title:
The complex time and energy evolution of quasi-periodic eruptions in
  eRO-QPE1

abstract:
  Quasi-periodic eruptions (QPEs) are recurrent X-ray bursts found so far in
the nuclei of low-mass galaxies. Their trigger mechanism is still unknown, but
recent models involving one or two stellar-mass companions around the central
massive ($\approx10^5-10^6$ solar masses) black hole have gathered significant
attention. While these have been compared only qualitatively with observations,
the phenomenology of QPEs is developing at a fast pace, with the potential to
reveal new insights. Here we report two new observational results found in
eRO-QPE1, the brightest QPE source discovered so far: i) the eruptions in
eRO-QPE1 occur sometimes as single isolated bursts, and at others as chaotic
mixtures of multiple overlapping bursts with very different amplitudes; ii) we
confirm that QPEs peak at later times and are broader at lower energies, with
respect to higher energies while, for the first time, we find that QPEs also
start earlier at lower energies. Furthermore, eruptions appear to undergo an
anti-clockwise hysteresis cycle in a plane of hardness ratio versus total count
rate. Behavior i) was not found before in any other QPE source and implies that
if a common trigger mechanism is in place for all QPEs, it must be able to
produce both types of timing properties, regular and complex. Result ii)
implies that the X-ray emitting component does not have an achromatic evolution
even during the start of QPEs, and that the rise is harder than the decay at a
given total count rate. This specific energy dependence could be qualitatively
compatible with inward radial propagation during the rise within a compact
accretion flow, the presence of which is suggested by the stable quiescence
spectrum observed in general for QPE sources.


title: On the Distribution of the Weighted Sum of Chi-Squared Variables

abstract:
  This paper presents the probability distribution function (p.d.f.) and
cumulative distribution function (c.d.f.) of the weighted sum of central
independent chi-squared random variables with non-zero weighs based on a method
using moment generating functions. To obtain the p.d.f. and c.d.f. of such a
function, we first derive the moment generating function of this weighted sum
using the partial fractions decomposition or the residue method. The results
cover the sum of two and three weighted chi-squared random variables, which can
easily be adapted to more general cases.


title: Maximum Entropy of Random Permutation Set

abstract:
  Recently, a new type of set, named as random permutation set (RPS), is
proposed by considering all the permutations of elements in a certain set. For
measuring the uncertainty of RPS, the entropy of RPS is presented. However, the
maximum entropy principle of RPS entropy has not been discussed. To address
this issue, in this paper, the maximum entropy of RPS is presented. The
analytical solution for maximum entropy of RPS and its corresponding PMF
condition are respectively proofed and discussed. Numerical examples are used
to illustrate the maximum entropy RPS. The results show that the maximum
entropy RPS is compatible with the maximum Deng entropy and the maximum Shannon
entropy. When the order of the element in the permutation event is ignored, the
maximum entropy of RPS will degenerate into the maximum Deng entropy. When each
permutation event is limited to containing just one element, the maximum
entropy of RPS will degenerate into the maximum Shannon entropy.


title:
Generalized critical Kirchhoff-type potential systems With Neumann
  Boundary conditions

abstract:
  In this paper, we consider a class of quasilinear stationary Kirchhoff type
potential systems with Neumann Boundary conditions, which involves a general
variable exponent elliptic operator with critical growth. Under some suitable
conditions on the nonlinearities, we establish existence and multiplicity of
solutions for the problem by using the concentration-compactness principle of
Lions for variable exponents found in [5, 7] and the Mountain Pass Theorem
without the Palais-Smale condition given in [43].


title:
A Quantitative Comparison between Shannon and Tsallis Havrda Charvat
  Entropies Applied to Cancer Outcome Prediction

abstract:
  In this paper, we propose to quantitatively compare loss functions based on
parameterized Tsallis-Havrda-Charvat entropy and classical Shannon entropy for
the training of a deep network in the case of small datasets which are usually
encountered in medical applications. Shannon cross-entropy is widely used as a
loss function for most neural networks applied to the segmentation,
classification and detection of images. Shannon entropy is a particular case of
Tsallis-Havrda-Charvat entropy. In this work, we compare these two entropies
through a medical application for predicting recurrence in patients with
head-neck and lung cancers after treatment. Based on both CT images and patient
information, a multitask deep neural network is proposed to perform a
recurrence prediction task using cross-entropy as a loss function and an image
reconstruction task. Tsallis-Havrda-Charvat cross-entropy is a parameterized
cross entropy with the parameter $\alpha$. Shannon entropy is a particular case
of Tsallis-Havrda-Charvat entropy for $\alpha$ = 1. The influence of this
parameter on the final prediction results is studied. In this paper, the
experiments are conducted on two datasets including in total 580 patients, of
whom 434 suffered from head-neck cancers and 146 from lung cancers. The results
show that Tsallis-Havrda-Charvat entropy can achieve better performance in
terms of prediction accuracy with some values of $\alpha$.


title:
Structural correlations in highly asymmetric binary charged colloidal
  mixtures

abstract:
  We explore structural correlations of strongly asymmetric mixtures of binary
charged colloids within the primitive model of electrolytes considering large
charge and size ratios of 10 and higher. Using computer simulations with
explicit microions, we obtain the partial pair correlation functions between
the like-charged colloidal macroions. Interestingly the big-small correlation
peak amplitude is smaller than that of the big-big and small-small macroion
correlation peaks, which is unfamiliar for additive repulsive interactions.
Extracting optimal effective microion-averaged pair interactions between the
macroions, we find that on top of non-additive Yukawa-like repulsions an
additional shifted Gaussian attractive potential between the small macroions is
needed to accurately reproduce their correct pair correlations. For small
Coulomb couplings, the behavior is reproduced in a coarse-grained theory with
microion-averaged effective interactions between the macroions. However, the
accuracy of the theory deteriorates with increasing Coulomb coupling. We
emphasize the relevance of entropic interactions exerted by the microions on
the macroions. Our results are experimentally verifiable in binary mixtures of
micron-sized colloids and like-charge nanoparticles


title:
sympy2c: from symbolic expressions to fast C/C++ functions and ODE
  solvers in Python

abstract:
  Computer algebra systems play an important role in science as they facilitate
the development of new theoretical models. The resulting symbolic equations are
often implemented in a compiled programming language in order to provide fast
and portable codes for practical applications. We describe sympy2c, a new
Python package designed to bridge the gap between the symbolic development and
the numerical implementation of a theoretical model. sympy2c translates
symbolic equations implemented in the SymPy Python package to C/C++ code that
is optimized using symbolic transformations. The resulting functions can be
conveniently used as an extension module in Python. sympy2c is used within the
PyCosmo Python package to solve the Einstein-Boltzmann equations, a large
system of ODEs describing the evolution of linear perturbations in the
Universe. After reviewing the functionalities and usage of sympy2c, we describe
its implementation and optimization strategies. This includes, in particular, a
novel approach to generate optimized ODE solvers making use of the sparsity of
the symbolic Jacobian matrix. We demonstrate its performance using the
Einstein-Boltzmann equations as a test case. sympy2c is widely applicable and
may prove useful for various areas of computational physics. sympy2c is
publicly available at
https://cosmology.ethz.ch/research/software-lab/sympy2c.html

categories: astro-ph.IM astro-ph.CO cs.MS physics.comp-ph


title:
Cosmological evolution of a statistical system of degenerate
  scalar-charged fermions with an asymmetric scalar doublet. I. Two-component
  system of assorted charges

abstract:
  Based on the mathematical model of a statistical system with scalar
interaction of fermions formulated earlier, a cosmological model based on a
two-component statistical system of scalar charged degenerate fermions
interacting with an asymmetric scalar doublet, canonical and phantom scalar
fields, is investigated. The asymptotic and limiting properties of the
cosmological model are investigated, and it is shown that among all models
there is a class of models with a finite lifetime. The asymptotic behavior of
models near the corresponding singularities is investigated and numerical
implementations of such models are constructed.


title:
CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware
  Training

abstract:
  Recent image inpainting methods have made great progress but often struggle
to generate plausible image structures when dealing with large holes in complex
images. This is partially due to the lack of effective network structures that
can capture both the long-range dependency and high-level semantics of an
image. To address these problems, we propose cascaded modulation GAN (CM-GAN),
a new network design consisting of an encoder with Fourier convolution blocks
that extract multi-scale feature representations from the input image with
holes and a StyleGAN-like decoder with a novel cascaded global-spatial
modulation block at each scale level. In each decoder block, global modulation
is first applied to perform coarse semantic-aware structure synthesis, then
spatial modulation is applied on the output of global modulation to further
adjust the feature map in a spatially adaptive fashion. In addition, we design
an object-aware training scheme to prevent the network from hallucinating new
objects inside holes, fulfilling the needs of object removal tasks in
real-world scenarios. Extensive experiments are conducted to show that our
method significantly outperforms existing methods in both quantitative and
qualitative evaluation.


title:
Gravitational - Scalar Instability of a Two-Component Degenerate System
  of Scalar Charged Fermions with Asymmetric Higgs Interaction

abstract:
  Based on the previously formulated mathematical model of a statistical system
with scalar interaction of fermions and the theory of gravitational-scalar
instability of a cosmological model based on a two-component statistical system
of scalar-charged degenerate fermions, a numerical model of the cosmological
evolution of gravitational-scalar perturbations is constructed and specific
examples of the development of instability are given. Some features of the
instability's development are investigated depending on the nature of the
behavior of the unperturbed cosmological model. It is shown that unstable modes
can appear at very early stages of cosmological expansion or contraction, and
the duration of the unstable phase is comparable to tens of Planck scales. In
this case, however, a very significant increase in unstable modes is possible
due to the redistribution of energy between the components of the scalar
doublet.


title: Cosmic-Ray Transport in Varying Galactic Environments

abstract:
  We study the propagation of mildly-relativistic cosmic rays (CRs) in
multiphase interstellar medium environments with conditions typical of nearby
disk galaxies. We employ the techniques developed in Armillotta+21 to
post-process three high-resolution TIGRESS magnetohydrodynamic simulations
modeling local patches of star-forming galactic disks. Together, the three
simulations cover a wide range of gas surface density, gravitational potential,
and star formation rate (SFR). Our prescription for CR propagation includes the
effects of advection by the background gas, streaming along the magnetic field
at the local ion Alfv\'en speed, and diffusion relative to the Alfv\'en waves,
with the diffusion coefficient set by the balance between streaming-driven
Alfv\'en wave excitation and damping mediated by local gas properties. We find
that the combined transport processes are more effective in environments with
higher SFR. These environments are characterized by higher-velocity hot
outflows (created by clustered supernovae) that rapidly advect CRs away from
the galactic plane. As a consequence, the ratio of midplane CR pressure to
midplane gas pressures decreases with increasing SFR. We also use the
post-processed simulations to make predictions regarding potential dynamical
impacts of CRs. The relatively flat CR pressure profiles near the midplane
argue that they would not provide significant support against gravity for most
of the ISM mass. However, the CR pressure gradients are larger than the other
pressure gradients in the extra-planar region (|z|>0.5 kpc), suggesting that
CRs may affect the dynamics of galactic fountains and/or winds. The degree of
this impact is expected to increase in environments with lower SFR.


title: Bootstrapping Pions at Large $N$

abstract:
  We revisit from a modern bootstrap perspective the longstanding problem of
solving QCD in the large $N$ limit. We derive universal bounds on the effective
field theory of massless pions by imposing the full set of positivity
constraints that follow from $2 \to 2$ scattering. Some features of our
exclusion plots have intriguing connections with hadronic phenomenology. The
exclusion boundary exhibits a sharp kink, raising the tantalizing scenario that
large $N$ QCD may sit at this kink. We critically examine this possibility,
developing in the process a partial analytic understanding of the geometry of
the bounds.


title: Portraying Double Higgs at the Large Hadron Collider II

abstract:
  The Higgs potential is vital to understand the electroweak symmetry breaking
mechanism, and probing the Higgs self-interaction is arguably one of the most
important physics targets at current and upcoming collider experiments. In
particular, the triple Higgs coupling may be accessible at the HL-LHC by
combining results in multiple channels, which motivates to study all possible
decay modes for the double Higgs production. In this paper, we revisit the
double Higgs production at the HL-LHC in the final state with two $b$-tagged
jets, two leptons and missing transverse momentum. We focus on the performance
of various neural network architectures with different input features:
low-level (four momenta), high-level (kinematic variables) and image-based. We
find it possible to bring a modest increase in the signal sensitivity over
existing results via careful optimization of machine learning algorithms making
a full use of novel kinematic variables.


title:
Action-angle coordinates for black-hole geodesics I: Spherically
  symmetric and Schwarzschild

abstract:
  Action-angle coordinates are a tool commonly used in celestial mechanics to
systematically parametrize and store general solutions of the equations of
motion of astrophysical bodies. I perturbatively construct action-angle
coordinates for bound test particle motion in static, spherically symmetric
space-times using a post-circular expansion. Then I specialise the expressions
to the motion in the gravitational fields of Schwarzschild black holes and give
explicit formulas for the Hamiltonian to the 10th power in the radial action
(20th power in eccentricity), and the transformation to angle coordinates up to
the 8th harmonic with respect to a relativistic orbital anomaly. The results
provide a closed-form perturbative solution for the orbital motion parametrized
by coordinate time that will find applications in the modelling of compact
binary inspirals and other fields of astrophysics.


title:
The Appearance of Vortices in Protoplanetary Disks in Near-Infrared
  Scattered Light

abstract:
  Azimuthally asymmetric structures have been discovered in millimeter
continuum emission from many protoplanetary disks. One hypothesis is that they
are vortices produced by the Rossby wave instability, for example at edges of
planet-opened gaps or deadzones. Confirming the vortex nature of these
structures will have profound implications to planet formation. One way to test
the hypothesis is to compare the observed morphology of vortex candidates in
near-infrared scattered light with theoretical expectations. To this end, we
synthesize the appearance of vortices in H-band polarized light by combining
hydrodynamic and radiative transfer simulations of the Rossby wave instability
at a deadzone edge. In a disk at 140 pc, at the peak in its evolution a vortex
at 65 au may appear as a radially narrow arc 50% - 70% brighter compared with
an axisymmetric disk model. The contrast depends on the inclination of the disk
and the position angle of the vortex only weakly. Such contrast levels are well
detectable in imaging observations of bright disks using instruments such as
VLT/SPHERE, Subaru/SCExAO, and Gemini/GPI. A vortex also casts a shadow in the
outer disk, which may aid its identification. Finally, at modest to high
inclinations (e.g., 60 degrees) a vortex may mimic a one-armed spiral. In the
HD 34282 disk, such a one-armed spiral with a shadowed region on the outside
has been found in scattered light. This feature roughly coincides with an
azimuthal asymmetry in mm continuum emission, signifying the presence of a
vortex.


title: Large and Small Corrections to the JLMS Formula from Replica Wormholes

abstract:
  The JLMS formula relates the bulk and boundary relative entropies and is
fundamental to the holographic dictionary, providing justification for
entanglement wedge reconstruction. We revisit the replica trick for relative
entropy and find corrections of the JLMS formula in a variety of scenarios,
even after accounting for effects of quantum extremality. We analyze the
problem in the PSSY model, a model of Jackiw-Teitelboim gravity coupled to
end-of-the-world branes. We find non-perturbative (in $G$) corrections that are
always present, arising from subdominant replica wormhole gravitational saddles
that indicate the approximate error-correcting nature of AdS/CFT. Near
entanglement phase transitions, these saddles can get enhanced to large
corrections. We find $O\left(G^{-1/2}\right)$ corrections arising from area
fluctuations and $O\left(G^{-1}\right)$ corrections from incompressible bulk
quantum states. Lastly, we find our most surprising result, an infinite
violation of the JLMS formula after the Page time arising from a rank
deficiency in the bulk entanglement spectrum. We discuss similar calculations
in tensor networks and comment on the implications for bulk reconstruction.


title:
An 8.56 keV absorption line in the hyperluminous X-ray source in NGC
  4045: ultra-fast outflow or cyclotron line?

abstract:
  We report on the discovery of an absorption line at $E=8.56^{+0.05}_{-0.11}$
keV detected with a significance of $>3.3\sigma$ in the NuSTAR and XMM-Newton
spectra of a newly discovered hyperluminous X-ray source (HLX, $L_{\rm
X}>10^{41}$ ergs$^{-1}$) in the galaxy NGC 4045 at a distance of 32 Mpc. The
source was first discovered serendipitously in a Swift/XRT observation of the
galaxy, and Swift monitoring reveals a highly variable source changing by over
an order of magnitude from maximum to minimum. The origin of the absorption
line appears likely to be by highly ionized iron with a blue shift of 0.19$c$,
indicating an ultrafast outflow (UFO). However, the large equivalent width of
the line (EW$=-0.22^{+0.08}_{-0.09}$ keV) paired with the lack of other
absorption lines detected are difficult to reconcile with models. An
alternative explanation is that the line is due to a cyclotron resonance
scattering feature (CRSF), produced by the interaction of X-ray photons with
the powerful magnetic field of a neutron star.


title:
Realistic galaxy images and improved robustness in machine learning
  tasks from generative modelling

abstract:
  We examine the capability of generative models to produce realistic galaxy
images. We show that mixing generated data with the original data improves the
robustness in downstream machine learning tasks. We focus on three different
data sets; analytical S\'ersic profiles, real galaxies from the COSMOS survey,
and galaxy images produced with the SKIRT code, from the IllustrisTNG
simulation. We quantify the performance of each generative model using the
Wasserstein distance between the distributions of morphological properties
(e.g. the Gini-coefficient, the asymmetry, and ellipticity), the surface
brightness distribution on various scales (as encoded by the power-spectrum),
the bulge statistic and the colour for the generated and source data sets. With
an average Wasserstein distance (Fr\'echet Inception Distance) of $7.19 \times
10^{-2}\, (0.55)$, $5.98 \times 10^{-2}\, (1.45)$ and $5.08 \times 10^{-2}\,
(7.76)$ for the S\'ersic, COSMOS and SKIRT data set, respectively, our best
models convincingly reproduce even the most complicated galaxy properties and
create images that are visually indistinguishable from the source data. We
demonstrate that by supplementing the training data set with generated data, it
is possible to significantly improve the robustness against domain-shifts and
out-of-distribution data. In particular, we train a convolutional neural
network to denoise a data set of mock observations. By mixing generated images
into the original training data, we obtain an improvement of $11$ and $45$ per
cent in the model performance regarding domain-shifts in the physical pixel
size and background noise level, respectively.


title:
COOL-LAMPS II. Characterizing the Size and Star Formation History of a
  Bright Strongly Lensed Early-Type Galaxy at Redshift 1.02

abstract:
  We present COOL J1323+0343, an early-type galaxy at $z = 1.0153 \pm 0.0006$,
strongly lensed by a cluster of galaxies at z = $z = 0.353 \pm 0.001$. This
object was originally imaged by DECaLS and noted as a gravitational lens by
COOL-LAMPS, a collaboration initiated to find strong-lensing systems in recent
public optical imaging data, and confirmed with follow-up data. With
ground-based grzH imaging and optical spectroscopy from the Las Campanas
Observatory and the Nordic Optical Telescope, we derive a stellar mass,
metallicity, and star-formation history from stellar-population synthesis
modeling. The lens modeling implies a total magnification of $\mu \sim $113.
The median remnant stellar mass in the source plane is M$_* \sim 10.63$
$M_\odot$ and the median star-formation rate in the source plane is SFR $\sim
1.55 \times 10^{-3}$ M$_\odot$ yr$^{-1}$ (log sSFR = -13.4 yr$^{-1}$) in the
youngest two age bins (0-100 Myr), closest to the epoch of observation. Our
measurements place COOL J1323+0343 below the characteristic mass of the stellar
mass function, making it an especially compelling target that could help
clarify how intermediate mass quiescent galaxies evolve. We reconstruct COOL
J1323+0343 in the source plane and fit its light profile. This object is below
the expected size-evolution of early-type galaxy at this mass with an effective
radius r$_e \sim$ 0.5 kpc. This extraordinarily magnified and bright lensed
early-type galaxy offers an exciting opportunity to study the morphology and
star formation history of an intermediate mass early-type galaxy in detail at
$z \sim $1 .


title:
Being KLEVER at cosmic noon: ionised gas outflows are inconspicuous in
  low-mass star-forming galaxies but prominent in massive AGN hosts

abstract:
  We investigate the presence of ionised gas outflows in a sample of 141
main-sequence star-forming galaxies at $1.2<z<2.6$ from the KLEVER (KMOS Lensed
Emission Lines and VElocity Review) survey. Our sample covers an exceptionally
wide range of stellar masses, $8.1<\log(M_\star/M_{\odot})<11.3$, pushing
outflow studies into the dwarf regime thanks to gravitationally lensed objects.
We stack optical rest-frame emission lines (H$\beta$, [OIII], H$\alpha$ and
[NII]) in different mass bins and seek for tracers of gas outflows by using a
novel, physically motivated method that improves over the widely used,
simplistic double Gaussian fitting. We compare the observed emission lines with
the expectations from a rotating disc (disc+bulge for the most massive
galaxies) model, whereby significant deviations are interpreted as a signature
of outflows. We find clear evidence for outflows in the most massive,
$\log(M_\star/M_{\odot}) > 10.8$, AGN-dominated galaxies, suggesting that AGNs
may be the primary drivers of these gas flows. Surprisingly, at
$\log(M_\star/M_{\odot})\leq 9.6$, the observed line profiles are fully
consistent with a rotating disc model, indicating that ionised gas outflows in
dwarf galaxies might play a negligible role even during the peak of cosmic
star-formation activity. Finally, we find that the observed mass loading factor
scales with stellar mass as expected from the TNG50 cosmological simulation,
but the ionised gas mass accounts for only 2$\%$ of the predicted value. This
suggests that either the bulk of the outflowing mass is in other gaseous phases
or the current feedback models implemented in cosmological simulations need to
be revised.


title:
Deconfinement Temperature of Rotating QGP at Intermediate Coupling from
  ${\cal M}$-Theory

abstract:
  With the aim of studying rotating Quark Gluon plasma, holographically, from a
top-down approach, study of the effect of vorticity on the deconfinement
temperature of thermal QCD-like theories at intermediate coupling from ${\cal
M}$-theory was missing in the literature. This paper fills this gap. The
gravity dual includes a rotating cylindrical black hole. In the presence of
vorticity, from a semi-classical computation we found that the deconfinement
temperature is inversely proportional to Lorentz factor which suggests that the
deconfinement temperature decreases with the increase of rotation. Further we
found that in the small frequency-limit, results from higher derivative
corrections at ${\cal O}(R^4)$ do not change and are same as in
arXiv:2108.05372. "The "UV-IR mixing, "Flavor Memory" effect and
non-renormalization of $T_c$ in the ${\cal M}$-theory dual, are similar to the
ones observed in arXiv:2108.05372.


title:
The Exclusive Vision of Rare $K$ and $B$ Decays and of the Quark Mixing
  in the Standard Model

abstract:
  The most common predictions for rare $K$ and $B$ decay branching ratios in
the Standard Model are based on the CKM elements $|V_{cb}|$ and $|V_{ub}|$
resulting from global fits, that are in the ballpark of their inclusive and
exclusive determinations, respectively. In the present paper we follow another
route. We assume that the future true values of $|V_{cb}|$ and $|V_{ub}|$ will
be both from exclusive determinations and set them equal to the most recent
ones from FLAG. An unusual pattern of SM predictions results from this study
with some existing tensions being dwarfed and new tensions being born. In
particular using the HPQCD $B^0_{s,d}-\bar B^0_{s,d}$ hadronic matrix elements
a $3.1\sigma$ tension in $\Delta M_s$ independently of $\gamma$ is found. For
$60^\circ\le\gamma\le 75^\circ$ the tension in $\Delta M_d$ between $4.0\sigma$
and $1.1\sigma$ is found and in the case of $\epsilon_K$ between $5.2\sigma$
and $2.1\sigma$. Moreover, the room for new physics in $K^+\to\pi^+\nu\bar\nu$,
$K_L\to\pi^0\nu\bar\nu$ and $B\to K(K^*)\nu\bar\nu$ decays is significantly
increased. We compare the results in this EXCLUSIVE scenario with the HYBRID
one in which $|V_{cb}|$ in the former scenario is replaced by the most recent
inclusive $|V_{cb}|$ and present the dependence of all observables considered
by us in both scenarios as functions of $\gamma$. We also compare the
determination of $|V_{cb}|$ from $\Delta M_s$, $\Delta M_d$, $\epsilon_K$ and
$S_{\psi K_S}$ using $B^0_{s,d}-\bar B^0_{s,d}$ hadronic matrix elements from
LQCD with $2+1+1$ flavours, $2+1$ flavours and their average. Only for the
$2+1+1$ case values for $\beta$ and $\gamma$ exist for which the same value of
$|V_{cb}|$ is found: $|V_{cb}|=42.6(7)\times 10^{-3}$. This in turn implies a
$2.7\sigma$ anomaly in $B_s\to\mu^+\mu^-$.


title:
Low X-ray surface brightness clusters: Implications on the scatter of
  the $M-T$ and $L-T$ relations

abstract:
  We aim at studying scaling relations of a small but well defined sample of
galaxy clusters that includes the recently discovered class of objects that are
X-ray faint for their mass. These clusters have an average low X-ray surface
brightness, a low gas fraction and are under-represented (by a factor of 10) in
X-ray surveys or entirely absent in SZ surveys. With the inclusion of these
objects, we find that the temperature-mass relation has an unprecedented large
scatter, 0.20+-0.03 dex at fixed mass, as wide as allowed by the temperature
range, and the location of a cluster in this plane depends on its surface
brightness. Clusters obey a relatively tight luminosity-temperature relation
independently of the their brightness. We interpret the wide difference in
scatter around the two relations as due to the fact that X-ray luminosity and
temperature are dominated by photons coming from small radii (in particular for
T we used a 300 kpc aperture radius) and strongly affected by gas
thermodynamics (e.g. shocks, cool-cores), whereas mass is dominated by dark
matter at large radii. We measure a slope of 2.0+-0.2 for the L500-T relation.
Given the characteristics of our sample, this value is free from the
collinearity (degeneracy) between evolution and slope and from hypothesis on
the undetected population, that both affect the analysis of X-ray selected
samples, and can therefore be profitably used both as reference and to break
the above degeneracy of X-ray selected-samples.


title: Self-Interacting Dark Matter from Gravitational Scattering

abstract:
  I show that gravitational scattering of dark-matter objects of 10^4 solar
masses and speeds of 10 km/s, provides the cross-section per unit mass required
in self-interacting dark matter models that alleviate the small-scale structure
challenges to the collisionless cold dark matter model. For primordial objects
of mass 10^4*(M_4) solar masses, moving at the velocity dispersion
characteristic of dwarf galaxies, 10*(v_1) km/s, the cross-section per unit
mass for gravitational scattering is 10*[M_4/(v_1)^4] cm^2/g. The steep decline
in interaction with increasing velocity explains why self-interaction is not
evident in data on massive galaxies and clusters of galaxies.


title:
Stringent $\sigma_8$ constraints from small-scale galaxy clustering
  using a hybrid MCMC+emulator framework

abstract:
  We present a novel simulation-based hybrid emulator approach that maximally
derives cosmological and Halo Occupation Distribution (HOD) information from
non-linear galaxy clustering, with sufficient precision for DESI Year 1 (Y1)
analysis. Our hybrid approach first samples the HOD space on a fixed
cosmological simulation grid to constrain the high-likelihood region of
cosmology+HOD parameter space, and then constructs the emulator within this
constrained region. This approach significantly reduces the parameter volume
emulated over, thus achieving much smaller emulator errors with fixed number of
training points. We demonstrate that this combined with state-of-the-art
simulations result in tight emulator errors comparable to expected DESI Y1 LRG
sample variance. We leverage the new AbacusSummit simulations and apply our
hybrid approach to CMASS non-linear galaxy clustering data. We infer
constraints on $\sigma_8 = 0.762\pm0.024$ and $f\sigma_8 (z_{eff} = 0.52) =
0.444\pm0.016$, the tightest among contemporary galaxy clustering studies. We
also demonstrate that our $f\sigma_8$ constraint is robust against secondary
biases and other HOD model choices, a critical first step towards showcasing
the robust cosmology information accessible in non-linear scales. We speculate
that the additional statistical power of DESI Y1 should tighten the growth rate
constraints by at least another 50-60%, significantly elucidating any potential
tension with Planck. We also address the "lensing is low" tension, where we
find that the combined effect of a lower $f\sigma_8$ and environment-based bias
lowers the predicted lensing signal by 15%, accounting for approximately 50% of
the discrepancy between the lensing measurement and clustering-based
predictions.


title:
The Physical Properties of Low Redshift FeLoBAL Quasars. I. Spectral
  Synthesis Analysis of the BAL Outflows using $SimBAL$

abstract:
  We present the first systematic study of 50 low redshift ($0.66 < z < 1.63$)
iron low-ionization broad absorption-line quasars (FeLoBALQs) using $SimBAL$
which represents a more than five-fold increase in the number of FeLoBALQs with
detailed absorption line spectral analyses. We found the outflows have a wide
range of ionization parameters, $-4\lesssim\log U\lesssim 1.2$ and densities,
$2.8\lesssim\log n\lesssim8\ \rm[cm^{-3}]$. The objects in our sample showed
FeLoBAL gas located at a wide range of distances $0\lesssim\log R\lesssim 4.4$
[pc], although we do not find any evidence for disk winds (with $R\ll0.01$ pc)
in our sample. The outflow strength primarily depends on the outflow velocity
with faster outflows found in quasars that are luminous or that have flat or
redder spectral energy distributions. We found that $\sim18\%$ of the FeLoBALQs
in the sample have the significantly powerful outflows needed for quasar
feedback. Eight objects showed "overlapping troughs" in the spectra and we
identified eleven "loitering outflow" objects, a new class of FeLoBALQs that
are characterized by low outflow velocities and high column density winds
located $\log R\lesssim1$ [pc] from the central engine. The FeLoBALs in
loitering outflows objects do not show properties expected for radiatively
driven winds and these objects may represent a distinct population among
FeLoBALQs. We discuss how the potential acceleration mechanisms and the origins
of the FeLoBAL winds may differ for outflows at different locations in quasars.


title:
Angular momentum transport and thermal stabilization of optically thin,
  advective accretion flows through large-scale magnetic fields

abstract:
  Outward transport of angular momentum, as well as viscous and thermal
stability, are the necessary criteria for the formation of accretion disc and
to radiate steadily. Turbulent motions originating from magneto-rotational
instability or hydrodynamic instability can do the required transport. We
explore the effect of a large-scale magnetic field (LSMF) over the turbulent
transport in an optically thin advective disc. In this work, turbulent
transport is represented through the usual Shakura-Sunyaev $\alpha$-viscosity.
The evolution of the magnetic field and other variables is found by solving
vertically integrated height averaged magnetohydrodynamic equations. Depending
on its configuration, the LSMF can support or oppose $\alpha$ in outward
transport of angular momentum. Once outward transport of angular momentum is
assured, i.e., formation of the disc is confirmed through the combined effect
of $\alpha$-viscosity and the LSMF, we explore the impact of the LSMF in
thermally stabilizing the disc. As found earlier, we also find that the
advection of heat energy becomes zero or negative with increasing accretion
rate. That is why at or above a critical accretion rate, the optically thin
advective disc becomes thermally unstable. We show however that with the
addition of a strong enough magnetic field, the disc regains its thermal
stability and Joule heating turns out to play the key role in that. Throughout
our analysis the plasma-$\beta$ ($\beta_\mathrm{m}$) remains within the range
of 5-$10^3$, which does not impose any restriction in the simultaneous
operation of the LSMF and the turbulent transport.


title:
Finiteness of the percolation threshold for inhomogeneous long-range
  models in one dimension

abstract:
  We consider a large class of inhomogeneous spatial random graphs on the real
line. Each vertex carries an i.i.d. weight and edges are drawn such that short
edges and edges to vertices with large weights are preferred. This allows the
study of models with long-range effects and heavy-tailed degree distributions.
We introduce a new coefficient, $\delta_\text{eff}$, measuring the influence of
the degree-distribution on the long-range edges. We identify a sharp phase
transition in $\delta_\text{eff}$ for the existence of a supercritical
percolation phase. In Gracar, L\"uchtrath, M\"orters 2021, it is shown that the
soft Boolean model and the age-dependent random connection model are examples
for models that have parameter regimes where there is no subcritical
percolation phase. This paper completes these results and shows that in
dimension one there exist parameter regimes in which the models have no
supercritical phase and regimes with both super- and a subcritical phases.


title: Bearing-Based Formation Control with Optimal Motion Trajectory

abstract:
  Bearing-based distributed formation control is attractive because it can be
implemented using vision-based measurements to achieve a desired formation.
Gradient-descent-based controllers using bearing measurements have been shown
to have many beneficial characteristics, such as global convergence,
applicability to different graph topologies and workspaces of arbitrary
dimension, and some flexibility in the choice of the cost. In practice,
however, such controllers typically yield convoluted paths from their initial
location to the final position in the formation. In this paper we propose a
novel procedure to optimize gradient-descent-based bearing-based formation
controllers to obtain shorter paths. Our approach is based on the
parameterization of the cost function and, by extension, of the controller. We
form and solve a nonlinear optimization problem with the sum of path lengths of
the agent trajectories as the objective and subject to the original equilibria
and global convergence conditions for formation control. Our simulation shows
that the parameters can be optimized from a very small number of training
samples (1 to 7) to straighten the trajectory by around 16% for a large number
of random initial conditions for bearing-only formation. However, in the
absence of any range information, the scale of the formation is not fixed and
this optimization may lead to an undesired compression of the formation size.
Including range measurements avoids this issue and leads to further
trajectories straightening by 66%.


title:
A forest formula for pre-Lie exponentials, Magnus' operator and
  cumulant-cumulant relations

abstract:
  Forest formulas that generalize Zimmermann's forest formula in quantum field
theory have been obtained for the computation of the antipode in the dual of
enveloping algebras of pre-Lie algebras. In this work, largely motivated by
Murua's analysis of the Baker-Campbell-Hausdorff formula, we show that the same
ideas and techniques generalize and provide effective tools to handle
computations in these algebras, which are of utmost importance in numerical
analysis and related areas. We illustrate our results by studying the action of
the pre-Lie exponential and the Magnus operator in the free pre-Lie algebra and
in a pre-Lie algebra of words originating in free probability. The latter
example provides combinatorial formulas relating the different brands of
cumulants in non-commutative probability.


title:
Composable end-to-end security of Gaussian quantum networks with
  untrusted relays

abstract:
  Gaussian networks are fundamental objects in network information theory. Here
many senders and receivers are connected by physically motivated Gaussian
channels while auxiliary Gaussian components, such as Gaussian relays, are
entailed. Whilst the theoretical backbone of classical Gaussian networks is
well established, the quantum analogue is yet immature. Here, we theoretically
tackle composable security of arbitrary Gaussian quantum networks (quantum
networks), with generally untrusted nodes, in the finite-size regime and put
forward a general methodology for parameter estimation, which is only based on
the data shared by the remote end-users. Taking a chain of quantum repeaters as
an example, we find that the composable key rate of the chain can beat the
fundamental repeaterless limit with practical block sizes.


title:
Hybrid Cerenkov-scintillation detector validation using Monte Carlo
  simulations

abstract:
  Objective: This study aimed at investigating through Monte Carlo simulations
the limitations of a novel hybrid Cerenkov-scintillation detector and the
associated method for irradiation angle measurements. Approach: Using Monte
Carlo simulations, previous experimental irradiations of the hybrid detector
with a linear accelerator were replicated to evaluate its general performances
and limitations. Cerenkov angular calibration curves and irradiation angle
measurements were then compared. Furthermore, the impact of the Cerenkov light
energy dependency on the detector accuracy was investigated using the energy
spectra of electrons travelling through the detector. Main results: Monte Carlo
simulations were found to be in good agreement with experimental values. The
irradiation angle absolute mean error was found to be lesser than what was
obtained experimentally, with a maximum value of 1.12 degree for the 9 MeV
beam. A 0.4% increase of the ratio of electrons having an energy below 1 MeV to
the total electrons was found to impact the Cerenkov light intensity collected
as a function of the incident angle. The effect of the Cerenkov intensity
variation on the measured angle was determined to vary according to the slope
of the angular calibration curve. While the contribution of scattered electrons
with a lower energy affects the detector accuracy, greatest discrepancies
result from the limitations of the calculation method and the calibration curve
itself. Significance: A precise knowledge of the limitations of the hybrid
detector and the irradiation angle calculation method is crucial for a clinical
implementation. Moreover, the simulations performed in this study also
corroborates hypotheses made regarding the relations between multiple Cerenkov
dependencies and observations from the experimental measurements.


title:
Variations in the $\Sigma_{\rm SFR} {-} \Sigma_{\rm mol} {-} \Sigma_{\rm
  \star}$ plane across galactic environments in PHANGS galaxies

abstract:
  There exists some consensus that stellar mass surface density ($\Sigma_{*}$)
and molecular gas mass surface density ($\Sigma_{\rm mol}$) are the main
quantities responsible for locally setting the star formation rate. This
regulation is inferred from locally resolved scaling relations between these
two quantities and the star formation rate surface density ($\Sigma_{\rm
SFR}$). However, the universality of these relations is debated. Here, we probe
the interplay between these three quantities across different galactic
environments at a spatial resolution of 150 pc. We perform a hierarchical
Bayesian linear regression to find the best set of parameters $C_{*}$, $C_{\rm
mol}$, and $C_{\rm norm}$ that describe the star-forming plane conformed by
these quantities, such that $\log \Sigma_{\rm SFR} = C_{*} \log \Sigma_{*} +
C_{\rm mol} \log \Sigma_{\rm mol} + C_{\rm norm}$, and explore variations in
the determined parameters across galactic environments, focusing our analysis
on the $C_{*}$ and $C_{\rm mol}$ slopes. We find signs of variations in the
posterior distributions of $C_{*}$ and $C_{\rm mol}$ across different galactic
environments. Bars show the most negative value of $C_{*}$, a sign of longer
depletion times, while spiral arms show the highest $C_{*}$ among all
environments. We conclude that systematic variations in the interplay of
$\Sigma_{*}$, $\Sigma_{\rm mol}$ and $\Sigma_{\rm SFR}$ across galactic
environments exist at a spatial resolution of 150 pc, and we interpret these
variations as produced by an additional mechanism regulating the formation of
stars that is not captured by either $\Sigma_{*}$ or $\Sigma_{\rm mol}$. We
find that these variations correlate with changes in the star formation
efficiency across environments, which could be linked to the dynamical state of
the gas that prevents it from collapsing and forming stars, or to changes in
the molecular gas fraction.


title: Economic Networks: Theory and Computation

abstract:
  This textbook is an introduction to economic networks, intended for students
and researchers in the fields of economics and applied mathematics. The
textbook emphasizes quantitative modeling, with the main underlying tools being
graph theory, linear algebra, fixed point theory and programming. The text is
suitable for a one-semester course, taught either to advanced undergraduate
students who are comfortable with linear algebra or to beginning graduate
students.


title: Scalable Deep Reinforcement Learning Algorithms for Mean Field Games

abstract:
  Mean Field Games (MFGs) have been introduced to efficiently approximate games
with very large populations of strategic agents. Recently, the question of
learning equilibria in MFGs has gained momentum, particularly using model-free
reinforcement learning (RL) methods. One limiting factor to further scale up
using RL is that existing algorithms to solve MFGs require the mixing of
approximated quantities such as strategies or $q$-values. This is non-trivial
in the case of non-linear function approximation that enjoy good generalization
properties, e.g. neural networks. We propose two methods to address this
shortcoming. The first one learns a mixed strategy from distillation of
historical data into a neural network and is applied to the Fictitious Play
algorithm. The second one is an online mixing method based on regularization
that does not require memorizing historical data or previous estimates. It is
used to extend Online Mirror Descent. We demonstrate numerically that these
methods efficiently enable the use of Deep RL algorithms to solve various MFGs.
In addition, we show that these methods outperform SotA baselines from the
literature.


title: On the global behavior of linear flows

abstract:
  For linear flows on vector bundles, it is analyzed when subbundles in the
Selgrade decomposition yield chain transitive subsets for the induced flow on
the associated Poincar\'e sphere bundle.


title:
Finite-depth scaling of infinite quantum circuits for quantum critical
  points

abstract:
  The scaling of the entanglement entropy at a quantum critical point allows us
to extract universal properties of the state, e.g., the central charge of a
conformal field theory. With the rapid improvement of noisy intermediate-scale
quantum (NISQ) devices, these quantum computers present themselves as a
powerful new tool to study critical many-body systems. We use finite-depth
quantum circuits suitable for NISQ devices as a variational ansatz to represent
ground states of critical, infinite systems. We find universal finite-depth
scaling relations for these circuits and verify them numerically at two
different critical points, i.e., the critical Ising model with an additional
symmetry-preserving term and the critical XXZ model.


title: Monolepton production in SMEFT to $\mathcal O(1/\Lambda^4)$ and beyond

abstract:
  We calculate $pp \to \ell^{+}\nu, \ell^-\bar \nu$ to ${\cal{O}}(1/\Lambda^4)$
within the Standard Model Effective Field Theory (SMEFT) framework. In
particular, we calculate the four-fermion contribution from dimension six and
eight operators, which dominates at large center of mass energy. We explore the
relative size of the $\mathcal O(1/\Lambda^4)$ and $\mathcal O(1/\Lambda^2)$
results for various kinematic regimes and assumptions about the Wilson
coefficients. Results for Drell-Yan production $pp \to \ell^+\ell^-$ at
${\cal{O}}(1/\Lambda^4)$ are also provided. Additionally, we develop the form
for four fermion contact term contributions to $pp \to \ell^{+}\nu, \ell^-\bar
\nu, pp \to \ell^+\ell^-$ of arbitrary mass dimension. This allows us to
estimate the effects from even higher dimensional (dimension $> 8$) terms in
the SMEFT framework.


title:
YouTube over Google's QUIC vs Internet Middleboxes: A Tug of War between
  Protocol Sustainability and Application QoE

abstract:
  Middleboxes such as web proxies, firewalls, etc. are widely deployed in
today's network infrastructure. As a result, most protocols need to adapt their
behavior to co-exist. One of the most commonly used transport protocols, QUIC,
adapts to such middleboxes by falling back to TCP, where they block it. In this
paper, we argue that the blind fallback behavior of QUIC, i.e., not
distinguishing between failures caused by middleboxes and that caused by
network congestion, hugely impacts the performance of QUIC. For this, we focus
on YouTube video streaming and conduct a measurement study by utilizing
production endpoints of YouTube by enabling TCP and QUIC at a time. In total,
we collect over 2600 streaming hours of data over various bandwidth patterns,
from 5 different geographical locations and various video genres. To our
surprise, we observe that the legacy setup (TCP) either outperforms or performs
the same as the QUIC-enabled browser for more than 60% of cases. We see that
our observation is consistent across individual QoE parameters, bandwidth
patterns, locations, and videos. Next, we conduct a deep-dive analysis to
discover the root cause behind such behavior. We find a good correlation
(0.3-0.7) between fallback and QoE drop events, i.e., quality drop and
re-buffering or stalling. We further perform Granger causal analysis and find
that fallback Granger causes either quality drop or stalling for 70% of the
QUIC-enabled sessions. We believe our study will help designers revisit the
decision to enable fallback in QUIC and distinguish between the packet drops
caused by middleboxes and network congestion.


title: Benchmark potential energy curve for collinear H$_3$

abstract:
  A benchmark-quality potential energy curve is reported for the H$_3$ system
in collinear nuclear configurations. The electronic Schr\"odinger equation is
solved using explicitly correlated Gaussian (ECG) basis functions using an
optimized fragment initialization technique that significantly reduces the
computational cost. As a result, the computed energies improve upon recent
orbital-based and ECG computations. Starting from a well-converged basis set, a
potential energy curve with an estimated sub-parts-per-billion precision is
generated for a series of nuclear configurations using an efficient ECG
rescaling approach.


title: Polarization from Aligned Dust Grains in the $\beta$ Pic Debris Disk

abstract:
  We present 870 $\mu$m ALMA polarization observations of thermal dust emission
from the iconic, edge-on debris disk $\beta$ Pic. While the spatially resolved
map does not exhibit detectable polarized dust emission, we detect polarization
at the $\sim$3$\sigma$ level when averaging the emission across the entire
disk. The corresponding polarization fraction is $P_\textrm{frac}$ = $0.51 \pm
0.19$%. The polarization position angle $\chi$ is aligned with the minor axis
of the disk, as expected from models of dust grains aligned via radiative
alignment torques (RAT) with respect to a toroidal magnetic field ($B$-RAT) or
with respect to the anisotropy in the radiation field ($k$-RAT). When averaging
the polarized emission across the outer versus inner thirds of the disk, we
find that the polarization arises primarily from the SW third. We perform
synthetic observations assuming grain alignment via both $k$-RAT and $B$-RAT.
Both models produce polarization fractions close to our observed value when the
emission is averaged across the entire disk. When we average the models in the
inner versus outer thirds of the disk, we find that $k$-RAT is the likely
mechanism producing the polarized emission in $\beta$ Pic. A comparison of
timescales relevant to grain alignment also yields the same conclusion. For
dust grains with realistic aspect ratios (i.e., $s > 1.1$), our models imply
low grain-alignment efficiencies.


title:
Nonlinear magnetoconductivity in Weyl and multi-Weyl semimetal in
  quantizing magnetic field

abstract:
  Magnetotransport and magneto-optics experiments offer a very powerful probe
for studying the physical properties of materials. Here, we investigate the
second-order nonlinear magnetoconductivity of tilted type-I Weyl and multi-Weyl
semimetal. In contrast to the presence of chiral anomaly in the linear response
regime, we show that Weyl semimetal do not host chiral charge pumping in the
nonlinear transport regime. We predict that an inversion symmetry broken and
tilted Weyl semimetal can support finite longitudinal nonlinear
magnetoconductivity, which is otherwise absent in untilted Weyl semimetal. The
nonlinear magnetoconductivity vanishes in the ultra-quantum limit, oscillates
in the intermediate magnetic field regime and saturates in the semiclassical
limit. The nonlinear magnetoconductivity depends intricately on the tilt
orientation, and it can be used to determine the tilt orientation in Weyl and
multi-Weyl semimetals, via nonlinear magnetoresistivity or second harmonic
generation experiments.


title: A Factor-Based Framework for Decision-Making Competency Self-Assessment

abstract:
  We summarize our efforts to date in developing a framework for generating
succinct human-understandable competency self-assessments in terms of machine
self confidence, i.e. a robot's self-trust in its functional abilities to
accomplish assigned tasks. Whereas early work explored machine self-confidence
in ad hoc ways for niche applications, our Factorized Machine Self-Confidence
framework introduces and combines several aspects of probabilistic meta
reasoning for algorithmic planning and decision-making under uncertainty to
arrive at a novel set of generalizable self-confidence factors, which can
support competency assessment for a wide variety of problems.


title:
Polarized products of elliptic curves with complex multiplication and
  field of moduli $\mathbb{Q}$

abstract:
  Let $R$ be the maximal order in a quadratic imaginary field $K$. We give an
equivalence of categories between the category of polarized abelian varieties
isomorphic to a product of elliptic curves over $\mathbb{C}$ with complex
multiplication (CM) by $R$ and the category of integral hermitian $R$-lattices.
Then we apply this equivalence to enumerate all the genus $2$ and $3$ curves
with field of moduli $\mathbb{Q}$ and with Jacobian isomorphic to a product of
elliptic curves with CM by $R$.


title:
Gyrokinetic particle-in-cell simulations of electromagnetic turbulence
  in the presence of fast particles and global modes

abstract:
  Global simulations of electromagnetic turbulence, collisionless tearing
modes, and Alfven Eigenmodes in the presence of fast particles are carried out
using the gyrokinetic particle-in-cell codes ORB5 (E. Lanti et al, Comp. Phys.
Comm., ${\bf 251}$, 107072 (2020)) and EUTERPE (V. Kornilov et al, Phys.
Plasmas, ${\bf 11}$, 3196 (2004)) in tokamak and stellarator geometries.
Computational feasibility of simulating such complex coupled systems is
demonstrated.


title: Experimental Realization of One Dimensional Helium

abstract:
  The realization of experimental platforms exhibiting one dimensional (1D)
quantum phenomena has been elusive, due to their inherent lack of stability,
with a few notable exceptions including spin chains, carbon nanotubes and
ultracold low-density gasses. The difficulty of such systems in exhibiting long
range order is integral to their effective description in terms of the
Tomonaga-Luttinger liquid theory. Recently, it has been proposed that bosonic
superfluid 4He could realize a 1D quantum system beyond the Luttinger liquid
paradigm. Here we describe an experimental observation of this behavior using
nanoengineering by preplating a porous material with a noble gas to enhance
dimensional reduction. The resulting excitations of the confined 4He are
qualitatively different than 3D and 2D superfluid helium, and can be analyzed
in terms of a mobile impurity in a Luttinger liquid allowing for the
characterization of the emergent quantum liquid. The confined helium system
offers the possibility of tuning via pressure - from weakly interacting, all
the way to the super Tonks-Girardeau gas of strongly interacting hard-core
particles.


title:
Periodic toughness distribution -- Can an average toughness concept be
  feasible? Case study: KGD fracture in an impermeable rock

abstract:
  The process of hydraulic fracture through heterogeneous rock with variable
material toughness is considered. Numerical simulations are used to examine the
effectiveness of differing strategies for homogenising this parameter: the
maximum toughness strategy and a newly proposed temporal averaging based
approach. We restrict ourselves to periodic distributions and consider only the
KGD model without leak-off, allowing us to easily investigate different regimes
(toughness/viscosity). Simulations are conducted using an extremely effective
(in house-built) time-space adaptive solver. The regimes in which each strategy
is effective are determined. It is demonstrated that an averaging based
approach can be proposed that incorporates crucial aspects of the process
behaviour.


title:
Effort Dynamics with Selective Predator Harvesting of a Ratio-dependent
  Predator-Prey System

abstract:
  In this paper, the selective predator harvesting is considered in a predator
prey system. The logistic growth of prey and ratio-dependent functional
response is assumed. The dynamically varying effort is employed for selective
harvesting of predator species using Michaelis-Menten type function The
boundedness, positivity and persistence of the nonlinear dynamical system is
established. The system being non-singular about origin, its dynamics is
explored by transforming it to a regular system. It is observed that the system
may collapse even with positive initial conditions attracted to one of the
boundary points under certain conditions. The local stability of various other
equilibrium states of the dynamic model is investigated. The region of
attraction of interior equilibrium state is obtained using Lyapunov stability.
The occurrence of hopf bifurcation about the coexistence equilibrium point with
respect to the parameter m (fraction of predators available for harvesting) is
established. The sustainable harvesting is possible in two ways firstly in the
form of stable interior equilibrium state and secondly in the form of limit
cycle. Considering the fraction m as a control variable, the optimal harvesting
policy is obtained using Pontraygin's maximum principle. The two-parameter
bifurcation diagram is obtained with respect to c and d (the cost of harvesting
and the death rate of predators respectively). The two bi-stability regions of
parameter space are identified. It is proved that for sustainable harvesting of
predators the ratio of p to c (price to cost) should be greater than a certain
threshold value dependent on predator density. The analytical results are
illustrated numerically with different parametric values.


title: Learning Patch-to-Cluster Attention in Vision Transformer

abstract:
  The Vision Transformer (ViT) model is built on the assumption of treating
image patches as "visual tokens" and learning patch-to-patch attention. The
patch embedding based tokenizer is a workaround in practice and has a semantic
gap with respect to its counterpart, the textual tokenizer. The patch-to-patch
attention suffers from the quadratic complexity issue, and also makes it
non-trivial to explain learned ViT models. To address these issues in ViT
models, this paper proposes to learn patch-to-cluster attention (PaCa) based
ViT models. Queries in our PaCaViT are based on patches, while keys and values
are based on clustering (with a predefined small number of clusters). The
clusters are learned end-to-end, leading to better tokenizers and realizing
joint clustering-for-attention and attention-for-clustering when deployed in
ViT models. The quadratic complexity is relaxed to linear complexity. Also,
directly visualizing the learned clusters can reveal how a trained ViT model
learns to perform a task (e.g., object detection). In experiments, the proposed
PaCa-ViT is tested on CIFAR-100 and ImageNet-1000 image classification, and
MS-COCO object detection and instance segmentation. Compared with prior arts,
it obtains better performance in classification and comparable performance in
detection and segmentation. It is significantly more efficient in COCO due to
the linear complexity. The learned clusters are also semantically meaningful
and shed light on designing more discriminative yet interpretable ViT models.


title:
Some Conceptual Aspects of Operator Design for Quantum Simulations of
  Non-Abelian Lattice Gauge Theories

abstract:
  In the Kogut-Susskind formulation of lattice gauge theories, a set of quantum
numbers resides at the ends of each link to characterize the vertex-local gauge
field. We discuss the role of these quantum numbers in propagating correlations
and supporting entanglement that ensures each vertex remains gauge invariant,
despite time evolution induced by operators with (only) partial access to each
vertex Hilbert space. Applied to recent proposals for eliminating vertex-local
Hilbert spaces in quantum simulation, we describe how the required entanglement
is generated via delocalization of the time evolution operator with
nearest-neighbor controls. These hybridizations, organized with qudits or
qubits, exchange classical operator preprocessing for reductions in quantum
resource requirements that extend throughout the lattice volume.


title:
A general classification scheme of detecting spatial and dynamical
  heterogeneities in super-cooled liquids

abstract:
  A computational approach via implementation of the Principle Component
Analysis (PCA) and Gaussian Mixture (GM) clustering methods from Machine
Learning (ML) algorithms to identify domain structures of supercooled liquids
is developed. Raw features data are collected from the coordination numbers of
particles smoothed using its radial distribution function and are used as an
order-parameter of disordered structures for GM clustering after dimensionality
reduction from the PCA. To transfer the knowledge from features(structural)
space to configurational space, another GM clustering is performed using the
Cartesian coordinates as an order-parameter with the particles' identity from
GM in the feature space. Both GM clustering are performed iteratively until
convergence. Results show the appearance of aggregated clusters of nano-domains
over sufficient long timescale both in structural and configurational spaces
with heterogeneous dynamics. More importantly, consistent nano-domains tilling
up the whole space regardless of the system size are observed and our approach
can be applied to any disordered systems.


title:
Aircraft Conflict Resolution with Trajectory Recovery Using
  Mixed-Integer Programming

abstract:
  To guarantee the safety of flight operations, decision-support systems for
air traffic control must be able to improve the usage of airspace capacity and
handle increasing demand. In this study, we address the aircraft conflict
avoidance and trajectory recovery problem. The problem of finding least
deviation conflict-free aircraft trajectories that guarantee the return to a
target waypoint is highly complex due to the nature of the nonlinear
trajectories that are sought. We present a two-stage iterative algorithm that
first solves initial conflict by manipulating their speed and heading control
and then identifying each aircraft's optimal time to recover its trajectory
towards their nominal. The avoidance stage extends existing mixed-integer
programming formulations, and for the recovery stage, we propose a novel
mixed-integer formulation. We assume that speed and heading control are
continuous variables for this approach while the recovery time is treated as a
discrete variable. In this approach, it is shown that the trajectory recovery
costs can be anticipated by inducing avoidance trajectories with higher
deviation, therefore obtaining earlier recovery time within few iterations.
Numerical results on benchmark conflict resolution problems show that this
approach can solve instances with up to 30 aircraft within 10 minutes.


title:
Joint Feature Learning and Relation Modeling for Tracking: A One-Stream
  Framework

abstract:
  The current popular two-stream, two-stage tracking framework extracts the
template and the search region features separately and then performs relation
modeling, thus the extracted features lack the awareness of the target and have
limited target-background discriminability. To tackle the above issue, we
propose a novel one-stream tracking (OSTrack) framework that unifies feature
learning and relation modeling by bridging the template-search image pairs with
bidirectional information flows. In this way, discriminative target-oriented
features can be dynamically extracted by mutual guidance. Since no extra heavy
relation modeling module is needed and the implementation is highly
parallelized, the proposed tracker runs at a fast speed. To further improve the
inference efficiency, an in-network candidate early elimination module is
proposed based on the strong similarity prior calculated in the one-stream
framework. As a unified framework, OSTrack achieves state-of-the-art
performance on multiple benchmarks, in particular, it shows impressive results
on the one-shot tracking benchmark GOT-10k, i.e., achieving 73.7% AO, improving
the existing best result (SwinTrack) by 4.3%. Besides, our method maintains a
good performance-speed trade-off and shows faster convergence. The code and
models will be available at https://github.com/botaoye/OSTrack.


title:
Resonance in Weight Space: Covariate Shift Can Drive Divergence of SGD
  with Momentum

abstract:
  Most convergence guarantees for stochastic gradient descent with momentum
(SGDm) rely on iid sampling. Yet, SGDm is often used outside this regime, in
settings with temporally correlated input samples such as continual learning
and reinforcement learning. Existing work has shown that SGDm with a decaying
step-size can converge under Markovian temporal correlation. In this work, we
show that SGDm under covariate shift with a fixed step-size can be unstable and
diverge. In particular, we show SGDm under covariate shift is a parametric
oscillator, and so can suffer from a phenomenon known as resonance. We
approximate the learning system as a time varying system of ordinary
differential equations, and leverage existing theory to characterize the
system's divergence/convergence as resonant/nonresonant modes. The theoretical
result is limited to the linear setting with periodic covariate shift, so we
empirically supplement this result to show that resonance phenomena persist
even under non-periodic covariate shift, nonlinear dynamics with neural
networks, and optimizers other than SGDm.


title:
Diagnosing Magnetic Fields in Cylindrical Implosions with Oblique Proton
  Radiography

abstract:
  Two experiments on the OMEGA Laser System used oblique proton radiography to
measure magnetic fields in cylindrical implosions with and without an applied
axial magnetic field. Although the goal of both experiments was to measure the
magnitude of the compressed axial magnetic field in the core of the implosion,
this field was obfuscated by two features in the coronal plasma produced by the
compression beams: an azimuthal self-generated magnetic field and small length
scale, high-amplitude structures attributed to collisionless effects. In order
to understand these features, synthetic radiographs are generated using fields
produced by 3-D HYDRA simulations. These synthetic radiographs reproduce the
features of the experimental radiographs with the exception of the small-scale
structures. A direct inversion algorithm is successfully applied to a synthetic
radiograph, but is only partially able to invert the experimental radiographs
in part because some protons are blocked by the field coils. The origins of the
radiograph features and their dependence on various experimental parameters are
explored. The results of this analysis should inform future measurements of
compressed axial magnetic fields in cylindrical implosions.


title:
The energy analyst's need for a standard that interprets the Global
  Information Infrastructure in the Metro Area

abstract:
  In this paper, we argue that the energy analyst's understanding of the metro
area network must be supported by a standard that (a) generalizes diversity,
through the means of the abstraction of the implementational model, while (b)
distinguishing between deployments through physical reference points. The need
for this kind of model has already been foreseen in the ITU-T's Recommendation
Y.110, including the need "to illustrate how system performance can be affected
by implementation." Preliminary results that concern the access network are
presented.


title:
On commutators of compact operators via block tridiagonalization:
  generalizations and limitations of Anderson's approach

abstract:
  We offer a new perspective and some advances on the 1971 Pearcy--Topping
problem: Is every compact operator a commutator of compact operators? Our goal
is to analyze and generalize the 1970's work in this area of Joel Anderson
combined with the work of the last named author of this paper. We reduce the
general problem to a simpler sequence of finite matrix equations with norm
constraints, while at the same time developing strategies for counterexamples.
Our approach is to ask which compact operators $T$ are commutators $AB-BA$ of
compact operators $A,B$; and to analyze the implications of Joel Anderson's
contributions to this problem, which will yield a generalization of his method.
By extending the techniques of Anderson [1] we obtain new classes of operators
that are commutators of compact operators beyond those obtained in [17] and
[2]. And by employing the techniques of the last named author [22], we found
obstructions to extending Anderson's techniques in terms of certain constraints
for $T$, with special focus on when $T$ is a strictly positive compact diagonal
operator. Some of these constraints involve general universal block tridiagonal
matrix forms for operators, and some involve $\mathcal{B(H)}$-ideal
constraints. And in terms of these matrix forms, we give some equivalences,
some sufficient conditions and some necessary conditions for this
Pearcy--Topping problem and its various offshoots to hold true. These matrix
forms are a sparsification of matrix representations of an operator (an
increase in the proportion of zeros in its corners by a change of basis) and we
measure the support density of these forms. And finally we provide some
necessary conditions for the Pearcy--Topping problem involving singular numbers
and $\mathcal{B(H)}$-ideal constraints.


title:
Commensurating HNN-extensions: hierarchical hyperbolicity and
  biautomaticity

abstract:
  We construct a CAT(0) hierarchically hyperbolic group (HHG) acting
geometrically on the product of a hyperbolic plane and a locally-finite tree
which is not biautomatic. This gives the first example of an HHG which is not
biautomatic, the first example of a non-biautomatic CAT(0) group of flat-rank
2, and the first example of an HHG which is injective but not Helly. Our proofs
heavily utilise the space of geodesic currents for a hyperbolic surface.


title: Federated Self-Supervised Learning for Acoustic Event Classification

abstract:
  Standard acoustic event classification (AEC) solutions require large-scale
collection of data from client devices for model optimization. Federated
learning (FL) is a compelling framework that decouples data collection and
model training to enhance customer privacy. In this work, we investigate the
feasibility of applying FL to improve AEC performance while no customer data
can be directly uploaded to the server. We assume no pseudo labels can be
inferred from on-device user inputs, aligning with the typical use cases of
AEC. We adapt self-supervised learning to the FL framework for on-device
continual learning of representations, and it results in improved performance
of the downstream AEC classifiers without labeled/pseudo-labeled data
available. Compared to the baseline w/o FL, the proposed method improves
precision up to 20.3\% relatively while maintaining the recall. Our work
differs from prior work in FL in that our approach does not require
user-generated learning targets, and the data we use is collected from our Beta
program and is de-identified, to maximally simulate the production settings.


title:
A pseudospectral method for investigating the stability of linear
  population models with two physiological structures

abstract:
  The asymptotic stability of the null equilibrium of a linear population model
with two physiological structures formulated as a first-order hyperbolic PDE is
determined by the spectrum of its infinitesimal generator. We propose an
equivalent reformulation of the problem in the space of absolutely continuous
functions in the sense of Carath\'eodory, so that the domain of the
corresponding infinitesimal generator is defined by trivial boundary
conditions. Via bivariate collocation, we discretize the reformulated operator
as a finite-dimensional matrix, which can be used to approximate the spectrum
of the original infinitesimal generator. Finally, we provide test examples
illustrating the converging behavior of the approximated eigenvalues and
eigenfunctions, and its dependence on the regularity of the model coefficients.


title:
A low-threshold diamond cryogenic detector for sub-GeV Dark Matter
  searches

abstract:
  In this work we report the realization of the first low-threshold cryogenic
detector that uses diamond as absorber for astroparticle physics applications.
We tested two 0.175$\,$g CVD diamond samples, each instrumented with a W-TES.
The sensors showed transitions at about 25 mK. We present the performance of
the diamond detectors and we highlight the best performing one, where we
obtained an energy threshold as low as 16.8 eV. This promising result lays the
foundation for the use of diamond for different fields of applications where
low threshold and excellent energy resolution are required, as i.e. light dark
matter searches and BSM physics with coherent elastic neutrino nucleus
scattering.


title: Text Transformations in Contrastive Self-Supervised Learning: A Review

abstract:
  Contrastive self-supervised learning has become a prominent technique in
representation learning. The main step in these methods is to contrast
semantically similar and dissimilar pairs of samples. However, in the domain of
Natural Language, the augmentation methods used in creating similar pairs with
regard to contrastive learning assumptions are challenging. This is because,
even simply modifying a word in the input might change the semantic meaning of
the sentence, and hence, would violate the distributional hypothesis. In this
review paper, we formalize the contrastive learning framework in the domain of
natural language processing. We emphasize the considerations that need to be
addressed in the data transformation step and review the state-of-the-art
methods and evaluations for contrastive representation learning in NLP.
Finally, we describe some challenges and potential directions for learning
better text representations using contrastive methods.


title: Mitigating Moral Hazard in Cyber Insurance Using Risk Preference Design

abstract:
  Cyber insurance is a risk-sharing mechanism that can improve cyber-physical
systems (CPS) security and resilience. The risk preference of the insured plays
an important role in cyber insurance markets. With the advances in information
technologies, it can be reshaped through nudging, marketing, or other types of
information campaigns. In this paper, we propose a framework of risk preference
design for a class of principal-agent cyber insurance problems. It creates an
additional dimension of freedom for the insurer for designing
incentive-compatible and welfare-maximizing cyber insurance contracts.
Furthermore, this approach enables a quantitative approach to reduce the moral
hazard that arises from information asymmetry between the insured and the
insurer. We characterize the conditions under which the optimal contract is
monotone in the outcome. This justifies the feasibility of linear contracts in
practice. This work establishes a metric to quantify the intensity of moral
hazard and create a theoretic underpinning for controlling moral hazard through
risk preference design. We use a linear contract case study to show numerical
results and demonstrate its role in strengthening CPS security.


title: An Inflationary Equation of State

abstract:
  We have studied inflationary paradigm through an inflationary equation of
state. With a single parameter equation of state as a function of the scalar
field responsible for accelerated expansion, we find an observationally viable
model satisfying all the constraints as laid down by the recent observations.
The resulting model can efficiently cover a wide range of tensor-to-scalar
ratio ranging from $r\sim\mathcal{O}(10^{-1})$ to $\mathcal{O}(10^{-6})$, other
inflationary observables being consistent with the latest data. Nowadays
ultimate eliminator between inflationary models is the tensor-to-scalar ratio,
the model presented here is capable of keeping up with the future probes of
tensor-to-scalar ratio at the same time having good agreement with other
inflationary observables.


title:
On block-wise and reference panel-based estimators for genetic data
  prediction in high dimensions

abstract:
  Genetic prediction of complex traits and diseases has attracted enormous
attention in precision medicine, mainly because it has the potential to
translate discoveries from genome-wide association studies (GWAS) into medical
advances. As the high dimensional covariance matrix (or the linkage
disequilibrium (LD) pattern) of genetic variants has a block-diagonal
structure, many existing methods attempt to account for the dependence among
variants in predetermined local LD blocks/regions. Moreover, due to privacy
restrictions and data protection concerns, genetic variant dependence in each
LD block is typically estimated from external reference panels rather than the
original training dataset. This paper presents a unified analysis of block-wise
and reference panel-based estimators in a high-dimensional prediction framework
without sparsity restrictions. We find that, surprisingly, even when the
covariance matrix has a block-diagonal structure with well-defined boundaries,
block-wise estimation methods adjusting for local dependence can be
substantially less accurate than methods controlling for the whole covariance
matrix. Further, estimation methods built on the original training dataset and
external reference panels are likely to have varying performance in high
dimensions, which may reflect the cost of having only access to summary level
data from the training dataset. This analysis is based on our novel results in
random matrix theory for block-diagonal covariance matrix. We numerically
evaluate our results using extensive simulations and the large-scale UK Biobank
real data analysis of 36 complex traits.


title: Topological Superconductivity in a two-dimensional Weyl SSH model

abstract:
  We study the emergence of topological superconductivity in a two-dimensional
(2D) Weyl system, composed of stacked Su-Schrieffer-Heeger (SSH) chains. A
previous analysis of the model showed that the addition of an attractive
Hubbard interaction between spinful electrons leads to a superconducting state
that has an intricate pairing structure, but is topologically trivial. Here we
consider a pairing interaction that couples spinless fermions on opposite
sublattices within the same unit cell. We observe that this physically
motivated, momentum-independent pairing interaction induces a topological
superconducting state, characterized by a gap function with a non-trivial
phase, as well as Majorana and Fermi arc edge states along the edge
perpendicular to the direction of the SSH dimerization. In addition, we observe
a transition as a function of pairing interaction strength and chemical
potential, indicated by a change in the sign of the topological charge carried
by each of the four Bogoliubov-Weyl nodes.


title: Sequential Bayesian Registration for Functional Data

abstract:
  In many modern applications, discretely-observed data may be naturally
understood as a set of functions. Functional data often exhibit two confounded
sources of variability: amplitude (y-axis) and phase (x-axis). The extraction
of amplitude and phase, a process known as registration, is essential in
exploring the underlying structure of functional data in a variety of areas,
from environmental monitoring to medical imaging. Critically, such data are
often gathered sequentially with new functional observations arriving over
time. Despite this, most available registration procedures are only applicable
to batch learning, leading to inefficient computation. To address these
challenges, we introduce a Bayesian framework for sequential registration of
functional data, which updates statistical inference as new sets of functions
are assimilated. This Bayesian model-based sequential learning approach
utilizes sequential Monte Carlo sampling to recursively update the alignment of
observed functions while accounting for associated uncertainty. As a result,
distributed computing, which is not generally an option in batch learning,
significantly reduces computational cost. Simulation studies and comparisons to
existing batch learning methods reveal that the proposed approach performs well
even when the target posterior distribution has a challenging structure. We
apply the proposed method to three real datasets: (1) functions of annual
drought intensity near Kaweah River in California, (2) annual sea surface
salinity functions near Null Island, and (3) PQRST complexes segmented from an
electrocardiogram signal.


title: On numbers not representable as $n + w(n)$

abstract:
  Let $w(n)$ be an additive non-negative integer-valued arithmetic function
which is equal to $1$ on primes. We study the distribution of $n + w(n)$ $\pmod
p$ and give a lower bound for the density of the set of numbers which are not
representable as $n + w(n)$.


title:
Certifying the Intersection of Reach Sets of Integrator Agents with
  Set-valued Input Uncertainties

abstract:
  We consider the problem of verifying safety for a pair of identical
integrator agents in continuous time with compact set-valued input
uncertainties. We encode this verification problem as that of certifying or
falsifying the intersection of their reach sets. We transcribe the same into a
variational problem, namely that of minimizing the support function of the
difference of the two reach sets over the unit sphere. We illustrate the
computational tractability of the proposed formulation by developing two cases
in detail, viz. when the inputs have time-varying norm-bounded and generic
hyperrectangular uncertainties. We show that the latter case allows distributed
certification via second order cone programming.


title:
Initial Log-Concavity in Power of Infinite Series Close to $(1 -
  z)^{-1}$

abstract:
  Using the analytic method of Odlyzko and Richmond, we show that if $f(z) =
\sum_n a_nz^n$ is an infinite series with $a_n \geq 1$ and $a_0 + \cdots + a_n
= O(n + 1)$ for all $n$, then a super-polynomially long initial segment of
$f^k(z)$ is log-concave. Furthermore, if $a_0 + \cdots + a_n = C(n + 1) + O((n
+ 1)^{\alpha})$ for constants $C > 1$ and $\alpha < 1$, we show that an
exponentially long initial segment of $f^k(z)$ is log-concave. This resolves a
conjecture of the author and Letong Hong in arXiv:2008.10069, and resolves a
conjecture of Heim and Neuhauser in arXiv:1810.02226 that the Nekrasov-Okounkov
polynomials $Q_n(z)$ are unimodal for sufficiently large $n$.


title:
Control of Multistability through Local Sensitivity Analysis:
  Application to Cellular Decision-making Networks

abstract:
  Control of multistable dynamical system has important applications, from
physics to biology. Here, we attack this problem from the perspective of local
sensitivity analysis. We develop sensitivity rules to control properties of
continuous-time multistable dynamics with simple attractors, namely, the
relative size and depth of their basins of attraction. Our parameter control
signal is computationally cheap and provides counter-intuitive information
about the sensitive parameters to be manipulated in an experimental setting.


title:
Baryon asymmetry from Barrow entropy: theoretical predictions and
  observational constraints

abstract:
  We investigate the generation of baryon asymmetry from the corrections
brought about in the Friedman equations due to Barrow entropy. In particular,
by applying the gravity-thermodynamics conjecture one obtains extra terms in
the Friedmann equations that change the Hubble function evolution during the
radiation-dominated epoch. Hence, even in the case of standard coupling between
the Ricci scalar and baryon current they can lead to a non-zero baryon
asymmetry. In order to match observations we find that the Barrow exponent
should lie in the interval $0.005 \lesssim \Delta \lesssim 0.008$, which
corresponds to a slight deviation from the standard Bekenstein-Hawking entropy.
The upper bound is tighter than the one of other observational constraints,
however the interesting feature is that in the present analysis we obtain a
non-zero lower bound. Nevertheless this lower bound would disappear if the
baryon asymmetry in Barrow-modified cosmology is generated by other mechanisms,
not related to the Barrow modification.


title:
Merging Knockout and Round-Robin Tournaments: A Flexible Linear
  Elimination Tournament Design

abstract:
  We propose a new tournament structure that combines the popular knockout
tournaments and the round-robin tournaments. As opposed to the extremes of
divisive elimination and no elimination, our tournament aims to eliminate the
participants as linearly as possible as a form of subtractive elimination. Our
design is flexible in the sense that it can be adapted to any number of players
$N$ and any number of matches $M$. Our design satisfies many properties that
are desirable for a tournament to select a winner and can be adapted to rank
all the participating players.


title:
The role of post-selection in generating vortex particles of arbitrary
  mass, spin, and energy

abstract:
  There exist many methods to obtain twisted photons with an orbital angular
momentum. However, despite the big interest in generating massive particles
with the phase vortices, the available diffraction techniques are only
applicable to the moderately relativistic beams of electron microscopes, to
cold neutrons, or non-relativistic atoms. To bring the matter waves physics
into the high energy domain, one needs to develop alternative methods,
applicable for ultrarelativistic energies and for composite particles,
including ions, and nuclei. Here, we show that vortex particles of arbitrary
mass, spin, and energy, including muons, hadrons, nuclei, and heavy ions, can
be generated during photon emission in helical undulators, via Cherenkov
radiation, in collisions of charged particles with intense laser beams, in such
scattering or annihilation processes as $e\mu \to e\mu, ep \to ep, e^-e^+ \to
p\bar{p}$, etc. We argue that the key element in obtaining such quantum states
is the post-selection protocol due to quantum entanglement between a pair of
the final particles and it is largely not the process itself and, in contrast
to the classical theory, not the trajectory of the emitting wave-packet's
centroid. The state of a final particle -- be it a photon, a proton, or a
nucleus -- becomes twisted if the azimuthal angle of the other particle's
momentum is weakly measured with a large error or not measured at all, which is
often the case when the scattering angle is small. As a result, the
requirements to the beam transverse coherence can be greatly relaxed, which
enables the generation of vortex particles at accelerators and synchrotron
radiation facilities, thus making them a new tool for hadronic and spin
studies. This weak-measurement technique can also facilitate the development of
sources of $\gamma$-range twisted photons for the purposes of nuclear and
particle physics.

categories: hep-ph physics.acc-ph physics.optics quant-ph


title: Census L-space knots are braid positive, except for one that is not

abstract:
  We exhibit braid positive presentations for all L-space knots in the SnapPy
census except one, which is not braid positive. The normalized HOMFLY
polynomial of o9_30634, when suitably normalized is not positive, failing a
condition of Ito for braid positive knots.
  We generalize this knot to a 1-parameter family of hyperbolic L-space knots
that might not be braid positive. Nevertheless, as pointed out by Teragaito,
this family yields the first examples of hyperbolic L-space knots whose formal
semigroups are actual semigroups, answering a question of Wang. Furthermore,
the roots of the Alexander polynomials of these knots are all roots of unity,
disproving a conjecture of Li-Ni.


title: Electric Dipole Moment Measurements at Storage Rings

abstract:
  Electric Dipole Moments (EDMs) of subatomic particles, are considered as one
of the most powerful tools to study CP-violation beyond the Standard Model.
Such CP-violating mechanisms are searched for to explain the dominance of
matter over anti-matter in our universe. This paper discusses EDM searches of
charged hadrons in storage rings.
  The document focuses on activities at the existing storage ring COSY at
Forschungszentrum J\"ulich, Germany and the design of a 100\,m circumference
prototype ring able to demonstrate key technologies and components. These
include simultaneous clockwise and counter-clockwise beam operation with
electrostatic bending elements and, by adding a magnetic field, the frozen spin
technique.


title: Modern Physics demonstrations with DIY Smartphone Spectrometers

abstract:
  Smartphones are widely available and used extensively by students worldwide.
These phones often come equipped with high-quality cameras that can be combined
with basic optical elements to build a cost-effective DIY spectrometer. Here,
we discuss a series of demonstrations and pedagogical exercises, accompanied by
our DIY diffractive spectrometer that uses a free web platform for instant
spectral analysis. Specifically, these demonstrations can be used to encourage
hands-on and inquiry-based learning of wave optics, broadband vs discrete light
emission, quantization, Heisenberg's energy-time uncertainty relation, and the
use of spectroscopy in day-to-day life. Hence, these simple tools can be
readily deployed in high school classrooms to communicate the practices of
science.


title: Learning Geodesic-Aware Local Features from RGB-D Images

abstract:
  Most of the existing handcrafted and learning-based local descriptors are
still at best approximately invariant to affine image transformations, often
disregarding deformable surfaces. In this paper, we take one step further by
proposing a new approach to compute descriptors from RGB-D images (where RGB
refers to the pixel color brightness and D stands for depth information) that
are invariant to isometric non-rigid deformations, as well as to scale changes
and rotation. Our proposed description strategies are grounded on the key idea
of learning feature representations on undistorted local image patches using
surface geodesics. We design two complementary local descriptors strategies to
compute geodesic-aware features efficiently: one efficient binary descriptor
based on handcrafted binary tests (named GeoBit), and one learning-based
descriptor (GeoPatch) with convolutional neural networks (CNNs) to compute
features. In different experiments using real and publicly available RGB-D data
benchmarks, they consistently outperforms state-of-the-art handcrafted and
learning-based image and RGB-D descriptors in matching scores, as well as in
object retrieval and non-rigid surface tracking experiments, with comparable
processing times. We also provide to the community a new dataset with accurate
matching annotations of RGB-D images of different objects (shirts, cloths,
paintings, bags), subjected to strong non-rigid deformations, for evaluation
benchmark of deformable surface correspondence algorithms.


title:
A Rokhlin Lemma for Noninvertible Totally-Ordered Measure-Preserving
  Dynamical Systems

abstract:
  Let $(X,\mathcal{F},\mu,T)$ be a not necessarily invertible non-atomic
measure-preserving dynamical system where the $\sigma$-algebra $\mathcal{F}$ is
generated by the intervals according to some total order. The main result is
that the classical Rokhlin lemma may be adapted to such a situation assuming a
slight extension of aperiodicity. This result is compared to previous
noninvertible versions of the Rokhlin lemma.


title: Quantum Cryptanalysis of Farfalle and (Generalised) Feistel Network

abstract:
  Farfalle is a permutation-based pseudo-random function which has been
proposed by G. Bertoni et al. in 2017. In this work, we show that by observing
suitable inputs to Farfalle, one can derive various constructions of a periodic
function with a period that involves a secret key. As this admits the
application of Simon's algorithm in the so-called Q2 attack model, we further
show that in the case when internal rolling function is linear, then the secret
key can be extracted under feasible assumptions. Furthermore, using the
provided constructions of periodic functions for Farfalle, we show that one can
mount forgery attacks on the session-supporting mode for authenticated
encryption (Farfalle-SAE) and the synthetic initial value AE mode
(Farfalle-SIV). In addition, as the wide block cipher mode Farfalle-WBC is a
4-round Feistel scheme, a quantum distinguisher is constructed in the case when
input branches are containing at last two blocks, where length of one block
corresponds to the size of a permutation employed in Farfalle (a similar attack
can be mounted to Farfalle-WBC-AE). And finally, we consider the problem of
extracting a secret round key out of different periods obtained from a
(Generalized) Feistel scheme (GFN), which has not been addressed in any of the
previous works which consider the application of Simon's (or Simon-Grover)
algorithm to round reduced versions of GFNs. In this part, we assume that the
key is added to an input of an inner function utilized in the round function of
a given GFN. By applying two different interpolation formulas, we show that one
can extract the round key by utilizing amount of different periods which is
closely related to the polynomial/algebraic degree of underlying inner
function.


title:
OSSCAR, an open platform for collaborative development of computational
  tools for education in science

abstract:
  In this paper we present the Open Software Services for Classrooms and
Research (OSSCAR) platform. OSSCAR provides an open collaborative environment
to develop, deploy and access educational resources in the form of web
applications. To minimize efforts in the creation and use of new educational
material, it combines software tools that have emerged as standards with custom
domain-specific ones. The technical solutions adopted to create and distribute
content are described and motivated on the basis of reliability,
sustainability, ease of uptake and use. Examples from courses in the domains of
physics, chemistry, and materials science are shown to demonstrate the style
and level of interactivity of typical applications. The tools presented are
easy to use, and create a uniform and open environment exploitable by a large
community of teachers, students, and researchers with the goal of facilitating
learning and avoiding, when possible, duplication of efforts in creating
teaching material. Contributions to expand the educational content of the
OSSCAR project are welcome.


title:
Thermodynamic inference in partially accessible Markov networks: A
  unifying perspective from transition-based waiting time distributions

abstract:
  The inference of thermodynamic quantities from the description of an only
partially accessible physical system is a central challenge in stochastic
thermodynamics. A common approach is coarse-graining, which maps the dynamics
of such a system to a reduced effective one. While coarse-graining states of
the system into compound ones is a well studied concept, recent evidence hints
at a complementary description by considering observable transitions and
waiting times. In this work, we consider waiting time distributions between two
consecutive transitions of a partially observable Markov network. We formulate
an entropy estimator using their ratios to quantify irreversibility. Depending
on the complexity of the underlying network, we formulate criteria to infer
whether the entropy estimator recovers the full physical entropy production or
whether it just provides a lower bound that improves on established results.
This conceptual approach, which is based on the irreversibility of underlying
cycles, additionally enables us to derive estimators for the topology of the
network, i.e., the presence of a hidden cycle, its number of states and its
driving affinity. Adopting an equivalent semi-Markov description, our results
can be condensed into a fluctuation theorem for the corresponding semi-Markov
process. This mathematical perspective provides a unifying framework for the
entropy estimators considered here and established earlier ones. The crucial
role of the correct version of time-reversal helps to clarify a recent debate
on the meaning of formal versus physical irreversibility. Extensive numerical
calculations based on a direct evaluation of waiting-time distributions
illustrate our exact results and provide an estimate on the quality of the
bounds for affinities of hidden cycles.