@article{22262, abstract = {Mixed modes are observed in many low-mass evolved stars. They provide information about core rotation rates of these stars, which are lower than predicted by stellar evolution models. The mixed modes themselves have been invoked as an angular momentum (AM) transport mechanism, but estimating their transport efficiency requires knowledge of their amplitudes. We constrain, for the first time, the mixed-mode amplitudes in 2D hydrodynamical simulations of a 1.3M⊙ red giant using the code MUSIC. We perform two simulations with outer radial truncations at fractional radii ro/r⋆ = 0.90 and 0.98. We compare the modes in the simulation with those found using both GYRE and a Dedalus eigenvalue solver. Excellent frequency agreement is found for all p-dominated modes, with minor discrepancies for g-dominated modes, especially in the frequency range [60, 240] μHz. We find excellent eigenfunction agreement for all modes except those in this frequency range. According to empirical predictions, the largest kinetic energies are located around Vmax= 312.μHz, but in both simulations, the modes with frequencies of ν < 50 μHz have the largest kinetic energies. In the simulation with r/r⋆ = 0.98, the simulated modes have extrapolated surface velocities comparable to the empirical predictions, with the highest surface velocities in a bell-shaped curve peaking around ν = 700 μHz. The extrapolated surface velocities of the low-frequency modes are small and thus hard to observe, but their large kinetic energies deeper in the interior could significantly impact AM transport, which has not yet been investigated.}, author = {De Vries, Nils B. and Le Saux, Arthur and Baraffe, Isabelle and Guillet, Thomas and Townsend, Richard H.D. and Leclerc, Armand and Morison, Adrien}, issn = {1538-4357}, journal = {The Astrophysical Journal}, keywords = {Stellar physics, Stellar interiors, Asteroseismology, Stellar oscillations, Hydrodynamical simulations}, number = {2}, publisher = {IOP Publishing}, title = {{Revealing mixed modes in compressible hydrodynamical simulations of red giant stars}}, doi = {10.3847/1538-4357/ae7a3c}, volume = {1005}, year = {2026}, } @phdthesis{19853, abstract = {The internal dynamical properties of red giant stars have been explored extensively in recent years as a result of the increase in high precision data availability from the space missions Kepler and TESS (Transiting Exoplanet Survey Satellite), and in this exploration, it has been discovered that some of these stars are not behaving as expected. Red giants are stars that have evolved off of the main sequence after having completed fusing hydrogen into helium in their core. Observational data shows that the cores are rotating significantly slower than models can recreate consistently across evolutionary stages. This discrepancy has prompted investigation into the efficiency of angular momentum transport mechanisms and mixing processes including meridional circulation, shear instability, internal gravity waves, Tayler-Spruit dynamo, fossil magnetic fields etc., to explain this behavior. Analyzing seismic oscillations in stars, via asteroseismology, is a powerful tool as it is the only way in which the deep stellar interior can be probed and subsequently characterized; this is possible as global oscillations modulating the stellar surface are effected by internal processes. For red giants, p-modes (pressure modes; resonating through the entire star) and g-modes (gravity-modes; resonating in the radiative interior) couple to create mixed modes. These mixed modes give access to the otherwise hidden stellar interior as g-modes couple to p-modes, delivering information from the interior to the surface. Internal magnetic signatures have been observationally confirmed in red giant stars via asteroseismology and characterized in two ways. One being that dipole mixed modes with ℓ = 1 will display a global asymmetric frequency shift of its azimuthal components; where the m = 0 and m = ±1 components of the ℓ = 1 dipole mode will be shifted by two different power laws, respectively. And the other being a reduced visibility of dipole mixed mode amplitudes in the power spectra, where stars presenting with this feature are denoted as suppressed. Several studies of the suppressed dipole mixed mode amplitudes have been carried out, but thus far, no dedicated studies of the asymmetric frequency shifts of suppressed red giants have been conducted; one reason being that the asymmetric frequency shifts cannot be characterized when the dipole mixed mode amplitudes are severely reduced in many of the suppressed stars. Sincefullysuppressedstarsdonothavedetectablemixed-modestoevaluate, partiallysuppressed stars, that is, red giant stars presenting with suppressed dipole mixed modes in select parts of their power spectra rather than across the entire spectra, will be the subject of this study as the respective mode amplitudes are still visible at high frequencies. As such, this study will search for asymmetric frequency shifts on the dipole mixed modes of partially suppressed red giant stars; the aim here is to investigate if both mode suppression and magnetic shifting of dipole mixed modes occur simultaneously. Thisstudywillbeconductedbycreatingapipelinetoestimatepriorsofasteroseismicparameters, use the priors to model the power spectra with the stellar modeling code sloscillations_ISTA, and perform a Bayesian fit of the parameters with the simulated data on the star KIC 6975038, a target with partially suppressed dipolar mode amplitudes identified in the literature, to fit its magnetic parameters. I present a novel method to model the stellar power spectra of partially suppressed red giants by application of a sigmoid profile to the ℓ= 1 dipolar mode component of the spectra. With the results of this study I aim at constraining the cause of this partial dipole mode amplitude suppression, allowing for more detailed studies regarding their astrophysical nature. Furthermore, the long term hope for the method used in this study will be to expand the sample of partially suppressed red giants and fit their asteroseismic parameters accordingly.}, author = {Smith, Kanah}, issn = {2791-4585}, keywords = {asteroseismology, stellar physics, red giant, magnetism, suppressed}, pages = {38}, publisher = {Institute of Science and Technology Austria}, title = {{Exploring internal magnetism in partially suppressed red giant stars}}, doi = {10.15479/AT-ISTA-19853}, year = {2025}, } @article{11606, abstract = {Context. Our knowledge of the dynamics of stars has undergone a revolution through the simultaneous large amount of high-quality photometric observations collected by space-based asteroseismology and ground-based high-precision spectropolarimetry. They allowed us to probe the internal rotation of stars and their surface magnetism in the whole Hertzsprung-Russell diagram. However, new methods should still be developed to probe the deep magnetic fields in these stars. Aims. Our goal is to provide seismic diagnoses that allow us to probe the internal magnetism of stars. Methods. We focused on asymptotic low-frequency gravity modes and high-frequency acoustic modes. Using a first-order perturbative theory, we derived magnetic splittings of their frequencies as explicit functions of stellar parameters. Results. As in the case of rotation, we show that asymptotic gravity and acoustic modes can allow us to probe the different components of the magnetic field in the cavities in which they propagate. This again demonstrates the high potential of using mixed-modes when this is possible.}, author = {Mathis, S. and Bugnet, Lisa Annabelle and Prat, V. and Augustson, K. and Mathur, S. and Garcia, R. A.}, issn = {1432-0746}, journal = {Astronomy & Astrophysics}, keywords = {Space and Planetary Science, Astronomy and Astrophysics, asteroseismology / waves / stars, magnetic field / stars, oscillations / methods, analytical}, publisher = {EDP Sciences}, title = {{Probing the internal magnetism of stars using asymptotic magneto-asteroseismology}}, doi = {10.1051/0004-6361/202039180}, volume = {647}, year = {2021}, } @article{11615, abstract = {The recently published Kepler mission Data Release 25 (DR25) reported on ∼197 000 targets observed during the mission. Despite this, no wide search for red giants showing solar-like oscillations have been made across all stars observed in Kepler’s long-cadence mode. In this work, we perform this task using custom apertures on the Kepler pixel files and detect oscillations in 21 914 stars, representing the largest sample of solar-like oscillating stars to date. We measure their frequency at maximum power, νmax, down to νmax≃4μHz and obtain log (g) estimates with a typical uncertainty below 0.05 dex, which is superior to typical measurements from spectroscopy. Additionally, the νmax distribution of our detections show good agreement with results from a simulated model of the Milky Way, with a ratio of observed to predicted stars of 0.992 for stars with 10<νmax<270μHz. Among our red giant detections, we find 909 to be dwarf/subgiant stars whose flux signal is polluted by a neighbouring giant as a result of using larger photometric apertures than those used by the NASA Kepler science processing pipeline. We further find that only 293 of the polluting giants are known Kepler targets. The remainder comprises over 600 newly identified oscillating red giants, with many expected to belong to the Galactic halo, serendipitously falling within the Kepler pixel files of targeted stars.}, author = {Hon, Marc and Stello, Dennis and García, Rafael A and Mathur, Savita and Sharma, Sanjib and Colman, Isabel L and Bugnet, Lisa Annabelle}, issn = {1365-2966}, journal = {Monthly Notices of the Royal Astronomical Society}, keywords = {Space and Planetary Science, Astronomy and Astrophysics, asteroseismology, methods: data analysis, techniques: image processing, stars: oscillations, stars: statistics}, number = {4}, pages = {5616--5630}, publisher = {Oxford University Press}, title = {{A search for red giant solar-like oscillations in all Kepler data}}, doi = {10.1093/mnras/stz622}, volume = {485}, year = {2019}, } @unpublished{11627, abstract = {For a solar-like star, the surface rotation evolves with time, allowing in principle to estimate the age of a star from its surface rotation period. Here we are interested in measuring surface rotation periods of solar-like stars observed by the NASA mission Kepler. Different methods have been developed to track rotation signals in Kepler photometric light curves: time-frequency analysis based on wavelet techniques, autocorrelation and composite spectrum. We use the learning abilities of random forest classifiers to take decisions during two crucial steps of the analysis. First, given some input parameters, we discriminate the considered Kepler targets between rotating MS stars, non-rotating MS stars, red giants, binaries and pulsators. We then use a second classifier only on the MS rotating targets to decide the best data analysis treatment.}, author = {Breton, S. N. and Bugnet, Lisa Annabelle and Santos, A. R. G. and Saux, A. Le and Mathur, S. and Palle, P. L. and Garcia, R. A.}, booktitle = {arXiv}, keywords = {asteroseismology, rotation, solar-like stars, kepler, machine learning, random forest}, title = {{Determining surface rotation periods of solar-like stars observed by the Kepler mission using machine learning techniques}}, doi = {10.48550/arXiv.1906.09609}, year = {2019}, } @unpublished{11630, abstract = {The second mission of NASA’s Kepler satellite, K2, has collected hundreds of thousands of lightcurves for stars close to the ecliptic plane. This new sample could increase the number of known pulsating stars and then improve our understanding of those stars. For the moment only a few stars have been properly classified and published. In this work, we present a method to automaticly classify K2 pulsating stars using a Machine Learning technique called Random Forest. The objective is to sort out the stars in four classes: red giant (RG), main-sequence Solar-like stars (SL), classical pulsators (PULS) and Other. To do this we use the effective temperatures and the luminosities of the stars as well as the FliPer features, that measures the amount of power contained in the power spectral density. The classifier now retrieves the right classification for more than 80% of the stars.}, author = {Saux, A. Le and Bugnet, Lisa Annabelle and Mathur, S. and Breton, S. N. and Garcia, R. A.}, booktitle = {arXiv}, keywords = {asteroseismology - methods, data analysis - thecniques, machine learning - stars, oscillations}, title = {{Automatic classification of K2 pulsating stars using machine learning techniques}}, doi = {10.48550/arXiv.1906.09611}, year = {2019}, } @article{11618, abstract = {Asteroseismology provides global stellar parameters such as masses, radii, or surface gravities using mean global seismic parameters and effective temperature for thousands of low-mass stars (0.8 M⊙ < M < 3 M⊙). This methodology has been successfully applied to stars in which acoustic modes excited by turbulent convection are measured. Other methods such as the Flicker technique can also be used to determine stellar surface gravities, but only works for log g above 2.5 dex. In this work, we present a new metric called FliPer (Flicker in spectral power density, in opposition to the standard Flicker measurement which is computed in the time domain); it is able to extend the range for which reliable surface gravities can be obtained (0.1 < log g < 4.6 dex) without performing any seismic analysis for stars brighter than Kp < 14. FliPer takes into account the average variability of a star measured in the power density spectrum in a given range of frequencies. However, FliPer values calculated on several ranges of frequency are required to better characterize a star. Using a large set of asteroseismic targets it is possible to calibrate the behavior of surface gravity with FliPer through machine learning. This calibration made with a random forest regressor covers a wide range of surface gravities from main-sequence stars to subgiants and red giants, with very small uncertainties from 0.04 to 0.1 dex. FliPer values can be inserted in automatic global seismic pipelines to either give an estimation of the stellar surface gravity or to assess the quality of the seismic results by detecting any outliers in the obtained νmax values. FliPer also constrains the surface gravities of main-sequence dwarfs using only long-cadence data for which the Nyquist frequency is too low to measure the acoustic-mode properties.}, author = {Bugnet, Lisa Annabelle and García, R. A. and Davies, G. R. and Mathur, S. and Corsaro, E. and Hall, O. J. and Rendle, B. M.}, issn = {1432-0746}, journal = {Astronomy & Astrophysics}, keywords = {Space and Planetary Science, Astronomy and Astrophysics, asteroseismology / methods, data analysis / stars, oscillations}, publisher = {EDP Sciences}, title = {{FliPer: A global measure of power density to estimate surface gravities of main-sequence solar-like stars and red giants}}, doi = {10.1051/0004-6361/201833106}, volume = {620}, year = {2018}, } @article{11620, abstract = {We report the discovery and characterization of HD 89345b (K2-234b; EPIC 248777106b), a Saturn-sized planet orbiting a slightly evolved star. HD 89345 is a bright star (V = 9.3 mag) observed by the K2 mission with 1 min time sampling. It exhibits solar-like oscillations. We conducted asteroseismology to determine the parameters of the star, finding the mass and radius to be 1.12+0.04−0.01M⊙ and 1.657+0.020−0.004R⊙⁠, respectively. The star appears to have recently left the main sequence, based on the inferred age, 9.4+0.4−1.3Gyr⁠, and the non-detection of mixed modes. The star hosts a ‘warm Saturn’ (P = 11.8 d, Rp = 6.86 ± 0.14 R⊕). Radial-velocity follow-up observations performed with the FIbre-fed Echelle Spectrograph, HARPS, and HARPS-N spectrographs show that the planet has a mass of 35.7 ± 3.3 M⊕. The data also show that the planet’s orbit is eccentric (e ≈ 0.2). An investigation of the rotational splitting of the oscillation frequencies of the star yields no conclusive evidence on the stellar inclination angle. We further obtained Rossiter–McLaughlin observations, which result in a broad posterior of the stellar obliquity. The planet seems to confirm to the same patterns that have been observed for other sub-Saturns regarding planet mass and multiplicity, orbital eccentricity, and stellar metallicity.}, author = {Van Eylen, V and Dai, F and Mathur, S and Gandolfi, D and Albrecht, S and Fridlund, M and García, R A and Guenther, E and Hjorth, M and Justesen, A B and Livingston, J and Lund, M N and Pérez Hernández, F and Prieto-Arranz, J and Regulo, C and Bugnet, Lisa Annabelle and Everett, M E and Hirano, T and Nespral, D and Nowak, G and Palle, E and Silva Aguirre, V and Trifonov, T and Winn, J N and Barragán, O and Beck, P G and Chaplin, W J and Cochran, W D and Csizmadia, S and Deeg, H and Endl, M and Heeren, P and Grziwa, S and Hatzes, A P and Hidalgo, D and Korth, J and Mathis, S and Montañes Rodriguez, P and Narita, N and Patzold, M and Persson, C M and Rodler, F and Smith, A M S}, issn = {1365-2966}, journal = {Monthly Notices of the Royal Astronomical Society}, keywords = {Space and Planetary Science, Astronomy and Astrophysics, asteroseismology, planets and satellites: composition, planets and satellites: formation, planets and satellites: fundamental parameters}, number = {4}, pages = {4866--4880}, publisher = {Oxford University Press}, title = {{HD 89345: A bright oscillating star hosting a transiting warm Saturn-sized planet observed by K2}}, doi = {10.1093/mnras/sty1390}, volume = {478}, year = {2018}, } @unpublished{11631, abstract = {The recently launched NASA Transiting Exoplanet Survey Satellite (TESS) mission is going to collect lightcurves for a few hundred million of stars and we expect to increase the number of pulsating stars to analyze compared to the few thousand stars observed by the CoRoT, Kepler and K2 missions. However, most of the TESS targets have not yet been properly classified and characterized. In order to improve the analysis of the TESS data, it is crucial to determine the type of stellar pulsations in a timely manner. We propose an automatic method to classify stars attending to their pulsation properties, in particular, to identify solar-like pulsators among all TESS targets. It relies on the use of the global amount of power contained in the power spectrum (already known as the FliPer method) as a key parameter, along with the effective temperature, to feed into a machine learning classifier. Our study, based on TESS simulated datasets, shows that we are able to classify pulsators with a 98% accuracy.}, author = {Bugnet, Lisa Annabelle and García, R. A. and Davies, G. R. and Mathur, S. and Hall, O. J. and Rendle, B. M.}, booktitle = {arXiv}, keywords = {asteroseismology - methods, data analysis - stars, oscillations}, title = {{FliPer: Classifying TESS pulsating stars}}, doi = {10.48550/arXiv.1811.12140}, year = {2018}, } @unpublished{11633, abstract = {Our understanding of stars through asteroseismic data analysis is limited by our ability to take advantage of the huge amount of observed stars provided by space missions such as CoRoT, Kepler , K2, and soon TESS and PLATO. Global seismic pipelines provide global stellar parameters such as mass and radius using the mean seismic parameters, as well as the effective temperature. These pipelines are commonly used automatically on thousands of stars observed by K2 for 3 months (and soon TESS for at least ∼ 1 month). However, pipelines are not immune from misidentifying noise peaks and stellar oscillations. Therefore, new validation techniques are required to assess the quality of these results. We present a new metric called FliPer (Flicker in Power), which takes into account the average variability at all measured time scales. The proper calibration of FliPer enables us to obtain good estimations of global stellar parameters such as surface gravity that are robust against the influence of noise peaks and hence are an excellent way to find faults in asteroseismic pipelines.}, author = {Bugnet, Lisa Annabelle and Garcia, R. A. and Davies, G. R. and Mathur, S. and Corsaro, E.}, booktitle = {arXiv}, keywords = {asteroseismology - methods, data analysis - stars, oscillations}, title = {{FliPer: Checking the reliability of global seismic parameters from automatic pipelines}}, doi = {10.48550/arXiv.1711.02890}, year = {2017}, }