  The number of measurements demanded by hybrid quantum-classical algorithms
such as the variational quantum eigensolver (VQE) is prohibitively high for
many problems of practical value. For such problems, realizing quantum
advantage will require methods which dramatically reduce this cost. Previous
quantum algorithms that reduce the measurement cost (e.g. quantum amplitude and
phase estimation) require error rates that are too low for near-term
implementation. Here we propose methods that take advantage of the available
quantum coherence to maximally enhance the power of sampling on noisy quantum
devices, reducing measurement number and runtime compared to the standard
sampling method of the variational quantum eigensolver (VQE). Our scheme
derives inspiration from quantum metrology, phase estimation, and the more
recent "alpha-VQE" proposal, arriving at a general formulation that is robust
to error and does not require ancilla qubits. The central object of this method
is what we call the "engineered likelihood function" (ELF), used for carrying
out Bayesian inference. We show how the ELF formalism enhances the rate of
information gain in sampling as the physical hardware transitions from the
regime of noisy intermediate-scale quantum computers into that of quantum error
corrected ones. This technique speeds up a central component of many quantum
algorithms, with applications including chemistry, materials, finance, and
beyond. Similar to VQE, we expect small-scale implementations to be realizable
on today's quantum devices.


  In this paper we consider a class of connected closed $G$-manifolds with a
non-empty finite fixed point set, each $M$ of which is totally non-homologous
to zero in $M_G$ (or $G$-equivariantly formal), where $G={\Bbb Z}_2$. With the
help of the equivariant index, we give an explicit description of the
equivariant cohomology of such a $G$-manifold in terms of algebra, so that we
can obtain analytic descriptions of ring isomorphisms among equivariant
cohomology rings of such $G$-manifolds, and a necessary and sufficient
condition that the equivariant cohomology rings of such two $G$-manifolds are
isomorphic. This also leads us to analyze how many there are equivariant
cohomology rings up to isomorphism for such $G$-manifolds in 2- and
3-dimensional cases.


  We present a general scheme for performing a simulation of the dynamics of
one quantum system using another. This scheme is used to experimentally
simulate the dynamics of truncated quantum harmonic and anharmonic oscillators
using nuclear magnetic resonance. We believe this to be the first explicit
physical realization of such a simulation.


  Noise measurements of heated axisymmetric jets at fixed supersonic acoustic
Mach number indicate that the acoustic spectrum reduces when the temperature
ratio increases. The `spectral quietening' effect has been observed both
experimentally and computationally using Large Eddy Simulations (LES). It was
explained by Afsar {\it et al}. (M. Z. Afsar and M. E. Goldstein $\&$ A. M.
Fagan AIAAJ., Vol. 49, p. 2522, 2011) through the cancellation introduced by
enthalpy flux/momentum flux coupling term using the generalized acoustic
analogy formulation. But the parallel flow assumption is known to give
inaccurate predictions at high jet speeds. In this paper we therefore extend
the non-parallel flow asymptotic theory of Goldstein {\it et al}. (M. E.
Goldstein, A. Sescu $\&$ M. Z. Afsar, J. Fluid Mech., Vol. 695, p. 199, 2012)
for the vector Green's function of the adjoint linearized Euler equations
(ALEE) in the analogy. Using a steady Reynolds Averaged Navier Stokes (RANS)
calculation for the jet mean flow, we find that the coupling term propagator is
positive-definite and asymptotically sub-dominant at low frequencies
corresponding to the peak jet noise when non-parallel flow effects are taken
into account and self-consistent approximations for the turbulence structure
are made. The validity of the non-parallel flow-based acoustic analogy model is
assessed at various observation angles by computing the overall sound pressure
level (OASPL) and use this to suggest a more rational explanation of the
quietening effect. In general, our noise predictions are in very good agreement
with acoustic data beyond the peak frequency.


  Phonons, the ubiquitous quanta of vibrational energy, play a vital role in
the performance of quantum technologies. Conversely, unintended coupling to
phonons degrades qubit performance and can lead to correlated errors in
superconducting qubit systems. Regardless of whether phonons play an enabling
or deleterious role, they do not typically admit control over their spectral
properties, nor the possibility of engineering their dissipation to be used as
a resource. Here we show that coupling a superconducting qubit to a bath of
piezoelectric surface acoustic wave phonons enables a novel platform for
investigating open quantum systems. By shaping the loss spectrum of the qubit
via the bath of lossy surface phonons, we demonstrate preparation and dynamical
stabilization of superposition states through the combined effects of drive and
dissipation. These experiments highlight the versatility of engineered phononic
dissipation and advance the understanding of mechanical losses in
superconducting qubit systems.


  The Telescope Array experiment has recently reported the most energetic event
detected in the hybrid technique era, with a reconstructed energy of 240 EeV,
which has been named "Amaterasu" after the Shinto deity. Its origin is
intriguing since no powerful enough candidate sources are located within the
region consistent with its propagation horizon and arrival direction. In this
work, we investigate the possibility of describing its origin in a scenario of
new physics, specifically under a Lorentz Invariance Violation (LIV)
assumption. The kinematics of UHECR propagation under a phenomenological LIV
approach is investigated. The total mean free path for a particle with
Amaterasu's energy increases from a few Mpc to hundreds of Mpc for
$-\delta_{\rm{had},0} > 10^{-22}$, expanding significantly the region from
which it could have originated. A combined fit of the spectrum and composition
data of Telescope Array under different LIV assumptions was performed. The data
is best fitted with some level of LIV both with and without Amaterasu. The
improvement of the LIV fit is larger when Amaterasu is considered. New physics
in the form of LIV could, thus, provide a plausible explanation for the
Amaterasu particle.


  In these conference proceedings, I describe recent developments in the study
of thermalization dynamics in strongly, but not infinitely strongly coupled
field theories using holography. After reviewing the main tools required in
these calculations, I introduce a set of central results, discuss their
physical implications, and finally outline a number of challenges to be tackled
in the future.


  For every CR-manifold germ (M,a) local tube realizations are characterized by
certain abelian subalgebras of the real Lie algebra hol(M,a) of all germs of
(real-analytic) infinitesimal transformations. For instance, if M is
holomorphically non-degenerate, every such subalgebra is maximal abelian and
the classification of all local tube realizations for (M,a) reduces to a purely
algebraic problem.


  This review covers four current questions in the behavior of the atomic and
molecular interstellar medium. These include whether the atomic gas originates
primarily in cold streams or hot flows onto galaxies; what the filling factor
of cold gas actually is in galactic regions observationally determined to be
completely molecular; whether molecular hydrogen determines or merely traces
star formation; and whether gravity or turbulence drives the dynamical motions
observed in interstellar clouds, with implications on their star formation
properties.


  We present the easy-to-use, publicly available, Python package petitRADTRANS,
built for the spectral characterization of exoplanet atmospheres. The code is
fast, accurate, and versatile; it can calculate both transmission and emission
spectra within a few seconds at low resolution ($\lambda/\Delta\lambda$ = 1000;
correlated-k method) and high resolution ($\lambda/\Delta\lambda = 10^6$;
line-by-line method), using only a few lines of input instruction. The somewhat
slower correlated-k method is used at low resolution because it is more
accurate than methods such as opacity sampling. Clouds can be included and
treated using wavelength-dependent power law opacities, or by using optical
constants of real condensates, specifying either the cloud particle size, or
the atmospheric mixing and particle settling strength. Opacities of amorphous
or crystalline, spherical or irregularly-shaped cloud particles are available.
The line opacity database spans temperatures between 80 and 3000 K, allowing to
model fluxes of objects such as terrestrial planets, super-Earths, Neptunes, or
hot Jupiters, if their atmospheres are hydrogen-dominated. Higher temperature
points and species will be added in the future, allowing to also model the
class of ultra hot-Jupiters, with equilibrium temperatures $T_{\rm eq} \gtrsim
2000$ K. Radiative transfer results were tested by cross-verifying the low- and
high-resolution implementation of petitRADTRANS, and benchmarked with the
petitCODE, which itself is also benchmarked to the ATMO and Exo-REM codes. We
successfully carried out test retrievals of synthetic JWST emission and
transmission spectra (for the hot Jupiter TrES-4b, which has a $T_{\rm eq}$ of
$\sim$ 1800 K). The code is publicly available at
http://gitlab.com/mauricemolli/petitRADTRANS, and its documentation can be
found at https://petitradtrans.readthedocs.io.


  Recently was reported a novel compound between rhenium and nitrogen,
announced with ReN2 composition. This compound was synthesized by the high
temperature and high pressure method. We found that the diffraction peaks of
this compound are in agreement with the x-ray pattern of a rhenium-nitrogen
film, under the assumption that the film is oriented on the substrate. The film
was prepared by reactive magnetron sputtering, at room temperature, and
deposited on a silicon wafer. From the analysis of the diffractograms it could
be concluded that both materials share the same structure. By density
functional calculation was found that the composition could be ReN3, instead of
ReN2, as stated before. The ReN3 fits in the Ama2 (40) orthorhombic space
group, and by the existence of N3 anions it should be categorized as an azide;
that is, a nitrogen-rich compound. To reach high nitrogen concentrations by
sputtering a crucial step is the target-poisoning. Under this regime of
deposition is ensured that the compound is formed simultaneously on the
substrate and the target. The poisoned target is rarely used because of a
reduced sputtering yield, but as shall see, it can be used as a novel synthetic
technique.


  We study the movement of the living organism in a band form towards the
presence of chemical substrates based on a system of partial differential
evolution equations. We incorporate Einstein's method of Brownian motion to
deduce the chemotactic model exhibiting a traveling band. It is the first time
that Einstein's method has been used to motivate equations describing the
mutual interaction of the chemotactic system. We have shown that in the
presence of limited and unlimited substrate, traveling bands are achievable and
it has been explained accordingly. We also study the stability of the constant
steady states for the system. The linearized system about a constant steady
state is obtained under the mixed Dirichlet and Neumann boundary conditions. We
are able to find explicit conditions for linear instability. The linear
stability is established with respect to the L-2 norm, H1-norm, and L-infinity
norm under certain conditions.


  We investigate numerically and theoretically the effect of spatial disorder
on two-dimensional split-step discrete-time quantum walks with two internal
"coin" states. Spatial disorder can lead to Anderson localization, inhibiting
the spread of quantum walks, putting them at a disadvantage against their
diffusively spreading classical counterparts. We find that spatial disorder of
the most general type, i.e., position-dependent Haar random coin operators,
does not lead to Anderson localization but to a diffusive spread instead. This
is a delocalization, which happens because disorder places the quantum walk to
a critical point between different anomalous Floquet-Anderson insulating
topological phases. We base this explanation on the relationship of this
general quantum walk to a simpler case more studied in the literature and for
which disorder-induced delocalization of a topological origin has been
observed. We review topological delocalization for the simpler quantum walk,
using time evolution of the wave functions and level spacing statistics. We
apply scattering theory to two-dimensional quantum walks and thus calculate the
topological invariants of disordered quantum walks, substantiating the
topological interpretation of the delocalization and finding signatures of the
delocalization in the finite-size scaling of transmission. We show criticality
of the Haar random quantum walk by calculating the critical exponent $\eta$ in
three different ways and find $\eta$ $\approx$ 0.52 as in the integer quantum
Hall effect. Our results showcase how theoretical ideas and numerical tools
from solid-state physics can help us understand spatially random quantum walks.


  The stochastic Landau--Lifshitz--Gilbert (LLG) equation coupled with the
Maxwell equations (the so called stochastic MLLG system) describes the creation
of domain walls and vortices (fundamental objects for the novel nanostructured
magnetic memories). We first reformulate the stochastic LLG equation into an
equation with time-differentiable solutions. We then propose a convergent
$\theta$-linear scheme to approximate the solutions of the reformulated system.
As a consequence, we prove convergence of the approximate solutions, with no or
minor conditions on time and space steps (depending on the value of $\theta$).
Hence, we prove the existence of weak martingale solutions of the stochastic
MLLG system. Numerical results are presented to show applicability of the
method.


  We perform numerical calculations of masses and decay constants of the
lightest (flavoured) pseudoscalar, vector and axial vector mesons in the
$Sp(4)$ lattice gauge theory with three Dirac fermions in the antisymmetric
representation. The corresponding continuum theory plays an important role in
certain ultra-violet complete realisations of composite Higgs, partial top
compositeness, and composite dark matter models. In addition, we measure the
masses of other flavoured mesons in spin-$0$ and $1$ channels, as well as the
first excited state of the vector mesons. Using the gradient flow to set the
scale, we carry out the continuum extrapolation and show preliminary results
for the meson spectrum of the theory.


  We examine a small prominence eruption that occurred on 2014 May 1 at 01:35
UT and was observed by the Interface Region Imaging Spectrometer (IRIS) and the
Atmospheric Imaging Assembly (AIA) on the Solar Dynamics Observatory (SDO).
Pre- and post-eruption images were taken by the X-Ray Telescope (XRT) on
Hinode. Pre-eruption, a dome-like structure exists above the prominence, as
demarcated by coronal rain. As the eruption progresses, we find evidence for
reconnection between the prominence magnetic field and the overlying field.
Fast flows are seen in AIA and IRIS, indicating reconnection outflows.
Plane-of-sky flows of ~300 km s$^{-1}$ are observed in the AIA 171 A channel
along a potentially reconnected field line. IRIS detects intermittent fast
line-of-sight flows of ~200 km s$^{-1}$ coincident with the AIA flows.
Differential emission measure calculations show heating at the origin of the
fast flows. Post-eruption XRT images show hot loops probably due to
reconfiguration of magnetic fields during the eruption and subsequent heating
of plasma in these loops. Although there is evidence for reconnection above the
prominence during the eruption, high spatial resolution images from IRIS reveal
potential reconnection sites below the prominence. A height-time analysis of
the erupting prominence shows a slow initial rise with a velocity of ~0.4 km
s$^{-1}$ followed by a rapid acceleration with a final velocity of ~250 km
s$^{-1}$. Brightenings in IRIS during the transition between these two phases
indicate the eruption trigger for the fast part of the eruption is likely a
tether-cutting mechanism rather than a break-out mechanism.


  We measure the mean free path ($\lambda_{\rm mfp,HI}$), photo-ionization rate
($\langle \Gamma_{\rm HI} \rangle$) and neutral fraction ($\langle f_{\rm HI}
\rangle$) of hydrogen in 12 redshift bins at $4.85<z<6.05$ from a large sample
of moderate resolution XShooter and ESI QSO absorption spectra. The
fluctuations in ionizing radiation field are modeled by post-processing
simulations from the Sherwood suite using our new code "EXtended reionization
based on the Code for Ionization and Temperature Evolution" (EX-CITE). EX-CITE
uses efficient Octree summation for computing intergalactic medium attenuation
and can generate large number of high resolution $\Gamma_{\rm HI}$ fluctuation
models. Our simulation with EX-CITE shows remarkable agreement with simulations
performed with the radiative transfer code Aton and can recover the simulated
parameters within $1\sigma$ uncertainty. We measure the three parameters by
forward-modeling the Ly$\alpha$ forest and comparing the effective optical
depth ($\tau_{\rm eff, HI}$) distribution in simulations and observations. The
final uncertainties in our measured parameters account for the uncertainties
due to thermal parameters, modeling parameters, observational systematics and
cosmic variance. Our best fit parameters show significant evolution with
redshift such that $\lambda_{\rm mfp,HI}$ and $\langle f_{\rm HI} \rangle$
decreases and increases by a factor $\sim 6$ and $\sim 10^{4}$, respectively
from $z \sim 5$ to $z \sim 6$. By comparing our $\lambda_{\rm mfp,HI}$,
$\langle \Gamma_{\rm HI} \rangle$ and $\langle f_{\rm HI} \rangle$ evolution
with that in state-of-the-art Aton radiative transfer simulations and the
Thesan and CoDa-III simulations, we find that our best fit parameter evolution
is consistent with a model in which reionization completes by $z \sim 5.2$.


  Object manipulation actions represent an important share of the Activities of
Daily Living (ADLs). In this work, we study how to enable service robots to use
human multi-modal data to understand object manipulation actions, and how they
can recognize such actions when humans perform them during human-robot
collaboration tasks. The multi-modal data in this study consists of videos,
hand motion data, applied forces as represented by the pressure patterns on the
hand, and measurements of the bending of the fingers, collected as human
subjects performed manipulation actions. We investigate two different
approaches. In the first one, we show that multi-modal signal (motion, finger
bending and hand pressure) generated by the action can be decomposed into a set
of primitives that can be seen as its building blocks. These primitives are
used to define 24 multi-modal primitive features. The primitive features can in
turn be used as an abstract representation of the multi-modal signal and
employed for action recognition. In the latter approach, the visual features
are extracted from the data using a pre-trained image classification deep
convolutional neural network. The visual features are subsequently used to
train the classifier. We also investigate whether adding data from other
modalities produces a statistically significant improvement in the classifier
performance. We show that both approaches produce a comparable performance.
This implies that image-based methods can successfully recognize human actions
during human-robot collaboration. On the other hand, in order to provide
training data for the robot so it can learn how to perform object manipulation
actions, multi-modal data provides a better alternative.


  We show that it is possible to explain the physical origin of jet precession
in active galactic nuclei (AGNs) through the misalignment between the rotation
axes of the accretion disk and of the Kerr black hole. We apply this scenario
to quasars, Seyfert galaxies and also to the Galactic Center black hole Sgr A*,
for which signatures of either jet or disk precession have been found. The
formalism adopted is parameterized by the ratio of the precession period to the
black hole mass and can be used to put constraints to the physical properties
of the accretion disk as well as to the black hole spin in those systems.


  Let $Q_n(z)$ be the polynomials associated with the Nekrasov-Okounkov formula
$$\sum_{n\geq 1} Q_n(z) q^n := \prod_{m = 1}^\infty (1 - q^m)^{-z - 1}.$$ In
this paper we partially answer a conjecture of Heim and Neuhauser, which asks
if $Q_n(z)$ is unimodal, or stronger, log-concave for all $n \geq 1$. Through a
new recursive formula, we show that if $A_{n,k}$ is the coefficient of $z^k$ in
$Q_n(z)$, then $A_{n,k}$ is log-concave in $k$ for $k \ll n^{1/6}/\log n$ and
monotonically decreasing for $k \gg \sqrt{n}\log n$. We also propose a
conjecture that can potentially close the gap.


  The successful preparation of superconducting alkali fulleride
(A$_x$C$_{60}$, A = K, Rb, Cs) films using state-of-the-art molecular beam
epitaxy overcomes the disadvantages of the air-sensitivity and phase separation
in bulk A$_x$C$_{60}$, enabling for the first time a direct investigation of
the superconductivity in alkali fullerides on the molecular scale. In this
paper, we briefly review recent cryogenic scanning tunneling microscopy results
of the structural, electronic, and superconducting properties of the fcc
A$_x$C$_{60}$ films grown on graphitized SiC substrates. Robust $s$-wave
superconductivity is revealed against the pseudogap, electronic correlation,
non-magnetic impurities, and merohedral disorder. By controlling the alkali
metal species, film thickness, and electron doping, we systematically tune the
C$_{60}^{x-}$ orientational orderings and superconductivity in A$_x$C$_{60}$
films and then complete a unified phase diagram of superconducting gap size vs
electronic correlation and doping. These investigations are conclusive and
elucidated that the $s$-wave superconductivity retains in alkali fullerides
despite of the electronic correlation and presence of pseudogap.


  A distinguishing trait of the three known Galactic recurrent novae with the
shortest orbital periods, T Pyx, IM Nor, and CI Aql, is that their optical
decline time-scales are significantly longer than those of the other recurrent
systems. On the other hand, some estimates of the mass of the ejecta, the
velocity of the ejecta, and the duration of the soft X-rays emission of these
systems are of the order of those of the other recurrent systems and the fast
classical novae. We put forth a tentative explanation of this phenomenon. We
propose that in these systems part of the material transferred from the
companion during the first few days of the eruption remains within the Roche
lobe of the white dwarf, preventing the radiation from ionizing the ejecta of
the system and increasing the optical decline time-scale. We explain why this
phenomenon is more likely in systems with a high mass transfer rate and a short
orbital period. Finally, we present a schematic model that shows that the
material transferred from the companion is sufficient to absorb the radiation
from the white dwarf in these systems, ultimately supporting this scenario as
quantitatively realistic.


  Let $\mathbb{P}$ be the complete metric space consisting of positive
invertible operators on an infinite-dimensional Hilbert space with the Thompson
metric. We introduce the notion of operator means of probability measures on
$\mathbb{P}$, in parallel with Kubo and Ando's definition of two-variable
operator means, and show that every operator mean is contractive for the
$\infty$-Wasserstein distance. By means of a fixed point method we consider
deformation of such operator means, and show that the deformation of any
operator mean becomes again an operator mean in our sense. Based on this
deformation procedure we prove a number of properties and inequalities for
operator means of probability measures.


  Let $(Z_n,n\geq 0)$ be a supercritical Galton-Watson process whose offspring
distribution $\mu$ has mean $\lambda>1$ and is such that $\int x(\log(x))_+
d\mu(x)<+\infty$. According to the famous Kesten \& Stigum theorem,
$(Z_n/\lambda^n)$ converges almost surely, as $n\to+\infty$. The limiting
random variable has mean~1, and its distribution is characterised as the
solution of a fixed point equation. \par In this paper, we consider a family of
Galton-Watson processes $(Z_n(\lambda), n\geq 0)$ defined for~$\lambda$ ranging
in an interval $I\subset (1, \infty)$, and where we interpret $\lambda$ as the
time (when $n$ is the generation). The number of children of an individual at
time~$\lambda$ is given by $X(\lambda)$, where $(X(\lambda))_{\lambda\in I}$ is
a c\`adl\`ag integer-valued process which is assumed to be almost surely
non-decreasing and such that $\mathbb E(X(\lambda))=\lambda >1$ for all
$\lambda\in I$. This allows us to define $Z_n(\lambda)$ the number of elements
in the $n$th generation at time $\lambda$.
  Set $W_n(\lambda)= Z_n(\lambda)/\lambda^n$ for all $n\geq 0$ and $\lambda\in
I$. We prove that, under some moment conditions on the process~$X$, the
sequence of processes $(W_n(\lambda), \lambda\in I)_{n\geq 0}$ converges in
probability as~$n$ tends to infinity in the space of c\`adl\`ag processes
equipped with the Skorokhod topology to a process, which we characterise as the
solution of a fixed point equation.


  We investigate the Bose-Einstein Condensation on nonhomogeneous amenable
networks for the model describing arrays of Josephson junctions. The resulting
topological model, whose Hamiltonian is the pure hopping one given by the
opposite of the adjacency operator, has also a mathematical interest in itself.
We show that for the nonhomogeneous networks like the comb graphs, particles
condensate in momentum and configuration space as well. In this case different
properties of the network, of geometric and probabilistic nature, such as the
volume growth, the shape of the ground state, and the transience, all play a
role in the condensation phenomena. The situation is quite different for
homogeneous networks where just one of these parameters, e.g. the volume
growth, is enough to determine the appearance of the condensation.


  In this paper we report some results obtained by applying the radial gauge to
2+1 dimensional gravity. The general features of this gauge are reviewed and it
is shown how they allow the general solution of the problem in terms of simple
quadratures. Then we concentrate on the general stationary problem providing
the explicit solving formulas for the metric and the explicit support
conditions for the energy momentum tensor. The chosen gauge allows, due to its
physical nature, to exploit the weak energy condition and in this connection it
is proved that for an open universe conical at space infinity the weak energy
condition and the absence of closed time like curves (CTC) at space infinity
imply the total absence of CTC. It is pointed out how the approach can be used
to examine cosmological solution in 2+1 dimensions.


  Let $d$ be a positive integer, $\mathbb K$ an algebraically closed field of
characteristic 0 and $ X$ an elliptic curve defined over K. We study the
hyperelliptic curves equipped with a projection over $ X$, such that the
natural image of $ X$ in the Jacobian of the curve osculates to order $d$ to
the embedding of the curve, at a Weierstrass point. We construct
($d-1$)-dimensional families of such curves, of arbitrary big genus $g$,
obtaining, in particular, $(g+d-1)$-dimensional families of solutions of the
$KdV$ hierarchy, doubly periodic with respect to the $d$-th $KdV$ flow.


  In this paper we discuss the design choices and construction strategy of the
tapered undulator system designed for a high energy extraction efficiency
experiment in the ultraviolet region of the electromagnetic spectrum planned
for installation at the Argonne National Laboratory Linac Extension Area (LEA)
beamline. The undulator is comprised of 4 sections pure permanent magnet
Halbach array separated by short break sections, each one of them housing a
focusing quadrupole doublet and a phase shifter. The quadrupoles use a novel
hybrid design which allows one to vary the gradient and match the beam
transversely. The undulator tapering profile is optimized to maximize the
energy conversion efficiency from a 343 MeV 1 kA beam into coherent 257.5 nm
radiation taking into account the longitudinal current profile generated by the
linac.


  The unordered tree edit distance is a natural metric to compute distances
between trees without intrinsic child order, such as representations of
chemical molecules. While the unordered tree edit distance is MAX SNP-hard in
principle, it is feasible for small cases, e.g. via an A* algorithm.
Unfortunately, current heuristics for the A* algorithm assume unit costs for
deletions, insertions, and replacements, which limits our ability to inject
domain knowledge. In this paper, we present three novel heuristics for the A*
algorithm that work with custom cost functions. In experiments on two chemical
data sets, we show that custom costs make the A* computation faster and improve
the error of a 5-nearest neighbor regressor, predicting chemical properties. We
also show that, on these data, polynomial edit distances can achieve similar
results as the unordered tree edit distance.


  We study a process of opinion formation in a population of agents whose
interaction pattern is defined on the basis of randomly distributed groups of
three agents, or triplets -in contrast to networks, which are defined on the
basis of agent pairs. Results for the time needed to reach full consensus are
compared between a triplet-based structure with a given number of triplets and
a random network with the same number of triangles. The full-consensus time in
the triplet structure is systematically lower than in the network. This
discrepancy can be ascribed to differences in the shape of the probability
distribution for the number of triplets and triangles per agent in each
interaction pattern.


  In this short note we show that, for any ample embedding of a variety of
dimension at least two in a projective space, all high enough degree Veronese
re-embeddings have non-empty Terracini loci.


  We present a calculation for single-inclusive large-p_T pion production in
longitudinally polarized pp collisions in next-to-leading order QCD. We choose
an approach where fully analytical expressions for the underlying partonic
hard-scattering cross sections are obtained. We simultaneously rederive the
corresponding corrections to unpolarized scattering and confirm the results
existing in the literature. Our results allow to calculate the double-spin
asymmetry A_LL^pi for this process at next-to-leading order, which will soon be
used at BNL-RHIC to measure the polarization of gluons in the nucleon.


  We prove that each bounded polytope can be represented as a polynomial
zonotope, which we refer to as the Z-representation of polytopes. Previous
representations are the vertex representation (V-representation) and the
halfspace representation (H-representation). Depending on the polytope, the
Z-representation can be more compact than the V-representation and the
H-representation. In addition, the Z-representation enables the computation of
linear maps, Minkowski addition, and convex hull with a computational
complexity that is polynomial in the representation size. The usefulness of the
new representation is demonstrated by range bounding within polytopes.


  This paper describes ANN-Benchmarks, a tool for evaluating the performance of
in-memory approximate nearest neighbor algorithms. It provides a standard
interface for measuring the performance and quality achieved by nearest
neighbor algorithms on different standard data sets. It supports several
different ways of integrating $k$-NN algorithms, and its configuration system
automatically tests a range of parameter settings for each algorithm.
Algorithms are compared with respect to many different (approximate) quality
measures, and adding more is easy and fast; the included plotting front-ends
can visualise these as images, $\LaTeX$ plots, and websites with interactive
plots. ANN-Benchmarks aims to provide a constantly updated overview of the
current state of the art of $k$-NN algorithms. In the short term, this overview
allows users to choose the correct $k$-NN algorithm and parameters for their
similarity search task; in the longer term, algorithm designers will be able to
use this overview to test and refine automatic parameter tuning. The paper
gives an overview of the system, evaluates the results of the benchmark, and
points out directions for future work. Interestingly, very different approaches
to $k$-NN search yield comparable quality-performance trade-offs. The system is
available at http://ann-benchmarks.com .


  Using nuclear magnetic resonance techniques, we experimentally investigated
the effects of applying a two bit phase error detection code to preserve
quantum information in nuclear spin systems. Input states were stored with and
without coding, and the resulting output states were compared with the
originals and with each other. The theoretically expected result, net reduction
of distortion and conditional error probabilities to second order, was indeed
observed, despite imperfect coding operations which increased the error
probabilities by approximately 5%. Systematic study of the deviations from the
ideal behavior provided quantitative measures of different sources of error,
and good agreement was found with a numerical model. Theoretical questions in
quantum error correction in bulk nuclear spin systems including fidelity
measures, signal strength and syndrome measurements are discussed.


  We propose Significance-Offset Convolutional Neural Network, a deep
convolutional network architecture for regression of multivariate asynchronous
time series. The model is inspired by standard autoregressive (AR) models and
gating mechanisms used in recurrent neural networks. It involves an AR-like
weighting system, where the final predictor is obtained as a weighted sum of
adjusted regressors, while the weights are datadependent functions learnt
through a convolutional network. The architecture was designed for applications
on asynchronous time series and is evaluated on such datasets: a hedge fund
proprietary dataset of over 2 million quotes for a credit derivative index, an
artificially generated noisy autoregressive series and UCI household
electricity consumption dataset. The proposed architecture achieves promising
results as compared to convolutional and recurrent neural networks.


  Using ultra-high quality SiGe/Si/SiGe quantum wells at millikelvin
temperatures, we experimentally compare the energy-averaged effective mass,
$m$, with that at the Fermi level, $m_F$, and verify that the behaviours of
these measured values are qualitatively different. With decreasing electron
density (or increasing interaction strength), the mass at the Fermi level
monotonically increases in the entire range of electron densities, while the
energy-averaged mass saturates at low densities. The qualitatively different
behaviour reveals a precursor to the interaction-induced single-particle
spectrum flattening at the Fermi level in this electron system.


  A quantum phase transition (QPT), including both topological and symmetry
breaking types, is usually induced by the change of global parameters, such as
external fields or global coupling constants. In this work, we demonstrate the
existence of QPT induced by the real-space topology of the system. We
investigate the groundstate properties of the tight-binding model on a
honeycomb lattice with the torus geometry based on exact results. It is shown
that the ground state experiences a second- order QPT, exhibiting the scaling
behavior, when the torus switches to a tube, which reveals the connection
between quantum phase and the real-space topology of the system.


  Continuous long-term monitoring of electrocardiography (ECG) signals is
crucial for the early detection of cardiac abnormalities such as arrhythmia.
Non-clinical ECG recordings acquired by Holter and wearable ECG sensors often
suffer from severe artifacts such as baseline wander, signal cuts, motion
artifacts, variations on QRS amplitude, noise, and other interferences.
Usually, a set of such artifacts occur on the same ECG signal with varying
severity and duration, and this makes an accurate diagnosis by machines or
medical doctors extremely difficult. Despite numerous studies that have
attempted ECG denoising, they naturally fail to restore the actual ECG signal
corrupted with such artifacts due to their simple and naive noise model. In
this study, we propose a novel approach for blind ECG restoration using
cycle-consistent generative adversarial networks (Cycle-GANs) where the quality
of the signal can be improved to a clinical level ECG regardless of the type
and severity of the artifacts corrupting the signal. To further boost the
restoration performance, we propose 1D operational Cycle-GANs with the
generative neuron model. The proposed approach has been evaluated extensively
using one of the largest benchmark ECG datasets from the China Physiological
Signal Challenge (CPSC-2020) with more than one million beats. Besides the
quantitative and qualitative evaluations, a group of cardiologists performed
medical evaluations to validate the quality and usability of the restored ECG,
especially for an accurate arrhythmia diagnosis.


  In this note, we determine the maximum number of edges of a $k$-uniform
hypergraph, $k\ge 3$, with a unique perfect matching. This settles a conjecture
proposed by Snevily.


  The thermodynamics of a scalar field with a quartic interaction is studied
within the linear delta expansion (LDE) method. Using the imaginary-time
formalism the free energy is evaluated up to second order in the LDE. The
method generates nonperturbative results that are then used to obtain
thermodynamic quantities like the pressure. The phase transition pattern of the
model is fully studied, from the broken to the symmetry restored phase. The
results are compared with those obtained with other nonperturbative methods and
also with ordinary perturbation theory. The results coming from the two main
optimization procedures used in conjunction with the LDE method, the Principle
of Minimal Sensitivity (PMS) and the Fastest Apparent Convergence (FAC) are
also compared with each other and studied in which cases they are applicable or
not. The optimization procedures are applied directly to the free energy.


  We prove, by employing rigorous numerics, that Shimizu-Morioka system has a
Lorenz attractor for an open set of parameter values. Using this result, we
prove the existence of a discrete version of the Lorenz attractor for a class
of three-dimensional polynomial diffeomorphisms.


  An LCK (locally conformally Kahler) manifold is a complex manifold admitting
a Hermitian form $\omega$ which satisfies $d\omega =\omega\wedge \theta$, where
$\theta$ is a closed 1-form, called the Lee form. An LCK manifold is called
Vaisman if the Lee form is parallel with respect to the Levi-Civita connection.
The dual vector field, called the Lee field, is holomorphic and Killing. We
prove that any holomorphic tensor on a Vaisman manifold is invariant with
respect to the Lee field. This is used to compute the Kodaira dimension of
Vaisman manifolds. We prove that the Kodaira dimension of a Vaisman manifold
obtained as a $Z$-quotient of an algebraic cone over a projective manifold $X$
is equal to the Kodaira dimension of $X$. This can be applied to prove the
deformational stability of the Kodaira dimension of Vaisman manifolds.


  Using 2.0 cm x 2.0 cm x 0.5 cm Cadmium Telluride (CdTe) substrates from the
company Acrorad, we have fabricated detectors with planar cathode contacts and
8x8 anode pixels. We investigate the I-V characteristics and energy resolution
of the detectors for different contact materials and surface treatments. After
biasing the detectors for a certain period of time, the dark currents increase
dramatically. Out studies show that the time before breakdown decreases for
higher detector temperatures and higher applied bias voltages. We obtained the
best results with a Pt cathode and In anode pixels when we heat the detector to
90 C for 30 minutes prior to depositing the In contacts. Flood-illuminating the
detector with 662 keV X-rays, we measured the pulse length distribution and
derived an electron mobility of ~860 cm^(2)/V/s. We show that the energy
resolution can be improved by correcting the anode signals for the depth of the
primary interaction. Operated at -40 C and cathode bias of -500 V, the best
pixels of the best detector achieved full width half maximum (FWHM) energy
resolutions of 8 keV (6.4%) and 23 keV (3.4%) at 122 keV and 662 keV,
respectively.


  Advances in 3D imaging technology in recent years have allowed for
increasingly high resolution volumetric images of large specimen. The resulting
datasets of hundreds of Gigabytes in size call for new scalable and memory
efficient approaches in the field of image processing, where some progress has
been made already. At the same time, quantitative evaluation of these new
methods is difficult both in terms of the availability of specific data sizes
and in the generation of associated ground truth data. In this paper we present
an algorithmic framework that can be used to efficiently generate test (and
ground truth) volume data, optionally even in a streaming fashion. As the
proposed nested sweeps algorithm is fast, it can be used to generate test data
on demand. We analyze the asymptotic run time of the presented algorithm and
compare it experimentally to alternative approaches as well as a hypothetical
best-case baseline method. In a case study, the framework is applied to the
popular VascuSynth software for vascular image generation, making it capable of
efficiently producing larger-than-main memory volumes which is demonstrated by
generating a trillion voxel (1TB) image. Implementations of the presented
framework are available online in the form of the modified version of
Vascusynth and the code used for the experimental evaluation. In addition, the
test data generation procedure has been integrated into the popular volume
rendering and processing framework Voreen.


  We have recently introduced a new model for the distribution of dark matter
(DM) in galaxies based on a self-gravitating system of massive fermions at
finite temperatures, the Ruffini-Arg\"uelles-Rueda (RAR) model. We show that
this model, for fermion masses in the keV range, explains the DM halo of the
Galaxy and predicts the existence of a denser quantum core at the center. We
demonstrate here that the introduction of a cutoff in the fermion phase-space
distribution, necessary to account for the finite Galaxy size, defines a new
solution with a central core which represents an alternative to the black hole
(BH) scenario for SgrA*. For a fermion mass in the range $mc^2 = 48$ --
$345$~keV, the DM halo distribution is in agreement with the Milky Way rotation
curve data, while harbors a dense quantum core of about $4\times10^6 M_\odot$
within the S2-star pericenter.


  This paper presents the benchmark score definitions of QPack, an
application-oriented cross-platform benchmarking suite for quantum computers
and simulators, which makes use of scalable Quantum Approximate Optimization
Algorithm and Variational Quantum Eigensolver applications. Using a varied set
of benchmark applications, an insight of how well a quantum computer or its
simulator performs on a general NISQ-era application can be quantitatively
made. This paper presents what quantum execution data can be collected and
transformed into benchmark scores for application-oriented quantum
benchmarking. Definitions are given for an overall benchmark score, as well as
sub-scores based on runtime, accuracy, scalability and capacity performance.
Using these scores, a comparison is made between various quantum computer
simulators, running both locally and on vendors' remote cloud services. We also
use the QPack benchmark to collect a small set of quantum execution data of the
IBMQ Nairobi quantum processor. The goal of the QPack benchmark scores is to
give a holistic insight into quantum performance and the ability to make easy
and quick comparisons between different quantum computers


  We predict that antiferromagnetic bilayers formed from van der Waals (vdW)
materials, like bilayer CrI$_3$, have a strong magnetoelectric response that
can be detected by measuring the gate voltage dependence of Faraday or Kerr
rotation signals, total magnetization, or anomalous Hall conductivity. Strong
effects are possible in single-gate geometries, and in dual-gate geometries
that allow internal electric fields and total carrier densities to be varied
independently. We comment on the reliability of density-functional-theory
estimates of interlayer magnetic interactions in van der Waals bilayers, and on
the sensitivity of magnetic interactions to pressure that alters the spatial
separation between layers.


  For real hyperbolic spaces, the dynamics of individual isometries and the
geometry of the limit set of nonelementary discrete isometry groups have been
studied in great detail. Most of the results were generalised to discrete
isometry groups of simply connected Riemannian manifolds of pinched negative
curvature. For symmetric spaces of higher rank, which contain isometrically
embedded Euclidean planes, the situation becomes far more complicated. This
paper is devoted to the study of the geometric limit set of ``nonelementary''
discrete isometry groups of higher rank symmetric spaces. We obtain the natural
generalisations of some well-known results from Kleinian group theory. Our main
tool consists in a detailed description of the dynamics of individual
isometries. As a by-product, we give a new geometric construction of free
isometry groups with parabolic elements in higher rank symmetric spaces.


  The vulnerability to slight input perturbations is a worrying yet intriguing
property of deep neural networks (DNNs). Despite many previous works studying
the reason behind such adversarial behavior, the relationship between the
generalization performance and adversarial behavior of DNNs is still little
understood. In this work, we reveal such relation by introducing a metric
characterizing the generalization performance of a DNN. The metric can be
disentangled into an information-theoretic non-robust component, responsible
for adversarial behavior, and a robust component. Then, we show by experiments
that current DNNs rely heavily on optimizing the non-robust component in
achieving decent performance. We also demonstrate that current state-of-the-art
adversarial training algorithms indeed try to robustify the DNNs by preventing
them from using the non-robust component to distinguish samples from different
categories. Also, based on our findings, we take a step forward and point out
the possible direction for achieving decent standard performance and
adversarial robustness simultaneously. We believe that our theory could further
inspire the community to make more interesting discoveries about the
relationship between standard generalization and adversarial generalization of
deep learning models.


  In the last decade, integrated logistics has become an important challenge in
the development of wireless communication, identification and sensing
technology, due to the growing complexity of logistics processes and the
increasing demand for adapting systems to new requirements. The advancement of
wireless technology provides a wide range of options for the maritime container
terminals. Electronic devices employed in container terminals reduce the manual
effort, facilitating timely information flow and enhancing control and quality
of service and decision made. In this paper, we examine the technology that can
be used to support integration in harbor's logistics. In the literature, most
systems have been developed to address specific needs of particular harbors,
but a systematic study is missing. The purpose is to provide an overview to the
reader about which technology of integrated logistics can be implemented and
what remains to be addressed in the future.


  This paper studies the relationship between the Lyapunov function of a
macrosystem whose dynamics is governed by the laws of stochastic chemical
kinetics and the invariant measure of this macrosystem arising at large times.
A necessary and sufficient condition for the reduction of the search problem
for the equilibrium of the macrosystem (the most probable macrostate of the
invariant measure of this macrosystem) to an entropy-linear programming problem
is given.


  Problems posed by semirelativistic Hamiltonians of the form
  H = sqrt{m^2+p^2} + V(r) are studied. It is shown that energy upper bounds
can be constructed in terms of certain related Schroedinger operators; these
bounds include free parameters which can be chosen optimally.


  Let $R$ be a commutative ring that is free of rank $k$ as an abelian group,
$p$ a prime, and $SL(n,R)$ the special linear group. We show that the Lie
algebra associated to the filtration of $SL(n,R)$ by $p$-congruence subgroups
is isomorphic to the tensor product
$\mathfrak{sl}_n(R\otimes_{\Z}\Z/p)\otimes_{\F_p}t\F_p[t]$, the Lie algebra of
polynomials with zero constant term and coefficients $n\times n$ traceless
matrices with entries polynomials in $k$ variables over $\F_p$.
  We use the Lie algebra structure along with the Lyndon-Hochschild-Serre
spectral sequence to compute the $d^2$ homology differential for certain
central extensions involving quotients of $p$-congruence subgroups. We also use
the underlying group structure to obtain several homological results. For
example, we compute the first homology group of the level $p$-congruence
subgroup for $n\geq3$. We show that the cohomology groups of the level
$p^r$-congruence subgroup are not finitely generated for $n=2$ and $R=\Z[t]$.
Finally, we show that for $n=2$ and $R=\Z[i]$, the Gaussian integers, the
second cohomology group of the level $p^r$-congruence subgroup has dimension at
least two as an $\F_p$-vector space.


  We re-examine physical state representations in the covariant quantization of
bosonic string. We especially consider one parameter family of gauge fixing
conditions for the residual gauge symmetry due to null states (or BRST exact
states), and obtain explicit representations of observable Hilbert space which
include those of the DDF states. This analysis is aimed at giving a necessary
ingredient for the complete gauge fixing procedures of covariant string field
theory such as temporal or light-cone gauge.


  We show cocycle stability for linear maps with a weak irreducibility
condition and their jointly integrable perturbations.


  We consider the production of lepton pairs with intermediate invariant
masses, in relativistic nuclear collisions. Thermal sources are briefly
discussed, as well as a newer production mechanism which involves jet-plasma
interactions. Estimates for high p_T lepton pairs are provided.


  A ternary complex tree related to the golden ratio is used to show how the
theory of complex trees works. We use the topological set of this tree to
obtain a parametric family of trees in one complex variable. Even though some
real ferns and leaves are reminiscent to elements of our family of study, here
we only consider the underlying mathematics. We provide aesthetically appealing
examples and a map of the unstable set $\mathcal{M}$ for this family. Moreover
we show that some elements found in the boundary of the unstable set
$\mathcal{M}$ possess interesting algebraic properties, and we explain how to
compute the Hausdorff dimension and the shortest path of self-similar sets
described by trees found outside the interior of the unstable set
$\mathcal{M}$.


  In a previous paper we derived a post-Newtonian approximation to cosmology
which, in contrast to former Newtonian and post-Newtonian cosmological
theories, has a well-posed initial value problem. In this paper, this new
post-Newtonian theory is compared with the fully general relativistic theory,
in the context of the k = 0 Friedmann Robertson Walker cosmologies. It is found
that the post-Newtonian theory reproduces the results of its general
relativistic counterpart, whilst the Newtonian theory does not.


  Double-level quantum systems are good candidates for revealing coherent
quantum transport properties. Here, we consider quantum interference effects
due to the formation of a two-level system (TLS) coupled to the edge channel of
a zigzag Phosphorene nanoribbon (ZPNR). Using the tight-binding approach, we
first demonstrate the formation of a TLS in bulk Phosphorene sheet due to the
existence of two nearby vacancy impurities. Then, we show that such a TLS can
couple to the quasi-one-dimensional continuum of the edge states in a ZPNR
which results in the the appearance of two-dip Fano-type line shapes. To this
end, we generalize the Lippmann-Schwinger approach to study the scattering of
edge electrons in a ZPNR by two coupled impurity defects. We obtain an
analytical expression of the transmission coefficient which shows that the
positions and widths of the anti-resonances can be controlled by changing the
intervacancy distance as well as their distance from the edge of the ribbon.
This work constitutes a clear example of the multiple Fano resonances in
mesoscopic transport.


  The Next Generation Balloon-borne Large Aperture Submillimeter Telescope
(BLAST-TNG) is a submillimeter polarimeter designed to map interstellar dust
and galactic foregrounds at 250, 350, and 500 microns during a 24-day Antarctic
flight. The BLAST-TNG detector arrays are comprised of 918, 469, and 272 MKID
pixels, respectively. The pixels are formed from two orthogonally oriented,
crossed, linear-polarization sensitive MKID antennae. The arrays are cooled to
sub 300mK temperatures and stabilized via a closed cycle $^3$He sorption fridge
in combination with a $^4$He vacuum pot. The detectors are read out through a
combination of the second-generation Reconfigurable Open Architecture Computing
Hardware (ROACH2) and custom RF electronics designed for BLAST-TNG. The
firmware and software designed to readout and characterize these detectors was
built from scratch by the BLAST team around these detectors, and has been
adapted for use by other MKID instruments such as TolTEC and OLIMPO. We present
an overview of these systems as well as in-depth methodology of the
ground-based characterization and the measured in-flight performance.


  Data preprocessing is an important component of machine learning pipelines,
which requires ample time and resources. An integral part of preprocessing is
data transformation into the format required by a given learning algorithm.
This paper outlines some of the modern data processing techniques used in
relational learning that enable data fusion from different input data types and
formats into a single table data representation, focusing on the
propositionalization and embedding data transformation approaches. While both
approaches aim at transforming data into tabular data format, they use
different terminology and task definitions, are perceived to address different
goals, and are used in different contexts. This paper contributes a unifying
framework that allows for improved understanding of these two data
transformation techniques by presenting their unified definitions, and by
explaining the similarities and differences between the two approaches as
variants of a unified complex data transformation task. In addition to the
unifying framework, the novelty of this paper is a unifying methodology
combining propositionalization and embeddings, which benefits from the
advantages of both in solving complex data transformation and learning tasks.
We present two efficient implementations of the unifying methodology: an
instance-based PropDRM approach, and a feature-based PropStar approach to data
transformation and learning, together with their empirical evaluation on
several relational problems. The results show that the new algorithms can
outperform existing relational learners and can solve much larger problems.


  In many deep reinforcement learning settings, when an agent takes an action,
it repeats the same action a predefined number of times without observing the
states until the next action-decision point. This technique of action
repetition has several merits in training the agent, but the data between
action-decision points (i.e., intermediate frames) are, in effect, discarded.
Since the amount of training data is inversely proportional to the interval of
action repeats, they can have a negative impact on the sample efficiency of
training. In this paper, we propose a simple but effective approach to
alleviate to this problem by introducing the concept of pseudo-actions. The key
idea of our method is making the transition between action-decision points
usable as training data by considering pseudo-actions. Pseudo-actions for
continuous control tasks are obtained as the average of the action sequence
straddling an action-decision point. For discrete control tasks, pseudo-actions
are computed from learned action embeddings. This method can be combined with
any model-free reinforcement learning algorithm that involves the learning of
Q-functions. We demonstrate the effectiveness of our approach on both
continuous and discrete control tasks in OpenAI Gym.


  We establish a general Liouville type theorem for conformally invariant fully
nonlinear equations.


  We present a solution for the F-symbols of the H3 fusion category, which is
Morita equivalent to the even parts of the Haagerup subfactor. This solution
has been computed by solving the pentagon equations and using several
properties of trivalent categories.


  When a laser-cooled atomic sample is optically excited, the envelope of
coherent forward scattering can often be decomposed into a few complex Gaussian
profiles. The convenience of Gaussian propagation helps addressing key
challenges in digital holography. In this work, we theoretically develop and
experimentally demonstrate a Gaussian-decomposition-assisted approach to inline
holography, for single-shot, simultaneous measurements of absorption and phase
shift of small atomic samples sparsely distributed in 3D. Experimentally, we
image a sparse lattice of $^{87}$Rb samples on the D2 line, to resolve their
axial positions with micrometer precision, and to retrieve their complex-valued
spectroscopic images. With the phase-angle readouts that are highly insensitive
to atom-number and interaction-strength uncertainties, we achieve
hundred-kHz-level single-shot-resolution to the transition frequency with
merely hundreds of atoms. We further demonstrate 3D sensing of local light
shift with micrometer spatial resolution.


  A large number of pulsars and X-rays sources are detected in globular
clusters. To understand the structure and content of these clusters, accurate
distances are required. We derive the distances of Terzan 5, Liller 1 and UKS 1
using as a reference a recent distance determination of NGC 6528, based on
HST/NICMOS and NTT/SOFI infrared photometry. The distance of the metal-poor
cluster Terzan 4 was derived from a comparison with M92 in NICMOS bands.
Distances of the metal-rich clusters are obtained by comparison of the
Horizontal Branch (HB) level of the clusters, relative to the reddening line
passing through the HB of NGC 6528. We use methods based on NICMOS bands and
transformations to J and H magnitudes with different assumptions. Liller~1 and
Terzan~4 are found to be at the central bulge distance, UKS~1 is beyond the
Galactic center, while Terzan 5 is closer to the Sun than the other four
clusters. The distance of Terzan 5 is of paramount importance, given the impact
of its population of 21 pulsars, which is related to the high cluster density.
The distance of Terzan 5 is found to be d$_{\odot}$=5.5$\pm$0.9 kpc from the
Sun, thus closer to us than values given in studies of pulsars in Terzan 5. As
a consequence, the higher cluster density is even more favourable for formation
of the millisecond pulsars recently detected in this cluster.


  We consider the nonlinear eigenvalue problem $-{\rm div}(|\nabla
u|^{p(x)-2}\nabla u)=\lambda |u|^{q(x)-2}u$ in $\Omega$, $u=0$ on
$\partial\Omega$, where $\Omega$ is a bounded open set in $\RR^N$ with smooth
boundary and $p$, $q$ are continuous functions on $\bar\Omega$ such that
$1<\inf\_\Omega q< \inf\_\Omega p<\sup\_\Omega q$, $\sup\_\Omega p<N$, and
$q(x)<Np(x)/(N-p(x))$ for all $x\in\bar\Omega$. The main result of this paper
establishes that any $\lambda>0$ sufficiently small is an eigenvalue of the
above nonhomogeneous quasilinear problem. The proof relies on simple
variational arguments based on Ekeland's variational principle.


  Recent developments have made it possible to overcome grid-based limitations
of finite difference (FD) methods by adopting the kernel-based meshless
framework using radial basis functions (RBFs). Such an approach provides a
meshless implementation and is referred to as the radial basis-generated finite
difference (RBF-FD) method. In this paper, we propose a stabilized RBF-FD
approach with a hybrid kernel, generated through a hybridization of the
Gaussian and cubic RBF. This hybrid kernel was found to improve the condition
of the system matrix, consequently, the linear system can be solved with direct
solvers which leads to a significant reduction in the computational cost as
compared to standard RBF-FD methods coupled with present stable algorithms.
Unlike other RBF-FD approaches, the eigenvalue spectra of differentiation
matrices were found to be stable irrespective of irregularity, and the size of
the stencils. As an application, we solve the frequency-domain acoustic wave
equation in a 2D half-space. In order to suppress spurious reflections from
truncated computational boundaries, absorbing boundary conditions have been
effectively implemented.


  We employ chordal decomposition to reformulate a large and sparse
semidefinite program (SDP), either in primal or dual standard form, into an
equivalent SDP with smaller positive semidefinite (PSD) constraints. In
contrast to previous approaches, the decomposed SDP is suitable for the
application of first-order operator-splitting methods, enabling the development
of efficient and scalable algorithms. In particular, we apply the alternating
direction method of multipliers (ADMM) to solve decomposed primal- and
dual-standard-form SDPs. Each iteration of such ADMM algorithms requires a
projection onto an affine subspace, and a set of projections onto small PSD
cones that can be computed in parallel. We also formulate the homogeneous
self-dual embedding (HSDE) of a primal-dual pair of decomposed SDPs, and extend
a recent ADMM-based algorithm to exploit the structure of our HSDE. The
resulting HSDE algorithm has the same leading-order computational cost as those
for the primal or dual problems only, with the advantage of being able to
identify infeasible problems and produce an infeasibility certificate. All
algorithms are implemented in the open-source MATLAB solver CDCS. Numerical
experiments on a range of large-scale SDPs demonstrate the computational
advantages of the proposed methods compared to common state-of-the-art solvers.


  Precise knowledge of X-ray diffraction profile shape is crucial in the
investigation of the properties of matter in crystals powder. Line-broadening
analysis is a pre-processing step in most of the full powder pattern fitting
softwares. Final result of line-broadening analysis strongly depends on
preliminary three steps: Noise filtering, removal of background signal and peak
fitting. In this work a new model independent procedure for two of the
aforementioned steps (background suppression and peak fitting) is presented.
The former is dealt with by using morphological mathematics, while the latter
relies on the Hankel Lanczos Singular Value Decomposition technique. Real X-ray
powder diffraction (XRPD) intensity profiles of Ceria samples are used to test
the performance of the proposed procedure. Results show the robustness of this
approach and its capability of efficiently improving the disentangling of
instrumental broadening. These features make the proposed approach an
interesting and user-friendly tool for the pre-processing of XRPD data.


  Adams inequalities with exact growth conditions are derived for Riesz-like
potentials on metric measure spaces. The results extend and improve those
obtained recently on $\mathbb R^n$ by the second author, for Riesz-like
convolution operators. As a consequence, we will obtain new sharp
Moser-Trudinger inequalities with exact growth conditions on $\mathbb R^n$, the
Heisenberg group, and Hadamard manifolds. On $\mathbb R^n$ such inequalities
will be used to prove the existence of radial ground states solutions for a
class of quasilinear elliptic equations, extending results due to Masmoudi and
Sani.


  The least action principle (LAP) is a dynamically rigorous method for
deriving the history of galaxy orbits. In particular it is an Omega_0 test,
predicting current epoch galaxy velocities as a function of position and of the
cosmological background. It is most usefully applied to in--falling structures,
such as the local group, where its application indicates that the preferred
cosmological model is Omega_0 = 0.1 and h=0.75 (h is the Hubble parameter in
units of 100 Km s^-1 Mpc^-1). The method assumes that all the mass acts as if
it were distributed as the visible galaxies. We test the reliability of the LAP
to Local Group-like systems extracted from Omega_0=1 N--body simulations. While
the orbits of the galaxies are qualitatively well reconstructed, the LAP
systematically underestimates the mass of the system. This failure is
attributed to the presence of extended halos weakly clustered around visible
galaxies which prevent a large fraction of the group mass from being detected
by the LAP technique. We conclude that the LAP method cannot rule out an
Omega_0=1 value on the Local Group scale. Better constraints on Omega_0 may be
obtained by applying this technique to in--falling systems, such as clusters,
containing objects with separations large compared to galaxy sizes.


  We study moduli spaces $\mathcal{N}$ of rank 2 stable reflexive sheaves on
$\mathbb{P}^3$. Fixing Chern classes $c_1$, $c_2$, and summing over $c_3$, we
consider the generating function $\mathsf{Z}^{\mathrm{refl}}(q)$ of Euler
characteristics of such moduli spaces. The action of the torus $T$ on
$\mathbb{P}^3$ lifts to $\mathcal{N}$ and we classify all sheaves in
$\mathcal{N}^T$. This leads to an explicit expression for
$\mathsf{Z}^{\mathrm{refl}}(q)$. Since $c_3$ is bounded below and above,
$\mathsf{Z}^{\mathrm{refl}}(q)$ is a polynomial. We find a simple formula for
its leading term when $c_1=-1$.
  Next, we study moduli spaces of rank 2 stable torsion free sheaves on
$\mathbb{P}^3$ and consider the generating function of Euler characteristics of
such moduli spaces. We give an expression for this generating function in terms
of $\mathsf{Z}^{\mathrm{refl}}(q)$ and Euler characteristics of Quot schemes of
certain $T$-equivariant reflexive sheaves, which are studied elsewhere. Many
techniques of this paper apply to any toric 3-fold. In general,
$\mathsf{Z}^{\mathrm{refl}}(q)$ depends on the choice of polarization which
leads to wall-crossing phenomena. We briefly illustrate this in the case of
$\mathbb{P}^2 \times \mathbb{P}^1$.


  In the paper two-weighted norm estimates with general weights for Hardy-type
transforms, maximal functions, potentials and Calder\'on-Zygmund singular
integrals in variable exponent Lebesgue spaces defined on quasimetric measure
spaces $(X, d, \mu)$ are established. In particular, we derive integral-type
easily verifiable sufficient conditions governing two-weight inequalities for
these operators. If exponents of Lebesgue spaces are constants, then most of
the derived conditions are simultaneously necessary and sufficient for
appropriate inequalities. Examples of weights governing the boundedness of
maximal, potential and singular operators in weighted variable exponent
Lebesgue spaces are given.


  The hybridization of distinct quantum systems is now seen as an effective way
to engineer the properties of an entire system leading to applications in
quantum metamaterials, quantum simulation, and quantum metrology. One well
known example is superconducting circuits coupled to ensembles of microscopic
natural atoms. In such cases, the properties of the individual atom are
intrinsic, and so are unchangeable. However, current technology allows us to
fabricate large ensembles of macroscopic artificial atoms such as
superconducting flux qubits, where we can really tailor and control the
properties of individual qubits. Here, we demonstrate coherent coupling between
a microwave resonator and several thousand superconducting flux qubits, where
we observe a large dispersive frequency shift in the spectrum of 250 MHz
induced by collective behavior. These results represent the largest number of
coupled superconducting qubits realized so far. Our approach shows that it is
now possible to engineer the properties of the ensemble, opening up the way for
the controlled exploration of the quantum many-body system.


  We study the effects of a dark energy component with equation of state p=w
rho with constant w >= -1 on the formation of Cold Dark Matter (CDM) haloes. We
find two main effects: first, haloes form earlier as w increases, and second,
the amplitude of the dark-matter power spectrum gets reduced in order to remain
compatible with the large scale Cosmic Microwave Background (CMB) anisotropies.
These effects counteract. Using recipes derived from numerical simulations, we
show that haloes are expected to be up to ~ 50% more concentrated in CDM models
with quintessence compared to Lambda-CDM models, the maximum increase being
reached for w ~ -0.6. For larger w, the amplitude of the power spectrum
decreases rapidly and makes expected halo concentrations drop. Halo detections
through weak gravitational lensing are highly sensitive to halo concentrations.
We show that weak-lensing halo counts with the aperture-mass technique can
increase by a factor of ~ 2 as w is increased from -1 to -0.6, offering a new
method for constraining the nature of dark energy.


  The transport properties of a disordered two-dimensional (2D) honeycomb
lattice are examined numerically using the spectral approach to the quantum
percolation problem, characterized by an Anderson-type Hamiltonian. In our
simulations, substitutional disorder (or doping) is represented by a modified
bimodal probability distribution of the on-site energies. The results indicate
the existence of extended energy states for nonzero disorder and the emergence
of a transition towards localized behavior for critical doping concentration
n_D>0.3%, in agreement with the experimentally observed metal-to-insulator
transition in graphene sheet doped with hydrogen.


  The Great Nebula in Carina is a superb location in which to study the physics
of violent massive star-formation and the resulting feedback effects, including
cloud dispersal and triggered star-formation. In order to reveal the cold dusty
clouds in the Carina Nebula complex, we used the Large APEX Bolometer Camera
LABOCA at the APEX telescope to map a 1.25 deg x 1.25 deg (= 50 x 50 pc^2)
region at 870 micrometer. From a comparison to Halpha images we infer that
about 6% of the 870 micrometer flux in the observed area is likely free-free
emission from the HII region, while about 94% of the flux is very likely
thermal dust emission. The total (dust + gas) mass of all clouds for which our
map is sensitive is ~ 60 000 Msun, in good agreement with the mass of the
compact clouds in this region derived from 13CO line observations. We generally
find good agreement in the cloud morphology seen at 870 micrometer and the
Spitzer 8 micrometer emission maps, but also identify a prominent infrared dark
cloud. Finally, we construct a radiative transfer model for the Carina Nebula
complex that reproduces the observed integrated spectral energy distribution
reasonably well. Our analysis suggests a total gas + dust mass of about 200000
Msun in the investigated area; most of this material is in the form of
molecular clouds, but a widely distributed component of (partly) atomic gas,
containing up to ~ 50% of the total mass, may also be present. Currently, only
some 10% of the gas is in sufficiently dense clouds to be immediately available
for future star formation, but this fraction may increase with time owing to
the ongoing compression of the strongly irradiated clouds and the expected
shockwaves of the imminent supernova explosions.


  The methods in the Gasoline2 Smoothed Particle Hydrodynamics (SPH) code are
described and tested. Gasoline2 is the most recent version of the Gasoline code
for parallel hydrodynamics and gravity with identical hydrodynamics to the
Changa code. As with other Modern SPH codes, we prevent sharp jumps in time
steps, use upgraded kernels and larger neighbour numbers and employ local
viscosity limiters. Unique features in Gasoline2 include its
Geometric-Density-Average Force expression, explicit Turbulent Diffusion terms
and Gradient-Based shock detection to limit artificial viscosity. This last
feature allows Gasoline2 to completely avoid artificial viscosity in
non-shocking compressive flows. We present a suite of tests demonstrating the
value of these features with the same code configuration and parameter choices
used for production simulations.


  A polarized atomic beam source was developed for the polarized internal
storage-cell gas target at the magnet spectrometer ANKE of COSY-J\"ulich. The
intensities of the beams injected into the storage cell, measured with a
compression tube, are $7.5\cdot 10^{16}$ hydrogen atoms/s (two hyperfine
states) and $3.9\cdot 10^{16}$ deuterium atoms/s (three hyperfine states). For
the hydrogen beam the achieved vector polarizations are $p_{\rm
z}\approx\pm0.92$. For the deuterium beam, the obtained combinations of vector
and tensor ($p_{\rm zz}$) polarizations are $p_{\rm z}\approx\pm 0.90$ (with a
constant $p_{\rm zz}\approx +0.86$), and $p_{\rm zz}=+0.90$ or $p_{\rm
zz}=-1.71$ (both with vanishing $p_{\rm z}$). The paper includes a detailed
technical description of the apparatus and of the investigations performed
during the development.


  In this paper, we investigate a class of hybrid stochastic heat equations. By
explicit formulae of solutions, we not only reveal the sample Lyapunov
exponents but also discuss the $p$th moment Lyapnov exponents. Moreover,
several examples are established to demonstrate that unstable (deterministic or
stochastic) dynamical systems can be stabilized by Markovian switching.


  The present article is a sequel of the article "Fislab the Fuzzy Inference
Tool-Box for Scilab" and it represents the practical application of:"The
development of the Fuzzy regulator with an input and an output in Fislab". The
article contains, besides this application, some functions to be used in the
program, namely Scilab functions for the fuzzification of the firm information,
functions for the operation of de-fuzzification and functions for the
implementation of.


  We compute the leading order perturbative correction to the static potential
in ${\cal N}=4$ supersymmetric Yang-Mills theory. We show that the perturbative
expansion contains infrared logarithms which, when resummed, become logarithms
of the coupling constant. The resulting correction goes in the right direction
to match the strong coupling behavior obtained from the AdS/CFT correspondence.
We find that the strong coupling extrapolation of the sum of ladder diagrams
goes as $\sqrt{g^2N}$, as in the supergravity approach.


  Approachability has become a standard tool in analyzing earning algorithms in
the adversarial online learning setup. We develop a variant of approachability
for games where there is ambiguity in the obtained reward that belongs to a
set, rather than being a single vector. Using this variant we tackle the
problem of approachability in games with partial monitoring and develop simple
and efficient algorithms (i.e., with constant per-step complexity) for this
setup. We finally consider external regret and internal regret in repeated
games with partial monitoring and derive regret-minimizing strategies based on
approachability theory.


  Necessary discretization rules to preserve the Painlev\'e property are
stated. A new method is added to the discrete Painlev\'e test, which perturbs
the continuous limit and generates infinitely many no-log conditions.


  Community detection methods can be used to explore the structure of complex
systems. The well-known modular configurations in complex financial systems
indicate the existence of community structures. Here we analyze the community
properties of correlation-based networks in worldwide stock markets and use
community information to construct portfolios. Portfolios constructed using
community detection methods perform well. Our results can be used as new
portfolio optimization and risk management tools.


  The key result in the theory of Bridgeland stability conditions is the
property that they form a complex manifold. This comes from the fact that given
any small deformation of the central charge, there is a unique way to
correspondingly deform the stability condition.
  We give a short direct proof of a strong version of this deformation
property.


  We report the detection of intermediate-age and old stars belonging to the
SMC at 6.5 kpc from the SMC center in the southern direction. We show, from the
analysis of three high quality 34\arcmin $\times$ 33\arcmin CMDs, that the age
composition of the stellar population is similar at galactocentric distances of
$\thicksim$4.7 kpc, $\thicksim$5.6 kpc, and $\thicksim$6.5 kpc. The surface
brightness profile of the SMC follows an exponential law, with no evidence of
truncation, all the way out to 6.5 kpc. These results, taken together, suggest
that the SMC `disk' population is dominating over a possible old Milky Way-like
stellar halo, and that the SMC may be significantly larger than previously
thought.


  Solar flares are the most powerful events in the solar system and the
brightest sources of X-rays, often associated with emission of particles
reaching the Earth and causing geomagnetic storms, giving problems to
communication, airplanes and even black-outs. X-rays emitted by accelerated
electrons are the most direct probe of solar flare phenomena. The Micro
Solar-Flare Apparatus (MiSolFA) is a proposed compact X-ray detector which will
address the two biggest issues in solar flare modeling. Dynamic range
limitations prevent simultaneous spectroscopy with a single instrument of all
X-ray emitting regions of a flare. In addition, most X-ray observations so far
are inconsistent with the high anisotropy predicted by the models usually
adopted for solar flares. Operated at the same time as the STIX instrument of
the ESA Solar Orbiter mission, at the next solar maximum (2020), they will have
the unique opportunity to look at the same flare from two different directions:
Solar Orbiter gets very close to the Sun with significant orbital inclination;
MiSolFA is in a near-Earth orbit. To solve the cross-calibration problems
affecting all previous attempts to combine data from different satellites,
MiSolFA will adopt the same photon detectors as STIX, precisely quantifying the
anisotropy of the X-ray emission for the first time. By selecting flares whose
footpoints (the brightest X-ray sources, at the chromosphere) are occulted by
the solar limb for one of the two detectors, the other will be able to study
the much fainter coronal emission, obtaining for the first time simultaneous
observations of all interesting regions. MiSolFA shall operate on board of a
very small satellite, with several launch opportunities, and will rely on
moir\'e imaging techniques.


  It has been a long-held belief that judicious resource allocation is critical
to mitigating interference, improving network efficiency, and ultimately
optimizing wireless communication performance. The traditional wisdom is to
explicitly formulate resource allocation as an optimization problem and then
exploit mathematical programming to solve the problem to a certain level of
optimality. Nonetheless, as wireless networks become increasingly diverse and
complex, e.g., in the high-mobility vehicular networks, the current design
methodologies face significant challenges and thus call for rethinking of the
traditional design philosophy. Meanwhile, deep learning, with many success
stories in various disciplines, represents a promising alternative due to its
remarkable power to leverage data for problem solving. In this paper, we
discuss the key motivations and roadblocks of using deep learning for wireless
resource allocation with application to vehicular networks. We review major
recent studies that mobilize the deep learning philosophy in wireless resource
allocation and achieve impressive results. We first discuss deep learning
assisted optimization for resource allocation. We then highlight the deep
reinforcement learning approach to address resource allocation problems that
are difficult to handle in the traditional optimization framework. We also
identify some research directions that deserve further investigation.


  Experiments have shown that shear waves induced in brain tissue can develop
into shock waves, thus providing a possible explanation of deep traumatic brain
injuries. Here, we study the formation of shock waves in soft viscoelastic
solids subject to an imposed velocity at their boundary. We consider the plane
shearing motion of a semi-infinite half-space, which corresponds to a spatially
one-dimensional problem. Incompressible soft solids whose behaviour is
described by the Fung-Simo quasi-linear viscoelasticy theory (QLV) are
considered, where the elastic response is either exponential or polynomial of
Mooney-Rivlin-Yeoh type. Waveform breaking can occur at the blow-up of
acceleration waves, leading to one sufficient condition for the formation of
shocks. A slow scale analysis based on a small amplitude parameter yields a
damped Burgers-like equation, thus leading to another shock formation
condition. Numerical experiments performed using a dedicated finite volume
scheme show that these estimates have limited accuracy. Their validity is
restricted in the elastic limit too, where exact shock formation conditions are
known.


  We consider a non-self-adjoint $h$-pseudodifferential operator $P$ in the
semi-classical limit ($h\to 0$). If $p$ is the leading symbol, then under
suitable assumptions about the behaviour of $p$ at infinity, we know that the
resolvent $(z-P)^{-1}$ is uniformly bounded for $z$ in any compact set not
intersecting the closure of the range of $p$. Under a subellipticity condition,
we show that the resolvent extends locally inside the range up to a distance
${\cal O}(1)((h\ln \frac{1}{h})^{k/(k+1)})$ from certain boundary points, where
$k\in \{2,4,...\}$. This is a slight improvement of a result by Dencker,
Zworski and the author, and it has recently been obtained by W. Bordeaux
Montrieux in a model situation where $k=2$. The method of proof is different
from the one of Dencker et al, and is based on estimates of an associated
semi-group.


  HIRES will be the high-resolution spectrograph of the European Extremely
Large Telescope at optical and near-infrared wavelengths. It consists of three
fibre-fed spectrographs providing a wavelength coverage of 0.4-1.8 mic (goal
0.35-1.8 mic) at a spectral resolution of ~100,000. The fibre-feeding allows
HIRES to have several, interchangeable observing modes including a SCAO module
and a small diffraction-limited IFU in the NIR. Therefore, it will be able to
operate both in seeing and diffraction-limited modes. ELT-HIRES has a wide
range of science cases spanning nearly all areas of research in astrophysics
and even fundamental physics. Some of the top science cases will be the
detection of bio signatures from exoplanet atmospheres, finding the
fingerprints of the first generation of stars (PopIII), tests on the stability
of Nature's fundamental couplings, and the direct detection of the cosmic
acceleration. The HIRES consortium is composed of more than 30 institutes from
14 countries, forming a team of more than 200 scientists and engineers.


  We demonstrate how different types of $SU(3)$ Heisenberg models can be
implemented with the use of the $p$ orbitals of three dimensional optical
lattices. By considering a Mott insulator with unit filling, the dynamics is
well described by an effective model derived from the perturbative treatment of
the tunneling elements relative to the onsite interaction terms. This yields
systems with degrees of freedom that are generators of the $SU(3)$ group, which
extends the Heisenberg models frequently used to analyze quantum magnetism. Due
to the different character of interactions in the bosonic and fermionic cases,
the choice of atom determines what type of anisotropies will appear in the
couplings of the corresponding effective Hamiltonians. Experimental schemes for
detection and manipulation of these systems are presented, and properties of
the ground states of selected examples are discussed.


  The impact of active galactic nuclei on low-ionization nuclear emission-line
regions (LINERs) remains a vigorous field of study. We present preliminary
results from a study of the mid-infrared atomic emission lines of LINERs with
the Spitzer Space Telescope. We assess the ubiquity and properties of AGN in
LINERs using this data. We discuss what powers the mid-infrared emission lines
and conclude that the answer depends unsurprisingly on the emission line
ionization state and, more interestingly, on the infrared luminosity.


  We define counting classes #P_R and #P_C in the Blum-Shub-Smale setting of
computations over the real or complex numbers, respectively. The problems of
counting the number of solutions of systems of polynomial inequalities over R,
or of systems of polynomial equalities over C, respectively, turn out to be
natural complete problems in these classes. We investigate to what extent the
new counting classes capture the complexity of computing basic topological
invariants of semialgebraic sets (over R) and algebraic sets (over C). We prove
that the problem of computing the (modified) Euler characteristic of
semialgebraic sets is FP_R^{#P_R}-complete, and that the problem of computing
the geometric degree of complex algebraic sets is FP_C^{#P_C}-complete. We also
define new counting complexity classes in the classical Turing model via taking
Boolean parts of the classes above, and show that the problems to compute the
Euler characteristic and the geometric degree of (semi)algebraic sets given by
integer polynomials are complete in these classes. We complement the results in
the Turing model by proving, for all k in N, the FPSPACE-hardness of the
problem of computing the k-th Betti number of the zet of real zeros of a given
integer polynomial. This holds with respect to the singular homology as well as
for the Borel-Moore homology.


  The performance of multi-image alignment, bringing different images into one
coordinate system, is critical in many applications with varied signal-to-noise
ratio (SNR) conditions. A great amount of effort is being invested into
developing methods to solve this problem. Several important questions thus
arise, including: Which are the fundamental limits in multi-image alignment
performance? Does having access to more images improve the alignment?
Theoretical bounds provide a fundamental benchmark to compare methods and can
help establish whether improvements can be made. In this work, we tackle the
problem of finding the performance limits in image registration when multiple
shifted and noisy observations are available. We derive and analyze the
Cram\'er-Rao and Ziv-Zakai lower bounds under different statistical models for
the underlying image. The accuracy of the derived bounds is experimentally
assessed through a comparison to the maximum likelihood estimator. We show the
existence of different behavior zones depending on the difficulty level of the
problem, given by the SNR conditions of the input images. We find that
increasing the number of images is only useful below a certain SNR threshold,
above which the pairwise MLE estimation proves to be optimal. The analysis we
present here brings further insight into the fundamental limitations of the
multi-image alignment problem.


  In this paper, we introduce an alternative approach, namely GEN (Genetic
Evolution Network) Model, to the deep learning models. Instead of building one
single deep model, GEN adopts a genetic-evolutionary learning strategy to build
a group of unit models generations by generations. Significantly different from
the wellknown representation learning models with extremely deep structures,
the unit models covered in GEN are of a much shallower architecture. In the
training process, from each generation, a subset of unit models will be
selected based on their performance to evolve and generate the child models in
the next generation. GEN has significant advantages compared with existing deep
representation learning models in terms of both learning effectiveness,
efficiency and interpretability of the learning process and learned results.
Extensive experiments have been done on diverse benchmark datasets, and the
experimental results have demonstrated the outstanding performance of GEN
compared with the state-of-the-art baseline methods in both effectiveness of
efficiency.


  In this paper, we investigate the necessity of finite blocklength codes in
distributed transmission of independent message sets over channels with
feedback. Previously, it was shown that finite effective length codes are
necessary in distributed transmission and compression of sources. We provide
two examples of three user interference channels with feedback where codes with
asymptotically large effective lengths are sub-optimal. As a result, we
conclude that coded transmission using finite effective length codes is
necessary to achieve optimality. We argue that the sub-optimal performance of
large effective length codes is due to their inefficiency in preserving the
correlation between the inputs to the distributed terminals in the
communication system. This correlation is made available by the presence of
feedback at the terminals and is used as a means for coordination between the
terminals when using finite effective length coding strategies.


  We show, by making conditional measurements on the Einstein-Podolsky-Rosen
(EPR) squeezed vacuum, that one can improve the efficacy of teleportation for
both the position difference, momentum sum and number difference, phase sum
continuous variable teleportation protocols. We investigate the relative
abilities of the standard and conditional EPR states, and show that by
conditioning we can improve the fidelity of teleportation of coherent states
from below to above the $\bar{F} = 2/3$ boundary.


  The modelling of Electronic Health Records (EHRs) has the potential to drive
more efficient allocation of healthcare resources, enabling early intervention
strategies and advancing personalised healthcare. However, EHRs are challenging
to model due to their realisation as noisy, multi-modal data occurring at
irregular time intervals. To address their temporal nature, we treat EHRs as
samples generated by a Temporal Point Process (TPP), enabling us to model what
happened in an event with when it happened in a principled way. We gather and
propose neural network parameterisations of TPPs, collectively referred to as
Neural TPPs. We perform evaluations on synthetic EHRs as well as on a set of
established benchmarks. We show that TPPs significantly outperform their
non-TPP counterparts on EHRs. We also show that an assumption of many Neural
TPPs, that the class distribution is conditionally independent of time, reduces
performance on EHRs. Finally, our proposed attention-based Neural TPP performs
favourably compared to existing models, whilst aligning with real world
interpretability requirements, an important step towards a component of
clinical decision support systems.


  Based on the relativistic Hartree-Fock formalism and one of the most advanced
Lagrangian PKA1, we investigate the properties of the exotic nucleus 48Si. We
found that 48Si may be an atypical nucleus characterized by i) the onset of
doubly magicity, ii) its location at the drip line, iii) the presence of a
doubly semibubble (central depletion of the neutron and proton density
profiles) in the ground state, and iv) the occurrence of pairing reentrance at
finite temperature. These phenomenons are not independent from each others. We
illustrate for instance that the doubly semibubble reduces the spin-orbit
splitting of low-l orbitals and modifies the splitting of relevant pseudospin
partners, favoring N = 34 as a new magic number for neutron rich nuclei. Since
48Si is predicted doubly magic, it could have an extra stability which puts it
at the drip line. Moreover, 48Si may have interesting excited states which may
induce pairing reentrance at finite temperature. While not being new, these
phenomenons are found to serendipitously occur together in 48Si, from our
theoretical calculation. Theoretical nuclear modelings are known to be poorly
predictive in general, and we asset our confidence in the prediction of our
modeling on the fact that the predictions of PKA1 in various regions of the
nuclear chart have systematically been found correct and more specifically in
the region around 48Si, our approach correctly reproduce the known features of
neighboring nuclei. Whether our predictions are confirmed or not, 48Si provides
a concrete benchmark for the understanding of the nature of nuclear forces.


  Precision experiments, such as the search for electric dipole moments of
charged particles using storage rings, demand for an understanding of the spin
dynamics with unprecedented accuracy. The ultimate aim is to measure the
electric dipole moments with a sensitivity up to 15 orders in magnitude better
than the magnetic dipole moment of the stored particles. This formidable task
requires an understanding of the background to the signal of the electric
dipole from rotations of the spins in the spurious magnetic fields of a storage
ring. One of the observables, especially sensitive to the imperfection magnetic
fields in the ring is the angular orientation of stable spin axis. Up to now,
the stable spin axis has never been determined experimentally, and in addition,
the JEDI collaboration for the first time succeeded to quantify the background
signals that stem from false rotations of the magnetic dipole moments in the
horizontal and longitudinal imperfection magnetic fields of the storage ring.
To this end, we developed a new method based on the spin tune response of a
machine to artificially applied longitudinal magnetic fields. This novel
technique, called \textit{spin tune mapping}, emerges as a very powerful tool
to probe the spin dynamics in storage rings. The technique was experimentally
tested in 2014 at the cooler synchrotron COSY, and for the first time, the
angular orientation of the stable spin axis at two different locations in the
ring has been determined to an unprecedented accuracy of better than
$2.8\mu$rad.


  Knowing the 3D motions in a dynamic scene is essential to many vision
applications. Recent progress is mainly focused on estimating the activity of
some specific elements like humans. In this paper, we leverage a neural motion
field for estimating the motion of all points in a multiview setting. Modeling
the motion from a dynamic scene with multiview data is challenging due to the
ambiguities in points of similar color and points with time-varying color. We
propose to regularize the estimated motion to be predictable. If the motion
from previous frames is known, then the motion in the near future should be
predictable. Therefore, we introduce a predictability regularization by first
conditioning the estimated motion on latent embeddings, then by adopting a
predictor network to enforce predictability on the embeddings. The proposed
framework PREF (Predictability REgularized Fields) achieves on par or better
results than state-of-the-art neural motion field-based dynamic scene
representation methods, while requiring no prior knowledge of the scene.


  We present the findings of our participation in the SemEval-2023 Task 10:
Explainable Detection of Online Sexism (EDOS) task, a shared task on offensive
language (sexism) detection on English Gab and Reddit dataset. We investigated
the effects of transferring two language models: XLM-T (sentiment
classification) and HateBERT (same domain -- Reddit) for multi-level
classification into Sexist or not Sexist, and other subsequent
sub-classifications of the sexist data. We also use synthetic classification of
unlabelled dataset and intermediary class information to maximize the
performance of our models. We submitted a system in Task A, and it ranked 49th
with F1-score of 0.82. This result showed to be competitive as it only
under-performed the best system by 0.052% F1-score.


  The notion of the Haagerup approximation property, originally introduced for
von Neumann algebras equipped with a faithful normal tracial state, is
generalized to arbitrary von Neumann algebras. We discuss two equivalent
characterisations, one in terms of the standard form and the other in terms of
the approximating maps with respect to a fixed faithful normal semifinite
weight. Several stability properties, in particular regarding the crossed
product construction are established and certain examples are introduced.