  On the example of a real scalar field, an approach to quantization of
non-linear fields and construction of the perturbation theory with account of
spontaneous symmetry breaking is proposed. The method is based on using as the
main approximation of the relativistic self-consistent field model, in which
the influence of vacuum field fluctuations is taken into account when
constructing the one-particle states. The solutions of the self-consistent
equations determine possible states, which also include the states with broken
symmetries. Different states of the field are matched to particles, whose
masses are determined by both parameters of the Lagrangian and vacuum
fluctuations. The density of the vacuum energy in these states is calculated.
It is shown that the concept of Bogolubov's quasi-averages can naturally be
applied for definition of exact Green functions in the states with broken
symmetries. Equations for exact one- and two-point Green functions are
obtained.


  We consider the modeling of light beams propagating in highly forward-peaked
turbulent media by fractional Fokker-Planck equations and their approximations
by fractional Fermi pencil-beam models. We obtain an error estimate in a
1-Wasserstein distance for the latter model showing that beam spreading is well
captured by the Fermi pencil-beam approximation in the small diffusion limit.


  Using field theoretic approach, we study equilibrium shape deformation of a
vesicle induced by the presence of enclosed flexible polymers, which is a
simple model of drug delivery system or endocytosis. To evaluate the total free
energy of this system, it is necessary to calculate the bending elastic energy
of the membrane, the conformation entropy of the polymers and their
interactions. For this purpose, we combine phase field theory for the membrane
and self-consistent field theory for the polymers. Simulations on this coupled
model system for axiosymmetric shapes show a shape deformation of the vesicle
induced by introducing polymers into it. We examined the dependence of the
stability of the vesicle shape on the chain length of the polymers and the
packing ratio of the vesicle. We present a simple model calculation that shows
the relative stability of the prolate shape compared to the oblate shape.


  Water is routinely exposed to external electric fields (EFs). Whether, e.g.,
at physiological conditions, in contact with biological systems, or at the
interface of polar surfaces in countless technological and industrial settings,
water responds to EFs on the order of a few V/{\AA} in a manner that is still
under intense investigation. Dating back to the $19^{th}$ century, the
possibility of solidifying water upon applying an EF instead of adjusting
temperature and pressure -- a process known as electrofreezing -- is an
alluring promise that has canalized major efforts since, with uncertain
outcomes. In this work, we perform long \emph{ab initio} molecular dynamics
simulations \textcolor{black}{of water at ambient conditions exposed at EFs of
different intensities. While the response of single water molecules is almost
instantaneous, the cooperativity of the hydrogen bonds induces slower
reorganizations that can be captured by dividing the trajectories in disjoint
time windows and by performing analysis on each of them separately. Upon
adopting this approach, we find} that EFs of $0.10\leq$EFs$\leq0.15$~V/{\AA}
induce electrofreezing \textcolor{black}{occurring after $\sim150$~ps. We
observe a continuous transition to a disordered state characterized by frozen
dynamical properties, damped oscillations, lower energy, and enhanced local
structural properties. Therefore, we ascribe this state to} a new ferroelectric
amorphous phase, which we term f-GW (ferroelectric glassy water). Our work
represents the first evidence of electrofreezing of liquid water at ambient
conditions and therefore impacts several fields, from
\textcolor{black}{fundamental chemical physics to} biology
\textcolor{black}{and} catalysis.


  (abridged) Thanks to the recent discovery by Fermi of about fifty new
gamma-ray pulsars, it becomes possible to look for statistical properties of
their pulsed high-energy emission, especially their light-curves and
phase-resolved spectra. These pulsars emit by definition mostly gamma-ray
photons but some of them are also detected in the radio band. For those seen in
these two extreme energies, the relation between time lag of radio/gamma-ray
pulses and gamma-ray peak separation, in case both high-energy pulses are seen,
helps to put some constrain on the magnetospheric emission mechanisms and
location. This idea is analyzed in detail in this paper, assuming a polar cap
model for the radio pulses and the striped wind geometry for the pulsed
high-energy counterpart.
  Combining the time-dependent emissivity in the wind, supposed to be inverse
Compton radiation, with a simple polar cap emission model along and around the
magnetic axis, we compute the radio and gamma-ray light-curves, summarizing the
results in several phase plots. The phase lag as well as the gamma-ray peak
separation dependence on the pulsar inclination angle and on the viewing angle
are studied. Using the gamma-ray pulsar catalog compiled from the Fermi data,
we are able to predict the radio lag/peak separation relation and compare it
with available observations taken from this catalog.


  We present a systematic study of the nematic fluctuations in the iron
chalcogenide superconductor Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ ($0 \leq x \leq 0.53$)
using the elastoresistivity technique. Near $x = 0$, in proximity to the
double-stripe magnetic order of Fe$_{1+y}$Te, a diverging $B_{1g}$ nematic
susceptibility is observed. Upon increasing $x$, despite the absence of
magnetic order, the $B_{2g}$ nematic susceptibility increases and becomes
dominant, closely following the strength of the $(\pi, \pi)$ spin fluctuations.
Over a wide range of compositions ($0.17 \leq x \leq 0.53$), while the $B_{2g}$
nematic susceptibility follows a Curie temperature dependence (with zero Weiss
temperature) at low temperatures, it shows deviations from Curie-Weiss behavior
for temperatures higher than $50K$. This is the opposite of what is observed in
typical iron pnictides, where Curie-Weiss deviations are seen at low
temperatures. We attribute this unusual temperature dependence to a loss of
coherence of the $d_{xy}$ orbital, which is supported by our theoretical
calculations. Our results highlight the importance of orbital differentiation
on the nematic properties of iron-based materials.


  In this paper, we present a deep learning-based network, GCNv2, for
generation of keypoints and descriptors. GCNv2 is built on our previous method,
GCN, a network trained for 3D projective geometry. GCNv2 is designed with a
binary descriptor vector as the ORB feature so that it can easily replace ORB
in systems such as ORB-SLAM2. GCNv2 significantly improves the computational
efficiency over GCN that was only able to run on desktop hardware. We show how
a modified version of ORB-SLAM2 using GCNv2 features runs on a Jetson TX2, an
embedded low-power platform. Experimental results show that GCNv2 retains
comparable accuracy as GCN and that it is robust enough to use for control of a
flying drone.


  Let $\widehat{\Gamma}$ be the natural map given in \cite[\S1]{Oh12}. Here, we
construct a deformation $B_q$ of a Poisson algebra $B_1$ and a prime ideal $P$
of $B_q$ such that $\widehat{\Gamma}(P)$ is not a Poisson prime ideal of $B_1$.


  It has been suggested that the effects of renormalization significantly
reduce the amplitude of the inflationary spectra at scales measurable in the
cosmic microwave background. Via a gauge-invariant analysis, we compute the
renormalized scalar and tensor power spectra and follow their evolution in an
inflating universe that undergoes a transition to an FRW phase with a growing
horizon. For perturbations originating from Minkowski vacuum fluctuations, we
show that the standard prediction for the spectra on superhorizon scales is a
late-time attractor, while they are UV finite at all times. Our result is
independent of the equation of state after inflation, showing that the standard
prediction is fully robust.


  Path following controllers make the output of a control system approach and
traverse a pre-specified path with no apriori time parametrization. In this
paper we present a method for path following control design applicable to
framed curves generated by splines in the workspace of kinematically redundant
mechanical systems. The class of admissible paths includes self-intersecting
curves. Kinematic redundancies are resolved by designing controllers that solve
a suitably defined constrained quadratic optimization problem. By employing
partial feedback linearization, the proposed path following controllers have a
clear physical meaning. The approach is experimentally verified on a
4-degree-of-freedom (4-DOF) manipulator with a combination of revolute and
linear actuated links and significant model uncertainty.


  We consider a linear consensus system with n agents that can switch between r
different connectivity patterns. A natural question is which switching law
yields the best (or worst) possible speed of convergence to consensus? We
formulate this question in a rigorous manner by relaxing the switched system
into a bilinear consensus control system, with the control playing the role of
the switching law. A best (or worst) possible switching law then corresponds to
an optimal control. We derive a necessary condition for optimality, stated in
the form of a maximum principle (MP). Our approach, combined with suitable
algorithms for numerically solving optimal control problems, may be used to
obtain explicit lower and upper bounds on the achievable rate of convergence to
consensus. We also show that the system will converge to consensus for any
switching law if and only if a certain (n-1) dimensional linear switched system
converges to the origin for any switching law. For the case n=3 and r=2, this
yields a necessary and sufficient condition for convergence to consensus that
admits a simple graph-theoretic interpretation.


  The impurity spectral function is studied in coupled double quantum wires at
finite temperatures. Simple anisotropy in the confinement direction of the
wires leads to finite non-diagonal elements of the impurity spectral function
matrix. These non-diagonal elements are responsible for tunneling effects and
result in pronounced extra peak in the impurity spectral function up to
temperatures as high as 20 K.


  We implement a quantum error correction algorithm for bit-flip errors on the
topological toric code using deep reinforcement learning. An action-value
Q-function encodes the discounted value of moving a defect to a neighboring
site on the square grid (the action) depending on the full set of defects on
the torus (the syndrome or state). The Q-function is represented by a deep
convolutional neural network. Using the translational invariance on the torus
allows for viewing each defect from a central perspective which significantly
simplifies the state space representation independently of the number of defect
pairs. The training is done using experience replay, where data from the
algorithm being played out is stored and used for mini-batch upgrade of the
Q-network. We find performance which is close to, and for small error rates
asymptotically equivalent to, that achieved by the Minimum Weight Perfect
Matching algorithm for code distances up to $d=7$. Our results show that it is
possible for a self-trained agent without supervision or support algorithms to
find a decoding scheme that performs on par with hand-made algorithms, opening
up for future machine engineered decoders for more general error models and
error correcting codes.


  Crystallization is one of the most important phase transformations of first
order. In the case of metals and alloys, the liquid phase is the parent phase
of materials production. The conditions of the crystallization process control
the as-solidified material in its chemical and physical properties. Nucleation
initiates the crystallization of a liquid. It selects the crystallographic
phase, stable or meta-stable. Its detailed knowledge is therefore mandatory for
the design of materials. We present techniques of containerless processing for
nucleation studies of metals and alloys. We demonstrate the power of these
methods for crystal nucleation of stable solids but in particular also for
investigations of crystal nucleation of metastable solids at extreme
undercooling. This concerns the issue of heterogeneous versus homogeneous
nucleation and non-equilibrium conditions. The results are analyzed within
classical nucleation theory, where the activation energy of homogeneous
nucleation depends on the interfacial energy and the difference of Gibbs free
energies of solid and liquid. The interfacial energy acts as barrier for the
nucleation process. Its experimental determination is difficult in the case of
metals. In the second part of this work we therefore explore the use of
colloidal suspensions as models for the crystallization process. Their
nucleation process is observed in situ by optical techniques and ultra-small
angle X-ray diffraction using high intensity synchrotron radiation. It allows
an unambiguous discrimination of homogeneous and heterogeneous nucleation as
well as the determination of the interfacial free energy of the solid-liquid
interface. Our results are used to construct Turnbull plots of colloids, which
are discussed in relation to Turnbull plots of metals and support the
hypothesis that colloids are useful model systems to investigate crystal
nucleation.


  Language constructs inspired by functional programming have made their way
into most mainstream programming languages. Many researchers and developers
consider that these constructs lead to programs that are more concise,
reusable, and easier to understand. However, few studies investigate the
implications of using them in mainstream programming languages. This paper
quantifies the prevalence of four concepts typically associated with functional
programming in JavaScript: recursion, immutability, lazy evaluation, and
functions as values. We focus on JavaScript programs due to the availability of
some of these concepts in the language since its inception, its inspiration
from functional programming languages, and its popularity. We mine 91 GitHub
repositories (22+ million LOC) written mostly in JavaScript (over 50% of the
code), measuring the usage of these concepts from both static and temporal
perspectives. We also measure the likelihood of bug-fixing commits removing
uses of these concepts (which would hint at bug-proneness) and their
association with the presence of code comments (which would hint at code that
is hard to understand). We find that these concepts are in widespread use (1
for every 46.65 LOC, 43.59% of LOC). In addition, the usage of higher-order
functions, immutability, and lazy evaluation-related structures has been
growing throughout the years for the analyzed projects, while the usage of
recursion and callbacks & promises has decreased. We also find statistical
evidence that removing these structures, with the exception of the ones
associated to immutability, is less common in bug-fixing commits than in other
commits. In addition, their presence is not correlated with comment size. Our
findings suggest that functional programming concepts are important for
developers using a multi-paradigm language, and their usage does not make
programs harder to understand.


  Channel estimation is challenging for the reconfigurable intelligence surface
(RIS) assisted millimeter wave (mmWave) communications. Since the number of
coefficients of the cascaded channels in such systems is closely dependent on
the product of the number of base station antennas and the number of RIS
elements, the pilot overhead would be prohibitively high. In this letter, we
propose a cascaded channel estimation framework for an RIS assisted mmWave
multiple-input multiple-output system, where the wideband effect on
transmission model is considered. Then, we transform the wideband channel
estimation into a parameter recovery problem and use a few pilot symbols to
detect the channel parameters by the Newtonized orthogonal matching pursuit
algorithm. Moreover, the Cramer-Rao lower bound on the channel estimation is
introduced. Numerical results show the effectiveness of the proposed channel
estimation scheme.


  Given an $n$-ary
  $k-$valued function $f$, $gap(f)$ denotes the essential arity gap of $f$
which is the minimal number of essential variables in $f$ which become fictive
when identifying any two distinct essential variables in $f$. In the present
paper we study the properties of the symmetric function with non-trivial arity
gap ($2\leq gap(f)$). We prove several results concerning decomposition of the
symmetric functions with non-trivial arity gap with its minors or subfunctions.
We show that all non-empty sets of essential variables in symmetric functions
with non-trivial arity gap are separable.


  A systematic study is made on geometric, electronic and magnetic properties
of one-dimensional graphene nanoribbons using the first-principles
calculations. The feature-rich essential properties result from the various
orbital hybridizations in chemical bonds and the edge-carbon- and
adatom-induced spin states. Pristine nanoribbons, with honeycomb lattices, can
exhibit the planar, curving, scrolling, folding, and stacking configurations.
Adatom adsorptions on surface and edge, respectively, create the buckled
structures and the non-hexagonal/non-planar edges. There exist six kinds of of
spin-dependent electronic and magnetic properties, non-magnetic, ferromagnetic
and anti-ferromagnetic metals, the non-magnetic semiconductors, and the
anti-ferromagnetic semiconductors with/without the spin splitting. They are
clearly illustrated by the energy gaps, the electron/hole densities, the net
magnetic moment, the atom-dominated energy bands, the spatial charge
distributions, the spin arrangements, and the orbital- and spin-projected
density of states. The diverse essential properties are determined by the
complicated relations among the finite-size confinement, edge structure,
curvature effect, interlayer atomic interaction, spin configuration, and
chemical adsorption. The theoretical predictions can provide the full
information in potential applications, and part of them agree with the recent
experimental measurements.


  This paper establishes Fokker-Planck-Kolmogorov type equations for
time-changed Gaussian processes. Examples include those equations for a
time-changed fractional Brownian motion with time-dependent Hurst parameter and
for a time-changed Ornstein-Uhlenbeck process. The time-change process
considered is the inverse of either a stable subordinator or a mixture of
independent stable subordinators.


  The papers [1,2] consider unbinding of a disordered heteropolymer. They find
the first order phase transition [1] when disorder is strong (i.e. the ratio v
of the binding energies is large; in DNA v is~1.1) and the Griffiths
singularity, i.e. infinite order transition, otherwise [2]. The problem is
important, since many physical phenomena map onto the same model (see refs. in
[1, 2]). Drastic non-universality in the strength of disorder is unanticipated.
Unfortunately, both titles are misleading: they claim the results which are
proven for homopolymers only.


  In order to unifiedly coordinate economy and voltage deviations, a novel
multi-objective optimal power flow (MOPF) algorithm is proposed for an AC/DC
system with VSC-HVDC based on cooperative multi-objective particle swarm
optimization (CMOPSO). In order to minimize power generation costs and voltage
deviations, the MOPF model of the AC/DC system is firstly built based on the
VSC-HVDC steady-state model. Then, the CMOPSO is adopted for solving the MOPF
model to find well-distributed Pareto-optimal solutions. Next, the solutions
are divided into different groups via the fuzzy C-means algorithm, and finally
the best compromise solutions reflecting decision-makers' different preferences
are identified from each group by comparing the priority memberships which are
calculated by using the grey relation projection method. The validity of the
proposed approach is verified by using the modified IEEE 14-bus and 118- bus
systems.


  We present new results on transverse momentum spectra, integrated yields, and
mean transverse momenta of pions, kaons, and protons, as well as of
$\phi$-mesons for various centrality classes measured in Pb-Pb and Xe-Xe
collisions at the LHC. This unique set of data allows us to investigate bulk
particle production for very different systems at similar multiplicities. The
chemical and kinetic freeze-out parameters are extracted via
statistical-thermal and combined blast-wave fits to the data in heavy-ion
collisions and are compared to results obtained in pp and p-Pb collisions at
similar multiplicities. The evolution of collective-like effects from pp and
p-Pb collisions to Xe-Xe and Pb-Pb collisions is further investigated by
detailed comparisons to predictions from models.


  Entropy and temperature of a system in a coherent state are naturally defined
on a base of a density matrix of the system. As an example, entropy and
temperature are evaluated for coherent states of a harmonic oscillator and
quantum field described by the Klein--Gordon--Fock equation with a source term.
It is shown, in particular, that the temperature of the coherent oscillator in
a ground state coincides with the effective temperature of a harmonic
oscillator being in contact with a heat bath (Bloch formula) when the bath
temperature tends to zero. The Bekenstein--Hawking entropy of a black hole can
also be interpreted as an entropy of coherent states of a physical vacuum in
the vicinity of a horizon surface.


  Policy gradient methods are often applied to reinforcement learning in
continuous multiagent games. These methods perform local search in the
joint-action space, and as we show, they are susceptable to a game-theoretic
pathology known as relative overgeneralization. To resolve this issue, we
propose Multiagent Soft Q-learning, which can be seen as the analogue of
applying Q-learning to continuous controls. We compare our method to MADDPG, a
state-of-the-art approach, and show that our method achieves better
coordination in multiagent cooperative tasks, converging to better local optima
in the joint action space.


  Nucleon-nucleon ($NN$) interactions based on chiral effective theories are
commonly used in ab initio calculations of light nuclei. Here we present a
study based on three different NN interactions (up to next-to-next-to-leading
order) for which structure and elastic proton scattering observables are
consistently calculated for $^4$He, $^{12}$C, and $^{16}$O. The interactions
are compared at the two-body level in terms of Wolfenstein amplitudes, and
their predictions for ground state energies, point-proton radii, and charge
form factors, as well as proton elastic scattering observables in the
leading-order spectator expansion in the energy range between 65 and 160 MeV
projectile energy are presented. To gain further insight into differences
visible in elastic scattering observables, we investigate the behavior of the
calculated effective nucleon-nucleus interactions for the $^{12}$C nucleus
based on the different $NN$ interactions.


  Laser cooling and trapping of lanthanides has opened the possibility to carry
out new experiments with ultracold dipolar gases, for example for quantum
simulation of solid state physics. To identify new suitable candidates for
laser-cooling, it is important to have a precise spectroscopic knowledge of the
atom under consideration. Along this direction, we present here a detailed
modeling of the energy levels of neutral neodymium (Nd), an element belonging
to the left part of the lanthanide row, which has not yet been considered for
laser-cooling. Using the semi-empirical method implemented in the Cowan suite
of codes, we are in particular able to interpret more than 200 experimental
levels of the NIST database belonging to both parities. The optimal set of
atomic parameters obtained after the least-square fitting step can serve to
calculate radiative transition probabilities in the future.


  In this paper we focus, from a mathematical point of view, on properties and
performances of some local interpolation schemes for landmark-based image
registration. Precisely, we consider modified Shepard's interpolants,
Wendland's functions, and Lobachevsky splines. They are quite unlike each
other, but all of them are compactly supported and enjoy interesting
theoretical and computational properties. In particular, we point out some
unusual forms of the considered functions. Finally, detailed numerical
comparisons are given, considering also Gaussians and thin plate splines, which
are really globally supported but widely used in applications.


  We say that a tempered distribution $A$ belongs to the class $S^m(\Ge)$ on a
homogeneous Lie algebra $\Ge$ if its Abelian Fourier transform $a=\hat{A}$ is a
smooth function on the dual $\Ges$ and satisfies the estimates $$
|D^{\alpha}a(\xi)|\le C_{\alpha}(1+|\xi|)^{m-|\alpha|}. $$ Let $A\in S^0(\Ge)$.
Then the operator $f\mapsto f\star\widetilde{A}(x)$ is bounded on $L^2(\Ge)$.
Suppose that the operator is invertible and denote by $B$ the convolution
kernel of its inverse. We show that $B$ belongs to the class $S^0(\Ge)$ as
well. As a corollary we generalize Melin's theorem on the parametrix
construction for Rockland operators.


  Endohedral fullerenes, or endofullerenes, are chemical systems of fullerene
cages encapsulating single atoms or small molecules. These species provide an
interesting challenge of Potential Energy Surface (PES) determination as
examples of non-covalently bonded, bound systems. While the majority of studies
focus on C$_{60}$ as the encapsulating cage, introducing some anisotropy by
using a different fullerene, e.g., C$_{70}$ can unveil a double well potential
along the unique axis. By approximating the potential as a pairwise
Lennard-Jones (LJ) summation over the fixed C cage atoms, the parameter space
of the Hamiltonian includes three tunable variables: $(M,\varepsilon,\sigma)$
representing the mass of the trapped species, the LJ energy, and length scales
respectively. Fixing the mass and allowing the others to vary can imitate the
potentials of endohedral species trapped in more elongated fullerenes. We
choose to explore the LJ parameter space of an endohedral atom in C$_{70}$ with
$\varepsilon\in$ [20cm$^{-1}$, 150cm$^{-1}$], and $\sigma\in$ [2.85\r{A} ,
3.05\r{A}].
  As the barrier height and positions of these wells vary between [1cm$^{-1}$,
264cm$^{-1}$] and [0.35\r{A}, 0.85\r{A}] respectively, using a 3D direct
product basis of 1D harmonic oscillator (HO) wavefunctions centred at the
origin where there is a local maximum is unphysical. Instead we propose the use
of a non-orthogonal basis set, using 1D HO wavefunctions centred in each
minimum and compare this to other choices. The ground state energy of the
X@C$_{70}$ is tracked across the LJ parameter space, along with its
corresponding nuclear translational wavefunctions. A classification of the
wavefunction characteristics, namely the prolateness and ``peanut-likeness''
based on its statistical moments is also proposed.


  Semiconductor heterostructures are backbones for solid state based
optoelectronic devices. Recent advances in assembly techniques for van der
Waals heterostructures has enabled the band engineering of semiconductor
heterojunctions for atomically thin optoelectronic devices. In two-dimensional
heterostructures with type II band alignment, interlayer excitons, where
Coulomb-bound electrons and holes are confined to opposite layers, have shown
promising properties for novel excitonic devices, including a large binding
energy, micron-scale in-plane drift-diffusion, and long population and valley
polarization lifetime. Here, we demonstrate interlayer exciton optoelectronics
based on electrostatically defined lateral p-n junctions in a MoSe2-WSe2
heterobilayer. Applying a forward bias enables the first observation of
electroluminescence from interlayer excitons. At zero bias, the p-n junction
functions as a highly sensitive photodetector, where the wavelength-dependent
photocurrent measurement allows the direct observation of resonant optical
excitation of the interlayer exciton. The resulting photocurrent amplitude from
the interlayer exciton is about 200 times smaller compared to the resonant
excitation of intralayer exciton. This implies that the interlayer exciton
oscillator strength is two orders of magnitude smaller than that of the
intralayer exciton due to the spatial separation of electron and hole to
opposite layers. These results lay the foundation for exploiting the interlayer
exciton in future 2D heterostructure optoelectronic devices.


  A global optimization problem is studied where the objective function $f(x)$
is a multidimensional black-box function and its gradient $f'(x)$ satisfies the
Lipschitz condition over a hyperinterval with an unknown Lipschitz constant
$K$. Different methods for solving this problem by using an a priori given
estimate of $K$, its adaptive estimates, and adaptive estimates of local
Lipschitz constants are known in the literature. Recently, the authors have
proposed a one-dimensional algorithm working with multiple estimates of the
Lipschitz constant for $f'(x)$ (the existence of such an algorithm was a
challenge for 15 years). In this paper, a new multidimensional geometric method
evolving the ideas of this one-dimensional scheme and using an efficient
one-point-based partitioning strategy is proposed. Numerical experiments
executed on 800 multidimensional test functions demonstrate quite a promising
performance in comparison with popular DIRECT-based methods.


  Tensile tests were carried out by deforming polycrystalline samples of
Al-2.5%Mg alloy at four different temperatures in an intermediate strain rate
regime of 2x10-4s-1 to 2x10-3s-1. The Portevin-Le Chatelier (PLC) effect was
observed throughout the strain rate and temperature region. The mean cumulative
stress drop magnitude and the mean reloading time exhibit an increasing trend
with temperature which is attributed to the enhanced solute diffusion at higher
temperature. The observed stress-time series data were analyzed using the
nonlinear dynamical methods. From the analyses, we could establish the presence
of deterministic chaos in the PLC effect throughout the temperature regime. The
dynamics goes to higher dimension at a sufficiently high temperature of 425K
but the complexity of the dynamics is not affected by the temperature.


  Given a vector bundle $E$ on a tree of smooth rational curves $C$, we give
necessary and sufficient conditions for a vector bundle $E'$ on $\mathbb{P}^1$
to specialize to $E$ on $C$, generalizing the rank 2 case, due to Coskun.


  We report constraints on cosmological parameters from the angular power
spectrum of a cosmic microwave background (CMB) gravitational lensing potential
map created using temperature data from 2500 deg$^2$ of South Pole Telescope
(SPT) data supplemented with data from Planck in the same sky region, with the
statistical power in the combined map primarily from the SPT data. We fit the
corresponding lensing angular power spectrum to a model including cold dark
matter and a cosmological constant ($\Lambda$CDM), and to models with
single-parameter extensions to $\Lambda$CDM. We find constraints that are
comparable to and consistent with constraints found using the full-sky Planck
CMB lensing data. Specifically, we find $\sigma_8 \Omega_{\rm m}^{0.25}=0.598
\pm 0.024$ from the lensing data alone with relatively weak priors placed on
the other $\Lambda$CDM parameters. In combination with primary CMB data from
Planck, we explore single-parameter extensions to the $\Lambda$CDM model. We
find $\Omega_k = -0.012^{+0.021}_{-0.023}$ or $M_{\nu}< 0.70$eV both at 95%
confidence, all in good agreement with results that include the lensing
potential as measured by Planck over the full sky. We include two independent
free parameters that scale the effect of lensing on the CMB: $A_{L}$, which
scales the lensing power spectrum in both the lens reconstruction power and in
the smearing of the acoustic peaks, and $A^{\phi \phi}$, which scales only the
amplitude of the CMB lensing reconstruction power spectrum. We find $A^{\phi
\phi} \times A_{L} =1.01 \pm 0.08$ for the lensing map made from combined SPT
and Planck temperature data, indicating that the amount of lensing is in
excellent agreement with what is expected from the observed CMB angular power
spectrum when not including the information from smearing of the acoustic
peaks.


  We give refined statements and modern proofs of Rosenlicht's results about
the canonical model C' of an arbitrary complete integral curve C. Notably, we
prove that C and C' are birationally equivalent if and only if C is
nonhyperelliptic, and that, if C is nonhyperelliptic, then C' is equal to the
blowup of C with respect to the canonical sheaf \omega. We also prove some new
results: we determine just when C' is rational normal, arithmetically normal,
projectively normal, and linearly normal.


  Hertzberg has constructed a quantum oscillon that decays into pairs of
relativistic mesons with a power much greater than the radiation from classical
oscillon decay. This result is often construed as a proof that quantum
oscillons decay quickly, and so are inconsequential. We apply a construction
similar to Hertzberg's to the quantum kink. Again it leads to a rapid decay via
the emission of relativistic mesons. However, we find that this is the decay of
a squeezed kink state to a stable kink state, and so it does not imply that the
quantum kink is unstable. We then consider a time-dependent solution, which may
be an oscillon, and we see that the argument proceeds identically.


  We identify and highlight certain landmark results in Samson Abramsky's work
which we believe are fundamental to current developments and future trends. In
particular, we focus on the use of (i) topological duality methods to solve
problems in logic and computer science; (ii) category theory and, more
particularly, free (and co-free) constructions; (iii) these tools to unify the
`power' and `structure' strands in computer science.


  Dense star clusters are spectacular self-gravitating stellar systems in our
Galaxy and across the Universe - in many respects. They populate disks and
spheroids of galaxies as well as almost every galactic center. In massive
elliptical galaxies nuclear clusters harbor supermassive black holes, which
might influence the evolution of their host galaxies as a whole. The evolution
of dense star clusters is not only governed by the aging of their stellar
populations and simple Newtonian dynamics. For increasing particle number,
unique gravitational effects of collisional many-body systems begin to dominate
the early cluster evolution. As a result, stellar densities become so high that
stars can interact and collide, stellar evolution and binary stars change the
dynamical evolution, black holes can accumulate in their centers and merge with
relativistic effects becoming important. Recent high-resolution imaging has
revealed even more complex structural properties with respect to stellar
populations, binary fractions and compact objects as well as - the still
controversial - existence of intermediate mass black holes in clusters of
intermediate mass. Dense star clusters therefore are the ideal laboratory for
the concomitant study of stellar evolution and Newtonian as well as
relativistic dynamics. Not only the formation and disruption of dense star
clusters has to be considered but also their galactic environments in terms of
initial conditions as well as their impact on galactic evolution. This review
deals with the specific computational challenges for modelling dense,
gravothermal star clusters.


  Implicit representations of geometry, such as occupancy fields or signed
distance fields (SDF), have recently re-gained popularity in encoding 3D solid
shape in a functional form. In this work, we introduce medial fields: a field
function derived from the medial axis transform (MAT) that makes available
information about the underlying 3D geometry that is immediately useful for a
number of downstream tasks. In particular, the medial field encodes the local
thickness of a 3D shape, and enables O(1) projection of a query point onto the
medial axis. To construct the medial field we require nothing but the SDF of
the shape itself, thus allowing its straightforward incorporation in any
application that relies on signed distance fields. Working in unison with the
O(1) surface projection supported by the SDF, the medial field opens the door
for an entirely new set of efficient, shape-aware operations on implicit
representations. We present three such applications, including a modification
to sphere tracing that renders implicit representations with better convergence
properties, a fast construction method for memory-efficient rigid-body
collision proxies, and an efficient approximation of ambient occlusion that
remains stable with respect to viewpoint variations.


  This work studies fundamental questions regarding the optimal design of
antimicrobial treatment protocols, using standard pharmacodynamic and
pharmacokinetic mathematical models. We consider the problem of designing an
antimicrobial treatment schedule to achieve eradication of a microbial
infection, while minimizing the area under the time-concentration curve (AUC).
We first solve this problem under the assumption that an arbitrary
antimicrobial concentration profile may be chosen, and prove that the 'ideal'
concentration profile consists of a constant concentration over a finite time
duration, where explicit expressions for the optimal concentration and the time
duration are given in terms of the pharmacodynamic parameters. Since
antimicrobial concentration profiles are induced by a dosing schedule and the
antimicrobial pharmacokinetics, the ideal concentration profile is not strictly
feasible. We therefore also investigate the possibility of achieving outcomes
which are close to those provided by the ideal concentration profile,using a
bolus+continuous dosing schedule, which consists of a loading dose followed by
infusion of the antimicrobial at a constant rate. We explicitly find the
optimal bolus+continuous dosing schedule, and show that, for realistic
parameter ranges, this schedule achieves results which are nearly as efficient
as those attained by the ideal concentration profile. The optimality results
obtained here provide a baseline and reference point for comparison and
evaluation of antimicrobial treatment plans.


  Entanglement of identical massive particles recently gained attention,
because of its relevance in highly controllable systems, e.g. ultracold gases.
It accounts for correlations among modes instead of particles, providing a
different paradigm for quantum information. We prove that the entanglement of
almost all states rarely vanishes in the presence of noise, and analyse the
most relevant noise in ultracold gases: dephasing and particle losses.
Furthermore, when the particle number increases, the entanglement decay can
turn from exponential into algebraic.


  Carr and Hawking showed that the proper size of a spherical overdense region
surrounded by a flat FRW universe cannot be arbitrarily large as otherwise the
region would close up on itself and become a separate universe. From this
result they derived a condition connecting size and density of the overdense
region ensuring that it is part of our universe. Carr used this condition to
obtain an upper bound for the density fluctuation amplitude with the property
that for smaller amplitudes the formation of a primordial black hole is
possible, while larger ones indicate a separate universe. In contrast, we find
that the appearance of a maximum is not a consequence of avoiding separate
universes but arises naturally from the geometry of the chosen slicing. Using
instead of density a volume fluctuation variable reveals that a fluctuation is
a separate universe iff this variable diverges on superhorizon scales. Hence
Carr's and Hawking's condition does not pose a physical constraint on density
fluctuations. The dynamics of primordial black hole formation with an initial
curvature fluctuation amplitude larger than the one corresponding to the
maximum density fluctuation amplitude was previously not considered in detail
and so we compare it to the well-known case where the amplitude is smaller by
presenting embedding and conformal diagrams of both types in dust spacetimes.


  Let $X$ and $Y$ be compact K\"ahler manifolds of dimension $3$. A
bimeromorphic map $f:X\rightarrow Y$ is pseudo-isomorphic if
$f:X-I(f)\rightarrow Y-I(f^{-1})$ is an isomorphism.
  Let $T=T^+-T^-$ be a current on $Y$, where $T^{\pm}$ are positive closed
$(1,1)$ currents which are smooth outside a finite number of points. We assume
that the following condition is satisfied:
  {\bf Condition 1.} For every curve $C$ in $I(f^{-1})$, then in cohomology
$\{T\}.\{C\}=0$.
  Then, we define a natural push-forward $f_*(\varphi dd^cu\wedge f^*(T))$ for
a quasi-psh function $u$ and a smooth function $\varphi$ on $Y$. We show that
this pushforward satisfies a Bedford-Taylor's monotone convergence type.
  Assume moreover that the following two conditions are satisfied
  {\bf Condition 2.} The signed measure $T\wedge T\wedge T$ has no mass on
$I(f^{-1})$.
  {\bf Condition 3.} For every curve $C$ in $I(f^{-1})$, the measure $T\wedge
[C]$ has no Dirac mass.
  Then, we define a Monge-Ampere operator $MA(f^*(T))=f^*(T)\wedge f^*(T)\wedge
f^*(T)$ for $f^*(T)$. We show that this Monge-Ampere operator satisfies several
continuous properties, including a Bedford-Taylor's monotone convergence type
when $T$ is positive. The measures $MA(f^*(T))$ are in general quite singular.
Also, note that it may be not possible to define $f^*(T^{\pm})\wedge
f^*(T^{\pm})\wedge f^*(T^{\pm})$.


  The response to a magnetic flux is considered of the vacuum state of charged
Dirac fermions interacting with a domain wall made of a neutral spinless field
in (3+1) dimensions with the fermion mass having a phase variation across the
wall. It is pointed out that due to simple C parity arguments the spontaneous
magnetization for this system is necessarily zero, thus invalidating some
claims to the contrary in the literature. The cancellation of the spontaneous
magnetization is explicitly demonstrated in a particular class of models. The
same calculation produces a general formula for the electric charge density
induced by the magnetic flux -- an effect previously discussed in the
literature for axionic domain walls. The distribution of the induced charge is
calculated in specific models.


  This paper presents a new class of 8th order canonical polynomials in
n-dimensional real space. Based on the sequential canonical dual
transformation, all extrema are obtained. The method can be used to solve the
associated 7th order nonlinear algebraic equations. Optimality conditions are
provided to find both global minimizers and local extrema. Applications are
illustrated by examples.


  Non-Standard neutral current Interactions (NSIs) of neutrinos with matter can
alter the pattern of neutrino oscillation due to the coherent forward
scattering of neutrinos on the medium. This effect makes long-baseline neutrino
experiments such as NO$\nu$A and DUNE a sensitive probe of beyond standard
model (BSM) physics. We construct light mediator models that can give rise to
both lepton flavor conserving as well as Lepton Flavor Violating (LFV) neutral
current NSI. We outline the present phenomenological viability of these models
and future prospects to test them. We predict a lower bound on Br$(H\to \mu
\tau)$ in terms of the parameters that can be measured by DUNE and NO$\nu$A,
and show that the hint for $H\to \mu \tau$ in current LHC data can be
accommodated in our model. A large part of the parameter space of the model is
already constrained by the bounds on Br$(\tau \to Z^\prime \mu)$ and rare meson
decays and can in principle fully tested by improving these bounds.


  We formulate a new two-variable river environmental restoration problem based
on jump stochastic differential equations (SDEs) governing the sediment storage
and nuisance benthic algae population dynamics in a dam-downstream river.
Controlling the dynamics is carried out through impulsive sediment
replenishment with discrete and random observation/intervention to avoid
sediment depletion and thick algae growth. We consider a cost-efficient
management problem of the SDEs to achieve the objectives whose resolution
reduces to solving a Hamilton-Jacobi-Bellman (HJB) equation. We also consider a
Fokker-Planck (FP) equation governing the probability density function of the
controlled dynamics. The HJB equation has a discontinuous solution, while the
FP equation has a Dirac's delta along boundaries. We show that the value
function, the optimized objective function, is governed by the HJB equation in
the simplified case and further that a threshold-type control is optimal. We
demonstrate that simple numerical schemes can handle these equations. Finally,
we numerically analyze the optimal controls and the resulting probability
density functions.


  Recent measurements of femtoscopic correlations at NA61/SHINE unravel that
the shape of the particle emitting source is not Gaussian. The measurements are
based on L\'evy-stable symmetric sources, and we discuss the average pair
transverse mass dependence of the source parameters. One of the parameters, the
L\'evy exponent $\alpha$, is of particular importance. It describes the shape
of the source, which, in the vicinity of the critical point of the QCD phase
diagram, may be related to the critical exponent $\eta$. Its measurement hence
may contribute to the search for and characterization of the critical point of
the phase diagram.


  We study models of emergent space associated with the Coulomb branch,
non-commutative and beta deformations of the N=4 super Yang-Mills theory,
extending a previous work on the undeformed conformal case. The idea is to
compute the effective action for D-instantons from the microscopic
four-dimensional open-string description and to compare with the non-abelian
D-instanton action in the dual ten-dimensional supergravity background. To
linear order in the deformation parameter, the D-instantons can probe the full
space-time geometry and we can derive all the supergravity fields in this way.
We find a perfect match with the known supergravity solutions, including for
the Neveu-Schwarz and Ramond-Ramond forms.


  There is a rapid growth of applications of Unmanned Aerial Vehicles (UAVs) in
traffic management, such as traffic surveillance, monitoring, and incident
detection. However, the existing literature lacks solutions to real-time
incident detection while addressing privacy issues in practice. This study
explored real-time vehicle detection algorithms on both visual and infrared
cameras and conducted experiments comparing their performance. Red Green Blue
(RGB) videos and thermal images were collected from a UAS platform along
highways in the Tampa, Florida, area. Experiments were designed to quantify the
performance of a real-time background subtraction-based method in vehicle
detection from a stationary camera on hovering UAVs under free-flow conditions.
Several parameters were set in the experiments based on the geometry of the
drone and sensor relative to the roadway. The results show that a background
subtraction-based method can achieve good detection performance on RGB images
(F1 scores around 0.9 for most cases), and a more varied performance is seen on
thermal images with different azimuth angles. The results of these experiments
will help inform the development of protocols, standards, and guidance for the
use of drones to detect highway congestion and provide input for the
development of incident detection algorithms.


  With the Gottesman-Kitaev-Preskill (GKP) encoding, Clifford gates and error
correction can be carried out using simple Gaussian operations. Still,
non-Clifford gates, required for universality, require non-Gaussian elements.
In their original proposal, GKP suggested a particularly simple method of using
a single application of the cubic phase gate to perform the logical
non-Clifford T-gate. Here we show that this cubic phase gate approach performs
extraordinarily poorly, even for arbitrarily large amounts of squeezing in the
GKP state. Thus, contrary to common belief, the cubic phase gate is not
suitable for achieving universal fault-tolerant quantum computation with GKP
states.


  Starting from a stationary set of supercompact cardinals we find a generic
extension in which the tree property holds at every regular cardinal between
$\aleph_2$ and $\aleph_{\omega^2}$.


  A modification of the usual Type-II second-harmonic-generation model is
proposed, which includes two additional features: linear conversion and walkoff
(group-velocity difference) between two components of the fundamental-frequency
(FF) wave. Physical interpretations of the model are possible in both temporal
and spatial domains. In the absence of the intrinsic walkoff, the linear mixing
makes real soliton solutions stable or unstable, depending on the relative sign
of the two FF components. Unstable solitons spontaneously re-arrange themselves
into stable ones. Fundamental solitons change their shape (in particular, they
develop chirp) but remain stable if the intrinsic walkoff is included. In
addition, quasi-stable double-humped solitary waves are found in the latter
case.


  A combination of dressing method and variation of constants as well as a
formula for constructing the eigenfunction is used to solve the extended KP
hierarchy, which is a hierarchy with one more series of time-flow and based on
the symmetry constaint of KP hierarchy. Similarly, extended mKP hierarchy is
formulated and its zero curvature form, Lax representation and reductions are
presented. Via gauge transformation, it is easy to transform dressing solutions
of extended KP hierarchy to the solutions of extended mKP hierarchy. Wronskian
solutions of extended KP and extended mKP hierarchies are constructed
explicitly.


  We study the geometry of foliated non-Lorentzian spacetimes in terms of the
Godbillon-Vey class of the foliation. We relate the intrinsic torsion of a
foliated Aristotelian manifold to its Godbillon-Vey class, and interpret it as
a measure of the local spin of the spatial leaves in the time direction. With
this characterisation, the Godbillon-Vey class is an obstruction to
integrability of the $\mathsf{G}$-structure defining the Aristotelian
spacetime. We use these notions to formulate a new geometric approach to
hydrodynamics of fluid flows by endowing them with Aristotelian structures. We
establish conditions under which the Godbillon-Vey class represents an
obstruction to steady flow of the fluid and prove new conservation laws.


  We present an adaptation of RNN sequence models to the problem of multi-label
classification for text, where the target is a set of labels, not a sequence.
Previous such RNN models define probabilities for sequences but not for sets;
attempts to obtain a set probability are after-thoughts of the network design,
including pre-specifying the label order, or relating the sequence probability
to the set probability in ad hoc ways.
  Our formulation is derived from a principled notion of set probability, as
the sum of probabilities of corresponding permutation sequences for the set. We
provide a new training objective that maximizes this set probability, and a new
prediction objective that finds the most probable set on a test document. These
new objectives are theoretically appealing because they give the RNN model
freedom to discover the best label order, which often is the natural one (but
different among documents).
  We develop efficient procedures to tackle the computation difficulties
involved in training and prediction. Experiments on benchmark datasets
demonstrate that we outperform state-of-the-art methods for this task.


  The Kosterlitz-Thouless transition for the spin 1/2 Heisenberg chain with the
next-to-the-nearest-neighbor interaction is investigated in the context of an
infinite matrix product state algorithm, which is a generalization of the
infinite time-evolving block decimation algorithm [G. Vidal, Phys. Rev. Lett.
\textbf{98}, 070201 (2007)] to accommodate both the
next-to-the-nearest-neighbor interaction and spontaneous dimerization. It is
found that, in the critical regime, the algorithm automatically leads to
infinite degenerate ground-state wave functions, due to the finiteness of the
truncation dimension. This results in \textit{pseudo} symmetry spontaneous
breakdown, as reflected in a bifurcation in the ground-state fidelity per
lattice site. In addition, this allows to introduce a pseudo-order parameter to
characterize the Kosterlitz-Thouless transition.


  The goal of this paper is to establish generic regularity of free boundaries
for the obstacle problem in $\mathbb R^n$. By classical results of Caffarelli,
the free boundary is $C^\infty$ outside a set of singular points. Explicit
examples show that the singular set could be in general $(n-1)$-dimensional
---that is, as large as the regular set. Our main result establishes that,
generically, the singular set has zero $\mathcal H^{n-4}$ measure (in
particular, it has codimension 3 inside the free boundary). In particular, for
$n\leq4$, the free boundary is generically a $C^\infty$ manifold. This solves a
conjecture of Schaeffer (dating back to 1974) on the generic regularity of free
boundaries in dimensions $n\leq4$.


  Feynmf is a LaTeX package for easy drawing of professional quality Feynman
diagrams with Metafont (or Metapost). Feynmf lays out most diagrams
satisfactorily from the structure of the graph without any need for manual
intervention. Nevertheless all the power of Metafont (or Metapost) is available
for the most complicated cases.


  The behavior of the gluon density in nuclei is investigated in the framework
of the rescaling model.


  We propose a feasible scheme to realize the optical entanglement of
single-photon-added coherent state (SPACS) and show that, besides the Sanders
entangled coherent state, the entangled SPACS also leads to new forms of hybrid
entanglement of quantum Fock state and classical coherent state. We probe the
essential difference of two types of hybrid entangled state (HES). This HES
provides a novel link between the discrete- and the continuous-variable
entanglement in a natural way.


  We investigate a topological inflation model in supergravity. By means of
numerical simulations, it is confirmed that topological inflation can take
place in supergravity. We also show that the condition for successful inflation
depends not only on the vacuum-expectation value (VEV) of inflaton field but
also on the form of its K\"ahler potential. In fact, it is found that the
required VEV of the inflaton $\phi$ can be as small as $<\phi > \simeq 1 \times
M_G$, where $M_{G}$ is the gravitational scale.


  Based on experimental mass hierarchy, a set of flavor-democratic (FD) quark
mass matrices at low energies is discussed. The model predicts CP violation
parameters $J_{CP}=(0.3 \pm 0.2) 10^{-4}$ and ${\epsilon'/\epsilon} = (0.6 \pm
0.5) 10^{-3}$. However, this simple FD model also predicts a physical top quark
mass not much higher than 100 GeV. As a next step, we assume that the Standard
Model (SM) breaks down around some high energy $\Lambda$, and is replaced by a
new FD flavor gauge theory (FGT). This possibility can be investigated by
studying renormalization group equations for the Yukawa couplings of the SM
with two Higgs doublets for various $m_t$ and VEV ratios $v_U/v_D$. With
appropriate flavor-democratic boundary conditions at $\Lambda_{FGT}$, bounds on
masses of top quark and tau-neutrino are derived, which are compatible with
experimental bounds.


  Let $A$ be an amenable separable \CA and $B$ be a non-unital but
$\sigma$-unital simple \CA with continuous scale. We show that two essential
extensions $\tau_1$ and $\tau_2$ of $A$ by $B$ are approximately unitarily
equivalent if and only if $$ [\tau_1]=[\tau_2] {\rm in} KL(A, M(B)/B). $$ If
$A$ is assumed to satisfy the Universal Coefficient Theorem, there is a
bijection from approximate unitary equivalence classes of the above mentioned
extensions to $KL(A, M(B)/B).$ Using $KL(A, M(B)/B),$ we compute exactly when
an essential extension is quasidiagonal. We show that quasidiagonal extensions
may not be approximately trivial. We also study the approximately trivial
extensions.


  From the assumption that the slow roll parameter $\epsilon$ has a Lorentzian
form as a function of the e-folds number $N$, a successful model of a
quintessential inflation is obtained, as succinctly studied in
\cite{Benisty:2020xqm}. The form corresponds to the vacuum energy both in the
inflationary and in the dark energy epochs and satisfies the condition to climb
from small values of $\epsilon$ to $1$ at the end of the inflationary epoch. We
find the corresponding scalar Quintessential Inflationary potential with two
flat regions. Moreover, a reheating mechanism is suggested with numerical
estimation for the homogeneous evolution of the universe. The suggested
mechanism is consistent with the BBN bound.


  Charge transfer in superlattices consisting of SrIrO$_3$ and SrMnO$_3$ is
investigated using density functional theory. Despite the nearly identical work
function and non-polar interfaces between SrIrO$_3$ and SrMnO$_3$, rather large
charge transfer was experimentally reported at the interface between them.
Here, we report a microscopic model that captures the mechanism behind this
phenomenon, providing a qualitative understanding of the experimental
observation. This leads to unique strain dependence of such charge transfer in
iridate-manganite superlattices. The predicted behavior is consistently
verified by experiment with soft x-ray and optical spectroscopy. Our work thus
demonstrates a new route to control electronic states in non-polar oxide
heterostructures.


  An assumption in micromechanical analysis of polymers is that the
constitutive polymeric media is non-porous. Non-porosity of media, however, is
merely a simplifying assumption. In this paper, we neglect this assumption and
studied polymer networks with a different porosity volume fraction. A random
morphology description function is used to model the porosity of the network
and nonlinear finite element analyses are conducted to perform structural
analysis of porous polymer networks. The results show that the porosity effect
is significant in mechanical behavior of polymer networks and may increase the
maximum Von-Mises stress drastically.


  We present the design and implementation of a trapped ion cavity QED system.
A single ytterbium ion is confined by a micron-scale ion trap inside a 2 mm
optical cavity. The ion is coherently pumped by near resonant laser light while
the cavity output is monitored as a function of pump intensity and cavity
detuning. We observe a Purcell enhancement of scattered light into the solid
angle subtended by the optical cavity, as well as a three-peak structure
arising from strongly driving the atom. This system can be integrated into
existing atom{photon quantum network protocols and is a pathway towards an
efficient atom{photon quantum interface.


  We study the influence of an external magnetic field h on the phase diagram
of a system of Fermi particles living on the sites of a Bethe lattice with
coordination number z and interacting through on-site U and nearest-neighbor V
interactions. This is a physical realization of the extended Hubbard model in
the narrow-band limit. Our results establish that the magnetic field may
dramatically affect the critical temperature below which a long-range charge
ordered phase is observed, as well as the behavior of physical quantities,
inducing, for instance, magnetization plateaus in the magnetization curves.
Relevant thermodynamic quantities - such as the specific heat and the
susceptibility - are also investigated at finite temperature by varying the
on-site potential, the particle density and the magnetic field.


  With technical performance being similar for various web browsers, improving
user perceived performance is integral to optimizing browser quality. We
investigated the importance of priming, which has a well-documented ability to
affect people's beliefs, on users' perceptions of web browser performance. We
studied 1495 participants who read either an article about performance
improvements to Mozilla Firefox, an article about user interface updates to
Firefox, or an article about self-driving cars, and then watched video clips of
browser tasks. As the priming effect would suggest, we found that reading
articles about Firefox increased participants' perceived performance of Firefox
over the most widely used web browser, Google Chrome. In addition, we found
that article content mattered, as the article about performance improvements
led to higher performance ratings than the article about UI updates. Our
findings demonstrate how perceived performance can be improved without making
technical improvements and that designers and developers must consider a wider
picture when trying to improve user attitudes about technology.


  Based on recent LHC Higgs analyses and in anticipation of future results we
revisit theories where Higgs bosons can couple to weak gauge bosons with
enhanced strength relative to the Standard Model value. Specifically, we look
at the Georgi-Machacek model and its generalizations where higher "spin"
representations of SU(2)_L break electroweak symmetry while maintaining
custodial SU(2). In these theories, there is not only a Higgs-like boson but
partner Higgs scalars transforming under representations of custodial SU(2),
leading to a rich phenomenology. These theories serve as a consistent
theoretical and experimental framework to explain enhanced couplings to gauge
bosons, including fermiophobic Higgses. We focus on the phenomenology of a
neutral scalar partner to the Higgs, which is determined once the Higgs
couplings are specified. Depending on the parameter space, this partner could
have i) enhanced fermion and gauge boson couplings and should be searched for
at high mass (> 600 GeV), ii) have suppressed couplings and could be searched
for at lower masses, where the Standard Model Higgs has already been ruled out,
and iii) have fermiophilic couplings, where it can be searched for in heavy
Higgs and top resonance searches. In the first two regions, the partner also
has substantial decay rates into a pair of Higgs bosons. We touch briefly on
the more model-dependent effects of the nontrivial SU(2)_C multiplets, which
have exotic signals, such as a doubly-charged Higgs. We also discuss how the
loop induced effects of these scalars tend to reduce the Higgs decay rate to
photons, adding an additional uncertainty when extracting the couplings for the
Higgs boson.


  Let $K$ be a number field and $E_1, \ldots, E_n$ be elliptic curves over $K$,
pairwise non-isogenous over $\overline{K}$ and without complex multiplication
over $\overline{K}$. We study the image of the adelic representation of the
absolute Galois group of $K$ naturally attached to $E_1 \times \cdots \times
E_n$. The main result is an explicit bound for the index of this image in
$\left\{ (x_1,\ldots,x_n) \in \operatorname{GL}_2(\hat{\mathbb{Z}})^n
\bigm\vert \det x_i = \det x_j \;\; \forall i,j \right\}$.


  The s-ID problem seeks to compute a causal effect in a specific
sub-population from the observational data pertaining to the same sub
population (Abouei et al., 2023). This problem has been addressed when all the
variables in the system are observable. In this paper, we consider an extension
of the s-ID problem that allows for the presence of latent variables. To tackle
the challenges induced by the presence of latent variables in a sub-population,
we first extend the classical relevant graphical definitions, such as
c-components and Hedges, initially defined for the so-called ID problem (Pearl,
1995; Tian & Pearl, 2002), to their new counterparts. Subsequently, we propose
a sound algorithm for the s-ID problem with latent variables.


  We present a new approach to the Marcinkiewicz interpolation inequality for
the distribution function of the Hilbert transform, and prove an "abstract"
version of this inequality. The approach uses "logarithmic determinants" and
new estimates of canonical products of genus one.


  We discuss a rigorous procedure for quantifying the difference between our
past lightcone and the past lightcone of the fiducial
Friedmann-Lemaitre-Robertson-Walker spacetime modeling the large-scale
description of cosmological data in the standard $\Lambda\mathrm{CDM}$
scenario. This result is made possible by exploiting the scale-dependent
distance functional between past lightcones recently introduced by us. We
express this harmonic map type functional in terms of the physical quantities
that characterize the actual measurements along our past lightcone, namely the
area distance and the lensing distortion, also addressing the very delicate
problem of the presence of lightcone caustics. This analysis works beautifully
and seems to remove several of the difficulties encountered in comparing the
actual geometry of our past lightcone with the geometry of the fiducial FLRW
lightcone of choice. We also discuss how, from the point of view of the FLRW
geometry, this distance functional may be interpreted as a scale-dependent
effective field, the pre-homogeneity field, that may be of relevance in
selecting the FLRW model that best fits the observational data.


  Studying a range of old metal-poor stars provides information over
cosmological timescales of our Galaxy. Such studies are indicative of the
pristine gases and evolution of the Milky Way. Deriving stellar parameters and
abundances from high-resolution observations of stars at various stellar
evolution stages (including old dwarfs and RR Lyrae), allows us to use these
abundances as tracers of an even earlier progenitor population. Here, we carry
out a detailed abundance study of mainly heavy elements (Z > 38), i.e.
neutron-capture elements, which we at low metallicities ([Fe/H] < -2.5) take as
pure supernova type II products. A comparison of the derived abundances to type
II supernova yields of heavy elements provides knowledge of the old stellar
generations as well as properties of neutron-capture formation sites.


  Primordial Black Holes (PBHs) have entered the forefront of theoretical
cosmology, due their potential role in phenomena ranging from gravitational
waves, to dark matter, to galaxy formation. While producing PBHs from
inflationary fluctuations naively would seem to require a large deceleration of
the inflaton from its velocity at the horizon exit of CMB scales, in this work
we demonstrate that an acceleration from a relatively small downward step in
the potential that is transited in much less than an e-fold amplifies
fluctuations as well. Depending on the location of the step, such PBHs could
explain dark matter or the black holes detected by the gravitational wave
interferometers. The perturbation enhancement has a natural interpretation as
particle production due to the non-adiabatic transition associated with the
step.


  Ensuring the highest training throughput to maximize resource efficiency,
while maintaining fairness among users, is critical for deep learning (DL)
training in heterogeneous GPU clusters. However, current DL schedulers provide
only limited fairness properties and suboptimal training throughput, impeding
tenants from effectively leveraging heterogeneous resources. The underlying
design challenge stems from inherent conflicts between efficiency and fairness
properties.
  In this paper, we introduce OEF, a new resource allocation framework
specifically developed for achieving optimal resource efficiency and ensuring
diverse fairness properties in heterogeneous GPU clusters. By integrating
resource efficiency and fairness within a global optimization framework, OEF is
capable of providing users with maximized overall efficiency, as well as
various guarantees of fairness, in both cooperative and non-cooperative
environments. We have implemented OEF in a cluster resource manager and
conducted large-scale experiments, showing that OEF can improve the overall
training throughput by up to 32% while improving fairness compared to
state-of-the-art heterogeneity-aware schedulers.


  Space weather phenomena like geomagnetic disturbances (GMDs) and
geomagnetically induced currents (GICs) pose significant risks to critical
technological infrastructure. While traditional predictive models, grounded in
simulation, hold theoretical robustness, they grapple with challenges, notably
the assimilation of imprecise data and extensive computational complexities. In
recent years, Tiny Machine Learning (TinyML) has been adopted to develop
Machine Learning (ML)-enabled magnetometer systems for predicting real-time
terrestrial magnetic perturbations as a proxy measure for GIC. While TinyML
offers efficient, real-time data processing, its intrinsic limitations prevent
the utilization of robust methods with high computational needs. This paper
developed a physics-guided TinyML framework to address the above challenges.
This framework integrates physics-based regularization at the stages of model
training and compression, thereby augmenting the reliability of predictions.
The developed pruning scheme within the framework harnesses the inherent
physical characteristics of the domain, striking a balance between model size
and robustness. The study presents empirical results, drawing a comprehensive
comparison between the accuracy and reliability of the developed framework and
its traditional counterpart. Such a comparative analysis underscores the
prospective applicability of the developed framework in conceptualizing robust,
ML-enabled magnetometer systems for real-time space weather forecasting.


  Recent text-to-image models have achieved impressive results. However, since
they require large-scale datasets of text-image pairs, it is impractical to
train them on new domains where data is scarce or not labeled. In this work, we
propose using large-scale retrieval methods, in particular, efficient
k-Nearest-Neighbors (kNN), which offers novel capabilities: (1) training a
substantially small and efficient text-to-image diffusion model without any
text, (2) generating out-of-distribution images by simply swapping the
retrieval database at inference time, and (3) performing text-driven local
semantic manipulations while preserving object identity. To demonstrate the
robustness of our method, we apply our kNN approach on two state-of-the-art
diffusion backbones, and show results on several different datasets. As
evaluated by human studies and automatic metrics, our method achieves
state-of-the-art results compared to existing approaches that train
text-to-image generation models using images only (without paired text data)


  Conversation agents fueled by Large Language Models (LLMs) are providing a
new way to interact with visual data. While there have been initial attempts
for image-based conversation models, this work addresses the under-explored
field of \emph{video-based conversation} by introducing Video-ChatGPT. It is a
multimodal model that merges a video-adapted visual encoder with an LLM. The
resulting model is capable of understanding and generating detailed
conversations about videos. We introduce a new dataset of 100,000
video-instruction pairs used to train Video-ChatGPT acquired via manual and
semi-automated pipeline that is easily scalable and robust to label noise. We
also develop a quantitative evaluation framework for video-based dialogue
models to objectively analyze the strengths and weaknesses of video-based
dialogue models. Code: https://github.com/mbzuai-oryx/Video-ChatGPT.


  Bregman parallel direction method of multipliers (BPDMM) efficiently solves
distributed optimization over a network, which arises in a wide spectrum of
collaborative multi-agent learning applications. In this paper, we generalize
BPDMM to stochastic BPDMM, where each iteration only solves local optimization
on a randomly selected subset of nodes rather than all the nodes in the
network. Such generalization reduce the need for computational resources and
allows applications to larger scale networks. We establish both the global
convergence and the \(O(1/T)\) iteration complexity of stochastic BPDMM. We
demonstrate our results via numerical examples.


  It is well known that semantic segmentation can be used as an effective
intermediate representation for learning driving policies. However, the task of
street scene semantic segmentation requires expensive annotations. Furthermore,
segmentation algorithms are often trained irrespective of the actual driving
task, using auxiliary image-space loss functions which are not guaranteed to
maximize driving metrics such as safety or distance traveled per intervention.
In this work, we seek to quantify the impact of reducing segmentation
annotation costs on learned behavior cloning agents. We analyze several
segmentation-based intermediate representations. We use these visual
abstractions to systematically study the trade-off between annotation
efficiency and driving performance, i.e., the types of classes labeled, the
number of image samples used to learn the visual abstraction model, and their
granularity (e.g., object masks vs. 2D bounding boxes). Our analysis uncovers
several practical insights into how segmentation-based visual abstractions can
be exploited in a more label efficient manner. Surprisingly, we find that
state-of-the-art driving performance can be achieved with orders of magnitude
reduction in annotation cost. Beyond label efficiency, we find several
additional training benefits when leveraging visual abstractions, such as a
significant reduction in the variance of the learned policy when compared to
state-of-the-art end-to-end driving models.


  In this first paper on the results of our Herschel PACS survey of local
Ultraluminous Infrared Galaxies (ULIRGs), as part of our SHINING survey of
local galaxies, we present far-infrared spectroscopy of Mrk 231, the most
luminous of the local ULIRGs, and a type 1 broad absorption line AGN. For the
first time in a ULIRG, all observed far-infrared fine-structure lines in the
PACS range were detected and all were found to be deficient relative to the far
infrared luminosity by 1 - 2 orders of magnitude compared with lower luminosity
galaxies. The deficits are similar to those for the mid-infrared lines, with
the most deficient lines showing high ionization potentials. Aged starbursts
may account for part of the deficits, but partial covering of the highest
excitation AGN powered regions may explain the remaining line deficits. A
massive molecular outflow, discovered in OH and 18OH, showing outflow
velocities out to at least 1400 km/sec, is a unique signature of the clearing
out of the molecular disk that formed by dissipative collapse during the
merger. The outflow is characterized by extremely high ratios of 18O / 16O
suggestive of interstellar medium processing by advanced starbursts.


  Accreted stellar populations are comprised of the remnants of destroyed
galaxies, and often dominate the `stellar haloes' of galaxies such as the Milky
Way (MW). This ensemble of external contributors is a key indicator of the past
assembly history of a galaxy. We introduce a novel statistical method that uses
the unbinned metallicity distribution function (MDF) of a stellar population to
estimate the mass spectrum of its progenitors. Our model makes use of the
well-known mass-metallicity relation of galaxies and assumes Gaussian MDF
distributions for individual progenitors: the overall MDF is thus a mixture of
MDFs from smaller galaxies. We apply the method to the stellar halo of the MW,
as well as the classical MW satellite galaxies. The stellar components of the
satellite galaxies have relatively small sample sizes, but we do not find any
evidence for accreted populations with L > L_host/100. We find that the MW
stellar halo has N~1-3 massive progenitors (L > 10^8 L_Sun) within 10 kpc, and
likely several hundred progenitors in total. We also test our method on
simulations of MW-mass haloes, and find that our method is able to recover the
true accreted population within a factor of two. Future datasets will provide
MDFs with orders of magnitude more stars, and this method could be a powerful
technique to quantify the accreted populations down to the ultra-faint dwarf
mass-scale for both the MW and its satellites.


  We propose a conjecture on the categorical trace of the 2-category of
perverse schobers (expected to model the Fukaya-Fueter 2-category of a
holomorphic symplectic space). By proving a Betti geometric version of Tate's
thesis, and combining it with our previous 3d mirror symmetry equivalence and
the Ben-Zvi--Nadler--Preygel result on spectral traces, we are able to
establish our conjecture in the simplest interesting case.


  We study how the presence of correlations in physical variables contributes
to the form of probability distributions. We investigate a process with
correlations in the variance generated by (i) a Gaussian or (ii) a truncated
L\'{e}vy distribution. For both (i) and (ii), we find that due to the
correlations in the variance, the process ``dynamically'' generates power-law
tails in the distributions, whose exponents can be controlled through the way
the correlations in the variance are introduced. For (ii), we find that the
process can extend a truncated distribution {\it beyond the truncation cutoff},
which leads to a crossover between a L\'{e}vy stable power law and the present
``dynamically-generated'' power law. We show that the process can explain the
crossover behavior recently observed in the $S&P500$ stock index.


  When communicating agents form opinions about a set of possible options,
agreement and disagreement are both possible outcomes. Depending on the
context, either can be desirable or undesirable. We show that for nonlinear
opinion dynamics on networks, and a variety of network structures, the spectral
properties of the underlying adjacency matrix fully characterize the occurrence
of either agreement or disagreement. We further show how the corresponding
eigenvector centrality, as well as any symmetry in the network, informs the
resulting patterns of opinion formation and agent sensitivity to input that
triggers opinion cascades.


  We consider covariance parameter estimation for a Gaussian process under
inequality constraints (boundedness, monotonicity or convexity) in fixed-domain
asymptotics. We address the estimation of the variance parameter and the
estimation of the microergodic parameter of the Mat\'ern and Wendland
covariance functions. First, we show that the (unconstrained) maximum
likelihood estimator has the same asymptotic distribution, unconditionally and
conditionally to the fact that the Gaussian process satisfies the inequality
constraints. Then, we study the recently suggested constrained maximum
likelihood estimator. We show that it has the same asymptotic distribution as
the (unconstrained) maximum likelihood estimator. In addition, we show in
simulations that the constrained maximum likelihood estimator is generally more
accurate on finite samples. Finally, we provide extensions to prediction and to
noisy observations.


  Quantum heat engines are commonly believed to achieve their optimal
efficiency when operated under quasi-static conditions. However, when running
at finite power, they suffer effective friction due to the generation of
coherences and transitions between energy eigenstates. It was noted that it is
possible to increase the power of a quantum heat engine using external control
schemes or suitable dephasing noise. Here, we investigate the thermodynamic
cost associated with dephasing noise schemes using both numerical and
analytical methods. Our findings unveil that the observed gain in power is
generally not free of thermodynamic costs, as it involves heat flows from
thermal baths into the dephasing bath. These contributions must be duly
accounted for when determining the engine's overall efficiency. Interestingly,
we identify a particular working regime where these costs become negligible,
demonstrating that quantum heat engines can be operated at any power with an
efficiency per cycle that approaches arbitrarily closely that under quasistatic
operation.


  Previous research indicates that after standard instruction students at all
academic levels often construct a conceptual framework in which the ideas of
absolute simultaneity and the relativity of simultaneity co-exist. This article
describes the development and assessment of instructional materials intended to
improve student understanding of the concept of time in special relativity, the
relativity of simultaneity, and the role of observers in inertial reference
frames. Results from pretests and post-tests are presented to demonstrate the
effect of the curriculum in helping students deepen their understanding of
these topics. Excerpts from taped interviews and classroom interactions help
illustrate the intense cognitive conflict that students encounter as they are
led to confront the incompatibility of their deeply-held beliefs about
simultaneity with the results of special relativity.


  We perform global two-dimensional hydrodynamical simulations of Keplerian
discs with free eccentricity over thousands of orbital periods. Our aim is to
determine the validity of secular theory in describing the evolution of
eccentric discs, and to explore their nonlinear evolution for moderate
eccentricities. Linear secular theory is found to correctly predict the
structure and precession rates of discs with small eccentricities. However,
discs with larger eccentricities (and eccentricity gradients) are observed to
precess faster (retrograde relative to the orbital motion), at a rate that
depends on their eccentricities (and eccentricity gradients). We derive
analytically a nonlinear secular theory for eccentric gas discs, which explains
this result as a modification of the pressure forces whenever eccentric orbits
in a disc nearly intersect. This effect could be particularly important for
highly eccentric discs produced in tidal disruption events, or for narrow
gaseous rings; it might also play a role in causing some of the variability in
superhump binary systems. In two dimensions, the eccentricity of a moderately
eccentric disc is long-lived and persists throughout the duration of our
simulations. Eccentric modes are however weakly damped by their interaction
with non-axisymmetric spiral density waves (driven by the Papaloizou-Pringle
instability, which occurs in our idealised setup with solid walls), as well as
numerical diffusion.


  Nested logic programs have recently been introduced in order to allow for
arbitrarily nested formulas in the heads and the bodies of logic program rules
under the answer sets semantics. Nested expressions can be formed using
conjunction, disjunction, as well as the negation as failure operator in an
unrestricted fashion. This provides a very flexible and compact framework for
knowledge representation and reasoning. Previous results show that nested logic
programs can be transformed into standard (unnested) disjunctive logic programs
in an elementary way, applying the negation as failure operator to body
literals only. This is of great practical relevance since it allows us to
evaluate nested logic programs by means of off-the-shelf disjunctive logic
programming systems, like DLV. However, it turns out that this straightforward
transformation results in an exponential blow-up in the worst-case, despite the
fact that complexity results indicate that there is a polynomial translation
among both formalisms. In this paper, we take up this challenge and provide a
polynomial translation of logic programs with nested expressions into
disjunctive logic programs. Moreover, we show that this translation is modular
and (strongly) faithful. We have implemented both the straightforward as well
as our advanced transformation; the resulting compiler serves as a front-end to
DLV and is publicly available on the Web.


  We propose a general principle for constructing higher-order topological
(HOT) phases. We argue that if a $D$-dimensional first-order or regular
topological phase involves $m$ Hermitian matrices that anti-commute with
additional $p-1$ mutually anti-commuting matrices, it is conceivable to realize
an $n$th-order HOT phase, where $n=1, \cdots, p$, with appropriate combinations
of discrete symmetry-breaking Wilsonian masses. An $n$th-order HOT phase
accommodates zero modes on a surface with codimension $n$. We exemplify these
scenarios for prototypical three-dimensional gapless systems, such as a
nodal-loop semimetal possessing SU(2) spin-rotational symmetry, and Dirac
semimetals, transforming under (pseudo-)spin-$\frac{1}{2}$ or 1
representations. The former system permits an unprecedented realization of a
fourth-order phase, without any surface zero modes. Our construction can be
generalized to HOT insulators and superconductors in any dimension and symmetry
class.


  Complex networks display various types of percolation transitions. We show
that the degree distribution and the degree-degree correlation alone are not
sufficient to describe diverse percolation critical phenomena. This suggests
that a genuine structural correlation is an essential ingredient in
characterizing networks. As a signature of the correlation we investigate a
scaling behavior in $M_N(h)$, the number of finite loops of size $h$, with
respect to a network size $N$. We find that networks, whose degree
distributions are not too broad, fall into two classes exhibiting $M_N(h)\sim
({constant})$ and $M_N(h) \sim (\ln N)^\psi$, respectively. This classification
coincides with the one according to the percolation critical phenomena.


  Astrophysics is gaining increased attention from the particle and nuclear
physics communities, as budget cuts, delays, and cancellations limit
opportunities for breakthrough research at accelerator laboratories.
Observations of cosmic rays (protons and nuclei), gamma rays and neutrinos
present a variety of puzzles whose eventual solution will shed light on many
issues ranging from the nature of fundamental interactions at extreme energies
to the mechanisms of astrophysical sources. Several important detectors are
just beginning full-scale operation and others are beginning construction.


  With the goal of improving spectral efficiency, complex rotation-based
precoding and power allocation schemes are developed for two multiple-input
multiple-output (MIMO) communication systems, namely, simultaneous wireless
information and power transfer (SWIPT) and physical layer multicasting. While
the state-of-the-art solutions for these problems use very different
approaches, the proposed approach treats them similarly using a general tool
and works efficiently for any number of antennas at each node. Through modeling
the precoder using complex rotation matrices, objective functions (transmission
rates) of the above systems can be formulated and solved in a similar
structure. Hence, this approach simplifies signaling design for MIMO systems
and can reduce the hardware complexity by having one set of parameters to
optimize. Extensive numerical results show that the proposed approach
outperforms state-of-the-art solutions for both problems. It increases
transmission rates for multicasting and achieves higher rate-energy regions in
the SWIPT case. In both cases, the improvement is significant (20%-30%) in
practically important settings where the users have one or two antennas.
Furthermore, the new precoders are less time-consuming than the existing
solutions.


  We carefully investigate the gravitational equations of the brane world, in
which all the matter forces except gravity are confined on the 3-brane in a
5-dimensional spacetime with $Z_2$ symmetry.
  We derive the effective gravitational equations on the brane, which reduce to
the conventional Einstein equations in the low energy limit. {}From our general
argument we conclude that the first Randall & Sundrum-type theory (RS1)
[hep-ph/9905221] predicts that the brane with the negative tension is an
anti-gravity world and hence should be excluded from the physical point of
view. Their second-type theory (RS2) [hep-th/9906064] where the brane has the
positive tension provides the correct signature of gravity. In this latter
case, if the bulk spacetime is exactly anti-de Sitter, generically the matter
on the brane is required to be spatially homogeneous because of the Bianchi
identities. By allowing deviations from anti-de Sitter in the bulk, the
situation will be relaxed and the Bianchi identities give just the relation
between the Weyl tensor and the energy momentum tensor. In the present brane
world scenario, the effective Einstein equations cease to be valid during an
era when the cosmological constant on the brane is not well-defined, such as in
the case of the matter dominated by the potential energy of the scalar field.


  We investigate the problem of finding paths that enable a robot modeled as a
Dubins car (i.e., a constant-speed finite-turn-rate unicycle) to escape from a
circular region of space in minimum time. This minimum-time escape problem
arises in marine, aerial, and ground robotics in situations where a safety
region has been violated and must be exited before a potential negative
consequence occurs (e.g., a collision). Using the tools of nonlinear optimal
control theory, we show that a surprisingly simple closed-form feedback control
law solves this minimum-time escape problem, and that the minimum-time paths
have an elegant geometric interpretation.


  Many functions have approximately-known upper and/or lower bounds,
potentially aiding the modeling of such functions. In this paper, we introduce
Gaussian process models for functions where such bounds are (approximately)
known. More specifically, we propose the first use of such bounds to improve
Gaussian process (GP) posterior sampling and Bayesian optimization (BO). That
is, we transform a GP model satisfying the given bounds, and then sample and
weight functions from its posterior. To further exploit these bounds in BO
settings, we present bounded entropy search (BES) to select the point gaining
the most information about the underlying function, estimated by the GP
samples, while satisfying the output constraints. We characterize the sample
variance bounds and show that the decision made by BES is explainable. Our
proposed approach is conceptually straightforward and can be used as a plug in
extension to existing methods for GP posterior sampling and Bayesian
optimization.


  The effect of the full treatment is a primary parameter of interest in policy
evaluation, while often only the effect of a subset of treatment is estimated.
We partially identify the local average treatment effect of receiving full
treatment (LAFTE) using an instrumental variable that may induce individuals
into only a subset of treatment (movers). We show that movers violate the
standard exclusion restriction, necessary conditions on the presence of movers
are testable, and partial identification holds under a double exclusion
restriction. We identify movers in four empirical applications and estimate
informative bounds on the LAFTE in three of them.


  Deep generative models are stochastic neural networks capable of learning the
distribution of data so as to generate new samples. Conditional Variational
Autoencoder (CVAE) is a powerful deep generative model aiming at maximizing the
lower bound of training data log-likelihood. In the CVAE structure, there is
appropriate regularizer, which makes it applicable for suitably constraining
the solution space in solving ill-posed problems and providing high
generalization power. Considering the stochastic prediction characteristic in
CVAE, depending on the problem at hand, it is desirable to be able to control
the uncertainty in CVAE predictions. Therefore, in this paper we analyze the
impact of CVAE's condition on the diversity of solutions given by our designed
CVAE in 3D shape inverse rendering as a prediction problem. The experimental
results using Modelnet10 and Shapenet datasets show the appropriate performance
of our designed CVAE and verify the hypothesis: \emph{"The more informative the
conditions in terms of object pose are, the less diverse the CVAE predictions
are}".


  We prove that for certain classes of pseudoconvex domains of finite type, the
Bergman-Toeplitz operator $T_{\psi}$ with symbol $\psi=K^{-\alpha}$ maps from
$L^{p}$ to $L^{q}$ continuously with $1< p\le q<\infty$ if and only if
$\alpha\ge\frac{1}{p}-\frac{1}{q}$, where $K$ is the Bergman kernel on
diagonal.
  This work generalises the results on strongly pseudoconvex domains by
\v{C}u\v{c}kovi\'{c} and McNeal, and Abeta, Raissy and Saracco.


  In this work we investigate the weak $\Lambda_{b}\to\Lambda_c$ semi-leptonic
and non-leptonic decays. The light-front quark model and diquark picture for
heavy baryons are adopted to evaluate the $\Lambda_{b}\to\Lambda_c$ transition
form factors. In the heavy quark limit we study the Isgur-Wise function. By
fitting the data of the semi-leptonic process we obtain the mass of the light
scalar diquark as 817 MeV. The numerical predictions on the branching ratios of
non-leptonic decay modes $\Lambda_{b}\to\Lambda_c M$ and various polarization
asymmetries are made. A comparison with other approaches is discussed.


  We consider a pointwise tracking optimal control problem for a semilinear
elliptic partial differential equation. We derive the existence of optimal
solutions and analyze first and, necessary and sufficient, second order
optimality conditions. We devise two strategies of discretization to
approximate a solution of the optimal control problem: a semidiscrete scheme
where the control variable is not discretized -- the so-called variational
discretization approach -- and a fully discrete scheme where the control
variable is discretized with piecewise constant functions. For both solution
techniques, we analyze convergence properties of discretizations and derive
error estimates.


  We investigate minimally completed models of extraordinary gauge mediation,
which are examples of direct gauge mediation, at finite temperature both
analytically and numerically. These models may have both supersymmetry breaking
and supersymmetric vacua. Our interest is in determining the preferred vacuum.
We do so by computing the finite temperature Coleman-Weinberg potential and
studying its thermal evolution.


  In this work, we investigate the microscopic nature of the magnetism in
honeycomb iridium-based systems by performing a systematic study of how the
effective magnetic interactions in these compounds depend on various electronic
microscopic parameters. We show that the minimal model describing the magnetism
in A$_2$IrO$_3$ includes both isotropic and anisotropic Kitaev-type
spin-exchange interactions between nearest and next-nearest neighbor Ir ions,
and that the magnitude of the Kitaev interaction between next-nearest neighbor
Ir magnetic moments is comparable with nearest neighbor interactions. We also
find that, while the Heisenberg and the Kitaev interactions between nearest
neighbors are correspondingly antiferro- and ferromagnetic, they both change
sign for the next-nearest neighbors. Using classical Monte Carlo simulations we
examine the magnetic phase diagram of the derived super-exchange model.
Zigzag-type antiferromagnetic order is found to occupy a large part of the
phase diagram of the model and, for ferromagnetic next-nearest neighbor
Heisenberg interaction relevant for Na$_2$IrO$_3$, it can be stabilized even in
the absence of third nearest neighbor coupling. Our results suggest that a
natural physical origin of the zigzag phase experimentally observed in
Na$_2$IrO$_3$ is due to the interplay of the Kitaev anisotropic interactions
between nearest and next-nearest neighbors.


  Students who eat breakfast more frequently tend to have a higher grade point
average. From this data, many people might confidently state that a
before-school breakfast program would lead to higher grades. This is a
reasoning error, because correlation does not necessarily indicate causation --
X and Y can be correlated without one directly causing the other. While this
error is pervasive, its prevalence might be amplified or mitigated by the way
that the data is presented to a viewer. Across three crowdsourced experiments,
we examined whether how simple data relations are presented would mitigate this
reasoning error. The first experiment tested examples similar to the
breakfast-GPA relation, varying in the plausibility of the causal link. We
asked participants to rate their level of agreement that the relation was
correlated, which they rated appropriately as high. However, participants also
expressed high agreement with a causal interpretation of the data. Levels of
support for the causal interpretation were not equally strong across
visualization types: causality ratings were highest for text descriptions and
bar graphs, but weaker for scatter plots. But is this effect driven by bar
graphs aggregating data into two groups or by the visual encoding type? We
isolated data aggregation versus visual encoding type and examined their
individual effect on perceived causality. Overall, different visualization
designs afford different cognitive reasoning affordances across the same data.
High levels of data aggregation by graphs tend to be associated with higher
perceived causality in data. Participants perceived line and dot visual
encodings as more causal than bar encodings. Our results demonstrate how some
visualization designs trigger stronger causal links while choosing others can
help mitigate unwarranted perceptions of causality.