at a nonzero, near-uniform rate
without requiring global synchronizations.


  A low-dimensional model of large Prandtl-number ($P$) Rayleigh B\'{e}nard
convection is constructed using some of the important modes of pseudospectral
direct numerical simulations. A detailed bifurcation analysis of the
low-dimensional model for $P=6.8$ and aspect ratio of $2\sqrt{2}$ reveals a
rich instability and chaos picture: steady rolls, time-periodicity,
quasiperiodicity, phase locking, chaos, and crisis. Bifurcation analysis also
reveals multiple co-existing attractors, and a window with time-periodicity
after chaos. The results of the low-dimensional model matches quite closely
with some of the past simulations and experimental results where they observe
chaos in RBC through quasiperiodicity and phase locking.


  In the absence of external reference position information (e.g. GNSS) SLAM
has proven to be an effective method for indoor navigation. The positioning
drift can be reduced with regular loop-closures and global relaxation as the
backend, thus achieving a good balance between exploration and exploitation.
Although vision-based systems like laser scanners are typically deployed for
SLAM, these sensors are heavy, energy inefficient, and expensive, making them
unattractive for wearables or smartphone applications. However, the concept of
SLAM can be extended to non-optical systems such as magnetometers. Instead of
matching features such as walls and furniture using some variation of the ICP
algorithm, the local magnetic field can be matched to provide loop-closure and
global trajectory updates in a Gaussian Process (GP) SLAM framework. With a
MEMS-based inertial measurement unit providing a continuous trajectory, and the
matching of locally distinct magnetic field maps, experimental results in this
paper show that a drift-free navigation solution in an indoor environment with
millimetre-level accuracy can be achieved. The GP-SLAM approach presented can
be formulated as a maximum a posteriori estimation problem and it can naturally
perform loop-detection, feature-to-feature distance minimization, global
trajectory optimization, and magnetic field map estimation simultaneously.
Spatially continuous features (i.e. smooth magnetic field signatures) are used
instead of discrete feature correspondences (e.g. point-to-point) as in
conventional vision-based SLAM. These position updates from the ambient
magnetic field also provide enough information for calibrating the
accelerometer and gyroscope bias in-use. The only restriction for this method
is the need for magnetic disturbances (which is typically not an issue
indoors); however, no assumptions are required for the general motion of the
sensor.


  The quantum theory of optical coherence is applied to the scrutiny of the
statistical properties of the relic inflaton quanta. After adapting the
description of the quantized scalar and tensor modes of the geometry to the
analysis of intensity correlations, the normalized degrees of first-order and
second-order coherence are computed in the concordance paradigm and are shown
to encode faithfully the statistical properties of the initial quantum state.
The strongly bunched curvature phonons are not only super-Poissonian but also
super-chaotic. Testable inequalities are derived in the limit of large angular
scales and can be physically interpreted in the light of the tenets of Hanbury
Brown-Twiss interferometry. The quantum mechanical results are compared and
contrasted with different situations including the one where intensity
correlations are the result of a classical stochastic process. The survival of
second-order correlations (not necessarily related to the purity of the initial
quantum state) is addressed by defining a generalized ensemble where
super-Poissonian statistics is an intrinsic property of the density matrix and
turns out to be associated with finite volume effects which are expected to
vanish in the thermodynamic limit.


  We generalise the RS braneworld model by taking into account a general
stringy bulk containing the scalar dilaton field and the two-form Kalb-Ramond
field, apart from gravity. Assuming small fluctuations around a RS background,
the back-reacted warp factor is obtained. It is shown that the fine tuning
problem in connection with the Higgs mass reappears in a new guise and the
effective modular potential fails to stabilise the braneworld.


  We study the renormalization of dimension four composite operators and the
energy-momentum tensor in noncommutative complex scalar field theory. The
proper operator basis is defined and it is proved that the bare composite
operators are expressed via renormalized ones with the help of an appropriate
mixing matrix which is calculated in the one-loop approximation. The number and
form of the operators in the basis and the structure of the mixing matrix
essentially differ from those in the corresponding commutative theory and in
noncommutative real scalar field theory. We show that the energy-momentum
tensor in the noncommutative complex scalar field theory is defined up to six
arbitrary constants. The canonically defined energy-momentum tensor is not
finite and must be replaced by the "improved" one, in order to provide
finiteness. Suitable "improving" terms are found. Renormalization of dimension
four composite operators at zero momentum transfer is also studied. It is shown
that the mixing matrices are different for the cases of arbitrary and zero
momentum transfer. The energy-momentum vector, unlike the energy-momentum
tensor, is defined unambigously and does not require "improving", in order to
be conserved and finite, at least in the one-loop approximation.


  Most old globular clusters (GCs) in the Galaxy are observed to have internal
chemical abundance spreads in light elements. We discuss a new GC formation
scenario based on hierarchical star formation within fractal molecular clouds.
In the new scenario, a cluster of bound and unbound star clusters (`star
cluster complex', SCC) that have a power-law cluster mass function with a slope
(beta) of 2 is first formed from a massive gas clump developed in a dwarf
galaxy. Such cluster complexes and beta=2 are observed and expected from
hierarchical star formation. The most massive star cluster (`main cluster'),
which is the progenitor of a GC, can accrete gas ejected from asymptotic giant
branch (AGB) stars initially in the cluster and other low-mass clusters before
the clusters are tidally stripped or destroyed to become field stars in the
dwarf. The SCC is initially embedded in a giant gas hole created by numerous
supernovae of the SCC so that cold gas outside the hole can be accreted onto
the main cluster later. New stars formed from the accreted gas have chemical
abundances that are different from those of the original SCC. Using
hydrodynamical simulations of GC formation based on this scenario, we show that
the main cluster with the initial mass as large as [2-5]x10^5 Msun can accrete
more than 10^5 Msun gas from AGB stars of the SCC. We suggest that merging of
hierarchical star cluster complexes can play key roles in stellar halo
formation around GCs and self-enrichment processes of GCs.


  We present Spitzer IRS mid-infrared (5-35 micron) spectra of a complete
flux-limited sample (> 3 mJy at 8 micron) of young stellar object (YSO)
candidates selected on the basis of their infrared colors in the Serpens
Molecular Cloud. Spectra of 147 sources are presented and classified.
Background stars (with slope consistent with a reddened stellar spectrum and
silicate features in absorption), galaxies (with redshifted PAH features) and a
planetary nebula (with high ionization lines) amount to 22% of contamination in
this sample, leaving 115 true YSOs. Sources with rising spectra and ice
absorption features, classified as embedded Stage I protostars, amount to 18%
of the sample. The remaining 82% (94) of the disk sources are analyzed in terms
of spectral energy distribution shapes, PAHs and silicate features. The
presence, strength and shape of these silicate features are used to infer disk
properties for these systems. About 8% of the disks have 30/13 micron flux
ratios consistent with cold disks with inner holes or gaps, and 3% of the disks
show PAH emission. Comparison with models indicates that dust grains in the
surface of these disks have sizes of at least a few \mu\m. The 20 micron
silicate feature is sometimes seen in absence of the 10 micron feature, which
may be indicative of very small holes in these disks. No significant difference
is found in the distribution of silicate feature shapes and strengths between
sources in clusters and in the field. Moreover, the results in Serpens are
compared with other well-studied samples: the c2d IRS sample distributed over 5
clouds and a large sample of disks in the Taurus star-forming region. The
remarkably similar distributions of silicate feature characteristics in samples
with different environment and median ages - if significant - imply that the
dust population in the disk surface results from an equilibrium between dust
growth and destructive collision processes that are maintained over a few
million years for any YSO population irrespective of environment.


  Single impurity problem in iron-pnictide superconductors is investigated by
solving Bogoliubov-de Gennes (BdG) equation in the five-orbital model, which
enables us to distinguish s$_{+-}$ and s$_{++}$ superconducting states. We
construct a five-orbital model suitable to BdG analysis. This model reproduces
the results of random phase approximation in the uniform case. Using this
model, we study the local density of states around a non-magnetic impurity and
discuss the bound-state peak structure, which can be used for distinguishing
s$_{+-}$ and s$_{++}$ states. A bound state with nearly zero-energy is found
for the impurity potential $I\sim 1.0$ eV, while the bound state peaks stick to
the gap edge in the unitary limit. Novel multiple peak structure originated
from the multi-orbital nature of the iron pnictides is also found.


  A locally testable language L is a language with the property that for some
non negative integer k, called the order of local testability, whether or not a
word u is in the language L depends on (1) the prefix and suffix of the word u
of length k + 1 and (2) the set of intermediate substrings of length k of the
word u. For given k the language is called k-testable. The local testability
has a wide spectrum of generalizations. A set of procedures for deciding
whether or not a language given by its minimal automaton or by its syntactic
semigroup is locally testable, right or left locally testable, threshold
locally testable, strictly locally testable, or piecewise testable was
implemented in the package TESTAS written in C=C++. The bounds on order of
local testability of transition graph and order of local testability of
transition semigroup are also found. For given k, the k-testability of
transition graph is verified. We consider some approaches to verify these
procedures and use for this aim some auxiliary programs. The approaches are
based on distinct forms of presentation of a given finite automaton and on
algebraic properties of the presentation. New proof and fresh wording of
necessary and sufficient conditions for local testability of deterministic
finite automaton is presented.


  A quasi-Hermitian operator is an operator that is similar to its adjoint in
some sense, via a metric operator, i.e., a strictly positive self-adjoint
operator. Whereas those metric operators are in general assumed to be bounded,
we analyze the structure generated by unbounded metric operators in a Hilbert
space. It turns out that such operators generate a canonical lattice of Hilbert
spaces, that is, the simplest case of a partial inner product space
(PIP-space). We introduce several generalizations of the notion of similarity
between operators, in particular, the notion of quasi-similarity, and we
explore to what extend they preserve spectral properties. Then we apply some of
the previous results to operators on a particular PIP-space, namely, a scale of
Hilbert spaces generated by a metric operator. Finally, motivated by the recent
developments of pseudo-Hermitian quantum mechanics, we reformulate the notion
of pseudo-Hermitian operators in the preceding formalism.


  It is imperative for all stakeholders that digital forensics investigations
produce reliable results to ensure the field delivers a positive contribution
to the pursuit of justice across the globe. Some aspects of these
investigations are inevitably contingent on trust, however this is not always
explicitly considered or critically evaluated. Erroneously treating features of
the investigation as trusted can be enormously damaging to the overall
reliability of an investigations findings as well as the confidence that
external stakeholders can have in it. As an example, digital crime scenes can
be manipulated by tampering with the digital artefacts left on devices, yet
recent studies have shown that efforts to detect occurrences of this are rare
and argue that this leaves digital forensics investigations vulnerable to
accusations of inaccuracy. In this paper a new approach to digital forensics is
considered based on the concept of Zero Trust, an increasingly popular design
in network security. Zero Trust describes the practitioner mindset and
principles upon which the reliance on trust in network components is eliminated
in favour of dynamic verification of network interactions. An initial
definition of Zero Trust Digital Forensics will be proposed and then a specific
example considered showing how this strategy can be applied to digital forensic
investigations to mitigate against the specific risk of evidence tampering. A
definition of Zero Trust Digital Forensics is proposed, specifically that it is
a strategy adopted by investigators whereby each aspect of an investigation is
assumed to be unreliable until verified. A new principle will be introduced,
namely the multifaceted verification of digital artefacts that can be used by
practitioners who wish to adopt a Zero Trust Digital Forensics strategy during
their investigations...


  A classical problem in algebraic geometry is to construct smooth algebraic
varieties with prescribed properties. In the approach via smoothings, one first
constructs a degenerate scheme with the prescribed properties, and then shows
the existence of a smooth variety degenerating to this scheme. Logarithmic
geometry has given important new impulses to the second step of this approach,
which we explore in this book. Degenerations, in particular in the context of
mirror symmetry, often enjoy similar formal properties as smooth morphisms once
considered from the logarithmic perspective. Logarithmic deformation theory has
therefore become an effective tool for the construction of smoothings and the
transfer of properties between smooth nearby fibers and the singular special
fiber.
  The strongest existence result for deformations in classical algebraic
geometry is the Bogomolov--Tian--Todorov theorem for Calabi--Yau varieties. A
logarithmic variant, once established, constructs log smooth deformations.
However, the logarithmic Bogomolov--Tian--Todorov theorem has resisted efforts
to its proof for a while. Finally, a method to prove it was discovered in 2019
by Chan, Leung, and Ma.
  In this book, we explore this new approach to the logarithmic
Bogomolov--Tian--Todorov theorem. We prove several variants of the abstract
unobstructedness theorem, some of which are new and stronger than previously
known results. We investigate its application to the global deformation theory
of log smooth and mildly log singular spaces, obtaining unobstructedness
results for log Calabi--Yau spaces, some log Fano spaces, and line bundles.
Special care is taken to allow sufficiently mild log singularities, including
all log singularities that appear in the Gross--Siebert construction of toric
log Calabi--Yau mirror pairs.


  The high-magnification microlensing event KMT-2021-BLG-1077 exhibits a subtle
and complex anomaly pattern in the region around the peak. We analyze the
lensing light curve of the event with the aim of revealing the nature of the
anomaly. We test various models in combination with several interpretations. We
find that the anomaly cannot be explained by the usual three-body (2L1S and
1L2S) models. The 2L2S model improves the fit compared to the three-body
models, but it still leaves noticeable residuals. On the other hand, the 3L1S
interpretation yields a model explaining all the major anomalous features in
the lensing light curve. According to the 3L1S interpretation, the estimated
mass ratios of the lens companions to the primary are $\sim 1.56 \times
10^{-3}$ and $\sim 1.75 \times 10^{-3}$, which correspond to $\sim 1.6$ and
$\sim 1.8$ times the Jupiter/Sun mass ratio, respectively, and therefore the
lens is a multiplanetary system containing two giant planets. With the
constraints of the event time-scale and angular Einstein radius, it is found
that the host of the lens system is a low-mass star of mid-to-late M spectral
type with a mass of $M_{\rm h} = 0.14^{+0.19}_{-0.07}~M_\odot$, and it hosts
two gas giant planets with masses of $M_{\rm p_1}=0.22^{+0.31}_{-0.12}~M_{\rm
J}$ and $M_{\rm p_2}=0.25^{+0.35}_{-0.13}~M_{\rm J}$. The planets lie beyond
the snow line of the host with projected separations of $a_{\perp, {\rm
p}_1}=1.26^{+1.41}_{-1.08}~{\rm AU}$ and $a_{\perp, {\rm
p}_2}=0.93^{+1.05}_{-0.80}~{\rm AU}$. The planetary system resides in the
Galactic bulge at a distance of $D_{\rm L}=8.24^{+1.02}_{-1.16}~{\rm kpc}$. The
lens of the event is the fifth confirmed multiplanetary system detected by
microlensing following OGLE-2006-BLG-109L, OGLE-2012-BLG-0026L,
OGLE-2018-BLG-1011L, and OGLE-2019-BLG-0468L.


  Following on the discovery of a strongly interacting quark-gluon plasma (QGP)
at RHIC, a program of detailed quarkonia measurements is crucial to
understanding the nature of deconfinement. Lattice QCD calculations suggest a
sequential melting of the quarkonia states in the deconfined medium. Such a
melting would lead to a suppression in the measured charmonium and bottomonium
yields. However, distinguishing a true suppression from shadowing, absorption,
and recombination effects requires detailed measurements of the charmonium
states (J/psi, psi', and chi_c) and bottomonium states (Y(1S), Y(2S), and
Y(3S)). Also, since measurements are needed not only in A+A, but also in p+p
for determining primary yields and in p+A for evaluating absorption, the
detector should perform well in all collision environments. To fully realize
the program outlined above, a new detector will be required at RHIC-II. We
present a proposal for a complete quarkonia program and the abilities of a new
detector, R2D, to meet the stated requirements. Comparisons will be made with
proposed upgrades to existing RHIC detectors and with the upcoming LHC program.


  Seminal results establish that the coverability problem for Vector Addition
Systems with States (VASS) is in EXPSPACE (Rackoff, '78) and is EXPSPACE-hard
already under unary encodings (Lipton, '76). More precisely, Rosier and Yen
later utilise Rackoff's bounding technique to show that if coverability holds
then there is a run of length at most $n^{2^{\mathcal{O}(d \log d)}}$, where
$d$ is the dimension and $n$ is the size of the given unary VASS. Earlier,
Lipton showed that there exist instances of coverability in $d$-dimensional
unary VASS that are only witnessed by runs of length at least
$n^{2^{\Omega(d)}}$. Our first result closes this gap. We improve the upper
bound by removing the twice-exponentiated $\log(d)$ factor, thus matching
Lipton's lower bound. This closes the corresponding gap for the exact space
required to decide coverability. This also yields a deterministic
$n^{2^{\mathcal{O}(d)}}$-time algorithm for coverability. Our second result is
a matching lower bound, that there does not exist a deterministic
$n^{2^{o(d)}}$-time algorithm, conditioned upon the Exponential Time
Hypothesis.
  When analysing coverability, a standard proof technique is to consider VASS
with bounded counters. Bounded VASS make for an interesting and popular model
due to strong connections with timed automata. Withal, we study a natural
setting where the counter bound is linear in the size of the VASS. Here the
trivial exhaustive search algorithm runs in $\mathcal{O}(n^{d+1})$-time. We
give evidence to this being near-optimal. We prove that in dimension one this
trivial algorithm is conditionally optimal, by showing that $n^{2-o(1)}$-time
is required under the $k$-cycle hypothesis. In general fixed dimension $d$, we
show that $n^{d-2-o(1)}$-time is required under the 3-uniform hyperclique
hypothesis.


  We introduce geometric and homological finiteness properties for countable
approximate groups via coarse geometry and then study these finiteness
properties for S-arithmetic reductive approximate groups. For S-arithmetic
approximate groups without infinite places we show that the finiteness length
is finite and compute this finiteness length explicitly. In the simple case it
is one less than the sum of the local ranks. This extends the Rank Theorem of
Bux, K\"ohl and the second author from positive characteristic to
characteristic zero. Our proof is based on a geometric version of their proof,
but except for some input from reduction theory it is characteristic free. This
indicates that the apparent differences between arithmetic groups in
characteristic zero and positive characteristic concerning finiteness
properties are entirely due to the presence of infinite places.


  Neural networks have proved to be very robust at processing unstructured data
like images, text, videos, and audio. However, it has been observed that their
performance is not up to the mark in tabular data; hence tree-based models are
preferred in such scenarios. A popular model for tabular data is boosted trees,
a highly efficacious and extensively used machine learning method, and it also
provides good interpretability compared to neural networks. In this paper, we
describe a novel architecture XBNet, which tries to combine tree-based models
with that of neural networks to create a robust architecture trained by using a
novel optimization technique, Boosted Gradient Descent for Tabular Data which
increases its interpretability and performance.


  We study the Yang-Lee zeros of a random matrix partition function with the
global symmetries of the QCD partition function. We consider both zeros in the
complex chemical potential plane and in the complex mass plane. In both cases
we find that the zeros are located on a curve. In the thermodynamic limit, the
zeros appear to merge to form a cut. The shape of this limiting curve can be
obtained from a saddle-point analysis of the partition function. An explicit
solution for the line of zeros in the complex chemical potential plane at zero
mass is given in the form of a transcendental equation.


  The discovery of pressure-induced superconductivity in helimagnets (CrAs,
MnP) has attracted considerable interest in understanding the relationship
between complex magnetism and unconventional superconductivity. However, the
nature of the magnetism and magnetic interactions that drive the unusual
double-helical magnetic order in these materials remains unclear. Here, we
report neutron scattering measurements of magnetic excitations in CrAs single
crystals at ambient pressure. Our experiments reveal well defined spin wave
excitations up to about 150 meV with a pseudogap below 7 meV, which can be
effectively described by the Heisenberg model with nearest neighbor exchange
interactions. Most surprisingly, the spin excitations are largely quenched
above the Neel temperature, in contrast to cuprates and iron pnictides where
the spectral weight is mostly preserved in the paramagnetic state. Our results
suggest that the helimagnetic order is driven by strongly frustrated exchange
interactions, and that CrAs is at the verge of itinerant and
correlation-induced localized states, which is therefore highly
pressure-tunable and favorable for superconductivity.


  The combined electric and acoustic stimulation (EAS) has demonstrated better
speech recognition than conventional cochlear implant (CI) and yielded
satisfactory performance under quiet conditions. However, when noise signals
are involved, both the electric signal and the acoustic signal may be
distorted, thereby resulting in poor recognition performance. To suppress noise
effects, speech enhancement (SE) is a necessary unit in EAS devices. Recently,
a time-domain speech enhancement algorithm based on the fully convolutional
neural networks (FCN) with a short-time objective intelligibility (STOI)-based
objective function (termed FCN(S) in short) has received increasing attention
due to its simple structure and effectiveness of restoring clean speech signals
from noisy counterparts. With evidence showing the benefits of FCN(S) for
normal speech, this study sets out to assess its ability to improve the
intelligibility of EAS simulated speech. Objective evaluations and listening
tests were conducted to examine the performance of FCN(S) in improving the
speech intelligibility of normal and vocoded speech in noisy environments. The
experimental results show that, compared with the traditional minimum-mean
square-error SE method and the deep denoising autoencoder SE method, FCN(S) can
obtain better gain in the speech intelligibility for normal as well as vocoded
speech. This study, being the first to evaluate deep learning SE approaches for
EAS, confirms that FCN(S) is an effective SE approach that may potentially be
integrated into an EAS processor to benefit users in noisy environments.


  This article presents results of the Z boson production in the proton-lead
collisions at $\sqrt{s_{\rm NN}} = 5.02$ TeV and $\sqrt{s_{\rm NN}}= 8.16$ TeV
collected in 2013 and 2016, respectively, by the LHCb detector at the LHC in
forward and backward rapidity. The great precision of the 2016 data are found
compatible with nPDFs theoretical predictions within large theoretical
uncertainties, and can be useful to constraint new predictions.


  The field dependence of the thermal switching rate of a ferromagnetic
material with uniaxial anisotropy was studied by solving the Fokker-Planck
equation. We derived the analytical expression of the thermal switching rate
using the mean first-passage time approach, and found that Brown's formula
[Phys. Rev. 130, 1677 (1963)] is applicable even in the low barrier limit by
replacing the attempt frequency with the proper factor which is expressed by
the error function.


  We construct a complete embedded minimal surface with arbitrary genus in the
doubled Schwarzschild 3-manifold. A classical desingularization method is used
for the construction.