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We construct global homotopies to compute differential Hochschild cohomologies in differential geometry. This relies on two different techniques: a symbol calculus from differential geometry and a coalgebraic version of the van Est theorem. Not only do we obtain an improved version of the Hochschild-Kostant-Rosenberg theorem but we also compute Hochschild cohomologies for related scenarios, e.g. for principal bundles, and invariant versions., Comment: 65 pages, comments are welcome!

We investigate the impact of using multipoint p-T profiles of varying complexity on the retrieval of synthetically generated hot Jupiter transmission spectra modelled after state-of-the-art observations of the hot Jupiter WASP-39~b with JWST. We perform homogenised atmospheric retrievals with the TauREx retrieval framework on a sample of synthetically generated transmission spectra, accounting for varying cases of underlying p-T profiles, cloud-top pressures, and expected noise levels. These retrievals are performed using a fixed-pressure multipoint p-T prescription with increasing complexity, ranging from isothermal to an eleven-point profile. We evaluate the performance of the retrievals based on the Bayesian model evidence, and the accuracy of the retrievals compared to the known input parameters. We find that performing atmospheric retrievals using an isothermal prescription for the pressure-temperature profile consistently results in wrongly retrieved atmospheric parameters when compared to the known input parameters. For an underlying p-T profile with a fully positive lapse rate, we find that a two-point profile is sufficient to retrieve the known atmospheric parameters, while under the presence of an atmospheric temperature inversion, we find that a more complex profile is necessary. Our investigation shows that, for a data quality scenario mirroring state-of-the-art observations of a hot Jupiter with JWST, an isothermal p-T prescription is insufficient to correctly retrieve the known atmospheric parameters. We find a model complexity preference dependent on the underlying pressure-temperature structure, but argue that a p-T prescription on the complexity level of a four-point profile should be preferred. This represents the overlap between the lowest number of free parameters and highest model preference in the cases investigated in this work., Comment: 16 pages, 14 figures, accepted for publication in A&A

Safe operation of machine learning models requires architectures that explicitly delimit their operational ranges. We evaluate the ability of anomaly detection algorithms to provide indicators correlated with degraded model performance. By placing acceptance thresholds over such indicators, hard boundaries are formed that define the model's coverage. As a use case, we consider the extraction of exoplanetary spectra from transit light curves, specifically within the context of ESA's upcoming Ariel mission. Isolation Forests are shown to effectively identify contexts where prediction models are likely to fail. Coverage/error trade-offs are evaluated under conditions of data and concept drift. The best performance is seen when Isolation Forests model projections of the prediction model's explainability SHAP values., Comment: To appear in "Proceedings of SPAICE 2024: 1st ESA/IAA conference on AI in and for Space". Conference page at https://spaice.esa.int/

With the James Webb Space Telescope (JWST) offering higher resolution data in space-based transmission spectroscopy, understanding the capabilities of our current atmospheric retrieval pipelines is essential. These new data cover wider wavelength ranges and at much higher spectral resolution than previous instruments have been able to offer. Therefore, it is often appealing to bin spectra to fewer points, better constrained in their transit depth, before using them as inputs for atmospheric retrievals. However, little quantitative analysis of the trade-off between spectral resolution and signal-to-noise ratio has been conducted thus far. As such, we produce a simulation replicating the observations of WASP-39b by the NIRSpec PRISM instrument on board JWST and assess the accuracy and consistency of retrievals while varying resolution and the average photometric error. While this probes a specific case we also plot `binning paths' in the resulting sensitivity maps to demonstrate the best attainable atmospheric parameter estimations starting from the position of the real JWST Early Release Science observation. We repeat this analysis on three different simulation setups where each includes an opaque cloud layer at a different height in the atmosphere. We find that a much greater resolution is needed in the case of a high cloud deck since features are already heavily muted by the presence of the clouds. In the other two cases, there are large `safe zones' in the parameter space. If these maps can be generalised, binning paths could inform future observations on how to achieve the most accurate retrieval results., Comment: Submitted to Monthly Notices of the Royal Astronomical Society, 25 pages, 27 figures

This work introduces an approach to enhancing the computational efficiency of 3D atmospheric simulations by integrating a machine-learned surrogate model into the OASIS global circulation model (GCM). Traditional GCMs, which are based on repeatedly numerically integrating physical equations governing atmospheric processes across a series of time-steps, are time-intensive, leading to compromises in spatial and temporal resolution of simulations. This research improves upon this limitation, enabling higher resolution simulations within practical timeframes. Speeding up 3D simulations holds significant implications in multiple domains. Firstly, it facilitates the integration of 3D models into exoplanet inference pipelines, allowing for robust characterisation of exoplanets from a previously unseen wealth of data anticipated from JWST and post-JWST instruments. Secondly, acceleration of 3D models will enable higher resolution atmospheric simulations of Earth and Solar System planets, enabling more detailed insights into their atmospheric physics and chemistry. Our method replaces the radiative transfer module in OASIS with a recurrent neural network-based model trained on simulation inputs and outputs. Radiative transfer is typically one of the slowest components of a GCM, thus providing the largest scope for overall model speed-up. The surrogate model was trained and tested on the specific test case of the Venusian atmosphere, to benchmark the utility of this approach in the case of non-terrestrial atmospheres. This approach yields promising results, with the surrogate-integrated GCM demonstrating above 99.0% accuracy and 147 factor GPU speed-up of the entire simulation compared to using the matched original GCM under Venus-like conditions., Comment: 20 pages, 14 figures

Bachmair's and Ganzinger's abstract redundancy concept for the Superposition Calculus justifies almost all operations that are used in superposition provers to delete or simplify clauses, and thus to keep the clause set manageable. Typical examples are tautology deletion, subsumption deletion, and demodulation, and with a more refined definition of redundancy joinability and connectedness can be covered as well. The notable exception is Destructive Equality Resolution, that is, the replacement of a clause $x \not\approx t \lor C$ with $x \notin \mathrm{vars}(t)$ by $C\{x \mapsto t\}$. This operation is implemented in state-of-the-art provers, and it is clearly useful in practice, but little is known about how it affects refutational completeness. We demonstrate on the one hand that the naive addition of Destructive Equality Resolution to the standard abstract redundancy concept renders the calculus refutationally incomplete. On the other hand, we present several restricted variants of the Superposition Calculus that are refutationally complete even with Destructive Equality Resolution., Comment: 22 pages; shortened version to appear in Proc. IJCAR 2024, Springer

We present a comprehensive analysis of the Hubble Space Telescope observations of the atmosphere of WASP-121 b, a ultra-hot Jupiter. After reducing the transit, eclipse, and phase-curve observations with a uniform methodology and addressing the biases from instrument systematics, sophisticated atmospheric retrievals are used to extract robust constraints on the thermal structure, chemistry, and cloud properties of the atmosphere. Our analysis shows that the observations are consistent with a strong thermal inversion beginning at ~0.1 bar on the dayside, solar to subsolar metallicity Z (i.e., -0.77 < log(Z) < 0.05), and super-solar C/O ratio (i.e., 0.59 < C/O < 0.87). More importantly, utilizing the high signal-to-noise ratio and repeated observations of the planet, we identify the following unambiguous time-varying signals in the data: i) a shift of the putative hotspot offset between the two phase-curves and ii) varying spectral signatures in the transits and eclipses. By simulating the global dynamics of WASP-121 b atmosphere at high-resolution, we show that the identified signals are consistent with quasi-periodic weather patterns, hence atmospheric variability, with signatures at the level probed by the observations (~5% to ~10%) that change on a timescale of ~5 planet days; in the simulations, the weather patterns arise from the formation and movement of storms and fronts, causing hot (as well as cold) patches of atmosphere to deform, separate, and mix in time., Comment: Accepted for publication in ApJS. 43 pages, 31 figures, 2 animations (available online at the journal)

WASP-107b is a warm ($\sim$740 K) transiting planet with a Neptune-like mass of $\sim$30.5 $M_{\oplus}$ and Jupiter-like radius of $\sim$0.94 $R_{\rm J}$, whose extended atmosphere is eroding. Previous observations showed evidence for water vapour and a thick high-altitude condensate layer in WASP-107b's atmosphere. Recently, photochemically produced sulphur dioxide (SO$_2$) was detected in the atmosphere of a hot ($\sim$1,200 K) Saturn-mass planet from transmission spectroscopy near 4.05 $\mu$m, but for temperatures below $\sim$1,000 K sulphur is predicted to preferably form sulphur allotropes instead of SO$_2$. Here we report the 9$\sigma$-detection of two fundamental vibration bands of SO$_2$, at 7.35 $\mu$m and 8.69 $\mu$m, in the transmission spectrum of WASP-107b using the Mid-Infrared Instrument (MIRI) of the JWST. This discovery establishes WASP-107b as the second irradiated exoplanet with confirmed photochemistry, extending the temperature range of exoplanets exhibiting detected photochemistry from $\sim$1,200 K down to $\sim$740 K. Additionally, our spectral analysis reveals the presence of silicate clouds, which are strongly favoured ($\sim$7$\sigma$) over simpler cloud setups. Furthermore, water is detected ($\sim$12$\sigma$), but methane is not. These findings provide evidence of disequilibrium chemistry and indicate a dynamically active atmosphere with a super-solar metallicity.

Brown dwarfs serve as ideal laboratories for studying the atmospheres of giant exoplanets on wide orbits as the governing physical and chemical processes in them are nearly identical. Understanding the formation of gas giant planets is challenging, often involving the endeavour to link atmospheric abundance ratios, such as the carbon-to-oxygen (C/O) ratio, to formation scenarios. However, the complexity of planet formation requires additional tracers, as the unambiguous interpretation of the measured C/O ratio is fraught with complexity. Isotope ratios, such as deuterium-to-hydrogen and 14N/15N, offer a promising avenue to gain further insight into this formation process, mirroring their utility within the solar system. For exoplanets only a handful of constraints on 12C/13C exist, pointing to the accretion of 13C-rich ice from beyond the disks' CO iceline. Here we report on the mid-infrared detection of the 14NH3 and 15NH3 isotopologues in the atmosphere of a cool brown dwarf with an effective temperature of 380 K in a spectrum taken with the Mid-InfraRed Instrument of the James Webb Space Telescope. As expected, our results reveal a 14N/15N value consistent with star-like formation by gravitational collapse, demonstrating that this ratio can be accurately constrained. Since young stars and their planets should be more strongly enriched in the 15N isotope, we expect that 15NH3 will be detectable in a number of cold, wide-separation exoplanets., Comment: Accepted by Nature. 28 pages, 7 figures, uses nature3.cls

We present a consistent and highly scalable local approach to learn the causal structure of a linear Gaussian polytree using data from interventional experiments with known intervention targets. Our methods first learn the skeleton of the polytree and then orient its edges. The output is a CPDAG representing the interventional equivalence class of the polytree of the true underlying distribution. The skeleton and orientation recovery procedures we use rely on second order statistics and low-dimensional marginal distributions. We assess the performance of our methods under different scenarios in synthetic data sets and apply our algorithm to learn a polytree in a gene expression interventional data set. Our simulation studies demonstrate that our approach is fast, has good accuracy in terms of structural Hamming distance, and handles problems with thousands of nodes., Comment: To be published in: IEEE Journal on Selected Areas in Information Theory, Special Issue: Causality: Fundamental Limits and Applications

Markerless methods for animal posture tracking have been rapidly developing recently, but frameworks and benchmarks for tracking large animal groups in 3D are still lacking. To overcome this gap in the literature, we present 3D-MuPPET, a framework to estimate and track 3D poses of up to 10 pigeons at interactive speed using multiple camera views. We train a pose estimator to infer 2D keypoints and bounding boxes of multiple pigeons, then triangulate the keypoints to 3D. For identity matching of individuals in all views, we first dynamically match 2D detections to global identities in the first frame, then use a 2D tracker to maintain IDs across views in subsequent frames. We achieve comparable accuracy to a state of the art 3D pose estimator in terms of median error and Percentage of Correct Keypoints. Additionally, we benchmark the inference speed of 3D-MuPPET, with up to 9.45 fps in 2D and 1.89 fps in 3D, and perform quantitative tracking evaluation, which yields encouraging results. Finally, we showcase two novel applications for 3D-MuPPET. First, we train a model with data of single pigeons and achieve comparable results in 2D and 3D posture estimation for up to 5 pigeons. Second, we show that 3D-MuPPET also works in outdoors without additional annotations from natural environments. Both use cases simplify the domain shift to new species and environments, largely reducing annotation effort needed for 3D posture tracking. To the best of our knowledge we are the first to present a framework for 2D/3D animal posture and trajectory tracking that works in both indoor and outdoor environments for up to 10 individuals. We hope that the framework can open up new opportunities in studying animal collective behaviour and encourages further developments in 3D multi-animal posture tracking.

Let $X$ be a hyperbolic Riemann surface. We study a convergent Wick-type star product $\star_X$ on $X$ which is induced by the canonical convergent star product $\star_{\mathbb{D}}$ on the unit disk $\mathbb{D}$ via Uniformization Theory. While by construction, the resulting Fr\'echet algebras $(\mathcal{A}(X),\star_X)$ are strongly isomorphic for conformally equivalent Riemann surfaces, our work exhibits additional severe topological obstructions. In particular, we show that the Fr\'echet algebra $(\mathcal{A}(X),\star_X)$ degenerates if and only if the connectivity of $X$ is at least $3$, and $(\mathcal{A}(X),\star_X)$ is noncommutative if and only if $X$ is simply connected. We also explicitly determine the algebra $\mathcal{A}_X$ and the star product $\star_X$ for the intermediate case of doubly connected Riemann surfaces $X$. As a perhaps surprinsing result, we deduce that two such Fr\'echet algebras are strongly isomorphic if and only if either both Riemann surfaces are conformally equivalent to an (not neccesarily the same) annulus or both are conformally equivalent to a punctured disk., Comment: References updated

We provide a critical assessment of the current set of benchmarks for relative SRS termination in the Termination Problems Database (TPDB): most of the benchmarks in Waldmann_19 and ICFP_10_relative are, in fact, strictly terminating (i. e., terminating when non-strict rules are considered strict), so these benchmarks should be removed, or relabelled. To fill this gap, we enumerate small relative string rewrite systems. At present, we have complete enumerations for a 2-letter alphabet up to size 11, and for a 3-letter alphabet up to size 8. For some selected benchmarks, old and new, we discuss how to prove termination, automated or not., Comment: Presented at WST 2023

In this study we investigate the stability limits of Micromegas detectors upon irradiation with alpha particles. The results are obtained with meshes with different optical transparency and geometry of wires. The measurements are performed in Ar- and Ne- based mixtures with different CO$_2$ content. We observe that the breakdown limit strongly depends on the gas and that a higher amount of quencher in the mixture does not necessarily correlate with higher stability. In addition, we observe discharge probability scaling with the wire pitch. This suggests that a Micromegas mesh cell can be treated as an independent amplification unit, similar to a hole in a GEM foil. The outcome of these studies provides valuable input for further optimization of MPGD detectors, multi-layer stacks in particular., Comment: 6 pages, 3 figures Part of MPGD 2022 proceedings

Individual vibrational band spectroscopy presents an opportunity to examine exoplanet atmospheres in detail by distinguishing where the vibrational state populations of molecules differ from the current assumption of a Boltzmann distribution. Here, retrieving vibrational bands of OH in exoplanet atmospheres is explored using the hot Jupiter WASP-33b as an example. We simulate low-resolution spectroscopic data for observations with the JWST's NIRSpec instrument and use high resolution observational data obtained from the Subaru InfraRed Doppler instrument (IRD). Vibrational band-specific OH cross section sets are constructed and used in retrievals on the (simulated) low and (real) high resolution data. Low resolution observations are simulated for two WASP-33b emission scenarios: under the assumption of local thermal equilibrium (LTE) and a toy non-LTE model for vibrational excitation of selected bands. We show that mixing ratios for individual bands can be retrieved with sufficient precision to allow the vibrational population distributions of the forward models to be reconstructed. A simple fit for the Boltzmann distribution in the LTE case shows that the vibrational temperature is recoverable in this manner. For high resolution, cross-correlation applications, we apply the individual vibrational band analysis to an IRD spectrum of WASP-33b, applying an 'un-peeling' technique. Individual detection significances for the two strongest bands are shown to be in line with Boltzmann distributed vibrational state populations consistent with the effective temperature of the WASP-33b atmosphere reported previously. We show the viability of this approach for analysing the individual vibrational state populations behind observed and simulated spectra including reconstructing state population distributions., Comment: Submitted for publication in AJ

Retrieval methods are a powerful analysis technique for modelling exoplanetary atmospheres by estimating the bulk physical and chemical properties that combine in a forward model to best-fit an observed spectrum, and they are increasingly being applied to observations of directly-imaged exoplanets. We have adapted TauREx3, the Bayesian retrieval suite, for the analysis of near-infrared spectrophotometry from directly-imaged gas giant exoplanets and brown dwarfs. We demonstrate TauREx3's applicability to sub-stellar atmospheres by presenting results for brown dwarf benchmark GJ 570D which are consistent with previous retrieval studies, whilst also exhibiting systematic biases associated with the presence of alkali lines. We also present results for the cool exoplanet 51 Eri b, the first application of a free chemistry retrieval analysis to this object, using spectroscopic observations from GPI and SPHERE. While our retrieval analysis is able to explain spectroscopic and photometric observations without employing cloud extinction, we conclude this may be a result of employing a flexible temperature-pressure profile which is able to mimic the presence of clouds. We present Bayesian evidence for an ammonia detection with a 2.7$\sigma$ confidence, the first indication of ammonia in an exoplanetary atmosphere. This is consistent with this molecule being present in brown dwarfs of a similar spectral type. We demonstrate the chemical similarities between 51 Eri b and GJ 570D in relation to their retrieved molecular abundances. Finally, we show that overall retrieval conclusions for 51 Eri b can vary when employing different spectral data and modelling components, such as temperature-pressure and cloud structures.

In this work, wake-tail plane interactions are investigated for a tandem wing configuration in buffet conditions using hybrid RANS/LES simulations with the Automated Zonal Detached Eddy Simulation (AZDES) method. The analyzed configuration consists of two untapered and unswept wing segments, representative of a wing-tail plane configuration. The shock oscillation on the front wing segment and the development of its turbulent wake are characterized, including a spectral analysis of the pressure and velocity fluctuations in the wake and a modal analysis of the flow field applying Proper Orthogonal Decomposition (POD). The impact of the wake on the aerodynamics and loads of the rear wing segment is then studied, with a spectral analysis of its lift and surface pressure oscillations. Finally, the influence of the position and the incidence angle of the rear wing segment are investigated. For the considered flow conditions, 2D buffet is present on the front wing segment. During the downstream movement of the shock, the amount of separation reaches its minimum and small vortices are present in the wake. During the upstream movement of the shock, the amount of separation is at its maximum and larger turbulent structures are present together with high fluctuation levels of velocity and pressure. A distinct peak can be associated with the meandering motion of wake vortices, identified by means of a modal analysis of the flow field using Proper Orthogonal Decomposition. The impingement of the wake causes a strong variation of the loading of the rear wing segment. A comparably low-frequent oscillation of the lift coefficient, attributed to the change of intensity of the downwash caused by the front segment, can be distinguished from fluctuations of high frequency that are caused by the impingement of the turbulent structures in the wake., Comment: Updated arXiv version to version published in CEAS Aeronautical Journal

This work provides an overview of aerodynamic data acquired in the European Transonic Windtunnel using an XRF-1 transport aircraft configuration both at cruise conditions and at the edges of the flight envelope. The goals and design of the wind tunnel test was described, highlighting the use of the cryogenic wind tunnel's capability to isolate the effects of Mach and Reynolds numbers and the dynamic pressure. The resulting dataset includes an aerodynamic baseline characterization of the full span model with vertical and horizontal tailplanes and without engine nacelles. The effects of different inflow conditions were studied using data from continuous polars, evaluating the changes in aeroelastic deformation which are proportional to $q/E$ and the influence of $M$ and $Re$ on the shock position. Off-design data was analyzed at the lowest and highest measured Mach numbers of 0.84 and 0.90, respectively. Wing lower surface flow and underside shock motion was analyzed at negative angles of attack using $c_p$ distribution and unsteady pressure transducer fluctuation data, identifying significant upstream displacement of the shock close to the leading edge. Wing upper side flow and the shock motion near buffet onset and beyond was analyzed using unsteady pressure data from point transducers and unsteady pressure sensitive paint (PSP) measurements. Buffet occurs at lower angles of attack at high Mach number, and without clearly defined lift break. Spectral contents at the acquired data points in the buffet range suggest broadband fluctuations at Strouhal numbers between 0.2 and 0.6, which is consistent with recent literature. The spanwise shock propagation velocities were determined independently via analysis of unsteady PSP and pressure transducers to be in the range between $u_s / u_{\infty} = 0.24$ and $0.32$.

We present the analysis of the atmospheres of 70 gaseous extrasolar planets via transit spectroscopy with Hubble's Wide Field Camera 3 (WFC3). For over half of these, we statistically detect spectral modulation which our retrievals attribute to molecular species. Among these, we use Bayesian Hierarchical Modelling to search for chemical trends with bulk parameters. We use the extracted water abundance to infer the atmospheric metallicity and compare it to the planet's mass. We also run chemical equilibrium retrievals, fitting for the atmospheric metallicity directly. However, although previous studies have found evidence of a mass-metallicity trend, we find no such relation within our data. For the hotter planets within our sample, we find evidence for thermal dissociation of dihydrogen and water via the H$^-$ opacity. We suggest that the general lack of trends seen across this population study could be due to i) the insufficient spectral coverage offered by HST WFC3 G141, ii) the lack of a simple trend across the whole population, iii) the essentially random nature of the target selection for this study or iv) a combination of all the above. We set out how we can learn from this vast dataset going forward in an attempt to ensure comparative planetology can be undertaken in the future with facilities such as JWST, Twinkle and Ariel. We conclude that a wider simultaneous spectral coverage is required as well as a more structured approach to target selection., Comment: Accepted for publication in ApJS

Carbon dioxide (CO2) is a key chemical species that is found in a wide range of planetary atmospheres. In the context of exoplanets, CO2 is an indicator of the metal enrichment (i.e., elements heavier than helium, also called "metallicity"), and thus formation processes of the primary atmospheres of hot gas giants. It is also one of the most promising species to detect in the secondary atmospheres of terrestrial exoplanets. Previous photometric measurements of transiting planets with the Spitzer Space Telescope have given hints of the presence of CO2 but have not yielded definitive detections due to the lack of unambiguous spectroscopic identification. Here we present the detection of CO2 in the atmosphere of the gas giant exoplanet WASP-39b from transmission spectroscopy observations obtained with JWST as part of the Early Release Science Program (ERS). The data used in this study span 3.0 to 5.5 {\mu}m in wavelength and show a prominent CO2 absorption feature at 4.3 {\mu}m (26{\sigma} significance). The overall spectrum is well matched by one-dimensional, 10x solar metallicity models that assume radiative-convective-thermochemical equilibrium and have moderate cloud opacity. These models predict that the atmosphere should have water, carbon monoxide, and hydrogen sulfide in addition to CO2, but little methane. Furthermore, we also tentatively detect a small absorption feature near 4.0 {\mu}m that is not reproduced by these models., Comment: 27 pages, 6 figures, Accepted for publication in Nature, data and models available at https://doi.10.5281/zenodo.6959427

Astrophysical light curves are particularly challenging data objects due to the intensity and variety of noise contaminating them. Yet, despite the astronomical volumes of light curves available, the majority of algorithms used to process them are still operating on a per-sample basis. To remedy this, we propose a simple Transformer model -- called Denoising Time Series Transformer (DTST) -- and show that it excels at removing the noise and outliers in datasets of time series when trained with a masked objective, even when no clean targets are available. Moreover, the use of self-attention enables rich and illustrative queries into the learned representations. We present experiments on real stellar light curves from the Transiting Exoplanet Space Satellite (TESS), showing advantages of our approach compared to traditional denoising techniques., Comment: ICML 2022 Workshop: Machine Learning for Astrophysics

Purpose: Understanding fluctuations of seizure severity within individuals is important for defining treatment outcomes and response to therapy, as well as developing novel treatments for epilepsy. Current methods for grading seizure severity rely on qualitative interpretations from patients and clinicians. Quantitative measures of seizure severity would complement existing approaches, for EEG monitoring, outcome monitoring, and seizure prediction. Therefore, we developed a library of quantitative electroencephalographic (EEG) markers that assess the spread and intensity of abnormal electrical activity during and after seizures. Methods: We analysed intracranial EEG (iEEG) recordings of 1056 seizures from 63 patients. For each seizure, we computed 16 markers of seizure severity that capture the signal magnitude, spread, duration, and post-ictal suppression of seizures. Results: Quantitative EEG markers of seizure severity distinguished focal vs. subclinical and focal vs. FTBTC seizures across patients. In individual patients, 71% had a moderate to large difference (ranksum r > 0.3) between focal and subclinical seizures in three or more markers. Circadian and longer-term changes in severity were found for 67% and 53% of patients, respectively. Conclusion: We demonstrate the feasibility of using quantitative iEEG markers to measure seizure severity. Our quantitative markers distinguish between seizure types and are therefore sensitive to established qualitative differences in seizure severity. Our results also suggest that seizure severity is modulated over different timescales. We envisage that our proposed seizure severity library will be expanded and updated in collaboration with the epilepsy research community to include more measures and modalities., Comment: 30 pages main text, 18 pages supplementary. Six main figures, two supplementary figures

The study of extra-solar planets, or simply, exoplanets, planets outside our own Solar System, is fundamentally a grand quest to understand our place in the Universe. Discoveries in the last two decades have re-defined our understanding of planets, and helped us comprehend the uniqueness of our very own Earth. In recent years the focus has shifted from planet detection to planet characterisation, where key planetary properties are inferred from telescope observations using Monte Carlo-based methods. However, the efficiency of sampling-based methodologies is put under strain by the high-resolution observational data from next generation telescopes, such as the James Webb Space Telescope and the Ariel Space Mission. We are delighted to announce the acceptance of the Ariel ML Data Challenge 2022 as part of the NeurIPS competition track. The goal of this challenge is to identify a reliable and scalable method to perform planetary characterisation. Depending on the chosen track, participants are tasked to provide either quartile estimates or the approximate distribution of key planetary properties. To this end, a synthetic spectroscopic dataset has been generated from the official simulators for the ESA Ariel Space Mission. The aims of the competition are three-fold. 1) To offer a challenging application for comparing and advancing conditional density estimation methods. 2) To provide a valuable contribution towards reliable and efficient analysis of spectroscopic data, enabling astronomers to build a better picture of planetary demographics, and 3) To promote the interaction between ML and exoplanetary science. The competition is open from 15th June and will run until early October, participants of all skill levels are more than welcomed!, Comment: 13 pages, Accepted in the Conference on Neural Information Processing Systems 2022 (NeurIPS 2022), Competition hosted on https://www.ariel-datachallenge.space/

Current endeavours in exoplanet characterisation rely on atmospheric retrieval to quantify crucial physical properties of remote exoplanets from observations. However, the scalability and efficiency of the technique are under strain with increasing spectroscopic resolution and forward model complexity. The situation becomes more acute with the recent launch of the James Webb Space Telescope and other upcoming missions. Recent advances in Machine Learning provide optimisation-based Variational Inference as an alternative approach to perform approximate Bayesian Posterior Inference. In this investigation we combined Normalising Flow-based neural network with our newly developed differentiable forward model, Diff-Tau, to perform Bayesian Inference in the context of atmospheric retrieval. Using examples from real and simulated spectroscopic data, we demonstrated the superiority of our proposed framework: 1) Training Our neural network only requires a single observation; 2) It produces high-fidelity posterior distributions similar to sampling-based retrieval and; 3) It requires 75% less forward model computation to converge. 4.) We performed, for the first time, Bayesian model selection on our trained neural network. Our proposed framework contribute towards the latest development of a neural-powered atmospheric retrieval. Its flexibility and speed hold the potential to complement sampling-based approaches in large and complex data sets in the future., Comment: 16 pages, 4 figures, Published in ApJ

Population studies of exoplanets are key to unlocking their statistical properties. So far the inferred properties have been mostly limited to planetary, orbital and stellar parameters extracted from, e.g., Kepler, radial velocity, and GAIA data. More recently an increasing number of exoplanet atmospheres have been observed in detail from space and the ground. Generally, however, these atmospheric studies have focused on individual planets, with the exception of a couple of works which have detected the presence of water vapor and clouds in populations of gaseous planets via transmission spectroscopy. Here, using a suite of retrieval tools, we analyse spectroscopic and photometric data of 25 hot Jupiters, obtained with the Hubble and Spitzer Space Telescopes via the eclipse technique. By applying the tools uniformly across the entire set of 25 planets, we extract robust trends in the thermal structure and chemical properties of hot Jupiters not obtained in past studies. With the recent launch of JWST and the upcoming missions Twinkle, and Ariel, population based studies of exoplanet atmospheres, such as the one presented here, will be a key approach to understanding planet characteristics, formation, and evolution in our galaxy., Comment: 66 pages, 23 figures, 7 tables. Published in The Astrophysical Journal Supplement Series

We present discharge probability studies performed with a single Thick Gas Electron Multiplier (THGEM) irradiated with alpha particles in Ar-CO$_2$ and Ne-CO$_2$ mixtures. We observe a clear dependency of the discharge stability on the noble gas and quencher content pointing to lighter gases being more stable against the development of streamer discharges. A detailed comparison of the measurements with Geant4 simulations allowed us to extract the critical charge value leading to the formation of a spark in a THGEM hole, which is found to be within the range of 3-7$\times10^6$ electrons, depending on the gas mixture. Our experimental findings are compared to previous GEM results. We show that the discharge probability of THGEMs exceeds the one measured with GEMs by orders of magnitude. This can be explained with simple geometrical considerations, where primary ionization is collected by a lower number of holes available in a THGEM structure, reaching higher primary charge densities and thus increasing the probability of a spark occurrence. However, we show that the critical charge limits are similar for both amplification structures., Comment: 10 pages, 8 figures