  Parkinson's disease (PD) is a chronic, degenerative neurological disorder. PD
cannot be prevented, slowed or cured as of today but highly effective
symptomatic treatments are available. We consider relevant estimands and
treatment effect estimators for randomized trials of a novel treatment which
aims to slow down disease progression versus placebo in early, untreated PD. A
commonly used endpoint in PD trials is the MDS-Unified Parkinson's Disease
Rating Scale (MDS-UPDRS), which is longitudinally assessed at scheduled visits.
The most important intercurrent events (ICEs) which affect the interpretation
of the MDS-UPDRS are study treatment discontinuations and initiations of
symptomatic treatment. Different estimand strategies are discussed and
hypothetical or treatment policy strategies, respectively, for different types
of ICEs seem most appropriate in this context. Several estimators based on
multiple imputation which target these estimands are proposed and compared in
terms of bias, mean-squared error, and power in a simulation study. The
investigated estimators include methods based on a missing-at-random (MAR)
assumption, with and without the inclusion of time-varying ICE-indicators, as
well as reference-based imputation methods. Simulation parameters are motivated
by data analyses of a cohort study from the Parkinson's Progression Markers
Initiative (PPMI).


  This paper presents competitive algorithms for a novel class of online
optimization problems with memory. We consider a setting where the learner
seeks to minimize the sum of a hitting cost and a switching cost that depends
on the previous $p$ decisions. This setting generalizes Smoothed Online Convex
Optimization. The proposed approach, Optimistic Regularized Online Balanced
Descent, achieves a constant, dimension-free competitive ratio. Further, we
show a connection between online optimization with memory and online control
with adversarial disturbances. This connection, in turn, leads to a new
constant-competitive policy for a rich class of online control problems.


  We revisit the gradient descent dynamics of the spherical
Sherrington-Kirkpatrick ($p=2$) model with finite number of degrees of freedom.
For fully random initial conditions we confirm that the relaxation takes place
in three time regimes: a first algebraic one controlled by the decay of the
eigenvalue distribution of the random exchange interaction matrix at its edge
in the infinite size limit; a faster algebraic one determined by the
distribution of the gap between the two extreme eigenvalues; and a final
exponential one determined by the minimal gap sampled in the disorder average.
We also analyse the finite size effects on the relaxation from initial states
which are almost projected on the saddles of the potential energy landscape,
and we show that for deviations scaling as $N^{-\nu}$ from perfect alignment
the system escapes the initial configuration in a time-scale scaling as $\ln N$
after which the dynamics no longer "self-averages" with respect to the initial
conditions. We prove these statements with a combination of analytic and
numerical methods.


  We introduce a combinatorial variant of the cost sharing problem: several
services can be provided to each player and each player values every
combination of services differently. A publicly known cost function specifies
the cost of providing every possible combination of services. A combinatorial
cost sharing mechanism is a protocol that decides which services each player
gets and at what price. We look for dominant strategy mechanisms that are
(economically) efficient and cover the cost, ideally without overcharging
(i.e., budget balanced). Note that unlike the standard cost sharing setting,
combinatorial cost sharing is a multi-parameter domain. This makes designing
dominant strategy mechanisms with good guarantees a challenging task.
  We present the Potential Mechanism -- a combination of the VCG mechanism and
a well-known tool from the theory of cooperative games: Hart and Mas-Colell's
potential function. The potential mechanism is a dominant strategy mechanism
that always covers the incurred cost. When the cost function is subadditive the
same mechanism is also approximately efficient. Our main technical contribution
shows that when the cost function is submodular the potential mechanism is
approximately budget balanced in three settings: supermodular valuations,
symmetric cost function and general symmetric valuations, and two players with
general valuations.


  Recently observed magnetophonon resonances in the magnetoresistance of
graphene are investigated using the Kubo formalism. This analysis provides a
quantitative fit to the experimental data over a wide range of carrier
densities. It demonstrates the predominance of carrier scattering by low energy
transverse acoustic (TA) mode phonons: the magnetophonon resonance amplitude is
significantly stronger for the TA modes than for the longitudinal acoustic (LA)
modes. We demonstrate that the LA and TA phonon speeds and the electron-phonon
coupling strengths determined from the magnetophonon resonance measurements
also provide an excellent fit to the measured dependence of the resistivity at
zero magnetic field over a temperature range of 4-150 K. A semiclassical
description of magnetophonon resonance in graphene is shown to provide a simple
physical explanation for the dependence of the magneto-oscillation period on
carrier density. The correspondence between the quantum calculation and the
semiclassical model is discussed.


  Envisioned application areas for reinforcement learning (RL) include
autonomous driving, precision agriculture, and finance, which all require RL
agents to make decisions in the real world. A significant challenge hindering
the adoption of RL methods in these domains is the non-robustness of
conventional algorithms. In this paper, we argue that a fundamental issue
contributing to this lack of robustness lies in the focus on the expected value
of the return as the sole ``correct'' optimization objective. The expected
value is the average over the statistical ensemble of infinitely many
trajectories. For non-ergodic returns, this average differs from the average
over a single but infinitely long trajectory. Consequently, optimizing the
expected value can lead to policies that yield exceptionally high returns with
probability zero but almost surely result in catastrophic outcomes. This
problem can be circumvented by transforming the time series of collected
returns into one with ergodic increments. This transformation enables learning
robust policies by optimizing the long-term return for individual agents rather
than the average across infinitely many trajectories. We propose an algorithm
for learning ergodicity transformations from data and demonstrate its
effectiveness in an instructive, non-ergodic environment and on standard RL
benchmarks.


  We demonstrate a formally exact quantum-classical correspondence between the
stationary coherent states associated with the commensurate anisotropic
two-dimensional harmonic oscillator and the classical Lissajous orbits. Our
derivation draws upon earlier work of Louck et al [1973 \textit {J. Math.
Phys.} \textbf {14} 692] wherein they have provided a non-bijective canonical
transformation that maps, within a degenerate eigenspace, the commensurate
anisotropic oscillator on to the isotropic oscillator. This mapping leads, in a
natural manner, to a Schwinger realization of SU(2) in terms of the canonically
transformed creation and annihilation operators. Through the corresponding
coherent states built over a degenerate eigenspace, we directly effect the
classical limit via the expectation values of the underlying generators. Our
work completely accounts for the fact that the SU(2) coherent state in general
corresponds to an ensemble of Lissajous orbits.


  The rate of a standard graded $K$-algebra $A$ is a measure of the growth of
the shifts in a minimal free resolution of $K$ as an $A$-module. In particular
$A$ has rate one if and only if it is Koszul. It is known that a generic
Artinian Gorenstein algebra of embedding dimension $n \geq 3$ and socle degree
$s=3$ is Koszul. We prove that a generic Artinian Gorenstein algebra with
$n\geq 4$ and $s \ge 3 $ has rate $ \lfloor \frac{s}{2} \rfloor. $ In the
process we show that such an algebra is generated in degree $\lfloor
\frac{s}{2} \rfloor +1. $ This gives a partial positive answer to a
longstanding conjecture stated by the first author on the minimal free
resolution of a generic Artinian Gorenstein ring of odd socle degree.


  We study a coevolving nonlinear voter model describing the coupled evolution
of the states of the nodes and the network topology. Nonlinearity of the
interaction is measured by a parameter q. The network topology changes by
rewiring links at a rate p. By analytical and numerical analysis we obtain a
phase diagram in p, q parameter space with three different phases: Dynamically
active coexistence phase in a single component network, absorbing consensus
phase in a single component network, and absorbing phase in a fragmented
network. For finite systems the active phase has a lifetime that grows
exponentially with system size, at variance with the similar phase for the
linear voter model that has a lifetime proportional to system size. We find
three transition lines that meet at the point of the fragmentation transition
of the linear voter model. A first transition line corresponds to a continuous
absorbing transition between the active and fragmented phases. The other two
transition lines are discontinuous transitions fundamentally different from the
transition of the linear voter model. One is a fragmentation transition between
the consensus and fragmented phases, and the other is an absorbing transition
in a single component network between the active and consensus phases.


  Identifying materials and devices which offer efficient thermoelectric
effects at low temperature is a major obstacle for the development of thermal
management strategies for low-temperature electronic systems. Superconductors
cannot offer a solution since their near perfect electron-hole symmetry leads
to a negligible thermoelectric response; however, here we demonstrate
theoretically a superconducting thermoelectric transistor which offers
unparalleled figures of merit of up to $\sim 45$ and Seebeck coefficients as
large as a few mV/K at sub-Kelvin temperatures. The device is also
phase-tunable meaning its thermoelectric response for power generation can be
precisely controlled with a small magnetic field. Our concept is based on a
superconductor-normal metal-superconductor interferometer in which the normal
metal weak-link is tunnel coupled to a ferromagnetic insulator and a Zeeman
split superconductor. Upon application of an external magnetic flux, the
interferometer enables phase-coherent manipulation of thermoelectric properties
whilst offering efficiencies which approach the Carnot limit.


  To improve the application-level communication performance, scheduling of
coflows, a collection of parallel flows sharing the same objective, is
prevalent in modern data center networks (DCNs). Meanwhile, a hybrid-switched
DCN design combining optical circuit switches (OPS) and electrical packet
switches (EPS) for transmitting high-volume traffic and low-volume traffic
separately has received considerable research attention recently. Efficient
scheduling of coflows on hybrid network links is crucial for reducing the
overall communication time. However, because of the reconfiguration delay in
the circuit switch due to the ultra-high transmission rate and the limitation
of bandwidth in the packet switch, coflow scheduling becomes increasingly
challenging. The existing coflow scheduling algorithms in hybrid-switched DCNs
are all heuristic and provide no performance guarantees. In this work, we
propose an approximation algorithm with the worst-case performance guarantee of
2+ \lambda?, where \lambda? is a factor related to system parameters and demand
characteristics, for single coflow scheduling in hybridswitched DCN to minimize
the coflow completion time (CCT). Extensive simulations based on Facebook data
traces show that our algorithm outperforms the state-of-the-art schemes
Solstice by 1.14? and Reco-Sin by 1.42? in terms of minimizing CCT.


  Modeling dynamical systems is crucial for a wide range of tasks, but it
remains challenging due to complex nonlinear dynamics, limited observations, or
lack of prior knowledge. Recently, data-driven approaches such as Neural
Ordinary Differential Equations (NODE) have shown promising results by
leveraging the expressive power of neural networks to model unknown dynamics.
However, these approaches often suffer from limited labeled training data,
leading to poor generalization and suboptimal predictions. On the other hand,
semi-supervised algorithms can utilize abundant unlabeled data and have
demonstrated good performance in classification and regression tasks. We
propose TS-NODE, the first semi-supervised approach to modeling dynamical
systems with NODE. TS-NODE explores cheaply generated synthetic pseudo rollouts
to broaden exploration in the state space and to tackle the challenges brought
by lack of ground-truth system data under a teacher-student model. TS-NODE
employs an unified optimization framework that corrects the teacher model based
on the student's feedback while mitigating the potential false system dynamics
present in pseudo rollouts. TS-NODE demonstrates significant performance
improvements over a baseline Neural ODE model on multiple dynamical system
modeling tasks.


  The violation of certain Bell inequalities allows for device-independent
information processing secure against non-signalling eavesdroppers. However,
this only holds for the Bell network, in which two or more agents perform local
measurements on a single shared source of entanglement. To overcome the
practical constraint that entangled systems can only be transmitted over
relatively short distances, large-scale multi-source networks have been
employed. Do there exist analogues of Bell inequalities for such networks,
whose violation is a resource for device-independence? In this paper, the
violation of recently derived polynomial Bell inequalities will be shown to
allow for device-independence on multi-source networks, secure against
non-signalling eavesdroppers.


  We propose the Legendrian web in a contact three manifold as a second order
generalization of the planar web. An Abelian relation for a Legendrian web is
analogously defined as an additive equation among the first integrals of its
foliations. For a class of Legendrian $\, d$-webs defined by simple second
order ODE's, we give an algebraic construction of $$ \rho_d =
\frac{(d-1)(d-2)(2d+3)}{6}$$ linearly independent Abelian relations. We then
employ the method of local differential analysis and the theory of linear
differential systems to show that $\, \rho_d$ is the maximum rank of a
Legendrian $\, d$-web.
  In the complex analytic category, we give a possible projective geometric
interpretation of $\rho_d$ as an analogue of Castelnuovo bound for degree 2d
surfaces in the 3-quadric $\mathbb{Q}^3\subset\mathbb{P}^4$ via the duality
between $\mathbb{P}^3$ and $\mathbb{Q}^3$ associated with the rank two complex
simple Lie group Sp$(2,\mathbb{C})$.
  The Legendrian 3-webs of maximum rank three are analytically characterized,
and their explicit local normal forms are found. For an application, we give an
alternative characterization of a Darboux super-integrable metric as a two
dimensional Riemannian metric $\,g_+$ which admits a mate metric $\, g_-$ such
that a Legendrian 3-web naturally associated with the geodesic foliations of
the pair $\, g_{\pm}$ has maximum rank.


  We give a possible generalization of Lutz twist to all dimensions. This
reproves the fact that every contact manifold can be given a non-fillable
contact structure and also shows great flexibility in the manifolds that can be
realized as cores of overtwisted families. We moreover show that $R^{2n+1}$ has
at least three distinct contact structures.
  This version of the paper contains both the texts of the published version of
the paper together with an Erratum to the published version appended to the
end.


  In this paper, the phase structure of the Hayward-AdS black hole (BH) is
studied using shadow formalism. It has been found that the shadow radius is a
monotonic function of the horizon radius and can therefore play an equivalent
role to the horizon radius in characterizing the thermodynamics of Hayward-AdS
BH. The thermodynamic phase transition (PT) of the Hayward-AdS BH is
investigated with the shadow radius. It is shown that as the magnetic charge
increases, the shadow radius becomes larger, while the coexistence temperature
becomes lower. The thermal profile of the Hayward-AdS BH is established by
combining the temperature diagram and the shadow cast diagram, which shows that
for a fixed magnetic charge, the temperature of the Hayward-AdS BH increases
with the pressure while the region of the thermal profile decreases with the
pressure. In particular, the temperature of the Hayward-AdS BH follows an
N-type change trend when it is smaller than the critical temperature. This
imply that the BH shadow may be used to investigate the thermodynamics of the
Hayward-AdS BH.


  The graded reflection equation is investigated for the
$U_{q}[sl(r|2m)^{(2)}]$ vertex model. We have found four classes of diagonal
solutions and twelve classes of non-diagonal ones. The number of free
parameters for some solutions depends on the number of bosonic and fermionic
degrees of freedom considered.


  Let $X$ be the product of two projective spaces and consider the general CICY
threefold $Y$ in $X$ with configuration matrix $A$. We prove the finiteness
part of the analogue of the Clemens' conjecture for such a CICY in low
bidegrees. More precisely, we prove that the number of smooth rational curves
on $Y$ with low bidegree and with nondegenerate birational projection is at
most finite (even in cases in which positive dimensional families of degenerate
rational curves are known).


  We present the results on the search for the coalescence of compact binary
mergers with very asymmetric mass configurations using convolutional neural
networks and the LIGO/Virgo data for the O3 observation period. Two-dimensional
images in time and frequency are used as input. Masses in the range between
0.01 Msun and 20 Msun are considered. We explore neural networks trained with
input information from a single interferometer, pairs of interferometers, or
all three interferometers together, indicating that the use of the maximum
information available leads to an improved performance. A scan over the O3 data
set using the convolutional neural networks for detection results into no
significant excess from an only-noise hypothesis. The results are translated
into 90% confidence level upper limits on the merger rate as a function of the
mass parameters of the binary system.


  We study the stability of static black holes in Lovelock theory which is a
natural higher dimensional generalization of Einstein theory. We show that
Lovelock black holes are stable under vector perturbations in all dimensions.
However, we prove that small Lovelock black holes are unstable under tensor
perturbations in even-dimensions and under scalar perturbations in
odd-dimensions. Therefore, we can conclude that small Lovelock black holes are
unstable in any dimensions. The instability is stronger on small scales and
hence catastrophic in the sense that there is no smooth descendant.


  On the one hand, checking specific termination proofs by hand, say using a
particular collection of matrix interpretations, can be an arduous and
error-prone task. On the other hand, automation of such checks would save time
and help to establish correctness of exam solutions, examples in lecture notes
etc. To this end, we introduce a template mechanism for the termination tool
TTT2 that allows us to restrict parameters of certain termination methods. In
the extreme, when all parameters are fixed, such restrictions result in checks
for specific proofs.


  The morphology of the superconducting flux line lattice (FLL) of Nb comprises
gradual variations with various lock-in transitions and symmetry breaking
rotations. We report a comprehensive small-angle neutron scattering study of
the FLL in an ultra-pure single crystal of Nb as a function of the orientation
of the applied magnetic field. We attribute the general morphology of the FLL
and its orientation to three dominant mechanisms. First, non-local
contributions, second, the transition between open and closed Fermi surface
sheets and, third, the intermediate mixed state between the Meissner and the
Shubnikov phase.


  In multiband superconductivity, the case where the single electron hopping
between different Fermi surface spots of different symmetry is forbidden by
selection rules is recently attracting a large interest. The focus is addressed
to superconductivity made of multiple condensates with different symmetry where
the chemical potential crosses a 2.5 Lifshitz transition. This can now be
investigated experimentally by fine-tuning of the chemical potential in the
range of tens meV around a band edge using gate voltage control. We discuss
here the case of the two-dimensional electron gas (2DEG), at the interface
between two insulating oxides confined within a slab of 5 nanometers thickness,
where the electronic structure is made of subbands generated by quantum size
effects. We focus on the case of the BCS-BEC transition in the upper subband
for different pairing strength in the shallow Fermi surface.


  Fermi has shown GRBs to be a source of >10 GeV photons. We present an
estimate of the detection rate of GRBs with a next generation Cherenkov
telescope. Our predictions are based on the observed properties of GRBs
detected by Fermi, combined with the spectral properties and redshift
determinations for the bursts population by instruments operating at lower
energies. While detection of VHE emission from GRBs has eluded ground-based
instruments thus far, our results suggest that ground-based detection may be
within reach of the proposed Cherenkov Telescope Array (CTA), albeit with a low
rate, 0.25 - 0.5/yr. Such a detection would help constrain the emission
mechanism of gamma-ray emission from GRBs. Photons at these energies from
distant GRBs are affected by the UV-optical background light, and a
ground-based detection could also provide a valuable probe of the Extragalactic
Background Light (EBL) in place at high redshift.


  We construct and analyze families of periodic delay orbits for a class of
delay differential equations in two dimensions depending on two real-valued
functions. These families are parametrized by the delay parameter. It is
possible to represent the dependency of these periodic delay orbits on the
delay parameter by a curve in the plane, without loss of information. It turns
out that the singularities of these curves necessarily are cusps in the
non-degenerate case. After discussing degenerate situations in general, we
explain how to glue different families of periodic delay orbits at degeneracies
in the delay parameter.


  We answer a question of Vorobets by showing that the lattice property for
flat surfaces is equivalent to the existence of a positive lower bound for the
areas of affine triangles. We show that the set of affine equivalence classes
of lattice surfaces with a fixed positive lower bound for the areas of
triangles is finite and we obtain explicit bounds on its cardinality. We deduce
several other characterizations of the lattice property.


  The quantum limit can be easily reached in the Dirac semimetals under the
magnetic field, which will lead to some exotic many-body physics due to the
high degeneracy of the topological zeroth Landau bands (LBs). By solving the
effective Hamiltonian, which is derived by tracing out the high energy degrees
of freedom, at the self-consistent mean field level, we have systematically
studied the instability of Dirac semimetal under a strong magnetic field. A
charge density wave (CDW) phase and a polarized nematic phase formed by
"exciton condensation" are predicted as the ground state for the tilted and
untilted bands, respectively. Furthermore, we propose that, distinguished from
the CDW phase, the polarized nematic phase can be identified in experiments by
anisotropic transport and Raman scattering.


  The chirally rotated Schr\"odinger functional ($\chi$SF) renders the
mechanism of automatic $O(a)$ improvement compatible with Schr\"odinger
functional (SF) renormalization schemes. Here we define a family of
renormalization schemes based on the $\chi$SF for a complete basis of $\Delta F
= 2$ parity-odd four-fermion operators. We compute the corresponding
scale-dependent renormalization constants to one-loop order in perturbation
theory and obtain their NLO anomalous dimensions by matching to the
$\overline{\textrm{MS}}$ scheme. Due to automatic $O(a)$ improvement, once the
$\chi$SF is renormalized and improved at the boundaries, the step scaling
functions (SSF) of these operators approach their continuum limit with
$O(a^{2})$ corrections without the need of operator improvement.


  For a linear complementarity problem, we present a relaxaiton accelerated
two-sweep matrix splitting iteration method. The convergence analysis
illustrates that the proposed method converges to the exact solution of the
linear complementarity problem when the system matrix is an $H_+$-matrix and
the convergence conditions are given. Numerical experiments show that the
proposed method is more efficient than the existing ones.


  Argument mining is a core technology for automating argument search in large
document collections. Despite its usefulness for this task, most current
approaches to argument mining are designed for use only with specific text
types and fall short when applied to heterogeneous texts. In this paper, we
propose a new sentential annotation scheme that is reliably applicable by crowd
workers to arbitrary Web texts. We source annotations for over 25,000 instances
covering eight controversial topics. The results of cross-topic experiments
show that our attention-based neural network generalizes best to unseen topics
and outperforms vanilla BiLSTM models by 6% in accuracy and 11% in F-score.


  We introduce a new class of weighted local approximate atoms including
classical weighted local atoms. Then we further obtain the weighted local
approximate atomic decompositions of weighted local Hardy spaces $h_{\omega}
^p(R^n)$ with $0<p\leq 1$ and weight $\omega\in A_1(R^n)$. As an application,
we prove the boundedness of inhomogeneous Calder\'on-Zygmund operators on
$h_{\omega}^p(R^n)$ via weighted local approximate atoms and molecules.


  Activity recognition, as an important component of behavioral monitoring and
intervention, has attracted enormous attention, especially in Mobile Cloud
Computing (MCC) and Remote Health Monitoring (RHM) paradigms. While recently
resource constrained wearable devices have been gaining popularity, their
battery life is limited and constrained by the frequent wireless transmission
of data to more computationally powerful back-ends. This paper proposes an
ultra-low power activity recognition system using a novel adaptive compressed
sensing technique that aims to minimize transmission costs. Coarse-grained
on-body sensor localization and unsupervised clustering modules are devised to
autonomously reconfigure the compressed sensing module for further power
saving. We perform a thorough heuristic optimization using Grammatical
Evolution (GE) to ensure minimal computation overhead of the proposed
methodology. Our evaluation on a real-world dataset and a low power wearable
sensing node demonstrates that our approach can reduce the energy consumption
of the wireless data transmission up to $81.2\%$ and $61.5\%$, with up to
$60.6\%$ and $35.0\%$ overall power savings in comparison with baseline and a
naive state-of-the-art approaches, respectively. These solutions lead to an
average activity recognition accuracy of $89.0\%$ -- only $4.8\%$ less than the
baseline accuracy -- while having a negligible energy overhead of on-node
computation.


  Exploring the impact of change requests applied to a software maintenance
project helps to assess the fault-proneness of the change request to be handled
further, which is perhaps a bug fix or even a new feature demand. In practice,
the major development community stores change requests and related data using
bug tracking systems such as Bugzilla. These data, together with the data
stored in a versioning system, such as Concurrent Versioning Systems, are a
valuable source of information to create descriptions and also can perform
useful analyzes. In our earlier work, we proposed a novel statistical bipartite
weighted graph-based approach to assessing the degree of fault-proneness of the
change request and Change Request artifacts. With the motivation gained from
this model, here we propose a novel strategy that estimates the degree of
fault-proneness of a change request by assessing the impact of a change request
artifact towards fault-proneness that considers the correlation between change
requests artifact as another factor, which is in addition to our earlier
strategy. The proposed model can be titled as Assessing the Fault Proneness
Degree of Change Request Artifacts by estimating the impact of change requests
correlation (DFP-CRC). As stated in our earlier model, the method DFP-CRC also
makes use of information retrieval methods to identify the change request
artifacts of the devised change request. And further evaluates the degree of
fault-proneness of the Change Requests by estimating the correlation between
change requests. The proposed method is evaluated by applying on concurrent
versioning and Change request logs of the production level maintenance project.


  Here we study nonmonotonic features which appear both in magnetoresistivity
and anomalous Hall resistivity during the simple magnetization process, by
systematically measuring type-II magnetic Weyl semimetal EuCd$_2$Sb$_2$ films
over a wide carrier density range. We find that a positive magnetoresistivity
hump can be explained as manifestation of a field-linear term in the
generalized magnetoconductivity formula including the Berry curvature. As also
confirmed by model calculation, the term can be negative and pronounced near
the Weyl point energy in the case that the Weyl cones are heavily tilted. Our
findings demonstrate extensive effects of the Berry curvature on various
magnetotransport in magnetic Weyl semimetals beyond the anomalous Hall effect.


  In this article we perform a computational study of Polyrakis algorithms
presented in [12,13]. These algorithms are used for the determination of the
vector sublattice and the minimal lattice-subspace generated by a finite set of
positive vectors of R^k. The study demonstrates that our findings can be very
useful in the field of Economics, especially in completion by options of
security markets and portfolio insurance.


  The group winning blasting is one of the most often applied method of
high-energy tremors provoking in underground mines of the Lower Silesian Copper
Basin. The simultaneous detonation of dozens mining faces are performed in
order to release of elastic energy which is cumulated in surrounding rock mass.
The accuracy of currently used non-electric initiation systems is insufficient
to provide a controlled interference of seismic wave generated by blasting
works. As a result, simultaneous detonation of higher number of mining faces
does not always correlate with improvement of the effectiveness of rockburst
prevention. In this paper, the records of seismic waves generated by blasting
works in one of the mining panels from the Polish copper mine were analysed.
The evaluation was performed by correlation of selected blasting parameters
such as the number of fired mining faces and the total amount of detonated
explosives with parameters of induced seismic wave


  Most of the analytic approaches which are used at present to understand Kaon
decays, get their inspiration from QCD in the limit of a large number of
colours $N_c$. After a general overview, we illustrate this with a recent
application to the evaluation of the process $K_L\ra\mu^+ \mu^-$ in the
Standard Model.


  Open quantum systems with nearly degenerate energy levels have been shown to
exhibit long-lived metastable states in the approach to equilibrium, even when
modelled with certain Lindblad-form quantum master equations. This is a result
of dramatic separation of timescales due to differences between Liouvillian
eigenvalues. These metastable states often have nonzero coherences which die
off only in the long time limit once the system reaches thermal equilibrium. We
examine two distinct situations that give rise to this effect: one in which
dissipative dynamics couple together states only within a nearly degenerate
subspace, and one in which they give rise to jumps over finite energy
splittings, between separate nearly degenerate subspaces. We find, in each
case, that a change of basis can often lead to a representation which more
naturally captures the impact of the system-bath interaction than does the
energy eigenbasis, revealing that separate timescales are associated with
separate processes (e.g. decoherence into a non-energy eigenbasis, decay of
population correlations to the initial state). This approach is paired with the
inspection of quantum trajectories, which further provide intuition as to how
open system evolution is characterized when coherent oscillations, thermal
relaxation, and decoherence all occur simultaneously.


  The twist-three distributions $g_2(x)$ and $h_2(x)$ are defined as
quark-field matrix elements between polarized hadron states. They can be
written in terms of quark-mass and gluonic operators, after which the
Burkhardt-Cottingham sum rule for $g_2$ can be derived and a similar sum rule
for $h_2$. Their role in the Drell-Yan double-spin asymmetry $A_{LT}$ is
explained.


  Optimising the execution of Bag-of-Tasks (BoT) applications on the cloud is a
hard problem due to the trade- offs between performance and monetary cost. The
problem can be further complicated when multiple BoT applications need to be
executed. In this paper, we propose and implement a heuristic algorithm that
schedules tasks of multiple applications onto different cloud virtual machines
in order to maximise performance while satisfying a given budget constraint.
Current approaches are limited in task scheduling since they place a limit on
the number of cloud resources that can be employed by the applications.
However, in the proposed algorithm there are no such limits, and in comparison
with other approaches, the algorithm on average achieves an improved
performance of 10%. The experimental results also highlight that the algorithm
yields consistent performance even with low budget constraints which cannot be
achieved by competing approaches.


  Exotic spin-dependent interactions mediated by new light particles led to
solutions to several important questions in modern physics. Such interactions
involving a scalar coupling $g_S^N$ at one vertex and a pseudo-scalar coupling
$g_P^n$ at the polarized neutron vertex can be induced by the exchange of
spin-0 bosons, or a vector/axial-vector coupling $g_V^N$/$g_A^N$ at one vertex
and an axial-vector coupling $g_A^n$ at the polarized neutron vertex can be
induced by the exchange of spin-1 bosons. If such new interactions exist, the
Sun and the Moon can induce sidereal variations of effective fields along the
direction perpendicular to the Earth's rotation axis. We derived new
experimental upper limits on such exotic spin-dependent interactions at
astronomical interaction ranges by analyzing existing data from laboratory
measurements on the Lorentz and CPT violation. We set the most stringent
experimental limits on $g_S^Ng_P^n$ ranging from $\sim 2\times 10^{10}$m to
$\sim 10^{14}$m. Previously, the best limit on $g_S^Ng_P^n$ at this range is
from astrophysics. The result is the first time laboratory limits surpass the
astrophysical ones on the scalar-pseudoscalar type interaction, to our best
knowledge. We report new constraints on vector-axial-vector and
axial-axial-vector type interaction at the range of astronomical scales. The
new limits on vector-axial-vector are improved by as much as $\sim$12 orders of
magnitude. We also apply the analysis to the Hari-Dass interactions and obtain
corresponding new constraints on the interactions. We discuss the possibilities
of using the beam method to further search the interaction involving other
particles, such as electrons, muons, etc., based on the same idea.


  Inappropriate use of Dempster's rule of combination has led some authors to
reject the Dempster-Shafer model, arguing that it leads to supposedly
unacceptable conclusions when defaults are involved. A most classic example is
about the penguin Tweety. This paper will successively present: the origin of
the miss-management of the Tweety example; two types of default; the correct
solution for both types based on the transferable belief model (our
interpretation of the Dempster-Shafer model (Shafer 1976, Smets 1988)); Except
when explicitly stated, all belief functions used in this paper are simple
support functions, i.e. belief functions for which only one proposition (the
focus) of the frame of discernment receives a positive basic belief mass with
the remaining mass being given to the tautology. Each belief function will be
described by its focus and the weight of the focus (e.g. m(A)=.9). Computation
of the basic belief masses are always performed by vacuously extending each
belief function to the product space built from all variables involved,
combining them on that space by Dempster's rule of combination, and projecting
the result to the space corresponding to each individual variable.


  Repetition-rate-scanned lasers are practical in accordion frequency comb
generation that serves as a variable gearbox connecting optical and radio wave
domains. Rapid and wide-range scanned repetition rate can benefit versatile
purposes, however scanning robustness remains unsecured that typically requires
complicated feedback loops. Recently, multiplexed lasers have been demonstrated
with the nature of common-noise rejection among simultaneously emitted combs.
Here, we propose a bidirectional polarization-multiplexed fiber laser that
delivers synchronized pulses with rapid-scanned and reference-free repetition
rates. Benefiting from the all polarization-maintaining fiber configuration,
the laser shows good robustness and inter-comb coherence. As rapid as 493.5
kHz/s scanning rate over 329-kHz scanning range of fundamental repetition rate
is realized. The 1-hour and 1-day maximal variations of difference frequency
are merely 0.52 Hz and 5.46 Hz. The capability to rebuilt steady state after
mode hopping is also demonstrated. These results provide a promising solution
for developing high-performance accordion-frequency laser sources.


  The video game industry has seen rapid growth over the last decade. Thousands
of video games are released and played by millions of people every year,
creating a large community of players. Steam is a leading gaming platform and
social networking site, which allows its users to purchase and store games. A
by-product of Steam is a large database of information about games, players,
and gaming behavior. In this paper, we take recent video games released on
Steam and aim to discover the relation between game popularity and a game's
features that can be acquired through Steam. We approach this task by
predicting the popularity of Steam games in the early stages after their
release and we use a Bayesian approach to understand the influence of a game's
price, size, supported languages, release date, and genres on its player count.
We implement several models and discover that a genre-based hierarchical
approach achieves the best performance. We further analyze the model and
interpret its coefficients, which indicate that games released at the beginning
of the month and games of certain genres correlate with game popularity.


  This article provides an overview of research on full-duplex at the
University of California, Riverside, in the past decade. This research was
initially focused on self-interference (SI) cancellation, then moved to
applications of full-duplex to improve network spectral efficiency, and in
recent years advanced to discover full-duplex's potentials for wireless network
security. The research on SI cancellation has resulted in both hardware-based
SI cancellation results and some advanced theoretical architectures which show
promises but are yet to be tested via advanced hardware implementations. The
applications of full-duplex for optimized spectral efficiency in ad hoc,
cognitive and cellular networks have shown how to optimize power allocation
among full-duplex nodes, in their antenna beamspace and over multiple
subcarriers. Full-duplex has also been found to be highly beneficial for
improving secrecy capacity between legitimate users against eavesdropping.
Among the new capabilities that full-duplex provides for network security is an
effective anti-eavesdropping channel estimation scheme which is not possible
for nodes without full-duplex.


  Building on earlier work in the high energy and condensed matter communities,
we present a web of dualities in $2+1$ dimensions that generalize the known
particle/vortex duality. Some of the dualities relate theories of fermions to
theories of bosons. Others relate different theories of fermions. For example,
the long distance behavior of the $2+1$-dimensional analog of QED with a single
Dirac fermion (a theory known as $U(1)_{1/2}$) is identified with the $O(2)$
Wilson-Fisher fixed point. The gauged version of that fixed point with a
Chern-Simons coupling at level one is identified as a free Dirac fermion. The
latter theory also has a dual version as a fermion interacting with some gauge
fields. Assuming some of these dualities, other dualities can be derived. Our
analysis resolves a number of confusing issues in the literature including how
time reversal is realized in these theories. It also has many applications in
condensed matter physics like the theory of topological insulators (and their
gapped boundary states) and the problem of electrons in the lowest Landau level
at half filling. (Our techniques also clarify some points in the fractional
Hall effect and its description using flux attachment.) In addition to
presenting several consistency checks, we also present plausible (but not
rigorous) derivations of the dualities and relate them to $3+1$-dimensional
$S$-duality.


  The Internet of Things (IoT) is on the verge of a major paradigm shift. In
the IoT system of the future, IoFT, the cloud will be substituted by the crowd
where model training is brought to the edge, allowing IoT devices to
collaboratively extract knowledge and build smart analytics/models while
keeping their personal data stored locally. This paradigm shift was set into
motion by the tremendous increase in computational power on IoT devices and the
recent advances in decentralized and privacy-preserving model training, coined
as federated learning (FL). This article provides a vision for IoFT and a
systematic overview of current efforts towards realizing this vision.
Specifically, we first introduce the defining characteristics of IoFT and
discuss FL data-driven approaches, opportunities, and challenges that allow
decentralized inference within three dimensions: (i) a global model that
maximizes utility across all IoT devices, (ii) a personalized model that
borrows strengths across all devices yet retains its own model, (iii) a
meta-learning model that quickly adapts to new devices or learning tasks. We
end by describing the vision and challenges of IoFT in reshaping different
industries through the lens of domain experts. Those industries include
manufacturing, transportation, energy, healthcare, quality & reliability,
business, and computing.


  As part of a wider search for radio emission from nearby systems known or
suspected to contain extrasolar planets $\epsilon$ Eridani was observed by the
Jansky Very Large Array (VLA) in the 2-4 GHz and 4-8 GHz frequency bands. In
addition, as part of a separate survey of thermal emission from solar-like
stars, $\epsilon$ Eri was observed in the 8-12 GHz and the 12-18 GHz bands of
the VLA. Quasi-steady continuum radio emission from $\epsilon$ Eri was detected
in the three high-frequency bands at levels ranging from 67-83 $\mu$Jy. No
significant variability is seen in the quasi-steady emission. The emission in
the 2-4 GHz emission, however, is shown to be the result of a circularly
polarized (up to 50\%) radio pulse or flare of a few minutes duration that
occurred at the beginning of the observation. We consider the astrometric
position of the radio source in each frequency band relative to the expected
position of the K2V star and the purported planet. The quasi-steady radio
emission at frequencies $\ge \!8$ GHz is consistent with a stellar origin. The
quality of the 4-8 GHz astrometry provides no meaningful constraint on the
origin of the emission. The location of the 2-4 GHz radio pulse is $>2.5\sigma$
from the star yet, based on the ephemeris of Benedict et al. (2006), it is not
consistent with the expected location of the planet either. If the radio pulse
has a planetary origin, then either the planetary ephemeris is incorrect or the
emission originates from another planet.


  We discuss how to understand the dynamical process of Kuznetsov-Ma breather,
based on some basic physical mechanisms. It is shown that dynamical process of
Kuznetsov-Ma breather involves at least two distinctive mechanisms:
modulational instability, and the interference effects between a bright soliton
and a plane wave background. Our analysis indicates that modulational
instability plays dominant roles in mechanism of Kuznetsov-Ma breather
admitting weak perturbations, and the interference effect plays dominant role
for the Kuznetsov-Ma breather admitting strong perturbations. For intermediate
cases, the two mechanisms are both involved greatly. These characters provide a
possible way to understand the evolution of strong perturbations on a plane
wave background.


  New observations of the eclipsing nova V1494 Aql were analysed in order to
estimate the effect of the optical companion located 1.4 arcsec southwest. R
and I-band images (stellar FWHM~1.2-1.4 arcsec) taken close to the primary
minimum were used to determine relative magnitude differences between the nova
and the companion, which were found to be Delta R~0.20 mag and Delta I~0.52 mag
(in the sense nova minus companion). After correcting R-band time-series
observations for the secondary light, the eclipse depth has been found to be
almost twice as deep. Before modelling any late eclipsing light curve that is
available in the literature, the data must be corrected for the light of the
companion.


  We investigate the low moments $\mathbb{E}[|A_N|^{2q}], 0<q\leq 1$ of
{secular coefficients} $A_N$ of the {critical non-Gaussian holomorphic
multiplicative chaos}, i.e. coefficients of $z^N$ in the power series expansion
of $\exp(\sum_{k=1}^\infty X_kz^k/\sqrt{k})$, where $\{X_k\}_{k\geq 1}$ are
i.i.d. rotationally invariant unit variance complex random variables. Inspired
by Harper's remarkable result on random multiplicative functions, Soundararajan
and Zaman recently showed that if each $X_k$ is standard complex Gaussian,
$A_N$ features better-than-square-root cancellation: $\mathbb{E}[|A_N|^2]=1$
and $\mathbb{E}[|A_N|^{2q}]\asymp (\log N)^{-q/2}$ for fixed $q\in(0,1)$ as
$N\to\infty$. We show that this asymptotic holds universally if
$\mathbb{E}[e^{\gamma|X_k|}]<\infty$ for some $\gamma>2q$. As a consequence, we
establish the universality for the tightness of the normalized secular
coefficients $A_N(\log(1+N))^{1/4}$, generalizing a result of Najnudel,
Paquette, and Simm. Another corollary is the almost sure regularity of some
critical non-Gaussian holomorphic chaos in appropriate Sobolev spaces.
Moreover, we characterize the asymptotic of $\mathbb{E}[|A_N|^{2q}]$ for
$|X_k|$ following a stretched exponential distribution with an arbitrary scale
parameter, which exhibits a completely different behavior and underlying
mechanism from the Gaussian universality regime. As a result, we unveil a
double-layer phase transition around the critical case of exponential tails.
Our proofs combine Harper's robust approach with a careful analysis of the
(possibly random) leading terms in the monomial decomposition of $A_N$.


  Based on a high resolution cosmological n-body simulation, we track the
hierarchical growth of black holes in galaxy clusters from z=20 to z=0. We
present a census of black holes as function of redshift and will determine
their mass assembly history under a variety of assumptions regarding the
importance of gas accretion in black hole growth, from early supercritical
Eddington accretion to gas-poor hierarchical assembly. Following a galaxy
merger, black holes are expected to form, inspiral and merge after strongly
radiating energy via gravitational waves. For each binary black hole inspiral
and merger, we determine the expected gravitational wave signal for the Laser
Interferometer Space Antenna (LISA), and calculate the LISA event rate as a
function of time. We will calculate the black hole mass assembly history for
several black hole growth scenerios, so that we can explore tests to
characterize each model observationally. In particular, we will study how well
LISA observations will be able to distinguish between these very different
assembly scenarios.


  Diffusion of electrons in three dimensional disordered systems is
investigated numerically for all the three universality classes, namely,
orthogonal, unitary and symplectic ensembles. The second moment of the wave
packet $<\vv{r}^2(t)>$ at the Anderson transition is shown to behave as $\sim
t^a (a\approx 2/3)$. From the temporal autocorrelation function $C(t)$, the
fractal dimension $D_2$ is deduced, which is almost half the value of space
dimension for all the universality classes.


  There is a growing interest in using robust control theory to analyze and
design optimization and machine learning algorithms. This paper studies a class
of nonconvex optimization problems whose cost functions satisfy the so-called
Regularity Condition (RC). Empirical studies show that accelerated gradient
descent (AGD) algorithms (e.g. Nesterov's acceleration and Heavy-ball) with
proper initializations often work well in practice. However, the convergence of
such AGD algorithms is largely unknown in the literature. The main contribution
of this paper is the analytical characterization of the convergence regions of
AGD under RC via robust control tools. Since such optimization problems arise
frequently in many applications such as phase retrieval, training of neural
networks and matrix sensing, our result shows promise of robust control theory
in these areas.


  Experimental analysis of the mechanics of a deformable object, and
particularly its stability, requires repetitive testing and, depending on the
complexity of the object's shape, a testing setup that can manipulate many
degrees of freedom at the object's boundary. Motivated by recent advancements
in robotic manipulation of deformable objects, this paper addresses these
challenges by constructing a method for automated stability testing of a
slender elastic rod -- a canonical example of a deformable object -- using a
robotic system. We focus on rod configurations with helical centerlines since
the stability of a helical rod can be described using only three parameters,
but experimentally determining the stability requires manipulation of both the
position and orientation at one end of the rod, which is not possible using
traditional experimental methods that only actuate a limited number of degrees
of freedom. Using a recent geometric characterization of stability for helical
rods, we construct and implement a manipulation scheme to explore the space of
stable helices, and we use a vision system to detect the onset of instabilities
within this space. The experimental results obtained by our automated testing
system show good agreement with numerical simulations of elastic rods in
helical configurations. The methods described in this paper lay the groundwork
for automation to grow within the field of experimental mechanics.


  We prove that (under appropriate orientation conditions, depending on $R$) a
Hamiltonian isotopy $\psi^1$ of a symplectic manifold $(M, \omega)$ fixing a
relatively exact Lagrangian $L$ setwise must act trivially on $R_*(L)$, where
$R_*$ is some generalised homology theory. We use a strategy inspired by that
of Hu, Lalonde and Leclercq (\cite{Hu-Lalonde-Leclercq}), who proved an
analogous result over $\mathbb{Z}/2$ and over $\mathbb{Z}$ under stronger
orientation assumptions. However the differences in our approaches let us
deduce that if $L$ is a homotopy sphere, $\psi^1|_L$ is homotopic to the
identity. Our technical set-up differs from both theirs and that of Cohen,
Jones and Segal (\cite{Cohen-Jones-Segal, Cohen}). We also prove (under similar
conditions) that $\psi^1|_L$ acts trivially on $R_*(\mathcal{L} L)$, where
$\mathcal{L} L$ is the free loop space of $L$. From this we deduce that when
$L$ is a surface or a $K(\pi, 1)$, $\psi^1|_L$ is homotopic to the identity.
Using methods of \cite{Lalonde-McDuff}, we also show that given a family of
Lagrangians all of which are Hamiltonian isotopic to $L$ over a sphere or a
torus, the associated fibre bundle cohomologically splits over $\mathbb{Z}/2$.


  We consider the open spin-s XXZ quantum spin chain with N sites and general
integrable boundary terms for generic values of the bulk anisotropy parameter,
and for values of the boundary parameters which satisfy a certain constraint.
We derive two sets of Bethe Ansatz equations, and find numerical evidence that
together they give the complete set of $(2s+1)^{N}$ eigenvalues of the transfer
matrix. For the case s=1, we explicitly determine the Hamiltonian, and find an
expression for its eigenvalues in terms of Bethe roots.


  This paper presents the algorithms and system architecture of an autonomous
racecar. The introduced vehicle is powered by a software stack designed for
robustness, reliability, and extensibility. In order to autonomously race
around a previously unknown track, the proposed solution combines state of the
art techniques from different fields of robotics. Specifically, perception,
estimation, and control are incorporated into one high-performance autonomous
racecar. This complex robotic system, developed by AMZ Driverless and ETH
Zurich, finished 1st overall at each competition we attended: Formula Student
Germany 2017, Formula Student Italy 2018 and Formula Student Germany 2018. We
discuss the findings and learnings from these competitions and present an
experimental evaluation of each module of our solution.


  We present a fixed energy sandpile (FES) model which, by increasing the
initial energy,undergoes, at the level of individual configurations, a
discontinuous transition.The model is obtained by modifying the toppling
procedure in the BTW rules: the energy transfer from a toppling site takes
place only to neighbouring sites with less energy (negative gradient
constraint) and with a time ordering (asynchronous). The model is minimal in
the sense that removing either of the two above mentioned constraints (negative
gradient or time ordering) the abrupt transition goes over to a continuous
transition as in the usual BTW case. Therefore the proposed model offers an
unique possibility to explore at the microscopic level the basic mechanisms
underlying discontinuous transitions.


  We present analytical and numerical results for the effect of Rashba
spin-orbit coupling on band structure, transport, and interaction effects in
quantum wires when the spin precession length is comparable to the wire width.
In contrast to the weak-coupling case, no common spin-quantization axis can be
defined for eigenstates within a single-electron band. The situation with only
the lowest spin-split subbands occupied is particularly interesting because
electrons close to Fermi points of the same chirality can have approximately
parallel spins. We discuss consequences for spin-dependent transport and
effective Tomonaga-Luttinger descriptions of interactions in the quantum wire.


  The growth of small planetesimals into large planetary embryos occurs much
before the dispersal of the gas from the protoplanetary disk. The planetesimal
- gaseous-disk interactions give rise to migration and orbital evolution of the
planetesimals/planets. Small planetesimals are dominated by aerodynamic gas
drag. Large protoplanets, $m\sim0.1M_{\oplus}$, are dominated by type I
migration \emph{differential} torque. There is an additional mass range,
$m\sim10^{21}-10^{25}g$ of \emph{intermediate mass} planetesimals (IMPs), where
gravitational interactions with the disk dominate over aerodynamic gas drag,
but for which such interactions were typically neglected. Here we model these
interactions using the \emph{gas dynamical friction} (GDF) approach, previously
used to study the disk-planet interactions at the planetary mass range. We find
the critical size where GDF dominates over gas drag, and then study the
implications of GDF on single IMPs. We find that planetesimals with small
inclinations rapidly become co-planar. Eccentric orbits circularize within a
few Myrs, provided the the planetesimal mass is large, $m\gtrsim10^{23}g$ and
that the initial eccentricity is low, $e\lesssim0.1$. Planetesimals of higher
masses, $m\sim10^{24}-10^{25}g$ inspiral on a time-scale of a few Myrs, leading
to \emph{an embryonic migration} to the inner disk. This can lead to an
over-abundance of rocky material (in the form of IMPs) in the inner
protoplanetary disk ($<1$AU) and induce rapid planetary growth. This can
explain the origin of super-Earth planets. In addition, GDF damps the
velocities of IMPs, thereby cooling the planetesimal disk and affecting its
collisional evolution through quenching the effects of viscous stirring by the
large bodies.


  We study the dynamical behavior of dissipative solitons in an optical cavity
filled with a Kerr medium when a localized beam is applied on top of the
homogeneous pumping. In particular, we report on the excitability regime that
cavity solitons exhibits which is emergent property since the system is not
locally excitable. The resulting scenario differs in an important way from the
case of a purely homogeneous pump and now two different excitable regimes, both
Class I, are shown. The whole scenario is presented and discussed, showing that
it is organized by three codimension-2 points. Moreover, the localized beam can
be used to control important features, such as the excitable threshold,
improving the possibilities for the experimental observation of this
phenomenon.


  Using elementary linear algebra, we develop a technique that leads to
solutions of two widely known problems on nonnegative matrices. First, we give
a short proof of the result by Vavasis stating that the nonnegative rank of a
matrix is NP-hard to compute. This proof is essentially contained in the paper
by Jiang and Ravikumar, who discussed this topic in different terms fifteen
years before the work of Vavasis. Secondly, we present a solution of the
problem of Cohen and Rothblum on rational nonnegative factorizations, which was
posed in 1993 and remained open.


  We study physical properties of a potential candidate for the physical
realization of the SU(4) spin-orbital model - layered alpha-ZrCl3. Both DFT and
DFT+U+SOC calculations show that this material most probably dimerizes at
normal conditions. Therefore it is unlikely that symmetric SU(4) model can be
used for description of magnetic properties of alpha-ZrCl3 at low temperatures.
In the dimerized structure electrons occupy molecular orbitals formed by the xy
orbitals. One might expect a non-magnetic ground state in this case.
Interestingly the energy difference between various dimers packings is rather
small and thus dimers may start to flow over the lattice as they do in Li2RuO3.


  To understand the magnetic properties of Fe$_3$GeTe$_2$, we performed the
detailed first-principles study. Contrary to the conventional wisdom, it is
unambiguously shown that Fe$_3$GeTe$_2$ is not ferromagnetic but
antiferromagnetic carrying zero net moment in its stoichiometric phase. Fe
defect and hole doping are the keys to make this material ferromagnetic, which
are shown by the magnetic force response as well as the total energy
calculation with the explicit Fe defects and the varied system charges.
Further, we found that the electron doping also induces the antiferro- to
ferromagnetic transition. It is a crucial factor to understand the notable
recent experiment of gate-controlled ferromagnetism. Our results not only
unveil the origin of ferromagnetism of this material but also show how it can
be manipulated with defect and doping.


  We address the distinction between dynamical and additive noise in time
series analysis by making a joint evaluation of both the statistical continuity
of the series and the statistical differentiability of the reconstructed
measure. Low levels of the latter and high levels of the former indicate the
presence of dynamical noise only, while low values of the two are observed as
soon as additive noise contaminates the signal. The method is presented through
the example of the Van der Pol oscillator, but is expected to be of general
validity for continuous-time systems.


  We study a model of opinion formation where the collective decision of group
is said to happen if the fraction of agents having the most common opinion
exceeds a threshold value, a \textit{critical mass}. We find that there exists
a unique, non-trivial critical mass giving the most efficient convergence to
consensus. In addition, we observe that for small critical masses, the
characteristic time scale for the relaxation to consensus splits into two. The
shorter time scale corresponds to a direct relaxation and the longer can be
explained by the existence of intermediate, metastable states similar to those
found in [P.\ Chen and S.\ Redner, Phys.\ Rev.\ E \textbf{71}, 036101 (2005)].
This longer time-scale is dependent on the precise condition for
consensus---with a modification of the condition it can go away.


  Efficient recovery of a low-dimensional structure from high-dimensional data
has been pursued in various settings including wavelet denoising, generalized
linear models and low-rank matrix estimation. By thresholding some parameters
to zero, estimators such as lasso, elastic net and subset selection allow to
perform not only parameter estimation but also variable selection, leading to
sparsity. Yet one crucial step challenges all these estimators: the choice of
the threshold parameter~$\lambda$. If too large, important features are
missing; if too small, incorrect features are included.
  Within a unified framework, we propose a new selection of $\lambda$ at the
detection edge under the null model. To that aim, we introduce the concept of a
zero-thresholding function and a null-thresholding statistic, that we
explicitly derive for a large class of estimators. The new approach has the
great advantage of transforming the selection of $\lambda$ from an unknown
scale to a probabilistic scale with the simple selection of a probability
level. Numerical results show the effectiveness of our approach in terms of
model selection and prediction.


  The challenge of associating entities across multiple domains is a key
problem in social media understanding. Successful cross-domain entity
resolution provides integration of information from multiple sites to create a
complete picture of user and community activities, characteristics, and trends.
In this work, we examine the problem of entity resolution across Twitter and
Instagram using general techniques. Our methods fall into three categories:
profile, content, and graph based. For the profile-based methods, we consider
techniques based on approximate string matching. For content-based methods, we
perform author identification. Finally, for graph-based methods, we apply novel
cross-domain community detection methods and generate neighborhood-based
features. The three categories of methods are applied to a large graph of users
in Twitter and Instagram to understand challenges, determine performance, and
understand fusion of multiple methods. Final results demonstrate an equal error
rate less than 1%.


  Coughlin et al. (2018) (Paper I) derived and analyzed a new regime of
self-similarity that describes weak shocks (Mach number of order unity) in the
gravitational field of a point mass. These solutions are relevant to low energy
explosions, including failed supernovae. In this paper, we develop a formalism
for analyzing the stability of shocks to radial perturbations, and we
demonstrate that the self-similar solutions of Paper I are extremely weakly
unstable to such radial perturbations. Specifically, we show that perturbations
to the shock velocity and post-shock fluid quantities (the velocity, density,
and pressure) grow with time as $t^{\alpha}$, where $\alpha \le 0.12$, implying
that the ten-folding timescale of such perturbations is roughly ten orders of
magnitude in time. We confirm these predictions by performing high-resolution,
time-dependent numerical simulations. Using the same formalism, we also show
that the Sedov-Taylor blastwave is trivially stable to radial perturbations
provided that the self-similar, Sedov-Taylor solutions extend to the origin,
and we derive simple expressions for the perturbations to the post-shock
velocity, density, and pressure. Finally, we show that there is a third,
self-similar solution (in addition to the the solutions in Paper I and the
Sedov-Taylor solution) to the fluid equations that describes a rarefaction
wave, i.e., an outward-propagating sound wave of infinitesimal amplitude. We
interpret the stability of shock propagation in light of these three distinct
self-similar solutions.


  Hundreds of radar-dark patches interpreted as lakes have been discovered in
the north and south polar regions of Titan. We have estimated the composition
of these lakes by using the direct abundance measurements from the Gas
Chromatograph Mass Spectrometer (GCMS) aboard the Huygens probe and recent
photochemical models based on the vertical temperature profile derived by the
Huygens Atmospheric Structure Instrument (HASI). Thermodynamic equilibrium is
assumed between the atmosphere and the lakes, which are also considered as
nonideal solutions. We find that the main constituents of the lakes are ethane
(C2H6) (~76-79%), propane (C3H8) (~7-8%), methane (CH4) (~5-10%), hydrogen
cyanide (HCN) (~2-3%), butene (C4H8) (~1%), butane (C4H10) (~1%) and acetylene
(C2H2) (~1%). The calculated composition of lakes is then substantially
different from what has been expected from models elaborated prior to the
exploration of Titan by the Cassini-Huygens spacecraft.


  The importance of real-time notification has been growing for social services
and Intelligent Transporting System (ITS). As an advanced version of Pub/Sub
systems, publish-process-subscribe systems, where published messages are
spooled and processed on edge servers, have been proposed to achieve
data-driven intelligent notifications. In this paper, we present a system that
allows a topic to be managed on multiple edge servers so that messages are
processed near the publishers, even when publishers are spread over a wide
area. Duplicating messages on geographically distributed servers could enable
immediate notification to neighboring subscribers. However, the duplicated
message spool may cause exhaustion of resources. We prepare a formal model of
our publish-process-subscribe system and formulate the topic allocation as an
optimization problem under the resource constraints of edge servers. As the
optimization problem is NP-hard, we propose heuristics leveraging the locality
and the pub/sub relationships observed between clients to use the edge server
resources efficiently. Our performance evaluation shows that our method reduces
the delay to deliver notifications and the effectiveness of the strategy
exploiting the relationships between clients.


  I review some theoretical ideas in cosmology different from the standard "Big
Bang": the quasi-steady state model, the plasma cosmology model,
non-cosmological redshifts, alternatives to non-baryonic dark matter and/or
dark energy, and others. Cosmologists do not usually work within the framework
of alternative cosmologies because they feel that these are not at present as
competitive as the standard model. Certainly, they are not so developed, and
they are not so developed because cosmologists do not work on them. It is a
vicious circle. The fact that most cosmologists do not pay them any attention
and only dedicate their research time to the standard model is to a great
extent due to a sociological phenomenon (the "snowball effect" or
"groupthink"). We might well wonder whether cosmology, our knowledge of the
Universe as a whole, is a science like other fields of physics or a predominant
ideology.


  Nanomagnets with giant magnetic anisotropy energy and long coherence time are
desired for various technological innovations such as quantum information
procession and storage. Based on the first-principles calculations and model
analyses, we demonstrate that a single uranium atom substituting Al on the
Al2O3(0001) surface may have high structural stability and large magnetic
anisotropy energy up to 48 meV per uranium atom. As the magnetization resides
in the localized f-shell and is not much involved in chemical bonding with
neighbors, long coherence time up to ~1.6 mS can be achieved for the quantum
spin states. These results suggest a new strategy for the search of ultrasmall
magnetic units for diverse applications in the quantum information era.


  Two main hypotheses for the origin of Galactic cosmic rays are the
"supernova" and "superbubble" origin hypotheses. We analyse the evidence for
the superbubble hypothesis provided by the measurements of the relativive
abundances of isotopes of cobalt and nickel in the cosmic ray flux. We compare
the measured upper limit on the abundance of 59Ni in the cosmic ray flux with
the 59Ni abundance predictions of the up-to-date stellar evolution models.
Non-detection of 59Ni in the cosmic ray flux has previously been attributed to
a large time delay of the order of 1e5 yr between the moment of supernova
explosion and the onset of particle acceleration process. This large time delay
was considered as an argument in favour of the "superbubble" scenario. We show
that the recent calculation of the 59Ni yield of massive stars, which takes
into account the initial mass range up to 120 solar masses and includes stellar
rotation, results in prediction of low 59Ni abundance relative to its decay
product 59Co. The predicted abundance is consistent with the upper bound on
59Ni abundance in the cosmic ray flux for the supernova parameters assumed.
This result removes the necessity of decay of 59Ni in the time interval between
the supernova explosion and the onset of acceleration process and restores the
consistency of measurements of 59Ni / 59Co abundances with the "supernova"
hypothesis of the CR origin.


  Given a large edge-capacitated network $G$ and a subset of $k$ vertices
called terminals, an (exact) flow sparsifier is a small network $G'$ that
preserves (exactly) all multicommodity flows that can be routed between the
terminals. Flow sparsifiers were introduced by Leighton and Moitra [STOC 2010],
and have been studied and used in many algorithmic contexts.
  A fundamental question that remained open for over a decade, asks whether
every $k$-terminal network admits an exact flow sparsifier whose size is
bounded by some function $f(k)$ (regardless of the size of $G$ or its
capacities). We resolve this question in the negative by proving that there
exist $6$-terminal networks $G$ whose flow sparsifiers $G'$ must have
arbitrarily large size. This unboundedness is perhaps surprising, since the
analogous sparsification that preserves all terminal cuts (called exact cut
sparsifier or mimicking network) admits sparsifiers of size $f_0(k)\leq
2^{2^k}$ [Hagerup, Katajainen, Nishimura, and Ragde, JCSS 1998].
  We prove our results by analyzing the set of all feasible demands in the
network, known as the demand polytope. We identify an invariant of this
polytope, essentially the slope of certain facets, that can be made arbitrarily
large even for $k=6$, and implies an explicit lower bound on the size of the
network. We further use this technique to answer, again in the negative, an
open question of Seymour [JCTB 2015] regarding flow-sparsification that uses
only contractions and preserves the infeasibility of one demand vector.


  The rapid spread of COVID-19 has affected thousands of people from different
socio-demographic groups all over the country. A decisive step in preventing or
slowing the outbreak is the use of mobility interventions, such as government
stay-at-home orders. However, different socio-demographic groups might have
different responses to these orders and regulations. In this paper, we attempt
to fill the current gap in the literature by examining how different
communities with different age groups performed social distancing by following
orders such as the national emergency declaration on March 13, as well as how
fast they started changing their behavior after the regulations were imposed.
For this purpose, we calculated the behavior changes of people in different
mobility metrics, such as percentage of people staying home during the study
period (March, April, and May 2020), in different age groups in comparison to
the days before the pandemic (January and February 2020), by utilizing
anonymized and privacy-protected mobile device data. Our study indicates that
senior communities outperformed younger communities in terms of their behavior
change. Senior communities not only had a faster response to the outbreak in
comparison to young communities, they also had better performance consistency
during the pandemic.


  PDDL+ is an extension of PDDL2.1 which incorporates fully-featured autonomous
processes and allows for better modelling of mixed discrete-continuous domains.
Unlike PDDL2.1, PDDL+ lacks a logical semantics, relying instead on
state-transitional semantics enriched with hybrid automata semantics for the
continuous states. This complex semantics makes analysis and comparisons to
other action formalisms difficult. In this paper, we propose a natural
extension of Reiter's situation calculus theories inspired by hybrid automata.
The kinship between PDDL+ and hybrid automata allows us to develop a direct
mapping between PDDL+ and situation calculus, thereby supplying PDDL+ with a
logical semantics and the situation calculus with a modern way of representing
autonomous processes. We outline the potential benefits of the mapping by
suggesting a new approach to effective planning in PDDL+.


  We present an algorithm for the efficient sampling of conditional paths of
stochastic differential equations (SDEs). While unconditional path sampling of
SDEs is straightforward, albeit expensive for high dimensional systems of SDEs,
conditional path sampling can be difficult even for low dimensional systems.
This is because we need to produce sample paths of the SDE which respect both
the dynamics of the SDE and the initial and endpoint conditions. The dynamics
of a SDE are governed by the deterministic term (drift) and the stochastic term
(noise). Instead of producing conditional paths directly from the original SDE,
one can consider a sequence of SDEs with modified drifts. The modified drifts
should be chosen so that it is easier to produce sample paths which satisfy the
initial and endpoint conditions. Also, the sequence of modified drifts
converges to the drift of the original SDE. We construct a simple Markov Chain
Monte Carlo (MCMC) algorithm which samples, in sequence, conditional paths from
the modified SDEs, by taking the last sampled path at each level of the
sequence as an initial condition for the sampling at the next level in the
sequence. The algorithm can be thought of as a stochastic analog of
deterministic homotopy methods for solving nonlinear algebraic equations or as
a SDE generalization of simulated annealing. The algorithm is particularly
suited for filtering/smoothing applications. We show how it can be used to
improve the performance of particle filters. Numerical results for filtering of
a stochastic differential equation are included.


  This expository article supplies the mathematical background underpinning the
braid representation calculator introduced in arXiv:2212.00831; those
representations describe the sets of logic gates available to a topological
quantum computer for processing encoded qubits. Assuming little background in
category theory, we first recall the notion of a ribbon fusion category (RFC),
collecting most of the necessary definitions. Then we discuss how certain RFCs
arise from the representation theory of quantum groups. We explore the braiding
in these categories in detail, since it is essential for the quantum computing
application.


  NLTE effects - the errors caused by assuming local thermodynamic equilibrium
(LTE) - on LiBeB abundance determinations for cool stars are discussed. These
NLTE effects are significant in many cases for B I and Li I lines. The Be II
313 nm lines are not formed under LTE circumstances, but the NLTE effects on
equivalent widths seem to be rather small. Reasons for doing LTE abundance
analysis are discussed and confronted with the reasons for doing NLTE abundance
analysis. The impact of three-dimensional photospheric inhomogeneity on line
formation is discussed - there are not many definite results on this yet, but
there may be soon.


  Developers across the world use autonumber or auto sequences field of the
backend databases for developing both the desktop and web based data centric
applications which is easier to use at the development and deployment purpose
but can create a lot of problems under varied situations. This paper examines
how a database independent autonumber could be developed and reused solving all
the problems as well as providing the same degree of easy to use features of
autonumber offered by modern Relational Database Systems.


  Diffusion models have significantly advanced the fields of image, audio, and
video generation, but they depend on an iterative sampling process that causes
slow generation. To overcome this limitation, we propose consistency models, a
new family of models that generate high quality samples by directly mapping
noise to data. They support fast one-step generation by design, while still
allowing multistep sampling to trade compute for sample quality. They also
support zero-shot data editing, such as image inpainting, colorization, and
super-resolution, without requiring explicit training on these tasks.
Consistency models can be trained either by distilling pre-trained diffusion
models, or as standalone generative models altogether. Through extensive
experiments, we demonstrate that they outperform existing distillation
techniques for diffusion models in one- and few-step sampling, achieving the
new state-of-the-art FID of 3.55 on CIFAR-10 and 6.20 on ImageNet 64x64 for
one-step generation. When trained in isolation, consistency models become a new
family of generative models that can outperform existing one-step,
non-adversarial generative models on standard benchmarks such as CIFAR-10,
ImageNet 64x64 and LSUN 256x256.


  We propose a generalized finite element method for the strongly damped wave
equation with highly varying coefficients. The proposed method is based on the
localized orthogonal decomposition introduced and is designed to handle
independent variations in both the damping and the wave propagation speed
respectively. The method does so by automatically correcting for the damping in
the transient phase and for the propagation speed in the steady state phase.
Convergence of optimal order is proven in $L_2(H^1)$-norm, independent of the
derivatives of the coefficients. We present numerical examples that confirm the
theoretical findings.


  In this paper, we present a robotic navigation algorithm with natural
language interfaces, which enables a robot to safely walk through a changing
environment with moving persons by following human instructions such as "go to
the restaurant and keep away from people". We first classify human instructions
into three types: the goal, the constraints, and uninformative phrases. Next,
we provide grounding for the extracted goal and constraint items in a dynamic
manner along with the navigation process, to deal with the target objects that
are too far away for sensor observation and the appearance of moving obstacles
like humans. In particular, for a goal phrase (e.g., "go to the restaurant"),
we ground it to a location in a predefined semantic map and treat it as a goal
for a global motion planner, which plans a collision-free path in the workspace
for the robot to follow. For a constraint phrase (e.g., "keep away from
people"), we dynamically add the corresponding constraint into a local planner
by adjusting the values of a local costmap according to the results returned by
the object detection module. The updated costmap is then used to compute a
local collision avoidance control for the safe navigation of the robot. By
combining natural language processing, motion planning, and computer vision,
our developed system is demonstrated to be able to successfully follow natural
language navigation instructions to achieve navigation tasks in both simulated
and real-world scenarios. Videos are available at
https://sites.google.com/view/snhi


  Several problems in stochastic analysis are defined through their geometry,
and preserving that geometric structure is essential to generating meaningful
predictions. Nevertheless, how to design principled deep learning (DL) models
capable of encoding these geometric structures remains largely unknown. We
address this open problem by introducing a universal causal geometric DL
framework in which the user specifies a suitable pair of metric spaces
$\mathscr{X}$ and $\mathscr{Y}$ and our framework returns a DL model capable of
causally approximating any ``regular'' map sending time series in
$\mathscr{X}^{\mathbb{Z}}$ to time series in $\mathscr{Y}^{\mathbb{Z}}$ while
respecting their forward flow of information throughout time. Suitable
geometries on $\mathscr{Y}$ include various (adapted) Wasserstein spaces
arising in optimal stopping problems, a variety of statistical manifolds
describing the conditional distribution of continuous-time finite state Markov
chains, and all Fr\'{e}chet spaces admitting a Schauder basis, e.g. as in
classical finance. Suitable spaces $\mathscr{X}$ are compact subsets of any
Euclidean space. Our results all quantitatively express the number of
parameters needed for our DL model to achieve a given approximation error as a
function of the target map's regularity and the geometric structure both of
$\mathscr{X}$ and of $\mathscr{Y}$. Even when omitting any temporal structure,
our universal approximation theorems are the first guarantees that H\"{o}lder
functions, defined between such $\mathscr{X}$ and $\mathscr{Y}$ can be
approximated by DL models.


  We describe the first term of the $\Lambda_{k-1}\mathcal{C}$--spectral
sequence (see math.DG/0610917) of the diffiety (E,C), E being the infinite
prolongation of an l-normal system of partial differential equations, and C the
Cartan distribution on it.


  This paper derives optimal coefficients for optimized Schwarz iterations for
the time-dependent Stokes-Darcy problem using an innovative strategy to solve a
nonstandard min-max problem. The coefficients take into account both physical
and discretization parameters that characterize the coupled problem, and they
guarantee the robustness of the associated domain decomposition method.
Numerical results validate the proposed approach in several test cases with
physically relevant parameters.


  This article investigates privacy risks to those visiting health- related web
pages. The population of pages analyzed is derived from the 50 top search
results for 1,986 common diseases. This yielded a total population of 80,124
unique pages which were analyzed for the presence of third-party HTTP requests.
91% of pages were found to make requests to third parties. Investigation of
URIs revealed that 70% of HTTP Referer strings contained information exposing
specific conditions, treatments, and diseases. This presents a risk to users in
the form of personal identification and blind discrimination. An examination of
extant government and corporate policies reveals that users are insufficiently
protected from such risks.


  We present a combined tomographic weak gravitational lensing analysis of the
Kilo Degree Survey (KV450) and the Dark Energy Survey (DES-Y1). We homogenize
the analysis of these two public cosmic shear datasets by adopting consistent
priors and modeling of nonlinear scales, and determine new redshift
distributions for DES-Y1 based on deep public spectroscopic surveys. Adopting
these revised redshifts results in a $0.8\sigma$ reduction in the DES-inferred
value for $S_8$, which decreases to a $0.5\sigma$ reduction when including a
systematic redshift calibration error model from mock DES data based on the
MICE2 simulation. The combined KV450 + DES-Y1 constraint on $S_8 =
0.762^{+0.025}_{-0.024}$ is in tension with the Planck 2018 constraint from the
cosmic microwave background at the level of $2.5\sigma$. This result highlights
the importance of developing methods to provide accurate redshift calibration
for current and future weak lensing surveys.


  Planet-planetesimal interactions cause a planet to migrate, manifesting as a
random walk in semi-major axis. In models for Neptune's migration involving a
gravitational upheaval, this planetesimal-driven migration is a side-effect of
the dynamical friction required to damp Neptune's orbital eccentricitiy. This
migration is noisy, potentially causing Trans Neptunian Objects (TNOs) in mean
motion resonance to be lost. With Nbody simulations, we validate a
previously-derived analytic model for resonance retention and determine unknown
coefficients. We identify the impact of random-walk (noisy) migration on
resonance retention for resonances up to fourth order lying between 39 au and
75 au. Using a population estimate for the weak 7:3 resonance from the
well-characterized Outer Solar System Origins Survey (OSSOS), we rule out two
cases: (1) a planetesimal disk distributed between 13.3 and 39.9 au with
$\gtrsim$ 30 Earth masses in today's size distribution and $T_{\rm mig}
\gtrsim$ 40Myr and (2) a top-heavy size distribution with $\gtrsim$ 2000
Pluto-sized TNOs and $T_{\rm mig} \gtrsim$ 10Myr, where $T_{\rm mig}$ is
Neptune's migration timescale. We find that low-eccentricity TNOs in the
heavily populated 5:2 resonance are easily lost due to noisy migration.
Improved observations of the low-eccentricity region of the 5:2 resonance and
of weak mean motion resonances with Rubin Observatory's Legacy Survey of Space
and Time (LSST) will provide better population estimates, allowing for
comparison with our model's retention fractions and providing strong evidence
for or against Neptune's random interactions with planetesimals.


  We report Knight shift experiments on the superconducting heavy electron
material CeCoIn$_5$ that allow one to track with some precision the behavior of
the heavy electron Kondo liquid in the superconducting state with results in
agreement with BCS theory. An analysis of the $^{115}$In nuclear quadrupole
resonance (NQR) spin-lattice relaxation rate $T_1^{-1}$ measurements under
pressure reveals the presence of 2d magnetic quantum critical fluctuations in
the heavy electron component that are a promising candidate for the pairing
mechanism in this material. Our results are consistent with an
antiferromagnetic quantum critical point (QCP) located at slightly negative
pressure in CeCoIn$_5$ and provide additional evidence for significant
similarities between the heavy electron materials and the high $T_c$ cuprates.


  Learning computational models for visual attention (saliency estimation) is
an effort to inch machines/robots closer to human visual cognitive abilities.
Data-driven efforts have dominated the landscape since the introduction of deep
neural network architectures. In deep learning research, the choices in
architecture design are often empirical and frequently lead to more complex
models than necessary. The complexity, in turn, hinders the application
requirements. In this paper, we identify four key components of saliency
models, i.e., input features, multi-level integration, readout architecture,
and loss functions. We review the existing state of the art models on these
four components and propose novel and simpler alternatives. As a result, we
propose two novel end-to-end architectures called SimpleNet and MDNSal, which
are neater, minimal, more interpretable and achieve state of the art
performance on public saliency benchmarks. SimpleNet is an optimized
encoder-decoder architecture and brings notable performance gains on the
SALICON dataset (the largest saliency benchmark). MDNSal is a parametric model
that directly predicts parameters of a GMM distribution and is aimed to bring
more interpretability to the prediction maps. The proposed saliency models can
be inferred at 25fps, making them suitable for real-time applications. Code and
pre-trained models are available at https://github.com/samyak0210/saliency.


  We present results from the Suzaku observation of the microquasar GRS
1915+105 performed during the 2005 October multiwavelength campaign. The data
include both stable state (class \chi) and limit-cycle oscillation (class
\theta). Correct interstellar absorption as well as effects of dust scattering
are fully taken into account in the spectral analysis. The energy spectra in
the 2-120 keV band in both states are all dominated by strong Comptonization of
disk photons by an optically thick (\tau ~7-10) and low temperature (T_e ~2-3
keV) hybrid plasmas containing non-thermal electrons produced with 10-60% of
the total power input. Absorption lines of highly ionized Fe ions detected
during the oscillation indicate that a strong disk wind is developed. The
ionization stage of the wind correlates with the X-ray flux, supporting the
photoionization origin. The iron-K emission line shows a strong variability
during the oscillation; the reflection is strongest during the dip but
disappears during the flare. We interpret this as evidence for "self-shielding"
that the Comptonizing corona becomes geometrically thick in the flare phase,
preventing photons from irradiating the outer disk. The low-temperature and
high luminosity disk emission suggests that the disk structure is similar to
that in the very high state of canonical black hole binaries. The spectral
variability during the oscillation is explained by the change of the disk
geometry and of the physical parameters of Comptonizing corona, particularly
the fractional power supplied to the acceleration of non-thermal particles.


  A magnetic moment in a metal or in a quantum dot is, at low temperatures,
screened by the conduction electrons through the mechanism of the Kondo effect.
This gives rise to spin-spin correlations between the magnetic moment and the
conduction electrons, which can have a substantial spatial extension. We study
this phenomenon, the so-called Kondo cloud, by means of the density matrix
renormalization group method for the case of the single-impurity Anderson
model. We focus on the question whether the Kondo screening length, typically
assumed to be proportional to the inverse Kondo temperature, can be extracted
from the spin-spin correlations. For several mechanisms -- the gate potential
and a magnetic field -- which destroy the Kondo effect, we investigate the
behavior of the screening cloud induced by these perturbations.


  We study the structure of generalized parton distributions in impact
parameter space with the aim of determining the size and role of small
transverse separations components in the quarks wave function. We analyze the
relation between transverse momentum components and transverse separations.
Wave functions with large transverse momentum components can simultaneously
reproduce the behavior of the Dirac form factor at large momentum transfer, and
of the deep inelastic structure functions at Bjorken x -> 1. The presence of
large momentum components does not ensure, however, the dominance of small
transverse distances at large x. We suggest that experiments measuring the
attenuation of hadrons in the nuclear medium, or the onset of color
transparency, can provide an alternative source of information on generalized
parton distributions, by mapping out the behavior of the transverse components
of the wave function.


  This paper proposes a non-data-driven deep neural network for spectral image
recovery problems such as denoising, single hyperspectral image
super-resolution, and compressive spectral imaging reconstruction. Unlike
previous methods, the proposed approach, dubbed Mixture-Net, implicitly learns
the prior information through the network. Mixture-Net consists of a deep
generative model whose layers are inspired by the linear and non-linear
low-rank mixture models, where the recovered image is composed of a weighted
sum between the linear and non-linear decomposition. Mixture-Net also provides
a low-rank decomposition interpreted as the spectral image abundances and
endmembers, helpful in achieving remote sensing tasks without running
additional routines. The experiments show the MixtureNet effectiveness
outperforming state-of-the-art methods in recovery quality with the advantage
of architecture interpretability.


  In this paper we consider a class of stochastic differential equations driven
by subordinate Brownian motion with Markovian switching. We use Malliavin
calculus to study the smoothness of the density for the solution under uniform
H\"ormander's type condition.


  Let $\Phi $ be a Drinfeld $\mathbf{F}_{q}[T]$-module of rank 2, over a finite
field $L$, a finite extension of $n$ degrees for a finite field with $q$
elements $% \mathbf{F}_{q}$. Let $P_{\Phi}(X)=$ $X^{2}-cX+\mu P^{m}$ ($c$ an
element of $% \mathbf{F}_{q}[T]$ and $\mu $ a no null element of
$\mathbf{F}_{q}$, $m$ the degree of the extension $L$ over the field
$\mathbf{F}_{q}[T]/P$, $P$ is a $\mathbf{F}%_{q}[T]$-characteristic of $L$ and
$d$ the degree of the polynomial $P$) the characteristic polynomial, of the
Frobenius $F$ of $L$. We will interested to the structure of finite
$\mathbf{F}_{q}[T]$-module $L^{\Phi}$ deduct by $\Phi $ over $L$ and will proof
our main result, the analogue of Deuring theorem for the elliptic curves : Let
$M=\frac{\mathbf{F}%_{q}[T]}{I_{1}}\oplus \frac{\mathbf{F}_{q}[T]}{I_{2}}$,
where $I_{1}=(i_{1})$,$% I_{2}=(i_{2})$ ($i_{1}$, $i_{2}$ two polynomials of
$\mathbf{F}_{q}[T]$%) and such that : $i_{2}\mid (c-2)$. Then there exists an
ordinary Drinfeld $\mathbf{F}_{q}[T]$% -module $\Phi $ over $L$ of rank 2, such
that : $% L^{\Phi}$ $\simeq M$. We finish by a statistic about the cyclicity of
such structure $L^{\Phi}$, and we prove that is cyclic only for the trivial
extensions of $\mathbf{F}_{q}$.


  Long Reed-Solomon (RS) codes are desirable for digital communication and
storage systems due to their improved error performance, but the high
computational complexity of their decoders is a key obstacle to their adoption
in practice. As discrete Fourier transforms (DFTs) can evaluate a polynomial at
multiple points, efficient DFT algorithms are promising in reducing the
computational complexities of syndrome based decoders for long RS codes. In
this paper, we first propose partial composite cyclotomic Fourier transforms
(CCFTs) and then devise syndrome based decoders for long RS codes over large
finite fields based on partial CCFTs. The new decoders based on partial CCFTs
achieve a significant saving of computational complexities for long RS codes.
Since partial CCFTs have modular and regular structures, the new decoders are
suitable for hardware implementations. To further verify and demonstrate the
advantages of partial CCFTs, we implement in hardware the syndrome computation
block for a $(2720, 2550)$ shortened RS code over GF$(2^{12})$. In comparison
to previous results based on Horner's rule, our hardware implementation not
only has a smaller gate count, but also achieves much higher throughputs.


  We use dynamic scanning capacitance microscopy (DSCM) to image compressible
and incompressible strips at the edge of a Hall bar in a two-dimensional
electron gas (2DEG) in the quantum Hall effect (QHE) regime. This method gives
access to the complex local conductance, Gts, between a sharp metallic tip
scanned across the sample surface and ground, comprising the complex sample
conductance. Near integer filling factors we observe a bright stripe along the
sample edge in the imaginary part of Gts. The simultaneously recorded real part
exhibits a sharp peak at the boundary between the sample interior and the
stripe observed in the imaginary part. The features are periodic in the inverse
magnetic field and consistent with compressible and incompressible strips
forming at the sample edge. For currents larger than the critical current of
the QHE break-down the stripes vanish sharply and a homogeneous signal is
recovered, similar to zero magnetic field. Our experiments directly illustrate
the formation and a variety of properties of the conceptually important QHE
edge states at the physical edge of a 2DEG.