title: Map-based Visual-Inertial Localization: Consistency and Complexity

abstract:
  Drift-free localization is essential for autonomous vehicles. In this paper,
we address the problem by proposing a filter-based framework, which integrates
the visual-inertial odometry and the measurements of the features in the
pre-built map. In this framework, the transformation between the odometry frame
and the map frame is augmented into the state and estimated on the fly.
Besides, we maintain only the keyframe poses in the map and employ Schmidt
extended Kalman filter to update the state partially, so that the uncertainty
of the map information can be consistently considered with low computational
cost. Moreover, we theoretically demonstrate that the ever-changing
linearization points of the estimated state can introduce spurious information
to the augmented system and make the original four-dimensional unobservable
subspace vanish, leading to inconsistent estimation in practice. To relieve
this problem, we employ first-estimate Jacobian (FEJ) to maintain the correct
observability properties of the augmented system. Furthermore, we introduce an
observability-constrained updating method to compensate for the significant
accumulated error after the long-term absence (can be 3 minutes and 1 km) of
map-based measurements. Through simulations, the consistent estimation of our
proposed algorithm is validated. Through real-world experiments, we demonstrate
that our proposed algorithm runs successfully on four kinds of datasets with
the lower computational cost (20% time-saving) and the better estimation
accuracy (45% trajectory error reduction) compared with the baseline algorithm
VINS-Fusion, whereas VINS-Fusion fails to give bounded localization performance
on three of four datasets because of its inconsistent estimation.


title:
From the delay time in Quantum Mechanics to the Goos-H\"anchen shift in
  Optics

abstract:
  Delay times in quantum mechanics always represented an intriguing challenge
for physicists. Due to the fact that quantum mechanical experiments are, often,
hard to be implemented, the possibility to connect delay times with laser
lateral displacements gives us the opportunity to prepare, in optical
laboratories, experiments which are equivalent to the quantum mechanical ones
in detecting delay times. In this article, we will show in detail not only the
relationship between delay times and Goos-Haenchen shifts, but also the close
connection between the impulse change in quantum mechanics and angular
deviations in optics. Lateral shifts are caused by the phase of Fresnel
coefficients whereas angular deviations by the breaking of symmetry of the wave
number distributions. The classical formula for the delay time is based on the
use of the stationary phase method and contains a divergence for incidence at a
critical potential energy. For Gaussian beams, the mean value calculation
removes such a divergence. The closed expression for the delay time for
incidence at critical energy show an excellent agreement with the numerical
calculation. The three-dimensional analysis of delay times allow to find the
final and definitive connection between wave packets reflected by a potential
in quantum mechanics and optical beams reflected by a dielectric/air interface.


title: Beyond the Standard Model with Lepton Flavor Universality Violation

abstract:
  In recent years, exciting (indirect) hints for physics beyond the Standard
Model (SM) have been accumulated. In particular, semi-leptonic $B$ decays show
deviations from the SM predictions, which, due to the ratios $R(K^{(*)})$ and
$R(D^{(*)})$ are obviously related to lepton flavour universality violation
(LFUV). However, {we point out} there are more anomalies which admit an
interpretation in terms of LFUV: The anomalous magnetic moment of the muon, the
Cabibbo angle anomaly, the CMS measurements of non-resonant di-electrons, the
difference of the forward-backward asymmetry in $B\to D^*\ell\nu$ and leptonic
tau decays. In this letter we discuss the experimental and theoretical status
of these anomalies, {compare their strength and weaknesses} and examine {and
synthesize} how they can be explained in terms of possible extensions of the SM
by new particles and interactions. Even though not all anomalies might be
confirmed in the future, this unified view of the anomalies in terms of LFUV
significantly strengthens their relevance, which is crucial in order to
construct a convincing physics case for future colliders.


title: Cross Pairwise Ranking for Unbiased Item Recommendation

abstract:
  Most recommender systems optimize the model on observed interaction data,
which is affected by the previous exposure mechanism and exhibits many biases
like popularity bias. The loss functions, such as the mostly used pointwise
Binary Cross-Entropy and pairwise Bayesian Personalized Ranking, are not
designed to consider the biases in observed data. As a result, the model
optimized on the loss would inherit the data biases, or even worse, amplify the
biases. For example, a few popular items take up more and more exposure
opportunities, severely hurting the recommendation quality on niche items --
known as the notorious Mathew effect. In this work, we develop a new learning
paradigm named Cross Pairwise Ranking (CPR) that achieves unbiased
recommendation without knowing the exposure mechanism. Distinct from inverse
propensity scoring (IPS), we change the loss term of a sample -- we
innovatively sample multiple observed interactions once and form the loss as
the combination of their predictions. We prove in theory that this way offsets
the influence of user/item propensity on the learning, removing the influence
of data biases caused by the exposure mechanism. Advantageous to IPS, our
proposed CPR ensures unbiased learning for each training instance without the
need of setting the propensity scores. Experimental results demonstrate the
superiority of CPR over state-of-the-art debiasing solutions in both model
generalization and training efficiency. The codes are available at
https://github.com/Qcactus/CPR.


title:
A Comparative Study on Approaches to Acoustic Scene Classification using
  CNNs

abstract:
  Acoustic scene classification is a process of characterizing and classifying
the environments from sound recordings. The first step is to generate features
(representations) from the recorded sound and then classify the background
environments. However, different kinds of representations have dramatic effects
on the accuracy of the classification. In this paper, we explored the three
such representations on classification accuracy using neural networks. We
investigated the spectrograms, MFCCs, and embeddings representations using
different CNN networks and autoencoders. Our dataset consists of sounds from
three settings of indoors and outdoors environments - thus the dataset contains
sound from six different kinds of environments. We found that the spectrogram
representation has the highest classification accuracy while MFCC has the
lowest classification accuracy. We reported our findings, insights as well as
some guidelines to achieve better accuracy for environment classification using
sounds.


title:
Network location and clustering of genetic mutations determine
  chronicity in a stylized model of genetic diseases

abstract:
  In a highly simplified view, a disease can be seen as the phenotype emerging
from the interplay of genetic predisposition and fluctuating environmental
stimuli. We formalize this situation in a minimal model, where a network
(representing cellular regulation) serves as an interface between an input
layer (representing environment) and an output layer (representing functional
phenotype). Genetic predisposition for a disease is represented as a loss of
function of some network nodes. Reduced, but non-zero, output indicates
disease. The simplicity of this genetic disease model and its deep relationship
to percolation theory allows us to understand the interplay between disease,
network topology and the location and clusters of affected network nodes. We
find that our model generates two different characteristics of diseases, which
can be interpreted as chronic and acute diseases. In its stylized form, our
model provides a new view on the relationship between genetic mutations and the
type and severity of a disease.


title: Monge-Amp\`ere measures for toric metrics on abelian varieties

abstract:
  Toric metrics on a line bundle of an abelian variety $A$ are the invariant
metrics under the natural torus action coming from Raynaud's uniformization
theory. We compute here the associated Monge-Amp\`ere measures for the
restriction to any closed subvariety of $A$. This generalizes the computation
of canonical measures done by the first author from canonical metrics to toric
metrics and from discrete valuations to arbitrary non-archimedean fields.


title:
Hubble Tension from Bubble Tension: Cosmic Voids, Local and Global
  Scales

abstract:
  Although the size of the cosmic void is much larger than the size of local
scales and much smaller than the size of cosmic scale, it will be shown that
they can be considered a very good representative for studying both local and
global scales. For this goal, we will first consider the cosmic voids in the
cosmic web as interconnected spherical bubbles. We will then show by heuristic
calculations that for each cosmic void we obtain different mass densities and
cosmological constants that are the same order of magnitude as the entire
universe. It will also be shown that the slight difference between the surface
tension of the bubbles may be the source of the $H_{\rm 0}$ tension between
local and global measurements. As a necessary consequence of this study is that
by examining a single cosmic void more seriously, both theoretically and
observationally, interesting possible propositions can be made to solve
important challenges in physical cosmology at local and global scales.


title:
Collaborative Target Search with a Visual Drone Swarm: An Adaptive
  Curriculum Embedded Multi-stage Reinforcement Learning Approach

abstract:
  Equipping drones with target search capabilities is desirable for
applications in disaster management scenarios and smart warehouse delivery
systems. Instead of deploying a single drone, an intelligent drone swarm that
can collaborate with one another in maneuvering among obstacles will be more
effective in accomplishing the target search in a shorter amount of time. In
this work, we propose a data-efficient reinforcement learning-based approach,
Adaptive Curriculum Embedded Multi-Stage Learning (ACEMSL), to address the
challenges of carrying out a collaborative target search with a visual drone
swarm, namely the 3D sparse reward space exploration and the collaborative
behavior requirement. Specifically, we develop an adaptive embedded curriculum,
where the task difficulty level can be adaptively adjusted according to the
success rate achieved in training. Meanwhile, with multi-stage learning, ACEMSL
allows data-efficient training and individual-team reward allocation for the
collaborative drone swarm. The effectiveness and generalization capability of
our approach are validated using simulations and actual flight tests.


title:
Direct Bound-Electron $g$ factor Difference Measurement with Coupled
  Ions

abstract:
  The quantum electrodynamic (QED) description of light-and-matter interaction
is one of the most fundamental theories of physics and has been shown to be in
excellent agreement with experimental results. Specifically, measurements of
the electronic magnetic moment (or $g$ factor) of highly charged ions (HCI) in
Penning traps can provide a stringent probe for QED, testing the Standard model
in the strongest electromagnetic fields. When studying the difference of
isotopes, even the intricate effects stemming from the nucleus can be resolved
and tested as, due to the identical electron configuration, many common QED
contributions do not have to be considered. Experimentally however, this
becomes quickly limited, particularly by the precision of the ion masses or the
achievable magnetic field stability. Here we report on a novel measurement
technique that overcomes both of these limitations by co-trapping two HCIs in a
Penning trap and measuring the difference of their $g$ factors directly. The
resulting correlation of magnetic field fluctuations leads to drastically
higher precision. We use a dual Ramsey-type measurement scheme with the ions
locked on a common magnetron orbit, separated by only a few hundred
micrometres, to extract the coherent spin precession frequency difference. We
have measured the isotopic shift of the bound electron $g$ factor of the neon
isotopes of $^{20}$Ne$^{9+}$ and $^{22}$Ne$^{9+}$ to 0.56 parts-per-trillion
($5.6 \cdot 10^{-13}$) precision relative to their $g$ factors, which is an
improvement of more than two orders of magnitude compared to state-of-the-art
techniques. This resolves the QED contribution to the nuclear recoil for the
very first time and accurately validates the corresponding theory. Furthermore,
the agreement with theory allows setting constraints for a fifth-force,
resulting from Higgs-portal-type dark-matter interactions.


title:
Comparing the number of infected vertices in two symmetric sets for
  Bernoulli percolation (and other random partitions)

abstract:
  For Bernoulli percolation on a given graph $G = (V,E)$ we consider the
cluster of some fixed vertex $o \in V$. We aim at comparing the number of
vertices of this cluster in the set $V_+$ and in the set $V_-$, where $V_+,V_-
\subset V$ have the same size. Intuitively, if $V_-$ is further away from $o$
than $V_+$, it should contain fewer vertices of the cluster. We prove such a
result in terms of stochastic domination, provided that $o \in V_+$, and
$V_+,V_-$ satisfy some strong symmetry conditions, and we give applications of
this result in case $G$ is a bunkbed graph, a layered graph, the 2D square
lattice or a hypercube graph. Our result only relies on general probabilistic
techniques and a combinatorial result on group actions, and thus extends to
fairly general random partitions, e.g. as induced by Bernoulli site percolation
or the random cluster model.


title:
SkillNet-NLG: General-Purpose Natural Language Generation with a
  Sparsely Activated Approach

abstract:
  We present SkillNet-NLG, a sparsely activated approach that handles many
natural language generation tasks with one model. Different from traditional
dense models that always activate all the parameters, SkillNet-NLG selectively
activates relevant parts of the parameters to accomplish a task, where the
relevance is controlled by a set of predefined skills. The strength of such
model design is that it provides an opportunity to precisely adapt relevant
skills to learn new tasks effectively. We evaluate on Chinese natural language
generation tasks. Results show that, with only one model file, SkillNet-NLG
outperforms previous best performance methods on four of five tasks.
SkillNet-NLG performs better than two multi-task learning baselines (a dense
model and a Mixture-of-Expert model) and achieves comparable performance to
task-specific models. Lastly, SkillNet-NLG surpasses baseline systems when
being adapted to new tasks.


title:
TranSiam: Fusing Multimodal Visual Features Using Transformer for
  Medical Image Segmentation

abstract:
  Automatic segmentation of medical images based on multi-modality is an
important topic for disease diagnosis. Although the convolutional neural
network (CNN) has been proven to have excellent performance in image
segmentation tasks, it is difficult to obtain global information. The lack of
global information will seriously affect the accuracy of the segmentation
results of the lesion area. In addition, there are visual representation
differences between multimodal data of the same patient. These differences will
affect the results of the automatic segmentation methods. To solve these
problems, we propose a segmentation method suitable for multimodal medical
images that can capture global information, named TranSiam. TranSiam is a 2D
dual path network that extracts features of different modalities. In each path,
we utilize convolution to extract detailed information in low level stage, and
design a ICMT block to extract global information in high level stage. ICMT
block embeds convolution in the transformer, which can extract global
information while retaining spatial and detailed information. Furthermore, we
design a novel fusion mechanism based on cross attention and selfattention,
called TMM block, which can effectively fuse features between different
modalities. On the BraTS 2019 and BraTS 2020 multimodal datasets, we have a
significant improvement in accuracy over other popular methods.


title:
Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level
  Parallel Decoding and Alignment Loss

abstract:
  Grammar-based parsers have achieved high performance in the cross-domain
text-to-SQL parsing task, but suffer from low decoding efficiency due to the
much larger number of actions for grammar selection than that of tokens in SQL
queries. Meanwhile, how to better align SQL clauses and question segments has
been a key challenge for parsing performance. Therefore, this paper proposes
clause-level parallel decoding and alignment loss to enhance two
high-performance grammar-based parsers, i.e., RATSQL and LGESQL. Experimental
results of two parsers show that our method obtains consistent improvements
both in accuracy and decoding speed.


title:
GASTRO library I: the simulated chemodynamical properties of several
  GSE-like stellar halos

abstract:
  The Milky Way stellar halo contains relics of ancient mergers that tell the
story of our Galaxy's formation. Some of them are identified due to their
similarity in energy, actions and chemistry, referred to as the "chemodynamical
space", and are often attributed to distinct merger events. It is also known
that our Galaxy went through a significant merger event that shaped the local
stellar halo during its first Gyr. Previous studies using $N$-body only and
cosmological hydrodynamical simulations have shown that such single massive
merger can produce several "signatures" in the chemodynamical space, which can
potentially be misinterpreted as distinct merger events. Motivated by these, in
this work we use a subset of the GASTRO, library which consists of several
SPH+$N$-body models of single accretion event in a Milky Way-like galaxy. Here,
we study models with orbital properties similar to the main merger event of our
Galaxy and explore the implications to known stellar halo substructures. We
find that: $i.$ supernova feedback efficiency influences the satellite's
structure and orbital evolution, resulting in distinct chemodynamical features
for models with the same initial conditions, $ii.$ very retrograde high energy
stars are the most metal-poor of the accreted dwarf galaxy and could be
misinterpreted as a distinct merger $iii.$ the most bound stars are more
metal-rich in our models, the opposite of what is observed in the Milky Way,
suggesting a secondary massive merger, and finally $iv.$ our models can
reconcile other known substructures to an unique progenitor.


title:
Design and Experimental Evaluation of a Bluetooth 5.1 Antenna Array for
  Angle-of-Arrival Estimation

abstract:
  On the of the applications in the realm of the Internet-of-Things (IoT) is
real-time localization of assets in specific application environments where
satellite based global positioning is unviable. Numerous approaches for
localization relying on wireless sensor mesh systems have been evaluated, but
the recent Bluetooth Low Energy (BLE) 5.1 direction finding features based on
Angle-of-Arrival (AoA) promise a low-cost solution for this application. In
this paper, we present an implementation of a BLE 5.1 based circular antenna
array, and perform two experimental evaluations over the quality of the
retrieved data sampled from the array: in an anechoic chamber, and in a
real-world environment using a setup composed of four BLE beacons.


title: Restoring rotational invariance for lattice QCD propagators

abstract:
  This note presents a method to reduce the discretization errors appearing
when solving a Quantum Field Theory in a hypercubic lattice in both position
and momentum-space. The method exploits the artifacts that break rotational
symmetry to recover rotationally invariant results for two-point Green
functions. We show that a combination of the results obtained in position and
momentum space can be useful to signal the presence of rotationally invariant
artifacts making use of their approximate Fourier transforms in the continuum.
The method will be introduced using a Klein-Gordon propagator, and a direct
application to gluon propagator in quenched lattice QCD will be given.


title:
Multi-Agent Reinforcement Learning for Traffic Signal Control through
  Universal Communication Method

abstract:
  How to coordinate the communication among intersections effectively in real
complex traffic scenarios with multi-intersection is challenging. Existing
approaches only enable the communication in a heuristic manner without
considering the content/importance of information to be shared. In this paper,
we propose a universal communication form UniComm between intersections.
UniComm embeds massive observations collected at one agent into crucial
predictions of their impact on its neighbors, which improves the communication
efficiency and is universal across existing methods. We also propose a concise
network UniLight to make full use of communications enabled by UniComm.
Experimental results on real datasets demonstrate that UniComm universally
improves the performance of existing state-of-the-art methods, and UniLight
significantly outperforms existing methods on a wide range of traffic
situations.


title: EmpHi: Generating Empathetic Responses with Human-like Intents

abstract:
  In empathetic conversations, humans express their empathy to others with
empathetic intents. However, most existing empathetic conversational methods
suffer from a lack of empathetic intents, which leads to monotonous empathy. To
address the bias of the empathetic intents distribution between empathetic
dialogue models and humans, we propose a novel model to generate empathetic
responses with human-consistent empathetic intents, EmpHi for short. Precisely,
EmpHi learns the distribution of potential empathetic intents with a discrete
latent variable, then combines both implicit and explicit intent representation
to generate responses with various empathetic intents. Experiments show that
EmpHi outperforms state-of-the-art models in terms of empathy, relevance, and
diversity on both automatic and human evaluation. Moreover, the case studies
demonstrate the high interpretability and outstanding performance of our model.


title: Noisy Quantum Kernel Machines

abstract:
  In the noisy intermediate-scale quantum era, an important goal is the
conception of implementable algorithms that exploit the rich dynamics of
quantum systems and the high dimensionality of the underlying Hilbert spaces to
perform tasks while prescinding from noise-proof physical systems. An emerging
class of quantum learning machines is that based on the paradigm of quantum
kernels. Here, we study how dissipation and decoherence affect their
performance. We address this issue by investigating the expressivity and the
generalization capacity of these models within the framework of kernel theory.
We introduce and study the effective kernel rank, a figure of merit that
quantifies the number of independent features a noisy quantum kernel is able to
extract from input data. Moreover, we derive an upper bound on the
generalization error of the model that involves the average purity of the
encoded states. Thereby we show that decoherence and dissipation can be seen as
an implicit regularization for the quantum kernel machines. As an illustrative
example, we report exact finite-size simulations of machines based on chains of
driven-dissipative quantum spins to perform a classification task, where the
input data are encoded into the driving fields and the quantum physical system
is fixed. We determine how the performance of noisy kernel machines scales with
the number of nodes (chain sites) as a function of decoherence and examine the
effect of imperfect measurements.


title:
Stochastic Coherence Over Attention Trajectory For Continuous Learning
  In Video Streams

abstract:
  Devising intelligent agents able to live in an environment and learn by
observing the surroundings is a longstanding goal of Artificial Intelligence.
From a bare Machine Learning perspective, challenges arise when the agent is
prevented from leveraging large fully-annotated dataset, but rather the
interactions with supervisory signals are sparsely distributed over space and
time. This paper proposes a novel neural-network-based approach to
progressively and autonomously develop pixel-wise representations in a video
stream. The proposed method is based on a human-like attention mechanism that
allows the agent to learn by observing what is moving in the attended
locations. Spatio-temporal stochastic coherence along the attention trajectory,
paired with a contrastive term, leads to an unsupervised learning criterion
that naturally copes with the considered setting. Differently from most
existing works, the learned representations are used in open-set
class-incremental classification of each frame pixel, relying on few
supervisions. Our experiments leverage 3D virtual environments and they show
that the proposed agents can learn to distinguish objects just by observing the
video stream. Inheriting features from state-of-the art models is not as
powerful as one might expect.


title:
Revealing the Mechanism of Magnetic Domain Formation by Topological Data
  Analysis

abstract:
  Understanding pattern formation processes with long-range interactions that
result in nonuniform and nonperiodic structures is important for revealing the
physical properties of widely observed complex systems in nature. In many
cases, pattern formation processes are measured on the basis of spatially
coarse-grained features of the smallest elements, that is, the pixel space of a
grayscale image. By binarizing the data using a common threshold, one can
analyze such grayscale image data using geometrical features, such as the
number of domains (Betti number) or domain size. Because such topological
features are indicators for evaluating all regions uniformly, it is difficult
to determine the nature of each region in a nonuniform structure. Moreover,
binarization leads to loss of valuable information such as fluctuations in the
domain. Here, we show that the analysis method based on persistent homology
provides effective knowledge to understand such pattern formation processes.
Specifically, we analyze the pattern formation process in ferromagnetic
materials under a rapidly sweeping external magnetic field and discover not
only existing types of pattern formation dynamics but also novel ones. On the
basis of results of topological data analysis, we also found a candidate
reduction model to describe the mechanics of these novel magnetic domain
formations. The analysis procedure with persistent homology presented in this
paper provides one format applicable to extracting scientific knowledge from a
wide range of pattern formation processes with long-range interactions.


title: Understanding User Satisfaction with Task-oriented Dialogue Systems

abstract:
  $ $Dialogue systems are evaluated depending on their type and purpose. Two
categories are often distinguished: (1) task-oriented dialogue systems (TDS),
which are typically evaluated on utility, i.e., their ability to complete a
specified task, and (2) open domain chatbots, which are evaluated on the user
experience, i.e., based on their ability to engage a person. What is the
influence of user experience on the user satisfaction rating of TDS as opposed
to, or in addition to, utility? We collect data by providing an additional
annotation layer for dialogues sampled from the ReDial dataset, a widely used
conversational recommendation dataset. Unlike prior work, we annotate the
sampled dialogues at both the turn and dialogue level on six dialogue aspects:
relevance, interestingness, understanding, task completion, efficiency, and
interest arousal. The annotations allow us to study how different dialogue
aspects influence user satisfaction. We introduce a comprehensive set of user
experience aspects derived from the annotators' open comments that can
influence users' overall impression. We find that the concept of satisfaction
varies across annotators and dialogues, and show that a relevant turn is
significant for some annotators, while for others, an interesting turn is all
they need. Our analysis indicates that the proposed user experience aspects
provide a fine-grained analysis of user satisfaction that is not captured by a
monolithic overall human rating.


title: Adaptive Split-Fusion Transformer

abstract:
  Neural networks for visual content understanding have recently evolved from
convolutional ones (CNNs) to transformers. The prior (CNN) relies on
small-windowed kernels to capture the regional clues, demonstrating solid local
expressiveness. On the contrary, the latter (transformer) establishes
long-range global connections between localities for holistic learning.
Inspired by this complementary nature, there is a growing interest in designing
hybrid models to best utilize each technique. Current hybrids merely replace
convolutions as simple approximations of linear projection or juxtapose a
convolution branch with attention, without concerning the importance of
local/global modeling. To tackle this, we propose a new hybrid named Adaptive
Split-Fusion Transformer (ASF-former) to treat convolutional and attention
branches differently with adaptive weights. Specifically, an ASF-former encoder
equally splits feature channels into half to fit dual-path inputs. Then, the
outputs of dual-path are fused with weighting scalars calculated from visual
cues. We also design the convolutional path compactly for efficiency concerns.
Extensive experiments on standard benchmarks, such as ImageNet-1K, CIFAR-10,
and CIFAR-100, show that our ASF-former outperforms its CNN, transformer
counterparts, and hybrid pilots in terms of accuracy (83.9% on ImageNet-1K),
under similar conditions (12.9G MACs/56.7M Params, without large-scale
pre-training). The code is available at:
https://github.com/szx503045266/ASF-former.


title:
Evaluating Automatic Difficulty Estimation of Logic Formalization
  Exercises

abstract:
  Teaching logic effectively requires an understanding of the factors which
cause logic students to struggle. Formalization exercises, which require the
student to produce a formula corresponding to the natural language sentence,
are a good candidate for scrutiny since they tap into the students'
understanding of various aspects of logic. We correlate the difficulty of
formalization exercises predicted by a previously proposed difficulty
estimation algorithm with two empirical difficulty measures on the Grade
Grinder corpus, which contains student solutions to FOL exercises. We obtain a
moderate correlation with both measures, suggesting that the said algorithm
indeed taps into important sources of difficulty but leaves a fair amount of
variance uncaptured. We conduct an error analysis, closely examining exercises
which were misclassified, with the aim of identifying additional sources of
difficulty. We identify three additional factors which emerge from the
difficulty analysis, namely predicate complexity, pragmatic factors and
typicality of the exercises, and discuss the implications of automated
difficulty estimation for logic teaching and explainable AI.


title:
Demonstration of Floquet engineering using pulse driving in a diamond
  two-level system under a large-amplitude modulation

abstract:
  The nitrogen-vacancy (NV) center in a diamond is a promising platform for
Floquet system. We investigate NV center's Floquet state driven by Carr-Purcell
sequence in a large-amplitude AC magnetic field using the sequential readout.
We observe the dynamics represented as Bessel functions up to 211th orders high
in a systematic and quantitative agreement with the theoretical model.
Furthermore, numerical calculations show that the effect of finite pulse
duration and error limits the modulation amplitude available for Floquet
engineering. This work provides an approach to precisely investigate Floquet
engineering, showing the extendable range of modulation amplitude, for
two-level systems.


title: Line Profile Asymmetry in Precision Spectroscopy

abstract:
  In this review, we have investigated the asymmetry of the line profile in
precision one- and two-photon spectroscopy of hydrogen and helium atoms within
the framework of a rigorous QED approach. A detailed analysis of the angular
correlations of the quantum interference effect has been carried out using
various examples. Nonresonant effects are also considered in relation to some
astrophysical problems. In particular, a rigorous QED derivation of the
nonresonant extension for the Lorentz line profile is given using the
Ly$_{\alpha}$ transition as an example; such a QED derivation has been lacking
in the literature.


abstract:
  Collaborative Filtering (CF) has emerged as fundamental paradigms for
parameterizing users and items into latent representation space, with their
correlative patterns from interaction data. Among various CF techniques, the
development of GNN-based recommender systems, e.g., PinSage and LightGCN, has
offered the state-of-the-art performance. However, two key challenges have not
been well explored in existing solutions: i) The over-smoothing effect with
deeper graph-based CF architecture, may cause the indistinguishable user
representations and degradation of recommendation results. ii) The supervision
signals (i.e., user-item interactions) are usually scarce and skewed
distributed in reality, which limits the representation power of CF paradigms.
To tackle these challenges, we propose a new self-supervised recommendation
framework Hypergraph Contrastive Collaborative Filtering (HCCF) to jointly
capture local and global collaborative relations with a hypergraph-enhanced
cross-view contrastive learning architecture. In particular, the designed
hypergraph structure learning enhances the discrimination ability of GNN-based
CF paradigm, so as to comprehensively capture the complex high-order
dependencies among users. Additionally, our HCCF model effectively integrates
the hypergraph structure encoding with self-supervised learning to reinforce
the representation quality of recommender systems, based on the
hypergraph-enhanced self-discrimination. Extensive experiments on three
benchmark datasets demonstrate the superiority of our model over various
state-of-the-art recommendation methods, and the robustness against sparse user
interaction data. Our model implementation codes are available at
https://github.com/akaxlh/HCCF.


title:
Accelerating Fully Homomorphic Encryption by Bridging Modular and
  Bit-Level Arithmetic

abstract:
  The dramatic increase of data breaches in modern computing platforms has
emphasized that access control is not sufficient to protect sensitive user
data. Recent advances in cryptography allow end-to-end processing of encrypted
data without the need for decryption using Fully Homomorphic Encryption (FHE).
Such computation however, is still orders of magnitude slower than direct
(unencrypted) computation. Depending on the underlying cryptographic scheme,
FHE schemes can work natively either at bit-level using Boolean circuits, or
over integers using modular arithmetic. Operations on integers are limited to
addition/subtraction and multiplication. On the other hand, bit-level
arithmetic is much more comprehensive allowing more operations, such as
comparison and division. While modular arithmetic can emulate bit-level
computation, there is a significant cost in performance. In this work, we
propose a novel method, dubbed \emph{bridging}, that blends faster and
restricted modular computation with slower and comprehensive bit-level
computation, making them both usable within the same application and with the
same cryptographic scheme instantiation. We introduce and open source C++ types
representing the two distinct arithmetic modes, offering the possibility to
convert from one to the other. Experimental results show that bridging modular
and bit-level arithmetic computation can lead to 1-2 orders of magnitude
performance improvement for tested synthetic benchmarks, as well as two
real-world FHE applications: A URL denylisting case study, and a genotype
imputation application. Bridging performance enhancement comes from two
factors: 1) Reduced number of operations (especially ciphertext
multiplications), and 2) Arithmetic circuits with smaller multiplicative depth,
allowing more efficient encryption parameters with smaller polynomial degrees.


title:
Urban Change Detection Using a Dual-Task Siamese Network and
  Semi-Supervised Learning

abstract:
  In this study, a Semi-Supervised Learning (SSL) method for improving urban
change detection from bi-temporal image pairs was presented. The proposed
method adapted a Dual-Task Siamese Difference network that not only predicts
changes with the difference decoder, but also segments buildings for both
images with a semantics decoder. First, the architecture was modified to
produce a second change prediction derived from the semantics predictions.
Second, SSL was adopted to improve supervised change detection. For unlabeled
data, we introduced a loss that encourages the network to predict consistent
changes across the two change outputs. The proposed method was tested on urban
change detection using the SpaceNet7 dataset. SSL achieved improved results
compared to three fully supervised benchmarks.


title: Lower bounds of sets of P-points

abstract:
  We show that $\mathrm{MA}_{\kappa}$ implies that each collection of
${P}_{\mathfrak c}$-points of size at most $\kappa$ which has a $P_{\mathfrak
c}$-point as an $RK$ upper bound also has a ${P}_{\mathfrak c}$-point as an
$RK$ lower bound.


title: Boosting Adversarial Transferability of MLP-Mixer

abstract:
  The security of models based on new architectures such as MLP-Mixer and ViTs
needs to be studied urgently. However, most of the current researches are
mainly aimed at the adversarial attack against ViTs, and there is still
relatively little adversarial work on MLP-mixer. We propose an adversarial
attack method against MLP-Mixer called Maxwell's demon Attack (MA). MA breaks
the channel-mixing and token-mixing mechanism of MLP-Mixer by controlling the
part input of MLP-Mixer's each Mixer layer, and disturbs MLP-Mixer to obtain
the main information of images. Our method can mask the part input of the Mixer
layer, avoid overfitting of the adversarial examples to the source model, and
improve the transferability of cross-architecture. Extensive experimental
evaluation demonstrates the effectiveness and superior performance of the
proposed MA. Our method can be easily combined with existing methods and can
improve the transferability by up to 38.0% on MLP-based ResMLP. Adversarial
examples produced by our method on MLP-Mixer are able to exceed the
transferability of adversarial examples produced using DenseNet against CNNs.
To the best of our knowledge, we are the first work to study adversarial
transferability of MLP-Mixer.


title:
The effects of driving time scales on coronal heating in a stratified
  atmosphere

abstract:
  Aims: We investigate the atmospheric response to coronal heating driven by
random flows with different characteristic time scales and amplitudes. Methods:
We conducted a series of 3D MHD simulations of random driving imposed on a
gravitationally stratified model of the solar atmosphere. In order to
understand differences between alternating current (AC) and direct current (DC)
heating, we considered the effects of changing the characteristic time scales
of the imposed velocities. We also investigated the effects of the magnitude of
the velocity driving. Results: Complex foot point motions lead to a
proliferation of current sheets and energy dissipation throughout the corona.
For a given amplitude, DC driving typically leads to a greater rate of energy
injection when compared to AC driving. This leads to the formation of larger
currents, increased heating rates and higher temperatures in DC simulations.
There is no difference in the spatial distribution of energy dissipation across
simulations, however, energy release events in AC cases tend to be more
frequent and last for less time. Higher velocity driving is associated with
larger currents, higher temperatures and the corona occupying a larger fraction
of the simulation volume. In all cases, most of heating is associated with
small energy release events, which occur much more frequently than large
events. Conclusions: When combined with observational results showing a greater
abundance of power in low frequency modes, these findings suggest that energy
release in the corona is likely to be driven by long time scale motions. In the
corona, AC and DC driving will occur concurrently and their effects remain
difficult to isolate. The distribution of field line temperatures and the
asymmetry of temperature profiles may reveal the frequency and longevity of
energy release events and therefore the relative importance of AC and DC
heating.


title:
The GAPS programme at TNG XXXIV. Activity-rotation, flux-flux
  relationships, and active region evolution through stellar age

abstract:
  Active region evolution plays an important role in the generation and
variability of magnetic fields on the surface of lower main-sequence stars.
However, determining the lifetime of active region growth and decay as well as
their evolution is a complex task. We aim to test whether the lifetime for
active region evolution shows any dependency on the stellar parameters. We
identify a sample of stars with well-defined ages via their kinematics. We made
use of high-resolution spectra to compute rotational velocities, activity
levels, and emission excesses. We use these data to revisit the
activity-rotation-age relationship. The time-series of the main optical
activity indicators were analysed together with the available photometry by
using Gaussian processes to model the stellar activity of these stars.
Autocorrelation functions of the available photometry were also analysed. We
use the derived lifetimes for active region evolution to search for
correlations with the stellar age, the spectral type, and the level of
activity. We also use the pooled variance technique to characterise the
activity behaviour of our targets. Our analysis confirms the decline of
activity and rotation as the star ages. We also confirm that the rotation rate
decays with age more slowly for cooler stars and that, for a given age, cooler
stars show higher levels of activity. We show that F- and G-type young stars
also depart from the inactive stars in the flux-flux relationship. The gaussian
process analysis of the different activity indicators does not seem to provide
any useful information on active region's lifetime and evolution. On the other
hand, active region's lifetimes derived from the light-curve analysis might
correlate with the stellar age and temperature. Although we caution the small
number statistics, our results suggest that active regions seem to live longer
on younger, cooler, and more active stars.


title:
Shrinking target horospherical equidistribution via translated Farey
  sequences

abstract:
  For a certain diagonal flow on $\operatorname{SL}(d, \mathbb{Z}) \backslash
\operatorname{SL}(d, \mathbb{R})$ where $d \geq 2$, we show that any bounded
subset (with measure zero boundary) of the horosphere or a translated
horosphere equidistributes, under a suitable normalization, on a target
shrinking into the cusp. This type of equidistribution is $\textit{shrinking
target horospherical equidistribution (STHE)}$, and we show STHE for several
types of shrinking targets. Our STHE results extend known results for $d=2$ and
$\mathcal{L} \backslash \operatorname{PSL}(2, \mathbb{R})$ where $\mathcal{L}$
is any cofinite Fuchsian group with at least one cusp.
  The two key tools needed to prove our STHE results for the horosphere are a
renormalization technique and Marklof's result on the equidistribution of the
Farey sequence on distinguished sections. For our STHE results for translated
horospheres, we introduce $\textit{translated Farey sequences}$, develop some
of their geometric and dynamical properties, generalize Marklof's result by
proving the equidistribution of translated Farey sequences for the same
distinguished sections, and use this equidistribution of translated Farey
sequences along with the renormalization technique to prove our STHE results
for translated horospheres.


title:
Charge order from the local Coulomb repulsion in undoped infinite-layer
  nickelates

abstract:
  Competition between superconductivity and other various ordered states plays
a central role in correlated electron materials. The charge order with
translational symmetry breaking has been observed in the parent compounds of
nickelate superconductors with a wave vector
$\mathbf{q}\simeq\left(\frac{1}{3},0,0\right)$. Here we combine
density-functional-theory and dynamical-mean-field-theory to study undoped
NdNiO$_2$, and find that the charge ordered state with a periodic
Ni$^{1+}$-Ni$^{2+}$-Ni$^{1+}$ pattern can have a lower energy than the
paramagnetic state and the checkerboard antiferromagnetic state for the strong
local Coulomb repulsion on the Ni-$d_{x^2-y^2}$ orbital. Its spectral function
evidently shows that the Ni$^{2+}$-$d_{x^2-y^2}$ orbital forms a hole-singlet
due to the electron transfer to the interstitial-$s$/Nd-$d$ conduction bands,
while the Ni$^{1+}$-$d_{x^2-y^2}$ orbital exhibits a sharp quasiparticle
resonance near the Fermi energy inside the Mott Hubbard gap. The charge order
can be controlled by the charge transfer energy between Ni-$d$ and
interstitial-$s$/Nd-$d$ orbitals, and there is a delicate competition between
the kinetic energy cost and the potential energy gain, compared to the
checkboard antiferromagnetic state. Our results provide a pure electronic
explanation of the charge order observed experimentally and reveal some
distinctive properties of the infinite-layer nickelates.


title:
Polarization switching induced by domain wall sliding in two-dimensional
  ferroelectric monochalcogenides

abstract:
  Monolayer ferroelectric materials have emerged as a promising avenue for
miniaturization of ferroelectric devices, and as potential candidate materials
for future photovoltaics or thermoelectrics. The properties of ferroelectrics
are strongly influenced by the presence of domain walls, but a detailed
theoretical understanding of their role in polarization switching and influence
on optical properties is still lacking in two-dimensional materials. In this
work we study structural, dynamic, electronic and optical properties of 90 and
180 degree DWs in monolayer GeS, GeSe, SnS and SnSe, by means of DFT
calculations. We find that, in all cases, 180 degree walls impact the
properties stronger than 90 degree walls and exhibit higher formation energies.
In particular, calculations of the optical absorption show that 180 degree
walls may induce a red shift of the optical absorption peak of the materials,
significantly enhancing their solar light absorption at high DW densities. We
then calculate the formation energies and migration barriers of DWs and find
that these are strongly dependent on lattice anisotropy. The barriers allow us
to extract the electric field required to induce DW migration and we find much
lower values of the coercive fields compared to coherent bulk polarization
switching. Our results are in agreement with experimental coercive field
measured for SnS and thus elucidate the crucial role of domain walls in
polarization switching.


title:
Period tripling due to Josephson parametric down-conversion beyond the
  rotating-wave approximation

abstract:
  Parametrically driven oscillators can display period-tripling in response to
a drive at thrice the resonance frequency. In contrast to the parametric
instability for period doubling, the symmetric fixed-point corresponding to the
state of rest remains stable at arbitrary strong driving for the tripling
transition. Previously, it has been shown that fluctuations can circumvent this
and induce a period-tripling instability. In this article, we explore an
alternative way of inducing a period-tripling transition by investigating
properties of period-tripling due to parametric down-conversion beyond the
rotating-wave approximation. We show that despite the absence of an instability
threshold, off-resonant frequency contributions can induce a period-tripling
transition by activating the parametric down-conversion. Moreover, we study the
subsequent period-tripled states of the Josephson potential and discuss the
asymmetry between the clockwise and counter-clockwise rotating fixed-points
that only arises beyond the rotating-wave approximation.


title:
Toeplitz operators and Carleson measure between weighted Bergman spaces
  induced by regular weights

abstract:
  In this paper, we give a universal description of the boundedness and
compactness of Toeplitz operator $\mathcal{T}_\mu^\omega$ between Bergman
spaces $A_\eta^p$ and $A_\upsilon^q$ when $\mu$ is a positive Borel measure,
$1<p,q<\infty$ and $\omega,\eta,\upsilon$ are regular weights. By using
Khinchin's inequality and Kahane's inequality, we get a new characterization of
the Carleson measure for Bergman spaces induced by regular weights.


title: Quantum Riemannian geometry of the discrete interval and q-deformation

abstract:
  We solve for quantum Riemannian geometries on the finite lattice interval
$\bullet-\bullet-\cdots-\bullet$ with $n$ nodes (the Dynkin graph of type
$A_n$) and find that they are necessarily $q$-deformed with
$q=e^{\imath\pi\over n+1}$. This comes out of the intrinsic geometry and not by
assuming any quantum group in the picture. Specifically, we discover a novel
`boundary effect' whereby, in order to admit a quantum-Levi Civita connection,
the `metric weight' at any edge is forced to be greater pointing towards the
bulk compared to towards the boundary, with ratio given by $(i+1)_q/(i)_q$ at
node $i$, where $(i)_q$ is a $q$-integer. The Christoffel symbols are also
q-deformed. The limit $q\to 1$ is the quantum Riemannian geometry of the
natural numbers $\Bbb N$ with rational metric multiples $(i+1)/i$ in the
direction of increasing $i$. In both cases there is a unique metric up to
normalisation with zero Ricci scalar curvature. Elements of QFT and quantum
gravity are exhibited for $n=3$ and for the continuum limit of the geometry of
$\Bbb N$. The Laplacian the scaler-flat metric becomes the Airy equation
operator ${1\over x}{d^2\over d x^2}$ in so far as a limit exists. Scaling this
metric by a conformal factor $e^{\psi(i)}$ gives a limiting Ricci scalar
curvature proportional to ${1\over x}{d \over d x}\left({d \psi\over d
x}\right)^2$.


title:
Nematic fluctuations mediated superconductivity revealed by anisotropic
  strain in Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$

abstract:
  Anisotropic strain is an external field capable of selectively addressing the
role of nematic fluctuations in promoting superconductivity. We demonstrate
this using polarization-resolved elasto-Raman scattering to probe the evolution
of nematic fluctuations under strain in the normal and superconducting states
of the paradigmatic iron-based superconductor Ba(Fe$_{1-x}$Co$_x$)$_2$As$_2$.
In the non-superconducting parent compound BaFe$_2$As$_2$ we observe a
strain-induced suppression of the nematic susceptibility which follows the
expected behavior of an Ising order parameter under a symmetry breaking field.
For the superconducting compound, the suppression of the nematic susceptibility
correlates with the decrease of the superconducting critical temperature $T_c$.
Our results indicate a significant contribution of nematic fluctuations to
electron pairing and validate theoretical scenarii of enhanced $T_c$ near a
nematic quantum critical point.


title: Derivations of a family of quantum second Weyl algebras

abstract:
  In view of a well-known theorem of Dixmier, its is natural to consider
primitive quotients of $U_q^+(\mathfrak{g})$ as quantum analogues of Weyl
algebras. In this work, we study these primitive quotients in the $G_2$ case
and compute their Lie algebra of derivations.


title: Entanglement in joint $\Lambda \bar{\Lambda}$ decay; cont

abstract:
  We have previously investigated joint $\Lambda \bar{\Lambda}$ decay in the
reaction $e^+ e^- \rightarrow \gamma \Lambda(\rightarrow p\pi^-)
\bar{\Lambda}(\rightarrow \bar{p}\pi^+)$. The cross-section-distribution
functions encountered were relativistically covariant and expressed in terms of
scalar products of the four-momentum vectors of the particles involved. In the
present, sequel investigation, we show that by working with three-momentum
scalars instead results could possibly become more transparant.


title: Lieb variation principle in density-functional theory

abstract:
  Lieb's convex formulation of density-functional theory is presented in a
pedagogical manner, emphasizing its connection to Hohenberg-Kohn theory and to
Levy's constrained-search theory. The Hohenberg-Kohn and Lieb variation
principles are discussed, highlighting the dual relationship between the
ground-state energy and the universal density functional. Applications of the
Lieb variation principle are reviewed, demonstrating how it may be utilized to
calculate the Kohn-Sham potential of atoms and molecules, to study the
exchange-correlation functional and the adiabatic connection by high-precision
many-body methods, and to calculate the exchange-correlation hole and energy
densities of atoms and molecules.


title:
Inverse molecular design from first principles: tailoring organic
  chromophore spectra for optoelectronic applications

abstract:
  The discovery of molecules with tailored optoelectronic properties such as
specific frequency and intensity of absorption or emission is a major challenge
in creating next-generation organic light-emitting diodes (OLEDs) and
photovoltaics. This raises the question: how can we predict a potential
chemical structure from these properties? Approaches that attempt to tackle
this inverse design problem include virtual screening, active machine learning
and genetic algorithms. However, these approaches rely on a molecular database
or many electronic structure calculations, and significant computational
savings could be achieved if there was prior knowledge of (i) whether the
optoelectronic properties of a parent molecule could easily be improved and
(ii) what morphing operations on a parent molecule could improve these
properties. In this perspective we address both of these challenges from first
principles. We firstly adapt the Thomas-Reiche-Kuhn sum rule to organic
chromophores and show how this indicates how easily the absorption and emission
of a molecule can be improved. We then show how by combining electronic
structure theory and intensity borrowing perturbation theory we can predict
whether or not the proposed morphing operations will achieve the desired
spectral alteration, and thereby derive widely-applicable design rules. We go
on to provide proof-of-concept illustrations of this approach to optimizing the
visible absorption of acenes and the emission of radical OLEDs. We believe this
approach can be integrated into genetic algorithms by biasing morphing
operations in favour of those which are likely to be successful, leading to
faster molecular discovery and greener chemistry.


title: Graph and Hodge Laplacians: Similarity and Difference

abstract:
  As key subjects in spectral geometry and spectral graph theory respectively,
the Hodge Laplacian and the graph Laplacian share similarities in their
realization of vector calculus, through the gradient, curl, and divergence, and
by revealing the topological dimension and geometric shape of data. These
similarities are reflected in the popular usage of "Hodge Laplacians on graphs"
in the literature. However, these Laplacians are intrinsically different in
their domains of definitions and applicability to specific data formats,
hindering any in-depth comparison of the two approaches. To bring the graph
Laplacian and Hodge Laplacian on an equal footing for manifolds with boundary,
we introduce Boundary-Induced Graph (BIG) Laplacians using tools from Discrete
Exterior Calculus (DEC). BIG Laplacians are defined on discrete domains with
appropriate boundary conditions to characterize the topology and shape of data.
The similarities and differences of the graph Laplacian, BIG Laplacian, and
Hodge Laplacian are examined. Through an Eulerian representation of 3D domains
as level-set functions on regular grids, we show experimentally the conditions
for the convergence of BIG Laplacian eigenvalues to those of the Hodge
Laplacian for elementary shapes.


title: A note on load balancing in DC microgrids

abstract:
  A problem of load balancing in isolated DC microgrids is considered in this
paper. Here, a DC load is fed by multiple heterogenous DC sources, each of
which is connected to the load via a boost converter. The gains of the DCC's
provide for a means to control the division of load current amongst the DC
sources. The primary objective of the control scheme is to minimise the total
losses in the network, while maintaining the output voltage within a desired
range, serving the load current demand and adhering to VI-characteristics of
the power sources. Under assumptions of
concavity/monotonocity/piece-wise-linearity of the VI-characteristics, the
problem is solved using a convex relaxation. It is shown that the solution to
the relaxed problem is tight. Thus, the resulting algorithm is guaranteed to
reach global optimality in a numerically efficient manner. Simulations are
provided for corroboration.


title: Mathematical multi-scale model of water purification

abstract:
  In this work we consider a mathematical model of the water treatment process
and determine the effective characteristics of this model. At the microscopic
length scale we describe our model in terms of a lattice random walk in a
high-contrast periodic medium with absorption. Applying then the upscaling
procedure we obtain the macroscopic model for total mass evolution. We discuss
both the dynamic and the stationary regimes, and show how the efficiency of the
purification process depends on the characteristics of the macroscopic model.


title:
Development and validation of the numerical model of Electron Cyclotron
  Resonance Ion Sources

abstract:
  Processes of the secondary electron emission (SEE) from the walls are
included into the Numerical Advanced Model of Electron Cyclotron Resonance Ion
Sources (NAM-ECRIS). It is found that SEE strongly influences electron
confinement time and ion production. With the modified model, we observe
reactions of the source to changes in a gas flow into the source and in an
injected microwave power. The source performance with scaling the hexapole
magnetic field is investigated. The calculated tendencies are close to the
experimental observations.


title: Invariant subspaces of idempotents on Hilbert spaces

abstract:
  In the setting of operators on Hilbert spaces, we prove that every
quasinilpotent operator has a non-trivial closed invariant subspace if and only
if every pair of idempotents with a quasinilpotent commutator has a non-trivial
common closed invariant subspace. We also present a geometric characterization
of invariant subspaces of idempotents and classify operators that are
essentially idempotent.


title: Context-Aware Sequence Alignment using 4D Skeletal Augmentation

abstract:
  Temporal alignment of fine-grained human actions in videos is important for
numerous applications in computer vision, robotics, and mixed reality.
State-of-the-art methods directly learn image-based embedding space by
leveraging powerful deep convolutional neural networks. While being
straightforward, their results are far from satisfactory, the aligned videos
exhibit severe temporal discontinuity without additional post-processing steps.
The recent advancements in human body and hand pose estimation in the wild
promise new ways of addressing the task of human action alignment in videos. In
this work, based on off-the-shelf human pose estimators, we propose a novel
context-aware self-supervised learning architecture to align sequences of
actions. We name it CASA. Specifically, CASA employs self-attention and
cross-attention mechanisms to incorporate the spatial and temporal context of
human actions, which can solve the temporal discontinuity problem. Moreover, we
introduce a self-supervised learning scheme that is empowered by novel 4D
augmentation techniques for 3D skeleton representations. We systematically
evaluate the key components of our method. Our experiments on three public
datasets demonstrate CASA significantly improves phase progress and Kendall's
Tau scores over the previous state-of-the-art methods.


title:
Yb$^{3+}$ $f$-$f$ excitations in NaYbSe$_2$: benchmarking
  embedded-cluster quantum chemical schemes for 4$f$ insulators

abstract:
  $\tilde{S}\!=\!1/2$ triangular-lattice $f$-electron materials define a
dynamic research area in condensed matter magnetism. In various Yb 4$f^{13}$
triangular-lattice compounds, for example, spin-liquid ground states seem to be
realized. Using {\it ab initio} quantum chemical methods, we here investigate
how correlation effects involving the 4$f$ electrons affect the on-site $f$-$f$
excitation spectrum in NaYbSe$_2$. The system is well suited for such a study
since unambiguous inelastic neutron scattering data are available for the
Yb$^{3+}$ $f$-$f$ transitions. The excitation energies obtained by
configuration-interaction calculations with single and double substitutions
agree within 3-4 meV with experimental values, which provides a not so
expensive alternative to fitting experimental data at the model-Hamiltonian
level in order to analyze $f$-center multiplet structures.


title: Flow-Adapter Architecture for Unsupervised Machine Translation

abstract:
  In this work, we propose a flow-adapter architecture for unsupervised NMT. It
leverages normalizing flows to explicitly model the distributions of
sentence-level latent representations, which are subsequently used in
conjunction with the attention mechanism for the translation task. The primary
novelties of our model are: (a) capturing language-specific sentence
representations separately for each language using normalizing flows and (b)
using a simple transformation of these latent representations for translating
from one language to another. This architecture allows for unsupervised
training of each language independently. While there is prior work on latent
variables for supervised MT, to the best of our knowledge, this is the first
work that uses latent variables and normalizing flows for unsupervised MT. We
obtain competitive results on several unsupervised MT benchmarks.


title:
IRFEL Selective Irradiation of Amorphous Solid Water: from Dangling to
  Bulk Modes

abstract:
  Amorphous solid water (ASW) is one of the most widely studied solid phase
systems. A better understanding of the nature of inter- and intramolecular
forces in ASW is, however, still required to correctly interpret the catalytic
role of ASW in the formation and preservation of molecular species in
environments such as the icy surfaces of Solar System objects, on interstellar
icy dust grains and potentially even in the upper layers of the Earth's
atmosphere. In this work, we have systematically exposed porous ASW (pASW) to
mid-infrared radiation generated by a free-electron laser at the HFML-FELIX
facility in the Netherlands to study the effect of vibrational energy injection
into the surface and bulk modes of pASW. During multiple sequential
irradiations on the same ice spot, we observed selective effects both at the
surface and in the bulk of the ice. Although the density of states in pASW
should allow for a fast vibrational relaxation through the H-bonded network,
part of the injected energy is converted into structural ice changes as
illustrated by the observation of spectral modifications when performing
Fourier transform infrared spectroscopy in reflection-absorption mode. Future
studies will include the quantification of such effects by systematically
investigating ice thickness, ice morphology, and ice composition.


title:
Open or not open: Are conventional radio access networks more secure and
  trustworthy than Open-RAN?

abstract:
  The Open RAN architecture is a promising and future-oriented architecture. It
is intended to open up the radio access network (RAN) and enable more
innovation and competition in the market. This will lead to RANs for current 5G
networks, but especially for future 6G networks, evolving from the current
highly integrated, vendor-specific RAN architecture towards disaggregated
architectures with open interfaces that will enable to better tailor RAN
solutions to the requirements of 5G and 6G applications. However, the
introduction of such an open architecture substantially broadens the attack
possibilities when compared to conventional RANs. In the past, this has often
led to negative headlines that in summary have associated Open RAN with faulty
or inadequate security. In this paper, we analyze what components are involved
in an Open RAN deployment, how to assess the current state of security, and
what measures need to be taken to ensure secure operation.


title:
Measurement of $CP$ asymmetries in $D^+_{(s)}\rightarrow \eta \pi^+$ and
  $D^+_{(s)}\rightarrow \eta^{\prime} \pi^+$ decays

abstract:
  Searches for $CP$ violation in the decays $D^+_{(s)}\rightarrow \eta \pi^+$
and $D^+_{(s)}\rightarrow \eta^{\prime} \pi^+$ are performed using $pp$
collision data corresponding to 6 fb$^{-1}$ of integrated luminosity collected
by the LHCb experiment. The calibration channels $D^+_{(s)}\rightarrow \phi
\pi^+$ are used to remove production and detection asymmetries. The resulting
$CP$-violating asymmetries are
  $A^{CP}(D^+ \rightarrow \eta \pi^+) = (0.34 \pm 0.66 \pm 0.16 \pm 0.05)\%$,
  $A^{CP}(D^+_s \rightarrow \eta \pi^+) = (0.32 \pm 0.51 \pm 0.12)\%$,
  $A^{CP}(D^+ \rightarrow \eta^{\prime} \pi^+) = (0.49 \pm 0.18 \pm 0.06 \pm
0.05)\%$,
  $A^{CP}(D^+_s \rightarrow \eta^{\prime} \pi^+) = (0.01 \pm 0.12 \pm 0.08)\%$,
where the first uncertainty is statistical, the second is systematic and the
third, relevant for the $D^+$ channels, is due to the uncertainty on
$A^{CP}(D^+ \to \phi \pi^+)$. These measurements, currently the most precise
for three of the four channels considered, are consistent with the absence of
$CP$ violation. A combination of these results with previous LHCb measurements
is presented.


title:
Light-induced topological superconductivity in transition metal
  dichalcogenide monolayers

abstract:
  Monolayer transition metal dichalcogenides (TMDs) host deeply bound excitons
interacting with itinerant electrons, and as such they represent an exciting
new quantum many-body Bose-Fermi mixture. Here, we demonstrate that electrons
interacting with a Bose-Einstein condensate (BEC) of exciton-polaritons can
realise a two-dimensional topological $p_x+ip_y$ superconductor. Using strong
coupling Eliashberg theory, we show that this is caused by an attractive
interaction mediated by the BEC, which overcompensates the repulsive Coulomb
interaction between the electrons. The hybrid light-matter nature of the BEC is
crucial for achieving this, since it can be tuned to reduce retardation effects
and increase the mediated interaction in regimes important for pairing. We
finally calculate the critical temperature and discuss how the great
flexibility of TMDs can be used to observe the elusive topological
superconducting phase.


title: User Trust on an Explainable AI-based Medical Diagnosis Support System

abstract:
  Recent research has supported that system explainability improves user trust
and willingness to use medical AI for diagnostic support. In this paper, we use
chest disease diagnosis based on X-Ray images as a case study to investigate
user trust and reliance. Building off explainability, we propose a support
system where users (radiologists) can view causal explanations for final
decisions. After observing these causal explanations, users provided their
opinions of the model predictions and could correct explanations if they did
not agree. We measured user trust as the agreement between the model's and the
radiologist's diagnosis as well as the radiologists' feedback on the model
explanations. Additionally, they reported their trust in the system. We tested
our model on the CXR-Eye dataset and it achieved an overall accuracy of 74.1%.
However, the experts in our user study agreed with the model for only 46.4% of
the cases, indicating the necessity of improving the trust. The self-reported
trust score was 3.2 on a scale of 1.0 to 5.0, showing that the users tended to
trust the model but the trust still needs to be enhanced.


title: IRC-safe Graph Autoencoder for an unsupervised anomaly detection

abstract:
  Anomaly detection through employing machine learning techniques has emerged
as a novel powerful tool in the search for new physics beyond the Standard
Model. Historically similar to the development of jet observables, theoretical
consistency has not always assumed a central role in the fast development of
algorithms and neural network architectures. In this work, we construct an
infrared and collinear safe autoencoder based on graph neural networks by
employing energy-weighted message passing. We demonstrate that whilst this
approach has theoretically favourable properties, it also exhibits formidable
sensitivity to non-QCD structures.


title:
Fully non-linear parabolic equations on compact manifolds with a flat
  hyperk\"ahler metric

abstract:
  Our recent work about fully non-linear elliptic equations on compact
manifolds with a flat hyperk\"ahler metric is hereby extended to the parabolic
setting. This approach will help us to study some problems arising from
hyperhermitian geometry.


title: Elliptic Hypertoric Varieties

abstract:
  We introduce elliptic hypertoric varieties, which is an elliptic analogue of
hypertoric varieties and multiplicative hypertoric varieties. We also prove an
elliptic version of Hikita conjecture, which relates elliptic (resp. additive
and mulitplicative) hypertoric varieties to the equivariant elliptic cohomology
(resp. ordinary cohomology and K-theory) of their 3d mirror hypertoric
varieties.


title: {\Sigma}-dual Rickart modules

abstract:
  In this paper, we dualize the concept of {\Sigma}-Rickart modules as
{\Sigma}-dual Rickart modules. An R-module M is said to be {\Sigma}-dual
Rickart if the direct sum of arbitrary copies of M is dual Rickart. We prove
that each cohereditary module over the Noetherian ring is a {\Sigma}-dual
Rickart. We introduce the notion of strongly cogenerated modules and
characterize {\Sigma}-dual Rickart modules in terms of strongly cogenerated
modules. We also study some properties of {\Sigma}- dual Rickart modules and
find connections with semisimple Artinian ring, regular ring semi-hereditary
ring and FP-injective module. Further, we study the endomorphism ring of
{\Sigma}-dual Rickart modules


title: Charge asymmetry in $e^+e^-\to \pi^+\pi^-$ process

abstract:
  We consider the charge asymmetry in the differential cross section of the
process $e^+e^- \rightarrow \pi^+\pi^-$. Experimental data show large
deviations from the results of the available theoretical calculations.
Motivated by this fact, we revisit the contribution of the two photon exchange
diagrams and find the origin of discrepancy in an oversimplified account of the
pion internal structure in the theoretical calculations. We present a natural
and simple approach that accounts for the pion structure in a more consistent
way and find remarkable agreement with the experimental data.


title:
Characteristic function of pencils. Model representations of a quadratic
  operator pencil

abstract:
  Notion of an open system of second order is introduced. Characteristic
function for such an open system is obtained. Model representations of a
quadratic non-self-adjoint operator pencil are found.


title:
Intercategorical Label Interpolation for Emotional Face Generation with
  Conditional Generative Adversarial Networks

abstract:
  Generative adversarial networks offer the possibility to generate deceptively
real images that are almost indistinguishable from actual photographs. Such
systems however rely on the presence of large datasets to realistically
replicate the corresponding domain. This is especially a problem if not only
random new images are to be generated, but specific (continuous) features are
to be co-modeled. A particularly important use case in \emph{Human-Computer
Interaction} (HCI) research is the generation of emotional images of human
faces, which can be used for various use cases, such as the automatic
generation of avatars. The problem hereby lies in the availability of training
data. Most suitable datasets for this task rely on categorical emotion models
and therefore feature only discrete annotation labels. This greatly hinders the
learning and modeling of smooth transitions between displayed affective states.
To overcome this challenge, we explore the potential of label interpolation to
enhance networks trained on categorical datasets with the ability to generate
images conditioned on continuous features.


title:
Environment Viewed from the Particle and Slowdown Estimates for
  Ballistic RWRE on $\mathbb{Z}^2$ and $\mathbb{Z}^3$

abstract:
  We consider a random walk in a random environment on $\mathbb{Z}^d$ under
Sznitman's ballisticity condition $(T)$. Using techniques from arXiv:1405.6819,
we show the existence of the invariant measure $Q$ with respect to the
environment viewed from the particle for $d=2$ and $d=3$. This disproves a
conjecture made in arXiv:1405.6819 that the invariant measure does not exist in
dimension $2$. As a corollary, we prove sharp tail bounds for regeneration
times for $d=3$. Finally, we also provide tail estimates for the Radon-Nikodym
derivative $dQ/dP$, where $P$ is the original distribution on the environment.


title: Penrose inequality in asymptotically anti-de Sitter spacetime

abstract:
  Considering static asymptotically Schwarzschild-AdS black holes, we
conjecture that the null energy condition can guarantee the Penrose inequality
when the cross-section of horizon has planar or spherical topology, but the
weak energy condition can even guarantee the inequality for hyperbolic
topology. We prove this conjecture under planar/spherically/hyperbolically
symmetric cases. We also propose two candidates of generalized Penrose
inequality in charged cases. If black holes are asymptotically AdS but not
asymptotically Schwarzschild-AdS, the total mass is defined according to
holographic renormalization and may not be determined completely by bulk
geometry. We construct an asymptotically AdS black hole coupled to a scalar
field to check the Penrose inequality in such case. It is found that whether
the Penrose inequality holds or not will depend on what kind of quantization
scheme we employ.


title:
Resolution of d'Alembert's paradox using slip boundary conditions: The
  effect of the friction parameter on the drag coefficient

abstract:
  d'Alembert's paradox is the contradictory observation that for incompressible
and inviscid (potential) fluid flow, there is no drag force experienced by a
body moving with constant velocity relative to the fluid. This paradox can be
straightforwardly resolved by considering Navier's slip boundary condition.
Potential flow around a cylinder then solves the Navier--Stokes equations using
friction parameter $\beta=-2\nu$. This negative friction parameter can be
interpreted physically as the fluid being accelerated by the cylinder wall.
This explains the lack of drag.
  In this paper, we introduce the Navier slip boundary condition and show that
choosing the friction parameter positive resolves d'Alembert's paradox. We then
further examine the effect of the friction parameter $\beta$ on the drag
coefficient. In particular, we show that for large $\beta$ the drag coefficient
corresponds well with experimental values. Moreover, we provide numerical
evidence that the Newton continuation method (moving from small to large
Reynold's numbers) requires fewer iterations to succeed. Thus the slip boundary
condition is advantageous also from a computational perspective.


title:
Charge gradients around dendritic voids cause nanoscale inhomogeneities
  in liquid water

abstract:
  Water is the matrix of life and is generally considered a homogeneous,
uniform, liquid. Recent experiments report that water is instead a two-state
liquid. However, subsequently, these findings were contested. The structure of
water and whether we should think of it as uniform therefore remains an open
question. Here, we report femtosecond elastic second harmonic scattering
(fs-ESHS) of liquid water in comparison to an isotropic liquid (CCl4) and show
that water is indeed a non-uniform liquid, The coherent fs-ESHS intensity was
interpreted, using molecular dynamics simulations, as arising from charge
density fluctuations and consequentially enhanced nanoscale polarizabilities
around transient voids having an average lifetime of 300 fs. Although voids
were also present in CCl4, they were not characterized by hydrogen bond defects
and did not show strong polarizability fluctuations, leading to fs-ESHS of an
isotropic liquid. The voids increased in number at higher temperatures above
room temperature, in agreement with the fs-ESHS results. The measured
nanoscale-femtosecond inhomogeneities therefore do not necessarily relate to
the proposed two state model of water, but instead underscore the elusive
nature of liquid water, and undoubtedly have an impact on any type of
transition that occurs in liquid water.


title:
Multiwavelength and Multimessenger Observations of Blazars and
  Theoretical Modeling: Blazars as Astrophysical Neutrino Sources

abstract:
  This contribution reviews recent advances in the possible identification of
blazars as potential sources of at least some of the very-high-energy neutrinos
detected by the IceCube neutrino detector at the South Pole. The basic physical
requirements for neutrino production and physics constraints that may be drawn
from neutrino - blazar associations are reviewed. Several individual cases of
possible associations will be discussed in more detail. It is emphasized that
due to $\gamma\gamma$ opacity constraints in efficiently neutrino-producing
blazars, an association between X-ray -- soft $\gamma$-ray activity and
very-high-energy neutrino production is more naturally expected than a
connection between neutrino and high-energy/very-high-energy $\gamma$-ray
activity.


title:
Modeling and Analysis of 2-Tier Heterogeneous Vehicular Networks
  Leveraging Roadside Units and Vehicle Relays

abstract:
  While roadside units (RSUs) play an essential role in vehicle-to-everything
(V2X) by communicating with users, some users in congestion areas may not be
well-served due to data traffic, signal attenuation, and interference. In these
cases, vehicle relays can be employed to enhance the network topology to better
serve those users. This paper leverages stochastic geometry to propose a novel
framework for the performance analysis of heterogeneous vehicular networks with
RSUs, vehicle relays, and vehicle users. We present a two-dimensional
analytical model where the spatial dependence between RSUs, vehicle relays,
vehicle users, and roads is accurately taken into account through a Cox point
process structure. Assuming relays are backhauled to RSUs over a reserved
wireless resource and users are associated with the closest RSU or relay, we
derive the probability that the typical user is associated with either an RSU
or a relay. Then, we derive the signal-to-interference ratio (SIR) coverage
probability of the typical user. Finally, using the derived formulas, we
evaluate the average effective rate of the typical user in the network. This
allows us to determine the gain of the average effective rate of users that
results from the deployment of relays in the network.


title: Hybridised Loss Functions for Improved Neural Network Generalisation

abstract:
  Loss functions play an important role in the training of artificial neural
networks (ANNs), and can affect the generalisation ability of the ANN model,
among other properties. Specifically, it has been shown that the cross entropy
and sum squared error loss functions result in different training dynamics, and
exhibit different properties that are complementary to one another. It has
previously been suggested that a hybrid of the entropy and sum squared error
loss functions could combine the advantages of the two functions, while
limiting their disadvantages. The effectiveness of such hybrid loss functions
is investigated in this study. It is shown that hybridisation of the two loss
functions improves the generalisation ability of the ANNs on all problems
considered. The hybrid loss function that starts training with the sum squared
error loss function and later switches to the cross entropy error loss function
is shown to either perform the best on average, or to not be significantly
different than the best loss function tested for all problems considered. This
study shows that the minima discovered by the sum squared error loss function
can be further exploited by switching to cross entropy error loss function. It
can thus be concluded that hybridisation of the two loss functions could lead
to better performance in ANNs.


title: Towards high photon density for Compton Scattering by spectral chirp

abstract:
  Scattering of intense laser pulses on high-energy electron beams allows one
to produce a large number of X and gamma rays. For temporally pulsed lasers the
resulting spectra is broadband which severely limits practical applications.
One could use linearly chirped laser pulses to compensate that broadening. We
show for laser pulses chirped in the spectral domain that there is the optimal
chirp parameter at which the spectra has the brightest peak. Additionally, we
use catastrophe theory to analytically find this optimal chirp value.


title:
Large time behaviour in nonlocal reaction-diffusion equations of the
  Fisher-KPP type

abstract:
  The basic question is the evolution of the solutions to equations of the
Fisher-KPP type, in which the diffusion is given by an integral operator. The
level sets will organize themselves into an invasion front that is
asymptotically linear in time, corrected by a logarithmic term.
  For a special class of nonlinearities, this fact can be deduced from the
study of an underlying branching random walk (A\"idekon, 2013). This extends a
famous result by Bramson (1983), where the diffusion is given by the Laplacian,
and the underlying random walk is the Branching Brownian Motion.
  Motivated by models arising from epidemiology and ecology, that go beyond the
equations arising from the branching random walks, this work explains how this
logarithmic correction can be derived by working directly on the
integro-differential equation.


title: Symmetric skew braces and brace systems

abstract:
  For a skew left brace $(G, \cdot, \circ)$, the map $\lambda : (G, \circ) \to
\Aut \,(G, \cdot),~~a \mapsto \lambda_a,$ where $\lambda_a(b) = a^{-1} \cdot (a
\circ b)$ for all $a, b \in G$, is a group homomorphism. Then $\lambda$ can
also be viewed as a map from $(G, \cdot)$ to $\Aut \, (G, \cdot)$, which, in
general, may not be a homomorphism. A skew left brace will be called
$\lambda$-anti-homomorphic ($\lambda$-homomorphic) if $\lambda : (G, \cdot) \to
\Aut \, (G, \cdot)$ is an anti-homomorphism (a homomorphism). We mainly study
such skew left braces. We device a method for constructing a class of binary
operations on a given set so that the set with any two such operations
constitute a $\lambda$-homomorphic symmetric skew brace. Most of the
constructions of symmetric skew braces dealt with in the literature fall in the
framework of our construction. We then carry out various such constructions on
specific infinite sets.


title:
Frustrated Antiferromagnetic Triangular Lattice with
  Dzyaloshinskii-Moriya Interaction: Ground States, Spin Waves, Skyrmion
  Crystal, Phase Transition

abstract:
  We study in this article a triangular lattice with Heisenberg spins
interacting with each other via an antiferromagnetic exchange interaction $J$
and a Dzyaloshinskii-Moriya (DM) interaction $D$, between nearest-neighbors
(NN). We consider two cases: the first case in which the DM vector $\mathbf D$
is perpendicular to the lattice plane and the second case where it lies in the
plane. A magnetic field $H$ is applied perpendicular to the spin plane in both
cases. The ground state (GS) of this system is calculated by minimizing the
energy using the very fast steepest-descent method in the two cases. In the
case of perpendicular $\mathbf D$ with $H=0$, the GS is periodic. We
analytically determine the GS configuration which is characterized by two
well-defined angles. We calculate the spin-wave spectrum in this case which
shows that for small wave vectors the spin waves are forbidden in the system.
When $H\neq 0$, the GS in the perpendicular $\mathbf D$ case shows no
skyrmions. However, in the case of in-plane $\mathbf D$ with $H\neq 0$, we find
a crystal of skyrmions at $T=0$ composed of three interpenetrating skyrmion
sublattice crystals, in agreement with low-$T$ spin textures found in earlier
works. We show by Monte Carlo simulations that this skyrmion crystal is stable
at finite temperatures below a critical temperature.


title: The proper Landau-Ginzburg potential is the open mirror map

abstract:
  The mirror dual of a smooth toric Fano surface $X$ equipped with an
anticanonical divisor $E$ is a Landau-Ginzburg model with superpotential, W.
Carl-Pumperla-Siebert give a definition of the the superpotential in terms of
tropical disks using a toric degeneration of the pair $(X,E)$. When $E$ is
smooth, the superpotential is proper. We show that this proper superpotential
equals the open mirror map for outer Aganagic-Vafa branes in the canonical
bundle $K_X$, in framing zero. As a consequence, the proper Landau-Ginzburg
potential is a solution to the Lerche-Mayr Picard-Fuchs equation.
  Along the way, we prove a generalization of a result about relative
Gromov-Witten invariants by Cadman-Chen to arbitrary genus using the
multiplication rule of quantum theta functions. In addition, we generalize a
theorem of Hu that relates Gromov-Witten invariants of a surface under a
blow-up from the absolute to the relative case. One of the two proofs that we
give introduces birational modifications of a scattering diagram. We also
demonstrate how the Hori-Vafa superpotential is related to the proper
superpotential by mutations from a toric chamber to the unbounded chamber of
the scattering diagram.


title: Martingale Schr\"odinger Bridges and Optimal Semistatic Portfolios

abstract:
  In a two-period financial market where a stock is traded dynamically and
European options at maturity are traded statically, we study the so-called
martingale Schr\"odinger bridge Q*; that is, the minimal-entropy martingale
measure among all models calibrated to option prices. This minimization is
shown to be in duality with an exponential utility maximization over semistatic
portfolios. Under a technical condition on the physical measure P, we show that
an optimal portfolio exists and provides an explicit solution for Q*. This
result overcomes the remarkable issue of non-closedness of semistatic
strategies discovered by Acciaio, Larsson and Schachermayer. Specifically, we
exhibit a dense subset of calibrated martingale measures with particular
properties to show that the portfolio in question has a well-defined and
integrable option position.


title: Limits of Semistatic Trading Strategies

abstract:
  We show that pointwise limits of semistatic trading strategies in discrete
time are again semistatic strategies. The analysis is carried out in full
generality for a two-period model, and under a probabilistic condition for
multi-period, multi-stock models. Our result contrasts with a counterexample of
Acciaio, Larsson and Schachermayer, and shows that their observation is due to
a failure of integrability rather than instability of the semistatic form.
Mathematically, our results relate to the decomposability of functions as
studied in the context of Schr\"odinger bridges.


title:
Evidence of Ferromagnetic Clusters and Griffiths Singularity in Magnetic
  Weyl Semimetal Co$ _{3} $Sn$ _{2} $S$ _{2} $

abstract:
  Cobalt based sulphides of compositional formula Co$ _{3} $A$ _{2} $S$ _{2} $
(A = Sn and In) are endowed with frustrated kagome lattice structure and a
plethora of novel phenomena determined from the topological band structure.
Here-in, we report on the detailed exploration of anisotropic magnetic
properties of single crystals of ferromagnetic compound Co$ _{3} $Sn$ _{2} $S$
_{2} $ under magnetic field $H$ applied along the c-axis $(H\parallel c)$ and
the ab-plane $(H\parallel ab)$. A low temperature clustered-glassy magnetic
behaviour is revealed in field-cooled and zero field-cooled magnetization and
memory effect measurement protocols. The sharp downturn and non-linearity
observed in the inverse susceptibility above the critical temperature $T
_{\text{C}} $ in the paramagnetic region corroborates to the presence of
short-range ferromagnetic clusters above $ T _{\text{C}} $ in Co$ _{3} $Sn$
_{2} $S$ _{2} $. The deviation from linear Curie-Weiss behaviour in the
paramagnetic state signifies the strong Griffiths singularity in the material.
The slow spin dynamics behaviour and zero spontaneous magnetization above $ T
_{\text{C}} $ give an evidence of Griffiths phase owing to the ferromagnetic
clusters. The Arrott plots derived from magnetization reveal convex type
curvature at low fields and linear positive behavior in the high field region,
confirming the second order magnetic phase transition in Co$ _{3} $Sn$ _{2} $S$
_{2} $. The Takahashi spin fluctuation theory analysis provides sufficient
evidence for itinerant ferromagnetism in Co$ _{3} $Sn$ _{2} $S$ _{2} $. A large
magneto-crystalline anisotropy concomitant with a high anisotropy field
suggests the dominance of strong spin orbit coupling phenomenon. Our
experimental results emphasize an intuitive understanding of the complex nature
of magnetism present in Co-based shandite systems.

categories: cond-mat.str-el cond-mat.mtrl-sci cond-mat.other cond-mat.stat-mech cond-mat.supr-con


title:
The Pseudo-Reachability Problem for Diagonalisable Linear Dynamical
  Systems

abstract:
  We study fundamental reachability problems on pseudo-orbits of linear
dynamical systems. Pseudo-orbits can be viewed as a model of computation with
limited precision and pseudo-reachability can be thought of as a robust version
of classical reachability. Using an approach based on $o$-minimality of
$\reals_{\exp}$ we prove decidability of the discrete-time pseudo-reachability
problem with arbitrary semialgebraic targets for diagonalisable linear
dynamical systems. We also show that our method can be used to reduce the
continuous-time pseudo-reachability problem to the (classical) time-bounded
reachability problem, which is known to be conditionally decidable.


title: Stopped Brownian-increment tamed Euler method

abstract:
  In this article we propose a new explicit Euler-type approximation method for
stochastic differential equations (SDEs). In this method, Brownian increments
in the recursion of the Euler method are replaced by suitable bounded functions
of the Brownian increments. We prove strong convergence rate one-half for a
large class of SDEs with polynomial coefficient functions whose local
monotonicity constant grows at most like the logarithm of a Lyapunov-type
function.


title:
Using Koopmans' theorem for constructing basis sets: Approaching high
  Rydberg excited states of lithium with a compact Gaussian basis

abstract:
  A contracted Gaussian basis set has been designed for modeling Rydberg
excited states of the lithium atom. The optimization of the diffuse basis
necessary for the Rydberg electron description was driven by the Koopmans'
theorem and used the even tempered Gaussian (ETG) functions. The electronic
correlation was sufficiently covered by the aug-ano-pVQZ basis that was
carefully merged with the optimal contracted diffuse orbitals. At the EOM-CCSD
level of theory and using only compact subsets of the resulting basis that were
specifically selected for states of the given angular momentum, many more
excited states could be reached than with superior and expensive approaches
such as the method of the explicitly correlated Gaussians (ECG), while
differing from the ECG excitation energies mostly only by several meV. Namely,
the states up to 24S, 25P, 14D, 16F and 16G were obtained, some of which were
even surpassing the accuracy of the Full-CI employing optimal Slater functions
by an order of magnitude.


title:
The muon anomalous magnetic moment with staggered fermions: is the
  lattice spacing small enough?

abstract:
  We extend our previous work on the light-quark connected part, $a_\mu^{\rm
HVP,lqc}$, of the leading order hadronic-vacuum-polarization (HVP) contribution
to the muon anomalous magnetic moment $a_\mu$, using staggered fermions, in
several directions. We have collected more statistics on ensembles with lattice
spacings of $0.06$, $0.09$ and $0.12$ fm, and we added two new ensembles, both
with lattice spacing $0.15$ fm, but with different volumes. The increased
statistics allow us to reduce statistical errors on $a_\mu^{\rm HVP,lqc}$ and
related window quantities significantly. We also calculate the current-current
correlator from which $a_\mu^{\rm HVP,lqc}$ is obtained to
next-to-next-to-leading order (NNLO) in staggered chiral perturbation theory,
so that we can correct lattice values for $a_\mu^{\rm HVP,lqc}$ to NNLO for
finite-volume, pion-mass mistuning and taste-breaking effects. We discuss the
applicability of NNLO chiral perturbation theory to $a_\mu^{\rm HVP,lqc}$ and
to the window quantities, emphasizing that it provides a systematic EFT
approach to $a_\mu^{\rm HVP,lqc}$, but not to short- or intermediate-distance
window quantities. This makes it difficult to assess systematic errors on the
standard intermediate-distance window quantity that is now widely considered in
the literature. In view of this, we investigate a longer-distance window, for
which EFT methods should be more reliable. Our most important conclusion is
that, especially for staggered fermions, new high-statistics computations at
lattice spacings smaller than $0.06$ fm are indispensable.


title: Theta functions, broken lines and 2-marked log Gromov-Witten invariants

abstract:
  Theta functions were defined for varieties with effective anticanonical
divisor and are related to certain punctured Gromov-Witten invariants. In this
paper we show that in the case of a log Calabi-Yau surface (X,D) with smooth
very ample anticanonical divisor we can circumvent the notion of punctured
Gromov-Witten invariants and relate theta functions and their multiplicative
structure to certain 2-marked log Gromov-Witten invariants. This is a natural
extension of the correspondence between wall functions and 1-marked log
Gromov-Witten invariants.


title: About Metallicity Variations in the Local Galactic Interstellar Medium

abstract:
  In this paper we discuss and confront recent results on metallicity
variations in the local interstellar medium, obtained from observations of HII
regions and neutral clouds of the Galactic thin disk, and compare them with
recent high-quality metallicity determinations of other tracers of the chemical
composition of the interstellar medium as B-type stars, classical Cepheids and
young clusters. We find that the metallicity variations obtained for these last
kinds of objects are consistent with each other and with that obtained for HII
regions but significantly smaller than those obtained for neutral clouds. We
also discuss the presence of a large population of low-metallicity clouds as
the possible origin for large metallicity variations in the local Galactic thin
disk. We find that such hypothesis does not seem compatible with: (a) what is
predicted by theoretical studies of gas mixing in galactic disks, and (b) the
models and observations on the metallicity of high-velocity clouds and its
evolution as they mix with the surrounding medium in their fall onto the
Galactic plane. We conclude that that most of the evidence favors that the
chemical composition of the interstellar medium in the solar neighborhood is
highly homogeneous.


title: On the Jones polynomial modulo primes

abstract:
  We derive an upper bound on the density of Jones polynomials of knots modulo
a prime number $p$, within a sufficiently large degree range: $4/p^7$. As an
application, we classify knot Jones polynomials modulo two of span up to eight.