  We examine the bound state and scattering problem of a spin-one-half particle
undergone to an Aharonov-Bohm potential in a conical space in the
nonrelativistic limit. The crucial problem of the \delta-function singularity
coming from the Zeeman spin interaction with the magnetic flux tube is solved
through the self-adjoint extension method. Using two different approaches
already known in the literature, both based on the self-adjoint extension
method, we obtain the self-adjoint extension parameter to the bound state and
scattering scenarios in terms of the physics of the problem. It is shown that
such a parameter is the same for both situations. The method is general and is
suitable for any quantum system with a singular Hamiltonian that has bound and
scattering states.


  With the emergence of connected and autonomous vehicles, sensors are
increasingly deployed within cars to support new functionalities. Traffic
generated by these sensors congest traditional intra-car networks, such as CAN
buses. Furthermore, the large amount of wires needed to connect sensors makes
it harder to design cars in a modular way. To alleviate these limitations, we
propose, simulate, and implement a hybrid wired/wireless architecture, in which
each node is connected to either a wired interface or a wireless interface or
both. Specifically, we propose a new protocol, called Hybrid-Backpressure
Collection Protocol (Hybrid-BCP), to efficiently collect data from sensors in
intra-car networks. Hybrid-BCP is backward-compatible with the CAN bus
technology, and builds on the BCP protocol, designed for wireless sensor
networks. Hybrid-BCP achieves high throughput and shows resilience to dynamic
network conditions, including adversarial interferences. Our testbed
implementation, based on CAN and ZigBee transceivers, demonstrates the load
balancing and routing functionalities of Hybrid-BCP and its resilience to DoS
attacks. We further provide simulation results, obtained with the ns-3
simulator and based on real intra-car RSSI traces, that compare between the
performance of Hybrid-BCP and a tree-based collection protocol. Notably, the
simulations show that Hybrid-BCP can achieve the same performance as the
tree-based protocol while reducing the radio transmission power by a factor of
10.


  We investigate the existence of self-dual solitons with internal structure in
a gauged $O(3)$ nonlinear sigma model immersed in a dielectric medium generated
by a real scalar field (dubbed the source field). We consider rotationally
symmetric configurations and applying the {Bogomol'nyi-Prasad-Sommerfield}
formalism to obtain the energy lower bound and the respective {first-order
differential equations (or self-dual equations).} By solving such a system of
equations for three different dielectric media, we find the internal structure
generates relevant changes in the soliton profiles when compared with the ones
obtained without the presence of the dielectric medium.


  We present a new methodology to determine the expansion history of the
Universe analyzing the spectral properties of early type galaxies (ETG). We
found that for these galaxies the 4000\AA break is a spectral feature that
correlates with the relative ages of ETGs. In this paper we describe the
method, explore its robustness using theoretical synthetic stellar population
models, and apply it using a SDSS sample of $\sim$14 000 ETGs. Our motivation
to look for a new technique has been to minimise the dependence of the cosmic
chronometer method on systematic errors. In particular, as a test of our
method, we derive the value of the Hubble constant $H_0 = 72.6 \pm 2.8$ (stat)
$\pm2.3$ (syst) (68% confidence), which is not only fully compatible with the
value derived from the Hubble key project, but also with a comparable error
budget. Using the SDSS, we also derive, assuming w=constant, a value for the
dark energy equation of state parameter $w = -1 \pm 0.2$ (stat) $\pm0.3$
(syst). Given the fact that the SDSS ETG sample only reaches $z \sim 0.3$, this
result shows the potential of the method. In future papers we will present
results using the high-redshift universe, to yield a determination of H(z) up
to $z \sim 1$.


  It is classically known that a real cubic surface in the real projective
3-space cannot have more than one solitary point (locally given by
x^2+y^2+z^2=0) whereas it can have up to four nodes (x^2+y^2-z^2=0). We show
that on any surface of degree at least 3 in the real projective 3-space, the
maximum possible number of solitary points is strictly smaller than the maximum
possible number of nodes. Conversely, we adapt a construction of Chmutov to
obtain surfaces with many solitary points by using a refined version of
Brusotti's theorem. Finally, we adapt this construction to get real algebraic
surfaces with many singular points of type $A_{2k-1}^\smbullet$ for all $k\ge
1$.


  During these last decades, our knowledge of evolutionary and structural
properties of stars of different mass and chemical composition is significantly
improved. This result has been achieved as a consequence of our improved
capability in understanding and describing the physical behavior of matter in
the different thermal regimes characteristic of the various stellar mass ranges
and evolutionary stages. This notwithstanding, current generation of stellar
models is still affected by significant and, usually, not negligible
uncertainties. These uncertainties are related to our poor knowledge of some
physical proceses occurring in the real stars such as, for instance, some
thermodynamical processes, nuclear reaction rates, as well as the efficiency of
mixing processes. These drawbacks of stellar models have to be properly taken
into account when comparing theory with observations in order to derive
relevant information about the properties of both resolved and unresolved
stellar populations. On the other hand, observations of both field and cluster
stars can provide fundamental benchmarks for constraining the reliability and
accuracy of the theoretical framework. In the following we review some
important evolutionary and structural properties of very-low and low-mass
stars, as well as the most important uncertainties affecting the stellar models
for such stars. We show what are the main sources of uncertainty along the main
evolutionary stages, and discuss the present level of agreement between theory
and observations.


  Click-Through Rate (CTR) prediction holds a pivotal place in online
advertising and recommender systems since CTR prediction performance directly
influences the overall satisfaction of the users and the revenue generated by
companies. Even so, CTR prediction is still an active area of research since it
involves accurately modelling the preferences of users based on sparse and
high-dimensional features where the higher-order interactions of multiple
features can lead to different outcomes.
  Most CTR prediction models have relied on a single fusion and interaction
learning strategy. The few CTR prediction models that have utilized multiple
interaction modelling strategies have treated each interaction to be
self-contained. In this paper, we propose a novel model named STEC that reaps
the benefits of multiple interaction learning approaches in a single unified
architecture. Additionally, our model introduces residual connections from
different orders of interactions which boosts the performance by allowing lower
level interactions to directly affect the predictions. Through extensive
experiments on four real-world datasets, we demonstrate that STEC outperforms
existing state-of-the-art approaches for CTR prediction thanks to its greater
expressive capabilities.


  This paper introduces the localized sparsifying preconditioner for the
pseudospectral approximations of indefinite systems on periodic structures. The
work is built on top of the recently proposed sparsifying preconditioner with
two major modifications. First, the local potential information is utilized to
improve the accuracy of the preconditioner. Second, an FFT based method to
compute the local stencil is proposed to reduce the setup time of the
algorithm. Numerical results show that the iteration number of this improved
method grows only mildly as the problem size grows, which implies that solving
pseudospectral approximation systems is computationally as efficient as solving
sparse systems, up to a mildly growing factor.


  We prove that the categories of Gelfand-Zeitlin modules of
$\mathfrak{g}=\mathfrak{gl}_n$ and Whittaker modules associated with a
semi-simple complex finite-dimensional algebra $\mathfrak{g}$ are extension
full in the category of all $\mathfrak{g}$-modules. This is used to estimate
and in some cases determine the global dimension of blocks of the categories of
Gelfand-Zeitlin and Whittaker modules.


  We present results from a search for gravitational-wave bursts coincident
with a set of two core-collapse supernovae observed between 2007 and 2011. We
employ data from the Laser Interferometer Gravitational-wave Observatory
(LIGO), the Virgo gravitational-wave observatory, and the GEO 600
gravitational-wave observatory. The targeted core-collapse supernovae were
selected on the basis of (1) proximity (within approximately 15 Mpc), (2)
tightness of observational constraints on the time of core collapse that
defines the gravitational-wave search window, and (3) coincident operation of
at least two interferometers at the time of core collapse. We find no plausible
gravitational-wave candidates. We present the probability of detecting signals
from both astrophysically well-motivated and more speculative
gravitational-wave emission mechanisms as a function of distance from Earth,
and discuss the implications for the detection of gravitational waves from
core-collapse supernovae by the upgraded Advanced LIGO and Virgo detectors.


  We investigate the problem of pointwise convergence of the family of
non-linear integral operators: \begin{equation} L_\lambda(f,x) = \int_a^b
\sum_{m=1}^N f^m(t) K_{\lambda ,m}(x,t) dt, \end{equation} where $\lambda $ is
a real parameters, $K_{\lambda ,m}(x,t)$ is non-negative kernel and $f$ is the
function in $L_{1}(a,b)$. We consider two cases where $% (a,b)$ is a finite
interval and when is the whole real axis.


  Problems involving boundary conditions on corrugated surfaces are relevant to
understand nature, since, at some scale, surfaces manifest corrugations that
have to be taken into account. In introductory level electromagnetism courses,
a very common and fundamental exercise is to solve Poisson's equation for a
point charge in the presence of an infinity perfectly conducting planar
surface, which is usually done by image method. Clinton, Esrick and Sacks
[Phys. Rev. B 31, 7540 (1985)] added corrugation to this surface, and solved
the problem by a perturbative analytical calculation of the corresponding
Green's function. In the present paper, we make a detailed pedagogical review
of this calculation, aiming to popularize their results. We also present an
original contribution, extending this perturbative approach to solve the
Laplace's equation for the electrostatic potential for a corrugated neutral
conducting cylinder in the presence of a uniform electric field (without
corrugation, this is another very common model considered as an exercise in
electromagnetism courses). All these calculations can be used as pedagogical
examples of the application of the present perturbative approach in
electromagnetism courses.


  This paper concerns the final value problem for the heat equation under the
homogeneous Neumann condition on the boundary of a smooth open set in Euclidean
space. The problem is here shown to be isomorphically well posed in the sense
that there exists a linear homeomorphism between suitably chosen Hilbert spaces
containing the solutions and the data, respectively. This improves a recent
work of the author, in which the problem was proven well-posed in the original
sense of Hadamard under an additional assumption of H\"older continuity of the
source term. The point of departure is an abstract analysis in spaces of vector
distributions of final value problems generated by coercive Lax--Milgram
operators, yielding isomorphic well-posedness for such problems. Hereby the
data space is the graph normed domain of an unbounded operator that maps final
states to the corresponding initial states, resulting in a non-local
compatibility condition on the data. As a novelty, a stronger version of the
compatibility condition is introduced with the purpose of characterising the
data that yield solutions having the regularity property of being square
integrable in the generator's graph norm (instead of its form domain norm).
This result allows a direct application to the considered inverse Neumann heat
problem.


  We study the dynamics near infinity of polynomial mappings $f$ in
$\mathbb{C}^2$. We assume that $f$ has indeterminacy points and is non constant
on the line at infinity $L_\infty$. If $L_\infty$ is $f$-attracting, we
decompose the Green current along itineraries defined by the indeterminacy
points and their preimages. The symbolic dynamics that arises is a subshift on
an infinite alphabet.


  We present high-order, fully explicit projective integration schemes for
nonlinear collisional kinetic equations such as the BGK and Boltzmann equation.
The methods first take a few small (inner) steps with a simple, explicit method
(such as direct forward Euler) to damp out the stiff components of the
solution. Then, the time derivative is estimated and used in an (outer)
Runge-Kutta method of arbitrary order. The procedure can be recursively
repeated on a hierarchy of projective levels to construct telescopic projective
integration methods. Based on the spectrum of the linearized collision
operator, we deduce that the computational cost of the method is essentially
independent of the stiffness of the problem: with an appropriate choice of
inner step size, the time step restriction on the outer time step, as well as
the number of inner time steps, is independent of the stiffness of the
(collisional) source term. In some cases, the number of levels in the
telescopic hierarchy depends logarithmically on the stiffness. We illustrate
the method with numerical results in one and two spatial dimensions.


  The weak lensing power spectrum carries cosmological information via its
dependence on the growth of structure and on geometric factors. Since much of
the cosmological information comes from scales affected by nonlinear
clustering, measurements of the lensing power spectrum can be degraded by
non-Gaussian covariances. Recently there have been conflicting studies about
the level of this degradation. We use the halo model to estimate it and include
new contributions related to the finite size of lensing surveys, following
Rimes and Hamilton's study of 3D simulations. We find that non-Gaussian
correlations between different multipoles can degrade the cumulative
signal-to-noise for the power spectrum amplitude by up to a factor of 2 (or 5
for a worst-case model that exceeds current N-body simulation predictions).
However, using an eight-parameter Fisher analysis we find that the marginalized
errors on individual parameters are degraded by less than 10% (or 20% for the
worst-case model). The smaller degradation in parameter accuracy is primarily
because: individual parameters in a high-dimensional parameter space are
degraded much less than the volume of the full Fisher ellipsoid; lensing
involves projections along the line of sight, which reduce the non-Gaussian
effect; some of the cosmological information comes from geometric factors which
are not degraded at all. We contrast our findings with those of Lee & Pen
(2008) who suggested a much larger degradation in information content. Finally,
our results give a useful guide for exploring survey design by giving the
cosmological information returns for varying survey area, depth and the level
of some systematic errors.


  We consider a toy model with flat thin branes embedded in a 5-dimensional
Weyl integrable manifold, where the geometric Weyl scalar provides the material
that constitute the brane configurations. The brane configuration is similar to
the Randall-Sundrum model. However, it is found that the massless graviton is
localized on the brane with negative tension. So in order to solve the gauge
hierarchy problem our world should be confined on the positive tension brane,
and this is crucial to reproduce a correct Friedmann-like equation on the
brane. The spacings of graviton mass spectrum are very tiny, but these massive
gravitons are hidden in low energy experiments because they are weakly coupled
with matter on the brane.


  Expert networks are formed by a group of expert-professionals with different
specialties to collaboratively resolve specific queries posted to the network.
In such networks, when a query reaches an expert who does not have sufficient
expertise, this query needs to be routed to other experts for further
processing until it is completely solved; therefore, query answering efficiency
is sensitive to the underlying query routing mechanism being used. Among all
possible query routing mechanisms, decentralized search, operating purely on
each expert's local information without any knowledge of network global
structure, represents the most basic and scalable routing mechanism, which is
applicable to any network scenarios even in dynamic networks. However, there is
still a lack of fundamental understanding of the efficiency of decentralized
search in expert networks. In this regard, we investigate decentralized search
by quantifying its performance under a variety of network settings. Our key
findings reveal the existence of network conditions, under which decentralized
search can achieve significantly short query routing paths (i.e., between
$O(\log n)$ and $O(\log^2 n)$ hops, $n$: total number of experts in the
network). Based on such theoretical foundation, we further study how the unique
properties of decentralized search in expert networks is related to the
anecdotal small-world phenomenon. In addition, we demonstrate that
decentralized search is robust against estimation errors introduced by
misinterpreting the required expertise levels. To the best of our knowledge,
this is the first work studying fundamental behaviors of decentralized search
in expert networks. The developed performance bounds, confirmed by real
datasets, are able to assist in predicting network performance and designing
complex expert networks.


  Regularization of damped motion under central forces in two and
three-dimensions are investigated and equivalent, undamped systems are
obtained. The dynamics of a particle moving in $\frac{1}{r}$ potential and
subjected to a damping force is shown to be regularized a la Levi-Civita. We
then generalize this regularization mapping to the case of damped motion in the
potential $r^{-\frac{2N}{N+1}}$. Further equation of motion of a damped Kepler
motion in 3-dimensions is mapped to an oscillator with inverted sextic
potential and couplings, in 4-dimensions using Kustaanheimo-Stiefel
regularization method. It is shown that the strength of the sextic potential is
given by the damping co-efficient of the Kepler motion. Using homogeneous
Hamiltonian formalism, we establish the mapping between the Hamiltonian of
these two models. Both in 2 and 3-dimensions, we show that the regularized
equation is non-linear, in contrast to undamped cases. Mapping of a particle
moving in a harmonic potential subjected to damping to an undamped system with
shifted frequency is then derived using Bohlin-Sudman transformation.


  We have carried out 21 cm radio continuum observations of 16 UC HII regions
using the VLA (D-array) in search of associated extended emission. We have also
observed H76$_\alpha$ recombination line towards all the sources and
He76$_\alpha$ line at the positions with strong H76$_\alpha$ line emission. The
UC HII regions have simple morphologies and large (>10) ratios of single-dish
to VLA fluxes. Extended emission was detected towards all the sources. The
extended emission consists of one to several compact components and a diffuse
extended envelope. All the UC HII regions but two are located in the compact
components, where the UC HII regions always correspond to their peaks. The
compact components with UC HII regions are usually smaller and denser than
those without UC HII regions. Our recombination line observations indicate that
the ultracompact, compact, and extended components are physically associated.
The UC HII regions and their associated compact components are likely to be
ionized by the same sources on the basis of the morphological relations
mentioned above. This suggests that almost all of the observed UC HII regions
are not `real' UC HII regions and that their actual ages are much greater than
their dynamical age (<10000 yr). We find that most of simple UC HII regions
previously known have large ratios of single-dish to VLA fluxes, similar to our
sources. Therefore, the `age problem' of UC HII regions does not seem to be as
serious as earlier studies argued. We present a simple model that explains
extended emission around UC HII regions. Some individual sources are discussed.


  A multilayer network approach combines different network layers, which are
connected by interlayer edges, to create a single mathematical object. These
networks can contain a variety of information types and represent different
aspects of a system. However, the process for selecting which information to
include is not always straightforward. Using data on two agonistic behaviors in
a captive population of monk parakeets (Myiopsitta monachus), we developed a
framework for investigating how pooling or splitting behaviors at the scale of
dyadic relationships (between two individuals) affects individual- and
group-level social properties. We designed two reference models to test whether
randomizing the number of interactions across behavior types results in similar
structural patterns as the observed data. Although the behaviors were
correlated, the first reference model suggests that the two behaviors convey
different information about some social properties and should therefore not be
pooled. However, once we controlled for data sparsity, we found that the
observed measures corresponded with those from the second reference model.
Hence, our initial result may have been due to the unequal frequencies of each
behavior. Overall, our findings support pooling the two behaviors. Awareness of
how selected measurements can be affected by data properties is warranted, but
nonetheless our framework disentangles these efforts and as a result can be
used for myriad types of behaviors and questions. This framework will help
researchers make informed and data-driven decisions about which behaviors to
pool or separate, prior to using the data in subsequent multilayer network
analyses.


  We have studied the pressure dependence of the magnetization of single
crystalline CeSi_1.81. At ambient pressure ferromagnetism develops below T_C =
9.5 Below ~ 5 K an additional shoulder in low-field hysteresis loops and a
metamagnetic crossover around 4 T suggest the appearance of an additional
magnetic modulation to the ferromagnetic state. The suppression of the magnetic
order in CeSi_1.81 as function of temperature at ambient pressure and as
function of pressure at low temperature are in remarkable qualitative
agreement. The continuous suppression of the ordered moment at p ~ 13.1 kbar
suggests the existence of a ferromagnetic quantum critical point in this
material.


  We propose and apply two methods to estimate pupil plane phase
discontinuities for two realistic scenarios on VLT and Keck. The methods use
both Phase Diversity and a form of image sharpening. For the case of VLT, we
simulate the `low wind effect' (LWE) which is responsible for focal plane
errors in the SPHERE system in low wind and good seeing conditions. We
successfully estimate the simulated LWE using both methods, and show that they
are complimentary to one another. We also demonstrate that single image Phase
Diversity (also known as Phase Retrieval with diversity) is also capable of
estimating the simulated LWE when using the natural de-focus on the SPHERE/DTTS
imager. We demonstrate that Phase Diversity can estimate the LWE to within 30
nm RMS WFE, which is within the allowable tolerances to achieve a target SPHERE
contrast of 10$^{-6}$. Finally, we simulate 153 nm RMS of piston errors on the
mirror segments of Keck and produce NIRC2 images subject to these effects. We
show that a single, diverse image with 1.5 waves (PV) of focus can be used to
estimate this error to within 29 nm RMS WFE, and a perfect correction of our
estimation would increase the Strehl ratio of a NIRC2 image by 12\%


  Gait as a biometric property for person identification plays a key role in
video surveillance and security applications. In gait recognition, normally,
gait feature such as Gait Energy Image (GEI) is extracted from one full gait
cycle. However in many circumstances, such a full gait cycle might not be
available due to occlusion. Thus, the GEI is not complete giving rise to a
degrading in gait-based person identification rate. In this paper, we address
this issue by proposing a novel method to identify individuals from gait
feature when a few (or even single) frame(s) is available. To do so, we propose
a deep learning-based approach to transform incomplete GEI to the corresponding
complete GEI obtained from a full gait cycle. More precisely, this
transformation is done gradually by training several auto encoders
independently and then combining these as a uniform model. Experimental results
on two public gait datasets, namely OULP and Casia-B demonstrate the validity
of the proposed method in dealing with very incomplete gait cycles.


  We develop an analytic model to quantitatively describe the evolution of
superconducting cosmic string networks. Specifically, we extend the
velocity-dependent one-scale (VOS) model to incorporate arbitrary currents and
charges on cosmic string worldsheets under two main assumptions, the validity
of which we also discuss. We derive equations that describe the string network
evolution in terms of four macroscopic parameters: the mean string separation
(or alternatively the string correlation length) and the root mean square (RMS)
velocity which are the cornerstones of the VOS model, together with parameters
describing the averaged timelike and spacelike current contributions. We show
that our extended description reproduces the particular cases of wiggly and
chiral cosmic strings, previously studied in the literature. This VOS model
enables investigation of the evolution and possible observational signatures of
superconducting cosmic string networks for more general equations of state, and
these opportunities will be exploited in a companion paper.


  Working within the context of the minimal supersymmetric standard model, we
compare current bounds from quark flavor changing processes with current and
upcoming bounds on lepton flavor violation. We assume supersymmetry breaking
approximately respects CP invariance. Under the further assumption that flavor
violating insertions in the quark and lepton scalar masses are comparable, we
explore when lepton flavor violation provides the strongest probe of new
physics. We quote results both for spectra with all superpartners near the TeV
scale and where scalars are multi-TeV. Constraints from quark flavor changing
neutral currents are in many cases already stronger than those expected from
future lepton flavor violation bounds, but large regions of parameter space
remain where the latter could provide a discovery mode for supersymmetry.


  The appearance of travelling-wave-type solutions in pipe Poiseuille flow that
are disconnected from the basic parabolic profile is numerically studied in
detail. We focus on solutions in the 2-fold azimuthally-periodic subspace
because of their special stability properties, but relate our findings to other
solutions as well. Using time-stepping, an adapted Krylov-Newton method and
Arnoldi iteration for the computation and stability analysis of relative
equilibria, and a robust pseudo-arclength continuation scheme we unfold a
double-zero (Takens-Bogdanov) bifurcating scenario as a function of Reynolds
number (Re) and wavenumber (k). This scenario is extended, by the inclusion of
higher order terms in the normal form, to account for the appearance of
supercritical modulated waves emanating from the upper branch of solutions at a
degenerate Hopf bifurcation. These waves are expected to disappear in
saddle-loop bifurcations upon collision with lower-branch solutions, thereby
leaving stable upper-branch solutions whose subsequent secondary bifurcations
could contribute to the formation of the phase space structures that are
required for turbulent dynamics at higher Re.


  We calculate the magnetisation relaxation in the short-time regime for an
ensemble of nanomagnets in the presence of a low-frequency external AC biasing
field, at temperatures lower than the magnetic anisotropy energy of the
individual nanomagnets. It is then found that the relaxation is strongly
affected by AC fields with amplitude larger than that of the $T_2$ fluctuations
in the nuclear field. This will allow experimental probing of the nuclear spin
relaxation mechanism.


  The ever-increasing sensor service, though opening a precious path and
providing a deluge of earth system data for deep-learning-oriented earth
science, sadly introduce a daunting obstacle to their industrial level
deployment. Concretely, earth science systems rely heavily on the extensive
deployment of sensors, however, the data collection from sensors is constrained
by complex geographical and social factors, making it challenging to achieve
comprehensive coverage and uniform deployment. To alleviate the obstacle,
traditional approaches to sensor deployment utilize specific algorithms to
design and deploy sensors. These methods dynamically adjust the activation
times of sensors to optimize the detection process across each sub-region.
Regrettably, formulating an activation strategy generally based on historical
observations and geographic characteristics, which make the methods and
resultant models were neither simple nor practical. Worse still, the complex
technical design may ultimately lead to a model with weak generalizability. In
this paper, we introduce for the first time the concept of spatio-temporal data
dynamic sparse training and are committed to adaptively, dynamically filtering
important sensor distributions. To our knowledge, this is the first proposal
(termed DynST) of an industry-level deployment optimization concept at the data
level. However, due to the existence of the temporal dimension, pruning of
spatio-temporal data may lead to conflicts at different timestamps. To achieve
this goal, we employ dynamic merge technology, along with ingenious dimensional
mapping to mitigate potential impacts caused by the temporal aspect. During the
training process, DynST utilize iterative pruning and sparse training,
repeatedly identifying and dynamically removing sensor perception areas that
contribute the least to future predictions.


  Ranked near the top of the long list of exciting discoveries made with NASA's
Kepler photometer is the detection of transiting circumbinary planets. In just
over a year the number of such planets went from zero to seven, including a
multi-planet system with one of the planets in the habitable zone (Kepler-47).
We are quickly learning to better detect and characterize these planets,
including the recognition of their transit timing and duration variation
"smoking gun" signature. Even with only a handful of such planets, some
exciting trends are emerging.


  We prove a lower bound for the $k$-th Steklov eigenvalues in terms of an
isoperimetric constant called the $k$-th Cheeger-Steklov constant in three
different situations: finite spaces, measurable spaces, and Riemannian
manifolds. These lower bounds can be considered as higher order Cheeger type
inequalities for the Steklov eigenvalues. In particular it extends the Cheeger
type inequality for the first nonzero Steklov eigenvalue previously studied by
Escobar in 1997 and by Jammes in 2015 to higher order Steklov eigenvalues. The
technique we develop to get this lower bound is based on considering a family
of accelerated Markov operators in the finite and mesurable situations and of
mass concentration deformations of the Laplace-Beltrami operator in the
manifold setting which converges uniformly to the Steklov operator. As an
intermediary step in the proof of the higher order Cheeger type inequality, we
define the Dirichlet-Steklov connectivity spectrum and show that the Dirichlet
connectivity spectra of this family of operators converges to (or bounded by)
the Dirichlet-Steklov spectrum uniformly. Moreover, we obtain bounds for the
Steklov eigenvalues in terms of its Dirichlet-Steklov connectivity spectrum
which is interesting in its own right and is more robust than the higher order
Cheeger type inequalities. The Dirichlet-Steklov spectrum is closely related to
the Cheeger-Steklov constants.


  We consider four-point correlation functions of protected single-trace scalar
operators in planar N = 4 supersymmetric Yang-Mills (SYM). We conjecture that
all loop corrections derive from an integrand which enjoys a ten-dimensional
symmetry. This symmetry combines spacetime and R-charge transformations. By
considering a 10D light-like limit, we extend the correlator/amplitude duality
by equating large R-charge octagons with Coulomb branch scattering amplitudes.
Using results from integrability, this predicts new finite amplitudes as well
as some Feynman integrals.


  We determine the exact physical parameters of the four Hyades cluster K
giants, using their parallaxes and atmospheric modeling of our red-channel
TIGRE high-resolution spectra. Performing a comparison with well-tested
evolutionary tracks, we derive exact masses and evolutionary stages. At an age
of 588 ($\pm 60$) Myrs and with a metallicity of Z=0.03 (consistent with the
spectroscopic abundances), we find HD~27371 and HD~28307, the two less bright K
giants, at the onset of central helium-burning, entering their blue loops with
a mass of 2.62 $M_{\odot}$, while the slightly brighter stars HD~28305 and
HD~27697 are already exiting their blue loop. Their more advanced evolution
suggests a higher mass of 2.75 $M_{\odot}$.
  Notably, this pairing coincides with the different activity levels, which we
find for these four stars from chromospheric activity monitoring with TIGRE and
archival Mount Wilson data as well as from ROSAT coronal detections: The two
less evolved K giants are the far more active pair, and we confidently confirm
their rotation with periods of about 142 days. This work therefore provides
some first, direct evidence of magnetic braking during the 130~Myrs lasting
phase of central helium-burning, similar to what has long been known to occur
to cool main-sequence stars.


  The goal of lossy data compression is to reduce the storage cost of a data
set $X$ while retaining as much information as possible about something ($Y$)
that you care about. For example, what aspects of an image $X$ contain the most
information about whether it depicts a cat? Mathematically, this corresponds to
finding a mapping $X\to Z\equiv f(X)$ that maximizes the mutual information
$I(Z,Y)$ while the entropy $H(Z)$ is kept below some fixed threshold. We
present a method for mapping out the Pareto frontier for classification tasks,
reflecting the tradeoff between retained entropy and class information. We
first show how a random variable $X$ (an image, say) drawn from a class
$Y\in\{1,...,n\}$ can be distilled into a vector $W=f(X)\in \mathbb{R}^{n-1}$
losslessly, so that $I(W,Y)=I(X,Y)$; for example, for a binary classification
task of cats and dogs, each image $X$ is mapped into a single real number $W$
retaining all information that helps distinguish cats from dogs. For the $n=2$
case of binary classification, we then show how $W$ can be further compressed
into a discrete variable $Z=g_\beta(W)\in\{1,...,m_\beta\}$ by binning $W$ into
$m_\beta$ bins, in such a way that varying the parameter $\beta$ sweeps out the
full Pareto frontier, solving a generalization of the Discrete Information
Bottleneck (DIB) problem. We argue that the most interesting points on this
frontier are "corners" maximizing $I(Z,Y)$ for a fixed number of bins
$m=2,3...$ which can be conveniently be found without multiobjective
optimization. We apply this method to the CIFAR-10, MNIST and Fashion-MNIST
datasets, illustrating how it can be interpreted as an
information-theoretically optimal image clustering algorithm.


  Recommender systems associated with social networks often use social
explanations (e.g. "X, Y and 2 friends like this") to support the
recommendations. We present a study of the effects of these social explanations
in a music recommendation context. We start with an experiment with 237 users,
in which we show explanations with varying levels of social information and
analyze their effect on users' decisions. We distinguish between two key
decisions: the likelihood of checking out the recommended artist, and the
actual rating of the artist based on listening to several songs. We find that
while the explanations do have some influence on the likelihood, there is
little correlation between the likelihood and actual (listening) rating for the
same artist. Based on these insights, we present a generative probabilistic
model that explains the interplay between explanations and background
information on music preferences, and how that leads to a final likelihood
rating for an artist. Acknowledging the impact of explanations, we discuss a
general recommendation framework that models external informational elements in
the recommendation interface, in addition to inherent preferences of users.


  Various types of equilibrium processes involve electric fields. In some
cases, the electrical energy appears to be negative (e.g. if the voltage is
fixed by an external source). This paper explains how to derive the correct
thermo-dynamic potential for electro-static phenomena, whether the voltage is
fixed, or the charge is fixed, or some combination is fixed. In particular, we
explain, in complete detail, why fixing the voltage introduces "a minus sign"
in the electrical energy.
  Two explanations are given. The first explanation is based on a
lumped-parameter argument (i.e. a lumped-capacitor model). The second
explanation uses a distributed parameter model (i.e. a partial differential
equation (PDE) model) of a dielectric medium, in this case, we allow for
non-linearity and external polarization effects. Connections with Legendre
(duality) transforms are also discussed.


  We study traveling waves of the KPP equation in the half-space with Dirichlet
boundary conditions. We show that minimal-speed waves are unique up to
translation and rotation but faster waves are not.
  We represent our waves as Laplace transforms of martingales associated to
branching Brownian motion in the half-plane with killing on the boundary. We
thereby identify the waves' asymptotic behavior and uncover a novel feature of
the minimal-speed wave $\Phi$. Far from the boundary, $\Phi$ converges to a
logarithmic shift of the 1D wave $w$ of the same speed: $\displaystyle \lim_{y
\to \infty} \Phi\big(x + \tfrac{1}{\sqrt{2}}\log y, y\big) = w(x)$.


  Space-time adaptive processing (STAP) is an effective tool for detecting a
moving target in the airborne radar system. Due to the fast-changing clutter
scenario and/or non side-looking configuration, the stationarity of the
training data is destroyed such that the statistical-based methods suffer
performance degradation. Direct data domain (D3) methods avoid non-stationary
training data and can effectively suppress the clutter within the test cell.
However, this benefit comes at the cost of a reduced system degree of freedom
(DOF), which results in performance loss. In this paper, by exploiting the
intrinsic sparsity of the spectral distribution, a new direct data domain
approach using sparse representation (D3SR) is proposed, which seeks to
estimate the high-resolution space-time spectrum with only the test cell. The
simulation of both side-looking and non side-looking cases has illustrated the
effectiveness of the D3SR spectrum estimation using focal underdetermined
system solution (FOCUSS) and norm minimization. Then the clutter covariance
matrix (CCM) and the corresponding adaptive filter can be effectively obtained.
Since D3SR maintains the full system DOF, it can achieve better performance of
output signal-clutter-ratio (SCR) and minimum detectable velocity (MDV) than
current D3 methods, e.g., direct data domain least squares (D3LS). Thus D3SR is
more effective against the range-dependent clutter and interference in the
non-stationary clutter scenario.


  End-to-end (E2E) keyword search (KWS) has emerged as an alternative and
complimentary approach to conventional keyword search which depends on the
output of automatic speech recognition (ASR) systems. While E2E methods greatly
simplify the KWS pipeline, they generally have worse performance than their
ASR-based counterparts, which can benefit from pretraining with untranscribed
data. In this work, we propose a method for pretraining E2E KWS systems with
untranscribed data, which involves using acoustic unit discovery (AUD) to
obtain discrete units for untranscribed data and then learning to locate
sequences of such units in the speech. We conduct experiments across languages
and AUD systems: we show that finetuning such a model significantly outperforms
a model trained from scratch, and the performance improvements are generally
correlated with the quality of the AUD system used for pretraining.


  Given its capability in efficient radio resource sharing, non-orthogonal
multiple access (NOMA) has been identified as a promising technology in 5G to
improve the system capacity, user connectivity, and scheduling latency. A dozen
of uplink NOMA schemes have been proposed recently and this paper considers the
design of a universal receiver suitable for all potential designs of NOMA
schemes. Firstly, a general turbo-like iterative receiver structure is
introduced, under which, a universal expectation propagation algorithm (EPA)
detector with hybrid parallel interference cancellation (PIC) is proposed (EPA
in short). Link-level simulations show that the proposed EPA receiver can
achieve superior block error rate (BLER) performance with implementation
friendly complexity and fast convergence, and is always better than the
traditional codeword level MMSE-PIC receiver for various kinds of NOMA schemes.


  This paper investigates the information loss paradox in the WKB/tunneling
picture of Hawking radiation. In the tunneling picture one can obtain the
tunneling amplitude to all orders in $\hbar$. However all terms beyond the
lowest, semi-classical term involve unknown constants. Despite this we find
that one can still arrive at interesting restrictions on Hawking radiation to
all orders in $\hbar$: (i) Taking into account only quantum corrections the
spectrum remains thermal to all orders. Thus quantum corrections by themselves
will not resolve the information loss paradox. (ii) The first quantum
correction give a temperature for the radiation which goes to zero as the mass
of the black hole goes to zero. Including higher order corrections changes this
nice result of the first order corrections. (iii) Finally we show that by
taking both quantum corrections and back reaction into account it is possible
under specific conditions to solve the information paradox by having the black
hole evaporate completely with the information carried away by the correlations
of the outgoing radiation.


  We give a detailed description of a recently proposed first principles
approach to the electronic structure of strongly correlated materials. The
method combines the GW approximation with dynamical mean field theory. It is
designed to describe Coulomb interactions and screening effects without
adjustable parameters, thus avoiding the conceptual problems inherent to
LDA+DMFT techniques.


  An energy-time entanglement-based dispersive optics quantum key distribution
(DO-QKD) is demonstrated experimentally over optical fibers of 20 km. In the
experiment, the telecom band energy-time entangled photon pairs are generated
through spontaneous four wave mixing in a silicon waveguide. The arrival time
of photons are registered for key generating and security test. High
dimensional encoding in the arrival time of photons is used to increase the
information per coincidence of photon pairs. The bin sifting process is
optimized by a three level structure, which significantly reduces the raw
quantum bit error rate (QBER) due to timing jitters of detectors and
electronics. A raw key generation rate of 151kbps with QBER of 4.95% is
achieved, under a time-bin encoding format with 4 bits per coincidence. This
experiment shows that entanglement-based DO-QKD can be implemented in an
efficient and convenient way, which has great potential in quantum secure
communication networks in the future.


  The relevance of single-W and single-Z production processes at hadron
colliders is well known: in the present paper the status of theoretical
calculations of Drell-Yan processes is summarized and some results on the
combination of electroweak and QCD corrections to a sample of observables of
the process $p p \to W^\pm \to \mu^\pm + X$ at the LHC are discussed. The
phenomenological analysis shows that a high-precision knowledge of QCD and a
careful combination of electroweak and strong contributions is mandatory in
view of the anticipated LHC experimental accuracy. One of the authors (O.N.)
dedicates these notes to Prof. S. Jadach, in honour of his 60th birthday and
grateful for all that Prof. Jadach taught him during their fruitful
collaboration.


  TAMA300, an interferometric gravitational-wave detector with 300-m baseline
length, has been developed and operated with sufficient sensitivity to detect
gravitational-wave events within our galaxy and sufficient stability for
observations; the interferometer was operated for over 10 hours stably and
continuously. With a strain-equivalent noise level of $h\sim 5 \times 10^{-21}
/\sqrt{\rm Hz}$, a signal-to-noise ratio (SNR) of 30 is expected for
gravitational waves generated by a coalescence of 1.4 $M_\odot$-1.4 $M_\odot$
binary neutron stars at 10 kpc distance. %In addition, almost all noise sources
which limit the sensitivity and which %disturb the stable operation have been
identified. We evaluated the stability of the detector sensitivity with a
2-week data-taking run, collecting 160 hours of data to be analyzed in the
search for gravitational waves.


  Sparse matrix-vector multiplication is often employed in many data-analytic
workloads in which low latency and high throughput are more valuable than exact
numerical convergence. FPGAs provide quick execution times while offering
precise control over the accuracy of the results thanks to reduced-precision
fixed-point arithmetic. In this work, we propose a novel streaming
implementation of Coordinate Format (COO) sparse matrix-vector multiplication,
and study its effectiveness when applied to the Personalized PageRank
algorithm, a common building block of recommender systems in e-commerce
websites and social networks. Our implementation achieves speedups up to 6x
over a reference floating-point FPGA architecture and a state-of-the-art
multi-threaded CPU implementation on 8 different data-sets, while preserving
the numerical fidelity of the results and reaching up to 42x higher energy
efficiency compared to the CPU implementation.


  We consider the statistics of extreme eigenvalues of random $d$-regular
graphs, with $N^{\mathfrak c}\leq d\leq N^{1/3-{\mathfrak c}}$ for arbitrarily
small ${\mathfrak c}>0$. We prove that in this regime, the fluctuations of
extreme eigenvalues are given by the Tracy-Widom distribution. As a
consequence, about 69% of $d$-regular graphs have all nontrivial eigenvalues
bounded in absolute value by $2\sqrt{d-1}$.


  Text sentiment transfer aims to flip the sentiment polarity of a sentence
(positive to negative or vice versa) while preserving its sentiment-independent
content. Although current models show good results at changing the sentiment,
content preservation in transferred sentences is insufficient. In this paper,
we present a sentiment transfer model based on polarity-aware denoising, which
accurately controls the sentiment attributes in generated text, preserving the
content to a great extent and helping to balance the style-content trade-off.
Our proposed model is structured around two key stages in the sentiment
transfer process: better representation learning using a shared encoder and
sentiment-controlled generation using separate sentiment-specific decoders.
Empirical results show that our methods outperforms state-of-the-art baselines
in terms of content preservation while staying competitive in terms of style
transfer accuracy and fluency.


  The stability of thermonuclear burning of hydrogen and helium accreted onto
neutron stars is strongly dependent on the mass accretion rate. The burning
behavior is observed to change from Type I X-ray bursts to stable burning, with
oscillatory burning occurring at the transition. Simulations predict the
transition at a ten times higher mass accretion rate than observed. Using
numerical models we investigate how the transition depends on the hydrogen,
helium, and CNO mass fractions of the accreted material, as well as on the
nuclear reaction rates of triple alpha and the hot-CNO breakout reactions
15O(a,g)19Ne and 18Ne(a,p)21Na. For a lower hydrogen content the transition is
at higher accretion rates. Furthermore, most experimentally allowed reaction
rate variations change the transition accretion rate by at most 10%. A factor
ten decrease of the 15O(a,g)19Ne rate, however, produces an increase of the
transition accretion rate of 35%. None of our models reproduce the transition
at the observed rate, and depending on the true 15O(a,g)19Ne reaction rate, the
actual discrepancy may be substantially larger. We find that the width of the
interval of accretion rates with marginally stable burning depends strongly on
both composition and reaction rates. Furthermore, close to the stability
transition, our models predict that X-ray bursts have extended tails where
freshly accreted fuel prolongs nuclear burning.


  In the present work is presented some considerations for a possible
generalization of the Microcanonical thermoestatics (M.Th) of D.H.E. Gross.The
same reveals a geometric aspect that commonly it has been disregarded so far:
the local reparametrization invariance . This new characteristic leads to the
needing of generalizing the methods of M.Th to be consequent with this
property.


  The asymptotic mean number of distinct sites visited by a subdiffusive
continuous time random walker in two dimensions seems not to have been
explicitly calculated anywhere in the literature. This number has been
calculated for other dimensions for only one specific asymptotic behavior of
the waiting time distribution between steps. We present an explicit derivation
for two cases in all integer dimensions so as to formally complete a tableaux
of results. In this tableaux we include the dominant as well as subdominant
contributions in all integer dimensions. Other quantities that can be
calculated from the mean number of distinct sites visited are also discussed.


  Early adolescence is a time of major social change; a strong sense of
belonging and peer connectedness is an essential protective factor in mental
health during that period. In this paper we introduce LINA, an augmented
reality (AR) smartphone-based serious game played in school by an entire class
(age 10+) together with their teacher, which aims to facilitate and improve
peer interaction, sense of belonging and class climate, while creating a safe
space to reflect on mental health and external stressors related to family
circumstance. LINA was developed through an interdisciplinary collaboration
involving a playwright, software developers, psychologists, and artists, via an
iterative co-development process with young people. A prototype has been
evaluated quantitatively for usability and qualitatively for efficacy in a
study with 91 early adolescents (agemean=11.41). Results from the Game User
Experience Satisfaction Scale (GUESS-18) and data from qualitative focus groups
showed high acceptability and preliminary efficacy of the game. Using AR, a
shared immersive narrative and collaborative gameplay in a shared physical
space offers an opportunity to harness adolescent affinity for digital
technology towards improving real-world social connection and sense of
belonging.


  Quantifying relevant interactions between neural populations is a prominent
question in the analysis of high-dimensional neural recordings. However,
existing dimension reduction methods often discuss communication in the absence
of a formal framework, while frameworks proposed to address this gap are
impractical in data analysis. This work bridges the formal framework of
M-Information Flow with practical analysis of real neural data. To this end, we
propose Iterative Regression, a message-dependent linear dimension reduction
technique that iteratively finds an orthonormal basis such that each basis
vector maximizes correlation between the projected data and the message. We
then define 'M-forwarding' to formally capture the notion of a message being
forwarded from one neural population to another. We apply our methodology to
recordings we collected from two neural populations in a simplified model of
whisker-based sensory detection in mice, and show that the low-dimensional
M-forwarding structure we infer supports biological evidence of a similar
structure between the two original, high-dimensional populations.


  We present a kinematic analysis of three triple stellar systems belonging to
two open clusters: CPD-60{\deg}961 and HD66137 in NGC2516, and HD315031 in
NGC6530. All three systems are hierarchical triples with a close binary bound
to a third body in a wider orbit, whose presence is detected through velocity
variations of the close binary barycentre. Orbital parameters are derived from
radial velocity curves. Absolute parameters for all stars are estimated
assuming cluster membership. Some dynamical and evolutionary aspects of these
systems are discussed, particularly the possible influence of Kozai cycles. The
two systems of NGC2516 have similar orbital configurations with inner periods
of 11.23 d and 8.70 d and outer periods of 9.79 yr and 9.24 yr. We report also
radial velocity measurements of the components of the visual binary
CPD-60{\deg}944 in NGC2516. Including results from previous works, this cluster
would harbor 5 hierarchical triples. The young system HD315031 has an inner
binary with a period of 1.37 d and a very eccentric (e=0.85) outer orbit with a
period of 483 d. Possible dynamical evolutionary scenarios are discussed.
Long-term radial velocity monitoring is highlighted as strategy for the
detection of subsystems with intermediate separations, which are hard to cover
with normal spectroscopic studies or visual techniques.


  We consider a two-Higgs doublet scenario containing three $SU(2)_L$ singlet
heavy neutrinos with Majorana masses. The second scalar doublet as well as the
neutrinos are odd under a $Z_2$ symmetry. This scenario not only generates
Majorana masses for the light neutrinos radiatively but also makes the lighter
of the neutral $Z_2$-odd scalars an eligible dark matter candidate, in addition
to triggering leptogenesis at the scale of the heavy neutrino masses. Taking
two representative values of this mass scale, we identify the allowed regions
of the parameter space of the model, which are consistent with all dark matter
constraints. At the same time, the running of quartic couplings in the scalar
potential to high scales is studied, thus subjecting the regions consistent
with dark matter constraints to further requirements of vacuum stability,
perturbativity and unitarity. It is found that part of the parameter space is
consistent with all of these requirements all the way up to the Planck scale,
and also yields the correct signal strength in the diphoton channel for the
scalar observed at the Large Hadron Collider.


  We study the evolution of thick domain walls in the different models of
cosmological inflation, in the matter-dominated and radiation-dominated
universe, or more generally in the universe with the equation of state
$p=w\rho$. We have found that the domain wall evolution crucially depends on
the time-dependent parameter $C(t)=1/(H(t)\delta_0)^2$, where $H(t)$ is the
Hubble parameter and $\delta_0$ is the thickness of the wall in flat
space-time. For $C(t)>2$ the physical thickness of the wall, $a(t)\delta(t)$,
tends with time to $\delta_0$, which is microscopically small. Otherwise, when
$C(t) \leq 2$, the wall steadily expands and can grow up to a cosmologically
large size.


  Using the APM cluster data we investigate whether the dynamical status of
clusters is related to the large-scale structure of the Universe. We find that
cluster substructure is strongly correlated with the tendency of clusters to be
aligned with their nearest neighbour and in general with the nearby clusters
that belong to the same supercluster. Furthermore, dynamically young clusters
are more clustered than the overall cluster population. These are strong
indications that cluster develop in a hierarchical fashion by anisotropy
merging along the large-scale filamentary superclusters within which they are
embedded.


  These are notes on the construction of the GIT-fans for quivers without
oriented cycles. We follow closely the steps outlined by N. Ressayre in "The
GIT-Equivalence for G-Line Bundles" (Geometriae Dedicata, Volume 81, Numbers
1-3, 2000). A simple construction of the GIT-fan for normal, affine G-varities
has been recently given by Ivan V. Arzhantsev and Juergen Hausen in "Geometric
Invariant Theory via Cox Rings"


  Microwave experiments in dilution refrigerators are a central tool in the
field of superconducting quantum circuits and other research areas. This type
of experiments relied so far on attaching a device to the mixing chamber of a
dilution refrigerator. The minimum turnaround time in this case is a few days
as required by cooling down and warming up the entire refrigerator. We
developed a new approach, in which a suitable sample holder is attached to a
cold-insertable probe and brought in contact with transmission lines
permanently mounted inside the cryostat. The total turnaround time is 8 hours
if the target temperature is 80 mK. The lowest attainable temperature is 30 mK.
Our system can accommodate up to six transmission lines, with a measurement
bandwidth tested between DC and 12 GHz. This bandwidth is limited by low pass
components in the setup; we expect the intrinsic bandwidth to be at least 18
GHz. We present our setup, discuss the experimental procedure, and give
examples of experiments enabled by this system. This new measurement method
will have a major impact on systematic ultra-low temperature studies using
microwave signals, including those requiring quantum coherence.


  With the popularity of 3D sensors in self-driving and other robotics
applications, extensive research has focused on designing novel neural network
architectures for accurate 3D point cloud completion. However, unlike in point
cloud classification and reconstruction, the role of adversarial samples in3D
point cloud completion has seldom been explored. In this work, we show that
training with adversarial samples can improve the performance of neural
networks on 3D point cloud completion tasks. We propose a novel approach to
generate adversarial samples that benefit both the performance of clean and
adversarial samples. In contrast to the PGD-k attack, our method generates
adversarial samples that keep the geometric features in clean samples and
contain few outliers. In particular, we use principal directions to constrain
the adversarial perturbations for each input point. The gradient components in
the mean direction of principal directions are taken as adversarial
perturbations. In addition, we also investigate the effect of using the minimum
curvature direction. Besides, we adopt attack strength accumulation and
auxiliary Batch Normalization layers method to speed up the training process
and alleviate the distribution mismatch between clean and adversarial samples.
Experimental results show that training with the adversarial samples crafted by
our method effectively enhances the performance of PCN on the ShapeNet dataset.


  Fujino gave a proof in [Fuj03] for the semi-ampleness of the moduli part in
the canonical bundle formula in the case when the general fibers are K3
surfaces or Abelian varieties. We show a similar statement when the general
fibers are primitive symplectic varieties with mild singularities. This answers
a question of Fujino raised in the same article. Moreover, using the structure
theory of varieties with trivial first Chern class, we reduce the question of
semi-ampleness in the case of families of K-trivial varieties to a question
when the general fibers satisfy a slightly weaker Calabi-Yau condition.


  Evidence in the literature shows that automated and human driving modes
demonstrate different driving characteristics, i.e., headway policy, spacing
policy, reaction time, comfortable acceleration, and others. These differences
alter observed traffic dynamics and have an impact on energy consumption. This
paper assesses the energy footprint of commercially implemented adaptive cruise
control (ACC) systems and human drivers in car-following formation via
different models using empirical observations on very similar driving cycles
and/or routes. Most importantly, it initiates a critical discussion of the
findings under the behavioral properties of each mode. Findings show that: ACC
systems propagate an increasing energy consumption upstream, while human
drivers do not; they succeed in maintaining a constant time-headway policy,
operating very reliably; they develop a strong bond with their leader compared
to their human counterparts; the two modes (humans and ACCs) are operating in
different phase-space areas with room for improvement. Overall, findings show
that ACC systems must be optimized to achieve a trade-off between functional
requirements and eco-driving instructions.


  In the paper a theoretical study of critical (Curie) temperature of diluted
ferromagnet based on multilayer graphene (or graphite) with hydrogen adatoms
deposited over carbon atoms belonging to single sublattice is presented. The
calculations are performed within Pair Approximation (PA) for diluted
ferromagnetic system with long-range interactions. The method is able to take
into account the spin-space anisotropy of coupling. The results obtained within
Mean Field Approximation (MFA) are also presented for comparison. The assumed
interaction between hydrogen adatom spins is inversely proportional to their
mutual distance, with the additional exponential attenuation reflecting the
presence of disorder in the system. The results obtained for a wide range of
impurity concentrations and interaction decay length are discussed. The
strongly non-linear behaviour of critical temperature as a function of dilution
is predicted, at variance with MFA predictions. Moreover, MFA tends to
overestimate heavily the critical temperature values compared to PA. An
universal dependence of critical temperature on impurity concentration and
interaction decay length is found for strong dilution regime.


  Using a \emph{gedanken} experiment providing presumably a minimal inaccuracy
the uncertainty contributions to the space-time measurement are precisely
evaluated for clock and mirror respectively. The resulting expression of
minimal uncertainty for the space(time) interval indicates the presence of
minimal Planck scale observable length(time). The synthesis of quantum
mechanics and general relativity predicts the UV and IR scales for Lorentz
invariance violation. The influence of background radiation on the space-time
measurement is estimated. Based on the minimal length uncertainty relation
which takes into account the wavelength of a quantum used for distance
measurement we evaluate the cumulative factor responsible for the magnification
of the space-time fluctuation induced phase incoherence of a light propagating
over a large distance. We notice that in view of the interferometric
observations the quantum fluctuations of space-time in the braneworld model are
enormously increased if the fundamental scale is taken much below the Planck
one. Present approach to the uncertainty in distance measurement leads to new
insight about the bounds of computation. The impact of the space-time
fluctuations on the black hole physics is briefly emphasized.


  We examine the behaviour of the infrared-radio correlation (IRRC) over the
range $0<z<6$ using new, highly sensitive 3GHz observations with the Karl G.
Jansky Very Large Array (VLA) and infrared data from the Herschel Space
Observatory in the 2deg$^{2}$ COSMOS field. We distinguish between objects
where emission is believed to arise solely from star-formation, and those where
an active galactic nucleus (AGN) is thought to be present. We account for
non-detections in the radio or in the infrared using a doubly-censored survival
analysis. We find that the IRRC of star-forming galaxies, quantified by the
infrared-to-1.4GHz radio luminosity ratio ($q_{\rm TIR}$), decreases with
increasing redshift: $q_{\rm TIR}(z)=(2.88\pm0.03)(1+z)^{-0.19\pm0.01}$.
Moderate-to-high radiative luminosity AGN do not follow the same $q_{\rm
TIR}$$(z)$ trend, having a lower normalisation and steeper decrease with
redshift. We cannot rule out the possibility that unidentified AGN
contributions only to the radio regime may be steepening the observed $q_{\rm
TIR}(z)$ trend of the star-forming population. An increasing fractional
contribution to the observed 3GHz flux by free-free emission of star-forming
galaxies may also affect the derived evolution. However, we find that the
standard (M82-based) assumption of the typical radio spectral energy
distribution (SED) for star-forming galaxies is inconsistent with our results.
This suggests a more complex shape of the typical radio SED for star-forming
galaxies, and that imperfect $K$ corrections in the radio may govern the
derived redshift trend of $q_{\rm TIR}$. Lastly, we present a
redshift-dependent relation between rest-frame 1.4GHz radio luminosity and star
formation rate taking the derived redshift trend into account.


  We report on the realization of polariton quantum boxes in a semiconductor
microcavity under strong coupling regime. The quantum boxes consist of mesas
that confine the cavity photon, etched on top of the spacer of a microcavity.
For mesas with sizes of the order of a few micron in width and nm in depth, we
observe quantization, caused by the lateral confinement, of the polariton modes
in several peaks. We evidence the strong exciton-photon coupling regime through
a typical/clear anticrossing curve for each quantized level. Moreover the
growth technique is of high quality, which opens the way for the conception of
new optoelectronic devices.


  We consider generalizations of parity polytopes whose variables, in addition
to a parity constraint, satisfy certain ordering constraints. More precisely,
the variable domain is partitioned into $k$ contiguous groups, and within each
group, we require that $x_i \geq x_{i+1}$ for all relevant $i$. Such
constraints are used to break symmetry after replacing an integer variable by a
sum of binary variables, so-called binarization. We provide extended
formulations for such polytopes, derive a complete outer description, and
present a separation algorithm for the new constraints. It turns out that
applying binarization and only enforcing parity constraints on the new
variables is often a bad idea. For our application, an integer programming
model for the graphic traveling salesman problem, we observe that parity
constraints do not improve the dual bounds, and we provide a theoretical
explanation of this effect.


  Within the standard Lagrangian settings (i.e., the difference between kinetic
and potential energies), we discuss and report isochronicity, linearizability
and exact solubility of some $n$-dimensional nonlinear position-dependent mass
(PDM) oscillators. In the process, negative the gradient of the PDM-potential
force field is shown to be no longer related to the time derivative of the
canonical momentum, $\mathbf{p}% =m\left( r\right) \mathbf{\dot{r}}$, but it is
rather related to the time derivative of the pseudo-momentum, $\mathbf{\pi
}\left( r\right) =\sqrt{% m\left( r\right) }\mathbf{\dot{r}}$ (i.e., Noether
momentum). Moreover, using some point transformation recipe, we show that the
linearizability of the $n$-dimensional nonlinear PDM-oscillators is only
possible for $n=1$ but not for $n\geq 2$. The Euler-Lagrange invariance falls
short/incomplete for $n\geq 2$ under PDM settings. Alternative invariances are
sought, therefore. Such invariances, like \emph{Newtonian invariance} of
Mustafa \cite{42}, effectively authorize the use of the exact solutions of one
system to find the solutions of the other. A sample of isochronous
$n$-dimensional nonlinear PDM-oscillators examples are reported.


  We consider a spherically symmetric line element which admits either a black
hole geometry or a wormhole geometry and show that in both cases the apparent
horizon or the wormhole throat is partially characterized by the zero-set of a
single curvature invariant. The detection of the apparent horizon by this
invariant is consistent with the geometric horizon detection conjectures and
implies that it is a geometric horizon of the black hole, while the detection
of the wormhole throat presents a conceptual problem for the conjectures. To
distinguish between these surfaces, we determine a set of curvature invariants
that fully characterize the apparent horizon and wormhole throat. Motivated by
this result, we introduce the concept of a geometric surface as a
generalization of a geometric horizon and extend the geometric horizon
detection conjectures to geometric surfaces. As an application, we employ
curvature invariants to characterize three important surfaces of the line
element introduced by Simpson, Martin-Moruno and Visser which describes
transitions between regular Vaidya black holes, traversable wormholes, and
black bounces.


  This paper proposes a network, referred to as MVSTR, for Multi-View Stereo
(MVS). It is built upon Transformer and is capable of extracting dense features
with global context and 3D consistency, which are crucial to achieving reliable
matching for MVS. Specifically, to tackle the problem of the limited receptive
field of existing CNN-based MVS methods, a global-context Transformer module is
first proposed to explore intra-view global context. In addition, to further
enable dense features to be 3D-consistent, a 3D-geometry Transformer module is
built with a well-designed cross-view attention mechanism to facilitate
inter-view information interaction. Experimental results show that the proposed
MVSTR achieves the best overall performance on the DTU dataset and strong
generalization on the Tanks & Temples benchmark dataset.


  Principal component analysis (PCA) is widely used for dimension reduction and
embedding of real data in social network analysis, information retrieval, and
natural language processing, etc. In this work we propose a fast randomized PCA
algorithm for processing large sparse data. The algorithm has similar accuracy
to the basic randomized SVD (rPCA) algorithm (Halko et al., 2011), but is
largely optimized for sparse data. It also has good flexibility to trade off
runtime against accuracy for practical usage. Experiments on real data show
that the proposed algorithm is up to 9.1X faster than the basic rPCA algorithm
without accuracy loss, and is up to 20X faster than the svds in Matlab with
little error. The algorithm computes the first 100 principal components of a
large information retrieval data with 12,869,521 persons and 323,899 keywords
in less than 400 seconds on a 24-core machine, while all conventional methods
fail due to the out-of-memory issue.


  Large dimensionless numbers, arising out of ratios of various physical
constants, intrigued many scientists, especially Dirac. Relying on the
coincidence of large numbers, Dirac arrived at the revolutionary hypothesis
that the gravitational constant $G$ should vary inversely as the cosmic time
$t$. This hypothesis of Dirac, known as Large Number Hypothesis (LNH), sparked
off many speculations, arguments and new ideas in terms of applications. Works
done by several authors with LNH as their basic platform are reviewed in this
work. Relationship between some of those works are pointed out here.
Possibility of time-variations of physical constants other than $G$ are also
discussed.


  Following N. Elkies ("ABC implies Mordell") we show that the abc conjecture
of Masser-Oesterle implies an effective version of Siegel's theorem about
integral points on algebraic curves, i.e. an upper bound for the S-integral
points where the dependence on S is explicit. The converse statement is also
announced in this note. For both results, the main geometric tool is a theorem
of G.V. Belyi.


  Multi-particle correlation techniques are frequently used to study jet shapes
and yields in hadronic and nuclear collisions. To date, a standard assumption
applied in such analyses is that the observed correlations arise from either
jets and associated hard scattering phenomena, or from a background component
due to combinatorial pairs connected only through whole even correlations.
Within this assumption of two essentially independent sources, a fundamental
problem centers around determining the relative contributions of each
component. We discuss the methods commonly used to establish the background
yield in jet correlation analyses, with a full explanation of the absolute
background normalization technique which establishes the background yield
without assumptions about the shape of jet correlations. This is especially
important in relativistic heavy ion collisions where the jet shapes are
significantly distorted from the well separated back-to-back di-jets observed
in proton-proton collisions.


  Dominant pre-training work for video-text retrieval mainly adopt the
"dual-encoder" architectures to enable efficient retrieval, where two separate
encoders are used to contrast global video and text representations, but ignore
detailed local semantics. The recent success of image BERT pre-training with
masked visual modeling that promotes the learning of local visual context,
motivates a possible solution to address the above limitation. In this work, we
for the first time investigate masked visual modeling in video-text
pre-training with the "dual-encoder" architecture. We perform Masked visual
modeling with Injected LanguagE Semantics (MILES) by employing an extra
snapshot video encoder as an evolving "tokenizer" to produce reconstruction
targets for masked video patch prediction. Given the corrupted video, the video
encoder is trained to recover text-aligned features of the masked patches via
reasoning with the visible regions along the spatial and temporal dimensions,
which enhances the discriminativeness of local visual features and the
fine-grained cross-modality alignment. Our method outperforms state-of-the-art
methods for text-to-video retrieval on four datasets with both zero-shot and
fine-tune evaluation protocols. Our approach also surpasses the baseline models
significantly on zero-shot action recognition, which can be cast as
video-to-text retrieval.


  Given a positive integer $m$, let $\mathbb{Z}_m$ be the set of residue
classes mod $m$. For $A\subseteq \mathbb{Z}_m$ and $n\in \mathbb{Z}_m$, let
$\sigma_A(n)$ be the number of solutions to the equation $n=x+y$ with $x,y\in
A$. Let $\mathcal{H}_m$ be the set of subsets $A\subseteq \mathbb{Z}_m$ such
that $\sigma_A(n)\geq1$ for all $n\in \mathbb{Z}_m$. Let
  $$
  \ell_m=\min\limits_{A\in \mathcal{H}_m}\left\lbrace m^{-1}\sum_{n\in
\mathbb{Z}_m}\sigma_A(n)\right\rbrace.
  $$ Following a prior result of Ding and Zhao on Ruzsa's number, we know that
$$ \limsup_{m\rightarrow\infty}\ell_m\le 192. $$ Ding and Zhao then asked
possible improvements on this value. In this paper, we prove $$
\limsup\limits_{m\rightarrow\infty}\ell_m\leq 144. $$ Moreover, parallel
results on subtractive bases of $ \mathbb{Z}_m$ were also investigated here.


  We address the problem of state estimation, attack isolation, and control for
discrete-time Linear Time Invariant (LTI) systems under (potentially unbounded)
actuator false data injection attacks. Using a bank of Unknown Input Observers
(UIOs), each observer leading to an exponentially stable estimation error in
the attack-free case, we propose an estimator that provides exponential
estimates of the system state and the attack signals when a sufficiently small
number of actuators are attacked. We use these estimates to control the system
and isolate actuator attacks. Simulations results are presented to illustrate
the performance of the results.


  We perform an expansion of the virtual Compton scattering amplitude for low
energies and low momenta and show that this expansion covers the transition
from the regime to be investigated in the scheduled photon electroproduction
experiments to the real Compton scattering regime.
  We discuss the relation of the generalized polarizabilities of virtual
Compton scattering to the polarizabilities of real Compton scattering.


  We consider a control problem where the system is driven by a decoupled as
well as a coupled forward-backward stochastic differential equation. We prove
the existence of an optimal control in the class of relaxed controls, which are
measure-valued processes, generalizing the usual strict controls. The proof is
based on some tightness properties and weak convergence on the space D of
c\`adl\`ag functions, endowed with the Jakubowsky S-topology. Moreover, under
some convexity assumptions, we show that the relaxed optimal control is
realized by a strict control.


  This paper explores the birational geometry of a general Horrocks-Mumford
quintic threefold, describing the set of all minimal models up to marked
isomorphism, the movable fan (the way in which the nef cones of all these
models are arranged to form the movable cone), and the birational automorphism
group. There are infinitely many models up to marked isomorphism, falling into
just eight (unmarked-) isomorphism classes.


  The large values of the singlet and triplet two-nucleon scattering lengths
locate the nuclear system close to the unitary limit. This particular position
strongly constrains the low-energy observables in the three-nucleon system as
depending on one parameter, the triton binding energy, and introduces
correlations in the low energy sector of light nuclei. Here we analyze the
propagation of these correlations to infinite nuclear matter showing that its
saturation properties, the equation of state of $\beta$-stable nuclear matter
and several properties of neutron stars, as their maximum mass, are well
determined solely by a few number of low-energy quantities of the two- and
three-nucleon systems. In this way we make a direct link between the universal
behavior observed in the low-energy region of few-nucleon systems and
fundamental properties of nuclear matter and neutron stars.


  We perform fracture experiments on nanoscale phase separated glasses and
measure crack surface roughness by atomic force microscopy. The ability of
tuning the phase domain size by thermal treatment allows us to test thoroughly
the predictions of crack font depinning models about the scaling properties of
crack surface roughness. It appears that in the range of validity of these
depinning models developed for the fracture of brittle materials, our
experimental results show a quantitative agreement with theoretical
predictions: beyond the characteristic size of disorder, the roughness of crack
surfaces obeys the logarithmic scaling early predicted by Ramanathan, Ertas and
Fisher (PRL97)


  Various approaches to quantum gravity suggest the possibility of violation of
Lorentz symmetry at very high energies. In these cases we expect a modification
at low energies of the dispersion relation of photons that contains extra
powers of the momentum suppressed by a high energy scale. These terms break
boost invariance and can be tested even at relatively low energies. We use the
light curves of the very bright short Gamma-Ray Burst GRB 051221A and compare
the arrival times of photons at different energies with the expected time delay
due to a modified dispersion relation. As no time delay was observed, we set a
lower bound of 0.0066 E_{pl} \sim 0.66 10^{17} GeV on the scale of Lorentz
invariance violation.


  The paper considers an opportunity of detecting explosives by using radiation
capture of a neutron with nitrogen nucleus. Proton LINAC is offered as the
neutron source with the following parameters: proton energy five Mega electron
Volts , beam pulse current one and seven-tenths milliampere, duration of the
current pulse two hundreds microseconds, repetition rate fifty Hertz. The
reaction in which neutrons are formed is lithium (p,n) beryllium. It is shown
that this neutron source will have the intensity of ten to the twelfth degree
neutron per second that will allow one to detect explosives of the size of a
tennis ball.


  Berry and Wang [Phys. Rev. A {\bf 83}, 042317 (2011)] show numerically that a
discrete-time quantum random walk of two noninteracting particles is able to
distinguish some non-isomorphic strongly regular graphs from the same family.
Here we analytically demonstrate how it is possible for these walks to
distinguish such graphs, while continuous-time quantum walks of two
noninteracting particles cannot. We show analytically and numerically that even
single-particle discrete-time quantum random walks can distinguish some
strongly regular graphs, though not as many as two-particle noninteracting
discrete-time walks. Additionally, we demonstrate how, given the same quantum
random walk, subtle differences in the graph certificate construction algorithm
can nontrivially impact the walk's distinguishing power. We also show that no
continuous-time walk of a fixed number of particles can distinguish all
strongly regular graphs when used in conjunction with any of the graph
certificates we consider. We extend this constraint to discrete-time walks of
fixed numbers of noninteracting particles for one kind of graph certificate; it
remains an open question as to whether or not this constraint applies to the
other graph certificates we consider.


  Clustering has been well studied for desktop malware analysis as an effective
triage method. Conventional similarity-based clustering techniques, however,
cannot be immediately applied to Android malware analysis due to the excessive
use of third-party libraries in Android application development and the
widespread use of repackaging in malware development. We design and implement
an Android malware clustering system through iterative mining of malicious
payload and checking whether malware samples share the same version of
malicious payload. Our system utilizes a hierarchical clustering technique and
an efficient bit-vector format to represent Android apps. Experimental results
demonstrate that our clustering approach achieves precision of 0.90 and recall
of 0.75 for Android Genome malware dataset, and average precision of 0.98 and
recall of 0.96 with respect to manually verified ground-truth.


  Automotive user interface (AUI) evaluation becomes increasingly complex due
to novel interaction modalities, driving automation, heterogeneous data, and
dynamic environmental contexts. Immersive analytics may enable efficient
explorations of the resulting multilayered interplay between humans, vehicles,
and the environment. However, no such tool exists for the automotive domain.
With AutoVis, we address this gap by combining a non-immersive desktop with a
virtual reality view enabling mixed-immersive analysis of AUIs. We identify
design requirements based on an analysis of AUI research and domain expert
interviews (N=5). AutoVis supports analyzing passenger behavior, physiology,
spatial interaction, and events in a replicated study environment using
avatars, trajectories, and heatmaps. We apply context portals and driving-path
events as automotive-specific visualizations. To validate AutoVis against
real-world analysis tasks, we implemented a prototype, conducted heuristic
walkthroughs using authentic data from a case study and public datasets, and
leveraged a real vehicle in the analysis process.


  Herschel observation has recently revealed that interstellar molecular clouds
consist of many filaments. Polarization observations in optical and infrared
wavelengths indicate that the magnetic field often runs perpendicular to the
filament. In this paper, the magnetohydrostatic configuration of isothermal gas
is studied, in which the thermal pressure and the Lorentz force are balanced
against the self-gravity and the magnetic field is globally perpendicular to
the axis of the filament. The model is controlled by three parameters:
center-to-surface density ratio (\rho_c/\rho_s), plasma \beta of surrounding
interstellar gas (\beta_0) and the radius of the hypothetical parent cloud
normalized by the scale-height (R'_0), although there remains a freedom how the
mass is distributed against the magnetic flux (mass loading). In the case that
R'_0 is small enough, the magnetic field plays a role in confining the gas.
However, the magnetic field generally has an effect in supporting the cloud.
There is a maximum line-mass (mass per unit length) above which the cloud is
not supported against the gravity. Compared with the maximum line-mass of
non-magnetized cloud (2c_s^2/G, where c_s and G represent respectively the
isothermal sound speed and the gravitational constant), that of the magnetized
filament is larger than the non-magnetized one. The maximum line-mass is
numerically obtained as \lambda_max \simeq 0.24 \Phi_cl/G^1/2 + 1.66 c_s^2/G,
where \Phi_cl represents one half of the magnetic flux threading the filament
per unit length. The maximum mass of the filamentary cloud is shown to be
significantly affected by the magnetic field when the magnetic flux per unit
length exceeds \Phi_cl \gtrsim 3 pc \mu G (c_s/190 m s^-1)^2.


  The X-ray Integral Field Unit (X-IFU) is the high-resolution X-ray
spectrometer to fly on board the Athena Space Observatory of the European Space
Agency (ESA). It is being developed by an international Consortium led by
France, involving twelve ESA member states, plus the United States. It is a
cryogenic instrument, involving state of the art technology, such as
micro-calorimeters, to be read out by low noise electronics. As the instrument
was undergoing its system requirement review (in 2022), a life cycle assessment
(LCA) was performed to estimate the environmental impacts associated with the
development of the sub-systems that were under the responsibility of the X-IFU
Consortium. The assessment included the supply, manufacturing and testing of
sub systems, as well as involved logistics and manpower. We find that the most
significant environmental impacts arise from testing activities, which is
related to energy consumption in clean rooms, office work, which is related to
energy consumption in office buildings, and instrument manufacturing, which is
related to the use of mineral and metal resources. Furthermore, business
travels is another area of concern, despite the policy to reduced flying
adopted by the Consortium. As the instrument is now being redesigned to fit
within the new boundaries set by ESA, the LCA will be updated, with a focus on
the hot spots identified in the first iteration. The new configuration,
consolidated in 2023, is significantly different from the previously studied
version and is marked by an increase of the perimeter of responsibility for the
Consortium. This will need to be folded in the updated LCA, keeping the
ambition to reduce the environmental footprint of X-IFU, while complying with
its stringent requirements in terms of performance and risk management.


  Anomaly detection in wind turbines typically involves using normal behaviour
models to detect faults early. However, training autoencoder models for each
turbine is time-consuming and resource intensive. Thus, transfer learning
becomes essential for wind turbines with limited data or applications with
limited computational resources. This study examines how cross-turbine transfer
learning can be applied to autoencoder-based anomaly detection. Here,
autoencoders are combined with constant thresholds for the reconstruction error
to determine if input data contains an anomaly. The models are initially
trained on one year's worth of data from one or more source wind turbines. They
are then fine-tuned using smaller amounts of data from another turbine. Three
methods for fine-tuning are investigated: adjusting the entire autoencoder,
only the decoder, or only the threshold of the model. The performance of the
transfer learning models is compared to baseline models that were trained on
one year's worth of data from the target wind turbine. The results of the tests
conducted in this study indicate that models trained on data of multiple wind
turbines do not improve the anomaly detection capability compared to models
trained on data of one source wind turbine. In addition, modifying the model's
threshold can lead to comparable or even superior performance compared to the
baseline, whereas fine-tuning the decoder or autoencoder further enhances the
models' performance.


  Privacy concerns have thrust privacy-preserving computation into the
spotlight. Homomorphic encryption (HE) is a cryptographic system that enables
computation to occur directly on encrypted data, providing users with strong
privacy (and security) guarantees while using the same services they enjoy
today unprotected. While promising, HE has seen little adoption due to
extremely high computational overheads, rendering it impractical. Homomorphic
encryption (HE) is a cryptographic system that enables computation to occur
directly on encrypted data. In this paper we develop a benchmark suite, named
NTTSuite, to enable researchers to better address these overheads by studying
the primary source of HE's slowdown: the number theoretic transform (NTT).
NTTSuite constitutes seven unique NTT algorithms with support for CPUs (C++),
GPUs (CUDA), and custom hardware (Catapult HLS).In addition, we propose
optimizations to improve the performance of NTT running on FPGAs. We find our
implementation outperforms the state-of-the-art by 30%.


  The notions Hodge-Newton decomposition and Hodge-Newton filtration for
F-crystals are due to Katz and generalize Messing's result on the existence of
the local-\'etale filtration for p-divisible groups. Recently, some of Katz's
classical results have been generalized by Kottwitz to the context of
F-crystals with additional structures and by Moonen to $\mu$-ordinary
p-divisible groups. In this paper, we discuss further generalizations to the
situation of crystals in characteristic p and of p-divisible groups with
additional structure by endomorphisms.


  The fidelity of continuous variable teleportation can be optimized by
changing the gain in the modulation of the output field. We discuss the gain
dependence of fidelity for coherent, vacuum and one photon inputs and propose
optimal gain tuning strategies for corresponding input selections.


  We use a covariant supermultiplet theory to determine the primary coupling
constant associated with several types of two-body meson decay. Despite the
diverse range of decays considered the primary coupling constant is
surprisingly uniform. We envisage the extension of the techniques to heavy
quark cases, including as preliminary examples the calculation of the $D^{*+}$
and $D^{*0}$ total decay widths with results $57.7 \pm 1.5$ KeV and $42.5 \pm
2.6$ KeV respectively, as well as some predictions about $D^*$ and $B^*$
radiative decays. (3 uuencoded Postscript Files are appended at the end of the
TexFile.)


  Even after the discovery of neutrino flavour oscillations, based on data from
atmospheric, solar, reactor, and accelerator experiments, many characteristics
of the neutrino remain unknown. Only the neutrino square-mass differences and
the mixing angle values have been estimated, while the value of each mass
eigenstate still hasn't. Its nature (massive Majorana or Dirac particle) is
still escaping. Neutrinoless double beta decay ($0\nu$-DBD) experimental
discovery could be the ultimate answer to some delicate questions of elementary
particle and nuclear physics. The Majorana description of neutrinos allows the
$0\nu$-DBD process, and consequently either a mass value could be measured or
the existence of physics beyond the standard should be confirmed without any
doubt. As expected, the $0\nu$-DBD measurement is a very difficult field of
application for experimentalists. In this paper, after a short summary of the
latest results in neutrino physics, the experimental status, the R&D projects,
and perspectives in $0\nu$-DBD sector are reviewed.


  Using a two-dimensional version of the delta method, we establish an
asymptotic formula for the number of rational points of bounded height on
non-singular complete intersections of cubic and quadric hypersurfaces of
dimension at least $23$ over $\mathbb{F}_q(t)$, provided
$\text{cha}(\mathbb{F}_q)>3$. Under the same hypotheses, we also verify weak
approximation.


  We consider a quantum system coupled to environment at a fixed temperature
and describe the reduced evolution of the system by means of a Redfield
equation with effective time-dependent contact temperature obeying a universal
law. At early times, after the system and environment start in a product state,
the effective contact temperature appears to be much higher, yet eventually it
settles down towards the true environment value. In this way, we obtain a
method which includes non-Markovian effects and can be further applied to
various types of GKSL equations, beyond the secular approximation and
time-averaging methods. We derive the theory from first principles and discuss
its application using a simple example of a single quantum dot.


  The self-energy method for quantum impurity models expresses the correlation
part of the self-energy in terms of the ratio of two Green's functions and
allows for a more accurate calculation of equilibrium spectral functions than
is possible directly from the one-particle Green's function [Bulla et al., J.
Phys.: Condens. Matter 10, 8365 (1998)], for example, within the numerical
renormalization group method. In addition, the self-energy itself is a central
quantity required in the dynamical mean field theory of strongly correlated
lattice models. Here, we show how to generalize the self-energy method to the
time-dependent situation for the prototype model of strong correlations, the
Anderson impurity model. We use the equation of motion method to obtain closed
expressions for the local Green's function in terms of a time-dependent
correlation self-energy, with the latter being given as a ratio of a
one-particle time-dependent Green's function and a higher-order correlation
function. We benchmark this self-energy approach to time-dependent spectral
functions against the direct approach within the time-dependent numerical
renormalization group method. The self-energy approach improves the accuracy of
time-dependent spectral function calculations, and the closed-form expressions
for the Green's function allow for a clear picture of the time-evolution of
spectral features at the different characteristic time-scales. The self-energy
approach is of potential interest also for other quantum impurity solvers for
real-time evolution, including time-dependent density matrix renormalization
group and continuous-time quantum Monte Carlo techniques.


  The Australia Telescope Compact Array (ATCA) has been used to map class I
methanol masers at 36 and 44 GHz in G309.38-0.13. Maser spots are found at nine
locations in an area of 50''x30'', with both transitions reliably detected at
only two locations. The brightest spot is associated with shocked gas traced by
4.5 micron emission. The data allowed us to make a serendipitous discovery of a
high-velocity 36-GHz spectral feature, which is blue-shifted by about 30 km/s
from the peak velocity at this frequency, but spatially located close to
(within a few arcseconds of) the brightest maser spot. We interpret this as
indicating an outflow parallel to the line of sight. Such a high velocity
spread of maser features, which has not been previously reported in the class I
methanol masers associated with a single molecular cloud, suggests that the
outflow most likely interacts with a moving parcel of gas.


  The Prisoners' Dilemma is perhaps the most famous model in the field of game
theory. Consequently, it is natural to investigate its quantum version when one
considers to apply quantum strategies to game theory. There are two main
results in this paper: 1) The well-known Prisoners' Dilemma can be categorized
into three types and only the third type is adaptable for quantum strategies.
2) As a reverse problem of game theory, mechanism design provides a better
circumstance for quantum strategies than game theory does.