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We present the MULTIMODAL UNIVERSE, a large-scale multimodal dataset of scientific astronomical data, compiled specifically to facilitate machine learning research. Overall, the MULTIMODAL UNIVERSE contains hundreds of millions of astronomical observations, constituting 100\,TB of multi-channel and hyper-spectral images, spectra, multivariate time series, as well as a wide variety of associated scientific measurements and "metadata". In addition, we include a range of benchmark tasks representative of standard practices for machine learning methods in astrophysics. This massive dataset will enable the development of large multi-modal models specifically targeted towards scientific applications. All codes used to compile the MULTIMODAL UNIVERSE and a description of how to access the data is available at https://github.com/MultimodalUniverse/MultimodalUniverse, Comment: Accepted at NeurIPS Datasets and Benchmarks track

The communication control delay between the inverters and the power plant controller can be caused by several factors related to the communication link between them. Under undesirable conditions, high delay values can produce oscillations in the wind power plant that can affect the rest of the power system. In this work, we present a new robust methodology for wind turbines to estimate the value of the communication control delay using PMU data. Several scenarios are considered where external faults are simulated and the performance of the algorithm is evaluated based on dynamic state estimation of the mathematical model of the wind turbine. In this paper, we have shown that the characterization of the delay can be performed offering the transmission system operator an online tool to identify the most suited communication delay for the plant controller models used in dynamic studies.

We present a novel representation learning method for downstream tasks such as anomaly detection and unsupervised transient classification in high-energy datasets. This approach enabled the discovery of a new fast X-ray transient (FXT) in the Chandra archive, XRT 200515, a needle-in-the-haystack event and the first Chandra FXT of its kind. Recent serendipitous breakthroughs in X-ray astronomy, including FXTs from binary neutron star mergers and an extragalactic planetary transit candidate, highlight the need for systematic transient searches in X-ray archives. We introduce new event file representations, E-t Maps and E-t-dt Cubes, designed to capture both temporal and spectral information, effectively addressing the challenges posed by variable-length event file time series in machine learning applications. Our pipeline extracts low-dimensional, informative features from these representations using principal component analysis or sparse autoencoders, followed by clustering in the embedding space with DBSCAN. New transients are identified within transient-dominant clusters or through nearest-neighbor searches around known transients, producing a catalog of 3,539 candidates (3,427 flares and 112 dips). XRT 200515 exhibits unique temporal and spectral variability, including an intense, hard <10 s initial burst followed by spectral softening in an ~800 s oscillating tail. We interpret XRT 200515 as either the first giant magnetar flare observed at low X-ray energies or the first extragalactic Type I X-ray burst from a faint LMXB in the LMC. Our method extends to datasets from other observatories such as XMM-Newton, Swift-XRT, eROSITA, Einstein Probe, and upcoming missions like AXIS., Comment: 25 pages, submitted to Monthly Notices of the Royal Astronomical Society, presented at the 2023 Conference on Machine Learning in Astronomical Surveys (ML-IAP/CCA-2023)

The typically large distances, extinction, and crowding of Galactic supermassive star clusters have so far hampered the identification of their very low mass members, required to extend our understanding of star and planet formation, and early stellar evolution, to starburst. This situation has now evolved thanks to the James Webb Space Telescope (JWST), and its unmatched resolution and sensitivity in the infrared. In this paper, the third of the series of the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS), we present JWST/NIRCam and JWST/MIRI observations of the supermassive star cluster Westerlund 1. These observations are specifically designed to unveil the cluster members down to the BD mass regime, and to allow us to select and study the protoplanetary disks and to study the mutual feedback between the cluster members and the surrounding environment. Westerlund 1 was observed as part of JWST GO-1905 for 23.6 hours. The data have been reduced using the JWST calibration pipeline, together with specific tools necessary to remove artifacts. Source identification and photometry were performed with DOLPHOT. The MIRI images show a plethora of different features. Diffuse nebular emission is observed around the cluster, which is typically composed of myriads of droplet-like features pointing toward the cluster center or the group of massive stars surrounding the WR star W72/A. A long pillar is also observed in the NW. The MIRI images also show resolved shells and outflows surrounding the M-type RSG W20, W26, W75, and W237, the sgB[e] star W9 and the YHG W4. The color-magnitude diagrams built using the NIRCam photometry show a clear cluster sequence, which is marked in its upper part by the 1828 NIRCam stars with X-ray counterparts. NIRCam observations using the F115W filter have reached the 23.8 mag limit with 50\% completeness (roughly corresponding to a 0.06 Msol brown dwarf)., Comment: Accepted for publication in Astronomy & Astrophysics

We present HIP 8522, a young solar twin with the lowest detected lithium, potentially a field blue straggler or the result of episodic early accretion. Its stellar parameters ($T_{\rm eff} = 5729 \pm 7$ K, $\log g = 4.532 \pm 0.016$ dex, $\rm{[Fe/H]} = 0.005 \pm 0.010$ dex, $v_{t} = 1.08 \pm 0.02$ km s$^{-1}$) and chemical composition were determined via spectroscopic equilibrium using high resolution spectra ($R = 60~000-165~000$). The age of HIP 8522 was estimated to be an upper limit of $<$1 Gyr through isochrone fitting and was further confirmed using chemical clocks. Spectral synthesis of the lithium line at $\sim$6707.8 \AA\ yielded an upper lithium abundance limit of $A(\rm{Li}) <$ 0.8 dex. This value is unusually low for solar twins of similar age, which typically have $A(\rm{Li})$ values ranging from 2.0 to 3.3 dex, suggesting that $\sim$2 dex of lithium is missing. We investigate various scenarios, such as planet engulfment, sub-stellar mergers, and extra mixing. However, two distinct hypotheses provide plausible explanations for the significant depletion of lithium: one suggests that HIP 8522 is a field blue straggler formed by the merger of a close binary, while the other proposes that HIP 8522 experienced early episodic accretion. The young solar twin HIP 8522 presents an exceptional opportunity to rigorously test stellar evolution models and gain crucial insights into the internal mixing mechanisms responsible for the significant destruction of lithium.

Measurement of lithium abundances in solar-type stars have shown that standard models of stellar evolution are incapable of explaining the observed depletion as a function of stellar age. Beryllium is one of the lightest elements that can be measured in stellar photospheres, and it can be burned in relatively low temperatures. Studying its abundances as a function of stellar age can provide important constraints to stellar mixing models, as the level of depletion as a function of time will indicate how deep the photospheric material must be dredged to explain the observed abundances of both elements. In an effort to provide the most stringent constraints for non-standard stellar mixing models, we observed a sample of solar-twins and concomitantly analyzed their lithium and beryllium abundances. Unlike what is typically observed for lithium, we find that beryllium does not decrease as a function of stellar age, constraining models that predict burning of both materials. Based on our data, models that invoke convective overshoot and convective settling are preferred over typical rotationaly-induced mixing models, as the later burn Be in excess while the former do not. Previous works also proposed mixing due to gravity waves as a possible explanation for observed abundances, which can fit our data as well. We also confirm previous finds of an increase in Be abundance as a function of metallicity, indicative of galactic production via cosmic ray spallation., Comment: Submitted to AJ - Comments are welcome!

Over the last decade, studies of large samples of binary systems identified chemical anomalies, and showed that they might be attributed to planet formation or planet engulfment. However, both scenarios have primarily been tested in pairs without known exoplanets. In this work, we explore these scenarios in the newly detected planet-hosting wide binary TOI-1173 A/B (projected separation $\sim 11,400$ AU) using high-resolution MAROON-X and ARCES spectra. We determined photospheric stellar parameters both by fitting stellar models and via the spectroscopic equilibrium approach. Both analyses agree and suggest that they are cool main sequence stars located in the thin disc. A line-by-line differential analysis between the components (B$-$A) displays an abundance pattern in the condensation temperature plane where the planet-hosting star TOI-1173 A is enhanced in refractory elements such as iron by more than 0.05 dex. This suggests the engulfment of $\sim$18 M$_{\oplus}$ of rocky material in star A. Our hypothesis is supported by the dynamics of the system detailed in our companion paper Yana Galarza et al. 2024, which suggest that the Super-Neptune TOI-1173 A $b$ might have been delivered to its current short period ($\sim7$ days) through circulatization and von Zeipel-Lidov-Kozai mechanisms, thereby triggering the engulfment of inner rocky exoplanets., Comment: Accepted for publication in the Astronomical Journal on July 29, 2024

The Chandra Source Catalog (CSC) is a virtual X-ray astrophysics facility that enables both detailed individual source studies and statistical studies of large samples of X-ray sources detected in ACIS and HRC-I imaging observations obtained by the Chandra X-ray Observatory. The catalog provides carefully-curated, high-quality, and uniformly calibrated and analyzed tabulated positional, spatial, photometric, spectral, and temporal source properties, as well as science-ready X-ray data products. The latter includes multiple types of source- and field-based FITS format products that can be used as a basis for further research, significantly simplifying followup analysis of scientifically meaningful source samples. We discuss in detail the algorithms used for the CSC Release 2 Series, including CSC 2.0, which includes 317,167 unique X-ray sources on the sky identified in observations released publicly through the end of 2014, and CSC 2.1, which adds Chandra data released through the end of 2021 and expands the catalog to 407,806 sources. Besides adding more recent observations, the CSC Release 2 Series includes multiple algorithmic enhancements that provide significant improvements over earlier releases. The compact source sensitivity limit for most observations is ~5 photons over most of the field of view, which is ~2x fainter than Release 1, achieved by co-adding observations and using an optimized source detection approach. A Bayesian X-ray aperture photometry code produces robust fluxes even in crowded fields and for low count sources. The current release, CSC 2.1, is tied to the Gaia-CRF3 astrometric reference frame for the best sky positions for catalog sources., Comment: 66 pages, 17 figures, 16 tables, accepted for publication in The Astrophysical Journal Supplement Series

Aims.We conduct a high-precision differential abundance analysis of the remarkable binary system HD 240429/30 (Krios and Kronos, respectively), whose difference in metallicity is one of the highest detected in systems with similar components to date (approximately 0.20 dex). A condensation temperature TC trend study was performed to search for possible chemical signatures of planet formation. In addition, other potential scenarios have been proposed to explain this disparity. Methods. Fundamental atmospheric parameters (Te f f , log g, [Fe/H], vturb) were calculated using the latest version of the FUNDPAR code employing high resolution MAROON-X spectra. We applied a full line-by-line differential technique to measure the abundances of 26 elements in both stars with equivalent widths and spectral synthesis taking advantage of the non-solar scaled opacities. Results.We found a difference in metallicity of approximately 0.230 dex, being Kronos more metal rich than Krios. The analysis encompassed the examination of the diffusion effect and primordial chemical differences, concluding that the observed chemical discrepancies in the binary system cannot be solely attributed to any of these processes. The results also shown a noticeable excess of Li by approximately 0.56 dex in Kronos, and an enhancement of refractories with respect to Krios. A photometric study with TESS data was carried out, without finding any signal of possible transiting planets around the stars. Several potential planet formation scenarios were also explored to account for the observed excess in both metallicity and lithium in Kronos. Planetary engulfment is a plausible explanation, considering the ingestion of an exceptionally large mass, approximately approximately 27.8M_Earth, but no scenario is definitively ruled out., Comment: 11 pages, 6 figures

Boolean networks can be viewed as functions on the set of binary strings of a given length, described via logical rules. They were introduced as dynamic models into biology, in particular as logical models of intracellular regulatory networks involving genes, proteins, and metabolites. Since genes can have several modes of action depending on their expression levels, binary variables are often not sufficiently rich, requiring the use of multivalued networks instead. In this paper, we explore the multivalued generalization of Boolean networks by writing the standard $(\wedge, \vee, \lnot)$ operations on $\{0, 1\}$ in terms of the operations $(\odot, \oplus, \neg)$ on $\big\{0,\frac{1}{m}, \frac{2}{m}, \dots, \frac{m-1}{m}, 1\big\}$ from multivalued logic. We recall the basic theory of this mathematical framework, and give a novel algorithm for computing the fixed points that in many cases has essentially the same complexity as in the binary case. Our approach provides a biologically intuitive representation of the network. Furthermore, it uses tools to compute lattice points in rational polytopes, tapping a rich area of algebraic combinatorics as a source for combinatorial algorithms for network analysis. An implementation of the algorithm is provided., Comment: 25 pages. Several improvements throughout the text, including a new title, missing references, and new Theorem 32

With its 12 optical filters, the Javalambre-Photometric Local Universe Survey (J-PLUS) provides an unprecedented multicolor view of the local Universe. The third data release (DR3) covers 3,192 deg$^2$ and contains 47.4 million objects. However, the classification algorithms currently implemented in its pipeline are deterministic and based solely on the sources morphology. Our goal is classify the sources identified in the J-PLUS DR3 images into stars, quasi-stellar objects (QSOs), and galaxies. For this task, we present BANNJOS, a machine learning pipeline that uses Bayesian neural networks to provide the probability distribution function (PDF) of the classification. BANNJOS is trained on photometric, astrometric, and morphological data from J-PLUS DR3, Gaia DR3, and CatWISE2020, using over 1.2 million objects with spectroscopic classification from SDSS DR18, LAMOST DR9, DESI EDR, and Gaia DR3. Results are validated using $1.4 10^5$ objects and cross-checked against theoretical model predictions. BANNJOS outperforms all previous classifiers in terms of accuracy, precision, and completeness across the entire magnitude range. It delivers over 95% accuracy for objects brighter than $r = 21.5$ mag, and ~90% accuracy for those up to $r = 22$ mag, where J-PLUS completeness is < 25%. BANNJOS is also the first object classifier to provide the full probability distribution function (PDF) of the classification, enabling precise object selection for high purity or completeness, and for identifying objects with complex features, like active galactic nuclei with resolved host galaxies. BANNJOS has effectively classified J-PLUS sources into around 20 million galaxies, 1 million QSOs, and 26 million stars, with full PDFs for each, which allow for later refinement of the sample. The upcoming J-PAS survey, with its 56 color bands, will further enhance BANNJOS's ability to detail each source's nature., Comment: Submitted to Astronomy and Astrophysics. 29 pages, 23 figures, 4 tables

The matrix pencil method (MPM) is a well-known technique for estimating the parameters of exponentially damped sinusoids in noise by solving a generalized eigenvalue problem. However, in several cases, this is an ill-conditioned problem whose solution is highly biased under small perturbations. When the estimation is performed to classify the observed signal into two categories, the estimation errors induce several misclassifications. In this work we propose a novel signal classification criteria by exploiting the relationship between the generalized eigenvalue problem posed in the MPM and the numerical range of a pair of rectangular matrices. In particular, the classification test is formulated as a set inclusion problem, and no spectrum estimation is required. The technique is applied to a problem of electromagnetic scattering to classify dielectric materials using the scattering signal observed when a target is illuminated by an ultra-wideband signal. The performance of the classification scheme is assessed in terms of error rate and it is compared to another classification technique, the generalized likelihood rate test (GLRT)., Comment: Submitted for possible publication

The growing number of Milky Way satellites detected in recent years has introduced a new focus for stellar abundance analysis. Abundances of stars in satellites have been used to probe the nature of these systems and their chemical evolution. However, for most satellites, only centrally located stars have been examined. This paper presents an analysis of three stars in the Tucana V system, one in the inner region and two at $\sim$10\arcmin\ (7--10 half-light radii) from the center. We find a remarkable chemical diversity between the stars. One star exhibits enhancements in rapid neutron-capture elements (an $r$-I star), and another is highly enhanced in C, N, and O but with low neutron-capture abundances (a CEMP-no star). The metallicities of the stars analyzed span more than 1~dex from $\mathrm{[Fe/H]}=-3.55$ to $-2.46$. This, combined with a large abundance range of other elements like Ca, Sc, and Ni, confirms that Tuc~V is an ultra-faint dwarf (UFD) galaxy. The variation in abundances, highlighted by [Mg/Ca] ratios ranging from $+0.89$ to $-0.75$, among the stars, demonstrates that the chemical enrichment history of Tuc~V was very inhomogeneous. Tuc~V is only the second UFD galaxy in which stars located at large distances from the galactic center have been analyzed, along with Tucana~II. The chemical diversity seen in these two galaxies, driven by the composition of the non-central member stars, suggests that distant member stars are important to include when classifying faint satellites and that these systems may have experienced more complex chemical enrichment histories than previously anticipated., Comment: 19 pages, 11 figures, accepted for publication in ApJ

Among Neptunian mass exoplanets ($20-50$ M$_\oplus$), puffy hot Neptunes are extremely rare, and their unique combination of low mass and extended radii implies very low density ($\rho < 0.3$~g~cm$^{-3}$). Over the last decade, only a few puffy planets have been detected and precisely characterized with both transit and radial velocity observations, most notably including WASP-107~$b$, TOI-1420~$b$, and WASP-193 $b$. In this paper, we report the discovery of TOI-1173 A $b$, a low-density ($\rho = 0.195_{-0.017}^{+0.018}$~g~cm$^{-3}$) super-Neptune with $P = 7.06$ days in a nearly circular orbit around the primary G-dwarf star in the wide binary system TOI-1173 A/B. Using radial velocity observations with the MAROON-X and HIRES spectrographs and transit photometry from TESS, we determined a planet mass of $M_{\rm{p}} = 27.4\pm1.7\ M_{\oplus}$ and radius of $R_{\rm{p}} = 9.19\pm0.18\ R_{\oplus}$. TOI-1173 A $b$ is the first puffy Super-Neptune planet detected in a wide binary system (projected separation $\sim 11,400$~AU). We explored several mechanisms to understand the puffy nature of TOI-1173 A $b$, and showed that tidal heating is the most promising explanation. Furthermore, we demonstrate that TOI-1173 A $b$ likely has maintained its orbital stability over time and may have undergone von-Zeipel-Lidov-Kozai migration followed by tidal circularization given its present-day architecture, with important implications for planet migration theory and induced engulfment into the host star. Further investigation of the atmosphere of TOI-1173 A $b$ will shed light on the origin of close-in low-density Neptunian planets in field and binary systems, while spin-orbit analyses may elucidate the dynamical evolution of the system., Comment: Accepted for publication in the Astronomical Journal on June 2, 2024

Aims. We explore different scenarios to explain the chemical difference found in the remarkable giant-giant binary system HD 138202 + CD-30 12303. For the first time, we suggest how to distinguish these scenarios by taking advantage of the extensive convective envelopes of giant stars. Methods. We carried out a high-precision determination of stellar parameters and abundances by applying a full line-by-line differential analysis on GHOST high-resolution spectra. Results. We found a significant chemical difference between the two stars (0.08 dex), which is largely unexpected considering the insensitivity of giant stars to planetary ingestion and diffusion effects. We tested the possibility of engulfment events by using several different combinations of stellar mass, ingested mass, metallicity of the engulfed object and different convective envelopes. However, the planetary ingestion scenario does not seem to explain the observed differences. For the first time, we distinguished the source of chemical differences using a giant-giant binary system. By ruling out other possible scenarios such as planet formation and evolutionary effects between the two stars, we suggest that primordial inhomogeneities might explain the observed differences. This remarkable result implies that the metallicity differences that were observed in at least some main-sequence binary systems might be related to primordial inhomogeneities rather than engulfment events. We also discuss the important implications of finding primordial inhomogeneities, which affect chemical tagging and other fields such as planet formation. We strongly encourage the use of giant-giant pairs. They are a relevant complement to main-sequence pairs for determining the origin of the observed chemical differences in multiple systems. [abridged], Comment: 11 pages, 7 figures, 4 tables. A&A Letters accepted

The automatic classification of X-ray detections is a necessary step in extracting astrophysical information from compiled catalogs of astrophysical sources. Classification is useful for the study of individual objects, statistics for population studies, as well as for anomaly detection, i.e., the identification of new unexplored phenomena, including transients and spectrally extreme sources. Despite the importance of this task, classification remains challenging in X-ray astronomy due to the lack of optical counterparts and representative training sets. We develop an alternative methodology that employs an unsupervised machine learning approach to provide probabilistic classes to Chandra Source Catalog sources with a limited number of labeled sources, and without ancillary information from optical and infrared catalogs. We provide a catalog of probabilistic classes for 8,756 sources, comprising a total of 14,507 detections, and demonstrate the success of the method at identifying emission from young stellar objects, as well as distinguishing between small-scale and large-scale compact accretors with a significant level of confidence. We investigate the consistency between the distribution of features among classified objects and well-established astrophysical hypotheses such as the unified AGN model. This provides interpretability to the probabilistic classifier. Code and tables are available publicly through GitHub. We provide a web playground for readers to explore our final classification at https://umlcaxs-playground.streamlit.app., Comment: 21 pages, 11 figures. Accepted in MNRAS

Context. With a mass exceeding several 10^4 solar masses and a rich and dense population of massive stars, supermassive young star clusters represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions among stars. Aims. In this paper we present the "Extended Westerlund 1 and 2 Open Clusters Survey" (EWOCS) project, which aims to investigate the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars. The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun. Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically, the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec. Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation were carried out using the ACIS-Extract software. Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a photon flux threshold of approximately 2x10^-8 photons/cm^2/s. The X-ray sources exhibit a highly concentrated spatial distribution, with 1075 sources located within the central 1 arcminute. We have successfully detected X-ray emissions from 126 out of the 166 known massive stars of the cluster, and we have collected over 71000 photons from the magnetar CXO J164710.20-455217, Comment: The paper has been accepted for publication by Astronomy and Astrophysics

It has been suggested that $\beta$ Pic b has a supersolar metallicity and subsolar C/O ratio. Assuming solar carbon and oxygen abundances for the star $\beta$ Pic and therefore the planet's parent protoplanetary disk, $\beta$ Pic b's C/O ratio suggests that it formed via core accretion between its parent protoplanteary disk's H$_{2}$O and CO$_{2}$ ice lines. $\beta$ Pic b's high metallicity is difficult to reconcile with its mass $M_{\text{p}}~=~11.7~M_{\text{Jup}}$ though. Massive stars can present peculiar photospheric abundances that are unlikely to record the abundances of their former protoplanetary disks. This issue can be overcome for early-type stars in moving groups by infering the elemental abundances of the FGK stars in the same moving group that formed in the same molecular cloud and presumably share the same composition. We infer the photospheric abundances of the F dwarf HD 181327, a $\beta$ Pic moving group member that is the best available proxy for the composition of $\beta$ Pic b's parent protoplanetary disk. In parallel, we infer updated atmospheric abundances for $\beta$ Pic b. As expected for a planet of its mass formed via core-accretion beyond its parent protoplanetary disk's H$_{2}$O ice line, we find that $\beta$ Pic b's atmosphere is consistent with stellar metallicity and confirm that is has superstellar carbon and oxygen abundances with a substellar C/O ratio. We propose that the elemental abundances of FGK dwarfs in moving groups can be used as proxies for the otherwise difficult-to-infer elemental abundances of early-type and late-type members of the same moving groups., Comment: Accepted for publication, 17 pages, 6 figures,. arXiv admin note: text overlap with arXiv:2201.08508

The astronomical community is grappling with the increasing volume and complexity of data produced by modern telescopes, due to difficulties in reducing, accessing, analyzing, and combining archives of data. To address this challenge, we propose the establishment of a coordinating body, an "entity," with the specific mission of enhancing the interoperability, archiving, distribution, and production of both astronomical data and software. This report is the culmination of a workshop held in February 2023 on the Future of Astronomical Data Infrastructure. Attended by 70 scientists and software professionals from ground-based and space-based missions and archives spanning the entire spectrum of astronomical research, the group deliberated on the prevailing state of software and data infrastructure in astronomy, identified pressing issues, and explored potential solutions. In this report, we describe the ecosystem of astronomical data, its existing flaws, and the many gaps, duplication, inconsistencies, barriers to access, drags on productivity, missed opportunities, and risks to the long-term integrity of essential data sets. We also highlight the successes and failures in a set of deep dives into several different illustrative components of the ecosystem, included as an appendix., Comment: 59 pages; please send comments and/or questions to foadi@googlegroups.com

In this paper, we show how convolutional neural networks (CNN) can be used in regression and classification learning problems of noisy and non-noisy functional data. The main idea is to transform the functional data into a 28 by 28 image. We use a specific but typical architecture of a convolutional neural network to perform all the regression exercises of parameter estimation and functional form classification. First, we use some functional case studies of functional data with and without random noise to showcase the strength of the new method. In particular, we use it to estimate exponential growth and decay rates, the bandwidths of sine and cosine functions, and the magnitudes and widths of curve peaks. We also use it to classify the monotonicity and curvatures of functional data, algebraic versus exponential growth, and the number of peaks of functional data. Second, we apply the same convolutional neural networks to Lyapunov exponent estimation in noisy and non-noisy chaotic data, in estimating rates of disease transmission from epidemic curves, and in detecting the similarity of drug dissolution profiles. Finally, we apply the method to real-life data to detect Parkinson's disease patients in a classification problem. The method, although simple, shows high accuracy and is promising for future use in engineering and medical applications., Comment: 38 pages, 23 figures

We employ the corrected Gaia Early Data Release 3 (EDR3) photometric data and spectroscopic data from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR7 to assemble a sample of approximately 0.25 million FGK dwarf photometric standard stars for the 12 J-PLUS filters using the Stellar Color Regression (SCR) method. We then independently validated the J-PLUS DR3 photometry, and uncovered significant systematic errors: up to 15 mmag in the results of Stellar Locus (SL) method, and up to 10 mmag mainly caused by magnitude-, color-, and extinction-dependent errors of the Gaia XP spectra with the Gaia BP/RP (XP) Synthetic Photometry (XPSP) method. We have also further developed the XPSP method using the corrected Gaia XP spectra by Huang et al. (2023) and applied it to the J-PLUS DR3 photometry. This resulted in an agreement of 1-5 mmag with the SCR method, and a two-fold improvement in the J-PLUS zero-point precision. Finally, the zero-point calibration for around 91% of the tiles within the LAMOST observation footprint is determined through the SCR method, with the remaining approximately 9% of tiles outside this footprint relying on the improved XPSP method. The re-calibrated J-PLUS DR3 photometric data establishes a solid data foundation for conducting research that depends on high-precision photometric calibration., Comment: ApJS accepted; 21 papes; 20 figures, see main results in Figures 5 and 12

We present an extensive and well-characterized Chandra X-ray Galaxy Catalog (CGC) of 8557 galaxy candidates in the redshift range z ~ 0.04 - 0.7, optical luminosity 1010 - 1011 Lro, and X-ray luminosity (0.5-7 keV) LX = 2x1040 - 2x1043 erg s-1. We estimate ~5% false match fraction and contamination by QSOs. The CGC was extracted from the Chandra Source Catalog version 2 (CSC2) by cross-correlating with optical and IR all-sky survey data, including SDSS, PanSTARRS, DESI Legacy, and WISE. Our selection makes use of two main criteria that we have tested on the subsample with optical spectroscopical identification. (1) A joint selection based on X-ray luminosity (LX) and X-ray to optical flux ratio (FXO), which recovers 63% of the spectroscopically classified galaxies with a small contamination fraction (7%), a significant improvement over methods using LX or FXO alone (< 50% recovery). (2) A joint W1-W2 (W12) WISE color and LX selection that proves effective in excluding QSOs and improves our selection by recovering 72% of the spectroscopically classified galaxies and reducing the contamination fraction (4%). Of the CGC, 24% was selected by means of optical spectroscopy; 30% on the basis of LX, FXO, and W12; and 46% by using either the LX-FXO or the LX-W12 selection criteria. We have individually examined the data for galaxies with z < 0.1, which may include more than one CSC2 X-ray source, leading to the exclusion of 110 local galaxies. Our catalog also includes near-IR and UV data and galaxy morphological types., Comment: Accepted in ApJS, 37 pages, 11 figures; Minor revisions

X-ray bright optically normal galaxies (XBONGs) are galaxies with X-ray luminosities consistent with those of active galactic nuclei (AGNs) but no evidence of AGN optical emission lines. Crossmatching the Chandra Source Catalog version 2 (CSC2) with the Sloan Digital Sky Survey (SDSS) sample of spectroscopically classified galaxies, we have identified 817 XBONG candidates with LX > 1042 erg s-1 and X-ray to optical flux ratio FXO > 0.1. Comparisons with WISE colors and NIR, optical, UV, and radio luminosities show that the loci of XBONGs are in-between those of control samples of normal galaxies and quasars and are consistent with low-luminosity quasars. We find that 43% of the XBONG sample have X-ray colors suggesting NH > 1022 cm-2, double the fraction in the QSO sample, suggesting that a large fraction of XBONG are highly obscured AGNs. However, ~50% of the XBONGs are not obscured and have X-ray colors harder than those of normal galaxies. Some of these XBONGs have spatially extended X-ray emission. These characteristics suggest that they may be unidentified galaxy groups and clusters. Using the X-ray luminosity functions of QSOs and galaxies/groups/clusters, we estimate the approximate fraction of extended XBONGs to be < 20%. We also assess the approximate fraction of XBONGs whose AGN signatures are diluted by stellar light of host galaxies to be ~30%, based on their redshift and deviation from the extrapolation of the QSO LX-Lr relation., Comment: Accepted in ApJ. 33 pages, 17 figures; minor revisions

With the upcoming plethora of astronomical time-domain datasets and surveys, anomaly detection as a way to discover new types of variable stars and transients has inspired a new wave of research. Yet, the fundamental definition of what constitutes an anomaly and how this depends on the overall properties of the population of light curves studied remains a discussed issue. Building on a previous study focused on Kepler light curves, we present an analysis that uses the Unsupervised Random Forest to search for anomalies in TESS light curves. We provide a catalogue of anomalous light curves, classify them according to their variability characteristics and associate their anomalous nature to any particular evolutionary stage or astrophysical configuration. For anomalies belonging to known classes (e.g. eclipsing binaries), we have investigated which physical parameters drive the anomaly score. We find a combination of unclassified anomalies and objects of a known class with outlying physical configurations, such as rapid pulsators, deep eclipsing binaries of long periods, and irregular light curves due to obscuration in YSOs. Remarkably, we find that the set of anomalous types differ between the Kepler and TESS datasets, indicating that the overall properties of the parent population are an important driver of anomalous behaviour., Comment: 23 pages, 26 figures. Submitted to MNRAS