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Counterfactual explanations are increasingly used as an Explainable Artificial Intelligence (XAI) technique to provide stakeholders of complex machine learning algorithms with explanations for data-driven decisions. The popularity of counterfactual explanations resulted in a boom in the algorithms generating them. However, not every algorithm creates uniform explanations for the same instance. Even though in some contexts multiple possible explanations are beneficial, there are circumstances where diversity amongst counterfactual explanations results in a potential disagreement problem among stakeholders. Ethical issues arise when for example, malicious agents use this diversity to fairwash an unfair machine learning model by hiding sensitive features. As legislators worldwide tend to start including the right to explanations for data-driven, high-stakes decisions in their policies, these ethical issues should be understood and addressed. Our literature review on the disagreement problem in XAI reveals that this problem has never been empirically assessed for counterfactual explanations. Therefore, in this work, we conduct a large-scale empirical analysis, on 40 datasets, using 12 explanation-generating methods, for two black-box models, yielding over 192.0000 explanations. Our study finds alarmingly high disagreement levels between the methods tested. A malicious user is able to both exclude and include desired features when multiple counterfactual explanations are available. This disagreement seems to be driven mainly by the dataset characteristics and the type of counterfactual algorithm. XAI centers on the transparency of algorithmic decision-making, but our analysis advocates for transparency about this self-proclaimed transparency

The Event Horizon Telescope (EHT) has led to the first images of a supermassive black hole, revealing the central compact objects in the elliptical galaxy M87 and the Milky Way. Proposed upgrades to this array through the next-generation EHT (ngEHT) program would sharply improve the angular resolution, dynamic range, and temporal coverage of the existing EHT observations. These improvements will uniquely enable a wealth of transformative new discoveries related to black hole science, extending from event-horizon-scale studies of strong gravity to studies of explosive transients to the cosmological growth and influence of supermassive black holes. Here, we present the key science goals for the ngEHT and their associated instrument requirements, both of which have been formulated through a multi-year international effort involving hundreds of scientists worldwide., Comment: 32 pages, 11 figures, accepted for publication in a special issue of Galaxies on the ngEHT (https://www.mdpi.com/journal/galaxies/special_issues/ngEHT_blackholes)

Multiple viable theoretical models predict heavy dark matter particles with a mass close to the Planck mass, a range relatively unexplored by current experimental measurements. We use 219.4 days of data collected with the XENON1T experiment to conduct a blind search for signals from Multiply-Interacting Massive Particles (MIMPs). Their unique track signature allows a targeted analysis with only 0.05 expected background events from muons. Following unblinding, we observe no signal candidate events. This work places strong constraints on spin-independent interactions of dark matter particles with a mass between 1$\times$10$^{12}\,$GeV/c$^2$ and 2$\times$10$^{17}\,$GeV/c$^2$. In addition, we present the first exclusion limits on spin-dependent MIMP-neutron and MIMP-proton cross-sections for dark matter particles with masses close to the Planck scale., Comment: 7 pages, 6 figures

Within its Voyage 2050 planning cycle, the European Space Agency (ESA) is considering long-term large class science mission themes. Gravitational-wave astronomy is among the topics under study. Building on previous work by other authors, this paper studies a gravitational-wave interferometer concept, dubbed "LISAmax", consisting of three spacecraft, each located close to one of the Sun-Earth libration points L3, L4 and L5, forming a triangular constellation with an arm length of 259 million kilometers (to be compared to LISA's 2.5 million kilometer arms). We argue that this is the largest triangular formation that can be reached from Earth without a major leap in mission complexity and cost (hence the name). The sensitivity curve of such a detector is at least two orders of magnitude lower in amplitude than that of LISA, at frequencies below 1 mHz. This makes the observatory sensitive to gravitational waves in the {\mu}Hz range and opens a new window for gravitational-wave astronomy, not covered by any other planned detector concept. We analyze in detail the constellation stability for a 10-year mission in the full numerical model including insertion, dispersion, and self-gravity-induced accelerations. We compute the orbit transfers using a European launcher and chemical propulsion. Different orbit options, such as precessing, inclined orbits, the use of flybys for the transfer, and the launch strategy, are discussed. The payload design parameters are assessed, and the expected sensitivity curve is compared with a number of potential gravitational-wave sources. No show stoppers are identified at this point of the analysis., Comment: 20 pages, 11 figures, 3 tables

We developed a detector signal characterization model based on a Bayesian network trained on the waveform attributes generated by a dual-phase xenon time projection chamber. By performing inference on the model, we produced a quantitative metric of signal characterization and demonstrate that this metric can be used to determine whether a detector signal is sourced from a scintillation or an ionization process. We describe the method and its performance on electronic-recoil (ER) data taken during the first science run of the XENONnT dark matter experiment. We demonstrate the first use of a Bayesian network in a waveform-based analysis of detector signals. This method resulted in a 3% increase in ER event-selection efficiency with a simultaneously effective rejection of events outside of the region of interest. The findings of this analysis are consistent with the previous analysis from XENONnT, namely a background-only fit of the ER data., Comment: 11 pages, 8 figures

This white paper outlines the plans of the History Philosophy Culture Working Group of the Next Generation Event Horizon Telescope Collaboration., Comment: 23 pages, 1 figure

Algorithms used by organizations increasingly wield power in society as they decide the allocation of key resources and basic goods. In order to promote fairer, juster, and more transparent uses of such decision-making power, explainable artificial intelligence (XAI) aims to provide insights into the logic of algorithmic decision-making. Despite much research on the topic, consumer-facing applications of XAI remain rare. A central reason may be that a viable platform-based monetization strategy for this new technology has yet to be found. We introduce and describe a novel monetization strategy for fusing algorithmic explanations with programmatic advertising via an explanation platform. We claim the explanation platform represents a new, socially-impactful, and profitable form of human-algorithm interaction and estimate its potential for revenue generation in the high-risk domains of finance, hiring, and education. We then consider possible undesirable and unintended effects of monetizing XAI and simulate these scenarios using real-world credit lending data. Ultimately, we argue that monetizing XAI may be a double-edged sword: while monetization may incentivize industry adoption of XAI in a variety of consumer applications, it may also conflict with the original legal and ethical justifications for developing XAI. We conclude by discussing whether there may be ways to responsibly and democratically harness the potential of monetized XAI to provide greater consumer access to algorithmic explanations.

We report on the first search for nuclear recoils from dark matter in the form of weakly interacting massive particles (WIMPs) with the XENONnT experiment which is based on a two-phase time projection chamber with a sensitive liquid xenon mass of $5.9$ t. During the approximately 1.1 tonne-year exposure used for this search, the intrinsic $^{85}$Kr and $^{222}$Rn concentrations in the liquid target were reduced to unprecedentedly low levels, giving an electronic recoil background rate of $(15.8\pm1.3)~\mathrm{events}/(\mathrm{t\cdot y \cdot keV})$ in the region of interest. A blind analysis of nuclear recoil events with energies between $3.3$ keV and $60.5$ keV finds no significant excess. This leads to a minimum upper limit on the spin-independent WIMP-nucleon cross section of $2.58\times 10^{-47}~\mathrm{cm}^2$ for a WIMP mass of $28~\mathrm{GeV}/c^2$ at $90\%$ confidence level. Limits for spin-dependent interactions are also provided. Both the limit and the sensitivity for the full range of WIMP masses analyzed here improve on previous results obtained with the XENON1T experiment for the same exposure., Comment: Limit points are included in the submission file

We report on the first simultaneous measurement of high-order harmonics, relativistic electrons and low divergence proton beams generated from plasma mirrors driven at kHz repetition rate by relativistic-intensity milliJoule-energy femtosecond laser pulses. This setup enables detailed parametric studies of the particle and radiation spatio-spectral beam properties for a wide range of controlled interaction conditions, such as pulse duration and plasma density scale length. This versatile setup should aid in further understanding the collective laser absorption mechanisms at play during the laser-plasma interaction and in optimizing the secondary beam properties for potential applications.

Yield stress materials fail when the imposed stress crosses a critical threshold. A well-known dynamical response to the applied stress is the phenomenon of creep where the cumulative deformation grows sublinearly with time, prior to failure or arrest. Using extensive molecular dynamics simulations, we study such response for a model amorphous system, in the athermal limit, and probe how the annealing history of the initial state determines the observed behaviour to an applied shear stress. Further, we analyze the microscopic dynamics in the vicinity of the yield threshold, using large systems, and characterize the spatiotemporal signatures towards arrest or flow, at different scales.

We study both numerically and experimentally the use of two third-order nonlinear temporal filtering techniques, namely nonlinear ellipse rotation (NER) and cross-polarized wave (XPW) generation, for spatio-temporal cleaning of mJ energy 30 fs Titanium:Sapphire laser pulses in a multi-pass cell. In both cases, a contrast enhancement greater than 3 orders of magnitude is observed, together with excellent output pulse quality and record high conversion efficiencies. Careful balancing of nonlinearity and dispersion inside the multi-pass cell helps tune the spectral broadening process and control the post-compressed pulse duration for specific applications.

Skip connections and normalisation layers form two standard architectural components that are ubiquitous for the training of Deep Neural Networks (DNNs), but whose precise roles are poorly understood. Recent approaches such as Deep Kernel Shaping have made progress towards reducing our reliance on them, using insights from wide NN kernel theory to improve signal propagation in vanilla DNNs (which we define as networks without skips or normalisation). However, these approaches are incompatible with the self-attention layers present in transformers, whose kernels are intrinsically more complicated to analyse and control. And so the question remains: is it possible to train deep vanilla transformers? We answer this question in the affirmative by designing several approaches that use combinations of parameter initialisations, bias matrices and location-dependent rescaling to achieve faithful signal propagation in vanilla transformers. Our methods address various intricacies specific to signal propagation in transformers, including the interaction with positional encoding and causal masking. In experiments on WikiText-103 and C4, our approaches enable deep transformers without normalisation to train at speeds matching their standard counterparts, and deep vanilla transformers to reach the same performance as standard ones after about 5 times more iterations., Comment: ICLR 2023

We examine the structural relaxation of glassy materials at finite temperatures, considering the effect of activated rearrangements and long-range elastic interactions. Our three-dimensional mesoscopic relaxation model shows how the displacements induced by localized relaxation events can result in faster-than-exponential relaxation. Thermal activation allows for local rearrangements, which generate elastic responses and possibly cascades of new relaxation events. To study the interplay between this elastically-dominated and thermally-dominated dynamics, we introduce tracer particles that follow the displacement field induced by the local relaxation events and also incorporate Brownian motion. Our results reveal that the dynamic exponents and shape parameter of the dynamical structure factor depend on this competition and display a crossover from faster-than-exponential to exponential relaxation as temperature increases, consistent with recent observations in metallic glasses. Additionally, we find the distribution of waiting times between activations to be broadly distributed at low temperatures, providing a measure of dynamical heterogeneities characteristic for to glassy dynamics., Comment: 20 pages, 19 figures

The formation process of multiple populations in globular clusters is still up for debate. Kinematic differences between the populations are particularly interesting in this respect, because they allow us to distinguish between single-epoch formation scenarios and multi-epoch formation scenarios. We analyze the kinematics of 25 globular clusters and aim to find kinematic differences between multiple populations to constrain their formation process. We split red-giant branch (RGB) stars in each cluster into three populations (P1, P2, P3) for the type-II clusters and two populations (P1 and P2) otherwise using Hubble photometry. We derive the rotation and dispersion profiles for each cluster and its populations by using all stars with radial velocity measurements obtained from MUSE spectroscopy. Based on these profiles, we calculate the rotation strength in terms of ordered-over-random motion $\left(v/\sigma\right)_\mathrm{HL}$ evaluated at the half-light radius of the cluster. We detect rotation in all but four clusters. For NGC~104, NGC~1851, NGC~2808, NGC~5286, NGC~5904, NGC~6093, NGC~6388, NGC~6541, NGC~7078 and NGC~7089 we also detect rotation for P1 and/or P2 stars. For NGC~2808, NGC~6093 and NGC~7078 we find differences in $\left(v/\sigma\right)_\mathrm{HL}$ between P1 and P2 that are larger than $1\sigma$. Whereas we find that P2 rotates faster than P1 for NGC~6093 and NGC~7078, the opposite is true for NGC~2808. However, even for these three clusters, the differences are still of low significance. We find that the strength of rotation of a cluster generally scales with its median relaxation time. For P1 and P2, the corresponding relation is very weak at best. We observe no correlation between the difference in rotation strength between P1 and P2 and cluster relaxation time. The MUSE stellar radial velocities that this analysis is based on are made publicly available.

We construct an asymmetric bouncing scenario within the VCDM model - also known as type-II minimally modified gravity -, a modified gravity theory with two local physical degrees of freedom. The scenario is exempt of any ghost or gradient instability, ad-hoc matching conditions or anisotropic stress issue (BKL instability). It moreover succeeds in generating the cosmological perturbations compatible with the observations. The scalar spectral index can be adapted by the choice of the equation of state of the matter sector and the form of the VCDM potential leading to an almost scale-invariant power spectrum. Satisfying the CMB bounds on the tensor-to-scalar ratio leads to a blue tensor spectrum., Comment: 15 pages, 8 figures; accepted version

The XENONnT detector uses the latest and largest liquid xenon-based time projection chamber (TPC) operated by the XENON Collaboration, aimed at detecting Weakly Interacting Massive Particles and conducting other rare event searches. The XENONnT data acquisition (DAQ) system constitutes an upgraded and expanded version of the XENON1T DAQ system. For its operation, it relies predominantly on commercially available hardware accompanied by open-source and custom-developed software. The three constituent subsystems of the XENONnT detector, the TPC (main detector), muon veto, and the newly introduced neutron veto, are integrated into a single DAQ, and can be operated both independently and as a unified system. In total, the DAQ digitizes the signals of 698 photomultiplier tubes (PMTs), of which 253 from the top PMT array of the TPC are digitized twice, at $\times10$ and $\times0.5$ gain. The DAQ for the most part is a triggerless system, reading out and storing every signal that exceeds the digitization thresholds. Custom-developed software is used to process the acquired data, making it available within $\mathcal{O}\left(10\text{ s}\right)$ for live data quality monitoring and online analyses. The entire system with all the three subsystems was successfully commissioned and has been operating continuously, comfortably withstanding readout rates that exceed $\sim500$ MB/s during calibration. Livetime during normal operation exceeds $99\%$ and is $\sim90\%$ during most high-rate calibrations. The combined DAQ system has collected more than 2 PB of both calibration and science data during the commissioning of XENONnT and the first science run.

Cosmic-ray muons that enter the Super-Kamiokande detector cause hadronic showers due to spallation in water, producing neutrons and radioactive isotopes. Those are a major background source for studies of MeV-scale neutrinos and searches for rare events. Since 2020, gadolinium was introduced in the ultra-pure water in the Super-Kamiokande detector to improve the detection efficiency of neutrons. In this study, the cosmogenic neutron yield was measured using data acquired during the period after the gadolinium loading. The yield was found to be $(2.76 \pm 0.02\,\mathrm{(stat.) \pm 0.19\,\mathrm{(syst.)}}) \times 10^{-4}\,\mu^{-1} \mathrm{g^{-1} cm^{2}}$ at 259 GeV of average muon energy at the Super-Kamiokande detector., Comment: 10 pages, 10 figures, 3 tables

Informed consent has become increasingly salient for data privacy and its regulation. Entities from governments to for-profit companies have addressed concerns about data privacy with policies that enumerate the conditions for personal data storage and transfer. However, increased enumeration of and transparency in data privacy policies has not improved end-users' comprehension of how their data might be used: not only are privacy policies written in legal language that users may struggle to understand, but elements of these policies may compose in such a way that the consequences of the policy are not immediately apparent. We present a framework that uses Answer Set Programming (ASP) -- a type of logic programming -- to formalize privacy policies. Privacy policies thus become constraints on a narrative planning space, allowing end-users to forward-simulate possible consequences of the policy in terms of actors having roles and taking actions in a domain. We demonstrate through the example of the Health Insurance Portability and Accountability Act (HIPAA) how to use the system in various ways, including asking questions about possibilities and identifying which clauses of the law are broken by a given sequence of events., Comment: 6 pages; will be presented as a long talk at ProLaLa 2023 (colocated with POPL 2023)

Classical novae are thermonuclear explosions in stellar binary systems, and important sources of $^{26}$Al and $^{22}$Na. While gamma rays from the decay of the former radioisotope have been observed throughout the Galaxy, $^{22}$Na remains untraceable. The half-life of $^{22}$Na (2.6 yr) would allow the observation of its 1.275 MeV gamma-ray line from a cosmic source. However, the prediction of such an observation requires good knowledge of the nuclear reactions involved in the production and destruction of this nucleus. The $^{22}$Na($p,\gamma$)$^{23}$Mg reaction remains the only source of large uncertainty about the amount of $^{22}$Na ejected. Its rate is dominated by a single resonance on the short-lived state at 7785.0(7) keV in $^{23}$Mg. In the present work, a combined analysis of particle-particle correlations and velocity-difference profiles is proposed to measure femtosecond nuclear lifetimes. The application of this novel method to the study of the $^{23}$Mg states, combining magnetic and highly-segmented tracking gamma-ray spectrometers, places strong limits on the amount of $^{22}$Na produced in novae, explains its non-observation to date in gamma rays (flux < 2.5x$10^{-4}$ ph/(cm$^2$s)), and constrains its detectability with future space-borne observatories., Comment: 18 pages, 3 figures, 1 table

THz spectroscopy has reached imaging capability with a spatial resolution of a few micrometres. This property enables measurements and imaging of biological samples like cells. THz photons have very low photon energies in the millielectronvolt range. These energies interact mainly with vibrations in the molecules. Therefore, the investigated samples are neither ionized nor their DNA damaged, making this the perfect method for application on living cell tissue. In the future, material databases with absorption spectra will empower this method to distinguish even artificial particles like microplastics inside biological tissue. Current research aims at the impact of plastic nanoparticles on cell tissue considering various aspects. One of them is the investigation of the potential harm, the interaction of these particles with human body cells can cause, as these highly abundant particles are found anywhere in the environment. THz absorption spectroscopy offers the opportunity to investigate the polymers and identify them using their specific absorption lines as a fingerprint. In this publication, we study different polymers and analyse their particular fingerprints in the THz frequency spectrum from 0.1 up to 4 THz using a commercially available THz spectrometer. With this work we are contributing to the development, using THz waves for imaging, by identifying the fingerprints of the four most used plastics by humankind. At the end of this development, we envision a method to investigate the influence of nanometre-sized plastic particles on the human body and other biological organisms., Comment: 10 pages, 6 figures plus Supplementary Materials

A low-energy electronic recoil calibration of XENON1T, a dual-phase xenon time projection chamber, with an internal $^{37}$Ar source was performed. This calibration source features a 35-day half-life and provides two mono-energetic lines at 2.82 keV and 0.27 keV. The photon yield and electron yield at 2.82 keV are measured to be (32.3$\pm$0.3) photons/keV and (40.6$\pm$0.5) electrons/keV, respectively, in agreement with other measurements and with NEST predictions. The electron yield at 0.27 keV is also measured and it is (68.0$^{+6.3}_{-3.7}$) electrons/keV. The $^{37}$Ar calibration confirms that the detector is well-understood in the energy region close to the detection threshold, with the 2.82 keV line reconstructed at (2.83$\pm$0.02) keV, which further validates the model used to interpret the low-energy electronic recoil excess previously reported by XENON1T. The ability to efficiently remove argon with cryogenic distillation after the calibration proves that $^{37}$Ar can be considered as a regular calibration source for multi-tonne xenon detectors.

Property graphs have reached a high level of maturity, witnessed by multiple robust graph database systems as well as the ongoing ISO standardization effort aiming at creating a new standard Graph Query Language (GQL). Yet, despite documented demand, schema support is limited both in existing systems and in the first version of the GQL Standard. It is anticipated that the second version of the GQL Standard will include a rich DDL. Aiming to inspire the development of GQL and enhance the capabilities of graph database systems, we propose PG-Schema, a simple yet powerful formalism for specifying property graph schemas. It features PG-Types with flexible type definitions supporting multi-inheritance, as well as expressive constraints based on the recently proposed PG-Keys formalism. We provide the formal syntax and semantics of PG-Schema, which meet principled design requirements grounded in contemporary property graph management scenarios, and offer a detailed comparison of its features with those of existing schema languages and graph database systems., Comment: 26 pages

Various WIMP dark matter searches using the full data set of XMASS-I, a single-phase liquid xenon detector, are reported in this paper. Stable XMASS-I data taking accumulated a total live time of 1590.9 days between November 20, 2013 and February 1, 2019 with an analysis threshold of ${\rm 1.0\,keV_{ee}}$. In the latter half of data taking a lower analysis threshold of ${\rm 0.5\,keV_{ee}}$ was also available through a new low threshold trigger. Searching for a WIMP signal in the detector's 97~kg fiducial volume yielded a limit on the WIMP-nucleon scattering cross section of ${\rm 1.4\times 10^{-44}\, cm^{2}}$ for a ${\rm 60\,GeV/c^{2}}$ WIMP at the 90$\%$ confidence level. We also searched for WIMP induced annual modulation signatures in the detector's whole target volume, containing 832~kg of liquid xenon. For nuclear recoils of a ${\rm 8\,GeV/c^{2}}$ WIMP this analysis yielded a 90\% CL cross section limit of ${\rm 2.3\times 10^{-42}\, cm^{2}}$. At a WIMP mass of ${\rm 0.5\, GeV/c^{2}}$ the Migdal effect and Bremsstrahlung signatures were evaluated and lead to 90\% CL cross section limits of ${\rm 1.4\times 10^{-35}\, cm^{2}}$ and ${\rm 1.1\times 10^{-33}\, cm^{2}}$ respectively.

The upgrade of the CMS experiment for the high luminosity operation of the LHC comprises the replacement of the current endcap calorimeter by a high granularity sampling calorimeter (HGCAL). The electromagnetic section of the HGCAL is based on silicon sensors interspersed between lead and copper (or copper tungsten) absorbers. The hadronic section uses layers of stainless steel as an absorbing medium and silicon sensors as an active medium in the regions of high radiation exposure, and scintillator tiles directly readout by silicon photomultipliers in the remaining regions. As part of the development of the detector and its readout electronic components, a section of a silicon-based HGCAL prototype detector along with a section of the CALICE AHCAL prototype was exposed to muons, electrons and charged pions in beam test experiments at the H2 beamline at the CERN SPS in October 2018. The AHCAL uses the same technology as foreseen for the HGCAL but with much finer longitudinal segmentation. The performance of the calorimeters in terms of energy response and resolution, longitudinal and transverse shower profiles is studied using negatively charged pions, and is compared to GEANT4 predictions. This is the first report summarizing results of hadronic showers measured by the HGCAL prototype using beam test data., Comment: Accepted for publication by JINST

The development of practical query languages for graph databases runs well ahead of the underlying theory. The ISO committee in charge of database query languages is currently developing a new standard called Graph Query Language (GQL) as well as an extension of the SQL Standard for querying property graphs represented by a relational schema, called SQL/PGQ. The main component of both is the pattern matching facility, which is shared by the two standards. In many aspects, it goes well beyond RPQs, CRPQs, and similar queries on which the research community has focused for years. Our main contribution is to distill the lengthy standard specification into a simple Graph Pattern Calculus (GPC) that reflects all the key pattern matching features of GQL and SQL/PGQ, and at the same time lends itself to rigorous theoretical investigation. We describe the syntax and semantics of GPC, along with the typing rules that ensure its expressions are well-defined, and state some basic properties of the language. With this paper we provide the community a tool to embark on a study of query languages that will soon be widely adopted by industry.

Discriminating between ballistic and diffuse components of light propagating through highly scattering media is not only important for imaging purposes but also for investigating the fundamental diffusion properties of the medium itself. Massively developed to this end over the past 20 years, nonlinear temporal gating remains limited to about 10e-10 transmission factors. Here, we report nonlinear time gated measurements of highly scattered femtosecond pulses with transmission factors as low as 10e-12. Our approach is based on third-order nonlinear cross-correlation of femtosecond pulses, a standard diagnostic used in high-power laser science, applied for the first time to the study of fundamental light scattering properties.

Neutrinos associated with solar flares (solar-flare neutrinos) provide information on particle acceleration mechanisms during the impulsive phase of solar flares. We searched using the Super-Kamiokande detector for neutrinos from solar flares that occurred during solar cycles $23$ and $24$, including the largest solar flare (X28.0) on November 4th, 2003. In order to minimize the background rate we searched for neutrino interactions within narrow time windows coincident with $\gamma$-rays and soft X-rays recorded by satellites. In addition, we performed the first attempt to search for solar-flare neutrinos from solar flares on the invisible side of the Sun by using the emission time of coronal mass ejections (CMEs). By selecting twenty powerful solar flares above X5.0 on the visible side and eight CMEs whose emission speed exceeds $2000$ $\mathrm{km \, s^{-1}}$ on the invisible side from 1996 to 2018, we found two (six) neutrino events coincident with solar flares occurring on the visible (invisible) side of the Sun, with a typical background rate of $0.10$ ($0.62$) events per flare in the MeV-GeV energy range. No significant solar-flare neutrino signal above the estimated background rate was observed. As a result we set the following upper limit on neutrino fluence at the Earth $\mathit{\Phi}<1.1\times10^{6}$ $\mathrm{cm^{-2}}$ at the $90\%$ confidence level for the largest solar flare. The resulting fluence limits allow us to constrain some of the theoretical models for solar-flare neutrino emission., Comment: 36 pages, 18 figures, 9 tables (Figure 12 was replaced because it was incorrect in version 1.)

Black-box machine learning models are being used in more and more high-stakes domains, which creates a growing need for Explainable AI (XAI). Unfortunately, the use of XAI in machine learning introduces new privacy risks, which currently remain largely unnoticed. We introduce the explanation linkage attack, which can occur when deploying instance-based strategies to find counterfactual explanations. To counter such an attack, we propose k-anonymous counterfactual explanations and introduce pureness as a new metric to evaluate the validity of these k-anonymous counterfactual explanations. Our results show that making the explanations, rather than the whole dataset, k- anonymous, is beneficial for the quality of the explanations.

In this work, we expand on the XENON1T nuclear recoil searches to study the individual signals of dark matter interactions from operators up to dimension-eight in a Chiral Effective Field Theory (ChEFT) and a model of inelastic dark matter (iDM). We analyze data from two science runs of the XENON1T detector totaling 1\,tonne$\times$year exposure. For these analyses, we extended the region of interest from [4.9, 40.9]$\,$keV$_{\text{NR}}$ to [4.9, 54.4]$\,$keV$_{\text{NR}}$ to enhance our sensitivity for signals that peak at nonzero energies. We show that the data is consistent with the background-only hypothesis, with a small background over-fluctuation observed peaking between 20 and 50$\,$keV$_{\text{NR}}$, resulting in a maximum local discovery significance of 1.7\,$\sigma$ for the Vector$\otimes$Vector$_{\text{strange}}$ ($VV_s$) ChEFT channel for a dark matter particle of 70$\,$GeV/c$^2$, and $1.8\,\sigma$ for an iDM particle of 50$\,$GeV/c$^2$ with a mass splitting of 100$\,$keV/c$^2$. For each model, we report 90\,\% confidence level (CL) upper limits. We also report upper limits on three benchmark models of dark matter interaction using ChEFT where we investigate the effect of isospin-breaking interactions. We observe rate-driven cancellations in regions of the isospin-breaking couplings, leading to up to 6 orders of magnitude weaker upper limits with respect to the isospin-conserving case.

The XENON collaboration has published stringent limits on specific dark matter -nucleon recoil spectra from dark matter recoiling on the liquid xenon detector target. In this paper, we present an approximate likelihood for the XENON1T 1 tonne-year nuclear recoil search applicable to any nuclear recoil spectrum. Alongside this paper, we publish data and code to compute upper limits using the method we present. The approximate likelihood is constructed in bins of reconstructed energy, profiled along the signal expectation in each bin. This approach can be used to compute an approximate likelihood and therefore most statistical results for any nuclear recoil spectrum. Computing approximate results with this method is approximately three orders of magnitude faster than the likelihood used in the original publications of XENON1T, where limits were set for specific families of recoil spectra. Using this same method, we include toy Monte Carlo simulation-derived binwise likelihoods for the upcoming XENONnT experiment that can similarly be used to assess the sensitivity to arbitrary nuclear recoil signatures in its eventual 20 tonne-year exposure., Comment: Accepted by European Physical Journal C

We report a search for cosmic-ray boosted dark matter with protons using the 0.37 megaton$\times$years data collected at Super-Kamiokande experiment during the 1996-2018 period (SKI-IV phase). We searched for an excess of proton recoils above the atmospheric neutrino background from the vicinity of the Galactic Center. No such excess is observed, and limits are calculated for two reference models of dark matter with either a constant interaction cross-section or through a scalar mediator. This is the first experimental search for boosted dark matter with hadrons using directional information. The results present the most stringent limits on cosmic-ray boosted dark matter and exclude the dark matter-nucleon elastic scattering cross-section between $10^{-33}\text{ cm}^{2}$ and $10^{-27}\text{ cm}^{2}$ for dark matter mass from 10 MeV/$c^2$ to 1 GeV/$c^2$., Comment: With 1-page appendix. A bug was found in July 2023. This version is updated to match the erratum

Freezing of gait (FoG) is one of the most common symptoms of Parkinson's disease, which is a neurodegenerative disorder of the central nervous system impacting millions of people around the world. To address the pressing need to improve the quality of treatment for FoG, devising a computer-aided detection and quantification tool for FoG has been increasingly important. As a non-invasive technique for collecting motion patterns, the footstep pressure sequences obtained from pressure sensitive gait mats provide a great opportunity for evaluating FoG in the clinic and potentially in the home environment. In this study, FoG detection is formulated as a sequential modelling task and a novel deep learning architecture, namely Adversarial Spatio-temporal Network (ASTN), is proposed to learn FoG patterns across multiple levels. A novel adversarial training scheme is introduced with a multi-level subject discriminator to obtain subject-independent FoG representations, which helps to reduce the over-fitting risk due to the high inter-subject variance. As a result, robust FoG detection can be achieved for unseen subjects. The proposed scheme also sheds light on improving subject-level clinical studies from other scenarios as it can be integrated with many existing deep architectures. To the best of our knowledge, this is one of the first studies of footstep pressure-based FoG detection and the approach of utilizing ASTN is the first deep neural network architecture in pursuit of subject-independent representations. Experimental results on 393 trials collected from 21 subjects demonstrate encouraging performance of the proposed ASTN for FoG detection with an AUC 0.85.