  Two quantitative tests DIFF1 and DIFF2 for measuring goodness-of-fit between
two locally-normalized supernova spectra are presented. Locally-normalized
spectra are obtained by dividing a spectrum by the same spectrum smoothed over
a wavelength interval relatively large compared to line features, but
relatively small compared to continuum features. DIFF1 essentially measures the
mean relative difference between the line patterns of locally-normalized
spectra and DIFF2 is DIFF1 minimized by a relative logarithmic wavelength shift
between the spectra: the shift is effectively an artificial relative Doppler
shift. Both DIFF1 and DIFF2 measure the physical similarity of line formation,
and thus of supernovae. DIFF1 puts more weight on overall physical similarity
of the supernovae than DIFF2 because the DIFF2 shift compensates somewhat for
some physical distinction in the supernovae. Both tests are useful in ordering
supernovae into empirical groupings for further analysis. We present some
examples of locally-normalized spectra for Type IIb supernova SN 1993J with
some analysis of these spectra. The UV parts of two of the SN 1993J spectra are
HST spectra that have not been published before. We also give an example of
fitted locally-normalized spectra and, as an example of the utility of DIFF1
and DIFF2, some preliminary statistical results for hydrogen-deficient
core-collapse (HDCC) supernova spectra. This paper makes use of and refers to
material to found at the first author's online supernova spectrum database
SUSPEND (SUpernovae Spectra PENDing further analysis: see
http://www.nhn.ou.edu/~jeffery/astro/sne/spectra/spectra.html)


  In this article the operator trace function $ \Lambda_{r,s}(A)[K, M] :=
{\operatorname{tr}}(K^*A^r M A^r K)^s$ is introduced and its convexity and
concavity properties are investigated. This function has a direct connection to
several well-studied operator trace functions that appear in quantum
information theory, in particular when studying data processing inequalities of
various relative entropies. In the paper the interplay between $\Lambda_ {r,s}$
and the well-known operator functions $\Gamma_{p,s}$ and $\Psi_{p,q,s}$ is used
to study the stability of their convexity (concavity) properties. This
interplay may be used to ensure that $\Lambda_{r,s}$ is convex (concave) in
certain parameter ranges when $M=I$ or $K=I.$ However, our main result shows
that convexity (concavity) is surprisingly lost when perturbing those matrices
even a little. To complement the main theorem, the convexity (concavity) domain
of $\Lambda$ itself is examined. The final result states that $\Lambda_{r,s}$
is never concave and it is convex if and only if $r=1$ and $s\geq 1/2.$


  Fuzzing has become one of the most popular techniques to identify bugs in
software. To improve the fuzzing process, a plethora of techniques have
recently appeared in academic literature. However, evaluating and comparing
these techniques is challenging as fuzzers depend on randomness when generating
test inputs. Commonly, existing evaluations only partially follow best
practices for fuzzing evaluations. We argue that the reason for this are
twofold. First, it is unclear if the proposed guidelines are necessary due to
the lack of comprehensive empirical data in the case of fuzz testing. Second,
there does not yet exist a framework that integrates statistical evaluation
techniques to enable fair comparison of fuzzers. To address these limitations,
we introduce a novel fuzzing evaluation framework called SENF (Statistical
EvaluatioN of Fuzzers). We demonstrate the practical applicability of our
framework by utilizing the most wide-spread fuzzer AFL as our baseline fuzzer
and exploring the impact of different evaluation parameters (e.g., the number
of repetitions or run-time), compilers, seeds, and fuzzing strategies. Using
our evaluation framework, we show that supposedly small changes of the
parameters can have a major influence on the measured performance of a fuzzer.


  Periodically driven systems often exhibit behavior distinct from static
systems. In single-particle, static systems, any amount of disorder generically
localizes all eigenstates in one dimension. In contrast, we show that in
topologically non-trivial, single-particle Floquet loop drives with chiral
symmetry in one dimension, a localization-delocalization transition occurs as
the time $t$ is varied within the driving period ($0 \le t \le
T_\text{drive}$). We find that the time-dependent localization length
$L_\text{loc}(t)$ diverges with a universal exponent as $t$ approaches the
midpoint of the drive: $L_\text{loc}(t) \sim (t - T_\text{drive}/2)^{-\nu}$
with $\nu=2$. We provide analytical and numerical evidence for the universality
of this exponent within the AIII symmetry class.


  Using K-band imaging for 15 of the Canadian Network for Observational
Cosmology (CNOC1) clusters we examine the near-infrared properties of
moderate-redshift (0.19 < z < 0.55) galaxy clusters. We find that the number of
K-band selected cluster galaxies within R_{500} (the Halo Occupation Number,
HON) is well-correlated with the the cluster dynamical mass (M_{500}) and X-ray
Temperature (T_{x}); however, the intrinsic scatter in these scaling relations
is 37% and 46% respectively. Comparison with clusters in the local universe
shows that the HON-M_{500} relation does not evolve significantly between z = 0
and z ~ 0.3. This suggests that if dark matter halos are disrupted or undergo
significant tidal-stripping in high-density regions as seen in numerical
simulations, the stellar mass within the halos is tightly bound, and not
removed during the process. The total K-band cluster light (L_{200,K}) and
K-band selected richness (parameterized by B_{gc,K}) are also correlated with
both the cluster T_{x} and M_{200}. The total (intrinsic) scatter in the
L_{200,K}-M_{200} and B_{gc,K}-M_{200} relations are 43%(31%) and 35%(18%)
respectively and indicates that for massive clusters both L_{200,K} and
B_{gc,K} can predict M_{200} with similar accuracy as T_{x}, L_{x} or optical
richness (B_{gc}). Examination of the mass-to-light ratios of the clusters
shows that similar to local clusters, the K-band mass-to-light ratio is an
increasing function of halo mass. Using the K-band mass-to-light ratios of the
clusters, we apply the Oort technique and find Omega_{m,0} = 0.22 pm 0.02,
which agrees well with recent combined concordance cosmology parameters, but,
similar to previous cluster studies, is on the low-density end of preferred
values.


  We compare the steady state velocity distributions from our three-dimensional
inelastic hard sphere molecular dynamics simulation for homogeneously heated
granular media, with the predictions of a mean field-type Enskog-Boltzmann
equation for inelastic hard spheres [van Noije & Ernst, Gran. Matt. {\bf 1}, 57
(1998)]. Although we find qualitative agreement for all values of density and
inelasticity, the quantitative disagreement approaches $\sim 40%$ at high
inelasticity or density. By contrast the predictions of the pseudo-Maxwell
molecule model [Carrillo, Cercignani & Gamba, Phys. Rev. E, {\bf 62}, 7700
(2000)] are both qualitatively and quantitatively different from those of our
simulation. We also measure short-range and long-range velocity correlations
exhibiting non-zero correlations at contact before the collision, and being
consistent with a slow algebraic decay over a decade in the unit of the
diameter of the particle, proportional to $r^{-(1+\alpha)}$, where $0.2 <
\alpha < 0.3$. The existence of these correlations imply the failure of the
molecular chaos assumption and the mean field approximation, which is
responsible for the quantitative disagreement of the inelastic hard sphere
kinetic theory.


  We present a measurement of the volumetric rate of `calcium-rich' optical
transients in the local universe, using a sample of three events from the
Palomar Transient Factory (PTF). This measurement builds on a detailed study of
the PTF transient detection efficiencies, and uses a Monte Carlo simulation of
the PTF survey. We measure the volumetric rate of calcium-rich transients to be
higher than previous estimates: $1.21^{+1.13}_{-0.39}\times10^{-5}$ events
yr$^{-1}$ Mpc$^{-3}$. This is equivalent to 33-94% of the local volumetric type
Ia supernova rate. This calcium-rich transient rate is sufficient to reproduce
the observed calcium abundances in galaxy clusters, assuming an asymptotic
calcium yield per calcium-rich event of ~0.05$\mathrm{M}_{\odot}$. We also
study the PTF detection efficiency of these transients as a function of
position within their candidate host galaxies. We confirm as a real physical
effect previous results that suggest calcium-rich transients prefer large
physical offsets from their host galaxies.


  Commencing from the centrosymmetric MnRMnSbO$_6$ compound, we explore the
realm of magnetic polar double-double perovskite oxides characterized by
significant ferroelectric polarization. Employing symmetry operations,
first-principles methodologies, and Monte Carlo simulations, our investigation
delves into the structural, magnetic, ferroelectric, and electronic attributes
of the polar LaFeMnNiO$_6$ and LaTiMnNiO$_6$ compounds. The structural analysis
uncovers that the paraelectric-ferroelectric phase transition is intricately
linked to the Fe/Ti-displacement of square planar Fe/TiO$_4$. Notably, the
magnetic LaFeMnNiO$_6$ and LaTiMnNiO$_6$ compounds demonstrate robust
ferroelectric polarizations, measuring 20.0 $\mu$C/cm$^2$ and 21.8
$\mu$C/cm$^2$, respectively, accompanied by minimalist forbidden energy gaps of
1.40 eV and 1.18 eV using the GGA+U method. Furthermore, we pinpoint elevated
magnetic transition temperatures for these compounds. Additionally, our study
scrutinizes the energies associated with diverse spin configurations and
identifies potential minimum decomposition pathways into stable oxides. This
comprehensive analysis ensures the meticulous formation of the LaFeMnNiO$_6$
and LaTiMnNiO$_6$ compounds.


  In this paper we show that absence of complex zeros of the partition function
of the hard-core model on any family of bounded degree graphs implies that the
associated probability measure, the \emph{hard-core measure}, satisfies strong
spatial mixing on that family. As a corollary we obtain that the hard-core
measure on the family of bounded degree claw-free graphs satisfies strong
spatial mixing. We furthermore derive strong spatial mixing for graph
homomorphism measures from absence of zeros of the graph homomorphism partition
function.


  We argue that because of valence-fluctuation caused dynamical changes
(fluctuations) of impurity energies in the impurity band of SmB6, energies of
electrons occupying impurity sites can be due to the uncertainty principle only
estimated with corresponding uncertainty, so they can be represented by energy
intervals of non-zero width. As a conse- quence, both occupied as well as
unoccupied states can be found in the impurity band above as well as below
Fermi level even in the ground state. Therefore the subsystem of localized
charge carriers in the ground state of SmB6 cannot be described by an energy
distribution function expected for T = 0 K. This fundamental conclusion adds
another reason for absence of resistivity divergence in SmB6 at lowest
temperatures, and sheds new light on interpretation of experimental data
obtained for SmB6 and similar systems at lowest temperatures.


  We study populations of agents evolving in fitness landscapes constructed
according to the rules of a modified NK model with a tunable amount of neutral
paths. In the `punctuated equilibrium' regime evolutionary events are
identified as jumps in the mean population fitness, and the statistics of these
jumps in an ensemble of independently evolving populations is analyzed. We show
that, for a wide range of landscapes parameters, the number of events in time t
is Poisson distributed, with the time parameter replaced by the logarithm of
time. This simple log-Poisson statistics likewise describes the number n of
records in any sequence of t independently generated random numbers. The
implications of this behavior for evolution dynamics are discussed.


  Magnetic Particle Imaging (MPI) is a highly sensitive imaging method that
enables the visualization of magnetic tracer materials with a temporal
resolution of more than 46 volumes per second. In MPI the size of the field of
view scales with the strengths of the applied magnetic fields. In clinical
applications those strengths are limited by peripheral nerve stimulation,
specific absorption rates, and the requirement to acquire images of high
spatial resolution. Therefore, the size of the field of view is usually a few
cubic centimeters. To bypass this limitation, additional focus fields and/or
external object movements can be applied. In this work, the latter approach is
investigated. An object is moved through the scanner bore one step at a time,
while the MPI scanner continuously acquires data from its static field of view.
Using a 3D phantom and dynamic 3D in vivo data it is shown that the data from
such a moving table experiment can be jointly reconstructed after reordering
the data with respect to the stepwise object shifts and heart beat phases.


  We investigate the structure of a field around the position of V838 Mon as
seen in the lowest CO rotational transitions. We also measure and analyse
emission in the same lines at the position of V838 Mon.Observations have
primarily been done in the CO J = 2-1 and J = 3-2 lines using the KOSMA
telescope. A field of 3.4 squared degrees has been mapped in the on-the-fly
mode in these transitions. Longer integration spectra in the on-off mode have
been obtained to study the emission at the position of V838 Mon. Selected
positions in the field have also been observed in the CO J = 1-0 transition
using the Delingha telescope.In the observed field we have identified many
molecular clouds. They can be divided into two groups from the point of view of
their observed radial velocities. One, having V(LSR) in the range 18-32 km/s,
can be identified with the Perseus Galactic arm. The other one, having V(LSR)
between 44-57 km/s, probably belongs to the Norma-Cygnus arm. The radial
velocity of V838 Mon is within the second range but the object does not seem to
be related to any of the observed clouds. We did not find any molecular buble
of a 1 degree dimension around the position of V838 Mon claimed in van Loon et
al. An emission has been detected at the position of the object in the CO J =
2-1 and J = 3-2 transitions. The emission is very narrow (FWHM ~ 1.2 km/s) and
at V(LSR) = 53.3 km/s. Our analysis of the data suggests that the emission is
probably extended.


  Following a recent work by C. Bai, O. Bellier, L. Guo, and X. Ni
(arXiv:1106.6080) we define what is a dendriform di- or trialgebra in an
arbitrary variety Var of algebras (associative, commutative, Poisson, etc.). We
prove that every dendriform dialgebra in Var can be embedded into a
Rota---Baxter algebra of weight zero in the same variety, and every dendriform
trialgebra can be embedded into a Rota---Baxter algebra of nonzero weight.


  The covariant understanding of dispersion relations as level sets of Hamilton
functions on phase space enables us to derive the most general dispersion
relation compatible with homogeneous and isotropic spacetimes. We use this
concept to present a Planck-scale deformation of the Hamiltonian of a particle
in Friedman-Lema\^itre-Robertson-Walker (FLRW) geometry that is locally
identical to the $\kappa$-Poincar\'e dispersion relation, in the same way as
the dispersion relation of point particles in general relativity is locally
identical to the one valid in special relativity. Studying the motion of
particles subject to such Hamiltonian we derive the redshift and lateshift as
observable consequences of the Planck-scale deformed FLRW universe.


  We survey the field of algorithms and complexity for graph problems
parameterized above or below guaranteed values, a research area which was
pioneered by Venkatesh Raman. Those problems seek, for a given graph $G$, a
solution whose value is at least $g(G)+k$ or at most $g(G)-k$, where $g(G)$ is
a guarantee on the value that any solution on $G$ takes. The goal is to design
algorithms which find such solution in time whose complexity in $k$ is
decoupled from that in the guarantee, or to rule out the existence of such
algorithms by means of intractability results. We discuss a large number of
algorithms and intractability results, and complement them by several open
problems.


  We consider a Tamari interval of size $n$ (i.e., a pair of Dyck paths which
are comparable for the Tamari relation) chosen uniformly at random. We show
that the height of a uniformly chosen vertex on the upper or lower path scales
as $n^{3/4}$, and has an explicit limit law. By the Bernardi-Bonichon
bijection, this result also describes the height of points in the canonical
Schnyder trees of a uniform random plane triangulation of size $n$.
  The exact solution of the model is based on polynomial equations with one and
two catalytic variables. To prove the convergence from the exact solution, we
use a version of moment pumping based on D-finiteness, which is essentially
automatic and should apply to many other models. We are not sure to have seen
this simple trick used before.
  It would be interesting to study the universality of this convergence for
decomposition trees associated to positive Bousquet-M\'elou--Jehanne equations.


  This paper studies homeomorphisms of the closed annulus that are isotopic to
the identity from the viewpoint of rotation theory, using a newly developed
forcing theory for surface homeomorphisms. Our first result is a solution to
the so called strong form of Boyland's Conjecture on the closed annulus: Assume
$f$ is a homeomorphism of $\overline{\mathbb{A}}:=(\mathbb{R}/\mathbb{Z})\times
[0,1]$ which is isotopic to the identity and preserves a Borel probability
measure $\mu$ with full support. We prove that if the rotation set of $f$ is a
non-trivial segment, then the rotation number of the measure $\mu$ cannot be an
endpoint of this segment. We also study the case of homeomorphisms such that
$\mathbb{A}=(\mathbb{R}/\mathbb{Z})\times (0,1)$ is a region of instability of
$f$. We show that, if the rotation numbers of the restriction of $f$ to the
boundary components lies in the interior of the rotation set of $f$, then $f$
has uniformly bounded deviations from its rotation set. Finally, by combining
this last result and recent work on realization of rotation vectors for annular
continua, we obtain that if $f$ is any area-preserving homeomorphism of
$\overline{\mathbb{A}}$ isotopic to the identity, then for every real number
$\rho$ in the rotation set of $f$, there exists an associated Aubry-Mather set,
that is, a compact $f$-invariant set such that every point in this set has a
rotation number equal to $\rho$. This extends a result by P. Le Calvez
previously known only for diffeomorphisms.


  Random uniform sampling has been studied in various statistical tasks but few
of them have covered the Q-error metric for cardinality estimation (CE). In
this paper, we analyze the confidence intervals of random uniform sampling with
and without replacement for single-table CE. Results indicate that the upper
Q-error bound depends on the sample size and true cardinality. Our bound gives
a rule-of-thumb for how large a sample should be kept for single-table CE.


  There has been a paradigm shift from the well-known laws of thermal radiation
derived over a century ago, valid only when the length scales involved are much
larger than the thermal wavelength (around 10 $\mu$m at room temperature), to a
general framework known as fluctuational electrodynamics that allows
calculations of radiative heat transfer for arbitrary sizes and length scales.
Near-field radiative heat transfer and thermal emission in systems of
sub-wavelength size can exhibit super-Planckian behaviour, i.e. flux rates
several orders of magnitude larger than that predicted by the Stefan-Boltzmann
(or blackbody) limit. These effects can be combined with novel materials, e.g.
low-dimensional or topological systems, to yield even larger modifications and
spectral and/or directional selectivity. We introduce briefly the context and
the main steps that have led to the current boom of ideas and applications. We
then discuss the original and impactful works gathered in the associated
Special Topic collection, which provides an overview of the flourishing field
of nanoscale thermal radiation.


  It is proposed that the new generation of spintronics should be ideally
massless and dissipationless for the realization of ultra-fast and
ultra-low-power spintronic devices. We demonstrate that the spin-gapless
materials with linear energy dispersion are unique materials that can realize
these massless and dissipationless states. Furthermore, we propose four new
types of spin Hall effects which consist of spin accumulation of equal numbers
of electrons and holes having the same or opposite spin polarization at the
sample edge in Hall effect measurements, but with vanishing Hall voltage. These
new Hall effects can be classified as (quantum) anomalous spin Hall effects.
The physics for massless and dissipationless spintronics and the new spin Hall
effects are presented for spin-gapless semiconductors with either linear or
parabolic dispersion. New possible candidates for Dirac-type or parabolic type
spin-gapless semiconductors are demonstrated in ferromagnetic monolayers of
simple oxides with either honeycomb or square lattices.


  One of the basic tasks in bioinformatics is localizing a short subsequence
$S$, read while sequencing, in a long reference sequence $R$, like the human
geneome. A natural rapid approach would be finding a hash value for $S$ and
compare it with a prepared database of hash values for each of length $|S|$
subsequences of $R$. The problem with such approach is that it would only spot
a perfect match, while in reality there are lots of small changes:
substitutions, deletions and insertions.
  This issue could be repaired if having a hash function designed to tolerate
some small distortion accordingly to an alignment metric (like
Needleman-Wunch): designed to make that two similar sequences should most
likely give the same hash value. This paper discusses construction of
Distortion-Resistant Hashing (DRH) to generate such fingerprints for rapid
search of similar subsequences. The proposed approach is based on the rate
distortion theory: in a nearly uniform subset of length $|S|$ sequences, the
hash value represents the closest sequence to $S$. This gives some control of
the distance of collisions: sequences having the same hash value.


  We consider the problem of nonlinear system identification when prior
knowledge is available on the region of attraction (ROA) of an equilibrium
point. We propose an identification method in the form of an optimization
problem, minimizing the fitting error and guaranteeing the desired stability
property. The problem is approached by joint identification the dynamics and a
Lyapunov function verifying the stability property. In this setting, the
hypothesis set is a reproducing kernel Hilbert space, and with respect to each
point of the given subset of the ROA, the Lie derivative inequality of the
Lyapunov function imposes a constraint. The problem is a non-convex
infinite-dimensional optimization with infinite number of constraints. To
obtain a tractable formulation, only a suitably designed finite subset of the
constraints are considered. The resulting problem admits a solution in form of
a linear combination of the sections of the kernel and its derivatives. An
equivalent optimization problem with a quadratic cost function subject to
linear and bilinear constraints is derived. A suitable change of variable gives
a convex reformulation of the problem. To reduce the number of hyperparameters,
the optimization problem is adapted to the case of diagonal kernels. The method
is demonstrate by means of an example.


  The effective medium approximation (EMA) method is commonly used to estimate
the effective conductivity development in composites containing two types of
materials: conductors and insulators. The effective conductivity is a global
parameter that measures how easily the composite conducts electric current.
Currently, financial transactions in society take place in cash or cashless,
and, in the cashless transactions the money flows faster than in the cash
transactions. Therefore, to provide a cashless grading of countries, we
introduce a cashless transaction index (CTI) which is calculated using the EMA
method in which individuals who make cash transactions are analogous to the
insulator element in the composite and individuals who make cash transactions
are analogous to the conductor element. We define the CTI as the logarithmic of
the effective conductivity of a country's transactions. We also introduce the
time dependent equation for the cashless share. Estimates from the proposed
model can explain well the data in the last few years.


  Nonclassical quantum effects gradually reach domains of physics of large
systems previously considered as purely classical. We derive a hierarchy of
operational criteria suitable for a reliable detection of nonclassicality of
light from an arbitrarily large ensemble of independent single-photon emitters.
We show, that such large ensemble can always emit nonclassical light without
any phase reference and under realistic experimental conditions including
incoherent background noise. The nonclassical light from the large ensemble of
the emitters can be witnessed much better than light coming from a single or a
few emitters.


  Recent magneto-transport experiments of holes in InGaAs quantum dots [D.
Reuter, P. Kailuweit, A.D. Wieck, U. Zeitler, O. Wibbelhoff, C. Meier, A.
Lorke, and J.C. Maan, Phys. Rev. Lett. 94, 026808 (2005)] are interpreted by
employing a multi-band kp Hamiltonian, which considers the interaction between
heavy hole and light hole subbands explicitely. No need of invoking an
incomplete energy shell filling is required within this model. The crucial role
we ascribe to the heavy hole-light hole interaction is further supported by
one-band local-spin-density functional calculations, which show that Coulomb
interactions do not induce any incomplete hole shell filling and therefore
cannot account for the experimental magnetic field dispersion.


  Since 2014, the F\'ed\'eration Internationale de l'Automobile has prescribed
a parallel hybrid powertrain for the Formula 1 race cars. The complex low-level
interactions between the thermal and the electrical part represent a
non-trivial and challenging system to be controlled online. We present a novel
controller architecture composed of a supervisory controller for the energy
management, a feedforward cylinder deactivation controller, and a track
region-dependent low-level nonlinear model predictive controller to optimize
the engine actuators. Except for the nonlinear model predictive controller, the
proposed controller subsystems are computationally inexpensive and are real
time capable. The framework is tested and validated in a simulation environment
for several realistic scenarios disturbed by driver actions or grip conditions
on the track. In particular, we analyze how the control architecture deals with
an unexpected gearshift trajectory during an acceleration phase. Further, we
demonstrate how an increased maximum velocity trajectory impacts the online
low-level controller. Our results show a suboptimality over an entire lap with
respect to the benchmark solution of 49 ms and 64 ms, respectively, which we
deem acceptable. Compared to the same control architecture with full knowledge
of the disturbances, the suboptimality amounted to only 2 ms and 17 ms. For all
case studies we show that the cylinder deactivation capability decreases the
suboptimality by 7 to 8 ms.


  We have designed a passive spintronic diode based on a single skyrmion
stabilized in a magnetic tunnel junction and studied its dynamics induced by
voltage-controlled anisotropy (VCMA) and Dzyaloshinskii-Moriya interaction
(VDMI). We have demonstrated that the sensitivity (rectified voltage over input
microwave power) with realistic physical parameters and geometry can be larger
than 10 kV/W which is one order of magnitude better than diodes employing a
uniform ferromagnetic state. Our numerical and analytical results on the VCMA
and VDMI-driven resonant excitation of skyrmions beyond the linear regime
reveal a frequency dependence on the amplitude and no efficient parametric
resonance. Skyrmions with a smaller radius produced higher sensitivities,
demonstrating the efficient scalability of skyrmion-based spintronic diodes.
These results pave the way for designing passive ultra-sensitive and energy
efficient skyrmion-based microwave detectors.


  We analyze rare kaon decays in models in which the dominant new effect is an
enhanced sbar d Z vertex Z_{ds}. We point out that in spite of large
theoretical uncertainties the CP-violating ratio epsilon'/epsilon provides at
present the strongest constraint on Im Z_{ds}. Assuming 1.5 10^{-3} <
epsilon'/epsilon < 3 10^{-3} and Standard Model values for the CKM parameters
we obtain the bounds BR(K_L -> pi^0 nu nubar) < 3.9 10^{-10} and BR(K_L -> pi^0
e^+ e^-)_{dir} < 7.9 10^{-11}. Using the bound on Re Z_{ds} from K_L -> mu^+
mu^- we find BR(K^+ -> pi^+ nu nubar) < 2.6 10^{-10}. We also discuss new
physics scenarios in which in addition to an enhanced sbar d Z vertex also
neutral meson mixing receives important new contributions. In this case our
most conservative bounds are BR(K_L -> pi^0 nu nubar) < 1.8 10^{-9}, BR(K_L ->
pi^0 e^+ e^-)_{dir} < 2.8 10^{-10} and BR(K^+ -> pi^+ nu nubar) < 6.1 10^{-10}.
The dependence of the upper bound for BR(K_L -> pi^0 nu nubar) on the CKM
parameters is also analyzed.


  We investigate the continuum limit of the rooted staggered determinant in the
2-dimensional Schwinger model. We match both the unrooted and rooted staggered
determinant with an overlap fermion determinant of two (one) flavors and a
local pure gauge effective action by fitting the coefficients of the effective
action and the mass of the overlap operator. The residue of this fit measures
the difference of the staggered and overlap fermion actions. We show that this
residue scales at least as O(a^2), implying that any difference, be it local or
non-local, between the staggered and overlap actions becomes irrelevant in the
continuum limit. This observation justifies the rooting procedure.


  In this article, we investigate the existence of joins in the weak order of
an infinite Coxeter group W. We give a geometric characterization of the
existence of a join for a subset X in W in terms of the inversion sets of its
elements and their position relative to the imaginary cone. Finally, we discuss
inversion sets of infinite reduced words and the notions of biconvex and
biclosed sets of positive roots.


  We have constructed a GEANT4-based detailed software model of photon
transport in plastic scintillator blocks and have used it to study the NEMO-3
and SuperNEMO calorimeters employed in experiments designed to search for
neutrinoless double beta decay. We compare our simulations to measurements
using conversion electrons from a calibration source of $\rm ^{207}Bi$ and show
that the agreement is improved if wavelength-dependent properties of the
calorimeter are taken into account. In this article, we briefly describe our
modeling approach and results of our studies.


  Post-hoc explanation methods have often been criticised for abstracting away
the decision-making process of deep neural networks. In this work, we would
like to provide natural language descriptions for what different layers of a
vision backbone have learned. Our DeViL method decodes vision features into
language, not only highlighting the attribution locations but also generating
textual descriptions of visual features at different layers of the network. We
train a transformer network to translate individual image features of any
vision layer into a prompt that a separate off-the-shelf language model decodes
into natural language. By employing dropout both per-layer and
per-spatial-location, our model can generalize training on image-text pairs to
generate localized explanations. As it uses a pre-trained language model, our
approach is fast to train, can be applied to any vision backbone, and produces
textual descriptions at different layers of the vision network. Moreover, DeViL
can create open-vocabulary attribution maps corresponding to words or phrases
even outside the training scope of the vision model. We demonstrate that DeViL
generates textual descriptions relevant to the image content on CC3M surpassing
previous lightweight captioning models and attribution maps uncovering the
learned concepts of the vision backbone. Finally, we show DeViL also
outperforms the current state-of-the-art on the neuron-wise descriptions of the
MILANNOTATIONS dataset. Code available at
https://github.com/ExplainableML/DeViL


  Infrared (IR) image segmentation is essential in many urban defence
applications, such as pedestrian surveillance, vehicle counting, security
monitoring, etc. Active contour model (ACM) is one of the most widely used
image segmentation tools at present, but the existing methods only utilize the
local or global single feature information of image to minimize the energy
function, which is easy to cause false segmentations in IR images. In this
paper, we propose a multi-feature driven active contour segmentation model to
handle IR images with intensity inhomogeneity. Firstly, an especially-designed
signed pressure force (SPF) function is constructed by combining the global
information calculated by global average gray information and the local
multi-feature information calculated by local entropy, local standard deviation
and gradient information. Then, we draw upon adaptive weight coefficient
calculated by local range to adjust the afore-mentioned global term and local
term. Next, the SPF function is substituted into the level set formulation
(LSF) for further evolution. Finally, the LSF converges after a finite number
of iterations, and the IR image segmentation result is obtained from the
corresponding convergence result. Experimental results demonstrate that the
presented method outperforms the state-of-the-art models in terms of precision
rate and overlapping rate in IR test images.


  Topographical structures represent connections between entities and provide a
comprehensive design of complex systems. Currently these structures are used to
discover correlates of neuronal and haemodynamical activity. In this work, we
incorporate them with neural processing techniques to perform regression, using
electrophysiological activity to retrieve haemodynamics. To this end, we use
Fourier features, attention mechanisms, shared space between modalities and
incorporation of style in the latent representation. By combining these
techniques, we propose several models that significantly outperform current
state-of-the-art of this task in resting state and task-based recording
settings. We report which EEG electrodes are the most relevant for the
regression task and which relations impacted it the most. In addition, we
observe that haemodynamic activity at the scalp, in contrast with sub-cortical
regions, is relevant to the learned shared space. Overall, these results
suggest that EEG electrode relationships are pivotal to retain information
necessary for haemodynamical activity retrieval.


  Many real-world strategic games involve interactions between multiple
players. We study a hierarchical multi-player game structure, where players
with asymmetric roles can be separated into leaders and followers, a setting
often referred to as Stackelberg game or leader-follower game. In particular,
we focus on a Stackelberg game scenario where there are multiple leaders and a
single follower, called the Multi-Leader-Single-Follower (MLSF) game. We
propose a novel asymmetric equilibrium concept for the MLSF game called
Correlated Stackelberg Equilibrium (CSE). We design online learning algorithms
that enable the players to interact in a distributed manner, and prove that it
can achieve no-external Stackelberg-regret learning. This further translates to
the convergence to approximate CSE via a reduction from no-external regret to
no-swap regret. At the core of our works, we solve the intricate problem of how
to learn equilibrium in leader-follower games with noisy bandit feedback by
balancing exploration and exploitation in different learning structures.


  Intelligent transport of molecular species across different barriers is
critical for various biological functions and is achieved through the unique
properties of biological membranes. An essential feature of intelligent
transport is the ability to adapt to different external and internal conditions
and also the ability to memorise the previous state. In biological systems, the
most common form of such intelligence is expressed as hysteresis. Despite
numerous advances made over previous decades on smart membranes, it is still a
challenge for a synthetic membrane to display stable hysteretic behaviour for
molecular transport. Here we show the memory effects and stimuli regulated
transport of molecules through an intelligent phase changing MoS$_2$ membrane
in response to external pH. We show that water and ion permeation through 1T'
MoS$_2$ membranes follows a pH dependent hysteresis with a permeation rate that
switches by a few orders of magnitude. We demonstrate that this phenomenon is
unique to the 1T' phase of MoS$_2$ due to the presence of surface charge and
exchangeable ions on the surface. We further demonstrate the potential
application of this phenomenon in autonomous wound infection monitoring and
pH-dependent nanofiltration. Our work significantly deepens understanding of
the mechanism of water transport at the nanoscale and opens an avenue for
developing neuromorphic applications, smart drug delivery systems,
point-of-care diagnostics, smart sensors, and intelligent filtration devices.


  We consider hyperfine splitting of 1s and, in part, of 2s levels in light
hydrogen-like atoms: hydrogen, deuterium, tritium, helium-3 ion, muonium and
positronium. We discuss present status of precision theory and experiment for
the hfs intervals. We pay a special attention to a specific difference, D_{21}
= 8 E_{hfs}(2s) - E_{hfs}(1s), which is known experimentally for hydrogen,
deuterium and ^3He^+ ion. The difference is weakly affected by the effects of
the nuclear structure and thus may be calculated with a high accuracy. We
complete a calculation of the fourth order QED contributions to this difference
and present here new results on corrections due to the nuclear effects. Our
theoretical predictions appear to be in a fair agreement with available
experimental data. Comparison of the experimental data with our examination of
D_{21} allows to test the state-dependent sector of theory of the hfs
separation of the 1s and 2s levels in the light hydrogen-like atoms up to
10^-8.


  Supersymmetric models with nearly-degenerate light higgsinos provide a
consistent solution to the naturalness problem under rigorous constraints from
current experimental searches for sparticles. However, it is challenging to
probe the compressed scenarios at collider experiments due to the
hard-to-detect soft final states. To overcome this issue, strategies have been
proposed to take advantage of the photon fusion along the ultraperipheral
collision at the Large Hadron Collider, which are feasible with the forward
detectors installed at the ATLAS and CMS detectors. In this paper, we
demonstrate a search strategy for the chargino pair production via photon
fusion at the 13 TeV LHC, realizing a good sensitivity that can exclude
$m_{\tilde{\chi}^{\pm}_{1}}$ up to 270 GeV (308 GeV) for a mass splitting
$\Delta m(\tilde{\chi}^{\pm}_{1},\tilde{\chi}^{0}_{1})\in[1,15]$ GeV with an
integrated luminosity of 100 fb$^{-1}$ (3 ab$^{-1}$) at 95% C.L.


  We introduce a family of compatible Poisson brackets on the space of $2\times
2$ polynomial matrices, which contains the reflection equation algebra bracket.
Then we use it to derive a multi-Hamiltonian structure for a set of integrable
systems that includes the $XXX$ Heisenberg magnet with boundary conditions, the
generalized Toda lattices and the Kowalevski top.


  We investigate whether the spin or charge degrees of freedom are responsible
for the nodal gap in underdoped cuprates by performing inelastic neutron
scattering and x-ray diffraction measurements on La$_{2-x}$Sr$_x$CuO$_4$, which
is on the edge of the antiferromagnetic phase. We found that fluctuating
incommensurate spin-density-wave (SDW) with a the bottom part of an hourglass
dispersion exists even in this magnetic sample. The strongest component of
these fluctuations diminishes at the same temperature where the nodal gap
opens. X-ray scattering measurements on the same crystal show no signature of
charge-density-wave (CDW). Therefore, we suggest that the nodal gap in the
electronic band of this cuprate opens due to fluctuating SDW with no
contribution from CDW.


  We compute the center and Azumaya locus in the simplest non-abelian examples
of quantized multiplicative quiver varieties at a root of unity: quantum Weyl
algebras of rank $N$, and quantum differential operators on the quantum group
$\mathrm{GL}_2$. These examples illustrate in elementary terms much more
general phenomena explored further in [Ganev-Jordan-Safronov 2019].


  We present a novel treatment of set theory in a four-valued paraconsistent
and paracomplete logic, i.e., a logic in which propositions can be both true
and false, and neither true nor false. Our approach is a significant departure
from previous research in paraconsistent set theory, which has almost
exclusively been motivated by a desire to avoid Russell's paradox and fulfil
naive comprehension. Instead, we prioritise setting up a system with a clear
ontology of non-classical sets, which can be used to reason informally about
incomplete and inconsistent phenomena, and is sufficiently similar to ZFC to
enable the development of interesting mathematics.
  We propose an axiomatic system BZFC, obtained by analysing the ZFC-axioms and
translating them to a four-valued setting in a careful manner, avoiding many of
the obstacles encountered by other attempted formalizations. We introduce the
anti-classicality axiom postulating the existence of non-classical sets, and
prove a surprising results stating that the existence of a single non-classical
set is sufficient to produce any other type of non-classical set.
  Our theory is naturally bi-interpretable with ZFC, and provides a
philosophically satisfying view in which non-classical sets can be seen as a
natural extension of classical ones, in a similar way to the non-well-founded
sets of Peter Aczel.
  Finally, we provide an interesting application concerning Tarski semantics,
showing that the classical definition of the satisfaction relation yields a
logic precisely reflecting the non-classicality in the meta-theory.


  Unprecedentedly massive electrorheology has been reported for dilute graphene
nanoflakes based ER fluids that have been engineered as novel, readily
synthesizable polymeric gels. Polyethylene glycol based graphene gels have been
synthesized and very high ER response, 25,000 percent enhancement in viscosity
under influence of electric field, has been observed for low concentration
systems 2 wt. percent. The gels overcome several drawbacks innate to ER fluids.
The gels exhibit long term stability, high graphene packing ratio which ensures
very high ER response and the microstructure of the gels ensure that
fibrillation of the graphene nanoflakes under field is undisturbed by thermal
fluctuations, further leading to mega ER. The gels exhibit large yield stress
handling caliber with yield stress observed as high as 13 kPa at 2 wt. perc.
graphene. Detailed investigations on the effects of graphene concentration,
electric field strength, imposed shear resistance and transients of electric
field actuation on the ER response of the gels have been performed. The gels
show nearly negligible hysteresis with respect to electro viscous effects which
speak of the stability and responsiveness required in transient situations.
Indepth analyses with explanations have been provided for the observations and
effects, such as sheet over-crowding induced loss of structural integrity at
high concentrations and inter flake lubrication or slip induced augmented ER
response. The present gels show great promise as potential ER gels for variant
smart applications, such as damping and vibration control in active aircraft
and vehicle structures, micronanoscale electroactuation, in suspensions or
braking clutching in high performance specialized vehicular systems, etc.


  On the Ethereum network, it is challenging to determine a gas price that
ensures a transaction will be included in a block within a user's required
timeline without overpaying. One way of addressing this problem is through the
use of gas price oracles that utilize historical block data to recommend gas
prices. However, when transaction volumes increase rapidly, these oracles often
underestimate or overestimate the price. In this paper, we demonstrate how
Gaussian process models can predict the distribution of the minimum price in an
upcoming block when transaction volumes are increasing. This is effective
because these processes account for time correlations between blocks. We
performed an empirical analysis using the Gaussian process model on historical
block data and compared the performance with GasStation-Express and Geth gas
price oracles. The results suggest that when transactions volumes fluctuate
greatly, the Gaussian process model offers a better estimation. Further, we
demonstrated that GasStation-Express and Geth can be improved upon by using a
smaller training sample size which is properly pre-processed. Based on the
results of empirical analysis, we recommended a gas price oracle made up of a
hybrid model consisting of both the Gaussian process and GasStation-Express.
This oracle provides efficiency, accuracy, and better cost.


  Physics-informed neural networks (PINNs) are effective in solving inverse
problems based on differential and integral equations with sparse, noisy,
unstructured, and multi-fidelity data. PINNs incorporate all available
information into a loss function, thus recasting the original problem into an
optimization problem. In this paper, we extend PINNs to parameter and function
inference for integral equations such as nonlocal Poisson and nonlocal
turbulence models, and we refer to them as nonlocal PINNs (nPINNs). The
contribution of the paper is three-fold. First, we propose a unified nonlocal
operator, which converges to the classical Laplacian as one of the operator
parameters, the nonlocal interaction radius $\delta$ goes to zero, and to the
fractional Laplacian as $\delta$ goes to infinity. This universal operator
forms a super-set of classical Laplacian and fractional Laplacian operators
and, thus, has the potential to fit a broad spectrum of data sets. We provide
theoretical convergence rates with respect to $\delta$ and verify them via
numerical experiments. Second, we use nPINNs to estimate the two parameters,
$\delta$ and $\alpha$. The strong non-convexity of the loss function yielding
multiple (good) local minima reveals the occurrence of the operator mimicking
phenomenon: different pairs of estimated parameters could produce multiple
solutions of comparable accuracy. Third, we propose another nonlocal operator
with spatially variable order $\alpha(y)$, which is more suitable for modeling
turbulent Couette flow. Our results show that nPINNs can jointly infer this
function as well as $\delta$. Also, these parameters exhibit a universal
behavior with respect to the Reynolds number, a finding that contributes to our
understanding of nonlocal interactions in wall-bounded turbulence.


  In this paper, we propose a simplified bidimensional Wolbachia infestation
model in a population of Aedes aegypti mosquitoes, preserving the main features
associated with the biology of this species that can be found in
higher-dimensional models. Namely, our model represents the maternal
transmission of the Wolbachia symbiont, expresses the reproductive phenotype of
cytoplasmic incompatibility, accounts for different fecundities and mortalities
of infected and wild insects, and exhibits the bistable nature leading to the
so-called principle of competitive exclusion. Since Wolbachia-based biocontrol
is now accepted as an ecologically friendly and potentially cost-effective
method for prevention and control of dengue and other arboviral infections, it
is essential to have reduced models with the main biological characteristics of
Aedes aegypti in the presence of Wolbachia-carriers because such models help to
simplify the mathematical analysis for determining appropriate biocontrol
strategies. Using tools borrowed from monotone dynamical system theory, in the
proposed model, we prove the existence of an invariant threshold manifold that
allows us to provide practical recommendations for performing single and
periodic releases of Wolbachia-carrying mosquitoes, seeking the eventual
elimination of wild insects that are capable of transmitting infections to
humans. We illustrate these findings with numerical simulations using parameter
values corresponding to the wMelPop strain of Wolbachia that is considered the
best virus blocker but induces fitness loss in its carriers.


  This review provides a brief and quick introduction to the quantum Langevin
equation for an oscillator, while focusing on the steady-state thermodynamic
aspects. A derivation of the quantum Langevin equation is carefully outlined
based on the microscopic model of the heat bath as a collection of a large
number of independent quantum oscillators, the so-called independent-oscillator
model. This is followed by a discussion on the relevant `weak-coupling' limit.
In the steady state, we analyze the quantum counterpart of energy equipartition
theorem which has generated a considerable amount of interest in recent
literature. The free energy, entropy, specific heat, and third law of
thermodynamics are discussed for one-dimensional quantum Brownian motion in a
harmonic well. Following this, we explore some aspects of dissipative
diamagnetism in the context of quantum Brownian oscillators, emphasizing upon
the role of confining potentials and also upon the environment-induced
classical-quantum crossover. We discuss situations where the system-bath
coupling is via the momentum variables by focusing on a gauge-invariant model
of momentum-momentum coupling in the presence of a vector potential; for this
problem, we derive the quantum Langevin equation and discuss quantum
thermodynamic functions. Finally, the topic of fluctuation theorems is
discussed (albeit, briefly) in the context of classical and quantum cyclotron
motion of a particle coupled to a heat bath.


  We decompose a matrix Y into a sum of bilinear terms in a stepwise manner, by
considering Y as a mapping from a finite dimensional Banach space into another
finite dimensional Banach space. We provide transition formulas, and represent
them in a duality diagram, thus generalizing the well known duality diagram in
the french school of data analysis. As an application, we introduce a family of
Euclidean multidimensional scaling models.


  Quantum entanglement marks a definitive feature of topological states.
However, the entanglement spectrum remains insufficiently explored for
topological states without a bulk energy gap. Using a combination of field
theory and numerical techniques, we accurately calculate and analyze the
entanglement spectrum of gapless symmetry protected topological states in one
dimension. We highlight that the universal entanglement spectrum not only
encodes the nontrivial edge degeneracy, generalizing the Li-Haldane conjecture
to gapless topological states, but also contains the operator content of the
underlying boundary conformal field theory. This implies that the bulk wave
function can act as a fingerprint of both quantum criticality and topology in
gapless symmetry protected topological states. We also identify a symmetry
enriched conformal boundary condition that goes beyond the conventional
conformal boundary condition.


  We show that the twisted second moments of the Riemann zeta function averaged
over the arithmetic progression $1/2 + i(an + b)$ with $a > 0$, $b$ real,
exhibits a remarkable correspondance with the analogous continuous average and
derive several consequences. For example, motivated by the linear independence
conjecture, we show at least one third of the elements in the arithmetic
progression $a n + b$ are not the ordinates of some zero of $\zeta(s)$ lying on
the critical line. This improves on earlier work of Martin and Ng. We then
complement this result by producing large and small values of $\zeta(s)$ on
arithmetic progressions which are of the same quality as the best $\Omega$
results currently known for $\zeta(1/2 + it)$ with $t$ real.


  We investigate the quasinormal modes for gravitational perturbations of
rotating black holes in four dimensional Anti-de Sitter (AdS) spacetime. The
study of the quasinormal frequencies related to these modes is relevant to the
AdS/CFT correspondence. Although results have been obtained for Schwarzschild
and Reissner-Nordstrom AdS black holes, quasinormal frequencies of Kerr-AdS
black holes are computed for the first time. We solve the Teukolsky equations
in AdS spacetime, providing a second order and a Pade approximation for the
angular eigenvalues associated to the Teukolsky angular equation. The
transformation theory and the Regge-Wheeler-Zerilli equations for Kerr-AdS are
obtained.


  In this paper it is shown that the Brans - Dicke scalar field itself can
serve the purpose of providing an early deceleration and a late time
acceleration of the universe without any need of quintessence field if one
considers an interaction, i.e, transfer of energy between the dark matter and
the Brans - Dicke scalar field.


  Among all the partition based clustering algorithms K-means is the most
popular and well known method. It generally shows impressive results even in
considerably large data sets. The computational complexity of K-means does not
suffer from the size of the data set. The main disadvantage faced in performing
this clustering is that the selection of initial means. If the user does not
have adequate knowledge about the data set, it may lead to erroneous results.
The algorithm Automatic Initialization of Means (AIM), which is an extension to
K-means, has been proposed to overcome the problem of initial mean generation.
In this paper an attempt has been made to compare the performance of the
algorithms through implementation


  Using the Lyapunov-Schmidt reduction method, we describe how to use annular
domains to construct (scalar curvature) functions on S^n, (n > 5), so that each
one of them enables the conformal scalar curvature equation to have a
blowing-up sequence of positive solutions. The prescribed scalar curvature
function is shown to have C^{n - 1, \beta} smoothness.


  We study the geometry of the triplectic quantization of gauge theories. We
show that underlying the triplectic geometry is a Kaehler manifold N endowed
with a pair of transversal polarizations. The antibrackets can be brought to
the canonical form if and only if N admits a flat symmetric connection that is
compatible with the complex structure and the polarizations.


  We consider static, external memory indexes for exact and approximate
versions of the $k$-nearest neighbor ($k$-NN) problem, and show new lower
bounds under a standard indivisibility assumption:
  - Polynomial space indexing schemes for high-dimensional $k$-NN in Hamming
space cannot take advantage of block transfers: $\Omega(k)$ block reads are
needed to to answer a query.
  - For the $\ell_\infty$ metric the lower bound holds even if we allow
$c$-appoximate nearest neighbors to be returned, for $c \in (1, 3)$.
  - The restriction to $c < 3$ is necessary: For every metric there exists an
indexing scheme in the indexability model of Hellerstein et al.~using space
$O(kn)$, where $n$ is the number of points, that can retrieve $k$ 3-approximate
nearest neighbors using $\lceil k/B\rceil$ I/Os, which is optimal.
  - For specific metrics, data structures with better approximation factors are
possible. For $k$-NN in Hamming space and every approximation factor $c>1$
there exists a polynomial space data structure that returns $k$ $c$-approximate
nearest neighbors in $\lceil k/B\rceil$ I/Os.
  To show these lower bounds we develop two new techniques: First, to handle
that approximation algorithms have more freedom in deciding which result set to
return we develop a relaxed version of the $\lambda$-set workload technique of
Hellerstein et al. This technique allows us to show lower bounds that hold in
$d\geq n$ dimensions. To extend the lower bounds down to $d = O(k \log(n/k))$
dimensions, we develop a new deterministic dimension reduction technique that
may be of independent interest.


  We report on the evaluation of microwave frequency synthesis using two
cryogenic sapphire oscillators developed at the University of Western
Australia. A down converter is used to make comparisons between microwave
clocks at different frequencies, where the synthesized signal has a stability
not significantly different from the reference oscillator. By combining the CSO
with a H-maser, a reference source of arbitrary frequency at X-band can be
synthesized with a fractional frequency stability of sub-$4 \times 10^{-15}$
for integration times between 1 s and 10,000 s.


  We derive a simple expression for the tail-asymptotics of an explosive birth
process at a fixed observation time conditioned on non-explosion. Using the
well-established exponential embedding, we apply this result to compute the
tail distribution of the number of balls of a losing colour in generalized P
\'{o}lya urn models with super-linear feedback, which are known to exhibit a
strong monopoly for the winning colour where losers only win a finite amount.
Previous results in this direction were restricted to two colours with the same
feedback, which we extend to an arbitrary finite number of colours with
individual feedback mechanisms. As an apparent paradox, losing colours with
weak feedback are more likely to win in many steps than those with strong
feedback. Our approach also allows to characterize the correlations of several
losing colours, which provides new insight in the distribution of other related
quantities like the total number of balls for losing colours or the time to
monopoly. In order to give a complete picture, we also consider sub-linear
feedback and discuss asymptotics for a diverging number of colours.


  Let xi be a non-null countable ordinal. We study the Borel subsets of the
plane that can be made $\bormxi$ by refining the Polish topology on the real
line. These sets are called potentially $\bormxi$. We give a Hurewicz-like test
to recognize potentially $\bormxi$ sets.


  We study the small-mass (overdamped) limit of Langevin equations for a
particle in a potential and/or magnetic field with matrix-valued and
state-dependent drift and diffusion. We utilize a bootstrapping argument to
derive a hierarchy of approximate equations for the position degrees of freedom
that are able to achieve accuracy of order $m^{\ell/2}$ over compact time
intervals for any $\ell\in\mathbb{Z}^+$. This generalizes prior derivations of
the homogenized equation for the position degrees of freedom in the $m\to 0$
limit, which result in order $m^{1/2}$ approximations. Our results cover
bounded forces, for which we prove convergence in $L^p$ norms, and unbounded
forces, in which case we prove convergence in probability.


  Many natural systems undergo critical transitions, i.e. sudden shifts from
one dynamical regime to another. In the climate system, the atmospheric
boundary layer can experience sudden transitions between fully turbulent states
and quiescent, quasi-laminar states. Such rapid transitions are observed in
Polar regions or at night when the atmospheric boundary layer is stably
stratified, and they have important consequences in the strength of mixing with
the higher levels of the atmosphere. To analyze the stable boundary layer, many
approaches rely on the identification of regimes that are commonly denoted as
weakly and very stable regimes. Detecting transitions between the regimes is
crucial for modeling purposes. In this work a combination of methods from
dynamical systems and statistical modeling is applied to study these regime
transitions and to develop an early-warning signal that can be applied to
non-stationary field data. The presented metric aims at detecting nearing
transitions by statistically quantifying the deviation from the dynamics
expected when the system is close to a stable equilibrium. An idealized
stochastic model of near-surface inversions is used to evaluate the potential
of the metric as an indicator of regime transitions. In this stochastic system,
small-scale perturbations can be amplified due to the nonlinearity, resulting
in transitions between two possible equilibria of the temperature inversion.
The simulations show such noise-induced regime transitions, successfully
identified by the indicator. The indicator is further applied to time series
data from nocturnal and Polar meteorological measurements.


  This paper considers the two-species chemotaxis-Stokes system with
competitive kinetics under homogeneous Neumann boundary conditions in a
three-dimensional bounded domain with smooth boundary. Both chemotaxis-fluid
systems and two-species chemotaxis systems with competitive terms are studied
by many mathematicians. However, there has not been rich results on coupled
two-species-fluid systems. Recently, global existence and asymptotic stability
in this problem with convection term in the fluid equation of the above system
were established in the 2-dimensional case. The purpose of this paper is to
give results for global existence, boundedness and stabilization of solutions
to this system in the 3-dimensional case.


  Spectral singularities are predicted to occur in a non-Hermitian extension of
the Friedrichs-Fano-Anderson model describing the decay of a discrete state $|a
>$ coupled to a continuum of modes. A physical realization of the model, based
on electronic or photonic transport in a semi-infinite tight-binding lattice
with an imaginary impurity site at the lattice boundary, is proposed. The
occurrence of the spectral singularities is shown to correspond either to a
diverging reflection probability (for an amplifying impurity) or to a vanishing
reflection probability (for an absorbing impurity) from the lattice boundary.
In the former case, the spectral singularity of the resolvent is also
responsible for the non-decay of state $|a>$ into the continuum, in spite of
the absence of bound states.


  We formulate a parametrized uniformly absolutely globally convergent series
of $\zeta$(s) denoted by Z(s, x). When expressed in closed form, it is given by
Z(s, x) = (s -- 1)$\zeta$(s) + 1 x Li s z z -- 1 dz, where Li s (x) is the
polylogarithm function. As an immediate first application of the new
parametrized series, a new expression of $\zeta$(s) follows: (s -- 1)$\zeta$(s)
= -- 1 0 Li s z z -- 1 dz. As a second important application, using the
functional equation and exploiting uniform convergence of the series defining
Z(s, x), we have for any non-trivial zero s


  Strong coupling calculations for the glueball spectrum in an $AdS^7$ black
hole are modified by introducing an UV cut-off at a Planck brane. A new
normalizable state in the tensor spectrum is found which reproduces
Einstein-Hilbert gravity up to exponentially small corrections due to off shell
mixing with massive glueballs.


  The classic question of whether one should walk or run in the rain to remain
the least wet has inspired a myriad of solutions ranging from physically
performing test runs in raining conditions to mathematically modeling human
movement through rain. This manuscript approaches the classical problem by
simulating movement through rainfall using MATLAB. Our simulation was
generalizable to include snowfall as well. An increase in walking speed
resulted in a corresponding decrease in raindrop and snowflake collisions. When
raindrops or snowflakes were given a horizontal movement vector due to wind, a
local minimum in collisions was achieved when moving in parallel with the same
horizontal speed as the raindrop; no local minimum was detected with
antiparallel movement. In general, our simulation revealed that the faster one
moves, the drier one remains.


  Beam-target double-spin asymmetries and target single-spin asymmetries were
measured for the exclusive $\pi^+$ electroproduction reaction $\gamma^* p \to n
\pi^+$. The results were obtained from scattering of 6 GeV longitudinally
polarized electrons off longitudinally polarized protons using the CEBAF Large
Acceptance Spectrometer at Jefferson Lab. The kinematic range covered is
$1.1<W<3$ GeV and $1<Q^2<6$ GeV$^2$. Results were obtained for about 6000 bins
in $W$, $Q^2$, $\cos(\theta^*)$, and $\phi^*$. Except at forward angles, very
large target-spin asymmetries are observed over the entire $W$ region.
Reasonable agreement is found with phenomenological fits to previous data for
$W<1.6$ GeV, but very large differences are seen at higher values of $W$. A
GPD-based model is in poor agreement with the data. When combined with cross
section measurements, the present results provide powerful constraints on
nucleon resonance amplitudes at moderate and large values of $Q^2$, for
resonances with masses as high as 2.4 GeV.


  Techniques for procedural content generation via machine learning (PCGML)
have been shown to be useful for generating novel game content. While used
primarily for producing new content in the style of the game domain used for
training, recent works have increasingly started to explore methods for
discovering and generating content in novel domains via techniques such as
level blending and domain transfer. In this paper, we build on these works and
introduce a new PCGML approach for producing novel game content spanning
multiple domains. We use a new affordance and path vocabulary to encode data
from six different platformer games and train variational autoencoders on this
data, enabling us to capture the latent level space spanning all the domains
and generate new content with varying proportions of the different domains.


  We prove a tight and close-to-optimal lower bound on the effectiveness of
local quantum measurements (without classical communication) at discriminating
any two bipartite quantum states. Our result implies, for example, that any two
orthogonal quantum states of a $n_A\times n_B$ bipartite quantum system can be
discriminated via local measurements with an error probability no larger than
$\frac12 \left(1 - \frac{1}{c \min\{n_A, n_B\}} \right)$, where $1\leq c\leq
2\sqrt2$ is a universal constant, and our bound scales provably optimally with
the local dimensions $n_A,n_B$. Mathematically, this is achieved by showing
that the distinguishability norm $\|\cdot\|_{LO}$ associated with local
measurements satisfies that $\|\cdot\|_1\leq 2\sqrt2 \min\{n_A,n_B\}
\|\cdot\|_{LO}$, where $\|\cdot\|_1$ is the trace norm.


  An open resonator fabricated in a two-dimensional electron gas is used to
explore the transition from strongly invasive scanning gate microscopy to the
perturbative regime of weak tip-induced potentials. With the help of numerical
simulations that faithfully reproduce the main experimental findings, we
quantify the extent of the perturbative regime in which the tip-induced
conductance change is unambiguously determined by properties of the unperturbed
system. The correspondence between the experimental and numerical results is
established by analyzing the characteristic length scale and the amplitude
modulation of the conductance change. In the perturbative regime, the former is
shown to assume a disorder-dependent maximum value, while the latter linearly
increases with the strength of a weak tip potential.


  A search for heavy Majorana neutrinos in scattering of same-sign $W$ boson
pairs in proton-proton collisions at $\sqrt{s}= 13$ TeV at the LHC is reported.
The dataset used corresponds to an integrated luminosity of 140 fb$^{-1}$,
collected with the ATLAS detector during 2015-2018. The search is performed in
final states including a same-sign $ee$ or $e\mu$ pair and at least two jets
with large invariant mass and a large rapidity difference. No significant
excess of events with respect to the Standard Model background predictions is
observed. The results are interpreted in a benchmark scenario of the
Phenomenological Type-I Seesaw model. New constraints are set on the values of
the $\vert V_{e N} \vert^{2}$ and $\vert V_{e N} V^{*}_{\mu N} \vert$
parameters for heavy Majorana neutrino masses between 50 GeV and 20 TeV, where
$V_{\ell N}$ is the matrix element describing the mixing of the heavy Majorana
neutrino mass eigenstate with the Standard Model neutrino of flavour $\ell = e,
\mu$. The sensitivity to the Weinberg operator is investigated and constraints
on the effective $ee$ and $e\mu$ Majorana neutrino masses are reported. The
statistical combination of the $ee$ and $e\mu$ channels with the previously
published $\mu\mu$ channel is performed.


  Giant elliptical galaxies, believed to be built from the merger of lesser
galaxies, are known to house a massive black hole at their center rather than a
compact star cluster. If low- and intermediate-mass galaxies do indeed partake
in the hierarchical merger scenario, then one needs to explain why their dense
nuclear star clusters are not preserved in merger events. A valuable clue may
the recent revelation that nuclear star clusters and massive black holes
frequently co-exist in intermediate mass bulges and elliptical galaxies. In an
effort to understand the physical mechanism responsible for the disappearance
of nuclear star clusters, we have numerically investigated the evolution of
merging star clusters with seed black holes. Using black holes that are 1-5% of
their host nuclear cluster mass, we reveal how their binary coalescence during
a merger dynamically heats the newly wed star cluster, expanding it,
significantly lowering its central stellar density, and thus making it
susceptible to tidal destruction during galaxy merging. Moreover, this
mechanism provides a pathway to explain the observed reduction in the
nucleus-to-galaxy stellar mass ratio as one proceeds from dwarf to giant
elliptical galaxies.


  Let $G$ be a connected nilpotent Lie group. Given probability-preserving
$G$-actions $(X_i,\Sigma_i,\mu_i,u_i)$, $i=0,1,...,k$, and also polynomial maps
$\phi_i:\mathbb{R}\to G$, $i=1,...,k$, we consider the trajectory of a joining
$\lambda$ of the systems $(X_i,\Sigma_i,\mu_i,u_i)$ under the `off-diagonal'
flow
  \[(t,(x_0,x_1,x_2,...,x_k))\mapsto
(x_0,u_1^{\phi_1(t)}x_1,u_2^{\phi_2(t)}x_2,...,u_k^{\phi_k(t)}x_k).\]
  It is proved that any joining $\lambda$ is equidistributed under this flow
with respect to some limit joining $\lambda'$. This is deduced from the
stronger fact of norm convergence for a system of multiple ergodic averages,
related to those arising in Furstenberg's approach to the study of multiple
recurrence. It is also shown that the limit joining $\lambda'$ is invariant
under the subgroup of $G^{k+1}$ generated by the image of the off-diagonal
flow, in addition to the diagonal subgroup.


  We study in detail the model by Isidori and Kamenik that is claimed to
explain the top quark forward-backward asymmetry at Tevatron, provide GeV-scale
dark matter (DM), and possibly improve the agreement between data and theory in
Tevatron W+jj events. We compute the DM thermal relic density, the
spin-independent DM-nucleon scattering cross section, and the cosmic microwave
background constraints on both Dirac and Majorana neutralino DM in the
parameter space that explains the top asymmetry. A stable light neutralino is
not allowed unless the local DM density is 3-4 times smaller than expected, in
which case Dirac DM with mass around 3 GeV may be possible, to be tested by the
Planck mission. The model predicts a too broad excess in the dijet distribution
and a strong modification of the missing E_T distribution in W+jj events.


  In this paper, a diffuse-interface lattice Boltzmann method (DI-LBM) is
developed for fluid-particle interaction problems. In this method, the sharp
interface between the fluid and solid is replaced by a thin but nonzero
thickness transition region named diffuse interface, where the physical
variables varies continuously. In order to describe the diffuse interface, we
introduce a smooth function, which is similar to the order parameter in
phase-field model or the volume fraction of solid phase in the partially
saturated lattice Boltzmann method (PS-LBM). In addition, to depict the
fluid-particle interaction more accurately, a modified force term is also
proposed and included in the evolution equation of the DI-LBM. Some classical
problems are used to test the DI-LBM, and the results are in good agreement
with some available theoretical and numerical works. Finally, it is also found
that the DI-LBM is more efficient and accurate than the PS-LBM with the
superposition model.


  We consider the implications of the condensation of a general local BRST
invariant dimension two operator built out of the localizing ghost fields of
the Gribov-Zwanziger Lagrangian which is a localized Lagrangian incorporating
the Gribov problem in the Landau gauge. For different colour tensor projections
of the general operator, the properties of a frozen gluon propagator and
unenhanced Faddeev-Popov ghost propagator, which are observed in lattice
computations, can be reproduced. The alternative possibilities are
distinguished by the infrared structure of the propagators of the spin-1
fields, other than those of the gluon and Faddeev-Popov ghost, for which there
is no numerical simulation data to compare with yet.


  The idea is advanced that strong perturbations of an initially equilibrium
Bose-condensed gas lead to the sequence of nonequilibrium states whose order is
inverse to the sequence of states arising in the process of the Bose-gas
relaxation from an initial nonequilibrium state. An approach is described for
constructing statistical models of nonequilibrium Bose gases. The method is
based on the averaging over heterogenous configurations of a nonequilibrium
system. A statistical model of grain turbulence is suggested. A simple model is
analyzed consisting of a mixture of two phases, one gauge symmetric and the
other with broken gauge symmetry.


  In this letter, we present a unified result for the stable recovery bound of
Lq(0 < q < 1) optimization model in compressed sensing, which is a constrained
Lq minimization problem aware of the noise in a linear system. Specifically,
without using the restricted isometry constant (RIC), we show that the error
between any global solution of the noise-aware Lq optimization model and the
ideal sparse solution of the noiseless model is upper bounded by a constant
times the noise level,given that the sparsity of the ideal solution is smaller
than a certain number. An interesting parameter {gamma} is introduced, which
indicates the sparsity level of the error vector and plays an important role in
our analysis. In addition, we show that when {\gamma} > 2, the recovery bound
of the Lq (0 < q < 1) model is smaller than that of the L1 model, and the
sparsity requirement of the ideal solution in the Lq(0 < q < 1) model is weaker
than that of the L1 model.


  Integrated sensing and communication (ISAC) is an encouraging wireless
technology which can simultaneously perform both radar and communication
functionalities by sharing the same transmit waveform, spectral resource, and
hardware platform. Recently emerged symbol-level precoding (SLP) technique
exhibits advancement in ISAC systems by leveraging the waveform design degrees
of freedom (DoFs) in both temporal and spatial domains. However, traditional
SLP-based ISAC systems are designed in a modular paradigm, which potentially
limits the overall performance of communication and radar sensing. The high
complexity of existing SLP design algorithms is another issue that hurdles the
practical deployment. To break through the bottleneck of these approaches, in
this paper we propose an end-to-end approach to jointly design the SLP-based
dual-functional transmitter and receivers of communication and radar sensing.
In particular, we aim to utilize deep learning-based methods to minimize the
symbol error rate (SER) of communication users, maximize the detection
probability, and minimize the root mean square error (RMSE) of the target angle
estimation. Multi-layer perceptron (MLP) networks and a long short term memory
(LSTM) network are respectively applied to the transmitter, communication users
and radar receiver. Simulation results verify the feasibility of the proposed
deep-learning-based end-to-end optimization for ISAC systems and reveal the
effectiveness of the proposed neural networks for the end-to-end design.


  In continuation of previous work, numerical results are presented, concerning
relativistically counter-streaming plasmas. Here, the relativistic mixed mode
instability evolves through, and beyond, the linear saturation -- well into the
nonlinear regime. Besides confirming earlier findings, that wave power
initially peaks on the mixed mode branch, it is observed that, during late time
evolution wave power is transferred to other wave numbers. It is argued that
the isotropization of power in wavenumber space may be a consequence of weak
turbulence. Further, some modifications to the ideal weak turbulence limit is
observed. Development of almost isotropic predominantly electrostatic --
partially electromagnetic -- turbulent spectra holds relevance when considering
the spectral emission signatures of the plasma, namely bremsstrahlung,
respectively magneto-bremsstrahlung (synchrotron radiation and jitter
radiation) from relativistic shocks in astrophysical jets and shocks from
gamma-ray bursts and active galactic nuclei.


  Self-supervised learning has unlocked the potential of scaling up pretraining
to billions of images, since annotation is unnecessary. But are we making the
best use of data? How more economical can we be? In this work, we attempt to
answer this question by making two contributions. First, we investigate
first-person videos and introduce a "Walking Tours" dataset. These videos are
high-resolution, hours-long, captured in a single uninterrupted take, depicting
a large number of objects and actions with natural scene transitions. They are
unlabeled and uncurated, thus realistic for self-supervision and comparable
with human learning.
  Second, we introduce a novel self-supervised image pretraining method
tailored for learning from continuous videos. Existing methods typically adapt
image-based pretraining approaches to incorporate more frames. Instead, we
advocate a "tracking to learn to recognize" approach. Our method called DoRA,
leads to attention maps that Discover and tRAck objects over time in an
end-to-end manner, using transformer cross-attention. We derive multiple views
from the tracks and use them in a classical self-supervised distillation loss.
Using our novel approach, a single Walking Tours video remarkably becomes a
strong competitor to ImageNet for several image and video downstream tasks.


  The $\Xi N$ interaction plays an important role in our understanding on the
long-anticipated $H$-dibaryon. Recent lattice QCD calculations verified the
attractive nature of the $\Xi N$ interaction. On the other hand, whether it is
strong enough to generate a bound state remains inconclusive.In this work,
assuming that it can generate a weakly bound state, we study the yields of the
$\Xi N$ dibaryon for different binding energies in $pp$ collisions at 7 TeV
using the coalescence model and the transport model PACIAE. The yields are
estimated first numerically and then analytically adopting a Yukawa-type wave
function. In particular, we find that in the weak binding limit, there exists a
universal relation between the yield and the binding energy, valid for $pp$
collisions.


  A major problem of causal inference is the arrangement of dependent nodes in
a directed acyclic graph (DAG) with path coefficients and observed confounders.
Path coefficients do not provide the units to measure the strength of
information flowing from one node to the other. Here we proposed the method of
causal structure learning using collider v-structures (CVS) with Negative
Percentage Mapping (NPM) to get selective thresholds of information strength,
to direct the edges and subjective confounders in a DAG. The NPM is used to
scale the strength of information passed through nodes in units of percentage
from interval from 0 to 1. The causal structures are constructed by bottom up
approach using path coefficients, causal directions and confounders, derived
implementing collider v-structure and NPM. The method is self-sufficient to
observe all the latent confounders present in the causal model and capable of
detecting every responsible causal direction. The results are tested for
simulated datasets of non-Gaussian distributions and compared with DirectLiNGAM
and ICA-LiNGAM to check efficiency of the proposed method.


  The diffusive epidemic process is a paradigmatic example of an absorbing
state phase transition in which healthy and infected individuals spread with
different diffusion constants. Using stochastic activity spreading simulations
in combination with finite-size scaling analyses we reveal two qualitatively
different processes that characterize the critical dynamics: subdiffusive
propagation of infection clusters and diffusive fluctuations in the healthy
population. This suggests the presence of a strong-coupling regime and sheds
new light on a longstanding debate about the theoretical classification of the
system.


  In this note we show that Lorentzian Concircular Structure manifolds (LCS)_n
coincide with Generalized Robertson-Walker space-times.


  We have derived a closed form analytic expression for the asymptotic motion
of a pair of identical ions in a high precision Penning trap. The analytic
solution includes the effects of special relativity and the Coulomb interaction
between the ions. The existence and physical relevance of such a final state is
supported by a confluence of theoretical, experimental and numerical evidence.


  Matter qubit to traveling photonic qubit conversion is the cornerstone of
numerous quantum technologies such as distributed quantum computing, as well as
several quantum internet and networking protocols. We formulate a theory for
stimulated Raman emission which is applicable to a wide range of physical
systems including quantum dots, solid state defects, and trapped ions, as well
as various parameter regimes. We find the upper bound for the photonic pulse
emission efficiency of arbitrary matter qubit states for imperfect emitters and
show a path forward to optimizing the fidelity. Based on these results we
propose a paradigm shift from optimizing the drive to directly optimizing the
temporal mode of the flying qubit using a closed-form expression. Protocols for
the production of time-bin encoding and spin-photon entanglement are proposed.
Furthermore, the mathematical idea to use input-output theory for pulses to
absorb the dominant emission process into the coherent dynamics, followed by a
non-Hermitian Schr\"odinger equation approach has great potential for studying
other physical systems.


  We propose a novel Text-to-Image Generation Network, Adaptive Layout
Refinement Generative Adversarial Network (ALR-GAN), to adaptively refine the
layout of synthesized images without any auxiliary information. The ALR-GAN
includes an Adaptive Layout Refinement (ALR) module and a Layout Visual
Refinement (LVR) loss. The ALR module aligns the layout structure (which refers
to locations of objects and background) of a synthesized image with that of its
corresponding real image. In ALR module, we proposed an Adaptive Layout
Refinement (ALR) loss to balance the matching of hard and easy features, for
more efficient layout structure matching. Based on the refined layout
structure, the LVR loss further refines the visual representation within the
layout area. Experimental results on two widely-used datasets show that ALR-GAN
performs competitively at the Text-to-Image generation task.


  Exactly estimating and tracking the motion of surrounding dynamic objects is
one of important tasks for the autonomy of a quadruped manipulator. However,
with only an onboard RGB camera, it is still a challenging work for a quadruped
manipulator to track the motion of a dynamic object moving with unknown and
changing velocities. To address this problem, this manuscript proposes a novel
image-based visual servoing (IBVS) approach consisting of three elements: a
spherical projection model, a robust super-twisting observer, and a model
predictive controller (MPC). The spherical projection model decouples the
visual error of the dynamic target into linear and angular ones. Then, with the
presence of the visual error, the robustness of the observer is exploited to
estimate the unknown and changing velocities of the dynamic target without
depth estimation. Finally, the estimated velocity is fed into the model
predictive controller (MPC) to generate joint torques for the quadruped
manipulator to track the motion of the dynamical target. The proposed approach
is validated through hardware experiments and the experimental results
illustrate the approach's effectiveness in improving the autonomy of the
quadruped manipulator.


  Using a nonlocal version of the center manifold theorem and a normal form
reduction, we prove the existence of small-amplitude generalized solitary-wave
solutions and modulated solitary-wave solutions to the steady gravity-capillary
Whitham equation with weak surface tension. Through the application of the
center manifold theorem, the nonlocal equation for the solitary wave profiles
is reduced to a four-dimensional system of ODEs inheriting reversibility. Along
particular parameter curves, relating directly to the classical
gravity-capillary water wave problem, the associated linear operator is seen to
undergo either a reversible $0^{2+}(i k_0)$ bifurcation or a reversible $(i
s)^2$ bifurcation. Through a normal form transformation, the reduced system of
ODEs along each relevant parameter curve is seen to be well approximated by a
truncated system retaining only second-order or third-order terms. These
truncated systems relate directly to systems obtained in the study of the full
gravity-capillary water wave equation and, as such, the existence of
generalized and modulated solitary waves for the truncated systems is
guaranteed by classical works, and they are readily seen to persist as
solutions of the gravity-capillary Whitham equation due to reversibility.
Consequently, this work illuminates further connections between the
gravity-capillary Whitham equation and the full two-dimensional
gravity-capillary water wave problem.


  Understanding gluon density distributions and how they are modified in nuclei
are among the most important goals in nuclear physics. In recent years,
diffractive vector meson production measured in ultra-peripheral collisions
(UPCs) at heavy-ion colliders has provided a new tool for probing the gluon
density. In this Letter, we report the first measurement of $J/\psi$
photoproduction off the deuteron in UPCs at the center-of-mass energy
$\sqrt{s_{_{\rm NN}}}=200~\rm GeV$ in d$+$Au collisions. The differential cross
section as a function of momentum transfer $-t$ is measured. In addition, data
with a neutron tagged in the deuteron-going Zero-Degree Calorimeter is
investigated for the first time, which is found to be consistent with the
expectation of incoherent diffractive scattering at low momentum transfer.
Theoretical predictions based on the Color Glass Condensate saturation model
and the gluon shadowing model are compared with the data quantitatively. A
better agreement with the saturation model has been observed. With the current
measurement, the results are found to be directly sensitive to the gluon
density distribution of the deuteron and the deuteron breakup, which provides
insights into the nuclear gluonic structure.


  In the seminal contribution [4] the joint weak convergence of maxima and
minima of weakly dependent stationary sequences is derived under some mild
asymptotic conditions. In this paper we address additionally the case of
incomplete samples assuming that the average proportion of incompleteness
converges in probability to some random variable. We show the joint weak
convergence of the maxima and minima of both complete and incomplete samples.
It turns out that for special cases, maxima and minima are asymptotically
independent.


  The purpose of this paper is to give an explicit formula of the
{\L}ojasiewicz exponent of an isolated weighted homogeneous singularity in
terms of its weights.


  We establish a theory of complexes of relative correspondences. The theory
generalizes the known theory of complexes of correspondences of smooth
projective varieties. It will be applied in the sequel of this paper to the
construction of the triangulated category of motives over a base variety.


  Umbral flashes are sudden brightenings commonly visible in the core of
chromospheric lines. Theoretical and numerical modeling suggest that they are
produced by the propagation of shock waves. According to these models and early
observations, umbral flashes are associated with upflows. However, recent
studies have reported umbral flashes in downflowing atmospheres. We aim to
understand the origin of downflowing umbral flashes. We explore how the
existence of standing waves in the umbral chromosphere impacts the generation
of flashed profiles. We performed numerical simulations of wave propagation in
a sunspot umbra with the code MANCHA. The Stokes profiles of the Ca II 8542
\AA\ line were synthesized with NICOLE. For freely-propagating waves, the
chromospheric temperature enhancements of the oscillations are in phase with
velocity upflows. In this case, the intensity core of the Ca II 8542 \AA\
atmosphere is heated during the upflowing stage of the oscillation. If we
consider a different scenario with a resonant cavity, the wave reflections at
the sharp temperature gradient of the transition region lead to standing
oscillations. In this situation, temperature fluctuations are shifted backward
and temperature enhancements partially coincide with the downflowing stage of
the oscillation. In umbral flashes produced by standing oscillations, the
reversal of the emission feature is produced when the oscillation is
downflowing. The chromospheric temperature keeps increasing while the
atmosphere is changing from a downflow to an upflow. During the appearance of
flashed Ca II 8542 \AA\ cores, the atmosphere is upflowing most of the time,
and only 38\% of the flashed profiles are associated with downflows. We find a
scenario that remarkably explains the recent empirical findings of downflowing
umbral flashes as a natural consequence of the presence of standing
oscillations above sunspot umbrae.


  In the present note we introduce a new solution of this equation, lead- ing
to a new integrable system with a quartic integral, which involves 16 free
parameters. A special case of the new system admits interpretation in a problem
of rigid body dynamics. It gives a new integrable variation of the cases due to
Kovalevskaya (1889), Chaplygin (1903) Goriatchev (1916) and Yehia (2006).


  We propose an adaptive variance-reduction method, called AdaSpider, for
minimization of $L$-smooth, non-convex functions with a finite-sum structure.
In essence, AdaSpider combines an AdaGrad-inspired [Duchi et al., 2011, McMahan
& Streeter, 2010], but a fairly distinct, adaptive step-size schedule with the
recursive stochastic path integrated estimator proposed in [Fang et al., 2018].
To our knowledge, Adaspider is the first parameter-free non-convex
variance-reduction method in the sense that it does not require the knowledge
of problem-dependent parameters, such as smoothness constant $L$, target
accuracy $\epsilon$ or any bound on gradient norms. In doing so, we are able to
compute an $\epsilon$-stationary point with $\tilde{O}\left(n +
\sqrt{n}/\epsilon^2\right)$ oracle-calls, which matches the respective lower
bound up to logarithmic factors.


  We present a data-driven verification approach that determines whether or not
a given chemical reaction network (CRN) satisfies a given property, expressed
as a formula in a modal logic. Our approach consists of three phases,
integrating formal verification over models with learning from data. First, we
consider a parametric set of possible models based on a known stoichiometry and
classify them against the property of interest. Secondly, we utilise Bayesian
inference to update a probability distribution of the parameters within a
parametric model with data gathered from the underlying CRN. In the third and
final stage, we combine the results of both steps to compute the probability
that the underlying CRN satisfies the given property. We apply the new approach
to a case study and compare it to Bayesian statistical model checking.


  In this paper, we show that if $X$ is a smooth variety of general type of
dimension $m \geq 3$ for which the canonical map induces a triple cover onto
$Y$, where $Y$ is a projective bundle over $\mathbf P^1$ or onto a projective
space or onto a quadric hypersurface, embedded by a complete linear series,
then the general deformation of the canonical morphism of $X$ is again
canonical and induces a triple cover. The extremal case when $Y$ is embedded as
a variety of minimal degree is of interest, due to its appearance in numerous
situations. This is especially interesting as well, since it has no lower
dimensional analogues.


  Multi-view crowd counting has been previously proposed to utilize
multi-cameras to extend the field-of-view of a single camera, capturing more
people in the scene, and improve counting performance for occluded people or
those in low resolution. However, the current multi-view paradigm trains and
tests on the same single scene and camera-views, which limits its practical
application. In this paper, we propose a cross-view cross-scene (CVCS)
multi-view crowd counting paradigm, where the training and testing occur on
different scenes with arbitrary camera layouts. To dynamically handle the
challenge of optimal view fusion under scene and camera layout change and
non-correspondence noise due to camera calibration errors or erroneous
features, we propose a CVCS model that attentively selects and fuses multiple
views together using camera layout geometry, and a noise view regularization
method to train the model to handle non-correspondence errors. We also generate
a large synthetic multi-camera crowd counting dataset with a large number of
scenes and camera views to capture many possible variations, which avoids the
difficulty of collecting and annotating such a large real dataset. We then test
our trained CVCS model on real multi-view counting datasets, by using
unsupervised domain transfer. The proposed CVCS model trained on synthetic data
outperforms the same model trained only on real data, and achieves promising
performance compared to fully supervised methods that train and test on the
same single scene.


  In this paper, we present a rotating de Rham-Gabadadze-Tolley black hole with
a positive cosmological constant in massive gravity, achieved by applying a
modified Newman-Janis algorithm. The black hole exhibits stable orbits of
constant radii, prompting a numerical study on the behavior of the solutions to
a nonic equation governing the radii of planar orbits around the black hole.
Additionally, we investigate the stability of orbits near the event horizon and
provide a comprehensive analytical examination of the solutions to the angular
equations of motion. This is followed by simulating some spherical particle
orbits around the black hole.


  First LHC data have been collected and collisions at a center-of-mass energy
of 7 TeV are anticipated for the next months. The commissioning of the
detectors and the re-establishment of the Standard Model in the new energy
regime will be the main tasks for the experimental collaborations in the year
to come. This report summarizes the measurement plans and performance
expectations of the ATLAS and CMS experiments for a selected number of QCD and
electroweak analyses with an emphasis on the early data taking phase. Some
longer term prospects are pointed out.


  In this paper, we present a probabilistic study of rare phenomena of the
cubic nonlinear Schr\"odinger equation on the torus in a weakly nonlinear
setting. This equation has been used as a model to numerically study the
formation of rogue waves in deep sea. Our results are twofold: first, we
introduce a notion of criticality and prove a Large Deviations Principle (LDP)
for the subcritical and critical cases. Second, we study the most likely
initial conditions that lead to the formation of a rogue wave, from a
theoretical and numerical point of view. Finally, we propose several open
questions for future research.


  We present a framework combining hierarchical and multi-agent deep
reinforcement learning approaches to solve coordination problems among a
multitude of agents using a semi-decentralized model. The framework extends the
multi-agent learning setup by introducing a meta-controller that guides the
communication between agent pairs, enabling agents to focus on communicating
with only one other agent at any step. This hierarchical decomposition of the
task allows for efficient exploration to learn policies that identify globally
optimal solutions even as the number of collaborating agents increases. We show
promising initial experimental results on a simulated distributed scheduling
problem.