title: Dust in AGB wind-ISM interaction regions

abstract:
  We aim to constrain the dust mass and grain sizes in the interaction regions
between the stellar winds and the ISM around asymptotic giant branch stars. By
describing the dust in these regions, we aim to shed light on the role of low
mass evolved stars in the origin of dust in galaxies. We use images in the
far-infrared at 70 micron and 160 micron to derive dust temperatures and dust
masses in the wind-ISM interaction regions around a sample of carbon-rich and
oxygen-rich asymptotic giant branch (AGB) stars. The dust temperature and mass
are determined in two ways. First directly from the data using the ratio of the
measured fluxes and assuming opacities for dust with a constant grain size of
0.1 micron. We then perform 3D dust-radiative transfer models spatially
constrained by the observations to consistently calculate the temperature and
mass. For the radiative transfer models each model contains one constant grain
size, which is varied between 0.01 micron to 5.0 micron. We find that the
observed dust mass in the wind-ISM interaction regions is consistent with mass
accumulated from the stellar winds. For the carbon-rich sources adding the
spatial constraints in the radiative transfer models results in preferentially
larger grain sizes (approx. 2 micron). For the oxygen-rich sources the spatial
constraints result in too high temperatures in the models, making it impossible
to fit the observed far-infrared ratio irrespective of the grain size used,
indicating a more complex interplay of grain properties and the stellar
radiation field. The results have implications for how likely it is for the
grains to survive the transition into the ISM, and the properties of dust
particles that later act as seeds for grain growth in the ISM. However, the
results for the oxygen-rich sources show that the derivation of dust properties
is not straight forward, requiring more complex modelling


title: Symmetry and Classification of Multipartite Entangled States

abstract:
  One of the key manifestations of quantum mechanics is the phenomenon of
quantum entanglement. While the entanglement of bipartite systems is already
well understood, our knowledge of entanglement in multipartite systems is still
limited. This dissertation covers various aspects of the quantification of
entanglement in multipartite states and the role of symmetry in such systems.
Firstly, we establish a connection between the classification of multipartite
entanglement and knot theory and investigate the family of states that are
resistant to particle loss. Furthermore, we construct several examples of such
states using the Majorana representation as well as some combinatorial methods.
Secondly, we introduce classes of highly-symmetric but not fully-symmetric
states and investigate their entanglement properties. Thirdly, we study the
well-established class of Absolutely Maximally Entangled (AME) quantum states.
On one hand, we provide construction of new states belonging to this family,
for instance, an AME state of 4 subsystems with six levels each, on the other,
we tackle the problem of equivalence of such states. Finally, we present a
novel approach for the general problem of verification of the equivalence
between any pair of arbitrary quantum states based on a single polynomial
entanglement measure.


title:
TTAGN: Temporal Transaction Aggregation Graph Network for Ethereum
  Phishing Scams Detection

abstract:
  In recent years, phishing scams have become the most serious type of crime
involved in Ethereum, the second-largest blockchain platform. The existing
phishing scams detection technology on Ethereum mostly uses traditional machine
learning or network representation learning to mine the key information from
the transaction network to identify phishing addresses. However, these methods
adopt the last transaction record or even completely ignore these records, and
only manual-designed features are taken for the node representation. In this
paper, we propose a Temporal Transaction Aggregation Graph Network (TTAGN) to
enhance phishing scams detection performance on Ethereum. Specifically, in the
temporal edges representation module, we model the temporal relationship of
historical transaction records between nodes to construct the edge
representation of the Ethereum transaction network. Moreover, the edge
representations around the node are aggregated to fuse topological interactive
relationships into its representation, also named as trading features, in the
edge2node module. We further combine trading features with common statistical
and structural features obtained by graph neural networks to identify phishing
addresses. Evaluated on real-world Ethereum phishing scams datasets, our TTAGN
(92.8% AUC, and 81.6% F1score) outperforms the state-of-the-art methods, and
the effectiveness of temporal edges representation and edge2node module is also
demonstrated.


title:
Analysis of MC Systems Employing Receivers Covered by Heterogeneous
  Receptors

abstract:
  This paper investigates the channel impulse response (CIR), i.e., the
molecule hitting rate, of a molecular communication (MC) system employing an
absorbing receiver (RX) covered by multiple non overlapping receptors. In this
system, receptors are heterogeneous, i.e., they may have different sizes and
arbitrary locations. Furthermore, we consider two types of transmitter (TX),
namely a point TX and a membrane fusion (MF)-based spherical TX. We assume the
point TX or the center of the MF-based TX has a fixed distance to the center of
the RX. Given this fixed distance, the TX can be at different locations and the
CIR of the RX depends on the exact location of the TX. By averaging over all
possible TX locations, we analyze the expected molecule hitting rate at the RX
as a function of the sizes and locations of the receptors, where we assume
molecule degradation may occur during the propagation of the signaling
molecules. Notably, our analysis is valid for different numbers, a wide range
of sizes, and arbitrary locations of the receptors, and its accuracy is
confirmed via particle-based simulations. Exploiting our numerical results, we
show that the expected number of absorbed molecules at the RX increases with
the number of receptors, when the total area on the RX surface covered by
receptors is fixed. Based on the derived analytical expressions, we compare
different geometric receptor distributions by examining the expected number of
absorbed molecules at the RX. We show that evenly distributed receptors result
in a larger number of absorbed molecules than other distributions. We further
compare three models that combine different types of TXs and RXs.


title:
Mobile EEG artifact correction on limited hardware using artifact
  subspace recon- struction

abstract:
  Biological data like electroencephalography (EEG) are typically contaminated
by unwanted signals, called artifacts. Therefore, many applications dealing
with biological data with low signal-to-noise ratio require robust artifact
correction. For some applications like brain-computer-interfaces (BCI), the
artifact correction needs to be real-time capable. Artifact subspace
reconstruction (ASR) is a statistical method for artifact reduction in EEG.
However, in its current implementation, ASR cannot be used in mobile data
recordings using limited hardware easily. In this report, we add to the growing
field of portable, online signal processing methods by describing an
implementation of ASR for limited hardware like single-board computers. We
describe the architecture, the process of translating and compiling a Matlab
codebase for a research platform, and a set of validation tests using publicly
available data sets. The implementation of ASR on limited, portable hardware
facilitates the online interpretation of EEG signals acquired outside of the
laboratory environment.


title:
Bibliographic Analysis of the Capacity and Applicability of Li-Fi
  Networks

abstract:
  This article aims to bring a metric of capacities and applicability of Light
Fidelity (Li-Fi) as a communication system through a direct comparison to
subareas of Wireless Fidelity (Wi-Fi) communication, which is the main wireless
communication system. The actual vision of Li-fi in a global scenario was
discussed based on the use cases of this technology and your relation to 5th
Generation (5G) technology. Finally, the difficulties and new paths that this
system must still take were presented.


title: Persistent sheaf cohomology

abstract:
  We expand the toolbox of (co)homological methods in computational topology by
applying the concept of persistence to sheaf cohomology. Since sheaves (of
modules) combine topological information with algebraic information, they allow
for variation along an algebraic dimension and along a topological dimension.
Consequently, we introduce two different constructions of sheaf cohomology
(co)persistence modules. One of them can be viewed as a natural generalization
of the construction of simplicial or singular cohomology copersistence modules.
We discuss how both constructions relate to each other and show that, in some
cases, we can reduce one of them to the other. Moreover, we show that we can
combine both constructions to obtain two-dimensional (co)persistence modules
with a topological and an algebraic dimension. We also show that some classical
results and methods from persistence theory can be generalized to sheaves. Our
results open up a new perspective on persistent cohomology of filtrations of
simplicial complexes.


title:
The string topology coproduct on complex and quaternionic projective
  space

abstract:
  On the free loop space of compact symmetric spaces Ziller introduced explicit
cycles generating the homology of the free loop space. We use these explicit
cycles to compute the string topology coproduct on complex and quaternionic
projective space. The behavior of the Goresky-Hingston product for these spaces
then follows directly.


title: Spin of protons in NICA and PTR storage rings as an axion antenna

abstract:
  We discuss a new approach to search for axions in the storage ring
experiments, applicable at short coherence time of the in-plane polarization as
is the case for protons. The technique can readily be applied at any storage
ring equipped with internal polarimeter for the radial polarization of the beam
(COSY, NICA, PTR). We point out a possibility of substantial broadening of the
range of attianable axion masses in storage rings with the hybrid electric and
magnetic bending, the PTR proton storage ring being an example.


title: Transfinite almost square Banach spaces

abstract:
  It is known that a Banach space contains an isomorphic copy of $c_0$ if, and
only if, it can be equivalently renormed to be almost square. We introduce and
study transfinite versions of almost square Banach spaces with the purpose to
relate them to the containment of isomorphic copies of $c_0(\kappa)$, where
$\kappa$ is some uncountable cardinal. We also provide several examples and
stability results of the above properties by taking direct sums, tensor
products and ultraproducts. By connecting the above properties with transfinite
analogues of the strong diameter two property and octahedral norms, we obtain a
solution to an open question from [8].


title:
Unsteady rheo-optical measurements of uniaxially extending liquid
  polymers

abstract:
  The viscoelastic behavior of liquid polymers changes depending on the
microstructure of the polymer chains. To investigate the unsteady structural
changes induced by polymer chain morphology under stress, we develop a simple
rheo-optical technique combining a high-speed polarization camera and
dripping-onto-substrate capillary breakup extensional rheometry (CaBER-DoS),
which uniaxially extends and aligns the polymer along the stress direction.
Using this technique, the viscoelastic behavior and birefringence field of an
extending liquid polymer are simultaneously measured. Unlike the conditions
that occur under shear-stress loading with a rotational rheometer, this
technique provides a linear relation between birefringence and extensional
stress. The measurements reflect the structural change in a flexible polymer (a
mixed solution of PEO and CNCs) in the temporal evolution of the birefringence
and orientation angle, which is a measure of the orientation state and
coil-stretch transition of a polymer chain. Remarkably, within the
elasto-capillary regime, the measured birefringence remains constant with a
constant orientation state, while the Weissenberg number gradually increases,
which provides experimental evidence of the coil-stretch transition of the
polymer chain under constant extensional stress loading.


title:
Cumulative Stay-time Representation for Electronic Health Records in
  Medical Event Time Prediction

abstract:
  We address the problem of predicting when a disease will develop, i.e.,
medical event time (MET), from a patient's electronic health record (EHR). The
MET of non-communicable diseases like diabetes is highly correlated to
cumulative health conditions, more specifically, how much time the patient
spent with specific health conditions in the past. The common time-series
representation is indirect in extracting such information from EHR because it
focuses on detailed dependencies between values in successive observations, not
cumulative information. We propose a novel data representation for EHR called
cumulative stay-time representation (CTR), which directly models such
cumulative health conditions. We derive a trainable construction of CTR based
on neural networks that has the flexibility to fit the target data and
scalability to handle high-dimensional EHR. Numerical experiments using
synthetic and real-world datasets demonstrate that CTR alone achieves a high
prediction performance, and it enhances the performance of existing models when
combined with them.


title:
Unveiling non-gray surface of cloudy exoplanets: the influence of
  wavelength-dependent surface albedo and cloud scattering properties on
  retrieval solutions

abstract:
  Direct-imaging spectra hold rich information about a planet's atmosphere and
surface, and several space-based missions aiming at such observations will
become a reality in the near future. Previous spectral retrieval works have
resulted in key atmospheric constraints under the assumption of a gray surface,
but the effect of wavelength-dependent surface albedo on retrieval has not been
shown. We explore the influence of the coupling effect of cloud and
wavelength-dependent surface albedo on retrieval performance via modeling
suites of Earth-like atmospheres with varying cloud and surface albedo
parameterizations. Under the assumption of known cloud scattering properties,
the surface spectral albedos can be reasonably recovered when the surface cover
represents that of Earth-like vegetation or ocean, which may aid in
characterizing the planet's habitability. When the cloud scattering properties
cannot be assumed, we show that the degeneracy between the cloud properties and
wavelength-dependent surface albedo leads to biased results of atmospheric and
cloud properties. The multi-epoch visible band observations offer limited
improvement in disentangling this degeneracy. However, the constraints on
atmospheric properties from the combination of UV band (R $\sim 6$) $+$ visible
band (R $\sim 140$) are consistent with input values to within 1 $\sigma$. If
short bandpass data is not available, an alternative solution to reduce the
retrieval uncertainties would be to have the prior constraints on planetary
cloud fraction with less than 20% uncertainty.


title:
Deep Orientation-Aware Functional Maps: Tackling Symmetry Issues in
  Shape Matching

abstract:
  State-of-the-art fully intrinsic networks for non-rigid shape matching often
struggle to disambiguate the symmetries of the shapes leading to unstable
correspondence predictions. Meanwhile, recent advances in the functional map
framework allow to enforce orientation preservation using a functional
representation for tangent vector field transfer, through so-called complex
functional maps. Using this representation, we propose a new deep learning
approach to learn orientation-aware features in a fully unsupervised setting.
Our architecture is built on top of DiffusionNet, making it robust to
discretization changes. Additionally, we introduce a vector field-based loss,
which promotes orientation preservation without using (often unstable)
extrinsic descriptors.


title:
A new certified hierarchical and adaptive RB-ML-ROM surrogate model for
  parametrized PDEs

abstract:
  We present a new surrogate modeling technique for efficient approximation of
input-output maps governed by parametrized PDEs. The model is hierarchical as
it is built on a full order model (FOM), reduced order model (ROM) and
machine-learning (ML) model chain. The model is adaptive in the sense that the
ROM and ML model are adapted on-the-fly during a sequence of parametric
requests to the model. To allow for a certification of the model hierarchy, as
well as to control the adaptation process, we employ rigorous a posteriori
error estimates for the ROM and ML models. In particular, we provide an example
of an ML-based model that allows for rigorous analytical quality statements. We
demonstrate the efficiency of the modeling chain on a Monte Carlo and a
parameter-optimization example. Here, the ROM is instantiated by Reduced Basis
Methods and the ML model is given by a neural network or a VKOGA kernel model.


title:
Fuzzy Cognitive Maps and Hidden Markov Models: Comparative Analysis of
  Efficiency within the Confines of the Time Series Classification Task

abstract:
  Time series classification is one of the very popular machine learning tasks.
In this paper, we explore the application of Hidden Markov Model (HMM) for time
series classification. We distinguish between two modes of HMM application. The
first, in which a single model is built for each class. The second, in which
one HMM is built for each time series. We then transfer both approaches for
classifier construction to the domain of Fuzzy Cognitive Maps. The identified
four models, HMM NN (HMM, one per series), HMM 1C (HMM, one per class), FCM NN,
and FCM 1C are then studied in a series of experiments. We compare the
performance of different models and investigate the impact of their
hyperparameters on the time series classification accuracy. The empirical
evaluation shows a clear advantage of the one-model-per-series approach. The
results show that the choice between HMM and FCM should be dataset-dependent.


title:
Learning from Pixel-Level Noisy Label : A New Perspective for Light
  Field Saliency Detection

abstract:
  Saliency detection with light field images is becoming attractive given the
abundant cues available, however, this comes at the expense of large-scale
pixel level annotated data which is expensive to generate. In this paper, we
propose to learn light field saliency from pixel-level noisy labels obtained
from unsupervised hand crafted featured based saliency methods. Given this
goal, a natural question is: can we efficiently incorporate the relationships
among light field cues while identifying clean labels in a unified framework?
We address this question by formulating the learning as a joint optimization of
intra light field features fusion stream and inter scenes correlation stream to
generate the predictions. Specially, we first introduce a pixel forgetting
guided fusion module to mutually enhance the light field features and exploit
pixel consistency across iterations to identify noisy pixels. Next, we
introduce a cross scene noise penalty loss for better reflecting latent
structures of training data and enabling the learning to be invariant to noise.
Extensive experiments on multiple benchmark datasets demonstrate the
superiority of our framework showing that it learns saliency prediction
comparable to state-of-the-art fully supervised light field saliency methods.
Our code is available at https://github.com/OLobbCode/NoiseLF.


title:
Arithmetic modularity of special divisors and arithmetic mixed
  Siegel-Weil formula (with an appendix by Yujie Xu)

abstract:
  We refine Kudla's modularity problem for generating series of arithmetic
special divisors on unitary Shimura varieties over CM fields using S. Zhang's
theory of admissible cycles. The admissibility reduces the arithmetic
modularity to an arithmetic mixed Siegel-Weil formula. We prove the arithmetic
modularity when the level at nonsplit place is good and arbitrary at split
places. The innovation in proving the arithmetic mixed Siegel-Weil formula is
to compute arithmetic improper intersections using admissibility and modularity
on the generic fiber.


title:
Ultralow Electron-Surface Scattering in Nanoscale Metals Leveraging
  Fermi Surface Anisotropy

abstract:
  Increasing resistivity of metal wires with reducing nanoscale dimensions is a
major performance bottleneck of semiconductor computing technologies. We show
that metals with suitably anisotropic Fermi velocity distributions can strongly
suppress electron scattering by surfaces and outperform isotropic conductors
such as copper in nanoscale wires. We derive a corresponding descriptor for the
resistivity scaling of anisotropic conductors, screen thousands of metals using
first-principles calculations of this descriptor and identify the most
promising materials for nanoscale interconnects. Previously-proposed layered
conductors such as MAX phases and delafossites show promise in thin films, but
not in narrow wires due to increased scattering from side walls. We find that
certain intermetallics (notably CoSn) and borides (such as YCo$_3$B$_2$) with
one-dimensionally anisotropic Fermi velocities are most promising for narrow
wires. Combined with first-principles electron-phonon scattering predictions,
we show that the proposed materials exhibit 2-3x lower resistivity than copper
at 5 nm wire dimensions.


title:
Weighted Packet Selection for Rechargeable Links: Complexity and
  Approximation

abstract:
  We consider a natural problem dealing with weighted packet selection across a
rechargeable link, which e.g., finds applications in cryptocurrency networks.
The capacity of a link $(u,v)$ is determined by how much players $u$ and $v$
allocate for this link. Specifically, the input is a finite ordered sequence of
packets that arrive in both directions along a link. Given $(u, v)$ and a
packet of weight $x$ going from $u$ to $v$, player $u$ can either accept or
reject the packet. If player $u$ accepts the packet, their capacity on link
$(u,v)$ decreases by $x$. Correspondingly, player $v$ capacity on $(u,v)$
increases by $x$. If a player rejects the packet, this will entail a cost
linear in the weight of the packet. A link is "rechargeable" in the sense that
the total capacity of the link has to remain constant, but the allocation of
capacity at the ends of the link can depend arbitrarily on players' decisions.
The goal is to minimise the sum of the capacity injected into the link and the
cost of rejecting packets. We show the problem is NP-hard, but can be
approximated efficiently with a ratio of $(1+ \varepsilon)\cdot (1+\sqrt{3})$
for some arbitrary $\varepsilon >0$.


title:
Derivation of Learning Rules for Coupled Principal Component Analysis in
  a Lagrange-Newton Framework

abstract:
  We describe a Lagrange-Newton framework for the derivation of learning rules
with desirable convergence properties and apply it to the case of principal
component analysis (PCA). In this framework, a Newton descent is applied to an
extended variable vector which also includes Lagrange multipliers introduced
with constraints. The Newton descent guarantees equal convergence speed from
all directions, but is also required to produce stable fixed points in the
system with the extended state vector. The framework produces "coupled" PCA
learning rules which simultaneously estimate an eigenvector and the
corresponding eigenvalue in cross-coupled differential equations. We
demonstrate the feasibility of this approach for two PCA learning rules, one
for the estimation of the principal, the other for the estimate of an arbitrary
eigenvector-eigenvalue pair (eigenpair).


title: Around the support problem for Hilbert class polynomials

abstract:
  Let $H_D(T)$ denote the Hilbert class polynomial of the imaginary quadratic
order of discriminant $D$. We study the rate of growth of the greatest common
divisor of $H_D(a)$ and $H_D(b)$ as $|D| \to \infty$ for $a$ and $b$ belonging
to various Dedekind domains. We also study the modular support problem: if for
all but finitely many $D$ every prime ideal dividing $H_D(a)$ also divides
$H_D(b)$, what can we say about $a$ and $b$? If we replace $H_D(T)$ by $T^n-1$
and the Dedekind domain is a ring of $S$-integers in some number field, then
these are classical questions that have been investigated by
Bugeaud-Corvaja-Zannier, Corvaja-Zannier, and Corrales-Rodrig\'a\~{n}ez-Schoof.


title:
Observation of Griffiths-like phase in the quaternary Heusler compound
  NiFeTiSn

abstract:
  The quaternary Heusler compound NiFeTiSn can be considered to be derived from
the exotic pseudogap-compound Fe2TiSn by the replacement of one Fe atom by Ni.
In contrast to Fe2TiSn, which shows a disorder-induced ferromagnetic phase, the
ground state of NiFeTiSn is antiferromagnetic with the signature of spin
canting. Interestingly, NiFeTiSn shows a Griffiths-like phase characterized by
isolated ferromagnetic clusters before attaining the antiferromagnetic state.
The Griffiths-like phase is possibly associated with the antisite disorder
between Fe and Ti sites as evident from our powder X-ray diffraction study. The
compound also shows rather an unusual temperature dependence of resistivity,
which can be accounted for by the prevailing structural disorder in the system.
NiFeTiSn turned out to be a rare example where a Griffiths-like phase is
observed in a semiconducting 3d transition metal-based intermetallic compound
with an antiferromagnetic ground state.


title:
Efficient Approximation of Action Potentials with High-Order Shape
  Preservation in Unsupervised Spike Sorting

abstract:
  This paper presents a novel approximation unit added to the conventional
spike processing chain which provides an appreciable reduction of complexity of
the high-hardware cost feature extractors. The use of the Taylor polynomial is
proposed and modelled employing its cascaded derivatives to non-uniformly
capture the essential samples in each spike for reliable feature extraction and
sorting. Inclusion of the approximation unit can provide 3X compression (i.e.
from 66 to 22 samples) to the spike waveforms while preserving their shapes.
Detailed spike waveform sequences based on in-vivo measurements have been
generated using a customized neural simulator for performance assessment of the
approximation unit tested on six published feature extractors. For noise levels
{\sigma}_N between 0.05 and 0.3 and groups of 3 spikes in each channel, all the
feature extractors provide almost same sorting performance before and after
approximation. The overall implementation cost when including the approximation
unit and feature extraction shows a large reduction (i.e. up to 8.7X) in the
hardware costly and more accurate feature extractors, offering a substantial
improvement in feature extraction design.


title:
Stay Safe under Panic: Affine Rust Programming with Multiparty Session
  Types

abstract:
  Communicating systems comprise diverse software components across networks.
To ensure their robustness, modern programming languages such as Rust provide
both strongly typed channels, whose usage is guaranteed to be affine (at most
once), and cancellation operations over binary channels. For coordinating
components to correctly communicate and synchronise with each other, we use the
structuring mechanism from multiparty session types, extending it with affine
communication channels and implicit/explicit cancellation mechanisms. This new
typing discipline, affine multiparty session types (AMPST), ensures
cancellation termination of multiple, independently running components and
guarantees that communication will not get stuck due to error or abrupt
termination. Guided by AMPST, we implemented an automated generation tool
(MultiCrusty) of Rust APIs associated with cancellation termination algorithms,
by which the Rust compiler auto-detects unsafe programs. Our evaluation shows
that MultiCrusty provides an efficient mechanism for communication,
synchronisation and propagation of the notifications of cancellation for
arbitrary processes. We have implemented several usecases, including popular
application protocols (OAuth, SMTP), and protocols with exception handling
patterns (circuit breaker, distributed logging).


title: Attention Based Neural Networks for Wireless Channel Estimation

abstract:
  In this paper, we deploy the self-attention mechanism to achieve improved
channel estimation for orthogonal frequency-division multiplexing waveforms in
the downlink. Specifically, we propose a new hybrid encoder-decoder structure
(called HA02) for the first time which exploits the attention mechanism to
focus on the most important input information. In particular, we implement a
transformer encoder block as the encoder to achieve the sparsity in the input
features and a residual neural network as the decoder respectively, inspired by
the success of the attention mechanism. Using 3GPP channel models, our
simulations show superior estimation performance compared with other candidate
neural network methods for channel estimation.


title: Clustering Systems of Phylogenetic Networks

abstract:
  Rooted acyclic graphs appear naturally when the phylogenetic relationship of
a set $X$ of taxa involves not only speciations but also recombination,
horizontal transfer, or hybridization, that cannot be captured by trees. A
variety of classes of such networks have been discussed in the literature,
including phylogenetic, level-1, tree-child, tree-based, galled tree, regular,
or normal networks as models of different types of evolutionary processes.
Clusters arise in models of phylogeny as the sets $\mathtt{C}(v)$ of descendant
taxa of a vertex $v$. The clustering system $\mathscr{C}_N$ comprising the
clusters of a network $N$ conveys key information on $N$ itself. In the special
case of rooted phylogenetic trees, $T$ is uniquely determined by its clustering
system $\mathscr{C}_T$. Although this is no longer true for networks in
general, it is of interest to relate properties of $N$ and $\mathscr{C}_N$.
Here, we systematically investigate the relationships of several well-studied
classes of networks and their clustering systems. The main results are
correspondences of classes of networks and clustering system of the following
form: If $N$ is a network of type $\mathbb{X}$, then $\mathcal{C}_N$ satisfies
$\mathbb{Y}$, and conversely if $\mathscr{C}$ is a clustering system satisfying
$\mathbb{Y}$ then there is network $N$ of type $\mathbb{X}$ such that
$\mathscr{C}\subseteq\mathscr{C}_N$.This, in turn, allows us to investigate the
mutual dependencies between the distinct types of networks in much detail.


title: COSTI: a New Classifier for Sequences of Temporal Intervals

abstract:
  Classification of sequences of temporal intervals is a part of time series
analysis which concerns series of events. We propose a new method of
transforming the problem to a task of multivariate series classification. We
use one of the state-of-the-art algorithms from the latter domain on the new
representation to obtain significantly better accuracy than the
state-of-the-art methods from the former field. We discuss limitations of this
workflow and address them by developing a novel method for classification
termed COSTI (short for Classification of Sequences of Temporal Intervals)
operating directly on sequences of temporal intervals. The proposed method
remains at a high level of accuracy and obtains better performance while
avoiding shortcomings connected to operating on transformed data. We propose a
generalized version of the problem of classification of temporal intervals,
where each event is supplemented with information about its intensity. We also
provide two new data sets where this information is of substantial value.


title: Tests of gravity theories with pulsar timing

abstract:
  Over the last few years, a set of new results from pulsar timing has
introduced much tighter constraints on violations of the strong equivalence
principle (SEP), either via a direct verification of the universality of free
fall for a pulsar in a triple star system, or from tests of the nature of
gravitational waves, in particular a search for dipolar gravitational wave
emission in a variety of binary pulsars with different masses. No deviations
from the SEP have been detected in our experiments. These results introduce
some of the most stringent constraints on several classes of alternative
theories of gravity and complement recent results from the ground-based
gravitational wave detectors.


title:
Uncertainties in measuring the dark matter signal from Milky Way
  satellites using Cherenkov telescopes

abstract:
  In this work, we present a modelling of the galactic sub-clumps based on
statistical estimations of the full Milky Way satellite population. We
introduce 10 substructure modellings (SM$_{i}$, i $\in$ {1, . . . , 10}) with
the following varying parameters: a) subhalos inner profile, b) spatial
distribution of subhalos, c) mass distribution of subhalos, d) total number of
subhalos and e) concentration parameter. The sensitivity curves of CTA for
sources in each model are calculated for the $\tau^{+}\tau^{-}$ and $b\bar{b}$
annihilation channels. With both detection of a signal (5$\sigma$) with the CTA
and no signal observation, no model was effective in accessing the thermal
values of <$\sigma$ v>. We analyse the systematic effects introduced by the
substructures models.


title: Second-order properties for planar Mondrian tessellations

abstract:
  In this paper planar STIT tesselations with weighted axis-parallel cutting
directions are considered. They are known also as weighted planar Mondrian
tesselations in the machine learning literature, where they are used in random
forest learning and kernel methods. Various second-order properties of such
random tessellations are derived, in particular, explicit formulas are obtained
for suitably adapted versions of the pair- and cross-correlation functions of
the length measure on the edge skeleton and the vertex point process. Also,
explicit formulas and the asymptotic behaviour of variances are discussed in
detail.


title: On moduli spaces of roots in algebraic and tropical geometry

abstract:
  In this paper we construct a tropical moduli space parametrizing roots of
divisors on tropical curves. We study the relation between this space and the
skeleton of Jarvis moduli space of nets of limit roots on stable curves. We
show that the combinatorics of the moduli space of tropical roots is governed
by the poset of flows, a poset parametrizing certain flows on graphs. We show
many properties of connectedness of this poset and generalize some results on
linkage of graphs. We compare our results with recent results about the
tropicalization of the space of admissible covers.


title: Integral points on symmetric affine cubic surfaces

abstract:
  We show that if $f(u)\in \mathbb{Z}[u]$ is a monic cubic polynomial, then for
all but finitely many $n\in \mathbb{Z}$ the affine cubic surface
$f(u_{1})+f(u_{2})+f(u_{3})=n \subset \mathbb{A}^{3}_{\mathbb{Z}}$ has no
integral Brauer-Manin obstruction to the Hasse principle.


title: Spin-glass-like behaviour in SmFeAsO0.8F0.2

abstract:
  The iron-based oxypnictide superconductor SmFeAsO0.8F0.2 was synthesized
under high-pressure and investigated by measuring dc magnetic susceptibility.
The zero-field cooled (ZFC) magnetic susceptibility confirmed the bulk
superconductivity of the sample with a critical temperature of Tc = 50 K and a
significant jump in the magnetization at 4.3 K, usually attributed to the
antiferromagnetic ordering of Sm3+ ions in this system. Since the occurrence of
the jump depends on the cooling history, our data strongly suggest a
spin-glass-like behaviour.


title: Port-Hamiltonian Dynamic Mode Decomposition

abstract:
  We present a novel physics-informed system identification method to construct
a passive linear time-invariant system. In more detail, for a given quadratic
energy functional, measurements of the input, state, and output of a system in
the time domain, we find a realization that approximates the data well while
guaranteeing that the energy functional satisfies a dissipation inequality. To
this end, we use the framework of port-Hamiltonian (pH) systems and modify the
dynamic mode decomposition to be feasible for continuous-time pH systems. We
propose an iterative numerical method to solve the corresponding least-squares
minimization problem. We construct an effective initialization of the algorithm
by studying the least-squares problem in a weighted norm, for which we present
the analytical minimum-norm solution. The efficiency of the proposed method is
demonstrated with several numerical examples.

categories: math.DS cs.NA cs.SY eess.SY math.NA math.OC


title:
High-Order Discretization of Backward Anisotropic Diffusion and
  Application to Image Processing

abstract:
  Anisotropic diffusion is a well recognized tool in digital image processing,
including edge detection and denoising. We present here a particular nonlinear
time-dependent operator together with an appropriate high-order discretization
for the space variable. The iterative procedure emphasizes the contour lines
encircling the objects, paving the way to accurate reconstructions at a very
low cost. One of the main features of such an approach is the possibility of
relying on a rather large set of invariant discontinuous images, whose edges
can be determined without introducing any approximation.


title:
Spectral pulsations of dissipative solitons in ultrafast fiber lasers:
  period doubling and beyond

abstract:
  Period doubling is a universal bifurcation of central importance in all
disciplines of nonlinear science, which generally signals the existence of
chaotic dynamics in the vicinity of the system parameters. Although observed in
diverse ultrafast laser configurations, there is still no consensus on its
physical origin. The observations also include other types of pulsating
dissipative solitons, with either short or long periods. Real time spectral
characterization allows to investigate optical spectral oscillations, whose
features reveal the intracavity dynamics leading to instabilities. Following a
contextual review, this article presents a variety of period doubling dynamics
manifesting in the spectral domain of dissipative solitons. These dynamics are
obtained with ultrafast fiber lasers featuring either anomalous or normal
dispersion. It reveals a sequence of period doubling bifurcations and
instabilities within transient dynamics, unveiling intertwined bifurcations and
the entrainment of new pulsating frequencies. The oscillating frequencies tend
to lock to the integral of roundtrip numbers as well as coexist with period
doubling, demonstrating new combinations of the period doubling bifurcation
with other bifurcations. These experimental findings are confirmed by numerical
simulations, emphasizing both the universality of the period doubling
bifurcations and their potentially highly complicated manifestations within
ultrafast laser systems.


title: Prediction uncertainty validation for computational chemists

abstract:
  Validation of prediction uncertainty (PU) is becoming an essential tool for
modern computational chemistry. Designed to quantify the reliability of
predictions in meteorology, the calibration-sharpness (CS) framework is now
widely used to optimize and validate uncertainty-aware machine learning (ML)
methods. However, its application is not limited to ML and it can serve as a
principled framework for any PU validation. The present article is intended as
a step-by-step introduction to the concepts and techniques of PU validation in
the CS framework, adapted to the specifics of computational chemistry. The
presented methods range from elementary graphical checks to more sophisticated
ones based on local calibration statistics. The concept of tightness, is
introduced. The methods are illustrated on synthetic datasets and applied to
uncertainty quantification data extracted from the computational chemistry
literature.


title:
Observation of the $\gamma\gamma\to\tau\tau$ process in Pb+Pb collisions
  and constraints on the $\tau$-lepton anomalous magnetic moment with the ATLAS
  detector

abstract:
  This Letter reports the observation of $\tau$-lepton pair production in
ultraperipheral lead-lead collisions, $\text{Pb+Pb} \to \text{Pb}(\gamma\gamma
\to \tau\tau)\text{Pb}$, and constraints on the $\tau$-lepton anomalous
magnetic moment, $a_\tau$. The dataset corresponds to an integrated luminosity
of 1.44 nb$^{-1}$ of LHC Pb+Pb collisions at $\sqrt{s_{_\text{NN}}} = 5.02$ TeV
recorded by the ATLAS experiment in 2018. Selected events contain one muon from
a $\tau$-lepton decay, an electron or charged-particle track(s) from the other
$\tau$-lepton decay, little additional central-detector activity, and no
forward neutrons. The $\gamma\gamma \to \tau\tau$ process is observed in Pb+Pb
collisions with a significance exceeding 5 standard deviations, and a signal
strength of $\mu_{\tau\tau} = 1.04^{+0.06}_{-0.05}$ assuming the Standard Model
value for $a_\tau$. To measure $a_\tau$, a template fit to the muon
transverse-momentum distribution from $\tau$-lepton candidates is performed,
using a dimuon ($\gamma\gamma \to \mu\mu$) control sample to constrain
systematic uncertainties. The observed 95% confidence-level intervals for
$a_\tau$ are $a_\tau \in (-0.058, -0.012) \cup (-0.006, 0.025)$.


title:
Unified approach to the electromagnetic field: the role of sources,
  causality and wave propagation

abstract:
  The question of the sources of electric and magnetic fields and their causes
has been discussed extensively in the literature over the last 50 years. In
this article, we approach this problem from the unified treatment of
electromagnetic fields emphasizing the role of their sources in accordance with
the cause-effect relationships. First, we analyze whether this unified
treatment contributes to a better understanding of these phenomena. Then, we
discuss the implications for teaching of a correct understanding of
electromagnetic field sources and causality in Maxwell's equations. In
particular, we present a series of examples at the introductory physics level
that allow us to recognize the reasons why considering electric and magnetic
fields as disjoint entities can lead to contradictions


title:
The Value of Measuring Trust in AI - A Socio-Technical System
  Perspective

abstract:
  Building trust in AI-based systems is deemed critical for their adoption and
appropriate use. Recent research has thus attempted to evaluate how various
attributes of these systems affect user trust. However, limitations regarding
the definition and measurement of trust in AI have hampered progress in the
field, leading to results that are inconsistent or difficult to compare. In
this work, we provide an overview of the main limitations in defining and
measuring trust in AI. We focus on the attempt of giving trust in AI a
numerical value and its utility in informing the design of real-world human-AI
interactions. Taking a socio-technical system perspective on AI, we explore two
distinct approaches to tackle these challenges. We provide actionable
recommendations on how these approaches can be implemented in practice and
inform the design of human-AI interactions. We thereby aim to provide a
starting point for researchers and designers to re-evaluate the current focus
on trust in AI, improving the alignment between what empirical research
paradigms may offer and the expectations of real-world human-AI interactions.


title: Bunching and Taxing Multidimensional Skills

abstract:
  We characterize optimal policies in a multidimensional nonlinear taxation
model with bunching. We develop an empirically relevant model with cognitive
and manual skills, firm heterogeneity, and labor market sorting. The analysis
of optimal policy is based on two main results. We first derive an optimality
condition - a general ABC formula - that states that the entire schedule of
benefits of taxes second order stochastically dominates the entire schedule of
tax distortions. Second, we use Legendre transforms to represent our problem as
a linear program. This linearization allows us to solve the model
quantitatively and to precisely characterize the regions and patterns of
bunching. At an optimum, 9.8 percent of workers is bunched both locally and
nonlocally. We introduce two notions of bunching - blunt bunching and targeted
bunching. Blunt bunching constitutes 30 percent of all bunching, occurs at the
lowest regions of cognitive and manual skills, and lumps the allocations of
these workers resulting in a significant distortion. Targeted bunching
constitutes 70 percent of all bunching and recognizes the workers' comparative
advantage. The planner separates workers on their dominant skill and bunches
them on their weaker skill, thus mitigating distortions along the dominant
skill dimension. Tax wedges are particularly high for low skilled workers who
are bluntly bunched and are also high along the dimension of comparative
disadvantage for somewhat more skilled workers who are targetedly bunched.


title:
Low-energy spin excitations of the frustrated ferromagnetic $J_1$-$J_2$
  chain material linarite, PbCuSO$_4$(OH)$_2$, in applied magnetic fields
  $\mathbf{H} \parallel b$ axis

abstract:
  We report a study of the spin dynamics of the frustrated ferromagnetic
$J_1$-$J_2$ chain compound linarite, PbCuSO$_4$(OH)$_2$, in applied magnetic
fields up to field polarization. By means of an extreme-environment inelastic
neutron scattering experiment, we have measured the low-energy spin excitations
of linarite in fields up to 8.8 T for $\mathbf{H} \parallel b$ axis and
temperatures as low as 500 mK. We have recorded the spin wave excitation
spectra along $h$, $k$ and $l$ for the field-induced magnetic phases IV, V and
the field polarized state close to saturation. By employing first-principles
calculations, we estimate the leading magnetic exchanges out of the $bc$ plane
and model the dispersion relations using linear spin wave theory. In this way,
we find evidence for a (very weak) residual magnetic exchange coupling out of
the $bc$ plane. Together with the previously established dominant in-chain
couplings $J_1$ and $J_2$ and the interchain coupling $J_3$, we derive an
effective set of exchange couplings for a microscopic description of linarite.
Further, we find that the peculiar character of the spin-density wave phase V
manifests itself in the measured spin dynamics. Having gained new insights from
our applied-field spin wave analysis, we discuss our experimental results
regarding the possibility of a spin-multipolar state close to saturation.


title: TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving

abstract:
  The new generation of 4D high-resolution imaging radar provides not only a
huge amount of point cloud but also additional elevation measurement, which has
a great potential of 3D sensing in autonomous driving. In this paper, we
introduce an autonomous driving dataset named TJ4DRadSet, including multi-modal
sensors that are 4D radar, lidar, camera and GNSS, with about 40K frames in
total. 7757 frames within 44 consecutive sequences in various driving scenarios
are well annotated with 3D bounding boxes and track id. We provide a 4D
radar-based 3D object detection baseline for our dataset to demonstrate the
effectiveness of deep learning methods for 4D radar point clouds.


title:
RIS-aided Joint Localization and Synchronization with a Single-Antenna
  Receiver: Beamforming Design and Low-Complexity Estimation

abstract:
  Reconfigurable intelligent surfaces (RISs) have attracted enormous interest
thanks to their ability to overcome line-of-sight blockages in mmWave systems,
enabling in turn accurate localization with minimal infrastructure. Less
investigated are however the benefits of exploiting RIS with suitably designed
beamforming strategies for optimized localization and synchronization
performance. In this paper, a novel low-complexity method for joint
localization and synchronization based on an optimized design of the base
station (BS) active precoding and RIS passive phase profiles is proposed, for
the challenging case of a single-antenna receiver. The theoretical position
error bound is first derived and used as metric to jointly optimize the BS-RIS
beamforming, assuming a priori knowledge of the user position. By exploiting
the low-dimensional structure of the solution, a novel codebook-based robust
design strategy with optimized beam power allocation is then proposed, which
provides low-complexity while taking into account the uncertainty on the user
position. Finally, a reduced-complexity maximum-likelihood based estimation
procedure is devised to jointly recover the user position and the
synchronization offset. Extensive numerical analysis shows that the proposed
joint BS-RIS beamforming scheme provides enhanced localization and
synchronization performance compared to existing solutions, with the proposed
estimator attaining the theoretical bounds even at low signal-to-noise-ratio
and in the presence of additional uncontrollable multipath propagation.


title: Manipulating the outcome of stable matching and roommates problems

abstract:
  The stable marriage and stable roommates problems have been extensively
studied due to their high applicability in various real-world scenarios.
However, it might happen that no stable solution exists, or stable solutions do
not meet certain requirements. In such cases, one might be interested in
modifying the instance so that the existence of a stable outcome with the
desired properties is ensured.
  We focus on three different modifications. In stable roommates problems with
all capacities being one, we give a simpler proof to show that removing an
agent from each odd cycle of a stable partition is optimal. We further show
that the problem becomes NP-complete if the capacities are greater than one, or
the deleted agents must belong to a fixed subset of vertices.
  Motivated by inverse optimization problems, we investigate how to modify the
preferences of the agents as little as possible so that a given matching
becomes stable. The deviation of the new preferences from the original ones can
be measured in various ways; here we concentrate on the $\ell_1$-norm. We show
that, assuming the Unique Games Conjecture, the problem does not admit a better
than $2$ approximation. By relying on bipartite-submodular functions, we give a
polynomial-time algorithm for the bipartite case. We also show that a similar
approach leads to a 2-approximation for general graphs.
  Last, we consider problems where the preferences of agents are not fully
prescribed, and the goal is to decide whether the preference lists can be
extended so that a stable matching exists. We settle the complexity of several
variants, including cases when some of the edges are required to be included or
excluded from the solution.


title:
Two-particle azimuthal correlations in $\gamma$p interactions using pPb
  collisions at $\sqrt{s_\mathrm{NN}}$ = 8.16 TeV

abstract:
  The first measurements of the Fourier coefficients ($V_{n\Delta}$) of the
azimuthal distributions of charged hadrons emitted from photon-proton
($\gamma$p) interactions are presented. The data are extracted from 68.8
nb$^{-1}$ of ultra-peripheral proton-lead (pPb) collisions at
$\sqrt{s_\mathrm{NN}}$ = 8.16 TeV using the CMS detector. The high energy lead
ions produce a flux of photons that can interact with the oncoming proton. This
$\gamma$p system provides a set of unique initial conditions with multiplicity
lower than in photon-lead collisions but comparable to recent electron-positron
and electron-proton data. The $V_{n\Delta}$ coefficients are presented in
ranges of event multiplicity and transverse momentum ($p_\mathrm{T}$) and are
compared to corresponding hadronic minimum bias pPb results. For a given
multiplicity range, the mean $p_\mathrm{T}$ of charged particles is smaller in
$\gamma$p than in pPb collisions. For both the $\gamma$p and pPb samples,
$V_{1\Delta}$ is negative, $V_{2\Delta}$ is positive, and $V_{3\Delta}$
consistent with 0. For each multiplicity and $p_\mathrm{T}$ range,
$V_{2\Delta}$ is larger for $\gamma$p events. The $\gamma$p data are consistent
with model predictions that have no collective effects thus suggesting the
absence of collectivity in the $\gamma$p system over the multiplicity range
explored in this work.


title:
Practical Analysis of Permeable Concrete Properties with Polypropylene
  Fiber Addition

abstract:
  One of the recent approaches used to minimize the impacts of the growth of
impermeable areas in urban centers is permeable flooring. Permeable floors can
be made of concrete and are called permeable concrete. This research aims to
analyze the use of polypropylene fibers in the mixture of permeable concrete to
assess whether the fibers significantly alter the properties of this type of
concrete, such as compression resistance and flexure tensile strength. For the
tests, three concrete mixes of permeable concrete were first used to determine
the reference of the composition of concrete: 1:3, without the use of sand and
with water-to-cement ratio (w/c) equal to 0.32; 1:4, with the use of 10\% of
coarse sand and w/c of 0.35; and finally 1:5, with the use of 10\% of coarse
sand and w/c of 0.35; and finally 1:5, using 10\% of coarse sand and w/c of
0.35. In these concrete mixes, tests were performed to determine their
mechanical properties being them: permeability, compression resistance, and
flexure tensile strength. After the reference concrete mix was determined,
three more concrete mixes were made using polypropylene fibers, at levels of
0.6 kg/m$^3$, 1.8 kg/m$^3$, and 3.0 kg/m$^3$. The same initial tests were then
carried out for concrete with the addition of fibers. The analysis of the
results showed that the concrete mix that achieved the best result for the
flexure tensile strength test, which was the main focus of the research, was
the 1:4 trait with the addition of 1.8 kg/m$^3$.


title: Penalized Sieve Estimation of Structural Models

abstract:
  Estimating structural models is an essential tool for economists. However,
existing methods are often inefficient either computationally or statistically,
depending on how equilibrium conditions are imposed. We propose a class of
penalized sieve estimators that are consistent, asymptotic normal, and
asymptotically efficient. Instead of solving the model repeatedly, we
approximate the solution with a linear combination of basis functions and
impose equilibrium conditions as a penalty in searching for the best fitting
coefficients. We apply our method to an entry game between Walmart and Kmart.


title: Formation of periodic FRB in binary systems with eccentricity

abstract:
  Long-term periodicity in the rate of flares is observed for two repeating
sources of fast radio bursts (FRBs). In this paper We present a hydrodynamical
modeling of a massive binary consisting of a magnetar and an early-type star.
We model the interaction of the pulsar wind from the magnetar with an intense
stellar wind. It is shown that only during a fraction of the orbital period
radio emission can escape the system. This explains the duty cycle of the two
repeating FRB sources with periodic activity. The width of the transparency
window depends on the eccentricity, stellar wind properties, and the viewing
angle. To describe properties of the known sources it is necessary to assume
large eccentricities $\gtrsim 0.5$. We apply the maser cyclotron mechanism of
the radio emission generation to model spectral properties of the sources. The
produced spectrum is not wide: $\Delta \nu/\nu \sim 0.3$ and the typical
frequency depends on the radius of the shock where the emission is generated.
The shock radius changes along the orbit. This, together with changing
parameters of the medium, allows us to explain the frequency drift during the
phase of visibility. Frequency dependence of the degree of polarization at few
GHz can be a consequence of a small scale turbulence in the shocked stellar
wind. It is much more difficult to explain huge ($\sim 10^5$ [rad/m$^2$]) and
variable value of the rotation measure observed for FRB 121102. We suggest that
this can be explained if the supernova explosion which produced the magnetar
happened near a dense interstellar cloud with $n \sim100$ cm$^{-3}$.


title: Theory for polaritonic quantum tunneling

abstract:
  I investigate the tunneling decay rate of a polaritonic system formed by a
strong coupling between a vacuum cavity mode and $N$ metastable systems. Using
a simple model potential, I find the instanton solutions controlling the
low-temperature tunneling rate. The resulting rate modification due to the
cavity is proportional to the mean of the second power of the light-matter
coupling. No collective effect that would enhance the rates by a factor of
$\sqrt{N}$ is present, which is in line with the results in the thermal
activation regime.


title:
First concurrent extraction of the leading-order scalar and spin proton
  polarizabilities

abstract:
  We performed the first simultaneous extraction of the six leading-order
proton polarizabilities. We reached this milestone thanks to both new
high-quality experimental data and an innovative bootstrap-base fitting method.
These new results provide a self-consistent and fundamental benchmark for all
future theoretical and experimental polarizability estimates.


title: Streaming Multiscale Deep Equilibrium Models

abstract:
  We present StreamDEQ, a method that infers frame-wise representations on
videos with minimal per-frame computation. In contrast to conventional methods
where compute time grows at least linearly with the network depth, we aim to
update the representations in a continuous manner. For this purpose, we
leverage the recently emerging implicit layer model which infers the
representation of an image by solving a fixed-point problem. Our main insight
is to leverage the slowly changing nature of videos and use the previous frame
representation as an initial condition on each frame. This scheme effectively
recycles the recent inference computations and greatly reduces the needed
processing time. Through extensive experimental analysis, we show that
StreamDEQ is able to recover near-optimal representations in a few frames time,
and maintain an up-to-date representation throughout the video duration. Our
experiments on video semantic segmentation and video object detection show that
StreamDEQ achieves on par accuracy with the baseline (standard MDEQ) while
being more than $3\times$ faster. The project page is available at:
https://ufukertenli.github.io/streamdeq/


title: A Probabilistic Chemical Programmable Computer

abstract:
  The exponential growth of the power of modern digital computers is based upon
the miniaturisation of vast nanoscale arrays of electronic switches, but this
will be eventually constrained by fabrication limits and power dissipation.
Chemical processes have the potential to scale beyond these limits performing
computations through chemical reactions, yet the lack of well-defined
programmability limits their scalability and performance. We present a hybrid
digitally programmable chemical array as a probabilistic computational machine
that uses chemical oscillators partitioned in interconnected cells as a
computational substrate. This hybrid architecture performs efficient
computation by distributing between chemical and digital domains together with
error correction. The efficiency is gained by combining digital with
probabilistic chemical logic based on nearest neighbour interactions and
hysteresis effects. We demonstrated the implementation of one- and two-
dimensional Chemical Cellular Automata and solutions to combinatorial
optimization problems.


title:
A Spiral into the Mind: Gaze Spiral Visualization for Mobile Eye
  Tracking

abstract:
  Comparing mobile eye tracking data from multiple participants without
information about areas of interest (AOIs) is challenging because of individual
timing and coordinate systems. We present a technique, the gaze spiral, that
visualizes individual recordings based on image content of the stimulus. The
spiral layout of the slitscan visualization is used to create a compact
representation of scanpaths. The visualization provides an overview of multiple
recordings even for long time spans and helps identify and annotate recurring
patterns within recordings. The gaze spirals can also serve as glyphs that can
be projected to 2D space based on established scanpath metrics in order to
interpret the metrics and identify groups of similar viewing behavior. We
present examples based on two egocentric datasets to demonstrate the
effectiveness of our approach for annotation and comparison tasks. Our examples
show that the technique has the potential to let users compare even long-term
recordings of pervasive scenarios without manual annotation.


title:
Binary black holes population and cosmology in new lights: Signature of
  PISN mass and formation channel in GWTC-3

abstract:
  The mass, spin, and merger rate distribution of the binary black holes (BBHs)
across cosmic redshifts provide a unique way to shed light on their formation
channel. Along with the redshift dependence of the BBH merger rate, the mass
distribution of BBHs can also exhibit redshift dependence due to different
formation channels and due to its dependence on the metallicity of the parent
stars. In this work, we explore the redshift dependence of the BBH mass
distribution jointly with the merger rate evolution from the third
gravitational wave (GW) catalog GWTC-3 of the LIGO-Virgo-KAGRA collaboration.
This analysis sheds light on multiple new aspects of the BBH formation channel
and mass distribution. We obtain interesting constraints on the minimum delay
time between the formation of stars and mergers of BBHs $t^{\rm min}_d =
1.95^{+0.97}_{-0.93}$ Gyrs, along with a hint towards a steeper power-law form
of the delay time distribution ($(t_d)^{d}$) with an index $d < -1.55$ at
68$\%$ C.L. The mass distribution of the BBHs agrees with a power-law form with
a Gaussian peak at $\mu_g=40.26^{+1.04}_{-2.32} $ $\rm M_\odot$ which agrees
with the theoretical prediction of the lower edge of the PISN mass scale and
differs from the previous analysis. This analysis sheds light on the lower edge
of the PISN mass scale of black holes and provides hints toward the formation
channel of the BBH systems that are different from the usual fiducial scenario
with a power-law index $d=-1$. Our results are consistent with the scenarios of
varying (or fixed) Hubble constant and also for events with lower matched
filtering network signal to noise ratio.


title:
EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based
  Enrolment, Verification, and Identification

abstract:
  Knowledge-based authentication is crucial for task-oriented spoken dialogue
systems that offer personalised and privacy-focused services. Such systems
should be able to enrol (E), verify (V), and identify (I) new and recurring
users based on their personal information, e.g. postcode, name, and date of
birth. In this work, we formalise the three authentication tasks and their
evaluation protocols, and we present EVI, a challenging spoken multilingual
dataset with 5,506 dialogues in English, Polish, and French. Our proposed
models set the first competitive benchmarks, explore the challenges of
multilingual natural language processing of spoken dialogue, and set directions
for future research.


title:
Unsupervised Spatial-spectral Hyperspectral Image Reconstruction and
  Clustering with Diffusion Geometry

abstract:
  Hyperspectral images, which store a hundred or more spectral bands of
reflectance, have become an important data source in natural and social
sciences. Hyperspectral images are often generated in large quantities at a
relatively coarse spatial resolution. As such, unsupervised machine learning
algorithms incorporating known structure in hyperspectral imagery are needed to
analyze these images automatically. This work introduces the Spatial-Spectral
Image Reconstruction and Clustering with Diffusion Geometry (DSIRC) algorithm
for partitioning highly mixed hyperspectral images. DSIRC reduces measurement
noise through a shape-adaptive reconstruction procedure. In particular, for
each pixel, DSIRC locates spectrally correlated pixels within a data-adaptive
spatial neighborhood and reconstructs that pixel's spectral signature using
those of its neighbors. DSIRC then locates high-density, high-purity pixels far
in diffusion distance (a data-dependent distance metric) from other
high-density, high-purity pixels and treats these as cluster exemplars, giving
each a unique label. Non-modal pixels are assigned the label of their diffusion
distance-nearest neighbor of higher density and purity that is already labeled.
Strong numerical results indicate that incorporating spatial information
through image reconstruction substantially improves the performance of
pixel-wise clustering.


title: Post-Training Dialogue Summarization using Pseudo-Paraphrasing

abstract:
  Previous dialogue summarization techniques adapt large language models
pretrained on the narrative text by injecting dialogue-specific features into
the models. These features either require additional knowledge to recognize or
make the resulting models harder to tune. To bridge the format gap between
dialogues and narrative summaries in dialogue summarization tasks, we propose
to post-train pretrained language models (PLMs) to rephrase from dialogue to
narratives. After that, the model is fine-tuned for dialogue summarization as
usual. Comprehensive experiments show that our approach significantly improves
vanilla PLMs on dialogue summarization and outperforms other SOTA models by the
summary quality and implementation costs.


title:
FieldFuzz: Enabling vulnerability discovery in Industrial Control
  Systems supply chain using stateful system-level fuzzing

abstract:
  With the advent of the fourth industrial revolution, Programmable Logic
Controllers (PLCs) used as field devices, have been growing in their
sophistication, offering extensive smart features, such as remote connectivity,
support for standardized cryptography, and visualization. Such computational
platforms incorporate components from various sources (vendor, platform
provider, open-source), bringing along their associated vulnerabilities. This,
combined with the increase in reliance on the Industrial Internet of Things
(IIoT) devices for automation and feedback, has opened previously airtight
networks to remote attacks. Furthermore, modern PLCs often employ commodity
software such as Linux on ARM, further expanding the threat surface towards
traditional vulnerabilities. Security analysis of Operational Technology (OT)
software, specifically, the control runtime and IEC applications, remains
relatively unexplored due to its proprietary nature. In this work, we implement
FieldFuzz, a methodology for discovering supply chain vulnerabilities in every
PLC component using stateful black-box fuzzing without the requirement of a
real device. FieldFuzz has been built using the Codesys v3 protocol, making it
applicable to at least 80 industrial device vendors ranging from over 400
devices. Fuzzing campaigns uncovered multiple vulnerabilities, leading to three
reported CVE IDs. To study the cross-platform applicability of FieldFuzz, we
reproduce the findings on a diverse set of Industrial Control System (ICS)
devices, showing a significant improvement over the state-of-the-art.


title:
One-loop squared amplitudes for hadronic $tW$ production at
  next-to-next-to-leading order in QCD

abstract:
  We present the analytic results of one-loop squared amplitudes for $tW$
production at a hadron collider. The calculation is performed using the method
of differential equations. After renormalization, we have checked that the
infrared divergences agree with the general structure predicted by anomalous
dimensions. The finite remainder contributes to the next-to-next-to-leading
order hard function, one of the essential gradients in the factorization
formula of the cross section near the infrared region, which can be used in
resummation of all-order soft gluon effects or a differential
next-to-next-to-leading order calculation based on the phase space slicing
method.


title: The tropical and zonotopal geometry of periodic timetables

abstract:
  The Periodic Event Scheduling Problem (PESP) is the standard mathematical
tool for optimizing periodic timetabling problems in public transport. A
solution to PESP consists of three parts: a periodic timetable, a periodic
tension, and integer periodic offset values. While the space of periodic
tension has received much attention in the past, we explore geometric
properties of the other two components, establishing novel connections between
periodic timetabling and discrete geometry. Firstly, we study the space of
feasible periodic timetables, and decompose it into polytropes, i.e., polytopes
that are convex both classically and in the sense of tropical geometry. We then
study this decomposition and use it to outline a new heuristic for PESP, based
on the tropical neighbourhood of the polytropes. Secondly, we recognize that
the space of fractional cycle offsets is in fact a zonotope. We relate its
zonotopal tilings back to the hyperrectangle of fractional periodic tensions
and to the tropical neighbourhood of the periodic timetable space. To conclude
we also use this new understanding to give tight lower bounds on the minimum
width of an integral cycle basis.


title:
Multi-Player Multi-Armed Bandits with Finite Shareable Resources Arms:
  Learning Algorithms & Applications

abstract:
  Multi-player multi-armed bandits (MMAB) study how decentralized players
cooperatively play the same multi-armed bandit so as to maximize their total
cumulative rewards. Existing MMAB models mostly assume when more than one
player pulls the same arm, they either have a collision and obtain zero
rewards, or have no collision and gain independent rewards, both of which are
usually too restrictive in practical scenarios. In this paper, we propose an
MMAB with shareable resources as an extension to the collision and
non-collision settings. Each shareable arm has finite shareable resources and a
"per-load" reward random variable, both of which are unknown to players. The
reward from a shareable arm is equal to the "per-load" reward multiplied by the
minimum between the number of players pulling the arm and the arm's maximal
shareable resources. We consider two types of feedback: sharing demand
information (SDI) and sharing demand awareness (SDA), each of which provides
different signals of resource sharing. We design the DPE-SDI and SIC-SDA
algorithms to address the shareable arm problem under these two cases of
feedback respectively and prove that both algorithms have logarithmic regrets
that are tight in the number of rounds. We conduct simulations to validate both
algorithms' performance and show their utilities in wireless networking and
edge computing.


title: Cohomology of the extended Schr\"odinger-Virasoro conformal algebra

abstract:
  All the basic cohomology groups and reduced cohomology groups of the extended
Schr\"odinger-Virasoro conformal algebra with trivial coefficients are
completely determined. In particular, we introduce the notion of the relative
cohomology of Lie conformal algebra, and then we can express our main results
in a more concise manner.


title: Algebraicity modulo p of generalized hypergeometric series $_nF_{n-1}$

abstract:
  Let $f(z)$ be the hypergeometric series with parameters
$\mathbf{\alpha}=(\alpha_1,\ldots,\alpha_n)$ and
$\mathbf{\beta}=(\beta_1,\ldots,\beta_{n-1},1)$ in $(\mathbb{Q}\cap(0,1])^n$,
let $d_{\mathbf{\alpha},\mathbf{\beta}}$ be the least common multiple of the
denominators of $\alpha_1,\ldots,\alpha_n$, $\beta_1,\ldots,\beta_{n-1}$
written in lowest form and let $\mathcal{S}$ be an infinite set of prime
numbers $p$ such that $p$ does not divide $d_{\mathbf{\alpha},\mathbf{\beta}}$
and $f(z)\in\mathbb{Z}_{(p)}[[z]]$. We say that $f(z)$ is algebraic modulo $p$,
if the reduction of $f$ modulo $p$ is an algebraic power series over
$\mathbb{F}_p(z)$. Recently in \cite{vmsff}, it was shown that if for all
$i,j\in\{1,\ldots,n\}$, $\alpha_i-\beta_j\notin\mathbb{Z}$ then, for every
$p\in\mathcal{S}$, $f(z)$ is algebraic modulo $p$. A standard way to measure
the complexity of an algebraic power series is to estimate its degree and its
height. In this work, under the same assumptions, we prove that, for almost
every prime number $p\in\mathcal{S}$, there is a nonzero polynomial
$P_p(Y)\in\mathbb{F}_p(z)[Y]$ having degree at most
$p^{2n\varphi(d_{\mathbf{\alpha}\mathbf{\beta}})}$ and height at most
$5^n(n+1)!p^{2(n+1)\varphi({d_{\mathbf{\alpha},\mathbf{\beta}})}}$ such that
$P_p(f(z)\bmod p)=0$, where $\varphi$ is the Euler's totient function.
Furthermore, our method of proof provides us a way to make an explicit
construction of the polynomial $P_p(Y)$. We illustrate this construction by
applying it to some explicit hypergeometric series.


title:
Sensing RISs: Enabling Dimension-Independent CSI Acquisition for
  Beamforming

abstract:
  Reconfigurable intelligent surfaces (RISs) are envisioned as a potentially
transformative technology for future wireless communications. However, RIS's
inability to process signals and their attendant increased channel dimension
have brought new challenges to RIS-assisted systems, which greatly increases
the pilot overhead required for channel estimation. To address these problems,
several prior contributions that enhance the hardware architecture of RISs or
develop algorithms to exploit the channels' mathematical properties have been
made, where the required pilot overhead is reduced to be proportional to the
number of RIS elements. In this paper, we propose a dimension-independent
channel state information (CSI) acquisition approach in which the required
pilot overhead is independent of the number of RIS elements. Specifically, in
contrast to traditional signal transmission methods, where signals from the
base station (BS) and the users are transmitted in different time slots, we
propose a novel method in which signals are transmitted from the BS and the
user simultaneously during CSI acquisition. Under this method, an
electromagnetic interference random field (IRF) will be induced on the RIS, and
we employ a sensing RIS to capture its features. Moreover, we develop three
algorithms for parameter estimation in this system, and also derive the
Cramer-Rao lower bound (CRLB) and an asymptotic expression for it. Simulation
results verify that our proposed signal transmission method and the
corresponding algorithms can achieve dimension-independent CSI acquisition for
beamforming.


title:
A Hamiltonian Dysthe equation for deep-water gravity waves with constant
  vorticity

abstract:
  This paper is a study of the water wave problem in a two-dimensional domain
of infinite depth in the presence of nonzero constant vorticity. A goal is to
describe the effects of uniform shear flow on the modulation of weakly
nonlinear quasi-monochromatic surface gravity waves. Starting from the
Hamiltonian formulation of this problem and using techniques from Hamiltonian
transformation theory, we derive a Hamiltonian Dysthe equation for the time
evolution of the wave envelope. Consistent with previous studies, we observe
that the uniform shear flow tends to enhance or weaken the modulational
instability of Stokes waves depending on its direction and strength. Our method
also provides a non-perturbative procedure to reconstruct the surface elevation
from the wave envelope, based on the Birkhoff normal form transformation to
eliminate all non-resonant triads. This model is tested against direct
numerical simulations of the full Euler equations and against a related Dysthe
equation recently derived by Curtis, Carter and Kalisch (J. Fluid Mech. 855,
2018) in the context of constant vorticity. Very good agreement is found for a
range of values of the vorticity.


title:
Optics of sunscreen lotions: Preliminary results on scattering and
  absorption coefficients

abstract:
  Sunscreen lotions are used to protect the skin from damage due to solar
ultraviolet (UV) radiation. The active UV blocking components can be organic
molecules or inorganic particles, for example TiO2. While both in vivo and in
vitro methods exist for assessing the protective capacity of sunscreens, their
basic optical properties have received little attention. In this paper we take
the first steps to address this issue by presenting a method to obtain spectra
of absorption and scattering coefficients of a sunscreen by analysis of
experimental transmittance and reflectance spectra. We model the optical
properties of the sunscreen by two flux theory, develop approximate expressions
for interface reflection coefficients and obtain the remaining optical
parameters by fitting the two-flux theory to measurements. We analyze
spectrophotometric reflectance and transmittance spectra of experimental narrow
band UV blocking materials based on mixtures of mesoporous magnesium carbonate
and TiO2, as well as some commercial sunscreens. Our method is demonstrated in
vitro using quartz substrates and is further used to model in vivo measurements
on the upside of the hand of one of the authors. The obtained absorption and
scattering coefficient spectra give information on the relative contributions
of these processes to the UV blocking effect as well as the scattering of
visible light responsible for the whitening of the skin upon application of a
sunscreen lotion. Our analysis method may be useful for computational
optimization of novel sunscreen formulations as well as for the development of
in vivo test methods.


title: Design of Blockchain-based Travel Rule Compliance System

abstract:
  In accordance with the guidelines of the Financial Action Task Force (FATF),
Virtual Asset Service Providers (VASPs) should comply with a `travel rule',
which requires them to exchange originator's and beneficiary's personal
information when transferring virtual assets. In this paper, we propose a novel
blockchain-based travel rule compliance system that supports
fully-decentralized data exchange. The proposed system uses a permissioned
blockchain, and thereby eliminates the possibility of leakage of personal
information to third parties or even to travel rule service providers, and
ensures that travel rule data can be managed securely.


title:
On the Effect of Pretraining Corpora on In-context Learning by a
  Large-scale Language Model

abstract:
  Many recent studies on large-scale language models have reported successful
in-context zero- and few-shot learning ability. However, the in-depth analysis
of when in-context learning occurs is still lacking. For example, it is unknown
how in-context learning performance changes as the training corpus varies.
Here, we investigate the effects of the source and size of the pretraining
corpus on in-context learning in HyperCLOVA, a Korean-centric GPT-3 model. From
our in-depth investigation, we introduce the following observations: (1)
in-context learning performance heavily depends on the corpus domain source,
and the size of the pretraining corpus does not necessarily determine the
emergence of in-context learning, (2) in-context learning ability can emerge
when a language model is trained on a combination of multiple corpora, even
when each corpus does not result in in-context learning on its own, (3)
pretraining with a corpus related to a downstream task does not always
guarantee the competitive in-context learning performance of the downstream
task, especially in the few-shot setting, and (4) the relationship between
language modeling (measured in perplexity) and in-context learning does not
always correlate: e.g., low perplexity does not always imply high in-context
few-shot learning performance.


title: The near-field shape and stability of a porous plume

abstract:
  When a fluid is injected into a porous medium saturated with an ambient fluid
of a greater density, the injected fluid forms a plume that rises upwards due
to buoyancy. In the near-field of the injection point the plume adjusts its
speed to match the buoyancy velocity of the porous medium, either thinning or
thickening to conserve mass. These adjustments are the dominant controls on the
near-field plume shape, rather than mixing with the ambient fluid, which occurs
over larger vertical distances. In this study, we focus on the plume behaviour
in the near-field, demonstrating that for moderate injection rates the plume
will reach a steady state, whereby it matches the buoyancy velocity over a few
plume width-scales from the injection point. However, for very small injection
rates an instability occurs in which the steady plume breaks apart due to the
insurmountable density contrast with the surrounding fluid. The steady shape of
the plume in the near-field only depends on a single dimensionless parameter,
which is the ratio between the inlet velocity and the buoyancy velocity. A
linear stability analysis is performed, indicating that for small velocity
ratios an infinitesimal perturbation can be constructed that becomes unstable,
whilst for moderate velocity ratios the shape is shown to be stable. Finally,
we comment on the application of such flows to the context of CO$_2$
sequestration in porous geological reservoirs.


title: RobBERTje: a Distilled Dutch BERT Model

abstract:
  Pre-trained large-scale language models such as BERT have gained a lot of
attention thanks to their outstanding performance on a wide range of natural
language tasks. However, due to their large number of parameters, they are
resource-intensive both to deploy and to fine-tune. Researchers have created
several methods for distilling language models into smaller ones to increase
efficiency, with a small performance trade-off. In this paper, we create
several different distilled versions of the state-of-the-art Dutch RobBERT
model and call them RobBERTje. The distillations differ in their distillation
corpus, namely whether or not they are shuffled and whether they are merged
with subsequent sentences. We found that the performance of the models using
the shuffled versus non-shuffled datasets is similar for most tasks and that
randomly merging subsequent sentences in a corpus creates models that train
faster and perform better on tasks with long sequences. Upon comparing
distillation architectures, we found that the larger DistilBERT architecture
worked significantly better than the Bort hyperparametrization. Interestingly,
we also found that the distilled models exhibit less gender-stereotypical bias
than its teacher model. Since smaller architectures decrease the time to
fine-tune, these models allow for more efficient training and more lightweight
deployment of many Dutch downstream language tasks.


title: Neural Label Search for Zero-Shot Multi-Lingual Extractive Summarization

abstract:
  In zero-shot multilingual extractive text summarization, a model is typically
trained on English summarization dataset and then applied on summarization
datasets of other languages. Given English gold summaries and documents,
sentence-level labels for extractive summarization are usually generated using
heuristics. However, these monolingual labels created on English datasets may
not be optimal on datasets of other languages, for that there is the syntactic
or semantic discrepancy between different languages. In this way, it is
possible to translate the English dataset to other languages and obtain
different sets of labels again using heuristics. To fully leverage the
information of these different sets of labels, we propose NLSSum (Neural Label
Search for Summarization), which jointly learns hierarchical weights for these
different sets of labels together with our summarization model. We conduct
multilingual zero-shot summarization experiments on MLSUM and WikiLingua
datasets, and we achieve state-of-the-art results using both human and
automatic evaluations across these two datasets.


title:
(Non)universality of Unruh-Fulling effect in nonlocal field theory - the
  role of Unruh decomposition

abstract:
  We investigate the Unruh-Fulling (UF) effect in a class of nonlocal field
theories by calculating the expectation value of the Rindler number operator in
Minkowski vacuum and the response function of the Unruh-DeWitt detector (UD).
Contrary to the existing approaches, here, the field is quantised in terms of
the Unruh creation and annihilation operators along with the Rindler mode
solutions. Such choice, as oppose to standard Minkowski decomposition,
naturally incorporates the time translational invariance in the positive
frequency Wightman function and hence inherently captures the thermal
equilibrium in the system. In this manuscript we analyse the fate of the UF
effect for a massless real scalar field in the context of both the Lorentz
noninvariant nonlocal theory (LNI-NLT) and Lorentz invariant nonlocal theory
(LI-NLT). In case of LNI-NLT, we find that both the expectation value of number
operator and the response function of the UD detector are modified by an
overall multiplicative factor. Whereas in the background of LI-NLT the
aforementioned quantities remain identical to those of the local field theory.
We also derive the temperature of the thermal bath as detected by the Rindler
observer by implementing the formulation of equilibrium thermodynamics. Our
results suggest that the Unruh bath temperature remains unaltered for both the
LNI-NLT and LI-NLT.


title:
Death By A Thousand COTS: Disrupting Satellite Communications using Low
  Earth Orbit Constellations

abstract:
  Satellites in Geostationary Orbit (GEO) provide a number of commercial,
government, and military services around the world, offering everything from
surveillance and monitoring to video calls and internet access. However a
dramatic lowering of the cost-per-kilogram to space has led to a recent
explosion in real and planned constellations in Low Earth Orbit (LEO) of
smaller satellites. These constellations are managed remotely and it is
important to consider a scenario in which an attacker gains control over the
constituent satellites. In this paper we aim to understand what damage this
attacker could cause, using the satellites to generate interference. To ground
our analysis, we simulate a number of existing and planned LEO constellations
against an example GEO constellation, and evaluate the relative effectiveness
of each. Our model shows that with conservative power estimates, both current
and planned constellations could disrupt GEO satellite services at every
groundstation considered, with effectiveness varying considerably between
locations. We analyse different patterns of interference, how they reflect the
structures of the constellations creating them, and how effective they might be
against a number of legitimate services. We found that real-time usage (e.g.
calls, streaming) would be most affected, with 3 constellation designs able to
generate thousands of outages of 30 seconds or longer over the course of the
day across all groundstations.


title:
UM6P-CS at SemEval-2022 Task 11: Enhancing Multilingual and Code-Mixed
  Complex Named Entity Recognition via Pseudo Labels using Multilingual
  Transformer

abstract:
  Building real-world complex Named Entity Recognition (NER) systems is a
challenging task. This is due to the complexity and ambiguity of named entities
that appear in various contexts such as short input sentences, emerging
entities, and complex entities. Besides, real-world queries are mostly
malformed, as they can be code-mixed or multilingual, among other scenarios. In
this paper, we introduce our submitted system to the Multilingual Complex Named
Entity Recognition (MultiCoNER) shared task. We approach the complex NER for
multilingual and code-mixed queries, by relying on the contextualized
representation provided by the multilingual Transformer XLM-RoBERTa. In
addition to the CRF-based token classification layer, we incorporate a span
classification loss to recognize named entities spans. Furthermore, we use a
self-training mechanism to generate weakly-annotated data from a large
unlabeled dataset. Our proposed system is ranked 6th and 8th in the
multilingual and code-mixed MultiCoNER's tracks respectively.


title:
What do You Mean by Relation Extraction? A Survey on Datasets and Study
  on Scientific Relation Classification

abstract:
  Over the last five years, research on Relation Extraction (RE) witnessed
extensive progress with many new dataset releases. At the same time, setup
clarity has decreased, contributing to increased difficulty of reliable
empirical evaluation (Taill\'e et al., 2020). In this paper, we provide a
comprehensive survey of RE datasets, and revisit the task definition and its
adoption by the community. We find that cross-dataset and cross-domain setups
are particularly lacking. We present an empirical study on scientific Relation
Classification across two datasets. Despite large data overlap, our analysis
reveals substantial discrepancies in annotation. Annotation discrepancies
strongly impact Relation Classification performance, explaining large drops in
cross-dataset evaluations. Variation within further sub-domains exists but
impacts Relation Classification only to limited degrees. Overall, our study
calls for more rigour in reporting setups in RE and evaluation across multiple
test sets.


title:
Unconventional bosonization of chiral quantum wires coupled through a
  point-contact

abstract:
  Non-chiral bosonization technique (NCBT) adapted to study chiral quantum
wires coupled through a point-contact with a constant bias between the wires is
introduced and is shown to reproduce the exact Green functions of this system
which was previously derived [Nikhil Danny Babu and Girish S Setlur 2022 J.
Phys.: Condens. Matter 34 125602] analytically using standard methods. The
tunneling I-V characteristics are obtained using the bosonized Green functions.


title: Cohomology theory of Rota-Baxter pre-Lie algebras of arbitrary weights

abstract:
  This paper is devoted to studying deformation, cohomology theory of
Rota-Baxter pre-Lie algebras of arbitrary weights. First we give the notion of
a new representation of a Rota-Baxter pre-Lie algebra of arbitrary weight and
define the cohomology theory of a Rota-Baxter pre-Lie algebra of arbitrary
weight. Then we study formal deformations by lower degree cohomology groups.
Finally, we classify abelian extensions of Rota-Baxter pre-Lie algebras of
arbitrary weight using the second cohomology group, and classify skeletal
Rota-Baxter pre-Lie 2-algebra of arbitrary weight using the third cohomology
group as applications.


title: On tuning a mean-field model for semi-supervised classification

abstract:
  Semi-supervised learning (SSL) has become an interesting research area due to
its capacity for learning in scenarios where both labeled and unlabeled data
are available. In this work, we focus on the task of transduction - when the
objective is to label all data presented to the learner - with a mean-field
approximation to the Potts model. Aiming at this particular task we study how
classification results depend on $\beta$ and find that the optimal phase
depends highly on the amount of labeled data available. In the same study, we
also observe that more stable classifications regarding small fluctuations in
$\beta$ are related to configurations of high probability and propose a tuning
approach based on such observation. This method relies on a novel parameter
$\gamma$ and we then evaluate two different values of the said quantity in
comparison with classical methods in the field. This evaluation is conducted by
changing the amount of labeled data available and the number of nearest
neighbors in the similarity graph. Empirical results show that the tuning
method is effective and allows NMF to outperform other approaches in datasets
with fewer classes. In addition, one of the chosen values for $\gamma$ also
leads to results that are more resilient to changes in the number of neighbors,
which might be of interest to practitioners in the field of SSL.


title:
Inverse-Designed Meta-Optics with Spectral-Spatial Engineered Response
  to Mimic Color Perception

abstract:
  Meta-optics have rapidly become a major research field within the optics and
photonics community, strongly driven by the seemingly limitless opportunities
made possible by controlling optical wavefronts through interaction with arrays
of sub-wavelength scatterers. As more and more modalities are explored, the
design strategies to achieve desired functionalities become increasingly
demanding, necessitating more advanced design techniques. Herein, the
inverse-design approach is utilized to create a set of single-layer meta-optics
that simultaneously focus light and shape the spectra of focused light without
using any filters. Thus, both spatial and spectral properties of the
meta-optics are optimized, resulting in spectra that mimic the color matching
functions of the CIE 1931 XYZ color space, which links the distributions of
wavelengths in light and the color perception of a human eye. Experimental
demonstrations of these meta-optics show qualitative agreement with the
theoretical predictions and help elucidate the focusing mechanism of these
devices.


title:
Single G centers in silicon fabricated by co-implantation with carbon
  and proton

abstract:
  We report the fabrication of G centers in silicon with an areal density
compatible with single photon emission at optical telecommunication
wavelengths. Our sample is made from a silicon-on-insulator wafer which is
locally implanted with carbon ions and protons at various fluences. Decreasing
the implantation fluences enables to gradually switch from large ensembles to
isolated single defects, reaching areal densities of G centers down to
$\sim$0.2 $\mu$m$^{-2}$. Single defect creation is demonstrated by photon
antibunching in intensity-correlation experiments, thus establishing our
approach as a reproducible procedure for generating single artificial atoms in
silicon for quantum technologies.


title:
Chapter: Energy conversion at water-solid interfaces using
  electrokinetic effects

abstract:
  Our Society is in high need of alternatives to fossil fuels. Nanoporous
systems filled with aqueous electrolytes show great promises for harvesting the
osmotic energy of sea water or waste heat. At the core of energy conversion in
such nanofluidic systems lie the so-called electrokinetic effects, coupling
thermodynamic gradients and fluxes of different types (hydrodynamical,
electrical, chemical, thermal) at electrified water-solid interfaces. This
chapter starts by introducing the framework of linear irreversible
thermodynamics, and how the latter can be used to describe the direct and
coupled responses of a fluidic system, providing general relations between the
different response coefficients. The chapter then focuses on the so-called
osmotic flows, generated by non-hydrodynamic actuation at liquid-solid
interfaces, and illustrate how the induced fluxes can be related to the
microscopic properties of the water-solid interface. Finally, the chapter moves
to electricity production from non-electric actuation, and discusses in
particular the performance of nanofluidic systems for the harvesting of osmotic
energy and waste heat.


title:
Jacobi-Maupertuis principle, mechanical Hamiltonian systems with respect
  to linear Poisson structures and Jacobi-Reeb dynamics

abstract:
  In this paper we extend the Jacobi-Maupertuis principle for mechanical
Hamiltonian systems with respect to linear Poisson structures on vector bundles
and we discuss the relation with Jacobi-Reeb dynamics. The theory is applied to
several examples.


title:
Numerical analysis of quantum circuits for state preparation and unitary
  operator synthesis

abstract:
  We perform optimal-control-theory calculations to determine the minimum
number of two-qubit CNOT gates needed to perform quantum state preparation and
unitary operator synthesis for few-qubit systems. By considering all possible
gate configurations, we determine the maximum achievable fidelity as a function
of quantum circuit size. This information allows us to identify the minimum
circuit size needed for a specific target operation and enumerate the different
gate configurations that allow a perfect implementation of the operation. We
find that there are a large number of configurations that all produce the
desired result, even at the minimum number of gates. We also show that the
number of entangling gates can reduced if we use multi-qubit entangling gates
instead of two-qubit CNOT gates, as one might expect based on parameter
counting calculations. As a special case, we apply the numerical approach to
investigate the decomposition of the multi-qubit Toffoli gate. Our calculations
provide the minimum circuit sizes needed for a number of few-qubit tasks and
provide insight into the tightness of different bounds in the literature.