  We consider the nonaxisymmetric modes of instability present in
Taylor-Couette flow under the application of helical magnetic fields, mainly
for magnetic Prandtl numbers close to the inductionless limit, and conduct a
full examination of marginal stability in the resulting parameter space. We
allow for the azimuthal magnetic field to be generated by a combination of
currents in the inner cylinder and fluid itself, and introduce a parameter
governing the relation between the strength of these currents. A set of
governing eigenvalue equations for the nonaxisymmetric modes of instability are
derived and solved by spectral collocation with Chebyshev polynomials over the
relevant parameter space, with the resulting instabilities examined in detail.
We find that by altering the azimuthal magnetic field profiles the azimuthal
magnetorotational instability, nonaxisymmetric helical magnetorotational
instability, and Tayler instability yield interesting dynamics, such as
different preferred mode types, and modes with azimuthal wave number $m>1$.
Finally, a comparison is given to the recent WKB analysis performed by Kirillov
$et$ $al$. [Kirillov, Stefani, and Fukumoto, J. Fluid Mech. 760, 591 (2014)]
and its validity in the linear regime.


  Using 462/fb of e+e- annihilation data recorded by the Belle detector, we
report the first observation of the decay Ds1(2536)+ -> D+pi-K+. The ratio of
branching fractions B(Ds1+ -> D+pi-K+)/B(Ds1+ -> D*+K0) is measured to be
(3.27+-0.18+-0.37)%. We also study the angular distributions in the Ds1(2536)+
-> D*+K0S decay and measure the ratio of D- and S-wave amplitudes. The S-wave
dominates, with a partial width of Gamma_S/Gamma_total=0.72+-0.05+-0.01.


  Interpretation of the energy spectrum and arrival distribution of cosmic rays
is complicated by lack of knowledge of the nature of the primaries. We review
claims for the mass composition above 1017 eV where it can be determined only
indirectly from air-shower observables. Difficulties in comparisons between
data arise because, inevitably, a set of measurements is interpreted using the
best model of hadronic interactions available at the time of analysis. We
discuss the situation and conclude that the evidence for a proton-dominated
mass composition, even at the highest energies, is unconvincing. However, it
may be that there are consistent differences between mass measurements from
optical techniques and those based upon other shower observables. We also find
that iron nuclei of ultra high energy can probably escape from the galaxies
that host GRBs, possible cosmic ray accelerators. The accelerators must lie
nearby.


  We forecast the ability of cosmic microwave background (CMB) temperature and
polarization datasets to constrain theories of eternal inflation using cosmic
bubble collisions. Using the Fisher matrix formalism, we determine both the
overall detectability of bubble collisions and the constraints achievable on
the fundamental parameters describing the underlying theory. The CMB signatures
considered are based on state-of-the-art numerical relativistic simulations of
the bubble collision spacetime, evolved using the full temperature and
polarization transfer functions. Comparing a theoretical
cosmic-variance-limited experiment to the WMAP and Planck satellites, we find
that there is no improvement to be gained from future temperature data, that
adding polarization improves detectability by approximately 30%, and that
cosmic-variance-limited polarization data offer only marginal improvements over
Planck. The fundamental parameter constraints achievable depend on the precise
values of the tensor-to-scalar ratio and energy density in (negative) spatial
curvature. For a tensor-to-scalar ratio of $0.1$ and spatial curvature at the
level of $10^{-4}$, using cosmic-variance-limited data it is possible to
measure the width of the potential barrier separating the inflating false
vacuum from the true vacuum down to $M_{\rm Pl}/500$, and the initial proper
distance between colliding bubbles to a factor $\pi/2$ of the false vacuum
horizon size (at three sigma). We conclude that very near-future data will have
the final word on bubble collisions in the CMB.


  Emerging applications -- cloud computing, the internet of things, and
augmented/virtual reality -- demand responsive, secure, and scalable datacenter
networks. These networks currently implement simple, per-packet, data-plane
heuristics (e.g., ECMP and sketches) under a slow, millisecond-latency control
plane that runs data-driven performance and security policies. However, to meet
applications' service-level objectives (SLOs) in a modern data center, networks
must bridge the gap between line-rate, per-packet execution and complex
decision making.
  In this work, we present the design and implementation of Taurus, a data
plane for line-rate inference. Taurus adds custom hardware based on a flexible,
parallel-patterns (MapReduce) abstraction to programmable network devices, such
as switches and NICs; this new hardware uses pipelined SIMD parallelism to
enable per-packet MapReduce operations (e.g., inference). Our evaluation of a
Taurus switch ASIC -- supporting several real-world models -- shows that Taurus
operates orders of magnitude faster than a server-based control plane while
increasing area by 3.8% and latency for line-rate ML models by up to 221 ns.
Furthermore, our Taurus FPGA prototype achieves full model accuracy and detects
two orders of magnitude more events than a state-of-the-art control-plane
anomaly-detection system.


  Aims: NGC 1530 has one of the strongest bars ever observed and recent star
formation sites are distributed across its bar. Our aim is to study the
photometric properties of the bar and its HII regions, to elucidate the
conditions under which HII regions form and their spatial relation to the
principal dynamical features of the bar. Methods: We obtained BVRKs and Halpha
photometry of the HII regions of the bar in NGC 1530. Broad-band integrated
colours and Halpha equivalent widths were carefully measured and analysed as a
function of position with respect to the main dust-lanes of the bar. Results:
We measured differences in the Halpha equivalent widths of the HII regions that
are located in the trailing and leading sides of the bar dust-lane. The
possible factors that could produce this difference, such as [NII]
contamination, Lyman-continuum-photon dust-extinction, escape of ionizing
radiation, metallicity, IMF and age, were carefully analysed. Age differences
were confirmed to be the most plausible explanation. This implies that HII
regions that are located further away from the bar dust-lane in its leading
side, downstream from the main bar dust-lane, are older than the rest by
~1.5-2.5 Myr. In addition, a clear spatial correlation has been found between:
location of HII regions, dust spurs on the trailing side of the bar dust-lane,
and the loci of maximum velocity gradients parallel to the bar major axis
(possibly tracing gas flow towards the main bar dust-lane). These results
support the hypothesis that massive stars are forming on the trailing side of
the bar dust-lane, and age as they cross the bar, on a timescale that is
compatible with the bar dynamics timescale.


  This paper investigates an open problem introduced in [14]. Two or more
mobile agents start from different nodes of a network and have to accomplish
the task of gathering which consists in getting all together at the same node
at the same time. An adversary chooses the initial nodes of the agents and
assigns a different positive integer (called label) to each of them. Initially,
each agent knows its label but does not know the labels of the other agents or
their positions relative to its own. Agents move in synchronous rounds and can
communicate with each other only when located at the same node. Up to f of the
agents are Byzantine. A Byzantine agent can choose an arbitrary port when it
moves, can convey arbitrary information to other agents and can change its
label in every round, in particular by forging the label of another agent or by
creating a completely new one.
  What is the minimum number M of good agents that guarantees deterministic
gathering of all of them, with termination?
  We provide exact answers to this open problem by considering the case when
the agents initially know the size of the network and the case when they do
not. In the former case, we prove M=f+1 while in the latter, we prove M=f+2.
More precisely, for networks of known size, we design a deterministic algorithm
gathering all good agents in any network provided that the number of good
agents is at least f+1. For networks of unknown size, we also design a
deterministic algorithm ensuring the gathering of all good agents in any
network but provided that the number of good agents is at least f+2. Both of
our algorithms are optimal in terms of required number of good agents, as each
of them perfectly matches the respective lower bound on M shown in [14], which
is of f+1 when the size of the network is known and of f+2 when it is unknown.


  Heart failure (HF) affects at least 26 million people worldwide, so
predicting adverse events in HF patients represents a major target of clinical
data science. However, achieving large sample sizes sometimes represents a
challenge due to difficulties in patient recruiting and long follow-up times,
increasing the problem of missing data. To overcome the issue of a narrow
dataset cardinality (in a clinical dataset, the cardinality is the number of
patients in that dataset), population-enhancing algorithms are therefore
crucial. The aim of this study was to design a random shuffle method to enhance
the cardinality of an HF dataset while it is statistically legitimate, without
the need of specific hypotheses and regression models. The cardinality
enhancement was validated against an established random repeated-measures
method with regard to the correctness in predicting clinical conditions and
endpoints. In particular, machine learning and regression models were employed
to highlight the benefits of the enhanced datasets. The proposed random shuffle
method was able to enhance the HF dataset cardinality (711 patients before
dataset preprocessing) circa 10 times and circa 21 times when followed by a
random repeated-measures approach. We believe that the random shuffle method
could be used in the cardiovascular field and in other data science problems
when missing data and the narrow dataset cardinality represent an issue.


  A three-dimensional nonlinear dynamo process is identified in rotating plane
Couette flow in the Keplerian regime. It is analogous to the hydrodynamic
self-sustaining process in non-rotating shear flows and relies on the
magneto-rotational instability of a toroidal magnetic field. Steady nonlinear
solutions are computed numerically for a wide range of magnetic Reynolds
numbers but are restricted to low Reynolds numbers. This process may be
important to explain the sustenance of coherent fields and turbulent motions in
Keplerian accretion disks, where all its basic ingredients are present.


  We consider theoretically ${}^{13}$C-hyperfine interaction induced dephasing
in carbon nanotubes double quantum dots with curvature induced spin-orbit
coupling. For two electrons initially occupying a single dot, we calculate the
average return probability after separation into the two dots, which have
random nuclear-spin configurations. We focus on the long time saturation value
of the return probability, $P_\infty$. Because of the valley degree of freedom,
the analysis is more complex than in, for example, GaAs quantum dots, which
have two distinct $P_\infty$ values depending on the magnetic field. Here the
prepared state and the measured state is non-unique because two electrons in
the same dot are allowed in six different states. Moreover, for one electron in
each dot sixteen states exist and therefore are available for being mixed by
the hyperfine field. The return probability experiment is found to be strongly
dependent on the prepared state, on the external magnetic field---both Zeeman
and orbital effects - and on the spin-orbit splitting. The lowest saturation
value, being $P_\infty$=1/3, occurs at zero magnetic field for nanotubes with
spin-orbit coupling and the initial state being the groundstate, this situation
is equivalent to double dots without the valley degree of freedom. In total, we
report nine dynamically different situations that give $P_\infty$=1/3, 3/8,
2/5, 1/2 and for valley anti-symmetric prepared states in an axial magnetic
field, $P_\infty$=1. When the groundstate is prepared the ratio between the
spin-orbit splitting and the Zeeman energy due to a perpendicular magnetic
field can tune the effective hyperfine field continuously from being three
dimensional to two dimensional giving saturation values from $P_\infty$=1/3 to
3/8.


  We study the measure of complexity in solid Argon system from the time series
data of kinetic energy of single Argon atoms at different equilibrated
temperatures. To account the inherent multi-scale dependence of the complexity,
the multi-scale entropy of the time series of kinetic energy of individual
Argon atoms are computed at different equilibrated temperatures. The
multi-scale entropy study reveals that the dynamics of an atom becomes more
complex at higher temperatures and the result corroborates well with the
variation of the pair correlation function of the atoms in the solid Argon
crystal. Also, we repeat the multi-scale entropy analysis for program generated
Levy noise time series and for time series data obtained from the outcomes of
exponential decay with noise dx(t) = -x(t) dt + sigma dB(t) (Langevin
equation). Our study establishes that the scale dependence of sample entropy
for time series of kinetic energy of individual atoms in solid Argon system has
similar tendency as that of Levy noise time series and the outcomes of
exponential decay with noise (Langevin equation).


  High-resolution neutron backscattering techniques are exploited to study the
elastic and quasi-elastic response of the high-density amorphous (HDA), the
low-density amorphous (LDA) and the crystalline ice Ic upon temperature
changes. Within the temperature ranges of their structural stability (HDA at T
> 80 K, LDA at T > 135 K, ice Ic at T < 200 K) the Debye-Waller factors and
mean-square displacements characterise all states as harmonic solids. During
the transformations HDA->LDA (T ~ 100 K), LDA->Ic (T ~ 150K) and the supposed
glass transition with Tg ~ 135 K no relaxation processes can be detected on a
time scale t < 4 ns. It can be concluded from coherent scattering measurements
(D_2O) that LDA starts to recrystallise into ice Ic at T ~ 135 K, i.e. at the
supposed Tg. In the framework of the Debye model of harmonic solids HDA reveals
the highest Debye temperature among the studied ice phases, which is in full
agreement with the lowest Debye level in the generalised density of states
derived from time-of-flight neutron scattering experiments. The elastic results
at low T indicate the presence of an excess of modes in HDA, which do not obey
the Bose statistics.


  We investigate the quantum field aspects in flat spacetime for an uniformly
accelerated observer moving in a thermal bath. In particular, we obtain an
exact closed expression of the reduced density matrix for an uniformly
accelerated observer with acceleration $a = 2\pi T$ when the state of the
quantum field is a thermal bath at temperature $T^\prime$. We find that the
density matrix has a simple form with an effective partition function $Z$ being
a product, $Z = Z_T Z_{T^\prime}$, of two thermal partition functions
corresponding to temperatures $T$ and $T^\prime$ and hence is not thermal, even
when $T = T^\prime$. We show that, even though the partition function has a
product structure, the two thermal baths are, in fact, interacting systems;
although in the high frequency limit $\omega_k \gg T$ and $\omega_k \gg
T^\prime$, the interactions are found to become sub-dominant. We further
demonstrate that the resulting spectrum of the Rindler particles can be
interpreted in terms of spontaneous and stimulated emission due to the
background thermal bath. The density matrix is also found to be symmetric in
the acceleration temperature $T$ and the thermal bath temperature $T^\prime$
indicating that thermodynamic experiments alone cannot distinguish between the
thermal effects due to $T$ and those due to $T^\prime$. The entanglement
entropy associated with the reduced density matrix (with the background
contribution of the Davies-Unruh bath removed) is shown to satisfy, in the
$\omega_k \gg T^\prime$ limit, a first law of thermodynamics relation of the
form $T \delta S = \delta E$ where $\delta E$ is the difference in the energies
corresponding to the reduced density matrix and the background Davies-Unruh
bath. The implications are discussed.


  The formation of a circumstellar disk in collapsing cloud cores is
investigated with three-dimensional magnetohydrodynamic simulations. We prepare
four types of initial cloud having different density profiles and calculate
their evolution with or without a sink. To investigate the effect of magnetic
dissipation on disk formation, the Ohmic dissipation is considered in some
models. Calculations show that disk formation is very sensitive to both the
initial cloud configuration and the sink treatment. The disk size considerably
differs in clouds with different density profiles even when the initial clouds
have almost the same mass-to-flux ratio. Only a very small disk (\sim 10 AU in
size) appears in clouds with a uniform density profile, whereas a large disk
(\sim 100 AU in size) forms in clouds with a Bonnor-Ebert density profile. In
addition, a large sink accretion radius numerically impedes disk formation
during the main accretion phase and tends to foster the misleading notion that
disk formation is completely suppressed by magnetic braking. The protostellar
outflow is also greatly affected by the sink properties. A sink accretion
radius of \lesssim 1 AU and sink threshold density of \gtrsim 10^ 13 cm^-3 are
necessary for investigating disk formation during the main accretion phase.


  The Atoyac River is among the two most polluted in Mexico. Water quality in
the Upper Atoyac River Basin (UARB) has been devastated by industrial and
municipal wastewater, as well as from effluents from local dwellers, that go
through little to no treatment, affecting health, production, ecosystems and
property value. We did a systematic review and mapping of the costs that
pollution imposes on different sectors and localities in the UARB, and
initially found 358 studies, of which 17 were of our particular interest. We
focus on estimating the cost of pollution through different valuation methods
such as averted costs, hedonic pricing, and contingent valuation, and for that
we only use 10 studies. Costs range from less than a million to over $16
million dollars a year, depending on the sector, with agriculture, industry and
tourism yielding the highest costs. This exercise is the first of its kind in
the UARB that maps costs for sectors and localities affected, and sheds light
on the need of additional research to estimate the total cost of pollution
throughout the basin. This information may help design further research needs
in the region.


  The technological progress in spatial-light modulators (SLM) technology has
made it possible to use those devices as programmable active focal-plane phase
coronagraphic masks, opening the door to novel versatile and adaptive
high-contrast imaging observation strategies. However, the scalar nature of the
SLM-induced phase response is a potential hurdle when applying the approach to
wideband light, as is typical in astronomical imaging. For the first time, we
present laboratory results with broadband light (up to ~12pc bandwidth) for two
commercially-available SLM devices used as active focal-plane phase masks in
the visible regime (640 nm). It is shown that under ideal or realistic
telescope aperture conditions, the contrast performance is negligibly affected
in this bandwidth regime, reaching sufficient level for ground-based
high-contrast imaging, which is typically dominated by atmospheric residuals.


  We study reconnections of quantum vortices by numerically solving the
governing Gross-Pitaevskii equation. We find that the minimum distance between
vortices scales differently with time before and after the vortex reconnection.
We also compute vortex reconnections using the Biot-Savart law for vortex
filaments of infinitesimal thickness, and find that, in this model,
reconnection are time-symmetric. We argue that the likely cause of the
difference between the Gross-Pitaevskii model and the Biot-Savart model is the
intense rarefaction wave which is radiated away from a Gross-Pitaeveskii
reconnection. Finally we compare our results to experimental observations in
superfluid helium, and discuss the different length scales probed by the two
models and by experiments.


  Constraints on a spin-independent interaction by exchange of a neutral light
boson are derived from precision data on the electron anomalous magnetic moment
and from atomic spectroscopy of hydrogen and deuterium atoms. The mass range
from $1 $eV$/c^2$ to $1 $Mev$/c^2$ is studied and the effective coupling
constant $\alpha^\prime$ is allowed below the level of $10^{-11} - 10^{-13}$
depending on the value of the boson mass. The mass range corresponds to the
Yukawa radius from 0.0002 nm to 20 nm, which covers the distances far above and
far below the Bohr radius of the hydrogen atom.


  This paper reports on the state of the art in underground SLAM by discussing
different SLAM strategies and results across six teams that participated in the
three-year-long SubT competition. In particular, the paper has four main goals.
First, we review the algorithms, architectures, and systems adopted by the
teams; particular emphasis is put on lidar-centric SLAM solutions (the go-to
approach for virtually all teams in the competition), heterogeneous multi-robot
operation (including both aerial and ground robots), and real-world underground
operation (from the presence of obscurants to the need to handle tight
computational constraints). We do not shy away from discussing the dirty
details behind the different SubT SLAM systems, which are often omitted from
technical papers. Second, we discuss the maturity of the field by highlighting
what is possible with the current SLAM systems and what we believe is within
reach with some good systems engineering. Third, we outline what we believe are
fundamental open problems, that are likely to require further research to break
through. Finally, we provide a list of open-source SLAM implementations and
datasets that have been produced during the SubT challenge and related efforts,
and constitute a useful resource for researchers and practitioners.


  We calculate the spectral gap of the Markov matrix of the totally asymmetric
simple exclusion process (TASEP) on a ring of L sites with N particles. Our
derivation is simple and self-contained and extends a previous calculation that
was valid only for half-filling. We use a special property of the Bethe
equations for TASEP to reformulate them as a one-body problem. Our method is
closely related to the one used to derive exact large deviation functions of
the TASEP.


  Machine learning is at the center of mainstream technology and outperforms
classical approaches to handcrafted feature design. Aside from its learning
process for artificial feature extraction, it has an end-to-end paradigm from
input to output, reaching outstandingly accurate results. However, security
concerns about its robustness to malicious and imperceptible perturbations have
drawn attention since its prediction can be changed entirely. Salient object
detection is a research area where deep convolutional neural networks have
proven effective but whose trustworthiness represents a significant issue
requiring analysis and solutions to hackers' attacks. Brain programming is a
kind of symbolic learning in the vein of good old-fashioned artificial
intelligence. This work provides evidence that symbolic learning robustness is
crucial in designing reliable visual attention systems since it can withstand
even the most intense perturbations. We test this evolutionary computation
methodology against several adversarial attacks and noise perturbations using
standard databases and a real-world problem of a shorebird called the Snowy
Plover portraying a visual attention task. We compare our methodology with five
different deep learning approaches, proving that they do not match the symbolic
paradigm regarding robustness. All neural networks suffer significant
performance losses, while brain programming stands its ground and remains
unaffected. Also, by studying the Snowy Plover, we remark on the importance of
security in surveillance activities regarding wildlife protection and
conservation.


  Special polynomials associated with rational solutions of the second
Painlev\'{e} equation and other members of its hierarchy are discussed. New
approach, which allows one to construct each polynomial is presented. The
structure of the polynomials is established. Formulas of their coefficients are
found. Correlations between the roots of every polynomial are obtained.


  Critical phenomena emerging from the critical end point of a first-order
transition are ubiquitous in nature. Here we bring the concept of a
supercritical crossover, the Widom line, initially developed in the context of
fluids, into the interacting matter described by quantum chromodynamics (QCD).
We show that the existence of the putative critical end point between hadron
gas and quark-gluon plasma in the temperature versus chemical potential of the
QCD phase diagram implies the existence of a Widom line emerging from it in the
supercritical region. We survey the thermodynamic anomalies already identified
in simplified theoretical models of QCD exhibiting a critical end point, to
show that they can be interpreted in terms of a Widom line. Then we suggest
possible directions where the Widom line concept could provide new light on the
QCD phase diagram.


  Let $T$ be a positive closed current of bidimension $(p,p)$ with unit mass on
the complex projective space $\mathbb P^n$. For certain values of $\alpha$ and
$\beta = \beta(p, \alpha)$ we show that if $T$ has enough points where the
Lelong number is at least $\alpha$, then the upper level set $E_{\beta}^+ (T)$
of points where $T$ has Lelong number strictly larger than $\beta$ has certain
geometric properties.


  Modern computational advances have enabled easy parallel implementations of
Markov chain Monte Carlo (MCMC). However, almost all work in estimating the
variance of Monte Carlo averages, including the efficient batch means (BM)
estimator, focuses on a single-chain MCMC run. We demonstrate that simply
averaging covariance matrix estimators from multiple chains can yield critical
underestimates in small Monte Carlo sample sizes, especially for slow-mixing
Markov chains. We extend the work of \cite{arg:and:2006} and propose a
multivariate replicated batch means (RBM) estimator that utilizes information
from parallel chains, thereby correcting for the underestimation. Under weak
conditions on the mixing rate of the process, RBM is strongly consistent and
exhibits similar large-sample bias and variance to the BM estimator. We also
exhibit superior theoretical properties of RBM by showing that the (negative)
bias in the RBM estimator is less than the average BM estimator in the presence
of positive correlation in MCMC. Consequently, in small runs, the RBM estimator
can be dramatically superior and this is demonstrated through a variety of
examples.


  We study minimum entropy submodular optimization, a common generalization of
the minimum entropy set cover problem, studied earlier by Cardinal et al., and
the submodular set cover problem.
  We give a general bound of the approximation performance of the greedy
algorithm using an approach that can be interpreted in terms of a particular
type of biased network flows. As an application we rederive known results for
the Minimum Entropy Set Cover and Minimum Entropy Orientation problems, and
obtain a nontrivial bound for a new problem called the Minimum Entropy Spanning
Tree problem.
  The problem can be applied to (and is partly motivated by) the definition of
worst-case approaches to fairness in concave cooperative games, similar to the
notion of price of anarchy in noncooperative settings.


  This article investigates higher dimensional vacuum solutions of the Einstein
equations. Generalizations of the definitions of spherical and axial symmetry
to higher dimensions are discussed before analyzing specific solutions bearing
one of these symmetries. The effective motions of the Tangherlini metric are
calculated and its Kruskal continuation is derived. Also the Myers-Perry metric
is analyzed with respect to its causal and horizontal structure.


  Given a Lipschitz function $f:\{1,...,d\}^\mathbb{N} \to \mathbb{R}$, for
each $\beta>0$ we denote by $\mu_\beta$ the equilibrium measure of $\beta f$
and by $h_\beta$ the main eigenfunction of the Ruelle Operator $L_{\beta f}$.
Assuming that $\{\mu_{\beta}\}_{\beta>0}$ satisfy a large deviation principle,
we prove the existence of the uniform limit $V=
\lim_{\beta\to\infty}\frac{1}{\beta}\log(h_{\beta})$. Furthermore, the
expression of the deviation function is determined by its values at the points
of the union of the supports of maximizing measures. We study a class of
potentials having two ergodic maximizing measures and prove that a L.D.P. is
satisfied. The deviation function is explicitly exhibited and does not coincide
with the one that appears in the paper by Baraviera-Lopes-Thieullen which
considers the case of potentials having a unique maximizing measure.


  Recent advances in numerical relativity have revealed how marginally trapped
surfaces behave when black holes merge. It is now known that interesting
topological features emerge during the merger, and marginally trapped surfaces
can have self-intersections. This paper presents the most detailed study yet of
the physical and geometric aspects of this scenario. For the case of a head-on
collision of non-spinning black holes, we study in detail the world tube formed
by the evolution of marginally trapped surfaces. In the first of this two-part
study, we focus on geometrical properties of the dynamical horizons, i.e. the
world tube traced out by the time evolution of marginally outer trapped
surfaces. We show that even the simple case of a head-on collision of
non-spinning black holes contains a rich variety of geometric and topological
properties and is generally more complex than considered previously in the
literature. The dynamical horizons are shown to have mixed signature and are
not future marginally trapped everywhere. We analyze the area increase of the
marginal surfaces along a sequence which connects the two initially disjoint
horizons with the final common horizon. While the area does increase overall
along this sequence, it is not monotonic. We find short durations of anomalous
area change which, given the connection of area with entropy, might have
interesting physical consequences. We investigate the possible reasons for this
effect and show that it is consistent with existing proofs of the area increase
law.


  We uncover an unexpected connection between the physics of loop integrals and
the mathematics of spline functions. One loop integrands are Laplace transforms
of splines. This clarifies the geometry of the associated loop integrals, since
a $n$-node spline has support on an $n$-vertex polyhedral cone. One-loop
integrals are integrals of splines on a hyperbolic slice of the cone, yielding
polytopes in $AdS$ space. Splines thus give a geometrical counterpart to the
rational function identities at the level of the integrand. Spline technology
also allows for a clear, simple, algebraic decomposition of higher point loop
integrals in lower dimensional kinematics in terms of lower point integrals -
e.g. an hexagon integral in 2d kinematics can be written as a sum of scalar
boxes. Higher loops can also be understood directly in terms of splines - they
map onto spline convolutions, leading to an intriguing representation in terms
of hyperbolic simplices integrated over other hyperbolic simplices. We finish
with speculations on the interpretation of one-loop integrals as partition
functions, inspired by the use of splines in counting points in polytopes.


  We calculate P(k_\perp), the probability distribution for an energetic parton
that propagates for a distance L through a medium without radiating to pick up
transverse momentum k_\perp, for a medium consisting of weakly coupled
quark-gluon plasma. We use full or HTL self-energies in appropriate regimes,
resumming each in order to find the leading large-L behavior. The jet quenching
parameter \hat q is the second moment of P(k_\perp), and we compare our results
to other determinations of this quantity in the literature, although we
emphasize the importance of looking at P(k_\perp) in its entirety. We compare
our results for P(k_\perp) in weakly coupled quark-gluon plasma to expectations
from holographic calculations that assume a plasma that is strongly coupled at
all length scales. We find that the shape of P(k_\perp) at modest k_\perp may
not be very different in weakly coupled and strongly coupled plasmas, but we
find that P(k_\perp) must be parametrically larger in a weakly coupled plasma
than in a strongly coupled plasma at large enough k_\perp. This means that by
looking for rare (but not exponentially rare) large-angle deflections of the
jet resulting from a parton produced initially back-to-back with a hard photon,
experimentalists can find the weakly coupled short-distance quark and gluon
quasiparticles within the strongly coupled liquid quark-gluon plasma produced
in heavy ion collisions, much as Rutherford found nuclei within atoms or
Friedman, Kendall and Taylor found quarks within nucleons.


  Smartphone carrier companies rely on mobile networks for keeping an accurate
record of customer data usage for billing purposes. In this paper, we present a
vulnerability that allows an attacker to force the victim's smartphone to
consume data through the cellular network by starting the data download on the
victim's cell phone without the victim's knowledge. The attack is based on
switching the victim's smartphones from the Wi-Fi network to the cellular
network while downloading a large data file. This attack has been implemented
in real-life scenarios where the test's outcomes demonstrate that the attack is
feasible and that mobile networks do not record customer data usage accurately.


  We develop approximate estimation methods for exponential random graph models
(ERGMs), whose likelihood is proportional to an intractable normalizing
constant. The usual approach approximates this constant with Monte Carlo
simulations, however convergence may be exponentially slow. We propose a
deterministic method, based on a variational mean-field approximation of the
ERGM's normalizing constant. We compute lower and upper bounds for the
approximation error for any network size, adapting nonlinear large deviations
results. This translates into bounds on the distance between true likelihood
and mean-field likelihood. Monte Carlo simulations suggest that in practice our
deterministic method performs better than our conservative theoretical
approximation bounds imply, for a large class of models.


  We investigate the intersubband spin-density-excitation spectrum of a double
quantum well in a low-density symmetry-broken phase with interwell
antiferromagnetic correlations. This spectrum is related to the intensity
measured in depolarized inelastic light scattering (ILS) experiments and
therefore provides a means of empirically identifying the antiferromagnetic
phase. Our computations reveal the existence of two collective modes, a damped
Nambu-Goldstone (NG) mode arising from the broken spin symmetry and an undamped
optical mode. Since the NG mode contains most of the spectral weight, ILS
experiments will need to examine the low-frequency response for signatures of
the antiferromagnetic phase.


  Godsil-McKay switching is an operation on graphs that doesn't change the
spectrum of the adjacency matrix. Usually (but not always) the obtained graph
is non-isomorphic with the original graph. We present a straightforward
sufficient condition for being isomorphic after switching, and give examples
which show that this condition is not necessary. For some graph products we
obtain sufficient conditions for being non-isomorphic after switching. As an
example we find that the tensor product of the $\ell\times m$ grid ($\ell>m\geq
2$) and a graph with at least one vertex of degree two is not determined by its
adjacency spectrum.


  Cylindrical implosions driven by intense heavy ions beams should be
instrumental in a near future to study High Energy Density Matter. By rotating
the beam by means of a high frequency wobbler, it should be possible to deposit
energy in the outer layers of a cylinder, compressing the material deposited in
its core. The beam temporal profile should however generate an inevitable
irradiation asymmetry likely to feed the Rayleigh-Taylor instability (RTI)
during the implosion phase. In this paper, we compute the Fourier components of
the target irradiation in order to make the junction with previous works on RTI
performed in this setting. Implementing a 1D and 2D beam models, we find these
components can be expressed exactly in terms of the Fourier transform of the
temporal beam profile. If $T$ is the beam duration and $\Omega$ its rotation
frequency, "magic products" $\Omega T$ can be identified which cancel the first
harmonic of the deposited density, resulting in an improved irradiation
symmetry.


  We establish bounds on the energy of a system of N identical bosons bound by
attractive pair potentials and obeying the semirelativistic Salpeter equation.
The lower bound is provided by a `reduction', with the aid of Jacobi relative
coordinates, to a suitably scaled one-body Klein-Gordon problem. Complementary
upper energy bounds are provided by means of a Gaussian trial function.
Detailed results are presented for the exponential pair potential V(r) =
-v\exp(-r/a).


  The arguments of Cohen [Phys. Rev. A {\bf 60}, 80 (1999)] against the
`ignorance interpretation' of mixed states are questioned. The physical
arguments are shown to be inconsistent and the supporting example illustrates
the opposite of the original statement. The operational difference between two
possible definitions of mixed states is exposed and the inadequacy of one of
them is stressed.


  We examine the steady state of turbulent flows in thin layers using direct
numerical simulations. It is shown that when the layer thickness is smaller
than a critical height, an inverse cascade arises which leads to the formation
of a steady state condensate where most of the energy is concentrated in the
largest scale of the system. For layers of thickness smaller than a second
critical height, the flow at steady state becomes exactly two-dimensional. The
amplitude of the condensate is studied as a function of layer thickness and
Reynolds number. Bi-stability and intermittent bursts are found close to the
two critical points. The results are interpreted based on a mean field
three-scale model that reproduces some of the basic features of the numerical
results.


  Let $K$ be a totally real field and
$\{\rho_{\pi,\lambda}:\mathrm{Gal}_K\to\mathrm{GL}_n(\overline
E_\lambda)\}_\lambda$ the strictly compatible system of $K$ defined over $E$
attached to a regular algebraic polarized cuspidal automorphic representation
$\pi$ of $\mathrm{GL}_n(\mathbb A_K)$. Let $\mathbf G_\lambda$ be the algebraic
monodromy group of $\rho_{\pi,\lambda}$. If there exists $\lambda_0$ such that
(a) $\rho_{\pi,\lambda_0}$ is irreducible, (b) $\mathbf G_{\lambda_0}$ is
connected and of type $A_1$, and (c) either at most one basic factor in the
exterior tensor decomposition of the tautological representation of $\mathbf
G_{\lambda_0}^{\mathrm{der}}$ is $(\mathrm{SL}_2,\mathrm{std})$ or the
tautological representation of $\mathbf G_{\lambda_0}^{\mathrm{der}}$ is
$(\mathrm{SO}_4,\mathrm{std})$, we prove that $\mathbf G_{\lambda,\mathbb
C}\subset\mathrm{GL}_{n, \mathbb C}$ is independent of $\lambda$,
$\rho_{\pi,\lambda}$ is irreducible for all $\lambda$ and residually
irreducible for almost all $\lambda$. If moreover $K=\mathbb Q$, we prove that
the compatible system $\{\rho_{\pi,\lambda}\}_\lambda$ is up to twist
constructed from some two-dimensional modular compatible systems.


  Active nanophotonic materials that can emulate and adapt between many
different spectral profiles -- with high fidelity and over a broad bandwidth --
could have a far-reaching impact, but are challenging to design due to a
high-dimensional and complex design space. Here, we show that a metamaterial
network of coupled 2D-material nanoresonators in graphene can adaptively match
multiple complex absorption spectra via a set of input voltages. To design such
networks, we develop a semi-analytical auto-differentiable dipole-coupled model
that allows scalable optimization of high-dimensional networks with many
elements and voltage signals. As a demonstration of multi-spectral capability,
we design a single network capable of mimicking four spectral targets
resembling select gases (nitric oxide, nitrogen dioxide, methane, nitrous
oxide) with very high fidelity (${>}\,90\%$). Our results are relevant for the
design of highly reconfigurable optical materials and platforms for
applications in sensing, communication and display technology, and signature
and thermal management.


  We examine new methods of producing and analyzing the empirical initial-final
mass relation for open cluster white dwarfs (WDs). We re-determine initial and
final masses for the complete sample of published cluster WDs and then pare
this sample using stringent criteria. We create an empirical initial-final mass
relation by binning all WDs in individual clusters to a single point. Despite
potentially significant systematics arising from this approach, we are
comfortable concluding that, to within current observational constraints, the
initial-final mass relation is linear, any intrinsic scatter in the relation is
<~0.05 solar masses, and there is no metallicity dependence. More exploration
of these issues is clearly warranted.


  Given an isolated, quasi-homogeneous singularity $X$ we prove that there is a
group isomorphism between the group of rank one reflexive sheaves on $X$ and
the free abelian group generated by $\mathbb{C}^*$-divisors, modulo linear
equivalence. When $\dim(X)=2$ we reduce the problem of finding matrix
factorizations of arbitrary reflexive $\mathcal{O}_X$-modules to the same
question on rank one reflexive sheaves. We then enumerate the matrix
factorizations of all rank one reflexive sheaves. As a consequence, we prove a
conjecture of Etingof and Ginzburg on point modules.


  Reconstructing network connectivity from the collective dynamics of a system
typically requires access to its complete continuous-time evolution although
these are often experimentally inaccessible. Here we propose a theory for
revealing physical connectivity of networked systems only from the event time
series their intrinsic collective dynamics generate. Representing the patterns
of event timings in an event space spanned by inter-event and cross-event
intervals, we reveal which other units directly influence the inter-event times
of any given unit. For illustration, we linearize an event space mapping
constructed from the spiking patterns in model neural circuits to reveal the
presence or absence of synapses between any pair of neurons as well as whether
the coupling acts in an inhibiting or activating (excitatory) manner. The
proposed model-independent reconstruction theory is scalable to larger networks
and may thus play an important role in the reconstruction of networks from
biology to social science and engineering.


  We consider sound wave propagation in a range-periodic acoustic waveguide in
the deep ocean. It is demonstrated that vertical oscillations of a sound-speed
perturbation, induced by ocean internal waves, influence near-axial rays in a
resonant way, producing ray chaos and forming a wide chaotic sea in the
underlying phase space. We study interplay between chaotic ray dynamics and
wave motion with signal frequencies of 50-100 Hz. The Floquet modes of the
waveguide are calculated and visualized by means of the Husimi plots. Despite
of irregular phase space distribution of periodic orbits, the Husimi plots
display the presence of ordered peaks within the chaotic sea. These peaks, not
being supported by certain periodic orbits, draw the specific "chainlike"
pattern, reminiscent of KAM resonance. The link between the peaks and KAM
resonance is confirmed by ray calculations with lower amplitude of the
sound-speed perturbation, when the periodic orbits are well-ordered. We
associate occurrence of the peaks with the recovery of ordered periodic orbits,
corresponding to KAM resonance, due to suppressing of wavefield sensitivity to
small-scale features of the sound-speed profile.


  An increasing number of sensors on mobile, Internet of things (IoT), and
wearable devices generate time-series measurements of physical activities.
Though access to the sensory data is critical to the success of many beneficial
applications such as health monitoring or activity recognition, a wide range of
potentially sensitive information about the individuals can also be discovered
through access to sensory data and this cannot easily be protected using
traditional privacy approaches.
  In this paper, we propose a privacy-preserving sensing framework for managing
access to time-series data in order to provide utility while protecting
individuals' privacy. We introduce Replacement AutoEncoder, a novel algorithm
which learns how to transform discriminative features of data that correspond
to sensitive inferences, into some features that have been more observed in
non-sensitive inferences, to protect users' privacy. This efficiency is
achieved by defining a user-customized objective function for deep
autoencoders. Our replacement method will not only eliminate the possibility of
recognizing sensitive inferences, it also eliminates the possibility of
detecting the occurrence of them. That is the main weakness of other approaches
such as filtering or randomization. We evaluate the efficacy of the algorithm
with an activity recognition task in a multi-sensing environment using
extensive experiments on three benchmark datasets. We show that it can retain
the recognition accuracy of state-of-the-art techniques while simultaneously
preserving the privacy of sensitive information. Finally, we utilize the GANs
for detecting the occurrence of replacement, after releasing data, and show
that this can be done only if the adversarial network is trained on the users'
original data.


In this paper we present simplified proofs of our results NP = coNP = PSPACE.


  We present the results of an exploratory numerical study of two dimensional
QCD with overlap fermions. We have performed extensive simulations for U(N_c)
and SU(N_c) color groups with N_c=2, 3, 4 and coupling constants chosen to
satisfy the 't Hooft condition g^2 N_c =const=4/3. We have computed the meson
spectrum and decay constants, the topological susceptibility and the chiral
condensate. For U(N_c) gauge groups, our results indicate that the
Witten-Veneziano relation is satisfied within our statistical errors and that
the chiral condensate for N_f=1 is compatible with a non-zero value. Our
results exhibit universality in N_c and confirm once more the excellent chiral
properties of the overlap-Dirac operator.


  In this paper, we show that the two concepts of generalised norm resolvent
convergence introduced by Weidmann and the first author of this paper are
equivalent. We also focus on the convergence speed and provide conditions under
which the convergence speed is the same for both concepts. We illustrate the
abstract results by a large number of examples.


  Sixth-generation (6G) mobile communication networks are expected to have
dense infrastructures, large antenna size, wide bandwidth, cost-effective
hardware, diversified positioning methods, and enhanced intelligence. Such
trends bring both new challenges and opportunities for the practical design of
6G. On one hand, acquiring channel state information (CSI) in real time for all
wireless links becomes quite challenging in 6G. On the other hand, there would
be numerous data sources in 6G containing high-quality location-tagged channel
data, e.g., the estimated channels or beams between base station (BS) and user
equipment (UE), making it possible to better learn the local wireless
environment. By exploiting this new opportunity and for tackling the CSI
acquisition challenge, there is a promising paradigm shift from the
conventional environment-unaware communications to the new environment-aware
communications based on the novel approach of channel knowledge map (CKM). This
article aims to provide a comprehensive overview on environment-aware
communications enabled by CKM to fully harness its benefits for 6G. First, the
basic concept of CKM is presented, followed by the comparison of CKM with
various existing channel inference techniques. Next, the main techniques for
CKM construction are discussed, including both environment model-free and
environment model-assisted approaches. Furthermore, a general framework is
presented for the utilization of CKM to achieve environment-aware
communications, followed by some typical CKM-aided communication scenarios.
Finally, important open problems in CKM research are highlighted and potential
solutions are discussed to inspire future work.


  We introduce ordered transfer hyperparameter optimisation (OTHPO), a version
of transfer learning for hyperparameter optimisation (HPO) where the tasks
follow a sequential order. Unlike for state-of-the-art transfer HPO, the
assumption is that each task is most correlated to those immediately before it.
This matches many deployed settings, where hyperparameters are retuned as more
data is collected; for instance tuning a sequence of movie recommendation
systems as more movies and ratings are added. We propose a formal definition,
outline the differences to related problems and propose a basic OTHPO method
that outperforms state-of-the-art transfer HPO. We empirically show the
importance of taking order into account using ten benchmarks. The benchmarks
are in the setting of gradually accumulating data, and span XGBoost, random
forest, approximate k-nearest neighbor, elastic net, support vector machines
and a separate real-world motivated optimisation problem. We open source the
benchmarks to foster future research on ordered transfer HPO.


  Using an analytical expression for an integral involving Bessel and Legendre
functions we succeeded to obtain the partial wave decomposition of a general
optical beam at an arbitrary location from the origin. We also showed that the
solid angle integration will eliminate the radial dependence of the expansion
coefficients. The beam shape coefficients obtained are given by an exact
expression in terms of single or double integrals. These integrals can be
evaluated numerically in a short time scale. We presented the results for the
case of linear polarized Gaussian beam.


  In the unsplittable capacitated vehicle routing problem (UCVRP) on trees, we
are given a rooted tree with edge weights and a subset of vertices of the tree
called terminals. Each terminal is associated with a positive demand between 0
and 1. The goal is to find a minimum length collection of tours starting and
ending at the root of the tree such that the demand of each terminal is covered
by a single tour (i.e., the demand cannot be split), and the total demand of
the terminals in each tour does not exceed the capacity of 1.
  For the special case when all terminals have equal demands, a long line of
research culminated in a quasi-polynomial time approximation scheme
[Jayaprakash and Salavatipour, SODA 2022] and a polynomial time approximation
scheme [Mathieu and Zhou, ICALP 2022].
  In this work, we study the general case when the terminals have arbitrary
demands. Our main contribution is a polynomial time
$(1.5+\epsilon)$-approximation algorithm for the UCVRP on trees. This is the
first improvement upon the 2-approximation algorithm more than 30 years ago
[Labb\'e, Laporte, and Mercure, Operations Research, 1991]. Our approximation
ratio is essentially best possible, since it is NP-hard to approximate the
UCVRP on trees to better than a 1.5 factor.


  We present an experiment of nonclassical interference between a pure heralded
single-photon state and a weak coherent state. Our experiment is the first to
demonstrate that spectrally pure single photons can have high interference
visibility, 89.4 \pm 0.5%, with weak coherent photons. Our scheme lays the
groundwork for future experiments requiring quantum interference between
photons in nonclassical states and those in coherent states.


  We have surveyed two science fields totaling one square degree with Bolocam
at 2.1 mm to search for secondary CMB anisotropies caused by the Sunyaev-
Zel'dovich effect (SZE). The fields are in the Lynx and Subaru/XMM SDS1 fields.
Our survey is sensitive to angular scales with an effective angular multipole
of l_eff = 5700 with FWHM_l = 2800 and has an angular resolution of 60
arcseconds FWHM. Our data provide no evidence for anisotropy. We are able to
constrain the level of total astronomical anisotropy, modeled as a flat
bandpower in C_l, with frequentist 68%, 90%, and 95% CL upper limits of 590,
760, and 830 uKCMB^2. We statistically subtract the known contribution from
primary CMB anisotropy, including cosmic variance, to obtain constraints on the
SZE anisotropy contribution. Now including flux calibration uncertainty, our
frequentist 68%, 90% and 95% CL upper limits on a flat bandpower in C_l are
690, 960, and 1000 uKCMB^2. When we instead employ the analytic spectrum
suggested by Komatsu and Seljak (2002), and account for the non-Gaussianity of
the SZE anisotropy signal, we obtain upper limits on the average amplitude of
their spectrum weighted by our transfer function of 790, 1060, and 1080
uKCMB^2. We obtain a 90% CL upper limit on sigma8, which normalizes the power
spectrum of density fluctuations, of 1.57. These are the first constraints on
anisotropy and sigma8 from survey data at these angular scales at frequencies
near 150 GHz.


  We study superdense relativistic stars with anisotropic matter distributions
with spheroidal spatial hypersurfaces. We propose a methodology to make an
anisotropic generalization of the Vaidya-Tikekar superdense star model. The
anisotropic Einstein field equations can be solved in terms of hypergeometric
functions for our choice of gravitational potential and anisotropy. Particular
parameter choices allow us to generate models of anisotropic stars in terms of
elementary functions. Also, isotropic stars can be generated in the limit of
vanishing anisotropy. In particular, we obtain the well known superdense models
of Tikekar which are isotropic and have specific spheroidal geometries. The
impact of anisotropy on the gross physical behaviour of a compact star is
studied.


  We propose a pyroelectric energy conversion device that converts heat
directly to electricity. In contrast to conventional pyroelectric energy
conversion designs, this energy harvesting system is detached from any external
power sources, operating only under periodically varying temperature. Such
detachment unambiguously attributes the converted electricity to heat that
drives the change of polarization in the pyroelectric material, not to the
electric field alternation caused by the external battery. Using pure and Zr
doped BaTiO$_3$, we demonstrate the electricity generation in consecutive
temperature cycles. We further develop a thermodynamic model for the energy
conversion system. Our model suggests that the work output is rate dependent:
the work output per cycle is linearly dependent on the heat/cooling frequency
below the predicted threshold. The linearity is confirmed by experiments, and
the threshold frequency is derived by theory. Finally we propose a figure of
merit that separates the materials intrinsic properties from the system design
parameters. The figure of merit guides the future material development and
device improvement. Our work clears out confusions and reforms the foundation
for pyroelectric materials' resurgence as a competitor for green electricity.


  This paper investigates the opportunities and limitations of adaptive virtual
machine (VM) migration to reduce communication costs in a virtualized
environment. We introduce a new formal model for the problem of online VM
migration in two scenarios: (1) VMs can be migrated arbitrarily in the
substrate network; e.g., a private cloud provider may have an incentive to
reduce the overall communication cost in the network. (2) VMs can only be
migrated within a given tenant; e.g., a user that was assigned a set of
physical machines may exchange the functionality of the VMs on these machines.
  We propose a simple class of Destination-Swap algorithms which are based on
an aggressive collocation strategy (inspired by splay datastructures) and which
maintain a minimal and local amount of per-node (amortized cost) information to
decide where to migrate a VM and how; thus, the algorithms react quickly to
changes in the load. The algorithms come in two main flavors, an indirect and
distributed variant which keeps existing VM placements local, and a direct
variant which keeps the number of affected VMs small.
  We show that naturally, inter-tenant optimizations yield a larger potential
for optimization, but generally also a tenant itself can improve its embedding.
Moreover, there exists an interesting tradeoff between direct and indirect
strategies: indirect variants are preferable under skewed and sparse
communication patterns due to their locality properties.


  Real-time speech extraction is an important challenge with various
applications such as speech recognition in a human-like avatar/robot. In this
paper, we propose the real-time extension of a speech extraction method based
on independent low-rank matrix analysis (ILRMA) and rank-constrained spatial
covariance matrix estimation (RCSCME). The RCSCME-based method is a
multichannel blind speech extraction method that demonstrates superior speech
extraction performance in diffuse noise environments. To improve the
performance, we introduce spatial regularization into the ILRMA part of the
RCSCME-based speech extraction and design two regularizers. Speech extraction
experiments demonstrated that the proposed methods can function in real time
and the designed regularizers improve the speech extraction performance.


  We study the evolution of perturbations during the domination and decay of a
massive particle species whose mass and decay rate are allowed to depend on the
expectation value of a light scalar field. We specialize in the case where the
light field is slow-rolling, showing that during a phase of inhomogeneous
mass-domination and decay the isocurvature perturbation of the light field is
converted into a curvature perturbation with an efficiency which is nine times
larger than when the mass is fixed. We derive a condition on the annihilation
cross section and on the decay rate for the domination of the massive particles
and we show that standard model particles cannot dominate the universe before
nucleosynthesis. We also compare this mechanism with the curvaton model.
Finally, observational signatures are discussed. A cold dark matter
isocurvature mode can be generated if the dark matter is produced out of
equilibrium by both the inflaton and the massive particle species decay.
Non-Gaussianities are present: they are chi-square deviations. However, they
might be too small to be observable.


  By taking the spin and polarization of the electrons, positrons and photons
into account in the strong-field QED processes of nonlinear Compton emission
and pair production, we find that the growth rate of QED cascades in
ultra-intense laser fields can be substantially reduced. While this means that
fewer particles are produced, we also found them to be highly polarized. We
further find that the high-energy tail of the particle spectra is polarized
opposite to that expected from Sokolov-Ternov theory, which cannot be explained
by just taking into account spin-asymmetries in the pair production process,
but results significantly from "spin-straggling". We employ a kinetic equation
approach for the electron, positron and photon distributions, each of them
spin/polarization-resolved, with the QED effects of photon emission and pair
production modelled by a spin/polarization dependent Boltzmann-type collision
operator. For photon-seeded cascades, depending on the photon polarization, we
find an excess or a shortage of particle production in the early stages of
cascade development, which provides a path towards a controlled experiment.
Throughout this paper we focus on rotating electric field configuration, which
represent an idealized model and allows for a straightforward interpretation of
the observed effects.


  Previous analyses of cosmic rays above 40 EeV observed by the AGASA
experiment have suggested that their arrival directions may be clustered.
However, estimates of the chance probability of this clustering signal vary
from 10^{-2} to 10^{-6} and beyond. It is essential that the strength of this
evidence be well understood in order to compare it with anisotropy studies in
other cosmic ray experiments. We apply two methods for extracting a meaningful
significance from this data set: one can scan for the cuts which optimize the
clustering signal, using simulations to determine the appropriate statistical
penalty for the scan. This analysis finds a chance probability of about 0.3%.
Alternatively, one can optimize the cuts with a first set of data, and then
apply them to the remaining data directly without statistical penalty. One can
extend the statistical power of this test by considering cross-correlation
between the initial data and the remaining data, as long as the initial
clustering signal is not included. While the scan is more useful in general, in
the present case only splitting the data set offers an unbiased test of the
clustering hypothesis. Using this test we find that the AGASA data is
consistent at the 8% level with the null hypothesis of isotropically
distributed arrival directions.


  We present here our response to Dikpati et al.'s criticism of our recent
solar dynamo model.


  A paradigm put forth by E. Schr\"odinger in 1931/32, known as Schr\"odinger
bridges, represents a formalism to pose and solve control and estimation
problems seeking a perturbation from an initial control schedule (in the case
of control), or from a prior probability law (in the case of estimation),
sufficient to reconcile data in the form of marginal distributions and minimal
in the sense of relative entropy to the prior. In the same spirit, we consider
traffic-flow and apply a Schr\"odinger-type dictum, to perturb minimally with
respect to a suitable relative entropy functional a prior schedule/law so as to
reconcile the traffic flow with scarce aggregate distributions on families of
indistinguishable individuals. Specifically, we consider the problem to
regulate/estimate multi-commodity network flow rates based only on empirical
distributions of commodities being transported (e.g., types of vehicles through
a network, in motion) at two given times. Thus, building on Schr\"odinger's
large deviation rationale, we develop a method to identify {\em the most likely
flow rates (traffic flow)}, given prior information and aggregate observations.
Our method further extends the Schr\"odinger bridge formalism to the
multi-commodity setting, allowing commodities to exit or enter the flow field
as well (e.g., vehicles to enter and stop and park) at any time. The behavior
of entering or exiting the flow field, by commodities or vehicles, is modeled
by a Markov chains with killing and creation states. Our method is illustrated
with a numerical experiment.


  Self-supervised pre-training recently demonstrates success on large-scale
multimodal data, and state-of-the-art contrastive learning methods often
enforce the feature consistency from cross-modality inputs, such as video/audio
or video/text pairs. Despite its convenience to formulate and leverage in
practice, such cross-modality alignment (CMA) is only a weak and noisy
supervision, since two modalities can be semantically misaligned even they are
temporally aligned. For example, even in the commonly adopted instructional
videos, a speaker can sometimes refer to something that is not visually present
in the current frame; and the semantic misalignment would only be more
unpredictable for the raw videos from the internet. We conjecture that might
cause conflicts and biases among modalities, and may hence prohibit CMA from
scaling up to training with larger and more heterogeneous data. This paper
first verifies our conjecture by observing that, even in the latest VATT
pre-training using only instructional videos, there exist strong gradient
conflicts between different CMA losses within the same video, audio, text
triplet, indicating them as the noisy source of supervision. We then propose to
harmonize such gradients, via two techniques: (i) cross-modality gradient
realignment: modifying different CMA loss gradients for each sample triplet, so
that their gradient directions are more aligned; and (ii) gradient-based
curriculum learning: leveraging the gradient conflict information on an
indicator of sample noisiness, to develop a curriculum learning strategy to
prioritize training on less noisy sample triplets. Applying those techniques to
pre-training VATT on the HowTo100M dataset, we consistently improve its
performance on different downstream tasks. Moreover, we are able to scale VATT
pre-training to more complicated non-narrative Youtube8M dataset to further
improve the state-of-the-arts.


  Measurements of the Hubble constant to distant galaxy clusters using the
Sunyaev-Zeldovich effect are systematically low in comparison to values
obtained by other means. These measurements usually assume a spherical
isothermal $\beta$ model for the intracluster medium (ICM). We present the
results of a statistical analysis of {\em temperature bias} in $H_0$
determinations in a sample of 27 numerically simulated X-ray clusters drawn
from a $\Lambda$CDM model at z=0.5. We employ adaptive mesh refinement to
provide high resolution (15.6 h$^{-1} kpc$) in cluster cores which dominate the
X-ray and radio signals. Fitting synthetic X-ray and y-parameter maps to the
standard isothermal beta model, we find a broad, skewed distribution in
$f\equiv H_0(SZ)/H_0(actual)$ with a mean, median, and standard deviation of
0.89, 0.83 and 0.32 respectively, where $H_0(SZ)$ is the value of $H_0$ derived
by using Sunyaev-Zeldovich effect method and $H_0(actual)$ is the value used in
the cosmological simulation. We find that the clusters' declining temperature
profiles systematically lower estimates of $H_0$ by 10% to 20%. The declining
temperature profile of our adiabatic system is consistent with the result
including radiative cooling and supernovae feedback (Loken et al. 2002). We
thereby introduce a non-isothermal $\beta$ model as an improvement. Applying
the non-isothermal $\beta$ model to the refined sample with well-fitted
temperature profile, the value of f improves 9% relative to the actual value.
The study of the morphology and the clumping effects conclude that these two
factors combine to induce scatter in f of $\pm$ 30 %.


  We construct functions and tensors on noncommutative spacetime by
systematically twisting the corresponding commutative structures. The study of
the deformed diffeomorphisms (and Poincare) Lie algebra allows to construct a
noncomutative theory of gravity.


  The very low frequency (VLF) regime below 30 MHz in the electromagnetic
spectrum has presently drawing global attentions in radio astronomical research
due to its potentially significant science outcomes exploring many unknown
extragalactic sources, transients, and so on. However, the non-transparency of
the Earth's ionosphere, ionospheric distortion and artificial radio frequency
interference (RFI) have made it difficult to detect the VLF celestial radio
emission with ground-based instruments. A straightforward solution to overcome
these problems is a space based VLF radio telescope, just like the VLF radio
instruments onboard the Chang'E 4 spacecraft. But building such a space
telescope would be inevitably costly and technically challenging. The
alternative approach would be then a ground based VLF radio telescope.
Particularly, in the period of post 2020 when the solar and terrestrial
ionospheric activities are expected to be in a 'calm' state, it will provide us
a good chance to perform VLF ground-based radio observations. Anticipating such
an opportunity, we built an agile VLF radio spectrum explorer co-located with
the currently operational Mingantu Spectra Radio Heliograph (MUSER). The
instrument includes four antennas operating in the VLF frequency range 1-70
MHz. Along with them, we employ an eight-channel analog and digital receivers
to amplify, digitize and process the radio signals received by the antennas. We
present in the paper this VLF radio spectrum explorer and the instrument will
be useful for celestial studies of VLF radio emissions.


  [abridged] The enhanced degrees of deuterium fractionation observed in
envelopes around protostars demonstrate the importance of chemistry at low
temperatures, relevant in pre- and protostellar cores. formaldehyde is an
important species in the formation of methanol and more complex molecules.
Here, we present the first study of formaldehyde deuteration on small scales
around the prototypical low-mass protostar IRAS 16293-2422 using high spatial
and spectral resolution Atacama Large Millimeter/submillimeter Array (ALMA)
observations. Numerous isotopologues of formaldehyde are detected, among them
H$_2$C$^{17}$O, and D$_2^{13}$CO for the first time in the ISM. The large range
of upper energy levels covered by the HDCO lines help constrain the excitation
temperature to 106$\pm$13 K. Using the derived column densities, formaldehyde
shows a deuterium fractionation of HDCO/H$_2$CO=6.5$\pm$1%,
D$_2$CO/HDCO=12.8$^{+3.3}_{-4.1}$%, and D$_2$CO/H$_2$CO=0.6(4)$\pm$0.1%. The
isotopic ratios derived are $^{16}$O/$^{18}$O=805, $^{18}$O/$^{17}$O=3.2 and
$^{12}$C/$^{13}$C=56. The HDCO/H$_2$CO ratio is lower than found in previous
studies, highlighting the uncertainties involved in interpreting single dish
observations of the inner warm regions. The D$_2$CO/HDCO ratio is only slightly
larger than the HDCO/H$_2$CO ratio. This is consistent with formaldehyde
forming in the ice as soon as CO has frozen onto the grains, with most of the
deuteration happening towards the end of the prestellar core phase. A
comparison with available time-dependent chemical models indicates that the
source is in the early Class 0 stage.


  We present a simulation-based inference (SBI) cosmological analysis of cosmic
shear two-point statistics from the fourth weak gravitational lensing data
release of the ESO Kilo-Degree Survey (KiDS-1000). KiDS-SBI efficiently
performs non-Limber projection of the matter power spectrum via Levin's method,
and constructs log-normal random matter fields on the curved sky for arbitrary
cosmologies, including effective prescriptions for intrinsic alignments and
baryonic feedback. The forward model samples realistic galaxy positions and
shapes based on the observational characteristics, incorporating shear
measurement and redshift calibration uncertainties, as well as angular
anisotropies due to variations in depth and point-spread function. To enable
direct comparison with standard inference, we limit our analysis to
pseudo-angular power spectra. The SBI is based on sequential neural likelihood
estimation to infer the posterior distribution of spatially-flat $\Lambda$CDM
cosmological parameters from 18,000 realisations. We infer a mean marginal of
the growth of structure parameter $S_{8} \equiv \sigma_8 (\Omega_\mathrm{m} /
0.3)^{0.5} = 0.731\pm 0.033$ ($68 \%$). We present a measure of goodness-of-fit
for SBI and determine that the forward model fits the data well with a
probability-to-exceed of $0.42$. For fixed cosmology, the learnt likelihood is
approximately Gaussian, while constraints widen compared to a Gaussian
likelihood analysis due to cosmology dependence in the covariance. Neglecting
variable depth and anisotropies in the point spread function in the model can
cause $S_{8}$ to be overestimated by ${\sim}5\%$. Our results are in agreement
with previous analysis of KiDS-1000 and reinforce a $2.9 \sigma$ tension with
constraints from cosmic microwave background measurements. This work highlights
the importance of forward-modelling systematic effects in upcoming galaxy
surveys.


  We investigate the correlation between nine different dark matter halo
properties using a rank correlation analysis and a Principal Component Analysis
for a sample of haloes spanning five orders of magnitude in mass. We consider
mass and dimensionless measures of concentration, age, relaxedness, sphericity,
triaxiality, substructure, spin, and environment, where the latter is defined
in a way that makes it insensitive to mass. We find that concentration is the
most fundamental property. Except for environment, all parameters are strongly
correlated with concentration. Concentration, age, substructure, mass,
sphericity and relaxedness can be considered a single family of parameters,
albeit with substantial scatter. In contrast, spin, environment, and
triaxiality are more independent, although spin does correlate strongly with
substructure and both spin and triaxiality correlate substantially with
concentration. Although mass sets the scale of a halo, all other properties are
more sensitive to concentration.


  Vakonomic mechanics has been proposed as a possible description of the
dynamics of systems subject to nonholonomic constraints. The aim of the present
work is to show that for an important physical system the motion brought about
by vakonomic mechanics is completely inequivalent to the one derived from
nonholonomic mechanics, which relies on the standard method of Lagrange
multipliers in the d'Alembert-Lagrange formulation of the classical equations
of motion. For the rolling coin on an inclined plane, it is proved that no
nontrivial solution to the equations of motion of nonholonomic mechanics can be
obtained in the framework of vakonomic mechanics. This completes previous
investigations that managed to show only that, for certain mechanical systems,
some but not necessarily all nonholonomic motions are beyond the reach of
vakonomic mechanics. Furthermore, it is argued that a simple qualitative
experiment that anyone can perform at home supports the predictions of
nonholonomic mechanics.


  Macroscopic systems with continuous symmetries subjected to oscillatory
fields have phases and transitions that are qualitatively different from their
equilibrium ones. Depending on the amplitude and frequency of the fields
applied, Heisenberg ferromagnets can become XY or Ising-like -or, conversely,
anisotropies can be compensated -thus changing the nature of the ordered phase
and the topology of defects. The phenomena can be viewed as a dynamic form of
"order by disorder".


  The goal of this paper is to deal with a data scarcity scenario where deep
learning techniques use to fail. We compare the use of two well established
techniques, Restricted Boltzmann Machines and Variational Auto-encoders, as
generative models in order to increase the training set in a classification
framework. Essentially, we rely on Markov Chain Monte Carlo (MCMC) algorithms
for generating new samples. We show that generalization can be improved
comparing this methodology to other state-of-the-art techniques, e.g.
semi-supervised learning with ladder networks. Furthermore, we show that RBM is
better than VAE generating new samples for training a classifier with good
generalization capabilities.


  Superconductivity has been the focus of enormous research effort since its
discovery more than a century ago. Yet, some features of this unique phenomenon
remain poorly understood; prime among these is the connection between
superconductivity and chemical/structural properties of materials. To bridge
the gap, several machine learning schemes are developed herein to model the
critical temperatures ($T_{\mathrm{c}}$) of the 12,000+ known superconductors
available via the SuperCon database. Materials are first divided into two
classes based on their $T_{\mathrm{c}}$ values, above and below 10 K, and a
classification model predicting this label is trained. The model uses
coarse-grained features based only on the chemical compositions. It shows
strong predictive power, with out-of-sample accuracy of about 92%. Separate
regression models are developed to predict the values of $T_{\mathrm{c}}$ for
cuprate, iron-based, and "low-$T_{\mathrm{c}}$" compounds. These models also
demonstrate good performance, with learned predictors offering potential
insights into the mechanisms behind superconductivity in different families of
materials. To improve the accuracy and interpretability of these models, new
features are incorporated using materials data from the AFLOW Online
Repositories. Finally, the classification and regression models are combined
into a single integrated pipeline and employed to search the entire Inorganic
Crystallographic Structure Database (ICSD) for potential new superconductors.
We identify more than 30 non-cuprate and non-iron-based oxides as candidate
materials.


  A variety of magnetohydrodynamic mechanisms that may play a role in magnetic,
chemically peculiar (mCP) stars is reviewed. These involve dynamo mechanisms in
laminar flows as well as turbulent environments, and magnetic instabilities of
poloidal and toroidal fields as well as combinations of the two. While the
proto-stellar phase makes the survival of primordial fields difficult, the
variety of magnetic field configurations on mCP stars may be an indication for
that they are instability remnants, but there is no process which is clearly
superior in explaining the strong fields.


  We present a Ginzburg-Landau theory of inhomogeneous polyelectrolytes with a
polar solvent. First, we take into account the molecular (solvation)
interaction among the ions, the charged monomers, the uncharged monomers, and
the solvent molecules, together with the electrostatic interaction with a
composition-dependent dielectric constant. Second, we treat the degree of
ionization as a fluctuating variable dependent on the local electric potential.
With these two ingredients included, our results are as follows. (i) We derive
a mass reaction law and a general expression for the surface tension. (ii) We
calculate the structure factor of the composition fluctuations as a function of
various parameters of the molecular interactions, which provides a general
criterion of the formation of mesophases. (iii) We numerically examine some
typical examples of interfaces and mesophase structures, which strongly depend
on the molecular interaction parameters.


  In 1981 F. Knight published an article with a partial solution to a problem
proposed by Ito-McKean see [Ito,[p.217]]. In this paper Knight, see [Knight],
characterized the Levy measures of gap diffusions also known as
quasi-diffusions. The proof is very elegant but it uses quite a lot functional
analysis, more specifically spectral Krein Theory. We present a new proof of
Knight's Theorem, defined at the beginning of the Introduction as well as the
new proof of the same theorem referred as Theorem 2.6 in Section 2.


  We investigate the doping effects of magnetic and nonmagnetic impurities
injected to the honeycomb iridate sample of Na2IrO3 . Both the doping result in
changing the ordering temperature as well as the Curie-Weiss temperature of the
parent sample as a consequence of enhancement of the lattice frustration,
screening of the Ir atoms and spin-orbit effects that reflects in the
susceptibility and specific heat measurements. Our findings are corroborated by
a detailed comparative study of various magnetic and nonmagnetic impurity atoms
that have notable effects on different electronic properties of the doped
compounds.


  This article is about chromatic numbers of hyperbolic surfaces. For a metric
space, the $d$-chromatic number is the minimum number of colors needed to color
the points of the space so that any two points at distance $d$ are of a
different color. We prove upper bounds on the $d$-chromatic number of any
hyperbolic surface which only depend on $d$. In another direction, we
investigate chromatic numbers of closed genus $g$ surfaces and find upper
bounds that only depend on $g$ (and not on $d$). For both problems, we
construct families of examples that show that our bounds are meaningful.


  This is a photographic dataset collected for testing image processing
algorithms. The idea is to have sets of different but statistically similar
images. In this work the images show randomly distributed peppercorns. The
dataset is made available at www.fips.fi/photographic_dataset.php .


  A Dirac-type energy spectrum was demonstrated in gapless ultra-short-period
metamorphic InAsSb/InSb superlattices by angle-resolved photoemission
spectroscopy (ARPES_ measurements. The Fermi velocity value 7.4x10^5 m/s in a
gapless superlattice with a period of 6.2nm is in a good agreement with the
results of magneto-absorption experiments. An "inverted" bandgap opens in the
center of the Brillouin zone at higher temperatures and in the SL with a larger
period. The ARPES data indicate the presence of a surface electron accumulation
layer


  The automorphism tower of a group is obtained by computing its automorphism
group, the automorphism group of THAT group, and so on, iterating
transfinitely. Each group maps canonically into the next using inner
automorphisms, and so at limit stages one can take a direct limit and continue
the iteration. The tower is said to terminate if a fixed point is reached, that
is, if a group is reached which is isomorphic to its automorphism group by the
natural map. This occurs if a complete group is reached, one which is
centerless and has only inner automorphisms. Wielandt [1939] proved the
classical result that the automorphism tower of any centerless finite group
terminates in finitely many steps. Rae and Roseblade [1970] proved that the
automorphism tower of any centerless Cernikov group terminates in finitely many
steps. Hulse [1970] proved that the the automorphism tower of any centerless
polycyclic group terminates in countably many steps. Simon Thomas [1985] proved
that the automorphism tower of any centerless group eventually terminates. In
this paper, I remove the centerless assumption, and prove that every group has
a terminating transfinite automorphism tower.


  Semiconductor quantum dots (QDs) in planar germanium (Ge) heterostructures
have emerged as frontrunners for future hole-based quantum processors. Notably,
the large spin-orbit interaction of holes offers rapid, coherent electrical
control of spin states, which can be further beneficial for interfacing hole
spins to microwave photons in superconducting circuits via coherent
charge-photon coupling. Here, we present strong coupling between a hole charge
qubit, defined in a double quantum dot (DQD) in a planar Ge, and microwave
photons in a high-impedance ($Z_\mathrm{r} = 1.3 ~ \mathrm{k}\Omega$)
superconducting quantum interference device (SQUID) array resonator. Our
investigation reveals vacuum-Rabi splittings with coupling strengths up to
$g_{0}/2\pi = 260 ~ \mathrm{MHz}$, and a cooperativity of $C \sim 100$,
dependent on DQD tuning, confirming the strong charge-photon coupling regime
within planar Ge. Furthermore, utilizing the frequency tunability of our
resonator, we explore the quenched energy splitting associated with
strongly-correlated Wigner molecule (WM) states that emerge in Ge QDs. The
observed enhanced coherence of the WM excited state signals the presence of
distinct symmetries within related spin functions, serving as a precursor to
the strong coupling between photons and spin-charge hybrid qubits in planar Ge.
This work paves the way towards coherent quantum connections between remote
hole qubits in planar Ge, required to scale up hole-based quantum processors.


  We present a simple exactly solvable extension of of the Jaynes-Cummings
model by adding dissipation. This is done such that the total number of
excitations is conserved. The Liouville operator in the resulting master
equation can be reduced to blocks of $4\times 4$ matrices.


  Coherent Raman scattering microscopy is a fast, label-free and chemically
specific imaging technique that has a high potential for future in-vivo optical
histology. However, its imaging depth into tissues is limited to the
sub-millimeter range by absorption and scattering. Performing coherent Raman
imaging in a fiber endoscope system is a crucial step to image deep inside
living tissues and provide the information inaccessible with current microscopy
tools. However the development of coherent Raman endoscopy has been hampered by
several issues in the fiber delivery of the excitation pulses and signal
collection. Here, we present a flexible, compact, and multimodal nonlinear
endoscope (4.2 mm outer diameter, 71 mm rigid length) based on a resonantly
scanned hollow-core Kagom\'e-lattice double-clad fiber. The fiber design allows
distortion-less, background-free delivery of femtosecond excitation pulses and
the back-collection of nonlinear signals through the same fiber. Sub-micron
spatial resolution together with large field of view is made possible by the
combination of a miniature objective lens together with a silica microsphere
lens inserted into the fiber core. We demonstrate coherent anti-Stokes Raman
scattering, 2-photon fluorescence and second harmonic generation imaging with
0.8 {\mu}m resolution over a field of view up to 320 {\mu}m and at a rate of
0.8 frames/s. These results pave the way for intra-operative label-free imaging
applied to real-time histopathology diagnosis and surgery guidance.


  Experiments and computer simulations have established that liquid water's
surfaces can deviate in important ways from familiar bulk behavior. Even in the
simplest case of an air-water interface, distinctive layering, orientational
biases, and hydrogen bond arrangements have been reported, but an overarching
picture of their origins and relationships has been incomplete. Here we show
that a broad set of such observations can be understood through an analogy with
the basal face of crystalline ice. Using simulations, we specifically
demonstrate that water and ice surfaces share a set of structural features
suggesting the presence of nanometer-scale ice-like domains at the air-water
interface. Most prominent is a shared characteristic layering of molecular
density and orientation perpendicular to the interface. Similarities in
two-point correlations of hydrogen bond network geometry point to shared
ice-like intermolecular structure in the parallel direction as well. Our
results bolster and significantly extend previous conceptions of ice-like
structure at the liquid's boundary, and suggest that the much-discussed
quasi-liquid layer on ice evolves subtly above the melting point into a
quasi-ice layer at the surface of liquid water.


  We introduce the concept of entropic nonsignaling correlations, i.e.,
entropies arising from probabilistic theories that are compatible with the fact
that we cannot transmit information instantaneously. We characterize and show
the relevance of these entropic correlations in a variety of different
scenarios, ranging from typical Bell experiments to more refined descriptions
such as bilocality and information causality. In particular, we apply the
framework to derive the first entropic inequality testing genuine tripartite
nonlocality in quantum systems of arbitrary dimension and also prove the first
known monogamy relation for entropic Bell inequalities. Further, within the
context of complex Bell networks, we show that entropic nonlocal correlations
can be activated.


  Recent estimates indicate that the U.S. Department of Defense spends over
\$20 billion USD annually on corrosion-related maintenance. This expenditure is
accompanied by a substantial loss in asset readiness, ranging from 10% to 30%.
Moreover, the global costs associated with corrosion damage have been estimated
at an astonishing \$2.5 trillion USD per year, or approximately 3.4% of global
GDP in 2016. This project aims to describe how quantum computers might be
leveraged to fundamentally change the way material-environment interactions are
modeled for material discovery, selection, and design. This project also seeks
to understand the plausibility and utility of replacing portions of classical
computing workflows with algorithms optimized for quantum computing hardware.
The utility of quantum computers is explored through the lens of two
industrially relevant problems: (1) characterizing magnesium alloy corrosion
properties in aqueous environments and (2) identifying stable niobium-rich
alloys with corrosion resistance at temperatures above 1500K. This paper
presents an end-to-end analysis of the complexity of both classical and quantum
algorithms used in application workflows. Resource estimates are produced using
a custom software package, pyLIQTR, based on the qubitized Quantum Phase
Estimation (QPE) algorithm. Estimates for the two aforementioned applications
show that industrially-relevant computational models that have the potential to
deliver commercial utility require quantum computers with thousands to hundreds
of thousands of logical qubits and the ability to execute $10^{13}$ to
$10^{19}$ T-gates. These estimates represent an upper bound and motivate
continued research into improved quantum algorithms and resource reduction
techniques.


  Skewed probit regression is but one example of a statistical model that
generalizes a simpler model, like probit regression. All skew-symmetric
distributions and link functions arise from symmetric distributions by
incorporating a skewness parameter through some skewing mechanism. In this work
we address some fundamental issues in skewed probit regression, and more
genreally skew-symmetric distributions or skew-symmetric link functions. We
address the issue of identifiability of the skewed probit model parameters by
reformulating the intercept from first principles. A new standardization of the
skew link function is given to provide and anchored interpretation of the
inference. Possible skewness parameters are investigated and the penalizing
complexity priors of these are derived. This prior is invariant under
reparameterization of the skewness parameter and quantifies the contraction of
the skewed probit model to the probit model. The proposed results are available
in the R-INLA package and we illustrate the use and effects of this work using
simulated data, and well-known datasets using the link as well as the
likelihood.


  This paper presents a novel method for rare event detection from an image
pair with class-imbalanced datasets. A straightforward approach for event
detection tasks is to train a detection network from a large-scale dataset in
an end-to-end manner. However, in many applications such as building change
detection on satellite images, few positive samples are available for the
training. Moreover, scene image pairs contain many trivial events, such as in
illumination changes or background motions. These many trivial events and the
class imbalance problem lead to false alarms for rare event detection. In order
to overcome these difficulties, we propose a novel method to learn disentangled
representations from only low-cost negative samples. The proposed method
disentangles different aspects in a pair of observations: variant and invariant
factors that represent trivial events and image contents, respectively. The
effectiveness of the proposed approach is verified by the quantitative
evaluations on four change detection datasets, and the qualitative analysis
shows that the proposed method can acquire the representations that disentangle
rare events from trivial ones.


  Cluster-level inference procedures are widely used for brain mapping. These
methods compare the size of clusters obtained by thresholding brain maps to an
upper bound under the global null hypothesis, computed using Random Field
Theory or permutations. However, the guarantees obtained by this type of
inference - i.e. at least one voxel is truly activated in the cluster - are not
informative with regards to the strength of the signal therein. There is thus a
need for methods to assess the amount of signal within clusters; yet such
methods have to take into account that clusters are defined based on the data,
which creates circularity in the inference scheme. This has motivated the use
of post hoc estimates that allow statistically valid estimation of the
proportion of activated voxels in clusters. In the context of fMRI data, the
All-Resolutions Inference framework introduced in [25] provides post hoc
estimates of the proportion of activated voxels. However, this method relies on
parametric threshold families, which results in conservative inference. In this
paper, we leverage randomization methods to adapt to data characteristics and
obtain tighter false discovery control. We obtain Notip, for Non-parametric
True Discovery Proportion control: a powerful, non-parametric method that
yields statistically valid guarantees on the proportion of activated voxels in
data-derived clusters. Numerical experiments demonstrate substantial gains in
number of detections compared with state-of-the-art methods on 36 fMRI
datasets. The conditions under which the proposed method brings benefits are
also discussed.


  We offer a new proof of the Furstenberg-Katznelson multiple recurrence
theorem for several commuting probability-preserving transformations T_1, T_2,
>..., T_d: \bbZ\curvearrowright (X,\S,\mu), and so, via the Furstenberg
correspondence principle introduced in, a new proof of the multi-dimensional
Szemeredi Theorem. We bypass the careful manipulation of certain towers of
factors of a probability-preserving system that underlies the
Furstenberg-Katznelson analysis, instead modifying an approach recently
developed for the study of convergence of nonconventional ergodic averages to
pass to a large extension of our original system in which this analysis greatly
simplifies. The proof is then completed using an adaptation of arguments
developed by Tao for his study of an infinitary analog of the hypergraph
removal lemma. In a sense, this addresses the difficulty, highlighted by Tao,
of establishing a direct connection between his infinitary, probabilistic
approach to the hypergraph removal lemma and the infinitary, ergodic-theoretic
approach to Szemeredi's Theorem set in motion by Furstenberg.


  A measurement of the mass of the Higgs boson in the diphoton decay channel is
presented. This analysis is based on 35.9 fb$^{-1}$ of proton-proton collision
data collected during the 2016 LHC running period, with the CMS detector at a
center-of-mass energy of 13 TeV. A refined detector calibration and new
analysis techniques have been used to improve the precision of this
measurement. The Higgs boson mass is measured to be $m_\mathrm{H} =$ 125.78
$\pm$ 0.26 GeV. This is combined with a measurement of $m_\mathrm{H}$ already
performed in the H $\to$ ZZ $\to$ 4$\ell$ decay channel using the same data
set, giving $m_\mathrm{H} =$ 125.46 $\pm$ 0.16 GeV. This result, when further
combined with an earlier measurement of $m_\mathrm{H}$ using data collected in
2011 and 2012 with the CMS detector, gives a value for the Higgs boson mass of
$m_\mathrm{H} =$ 125.38 $\pm$ 0.14 GeV. This is currently the most precise
measurement of the mass of the Higgs boson.


  Viscoelastic flows are pervasive in a host of natural and industrial
processes, where the emergence of nonlinear and time-dependent dynamics
regulate flow resistance, energy consumption, and particulate dispersal.
Polymeric stress induced by the advection and stretching of suspended polymers
feeds back on the underlying fluid flow, which ultimately dictates the
dynamics, instability, and transport properties of viscoelastic fluids.
However, direct experimental quantification of the stress field is challenging,
and a fundamental understanding of how Lagrangian flow structure regulates the
distribution of polymeric stress is lacking. In this work, we show that the
topology of the polymeric stress field precisely mirrors the Lagrangian
stretching field, where the latter depends solely on flow kinematics. We
develop a general analytical expression that directly relates the polymeric
stress and stretching in weakly viscoelastic fluids for both nonlinear and
unsteady flows, which is also extended to special cases characterized by strong
kinematics. Furthermore, numerical simulations reveal a clear correlation
between the stress and stretching field topologies for unstable viscoelastic
flows across a broad range of geometries. Ultimately, our results establish a
connection between the Eulerian stress field and the Lagrangian structure of
viscoelastic flows. This work provides a simple framework to determine the
topology of polymeric stress directly from readily measurable flow field data
and lays the foundation for directly linking the polymeric stress to flow
transport properties.


  With an X-ray luminosity of about 10^39 erg/s, the source X-8 coincident with
the optical center of M33 is the most luminous X-ray source in the Local Group.
However, its nature remains a mystery. We present here new and archival ROSAT
observations of X-8 spread over 6 years which show variability and a ~ 106-d
periodicity. This implies that (most of) the emission from M33 X-8 arises from
a single object, perhaps a binary system with a ~ 10 Msol black hole primary.
We suggest that the companion is a giant orbiting with a ~ 10 day period, and
that the observed modulation is ``super-orbital'', analogous to that seen in
Cyg X-2 and X1820-30.