Locally authored papers of the past 5 days

Two detector modules with lithium aluminate targets were operated in the CRESST underground setup between February and June 2021. The data collected in this period was used to set the currently strongest cross-section upper limits on the spin-dependent interaction of dark matter (DM) with protons and neutrons for the mass region between 0.25 and 1.5 GeV/c$^2$. The data are available online. In this document, we describe how the data set should be used to reproduce our dark matter results.

A set of data from 68 cryogenic detectors operated in the CRESST dark matter search experiment between 2013 and 2019 was collected and labeled to train binary classifiers for data cleaning. Here, we describe the data set and how the trained models can be applied to new data. The data and models are available online.

The first JWST observations of SN 1987A provided clear evidence that a compact object is ionizing the innermost ejecta. Here we analyze a second epoch of JWST NIRSpec and MIRI/MRS observations to better characterize the properties of this region, aided by a higher spectral resolving power for the new NIRSpec data. We confirm the presence of the previously identified narrow lines from the central region; [Ar VI] 4.5292 $\mu$m, [Ar II] 6.9853 $\mu$m, [S IV] 10.5105 $\mu$m, and [S III] 18.7130 $\mu$m, and also identify similar components in [Ca V] 4.1585 $\mu$m, [Cl II] 14.3678 $\mu$m, and possibly [Fe II] 1.6440 $\mu$m. These lines are blueshifted by $\sim$ -250 km/s, while the emission region is spatially unresolved and located southeast of the center. The offset and blueshift could imply a kick velocity of $510 \pm 55$ km/s for the neutron star. We also identify [Ca IV] 3.2068 $\mu$m near the center, but it is displaced to the north and has a redshift of $\sim 700$ km/s. We find that scattering by dust in the ejecta with a typical grain size $\sim 0.3\ \mu$m can explain the [Ca IV] properties and the absence of other narrow lines at shorter wavelengths, while dust absorption is important at $\lambda \gtrsim 8\ \mu$m. Photoionization models for a pulsar wind nebula and a cooling neutron star are both compatible with the observations, with the exception of the [Fe II] feature. The two models primarily differ at short wavelengths, where new lines are expected to emerge over time as the optical depth of dust in the expanding ejecta decreases.

Aperture photometry is a fundamental technique widely used to obtain high-precision light curves in optical survey projects like Tianyu. However, its effectiveness is limited in crowded fields, and the choice of aperture size critically impacts photometric precision. To address these challenges, we propose DeepAP, an efficient and accurate two-stage deep learning framework for aperture photometry. Specifically, for a given source, we first train a Vision Transformer (ViT) model to assess its feasibility of aperture photometry. We then train the Residual Neural Network (ResNet) to predict its optimal aperture size. For aperture photometry feasibility assessment, the ViT model yields an ROC AUC value of 0.96, and achieves a precision of 0.974, a recall of 0.930, and an F1 score of 0.952 on the test set. For aperture size prediction, the ResNet model effectively mitigates biases inherent in classical growth curve methods by adaptively selecting apertures appropriate for sources of varying brightness, thereby enhancing the signal-to-noise ratio (SNR) across a wide range of targets. Meanwhile, some samples in the test set have a higher SNR than those obtained by exhaustive aperture size enumeration because of the finer granularity of aperture size estimation. By integrating ResNet with the ViT network, the DeepAP framework achieves a median total processing time of 18 milliseconds for a batch of 10 images, representing a speed-up of approximately 59000 times compared to exhaustive aperture size enumeration. This work paves the way for the automatic application of aperture photometry in future high-precision surveys such as Tianyu and LSST. The source code and model are available at this https URL.

We assemble a homogeneous database of precise and consistent determinations of effective temperature, surface gravity, projected rotational rate, and macro- and micro-turbulent velocities for over 1800 Galactic stars spanning spectral types O to K and luminosity classes I to V. By carefully minimizing biases due to target selection, data quality, and disparate analysis techniques, we carry out statistical tests and comparative analyses to probe potential dependencies between these parameters and micro-turbulence. Our findings indicate that photospheric micro-turbulence is a genuine physical phenomenon rather than a modelling artifact. A direct comparison between observed micro-turbulent velocities and corresponding theoretical predictions for the turbulent pressure fraction strongly suggests that this phenomenon most likely arises from photospheric motions driven by envelope convection zones, with an additional pulsational component likely operating in main-sequence B stars. We show that neglecting micro-turbulent broadening in Fourier transform analyses can partly explain the dearth of slow rotators and the scarcity of stars with extremely low macro-turbulent velocity. We argue that including micro-turbulent pressure in atmospheric modelling can significantly mitigate (even resolve) the mass discrepancy for less massive O stars. Our database offers a valuable resource for testing and refining theoretical scenarios, particularly those addressing puzzling phenomena in hot massive stars.

The fifth-generation Sloan Digital Sky Survey (SDSS-V) is conducting the first all-sky low-resolution spectroscopic survey of the Milky Way's stellar halo. We describe the stellar parameter pipeline for the SDSS-V halo survey, which simultaneously models spectra, broadband photometry, and parallaxes to derive stellar parameters, metallicities, alpha abundances, and distances. The resulting BOSS-MINESweeper catalog is validated across a wide range of stellar parameters and metallicities using star clusters and a comparison to high-resolution spectroscopic surveys. We demonstrate several scientific capabilities of this dataset: identifying the most chemically peculiar stars in our Galaxy, discovering and mapping distant halo substructures, and measuring the all--sky dynamics of the Milky Way on the largest scales. The BOSS-MINESweeper catalog for SDSS DR19 is publicly available and will be updated for future data releases.

The Tianlai Cylinder Pathfinder Array consists of three adjacent cylindrical reflectors fixed on the ground, each 40 meters long and 15 meters wide, with the cylinder axis oriented along the North-South (N-S)direction. Dual linear polarisation feeds are distributed along the focus line, parallel to the cylinder axis. Measurement of the primary beam profile of these cylindrical reflectors is difficult, as they are too large to be placed in an anechoic chamber. While the beam profile along the East-West (E-W) direction can be measured with the transit observations of bright astronomical radio sources, the beam profile along the N-S direction remains very uncertain. We present a preliminary measurement of the beam profile of the Tianlai cylindrical antenna along both the N-S direction and E-W direction in the frequency range of 700-800 MHz, using a calibrator source carried by an unmanned aerial vehicle (UAV) flying in the far field. The beam profile of the Tianlai cylindrical antenna is determined from the analysis of the auto-correlation signals from the the cylinder array correlator, taking into account the emitter antenna beam profile, itself measured with a dipole antenna on the ground. The accuracy of the UAV-based determination of the cylinder beam profiles is validated by comparing the results with the one derived from bright astronomical source transits, and with simulated beams.

We present photometric and spectroscopic observations of SN 2024gy, a Type Ia supernova (SN Ia) exhibiting high-velocity features (HVFs) in its early-time spectra. This SN reaches a peak $B$-band magnitude of $-19.25 \pm 0.28$ mag and subsequently declines by $\Delta m_{15}(B) \approx 1.12$ mag, consistent with the luminosity-width relation characteristic of normal SNe Ia. Based on the peak thermal luminosity of $(1.2 \pm 0.3) \times 10^{43}$ erg s$^{-1}$, we estimate that $0.57 \pm 0.14~\rm M_{\odot}$ of $^{56}$Ni was synthesized during the explosion. Our dense early spectral monitoring revealed significant velocity disparities within the ejecta. Notably, absorption features from the \CaII\ near-infrared triplet were observed at velocities exceeding 25,000 km s$^{-1}$, while the \SiII\, \ld 6355 line velocity at the same epoch was significantly lower at $\sim$ 16,000 km s$^{-1}$. This velocity disparity likely reflects distinct ionization states of intermediate-mass elements in the outermost layers. The prominent \CaII\, HVFs may originate from ionization suppression within the highest-velocity ejecta, potentially indicative of minimal hydrogen mixing in a delayed-detonation explosion scenario. Additionally, the Ni/Fe ratio derived from the nebular spectrum of SN 2024gy provides further support for this model.

Context. Active galactic nuclei (AGNs) and star forming galaxies (SFGs) are the primary sources of extragalactic radio sky. But it is difficult to distinguish the radio emission produced by AGNs from that by SFGs, especially when the radio sources are faint. Best et al. (2023) classified the radio sources in LoTSS Deep Fields DR1 through multiwavelength SED fitting. With the classification results of them, we perform a supervised machine learning to distinguish radio AGNs and radio SFGs. Aims. We aim to provide a supervised classifier to identify radio AGNs, which can get both high purity and completeness simultaneously, and can easily be applied to datasets of large-area surveys. Methods. The classifications of Best et al. (2023) are used as the true labels for supervised machine learning. With the cross-matched sample of LoTSS Deep Fields DR1, AllWISE and Gaia DR3, the features of optical and mid-infrared magnitude and colors, are applied to train the classifier. The performance of the classifier is evaluated mainly by the precission, recall and F1 score of both AGNs and non-AGNs. Results. By comparing the performance of six learning algorithms, CatBoost is chosen to construct the best classifier. The best classifier get precision = 0.974, recall = 0.865 and F1 = 0.916 for AGNs, precision = 0.936, recall = 0.988 and F1 = 0.961 for non-AGNs. After applying our classifier to the cross-matched sample of LoTSS DR2, AllWISE and Gaia DR3, we obtain a sample of 49716 AGNs and 102261 non-AGNs. The reliability of these classification results is confirmed by comparing with the spectroscopic classification of SDSS. The precission and recall of AGN sample can be as high as 94.2% and 92.3%, respectively. We also train a model to identify radio excess sources. The F1 scores are 0.610 and 0.965 for sources with and without radio excess, respectively.

We present space-based very long baseline interferometry observations of the BL Lac type object OJ 287 taken with RadioAstron at 22 GHz on April 25, 2016, in conjunction with a ground array comprising 27 radio telescopes. We detect ground-space fringes at projected baselines extending up to 4.6 Earth diameters, which allowed us to image the jet in OJ 287 with an angular resolution of ~47 {\mu}as. Applying an advanced regularized maximum likelihood imaging method, we resolved the innermost jet structure with a complex morphology at a resolution of ~15 {\mu}as (~0.1 pc projected distance). For the first time, due to a favorable geometrical position of the jet in tandem with high data quality, we detect multiple sharp bends that form a "ribbon-like" jet structure that extends down to 1 mas. Two-dimensional Gaussian model-fitting reveals regions of the jet with brightness temperatures of more than 10^13 K, indicative of strong Doppler boosting. Polarimetric imaging reveals that the electric vector position angles are predominantly perpendicular to the innermost jet direction, implying a dominant poloidal magnetic field component near the central engine. Complementary multi-epoch Very Long Baseline Array observations at 43 GHz provide a multifrequency view of the jet evolution. Ridgeline analysis of the 43 GHz data shows significant variations in the jet position angle from 2014 to 2017, behavior consistent with a rotating helical jet structure. Finally, we confirm the emergence of a new jet component (B15 or K), which may be associated with the source's first TeV flare, and offer new observational constraints relevant to models involving a supermassive black hole binary.

Primordial non-Gaussianity is predicted by various inflationary models, and N-body simulations are a crucial tool for studying its imprints on large-scale structure. In this work, we present \texttt{GENGARS} ( GEnerator of Non-Gaussian ARbitrary Shapes), a framework for generating accurate non-Gaussian initial conditions for N-body simulations. It builds upon the formulation introduced by Wagner \& Verde (2012), enabling to generate a primordial gravitational potential with a desired separable bispectrum $B_{\Phi}(k_1,k_2,k_3)$. For the local, equilateral and orthogonal non-Gaussian templates, we benchmark our method against the well-established \texttt{2LPT-PNG} code. We show that \texttt{GENGARS} achieves improved accuracy and lower noise by suppressing spurious contributions to the primordial power spectrum. This paper aims at presenting the method, quantifying its performance and illustrating the benefits and applicable use cases over existing approaches.

Tidal features from galaxy mergers, particularly stellar streams, offer valuable insights into galaxy assembly and dark matter halo properties. This paper aims to identify a large sample of nearby stellar streams suitable for detailed modelling and comparison with simulations to enable population-level constraints on halo properties. We visually inspect and compile a tidal feature catalogue for $19,387$ galaxies with redshift $z \leq 0.02$ from the Siena Galaxy Atlas 2020 using original, model, and residual images from the DESI Legacy Imaging Surveys. Residual images, produced by subtracting models of all sources, enhance the detectability of faint asymmetries such as tidal features. We find that $11.9 \pm 0.2\%$ of galaxies host tidal features, more frequently around early-type than late-type galaxies. The tidal feature fraction increases with stellar mass, from $2.4 \pm 0.4\%$ at $\sim10^8$M$_\odot$ to $36.5 \pm 1.2\%$ at $\sim 5\times10^{11}$M$_\odot$. From this, we present the first release of STRRINGS: STReams in Residual Images of Nearby GalaxieS, a subsample of 35 galaxies with long, narrow streams suitable for modelling. We segment these streams and derive their geometry, surface brightness, colours, and stellar masses. The median $g$-band surface brightness is 26.8 mag$\,$arcsec$^{-2}$, reaching 27.5 mag$\,$arcsec$^{-2}$ for the faintest stream. Mass ratios are consistent with minor mergers, and we identify five potential dwarf galaxy progenitors. Our streams are typically longer (median 124 kpc) than the literature, with comparable widths. Stream mass correlates with length and colour, and wider streams lie at larger galactocentric radii. STRRINGS will be expanded and used to constrain halo properties in future work.

Trans-Neptunian objects (TNOs) with large perihelion distances ($q > 60$ au) and semi-major axes ($a > 200$ au) provide insights into the early evolution of the solar system and the existence of a hypothetical distant planet. These objects are still rare and their detection is challenging, yet they play a crucial role in constraining models of solar system formation. Here we report the discovery of a Sedna-like TNO, 2023\,KQ$_{14}$, nicknamed `Ammonite', with $q = 66$ au, $a = 252$ au, and inclination $i=11^\circ$. Ammonite's orbit does not align with those of the other Sedna-like objects and fills the previously unexplained `$q$-gap' in the observed distribution of distant solar system objects. Simulations demonstrate that Ammonite is dynamically stable over 4.5 billion years. % with less than 1\% variation in its semi-major axis. Our analysis suggests that Ammonite and the other Sedna-like objects may have shared a primordial orbital clustering around 4.2 billion years ago. Furthermore, Ammonite's stable orbit favors larger orbits ($\sim$ 500 au) rather than closer ones for a large hypothetical planet in present-day trans-Neptunian space.

PARSEC v2.0 rotating stellar tracks were previously presented for six values of metallicity from subsolar to solar values, with initial rotation rates ($\omega_\mathrm{i}$, defined as the ratio of angular velocity and its critical value) spanning from the non-rotating case to very near the critical velocity (i.e. $\omega_\mathrm{i}=0.99$), and for initial masses covering the $\sim 0.7 M_\odot$ to $14 M_\odot$ interval. Furthermore, we provided the corresponding isochrones converted into several photometric systems, for different inclination angles between the line-of-sight and the rotation axes, from $0^\circ$ (pole-on) to $90^\circ$ (equator-on). In this work, we expand this database with seven other sets of metallicity, including five sets of low metallicity ($Z=0.0001-0.002$) and two sets of super-solar values (up to $Z=0.03$). Here, we present the new stellar tracks, comprising $\sim$3\,040 tracks in total ($\sim$5\,500 including previous sets), along with the new corresponding rotating isochrones. We also introduce the possibility of creating isochrones, by interpolation, for values of rotating rates not available in the initial set of tracks. We compare a selection of our new models with rotating stellar tracks from the Geneva Stellar Evolution Code, and we assess the quality of our new tracks by fitting the colour-magnitude diagram of the open cluster NGC6067. We take advantage of the projected rotational velocity of member stars measured by Gaia to validate our results and examine the surface oxygen abundances in comparison with the observed data. All newly computed stellar tracks and isochrones are retrievable via our dedicated web databases and interfaces.

Upcoming ground and space-based surveys are poised to illuminate low surface brightness tidal features, providing a new observable connection to dark matter physics. From imaging of tidal debris, the morphology of stellar streams can be used to infer the geometry of dark matter halos. In this paper, we develop a generative approach, X-Stream, which translates stream imaging into constraints on the radial density profile of dark matter halos--from the inner region out to the virial radius. Using the GPU-accelerated code streamsculptor, we generate thousands of stream realizations in trial gravitational potentials and apply nested sampling with a custom objective function to explore viable regions of parameter space. We find that multiple stellar streams can be used to constrain the entire radial density profile of a halo, including both its inner and outer density slopes. These constraints provide a test for alternatives to cold dark matter, such as self-interacting dark matter, which predicts cored density profiles. From cosmological simulations, the outer density slope is expected to correlate with merger histories though remains underexplored observationally. With ongoing and upcoming missions such as Euclid, the Rubin Observatory, ARRAKIHS, and the Nancy Grace Roman Space Telescope, X-Stream will enable detailed mapping of dark matter for thousands of galaxies across a wide range of redshifts and halo masses.

We present the first astrophysical detection of methanol (CH3OH) in the torsional band near 25 um. Using high resolution mid-infrared (MIR) spectroscopy, we identified over seventy gas-phase CH3OH absorption lines between 20 and 28 um towards the massive protostar NGC 7538 IRS 1 with SOFIA/EXES. We derive a temperature of 180 K and a total column density of 2 x 10^17 cm-2, comparable to sub-mm measurements. Complementary analysis of acetylene (C2H2) absorption lines is also included. Both CH3OH and C2H2 reveal an unresolved second velocity component. These MIR absorption lines likely probe the molecular material in two edge-on disks, supporting the scenario that NGC 7538 IRS 1 consists of multiple protostars. We provide an updated line list for the torsional band of CH3OH, which was generated from lab work and model calculations. This discovery and the updated line list will enable the search for CH3OH in JWST/MIRI spectra.

We investigate how dust foreground complexity can affect measurements of the tensor-to-scalar ratio, $r$, in the context of the Simons Observatory, using a cross-spectrum component separation analysis. Employing a suite of simulations with realistic Galactic dust emission, we find that spatial variation in the dust frequency spectrum, parametrized by $\beta_d$, can bias the estimate for $r$ when modeled using a low-order moment expansion to capture this spatial variation. While this approach performs well across a broad range of dust complexity, the bias increases with more extreme spatial variation in dust frequency spectrum, reaching as high as $r\sim0.03$ for simulations with no primordial tensors and a spatial dispersion of $\sigma(\beta_d)\simeq0.3$ -- the most extreme case considered, yet still consistent with current observational constraints. This bias is driven by changes in the $\ell$-dependence of the dust power spectrum as a function of frequency that can mimic a primordial $B$-mode tensor signal. Although low-order moment expansions fail to capture the full effect when the spatial variations of $\beta_d$ become large and highly non-Gaussian, our results show that extended parametric methods can still recover unbiased estimates of $r$ under a wide range of dust complexities. We further find that the bias in $r$, at the highest degrees of dust complexity, is largely insensitive to the spatial structure of the dust amplitude and is instead dominated by spatial correlations between $\beta_d$ and dust amplitude, particularly at higher orders. If $\beta_d$ does spatially vary at the highest levels investigated here, we would expect to use more flexible foreground models to achieve an unbiased constraint on $r$ for the noise levels anticipated from the Simons Observatory.