  I introduce a stability notion, dynamic stability, for two-sided dynamic
matching markets where (i) matching opportunities arrive over time, (ii)
matching is one-to-one, and (iii) matching is irreversible. The definition
addresses two conceptual issues. First, since not all agents are available to
match at the same time, one must establish which agents are allowed to form
blocking pairs. Second, dynamic matching markets exhibit a form of externality
that is not present in static markets: an agent's payoff from remaining
unmatched cannot be defined independently of what other contemporaneous agents'
outcomes are. Dynamically stable matchings always exist. Dynamic stability is a
necessary condition to ensure timely participation in the economy by ensuring
that agents do not strategically delay the time at which they are available to
match.


  We report the synthesis and initial characterization of
Ba6Y2Rh2Ti2O17-{\delta}, a previously unreported material with a hexagonal
symmetry structure. Face-sharing RhO6 octahedra form triangular planes of Rh2O9
dimers that are widely separated in the perpendicular direction. The material
displays a small effective magnetic moment, due to the Rh ions present, and a
negative Curie-Weiss temperature. The charge transport and optical band gaps
are very similar, near 0.16 eV. A large upturn in the heat capacity at
temperatures below 1 K, suppressed by applied magnetic fields larger than
{{\mu}0H = 2 Tesla, is observed. A large T-linear term in the specific heat
({\gamma}=166 mJ/mol f.u-K2) is seen, although the material is insulating at
low temperatures. These results suggest the possibility of a spin liquid ground
state in this material.


  We propose a new method to calculate polarization induced interfacial charges
in semiconductor heterostructures using classical electrostatics applied to
real-space band diagrams from first principles calculations and apply it to
GaN/AlN heterostructures with ultrathin AlN layers (4-6 monolayers). We show
that the calculated electric fields and interfacial charges are independent of
the exchange-correlation functionals used (local-density approximation and
hybrid functionals). We also find the calculated interfacial charge of (6.8 +/-
0.4) x 10^13 cm-2 to be in excellent agreement with experiments and the value
of 6.58 x 10^13 cm-2 calculated from bulk polarization constants, validating
the use of bulk constants even for very thin films.


  In this paper, by using the method of Contour Integral Representations and
the Theorem of Residues and integral representations of series, we discuss the
analytic representa- tions of parametric Euler sums that involve harmonic
numbers through zeta values and rational function series, either linearly or
nonlinearly. Furthermore, we give explicit formulae for several parametric
quadratic and cubic sums in terms of zeta values and rational series. Moreover,
some interesting new consequences and illustrative examples are considered.


  In this paper, we propose normalizing flows (NF) as a novel probability
density function (PDF) turbulence model (NF-PDF model) for the
Reynolds-averaged Navier-Stokes (RANS) equations. We propose to use normalizing
flows in two different ways: firstly, as a direct model for the Reynolds stress
tensor, and secondly as a second-moment closure model, i.e. for modeling the
pressure-strain and dissipation tensor in the Reynolds stress transport
equation. In classical PDF closure models, a stochastic differential equation
has to be modeled and solved to obtain samples of turbulent quantities. The
NF-PDF closure model allows for direct sampling from the underlying probability
density functions of fluctuating turbulent quantities, such that
ensemble-averaged quantities can then be computed. To illustrate this approach
we demonstrate an application for the canonical case of homogeneous shear
turbulence. Training data are extracted from high-fidelity direct numerical
simulations (DNS).


  Inductive inference is a recursion-theoretic theory of learning, first
developed by E. M. Gold (1967). This paper surveys developments in
probabilistic inductive inference. We mainly focus on finite inference of
recursive functions, since this simple paradigm has produced the most
interesting (and most complex) results.


  We present a thermodynamic analysis of a quantum engine that uses a single
quantum particle as its working fluid, inspired by Szilard's classical
single-particle engine. Our design is modeled after the classically-chaotic
Szilard Map and involves a thermodynamic cycle of measurement, thermal-energy
extraction, and memory reset. Our focus is on investigating the thermodynamic
costs associated with observing and controlling the particle and comparing
these costs in the quantum and classical limits. Through our study, we aim to
shed light on the thermodynamic trade-offs that arise from Lindauer's Principle
for information-processing-induced thermodynamic dissipation in both the
quantum and classical regimes. Using machine learning methods, we demonstrate
that energy analysis can be performed and the quantum engine can be simulated
according to the Szilard engine based Second Law of Thermodynamics in its
working condition. However, we note that the quantum engine operates using
significantly different mechanisms than its classical counterpart, where the
cost of inserting partitions plays a critical role in the quantum
implementation.


  In an interesting recent paper on the growth of inhomogeneity through the
effect of gravity [1], Bertschinger and Hamilton derive equations for the
electric and magnetic parts of the Weyl tensor for cold dust for both General
Relativity and Newtonian theory. Their conclusion is that both in General
Relativity and in Newtonian theory, in general the magnetic part of the Weyl
tensor does not vanish, implying that the Lagrangian evolution of the fluid is
not local. We show here that the `Newtonian' theory discussed by them is in
fact not Newtonian theory {\it per se}, but rather a plausible relativistic
generalisation of Newtonian theory. Newtonian cosmology itself is highly
non-local irrespective of the behaviour of the magnetic part of the Weyl
tensor; in this respect the Bertschinger-Hamilton generalisation is a better
theory.


  LiDAR datasets for autonomous driving exhibit biases in properties such as
point cloud density, range, and object dimensions. As a result, object
detection networks trained and evaluated in different environments often
experience performance degradation. Domain adaptation approaches assume access
to unannotated samples from the test distribution to address this problem.
However, in the real world, the exact conditions of deployment and access to
samples representative of the test dataset may be unavailable while training.
We argue that the more realistic and challenging formulation is to require
robustness in performance to unseen target domains. We propose to address this
problem in a two-pronged manner. First, we leverage paired LiDAR-image data
present in most autonomous driving datasets to perform multimodal object
detection. We suggest that working with multimodal features by leveraging both
images and LiDAR point clouds for scene understanding tasks results in object
detectors more robust to unseen domain shifts. Second, we train a 3D object
detector to learn multimodal object features across different distributions and
promote feature invariance across these source domains to improve
generalizability to unseen target domains. To this end, we propose
CLIX$^\text{3D}$, a multimodal fusion and supervised contrastive learning
framework for 3D object detection that performs alignment of object features
from same-class samples of different domains while pushing the features from
different classes apart. We show that CLIX$^\text{3D}$ yields state-of-the-art
domain generalization performance under multiple dataset shifts.


  In recent years, social media platforms have hosted an explosion of hate
speech and objectionable content. The urgent need for effective automatic hate
speech detection models have drawn remarkable investment from companies and
researchers. Social media posts are generally short and their semantics could
drastically be altered by even a single token. Thus, it is crucial for this
task to learn context-aware input representations, and consider relevancy
scores between input embeddings and class representations as an additional
signal. To accommodate these needs, this paper introduces CRAB (Class
Representation Attentive BERT), a neural model for detecting hate speech in
social media. The model benefits from two semantic representations: (i)
trainable token-wise and sentence-wise class representations, and (ii)
contextualized input embeddings from state-of-the-art BERT encoder. To
investigate effectiveness of CRAB, we train our model on Twitter data and
compare it against strong baselines. Our results show that CRAB achieves 1.89%
relative improved Macro-averaged F1 over state-of-the-art baseline. The results
of this research open an opportunity for the future research on automated
abusive behavior detection in social media


  Lannes' T-functor is used to give a construction of the Singer functor R_1 on
the category U of unstable modules over the Steenrod algebra A. This leads to a
direct proof that the composite functor Fix R_1 is naturally equivalent to the
identity. Further properties of the functors R_1 are deduced, especially when
applied to reduced and nilclosed unstable modules.


  This work is concerned with Al/Al-oxide(AlO$_{x}$)/Al-layer systems which are
important for Josephson-junction-based superconducting devices such as quantum
bits. The device performance is limited by noise, which has been to a large
degree assigned to the presence and properties of two-level tunneling systems
in the amorphous AlO$_{x}$ tunnel barrier. The study is focused on the
correlation of the fabrication conditions, nanostructural and nanochemical
properties and the occurrence of two-level tunneling systems with particular
emphasis on the AlO$_{x}$-layer. Electron-beam evaporation with two different
processes and sputter deposition were used for structure fabrication, and the
effect of illumination by ultraviolet light during Al-oxide formation is
elucidated. Characterization was performed by analytical transmission electron
microscopy and low-temperature dielectric measurements. We show that the
fabrication conditions have a strong impact on the nanostructural and
nanochemical properties of the layer systems and the properties of two-level
tunneling systems. Based on the understanding of the observed structural
characteristics, routes are derived towards the fabrication of
Al/AlO$_{x}$/Al-layers systems with improved properties.


  This short note is devoted to the Hamiltonian formulation of the conformal
decomposition of the gravitational field that was performed in [gr-qc/0501092].
We also analyze the gauge fixed form of the theory when we fix the conformal
symmetry by imposing the condition det g=1.


  We investigate the structural, vibrational, and mechanical properties of
jammed packings of deformable particles with shape degrees of freedom in three
dimensions (3D). Each 3D deformable particle is modeled as a
surface-triangulated polyhedron, with spherical vertices whose positions are
determined by a shape-energy function with terms that constrain the particle
surface area, volume, and curvature, and prevent interparticle overlap. We show
that jammed packings of deformable particles without bending energy possess
low-frequency, quartic vibrational modes, whose number decreases with
increasing asphericity and matches the number of missing contacts relative to
the isostatic value. In contrast, jammed packings of deformable particles with
non-zero bending energy are isostatic in 3D, with no quartic modes. We find
that the contributions to the eigenmodes of the dynamical matrix from the shape
degrees of freedom are significant over the full range of frequency and shape
parameters for particles with zero bending energy. We further show that the
ensemble-averaged shear modulus $\langle G \rangle$ scales with pressure $P$ as
$\langle G \rangle \sim P^{\beta}$, with $\beta \approx 0.75$ for jammed
packings of deformable particles with zero bending energy. In contrast, $\beta
\approx 0.5$ for packings of deformable particles with non-zero bending energy,
which matches the value for jammed packings of soft, spherical particles with
fixed shape. These studies underscore the importance of incorporating particle
deformability and shape change when modeling the properties of jammed soft
materials.


  A strange title, might you say: Answer is in the question! However, contrary
to popular belief and numerous citations in the literature, the image of the
snowflake curve is not present or even mentioned in von Koch's original
articles. So, where and when did the first snowflake fall? Unravel the mystery
of the snowflake curve with us on a journey through time.


  The composite load model (CLM) proposed by the Western Electricity
Coordinating Council (WECC) is gaining increasing traction in industry,
particularly in North America. At the same time, it has been recognized that
further improvements in structure, initialization and aggregation methods are
needed to enhance model accuracy. However, the lack of an open-source
implementation of the WECC CLM has become a roadblock for many researchers for
further improvement. To bridge this gap, this paper presents the first open
reference implementation of the WECC CLM. Individual load components and the
CLM are first developed and tested in Matlab, then translated to the high
performance computing (HPC) based, parallel simulation framework - GridPACK.
The main contributions of the paper include: 1) presenting important yet
undocumented details of modeling and initializing the CLM, particularly for a
parallel simulation frame-work like GridPACK; 2) implementation details of the
load components such as the single-phase air conditioner motor; 3) implementing
the CLM in a modular and extensible manner. The implementation has been tested
at both the component as well as system levels and benchmarked against
commercial simulation programs, with satisfactory accuracy.


  Point singularities of solutions to the classical Lane-Emden-Serrin equation
have a polyhomogeneous asymptotic expansion whose logarithmic corrections are
determined by a first order ODE. Surprisingly, we are able to discover such an
ODE for the fractional Lane-Emden-Serrin equation, and therefore give a short
classification for the precise local behavior of its solutions up to the second
order involving a double logarithm. This seems to be the first time that a
nonlocal equation is associated to a genuinely local ODE in one dimension. New
non-existence, existence and multiplicity results for the corresponding
Dirichlet problem are also discussed.
  Moreover, we construct complete $s$-fractional Yamabe metrics in
$\mathbb{R}^n$ which are singular along a smooth submanifold of dimension
$(n-2s)/2$, via direct integral asymptotic analysis with global geometric
weights. This covers the missing borderline case as suggested by the deep work
of Schoen and Yau. While such dimension is maximal in the class of
distributional solutions, we conjecture the existence of complete metrics,
understood in a suitably generalized sense, with prescribed singularities of
strictly higher dimensions.


  Molecular simulations employing empiric force fields have provided valuable
knowledge about the ice growth process in the last decade. The development of
novel computational techniques allows us to study this process, which requires
long simulations of relatively large systems, with ab initio accuracy. In this
work, we use a neural-network potential for water trained on the Revised
Perdew-Burke-Ernzerhof functional to describe the kinetics of the ice-water
interface. We study both ice melting and growth processes. Our results for the
ice growth rate are in reasonable agreement with previous experiments and
simulations. We find that the kinetics of ice melting presents a different
behavior (monotonic) than that of ice growth (non-monotonic). In particular, a
maximum in the ice growth rate of 6.5 {\AA}/ns is found at 14 K of
supercooling. The effect of the surface structure is explored by investigating
the basal and primary and secondary prismatic facets. We use the Wilson-Frenkel
relation to explain these results in terms of the mobility of molecules and the
thermodynamic driving force. Moreover, we study the effect of pressure by
complementing the standard isobar with simulations at negative pressure (-1000
bar) and at high pressure (2000 bar). We find that prismatic facets grow faster
than the basal one, and that pressure does not play an important role when the
speed of the interface is considered as a function of the difference between
the melting temperature and the actual one, i.e. to the degree of either
supercooling or overheating.


  The flourishing rare earth superhydrides are a class of recently discovered
materials that possess near-room-temperature superconductivity at high
pressures, opening a new era of superconductivity research at high pressures.
Among these superhydrides, yttrium superhydrides attracted great interest owing
to their abundance of stoichiometries and excellent superconductivities. Here,
we carried out a comprehensive study of yttrium superhydrides in a wide
pressure range of 145-300 GPa. We successfully synthesized a series of
superhydrides with the compositions of YH4, YH6, YH7, and YH9, and reported
their superconducting transition temperatures of 82 K at 167 GPa, 218 K at 165
GPa, 29 K at 162 GPa, and 230 K at 300 GPa, respectively, which were evidenced
by a sharp drop of resistivity. The structure and superconductivity of YH4,
which was taken as a representative example, were also examined by X-ray
diffraction measurements and the suppression of the superconductivity under
external magnetic fields, respectively. Clathrate YH10 as a candidate of
room-temperature superconductor was not synthesized within the studied pressure
and temperature ranges of up to 300 GPa and 2000 K, respectively. The current
work created a detailed platform for further searching room-temperature
superconductors in polynary yttrium-based superhydrides.


  We provide a general, homotopy-theoretic definition of string group models
within an $\infty$-category of smooth spaces, and we present new smooth models
for the string group. Here, a smooth space is a presheaf of $\infty$-groupoids
on the category of cartesian spaces. The key to our definition and construction
of smooth string group models is a version of the singular complex functor,
which assigns to a smooth space an underlying ordinary space. We provide new
characterisations of principal $\infty$-bundles and group extensions in
$\infty$-topoi, building on work of Nikolaus, Schreiber, and Stevenson. These
insights allow us to transfer the definition of string group extensions from
the $\infty$-category of spaces to the $\infty$-category of smooth spaces.
Finally, we consider smooth higher-categorical group extensions that arise as
obstructions to the existence of equivariant structures on gerbes. We show that
these extensions give rise to new smooth models for the string group, as
recently conjectured in joint work with M\"uller and Szabo.


  High-energy irradiation of the circumstellar material might impact the
structure and the composition of a protoplanetary disk and hence the process of
planet formation. In this paper, we present a study on the possible influence
of the stellar irradiation, indicated by X-ray emission, on the crystalline
structure of the circumstellar dust. The dust crystallinity is measured for 42
class II T Tauri stars in the Taurus star-forming region using a decomposition
fit of the 10 micron silicate feature, measured with the Spitzer IRS
instrument. Since the sample includes objects with disks of various
evolutionary stages, we further confine the target selection, using the age of
the objects as a selection parameter. We correlate the X-ray luminosity and the
X-ray hardness of the central object with the crystalline mass fraction of the
circumstellar dust and find a significant anti-correlation for 20 objects
within an age range of approx. 1 to 4.5 Myr. We postulate that X-rays represent
the stellar activity and consequently the energetic ions of the stellar winds
which interact with the circumstellar disk. We show that the fluxes around 1 AU
and ion energies of the present solar wind are sufficient to amorphize the
upper layer of dust grains very efficiently, leading to an observable reduction
of the crystalline mass fraction of the circumstellar, sub-micron sized dust.
This effect could also erase other relations between crystallinity and
disk/star parameters such as age or spectral type.


  Community search is a personalized community discovery problem aimed at
finding densely-connected subgraphs containing the query vertex. In particular,
the search for communities with high-importance vertices has recently received
a great deal of attention. However, existing works mainly focus on conventional
homogeneous networks where vertices are of the same type, but are not
applicable to heterogeneous information networks (HINs) composed of multi-typed
vertices and different semantic relations, such as bibliographic networks. In
this paper, we study the problem of high-importance community search in HINs. A
novel community model is introduced, named heterogeneous significant community
(HSC), to unravel the closely connected vertices of the same type with high
attribute values through multiple semantic relationships. An HSC not only
maximizes the exploration of indirect relationships across entities of the
anchor-type but incorporates their significance. To search the HSCs, we first
develop online algorithms by exploiting both segmented-based meta-path
expansion and significance increment. Specially, a solution space reuse
strategy based on structural nesting is designed to boost the efficiency. In
addition, we further devise a two-level index to support searching HSCs in
optimal time, based on which a space-efficient compact index is proposed.
Extensive experiments on real-world large-scale HINs demonstrate that our
solutions are effective and efficient for searching HSCs, and the index-based
algorithms are 2-4 orders of magnitude faster than online algorithms.


  Receiver-operating-characteristic (ROC) analysis was used to assess the
suitability of various heart rate variability (HRV) measures for correctly
classifying electrocardiogram records of varying lengths as normal or revealing
the presence of heart failure. Scale-dependent HRV measures were found to be
substantially superior to scale-independent measures (scaling exponents) for
discriminating the two classes of data over a broad range of record lengths.
The wavelet-coefficient standard deviation at a scale near 32 heartbeat
intervals, and its spectral counterpart near 1/32 cycles per interval, provide
reliable results using record lengths just minutes long. A jittered
integrate-and-fire model built around a fractal Gaussian-noise kernel provides
a realistic, though not perfect, simulation of heartbeat sequences.


  The aim of this paper is to give a new link between integrable systems and
minimal surface theory. The dressing operation uses the associated family of
flat connections of a harmonic map to construct new harmonic maps. Since a
minimal surface in 3-space is a Willmore surface, its conformal Gauss map is
harmonic and a dressing on the conformal Gauss map can be defined. We study the
induced transformation on minimal surfaces in the simplest case, the simple
factor dressing, and show that the well-known Lopez-Ros deformation of minimal
surfaces is a special case of this transformation. We express the simple factor
dressing and the Lopez-Ros deformation explicitly in terms of the minimal
surface and its conjugate surface. In particular, we can control periods and
end behaviour of the simple factor dressing. This allows to construct new
examples of doubly-periodic minimal surfaces arising as simple factor dressings
of Scherk's first surface.


  Many security techniques working at the physical layer need a correct channel
state information (CSI) at the transmitter, especially when devices are
equipped with multiple antennas. Therefore such techniques are vulnerable to
pilot contamination attacks (PCAs) by which an attacker aims at inducing false
CSI. In this paper we provide a solution to some PCA methods, by letting two
legitimate parties to compare their channel estimates. The comparison is made
in order to minimize the information leakage on the channel to a possible
attacker. By reasonable assumptions on both the channel knowledge by the
attacker and the correlation properties of the attacker and legitimate channels
we show the validity of our solution. An accurate analysis of possible attacks
and countermeasures is provided, together with a numerical evaluation of the
attainable secrecy outage probability when our solution is used in conjunction
with beamforming for secret communications.


  A quasar (as well as an active galactic nucleus) which emits a one-side jet
(or which is an anisotropic emitter of particles and quanta) can be accelerated
and leave its host galaxy.


  We use deep NIRSpec spectroscopic data from the JADES survey to derive the
star formation histories (SFHs) of a sample of 200 galaxies at 0.6$<$z$<$11 and
spanning stellar masses from $\rm 10^6$ to $\rm 10^{9.5}~M_\odot$. We find that
galaxies at high-redshift, galaxies above the Main Sequence (MS) and low-mass
galaxies tend to host younger stellar populations than their low-redshift,
massive, and below the MS counterparts. Interestingly, the correlation between
age, M$_*$ and SFR existed even earlier than Cosmic Noon, out to the earliest
cosmic epochs. However, these trends have a large scatter. Indeed, there are
examples of young stellar populations also below the MS, indicating recent
(bursty) star formation in evolved systems. We explore further the burstiness
of the SFHs by using the ratio between SFR averaged over the last 10 Myr and
averaged between 10 Myr and 100 Myr before the epoch of observation
($\mathrm{SFR_{cont, 10}/SFR_{cont, 90}}$). We find that high-redshift and
low-mass galaxies have particularly bursty SFHs, while more massive and
lower-redshift systems evolve more steadily. We also present the discovery of
another (mini-)quenched galaxy at z = 4.4 (in addition to the one at z=7.3
reported by Looser et al. 2023), which might be only temporarily quiescent as a
consequence of the extremely bursty evolution. Finally, we also find a steady
decline of dust reddening of the stellar population approaching the earliest
cosmic epochs, although some dust reddening is still observed in some of the
highest redshift and most star forming systems.


  A novel scheme to solve the quantum eigenvalue problem through the
imaginary-time Green function Monte Carlo method is presented. This method is
applicable to the excited states as well as to the ground state of a generic
system. We demonstrate the validity of the method with the numerical examples
on three simple systems including a discretized sine-Gordon model.


  We present a simple library which equips MPI implementations with truly
asynchronous non-blocking point-to-point operations, and which is independent
of the underlying communication infrastructure. It utilizes the MPI profiling
interface (PMPI) and the MPI_THREAD_MULTIPLE thread compatibility level, and
works with current versions of Intel MPI, Open MPI, MPICH2, MVAPICH2, Cray MPI,
and IBM MPI. We show performance comparisons on a commodity InfiniBand cluster
and two tier-1 systems in Germany, using low-level and application benchmarks.
Issues of thread/process placement and the peculiarities of different MPI
implementations are discussed in detail. We also identify the MPI libraries
that already support asynchronous operations. Finally we show how our ideas can
be extended to MPI-IO.


  With the rapid development of Internet of Things (IoT), low earth orbit (LEO)
satellite IoT is expected to provide low power, massive connectivity and wide
coverage IoT applications. In this context, this paper provides a massive
grant-free random access (GF-RA) scheme for LEO satellite IoT. This scheme does
not need to change the transceiver, but transforms the received signal to a
tensor decomposition form. By exploiting the characteristics of the tensor
structure, a Bayesian learning algorithm for joint active device detection and
channel estimation during massive GF-RA is designed. Theoretical analysis shows
that the proposed algorithm has fast convergence and low complexity. Finally,
extensive simulation results confirm its better performance in terms of error
probability for active device detection and normalized mean square error for
channel estimation over baseline algorithms in LEO satellite IoT. Especially,
it is found that the proposed algorithm requires short preamble sequences and
support massive connectivity with a low power, which is appealing to LEO
satellite IoT.


  We present an updated UBVRI photometric catalog containing 970 objects in the
field of M31, selected from the Revised Bologna Catalog (RBC v.4.0), including
965, 967, 965, 953, and 827 sources in the individual UBVRI bands,
respectively, of which 205, 123, 14, 126, and 109 objects do not have
previously published photometry. Photometry is performed using archival images
from the Local Group Galaxies Survey, which covers 2.2 deg^2 along the major
axis of M31. We focus on 445 confirmed `globular-like' clusters and candidates,
comprising typical globular and young massive clusters. The ages and masses of
these objects are derived by comparison of their observed spectral-energy
distributions with simple stellar population synthesis. Approximately half of
the clusters are younger than 2 Gyr, suggesting that there has been significant
recent active star formation in M31, which is consistent with previous results.
We note that clusters in the halo (r_ projected>30kpc) are composed of two
different components, older clusters with ages >10 Gyr and younger clusters
with ages around 1 Gyr. The spatial distributions show that the young clusters
(<2 Gyr) are spatially coincident with the galaxy's disk, including the `10 kpc
ring,' the `outer ring,' and the halo of M31, while the old clusters (> 2 Gyr)
are spatially correlated with the bulge and halo. We also estimate the masses
of the 445 confirmed clusters and candidates in M31 and find that our estimates
agree well with previously published values. We find that none of the young
disk clusters can survive the inevitable encounters with giant molecular clouds
in the galaxy's disk and that they will eventually disrupt on timescales of a
few Gyr. Specifically, young disk clusters with a mass of 10^4 M_\odot are
expected to dissolve within 3.0 Gyr and will, thus, not evolve to become
globular clusters.


  Type II radio bursts are thought to be produced by shock waves in the solar
atmosphere. However, what magnetic conditions are needed for the generation of
type II radio bursts is still a puzzling issue. Here, we quantify the magnetic
structure of a coronal shock associated with a type II radio burst. Based on
the multi-perspective extreme-ultraviolet observations, we reconstruct the
three-dimensional (3D) shock surface. By using a magnetic field extrapolation
model, we then derive the orientation of the magnetic field relative to the
normal of the shock front ($\theta_{\rm Bn}$) and Alfv\'{e}n Mach number
($M_A$) on the shock front. Combining the radio observations from Nancay Radio
Heliograph, we obtain the source region of the type II radio burst on the shock
front. It is found that the radio burst is generated by a shock with $M_A
\gtrsim 1.5$ and a bimodal distribution of $\theta_{Bn}$. We also use the
Rankine-Hugoniot relations to quantify the properties of the shock downstream.
Our results provide a quantitative 3D magnetic structure condition of a coronal
shock that produces a type II radio burst.


  This article introduces methods for constructing prediction bounds or
intervals for the number of future failures from heterogeneous reliability
field data. We focus on within-sample prediction where early data from a
failure-time process is used to predict future failures from the same process.
Early data from high-reliability products, however, often have limited
information due to some combination of small sample sizes, censoring, and
truncation. In such cases, we use a Bayesian hierarchical model to model
jointly multiple lifetime distributions arising from different subpopulations
of similar products. By borrowing information across subpopulations, our method
enables stable estimation and the computation of corresponding prediction
intervals, even in cases where there are few observed failures. Three
applications are provided to illustrate this methodology, and a simulation
study is used to validate the coverage performance of the prediction intervals.


  The relativistic kinetic equations (RKE) for lepton plasma in the presence of
a strong external magnetic field are derived in Vlasov approximation. The new
RKE for the electron spin distribution function includes the weak interaction
with neutrinos originated by the axial vector current ($\sim c_A$) and provided
by the parity nonconservation. In a polarized electron gas Bloch equation
describing the evolution of the magnetization density perturbation is derived
from the electron spin RKE being modified in the presence of neutrino fluxes.
Such modified hydrodynamical equation allows to obtain the new dispersion
equation in a magnetized plasma from which the neutrino driven instability of
spin waves can be found. It is shown that this instability is more efficient
e.g. in a magnetized supernova than the analogous one for Langmuir waves
enhanced in an isotropic plasma.


  Quantum key distribution (QKD) offers a reliable solution to communication
problems that require long-term data security. For its widespread use, however,
the rate and reach of QKD systems must be improved. Twin-field (TF) QKD is a
step forward toward this direction, with early demonstrations suggesting it can
beat the current rate-versus-distance records. A recently introduced variant of
TF-QKD is particularly suited for experimental implementation, and has been
shown to offer a higher key rate than other variants in the asymptotic regime
where users exchange an infinite number of signals. Here, we extend the
security of this protocol to the finite-key regime, showing that it can
overcome the fundamental bounds on point-to-point QKD with around $10^{10}$
transmitted signals. Within distance regimes of interest, our analysis offers
higher key rates than those of alternative variants. Moreover, some of the
techniques we develop are applicable to the finite-key analysis of other QKD
protocols.


  1) We identify new parameter branches for the ultra-local boundary Poisson
bracket in d spatial dimension with a (d-1)-dimensional spatial boundary. There
exist 2^{r(r-1)/2} r-dimensional parameter branches for each d-box, r-row Young
tableau. The already known branch (hep-th/9912017) corresponds to a vertical
1-column, d-box Young tableau. 2) We consider a local distribution product
among the so-called boundary distributions. The product is required to respect
the associativity and the Leibnitz rule. We show that the consistency
requirements on this product correspond to the Jacobi identity conditions for
the boundary Poisson bracket. In other words, the restrictions on forming a
boundary Poisson bracket can be related to the more fundamental distribution
product construction. 3) The definition of the higher functional derivatives is
made independent of the choice of integral kernel representative for a
functional.


  People can think in auditory, visual and tactile forms of language, so can
machines principally. But is it possible for them to think in radio language?
According to a first principle presented for general intelligence, i.e. the
principle of language's relativity, the answer may give an exceptional solution
for robot astronauts to talk with each other in space exploration.


  A circular Nim game is a two player impartial combinatorial game consisting
of n stacks of tokens placed in a circle. A move consists of choosing k
consecutive stacks, and taking at least one token from one or more of the k
stacks. The last player able to make a move wins. We prove results on the
structure of the losing positions for small n and k and pose some open
questions for further investigations.


  We study the expressivity and learning process for polynomial neural networks
(PNNs) with monomial activation functions. The weights of the network
parametrize the neuromanifold. In this paper, we study certain neuromanifolds
using tools from algebraic geometry: we give explicit descriptions as
semialgebraic sets and characterize their Zariski closures, called
neurovarieties. We study their dimension and associate an algebraic degree, the
learning degree, to the neurovariety. The dimension serves as a geometric
measure for the expressivity of the network, the learning degree is a measure
for the complexity of training the network and provides upper bounds on the
number of learnable functions. These theoretical results are accompanied with
experiments.


  Searching for exotic multiquark states and elucidating their nature remains a
central topic in understanding quantum chromodynamics--the underlying theory of
the strong interaction. Two of the most studied such states are the
charm-strange states $D_{s0}^*(2317)$ and $D_{s1}(2460)$. In this letter, we
show for the first time that their prompt production yields in inclusive
$e^+e^-\to c\bar{c}$ collisions near $\sqrt{s}=10.6$ GeV measured by the BABAR
Collaboration, $Y(D_{s0}^*(2317))$ and $Y(D_{s1}(2460))$, in particular the
ratio $R=Y(D_{s0}^*(2317))/Y(D_{s1}(2460))$, can be well explained in the
molecular picture, which provide a highly nontrivial verification of their
nature being $DK/D^*K$ molecules. On the contrary, treating them as pure
$c\bar{s}$ $P-$wave states, the statistical model predicts a ratio $R$ smaller
than unity, in contrast with the experimental central value, though in
agreement with it considering its relatively large uncertainty. In addition, we
predict the production yield of the $D\bar{D}K$ three-body bound state,
$K_{c\bar{c}}(4180)$, in $e^+e^-\to c\bar{c}$ collisions and find that it is
within the reach of the ongoing Belle II experiment. The present study
demonstrates the feasibility of a novel method to unravel the nature of exotic
hadrons and the potential of electron-positron collisions in this regard.


  This work reports on the bulk properties of the quaternary Heusler alloy
Co$_2$Mn$_{1-x}$Fe$_x$Si with the Fe concentration $x=$. All samples, which
were prepared by arc melting, exhibit $L2_1$ long range order over the complete
range of Fe concentration. Structural and magnetic properties of
Co$_2$Mn$_{1-x}$Fe$_x$Si Heusler alloys were investigated by means of X-ray
diffraction, high and low temperature magnetometry, M{\"o\ss}bauer
spectroscopy, and differential scanning calorimetry. The electronic structure
was explored by means of high energy photo emission spectroscopy at about 8 keV
photon energy. This ensures true bulk sensitivity of the measurements. The
magnetization of the Fe doped Heusler alloys is in agreement with the values of
the magnetic moments expected for a Slater-Pauling like behavior of
half-metallic ferromagnets. The experimental findings are discussed on the hand
of self-consistent calculations of the electronic and magnetic structure. To
achieve good agreement with experiment, the calculations indicate that on-site
electron-electron correlation must be taken into account, even at low Fe
concentration. The present investigation focuses on searching for the
quaternary compound where the half-metallic behavior is stable against outside
influences. Overall, the results suggest that the best candidate may be found
at an iron concentration of about 50%.


  We define a family of symplectic invariants which obstruct exact symplectic
embeddings between Liouville manifolds, using the general formalism of
linearized contact homology and its L-infinity structure. As our primary
application, we investigate embeddings between normal crossing divisor
complements in complex projective space, giving a complete characterization in
many cases. Our main embedding results are deduced explicitly from
pseudoholomorphic curves, without appealing to Hamiltonian or virtual
perturbations.


  We present a quantum field theoretical method for the characterization of
disordered complex media with short laser pulses in an optical coherence
tomography setup (OCT). We solve this scheme of coherent transport in space and
time with weighted essentially nonoscillatory methods (WENO). WENO is
preferentially used for the determination of highly nonlinear and discontinuous
processes including interference effects and phase transitions like Anderson
localization of light. The theory determines spatiotemporal characteristics of
the scattering mean free path and the transmission cross section that are
directly measurable in time-of-flight (ToF) and pump-probe experiments. The
results are a measure of the coherence of multiple scattering photons in
passive as well as in optically soft random media. Our theoretical results of
ToF are instructive in spectral regions where material characteristics such as
the scattering mean free path and the diffusion coefficient are
methodologically almost insensitive to gain or absorption and to higher-order
nonlinear effects. Our method is applicable to OCT and other advanced
spectroscopy setups including samples of strongly scattering mono- and
polydisperse complex nano- and microresonators.


  We consider recent reports on small-world topologies of interaction networks
derived from the dynamics of spatially extended systems that are investigated
in diverse scientific fields such as neurosciences, geophysics, or meteorology.
With numerical simulations that mimic typical experimental situations we have
identified an important constraint when characterizing such networks:
indications of a small-world topology can be expected solely due to the spatial
sampling of the system along with commonly used time series analysis based
approaches to network characterization.


  Precision measurements at the LHC can provide probes of new physics, and they
are complementary to direct searches. The high energy distribution of di-boson
processes ($WW,WZ,Vh$) is a promising place, with the possibility of
significant improvement in sensitivity as the data accumulates. We focus on the
semi-leptonic final states, and make projections of the reach for future runs
of the LHC with integrated luminosities of 300 fb$^{-1}$ and 3 ab$^{-1}$. We
emphasize the importance of tagging the polarization of the vector bosons, in
particular for the $WW$ and $WZ$ channels. We employ a combination of
kinematical distributions of both the $W$ and $Z$, and their decay products to
select the longitudinally polarized $W$ and $Z$. We have also included our
projections for the reach using the associated production of vector boson and
the Higgs. We demonstrate that di-boson measurement in the semi-leptonic
channel can surpass the sensitivity of the precision measurement at LEP, and
they can be significantly more sensitive than the HL-LHC $h \to Z \gamma$
measurements. Compared with fully leptonic decaying $WZ$ channel, the reach
from semi-leptonic channel can be better with effective suppression of the
reducible background and systematic error. We have also considered the reaches
on the new physics mass scale in different new physics scenarios, including the
Strongly Interacting-Light Higgs (SILH), the Strongly Coupled Multi-pole
Interaction (Remedios), and the class of models with partially composite
fermions. We find that in the SILH and non-compact Remedios scenario with large
coupling $g_* > 7$, measurements in the di-boson channel is more sensitive than
the Drell-Yan di-lepton channel at the HL-LHC.


  In this paper, we introduce a novel mathematical framework for assessing the
performance of joint communication and sensing (JCAS) in wireless networks,
employing stochastic geometry as an analytical tool. We focus on deriving the
meta distribution of the signal-to-interference ratio (SIR) for JCAS networks.
This approach enables a fine-grained quantification of individual user or radar
performance intrinsic to these networks. Our work involves the modeling of JCAS
networks and the derivation of mathematical expressions for the JCAS SIR meta
distribution. Through simulations, we validate both our theoretical analysis
and illustrate how the JCAS SIR meta distribution varies with the network
deployment density.


  We analyze the Lepton Flavor Violating (LFV) Higgs decay h -> tau mu in three
supersymmetric models: Minimal Supersymmetric Standard Model (MSSM),
Supersymmetric Seesaw Model (SSM), and Supersymmetric B-L model with Inverse
Seesaw (BLSSM-IS). We show that in generic MSSM, with non-universal slepton
masses and/or trilinear couplings, it is not possible to enhance BR(h -> tau
mu) without violating the experimental bound on the BR(tau -> mu gamma). In
SSM, where flavor mixing is radiatively generated, the LFV process mu -> e
gamma strictly constrains the parameter space and the maximum value of BR(h ->
tau mu) is of order 10^-10, which is extremely smaller than the recent results
reported by the CMS and ATLAS experiments. In BLSSM-IS, with universal soft
SUSY breaking terms at the grand unified scale, we emphasize that the measured
values of BR(h -> tau mu) can be accommodated in a wide region of parameter
space without violating LFV constraints. Thus, confirming the LFV Higgs decay
results will be a clear signal of BLSSM-IS type of models. Finally, the signal
of h -> tau mu in the BLSSM-IS at the LHC, which has a tiny background, is
analyzed.


  Background: There is increasing interest in approaches for analyzing the
effect of exposure mixtures on health. A key issue is how to simultaneously
analyze often highly collinear components of the mixture, which can create
problems such as confounding by co-exposure and co-exposure amplification bias
(CAB). Evaluation of novel mixtures methods, typically using synthetic data, is
critical to their ultimate utility. Objectives: This paper aims to answer two
questions. How do causal models inform the interpretation of statistical models
and the creation of synthetic data used to test them? Are novel mixtures
methods susceptible to CAB? Methods: We use directed acyclic graphs (DAGs) and
linear models to derive closed form solutions for model parameters to examine
how underlying causal assumptions affect the interpretation of model results.
Results: The same beta coefficients estimated by a statistical model can have
different interpretations depending on the assumed causal structure. Similarly,
the method used to simulate data can have implications for the underlying DAG
(and vice versa), and therefore the identification of the parameter being
estimated with an analytic approach. We demonstrate that methods that can
reproduce results of linear regression, such as Bayesian kernel machine
regression and the new quantile g-computation approach, will be subject to CAB.
However, under some conditions, estimates of an overall effect of the mixture
is not subject to CAB and even has reduced uncontrolled bias. Discussion: Just
as DAGs encode a priori subject matter knowledge allowing identification of
variable control needed to block analytic bias, we recommend explicitly
identifying DAGs underlying synthetic data created to test statistical mixtures
approaches. Estimates of the total effect of a mixture is an important but
relatively underexplored topic that warrants further investigation.


  The results of micro-structural and detailed magnetization studies are
reported here for our recently published TbSr2Cu2.7Mo0.3O7+d superconductor
with a transition temperature (Tc) at as high as 80 K [1]. From XRD and EDX the
sample was confirmed to be of single-phase and possess the nominal cation
stoichiometry. The SEM images showed well-developed grains for this ceramic
high-Tc superconductor. Magnetization measurements at various temperatures and
fields revealed bulk superconductivity below 80 K. Magnetization versus applied
field (M vs. H) loops at various temperatures below the Tc exhibited clear full
penetration field HP. In normal state (> 100 K) the susceptibility follows the
Curie-Weiss behavior with an effective paramagnetic moment of 9.83 mB.


  In their 1968 paper Fujita and Watanabe considered the issue of uniqueness of
the trivial solution of semilinear parabolic equations with respect to the
class of bounded, non-negative solutions. In particular they showed that if the
underlying ODE has non-unique solutions (as characterised via an Osgood-type
condition) {\em and} the nonlinearity $f$ satisfies a concavity condition, then
the parabolic PDE also inherits the non-uniqueness property. This concavity
assumption has remained in place either implicitly or explicitly in all
subsequent work in the literature relating to this and other, similar,
non-uniqueness phenomena in parabolic equations. In this paper we provide an
elementary proof of non-uniqueness for the PDE without any such concavity
assumption on $f$. An important consequence of our result is that uniqueness of
the trivial solution of the PDE is equivalent to uniqueness of the trivial
solution of the corresponding ODE, which in turn is known to be equivalent to
an Osgood-type integral condition on $f$.


  We report a method to derive the potential barrier profile shape in a dynamic
quantum dot and show the loading statistics, and hence accuracy of electron
transfer, depend significantly on the shape of the barrier. This method takes a
further step towards tunable barrier shapes, which would greatly increase the
accuracy of single electron sources, allowing the single electron current to be
useful for quantum sensing, quantum information and metrology. We apply our
method to the case of a tunable-barrier single-electron pump, an exemplary
device that shows promise as a source of hot single electron wavepackets.


  The classification of projective elliptic line scrolls with the description
of their singular loci is given. In particular we recover Atiyah Theorem by
using classical methods.


  We study walk-based centrality measures for time-ordered network sequences.
For the case of standard dynamic walk-counting, we show how to derive and
compute centrality measures induced by analytic functions. We also prove that
dynamic Katz centrality, based on the resolvent function, has the unique
advantage of allowing computations to be performed entirely at the node level.
We then consider two distinct types of backtracking and develop a framework for
capturing dynamic walk combinatorics when either or both is disallowed.


  We consider Cosserat media as SO(3)-structures over a domain D in R3. Motions
of such media are given by automorphisms of the SO(3)-bundle. We present
Euler-type equations for such media and discuss their structure.


  Building on the results of Ref. \cite{faye2018phase}, which identified an
antiferromagnetic and Kondo singlet phases on the Kondo-Hubbard square lattice,
we use the variational cluster approximation (VCA) to investigate the
competition between these phases on a two-dimensional triangular lattice with
$120^{o}$ spin orientation. In addition to the antiferromagnetic exchange
interaction $J_{\perp}$ between the localized (impurity) and conduction
(itinerant) electrons, our model includes the local repulsion $U$ of the
conduction electrons and the Heisenberg interaction $J_H$ between the
impurities. At half-filling, we obtain the quantum phase diagrams in both
planes $(J_{\perp}, U J_{\perp})$ and $(J_{\perp}, J_{H})$. We identify a
long-range, three-sublattice, spiral magnetic order which dominates the phase
diagrams for small $J_{\perp}$ and moderate $U$, while a Kondo singlet phase
becomes more stable at large $J_{\perp}$. The transition from the spiral
magnetic order to the Kondo singlet phase is a second-order phase transition.
In the $(J_{\perp}, J_{H})$ plane, we observe that the effect of $J_H$ is to
reduce the Kondo singlet phase, giving more room to the spiral magnetic order
phase. It also introduces some small magnetic oscillations of the spiral
magnetic order parameter. At finite doping and when spiral magnetism is
ignored, we find superconductivity with symmetry order parameter $d+id$, which
breaks time reversal symmetry. The superconducting order parameter has a dome
centered at around $5\%$ hole doping, and its amplitude decreases with
increasing $J_{\perp}$. We show that spiral magnetism can coexist with $d+id$
state and that superconductivity is suppressed, indicating that these two
phases are in competition.


  Current limits from the LHC on fourth generation quarks are already at the
unitarity bound of 500 GeV or so. If they exist, the strong Yukawa couplings
are turning nonperturbative, and may form bound states. We study the domain of
m_{b'} and m_{t'} in the range of 500 to 700 GeV, where we expect binding
energies are mainly of Yukawa origin, with QCD subdominant. To be consistent
with electroweak precision tests, the t' and b' quarks have to be nearly
degenerate, exhibiting a new "isospin". Comparing relativistic expansion with a
relativistic bound state approach, we find the most interesting is the
production of a color octet, isosinglet vector meson (a "gluon-prime") via
q\bar{q} to \omega_8. Leading decay modes are \pi_8^\pm W^\mp, \pi_8^0Z^0, and
constituent quark decay, with q\bar{q} and t\bar{t}' and b\bar{b}' subdominant.
The color octet, isovector pseudoscalar \pi_8 meson decays via constituent
quark decay, or to Wg. These decay rates are parameterized by the decay
constant, the binding energy and mass differences, and V_{tb'}. For small
V_{t'b}, one could have a spectacular signal of WWg, where a soft W accompanies
a very massive Wg pair. In general, however, one has high multiplicity signals
with b, W and t jet substructures that are not so different from t'\bar{t}' and
b'\bar{b}' search.


  Parameter estimation method of Jelinski-Moranda (JM) model based on weighted
nonlinear least squares (WNLS) is proposed. The formulae of resolving the
parameter WNLS estimation (WNLSE) are derived, and the empirical weight
function and heteroscedasticity problem are discussed. The effects of
optimization parameter estimation selection based on maximum likelihood
estimation (MLE) method, least squares estimation (LSE) method and weighted
nonlinear least squares estimation (WNLSE) method are also investigated. Two
strategies of heteroscedasticity decision and weighting methods embedded in JM
model prediction process are also investigated. The experimental results on
standard software reliability analysis database-Naval Tactical Data System
(NTDS) and three datasets used by J.D. Musa demonstrate that WNLSE method can
be superior to LSE and MLE under the relative error (RE) criterion.


  The enumeration $d_k(n)$ of $k$-elongated plane partition diamonds has
emerged as a generalization of the classical integer partition function $p(n)$.
We undertake a comprehensive study of congruence families for $d_k(n)$ modulo
powers of 5, with $n$ and $k$ in respective linear progressions. In particular,
we give an infinite congruence family for $d_k(n)$ modulo powers of 5. This
family cannot be proved by the classical methods, i.e., the techniques used to
prove Ramanujan's congruence families for $p(n)$. Indeed, the proof employs the
recently developed localization method, and utilizes a striking internal
algebraic structure which has not yet been seen in the proof of any congruence
family. We believe that this discovery poses important implications on future
work in partition congruences.


  The 2MASS photometric calibration observations cover ~6 square degrees on the
sky in 35 "calibration fields" each sampled in nominal photometric conditions
between 562 and 3692 times during the four years of the 2MASS mission. We
compile a catalog of variables from the calibration observations to search for
M dwarfs transited by extra-solar planets. We present our methods for measuring
periodic and non-periodic flux variability. From 7554 sources with apparent Ks
magnitudes between 5.6 and 16.1, we identify 247 variables, including
extragalactic variables and 23 periodic variables. We have discovered three M
dwarf eclipsing systems, including two candidates for transiting extrasolar
planets.


  Using the Poisson current algebra of the supersymmetric principal chiral
model, we develop the algebraic canonical structure of the model by evaluating
the fundamental Poisson bracket of the Lax matrices that fits into the rs
matrix formalism of non-ultralocal integrable models. The fundamental Poisson
bracket has been used to compute the Poisson bracket algebra of the monodromy
matrix that gives the conserved quantities in involution.


  This work studies the parameter-dependent diffusion equation in a
two-dimensional domain consisting of locally mirror symmetric layers. It is
assumed that the diffusion coefficient is a constant in each layer. The goal is
to find approximate parameter-to-solution maps that have a small number of
terms. It is shown that in the case of two layers one can find a solution
formula consisting of three terms with explicit dependencies on the diffusion
coefficient. The formula is based on decomposing the solution into orthogonal
parts related to both of the layers and the interface between them. This
formula is then expanded to an approximate one for the multi-layer case. We
give an analytical formula for square layers and use the finite element
formulation for more general layers. The results are illustrated with numerical
examples and have applications for reduced basis methods by analyzing the
Kolmogorov n-width.


  We reconsider the scenario in which the knee in the cosmic ray spectrum is
explained as due to a change in the escape mechanism of cosmic rays from the
Galaxy from one dominated by transverse diffusion to one dominated by drifts.
We solve the diffusion equations adopting realistic galactic field models and
using diffusion coefficients appropriate for strong turbulence (with a
Kolmogorov spectrum of fluctuations) and consistent with the assumed magnetic
fields. We show that properly taking into account these effects leads to a
natural explanation of the knee in the spectrum, and a transition towards a
heavier composition above the knee is predicted.


  Memory for the past makes use of a record of what happened when---a function
over past time. Time cells in the hippocampus and temporal context cells in the
entorhinal cortex both code for events as a function of past time, but with
very different receptive fields. Time cells in the hippocampus can be
understood as a compressed estimate of events as a function of the past.
Temporal context cells in the entorhinal cortex can be understood as the
Laplace transform of that function, respectively. Other functional cell types
in the hippocampus and related regions, including border cells, place cells,
trajectory coding, splitter cells, can be understood as coding for functions
over space or past movements or their Laplace transforms. More abstract
quantities, like distance in an abstract conceptual space or numerosity could
also be mapped onto populations of neurons coding for the Laplace transform of
functions over those variables. Quantitative cognitive models of memory and
evidence accumulation can also be specified in this framework allowing
constraints from both behavior and neurophysiology. More generally, the
computational power of the Laplace domain could be important for efficiently
implementing data-independent operators, which could serve as a basis for
neural models of a very broad range of cognitive computations.


  Efficient spatiotemporal control of optical beams is of paramount importance
in diverse technological domains. Conventional systems focusing on quasi-static
beam control demand precise phase or wavelength tuning for steering. This work
presents a time-efficient solution for dynamic beam steering, emphasizing
high-duty-cycle operation with fast scan rates, and eliminating the need for
active tuning of the beam direction. We achieve 100%-duty-cycle scans at a rate
of $\sim$9.8 GHz within an angular range of $\sim$1$^\circ$. Furthermore,
leveraging the dispersion characteristics of a virtually imaged phased array
(VIPA), we devise a broadband source array that seamlessly transitions from
continuous-angular steering to pulsed discrete-angular operation, unlocking
possibilities for high-sensitivity angle-, range-, and time-resolved imaging.
We also elucidate the adaptability of integrated photonic designs incorporating
wavelength-selective switches and spectral dispersers, for enabling a versatile
on-chip realization of the proposed beam steering schemes.


  We use the cellular automaton model described in L\'opez Fuentes \& Klimchuk
(2015, ApJ, 799, 128) to study the evolution of coronal loop plasmas. The
model, based on the idea of a critical misalignment angle in tangled magnetic
fields, produces nanoflares of varying frequency with respect to the plasma
cooling time. We compare the results of the model with active region (AR)
observations obtained with the Hinode/XRT and SDO/AIA instruments. The
comparison is based on the statistical properties of synthetic and observed
loop lightcurves. Our results show that the model reproduces the main
observational characteristics of the evolution of the plasma in AR coronal
loops. The typical intensity fluctuations have an amplitude of 10 to 15\% both
for the model and the observations. The sign of the skewness of the intensity
distributions indicates the presence of cooling plasma in the loops. We also
study the emission measure (EM) distribution predicted by the model and obtain
slopes in log(EM) versus log(T) between 2.7 and 4.3, in agreement with
published observational values.


  The proliferation of medical monitoring devices makes it possible to track
health vitals at high frequency, enabling the development of dynamic health
risk scores that change with the underlying readings. Survival analysis, in
particular hazard estimation, is well-suited to analyzing this stream of data
to predict disease onset as a function of the time-varying vitals. This paper
introduces the software package BoXHED (pronounced 'box-head') for
nonparametrically estimating hazard functions via gradient boosting. BoXHED 1.0
is a novel tree-based implementation of the generic estimator proposed in Lee,
Chen, Ishwaran (2017), which was designed for handling time-dependent
covariates in a fully nonparametric manner. BoXHED is also the first publicly
available software implementation for Lee, Chen, Ishwaran (2017). Applying
BoXHED to cardiovascular disease onset data from the Framingham Heart Study
reveals novel interaction effects among known risk factors, potentially
resolving an open question in clinical literature.


  Constraints on the common trilinear coupling constant $A_{0}$ are obtained in
the minimal supergravity model. $A_{0}$ is usually given at GUT scale $M_{X}$
by-hand, and has been regarded as one of the five arbitrary parameters in this
model. However, $B(M_{Z})$ as the common bilinear coupling constant $B$ at the
electroweak scale $M_{Z} \simeq 91$(GeV) is fixed by the shape of the Higgs
potential. With the renormalization group equations, this $B(M_{Z})$ is evolved
to $B_{0}$ at $M_{X}$ where a well-known relation exists between the evolved
$B_{0}$ and $A_{0}$ as $B_{0} = (A_{0}-1) m_{0}$. Therefore, $A_{0}$ is fixed
as a function of the other arbitrary parameters. In other words, the number of
arbitrary parameters are reduced by this method. Additionally, large
$\tan{\beta} > 40$ is forbidden by the conditions at $M_Z$.


  We report on observations of circumstellar disks around young stars that have
been obtained with the MIDI instrument, which is mounted on the VLT
Interferometer and operates in the 10 micrometer atmospheric window. The
maximum spatial resolution of 5 milli-arcsec corresponds to sub-AU scales at
the distance to nearby star formation regions. Thus, we can study the disks on
the spatial scales at which important processes occur, such as accretion, dust
processing, and planet formation. The main results obtained so far can be
summarized as follows: 1. The measured interferometric visibilities are in good
qualitative agreement with those predicted by models of circumstellar disks. In
particular, a predicted correlation between the strength of the far-infrared
excess and the spatial structure of the disk is confirmed by direct
measurements; 2. In several objects strong evidence for deviations from
circular symmetry is present, indicating that an inclined disk is indeed the
dominant component seen in the mid-infrared; 3. The dust properties are not
uniform over the disk, but are instead a strong function of distance to the
central star. The dust in the innermost disk regions is observed to be more
``processed'' than the dust further out, both in Herbig Ae star disks and in
those around T-Tauri stars.


  In this paper, we develop a graphical modeling framework for the inference of
networks across multiple sample groups and data types. In medical studies, this
setting arises whenever a set of subjects, which may be heterogeneous due to
differing disease stage or subtype, is profiled across multiple platforms, such
as metabolomics, proteomics, or transcriptomics data. Our proposed Bayesian
hierarchical model first links the network structures within each platform
using a Markov random field prior to relate edge selection across sample
groups, and then links the network similarity parameters across platforms. This
enables joint estimation in a flexible manner, as we make no assumptions on the
directionality of influence across the data types or the extent of network
similarity across the sample groups and platforms. In addition, our model
formulation allows the number of variables and number of subjects to differ
across the data types, and only requires that we have data for the same set of
groups. We illustrate the proposed approach through both simulation studies and
an application to gene expression levels and metabolite abundances on subjects
with varying severity levels of Chronic Obstructive Pulmonary Disease (COPD).


  JWST gives a unique access to the physical and chemical structure of inner
disks ($<10$~au), where the majority of the planets are forming. However, the
interpretation of mid-infrared (mid-IR) spectra requires detailed
thermo-chemical models able to provide synthetic spectra readily comparable to
spectroscopic observations. Our goal is to explore the potential of mid-IR
emission of OH to probe H$_2$O photodissociation. We include in the DALI disk
model prompt emission of OH following photodissociation of H$_2$O in its
$\tilde{B}$ electronic state ($\lambda < 144$~nm). This model allows to compute
in a self-consistent manner the thermo-chemical structure of the disk and the
resulting mid-IR line intensities of OH and H$_2$O. The OH line intensities in
the $9-13~\mu$m range are proportional to the total amount of water
photodissociated. As such, these lines are a tracer of the amount of water
exposed to the FUV field, which depends on the temperature, density, and
strength of the FUV field reaching the upper molecular layers. In particular,
the OH line fluxes primarily scale with the FUV field emitted by the star in
contrast with H$_2$O lines in the 10-20$~\mu$m range which scale with the
bolometric luminosity. OH is therefore a key diagnostic to probe the effect of
Ly$\alpha$ and constrain the dust FUV opacity in the upper molecular layers. A
strong asymmetry between the A' and A'' components of each rotational
quadruplet is also predicted. OH mid-IR emission is a powerful tool to probe
H$_2$O photodissociation and infer the physical conditions in disk atmospheres.
As such, the inclusion of OH mid-IR lines in the analysis of JWST-MIRI spectra
will be key for robustly inferring the composition of planet-forming disks. The
interpretation of less excited OH lines requires additional quantum
calculations of the formation pumping of OH levels by O+H$_2$ and the
collisional rate coefficients.


  We study the phases of strongly correlated electron systems in two spatial
dimensions in the framework of AdS${}_4$/CFT${}_3$ correspondence. The AdS
(gravity) model consists of a Dirac fermion coupled to electromagnetic field
and gravity. To classify the ground states of strongly correlated electrons on
the CFT side and to construct the full phase diagram of the system, we
construct a quantum many-body model of bulk fermion dynamics, based on the WKB
approximation to the Dirac equation. At low temperatures, we find a quantum
corrected approximation to the electron star where the edge is resolved in
terms of wavefunctions extended fully through AdS. At high temperatures, the
system exhibits a {\em first} order thermal phase transition to a charged
AdS-RN black hole in the bulk and the emergence of local quantum criticality on
the CFT side. This change from the third order transition experienced by the
semi-classical electron star restores the intuition that the transition between
the critical AdS-RN liquid and the finite density Fermi system is of van der
Waals liquid-gas type.


  Nonuniform neutron-rich matter present in both core-collapse supernovae and
neutron-star crusts is described in terms of a semiclassical model that
reproduces nuclear-matter properties and includes long-range Coulomb
interactions. The neutron-neutron correlation function and the corresponding
static structure factor are calculated from molecular dynamics simulations
involving 40,000 to 100,000 nucleons. The static structure factor describes
coherent neutrino scattering which is expected to dominate the neutrino
opacity. At low momentum transfers the static structure factor is found to be
small because of ion screening. In contrast, at intermediate momentum transfers
the static structure factor displays a large peak due to coherent scattering
from all the neutrons in a cluster. This peak moves to higher momentum
transfers and decreases in amplitude as the density increases. A large static
structure factor at zero momentum transfer, indicative of large density
fluctuations during a first-order phase transition, may increase the neutrino
opacity. However, no evidence of such an increase has been found. Therefore, it
is unlikely that the system undergoes a simple first-order phase transition. It
is found that corrections to the commonly used single heavy nucleus
approximation first appear at a density of the order of $10^{13}$ g/cm$^3$ and
increase rapidly with increasing density. Thus, neutrino opacities are
overestimated in the single heavy nucleus approximation relative to the
complete molecular dynamics simulations.


  We perform a general analysis of the cosmological viability of Geometric
Inflation. We show that the evolution of the universe, from inflation to the
present day, can be seen from the addition of an infinite tower of curvature
invariants into the Hilbert-Einstein action. The main epochs of the Universe
can be reproduced: Inflation, Big Bang Nucleosynthesis, and Late-time
acceleration driven by the cosmological constant. The slow-roll condition is a
robust prediction of the theory. Inflation possesses a graceful exit with
enough number of $e-$folds between the limit imposed by the Planck density and
the exit of the exponential expansion to solve the horizon problem and the
absence of topological defects. We also provide some scenarios where the energy
scale of the theory can be calibrated.


  The quest for deeper understanding of biological systems has driven the
acquisition of increasingly larger multidimensional image datasets. Inspecting
and manipulating data of this complexity is very challenging in traditional
visualization systems. We developed syGlass, a software package capable of
visualizing large scale volumetric data with inexpensive virtual reality
head-mounted display technology. This allows leveraging stereoscopic vision to
significantly improve perception of complex 3D structures, and provides
immersive interaction with data directly in 3D. We accomplished this by
developing highly optimized data flow and volume rendering pipelines, tested on
datasets up to 16TB in size, as well as tools available in a virtual reality
GUI to support advanced data exploration, annotation, and cataloguing.


  Rapid variability before and near the maximum brightness of supernovae has
the potential to provide a better understanding of nearly every aspect of
supernovae, from the physics of the explosion up to their progenitors and the
circumstellar environment. Thanks to modern time-domain optical surveys, which
are discovering supernovae in the early stage of their evolution, we have the
unique opportunity to capture their intraday behavior before maximum. We
present high-cadence photometric monitoring (on the order of seconds-minutes)
of the optical light curves of three Type Ia and two Type II SNe over several
nights before and near maximum light, using the fast imagers available on the
2.3~m Aristarchos telescope at Helmos Observatory and the 1.2~m telescope at
Kryoneri Observatory in Greece. We applied differential aperture photometry
techniques using optimal apertures and we present reconstructed light curves
after implementing a seeing correction and the Trend Filtering Algorithm(TFA).
TFA yielded the best results, achieving a typical precision between
0.01-0.04~mag. We did not detect significant bumps with amplitudes greater than
0.05~mag in any of the SNe targets in the VR-, R-, and I- bands light curves
obtained. We measured the intraday slope for each light curve, which ranges
between -0.37-0.36 mag/day in broadband VR, -0.19-0.31 mag/day in R band, and
-0.13-0.10 mag/day in I band. We used SNe light curve fitting templates for SN
2018gv, SN 2018hgc and SN 2018hhn to photometrically classify the light curves
and to calculate the time of maximum. We provide values for the maximum of SN
2018zd after applying a low-order polynomial fit and SN 2018hhn for the first
time. We suggest monitoring early supernovae light curves in hotter (bluer)
bands with a cadence of hours as a promising way of investigating the
post-explosion photometric behavior of the progenitor stars.


  Accurate galaxy scaling relations are essential for a successful model of
galaxy formation and evolution as they provide direct information about the
physical mechanisms of galaxy assembly over cosmic time. We present here a
detailed analysis of a sample of nearby spiral galaxies taken from the KINGFISH
survey. The photometric parameters of the morphological components are obtained
from bulge-disk decompositions using GALFIT data analysis algorithm, with
surface photometry of the sample done beforehand. Dust opacities are determined
using a previously discovered correlation between the central face-on dust
opacity of the disk and the stellar mass surface density. The method and the
library of numerical results previously obtained are used to correct the
measured photometric and structural parameteres for projection (inclination),
dust and decomposition effects in order to derive their intrinsic values.
Galaxy disk scaling relations are then presented, both the measured (observed)
and the intrinsic (corrected) ones, in the optical regime, to show the scale of
the biases introduced by the aforementioned effects. The slopes of the
size-luminosity relations and the dust vs stellar mass are in agreement with
values found in other works. We derive mean dust optical depth and dust/stellar
mass ratios of the sample, which we find to be consistent with previous studies
of nearby spiral galaxies. While our sample is rather small, it is sufficient
to quantify the influence of galaxy environment (dust, in this case) when
deriving scaling relations.


  Based on our deep image of Sgr A using broadband data observed with the
Jansky VLA at 6 cm, we present a new perspective of the radio bright zone at
the Galactic center. We further show the radio detection of the X-ray
Cannonball, a candidate neutron star associated with the Galactic center SNR
Sgr A East. The radio image is compared with the Chandra X-ray image to show
the detailed structure of the radio counterparts of the bipolar X-ray lobes.
The bipolar lobes are likely produced by the winds from the activities within
Sgr A West, which could be collimated by the inertia of gas in the CND, or by
the momentum driving of Sgr A*; and the poloidal magnetic fields likely play an
important role in the collimation. The less-collimated SE lobe, in comparison
to the NW one, is perhaps due to the fact that the Sgr A East SN might have
locally reconfigured the magnetic field toward negative galactic latitudes. In
agreement with the X-ray observations, the time-scale of ~ $1\times10^4$ yr
estimated for the outermost radio ring appears to be comparable to the inferred
age of the Sgr A East SNR.


  Densities from relativistic mean field calculations are applied to construct
the optical potential and, hence calculate the endpoint of the rapid proton
capture ($rp$) process. Mass values are taken from a new phenomenological mass
formula. Endpoints are calculated for different temperature- density profiles
of various X-ray bursters. We find that the $rp$ process can produce
significant quantities of nuclei upto around mass 95. Our results differ from
existing works to some extent.


  We investigate the mechanism to reproduce notable spectral features at the
ignition phase of nova explosion observed for a super-Eddington X-ray transient
source MAXI J0158$-$744 in the Small Magellanic Cloud. These are a strong Ne IX
emission line at 0.92 keV with a large equivalent width of
$0.32^{+0.21}_{-0.11}$ keV and the absence of Ne X line at 1.02 keV. In this
paper, we calculate the radiative transfer using a Monte Carlo code, taking
into account the line blanketing effect due to transitions of N, O, Ne, Mg and
Al ions in an accelerating wind emanating from a white dwarf with a structure
based on a spherically symmetric stationary model. We found that the strong Ne
IX line can be reproduced if the mass fraction of Ne is enhanced to $10^{-3}$
or more and that of O is reduced to $\sim5\times10^{-9}$ or less and that the
absence of other lines including Ne X ions at higher energies can be also
reproduced by the line blanketing effect. This enhancement of the Ne mass
fraction indicates that the ejecta are enriched by Ne dredged up from the
surface of the white dwarf composed of O, Ne, and Mg rather than C and O, as
already pointed out in the previous work. We argue that the CNO cycle driving
this nova explosion converted most of C and O into N and thus reduced the O
mass fraction.


  Rational design and cost-effective fabrication of layered double hydroxides
(LDHs) nanosheets with extraordinary electrochemical performance is a key
challenge for hybrid supercapacitors (HSCs). Herein, we report a facile in situ
growth methodology to eco-friendly synthesize hydrophilic NiCo-LDHs nanosheets
on biomass waste-derived porous carbon (BC) for robust high-performance HSC
cathode. The in situ growth process under ultrasonication realizes the rational
arrangement of NiCo-LDHs nanosheets on the surface of BC, which effectively
increases the specific surface area, promotes the electronic conductivity and
enhances the wettability of NiCo-LDHs nanosheets without affecting their
thickness values. With the beneficial effects of ultrathin thickness of LDHs
nanosheets (6.20 nm), large specific surface area (2324.1 m2 g-1), low charge
transfer resistance (1.65 ohm), and high wettability with electrolyte (34-35
degree), the obtained Ni2Co1-LDHs/BC50 electrode possesses an ultra-high
specific capacitance of 2390 F g-1 (956 C g-1) at 1 A g-1, which is superior to
most reported values. Furthermore, an assembled Ni2Co1-LDHs/BC50//YP-80F HSC
delivers a maximum specific energy of 52.47 Wh kg-1 at 375 W kg-1, and
maintains a high capacitance retention of 75.9% even after 4000 cycles. This
work provides a facile approach to fabricate LDHs nanosheets based cathode
materials for high-performance HSCs.


  We present a very quick and powerful method for the calculation of
heat-kernel coefficients. It makes use of rather common ideas, as integral
representations of the spectral sum, Mellin transforms, non-trivial commutation
of series and integrals and skilful analytic continuation of zeta functions on
the complex plane. We apply our method to the case of the heat-kernel expansion
of the Laplace operator on a $D$-dimensional ball with either Dirichlet,
Neumann or, in general, Robin boundary conditions. The final formulas are quite
simple. Using this case as an example, we illustrate in detail our scheme
---which serves for the calculation of an (in principle) arbitrary number of
heat-kernel coefficients in any situation when the basis functions are known.
We provide a complete list of new results for the coefficients
$B_3,...,B_{10}$, corresponding to the $D$-dimensional ball with all the
mentioned boundary conditions and $D=3,4,5$.


  Let $\{u(t\,, x)\}_{(t, x)\in \mathbb{R}_+\times \mathbb{R}}$ be the density
of one-dimensional super-Brownian motion starting from Lebesgue measure. Using
the Laplace functional of super-Brownian motion, we prove that as $N\to
\infty$, the normalized spatial integral $N^{-1/2}\int_0^{xN}[u(t\,, z)-1
]\rm{d} z$ converges jointly in $(t, x)$ to Brownian sheet in distribution.


  Magneto-transport measurements of ferromagnetic MnAs epilayers grown by
molecular beam epitaxy reveal the presence of both positive and negative charge
carriers. Electrical transport at high temperatures is dominated by holes, and
at low temperatures by electrons. We also observe distinct changes in the
magnetoresistance associated with the transition between the electron- and
hole-dominated transport regimes. These results are of direct relevance to
MnAs/semiconductor hybrid heterostructures and their exploitation in electronic
and optical spin injection experiments.


  The orange carotenoid protein (OCP) is the water-soluble mediator of
non-photochemical quenching in cyanobacteria, a crucial photoprotective
mechanism in response to excess illumination. OCP converts from a globular,
inactive state (OCPo) to an extended, active conformation (OCPr) under
high-light conditions, resulting in a concomitant redshift in the absorption of
the bound carotenoid. Here, OCP was trapped in either the active or inactive
state by fixing each protein conformation in trehalose-sucrose glass.
Glass-encapsulated OCPo did not convert under intense illumination and OCPr did
not convert in darkness, allowing the optical properties of each conformation
to be determined at room temperature. We measured pump wavelength-dependent
transient absorption of OCPo in glass films and found that initial OCP
photoproducts are still formed, despite the glass preventing completion of the
photocycle. By comparison to the pump wavelength dependence of the OCPo to OCPr
photoconversion yield in buffer, we show that the long-lived carotenoid
singlet-like feature (S*) is associated with ground-state heterogeneity within
OCPo, rather than triggering OCP photoconversion.


  This article investigates the relationship between the interconnectivity and
simulated dynamics of the thalamocortical system from the specific perspective
of attempting to maximize the diversity of cortical states. This is achieved by
designing the dynamics such that they favor opposing activity between adjacent
regions, thus promoting dynamic diversity while avoiding widespread activation
or de-activation. The anti-ferromagnetic Ising model with Metropolis dynamics
is adopted and applied to four variations of the large-scale connectivity of
the cat thalamocortical system: (a) considering only cortical regions and
connections; (b) considering the entire thalamocortical system; (c) the same as
in (b) but with the thalamic connections rewired so as to maintain the
statistics of node degree and node degree correlations; and (d) as in (b) but
with attenuated weights of the connections between cortical and thalamic nodes.
A series of interesting findings are obtained, including the identification of
specific substructures revealed by correlations between the activity of
adjacent regions in case (a) and a pronounced effect of the thalamic
connections in splitting the thalamocortical regions into two large groups of
nearly homogenous opposite activation (i.e. cortical regions and thalamic
nuclei, respectively) in cases (b) and (c). The latter effect is due to the
existence of dense connections between cortical and thalamic regions and the
lack of interconnectivity between the latter. Another interesting result
regarding case (d) is the fact that the pattern of thalamic correlations tended
to mirror that of the cortical regions. The possibility to control the level of
correlation between the cortical regions by varying the strength of
thalamocortical connections is also identified and discussed.


  We investigate the application of amplitude-shaped control pulses for
enhancing the time and frequency resolution of multipulse quantum sensing
sequences. Using the electronic spin of a single nitrogen vacancy center in
diamond and up to 10,000 coherent microwave pulses with a cosine square
envelope, we demonstrate 0.6 ps timing resolution for the interpulse delay.
This represents a refinement by over 3 orders of magnitude compared to the 2 ns
hardware sampling. We apply the method for the detection of external AC
magnetic fields and nuclear magnetic resonance signals of carbon-13 spins with
high spectral resolution. Our method is simple to implement and especially
useful for quantum applications that require fast phase gates, many control
pulses, and high fidelity.


  Visually guided control of micro aerial vehicles (MAV) demands for robust
real-time perception, fast trajectory generation, and a capable flight
platform. We present a fully autonomous MAV that is able to pop balloons,
relying only on onboard sensing and computing. The system is evaluated with
real robot experiments during the Mohamed Bin Zayed International Robotics
Challenge (MBZIRC) 2020 where it showed its resilience and speed. In all three
competition runs we were able to pop all five balloons in less than two minutes
flight time with a single MAV.


  The study of essential and strongly essential variables in functions defined
on finite sets is a part of $k$-valued logic. We extend the main definitions
from functions to terms. This allows us to apply concepts and results of
Universal Algebra. On the basis of the concept of a separable set of variables
in a term we introduce a new notion of complexity of terms, algebras and
varieties and give examples.


  As people's opinions change, their social networks typically coevolve with
them. People are often more susceptible to influence by people with similar
opinions than by people with dissimilar opinions. In a bounded-confidence model
(BCM) of opinion dynamics, interacting individuals influence each other through
dyadic influence if and only if their opinions are sufficiently similar to each
other. We introduce `neighborhood BCMs' (NBCMs) that include both the usual
dyadic influence and a transitive influence, which models the effect of friends
of a friend when determining whether or not an interaction with a friend
influences an individual. In this transitive influence, an individual's opinion
is influenced by a neighbor when, on average, the opinions of the neighbor's
neighbors are sufficiently similar to their own opinion. We formulate
neighborhood Deffuant--Weisbuch (NDW) and neighborhood Hegselmann--Krause (NHK)
BCMs. We simulate our NDW model on time-independent networks and observe
interesting opinion states that cannot occur in an associated baseline DW
model. We also simulate our NDW model on adaptive networks that coevolve with
opinions by changing its structure through `transitive homophily'. An
individual that breaks a tie to one of its neighbors and then rewires that tie
to a new individual, with a preference for individuals with a mean neighbor
opinion that is closer to that individual's opinion. We explore how the
qualitative opinion dynamics and network properties of our time-independent and
adaptive NDWM models change as we adjust the relative proportions of dyadic and
transitive influence. Finally, we study a two-layer opinion--disease model in
which we couple our NDW model with disease spread through a shared adaptive
network that can change both on the opinion layer and on the disease layer and
we examine how the opinion dynamics affect disease spread.


  In this work, we investigate the spin-wave propagation in three-dimensional
nanoscale CoFeB/Ta/NiFe meander structures fabricated on a structured SiO2/Si
substrate. The magnonic band structure has been experimentally determined by
wavevector-resolved Brillouin light scattering (BLS) spectroscopy and a set of
stationary modes interposed by two dispersive modes of Bloch type have been
identified. The results could be understood by micromagnetic and finite element
simulations of the mode distributions in both real space and the frequency
domain. The dispersive modes periodically oscillate in frequency over the
Brillouin zones and correspond to modes, whose spatial distributions extend
over the entire sample and are either localized exclusively in the CoFeB layer
or the entire CoFeB/Ta/NiFe magnetic bilayer. Stationary modes are mainly
concentrated in the vertical segments of the CoFeB and NiFe layers and show
negligible amplitudes in the horizon-tal segments. The findings are compared
with those of single-layer CoFeB meander structures with the same geometry
parameters, which reveals the influence of the dipolar coupling between the two
ferromagnetic layers on the magnonic band structure.


  Doping ferroelectric Hf0.5Zr0.5O2 with La is a promising route to improve
endurance. However, the beneficial effect of La on the endurance of
polycrystalline films may be accompanied by degradation of the retention. We
have investigated the endurance - retention dilemma in La-doped epitaxial
films. Compared to undoped epitaxial films, large values of polarization are
obtained in a wider thickness range, whereas the coercive fields are similar,
and the leakage current is substantially reduced. Compared to polycrystalline
La-doped films, epitaxial La-doped films show more fatigue but there is not
significant wake-up effect and endurance-retention dilemma. The persistent
wake-up effect common to polycrystalline La-doped Hf0.5Zr0.5O2 films, is
limited to a few cycles in epitaxial films. Despite fatigue, endurance in
epitaxial La-doped films is more than 1010 cycles, and this good property is
accompanied by excellent retention of more than 10 years. These results
demonstrate that wake-up effect and endurance-retention dilemma are not
intrinsic in La-doped Hf0.5Zr0.5O2.


  We consider a 2D stochastic wave equation driven by a Gaussian noise, which
is temporally white and spatially colored described by the Riesz kernel. Our
first main result is the functional central limit theorem for the spatial
average of the solution. And we also establish a quantitative central limit
theorem for the marginal and the rate of convergence is described by the
total-variation distance. A fundamental ingredient in our proofs is the
pointwise $L^p$-estimate of Malliavin derivative, which is of independent
interest.


  The effects of a running gravitational coupling and the entropic force on
future singularities are considered. Although it is expected that the quantum
corrections remove the future singularities or change the singularity type,
treating the running gravitational coupling as a function of energy density is
found to cause no change in the type of singularity but causes a delay in the
time that a singularity occurs. The entropic force is found to replaces the
singularity type $II$ by $\bar{III}$ ($a=$const., $H=$const., $\dot{H} \to
\infty$, $p \to \infty$, $\rho \to \infty$) which differs from previously known
type $III$ and to remove the $w$-singularity. We also consider an effective
cosmological model and show that the types $I$ and $II$ are replaced by the
singularity type $III$.


  B-factories provide a unique environment to test the standard model in search
for new physics. The Belle and Belle II experiments succeeded each other at
KEK, in Tsukuba, Japan. During its lifetime, Belle collected $1{\,ab}^{-1}$ of
data; at the time of this contribution, Belle II recorded $424{\,fb}^{-1}$ more
aiming for an unprecedented sample of $50{\,ab}^{-1}$. This unique data set
will allow them to search for new physics with unmatched precision. We discuss
select recent results from both experiments.


  Many machine learning tasks such as clustering, classification, and dataset
search benefit from embedding data points in a space where distances reflect
notions of relative similarity as perceived by humans. A common way to
construct such an embedding is to request triplet similarity queries to an
oracle, comparing two objects with respect to a reference. This work
generalizes triplet queries to tuple queries of arbitrary size that ask an
oracle to rank multiple objects against a reference, and introduces an
efficient and robust adaptive selection method called InfoTuple that uses a
novel approach to mutual information maximization. We show that the performance
of InfoTuple at various tuple sizes exceeds that of the state-of-the-art
adaptive triplet selection method on synthetic tests and new human response
datasets, and empirically demonstrate the significant gains in efficiency and
query consistency achieved by querying larger tuples instead of triplets.


  The theory of N = 1 supergravity with gauged supermatter is studied in the
context of a k = + 1 Friedmann minisuperspace model. It is found by imposing
the Lorentz and supersymmetry constraints that there are {\seveni no} physical
states in the particular SU(2) model studied.


  The coupled motion of ions in a radiofrequency trap has been used to connect
the frequency- dependent laser-induced heating of a sympathetically cooled
spectroscopy ion with changes in the fluorescence of a laser-cooled control
ion. This technique, sympathetic heating spectroscopy, is demonstrated using
two isotopes of calcium. In the experiment, a few scattered photons from the
spectroscopy ion are transformed into a large deviation from the steady-state
fluorescence of the control ion. This allows us to detect an optical transition
where the number of scattered photons is below our fluorescence detection
limit. Possible applications of the technique to molecular ion spectroscopy are
briefly discussed.


  When studying fluid mechanics in terms of instability, bifurcation and
invariant solutions one quickly finds out how little can be done by pen and
paper. For flows on sufficiently simple domains and under sufficiently simple
boundary conditions, one may be able to predict the parameter values at which
the base flow becomes unstable and the basic properties of the secondary flow.
On more complicated domains and under more realistic boundary conditions, such
questions can usually only be addressed by numerical means. Moreover, for a
wide class of elementary parallel shear flows the base flow remains stable in
the presence of sustained turbulent motion. In such flows, secondary solutions
often appear with finite amplitude and completely unconnected to the base flow.
Only using techniques from computational dynamical systems can such behaviour
be explained. Many of these techniques, such as for the detection and
classification of bifurcations and for the continuation in parameters of
equilibria and time-periodic solutions, were developed in the late 1970s for
dynamical systems with few degrees of freedom. The application to fluid
dynamics or, to be more precise, to spatially discretized Navier-Stokes flow,
is far from straightforward. In this historical review chapter, we follow the
development of this field of research from the valiant naivety of the early
1980s to the open challenges of today.


  ChromaStaraAtlas (CSA) is a web application that uses the ChromaStar (CS)
user interface (UI) to allow users to navigate and display a subset of the
uniformly computed comprehensive ATLAS9 grid of atmosphere and spectrum models.
It provides almost the same functionality as the CS UI in its more basic
display modes, but presents the user with primary and post-processed outputs,
including photometric color indices, based on a properly line blanketed
spectral energy distribution (SED). CSA interpolates in logarithmic quantities
within the subset of the ATLAS9 grid ranging in Teff from 3500 to 25000 K, in
log g from 0.0 to 5.0, and in [Fe/H] from 0.0 to -1.0 at a fixed
microturbulence parameter of 2 km/s, and presents outputs derived from the
monochromatic specific intensity distribution, I_lambda, in the lambda range
from 250 to 2500 nm, and performs an approximate continuum rectification of the
corresponding flux spectrum F_lambda based on its own internal model of the
corresponding continuous extinction distribution, kappa^C_lambda, based on the
procedures of CS. Optional advanced plots can be turned on that display both
the primary atmospheric structure quantities from the public ATLAS9 data files,
and secondary structure quantities computed from internal modeling. Unlike CS,
CSA allows for activities in which students derive Teff values from fitting
observed colors. The application may be found at
www.ap.smu.ca/~ishort/OpenStars.