Stellar Spectra Research Articles

Laboratory confirmation and improved accuracy of 4f and 5d energy levels of Fe II previously identified from stellar spectra

Laboratory confirmation and improved accuracy of 4f and 5d energy levels of Fe II previously identified from stellar spectra

Inferring stellar parameters and their uncertainties from high-resolution spectroscopy using invertible neural networks

New spectroscopic surveys will increase the number of astronomical objects in need of characterisation by more than an order of magnitude. Machine learning tools are required to address this data deluge in a fast and accurate fashion. Most machine learning algorithms cannot directly estimate error, making them unsuitable for reliable science. We aim to train a supervised deep-learning algorithm tailored for high-resolution observational stellar spectra. This algorithm accurately infers precise estimates while providing coherent estimates of uncertainties by leveraging information from both the neural network and the spectra. We trained a conditional invertible neural network (cINN) on observational spectroscopic data obtained from the GIRAFFE spectrograph (HR10 and HR21 setups) within the Gaia-ESO survey. A key feature of cINN is its ability to produce the Bayesian posterior distribution of parameters for each spectrum. By analysing this distribution, we inferred stellar parameters and their corresponding uncertainties. We carried out several tests to investigate how parameters are inferred and errors are estimated. We achieved an accuracy of 28K in $T_ eff $, 0.06 dex in $ g$, 0.03 dex in Fe/H $, and between 0.05 dex and 0.17 dex for the other abundances for high-quality spectra. Accuracy remains stable with low signal-to-noise ratio (between 5 and 25) spectra, with an accuracy of 39K in $T_ eff $, 0.08 dex in $ g$, and 0.05 dex in Fe/H $. The uncertainties obtained are well within the same order of magnitude. The network accurately reproduces astrophysical relationships both on the scale of the Milky Way and within smaller star clusters. We created a table containing the new parameters generated by our cINN. This neural network represents a compelling proposition for future astronomical surveys. These derived uncertainties are coherent and can therefore be reused in future works as Bayesian priors.

Spectroscopic study of late-type emission-line stars using the data from LAMOST DR6

Abstract Low-mass emission-line stars belong to various evolutionary stages, from pre-main-sequence young stars to evolved stars. In this work, we present a catalog of late-type (F0 to M9) emission-line stars from the LAMOST Data Release 6. Using the scipy package, we created a Python code that finds the emission peak at H-alpha in all late-type stellar spectra. A dataset of 38,152 late-type emission-line stars was obtained after a rigorous examination of the photometric quality flags and the signal-to-noise ratio of the spectra. Adopting well-known photometric and spectroscopic methods, we classified our sample into 438 infrared excess sources, 4,669 post-main-sequence candidates, 9,718 Fe/Ge/Ke sources, and 23,264 dMe sources. From a cross-match with known databases, we found that 29,213 sources, comprising 56 IR excess sources, 7,899 Fe/Ge/Ke stars, 17,533 dMe stars, and 3,725 PtMS candidates, are new detections. We measured the equivalent width of the major emission lines observed in the spectra of our sample of emission-line stars. Furthermore, the trend observed in the line strengths of major emission lines over the entire late-type spectral range is analyzed. We further classified the sample into 4 groups based on the presence of Hydrogen and Calcium emission lines. This work presents a large dataset of late-type emission-line stars which improves the current sample to study active phenomena in late-type stars.

Spectrum and energy levels of the high-lying singly excited configurations of Nd III. New Nd III experimental energy levels and wavelengths, with transition probability and ionisation energy calculations

We aim to accurately determine bound-to-bound transition wavelengths and energy levels of the high-lying open-shell configurations 4f$^3$7s, 4f$^3$6d, and 4f$^3$5f of doubly ionised neodymium (Nd III, $Z=60$) through high-resolution spectroscopy and semi-empirical calculations. This study is motivated by lanthanide atomic data requirements in astronomy, such those involved in investigations of kilonova spectra. Fourier transform spectra of Nd Penning and hollow cathode discharge lamps were recorded within the region 32\,500--54\,000 and grating spectra of Nd vacuum sliding sparks were recorded within the regions 820--1159 and 1600--3250 . New energy levels were found using the observed wavelengths measured accurate to a few parts in $10^8$ in Fourier transform spectra and to a few parts in $10^7$ in grating spectra. Atomic structure and transition probability calculations of Nd III were carried out using the Cowan codes, where energy parameters were adjusted to fit all known Nd III levels. Finally, Nd-rich stellar spectra were also used to aid in the analysis. In total, 355 transitions were classified from observed spectra involving 116 previously experimentally unknown energy levels of the 4f$^3$7s, 4f$^3$6d, and 4f$^3$5f configurations of Nd III, all reported here for the first time. Three newly identified levels of the 4f$^3$5d configuration and one newly identified 4f$^4$ level are also reported. Typical level energy uncertainties are 0.01 cm$^ $ for the 4f$^3$7s and 4f$^3$6d levels and 0.3 cm$^ $ for the 4f$^3$5f levels. In addition, calculated energy levels up to 130\,936 $ are presented, including eigenvector composition and calculated level lifetimes. Calculated transition probabilities and wavelengths between 1900--50\,000 are also given. Using newly established levels of the 4f$^3$7s configuration and the recently established levels of the 4f$^3$6s configuration, the ionisation energy of Nd III has been estimated at $178\,090 $. This result offers up to twice the accuracy of the most recently published value.

The ANTARESS workflow

High-resolution spectrographs open a detailed window onto the atmospheres of stars and planets. As the number of systems observed with different instruments grows, it is crucial to develop a standard in analyzing spectral time series of exoplanet transits and occultations, for the benefit of reproducibility. Here, we introduce the ANTARESS workflow, a set of methods aimed at processing high-resolution spectroscopy datasets in a robust way and extracting accurate exoplanetary and stellar spectra. While a fast preliminary analysis can be run on order-merged 1D spectra and cross-correlation functions (CCFs), the workflow was optimally designed for extracted 2D echelle spectra to remain close to the original detector counts, limit the spectral resampling, and propagate the correlated noise. Input data from multiple instruments and epochs were corrected for relevant environmental and instrumental effects, processed homogeneously, and analyzed independently or jointly. In this first paper, we show how planet-occulted stellar spectra extracted along the transit chord and cleaned from planetary contamination provide a direct comparison with theoretical stellar models and enable a spectral and spatial mapping of the photosphere. We illustrate this application of the workflow to archival ESPRESSO data, using the Rossiter-McLaughlin effect Revolutions (RMR) technique to confirm the spin-orbit alignment of HD 209458b and unveil biases in WASP-76b’s published orbital architecture. Because the workflow is modular and its concepts are general, it can support new methods and be extended to additional spectrographs to find a range of applications beyond the proposed scope. In a companion paper, we will present how planet-occulted spectra can be processed further to extract and analyze planetary spectra decontaminated from the star, providing clean and direct measurements of atmospheric properties.

Spectral reconstruction for radiation hydrodynamic simulations of galaxy evolution

Radiation from stars and active galactic nuclei (AGN) plays an important role in galaxy formation and evolution, and profoundly transforms the intergalactic, circumgalactic, and interstellar medium (IGM, CGM, and ISM). On-the-fly radiative transfer (RT) has started being incorporated in cosmological simulations, but the complex evolving radiation spectra are often crudely approximated with a small number of broad bands with piece-wise constant intensity and a fixed photo-ionisation cross-section. Such a treatment is unable to capture the changes to the spectrum as light is absorbed while it propagates through a medium with non-zero opacity. This can lead to large errors in photo-ionisation and heating rates. In this work we present a novel approach of discretising the radiation field at discrete photon energies, at the edges of the typically used photo-ionising bands, in order to capture the power-law slope of the radiation field. In combination with power-law approximations for the photo-ionisation cross-sections, this model allows us to self-consistently combine radiation from sources with different spectra and accurately follow the ionisation states of primordial and metal species through time. The method is implemented in GASOLINE2 in connection with TREVR2, a fast reverse ray tracing algorithm with 𝒪(Nactive log2 N) scaling. We compare our new piece-wise power-law reconstruction to the piece-wise constant method in calculating the primordial chemistry photo-ionisation and heating rates under an evolving UV background (UVB) and stellar spectrum, and find that our method reduces errors significantly, by up to two orders of magnitude in the case of HeII ionisation. We apply our new spectral reconstruction method in RT post-processing of a cosmological zoom-in simulation, MUGS2 g1536, including radiation from stars and a live UVB, and find a significant increase in total neutral hydrogen (HI) mass in the ISM and the CGM due to shielding of the UVB and a low escape fraction of the stellar radiation. This demonstrates the importance of RT and an accurate spectral approximation in simulating the CGM-galaxy ecosystem.

Probing Na in giant exoplanets with ESPRESSO and 3D NLTE stellar spectra

Neutral sodium was the first atom that was detected in an exoplanetary atmosphere using the transmission spectroscopy technique. To date, it remains the most successfully detected species due to its strong doublet in the optical at 5890\ A and 5896\ A . However, the center-to-limb variation (CLV) of these lines in the host star can bias the Na I detection. When combined with the Rossiter-McLaughlin (RM) effect, the CLV can mimic or obscure a planetary absorption feature if it is not properly accounted for. This work aims to investigate the impact of three-dimensional (3D) radiation hydrodynamic stellar atmospheres and non-local thermodynamic equilibrium (NLTE) radiative transfer on the modeling of the CLV+RM effect in single-line transmission spectroscopy to improve the detection and characterization of exoplanet atmospheres. We produced a grid of 3D NLTE synthetic spectra for Na I for FGK-type dwarfs within the following parameter space: $T_ eff =4500-6500$\,K, $ g =4.0-5.0$, and Fe/H . This grid was then interpolated to match the stellar parameters of four stars hosting well-known giant exoplanets, generating stellar spectra to correct for the CLV+RM effect in their transmission spectra. We used archival observations taken with the high-resolution ESPRESSO spectrograph. Our work confirms the Na I detections in three systems, namely WASP-52b, WASP-76b, and WASP-127b, also improving the accuracy of the measured absorption depth. Furthermore, we find that 3D NLTE stellar models can explain the spectral features in the transmission spectra of HD 209458b without the need for any planetary absorption. In the grid of stellar synthetic spectra, we observe that the CLV effect is stronger for stars with low $T_ eff $ and high $ g$. However, the combined effect of CLV and RM is highly dependent on the orbital geometry of the planet-star system. With the continuous improvement of instrumentation, it is crucial to use the most accurate stellar models available to correct for the CLV+RM effect in high-resolution transmission spectra to achieve the best possible characterization of exoplanet atmospheres. This will be fundamental in preparation for instruments such as ANDES at the Extremely Large Telescope to fully exploit its capabilities in the near future. We make our grid of 3D NLTE synthetic spectra for Na I publicly available.

Population of excited levels of Fe+, Ni+, and Cr+ in exocomets’ gaseous tails

The star β Pictoris is widely known for harbouring a large population of exocomets, which create variable absorption signatures in the stellar spectrum as they transit the star. Although the physical and chemical properties of these objects have long been elusive, the recently developed exocomet curve of growth technique has, for the first time, enabled estimates of exocometary column densities and excitation temperatures, based on absorption measurements in mutliple spectral lines. Using this new tool, we present a refined study of a β Pic exocomet observed on December 6, 1997 with the Hubble Space Telescope. We first show that the comet’s signature in Fe II lines is well explained by the transit of two gaseous components, with different covering factors and opacities. Then, we show that the studied comet is detected in the lines of other species, such as Ni II and Cr II. These species are shown to experience similar physical conditions as Fe II (same radial velocity profiles and same excitation temperatures), hinting that they are well mixed. Finally, using almost 100 Fe II lines rising from energy levels between 0 and 33 000 cm–1, we derive the complete excitation diagram of Fe+ in the comet. The transiting gas is found to be populated at an excitation temperature of 8190 ± 160 K, very close to the stellar effective temperature (8052 K). Using a model of radiative and collisional excitation, we show that the observed excitation diagram is compatible with a radiative regime, associated with a close transit distance (≤60 R⋆ ∼ 0.43 au) and a low electronic density (≤107 cm–3). In this regime, the excitation of Fe+ is controlled by the stellar flux, and does not depend on the local electronic temperature or density. These results allow us to derive the Ni+/Fe+ and Cr+/Fe+ ratios in the December 6, 1997 comet, at 8.5 ± 0.8 ⋅ 10–2 and 1.04 ± 0.15 ⋅10–2, respectively, close to solar abundances.

High-resolution transmission spectroscopy of the hot-Saturn HD 149026b

Advances in modern technology have enabled the characterization of exoplanetary atmospheres, which can be achieved by exploitation of the transmission spectroscopy technique. We performed visible (VIS) and near-infrared (NIR) high-resolution spectroscopic observations of one transit of HD 149026b, a close-in orbit sub-Saturn exoplanet by using the GIARPS configuration at the Telescopio Nazionale Galileo (TNG). We first analyzed the radial-velocity data, refining the value of the projected spin-orbit obliquity (lambda ). We then performed transmission spectroscopy, looking for absorption signals from the planetary atmosphere. We find no evidence for Halpha \, D2$-$D1 or in the VIS and metastable helium triplet in the NIR using a line-by-line approach. The non-detection of HeI is also supported by theoretical simulations. With the use of the cross-correlation technique (CCF), we do not detect or VO in the visible, or indeed CH$_4$, CO$_2$, H$_2$O, HCN, NH$_3$, or VO in the NIR. Our non-detection of in the planetary atmosphere is in contrast with a previous detection. We performed injection-retrieval tests, finding that our dataset is sensitive to our \, model. The non-detection supports the \, cold-trap theory, which is valid for planets with eq <$ 2200 K, such as HD 149026b. Although we do not attribute it directly to the planet, we find a possibly significant \, signal that is highly redshifted (simeq +20 with respect to the planetary rest frame. Redshifted signals are also found in the \, and \, maps. While we can exclude an eccentric orbit as the cause of this redshifted \, signal, we investigated the possibility of material accretion falling onto the star --- which is possibly supported by the presence of strong \, in the stellar spectrum --- but obtained inconclusive results. The analysis of multiple transits datasets could shed more light on this target.

X-Ray Emission of Nearby Low-mass and Sunlike Stars with Directly Imageable Habitable Zones

Stellar X-ray and UV radiation can significantly affect the survival, composition, and long-term evolution of the atmospheres of planets in or near their host star’s habitable zone (HZ). Especially interesting are planetary systems in the solar neighborhood that may host temperate and potentially habitable surface conditions, which may be analyzed by future ground- and space-based direct-imaging surveys for signatures of habitability and life. To advance our understanding of the radiation environment in these systems, we leverage ∼3 Ms of XMM-Newton and Chandra observations in order to measure three fundamental stellar properties at X-ray energies for 57 nearby FGKM stellar systems: the shape of the stellar X-ray spectrum, the luminosity, and the timescales over which the stars vary (e.g., due to flares). These systems possess HZs that will be directly imageable to next-generation telescopes such as the Habitable Worlds Observatory and ground-based Extremely Large Telescopes. We identify 29 stellar systems with L X/L bol ratios similar to (or less than) that of the Sun; any potential planets in the HZs of these stars therefore reside in present-day X-ray radiation environments similar to (or less hostile than) modern Earth, though a broader set of these targets could host habitable planets. An additional 19 stellar systems have been observed with the Swift X-ray Telescope; in total, only ∼30% of potential direct imaging target stars has been observed with XMM-Newton, Chandra, or Swift. The data products from this work (X-ray light curves and spectra) are available via a public Zenodo repository (doi:10.5281/zenodo.11490574).

Research on the simulation method of a BP neural network PID control for stellar spectrum

This study investigated the multiple correlations among spectral simulation units based on digital micromirror device (DMD) spectral simulation, which leads to the problem that conventional spectral simulation methods such as PID control exhibit a low fitting accuracy or long fitting time in the spectral simulation of various targets. In this paper, a method of stellar spectrum simulation based on back propagation neural network-based PID (BP-PID) control is proposed to achieve high efficiency and high precision simulation of various spectral targets. The topology of the BP neural network was constructed based on the spectral modulation model of a DMD stellar spectrum simulation system, and the algorithm of the BP-PID control was designed. Finally, an experimental platform was built to verify the performance and spectral simulation accuracy of the BP-PID control algorithm. The results show that the overshoot and response time of the BP-PID control algorithm decreased by 79.01% and 30%, respectively compared with those of the PID control algorithm. The maximum spectral simulation accuracies of 2000K, 7000K, and 12000K color temperature increased by a factor of 2.311, 1.871, and 2.254, respectively, and the standard deviations of the spectral simulation error decreased by 56%, 41%, and 54%, respectively. In the range of 2000-12000K color temperature, the spectral simulation error of the BP-PID control algorithm is better than ±3.495%, and the standard deviation of the spectral simulation error is between 1.8255 and 2.2358. The proposed method can improve the spectral simulation accuracy and simulation efficiency of a star simulator, reduce the magnitude and spectrum calibration errors caused by the differential response, improve the star feature recognition accuracy of the orbiting star sensor, and hence, provide a theoretical and technical basis for the development of high-precision star sensors.

Denoising Medium Resolution Stellar Spectra With Neural Networks

ABSTRACTWe trained denoiser autoencoding neural networks on medium resolution simulated optical spectra of late‐type stars to demonstrate that the reconstruction of the original flux is possible at a typical relative error of a fraction of a percent down to a typical signal‐to‐noise ratio of per pixel. We show that relatively simple networks are capable of learning the characteristics of stellar spectra while still flexible enough to adapt to different values of extinction and fluxing imperfections that modifies the overall shape of the continuum, as well as to different values of Doppler shift. Denoised spectra can be used to find initial values for traditional stellar template fitting algorithms and—since evaluation of pretrained neural networks is significantly faster than traditional template fitting—denoiser networks can be useful when a fast analysis of the noisy spectrum is necessary, for example during observations, between individual exposures.

Estimation of Physical Stellar Parameters from Spectral Models Using Deep Learning Techniques

This article presents a new algorithm that uses techniques from the field of artificial intelligence to automatically estimate the physical parameters of massive stars from a grid of stellar spectral models. This is the first grid to consider hydrodynamic solutions for stellar winds and radiative transport, containing more than 573 thousand synthetic spectra. The methodology involves grouping spectral models using deep learning and clustering techniques. The goal is to delineate the search regions and differentiate the “species” of spectra based on the shapes of the spectral line profiles. Synthetic spectra close to an observed stellar spectrum are selected using deep learning and unsupervised clustering algorithms. As a result, for each spectrum, we found the effective temperature, surface gravity, micro-turbulence velocity, and abundance of elements, such as helium and silicon. In addition, the values of the line force parameters were obtained. The developed algorithm was tested with 40 observed spectra, achieving 85% of the expected results according to the scientific literature. The execution time ranged from 6 to 13 min per spectrum, which represents less than 5% of the total time required for a one-to-one comparison search under the same conditions.

Production and measurement of a stellar neutron spectrum at 30 keV

A few years ago, we theoretically studied the production of a stellar neutron spectrum at kT = 30 keV using a shaped proton beam impinging on a thick lithium target. Here, we first measure the proton distribution to better control the produced neutron spectrum. Then, we measure the forward-emitted angle-integrated neutron spectrum of the 7Li(p,n)7Be reaction via time-of-flight neutron spectrometry with such proton distribution. The result resembles a stellar neutron spectrum at kT = 30 keV. This method avoids in activation experiments the need for spectrum correction. In the case of spherical samples, no knowledge of the cross-section of the isotope being measured by activation would be necessary. Therefore, the present method is of interest for isotopes with unknown or poorly known cross-sections, such as branching points in astrophysics. The key point of our method is the experimental control of the proton distribution that impinges on the lithium target.

Secrets in the shadow: High precision stellar abundances of fast-rotating A-type exoplanet host stars through transit spectroscopy

The spectra of fast-rotating A-type stars have strongly broadened absorption lines. This effect causes blending of the absorption lines, hindering the measurement of the abundances of the elements that are in the stellar photosphere. As the exoplanet transits across its host star, it obscures the stellar spectrum that is emitted from directly behind the planet. We aim to extract this obscured spectrum because it is less affected by rotational broadening, resolving the blending of weak lines of elements that would otherwise remain inaccessible. This allows us to more precisely measure the metal abundances in ultra-hot Jupiter systems, many of which have fast-rotating host stars. We developed a novel method that isolates the stellar spectra behind the planet during a spectral time series, and reconstructs the disc-integrated non-broadened spectrum of the host star. We have systematically tested this method with model-generated spectra of the transit of WASP-189 b across its fast-rotating A-type host star, assessing the effects of limb-darkening, the choice of absorption lines, and the signal-to-noise regime; and demonstrating the sensitivity to photospheric parameters ($T_ eff $ and log $g$) and elemental abundances. We applied the method to observations by the HARPS high-resolution spectrograph. For WASP-189, we obtain the metallicity and photospheric abundances for several species previously not reported in literature, Mg, Ca, and Ti, with a significantly improved accuracy compared to the ordinary broadened stellar spectrum. This method can be generally applied to other transiting systems in which abundance determinations via spectral synthesis are imprecise due to severe line blending. It is important to accurately determine the photospheric properties of exoplanet host stars, as it can provide further insight into the formation and evolution of the planets.

KPF Confirms a Polar Orbit for KELT-18 b

We present the first spectroscopic transit results from the newly commissioned Keck Planet Finder on the Keck-I telescope at W. M. Keck Observatory. We observed a transit of KELT-18 b, an inflated ultrahot Jupiter orbiting a hot star (T eff = 6670 K) with a binary stellar companion. By modeling the perturbation to the measured cross-correlation functions using the Reloaded Rossiter–McLaughlin technique, we derived a sky-projected obliquity of λ = − 94.°8 ± 0.°7 ( ψ=93.8−1.8+1.6° for isotropic i ⋆). The data are consistent with an extreme stellar differential rotation (α = 0.9), though a more likely explanation is moderate center-to-limb variations of the emergent stellar spectrum. We see additional evidence for the latter from line widths increasing toward the limb. Using loose constraints on the stellar rotation period from observed variability in the available TESS photometry, we were able to constrain the stellar inclination and thus the true 3D stellar obliquity to ψ=91.7−1.8+2.2° . KELT-18 b could have obtained its polar orbit through high-eccentricity migration initiated by Kozai–Lidov oscillations induced by the binary stellar companion KELT-18 B, as the two likely have a large mutual inclination as evidenced by Gaia astrometry. KELT-18 b adds another data point to the growing population of close-in polar planets, particularly around hot stars.

MEASNet. I. A Model for Barium Star Identification and s-process Abundance Estimation from LAMOST DR10 Low-resolution Survey

Barium stars are peculiar stars with enhanced slow neutron capture process (s-process) elements. Abundance analysis of them aids in better understanding the chemical evolution of the Milky Way. In this paper, we introduce a data-driven method named the memory-enhanced adaptive spectral network (MEASNet) to search for barium candidates in the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) low-resolution survey (LRS) and estimate the abundance of five s-process elements: Sr, Y, Ba, Ce, and Nd. MEASNet, trained using spectra from common stars in both LAMOST and the Galactic Archaeology with HERMES survey, showcases notable performance: for the classification task, precision = 98.22% and recall = 94.12%; in prediction, the mean absolute error for the seven elements range between 0.07 and 0.15 dex. After training, we apply the model to 4,083,003 stellar spectra from LAMOST DR10 LRS, successfully identifying 1,803,670 spectra of barium candidates ([Ba/Fe] ≥ 0.25 dex) along with their five s-process elemental abundances. The catalog enlarges the sample size, providing a wealth of data for further statistical analysis of the formation and evolution of barium stars. Meanwhile, this work highlights the potential value of MEASNet in star classification and abundance estimation, offering a strong reference for future data-driven models.

Analyzing Stellar Spectra for PRV by Accurate Modeling and Retrieval of Telluric Absorption Features

Ground-based Precision Radial Velocity (PRV) measurements are inevitably impeded by contamination from telluric absorption features, particularly in the infrared region. Thus, it is crucial to improve modeling of the telluric absorption features down to the spectral noise level. As part of the efforts towards improved PRV measurements, we have taken an existing atmospheric trace gas retrieval algorithm (GFIT) and have successfully adapted it to fit the telluric absorption features in stellar spectra down to the spectral noise level (typically ∼1%). We have established a stellar spectral fitting processing pipeline, Stellar-GFIT, to analyze a series of stellar spectra observed by two spectrographs, PARVI (1.1–1.76 μm) commissioned at the Palomar Observatory (Palomar Mountain, CA) and iSHELL (1–5 μm) deployed on the IRTF (Mauna Kea, HI). For this, we have (1) implemented a Gaussian instrumental line shape function, (2) generated atmospheric models (consisting of temperature, pressure, and volume mixing ratios of all the known trace gases) for the particular observation sites and times, (3) employed the most up-to-date spectroscopic parameters in the target spectral regions, and finally (4) developed a series of spectral fitting intervals of ∼60 cm−1 width, i.e., micro-windows, customized to the individual orders of each spectrograph. Stellar-GFIT is also capable of handling non-telluric features, such as transitions from a gas cell placed in the starlight beam and stellar features if a model spectrum template is available for the target star. We present spectrum fits from the observations of various target stars and discuss the performance and advantages of our novel approach. One of the major strengths of Stellar-GFIT is an ability to adjust the abundance of atmospheric trace gases simultaneously with determining the stellar doppler shift, mitigating any adverse impacts of short-timescale variations of water vapor.

Baryonification extended to thermal Sunyaev Zel’dovich

Baryonification algorithms model the impact of galaxy formation and feedback on the matter field in gravity-only simulations by adopting physically motivated parametric prescriptions. In this paper, we extend these models to describe gas temperature and pressure, allowing for a self-consistent modelling of the thermal Sunyaev-Zel’dovich effect, weak gravitational lensing, and their cross-correlation, down to small scales. We validate our approach by showing that it can simultaneously reproduce the electron pressure, gas, stellar, and dark matter power spectra as measured in all BAHAMAS hydrodynamical simulations. Specifically, with only two additional free parameters, we can fit the electron pressure auto- and cross-power spectra at 10% while reproducing the suppression in the matter power spectrum induced by baryons at the per cent level, for different active galactic nuclei (AGN) feedback strengths in BAHAMAS. Furthermore, we reproduce BAHAMAS convergence and thermal Sunyaev Zel’dovich angular power spectra within 1% and 10% accuracy, respectively, down to ℓ = 5000. When used jointly with cosmological rescaling algorithms, the baryonification presented here allows for a fast and accurate exploration of cosmological and astrophysical scenarios. Therefore, it can be employed to create mock catalogues, lightcones, and large training sets for emulators aimed at interpreting forthcoming multi-wavelength observations of the large-scale structure of the Universe.

The IACOB project

Context. With the advent of large spectroscopic surveys, automated stellar parameter determination has become commonplace. Nevertheless, spectral classification still offers a quick and useful alternative for obtaining parameter estimates for large samples of spectra of varying quality. Aims. We present a new atlas of stellar spectra covering the B-type range, with the intention of providing detailed classification criteria valid for modern spectra and improving the grid of reliable standards. This new grid will be used in future works to provide classification criteria beyond the classical classification range and addressing, in particular, the use of Gaia/RVS spectra. Methods. We analysed historical standards by means of multiple high-resolution spectra, marking out problematic cases and complementing the grid with a new set of reliable comparators. We then elaborated on a new set of classification criteria based on high-quality R = 4000 spectra. Results. Our new classification grid is much thicker than any previous set of standards, presenting a high degree of self-consistency. Although it is based entirely on morphological criteria, the grid demonstrates a much better correlation with different physical parameters. Conclusions. The new grid can be used to study classification criteria in other spectral ranges, providing a valuable tool for the study of B-type stars that covers a very wide range of temperatures, luminosities, and stellar masses. The very process of classification also offers valuable insights into stellar evolution.