title:
Agree to Disagree: Diversity through Disagreement for Better
  Transferability

abstract:
  Gradient-based learning algorithms have an implicit simplicity bias which in
effect can limit the diversity of predictors being sampled by the learning
procedure. This behavior can hinder the transferability of trained models by
(i) favoring the learning of simpler but spurious features -- present in the
training data but absent from the test data -- and (ii) by only leveraging a
small subset of predictive features. Such an effect is especially magnified
when the test distribution does not exactly match the train distribution --
referred to as the Out of Distribution (OOD) generalization problem. However,
given only the training data, it is not always possible to apriori assess if a
given feature is spurious or transferable. Instead, we advocate for learning an
ensemble of models which capture a diverse set of predictive features. Towards
this, we propose a new algorithm D-BAT (Diversity-By-disAgreement Training),
which enforces agreement among the models on the training data, but
disagreement on the OOD data. We show how D-BAT naturally emerges from the
notion of generalized discrepancy, as well as demonstrate in multiple
experiments how the proposed method can mitigate shortcut-learning, enhance
uncertainty and OOD detection, as well as improve transferability.


title:
Towards Empirical Process Theory for Vector-Valued Functions: Metric
  Entropy of Smooth Function Classes

abstract:
  This paper provides some first steps in developing empirical process theory
for functions taking values in a vector space. Our main results provide bounds
on the entropy of classes of smooth functions taking values in a Hilbert space,
by leveraging theory from differential calculus of vector-valued functions and
fractal dimension theory of metric spaces. We demonstrate how these entropy
bounds can be used to show the uniform law of large numbers and asymptotic
equicontinuity of the function classes, and also apply it to statistical
learning theory in which the output space is a Hilbert space. We conclude with
a discussion on the extension of Rademacher complexities to vector-valued
function classes.


title:
Bounded weak solution and long time behavior of a degenerate particle
  flow model

abstract:
  In this paper it is proved that a strongly degenerate parabolic equation with
a given critical density $\rho_{cr}$, derived from a density dependent particle
flow model, has a global bounded weak solution. The solution is shown to
converge towards a steady state as $t\to\infty$; when the average density
$\rho_{\infty}$ is larger than $\rho_{cr}$ the steady state coincides with
$\rho_{\infty}$ and the convergence rate is exponential with respect to the
$L^2$ norm, while in the case that $\rho_{\infty}<\rho_{cr}$ the steady state
is unknown and the convergence is algebraic with respect to the 2-Wasserstein
metric. A formal reformulation of the system as a nondegenerate free boundary
problem is also shown under suitable assumptions on the initial data. Finally
numerical experiments in the 2-dimensional case are presented, which show that
segregation phenomena can appear when the initial average density is smaller
than the critical density.


title:
On integral bases and monogenity of pure octic number fields with
  non-square free parameters

abstract:
  In all available papers, on power integral bases of pure octic number fields
$K$, generated by a root $\alpha$ of a monic irreducible polynomial
$f(x)=x^8-m\in\mathbf Z[x]$, it was assumed that $m\neq \pm 1$ is square free.
In this paper, we investigate the monogenity of any pure octic number field,
without the condition that $m$ is square free. We start by calculating an
integral basis of $\mathbf Z_K$, the ring of integers of $K$. In particular, we
characterize when $\mathbf Z_K=\mathbf Z[\alpha]$. We give sufficient
conditions on $m$, which guarantee that $K$ is not monogenic. We finish the
paper by investigating the case when $m=a^u$, $u\in\{1,3,5,7\}$ and $a\neq \mp
1$ is a square free rational integer.


title: Riemann-Roch for stacky matrix factorizations

abstract:
  We establish a Hirzebruch-Riemann-Roch type theorem and
Grothendieck-Riemann-Roch type theorem for matrix factorizations on quotient
Deligne-Mumford stacks. For this we first construct a
Hochschild-Kostant-Rosenberg type isomorphism explicit enough to yield a
categorical Chern character formula. We next find an expression of the
canonical pairing of Shklyarov under the isomorphism.


title: Cup product in bounded cohomology of negatively curved manifolds

abstract:
  Let $M$ be a negatively curved compact Riemannian manifold with (possibly
empty) convex boundary. Every closed differential $2$-form $\xi\in\Omega^2(M)$
defines a bounded cocycle $c_\xi\in C_b^2(M)$ by integrating $\xi$ over
straightened $2$-simplices. In particular Barge and Ghys proved that, when $M$
is a closed hyperbolic surface, $\Omega^2(M)$ injects this way in $H_b^2(M)$ as
an infinite dimensional subspace. We show that any class of the form $[c_\xi]$,
where $\xi$ is an exact differential 2-form, belongs to the radical of the cup
product on the graded algebra $H_b^\bullet(M)$.


title: PRAiSE: Resolved spectral evolution in simulated radio sources

abstract:
  We present a method for applying spatially resolved adiabatic and radiative
loss processes to synthetic radio emission from hydrodynamic simulations of
radio sources from active galactic nuclei (AGN). Lagrangian tracer particles,
each representing an ensemble of electrons, are injected into simulations and
the position, grid pressure, and time since the last strong shock are recorded.
These quantities are used to track the losses of the electron packet through
the radio source in a manner similar to the Radio AGN in Semi-analytic
Environments (RAiSE) formalism, which uses global source properties to
calculate the emissivity of each particle ex-situ. Freedom in the choice of
observing parameters, including redshift, is provided through the
post-processing nature of this approach. We apply this framework to simulations
of jets in different environments, including asymmetric ones. We find a strong
dependence of radio source properties on frequency and redshift, in good
agreement with observations and previous modelling work. There is a strong
evolution of radio spectra with redshift due to the more prominent
inverse-Compton losses at high redshift. Radio sources in denser environments
have flatter spectral indices, suggesting that spectral index asymmetry may be
a useful environment tracer. We simulate intermediate Mach number jets that
disrupt before reaching the tip of the lobe, and find that these retain an
edge-brightened Fanaroff-Riley Type II morphology, with the most prominent
emission remaining near the tip of the lobes for all environments and redshifts
we study.


title:
On $K$-stability of $\mathbb{P}^3$ blown up along the disjoint union of
  a twisted cubic curve and a line

abstract:
  We find all K-polystable smooth Fano threefolds that can be obtained as
blowup of projective space along the disjoint union of a twisted cubic curve
and a line.


title:
Can a Single Population Account for the Discriminant Properties in Fast
  Radio Bursts?

abstract:
  To probe this question, we perform a statistical analysis using the first
Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB)
catalog and identify a few discriminant properties between repeating and
non-repeating FRBs such as the repetition rate, duration, bandwidth, spectral
index, peak luminosity, and potential peak frequency. If repeating and
non-repeating FRBs belong to one population, their distribution distinctions
for the repetition rate and duration can be explained by the selection effect
due to the beamed emission as in Connor et al. (2020). However, we obtain that
the distribution distinctions for the spectral index and potentially the peak
frequency cannot be explained by the beamed emission within the framework of
either the coherent curvature radiation or synchrotron maser emission. This
indicates that there could be two populations. We further discuss three
possible scenarios for the required two populations.


title:
Active Brownian particles in external force fields: field-theoretical
  models, generalized barometric law, and programmable density patterns

abstract:
  We investigate the influence of external forces on the collective dynamics of
interacting active Brownian particles in two as well as three spatial
dimensions. Via explicit coarse graining, we derive predictive models that are
applicable for space- and time-dependent external force fields. We study these
models for the cases of gravity and harmonic traps. In particular, we derive a
generalized barometric formula for interacting active Brownian particles under
gravity that is valid for low to high concentrations and activities of the
particles. Furthermore, we show that one can use an external harmonic trap to
induce motility-induced phase separation in systems that, without external
fields, remain in a homogeneous state. This finding makes it possible to
realize programmable density patterns in systems of active Brownian particles.
Our analytic predictions are found to be in very good agreement with Brownian
dynamics simulations.

categories: cond-mat.soft cond-mat.mes-hall cond-mat.stat-mech nlin.AO


title:
External sources in a minimal and nonminimal CPT-odd Lorentz violating
  Maxwell electrodynamics

abstract:
  This paper is devoted to the study of interactions between stationary
electromagnetic sources for the minimal and nonminimal CPT-odd photon sector of
the Standard Model Extension (SME), where we search mainly for physical
phenomena not present in the Maxwell electrodynamics. First we consider the
minimal CPT-odd sector, where the Lorentz violation is caused by the
Carroll-Field-Jackiw (CFJ) term, namely
$\sim\epsilon^{\mu\nu\alpha\beta}\left(k_{AF}\right)_{\mu}A_{\nu}F_{\alpha\beta}$,
and we treat the Lorentz breaking parameter $\left(k_{AF}\right)^{\mu}$
perturbatively up to second order. We consider effects due to the presence of
point-like charges, Dirac strings and point-like dipoles. In special, we
calculate the electromagnetic field produced outside the string and investigate
the so called Aharonov-Bohm bound states in Lorentz violation context. After,
we consider a model where the Lorentz violation is generated by the
higher-derivative version of the CFJ model, namely
$\sim\epsilon^{\mu\nu\alpha\beta}V_{\mu}A_{\nu}\Box F_{\alpha\beta}$, which is
a dimension five term of the CPT-odd sector of the nonminimal SME. For this
higher-derivative model, we obtain effects up to second order in $V^{\mu}$
related to the presence of point-like charges and a steady current line. We use
overestimated constrains for the Lorentz violation parameters in order to
investigate the physical relevance of some results found in atomic systems. We
also make an overestimate for the background vectors using experimental data
from the atomic electric field.


title:
First observation of a quadruple asteroid -- Detection of a third moon
  around (130) Elektra with SPHERE/IFS

abstract:
  Aims. We aim to increase the contrast limits to detect new satellites
orbiting known asteroids. We use cutting-edge data reduction techniques and
data processing algorithms that are essential to best analyse the raw data
provided by the instruments and increase their performances. Doing so, the
unequalled performances of SPHERE also make it a unique tool to resolve and
study asteroids in the solar system, expanding the domain of its main science
targets.
  Methods. We applied a newly developed data reduction pipeline for integral
field spectrographs on archival SPHERE data of a resolved asteroid, (130)
Elektra. It was coupled with a dedicated point spread function reconstruction
algorithm to model the asteroid halo. Following the halo removal, the moon
signal could be extracted more accurately. The moon positions were fitted at
three epochs and were used to derive the orbital parameters via a genetic-based
algorithm.
  Results. We announce the discovery of S/2014 (130) 2, a third moon orbiting
(130) Elektra, making it the first quadruple asteroid ever found. It is
identified in three different epochs, 9, 30, and 31 Dec. 2014, at a respective
angular separation of 258 mas (333 km), 229 mas (327 km), and 319 mas (457 km).
We estimate that this moon has a period of 0.679 day and a semi-major axis of
344 km, with an eccentricity of 0.33 and an inclination of 38 degrees compared
to the primary rotation axis. With a relative magnitude to the primary of 10.5,
its size is estimated to be 1.6 km.


title: Deep Feature Rotation for Multimodal Image Style Transfer

abstract:
  Recently, style transfer is a research area that attracts a lot of attention,
which transfers the style of an image onto a content target. Extensive research
on style transfer has aimed at speeding up processing or generating
high-quality stylized images. Most approaches only produce an output from a
content and style image pair, while a few others use complex architectures and
can only produce a certain number of outputs. In this paper, we propose a
simple method for representing style features in many ways called Deep Feature
Rotation (DFR), while not only producing diverse outputs but also still
achieving effective stylization compared to more complex methods. Our approach
is representative of the many ways of augmentation for intermediate feature
embedding without consuming too much computational expense. We also analyze our
method by visualizing output in different rotation weights. Our code is
available at https://github.com/sonnguyen129/deep-feature-rotation.


title:
Revisiting QMIX: Discriminative Credit Assignment by Gradient Entropy
  Regularization

abstract:
  In cooperative multi-agent systems, agents jointly take actions and receive a
team reward instead of individual rewards. In the absence of individual reward
signals, credit assignment mechanisms are usually introduced to discriminate
the contributions of different agents so as to achieve effective cooperation.
Recently, the value decomposition paradigm has been widely adopted to realize
credit assignment, and QMIX has become the state-of-the-art solution. In this
paper, we revisit QMIX from two aspects. First, we propose a new perspective on
credit assignment measurement and empirically show that QMIX suffers limited
discriminability on the assignment of credits to agents. Second, we propose a
gradient entropy regularization with QMIX to realize a discriminative credit
assignment, thereby improving the overall performance. The experiments
demonstrate that our approach can comparatively improve learning efficiency and
achieve better performance.


title: Adapting to Mixing Time in Stochastic Optimization with Markovian Data

abstract:
  We consider stochastic optimization problems where data is drawn from a
Markov chain. Existing methods for this setting crucially rely on knowing the
mixing time of the chain, which in real-world applications is usually unknown.
We propose the first optimization method that does not require the knowledge of
the mixing time, yet obtains the optimal asymptotic convergence rate when
applied to convex problems. We further show that our approach can be extended
to: (i) finding stationary points in non-convex optimization with Markovian
data, and (ii) obtaining better dependence on the mixing time in temporal
difference (TD) learning; in both cases, our method is completely oblivious to
the mixing time. Our method relies on a novel combination of multi-level Monte
Carlo (MLMC) gradient estimation together with an adaptive learning method.


title:
Mass gap for a monopole interacting with different nonlinear spinor
  fields

abstract:
  We study the properties of the mass gap for monopole solutions in SU(2)
Yang-Mills theory with a source of the non-Abelian gauge field in the form of a
spinor field described by the nonlinear Dirac equation. Different types of
nonlinearities parameterized by the parameter $\lambda$ are under
consideration. It is shown that for the range of values of this parameter
studied in the present paper the value of the mass gap depends monotonically on
this parameter, and the position of the mass gap does not practically depend on
$\lambda$.


title: Reappraisal of the minimal flavoured $Z^{\prime}$ scenario

abstract:
  Recent results from the intensity frontier indicate the tantalizing
possibility of violation in lepton flavour universality. In light of this we
revisit the minimal phenomenological $Z'$ model taking in account both
vectorial and axial-vectorial flavour violating coupling in the leptonic
sector. We make a systematic study to identify the minimal framework that can
simultaneously explain the recent results on anomalous magnetic moment of muon
and electron while remaining in consonance with $R_{K^{(*)}}$,
$B^0_s-\bar{B^0_s}$ mixing and angular observables in the $B^+\to K^{+*}
\mu^+\mu^-$ channel reported by the LHCb collaboration.


title:
Assessing the alignment between the information needs of developers and
  the documentation of programming languages: A case study on Rust

abstract:
  Programming language documentation refers to the set of technical documents
that provide application developers with a description of the high-level
concepts of a language. Such documentation is essential to support application
developers in the effective use of a programming language. One of the
challenges faced by documenters (i.e., personnel that produce documentation) is
to ensure that documentation has relevant information that aligns with the
concrete needs of developers. In this paper, we present an automated approach
to support documenters in evaluating the differences and similarities between
the concrete information need of developers and the current state of
documentation (a problem that we refer to as the topical alignment of a
programming language documentation). Our approach leverages semi-supervised
topic modelling to assess the similarities and differences between the topics
of Q&A posts and the official documentation. To demonstrate the application of
our approach, we perform a case study on the documentation of Rust. Our results
show that there is a relatively high level of topical alignment in Rust
documentation. Still, information about specific topics is scarce in both the
Q&A websites and the documentation, particularly related topics with
programming niches such as network, game, and database development. For other
topics (e.g., related topics with language features such as structs, patterns
and matchings, and foreign function interface), information is only available
on Q&A websites while lacking in the official documentation. Finally, we
discuss implications for programming language documenters, particularly how to
leverage our approach to prioritize topics that should be added to the
documentation.


title: Entropy of the Universe and Hierarchical Dark Matter

abstract:
  We discuss the relationship between dark matter and the entropy of the
universe with the premise that dark matter exists in the form of primordial
black holes (PBHs) in a hierarchy of mass tiers. The lightest tier are
intermediate-mass PIMBHs within galaxies including the Milky Way. Supermassive
black holes at galactic centres are in the second tier. We are led to speculate
that there exists a third tier of extremely massive PBHs, more massive than
entire galaxies. We discuss future observations by the Rubin Observatory and
James Webb Space Telescope.


title:
Co-WIN: Really Winning? Analysing Inequity in India's Vaccination
  Response

abstract:
  The COVID-19 pandemic has so far accounted for reported 5.5M deaths
worldwide, with 8.7% of these coming from India. The pandemic exacerbated the
weakness of the Indian healthcare system. As of January 20, 2022, India is the
second worst affected country with 38.2M reported cases and 487K deaths.
According to epidemiologists, vaccines are an essential tool to prevent the
spread of the pandemic. India's vaccination drive began on January 16, 2021
with governmental policies being introduced to prioritize different populations
of the society. Through the course of the vaccination drive, multiple new
policies were also introduced to ensure that vaccines are readily available and
vaccination coverage is increased. However, at the same time, some of the
government policies introduced led to unintended inequities in the populations
being targeted. In this report, we enumerate and analyze the inequities that
existed in India's vaccination policy drive, and also compute the effect of the
new policies that were introduced. We analyze these potential inequities not
only qualitatively but also quantitatively by leveraging the data that was made
available through the government portals. Specifically, (a) we discover
inequities that might exist in the policies, (b) we quantify the effect of new
policies introduced to increase vaccination coverage, and (c) we also point the
data discrepancies that exist across different data sources.


title: Fabry-P\'{e}rot interference in 2D low-density Rashba gas

abstract:
  In mesoscopic electronic systems, the Fabry-P\'{e}rot (FP) oscillation is
observed in various 1D devices. As for higher dimensions, numerous transverse
channels usually lead to dephasing that quenches the overall oscillation of the
conductance. Up to now, the FP oscillation in 2D electronic systems is only
reported in graphene-based devices, and very recently, the \emph{pn} junctions
of inverted InAs/GaSb double quantum well [Phys. Rev. X 10, 031007 (2020)]. In
the latter, the band shape of a sombrero hat plays an essential role, which
introduces a novel mechanism of electron-hole hybridization for the 2D FP
oscillation. In this work, we propose that such a scenario can be generalized
to the 2D planar junction composed of low-density Rashba gas, where the band
bottom possesses a sombrero hat shape as well. We show that the backscattering
between the outer and inner Fermi circles dominates the FP interference and
significantly suppresses the dephasing effect between different transverse
channels, which leads to a visible oscillation of the tunneling conductance.
Specially, the visibility of the oscillating pattern can be enhanced by
applying interface barriers, in contrast to that in the InAs/GaSb double
quantum well. Our results provide a promising way for the implementation of the
FP oscillation in the 2D electron gas.


title:
Standing Sausage Perturbations in solar coronal loops with diffuse
  boundaries: An initial-value-problem perspective

abstract:
  Working in pressureless magnetohydrodynamics, we examine the consequences of
some peculiar dispersive properties of linear fast sausage modes (FSMs) in
one-dimensional cylindrical equilibria with a continuous radial density profile
($\rho_0(r)$). As recognized recently on solid mathematical grounds, cutoff
axial wavenumbers may be absent for FSMs when $\rho_0(r)$ varies sufficiently
slowly outside the nominal cylinder. Trapped modes may therefore exist for
arbitrary axial wavenumbers and density contrasts, their axial phase speeds in
the long-wavelength regime differing little from the external Alfv$\acute{\rm
e}$n speed. If these trapped modes indeed show up in the solutions to the
associated initial value problem (IVP), then FSMs have a much better chance to
be observed than expected with classical theory, and can be invoked to account
for a considerably broader range of periodicities than practiced. However, with
axial fundamentals in active region loops as an example, we show that this
long-wavelength expectation is not seen in our finite-difference solutions to
the IVP, the reason for which is then explored by superposing the necessary
eigenmodes to re-solve the IVP. At least for the parameters we examine, the
eigenfunctions of trapped modes are characterized by a spatial extent well
exceeding the observationally reasonable range of the spatial extent of initial
perturbations, meaning a negligible fraction of energy that a trapped mode can
receive. We conclude that the absence of cutoff wavenumbers for FSMs in the
examined equilibrium does not guarantee a distinct temporal behavior.


title:
Anomalous Long-Range Fluctuations in Homogeneous Fluid Phase of Active
  Brownian Particles

abstract:
  We numerically investigate active Brownian particles with a finite mass for a
wide range of activities. When the mass is sufficiently large, the motility
induced phase separation (MIPS) is suppressed even when the activities are
large, and the system remains spatially homogeneous. Thus obtained uniform
fluids are an ideal system to study the non-equilibrium fluctuations without
being impeded by heterogeneous structures caused by MIPS. We find that velocity
correlation becomes long-ranged, and concomitantly the system develops the
vortex-like structure reminiscent of active turbulence. A length scale of the
transverse velocity associated with vortexes is found to be substantially
shorter than the longitudinal counterpart. Escorted by the longitudinal
velocity field, the density fluctuations also become long-ranged. Surprisingly,
the giant number fluctuation (GNF) arises due to the growth of the density
fluctuations. Our findings suggest the universality and ubiquitousness of
long-range fluctuations in homogeneous active fluids.


title:
Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction in Weyl semimetals with
  tilted energy dispersion

abstract:
  Ruderman-Kittel-Kasuya-Yosida (RKKY) is an essential long range magnetic
interaction between magnetic impurities or magnetic layered structures, the
magnitude of which oscillates with the distance ($\mathrm{R}$) between them. We
have investigated the RKKY interaction between two magnetic impurities in both
time-reversal and inversion symmetry broken Weyl semimetals (WSMs) where the
energy dispersion is tilted in momentum space and the momentum of the
conduction electron is locked with the pseudo-spin. Two important features are
revealed, firstly, at the small tilt limit, we show that the RKKY coupling
varies quadratically with the tilt parameter and strikingly, at large
separation distance $\mathrm{R}$, the coupling decays as $1/\mathrm{R}$
compared to the conventional of $1/\mathrm{R}^{3}$ dependence exhibited by WSMs
with non-tilted dispersion. The slower decay by two orders i.e. ($1/\mathrm{R}$
as opposed to $1/\mathrm{R}^{3}$) of the RKKY coupling is significant for
maintaining long range RKKY coupling. Secondly, the RKKY coupling exhibits an
anisotropy with respect to the angle between the tilt direction ($\mathbf{w}$)
and the separation direction $\mathbf{R}$ unlike the case of non-tilted WSMs
which exhibit isotropic RKKY coupling. Consequently, the RKKY coupling in
tilted WSMs alternately favours ferromagnetic and anti-ferromagnetic orders and
vice-versa with the change of the angle. Our results are derived analytically
and verified by numerical calculations based on realistic parameter values.


title: An electrically-driven single-atom `flip-flop' qubit

abstract:
  The spins of atoms and atom-like systems are among the most coherent objects
in which to store quantum information. However, the need to address them using
oscillating magnetic fields hinders their integration with quantum electronic
devices. Here we circumvent this hurdle by operating a single-atom `flip-flop'
qubit in silicon, where quantum information is encoded in the electron-nuclear
states of a phosphorus donor. The qubit is controlled using local electric
fields at microwave frequencies, produced within a metal-oxide-semiconductor
device. The electrical drive is mediated by the modulation of the
electron-nuclear hyperfine coupling, a method that can be extended to many
other atomic and molecular systems. These results pave the way to the
construction of solid-state quantum processors where dense arrays of atoms can
be controlled using only local electric fields.


title: Is gravitational collapse possible in $f(R)$ gravity?

abstract:
  Gravitational collapse is still poorly understood in the context of $f(R)$
theories of gravity, since the Oppenheimer-Snyder model is incompatible with
their junction conditions. In this work, we will present a systematic approach
to the problem. Starting with a thorough analysis of how the Oppenheimer-Snyder
construction should be generalised to fit within metric $f(R)$ gravity, we
shall subsequently proceed to explore the existence of novel exterior solutions
compatible with physically viable interiors. Our formalism has allowed us to
show that some paradigmatic vacuum metrics cannot represent spacetime outside a
collapsing dust star in metric $f(R)$ gravity. Moreover, using the junction
conditions, we have found a novel vacuole solution of a large class of $f(R)$
models, whose exterior spacetime is documented here for the first time in the
literature as well. Finally, we also report the previously unnoticed fact that
the Oppenheimer-Snyder model of gravitational collapse is incompatible with the
Palatini formulation of $f(R)$ gravity.


title:
On Monopole Bundle Systems of Complex Hypermanifolds for Composition
  Operators

abstract:
  In this paper, we give new characterizations of monopole bundle systems of
complex hypermanifolds in $n$-dimensional spaces for certain classes of
operators. In particular, we consider the reproducing kernels for decomposable
polynomials of finite algebraic multiplicity for the trace class of composition
operators.


title: Evolution patterns in Collatz problem

abstract:
  The concept of evolution patterns is introduced for Collatz sequences and it
is shown that any finite evolution pattern is implemented in some particular
Collatz sequence.


title:
High Precision, Low Excitation Capactiance Measurement Methods from 10
  mK- to Room-Temperature

abstract:
  Capacitance measurement is a useful technique in studying quantum devices, as
it directly probes the local particle charging properties, i.e. the system
compressibility. Here we report one approach which can measure capacitance from
mK to room temperature with excellent accuracy. Our experiments show that such
a high-precision technique is able to reveal delicate and essential properties
of high-mobility two-dimensional electron systems.


title:
From a conjecture of Collatz to Thompson's group F, via a conjunction of
  Girard

abstract:
  The famous 3x + 1 problem of L. Collatz needs no introduction; however, this
paper concerns a lesser-known, but similarly unresolved, precursor problem :
the Original Collatz Conjecture, or OCC. We demonstrate that the core
arithmetic operator from the OCC, when combined with a conjunction of J.-Y.
Girard from his Geometry of Interaction system, leads to a realisation of R.
Thompson's group F as congruential functions, in the sense of J. Conway. We
also give the underlying category theory that accounts for this, and describe
the core operator from the OCC as a canonical coherence isomorphism.


title:
Impacts of climate change on groundwater droughts by means of
  standardized indices and regional climate models

abstract:
  This paper investigates the impacts of climate change on groundwater droughts
making use of regional projections and standardized indices: the Standardized
Precipitation Index (SPI), the Standardized Precipitation Evapotranspiration
Index (SPEI) and the Standardized Groundwater Index (SGI). The method adopted,
using historical precipitation and temperature data and water levels collected
in monitoring wells, first investigates the possible correlations between
meteorological and groundwater indices at each well. Then, if there is a
correlation, a linear regression analysis is used to model the relationships
between SGIs and SPIs, and SGIs and SPEIs. The same relationships are used to
infer future SGIs from SPI and SPEI projections obtained by means of an
ensemble of Regional Climate Models (RCMs), under different climate scenarios
(RCP 4.5 and RCP 8.5). This methodology has been applied to data collected in
Tuscany (Italy), where historical series of daily climate variables (since
1934) and daily records for 16 wells, covering the period 2005-2020, are
available. The impacts on groundwater have been computed in the short
(2006-2035), medium (2036-2065) and long term (2066-2095). The analysis
indicates that, in the historical period and for most of the monitoring wells,
there is a good correlation between SGIs and SPIs or SPEIs. In a global warming
scenario, the influence of temperature on evapotranspiration phenomena cannot
be overlooked so the SGI-SPEI relationships seem more suitable to forecast
groundwater droughts. According to these relationships, negative effects on
groundwater levels in almost all wells are estimated for the futureDue to the
type of data required and its simplicity, this methodology can be applied to
different areas of interest for a quick estimate of groundwater availability
under climate change scenarios.


title: Object-Guided Day-Night Visual Localization in Urban Scenes

abstract:
  We introduce Object-Guided Localization (OGuL) based on a novel method of
local-feature matching. Direct matching of local features is sensitive to
significant changes in illumination. In contrast, object detection often
survives severe changes in lighting conditions. The proposed method first
detects semantic objects and establishes correspondences of those objects
between images. Object correspondences provide local coarse alignment of the
images in the form of a planar homography. These homographies are consequently
used to guide the matching of local features. Experiments on standard urban
localization datasets (Aachen, Extended-CMU-Season, RobotCar-Season) show that
OGuL significantly improves localization results with as simple local features
as SIFT, and its performance competes with the state-of-the-art CNN-based
methods trained for day-to-night localization.


title:
Ponderomotive coupling of waves to sea surface currents via horizontal
  density gradients

abstract:
  The mathematical models and numerical simulations reported here are motivated
by satellite observations of horizontal sea surface fluid motions that are
closely coordinated with the vertical motion of waves or, after an
approximation, an envelope of rapidly oscillating waves. This coordination of
fluid movements with wave envelopes tends to occur when strong horizontal
buoyancy gradients are present. The nonlinear models of this coordinated
movement presented here may provide future opportunities for the optimal design
of satellite imagery that could simultaneously capture the dynamics of both
waves and currents directly.
  The models derived here appear first in their unapproximated form, then again
with a slowly varying envelope (SVE) approximation using the WKB approach. The
WKB wave-current-buoyancy interaction model derived here for a free surface
with horizontal buoyancy gradients indicates that the mechanism for these
correlations is the ponderomotive force of the slowly varying envelope of
rapidly oscillating waves acting on the surface currents via the horizontal
buoyancy gradient. In this model, the buoyancy gradient appears explicitly in
the WKB wave momentum, which in turn generates density-weighted potential
vorticity whenever the buoyancy gradient is not aligned with the wave-envelope
gradient.

categories: physics.ao-ph math-ph math.MP physics.flu-dyn


title: On the origin of the rhythmic Sun's radius variation

abstract:
  The Sun shrinks during solar maximum and regrows during solar minimum by a
few kilometers. Here, we observe, for the first time, that the solar radius
variation shows planetary relationship. This suggests that some remote
planetary links must exist, even though this is unexpected within known
physics. Therefore, we speculate about its cause, which is the driving idea
behind this investigation. Namely, it must be some generic as yet invisible
streaming matter from the dark Universe. The associated energy change is
massive although it extends from months to several years. The impact by the
tentative invisible massive matter accumulates with time, triggering slowly the
underlying processes. This study shows that the sun size response is as short
as a few months. Then, the solar system is the target and the antenna of still
unidentified external impact, assuming to be from the dark sector.


title:
Self-consistent energy density functional approaches to the crust of
  neutron stars

abstract:
  In order to study structure of the crust in neutron stars, we develop a
finite-temperature Skyrme-Hartree-Fock method in the full three-dimensional
coordinate space using the Fermion operator expansion method. It provides us
with a possible order-N approach to non-uniform neutron-star matters.


title: On inertia forces and cosmological acceleration

abstract:
  It is shown that the equations of gravitational waves and cosmological
acceleration follow from the tensor of inertial forces. The possibility of the
existence of three types of gravitational waves: transverse, potential and
vortex waves are shown. The equation of "free cosmological fall" of matter is
obtained. It is concluded that the cosmological acceleration is an attribute of
the geometry of space-time and for its explanation does not require the
involvement of the hypothesis of "dark" energy.


title: Be, V and Cu in the halo star CS 31082-001 from near-UV spectroscopy

abstract:
  The 'First Stars' programme revealed the metal-poor halo star CS 31082-001 to
be r-process and actinide rich, including the first measurement of a uranium
abundance for an old star. To better characterise and understand such rare
objects, we present the first abundance estimates of three elements (Be, V, Cu)
for CS 31082-001 from analysis of its near-ultraviolet spectrum. Beryllium is
rarely measured in giant stars, and we confirm that its abundance in this star
is low due to the rather cool effective temperature that causes destruction of
both Be and Li in its atmosphere. Vanadium and copper are iron-peak elements
that are starting to be used as chemical-tagging indicators to investigate the
origin of stellar populations. We find V and Cu abundances for CS 31082-001
that are comparable to other metal-poor stars, and present new chemical
evolution models to investigate our results. In the case of V, extra
nucleosynthesis due to interaction of neutrinos with matter is included in the
models to be able to reproduce the measured abundance. Given the availability
of high-quality spectroscopy of CS 31082-001, we also explore other atomic
lines in the near-ultraviolet as a template for future studies of metal-poor
stars with the planned CUBES instrument in development for the Very Large
Telescope.


title: Constructing synthetic populations in the age of big data

abstract:
  To develop public health intervention models using microsimulations,
extensive personal information about inhabitants is needed, such as
socio-demographic, economic and health figures. Data confidentiality is an
essential characteristic of such data, while the data should support realistic
scenarios. Collection of such data is possible only in secured environments and
not directly available for external micro-simulation models. The aim of this
paper is to illustrate a method for construction of synthetic data by
predicting individual features through models based on confidential data on
health and socio-economic determinants of the entire Dutch population.


title: On the trace of linear combination of powers of algebraic numbers

abstract:
  In this article, we prove three main results. Let $\lambda_1, \ldots,
\lambda_k$ and $\alpha_1, \ldots, \alpha_k$ be nonzero algebraic numbers for
some integer $k\geq 1$ and let $L = \mathbb{Q}(\lambda_1, \ldots, \lambda_k,
\alpha_1, \ldots, \alpha_k)$ be the number field. Let $K$ be the Galois closure
of $L$ and let $h$ be the order of the torsion subgroup of $K^\times$. We first
prove an extension of a result of B. de Smit [3] as follows: {\it Take
$\lambda_i = b_i \in\mathbb{Q}$ for $i=1,\ldots, k$ such that $b_1+\cdots+b_k =
n\ne 0$ and $\alpha_j$'s are some of the Galois conjugates (not necessarily
distinct) of $\alpha_1$ for all $j = 2, \ldots, k$ and $d\geq 1$ is the degree
of $\alpha_1$. If
$\displaystyle{\mathrm{Tr}}_{L/\mathbb{Q}}(b_1\alpha_1^j+\cdots+b_k\alpha_k^j)
\in \mathbb{Z}$ for all $j = 1, 2, \ldots, d+d[\log_2(nd)]+1$, then $\alpha_1$
is an algebraic integer.} We then prove a general result for the infinite
version as follows. {\it Suppose
${\mathrm{Tr}}_{L/\mathbb{Q}}(\lambda_i\alpha_i^a) \ne 0$ for all integers
$a\in \{0, 1, 2, \ldots, h-1\}$ and for all integers $i=1,\ldots,k$. If
${\mathrm{Tr}}_{L/\mathbb{Q}}(\lambda_1\alpha_1^n+\cdots +\lambda_k
\alpha^n_k)\in\mathbb{Z}$ holds true for infinitely many natural numbers $n$,
then each $\alpha_i$ is an algebraic integer for all $i=1,\ldots,k$. } Here the
extra assumption is a necessary condition for $k > 1$ (See Remark 1.3). We also
prove a Diophantine result which states: {\it For a given rational number
$p/q$, there are at most finitely many natural numbers $n$ such that
${\mathrm{Tr}}_{L/\mathbb{Q}}(\lambda_1\alpha_1^n+\cdots +\lambda_k \alpha^n_k)
= p/q$.}


title:
Analyzing the Hubble tension through hidden sector dynamics in the early
  universe

abstract:
  The recent analysis from the SH0ES Collaboration has confirmed the existence
of a Hubble tension between measurements at high redshift ($z> 1000$) and at
low redshift ($z<1$) at the $5\sigma$ level with the low redshift measurement
giving a higher value. In this work we propose a particle physics model that
can help alleviate the Hubble tension via an out-of-equilibrium hidden sector
coupled to the visible sector. The particles that populate the dark sector
consist of a dark fermion, which acts as dark matter, a dark photon, a massive
scalar and a massless pseudo-scalar. Assuming no initial population of
particles in the dark sector, feeble couplings between the visible and the
hidden sectors via kinetic mixing populate the dark sector even though the
number densities of hidden sector particles never reach their equilibrium
distribution and the two sectors remain at different temperatures. A
cosmologically consistent analysis is presented where a correlated evolution of
the visible and the hidden sectors with coupled Boltzmann equations involving
two temperatures, one for the visible sector and the other for the hidden
sector, is carried out. The relic density of the dark matter constituted of
dark fermions is computed in this two-temperature formalism. As a consequence,
BBN predictions are upheld with a minimal contribution to $\Delta N_{\rm eff}$.
However, the out-of-equilibrium decay of the massive scalar to the massless
pseudo-scalar close to the recombination time causes an increase in $\Delta
N_{\rm eff}$ that can help weaken the Hubble tension.


title:
Adjacent-Bits-Swapped Polar codes: A new code construction to speed up
  polarization

abstract:
  The construction of polar codes with code length $n=2^m$ involves $m$ layers
of polar transforms. In this paper, we observe that after each layer of polar
transforms, one can swap certain pairs of adjacent bits to accelerate the
polarization process. More precisely, if the previous bit is more reliable than
its next bit under the successive decoder, then switching the decoding order of
these two adjacent bits will make the reliable bit even more reliable and the
noisy bit even noisier.
  Based on this observation, we propose a new family of codes called the
Adjacent-Bits-Swapped (ABS) polar codes. We add a permutation layer after each
polar transform layer in the construction of the ABS polar codes. In order to
choose which pairs of adjacent bits to swap in the permutation layers, we rely
on a new polar transform that combines two independent channels with $4$-ary
inputs. This new polar transform allows us to track the evolution of every pair
of adjacent bits through different layers of polar transforms, and it also
plays an essential role in the Successive Cancellation List (SCL) decoder for
the ABS polar codes. Extensive simulation results show that ABS polar codes
consistently outperform standard polar codes by 0.15dB -- 0.6dB when we use
CRC-aided SCL decoder with list size $32$ for both codes. The implementations
of all the algorithms in this paper are available at
https://github.com/PlumJelly/ABS-Polar


title: Core-periphery structure in networks: a statistical exposition

abstract:
  Many real-world networks are theorized to have core-periphery structure
consisting of a densely-connected core and a loosely-connected periphery. While
this network feature has been extensively studied in various scientific
disciplines, it has not received sufficient attention in the statistics
community. In this expository article, our goal is to raise awareness about
this topic and encourage statisticians to address the many interesting open
problems in this area. We present the current research landscape by reviewing
the most popular metrics and models that have been used for quantitative
studies on core-periphery structure. Next, we formulate and explore various
inferential problems in this context, such as estimation, hypothesis testing,
and Bayesian inference, and discuss related computational techniques. We also
outline the multidisciplinary scientific impact of core-periphery structure in
a number of real-world networks. Throughout the article, we provide our own
interpretation of the literature from a statistical perspective, with the goal
of prioritizing open problems where contribution from the statistics community
will be effective and important.


title:
AC-Feasible Power Transfer Regions of Virtual Power Plants:
  Characterization and Application

abstract:
  Distributed energy resources (DERs) in distribution networks can be
aggregated as a virtual power plant (VPP) for transmission-level operations. A
critical challenge for such coordination is the complexity of the AC-feasible
power transfer region between a VPP and the transmission system at their point
of common coupling. To overcome this challenge, this paper develops a
characterization method for such regions. The proposed method constructs linear
constraints to inner-approximate the AC-feasible power transfer regions. To
guarantee AC-feasibility, the parameters in these constraints are determined by
applying the Brouwer fixed point theorem to the second-order Taylor expansion
of the nonlinear Dist-Flow equations. Based on the power transfer regions
characterized with our method, a transmission-level operation problem with VPP
participation is formulated and solved through big-M linearization. The
proposed methods are verified by numerical experiments in the IEEE 33-bus and
IEEE 136-bus test systems.


title:
Femtosecond pumping of nuclear isomeric states by the Coulomb collision
  of ions with quivering electrons

abstract:
  Efficient production of nuclear isomers is critical for pioneering
applications, like nuclear clocks, nuclear batteries, clean nuclear energy, and
nuclear {\gamma}-ray lasers. However, due to small production cross sections
and quick decays, it is extremely difficult to acquire a significant amount of
isomers with short lifetimes via traditional accelerators or reactors because
of low beam intensity. Here, for the first time, we experimentally present
femtosecond pumping of nuclear isomeric states by the Coulomb excitation of
ions with the quivering electrons induced by laser fields. Nuclei populated on
the third excited state of 83Kr are generated with a peak efficiency of
2.34*10^15 particles=s from a tabletop hundred-TW laser system. It can be
explained by the Coulomb excitation of ions with the quivering electrons during
the interaction between laser pulses and clusters at nearly solid densities.
This efficient and universal production method can be widely used for pumping
isotopes with excited state lifetimes down to picoseconds, and could be a
benefit for fields like nuclear transition mechanisms and nuclear {\gamma}-ray
lasers.


title:
Measurement and simulation of mechanical and optical properties of
  sputtered amorphous SiC coatings

abstract:
  In this work We report on the extensive characterization of amorphous silicon
carbide (a-SiC) coatings prepared by physical deposition methods. We compare
the results obtained on two different sputtering systems (a standard RF
magnetron sputtering and a ion-beam assisted sputtering) to seize the impact of
two different setups on the repeatably of the results.
  After a thorough characterization of structural, morphological, and
compositional characteristics of the prepared samples, we focus on a detailed
study of the optical and mechanical losses in those materials. Mechanical
losses are further investigated from a microscopic point of view by comparing
our experimental results with molecular dynamic simulations of the amorphous
SiC structure: first we define a protocol to generate a numerical model of the
amorphous film, capturing the main features of the real system; then we
simulate its dynamical behaviour upon deformation in order to obtain its
mechanical response. Our results are discussed within the perspective
application of a-SiC as an optical material for high-precision optical
experiments and in particular in gravitational wave interferometry.


title: Inducing a bound state between active particles

abstract:
  We show that two active particles can form a bound state by coupling to a
driven nonequilibrium environment. We specifically investigate the case of two
mutually noninteracting run-and-tumble probes moving on a ring, each in
short-range interaction with driven colloids. Under conditions of time-scale
separation, these active probes become trapped in bound states. In fact, the
bound state appears at high enough persistence (low effective temperature).
From the perspective of a co-moving frame, where colloids are in thermal
equilibrium and the probes are active and driven, an appealing analogy appears
with Cooper pairing, as electrons can be viewed as run-and-tumble particles in
a pilot-wave picture.

categories: cond-mat.soft cond-mat.stat-mech nlin.AO physics.bio-ph


title:
Quantum Computing in Pharma: A Multilayer Embedding Approach for Near
  Future Applications

abstract:
  Quantum computers are special purpose machines that are expected to be
particularly useful in simulating strongly correlated chemical systems. The
quantum computer excels at treating a moderate number of orbitals within an
active space in a fully quantum mechanical manner. We present a quantum phase
estimation calculation on F$_2$ in a (2,2) active space on Rigetti's Aspen-11
QPU. While this is a promising start, it also underlines the need for carefully
selecting the orbital spaces treated by the quantum computer. In this work, a
scheme for selecting such an active space automatically is described and
simulated results obtained using both the quantum phase estimation (QPE) and
variational quantum eigensolver (VQE) algorithms are presented and combined
with a subtractive method to enable accurate description of the environment.
The active occupied space is selected from orbitals localized on the chemically
relevant fragment of the molecule, while the corresponding virtual space is
chosen based on the magnitude of interactions with the occupied space
calculated from perturbation theory. This protocol is then applied to two
chemical systems of pharmaceutical relevance: the enzyme [Fe] hydrogenase and
the photosenzitizer temoporfin. While the sizes of the active spaces currently
amenable to a quantum computational treatment are not enough to demonstrate
quantum advantage, the procedure outlined here is applicable to any active
space size, including those that are outside the reach of classical
computation.


title:
A Multi-Task Recurrent Neural Network for End-to-End Dynamic Occupancy
  Grid Mapping

abstract:
  A common approach for modeling the environment of an autonomous vehicle are
dynamic occupancy grid maps, in which the surrounding is divided into cells,
each containing the occupancy and velocity state of its location. Despite the
advantage of modeling arbitrary shaped objects, the used algorithms rely on
hand-designed inverse sensor models and semantic information is missing.
Therefore, we introduce a multi-task recurrent neural network to predict grid
maps providing occupancies, velocity estimates, semantic information and the
driveable area. During training, our network architecture, which is a
combination of convolutional and recurrent layers, processes sequences of raw
lidar data, that is represented as bird's eye view images with several height
channels. The multi-task network is trained in an end-to-end fashion to predict
occupancy grid maps without the usual preprocessing steps consisting of
removing ground points and applying an inverse sensor model. In our
evaluations, we show that our learned inverse sensor model is able to overcome
some limitations of a geometric inverse sensor model in terms of representing
object shapes and modeling freespace. Moreover, we report a better runtime
performance and more accurate semantic predictions for our end-to-end approach,
compared to our network relying on measurement grid maps as input data.


title:
Merit-based Fusion of NLP Techniques for Instant Feedback on Water
  Quality from Twitter Text

abstract:
  This paper focuses on an important environmental challenge; namely, water
quality by analyzing the potential of social media as an immediate source of
feedback. The main goal of the work is to automatically analyze and retrieve
social media posts relevant to water quality with particular attention to posts
describing different aspects of water quality, such as watercolor, smell,
taste, and related illnesses. To this aim, we propose a novel framework
incorporating different preprocessing, data augmentation, and classification
techniques. In total, three different Neural Networks (NNs) architectures,
namely (i) Bidirectional Encoder Representations from Transformers (BERT), (ii)
Robustly Optimized BERT Pre-training Approach (XLM-RoBERTa), and (iii) custom
Long short-term memory (LSTM) model, are employed in a merit-based fusion
scheme. For merit-based weight assignment to the models, several optimization
and search techniques are compared including a Particle Swarm Optimization
(PSO), a Genetic Algorithm (GA), Brute Force (BF), Nelder-Mead, and Powell's
optimization methods. We also provide an evaluation of the individual models
where the highest F1-score of 0.81 is obtained with the BERT model. In
merit-based fusion, overall better results are obtained with BF achieving an
F1-score score of 0.852.
  We also provide comparison against existing methods, where a significant
improvement for our proposed solutions is obtained. We believe such rigorous
analysis of this relatively new topic will provide a baseline for future
research.


title: Dual involutions in finite Coxeter groups

abstract:
  There is a well-known classification of conjugacy classes of involutions in
finite Coxeter groups, in terms of subsets of nodes of their Coxeter graphs. In
many cases, the product of an involution with the longest element is again an
involution. We identify the conjugacy class of this product involution in terms
of said classification.


title: Conditional Drums Generation using Compound Word Representations

abstract:
  The field of automatic music composition has seen great progress in recent
years, specifically with the invention of transformer-based architectures. When
using any deep learning model which considers music as a sequence of events
with multiple complex dependencies, the selection of a proper data
representation is crucial. In this paper, we tackle the task of conditional
drums generation using a novel data encoding scheme inspired by the Compound
Word representation, a tokenization process of sequential data. Therefore, we
present a sequence-to-sequence architecture where a Bidirectional Long
short-term memory (BiLSTM) Encoder receives information about the conditioning
parameters (i.e., accompanying tracks and musical attributes), while a
Transformer-based Decoder with relative global attention produces the generated
drum sequences. We conducted experiments to thoroughly compare the
effectiveness of our method to several baselines. Quantitative evaluation shows
that our model is able to generate drums sequences that have similar
statistical distributions and characteristics to the training corpus. These
features include syncopation, compression ratio, and symmetry among others. We
also verified, through a listening test, that generated drum sequences sound
pleasant, natural and coherent while they "groove" with the given
accompaniment.


title: Allocation of Indivisible Items with Individual Preference Graphs

abstract:
  This paper studies the allocation of indivisible items to agents, when each
agent's preferences are expressed by means of a directed acyclic graph. The
vertices of each preference graph represent the subset of items approved of by
the respective agent. An arc $(a,b)$ in such a graph means that the respective
agent prefers item $a$ over item $b$. We introduce a new measure of
dissatisfaction of an agent by counting the number of non-assigned items which
are approved of by the agent and for which no more preferred item is allocated
to the agent. Considering two problem variants, we seek an allocation of the
items to the agents in a way that minimizes (i) the total dissatisfaction over
all agents or (ii) the maximum dissatisfaction among the agents. For both
optimization problems we study the status of computational complexity and
obtain NP-hardness results as well as polynomial algorithms with respect to
natural underlying graph structures, such as stars, trees, paths, and
matchings. We also analyze the parameterized complexity of the two problems
with respect to various parameters related to the number of agents, the
dissatisfaction threshold, the vertex degrees of the preference graphs, and the
treewidth.


title: Predicting the intended action using internal simulation of perception

abstract:
  This article proposes an architecture, which allows the prediction of
intention by internally simulating perceptual states represented by action
pattern vectors. To this end, associative self-organising neural networks
(A-SOM) is utilised to build a hierarchical cognitive architecture for
recognition and simulation of the skeleton based human actions. The abilities
of the proposed architecture in recognising and predicting actions is evaluated
in experiments using three different datasets of 3D actions. Based on the
experiments of this article, applying internally simulated perceptual states
represented by action pattern vectors improves the performance of the
recognition task in all experiments. Furthermore, internal simulation of
perception addresses the problem of having limited access to the sensory input,
and also the future prediction of the consecutive perceptual sequences. The
performance of the system is compared and discussed with similar architecture
using self-organizing neural networks (SOM).


title: Anisotropic quark stars in $f(R)= R^{1+\epsilon}$ gravity

abstract:
  Within the metric formalism of $f(R)$ theories of gravity, where $R$ is the
Ricci scalar, we study the hydrostatic equilibrium structure of compact stars
with the inclusion of anisotropic pressure. In particular, we focus on the
$f(R)= R^{1+\epsilon}$ model and we examine small deviations from General
Relativity (GR) for $\vert \epsilon \vert \ll 1$. A suitable definition of mass
function is explicitly formulated from the field equations and the value of the
Ricci scalar at the center of each star is chosen such that it satisfies the
asymptotic flatness requirement. We find that both the mass and the radius of a
compact star are larger with respect to the general relativistic counterpart.
Furthermore, we remark that the substantial changes due to anisotropy occur
mainly in the high-central-density region.


title: Opportunities for studying C+ resonances at 3--12 GeV photon collider

abstract:
  Recently, a $\gamma\gamma$ collider based on existing 17.5 GeV linac of the
European XFEL has been proposed. High energy photons will be generated by
Compton scattering of laser photons with a wavelength of 0.5--1 $\mu$m on
electrons. Such photon collider covers the range of invariant masses
$W_{\gamma\gamma} <12$ GeV. The physics program includes spectroscopy of $C=+$
resonances ($c$-, $b$-quarkonia, 4-quark states, glueballs) in various $J^P$
states. Variable circular and linear polarizations will help in determining the
quantum numbers. In this paper, we present a summary of measured and predicted
two-photon widths of various resonances in the mass region 3--12 GeV and
investigate the experimental possibility of observing these heavy two-photon
resonances under conditions of a large multi-hadron background. Registration of
all final particles is assumed. The minimum values of $\Gamma_{\gamma\gamma}$
for detecting resonances at the $5\sigma$ level are obtained.


title:
Mapping hydrodynamics for the facilitated exclusion and zero-range
  processes

abstract:
  We derive the hydrodynamic limit for two degenerate lattice gases, the
\emph{facilitated exclusion process} (FEP) and the \emph{facilitated zero-range
process} (FZRP), both in the symmetric and the asymmetric case. For both
processes, the hydrodynamic limit in the symmetric case takes the form of a
diffusive Stefan problem, whereas the asymmetric case is characterized by a
hyperbolic Stefan problem. Although the FZRP is attractive, a property that we
extensively use to derive its hydrodynamic limits in both cases, the FEP is
not. To derive the hydrodynamic limit for the latter, we exploit that of the
zero-range process, together with a classical mapping between exclusion and
zero-range processes, both at the microscopic and macroscopic level. Due to the
degeneracy of both processes, the asymmetric case is a new result, but our work
also provides a simpler proof than the one that was previously proposed for the
FEP in the symmetric case in \cite{blondel2021stefan}.


title: u-Channel Color Transparency Observables

abstract:
  We propose to study the onset of color transparency in hard exclusive
reactions in the backward regime. Guided by the encouraging JLab results on
backward pion and omega electro-production data at moderate Q^2, which may be
interpreted as the signal of an early scaling regime where the scattering
amplitude factorizes in a hard coefficient function convoluted with nucleon to
meson transition distribution amplitudes, we show that the study of these
channels on nuclear targets opens a new opportunity to test the appearance of
nuclear color transparency for a fast moving nucleon.


title:
Domain-wall topology induced by spontaneous symmetry breaking in
  polariton graphene

abstract:
  We present a numerical study of exciton-polariton (polariton) condensation in
a staggered polariton graphene showing a gapped s-band at the $K$ and $K'$
valleys. The condensation occurs at $K$ or $K'$, at the kinetically-favorable
negative mass extrema of the valence band. Considering attractive
polariton-polariton interaction allows to generate a spatially extended
condensate. Spontaneous symmetry breaking occurring during the condensate
build-up leads to the formation of valley-polarized domains following the
Kibble-Zurek scenario. The selection of a single valley breaks time-reversal
symmetry and the walls separating domains exhibit a topologically-protected
chiral current. This current therefore emerges as a result of the interplay
between the non-trivial valley topology and the condensation-induced symmetry
breaking.


title:
Images of magnetospheric reconnection-powered radiation around
  supermassive black holes

abstract:
  Accreting supermassive black holes can now be observed at the event-horizon
scale at mm wavelengths. Current predictions for the image rely on hypotheses
(fluid modeling, thermal electrons) which might not always hold in the vicinity
of the black hole, so that a full kinetic treatment is in order. In this
letter, we describe the first 3D global general-relativistic particle-in-cell
simulation of a black-hole magnetosphere. The system displays a persistent
equatorial current sheet. Synthetic images are computed by ray-tracing
synchrotron emission from nonthermal particles accelerated in this current
sheet by magnetic reconnection. We identify several time-dependent features of
the image at moderate viewing angles: a variable radius of the ring, and hot
spots moving along it. In this regime, our model predicts that most of the flux
of the image lies inside the critical curve. These results could help
understand future observations of black-hole magnetospheres at improved
temporal and spatial resolution.


title: MapiFi: Using Wi-Fi Signals to Map Home Devices

abstract:
  Imagine a map of your home with all of your connected devices (computers,
TVs, voice control devices, printers, security cameras, etc.), in their
location. You could then easily group devices into user-profiles, monitor Wi-Fi
quality and activity in different areas of your home, and even locate a lost
tablet in your home. MapiFi is a method to generate that map of the devices in
a home. The first part of MapiFi involves the user (either a technician or the
resident) walking around the home with a mobile device that listens to Wi-Fi
radio channels. The mobile device detects Wi-Fi packets that come from all of
the home's devices that connect to the gateway and measures their signal
strengths (ignoring the content of the packets). The second part is an
algorithm that uses all the signal-strength measurements to estimate the
locations of all the devices in the home. Then, MapiFi visualizes the home's
space as a coordinate system with devices marked as points in this space. A
patent has been filed based on this technology. This paper was published in
SCTE Technical Journal (see published paper at
https://wagtail-prod-storage.s3.amazonaws.com/documents/SCTE_Technical_Journal_V1N3.pdf).


title: Markovian Modelling and Calibration of IBMQ Transmon Qubits

abstract:
  In the design of quantum devices, it is crucial to account for the
interaction between qubits and their environment to understand and improve the
coherence and stability of the quantum states. This is especially prevalent in
Noisy Intermediate Scale Quantum (NISQ) devices in which the qubit states
quickly decay through processes of relaxation and decoherence. Ideal quantum
states evolve according to Markovian dynamics, which modern devices are not
always capable of maintaining. NISQ devices, such as those offered by IBM
through their cloud-based open-access IBM Quantum Experience (IBM QE) are
regularly calibrated to provide the users with data about the qubit dynamics
which can be accounted for in the design of experiments on the quantum devices.
In this paper we demonstrate a method of verifying the Markovianity of the IBMQ
devices while extracting multiple calibration parameters simultaneously through
a simplified process which can be modified for more complex modelling of qubit
dynamics.


title:
Rave: A non-parametric method for recovering the surface brightness and
  height profiles of edge-on debris disks

abstract:
  Extrasolar analogues of the Solar System's Kuiper belt offer unique
constraints on outer planetary system architecture. Radial features such as the
sharpness of disk edges and substructures such as gaps may be indicative of
embedded planets within a disk. Vertically, the height of a disk can constrain
the mass of embedded bodies. Edge-on debris disks offer a unique opportunity to
simultaneously access the radial and vertical distribution of material, however
recovering either distribution in an unbiased way is challenging. In this
study, we present a non-parametric method to recover the surface brightness
profile (face-on surface brightness as a function of radius) and height profile
(scale height as a function of radius) of azimuthally symmetric, edge-on debris
disks. The method is primarily designed for observations at thermal emission
wavelengths, but is also applicable to scattered light observations under the
assumption of isotropic scattering. By removing assumptions on underlying
functional forms, this algorithm provides more realistic constraints on disk
structures. We also apply this technique to ALMA observations of the AU Mic
debris disk and derive a surface brightness profile consistent with estimates
from parametric approaches, but with a more realistic range of possible models
that is independent of parametrisation assumptions. Our results are consistent
with a uniform scale height of 0.8 au, but a scale height that increases
linearly with radius is also possible.


title: Counting Kernels in Directed Graphs with Arbitrary Orientations

abstract:
  A kernel of a directed graph is a subset of vertices that is both independent
and absorbing (every vertex not in the kernel has an out-neighbour in the
kernel). Not all directed graphs contain kernels, and computing a kernel or
deciding that none exist is NP-complete even on low-degree planar digraphs. The
existing polynomial-time algorithms for this problem all restrict both the
undirected structure and the edge orientations of the input: for example, to
chordal graphs without bidirectional edges (Pass-Lanneau, Igarashi and Meunier,
Discrete Appl Math 2020) or to permutation graphs where each clique has a sink
(Abbas and Saoula, 4OR 2005). By contrast, we count the kernels of a fuzzy
circular interval graph in polynomial time, regardless of its edge
orientations, and return a kernel when one exists. (Fuzzy circular graphs were
introduced by Chudnovsky and Seymour in their structure theorem for claw-free
graphs.) We also consider kernels on cographs, where we establish NP-hardness
in general but linear running times on the subclass of threshold graphs.


title:
Scalable $\rm Al_2O_3-TiO_2$ Conductive Oxide Interfaces as Defect
  Reservoirs for Resistive Switching Devices

abstract:
  Resistive switching devices herald a transformative technology for memory and
computation, offering considerable advantages in performance and energy
efficiency. Here we employ a simple and scalable material system of conductive
oxide interfaces and leverage their unique properties for a new type of
resistive switching device. For the first time, we demonstrate an $\rm
Al_2O_3-TiO_2$ based valence-change resistive switching device, where the
conductive oxide interface serves both as the back electrode and as a reservoir
of defects for switching. The amorphous-polycrystalline $\rm Al_2O_3-TiO_2$
conductive interface is obtained following the technological path of
simplifying the fabrication of the two-dimensional electron gases (2DEGs),
making them more scalable for practical mass integration. We combine physical
analysis of the device chemistry and microstructure with comprehensive
electrical analysis of its switching behavior and performance. We pinpoint the
origin of the resistive switching to the conductive oxide interface, which
serves as the bottom electrode and as a reservoir of oxygen vacancies. The
latter plays a key role in valence-change resistive switching devices. The new
device, based on scalable and complementary metal-oxide-semiconductor (CMOS)
technology-compatible fabrication processes, opens new design spaces towards
increased tunability and simplification of the device selection challenge.


title:
Rethinking Goal-conditioned Supervised Learning and Its Connection to
  Offline RL

abstract:
  Solving goal-conditioned tasks with sparse rewards using self-supervised
learning is promising because of its simplicity and stability over current
reinforcement learning (RL) algorithms. A recent work, called Goal-Conditioned
Supervised Learning (GCSL), provides a new learning framework by iteratively
relabeling and imitating self-generated experiences. In this paper, we revisit
the theoretical property of GCSL -- optimizing a lower bound of the goal
reaching objective, and extend GCSL as a novel offline goal-conditioned RL
algorithm. The proposed method is named Weighted GCSL (WGCSL), in which we
introduce an advanced compound weight consisting of three parts (1) discounted
weight for goal relabeling, (2) goal-conditioned exponential advantage weight,
and (3) best-advantage weight. Theoretically, WGCSL is proved to optimize an
equivalent lower bound of the goal-conditioned RL objective and generates
monotonically improved policies via an iterated scheme. The monotonic property
holds for any behavior policies, and therefore WGCSL can be applied to both
online and offline settings. To evaluate algorithms in the offline
goal-conditioned RL setting, we provide a benchmark including a range of point
and simulated robot domains. Experiments in the introduced benchmark
demonstrate that WGCSL can consistently outperform GCSL and existing
state-of-the-art offline methods in the fully offline goal-conditioned setting.


title:
False Memory Formation in Continual Learners Through Imperceptible
  Backdoor Trigger

abstract:
  In this brief, we show that sequentially learning new information presented
to a continual (incremental) learning model introduces new security risks: an
intelligent adversary can introduce small amount of misinformation to the model
during training to cause deliberate forgetting of a specific task or class at
test time, thus creating "false memory" about that task. We demonstrate such an
adversary's ability to assume control of the model by injecting "backdoor"
attack samples to commonly used generative replay and regularization based
continual learning approaches using continual learning benchmark variants of
MNIST, as well as the more challenging SVHN and CIFAR 10 datasets. Perhaps most
damaging, we show this vulnerability to be very acute and exceptionally
effective: the backdoor pattern in our attack model can be imperceptible to
human eye, can be provided at any point in time, can be added into the training
data of even a single possibly unrelated task and can be achieved with as few
as just 1\% of total training dataset of a single task.


title: Adjoint Node-Based Shape Optimization of Free Floating Vessels

abstract:
  The paper is concerned with a node-based, gradient-driven, continuous adjoint
two-phase flow procedure to optimize the shapes of free-floating vessels and
discusses three topics. First, we aim to convey that elements of a
Cahn-Hilliard formulation should augment the frequently employed
Volume-of-Fluid two-phase flow model to maintain dual consistency. It is seen
that such consistency serves as the basis for a robust primal/adjoint coupling
in practical applications at huge Reynolds and Froude numbers. The second topic
covers different adjoint coupling strategies. A central aspect of the
application is the floating position, particularly the trim and the sinkage,
that interact with a variation of hydrodynamic loads induced by the shape
updates. Other topics addressed refer to the required level of density coupling
and a more straightforward -- yet non-frozen -- adjoint treatment of
turbulence. The third part discusses the computation of a descent direction
within a node-based environment. We will illustrate means to deform both the
volume mesh and the hull shape simultaneously and at the same time obey
technical constraints on the vessel's displacement and its extensions. The
Hilbert-space approach provides smooth shape updates using the established
coding infrastructure of a computational fluid dynamics algorithm and provides
access to managing additional technical constraints. Verification and
validation follow from a submerged 2D cylinder case. The application includes a
full-scale offshore supply vessel at Re=3E+08 and Fn=0.37. Results illustrate
that the fully parallel procedure can automatically reduce the drag of an
already pre-optimized shape by 9-13 within approximately O(10.000-30.000) CPUh
depending on the considered couplings and floatation aspects.


title: Minimax Rate-Distortion

abstract:
  We show the existence of universal, variable-rate rate-distortion codes that
meet the distortion constraint almost surely and approach the rate-distortion
function uniformly with respect to an unknown source distribution and a
distortion measure that is only revealed to the encoder and only at run-time.
If the convergence only needs to be uniform with respect to the source
distribution and not the distortion measure, then we provide an explicit bound
on the minimax rate of convergence. Our construction combines conventional
random coding with a zero-rate uncoded transmission scheme. The proof uses
exact asymptotics from large deviations, acceptance-rejection sampling, the VC
dimension of distortion measures, and the identification of an explicit,
code-independent, finite-blocklength quantity, which converges to the
rate-distortion function, that controls the performance of the best codes.


title:
A quantum dot crossbar with sublinear scaling of interconnects at
  cryogenic temperature

abstract:
  We demonstrate a 36$\times$36 gate electrode crossbar that supports 648
narrow-channel field effect transistors (FET) for gate-defined quantum dots,
with a quadratic increase in quantum dot count upon a linear increase in
control lines. The crossbar is fabricated on an industrial $^{28}$Si-MOS stack
and shows 100% FET yield at cryogenic temperature. We observe a decreasing
threshold voltage for wider channel devices and obtain a normal distribution of
pinch-off voltages for nominally identical tunnel barriers probed over 1296
gate crossings. Macroscopically across the crossbar, we measure an average
pinch-off of 1.17~V with a standard deviation of 46.8 mV, while local
differences within each unit cell indicate a standard deviation of 23.1~mV.
These disorder potential landscape variations translate to 1.2 and 0.6 times
the measured quantum dot charging energy, respectively. Such metrics provide
means for material and device optimization and serve as guidelines in the
design of large-scale architectures for fault-tolerant semiconductor-based
quantum computing.


title:
Substrate influence on transition metal dichalcogenide monolayer exciton
  absorption linewidth broadening

abstract:
  The excitonic states of transition metal dichacolgenide (TMD) monolayers are
heavily influenced by their external dielectric environment based on the
substrate used. In this work, various wide bandgap dielectric materials, namely
hexagonal boron nitride (\textit{h}-BN) and amorphous silicon nitride
(Si$_3$N$_4$), under different configurations as support or encapsulation
material for WS$_2$ monolayers are investigated to disentangle the factors
contributing to inhomogeneous broadening of exciton absorption lines in TMDs
using electron energy loss spectroscopy (EELS) in a scanning transmission
electron microscope (STEM). In addition, monolayer roughness in each
configuration was determined from tilt series of electron diffraction patterns
by assessing the broadening of diffraction spots by comparison with
simulations. From our experiments, the main factors that play a role in
linewidth broadening can be classified in increasing order of importance by:
monolayer roughness, surface cleanliness, and substrate-induced charge
trapping. Furthermore, because high-energy electrons are used as a probe,
electron beam-induced damage on bare TMD monolayer is also revealed to be
responsible for irreversible linewidth increases. \textit{h}-BN not only
provides clean surfaces of TMD monolayer, and minimal charge disorder, but can
also protect the TMD from irradiation damage. This work provides a better
understanding of the mechanisms by which \textit{h}-BN remains, to date, the
most compatible material for 2D material encapsulation, facilitating the
realization of intrinsic material properties to their full potential.


title:
Exchange-biased topological transverse thermoelectric effects in a
  Kagome ferrimagnet

abstract:
  Kagome metal TbMn6Sn6 was recently discovered to be a ferrimagnetic
topological Dirac material by scanning tunneling microscopy/spectroscopy
measurements. Here, we report the observation of large anomalous Nernst effect
and anomalous thermal Hall effect in this compound. The anomalous transverse
transport is consistent with the Berry curvature contribution from the massive
Dirac gaps in the 3D momentum space as demonstrated by our first-principles
calculations. Furthermore, the transverse thermoelectric transport exhibits
asymmetry with respect to the applied magnetic field, i.e., an exchange-bias
behavior. Together, these features place TbMn6Sn6 as a promising system for the
outstanding thermoelectric performance based on anomalous Nernst effect.


title: Indirect measurement of the carbon adatom migration barrier on graphene

abstract:
  Although surface diffusion is critical for many physical and chemical
processes, including the epitaxial growth of crystals and heterogeneous
catalysis, it is particularly challenging to directly study. Here, we estimate
the carbon adatom migration barrier on freestanding monolayer graphene by
quantifying its temperature-dependent electron knock-on damage. Due to the fast
healing of vacancies by diffusing adatoms, the damage rate decreases with
increasing temperature. By analyzing the observed damage rates at 300-1073 K
using a model describing our finite scanning probe, we find a barrier of (0.33
\pm 0.03) eV.


title: Stochastic Multi-Dimensional Deconvolution

abstract:
  Seismic datasets contain valuable information that originate from areas of
interest in the subsurface; such seismic reflections are however inevitably
contaminated by other events created by waves reverberating in the overburden.
Multi-Dimensional Deconvolution (MDD) is a powerful technique used at various
stages of the seismic processing sequence to create ideal datasets deprived of
such overburden effects. Whilst the underlying forward problem is well defined
for a single source, a successful inversion of the MDD equations requires
availability of a large number of sources alongside prior information
introduced in the form of physical preconditioners (e.g., reciprocity). In this
work, we reinterpret the cost function of time-domain MDD as a finite-sum
functional, and solve the associated inverse problem by means of stochastic
gradient descent algorithms, where gradients are computed using a small subset
of randomly selected sources. Through synthetic and field data examples, the
proposed method is shown to converge more stably than the conventional approach
based on full gradients. Stochastic MDD represents a novel, efficient, and
robust strategy to deconvolve seismic wavefields in a multi-dimensional
fashion.


title:
Finding Optimal Arms in Non-stochastic Combinatorial Bandits with
  Semi-bandit Feedback and Finite Budget

abstract:
  We consider the combinatorial bandits problem with semi-bandit feedback under
finite sampling budget constraints, in which the learner can carry out its
action only for a limited number of times specified by an overall budget. The
action is to choose a set of arms, whereupon feedback for each arm in the
chosen set is received. Unlike existing works, we study this problem in a
non-stochastic setting with subset-dependent feedback, i.e., the semi-bandit
feedback received could be generated by an oblivious adversary and also might
depend on the chosen set of arms. In addition, we consider a general feedback
scenario covering both the numerical-based as well as preference-based case and
introduce a sound theoretical framework for this setting guaranteeing sensible
notions of optimal arms, which a learner seeks to find. We suggest a generic
algorithm suitable to cover the full spectrum of conceivable arm elimination
strategies from aggressive to conservative. Theoretical questions about the
sufficient and necessary budget of the algorithm to find the best arm are
answered and complemented by deriving lower bounds for any learning algorithm
for this problem scenario.


title:
CRAT-Pred: Vehicle Trajectory Prediction with Crystal Graph
  Convolutional Neural Networks and Multi-Head Self-Attention

abstract:
  Predicting the motion of surrounding vehicles is essential for autonomous
vehicles, as it governs their own motion plan. Current state-of-the-art vehicle
prediction models heavily rely on map information. In reality, however, this
information is not always available. We therefore propose CRAT-Pred, a
multi-modal and non-rasterization-based trajectory prediction model,
specifically designed to effectively model social interactions between
vehicles, without relying on map information. CRAT-Pred applies a graph
convolution method originating from the field of material science to vehicle
prediction, allowing to efficiently leverage edge features, and combines it
with multi-head self-attention. Compared to other map-free approaches, the
model achieves state-of-the-art performance with a significantly lower number
of model parameters. In addition to that, we quantitatively show that the
self-attention mechanism is able to learn social interactions between vehicles,
with the weights representing a measurable interaction score. The source code
is publicly available.


title:
4D dS vacua from AdS vacua of type IIB string theory and AdS distance
  conjecture

abstract:
  By exploring the Kaluza-Klein (KK) compactification of 5D gravity plus a
negative cosmological constant where the dynamics of the 4D tensor component of
the bulk metric along the fifth dimension is taken into account and considering
its stringy UV completion, we show that there exists an explicit way to turn
AdS vacua of type IIB string theory to dS vacua of the 4D effective theory.
Hence this opens a new approach to construct realistic models on AdS vacua in
string theory, rather than dS vacua which are particularly difficult to
realize, consistent with the observation of positive cosmological constant.
Additionally, we find that the mass spectrum of KK tower for the 5D bulk fields
provides evidence coming from the bottom-up physics for the strong version of
the AdS distance conjecture realized from AdS vacua in string theory. Since
this evidence supports the sharpening of the AdS distance conjecture as one of
universal features of quantum gravity.


title:
The first X-ray spectrum of the HMXB XTE J1855-026 during the compact
  object eclipse

abstract:
  We present the first {\it XMM-Newton} observation of the classical supergiant
high-mass X-ray binary XTE J1855$-$026 taken entirely during the eclipse of the
neutron star (NS), covering the orbital phases $\phi= 0.00-0.11$. The analysis
of the data allows us to a) compare with the parameters obtained during the
existing pre eclipse observation and b) explore the back illuminated stellar
wind of the B0I type donor. The black body component, used to describe the soft
excess during pre eclipse, is not observed during eclipse. It must be then
produced near the NS or along the donor-NS line. The $0.3-10$ keV luminosity
during eclipse ($\sim 10^{34}$ erg s$^{-1}$) is 70 times lower than pre
eclipse. The intensity of the Fe K$\alpha$ line, in the average eclipse
spectrum, is $\sim 7.4$ times lower than the one measured during pre eclipse.
Since K$\alpha$ photons can not be resonantly scattered in the wind, the vast
majority of Fe K$\alpha$ emission must come from distances within $1R_{*}$ from
the NS. The eclipse spectrum is successfully modelled through the addition of
two photoionized plasmas, one with low ionization ($\log\xi_{\rm 1,cold}=0.36$)
and high emission measure ($EM_{\rm 1,cold}\approx 3\times 10^{59}$ cm$^{-3}$)
and another with high ionization ($\log\xi_{\rm 2,hot}=3.7$) and low emission
measure ($EM_{\rm hot}\approx 2\times 10^{56}$ cm$^{-3}$). Assuming that the
cold and hot gas phases are the clumps and the interclump medium of the stellar
wind, respectively, and a clump volume filling factor of $\approx [0.04-0.05]$,
typical for massive stars, a density contrast between clumps and the interclump
medium of $n_{\rm c}/n_{\rm i}\approx 180$ is deduced, in agreement with
theoretical expectations and optical-UV observations of massive star winds.


title: Phase-matched high-order harmonic generation in pre-ionized noble gases

abstract:
  One of the main difficulties to efficiently generating high-order harmonics
in long neutral-gas targets is to reach the phase-matching conditions. One
issue is that the medium cannot be sufficiently ionized by the driving laser
due to plasma defocusing. We propose a method to improve the phase-matching by
pre-ionizing the gas using a weak capillary discharge. We have demonstrated
this mechanism, for the first time, in absorption-limited XUV generation by an
800 nm femtosecond laser in argon and krypton. The phase-mismatch control
ability of our method is confirmed by an analytical model and numerical
simulation of the complete generation process. Our method allows increasing the
efficiency of the harmonic generation significantly, paving the way towards
photon-hungry applications of these short-wavelength compact sources.


title:
Dark-exciton driven energy funneling into dielectric inhomogeneities in
  two-dimensional semiconductors

abstract:
  The optoelectronic and transport properties of two-dimensional transition
metal dichalcogenide semiconductors (2D TMDs) are highly susceptible to
external perturbation, enabling precise tailoring of material function through
post-synthetic modifications. Here we show that nanoscale inhomogeneities known
as nanobubbles can be used for both strain and, less invasively, dielectric
tuning of exciton transport in bilayer tungsten disulfide (WSe2). We use
ultrasensitive spatiotemporally resolved optical scattering microscopy to
directly image exciton transport, revealing that dielectric nanobubbles are
surprisingly efficient at funneling and trapping excitons at room temperature,
even though the energies of the bright excitons are negligibly affected. Our
observations suggest that exciton funneling in dielectric inhomogeneities is
driven by momentum-indirect (dark) excitons whose energies are more sensitive
to dielectric perturbations than bright excitons. These results reveal a new
pathway to control exciton transport in 2D semiconductors with exceptional
spatial and energetic precision using dielectric engineering of dark state
energetic landscapes.


title:
Pressure-induced reemergence of superconductivity in BaIr2Ge7 and
  Ba3Ir4Ge16 with cage structures

abstract:
  The clathrate-like or caged compounds have attracted continuing interest due
to their structural flexibility as well as fertile physical properties. Here we
report a pressure-induced reemergence of superconductivity in BaIr2Ge7 and
Ba3Ir4Ge16, two new caged superconductors with two-dimensional building blocks
of cage structures. After suppressing the ambient-pressure superconducting
(SC-I) state, a new superconducting (SC-II) state emerges unexpectedly, with Tc
increased to a maximum of 4.4 K and 4.0 K for BaIr2Ge7 and Ba3Ir4Ge16,
respectively. Combined with high-pressure synchrotron x-ray diffraction and
Raman measurements, we propose that the reemergence of superconductivity in the
caged superconductors can be ascribed to a pressure-induced phonon softening
linked to the cage shrink.


title:
A Circle Grid-based Approach for Obstacle Avoidance Motion Planning of
  Unmanned Surface Vehicles

abstract:
  Aiming at an obstacle avoidance problem with dynamic constraints for Unmanned
Surface Vehicle (USV), a method based on Circle Grid Trajectory Cell (CGTC) is
proposed. Firstly, the ship model and standardization rules are constructed to
develop and constrain the trajectory, respectively. Secondly, by analyzing the
properties of the circle grid, the circle grid tree is produced to guide the
motion of the USV. Then, the kinematics and dynamics of the USV are considered
through the on-line trajectory generator by designing a relational function
that links the rudder angle, heading angle, and the central angle of the circle
grid. Finally, obstacle avoidance is achieved by leveraging the on-line
trajectory generator to choose a safe, smooth, and efficient path for the USV.
The experimental results indicate that the proposed method can avoid both
static and dynamic obstacles, have better performance in terms of distance cost
and steering cost comparing with the related methods, and our method only takes
50% steering cost of the grid-based method; the collision avoidance path not
only conforms to the USV dynamic characteristic but also provides a reference
of steering command.


title:
Data-driven Safe Control of Linear Systems Under Epistemic and Aleatory
  Uncertainties

abstract:
  Safe control of constrained linear systems under both epistemic and aleatory
uncertainties is considered. The aleatory uncertainty characterizes random
noises and is modeled by a probability distribution function (PDF) and the
epistemic uncertainty characterizes the lack of knowledge on the system
dynamics. Data-based probabilistic safe controllers are designed for the cases
where the noise PDF is 1) zero-mean Gaussian with a known covariance, 2)
zero-mean Gaussian with an uncertain covariance, and 3) zero-mean non-Gaussian
with an unknown distribution. Easy-to-check model-based conditions for
guaranteeing probabilistic safety are provided for the first case by
introducing probabilistic contractive sets. These results are then extended to
the second and third cases by leveraging distributionally-robust probabilistic
safe control and conditional value-at-risk (CVaR) based probabilistic safe
control, respectively. Data-based implementations of these probabilistic safe
controllers are then considered. It is shown that data-richness requirements
for directly learning a safe controller is considerably weaker than
data-richness requirements for model-based safe control approaches that
undertake a model identification. Moreover, an upper bound on the minimal risk
level, under which the existence of a safe controller is guaranteed, is learned
using collected data. A simulation example is provided to show the
effectiveness of the proposed approach.


title:
Neutrino astronomy as a probe of physics beyond the Standard Model:
  decay of sub-MeV $B$-$L$ gauge boson dark matter

abstract:
  The $U(1)_{B\textrm{--}L}$ symmetry, the essential component in the seesaw
mechanism and leptogenesis, is naturally equipped with a massive gauge boson.
When the gauge coupling is of the order of $\mathcal{O}(10^{-19})$, this gauge
boson is a light and long-lived dark matter candidate which dominantly decays
into active neutrinos. This consistent dark matter scenario predicts a
characteristic neutrino signal that is potentially detectable at future
neutrino observatories. Once detected, such a neutrino signal would serve as a
smoking gun for this minimal extension to the Standard Model of particle
physics, opening new windows to tackle cosmological and astrophysical conundra.


title:
Recurrent Spectral Network (RSN): shaping the basin of attraction of a
  discrete map to reach automated classification

abstract:
  A novel strategy to automated classification is introduced which exploits a
fully trained dynamical system to steer items belonging to different categories
toward distinct asymptotic attractors. These latter are incorporated into the
model by taking advantage of the spectral decomposition of the operator that
rules the linear evolution across the processing network. Non-linear terms act
for a transient and allow to disentangle the data supplied as initial condition
to the discrete dynamical system, shaping the boundaries of different
attractors. The network can be equipped with several memory kernels which can
be sequentially activated for serial datasets handling. Our novel approach to
classification, that we here term Recurrent Spectral Network (RSN), is
successfully challenged against a simple test-bed model, created for
illustrative purposes, as well as a standard dataset for image processing
training.


title: Analytic thin wall false vacuum decay rate

abstract:
  We derive a closed-form false vacuum decay rate at one loop in the thin wall
limit, where the true and false vacua are nearly degenerate. We obtain the
bounce configuration in $D$ dimensions, together with the Euclidean action with
a higher order correction, counter-terms and renormalization group running. We
extract the functional determinant via the Gel'fand-Yaglom theorem for low and
generic orbital multipoles. The negative and zero eigenvalues appear for low
multipoles and the translational zeroes are removed. We compute the
fluctuations for generic multipoles, multiply and regulate the orbital modes.
We find an explicit finite renormalized decay rate in $D = 3, 4$ and give a
closed-form expression for the finite functional determinant in any dimension.


title:
Lightweight Jet Reconstruction and Identification as an Object Detection
  Task

abstract:
  We apply object detection techniques based on deep convolutional blocks to
end-to-end jet identification and reconstruction tasks encountered at the CERN
Large Hadron Collider (LHC). Collision events produced at the LHC and
represented as an image composed of calorimeter and tracker cells are given as
an input to a Single Shot Detection network. The algorithm, named PFJet-SSD
performs simultaneous localization, classification and regression tasks to
cluster jets and reconstruct their features. This all-in-one single
feed-forward pass gives advantages in terms of execution time and an improved
accuracy w.r.t. traditional rule-based methods. A further gain is obtained from
network slimming, homogeneous quantization, and optimized runtime for meeting
memory and latency constraints of a typical real-time processing environment.
We experiment with 8-bit and ternary quantization, benchmarking their accuracy
and inference latency against a single-precision floating-point. We show that
the ternary network closely matches the performance of its full-precision
equivalent and outperforms the state-of-the-art rule-based algorithm. Finally,
we report the inference latency on different hardware platforms and discuss
future applications.