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This paper explores cooperative trajectory planning approaches within the context of human-machine shared control. In shared control research, it is typically assumed that the human and the automation use the same reference trajectory to stabilize the coupled system. However, this assumption is often incorrect, as they usually follow different trajectories, causing control conflicts at the action level that have not been widely researched. To address this, it is logical to extend shared control concepts to include human-machine interaction at the trajectory-level before action execution, resulting in a unified reference trajectory for both human and automation. This paper begins with a literature overview on approaches of cooperative trajectory planning. It then presents an approach of finding a joint trajectory by modelling cooperative trajectory planning as an agreement process. A generally valid system structure is proposed for this purpose. Finally, it proposes concepts to implement cooperative trajectory planning as an agreement process.

We experimentally studied the formation of CH(A) radicals in butane seeded plasma generated with chirp-controlled ultrashort laser pulses (\(\sim 760 \, \mu \text{J}/\text{pulse}\), 890 nm, 1 kHz, 8 fs). The focused beam with high peak intensity (\(\sim 10^{14} - 10^{16} \, \text{W/cm}^2\)) caused Coulomb explosion (CE). The time dependent emission spectra were observed with the Fourier-transform Visible spectroscopy (FTVis) step-scan method. The average signal intensity decreased with the chirp in the Ar\(^+\) > C\(_2\) > H-\(\alpha\) \(\sim\) CH(A) order with a plateau for CH(A) in the \(-200\) to \(-100 \, \text{fs}^2\) range. The short rise time of the CH(A) emission signal, the monoexponential emission decay, and the nearly constant rotational and vibrational temperatures of the CH(A) radicals (\(\sim 3000 \, \text{K}\) and \(\sim 3800 \, \text{K}\)) all support their formation as a primary product. Our TDDFT calculations predict that CH and many other fragments can be formed beyond CE at \(\sim 7 \times 10^{14} \, \text{W/cm}^2\) intensity. The average charge of CH (+0.6) and its relative abundance (0.5\%) support the formation of detectable CH(A) within 120 fs.

Fragmentation dynamics in the Coulomb explosion of hydrocarbons, specifically methane, ethane, propane, and butane, are investigated using time dependent density functional theory (TDDFT) simulations. The goal of this work is to elucidate the distribution of fragments generated under laser-driven Coulomb explosion conditions. Detailed analysis reveals the types of fragments formed, their respective charge states, and the optimal laser intensities required for achieving various fragmentations. Our results indicate distinct fragmentation patterns for each hydrocarbon, correlating with the molecular structure and ionization potential. Additionally, we identify the laser parameters that maximize fragmentation efficiency, providing valuable insights for experimental setups. This research advances our understanding of Coulomb explosion mechanisms and offers a foundation for further studies in controlled molecular fragmentation.

Gaia Data Release 3 (DR3) has provided the largest and most astrometrically precise catalogue of nearby stars to date, allowing for a more complete membership census of nearby, young stellar moving groups. These loose associations of young (age $<$100 Myr) stars within $\sim$100 pc are vital laboratories for the study of the early evolution of low-mass stars and planetary systems. We have exploited DR3 data to examine the boundary region between two of the youngest nearby moving groups, the $\sim$3--8 Myr-old $\epsilon$ Cha Association (ECA) and an $\sim$8 Myr-old sub-population of the sprawling Lower Centaurus Crux (LCC) young star complex. Using spatio-kinematic and color-magnitude criteria designed to select stars in the ECA, we identify $\sim$54 new young-star candidates that extend from the ECA core to the southern edge of the LCC. Included among our new candidates are six previously unidentified ultra-low-mass, mid- to late-M stars, lying near the future hydrogen-burning limit, that display significant infrared excesses. Our spatial, kinematic, and CMD analysis of these new candidates and previously established LCC and ECA members blurs the boundary between these groups and provides evidence for a wave of continuous star formation extending from north (LCC) to south (ECA). We discuss the factors which studies of nearby young moving groups must consider when constraining the ages of stars in these groups., Comment: Accepted by AJ

We propose a method to measure the similarity of papers and authors by simulating a literature search procedure on citation networks, which is an information retrieval inspired conceptualization of similarity. This transition probability (TP) based approach does not require a curated classification system, avoids clustering complications, and provides a continuous measure of similarity. We perform testing scenarios to explore several versions of the general TP concept and the Node2vec machine-learning technique. We found that TP measures outperform Node2vec in mapping the macroscopic structure of fields. The paper provides a general discussion of how to implement TP similarity measurement, with a particular focus on how to utilize publication-level information to approximate the research interest similarity of individual scientists. This paper is accompanied by a Python package capable of calculating all the tested metrics.

Suppose in a stable urban traffic system populated only by human driven vehicles (HDVs), a given proportion (e.g. 10%) is replaced by a fleet of Connected and Autonomous Vehicles (CAVs), which share information and pursue a collective goal. Suppose these vehicles are centrally coordinated and differ from HDVs only by their collective capacities allowing them to make more efficient routing decisions before the travel on a given day begins. Suppose there is a choice between two routes and every day each driver makes a decision which route to take. Human drivers maximize their utility. CAVs might optimize different goals, such as the total travel time of the fleet. We show that in this plausible futuristic setting, the strategy CAVs are allowed to adopt may result in human drivers either benefitting or being systematically disadvantaged and urban networks becoming more or less optimal. Consequently, some regulatory measures might become indispensable.

We study equilibrium states and phases of a quasi-one-dimensional system of hard superdisks (anisotropic particles interpolating between disks and squares) where the centers of the particles are constrained to move on a line. A continuous change from a quasi-isotropic to a tetratic phase is found upon increasing the density. Somewhat unexpected, for isobaric states, systems with larger and more anisotropic particles in the tetratic phase are denser than systems with smaller and less anisotropic particles in a quasi-isotropic phase. Close packing behaviour is characterised by exponents describing the behaviour of the pressure, the angular fluctuations and the angular correlation length. We obtain two universal, shape-independent relations between them., Comment: Submission to SciPost

Assume two finite families $\mathcal A$ and $\mathcal B$ of convex sets in $\mathbb{R}^3$ have the property that $A\cap B\ne \emptyset$ for every $A \in \mathcal A$ and $B\in \mathcal B$. Is there a constant $\gamma >0$ (independent of $\mathcal A$ and $\mathcal B$) such that there is a line intersecting $\gamma|\mathcal A|$ sets in $\mathcal A$ or $\gamma|\mathcal B|$ sets in $\mathcal B$? This is an intriguing Helly-type question from a paper by Mart\'{i}nez, Roldan and Rubin. We confirm this in the special case when all sets in $\mathcal A$ lie in parallel planes and all sets in $\mathcal B$ lie in parallel planes; in fact, all sets from one of the two families has a line transversal.

By considering linear scattering of cold atoms inside an undriven high-finesse optical resonator, we experimentally demonstrate effects unique to a strongly coupled vacuum field. Arranging the atoms in an incommensurate lattice, with respect to the resonator mode, the scattering can be suppressed by destructive interference: resulting in a subradiant atomic array. We show however, that strong coupling leads to a drastic modification of the excitation spectrum, as evidenced by well-resolved vacuum Rabi splitting in the intensity of the fluctuations. Furthermore, we demonstrate a significant polarization rotation in the linear scattering off the subradiant array via Raman scattering induced by the strongly coupled vacuum field.

Recent results from ALICE and CMS show a low-transverse-momentum enhancement of charm baryon-to-meson production ratios over model predictions based on e$^+$e$^-$ collisions. Several mechanisms are proposed to understand this phenomenon. New measurements by the LHCb and ALICE experiments show a similar enhancement in the beauty sector. We explore this enhancement in terms of event activity using the color-reconnection beyond leading order approximation model. We propose sensitive probes relying on the event shape that will allow for the differentiation between the proposed beauty-production scenarios using freshly collected LHC Run-3 data, and we also compare these to predictions for charm. Our results will contribute to a deeper theoretical understanding of the heavy-flavor baryon enhancement and its relation to baryon enhancement in general., Comment: Submiited to IJMPA Special Issue Zim\'anyi School 2023

The progenitor system(s) as well as the explosion mechanism(s) of thermonuclear (Type Ia) supernovae are long-standing issues in astrophysics. Here we present ejecta masses and other physical parameters for 28 recent Type Ia supernovae inferred from multiband photometric and optical spectroscopic data. Our results confirm that the majority of SNe Ia show {\it observable} ejecta masses below the Chandrasekhar-limit (having a mean $M_{\rm ej} \approx 1.1 \pm 0.3$ M$_\odot$), consistent with the predictions of recent sub-M$_{\rm Ch}$ explosion models. They are compatible with models assuming either single- or double-degenerate progenitor configurations. We also recover a sub-sample of supernovae within $1.2 $ M$_\odot$ $< M_{\rm {ej}} < 1.5$ M$_\odot$ that are consistent with near-Chandrasekhar explosions. Taking into account the uncertainties of the inferred ejecta masses, about half of our SNe are compatible with both explosion models. We compare our results with those in previous studies, and discuss the caveats and concerns regarding the applied methodology.

Broad application of human-machine interaction (HMI) demands advanced and human-centered control designs for the machine's automation. Human natural motor action shows stochastic behavior, which has so far not been respected in HMI control designs. Using a previously presented novel human-variability-respecting optimal controller we present a study design which allows the investigation of respecting human natural variability and its effect on human interaction experience. Our approach is tested in simulation based on an identified real human subject and presents a promising approach to be used for a larger subject study.

Complexity of two-level systems, e.g. spins, qubits, magnetic moments etc, are analysed based on the so-called correlational entropy in the case of pure quantum systems and the thermal entropy in case of thermal equilibrium that are suitable quantities essentially free from basis dependence. The complexity is defined as the difference between the Shannon-entropy and the second order R\'enyi-entropy, where the latter is connected to the traditional participation measure or purity. It is shown that the system attains maximal complexity for special choice of control parameters, i.e. strength of disorder either in the presence of noise of the energy states or the presence of disorder in the off diagonal coupling. It is shown that such a noise or disorder dependence provides a basis free analysis and gives meaningful insights. We also look at similar entropic complexity of spins in thermal equilibrium for a paramagnet at finite temperature, $T$ and magnetic field $B$, as well as the case of an Ising model in the mean-field approximation. As a result all examples provide important evidence that the investigation of the entropic complexity parameters help to get deeper understanding in the behavior of these systems., Comment: 9 pages, 9 figures

Characterization of the redshift distribution of ensembles of galaxies is pivotal for large scale structure cosmological studies. In this work, we focus on improving the Self-Organizing Map (SOM) methodology for photometric redshift estimation (SOMPZ), specifically in anticipation of the Dark Energy Survey Year 6 (DES Y6) data. This data set, featuring deeper and fainter galaxies than DES Year 3 (DES Y3), demands adapted techniques to ensure accurate recovery of the underlying redshift distribution. We investigate three strategies for enhancing the existing SOM-based approach used in DES Y3: 1) Replacing the Y3 SOM algorithm with one tailored for redshift estimation challenges; 2) Incorporating $\textit{g}$-band flux information to refine redshift estimates (i.e. using $\textit{griz}$ fluxes as opposed to only $\textit{riz}$); 3) Augmenting redshift data for galaxies where available. These methods are applied to DES Y3 data, and results are compared to the Y3 fiducial ones. Our analysis indicates significant improvements with the first two strategies, notably reducing the overlap between redshift bins. By combining strategies 1 and 2, we have successfully managed to reduce redshift bin overlap in DES Y3 by up to 66$\%$. Conversely, the third strategy, involving the addition of redshift data for selected galaxies as an additional feature in the method, yields inferior results and is abandoned. Our findings contribute to the advancement of weak lensing redshift characterization and lay the groundwork for better redshift characterization in DES Year 6 and future stage IV surveys, like the Rubin Observatory.

Understanding causal relationships within a system is crucial for uncovering its underlying mechanisms. Causal discovery methods, which facilitate the construction of such models from time-series data, hold the potential to significantly advance scientific and engineering fields. This study introduces the Cross-Mapping Coherence (CMC) method, designed to reveal causal connections in the frequency domain between time series. CMC builds upon nonlinear state-space reconstruction and extends the Convergent Cross-Mapping algorithm to the frequency domain by utilizing coherence metrics for evaluation. We tested the Cross-Mapping Coherence method using simulations of logistic maps, Lorenz systems, Kuramoto oscillators, and the Wilson-Cowan model of the visual cortex. CMC accurately identified the direction of causal connections in all simulated scenarios. When applied to the Wilson-Cowan model, CMC yielded consistent results similar to spectral Granger causality. Furthermore, CMC exhibits high sensitivity in detecting weak connections, demonstrates sample efficiency, and maintains robustness in the presence of noise. In conclusion, the capability to determine directed causal influences across different frequency bands allows CMC to provide valuable insights into the dynamics of complex, nonlinear systems.

We present galaxy-galaxy lensing measurements using a sample of low surface brightness galaxies (LSBGs) drawn from the Dark Energy Survey Year 3 (Y3) data as lenses. LSBGs are diffuse galaxies with a surface brightness dimmer than the ambient night sky. These dark-matter-dominated objects are intriguing due to potentially unusual formation channels that lead to their diffuse stellar component. Given the faintness of LSBGs, using standard observational techniques to characterize their total masses proves challenging. Weak gravitational lensing, which is less sensitive to the stellar component of galaxies, could be a promising avenue to estimate the masses of LSBGs. Our LSBG sample consists of 23,790 galaxies separated into red and blue color types at $g-i\ge 0.60$ and $g-i< 0.60$, respectively. Combined with the DES Y3 shear catalog, we measure the tangential shear around these LSBGs and find signal-to-noise ratios of 6.67 for the red sample, 2.17 for the blue sample, and 5.30 for the full sample. We use the clustering redshifts method to obtain redshift distributions for the red and blue LSBG samples. Assuming all red LSBGs are satellites, we fit a simple model to the measurements and estimate the host halo mass of these LSBGs to be $\log(M_{\rm host}/M_{\odot}) = 12.98 ^{+0.10}_{-0.11}$. We place a 95% upper bound on the subhalo mass at $\log(M_{\rm sub}/M_{\odot})<11.51$. By contrast, we assume the blue LSBGs are centrals, and place a 95% upper bound on the halo mass at $\log(M_\mathrm{host}/M_\odot) < 11.84$. We find that the stellar-to-halo mass ratio of the LSBG samples is consistent with that of the general galaxy population. This work illustrates the viability of using weak gravitational lensing to constrain the halo masses of LSBGs., Comment: 20 pages, 14 figures

In this paper, a method for a cooperative trajectory planning between a human and an automation is extended by a behavioral model of the human. This model can characterize the stubbornness of the human, which measures how strong the human adheres to his preferred trajectory. Accordingly, a static model is introduced indicating a link between the force in haptically coupled human-robot interactions and humans's stubbornness. The introduced stubbornness parameter enables an application-independent reaction of the automation for the cooperative trajectory planning. Simulation results in the context of human-machine cooperation in a care application show that the proposed behavioral model can quantitatively estimate the stubbornness of the interacting human, enabling a more targeted adaptation of the automation to the human behavior.

Deep Brain Stimulation (DBS) is one of the most successful methods to diminish late-stage Parkinson's Disease (PD) symptoms. It is a delicate surgical procedure which requires detailed pre-surgical patient's study. High-field Magnetic Resonance Imaging (MRI) has proven its improved capacity of capturing the Subthalamic Nucleus (STN) - the main target of DBS in PD - in greater detail than lower field images. Here, we present a comparison between the performance of two different Deep Learning (DL) automatic segmentation architectures, one based in the registration to a brain template and the other performing the segmentation in in the MRI acquisition native space. The study was based on publicly available high-field 7 Tesla (T) brain MRI datasets of T1-weighted and T2-weighted sequences. nnUNet was used on the segmentation step of both architectures, while the data pre and post-processing pipelines diverged. The evaluation metrics showed that the performance of the segmentation directly in the native space yielded better results for the STN segmentation, despite not showing any advantage over the template-based method for the to other analysed structures: the Red Nucleus (RN) and the Substantia Nigra (SN).

A system of one electron in a Coulomb potential in an optical cavity is solved using a tensor-product light-matter basis. The problem was treated at the level of the Pauli-Fierz Hamiltonian describing both light and matter quantum mechanically. The effect of cavity size on the energy levels and high harmonics generation (HHG) spectrum is studied. We have shown that the energy levels, transition states, entanglement, and the HHG spectrum can be strongly influenced by changing the cavity size.

Generation, statistically steady state, and temporal decay of axially rotating thermal counterflow of superfluid $^4$He (He~II) in a square channel is probed using the second sound attenuation technique, measuring the density of quantized vortex lines. The array of rectilinear quantized vortices created by rotation strongly affects the development of quantum turbulence. At relatively slow angular velocities, the type of instability responsible for the destruction of the laminar counterflow qualitatively changes: the growth of seed vortex loops pinned on the channel wall becomes gradually replaced by the growth due to Donnelly-Glaberson instability, which leads to rapid growth of helical Kelvin waves on vortices parallel with applied counterflow. The initial transient growth of vortex line density that follows the sudden start of the counterflow appears self-similar, linear in dimensionless time, $\Omega t$. We show numerically that Kelvin waves of sufficiently strong amplitude reorient the vortices into more flattened shapes, which grow similarly to a free vortex ring. The observed steady state vortex line density at sufficiently high counterflow velocity and its early temporal decay after the counterflow is switched off is not appreciably affected by rotation. It is striking, however, that although the steady state of rotating counterflow is very different from rotating classical grid-generated turbulence, the late temporal decay of both displays similar features: the decay exponent decreases with the rotation rate $\Omega$ from -3/2 towards approximately -0.7, typical for two-dimensional turbulence, consistent with the transition to bidirectional cascade., Comment: 20 pages, 9 figures, 2 videos

The paper is devoted to the study of the backward behavior of solutions of the initial boundary value problem for the chevron pattern equations under homogeneous Dirichlet's boundary conditions. We prove that, as $t\rightarrow \infty$, the asymptotic behavior of solutions of the considered problem is completely determined by the dynamics of a finite set of functionals. Furthermore, we provide numerical evidence for the blow-up of certain solutions of the backward problem in finite time in 1D.

This paper addresses the problem of determining the maximum number of edges in a unit distance graph (UDG) of $n$ vertices using computer search. An unsolved problem of Paul Erd\H{o}s asks the maximum number of edges $u(n)$ a UDG of $n$ vertices can have. Those UDGs that attain $u(n)$ are called "maximally dense." In this paper, we seek to demonstrate a computer algorithm to generate dense UDGs for vertex counts up to at least 100. Via beam search with an added visitation metric, our algorithm finds all known maximally dense UDGs up to isomorphism at the push of a button. In addition, for $15 < n$, where $u(n)$ is unknown, i) the algorithm finds all previously published densest UDGs up to isomorphism for $15 < n \le 30$, and ii) the rate of growth of $u(n)/n$ remains similar for $30 < n$. The code and database of over 60 million UDGs found by our algorithm will be open-sourced at time of publication.

Two-dimensional (2D) turbulence, despite being an idealization of real flows, is of fundamental interest as a model of the spontaneous emergence of order from chaotic flows. The emergence of order often displays critical behavior, whose study is hindered by the long spatial and temporal scales involved. Here, we experimentally study turbulence in periodically driven nanofluidic channels with a high aspect ratio using superfluid helium. We find a multistable transition behavior resulting from cascading bifurcations of large-scale vorticity and critical behavior at the transition to quasi-2D turbulence consistent with phase transitions in periodically driven many-body systems. We demonstrate that quasi-2D turbulent systems can undergo an abrupt change in response to a small change in a control parameter, consistent with predictions for large-scale atmospheric or oceanic flows., Comment: 24 pages (6 pages main text + 18 SI), 21 figures (4 + 17)

Magnetic field is a powerful tool for the manipulation of material's electronic and optical properties. In the domain of transition metal dichalcogenide monolayers, it allows one to unveil the spin, valley, and orbital properties of many-body excitonic complexes. Here we study theoretically the impact of normal-to-plane magnetic field on trions and trion-polaritons. We demonstrate that spin and orbital effects of a magnetic field give comparable contributions to the trion energies. Moreover, as magnetic field redistributes the free electron gas between two valleys in the conductance band, the trion-photon coupling becomes polarization and valley dependent. This results in an effective giant Zeeman splitting of trion-polaritons, in-line with the recent experimental observations.

Context: MATISSE, the mid-infrared spectro-imaging instrument of VLTI, was designed to deliver its advertised performance when paired with an external second generation fringe tracker. Science observation started in 2019, demonstrating imaging capabilities and faint science target observations. Now, The GRAVITY fringe tracker stabilizes the MATISSE fringes which allows using all spectroscopic modes and improves sensitivity and data accuracy. Aims: We present how the MATISSE and GRAVITY instruments were adapted to make the GRAVITY fringe tracker work with MATISSE, under the umbrella of the aptly-named GRA4MAT project, led by ESO in collaboration with the two instrument consortia. Methods: We detail the software modifications needed to implement an acquisition and observing sequence specific to GRA4MAT, including simultaneous fringe tracking and chopping and a narrow off-axis capability inspired by the galactic center and exoplanet capability of GRAVITY. We explain the modified data collection and reduction processes. We show how we leveraged the recent fringe tracker upgrade to implement features specific to its use with MATISSE, e.g. fringe jumps mitigation with an improved group delay control and simultaneous fringe tracking and chopping with a new state machine. Results: We successfully demonstrate significant improvements to the MATISSE instrument. Observations can now be performed at higher spectral resolutions of up to $R\sim3300$ and across the full LM bands at once. Long detector integration times, made possible with stabilized fringes, have improved the LM-bands sensitivity by a factor of 10. Low flux biases in coherently-reduced N-band data have been eliminated. The L-band transfer function is now higher and more stable. We finally illustrate the scientific potential of GRA4MAT with a preview of the first exoplanet observation made by MATISSE on $\beta$ Pictoris b., Comment: Revised after language editing

We present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years (Y3) of the Dark Energy Survey (DES). We implement: 1) second and third moments; 2) wavelet phase harmonics; 3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven $\nu w$CDM cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the Figure of Merit $\textrm{FoM}(S_8, \Omega_{\textrm{m}})$ is improved by 70 percent ($\Lambda$CDM) and 90 percent ($w$CDM). When all the summary statistics are combined, we achieve a 2 percent constraint on the amplitude of fluctuations parameter $S_8 \equiv \sigma_8 (\Omega_{\textrm{m}}/0.3)^{0.5}$, obtaining $S_8 = 0.794 \pm 0.017$ ($\Lambda$CDM) and $S_8 = 0.817 \pm 0.021$ ($w$CDM). The constraints from different statistics are shown to be internally consistent (with a $p$-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the DES Y3 data, finding good consistency; we also compare with results from external datasets, such as \planck{} constraints from the Cosmic Microwave Background, finding statistical agreement, with discrepancies no greater than $<2.2\sigma$., Comment: 24 pages, 13 figures, to be submitted to PRD. Comments welcome!

This article introduces a novel approach to perform the simulation of a single qubit quantum algorithm using laser beams. Leveraging the polarization states of photonic qubits, and inspired by variational quantum eigensolvers, we develop a variational quantum algorithm implementing a clustering procedure following the approach proposed by some of us in SciRep 13, 13284 (2023). A key aspect of our research involves the utilization of non-orthogonal states within the photonic domain, harnessing the potential of polarization schemes to reproduce unitary circuits. By mapping these non-orthogonal states into polarization states, we achieve an efficient and versatile quantum information processing unit which serves as a clustering device for a diverse set of datasets., Comment: 5 pages, 5 figures

Physical Human-Machine Interaction plays a pivotal role in facilitating collaboration across various domains. When designing appropriate model-based controllers to assist a human in the interaction, the accuracy of the human model is crucial for the resulting overall behavior of the coupled system. When looking at state-of-the-art control approaches, most methods rely on a deterministic model or no model at all of the human behavior. This poses a gap to the current neuroscientific standard regarding human movement modeling, which uses stochastic optimal control models that include signal-dependent noise processes and therefore describe the human behavior much more accurate than the deterministic counterparts. To close this gap by including these stochastic human models in the control design, we introduce a novel design methodology resulting in a Human-Variability-Respecting Optimal Control that explicitly incorporates the human noise processes and their influence on the mean and variability behavior of a physically coupled human-machine system. Our approach results in an improved overall system performance, i.e. higher accuracy and lower variability in target point reaching, while allowing to shape the joint variability, for example to preserve human natural variability patterns.

This paper presents a novel method for low maintenance, low ambiguity in-situ drift velocity monitoring in large volume Time Projection Chambers (TPCs). The method was developed and deployed for the 40m^3 TPC tracker system of the NA61/SHINE experiment at CERN, which has a one meter of drift length. The method relies on a low-cost multi-wire proportional chamber placed next to the TPC to be monitored, downstream with respect to the particle flux. Reconstructed tracks in the TPC are matched to hits in the monitoring chamber, called the Geometry Reference Chamber (GRC). Relative differences in positions of hits in the GRC are used to estimate the drift velocity, removing the need for an accurate alignment of the TPC to the GRC. An important design requirement on the GRC was minimal added complexity to the existing system, in particular, compatibility with Front-End Electronics cards already used to read out the TPCs. Moreover, the GRC system was designed to operate both in large and small particle fluxes. The system is capable of monitoring the evolution of the drift velocity inside the TPC down to a one permil precision, with a few minutes of data collection., Comment: 18 pages, 9 figures

Since 2016 the operation of insurance companies in the European Union is regulated by the Solvency II directive. According to the EU directive the capital requirement should be calculated as a 99.5\% of Value at Risk. In this study, we examine the impact of this capital requirement constraint on equilibrium premiums and capitals. We discuss the case of the oligopoly insurance market using Bertrand's model, assuming profit maximizing insurance companies facing Value at Risk constraints. First we analyze companies' decision on premium level. The companies strategic behavior can result positive as well as negative expected profit for companies. The desired situation where competition eliminate positive profit and lead the market to zero-profit state is rare. Later we examine ex post and ax ante capital adjustments. Capital adjustment does not rule out market anomalies, although somehow changes them. Possibility of capital adjustment can lead the market to a situation where all of the companies suffer loss. Allowing capital adjustment results monopolistic premium level or market failure with positive probabilities., Comment: 47 pages

Over the recent years, additional low-amplitude non-radial modes were detected in many of the first-overtone RR Lyrae stars. These non-radial modes form a characteristic period ratio with the dominant first-overtone mode of around 0.61. The incidence rate of this phenomenon changes from population to population. It is also strongly dependent on the quality of the analyzed data. Current models explaining these additional signals involve non-radial modes of degrees 8 and 9. Using synthetic horizontal branch populations, we investigate the incidence rate of first-overtone RR Lyrae stars with non-radial modes depending on the population properties, i.e., ages and metallicities. We compare our results with the observed results for globular clusters and the numerous collection of field first-overtone RR Lyrae stars to test the predictions of the models. We used synthetic horizontal branches combined with pulsation models to predict how the incidence rate would depend on the age and metallicity of the population. To test whether the results based on synthetic horizontal branches are realistic, we compared them to incidence rates observed by TESS in first-overtone field RR Lyrae stars, using photometric metallicity values from a newly established calibration for TESS. The analysis of synthetic horizontal branches showed that the incidence rate decreases with decreasing metallicity. We inferred photometric metallicity for RR Lyrae stars observed by TESS and showed that the theoretical predictions are in agreement with the observations. Using the same method, we also conclude that the metallicity distribution of RR Lyrae stars showing an additional mode with a period-ratio around $0.68$ appears to be different from that of both all first-overtone stars and those showing additional non-radial modes., Comment: 9 pages, 7 figures, 2 tables, accepted for publication in A&A

X-ray grating interferometry allows for the simultaneous acquisition of attenuation, differential-phase contrast, and dark-field images, resulting from X-ray attenuation, refraction, and small-angle scattering, respectively. The modulated phase grating (MPG) interferometer is a recently developed grating interferometry system capable of generating a directly resolvable interference pattern using a relatively large period grating envelope function that is sampled at a pitch that allows for X-ray spatial coherence using a microfocus X-ray source or by use of a source G0 grating that follows the Lau condition. We present the theory of the MPG interferometry system for a 2-dimensional staggered grating, derived using Fourier optics, and we compare the theoretical predictions with experiments we have performed with a microfocus X-ray system at Pennington Biomedical Research Center, LSU. The theoretical and experimental fringe visibility is evaluated as a function of grating-to-detector distance. Quantitative experiments are performed with porous carbon and alumina samples, and qualitative analysis of attenuation and dark-field images of a dried anchovy are shown., Comment: 22 pages, 13 figures. This is a pre-print

Tracking the build-up of financial vulnerabilities is a key component of financial stability policy. Due to the complexity of the financial system, this task is daunting, and there have been several proposals on how to manage this goal. One way to do this is by the creation of indices that act as a signal for the policy maker. While factor modelling in finance and economics has a rich history, most of the applications tend to focus on stationary factors. Nevertheless, financial stress (and in particular tail events) can exhibit a high degree of inertia. This paper advocates moving away from the stationary paradigm and instead proposes non-stationary factor models as measures of financial stress. Key advantage of a non-stationary factor model is that while some popular measures of financial stress describe the variance-covariance structure of the financial stress indicators, the new index can capture the tails of the distribution. To showcase this, we use the obtained factors as variables in a growth-at-risk exercise. This paper offers an overview of how to construct non-stationary dynamic factors of financial stress using the UK financial market as an example.

In this paper, we explore the application of Unmanned Aerial Vehicles (UAVs) in maritime search and rescue (mSAR) missions, focusing on medium-sized fixed-wing drones and quadcopters. We address the challenges and limitations inherent in operating some of the different classes of UAVs, particularly in search operations. Our research includes the development of a comprehensive software framework designed to enhance the efficiency and efficacy of SAR operations. This framework combines preliminary detection onboard UAVs with advanced object detection at ground stations, aiming to reduce visual strain and improve decision-making for operators. It will be made publicly available upon publication. We conduct experiments to evaluate various Region of Interest (RoI) proposal methods, especially by imposing simulated limited bandwidth on them, an important consideration when flying remote or offshore operations. This forces the algorithm to prioritize some predictions over others.

This paper introduces a novel model-based adaptive shared control to allow for the identification and design challenge for shared-control systems, in which humans and automation share control tasks. The main challenge is the adaptive behavior of the human in such shared control interactions. Consequently, merely identifying human behavior without considering automation is insufficient and often leads to inadequate automation design. Therefore, this paper proposes a novel solution involving online identification of the human and the adaptation of shared control using Linear-Quadratic differential games. The effectiveness of the proposed online adaptation is analyzed in simulations and compared with a non-adaptive shared control from the state of the art. Finally, the proposed approach is tested through human-in-the-loop experiments, highlighting its suitability for real-time applications.

Analogue test structures were fabricated using the Tower Partners Semiconductor Co. CMOS 65 nm ISC process. The purpose was to characterise and qualify this process and to optimise the sensor for the next generation of Monolithic Active Pixels Sensors for high-energy physics. The technology was explored in several variants which differed by: doping levels, pixel geometries and pixel pitches (10-25 $\mu$m). These variants have been tested following exposure to varying levels of irradiation up to 3 MGy and $10^{16}$ 1 MeV n$_\text{eq}$ cm$^{-2}$. Here the results from prototypes that feature direct analogue output of a 4$\times$4 pixel matrix are reported, allowing the systematic and detailed study of charge collection properties. Measurements were taken both using $^{55}$Fe X-ray sources and in beam tests using minimum ionizing particles. The results not only demonstrate the feasibility of using this technology for particle detection but also serve as a reference for future applications and optimisations.

We introduce the Piquasso quantum programming framework, a full-stack open-source software platform for the simulation and programming of photonic quantum computers. Piquasso can be programmed via a high-level Python programming interface enabling users to perform efficient quantum computing with discrete and continuous variables. Via optional high-performance C++ backends, Piquasso provides state-of-the-art performance in the simulation of photonic quantum computers. The Piquasso framework is supported by an intuitive web-based graphical user interface where the users can design quantum circuits, run computations, and visualize the results., Comment: The source code is made available at https://github.com/Budapest-Quantum-Computing-Group/piquasso, and the documentation is published at https://piquasso.readthedocs.io/; November 2024 update: code examples adapted to Piquasso v5.0.0, presentation improved, minor errors corrected, references updated, new "Benchmarks" section added

We present simulation-based cosmological $w$CDM inference using Dark Energy Survey Year 3 weak-lensing maps, via neural data compression of weak-lensing map summary statistics: power spectra, peak counts, and direct map-level compression/inference with convolutional neural networks (CNN). Using simulation-based inference, also known as likelihood-free or implicit inference, we use forward-modelled mock data to estimate posterior probability distributions of unknown parameters. This approach allows all statistical assumptions and uncertainties to be propagated through the forward-modelled mock data; these include sky masks, non-Gaussian shape noise, shape measurement bias, source galaxy clustering, photometric redshift uncertainty, intrinsic galaxy alignments, non-Gaussian density fields, neutrinos, and non-linear summary statistics. We include a series of tests to validate our inference results. This paper also describes the Gower Street simulation suite: 791 full-sky PKDGRAV dark matter simulations, with cosmological model parameters sampled with a mixed active-learning strategy, from which we construct over 3000 mock DES lensing data sets. For $w$CDM inference, for which we allow $-1