Engineering topics

Varela, J.

Publications and source records attributed to Varela, J..

8 records

DOE OSTI2024

Transport and losses of energetic particles in tokamaks in the presence of Alfvén activity using the new full orbit TAPaS code coupled to FAR3d

Recent developments and tools integrated into the TAPaS code are presented, enabling realistic scenario simulations of particle dynamics within experimental tokamak magnetic equilibria. In particular, the enhanced capabilities of TAPaS enable seamless coupling with external simulations, provided the metric and equilibrium magnetic field of the external code are known. Coupling TAPaS with the gyro-fluid code FAR3d, the transport and losses of energetic particles in the presence Alfvén eigenmodes (AEs) in DIII-D plasma discharge #159243 were investigated. Detailed analyses of prompt losses with and without collisions were performed. Then, further analysis was performed in the presence of electromagnetic perturbations resulting from AEs activity. The results indicate that, for the energies and the initial conditions considered here, the presence of AEs enhances the particle losses.

Alfven eigenmodes↗

DOE OSTI2023

The miniJPAS survey: AGN and host galaxy coevolution of X-ray-selected sources

Studies indicate strong evidence of a scaling relation in the local Universe between the supermassive black hole mass (MBH) and the stellar mass of their host galaxies (M * ). They even show similar histories across cosmic times of their differential terms: the star formation rate (SFR) and black hole accretion rate (BHAR). However, a clear picture of this coevolution is far from being understood. We selected an X-ray sample of active galactic nuclei (AGN) up to z = 2.5 in the miniJPAS footprint. Their X-ray to infrared spectral energy distributions (SEDs) have been modeled with the CIGALE code, constraining the emission to 68 bands, from which 54 are the narrow filters from the miniJPAS survey. For a final sample of 308 galaxies, we derived their physical properties, such as their M * , SFR, star formation history (SFH), and the luminosity produced by the accretion process of the central BH (L AGN ). For a subsample of 113 sources, we also fit their optical spectra to obtain the gas velocity dispersion from the broad emission lines and estimated the M BH . We calculated the BHAR in physical units depending on two radiative efficiency regimes. We find that the Eddington ratios (λ Edd ) and its popular proxy (L X /M * ) have a difference of 0.6 dex, on average, and a KS test indicates that they come from different distributions. Our sources exhibit a considerable scatter on the MBH - M * scaling relation, which can explain the difference between λ Edd and its proxy. We also modeled three evolution scenarios for each source to recover the integral properties at z = 0. Using the SFR and BHAR, we show a notable diminution in the scattering between MBH - M * . For the last scenario, we considered the SFH and a simple energy budget for the AGN accretion, and we retrieved a relation similar to the calibrations known for the local Universe. Our study covers ~1 deg 2 in the sky and is sensitive to biases in luminosity. Nevertheless, we show that, for bright sources, the link between the differential values (SFR and BHAR) and their decoupling based on an energy limit is the key that leads to the local M BH - M * scaling relation. In the future, we plan to extend this methodology to a thousand degrees of the sky using JPAS with an X-ray selection from eROSITA, to obtain an unbiased distribution of BHAR and Eddington ratios.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Study of Alfvén eigenmode stability in Quasi-Poloidal Stellarator (QPS) plasma using a Landau closure model

The aim of this study is to analyze the linear stability of Alfvén eigenmodes (AE) in the QPS device heated by a tangential neutral beam injector (NBI). The analysis is performed using the gyro-fluid code FAR3d, that solves the reduced MHD equations for the thermal plasma coupled with moments of the kinetic equation for the energetic particles (EP). The AE stability is calculated in several operational regimes of the tangential NBI: EP β between 0.001 and 0.1, EP energy between 12 and 180 keV and different radial locations of the beam. The analysis is performed for vacuum and finite β equilibria as well as QPS configurations with two and three periods. The EP β threshold in the vacuum case is 0.001 and the AE frequency is lower as the energy of the EP population decreases. Toroidal Alfvén eigenmodes with f = 80–120 kHz and elliptical AE between f = 120–350 kHz are triggered between the middle-outer plasma region ($r/a \gt 0.5$). The AE stability improves in the simulations with finite β equilibria and three period configurations with respect to the vacuum case with two periods because the continuum gaps are slender, leading to a higher threshold of the EP β, above 0.03 for the AEs triggered by the helical mode families. Helical effects are not strong enough to destabilize Helical Alfvén eigenmodes, the AEs with the largest growth rates are triggered by the n = 1 and n = 2 toroidal families.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

J-PLUS: Uncovering a large population of extreme [OIII] emitters in the local Universe

Over the past decades, several studies have discovered a population of galaxies that undergo very strong star formation events. They are called extreme emission line galaxies (EELGs). We exploit the capabilities of the Javalambre Photometric Local Universe Survey (J-PLUS), a wide-field multifilter survey, with which 2000 square degrees of the northern sky are already observed. We use it to identify EELGs at low redshift by their [OIII]5007 emission line. We intend to provide a more complete, deep, and less biased sample of local EELGs. We selected objects with an excess of flux in the J-PLUS medium-band J0515 filter, which covers the [OIII] line at z < 0.06. We removed contaminants (stars and higher-redshift systems) using J-PLUS and WISE infrared photometry, with SDSS spectra as a benchmark. We performed spectral energy distribution fitting to estimate the physical properties of the galaxies: line fluxes, equivalent widths (EWs), masses, stellar population ages, and so on. We identify 466 EELGs at z < 0.06 with [OIII] EW over 300 Å and an r-band magnitude below 20, of which 411 were previously unknown. Most show compact morphologies, low stellar masses (log(M • /M ⊙ ) ~ 8.13 –0.58 +0.61 ), low dust extinction (E( B–V ) ~ 0.1 –0.1 +0.2 ), and very young bursts of star formation (3.0 –2.0 +2.7 Myr). Our method is up to ~20 times more efficient in detecting EELGs per Mpc 3 than broadband surveys, and it is as complete as magnitude-limited spectroscopic surveys (but reaches fainter objects). The sample is not directly biased against strong Hα emitters, in contrast with works using broadband surveys. We demonstrate that J-PLUS can identify a large sample of previously unknown EELGs showing unique properties following a clear selection process. A fraction of the EELGs are probably similar to the first galaxies in the Universe, but they are at a much lower redshift, which makes them ideal targets for follow-up studies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The miniJPAS survey: White dwarf science with 56 optical filters

We analyze the white dwarf population in miniJPAS, the first square degree observed with 56 medium-band, 145 Å in width optical filters by the Javalambre Physics of the accelerating Universe Astrophysical Survey (J-PAS), to provide a data-based forecast for the white dwarf science with low-resolution ($R$ ~ 50) photo-spectra. We define the sample of the bluest point-like sources in miniJPAS with $r$ < 21.5 mag, a point-like probability larger than 0.5, ($u$ - $r$)< 0.80 mag, and ($g$ - $i$)< 0.25 mag. This sample comprises 33 sources with spectroscopic information: 11 white dwarfs and 22 quasi-stellar objects (QSOs). We estimate the effective temperature ($T$ eff ), the surface gravity, and the composition of the white dwarf population by a Bayesian fitting to the observed photo-spectra. The miniJPAS data are sensitive to the Balmer series and the presence of polluting metals. Our results, combined with those from the Javalambre Photometric Local Universe Survey (J-PLUS) which has a lower spectral resolution but has already observed thousands of white dwarfs, suggest that J-PAS photometry would permit – down to $r$ ~ 21.5 mag and at least for sources with 7000 < $T$ eff < 22 000 K – both the classification of the observed white dwarfs into H-dominated and He-dominated with 99% confidence and the detection of calcium absorption for equivalent widths larger than 15 Å. The effective temperature is estimated with a 2% uncertainty, which is close to the 1% from spectroscopy. A precise estimation of the surface gravity depends on the available parallax information. In addition, the white dwarf population at $T$ eff > 7000 K can be segregated from the bluest extragalactic QSOs, providing a clean sample based on optical photometry alone. The J-PAS low-resolution photo-spectra would produce precise effective temperatures and atmospheric compositions for white dwarfs, complementing the data from Gaia. J-PAS will also detect and characterize new white dwarfs beyond the Gaia magnitude limit, providing faint candidates for spectroscopic follow-up.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

The miniJPAS survey: A search for extreme emission-line galaxies

Context. Galaxies with extreme emission lines (EELGs) may play a key role in the evolution of the Universe, as well as in our understanding of the star formation process itself. For this reason an accurate determination of their spatial density and fundamental properties in different epochs of the Universe will constitute a unique perspective towards a comprehensive picture of the interplay between star formation and mass assembly in galaxies. In addition to this, EELGs are also interesting in order to explain the reionization of the Universe, since their interstellar medium (ISM) could be leaking ionizing photons, and thus they could be low z, analogous of extreme galaxies at high z . Aims. This paper presents a method to obtain a census of EELGs over a large area of the sky by detecting galaxies with rest-frame equivalent widths ≥300 Å in the emission lines [O II]λλ3727,3729Å, [O III]λ5007Å, and Hα. For this, we aim to use the J-PAS survey, which will image an area of ≈8000 deg 2 with 56 narrow band filters in the optical. As a pilot study, we present a methodology designed to select EELGs on the miniJPAS images, which use the same filter dataset as J-PAS, and thus will be exportable to this larger survey. Methods. We make use of the miniJPAS survey data, conceived as a proof of concept of J-PAS, and covering an area of ≈1 deg 2 . Objects were detected in the r SDSS images and selected by imposing a condition on the flux in a given narrow-band J-PAS filter with respect to the contiguous ones, which is analogous to requiring an observed equivalent width larger than 300 Å in a certain emission line within the filter bandwidth. The selected sources were then classified as galaxies or quasi-stellar objects (QSOs) after a comparison of their miniJPAS fluxes with those of a spectral database of objects known to present strong emission lines. This comparison also provided a redshift for each source, which turned out to be consistent with the spectroscopic redshifts when available (|Δz/(1 + z spec )| ≤ 0.01). Results. The selected candidates were found to show a compact appearance in the optical images, some of them even being classified as point-like sources according to their stellarity index. After discarding sources classified as QSOs, a total of 17 sources turned out to exhibit EW 0 ≥ 300 Å in at least one emission line, thus constituting our final list of EELGs. Our counts are fairly consistent with those of other samples of EELGs in the literature, although there are some differences, which were expected due to biases resulting from different selection criteria.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

J-PLUS: Support vector regression to measure stellar parameters

Stellar parameters are among the most important characteristics in studies of stars which, in traditional methods, are based on atmosphere models. However, time, cost, and brightness limits restrain the efficiency of spectral observations. The Javalambre Photometric Local Universe Survey (J-PLUS) is an observational campaign that aims to obtain photometry in 12 bands. Owing to its characteristics, J-PLUS data have become a valuable resource for studies of stars. Machine learning provides powerful tools for efficiently analyzing large data sets, such as the one from J-PLUS, and enables us to expand the research domain to stellar parameters. The main goal of this study is to construct a support vector regression (SVR) algorithm to estimate stellar parameters of the stars in the first data release of the J-PLUS observational campaign. The training data for the parameter's regressions are featured with 12-waveband photometry from J-PLUS and are crossidentified with spectrum-based catalogs. These catalogs are from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, the Apache Point Observatory Galactic Evolution Experiment, and the Sloan Extension for Galactic Understanding and Exploration. We then label them with the stellar effective temperature, the surface gravity, and the metallicity. Ten percent of the sample is held out to apply a blind test. We develop a new method, a multi-model approach, in order to fully take into account, the uncertainties of both the magnitudes and the stellar parameters. The method utilizes more than 200 models to apply the uncertainty analysis. We present a catalog of 2 493 424 stars with the root mean square error of 160 K in the effective temperature regression, 0.35 in the surface gravity regression, and 0.25 in the metallicity regression. We also discuss the advantages of this multi-model approach and compare it to other machine-learning methods.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

J-PLUS: Support vector machine applied to STAR-GALAXY-QSO classification

Context. In modern astronomy, machine learning has proved to be efficient and effective in mining big data from the newest telescopes. Aims. In this study, we construct a supervised machine-learning algorithm to classify the objects in the Javalambre Photometric Local Universe Survey first data release (J-PLUS DR1). Methods. The sample set is featured with 12-waveband photometry and labeled with spectrum-based catalogs, including Sloan Digital Sky Survey spectroscopic data, the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, and VERONCAT – the Veron Catalog of Quasars & AGN. The performance of the classifier is presented with the applications of blind test validations based on RAdial Velocity Extension, the Kepler Input Catalog, the Two Micron All Sky Survey Redshift Survey, and the UV-bright Quasar Survey. A new algorithm was applied to constrain the potential extrapolation that could decrease the performance of the machine-learning classifier. Results. The accuracies of the classifier are 96.5% in the blind test and 97.0% in training cross-validation. The F1-scores for each class are presented to show the balance between the precision and the recall of the classifier. We also discuss different methods to constrain the potential extrapolation.

79 ASTRONOMY AND ASTROPHYSICS↗