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The rapid rise of Large Language Models (LLMs) has created new disruptive possibilities for persuasive communication, by enabling fully-automated personalized and interactive content generation at an unprecedented scale. In this paper, we survey the research field of LLM-based persuasion that has emerged as a result. We begin by exploring the different modes in which LLM Systems are used to influence human attitudes and behaviors. In areas such as politics, marketing, public health, e-commerce, and charitable giving, such LLM Systems have already achieved human-level or even super-human persuasiveness. We identify key factors influencing their effectiveness, such as the manner of personalization and whether the content is labelled as AI-generated. We also summarize the experimental designs that have been used to evaluate progress. Our survey suggests that the current and future potential of LLM-based persuasion poses profound ethical and societal risks, including the spread of misinformation, the magnification of biases, and the invasion of privacy. These risks underscore the urgent need for ethical guidelines and updated regulatory frameworks to avoid the widespread deployment of irresponsible and harmful LLM Systems.

Large language models (LLMs) are trained on vast amounts of data to generate natural language, enabling them to perform tasks like text summarization and question answering. These models have become popular in artificial intelligence (AI) assistants like ChatGPT and already play an influential role in how humans access information. However, the behavior of LLMs varies depending on their design, training, and use. In this paper, we uncover notable diversity in the ideological stance exhibited across different LLMs and languages in which they are accessed. We do this by prompting a diverse panel of popular LLMs to describe a large number of prominent and controversial personalities from recent world history, both in English and in Chinese. By identifying and analyzing moral assessments reflected in the generated descriptions, we find consistent normative differences between how the same LLM responds in Chinese compared to English. Similarly, we identify normative disagreements between Western and non-Western LLMs about prominent actors in geopolitical conflicts. Furthermore, popularly hypothesized disparities in political goals among Western models are reflected in significant normative differences related to inclusion, social inequality, and political scandals. Our results show that the ideological stance of an LLM often reflects the worldview of its creators. This raises important concerns around technological and regulatory efforts with the stated aim of making LLMs ideologically `unbiased', and it poses risks for political instrumentalization.

This paper presents FinGEITje, the first Dutch financial Large Language Model (LLM) specifically designed and optimized for various financial tasks. Together with the model, we release a specialized Dutch financial instruction tuning dataset with over 140,000 samples, constructed employing an automated translation and data processing method. The open-source data construction method is provided, facilitating the creation of financial instruction datasets in different languages. To evaluate model performance, the study introduces the first Dutch financial evaluation benchmark, along with an automated evaluation method that utilizes an LLM as an independent evaluator, reducing manual intervention in performance evaluation. The experimental results highlight the superior performance of FinGEITje across five critical Dutch and English financial tasks., Comment: 9 pages, 1 figure, accepted at ACM ICAIF'24

The first adiabatic exponent profile, noted $\Gamma_1$, computed along adiabatic coordinates $(T, \rho)$ is in the focus of our study. Under conditions of almost fully ionized hydrogen and helium, the $\Gamma_1$ profile is quite sensitive to heavy elements ionization. $\Gamma_1$ decreases in regions where an element is partially ionized. The recent helioseismic structural inversion is obtained with an accuracy better than $10^{-4}$ in the most of the adiabatic convective zone that allows to study ionization variations. The aim is to determine the major heavy elements content in the solar convective zone. The method of our research is synthesis of the $\Gamma_1$ profile which is based on a linear combination of the contributions of individual heavy elements. The idea of the approach was proposed and justified by Baturin et al. (Astron. Astrophys., 660, A125, 2022). We find the best approximation of the inverted profile $\Gamma_1$ adjusting the abundances of major elements (C, N, O, Ne), meanwhile the abundances of elements heavier than neon are fixed. We synthesize the theoretical $\Gamma_1$ profile using the SAHA-S equation of state, and are able to reproduce the inverted profiles with an accuracy of $(1-2)\cdot 10^{-5}$. Total mass fraction of heavy elements found by this method is $Z=0.0148\pm 0.0004$. The oxygen logarithmic abundance is $8.70\pm 0.03$, carbon $8.44\pm 0.04$, nitrogen $8.12\pm 0.08$, and neon $8.17\pm 0.09$. The obtained estimations of oxygen and carbon agree with spectroscopic abundances by Asplund et al. (Astron. Astrophys., 653, A141, 2021)., Comment: Accepted for publication in Solar Physics

PLATO (PLAnetary Transits and Oscillations of stars) is ESA's M3 mission designed to detect and characterise extrasolar planets and perform asteroseismic monitoring of a large number of stars. PLATO will detect small planets (down to <2 R_(Earth)) around bright stars (<11 mag), including terrestrial planets in the habitable zone of solar-like stars. With the complement of radial velocity observations from the ground, planets will be characterised for their radius, mass, and age with high accuracy (5 %, 10 %, 10 % for an Earth-Sun combination respectively). PLATO will provide us with a large-scale catalogue of well-characterised small planets up to intermediate orbital periods, relevant for a meaningful comparison to planet formation theories and to better understand planet evolution. It will make possible comparative exoplanetology to place our Solar System planets in a broader context. In parallel, PLATO will study (host) stars using asteroseismology, allowing us to determine the stellar properties with high accuracy, substantially enhancing our knowledge of stellar structure and evolution. The payload instrument consists of 26 cameras with 12cm aperture each. For at least four years, the mission will perform high-precision photometric measurements. Here we review the science objectives, present PLATO's target samples and fields, provide an overview of expected core science performance as well as a description of the instrument and the mission profile at the beginning of the serial production of the flight cameras. PLATO is scheduled for a launch date end 2026. This overview therefore provides a summary of the mission to the community in preparation of the upcoming operational phases.

This paper addresses a long-standing problem in the field of accounting: mapping company-specific ledger accounts to a standardized chart of accounts. We propose a novel solution, TopoLedgerBERT, a unique sentence embedding method devised specifically for ledger account mapping. This model integrates hierarchical information from the charts of accounts into the sentence embedding process, aiming to accurately capture both the semantic similarity and the hierarchical structure of the ledger accounts. In addition, we introduce a data augmentation strategy that enriches the training data and, as a result, increases the performance of our proposed model. Compared to benchmark methods, TopoLedgerBERT demonstrates superior performance in terms of accuracy and mean reciprocal rank., Comment: 8 pages, 4 figures

Due to the high quality constraints available for the Sun, we can carry out combined analyses using neutrino, spectroscopic and helioseismic observations. Such studies lay the ground for future improvements of key physical components of solar and stellar models, such as the equation of state, radiative opacities or prescriptions for macroscopic transport processes of chemicals which are then used to study other stars in the Universe. We study the existing degeneracies in solar models using the recent high-metallicity spectroscopic abundances by comparing them to helioseismic and neutrino data and discuss how their properties are impacted by changes in various physical ingredients. We carry out a detailed study of solar models computed with a high-metallicity composition from the literature based on averaged-3D models that was claimed to solve the solar problem. The properties of the solar models are significantly affected by using the recent OPLIB opacities and the inclusion of macroscopic transport. The properties of the standard solar models computed using the OPAL opacities are similar to those using the OP opacities. We show that a modifying the temperature gradient just below the base of the convective zone is required to erase the discrepancies in solar models, particularly in the presence of macroscopic mixing. This can be simulated by a local increase of opacity of a few percent. We conclude that the existing degeneracies and issues in solar modelling are not erased by an increase in the solar metallicity in contradiction to was suggested in recent papers. Therefore, standard solar models cannot be used as an argument for a high metallicity composition. While further work is required to improve solar models, we note that direct helioseismic inversions indicate a low metallicity in the convective envelope, in agreement with spectroscopic analyses based on full 3D models., Comment: Accepted for publication in Astronomy and Astrophysics, version before language editing

We propose a framework to solve non-linear and history-dependent mechanical problems based on a hybrid classical computer -- quantum annealer approach. Quantum Computers are anticipated to solve particular operations exponentially faster. The available possible operations are however not as versatile as with a classical computer. However, quantum annealers (QAs) are well suited to evaluate the minimum state of a Hamiltonian quadratic potential. Therefore, we reformulate the elasto-plastic finite element problem as a double-minimisation process framed at the structural scale using the variational updates formulation. In order to comply with the expected quadratic nature of the Hamiltonian, the resulting non-linear minimisation problems are iteratively solved with the suggested Quantum Annealing-assisted Sequential Quadratic Programming (QA-SQP): a sequence of minimising quadratic problems is performed by approximating the objective function by a quadratic Taylor's series. Each quadratic minimisation problem of continuous variables is then transformed into a binary quadratic problem. This binary quadratic minimisation problem can be solved on quantum annealing hardware such as the D-Wave system. The applicability of the proposed framework is demonstrated with one- and two-dimensional elasto-plastic numerical benchmarks. The current work provides a pathway of performing general non-linear finite element simulations assisted by quantum computing., Comment: This is an updated version following reviewing process. The code and raw/processed data required to reproduce these findings is available on http://dx.doi.org/10.5281/zenodo.10451584 under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence

Context. The metal mass fraction of the Sun Z is a key constraint in solar modelling, but its value is still under debate. The standard solar chemical composition of the late 2000s have the ratio of metals to hydrogen Z/X = 0.0181, with a small increase to 0.0187 in 2021, as inferred from 3D non-LTE spectroscopy. However, more recent work on a horizontally and temporally averaged <3D> model claim Z/X = 0.0225, consistent with the high values of twenty-five years ago based on 1D LTE spectroscopy. Aims. We aim to determine a precise and robust value of the solar metal mass fraction from helioseismic inversions, thus providing independent constraints from spectroscopic methods. Methods. We devise a detailed seismic reconstruction technique of the solar envelope, combining multiple inversions and equations of state to accurately and precisely determine the metal mass fraction value. Results. We show that a low value of the solar metal mass fraction corresponding to Z/X = 0.0187 is favoured by helioseismic constraints and that a higher metal mass fraction corresponding to Z/X = 0.0225 are strongly rejected by helioseismic data. Conclusions. We conclude that direct measurement of the metal mass fraction in the solar envelope favours a low metallicity, in line with the 3D non-LTE spectroscopic determination of 2021. A high metal mass fraction as measured using a <3D> model in 2022 is disfavoured by helioseismology for all modern equations of state used to model the solar convective envelope., Comment: Accepted for publication in A&A, online materials available on demand or on publisher website

Context. The Sun acts as a cornerstone of stellar physics. Thanks to spectroscopic, helioseismic and neutrino flux observations, we can use the Sun as a laboratory of fundamental physics in extreme conditions. The conclusions we draw are then used to inform and calibrate evolutionary models of all other stars in the Universe. However, solar models are in tension with helioseismic constraints. The debate on the ``solar problem'' has hitherto led to numerous publications discussing potential issues with solar models and abundances. Aims. Using the recently suggested high-metallicity abundances for the Sun, we investigate whether standard solar models, as well as models with macroscopic transport reproducing the solar surface lithium abundances and analyze their properties in terms of helioseismic and neutrino flux observations. Methods. We compute solar evolutionary models and combine spectroscopic and helioseismic constraints as well as neutrino fluxes to investigate the impact of macroscopic transport on these measurements. Results. When high-metallicity solar models are calibrated to reproduce the measured solar lithium depletion, tensions arise with respect to helioseismology and neutrino fluxes. This is yet another demonstration that the solar problem is also linked to the physical prescriptions of solar evolutionary models and not to chemical composition alone. Conclusions. A revision of the physical ingredients of solar models is needed in order to improve our understanding of stellar structure and evolution. The solar problem is not limited to the photospheric abundances if the depletion of light elements is considered. In addition, tighter constraints on the solar beryllium abundance will play a key role in the improvement of solar models., Comment: Accepted for publication in Astronomy and Astrophysics

The measurement of the apsidal motion in close eccentric massive binary systems provides essential information to probe the internal structure of the stars that compose the system. Following the determination of the fundamental stellar and binary parameters, we make use of the tidally induced apsidal motion to infer constraints on the internal structure of the stars composing the binary system HD152219. The extensive set of spectroscopic, photometric, and radial velocity observations allows us to constrain the fundamental parameters of the stars together with the rate of apsidal motion of the system. Stellar structure and evolution models are further built with the Cl\'es code testing different prescriptions for the internal mixing occurring inside the stars. The effect of stellar rotation axis misalignment with respect to the normal to the orbital plane on our interpretation of the apsidal motion in terms of internal structure constants is investigated. Made of an O9.5 III primary star (M1 = 18.64+/-0.47M${_\odot}$, R1 = 9.40+0.14-0.15R${_\odot}$, Teff,1 = 30900+/-1000 K) and a B1-2 V-III secondary star (M2 = 7.70+/-0.12M${_\odot}$, R2 = 3.69+/-0.06R${_\odot}$, Teff,2 = 21697+/-1000 K), the binary system HD152219 displays apsidal motion at a rate (1.198+/-0.300){\deg}yr-1. The weighted-average mean of the internal structure constant of the binary system is inferred: k2 = 0.00173+/-0.00052. For the Cl\'es models to reproduce the k2-value of the primary star, a significant enhanced mixing is required, notably through the turbulent mixing, but at the cost that other stellar parameters cannot be reproduced simultaneously. The difficulty to reproduce the k2-value simultaneously with the stellar parameters as well as the incompatibility between the age estimates of the primary and secondary stars are indications that some physics of the stellar interior are still not completely understood., Comment: 30 pages

Artificial Neural Networks (NNWs) are appealing functions to substitute high dimensional and non-linear history-dependent problems in computational mechanics since they offer the possibility to drastically reduce the computational time. This feature has recently been exploited in the context of multi-scale simulations, in which the NNWs serve as surrogate model of micro-scale finite element resolutions. Nevertheless, in the literature, mainly the macro-stress-macro-strain response of the meso-scale boundary value problem was considered and the micro-structure information could not be recovered in a so-called localization step. In this work, we develop Recurrent Neural Networks (RNNs) as surrogates of the RVE response while being able to recover the evolution of the local micro-structure state variables for complex loading scenarios. The main difficulty is the high dimensionality of the RNNs output which consists in the internal state variable distribution in the micro-structure. We thus propose and compare several surrogate models based on a dimensionality reduction: i) direct RNN modeling with implicit NNW dimensionality reduction, ii) RNN with PCA dimensionality reduction, and iii) RNN with PCA dimensionality reduction and dimensionality break down, i.e. the use of several RNNs instead of a single one. Besides, we optimize the sequential training strategy of the latter surrogate for GPU usage in order to speed up the process. Finally, through RNN modeling of the principal components coefficients, the connection between the physical state variables and the hidden variables of the RNN is revealed, and exploited in order to select the hyper-parameters of the RNN-based surrogate models in their design stage.

Quantifying the similarity between a group of companies has proven to be useful for several purposes, including company benchmarking, fraud detection, and searching for investment opportunities. This exercise can be done using a variety of data sources, such as company activity data and financial data. However, ledger account data is widely available and is standardized to a large extent. Such ledger accounts within a financial statement can be represented by means of a tree, i.e. a special type of graph, representing both the values of the ledger accounts and the relationships between them. Given their broad availability and rich information content, financial statements form a prime data source based on which company similarities or distances could be computed. In this paper, we present a graph distance metric that enables one to compute the similarity between the financial statements of two companies. We conduct a comprehensive experimental study using real-world financial data to demonstrate the usefulness of our proposed distance metric. The experimental results show promising results on a number of use cases. This method may be useful for investors looking for investment opportunities, government officials attempting to identify fraudulent companies, and accountants looking to benchmark a group of companies based on their financial statements., Comment: 8 pages, 5 figures

The $\beta$ Cephei pulsators are massive main-sequence stars, presenting low radial-order modes. These modes probe in particular the chemical gradient at the edge of the convective core. They hence give constraints on macroscopic processes, such as hydrodynamic or magnetic instabilities. Yet, it is not clear to what extent the seismic inferences depend on the physics employed for the stellar modelling or on the observational dataset. We investigate the observational constraints which are necessary to provide accurate constraints on the mixing processes in $\beta$ Cephei stars. We explore the importance of the identification of the angular degree of modes. Depending on the quality of the seismic dataset and the classical constraints, we estimate the precision achievable with asteroseismology. We propose a method extending the forward approach classically used to model $\beta$ Cephei stars The probability distributions of the asteroseismic-derived stellar parameters are obtained. With these distributions, we provide a systemic way to estimate the errors of the modelling. A particular effort is made to also include the theoretical uncertainties of the models. We then estimate the accuracy and precision of asteroseismology for $\beta$ Cephei stars in a series of hare and hound exercises. The exercises show that a set of four to five oscillation frequencies with an identified angular degree already leads to accurate inferences on the stellar parameters. Without the identification of the modes, the addition of other classical observational constraints allow to succeed the seismic modelling. When the micro-physics of the star and stellar models used for the modelling differ, the constraints derived on the internal structure remain valid if expressed in terms of acoustic variables. The characterisation of the mixing processes at the boundary of the convective core remain model-dependent., Comment: 17 pages, 14 figures, accepted for publication in A&A

Compared to conventional projection-based model-order-reduction, its neural-network acceleration has the advantage that the online simulations are equation-free, meaning that no system of equations needs to be solved iteratively. Consequently, no stiffness matrix needs to be constructed and the stress update needs to be computed only once per increment. In this contribution, a recurrent neural network is developed to accelerate a projection-based model-order-reduction of the elastoplastic mechanical behaviour of an RVE. In contrast to a neural network that merely emulates the relation between the macroscopic deformation (path) and the macroscopic stress, the neural network acceleration of projection-based model-order-reduction preserves all microstructural information, at the price of computing this information once per increment.

This study is the first of a series of papers that provide a technique to analyse the mixed-modes frequency spectra and characterise the structure of stars on the subgiant and red-giant branches. We define seismic indicators, relevant of the stellar structure and study their evolution on a grid of models. The proposed method, EGGMiMoSA, relies on the asymptotic description of mixed modes, defines initial guesses for the parameters, and uses a Levenberg-Marquardt technique to adjust the mixed-modes pattern efficiently. We follow the evolution of the mixed-modes parameters along a grid of models from the subgiant phase to the RGB bump and extend past works. We show the impact of the mass and composition on their evolution. The evolution of the period spacing $\Delta\pi_1$, pressure offset $\epsilon_p$, gravity offset $\epsilon_g$, and coupling factor $q$ as a function of $\Delta\nu$ is little affected by the chemical composition and it follows two different regimes depending on the evolutionary stage. On the subgiant branch, the models display a moderate core-envelope density contrast. The evolution of $\Delta \pi_1$, $\epsilon_p$, $\epsilon_g$, and $q$ thus significantly changes with the mass. Also, we demonstrate that, at fixed Z/X and with proper measurements of $\Delta\pi_1$ and $\Delta\nu$, we may unambiguously constrain the mass, radius and age of a subgiant star. Conversely, on the red-giant branch, the core-envelope density contrast becomes very large. Consequently, the evolution of $\epsilon_p$, $\epsilon_g$ and $q$ as a function of $\Delta\nu$ becomes independent of the mass. This is also true for $\Delta \pi_1$ in stars with masses $\lesssim 1.8M_\odot$ because of core electron degeneracy. This degeneracy is lifted for higher masses, again allowing for a precise measurement of the age. Overall, our computations qualitatively agree with past observed and theoretical studies., Comment: 21 pages, accepeted on the 30th of June 2021, condensed abstract to meet the 1920 characters requirement (the full abstract will be available in the journal)

Context: The Sun is by far a privileged target for testing stellar models with unique precision. A recent concern appeared with the progress in the solar surface abundances derivation that has led to a decrease of the solar metallicity. While the ancient high-metallicity models were in fair agreement with other solar observational indicators, it is no longer the case for low-metallicity models. Recent collection of data are however promising to shed a new light on it. For instance, the Borexino collaboration released in 2020 the first-ever complete estimate of neutrinos emitted in the CNO cycle. It has reaffirmed the role of the neutrino constraints in the solar modelling process and its associated issues. In parallel, newly claimed detection of solar gravity modes of oscillations offers another opportunity of probing the stratification in the Sun's central layers. Aims: We propose to combine the diagnoses from neutrinos and helioseismology, both from pressure and gravity modes, for assessing the predictions of solar models. We compare in detail the different physical prescriptions currently at disposal for stellar model computations. Results: The CNO neutrino flux confirms a preference for high-metallicity models. Nevertheless, we found that mild modification of the nuclear screening factors can re-match low-metallicity model predictions to observed fluxes, although it does not restore the agreement with the helioseismic frequency ratios. Neither the high-metallicity or low-metallicity models are able to reproduce the gravity-mode period spacing. The disagreement is huge, more than 100$\sigma$ to the reported value. Reversely, the family of standard models narrows the expected range of the Sun's period spacing: between $\sim$2150 to $\sim$2190~s. Moreover, we show this indicator can constrain the chemical mixture, opacity, and to a lower extent nuclear reactions in solar models., Comment: 18 pages, 10 figures, accepted for publications in Astronomy and Astrophysics

Context: Being part of the brightest solar-like stars, and close solar analogues, the 16 Cygni system is of great interest to the scientific community and may provide insight into the past and future evolution of our Sun. It has been observed thoroughly by the Kepler satellite, which provided us with data of an unprecedented quality. Aims: This paper is the first of a series aiming to extensively characterise the system. We test several choices of micro- and macro-physics to highlight their effects on optimal stellar parameters and provide realistic stellar parameter ranges. Methods: We used a recently developed method, WhoSGlAd, that takes the utmost advantage of the whole oscillation spectrum of solar-like stars by simultaneously adjusting the acoustic glitches and the smoothly varying trend. For each choice of input physics, we computed models which account, at best, for a set of seismic indicators that are representative of the stellar structure and are as uncorrelated as possible. The search for optimal models was carried out through a Levenberg-Marquardt minimisation. First, we found individual optimal models for both stars. We then selected the best candidates to fit both stars while imposing a common age and composition. Results: We computed realistic ranges of stellar parameters for individual stars. We also provide two models of the system regarded as a whole. We were not able to build binary models with the whole set of choices of input physics considered for individual stars as our constraints seem too stringent. We may need to include additional parameters to the optimal model search or invoke non-standard physical processes., Comment: 25 pages, Accepted for publication in Astronomy and Astrophysics

In a series of papers, we have recently demonstrated that it is possible to construct stellar structure models that robustly mimic the stratification of multi-dimensional radiative magneto-hydrodynamic simulations at every time-step of the computed evolution. The resulting models offer a more realistic depiction of the near-surface layers of stars with convective envelopes than parameterizations, such as mixing length theory, do. In this paper, we explore how this model improvement impacts on seismic and non-seismic properties of stellar models across the Hertzsprung-Russell diagram. We show that the improved description of the outer boundary layers alters the predicted global stellar properties at different evolutionary stages. In a hare and hound exercise, we show that this plays a key role for asteroseismic analyses, as it, for instance, often shifts the inferred stellar age estimates by more than 10 per cent. Improper boundary conditions may thus introduce systematic errors that exceed the required accuracy of the PLATO space mission. Moreover, we discuss different approximations for how to compute stellar oscillation frequencies. We demonstrate that the so-called gas $\Gamma_1$ approximation performs reasonably well for all main-sequence stars. Using a Monte Carlo approach, we show that the model frequencies of our hybrid solar models are consistent with observations within the uncertainties of the global solar parameters when using the so-called reduced $\Gamma_1$ approximation., Comment: Submitted to MNRAS

Apsidal motion in massive eccentric binaries offers precious information about the internal structure of the stars. This is especially true for twin binaries consisting of two nearly identical stars. We make use of the tidally induced apsidal motion in the twin binary HD152248 to infer constraints on the internal structure of the O7.5 III-II stars composing this system. We build stellar evolution models with the code Cl\'es assuming different prescriptions for the internal mixing occurring inside the stars. We identify the models that best reproduce the observationally determined present-day properties of the components of HD152248, as well as their $k_2$, and the apsidal motion rate of the system. We analyse the impact of some poorly constrained input parameters, including overshooting, turbulent diffusion, and metallicity. We further build 'single' and 'binary' GENEC models that account for stellar rotation to investigate the impacts of binarity and rotation. We discuss some effects that could bias our interpretation of the apsidal motion in terms of the internal structure constant. Reproducing the observed $k_2$ value and rate of apsidal motion simultaneously with the other stellar parameters requires a significant amount of internal mixing or enhanced mass-loss. The results suggest that a single-star evolution model is sufficient to describe the physics inside this binary system. Qualitatively, the high turbulent diffusion required to reproduce the observations could be partly attributed to stellar rotation. Higher-order terms in the apsidal motion are negligible. Only a very severe misalignment of the rotation axes could significantly impact the rate of apsidal motion, but such a high misalignment is highly unlikely in such a binary system. We infer an age estimate of $5.15\pm0.13$ Myr for the binary and initial masses of $32.8\pm0.6$ M$_\odot$ for both stars., Comment: 16 pages, A&A accepted

The Sun constitutes an excellent laboratory of fundamental physics. With the advent of helioseismology, we were able to probe its internal layers with unprecedented precision. However, the current state of solar modelling is still stained by tedious issues. One of these problems is related to the disagreement between models computed with recent photospheric abundances and helioseismic constraints. We use solar evolutionary models as initial conditions for reintegrations of their structure using Ledoux discriminant inversions. The resulting models are defined as seismic solar models, satisfying the equations of hydrostatic equilibrium. They will allow us to better constrain the internal structure of the Sun and provide complementary information to that of evolutionary models. These seismic models were computed using various reference models with different equations of state, abundances and opacity tables. We check the robustness of our approach by confirming the good agreement of our seismic models in terms of sound speed, density and entropy proxy inversions as well as frequency-separation ratios of low-degree pressure modes. Our method allows us to determine with an excellent accuracy the Ledoux discriminant profile of the Sun and compute full profiles of this quantity. Our models show an agreement with seismic data of ~0.1% in sound speed, density and entropy proxy as well as with the observed frequency-separation ratios. They surpass all standard and non-standard evolutionary models including ad-hoc changes aiming at reproducing helioseismic constraints. The obtained seismic Ledoux discriminant profile as well as the consistent structure obtained from our procedure paves the way for renewed attempts at constraining the solar modelling problem and the missing physical processes acting in the solar interior by breaking free from the hypotheses of evolutionary models., Comment: Accepted for publication in A&A

The standard cosmological model ($\Lambda$-CDM) predicts that galaxies are built through hierarchical assembly on cosmological timescales$^{1,2}$. The Milky Way, like other disc galaxies, underwent violent mergers and accretion of small satellite galaxies in its early history. Thanks to Gaia-DR2$^3$ and spectroscopic surveys$^4$, the stellar remnants of such mergers have been identified$^{5-7}$. The chronological dating of such events is crucial to uncover the formation and evolution of the Galaxy at high redshift, but it has so far been challenging owing to difficulties in obtaining precise ages for these oldest stars. Here we combine asteroseismology -- the study of stellar oscillations -- with kinematics and chemical abundances, to estimate precise stellar ages ($\sim$ 11%) for a sample of stars observed by the $\mathit{Kepler}$ space mission$^8$. Crucially, this sample includes not only some of the oldest stars that were formed inside the Galaxy, but also stars formed externally and subsequently accreted onto the Milky Way. Leveraging this resolution in age, we provide compelling evidence in favour of models in which the Galaxy had already formed a substantial population of its stars (which now reside mainly in its thick disc) before the in-fall of the satellite galaxy Gaia-Enceladus/Sausage$^{5,6}$ around 10 billions years ago, Comment: Updated with the final version accepted for publication as a Letter in Nature Astronomy (29 pages, 10 figures, 2 tables, including main article and methods section). Improved presentation of results, which have not changed from the previous version

[Abridged] Ensemble studies of red-giant stars with exquisite asteroseismic, spectroscopic, and astrometric constraints offer a novel opportunity to recast and address long-standing questions concerning the evolution of stars and of the Galaxy. Here, we infer masses and ages for nearly 5400 giants with available Kepler light curves and APOGEE spectra, and discuss some of the systematics that may affect the accuracy of the inferred stellar properties. First, we look at age-chemical-abundances relations. We find a dearth of young, metal-rich stars, and the existence of a significant population of old (8-9 Gyr), low-[$\alpha$/Fe], super-solar metallicity stars, reminiscent of the age and metallicity of the well-studied open cluster NGC6791. The age-chemo-kinematic properties of these stars indicate that efficient radial migration happens in the thin disk. We find that ages and masses of the nearly 400 $\alpha$-element-rich red-giant-branch (RGB) stars in our sample are compatible with those of an old (~11 Gyr), nearly coeval, chemical-thick disk population. Using a statistical model, we show that 95% of the population was born within ~1.5 Gyr. Moreover, we find a difference in the vertical velocity dispersion between low- and high-[$\alpha$/Fe] populations, confirming their different chemo-dynamical histories. We then exploit the almost coeval $\alpha$-rich population to gain insight into processes that may have altered the mass of a star along its evolution, which are key to improve the mapping of the observed stellar mass to age. We find evidence for a mean integrated RGB mass loss <$\Delta$M>= 0.10 $\pm$ 0.02 Msun and that the occurrence of massive (M $\gtrsim$ 1.1 Msun) $\alpha$-rich stars is of the order of 5% on the RGB, and significantly higher in the RC, supporting the scenario in which most of these stars had undergone interaction with a companion., Comment: accepted for publication in A&A, 26 pages, 24 figures, catalogue available via cds