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Magnetoencephalography (MEG) allows the non-invasive detection of interictal epileptiform discharges (IEDs). Clinical MEG analysis in epileptic patients traditionally relies on the visual identification of IEDs, which is time consuming and partially subjective. Automatic, data-driven detection methods exist but show limited performance. Still, the rise of deep learning (DL)-with its ability to reproduce human-like abilities-could revolutionize clinical MEG practice. Here, we developed and validated STIED, a simple yet powerful supervised DL algorithm combining two convolutional neural networks with temporal (1D time-course) and spatial (2D topography) features of MEG signals inspired from current clinical guidelines. Our DL model enabled both temporal and spatial localization of IEDs in patients suffering from focal epilepsy with frequent and high amplitude spikes (FE group), with high-performance metrics-accuracy, specificity, and sensitivity all exceeding 85%-when learning from spatiotemporal features of IEDs. This performance can be attributed to our handling of input data, which mimics established clinical MEG practice. Reverse engineering further revealed that STIED encodes fine spatiotemporal features of IEDs rather than their mere amplitude. The model trained on the FE group also showed promising results when applied to a separate group of presurgical patients with different types of refractory focal epilepsy, though further work is needed to distinguish IEDs from physiological transients. This study paves the way of incorporating STIED and DL algorithms into the routine clinical MEG evaluation of epilepsy., Comment: 10 pages, 7 figures

Understanding planet formation is important in the context of the origin of planetary systems in general and of the Solar System in particular, as well as to predict the likelihood of finding Jupiter, Neptune, and Earth analogues around other stars. We aim to precisely determine the radii and dynamical masses of transiting planets orbiting the young M star AU Mic using public photometric and spectroscopic datasets. We characterise the stellar activity and physical properties (radius, mass, density) of the transiting planets in the young AU Mic system through joint transit and radial velocity fits with Gaussian processes. We determine a radius of $R^{b}$= 4.79 +/- 0.29 R$_\oplus$, a mass of $M^{b}$= 9.0 +/- 2.7 M$_\oplus$, and a bulk density of $\rho^{b}$ = 0.49 +/- 0.16 g cm$^{-3}$ for the innermost transiting planet AU Mic b. For the second known transiting planet, AU Mic c, we infer a radius of $R^{c}$= 2.79 +/- 0.18 R$_\oplus$, a mass of $M^{c}$= 14.5 +/- 3.4 M$_\oplus$, and a bulk density of $\rho^{c}$ = 3.90 +/- 1.17 g cm$^{-3}$. According to theoretical models, AU Mic b may harbour an H2 envelope larger than 5\% by mass, with a fraction of rock and a fraction of water. AU Mic c could be made of rock and/or water and may have an H2 atmosphere comprising at most 5\% of its mass. AU Mic b has retained most of its atmosphere but might lose it over tens of millions of years due to the strong stellar radiation, while AU Mic c likely suffers much less photo-evaporation because it lies at a larger separation from its host. Using all the datasets in hand, we determine a 3$\sigma$ upper mass limit of $M^{[d]}\sin{i}$ = 8.6 M$_{\oplus}$ for the AU Mic 'd' TTV-candidate. In addition, we do not confirm the recently proposed existence of the planet candidate AU Mic 'e' with an orbital period of 33.4 days., Comment: Accepted in A&A. 28 pages, 15 figures

We have learnt in the last decades that the majority of galaxies belong to high density regions interconnected in a sponge-like fashion. This large-scale structure is characterised by clusters, filaments, walls, where most galaxies concentrate, but also under-dense regions, called voids. The void regions and the galaxies within represent an ideal place for the study of galaxy formation and evolution as they are largely unaffected by the complex physical processes that transform galaxies in high-density environments. These void galaxies can hold the key as well to answer current challenges to the $\Lambda$CDM paradigm. The Calar Alto Void Integral-field Treasury surveY (CAVITY) is a Legacy project approved by the Calar Alto Observatory to obtain spatially resolved spectroscopic information of $\sim300$ void galaxies in the Local Universe (0.005 < z < 0.050) covering from -17.0 to -21.5 in $\rm r$ band absolute magnitude. It officially started in January 2021 and has been awarded 110 useful dark observing nights at the 3.5 m telescope using the PMAS spectrograph. Complementary follow-up projects including deep optical imaging, integrated, as well as resolved CO data, and integrated HI spectra, have joint the PMAS observations and naturally complete the scientific aim of characterising galaxies in cosmic voids. The extension data has been denominated CAVITY+. The data will be available to the whole community in different data releases, the first of which is planned for July 2024, and it will provide the community with PMAS data cubes for around 100 void galaxies through a user friendly, and well documented, database platform. We present here the survey, sample selection, data reduction, quality control schemes, science goals, and some examples of the scientific power of the CAVITY and CAVITY+ data., Comment: 19 pages, 11 figures. Accepted for publication in A&A - Replacement after A&A minor language edition

We make forecasts for the constraining power of the 1D Wavelet Scattering Transform (WST) when used with a Lyman-$\alpha$ forest cosmology survey. Using mock simulations and a Fisher matrix, we show that there is considerable cosmological information in the scattering transform coefficients not captured by the flux power spectrum. We estimate mock covariance matrices assuming uncorrelated Gaussian pixel noise for each quasar, at a level drawn from a simple lognormal model. The extra information comes from a smaller estimated covariance in the first-order wavelet power, and from second-order wavelet coefficients which probe non-Gaussian information in the forest. Forecast constraints on cosmological parameters from the WST are more than an order of magnitude tighter than for the power spectrum, shrinking a $4D$ parameter space by a factor of $10^6$. Should these improvements be realised with DESI, inflationary running would be constrained to test common inflationary models predicting $\alpha_s = - 6\times 10^{-4}$ and neutrino mass constraints would be improved enough for a $5-\sigma$ detection of the minimal neutrino mass.

HD235088 (TOI-1430) is a young star known to host a sub-Neptune-sized planet candidate. We validated the planetary nature of HD235088 b with multiband photometry, refined its planetary parameters, and obtained a new age estimate of the host star, placing it at 600-800 Myr. Previous spectroscopic observations of a single transit detected an excess absorption of He I coincident in time with the planet candidate transit. Here, we confirm the presence of He I in the atmosphere of HD235088 b with one transit observed with CARMENES. We also detected hints of variability in the strength of the helium signal, with an absorption of $-$0.91$\pm$0.11%, which is slightly deeper (2$\sigma$) than the previous measurement. Furthermore, we simulated the He I signal with a spherically symmetric 1D hydrodynamic model, finding that the upper atmosphere of HD235088 b escapes hydrodynamically with a significant mass loss rate of (1.5-5) $\times$10$^{10}$g s$^{-1}$, in a relatively cold outflow, with $T$=3125$\pm$375 K, in the photon-limited escape regime. HD235088 b ($R_{p}$ = 2.045$\pm$0.075 R$_{\oplus}$) is the smallest planet found to date with a solid atmospheric detection - not just of He I but any other atom or molecule. This positions it a benchmark planet for further analyses of evolving young sub-Neptune atmospheres., Comment: Accepted for publication in A&A. 17 pages, 18 figures

We present the PRIYA suite of cosmological simulations, based on the code and hydrodynamic model of the ASTRID simulation, and designed for cosmological analyses of the Lyman-$\alpha$ forest. Our simulation suite spans a $9$-dimensional parameter space, including $4$ cosmological parameters and $5$ astrophysical/thermal parameters. We have run $48$ low fidelity simulations with $1536^3$ particles in a $120$ Mpc/h box and $3$ high fidelity simulations with $3072^3$ particles in a $120$ Mpc/h box. All our simulations include a full physics model for galaxy formation, including supernova and AGN feedback, and thus also contain a realistic population of DLAs. We advance on earlier simulations suites by larger particle loads, by incorporating new physical models for patchy hydrogen and helium reionization, and by self-consistently incorporating a model for AGN feedback. We show that patchy helium reionization imprints an excess in the 1D flux power spectrum on large scales, which may allow future measurements of helium reionization bubble sizes. Simulation parameters are chosen based on a Latin hypercube design and a Gaussian process is used to interpolate to arbitrary parameter combinations. We build a multi-fidelity emulator for the 1D flux power spectrum and the mean IGM temperature. We show that our final interpolation error is $< 1\%$ and that our simulations produce a flux power spectrum converged at the percent level for $z=5.4$ - $2.2$. Our simulation suite will be used to interpret Lyman-$\alpha$ forest 1D flux power spectra from SDSS and future DESI data releases., Comment: 25 pages, 11 figures, matches version published in JCAP

We introduce MF-Box, an extended version of MFEmulator, designed as a fast surrogate for power spectra, trained using N-body simulation suites from various box sizes and particle loads. To demonstrate MF-Box's effectiveness, we design simulation suites that include low-fidelity suites (L1 and L2) at $256 \,\mathrm{Mpc}/h$ and $100 \,\mathrm{Mpc}/h$, each with $128^3$ particles, and a high-fidelity suite (HF) with $512^3$ particles at $256 \,\mathrm{Mpc}/h$, representing a higher particle load compared to the low-fidelity suites. MF-Box acts as a probabilistic resolution correction function, learning most of the cosmological dependencies from L1 and L2 simulations and rectifying resolution differences with just 3 HF simulations using a Gaussian process. MF-Box successfully emulates power spectra from our HF testing set with a relative error of $< 3\%$ up to $k \simeq 7 \,h/\mathrm{Mpc}$ at $z \in [0, 3]$, while maintaining a cost similar to our previous multi-fidelity approach, which was accurate only up to $z = 1$. The addition of an extra low-fidelity node in a smaller box significantly improves emulation accuracy for MF-Box at $k > 2 \,h/\mathrm{Mpc}$, increasing it by a factor of $10$. We conduct an error analysis of MF-Box based on computational budget, providing guidance for optimizing budget allocation per fidelity node. Our proposed MF-Box enables future surveys to efficiently combine simulation suites of varying quality, effectively expanding the range of emulation capabilities while ensuring cost efficiency., Comment: 19 pages, 16 figures. Match the MNRAS version. Data available at: https://github.com/jibanCat/MFBoxData, Code and tutorials available at: https://github.com/jibanCat/matter_emu_mfbox

Mitotic activity is a crucial proliferation biomarker for the diagnosis and prognosis of different types of cancers. Nevertheless, mitosis counting is a cumbersome process for pathologists, prone to low reproducibility, due to the large size of augmented biopsy slides, the low density of mitotic cells, and pattern heterogeneity. To improve reproducibility, deep learning methods have been proposed in the last years using convolutional neural networks. However, these methods have been hindered by the process of data labelling, which usually solely consist of the mitosis centroids. Therefore, current literature proposes complex algorithms with multiple stages to refine the labels at pixel level, and to reduce the number of false positives. In this work, we propose to avoid complex scenarios, and we perform the localization task in a weakly supervised manner, using only image-level labels on patches. The results obtained on the publicly available TUPAC16 dataset are competitive with state-of-the-art methods, using only one training phase. Our method achieves an F1-score of 0.729 and challenges the efficiency of previous methods, which required multiple stages and strong mitosis location information., Comment: Presented at IDEAL 2022

The detection of habitable worlds is one of humanity's greatest endeavors. So far, astrobiological studies show that one of the most critical components for life development is liquid water. Its chemical properties and its capacity to dissolve and hence transport other substances makes this constituent a key piece in the development of life. As a consequence, looking for life as we know it is directly related to the search for liquid water. For a remote detection of life in distant planetary systems, this means looking for planets in the so-called habitable zone. In this sense, K-dwarf stars are the perfect hosts. Contrary to G-dwarfs, the habitable zone is closer, thus making planet detection easier using transit or radial velocity techniques. Contrary to M-dwarfs, the stellar activity is much smaller, hence having a smaller impact in both the detectability and in the true habitability of the planet. Also, K-dwarfs are the quietest in terms of oscillations, and granulation noise. Despite this, there is a dearth of planets in the habitable zone of K-dwarfs due to a lack of observing programs devoted to this parameter space. In response to a call for Legacy Programs of the Calar Alto observatory, we have started the first dedicated and systematic search for habitable planets around K-dwarfs, the K-dwarfs Orbited By habitable Exoplanets (KOBE). This survey is monitoring the radial velocity of 50 carefully pre-selected K-dwarfs with the CARMENES instrument along 5 semesters with an average of 90 data points per target. Based on planet occurrence rates convolved with our detectability limits, we expect to find $1.68\pm 0.25$ planets per star in the KOBE sample and in half of the sample we expect to find one of those planets within the habitable zone. In this paper, we describe the project motivation, goals and target selection and preliminary stellar characterization., Comment: Accepted for publication in A&A. 12 pages, 9 figures, 1 table. Language corrected

Metal-halide perovskite nanocrystals have demonstrated excellent optoelectronic properties for light-emitting applications. Isovalent doping with various metals (M2+) can be used to tailor and enhance their light emission. Although crucial to maximize performance, an understanding of the universal working mechanism for such doping is still missing. Here, we directly compare the optical properties of nanocrystals containing the most commonly employed dopants, fabricated under identical synthesis conditions. We show for the first time unambiguously and supported by first principles calculations and molecular orbital theory that element-unspecific symmetry-breaking rather than element-specific electronic effects dominate these properties under device-relevant conditions. The impact of most dopants on the perovskite electronic structure is predominantly based on local lattice periodicity breaking and resulting charge carrier localization, leading to enhanced radiative recombination, while dopant-specific hybridization effects play a secondary role. Our results suggest specific guidelines for selecting a dopant to maximize the performance of perovskite emitters in the desired optoelectronic devices.