  An increasing number of applications require to recognize the class of an
incoming time series as quickly as possible without unduly compromising the
accuracy of the prediction. In this paper, we put forward a new optimization
criterion which takes into account both the cost of misclassification and the
cost of delaying the decision. Based on this optimization criterion, we derived
a family of non-myopic algorithms which try to anticipate the expected future
gain in information in balance with the cost of waiting. In one class of
algorithms, unsupervised-based, the expectations use the clustering of time
series, while in a second class, supervised-based, time series are grouped
according to the confidence level of the classifier used to label them.
Extensive experiments carried out on real data sets using a large range of
delay cost functions show that the presented algorithms are able to
satisfactorily solving the earliness vs. accuracy trade-off, with the
supervised-based approaches faring better than the unsupervised-based ones. In
addition, all these methods perform better in a wide variety of conditions than
a state of the art method based on a myopic strategy which is recognized as
very competitive.


  Discrete wave mechanics describes the evolution of classical or matter waves
on a lattice, which is governed by a discretized version of the Schr\"odinger
equation. While for a vanishing lattice spacing wave evolution of the
continuous Schr\"odinger equation is retrieved, spatial discretization and
lattice effects can deeply modify wave dynamics. Here we discuss implications
of breakdown of exact Galilean invariance of the discrete Schr\"odinger
equation on the bound states sustained by a smooth potential well which is
uniformly moving on the lattice with a drift velocity $v$. While in the
continuous limit the number of bound states does not depend on the drift
velocity $v$, as one expects from the covariance of ordinary Schr\"odinger
equation for a Galilean boost, lattice effects can lead to a larger number of
bound states for the moving potential well as compared to the potential well at
rest. Moreover, for a moving potential bound states on a lattice become rather
generally quasi-bound (resonance) states.


  We discuss the correlation function of hadronic currents in the Schwinger
model at finite temperature $T$. We explicitly construct the retarded
correlator in real time and obtain analytical results for the Euclidean
correlator on a torus. Both constructions lead to the same finite temperature
spectral function. The spatial screening lengths in the mesonic channels are
related to the dynamical meson mass $m=e/\sqrt{\pi}$ and not $2\pi T$ even in
the infinite temperature limit. The relevance of our results for the finite
temperature problem in four dimensions is discussed.


  The thermal conductivities of beta-Ga2O3 single crystals along four different
crystal directions were measured in the temperature range of 80-495K using the
time domain thermoreflectance (TDTR) method. A large anisotropy was found. At
room temperature, the [010] direction has the highest thermal conductivity of
27.0+/-2.0 W/mK, while that along the [100] direction has the lowest value of
10.9+/-1.0 W/mK. At high temperatures, the thermal conductivity follows a ~1/T
relationship characteristic of Umklapp phonon scattering, indicating
phonon-dominated heat transport in the \b{eta}-Ga2O3 crystal. The measured
experimental thermal conductivity is supported by first-principles calculations
which suggest that the anisotropy in thermal conductivity is due to the
differences of the speed of sound along different crystal directions.


  Herzog-Hibi-Hreind\'{o}ttir-Kahle-Rauh introduced the class of closed graph
and they proved that the binomial edge ideal $J(G)$ of a graph $G$ has
quadratic Gr\"{o}bner bases if $G$ is closed. In this paper, we introduce the
class of weakly closed graph as a generalization of the closed graph and prove
that the quotient ring $S/J(G)$ is $F$-pure if $G$ is weakly closed. This fact
is a generalization of Ohtani's theorem.


  In this dissertation the notion of deformation quantization of principal
fibre bundles is established and investigated in order to find a geometric
formulation of classical gauge theories on noncommutative space-times. As a
generalization, the notion of deformation quantization of surjective
submersions is also discussed.
  It is shown that deformation quantizations of surjective submersions and
principal fibre bundles always exist and are unique up to equivalence. These
statements concerning complex-valued functions are moreover formulated and
proved for sections of arbitrary vector bundles over the total space, in
particular equivariant vector bundles. The commutants of the deformed right
module structures within the differential operators, playing an inportant role
with regard to the infinitesimal gauge transformations, are computed explicitly
in each case. Depending on the choice of specific covariant derivatives and
connections the commutants are isomorphic to the formal power series of the
respective vertical differential operators which thus inherit a deformation of
the algebra structure. The resulting deformed bimodules are again unique up to
equivalence. With respect to further applications it is finally shown that
every deformation quantization of a principal fibre bundle induces a
deformation quantization of any associated vector bundle.


  Abridged.-- We demonstrate that the radiation emitted by ultrarelativistic
electrons in highly nonuniform, small-scale magnetic fields is different from
synchrotron radiation if the electron's transverse deflections in these fields
are much smaller than the beaming angle. A quantitative analytical theory of
this radiation, which we refer to as jitter radiation, is developed. It is
shown that the emergent spectrum is determined by statistical properties of the
magnetic field. As an example,we then use the model of a magnetic field in
internal shocks of GRBs. The spectral power distribution of radiation produced
by the power-law electrons is well described by a sharply broken power-law with
indices 1 and -(p-1)/2 and the jitter break frequency is independent of the
field strength but depends on the electron density in the ejecta. Since
large-scale fields may also be present in the ejecta, we construct a
two-component, jitter+synchrotron spectral model of the prompt $\gamma$-ray
emission. Quite surprisingly, this model seems to be readily capable of
explaining several properties of time-resolved spectra of some GRBs, such as
(i) the violation of the constraint on the low-energy spectral index called the
synchrotron ``line of death'', (ii) the sharp spectral break at the peak
frequency, inconsistent with the broad synchrotron bump, (iii) the evidence for
two spectral sub-components, and (iv) possible existence of emission features
called ``GRB lines''. We believe these facts strongly support both the
existence of small-scale magnetic fields and the proposed radiation mechanism
from GRB shocks. As an example, we use the composite model to analyze GRB
910503 which has two spectral peaks.


  This work proposes a metric learning approach for self-supervised scene flow
estimation. Scene flow estimation is the task of estimating 3D flow vectors for
consecutive 3D point clouds. Such flow vectors are fruitful, \eg for
recognizing actions, or avoiding collisions. Training a neural network via
supervised learning for scene flow is impractical, as this requires manual
annotations for each 3D point at each new timestamp for each scene. To that
end, we seek for a self-supervised approach, where a network learns a latent
metric to distinguish between points translated by flow estimations and the
target point cloud. Our adversarial metric learning includes a multi-scale
triplet loss on sequences of two-point clouds as well as a cycle consistency
loss. Furthermore, we outline a benchmark for self-supervised scene flow
estimation: the Scene Flow Sandbox. The benchmark consists of five datasets
designed to study individual aspects of flow estimation in progressive order of
complexity, from a moving object to real-world scenes. Experimental evaluation
on the benchmark shows that our approach obtains state-of-the-art
self-supervised scene flow results, outperforming recent neighbor-based
approaches. We use our proposed benchmark to expose shortcomings and draw
insights on various training setups. We find that our setup captures motion
coherence and preserves local geometries. Dealing with occlusions, on the other
hand, is still an open challenge.


  In this paper, we propose numerical scheme for the Riesz space fractional
advection-dispersion equations with delay (RFADED). Firstly, analytical
solution for RFADED in terms of the functions of Mittag-Leffler type is
derived. Secondly, the fractional backward differential formulas (FBDF) method
and shifted Gr\"{u}nwald method are introduced to the Riesz space fractional
derivatives. Next, stability and convergency of these methods have been proved.
Thirdly, Crank-Nicolson scheme for solving this problem is proposed. We prove
that the scheme is conditionally stable and convergent with the order accuracy
of ${\rm O}({\kappa ^2} + {h^2})$. Finally, some numerical results are given to
demonstrate that presented method is a computationally efficient and accurate
method for solving RFADED.


  The functional linear regression model with points of impact is a recent
augmentation of the classical functional linear model with many practically
important applications. In this work, however, we demonstrate that the existing
data-driven procedure for estimating the parameters of this regression model
can be very instable and inaccurate. The tendency to omit relevant points of
impact is a particularly problematic aspect resulting in omitted-variable
biases. We explain the theoretical reason for this problem and propose a new
sequential estimation algorithm that leads to significantly improved estimation
results. Our estimation algorithm is compared with the existing estimation
procedure using an in-depth simulation study. The applicability is demonstrated
using data from Google AdWords, today's most important platform for online
advertisements. The \textsf{R}-package \texttt{FunRegPoI} and additional
\textsf{R}-codes are provided in the online supplementary material.


  The scaling behaviors of graphene nanoribbon (GNR) Schottky barrier
field-effect transistors (SBFETs) are studied by solving the non-equilibrium
Green's function (NEGF) transport equation in an atomistic basis set
self-consistently with a three-dimensional Poisson equation. The armchair edge
GNR channel shares similarities with a zigzag CNT, but it has a different
geometry and quantum confinement boundary condition in the transverse
direction. The results indicate that the I-V characteristics are ambipolar and
strongly depend on the GNR width because the bandgap of the GNR is
approximately inversely proportional to its width, which agrees with recent
experiments. A multiple gate geometry improves immunity to short channel
effects, but it offers smaller improvement than it does for Si MOSFETs in terms
of the on-current and transconductance. Reducing the oxide thickness is more
useful for improving transistor performance than using a high-k gate insulator.
Significant increase of the minimal leakage current is observed when the
channel length is scaled below 10nm because the small effective mass
facilitates strong source-drain tunneling. The GNRFET, therefore, does not
promise extending the ultimate scaling limit of Si MOSFETs. The intrinsic
switching speed of a GNR SBFET, however, is several times faster than that of
Si MOSFETs, which could lead to promising high speed electronics applications,
where the large leakage of GNR SBFETs is of less concern.


  We present two NuSTAR observations of the local Seyfert 2 active galactic
nucleus (AGN) and an ultraluminous X-ray source (ULX) candidate in NGC 5643.
Together with archival data from Chandra, XMM-Newton and Swift-BAT, we perform
a high-quality broadband spectral analysis of the AGN over two decades in
energy ($\sim$0.5-100 keV). Previous X-ray observations suggested that the AGN
is obscured by a Compton-thick (CT) column of obscuring gas along our
line-of-sight. However, the lack of high-quality $\gtrsim$ 10 keV observations,
together with the presence of a nearby X-ray luminous source, NGC 5643 X-1, had
left significant uncertainties in the characterization of the nuclear spectrum.
NuSTAR now enables the AGN and NGC 5643 X-1 to be separately resolved above 10
keV for the first time and allows a direct measurement of the absorbing column
density toward the nucleus. The new data show that the nucleus is indeed
obscured by a CT column of $N_{\rm{H}}$ $\gtrsim$ 5 $\times$ 10$^{24}$
cm$^{-2}$. The range of 2-10 keV absorption-corrected luminosity inferred from
the best fitting models is $L_{2-10,\rm{int}} =$ (0.8-1.7) $\times$ 10$^{42}$
erg s$^{-1}$, consistent with that predicted from multiwavelength intrinsic
luminosity indicators. We also study the NuSTAR data for NGC 5643 X-1, and show
that it exhibits evidence for a spectral cut-off at energy, $E$ $\sim$ 10 keV,
similar to that seen in other ULXs observed by NuSTAR. Along with the evidence
for significant X-ray luminosity variations in the 3-8 keV band from 2003-2014,
our results further strengthen the ULX classification of NGC 5643 X-1.


  A three-field local projection stabilized finite element method is developed
for computations of a 3D-axisymmetric buoyancy driven bubble rising in a liquid
column in which either the bubble or the liquid column can be viscoelastic. The
two-phase flow is described by the time-dependent incompressible Navier--Stokes
equations, whereas the viscoelasticity is modeled by the Giesekus constitutive
equation in a time-dependent domain. The arbitrary Lagrangian Eulerian~(ALE)
formulation with finite elements is used to solve the governing equations in
the time-dependent domain. The interface-resolved moving meshes in ALE allows
to incorporate the interfacial tension force and jumps in the material
parameters accurately. An one-level Local Projection Stabilization~(LPS), which
is based on an enriched approximation space and a discontinuous projection
space, where both spaces are defined on a same mesh is used to stabilize the
model equations. The stabilized numerical scheme allows us to use equal order
interpolation spaces for the velocity and the viscoelastic stress, whereas
inf-sup stable finite elements are used for the velocity and the pressure. A
comprehensive numerical investigation is performed for a Newtonian bubble
rising in a viscoelastic fluid and a viscoelastic bubble rising in a Newtonian
fluid. The influence of the viscosity ratio, Newtonian solvent ratio, Giesekus
mobility factor and the E\"{o}tv\"{o}s number on the bubble dynamics are
analyzed. The numerical study shows that a Newtonian bubble rising in a
viscoelastic fluid experiences an extended trailing edge with a cusp-like shape
and also exhibits the negative wake phenomena. However, a viscoelastic bubble
rising in a Newtonian fluid develops an indentation around the rear stagnation
point with a dimpled shape.


  A new class of exact-repair regenerating codes is constructed by combining
two layers of erasure correction codes together with combinatorial block
designs, e.g., Steiner systems, balanced incomplete block designs and
t-designs. The proposed codes have the "uncoded repair" property where the
nodes participating in the repair simply transfer part of the stored data
directly, without performing any computation. The layered error correction
structure makes the decoding process rather straightforward, and in general the
complexity is low. We show that this construction is able to achieve
performance better than time-sharing between the minimum storage regenerating
codes and the minimum repair-bandwidth regenerating codes.


  We study the one-dimensional motion of a Brownian particle inside a
confinement described by two reactive boundaries which can partially reflect or
absorb the particle. Understanding the effects of such boundaries is important
in physics, chemistry and biology. We compute the probability density of the
particle displacement exactly, from which we derive expressions for the
survival probability and the mean absorption time as a function of the reactive
coefficients. Furthermore, using the Feynman-Kac formalism, we investigate the
reaction time profile, which is the fluctuating time spent by the particle at a
given location, both till a fixed observation time and till the absorption
time. Our analytical results are compared to numerical simulations showing
perfect agreement.


  In a recent paper, Drusvyatskiy, Lee, Ottaviani, and Thomas establish a
"transfer principle" by means of which the Euclidean distance degree of an
orthogonally-stable matrix variety can be computed from the Euclidean distance
degree of its intersection with a linear subspace. We generalise this
principle.


  We present measurements of asymmetries in angular distributions of leptons
produced in ttbar events in proton-antiproton collisions at the Fermilab
Tevatron Collider. We consider final states where the W bosons from top quark
and antiquark decays both decay into l nu (l=e, mu) resulting in oppositely
charged dilepton final states with accompanying jets. Using 9.7 fb^-1 of
integrated luminosity collected with the D0 detector, we find the asymmetries
in lepton pseudorapidity compatible with predictions based on the standard
model.


  The A-type metallic-line (Am) stars are typically considered to be
non-magnetic or possessing very weak sub-G magnetic fields. This view has been
repeatedly challenged in the literature, most commonly for the bright hot Am
star o Peg. Several studies claimed to detect 1-2 kG field of unknown topology
in this object, possibly indicating a new process of magnetic field generation
in intermediate-mass stars. In this study, we revisit the evidence of a strong
magnetic field in o Peg using new high-resolution spectropolarimetric
observations and advanced spectral fitting techniques. The mean magnetic field
strength in o Peg is estimated from the high-precision CRIRES+ measurement of
near-infrared sulphur lines. This observation is modelled with a polarised
radiative transfer code, including treatment of the departures from local
thermodynamic equilibrium. In addition, the least-squares deconvolution
multi-line technique is employed to derive longitudinal field measurements from
archival optical spectropolarimetric observations of this star. Our analysis of
the near-infrared S I lines reveals no evidence of Zeeman broadening, ruling
out magnetic field with a strength exceeding 260 G. This null result is
compatible with the relative intensification of Fe II lines in the optical
spectrum taking into account blending and uncertain atomic parameters of the
relevant diagnostic transitions. Longitudinal field measurements at three
different nights also yield null results with a precision of 2 G. This study
refutes the claims of kG-strength dipolar or tangled magnetic field in o Peg.
This star is effectively non-magnetic, with the surface magnetic field
characteristics no different from those of other Am stars.


  We study dynamical systems induced by birational automorphisms on smooth
cubic surfaces defined over a number field $K$. In particular we are interested
in the product of non-commuting birational Geiser involutions of the cubic
surface. We present results describing the sets of $K$ and $\bar{K}$-periodic
points of the system, and give a necessary and sufficient condition for a
dynamical local-global property called strong residual periodicity. Finally, we
give a dynamical result relating to the Mordell--Weil problem on cubic
surfaces.


  In this paper, we produce new classes of MDS self-dual codes via (extended)
generalized Reed-Solomon codes over finite fields of odd characteristic. Among
our constructions, there are many MDS self-dual codes with new parameters which
have never been reported. For odd prime power $q$ with $q$ square, the total
number of lengths for MDS self-dual codes over $\mathbb{F}_q$ presented in this
paper is much more than those in all the previous results.


  Completely positive maps are useful in modeling the discrete evolution of
quantum systems. Spectral properties of operators associated with such maps are
relevant for determining the asymptotic dynamics of quantum systems subjected
to multiple interactions described by the same quantum channel. We discuss a
connection between the properties of the peripheral spectrum of completely
positive and trace preserving map and the algebra generated by its Kraus
operators $\mathcal{A}(A_1,\ldots A_K)$. By applying the Shemesh and Amitsur -
Levitzki theorems to analyse the structure of the algebra
$\mathcal{A}(A_1,\ldots A_K)$ one can predict the asymptotic dynamics for a
class of operations.


  We identify the "organization" of a human social group as the communication
network(s) within that group. We then introduce three theoretical approaches to
analyzing what determines the structures of human organizations. All three
approaches adopt a group-selection perspective, so that the group's network
structure is (approximately) optimal, given the information-processing
limitations of agents within the social group, and the exogenous welfare
function of the overall group. In the first approach we use a new sub-field of
telecommunications theory called network coding, and focus on a welfare
function that involves the ability of the organization to convey information
among the agents. In the second approach we focus on a scenario where agents
within the organization must allocate their future communication resources when
the state of the future environment is uncertain. We show how this formulation
can be solved with a linear program. In the third approach, we introduce an
information synthesis problem in which agents within an organization receive
information from various sources and must decide how to transform such
information and transmit the results to other agents in the organization. We
propose leveraging the computational power of neural networks to solve such
problems. These three approaches formalize and synthesize work in fields
including anthropology, archeology, economics and psychology that deal with
organization structure, theory of the firm, span of control and cognitive
limits on communication.


  The merger remnant NGC 1316 (Fornax A) is one of the most important objects
regarding the investigation of merger-related processes. We use kinematical
data of globular clusters (GCs) and the diffuse stellar light to investigate
the global structure of NGC 1316 and to constrain the dark matter content. We
perform multi-object-spectroscopy with VLT/FORS2 and MXU. Out of 562 slits, we
extract radial velocities for 177 GCs. Moreover, we measure radial velocities
of the integrated galaxy light, using slits with a sufficiently bright "sky".
To these data, we add 20 cluster velocities from Goudfrooij et al. (2001). In
an appendix, we identify new morphological features of NGC 1316 and its
companion galaxy NGC 1317. The GC sample based on radial velocities confirms
the colour peaks already found in our photometric study. The bright clusters,
which probably have their origin in a 2 Gyr-old starburst and younger star
formation events, avoid the systemic velocity. A Gaussian velocity distribution
is found only for clusters fainter than about m_R=22 mag. The velocity
distribution of clusters shows a pronounced peak at 1600 km/s. These clusters
populate a wide area in the south-western region which we suspect to be a disk
population. Globular clusters or subsamples of them do not show a clear
rotation signal. This is different from the galaxy light, where rotation along
the major axis is discernable out to 3 arcmin radius. A simple spherical model
like that suggested by dynamical analyses of planetary nebulae reproduces also
the velocity dispersions of the faint GCs. The central dark matter density of
the present model resembles a giant elliptical galaxy. This contradicts
population properties which indicate spiral galaxies as pre-merger components.
MOND would provide a solution, but the kinematical complexity of NGC 1316 does
not allow a really firm conclusion. (abridged)


  This study introduces a connective model of routing -- local path planning
for Autonomous Underwater Vehicle (AUV) time efficient maneuver in long-range
operations. Assuming the vehicle operating in a turbulent underwater
environment, the local path planner produces the water-current resilient
shortest paths along the existent nodes in the global route. A re-routing
procedure is defined to re-organize the order of nodes in a route and
compensate any lost time during the mission. The Firefly Optimization Algorithm
(FOA) is conducted by both of the planners to validate the model's performance
in mission timing and its robustness against water current variations.
Considering the limitation over the battery life time, the model offers an
accurate mission timing and real-time performance. The routing system and the
local path planner operate cooperatively, and this is another reason for
model's real-time performance. The simulation results confirms the model's
capability in fulfillment of the expected criterion and proves its significant
robustness against underwater uncertainties and variations of the mission
conditions.


  We study various classical aspects of the Weyl transverse (WTDiff) gravity in
a general space-time dimension. First of all, we clarify a classical
equivalence among three kinds of gravitational theories, those are, the
conformally-invariant scalar tensor gravity, Einstein's general relativity and
the WTDiff gravity via the gauge fixing procedure. Secondly, we show that in
the WTDiff gravity the cosmological constant is a mere integration constant as
in unimodular gravity, but it does not receive any radiative corrections unlike
the unimodular gravity. A key point in this proof is to construct a covariantly
conserved energy-momentum tensor, which is achieved on the basis of this
equivalence relation. Thirdly, we demonstrate that the Noether current for the
Weyl transformation is identically vanishing, thereby implying that the Weyl
symmetry existing in both the conformally-invariant scalar tensor gravity and
the WTDiff gravity is a "fake" symmetry. We find it possible to extend this
proof to all matter fields, i.e. the Weyl invariant scalar, vector and spinor
fields. Fourthly, it is explicitly shown that in the WTDiff gravity the
Schwarzshild black hole metric and a charged black hole one are classical
solutions to the equations of motion only when they are expressed in the
Cartesian coordinate system. Finally, we consider the
Friedmann-Lemaitre-Robertson-Walker (FLRW) cosmology and provide some exact
solutions.


  Multi objective (MO) optimization is an emerging field which is increasingly
being implemented in many industries globally. In this work, the MO
optimization of the extraction process of bioactive compounds from the Gardenia
Jasminoides Ellis fruit was solved. Three swarm-based algorithms have been
applied in conjunction with normal-boundary intersection (NBI) method to solve
this MO problem. The gravitational search algorithm (GSA) and the particle
swarm optimization (PSO) technique were implemented in this work. In addition,
a novel Hopfield-enhanced particle swarm optimization was developed and applied
to the extraction problem. By measuring the levels of dominance, the optimality
of the approximate Pareto frontiers produced by all the algorithms were gauged
and compared. Besides, by measuring the levels of convergence of the frontier,
some understanding regarding the structure of the objective space in terms of
its relation to the level of frontier dominance is uncovered. Detail
comparative studies were conducted on all the algorithms employed and developed
in this work.


  Efficient anti-reflection coatings (ARC) improve the light collection and
thereby increase the current output of solar cells. By simple electrochemical
etching of the Si wafer, porous silicon (PS) layers with excellent broadband
anti-reflection properties can be fabricated. In this work, ageing of graded PS
has been studied using Spectroscopic Ellipsometry, Transmission Electron
Microscopy and X-ray Photoelectron Spectroscopy. During oxidation of PS
elements such as pure Si (Si$^0$), Si$_2$O (Si$^+$), SiO (Si$^{2+}$),
Si$_2$O$_3$ (Si$^{3+}$), and SiO$_2$ (Si$^{4+}$) are present. In addition both
hydrogen and carbon is introduced to the PS in the form of Si$_3$SiH and CO.
The oxide grows almost linearly with time when exposed to oxygen, from an
average thickness of 0 - 3.8 nm for the surface PS. The oxidation is then
correlated to the optical stability of multi-layered PS ARCs. It is found that
even after extensive oxidation, the changes in the optical properties of the PS
structures are small.


  Operator splitting is a popular divide-and-conquer strategy for solving
differential equations. Typically, the right-hand side of the differential
equation is split into a number of parts that are then integrated separately.
Many methods are known that split the right-hand side into two parts. This
approach is limiting, however, and there are situations when 3-splitting is
more natural and ultimately more advantageous. The second-order Strang
operator-splitting method readily generalizes to a right-hand side splitting
into any number of operators. It is arguably the most popular method for
3-splitting because of its efficiency, ease of implementation, and intuitive
nature. Other 3-splitting methods exist, but they are less well-known, and
\rev{analysis and} evaluation of their performance in practice are scarce. We
demonstrate the effectiveness of some alternative 3-split, second-order methods
to Strang splitting on two problems: the reaction-diffusion Brusselator, which
can be split into three parts that each have closed-form solutions, and the
kinetic Vlasov--Poisson equations that is used in semi-Lagrangian plasma
simulations. We find alternative second-order 3-operator-splitting methods that
realize efficiency gains of 10\%--20\% over traditional Strang splitting. Our
analysis for the practical assessment of efficiency of operator-splitting
methods includes the computational cost of the integrators and can be used in
method design.


  We study the behaviour of the K\"ahler-Ricci flow on projective bundles. We
show that if the initial metric is in a suitable K\"ahler class, then the
fibers collapse in finite time and the metrics converge subsequentially in the
Gromov-Hausdorff sense to a metric on the base.


  We show that, independently of the boundary conditions, the two phases of the
4-dimensional compact U(1) lattice gauge theory can be characterized by the
presence or absence of an ``infinite'' current network, with an appropriate
definition of ``infinite'' for the various types of boundary conditions imposed
on the finite lattice. The probability for the occurrence of an ``infinite''
network takes values 0 or 1 in the cold and hot phase, respectively. It thus
constitutes a very efficient order parameter, which allows one to determine the
transition region at low computational cost. In addition, for open and fixed
boundary conditions we address the question of the impact of inhomogeneities
and give examples of the reappearance of an energy gap already at moderate
lattice sizes.


  In this paper, we establish the weak convergence rate of density-dependent
stochastic differential equations with bounded drift driven by $\alpha$-stable
processes with $\alpha\in(1,2)$. The well-posedness of these equations has been
previously obtained in \cite{wu2023well}. We derive an explicit convergence
rate in total variation for the Euler-Maruyama scheme, employing a technique
rooted in \cite{hao2023}.


  We revise the proof of low-rate upper bounds on the reliability function of
discrete memoryless channels for ordinary and list-decoding schemes, in
particular Berlekamp and Blinovsky's zero-rate bound, as well as Blahut's bound
for low rates. The available proofs of the zero-rate bound devised by Berlekamp
and Blinovsky are somehow complicated in that they contain in one form or
another some cumbersome "non-standard" procedures or computations. Here we
follow Blinovsky's idea of using a Ramsey-theoretic result by Komlos, and we
complement it with some missing steps to present a proof which is rigorous and
easier to inspect. Furthermore, we show how these techniques can be used to fix
an error that invalidated the proof of Blahut's low-rate bound, which is here
presented in an extended form for list decoding and for general channels.


  We describe the Dark Energy Survey (DES) photometric data set assembled from
the first three years of science operations to support DES Year 3 cosmology
analyses, and provide usage notes aimed at the broad astrophysics community. Y3
Gold improves on previous releases from DES, Y1 Gold and Data Release 1 (DES
DR1), presenting an expanded and curated data set that incorporates algorithmic
developments in image detrending and processing, photometric calibration, and
object classification. Y3 Gold comprises nearly 5000 square degrees of grizY
imaging in the south Galactic cap, including nearly 390 million objects, with
depth reaching S/N ~ 10 for extended objects up to $i_{AB}\sim 23.0$, and
top-of-the-atmosphere photometric uniformity $< 3$ mmag. Compared to DR1,
photometric residuals with respect to Gaia are reduced by $50\%$, and
per-object chromatic corrections are introduced. Y3 Gold augments DES DR1 with
simultaneous fits to multi-epoch photometry for more robust galaxy color
measurements and corresponding photometric redshift estimates. Y3 Gold features
improved morphological star-galaxy classification with efficiency $>98\%$ and
purity $>99\%$ for galaxies with $19 < i_{AB} < 22.5$. Additionally, it
includes per-object quality information, and accompanying maps of the footprint
coverage, masked regions, imaging depth, survey conditions, and astrophysical
foregrounds that are used to select the cosmology analysis samples. This paper
will be complemented by online resources.


  In his seminal work on Sidon sets, Pisier found an important characterization
of Sidonicity: A set is Sidon if and only if it is proportionally
quasi-independent. Later, it was shown that Sidon sets were proportionally
`special' Sidon in several other ways. Here, we prove that Sidon sets in
torsion-free groups are proportionally $n$-degree independent, a higher order
of independence than quasi-independence, and we use this to prove that Sidon
sets are proportionally Sidon with Sidon constants arbitrarily close to one,
the minimum possible value.


  We theoretically investigate the current-current correlation of the
two-dimensional (2D) parabolic Dirac system in hexogonal lattice. The
analytical expressions of the random phase approximation (RPA) susceptibility,
Ruderman-Kittel-Kasuya-Yosida (RKKY) Hamiltonian, and the diamagnetic orbital
susceptibility in noninteracting case base on the density-density or
current-current correlation function are derived and quantitatively analyzed.
In noninteracting case, the dynamical polarization with- in RPA and spin
transverse susceptibility as well as the RKKY interaction (when close to the
half-filling) are related to the the current-current response in the 2D
parabolic Dirac system. Both the case of anisotropic dispersion and isotropic
dispersion are discussed.


  Active learning agents typically employ a query selection algorithm which
solely considers the agent's learning objectives. However, this may be
insufficient in more realistic human domains. This work uses imitation learning
to enable an agent in a constrained environment to concurrently reason about
both its internal learning goals and environmental constraints externally
imposed, all within its objective function. Experiments are conducted on a
concept learning task to test generalization of the proposed algorithm to
different environmental conditions and analyze how time and resource
constraints impact efficacy of solving the learning problem. Our findings show
the environmentally-aware learning agent is able to statistically outperform
all other active learners explored under most of the constrained conditions. A
key implication is adaptation for active learning agents to more realistic
human environments, where constraints are often externally imposed on the
learner.


  Interpretability is an elusive but highly sought-after characteristic of
modern machine learning methods. Recent work has focused on interpretability
via $\textit{explanations}$, which justify individual model predictions. In
this work, we take a step towards reconciling machine explanations with those
that humans produce and prefer by taking inspiration from the study of
explanation in philosophy, cognitive science, and the social sciences. We
identify key aspects in which these human explanations differ from current
machine explanations, distill them into a list of desiderata, and formalize
them into a framework via the notion of $\textit{weight of evidence}$ from
information theory. Finally, we instantiate this framework in two simple
applications and show it produces intuitive and comprehensible explanations.


  Time dependence for barrier penetration is considered in the phase space. An
asymptotic phase-space propagator for nonrelativistic scattering on a one -
dimensional barrier is constructed. The propagator has a form universal for
various initial state preparations and local potential barriers. It is
manifestly causal and includes time-lag effects and quantum spreading. Specific
features of quantum dynamics which disappear in the standard semi-classical
approximation are revealed. The propagator may be applied to calculation of the
final momentum and coordinate distributions, for particles transmitted through
or reflected from the potential barrier, as well as for elucidating the
tunneling time problem.


  An interaction between the vacuum energy and dark matter is an intriguing
possibility which may offer a way of solving the cosmological constant problem.
Adopting a general prescription for momentum exchange between the two dark
components, we reconstruct $\alpha(a)$, the temporal evolution of the coupling
strength between dark matter and vacuum energy, in a nonparametric Bayesian
approach using combined observational data sets from the cosmic microwave
background, supernovae and large scale structure. An evolving interaction
between the vacuum energy and dark matter removes some of the tensions between
different data sets. However, it is not preferred over $\Lambda$CDM in the
Bayesian sense, as improvement in the fit is not sufficient to compensate for
the increase in the volume of the parameter space.


  It is known that circularly symmetric Gaussian signals are the optimal input
signals for the partial decode-and-forward (PDF) coding scheme in the Gaussian
multiple-input multiple-output (MIMO) relay channel, but there is currently no
method to find the optimal covariance matrices nor to compute the optimal
achievable PDF rate since the optimization is a non-convex problem in its
original formulation. In this paper, we show that it is possible to find a
convex reformulation of the problem by means of an approximation and a primal
decomposition. We derive an explicit solution for the inner problems as well as
an explicit gradient for the outer problem, so that the efficient cutting-plane
method can be applied for solving the outer problem. As the accuracy of this
provably convergent algorithm might be impaired by the previous approximation,
we additionally propose a modified algorithm, for which we cannot give a
converge guarantee, but which provides rigorous upper and lower bounds to the
optimum of the original rate maximization. In numerical simulations, these
bounds become tight in all considered instances of the problem, showing that
the proposed method manages to find the global optimum in all these instances.


  I defend an analog of probabilism that characterizes rationally coherent
estimates for chances. Specifically, I demonstrate the following
accuracy-dominance result for stochastic theories in the C*-algebraic
framework: supposing an assignment of chance values is possible if and only if
it is given by a pure state on a given algebra, your estimates for chances
avoid accuracy-dominance if and only if they are given by a state on that
algebra. When your estimates avoid accuracy-dominance (roughly: when you cannot
guarantee that other estimates would be more accurate), I say that they are
sufficiently coherent. In formal epistemology and quantum foundations, the
notion of rational coherence that gets more attention requires that you never
allow for a sure loss (or 'Dutch book') in a given sort of betting game; I call
this notion full coherence. I characterize when these two notions of rational
coherence align, and I show that there is a quantum state giving estimates that
are sufficiently coherent, but not fully coherent.


  We discuss the epistemological features of the Ghirardi, Rimini and Weber
proposal to modify quantum mechanics in order to overcome the objectification
problem, that means the transition between the quantum and the classical level
of description of natural phenomena. We shall show that the GRW is a realistic
theory, but in a way quite different from Einstein realism or other kinds of
realism proposed in the past, such as the Many World Interpretation or the
Bohmian Mechanics.


  The $T\bar{T}$ deformation of a supersymmetric two-dimensional theory
preserves the original supersymmetry. Moreover, in several interesting cases
the deformed theory possesses additional non-linearly realized supersymmetries.
We show this for certain $\mathcal N =(2,2)$ models in two dimensions, where we
observe an intriguing similarity with known $\mathcal N=1 $ models in four
dimensions. This suggests that higher-dimensional models with non-linearly
realized supersymmetries might also be obtained from $T\bar{T}$-like flow
equations. We show that in four dimensions this is indeed the case for
$\mathcal N=1 $ Born-Infeld theory, as well as for the Goldstino action for
spontaneously broken $\mathcal N=1 $ supersymmetry.


  We study the quantum coherent-tunneling between two Bose-Einstein condensates
separated through an oscillating trap potential. The cases of slowly and
rapidly varying in time trap potential are considered. In the case of a slowly
varying trap we study the nonlinear resonances and chaos in the oscillations of
the relative atomic population. Using the Melnikov function approach, we find
the conditions for chaotic macroscopic quantum-tunneling phenomena to exists.
Criteria for the onset of chaos are also given. We find the values of frequency
and modulation amplitude which lead to chaos on oscillations in the relative
population, for any given damping and the nonlinear atomic interaction. In the
case of a rapidly varying trap we use the multiscale expansion method in the
parameter epsilon = 1/Omega, where Omega is the frequency of modulations and we
derive the averaged system of equations for the modes. The analysis of this
system shows that new macroscopic quantum self trapping regions, in comparison
with the constant trap case, exist.


  The task of {\em data fusion} is to identify the true values of data items
(eg, the true date of birth for {\em Tom Cruise}) among multiple observed
values drawn from different sources (eg, Web sites) of varying (and unknown)
reliability. A recent survey\cite{LDL+12} has provided a detailed comparison of
various fusion methods on Deep Web data. In this paper, we study the
applicability and limitations of different fusion techniques on a more
challenging problem: {\em knowledge fusion}. Knowledge fusion identifies true
subject-predicate-object triples extracted by multiple information extractors
from multiple information sources. These extractors perform the tasks of entity
linkage and schema alignment, thus introducing an additional source of noise
that is quite different from that traditionally considered in the data fusion
literature, which only focuses on factual errors in the original sources. We
adapt state-of-the-art data fusion techniques and apply them to a knowledge
base with 1.6B unique knowledge triples extracted by 12 extractors from over 1B
Web pages, which is three orders of magnitude larger than the data sets used in
previous data fusion papers. We show great promise of the data fusion
approaches in solving the knowledge fusion problem, and suggest interesting
research directions through a detailed error analysis of the methods.


  We study the problem of nonepisodic reinforcement learning (RL) for nonlinear
dynamical systems, where the system dynamics are unknown and the RL agent has
to learn from a single trajectory, i.e., without resets. We propose Nonepisodic
Optimistic RL (NeoRL), an approach based on the principle of optimism in the
face of uncertainty. NeoRL uses well-calibrated probabilistic models and plans
optimistically w.r.t. the epistemic uncertainty about the unknown dynamics.
Under continuity and bounded energy assumptions on the system, we provide a
first-of-its-kind regret bound of $\setO(\beta_T \sqrt{T \Gamma_T})$ for
general nonlinear systems with Gaussian process dynamics. We compare NeoRL to
other baselines on several deep RL environments and empirically demonstrate
that NeoRL achieves the optimal average cost while incurring the least regret.


  We consider asymptotically exact inference on the leading canonical
correlation directions and strengths between two high dimensional vectors under
sparsity restrictions. In this regard, our main contribution is the development
of a loss function, based on which, one can operationalize a one-step
bias-correction on reasonable initial estimators. Our analytic results in this
regard are adaptive over suitable structural restrictions of the high
dimensional nuisance parameters, which, in this set-up, correspond to the
covariance matrices of the variables of interest. We further supplement the
theoretical guarantees behind our procedures with extensive numerical studies.


  Classification and localization are two pillars of visual object detectors.
However, in CNN-based detectors, these two modules are usually optimized under
a fixed set of candidate (or anchor) bounding boxes. This configuration
significantly limits the possibility to jointly optimize classification and
localization. In this paper, we propose a Multiple Instance Learning (MIL)
approach that selects anchors and jointly optimizes the two modules of a
CNN-based object detector. Our approach, referred to as Multiple Anchor
Learning (MAL), constructs anchor bags and selects the most representative
anchors from each bag. Such an iterative selection process is potentially
NP-hard to optimize. To address this issue, we solve MAL by repetitively
depressing the confidence of selected anchors by perturbing their corresponding
features. In an adversarial selection-depression manner, MAL not only pursues
optimal solutions but also fully leverages multiple anchors/features to learn a
detection model. Experiments show that MAL improves the baseline RetinaNet with
significant margins on the commonly used MS-COCO object detection benchmark and
achieves new state-of-the-art detection performance compared with recent
methods.


  Ultracold atomic systems have emerged as strong contenders amongst the
various quantum systems relevant for developing and implementing quantum
technologies due to their enhanced control and flexibility of the operating
conditions. In this thesis, we explore persistent currents generated in a
ring-shaped quantum gas of strongly interacting \textit{N}-component fermions,
specifically the so-called SU(\textit{N}) fermions. Our results, apart from
being a relevant contribution to many-body physics, prove the `primum mobile'
for a new concept of matter-wave circuits based on SU(\textit{N}) fermionic
platforms, opening an exciting chapter in the field of atomtronics. Indeed, the
specific properties of quantization are expected to provide the core to
fabricate quantum devices with enhanced sensitivity like interferometers. At
the same time, SU(\textit{N}) fermionic circuits show promise in engineering
cold atoms quantum simulators with this artificial fermionic matter.


  This paper proposes a Federated Learning Code Smell Detection (FedCSD)
approach that allows organizations to collaboratively train federated ML models
while preserving their data privacy. These assertions have been supported by
three experiments that have significantly leveraged three manually validated
datasets aimed at detecting and examining different code smell scenarios. In
experiment 1, which was concerned with a centralized training experiment,
dataset two achieved the lowest accuracy (92.30%) with fewer smells, while
datasets one and three achieved the highest accuracy with a slight difference
(98.90% and 99.5%, respectively). This was followed by experiment 2, which was
concerned with cross-evaluation, where each ML model was trained using one
dataset, which was then evaluated over the other two datasets. Results from
this experiment show a significant drop in the model's accuracy (lowest
accuracy: 63.80\%) where fewer smells exist in the training dataset, which has
a noticeable reflection (technical debt) on the model's performance. Finally,
the last and third experiments evaluate our approach by splitting the dataset
into 10 companies. The ML model was trained on the company's site, then all
model-updated weights were transferred to the server. Ultimately, an accuracy
of 98.34% was achieved by the global model that has been trained using 10
companies for 100 training rounds. The results reveal a slight difference in
the global model's accuracy compared to the highest accuracy of the centralized
model, which can be ignored in favour of the global model's comprehensive
knowledge, lower training cost, preservation of data privacy, and avoidance of
the technical debt problem.


  Recently, Cheng et al. identified a number of massive white dwarfs (WD) that
appear to have an additional heat source providing a luminosity near $\approx
10^{-3}L_\odot$ for multiple Gyr. In this paper we explore heating from
electron capture and pycnonuclear reactions. We also explore heating from dark
matter annihilation. WD stars appear to be too small to capture enough dark
matter for this to be important. Finally, if dark matter condenses to very high
densities inside a WD this could ignite nuclear reactions. We calculate the
enhanced central density of a WD in the gravitational potential of a very dense
dark matter core. While this might start a supernova, it seems unlikely to
provide modest heating for a long time. We conclude that electron capture,
pycnonuclear, and dark matter reactions are unlikely to provide significant
heating in the massive WD that Cheng considers.


  A gas or vapor bubble collapsing in the vicinity of a rigid boundary
displaces towards the boundary and produces a high-speed jet directed at the
boundary. This behavior has been shown to be a function of the 'anisotropy' of
the collapse, measured by a dimensionless representation of the Kelvin impulse
known as the anisotropy parameter [Supponen et al., J. Fluid Mech. 802, 263-293
(2016)]. However, characterisation of the anisotropy parameter in different
geometries has been limited to simplified analytic solutions. In this work we
develop an inexpensive numerical model, based on the Boundary Element Method,
capable of predicting the anisotropy parameter for any rigid complex geometry.
We experimentally explore a robust measure of bubble displacement, showing that
the bubble displacement in a range of complex geometries behaves as a single
function of the predicted anisotropy parameter values.


  We investigate the atmospheric composition of the long period ($P_{\rm orb}=$
10 days), eccentric exo-Saturn WASP-117b. WASP-117b could be in atmospheric
temperature and chemistry similar to WASP-107b. In mass and radius WASP-117b is
similar to WASP-39b, which allows a comparative study of these planets.
  We analyze a near-infrared transmission spectrum of WASP-117b taken with
Hubble Space Telescope/WFC3 G141, which was reduced with two independent
pipelines. High resolution measurements were taken with VLT/ESPRESSO in the
optical. We report the robust ($3\sigma$) detection of a water spectral
feature. Using a 1D atmosphere model with isothermal temperature, uniform cloud
deck and equilibrium chemistry, the Bayesian evidence of a retrieval analysis
of the transmission spectrum indicates a preference for a high atmospheric
metallicity ${\rm [Fe/H]}=2.58^{+0.26}_{-0.37}$ and clear skies. The data are
also consistent with a lower-metallicity composition ${\rm [Fe/H]}<1.75$ and a
cloud deck between $10^{-2.2} - 10^{-5.1}$ bar, but with weaker Bayesian
preference. We retrieve a low CH$_4$ abundance of $<10^{-4}$ volume fraction
within $1 \sigma$ and $<2\cdot 10^{-1}$ volume fraction within $3 \sigma$. We
cannot constrain the equilibrium temperature between theoretically imposed
limits of 700 and 1000~K. Further observations are needed to confirm quenching
of CH$_4$ with $K_{zz}\geq 10^8$~cm$^2$/s. We report indications of Na and K in
the VLT/ESPRESSO high resolution spectrum with substantial Bayesian evidence in
combination with HST data.


  The cross sections of high energy neutron-induced spallation is useful for
studying the transmutation of long-life fission products. However, due to the
difficulty of obtaining high-energy neutrons, the experimental data are still
scarce. The present work studies the possibility to produce high energy
neutrons by interactions between deuteron beam and thick target. The Geant4
toolkit is applied to simulate the interaction between the deuteron beam and
thick target. An analytical method is also developed to calculate the neutron
yields emitted in the interaction between the deuteron beam and thick target.
The input cross section data is not only taken from the TEDNL-2017 library but
also calculated by the isospin-dependent quantum molecular dynamics model. It
is indicated that it is possible to produce high energy neutron by deuteron
beam interaction with matter. If one wants to get high energy neutrons, low-Z
matter, thin target, and small emission angle may be considered.


  We prove rigidity for the Lichnerowicz-type eigenvalue estimate for the Kohn
Laplacian on strictly pseudoconvex three-manifolds with nonnegative CR Paneitz
operator and positive Webster curvature.


  CCD photometry on the uvbyCaHbeta system is presented for the open cluster,
NGC 3680. Restricting the data to probable cluster members using the CMD and
the photometric indices alone defines a sample of 34 stars at the cluster
turnoff that imply E(b-y)=0.042(0.002) or E(B-V) = 0.058(0.003), where the
errors (s.e.m) refer to internal errors alone. With this reddening, [Fe/H] is
derived from both m1 and hk using both b-y and Hbeta as the temperature
indices. The agreement among the four approaches is excellent, leading to final
value of [Fe/H] = -0.14 (0.03) for the cluster and removing the apparent
discrepancy between the past uvby analyses and extensive results from the red
giants for which the cause has been traced to an apparent zero-point offset in
the original m1 indices. Using the homogenized and combined V, b-y data from a
variety of studies transformed to B-V, the cluster CMD is compared to NGC 752,
IC 4651, and the core-convective-overshoot isochrones of Girardi et al. (2002).
By interpolation to the proper metallicity, it is found that the E(B-V), (m-M),
and age for NGC 752, IC 4651, and NGC 3680 are (0.03, 8.30, 1.55 Gyr), (0.10,
10.20, 1.7 Gyr), and (0.06, 10.20, 1.85 Gyr), respectively. The revised age and
metallicity sequence and the color distribution of the giants provide evidence
for the suggestion that the giants defining the apparent clump in NGC 3680 are
predominantly first-ascent giants, as indicated by their Li abundance, while
the clump stars in NGC 752, 0.1 mag bluer in (B-V), are He-core-burning stars.
When combined with the color distribution in IC 4651, it is suggested that over
this modest age range where He-core flash becomes important, the distribution
of so-called clump stars switches from being dominated by He-core burning stars
to first-ascent giants in the bump phase.


  We present the principle and the main steps of a new method for the
visuo-spatial analysis of geometrical sketches recorded online. Visuo-spatial
analysis is a necessary step for multi-level analysis. Multi-level analysis
simultaneously allows classification, comparison or clustering of the
constituent parts of a pattern according to their visuo-spatial properties,
their procedural strategies, their structural or temporal parameters, or any
combination of two or more of those parameters. The first results provided by
this method concern the comparison of sketches to some perfect patterns of
simple geometrical figures and the measure of dissimilarity between real
sketches. The mean rates of good decision higher than 95% obtained are
promising in both cases.


  Let $(X,\mathcal{B},\mu)$ be a probability space and let $T_1,..., T_l$ be
$l$ commuting invertible measure preserving transformations \linebreak of $X$.
We show that if $T_1^{c_1} ... T_l^{c_l}$ is ergodic for each
$(c_1,...,c_l)\neq (0,...,0)$, then the averages
$\frac{1}{|\Phi_N|}\sum_{u\in\Phi_N}\prod_{i=1}^r T_1^{p_{i1}(u)}...
T_l^{p_{il}(u)}f_i$ converge in $L^2(\mu)$ for all polynomials $p_{ij}\colon
\mathbb{Z}^d\to\mathbb{Z}$, all $f_i\in L^{\infty}(\mu)$, and all F{\o}lner
sequences $\{\Phi_N\}_{N=1}^{\infty}$ in $\mathbb{Z}^d$.


  The critical role that Network Time Protocol (NTP) plays in the Internet led
to multiple efforts to secure it against time-shifting attacks. A recent
proposal for enhancing the security of NTP with Chronos against on-path
attackers seems the most promising one and is on a standardisation track of the
IETF. In this work we demonstrate off-path attacks against Chronos enhanced NTP
clients. The weak link is a central security feature of Chronos: The server
pool generation mechanism using DNS. We show that the insecurity of DNS allows
to subvert the security of Chronos making the time-shifting attacks against
Chronos-NTP even easier than attacks against plain NTP.


  We present a Dirac mass model based on $A_{4}$ modular symmetry within Type-I
seesaw framework. This extension of Standard Model requires three right-handed
neutrinos and three heavy Dirac fermions superfields, all singlet under
$SU(2)_{L}$ symmetry. The scalar sector is extended by the inclusion of a
$SU(2)_{L}$ singlet superfield, $\chi$. Here, the modular symmetry plays a
crucial role as the Yukawa couplings acquire modular forms, which are expressed
in terms of Dedekind eta function $\eta(\tau)$. Therefore, the Yukawa couplings
follow transformations akin to other matter fields, thereby obviating the
necessity of additional flavon fields. The acquisition of $vev$ by complex
modulus $\tau$ leads to the breaking of $A_{4}$ modular symmetry. We have
obtained predictions on neutrino oscillation parameters, for example, the model
favours ( \theta_{23} ) to be in the lower octant and normal hierarchy for
neutrino mass spectrum. Furthermore, we find that heavy Dirac fermions, in our
model, can decay to produce observed baryon asymmetry of the Universe through
Dirac leptogenesis.


  We use photometric observations of solar-type stars, made by the NASA Kepler
Mission, to conduct a statistical study of the impact of stellar surface
activity on the detectability of solar-like oscillations. We find that the
number of stars with detected oscillations fall significantly with increasing
levels of activity. The results present strong evidence for the impact of
magnetic activity on the properties of near-surface convection in the stars,
which appears to inhibit the amplitudes of the stochastically excited,
intrinsically damped solar-like oscillations.


  The performance of existing single-view 3D reconstruction methods heavily
relies on large-scale 3D annotations. However, such annotations are tedious and
expensive to collect. Semi-supervised learning serves as an alternative way to
mitigate the need for manual labels, but remains unexplored in 3D
reconstruction. Inspired by the recent success of semi-supervised image
classification tasks, we propose SSP3D, a semi-supervised framework for 3D
reconstruction. In particular, we introduce an attention-guided prototype shape
prior module for guiding realistic object reconstruction. We further introduce
a discriminator-guided module to incentivize better shape generation, as well
as a regularizer to tolerate noisy training samples. On the ShapeNet benchmark,
the proposed approach outperforms previous supervised methods by clear margins
under various labeling ratios, (i.e., 1%, 5% , 10% and 20%). Moreover, our
approach also performs well when transferring to real-world Pix3D datasets
under labeling ratios of 10%. We also demonstrate our method could transfer to
novel categories with few novel supervised data. Experiments on the popular
ShapeNet dataset show that our method outperforms the zero-shot baseline by
over 12% and we also perform rigorous ablations and analysis to validate our
approach.


  In alignment with the Paris Agreement, the city of Oxford in the UK aims to
become carbon neutral by 2040. Renewable energy help achieve this target by
reducing the reliance on carbon-intensive grid electricity. This research seeks
to optimally size solar photovoltaic and lithium battery storage systems,
reducing Oxford's grid electricity reliance in buildings. The analysis starts
with modeling the electricity demand. The model uses Elexon electricity
settlement profiles, and assembles them into the demand profile according to
the quantity and types of buildings in Oxford. Then, solar generation is
modeled using Pfenninger and Staffell's method. Solar photovoltaic and lithium
storage systems are sized using a hybridized analytical and iterative method.
First, the method calculates the solar system size search range, then iterates
through the range. At each solar size, the method calculates and iterates
through the storage system size search range. Within each iteration, the
renewable system is simulated using demand and generation data with a
simplified system set-up and the conventional operation strategy. The method
outputs combinations of solar system capacity, storage system capacity, and
grid electricity import. Each combination's levelized cost of electricity is
calculated, and the lowest cost combination is the optimal sizing. Solar and
storage system costs are projected from 2019 to 2100, and the optimal sizing is
calculated for each year. The result shows that solar photovoltaic is
economically competitive, but lithium storage cost is still too high. As solar
and storage prices continue to drop, they will take up greater portions of the
energy system. However, there will always be a need for the grid, as it
provides flexibility and can meet demands that are too costly for solar and
storage


  In this paper we studied the fermi arc and the fermi pocket in cuprates in a
short-range diagonal stripe phase with wave vectors $(7\pi/8, 7\pi/8)$, which
reproduce with a high accuracy the positions and sizes of the fermi arc and
fermi pocket and the superstructure in cuprates observed by Meng et
al\cite{Meng}. The low-energy spectral function indicates that the fermi pocket
results from the main band and the shadow band at the fermi energy. Above the
fermi energy the shadow band gradually departs away from the main band, leaving
a fermi arc. Thus we conclude that the fermi arc and fermi pocket can be fully
attributed to the stripe phase but has nothing to do with pairing.
Incorporating a d-wave pairing potential in the stripe phase the spectral
weight in the antinodal region is removed, leaving a clean fermi pocket in the
nodal region.


  We present here a three-dimesional hydrodynamical simulation for star
formation. Our aim is to explore the effect of the metal-line cooling on the
thermodynamics of the star-formation process. We explore the effect of changing
the metallicty of the gas from $Z/Z_{\odot}=10^{-4}$ to $Z/Z_{\odot}=10^{-2}$.
Furthermore, we explore the implications of using the observational abundance
pattern of a CEMP-no star, which have been considered to be the missing
second-generation stars, the so-called Pop. III.2 stars. In order to pursue our
aim, we modelled the microphysics by employing the public astrochemistry
package KROME, using a chemical network which includes sixteen chemical species
(H, H$^{+}$, H$^{-}$, He, He$^{+}$, He$^{++}$, e$^{-}$, H$_{2}$, H$_{2}^{+}$,
C, C$^{+}$, O, O$^{+}$, Si, Si$^{+}$, and Si$^{++}$). We couple KROME with the
fully three-dimensional Smoothed-particle hydrodynamics (SPH) code GRADSPH.
With this framework we investigate the collapse of a metal-enhanced cloud,
exploring the fragmentation process and the formation of stars. We found that
the metallicity has a clear impact on the thermodynamics of the collapse,
allowing the cloud to reach the CMB temperature floor for a metallicity
$Z/Z_{\odot}=10^{-2}$, which is in agreement with previous work. Moreover, we
found that adopting the abundance pattern given by the star SMSS
J031300.36-670839.3 the thermodynamics behavior is very similar to simulations
with a metallicity of $Z/Z_{\odot}=10^{-2}$, due to the high carbon abundance.
As long as only metal line cooling is considered, our results support the
metallicity threshold proposed by previous works, which will very likely
regulate the first episode of fragmentation and potentially determine the
masses of the resulting star clusters.


  We present numerical calculations of a four-point dynamic susceptibility,
chi_4(t), for the Kob-Andersen Lennard-Jones mixture as a function of
temperature T and density rho. Over a relevant range of T and rho, the full
t-dependence of chi_4(t) and thus the maximum in chi_4(t), which is
proportional to the dynamic correlation volume, are invariant for state points
for which the scaling variable rho^gamma/T is constant. The value of the
material constant gamma is the same as that which superposes the relaxation
time, tau, of the system versus rho^gamma/T. Thus, the dynamic correlation
volume is directly related to tau for any thermodynamic condition in the regime
where density scaling holds. Finally, we examine the conditions under which the
density scaling properties are related to the existence of strong correlations
between pressure and energy fluctuations.


  In this paper, we design a supervisor to prevent vehicle collisions at
intersections. An intersection is modeled as an area containing multiple
conflict points where vehicle paths cross in the future. At every time step,
the supervisor determines whether there will be more than one vehicle in the
vicinity of a conflict point at the same time. If there is, then an impending
collision is detected, and the supervisor overrides the drivers to avoid
collision. A major challenge in the design of a supervisor as opposed to an
autonomous vehicle controller is to verify whether future collisions will occur
based on the current drivers choices. This verification problem is particularly
hard due to the large number of vehicles often involved in intersection
collision, to the multitude of conflict points, and to the vehicles dynamics.
In order to solve the verification problem, we translate the problem to a
job-shop scheduling problem that yields equivalent answers. The job-shop
scheduling problem can, in turn, be transformed into a mixed-integer linear
program when the vehicle dynamics are first-order dynamics, and can thus be
solved by using a commercial solver.


  This paper focuses on the observations of sunspots made by Ru{\dj}er
Bo\v{s}kovi\'c in 1777. We derived the expressions needed to calculate the
elements of the Sun's rotation and period from observations. We used modern
ephemeris data in the processing of the observation results. Obtained results
are very similar to Bo\v{s}kovi\'c's original calculations. In addition to
historical significance, they also provide scientifically valuable data on the
Sun's differential rotation, which plays a significant role in generating and
maintaining solar magnetic activity.


  We study semigroups generated by two-dimensional relativistic Hamiltonians
with magnetic field. In particular, for compactly supported radial magnetic
field we show how the long time behaviour of the associated heat kernel depends
on the flux of the field. Similar questions are addressed for Aharonov-Bohm
type magnetic field.


  The decomposability of a Cartesian product of two nondecomposable manifolds
into products of lower dimensional manifolds is studied. For 3-manifolds we
obtain an analog of a result due to Borsuk for surfaces, and in higher
dimensions we show that similar analogs do not exist unless one imposes further
restrictions such as simple connectivity.


  Given a hypersurface $X\subset \mathbb{P}^{N+1}_{\mathbb{C}}$ Dimca gave a
proof showing that the cohomologies of X are the same as the projective space
in a range determined by the dimension of the singular locus of X. We prove the
analog of Dimca's result case when $\mathbb{C}$ is replaced with an
algebraically closed field of finite characteristic and singular cohomology is
replaced with $\ell$-adic \'etale cohomology. The Weil conjectures allow
relating results about \'eatle cohomology to counting problems over a finite
field. Thus by applying this result, we are able to get a relationship between
the algebraic properties of certain polynomials and the size of their zero set.


  We present a general scheme for the nonlinear gauge realizations of spacetime
groups on coset spaces of the groups considered. In order to show the relevance
of the method for the rigorous treatment of the translations in gravitational
gauge theories, we apply it in particular to the affine group. This is an
illustration of the family of spacetime symmetries having the form of a
semidirect product $H\semidirect T$, where $H$ is the stability subgroup and
$T$ are the translations . The translational component of the connection
behaves like a true tensor under $H$ when coset realizations are involved.


  Magnetic frustration in ferromagnetic metallic systems is unusual due to the
long-range and symmetric nature of the exchange interactions. In this work we
prove that it is possible to obtain a highly frustrated ferromagnetic phase in
a multi-sublattices cubic structure through a fine tuning of the magnetic
interactions. This peculiar state is achieved in Ni-Mn-(In, Sn) Heusler alloys
and results in the effective decoupling of their two intertwined ferromagnetic
sublattices. One sublattice is ferromagnetic long range ordered below the
macroscopic Curie temperature (TC ) whereas the second one remains disordered
until a crossover to a polarized state occurs at T << TC . This result points
out that a fine engineering of the magnetic interactions in metallic systems
can lead to interesting novel and emergent phenomena.


  The effects of oxygen adsorption on the reflectance anisotropy spectrum (RAS)
of reconstructed Si(100):O surfaces at sub-monolayer coverage (first stages of
oxidation) have been studied by an ab initio DFT-LDA scheme within a
plane-wave, norm-conserving pseudopotential approach. Dangling bonds and the
main features of the characteristic RAS of the clean Si(100) surface are mostly
preserved after oxidation of 50% of the surface dimers, with some visible
changes: a small red shift of the first peak, and the appearance of a distinct
spectral structure at about 1.5 eV. The electronic transitions involved in the
latter have been analyzed through state-by-state and layer-by-layer
decompositions of the RAS. We suggest that new interplay between present
theoretical results and reflectance anisotropy spectroscopy experiments could
lead to further clarification of structural and kinetic details of the Si(100)
oxidation process in the sub-monolayer range.


  I describe a simple method to calculate Earth dimensions using only local
measurements and observations. I used modern technology (a digital photo camera
and Google Earth) but the exact same method can be used without any aid, with
naked eye observations and distances measured by walking, and so it was
perfectly accessible to Ancient Greek science.


  We evaluate a range of recent LLMs on English creative writing, a challenging
and complex task that requires imagination, coherence, and style. We use a
difficult, open-ended scenario chosen to avoid training data reuse: an epic
narration of a single combat between Ignatius J. Reilly, the protagonist of the
Pulitzer Prize-winning novel A Confederacy of Dunces (1980), and a pterodactyl,
a prehistoric flying reptile. We ask several LLMs and humans to write such a
story and conduct a human evalution involving various criteria such as fluency,
coherence, originality, humor, and style. Our results show that some
state-of-the-art commercial LLMs match or slightly outperform our writers in
most dimensions; whereas open-source LLMs lag behind. Humans retain an edge in
creativity, while humor shows a binary divide between LLMs that can handle it
comparably to humans and those that fail at it. We discuss the implications and
limitations of our study and suggest directions for future research.


  The problem of estimating small transition probabilities for overdamped
Langevin dynamics is considered. A simplification of Girsanov's formula is
obtained in which the relationship between the infinitesimal generator of the
underlying diffusion and the change of probability measure corresponding to a
change in the potential energy is made explicit. From this formula an
asymptotic expression for transition probability densities is derived.
Separately the problem of estimating the probability that a small noise
Langevin process excapes a potential well is discussed.


  We report an experiment to generate maximally entangled states of
D-dimensional quantum systems, qudits, by using transverse spatial correlations
of two parametric down-converted photons. Apertures with D-slits in the arms of
the twin fotons define the qudit space. By manipulating the pump beam correctly
the twin photons will pass only by symmetrically opposite slits, generating
entangled states between these differents paths. Experimental results for
qudits with D=4 and D=8 are shown. We demonstrate that the generated states are
entangled states.


  We develop a Fokker-Planck theory of tissue growth with three types of cells
(symmetrically dividing, asymmetrically dividing and non-dividing) as main
agents to study the growth dynamics of human cerebral organoids. Fitting the
theory to lineage tracing data obtained in next generation sequencing
experiments, we show that the growth of cerebral organoids is a critical
process. We derive analytical expressions describing the time evolution of
clonal lineage sizes and show how power-law distributions arise in the limit of
long times due to the vanishing of a characteristic growth scale. We discuss
that the independence of critical growth on initial conditions could be
biologically advantageous.


  We consider the prediction of the Hamiltonian matrix, which finds use in
quantum chemistry and condensed matter physics. Efficiency and equivariance are
two important, but conflicting factors. In this work, we propose a
SE(3)-equivariant network, named QHNet, that achieves efficiency and
equivariance. Our key advance lies at the innovative design of QHNet
architecture, which not only obeys the underlying symmetries, but also enables
the reduction of number of tensor products by 92\%. In addition, QHNet prevents
the exponential growth of channel dimension when more atom types are involved.
We perform experiments on MD17 datasets, including four molecular systems.
Experimental results show that our QHNet can achieve comparable performance to
the state of the art methods at a significantly faster speed. Besides, our
QHNet consumes 50\% less memory due to its streamlined architecture. Our code
is publicly available as part of the AIRS library
(\url{https://github.com/divelab/AIRS}).


  Measuring the response of the intergalactic medium to a blast of ionizing
radiation allows one to infer the physical properties of the medium and, in
principle, the lifetime and isotropy of the radiating source. The most
sensitive such measurements can be made if the source of radiation is near the
line of sight to a bright background QSO. We present results based on deep
Keck/HIRES observations of the QSO triplet KP76, KP77 and KP78 at z ~2.5, with
separations of 2-3 arcmin on the plane of the sky. Using accurate systemic
redshifts of the QSOs from near-IR spectroscopy, we quantify the state of the
IGM gas in the proximity regions where the expected ionizing flux from the
foreground QSOs exceeds that of the metagalactic background by factors of
10-200, assuming constant and isotropic emission. Based on the unusual
ionization properties of the absorption systems with detected HI, CIV, and OVI,
we conclude that the gas has been significantly affected by the UV radiation
from the nearby QSOs. Aided by observations of the galaxy density near the
foreground QSOs, we discuss several effects that may explain why the transverse
proximity effect has eluded most previous attempts to detect it. Our
observations suggest that the luminosities of KP76 and KP77 have remained
comparable to current values over timescales of, respectively, Delta t > 25 Myr
and 16 Myr < Delta t < 33 Myr - consistent with typical QSO lifetimes estimated
from independent, less-direct methods. There is no evidence that the UV
radiation from either QSO was significantly anisotropic during these intervals.


  In this paper, the problem of robust reconfigurable intelligent surface (RIS)
system design under changes in data distributions is investigated. Using the
notion of invariant risk minimization (IRM), an invariant causal representation
across multiple environments is used such that the predictor is simultaneously
optimal for each environment. A neural network-based solution is adopted to
seek the predictor and its performance is validated via simulations against an
empirical risk minimization-based design. Results show that leveraging
invariance yields more robustness against unseen and out-of-distribution
testing environments.


  The algebra of invariants of d-tuples of n x n skew-symmetric matrices under
the action of the orthogonal group by simultaneous conjugation is considered
over an infinite field of characteristic different from two. For n=3 and d>0 a
minimal set of generators is established. A homogeneous system of parameters
(i.e., an algebraically independent set such that the algebra of invariants is
a finitely generated free module over subalgebra generated by this set) is
described for n=3 and d>0, for n=4 and d=2,3, for n=5 and d=2.


  Topological materials exhibit properties dictated by quantised invariants
that make them robust against perturbations. This topological protection is a
universal wave phenomenon that applies not only in the context of electrons in
solid-state materials but also to photonic systems, ultracold atoms, mechanical
systems, circuits, exciton-polaritons and beyond. However, the vast majority of
research in these systems has focused on the linear domain, i.e., where
inter-particle interactions do not play a role. Here, we experimentally observe
solitons -- waves that propagate without changing shape as a result of
nonlinearity -- in the bulk of a photonic Floquet topological insulator. These
solitons exhibit fundamentally different behaviour than solitons in ordinary
band gaps in that they execute cyclotron-like orbits that are associated with
the topology of the lattice. Specifically, we employ a laser-written waveguide
array with periodic variations along the waveguide axis that give rise to
non-zero Floquet winding number, where the nonlinearity arises from the optical
Kerr effect of the ambient glass. The effect described here is applicable to a
range of bosonic systems due to its description by the focusing nonlinear
Schr\"odinger equation, i.e., the Gross-Pitaevskii equation with attractive
interactions.


  In the present paper we study geodesic mappings of special pseudo-Riemannian
manifolds called $V_n(K)$-spaces. We prove that the set of solutions of the
system of equations of geodesic mappings on $V_n(K)$-spaces $(K\neq0)$ forms a
special Jordan algebra and the set of solutions generated by consircular fields
is an ideal of this algebra. We show that pseudo-Riemannian manifolds admitting
a concircular field of the basic type form the class of manifolds closed with
respect to the geodesic mappings.


  The notion of 'resource' plays an important role in the overall efficiency
and performance of most cross-docks. The processing time can often be described
in terms of the resources allocated to different trucks. Conversely, for a
given processing time, different combinations of resources can be prescribed.
We study the problem of truck scheduling and dock assignment in the presence of
resource constraints. In the absence of a closed-form (or well-defined) linear
formulation describing the processing times as a function of resources, expert'
knowledge has been mobilised to enable modelling of the problem as an integer
linear model. Two cases are taken into account: In the first one, the expert
believes in his/her estimation of the processing time for every truck and only
proposes a different combination of resources for his/her estimation, while in
the second one the expert proposes a limited number of resource deployment
scenarios for serving trucks, each of which has a different combination of
resources and different processing times. We propose a novel compact integer
programming formulation for the problem, which is particularly designed with an
embedded structure that can be exploited in dual decomposition techniques with
a remarkably computationally efficient column generation approach in this case.
The case in which a scenario with invariant processing time is considered and
modelled as a special case of the proposed model. Since a direct application of
commercial solvers such as CPLEX to solve instances of this problem is not
realistic, we propose a branch-and-price framework and, moreover, several
classes of valid inequalities. Our extensive computational experiments confirm
that the proposed exact solution framework is very efficient and viable in
solving real-size instances of the practice and in a reasonable amount of time.


  I give a general review of inflationary cosmology and of its present status,
in view of the 2013 data release by the Planck satellite. A specific emphasis
is given to the new broad class of theories, the cosmological attractors, which
have nearly model-independent predictions converging at the sweet spot of the
Planck data in the (n_s,r) plane. I also discuss the problem of initial
conditions for the theories favored by the Planck data.


  In the robot follow-ahead task, a mobile robot is tasked to maintain its
relative position in front of a moving human actor while keeping the actor in
sight. To accomplish this task, it is important that the robot understand the
full 3D pose of the human (since the head orientation can be different than the
torso) and predict future human poses so as to plan accordingly. This
prediction task is especially tricky in a complex environment with junctions
and multiple corridors. In this work, we address the problem of forecasting the
full 3D trajectory of a human in such environments. Our main insight is to show
that one can first predict the 2D trajectory and then estimate the full 3D
trajectory by conditioning the estimator on the predicted 2D trajectory. With
this approach, we achieve results comparable or better than the
state-of-the-art methods three times faster. As part of our contribution, we
present a new dataset where, in contrast to existing datasets, the human motion
is in a much larger area than a single room. We also present a complete robot
system that integrates our human pose forecasting network on the mobile robot
to enable real-time robot follow-ahead and present results from real-world
experiments in multiple buildings on campus. Our project page, including
supplementary material and videos, can be found at:
https://qingyuan-jiang.github.io/iros2024_poseForecasting/


  With the aim of constructing accurate 2D maps of the stellar mass
distribution in nearby galaxies from S4G 3.6 and 4.5 micron images, we report
on the separation of the light from old stars from the emission contributed by
contaminants (e.g. hot dust and the 3.3 micron PAH feature). Results for a
small sample of six disk galaxies (NGC 1566, NGC 2976, NGC 3031, NGC 3184, NGC
4321, and NGC 5194) with a range of morphological properties, dust contents and
star formation histories are presented to demonstrate our approach. We use an
Independent Component Analysis (ICA) technique designed to separate
statistically independent source distributions, maximizing the distinction in
the [3.6]-[4.5] colors of the sources. The technique also removes emission from
intermediate-age evolved red objects with a low mass-to-light ratio, such as
asymptotic giant branch (AGB) and red supergiant (RSG) stars, revealing maps of
the underlying old distribution of light with [3.6]-[4.5] colors consistent
with the colors of K and M giants. Contaminants are identified via comparison
to the non-stellar emission imaged at 8 microns, which is dominated by the
broad PAH feature. Using the measured 3.6/8 micron ratio to select the
individual contaminants, we find that hot dust and PAH together contribute
between ~5-15% to the integrated light at 3.6 microns, while light from regions
dominated by intermediate-age stars accounts for only 1-5%. Locally, however,
the contribution from either contaminant can reach much higher levels; dust
contributes on average 22% to the emission in star-forming regions throughout
the sample, while intermediate age-stars contribute upwards of 50% in localized
knots. The removal of these contaminants with ICA leaves maps of the old
stellar disk that retain a high degree of structural information and are
ideally suited for tracing the stellar mass, as will be the focus in a
companion paper.


  In this paper, the second of a series of two, we continue the study of higher
index theory for expanders. We prove that if a sequence of graphs has girth
tending to infinity, then the maximal coarse Baum-Connes assembly map is an
isomorphism for the associated metric space $X$. As discussed in the first
paper in this series, this has applications to the Baum-Connes conjecture for
`Gromov monster' groups.
  We also introduce a new property, `geometric property (T)'. For the metric
space associated to a sequence of graphs, this property is an obstruction to
the maximal coarse assembly map being an isomorphism. This enables us to
distinguish between expanders with girth tending to infinity, and, for example,
those constructed from property (T) groups.


  A linear equation $E$ is said to be sparse if there is $c>0$ so that every
subset of $[n]$ of size $n^{1-c}$ contains a solution of $E$ in distinct
integers. The problem of characterizing the sparse equations, first raised by
Ruzsa in the 90's, is one of the most important open problems in additive
combinatorics. We say that $E$ in $k$ variables is abundant if every subset of
$[n]$ of size $\varepsilon n$ contains at least poly$(\varepsilon)\cdot
n^{k-1}$ solutions of $E$. It is clear that every abundant $E$ is sparse, and
Gir\~{a}o, Hurley, Illingworth and Michel asked if the converse implication
also holds. In this note we show that this is the case for every $E$ in $4$
variables. We further discuss a generalization of this problem which applies to
all linear equations.


  This paper provides a brief look at dynamo scaling relationships for the
degree of equipartition between magnetic and kinetic energies. Two simple
models are examined, where one that assumes magnetostrophy and another that
includes the effects of inertia. These models are then compared to a suite of
convective dynamo simulations of the convective core of a main-sequence B-type
star and applied to its later evolutionary stages.


  We give a complete classification of the reductive symmetric pairs (G,H) for
which the homogeneous space $(G \times H)/diag(H)$ is real spherical in the
sense that a minimal parabolic subgroup has an open orbit.
  Combining with a criterion established in [T. Kobayashi--T. Oshima, Adv.
Math. 2013], we give a necessary and sufficient condition for a reductive
symmetric pair $(G,H)$ such that the multiplicities for the branching law of
the restriction any admissible smooth representation of $G$ to $H$ have
finiteness/boundedness property.


  When $G$ is a real reductive group and $G_0$ is its Cartan motion group, the
Mackey-Higson bijection is a natural one-to-one correspondence between all
irreducible tempered representations of $G$ and all irreducible unitary
representations of $G_0$. In this short note, we collect some known facts about
the topology of the tempered dual $\widetilde{G}$ and that of the unitary dual
$\widehat{G_0}$, then verify that the Mackey-Higson bijection $\widetilde{G}
\to \widehat{G_0}$ is continuous.


  Over-the-air computation (AirComp) is a promising technology that is capable
of achieving fast data aggregation in Internet of Things (IoT) networks. The
mean-squared error (MSE) performance of AirComp is bottlenecked by the
unfavorable channel conditions. This limitation can be mitigated by deploying a
reconfigurable intelligent surface (RIS), which reconfigures the propagation
environment to facilitate the receiving power equalization. The achievable
performance of RIS relies on the availability of accurate channel state
information (CSI), which however is generally difficult to be obtained. In this
paper, we consider an RIS-aided AirComp IoT network, where an access point (AP)
aggregates sensing data from distributed devices. Without assuming any prior
knowledge on the underlying channel distribution, we formulate a stochastic
optimization problem to maximize the probability that the MSE is below a
certain threshold. The formulated problem turns out to be non-convex and highly
intractable. To this end, we propose a data-driven approach to jointly optimize
the receive beamforming vector at the AP and the phase-shift vector at the RIS
based on historical channel realizations. After smoothing the objective
function by adopting the sigmoid function, we develop an alternating stochastic
variance reduced gradient (SVRG) algorithm with a fast convergence rate to
solve the problem. Simulation results demonstrate the effectiveness of the
proposed algorithm and the importance of deploying an RIS in reducing the MSE
outage probability.


  We develop tools from computational algebraic geometry for the study of
steady state features of autonomous polynomial dynamical systems via
elimination of variables. In particular, we obtain nontrivial bounds for the
steady state concentration of a given species in biochemical reaction networks
with mass-action kinetics. This species is understood as the output of the
network and we thus bound the maximal response of the system. The improved
bounds give smaller starting boxes to launch numerical methods. We apply our
results to the sequential enzymatic network studied in Markevich et al.(2004)
to find nontrivial upper bounds for the different substrate concentrations at
steady state.
  Our approach does not require any simulation, analytical expression to
describe the output in terms of the input, or the absence of multistationarity.
Instead, we show how to extract information from effectively computable
implicit dose-response curves with the use of resultants and discriminants. We
moreover illustrate in the application to an enzymatic network, the relation
between the exact implicit dose-response curve we obtain symbolically and the
standard hysteresis diagram provided by a numerical solver.
  The setting and tools we propose could yield many other results adapted to
any autonomous polynomial dynamical system, beyond those where it is possible
to get explicit expressions.


  Random Matrix Theory (RMT) is applied to analyze the weight matrices of Deep
Neural Networks (DNNs), including both production quality, pre-trained models
such as AlexNet and Inception, and smaller models trained from scratch, such as
LeNet5 and a miniature-AlexNet. Empirical and theoretical results clearly
indicate that the empirical spectral density (ESD) of DNN layer matrices
displays signatures of traditionally-regularized statistical models, even in
the absence of exogenously specifying traditional forms of regularization, such
as Dropout or Weight Norm constraints. Building on recent results in RMT, most
notably its extension to Universality classes of Heavy-Tailed matrices, we
develop a theory to identify \emph{5+1 Phases of Training}, corresponding to
increasing amounts of \emph{Implicit Self-Regularization}. For smaller and/or
older DNNs, this Implicit Self-Regularization is like traditional Tikhonov
regularization, in that there is a `size scale' separating signal from noise.
For state-of-the-art DNNs, however, we identify a novel form of
\emph{Heavy-Tailed Self-Regularization}, similar to the self-organization seen
in the statistical physics of disordered systems. This implicit
Self-Regularization can depend strongly on the many knobs of the training
process. By exploiting the generalization gap phenomena, we demonstrate that we
can cause a small model to exhibit all 5+1 phases of training simply by
changing the batch size.


  In this paper we study the Single Top and W boson associated photoproduction
via the main reaction $\rm pp\rightarrow p\gamma p\rightarrow pW^{\pm}t+Y$ at
the 14 TeV Large Hadron Collider (LHC) up to next-to-leading order (NLO) QCD
level assuming a typical LHC multipurpose forward detector. We use the
Five-Flavor-Number Schemes (5FNS) with massless bottom quark assumption in the
whole calculation. Our results show that the QCD NLO corrections can reduce the
scale uncertainty. The typical K-factors are in the range of 1.15 to 1.2 which
lead to the QCD NLO corrections of 15$%$ to 20$%$ correspond to the
leading-order (LO) predictions with our chosen parameters.


  This thesis presents a set of studies on atomic systems where quantum effects
are particularly relevant. These studies have been developed by applying a
variety of tools from many-body physics.
  First of all, we have studied the prospects for the existence of a superfluid
transition in an ultracold gas of fermionic atoms, by generalizing the BCS
theory of superconductivity to the case when the two species that pair have
different densities and the ground state may spontaneously break one or more
symmetries.
  In a second part, we have studied the dynamics of a Bose-Einstein condensate
whose spin degree of freedom is free to evolve inside a quasi-onedimensional
optical trap. We have used a mean-field formulation to address both the zero
temperature case and the finite temperature one.
  Finally, we have performed a careful study of the ground state and the line
tension of two-dimensional systems of helium-4. First, we have used Monte Carlo
techniques, then with a Density Functional built on-purpose.
  Comments are welcome!
  KEYWORDS: Cold gases, Pairing, Spinor condensate, Helium, Two dimensions


  The intricate interplay between colloidal particle shape and precisely
engineered interaction potentials has paved the way for the discovery of
unprecedented crystal structures in both two and three dimensions. Here, we
make use of anisotropic triblock colloidal particles composed of two distinct
materials. The resulting surface charge heterogeneity can be exploited to
generate regioselective depletion interactions and directional bonding. Using
extensive molecular dynamics simulations and a dimensionality reduction
analysis approach, we map out state diagrams for the self-assembly of such
colloids as a function of their aspect ratio and packing fraction for varying
depletant sizes in a quasi two-dimensional set-up. We observe the formation of
a wide variety of crystal structures such as a herringbone, brick-wall, tilted
brick-wall, and (tilted) ladder-like structures. More specifically, we
determine the optimal parameters to enhance crystallization, and investigate
the nucleation process. Additionally, we explore the potential of using crystal
monolayers as templates for deposition, thereby creating complex
three-dimensional structures that hold promise for future applications.


  The ability to learn from human supervision is fundamental for personal
assistants and other interactive applications of AI. Two central challenges for
deploying interactive learners in the wild are the unreliable nature of the
supervision and the varying complexity of the prediction task. We address a
simple but representative setting, incremental classification in the wild,
where the supervision is noisy and the number of classes grows over time. In
order to tackle this task, we propose a redesign of skeptical learning centered
around Gaussian Processes (GPs). Skeptical learning is a recent interactive
strategy in which, if the machine is sufficiently confident that an example is
mislabeled, it asks the annotator to reconsider her feedback. In many cases,
this is often enough to obtain clean supervision. Our redesign, dubbed ISGP,
leverages the uncertainty estimates supplied by GPs to better allocate labeling
and contradiction queries, especially in the presence of noise. Our experiments
on synthetic and real-world data show that, as a result, while the original
formulation of skeptical learning produces over-confident models that can fail
completely in the wild, ISGP works well at varying levels of noise and as new
classes are observed.


  In higher derivative theories, gravity can travel slower or faster than
light. With this feature in mind, we revisit the construction of the causal and
entanglement wedges in this type of theories, and argue that they must be
constructed using the fastest mode instead of null rays. We show that the
property of causal wedge inclusion, i.e., the fact that the causal wedge must
be contained in the entanglement wedge, leads to more stringent constraints on
the couplings than those imposed by hyperbolicity and boundary causality. Our
results imply that the full power of subregion-subregion duality could lead to
the same conclusions previously obtained based on high energy graviton
scattering. We illustrate our findings with a systematic analysis in
Gauss-Bonnet gravity.