  Here we present the results of a Suzaku observation of the Broad Line Radio
Galaxy 3C 445. We confirm the results obtained with the previous X-ray
observations which unveiled the presence of several soft X-ray emission lines
and an overall X-ray emission which strongly resembles a typical Seyfert 2
despite of the optical classification as an unobscured AGN. The broad band
spectrum allowed us to measure for the first time the amount of reflection
(R~0.9) which together with the relatively strong neutral Fe Kalpha emission
line (EW ~ 100 eV) strongly supports a scenario where a Compton-thick mirror is
present. The primary X-ray continuum is strongly obscured by an absorber with a
column density of NH =2-3 x10^{23} cm^{-2}. Two possible scenarios are proposed
for the absorber: a neutral partial covering or a mildly ionised absorber with
an ionisation parameter log\xi ~ 1.0 erg cm s^{-1}. A comparison with the past
and more recent X-ray observations of 3C 445 performed with XMM-Newton and
Chandra is presented, which provided tentative evidence that the ionised and
outflowing absorber varied. We argue that the absorber is probably associated
with an equatorial disk-wind located within the parsec scale molecular torus.


  The notion of families of quantum invertible maps ($C^*$-algebra
homomorphisms satisfying Podle\'s condition) is employed to strengthen and
reinterpret several results concerning universal quantum groups acting on
finite quantum spaces. In particular Wang's quantum automorphism groups are
shown to be universal with respect to quantum families of invertible maps.
Further the construction of the Hopf image of Banica and Bichon is phrased in
the purely analytic language and employed to define the quantum subgroup
generated by a family of quantum subgroups or more generally a family of
quantum invertible maps.


  On an arbitrary toric variety, we introduce the logarithmic double complex,
which is essentially the same as the algebraic de Rham complex in the
nonsingular case, but which behaves much better in the singular case. Over the
field of complex numbers, we prove the toric analog of the algebraic de Rham
theorem which Grothendieck formulated and proved for general nonsingular
algebraic varieties re-interpreting an earlier work of Hodge-Atiyah. Namely,
for a finite simplicial fan which need not be complete, the complex cohomology
groups of the corresponding toric variety as an analytic space coincide with
the hypercohomology groups of the single complex associated to the logarithmic
double complex. They can then be described combinatorially as Ishida's
cohomology groups for the fan. We also prove vanishing theorems for Ishida's
cohomology groups. As a consequence, we deduce directly that the complex
cohomology groups vanish in odd degrees for toric varieties which correspond to
finite simplicial fans with full-dimensional convex support. In the particular
case of complete simplicial fans, we thus have a direct proof for an earlier
result of Danilov and the author.


  We review recent progress in operator algebraic approach to conformal quantum
field theory. Our emphasis is on use of representation theory in classification
theory. This is based on a series of joint works with R. Longo.


  Database schema elements such as tables, views, triggers and functions are
typically defined with many interrelationships. In order to support database
users in understanding a given schema, a rule-based approach for analyzing the
respective dependencies is proposed using Datalog expressions. We show that
many interesting properties of schema elements can be systematically determined
this way. The expressiveness of the proposed analysis is exemplarily shown with
the problem of computing induced functional dependencies for derived relations.
The propagation of functional dependencies plays an important role in data
integration and query optimization but represents an undecidable problem in
general. And yet, our rule-based analysis covers all relational operators as
well as linear recursive expressions in a systematic way showing the depth of
analysis possible by our proposal. The analysis of functional dependencies is
well-integrated in a uniform approach to analyzing dependencies between schema
elements in general.


  The quantum electrodynamic (QED) description of light-and-matter interaction
is one of the most fundamental theories of physics and has been shown to be in
excellent agreement with experimental results. Specifically, measurements of
the electronic magnetic moment (or $g$ factor) of highly charged ions (HCI) in
Penning traps can provide a stringent probe for QED, testing the Standard model
in the strongest electromagnetic fields. When studying the difference of
isotopes, even the intricate effects stemming from the nucleus can be resolved
and tested as, due to the identical electron configuration, many common QED
contributions do not have to be considered. Experimentally however, this
becomes quickly limited, particularly by the precision of the ion masses or the
achievable magnetic field stability. Here we report on a novel measurement
technique that overcomes both of these limitations by co-trapping two HCIs in a
Penning trap and measuring the difference of their $g$ factors directly. The
resulting correlation of magnetic field fluctuations leads to drastically
higher precision. We use a dual Ramsey-type measurement scheme with the ions
locked on a common magnetron orbit, separated by only a few hundred
micrometres, to extract the coherent spin precession frequency difference. We
have measured the isotopic shift of the bound electron $g$ factor of the neon
isotopes of $^{20}$Ne$^{9+}$ and $^{22}$Ne$^{9+}$ to 0.56 parts-per-trillion
($5.6 \cdot 10^{-13}$) precision relative to their $g$ factors, which is an
improvement of more than two orders of magnitude compared to state-of-the-art
techniques. This resolves the QED contribution to the nuclear recoil for the
very first time and accurately validates the corresponding theory. Furthermore,
the agreement with theory allows setting constraints for a fifth-force,
resulting from Higgs-portal-type dark-matter interactions.


  Short lived hadronic resonances are a very important tool for the study of
the dynamics of the matter produced in heavy-ion collisions since they should
be sensitive to the medium properties such as temperature, density and
expansion velocity. In particular they are sensitive to the time span between
chemical and kinetic freeze-out of the hadronic phase of the fireball. The
study of resonances in 7 TeV pp collisions is useful both in order to constrain
QCD inspired models and to form a baseline for the production in heavy-ion
collisions. The resonances $\mathrm{K}^{*0}$(892), $\phiup$(1020),
$\Sigma(1385)^{\pm}$, $\Lambda$(1520), $\Xi$(1530) are reconstructed from their
hadronic decay using data collected by the ALICE detector in pp collisions at 7
TeV. Their yields and $p_{\mathrm{T}}$ spectra are compared with Monte Carlo
models such as PHOJET and different PYTHIA tunes.


  We analyse the dynamics of near-extremal Reissner-Nordstr\"om black holes in
asymptotically four-dimensional Anti-de Sitter space (AdS$_4$). We work in the
spherically symmetric approximation and study the thermodynamics and the
response to a probe scalar field. We find that the behaviour of the system, at
low energies and to leading order in our approximations, is well described by
the Jackiw-Teitelboim (JT) model of gravity. In fact, this behaviour can be
understood from symmetry considerations and arises due to the breaking of time
reparametrisation invariance. The JT model has been analysed in considerable
detail recently and related to the behaviour of the SYK model. Our results
indicate that features in these models which arise from symmetry considerations
alone are more general and present quite universally in near-extremal black
holes.


  We present radial velocity measurements of two stars observed as part of the
Lick Subgiants Planet Search and the Keck N2K survey. Variations in the radial
velocities of both stars reveal the presence of Jupiter-mass exoplanets in
highly eccentric orbits. HD 16175 is a G0 subgiant from the Lick Subgiants
Planet Search, orbited by a planet having a minimum mass of 4.4 M_Jup, in an
eccentric (e = 0.59), 2.71 yr orbit. HD 96167 is a G5 subgiant from the N2K
("Next 2000") program at Keck Observatory, orbited by a planet having a minimum
mass of 0.68 M_Jup, in an eccentric (e = 0.71), 1.366 yr orbit. Both stars are
relatively massive (M_star = 1.3 M_sun) and are very metal rich ([Fe/H] >
+0.3). We describe our methods for measuring the stars' radial velocity
variations and photometric stability.


  We study orthogonal decompositions of symmetric and ordinary tensors using
methods from linear algebra. For the field of real numbers we show that the
sets of decomposable tensors can be defined be equations of degree 2. This
gives a new proof of some of the results of Robeva and Boralevi et al.
Orthogonal decompositions over the field of complex numbers had not been
studied previously; we give an explicit description of the set of decomposable
tensors using polynomial equalities and inequalities, and we begin a study of
their closures. The main open problem that arises from this work is to obtain a
complete description of the closures. This question is akin to that of
characterizing border rank of tensors in algebraic complexity. We give partial
results using in particular a connection with approximate simultaneous
diagonalization (the so-called "ASD property").


  A finite thermal anisotropy, if maintained for times longer than thermal
relaxation times, may have a positive effect on the critical temperature in
Bose-Einstein condensation of a dilute boson gas not in thermal equilibrium or
quasi-particle fermi fluid consisting of spin-compensated electron pairs. It
raises the transition temperature while increasing the condensate density.


  This is an initial study of the longitudinal, single-bunch stability in the
proposed FACET-II e+ damping ring. It is preliminary because many vacuum
chamber objects of the ring have not yet been designed.


  Timely and effective load shedding in power systems is critical for
maintaining supply-demand balance and preventing cascading blackouts. To
eliminate load shedding bias against specific regions in the system,
optimization-based methods are uniquely positioned to help balance between
economical and equity considerations. However, the resulting optimization
problem involves complex constraints, which can be time-consuming to solve and
thus cannot meet the real-time requirements of load shedding. To tackle this
challenge, in this paper we present an efficient machine learning algorithm to
enable millisecond-level computation for the optimization-based load shedding
problem. Numerical studies on both a 3-bus toy example and a realistic RTS-GMLC
system have demonstrated the validity and efficiency of the proposed algorithm
for delivering equitable and real-time load shedding decisions.


  Growing set of optimization and regression techniques, based upon sparse
representations of signals, to build models from data sets has received
widespread attention recently with the advent of compressed sensing. This paper
deals with the parameterization of the Lorenz-96 model with two time-scales
that mimics mid-latitude atmospheric dynamics with microscopic convective
processes. Compressed sensing is used to build models (vector fields) to
emulate the behavior of the fine-scale process, so that explicit simulations
become an online benchmark for parameterization. We apply compressed sensing,
where the sparse recovery is achieved by constructing a sensing/dictionary
matrix from ergodic samples generated by the Lorenz-96 atmospheric model, to
parameterize the unresolved variables in terms of resolved variables.
Stochastic parameterization is achieved by auto-regressive modelling of noise.
We utilize the ensemble Kalman filter for data assimilation, where observations
(direct measurements) are assimilated in the low-dimensional stochastic
parameterized model to provide predictions. Finally, we compare the predictions
of compressed sensing and Wilk's polynomial regression to demonstrate the
potential effectiveness of the proposed methodology.


  We present here a nearly complete census of classical Cepheids in the
Magellanic System. The sample extends the set of Cepheids published in the past
by the Optical Gravitational Lensing Experiment (OGLE) to the outer regions of
the Large (LMC) and Small Magellanic Cloud (SMC). The entire collection
consists of 9535 Cepheids of which 4620 belong to the LMC and 4915 are members
of the SMC. We provide the I- and V-band time-series photometry of the
published Cepheids, their finding charts, and basic observational parameters.
  Based on this unique OGLE sample of Cepheids we present updated
period--luminosity relations for fundamental, first, and second mode of
pulsations in the I- and V-bands and for the W_I extinction-free Wesenheit
index. We also show the distribution of classical Cepheids in the Magellanic
System. The OGLE collection contains several classical Cepheids in the
Magellanic Bridge - the region of interaction between the Magellanic Clouds.
The discovery of classical Cepheids and their estimated ages confirm the
presence of young stellar population between these galaxies.


  Motivated by the long-time transport properties of quantum waves in weakly
disordered media, the present work puts random Schr\"odinger operators into a
new spectral perspective. Based on a stationary random version of a Floquet
type fibration, we reduce the description of the quantum dynamics to a fibered
family of abstract spectral perturbation problems on the underlying probability
space. We state a natural resonance conjecture for these fibered operators: in
contrast with periodic and quasiperiodic settings, this would entail that Bloch
waves do not exist as extended states, but rather as resonant modes, and this
would justify the expected exponential decay of time correlations. Although
this resonance conjecture remains open, we develop new tools for spectral
analysis on the probability space, and in particular we show how ideas from
Malliavin calculus lead to rigorous Mourre type results: we obtain an
approximate dynamical resonance result and the first spectral proof of the
decay of time correlations on the kinetic timescale. This spectral approach
suggests a whole new way of circumventing perturbative expansions and
renormalization techniques.


  Anthropic reasoning is a critical tool to understand probabilities,
especially in a large universe or multiverse. According to anthropic reasoning,
we should consider ourselves typical among members of a reference class that
must include all subjectively indistinguishable observers. We discuss here
whether such a reference class, which we assume must include computer
simulations, must also include computers that replay previous simulations,
magnetic tapes that store but do not "run" the simulation, and even abstract
mathematical functions. We do not see any clear criterion for excluding these
anomalous observers, but their presence is deeply troubling to the idea of
anthropic reasoning.


  Si nanocrystals have been extensively studied because of their novel
properties and their potential applications in electronic, optoelectronic,
photovoltaic, thermoelectric and biological devices. These new properties are
achieved through the combination of the quantum confinement of carriers and the
strong influence of surface chemistry. As in the case of bulk Si the tuning of
the electronic, optical and transport properties is related to the possibility
of doping, in a controlled way, the nanocrystals. This is a big challenge since
several studies have revealed that doping in Si nanocrystals differs from the
one of the bulk. Theory and experiments have underlined that doping and
codoping are influenced by a large number of parameters such as size, shape,
passivation and chemical environment of the silicon nanocrystals. However, the
connection between these parameters and dopant localization as well as the
occurrence of self-purification effects are still not clear. In this review we
summarize the latest progress in this fascinating research field considering
free-standing and matrix-embedded Si nanocrystals both from the theoretical and
experimental point of view, with special attention given to the results
obtained by ab-initio calculations and to size-, surface- and interface-induced
effects.


  We report on the selective addressing of an individual atom in a pair of
single-atom microtraps separated by $3\;\mu$m. Using a tunable light-shift, we
render the selected atom off-resonant with a global Rydberg excitation laser
which is resonant with the other atom, making it possible to selectively block
this atom from being excited to the Rydberg state. Furthermore we demonstrate
the controlled manipulation of a two-atom entangled state by using the
addressing beam to induce a phase shift onto one component of the wave function
of the system, transferring it to a dark state for the Rydberg excitation
light. Our results are an important step towards implementing quantum
information processing and quantum simulation with large arrays of Rydberg
atoms.


  Quadratic Lyapunov function has been widely used in the analysis of linear
time invariant (LTI) systems ever since it has shown that the existence of such
quadratic Lyapunov function certifies the stability of the LTI system. In this
work, the problem of finding upper and lower bounds for the
$L_{\infty}$-induced norm of the LTI system is considered. Quadratic Lyapunov
functions are used to find the star norm, the best upper on the
$L_{\infty}$-induced norm, by bounding the unit peak input reachable sets by
inescapable ellipsoids. Instead, a more general class of homogeneous Lyapunov
functions is used to get less conservative upper bounds on the
$L_{\infty}$-induced norm and better conservative approximations for the
reachable sets than those obtained using standard quadratic Lyapunov functions.
The homogeneous Lyapunov function for the LTI system is considered to be a
quadratic Lyapunov function for a higher-order system obtained by Lifting the
LTI system via Kronecker product. Different examples are provided to show the
significant improvements on the bounds obtained by using Homogeneous Lyapunov
functions.


  A unified description of single-pion photoproduction data, together with
pion- and eta-hadroproduction data, has been achieved in a Chew-Mandelstam
parametrization which is consistent with unitarity at the two-body level.
Energy-dependent and single-energy partial wave analyses of pion
photoproduction data have been performed and compared to previous SAID fits and
multipoles from the Mainz and Bonn-Gatchina groups.


  We have proved in a previous paper that a space-time Brownian motion
conditioned to remain in a Weyl chamber associated to an affine Kac-Moody Lie
algebra is distributed as the radial part process of a Brownian sheet on the
compact real form of the underlying finite dimensional Lie algebra, the radial
part being defined considering the coadjoint action of a loop group on the dual
of a centrally extended loop algebra. We present here a very brief proof of
this result based on a time inversion argument and on elementary stochastic
differential calculus.


  Trapped interlayer excitons (IXs) in MoSe2-WSe2 heterobilayers have generated
interest for use as single quantum emitter arrays and as an opportunity to
study moir\'e physics in transition metal dichalcogenide (TMD)
heterostructures. IXs are spatially indirectly excitons comprised of an
electron in the MoSe2 layer bound to a hole in the WSe2 layer. Previous reports
of spectrally narrow (<1 meV) photoluminescence (PL) emission lines at low
temperature have been attributed to IXs localized by the moir\'e potential
between the TMD layers. Here, we show that spectrally narrow IX PL lines are
present even when the moir\'e potential is suppressed by inserting a bilayer
hexagonal boron nitride (hBN) spacer between the TMD layers. We directly
compare the doping, electric field, magnetic field, and temperature dependence
of IXs in a directly contacted MoSe2-WSe2 region to those in a region separated
by bilayer hBN. Our results show that the localization potential resulting in
the narrow PL lines is independent of the moir\'e potential, and instead likely
due to extrinsic effects such as nanobubbles or defects. We show that while the
doping, electric field, and temperature dependence of the narrow IX lines is
similar for both regions, their excitonic g-factors have opposite signs,
indicating that the IXs in the directly contacted region are trapped by both
moir\'e and extrinsic localization potentials.


  Among algorithms used for sensor fusion for attitude estimation in unmanned
aerial vehicles, the Extended Kalman Filter (EKF) is the most commonly used for
estimation. In this paper, we propose a new version of H2 estimation called
extended H2 estimation that can overcome the limitations of the extended Kalman
Filter, specifically with respect to computational speed, memory usage, and
root mean squared error. We formulate a new attitude-estimation algorithm,
where the filter gain is designed offline about a nominal operating point, but
the filter dynamics is implemented using the nonlinear system dynamics. We
refer to this implementation of the H2 optimal estimator as the extended H2
estimator. The solution presented is tested on two cases, corresponding to slow
and rapid motions, and compared against the EKF in the performance metrics
mentioned above.


  Within the Type-I seesaw mechanism, quantum effects of the right-handed (RH)
neutrinos in the gravitational background lead to an asymmetric propagation of
lepton and anti-leptons which allows a Ricci scalar and neutrino Dirac-Yukawa
coupling dependent chemical potential and therefore a lepton asymmetry in
equilibrium. At high temperature, lepton number violating scattering processes
try to maintain a dynamically generated lepton asymmetry in equilibrium.
However, when the temperature drops down, the interactions become weaker, and
the asymmetry freezes out. The frozen out asymmetry can act as a pre-existing
asymmetry prior to the standard Fukugita-Yanagida leptogenesis phase ($T_i\sim
M_i$, where $M_i$ is the mass of $i$th RH neutrino). It is then natural to
consider the viability of gravitational leptogenesis for a given RH mass
spectrum which is not consistent with successful leptogenesis from decays.
Primary threat to this gravity-induced lepton asymmetry to be able to
successfully reproduce the observed baryon-to-photon ratio is the lepton number
violating washout processes at $T_i\sim M_i$. In a minimal seesaw set up with
two RH neutrinos, these washout processes are strong enough to erase a
pre-existing asymmetry of significant magnitude. We show that when effects of
flavour on the washout processes are taken into account, the mechanism opens up
the possibility of successful leptogenesis (gravitational) for a mass spectrum
$M_2\gg 10^9 {\rm GeV}\gg M_1$ with $M_1 \gtrsim 6.3 \times 10^6$ GeV. We then
briefly discuss how, in general, the mechanism leaves its imprints on the low
energy CP phases and absolute light neutrino mass scale.


  Block Floating Point (BFP) arithmetic is currently seeing a resurgence in
interest because it requires less power, less chip area, and is less
complicated to implement in hardware than standard floating point arithmetic.
This paper explores the application of BFP to mixed- and progressive-precision
multigrid methods, enabling the solution of linear elliptic partial
differential equations (PDEs) in energy- and hardware-efficient integer
arithmetic. While most existing applications of BFP arithmetic tend to use
small block sizes, the block size here is chosen to be maximal such that
matrices and vectors share a single exponent for all entries. This is sometimes
also referred to as a scaled fixed-point format. We provide algorithms for
BLAS-like routines for BFP arithmetic that ensure exact vector-vector and
matrix-vector computations up to a specified precision. Using these algorithms,
we study the asymptotic precision requirements to achieve
discretization-error-accuracy. We demonstrate that some computations can be
performed using as little as 4-bit integers, while the number of bits required
to attain a certain target accuracy is similar to that of standard floating
point arithmetic. Finally, we present a heuristic for full multigrid in BFP
arithmetic based on saturation and truncation that still achieves
discretization-error-accuracy without the need for expensive normalization
steps of intermediate results.


  When annealing a 4H silicon carbide (SiC) crystal, a sequence of optically
active defect centers occurs among which the TS center is a prominent example.
Here, we present low-temperature photoluminescence analyses on the single
defect level. They reveal that the three occurring spectral signatures TS1, TS2
and TS3 originate from one single defect. Their polarization dependences expose
three different crystallographic orientations in the basal plane, which relate
to the projections of the nearest neighbor directions. Accordingly, we find a
three-fold level-splitting in ensemble studies, when applying mechanical
strain. This dependency is quantitatively calibrated. A complementary
electrical measurement, deep level transient spectroscopy, reveals a charge
transition level of the TS defect at 0.6 eV above the valence band. For a
future identification, this accurate characterization of its optical and
electronic properties along with their response to mechanical strain is a
milestone.


  We present a Green's function technique for studying the nonlinear
conductance of a nanocontact system with two electrodes at different chemical
potentials. The retarded Green's function for a single-impurity Anderson model
with two reservoirs is obtained in terms of a $5\times 5$ matrix in which the
effect of bias is contained. A complete set of basis vectors for the
single-impurity Anderson model has been provided before formulating the Green's
function. Finally, we present a self-consistent method to fix the undetermined
quantities existing in the matrix elements for the retarded Green's function.


  We present magneto-hydrodynamic simulation results for heterogeneous systems.
Heterogeneous architectures combine high floating point performance many-core
units hosted in conventional server nodes. Examples include Graphics Processing
Units (GPU's) and Cell. They have potentially large gains in performance, at
modest power and monetary cost. We implemented a magneto-hydrodynamic (MHD)
simulation code on a variety of heterogeneous and multi-core architectures ---
multi-core x86, Cell, Nvidia and ATI GPU --- in different languages, FORTRAN,
C, Cell, CUDA and OpenCL. We present initial performance results for these
systems. To our knowledge, this is the widest comparison of heterogeneous
systems for MHD simulations. We review the different challenges faced in each
architecture, and potential bottlenecks. We conclude that substantial gains in
performance over traditional systems are possible, and in particular that is
possible to extract a greater percentage of peak theoretical performance from
some systems when compared to x86 architectures.


  For Einstein four-manifolds with positive scalar curvature, we derive
relations among various positivity conditions on the curvature tensor, some of
which are of great importance in the study of the Ricci flow. These relations
suggest possible new ideas to study the well-known rigidity conjecture for
positively curved Einstein four-manifolds.


  Indoor localization systems based on Visible Light Communication (VLC) have
shown promising advantages compared with systems based on other wireless
technologies. In these systems, many VLC light-emitting diode (LED) anchors are
employed in an indoor space in which location identification messages are sent
to user devices in small packets. In normal beacon network models,
micro-controller (MCU) or low-end system-on-chip (SoC) are often the
coordinators which configure messages for one or many VLC-LED bulbs. In this
paper, we discuss about processing overload and implementation cost of the two
typical models of VLC beacon network in scenarios of a hundred of VLC-LED
anchors are taken into account. Finally, an FPGA-based centralized VLC
transmitter and its aided Nios II-based system has been introduced to enhance
the performance of the VLC beacon network. Besides, due to the centralized
processing, our system model is considered to be more cost-efficient than the
dedicated-processor-based models


  In this paper, we describe a new class of fast solvers for separable elliptic
partial differential equations in cylindrical coordinates $(r,\theta,z)$ with
free-space radiation conditions. By combining integral equation methods in the
radial variable $r$ with Fourier methods in $\theta$ and $z$, we show that
high-order accuracy can be achieved in both the governing potential and its
derivatives. A weak singularity arises in the Fourier transform with respect to
$z$ that is handled with special purpose quadratures. We show how these solvers
can be applied to the evaluation of the Coulomb collision operator in kinetic
models of ionized gases.


  We present a sample of 40 Ultra Steep Spectrum (USS, $\alpha \leq -1.3$,
$S_{\nu}\propto \nu^{\alpha}$) radio sources selected from the Westerbork in
the Southern Hemisphere (WISH) catalog. The USS sources have been imaged in
K--band at the Cerro Tololo Inter-American Observatory (CTIO) and with the Very
Large Telescope at Cerro Paranal. We also present VLT, Keck and Willian
Herschel Telescope(WHT) optical spectroscopy of 14 targets selection from 4
different USS samples. For 12 sources, we have been able to determine the
redshifts, including 4 new radio galaxies at z > 3. We find that most of our
USS sources have predominantly small (6'') radio sizes and faint magnitudes
(K~18). The mean K-band counterpart magnitude is $\bar{K}$=18.6. The expected
redshift distribution estimated using the Hubble K-z diagram has a mean of
$\bar{z}_{exp}$$\sim$2.13, which is higher than the predicted redshift obtained
for the SUMSS-NVSS sample and the expected redshift obtained in the 6C$^{**}$
survey. The compact USS sample analyzed here may contain a higher fraction of
galaxies which are high redshift and/or are heavily obscured by dust. Using the
74, 352 and 1400 MHz flux densities of a sub-sample, we construct a radio
colour-colour diagram. We find that all but one of our USS sources have a
strong tendency to flatten below 352 MHz. We also find that the highest
redshift source from this paper (at z=3.84) does not show evidence for spectral
flattening down to 151 MHz. This suggests that very low frequency selected USS
samples will likely be more efficient to find high redshift galaxies.


  As an unusual type of anomalous diffusion behavior, superballistic transport
is not well known but has been experimentally simulated recently. Quantum
superballistic transport models to date are mainly based on connected
sublattices which are constructed to have different properties. In this work,
we show that both quantum and classical superballistic transport in the
momentum space can occur in a simple periodically driven Hamiltonian system,
namely, a relativistic kicked-rotor system with a nonzero mass term. The
nonzero mass term essentially realizes a junction-like scenario: regimes with
low or high momentum values have different dispersion relations and hence
different transport properties. It is further shown that the quantum and
classical superballistic transport should occur under much different choices of
the system parameters. The results are of interest to studies of anomalous
transport, quantum and classical chaos, and the issue of quantum-classical
correspondence.


  We study a particular class of moving average processes which possess a
property called localisability. This means that, at any given point, they admit
a ``tangent process'', in a suitable sense. We give general conditions on the
kernel g defining the moving average which ensures that the process is
localisable and we characterize the nature of the associated tangent processes.
Examples include the reverse Ornstein-Uhlenbeck process and the multistable
reverse Ornstein-Uhlenbeck process. In the latter case, the tangent process is,
at each time t, a L\'evy stable motion with stability index possibly varying
with t. We also consider the problem of path synthesis, for which we give both
theoretical results and numerical simulations.


  A system's invariance under Galilean transformation implies three locally
conserved densities. Including them as variables, the thermodynamics is
rendered explicitly frame independent, dissipative mass currents are shown to
vanish, and spontaneously broken Galilean symmetry becomes a sensible concept
in condensed systems.


  Software requirement selection aims to find an optimal subset of the
requirements with the highest value while respecting the budget. But the value
of a requirement may depend on the presence or absence of other requirements in
the optimal subset. Existing requirement selection methods, however, do not
consider Value Dependencies, thus increasing the risk of value loss. To address
this, we have proposed Dependency-Aware Requirement Selection (DARS) method
with two main components: (i) a fuzzy-based technique for identifying and
modeling value dependencies, and (ii) an Integer Programming model that takes
into account value dependencies in software requirement selection. We have
further, proposed an alternative optimization model for situations where
quantifying value dependencies is hard. The scalability of DARS and its
effectiveness in reducing the risk of value loss are demonstrated through
exhaustive simulations.


  I show that if a dimensionless parameter is tuned to be close to the boundary
of the positivity domain and symmetry breaking is driven by a cubic term in the
Lagrangian, the scale of the physics of symmetry breaking in a quantum field
theory as measured by the Higgs mass can be much greater than the dimensional
scales in the classical Lagrangian. Radiative corrections produce large and
physically important corrections, helping to stabilize the large VEV. The
resulting picture contrasts sharply with the "modern" view of QFT as an
effective field theory. I describe how this mechanism might produce the GUT
scale in an SU(5) model in which the dimensional parameters in the Lagrangian
are at the low scale.


  We study the level-statistics of a disordered system undergoing the Anderson
type metal-insulator transition. The disordered Hamiltonian is a sparse random
matrix in the site representation and the statistics is obtained by taking an
ensemble of such matrices. It is shown that the transition of levels due to
change of various parameters e.g. disorder, system size, hopping rate can be
mapped to the perturbation driven evolution of the eigenvalues of an ensemble
subjected to Wigner-Dyson type perturbation with an initial state given by a
Poisson ensemble; the mapping is then used to obtain desired
level-correlations.


  In (2+1)-dimensional pure gravity with cosmological constant, the dynamics of
double torus universe with pinching parameter is investigated. Each mode of
affine stretching deformation is illustrated in the context of horizontal
foliation along the holomorphic quadratic differential. The formulation of the
Einstein Hilbert action for the parameters of the affine stretching is
developed. Then the dynamics along one holomorphic quadratic differential will
be solved concretely.


  The ``14-1-11'' phase compounds based on magnetic Mn ions and typified by
Ca14MnBi11 and Ba14MnBi11 show unusual magnetic behavior, but the large number
(104) of atoms in the primitive cell has precluded any previous full electronic
structure study. Using an efficient, local orbital based method within the
local spin density approximation to study the electronic structure, we find a
gap between a bonding valence band complex and an antibonding conduction band
continuum. The bonding bands lack one electron per formula unit of being
filled, making them low carrier density p-type metals. The hole resides in the
MnBi4 tetrahedral unit and partially compensates the high spin d^5 Mn moment,
leaving a net spin near 4 \mu_B that is consistent with experiment. These
manganites are composed of two disjoint but interpenetrating `jungle gym'
networks of spin 4/2 MnBi4^{9-} units with ferromagnetic interactions within
the same network, and weaker couplings between the networks whose sign and
magnitude is sensitive to materials parameters. Ca14MnBi11 is calculated to be
ferromagnetic as observed, while for Ba14MnBi11 (which is antiferromagnetic)
the ferro- and antiferromagnetic states are calculated to be essentially
degenerate. The band structure of the ferromagnetic states is very close to
half metallic.


  This paper presents the Relational Machine Calculus (RMC): a simple,
foundational model of first-order relational programming. The RMC originates
from the Functional Machine Calculus (FMC), which generalizes the
lambda-calculus and its standard call-by-name stack machine in two directions.
One, "locations", introduces multiple stacks, which enable effect operators to
be encoded into the abstraction and application constructs. The second,
"sequencing", introduces the imperative notions of "skip" and "sequence",
similar to kappa-calculus and concatenative programming languages. The key
observation of the RMC is that the first-order fragment of the FMC exhibits a
latent duality which, given a simple decomposition of the relevant
constructors, can be concretely expressed as an involution on syntax.
Semantically, this gives rise to a sound and complete calculus for string
diagrams of Frobenius monoids. We consider unification as the corresponding
symmetric generalization of beta-reduction. By further including standard
operators of Kleene algebra, the RMC embeds a range of computational models:
the kappa-calculus, logic programming, automata, Interaction Nets, and Petri
Nets, among others. These embeddings preserve operational semantics, which for
the RMC is again given by a generalization of the standard stack machine for
the lambda-calculus. The equational theory of the RMC (which supports reasoning
about its operational semantics) is conservative over both the first-order
lambda-calculus and Kleene algebra, and can be oriented to give a confluent
reduction relation.


  Recently, LHCb observed a double-charmed tetraquark candidate $T_{cc}^+$ and
claimed its isospin to be zero due to the absence of $T_{cc}^{++}$. However,
the absence of the $T_{cc}^{++}$ in LHCb may be due to their low production in
$pp$ collisions, thus the isospin of $T_{cc}^+$ still needs to be clarified. We
propose an efficient way to investigate the isospin property of $T_{cc}^+$ from
the Dalitz plot distribution of $T_{cc}^+\to D^+D^0\pi^0$. This method can also
be applied to other exotic candidates.


  Caching popular content in the storage of small cells is being considered as
an efficient technique to complement limited backhaul of small cells in
ultra-dense heterogeneous cellular networks. Limited storage capacity of the
small cells renders it important to determine the optimal set of files (cache)
to be placed on each small cell. In contrast to prior works on optimal caching,
in this work we study the effect of retransmissions on the optimal cache
placement policy for both static and mobile user scenarios. With the popularity
of files modeled as a Zipf distribution and a maximum n transmissions, i.e.,
n-1 retransmissions, allowed to receive each file, we determine the optimal
caching probability of the files that maximizes the hit probability. Our
closed-form optimal solutions concretely demonstrate that the optimal caching
probabilities are very sensitive to the number of retransmissions.


  Kinematical distributions of decay products of the top quark carry
information on the polarisation of the top as well as on any possible new
physics in the decay of the top quark. We construct observables in the form of
asymmetries in the kinematical distributions to probe their effects.
Charged-lepton angular distributions in the decay are insensitive to anomalous
couplings to leading order. Hence these can be a robust probe of top
polarisation. However, these are difficult to measure in the case of highly
boosted top quarks as compared to energy distributions of decay products. These
are then sensitive, in general, to both top polarisation and top anomalous
couplings. We compare various asymmetries for their sensitivities to the
longitudinal polarisation of the top quark as well as to possible new physics
in the $Wtb$ vertex, paying special attention to the case of highly boosted top
quarks. We perform a $\chi ^2$- analysis to determine the regions in the
longitudinal polarisation of the top quark and the couplings of the $Wtb$
vertex constrained by different combinations of the asymmetries. Moreover, we
find that use of observables sensitive to the longitudinal top polarisation can
add to the sensitivity to which the $Wtb$ vertex can be probed.


  We study synchronization properties of coupled oscillators on networks that
allow description in terms of global mean field coupling. These models
generalize the standard Kuramoto-Sakaguchi model, allowing for different
contributions of oscillators to the mean field and to different forces from the
mean field on oscillators. We present the explicit solutions of
self-consistency equations for the amplitude and frequency of the mean field in
a parametric form, valid for noise-free and noise-driven oscillators. As an
example we consider spatially spreaded oscillators, for which the coupling
properties are determined by finite velocity of signal propagation.


  We present results from simulations of rotating magnetized turbulent
convection in spherical wedge geometry representing parts of the latitudinal
and longitudinal extents of a star. Here we consider a set of runs for which
the density stratification is varied, keeping the Reynolds and Coriolis numbers
at similar values. In the case of weak stratification, we find quasi-steady
dynamo solutions for moderate rotation and oscillatory ones with poleward
migration of activity belts for more rapid rotation. For stronger
stratification, the growth rate tends to become smaller. Furthermore, a
transition from quasi-steady to oscillatory dynamos is found as the Coriolis
number is increased, but now there is an equatorward migrating branch near the
equator. The breakpoint where this happens corresponds to a rotation rate that
is about 3-7 times the solar value. The phase relation of the magnetic field is
such that the toroidal field lags behind the radial field by about $\pi/2$,
which can be explained by an oscillatory $\alpha^2$ dynamo caused by the sign
change of the $\alpha$-effect about the equator. We test the domain size
dependence of our results for a rapidly rotating run with equatorward migration
by varying the longitudinal extent of our wedge. The energy of the axisymmetric
mean magnetic field decreases as the domain size increases and we find that an
$m=1$ mode is excited for a full $2\pi$ azimuthal extent, reminiscent of the
field configurations deduced from observations of rapidly rotating late-type
stars.


  Excerpts are widely used to preview and promote musical works. Effective
excerpts induce consumption of the source musical work and thus generate
revenue. Yet, what makes an excerpt effective remains unexplored. We leverage a
policy change by Apple that generates quasi-exogenous variation in the excerpts
of songs in the iTunes Music Store to estimate that having a 60 second longer
excerpt increases songs' unique monthly listeners by 5.4% on average, by 9.7%
for lesser known songs, and by 11.1% for lesser known artists. This is
comparable to the impact of being featured on the Spotify Global Top 50
playlist. We develop measures of musical repetition and unpredictability to
examine information provision as a mechanism, and find that the
demand-enhancing effect of longer excerpts is suppressed when they are
repetitive, too predictable, or too unpredictable. Our findings support
platforms' adoption of longer excerpts to improve content discovery and our
measures can help inform excerpt selection in practice.


  We consider Brownian motion in a circular disk $\Omega$, whose boundary
$\p\Omega$ is reflecting, except for a small arc, $\p\Omega_a$, which is
absorbing. As $\epsilon=|\partial \Omega_a|/|\partial \Omega|$ decreases to
zero the mean time to absorption in $\p\Omega_a$, denoted $E\tau$, becomes
infinite. The narrow escape problem is to find an asymptotic expansion of
$E\tau$ for $\epsilon\ll1$. We find the first two terms in the expansion and an
estimate of the error. The results are extended in a straightforward manner to
planar domains and two-dimensional Riemannian manifolds that can be mapped
conformally onto the disk. Our results improve the previously derived expansion
for a general smooth domain, $E\tau =
\ds{\frac{|\Omega|}{D\pi}}[\log\ds{\frac{1}{\epsilon}}+O(1)],$ ($D$ is the
diffusion coefficient) in the case of a circular disk. We find that the mean
first passage time from the center of the disk is $E[\tau |
\x(0)=\mb{0}]=\ds{\frac{R^2}{D}}[\log\ds{\frac{1}{\epsilon}} + \log 2
+\ds{{1/4}} + O(\epsilon)]$. The second term in the expansion is needed in real
life applications, such as trafficking of receptors on neuronal spines, because
$\log\ds{\frac{1}{\epsilon}}$ is not necessarily large, even when $\epsilon$ is
small. We also find the singular behavior of the probability flux profile into
$\p\Omega_a$ at the endpoints of $\p\Omega_a$, and find the value of the flux
near the center of the window.


  We report experimentally and in theory on the detection of edge information
in digital images using ultrafast spiking optical artificial neurons towards
convolutional neural networks (CNNs). In tandem with traditional convolution
techniques, a photonic neuron model based on a Vertical-Cavity Surface Emitting
Laser (VCSEL) is implemented experimentally to threshold and activate fast
spiking responses upon the detection of target edge features in digital images.
Edges of different directionalities are detected using individual kernel
operators and complete image edge detection is achieved using gradient
magnitude. Importantly, the neuromorphic (brain-like) image edge detection
system of this work uses commercially sourced VCSELs exhibiting spiking
responses at sub-nanosecond rates (many orders of magnitude faster than
biological neurons) and operating at the telecom wavelength of 1300 nm; hence
making our approach compatible with optical communication and data-center
technologies. These results therefore have exciting prospects for ultrafast
photonic implementations of neural networks towards computer vision and
decision making systems for future artificial intelligence applications.


  Cloud computing, offering on-demand access to computing resources through the
Internet and the pay-as-you-go model, has marked the last decade with its three
main service models; Infrastructure as a Service (IaaS), Platform as a Service
(PaaS), and Software as a Service (SaaS). The lightweight nature of containers
compared to virtual machines has led to the rapid uptake of another in recent
years, called Containers as a Service (CaaS), which falls between IaaS and PaaS
regarding control abstraction. However, when CaaS is offered to multiple
independent users, or tenants, a multi-instance approach is used, in which each
tenant receives its own separate cluster, which reimposes significant overhead
due to employing virtual machines for isolation. If CaaS is to be offered not
just at the cloud, but also at the edge cloud, where resources are limited,
another solution is required. We introduce a native CaaS multitenancy
framework, meaning that tenants share a cluster, which is more efficient than
the one tenant per cluster model. Whenever there are shared resources,
isolation of multitenant workloads is an issue. Such workloads can be isolated
by Kata Containers today. Besides, our framework esteems the application
requirements that compel complete isolation and a fully customized environment.
Node-level slicing empowers tenants to programmatically reserve isolated
subclusters where they can choose the container runtime that suits application
needs. The framework is publicly available as liberally-licensed, free,
open-source software that extends Kubernetes, the de facto standard container
orchestration system. It is in production use within the EdgeNet testbed for
researchers.


  The current status of evaluating thermal production of lepton pairs in
high-energy collisions of heavy nuclei is discussed. After a brief survey of
emission rates from hot and dense matter, we address applications to (and
interpretations of) recent SPS data including 40 AGeV CERES results, as well as
prospects for NA60. Emphasis is put on predictions for RHIC. In particular,
implications of hadronic observables and first single-electron measurements at
$\sqrt{s}=130$ AGeV for upcoming pair spectra from PHENIX at $\sqrt{s}=200$
AGeV are assessed.


  Many practical applications of high T$_c$ superconductors involve layered
materials and magnetic fields applied on an arbitrary direction with respect to
the layers. When the anisotropy is very large, Cooper pair currents can
circulate either within or perpendicular to the layers. Thus, tilted magnetic
fields lead to intertwined lattices of Josephson and Abrikosov vortices, with
quantized circulation across and within layers, respectively. Transport in such
intertwined lattices has been studied in detail, but direct observation and
manipulation of vortices remains challenging. Here we present magnetic force
microscopy experiments in tilted magnetic fields in the extremely quasi-two
dimensional superconductor $Bi_{2}Sr_{2}CaCu_{2}O_{8}$. We trigger Abrikosov
vortex motion in between Josephson vortices, and find that Josephson vortices
in different layers can be brought on top of each other. Our measurements
suggest that intertwined lattices in tilted magnetic fields can be
intrinsically easy to manipulate thanks to the mutual interaction between
Abrikosov and Josephson vortices.


  The distribution of photoelectrons acquired in angle-resolved photoemission
spectroscopy can be mapped onto energy-momentum space of the Bloch electrons in
the crystal. The explicit forms of the mapping function $f$ depend on the
configuration of the apparatus as well as on the type of the photoelectron
analyzer. We show that the existence of the analytic forms of $f^{\text{-}1}$
is guaranteed in a variety of setups. The variety includes the case when the
analyzer is equipped with a photoelectron deflector. Thereby, we provide a
demonstrative mapping program implemented by an algorithm that utilizes both
$f$ and $f^{\text{-}1}$. The mapping methodology is also usable in other
spectroscopic methods such as momentum-resolved electron-energy loss
spectroscopy.


  The predictive power and overall computational efficiency of
Diffusion-convolutional neural networks make them an attractive choice for node
classification tasks. However, a naive dense-tensor-based implementation of
DCNNs leads to $\mathcal{O}(N^2)$ memory complexity which is prohibitive for
large graphs. In this paper, we introduce a simple method for thresholding
input graphs that provably reduces memory requirements of DCNNs to O(N) (i.e.
linear in the number of nodes in the input) without significantly affecting
predictive performance.


  Hexagonal diamond has been predicted computationally to display extraordinary
physical properties including a hardness that exceeds cubic diamond. However, a
recent electron microscopy study has shown that so-called hexagonal diamond
samples are in fact not discrete materials but faulted and twinned cubic
diamond. We now provide a quantitative analysis of cubic and hexagonal stacking
in diamond samples by analysing X-ray diffraction data with the DIFFaX software
package. The highest fractions of hexagonal stacking we find in materials which
were previously referred to as hexagonal diamond are below 60%. The remainder
of the stacking sequences are cubic. We show that the cubic and hexagonal
sequences are interlaced in a complex way and that naturally occurring
Lonsdaleite is not a simple phase mixture of cubic and hexagonal diamond.
Instead, it is structurally best described as stacking disordered diamond. The
future experimental challenge will be to prepare diamond samples beyond 60%
hexagonality and towards the so far elusive 'perfect' hexagonal diamond.


  With the advent of surveys generating multi-epoch photometry and the
discovery of large numbers of variable stars, the classification of these stars
has to be automatic. We have developed such a classification procedure for
about 1700 stars from the variable star catalogue of ASAS 1-2 (All Sky
Automated Survey, Pojmanski 2000) by selecting the periodic ones and by
applying an unsupervised Bayesian classifier using parameters obtained through
a Fourier decomposition of the light curve. For irregular light curves we used
the period and moments of the magnitude distribution for the classification. In
the case of ASAS 1-2, 83% of variable objects are red giants. A general
relation between the period and amplitude is found for a large fraction of
those stars. The selection led to 302 periodic and 1429 semi-periodic stars
which are classified in 6 major groups: eclipsing binaries, "sinusoidal
curves", Cepheids, small amplitude red variables, SR and Mira stars. The type
classification error level is estimated to be about 7%.


  We carry out a systematical study of the size scaling of Liouvillian gap in
boundary-dissipated one-dimensional quasiperiodic and disorder systems. By
treating the boundary-dissipation operators as a perturbation, we derive an
analytical expression of the Liouvillian gap, which indicates clearly the
Liouvillian gap being proportional to the minimum of boundary densities of
eigenstates of the underlying Hamiltonian, and thus give a theoretical
explanation why the Liouvillian gap has different size scaling relation in the
extended and localized phase. While the Liouvillian gap displays a power-law
size scaling $\Delta_{g}\propto L^{- 3}$ in the extended phase, our analytical
result unveils that the Liouvillian gap fulfills an exponential scaling
relation $\Delta_{g}\propto e^{- \kappa L}$ in the localized phase, where
$\kappa$ takes the largest Lyapunov exponent of localized eigenstates of the
underlying Hamiltonian. By scrutinizing the extended Aubry-Andr\'{e}-Harper
model, we numerically confirm that the Liouvillian gap fulfills the exponential
scaling relation and the fitting exponent $\kappa$ coincides pretty well with
the analytical result of Lyapunov exponent. The exponential scaling relation is
further verified numerically in other one-dimensional quasiperiodic and random
disorder models. We also study the relaxation dynamics and show the inverse of
Liouvillian gap giving a reasonable timescale of asymptotic convergence to the
steady state.


  We explicitly show that symmetric Frobenius structures on a
finite-dimensional, semi-simple algebra stand in bijection to homotopy fixed
points of the trivial SO(2)-action on the bicategory of finite-dimensional,
semi-simple algebras, bimodules and intertwiners. The results are motivated by
the 2-dimensional Cobordism Hypothesis for oriented manifolds, and can hence be
interpreted in the realm of Topological Quantum Field Theory.


  A time dependent variational principle is used to dequantize a second order
quadrupole boson Hamiltonian. The classical equations for the generalized
coordinate and the constraint for angular momentum are quantized and then
analytically solved. A generalized Holmberg-Lipas formula for energies is
obtained. A similar $J(J+1)$ dependence is provided by the coherent state model
(CSM) in the large deformation regime, by using an expansion in powers of $1/x$
for energies, with $x$ denoting a deformation parameter squared. A simple
compact expression is also possible for the near vibrational regime. These
three expressions have been used for 44 nuclei covering regions characterized
by different dynamic symmetries or in other words belonging to the all known
nuclear phases. Nuclei satisfying the specific symmetries of the critical point
in the phase transitions $O(6)\to SU(3)$, $SU(5)\to SU(3)$ have been also
considered. The agreement between the results and the corresponding
experimental data is very good. This is reflected in very small r.m.s. values
of deviations.


  The election forecasting 'industry' is a growing one, both in the volume of
scholars producing forecasts and methodological diversity. In recent years a
new approach has emerged that relies on social media and particularly Twitter
data to predict election outcomes. While some studies have shown the method to
hold a surprising degree of accuracy there has been criticism over the lack of
consistency and clarity in the methods used, along with inevitable problems of
population bias. In this paper we set out a 'baseline' model for using Twitter
as an election forecasting tool that we then apply to the UK 2015 General
Election. The paper builds on existing literature by extending the use of
Twitter as a forecasting tool to the UK context and identifying its
limitations, particularly with regard to its application in a multi-party
environment with geographic concentration of power for minor parties.


  This study presents a novel multimodal fusion model for three-dimensional
mineral prospectivity mapping (3D MPM), effectively integrating structural and
fluid information through a deep network architecture. Leveraging Convolutional
Neural Networks (CNN) and Multilayer Perceptrons (MLP), the model employs
canonical correlation analysis (CCA) to align and fuse multimodal features.
Rigorous evaluation on the Jiaojia gold deposit dataset demonstrates the
model's superior performance in distinguishing ore-bearing instances and
predicting mineral prospectivity, outperforming other models in result
analyses. Ablation studies further reveal the benefits of joint feature
utilization and CCA incorporation. This research not only advances mineral
prospectivity modeling but also highlights the pivotal role of data integration
and feature alignment for enhanced exploration decision-making.


  We are concerned with the long time behavior of the stochastic Navier--Stokes
system for compressible fluids in dimension two and three. In this setting, the
part of the phase space occupied by the solution depends sensitively on the
choice of the initial state. Our main results are threefold. (i) The kinetic
energy of a solution is universally and asymptotically bounded, independent of
the initial datum. (ii) Time shifts of a solution with initially controlled
energy are asymptotically compact and generate an entire solution defined for
all $t\in R$. (iii) Every solution with initially controlled energy generates a
stationary solution and even an ergodic stationary solution on the closure of
the convex hull of its $\omega$--limit set.


  Transformers have become one of the foundational architectures in point cloud
analysis tasks due to their excellent global modeling ability. However, the
attention mechanism has quadratic complexity, making the design of a linear
complexity method with global modeling appealing. In this paper, we propose
PointMamba, transferring the success of Mamba, a recent representative state
space model (SSM), from NLP to point cloud analysis tasks. Unlike traditional
Transformers, PointMamba employs a linear complexity algorithm, presenting
global modeling capacity while significantly reducing computational costs.
Specifically, our method leverages space-filling curves for effective point
tokenization and adopts an extremely simple, non-hierarchical Mamba encoder as
the backbone. Comprehensive evaluations demonstrate that PointMamba achieves
superior performance across multiple datasets while significantly reducing GPU
memory usage and FLOPs. This work underscores the potential of SSMs in 3D
vision-related tasks and presents a simple yet effective Mamba-based baseline
for future research. The code is available at
https://github.com/LMD0311/PointMamba.


  Emotional Text-To-Speech (TTS) is an important task in the development of
systems (e.g., human-like dialogue agents) that require natural and emotional
speech. Existing approaches, however, only aim to produce emotional TTS for
seen speakers during training, without consideration of the generalization to
unseen speakers. In this paper, we propose ZET-Speech, a zero-shot adaptive
emotion-controllable TTS model that allows users to synthesize any speaker's
emotional speech using only a short, neutral speech segment and the target
emotion label. Specifically, to enable a zero-shot adaptive TTS model to
synthesize emotional speech, we propose domain adversarial learning and
guidance methods on the diffusion model. Experimental results demonstrate that
ZET-Speech successfully synthesizes natural and emotional speech with the
desired emotion for both seen and unseen speakers. Samples are at
https://ZET-Speech.github.io/ZET-Speech-Demo/.


  In this paper, we provide a simpler proof of the Kr\"otz--Stanton Extension
Theorem for holomorphic extensions of orbit maps in unitary irreducible
representations of connected semisimple Lie groups. Our result is a
generalization of the previous result as it applies to Hilbert globalizations
of finitely generated admissible $(\mathfrak{g},K)$-modules for arbitrary
connected semisimple Lie groups $G$ with not necessarily finite center.
Furthermore, we give polynomial growth estimates for the norms of the
holomorphic extensions of the orbit maps of $K$-finite vectors in irreducible
unitary representations. We use this to prove that, at the boundary of the
principal crown bundle, these holomorphic extensions have boundary values in
the space of distribution vectors.


  We present an updated status of the EDGE project, which is a survey of 125
local galaxies in the $^{12}$CO($1-0$) and $^{13}$CO($1-0$) lines. We combine
the molecular data of the EDGE survey with the stellar and ionized gas maps of
the CALIFA survey to give a comprehensive view of the dependence of the star
formation efficiency, or equivalently, the molecular gas depletion time, on
various local environments, such as the stellar surface density, metallicity,
and radius from the galaxy center. This study will provide insight into the
parameters that drive the star formation efficiency in galaxies at $z \sim 0$.


  In a microservices-based system, reliability and availability are key
components to guarantee the best-in-class experience for the consumers. One of
the key advantages of microservices architecture is the ability to
independently deploy services, providing maximum change flexibility. However,
this introduces an extra complexity in managing the risk associated with every
change: any mutation of a service might cause the whole system to fail. In this
research, we would propose an algorithm to enable development teams to
determine the risk associated with each change to any of the microservices in
the system.


  In many-body systems governed by pairwise contact interactions, a wide range
of observables is linked by a single parameter, the two-body contact, which
quantifies two-particle correlations. This profound insight has transformed our
understanding of strongly interacting Fermi gases. Here, using Ramsey
interferometry, we study coherent evolution of the resonantly interacting Bose
gas, and show that it cannot be explained by only pairwise correlations. Our
experiments reveal the crucial role of three-body correlations arising from
Efimov physics, and provide a direct measurement of the associated three-body
contact.


  We compute the modification of the photon self-energy due to dynamical
diquark fluctuations developed near the critical temperature of the color
superconductivity through the Aslamasov-Larkin, Maki-Thompson and density of
states terms, which are responsible for the paraconductivity in metals at
vanishing energy and momentum. It is shown that the rate has a significant
enhancement at low invariant-mass region over a rather wide range of
temperature in the normal phase. This enhancement is worth exploration in the
relativistic heavy-ion collisions, which may thereby reveal the significance of
the diquark fluctuations in dense quark matter.


  Many interesting applications of hyperbolic systems of equations are stiff,
and require the time step to satisfy restrictive stability conditions. One way
to avoid small time steps is to use implicit time integration. Implicit
integration is quite straightforward for first order schemes. High order
schemes instead need also to control spurious oscillations, which requires
limiting in space and time also in the implicit case. We propose a framework to
simplify considerably the application of high order non oscillatory schemes
through the introduction of a low order implicit predictor, which is used both
to set up the nonlinear weights of a standard high order space reconstruction,
and to achieve limiting in time. In this preliminary work, we concentrate on
the case of a third order scheme, based on DIRK integration in time and CWENO
reconstruction in space. The numerical tests involve linear and nonlinear
scalar conservation laws.


  We have performed systematic studies of narrow Fe-K line (6.4 keV) flux
variability and Ni-K line intensity for Seyfert galaxies, using {\em Suzaku}
and {\em XMM-Newton} archival data. Significant Fe-K line variability of
several tens percents was detected for a pair of observations separated by
1000--2000 days (Cen A, IC 4329 A, NGC 3516, and NGC 4151) and 158 days (NGC
3516). These timescales are larger by a factor of 10--100 than the inner radius
of torus, consistent with the view that X-ray reflection by torus is a main
origin of a narrow Fe-K line. Ni-K line was detected with $>2\sigma$ level for
the Circinus galaxy, Cen A, MRK 3, NGC 4388, and NGC 4151. A mean and variance
of Ni-K$\alpha$ to Fe-K$\alpha$ line intensity ratio are 0.066 and 0.026,
respectively. Comparing this with the Monte-Carlo simulation of reflection, Ni
to Fe abundance ratio is 1.9$\pm$0.8 solar. We discuss the results and
possibility of Ni abundance enhancement.


  We introduce and study a class of discrete particle ensembles that naturally
arise in connection with classical random matrix ensembles, log-gases and Jack
polynomials. Under technical assumptions on a general analytic potential we
prove that the global fluctuations of these ensembles are asymptotically
Gaussian with a universal covariance that remarkably differs from its
counterpart in random matrix theory. Our main tools are certain novel algebraic
identities that we have discovered. They play a role of discrete multi-level
analogues of loop equations.


  The CMS experiment recently reported an excess consistent with an invariant
mass edge in opposite-sign same flavor (OSSF) leptons, when produced in
conjunction with at least two jets and missing transverse momentum. We provide
an interpretation of the edge in terms of (anti-)squark pair production
followed by the `golden cascade' decay for one of the squarks: $\tilde q
\rightarrow \tilde\chi_2^0 q \to \tilde l l q \to \tilde\chi_1^0 q l l$ in the
minimal supersymmetric standard model (MSSM). A simplified model involving
binos, winos, an on-shell slepton, and the first two generations of squarks
fits the event rate and the invariant mass edge. We check consistency with a
recent ATLAS search in a similar region, finding that much of the good-fit
parameter space is still allowed at the 95% confidence level (CL). However, a
combination of other LHC searches, notably two-lepton stop pair searches and
jets plus $p_T^{\rm miss}$, rule out all of the remaining parameter space at
the 95% CL.


See comment above.


  We study a theoretical and algorithmic framework for structured prediction in
the online learning setting. The problem of structured prediction, i.e.
estimating function where the output space lacks a vectorial structure, is well
studied in the literature of supervised statistical learning. We show that our
algorithm is a generalisation of optimal algorithms from the supervised
learning setting, and achieves the same excess risk upper bound also when data
are not i.i.d. Moreover, we consider a second algorithm designed especially for
non-stationary data distributions, including adversarial data. We bound its
stochastic regret in function of the variation of the data distributions.


  Suppose that every non-minimal bridge position of a knot $K$ is perturbed. We
show that if $L$ is a $(2, 2q)$-cable link of $K$, then every non-minimal
bridge position of $L$ is also perturbed.


  A source code summary of a subroutine is a brief description of that
subroutine. Summaries underpin a majority of documentation consumed by
programmers, such as the method summaries in JavaDocs. Source code
summarization is the task of writing these summaries. At present, most
state-of-the-art approaches for code summarization are neural network-based
solutions akin to seq2seq, graph2seq, and other encoder-decoder architectures.
The input to the encoder is source code, while the decoder helps predict the
natural language summary. While these models tend to be similar in structure,
evidence is emerging that different models make different contributions to
prediction quality -- differences in model performance are orthogonal and
complementary rather than uniform over the entire dataset. In this paper, we
explore the orthogonal nature of different neural code summarization approaches
and propose ensemble models to exploit this orthogonality for better overall
performance. We demonstrate that a simple ensemble strategy boosts performance
by up to 14.8%, and provide an explanation for this boost. The takeaway from
this work is that a relatively small change to the inference procedure in most
neural code summarization techniques leads to outsized improvements in
prediction quality.


  We proposed a general transformation in probabilistic teleportation, which is
based on different entanglement matching coefficients $K$ corresponding to
different unitary evolution which provides one with more flexible evolution
method experimentally. Through analysis based on the Bell basis and generalized
Bell basis measurement for two probabilistic teleportation, we suggested a
general probability of successful teleportation, which is not only determined
by the entanglement degree of transmission channels and measurement methods,
but also related to the unitary transformation in the teleportation process.


  I demonstrate that one can detect pixel gravitational microlensing events at
the rate $\sim 180\ {\rm events}\ {\rm yr}^{-1}$ and that some fraction of
events ($\sim 15$) will be good enough to measure time scales at the $20\%$
level if the experiment is carried out toward the central M31 bulge region with
a dedicated 1 m telescope and a $2{\rm K}\times2{\rm K}$ CCD. I also show that
the event rate could be significantly increased (up to a factor 6.5) if more
aggressive observation strategies are adopted. These aggressive strategies
include multiple observation sites, using a bigger telescope, and reduction of
seeing differences among images. A few years of observation could provide a
data set big enough to extract important information about the M31 bulge such
as the optical depth distribution, the mass spectrum of M31 MACHOs, and the
luminosity function, which currently cannot be obtained by other methods.
Additionally, I find that the extinction of M31 bulge light by dust in the disk
is {\it not} important and can be approximated by the model in which only
$20\%$ of light in $V$ band is extinguished over most of the bulge area.


  The exponential decay of the relative entropy associated to a fully discrete
porous-medium equation in one space dimension is shown by means of a discrete
Bakry-Emery approach. The first ingredient of the proof is an abstract discrete
Bakry-Emery method, which states conditions on a sequence under which the
exponential decay of the discrete entropy follows. The second ingredient is a
new nonlinear summation-by-parts formula which is inspired by systematic
integration by parts developed by Matthes and the first author. Numerical
simulations illustrate the exponential decay of the entropy for various time
and space step sizes.


  Tracking and identifying athletes on the pitch holds a central role in
collecting essential insights from the game, such as estimating the total
distance covered by players or understanding team tactics. This tracking and
identification process is crucial for reconstructing the game state, defined by
the athletes' positions and identities on a 2D top-view of the pitch, (i.e. a
minimap). However, reconstructing the game state from videos captured by a
single camera is challenging. It requires understanding the position of the
athletes and the viewpoint of the camera to localize and identify players
within the field. In this work, we formalize the task of Game State
Reconstruction and introduce SoccerNet-GSR, a novel Game State Reconstruction
dataset focusing on football videos. SoccerNet-GSR is composed of 200 video
sequences of 30 seconds, annotated with 9.37 million line points for pitch
localization and camera calibration, as well as over 2.36 million athlete
positions on the pitch with their respective role, team, and jersey number.
Furthermore, we introduce GS-HOTA, a novel metric to evaluate game state
reconstruction methods. Finally, we propose and release an end-to-end baseline
for game state reconstruction, bootstrapping the research on this task. Our
experiments show that GSR is a challenging novel task, which opens the field
for future research. Our dataset and codebase are publicly available at
https://github.com/SoccerNet/sn-gamestate.


  The primal cohomology $\mathbb{K}_\mathbb{Q}$ of the theta divisor $\Theta$
of a principally polarized abelian fivefold (ppav) is the direct sum of its
invariant and anti-invariant parts $\mathbb{K}_\mathbb{Q}^{+1}$, resp.
$\mathbb{K}_\mathbb{Q}^{-1}$ under the action of $-1$. For smooth $\Theta$,
these have dimension $6$ and $72$ respectively. We show that
$\mathbb{K}_\mathbb{Q}^{+1}$ consists of Hodge classes and, for a very general
ppav, $\mathbb{K}_\mathbb{Q}^{-1}$ is a simple Hodge structure of level $2$.


  The interaction between matter and squeezed light has mostly been treated
within the approximation that the field correlation time is small. Methods for
treating squeezed light with more general correlations currently involve
explicitly modeling the systems producing the light. We develop a general
purpose input-output theory for a particular form of narrowband squeezed light
-- a squeezed wave-packet mode -- that only cares about the statistics of the
squeezed field and the shape of the wave packet. This formalism allows us to
derive the input-output relations and the master equation. We also consider
detecting the scattered field using photon counting and homodyne measurements
which necessitates the derivation of the stochastic master equation. The non
Markovian nature of the field manifests itself in the master equation as a
coupled hierarchy of equations. We illustrate these with consequences for the
decay and resonance fluorescence of two-level atoms in the presence of such
fields.


  We theoretically investigate the effect of anomalous quantum correlations on
the light-induced frequency shift in the photoassociation spectrum of a
Bose-Einstein condensate (BEC). Anomalous quantum correlations arise because,
although formed from a pair of zero-momentum condensate atoms, a condensate
molecule need not dissociate back to the BEC, but may just as well form a
noncondensate atom pair with equal and opposite momentum, i.e., due to rogue
photodissociation. The uncorrelated frequency shift of the photoassociation
spectrum is to the red and linearly dependent on the laser intensity. In
contrast, anomalous correlations due to rogue dissociation lead to a
blueshifted photoassociation spectrum. For sufficiently low light intensities,
the rogue blueshift is dominant and proportional to the squareroot of
intensity.


  Rotation axis variation due to spin orbit resonance: conference report;
keywords: planetary precession, rigid body, chaos, KAM, Arnold diffusion,
averaging, celestial mechanics, classical mechanics, large deviations


  Fast and efficient detection of the qubit state in trapped ion quantum
information processing is critical for implementing quantum error correction
and performing fundamental tests such as a loophole-free Bell test. In this
work we present a simple qubit state detection protocol for a $^{171}$Yb$^+$
hyperfine atomic qubit trapped in a microfabricated surface trap, enabled by
high collection efficiency of the scattered photons and low background photon
count rate. We demonstrate average detection times of 10.5, 28.1 and
99.8\,$\upmu$s, corresponding to state detection fidelities of 99%, 99.85(1)%
and 99.915(7)%, respectively.


  Hapke proposed a convenient and widely used analytical model to describe the
spectro-photometry of granular materials. Using a compilation of the published
data, Hapke (2012, Icarus, 221, 1079-1083) recently studied the relationship of
b and c for natural examples and proposed the hockey stick relation (excluding
b>0.5 and c>0.5). For the moment, there is no theoretical explanation for this
relationship. One goal of this article is to study a possible bias due to the
retrieval method. We expand here an innovative Bayesian inversion method in
order to study into detail the uncertainties of retrieved parameters. On
Emission Phase Function (EPF) data, we demonstrate that the uncertainties of
the retrieved parameters follow the same hockey stick relation, suggesting that
this relation is due to the fact that b and c are coupled parameters in the
Hapke model instead of a natural phenomena. Nevertheless, the data used in the
Hapke (2012) compilation generally are full Bidirectional Reflectance Diffusion
Function (BRDF) that are shown not to be subject to this artifact. Moreover,
the Bayesian method is a good tool to test if the sampling geometry is
sufficient to constrain the parameters (single scattering albedo, surface
roughness, b, c, opposition effect). We performed sensitivity tests by
mimicking various surface scattering properties and various single
image-like/disk resolved image, EPF-like and BRDF-like geometric sampling
conditions. The second goal of this article is to estimate the favorable
geometric conditions for an accurate estimation of photometric parameters in
order to provide new constraints for future observation campaigns and
instrumentations.


  This work is devoted to study the asymptotic behavior of critical points
$\{(u_\varepsilon,v_\varepsilon)\}_{\varepsilon>0}$ of the Ambrosio-Tortorelli
functional. Under a uniform energy bound assumption, the usual
$\Gamma$-convergence theory ensures that $(u_\varepsilon,v_\varepsilon)$
converges in the $L^2$-sense to some $(u_*,1)$ as $\varepsilon\to 0$, where
$u_*$ is a special function of bounded variation. Assuming further the
Ambrosio-Tortorelli energy of $(u_\varepsilon,v_\varepsilon)$ to converge to
the Mumford-Shah energy of $u_*$, the later is shown to be a critical point
with respect to inner variations of the Mumford-Shah functional. As a
byproduct, the second inner variation is also shown to pass to the limit. To
establish these convergence results, interior ($\mathscr{C}^\infty$) regularity
and boundary regularity for Dirichlet boundary conditions are first obtained
for a fixed parameter $\varepsilon>0$. The asymptotic analysis is then
performed by means of varifold theory in the spirit of scalar phase transition
problems.


  We study gradings by noncommutative groups on finite dimensional Lie algebras
over an algebraically closed field of characteristic zero. It is shown that if
$L$ is gradeg by a non-abelian finite group $G$ then the solvable radical $R$
of $L$ is $G$-graded and there exists a Levi subalgebra
$B=H_1\oplus\cdots\oplus H_m$ homogeneous in $G$-grading with graded simple
summands $H_1, \ldots, H_m$. All supports $Supp~H_i, i=1\ldots, m$, are
commutative subsets of $G$.


  In this work, we consider self-similar profiles for Smoluchowski's
coagulation equation for kernels which are possibly unbounded perturbations of
the constant one. For this model, we show that the self-similar solutions for
the perturbed kernel are close in weighted $L^1$ spaces to the profile of the
unperturbed equation, i.e. the profiles are stable with respect to the
perturbation. Additionally, we revisit the problem of uniqueness for these
coagulation kernels. In fact, we will improve a corresponding result (see
arXiv:1510.03361 and ref. [22]) by relaxing the conditions on the perturbation
significantly while at the same time the corresponding proof can also be
notably shortened.


  In this paper, we propose $\tau$GAN a tensor-based method for modeling the
latent space of generative models. The objective is to identify semantic
directions in latent space. To this end, we propose to fit a multilinear tensor
model on a structured facial expression database, which is initially embedded
into latent space. We validate our approach on StyleGAN trained on FFHQ using
BU-3DFE as a structured facial expression database. We show how the parameters
of the multilinear tensor model can be approximated by Alternating Least
Squares. Further, we introduce a tacked style-separated tensor model, defined
as an ensemble of style-specific models to integrate our approach with the
extended latent space of StyleGAN. We show that taking the individual styles of
the extended latent space into account leads to higher model flexibility and
lower reconstruction error. Finally, we do several experiments comparing our
approach to former work on both GANs and multilinear models. Concretely, we
analyze the expression subspace and find that the expression trajectories meet
at an apathetic face that is consistent with earlier work. We also show that by
changing the pose of a person, the generated image from our approach is closer
to the ground truth than results from two competing approaches.


  We explore the idea of accidental dark matter (aDM) stability in the scale
invariant local $U(1)_{B-L}$ model, which is a theory for neutrino and at the
same time radiatively breaks scale invariance via quantum mechanical dynamics
in the $U(1)_{B-L}$ sector. A real singlet scalar can be accidental DM with an
accidental $Z_2$, by virtue of both extended symmetries. A $U(1)_{B-L}$ charged
complex scalar can also be a viable accidental DM due to an accidental (or
remanent) $Z_3$. They can reproduce correct relic density via the annihilations
through the conventional Higgs portal or dark Higgs portal. The dark Higgs
portal scenario is in tension with the LHC bound on $Z_{B-L}$, and only heavy
DM of a few TeVs can have correct relic density. In particular, DM may trigger
spontaneous breaking of scale Invariance (SISB). The situation is relaxed
significantly in the $Z_3$ case due to the effective semi-annihilation mode and
then light DM can be accommodated easily. In addition, the $Z_3$ model can
accommodate the GeV scale $\gamma-$ray excess from the galactic center (GC) via
semi-annihilation into pseudo Goldstone boson (PGSB). The best fit is achieved
at a DM about 52 GeV, with annihilation cross section consistent with the
thermal relic density. The invisible Higgs branching ratio is negligible
because the Higgs portal quartic coupling is very small $\lambda_{h\phi}
\lesssim 10^{-3}$.


  Post-hoc explanation methods are gaining popularity for interpreting,
understanding, and debugging neural networks. Most analyses using such methods
explain decisions in response to inputs drawn from the test set. However, the
test set may have few examples that trigger some model behaviors, such as
high-confidence failures or ambiguous classifications. To address these
challenges, we introduce a flexible model inspection framework: Bayes-TrEx.
Given a data distribution, Bayes-TrEx finds in-distribution examples with a
specified prediction confidence. We demonstrate several use cases of
Bayes-TrEx, including revealing highly confident (mis)classifications,
visualizing class boundaries via ambiguous examples, understanding novel-class
extrapolation behavior, and exposing neural network overconfidence. We use
Bayes-TrEx to study classifiers trained on CLEVR, MNIST, and Fashion-MNIST, and
we show that this framework enables more flexible holistic model analysis than
just inspecting the test set. Code is available at
https://github.com/serenabooth/Bayes-TrEx.


  We investigate the mass range of the quark-antiquark fluctuations of the
photon that are active in producing the total photoabsorption cross section in
the color dipole picture, emphasizing the notion of color transparency and
saturation. We consider the implications of measurements at future extensions
of the available electron-proton-scattering energy.


  The explainability of deep networks is becoming a central issue in the deep
learning community. It is the same for learning on graphs, a data structure
present in many real world problems. In this paper, we propose a method that is
more optimal, lighter, consistent and better exploits the topology of the
evaluated graph than the state-of-the-art methods.


  This paper presents an experimental investigation of moving grains over
subaqueous barchan dunes that consisted of spherical glass beads of known
granulometry. Prior to each test run, a pre-determined quantity of grains was
poured inside a closed conduit, and the grains settled on its bottom wall
forming one conical heap. As different turbulent water flows were imposed, each
heap evolved to a barchan dune, which was filmed with a high-speed camera. An
image processing code was written to identify some of the moving grains and
compute their velocity fields and trajectories. Our results show that the
velocity of grains varies along the barchan dune, with higher velocities
occurring close to the dune centroid, and that grains trajectories are
intermittent. Depending on the region over the dune, we found that the velocity
fields present values within 1 and 10 % of the cross-sectional mean velocity of
the fluid. Considering the average trajectories of grains moving over a given
dune, their mean displacement varies within 30 and 60 grain diameters and their
characteristic velocities within 10 and 20 % of the cross-sectional mean
velocity of the fluid. The displacement time varies between 30 and 90 % of the
settling time, and it seems to have two asymptotic behaviors: one close to bed
load inception and other far from it. When compared with bed load over a plane
bed, we observe that grains have the same mean velocity, but they travel
distances up to 5 times larger, with higher densities of moving grains.


  Many prior face anti-spoofing works develop discriminative models for
recognizing the subtle differences between live and spoof faces. Those
approaches often regard the image as an indivisible unit, and process it
holistically, without explicit modeling of the spoofing process. In this work,
motivated by the noise modeling and denoising algorithms, we identify a new
problem of face de-spoofing, for the purpose of anti-spoofing: inversely
decomposing a spoof face into a spoof noise and a live face, and then utilizing
the spoof noise for classification. A CNN architecture with proper constraints
and supervisions is proposed to overcome the problem of having no ground truth
for the decomposition. We evaluate the proposed method on multiple face
anti-spoofing databases. The results show promising improvements due to our
spoof noise modeling. Moreover, the estimated spoof noise provides a
visualization which helps to understand the added spoof noise by each spoof
medium.


  The nanometer scale beam sizes at the interaction point in linear colliders
limit the allowable motion of the final focus magnets. We have constructed a
prototype system to investigate the use of active vibration damping to control
magnet motion. Inertial sensors are used to measure the position of a test
mass, and a DSP based system provides feedback using electrostatic pushers.
Simulation and experimental results for the control of a mechanically simple
system are presented.


  In this work, we consider the error estimates of some splitting schemes for
the charged-particle dynamics under a strong magnetic field. We first propose a
novel energy-preserving splitting scheme with computational cost per step
independent from the strength of the magnetic field. Then under the maximal
ordering scaling case, we establish for the scheme and in fact for a class of
Lie-Trotter type splitting schemes, a uniform (in the strength of the magnetic
field) and optimal error bound in the position and in the velocity parallel to
the magnetic field. For the general strong magnetic field case, the modulated
Fourier expansions of the exact and the numerical solutions are constructed to
obtain a convergence result. Numerical experiments are presented to illustrate
the error and energy behaviour of the splitting schemes.


  As image generation techniques mature, there is a growing interest in
explainable representations that are easy to understand and intuitive to
manipulate. In this work, we turn to co-occurrence statistics, which have long
been used for texture analysis, to learn a controllable texture synthesis
model. We propose a fully convolutional generative adversarial network,
conditioned locally on co-occurrence statistics, to generate arbitrarily large
images while having local, interpretable control over the texture appearance.
To encourage fidelity to the input condition, we introduce a novel
differentiable co-occurrence loss that is integrated seamlessly into our
framework in an end-to-end fashion. We demonstrate that our solution offers a
stable, intuitive and interpretable latent representation for texture
synthesis, which can be used to generate a smooth texture morph between
different textures. We further show an interactive texture tool that allows a
user to adjust local characteristics of the synthesized texture image using the
co-occurrence values directly.


  A transiting planet eclipses part of the rotating stellar surface, thereby
producing an anomalous Doppler shift of the stellar spectrum. Here I review how
this "Rossiter-McLaughlin Effect" can be used to characterize exoplanetary
systems. In particular, one can measure the angle on the sky between the
orbital axis and the stellar rotation axis. This may help to discriminate among
migration theories. Measurements have been made for 4 exoplanets, and in all
cases the spin and orbital axes are fairly well-aligned. In the future, the
Rossiter-McLaughlin effect may also be important as an alternative means of
probing exoplanetary atmospheres, and for confirming the transits of objects
identified by the satellite missions Corot and Kepler.


  We study the Wigner function for the inflationary tensor perturbation defined
in the real phase space. We compute explicitly the Wigner function including
the contributions from the cubic self-interaction Hamiltonian of tensor
perturbations. Then we argue that it is no longer an appropriate description
for the probability distribution in the sense that quantum nature allows
negativity around vanishing phase variables. This comes from the non-Gaussian
wavefunction in the mixed state as a result of the non-linear interaction
between super- and sub-horizon modes. We also show that this is related to the
explicit infrared divergence in the Wigner function, in contrast to the trace
of the density matrix.


  Journalists are among the many users of large language models (LLMs). To
better understand the journalist-AI interactions, we conduct a study of LLM
usage by two news agencies through browsing the WildChat dataset, identifying
candidate interactions, and verifying them by matching to online published
articles. Our analysis uncovers instances where journalists provide sensitive
material such as confidential correspondence with sources or articles from
other agencies to the LLM as stimuli and prompt it to generate articles, and
publish these machine-generated articles with limited intervention (median
output-publication ROUGE-L of 0.62). Based on our findings, we call for further
research into what constitutes responsible use of AI, and the establishment of
clear guidelines and best practices on using LLMs in a journalistic context.


  Quark matter may appear due to a hadronic-quark transition in the core of a
hybrid star. Quarkyonic matter is an approach in which both quarks and nucleons
appear as quasi-particles in a crossover transition, and provides an explicit
realization of early ideas concerning quark matter (e.g., the MIT bag model).
This description has recently been employed by McLerran and Reddy to model
chargeless (pure neutron) matter with an approach that has the virtue that the
speed of sound rises quickly at a neutron-quark transition so as to satisfy
observational constraints on the neutron star maximum mass ($\gtrsim2M_\odot$)
and the radius of a $1.4M_\odot$ star ($R_{1.4}\lesssim 13.5$ km). Traditional
models involving first-order transitions result in softer pressure-energy
density relations that have difficulty satisfying these constraints except with
very narrow choices of parameters. We propose a variation of quarkyonic matter
involving protons and leptons whose energy can be explicitly minimized to
achieve both chemical and beta equilibrium, which cannot be done in the
chargeless formulation. Quarkyonic stellar models are able to satisfy observed
mass and radius constraints with a wide range of model parameters, avoiding the
obligatory fine-tuning of conventional hybrid star models, including requiring
the transition density to be very close to the nuclear saturation density. Our
formulation fits experimental and theoretical properties of the nuclear
symmetry energy and pure neutron matter, and contains as few as three free
parameters. This makes it an ideal tool for the study of high-density matter
that is an efficient alternative to piecewise polytrope or spectral
decomposition methods.


  During time-critical situations such as natural disasters, rapid
classification of data posted on social networks by affected people is useful
for humanitarian organizations to gain situational awareness and to plan
response efforts. However, the scarcity of labeled data in the early hours of a
crisis hinders machine learning tasks thus delays crisis response. In this
work, we propose to use an inductive semi-supervised technique to utilize
unlabeled data, which is often abundant at the onset of a crisis event, along
with fewer labeled data. Specif- ically, we adopt a graph-based deep learning
framework to learn an inductive semi-supervised model. We use two real-world
crisis datasets from Twitter to evaluate the proposed approach. Our results
show significant improvements using unlabeled data as compared to only using
labeled data.


  We prove a conjecture due to Makanin: if a and b are elements of the Artin
braid group B_n such that a^k=b^k for some nonzero integer k, then a and b are
conjugate. The proof involves the Nielsen-Thurston classification of braids.


  Decentralized, tamper-proof blockchain is regarded as a solution to a
challenging authentication issue in the Internet of Vehicles (IoVs). However,
the consensus time and communication overhead of blockchain increase
significantly as the number of vehicles connected to the blockchain. To address
this issue, vehicular fog computing has been introduced to improve efficiency.
However, existing studies ignore several key factors such as the number of
vehicles in the fog computing system, which can impact the consensus
communication overhead. Meanwhile, there is no comprehensive study on the
stability of vehicular fog composition. The vehicle movement will lead to
dynamic changes in fog. If the composition of vehicular fog is unstable, the
blockchain formed by this fog computing system will be unstable, which can
affect the consensus efficiency. With the above considerations, we propose an
efficient and stable identity authentication (ESIA) empowered by hierarchical
blockchain and fog computing. By grouping vehicles efficiently, ESIA has low
communication complexity and achieves high stability. Moreover, to enhance the
consensus security of the hierarchical blockchain, the consensus process is
from the bottom layer to the up layer (bottom-up), which we call B2UHChain.
Through theoretical analysis and simulation verification, our scheme achieves
the design goals of high efficiency and stability while significantly improving
the IoV scalability to the power of 1.5 (^1.5) under similar security to a
single-layer blockchain. In addition, ESIA has less communication and
computation overhead, lower latency, and higher throughput than other baseline
authentication schemes.


  One of the unifying concepts in the iron-pnictide superconductors, both for
the mechanism of magnetic ordering and of unconventional order parameter
character, has been the electron and hole Fermi surfaces that are approximately
nested. Using the density functional methods that have predicted Fermi surfaces
correctly in SrFe$_2$P$_2$, we find that the recently reported superconducting
Sr$_2$VO$_3$FeAs, with $T_c$=37 K and no apparent competition between magnetism
and superconductivity, possesses different Fermi surface geometry and character
than previous classes of iron pnictides. The intervening layer (a V bilayer)
gives rise to bands that cross the Fermi level. Coupling to the FeAs layer is
small except for interaction along the zone boundary, however that coupling
degrades the Fermi surface nesting. Sr$_2$VO$_3$FeAs, with its alternating
layers of open shell atoms, deserves further close study that should help to
understand the origin of the properties of iron pnictide compounds.