242 research outputs found

    Asteroseismic modelling strategies in the PLATO era. II. Automation of seismic inversions and quality assessment procedure

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    *Context*. In the framework of the PLATO mission, to be launched in late 2026, seismic inversion techniques will play a key role in the mission precision requirements of the stellar mass, radius, and age. It is therefore relevant to discuss the challenges of the automation of seismic inversions, which were originally developed for individual modelling.\\ *Aims*. We tested the performance of our newly developed quality assessment procedure of seismic inversions, which was designed in the perspective of a pipeline implementation.\\ *Methods*. We applied our assessment procedure on a testing set composed of 26 reference models. We divided our testing set into two categories, calibrator targets whose inversion behaviour is well known from the literature and targets for which we assessed manually the quality of the inversion. We then compared the results of our assessment procedure with our expectations as a human modeller for three types of inversions, the mean density inversion, the acoustic radius inversion, and the central entropy inversion.\\ *Results*. We found that our quality assessment procedure performs as well as a human modeller. The mean density inversion and the acoustic radius inversion are suited for a large-scale application, but not the central entropy inversion, at least in its current form.\\ *Conclusions*. Our assessment procedure showed promising results for a pipeline implementation. It is based on by-products of the inversion and therefore requires few numerical resources to assess quickly the quality of an inversion result.Comment: Accepted for publication in Astronomy & Astrophysic

    A Bayesian Augmented-Learning framework for spectral uncertainty quantification of incomplete records of stochastic processes

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    A novel Bayesian Augmented-Learning framework, quantifying the uncertainty of spectral representations of stochastic processes in the presence of missing data, is developed. The approach combines additional information (prior domain knowledge) of the physical processes with real, yet incomplete, observations. Bayesian deep learning models are trained to learn the underlying stochastic process, probabilistically capturing temporal dynamics, from the physics-based pre-simulated data. An ensemble of time domain reconstructions are provided through recurrent computations using the learned Bayesian models. Models are characterized by the posterior distribution of model parameters, whereby uncertainties over learned models, reconstructions and spectral representations are all quantified. In particular, three recurrent neural network architectures, (namely long short-term memory, or LSTM, LSTM-Autoencoder, LSTM-Autoencoder with teacher forcing mechanism), which are implemented in a Bayesian framework through stochastic variational inference, are investigated and compared under many missing data scenarios. An example from stochastic dynamics pertaining to the characterization of earthquake-induced stochastic excitations even when the source load data records are incomplete is used to illustrate the framework. Results highlight the superiority of the proposed approach, which adopts additional information, and the versatility of outputting many forms of results in a probabilistic manner

    Understanding mixing processes in stars using hydrodynamic simulations

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    Waves that propagate in stellar interiors are essential to stellar physics for two reasons. First, the interiors of stars are studied by detection of global modes of oscillations resulting from wave interference. Secondly, waves are involved in various transport phenomena. In stars, there are two main types of waves: acoustic and gravity. This duality of waves as observational tools and physical processes impacting stellar structure makes them a crucial field of study in astrophysics. In this thesis, we focus on internal gravity waves (IGWs), which are well known for transporting angular momentum, energy and chemical elements in stably stratified media. Despite observations of very high precision, detection of IGWs is still challenging and their properties in stellar interiors remain poorly understood and/or constrained. This is mostly because IGWs are inherently 3D, non-linear and anisotropic phenomena. Consequently, multidimensional modelling is a great tool to study these waves. However, stellar hydrodynamics faces important challenges such as numerical stability and thermal relaxation. To face them, an artificial increase of the stellar luminosity and of the thermal diffusivity by several orders of magnitudes is a commonly used tactic. Using two-dimensional simulations of a solar-like model, we quantify the impact of such a technique on IGWs. Our results suggest that this technique affect the excitation of IGWs, because of an impact on convective motions and overshooting, but also their damping. Main-sequence intermediate-mass stars, with M ≳ 2M⊙, possess a convective core and a radiative envelope. It remains unclear if waves generated at the edge of the convective core should be able to propagate up to the stellar surface. In this context, we have carried out an analysis of IGWs in simulations of 5 M⊙ star model. Our results show that low frequency waves excited by core convection are strongly impacted by radiative effects as they propagate. In the upper layers of the simulation domain, we observe an increase of the temperature, likely due to heat added in these layers by IGWs damped by radiative diffusion. We show that nonlinear effects linked to large amplitude IGWs may be relevant just above the convective core. Both these effects are intensified by the artificial enhancement of the luminosity and radiative diffusivity. Our results also highlight that direct comparison between numerical simulations with enhanced luminosity and observations must be made with caution

    Hydrodynamical simulations of massive stars collisions

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    openSince the detection of gravitational waves traveling through our universe, a new field of astrophysics has opened up, and with it many hypotheses and theoretical predictions have been put to the test. This is the case of the pair-instability mass gap (60 and 120 Msun. Gravitational wave signals have been detected whose primary and secondary black holes fall within the mass range where it was previously thought unthinkable that they could exist as a product of stellar evolution. Different mechanisms could explain these observations, among which the gravitational collapse of a particular type of remnant from a collision between two predecessor stars stands out. Multiple studies support this hypothesis, however, it is necessary to determine the incidence of the collision parameters on the main characteristics of the post-coalescence star, especially to corroborate that its final mass and chemical composition made it a suitable remnant to produce these special black holes. To achieve this goal, the hydrodynamic simulations of stellar collisions are a perfect tool. In this thesis, we have analyzed a set of simulations produced with the smoothed particle hydrodynamics code StarSmasher. This set explores different configurations of mass, radius, stellar evolution time, velocity at infinity and impact parameter for the two colliding stars. We have been able to analyze the temporal evolution of the percentage of unbound mass for all cases, obtaining that collisions produce a range of mass loss between 9.7 % and 19.3 %, with the impact parameter being the most influential value in the increase of this percentage. We have also visualized that the relaxation of the final remnant occurs quite quickly after the impact as long as the collision is radial. Only two days are necessary for the remnant mass to remain stable, as well as its velocity. In the case of non-radial collisions, the relaxation of the post-coalescence star is much more complex, since it is altered by successive collisions between the cores of the two primary stars. Finally, we also found that non-radial collisions are the only ones that result in a remnant with tangential rotational velocity, a fact that would favor the chemical enrichment of its constituent layers and modify its subsequent evolution.Since the detection of gravitational waves traveling through our universe, a new field of astrophysics has opened up, and with it many hypotheses and theoretical predictions have been put to the test. This is the case of the pair-instability mass gap (60 and 120 Msun. Gravitational wave signals have been detected whose primary and secondary black holes fall within the mass range where it was previously thought unthinkable that they could exist as a product of stellar evolution. Different mechanisms could explain these observations, among which the gravitational collapse of a particular type of remnant from a collision between two predecessor stars stands out. Multiple studies support this hypothesis, however, it is necessary to determine the incidence of the collision parameters on the main characteristics of the post-coalescence star, especially to corroborate that its final mass and chemical composition made it a suitable remnant to produce these special black holes. To achieve this goal, the hydrodynamic simulations of stellar collisions are a perfect tool. In this thesis, we have analyzed a set of simulations produced with the smoothed particle hydrodynamics code StarSmasher. This set explores different configurations of mass, radius, stellar evolution time, velocity at infinity and impact parameter for the two colliding stars. We have been able to analyze the temporal evolution of the percentage of unbound mass for all cases, obtaining that collisions produce a range of mass loss between 9.7 % and 19.3 %, with the impact parameter being the most influential value in the increase of this percentage. We have also visualized that the relaxation of the final remnant occurs quite quickly after the impact as long as the collision is radial. Only two days are necessary for the remnant mass to remain stable, as well as its velocity. In the case of non-radial collisions, the relaxation of the post-coalescence star is much more complex, since it is altered by successive collisions between the cores of the two primary stars. Finally, we also found that non-radial collisions are the only ones that result in a remnant with tangential rotational velocity, a fact that would favor the chemical enrichment of its constituent layers and modify its subsequent evolution

    Two-dimensional simulations of internal gravity waves in a 5 MM_{\odot} Zero-Age-Main-Sequence model

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    Main-sequence intermediate-mass stars present a radiative envelope that supports internal gravity waves (IGWs). Excited at the boundary with the convective core, IGWs propagate towards the stellar surface and are suspected to impact physical processes such as rotation and chemical mixing. Using the fully compressible time-implicit code MUSIC, we study IGWs in two-dimensional simulations of a zero-age-main-sequence 5 solar mass star model up to 91\% of the stellar radius with different luminosity and radiative diffusivity enhancements. Our results show that low frequency waves excited by core convection are strongly impacted by radiative effects as they propagate. This impact depends on the radial profile of radiative diffusivity which increases by almost 5 orders of magnitude between the centre of the star and the top of the simulation domain. In the upper layers of the simulation domain, we observe an increase of the temperature. Our study suggests that this is due to heat added in these layers by IGWs damped by radiative diffusion. We show that non-linear effects linked to large amplitude IGWs may be relevant just above the convective core. Both these effects are intensified by the artificial enhancement of the luminosity and radiative diffusivity, with enhancement factors up to 10410^4 times the realistic values. Our results also highlight that direct comparison between numerical simulations with enhanced luminosity and observations must be made with caution. Finally, our work suggests that thermal effects linked to the damping of IGWs could have a non-negligible impact on stellar structure.Comment: 15 pages, 10 figures, accepted for publication in MNRA

    Stellar Activity Cycles

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    The magnetic field of the Sun is generated by internal dynamo process with a cyclic period of 11 years or a 22 year magnetic cycle. The signatures of the Sun's magnetic cycle are observed in the different layers of its atmosphere and in its internal layers. In this review, we use the same diagnostics to understand the magnetic cycles of other stars with the same internal structure as the Sun. We review what is currently known about mapping the surface magnetic fields, chromospheric and coronal indicators, cycles in photometry and asteroseismology. We conclude our review with an outlook for the future.Comment: accepted by Space Science Review

    Feebly Interacting Particles: FIPs 2022 workshop report

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    Particle physics today faces the challenge of explaining the mystery of dark matter, the origin of matter over anti-matter in the Universe, the origin of the neutrino masses, the apparent fine-tuning of the electro-weak scale, and many other aspects of fundamental physics. Perhaps the most striking frontier to emerge in the search for answers involves new physics at mass scales comparable to familiar matter, below the GeV-scale, or even radically below, down to sub-eV scales, and with very feeble interaction strength. New theoretical ideas to address dark matter and other fundamental questions predict such feebly interacting particles (FIPs) at these scales, and indeed, existing data provide numerous hints for such possibility. A vibrant experimental program to discover such physics is under way, guided by a systematic theoretical approach firmly grounded on the underlying principles of the Standard Model. This document represents the report of the FIPs 2022 workshop, held at CERN between the 17 and 21 October 2022 and aims to give an overview of these efforts, their motivations, and the decadal goals that animate the community involved in the search for FIPs

    Asteroseismic modelling strategies in the PLATO era I. Mean density inversions and direct treatment of the seismic information

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    Asteroseismic modelling will be part of the pipeline of the PLATO mission and will play a key role in the mission precision requirements on stellar mass, radius and age. It is therefore crucial to compare how current modelling strategies perform, and discuss the limitations and remaining challenges for PLATO, such as the so-called surface effects, the choice of physical ingredients, and stellar activity. In this context, we carried out a systematic study of the impact of surface effects on the estimation of stellar parameters. In this work, we demonstrated how combining a mean density inversion with a fit of frequencies separation ratios can efficiently damp the surface effects and achieve precise and accurate stellar parameters for ten Kepler LEGACY targets, well within the PLATO mission requirements. We applied and compared two modelling approaches, directly fitting the individual frequencies, or coupling a mean density inversion with a fit of the ratios, to six synthetic targets with a patched 3D atmosphere from Sonoi et al. (2015) and ten actual targets from the LEGACY sample. The fit of the individual frequencies is unsurprisingly very sensitive to surface effects and the stellar parameters tend to be biased, which constitutes a fundamental limit to both accuracy and precision. In contrast, coupling a mean density inversion and a fit of the ratios efficiently damps the surface effects, and allows us to get both precise and accurate stellar parameters. The average statistical precision of our selection of LEGACY targets with this second strategy is 1.9% for the mass, 0.7% for the radius, and 4.1% for the age, well within the PLATO requirements. Using the mean density in the constraints significantly improves the precision of the mass, radius and age determinations, on average by 20%, 33%, and 16%, respectively.Comment: Accepted for publication in Astronomy & Astrophysic

    Bulk classification and analysis of TESS γ Doradus stars using machine learning methods

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    Supervised machine learning was used to classify γ Doradus stars present in the TESS-SPOC data pipeline, to investigate the efficacy of fast bulk classification of pulsating stars in minimally-processed data. A fully-connected neural network was set up and trained as a binary classifier using built catalogues of previously confirmed pulsators of four types present in the γ Doradus instability strip, as well as known non-variable stars. During validation, the model obtained a 94.4% precision score. The trained network was then input with binned Lomb-Scargle periodograms of 173,398 stars within the ranges Teff = 6500 - 7500 K and Tmag = 9.0 - 12.0. The total time for the network to classify all candidates was 11.1 minutes, with a pre-processing time of ∼5 ms per lightcurve. The probability distributions and HR diagram positions of the output classifications were analysed and a small set of the results visually verified. It was found that a classifier confidence threshold of 77.4% was most suitable and yielded 7,749 potential γ Doradus candidates, representing 4.47% of the analysed set. Of 100 of these visually checked, only seven were misclassified EB stars, and three likely rotational variables. Eight of the classifications showed evidence of p-mode pulsations suggestive of γ Doradus and δ Scuti hybrids. This investigation shows a way in which only minimal treatment of TESS lightcurve data is necessary for high quality classifications of pulsators, allowing for quick identification in large datasets. This is important, as a large and diverse pool of candidates is necessary for thorough investigation and testing of stellar evolution models

    The Fifteenth Marcel Grossmann Meeting

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    The three volumes of the proceedings of MG15 give a broad view of all aspects of gravitational physics and astrophysics, from mathematical issues to recent observations and experiments. The scientific program of the meeting included 40 morning plenary talks over 6 days, 5 evening popular talks and nearly 100 parallel sessions on 71 topics spread over 4 afternoons. These proceedings are a representative sample of the very many oral and poster presentations made at the meeting.Part A contains plenary and review articles and the contributions from some parallel sessions, while Parts B and C consist of those from the remaining parallel sessions. The contents range from the mathematical foundations of classical and quantum gravitational theories including recent developments in string theory, to precision tests of general relativity including progress towards the detection of gravitational waves, and from supernova cosmology to relativistic astrophysics, including topics such as gamma ray bursts, black hole physics both in our galaxy and in active galactic nuclei in other galaxies, and neutron star, pulsar and white dwarf astrophysics. Parallel sessions touch on dark matter, neutrinos, X-ray sources, astrophysical black holes, neutron stars, white dwarfs, binary systems, radiative transfer, accretion disks, quasars, gamma ray bursts, supernovas, alternative gravitational theories, perturbations of collapsed objects, analog models, black hole thermodynamics, numerical relativity, gravitational lensing, large scale structure, observational cosmology, early universe models and cosmic microwave background anisotropies, inhomogeneous cosmology, inflation, global structure, singularities, chaos, Einstein-Maxwell systems, wormholes, exact solutions of Einstein's equations, gravitational waves, gravitational wave detectors and data analysis, precision gravitational measurements, quantum gravity and loop quantum gravity, quantum cosmology, strings and branes, self-gravitating systems, gamma ray astronomy, cosmic rays and the history of general relativity
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