title: Mixture-of-Rookies: Saving DNN Computations by Predicting ReLU Outputs

abstract:
  Deep Neural Networks (DNNs) are widely used in many applications domains.
However, they require a vast amount of computations and memory accesses to
deliver outstanding accuracy. In this paper, we propose a scheme to predict
whether the output of each ReLu activated neuron will be a zero or a positive
number in order to skip the computation of those neurons that will likely
output a zero. Our predictor, named Mixture-of-Rookies, combines two
inexpensive components. The first one exploits the high linear correlation
between binarized (1-bit) and full-precision (8-bit) dot products, whereas the
second component clusters together neurons that tend to output zero at the same
time. We propose a novel clustering scheme based on the analysis of angles, as
the sign of the dot product of two vectors depends on the cosine of the angle
between them. We implement our hybrid zero output predictor on top of a
state-of-the-art DNN accelerator. Experimental results show that our scheme
introduces a small area overhead of 5.3% while achieving a speedup of 1.2x and
reducing energy consumption by 16.5% on average for a set of diverse DNNs.


title: A note on a prey-predator model with constant-effort harvesting

abstract:
  We study a prey-predator model based on the classical Lotka-Volterra system
with Leslie-Gower and Holling IV schemes and a constant-effort harvesting. Our
goal is twofold: to present the model proposed by Cheng and Zhang in 2021,
pointing out some inconsistencies; to analyse the number and type of
equilibrium points of the model. We end by proving the stability of the
meaningful equilibrium point, according to the distribution of the eigenvalues.


title: Surface astrochemistry: a computational chemistry perspective

abstract:
  Molecules in space are synthesized via a large variety of gas-phase
reactions, and reactions on dust-grain surfaces, where the surface acts as a
catalyst. Especially, saturated, hydrogen-rich molecules are formed through
surface chemistry. Astrochemical models have developed over the decades to
understand the molecular processes in the interstellar medium, taking into
account grain surface chemistry. However, essential input information for
gas-grain models, such as binding energies of molecules to the surface, have
been derived experimentally only for a handful of species, leaving hundreds of
species with highly uncertain estimates. Moreover, some fundamental processes
are not well enough constrained to implement these into the models.
  The proceedings gives three examples how computational chemistry techniques
can help answer fundamental questions regarding grain surface chemistry.


title: Minimum rank and failed zero forcing number of graphs

abstract:
  Let $G$ be a simple, finite, and undirected graph with vertices each given an
initial coloring of either blue or white. Zero forcing on graph $G$ is an
iterative process of forcing its white vertices to become blue after a finite
application of a specified color-change rule. We say that an initial set $S$ of
blue vertices of $G$ is a zero forcing set for $G$ under the specified
color-change rule if a finite number of iterations of zero forcing results to
an updated coloring where all vertices of $G$ are blue. Otherwise, we say that
$S$ is a failed zero forcing set for $G$ under the specified color-change rule.
It is not difficult to see that any subset of a failed zero forcing set is also
failed. Hence, our interest lies on the maximum possible cardinality of a
failed zero forcing set, which we refer to as the failed zero forcing number of
$G$. In this paper, we consider two color-change rules $-$ standard and
positive semidefinite. We compute for the failed zero forcing numbers of
several graph families. Furthermore, under each graph family, we characterize
the graphs $G$ for which the failed zero forcing number is equal to the minimum
rank of $G$.


title: Slovene SuperGLUE Benchmark: Translation and Evaluation

abstract:
  We present a Slovene combined machine-human translated SuperGLUE benchmark.
We describe the translation process and problems arising due to differences in
morphology and grammar. We evaluate the translated datasets in several modes:
monolingual, cross-lingual, and multilingual, taking into account differences
between machine and human translated training sets. The results show that the
monolingual Slovene SloBERTa model is superior to massively multilingual and
trilingual BERT models, but these also show a good cross-lingual performance on
certain tasks. The performance of Slovene models still lags behind the best
English models.


title:
Photo-excitation measurement of Tan's contact for a strongly interacting
  Fermi gas

abstract:
  We derive theoretically an exact relation between Tan's universal contact and
the photo-excitation rate of a strongly interacting Fermi gas, in the case of
optically transferring fermionic pairs to a more tightly bound molecular state.
Our deviation generalizes the relation between Tan's contact and the
closed-channel molecular fraction found earlier by Werner, Tarruell and Castin
in Eur. Phys. J. B \textbf{68}, 401 (2009). We use the relation to understand
the recent low-temperature photo-excitation measurement in a strongly
interacting $^{6}$Li Fermi gas {[}Liu \textit{et al.}, arXiv:1903.12321{]} and
show that there is a reasonable agreement between theory and experiment close
to the unitary limit. We propose that our relation can be applied to accurately
measure Tan's contact coefficient at finite temperature in future experiments.


title: AA-TransUNet: Attention Augmented TransUNet For Nowcasting Tasks

abstract:
  Data driven modeling based approaches have recently gained a lot of attention
in many challenging meteorological applications including weather element
forecasting. This paper introduces a novel data-driven predictive model based
on TransUNet for precipitation nowcasting task. The TransUNet model which
combines the Transformer and U-Net models has been previously successfully
applied in medical segmentation tasks. Here, TransUNet is used as a core model
and is further equipped with Convolutional Block Attention Modules (CBAM) and
Depthwise-separable Convolution (DSC). The proposed Attention Augmented
TransUNet (AA-TransUNet) model is evaluated on two distinct datasets: the Dutch
precipitation map dataset and the French cloud cover dataset. The obtained
results show that the proposed model outperforms other examined models on both
tested datasets. Furthermore, the uncertainty analysis of the proposed
AA-TransUNet is provided to give additional insights on its predictions.


title: Maximal failed zero forcing sets for products of two graphs

abstract:
  Let $G$ be a simple, finite graph with vertex set $V(G)$ and edge set $E(G)$,
where each vertex is either colored blue or white. Define the standard zero
forcing process on $G$ with the following color-change rule: let $S$ be the set
of all initially blue vertices of $G$ and let $u \in S$. If $v$ is the unique
white vertex adjacent to $u$ in $G$, color $v$ blue and update $S$ by adding
$v$ to $S$. If $S = V(G)$ after a finite number of iterations of the
color-change rule, we say that $S$ is a zero forcing set for $G$. Otherwise, we
say that $S$ is a failed zero forcing set. In this paper, we construct maximal
failed zero forcing sets for graph products such as Cartesian products, strong
products, lexicographic products, and coronas. In particular, we consider
products of two paths, two cycles, and two complete graphs.


title:
Effective powers of $\omega$ over $\Delta_2$ cohesive sets, and an
  infinite $\Pi_1$ set with no $\Delta_2$ cohesive subset

abstract:
  A cohesive power of a computable structure is an effective ultrapower of the
structure, where a cohesive set plays the role of an ultrafilter. Let $\omega$,
$\zeta$, and $\eta$ denote the respective order-types of the natural numbers,
the integers, and the rationals. We study cohesive powers of computable copies
of $\omega$ over $\Delta_2$ cohesive sets. We show that there is a computable
copy $\mathcal{L}$ of $\omega$ such that, for every $\Delta_2$ cohesive set
$C$, the cohesive power of $\mathcal{L}$ over $C$ has order-type $\omega +
\eta$. This improves an earlier result of Dimitrov, Harizanov, Morozov, Shafer,
A. Soskova, and Vatev by generalizing from $\Sigma_1$ cohesive sets to
$\Delta_2$ cohesive sets and by computing a single copy of $\omega$ that has
the desired cohesive power over all $\Delta_2$ cohesive sets. Furthermore, our
result is optimal in the sense that $\Delta_2$ cannot be replaced by $\Pi_2$.
More generally, we show that if $X \subseteq \mathbb{N} \setminus \{0\}$ is a
Boolean combination of $\Sigma_2$ sets, thought of as a set of finite
order-types, then there is a computable copy $\mathcal{L}$ of $\omega$ where
the cohesive power of $\mathcal{L}$ over any $\Delta_2$ cohesive set has
order-type $\omega + \sigma(X \cup \{\omega + \zeta\eta + \omega^*\})$.
Moreover, if $X$ is finite and non-empty, then there is also a computable copy
$\mathcal{L}$ of $\omega$ where the cohesive power of $\mathcal{L}$ over any
$\Delta_2$ cohesive set has order-type $\omega + \sigma(X)$. Here $\sigma$
denotes the shuffle operation. An unexpected corollary of our work is the
existence of an infinite $\Pi_1$ set that has no $\Delta_2$ cohesive subset.
This result generalizes D. Martin's well-known result that there is a
co-infinite c.e. set with no maximal superset, and it is also optimal in that
$\Delta_2$ cannot be replaced by $\Pi_2$.


title: On Generalized Powers of Operators

abstract:
  In this note, we introduce generalized powers of linear operators. More
precisely, operators are not raised to numbers but to other operators. We
discuss several properties as regards this notion.


title:
Experimental study of the relative probability of high-spin isomeric
  states population in ($\alpha$,n)-reactions

abstract:
  Results of the investigations of the yield of high-spin and low-spin isomers
in reactions $^{41}$K($\alpha $,n)$^{44}$Sc, $^{86}$Sr ($\alpha $,n)$^{89}$Zr,
$^{112}$Sn($\alpha$,n)$^{115}$Te, and $^{134}$Ba($\alpha$,n)$^{137}$Ce in the
energy range of the alpha particles 15 $\div$ 31 MeV based on off-beam
measurements of induced activity of members of the isomeric pair are presented.
The anomalous behavior of the isomeric cross-section ratios for the first of
these reactions is confirmed. Uniquely large isomeric cross-section ratios for
the second and third ones are obtained. The features of the fourth reaction,
which are promising for its application in fundamental research, are revealed.
Quality of the description of this dynamics by popular computer codes is
analyzed.


title:
IEC Flickermeter Measurement Results for Distorted Modulating Signal
  while Supplied with Distorted Voltage

abstract:
  The paper presents IEC flickermeter measurement results for voltage
fluctuations modelled by amplitude modulation of distorted supply voltage. The
supply voltage distortion caused by electronic and power electronic devices in
the "clipped cosine" form is assumed. This type of supply voltage distortion is
a common disturbance in low voltage networks. Several arbitrary distorted
waveforms of the modulating signal with different modulation depth and
modulating frequency up to approx. 1 kHz are selected to determine the
dependence of severity of voltage fluctuation on their shape. The paper mainly
presents the dependence of voltage fluctuation severity with a frequency
greater than 3fc, where fc is the power frequency. The voltage fluctuation
severity and the dependencies associated with it have been determined on the
basis of numerical simulation studies and experimental laboratory tests.


title:
Achievable Information-Energy Region in the Finite Block-Length Regime
  with Finite Constellations

abstract:
  This paper characterizes an achievable information-energy region of
simultaneous information and energy transmission over an additive white
Gaussian noise channel. This analysis is performed in the finite block-length
regime with finite constellations. More specifically, a method for constructing
a family of codes is proposed and the set of achievable tuples of information
rate, energy rate, decoding error probability (DEP) and energy outage
probability (EOP) is characterized. Using existing converse results, it is
shown that the construction is information rate, energy rate, and EOP optimal.
The achieved DEP is, however, sub-optimal.


title: The Dirichlet problem for a class of prescribed curvature equations

abstract:
  In this paper, we consider the Dirichlet problem for a class of prescribed
curvature equations. The existence of graphic hypersurfaces with prescribing a
class of curvatures and constant boundary is proved.


title:
Surface-bulk coupling in a Bi$_2$Te$_3$ nanoplate grown by van der Waals
  epitaxy

abstract:
  We report on an experimental study of the effect of coherent surface-bulk
electron scattering on quantum transport in a three-dimensional topological
insulator Bi$_2$Te$_3$ nanoplate. The nanoplate is grown via van der Waals
epitaxy on a mica substrate and a top-gated Hall-bar device is fabricated from
the nanoplate directly on the growth substrate. Top-gate voltage dependent
measurements of the sheet resistance of the device reveal that the transport
carriers in the nanoplate are of n-type and that, with decreasing top gate
voltage, the carrier density in the nanoplate is decreased. However, the
mobility is increased with decreasing top-gate voltage. This mobility increase
with decreasing carrier density in the nanoplate is demonstrated to arise from
a decrease in bulk-to-surface electron scattering rate. Low-field
magnetotransport measurements are performed at low temperatures. The measured
magnetoconductivity of the nanoplate shows typical weak anti-localization (WAL)
characteristics. We analyze the measurements by taking surface-bulk
inter-channel electron scattering into account and extract dephasing times
${\tau}_{\phi}$, diffusion coefficients $D$ of electrons at the top surface and
in the bulk, and the surface-bulk scattering times ${\tau}_{SB}$ as a function
of top-gate voltage and temperature. It is found that the dephasing in the
nanoplate arises dominantly from electron-electron scattering with small energy
transfers. It is also found that the ratio of ${\tau}_{\phi}$/${\tau}_{SB}$ (a
measure of the surface-bulk electron coherent coupling) is decreased with
decreasing gate voltage or increasing temperature. We demonstrate that taking
the surface-bulk coherent electron scattering in our Bi$_2$Te$_3$ nanoplate
into account is essential to understand quantum transport measurements at low
temperatures.


title:
The chemical footprint of AGN feedback in the outflowing circumnuclear
  disk of NGC 1068

abstract:
  In the nearby (D=14 Mpc) AGN-starburst composite galaxy NGC 1068, it has been
found that the molecular gas in the Circum-nuclear Disk (CND) is outflowing,
which is a manifestation of ongoing AGN feedback. The outflowing gas has a
large spread of velocities, which likely drive different shock chemistry
signatures at different locations in the CND. We perform a multi-line molecular
study using two shock tracers, SiO and HNCO, with the aim to determine the gas
properties traced by these two species, and explore the possibility of
reconstructing the shock history in the CND. Five SiO transitions and three
HNCO transitions were imaged at high resolution $0''.5-0''.8$ with the Atacama
Large Millimeter/submillimeter Array (ALMA). We performed both LTE and non-LTE
radiative transfer analysis coupled with Bayesian inference process in order to
characterize the gas properties, such as molecular gas density and gas
temperature. We found clear evidence of chemical differentiation between SiO
and HNCO, with the SiO/HNCO ratio ranging from greater than one on the east of
CND to lower than one on the west side. The non-LTE radiative transfer analysis
coupled with Bayesian inference confirms that the gas traced by SiO has
different densities - and possibly temperatures - than that traced by HNCO. We
find that SiO traces gas affected by fast shocks while the gas traced by HNCO
is either just affected by slow shocks or not shocked at all. A distinct
differentiation between SiO and HNCO has been revealed in our observations and
the further analysis of the gas properties traced by both species, which
confirms the results from previous chemical modelings.


title: Ultimate Physical Limits to the Growth of Operator Complexity

abstract:
  In an isolated system, the time evolution of a given observable in the
Heisenberg picture can be efficiently represented in Krylov space. In this
representation, an initial operator becomes increasingly complex as time goes
by, a feature that can be quantified by the Krylov complexity. We introduce a
fundamental and universal limit to the growth of the Krylov complexity by
formulating a Robertson uncertainty relation, involving the Krylov complexity
operator and the Liouvillian, as generator of time evolution. We further show
the conditions for this bound to be saturated and illustrate its validity in
the paradigmatic models of quantum chaos.

categories: quant-ph cond-mat.stat-mech hep-th math-ph math.MP nlin.CD


title: Projective measurements are sufficient for recycling nonlocality

abstract:
  Unsharp measurements are widely seen as the key resource for recycling the
nonlocality of an entangled state shared between several sequential observers.
Contrasting this, we here show that nonlocality can be recycled using only
standard projective measurements, without using quantum ancillas. Focusing on
the CHSH inequality, we determine the optimal trade-off in the Bell parameters
for a maximally entangled two-qubit state in the presence of shared classical
randomness. We then find that non-maximally entangled states make possible
larger sequential violations, which contrasts the standard CHSH scenario.
Furthermore, we show that nonlocality can be recycled even when only using
projective measurements and local randomness. We discuss the implications of
our results for experimental implementations of sequential nonlocality.


title: EvoJAX: Hardware-Accelerated Neuroevolution

abstract:
  Evolutionary computation has been shown to be a highly effective method for
training neural networks, particularly when employed at scale on CPU clusters.
Recent work have also showcased their effectiveness on hardware accelerators,
such as GPUs, but so far such demonstrations are tailored for very specific
tasks, limiting applicability to other domains. We present EvoJAX, a scalable,
general purpose, hardware-accelerated neuroevolution toolkit. Building on top
of the JAX library, our toolkit enables neuroevolution algorithms to work with
neural networks running in parallel across multiple TPU/GPUs. EvoJAX achieves
very high performance by implementing the evolution algorithm, neural network
and task all in NumPy, which is compiled just-in-time to run on accelerators.
We provide extensible examples of EvoJAX for a wide range of tasks, including
supervised learning, reinforcement learning and generative art. Since EvoJAX
can find solutions to most of these tasks within minutes on a single
accelerator, compared to hours or days when using CPUs, our toolkit can
significantly shorten the iteration cycle of evolutionary computation
experiments. EvoJAX is available at https://github.com/google/evojax


title: N\"UWA-LIP: Language Guided Image Inpainting with Defect-free VQGAN

abstract:
  Language guided image inpainting aims to fill in the defective regions of an
image under the guidance of text while keeping non-defective regions unchanged.
However, the encoding process of existing models suffers from either receptive
spreading of defective regions or information loss of non-defective regions,
giving rise to visually unappealing inpainting results. To address the above
issues, this paper proposes N\"UWA-LIP by incorporating defect-free VQGAN
(DF-VQGAN) with multi-perspective sequence to sequence (MP-S2S). In particular,
DF-VQGAN introduces relative estimation to control receptive spreading and
adopts symmetrical connections to protect information. MP-S2S further enhances
visual information from complementary perspectives, including both low-level
pixels and high-level tokens. Experiments show that DF-VQGAN performs more
robustness than VQGAN. To evaluate the inpainting performance of our model, we
built up 3 open-domain benchmarks, where N\"UWA-LIP is also superior to recent
strong baselines.


title: Hilbert's irreducibility theorem via random walks

abstract:
  Let $G$ be a connected linear algebraic group over a number field $K$, let
$\Gamma$ be a finitely generated Zariski dense subgroup of $G(K)$ and let
$Z\subseteq G(K)$ be a thin set, in the sense of Serre. We prove that, if
$G/\mathrm{R}_u(G)$ is semisimple and $Z$ satisfies certain necessary
conditions, then a long random walk on a Cayley graph of $\Gamma$ hits elements
of $Z$ with negligible probability. We deduce corollaries to Galois covers,
characteristic polynomials, and fixed points in group actions. We also prove
analogous results in the case where $K$ is a global function field.


title:
Hardness Results for Laplacians of Simplicial Complexes via
  Sparse-Linear Equation Complete Gadgets

abstract:
  We study linear equations in combinatorial Laplacians of $k$-dimensional
simplicial complexes ($k$-complexes), a natural generalization of graph
Laplacians. Combinatorial Laplacians play a crucial role in homology and are a
central tool in topology. Beyond this, they have various applications in data
analysis and physical modeling problems. It is known that nearly-linear time
solvers exist for graph Laplacians. However, nearly-linear time solvers for
combinatorial Laplacians are only known for restricted classes of complexes.
  This paper shows that linear equations in combinatorial Laplacians of
2-complexes are as hard to solve as general linear equations. More precisely,
for any constant $c \geq 1$, if we can solve linear equations in combinatorial
Laplacians of 2-complexes up to high accuracy in time $\tilde{O}((\# \text{ of
nonzero coefficients})^c)$, then we can solve general linear equations with
polynomially bounded integer coefficients and condition numbers up to high
accuracy in time $\tilde{O}((\# \text{ of nonzero coefficients})^c)$. We prove
this by a nearly-linear time reduction from general linear equations to
combinatorial Laplacians of 2-complexes. Our reduction preserves the sparsity
of the problem instances up to poly-logarithmic factors.


title:
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in
  Particle Physics

abstract:
  Deep learning methods have gained popularity in high energy physics for fast
modeling of particle showers in detectors. Detailed simulation frameworks such
as the gold standard Geant4 are computationally intensive, and current deep
generative architectures work on discretized, lower resolution versions of the
detailed simulation. The development of models that work at higher spatial
resolutions is currently hindered by the complexity of the full simulation
data, and by the lack of simpler, more interpretable benchmarks. Our
contribution is SUPA, the SUrrogate PArticle propagation simulator, an
algorithm and software package for generating data by simulating simplified
particle propagation, scattering and shower development in matter. The
generation is extremely fast and easy to use compared to Geant4, but still
exhibits the key characteristics and challenges of the detailed simulation. We
support this claim experimentally by showing that performance of generative
models on data from our simulator reflects the performance on a dataset
generated with Geant4. The proposed simulator generates thousands of particle
showers per second on a desktop machine, a speed up of up to 6 orders of
magnitudes over Geant4, and stores detailed geometric information about the
shower propagation. SUPA provides much greater flexibility for setting initial
conditions and defining multiple benchmarks for the development of models.
Moreover, interpreting particle showers as point clouds creates a connection to
geometric machine learning and provides challenging and fundamentally new
datasets for the field.
  The code for SUPA is available at https://github.com/itsdaniele/SUPA.

categories: physics.data-an astro-ph.IM cs.LG hep-ex physics.acc-ph


title: Equality in Hausdorff-Young for Hypergroups

abstract:
  It has been shown in "On the Hausdorff-Young theorem for commutative
hypergroups" by Sina Degenfeld-Schonburg, that one can extend the domain of
Fourier transform of a commutative hypergroup $K$ to $L^p(K)$ for $1\leq p \leq
2$, and the Hausdorff-Young inequality holds true for these cases. In this
article, we examine the structure of non-zero functions in $L^p(K)$ for which
equality is attained in the Hausdorff-Young inequality, for $1<p<2$, and
further provide a characterization for the basic uncertainty principle for
commutative hypergroups with non-trivial centre.


title:
Coverage Probability and Spectral Efficiency Analysis of Multi-Gateway
  Downlink LoRa Networks

abstract:
  The system-level performance of multi-gateway downlink long-range (LoRa)
networks is investigated in the present paper.
  Specifically, we first compute the active probability of a channel and the
selection probability of an active end-device (ED) in the closed-form
expressions. We then derive the coverage probability (Pcov) and the area
spectral efficiency (ASE) under the impact of the capture effects and different
spreading factor (SF) allocation schemes.
  Our findings show that both the Pcov and the ASE of the considered networks
can be enhanced significantly by increasing both the duty cycle and the
transmit power.
  Finally, Monte-Carlo simulations are provided to verify the accuracy of the
proposed mathematical frameworks.


title:
Towards a derivation of Classical ElectroDynamics of charges and fields
  from QED

abstract:
  The purpose of this article is twofold. On one hand, we rigorously derive the
Newton--Maxwell equation in the Coulomb gauge from first principles of quantum
electrodynamics in agreement with the formal Bohr's correspondence principle of
quantum mechanics. On the other hand, we establish the global well-posedness of
the Newton--Maxwell system on energy-spaces under weak assumptions on the
charge distribution. Both results improve the state of the art, and are
obtained by incorporating semiclassical and measure theoretical techniques. One
of the novelties is the use of quantum propagation properties in order to build
global solutions of the Newton--Maxwell equation.


title:
A Continuum Approximation Approach to the Hub Location Problem in a
  Crowd-Shipping System

abstract:
  Last-mile delivery in the logistics chain contributes to emissions and
increased congestion. Crowd-shipping is a sustainable and low-cost alternative
to traditional delivery, but relies heavily on the availability of occasional
couriers. In this work, we propose a hub-based crowd-shipping system that aims
to attract sufficient potential crowd-shippers to serve a large portion of the
demand for small parcels. While small-scale versions of this problem have been
recently addressed, a scaling to larger instances significantly complexifies
the problem. A heuristic approach based on continuum approximation is designed
to evaluate the quality of a potential set of hub locations. By combining an
efficient and accurate approximation method with a large neighborhood search
heuristic, we are able to efficiently find a good set of hub locations, even
for large scale networks. Furthermore, on top of determining good hub
locations, our methods allow to identify the expected number of delivered
parcels in every region, which can be used to design a smart dynamic assignment
strategy. A case study on the Washington DC network shows that hubs are built
at locations that are both geographically central, but most importantly are
popular origins for crowd-shippers. The optimal number of hubs is mainly
dependent on the marginal number of parcels that can be served by
crowd-shippers from a specific hub, relative to the costs involved in opening
that hub. The performance of our algorithm is close to that of a
simulation-optimization algorithm, yet being up to 25 times faster. Thereby,
the results show a dynamic assignment policy based on continuum approximation
estimates outperforms existing assignment strategies.


title:
Intelligent Resource Allocations for IRS-Assisted OFDM Communications: A
  Hybrid MDQN-DDPG Approach

abstract:
  In this paper, we study the resource allocation problem for an intelligent
reflecting surface (IRS)-assisted OFDM system. The system sum rate maximization
framework is formulated by jointly optimizing subcarrier allocation, base
station transmit beamforming and IRS phase shift. Considering the continuous
and discrete hybrid action space characteristics of the optimization variables,
we propose an efficient resource allocation algorithm combining multiple deep Q
networks (MDQN) and deep deterministic policy-gradient (DDPG) to deal with this
issue. In our algorithm, MDQN are employed to solve the problem of large
discrete action space, while DDPG is introduced to tackle the continuous action
allocation. Compared with the traditional approaches, our proposed MDQN-DDPG
based algorithm has the advantage of continuous behavior improvement through
learning from the environment. Simulation results demonstrate superior
performance of our design in terms of system sum rate compared with the
benchmark schemes.


title:
From atomistic systems to linearized continuum models for elastic
  materials with voids

abstract:
  We study an atomistic model that describes the microscopic formation of
material voids inside elastically stressed solids under an additional curvature
regularization at the discrete level. Using a discrete-to-continuum analysis,
by means of a recent geometric rigidity result in variable domains [27] and
{\Gamma}-convergence tools, we rigorously derive effective linearized continuum
models for elastically stressed solids with material voids in three-dimensional
elasticity.


title: Thermodynamic formalism for expanding measures

abstract:
  We study the Thermodynamic Formalism for strongly transitive endomorphisms
$f$, focusing on the set all expanding measures. When $f$ is a non-flat
$C^{1+}$ map defined on a Riemannian manifold, being an expanding measure means
being an invariant probability with all its Lyapunov exponents positive.
Roughly speaking, given a H\"older potential $\varphi$, we establish the
uniqueness of the equilibrium state among the expanding measures. Moreover, the
existence of an expanding measure $\mu$ maximizing the entropy implies the
existence and uniqueness of the equilibrium state $\mu_{\varphi}$ among all
invariant probabilities, not only the expanding ones, for any given H\"older
potential $\varphi$ with a small oscillation
$osc\varphi=\sup\varphi-\inf\varphi$. As one of the applications, we show that
if $f$ is a Viana map and $\varphi$ a H\"older continuous potential with small
oscillation, then there exists one and only only one equilibrium state for
$\varphi$.


title:
Decomposition Problem in Process of Selective Identification and
  Localization of Voltage Fluctuations Sources in Power Grids

abstract:
  Voltage fluctuations are common disturbances in power grids, therefore the
effective and selective process of identification and localization of
individual voltage fluctuations sources is necessary for the minimization of
such disturbances. Selectivity in the process of identification and
localization disturbing loads is possible by the use cascade of blocks:
demodulation, decomposition and propagation assessment. The effectiveness of
this approach is closely related to the used method of decomposition. The paper
presents the problem of decomposition process for the selected method of
selective identification and localization of voltage fluctuation sources, in
which the algorithm of enhanced empirical wavelet transform (EEWT) is used as
the decomposition method. The paper presents selected research results from the
real power grid, for which the result of selected approach causes mistakes in
the process of identification and localization of voltage fluctuations sources.
The potential causes of such mistakes related to the decomposition process are
discussed on the basis of obtained research results.


title: On additive decompositions of primitive elements in finite fields

abstract:
  In this paper, we study several topics on additive decompositions of
primitive elemements in finite fields. Also we refine some bounds obtained by
Dartyge and S\'{a}rk\"{o}zy and Shparlinski.


title: CMOS Circuits for Shape-Based Analog Machine Learning

abstract:
  While analog computing is attractive for implementing machine learning (ML)
processors, the paradigm requires chip-in-the-loop training for every processor
to alleviate artifacts due to device mismatch and device non-linearity.
Speeding up chip-in-the-loop training requires re-biasing the circuits in a
manner that the analog functions remain invariant across training and
inference. In this paper, we present an analog computational paradigm and
circuits using "shape" functions that remain invariant to transistor biasing
(weak, moderate, and strong inversion) and ambient temperature variation. We
show that a core Shape-based Analog Compute (S-AC) circuit could be re-biased
and reused to implement: (a) non-linear functions; (b) inner-product building
blocks; and (c) a mixed-signal logarithmic memory, all of which are integral
towards designing an ML inference processor. Measured results using a prototype
fabricated in a 180nm standard CMOS process demonstrate bias invariance and
hence the resulting analog designs can be scaled for power and speed like
digital logic circuits. We also demonstrate a regression task using these CMOS
building blocks.


title: Cybersecurity Challenges Of IoT-enabled Smart Cities: A Survey

abstract:
  The new era of the Internet of Things (IoT) is changing our urban lives in
every way. With the support of recent IoT technologies, IoT-enabled smart
cities are capable of building extensive data networks incorporating a large
number of heterogeneous devices participating in the data collection and
decision-making process. This massive data backbone formed by IoT devices
allows systems to perform real-time environmental monitoring and actuating.
Coupled with high flexibility and ease of deployment, IoT-based solutions can
be easily adopted for different application scenarios. However, there are many
challenges that system designers would need to consider before employing
large-scale IoT deployment. Our current infrastructure will have to quickly
adapt to handle the big data in our systems, supply interoperability for
cross-functional performance, and provide the cognitive capabilities for system
intelligence. Most importantly, we must consider a new spectrum of security
challenges arising from the new context. In this paper, we aim to provide
general security guidelines for IoT-enabled smart city developments by 1)
presenting some of the latest innovations in IoT-enabled smart cities, and
highlighting common security challenges and research opportunities; 2)
reviewing recent cryptographic security implementations for IoT-enabled smart
cities; 3) using the Activity-Network-Things architecture to analyze major
security challenges in IoT deployments and proposing a set of specialized
security requirements for IoT-enabled smart cities; 4) providing a discussion
on the potential prospect for IoT and IoT security.


title: On distribution of the depth index on perfect matchings

abstract:
  We study the restriction of depth index statistic on the set of perfect
matchings. In particular, we provide additional combinatorial description of
the statistic for perfect matchings and calculate the generating polynomial.
The main result of the present short paper is that the depth index on perfect
matchings is equidistributed with the rank function of the Bruhat order.


title: Two-colour spectrally multimode integrated SU(1,1) interferometer

abstract:
  Multimode integrated interferometers have great potential for both spectral
engineering and metrological applications. However, material dispersion of
integrated platforms constitutes an obstacle which limits the performance and
precision of such interferometers. At the same time, two-colour non-linear
interferometers present an important tool for metrological applications, when
measurements in a certain frequency range are difficult. In this manuscript, we
theoretically develop and investigate an integrated multimode two-colour
SU(1,1) interferometer that operates in a supersensitive mode. By ensuring a
proper design of the integrated platform, we suppress dispersion and thereby
significantly increase the visibility of the interference pattern. We
demonstrate that such an interferometer overcomes the classical phase
sensitivity limit for wide parametric gain ranges, when up to $3*10^4$ photons
are generated.


title: Infinite-dimensional algebras as extensions of kinematic algebras

abstract:
  Kinematic algebras can be realised on geometric spaces and constrain the
physical models that can live on these spaces. Different types of kinematic
algebras exist and we consider the interplay of these algebras for
non-relativistic limits of a relativistic system, including both the Galilei
and the Carroll limit. We develop a framework that captures systematically the
corrections to the strict non-relativistic limit by introducing new
infinite-dimensional algebras, with emphasis on the Carroll case. One of our
results is to highlight a new type of duality between Galilei and Carroll
limits that extends to corrections as well. We realise these algebras in terms
of particle models. Other applications include curvature corrections and
particles in a background electro-magnetic field.


title: Blowup analysis of a hysteresis model based upon singular perturbations

abstract:
  In this paper, we provide a geometric analysis of a new hysteresis model that
is based upon singular perturbations. Here hysteresis refers to a type of
regularization of piecewise smooth differential equations where the past of a
trajectory, in a small neighborhood of the discontinuity set, determines the
vector-field at present. In fact, in the limit where the neighborhood of the
discontinuity becomes smaller, hysteresis converges in an appropriate sense to
Filippov's sliding vector-field. Recently, however, in \cite{rev2021a} it has
been shown that hysteresis, in contrast to regularization through smoothing,
leads to chaos in the regularization of grazing bifurcations, even in two
dimensions. The hysteresis model we analyze in the present paper -- which was
developed by Bonet et al \cite{bonet2017a} as an attempt to unify different
regularizations of piecewise smooth systems -- involves two singular
perturbation parameters and includes a combination of slow-fast and nonsmooth
effects. The description of this model is therefore -- from the perspective of
singular perturbation theory -- challenging, even in two dimensions. In this
paper, using blowup as our main technical tool, we present a detailed geometric
description of the dynamics. Specifically, this description allows us to prove
existence of an invariant cylinder carrying fast dynamics in the azimuthal
direction and a slow drift in the axial direction. We find that the slow drift
is given by Filippov's sliding to leading order. In the case of grazing, we
identify two important parameter regimes that relate the model to smoothing and
hysteresis. In particular, in one of these regimes we prove existence of
chaotic dynamics through a horseshoe obtained by a folded saddle and a novel
return mechanism.


title: SU(2)^2xU(1)-invariant G_2-instantons on the AC limit of the C7 family

abstract:
  We construct SU(2)^2xU(1)-invariant G_2-instantons on the asymptotically
conical limit of the C7 family of G_2-metrics. The construction uses a
dynamical systems approach involving perturbations of an abelian solution and a
solution on the G_2-cone. From this we obtain a 1-parameter family of invariant
instantons with gauge group SU(2) and bounded curvature.


title:
Moments and multiplets in moir\'e materials: A pseudo-fermion functional
  renormalization group for spin-valley models

abstract:
  The observation of strongly-correlated states in moir\'e systems has renewed
the conceptual interest in magnetic systems with higher SU(4) spin symmetry,
e.g. to describe Mott insulators where the local moments are coupled
spin-valley degrees of freedom. Here, we discuss a numerical renormalization
group scheme to explore the formation of spin-valley ordered and unconventional
spin-valley liquid states at zero temperature based on a pseudo-fermion
representation. Our generalization of the conventional pseudo-fermion
functional renormalization group approach for $\mathfrak{su}$(2) spins is
capable of treating diagonal and off-diagonal couplings of generic spin-valley
exchange Hamiltonians in the self-conjugate representation of the
$\mathfrak{su}$(4) algebra. To achieve proper numerical efficiency, we derive a
number of symmetry constraints on the flow equations that significantly limit
the number of ordinary differential equations to be solved. As an example
system, we investigate a diagonal SU(2)$_{\textrm{spin}}$ $\otimes$
U(1)$_{\textrm{valley}}$ model on the triangular lattice which exhibits a rich
phase diagram of spin and valley ordered phases.


title: Porous medium equation as limit of nonlocal interaction

abstract:
  This paper studies the convergence of solutions of a nonlocal interaction
equation to the solution of the quadratic porous medium equation in the limit
of a localising interaction kernel. The analysis is carried out at the level of
the (nonlocal) partial differential equations and we use the gradient flow
structure of the equations to derive bounds on energy, second order moments,
and logarithmic entropy. The dissipation of the latter yields sufficient
regularity to obtain compactness results and pass to the limit in the localised
convolutions. The strategy we propose relies on a discretisation scheme which
could be slightly modified in order to extend our result to PDEs with no
gradient flow structure. Our analysis allows to treat the case of limiting weak
solutions of the non-viscous porous medium equation at relevant low regularity,
assuming the initial value to have finite energy and entropy. However, the
latter excludes particle solutions of the nonlocal interaction equation.


title:
Omicron BA.2 (B.1.1.529.2): high potential to becoming the next
  dominating variant

abstract:
  The Omicron variant of severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2) has rapidly replaced the Delta variant as a dominating SARS-CoV-2
variant because of natural selection, which favors the variant with higher
infectivity and stronger vaccine breakthrough ability. Omicron has three
lineages or subvariants, BA.1 (B.1.1.529.1), BA.2 (B.1.1.529.2), and BA.3
(B.1.1.529.3). Among them, BA.1 is the currently prevailing subvariant. BA.2
shares 32 mutations with BA.1 but has 28 distinct ones. BA.3 shares most of its
mutations with BA.1 and BA.2 except for one. BA.2 is found to be able to
alarmingly reinfect patients originally infected by Omicron BA.1. An important
question is whether BA.2 or BA.3 will become a new dominating "variant of
concern". Currently, no experimental data has been reported about BA.2 and
BA.3. We construct a novel algebraic topology-based deep learning model trained
with tens of thousands of mutational and deep mutational data to systematically
evaluate BA.2's and BA.3's infectivity, vaccine breakthrough capability, and
antibody resistance. Our comparative analysis of all main variants namely,
Alpha, Beta, Gamma, Delta, Lambda, Mu, BA.1, BA.2, and BA.3, unveils that BA.2
is about 1.5 and 4.2 times as contagious as BA.1 and Delta, respectively. It is
also 30% and 17-fold more capable than BA.1 and Delta, respectively, to escape
current vaccines. Therefore, we project that Omicron BA.2 is on its path to
becoming the next dominating variant. We forecast that like Omicron BA.1, BA.2
will also seriously compromise most existing mAbs, except for sotrovimab
developed by GlaxoSmithKline.


title:
Hybrid Mie-Tamm photonic structure as a highly directional GHz
  single-photon source

abstract:
  We present a photonic structure where Mie, Tamm, and surface plasmon optical
modes can be tailored to enhance the brightness of an embedded single-photon
emitter. Contrarily to most proposals, the structure is designed for excitation
and collection through the substrate side. The front surface can be used
instead to arrange metal contacts which serve both, as electrical gates and
optical mirrors. The design is particularized for InGaAs QDs on GaAs resulting
in an outcoupled single-photon rate exceeding 3 GHz in a narrow cone of NA =
0.17. The fabrication tolerances are also discussed.


title: Floquet engineering topological Dirac bands

abstract:
  We experimentally realized a time-periodically modulated 1D lattice for
ultracold atoms featuring a pair of linear bands, each associated with a
Floquet winding number: a topological invariant. These bands are spin-momentum
locked and almost perfectly linear everywhere in the Brillouin zone (BZ),
making this system a near-ideal realization of the 1D Dirac Hamiltonian. We
characterized the Floquet winding number using a form of quantum state
tomography, covering the BZ and following the micromotion through one Floquet
period. Lastly, we altered the modulation timing to lift the topological
protection, opening a gap at the Dirac point that grew in proportion to the
deviation from the topological configuration.


title: Sharp $L_p$-error estimates for sampling operators

abstract:
  We study approximation properties of linear sampling operators in the spaces
$L_p$ for $1\le p<\infty$. By means of the Steklov averages, we introduce a new
measure of smoothness that simultaneously contains information on the
smoothness of a function in $L_p$ and discrete information on the behaviour of
a function at sampling points. The new measure of smoothness enables us to
improve and extend several classical results of approximation theory to the
case of linear sampling operators. In particular, we obtain matching direct and
inverse approximation inequalities for sampling operators in $L_p$, find the
exact order of decay of the corresponding $L_p$-errors for particular classes
of functions, and introduce a special $K$-functional and its realization
suitable for studying smoothness properties of sampling operators.


title:
Isospin symmetry breaking in the charge radius difference of mirror
  nuclei

abstract:
  Isospin symmetry breaking (ISB) effects in the charge radius difference
$\Delta R_{\rm ch}$ of mirror nuclei are studied using the test example of
${}^{48}$Ca and ${}^{48}$Ni. This choice allows for a transparent study of ISB
contributions since paring and deformation effects, commonly required for the
study of mirror nuclei, can be neglected in this specific pair. The connection
of $\Delta R_{\rm ch}$ with the nuclear Equation of State and the effect of ISB
on such a relation are discussed according to an Energy Density Functional
approach. We find that nuclear ISB effects may shift the estimated value for
the symmetry energy slope parameter $L$ by more than 10 MeV while Coulomb
corrections can be neglected. ISB effects on the ground-state energy and charge
radii in mirror nuclei have been recently predicted by {\it ab initio}
calculations to be relatively small, pointing to a negligible effect for the
extraction of information on the nuclear EoS. These contrasting results call
for a dedicated theoretical effort to solve this overarching problem that
impacts not only the neutron skin thickness or the difference in mass and
charge radii of mirror nuclei but also other observables such as the Isobaric
Analog State energy.


title: Remarks on chromatically localised hermitian K-theory

abstract:
  We describe chromatic localisations of genuine L-spectra of discrete rings
and deduce that the purity property of $K(1)$-local $K$-theory of rings
established by Bhatt-Clausen-Mathew also holds in Grothendieck-Witt theory. In
addition, we collect some results on higher chromatic localisations of various
L-theory spectra and their consequences for Grothendieck-Witt theory.


title:
Differential $t\bar{t}$ cross-section measurements using boosted top
  quarks with 139 fb$^{-1}$ of ATLAS data

abstract:
  Preliminary results of two differential cross-section measurements in the
ATLAS experiment at CERN are presented. Measurements are focused on the
top-antitop quark pair production in the~lepton+jets and the~all-hadronic
channels in the kinematic region with high transverse momentum top quarks. Both
measurements use the full Run 2 data of 13 TeV proton-proton collisions from
the Large Hadron Collider collected by the ATLAS detector in 2015-2018,
corresponding to an integrated luminosity of 139 fb$^{-1}$. The measured
spectra are compared with the Standard Model predictions. They are also used to
set limits on the Wilson coefficients of an effective field theory extension of
the Standard Model.


title: Improving CP Measurement with THEIA and Muon Decay at Rest

abstract:
  We explore the possibility of using the recently proposed THEIA detector to
measure the $\bar \nu_\mu \rightarrow \bar \nu_e$ oscillation with neutrinos
from a muon decay at rest ($\mu$DAR) source to improve the leptonic CP phase
measurement. Due to its intrinsic low-energy beam, this $\mu$THEIA
configuration ($\mu$DAR neutrinos at THEIA) is only sensitive to the genuine
leptonic CP phase $\delta_D$ and not contaminated by the matter effect. With
detailed study of neutrino energy reconstruction and backgrounds at the THEIA
detector, we find that the combination with the high-energy DUNE can
significantly reduce the CP uncertainty, especially around the maximal CP
violation cases $\delta_D = \pm 90^\circ$. Both the $\mu$THEIA-25 with 17kt and
$\mu$THEIA-100 with 70kt fiducial volumes are considered. For DUNE +
$\mu$THEIA-100, the CP uncertainty can be better than $8^\circ$.


title:
Existence and uniqueness of solutions to the Bogomol'nyi equation on
  graphs

abstract:
  Let $G=(V,E)$ be a connected finite graph. We study the Bogomol'nyi equation
\begin{equation*}
  \Delta u= \mathrm{e}^{u}-1 +4 \pi \sum_{s=1}^{k} n_s \delta_{z_{s}} \quad
\text { on } \quad G, \end{equation*} where $z_1, z_2,\dots, z_k$ are
arbitrarily chosen distinct vertices on the graph, $n_j$ is a positive integer,
$j=1,2,\cdots, k$ and $\delta_{z_{s}}$ is the Dirac mass at $z_s$. We obtain a
necessary and sufficient condition for the existence and uniqueness of
solutions to the Bogomol'nyi equation.


title: Lebesgue Induction and Tonelli's Theorem in Coq

abstract:
  Lebesgue integration is a well-known mathematical tool, used for instance in
probability theory, real analysis, and numerical mathematics. Thus its
formalization in a proof assistant is to be designed to fit different goals and
projects. Once Lebesgue integral is formally defined and the first lemmas are
proved, the question of the convenience of the formalization naturally arises.
To check it, a useful extension is the Tonelli theorem, stating that the
(double) integral of a nonnegative measurable function of two variables can be
computed by iterated integrals, and allowing to switch the order of
integration. Therefore, we need to define and prove results on product spaces,
hoping that they can easily derive from the existing ones on a single space.
This article describes the formal definition and proof in Coq of product
$\sigma$-algebras, product measures and their uniqueness, the construction of
iterated integrals, up to the Tonelli theorem. We also advertise the
\emph{Lebesgue induction principle} provided by an inductive type for
{\nonnegative} measurable functions.


title: On characterizations of learnability with computable learners

abstract:
  We study computable PAC (CPAC) learning as introduced by Agarwal et al.
(2020). First, we consider the main open question of finding characterizations
of proper and improper CPAC learning. We give a characterization of a closely
related notion of strong CPAC learning, and we provide a negative answer to the
open problem posed by Agarwal et al. (2021) whether all decidable PAC learnable
classes are improperly CPAC learnable. Second, we consider undecidability of
(computable) PAC learnability. We give a simple and general argument to exhibit
such undecidability, and we initiate a study of the arithmetical complexity of
learnability. We briefly discuss the relation to the undecidability result of
Ben-David et al. (2019), that motivated the work of Agarwal et al.


title:
Mapping the power-law decay of high-harmonic spectra from laser-plasma
  interactions

abstract:
  Visible or near infra-red light can be manipulated to produce bursts of
coherent extreme ultraviolet (XUV) or X-rays via the relativistic high-order
harmonic generation process when a laser irradiates a solid plasma target. The
intensity of the spectral components of the reflected signal decays with
increase of harmonic order and the efficiency of this non-linear process
largely hinges on how prompt this decay is. This is governed by the conditions
of the laser-plasma interaction for which various models have been proposed. At
relativistic intensities, a spectrum exhibiting a power-law decay with an
exponent of 8/3 or 4/3 is often stated. Here, we analyse the dependence of this
exponent on interaction parameters including the angle of incidence, the
carrier envelope phase, intensity of the laser and the pre-plasma length, and
discuss opportunities for optimization. Our simulations show that, rather than
there being one universal exponent, the spectral decay is a continuous function
of the laser-plasma interaction parameters.


title: On Romanoff's theorem

abstract: We obtain some results related to Romanoff's theorem.


title: On denseness of horospheres in higher rank homogeneous spaces

abstract:
  Let $ G $ be a connected, semisimple real algebraic group and $\Gamma < G$ be
a Zariski dense discrete subgroup. Let $N$ denote a maximal horospherical
subgroup of $G$, and $P=MAN$ the minimal parabolic subgroup which is the
normalizer of $N$. Let $\mathcal{E}$ denote the unique $P$-minimal subset of
$\Gamma \backslash G$ and let $\mathcal{E}_0$ be a $P^\circ$-minimal subset. We
consider a notion of a horospherical limit point in the Furstenberg boundary $
G/P $ and show that the following are equivalent for any $[g]\in
\mathcal{E}_0$: (1) $gP\in G/P$ is a horospherical limit point; (2) $[g]NM$ is
dense in $\mathcal{E}$; (3) $[g]N$ is dense in $\mathcal{E}_0$. The equivalence
of (1) and (2) is due to Dal'bo in the rank one case. We also observe that
unlike convex cocompact groups of rank one Lie groups, the $NM$-minimality of
$\mathcal{E}$ does not hold in a general Anosov homogeneous space.


title:
Entanglement Hamiltonians: from field theory, to lattice models and
  experiments

abstract:
  We review results about entanglement (or modular) Hamiltonians of quantum
many-body systems in field theory and statistical mechanics models, as well as
recent applications in the context of quantum information and quantum
simulation.

categories: cond-mat.stat-mech cond-mat.str-el hep-th math-ph math.MP quant-ph


title:
HyGAL: Characterizing the Galactic ISM with observations of hydrides and
  other small molecules -- I. Survey description and a first look toward
  W3(OH), W3 IRS5 and NGC 7538 IRS1

abstract:
  The HyGAL SOFIA legacy program surveys six hydride molecules -- ArH+, OH+,
H2O+, SH, OH, and CH -- and two atomic constituents -- C+ and O -- within the
diffuse interstellar medium (ISM) by means of absorption-line spectroscopy
toward 25 bright Galactic background continuum sources. This detailed
spectroscopic study is designed to exploit the unique value of specific
hydrides as tracers and probes of different phases of the ISM, as demonstrated
by recent studies with the Herschel Space Observatory. The observations
performed under the HyGAL program will allow us to address several questions
related to the lifecycle of molecular material in the ISM and the physical
processes that impact its phase transition, such as: (1) What is the
distribution function of the H2 fraction in the ISM? (2) How does the
ionization rate due to low-energy cosmic-rays vary within the Galaxy? (3) What
is the nature of interstellar turbulence, and what mechanisms lead to its
dissipation? This overview discusses the observing strategy, synergies with
ancillary and archival observations, the data reduction and analysis schemes
adopted; and presents the first results obtained toward three of the survey
targets, W3(OH), W3IRS5 and NGC7538IRS1. Robust measurements of the column
densities of these hydrides -- obtained through widespread observations of
absorption lines-- help address the questions raised, and there is a timely
synergy between these observations and the development of theoretical models,
particularly pertaining to the formation of H2 within the turbulent ISM. The
provision of enhanced HyGAL data products will therefore serve as a legacy for
future ISM studies.


title:
Infinitary Noetherian Constructions II. Transfinite Words and the
  Regular Subword Topology

abstract:
  We show that the spaces of transfinite words, namely ordinal-indexed words,
over a Noetherian space, is also Noetherian, under a natural topology which we
call the regular subword topology. We characterize its sobrification and its
specialization ordering, and we give an upper bound on its dimension and on its
stature.


title:
Quantune: Post-training Quantization of Convolutional Neural Networks
  using Extreme Gradient Boosting for Fast Deployment

abstract:
  To adopt convolutional neural networks (CNN) for a range of
resource-constrained targets, it is necessary to compress the CNN models by
performing quantization, whereby precision representation is converted to a
lower bit representation. To overcome problems such as sensitivity of the
training dataset, high computational requirements, and large time consumption,
post-training quantization methods that do not require retraining have been
proposed. In addition, to compensate for the accuracy drop without retraining,
previous studies on post-training quantization have proposed several
complementary methods: calibration, schemes, clipping, granularity, and
mixed-precision. To generate a quantized model with minimal error, it is
necessary to study all possible combinations of the methods because each of
them is complementary and the CNN models have different characteristics.
However, an exhaustive or a heuristic search is either too time-consuming or
suboptimal. To overcome this challenge, we propose an auto-tuner known as
Quantune, which builds a gradient tree boosting model to accelerate the search
for the configurations of quantization and reduce the quantization error. We
evaluate and compare Quantune with the random, grid, and genetic algorithms.
The experimental results show that Quantune reduces the search time for
quantization by approximately 36.5x with an accuracy loss of 0.07 ~ 0.65%
across six CNN models, including the fragile ones (MobileNet, SqueezeNet, and
ShuffleNet). To support multiple targets and adopt continuously evolving
quantization works, Quantune is implemented on a full-fledged compiler for deep
learning as an open-sourced project.


title:
Fair When Trained, Unfair When Deployed: Observable Fairness Measures
  are Unstable in Performative Prediction Settings

abstract:
  Many popular algorithmic fairness measures depend on the joint distribution
of predictions, outcomes, and a sensitive feature like race or gender. These
measures are sensitive to distribution shift: a predictor which is trained to
satisfy one of these fairness definitions may become unfair if the distribution
changes. In performative prediction settings, however, predictors are precisely
intended to induce distribution shift. For example, in many applications in
criminal justice, healthcare, and consumer finance, the purpose of building a
predictor is to reduce the rate of adverse outcomes such as recidivism,
hospitalization, or default on a loan. We formalize the effect of such
predictors as a type of concept shift-a particular variety of distribution
shift-and show both theoretically and via simulated examples how this causes
predictors which are fair when they are trained to become unfair when they are
deployed. We further show how many of these issues can be avoided by using
fairness definitions that depend on counterfactual rather than observable
outcomes.


title: Quantum correlations and ergotropy

abstract:
  Understanding the role of classical and quantum correlations in work
extraction is a problem of fundamental importance in thermodynamics. We
approach this problem by considering that, in closed quantum systems, the
maximum cyclic work extractable is equal to the ergotropy. Thus, we aim to
identify and investigate the contributions to the ergotropy coming from
different kinds of initial correlations (total, classical, discord and
entanglement correlations). By doing so, we have introduced and studied
quantifiers of correlations which are based on ergotropy. In particular, our
results suggest that only discord correlations always give a positive
contribution to work extraction, while total, classical and entanglement
correlations can reduce the work extraction.


title:
Partial regularity for degenerate parabolic systems with non-standard
  growth and discontinuous coefficients

abstract:
  This article studies the partial H\"older continuity of weak solutions to
certain degenerate parabolic systems whose model is the differentiable
parabolic $p(x,t)$-Laplacian system, \begin{equation*}\partial_t
u-\operatorname{div}[\mu(z)(1+|Du|^2)^{\frac{p(z)-2}{2}}Du]=0,\qquad
p(z)\geq2.\end{equation*} Here, the exponential function $p(z)$ satisfies a
logarithmic continuity condition. We show that if $\mu(z)$ satisfies a certain
VMO-type condition, then $u$ is locally H\"older continuous except for a
measure zero set.


title: The tropical discriminant of a polynomial map on a plane

abstract:
  The discriminant of a polynomial map between two spaces is an object central
to many problems in mathematics. Standard methods for computing it rely on
elimination techniques which can be inefficient. This paper concerns polynomial
maps on the two-dimensional torus defined over the field of Puiseux series with
complex coefficients. We present a combinatorial procedure for computing the
tropical curve of the discriminant of such maps that satisfy some mild
genericity conditions. Thanks to the advances made in tropical geometry, our
results give rise to a new tool for investigating the discriminant of a complex
polynomial map on the plane, and for computing its Newton polytope.


title: Leveraging Multi-Connectivity for Multicast Video Streaming

abstract:
  Multi-connectivity has emerged as a key enabler for providing seamless
connectivity in cellular mobile networks. However, its potential for improving
the quality of multicast transmissions has remained unexplored. In this paper,
we investigate the use of multi-connectivity in wireless multicast streaming.
Multi-connectivity can significantly improve the performance of multicast
services. It especially benefits the cell edge users who often suffer from poor
channel conditions. In this work, we assess the impact of multi-connectivity on
the performance of multicast streaming. We propose procedures for establishing
multi-connectivity in a multicast system and address the associated resource
allocation problem. We prove that the optimal resource allocation problem is
NP-hard. We propose a greedy approximation algorithm for this problem and prove
that no other polynomial-time algorithm can provide a better approximation.
Since video streaming is the primary use case under consideration here, we use
traces from actual videos to generate realistic video traffic patterns in our
simulations. Our simulation results clearly establish that multi-connectivity
results in considerable performance improvement in multicast streaming.


title: Exploiting Spatial Sparsity for Event Cameras with Visual Transformers

abstract:
  Event cameras report local changes of brightness through an asynchronous
stream of output events. Events are spatially sparse at pixel locations with
little brightness variation. We propose using a visual transformer (ViT)
architecture to leverage its ability to process a variable-length input. The
input to the ViT consists of events that are accumulated into time bins and
spatially separated into non-overlapping sub-regions called patches. Patches
are selected when the number of nonzero pixel locations within a sub-region is
above a threshold. We show that by fine-tuning a ViT model on the selected
active patches, we can reduce the average number of patches fed into the
backbone during the inference by at least 50% with only a minor drop (0.34%) of
the classification accuracy on the N-Caltech101 dataset. This reduction
translates into a decrease of 51% in Multiply-Accumulate (MAC) operations and
an increase of 46% in the inference speed using a server CPU.


title: Light Baryon Spectroscopy

abstract:
  This review treats the advances in Light Baryon Spectroscopy of the last two
decades, which were mainly obtained by measuring meson-production reactions at
photon facilities all over the world. We provide a consistent compendium of
experimental results, as well as a review of the theoretical methods of
amplitude analysis used to analyze the data. The most significant datasets are
presented in detail and are listed in combination with a full set of the
relevant references. In addition, a brief summary of spin-formalisms, which are
ubiquitous in Light Baryon Spectroscopy, as well as a review on complete
experiments, are provided. The synthesis of the reviewed knowledge is presented
in a full interpretation of the new results on the Light Baryon Spectrum.


title:
Elucidating the rho-meson's role as intermediate resonance in the
  time-like electromagnetic pion form factor

abstract:
  Motivated by the planned measurements of the time-like electromagnetic proton
form factors an exploratory study of the time-like electromagnetic pion form
factor is presented in a formalism which describes mesons as
Poincar\'e-invariant bound states. In the respective quark interaction kernel,
beyond the gluon-intermediated interactions for valence-type quarks,
non-valence effects are included by allowing the pions to couple back in a
self-consistent manner to the quarks. Consequently, the opening of the dominant
$\rho$ decay channel, $\rho \to \pi\pi$, and the presence of a multi-particle
branch cut, setting in when the two-pion threshold is crossed, are included
consistently, first in the correspondingly calculated quark-photon vertex, and
then consequently in the time-like electromagnetic pion form factor. The
obtained results are in agreement with the available experimental data and
provide further evidence for the efficacy of a vector-meson dominance model.
Effects of going beyond the here employed isospin-symmetric limit are
discussed. Last but not least, an outlook is provided on how to include in
Poincar\'e-covariant Faddeev approaches the effects of intermediate resonances
in the calculation of baryon properties.


title: A VM/Containerized Approach for Scaling TinyML Applications

abstract:
  Although deep neural networks are typically computationally expensive to use,
technological advances in both the design of hardware platforms and of neural
network architectures, have made it possible to use powerful models on edge
devices. To enable widespread adoption of edge based machine learning, we
introduce a set of open-source tools that make it easy to deploy, update and
monitor machine learning models on a wide variety of edge devices. Our tools
bring the concept of containerization to the TinyML world. We propose to
package ML and application logic as containers called Runes to deploy onto edge
devices. The containerization allows us to target a fragmented
Internet-of-Things (IoT) ecosystem by providing a common platform for Runes to
run across devices.


title: A Geometric Realization of Symmetric Pairs of Type AIII

abstract:
  In this paper, we construct a geometric realization of symmetric pair of type
AIII over $\sigma$-quiver varieties as an analogy of the construction over
Nakajima quiver varieties. To achieve this, we define the action of generators
by pull back and push forward through $\iota$Hecke correspondences and check
the relations.


title:
TV-based Spline Reconstruction with Fourier Measurements: Uniqueness and
  Convergence of Grid-Based Methods

abstract:
  We study the problem of recovering piecewise-polynomial periodic functions
from their low-frequency information. This means that we only have access to
possibly corrupted versions of the Fourier samples of the ground truth up to a
maximum cutoff frequency $K_c$. The reconstruction task is specified as an
optimization problem with total-variation (TV) regularization (in the sense of
measures) involving the $M$-th order derivative regularization operator
$\mathrm{L} = \mathrm{D}^M$. The order $M \geq 1$ determines the degree of the
reconstructed piecewise polynomial spline, whereas the TV regularization norm,
which is known to promote sparsity, guarantees a small number of pieces. We
show that the solution of our optimization problem is always unique, which, to
the best of our knowledge, is a first for TV-based problems. Moreover, we show
that this solution is a periodic spline matched to the regularization operator
$\mathrm{L}$ whose number of knots is upper-bounded by $2 K_c$. We then
consider the grid-based discretization of our optimization problem in the space
of uniform $\mathrm{L}$-splines. On the theoretical side, we show that any
sequence of solutions of the discretized problem converges uniformly to the
unique solution of the gridless problem as the grid size vanishes. Finally, on
the algorithmic side, we propose a B-spline-based algorithm to solve the
grid-based problem, and we demonstrate its numerical feasibility
experimentally. On both of these aspects, we leverage the uniqueness of the
solution of the original problem.


title:
Towards a Global QCD Analysis of Fragmentation Functions at
  Next-To-Next-To-Leading Order Accuracy

abstract:
  We carry out a global QCD analysis of parton-to-pion fragmentation functions
at next-to-next-to-leading order (NNLO) accuracy by performing a fit to the
combined set of single-inclusive electron-positron annihilation and, for the
first time, semi-inclusive deep-inelastic scattering (SIDIS) multiplicity data.
For the latter, we utilize the approximate NNLO QCD corrections that were
derived recently within the threshold resummation formalism. We explore the
impact of the NNLO corrections on the description of the SIDIS data sets in
various kinematic regimes and on the resulting pion fragmentation functions.


title: Quark deconfinement in compact stars through sexaquark condensation

abstract:
  In this contribution, we present for the first time a scenario according to
which early quark deconfinement in compact stars is triggered by the
Bose-Einstein condensation (BEC) of a light sexaquark (S) with a mass
$m_S<2054$ MeV, that has been suggested as a candidate particle to explain the
baryonic dark matter in the Universe. The onset of S BEC marks the maximum mass
of hadronic neutron stars and it occurs when the condition for the baryon
chemical potential $\mu=m_S/2$ is fulfilled in the center of the star,
corresponding to $M_{\rm onset}\lesssim 0.7~M_\odot$. In the gravitational
field of the star the density of the BEC of the S increases until a new state
of the matter is attained, where each of the S-states got dissociated into a
triplet of color-flavor-locked (CFL) diquark states. These diquarks are the
Cooper pairs in the color superconducting CFL phase of quark matter, so that
the developed scenario corresponds to a Bose-Einstein condensation -
Bardeen-Cooper-Schrieffer (BEC-BCS) transition in strongly interacting matter.
For the description of the CFL phase, we develop here for the first time the
three-flavor extension of the density-functional formulation of a chirally
symmetric Lagrangian model of quark matter where confining properties are
encoded in a divergence of the scalar self-energy at low densities and
temperatures.


title: Equivariance Regularization for Image Reconstruction

abstract:
  In this work, we propose Regularization-by-Equivariance (REV), a novel
structure-adaptive regularization scheme for solving imaging inverse problems
under incomplete measurements. This regularization scheme utilizes the
equivariant structure in the physics of the measurements -- which is prevalent
in many inverse problems such as tomographic image reconstruction -- to
mitigate the ill-poseness of the inverse problem. Our proposed scheme can be
applied in a plug-and-play manner alongside with any classic first-order
optimization algorithm such as the accelerated gradient descent/FISTA for
simplicity and fast convergence. The numerical experiments in sparse-view X-ray
CT image reconstruction tasks demonstrate the effectiveness of our approach.


title: PCENet: High Dimensional Surrogate Modeling for Learning Uncertainty

abstract:
  Learning data representations under uncertainty is an important task that
emerges in numerous machine learning applications. However, uncertainty
quantification (UQ) techniques are computationally intensive and become
prohibitively expensive for high-dimensional data. In this paper, we present a
novel surrogate model for representation learning and uncertainty
quantification, which aims to deal with data of moderate to high dimensions.
The proposed model combines a neural network approach for dimensionality
reduction of the (potentially high-dimensional) data, with a surrogate model
method for learning the data distribution. We first employ a variational
autoencoder (VAE) to learn a low-dimensional representation of the data
distribution. We then propose to harness polynomial chaos expansion (PCE)
formulation to map this distribution to the output target. The coefficients of
PCE are learned from the distribution representation of the training data using
a maximum mean discrepancy (MMD) approach. Our model enables us to (a) learn a
representation of the data, (b) estimate uncertainty in the high-dimensional
data system, and (c) match high order moments of the output distribution;
without any prior statistical assumptions on the data. Numerical experimental
results are presented to illustrate the performance of the proposed method.


title:
The Goeritz group of a Heegaard splitting of genus two of a Seifert
  manifold whose base orbifold is sphere with three exceptional points of
  sufficiently complex coefficients

abstract:
  In this paper, we add examples to Goeritz groups, the mapping class groups of
given Heegaard splittings of 3-manifolds. We focus on a Heegaard splitting of
genus two of a Seifert manifold whose base orbifold is sphere with three
exceptional points of sufficiently complex coefficients, where "sufficiently
complex" means that every surgery coefficient p_{l} over q_{l} of each
exceptional fiber (in a surgery description) satisfies that q_{l} is congruent
to neither +1 or -1 modulo p_{l}.


title:
Natural Language in Requirements Engineering for Structure Inference --
  An Integrative Review

abstract:
  The automatic extraction of structure from text can be difficult for
machines. Yet, the elicitation of this information can provide many benefits
and opportunities for various applications. Benefits have also been identified
for the area of Requirements Engineering. To evaluate what work has been done
and is currently available, the paper at hand provides an integrative review
regarding Natural Language Processing (NLP) tools for Requirements Engineering.
This assessment was conducted to provide a foundation for future work as well
as deduce insights from the stats quo. To conduct the review, the history of
Requirements Engineering and NLP are described as well as an evaluation of over
136 NLP tools. To assess these tools, a set of criteria was defined. The
results are that currently no open source approach exists that allows for the
direct/primary extraction of information structure and even closed source
solutions show limitations such as supervision or input limitations, which
eliminates the possibility for fully automatic and universal application. As a
results, the authors deduce that the current approaches are not applicable and
a different methodology is necessary. An approach that allows for individual
management of the algorithm, knowledge base, and text corpus is a possibility
being pursued.


title: Testing the accretion scenario of lambda Boo stars

abstract:
  Our aim is to test the accretion scenario of lambda Boo stars. This model
predicts that a binary system with two early-type stars passing through a
diffuse cloud should both display the same superficial peculiarity. We carried
out a detailed abundance determination of three multiple systems hosting a
candidate lambda Boo star: the remarkable triple system HD 15164/65/65C and the
binary systems HD 193256/281 and HD 198160/161. The abundance analysis of HD
15164/65/65C shows a clear lambda Boo object (HD 15165) and two objects with
near solar composition (HD 15164 and 15165C). Notably, the presence of a lambda
Boo star (HD 15165) together with a near solar early-type object (HD 15164) is
difficult to explain under the accretion scenario. Also, the solar-like
composition derived for the late-type star of the system (HD 15165C) could be
used, for the first time, as a proxy for the initial composition of the lambda
Boo stars. Then, by reviewing abundance analysis of all known binary systems
with candidate lambda Boo stars from literature and including the systems
analyzed here, we find no binary/multiple system having two clear "bonafide"
lambda Boo stars, as expected from the accretion scenario. The closer
candidates to show two lambda Boo-like stars are HD 84948, HD 171948 and HD
198160; however, in our opinion they show mild rather than clear lambda Boo
patterns. Our results brings little support to the accretion scenario. Then,
there is an urgent need of additional binary and multiple systemsto be analyzed
through a detailed abundance analysis.[abridged]


title: On a class of Hessian type equations on Riemannian manifolds

abstract:
  In this paper, we consider a class of Hessian type equations which include
the $(n-1)$ Monge-Amp\`{e}re equation on Riemannian manifolds. The \emph{a
priori} $C^2$ estimates and the existence of solutions are established.


title:
Controlling the Complexity and Lipschitz Constant improves polynomial
  nets

abstract:
  While the class of Polynomial Nets demonstrates comparable performance to
neural networks (NN), it currently has neither theoretical generalization
characterization nor robustness guarantees. To this end, we derive new
complexity bounds for the set of Coupled CP-Decomposition (CCP) and Nested
Coupled CP-decomposition (NCP) models of Polynomial Nets in terms of the
$\ell_\infty$-operator-norm and the $\ell_2$-operator norm. In addition, we
derive bounds on the Lipschitz constant for both models to establish a
theoretical certificate for their robustness. The theoretical results enable us
to propose a principled regularization scheme that we also evaluate
experimentally in six datasets and show that it improves the accuracy as well
as the robustness of the models to adversarial perturbations. We showcase how
this regularization can be combined with adversarial training, resulting in
further improvements.


title:
Transfer-Learning Across Datasets with Different Input Dimensions: An
  Algorithm and Analysis for the Linear Regression Case

abstract:
  With the development of new sensors and monitoring devices, more sources of
data become available to be used as inputs for machine learning models. These
can on the one hand help to improve the accuracy of a model. On the other hand
however, combining these new inputs with historical data remains a challenge
that has not yet been studied in enough detail. In this work, we propose a
transfer-learning algorithm that combines the new and the historical data, that
is especially beneficial when the new data is scarce. We focus the approach on
the linear regression case, which allows us to conduct a rigorous theoretical
study on the benefits of the approach. We show that our approach is robust
against negative transfer-learning, and we confirm this result empirically with
real and simulated data.


title: New Opportunities in Femto-to-Nanometer Scale with High-Intensity Lasers

abstract:
  On the scale of nanometer to femtometer, there have several puzzles,
including neutron lifetime, proton charge radius, and deep Dirac level, etc.
With the development of high-intensity laser technologies, lasers today can
induce extremely strong electromagnetic (EM) fields. Electrons in deep shells
of atoms, as well as the atomic nucleus themself, can be affected by the laser
EM fields. This may provide a new experimental platform for studies the
physical processes on the femto-to-nanometer scale, where atomic physics and
nuclear physics coexist. In this paper, we review possible new opportunities
for studying the puzzles on femto-to-nanometer scale with high-intensity
lasers.


title:
Experimental study of turbulent transport of nanoparticles in convective
  turbulence

abstract:
  We perform experimental study of turbulent transport of nanoparticles in
convective turbulence with the Rayleigh number $\sim 10^8$ in the air flow. We
measure temperature field in many locations by a temperature probe equipped
with 11 E-thermocouples. Nanoparticles of the size $\sim 70$ nm in diameter are
produced by Advanced Electrospray Aerosol Generator. To determine the number
density of nanoparticles, we use Condensation Particle Counter. We demonstrate
that the joint action of turbulent effects (which are important in the core
flow) and molecular effects (which are essential near the boundaries of the
chamber) results in an effective accumulation of nanoparticles at the cold wall
of the chamber. The turbulent effects are characterised by turbulent diffusion
and turbulent thermal diffusion of nanoparticles, while the molecular effects
are described by the Brownian diffusion and thermophoresis, as well as the
adhesion of nanoparticles at the cold wall of the chamber. In different
experiments in convective turbulence in a chamber with the temperature
difference $\Delta T$ between the bottom and top walls varying between $\Delta
T= 29$ K to $\Delta T= 61$ K, we find that the mean number density of
nanoparticles decreases exponentially in time. For instance, the characteristic
decay time of the mean number density of nanoparticles varies from 12.8 min for
$\Delta T= 61$ K to 24 min for $\Delta T= 29$ K. For better understanding of
experimental results, we perform one-dimensional mean-field numerical
simulations of the evolution of the mean number density of nanoparticles for
conditions pertinent to the laboratory experiments. The obtained numerical
results are in a good agreement with the experimental results.


title:
Optimised operation of low-emission offshore oil and gas platform
  integrated energy systems

abstract:
  This paper considers the operation of offshore oil and gas platform energy
systems with energy supply from wind turbines to reduce local CO2 emissions. A
new integrated energy system model for operational planning and simulation has
been developed and implemented in an open-source software tool (Oogeso). This
model and tool is first presented, and then applied on a relevant North Sea
case with different energy supply alternatives to quantify and compare CO2
emission reductions and other key indicators.


title: Computer Validation of Neural Network Dynamics: A First Case Study

abstract:
  A large number of current machine learning methods rely upon deep neural
networks. Yet, viewing neural networks as nonlinear dynamical systems, it
becomes quickly apparent that mathematically rigorously establishing certain
patterns generated by the nodes in the network is extremely difficult. Indeed,
it is well-understood in the nonlinear dynamics of complex systems that, even
in low-dimensional models, analytical techniques rooted in pencil-and-paper
approaches reach their limits quickly. In this work, we propose a completely
different perspective via the paradigm of rigorous numerical methods of
nonlinear dynamics. The idea is to use computer-assisted proofs to validate
mathematically the existence of nonlinear patterns in neural networks. As a
case study, we consider a class of recurrent neural networks, where we prove
via computer assistance the existence of several hundred Hopf bifurcation
points, their non-degeneracy, and hence also the existence of several hundred
periodic orbits. Our paradigm has the capability to rigorously verify complex
nonlinear behaviour of neural networks, which provides a first step to explain
the full abilities, as well as potential sensitivities, of machine learning
methods via computer-assisted proofs.


title:
Leveraging Google's Publisher-specific IDs to Detect Website
  Administration

abstract:
  Digital advertising is the most popular way for content monetization on the
Internet. Publishers spawn new websites, and older ones change hands with the
sole purpose of monetizing user traffic. In this ever-evolving ecosystem, it is
challenging to effectively answer questions such as: Which entities monetize
what websites? What categories of websites does an average entity typically
monetize on and how diverse are these websites? How has this website
administration ecosystem changed across time?
  In this paper, we propose a novel, graph-based methodology to detect
administration of websites on the Web, by exploiting the ad-related
publisher-specific IDs. We apply our methodology across the top 1 million
websites and study the characteristics of the created graphs of website
administration. Our findings show that approximately 90% of the websites are
associated each with a single publisher, and that small publishers tend to
manage less popular websites. We perform a historical analysis of up to 8
million websites, and find a new, constantly rising number of (intermediary)
publishers that control and monetize traffic from hundreds of websites, seeking
a share of the ad-market pie. We also observe that over time, websites tend to
move from big to smaller administrators.


title: Beta decay of halo nuclei

abstract:
  Beta decay is a well-established and efficient probe of nuclear structure and
provides important information also for halo nuclei. Detailed decay studies of
near-dripline nuclei are challenging, but are now feasible due to the technical
progress during the last decades in isotope production as well as detection
capabilities. The halo structure can change the dynamics of the decay process,
most noticably when decays proceed directly to continuum states as seems to be
the case in beta-delayed deuteron emission, a process only observed until now
for the halo nuclei $^6$He and $^{11}$Li. The pronounced clustering in halo
states also leaves an imprint on the decay patterns, although the isospin
symmetry remains important; in several cases the isobaric analogue states of
halo states have also been established. Beta-delayed particle emission channels
can be expected to dominate the decays of heavier halo nuclei, if not in terms
of branching ratio than certainly in terms of beta strength. A remaining
challenge is to find experimental as well as theoretical tools to study the
multi-neutron final states that appear for most neutron dripline nuclei.


title:
Volterra equations driven by rough signals 3: Probabilistic construction
  of the Volterra rough path for fractional Brownian motions

abstract:
  Based on the recent development of the framework of Volterra rough paths, we
consider here the probabilistic construction of the Volterra rough path
associated to the fractional Brownian motion with $H>\frac{1}{2}$ and for the
standard Brownian motion. The Volterra kernel $k(t,s)$ is allowed to be
singular, and behaving similar to $|t-s|^{-\gamma}$ for some $\gamma\geq 0$.
The construction is done in both the Stratonovich and It\^o sense. It is based
on a modified Garsia-Rodemich-Romsey lemma which has an interest in its own
right, as well as tools from Malliavin calculus. A discussion of challenges and
potential extensions is provided.


title: Congruences for sums involving products of three binomial coefficients

abstract:
  Let $p>3$ be a prime, and let $a$ be a rational $p$-adic integer, using WZ
method we establish the congruences modulo $p^3$ for $$\sum_{k=0}^{p-1} \binom
ak\binom{-1-a}k\binom{2k}k\frac {w(k)}{4^k},$$ where $$w(k)=1,\frac
1{k+1},\frac 1{(k+1)^2},\frac 1{(k+1)^3},\frac 1{2k-1},\frac 1{k+2}, \frac
1{k+3}, k,k^2,k^3,\frac 1{a+k},\frac 1{a+k-1}.$$ As consequences, taking
$a=-\frac 12,-\frac 13,-\frac 14,-\frac 16$ we deduce many congruences modulo
$p^3$ and so solve some conjectures posed by the author earlier.


title:
Reply to Chen and Ni on "Explicit analytical solution for random close
  packing in $d=2$ and $d=3$"

abstract:
  We show that very clear answers to the queries raised by D. Chen and R. Ni in
their Comment on our recent paper [A. Zaccone, Phys. Rev. Lett. 128, 028002
(2022)] can be found in our original paper already. The paper [A. Zaccone,
Phys. Rev. Lett. 128, 028002 (2022)] is free of mathematical errors, as anyone
can easily verify, and all the assumptions were carefully, and critically
discussed in the paper.


title:
Who Funds Misinformation? A Systematic Analysis of the Ad-related Profit
  Routines of Fake News sites

abstract:
  Fake news is an age-old phenomenon, widely assumed to be associated with
political propaganda published to sway public opinion. Yet, with the growth of
social media it has become a lucrative business for web publishers. Despite
many studies performed and countermeasures deployed from researchers and
stakeholders, unreliable news sites have increased their share of engagement
among the top performing news sources in last years. Indeed, stifling fake news
impact depends on the efforts from the society, and the market, in limiting the
(economic) incentives of fake news producers.
  In this paper, we aim at enhancing the transparency around these exact
incentives and explore the following main questions: Who supports the existence
of fake news websites via paid ads, either as an advertiser or an ad seller?
Who owns these websites and what other Web business are they into? What
tracking activity do they perform in these websites?
  Aiming to answer these questions, we are the first to systematize the
auditing process of fake news revenue flows. We develop a novel ad detection
methodology to identify the companies that advertise in fake news websites and
the intermediary companies responsible for facilitating those ad revenues. We
study more than 2400 popular fake and real news websites and show that
well-known legitimate ad networks, such as of Google, IndexExchange, and
AppNexus, have a direct advertising relation with more than 40% of these fake
news websites, and a re-seller advertising relation with more than 60% of them.
Using a graph clustering approach on an extended set of 114.5K sites connected
with 443K edges, we show that entities who own fake news websites, also own (or
operate) other types of websites for entertainment, business, and politics,
pointing to the fact that owning a fake news website is part of a broader
business operation.


title:
On an Asymptotic Criterion for Blockchain Design: The Asynchronous
  Composition Model

abstract:
  Inspired by blockchains, we introduce a dynamically growing model of rooted
Directed Acyclic Graphs (DAGs) referred to as the asynchronous composition
model, subject to i.i.d. random delays $(\xi_t)$ with finite mean. The new
vertex at time $t$ is connected to vertices chosen from the graph
$G_{(t-\xi_t)_+}$ according to a construction function $f$ and the graph is
updated by taking union with the graph $G_{t-1}$. This process corresponds to
adding new blocks in a blockchain, where the delays arise due to network
communication. The main question of interest is the end structure of the
asynchronous limit of the graph sequence as time increases to infinity.
  We consider the following construction functions of interest, a) Nakamoto
construction $f_{\mathrm{Nak}}$, in which a vertex is uniformly selected from
those furthest from the root, resulting in a tree, and b) mixture of
construction functions $(f_k)_{1\le k\le \infty}$, where in $f_k$ a random set
of $k$ leaves (all if there are less than $k$ in total) is chosen without
replacement. The main idea behind the analysis is decoupling the time-delay
process from the DAG process and constructing an appropriate regenerative
structure in the time-delay process giving rise to Markovian behavior for a
functional of the DAG process. We establish that the asynchronous limits for
$f_\mathrm{Nak}, (f_k)_{k \ge 2}$, and any non-trivial mixture $f$ are
one-ended, while the asynchronous limit for $f_1$ has infinitely many ends,
almost surely. We also study fundamental growth properties of the longest path
for the sequence of graphs for $f_\mathrm{Nak}$. In addition, we prove a phase
transition on the (time and sample-path dependent) probability of choosing
$f_1$ such that the asynchronous limit either has one or infinitely many ends.
Finally, we show that the construction $f_\infty$ is an appropriate limit of
the $(f_k)_k$.


title:
An efficient contextual ontological model of $n$-qubit stabilizer
  quantum mechanics

abstract:
  The most well-known tool for studying contextuality in quantum computation is
the n-qubit stabilizer state tableau representation. We provide an extension
that describes not only the quantum state, but is also outcome deterministic.
The extension enables a value assignment to exponentially many Pauli
observables, yet remains quadratic in both memory and computational complexity.
Furthermore, we show that the mechanisms employed for contextuality and
measurement disturbance are wholly separate. The model will be useful for
investigating the role of contextuality in $n$-qubit quantum computation.


title: Identification of b-jets using QCD-inspired observables

abstract:
  We study the issue of separating hadronic jets that contain bottom quarks
($b$-jets) from jets featuring light partons only. We develop a novel approach
to $b$-tagging that exploits the application of QCD-inspired jet substructure
observables such as one-dimensional jet angularities and the two-dimensional
primary Lund plane. We demonstrate that these observables can be used as inputs
to modern machine-learning algorithms to efficiently separate $b$-jets from
light ones. In order to test our tagging procedure, we consider simulated
events where a $Z$ boson is produced is association with jets and show that
using jet angularities as an input for a deep neural network, as well as using
images obtained from the primary Lund jet plane as input to a convolutional
neural network, one can achieve tagging accuracy comparable with the accuracy
of conventional track-based taggers. We argue that the complementary usage of
the track-based taggers together with the ones based upon QCD-inspired
observables could improve $b$-tagging accuracy.


title: Cross-speaker style transfer for text-to-speech using data augmentation

abstract:
  We address the problem of cross-speaker style transfer for text-to-speech
(TTS) using data augmentation via voice conversion. We assume to have a corpus
of neutral non-expressive data from a target speaker and supporting
conversational expressive data from different speakers. Our goal is to build a
TTS system that is expressive, while retaining the target speaker's identity.
The proposed approach relies on voice conversion to first generate high-quality
data from the set of supporting expressive speakers. The voice converted data
is then pooled with natural data from the target speaker and used to train a
single-speaker multi-style TTS system. We provide evidence that this approach
is efficient, flexible, and scalable. The method is evaluated using one or more
supporting speakers, as well as a variable amount of supporting data. We
further provide evidence that this approach allows some controllability of
speaking style, when using multiple supporting speakers. We conclude by scaling
our proposed technology to a set of 14 speakers across 7 languages. Results
indicate that our technology consistently improves synthetic samples in terms
of style similarity, while retaining the target speaker's identity.


title: Geodesic Anosov flows, hyperbolic closed geodesics and stable ergodicity

abstract:
  In this paper we show that the geodesic flow of a Finsler metric is Anosov if
and only if there exists a $C^2$ open neighborhood of Finsler metrics all of
whose closed geodesics are hyperbolic. For surfaces this result holds also for
Riemannian metrics. This follows from a recent result of Contreras and
Mazzucchelli. Furthermore, geodesic flows of Riemannian or Finsler metrics on
surfaces are $C^2$ stably ergodic if and only if they are Anosov.


title: MONI can find k-MEMs

abstract:
  Maximal exact matches (MEMs) have been widely used in bioinformatics at least
since Li (2013) presented BWA-MEM. Building on work by Bannai, Gagie and I
(2018), Rossi et al.\ (2022) recently built an index called MONI, based on the
run-length compressed Burrows-Wheeler Transform, that can find MEMs efficiently
with respect to pangenomes. In this paper we define $k$-MEMs to be maximal
substrings of a pattern that each occur exactly at $k$ times in a text (so a
MEM is a 1-MEM) and show that, when $k$ is given at construction time, MONI can
find $k$-MEMs efficiently as well.