  A group $\Gamma$ is said to be uniformly HS stable if any map $\varphi :
\Gamma \to U(n)$ that is almost a unitary representation (w.r.t. the Hilbert
Schmidt norm) is close to a genuine unitary representation of the same
dimension. We present a complete classification of uniformly HS stable groups
among finitely generated residually finite ones. Necessity of the residual
finiteness assumption is discussed. A similar result is shown to hold assuming
only amenability.


  The frequency stability of power systems is increasingly challenged by
various types of disturbances. In particular, the increasing penetration of
renewable energy sources is increasing the variability of power generation and
at the same time reducing system inertia against disturbances. In this paper we
are particularly interested in understanding how rate of change of frequency
(RoCoF) violations could arise from unusually large power disturbances. We
devise a novel specialization, named ghost sampling, of the Metropolis-Hastings
Markov Chain Monte Carlo method that is tailored to efficiently sample rare
power disturbances leading to nodal frequency violations. Generating a
representative random sample addresses important statistical questions such as
"which generator is most likely to be disconnected due to a RoCoF violation?"
or "what is the probability of having simultaneous RoCoF violations, given that
a violation occurs?" Our method can perform conditional sampling from any joint
distribution of power disturbances including, for instance, correlated and
non-Gaussian disturbances, features which have both been recently shown to be
significant in security analyses.


  The radiation of stars heats dust grains in the diffuse interstellar medium
and in star-forming regions in galaxies. Modelling this interaction provides
information on dust in galaxies, a vital ingredient for their evolution. It is
not straightforward to identify the stellar populations heating the dust, and
to link attenuation to emission on a sub-galactic scale. Radiative transfer
models are able to simulate this dust-starlight interaction in a realistic,
three-dimensional setting. We investigate the dust heating mechanisms on a
local and global galactic scale, using the Andromeda galaxy (M31) as our
laboratory. We perform a series of panchromatic radiative transfer simulations
of Andromeda with our code SKIRT. The high inclination angle of M31 complicates
the 3D modelling and causes projection effects. However, the observed
morphology and flux density are reproduced fairly well from UV to
sub-millimeter wavelengths. Our model reveals a realistic attenuation curve,
compatible with previous, observational estimates. We find that the dust in M31
is mainly (91 % of the absorbed luminosity) heated by the evolved stellar
populations. The bright bulge produces a strong radiation field and induces
non-local heating up to the main star-forming ring at 10 kpc. The relative
contribution of unevolved stellar populations to the dust heating varies
strongly with wavelength and with galactocentric distance.The dust heating
fraction of unevolved stellar populations correlates strongly with NUV-r colour
and specific star formation rate. These two related parameters are promising
probes for the dust heating sources at a local scale.


  In this paper, we compute the expectation of traces of powers of the
hermitian matrix Jacobi process for a large enough but fixed size. To proceed,
we first derive the semi-group density of its eigenvalues process as a bilinear
series of symmetric Jacobi polynomials. Next, we use the expansion of power
sums in the Schur polynomial basis and the integral Cauchy-Binet formula in
order to determine the partitions having non zero contributions after
integration. It turns out that these are hooks of bounded weight and the sought
expectation results from the integral of a product of two Schur functions with
respect to a generalized Beta distribution. For special values of the
parameters on which the matrix Jacobi process depends, the last integral
reduces to the Cauchy determinant and we close the paper with the investigation
of the asymptotic behavior of the resulting formula as the matrix size tends to
infinity.


  We calculate the off-equilibrium hydrostatic pressure for the O(N) Phi^{4}
theory to the leading order in 1/N. The present paper, the first of a series,
concentrates on the calculation of pressure in the non-equilibrium but
translationally invariant medium. The Jaynes-Gibbs principle of maximal entropy
is used to introduce the relevant density matrix which is then directly
implemented into dynamical equations through generalised Kubo-Martin-Schwinger
(KMS) conditions. We show that in the large N limit use of Ward identities
enables the pressure to be expressed in terms of two point Green's functions.
These satisfy the Kadanoff-Baym equations which are exactly solvable, and we
explicitly calculate the pressure for three illustrative choices of \rho.


  \emph{Spiroplasma} swimming is studied with a simple model based on
resistive-force theory. Specifically, we consider a bacterium shaped in the
form of a helix that propagates traveling-wave distortions which flip the
handedness of the helical cell body. We treat cell length, pitch angle, kink
velocity, and distance between kinks as parameters and calculate the swimming
velocity that arises due to the distortions. We find that, for a fixed pitch
angle, scaling collapses the swimming velocity (and the swimming efficiency) to
a universal curve that depends only on the ratio of the distance between kinks
to the cell length. Simultaneously optimizing the swimming efficiency with
respect to inter-kink length and pitch angle, we find that the optimal pitch
angle is 35.5$^\circ$ and the optimal inter-kink length ratio is 0.338, values
in good agreement with experimental observations.


  Observations of the S-stars, the cluster of young stars in the inner 0.1 pc
of the Galactic Center, have been crucial in providing conclusive evidence for
a supermassive black hole at the center of our galaxy. Since some of the stars
have orbits less than that of a typical human lifetime, it is possible to
observe multiple orbits and test the weak-field regime of general relativity.
Current calculations of S-star orbits require slow and expensive computations
in order to numerically solve geodesic equations for many small time steps. In
this paper, we present a computationally efficient, first-order post-Newtonian
model for the astrometric and spectroscopic data gathered for the S-stars. We
find that future, 30-m class telescopes -- and potentially even current large
telescopes with very high spectroscopic resolution -- may be able to detect the
Shapiro effect for an S-star in the next decade or so.


  We study the implications of the recent LHCb limit and results on Bs ->
mu+mu- and B -> K* mu+mu- observables in the constrained SUSY scenarios. After
discussing the Standard Model predictions and carefully estimating the
theoretical errors, we show the constraining power of these observables in
CMSSM and NUHM. The latest limit on BR(Bs -> mu+mu-), being very close to the
SM prediction, constrains strongly the large tan(beta) regime and we show that
the various angular observables from B -> K* mu+mu- decay can provide
complementary information in particular for moderate tan(beta) values.


  We present two-particle $p_{\rm t}$ correlations as a function of event
centrality for Au+Au collisions at $\sqrt{s_{\rm NN}}$ = 7.7, 11.5, 14.5, 19.6,
27, 39, 62.4, and 200 GeV at the Relativistic Heavy Ion Collider using the STAR
detector. These results are compared to previous measurements from CERES at the
Super Proton Synchrotron and from ALICE at the Large Hadron Collider. The data
are compared with UrQMD model calculations and with a model based on a
Boltzmann-Langevin approach incorporating effects from thermalization. The
relative dynamical correlations for Au+Au collisions at $\sqrt{s_{\rm NN}}$ =
200 GeV show a power law dependence on the number of participant nucleons and
agree with the results for Pb+Pb collisions at $\sqrt{s_{\rm NN}} = 2.76~ {\rm
TeV}$ from ALICE. As the collision energy is lowered from $\sqrt{s_{\rm NN}}$ =
200 GeV to 7.7 GeV, the centrality dependence of the relative dynamical
correlations departs from the power law behavior observed at the higher
collision energies. In central collisions, the relative dynamical correlations
increase with collision energy up to $\sqrt{s_{\rm NN}}$ = 200 GeV in contrast
to previous measurements that showed little dependence on the collision energy.


  We study second order gravitational effects of local inhomogeneities on the
cosmic microwave background radiation in flat universes with matter and a
cosmological constant $\Lambda$. We find that the general relativistic
correction to the Newtonian approximation is negligible at second order
provided that the size of the inhomogeneous region is sufficiently smaller than
the horizon scale. For a spherically symmetric top-hat type quasi-linear
perturbation, the first order temperature fluctuation corresponding to the
linear integrated Sachs-Wolfe (ISW) effect is enhanced(suppressed) by the
second order one for a compensated void(lump). As a function of redshift of the
local inhomogeneity, the second order temperature fluctuations due to evolution
of the gravitational potential have a peak before the matter-$\Lambda$ equality
epoch for a fixed comoving size and a density contrast. The second order
gravitational effects from local quasi-linear inhomogeneities at a redshift z~1
may significantly affect the cosmic microwave background.


  We describe new results and algorithms for two different, but related,
problems which deal with circulant matrices: learning shift-invariant
components from training data and calculating the shift (or alignment) between
two given signals. In the first instance, we deal with the shift-invariant
dictionary learning problem while the latter bears the name of (compressive)
shift retrieval. We formulate these problems using circulant and convolutional
matrices (including unions of such matrices), define optimization problems that
describe our goals and propose efficient ways to solve them. Based on these
findings, we also show how to learn a wavelet-like dictionary from training
data. We connect our work with various previous results from the literature and
we show the effectiveness of our proposed algorithms using synthetic, ECG
signals and images.


  A graph G = (V,E) is called fully regular if for every independent set
$I\subset V$ , the number of vertices in $V\setminus$ I that are not connected
to any element of I depends only on the size of I. A linear ordering of the
vertices of G is called successive if for every i, the first i vertices induce
a connected subgraph of G. We give an explicit formula for the number of
successive vertex orderings of a fully regular graph.
  As an application of our results, we give alternative proofs of two theorems
of Stanley and Gao + Peng, determining the number of linear edge orderings of
complete graphs and complete bipartite graphs, respectively, with the property
that the first i edges induce a connected subgraph. As another application, we
give a simple product formula for the number of linear orderings of the
hyperedges of a complete 3-partite 3-uniform hypergraph such that, for every i,
the first i hyperedges induce a connected subgraph. We found similar formulas
for complete (non-partite) 3-uniform hypergraphs and in another closely related
case, but we managed to verify them only when the number of vertices is small.


  We demonstrate a new method of variability classification using observations
of black hole X-ray binaries. Using `power colours' -- ratios of integrated
power in different Fourier frequency bands -- we can clearly differentiate
different canonical black hole states as the objects evolve during outburst. We
analyse (~ 2400) Rossi X-ray Timing Explorer observations of 12 transient low
mass black hole X-ray binaries and find that the path taken around the power
colour-colour diagram as the sources evolve is highly consistent from object to
object. We discuss how the consistency observed in the power colour-colour
diagram between different objects allows for easy state classification based on
only a few observations, and show how the power-spectral shapes can be simply
classified using a single parameter, the power-spectral `hue'. To illustrate
the benefits of our simple model-independent approach, we show that the
persistent high mass X-ray binary Cyg X-1 shows very similar power-spectral
evolution to the transient black hole sources, with the main difference being
caused by a combination of a lack of quasi-periodic oscillations and an excess
of low-frequency power-law noise in the Cyg X-1 power spectra during the
transitional state. We also compare the transient objects to the neutron star
atoll source Aquila X-1, demonstrating that it traces a different path in the
power colour-colour plot. Thus, power-colours could be an effective method to
classify newly discovered X-ray binaries.


  Robotic-assisted surgery is now well-established in clinical practice and has
become the gold standard clinical treatment option for several clinical
indications. The field of robotic-assisted surgery is expected to grow
substantially in the next decade with a range of new robotic devices emerging
to address unmet clinical needs across different specialities. A vibrant
surgical robotics research community is pivotal for conceptualizing such new
systems as well as for developing and training the engineers and scientists to
translate them into practice. The da Vinci Research Kit (dVRK), an academic and
industry collaborative effort to re-purpose decommissioned da Vinci surgical
systems (Intuitive Surgical Inc, CA, USA) as a research platform for surgical
robotics research, has been a key initiative for addressing a barrier to entry
for new research groups in surgical robotics. In this paper, we present an
extensive review of the publications that have been facilitated by the dVRK
over the past decade. We classify research efforts into different categories
and outline some of the major challenges and needs for the robotics community
to maintain this initiative and build upon it.


  Existing approaches to dialogue state tracking rely on pre-defined ontologies
consisting of a set of all possible slot types and values. Though such
approaches exhibit promising performance on single-domain benchmarks, they
suffer from computational complexity that increases proportionally to the
number of pre-defined slots that need tracking. This issue becomes more severe
when it comes to multi-domain dialogues which include larger numbers of slots.
In this paper, we investigate how to approach DST using a generation framework
without the pre-defined ontology list. Given each turn of user utterance and
system response, we directly generate a sequence of belief states by applying a
hierarchical encoder-decoder structure. In this way, the computational
complexity of our model will be a constant regardless of the number of
pre-defined slots. Experiments on both the multi-domain and the single domain
dialogue state tracking dataset show that our model not only scales easily with
the increasing number of pre-defined domains and slots but also reaches the
state-of-the-art performance.


  Reconfigurable intelligent surface (RIS)-based communication networks promise
to improve channel capacity and energy efficiency. However, the promised
capacity gains could be negligible for passive RISs because of the double
pathloss effect. Active RISs can overcome this issue because they have
reflector elements with a low-cost amplifier. This letter studies the active
RIS-aided simultaneous wireless information and power transfer (SWIPT) in a
multiuser system. The users exploit power splitting (PS) to decode information
and harvest energy simultaneously based on a realistic piecewise nonlinear
energy harvesting model. The goal is to minimize the base station (BS) transmit
power by optimizing its beamformers, PS ratios, and RIS phase
shifts/amplification factors. The simulation results show significant
improvements (e.g., 19% and 28%) with the maximum reflect power of 10 mW and 15
mW, respectively, compared to the passive RIS without higher computational
complexity cost. We also show the robustness of the proposed algorithm against
imperfect channel state information.


  The Space-Weather ANalytics for Solar Flares (SWAN-SF) is a multivariate time
series benchmark dataset recently created to serve the heliophysics community
as a testbed for solar flare forecasting models. SWAN-SF contains 54 unique
features, with 24 quantitative features computed from the photospheric magnetic
field maps of active regions, describing their precedent flare activity. In
this study, for the first time, we systematically attacked the problem of
quantifying the relevance of these features to the ambitious task of flare
forecasting. We implemented an end-to-end pipeline for preprocessing, feature
selection, and evaluation phases. We incorporated 24 Feature Subset Selection
(FSS) algorithms, including multivariate and univariate, supervised and
unsupervised, wrappers and filters. We methodologically compared the results of
different FSS algorithms, both on the multivariate time series and vectorized
formats, and tested their correlation and reliability, to the extent possible,
by using the selected features for flare forecasting on unseen data, in
univariate and multivariate fashions. We concluded our investigation with a
report of the best FSS methods in terms of their top-k features, and the
analysis of the findings. We wish the reproducibility of our study and the
availability of the data allow the future attempts be comparable with our
findings and themselves.


  We show that the zero temperature phase diagram of the vortex free sector of
the Kitaev model is in one to one correspondence with that of the classical
dimer model on the same lattice. We find that the model generically has three
distinct phases. On a honeycomb lattice with a $3\times3$ fundamental domain
all three phases are accessible. As the couplings are varied there are two
distinct transitions. The new transition is one to a gapped phase that opens up
in the interior of the $B$ phase.


  In a high-energy scattering process with hadrons in the initial state, color
is involved. Transverse momentum dependent distribution functions (TMDs)
describe the quark and gluon distributions in these hadrons in momentum space
with the inclusion of transverse directions. Apart from the (anti)-quarks and
gluons that are involved in the hard scattering process, additional gluon
emissions by the hadrons have to be taken into account as well, giving rise to
Wilson lines or gauge links. The TMDs involved are sensitive to the process
under consideration and hence potentially nonuniversal due to these Wilson line
interactions with the hard process; different hard processes give rise to
different Wilson line structures. We will show that in practice only a finite
number of universal TMDs have to be considered, which come in different linear
combinations depending on the hard process under consideration, ensuring a
generalized universality. For quarks this gives rise to three Pretzelocity
functions, whereas for gluons a richer structure of functions arises.


  Combination of different nontrivial topological states in a single material
is capable of realizing multiple functionalities and exotic physics, but such
materials are still very sparse. We report herein the results of
magnetotransport measurements and ab initio calculations on single crystalline
CaAl2Si2 semimetal. The transport properties could be well understood in
connection with the two-band model, agreeing well with the theoretical
calculations indicating four main sheets of Fermi surface consisting of three
hole pockets centered at the {\Gamma} point and one electron pocket centered at
the M point in the Brillouin zone. The single fundamental frequency imposed in
the quantum oscillations of magnetoresistance corresponds to the electron Fermi
pocket. Without spin-orbit coupling (SOC), the ab initio calculations suggest
CaAl2Si2 as a system hosting a topological nodal-line setting around the
{\Gamma} point in the Brillouin zone close to the Fermi level. Once including
the SOC, the fragile nodal-line will be gapped and a pair of Dirac points
emerge along the high symmetric {\Gamma}-A direction, which is about 1.22 eV
below the Fermi level. The SOC can also induce a topological insulator state
along the {\Gamma}-A direction with a gap of about 3 meV. The results
demonstrate CaAl2Si2 as an excellent platform for the study of novel
topological physics with multiple topological states.


  Inferring the parameters of a stochastic model based on experimental
observations is central to the scientific method. A particularly challenging
setting is when the model is strongly indeterminate, i.e. when distinct sets of
parameters yield identical observations. This arises in many practical
situations, such as when inferring the distance and power of a radio source (is
the source close and weak or far and strong?) or when estimating the amplifier
gain and underlying brain activity of an electrophysiological experiment. In
this work, we present hierarchical neural posterior estimation (HNPE), a novel
method for cracking such indeterminacy by exploiting additional information
conveyed by an auxiliary set of observations sharing global parameters. Our
method extends recent developments in simulation-based inference (SBI) based on
normalizing flows to Bayesian hierarchical models. We validate quantitatively
our proposal on a motivating example amenable to analytical solutions and then
apply it to invert a well known non-linear model from computational
neuroscience, using both simulated and real EEG data.


  We propose and test new statistical tools to study the distribution of cosmic
rays based on the use of the Minimal Spanning Tree. The method described is
particularly sensitive to filamentary structures, as those expected to arise
from strong sources of charged cosmic rays which get deflected by intervening
magnetic fields. We also test the method with data available from the AGASA and
SUGAR surface detector arrays.


  Different subsystems of organisms adapt over many time scales, such as rapid
changes in the nervous system (learning), slower morphological and neurological
change over the lifetime of the organism (postnatal development), and change
over many generations (evolution). Much work has focused on instantiating
learning or evolution in robots, but relatively little on development. Although
many theories have been forwarded as to how development can aid evolution, it
is difficult to isolate each such proposed mechanism. Thus, here we introduce a
minimal yet embodied model of development: the body of the robot changes over
its lifetime, yet growth is not influenced by the environment. We show that
even this simple developmental model confers evolvability because it allows
evolution to sweep over a larger range of body plans than an equivalent
non-developmental system, and subsequent heterochronic mutations 'lock in' this
body plan in more morphologically-static descendants. Future work will involve
gradually complexifying the developmental model to determine when and how such
added complexity increases evolvability.


  We study the x-ray emission following the collision of a Bi$^{83+}$ ion with
a neutral Xe atom at the projectile energy 70 MeV/u. The collisional and
post-collisional processes are treated separately. The probabilities of various
many-electron processes at the collision are calculated within a relativistic
independent electron model using the coupled-channel approach with atomic-like
Dirac-Fock-Sturm orbitals. The analysis of the post-collisional processes
resulting in the x-ray emission is based on the fluorescence yields, the
radiation and Auger decay rates, and allows to derive intensities of the x-ray
emission and compare them with experimental data. A reasonable agreement
between the theoretical results and the recent experimental data is observed.
The role of the relativistic effects is investigated.


  Necessary and sufficient conditions for some deformation algebras to provide
formal Frobenius structures are given. Also, examples of formal Frobenius
structures with fundamental tensor that is not of the deformation type and
examples of symmetric non-metric connections are presented.


  The problem of clustering noisy and incompletely observed high-dimensional
data points into a union of low-dimensional subspaces and a set of outliers is
considered. The number of subspaces, their dimensions, and their orientations
are assumed unknown. We propose a simple low-complexity subspace clustering
algorithm, which applies spectral clustering to an adjacency matrix obtained by
thresholding the correlations between data points. In other words, the
adjacency matrix is constructed from the nearest neighbors of each data point
in spherical distance. A statistical performance analysis shows that the
algorithm exhibits robustness to additive noise and succeeds even when the
subspaces intersect. Specifically, our results reveal an explicit tradeoff
between the affinity of the subspaces and the tolerable noise level. We
furthermore prove that the algorithm succeeds even when the data points are
incompletely observed with the number of missing entries allowed to be (up to a
log-factor) linear in the ambient dimension. We also propose a simple scheme
that provably detects outliers, and we present numerical results on real and
synthetic data.


  We present a combined analysis of rest-frame far-UV (1000-2000 A) and
rest-frame optical (3600-7000 A) composite spectra formed from very deep
observations of a sample of 30 star-forming galaxies with z=2.4+/-0.1, selected
to be representative of the full KBSS-MOSFIRE spectroscopic survey. Since the
same massive stars are responsible for the observed FUV continuum and the
excitation of the observed nebular emission, a self-consistent stellar
population synthesis model must simultaneously match the details of the far-UV
stellar+nebular continuum and-- when inserted as the excitation source in
photoionization models-- account for all observed nebular emission line ratios.
We find that only models including massive star binaries, having low stellar
metallicity (Z_*/Z_{sun} ~ 0.1) but relatively high ionized gas-phase oxygen
abundances (Z_{neb}/Z_{sun} ~ 0.5), can successfully match all of the
observational constraints. We argue that this apparent discrepancy is naturally
explained by highly super-solar O/Fe [4-5 times (O/Fe)_{sun}], expected for gas
whose enrichment is dominated by the products of core-collapse supernovae. Once
the correct ionizing spectrum is identified, photoionization models reproduce
all of the observed strong emission line ratios, the direct T_e measurement of
O/H, and allow accurate measurement of the gas-phase abundance ratios of N/O
and C/O -- both of which are significantly sub-solar but, as for O/Fe, are in
remarkable agreement with abundance patterns observed in Galactic thick disk,
bulge, and halo stars with similar O/H. High nebular excitation is the rule at
high-z (and rare at low-z) because of systematically shorter enrichment
timescales (<<1 Gyr): low Fe/O environments produce harder (and longer-lived)
stellar EUV spectra at a given O/H, enhanced by dramatic effects on the
evolution of massive star binaries.


  Aims: To investigate structure of the hot object in the symbiotic prototype Z
And during its major 2000-03 active phase. Methods: Analysis of the far
ultraviolet, optical low- and high-resolution spectroscopy and UBVR photometry.
Reconstruction of the spectral energy distribution (SED) during the outburst.
The Raman scattering process. Results: At the initial stages of the outburst
the hot object was characterized by the two-temperature spectrum (a warm
stellar radiation and a strong nebular emission) with signatures of a
mass-outflow at moderate (100-200 km/s) and very high (1000-2000 km/s)
velocities. The corresponding structure of the hot object consists of an
optically thick, slowly-expanding disk-like material encompassing the accretor
at the orbital plane and a fast optically thin wind over the remainder of the
star. A striking similarity of [FeVII]6087 and Raman 6825 profiles at/after the
dilution of the disk suggested their origin within the interaction zone where
the winds from the binary components collide.


  We explore predictive flavor models based on subgroups of the standard-model
$SU(3)^5$ flavor symmetry. Restricting to products of $SU(3)$, we find that a
global $SU(3)^3$ flavor symmetry, broken only by two Yukawa spurions, leads to
a relation among down-type quark, up-type quark and charged-lepton Yukawa
matrices: $Y_d \propto Y_u Y_e^\dagger$. As a result, the charged-lepton mass
ratios are expressed in terms of quark mass ratios and mixing angles. Large
leptonic mixing angles appear to be natural and lead to contributions to
flavor-changing neutral currents in the charged-lepton sector, which can be
tested in future precision experiments.


  The notion of singular limiting induced from continuum solutions
(slic-solutions) is applied to the problem of cavitation in nonlinear
elasticity, in order to re-assess an example of non-uniqueness of entropic weak
solutions (with polyconvex energy) due to a forming cavity.


  The widespread use of large language models (LLMs) is increasing the demand
for methods that detect machine-generated text to prevent misuse. The goal of
our study is to stress test the detectors' robustness to malicious attacks
under realistic scenarios. We comprehensively study the robustness of popular
machine-generated text detectors under attacks from diverse categories:
editing, paraphrasing, prompting, and co-generating. Our attacks assume limited
access to the generator LLMs, and we compare the performance of detectors on
different attacks under different budget levels. Our experiments reveal that
almost none of the existing detectors remain robust under all the attacks, and
all detectors exhibit different loopholes. Averaging all detectors, the
performance drops by 35% across all attacks. Further, we investigate the
reasons behind these defects and propose initial out-of-the-box patches to
improve robustness.


  High-Sensitivity Electron Paramagnetic Resonance experiments have been
carried out in fresh and stressed Mn12-Acetate single crystals for frequencies
ranging from 40 GHz up to 110 GHz. The high number of crystal dislocations
formed in the stressing process introduces a E(S_x^2-S_y^2) transverse
anisotropy term in the spin hamiltonian. From the behaviour of the resonant
absorptions on the applied transverse magnetic field we have obtained an
average value for E = 22 mK, corresponding to a concentration of dislocations
per unit cell of c = 10^-3.


  We discuss the dynamics of field configurations encoded in the certain class
of electric (magnetic) dipole-charged states in the Proca theory of the real
massive vector field. We construct such states so as to ensure that the long
distance structure of the mean electromagnetic field in them is initially set
by the formula describing the electromagnetic field of the electric (magnetic)
dipole. We analyze then how such a mean electromagnetic field evolves in time.
We find that far away from the center of the initial field configuration, the
long range component of the mean electromagnetic field harmonically oscillates,
which leads to the phenomenon of the periodic oscillations of the electric
(magnetic) dipole moment. We also find that near the center of the initial
field configuration, the mean electromagnetic field escapes from its initial
arrangement and a spherical shock wave propagating with the speed of light
appears in the studied system. A curious configuration of the axisymmetric mean
electric field is found to accompany the mean magnetic field in magnetic
dipole-charged states.


  We present a compact analytic formula for the two-loop six-particle MHV
remainder function (equivalently, the two-loop light-like hexagon Wilson loop)
in N = 4 supersymmetric Yang-Mills theory in terms of the classical
polylogarithm functions Li_k with cross-ratios of momentum twistor invariants
as their arguments. In deriving our result we rely on results from the theory
of motives.


  Kernel methods are an extremely popular set of techniques used for many
important machine learning and data analysis applications. In addition to
having good practical performances, these methods are supported by a
well-developed theory. Kernel methods use an implicit mapping of the input data
into a high dimensional feature space defined by a kernel function, i.e., a
function returning the inner product between the images of two data points in
the feature space. Central to any kernel method is the kernel matrix, which is
built by evaluating the kernel function on a given sample dataset.
  In this paper, we initiate the study of non-asymptotic spectral theory of
random kernel matrices. These are n x n random matrices whose (i,j)th entry is
obtained by evaluating the kernel function on $x_i$ and $x_j$, where
$x_1,...,x_n$ are a set of n independent random high-dimensional vectors. Our
main contribution is to obtain tight upper bounds on the spectral norm (largest
eigenvalue) of random kernel matrices constructed by commonly used kernel
functions based on polynomials and Gaussian radial basis.
  As an application of these results, we provide lower bounds on the distortion
needed for releasing the coefficients of kernel ridge regression under
attribute privacy, a general privacy notion which captures a large class of
privacy definitions. Kernel ridge regression is standard method for performing
non-parametric regression that regularly outperforms traditional regression
approaches in various domains. Our privacy distortion lower bounds are the
first for any kernel technique, and our analysis assumes realistic scenarios
for the input, unlike all previous lower bounds for other release problems
which only hold under very restrictive input settings.


  We establish an improved upper estimate on dimension of any solvable algebra
s with its nilradical isomorphic to a given nilpotent Lie algebra n. Next we
consider Levi decomposable algebras with a given nilradical n and investigate
restrictions on possible Levi factors originating from the structure of
characteristic ideals of n. We present a new perspective on Turkowski's
classification of Levi decomposable algebras up to dimension 9.


  The need to analyze the available large synoptic multi-band surveys drives
the development of new data-analysis methods. Photometric redshift estimation
is one field of application where such new methods improved the results,
substantially. Up to now, the vast majority of applied redshift estimation
methods have utilized photometric features. We aim to develop a method to
derive probabilistic photometric redshift directly from multi-band imaging
data, rendering pre-classification of objects and feature extraction obsolete.
A modified version of a deep convolutional network was combined with a mixture
density network. The estimates are expressed as Gaussian mixture models
representing the probability density functions (PDFs) in the redshift space. In
addition to the traditional scores, the continuous ranked probability score
(CRPS) and the probability integral transform (PIT) were applied as performance
criteria. We have adopted a feature based random forest and a plain mixture
density network to compare performances on experiments with data from SDSS
(DR9). We show that the proposed method is able to predict redshift PDFs
independently from the type of source, for example galaxies, quasars or stars.
Thereby the prediction performance is better than both presented reference
methods and is comparable to results from the literature. The presented method
is extremely general and allows us to solve of any kind of probabilistic
regression problems based on imaging data, for example estimating metallicity
or star formation rate of galaxies. This kind of methodology is tremendously
important for the next generation of surveys.


  We study regret minimization in non-episodic factored Markov decision
processes (FMDPs), where all existing algorithms make the strong assumption
that the factored structure of the FMDP is known to the learner in advance. In
this paper, we provide the first algorithm that learns the structure of the
FMDP while minimizing the regret. Our algorithm is based on the optimism in
face of uncertainty principle, combined with a simple statistical method for
structure learning, and can be implemented efficiently given oracle-access to
an FMDP planner. Moreover, we give a variant of our algorithm that remains
efficient even when the oracle is limited to non-factored actions, which is the
case with almost all existing approximate planners. Finally, we leverage our
techniques to prove a novel lower bound for the known structure case, closing
the gap to the regret bound of Chen et al. [2021].


  The constants of the effective action describing the massless modes in the
color-flavor-locking phase of QCD have been recently evaluated at high density.
Values of the pseudoscalar masses for nonvanishing quark masses have also been
given. The calculated values show however a puzzling feature: when $m_u=m_d=0$
and $m_s\not=0$ all the goldstones remain massless. We show that an additional
invariant is present which avoids this feature. We costruct this invariant and
discuss the emerging mass pattern for the pseudogoldstones. This provides for a
complete scheme for the pseudogoldstone masses in the color-flavor-locking
phase of QCD.


  We analyze dropout in deep networks with rectified linear units and the
quadratic loss. Our results expose surprising differences between the behavior
of dropout and more traditional regularizers like weight decay. For example, on
some simple data sets dropout training produces negative weights even though
the output is the sum of the inputs. This provides a counterpoint to the
suggestion that dropout discourages co-adaptation of weights. We also show that
the dropout penalty can grow exponentially in the depth of the network while
the weight-decay penalty remains essentially linear, and that dropout is
insensitive to various re-scalings of the input features, outputs, and network
weights. This last insensitivity implies that there are no isolated local
minima of the dropout training criterion. Our work uncovers new properties of
dropout, extends our understanding of why dropout succeeds, and lays the
foundation for further progress.


  Taking up and extending earlier suggestions, we show how two- and
threedimensional shapes of second-order HBT correlations can be described in a
multivariate Edgeworth expansion around gaussian ellipsoids, with expansion
coefficients, identified as the cumulants of pair momentum difference q, acting
as shape parameters. Off-diagonal terms dominate both the character and
magnitude of shapes. Cumulants can be measured directly and so the shape
analysis has no need for fitting.


  Deepfake technologies have become ubiquitous, "democratizing" the ability to
manipulate photos and videos. One popular use of deepfake technology is the
creation of sexually explicit content, which can then be posted and shared
widely on the internet. Drawing on a survey of over 16,000 respondents in 10
different countries, this article examines attitudes and behaviors related to
"deepfake pornography" as a specific form of non-consensual synthetic intimate
imagery (NSII). Our study found that deepfake pornography behaviors were
considered harmful by respondents, despite nascent societal awareness.
Regarding the prevalence of deepfake porn victimization and perpetration, 2.2%
of all respondents indicated personal victimization, and 1.8% all of
respondents indicated perpetration behaviors. Respondents from countries with
specific legislation still reported perpetration and victimization experiences,
suggesting NSII laws are inadequate to deter perpetration. Approaches to
prevent and reduce harms may include digital literacy education, as well as
enforced platform policies, practices, and tools which better detect, prevent,
and respond to NSII content.


  We consider de Sitter spacetime solutions and the corresponding de Sitter
kind of plane-wave solutions in M* theory. We attempt to write down
corresponsing matrix model which is found to have explicit negative energy mass
terms as well as negative energy kinetic terms for the matrix fields.


  We present here a version of the existence and uniqueness result of time
periodic solutions to the viscous Burgers equation with irregular forcing terms
(with Sobolev regularity -1 in space). The key result here is an a priori
estimate which is simpler than the previously treated case of forcing terms
with regularity -1/2 in time.


  Nonstationary Gabor frames were recently introduced in adaptive signal
analysis. They represent a natural generalization of classical Gabor frames by
allowing for adaptivity of windows and lattice in either time or frequency. In
this paper we show a general existence result for this family of frames. We
then give a perturbation result for nonstationary Gabor frames and construct
nonstationary Gabor frames with non-compactly supported windows from a related
painless nonorthogonal expansion. Finally, the theoretical results are
illustrated by two examples of practical relevance.


  Exceptional orthogonal polynomial systems (X-OPS) arise as eigenfunctions of
Sturm-Liouville problems and generalize in this sense the classical families of
Hermite, Laguerre and Jacobi. They also generalize the family of CPRS
orthogonal polynomials. We formulate the following conjecture: every
exceptional orthogonal polynomial system is related to a classical system by a
Darboux-Crum transformation. We give a proof of this conjecture for codimension
2 exceptional orthogonal polynomials (X2-OPs). As a by-product of this
analysis, we prove a Bochner-type theorem classifying all possible X2-OPS. The
classification includes all cases known to date plus some new examples of
X2-Laguerre and X2-Jacobi polynomials.


  Recently, Duncan and Mawhinney introduced a method to find saddle points of
the action in simulations of non-abelian lattice gauge theory. The idea, called
`extremization', is to minimize $\int(\delta S/\delta A_\mu)^2$ instead of the
action $S$ itself as in conventional `cooling'. The method was implemented in
an explicitly gauge variant way, however, and gauge dependence showed up in the
results. Here we present a gauge invariant formulaton of extremization on the
lattice, applicable to any gauge group and any lattice action. The procedure is
worked out in detail for U(1) and SU(N) lattice gauge theory with the plaquette
action.


  Color in an image is resolved into 3 or 4 color components and 2-Dimages of
these components are stored in separate channels. Most of the color image
enhancement algorithms are applied channel-by-channel on each image. But such a
system of color image processing is not processing the original color. When a
color image is represented as a quaternion image, processing is done in
original colors. This paper proposes an implementation of the quaternion
approach of enhancement algorithm for enhancing color images and is referred as
the modified alpha-rooting by the two-dimensional quaternion discrete Fourier
transform (2-D QDFT). Enhancement results of this proposed method are compared
with the channel-by-channel image enhancement by the 2-D DFT. Enhancements in
color images are quantitatively measured by the color enhancement measure
estimation (CEME), which allows for selecting optimum parameters for processing
by the genetic algorithm. Enhancement of color images by the quaternion based
method allows for obtaining images which are closer to the genuine
representation of the real original color.


  Many reinforcement learning algorithms can be seen as versions of approximate
policy iteration (API). While standard API often performs poorly, it has been
shown that learning can be stabilized by regularizing each policy update by the
KL-divergence to the previous policy. Popular practical algorithms such as
TRPO, MPO, and VMPO replace regularization by a constraint on KL-divergence of
consecutive policies, arguing that this is easier to implement and tune. In
this work, we study this implementation choice in more detail. We compare the
use of KL divergence as a constraint vs. as a regularizer, and point out
several optimization issues with the widely-used constrained approach. We show
that the constrained algorithm is not guaranteed to converge even on simple
problem instances where the constrained problem can be solved exactly, and in
fact incurs linear expected regret. With approximate implementation using
softmax policies, we show that regularization can improve the optimization
landscape of the original objective. We demonstrate these issues empirically on
several bandit and RL environments.


  The purpose of this note is to provide an existence result for the solution
of fully coupled Forward Backward Stochastic Differential Equations (FBSDEs) of
the mean field type. These equations occur in the study of mean field games and
the optimal control of dynamics of the McKean Vlasov type.


  We study the generalized ultradiscrete periodic Toda lattice T(M,N) which has
tropical spectral curve. We introduce a tropical analogue of Fay's trisecant
identity, and apply it to construct a general solution to T(M,N).


  In this paper we study Ramanujan sums $c_{\bf m}(\bf n)$, where
  $ {\bf m}$ and ${\bf n}$ are integral ideals in an arbitrary quadratic number
field. We give some new results about the asymptotic behavior of sums of
$c_{\bf m}(\bf n)$ over both $ {\bf m}$ and $ {\bf n}$.


  This paper investigates the energy efficiency of a multiple-input
multiple-output (MIMO) integrated sensing and communications (ISAC) system, in
which one multi-antenna base station (BS) transmits unified ISAC signals to a
multi-antenna communication user (CU) and at the same time use the echo signals
to estimate an extended target. We focus on one particular ISAC transmission
block and take into account the practical on-off non-transmission power at the
BS. Under this setup, we minimize the energy consumption at the BS while
ensuring a minimum average data rate requirement for communication and a
maximum Cram\'er-Rao bound (CRB) requirement for target estimation, by jointly
optimizing the transmit covariance matrix and the ``on'' duration for active
transmission. We obtain the optimal solution to the rate-and-CRB-constrained
energy minimization problem in a semi-closed form. Interestingly, the obtained
optimal solution is shown to unify the spectrum-efficient and energy-efficient
communications and sensing designs. In particular, for the special MIMO sensing
case with rate constraint inactive, the optimal solution follows the isotropic
transmission with shortest ``on'' duration, in which the BS radiates the
required sensing energy by using sufficiently high power over the shortest
duration. For the general ISAC case, the optimal transmit covariance solution
is of full rank and follows the eigenmode transmission based on the
communication channel, while the optimal ``on'' duration is determined based on
both the rate and CRB constraints. Numerical results show that the proposed
ISAC design achieves significantly reduced energy consumption as compared to
the benchmark schemes based on isotropic transmission, always-on transmission,
and sensing or communications only designs, especially when the rate and CRB
constraints become stringent.


  A Maple implementation of partitioned matrices is described. A recursive
block data structure is used, with all operations preserving the block
abstraction. These include constructor functions, ring operations such as
addition and product, and inversion. The package is demonstrated by calculating
the PLU factorization of a block matrix.


  Kondo hybridization in partially filled f-electron systems conveys
significant amount of electronic states sharply near the Fermi energy leading
to various instabilities from superconductivity to exotic electronic orders.
UGe2 is a 5f heavy fermion system, where the Kondo hybridization is interrupted
by the formation of two ferromagnetic phases below a 2nd order transition Tc ~
52 K and a crossover transition Tx ~ 32 K. These two ferromagnetic phases are
concomitantly related to a spin-triplet superconductivity that only emerges and
persists inside the magnetically ordered phase at high pressure. The origin of
the two ferromagnetic phases and how they form within a Kondo-lattice remain
ambiguous. Using scanning tunneling microscopy and spectroscopy, we probe the
spatial electronic states in the UGe2 as a function of temperature. We find a
Kondo resonance and sharp 5f-electron states near the chemical potential that
form at high temperatures above Tc in accordance with our density functional
theory (DFT) + Gutzwiller calculations. As temperature is lowered below Tc, the
resonance narrows and eventually splits below Tx dumping itinerant f-electron
spectral weight right at the Fermi energy. Our findings suggest a Stoner
mechanism forming the highly polarized ferromagnetic phase below Tx that itself
sets the stage for the emergence of unconventional superconductivity at high
pressure.


  Hearing Aid (HA) algorithms need to be tuned ("fitted") to match the
impairment of each specific patient. The lack of a fundamental HA fitting
theory is a strong contributing factor to an unsatisfying sound experience for
about 20% of hearing aid patients. This paper proposes a probabilistic modeling
approach to the design of HA algorithms. The proposed method relies on a
generative probabilistic model for the hearing loss problem and provides for
automated inference of the corresponding (1) signal processing algorithm, (2)
the fitting solution as well as a principled (3) performance evaluation metric.
All three tasks are realized as message passing algorithms in a factor graph
representation of the generative model, which in principle allows for fast
implementation on hearing aid or mobile device hardware. The methods are
theoretically worked out and simulated with a custom-built factor graph toolbox
for a specific hearing loss model.


  Instruction-based image editing improves the controllability and flexibility
of image manipulation via natural commands without elaborate descriptions or
regional masks. However, human instructions are sometimes too brief for current
methods to capture and follow. Multimodal large language models (MLLMs) show
promising capabilities in cross-modal understanding and visual-aware response
generation via LMs. We investigate how MLLMs facilitate edit instructions and
present MLLM-Guided Image Editing (MGIE). MGIE learns to derive expressive
instructions and provides explicit guidance. The editing model jointly captures
this visual imagination and performs manipulation through end-to-end training.
We evaluate various aspects of Photoshop-style modification, global photo
optimization, and local editing. Extensive experimental results demonstrate
that expressive instructions are crucial to instruction-based image editing,
and our MGIE can lead to a notable improvement in automatic metrics and human
evaluation while maintaining competitive inference efficiency.


  Image to image translation is the problem of transferring an image from a
source domain to a different (but related) target domain. We present a new
unsupervised image to image translation technique that leverages the underlying
semantic information for object transfiguration and domain transfer tasks.
Specifically, we present a generative adversarial learning approach that
jointly translates images and labels from a source domain to a target domain.
Our main technical contribution is an encoder-decoder based network
architecture that jointly encodes the image and its underlying semantics and
translates both individually to the target domain. Additionally, we propose
object transfiguration and cross-domain semantic consistency losses that
preserve semantic labels. Through extensive experimental evaluation, we
demonstrate the effectiveness of our approach as compared to the
state-of-the-art methods on unsupervised image-to-image translation, domain
adaptation, and object transfiguration.


  In the present paper we study description of Kadison-Schwarz type quantum
quadratic operators acting from $\bm_2(\mathbb{C})$ into
$\bm_2(\mathbb{C})\o\bm_2(\mathbb{C})$. Note that such kind of operator is a
generalization of quantum convolution. By means of such a description we
provide an example of q.q.o. which is not a Kadision-Schwartz operator.
Moreover, we study dynamics of an associated nonlinear (i.e. quadratic)
operators acting on the state space of $\bm_2(\mathbb{C})$.


  We describe a three hour inquiry activity involving converging lenses and
telescopes as part of a semester-long astronomy lab course for non-science
majors at Hartnell Community College in Salinas, CA. Students were shown
several short demonstrations and given the chance to experiment with the
materials, after which there was a class discussion about the phenomena they
observed. Students worked in groups of 2-4 to design their own experiments to
address a particular question of interest to them and then presented their
findings to the class. An instructor-led presentation highlighted the students'
discoveries and the lab's content goals, followed by a short worksheet-based
activity that guided them in applying their new knowledge to build a simple
telescope using two converging lenses. The activity was successful in
emphasizing communication skills and giving students opportunities to engage in
the process of science in different ways. One of the biggest challenges in
designing this activity was covering all of the content given the short amount
of time available. Future implementations may have more success by splitting
the lab into two sessions, one focusing on converging lenses and the other
focusing on telescopes.


  We present Hubble Space Telescope (HST) observations of the low surface
brightness (SB) galaxy Coma P. This system was first discovered in the Arecibo
Legacy Fast ALFA HI survey and was cataloged as an (almost) dark galaxy because
it did not exhibit any obvious optical counterpart in the available survey data
(e.g., Sloan Digital Sky Survey). Subsequent WIYN pODI imaging revealed an
ultra-low SB stellar component located at the center of the HI detection. We
use the HST images to produce a deep color-magnitude diagram (CMD) of the
resolved stellar population present in Coma P. We clearly detect a red stellar
sequence that we interpret to be a red giant branch, and use it to infer a tip
of the red giant branch (TRGB) distance of 5.50$^{+0.28}_{-0.53}$ Mpc. The new
distance is substantially lower than earlier estimates and shows that Coma P is
an extreme dwarf galaxy. Our derived stellar mass is only 4.3 $\times$ 10$^5$
$M_\odot$, meaning that Coma P has an extreme HI-to-stellar mass ratio of 81.
We present a detailed analysis of the galaxy environment within which Coma P
resides. We hypothesize that Coma P formed within a local void and has spent
most of its lifetime in a low-density environment. Over time, the gravitational
attraction of the galaxies located in the void wall has moved it to the edge,
where it had a recent "fly-by" interaction with M64. We investigate the
possibility that Coma P is at a farther distance and conclude that the
available data are best fit by a distance of 5.5 Mpc.


  A new gauge driver is introduced for the generalized harmonic (GH)
representation of Einstein's equation. This new driver allows a rather general
class of gauge conditions to be implemented in a way that maintains the
hyperbolicity of the combined evolution system. This driver is more stable and
effective, and unlike previous drivers, allows stable evolutions using the
dual-frame evolution technique. Appropriate boundary conditions for this new
gauge driver are constructed, and a new boundary condition for the ``gauge''
components of the spacetime metric in the GH Einstein system is introduced. The
stability and effectiveness of this new gauge driver are demonstrated through
numerical tests, which impose a new damped-wave gauge condition on the
evolutions of single black-hole spacetimes.


  News items have a significant impact on stock markets but the ways are
obscure. Many previous works have aimed at finding accurate stock market
forecasting models. In this paper, we use text mining and sentiment analysis on
Chinese online financial news, to predict Chinese stock tendency and stock
prices based on support vector machine (SVM). Firstly, we collect 2,302,692
news items, which date from 1/1/2008 to 1/1/2015. Secondly, based on this
dataset, a specific domain stop-word dictionary and a precise sentiment
dictionary are formed. Thirdly, we propose a forecasting model using SVM. On
the algorithm of SVM implementation, we also propose two-parameter optimization
algorithms to search for the best initial parameter setting. The result shows
that parameter G has the main effect, while parameter C's effect is not
obvious. Furthermore, support vector regression (SVR) models for different
Chinese stocks are similar whereas in support vector classification (SVC)
models best parameters are quite differential. Series of contrast experiments
show that: a) News has significant influence on stock market; b) Expansion
input vector for additional situations when that day has no news data is better
than normal input in SVR, yet is worse in SVC; c) SVR shows a fantastic degree
of fitting in predicting stock fluctuation while such result has some time lag;
d) News effect time lag for stock market is less than two days; e) In SVC,
historic stock data has a most efficient time lag which is about 10 days,
whereas in SVR this effect is not obvious. Besides, based on the special
structure of the input vector, we also design a method to calculate the
financial source impact factor. Result suggests that the news quality and
audience number both have a significant effect on the source impact factor.
Besides, for Chinese investors, traditional media has more influence than
digital media.


  Moments of the characteristic polynomial of a random matrix taken from any of
the three ensembles, orthogonal, unitary or symplectic, are given either as a
determinant or a pfaffian or as a sum of determinants. For gaussian ensembles
comparing the two expressions of the same moment one gets two remarkable
identities, one between an $n\times n$ determinant and an $m\times m$
determinant and another between the pfaffian of a $2n\times 2n$ anti-symmetric
matrix and a sum of $m\times m$ determinants.


  Dielectric permittivity measurements show that (1-x)NaNbO3-(x)Gd1/3NbO3
crystals, at $x=0.09$, exhibit a first order phase transition near 150 C which
is diffuse over a wide temperature interval. The area of the \epsilon(T)
thermal hysteresis loop was found to depend both on the annealing and cooling
temperatures. Optical studies in polarized light show the decrease of the
domains sizes at this phase transition. The results obtained are fitted
assuming the space distribution of Curie temperatures.


  We study a recently introduced base $b$ polynomial analog of Stern's diatomic
sequence, which generalizes Stern polynomials of Klavar, Dilcher, Ericksen,
Mansour, Stolarsky, and others. We lift some basic properties of base $2$ Stern
polynomials to arbitrary base, and introduce a matrix characterization of Stern
polynomials. By specializing, we recover some new number theoretic results
about hyper $b$-ary partitions, which count partitions of $n$ into powers of
$b$.


  We investigated the kinetics of domain growth on liposomes consisting of a
ternary mixture (unsaturated phospholipid, saturated phospholipid, and
cholesterol) by temperature jump. The domain growth process was monitored by
fluorescence microscopy, where the growth was mediated by the fusion of domains
through the collision. It was found that an average domain size r develops with
time t as r ~ t^0.15, indicating that the power is around a half of the
theoretical expectation deduced from a model of Brownian motion on a
2-dimensional membrane. We discuss the mechanism of the experimental scaling
behavior by considering the elasticity of the membrane.


  The problem of separation of variables (SoV) in supersymmetric spin chains is
closely related to the calculation of correlation functions in N=4 SYM theory
which is integrable in the planar limit. To address this question we find a
compact formula for the spin chain eigenstates, which does not have any sums
over auxiliary roots one usually gets in the widely adopted nested Bethe
ansatz. Our construction only involves one application of a simple Bg(u_k)
operator to the reference state for each of the magnons, in complete analogy
with the su(2) algebraic Bethe ansatz. This generalizes our SoV based
construction for su(n) to the supersymmetric su(1|2) case.


  Given an odd prime p, we present three independent ways of relating modulo p
certain truncated convolutions of divided Bernoulli numbers to certain full
convolutions of divided Bernoulli numbers.


  Control of hyperfine interactions is a fundamental requirement for quantum
computing architecture schemes based on shallow donors in silicon. However, at
present, there is lacking an atomistic approach including critical effects of
central-cell corrections and non-static screening of the donor potential
capable of describing the hyperfine interaction in the presence of both strain
and electric fields in realistically sized devices. We establish and apply a
theoretical framework, based on atomistic tight-binding theory, to
quantitatively determine the strain and electric field dependent hyperfine
couplings of donors. Our method is scalable to millions of atoms, and yet
captures the strain effects with an accuracy level of DFT method. Excellent
agreement with the available experimental data sets allow reliable
investigation of the design space of multi-qubit architectures, based on both
strain-only as well as hybrid (strain+field) control of qubits. The benefits of
strain are uncovered by demonstrating that a hybrid control of qubits based on
(001) compressive strain and in-plane (100 or 010) fields results in higher
gate fidelities and/or faster gate operations, for all of the four donor
species considered (P, As, Sb, and Bi). The comparison between different donor
species in strained environments further highlights the trends of hyperfine
shifts, providing predictions where no experimental data exists. Whilst faster
gate operations are realisable with in-plane fields for P, As, and Sb donors,
only for the Bi donor, our calculations predict faster gate response in the
presence of both in-plane and out-of-plane fields, truly benefiting from the
proposed planar field control mechanism of the hyperfine interactions.


  We answer a question of Durham, Hagen, and Sisto, proving that a
Teichm\"uller geodesic ray does not necessarily converge to a unique point in
the hierarchically hyperbolic space boundary of Teichm\"uller space. In fact,
we prove that the limit set can be almost anything allowed by the topology.


  Machine learning models have been found to learn shortcuts -- unintended
decision rules that are unable to generalize -- undermining models'
reliability. Previous works address this problem under the tenuous assumption
that only a single shortcut exists in the training data. Real-world images are
rife with multiple visual cues from background to texture. Key to advancing the
reliability of vision systems is understanding whether existing methods can
overcome multiple shortcuts or struggle in a Whac-A-Mole game, i.e., where
mitigating one shortcut amplifies reliance on others. To address this
shortcoming, we propose two benchmarks: 1) UrbanCars, a dataset with precisely
controlled spurious cues, and 2) ImageNet-W, an evaluation set based on
ImageNet for watermark, a shortcut we discovered affects nearly every modern
vision model. Along with texture and background, ImageNet-W allows us to study
multiple shortcuts emerging from training on natural images. We find computer
vision models, including large foundation models -- regardless of training set,
architecture, and supervision -- struggle when multiple shortcuts are present.
Even methods explicitly designed to combat shortcuts struggle in a Whac-A-Mole
dilemma. To tackle this challenge, we propose Last Layer Ensemble, a
simple-yet-effective method to mitigate multiple shortcuts without Whac-A-Mole
behavior. Our results surface multi-shortcut mitigation as an overlooked
challenge critical to advancing the reliability of vision systems. The datasets
and code are released: https://github.com/facebookresearch/Whac-A-Mole.


  At large institutions of higher education, students frequently have a choice
whether to attend the introductory physics sequence asynchronously online,
on-site in a traditional lecture-setting, or in a reformed studio setting. In
this study, we investigate how these different settings are correlated with
measures of self-efficacy, interest in physics, and success in subsequent
physics and engineering courses, which have the introductory physics sequence
as prerequisites. As previous research indicates, some of these measures may
depend on gender. We found that the course setting had no significant
correlation with the grade in subsequent courses, but that studio-settings gave
students the feeling of being better prepared, particularly for subsequent
courses that included laboratory or recitation components. We also found that
gender was correlated with measures of interest in physics, where female
students expressed significantly less interest in the subject, regardless of
course setting.


  We have computed the contribution to the observables of the final two fermion
channel at LEP2, at the limiting energy $\sqrt{q^2}=200 GeV$, coming from boxes
with two neutralinos of purely gaugino type, of mass $M=100 GeV$. We find a
potentially visible effect only for the muon channel, in the cross section and,
to a lesser extent, in the forward-backward asymmetry. Analogous effects coming
from the chargino box are also briefly discussed.


  In this paper we study the interactions among a static quark-antiquark pair
in the presence of dense two-color quark matter with lattice simulation. To
this end we compute Polyakov line correlation functions and determine the
renormalized color averaged, color singlet and color triplet grand potentials.
The color singlet grand potential allows us to elucidate the number of quarks
induced by a static quark antiquark source, as well as the internal energy of
such a pair in dense quark matter. We furthermore determine the screening
length, which in the confinement phase is synonymous with the string breaking
distance. The screening length is a decreasing function of baryon density, due
to the possibility to break the interquark string via a scalar diquark
condensate at high density. We also study the large distance properties of the
color singlet grand potential in a dense medium and find that it is well
described by a simple Debye screening formula, parameterized by a Debye mass
and an effective coupling constant. The latter is of order of unity, i.e. even
at large density two-color quark matter is a strongly correlated system.


  Next generation optoelectronic systems will require the efficient transfer of
optical signals between many discrete photonic components integrated onto a
single substrate. While modern assembly processes can easily integrate
thousands of electrical components onto a single board, photonic assembly is
far more challenging due to the wavelength-scale alignment tolerances required.
Here we address this problem by introducing an alignment-free photonic coupler
robust to x, y, z displacement and angular misalignment. This alignment-free
coupler engineers a translationally-invariant evanescent interaction between
waveguides by intersecting them at an angle, which enables a lateral and
angular alignment tolerance fundamentally larger than non-evanescent approaches
such as edge coupling. We show that our approach can function as a universal
photonic connector interfacing photonic integrated circuits and microchiplets
across different platforms. As a potential use case, we describe a new type of
self-aligning photonic circuit board enabled by our approach that greatly
simplifies assembly of complex optoelectronic systems.


  Reflectance Transformation Imaging (RTI) is a popular technique that allows
the recovery of per-pixel reflectance information by capturing an object under
different light conditions. This can be later used to reveal surface details
and interactively relight the subject. Such process, however, typically
requires dedicated hardware setups to recover the light direction from multiple
locations, making the process tedious when performed outside the lab.
  We propose a novel RTI method that can be carried out by recording videos
with two ordinary smartphones. The flash led-light of one device is used to
illuminate the subject while the other captures the reflectance. Since the led
is mounted close to the camera lenses, we can infer the light direction for
thousands of images by freely moving the illuminating device while observing a
fiducial marker surrounding the subject. To deal with such amount of data, we
propose a neural relighting model that reconstructs object appearance for
arbitrary light directions from extremely compact reflectance distribution data
compressed via Principal Components Analysis (PCA). Experiments shows that the
proposed technique can be easily performed on the field with a resulting RTI
model that can outperform state-of-the-art approaches involving dedicated
hardware setups.


  We study the conditions for the existence of neutrino oscillations in the
field-theoretical approach which combines neutrino production and detection
processes in a single Feynman graph. The ``oscillating neutrino'' is
represented by an inner line of this graph where, due to the macroscopic
distance L between source and detector, the neutrino propagators for neutrinos
with definite mass are replaced by the projection operators unto the neutrino
states on mass shell. We use as a concrete model reaction the neutrino source
and detector as given in the LSND experiment and we carefully take into account
the finite lifetime of the stopped muons which provide the anti-muon neutrino
beam. We show that the field-theoretical approach provides a solid method to
locate all possible conditions and allows to separate unambiguously their
different origins. Some of these conditions are independent of L whereas others
state that coherence is lost when L exceeds a certain ``coherence length''.
Also it turns out that, at least in the concrete situation considered here, the
concept of neutrino wave packets is not supported by the field-theoretical
approach for realistic experimental conditions, i.e., the neutrino energy
spread is incoherent in origin.


  We show how to map gravitational theories formulated in the Jordan frame to
the Einstein frame at the quantum field theoretical level considering quantum
fields in curved space-time. As an example, we consider gravitational theories
in the Jordan frame of the type $F(\phi,\, R)=f(\phi)\, R-V(\phi)$ and perform
the map to the Einstein frame. Our results can easily be extended to any
gravitational theory. We consider the Higgs inflation model as an application
of our results.


  In conditional Generative Adversarial Networks (cGANs), when two different
initial noises are concatenated with the same conditional information, the
distance between their outputs is relatively smaller, which makes minor modes
likely to collapse into large modes. To prevent this happen, we proposed a
hierarchical mode exploring method to alleviate mode collapse in cGANs by
introducing a diversity measurement into the objective function as the
regularization term. We also introduced the Expected Ratios of Expansion (ERE)
into the regularization term, by minimizing the sum of differences between the
real change of distance and ERE, we can control the diversity of generated
images w.r.t specific-level features. We validated the proposed algorithm on
four conditional image synthesis tasks including categorical generation, paired
and un-paired image translation and text-to-image generation. Both qualitative
and quantitative results show that the proposed method is effective in
alleviating the mode collapse problem in cGANs, and can control the diversity
of output images w.r.t specific-level features.


  A 2-D version of the asymmetric exclusion model for granular sheared flows is
presented. The velocity profile exhibits two qualitatively different behaviors,
dependent on control parameters. For low friction, the velocity profile follows
an exponential decay while for large friction the profile is more accurately
represented by a Gaussian law. The phase transition occurring between these two
behavior is identified by the appearance of correlations in the cluster size
distribution. Finally, a mean--field theory gives qualitative and quantitative
good agreement with the numerical results.


  Violation of the no-signaling principle may occur in PT-symmetric evolutions,
that is, evolutions that stem from Hamiltonians that are symmetric with respect
to parity and time-reversal, of bipartite entangled states. The violation can
be avoided by using a non-conventional inner product. We show that even within
the formalism that utilizes the conventional Dirac inner product between
physical state vectors, it is possible to obtain instances of local
preservation of the no-signaling principle for evolutions corresponding to
PT-symmetric non-hermitian Hamiltonians with real eigenvalues, of multiparty
entangled states, whose bipartite versions still violate the principle. The
phenomenon can be witnessed already by using the Greenberger-Horne-Zeilinger
state. Interestingly, the generalized W states do not support such a local
preservation of no-signaling.


  Observations of the early rise and propagation phases of solar eruptive
prominences can provide clues about the forces acting on them through the
behavior of their acceleration with height. We have analyzed such an event,
observed on 13 April 2010 by SWAP on PROBA2 and EUVI on STEREO. A feature at
the top of the erupting prominence was identified and tracked in images from
the three spacecraft. The triangulation technique was used to derive the true
direction of propagation of this feature. The reconstructed points were fitted
with two mathematical models: i) a power-law polynomial function and ii) a
cubic smoothing spline, in order to derive the accelerations. The first model
is characterized by five degrees of freedom while the second one is
characterized by ten degrees of freedom. The results show that the acceleration
increases smoothly and it is continuously increasing with height. We conclude
that the prominence is not accelerated immediately by local reconnection but
rather is swept away as part of a large-scale relaxation of the coronal
magnetic field.


  We have evaluated the amplitude for muon capture by a proton, mu + p --> n +
nu, to O(p^3) within the context of heavy baryon chiral perturbation theory
(HBChPT) using the new O(p^3) Lagrangian of Ecker and Mojzis (E&M). We obtain
expressions for the standard muon capture form factors and determine three of
the coefficients of the E&M Lagrangian, namely, b_7, b_{19}, and b_{23}. We
describe progress on the next step, a calculation of the radiative muon capture
process, mu + p --> n + nu + gamma.


  We have investigated the nanostructure and microstructure resulting from ns
laser irradiation simultaneous with deposition of Co films on Si(001)
substrates. The spatial order and length scales of the resulting nanopatterns
and their crystalline microstructure were investigated as a function of film
thickness h and laser energy density E using a combination of atomic force,
scanning electron and transmission electron microscopies. The results could be
classified into two distinct categories based on the laser energy density used.
It was observed that the thickness-dependent E required to melt the Co film
(E_{Co}) was lower than Si (E_{Si}) primarily because of the higher
reflectivity of Si. Consequently, for energy densities E_{Co}<E_{1}<E_{Si} that
preferentially melted the Co film, spatially ordered nanoparticles were formed
and were attributed to capillary-driven transport in the liquid phase. The
ordering length scale corresponded to the interference fringe spacing \Lambda
and the microstructure was primarily Co metal and a metal-rich silicide phase.
The native oxide layer played an important role in minimizing the Co-Si
reaction. For laser energy densities E_{2}\geq E_{Si}, spatially ordered
patterns with periodic length scales L<\Lambda were observed and resulted from
interference of an incident laser beam with a beam transmitted into the Si
substrate. These nanopatterns showed one- as well as two-dimensional spatial
ordering of the nanostructures. The microstructure in this laser energy regime
was dominated by silicide formation. These results suggest that various
nanostructures and microstructures, ranging from nearly pure metal to a Si-rich
silicide phase can be formed by appropriate choice of the laser energy
simultaneous with film growth.


  In physical systems, decoherence can arise from both dissipative and
dephasing processes. In mechanical resonators, the driven frequency response
measures a combination of both, while time domain techniques such as ringdown
measurements can separate the two. Here, we report the first observation of the
mechanical ringdown of a carbon nanotube mechanical resonator. Comparing the
mechanical quality factor obtained from frequency- and time-domain
measurements, we find a spectral quality factor four times smaller than that
measured in ringdown, demonstrating dephasing-induced decoherence of the
nanomechanical motion. This decoherence is seen to arise at high driving
amplitudes, pointing to a non-linear dephasing mechanism. Our results highlight
the importance of time-domain techniques for understanding dissipation in
nano-mechanical resonators, and the relevance of decoherence mechanisms in
nanotube mechanics.


  The [CII] 157.74 $\mu$m fine structure transition is one of the brightest and
most well-studied emission lines in the far-infrared (FIR), produced in the
interstellar medium (ISM) of galaxies. We study its properties in sub-pc
resolution hydrodynamical simulations for an ISM patch with gas surface density
of $\Sigma_{\rm{g}}=10\;M_{\odot}\;\rm{pc}^{-2}$, coupled with time-dependent
chemistry, far-ultraviolet (FUV) dust and gas shielding, star formation,
photoionization and supernova (SN) feedback, and full line-radiative transfer.
We find a [CII]-to-H$_2$ conversion factor that scales weakly with metallicity
$X_{\rm{[CII]}}=6.31\times 10^{19} \;Z^{\prime\;0.17}\;
\rm{cm}^{-2}\;(\rm{K}\;\rm{km}\;\rm{s}^{-1})^{-1}$, where $Z^{\prime}$ is the
normalized metallicity relative to solar. {The majority of [CII] originates
from atomic gas with hydrogen number density $n\sim 10~{\rm cm^{-3}}$.} The
[CII] line intensity positively correlates with the star formation rate (SFR),
with a normalization factor that scales linearly with metallicity. We find that
this is broadly consistent with $z\sim0$ observations. As such, [CII] is a good
SFR tracer even in metal-poor environments where molecular lines might be
undetectable. Resolving the clumpy structure of the dense
($n=10-10^3\;\rm{cm}^{-3}$) interstellar medium (ISM) is important as it
dominates [CII] 157.74 $\mu$m emission. We compare our full radiative transfer
computation with the optically-thin limit and find that the [CII] line becomes
marginally optically thick only at super-solar metallicity for our assumed gas
surface density.


  Putting dynamics into random matrix models leads to finitely many
nonintersecting Brownian motions on the real line for the eigenvalues, as was
discovered by Dyson. Applying scaling limits to the random matrix models,
combined with Dyson's dynamics, then leads to interesting, infinite-dimensional
diffusions for the eigenvalues. This paper studies the relationship between two
of the models, namely the Airy and Pearcey processes and more precisely shows
how to approximate the multi-time statistics for the Pearcey process by the one
of the Airy process with the help of a PDE governing the gap probabilities for
the Pearcey process.


  Owing to the variety of possible charge and spin states and to the different
ways of coupling to the environment, paramagnetic centres in wide band-gap
semiconductors and insulators exhibit a strikingly rich spectrum of properties
and functionalities, exploited in commercial light emitters and proposed for
applications in quantum information. Here we demonstrate, by combining
synchrotron techniques with magnetic, optical and \emph{ab initio} studies,
that the codoping of GaN:Mn with Mg allows to control the Mn$^{n+}$ charge and
spin state in the range $3\le n\le 5$ and $2\ge S\ge 1$. According to our
results, this outstanding degree of tunability arises from the formation of
hitherto concealed cation complexes Mn-Mg$_k$, where the number of ligands $k$
is pre-defined by fabrication conditions. The properties of these complexes
allow to extend towards the infrared the already remarkable optical
capabilities of nitrides, open to solotronics functionalities, and generally
represent a fresh perspective for magnetic semiconductors.


  In this paper we state and prove Morse type inequalities for Morse functions
as well as for closed differential 1-forms. These inequalities involve
delocalized Betti numbers. As an immediate consequence, we prove the vanishing
of delocalized Betti numbers of manifolds fibering over the circle.


  In this paper we use a variation of simulated annealing algorithm for
optimizing two-dimensional constellations with 32 signals. The main objective
is to maximize the symmetric pragmatic capacity under the peak-power
constraint. The method allows the joint optimization of constellation and
binary labeling. We also investigate the performance of the optimized
constellation over nonlinear satellite channel under additive white Gaussian
noise. We consider the performance over systems with and without
pre-distorters. In both cases the optimized constellations perform considerably
better than the conventional Amplitude Phase Shift Keying (APSK) modulations,
used in the current digital video broadcasting standard (DVB-S2) on satellite
channels. Based on our optimized constellations, we also propose a new labeling
for the 4+12+16-APSK constellation of the DVB-S2 standard which is Gray over
all rings.


  Extensive measurements of the X-ray background (XRB) yield a reasonably
reliable characterisation of its basic properties. Having resolved most of the
cosmic XRB into discrete sources, the levels and spectral shapes of its main
components can be used to probe both the source populations and also
alternative cosmological and large-scale structure models. Recent observations
of clusters seem to provide evidence that clusters formed earlier and are more
abundant than predicted in the standard $\Lambda$CDM model. This motivates
interest in alternative models that predict enhanced power on cluster scales.
We calculate predicted levels and spectra of the superposed emission from
groups and clusters of galaxies in $\Lambda$CDM and in two viable alternative
non-Gaussian ($\chi^2$) and early dark energy models. The predicted levels of
the contribution of clusters to the XRB in the non-Gaussian models exceed the
measured level at low energies and levels of the residual XRB in the 2-8 keV
band; these particular models are essentially ruled out. Our work demonstrates
the diagnostic value of the integrated X-ray emission from clusters, by
considering also its dependences on different metallicities, gas and
temperature profiles, Galactic absorption, merger scenarios, and on a
non-thermal pressure component. We also show that the XRB can be used for a
upper limit for the concentration parameter value.


  This paper reports on the measurement of the large-scale anisotropy in the
distribution of cosmic-ray arrival directions using the data collected by the
air shower detector ARGO-YBJ from 2008 January to 2009 December,during the
minimum of solar activity between cycles 23 and 24. In this period, more than
200 billion showers were recorded with energies between 1 and 30 TeV. The
observed two-dimensional distribution of cosmic rays is characterized by two
wide regions of excess and deficit, respectively, both of relative intensity
0.001 with respect to a uniform flux, superimposed on smaller size structures.
The harmonic analysis shows that the large-scale cosmic-ray relative intensity
as a function of R.A. can be described by the first and second terms of a
Fouries series. The high event statistics allow the study of the energy
dependence of the anistropy, showing that the amplitude increases with energy,
with a maximum intensity at 10 TeV, and then decreases while the phase slowly
shifts toward lower values of R.A. with increasing energy. The ARGO-YBJ data
provide accurate observations over more than a decade of energy around this
feature of the anisotropy spectrum.


  The dependency graph is a data architecture that models all the dependencies
between the different types of assets in the game. It depicts the
dependency-based relationships between the assets of a game. For example, a
player must construct an arsenal before he can build weapons. It is vital that
the dependency graph of a game is designed logically to ensure a logical
sequence of game play. However, a mere logical dependency graph is not
sufficient in sustaining the players' enduring interests in a game, which
brings the problem of game balancing into picture. The issue of game balancing
arises when the players do not feel the chances of winning the game over their
AI opponents who are more skillful in the game play. At the current state of
research, the architecture of dependency graph is monolithic for the players.
The sequence of asset possession is always foreseeable because there is only a
single dependency graph. Game balancing is impossible when the assets of AI
players are overwhelmingly outnumbering that of human players. This paper
proposes a parallel architecture of dependency graph for the AI players and
human players. Instead of having a single dependency graph, a parallel
architecture is proposed where the dependency graph of AI player is adjustable
with that of human player using a support dependency as a game balancing
mechanism. This paper exhibits that the parallel dependency graph helps to
improve game balancing.


  Motivated by the bootstrap percolation process for graphs, we define a new,
high-order generalisation to $k$-uniform hypergraphs, in which we infect
$j$-sets of vertices for some integer $1\le j \le k-1$. We investigate the
smallest possible size of an initially infected set which ultimately percolates
and determine the exact size in almost all cases of $k$ and $j$.


  We have monitored the pulse frequencies of the two soft gamma repeaters SGR
1806-20 and SGR 1900+14 through the beginning of year 2001 using primarily
Rossi X-ray Timing Explorer Proportional Counter Array observations. In both
sources, we observe large changes in the spin-down torque up to a factor of ~4,
which persist for several months. Using long baseline phase-connected timing
solutions as well as the overall frequency histories, we construct torque noise
power spectra for each SGR. The power spectrum of each source is very red
(power-law slope ~-3.5). The torque noise power levels are consistent with some
accreting systems on time scales of ~1 year, yet the full power spectrum is
much steeper in frequency than any known accreting source. To the best of our
knowledge, torque noise power spectra with a comparably steep frequency
dependence have only been seen in young, glitching radio pulsars (e.g. Vela).
The observed changes in spin-down rate do not correlate with burst activity,
therefore, the physical mechanisms behind each phenomenon are also likely
unrelated. Within the context of the magnetar model, seismic activity cannot
account for both the bursts and the long-term torque changes unless the
seismically active regions are decoupled from one another.


  We explain how to deduce the degenerate analogue of Ariki's categorification
theorem over the ground field C as an application of Schur-Weyl duality for
higher levels and the Kazhdan-Lusztig conjecture in finite type A. We also
discuss some supplementary topics, including Young modules, tensoring with
sign, tilting modules and Ringel duality.


  Using the Berline-Vergne integration formula for equivariant cohomology for
torus actions, we prove that integrals over Grassmannians (classical,
Lagrangian or orthogonal ones) of characteristic classes of the tautological
bundle, can be expressed as iterated residues at infinity of some holomorphic
functions of several variables. The results obtained for these cases, can be
expressed as special cases of one formula, involving the Weyl group action on
the characters of the natural representation of the torus.


  We characterize several equilibrium vortex effects in a rotating
Bose-Einstein condensate. Specifically we attempt precision measurements of
vortex lattice spacing and the vortex core size over a range of condensate
densities and rotation rates. These measurements are supplemented by numerical
simulations, and both experimental and numerical data are compared to theory
predictions of Sheehy and Radzihovsky [17] (cond-mat/0402637) and Baym and
Pethick [25] (cond-mat/0308325). Finally, we study the effect of the
centrifugal weakening of the trapping spring constants on the critical
temperature for quantum degeneracy and the effects of finite temperature on
vortex contrast.


  The study of learning in games has thus far focused primarily on normal form
games. In contrast, our understanding of learning in extensive form games
(EFGs) and particularly in EFGs with many agents lags far behind, despite them
being closer in nature to many real world applications. We consider the natural
class of Network Zero-Sum Extensive Form Games, which combines the global
zero-sum property of agent payoffs, the efficient representation of graphical
games as well the expressive power of EFGs. We examine the convergence
properties of Optimistic Gradient Ascent (OGA) in these games. We prove that
the time-average behavior of such online learning dynamics exhibits $O(1/T)$
rate convergence to the set of Nash Equilibria. Moreover, we show that the
day-to-day behavior also converges to Nash with rate $O(c^{-t})$ for some
game-dependent constant $c>0$.


  We present a study of the physical plasma parameters such as electron
temperature, electron density, column depth and filling factors in the moss
regions and their variability over a short (an hour) and a long period (5
consecutive days) of time. Primarily, we have analyzed the spectroscopic
observations recorded by the Extreme-ultraviolet Imaging Spectrometer (EIS)
aboard Hinode. In addition we have used supplementary observations taken from
TRACE and the X-Ray Telescope (XRT). We find that the moss emission is
strongest in the Fe xii and Fe xiii lines. Based on analyses using line ratios
and emission measure we found that the moss region has a characteristic
temperature of log T = 6.2. The electron densities measured at different
locations in the moss regions using Fe xii ratios are about 1-3\times1010
cm(-3) and about 2-4\times10^9 cm^(-3) using Fe xiii and Fe xiv. The electron
density substantially increases (by a factor of about 3-4 or even more in some
cases) when a background subtraction was performed. The density and temperature
show very small variation over time. The filling factor of the moss plasma can
vary between 0.1-1 and the path length along which the emission originates is
from a few 100 to a few 1000 kms long. By combining the observations recorded
by TRACE, EIS and XRT, we find that the moss regions correspond to the
foot-points of both hot and warm loops.


  In this paper, we discuss the U-MUSCL reconstruction scheme -- an
unstructured-grid extension of Van Leer's kappa-scheme -- proposed by Burg for
the edge-based discretization [AIAA Paper 2005-4999]. This technique has been
widely used in practical unstructured-grid fluid-dynamics solvers but with
confusions: e.g., third-order accuracy with kappa=1/2 or kappa=1/3. This paper
clarifies some of these confusions: e.g., the U-MUSCL scheme can be third-order
accurate in the point-valued solution with kappa=1/3 on regular grids for
linear equations in all dimensions, it can be third-order accurate with
kappa=1/2 as the QUICK scheme in one dimension. It is shown that the U-MUSCL
scheme cannot be third-order accurate for nonlinear equations, except a very
special case of kappa=1/2 on regular simplex-element grids, but it can be an
accurate low-dissipation second-order scheme. It is also shown that U-MUSCL
extrapolates a quadratic function exactly with kappa=1/2 on arbitrary grids
provided the gradient is computed by a quadratic least-squares method. Two
techniques are discussed, which transform the U-MUSCL scheme into being
genuinely third-order accurate on a regular grid: an efficient
flux-reconstruction method and a special source term quadrature formula for
kappa=1/2.


  The first heavy fermion superconductor CeCu$_2$Si$_2$ has not revealed all
its striking mysteries yet. At high pressures, superconductivity is supposed to
be mediated by valence fluctuations, in contrast to ambient pressure, where
spin fluctuations most likely act as pairing glue. We have carried out a
multiprobe (electric transport, thermopower, ac specific heat, Hall and Nernst
effects) experiment up to $7 \text{GPa}$ on a high quality CeCu$_2$Si$_2$
single crystal. Reliable resistivity data reveal for the first time a scaling
behavior close to the supposed valence transition, and allow to locate the
critical end point at $4.5\pm0.2 \text{GPa}$ and a slightly negative
temperature. In the same pressure region, remarkable features have also been
detected in the other physical properties, acting as further signatures of the
Ce valence crossover and the associated critical fluctuations.


  [abridged] We describe the first results from the NOAO Outer Limits Survey.
The survey consists of deep images of 55 0.6x0.6 degree fields at distances up
to 20 degrees from the LMC/SMC, and 10 controls. The fields probe the outer
structure of the Clouds, the Magellanic Stream, the Leading Arm, and the wake
of the new LMC orbit. Images were taken in 5 filters on the CTIO Blanco 4-m and
Mosaic2 camera, with calibration at the CTIO 0.9-m. The CRI images reach depths
below the oldest LMC/SMC main sequence (MS) turnoffs, yielding probes of
structure combined with ability to measure stellar ages and metallicities. M
and DDO51 images allow for discrimination of LMC and SMC giant stars from
foreground dwarfs, allowing us to use giants as additional probes. From
photometry of 8 fields at radii of 7-19 degrees N of the LMC bar, we find MS
stars associated with the LMC to 16 degrees from the LMC center, while the much
rarer giants can only be convincingly detected out to 11 degrees. In one
control field, we see the signature of the Milky Way globular cluster NGC 1851.
The CMDs show that while at 7-degree radius LMC populations as young as 500 Myr
are present, at radii more than 11 degrees only the underlying old metal-poor
population remains, demonstrating the existence of a population gradient. Even
at extreme distances, the dominant age is much less than "globular Cluster
age." MS star counts follow an exponential decline with a scale length of 1.15
kpc, essentially the same scale length as gleaned for the inner LMC disk from
prior studies. While we cannot rule out tidal structure elsewhere, detection of
ordered structure to 12 disk scale lengths is unprecedented, and adds to the
puzzle of the LMC's interaction history. Our results do not rule out the
possible existence of an LMC stellar halo, which may only dominate the disk at
yet larger radii.


  Spatiotemporal data mining (STDM) discovers useful patterns from the dynamic
interplay between space and time. Several available surveys capture STDM
advances and report a wealth of important progress in this field. However, STDM
challenges and problems are not thoroughly discussed and presented in articles
of their own. We attempt to fill this gap by providing a comprehensive
literature survey on state-of-the-art advances in STDM. We describe the
challenging issues and their causes and open gaps of multiple STDM directions
and aspects. Specifically, we investigate the challenging issues in regards to
spatiotemporal relationships, interdisciplinarity, discretisation, and data
characteristics. Moreover, we discuss the limitations in the literature and
open research problems related to spatiotemporal data representations,
modelling and visualisation, and comprehensiveness of approaches. We explain
issues related to STDM tasks of classification, clustering, hotspot detection,
association and pattern mining, outlier detection, visualisation, visual
analytics, and computer vision tasks. We also highlight STDM issues related to
multiple applications including crime and public safety, traffic and
transportation, earth and environment monitoring, epidemiology, social media,
and Internet of Things.