  We show that claims, presented in Phys. Rev. B {\bf 65}, 125109 (2002)
concerning the threshold behavior of dynamical correlations of a Coulomb
Luttinger liquid, are based on an inconsistent mathematical analysis. Physical
arguments are also presented, indicating that the claimed behavior is unlikely
to be correct.


  Heat fluxes in a district heating pipeline systems need to be controlled on
the scale from minutes to an hour to adjust to evolving demand. There are two
principal ways to control the heat flux - keep temperature fixed but adjust
velocity of the carrier (typically water) or keep the velocity flow steady but
then adjust temperature at the heat producing source (heat plant). We study the
latter scenario, commonly used for operations in Russia and Nordic countries,
and analyze dynamics of the heat front as it propagates through the system.
Steady velocity flows in the district heating pipelines are typically turbulent
and incompressible. Changes in the heat, on either consumption or production
sides, lead to slow transients which last from tens of minutes to hours. We
classify relevant physical phenomena in a single pipe, e.g. turbulent spread of
the turbulent front. We then explain how to describe dynamics of temperature
and heat flux evolution over a network efficiently and illustrate the network
solution on a simple example involving one producer and one consumer of heat
connected by "hot" and "cold" pipes. We conclude the manuscript motivating
future research directions.


  The study of this paper is inspired by the conjecture of Zagier on the
explicit dimension formula for the space of the same weight double zeta values
in terms of the dimension of cusp forms for SL_{2}(Z). Our main result is to
devise an effective criterion for computing the dimension of the same weight
double zeta values over a rational function field F_{q}(theta) in positive
characteristic. Contrary to the Zagier's conjecture, the analogue of Zagier's
conjectural dimension provides a lower bound for the dimension of the double
zeta values when the weight is $A$-even.


  A signed network is a network with each link associated with a positive or
negative sign. Models for nodes interacting over such signed networks, where
two different types of interactions take place along the positive and negative
links, respectively, arise from various biological, social, political, and
economic systems. As modifications to the conventional DeGroot dynamics for
positive links, two basic types of negative interactions along negative links,
namely the opposing rule and the repelling rule, have been proposed and studied
in the literature. This paper reviews a few fundamental convergence results for
such dynamics over deterministic or random signed networks under a unified
algebraic-graphical method. We show that a systematic tool of studying node
state evolution over signed networks can be obtained utilizing generalized
Perron-Frobenius theory, graph theory, and elementary algebraic recursions.


  With the development of multimedia technology, Video Copy Detection has been
a crucial problem for social media platforms. Meta AI hold Video Similarity
Challenge on CVPR 2023 to push the technology forward. In this paper, we share
our winner solutions on both tracks to help progress in this area. For
Descriptor Track, we propose a dual-level detection method with Video Editing
Detection (VED) and Frame Scenes Detection (FSD) to tackle the core challenges
on Video Copy Detection. Experimental results demonstrate the effectiveness and
efficiency of our proposed method. Code is available at
https://github.com/FeipengMa6/VSC22-Submission.


  Using unbiased Monte Carlo simulations and variational analysis, we present
the ground state and finite temperature phase diagrams of an exactly solvable
spin-orbital model with Kitaev-type interactions on a square lattice. We show
that an array of new gapped and gapless vison crystals -- characterized by the
periodic arrangement of $\mathbb{Z}_2$ flux excitations -- can be stabilized as
a function of external magnetic field and exchange anisotropy. In particular,
we discover a variety of `quarter phases' wherein new sixteen-site periodic
patterns emerge, with only a quarter of the fluxes adopting 0-flux
configurations. In contrast, the rest remain in $\pi$-flux configurations.
Vison crystals break translational symmetry and undergo finite temperature
phase transitions. We investigate the finite temperature properties of these
phases and report the corresponding critical and crossover temperatures. Our
results reveal an array of novel phases in exactly solvable extensions of the
Kitaev model, wherein local and topological orders can coexist.


  This research study investigates the minimization of inequality in the ranks
of vertices obtained using the PageRank algorithm. PageRank is a widely used
algorithm for ranking webpages and plays a significant role in determining web
traffic. This study employs the Gini coefficient, a measure of income/wealth
inequality, to assess the inequality in PageRank distributions on various types
of graphs. The investigation involves two experiments: one that modifies
strategies for handling dead-end nodes and another that explores six
deterministic methods for reducing inequality. Our findings indicate that a
combination of two distinct heuristics may present an effective strategy for
minimizing inequality.


  Leptoquarks (LQs) are predicted within Grand Unified Theories and are well
motivated by the current flavor anomalies. In this article we investigate the
impact of scalar LQs on Higgs decays and oblique corrections as complementary
observables in the search for them. Taking into account all five LQ
representations under the Standard Model gauge group and including the most
general mixing among them, we calculate the effects in $h\to\gamma\gamma$,
$h\to gg$, $h \to Z \gamma$ and the Peskin-Takeuchi parameters $S$, $T$ and
$U$. We find that these observables depend on the same Lagrangian parameters,
leading to interesting correlations among them. While the current experimental
bounds only yield weak constraints on the model, these correlations can be used
to distinguish different LQ representations at future colliders (ILC, CLIC,
FCC-ee and FCC-hh), whose discovery potential we are going to discuss.


  Massive stars that lose their hydrogen-rich envelope down to a few tenths of
a solar mass explode as extended type IIb supernovae, an intriguing subtype
that links the hydrogen-rich type II supernovae with the hydrogen-poor type Ib
and Ic. The progenitors may be very massive single stars that lose their
envelope due to their stellar wind, but mass stripping due to interaction with
a companion star in a binary system is currently considered to be the dominant
formation channel. We computed an extensive grid of binary models with the
Eggleton binary evolution code. The predicted rate from our standard models,
which assume conservative mass transfer, is about 6 times smaller than the
current rate indicated by observations. It is larger but still comparable to
the rate expected from single stars. To recover the observed rate we must
generously allow for uncertainties and low accretion efficiencies in
combination with limited angular momentum loss from the system. Motivated by
the claims of detection and non-detection of companions for a few IIb
supernovae, we investigate the properties of the secondary star at the moment
of explosion. We identify three cases: (1) the companion appears as a hot O
star in about 90% of the cases, (2) the companion becomes an over-luminous B
star in about 3% of the cases, or (3) the companion will appear as a K
supergiant. The second case, which applies to the well-studied case of SN 1993J
and possibly to SN 2001ig, is the least common case and requires that the
companion very efficiently accretes the transferred material -in contrast to
what is required to recover the overall IIb rate. The fast increasing number of
type IIb detections may lead to more solid constraints on model uncertainties,
like stellar wind-mass loss and internal mixing.


  The response of a semiflexible polyelectrolyte chain to stretching in the
regimes of moderate and weak screening is studied theoretically, with a special
focus on DNA experiments. By using the nonlinear Poisson--Boltzmann description
of electrostatic self--interactions of the chain, we explicitly demonstrate the
applicability of the concept of effective charge to certain aspects of the
problem. This charge can be extracted from the far--field asymptotic behavior
of electrostatic potential of the fully aligned chain. Surprisingly, in terms
of the effective charge, the electrostatically renormalized persistence length
can be formally described by the classical Odijk-Skolnick-Fixman (OSF) formula,
whose domain of applicability is limited to linearized Debye Huckel (DH)
approximation. However, the short--length behavior of the chain in the
nonlinear regime deviates from the of DH--based result, even upon the charge
renormalization. This difference is revealed in calculated stretching curves of
strongly charged DNA, and our results are in good agreement with the recent
experiments. In the limit of weak screening we predict the elastic response to
have a distinctive two-stage character, with a peculiar intermediate
"unstretchable" regime.


  We discuss Weyl (conformal) transformations in two-dimensional matterless
dilaton gravity. We argue that both classical and quantum dilaton gravity
theories are invariant under Weyl transformations.


  Motivated by some earlier works \cite{pavon,sadjadi} dealing with the study
of generalized second law (GSL) of thermodynamics for a system comprising of a
Schwarzschild black accreting a test non-self-gravitating fluid namely phantom
energy in FRW universe, we extend them when the entropy of horizons of black
hole and the cosmological undergo quantum corrections. Two types of such
corrections are relevant here including logarithmic and power-law, while both
are motivated from different theoretical backgrounds. We obtain general
mathematical conditions for the validity of GSL in each case. Further we find
that GSL restricts the mass of black hole for accretion of phantom energy. As
such we obtain upper bounds on the mass of black hole above which the black
hole cannot accrete the phantom fluid, otherwise the GSL is violated.


  We present numerical evolutions of three equal-mass black holes using the
moving puncture approach. We calculate puncture initial data for three black
holes solving the constraint equations by means of a high-order multigrid
elliptic solver. Using these initial data, we show the results for three black
hole evolutions with sixth-order waveform convergence. We compare results
obtained with the BAM and AMSS-NCKU codes with previous results. The
approximate analytic solution to the Hamiltonian constraint used in previous
simulations of three black holes leads to different dynamics and waveforms. We
present some numerical experiments showing the evolution of four black holes
and the resulting gravitational waveform.


  We study the dynamics of protein folding via statistical energy-landscape
theory. In particular, we concentrate on the local-connectivity case with the
folding progress described by the fraction of native conformations. We obtain
information for the first passage-time (FPT) distribution and its moments. The
results show a dynamic transition temperature below which the FPT distribution
develops a power-law tail, a signature of the intermittency phenomena of the
folding dynamics. We also discuss the possible application of the results to
single-molecule dynamics experiments.


  A permutation is called Grassmannian if it has at most one descent. The study
of pattern avoidance in such permutations was initiated by Gil and Tomasko in
2021. We continue this work by studying Grassmannian permutations that avoid an
increasing pattern. In particular, we count the Grassmannian permutations of
size $m$ avoiding the identity permutation of size $k$, thus solving a
conjecture made by Weiner. We also refine our counts to special classes such as
odd Grassmannian permutations and Grassmannian involutions. We prove most of
our results by relating Grassmannian permutations to Dyck paths and binary
words.


  The geographically weighted regression (GWR) is a well-known statistical
approach to explore spatial non-stationarity of the regression relationship in
spatial data analysis. In this paper, we discuss a Bayesian recourse of GWR.
Bayesian variable selection based on spike-and-slab prior, bandwidth selection
based on range prior, and model assessment using a modified deviance
information criterion and a modified logarithm of pseudo-marginal likelihood
are fully discussed in this paper. Usage of the graph distance in modeling
areal data is also introduced. Extensive simulation studies are carried out to
examine the empirical performance of the proposed methods with both small and
large number of location scenarios, and comparison with the classical
frequentist GWR is made. The performance of variable selection and estimation
of the proposed methodology under different circumstances are satisfactory. We
further apply the proposed methodology in analysis of a province-level
macroeconomic data of 30 selected provinces in China. The estimation and
variable selection results reveal insights about China's economy that are
convincing and agree with previous studies and facts.


  In this note, we give several definitions of metric corona properties which
could be of interest in Set Topology, Functional Analysis and Approximation
Theory, and prove that there are complete metrizable t.v.s. which are nice in
the sense that they have a metric which is invariant by translations, but they
do not have good corona properties. All classical function spaces satisfy good
corona properties but it is an open question to know if this also holds for the
more general setting of locally convex t.v.s.


  Maximum entropy deep reinforcement learning (RL) methods have been
demonstrated on a range of challenging continuous tasks. However, existing
methods either suffer from severe instability when training on large off-policy
data or cannot scale to tasks with very high state and action dimensionality
such as 3D humanoid locomotion. Besides, the optimality of desired Boltzmann
policy set for non-optimal soft value function is not persuasive enough. In
this paper, we first derive soft policy gradient based on entropy regularized
expected reward objective for RL with continuous actions. Then, we present an
off-policy actor-critic, model-free maximum entropy deep RL algorithm called
deep soft policy gradient (DSPG) by combining soft policy gradient with soft
Bellman equation. To ensure stable learning while eliminating the need of two
separate critics for soft value functions, we leverage double sampling approach
to making the soft Bellman equation tractable. The experimental results
demonstrate that our method outperforms in performance over off-policy prior
methods.


  Using collision driven molecular dynamics a system of spherical particles
interacting through an effective two length scales potential is studied. The
potential can be tuned by means of a single parameter, $\lambda$, from a ramp
$(\lambda=0.5)$ to a square-shoulder potential $(\lambda=1.0)$ representing a
family of two length scales potential in which the shortest interaction
distance has higher potential energy than the largest interaction distance. For
all the potentials, ranging between the ramp and the square-shoulder, density
and structural anomalies were found, while the diffusion anomaly is found in
all but in the square-shoulder potential. The presence anomalies in
square-shoulder potential, not observed in previous simulations, confirm the
assumption that the two length scales potential is an ubiquitous ingredient for
a system to exhibit water-like anomalies


  We study Schubert polynomials using geometry of infinite-dimensional flag
varieties and degeneracy loci. Applications include Graham-positivity of
coefficients appearing in equivariant coproduct formulas and expansions of
back-stable and enriched Schubert polynomials. We also construct an embedding
of the type C flag variety, and study the corresponding pullback map on
(equivariant) cohomology rings.


  We study the arbitrary cost case of the unweighted Stochastic Score
Classification (SSClass) problem. We show two constant approximation algorithms
and both algorithms are 6-approximation non-adaptive algorithms with respect to
the optimal adaptive algorithm. The first algorithm uses a modified round-robin
approach among three sequences, which is inspired by a recent result on the
unit cost case of the SSClass problem. The second algorithm is originally from
the work of Gkenosis et al. In our work, we successfully improve its
approximation factor from 2(B-1) to 6. Our analysis heavily uses the relation
between computation and verification of functions, which was studied in the
information theory literature.


  We consider a family of local search algorithms for the minimum-weight
spanning tree, indexed by a parameter $\rho$. One step of the local search
corresponds to replacing a connected induced subgraph of the current candidate
graph whose total weight is at most $\rho$ by the minimum spanning tree (MST)
on the same vertex set. Fix a non-negative random variable $X$, and consider
this local search problem on the complete graph $K_n$ with independent
$X$-distributed edge weights. Under rather weak conditions on the distribution
of $X$, we determine a threshold value $\rho^*$ such that the following holds.
If the starting graph (the "initial candidate MST") is independent of the edge
weights, then if $\rho > \rho^*$ local search can construct the MST with high
probability (tending to $1$ as $n \to \infty$), whereas if $\rho < \rho^*$ it
cannot with high probability.


  We firstly demonstrate physically-prepared compliant PVA hydrogel electrodes
as a promising supplement in dielectric elastomer actuators. They are capable
of conducting high voltages over 5 kV without electrolysis by an electrical
double layer effect. The hydrogel electrodes adhere tightly to the dielectric
layer, which ensures its structural stability during actuation. All-polymeric
actuators fabricated by these electrodes exhibited excellent consecutive
working performance over 2960 cycles. The actuation was influenced by applied
voltage, ramp rate, electrode elastic modulus and moisture content. A maximum
areal strain over 78% was achieved. Tunable transparency, good
biocompatibility, long lifetime, low cost and facile fabrication make PVA
hydrogel electrode another promising candidate in the fields of sensors,
artificial muscles and optical applications.


  The 9 Myr old TW Hya Association (TWA) is the nearest group (typical
distances of $\sim$50 pc) of pre-main-sequence (PMS) stars with ages less than
10 Myr and contains stars with both actively accreting disks and debris disks.
We have studied the coronal X-ray emission from a group of low mass TWA common
proper motion binaries using the {\it{Chandra}} and {\it{Swift}} satellites.
Our aim is to understand better their coronal properties and how high energy
photons affect the conditions around young stars and their role in
photo-exciting atoms, molecules and dust grains in circumstellar disks and
lower density circumstellar gas. Once planet formation is underway, this
emission influences protoplanetary evolution and the atmospheric conditions of
the newly-formed planets. The X-ray properties for 7 individual stars (TWA 13A,
TWA 13B, TWA 9A, TWA 9B, TWA 8A, TWA 8B, and TWA 7) and 2 combined binary
systems (TWA 3AB and TWA 2AB) have been measured. All the stars with sufficient
signal require two-component fits to their CCD-resolution X-ray spectra,
typically with a dominant hot (~2 kev (25 MK)) component and a cooler component
at ~0.4 keV (4 MK). The brighter sources all show significant X-ray variability
(at a level of 50-100\% of quiescence) over the course of 5-15 ksec
observations due to flares. We present the X-ray properties for each of the
stars and find that the coronal emission is in the super-saturated rotational
domain.


  We introduce a new task called Referring Atomic Video Action Recognition
(RAVAR), aimed at identifying atomic actions of a particular person based on a
textual description and the video data of this person. This task differs from
traditional action recognition and localization, where predictions are
delivered for all present individuals. In contrast, we focus on recognizing the
correct atomic action of a specific individual, guided by text. To explore this
task, we present the RefAVA dataset, containing 36,630 instances with manually
annotated textual descriptions of the individuals. To establish a strong
initial benchmark, we implement and validate baselines from various domains,
e.g., atomic action localization, video question answering, and text-video
retrieval. Since these existing methods underperform on RAVAR, we introduce
RefAtomNet -- a novel cross-stream attention-driven method specialized for the
unique challenges of RAVAR: the need to interpret a textual referring
expression for the targeted individual, utilize this reference to guide the
spatial localization and harvest the prediction of the atomic actions for the
referring person. The key ingredients are: (1) a multi-stream architecture that
connects video, text, and a new location-semantic stream, and (2) cross-stream
agent attention fusion and agent token fusion which amplify the most relevant
information across these streams and consistently surpasses standard
attention-based fusion on RAVAR. Extensive experiments demonstrate the
effectiveness of RefAtomNet and its building blocks for recognizing the action
of the described individual. The dataset and code will be made publicly
available at https://github.com/KPeng9510/RAVAR.


  Finding tampered regions in images is a hot research topic in machine
learning and computer vision. Although many image manipulation location
algorithms have been proposed, most of them only focus on the RGB images with
different color spaces, and the frequency information that contains the
potential tampering clues is often ignored. In this work, a novel end-to-end
two-stream boundary-aware network (abbreviated as TBNet) is proposed for
generic image manipulation localization in which the RGB stream, the frequency
stream, and the boundary artifact location are explored in a unified framework.
Specifically, we first design an adaptive frequency selection module (AFS) to
adaptively select the appropriate frequency to mine inconsistent statistics and
eliminate the interference of redundant statistics. Then, an adaptive
cross-attention fusion module (ACF) is proposed to adaptively fuse the RGB
feature and the frequency feature. Finally, the boundary artifact location
network (BAL) is designed to locate the boundary artifacts for which the
parameters are jointly updated by the outputs of the ACF, and its results are
further fed into the decoder. Thus, the parameters of the RGB stream, the
frequency stream, and the boundary artifact location network are jointly
optimized, and their latent complementary relationships are fully mined. The
results of extensive experiments performed on four public benchmarks of the
image manipulation localization task, namely, CASIA1.0, COVER, Carvalho, and
In-The-Wild, demonstrate that the proposed TBNet can significantly outperform
state-of-the-art generic image manipulation localization methods in terms of
both MCC and F1.


  We introduce our method and system for face recognition using multiple
pose-aware deep learning models. In our representation, a face image is
processed by several pose-specific deep convolutional neural network (CNN)
models to generate multiple pose-specific features. 3D rendering is used to
generate multiple face poses from the input image. Sensitivity of the
recognition system to pose variations is reduced since we use an ensemble of
pose-specific CNN features. The paper presents extensive experimental results
on the effect of landmark detection, CNN layer selection and pose model
selection on the performance of the recognition pipeline. Our novel
representation achieves better results than the state-of-the-art on IARPA's CS2
and NIST's IJB-A in both verification and identification (i.e. search) tasks.


  Spherically complete ball spaces provide a framework for the proof of generic
fixed point theorems. For the purpose of their application it is important to
have methods for the construction of new spherically complete ball spaces from
given ones. Given various ball spaces on the same underlying set, we discuss
the construction of new ball spaces through set theoretic operations on the
balls. A definition of continuity for functions on ball spaces leads to the
notion of quotient spaces. Further, we show the existence of products and
coproducts and use this to derive a topological category associated with ball
spaces.


  The mean-field dynamics of a Bose gas is shown to break down at time $\tau_h
= (c_1/\gamma) \ln N$ where $\gamma$ is the Lyapunov exponent of the mean-field
theory, $N$ is the number of bosons, and $c_1$ is a system-dependent constant.
The breakdown time $\tau_h$ is essentially the Ehrenfest time that
characterizes the breakdown of the correspondence between classical and quantum
dynamics. This breakdown can be well described by the quantum fidelity defined
for reduced density matrices. Our results are obtained with the formalism in
particle-number phase space and are illustrated with a triple-well model. The
logarithmic quantum-classical correspondence time may be verified
experimentally with Bose-Einstein condensates.


  In this article we study the long-time behaviour of a system of nonlinear
Partial Differential Equations (PDEs) modelling the motion of incompressible,
isothermal and conducting modified bipolar fluids in presence of magnetic
field. We mainly prove the existence of a global attractor denoted by $\A$ for
the nonlinear semigroup associated to the aforementioned systems of nonlinear
PDEs. We also show that this nonlinear semigroup is uniformly differentiable on
$\A$. This fact enables us to go further and prove that the attractor $\A$ is
of finite-dimensional and we give an explicit bounds for its Hausdorff and
fractal dimensions.


  A characterization of Blaschke addition as a map between origin-symmetric
convex bodies is established. This results from a new characterization of
Minkowski addition as a map between origin-symmetric zonoids, combined with the
use of L\'{e}vy-Prokhorov metrics. A full set of examples is provided that show
the results are in a sense the best possible.


  A number of recent works in E-print arXiv have addressed the foundation of
gauge gravitation theory again. As is well known, differential geometry of
fibre bundles provides the adequate mathematical formulation of classical field
theory, including gauge theory on principal bundles. Gauge gravitation theory
is formulated on the natural bundles over a world manifold whose structure
group is reducible to the Lorentz group. It is the metric-affine gravitation
theory where a metric (tetrad) gravitational field is a Higgs field.


  We consider Markov jump processes describing structured populations with
interactions via density dependance. We propose a Markov construction with a
distinguished individual which allows to describe the random tree and random
sample at a given time via a change of probability. This spine construction
involves the extension of type space of individuals to include the state of the
population. The jump rates outside the spine are also modified. We apply this
approach to some issues concerning evolution of populations and competition.
For single type populations, we derive the diagram phase of a growth
fragmentation model with competition and the growth of the size of birth and
death processes with multiple births. We also describe the ancestral lineages
of a uniform sample in multitype populations.


  The paper presents a simulation on automotive inventory and stock issue,
followed by evaluated performance of automotif Sector Company, focused on
getting optimum profit from supply and demand balancing. Starting by evaluating
and verification of customer's document until car delivered to customer.
Simulation method of performance is used to evaluate company activity. excess
demand of car by customer, not eligible customer to rented a car, number of
customer who served and number of customer who served including the driver, the
last result is number of optimum demand that match with the stock or supply of
car by the company. Finally, board of management should be making decision; the
first decision is buy the new car for meet with the demand or second decision
is recruit new staff for increasing customer service or customer care.


  The region around neutron number N = 60 in the neutron-rich Sr and Zr nuclei
is one of the most dramatic examples of a ground state shape transition from
(near) spherical below N = 60 to strongly deformed shapes in the heavier
isotopes. The single-particle structure of 95-97Sr approaching the ground state
shape transition at 98 Sr has been investigated via single-neutron transfer
reactions using the (d, p) reaction in inverse kinematics. These reactions
selectively populate states with a large overlap of the projectile ground state
coupled to a neutron in a single-particle orbital. Radioactive 94,95,96Sr
nuclei with energies of 5.5 AMeV were used to bombard a CD 2 target. Recoiling
light charged particles and {\gamma} rays were detected using a quasi-4{\pi}
silicon strip detector array and a 12 element Ge array. The excitation energy
of states populated was reconstructed employing the missing mass method
combined with {\gamma}-ray tagging and differential cross sections for final
states were extracted. A reaction model analysis of the angular distributions
allowed for firm spin assignments to be made for the low-lying 352, 556 and 681
keV excited states in 95Sr and a constraint has been placed on the spin of the
higher-lying 1666 keV state. Angular distributions have been extracted for 10
states populated in the d(95Sr,p)96Sr reaction, and constraints have been
provided for the spins and parities of several final states. Results are
compared to shell model calculations in several model spaces and the structure
of low-lying states in 94Sr and 95Sr is well-described. The spectroscopic
strength of the 0+ and 2 states in 96Sr is significantly more fragmented than
predicted.


  Dijkstra's algorithm for the Single-Source Shortest Path (SSSP) problem is
notoriously hard to parallelize in $o(n)$ depth, $n$ being the number of
vertices in the input graph, without increasing the required parallel work
unreasonably. Crauser et al.\ (1998) presented observations that allow to
identify more than a single vertex at a time as correct and correspondingly
more edges to be relaxed simultaneously. Their algorithm runs in parallel
phases, and for certain random graphs they showed that the number of phases is
$O(n^{1/3})$ with high probability. A work-efficient CRCW PRAM with this depth
was given, but no implementation on a real, parallel system.
  In this paper we strengthen the criteria of Crauser et al., and discuss
tradeoffs between work and number of phases in their implementation. We present
simulation results with a range of common input graphs for the depth that an
ideal parallel algorithm that can apply the criteria at no cost and parallelize
relaxations without conflicts can achieve. These results show that the number
of phases is indeed a small root of $n$, but still off from the shortest path
length lower bound that can also be computed.
  We give a shared-memory parallel implementation of the most work-efficient
version of a Dijkstra's algorithm running in parallel phases, which we compare
to an own implementation of the well-known $\Delta$-stepping algorithm. We can
show that the work-efficient SSSP algorithm applying the criteria of Crauser et
al. is competitive to and often better than $\Delta$-stepping on our chosen
input graphs. Despite not providing an $o(n)$ guarantee on the number of
required phases, criteria allowing concurrent relaxation of many correct
vertices may be a viable approach to practically fast, parallel SSSP
implementations.


  Let $X=(V, E)$ be a finite regular graph and $H_t(u, v), \, u, v \in V$, the
heat kernel on $X$. We prove that, if the graph $X$ is bipartite and has four
distinct Laplacian eigenvalues, the ratio $H_t(u, v)/H_t(u, u), \, u, v \in V,$
is monotonically non-decreasing as a function of $t$. The key to the proof is
the fact that such a graph is an incidence graph of a symmetric 2-design.


  We derive an upper bound on the number of models for exact satisfiability
(XSAT) of arbitrary CNF formulas F. The bound can be calculated solely from the
distribution of positive and negated literals in the formula. For certain
subsets of CNF instances the new bound can be computed in sub-exponential time,
namely in at most O(exp(sqrt(n))) , where n is the number of variables of F. A
wider class of SAT problems beyond XSAT is defined to which the method can be
extended.


  mDCThermalC is a program written in Python for computing lattice thermal
conductivity of crystalline bulk materials using the modified Debye-Callaway
model. Building upon the traditional Debye-Callaway theory, the modified model
obtains the lattice thermal conductivity by averaging the contributions from
acoustic and optical branches based on their specific heat. The only inputs of
this program are the phonon spectrum, phonon velocity and Gruneisen parameter,
all of which can be calculated using third-party ab initio packages, making the
method fully parameter-free. This leads to a fast and accurate evaluation and
enables high-throughput calculations of lattice thermal conductivity even in
large and complex systems. In addition, this program calculates the specific
heat and phonon relaxation times for different scattering processes, which will
be beneficial for understanding the phonon transfer behavior.


  The research of the derivative nonlinear Schrodinger equation (DNLS) has
attracted more and more extensive attention in theoretical analysis and
physical application. The improved physicsinformed neural network (IPINN)
approach with neuron-wise locally adaptive activation function is presented to
derive the data-driven localized wave solutions, which contain rational
solution, soliton solution, rogue wave, periodic wave and rogue periodic wave
for the DNLS with initial and boundary conditions in complex space. Especially,
the data-driven periodic wave and rogue periodic wave of the DNLS are
investigated by employing the IPINN method for the first time. Furthermore, the
relevant dynamical behaviors, error analysis and vivid plots have been
exhibited in detail. The numerical results indicate the IPINN method can well
simulate the localized wave solutions of the DNLS under a small data set.


  A triple-quantum-dot system can be operated as either an exchange-only qubit
or a resonant-exchange qubit. While it is generally believed that the decisive
advantage of the resonant-exchange qubit is the suppression of charge noise
because it is operated at a sweet spot, we show that the leakage is also an
important factor. Through molecular-orbital-theoretic calculations, we show
that when the system is operated in the exchange-only scheme, the leakage to
states with double electron occupancy in quantum dots is severe when rotations
around the axis 120$^\circ$ from $\hat{z}$ is performed. While this leakage can
be reduced by either shrinking the dots or separating them further, the
exchange interactions are also suppressed at the same time, making the gate
operations unfavorably slow. When the system is operated as a resonant-exchange
qubit, the leakage is 3-5 orders of magnitude smaller. We have also calculated
the optimal detuning point which minimizes the leakage for the
resonant-exchange qubit, and have found that although it does not coincide with
the double-sweet-spot for the charge noise, they are rather close. Our results
suggest that the resonant-exchange qubit has another advantage that leakage can
be greatly suppressed compared to the exchange-only qubit, and operating at the
double-sweet-spot point should be optimal both for reducing charge noise and
suppressing leakage.


  Many online hate groups exist to disparage others based on race, gender
identity, sex, or other characteristics. The accessibility of these communities
allows users to join multiple types of hate groups (e.g., a racist community
and misogynistic community), which calls into question whether these
peripatetic users could be further radicalized compared to users that stay in
one type of hate group. However, little is known about the dynamics of joining
multiple types of hate groups, nor the effect of these groups on peripatetic
users. In this paper, we develop a new method to classify hate subreddits, and
the identities they disparage, which we use to better understand how users
become peripatetic (join different types of hate subreddits). The hate
classification technique utilizes human-validated LLMs to extract the protected
identities attacked, if any, across 168 subreddits. We then cluster
identity-attacking subreddits to discover three broad categories of hate:
racist, anti-LGBTQ, and misogynistic. We show that becoming active in a user's
first hate subreddit can cause them to become active in additional hate
subreddits of a different category. We also find that users who join additional
hate subreddits, especially of a different category, become more active in hate
subreddits as a whole and develop a wider hate group lexicon. We are therefore
motivated to train an AI model that we find usefully predicts the hate
categories users will become active in based on post text read and written. The
accuracy of this model may be partly driven by peripatetic users often using
the language of hate subreddits they eventually join. Overall, these results
highlight the unique risks associated with hate communities on a social media
platform, as discussion of alternative targets of hate may lead users to target
more protected identities.


  The formation of energy communities is pivotal for advancing decentralized
and sustainable energy management. Within this context, Coalition Structure
Generation (CSG) emerges as a promising framework. The complexity of CSG grows
rapidly with the number of agents, making classical solvers impractical for
even moderate sizes (number of agents>30). Therefore, the development of
advanced computational methods is essential. Motivated by this challenge, this
study conducts a benchmark comparing classical solvers with quantum annealing
on Dwave hardware and the Quantum Approximation Optimization Algorithm (QAOA)
on both simulator and IBMQ hardware to address energy community formation. Our
classical solvers include Tabu search, simulated annealing, and an exact
classical solver. Our findings reveal that Dwave surpasses QAOA on hardware in
terms of solution quality. Remarkably, QAOA demonstrates comparable runtime
scaling with Dwave, albeit with a significantly larger prefactor. Notably,
Dwave exhibits competitive performance compared to the classical solvers,
achieving solutions of equal quality with more favorable runtime scaling.


  We have found out that the band inversion in a silicene quantum dot (QD), in
perpendicular magnetic $B$ and electric $\Delta_z$ fields, drastically depends
on the strength of the magnetic field. We study the energy spectrum of the
silicene QD where the electric field provides a tunable band gap $\Delta$.
Boundary conditions introduce chirality, so that negative and positive angular
momentum $m$ zero Landau level (ZLL) edge states show a quite different
behavior regarding the band-inversion mechanism underlying the topological
insulator transition. We show that, whereas some ZLLs suffer band inversion at
$\Delta=0$ for any $B>0$, other ZLLs only suffer band inversion above critical
values of the magnetic field at nonzero values of the gap.


  Despite the recent popularity of neural network-based solvers for optimal
transport (OT), there is no standard quantitative way to evaluate their
performance. In this paper, we address this issue for quadratic-cost transport
-- specifically, computation of the Wasserstein-2 distance, a commonly-used
formulation of optimal transport in machine learning. To overcome the challenge
of computing ground truth transport maps between continuous measures needed to
assess these solvers, we use input-convex neural networks (ICNN) to construct
pairs of measures whose ground truth OT maps can be obtained analytically. This
strategy yields pairs of continuous benchmark measures in high-dimensional
spaces such as spaces of images. We thoroughly evaluate existing optimal
transport solvers using these benchmark measures. Even though these solvers
perform well in downstream tasks, many do not faithfully recover optimal
transport maps. To investigate the cause of this discrepancy, we further test
the solvers in a setting of image generation. Our study reveals crucial
limitations of existing solvers and shows that increased OT accuracy does not
necessarily correlate to better results downstream.


  Sample efficiency remains a fundamental issue of reinforcement learning.
Model-based algorithms try to make better use of data by simulating the
environment with a model. We propose a new neural network architecture for
world models based on a vector quantized-variational autoencoder (VQ-VAE) to
encode observations and a convolutional LSTM to predict the next embedding
indices. A model-free PPO agent is trained purely on simulated experience from
the world model. We adopt the setup introduced by Kaiser et al. (2020), which
only allows 100K interactions with the real environment. We apply our method on
36 Atari environments and show that we reach comparable performance to their
SimPLe algorithm, while our model is significantly smaller.


  We present optical imaging and spectroscopy of supernova (SN) LSQ13fn, a type
II supernova with several hitherto-unseen properties. Although it initially
showed strong symmetric spectral emission features attributable to
\ion{He}{ii}, \ion{N}{iii}, and \ion{C}{iii}, reminiscent of some interacting
SNe, it transitioned into an object that would fall more naturally under a type
II-Plateau (IIP) classification. However, its spectral evolution revealed
several unusual properties: metal lines appeared later than expected, were
weak, and some species were conspicuous by their absence. Furthermore, the line
velocities were found to be lower than expected given the plateau brightness,
breaking the SNe~IIP standardised candle method for distance estimates. We
found that, in combination with a short phase of early-time
ejecta-circumstellar material interaction, metal-poor ejecta, and a large
progenitor radius could reasonably account for the observed behaviour.
Comparisons with synthetic model spectra of SNe~IIP of a given progenitor mass
would imply a progenitor star metallicity as low as 0.1\,Z$_{\odot}$. LSQ13fn
highlights the diversity of SNe~II and the many competing physical effects that
come into play towards the final stages of massive star evolution immediately
preceding core-collapse.


  This paper reports on developing a real-time invariant proprioceptive robot
state estimation framework called DRIFT. A didactic introduction to invariant
Kalman filtering is provided to make this cutting-edge symmetry-preserving
approach accessible to a broader range of robotics applications. Furthermore,
this work dives into the development of a proprioceptive state estimation
framework for dead reckoning that only consumes data from an onboard inertial
measurement unit and kinematics of the robot, with two optional modules, a
contact estimator and a gyro filter for low-cost robots, enabling a significant
capability on a variety of robotics platforms to track the robot's state over
long trajectories in the absence of perceptual data. Extensive real-world
experiments using a legged robot, an indoor wheeled robot, a field robot, and a
full-size vehicle, as well as simulation results with a marine robot, are
provided to understand the limits of DRIFT.


  We characterise high-dimensional topology that arises from a random Cech
complex constructed on the circle. Expected Euler characteristic curve is
computed, where we observe limiting spikes. The spikes correspond to expected
Betti numbers growing arbitrarily large over shrinking intervals of filtration
radii. Using the fact that the homotopy type of the random Cech complex is
either an odd-dimensional sphere or a bouquet of even-dimensional spheres, we
give probabilistic bounds of the homotopy types. By departing from the
conventional practice of scaling down filtration radii as the sample size grows
large, our findings indicate that the full breadth of filtration radii leads to
interesting systematic behaviour that cannot be regarded as "topological
noise".


  Encrypted control has been introduced to protect controller data by
encryption at the stage of computation and communication, by performing the
computation directly on encrypted data. In this article, we first review and
categorize recent relevant studies on encrypted control. Approaches based on
homomorphic encryption, multi-party computation, and secret sharing are
introduced, compared, and then discussed with respect to computational
complexity, communication load, enabled operations, security, and research
directions. We proceed to discuss a current challenge in the application of
homomorphic encryption to dynamic systems, where arithmetic operations other
than integer addition and multiplication are limited. We also introduce a
homomorphic cryptosystem called ``GSW-LWE'' and discuss its benefits that allow
for recursive multiplication of encrypted dynamic systems, without use of
computationally expensive bootstrapping techniques.


  The motivation to study experimentally CO ice under mimicked interstellar
conditions is supported by the large CO gas abundances and ubiquitous presence
of CO in icy grain mantles. Upon irradiation in its pure ice form, this highly
stable species presents a limited ion and photon-induced chemistry, and an
efficient non-thermal desorption. Using infrared spectroscopy, single laser
interference, and quadrupole mass spectrometry during CO ice deposition, the CO
ice density was estimated as a function of deposition temperature. Only minor
variations in the density were found. The proposed methodology can be used to
obtain the density of other ice components at various deposition temperatures
provided that this value of the density is known for one of these temperatures,
which is typically the temperature corresponding to the crystalline form. The
apparent tendency of the CO ice density to decrease at deposition temperatures
below 14 K is in line with recently published colorimetric measurements. This
work allowed to revisit the value of the infrared band strength needed for
calculation of the CO ice column density in infrared observations, $8.7 \times
10^{-18} ~ {\rm cm ~ molecule}^{-1}$ at 20 K deposition temperature.


  Within the framework of the minimal non-minimal supersymmetric standard model
(MNMSSM) with tadpole terms, CP violation effects in the Higgs sector are
investigated at the one-loop level, where the radiative corrections from the
loops of the quark and squarks of the third generation are taken into account.
Assuming that the squark masses are not degenerate, the radiative corrections
due to the stop and sbottom quarks give rise to CP phases, which trigger the CP
violation explicitly in the Higgs sector of the MNMSSM. The masses, the
branching ratios for dominant decay channels, and the total decay widths of the
five neutral Higgs bosons in the MNMSSM are calculated in the presence of the
explicit CP violation. The dependence of these quantities on the CP phases is
quite recognizable, for given parameter values.


  We studied the evolution of the electronic structure across the quantum
critical point in V doped Cr employing high resolution photoemission
spectroscopy. Experimental results exhibit signatures of pseudogap and orbital
Kondo resonance peak at low temperatures for all the compositions studied
suggesting a scenario of spin density wave quantum criticality corresponding to
orbital Kondo effect. The pseudogap and the Kondo peak gradually reduces with V
doping but remains finite at the quantum critical point indicating their
relevance in widely discussed quantum phases in correlated electron systems.
The spectral lineshape near the Fermi level exhibit (E_F - E)^{0.25} dependence
evidencing deviation from Fermi liquid behavior.


  Experiment and theory indicate that UPt3 is a topological superconductor in
an odd-parity state, based in part from temperature independence of the NMR
Knight shift. However, quasiparticle spin-flip scattering near a surface, where
the Knight shift is measured, might be responsible. We use polarized neutron
scattering to measure the bulk susceptibility with H||c, finding consistency
with the Knight shift but inconsistent with theory for this field orientation.
We infer that neither spin susceptibility nor Knight shift are a reliable
indication of odd-parity.


  We introduce a fast and robust algorithm for finding a plane $\Gamma$ with
given normal $\vec{n}_\Gamma$, which truncates an arbitrary polyhedron
$\mathcal{P}$ such that the remaining sub-polyhedron admits a given volume
$\alpha|\mathcal{P}|$. In the literature, this is commonly referred to as
Volume-of-Fluid (VoF) interface positioning problem. The novelty of our work is
twofold: firstly, by recursive application of the Gaussian divergence theorem,
the volume of a truncated polyhedron can be computed at high efficiency, based
on summation over quantities associated to the faces of the polyhedron. One
obtains a very convenient piecewise parametrization (within so-called brackets)
in terms of the signed distance s to the plane $\Gamma$. As an implication, one
can restrain from the costly necessity to establish topological connectivity,
rendering the present approach most suitable for the application to
unstructured computational meshes. Secondly, in the vicinity of the truncation
position s, the volume can be expressed exactly, i.e. in terms of a cubic
polynomial of the normal distance to the PLIC plane. The local knowledge of
derivatives enables to construct a root-finding algorithm that pairs bracketing
and higher-order approximation. The performance is assessed by conducting an
extensive set of numerical experiments, considering convex and non-convex
polyhedra of genus (i.e., number of holes) zero and one in combination with
carefully selected volume fractions $\alpha$ (including $\alpha\approx0$ and
$\alpha\approx1$) and normal orientations $\vec{n}_\Gamma$. For all
configurations we obtain a significant reduction of the number of
(computationally costly) truncations required for the positioning: on average,
our algorithm requires between one and two polyhedron truncations to find the
position of the plane $\Gamma$, outperforming existing methods.


  We examine the dipole approximated Pauli-Fierz Hamiltonians of the
nonrelativistic QED. We assume that the Coulomb potential of the nuclei
together with the Coulomb interaction between the electrons can be approximated
by harmonic potentials. By an exact diagonalization method, we prove that the
binding energy of the two hydrogen atoms behaves as $R^{-7}$, provided that the
distance between atoms $R$ is sufficiently large. We employ the Feynman's
representation of the quantized radiation fields which enables us to
diagonalize Hamiltonians, rigorously. Our result supports the famous conjecture
by Casimir and Polder.


  We present a systematical study via scanning tunneling microscopy (STM) and
low-energy electron diffraction (LEED) on the effect of the exposure of Lithium
(Li) on graphene on silicon carbide (SiC). We have investigated Li deposition
both on epitaxial monolayer graphene and on buffer layer surfaces on the
Si-face of SiC. At room temperature, Li immediately intercalates at the
interface between the SiC substrate and the buffer layer and transforms the
buffer layer into a quasi-free-standing graphene. This conclusion is
substantiated by LEED and STM evidence. We show that intercalation occurs
through the SiC step sites or graphene defects. We obtain a good quantitative
agreement between the number of Li atoms deposited and the number of available
Si bonds at the surface of the SiC crystal. Through STM analysis, we are able
to determine the interlayer distance induced by Li-intercalation at the
interface between the SiC substrate and the buffer layer.


  We show that for every integer $m > 0$, there is an ordinary abelian variety
over ${\mathbb F}_2$ that has exactly $m$ rational points.


  We present results from the JWST First Reionization Epoch Spectroscopically
Complete Observations survey (FRESCO) on the star forming sequence of galaxies
at $1.0<z<1.7$, around the peak of the cosmic star formation history. Star
formation rates (SFRs) are measured from the redshifted, nearly
dust-insensitive Paschen-$\alpha$ emission line, and stellar mass measurements
include the F444W (4.4 $\mu$m; rest-frame H) band. We find SFRs of galaxies
with $M*>9.5 M_\odot$ that are lower than found in many earlier studies by up
to 0.6 dex, but in good agreement with recent results obtained with the
Prospector fitting framework. The difference
log(SFR(Pa$\alpha$)-SFR(Prospector)) is -0.09 $\pm$ 0.04 dex at $10^{10-11}
M_\odot$. We also measure the empirical relation between Paschen-$\alpha$
luminosity and rest-frame H band magnitude and find that the scatter is only
0.04 dex lower than that of the SFR-M* relation and is much lower than the
systematic differences among relations in the literature due to various methods
of converting observed measurements to physical properties. We additionally
identify examples of sources -- that, with standard cutoffs via the UVJ
diagram, would be deemed quiescent -- with significant, typically extended,
Paschen-$\alpha$ emission. Our results may be indicative of the potential
unification of methods used to derive the star forming sequence with careful
selection of star forming galaxies and independent star formation rate and
stellar mass indicators.


  We present new abundances derived from Cu I, Cu II, Zn I, and Zn II lines in
six warm (5766 < Teff < 6427 K), metal-poor (-2.50 < [Fe/H] < -0.95) dwarf and
subgiant (3.64 < log g < 4.44) stars. These abundances are derived from
archival high-resolution ultraviolet spectra from the Space Telescope Imaging
Spectrograph on board the Hubble Space Telescope and ground-based optical
spectra from several observatories. Ionized Cu and Zn are the majority species,
and abundances derived from Cu II and Zn II lines should be largely insensitive
to departures from local thermodynamic equilibrium (LTE). We find good
agreement between the [Zn/H] ratios derived separately from Zn I and Zn II
lines, suggesting that departures from LTE are, at most, minimal (< 0.1 dex).
We find that the [Cu/H] ratios derived from Cu II lines are 0.36 +/- 0.06 dex
larger than those derived from Cu I lines in the most metal-poor stars ([Fe/H]
< -1.8), suggesting that LTE underestimates the Cu abundance derived from Cu I
lines. The deviations decrease in more metal-rich stars. Our results validate
previous theoretical non-LTE calculations for both Cu and Zn, supporting
earlier conclusions that the enhancement of [Zn/Fe] in metal-poor stars is
legitimate, and the deficiency of [Cu/Fe] in metal-poor stars may not be as
large as previously thought.


  We propose the use of dipolaritons -- quantum well excitons with large dipole
moment, coupled to a planar microcavity -- for generating terahertz (THz)
radiation. This is achieved by exciting the system with two THz detuned lasers
that leads to dipole moment oscillations of the exciton polariton at the
detuning frequency, thus generating a THz emission. We have optimized the
structural parameters of a system with microcavity embedded AlGaAs double
quantum wells and shown that the THz emission intensity is maximized if the
laser frequencies both match different dipolariton states. The influence of the
electronic tunnel coupling between the wells on the frequency and intensity of
the THz radiation is also investigated, demonstrating a trade-off between the
polariton dipole moment and the Rabi splitting.


  This paper studies the problem of inferring a global preference based on the
partial rankings provided by many users over different subsets of items
according to the Plackett-Luce model. A question of particular interest is how
to optimally assign items to users for ranking and how many item assignments
are needed to achieve a target estimation error. For a given assignment of
items to users, we first derive an oracle lower bound of the estimation error
that holds even for the more general Thurstone models. Then we show that the
Cram\'er-Rao lower bound and our upper bounds inversely depend on the spectral
gap of the Laplacian of an appropriately defined comparison graph. When the
system is allowed to choose the item assignment, we propose a random assignment
scheme. Our oracle lower bound and upper bounds imply that it is
minimax-optimal up to a logarithmic factor among all assignment schemes and the
lower bound can be achieved by the maximum likelihood estimator as well as
popular rank-breaking schemes that decompose partial rankings into pairwise
comparisons. The numerical experiments corroborate our theoretical findings.


  A search is performed for the production of heavy resonances decaying into
top-antitop quark pairs in proton-proton collisions at sqrt(s) = 8 TeV. Data
used for the analyses were collected with the CMS detector and correspond to an
integrated luminosity of 19.7 inverse femtobarns. The search is performed using
events with three different final states, defined by the number of leptons
(electrons and muons) from the t t-bar to W b W b decay. The analyses are
optimized for reconstruction of top quarks with high Lorentz boosts, where jet
substructure techniques are used to enhance the sensitivity. Results are
presented for all channels and a combination is performed. No significant
excess of events relative to the expected yield from standard model processes
is observed. Upper limits on the production cross section of heavy resonances
decaying to t t-bar are calculated. A narrow leptophobic topcolor Z' resonance
with a mass below 2.4 TeV is excluded at 95% confidence level. Limits are also
derived for a broad Z' resonance with a 10% width relative to the resonance
mass, and a Kaluza-Klein excitation of the gluon in the Randall-Sundrum model.
These are the most stringent limits to date on heavy resonances decaying into
top-antitop quark pairs.


  In this thesis, we study connections between metric and combinatorial graphs
from a Dirichlet space point of view.


  We prove a novel inversion theorem for functionals given as power series in
infinite-dimensional spaces and apply it to the inversion of the
density-activity relation for inhomogeneous systems. This provides a rigorous
framework to prove convergence for density functionals for inhomogeneous
systems with applications in classical density function theory, liquid
crystals, molecules with various shapes or other internal degrees of freedom.
The key technical tool is the representation of the inverse via a fixed point
equation and a combinatorial identity for trees, which allows us to obtain
convergence estimates in situations where Banach inversion fails. Moreover, the
new method for the inversion gives for the (homogeneous) hard sphere gas a
significantly improved radius of convergence for the virial expansion improving
the first and up to now best result by Lebowitz and Penrose (1964).


  We argue that it is not possible to infer from the results of Partridge et
al. (Reports, 27 January 2006, p. 503) which of their data was taken in the
superfluid or normal regime, and which of their clouds are phase-separated and
which are not. Some of the conclusions in this paper are inconsistent with
recent experiments.


  The demand for more transparency of decision-making processes of deep
reinforcement learning agents is greater than ever, due to their increased use
in safety critical and ethically challenging domains such as autonomous
driving. In this empirical study, we address this lack of transparency
following an idea that is inspired by research in the field of neuroscience. We
characterize the learned representations of an agent's policy network through
its activation space and perform partial network ablations to compare the
representations of the healthy and the intentionally damaged networks. We show
that the healthy agent's behavior is characterized by a distinct correlation
pattern between the network's layer activation and the performed actions during
an episode and that network ablations, which cause a strong change of this
pattern, lead to the agent failing its trained control task. Furthermore, the
learned representation of the healthy agent is characterized by a distinct
pattern in its activation space reflecting its different behavioral stages
during an episode, which again, when distorted by network ablations, leads to
the agent failing its trained control task. Concludingly, we argue in favor of
a new perspective on artificial neural networks as objects of empirical
investigations, just as biological neural systems in neuroscientific studies,
paving the way towards a new standard of scientific falsifiability with respect
to research on transparency and interpretability of artificial neural networks.


  We report on the origin of the surface structural disordering in graphite
anodes induced by lithium intercalation and deintercalation processes. Average
Raman spectra of graphitic anodes reveal that cycling at potentials that
correspond to low lithium concentrations in LixC (0 \leq x < 0.16) is
responsible for most of the structural damage observed at the graphite surface.
The extent of surface structural disorder in graphite is significantly reduced
for the anodes that were cycled at potentials where stage-1 and stage-2
compounds (x > 0.33) are present. Electrochemical impedance spectra show larger
interfacial impedance for the electrodes that were fully delithiated during
cycling as compared to electrodes that were cycled at lower potentials (U <
0.15 V vs. Li/Li+). Steep Li+ surface-bulk concentration gradients at the
surface of graphite during early stages of intercalation processes, and the
inherent increase of the LixC d-spacing tend to induce local stresses at the
edges of graphene layers, and lead to the breakage of C-C bonds. The exposed
graphite edge sites react with the electrolyte to (re)form the SEI layer, which
leads to gradual degradation of the graphite anode, and causes reversible
capacity loss in a lithium-ion battery.


  We use both Bayesian and neural models to dissect a data set of Chinese
learners' pre- and post-interventional responses to two tests measuring their
understanding of English prepositions. The results mostly replicate previous
findings from frequentist analyses and newly reveal crucial interactions
between student ability, task type, and stimulus sentence. Given the sparsity
of the data as well as high diversity among learners, the Bayesian method
proves most useful; but we also see potential in using language model
probabilities as predictors of grammaticality and learnability.


  In this paper, we manage to apply Schmidt games to certain non-algebraic
dynamical systems. More precisely, we show that the set of points with
non-dense forward orbit under a $C^2$-Anosov diffeomorphism with conformality
on unstable manifolds is a winning set for Schmidt games. It is also proved
that for a $C^{1+\theta}$-expanding endomorphism the set of points with
non-dense forward orbit is a winning set for certain variants of Schmidt games.


  Quaternary CaO-MgO-Al2O3-SiO2 glasses are important constituents of the
Earth's lower crust and mantle, and they also have important industrial
applications such as in metallurgical processes, concrete production and
emerging low-CO2 cement technologies. In particular, these applications rely
heavily on the composition-structure-reactivity relationships for CMAS glasses,
which are not yet well established. In this study, we developed a robust method
that combines force-field molecular dynamics (MD) simulations and density
functional theory (DFT) calculations with X-ray/neutron scattering experiments
to resolve the atomic structure of a CMAS glass. The final structural
representation generated using this method is not only thermodynamically
favorable (according to DFT calculations) but also agrees with experiments
(including X-ray/neutron scattering data as well as literature data). Detailed
analysis of the final structure (including partial pair distribution functions,
coordination number, oxygen environment) enabled existing discrepancies in the
literature to be reconciled and has revealed new structural information on the
CMAS glass, specifically, (i) the unambiguous assignment of medium-range atomic
ordering, (ii) the preferential role of Ca atoms as charge compensators and Mg
atoms as network modifiers, (iii) the proximity of Mg atoms to free oxygen
sites, and (iv) clustering of Mg atoms. Overall, this new structural
information will enhance our mechanistic understanding on CMAS glass
dissolution behavior, including dissolution-related mechanisms occurring during
the formation of low-CO2 cements.


  Starting from an arbitrary cluster-tilting object $T$ in a 2-Calabi--Yau
category over an algebraically closed field, as in the setting of Keller and
Reiten, we define, for each object $L$, a fraction $X(T,L)$ using a formula
proposed by Caldero and Keller. We show that the map taking $L$ to $X(T,L)$ is
a cluster character, i.e. that it satisfies a certain multiplication formula.
We deduce that it induces a bijection, in the finite and the acyclic case,
between the indecomposable rigid objects of the cluster category and the
cluster variables, which confirms a conjecture of Caldero and Keller.


  Inverted repeat (IR) sequences in DNA can form non-canonical cruciform
structures to relieve torsional stress. We use Monte Carlo simulations of a
recently developed coarse-grained model of DNA to demonstrate that the
nucleation of a cruciform can proceed through a cooperative mechanism. Firstly,
a twist-induced denaturation bubble must diffuse so that its midpoint is near
the centre of symmetry of the IR sequence. Secondly, bubble fluctuations must
be large enough to allow one of the arms to form a small number of hairpin
bonds. Once the first arm is partially formed, the second arm can rapidly grow
to a similar size. Because bubbles can twist back on themselves, they need
considerably fewer bases to resolve torsional stress than the final cruciform
state does. The initially stabilised cruciform therefore continues to grow,
which typically proceeds synchronously, reminiscent of the S-type mechanism of
cruciform formation. By using umbrella sampling techniques we calculate, for
different temperatures and superhelical densities, the free energy as a
function of the number of bonds in each cruciform along the correlated but
non-synchronous nucleation pathways we observed in direct simulations.


  Signals from different modalities each have their own combination algebra
which affects their sampling processing. RGB is mostly linear; depth is a
geometric signal following the operations of mathematical morphology. If a
network obtaining RGB-D input has both kinds of operators available in its
layers, it should be able to give effective output with fewer parameters. In
this paper, morphological elements in conjunction with more familiar linear
modules are used to construct a mixed linear-morphological network called
HaarNet. This is the first large-scale linear-morphological hybrid, evaluated
on a set of sizeable real-world datasets. In the network, morphological Haar
sampling is applied to both feature channels in several layers, which splits
extreme values and high-frequency information such that both can be processed
to improve both modalities. Moreover, morphologically parameterised ReLU is
used, and morphologically-sound up-sampling is applied to obtain a
full-resolution output. Experiments show that HaarNet is competitive with a
state-of-the-art CNN, implying that morphological networks are a promising
research direction for geometry-based learning tasks.


  Using the time-dependent theory of quantum mechanics, we investigate nuclear
electric dipole responses. The time evolution of a wave function is explicitly
calculated in the coordinate-space representation. The particle continuum is
treated with the absorbing boundary condition. Calculated time-dependent
quantities are transformed into those of familiar energy representation. We
apply the method to a three-body model for 11Li and to the mean-field model for
22O, then discuss properties of E1 response.


  We look into the newly observed $\Omega (2012)$ state from the molecular
perspective in which the resonance is generated from the $\bar{K} \Xi^*$, $\eta
\Omega$ and $\bar{K} \Xi$ channels. We find that this picture provides a
natural explanation of the properties of the $\Omega (2012)$ state. We stress
that the molecular nature of the resonance is revealed with a large coupling of
the $\Omega (2012)$ to the $\bar{K} \Xi^*$ channel, that can be observed in the
$\Omega (2012) \rightarrow \bar{K} \pi \Xi$ decay which is incorporated
automatically in our chiral unitary approach via the use of the spectral
function of $\Xi^*$ in the evaluation of the $\bar{K} \Xi^*$ loop function.


  We have investigated the elastic properties of the cubic dense Kondo compound
Ce0.75La0.25B6 by means of ultrasonic measurements. We have obtained magnetic
fields vs temperatures (H-T) phase diagrams under magnetic fields along the
crystallographic [001], [110] and [111] axes. An ordered phase IV showing the
elastic softening of c44 locates in low temperature region between 1.6 and 1.1
K below 0.7 T in all field directions. The phase IV shows an isotropic nature
with regard to the field directions, while the antiferro-magnetic phase III
shows an anisotropic character. A remarkable softening of c44 and a spontaneous
trigonal distortion εyz+εzx+εxy recently reported by Akatsu et
al. [J. Phys. Soc. Jpn. 72 (2003) 205] in the phase IV favor a ferro-quadrupole
(FQ) moment of Oyz+Ozx+Oxy induced by an octupole ordering.


  We experimentally study magnetization reversal curves for MnTe single
crystals, which is the altermagnetic candidate. Above 85~K temperature, we
confirm the antiferromagnetic behavior of magnetization $M$, which is known for
$\alpha$--MnTe. Below 85~K, we observe anomalous low-field magnetization
behavior, which is accompanied by the sophisticated $M(\alpha)$ angle
dependence with beating pattern as the interplay between $M(\alpha)$ maxima and
minima: in low fields, $M(\alpha)$ shows ferromagnetic-like 180$^\circ$
periodicity, while at high magnetic fields, the periodicity is changed to the
90$^\circ$ one. This angle dependence is the most striking result of our
experiment, while it can not be expected for standard magnetic systems. In
contrast, in altermagnets, symmetry allows ferromagnetic behavior only due to
the spin-orbit coupling. Thus, we claim that our experiment shows the effect of
weak spin-orbit coupling in MnTe, with crossover from relativistic to
non-relativistic net magnetization, and, therefore, we experimentally confirm
altermagnetism in MnTe.


  For a given computational problem, a certificate is a piece of data that one
(the prover) attaches to the output with the aim of allowing efficient
verification (by the verifier) that this output is correct. Here, we consider
the minimal approximant basis problem, for which the fastest known algorithms
output a polynomial matrix of dimensions $m \times m$ and average degree $D/m$
using $O\tilde{~}(m^\omega \frac{D}{m})$ field operations. We propose a
certificate which, for typical instances of the problem, is computed by the
prover using $O(m^\omega \frac{D}{m})$ additional field operations and allows
verification of the approximant basis by a Monte Carlo algorithm with cost
bound $O(m^\omega + m D)$.
  Besides theoretical interest, our motivation also comes from the fact that
approximant bases arise in most of the fastest known algorithms for linear
algebra over the univariate polynomials; thus, this work may help in designing
certificates for other polynomial matrix computations. Furthermore,
cryptographic challenges such as breaking records for discrete logarithm
computations or for integer factorization rely in particular on computing
minimal approximant bases for large instances: certificates can then be used to
provide reliable computation on outsourced and error-prone clusters.


  We review the formalism of the effective average action in quantum field
theory which corresponds to a coarse grained free energy in statistical
mechanics. The associated exact renormalization group equation and possible
nonperturbative approximations for its solution are discussed. This is applied
to QCD where one observes the consecutive emergence of mesonic bound states and
spontaneous chiral symmetry breaking as the coarse graining scale is lowered.
We finally present a study of the phenomenological importance of
non--renormalizable terms in the effective linear meson model.


  Federated learning (FL) is a distributed learning paradigm that maximizes the
potential of data-driven models for edge devices without sharing their raw
data. However, devices often have non-independent and identically distributed
(non-IID) data, meaning their local data distributions can vary significantly.
The heterogeneity in input data distributions across devices, commonly referred
to as the feature shift problem, can adversely impact the training convergence
and accuracy of the global model. To analyze the intrinsic causes of the
feature shift problem, we develop a generalization error bound in FL, which
motivates us to propose FedCiR, a client-invariant representation learning
framework that enables clients to extract informative and client-invariant
features. Specifically, we improve the mutual information term between
representations and labels to encourage representations to carry essential
classification knowledge, and diminish the mutual information term between the
client set and representations conditioned on labels to promote representations
of clients to be client-invariant. We further incorporate two regularizers into
the FL framework to bound the mutual information terms with an approximate
global representation distribution to compensate for the absence of the
ground-truth global representation distribution, thus achieving informative and
client-invariant feature extraction. To achieve global representation
distribution approximation, we propose a data-free mechanism performed by the
server without compromising privacy. Extensive experiments demonstrate the
effectiveness of our approach in achieving client-invariant representation
learning and solving the data heterogeneity issue.


  In this paper, we propose a novel touchless typing interface that makes use
of an on-screen QWERTY keyboard and a smartphone camera. The keyboard was
divided into nine color-coded clusters. The user moved their head toward
clusters, which contained the letters that they wanted to type. A front-facing
smartphone camera recorded the head movements. A bidirectional GRU based model
which used pre-trained embedding rich in head pose features was employed to
translate the recordings into cluster sequences. The model achieved an accuracy
of 96.78% and 86.81% under intra- and inter-user scenarios, respectively, over
a dataset of 2234 video sequences collected from 22 users.


  Let $M$ be an exact symplectic manifold with contact type boundary such that
$c_1(M)=0$. In this paper we show that the cyclic cohomology of the Fukaya
category of $M$ has the structure of an involutive Lie bialgebra. Inspired by a
work of Cieliebak-Latschev we show that there is a Lie bialgebra homomorphism
from the linearized contact homology of $M$ to the cyclic cohomology of the
Fukaya category. Our study is also motivated by string topology and
2-dimensional topological conformal field theory.


  A four-fold segmented n-type point-contact "Broad Energy" high-purity
germanium detector, SegBEGe, has been characterised at the Max-Planck-Institut
f\"ur Physik in Munich. The main characteristics of the detector are described
and first measurements concerning the detector properties are presented. The
possibility to use mirror pulses to determine source positions is discussed as
well as charge losses observed close to the core contact.


  A relativistic model for quasielastic (QE) lepton-nucleus scattering is
presented. The effects of final-state interactions (FSI) between the ejected
nucleon and the residual nucleus are described in the relativistic Green's
function (RGF) model where FSI are consistently described with exclusive
scattering using a complex optical potential. The results of the model are
compared with experimental results of electron and neutrino scattering.


  Evolutionary crystal structure prediction proved to be a powerful approach
for studying a wide range of materials. Here, we present a specifically
designed algorithm for the prediction of the structure of complex crystals
consisting of well-defined molecular units. The main feature of this new
approach is that each unit is treated as a whole body, which drastically
reduces the search space and improves the efficiency, but necessitates the
introduction of new variation operators described here. To increase diversity
of the population of structures, the initial population and
part($\scriptsize{\sim}$20%) of the new generations are generated using space
group symmetry combined with random cell parameters and random positions and
orientations of molecular units. We illustrate the efficiency and reliability
of this approach by number of tests (ice, ammonia, carbon dioxide, methane,
benzene, glycine and butane-1,4-diammonium dibromide). This approach easily
predicts the crystal structure of methane \emph{A} containing 21 methane
molecules (105 atoms) per unit cell. We demonstrate that this new approach has
also a high potential for the study of complex inorganic crystals on the
examples of a complex hydrogen storage material Mg(BH$_4$)$_2$ and elemental
boron.


  Cosmic-ray (CR) positrons are relatively rare due to its secondary origin and
thus sensitive to exotic contributions. Primordial black holes (PBHs) with
masses above $\sim 5\times10^{14}\,\mathrm{g}$ can be stable sources of CR
positrons due to Hawking radiation. We show that the CR positron flux measured
by AMS-02 can place stringent constraints on the energy fraction of PBHs
relative to that of dark matter $f_{\text{PBH}}$. Making use of the
state-of-the-art models for CR propagation in both the Galaxy and heliosphere,
we obtain conservative upper limit of $f_{\text{PBH}}\lesssim3\times 10^{-4}$
at $M_{\mathrm{PBH}}\simeq2\times 10^{16}$ g, which improves the previous
constraints obtained from the Voyager CR all-electron data by around an order
of magnitude.


  The current revolution in collaborating distributed things is seen as the
first phase of IoT to develop various services. Such collaboration is
threatened by the fragmentation found in the industry nowadays as it brings
challenges stemming from the difficulty to integrate diverse technologies in
system. Diverse networking technologies induce interoperability issues, hence,
limiting the possibility of reusing the data to develop new services. Different
aspects of handling data collection must be available to provide
interoperability to the diverse objects interacting; however, such approaches
are challenged as they bring substantial performance impairments in settings
with the increasing number of collaborating devices/technologies.


  We investigate the evolution of mass-selected early-type field galaxies using
a sample of 28 gravitational lenses spanning the redshift range 0 < z < 1.
Based on the redshift-dependent intercept of the fundamental plane in the rest
frame B band, we measure an evolution rate of d log (M/L)_B / dz = -0.56 +/-
0.04 (all errors are 1 sigma unless noted) if we directly compare to the local
intercept measured from the Coma cluster. Re-fitting the local intercept helps
minimize potential systematic errors, and yields an evolution rate of d log
(M/L)_B / dz = -0.54 +/- 0.09. An evolution analysis of properly-corrected
aperture mass-to-light ratios (defined by the lensed image separations) is
closely related to the Faber-Jackson relation. In rest frame B band we find an
evolution rate of d log (M/L)_B / dz = -0.41 +/- 0.21, a present-day
characteristic magnitude of M_{*0} = -19.70 + 5 log h +/- 0.29 (assuming a
characteristic velocity dispersion of sigma_{DM*} = 225 km/s), and a
Faber-Jackson slope of gamma_{FJ} = 3.29 +/- 0.58. The measured evolution rates
favor old stellar populations (mean formation redshift z_f > 1.8 at 2 sigma
confidence for a Salpeter initial mass function and a flat Omega_m =0.3
cosmology) among early-type field galaxies, and argue against significant
episodes of star formation at z < 1.


  We present high-resolution images of the Sun in the near ultraviolet spectral
range between 214 nm and 397 nm as obtained from the first science flight of
the 1-m Sunrise balloon-borne solar telescope. The quiet-Sun rms intensity
contrasts found in this wavelength range are among the highest values ever
obtained for quiet-Sun solar surface structures - up to 32.8% at a wavelength
of 214 nm. We compare with theoretical intensity contrasts obtained from
numerical magneto-hydrodynamic simulations. For 388 nm and 312 nm the
observations agree well with the numerical simulations whereas at shorter
wavelengths discrepancies between observed and simulated contrasts remain.


  We present a new method for detection of the integrated Sachs-Wolfe (ISW)
imprints of cosmic superstructures on the cosmic microwave background, based on
a matched filtering approach. The expected signal-to-noise ratio for this
method is comparable to that obtained from the full cross-correlation, and
unlike other stacked filtering techniques it is not subject to an a posteriori
bias. We apply this method to Planck CMB data using voids and superclusters
identified in the CMASS galaxy data from the Sloan Digital Sky Survey Data
Release 12, and measure the ISW amplitude to be $A_\mathrm{ISW}=1.64\pm0.53$
relative to the $\Lambda$CDM expectation, corresponding to a $3.1\sigma$
detection. In contrast to some previous measurements of the ISW effect of
superstructures, our result is in agreement with the $\Lambda$CDM model.


  Recently, concerns regarding potential biases in the underlying algorithms of
many automated systems (including biometrics) have been raised. In this
context, a biased algorithm produces statistically different outcomes for
different groups of individuals based on certain (often protected by
anti-discrimination legislation) attributes such as sex and age. While several
preliminary studies investigating this matter for facial recognition algorithms
do exist, said topic has not yet been addressed for vascular biometric
characteristics. Accordingly, in this paper, several popular types of
recognition algorithms are benchmarked to ascertain the matter for fingervein
recognition. The experimental evaluation suggests lack of bias for the tested
algorithms, although future works with larger datasets are needed to validate
and confirm those preliminary results.


  In this paper, we put forward a connection between the self-interacting dark
matter and the Dirac nature of neutrinos. Our exploration involves a $Z_4
\otimes Z_4'$ discrete symmetry, wherein the Dirac neutrino mass is produced
through a type-I seesaw mechanism. This symmetry not only contributes to the
generation of the Dirac neutrino mass but also facilitates the realization of
self-interacting dark matter with a light mediator that can alleviate
small-scale anomalies of the $\Lambda {\rm CDM}$ while being consistent with
the latter at large scales, as suggested by astrophysical observations. Thus
the stability of the DM and Dirac nature of neutrinos are shown to stem from
the same underlying symmetry. The model also features additional relativistic
degrees of freedom $\Delta N_{\rm eff}$ of either thermal or non-thermal
origin, within the reach of cosmic microwave background (CMB) experiment
providing a complementary probe in addition to the detection prospects of DM.


  We develop a semi-analytical model to describe bound states in the continuum
(BICs) in photonic crystal slabs. We model leaky modes supported by photonic
crystal slabs as a transverse Fabry-Perot resonance composed of a few
propagative Bloch waves bouncing back and forth vertically inside the slab.
This multimode Fabry-Perot model accurately predicts the existence of BICs and
their positions in the parameter space. We show that, regardless of the slab
thickness, BICs cannot exist below a cut-off frequency, which is related to the
existence of the second-order Bloch wave in the photonic crystal. Thanks to the
semi-analyticity of the model, we investigate the dynamics of BICs with the
slab thickness in symmetric and asymmetric photonic crystal slabs. We evidence
that the symmetry-protected BICs that exist in symmetric structures at the
{\Gamma}-point of the dispersion diagram can still exist when the horizontal
mirror symmetry is broken, but only for particular values of the slab
thickness.


  Diffusion of information and viral content, social contagion and influence
are still topics of broad evaluation. As theory explaining the role of
influentials moves slightly to reduce their importance in the propagation of
viral content, authors of the following paper have studied the information
epidemic in a social networking platform in order to confirm recent theoretical
findings in this area. While most of related experiments focus on the level of
individuals, the elementary entities of the following analysis are dyads. The
authors study behavioral motifs that are possible to observe at the dyadic
level. The study shows significant differences between dyads that are more vs
less engaged in the diffusion process. Dyads that fuel the diffusion proccess
are characterized by stronger relationships (higher activity, more common
friends), more active and networked receiving party (higher centrality
measures), and higher authority centrality of person sending a viral message.


  Cascades of a machine learning-based EDFA gain model trained on a single
physical device and a fully differentiable stimulated Raman scattering fiber
model are used to predict and optimize the power profile at the output of an
experimental multi-span fully-loaded C-band optical communication system.


  We consider two neuronal networks coupled by long-range excitatory
interactions. Oscillations in the gamma frequency band are generated within
each network by local inhibition. When long-range excitation is weak, these
oscillations phase-lock with a phase-shift dependent on the strength of local
inhibition. Increasing the strength of long-range excitation induces a
transition to chaos via period-doubling or quasi-periodic scenarios. In the
chaotic regime oscillatory activity undergoes fast temporal decorrelation. The
generality of these dynamical properties is assessed in firing-rate models as
well as in large networks of conductance-based neurons.


  Label-free biosensors are important tools for clinical diagnostics and for
studying biology at the single molecule level. The development of optical
label-free sensors has allowed extreme sensitivity, but can expose the
biological sample to photodamage. Moreover, the fragility and complexity of
these sensors can be prohibitive to applications. To overcome these problems,
we develop a quantum noise limited exposed-core fiber sensor providing robust
platform for label-free biosensing with a natural path toward microfluidic
integration. We demonstrate the detection of single nanoparticles down to 25 nm
in radius with optical intensities beneath known biophysical damage thresholds.


  We report the discovery of a narrow stellar stream crossing the
constellations of Sculptor and Fornax in the Southern celestial hemisphere. The
portion of the stream detected in the Data Release 1 photometry of the ATLAS
survey is at least 12 degrees long, while its width is $\approx$ 0.25 deg. The
Color Magnitude Diagram of this halo sub-structure is consistent with a
metal-poor [Fe/H] $\lesssim -1.4$ stellar population located at a heliocentric
distance of 20 $\pm$ 2 kpc. There are three globular clusters that could
tentatively be associated with the stream: NGC 7006, NGC 7078 (M15) and Pyxis,
but NGC 7006 and 7078 seem to have proper motions incompatible with the stream
orbit.


  We consider a wireless network where each flow (instead of each link) runs
its own CSMA (Carrier Sense Multiple Access) algorithm. Specifically, each flow
attempts to access the radio channel after some random time and transmits a
packet if the channel is sensed idle. We prove that, unlike the standard CSMA
algorithm, this simple distributed access scheme is optimal in the sense that
the network is stable for all traffic intensities in the capacity region of the
network.


  We study the relationship between supermassive black hole (BH) feedback, BH
luminosity and the kinematics of stars and gas for galaxies in IllustrisTNG. We
use a sample of galaxies with mock MaNGA observations to identify kinematic
misalignment at $z=0$ (difference in rotation of stars and gas), for which we
follow the evolutionary history of BH activity and gas properties over the last
8 Gyrs. Misaligned low mass galaxies typically have boosted BH luminosity, BH
growth and have had more energy injected into the gas over the last 8 Gyr in
comparison to aligned galaxies. These properties likely lead to outflows and
gas loss, in agreement with active low mass galaxies in observations. We show
that splitting on BH luminosity at $z=0$ produces statistically consistent
distributions of kinematic misalignment at $z=0$, however, splitting on the
maximum BH luminosity over the last 8 Gyrs does not. While instantaneous
correlation at $z=0$ is difficult due to misalignment persisting on longer
timescales, the relationship between BH activity and misalignment is clear.
High mass quenched galaxies with misalignment typically have similar BH
luminosities, show no overall gas loss, and have typically lower gas phase
metallicity over the last 8 Gyrs in comparison to those aligned; suggesting
external origin.


  The transmission of a pump laser resonant with the lower polariton branch of
a semiconductor microcavity is shown to be highly dependent on the degree of
circular polarization of the pump. Spin dependent anisotropy of
polariton-polariton interactions allows the internal polarization to be
controlled by varying the pump power. The formation of spatial patterns, spin
rings with high degree of circular polarization, arising as a result of
polarization bistability, is observed. A phenomenological model based on spin
dependent Gross-Pitaevskii equations provides a good description of the
experimental results. Inclusion of interactions with the incoherent exciton
reservoir, which provides spin-independent blueshifts of the polariton modes,
is found to be essential.


  The dark matter halo sparsity provides a direct observational proxy of the
halo mass profile, characterizing halos in terms of the ratio of masses within
radii which enclose two different overdensities. Previous numerical simulation
analyses have shown that at a given redshift the halo sparsity carries
cosmological information encoded in the halo mass profile. Moreover, its
ensemble averaged value can be inferred from prior knowledge of the halo mass
function at the overdensities of interest. Here, we present a detailed study of
the ensemble average properties of the halo sparsity. In particular, using halo
catalogs from high-resolution N-body simulations, we show that its ensemble
average value can be estimated from the ratio of the averages of the inverse
halo masses as well as the ratio of the averages of the halo masses at the
overdensity of interests. This can be relevant for galaxy clusters data
analyses. As an example, we have estimated the average sparsity properties of
galaxy clusters from the LoCuSS and HIFLUGCS datasets respectively. The results
suggest that the expected consistency of the different average sparsity
estimates can provide a test of the robustness of mass measurements in galaxy
cluster samples.


  A wide range of applications in science and engineering involve a PDE model
in a domain with perforations, such as perforated metals or air filters.
Solving such perforated domain problems suffers from computational challenges
related to resolving the scale imposed by the geometries of perforations. We
propose a neural network-based mesh-free approach for perforated domain
problems. The method is robust and efficient in capturing various configuration
scales, including the averaged macroscopic behavior of the solution that
involves a multiscale nature induced by small perforations. The new approach
incorporates the derivative-free loss method that uses a stochastic
representation or the Feynman-Kac formulation. In particular, we implement the
Neumann boundary condition for the derivative-free loss method to handle the
interface between the domain and perforations. A suite of stringent numerical
tests is provided to support the proposed method's efficacy in handling various
perforation scales.


  We consider uplink power control in wireless communication when a large
number of users compete over the channel resources. The CDMA protocol, as a
supporting technology of 3G networks accommodating signal from different
sources over the code domain, represents the orthogonal multiple access (OMA)
techniques. With the development of 5G wireless networks, non-orthogonal
multiple access (NOMA) is introduced to improve the efficiency of channel
allocation. Our goal is to investigate whether the power-domain NOMA protocol
can introduce performance improvement when the users interact with each other
in a non-cooperative manner. It is compared with the CDMA protocol, where the
fierce competition among users jeopardizes the efficiency of channel usage. In
this work, we conduct analysis with an aggregative game model, and show the
existence and uniqueness of an equilibrium strategy. Next, we adopt the social
welfare of the population as the performance metric, which is the average
utility achieved by the user population. It is shown that under the
corresponding equilibrium strategies, NOMA outperforms CDMA by higher
efficiency of channel access for uplink communications.


  We analyze the fidelity of a quantum simulation and we show that it displays
fractal fluctuations iff the simulated dynamics is chaotic. This analysis
allows us to investigate a given simulated dynamics without any prior
knowledge. In the case of integrable dynamics, the appearance of fidelity
fractal fluctuations is a signal of a highly corrupted simulation. We
conjecture that fidelity fractal fluctuations are a signature of the appearance
of quantum chaos. Our analysis can be realized already by a few qubit quantum
processor.


  Let $X$ be a Banach space. Then $X$ is complemented in the bidual $X^{**}$ if
and only if there exists an invariant mean $\ell_\infty(G, X)\to X$ with
respect to a free Abelian group $G$ of rank equal to the cardinality of
$X^{**}$, and this happens if and only if there exists an invariant mean with
respect to the additive group of $X^{**}$. This improves upon previous results
due to Bustos Domecq =and the second-named author, where certain idempotent
semigroups of cardinality equal to the cardinality of $X^{**}$ were considered,
and answers a question of J.M.F. Castillo (private communication). En route to
the proof of the main result, we endow the family of all finite-dimensional
subspaces of an infinite-dimensional vector space with a structure of a free
commutative monoid with the property that the product of two subspaces contains
the respective subspaces, which is possibly of interest in itself.


  This work investigated the vorticity dynamics and stability of leading-edge
vortices (LEVs) in revolving wings. Previous studies suggested that Coriolis
acceleration and spanwise flow both played key roles in stabilizing the LEV;
however, the exact mechanism remains unclear. The current study examined a
mechanism that relates the effects of Coriolis acceleration, spanwise flow, and
the tilting of the planetary vortex on limiting the growth of the LEV.
Specifically, this mechanism states that a vertical gradient in spanwise flow
can create a vertical gradient in Coriolis acceleration, which will in turn
produce oppositely-signed vorticity within the LEV. This gradient of Coriolis
acceleration corresponds to the spanwise (radial) component of planetary vortex
tilting (PVTr) that reorients the planetary vortex into the spanwise direction
therefore creating oppositely-signed LEV vorticity. Using an in-house,
immersed-boundary-method flow solver, this mechanism was investigated alongside
the other vorticity dynamics for revolving wings of varying aspect ratio (AR=3,
5, and 7) and Reynolds number (Re=110, and 1400). Analyses of vorticity
dynamics showed that the PVTr consistently produced oppositely-signed vorticity
for all values of AR and Re investigated, although other three-dimensional
phenomena play a similar but more dominant role when Re = 1400. In addition,
the relative strength of the PVTr increased with increasing AR due to a
decrease in the magnitude of advection. Finally, the effects of AR and Re on
the vorticity dynamics and LEV stability were also investigated.


  High voltage (~2 kV) AlGaN-channel HEMTs were fabricated with 64% Aluminum
composition in the channel. The average on-resistance was ~75 ohm. mm (~21
miliohm. cm^2) for LGD = 20 microns. Breakdown voltage reached >3 kV (tool
limit) before passivation however it reduced to ~2 kV after SiN surface
passivation and field plates. The apparent high breakdown voltage prior to
passivation can possibly be attributed to the field plate effect of the charged
trap states of the surface. The breakdown voltage and RON demonstrated a strong
linear correlation in a scattered plot with ~50 measured transistors. In pulsed
IV measurements with 100 microsecond pulse width and 40 V of off-state bias
(tool limit), the dynamic RON increased by ~5% compared to DC RON and current
collapse was <10%.