  We develop reverse versions of hypercontractive inequalities for quantum
channels. By generalizing classical techniques, we prove a reverse
hypercontractive inequality for tensor products of qubit depolarizing channels.
We apply this to obtain a rapid mixing result for depolarizing noise applied to
large subspaces, and to prove bounds on a quantum generalization of
non-interactive correlation distillation.


  A complete calculation of the rare three-body decay t --> c h gamma is
presented in the framework of the standard model. In the unitary gauge, such a
calculation involves about 20 Feynman diagrams. We also calculate this decay in
the general two-Higgs doublet model (model III), in which it arises at the
tree-level. While in the standard model the decay t --> c h gamma is extremely
suppressed, with a branching fraction of the order of $10^{-15}$ for a Higgs
boson mass of the order of 115 GeV, in the model III it may have a branching
ratio up to $10^{-5}$. We also discuss the crossed decay h --> b \bar{s} gamma.


  One of the most difficult challenges in creating successful human-AI
collaborations is aligning a robot's behavior with a human user's expectations.
When this fails to occur, a robot may misinterpret their specified goals,
prompting it to perform actions with unanticipated, potentially dangerous side
effects. To avoid this, we propose a new metric we call Goal State Divergence
$\mathcal{(GSD)}$, which represents the difference between a robot's final goal
state and the one a human user expected. In cases where $\mathcal{GSD}$ cannot
be directly calculated, we show how it can be approximated using maximal and
minimal bounds. We then input the $\mathcal{GSD}$ value into our novel
human-robot goal alignment (HRGA) design problem, which identifies a minimal
set of environment modifications that can prevent mismatches like this. To show
the effectiveness of $\mathcal{GSD}$ for reducing differences between
human-robot goal states, we empirically evaluate our approach on several
standard benchmarks.


  The development of cancer is difficult to express on a simple and intuitive
level due to its complexity. Since cancer is so widespread, raising public
awareness about its mechanisms can help those affected cope with its realities,
as well as inspire others to make lifestyle adjustments and screen for the
disease. Unfortunately, studies have shown that cancer literature is too
technical for the general public to understand. We found that musification, the
process of turning data into music, remains an unexplored avenue for conveying
this information. We explore the pedagogical effectiveness of musification
through the use of an algorithm that manipulates a piece of music in a manner
analogous to the development of cancer. We conducted two lab studies and found
that our approach is marginally more effective at promoting cancer literacy
when accompanied by a text-based article than text-based articles alone.


  We present new developments in FeynArts 3.9 and FormCalc 8.4, in particular
the MSSMCT model file including the complete one-loop renormalization,
vectorization/parallelization issues, and the interface to the Ninja library
for tensor reduction.


  We show that light-pulse atom interferometry with atomic point sources and
spatially resolved detection enables multi-axis (two rotation, one
acceleration) precision inertial sensing at long interrogation times. Using
this method, we demonstrate a light-pulse atom interferometer for Rb-87 with
1.4 cm peak wavepacket separation and a duration of 2T = 2.3 seconds. The
inferred acceleration sensitivity of each shot is 6.7 * 10^(-12) g, which
improves on previous limits by more than two orders of magnitude. We also
measure the Earth's rotation rate with a precision of 200 nrad/s.


  We study the effect of surface temperature oscillations on diffusive
transport of solutes of weaklysoluble substances through liquid-saturated
porous media. Temperature wave induced by these oscillations and decaying deep
in the porous massif creates the solubility wave along with the corresponding
solute diffusion flux wave. When the non-dissolved fraction is immobilized in
pores---for gases the bubbles can be immobilized by the surface tension force,
for solids (e.g., limestone, gas-hydrates) the immobilization of non-dissolved
phase is obvious---the only remaining mechanisms of mass transport are related
to solute flux through liquid in pores. We evaluate analytically the generated
time-average mass flux for the case of medium everywhere littered with
non-dissolved phase and reveal the significant effect of the temperature wave
on the substance release from the massif and non-dissolved mass redistribution
within the massif. Analytical theory is validated with numerical calculations.


  We investigate the impact of fading correlation on the performance of the
doubly dirty fading multiple access channel (MAC) with non-causally known side
information at transmitters. Using Copula theory, we derive closed-form
expressions for the outage probability and the coverage region under arbitrary
dependence conditions. We show that a positive dependence structure between the
fading channel coefficients is beneficial for the system performance, as it
improves the outage probability and extends the coverage region compared to the
case of independent fading. Conversely, a negative dependence structure has a
detrimental effect on both performance metrics.


  The electromagnetic form factors of the nucleon are calculated in an extended
chiral constituent-quark model where the effective interaction is described by
the exchange of pseudoscalar, vector, and scalar mesons. Two-body
current-density operators, constructed consistently with the extended model
Hamiltonian in order to preserve gauge invariance and current conservation, are
found to give a significant contribution to the nucleon magnetic form factors
and improve the estimates of the nucleon magnetic moments.


  In this note, we study the Liouville equation $\Delta u = -e^u$ on a graph G
satisfying certain isoperimetric inequality. Following the idea of W. Ding, we
prove that there exists a uniform lower bound for the energy, $\Sigma_G e^u$ of
any solution $u$, to the equation. In particular, for the 2-dimensional lattice
graph $Z^2$; the lower bound is given by 4.


  UNi4B exhibits unusual properties and, in particular, a unique
antiferromagnetic arrangement involving only 2/3 of the U sites. Based on the
low temperature behavior of this compound, we propose that the remaining 1/3 U
sites are nonmagnetic due to the Kondo effect. We derive a model in which the
coexistence of magnetic and nonmagnetic U sites is the consequence of the
competition between frustration of the crystallographic structure and
instability of the 5f moments.


  We prove definitive results on the global stability of the flat space among
solutions of the Einstein-Klein-Gordon system. Our main theorems in this
monograph include: (1) A proof of global regularity (in wave coordinates) of
solutions of the Einstein-Klein-Gordon coupled system, in the case of small,
smooth, and localized perturbations of the stationary Minkowski solution; (2)
Precise asymptotics of the metric components and the Klein-Gordon field as the
time goes to infinity, including the construction of modified (nonlinear)
scattering profiles and quantitative bounds for convergence; (3) Classical
estimates on the solutions at null and timelike infinity, such as bounds on the
metric components, weak peeling estimates of the Riemann curvature tensor, ADM
and Bondi energy identities and estimates, and asymptotic description of null
and timelike geodesics.


  In this note we study chaos in generic quantum systems with a global symmetry
generalizing seminal work [arXiv : 1503.01409] by Maldacena, Shenker and
Stanford. We conjecture a bound on instantaneous chaos exponent in a
thermodynamic ensemble at temperature $T$ and chemical potential $\mu$ for the
continuous global symmetry under consideration. For local operators which could
create excitation up to some fixed charge, the bound on chaos (Lyapunov)
exponent is independent of chemical potential $\lambda_L \leq \frac{2 \pi T}{
\hbar} $. On the other hand when the operators could create excitation of
arbitrary high charge, we find that exponent must satisfy $\lambda_L \leq
\frac{2 \pi T}{(1-|\frac{\mu}{\mu_c}|) \hbar} $, where $\mu_c$ is the maximum
value of chemical potential for which the thermodynamic ensemble makes sense.
As specific examples of quantum mechanical systems we consider conformal field
theories. In a generic conformal field theory with internal $U(1)$ symmetry
living on a cylinder the former bound is applicable, whereas in more
interesting examples of holographic two dimensional conformal field theories
dual to Einstein gravity, we argue that later bound is saturated in presence of
a non-zero chemical potential for rotation.


  Large-scale systems with all-flash arrays have become increasingly common in
many computing segments. To make such systems resilient, we can adopt erasure
coding such as Reed-Solomon (RS) code as an alternative to replication because
erasure coding incurs a significantly lower storage overhead than replication.
To understand the impact of using erasure coding on the system performance and
other system aspects such as CPU utilization and network traffic, we build a
storage cluster that consists of approximately 100 processor cores with more
than 50 high-performance solid-state drives (SSDs), and evaluate the cluster
with a popular open-source distributed parallel file system, called Ceph.
Specifically, we analyze the behaviors of a system adopting erasure coding from
the following five viewpoints, and compare with those of another system using
replication: (1) storage system I/O performance; (2) computing and software
overheads; (3) I/O amplification; (4) network traffic among storage nodes, and
(5) impact of physical data layout on performance of RS-coded SSD arrays. For
all these analyses, we examine two representative RS configurations, used by
Google file systems, and compare them with triple replication employed by a
typical parallel file system as a default fault tolerance mechanism. Lastly, we
collect 96 block-level traces from the cluster and release them to the public
domain for the use of other researchers.


  We review recent developments (up to January 2004) of the Liouville field
theory and its matrix model dual. This review consists of three parts. In part
I, we review the bosonic Liouville theory. After briefly reviewing the
necessary background, we discuss the bulk structure constants (the DOZZ
formula) and the boundary states (the FZZT brane and the ZZ brane). Various
applications are also presented. In part II, we review the supersymmetric
extension of the Liouville theory. We first discuss the bulk structure
constants and the branes as in the bosonic Liouville theory, and then we
present the matrix dual descriptions with some applications. In part III, the
Liouville theory on unoriented surfaces is reviewed. After introducing the
crosscap state, we discuss the matrix model dual description and the tadpole
cancellation condition. This review also includes some original material such
as the derivation of the conjectured dual action for the N = 2 Liouville theory
from other known dualities and the comparison of the Liouville crosscap state
with the c = 0 unoriented matrix model. This is based on my master's thesis
submitted to Department of Physics, Faculty of Science, University of Tokyo on
January 2004.


  We present the Calar Alto Legacy Integral Field Area survey (CALIFA).
CALIFA's main aim is to obtain spatially resolved spectroscopic information for
~600 galaxies of all Hubble types in the Local Universe (0.005< z <0.03). The
survey has been designed to allow three key measurements to be made: (a)
Two-dimensional maps of stellar populations (star formation histories, chemical
elements); (b) The distribution of the excitation mechanism and element
abundances of the ionized gas; and (c) Kinematic properties (velocity fields,
velocity dispersion), both from emission and from absorption lines. To cover
the full optical extension of the target galaxies (i.e. out to a 3sigma depth
of ~23 mag/arcsec2), CALIFA uses the exceptionally large field of view of the
PPAK/PMAS IFU at the 3.5m telescope of the Calar Alto observatory. We use two
grating setups, one covering the wavelength range between 3700 and 5000 AA at a
spectral resolution R~1650, and the other covering 4300 to 7000 AA at R~850.
The survey was allocated 210 dark nights, distributed in 6 semesters and
starting in July 2010 and is carried out by the CALIFA collaboration,
comprising ~70 astronomers from 8 different countries. As a legacy survey, the
fully reduced data will be made publically available, once their quality has
been verified. We showcase here early results obtained from the data taken so
far (21 galaxies).


  Femtosecond lasers interacting with Kerr nonlinear optical materials,
propagate in form of filaments due to the balance of beam diffraction by
self-focusing induced by the Kerr nonlinearity. Femtosecond laser filamentation
is a universal phenomenon that belongs to a general class of processes proper
to ultrashort lasers processing systems, associated with the competition
between nonlinearity and dispersion also known to promote optical solitons. The
present work considers a model describing femtosecond laser inscriptions in a
transparent medium with Kerr nonlinearity. Upon inscription, the laser stores
energy in the optical material which induces an electron plasma. The model
consists of a cubic complex Ginzburg-Landau equation, in which an additional
K-order nonlinear term takes into account K-photon absorption processes. The
complex Ginzburg-Landau equation is coupled to a time first-order nonlinear
ordinary differential equation, accounting for time evolution of the plasma
density. The main objective of the study is to examine effects of the
competition between multi-photon absorptions, radiative recombination and
electron diffusion processes, on temporal profiles of the laser amplitude as
well as of the plasma density. From numerical simulations, it is found that
when the photon number (i.e. K) contributing to multiphoton ionization is large
enough, taking the electron diffusion processes into account favours periodic
structures in temporal profiles both of the laser and the plasma density. The
pulse repetition rate in the optical soliton train is increased with increase
of the electron diffusion coefficient, while the plasma density is a train of
multi-periodic anharmonic wave patterns.


  The \'{I}slendinga s\"{o}gur - or Sagas of Icelanders - constitute a
collection of medieval literature set in Iceland around the late 9th to early
11th centuries, the so-called Saga Age. They purport to describe events during
the period around the settlement of Iceland and the generations immediately
following and constitute an important element of world literature thanks to
their unique narrative style. Although their historicity is a matter of
scholarly debate, the narratives contain interwoven and overlapping plots
involving thousands of characters and interactions between them. Here we
perform a network analysis of the \'{I}slendinga s\"{o}gur in an attempt to
gather quantitative information on interrelationships between characters and to
compare saga society to other social networks.


  The vacuum fluctuations that induce the transitions and the thermalisation of
a uniformly accelerated two level atom are studied in detail. Their energy
content is revealed through the weak measurement formalism of Aharonov et al.
It is shown that each time the detector makes a transition it radiates a
Minkowski photon. The same analysis is then applied to the conversion of vacuum
fluctuations into real quanta in the context of black hole radiation. Initially
these fluctuations are located around the light like geodesic that shall
generate the horizon and carry zero total energy. However upon exiting from the
star they break up into two pieces one of which gradually acquires positive
energy and becomes a Hawking quantum, the other, its ''partner", ends up in the
singularity. As time goes by the vacuum fluctuations generating Hawking quanta
have exponentially large energy densities. This implies that back reaction
effects are large.


  Symbolic-inference methods have recently found a broad application in
materials science. In particular, the Sure-Independence Screening and
Sparsifying Operator (SISSO) performs symbolic regression and classification by
adopting compressed sensing for the selection of an optimized subset of
features and mathematical operators out of a given set of candidates. However,
SISSO becomes computationally unpractical when the set of candidate features
and operators exceeds the size of few tens. In the present work, we combine
SISSO with a genetic algorithm (GA) for the global search of the optimal subset
of features and operators. We demonstrate that GA-SISSO efficiently finds more
accurate predictive models than the original SISSO, due to the possibility to
access a larger input feature and operator space. GA-SISSO was applied for the
search of the model for the prediction of carbon-dioxide adsorption energies on
semiconductor oxides. The obtained with GA-SISSO model has much higher accuracy
compared to models previously discussed in the literature (based solely on the
O 2p-band center). The analysis of features importance shows that, besides the
O 2p-band center, the contribution of the electrostatic potential above
adsorption sites and the surface formation energies are also important.


  The results of mentioned physicochemical and biological analysis show that in
more polluted sampling points, the number of resistance benthos (Bivalves) are
more than other points of the study area. Heavy metal concentration in sediment
is between 10 to 1000 times more than water samples especially for Arsenic,
Mercury, and Vanadium. Dissolved Oxygen is acceptable all over the study area
(more than 4 mg/L) based on environmental quality standards for dissolved
oxygen which present the range of 2-9 mg/l for sensitive aquatic lives to less
sensitive ones. However the presence of chemicals causes increase in the value
of Chemical Oxygen Demand (around 500 to 1000 mg/L) and consequent decrease in
water purification ability Nutrient uptake capacity which shown as the ratio of
Nitrogen to phosphorus is appropriate (around 6) in parts of Musa estuary with
more than 3 meters depth . The study area is a semi-closed tide-dominant water
body with shallow depth, in comparison to the oceans. A 2-D modelling is
applied to simulate current speed and direction. The results of this modelling
shows except in the creeks, we have relatively suitable circulation of water in
the estuary and current speed may exceed 0.8 m/s. It means Musa estuary is not
a dead zone and in some parts which have enough water circulation and nutrient
uptake for aquatic life, but huge amount of heavy metal (especially Mercury) in
the sediment and water samples, indicates that all aquatic bodies overwhelmed
by dangerous heavy metals.


  Social events reflect the dynamics of society and, here, natural disasters
and emergencies receive significant attention. The timely detection of these
events can provide organisations and individuals with valuable information to
reduce or avoid losses. However, due to the complex heterogeneities of the
content and structure of social media, existing models can only learn limited
information; large amounts of semantic and structural information are ignored.
In addition, due to high labour costs, it is rare for social media datasets to
include high-quality labels, which also makes it challenging for models to
learn information from social media. In this study, we propose two hyperbolic
graph representation-based methods for detecting social events from
heterogeneous social media environments. For cases where a dataset has labels,
we designed a Hyperbolic Social Event Detection (HSED) model that converts
complex social information into a unified social message graph. This model
addresses the heterogeneity of social media, and, with this graph, the
information in social media can be used to capture structural information based
on the properties of hyperbolic space. For cases where the dataset is
unlabelled, we designed an Unsupervised Hyperbolic Social Event Detection
(UHSED). This model is based on the HSED model but includes graph contrastive
learning to make it work in unlabelled scenarios. Extensive experiments
demonstrate the superiority of the proposed approaches.


  Inclusive photoproduction of D*+- mesons has been measured for photon-proton
centre-of-mass energies in the range 130 < W < 280 GeV and a photon virtuality
Q^2 < 1 GeV^2. The data sample used corresponds to an integrated luminosity of
37 pb^-1. Total and differential cross sections as functions of the D*
transverse momentum and pseudorapidity are presented in restricted kinematical
regions and the data are compared with next-to-leading order (NLO) perturbative
QCD calculations using the "massive charm" and "massless charm" schemes. The
measured cross sections are generally above the NLO calculations, in particular
in the forward (proton) direction. The large data sample also allows the study
of dijet production associated with charm. A significant resolved as well as a
direct photon component contribute to the cross section. Leading order QCD
Monte Carlo calculations indicate that the resolved contribution arises from a
significant charm component in the photon. A massive charm NLO parton level
calculation yields lower cross sections compared to the measured results in a
kinematic region where the resolved photon contribution is significant.


  The primordial deuterium abundance is an important tracer of the fundamental
physics taking place during Big Bang Nucleosynthesis. It can be determined from
absorption features along the line of sight to distant quasars. The quasar
PKS1937-1009 contains two absorptions systems that have been used to measure
the primordial deuterium abundance, the lower redshift one being at z_abs =
3.256. New observations of this absorber are of a substantially higher
signal-to-noise and thus permit a significantly more robust estimate of the
primordial deuterium abundance, leading to a D/H ratio of 2.45+/-0.28 x10^-5.
Whilst the precision of the new measurement presented here is below that
obtained from the recent cosmological parameter measurements by Planck, our
analysis illustrates how a statistical sample obtained using similarly high
spectral signal-to-noise can make deuterium a competitive and complementary
cosmological parameter estimator and provide an explanation for the scatter
seen between some existing deuterium measurements.


  Beyond-Moore computing technologies are expected to provide a sustainable
alternative to the von Neumann approach not only due to their down-scaling
potential but also via exploiting device-level functional complexity at the
lowest possible energy consumption. The dynamics of the Mott transition in
correlated electron oxides, such as vanadium dioxide, has been identified as a
rich and reliable source of such functional complexity. However, its full
potential in high-speed and low-power operation has been largely unexplored. We
fabricated nanoscale VO$_{2}$ devices embedded in a broad-band test circuit to
study the speed and energy limitations of their resistive switching operation.
Our picosecond time-resolution, real-time resistive switching experiments and
numerical simulations demonstrate that tunable low-resistance states can be set
by the application of 20~ps long, $<$1.7~V amplitude voltage pulses at 15~ps
incubation times and switching energies starting from a few femtojoule.
Moreover, we demonstrate that at nanometer-scale device sizes not only the
electric field induced insulator-to-metal transition, but also the thermal
conduction limited metal-to-insulator transition can take place at timescales
of 100's of picoseconds. These orders of magnitude breakthroughs open the route
to the design of high-speed and low-power dynamical circuits for a plethora of
neuromorphic computing applications from pattern recognition to numerical
optimization.


  Di-Higgs couplings to fermions of the form $h^{2}\overline{f}f$ are absent in
the Standard Model, however, they are present in several physics Beyond
Standard Model (BSM) extensions, including those with vector-like fermions. In
Effective Field Theories (EFTs), such as the Standard Model Effective Field
Theory (SMEFT) and the Higgs Effective Field Theory (HEFT), these couplings
appear at dimension 6 and can in general, be flavour-violating (FV). In the
present work, we employ a bottom-up approach to investigate the FV in the
lepton and quarks sectors through the di-Higgs effective couplings. We assume
that all FV arises from this type of couplings and assume that the Yukawa
couplings $Y_{ij}$ are given by their SM values, i.e. $Y_{ij} =
\sqrt{2}m_{i}\delta_{ij}/v$. In the lepton sector, we set upper limits on the
Wilson coefficients $C_{ll'}$ from $l \rightarrow 3l'$ decays, $l \rightarrow
l\gamma$ decays, muonium oscillations, the $(g-2)_{\mu}$ anomaly, LEP searches,
muon conversion in nuclei, FV Higgs decays, and $Z$ decays. We also make
projections on some of these coefficients from Belle II, the Mu2e experiment
and the LHC's High Luminosity (HL) run. In the quark sector, we set upper
limits on the Wilson coefficients $C_{qq'}$ from meson oscillations and from
$B$-physics searches. A key takeaway from this study is that current and future
experiments should set out to measure the effective di-Higgs couplings
$C_{ff'}$, whether these couplings are FV or flavour-conserving. We also
present a matching between our formalism and the SMEFT operators and show the
bounds in both bases.


  Condensed planets contract or expand as their temperature changes. With the
exception of the effect of phase changes, this phenomenon is generally
interpreted as being solely related to the thermal expansivity of the planet's
components. However, changes in density affect pressure and gravity and,
consequently, the planet's compressibility. A planet's radius is also linked to
its rate of rotation. Here again, changes in pressure, gravity and
compressibility are coupled. In this article we clarify how the radius of a
condensed planet changes with temperature and rotation, using a simple and
rigorous thermodynamic model. We consider condensed materials to obey a simple
equation of state which generalizes a polytopic EoS as temperature varies.
Using this equation, we build simple models of condensed planet's interiors
including exoplanets, derive their mass-radius relationships, and study the
dependence of their radius with temperature and rotation rate. We show that it
depends crucially on the value of $\rho_s g R/K_s$ ($\rho_s$ being surface
density, $g$ gravity, $R$ radius, $K_s$ surface incompressibility). This
non-dimensional number is also the ratio of the dissipation number which
appears in compressible convection and the Grune\"isen mineralogic parameter.
While the radius of small planets depends on temperature, this is not the case
for large planets with large dissipation numbers; Earth and a super-Earth like
CoRoT-7b are in something of an intermediate state, with a moderately
temperature-dependent radius. Similarly, while the radius of these two planets
are functions of their rotation rates, this is not the case for smaller or
larger planets.


  Structural identifiability and observability are desirable properties of
systems biology models. Many software toolboxes have been developed for their
analysis in the last decades. STRIKE-GOLDD is a generally applicable tool that
can analyse non-linear, non-rational ODE models with unknown inputs. However,
this generality comes at the expense of a lower computational efficiency than
other tools. Here we present STRIKE-GOLDD 4.0, which includes a new algorithm,
ProbObsTest, specifically designed for the analysis of rational models.
ProbObsTest is significantly faster than the FISPO algorithm - which was
already available in older versions of the toolbox - when applied to
computationally expensive models. An important feature of both algorithms is
their ability to analyse models with unknown inputs. Thus, their coexistence in
the same toolbox provides a combination of general applicability and
computational efficiency. STRIKE-GOLDD 4.0 is implemented as a free and
open-source Matlab toolbox with a user-friendly graphical interface. It is
available under a GPLv3 license and it can be downloaded from GitHub at
https://github.com/afvillaverde/strike-goldd.


  We determine the statistics of work in isothermal volume changes of a
classical ideal gas consisting of a single particle. Combining our results with
the findings of Lua and Grosberg [J. Chem. Phys. B 109, 6805 (2005)] on
adiabatic expansions and compressions we then analyze the joint probability
distribution of heat and work for a microscopic, non-equilibrium Carnot cycle
and determine its efficiency at maximum power.


  We examine the question how string theory achieves a sum over bulk geometries
with fixed asymptotic boundary conditions. We discuss this problem with the
help of the tensionless string on $\mathcal{M}_3 \times \mathrm{S}^3 \times
\mathbb{T}^4$ (with one unit of NS-NS flux) that was recently understood to be
dual to the symmetric orbifold $\text{Sym}^N(\mathbb{T}^4)$. We strengthen the
analysis of arXiv:2008.07533 and show that the perturbative string partition
function around a fixed bulk background already includes a sum over
semi-classical geometries and large stringy corrections can be interpreted as
various semi-classical geometries. We argue in particular that the string
partition function on a Euclidean wormhole geometry factorizes completely into
factors associated to the two boundaries of spacetime. Central to this is the
remarkable property of the moduli space integral of string theory to localize
on covering spaces of the conformal boundary of $\mathcal{M}_3$. We also
emphasize the fact that string perturbation theory computes the grand canonical
partition function of the family of theories
$\bigoplus_N\text{Sym}^N(\mathbb{T}^4)$. The boundary partition function is
naturally expressed as a sum over winding worldsheets, each of which we
interpret as a `stringy geometry'. We argue that the semi-classical bulk
geometry can be understood as a condensate of such stringy geometries. We also
briefly discuss the effect of ensemble averaging over the Narain moduli space
of $\mathbb{T}^4$ and of deforming away from the orbifold by the marginal
deformation.


  The relevance of the pion mass, provenient from a term which explicitely
breaks chiral symmetry in the Lagrangian, for nucleon magnetic moment in the
frame of the Skyrmion model in two different versions: the usual Skyrme model
and a modified one which includes a coupling to a light scalar meson field, the
sigma $\sigma (\simeq 500-600$ MeV). The results are compared to other
calculations. Our main motivation comes from usual extrapolations for values of
low energy QCD observables obtained in lattices with large values of pion/quark
masses toward realistic value of $m_{\pi}$. which do not allow it. We do a
comparison with results from the Cloudy Bag Model and a chiral hadronic model
from chiral perturbation theory. There are several resulting extrapolations
from the region of large pion mass to the realistic value depending on the
considered model for low energy QCD.


  We apply the method of shortcuts to adiabaticity to nonequilibrium systems.
For unitary dynamics, the system Hamiltonian is separated into two parts. One
of them defines the adiabatic states for the state to follow and the
nonadiabatic transitions are prevented by the other part. This property is
implemented to the nonequilibrium entropy production and we find that the
entropy is separated into two parts. The separation represents the Pythagorean
theorem for the Kullback-Leibler divergence and an information-geometric
interpretation is obtained. We also study a lower bound of the entropy, which
is applied to derive a trade-off relation between time, entropy and state
distance.


  We put forward a strategy to encode a quantum operation into the unmodulated
dynamics of a quantum network without the need of external control pulses,
measurements or active feedback. Our optimization scheme, inspired by
supervised machine learning, consists in engineering the pairwise couplings
between the network qubits so that the target quantum operation is encoded in
the natural reduced dynamics of a network section. The efficacy of the proposed
scheme is demonstrated by the finding of uncontrolled four-qubit networks that
implement either the Toffoli gate, the Fredkin gate, or remote logic
operations. The proposed Toffoli gate is stable against imperfections, has a
high-fidelity for fault tolerant quantum computation, and is fast, being based
on the non-equilibrium dynamics.


  We calculate ground state energies in the Brueckner-Hartree-Fock theory for
$N$ electrons (with $N\le 20$) confined to a circular quantum dot and in
presence of a static magnetic field. Comparison with the predictions of
Hartree-Fock, local-spin-density and exact configuration-interaction theories
is made. We find that the correlations taken into account in
Brueckner-Hartree-Fock calculations give an important contribution to the
ground state energies, specially in strongly confined dots. In this
high-density range, corresponding in practice to self-assembled quantum dots,
the results of Brueckner-Hartree-Fock calculations are close to the exact
values and better than those obtained in the local-spin-density approximation.


  Graphene with high carrier mobility \mu\ is required both for graphene-based
electronic devices and for the investigation of the fundamental properties of
graphene's Dirac fermions. It is largely accepted that the mobility-limiting
factor in graphene is the Coulomb scattering off of charged impurities that
reside either on graphene or in the underlying substrate. This is true both for
traditional graphene devices on SiO2 substrates and possibly for the recently
reported high-mobility suspended and supported devices. An attractive approach
to reduce such scattering is to place graphene in an environment with high
static dielectric constant \kappa\ that would effectively screen the electric
field due to the impurities. However, experiments so far report only a modest
effect of high-\kappa\ environment on mobility. Here, we investigate the effect
of the dielectric environment of graphene by studying electrical transport in
multi-terminal graphene devices that are suspended in liquids with \kappa\
ranging from 1.9 to 33. For non-polar liquids (\kappa <5) we observe a rapid
increase of \mu\ with \kappa\ and report a record room-temperature mobility as
large as ~60,000 cm2/Vs for graphene devices in anisole (\kappa=4.3), while in
polar liquids (\kappa >18) we observe a drastic drop in mobility. We
demonstrate that non-polar liquids enhance mobility by screening charged
impurities adsorbed on graphene, while charged ions in polar liquids cause the
observed mobility suppression. Furthermore, using molecular dynamics simulation
we establish that scattering by out-of-plane flexural phonons, a dominant
scattering mechanism in suspended graphene in vacuum at room temperature, is
suppressed by the presence of liquids. We expect that our findings may provide
avenues to control and reduce carrier scattering in future graphene-based
electronic devices.


  The vector-like quarks are predicted in many new physics scenarios beyond the
Standard Model~(SM) and could be seen potential signatures of new physics at
the TeV energy scale. In this work, we study single production of exotic
singlet and doublet vectorlike bottom quarks (VLQ-$B$) at future Compact Linear
Collider~(CLIC) via the process $e^{+}e^{-}\to B\bar{b}$ with the decay channel
$B\to bZ$ and two types of modes: $Z\to \ell^{+}\ell^{-}$ and $Z\to
\nu\bar{\nu}$. We calculate the cross sections of signal and relevant SM
backgrounds. After a fast simulation of the signal and background events, the
exclusion limit at 95\% confidence level and $5\sigma$ discovery prospects on
the parameters (the coupling strength $\kappa_{B}$ and the VLQ-$B$ mass) have
been, respectively, presented at the future CLIC with centre of mass energy
$\sqrt{s}=3$ TeV and integrated luminosity of 5~ab$^{-1}$.


  Graph neural networks (GNNs) are designed for semi-supervised node
classification on graphs where only a subset of nodes have class labels.
However, under extreme cases when very few labels are available (e.g., 1
labeled node per class), GNNs suffer from severe performance degradation.
Specifically, we observe that existing GNNs suffer from unstable training
process on few-labeled graphs, resulting to inferior performance on node
classification. Therefore, we propose an effective framework, Stabilized
Self-Training (SST), which is applicable to existing GNNs to handle the
scarcity of labeled data, and consequently, boost classification accuracy. We
conduct thorough empirical and theoretical analysis to support our findings and
motivate the algorithmic designs in SST. We apply SST to two popular GNN models
GCN and DAGNN, to get SSTGCN and SSTDA methods respectively, and evaluate the
two methods against 10 competitors over 5 benchmarking datasets. Extensive
experiments show that the proposed SST framework is highly effective,
especially when few labeled data are available. Our methods achieve superior
performance under almost all settings over all datasets. For instance, on a
Cora dataset with only 1 labeled node per class, the accuracy of SSTGCN is
62.5%, 17.9% higher than GCN, and the accuracy of SSTDA is 66.4%, which
outperforms DAGNN by 6.6%.


  In this work we study rapidly rotating stars by considering the Rastall
theory of gravity. We obtain and solve the equations by numerical methods for
two usual parametrization of polytropic stars. Then the mass-radius relations,
moments of inertia and other results of interest are obtained and compared with
the ones for non-rotating stars.


  We use a generalization of the Rosenbluth separation method for a model
independent simultaneous extraction of the Compton Form Factors ${\cal H}$ and
${\cal E}$, from virtual Compton scattering data on an unpolarized target. A
precise evaluation of ${\cal H}$ and ${\cal E}$, enabled by the proposed
method, is the first step towards pinning down the the distribution of angular
momentum inside the proton.


  We analyze the complexity of learning directed acyclic graphical models from
observational data in general settings without specific distributional
assumptions. Our approach is information-theoretic and uses a local Markov
boundary search procedure in order to recursively construct ancestral sets in
the underlying graphical model. Perhaps surprisingly, we show that for certain
graph ensembles, a simple forward greedy search algorithm (i.e. without a
backward pruning phase) suffices to learn the Markov boundary of each node.
This substantially improves the sample complexity, which we show is at most
polynomial in the number of nodes. This is then applied to learn the entire
graph under a novel identifiability condition that generalizes existing
conditions from the literature. As a matter of independent interest, we
establish finite-sample guarantees for the problem of recovering Markov
boundaries from data. Moreover, we apply our results to the special case of
polytrees, for which the assumptions simplify, and provide explicit conditions
under which polytrees are identifiable and learnable in polynomial time. We
further illustrate the performance of the algorithm, which is easy to
implement, in a simulation study. Our approach is general, works for discrete
or continuous distributions without distributional assumptions, and as such
sheds light on the minimal assumptions required to efficiently learn the
structure of directed graphical models from data.


  Recent research in dynamic convolution shows substantial performance boost
for efficient CNNs, due to the adaptive aggregation of K static convolution
kernels. It has two limitations: (a) it increases the number of convolutional
weights by K-times, and (b) the joint optimization of dynamic attention and
static convolution kernels is challenging. In this paper, we revisit it from a
new perspective of matrix decomposition and reveal the key issue is that
dynamic convolution applies dynamic attention over channel groups after
projecting into a higher dimensional latent space. To address this issue, we
propose dynamic channel fusion to replace dynamic attention over channel
groups. Dynamic channel fusion not only enables significant dimension reduction
of the latent space, but also mitigates the joint optimization difficulty. As a
result, our method is easier to train and requires significantly fewer
parameters without sacrificing accuracy. Source code is at
https://github.com/liyunsheng13/dcd.


  This paper discusses several recent electronic-paper remote voting hybrid
schemes, concentrating more specifically on the proposal put forward for
Belgian elections. We point to some problems in the proposal, and consider
addition of blind signatures as one possible approach to dealing with the
identified shortcomings. We discuss the concomitant updates from both the
protocol and electoral processes point of view, arguing that our proposal would
strike a better balance between different requirements. To the best of our
knowledge, this is also the first proposal to use blind signatures in a
paper-based voting system.


  This work is concerned with thermal quantum states of Hamiltonians on spin
and fermionic lattice systems with short range interactions. We provide results
leading to a local definition of temperature, thereby extending the notion of
"intensivity of temperature" to interacting quantum models. More precisely, we
derive a perturbation formula for thermal states. The influence of the
perturbation is exactly given in terms of a generalized covariance. For this
covariance, we prove exponential clustering of correlations above a universal
critical temperature that upper bounds physical critical temperatures such as
the Curie temperature. As a corollary, we obtain that above the critical
temperature, thermal states are stable against distant Hamiltonian
perturbations. Moreover, our results imply that above the critical temperature,
local expectation values can be approximated efficiently in the error and the
system size.


  Waves can drastically transform a sea ice cover by inducing break-up over
vast distances in the course of a few hours. However, relatively few detailed
studies have described this phenomenon in a quantitative manner, and the
process of sea ice break-up by waves needs to be further parameterized and
verified before it can be reliably included in forecasting models. In the
present work, we discuss sea ice break-up parameterization and demonstrate the
existence of an observational threshold separating breaking and non-breaking
cases. This threshold is based on information from two recent field campaigns,
supplemented with existing observations of sea ice break-up. The data used
cover a wide range of scales, from laboratory-grown sea ice to polar field
observations. Remarkably, we show that both field and laboratory observations
tend to converge to a single quantitative threshold at which the wave-induced
sea ice break-up takes place, which opens a promising avenue for robust
parametrization in operational forecasting models.


  Special $\alpha$-limit sets ($s\alpha$-limit sets) combine together all
accumulation points of all backward orbit branches of a point $x$ under a
noninvertible map. The most important question about them is whether or not
they are closed. We challenge the notion of $s\alpha$-limit sets as backward
attractors for interval maps by showing that they need not be closed. This
disproves a conjecture by Kolyada, Misiurewicz, and Snoha. We give a criterion
in terms of Xiong's attracting center that completely characterizes which
interval maps have all $s\alpha$-limit sets closed, and we show that our
criterion is satisfied in the piecewise monotone case. We apply Blokh's models
of solenoidal and basic $\omega$-limit sets to solve four additional
conjectures by Kolyada, Misiurewicz, and Snoha relating topological properties
of $s\alpha$-limit sets to the dynamics within them. For example, we show that
the isolated points in a $s\alpha$-limit set of an interval map are always
periodic, the non-degenerate components are the union of one or two transitive
cycles of intervals, and the rest of the $s\alpha$-limit set is nowhere dense.
Moreover, we show that $s\alpha$-limit sets in the interval are always both
$F_\sigma$ and $G_\delta$. Finally, since $s\alpha$-limit sets need not be
closed, we propose a new notion of $\beta$-limit sets to serve as backward
attractors. The $\beta$-limit set of $x$ is the smallest closed set to which
all backward orbit branches of $x$ converge, and it coincides with the closure
of the $s\alpha$-limit set. At the end of the paper we suggest several new
problems about backward attractors.


  This paper presents the latest observations from the newly-built solar radio
spectrograph at the \emph{Chashan Solar Observatory}. On July 18 2016, the
spectrograph records a solar spike burst event, which has several episodes
showing harmonic structures, with the second, third, and fourth harmonics. The
lower harmonic radio spike emissions are observed later than the higher
harmonic bands, and the temporal delay of the second (third) harmonic relative
to the fourth harmonic is about 30\ --\ 40 (10) ms. Based on the electron
cyclotron maser emission mechanism, we analyze possible causes of the temporal
delay and further infer relevant coronal parameters, such as the magnetic field
strength and the electron density at the radio source.


  The variational iteration method is used to solve nonlinear Volterra integral
equations. Two approaches are presented distinguished by the method to compute
the Lagrange multiplier.


  Given an array of distinct integers $A[1\ldots n]$, the Range Minimum Query
(RMQ) problem requires us to construct a data structure from $A$, supporting
the RMQ query: given an interval $[a,b]\subseteq[1,n]$, return the index of the
minimum element in subarray $A[a\ldots b]$, i.e. return
$\text{argmin}_{i\in[a,b]}A[i]$. The fundamental problem has a long history.
The textbook solution which uses $O(n)$ words of space and $O(1)$ time by
Gabow, Bentley, Tarjan (STOC 1984) and Harel, Tarjan (SICOMP 1984) dates back
to 1980s. The state-of-the-art solution is presented by Fischer, Heun (SICOMP
2011) and Navarro, Sadakane (TALG 2014). The solution uses $2n-1.5\log
n+n/\left(\frac{\log n}{t}\right)^t+\tilde{O}(n^{3/4})$ bits of space and
$O(t)$ query time, where the additive $\tilde{O}(n^{3/4})$ is a pre-computed
lookup table used in the RAM model, assuming the word-size is $\Theta(\log n)$
bits. On the other hand, the only known lower bound is proved by Liu and Yu
(STOC 2020). They show that any data structure which solves RMQ in $t$ query
time must use $2n-1.5\log n+n/(\log n)^{O(t^2\log^2t)}$ bits of space, assuming
the word-size is $\Theta(\log n)$ bits.
  In this paper, we prove nearly tight lower bound for this problem. We show
that, for any data structure which solves RMQ in $t$ query time, $2n-1.5\log
n+n/(\log n)^{O(t\log^2t)}$ bits of space is necessary in the cell-probe model
with word-size $\Theta(\log n)$ bits. We emphasize that, in terms of time
complexity, our lower bound is tight up to a polylogarithmic factor.


  This paper considers secret-key generation between several agents and a base
station that observe independent and identically distributed realizations of
correlated random variables. Each agent wishes to generate the longest possible
individual key with the base station by means of public communication. All keys
must be jointly kept secret from all external entities. In this many-to-one
secret-key generation setting, it can be shown that the agents can take
advantage of a collective protocol to increase the sum-rate of their generated
keys. However, when each agent is only interested in maximizing its own
secret-key rate, agents may be unwilling to participate in a collective
protocol. Furthermore, when such a collective protocol is employed, how to
fairly allocate individual key rates arises as a valid issue. This paper
studies this tension between cooperation and self-interest with a
game-theoretic treatment. The work establishes that cooperation is in the best
interest of all individualistic agents and that there exists individual
secret-key rate allocations that incentivize the agents to follow the protocol.
Additionally, an explicit coding scheme that achieves such allocations is
proposed.


  If an experimentalist wants to decide which one of n possible Hamiltonians
acting on an n dimensional Hilbert space is present, he can conjugate the time
evolution by an appropriate sequence of known unitary transformations in such a
way that the different Hamiltonians result in mutual orthogonal final states.
We present a general scheme providing such a sequence.


  Three supernova remnants form the CTB 37 complex: CTB 37A (G348.5+0.1,
associated with the TeV $\gamma$-ray source HESS J1714-385), CTB 37B
(G348.7+0.3, associated with HESS J1713-381 and the magnetar CXOU
J171405.7.381031), and G348.5-0.0. We use 21 cm HI absorption measurements to
constrain the kinematic distances to these SNRs, which have not previously been
determined well. We revise the kinematic distance for CTB 37A to be in the
range 6.3 to 9.5 kpc (previously $\sim$11.3 kpc) because it is beyond the near
3-kpc arm and in front of the far side of the CO cloud at -145 km s$^{-1}$
towards $l$=348.5. G348.5-0.0 has a HI column density (N$_{HI}$
$\sim6.1\times10^{21}$ cm$^{-2}$) lower than CTB 37A ($\sim7.1\time10^{21}$
cm$^{-2}$). Also, G348.5-0.0 does not have the major absorption feature at -107
km s$^{-1}$ that CTB 37A shows. This is caused by the near 3-kpc arm, so
G348.5-0.0 is at a distance of $\le$ 6.3 kpc. CTB 37B is at a distance of
$\sim$13.2 kpc (previously 5 to 9 kpc) based on: 1) it has an absorption
feature at -10$\pm$5 km s$^{-1}$ from the far 3-kpc arm, so CTB 37B is behind
it; 2) there is absorption at -30 km s$^{-1}$ but not at -26 km s$^{-1}$, which
yields the distance value; 3) the HI column density towards CTB 37B
($\sim8.3\times10^{21}$ cm$^{-2}$) is larger than CTB 37A. In summary, CTB 37A,
CTB 37B and G348.5+0.0 are all at different distances and are only by chance
nearby each other on the sky. In addition, we conclude that CTB 37 A and B are
not associated with the historical Supernova AD 393.


  Network intrusion detection (NID) systems which leverage machine learning
have been shown to have strong performance in practice when used to detect
malicious network traffic. Decision trees in particular offer a strong balance
between performance and simplicity, but require users of NID systems to have
background knowledge in machine learning to interpret. In addition, they are
unable to provide additional outside information as to why certain features may
be important for classification.
  In this work, we explore the use of large language models (LLMs) to provide
explanations and additional background knowledge for decision tree NID systems.
Further, we introduce a new human evaluation framework for decision tree
explanations, which leverages automatically generated quiz questions that
measure human evaluators' understanding of decision tree inference. Finally, we
show LLM generated decision tree explanations correlate highly with human
ratings of readability, quality, and use of background knowledge while
simultaneously providing better understanding of decision boundaries.


  Two of the emerging trends in wireless cellular systems are Device-to-Device
(D2D) and Machine-to-Machine (M2M) communications. D2D enables efficient reuse
of the licensed spectrum to support localized transmissions, while M2M
connections are often characterized by fixed and low transmission rates. D2D
connections can be instrumental in localized aggregation of uplink M2M traffic
to a more capable cellular device, before being finally delivered to the Base
Station (BS). In this paper we show that a fixed M2M rate is an enabler of
efficient Machine-Type D2D underlay operation taking place simultaneously with
another \emph{downlink} cellular transmission. In the considered scenario, a BS
$B$ transmits to a user $U$, while there are $N_M$ Machine-Type Devices (MTDs)
attached to $U$, all sending simultaneously to $U$ and each using the same rate
$R_M$. While assuming that $B$ knows the channel $B-U$, but not the interfering
channels from the MTDs to $U$, we prove that there is a positive downlink rate
that can always be decoded by $U$, leading to zero-outage of the downlink
signal. This is a rather surprising consequence of the features of the multiple
access channel and the fixed rate $R_M$. We also consider the case of a
simpler, single-user decoder at $U$ with successive interference cancellation.
However, with single-user decoder, a positive zero-outage rate exists only when
$N_M=1$ and is zero when $N_M>1$. This implies that joint decoding is
instrumental in enabling fixed-rate underlay operation.


  We present an analysis of the light curve (LC) decline rates $(\Delta
m_{15})$ of 407 normal and peculiar supernovae (SNe) Ia and global parameters
of their host galaxies. As previously known, there is a significant correlation
between the $\Delta m_{15}$ of normal SNe Ia and global ages (morphologies,
colours, masses) of their hosts. On average, those normal SNe Ia that are in
galaxies from the Red Sequence (early-type, massive, old hosts) have faster
declining LCs in comparison with those from the Blue Cloud (late-type, less
massive, younger hosts) of the colour-mass diagram. The observed correlations
between the $\Delta m_{15}$ of normal SNe Ia and hosts' parameters appear to be
due to the superposition of at least two distinct populations of faster and
slower declining normal SNe Ia from older and younger stellar components. We
show, for the first time, that the $\Delta m_{15}$ of 91bg- and 91T-like SNe is
independent of host morphology and colour. The distribution of hosts on the
colour-mass diagram confirms the known tendency for 91bg-like SNe to occur in
globally red/old galaxies while 91T-like events prefer blue/younger hosts. On
average, the youngest global ages of 02cx-like SNe hosts and their positions in
the colour-mass diagram hint that these events likely originate from young
population, but they differ from 91T-like events in the LC decline rate.
Finally, we discuss the possible explosion channels and present our favoured SN
Ia models that have the potential to explain the observed SN-host relations.


  We use Anti-de Sitter quantum field theory to prove a new class of identities
between hypergeometric functions related to the K\"all\'en-Lehmann
representation of products of two Anti-de Sitter two-point functions. A rich
mathematical structure emerges. We apply our results to study the decay of
unstable Anti-de Sitter particles. The total amplitude is in this case finite
and Anti-de Sitter invariant.


  In this paper, we propose a novel deep Q-network (DQN)-based edge selection
algorithm designed specifically for real-time surveillance in unmanned aerial
vehicle (UAV) networks. The proposed algorithm is designed under the
consideration of delay, energy, and overflow as optimizations to ensure
real-time properties while striking a balance for other environment-related
parameters. The merit of the proposed algorithm is verified via
simulation-based performance evaluation.


  Let $\{V_{i,j}; (i,j)\in\N^2\}$ be a two-dimensional array of i.i.d.\ random
variables. The limit laws of the sum of independent random products $$
Z_n=\sum_{i=1}^{N_n} \prod_{j=1}^{n} e^{V_{i,j}} $$ as $n,N_n\to\infty$ have
been investigated by a number of authors. Depending on the growth rate of
$N_n$, the random variable $Z_n$ obeys a central limit theorem, or has limiting
$\alpha$-stable distribution. The latter result is true for non-lattice
$V_{i,j}$ only. Our aim is to study the lattice case. We prove that although
the (suitably normalized) sequence $Z_n$ fails to converge in distribution, it
is relatively compact in the weak topology, and describe its cluster set. This
set is a topological circle consisting of semi-stable distributions.


  Uniswap is a Constant Product Market Maker built around liquidity pools,
where pairs of tokens are exchanged subject to a fee that is proportional to
the size of transactions. At the time of writing, there exist more than 6,000
pools associated with Uniswap v3, implying that empirical investigations on the
full ecosystem can easily become computationally expensive. Thus, we propose a
systematic workflow to extract and analyse a meaningful but computationally
tractable sub-universe of liquidity pools. Leveraging on the 34 pools found
relevant for the six-months time window January-June 2022, we then investigate
the related liquidity consumption behaviour of market participants. We propose
to represent each liquidity taker by a suitably constructed transaction graph,
which is a fully connected network where nodes are the liquidity taker's
executed transactions, and edges contain weights encoding the time elapsed
between any two transactions. We extend the NLP-inspired graph2vec algorithm to
the weighted undirected setting, and employ it to obtain an embedding of the
set of graphs. This embedding allows us to extract seven clusters of liquidity
takers, with equivalent behavioural patters and interpretable trading
preferences. We conclude our work by testing for relationships between the
characteristic mechanisms of each pool, i.e. liquidity provision, consumption,
and price variation. We introduce a related ideal crypto law, inspired from the
ideal gas law of thermodynamics, and demonstrate that pools adhering to this
law are healthier trading venues in terms of sensitivity of liquidity and
agents' activity. Regulators and practitioners could benefit from our model by
developing related pool health monitoring tools.


  Self-supervised representation learning is heavily dependent on data
augmentations to specify the invariances encoded in representations. Previous
work has shown that applying diverse data augmentations is crucial to
downstream performance, but augmentation techniques remain under-explored. In
this work, we propose a new family of local transformations based on Gaussian
random fields to generate image augmentations for self-supervised
representation learning. These transformations generalize the well-established
affine and color transformations (translation, rotation, color jitter, etc.)
and greatly increase the space of augmentations by allowing transformation
parameter values to vary from pixel to pixel. The parameters are treated as
continuous functions of spatial coordinates, and modeled as independent
Gaussian random fields. Empirical results show the effectiveness of the new
transformations for self-supervised representation learning. Specifically, we
achieve a 1.7% top-1 accuracy improvement over baseline on ImageNet downstream
classification, and a 3.6% improvement on out-of-distribution iNaturalist
downstream classification. However, due to the flexibility of the new
transformations, learned representations are sensitive to hyperparameters.
While mild transformations improve representations, we observe that strong
transformations can degrade the structure of an image, indicating that
balancing the diversity and strength of augmentations is important for
improving generalization of learned representations.


  In this paper, a computationally efficient frequency-limited model reduction
algorithm is presented for large-scale interconnected power systems. The
algorithm generates a reduced order model which not only preserves the
electromechanical modes of the original power system but also satisfies a
subset of the first-order optimality conditions for H2;! model reduction
problem within the desired frequency interval. The reduced-order model
accurately captures the oscillatory behavior of the original power system and
provides a good time- and frequency-domain accuracy. The proposed algorithm
enables fast simulation, analysis, and damping controller design for the
original large-scale power system. The efficacy of the proposed algorithm is
validated on benchmark power system examples.


  Much has been written about the golden ratio $\phi=\frac{1+\sqrt{5}}{2}$ and
this strange number appears mysteriously in many mathematical calculations. In
this article, we review the appearance of this number in the graph theory. More
precisely, we review the relevance of this number in topics such as the number
of spanning trees, topological indices, energy, chromatic roots, domination
roots and the number of domatic partitions of graphs.


  We identify gauge freedoms in quantum error correction (QEC) codes and
introduce strategies for optimal control algorithms to find the gauges which
allow the easiest experimental realization. Hereby, the optimal gauge depends
on the underlying physical system and the available means to manipulate it. The
final goal is to obtain optimal decompositions of QEC codes into elementary
operations which can be realized with high experimental fidelities. In the
first part of this paper, this subject is studied in a general fashion, while
in the second part, a system of trapped ions is treated as a concrete example.
A detailed optimization algorithm is explained and various decompositions are
presented for the three qubit code, the five qubit code and the seven qubit
Steane code.


  In this paper, we study static and spherically symmetric black hole (BH)
solutions in the scalar-tensor theories with the coupling of the scalar field
to the Gauss-Bonnet (GB) term $\xi (\phi) R_{\rm GB}$, where $R_{\rm
GB}:=R^2-4R^{\alpha\beta}R_{\alpha\beta}+R^{\alpha\beta\mu\nu}R_{\alpha\beta\mu\nu}$
is the GB invariant and $\xi(\phi)$ is a function of the scalar field $\phi$.
Recently, it was shown that in these theories scalarized static and spherically
symmetric BH solutions which are different from the Schwarzschild solution and
possess the nontrivial profiles of the scalar field can be realized for certain
choices of the coupling functions and parameters. These scalarized BH solutions
are classified in terms of the number of nodes of the scalar field. It was then
pointed out that in the case of the pure quadratic order coupling to the GB
term, $\xi(\phi)=\eta \phi^2/8$, scalarized BH solutions with any number of
nodes are unstable against the radial perturbation. In order to see how a
higher order power of $\phi$ in the coupling function $\xi(\phi)$ affects the
properties of the scalarized BHs and their stability, we investigate scalarized
BH solutions in the presence of the quartic order term in the GB coupling
function, $\xi(\phi)=\eta \phi^2 (1+\alpha \phi^2)/8$. We clarify that the
existence of the higher order term in the coupling function can realize
scalarized BHs with zero nodes of the scalar field which are stable against the
radial perturbation.


  A key sticking point of Bayesian analysis is the choice of prior
distribution, and there is a vast literature on potential defaults including
uniform priors, Jeffreys' priors, reference priors, maximum entropy priors, and
weakly informative priors. These methods, however, often manifest a key
conceptual tension in prior modeling: a model encoding true prior information
should be chosen without reference to the model of the measurement process, but
almost all common prior modeling techniques are implicitly motivated by a
reference likelihood. In this paper we resolve this apparent paradox by placing
the choice of prior into the context of the entire Bayesian analysis, from
inference to prediction to model evaluation.


  Terahertz time-domain spectroscopy is employed to investigate
temperature-dependent properties of bulk chalcopyrite crystals (CdGeP$_2$,
ZnGeP$_2$ and CdSiP$_2$). The complex spectra provide the refraction and
absorption as a function of temperature, from which electron-phonon coupling
and average phonon energies are extracted and linked to the mechanics of the A-
and B-site cations. Also, AC conductivity spectra provide carrier densities and
electron scattering times, the temperature dependence of which is associated
with unintentional shallow dopants. Temperature dependence of the scattering
time is converted into carrier mobility and modeled with microscopic transport
mechanisms such as polar optical phonon, acoustic phonons, deformation
potential, ionized impurity and dislocation scattering. Hence, analysis links
the THz optical and electronic properties to relate microscopic carrier
transport and carrier-lattice interactions.


  The solar convection zone exhibits a strong level of differential rotation,
whereby the rotation period of the polar regions is about 25-30% longer than
the equatorial regions. The Coriolis force associated with these zonal flows
perpetually "pumps" the convection zone fluid, and maintains a quasi-steady
circulation, poleward near the surface. What is the influence of this
meridional circulation on the underlying radiative zone, and in particular,
does it provide a significant source of mixing between the two regions? In
Paper I, we began to study this question by assuming a fixed meridional flow
pattern in the convection zone and calculating its penetration depth into the
radiative zone. We found that the amount of mixing caused depends very
sensitively on the assumed flow structure near the radiative--convective
interface. We continue this study here by including a simple model for the
convection zone "pump", and calculating in a self-consistent manner the
meridional flows generated in the whole Sun. We find that the global
circulation timescale depends in a crucial way on two factors: the overall
stratification of the radiative zone as measured by the Rossby number times the
square root of the Prandtl number, and, for weakly stratified systems, the
presence or absence of stresses within the radiative zone capable of breaking
the Taylor-Proudman constraint. We conclude by discussing the consequences of
our findings for the solar interior and argue that a potentially important
mechanism for mixing in Main Sequence stars has so far been neglected.


  In the description of the relativistic two-body interaction, together with
the effects of energy and angular momentum losses due to the emission of
gravitational radiation, one has to take into account also the loss of linear
momentum, which is responsible for the recoil of the center-of-mass of the
system. We compute higher-order tail (i.e., tail-of-tail and tail-squared)
contributions to the linear momentum flux for a nonspinning binary system
either along hyperboliclike or ellipticlike orbits. The corresponding orbital
averages are evaluated at their leading post-Newtonian approximation, using
harmonic coordinates and working in the Fourier domain. The final expressions
are given in a large-eccentricity (or large-angular momentum) expansion along
hyperboliclike orbits and in a small-eccentricity expansion along ellipticlike
orbits. We thus complete a previous analysis focusing on both energy and
angular momentum losses [Phys. Rev. D \textbf{104}, no.10, 104020 (2021)],
providing brick-type results which will be useful, e.g., in the high-accurate
determination of the radiated impulses of the two bodies undergoing a
scattering process.


  This paper discusses some of the major experimental features of microwave
nonlinearity in high temperature superconductors, both intrinsic and extrinsic.
The case is made for solving the problem of extrinsic nonlinearity through the
use of localized measurements of microwave surface impedance and
electromagnetic fields. Along these lines, a brief introduction is given to our
work on scanning near-field microwave microscopy


  The simulation of large open water surface is challenging using a uniform
volumetric discretization of the Navier-Stokes equations. Simulating water
splashes near moving objects, which height field methods for water waves cannot
capture, necessitates high resolutions. Such simulations can be carried out
using the Fluid-Implicit-Particle (FLIP) method. However, the FLIP method is
not efficient for the long-lasting water waves that propagate to long
distances, which require sufficient depth for a correct dispersion
relationship. This paper presents a new method to tackle this dilemma through
an efficient hybridization of volumetric and surface-based advection-projection
discretizations. We design a hybrid time-stepping algorithm that combines a
FLIP domain and an adaptively remeshed Boundary Element Method (BEM) domain for
the incompressible Euler equations. The resulting framework captures the
detailed water splashes near moving objects with the FLIP method, and produces
convincing water waves with correct dispersion relationships at modest
additional costs.


  The one-loop induced magnetic dipole moments of a neutrino are examined in a
background of degenerate electrons in the standard model. For the
nonrelativistic neutrino, they are enhanced by a factor \( (8\pF/3\mnu) \),
where \pF\ is the electron Fermi momentum and \mnu\ the neutrino mass. For the
relativistic neutrino, they enhance the flavor-changing but helicity-conserving
process because of the absence of the GIM cancellation.


  A small fluctuation of the photon beam position will affect the
characteristics of the synchrotron radiation (SR) intensity and polarization
when it enters the end-station through the related beamline. In this paper, by
changing the electron orbit equilibrium position in the vertical direction, we
have measured the corresponding changes in the absorption strength of the SR
with a gold mesh in different chopper aperture positions. It is found that for
three aperture positions, the absorption intensity of the gold mesh shows a
good Gaussian distribution as the photon beam position moves, while the ratio
of the SR intensity passing through the upper and lower apertures shows a
monotonous variation. This suggests a new method for estimating the circular
polarization degree of SR originating from the bending magnet based on our
current measurement.


  Observation of gravitational waves from inspiralling binary black holes has
offered a unique opportunity to study the physical parameters of the component
black holes. To infer these parameters, Bayesian methods are employed in
conjunction with general relativistic waveform models that describe the
source's inspiral, merger, and ringdown. The results depend not only on the
accuracy of the waveform models but also on the underlying fiducial prior
distribution used for the analysis. In particular, when the pre-merger phase of
the signal is barely observable within the detectors' bandwidth, as is
currently the case with intermediate-mass black hole binary signals in
ground-based gravitational wave detectors, different prior assumptions can lead
to different interpretations. In this study, we utilise the gravitational-wave
inference library, $\texttt{Parallel Bilby}$, to evaluate the impact of mass
prior choices on the parameter estimation of intermediate-mass black hole
binary signals. While previous studies focused primarily on analysing event
data, we offer a broader, more controlled study by using simulations. Our
findings suggest that the posteriors in total mass, mass ratio and luminosity
distance are contingent on the assumed mass prior distribution used during the
inference process. This is especially true when the signal lacks sufficient
pre-merger information and/or has inadequate power in the higher-order
radiation multipoles. In conclusion, our study underscores the importance of
thoroughly investigating similarly heavy events in current detector sensitivity
using a diverse choice of priors. Absent such an approach, adopting a flat
prior on the binary's redshifted total mass and mass ratio emerges as a
reasonable choice, preventing biases in the detector-frame mass posteriors.


  Foundation models (FMs), including large language models, have become
increasingly popular due to their wide-ranging applicability and ability to
understand human-like semantics. While previous research has explored the use
of FMs in semantic communications to improve semantic extraction and
reconstruction, the impact of these models on different system levels,
considering computation and memory complexity, requires further analysis. This
study focuses on integrating FMs at the effectiveness, semantic, and physical
levels, using universal knowledge to profoundly transform system design.
Additionally, it examines the use of compact models to balance performance and
complexity, comparing three separate approaches that employ FMs. Ultimately,
the study highlights unresolved issues in the field that need addressing.


  We present a new method of matching observations of Type I (thermonuclear)
X-ray bursts with models, comparing the predictions of a semi-analytic ignition
model with X-ray observations of the accretion-powered millisecond pulsar SAX
J1808.4--3658 in outburst. We used a Bayesian analysis approach to marginalise
over the parameters of interest and determine parameters such as fuel
composition, distance/anisotropy factors, neutron star mass and neutron star
radius. Our study includes a treatment of the system inclination effects,
inferring that the rotation axis of the system is inclined
$\left(69^{+4}_{-2}\right)^\circ$ from the observers line of sight, assuming a
flat disc model. This method can be applied to any accreting source that
exhibits Type I X-ray bursts. We find a hydrogen mass fraction of
$0.57^{+0.13}_{-0.14}$ and CNO metallicity of $0.013^{+0.006}_{-0.004}$ for the
accreted fuel is required by the model to match the observed burst energies,
for a distance to the source of $3.3^{+0.3}_{-0.2}\,\mathrm{kpc}$. We infer a
neutron star mass of $1.5^{+0.6}_{-0.3}\,\mathrm{M}_{\odot}$ and radius of
$11.8^{+1.3}_{-0.9}\,\mathrm{km}$ for a surface gravity of
$1.9^{+0.7}_{-0.4}\times10^{14}\,\mathrm{cm}\,\mathrm{s}^{-2}$ for SAX
J1808.4--3658.


  This article introduces an experimental emulation of a novel chunk-based
flexible multi-DoF aerial 3D printing framework. The experimental demonstration
of the overall autonomy focuses on precise motion planning and task allocation
for a UAV, traversing through a series of planned space-filling paths involved
in the aerial 3D printing process without physically depositing the overlaying
material. The flexible multi-DoF aerial 3D printing is a newly developed
framework and has the potential to strategically distribute the envisioned 3D
model to be printed into small, manageable chunks suitable for distributed 3D
printing. Moreover, by harnessing the dexterous flexibility due to the 6 DoF
motion of UAV, the framework enables the provision of integrating the overall
autonomy stack, potentially opening up an entirely new frontier in additive
manufacturing. However, it's essential to note that the feasibility of this
pioneering concept is still in its very early stage of development, which yet
needs to be experimentally verified. Towards this direction, experimental
emulation serves as the crucial stepping stone, providing a pseudo mockup
scenario by virtual material deposition, helping to identify technological gaps
from simulation to reality. Experimental emulation results, supported by
critical analysis and discussion, lay the foundation for addressing the
technological and research challenges to significantly push the boundaries of
the state-of-the-art 3D printing mechanism.


  We propose a unified framework for coordinating Unmanned Aerial Vehicle (UAV)
swarms operating under time-varying communication networks. Our framework
builds on the concept of graphical games, which we argue provides a compelling
paradigm to subsume the interaction structures found in networked UAV swarms
thanks to the shared local neighborhood properties. We present a general-sum,
factorizable payoff function for cooperative UAV swarms based on the aggregated
local states and yield a Nash equilibrium for the stage games. Further, we
propose a decomposition-based approach to solve stage-graphical games in a
scalable and decentralized fashion by approximating virtual, mean
neighborhoods. Finally, we discuss extending the proposed framework toward
general-sum stochastic games by leveraging deep Q-learning and model-predictive
control.


  Ranking is a fundamental operation in information access systems, to filter
information and direct user attention towards items deemed most relevant to
them. Due to position bias, items of similar relevance may receive
significantly different exposure, raising fairness concerns for item providers
and motivating recent research into fair ranking. While the area has progressed
dramatically over recent years, no study to date has investigated the potential
problem posed by duplicated items. Duplicates and near-duplicates are common in
several domains, including marketplaces and document collections available to
search engines. In this work, we study the behaviour of different fair ranking
policies in the presence of duplicates, quantifying the extra-exposure gained
by redundant items. We find that fairness-aware ranking policies may conflict
with diversity, due to their potential to incentivize duplication more than
policies solely focused on relevance. This fact poses a problem for system
owners who, as a result of this incentive, may have to deal with increased
redundancy, which is at odds with user satisfaction. Finally, we argue that
this aspect represents a blind spot in the normative reasoning underlying
common fair ranking metrics, as rewarding providers who duplicate their items
with increased exposure seems unfair for the remaining providers.


  We consider the existence of non-synchronized fixed points to the Kuramoto
model defined on sparse networks: specifically, networks where each vertex has
degree exactly three. We show that "most" such networks support multiple
attracting phase-locked solutions that are not synchronized, and study the
depth and width of the basins of attraction of these phase-locked solutions. We
also show that it is common in "large enough" graphs to find phase-locked
solutions where one or more of the links has angle difference greater than
$\pi/2$.


  New lower bounds of the first nonzero eigenvalue of the weighted
$p$-Laplacian are established on compact smooth metric measure spaces with or
without boundaries. Under the assumption of positive lower bound for the
$m$-Bakry--\'{E}mery Ricci curvature, the Escober--Lichnerowicz--Reilly type
estimates are proved; under the assumption of nonnegative
$\infty$-Bakry--\'{E}mery Ricci curvature and the $m$-Bakry--\'{E}mery Ricci
curvature bounded from below by a non-positive constant, the Li--Yau type lower
bound estimates are given. The weighted $p$-Bochner formula and the weighted
$p$-Reilly formula are derived as the key tools for the establishment of the
above results.


  We present a systematical study of static D >= 4 space-times of high symmetry
with the matter source being a thin charged dust hypersurface shell. The shell
manifold is assumed to have the following structure S_(beta) X R^(D-2-beta),
beta (in the interval <0,...,D-2>) is dimension of a sphere S_(beta). In case
of (beta) = 0, we assume that there are two parallel hyper-plane shells instead
of only one. The space-time has Majumdar-Papapetrou form and it inherits the
symmetries of the shell manifold - it is invariant under both rotations of the
S_(beta) and translations along R^(D-2-beta). We find a general solution to the
Einstein-Maxwell equations with a given shell. Then, we examine some flat
interior solutions with special attention paid to D = 4. A connection to D = 4
non-relativistic theory is pointed out. We also comment on a straightforward
generalisation to the case of Kastor-Traschen space-time, i.e. adding a
non-negative cosmological constant to the charged dust matter source.


  This paper addresses the problem of speech separation and enhancement from
multichannel convolutive and noisy mixtures, \emph{assuming known mixing
filters}. We propose to perform the speech separation and enhancement task in
the short-time Fourier transform domain, using the convolutive transfer
function (CTF) approximation. Compared to time-domain filters, CTF has much
less taps, consequently it has less near-common zeros among channels and less
computational complexity. The work proposes three speech-source recovery
methods, namely: i) the multichannel inverse filtering method, i.e. the
multiple input/output inverse theorem (MINT), is exploited in the CTF domain,
and for the multi-source case, ii) a beamforming-like multichannel inverse
filtering method applying single source MINT and using power minimization,
which is suitable whenever the source CTFs are not all known, and iii) a
constrained Lasso method, where the sources are recovered by minimizing the
$\ell_1$-norm to impose their spectral sparsity, with the constraint that the
$\ell_2$-norm fitting cost, between the microphone signals and the mixing model
involving the unknown source signals, is less than a tolerance. The noise can
be reduced by setting a tolerance onto the noise power. Experiments under
various acoustic conditions are carried out to evaluate the three proposed
methods. The comparison between them as well as with the baseline methods is
presented.


  We obtain new Faber-Krahn-type inequalities for certain perturbations of the
Dirichlet Laplacian on a bounded domain. First, we establish a two- and
three-dimensional Faber-Krahn inequality for the Schr\"odinger operator with
point interaction: the optimiser is the ball with the point interaction
supported at its centre. Next, we establish three-dimensional Faber-Krahn
inequalities for one- and two-body Schr\"odinger operator with attractive
Coulomb interactions, the optimiser being given in terms of Coulomb attraction
at the centre of the ball. The proofs of such results are based on symmetric
decreasing rearrangement and Steiner rearrangement techniques; in the first
model a careful analysis of certain monotonicity properties of the lowest
eigenvalue is also needed.


  Electron-electron interactions in general lead to both ground state and
excited state confinement. We show, however, that in phenyl-substituted
polyacetylenes electron-electron interactions cause enhanced delocalization of
quasiparticles in the optically excited state from the backbone polyene chain
into the phenyl groups, which in turn leads to enhanced confinement in the
chain direction. This co-operative delocalization--confinement lowers the
energy of the one-photon state and raises the relative energy of the lowest
two-photon state. The two-photon state is slightly below the optical state in
mono-phenyl substituted polyacetylenes, but above the optical state in
di-phenyl substituted polyacetylenes, thereby explaining the strong
photoluminescence of the latter class of materials. We present a detailed
mechanism of the crossover in the energies of the one- and two-photon states in
these systems. In addition, we calculate the optical absorption spectra over a
wide wavelength region, and make specific predictions for the polarizations of
low and high energy transitions that can be tested on oriented samples. Within
existing theories of light emission from $\pi$-conjugated polymers, strong
photoluminescence should be restricted to materials whose optical gaps are
larger than that of trans-polyacetylene. The present work show that
conceptually at least, it is possible to have light emission from systems with
smaller optical gaps.


  Stellar winds and supernova (SN) explosions of massive stars ("stellar
feedback") create bubbles in the interstellar medium (ISM) and insert newly
produced heavy elements and kinetic energy into their surroundings, possibly
driving turbulence. Most of this energy is thermalized and immediately removed
from the ISM by radiative cooling. The rest is available for driving ISM
dynamics. In this work we estimate the amount of feedback energy retained as
kinetic energy when the bubble walls have decelerated to the sound speed of the
ambient medium. We show that the feedback of the most massive star outweighs
the feedback from less massive stars. For a giant molecular cloud (GMC) mass of
1e5 solar masses (as e.g. found in the Orion GMCs) and a star formation
efficiency of 8% the initial mass function predicts a most massive star of
approximately 60 solar masses. For this stellar evolution model we test the
dependence of the retained kinetic energy of the cold GMC gas on the inclusion
of stellar winds. In our model winds insert 2.34 times the energy of a SN and
create stellar wind bubbles serving as pressure reservoirs. We find that during
the pressure driven phases of the bubble evolution radiative losses peak near
the contact discontinuity (CD), and thus, the retained energy depends
critically on the scales of the mixing processes across the CD. Taking into
account the winds of massive stars increases the amount of kinetic energy
deposited in the cold ISM from 0.1% to a few percent of the feedback energy.


  Infra-red properties of the triangle anomaly and the ``anomaly pole'' are
elaborated and applied to the study of high-energy scattering in QCD, when the
gauge symmetry is partially broken to SU(2). It is shown that the chiral flavor
anomaly provides a wee-gluon component for Goldstone bosons that combines with
interactions due to the U(1) anomaly to produce an infra-red transverse
momentum scaling divergence in scattering amplitudes. After the divergence is
factorized out, as a wee-gluon condensate in the infinite momentum pion, the
remaining physical amplitudes have confinement and chiral symmetry breaking. A
lowest-order contribution to the pion scattering amplitude is calculated in
detail. Although originating from very complicated diagrams, the amplitude has
a remarkable (semi-)perturbative simplicity. The momentum structure is that of
single gluon exchange but zero momentum quarks inject additional spin and color
structure via anomaly interactions.


  Physics simulation results of natural processes usually do not fully capture
the real world. This is caused for instance by limits in what physical
processes are simulated and to what accuracy. In this work we propose and
analyze the use of an LSTM-based deep learning network machine learning (ML)
architecture for capturing and predicting the behavior of the systemic error
for storm surge forecast models with respect to real-world water height
observations from gauge stations during hurricane events. The overall goal of
this work is to predict the systemic error of the physics model and use it to
improve the accuracy of the simulation results post factum. We trained our
proposed ML model on a dataset of 61 historical storms in the coastal regions
of the U.S. and we tested its performance in bias correcting modeled water
level data predictions from hurricane Ian (2022). We show that our model can
consistently improve the forecasting accuracy for hurricane Ian -- unknown to
the ML model -- at all gauge station coordinates used for the initial data.
Moreover, by examining the impact of using different subsets of the initial
training dataset, containing a number of relatively similar or different
hurricanes in terms of hurricane track, we found that we can obtain similar
quality of bias correction by only using a subset of six hurricanes. This is an
important result that implies the possibility to apply a pre-trained ML model
to real-time hurricane forecasting results with the goal of bias correcting and
improving the produced simulation accuracy. The presented work is an important
first step in creating a bias correction system for real-time storm surge
forecasting applicable to the full simulation area. It also presents a highly
transferable and operationally applicable methodology for improving the
accuracy in a wide range of physics simulation scenarios beyond storm surge
forecasting.


  In this paper, we give constructions of strongly regular Cayley graphs and
skew Hadamard difference sets. Both constructions are based on choosing
cyclotomic classes in finite fields, and our results generalize ten of the
eleven sporadic examples of cyclotomic strongly regular graphs given by Schmidt
and White [24] and several of subfield examples into infinite families. These
infinite families of strongly regular graphs have new parameters. The main
tools that we employed are relative Gauss sums instead of explicit evaluations
of Gauss sums.


  Recent observations suggest that mass ejection and mass accretion both
decline significantly with time during early protostellar evolution (Bontemps
et al. 1996). In the present paper, we propose that this rapid decay of
accretion/ejection activity is a direct result of the non-singular density
profiles characterizing pre-collapse clouds. The radial density profiles of
pre-stellar cores are indeed found to be much flatter than rho(r) ~ r(-2) at
radii less than a few thousand AU (Ward-Thompson et al. 1994). Here we show,
through Lagrangian analytical calculations, that the supersonic gravitational
collapse of pre-stellar cloud cores with centrally peaked, but flattened
density profiles leads to a transitory phase of energetic accretion immediately
following the formation of the central hydrostatic protostar. Physically, the
flat inner region collapses first nearly homologously to form a finite mass
stellar nucleus, and the remaining cloud core material then accretes
supersonically onto a non-zero point mass. Enhanced accretion persists as long
as the gravitational pull of this initial point mass, which does not exist in
the Shu singular solution, remains significant. We suggest that this epoch of
vigorous accretion coincides with Class 0 protostars, which would explain their
unusually powerful jets compared to the more evolved Class I objects. We also
use a simple two-component power-law model to fit the diagrams of outflow power
versus envelope mass observed by Bontemps et al. (1996), and suggest that rho
Ophiuchi and Taurus young stellar objects follow different accretion histories
because of differing initial conditions.


  We have trained a named entity recognition (NER) model that screens Swedish
job ads for different kinds of useful information (e.g. skills required from a
job seeker). It was obtained by fine-tuning KB-BERT. The biggest challenge we
faced was the creation of a labelled dataset, which required manual annotation.
This paper gives an overview of the methods we employed to make the annotation
process more efficient and to ensure high quality data. We also report on the
performance of the resulting model.


  Graph cuts are among the most prominent tools for clustering and
classification analysis. While intensively studied from geometric and
algorithmic perspectives, graph cut-based statistical inference still remains
elusive to a certain extent. Distributional limits are fundamental in
understanding and designing such statistical procedures on randomly sampled
data. We provide explicit limiting distributions for balanced graph cuts in
general on a fixed but arbitrary discretization. In particular, we show that
Minimum Cut, Ratio Cut and Normalized Cut behave asymptotically as the minimum
of Gaussians as sample size increases. Interestingly, our results reveal a
dichotomy for Cheeger Cut: The limiting distribution of the optimal objective
value is the minimum of Gaussians only when the optimal partition yields two
sets of unequal volumes, while otherwise the limiting distribution is the
minimum of a random mixture of Gaussians. Further, we show the bootstrap
consistency for all types of graph cuts by utilizing the directional
differentiability of cut functionals. We validate these theoretical findings by
Monte Carlo experiments, and examine differences between the cuts and the
dependency on the underlying distribution. Additionally, we expand our
theoretical findings to the Xist algorithm, a computational surrogate of graph
cuts recently proposed in Suchan, Li and Munk (arXiv, 2023), thus demonstrating
the practical applicability of our findings e.g. in statistical tests.


  We investigate the phase diagram of the so-called
Polyakov--Nambu--Jona-Lasinio model at finite temperature and nonzero chemical
potential with three quark flavours. Chiral and deconfinement phase transitions
are discussed, and the relevant order-like parameters are analyzed. The results
are compared with simple thermodynamic expectations and lattice data. A special
attention is payed to the critical end point: as the strength of the
flavour-mixing interaction becomes weaker, the critical end point moves to low
temperatures and can even disappear.


  We import the algebro-geometric notion of a complete collineation into the
study of maximum likelihood estimation in directed Gaussian graphical models. A
complete collineation produces a perturbation of sample data, which we call a
stabilisation of the sample. While a maximum likelihood estimate (MLE) may not
exist or be unique given sample data, it is always unique given a
stabilisation. We relate the MLE given a stabilisation to the MLE given
original sample data, when one exists, providing necessary and sufficient
conditions for the MLE given a stabilisation to be one given the original
sample. For linear regression models, we show that the MLE given any
stabilisation is the minimal norm choice among the MLEs given an original
sample. We show that the MLE has a well-defined limit as the stabilisation of a
sample tends to the original sample, and that the limit is an MLE given the
original sample, when one exists. Finally, we study which MLEs given a sample
can arise as such limits. We reduce this to a question regarding the
non-emptiness of certain algebraic varieties.


  We propose a model uncertainty approach to heavy traffic asymptotics that
allows for a high level of uncertainty. That is, the uncertainty classes of
underlying distributions accommodate disturbances that are of order 1 at the
usual diffusion scale, as opposed to asymptotically vanishing disturbances
studied previously in relation to heavy traffic. A main advantage of the
approach is that the invariance principle underlying diffusion limits makes it
possible to define uncertainty classes in terms of the first two moments only.
The model we consider is a single server queue with multiple job types. The
problem is formulated as a zero sum stochastic game played between the system
controller, who determines scheduling and attempts to minimize an expected
linear holding cost, and an adversary, who dynamically controls the service
time distributions of arriving jobs, and attempts to maximize the cost. The
heavy traffic asymptotics of the game are fully solved. It is shown that an
asymptotically optimal policy for the system controller is to prioritize
according to an index rule and for the adversary it is to select distributions
based on the system's current workload. The workload-to-distribution feedback
mapping is determined by an HJB equation, which also characterizes the game's
limit value. Unlike in the vast majority of results in the heavy traffic
theory, and as a direct consequence of the diffusive size disturbances, the
limiting dynamics under asymptotically optimal play are captured by a
stochastic differential equation where both the drift and the diffusion
coefficients may be discontinuous.


  The strong-isospin violation in $\psi(3770)\rightarrow J/\psi + \pi^0$ via
intermediate $D$ meson loops is investigated in an effective Lagrangian
approach. In this process, there is only one $D$-meson loop contributing to the
absorptive part, and the uncertainties due to the introduction of form factors
can be minimized. With the help of QCD spectral sum rules (QSSR), we extract
the $J/\psi DD^*$ form factor as an implement from the first principle of QCD.
The $DD^*\pi^0$ form factor can be well determined from the experimental data
for $D\rightarrow\pi l\nu$. The exploration of the dispersion relation suggests
the dominance of the dispersive part via the intermediate $D$ meson loops even
below the open charm threshold. This investigation could provide further
insights into the puzzling question on the mechanisms for $\psi(3770)\to$
non-$D\bar{D}$ transitions.


  We perform first-principles calculations of wurtzite GaAs nanorods to explore
the factors determining charge distributions in polar nanostructures. We show
that both the direction and magnitude of the dipole moment $\mathbf{d}$ of a
nanorod, and its electic field, depend sensitively on how its surfaces are
terminated and do not depend strongly on the spontaneous polarization of the
underlying lattice. We identify two physical mechanisms by which $\mathbf{d}$
is controlled by the surface termination, and we show that the excess charge on
the nanorod ends is not strongly localized. We discuss the implications of
these results for tuning nanocrystal properties, and for their growth and
assembly.


  The complex theoretical and experimental studies of the band structure and
the optical functions of the Cu2CdGeSe4 quaternary crystals are reported. The
benchmark band structure calculations were performed using the first-principles
methods. As a result, the structural, electronic, optical and elastic
properties of Cu2CdGeSe4 were calculated in the general gradient approximation
(GGA) and local density approximation (LDA). The calculated dielectric function
and optical absorption spectra exhibit some anisotropic behavior. Detailed
analysis of the band energy dispersion and the effective space charge density
helped in establishing the origin of the band structure anisotropy. All
calculated properties are compared with the experimental data. An additional
comparison with a similar crystal of Cu2CdGeSe4 allowed to reveal the role
played by the anions (S or Se) in formation of the optical properties of these
two materials.