  In this article we investigate consistency of selection in regression models
via the popular Lasso method. Here we depart from the traditional linear
regression assumption and consider approximations of the regression function
$f$ with elements of a given dictionary of $M$ functions. The target for
consistency is the index set of those functions from this dictionary that
realize the most parsimonious approximation to $f$ among all linear
combinations belonging to an $L_2$ ball centered at $f$ and of radius
$r_{n,M}^2$. In this framework we show that a consistent estimate of this index
set can be derived via $\ell_1$ penalized least squares, with a data dependent
penalty and with tuning sequence $r_{n,M}>\sqrt{\log(Mn)/n}$, where $n$ is the
sample size. Our results hold for any $1\leq M\leq n^{\gamma}$, for any
$\gamma>0$.


  We prove that superhigh sets can be jump traceable, answering a question of
Cole and Simpson. On the other hand, we show that such sets cannot be weakly
2-random. We also study the class superhigh$^\Diamond$, and show that it
contains some, but not all, of the noncomputable $K$-trivial sets.


  We obtained optical spectra of the counterpart of the ultraluminous X-ray
source NGC 5408 X-1 using the FORS spectrograph on the VLT. The spectra show
strong high excitation emission lines, He{\sc ii} $\lambda$4686 and [Ne{\sc V}]
$\lambda$3426, indicative of X-ray photoionization. Using the measured X-ray
spectrum as input to a photoionization model, we calculated the relation
between the He{\sc ii} and X-ray luminosities and found that the He{\sc ii}
flux implies a lower bound on the X-ray luminosity of $3 \times 10^{39} \rm erg
s^{-1}$. The [Ne{\sc v}] flux requires a similar X-ray luminosity. After
subtraction of the nebular emission, the continuum appears to have a power-law
form with a spectral slope of $-2.0^{+0.1}_{-0.2}$. This is similar to low-mass
X-ray binaries where the optical spectra are dominated by reprocessing of
X-rays in the outer accretion disk. In one observation, the continuum, He{\sc
ii} $\lambda$4686, and [Ne{\sc V}] $\lambda$3426 fluxes are about 30% lower
than in the other five observations. This implies that part of the line
emission originates within one light-day of the compact object. Fitting the
optical continuum emission and archival X-ray data to an irradiated disk model,
we find that $(6.5 \pm 0.7) \times 10^{-3}$ of the total bolometric luminosity
is thermalized in the outer accretion disk. This is consistent with values
found for stellar-mass X-ray binaries and larger than expected in models of
super-Eddington accretion flows. We find no evidence for absorption lines that
would permit measurement of the radial velocity of the companion star.


  Gender representation in the physical sciences remains inequitable and
continues to lag behind other fields. Even though there exists adequate
documentation regarding programmatic postures and innovations, difficulties
persist within the physics discipline. In this paper, we present innovative,
programmatic implementations over an eight-year period at an undergraduate,
liberal arts physics program. Some of these innovations accord with
nationally-published, `best practices' for undergraduate physics programs,
while others are novel to the program's context. Within this eight-year period,
alterations are separated into curricular, co-curricular, and experiential
elements. Innovations are introduced in some detail, and data are presented
before, during, and after their introduction. While it is currently impossible
to say which elements had the greatest impact, the synergistic combination did
have a positive effect on the program. Not only did the number of total majors
and graduates increase, there was a 200% increase of women degree recipients
compared to the previous ten years, which boosted average graduation rates
above the national average (30% > 20%). Women were retained within the
undergraduate physics major at a higher percentage during this time period when
compared to men in the program. Lastly, these women physics majors maintained
careers in science advancement fields at a rate of ~90% after $\leq5$ years
post-graduation. While this paper presents a singular case study, the purpose
is two-fold: a) to validate quantitatively the work of national physics
organizations within the context of a liberal arts institution, and b) to
suggest that a multi-level approach is most efficacious when considering
programmatic innovations.


  We study the anomalous dynamical scaling of equilibrium correlations in one
dimensional systems. Two different models are compared: the Fermi-Pasta-Ulam
chain with cubic and quartic nonlinearity and a gas of point particles
interacting stochastically through the multiparticle collision dynamics. For
both models -that admit three conservation laws- by means of detailed numerical
simulations we verify the predictions of nonlinear fluctuating hydrodynamics
for the structure factors of density and energy fluctuations at equilibrium.
Despite this, violations of the expected scaling in the currents correlation
are found in some regimes, hindering the observation of the asymptotic scaling
predicted by the theory. In the case of the gas model this crossover is clearly
demonstrated upon changing the coupling constant.


  Effetive field theory is believed to provide a useful framework for
describing low-energy nuclear phenomena in a model-independent fashion. I give
here a brief account of the basic features of this approach, some of its latest
developments, and examples of actual calculations carried out in this
framework.


  In this paper we prove stability estimates of logarithmic type for an inverse
problem consisting in the determination of unknown portions of the boundary of
a domain in $\mathbb{R}^n$, from a knowledge, in a finite time observation, of
overdetermined boundary data for initial boundary value problem for anisotropic
wave equation.


  We investigate the efficiency of an isothermal Brownian work-to-work
converter engine, composed of a Brownian particle coupled to a heat bath at a
constant temperature. The system is maintained out of equilibrium by using two
external time-dependent stochastic Gaussian forces, where one is called load
force and the other is called drive force. Work done by these two forces are
stochastic quantities. The efficiency of this small engine is defined as the
ratio of stochastic work done against load force to stochastic work done by the
drive force. The probability density function as well as large deviation
function of the stochastic efficiency are studied analytically and verified by
numerical simulations.


  Current state-of-the-art models of the solar convection zone consist of
solutions to the Navier-Stokes equations in rotating, 3D spherical shells. Such
models are highly sensitive to the choice of boundary conditions. Here, we
present two suites of simulations differing only in their outer thermal
boundary condition, which is either one of fixed-entropy or
fixed-entropy-gradient. We find that the resulting differential rotation is
markedly different between the two sets. The fixed-entropy-gradient simulations
have strong differential rotation contrast and isocontours tilted along radial
lines (in good agreement with the Sun's interior rotation revealed by
helioseismology), whereas the fixed-entropy simulations have weaker contrast
and contours tilted in the opposite sense. We examine in detail the force
balances in our models and find that the poleward transport of heat by Busse
columns drives a thermal wind responsible for the different rotation profiles.
We conclude that the Sun's strong differential rotation along radial lines may
result from the solar emissivity being invariant with latitude (which is
similar to the fixed-entropy-gradient condition in our models) and the poleward
transport of heat by Busse columns. In future work on convection in the solar
context, we strongly advise modelers to use a fixed-gradient outer boundary
condition.


  We consider properties of solitons in general orbifolds in the algebraic
quantum field theory framework and constructions of solitons in affine and
permutation orbifolds. Under general conditions we show that our construction
gives all the twisted representations of the fixed point subnet. This allows us
to prove a number of conjectures: in the affine orbifold case we clarify the
issue of ``fixed point resolutions''; in the permutation orbifold case we
determine all irreducible representations of the orbifold, and we also
determine the fusion rules in a nontrivial case, which imply an integral
property of chiral data for any completely rational conformal net.


  Similarities between fragile glasses and spin glasses (SG) suggest the study
of frustrated spin model to understand the complex dynamics of glasses above
the glass transition. We consider a frustrated spin model with Ising spins and
s-state Potts spins both with and without disorder. We study the two models by
Monte Carlo simulations in two dimensions. The Potts spins mimic orientational
degrees of freedom and the coupled frustrated Ising spins take into account for
frustrating effects like the geometrical hindrance. We show that in this model
dynamical transitions and crossovers are related to static transitions. In
particular, when disorder is present, as predicted and verified in SG, a
dynamical transition between high-temperatures exponential to low-temperatures
non-exponential correlation functions numerically coincides with the ordering
temperature of the ferromagnetic regions, i.e. the Griffiths temperature
$T_c(s)$, while a crossover between power law growth of correlation times to
Arrhenius law occurs near a Potts transition at $T_p(s)<T_c(s)$. In the model
without disorder, where $T_c(s)$ is not defined, both dynamical transition and
crossover occur at $T_p(s)$. Furthermore the static susceptibility and the
autocorrelation times of quantities depending on Potts spins diverge at
$T_p(s)$. This is reminescent of recent experimental results on glass-forming
liquids.


  Reproducibility is a crucial requirement in scientific research. When results
of research studies and scientific papers have been found difficult or
impossible to reproduce, we face a challenge which is called reproducibility
crisis. Although the demand for reproducibility in Machine Learning (ML) is
acknowledged in the literature, a main barrier is inherent non-determinism in
ML training and inference. In this paper, we establish the fundamental factors
that cause non-determinism in ML systems. A framework, ReproduceML, is then
introduced for deterministic evaluation of ML experiments in a real, controlled
environment. ReproduceML allows researchers to investigate software
configuration effects on ML training and inference. Using ReproduceML, we run a
case study: investigation of the impact of bugs inside ML libraries on
performance of ML experiments. This study attempts to quantify the impact that
the occurrence of bugs in a popular ML framework, PyTorch, has on the
performance of trained models. To do so, a comprehensive methodology is
proposed to collect buggy versions of ML libraries and run deterministic ML
experiments using ReproduceML. Our initial finding is that there is no evidence
based on our limited dataset to show that bugs which occurred in PyTorch do
affect the performance of trained models. The proposed methodology as well as
ReproduceML can be employed for further research on non-determinism and bugs.


  This contribution attempts to determine the $b$-quark pole mass $M_b$ and
\MSbar running mass $\overline{m}_b$ with two different approaches at the
next-to-next-to-leading order (NNLO) corrections. At the first approach, we
derive a relation between the $b$-quark pole mass $M_b$ and its \MSbar running
mass $\overline{m}_b$ at the NNLO corrections based on the perturbative Quantum
Chromo Dynamics (pQCD) predictions. At the second approach, we extract
numerical values of the $b$-quark pole and \MSbar running masses based on the
NNLO phenomenology of H1 and ZEUS Collaborations combined beauty vertex
production experimental data. Then we discuss about the compatibility between
the pQCD theory results and phenomenology approach in determination of the
$b$-quark pole and \MSbar running masses at the NNLO corrections. Also, we
investigate the role and influence of the $b$-quark mass as an extra degree of
freedom added to the input parameters of the Standard Model Lagrangian, on the
improvement of the uncertainty band of the proton parton distribution functions
(PDFs) and particularly on the gluon distribution.


  In this paper we study Green measures for certain classes of random time
change Markov processes where the random time change are inverse subordinators.
We show the existence of the Green measure for these processes under the
condition of the existence of the Green measure of the original Markov
processes and they coincide. Applications to fractional dynamics in given.


  Existing approaches to few-shot learning in NLP rely on large language models
and fine-tuning of these to generalise on out-of-distribution data. In this
work, we propose a simple yet powerful approach to "extreme" few-shot learning,
wherein models are exposed to as little as 4 examples per class, based on
soft-label prototypes that collectively capture the distribution of different
classes across the input domain space. Inspired by previous work (Sucholutsky
et al., 2021) on univariate or simple multivariate (synthetic) data, we propose
a novel approach that is effective on large, high-dimensional and real-world
datasets. We learn soft-label prototypes within a neural framework (DeepSLP)
and we experimentally demonstrate that it achieves superior performance on
31/48 tested tasks and few-shot settings while closely matching the performance
of strong baselines on the rest. We focus on learning previously unseen NLP
tasks from very few examples (4, 8, 16) per label and present an in-depth
analysis of the effectiveness of our approach.


  Precise measurement of the angular deviation of an object is a common task in
science and technology. Many methods use light for this purpose. Some of these
exploit interference effects to achieve technological advantages, such as
amplification effects, or simplified measurement devices. However, all of these
schemes require phase stability to be useful. Here we show theoretically and
experimentally that this drawback can be lifted by utilizing two-photon
interference, which is known to be less sensitive to phase fluctuations. Our
results show that non-classical interference can provide a path towards robust
interferometric sensing, allowing for increased metrological precision in the
presence of phase noise.


  A statistical predictive model in which a high-dimensional time-series
regenerates at the end of each day is used to model road traffic. Due to the
regeneration, prediction is based on a daily modeling using a vector
autoregressive model that combines linearly the past observations of the day.
Due to the high-dimension, the learning algorithm follows from an
L1-penalization of the regression coefficients. Excess risk bounds are
established under the high-dimensional framework in which the number of road
sections goes to infinity with the number of observed days. Considering
floating car data observed in an urban area, the approach is compared to
state-of-the-art methods including neural networks. In addition of being highly
competitive in terms of prediction, it enables the identification of the most
determinant sections of the road network.


  Multi-robot rendezvous and exploration are fundamental challenges in the
domain of mobile robotic systems. This paper addresses multi-robot rendezvous
within an initially unknown environment where communication is only possible
after the rendezvous. Traditionally, exploration has been focused on rapidly
mapping the environment, often leading to suboptimal rendezvous performance in
later stages. We adapt a standard frontier-based exploration technique to
integrate exploration and rendezvous into a unified strategy, with a mechanism
that allows robots to re-visit previously explored regions thus enhancing
rendezvous opportunities. We validate our approach in 3D realistic simulations
using ROS, showcasing its effectiveness in achieving faster rendezvous times
compared to exploration strategies.


  We study the design of scheduling policies to minimize monitoring error for a
collection of correlated sources, where only one source can be observed at any
given time. We model correlated sources as a discrete-time Wiener process,
where the increments are multivariate normal random variables, with a general
covariance matrix that captures the correlation structure between the sources.
Under a Kalman filter-based optimal estimation framework, we show that the
performance of all scheduling policies oblivious to instantaneous error, can be
lower and upper bounded by the weighted sum of Age of Information (AoI) across
the sources for appropriately chosen weights. We use this insight to design
scheduling policies that are only a constant factor away from optimality, and
make the rather surprising observation that AoI-based scheduling that ignores
correlation is sufficient to obtain performance guarantees. We also derive
scaling results that show that the optimal error scales roughly as the square
of the dimensionality of the system, even in the presence of correlation.
Finally, we provide simulation results to verify our claims.


  By scaling the mesonic masses in the Walecka model, to the inverse of the
hadronic effective mass in medium, we generate the Zimanyi-Moszkowski (ZM)
models added to a surface term. For infinite nuclear matter, the surface term
vanishes and this new model becomes equivalent to the usual ZM model. For
finite nuclei calculations, the surface contribution changes the spin-orbit
splitting in the right experimental direction. Calculations for some nuclei are
presented.


  Observations of the expansion rate of the universe at late times disagree by
a factor of 1.5-2 with the prediction of homogeneous and isotropic models based
on ordinary matter and gravity. We discuss how the departure from linearly
perturbed homogeneity and isotropy due to structure formation could explain
this discrepancy. We evaluate the expansion rate in a dust universe which
contains non-linear structures with a statistically homogeneous and isotropic
distribution. The expansion rate is found to increase relative to the exactly
homogeneous and isotropic case by a factor of 1.1-1.3 at some tens of billion
of years. The timescale follows from the cold dark matter transfer function and
the amplitude of primordial perturbations without additional free parameters.


  In this article (after some brief theoretical considerations) a bird-eye view
is presented -with the help of nine figures- of the various experimental
sectors of physics in which Superluminal motions seem to appear. In particular,
a panorama is presented of the experiments with evanescent waves and/or
tunnelling photons, and with the "localized Superluminal solutions" to the
Maxwell equations (e.g., with the so-called X-shaped ones). The present paper
is sketchy, but is followed by a large enough bibliography to allow the
interested reader deepening the preferred topic.


  We create a new, functional calculus, approach to approximation of
C_0-semigroups on Banach spaces. As an application of this approach, we obtain
optimal convergence rates in classical approximation formulas for
C_0-semigroups. In fact, our methods allow one to derive a number of similar
formulas and equip them with sharp convergence rates. As a byproduct, we prove
a new interpolation principle leading to efficient norm estimates in the Banach
algebra of Laplace transforms of bounded measures on the semi-axis.


  Let $\Aa_t$ be the directed quiver of type $\Aa$ with $t$ vertices. For each
dimension vector $d$ there is a dense orbit in the corresponding representation
space. The principal aim of this note is to use just rank conditions to define
the irreducible components in the complement of the dense orbit. Then we
compare this result with already existing ones by Knight and Zelevinsky, and by
Ringel. Moreover, we compare with the fan associated to the quiver $\Aa$ and
derive a new formula for the number of orbits using nilpotent classes. In the
complement of the dense orbit we determine the irreducible components and their
codimension. Finally, we consider several particular examples.


  The remarkable Crab Nebula is powered by an energetic pulsar whose
relativistic wind interacts with the inner parts of the Supernova Remnant
SN1054. Despite low-intensity optical and X-ray variations in the inner Nebula,
the Crab has been considered until now substantially stable at X-ray and
gamma-ray energies. This paradigm has been shattered by the AGILE discovery in
September 2010 of a very intense transient gamma-ray flare of nebular origin.
For the first time, the Crab Nebula was "caught in the act" of accelerating
particles up to 10^15 eV within the shortest timescale ever observed in a
cosmic nebula (1 day or less). Emission between 50 MeV and a few GeV was
detected with a quite hard spectrum within a short timescale. Additional
analysis and recent Crab Nebula data lead to identify a total of four major
flaring gamma-ray episodes detected by AGILE and Fermi during the period
mid-2007/mid-2011. These observations challenge emission models of the pulsar
wind interaction and particle acceleration processes. Indeed, the discovery of
fast and efficient gamma-ray transient emission from the Crab leads to
substantially revise current models of particle acceleration.


  A large proportion of Africa's infrastructure is yet to be built. Where and
how these new buildings are constructed matters since today's decisions will
last for decades. The resulting morphology of cities has lasting implications
for a city's energy needs. Estimating and projecting these needs has always
been challenging in Africa due to the lack of data. Yet, given the sweeping
urbanisation expected in Africa over the next three decades, this obstacle must
be overcome to guide cities towards a trajectory of sustainability and
resilience. Based on the location and surface of nearly 200 million buildings
on the continent, we estimate the inter-building distance of almost six
thousand cities. Buildings' footprint data enables the construction of urban
form indicators to compare African cities' elongation, sprawl and emptiness. We
establish the BASE model, where the mean distance between buildings is a
functional relation to the number of Buildings and their average Area, as well
as the Sprawl and the Elongation of its spatial arrangement. The mean distance
between structures in cities -- our proxy for its energy demands related to
mobility -- grows faster than the square root of its population, resulting from
the combined impact of a sublinear growth in the number of buildings and a
sublinear increase in building size and sprawl. We show that when a city
doubles its population, it triples the energy demand related to commutes.


  Extended Drude model formalism has been successfully utilized for analyzing
optical spectra of strongly correlated electron systems including heavy-fermion
systems and high-$T_c$ superconducting iron pnictides and cuprates.
Furthermore, generalized Allen's formulas has been developed and applied to
extract the electron-boson spectral density function from measured optical data
of high temperature superconductors including cuprates in various material
phases. Here we used a reverse process to obtain various optical quantities
starting from two typical electron-boson spectral density model functions for
three intriguing (normal, pseudogap, and $d$-wave superconducting) material
phases in cuprates. We also assigned the calculated optical results to
designated regions in the phase diagram of hole-doped cuprates and compared
them with the corresponding measured optical spectra of
Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$ (Bi-2212). This comparison suggested that
this way of optical data analysis can be a convincing method to study
correlated electrons in the copper oxide superconductors and other
superconducting systems as well.


  We propose a new quantum-computing scheme using ultracold neutral ytterbium
atoms in an optical lattice. The nuclear Zeeman sublevels define a qubit. This
choice avoids the natural phase evolution due to the magnetic dipole
interaction between qubits. The Zeeman sublevels with large magnetic moments in
the long-lived metastable state are also exploited to address individual atoms
and to construct a controlled-multiqubit gate. Estimated parameters required
for this scheme show that this proposal is scalable and experimentally
feasible.


  This paper gives an analogue to the classical Schur-Weyl duality in the
setting of Deligne categories. Given a finite-dimensional unital vector space V
(i.e. a vector space V with a distinguished non-zero vector 1), we give a
definition of a complex tensor power of V. This is an Ind-object of the Deligne
category Rep(S_t), equipped with a natural action of gl(V).
  This construction allows us to describe a duality between the abelian
envelope of the category Rep(S_t) and a localization of the parabolic category
O for gl(V) associated with the pair (V, 1).
  In particular, we obtain an exact contravariant functor SW from the category
Rep^{ab}(S_t) (the abelian envelope of the category Rep(S_t)) to a certain
quotient \hat{O} of the parabolic category O. This quotient is obtained by
taking the full subcategory consisting of modules of degree t, and localizing
by the subcategory of finite dimensional modules. It turns out that the
contravariant functor SW makes \hat{O} a Serre quotient of the category
Rep^{ab}(S_t)^{op}, and the kernel of SW can be explicitly described.


  We show that when screening corrections are included $ \frac{\partial
F_{2}(x,Q^{2})}{\partial \ln Q^{2}}$ is consistent with the behaviour that one
expects in pQCD. Screening corrections explain the enigma of the Caldwell plot.


  Alfven Eigenmodes are destabilized at the DIII-D pedestal during transient
beta drops in high poloidal beta discharges with internal transport barriers
(ITBs), driven by n=1 external kink modes, leading to energetic particle
losses. There are two different scenarios in the thermal beta recovery phase:
with bifurcation (two instability branches with different frequencies) or
without bifurcation (single instability branch). We use the reduced MHD
equations in a full 3D system, coupled with equations of density and parallel
velocity moments for the energetic particles as well as the geodesic acoustic
wave dynamics, to study the properties of the instabilities observed in the
DIII-D high poloidal beta discharges and identify the conditions to trigger the
bifurcation. The simulations suggest that instabilities with lower frequency in
the bifurcation case are ballooning modes driven at the plasma pedestal, while
the instability branch with higher frequencies are low n (n<4) Toroidal Alfven
Eigenmodes nearby the pedestal. The reverse shear region between the middle and
plasma periphery in the non-bifurcated case avoids the excitation of ballooning
modes at the pedestal, although Toroidal Alfven Eigenmodes and Reverse Shear
Alfven Eigenmodes are unstable in the reverse shear region. The n=1 and n=2
Alfven Eigenmode activity can be suppressed or minimized if the neutral beam
injector (NBI) intensity is lower than the experimental value (betaf < 0.03).
In addition, if the beam energy or neutral beam injector voltage is lower than
in the experiment (Vth,f / VA0 < 0.2), the resonance between beam and thermal
plasma is weaker. The n=3,4,5 and 6 AE activity can't be fully suppressed,
although the growth rate and frequency is smaller for an optimized neutral beam
injector operation regime. In conclusion, AE activity in high poloidal beta
discharges can be minimized for optimized NBI operation regimes.


  We consider a model of an artificial neural network based on
quantum-mechanical particles in $W$ potential. These particles play the role of
neurons in our model. To simulate such a quantum-mechanical system the
Monte-Carlo integration method is used. A form of the self-potential of a
particle as well as two interaction potentials (exciting and inhibiting) are
proposed. Examples of simplest logical elements (such as AND, OR and NOT) are
shown. Further we show an implementation of the simplest convolutional network
in framework of our model.


  We performed analytical calculations of the current-voltage and
strain-voltage response of the heterostructure like "charged SPM tip electrode
/ gap / ionic-semiconductor film" caused by the local changes of (a) ions
concentration (stoichiometry contribution); (b) acceptors (donors) charge state
(recharging contribution via ionic radius variation); (c) free electrons
(holes) concentration (electron-phonon coupling via the deformation potential).
The contribution (b) into the strain-voltage SPM was not calculated previously,
while the contribution (c) was not even predicted before, while our estimations
performed for correlated oxides show that strength of (c) appeared comparable
with (a,b). For the case of ion-blocking tip and substrate electrode mainly the
changes in holes (electrons) concentration contribute into the
voltage-dependent mechanical displacement of the film surface, directly
registered by strain SPM. Thus, we predict that the SPM measurements of the
ionic semiconductor surface displacement could provide important information
about the local changes of the acceptors (donors) charge state and electron
(hole)-phonon correlations via the deformation potential. We obtained the great
variety of the nonlinear static and dynamic current-voltage and strain-voltage
hysteresis loops in the ionic semiconductor thin film with mobile acceptors
(donors) and holes (electrons). Some types of the current-voltage hysteresis
with pronounced memory window and double loops are observed experimentally in
the correlated oxides and resistive switching materials like p-La1-xSrxMnO3-d
and La1-xSrxCoO3-d, while predicted strain-voltage hysteresis of
piezoelectric-like and butterfly-like shape requires experimental justification
by SPM.


  Local chain structure and local environment play an important role in the
dynamics of polymer chains in miscible blends. In general, the friction
coefficients that describe the segmental dynamics of the two components in a
blend differ from each other and from those of the pure melts. In this work, we
investigate polymer blend dynamics with Monte Carlo simulations of a
generalized bond-fluctuation model, where differences in the interaction
energies between non-bonded nearest neighbors distinguish the two components of
a blend. Simulations employing only local moves and respecting a non-bond
crossing condition were carried out for blends with a range of compositions,
densities, and chain lengths. The blends investigated here have long-chain
dynamics in the crossover region between Rouse and entangled behavior. In order
to investigate the scaling of the self-diffusion coefficients, characteristic
chain lengths $N_\mathrm{c}$ are calculated from the packing length of the
chains. These are combined with a local mobility $\mu$ determined from the
acceptance rate and the effective bond length to yield characteristic
self-diffusion coefficients $D_\mathrm{c}=\mu/N_\mathrm{c}$. We find that the
data for both melts and blends collapse onto a common line in a graph of
reduced diffusion coefficients $D/D_\mathrm{c}$ as a function of reduced chain
length $N/N_\mathrm{c}$. The composition dependence of dynamic properties is
investigated in detail for melts and blends with chains of length twenty at
three different densities. For these blends, we calculate friction coefficients
from the local mobilities and consider their composition and pressure
dependence. The friction coefficients determined in this way show many of the
characteristics observed in experiments on miscible blends.


  We present multi-wavelength observations of the centre of RXCJ1504.1-0248 -
the galaxy cluster with the most luminous and relatively nearby cool core at
z~0.2. Although there are several galaxies within 100 kpc of the cluster core,
only the brightest cluster galaxy (BCG), which lies at the peak of the X-ray
emission, has blue colours and strong line-emission. Approximately 80 Msun/yr
of intracluster gas is cooling below X-ray emitting temperatures, similar to
the observed UV star formation rate of ~140 Msun/yr. Most star formation occurs
in the core of the BCG and in a 42 kpc long filament of blue continuum, line
emission, and X-ray emission, that extends southwest of the galaxy. The
surrounding filamentary nebula is the most luminous around any observed BCG.
The number of ionizing stars in the BCG is barely sufficient to ionize and heat
the nebula, and the line ratios indicate an additional heat source is needed.
This heat source can contribute to the H\alpha-deduced star formation rates
(SFRs) in BCGs and therefore the derived SFRs should only be considered upper
limits. AGN feedback can slow down the cooling flow to the observed mass
deposition rate if the black hole accretion rate is of the order of 0.5 Msun/yr
at 10% energy output efficiency. The average turbulent velocity of the nebula
is vturb ~325 km/s which, if shared by the hot gas, limits the ratio of
turbulent to thermal energy of the intracluster medium to less than 6%.


  Phylogenetic networks are rooted, labelled directed acyclic graphs which are
commonly used to represent reticulate evolution. There is a close relationship
between phylogenetic networks and multi-labelled trees (MUL-trees). Indeed, any
phylogenetic network $N$ can be 'unfolded' to obtain a MUL-tree $U(N)$ and,
conversely, a MUL-tree $T$ can in certain circumstances be 'folded' to obtain a
phylogenetic network $F(T)$ that exhibits $T$. In this paper, we study
properties of the operations $U$ and $F$ in more detail. In particular, we
introduce the class of stable networks, phylogenetic networks $N$ for which
$F(U(N))$ is isomorphic to $N$, characterise such networks, and show that that
they are related to the well-known class of tree-sibling networks. We also
explore how the concept of displaying a tree in a network $N$ can be related to
displaying the tree in the MUL-tree $U(N)$. To do this, we develop a
phylogenetic analogue of graph fibrations. This allows us to view $U(N)$ as the
analogue of the universal cover of a digraph, and to establish a close
connection between displaying trees in $U(N)$ and reconciling phylogenetic
trees with networks.


  Quasi-Monte Carlo methods are a way of improving the efficiency of Monte
Carlo methods. Digital nets and sequences are one of the low discrepancy point
sets used in quasi-Monte Carlo methods. This thesis presents the three new
results pertaining to digital nets and sequences: implementing randomized
digital nets, finding the distribution of the discrepancy of scrambled digital
nets, and obtaining better quality of digital nets through evolutionary
computation. Finally, applications of scrambled and non-scrambled digital nets
are provided.


  We study the dynamics of the center of mass of a Brownian particle levitated
in a Paul trap. We focus on the overdamped regime in the context of
levitodynamics, comparing theory with our numerical simulations and
experimental data from a nanoparticle in a Paul trap. We provide an exact
analytical solution to the stochastic equation of motion, expressions for the
standard deviation of the motion, and thermalization times by using the WKB
method under two different limits. Finally, we prove the power spectral density
of the motion can be approximated by that of an Ornstein-Uhlenbeck process and
use the found expression to calibrate the motion of a trapped particle.


  We studied the uniaxial-pressure dependence of the resistivity for
URu$_{2-x}$Fe$_x$Si$_2$ samples with $x$ = 0 and 0.2, which host a hidden order
(HO) and a large-moment antiferromagnetic (LMAFM) phase, respectively. For both
samples, the elastoresistivity $\zeta$ shows a seemingly divergent behavior
above the transition temperature $T_0$ and a quick decrease below it. We found
that the temperature dependence of $\zeta$ for both samples can be well
described by assuming the uniaxial pressure effect on the gap or certain energy
scale except for $\zeta_{(110)}$ of the $x$ = 0 sample, which exhibits a
non-zero residual value at 0 K. We show that this provides a qualitative
difference between the HO and LMAFM phases. Our results suggest that there is
an in-plane anisotropic response to the uniaxial pressure that only exists in
the hidden order state without necessarily breaking the rotational lattice
symmetry.


  The Erd\"os-Moser conjecture states that the Diophantine equation $S_k(m) =
m^k$, where $S_k(m)=1^k+2^k+...+(m-1)^k$, has no solution for positive integers
$k$ and $m$ with $k \geq 2$. We show that stronger conjectures about
consecutive values of the function $S_k$, that seem to be more naturally, imply
the Erd\"os-Moser conjecture.


  We study the one-particle von Neumann entropy of a system of N hard-core
anyons on a ring. The entropy is found to have a clear dependence on the
anyonic parameter which characterizes the generalized fractional statistics
described by the anyons. This confirms the entanglement as a valuable measure
to investigate topological properties of quantum states. Furthermore, we
determine analytically the large N asymptotics of the anyonic one-particle
density matrix. The formula presented here generalizes the Lenard formula
obtained for a system of N hard-core bosons. Finally, we present a numerical
analysis which confirms the analytical results and provides additional insight
into the problem under consideration.


  We have made sensitive milliarcsecond-resolution radio images of the nearby
merger galaxy Arp 299 at four epochs spread over 18 months between 2003 and
2005. The combined data revealed a total of 30 point sources in the two primary
merger nuclei. Twenty-five of these are found in the northeastern nucleus
(component "A"=IC 694) over a region ~100 pc in diameter, while five are in the
southwestern nucleus (component "B1"=NGC 3690) within a region ~30 pc in size.
These objects are interpreted as young supernovae and supernova remnants; the
ratio of the source counts in nuclei A and B1 is approximately equal to the
ratio of their predicted supernova rates. An approximate luminosity function
has been derived for nucleus A, and indicates that it might contain as many as
500-1000 compact radio sources more powerful than Cas A; the integrated flux
density of these sources would be about 20% of the total flux density seen at
lower resolution. A new supernova occurred in nucleus B1 in the first half of
2005, having a peak radio power at least 2,000 times the present power of
Cassiopeia A. This supernova is located within 0.4 pc (projected distance) of
an apparently older supernova remnant, making it very likely that this
indicates the presence of a massive super star cluster within nucleus B1.
Comparison of the typical radio flux densities of our compact radio sources to
the observed X-ray luminosities of nuclei A and B1 indicates that it is
possible that one radio source in each nucleus actually could be associated
with an active galactic nucleus rather than being a supernova remnant.


  We study superconductivity driven by screened Coulomb repulsion in
three-dimensional Luttinger semimetals with a quadratic band touching and
strong spin-orbit coupling. In these semimetals, the Cooper pairs are formed by
spin-3/2 fermions with non-trivial wavefunctions. We numerically solve the
linear Eliashberg equation to obtain the critical temperature of a singlet
s-wave gap function as a function of doping, with account of spin-orbit and
self-energy corrections. In order to understand the underlying mechanism of
superconductivity, we compute the sensitivity of the critical temperature to
changes in the dielectric function $\epsilon(i\Omega_n,q)$. We relate our
results to the plasmon and Kohn-Luttinger mechanisms. Finally, we discuss the
validity of our approach and compare our results to the litterature. We find
good agreement with some bismuth-based half-Heuslers, such as YPtBi, and
speculate on superconductivity in the iridate Pr2Ir2O7.


  In this paper we introduce a novel particle filter scheme for a class of
partially-observed multivariate diffusions. %continuous-time dynamic models
where the %signal is given by a multivariate diffusion process. We consider a
variety of observation schemes, including diffusion observed with error,
observation of a subset of the components of the multivariate diffusion and
arrival times of a Poisson process whose intensity is a known function of the
diffusion (Cox process). Unlike currently available methods, our particle
filters do not require approximations of the transition and/or the observation
density using time-discretisations. Instead, they build on recent methodology
for the exact simulation of the diffusion process and the unbiased estimation
of the transition density as described in \cite{besk:papa:robe:fear:2006}. %In
particular, w We introduce the Generalised Poisson Estimator, which generalises
the Poisson Estimator of \cite{besk:papa:robe:fear:2006}. %Thus, our filters
avoid the systematic biases caused by %time-discretisations and they have
significant computational %advantages over alternative continuous-time filters.
These %advantages are supported theoretically by a A central limit theorem is
given for our particle filter scheme.


  We theoretically study the spin current between two polarized Fermi gases
with repulsive interactions near the itinerant ferromagnetic phase transition.
We consider a two-terminal model where the left reservoir is fixed to be fully
polarized while the polarization of the right reservoir is tuned through a
fictitious magnetic field defined by the chemical-potential difference between
different atomic hyperfine states. We calculate the spectra of the spin-flip
susceptibility function, which displays a magnon dispersion emerging from the
Stoner continuum at low momentum in the ferromagnetic phase. Based on the
spin-flip susceptibility and using Keldysh Green's function formalism, we
investigate the spin current induced by quasiparticle and spin-flip tunneling
processes, respectively, and show their dependence on the polarization bias
between two reservoirs. The one-body (quasiparticle) tunneling demonstrates a
linear dependence with respect to the polarization bias. In contrast, the
spin-flip process manifests a predominantly cubic dependence on the bias. While
indicating an enhanced magnon tunneling in the strong-coupling regime, our
results also demonstrate a characteristic behavior around the critical
repulsive strength for ferromagnetic phase transition at low temperatures.


  Quasi-brittle behavior where macroscopic failure is preceded by stable
damaging and intensive cracking activity is a desired feature of materials
because it makes fracture predictable. Based on a fiber bundle model with
global load sharing we show that blending strength and stiffness disorder of
material elements leads to the stabilization of fracture, i.e. samples which
are brittle when one source of disorder is present, become quasi-brittle as a
consequence of blending. We derive a condition of quasi-brittle behavior in
terms of the joint distribution of the two sources of disorder. Breaking bursts
have a power law size distribution of exponent 5/2 without any crossover to a
lower exponent when the amount of disorder is gradually decreased. The results
have practical relevance for the design of materials to increase the safety of
constructions.


  I outline a signal resampling strategy for aligning event times between time
series trials in contexts where significant event times like onsets and offsets
vary between trials. These variations prevent direct comparisons of trials in
practical contexts as comparisons require equal-length time series (Salari et
al., 2019). Algorithms like dynamic time warping help us quantify these
variations locally but do not apply well to continuous transformations of time
series signals without interpolating or downsampling to add or remove samples
(Jamid, 2004; Eckner, 2014). I show that with consideration for padding and
sampling frequency that sinc interpolation is sufficient to resample parts of
trial intervals to produce equal-length time-locked trials that correlate to
and strongly approximate their unwarped counterparts with minimal interpolation
effects. Specifically I show that interpolation effects can be minimized by
oversampling, selectively interpolating mis-aligned parts of trials with
respect to mean mis-aligned event lengths, and interpolating mis-aligned events
with sufficient zero-padding. Interpolated signals then have a bandlimit well
below the Nyquist frequency and satisfy the Nyquist-Shannon sampling theorem
ensuring perfect reconstructions, and I find that I can track and potentially
counteract resampling effects on signal energy quantities.


  An infinite array of parallel current-carrying wires is known, from the field
of neutral particle optics, to produce an exponentially localized magnetic
field when the current direction is antiparallel in adjacent wires. We show
that a finite array of several tens of superconducting Nb nanowires can produce
a peak magnetic field of 10mT that decays by a factor of 10^4 over a length
scale of 500nm. Such an array is readily manufacturable with current
technology, and is compatible with both semiconductor and superconducting
quantum computer architectures. A series of such arrays can be used to
individually address single single-spin or flux qubits spaced as little as
100nm apart, and can lead to quantum logic gate times of 5ns.


  We investigate whether it is possible to extract the quark mass anomalous
dimension and its scale dependence from the spectrum of the twisted mass Dirac
operator in Lattice QCD. The answer to this question appears to be positive,
provided that one goes to large enough eigenvalues, sufficiently above the
non-perturbative regime. The obtained results are compared to continuum
perturbation theory. By analyzing possible sources of systematic effects, we
find the domain of applicability of the approach, extending from an energy
scale of around 1.5 to 4 GeV. The lower limit is dictated by physics
(non-perturbative effects at low energies), while the upper bound is set by the
ultraviolet cut-off of present-day lattice simulations. The information about
the scale dependence of the anomalous dimension allows also to extract the
value of the $\Lambda_{\overline{\textrm{MS}}}$-parameter of 2-flavour QCD,
yielding the value $303(13)(25)$ MeV, where the first error is statistical and
the second one systematic. We use gauge field configuration ensembles generated
by the European Twisted Mass Collaboration (ETMC) with 2 flavours of dynamical
twisted mass quarks, at 4 lattice spacings in the range between around 0.04 and
0.08 fm.


  Recognizing irregular text in natural scene images is challenging due to the
large variance in text appearance, such as curvature, orientation and
distortion. Most existing approaches rely heavily on sophisticated model
designs and/or extra fine-grained annotations, which, to some extent, increase
the difficulty in algorithm implementation and data collection. In this work,
we propose an easy-to-implement strong baseline for irregular scene text
recognition, using off-the-shelf neural network components and only word-level
annotations. It is composed of a $31$-layer ResNet, an LSTM-based
encoder-decoder framework and a 2-dimensional attention module. Despite its
simplicity, the proposed method is robust and achieves state-of-the-art
performance on both regular and irregular scene text recognition benchmarks.
Code is available at: https://tinyurl.com/ShowAttendRead


  User-generated social media data is constantly changing as new trends
influence online discussion and personal information is deleted due to privacy
concerns. However, most current NLP models are static and rely on fixed
training data, which means they are unable to adapt to temporal change -- both
test distribution shift and deleted training data -- without frequent, costly
re-training. In this paper, we study temporal adaptation through the task of
longitudinal hashtag prediction and propose a non-parametric dense retrieval
technique, which does not require re-training, as a simple but effective
solution. In experiments on a newly collected, publicly available, year-long
Twitter dataset exhibiting temporal distribution shift, our method improves by
64.12% over the best parametric baseline without any of its costly
gradient-based updating. Our dense retrieval approach is also particularly
well-suited to dynamically deleted user data in line with data privacy laws,
with negligible computational cost and performance loss.


  The paper presents a reflectionless stripline filter with reduced dimensions
having a single bandwidth over a wide frequency range. The filter consists of
coupled strip lines and RLC circuits included in the diagonal ports of the
coupled strip lines. Calculations and measurements of the reflectionless
stripline filter layout in the frequency range up to 4.8 GHz have been carried
out. The obtained results show that the dimensions are reduced by a factor of
two compared to previously developed reflectionless stripline filter designs.
It is achieved by folding the coupled lines in the form of a meander formed by
horizontally and vertically arranged conductors on horizontally and vertically
oriented dielectric substrates. The proposed reflectionless stripline filter
allows to solve the problem of improving the mass-dimensional parameters of the
equipment and to provide signal selection with minimum reflection at
out-of-band frequencies. It can be in demand in multichannel systems of
wireless communications, radar, and measurements.


  We present measurements of the star formation efficiency (SFE) in 3D
numerical simulations of driven turbulence in supercritical, ideal-MHD, and
non-magnetic regimes, characterized by their mean normalized mass-to-flux ratio
$\mu$, all with 64 Jeans masses and similar rms Mach numbers ($\sim 10$). In
most cases, the moderately supercritical runs with $\mu = 2.8$ have
significantly lower SFEs than the non-magnetic cases, being comparable to
observational estimates for whole molecular clouds ($\lesssim$ 5% over 4 Myr).
Also, as the mean field is increased, the number of collapsed objects
decreases, and the median mass of the collapsed objects increases. However, the
largest collapsed-object masses systematically occur in the weak-field case
$\mu = 8.8$. The high-density tails of the density histograms in the
simulations are depressed as the mean magnetic field strength is increased.
This suggests that the smaller numbers and larger masses of the collapsed
objects in the magnetic cases may be due to a greater scarcity and lower mean
densities (implying larger Jeans masses) of the collapse candidates. In this
scenario, the effect of a weak field is to reduce the probability of a core
reaching its thermal Jeans mass, even if it is supercritical. We thus suggest
that the SFE may be monotonically reduced as the field strength increases from
zero to subcritical values, rather than there being a discontinuous transition
between the sub- and supercritical regimes, and that a crucial question to
address is whether the turbulence in molecular clouds is driven or decaying,
with current observational and theoretical evidence favoring (albeit
inconclusively) the driven regime.


  In the present work we calculate the theoretical tunneling conductance curves
of SIN junctions involving high-Tc superconductors, for different possible
symmetries of the order parameter (s, d, s+id, s+d, anisotropic s and extended
s). To do so, we solve the real-axis Eliashberg equations in the case of an
half-filled infinite band. We show that some of the peculiar characteristics of
HTSC tunneling curves (dip and hump at eV > Delta, broadening of the gap peak,
zero bias and so on) can be explained in the framework of the Migdal-Eliashberg
theory. The theoretical dI/dV curves calculated for the different symmetries at
T=4 K are then compared to various experimental tunneling data obtained in
optimally-doped BSCCO, TBCO, HBCO, LSCO and YBCO single crystals. To best fit
the experimental data, the scattering by non-magnetic impurities has to be
taken into account, thus limiting the sensitivity of this procedure in
determining the exact gap symmetry of these materials. Finally, the effect of
the temperature on the theoretical tunneling conductance is also discussed and
the curves obtained at T=2 K are compared to those given by the analytical
continuation of the imaginary-axis solution.


  We propose in this paper an architecture for near-duplicate video detection
based on: (i) index and query signature based structures integrating temporal
and perceptual visual features and (ii) a matching framework computing the
logical inference between index and query documents. As far as indexing is
concerned, instead of concatenating low-level visual features in
high-dimensional spaces which results in curse of dimensionality and redundancy
issues, we adopt a perceptual symbolic representation based on color and
texture concepts. For matching, we propose to instantiate a retrieval model
based on logical inference through the coupling of an N-gram sliding window
process and theoretically-sound lattice-based structures. The techniques we
cover are robust and insensitive to general video editing and/or degradation,
making it ideal for re-broadcasted video search. Experiments are carried out on
large quantities of video data collected from the TRECVID 02, 03 and 04
collections and real-world video broadcasts recorded from two German TV
stations. An empirical comparison over two state-of-the-art dynamic programming
techniques is encouraging and demonstrates the advantage and feasibility of our
method.


  We provide two derivations of the baryonic equations that can be
straightforwardly implemented in existing Einstein--Boltzmann solvers. One of
the derivations begins with an action principle, while the other exploits the
conservation of the stress-energy tensor. While our result is manifestly
covariant and satisfies the Bianchi identities, we point out that this is not
the case for the implementation of the seminal work by Ma and Bertschinger and
in the existing Boltzmann codes. We also study the tight coupling approximation
up to the second order without choosing any gauge using the covariant full
baryon equations. We implement the improved baryon equations in a Boltzmann
code and investigate the change in the estimate of cosmological parameters by
performing an MCMC analysis. With the covariantly correct baryon equations of
motion, we find 1% deviation for the best fit values of the cosmological
parameters that should be taken into account. While in this paper, we study the
Lambda-CDM model only, our baryon equations can be easily implemented in other
models and various modified gravity theories.


  We analyze the implications of the microlocal spectrum/Hadamard condition for
states in a (linear) quantum field theory on a globally hyperbolic spacetime
$M$ in the context of a (distributional) initial value formulation. More
specifically, we work in a $3+1$-split $M\cong\mathbb{R}\times\Sigma$ and give
a bound, independent of the spacetime metric, on the wave front sets of the
initial data for a quasi-free Hadamard state in the quantum field theory
defined by a normally hyperbolic differential operator $P$ acting in a vector
bundle $E\stackrel{\pi}{\rightarrow}M$. This aims at a possible way to apply
the concept of Hadamard states within approaches to quantum field
theory/gravity relying on a Hamiltonian formulation, potentially without a
(classical) background metric $g$.


  This paper address the problem of voltage regulation in power distribution
networks with deep penetration of distributed energy resources (DERs) without
any explicit communication between the buses in the network. We cast the
problem as an optimization problem with the objective of minimizing the
distance between the bus voltage magnitudes and some reference voltage profile.
We present an iterative algorithm where each bus updates the reactive power
injection provided by their DER. The update at a bus only depends on the
voltage magnitude at that bus, and for this reason, we call the algorithm a
local control algorithm. We provide sufficient conditions that guarantee the
convergence of the algorithm and these conditions can be checked a priori for a
set of feasible power injections. We also provide necessary conditions
establishing that longer and more heavily loaded networks are inherently more
difficult to control. We illustrate the operation of the algorithm through case
studies involving 8-,34- and 123-bus test distribution systems.


  The importance of accurately quantifying forecast uncertainty has motivated
much recent research on probabilistic forecasting. In particular, a variety of
deep learning approaches has been proposed, with forecast distributions
obtained as output of neural networks. These neural network-based methods are
often used in the form of an ensemble based on multiple model runs from
different random initializations, resulting in a collection of forecast
distributions that need to be aggregated into a final probabilistic prediction.
With the aim of consolidating findings from the machine learning literature on
ensemble methods and the statistical literature on forecast combination, we
address the question of how to aggregate distribution forecasts based on such
deep ensembles. Using theoretical arguments, simulation experiments and a case
study on wind gust forecasting, we systematically compare probability- and
quantile-based aggregation methods for three neural network-based approaches
with different forecast distribution types as output. Our results show that
combining forecast distributions can substantially improve the predictive
performance. We propose a general quantile aggregation framework for deep
ensembles that shows superior performance compared to a linear combination of
the forecast densities. Finally, we investigate the effects of the ensemble
size and derive recommendations of aggregating distribution forecasts from deep
ensembles in practice.


  Only one exoplanet has so far been mapped in both longitude and latitude, but
the James Webb Space Telescope should provide mapping-quality data for dozens
of exoplanets. The thermal phase mapping problem has previously been solved
analytically, with orthogonal maps---spherical harmonics---yielding orthogonal
lightcurves---sinusoids. The eclipse mapping problem, let alone combined
phase+eclipse mapping, does not lend itself to such a neat solution. Previous
efforts have either adopted spherical harmonics, or various ad hoc map
parameterizations, none of which produce orthogonal lightcurves. We use
principal component analysis to construct orthogonal "eigencurves," which we
then use to fit published 8 micron observations of the hot Jupiter HD 189733b.
This approach has a few advantages over previously used techniques: 1) the
lightcurves can be pre-computed, accelerating the fitting process, 2) the
eigencurves are orthogonal to each other, reducing parameter correlations, and
3) the eigencurves are model-independent and are ranked in order of
sensitivity. One notable result of our analysis is that eclipse-only mapping of
HD 189733b is far more sensitive to the central concentration of dayside flux
than to the eastward offset of that hotspot. Mapping can, in principle, suffer
from degeneracies between spatial patterns and orbital parameters. Previous
mapping efforts using these data have either assumed a circular orbit and
precise inclination, or have been pessimistic about the prospects of eclipse
mapping in the face of uncertain orbital parameters. We show that for HD
189733b the combined photometry and radial velocity are sufficiently precise to
retire this concern. Lastly, we present the first map of brightness
temperature, and we quantify the amplitude and longitude offset of the dayside
hotspot.


  We record for reference a detailed description of the automorphism groups of
the groups of order $p^{2} q$, where $p$ and $q$ are distinct primes.


  In recent years, the Renyi entropy has repeatedly been discussed for
characterization of quantum critical states and entanglement. Here, time
evolution of the Renyi entropy is studied. A compact general formula is
presented for the lower bound on the entropy rate.


  This paper proposes a new mechanism for pruning a search game-tree in
computer chess. The algorithm stores and then reuses chains or sequences of
moves, built up from previous searches. These move sequences have a built-in
forward-pruning mechanism that can radically reduce the search space. A typical
search process might retrieve a move from a Transposition Table, where the
decision of what move to retrieve would be based on the position itself. This
algorithm stores move sequences based on what previous sequences were better,
or caused cutoffs. This is therefore position independent and so it could also
be useful in games with imperfect information or uncertainty, where the whole
situation is not known at any one time. Over a small set of tests, the
algorithm was shown to clearly out-perform Transposition Tables, both in terms
of search reduction and game-play results.


  In order for Dirac theory to be gauge invariant it can be shown that the
Schwinger term must be zero. However, it can also be shown that for the vacuum
state to be the lowest energy state the Schwinger term must be nonzero.
Therefore there is an inconsistency in Dirac theory involving the evaluation of
the Schwinger term. This inconsistency is discussed along with a possible way
to resolve it.


  This paper develops sharp bounds on moments of sums of k-wise independent
bounded random variables, under constrained average variance. The result closes
the problem addressed in part in the previous works of Schmidt et al. and
Bellare, Rompel. We The work also discuss discusses other applications of
independent interests, such as asymptotically sharp bounds on binomial moments.


  The application of psychophysiology in human-computer interaction is a
growing field with significant potential for future smart personalised systems.
Working in this emerging field requires comprehension of an array of
physiological signals and analysis techniques.
  Methods to study central nervous system (CNS) are usually expensive and
laborious. However, electroencephalography (EEG) is one of the most affordable
and ambulatory methodologies for CNS research. It is in use in various clinical
studies and have been broadly studied over decades. Despite that the recorded
EEG signals are quite prone to noise and environmental factors it is the most
widely used method in study of brain-computer interaction (BCI). Here we
discuss briefly on various aspects of the recorded signals, their
interpretation, and usage in the field of interaction studies.
  This paper aims to serve as a primer for the novice, enabling rapid
familiarisation with the latest core concepts. We put special emphasis on
everyday human-computer interface applications to distinguish from the more
common clinical or sports uses of psychophysiology.
  This paper is an extract from a comprehensive review of the entire field of
ambulatory psychophysiology, including 12 similar chapters, plus application
guidelines and systematic review. Thus any citation should be made using the
following reference:
  B. Cowley, M. Filetti, K. Lukander, J. Torniainen, A. Henelius, L. Ahonen, O.
Barral, I. Kosunen, T. Valtonen, M. Huotilainen, N. Ravaja, G. Jacucci. The
Psychophysiology Primer: a guide to methods and a broad review with a focus on
human-computer interaction. Foundations and Trends in Human-Computer
Interaction, vol. 9, no. 3-4, pp. 150--307, 2016.


  Quantum gravity is extended to include purely virtual "cloud sectors", which
allow us to define a complete set of point-dependent observables, including a
gauge invariant metric and gauge invariant matter fields, and calculate their
off-shell correlation functions perturbatively. The ordinary on-shell
correlation functions and the $S$ matrix elements are unaffected. Each extra
sector is made of a cloud field, its anticommuting partner, a "cloud-fixing"
function and a cloud Faddeev-Popov determinant. The additional fields are
purely virtual, to ensure that no ghosts propagate. The extension is unitary.
In particular, the off-shell, diagrammatic version of the optical theorem
holds. The one-loop two-point functions of dressed scalars, vectors and
gravitons are calculated. Their absorptive parts are positive, cloud
independent and gauge independent, while they are unphysical if non purely
virtual clouds are used. We illustrate the differences between our approach to
the problem of finding a complete set of observables in quantum gravity and
other approaches available in the literature.


  In this paper we consider the classification of minimal cellular structures
of spaces of topological complexity two under some hypotheses on there graded
cohomological algebra. This continues the method used by M.Grant et al. in [1].


  Prescriptions for electron injection into the diffusive shock acceleration
process are required in many practical considerations of cosmic-ray
astrophysics, particularly in modeling of the synchrotron emission of
astrophysical sources. In particle-in-cell simulations of quasi-parallel
magnetized collisionless shocks, we analyse the evolution of particle spectra.
We find that in the later stages of shock evolution, the initially strong
suprathermal part in the ion spectra fades, thus leaving the spectra composed
of a Maxwellian and a power law. Once the electron and ion spectra flatten and
become parallel, we find that the amounts of cosmic ray ions and electrons
become similar. We make the step towards relating the micro and macro-scale
physics by applying this injection rule to Blasi's semi-analytical model of
non-linear diffusive shock acceleration, in order to obtain the particle
spectra and electron-to-proton ratio $K_{\mathrm{ep}}$ at high energies. By
using shock jump conditions that include the electron heating, we find
$K_{\mathrm{ep}}$ as a function of Mach number. For Mach number $\sim$ 100, our
model finely reproduces the typically observed ratio for Galactic cosmic-rays
$K_{\mathrm{ep}} \sim$ 1:100 in the test particle regime.


  The main goal of this project is to search for p-mode oscillations in a
selected sample of DA white dwarfs near the blue edge of the DAV (g-mode)
instability strip, where the p-modes should be excited following theoretical
models. A set of high quality time-series data on nine targets has been
obtained in 3 photometric bands (Sloan u', g', r') using ULTRACAM at the VLT
with a typical time resolution of a few tens of ms. Such high resolution is
required because theory predicts very short periods, of the order of a second,
for the p-modes in white dwarfs. The data have been analyzed using Fourier
transform and correlation analysis methods. Results: P-modes have not been
detected in any of our targets. The upper limits obtained for the pulsation
amplitude, typically less than 0.1%, are the smallest limits reported in the
literature. The Nyquist frequencies are large enough to fully cover the
frequency range of interest for the p-modes. For the brightest target of our
sample, G 185-32, a p-mode oscillation with a relative amplitude of 5x10**(-4)
would have been easily detected, as shown by a simple simulation. For G 185-32
we note an excess of power below ~2 Hz in all the three nights of observation,
which might be due in principle to tens of low-amplitude close modes. However,
neither correlation analysis nor Fourier transform of the amplitude spectrum
show significant results. We also checked the possibility that the p-modes have
a very short lifetime, shorter than the observing runs, by dividing each run in
several subsets and analyzing these subsets independently. The amplitude
spectra show only a few peaks with S/N ratio higher than 4 sigma but the same
peaks are not detected in different subsets, as we would expect, and we do not
see any indication of frequency spacing. As a secondary result of this project,
... (see the paper)


  Quasars at high redshift provide direct information on the mass growth of
supermassive black holes and, in turn, yield important clues about how the
Universe evolved since the first (Pop III) stars started forming. Yet even
basic questions regarding the seeds of these objects and their growth mechanism
remain unanswered. The anticipated launch of eROSITA and ATHENA is expected to
facilitate observations of high-redshift quasars needed to resolve these
issues. In this paper, we compare accretion-based supermassive black hole
growth in the concordance LCDM model with that in the alternative
Friedmann-Robertson Walker cosmology known as the R_h=ct universe. Previous
work has shown that the timeline predicted by the latter can account for the
origin and growth of the > 10^9 M_sol highest redshift quasars better than that
of the standard model. Here, we significantly advance this comparison by
determining the soft X-ray flux that would be observed for Eddington-limited
accretion growth as a function of redshift in both cosmologies. Our results
indicate that a clear difference emerges between the two in terms of the number
of detectable quasars at redshift z > 6, raising the expectation that the next
decade will provide the observational data needed to discriminate between these
two models based on the number of detected high-redshift quasar progenitors.
For example, while the upcoming ATHENA mission is expected to detect ~0.16
(i.e., essentially zero) quasars at z ~ 7 in R_h=ct, it should detect ~160 in
LCDM---a quantitatively compelling difference.


  Despite their large-scale coverage, cross-domain knowledge graphs invariably
suffer from inherent incompleteness and sparsity. Link prediction can alleviate
this by inferring a target entity, given a source entity and a query relation.
Recent embedding-based approaches operate in an uninterpretable latent semantic
vector space of entities and relations, while path-based approaches operate in
the symbolic space, making the inference process explainable. However, these
approaches typically consider static snapshots of the knowledge graphs,
severely restricting their applicability for evolving knowledge graphs with
newly emerging entities. To overcome this issue, we propose an inductive
representation learning framework that is able to learn representations of
previously unseen entities. Our method finds reasoning paths between source and
target entities, thereby making the link prediction for unseen entities
interpretable and providing support evidence for the inferred link.


  Graph representations of a target domain often project it to a set of
entities (nodes) and their relations (edges). However, such projections often
miss important and rich information. For example, in graph representations used
in missing value imputation, items - represented as nodes - may contain rich
textual information. However, when processing graphs with graph neural networks
(GNN), such information is either ignored or summarized into a single vector
representation used to initialize the GNN. Towards addressing this, we present
CoRGi, a GNN that considers the rich data within nodes in the context of their
neighbors. This is achieved by endowing CoRGi's message passing with a
personalized attention mechanism over the content of each node. This way, CoRGi
assigns user-item-specific attention scores with respect to the words that
appear in an item's content. We evaluate CoRGi on two edge-value prediction
tasks and show that CoRGi is better at making edge-value predictions over
existing methods, especially on sparse regions of the graph.


  For an abelian category $A$ equipped with a torsion pair, we give an explicit
description for the abelian category $B$ introduced by Happel-Reiten-Smalo, and
also for the category of chain complexes $Ch(B)$ and the derived category
$D(B)$ of $B$. We also describe the DG structure on $Ch(B)$. As a consequence,
we find new proofs of certain results of Happel-Reiten-Smalo. The main
ingredient is the category of {\em decorated} complexes.


  We show that the $R_K$ puzzle in LHCb data and the discrepancy in the
anomalous magnetic moment of the muon can be simultaneously explained if a 10
MeV mass $Z^\prime$ boson couples to the muon but not the electron, and that
clear evidence of the nonstandard matter interactions of neutrinos induced by
this coupling may be found at DUNE.


  In this paper we study dynamic backward problems, with the computation of
conditional expectations as a main objective, in a framework where the
(forward) state process satisfies a Volterra type SDE, with fractional Brownian
motion as a typical example. Such processes are neither Markov processes nor
semimartingales, and most notably, they feature a certain time inconsistency
which makes any direct application of Markovian ideas, such as flow properties,
impossible without passing to a path-dependent framework. Our main result is a
functional It\^{o} formula, extending the seminal work of Dupire \cite{Dupire}
to our more general framework. In particular, unlike in \cite{Dupire} where one
needs only to consider the stopped paths, here we need to concatenate the
observed path up to the current time with a certain smooth observable curve
derived from the distribution of the future paths. This new feature is due to
the time inconsistency involved in this paper. We then derive the path
dependent PDEs for the backward problems. Finally, an application to option
pricing in a financial market with rough volatility is presented.


  We present a fast algorithm to calculate Coulomb/exchange integrals of
prolate spheroidal electronic orbitals, which are the exact solutions of the
single-electron, two-center Schr\"odinger equation for diatomic molecules. Our
approach employs Neumann's expansion of the Coulomb repulsion 1/|x-y|, solves
the resulting integrals symbolically in closed form and subsequently performs a
numeric Taylor expansion for efficiency. Thanks to the general form of the
integrals, the obtained coefficients are independent of the particular
wavefunctions and can thus be reused later.
  Key features of our algorithm include complete avoidance of numeric
integration, drafting of the individual steps as fast matrix operations and
high accuracy due to the exponential convergence of the expansions.
  Application to the diatomic molecules O2 and CO exemplifies the developed
methods, which can be relevant for a quantitative understanding of chemical
bonds in general.


  In this work we propose lifted regression/reconstruction networks (LRRNs),
which combine lifted neural networks with a guaranteed Lipschitz continuity
property for the output layer. Lifted neural networks explicitly optimize an
energy model to infer the unit activations and therefore---in contrast to
standard feed-forward neural networks---allow bidirectional feedback between
layers. So far lifted neural networks have been modelled around standard
feed-forward architectures. We propose to take further advantage of the
feedback property by letting the layers simultaneously perform regression and
reconstruction. The resulting lifted network architecture allows to control the
desired amount of Lipschitz continuity, which is an important feature to obtain
adversarially robust regression and classification methods. We analyse and
numerically demonstrate applications for unsupervised and supervised learning.


  Deep neural network (DNN) based machine perception frameworks process the
entire input in a one-shot manner to provide answers to both "what object is
being observed" and "where it is located". In contrast, the "two-stream
hypothesis" from neuroscience explains the neural processing in the human
visual cortex as an active vision system that utilizes two separate regions of
the brain to answer the what and the where questions. In this work, we propose
a machine learning framework inspired by the "two-stream hypothesis" and
explore the potential benefits that it offers. Specifically, the proposed
framework models the following mechanisms: 1) ventral (what) stream focusing on
the input regions perceived by the fovea part of an eye (foveation), 2) dorsal
(where) stream providing visual guidance, and 3) iterative processing of the
two streams to calibrate visual focus and process the sequence of focused image
patches. The training of the proposed framework is accomplished by label-based
DNN training for the ventral stream model and reinforcement learning for the
dorsal stream model. We show that the two-stream foveation-based learning is
applicable to the challenging task of weakly-supervised object localization
(WSOL), where the training data is limited to the object class or its
attributes. The framework is capable of both predicting the properties of an
object and successfully localizing it by predicting its bounding box. We also
show that, due to the independent nature of the two streams, the dorsal model
can be applied on its own to unseen images to localize objects from different
datasets.


  Nonminimal coupling of the inflaton field to the Ricci curvature of spacetime
is generally unavoidable, and the paradigm of inflation should be generalized
by including the corresponding term in the Lagrangian of the inflationary
theory. This paper reports on the status of the programme of generalizing
inflation. First, the problem of finding the correct value (or set of values)
of the coupling constant is analyzed; the result has important consequences for
the success or failure of inflationary scenarios. Then, the slow-roll
approximation to generalized inflation is studied. Both the unperturbed
inflating universe models and scalar/tensor perturbations are discussed, and
open problems are pointed out.


  Knowledge graphs have become a popular formalism for representing entities
and their properties using a graph data model, e.g., the Resource Description
Framework (RDF). An RDF graph comprises entities of the same type connected to
objects or other entities using labeled edges annotated with properties. RDF
graphs usually contain entities that share the same objects in a certain group
of properties, i.e., they match star patterns composed of these properties and
objects. In case the number of these entities or properties in these star
patterns is large, the size of the RDF graph and query processing are
negatively impacted; we refer these star patterns as frequent star patterns. We
address the problem of identifying frequent star patterns in RDF graphs and
devise the concept of factorized RDF graphs, which denote compact
representations of RDF graphs where the number of frequent star patterns is
minimized. We also develop computational methods to identify frequent star
patterns and generate a factorized RDF graph, where compact RDF molecules
replace frequent star patterns. A compact RDF molecule of a frequent star
pattern denotes an RDF subgraph that instantiates the corresponding star
pattern. Instead of having all the entities matching the original frequent star
pattern, a surrogate entity is added and related to the properties of the
frequent star pattern; it is linked to the entities that originally match the
frequent star pattern. We evaluate the performance of our factorization
techniques on several RDF graph benchmarks and compare with a baseline built on
top of gSpan, a state-of-the-art algorithm to detect frequent patterns. The
outcomes evidence the efficiency of proposed approach and show that our
techniques are able to reduce execution time of the baseline approach in at
least three orders of magnitude reducing the RDF graph size by up to 66.56%.


  Alice strings are cosmic strings that turn matter into antimatter. Although
they arise naturally in many GUT's, it has long been believed that because of
the monopole problem they can have no cosmological effects. We show this
conclusion to be false; by using the Langacker-Pi mechanism, monopoles can in
fact be annihilated while Alice strings are left intact. This opens up the
possibility that they can after all contribute to cosmology, and we mention
some particularly important examples.


  In previous works, we devised a differential operator for evaluating typical
integrals appearing in the Cachazo-He-Yuan (CHY) forms and in this paper we
further streamline this method. We observe that at tree level, the number of
free parameters controlling the differential operator depends solely on the
number of external lines, after solving the constraints arising from the
scattering equations. This allows us to construct a reduction matrix that
relates the parameters of a higher-order differential operator to those of a
lower-order one. The reduction matrix is theory-independent and can be obtained
by solving a set of explicitly given linear conditions. The repeated
application of such reduction matrices eventually transforms a given tree-level
CHY-like integral to a prepared form. We also provide analytic expressions for
the parameters associated with any such prepared form at tree level. We finally
give a compact expression for the multidimensional residue for any CHY-like
integral in terms of the reduction matrices. We adopt a dual basis projector
which leads to the CHY-like representation for the non-local
Bern-Carrasco-Johansson (BCJ) numerators at tree level in Yang-Mills theory.
These BCJ numerators are efficiently computed by the improved method involving
the reduction matrix.


  This paper defines the pressure for asymptotically subadditive potentials
under a mistake function, including the measuretheoretical and the topological
versions. Using the advanced techniques of ergodic theory and topological
dynamics, we reveals a variational principle for the new defined topological
pressure without any additional conditions on the potentials and the compact
metric space.


  The perturbative approach to nonlinear Sigma models and the associated
renormalization group flow are discussed within the framework of Euclidean
algebraic quantum field theory and of the principle of general local
covariance. In particular we show in an Euclidean setting how to define Wick
ordered powers of the underlying quantum fields and we classify the freedom in
such procedure by extending to this setting a recent construction of Khavkine,
Melati and Moretti for vector valued free fields. As a by-product of such
classification, we prove that, at first order in perturbation theory, the
renormalization group flow of the nonlinear Sigma model is the Ricci flow.


  I summarize evidence against the hypothesis that `Oumuamua is the artificial
creation of an advanced civilization. An appendix discusses the flaws and
inconsistencies of the "Breakthrough" proposal for laser acceleration of
spacecraft to semi-relativistic speeds. Reality is much more challenging, and
interesting.


  Several recent results on thermodynamics have been obtained using the tools
of quantum information theory and resource theories. So far, the resource
theories utilised to describe thermodynamics have assumed the existence of an
infinite thermal reservoir, by declaring that thermal states at some background
temperature come for free. Here, we propose a resource theory of quantum
thermodynamics without a background temperature, so that no states at all come
for free. We apply this resource theory to the case of many non-interacting
systems, and show that all quantum states are classified by their entropy and
average energy, even arbitrarily far away from equilibrium. This implies that
thermodynamics takes place in a two-dimensional convex set that we call the
energy-entropy diagram. The answers to many resource-theoretic questions about
thermodynamics can be read off from this diagram, such as the efficiency of a
heat engine consisting of finite reservoirs, or the rate of conversion between
two states. This allows us to consider a resource theory which puts work and
heat on an equal footing, and serves as a model for other resource theories.


  We characterize locally Lipschitz mappings and existence of Lipschitz
extensions through a first order nonlinear system of PDEs. We extend this study
to graded group-valued Lipschitz mappings defined on compact Riemannian
manifolds. Through a simple application, we emphasize the connection between
these PDEs and the Rumin complex. We introduce a class of 2-step groups,
satisfying some abstract geometric conditions and we show that Lipschitz
mappings taking values in these groups and defined on subsets of the plane
admit Lipschitz extensions. We present several examples of these groups, called
Allcock groups, observing that their horizontal distribution may have any
codimesion. Finally, we show how these Lipschitz extensions theorems lead us to
quadratic isoperimetric inequalities in all Allcock groups.


  The goal of this project is to predict the opponent's configuration in a
RoboCup SSL environment. For simplicity, a Markov model assumption is made such
that the predicted formation of the opponent team only depends on its current
formation. The field is divided into a grid and a robot state per player is
created with information about its position and its velocity. To gather a more
general sense of what the opposing team is doing, the state also incorporates
the team's average position (centroid). All possible state transitions are
stored in a hash table that requires minimum storage space. The table is
populated with transition probabilities that are learned by reading vision
packages and counting the state transitions regardless of the specific robot
player. Therefore, the computation during the game is reduced to interpreting a
given vision package to assign each player to a state, and looking for the most
likely state it will transition to. The confidence of the predicted team's
formation is the product of each individual player's probability. The project
is noteworthy in that it minimizes the time and space complexity requirements
for opponent's moves prediction.


  We consider volume-constrained minimizers of the fractional perimeter with
the addition of a potential energy in the form of a volume inte- gral. Such
minimizers are solutions of the prescribed fractional curvature problem. We
prove existence and regularity of minimizers under suitable assumptions on the
potential energy, which cover the periodic case. In the small volume regime we
show that minimizers are close to balls, with a quantitative estimate.


  Computing maximum a posteriori (MAP) estimation in graphical models is an
important inference problem with many applications. We present message-passing
algorithms for quadratic programming (QP) formulations of MAP estimation for
pairwise Markov random fields. In particular, we use the concave-convex
procedure (CCCP) to obtain a locally optimal algorithm for the non-convex QP
formulation. A similar technique is used to derive a globally convergent
algorithm for the convex QP relaxation of MAP. We also show that a recently
developed expectation-maximization (EM) algorithm for the QP formulation of MAP
can be derived from the CCCP perspective. Experiments on synthetic and
real-world problems confirm that our new approach is competitive with
max-product and its variations. Compared with CPLEX, we achieve more than an
order-of-magnitude speedup in solving optimally the convex QP relaxation.


  We study the radiative decay $\phi\to\pi^{0}\eta\gamma$ within the framework
of a phenomenological approach in which the contributions of $\rho$-meson,
chiral loop and $a_0$-meson are considered. We analyze the interference effects
between different contributions and utilizing the experimental branching ratio
and invariant $\pi^0\eta$ mass spectrum for $\phi\to\pi^{0}\eta\gamma$ decay we
estimate the branching ratio of $\phi\to a_0\gamma$ decay.


  In all but special circumstances, measurements of time-dependent processes
reflect internal structures and correlations only indirectly. Building
predictive models of such hidden information sources requires discovering, in
some way, the internal states and mechanisms. Unfortunately, there are often
many possible models that are observationally equivalent. Here we show that the
situation is not as arbitrary as one would think. We show that generators of
hidden stochastic processes can be reduced to a minimal form and compare this
reduced representation to that provided by computational mechanics--the
epsilon-machine. On the way to developing deeper, measure-theoretic foundations
for the latter, we introduce a new two-step reduction process. The first step
(internal-event reduction) produces the smallest observationally equivalent
sigma-algebra and the second (internal-state reduction) removes sigma-algebra
components that are redundant for optimal prediction. For several classes of
stochastic dynamical systems these reductions produce representations that are
equivalent to epsilon-machines.


  A simple variational argument based on the Gaussian Effective Potential (GEP)
is put forward to give evidence for mass generation and deconfinement in pure
Yang-Mills SU(N) theory. The GEP analysis shows that the massless gaussian
vacuum of Yang-Mills theory is perturbatively unstable towards a massive
gaussian vacuum, indicating that a massive expansion is the natural choice for
computations in YMT. At finite temperature, the GEP provides an optimal
temperature-dependent mass parameter for the expansion and signals the
occurrence of a weakly first-order phase transition at $T_{c}\approx$ 255 MeV
for $N=3$. The equation of state is found to be in good agreement with the
lattice data. This work is complemented with review material on the standard
and massive expansions of Yang-Mills theory and on the formalism of quantum
field theory at finite temperature. Comparisons are made with lattice results
and numerical tables are provided to support our findings.


  Given a finite group $G$, the generating graph $\Gamma(G)$ of $G$ has as
vertices the (nontrivial) elements of $G$ and two vertices are adjacent if and
only if they are distinct and generate $G$ as group elements. In this paper we
investigate properties about the degrees of the vertices of $\Gamma(G)$ when
$G$ is an alternating group or a symmetric group. In particular, we determine
the vertices of $\Gamma(G)$ having even degree and show that $\Gamma(G)$ is
Eulerian if and only if $n$ and $n-1$ are not equal to a prime number congruent
to 3 modulo 4.


  A small prototype of a finely granulated digital hadron calorimeter with
Resistive Plate Chambers as active elements was exposed to positive pions of 1
>. 16 GeV energy from the Fermilab test beam. The event selection separates
events with mostly non-interacting particles and events with hadronic showers
which initiated in the front part of the calorimeter. The data are compared to
a Monte Carlo simulation of the set-up. The paper concludes with predictions
for the performance of an extended digital hadron calorimeter.


  The evolution of fifth generation (5G) networks needs to support the latest
use cases, which demand robust network connectivity for the collaborative
performance of the network agents, like multi-robot systems and vehicle to
anything (V2X) communication. Unfortunately, the user device's limited
communication range and battery constraint confirm the unfitness of known
robustness metrics suggested for fixed networks, when applied to time-switching
communication graphs. Furthermore, the calculation of most of the existing
robustness metrics involves non-deterministic polynomial-time complexity, and
hence are best-fitted only for small networks. Despite a large volume of works,
the complete analysis of a $\textit{low-complexity}$ temporal robustness metric
for a communication network is absent in the literature, and the present work
aims to fill this gap. More in detail, our work provides a stochastic analysis
of network robustness for a massive machine type communication (mMTC) network.
The numerical investigation corroborates the exactness of the proposed
analytical framework for temporal robustness metric. Along with studying the
impact on network robustness of various system parameters, such as cluster head
(CH) probability, power threshold value, network size, and node failure
probability, we justify the observed trend of numerical results
probabilistically.


  In extension problems of partial graph drawings one is given an incomplete
drawing of an input graph $G$ and is asked to complete the drawing while
maintaining certain properties. A prominent area where such problems arise is
that of crossing minimization. For plane drawings and various relaxations of
these, there is a number of tractability as well as lower-bound results
exploring the computational complexity of crossing-sensitive drawing extension
problems. In contrast, comparatively few results are known on extension
problems for the fundamental and broad class of simple drawings, that is,
drawings in which each pair of edges intersects in at most one point. In fact,
only recently it has been shown that the extension problem of simple drawings
is NP-hard even when the task is to insert a single edge.
  In this paper we present tractability results for the crossing-sensitive
extension problem of simple drawings. In particular, we show that the problem
of inserting edges into a simple drawing is fixed-parameter tractable when
parameterized by the number of edges to insert and an upper bound on newly
created crossings. Using the same proof techniques, we are also able to answer
several closely related variants of this problem, among others the extension
problem for $k$-plane drawings. Moreover, using a different approach, we
provide a single-exponential fixed-parameter algorithm for the case in which we
are only trying to insert a single edge into the drawing.


  The selective number-dependent arbitrary phase (SNAP) gates form a powerful
class of quantum gates, imparting arbitrarily chosen phases to the Fock modes
of a cavity. However, for short pulses, coherent errors limit the performance.
Here we demonstrate in theory and experiment that such errors can be completely
suppressed, provided that the pulse times exceed a specific limit. The
resulting shorter gate times also reduce incoherent errors. Our approach needs
only a small number of frequency components, the resulting pulses can be
interpreted easily, and it is compatible with fault-tolerant schemes.


  We employ the perturbation series expansion for derivation of the reduced
master equations for the three-site Bose-Hubbard model subject to strong atom
losses from the central site. The model describes a condensate trapped in a
triple-well potential subject to externally controlled removal of atoms. We
find that the $\pi$-phase state of the coherent superposition between the side
wells decays via two dissipation channels, the single-boson channel (similar to
the externally applied dissipation) and the boson-pair channel. The quantum
derivation is compared to the classical adiabatic elimination within the
mean-field approximation. We find that the boson-pair dissipation channel is
not captured by the mean-field model, whereas the single-boson channel is
described by it. Moreover, there is a matching condition between the zero-point
energy bias of the side wells and the nonlinear interaction parameter which
separates the regions where either the single-boson or the boson-pair
dissipation channel dominate. Our results indicate that the $M$-site
Bose-Hubbard models, for $M>2$, subject to atom losses may require an analysis
which goes beyond the usual mean-field approximation for correct description of
their dissipative features. This is an important result in view of the recent
experimental works on the single site addressability of condensates trapped in
optical lattices.


  In this letter, the incremental stability of interconnected systems is
discussed. In particular, we consider an interconnection of switched nonlinear
systems. The incremental stability of the switched interconnected system is a
stronger property as compared to conventional stability. Guaranteeing such a
notion of stability for an overall interconnected nonlinear system is
challenging, even if individual subsystems are incrementally stable. Here,
preserving incremental stability for the interconnection is ensured with a set
of sufficient conditions. Contraction theory is used as a tool to achieve
incremental convergence. For the feedback interconnection, the small gain
characterisation is presented for the overall system's incremental stability.
The results are derived for a special case of feedback, i.e., cascade
interconnection. Matrix-measure-based conditions are presented, which are
computationally tractable. Two numerical examples are demonstrated and
supported with simulation results to verify the theoretical claims.


  Gliomas are the most common primary brain tumors, evolving from the cerebral
supportive cells. For clinical follow-up, the evaluation of the preoperative
tumor volume is essential. Volumetric assessment of tumor volume with manual
segmentation of its outlines is a time-consuming process that can be overcome
with the help of computer-assisted segmentation methods. In this paper, a
semi-automatic approach for World Health Organization (WHO) grade IV glioma
segmentation is introduced that uses balloon inflation forces, and relies on
the detection of high-intensity tumor boundaries that are coupled by using
contrast agent gadolinium. The presented method is evaluated on 27 magnetic
resonance imaging (MRI) data sets and the ground truth data of the tumor
boundaries - for evaluation of the results - are manually extracted by
neurosurgeons.


  Using mean-field theory, exact diagonalizations and SU(3) flavour theory, we
have precisely mapped out the phase diagram of the S=1 bilinear-biquadratic
Heisenberg model on the triangular lattice in a magnetic field, with emphasis
on the quadrupolar phases and their excitations. In particular, we show that
ferroquadrupolar order can coexist with short-range helical magnetic order, and
that the antiferroquadrupolar phase is characterized by a remarkable 2/3
magnetization plateau, in which one site per triangle retains quadrupolar order
while the other two are polarized along the field. Implications for actual S=1
magnets are discussed.