  The dynamics of frontal and transverse shocks in gaseous detonation waves is
a complex phenomenon bringing many difficulties to both numerical and
experimental research. Advanced laser-optical visualization of detonation
structure may provide certain information of its reactive front, but the
corresponding lead shock needs to be reconstructed building the complete flow
field. Using the Multi-Layer Perceptron (MLP) approach, we propose in this
study a shock front reconstruction method which can predict evolution of the
lead shock wavefront from the state of the reactive front. The method is
verified through the numerical results of one- and two-dimensional unstable
detonations based on the reactive Euler equations with a one-step irreversible
chemical reaction model. Results show that the accuracy of the proposed method
depends on the activation energy of the reactive mixture, which influences
prominently the cellular detonation instability and hence, the distortion of
the lead shock surface. To select the input variables for training and evaluate
their influence on the effectiveness of the proposed method, five groups, one
with six variables and the other with four variables, are tested and analyzed
in the MLP model. The trained MLP is tested in the cases with different
activation energies, demonstrates the inspiring generalization capability. This
paper offers a universal framework for predicting detonation frontal evolution
and provides a novel way to interpret numerical and experimental results of
detonation waves.


  We re-examine the discovery potential at hadron colliders of high-mass
right-handed (RH) gauge bosons $W_R$ - an inherent ingredient of Left-Right
Symmetric Models (LRSM). We focus on the regime where the $W_R$ is very heavy
compared to the heavy Majorana neutrino $N$, and investigate an alternative
signature for $W_R \rightarrow N$ decays. The produced neutrinos are highly
boosted in this mass regime. Subsequently, their decays via off-shell $W_R$
bosons to jets, i.e., $N \rightarrow \ell^\pm j j$ are highly collimated,
forming a single neutrino jet $(j_N)$. The final-state collider signature is
then $\ell^\pm j_N$, instead of the widely studied $\ell^\pm\ell^\pm jj$.
Present search strategies are not sensitive to this hierarchical mass regime
due to the breakdown of the collider signature definition. We take into account
QCD corrections beyond next-to-leading order (NLO) that are important for
high-mass Drell-Yan processes at the 13 TeV Large Hadron Collider (LHC). For
the first time, we evaluate $W_R$ production at NLO with threshold resummation
at next-to-next-to-leading logarithm (NNLL) matched to the threshold-improved
parton distributions. With these improvements, we find that a ${W_R}$ of mass
$M_{W_R} = 3~(4)~[5]$ TeV and mass ratio of $(m_N/M_{W_R})<0.1$ can be
discovered with a $5-6 \sigma$ statistical significance at 13 TeV after
${10~(100)~[2000]~\text{fb}^{-1}}$ of data. Extending the analysis to the
hypothetical 100 TeV Very Large Hadron Collider (VLHC), $5\sigma$ can be
obtained for $W_R$ masses up to $M_{W_R}=15~(30)$ with approximately
$100~\text{fb}^{-1}~(10~\text{ab}^{-1})$.


  This paper presents {\scshape PaSh}, a system for parallelizing POSIX shell
scripts. Given a script, {\scshape PaSh} converts it to a dataflow graph,
performs a series of semantics-preserving program transformations that expose
parallelism, and then converts the dataflow graph back into a script -- one
that adds POSIX constructs to explicitly guide parallelism coupled with
{\scshape PaSh}-provided {\scshape Unix}-aware runtime primitives for
addressing performance- and correctness-related issues. A lightweight
annotation language allows command developers to express key parallelizability
properties about their commands. An accompanying parallelizability study of
POSIX and GNU commands -- two large and commonly used groups -- guides the
annotation language and optimized aggregator library that {\scshape PaSh} uses.
Finally, {\scshape PaSh}'s {\scshape PaSh}'s extensive evaluation over 44
unmodified {\scshape Unix} scripts shows significant speedups
($0.89$--$61.1\times$, avg: $6.7\times$) stemming from the combination of its
program transformations and runtime primitives.


  The temperature and field dependences of the trapped magnetic fields and of
the frozen magnetoresistance of (Pb)Bi-Sr-Ca-Cu-O ceramics and Bi-based
magnetron films are investigated. It is found that in the resistive transition
region of granular Bi-HTSC the trapped magnetic fields become highly
inhomogeneous and alternating in sign at scale of less than 50 microns. Unlike
ceramic the films have critical temperature of trapping lower than the upper
temperature of magnetoresistance disappearance. The experimental results are
explained by a model in which the magnetic fields are trapped in
superconducting loops embedded in Josephson weak links medium. The loops nature
which is essentially different for films and ceramics is discussed. Observed
temperature and field dependences of trapped field are in good agreement with
those calculated for normal law of the loops distribution on critical fields.


  We study the well-known Vertex Cover problem parameterized above and below
tight bounds. We show that two of the parameterizations (both were suggested by
Mahajan, Raman and Sikdar, J. Computer and System Sciences, 75(2):137--153,
2009) are fixed-parameter tractable and two other parameterizations are
W[1]-hard (one of them is, in fact, W[2]-hard).


  The recovery of network structure from experimental data is a basic and
fundamental problem. Unfortunately, experimental data often do not directly
reveal structure due to inherent limitations such as imprecision in timing or
other observation mechanisms. We consider the problem of inferring network
structure in the form of a directed graph from co-occurrence observations. Each
observation arises from a transmission made over the network and indicates
which vertices carry the transmission without explicitly conveying their order
in the path. Without order information, there are an exponential number of
feasible graphs which agree with the observed data equally well. Yet, the basic
physical principles underlying most networks strongly suggest that all feasible
graphs are not equally likely. In particular, vertices that co-occur in many
observations are probably closely connected. Previous approaches to this
problem are based on ad hoc heuristics. We model the experimental observations
as independent realizations of a random walk on the underlying graph, subjected
to a random permutation which accounts for the lack of order information.
Treating the permutations as missing data, we derive an exact
expectation-maximization (EM) algorithm for estimating the random walk
parameters. For long transmission paths the exact E-step may be computationally
intractable, so we also describe an efficient Monte Carlo EM (MCEM) algorithm
and derive conditions which ensure convergence of the MCEM algorithm with high
probability. Simulations and experiments with Internet measurements demonstrate
the promise of this approach.


  The use of complexified quaternions and $i$-complex geometry in formulating
the Dirac equation allows us to give interesting geometric interpretations
hidden in the conventional matrix-based approach.


  Rare-earth ions (REI) have emerged as an attractive candidate for solid-state
qubits, particularly as a quantum memory. Their 4f-4f transitions are shielded
by filled 5s and 5p orbitals, offering a degree of protection from external
electric fields. Embedded within a thin film oxide host, REIs could enable a
qubit platform with significant memory capabilities. Furthermore, a
silicon-compatible thin film form factor would enable the use of standard
semiconductor fabrication processes to achieve chip-based integrability and
scalability for functional quantum networks. Towards this goal, we have carried
out optical and microstructural studies of erbium-doped polycrystalline and
epitaxial TiO$_2$ thin films on Si (100), r-sapphire, and SrTiO$_3$ (100). We
observe that the inhomogeneous optical linewidth of the Er photoluminescence is
comparable or better for polycrystalline Er:TiO$_2$(grown on Si) in comparison
to single crystal epitaxial films on sapphire or SrTiO$_3$, implying a relative
insensitivity to extended defects. We investigated the effect of the
film/substrate and film/air interface and found that the inhomogeneous
linewidth and spectral diffusion can be significantly improved via bottom
buffer and top capping layers of undoped TiO$_2$. Using such approaches, we
obtain inhomogeneous linewidths of 5.2 GHz and spectral diffusion of 180 MHz in
Er:TiO$_2$ /Si(100) films and have demonstrated the engineerability of
quantum-relevant properties in these thin films.


  In this article, we introduce parallel-in-time methods for state and
parameter estimation in general nonlinear non-Gaussian state-space models using
the statistical linear regression and the iterated statistical posterior
linearization paradigms. We also reformulate the proposed methods in a
square-root form, resulting in improved numerical stability while preserving
the parallelization capabilities. We then leverage the fixed-point structure of
our methods to perform likelihood-based parameter estimation in logarithmic
time with respect to the number of observations. Finally, we demonstrate the
practical performance of the methodology with numerical experiments run on a
graphics processing unit (GPU).


  In a series of papers, cited in the main body of the paper below, detailed
calculations have been presented which show that electromagnetic and weak
interactions can induce low energy nuclear reactions to occur with observable
rates for a variety of processes. A common element in all these applications is
that the electromagnetic energy stored in many relatively slow moving electrons
can -under appropriate circumstances- be collectively transferred into fewer,
much faster electrons with energies sufficient for the latter to combine with
protons (or deuterons, if present) to produce neutrons via weak interactions.
The produced neutrons can then initiate low energy nuclear reactions through
further nuclear transmutations. The aim of this paper is to extend and enlarge
upon various examples analyzed previously, present simplified order of
magnitude estimates for each and to illuminate a common unifying theme amongst
all of them.


  In the wireless sensor networks composed of battery-powered sensor nodes, one
of the main issues is how to save power consumption at each node. The usual
approach to this problem is to activate only necessary nodes (e.g., those nodes
which compose a backbone network), and to put other nodes to sleep. One such
algorithm using location information is GAF (Geographical Adaptive Fidelity),
and the GAF is enhanced to HGAF (Hierarchical Geographical Adaptive Fidelity).
In this paper, we show that we can further improve the energy efficiency of
HGAF by modifying the manner of dividing sensor-field. We also provide a
theoretical bound on this problem.


  We prove a number of results on the determinacy of $\sigma$-projective sets
of reals, i.e., those belonging to the smallest pointclass containing the open
sets and closed under complements, countable unions, and projections. We first
prove the equivalence between $\sigma$-projective determinacy and the
determinacy of certain classes of games of variable length ${<}\omega^2$
(Theorem 2.4). We then give an elementary proof of the determinacy of
$\sigma$-projective sets from optimal large-cardinal hypotheses (Theorem 4.4).
Finally, we show how to generalize the proof to obtain proofs of the
determinacy of $\sigma$-projective games of a given countable length and of
games with payoff in the smallest $\sigma$-algebra containing the projective
sets, from corresponding assumptions (Theorems 5.1 and 5.4).


  The influence of the magnetic field shear is studied on the $E\times B$
(and/or Gravitational) and the Current Convective Instabilities (CCI) occuring
in the High latitude F-layer ionosphere. It is shown that magnetic shear
reduces the growth rate of these instabilties. The magnetic shear induced
stabilization is more effective at the larger scale sizes ($\geq$ tens of
kilometers) while at the scintillation causing intermediate scale sizes ($\sim$
a few kms), the growth rate is largely unaffected. The eigen mode structure is
localised about a rational surface due to finite magnetic shear and has broken
reflectional symmetry due to centroid shift of the mode by equilibrium parallel
flow or current.


  Network hypervisors provide the network virtualization layer for Software
Defined Networking (SDN). They enable virtual network (VN) tenants to bring
their SDN controllers to program their logical networks individually according
to their demands. In order to make use of the high flexibility of virtual SDN
networks and to provide high performance, the deployment of the virtualization
layer needs to adapt to changing VN demands. This paper initializes the study
of the optimization of dynamic SDN network virtualization layers. Based on the
definition of reconfiguration events, we formalized mixed integer programs to
analyze the multi-objective problem of adapting virtualization layers. Our
initial simulation results demonstrate Pareto frontiers of conflicting
objectives, namely control plane latency and hypervisor and control path
reconfigurations.


  We establish finite-time singularity formation for $C^{1,\alpha}$ solutions
to the Boussinesq system that are compactly supported on $\mathbb{R}^2$ and
infinitely smooth except in the radial direction at the origin. The solutions
are smooth in the angular variable at the blow-up point, which was a
fundamental obstruction in previous works. This is done by exploiting a
second-order effect, related to the classical Rayleigh--B\'enard instability,
that overcomes the regularizing effect of transport. A similar result is
established for the 3d Euler system based on the Taylor--Couette instability.


  In autonomous aerial navigation, real-time and energy-efficient obstacle
avoidance remains a significant challenge, especially in dynamic and complex
indoor environments. This work presents a novel integration of neuromorphic
event cameras with physics-driven planning algorithms implemented on a Parrot
Bebop2 quadrotor. Neuromorphic event cameras, characterized by their high
dynamic range and low latency, offer significant advantages over traditional
frame-based systems, particularly in poor lighting conditions or during
high-speed maneuvers. We use a DVS camera with a shallow Spiking Neural Network
(SNN) for event-based object detection of a moving ring in real-time in an
indoor lab. Further, we enhance drone control with physics-guided empirical
knowledge inside a neural network training mechanism, to predict
energy-efficient flight paths to fly through the moving ring. This integration
results in a real-time, low-latency navigation system capable of dynamically
responding to environmental changes while minimizing energy consumption. We
detail our hardware setup, control loop, and modifications necessary for
real-world applications, including the challenges of sensor integration without
burdening the flight capabilities. Experimental results demonstrate the
effectiveness of our approach in achieving robust, collision-free, and
energy-efficient flight paths, showcasing the potential of neuromorphic vision
and physics-driven planning in enhancing autonomous navigation systems.


  A classical queuing theory result states that in a parallel-queue
single-server model, the maximum stability region does not depend on the
scheduling decision epochs, and in particular is the same for preemptive and
non-preemptive systems. We consider here the case in which each of the queues
may be connected to the server or not, depending on an exogenous process. In
our main result, we show that the maximum stability region now does strongly
depend on how the decision epochs are defined. We compare the setting where
decisions can be made at any moment in time (the unconstrained setting), to two
other settings: decisions are taken either (i) at moments of a departure
(non-preemptive scheduling), or (ii) when an exponentially clock rings with
rate $\gamma$. We characterise the maximum stability region for the two
constrained configurations, allowing us to observe a reduction compared to the
unconstrained configuration. In the non-preemptive setting, the maximum
stability region is drastically reduced compared to the unconstrained setting
and we conclude that a non-preemptive scheduler cannot take opportunistically
advantage (in terms of stability) of the random varying connectivity. Instead,
for the $\gamma$ decision epochs, we observe that the maximum stability region
is monotone in the rate of the decision moments $\gamma$, and that one can be
arbitrarily close to the maximum stability region in the unconstrained setting
if we choose $\gamma$ large enough. We further show that Serve Longest
Connected (SLC) queue is maximum stable in both constrained settings, within
the set of policies that select a queue among the connected ones. From a
methodological viewpoint, we introduce a novel theoretical tool termed a ``test
for fluid limits'' (TFL) that might be of independent interest. TFL is a simple
test that, if satisfied by the fluid limit, allows us to conclude for
stability.


  We propose Dirichlet Simplex Nest, a class of probabilistic models suitable
for a variety of data types, and develop fast and provably accurate inference
algorithms by accounting for the model's convex geometry and low dimensional
simplicial structure. By exploiting the connection to Voronoi tessellation and
properties of Dirichlet distribution, the proposed inference algorithm is shown
to achieve consistency and strong error bound guarantees on a range of model
settings and data distributions. The effectiveness of our model and the
learning algorithm is demonstrated by simulations and by analyses of text and
financial data.


  Quantitative models of associative learning that explain the behavior of real
animals with high precision have turned out very difficult to construct. We do
this in the context of the dynamics of the thermal preference of C. elegans.
For this, we quantify C. elegans thermotaxis in response to various
conditioning parameters, genetic perturbations, and operant behavior using a
fast, high-throughput microfluidic droplet assay. We then model this data
comprehensively, within a new, biologically interpretable, multi-modal
framework. We discover that the dynamics of thermal preference are described by
two independent contributions and require a model with at least four dynamical
variables. One pathway positively associates the experienced temperature
independently of food and the other negatively associates to the temperature
when food is absent.


  Existing salient object detection methods often adopt deeper and wider
networks for better performance, resulting in heavy computational burden and
slow inference speed. This inspires us to rethink saliency detection to achieve
a favorable balance between efficiency and accuracy. To this end, we design a
lightweight framework while maintaining satisfying competitive accuracy.
Specifically, we propose a novel trilateral decoder framework by decoupling the
U-shape structure into three complementary branches, which are devised to
confront the dilution of semantic context, loss of spatial structure and
absence of boundary detail, respectively. Along with the fusion of three
branches, the coarse segmentation results are gradually refined in structure
details and boundary quality. Without adding additional learnable parameters,
we further propose Scale-Adaptive Pooling Module to obtain multi-scale
receptive filed. In particular, on the premise of inheriting this framework, we
rethink the relationship among accuracy, parameters and speed via network
depth-width tradeoff. With these insightful considerations, we comprehensively
design shallower and narrower models to explore the maximum potential of
lightweight SOD. Our models are purposed for different application
environments: 1) a tiny version CTD-S (1.7M, 125FPS) for resource constrained
devices, 2) a fast version CTD-M (12.6M, 158FPS) for speed-demanding scenarios,
3) a standard version CTD-L (26.5M, 84FPS) for high-performance platforms.
Extensive experiments validate the superiority of our method, which achieves
better efficiency-accuracy balance across five benchmarks.


  Chiral perturbation theory predicts the chiral anomaly to induce a so-called
Chiral Soliton Lattice at sufficiently large magnetic fields and baryon
chemical potentials. This state breaks translational invariance in the
direction of the magnetic field and was shown to be unstable with respect to
charged pion condensation. Improving on previous work by considering a
realistic pion mass, we employ methods from type-II superconductivity and
construct a three-dimensional pion (and baryon) crystal perturbatively, close
to the instability curve of the Chiral Soliton Lattice. We find an analogue of
the usual type-I/type-II transition in superconductivity: Along the instability
curve for magnetic fields $eB > 0.12\, {\rm GeV}^2$ and chemical potentials
$\mu< 910\, {\rm MeV}$, this crystal can continuously supersede the Chiral
Soliton Lattice. For smaller magnetic fields the instability curve must be
preceded by a discontinuous transition.


  In the cooling concept by adiabatic melting, solid $^{4}$He is converted to
liquid and mixed with $^{3}$He to produce cooling power directly in the liquid
phase. This method overcomes the thermal boundary resistance that
conventionally limits the lowest available temperatures in the helium fluids,
and hence makes it possible to reach for the temperatures significantly below
100 $\mu$K. In this paper we focus on the thermodynamics of the melting
process, and examine the factors affecting the lowest temperatures achievable.
We show that the amount of $^{3}$He-$^{4}$He mixture in the initial state,
before the melting, can substantially lift the final temperature, as its normal
Fermi fluid entropy will remain relatively large compared to the entropy of
superfluid $^{3}$He. We present the collection of formulas and parameters in
order to work out the thermodynamics of the process at very low temperatures,
study the heat capacity and entropy of the system with different liquid
$^{3}$He, mixture, and solid $^{4}$He contents, and use them to estimate the
lowest temperatures achievable by the melting process, as well as compare our
calculations to the experimental saturated $^{3}$He-$^{4}$He mixture
crystallization pressure data. Realistic expectations in the execution of the
actual experiment are considered. Further, we study the cooling power of the
process, and find the coefficient connecting the melting rate of solid $^{4}$He
to the dilution rate of $^{3}He$.


  Nonrenormalization theorems involving the transverse, i.e. non anomalous,
part of the <VVA> correlator in perturbative QCD are proven. Some of their
consequences and questions they raise are discussed.


  The detailed process of preparing enriched $^{108}$Cd targets on mylar and
copper backing using the vacuum evaporation technique is described. These
targets were employed in an experiment to measure the proton capture
cross-section at energies significantly below the Coulomb barrier, for the
astrophysical p-process studies. Due to the low melting point and high vapor
pressure of cadmium, some adjustments were implemented in the Telemark
multipocket e-beam setup. The target thickness was determined through the
measurement of alpha particle energy loss from a triple alpha source and also
by RBS measurements. The thickness of the $^{108}$Cd films varies between 290
to 660 $\mu$g/cm$^2$, with a non-uniformity of approximately 10$\%$. X-ray
Photoelectron Spectroscopy (XPS) and X-ray Fluorescence (XRF) analyses were
conducted to examine the presence of impurities and to assess surface
morphology, phase, and chemical composition.


  In this article, we give a brief overview of the current state and future
potential of symbolic computation within the Python statistical modeling and
machine learning community. We detail the use of miniKanren as an underlying
framework for term rewriting and symbolic mathematics, as well as its ability
to orchestrate the use of existing Python libraries. We also discuss the
relevance and potential of relational programming for implementing more robust,
portable, domain-specific "math-level" optimizations--with a slight focus on
Bayesian modeling. Finally, we describe the work going forward and raise some
questions regarding potential cross-overs between statistical modeling and
programming language theory.


  In this paper we study the semiclassical limit for the pseudo-relativistic
Hartree equation $\sqrt{-\varepsilon^2 \Delta + m^2}u + V u = (I_\alpha *
|u|^{p})
  |u|^{p-2}u$ in $\mathbb{R}^N$ where $m>0$, $2 \leq p < \frac{2N}{N-1}$, $V
\colon \mathbb{R}^N \to \mathbb{R}$ is an external scalar potential, $I_\alpha
(x) = \frac{c_{N,\alpha}}{|x|^{N-\alpha}}$ is a convolution kernel,
$c_{N,\alpha}$ is a positive constant and $(N-1)p-N<\alpha <N$. For $N=3$,
$\alpha=p=2$, our equation becomes the pseudo-relativistic Hartree equation
with Coulomb kernel.


  Recognition of mitotic figures in histologic tumor specimens is highly
relevant to patient outcome assessment. This task is challenging for algorithms
and human experts alike, with deterioration of algorithmic performance under
shifts in image representations. Considerable covariate shifts occur when
assessment is performed on different tumor types, images are acquired using
different digitization devices, or specimens are produced in different
laboratories. This observation motivated the inception of the 2022 challenge on
MItosis Domain Generalization (MIDOG 2022). The challenge provided annotated
histologic tumor images from six different domains and evaluated the
algorithmic approaches for mitotic figure detection provided by nine challenge
participants on ten independent domains. Ground truth for mitotic figure
detection was established in two ways: a three-expert consensus and an
independent, immunohistochemistry-assisted set of labels. This work represents
an overview of the challenge tasks, the algorithmic strategies employed by the
participants, and potential factors contributing to their success. With an
$F_1$ score of 0.764 for the top-performing team, we summarize that domain
generalization across various tumor domains is possible with today's deep
learning-based recognition pipelines. However, we also found that domain
characteristics not present in the training set (feline as new species, spindle
cell shape as new morphology and a new scanner) led to small but significant
decreases in performance. When assessed against the
immunohistochemistry-assisted reference standard, all methods resulted in
reduced recall scores, but with only minor changes in the order of participants
in the ranking.


  We discuss dense states of QCD matter formed in high-energy hadronic and
heavy-ion collisions from the point of view of statistical physics of
non-equilibrium processes. For this sake, we first propose a formulation of the
dynamical entropy of dense QCD states in the "saturation regime" leading to a
color glass condensate (CGC). The statistical physics description amounts to
describe the modification of the color correlation length with energy as a
compression process for which non equilibrium thermodynamic properties are
applicable. We derive an expression of the dynamical entropy in terms of the
rapidity evolution of the unintegrated gluon distributions in the colliding
nuclei, verifying suitable positivity and irreversibility properties. We extend
this approach to the initial pre-equilibrium (glasma) state of an heavy-ion
collision. It allows for a definition of the initial entropy before the
evolution towards the hydrodynamic regime as a function of the glasma
correlation length and an overlap parameter characterizing the low-momentum
spectrum of the glasma state. This initial entropy, by extension to the N=4 SYM
theory, is then matched as the key input parameter to the strong coupling
evaluation of thermalization towards the hydrodynamic regime based on the
AdS/CFT correspondence. It thus allows to cast a bridge between the weak and
strong coupling phases of an heavy-ion reaction.


  Material properties depend sensitively on picometer scale atomic
displacements introduced by local chemical fluctuations. Direct real-space,
high spatial-resolution measurements of this compositional variation and
corresponding distortion can provide new insights into materials behavior at
the atomic scale. Using aberration corrected scanning transmission electron
microscopy combined with advanced imaging methods, we observed atom column
specific, picometer-scale displacements induced by local chemistry in a complex
oxide solid solution. Displacements predicted from density functional theory
were found to correlate with the observed experimental trends. Further analysis
of bonding and charge distribution were used to clarify the mechanisms
responsible for the detected structural behavior. By extending the experimental
electron microscopy measurements to previously inaccessible length scales, we
identified correlated atomic displacements linked to bond differences within
the complex oxide structure.


  The absolute/relative debate on the nature of space and time is ongoing for
thousands of years. Here we attempt to investigate space and time from the
information theoretic point of view to understand spatial and temporal
correlations under the relative assumption. Correlations, as a measure of
relationship between two quantities, do not distinguish space and time in
classical probability theory; quantum correlations in space are well-studied
but temporal correlations are not well understood. The thesis investigates
quantum correlations in space-time, by treating temporal correlations equally
in form as spatial correlations and unifying quantum correlations in space and
time. In particular, we follow the pseudo-density matrix formalism in which
quantum states in spacetime are properly defined by correlations from
measurements. We first review classical correlations, quantum correlations in
space and time, to motivate the pseudo-density matrix formalism in finite
dimensions. Next we generalise the pseudo-density matrix formulation to the
Gaussian case, general continuous variables via Wigner representations, and
general measurement processes like weak measurements. Then we compare the
pseudo-density matrix formalism with other spacetime formulations: indefinite
causal structures, consistent histories, generalised non-local games,
out-of-time-order correlation functions, and path integrals. We argue that in
non-relativistic quantum mechanics, different spacetime formulations are
closely related via quantum correlations, except path integrals. Finally, we
apply the pseudo-density matrix formulation to time crystals. By defining time
crystals as long-range order in time, we analyse continuous and discrete time
translation symmetry as well as discuss the existence of time crystals from an
algebraic point of view. Finally, we summarise our work and provide the outlook
for future directions.


  We attempt to detect optical GRB afterglows on images taken by the Canada
France Hawaii Telescope for the Very Wide survey, component of the Legacy
Survey. To do so, a Real Time Analysis System called "Optically Selected GRB
Afterglows" has been installed on a dedicated computer in Hawaii. This pipeline
automatically and quickly analyzes Megacam images and extracts from them a list
of variable objects which is displayed on a web page for validation by a member
of the collaboration. The Very Wide survey covers 1200 square degrees down to
i'=23.5. This paper briefly explain the RTAS process.


  Blockchain is a form of distributed ledger technology (DLT) where data is
shared among users connected over the internet. Transactions are data state
changes on the blockchain that are permanently recorded in a secure and
transparent way without the need of a third party. Besides, the introduction of
smart contracts to the blockchain has added programmability to the blockchain
and revolutionized the software ecosystem leading toward decentralized
applications (DApps) attracting businesses and organizations to employ this
technology. Although promising, blockchains and smart contracts have no access
to the external systems (i.e., off-chain) where real-world data and events
resides; consequently, the usability of smart contracts in terms of performance
and programmability would be limited to the on-chain data. Hence,
\emph{blockchain oracles} are introduced to mitigate the issue and are defined
as trusted third-party services that send and verify the external information
(i.e., feedback) and submit it to smart contracts for triggering state changes
in the blockchain. In this paper, we will study and analyze blockchain oracles
with regard to how they provide feedback to the blockchain and smart contracts.
We classify the blockchain oracle techniques into two major groups such as
voting-based strategies and reputation-based ones. The former mainly relies on
participants' stakes for outcome finalization while the latter considers
reputation in conjunction with authenticity proof mechanisms for data
correctness and integrity. We then provide a structured description of patterns
in detail for each classification and discuss research directions in the end.


  Grover's algorithm has achieved great success. But quantum search algorithms
still are not complete algorithms because of Grover's Oracle. We concerned on
this problem and present a new quantum search algorithm in adiabatic model
without Oracle. We analyze the general difficulties in quantum search
algorithms and show how to solve them in the present algorithm. As well this
algorithm could deal with both single-solution and multi-solution searches
without modification. We also implement this algorithm on NMR quantum computer.
It is the first experiment which perform a real quantum database search rather
than a marked-state search.


  A classical random variable can be faithfully compressed into a sequence of
bits with its expected length lies within one bit of Shannon entropy. We
generalize this variable-length and faithful scenario to the general quantum
source producing mixed states $\rho_i$ with probability $p_i$. In contrast to
the classical case, the optimal compression rate in the limit of large block
length differs from the one in the fixed-length and asymptotically faithful
scenario. The amount of this gap is interpreted as the genuinely quantum part
being incompressible in the former scenario.


  We consider multi-flavor QED on a finite lattice at a finite chemical
potential and show that the partition function only depends on the variables,
$(\frac{\mu_i}{q_i} -\frac{\mu_1}{q_1})$, for $i=2,...$, where $q_i$, $i=1...$
are integer valued charges of the various flavors and $\mu_i$, $i=1...$ are the
dimensional chemical potentials of the various flavors.


  One of the most striking predictions of quantum electrodynamics is that
vacuum fluctuations of the electromagnetic field can lead to spontaneous
emission of atoms as well as photon-mediated interactions among them. Since
these processes strongly depend on the nature of the photonic bath, a current
burgeoning field is the study of their modification in the presence of photons
with non-trivial energy dispersions, e.g., the ones confined in photonic
crystals. A remarkable example is the case of isotropic Dirac-photons, which
has been recently shown to lead to non-exponential spontaneous emission as well
as dissipation-less long-range emitter interactions. In this work, we show how
to further tune these processes by considering anisotropic Dirac cone
dispersions, which include tilted, semi-Dirac, and the recently discovered type
II and III Dirac points. In particular, we show how by changing the anisotropy
of the lattice one can change both the spatial shape of the interactions as
well as its coherent/incoherent nature. Finally, we discuss a possible
implementation where these energy dispersions can be engineered and interfaced
with quantum emitters based on subwavelength atomic arrays.


  Discrete analogs of the index transforms with squares of Bessel functions of
the first and second kind $J_\nu(z),\ Y_\nu(z)$ are introduced and
investigated. The corresponding inversion theorems for suitable classes of
functions and sequences are established.


  Food image recognition is one of the promising applications of visual object
recognition in computer vision. In this study, a small-scale dataset consisting
of 5822 images of ten categories and a five-layer CNN was constructed to
recognize these images. The bag-of-features (BoF) model coupled with support
vector machine (SVM) was first evaluated for image classification, resulting in
an overall accuracy of 56%; while the CNN model performed much better with an
overall accuracy of 74%. Data augmentation techniques based on geometric
transformation were applied to increase the size of training images, which
achieved a significantly improved accuracy of more than 90% while preventing
the overfitting issue that occurred to the CNN based on raw training data.
Further improvements can be expected by collecting more images and optimizing
the network architecture and hyper-parameters.


  Data augmentation methods in combination with deep neural networks have been
used extensively in computer vision on classification tasks, achieving great
success; however, their use in time series classification is still at an early
stage. This is even more so in the field of financial prediction, where data
tends to be small, noisy and non-stationary. In this paper we evaluate several
augmentation methods applied to stocks datasets using two state-of-the-art deep
learning models. The results show that several augmentation methods
significantly improve financial performance when used in combination with a
trading strategy. For a relatively small dataset ($\approx30K$ samples),
augmentation methods achieve up to $400\%$ improvement in risk adjusted return
performance; for a larger stock dataset ($\approx300K$ samples), results show
up to $40\%$ improvement.


  We characterize the late-time scaling state of dry, coarsening,
two-dimensional froths using a detailed, force-based vertex model. We find that
the slow evolution of bubbles leads to systematic deviations from 120degree
angles at three-fold vertices in the froth, with an amplitude proportional to
the vertex speed, v ~ sqrt(t), but with a side-number dependence that is
independent of time. We also find that a significant number of T1
side-switching processes occur for macroscopic bubbles in the scaling state,
though most bubble annihilations involve four-sided bubbles at microscopic
scales.


  An expository approach is given on the relationship between algebraic and
geometric approaches to properties of isometries in the plane and the 2-sphere.


  The gravitational waveform of a merging stellar-mass binary is described at
leading order by a quadrupolar mode. However, the complete waveform includes
higher-order modes, which encode valuable information not accessible from the
leading-order mode alone. Despite this, the majority of astrophysical
inferences so far obtained with observations of gravitational waves employ only
the leading order mode because calculations with higher-order modes are often
computationally challenging. We show how to efficiently incorporate
higher-order modes into astrophysical inference calculations with a two step
procedure. First, we carry out Bayesian parameter estimation using a
computationally cheap leading-order-mode waveform, which provides an initial
estimate of binary parameters. Second, we weight the initial estimate using
higher-order mode waveforms in order to fold in the extra information from the
full waveform. We use mock data to demonstrate the effectiveness of this
method. We apply the method to each binary black hole event in the first
gravitational-wave transient catalog GWTC-1 to obtain posterior distributions
and Bayesian evidence with higher-order modes. Performing Bayesian model
selection on the events in GWTC-1, we find only a weak preference for waveforms
with higher order modes. We discuss how this method can be generalized to a
variety of other applications.


  The history and the main results of the energy scan program at the CERN SPS
are reviewed. Several anomalies in energy dependence of hadron production
predicted as signals of deconfinement phase transition are observed and they
indicate that the onset of deconfinement is located at about 30 A GeV. For the
first time we seem to have clear evidence for the existence of a deconfined
state of matter in nature.


  We perform the complete regularization of all Green functions with a single
incoming and outgoing baryon to order q^3 in the low energy expansion for the
SU(3) meson-baryon system in chiral perturbation theory. The divergences can be
extracted in a chiral invariant manner by making use of the heat kernel
representation of the propagators in d-dimensional Euclidean space.


  We study the continuity regularity of functions in the complex Sobolev
spaces. As applications, we obtain Hermitian generalizations of a recent result
due Guedj-Guenancia-Zeriahi on the diameters of Kaehler metrics.


  The magnetic moments of heavy $\Xi_{Q}$ baryons containing a single charm or
bottom quark are calculated in the framework of light cone QCD sum rules
method. A comparison of our results with the predictions of the quark models is
presented.


  We report on a search for the flavor-changing neutral current decay $D^0 \to
\mu^+\mu^-$ using $50 \times 10^6$ events recorded with a dimuon trigger in
interactions of 920 GeV protons with nuclei by the HERA-B experiment. We find
no evidence for such decays and set a 90% confidence level upper limit on the
branching fraction $Br(D^0 \to \mu^+\mu^-) <2.0 \times 10^{-6}$.


  Just as knots and links can be algebraically described as certain morphisms
in the category of tangles in 3 dimensions, compact surfaces smoothly embedded
in R^4 can be described as certain 2-morphisms in the 2-category of `2-tangles
in 4 dimensions'. Using the work of Carter, Rieger and Saito, we prove that
this 2-category is the `free semistrict braided monoidal 2-category with duals
on one unframed self-dual object'. By this universal property, any unframed
self-dual object in a braided monoidal 2-category with duals determines an
invariant of 2-tangles in 4 dimensions.


  We present new GMRT observations of HDF 130, an inverse-Compton (IC) ghost of
a giant radio source that is no longer being powered by jets. We compare the
properties of HDF 130 with the new and important constraint of the upper limit
of the radio flux density at 240 MHz to an analytic model. We learn what values
of physical parameters in the model for the dynamics and evolution of the radio
luminosity and X-ray luminosity (due to IC scattering of the cosmic microwave
background (CMB)) of a Fanaroff-Riley II (FR II) source are able to describe a
source with features (lobe length, axial ratio, X-ray luminosity, photon index
and upper limit of radio luminosity) similar to the observations. HDF 130 is
found to agree with the interpretation that it is an IC ghost of a powerful
double-lobed radio source, and we are observing it at least a few Myr after jet
activity (which lasted 5--100 Myr) has ceased. The minimum Lorentz factor of
injected particles into the lobes from the hotspot is preferred to be
$\gamma\sim10^3$ for the model to describe the observed quantities well,
assuming that the magnetic energy density, electron energy density, and lobe
pressure at time of injection into the lobe are linked by constant factors
according to a minimum energy argument, so that the minimum Lorentz factor is
constrained by the lobe pressure. We also apply the model to match the features
of 6C 0905+3955, a classical double FR II galaxy thought to have a low-energy
cutoff of $\gamma\sim10^4$ in the hotspot due to a lack of hotspot
inverse-Compton X-ray emission. The models suggest that the low-energy cutoff
in the hotspots of 6C 0905+3955 is $\gamma\gtrsim 10^3$, just slightly above
the particles required for X-ray emission.


  I discuss recent work (gr-qc/0001047) on non-oscillatory singularities in
four dimensional space-times with scalar field or stiff fluid matter, in the
context of the BKL proposal.


  We developed a spectroscopic monitoring project to investigate the kinematics
of the broad-line region (BLR) in active galactic nuclei (AGN) with ultra-fast
outflows (UFOs). Mrk~79 is a radio-quiet AGN with UFOs and warm absorbers, had
been monitored by three reverberation mapping (RM) campaigns, but its BLR
kinematics is not understood yet. In this paper, we report the results from a
new RM-campaign of Mrk~79, which was undertaken by Lijiang 2.4-m telescope.
Mrk~79 is seeming to come out the faint state, the mean flux approximates a
magnitude fainter than historical record. We successfully measured the lags of
the broad emission lines including H$\beta~\lambda4861$, H$\gamma~\lambda4340$,
He II $\lambda4686$ and He I $\lambda5876$ with respect to the varying AGN
continuum. Based on the broad H$\beta~\lambda4861$ line, we measured black hole
(BH) mass of $M_{\bullet}=5.13^{+1.57}_{-1.55}\times10^{7}M_{\odot}$, estimated
accretion rates of ${\dot{M}_{\bullet}}=(0.05\pm0.02)~L_{\rm Edd}~c^{-2}$,
indicating that Mrk~79 is a sub-Eddington accretor. We found that Mrk~79
deviates from the canonical Radius$-$Luminosity relationship. The marginal
blueshift of the broad He II $\lambda4686$ line detected from rms spectrum
indicates outflow of high-ionization gas. The velocity-resolved lag profiles of
the broad H$\gamma~\lambda4340$, H$\beta~\lambda4861$, and He I $\lambda5876$
lines show similar signatures that the largest lag occurs in the red wing of
the lines then the lag decreases to both sides. These signatures should suggest
that the BLR of Keplerian motion probably exists the outflow gas motion. All
findings including UFOs, warm absorbers, and the kinematics of high- and
low-ionization BLR, may provide an indirect evidence that the BLR of Mrk~79
probably originates from disk wind.


  We present cluster decay studies of $^{56}$Ni$^*$ formed in heavy-ion
collisions using different Skyrme forces. Our study reveals that different
Skyrme forces do not alter the transfer structure of fractional yields
significantly. The cluster decay half-lives of different clusters lies within
\pm 10% for PCM and \pm 15% for UFM.


  Rapid rotation in massive stars imposes a latitudinal variation in the mass
loss from radiatively driven winds that can lead to enhanced mass loss at the
poles (with little angular momentum loss) and/or equator (with maximal angular
momentum loss). Here we present an examination of the stellar wind lines of the
two O-type stars with the fastest known equatorial velocities, VFTS 102 ($V\sin
i = 610 \pm 30$ km/s; O9:Vnnne+) and VFTS 285 ($V\sin i = 609 \pm 29$ km/s;
O7.5 Vnnn) in the Large Magellanic Cloud. Ultraviolet spectra of both stars
were obtained with the Hubble Space Telescope Cosmic Origins Spectrograph. The
spectrum of VFTS 285 displays a fast outflow in N V and a much slower wind in
Si IV, and we argue that there is a two-wind regime in which mass loss is
strong at the poles (fast and tenuous wind) but dominant at the equator (slow
and dense winds). These ions and wind lines are not present in the spectrum of
the cooler star VFTS 102, but the double-peaked H$\alpha$ emission in its
spectrum implies equatorial mass loss into a circumstellar disk. The results
suggest that in the fastest rotating O-stars, most mass is lost as an
equatorial outflow, promoting angular momentum loss that contributes to a spin
down over time.


  Surface plasmon polaritons (SPPs) propagating along a waveguide working
electrode are sensitive to changes in local refractive index, which follow
changes in the concentration of reduced and oxidised species near the working
electrode. The real-time response of the output optical power from a waveguide
working electrode is proportional to the time convolution of the
electrochemical current density, precluding the need to compute the latter a
posteriori via numerical integration. The theoretical optical response of a
waveguide working electrode is derived, and validated experimentally via
chronoamperometry and cyclic voltammetry measurements under low power SPP
excitation, for various concentrations of potassium ferricyanide in potassium
nitrate electrolyte at various scan rates. Increasing the SPP power induces a
regime where the SPPs no longer act solely as a probe of electrochemical
activity, but also as a pump creating energetic electrons and holes via
absorption in the working electrode. In this regime the transfer of energetic
carriers (electrons and holes) to the redox species dominates the
electrochemical current density, which becomes significantly enhanced relative
to equilibrium (low SPP power) conditions. In this regime the output optical
power remains proportional to the time convolution of the current density, even
with the latter significantly enhanced by the transfer of energetic carriers.


  Tungsten oxide and its associated bronzes (compounds of tungsten oxide and an
alkali metal) are well known for their interesting optical and electrical
characteristics. We have modified the transport properties of thin WO$_3$ films
by electrolyte gating using both ionic liquids and polymer electrolytes. We are
able to tune the resistivity of the gated film by more than five orders of
magnitude, and a clear insulator-to-metal transition is observed. To clarify
the doping mechanism, we have performed a series of incisive operando
experiments, ruling out both a purely electronic effect (charge accumulation
near the interface) and oxygen-related mechanisms. We propose instead that
hydrogen intercalation is responsible for doping WO$_3$ into a highly
conductive ground state and provide evidence that it can be described as a
dense polaronic gas.


  An effect of metallization of the magnonic crystal surface on the band gaps
formation in the spectra of the surface spin wave (SSW) is studied both
theoretically and experimentally. The structures under consideration are
one-dimensional magnonic crystals based on yttrium iron garnet with an array of
etched grooves with metal screen on the top of the corrugated surface and
without it. Due to nonreciprocity of propagation of the SSW the shift of band
gap to higher frequency and from the border of the Brillouin zone in presence
of conducting overlayer was measured in transmission line experiment. Results
of numerical calculations and model analysis are in agreement with experimental
data and give further insight into origin of the band gap and properties of the
nonreciprocal SSW in metallized magnonic crystals. This gives positive answer
to the outstanding question about possibility of detection of magnonic band
gaps in the spectra of the spin waves with nonreciprocal dispersion in magnonic
crystals and creates potential for new applications and improvements of already
existing prototype magnonic devices.


  Many real-world applications operate on dynamic graphs that undergo rapid
changes in their topological structure over time. However, it is challenging to
design dynamic algorithms that are capable of supporting such graph changes
efficiently. To circumvent the challenge, we propose a batch-dynamic framework
for answering distance queries, which combines offline labelling and online
searching to leverage the advantages from both sides - accelerating query
processing through a partial distance labelling that is of limited size but
provides a good approximation to bound online searches. We devise batch-dynamic
algorithms to dynamize a distance labelling efficiently in order to reflect
batch updates on the underlying graph. In addition to providing theoretical
analysis for the correctness, labelling minimality, and computational
complexity, we have conducted experiments on 14 real-world networks to
empirically verify the efficiency and scalability of the proposed algorithms.


  Efficient algorithms for the calculation of minimum energy paths of magnetic
transitions are implemented within the geodesic nudged elastic band (GNEB)
approach. While an objective function is not available for GNEB and a
traditional line search can, therefore, not be performed, the use of limited
memory Broyden-Fletcher-Goldfarb-Shanno (LBFGS) and conjugate gradient
algorithms in conjunction with orthogonal spin optimization (OSO) approach is
shown to greatly outperform the previously used velocity projection and
dissipative Landau-Lifschitz dynamics optimization methods. The implementation
makes use of energy weighted springs for the distribution of the discretization
points along the path and this is found to improve performance significantly.
The various methods are applied to several test problems using a
Heisenberg-type Hamiltonian, extended in some cases to include
Dzyaloshinskii-Moriya and exchange interactions beyond nearest neighbours.
Minimum energy paths are found for magnetization reversals in a nano-island,
collapse of skyrmions in two-dimensional layers and annihilation of a chiral
bobber near the surface of a three-dimensional magnet. The LBFGS-OSO method is
found to outperform the dynamics based approaches by up to a factor of 8 in
some cases.


  With the improvements of computing technology, more and more applications
embed powerful ARM processors into their devices. These systems can be attacked
by redirecting the control-flow of a program to bypass critical pieces of code
such as privilege checks or signature verifications. Control-flow hijacks can
be performed using classical software vulnerabilities, physical fault attacks,
or software-induced fault attacks. To cope with this threat and to protect the
control-flow, dedicated countermeasures are needed. To counteract control-flow
hijacks, control-flow integrity~(CFI) aims to be a generic solution. However,
software-based CFI typically either protects against software or fault attacks,
but not against both. While hardware-assisted CFI can mitigate both types of
attacks, they require extensive hardware modifications. As hardware changes are
unrealistic for existing ARM architectures, a wide range of systems remains
unprotected and vulnerable to control-flow attacks.
  In this work, we present FIPAC, an efficient software-based CFI scheme
protecting the execution at basic block granularity of ARM-based devices
against software and fault attacks. FIPAC exploits ARM pointer authentication
of ARMv8.6-A to implement a cryptographically signed control-flow graph. We
cryptographically link the correct sequence of executed basic blocks to enforce
CFI at this granularity. We use an LLVM-based toolchain to automatically
instrument programs. The evaluation on SPEC2017 with different security
policies shows a code overhead between 54-97\% and a runtime overhead between
35-105%. While these overheads are higher than for countermeasures against
software attacks, FIPAC outperforms related work protecting the control-flow
against fault attacks. FIPAC is an efficient solution to provide protection
against software- and fault-based CFI attacks on basic block level on modern
ARM devices.


  Research on gender and language is tightly knitted to social debates on
gender equality and non-discriminatory language use. Psycholinguistic scholars
have made significant contributions in this field. However, corpus-based
studies that investigate these matters within the context of language use are
still rare. In our study, we address the question of how much textual material
would actually have to be changed if non-gender-inclusive texts were rewritten
to be gender-inclusive. This quantitative measure is an important empirical
insight, as a recurring argument against the use of gender-inclusive German is
that it supposedly makes written texts too long and complicated. It is also
argued that gender-inclusive language has negative effects on language
learners. However, such effects are only likely if gender-inclusive texts are
very different from those that are not gender-inclusive. In our
corpus-linguistic study, we manually annotated German press texts to identify
the parts that would have to be changed. Our results show that, on average,
less than 1% of all tokens would be affected by gender-inclusive language. This
small proportion calls into question whether gender-inclusive German presents a
substantial barrier to understanding and learning the language, particularly
when we take into account the potential complexities of interpreting masculine
generics.


  Multiple myeloma (MM), a plasma cell cancer, is associated with many health
challenges, including damage to the kidney by tubulointerstitial fibrosis. We
develop a mathematical model which captures the qualitative behavior of the
cell and protein populations involved. Specifically, we model the interaction
between cells in the proximal tubule of the kidney, free light chains, renal
fibroblasts, and myeloma cells. We analyze the model for steady-state solutions
to find a mathematically and biologically relevant stable steady-state
solution. This foundational model provides a representation of dynamics between
key populations in tubulointerstitial fibrosis that demonstrates how these
populations interact to affect patient prognosis in patients with MM and renal
impairment.


  Let X be Drinfeld's half space over a p-adic field K. The de Rham cohomology
of X was first computed by Schneider and Stuhler. Afterwards there were given
different proofs by Alon, de Shalit, Iovita and Spiess. This paper presents yet
another approach for the determination of these invariants by analysing the de
Rham complex of X from the viewpoint of recent results by the author.


  Using real-space view of high harmonic generation (HHG) in solids, we develop
a physically transparent and gauge-invariant approach for distinguishing
intraband and interband HHG mechanisms. Our approach relies on resolving the
harmonic emission according to the separation between Wannier states involved
in radiative transitions. We show that the intra- and inter-band HHG emission
exhibit striking qualitative differences in their dependence on this separation
and can be clearly distinguished using the Wannier basis.


  By considering radiative corrections of up to 3rd-loop order, Ritus and
Narozhny conjectured that the proper expansion parameter for QED in a strong
constant crossed field is $g=\alpha\chi^{2/3}$, where the dynamical quantum
parameter $\chi=e\sqrt{-(Fp)^2}/m^3$ combines the particle momentum $p$ with
the external field strength tensor $F$. Here we present and discuss the first
non-perturbative result in this context, the resummed bubble-type polarization
corrections to the electron self-energy in a constant crossed field. Our
analysis confirms the relevance of the scaling parameter $g$ to the enhancement
of bubble-type radiative corrections. This parameter actually represents the
characteristic value of the ratio of the 1-loop polarization bubble to the
photon virtuality. After an all-order resummation we identify and discuss two
contributions to the self-energy with different formation regions and
asymptotic behavior for $g\gg1$. Whereas the breakdown of perturbation theory
occurs already for $g\gtrsim1$, the leading-order result remains dominant until
the asymptotic regime $g\gg 1$ is reached. However, the latter is specific to
processes like elastic scattering or photon emission and does not have to
remain true for general higher-order QED processes.


  We study the problem of training a model that must obey demographic fairness
conditions when the sensitive features are not available at training time -- in
other words, how can we train a model to be fair by race when we don't have
data about race? We adopt a fairness pipeline perspective, in which an
"upstream" learner that does have access to the sensitive features will learn a
proxy model for these features from the other attributes. The goal of the proxy
is to allow a general "downstream" learner -- with minimal assumptions on their
prediction task -- to be able to use the proxy to train a model that is fair
with respect to the true sensitive features. We show that obeying multiaccuracy
constraints with respect to the downstream model class suffices for this
purpose, provide sample- and oracle efficient-algorithms and generalization
bounds for learning such proxies, and conduct an experimental evaluation. In
general, multiaccuracy is much easier to satisfy than classification accuracy,
and can be satisfied even when the sensitive features are hard to predict.


  We construct level one dominant representations of the affine Kac-Moody
algebra $\widehat{\mathfrak{gl}}_k$ on the equivariant cohomology groups of
moduli spaces of rank one framed sheaves on the orbifold compactification of
the minimal resolution $X_k$ of the $A_{k-1}$ toric singularity
$\mathbb{C}^2/\mathbb{Z}_k$. We show that the direct sum of the fundamental
classes of these moduli spaces is a Whittaker vector for
$\widehat{\mathfrak{gl}}_k$, which proves the AGT correspondence for pure
$\mathcal{N}=2$ $U(1)$ gauge theory on $X_k$. We consider Carlsson-Okounkov
type Ext-bundles over products of the moduli spaces and use their Euler classes
to define vertex operators. Under the decomposition
$\widehat{\mathfrak{gl}}_k\simeq \mathfrak{h}\oplus \widehat{\mathfrak{sl}}_k$,
these vertex operators decompose as products of bosonic exponentials associated
to the Heisenberg algebra $\mathfrak{h}$ and primary fields of
$\widehat{\mathfrak{sl}}_k$. We use these operators to prove the AGT
correspondence for $\mathcal{N}=2$ superconformal abelian quiver gauge theories
on $X_k$.


  We analyze the annihilation of equally-charged particles based on the
Brownian motion model built by F. Dyson for $N$ particles with charge $q$
interacting via the log-Coulomb potential on the unitary circle at a reduced
inverse temperature $\beta$, defined as $\beta=q^2/(k_B T)$. We derive an
analytical approach in order to describe the large-$t$ asymptotic behaviour for
the number density decay, which can be described as a power law, i.e., $n\sim
t^{-\nu}$. For a sufficiently large $\beta$, the power law exponent $\nu$
behaves as $(\beta +1)^{-1}$, which was corroborated through several
computational simulations. For small $\beta$, in the diffusive regime, we
recover the exponent of 1/2 as predicted by single-species uncharged
annihilation.


  The multiple-input multiple-output (MIMO) detection problem, a fundamental
problem in modern digital communications, is to detect a vector of transmitted
symbols from the noisy outputs of a fading MIMO channel. The maximum likelihood
detector can be formulated as a complex least-squares problem with discrete
variables, which is NP-hard in general. Various semidefinite relaxation (SDR)
methods have been proposed in the literature to solve the problem due to their
polynomial-time worst-case complexity and good detection error rate
performance. In this paper, we consider two popular classes of SDR-based
detectors and study the conditions under which the SDRs are tight and the
relationship between different SDR models. For the enhanced complex and real
SDRs proposed recently by Lu et al., we refine their analysis and derive the
necessary and sufficient condition for the complex SDR to be tight, as well as
a necessary condition for the real SDR to be tight. In contrast, we also show
that another SDR proposed by Mobasher et al. is not tight with high probability
under mild conditions. Moreover, we establish a general theorem that shows the
equivalence between two subsets of positive semidefinite matrices in different
dimensions by exploiting a special "separable" structure in the constraints.
Our theorem recovers two existing equivalence results of SDRs defined in
different settings and has the potential to find other applications due to its
generality.


  Company engagement in open source (OSS) is now the new norm. From large
technology companies to startups, companies are participating in the OSS
ecosystem by open-sourcing their technology, sponsoring projects through
funding or paid developer time. However, our understanding of the OSS ecosystem
is rooted in the 'old world' model where individual contributors sustain OSS
projects. In this work, we create a more comprehensive understanding of the
hybrid OSS landscape by investigating what motivates companies to contribute
and how they contribute to OSS. We conducted interviews with 20 participants
who have different roles (e.g., CEO, OSPO Lead, Ecosystem Strategist) at 17
different companies of different sizes from large companies (e.g. Microsoft,
RedHat, Google, Spotify) to startups. Data from semi-structured interviews
reveal that company motivations can be categorized into four levels (Founders'
Vision, Reputation, Business Advantage, and Reciprocity) and companies
participate through different mechanisms (e.g., Developers' Time, Mentoring
Time, Advocacy & Promotion Time), each of which tie to the different types of
motivations. We hope our findings nudge more companies to participate in the
OSS ecosystem, helping make it robust, diverse, and sustainable.


  The discrepancy between the Standard Model theory and experimental
measurement of the muon magnetic moment anomaly,
$a_{\mu}=\left(g_{\mu}-2\right)/2$, is connected to precision electroweak (EW)
predictions via their common dependence on hadronic vacuum polarization
effects. The same data for the total $e^+e^- \rightarrow \text{hadrons}$ cross
section, $\sigma_{\rm had}(s)$, are used as input into dispersion relations to
estimate the hadronic vacuum polarization contributions, $a_{\mu}^{\rm
had,\,VP}$, as well as the five-flavor hadronic contribution to the running QED
coupling at the $Z$-pole, $\Delta\alpha_{\rm had}^{(5)}(M_{Z}^2)$, which enters
natural relations and global EW fits. The EW fit prediction of
$\Delta\alpha_{\rm had}^{(5)}(M_{Z}^2) = 0.02722(41)$ agrees well with
$\Delta\alpha_{\rm had}^{(5)}(M_{Z}^2) = 0.02761(11)$ obtained from the
dispersion relation approach, but exhibits a smaller central value suggestive
of a larger discrepancy $\Delta a_{\mu}=a_{\mu}^{\rm exp} - a_{\mu}^{\rm SM}$
than currently expected. Postulating that the $\Delta a_{\mu}$ difference may
be due to missing $\sigma_{\rm had}(s)$ contributions, implications for $M_W$,
$\sin^2 \! \theta^{\rm lep}_{\rm eff}$ and $M_H$ obtained from global EW fits
are investigated. Shifts in $\sigma_{\rm had}(s)$ needed to bridge $\Delta
a_{\mu}$ are found to be excluded above $\sqrt{s} \gtrsim 0.7$ GeV at the
95\%CL. Moreover, prospects for $\Delta a_{\mu}$ originating below that energy
are deemed improbable given the required increases in the cross section. Such
hypothetical changes to the hadronic data are also found to affect other
related observables, such as the electron anomaly, $a_e^{\rm SM}$, the ratio
$R_{e/\mu} = (m_\mu/m_e)^2 (a_{e}^{\rm had,\,LO\,VP}/a_{\mu}^{\rm
had,\,LO\,VP})$ and the running of the weak mixing angle at low energies,
although the consequences of these are currently less constraining.


  It is known that for the Heisenberg XXZ spin-$\frac{1}{2}$ chain in the
critical regime, the scaling limit of the vacuum Bethe roots yields an infinite
set of numbers that coincide with the energy spectrum of the quantum mechanical
3D anharmonic oscillator. The discovery of this curious relation, among others,
gave rise to the approach referred to as the ODE/IQFT (or ODE/IM)
correspondence. Here we consider a multiparametric generalization of the
Heisenberg spin chain, which is associated with the inhomogeneous six-vertex
model. When quasi-periodic boundary conditions are imposed the lattice system
may be explored within the Bethe Ansatz technique. We argue that for the
critical spin chain, with a properly formulated scaling limit, the scaled Bethe
roots for the ground state are described by second order differential
equations, which are multi-parametric generalizations of the Schr\"{o}dinger
equation for the anharmonic oscillator.


  A Bott tower is the total space of a tower of fibre bundles with base CP^1
and fibres CP^1. Every Bott tower of height n is a smooth projective toric
variety whose moment polytope is combinatorially equivalent to an n-cube. A
circle action is semifree if it is free on the complement to fixed points. We
show that a (quasi)toric manifold (in the sense of Davis-Januszkiewicz) over an
n-cube with a semifree circle action and isolated fixed points is a Bott tower.
Then we show that every Bott tower obtained in this way is topologically
trivial, that is, homeomorphic to a product of 2-spheres. This extends a recent
result of Ilinskii, who showed that a smooth compact toric variety with a
semifree circle action and isolated fixed points is homeomorphic to a product
of 2-spheres, and makes a further step towards our understanding of a problem
motivated by Hattori's work on semifree circle actions. Finally, we show that
if the cohomology ring of a quasitoric manifold (or Bott tower) is isomorphic
to that of a product of 2-spheres, then the manifold is homeomorphic to the
product.


  Seismic data interpolation of irregularly missing traces plays a crucial role
in subsurface imaging, enabling accurate analysis and interpretation throughout
the seismic processing workflow. Despite the widespread exploration of deep
supervised learning methods for seismic data reconstruction, several challenges
still remain open. Particularly, the requirement of extensive training data and
poor domain generalization due to the seismic survey's variability poses
significant issues. To overcome these limitations, this paper introduces a
deep-learning-based seismic data reconstruction approach that leverages data
redundancy. This method involves a two-stage training process. First, an
adversarial generative network (GAN) is trained using synthetic seismic data,
enabling the extraction and learning of their primary and local seismic
characteristics. Second, a reconstruction network is trained with synthetic
data generated by the GAN, which dynamically adjusts the noise and distortion
level at each epoch to promote feature diversity. This approach enhances the
generalization capabilities of the reconstruction network by allowing control
over the generation of seismic patterns from the latent space of the GAN,
thereby reducing the dependency on large seismic databases. Experimental
results on field and synthetic seismic datasets both pre-stack and post-stack
show that the proposed method outperforms the baseline supervised learning and
unsupervised approaches such as deep seismic prior and internal learning, by up
to 8 dB of PSNR.


  Unhappily, there has been a maelstrom of problems for dark matter theories
over the last few years and many serious difficulties still have no resolution
in sight. This article reviews the evidence for dark matter in galaxies. The
haloes built up by hierarchical merging in dark matter cosmogonies are cusped
and dominated by dark matter at the center. Evidence from the microlensing
optical depth towards Baade's Window and from dynamical modelling of the
Galactic bar already suggests that the Galactic halo is not cusped. Similarly,
evidence from the stability of unbarred disk galaxies, as well as the survival
of fast bars in barred galaxies, suggests that the this result holds good more
generally. Judged on the data from galactic scales alone, the case for dark
matter is weak and non-standard theories of gravity provide a better
description. Of course, non-standard theories of gravity have their own
problems, but not on galactic scales.


  Fermi Large Area Telescope (LAT) has recently detected 8 gamma-ray
millisecond pulsars (MSPs), providing an unprecedented opportunity to probe the
magnetospheres of these low-spin-down pulsars. We performed 3D emission
modeling, including various Special Relativistic effects, in the context of
pair-starved polar cap (PSPC), slot gap (SG), and outer gap (OG) pulsar models.
Most of the light curves are best fit by SG and OG models, surprisingly
indicating the presence of narrow accelerating gaps limited by robust pair
production. All model fits imply high-altitude emission, and we observe
exclusive differentiation of the current gamma-ray MSP population into two
sub-classes: light curve shapes and lags across wavebands impose either PSPC or
SG / OG-type geometries.


  We study actions of pointed Hopf algebras in the $\ZZ$-graded setting. Our
main result classifies inner-faithful actions of generalized Taft algebras on
quantum generalized Weyl algebras which respect the $\ZZ$-grading. We also show
that generically the invariant rings of Taft actions on quantum generalized
Weyl algebras are commutative Kleinian singularities.


  We propose the use of automatic differentiation through the programming
framework jax for accelerating a variety of analysis tasks throughout
gravitational wave (GW) science. Firstly, we demonstrate that complete
waveforms which cover the inspiral, merger, and ringdown of binary black holes
(i.e. IMRPhenomD) can be written in jax and demonstrate that the serial
evaluation speed of the waveform (and its derivative) is similar to the
lalsuite implementation in C. Moreover, jax allows for GPU-accelerated waveform
calls which can be over an order of magnitude faster than serial evaluation on
a CPU. We then focus on three applications where efficient and differentiable
waveforms are essential. Firstly, we demonstrate how gradient descent can be
used to optimize the $\sim 200$ coefficients that are used to calibrate the
waveform model. In particular, we demonstrate that the typical match with
numerical relativity waveforms can be improved by more than 50% without any
additional overhead. Secondly, we show that Fisher forecasting calculations can
be sped up by $\sim 100\times$ (on a CPU) with no loss in accuracy. This
increased speed makes population forecasting substantially simpler. Finally, we
show that gradient-based samplers like Hamiltonian Monte Carlo lead to
significantly reduced autocorrelation values when compared to traditional Monte
Carlo methods. Since differentiable waveforms have substantial advantages for a
variety of tasks throughout GW science, we propose that waveform developers use
jax to build new waveforms moving forward. Our waveform code, ripple, can be
found at https://github.com/tedwards2412/ripple, and will continue to be
updated with new waveforms as they are implemented.


  We consider solutions of the non-linear von Neumann equation involving
Jacobi's elliptic functions sn, cn, and dn, and 3 linearly independent
operators. In two cases one can construct a state-dependent Hamiltonian which
is such that the corresponding non-linear von Neumann equation is solved by the
given density operator. We prove that in a certain context these two cases are
the only possibilities to obtain special solutions of this kind. Well-known
solutions of the reduced Maxwell-Bloch equations produce examples of each of
the two cases. Also known solutions of the non-linear von Neumann equation in
dimension 3 are reproduced by the present approach.


  The overall {\it steady}-state energy balance with two phases in a flow
domain requires that the change in energy of the domain is equal to the
difference between the total energy entering the domain and that leaving the
domain. From the condition, the integral thermal flux across the surface is
studied for a {\it steady} thermocapillary drop migration in a flow field with
uniform temperature gradient at small and large Marangoni (Reynolds) numbers.
The drop is assumed to have only a slight axisymmetric deformation from a
sphere. It is identified that a conservative/nonconservative integral thermal
flux across the surface in the {\it steady} thermocapillary drop migration at
small/large Marangoni (Reynolds) numbers. The conservative flux confirms the
assumption of {\it quasi-steady} state in the thermocapillary drop migration at
small Marangoni (Reynolds) numbers. The nonconservative flux may well result
from the invalid assumption of {\it quasi-steady} state, which indicates that
the thermocapillary drop migration at large Marangoni (Reynolds) numbers cannot
reach {\it steady} state and is thus a {\it unsteady} process.


  Extracting Empirical Green's Functions (EGFs) by cross-correlating ambient
seismic noise or coda, considered as an efficient approach of retrieving new
response inside the media of two receivers, has been developed well in the past
two decades. However, EGFs emerge with high Signal-to-Noise Ratios (SNRs),
which needs us to stack a large number of cross-correlations. Here, we retrieve
EGFs with high SNRs from ambient seismic noise released by hurricane Dorian
moving along the eastern coast of the United States during 3 days in Sept 2019.
We systematically analyze the energy sources of seismic noise records with
time-frequency analysis and beam-forming. We find that the energy exhibits very
strongly when hurricane Dorian progresses along the coast from 4th to 6th Sept.
Our results suggest that EGFs exhibit strong directionality and only emerge in
the negative part of cross-correlation time functions due to the noise sources
of Dorian. We extract clear multimodal dispersion curves of Rayleigh waves from
retrieved EGFs. Our results, indeed, reveal that multimodal dispersion curves
pf Rayleigh wave could be extracted from ambient seismic noise excited by
Dorian for several days or even a single day, which means that we enlarge the
seismic data sets for the future work of investigating shear velocity
structures of the Earth's crust and upper mantle and understanding our planet
more deeply.


  Automation in farming processes is a growing field of research in both
academia and industries. A considerable amount of work has been put into this
field to develop systems robust enough for farming. Terrace farming, in
particular, provides a varying set of challenges, including robust stair
climbing methods and stable navigation in unstructured terrains. We propose the
design of a novel autonomous terrace farming robot, Aarohi, that can
effectively climb steep terraces of considerable heights and execute several
farming operations. The design optimisation strategy for the overall mechanical
structure is elucidated. Further, the embedded and software architecture along
with fail-safe strategies are presented for a working prototype. Algorithms for
autonomous traversal over the terrace steps using the scissor lift mechanism
and performing various farming operations have also been discussed. The
adaptability of the design to specific operational requirements and modular
farm tools allow Aarohi to be customised for a wide variety of use cases.


  Weakly interacting quantum fluids allow for a natural kinetic theory
description which takes into account the fermionic or bosonic nature of the
interacting particles. In the simplest cases, one arrives at the
Boltzmann-Nordheim equations for the reduced density matrix of the fluid. We
discuss here two related topics: the kinetic theory of the fermionic Hubbard
model, in which conservation of total spin results in an additional Vlasov type
term in the Boltzmann equation, and the relation between kinetic theory and
thermalization.


  We show a control algorithm to guide a robotic walking assistant along a
planned path. The control strategy exploits the electromechanical brakes
mounted on the back wheels of the walker. In order to reduce the hardware
requirements we adopt a Bang Bang approach relying of four actions (with
saturated value for the braking torques).When the platform is far away from the
path, we execute an approach phase in which the walker converges toward the
platform with a specified angle. When it comes in proximity of the platform,
the control strategy switches to a path tracking mode, which uses the four
control actions to converge toward the path with an angle which is a function
of the state. This way it is possible to control the vehicle in feedback,
secure a gentle convergence of the user to the planned path and her steady
progress towards the destination.


  Unpaired image-to-image translation using Generative Adversarial Networks
(GAN) is successful in converting images among multiple domains. Moreover,
recent studies have shown a way to diversify the outputs of the generator.
However, since there are no restrictions on how the generator diversifies the
results, it is likely to translate some unexpected features. In this paper, we
propose Style-Restricted GAN (SRGAN) to demonstrate the importance of
controlling the encoded features used in style diversifying process. More
specifically, instead of KL divergence loss, we adopt three new losses to
restrict the distribution of the encoded features: batch KL divergence loss,
correlation loss, and histogram imitation loss. Further, the encoder is
pre-trained with classification tasks before being used in translation process.
The study reports quantitative as well as qualitative results with Precision,
Recall, Density, and Coverage. The proposed three losses lead to the
enhancement of the level of diversity compared to the conventional KL loss. In
particular, SRGAN is found to be successful in translating with higher
diversity and without changing the class-unrelated features in the CelebA face
dataset. To conclude, the importance of the encoded features being
well-regulated was proven with two experiments. Our implementation is available
at https://github.com/shinshoji01/Style-Restricted_GAN.


  Electron-impact cross sections for the dissociation process of vibrationally
excited He2+ molecular ion, as a function of the incident electron energy are
calculated for the dissociative transition X2\Sigma+u \to A2\Sigma+g by using
the R-matrix method in the adiabatic-nuclei approximation. The potential energy
curves for the involved electronic states and target properties, also
calculated with the R-matrix method, were found to be in good agreement with
the results reported in literature.


  We investigate $\eta/s$ in linear scalar fields modified Gauss-Bonnet theory
that breaks translation invariance. We first calculate $\eta/s$ both
analytically and numerically and show its relationship with temperature in
log-log plot. Our results show that $\eta/s\sim T^2$ at low temperatures. The
causality is also considered in this work. We then find that causality
violation still happens in the presence of the linear scalar field and we
suggest there is a Gauss-Bonnet coupling dependent lower limit for the
effective mass of the graviton. If the effective mass of the graviton is big
enough, then there will be no causality violation and hence no constraints for
the Gauss-Bonnet coupling.


  Rhetorical Structure Theory implies no single discourse interpretation of a
text, and the limitations of RST parsers further exacerbate inconsistent
parsing of similar structures. Therefore, it is important to take into account
that the same argumentative structure can be found in semantically similar
texts with varying rhetorical structures. In this work, the differences between
paraphrases within the same argument scheme are evaluated from a rhetorical
perspective. The study proposes a deep dependency parsing model to assess the
connection between rhetorical and argument structures. The model utilizes
rhetorical relations; RST structures of paraphrases serve as training data
augmentations. The method allows for end-to-end argumentation analysis using a
rhetorical tree instead of a word sequence. It is evaluated on the bilingual
Microtexts corpus, and the first results on fully-fledged argument parsing for
the Russian version of the corpus are reported. The results suggest that
argument mining can benefit from multiple variants of discourse structure.


  We define a new cohomology for associative algebras which we compute for
algebras with units.


  Cosmic far-infrared background (CFIRB) probes unresolved dusty star-forming
galaxies across cosmic time and is complementary to ultraviolet and optical
observations of galaxy evolution. In this work, we interpret the observed CFIRB
anisotropies using an empirical model based on resolved galaxies in ultraviolet
and optical surveys. Our model includes stellar mass functions, star-forming
main sequence, and dust attenuation. We find that the commonly used linear
Kennicutt relation between infrared luminosity and star formation rate
overproduces the observed CFIRB amplitudes. The observed CFIRB requires that
low-mass galaxies have lower infrared luminosities than expected from the
Kennicutt relation, implying that low-mass galaxies have lower dust content and
weaker dust attenuation. Our results demonstrate that CFIRB not only provides a
stringent consistency check for galaxy evolution models but also constrains the
dust content of low-mass galaxies.


  State-of-the-art fluid dynamical simulations of relativistic heavy-ion
collisions employ initial state models which result in a rather strong radial
flow. In order to fit the experimental observables, a non-negligible bulk
viscosity of the QGP and/or hadronic matter is required. We examine modern
parametrizations of the bulk viscosity to entropy density ratio $\zeta/s$ used
in recent fluid dynamical simulations, and explore the relative magnitude of
the associated bulk viscous corrections in space-time, for Pb-Pb and p-Pb
collisions at $\sqrt{s_{\rm NN}}=2.76$ TeV LHC energy with a state-of-the-art
initial state provided by TRENTo model. It turns out that, at a typical
particlization hypersurface, the effect of bulk viscosity out-competes the one
of shear viscosity, and in a significantly large part of the space-time volume,
the bulk pressure strongly counteracts the equilibrium pressure, thus the
effective pressure approaches zero. The latter potentially challenges the
applicability of fluid-dynamical modelling of heavy ion-ion and proton-ion
collisions at the LHC energies.


  First results on charged hadron transverse momentum spectra in pp collisions
obtained by the CMS Collaboration at LHC were analyzed in z-scaling approach.
The first LHC data confirm z-scaling. The saturation regime of the scaling
function psi(z) observed in pp and antp-pp interactions at lower energy sqrt s
= 19-1960 GeV is verified. The saturation of psi(z) for charged hadrons is
found down to z=0.05 at the highest energy sqrt s = 2360 GeV reached till now
at colliders. A microscopic scenario of hadron production is discussed in
connection with search for new signatures of phase transitions in hadron
matter. Constituent energy loss and its dependencies on the transverse momentum
of charged hadrons and collision energy are estimated. The beam energy scan at
LHC in the saturation region is suggested.


  We establish a dichotomy for the rate of the decay of the Ces\`aro averages
of correlations of sufficiently regular functions for typical interval exchange
transformations (IET) which are not rigid rotations (for which weak mixing had
been previously established in the works of Katok-Stepin, Veech, and
Avila-Forni). We show that the rate of decay is either logarithmic or
polynomial, according to whether the IET is of rotation class (i.e., it can be
obtained as the induced map of a rigid rotation) or not. In the latter case, we
also establish that the spectral measures of Lipschitz functions have local
dimension bounded away from zero (by a constant depending only on the number of
intervals). In our approach, upper bounds are obtained through estimates of
twisted Birkhoff sums of Lipschitz functions, while the logarithmic lower
bounds are based on the slow deviation of ergodic averages that govern the
relation between rigid rotations and their induced maps.


  The frog model is an infection process in which dormant particles begin
moving and infecting others once they become infected. We show that on the
rooted $d$-ary tree with particle density $\Omega(d^2)$, the set of visited
sites contains a linearly expanding ball and the number of visits to the root
grows linearly with high probability.


  We present a systematic study of the dynamical scaling process leading to the
establishment of the Kolmogorov--Zakharov (KZ) spectrum in weak 3-wave
turbulence. In the finite capacity case, in which the transient spectrum
reaches infinite frequency in finite time, the dynamical scaling exponent is
anomalous in the sense that it cannot be determined from dimensional
considerations. As a consequence, the transient spectrum preceding the
establishment of the steady state is steeper than the KZ spectrum. Constant
energy flux is actually established from right to left in frequency space after
the singularity of the transient solution. From arguments based on entropy
production, a steeper transient spectrum is heuristically plausible.


  Kilonovae are generally believed to originate from the ejecta of binary
neutron stars (NSs) or black hole and NS mergers. Free neutrons might be
retained in the outermost layer of the ejecta to produce a precursor via
$\beta$-decay. During the propagation of kilonovae to observers, a small
percentage of them might be gravitationally lensed by foreground objects. In
this paper, three lens models, i.e., the point-mass model, the singular
isothermal sphere (SIS) model, and the Chang-Refsdal model, were taken into
consideration to explore the light curves and polarizations of gravitationally
lensed kilonovae. We found that if the time delay between two images exceeds
the ejecta heating timescale for the lens mass $\sim 10^{10}~M_\odot$ in the
SIS model, a tiny bump-like signal will be generated in the light curve, and
the total luminosity will be magnified in all cases. The polarization of lensed
kilonovae is significantly enhanced in most cases. Future detections of lensed
kilonovae will impose constraints on the morphology of the ejecta and aid in
the determination of the nature of compact object mergers and the search for
strong gravitational lenses.


  We study the spectral norm of N-dimensional hermitian random matrices whose
entries are zero outside of the band of the width b along the principal
diagonal. Inside this band the elements are given by gaussian centered jointly
independent random variables with the variance of the order 1/b. We show that
if b tends to infinity faster than the third power of log N, then the spectral
norm is bounded with probability 1.


  Natural language interfaces (NLIs) provide users with a convenient way to
interactively analyze data through natural language queries. Nevertheless,
interactive data analysis is a demanding process, especially for novice data
analysts. When exploring large and complex SQL databases from different
domains, data analysts do not necessarily have sufficient knowledge about
different data tables and application domains. It makes them unable to
systematically elicit a series of topically-related and meaningful queries for
insight discovery in target domains. We develop a NLI with a step-wise query
recommendation module to assist users in choosing appropriate next-step
exploration actions. The system adopts a data-driven approach to suggest
semantically relevant and context-aware queries for application domains of
users' interest based on their query logs. Also, the system helps users
organize query histories and results into a dashboard to communicate the
discovered data insights. With a comparative user study, we show that our
system can facilitate a more effective and systematic data analysis process
than a baseline without the recommendation module.


  We present measurements of the fluorine abundance in a Galactic Bulge
Asymptotic Giant Branch (AGB) star. The measurements were performed using high
resolution K-band spectra obtained with the CRIRES spectrograph, which has been
recently installed at ESO's VLT, together with state-of-the-art model
atmospheres and synthetic spectra. This represents the first fluorine abundance
measurement in a Galactic Bulge star, and one of few measurements of this kind
in a third dredge-up oxygen-rich AGB star. The F abundance is found to be close
to the solar value scaled down to the metallicity of the star, and in agreement
with Disk giants that are comparable to the Bulge giant studied here. The
measurement is of astrophysical interest also because the star's mass can be
estimated rather accurately ($1.4 \lesssim M/\mathrm{M}_{\sun} \lesssim 2.0$).
AGB nucleosynthesis models predict only a very mild enrichment of F in such low
mass AGB stars. Thus, we suggest that the fluorine abundance found in the
studied star is representative for the star's natal cloud, and that fluorine
must have been produced at a similar level in the Bulge and in the Disk.


  We study collinear and soft singularities in perturbative quantum gravity by
constructing an effective field theory similar to soft-collinear effective
theory for QCD (SCET). We find that the soft sector exhibits factorization
properties similar to those of SCET. The collinear sector is, however, quite
different. While the leading-power collinear effective Lagrangian is trivial,
the presence of the metric field $h_{++}$ with negative scaling dimension
allows for collinear divergences in loop diagrams with couplings to
non-collinear sources. We provide a compact proof of the well-known fact that
there are no collinear singularities in perturbative quantum gravity by
demonstrating the decoupling of $h_{++}$ from the sources. We briefly discuss
the connection of our approach to recent work by Akhoury et al. (Phys. Rev. D84
(2011) 104040) as well as to the Weinberg's original paper (Phys. Rev. 140
(1965) B516), where the cancellation of the collinear singularities was
demonstrated for the first time in the eikonal approximation.


  We study the new case of the application of the JKLMR conjecture on the
connection between the exact partition functions of $\mathcal{N}=(2,2)$
supersymmetric gauged linear sigma models (GLSM) on $S^2$ and special K\"ahler
geometry on the moduli spaces of Calabi-Yau manifold $Y$. The last ones arise
as manifolds of the supersymmetric vacua of the GLSM. We establish this
correspondence using the Mirror symmetry in Batyrev's approach. Namely,
starting from the two-moduli non-Fermat Calabi-Yau manifold $X$ we construct
the dual GLSM with the supersymmetric vacua $Y$, which is the mirror for $X$.
Knowing the special geometry on the complex moduli space of $X$ we verify the
mirror version of the JKLMR conjecture by explicit computation.


  In this paper, we study the holographic R\'enyi entropy of a large interval
on a circle at high temperature for the two-dimensional conformal field theory
(CFT) dual to pure AdS$_3$ gravity. In the field theory, the R\'enyi entropy is
encoded in the CFT partition function on $n$-sheeted torus connected with each
other by a large branch cut. As proposed by Chen and Wu [Large interval limit
of R\'enyi entropy at high temperature, arXiv:1412.0763], the effective way to
read the entropy in the large interval limit is to insert a complete set of
state bases of the twist sector at the branch cut. Then the calculation
transforms into an expansion of four-point functions in the twist sector with
respect to $e^{-\frac{2\pi TR}{n}}$. By using the operator product expansion of
the twist operators at the branch points, we read the first few terms of the
R\'enyi entropy, including the leading and next-to-leading contributions in the
large central charge limit. Moreover, we show that the leading contribution is
actually captured by the twist vacuum module. In this case by the Ward identity
the four-point functions can be derived from the correlation function of four
twist operators, which is related to double interval entanglement entropy.
Holographically, we apply the recipe in [T. Faulkner, The entanglement R\'enyi
entropies of disjoint intervals in AdS/CFT, arXiv:1303.7221] and [T. Barrella
et al., Holographic entanglement beyond classical gravity, J. High Energy Phys.
09 (2013) 109] to compute the classical R\'enyi entropy and its one-loop
quantum correction, after imposing a new set of monodromy conditions. The
holographic classical result matches exactly with the leading contribution in
the field theory up to $e^{-4\pi TR}$ and $l^6$, while the holographical
one-loop contribution is in exact agreement with next-to-leading results in
field theory up to $e^{-\frac{6\pi TR}{n}}$ and $l^4$ as well.


  In a recent paper, Rovelli responds to our critical assessment of Relational
Quantum Mechanics (RQM). His main argument is that our assessment lacks merit,
because we fail to understand, or cope with, the premises of his theory;
instead, he argues, we judge his proposal, blinded by the preconceptions
inherent to ``our camp''. Here, we explicitly show that our assessment judges
RQM on its own terms, together with the basic requirements of precision,
clarity, logical soundness and empirical suitability. Under those
circumstances, we prove false Rovelli's claim that RQM provides a satisfactory,
realistic, non-solipsistic description of the world. Moreover, his reply serves
us to further exhibit the serious problems of the RQM proposal, as well as the
failures of its author to understanding the basic conceptual difficulties of
quantum theory.


  We obtain non-linear kinetic equations for sterile neutrino occupancies and
lepton minus baryon numbers by matching real time correlation functions of
thermal fluctuations computed in an effective description to those computed in
thermal quantum field theory. After expanding in the sterile-neutrino Yukawa
couplings, the coefficients in the equations are written as real time
correlation functions of Standard Model operators. Our kinetic equations are
valid for an arbitrary number of sterile neutrinos of any mass spectrum. They
can be used to describe, e.g., low-scale leptogenesis via neutrino
oscillations, or sterile neutrino dark matter production in the Higgs phase.


  In this short note, we study quantum walks (QWs) on one dimensional lattice
$\delta \mathbb{Z}$. Following Hong-Yang, we prove Strichartz estimates for QWs
independent of the lattice width $\delta$.