  Band split of solar type II radio bursts, discovered several decades ago, is
a fascinating phenomenon with the type-II lanes exhibiting two almost-parallel
sub-bands with similar morphology. The underlying split mechanism remains
elusive. One popular interpretation is that the splitting bands are emitted
from the shock upstream and downstream, respectively, with their frequency
ratio ({\gamma}) determined by the shock compression ratio. This interpretation
has been taken as the physical basis for many published references. Here we
report an observational analysis of type II events with nice split selected
from the ground-based RSTN data from 2001 to 2014, in the metric-decametric
wavelength. We investigate the temporal variation and distribution of {\gamma},
and conduct correlation analyses on the deduced spectral values. It is found
that {\gamma} varies in a very narrow range with >80% of {\gamma} (one-minute
averaged data) being between 1.15 to 1.25. For some well-observed and
long-lasting events, {\gamma} does not show a systematic variation trend within
observational uncertainties, from the onset to the termination of the splits.
In addition, the parameters representing the propagation speed of the radio
source (presumably the coronal shock) show a very weak or basically no
correlation with {\gamma}. We suggest that these results do not favor the
upstreamdownstream scenario of band splits.


  Despite interest in communicating ethical problems and social contexts within
the undergraduate curriculum to advance Public Interest Technology (PIT) goals,
interventions at the graduate level remain largely unexplored. This may be due
to the conflicting ways through which distinct Artificial Intelligence (AI)
research tracks conceive of their interface with social contexts. In this paper
we track the historical emergence of sociotechnical inquiry in three distinct
subfields of AI research: AI Safety, Fair Machine Learning (Fair ML) and
Human-in-the-Loop (HIL) Autonomy. We show that for each subfield, perceptions
of PIT stem from the particular dangers faced by past integration of technical
systems within a normative social order. We further interrogate how these
histories dictate the response of each subfield to conceptual traps, as defined
in the Science and Technology Studies literature. Finally, through a
comparative analysis of these currently siloed fields, we present a roadmap for
a unified approach to sociotechnical graduate pedagogy in AI.


  Non-uniform grids and mesh adaptation have been a growing part of numerical
simulation over the past years. It has been experimentally noted that mesh
adaptation leads not only to locally improved solution but also to numerical
stability of the underlying method. There have been though only few results on
the mathematical analysis of these schemes due to the lack of proper tools that
incorporate both the time evolution and the mesh adaptation step of the overall
algorithm.
  In this paper we provide a method to perform the analysis of the mesh
adaptation method, including both the mesh reconstruction and evolution of the
solution. We moreover employ this method to extract sufficient conditions -on
the adaptation of the mesh- that stabilize a numerical scheme in the sense of
the entropy dissipation.


  Minimal rank-metric codes or, equivalently, linear cutting blocking sets are
characterized in terms of the second generalized rank weight, via their
connection with evasiveness properties of the associated $q$-system. Using this
result, we provide the first construction of a family of
$\mathbb{F}_{q^m}$-linear MRD codes of length $2m$ that are not obtained as a
direct sum of two smaller MRD codes. In addition, such a family has better
parameters, since its codes possess generalized rank weights strictly larger
than those of the previously known MRD codes. This shows that not all the MRD
codes have the same generalized rank weights, in contrast to what happens in
the Hamming metric setting.


  The independence of the dynamic conductivity of intrinsic graphene of
frequency takes its origin in the compensation of the vanishing density of
states by the diverging matrix element of the corresponding interband
transition. The applicability of the linear response approach, however, breaks
down when this matrix element becomes comparable with the inverse electron
lifetime. We show that the physics of the ac conductivity in this regime is
determined by Rabi oscillations and obtain it beyond the first order
perturbation theory. Under strong applied electric fields the induced current
eventually saturates at a value determined by the frequency and the lifetime.
We also calculate the electromagnetic response of a graphene sheet and find
that the optical transparency is increased by the non-linear effects and make
experimental predictions.


  For an expensive to evaluate computer simulator, even the estimate of the
overall surface can be a challenging problem. In this paper, we focus on the
estimation of the inverse solution, i.e., to find the set(s) of input
combinations of the simulator that generates (or gives good approximation of) a
pre-determined simulator output. Ranjan et al. (2008) proposed an expected
improvement criterion under a sequential design framework for the inverse
problem with a scalar valued simulator. In this paper, we focus on the inverse
problem for a time-series valued simulator. We have used a few simulated and
two real examples for performance comparison.


  We explore three versions of the Laplacian coflow of $G_2$-structures on
circle fibrations over Calabi--Yau 3-folds, interpreting their dimensional
reductions to the K\"ahler geometry of the base. Precisely, we reduce Ans\"atze
for the Laplacian coflow, modified or not by de Turck's trick, both on trivial
products $CY^3\times S^1$ and on contact Calabi--Yau 7-manifolds, obtaining in
each case a natural modification of the K\"ahler--Ricci flow.


  The Rosenblatt process is a self-similar non-Gaussian process which lives in
second Wiener chaos, and occurs as the limit of correlated random sequences in
so-called \textquotedblleft non-central limit theorems\textquotedblright. It
shares the same covariance as fractional Brownian motion. We study the
asymptotic distribution of the quadratic variations of the Rosenblatt process
based on long filters, including filters based on high-order finite-difference
and wavelet-based schemes. We find exact formulas for the limiting
distributions, which we then use to devise strongly consistent estimators of
the self-similarity parameter $H$. Unlike the case of fractional Brownian
motion, no matter now high the filter orders are, the estimators are never
asymptotically normal, converging instead in the mean square to the observed
value of the Rosenblatt process at time 1.


  We study integrals over Hermitian supermatrices of arbitrary size $p+q$, that
are parametrized by an external field $X$ and a source $Y$, of respective size
$m+n$ and $p+q$. We show that these integrals exhibit a simple topological
expansion in powers of a formal parameter $\hbar$, which can be identified with
$1/(p-q)$. The loop equation and the associated spectral curve are also
obtained. The solutions to the loop equation are given in terms of the
symplectic invariants introduced in arXiv:math-ph/0702045. The symmetry
property of the latter objects allows us to prove a duality that relates
supermatrix models in which the role of $X$ and $Y$ are interchanged.


  A ``large'' AdS black hole can attain equilibrium with its own Hawking
radiation, and in that condition it is thought to be dual to a strongly coupled
field theory, also at equilibrium. But the interior of the black hole is by no
means static: the geometry of spatial sections lying inside the event horizon
evolves at some rate. This prompts the obvious question: can this rate possibly
have a holographic dual? We present circumstantial evidence that such a dual
does exist. We do this by making concrete proposals for two objects: first, a
rough measure (already suggested in the literature) of the rate at which the
unitary evolution of the state vector describing equilibrated strongly coupled
matter evolves; and, second, a rough measure of the rate at which the interior
(just under the horizon) evolves (in the case of the AdS$_5$-Kerr black hole).
We then study how these two very different objects change as two physical
parameters describing the exterior of the bulk black hole (the specific angular
momentum and the temperature) are varied. We find that they change in
remarkably similar ways, as holographic duals should.


  Bipartite graphs are often found to represent the connectivity between the
components of many systems such as ecosystems. A bipartite graph is a set of
$n$ nodes that is decomposed into two disjoint subsets, having $m$ and $n-m$
vertices each, such that there are no adjacent vertices within the same set.
The connectivity between both sets, which is the relevant quantity in terms of
connections, can be quantified by a parameter $\alpha\in[0,1]$ that equals the
ratio of existent adjacent pairs over the total number of possible adjacent
pairs. Here, we study the spectral and localization properties of such random
bipartite graphs. Specifically, within a Random Matrix Theory (RMT) approach,
we identify a scaling parameter $\xi\equiv\xi(n,m,\alpha)$ that fixes the
localization properties of the eigenvectors of the adjacency matrices of random
bipartite graphs. We also show that, when $\xi<1/10$ ($\xi>10$) the
eigenvectors are localized (extended), whereas the
localization--to--delocalization transition occurs in the interval
$1/10<\xi<10$. Finally, given the potential applications of our findings, we
round off the study by demonstrating that for fixed $\xi$, the spectral
properties of our graph model are also universal.


  In this short note, it is shown that there is a gap in the proof of Theorem
11 in the paper of Meyer and Neutsch (J. of Algebra, 1993). We prove,
nevertheless, that the statement of the theorem is true and fix the proof by
using a certain extremal property of idempotents which has an independent
interest.


  Steady forcing at the wall of a channel flow is studied via DNS to assess its
ability of yielding reductions of turbulent friction drag. The wall forcing
consists of a stationary distribution of spanwise velocity that alternates in
the streamwise direction. The idea behind the forcing builds upon the existing
technique of the spanwise wall oscillation, and exploits the convective nature
of the flow to achieve an unsteady interaction with turbulence.
  The analysis takes advantage of the equivalent laminar flow, that is solved
analytically to show that the energetic cost of the forcing is unaffected by
turbulence. In a turbulent flow, the alternate forcing is found to behave
similarly to the oscillating wall; in particular an optimal wavelength is found
that yields a maximal reduction of turbulent drag. The energetic performance is
significantly improved, with more than 50% of maximum friction saving at large
intensities of the forcing, and a net energetic saving of 23% for smaller
intensities.
  Such a steady, wall-based forcing may pave the way to passively interacting
with the turbulent flow to achieve drag reduction through a suitable
distribution of roughness, designed to excite a selected streamwise wavelength.


  We study a statistical model describing the steady state distribution of the
fluxes in a metabolic network. The resulting model on continuous variables can
be solved by the cavity method. In particular analytical tractability is
possible solving the cavity equation over an ensemble of networks with the same
degree distribution of the real metabolic network. The flux distribution that
optimizes production of biomass has a fat tail with a power-law exponent
independent on the structural properties of the underling network. These
results are in complete agreement with the Flux-Balance-Analysis outcome of the
same system and in qualitative agreement with the experimental results.


  We present a stochastic description of multiple scattering of polarized waves
in the regime of forward scattering. In this regime, if the source is
polarized, polarization survives along a few transport mean free paths, making
it possible to measure an outgoing polarization distribution. We solve the
direct problem using compound Poisson processes on the rotation group SO(3) and
non-commutative harmonic analysis. The obtained solution generalizes previous
works in multiple scattering theory and is used to design an algorithm solving
the inverse problem of estimating the scattering properties of the medium from
the observations. This technique applies to thin disordered layers, spatially
fluctuating media and multiple scattering systems and is based on the
polarization but not on the signal amplitude. We suggest that it can be used as
a non invasive testing method.


  The COVID-19 pandemic and the mitigation policies implemented in response to
it have resulted in economic losses worldwide. Attempts to understand the
relationship between economics and epidemiology has lead to a new generation of
integrated mathematical models. The data needs for these models transcend those
of the individual fields, especially where human interaction patterns are
closely linked with economic activity. In this article, we reflect upon
modelling efforts to date, discussing the data needs that they have identified,
both for understanding the consequences of the pandemic and policy responses to
it through analysis of historic data and for the further development of this
new and exciting interdisciplinary field.


  We present a simple way of generating the infinite set of Jacobi tensors,
compatible with a given one, via the "gauge transformations" of the functions
on Jacobi manifold. We consider also some applications of this result to the
construction of bi-Hamiltonian systems on Jacobi manifolds.


  We consider twisted zeta series of several variables associated to
polynomials of several variables. Thanks to a totally new method (exchange
lemma) we calculate the values at vectors formed of negative integers.After
transformation of the formula we obtained, we make p-adic interpolation.
  -----
  Nous considerons des series zetas multivariables associees a des polynomes de
plusieurs variables. Grace a une methode totalement nouvelle (dite du lemme
d'echange) nous calculons les valeurs aux T-uplets d'entiers negatifs. Apres
transformation des formules ainsi obtenues nous faisons l'interpolation
p-adique.


  Using aritmethic conditions on affine semigroups we prove that for a
simplicial toric variety of codimension 2 the property of being a set-theoretic
complete intersection on binomials in characteristic $p$ holds either for all
primes $p$, or for no prime $p$, or for exactly one prime $p$.


  We describe a natural inhomogeneous generalization of high frequency plane
gravitational waves. The waves are high frequency waves of the Kundt type whose
null propagation direction in space-time has vanishing expansion, twist and
shear but is not covariantly constant. The introduction of a cosmological
constant is discussed in some detail and a comparison is made with high
frequency gravity waves having wave fronts homeomorphic to 2-spheres.


  The majority of work in targeted sentiment analysis has concentrated on
finding better methods to improve the overall results. Within this paper we
show that these models are not robust to linguistic phenomena, specifically
negation and speculation. In this paper, we propose a multi-task learning
method to incorporate information from syntactic and semantic auxiliary tasks,
including negation and speculation scope detection, to create English-language
models that are more robust to these phenomena. Further we create two challenge
datasets to evaluate model performance on negated and speculative samples. We
find that multi-task models and transfer learning via language modelling can
improve performance on these challenge datasets, but the overall performances
indicate that there is still much room for improvement. We release both the
datasets and the source code at
https://github.com/jerbarnes/multitask_negation_for_targeted_sentiment.


  The hypothesis that cold dark matter consists of primordial superheavy
particles, the decay of short lifetime component of which led to the observable
mass of matter while long living component survived up to modern times
manifesting its presence in high energetic cosmic rays particles is
investigated.


  In this paper, we generalize a recent work of Liu et al. from the open unit
ball $\mathbb B^n$ to more general bounded strongly pseudoconvex domains with
$C^2$ boundary. It turns out that part of the main result in this paper is in
some certain sense just a part of results in a work of Bracci and Zaitsev.
However, the proofs are significantly different: the argument in this paper
involves a simple growth estimate for the Carath\'eodory metric near the
boundary of $C^2$ domains and the well-known Graham's estimate on the boundary
behavior of the Carath\'eodory metric on strongly pseudoconvex domains, while
Bracci and Zaitsev use other arguments.


  We present PyMerger, a Python tool for detecting binary black hole (BBH)
mergers from the Einstein Telescope (ET), based on a Deep Residual Neural
Network model (ResNet). ResNet was trained on data combined from all three
proposed sub-detectors of ET (TSDCD) to detect BBH mergers. Five different
lower frequency cutoffs ($F_{\text{low}}$): 5 Hz, 10 Hz, 15 Hz, 20 Hz, and 30
Hz, with match-filter Signal-to-Noise Ratio ($MSNR$) ranges: 4-5, 5-6, 6-7,
7-8, and >8, were employed in the data simulation. Compared to previous work
that utilized data from single sub-detector data (SSDD), the detection accuracy
from TSDCD has shown substantial improvements, increasing from $60\%$,
$60.5\%$, $84.5\%$, $94.5\%$ to $78.5\%$, $84\%$, $99.5\%$, $100\%$, and
$100\%$ for sources with $MSNR$ of 4-5, 5-6, 6-7, 7-8, and >8, respectively.
The ResNet model was evaluated on the first Einstein Telescope mock Data
Challenge (ET-MDC1) dataset, where the model demonstrated strong performance in
detecting BBH mergers, identifying 5,566 out of 6,578 BBH events, with optimal
SNR starting from 1.2, and a minimum and maximum $D_{L}$ of 0.5 Gpc and 148.95
Gpc, respectively. Despite being trained only on BBH mergers without
overlapping sources, the model achieved high BBH detection rates. Notably, even
though the model was not trained on BNS and BHNS mergers, it successfully
detected 11,477 BNS and 323 BHNS mergers in ET-MDC1, with optimal SNR starting
from 0.2 and 1, respectively, indicating its potential for broader
applicability.


  We have assembled the historical variability data of Mrk 421 at radio 15 GHz,
X-ray and gamma-ray bands, spanning about 6.3, 10.3 and 7.5 yr, respective- ly.
We analyzed the variability by using three methods. The results indicated that
there is a period of 287.6 +- 4.4 days for 15 GHz, 309.5 +- 5.8 days for X- ray
and 283.4+- 4.7 days for gamma-ray, respectively. This period can be reasonably
explained by the nonballistic helical motion of the emitting material. The cor-
relation analysis suggested that the variabilities of radio 15 GHz, X-ray and
0-ray are remarkable correlated, and the emission of radio 15 GHz lags behind
that of X-ray, and the X-ray flux lags behind the gamma-ray. This suggests that
the gamma-ray derives from inverse Compton (IC) scattering of the synchrotron
photons, supporting the synchrotron self-Compton (SSC) model. Moreover, the
time delay between different wavebands could be explained by the shock-in-jet
models, in which a moving emission region produces the radio to gamma-ray
activity, implying that the emission region of gamma-ray is closer to the
center than ones of X-ray and radio emission.


  We study quantitative versions of the Schur property and weak sequential
completeness, proceeding thus with investigations started by G. Godefroy, N.
Kalton and D. Li and continued by H. Pfitzner and the authors. We show that the
Schur property of $\ell_1$ holds quantitatively in the strongest possible way
and construct an example of a Banach space which is quantitatively weakly
sequentially complete, has the Schur property but fails the quantitative form
of the Schur property.


  The field of algorithmic self-assembly is concerned with the computational
and expressive power of nanoscale self-assembling molecular systems. In the
well-studied cooperative, or temperature 2, abstract tile assembly model it is
known that there is a tile set to simulate any Turing machine and an
intrinsically universal tile set that simulates the shapes and dynamics of any
instance of the model, up to spatial rescaling. It has been an open question as
to whether the seemingly simpler noncooperative, or temperature 1, model is
capable of such behaviour. Here we show that this is not the case, by showing
that there is no tile set in the noncooperative model that is intrinsically
universal, nor one capable of time-bounded Turing machine simulation within a
bounded region of the plane.
  Although the noncooperative model intuitively seems to lack the complexity
and power of the cooperative model it was not obvious how to prove this. One
reason is that there have been few tools to analyse the structure of
complicated paths in the plane. This paper provides a number of such tools. A
second reason is that almost every obvious and small generalisation to the
model (e.g. allowing error, 3D, non-square tiles, signals/wires on tiles, tiles
that repel each other, parallel synchronous growth) endows it with great
computational, and sometimes simulation, power. Our main results show that all
of these generalisations provably increase computational and/or simulation
power. Our results hold for both deterministic and nondeterministic
noncooperative systems. Our first main result stands in stark contrast with the
fact that for both the cooperative tile assembly model, and for 3D
noncooperative tile assembly, there are respective intrinsically universal
tilesets. Our second main result gives a new technique (reduction to
simulation) for proving negative results about computation in tile assembly.


  Approximate Bayesian inference methods provide a powerful suite of tools for
finding approximations to intractable posterior distributions. However, machine
learning applications typically involve selecting actions, which -- in a
Bayesian setting -- depend on the posterior distribution only via its
contribution to expected utility. A growing body of work on loss-calibrated
approximate inference methods has therefore sought to develop posterior
approximations sensitive to the influence of the utility function. Here we
introduce loss-calibrated expectation propagation (Loss-EP), a loss-calibrated
variant of expectation propagation. This method resembles standard EP with an
additional factor that "tilts" the posterior towards higher-utility decisions.
We show applications to Gaussian process classification under binary utility
functions with asymmetric penalties on False Negative and False Positive
errors, and show how this asymmetry can have dramatic consequences on what
information is "useful" to capture in an approximation.


  We investigate the far-infrared (IR) dust emission for 20 local star forming
galaxies from the Key Insights on Nearby Galaxies: A Far-IR Survey with
Herschel (KINGFISH) sample. We model the far-IR/submillimeter spectral energy
distribution (SED) using images from Spitzer Space Telescope and Herschel Space
Observatory. We calculate the cold dust temperature (T(cold)) and emissivity
(beta) on a pixel by pixel basis (where each pixel ranges from 0.1-3 kpc^2)
using a two temperature modified blackbody fitting routine. Our fitting method
allows us to investigate the resolved nature of temperature and emissivity
variations by modeling from the galaxy centers to the outskirts (physical
scales of ~15-50 kpc, depending on the size of the galaxy). We fit each SED in
two ways: (1) fit T(cold) and beta simultaneously, (2) hold beta constant and
fit T(cold). We compare T(cold) and beta with star formation rates (calculated
from L(Halpha) and L(24)), the luminosity of the old stellar population (traced
through L(3.6), and the dust mass surface density (traced by 500 micron
luminosity, L(500)). We find a significant trend between SFR/L(500) and
T(cold), implying that the flux of hard UV photons relative to the amount of
dust is significantly contributing to the heating of the cold, or diffuse, dust
component. We also see a trend between L(3.6)/L(500) and beta, indicating that
the old stellar population contributes to the heating at far-IR/submillimeter
wavelengths. Finally, we find that when beta is held constant, T(cold) exhibits
a strongly decreasing radial trend, illustrating that the shape of the far-IR
SED is changing radially through a galaxy, thus confirming on a sample almost
double in size the trends observed in Galametz et al. (2012).


  We have measured the elemental abundances of 68 Galactic and Magellanic
Cepheids from FEROS and UVES high-resolution and high signal-to-noise spectra
in order to establish the influence of the chemical composition on the
properties of these stars (see Romaniello et al. 2005). Here we describe the
robust analytical procedure we have developed to accurately determine them. The
resulting iron abundances span a range between ~ -0.80 dex for stars in the
Small Magellanic Cloud and ~ +0.20 dex for the most metal-rich ones in the
Galaxy. While the average values for each galaxy are in good agreement with
non-pulsating stars of similar age, Cepheids display a significant spread. Thus
it is fundamental to measure the metallicity of individual stars.


  I present the recent electroweak measurements related to single W, Z boson
and diboson productions from the CDF and D0 experiments at the Fermilab
Tevatron collider.


  With the development of depth sensors in recent years, RGBD object tracking
has received significant attention. Compared with the traditional RGB object
tracking, the addition of the depth modality can effectively solve the target
and background interference. However, some existing RGBD trackers use the two
modalities separately and thus some particularly useful shared information
between them is ignored. On the other hand, some methods attempt to fuse the
two modalities by treating them equally, resulting in the missing of
modality-specific features. To tackle these limitations, we propose a novel
Dual-fused Modality-aware Tracker (termed DMTracker) which aims to learn
informative and discriminative representations of the target objects for robust
RGBD tracking. The first fusion module focuses on extracting the shared
information between modalities based on cross-modal attention. The second aims
at integrating the RGB-specific and depth-specific information to enhance the
fused features. By fusing both the modality-shared and modality-specific
information in a modality-aware scheme, our DMTracker can learn discriminative
representations in complex tracking scenes. Experiments show that our proposed
tracker achieves very promising results on challenging RGBD benchmarks.


  The method of neural radiance fields (NeRF) has been developed in recent
years, and this technology has promising applications for synthesizing novel
views of complex scenes. However, NeRF requires dense input views, typically
numbering in the hundreds, for generating high-quality images. With a decrease
in the number of input views, the rendering quality of NeRF for unseen
viewpoints tends to degenerate drastically. To overcome this challenge, we
propose pseudo-view augmentation of NeRF, a scheme that expands a sufficient
amount of data by considering the geometry of few-shot inputs. We first
initialized the NeRF network by leveraging the expanded pseudo-views, which
efficiently minimizes uncertainty when rendering unseen views. Subsequently, we
fine-tuned the network by utilizing sparse-view inputs containing precise
geometry and color information. Through experiments under various settings, we
verified that our model faithfully synthesizes novel-view images of superior
quality and outperforms existing methods for multi-view datasets.


  We discuss the case of simultaneous mixing of gauge bosons and mixing of
fermions in a model independent way and for a variety of extra-fermion
representations.
  In this context we analyze a class of lepton family violating processes,
namely Z --> e tau, Z --> mu tau, Z --> e mu, mu --> e e e, tau --> e e e, tau
--> mu mu mu, tau --> e mu mu and tau --> mu e e in the presence of one extra
neutral gauge boson, Z', with universal, non-universal or family changing
couplings.
  We derive bounds on the combined effect of Z-Z' mixing and ordinary--exotic
lepton mixing.


  The detailed knowledge of plasma heating and acceleration region properties
presents a major observational challenge in solar flare physics. Using the
Ramaty High Energy Solar Spectroscopic Imager (RHESSI), the high temperature
differential emission measure, DEM(T), and the energy-dependent spatial
structure of solar flare coronal sources are studied quantitatively. The
altitude of the coronal X-ray source is observed to increase with energy by
~+0.2 arcsec/keV between 10 and 25 keV. Although an isothermal model can fit
the thermal X-ray spectrum observed by RHESSI, such a model cannot account for
the changes in altitude, and multi-thermal coronal sources are required where
the temperature increases with altitude. For the first time, we show how RHESSI
imaging information can be used to constrain the DEM(T) of a flaring plasma. We
develop a thermal bremsstrahlung X-ray emission model with inhomogeneous
temperature and density distributions to simultaneously reproduce: i) DEM(T),
ii) altitude as a function of energy, and iii) vertical extent of the flaring
coronal source versus energy. We find that the temperature-altitude gradient in
the region is ~+0.08 keV/arcsec (~1.3 MK/Mm). Similar altitude-energy trends in
other flares suggest that the majority of coronal X-ray sources are
multi-thermal and have strong vertical temperature and density gradients with a
broad DEM(T).


  We extend to arbitrary commutative base rings a recent result of Demeneghi
that every ideal of an ample groupoid algebra over a field is an intersection
of kernels of induced representations from isotropy groups, with a much shorter
proof, by using the author's Disintegration Theorem for groupoid
representations. We also prove that every primitive ideal is the kernel of an
induced representation from an isotropy group; however, we are unable to show,
in general, that it is the kernel of an irreducible induced representation. If
each isotropy group is finite (e.g., if the groupoid is principal) and if the
base ring is Artinian (e.g., a field), then we can show that every primitive
ideal is the kernel of an irreducible representation induced from isotropy.


  We present an exact dynamical solution of a spherical version of the batch
minority game (MG) with random external information. The control parameters in
this model are the ratio of the number of possible values for the public
information over the number of agents, and the radius of the spherical
constraint on the microscopic degrees of freedom. We find a phase diagram with
three phases: two without anomalous response (an oscillating versus a frozen
state), and a further frozen phase with divergent integrated response. In
contrast to standard MG versions, we can also calculate the volatility exactly.
Our study reveals similarities between the spherical and the conventional MG,
but also intriguing differences. Numerical simulations confirm our analytical
results.


  We study the potential effects of spacetime non-metricity in cosmology. In
the spirit of Einstein-Cartan gravity, but with non-metricity replacing
torsion, we consider the Einstein-Hilbert action and assume zero torsion.
Adopting certain hyperfluid models, with non-vanishing hypermomentum that can
source spacetime non-metricity, we add a matter component into the action and
derive the field equations, along with the conservation laws. Applying our
formulae to cosmology, we generalize the Friedmann and the Raychaudhuri
equations in the presence of non-metricity. Our results show that, in a number
of cases, non-metricity can mimic the effects of matter with unconventional
equation of state. For instance, specific types of hypermomentum are found to
act as an effective stiff fluid, thus opening the possibility that
non-metricity could have played a significant role in the early stages of the
universe's evolution. Alternative forms of hypermomentum can dominate the
universal dynamics at late times. In either case, the equilibrium moment
depends on the initial conditions and it is determined by a simple relation
between the matter component and the hyperfluid.


  We present multi-wavelength observations of two gap transients followed by
the Carnegie Supernova Project-II and supplemented with data obtained by a
number of different programs. Here in the first of two papers, we focus on the
intermediate luminosity red transient (ILRT) designated SNhunt120, while in a
companion paper we examine the luminous red novae AT 2014ej. Our data set for
SNhunt120 consists of an early optical discovery, estimated to be within 3 days
after outburst, the subsequent optical and near-infrared broadband followup
extending over a $\sim$2 month period, two visual- and two near-infrared
wavelength spectra, and Spitzer Space Telescope observations extending from
early ($+$28 d) to late ($+$1155 d) phases. SNhunt120 resembles other ILRTs
such as NGC 300-2008-OT and SN 2008S, and like these other ILRTs, SNhunt120
exhibits prevalent mid-infrared emission at both early and late phases. From
the comparison of SNhunt120 and other ILRTs to electron-capture supernova
simulations, we find that the current models underestimate the explosion
kinetic energy and thereby produce synthetic light curves that over-estimate
the luminosity. Finally, examination of pre-outburst Hubble Space Telescope
images yields no progenitor detection.


  Some frustrated pyrochlore antiferromagnets, such as Y2Mo2O7, show a
spin-freezing transition and magnetic irreversibilities below a temperature Tf
similar to what is observed nonlinear magnetization measurements on Y2Mo2O7
that provide strong evidence that there is an underlying thermodynamic phase
transition at Tf, which is characterized by critical exponents \gamma \approx
2.8 and \beta \approx 0.8. These values are typical of those found in random
spin glasses, despite the fact that the level of random disorder in Y2Mo2O7 is
immeasurably small.


  We compile observations of early-type binaries identified via spectroscopy,
eclipses, long-baseline interferometry, adaptive optics, common proper motion,
etc. Each observational technique is sensitive to companions across a narrow
parameter space of orbital periods P and mass ratios q = M_comp/M_1. After
combining the samples from the various surveys and correcting for their
respective selection effects, we find the properties of companions to O-type
and B-type main-sequence (MS) stars differ among three regimes. First, at short
orbital periods P < 20 days (separations a < 0.4 AU), the binaries have small
eccentricities e < 0.4, favor modest mass ratios <q> = 0.5, and exhibit a small
excess of twins q > 0.95. Second, the companion frequency peaks at intermediate
periods log P (days) = 3.5 (a = 10 AU), where the binaries have mass ratios
weighted toward small values q = 0.2-0.3 and follow a Maxwellian "thermal"
eccentricity distribution. Finally, companions with long orbital periods log P
(days) = 5.5-7.5 (a = 200-5,000 AU) are outer tertiary components in
hierarchical triples, and have a mass ratio distribution across q = 0.1-1.0
that is nearly consistent with random pairings drawn from the initial mass
function. We discuss these companion distributions and properties in the
context of binary star formation and evolution. We also reanalyze the binary
statistics of solar-type MS primaries, taking into account that (30+/-10)% of
single-lined spectroscopic binaries likely contain white dwarf companions
instead of low-mass stellar secondaries. The mean frequency of stellar
companions with q > 0.1 and log P (days) < 8.0 per primary increases from
0.50+/-0.04 for solar-type MS primaries to 2.1+/-0.3 for O-type MS primaries.
We fit joint probability density functions f(M_1,q,P,e) to the corrected
distributions, which can be incorporated into binary population synthesis
studies.


  We consider the problem of computing an equilibrium in a class of
\textit{nonlinear generalized Nash equilibrium problems (NGNEPs)} in which the
strategy sets for each player are defined by equality and inequality
constraints that may depend on the choices of rival players. While the
asymptotic global convergence and local convergence rates of algorithms to
solve this problem have been extensively investigated, the analysis of
nonasymptotic iteration complexity is still in its infancy. This paper presents
two first-order algorithms -- based on the quadratic penalty method (QPM) and
augmented Lagrangian method (ALM), respectively -- with an accelerated
mirror-prox algorithm as the solver in each inner loop. We establish a global
convergence guarantee for solving monotone and strongly monotone NGNEPs and
provide nonasymptotic complexity bounds expressed in terms of the number of
gradient evaluations. Experimental results demonstrate the efficiency of our
algorithms in practice.


  We discuss the generation of the baryon asymmetry by a strong first order
electroweak phase transition in the early universe, particularly in the context
of the MSSM. This requires a thorough numerical treatment of the bubble wall
profile in the case of two Higgs fields. CP violating complex particle masses
varying with the Higgs field in the wall are essential. Since in the MSSM there
is no indication of spontaneous CP violation around the critical temperature
(contrary to the NMSSM) we have to rely on standard explicit CP violation.
Using the WKB approximation for particles in the plasma we are led to Boltzmann
transport equations for the difference of left-handed particles and their CP
conjugates. This asymmetry is finally transformed into a baryon asymmetry by
out of equilibrium sphaleron transitions in the symmetric phase. We solve the
transport equations and find a baryon asymmetry depending mostly on the CP
violating phases and the wall velocity.


  A critical question for the field of quantum computing in the near future is
whether quantum devices without error correction can perform a well-defined
computational task beyond the capabilities of state-of-the-art classical
computers, achieving so-called quantum supremacy. We study the task of sampling
from the output distributions of (pseudo-)random quantum circuits, a natural
task for benchmarking quantum computers. Crucially, sampling this distribution
classically requires a direct numerical simulation of the circuit, with
computational cost exponential in the number of qubits. This requirement is
typical of chaotic systems. We extend previous results in computational
complexity to argue more formally that this sampling task must take exponential
time in a classical computer. We study the convergence to the chaotic regime
using extensive supercomputer simulations, modeling circuits with up to 42
qubits - the largest quantum circuits simulated to date for a computational
task that approaches quantum supremacy. We argue that while chaotic states are
extremely sensitive to errors, quantum supremacy can be achieved in the
near-term with approximately fifty superconducting qubits. We introduce cross
entropy as a useful benchmark of quantum circuits which approximates the
circuit fidelity. We show that the cross entropy can be efficiently measured
when circuit simulations are available. Beyond the classically tractable
regime, the cross entropy can be extrapolated and compared with theoretical
estimates of circuit fidelity to define a practical quantum supremacy test.


  Approximately 10 per cent of star clusters are found in pairs, known as
binary clusters. We propose a mechanism for binary cluster formation; we use
N-body simulations to show that velocity substructure in a single (even fairly
smooth) region can cause binary clusters to form. This process is highly
stochastic and it is not obvious from a region's initial conditions whether a
binary will form and, if it does, which stars will end up in which cluster. We
find the probability that a region will divide is mainly determined by its
virial ratio, and a virial ratio above 'equilibrium' is generally necessary for
binary formation. We also find that the mass ratio of the two clusters is
strongly influenced by the initial degree of spatial substructure in the
region.


  Experience replay is widely used in deep reinforcement learning algorithms
and allows agents to remember and learn from experiences from the past. In an
effort to learn more efficiently, researchers proposed prioritized experience
replay (PER) which samples important transitions more frequently. In this
paper, we propose Prioritized Sequence Experience Replay (PSER) a framework for
prioritizing sequences of experience in an attempt to both learn more
efficiently and to obtain better performance. We compare the performance of PER
and PSER sampling techniques in a tabular Q-learning environment and in DQN on
the Atari 2600 benchmark. We prove theoretically that PSER is guaranteed to
converge faster than PER and empirically show PSER substantially improves upon
PER.


  The locality of words is a relatively young structural complexity measure,
introduced by Day et al. in 2017 in order to define classes of patterns with
variables which can be matched in polynomial time. The main tool used to
compute the locality of a word is called marking sequence: an ordering of the
distinct letters occurring in the respective order. Once a marking sequence is
defined, the letters of the word are marked in steps: in the ith marking step,
all occurrences of the ith letter of the marking sequence are marked. As such,
after each marking step, the word can be seen as a sequence of blocks of marked
letters separated by blocks of non-marked letters. By keeping track of the
evolution of the marked blocks of the word through the marking defined by a
marking sequence, one defines the blocksequence of the respective marking
sequence. We first show that the words sharing the same blocksequence are only
loosely connected, so we consider the stronger notion of extended
blocksequence, which stores additional information on the form of each single
marked block. In this context, we present a series of combinatorial results for
words sharing the extended blocksequence.


  We show that asymptotically the first Betti number, or the arithmetic genus,
of a Shimura curve satisfies the Gauss--Bonnet equality. We also show that the
first Betti number of a congruence hyperbolic 3--orbifold asymptotically
vanishes relatively to hyperbolic volume.


  The proposed temporal fluctuations model attempt for a unitary vision on
gravity, electromagnetism and inertia. On obtain Newton law of gravitation and
Coulomb law by starting from simple principles. On obtain too the main results
of General Relativity Theory and Electromagnetism. One of the major points of
present work is to obtain unified potential, which allow a unitary description
of gravity and electromagnetism. As consequence, on obtain supplemental effects
responsible for conservation laws violation in certain closed systems. On
maintain the validity of conservation laws only if those systems are coupling
with vacuum. This fact can be used for energy production and/or transport. This
proposed model opening to quantum and nuclear physics, but those subjects will
be developed in a future work.
  Keywords: general relativity, gravitation, inertia, electromagnetism,
Biefild-Brown effect


  We start from the polynomic interatomic potentials introduced by Wojde{\l} et
al. [J. Phys. Condens. Matt. 25, 305401(2013)] and take advantage of one of
their key features -- namely, the linear dependence of the energy on the
potential's adjustable parameters -- to devise a scheme for the construction of
first-principles-based ({\em second-principles}) models for large-scale
lattice-dynamical simulations. Our method presents the following convenient
features. The parameters of the model are computed in a very fast and efficient
way, as it is possible to recast the fit to a training set of first-principles
data into a simple matrix diagonalization problem. Our method selects
automatically the interactions that are most relevant to reproduce the
training-set data, by choosing from a pool that includes virtually all possible
coupling terms, and produces a family of models of increasing complexity and
accuracy. We work with practical and convenient cross-validation criteria
linked to the physical properties that will be relevant in future simulations
based on the new model, and which greatly facilitate the task of identifying a
potential that is simultaneously simple (thus computationally light), very
accurate, and predictive. We also discuss practical ways to guarantee that our
energy models are bounded from below, with a minimal impact on their accuracy.
Finally, we demonstrate our scheme with an application to ferroelastic
perovskite SrTiO$_{3}$, which features many non-trivial lattice-dynamical
features (e.g., a phase transition driven by soft phonons, competing structural
instabilities, highly anharmonic dynamics) and provides a very demanding test.


  Flexible continuum manipulators are valued for minimally invasive surgery,
offering access to confined spaces through nonlinear paths. However,
cable-driven manipulators face control difficulties due to hysteresis from
cabling effects such as friction, elongation, and coupling. These effects are
difficult to model due to nonlinearity and the difficulties become even more
evident when dealing with long and coupled, multi-segmented manipulator. This
paper proposes a data-driven approach based on Deep Neural Networks (DNN) to
capture these nonlinear and previous states-dependent characteristics of cable
actuation. We collect physical joint configurations according to command joint
configurations using RGBD sensing and 7 fiducial markers to model the
hysteresis of the proposed manipulator. Result on a study comparing the
estimation performance of four DNN models show that the Temporal Convolution
Network (TCN) demonstrates the highest predictive capability. Leveraging
trained TCNs, we build a control algorithm to compensate for hysteresis.
Tracking tests in task space using unseen trajectories show that the proposed
control algorithm reduces the average position and orientation error by 61.39%
(from 13.7mm to 5.29 mm) and 64.04% (from 31.17{\deg} to 11.21{\deg}),
respectively. This result implies that the proposed calibrated controller
effectively reaches the desired configurations by estimating the hysteresis of
the manipulator. Applying this method in real surgical scenarios has the
potential to enhance control precision and improve surgical performance.


  We analyze the complexity of fitting a variety, coming from a class of
varieties, to a configuration of points in $\Bbb C^n$. The complexity measure,
called the algebraic complexity, computes the Euclidean Distance Degree
(EDdegree) of a certain variety called the hypothesis variety as the number of
points in the configuration increases. For the problem of fitting an
$(n-1)$-sphere to a configuration of $m$ points in $\Bbb C^n$, we give a closed
formula of the algebraic complexity of the hypothesis variety as $m$ grows for
the case of $n=1$. For the case $n>1$ we conjecture a generalization of this
formula supported by numerical experiments.


  We consider a layered system of fermionic molecules with permanent dipole
moments aligned by an external field. The dipole interactions between fermions
in adjacent layers are attractive and induce inter-layer pairing. Due to
competition for pairing among adjacent layers, the mean-field ground state of
the layered system is a dimerized superfluid, with pairing only between
every-other layer. We construct an effective Ising-XY lattice model that
describes the interplay between dimerization and superfluid phase fluctuations.
In addition to the dimerized superfluid ground state, and high temperature
normal state, at intermediate temperature, we find an unusual dimerized
"pseudogap" state with only short-range phase coherence. We propose light
scattering experiments to detect dimerization.


  Semantic annotations have to satisfy quality constraints to be useful for
digital libraries, which is particularly challenging on large and diverse
datasets. Confidence scores of multi-label classification methods typically
refer only to the relevance of particular subjects, disregarding indicators of
insufficient content representation at the document-level. Therefore, we
propose a novel approach that detects documents rather than concepts where
quality criteria are met. Our approach uses a deep, multi-layered regression
architecture, which comprises a variety of content-based indicators. We
evaluated multiple configurations using text collections from law and
economics, where the available content is restricted to very short texts.
Notably, we demonstrate that the proposed quality estimation technique can
determine subsets of the previously unseen data where considerable gains in
document-level recall can be achieved, while upholding precision at the same
time. Hence, the approach effectively performs a filtering that ensures high
data quality standards in operative information retrieval systems.


  An action for a massless graviton interacting with a massive tensor field is
proposed. The model is based on coupling the metric tensor to an SP(4) gauge
theory spontaneously broken to $SL(2,C)$. The symmetry breaking is achieved by
using a Higgs multiplet containing a scalar field and a vector field related by
a constraint. We show that in the non-unitary gauge and for the Fierz-Pauli
form of the mass term, the six degrees of freedom of the massive tensor are
identified with two tensor helicities, two vector helicities of the Goldstone
vector, and two scalars present in the Goldstone multiplet. The propagators of
this system are well behaved, in contrast to the system consisting of two
tensors.


  We introduce a categorical framework for the study of representations of
$G_F$, where $G$ is a reductive group, and $\bF$ is a 2-dimensional local
field, i.e. $F=K((t))$, where $K$ is a local field. Our main result says that
the space of functions on $G_F$, which is an object of a suitable category of
representations of $G_F$ with the respect to the action of $G_F$ on itself by
left translations, becomes a representation of a certain central extension of
$G_F$, when we consider the action by right translations.


  This correspondence studies the wireless powered over-the-air computation
(AirComp) for achieving sustainable wireless data aggregation (WDA) by
integrating AirComp and wireless power transfer (WPT) into a joint design. In
particular, we consider that a multi-antenna hybrid access point (HAP) employs
the transmit energy beamforming to charge multiple single-antenna low-power
wireless devices (WDs) in the downlink, and the WDs use the harvested energy to
simultaneously send their messages to the HAP for AirComp in the uplink. Under
this setup, we minimize the computation mean square error (MSE), by jointly
optimizing the transmit energy beamforming and the receive AirComp beamforming
at the HAP, as well as the transmit power at the WDs, subject to the maximum
transmit power constraint at the HAP and the wireless energy harvesting
constraints at individual WDs. To tackle the non-convex computation MSE
minimization problem, we present an efficient algorithm to find a converged
high-quality solution by using the alternating optimization technique.
Numerical results show that the proposed joint WPT-AirComp approach
significantly reduces the computation MSE, as compared to other benchmark
schemes.


  We examine the post-Newtonian limit of the minimal exponential measure (MEMe)
model presented in [J. C. Feng, S. Carloni, Phys. Rev. D 101, 064002 (2020)]
using an extension of the parameterized post-Newtonian (PPN) formalism which is
also suitable for other type-I minimally modified Gravity theories. The new PPN
expansion is then used to calculate the monopole term of the post-Newtonian
gravitational potential and to perform an analysis of circular orbits within
spherically symmetric matter distributions. The latter shows that the behavior
does not differ significantly from that of general relativity for realistic
values of the MEMe model parameter $q$. Instead the former shows that one can
use precision measurements of Newton's constant $G$ to improve the constraint
on $q$ by up to $10$ orders of magnitude.


  Designing waterfront redevelopment generally focuses on attractiveness,
leisure, and beauty, resulting in various types of building and block shapes
with limited considerations on environmental aspects. However, increasing
climate change impacts necessitate these buildings to be sustainable,
resilient, and zero CO2 emissions. By producing five scenarios (plus existing
buildings) with constant floor areas, we investigated how building and district
form with building integrated photovoltaics (BIPV) affect energy consumption
and production, self-sufficiency, CO2 emission, and energy costs in the context
of waterfront redevelopment in Tokyo. From estimated hourly electricity demands
of the buildings, techno-economic analyses are conducted for rooftop PV systems
for 2018 and 2030 with declining costs of rooftop PV systems. We found that
environmental building designs with rooftop PV system are increasingly
economical in Tokyo with CO2 emission reduction of 2-9% that depends on rooftop
sizes. Payback periods drop from 14 years in 2018 to 6 years in 2030. Toward
net-zero CO2 emissions by 2050, immediate actions are necessary to install
rooftop PVs on existing and new buildings with energy efficiency improvements
by construction industry and building owners. To facilitate such actions,
national and local governments need to adopt appropriate policies.


  We consider ideals involving the maximal minors of a polynomial matrix. For
example, those arising in the computation of the critical values of a
polynomial restricted to a variety for polynomial optimisation. Gr\"obner bases
are a classical tool for solving polynomial systems. For practical
computations, this consists of two stages. First, a Gr\"obner basis is computed
with respect to a DRL (degree reverse lexicographic) ordering. Then, a change
of ordering algorithm, such as \textsf{Sparse-FGLM}, designed by Faug\`ere and
Mou, is used to find a Gr\"obner basis of the same ideal but with respect to a
lexicographic ordering. The complexity of this latter step, in terms of
arithmetic operations, is $O(mD^2)$, where $D$ is the degree of the ideal and
$m$ is the number of non-trivial columns of a certain $D \times D$ matrix.
While asymptotic estimates are known for $m$ for generic polynomial systems,
thus far, the complexity of \textsf{Sparse-FGLM} was unknown for determinantal
systems.
  By assuming Fr\"oberg's conjecture we expand the work of Moreno-Soc\'ias by
detailing the structure of the DRL staircase in the determinantal setting. Then
we study the asymptotics of the quantity $m$ by relating it to the coefficients
of these Hilbert series. Consequently, we arrive at a new bound on the
complexity of the \textsf{Sparse-FGLM} algorithm for generic determinantal
systems and for generic critical point systems. We consider the ideal in the
polynomial ring $\mathbb{K}[x_1, \dots, x_n]$, where $\mathbb{K}$ is some
infinite field, generated by $p$ generic polynomials of degree $d$ and the
maximal minors of a $p \times (n-1)$ polynomial matrix with generic entries of
degree $d-1$. Then for the case $d=2$ and for $n \gg p$ we give an exact
formula for $m$ in terms of $n$ and $p$. Moreover, for $d \geq 3$, we give an
asymptotic formula, as $n \to \infty$, for $m$ in terms of $n,p$ and $d$.


  Path-integral for theories with degenerate vacua is investigated. The origin
of the non Borel-summability of the perturbation theory is studied. A new
prescription to deal with small coupling is proposed. It leads to a series,
which at low orders and small coupling differs from the ordinary perturbative
series by nonperturbative amount, but is Borel-summable.


  We demonstrate the use of a piezoelectric actuator to apply, at low
temperatures, uniaxial stress in the plane of a two-dimensional electron system
confined to a modulation-doped AlAs quantum well. Via the application of
stress, which can be tuned in situ and continuously, we control the energies
and occupations of the conduction-band minima and the electronic properties of
the electron system. We also report measurements of the longitudinal and
transverse strain versus bias for the actuator at 300, 77, and 4.2 K. A
pronounced hysteresis is observed at 300 and 77 K, while at 4.2 K, strain is
nearly linear and shows very little hysteresis with the applied bias.


  Acoustic echo cancellation (AEC) algorithms have a long-term steady role in
signal processing, with approaches improving the performance of applications
such as automotive hands-free systems, smart home and loudspeaker devices, or
web conference systems. Just recently, very first deep neural network
(DNN)-based approaches were proposed with a DNN for joint AEC and residual echo
suppression (RES)/noise reduction, showing significant improvements in terms of
echo suppression performance. Noise reduction algorithms, on the other hand,
have enjoyed already a lot of attention with regard to DNN approaches, with the
fully convolutional recurrent network (FCRN) architecture being among state of
the art topologies. The recently published impressive echo cancellation
performance of joint AEC/RES DNNs, however, so far came along with an
undeniable impairment of speech quality. In this work we will heal this issue
and significantly improve the near-end speech component quality over existing
approaches. Also, we propose for the first time-to the best of our knowledge-a
pure DNN AEC in the form of an echo estimator, that is based on a competitive
FCRN structure and delivers a quality useful for practical applications.


  In this report, some cosmological correlation functions are used to evaluate
the differential performance between C2075 and P100 GPU cards. In the past, the
correlation functions used in this work have been widely studied and exploited
on some previous GPU architectures. The analysis of the performance indicates
that a speedup in the range from 13 to 15 is achieved without any additional
optimization process for the P100 card.


  Using the first-principles spin density functional approach, we have studied
magnetism of a new type of all-carbon nanomaterials, i.e., the carbon nanowires
inserted into the single-walled carbon nanotubes. It is found that if the 1D
carbon nanowire density is not too higher, the ferromagnetic ground state will
be more stable than the antiferromagnetic one, which is caused by weak coupling
between the 1D carbon nanowire and the single-walled carbon nanotube. Also,
both dimerization of the carbon nanowire and carbon vacancy on the tube-wall
are found to enhance the magnetic moment of the composite.


  Let $\mathsf{MM}^{++}(\kappa)$ state that the forcing axiom
$\mathsf{MM}^{++}$ can be instantiated only for stationary set preserving
posets of size at most $\kappa$. We give a detailed account of Asper\`o and
Schindler's proof that $\mathsf{MM}^{++}(\kappa)+$there are class many Woodin
cardinals implies Woodin's axiom $(*)$ if $\Diamond_\kappa$ holds and
$\kappa>\aleph_2$. Our presentation takes advantage of the notion of
consistency property: specifically we rephrase Asper\`o and Schindler's forcing
as a specific instantiation of the notion of ``consistency property'' used by
Makkai, Keisler, Mansfield and others in the study of infinitary logics. We
also reorganize the order of presentation of the various parts of the proof.
Taken aside these variations, our account is quite close to the original proof
of Asper\`o and Schindler.


  In the last decades, the number of exotic candidates which are beyond the
conventional quark model has grown dramatically. At the same time, numerous
theoretical interpretations, such as tetraquark, hybrid, hadroquarkonium and
hadronic molecule, have been proposed to understand their nature. In principle,
all the configurations with the same quantum numbers can mix with each other.
Thus at present we aim at identifying the prominent component. As an extended
object, a hadronic molecule has some distinguishable features from other more
compact configurations. In the end, the two $Z_b$ states are used to illustrate
some features of the molecular scenario.


  Recent years have witnessed significant progress in generative models for
music, featuring diverse architectures that balance output quality, diversity,
speed, and user control. This study explores a user-friendly graphical
interface enabling the drawing of masked regions for inpainting by an Hourglass
Diffusion Transformer (HDiT) model trained on MIDI piano roll images. To
enhance note generation in specified areas, masked regions can be "repainted"
with extra noise. The non-latent HDiTs linear scaling with pixel count allows
efficient generation in pixel space, providing intuitive and interpretable
controls such as masking throughout the network and removing the need to
operate in compressed latent spaces such as those provided by pretrained
autoencoders. We demonstrate that, in addition to inpainting of melodies,
accompaniment, and continuations, the use of repainting can help increase note
density yielding musical structures closely matching user specifications such
as rising, falling, or diverging melody and/or accompaniment, even when these
lie outside the typical training data distribution. We achieve performance on
par with prior results while operating at longer context windows, with no
autoencoder, and can enable complex geometries for inpainting masks, increasing
the options for machine-assisted composers to control the generated music.


  We show that it is possible to add $\kappa^+-$Cohen subsets to $\kappa$ with
a Prikry forcing over $\kappa$. This answers a question from
\cite{HayutBenhanouGitik}. A strengthening of non-Galvin property is
introduced. It is shown to be consistent using a single measurable cardinal
which improves a previous result by S. Garti, S. Shelah, and the first author
\cite{BenhamouGartieShelah}. A situation with extender-based Prikry forcings is
examined. This relates to a question of H. Woodin.


  Machine learning requires exuberant amounts of data and computation. Also,
models require equally excessive growth in the number of parameters. It is,
therefore, sensible to look for technologies that reduce these demands on
resources. Here, we propose an approach called guided transfer learning. Each
weight and bias in the network has its own guiding parameter that indicates how
much this parameter is allowed to change while learning a new task. Guiding
parameters are learned during an initial scouting process. Guided transfer
learning can result in a reduction in resources needed to train a network. In
some applications, guided transfer learning enables the network to learn from a
small amount of data. In other cases, a network with a smaller number of
parameters can learn a task which otherwise only a larger network could learn.
Guided transfer learning potentially has many applications when the amount of
data, model size, or the availability of computational resources reach their
limits.


  This is the text of a talk to the study week on \emph{Modular forms and
Galois representations} held in Luminy, 1997. We give a survey of $p$-adic
modular forms, as developped by Serre, Katz, Hida, Wiles, Coleman and others...


  In the era of precision cosmology, establishing the correct magnitude of
statistical errors in cosmological parameters is of crucial importance.
However, widely used approximations in galaxy surveys analyses can lead to
parameter uncertainties that are grossly mis-estimated, even in a regime where
the theory is well understood (e.g., linear scales). These approximations can
be introduced at three different levels: in the form of the likelihood, in the
theoretical modelling of the observable and in the numerical computation of the
observable. Their consequences are important both in data analysis through
e.g., Markov Chain Monte Carlo parameter inference, and when survey instrument
and strategy are designed and their constraining power on cosmological
parameters is forecasted, for instance using Fisher matrix analyses. In this
work, considering the galaxy angular power spectrum as the target observable,
we report one example of approximation for each of such three categories:
neglecting off-diagonal terms in the covariance matrix, neglecting cosmic
magnification and using the Limber approximation on large scales. We show that
these commonly used approximations affect the robustness of the analysis and
lead, perhaps counter-intuitively, to unacceptably large mis-estimates of
parameters errors (from few~$10\%$ up to few~$100\%$) and correlations.
Furthermore, these approximations might even spoil the benefits of the nascent
multi-tracer and multi-messenger cosmology. Hence we recommend that the type of
analysis presented here should be repeated for every approximation adopted in
survey design or data analysis, to quantify how it may affect the results. To
this aim, we have developed \texttt{Multi\_CLASS}, a new extension of
\texttt{CLASS} that includes the angular power spectrum for multiple (galaxy
and other tracers such as gravitational waves) populations.


  Niels Bohr's arguments indicating the non-applicability of quantum
methodology to the study of the ultimate details of life given in his book
"Atomic physics and human knowledge" conflict with the commonly held opposite
view. The bases for the usual beliefs are examined and shown to have little
validity. Significant differences do exist between the living organism and the
type of system studied successfully in the physics laboratory. Dealing with
living organisms in quantum-mechanical terms with the same degree of rigour as
is normal for non-living systems would seem not to be possible without
considering also questions of the origins of life and of the universe.


  In an earlier article [arXiv:0902.0590 [hep-th], Phys. Rev D80 (2009)
025011], I discussed the potential benefits of allowing Lorentz symmetry
breaking in quantum field theories. In particular I discussed the perturbative
power-counting finiteness of the normal-ordered :P(phi)^{z>=d}_{d+1}: scalar
quantum field theories, and sketched the implications for Horava's model of
quantum gravity. In the current rather brief addendum, I will tidy up some
dangling issues and fill out some of the technical details of the argument
indicating the power-counting renormalizability of a z>=d variant of Horava
gravity in (d+1) dimensions.


  In multiagent environments, several decision-making individuals interact
while adhering to the dynamics constraints imposed by the environment. These
interactions, combined with the potential stochasticity of the agents'
decision-making processes, make such systems complex and interesting to study
from a dynamical perspective. Significant research has been conducted on
learning models for forward-direction estimation of agent behaviors, for
example, pedestrian predictions used for collision-avoidance in self-driving
cars. However, in many settings, only sporadic observations of agents may be
available in a given trajectory sequence. For instance, in football, subsets of
players may come in and out of view of broadcast video footage, while
unobserved players continue to interact off-screen. In this paper, we study the
problem of multiagent time-series imputation, where available past and future
observations of subsets of agents are used to estimate missing observations for
other agents. Our approach, called the Graph Imputer, uses forward- and
backward-information in combination with graph networks and variational
autoencoders to enable learning of a distribution of imputed trajectories. We
evaluate our approach on a dataset of football matches, using a projective
camera module to train and evaluate our model for the off-screen player state
estimation setting. We illustrate that our method outperforms several
state-of-the-art approaches, including those hand-crafted for football.


  A regression problem with dependent data is considered. Regularity
assumptions on the dependency of the data are introduced, and it is shown that
under suitable structural assumptions on the regression function a deep
recurrent neural network estimate is able to circumvent the curse of
dimensionality.


  We develop an analytic theory of strong anisotropy of the energy spectra in
the thermally-driven turbulent counterflow of superfluid He-4. The key
ingredients of the theory are the three-dimensional differential closure for
the vector of the energy flux and the anisotropy of the mutual friction force.
We suggest an approximate analytic solution of the resulting energy-rate
equation, which is fully supported by the numerical solution. The
two-dimensional energy spectrum is strongly confined in the direction of the
counterflow velocity. In agreement with the experiment, the energy spectra in
the direction orthogonal to the counterflow exhibit two scaling ranges: a
near-classical non-universal cascade-dominated range and a universal critical
regime at large wavenumbers. The theory predicts the dependence of various
details of the spectra and the transition to the universal critical regime on
the flow parameters.
  This article is a part of the theme issue 'Scaling the turbulence edifice'.


  Solving long-tail large vocabulary object detection with deep learning based
models is a challenging and demanding task, which is however under-explored.In
this work, we provide the first systematic analysis on the underperformance of
state-of-the-art models in front of long-tail distribution. We find existing
detection methods are unable to model few-shot classes when the dataset is
extremely skewed, which can result in classifier imbalance in terms of
parameter magnitude. Directly adapting long-tail classification models to
detection frameworks can not solve this problem due to the intrinsic difference
between detection and classification.In this work, we propose a novel balanced
group softmax (BAGS) module for balancing the classifiers within the detection
frameworks through group-wise training. It implicitly modulates the training
process for the head and tail classes and ensures they are both sufficiently
trained, without requiring any extra sampling for the instances from the tail
classes.Extensive experiments on the very recent long-tail large vocabulary
object recognition benchmark LVIS show that our proposed BAGS significantly
improves the performance of detectors with various backbones and frameworks on
both object detection and instance segmentation. It beats all state-of-the-art
methods transferred from long-tail image classification and establishes new
state-of-the-art.Code is available at
https://github.com/FishYuLi/BalancedGroupSoftmax.


  We derive a crepant resolution correspondence for some genus zero reduced
Gromov-Witten invariants of Hilbert schemes of points on a K3 surface.


  These notes provide a detailed catalog of surface charge formulas for
different classes of gravity theories. The present catalog reviews and extends
the existing literature on the topic. Part of the focus is on reviewing the
method to compute quasi-local surface charges for gauge theories in order to
clarify conceptual issues and their range of applicability. Many surface charge
formulas for gravity theories are expressed in metric, tetrads-connection,
Chern-Simons connection, and even BF variables. For most of them, the language
of differential forms is exploited and contrasted with the more popular metric
components language. The gravity theory is coupled with matter fields as
scalar, Maxwell, Skyrme, Yang-Mills, and spinors. Furthermore, three examples
with ready-to-download notebook codes, show the method in full action. Several
new results are highlighted through the notes.


  Brain tumor segmentation is a critical task in medical image analysis, aiding
in the diagnosis and treatment planning of brain tumor patients. The importance
of automated and accurate brain tumor segmentation cannot be overstated. It
enables medical professionals to precisely delineate tumor regions, assess
tumor growth or regression, and plan targeted treatments. Various deep
learning-based techniques proposed in the literature have made significant
progress in this field, however, they still face limitations in terms of
accuracy due to the complex and variable nature of brain tumor morphology. In
this research paper, we propose a novel Hybrid Multihead Attentive U-Net
architecture, to address the challenges in accurate brain tumor segmentation,
and to capture complex spatial relationships and subtle tumor boundaries. The
U-Net architecture has proven effective in capturing contextual information and
feature representations, while attention mechanisms enhance the model's ability
to focus on informative regions and refine the segmentation boundaries. By
integrating these two components, our proposed architecture improves accuracy
in brain tumor segmentation. We test our proposed model on the BraTS 2020
benchmark dataset and compare its performance with the state-of-the-art
well-known SegNet, FCN-8s, and Dense121 U-Net architectures. The results show
that our proposed model outperforms the others in terms of the evaluated
performance metrics.


  Some analogies between different nonequilibrium heat conduction models,
particularly, random walk, discrete variable model, and Boltzmann transport
equation with the single relaxation time approximation, have been discussed. We
show that under an assumption of a finite value of the heat carriers velocity,
these models lead to the hyperbolic heat conduction equation and the modified
Fourier law with the relaxation term. Corresponding effective temperature and
entropy have been introduced and analyzed. It has been demonstrated that the
effective temperature, defined as a geometric mean of the kinetic temperatures
of the heat carriers moving in opposite directions, is governed by a non-linear
relation and acts as a criterion for thermalization. It is shown that when the
heat flux tends to its maximum possible value, the effective temperature, heat
capacity and local entropy go to zero even at a nonzero equilibrium
temperature. This provides a possible generalization of the third law to
nonequilibrium situations. Analogies between the effective temperature and some
other definitions of temperature in nonequilibrium state, particularly, for
active systems, disordered semiconductors under electric field, and adiabatic
gas flow, have been shown and discussed. Illustrative examples of the behavior
of the effective temperature and entropy during nonequilibrium heat conduction
in a monatomic gas, a nano film, and a strong shockwave have been analyzed.


  We propose a framework where generation and transmission capacities are
planned concurrently in market environments with a focus on the prosumers. This
paper is a continuation of Part I and presents numerical results from three
archetypal case studies. Following the proposed framework, optimal planning
decisions are shown in all the cases. Furthermore, in case study I, no-regret
planning decisions considering the uncertainties in future electricity market
designs are discussed. In case study II, we look at a situation where the
social resistance of wind energy prevails and the prosumers choose to not
invest in wind energy. This preference results in an increased system cost, and
thus may harm other prosumers. The framework is used as a negotiation simulator
to deal with this problem. Case study III presents numerical results for a
mixed bilateral/pool market. The case studies utilize realistic data from the
Dutch power system and the European power system to provide policy-relevant
results that aid their decarbonization in various market environments.


  Warm Dark Matter(WDM), considerably clarifies and simplifies galaxies and
galaxy formation in agreement with observations. WDM essentially works,
naturally reproducing the astronomical observations over all scales, small
(galactic) as well as large and cosmological scales.Evidence that CDM,
CDM+baryons and proposed tailored cures do not work in galaxies is staggering,
The Chalonge Meudon Workshop 2012 approached DM in a fourfold coherent way:
astronomical observations (galaxy and cluster properties, haloes, rotation
curves, density profiles, surface density), LambdaWDM N-body simulations, WDM
theory (Boltzmann-Vlasov evolution, halo mass functions, halo models, improved
perturbative approachs), quantum WDM fermions forming the observed cores, WDM
particle and nuclear physics (sterile neutrinos) and its experimental search. N
Amorisco, P Biermann, S Das, H J de Vega, A Kamada, E Ferri(MARE),I D
Karanchetsev, W Liao, M Lovell, M Papastergis, N G Sanchez, P Valageas,C
Watson, J Zavala,He Zhang present their Highlights.Inside galaxy cores, N-body
classical physics simulations are incorrect for WDM because of important
quantum effects at such scales.Quantum WDM calculations (Thomas-Fermi) provide
galaxy cores, galaxy masses, velocity dispersions and density profiles in
agreement with observations.Baryons (16% of DM) are expected to give a
correction to pure WDM results. The summary and conclusions by H. J. de Vega
and N. G. Sanchez stress that all evidences point to a DM particle mass around
2 keV. Peter Biermann in his live minutes concludes that a few keV sterile
neutrino is the most serious DM candidate. MARE -and hopefully KATRIN- could
provide a sterile neutrino signal.There is a formidable WDM work to perform
ahead of us, these highlights point research directions worthwhile to
pursue.Photos of the Workshop are included (Abridged).


  The impact of new interactions on the triviality and stability Higgs-boson
mass bounds has been studied. The interactions have been parame- trized in a
model-independent way by a set of effective operators of dimension 6.
Constraints from electroweak observables at 1-loop level have been included. In
the analyzed region of scale of new physics $\La \simeq 2 \div 50 \tev$ the
classic triviality bound remains unchanged. An extension of the triviality
condition that has been introduced leads to strong constraints on the possible
models. The stability bound on the Higgs boson mass is substantially modified
depending on the scale $\La$ and strength of coefficients of relevant effective
operators.


  The recent discovery of orientation-dependent superconductivity in
KTaO3-based interfaces has attracted considerable interest, while the
underlying origin remains an open question. Here we report a different approach
to tune the interfacial electron gas and superconductivity by forming
interfaces between rare-earth (RE) metals (RE being La, Ce, Eu) and KTaO3
substrates with different orientations. We found that the interfacial
superconductivity is strongest for the Eu/KTaO3 interfaces, becomes weaker in
La/KTaO3 and is absent in Ce/KTaO3. Using in-situ photoemission, we observed
distinct valence bands associated with RE metals, as well as a pronounced
orientation dependence in the interfacial electronic structure, which can be
linked to the orientation-dependent superconductivity. The photoemission
spectra show similar double-peak structures for the (111) and (110) oriented
interfaces, with an energy separation close to the LO4 phonon of KTaO3.
Detailed analyses suggest that this double-peak structure could be attributed
to electron-phonon coupling, which might be important for the interfacial
superconductivity.


  We compare the main competing theories of tunneling time against experimental
measurements using the attoclock in strong laser field ionization of helium
atoms. Refined attoclock measurements reveal a real and not instantaneous
tunneling delay time over a large intensity regime, using two different
experimental apparatus. Only two of the theoretical predictions are compatible
within our experimental error: the Larmor time, and the probability
distribution of tunneling times constructed using a Feynman Path Integral (FPI)
formulation. The latter better matches the observed qualitative change in
tunneling time over a wide intensity range, and predicts a broad tunneling time
distribution with a long tail. The implication of such a probability
distribution of tunneling times, as opposed to a distinct tunneling time,
challenges how valence electron dynamics are currently reconstructed in
attosecond science. It means that one must account for a significant
uncertainty as to when the hole dynamics begin to evolve.


  We study some aspects of classical & quantum cosmology in the context of
two-dimensionsal dilaton gravity theories with matter being described by a
perfect fluid. We derive the classical equations obeyed by the metric function
& the dilaton field. An impicit solution for the metric function is obtained &
used to discuss possible expansion & contraction scenarios for the universe.
Quantization is carried out & finite norm exact solutions of the Wheeler-DeWitt
equation are obtained.


  A compiler bug arises if the behaviour of a compiled concurrent program, as
allowed by its architecture memory model, is not a behaviour permitted by the
source program under its source model. One might reasonably think that most
compiler bugs have been found in the decade since the introduction of the C/C++
memory model. We observe that processor implementations are increasingly
exploiting the behaviour of relaxed architecture models. As such, compiled
programs may exhibit bugs not seen on older hardware. To account for this we
require model-based compiler testing.
  While this observation is not surprising, its implications are broad.
Compilers and their testing tools will need to be updated to follow hardware
relaxations, concurrent test generators will need to be improved, and
assumptions of prior work will need revisiting. We explore these ideas using a
compiler toolchain bug we reported in LLVM.


  The main result of this paper asserts that if a Seifert fibered 4-manifold
has nonzero Seiberg-Witten invariant, the homotopy class of regular fibers has
infinite order. This is a nontrivial obstruction to smooth circle actions; as
applications, we show how to destroy smooth circle actions on a 4-manifold by
knot surgery, without changing the integral homology, intersection form, and
even the Seiberg-Witten invariant. Results concerning classification of Seifert
fibered complex surfaces or symplectic 4-manifolds are included. We also show
that every smooth circle action on the 4-torus is smoothly conjugate to a
linear action.


  This paper investigates the decoding of certain Gabidulin codes that were
transmitted over a channel with space-symmetric errors. Space-symmetric errors
are additive error matrices that have the property that their column and row
spaces are equal. We show that for channels restricted to space-symmetric
errors, with high probability errors of rank up to 2(n-k)/3 can be decoded with
a Gabidulin code of length n and dimension k, using a weak-self orthogonal
basis as code locators.


  We study the far-infrared emission from the nearby spiral galaxy M33 in order
to investigate the dust physical properties such as the temperature and the
luminosity density across the galaxy. Taking advantage of the unique wavelength
coverage (100, 160, 250, 350 and 500 micron) of the Herschel Space Observatory
and complementing our dataset with Spitzer-IRAC 5.8 and 8 micron and
Spitzer-MIPS 24 and 70 micron data, we construct temperature and luminosity
density maps by fitting two modified blackbodies of a fixed emissivity index of
1.5. We find that the 'cool' dust grains are heated at temperatures between 11
and 28 K with the lowest temperatures found in the outskirts of the galaxy and
the highest ones in the center and in the bright HII regions. The
infrared/submillimeter total luminosity (5 - 1000 micron) is estimated to be
1.9x10^9 Lsun. 59% of the total luminosity of the galaxy is produced by the
'cool' dust grains (~15 K) while the rest 41% is produced by 'warm' dust grains
(~55 K). The ratio of the cool-to-warm dust luminosity is close to unity
(within the computed uncertainties), throughout the galaxy, with the luminosity
of the cool dust being slightly enhanced in the center of the galaxy.
Decomposing the emission of the dust into two components (one emitted by the
diffuse disk of the galaxy and one emitted by the spiral arms) we find that the
fraction of the emission in the disk in the mid-infrared (24 micron) is 21%,
while it gradually rises up to 57% in the submillimeter (500 micron). We find
that the bulk of the luminosity comes from the spiral arm network that produces
70% of the total luminosity of the galaxy with the rest coming from the diffuse
dust disk. The 'cool' dust inside the disk is heated at a narrow range of
temperatures between 18 and 15 K (going from the center to the outer parts of
the galaxy).


  We consider the Cauchy problem for the inhomogeneous nonlinear
Schr\"{o}dinger (INLS) equation \[iu_{t} +\Delta u=|x|^{-b} f(u),\;u(0)\in
H^{s} (\mathbb R^{n} ),\] where $n\in \mathbb N$, $0<s<\min \{ n,\; 1+n/2\} $,
$0<b<\min \{ 2,\;n-s,\;1+\frac{n-2s}{2} \} $ and $f(u)$ is a nonlinear function
that behaves like $\lambda \left|u\right|^{\sigma } u$ with $\sigma>0$ and
$\lambda \in \mathbb C$. Recently, An--Kim \cite{AK21} proved the local
existence of solutions in $H^{s}(\mathbb R^{n} )$ with $0\le s<\min \{ n,\;
1+n/2\}$. However even though the solution is constructed by a fixed point
technique, continuous dependence in the standard sense in $H^{s}(\mathbb R^{n}
)$ with $0< s<\min \{ n,\; 1+n/2\}$ doesn't follow from the contraction mapping
argument. In this paper, we show that the solution depends continuously on the
initial data in the standard sense in $H^{s}(\mathbb R^{n} )$, i.e. in the
sense that the local solution flow is continuous $H^{s}(\mathbb R^{n} )\to
H^{s}(\mathbb R^{n} )$, if $\sigma $ satisfies certain assumptions.


  In this work we derive a general formula for the charge pumped in a
superconducting nanocircuit. Our expression generalizes previous results in
several ways, it is applicable both in the adiabatic and in the non-adiabatic
regimes and it takes into account also the effect of an external environment.
More specifically, by applying Floquet theory to Cooper pair pumping, we show
that under a cyclic evolution the total charge transferred through the circuit
is proportional to the derivative of the associated Floquet quasi-energy with
respect to the superconducting phase difference. In the presence of an external
environment the expression for the transferred charge acquires a transparent
form in the Floquet representation. It is given by the weighted sum of the
charge transferred in each Floquet state, the weights being the diagonal
components of the stationary density matrix of the system expressed in the
Floquet basis. In order to test the power of this formulation we apply it to
the study of pumping in a Cooper pair sluice. We reproduce the known results in
the adiabatic regime and we show new data in the non-adiabatic case.


  Bowden, Hensel, and Webb constructed infinitely many quasimophisms on the
diffeomorphism groups of orientable surfaces. In this paper, we extend their
result to nonorientable surfaces. Namely, we prove that the space of nontrivial
quasimorphisms $\widetilde{QH}(\mathrm{Diff}_0(N_g))$ on the identity component
of the diffeomorphism group $\mathrm{Diff}_0(N_g)$ on a closed nonorientable
surface $N_g$ of genus $g\geq 3$ is infinite dimensional. As a corollary, we
obtain the unboundedness of the commutator length and the fragmentation length
on $\mathrm{Diff}_0(N_g)$.


  A spin one-half particle propagating in a de Sitter background has a one
parameter family of states which transform covariantly under the isometry group
of the background. These states are the fermionic analogues of the alpha-vacua
for a scalar field. We shall show how using a point-source propagator for a
fermion in an alpha-state produces divergent perturbative corrections. These
corrections cannot be used to cancel similar divergences arising from scalar
fields in bosonic alpha-vacua since they have an incompatible dependence on the
external momenta. The theory can be regularized by modifying the propagator to
include an antipodal source.


  We report the detection of X-ray emission from the jet-driving symbiotic star
MWC 560. We observed MWC 560 with XMM-Newton for 36 ks. We fitted the spectra
from the EPIC pn, MOS1 and MOS2 instruments with XSPEC and examined the light
curves with the package XRONOS. The spectrum can be fitted with a highly
absorbed hard X-ray component from an optically-thin hot plasma, a Gaussian
emission line with an energy of 6.1 keV and a less absorbed soft thermal
component. The best fit is obtained with a model in which the hot component is
produced by optically thin thermal emission from an isobaric cooling flow with
a maximum temperature of 61 keV, which might be created inside an
optically-thin boundary layer on the surface of the accreting with dwarf. The
derived parameters of the hard component detected in MWC 560 are in good
agreement with similar objects as CH Cyg, SS7317, RT Cru and T CrB, which all
form a new sub-class of symbiotic stars emitting hard X-rays. Our previous
numerical simulations of the jet in MWC 560 showed that it should produce
detectable soft X-ray emission. We infer a temperature of 0.17 keV for the
observed soft component, i.e. less than expected from our models. The total
soft X-ray flux (i.e. at < 3 keV) is more than a factor 100 less than predicted
for the propagating jet soon after its birth (<0.3 yr), but consistent with the
value expected due its decrease with age. The ROSAT upper limit is also
consistent with such a decrease. We find aperiodic or quasi-periodic
variability on timescales of minutes and hours, but no periodic rapid
variability. All results are consistent with an accreting white dwarf powering
the X-ray emission and the existence of an optically-thin boundary layer around
it.


  Highly extended gamma-ray emission around the Geminga pulsar was discovered
by Milagro and verified by HAWC. Despite many observations with Imaging
Atmospheric Cherenkov Telescopes (IACTs), detection of gamma-ray emission on
angular scales exceeding the IACT field-of-view has proven challenging. Recent
developments in analysis techniques have enabled the detection of significant
emission around Geminga in archival data with H.E.S.S.. In 2019, further data
on the Geminga region were obtained with an adapted observation strategy.
Following the announcement of the detection of significant TeV emission around
Geminga in archival data, in this contribution we present the detection in an
independent dataset. New analysis results will be presented, and emphasis given
to the technical challenges involved in observations of highly extended
gamma-ray emission with IACTs.


  Based on symmetries Taub-NUT shares with Bertrand spacetime, we cast it as
the latter with magnetic fields. Its nature as a Bianchi-IX gravitational
instanton and other related geometrical properties are reviewed. We provide an
easy derivation and comparison between the spatial Killing-Yano tensors deduced
from first-integrals and the corresponding hyperk\"ahler structures and finally
verify the existence of a graded Lie-algebra structure via Schouten-Nijenhuis
brackets.


  Magic-angle twisted trilayer graphene (MATTG) has emerged as a novel moir\'e
material that exhibits both strong electronic correlations and unconventional
superconductivity. However, spectroscopic studies of its electronic properties
are lacking, and the nature of superconductivity and the corresponding order
parameter in this system remain elusive. Here we perform high-resolution
scanning tunneling microscopy and spectroscopy of MATTG and reveal extensive
regions of atomic reconstruction that favor mirror-symmetric stacking. In these
regions, we observe a cascade of symmetry-breaking electronic transitions and
doping-dependent band structure deformations similar to those realized in
magic-angle bilayers, as expected theoretically given the commonality of flat
bands. More strikingly, in a density window spanning two to three holes per
moire unit cell, spectroscopic signatures of superconductivity are manifest as
pronounced dips in the tunneling conductance at the Fermi level accompanied by
coherence peaks that become gradually suppressed at elevated temperatures and
magnetic fields. The observed evolution of the conductance with doping is
consistent with a gate-tunable transition from a gapped to a nodal
superconductor, which we show theoretically is compatible with a sharp
transition from a Bardeen-Cooper-Schrieffer (BCS) to a Bose-Einstein
condensation (BEC) superconductor with a nodal order parameter. Within this
doping window, we also detect peak-dip-hump structures suggesting that
superconductivity is driven by strong coupling to bosonic modes of MATTG. Our
results pave the way for further understanding of superconductivity and
correlated states in graphene-based moir\'e structures beyond twisted bilayers,
where unconventional superconductivity and nodal pairing were reported.


  Since the seminal work by Nagel and Weiss, the iteration stable (STIT)
tessellations have attracted considerable interest in stochastic geometry as a
natural and flexible, yet analytically tractable model for hierarchical spatial
cell-splitting and crack-formation processes. We provide in this paper a
fundamental link between typical characteristics of STIT tessellations and
those of suitable mixtures of Poisson hyperplane tessellations using martingale
techniques and general theory of piecewise deterministic Markov processes
(PDMPs). As applications, new mean values and new distributional results for
the STIT model are obtained.


  Using deep convolutional neural network (CNN), the nature of the QCD
transition can be identified from the final-state pion spectra from hybrid
model simulations of heavy-ion collisions that combines a viscous hydrodynamic
model with a hadronic cascade "after-burner". Two different types of equations
of state (EoS) of the medium are used in the hydrodynamic evolution. The
resulting spectra in transverse momentum and azimuthal angle are used as the
input data to train the neural network to distinguish different EoS. Different
scenarios for the input data are studied and compared in a systematic way. A
clear hierarchy is observed in the prediction accuracy when using the
event-by-event, cascade-coarse-grained and event-fine-averaged spectra as input
for the network, which are about 80%, 90% and 99%, respectively. A comparison
with the prediction performance by deep neural network (DNN) with only the
normalized pion transverse momentum spectra is also made. High-level features
of pion spectra captured by a carefully-trained neural network were found to be
able to distinguish the nature of the QCD transition even in a simulation
scenario which is close to the experiments.


  A frequently confused point in studies of symmetry violation is the
distinction between observer and particle transformations. In this work, we
consider a model in which a coefficient in the Standard-Model Extension leads
to violations of rotation invariance in Newton's second law. The model
highlights the distinction between observer and particle transformations.


  Electrons undergoing a Mott transition may shed their charge but persist as
neutral excitations of a quantum spin liquid (QSL). We introduce concrete
two-dimensional models exhibiting this exotic behavior as they transition from
superconducting or topological phases into fully charge-localized insulators.
We study these Mott transitions and the confinement of neutral fermions at a
second transition into a symmetry-broken phase. In the process, we also derive
coupled-wire parent Hamiltonians for a non-Abelian QSL and a $\mathbb{Z}_4$
QSL.


  Robotic minimally invasive interventions typically require using more than
two instruments. We thus developed a foot pedal interface which allows the user
to control a robotic arm (simultaneously to working with the hands) with four
degrees of freedom in continuous directions and speeds. This paper evaluates
and compares the performances of ten naive operators in using this new pedal
interface and a traditional button interface in completing tasks. These tasks
are geometrically complex path-following tasks similar to those in laparoscopic
training, and the traditional button interface allows axis-by-axis control with
constant speeds. Precision, time, and smoothness of the subjects' control
movements for these tasks are analysed. The results demonstrate that the pedal
interface can be used to control a robot for complex motion tasks. The subjects
kept the average error rate at a low level of around 2.6% with both interfaces,
but the pedal interface resulted in about 30% faster operation speed and 60%
smoother movement, which indicates improved efficiency and user experience as
compared with the button interface. The results of a questionnaire show that
the operators found that controlling the robot with the pedal interface was
more intuitive, comfortable, and less tiring than using the button interface.


  We have operated a Medipix2 CMOS readout chip, with amplifying, shaping and
charge discriminating front-end electronics integrated on the pixel-level, as a
highly segmented direct charge collecting anode in a three-stage gas electron
multiplier (Triple-GEM) to detect the ionization from $^{55}$Fe X-rays and
electrons from $^{106}$Ru. The device allows to perform moderate energy
spectroscopy measurements (20 % FWHM at 5.9 keV $X$-rays) using only digital
readout and two discriminator thresholds. Being a truly 2D-detector, it allows
to observe individual clusters of minimum ionizing charged particles in
$Ar/CO_2$ (70:30) and $He/CO_2$ (70:30) mixtures and to achieve excellent
spatial resolution for position reconstruction of primary clusters down to
$\sim 50 \mu m$, based on the binary centroid determination method.