arXiv subjects

E. Hatt

Publications and source records attributed to E. Hatt.

5 recordsLinked to original sources

arXiv2026

Constraining the model-based uncertainties of asteroseismic magnetic field measurements in red giants

Magnetic fields inside red giants are measured using shifts to the oscillation frequencies. However, in the asymptotic framework, converting a frequency shift into a radial magnetic field strength requires knowing the global magnetic sensitivity. This parameter (also called the core structure parameter) must be inferred from stellar models, introducing a source of uncertainty. We seek to understand how the global magnetic sensitivity depends on stellar properties such as mass and metallicity, and to quantify the model-based uncertainty on magnetic field measurements. We also explore which stellar properties are key to finding a precise and accurate estimate of the global magnetic sensitivity. Using MESA models, we examine how the global magnetic sensitivity changes with mass, metallicity, and age. We then create a set of synthetic stars and test how well we recover the sensitivity parameter. We consider different grid construction approaches and the choice of which observables are used in the fitting process. We find that the global magnetic sensitivity shows a stronger dependence on mass for higher mass models and a stronger metallicity dependence for lower metallicity models. Our approach recovers the sensitivity parameter well, with an uncertainty of 10% when precise metallicity measurements are used. We apply our method to stars with existing magnetic field measurements. In most cases, the dominant source of uncertainty remains observational, although precise modeling can significantly reduce the magnetic field uncertainty for stars with exceptional data. With careful fitting, models yield accurate values for the global magnetic sensitivity. We recommend that future work obtain the global magnetic sensitivity using both asteroseismic and high-quality spectroscopic data. Under these conditions, we recommend adopting a model-based uncertainty of 10% on the sensitivity parameter.

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arXiv2025

Farside helioseismology with Sun-as-a-star data: the solar cycle as seen with 7-day-long BiSON timeseries

We present results from fitting $p$-mode spectra derived from 7-d segments of Sun-as-a-star helioseismic observations from the Birmingham Solar Oscillations Network covering 32 yr. The results show a clear dependence of the mode frequencies on solar activity, and the frequency dependence of the sensitivity to activity can also be seen. Because we use data segments that cover less than half of a solar rotation, we are able to test for the effect of activity on the solar far side. By fitting with a model that takes into account activity on the far side of the Sun, we show that the frequency shifts are sensitive to activity from the whole Sun, not just the side facing the observer. Our results suggest that there is potential to investigate activity-related asteroseismic frequency shifts in solar-like oscillators using short time series of observations.

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arXiv2024

Predicted asteroseismic detection yield for solar-like oscillating stars with PLATO

We determine the expected yield of detections of solar-like oscillations for the PLATO ESA mission. We used a formulation from the literature to calculate the probability of detection and validated it with Kepler data. We then applied this approach to the PLATO P1 and P2 samples with the lowest noise level and the much larger P5 sample, which has a higher noise level. We used the information available in in the PIC 1.1.0, including the current best estimate of the signal-to-noise ratio. We also derived relations to estimate the uncertainties of seismically inferred stellar mass, radius and age and applied those relations to the main sequence stars of the PLATO P1 and P2 samples with masses equal to or below 1.2 $\rm{M}_\odot$ for which we had obtained a positive seismic detection. We found that one can expect positive detections of solar-like oscillations for more than 15 000 FGK stars in one single field after a two-years run of observation. For main sequence stars with masses $\leq 1.2 \rm{M}_\odot$, we found that about 1131 stars satisfy the PLATO requirements for the uncertainties of the seismically inferred stellar masses, radii and ages in one single field after a two-year run of observation. The baseline observation programme of PLATO consists in observing two fields of similar size (in the Southern and Northern hemispheres) for two years each. The expected seismic yields of the mission are more 30000 FGK dwarfs and subgiants with positive detections of solar-like oscillations, enabling to achieve the mission stellar objectives. The PLATO mission should produce a sample of seismically extremely well characterized stars of quality equivalent to the Kepler Legacy sample but containing a number of stars $\sim$ 80 times larger if observing two PLATO fields for two years each. They will represent a goldmine which will make possible significant advances in stellar modelling.

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arXiv2023

Simplifying asteroseismic analysis of solar-like oscillators: An application of principal component analysis for dimensionality reduction

The asteroseismic analysis of stellar power density spectra is often computationally expensive. The models used in the analysis may use several dozen parameters to accurately describe features in the spectra caused by oscillation modes and surface granulation. Many parameters are often highly correlated, making the parameter space difficult to quickly and accurately sample. They are, however, all dependent on a smaller set of parameters, namely the fundamental stellar properties. We aim to leverage this to simplify the process of sampling the model parameter space for the asteroseismic analysis of solar-like oscillators, with an emphasis on mode identification. Using a large set of previous observations, we applied principal component analysis to the sample covariance matrix to select a new basis on which to sample the model parameters. Selecting the subset of basis vectors that explains the majority of the sample variance, we redefine the model parameter prior probability density distributions in terms of a smaller set of latent parameters. We are able to reduce the dimensionality of the sampled parameter space by a factor of two to three. The number of latent parameters needed to accurately model the stellar oscillation spectra cannot be determined exactly but is likely only between four and six. Using two latent parameters, the method is able to describe the bulk features of the oscillation spectrum, while including more latent parameters allows for a frequency precision better than $\approx10\%$ of the small frequency separation for a given target. We find that sampling a lower-rank latent parameter space still allows for accurate mode identification and parameter estimation on solar-like oscillators over a wide range of evolutionary stages. This allows for the potential to increase the complexity of spectrum models without a corresponding increase in computational expense.

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arXiv2022

A probabilistic method for detecting solar-like oscillations using meaningful prior information

Current and future space-based observatories such as the Transiting Exoplanet Survey Satellite (TESS) and PLATO are set to provide an enormous amount of new data on oscillating stars, and in particular stars that oscillate similar to the Sun. Solar-like oscillators constitute the majority of known oscillating stars and so automated analysis methods are becoming an ever increasing necessity to make as much use of these data as possible. Here we aim to construct an algorithm that can automatically determine if a given time series of photometric measurements shows evidence of solar-like oscillations. The algorithm is aimed at analyzing data from the TESS mission and the future PLATO mission, and in particular stars in the main-sequence and subgiant evolutionary stages. The algorithm first tests the range of observable frequencies in the power spectrum of a TESS light curve for an excess that is consistent with that expected from solar-like oscillations. In addition, the algorithm tests if a repeating pattern of oscillation frequencies is present in the time series, and whether it is consistent with the large separation seen in solar-like oscillators. Both methods use scaling relations and observations which were established and obtained during the CoRoT, Kepler, and K2 missions. Using a set of test data consisting of visually confirmed solar-like oscillators and nonoscillators observed by TESS, we find that the proposed algorithm can attain a $94.7\%$ true positive rate and a $8.2\%$ false positive rate at peak accuracy. However, by applying stricter selection criteria, the false positive rate can be reduced to $\approx2\%$, while retaining an $80\%$ true positive rate.

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