We present a novel technique that uses the autocorrelation of the spectrum of a star to measure the line broadening caused by the modulus of its average surface magnetic field. The advantage of the autocorrelation comes from the fact that it can detect very small spectral line broadening effects because it averages over many spectral lines and therefore gives an average with a very high signal to noise ratio. We validate the technique with the spectra of known magnetic stars and obtain autocorrelation curves that are in full agreement with published magnetic curves obtained with Zeeman splitting. The autocorrelation also gives less noisy curves so that it can be used to obtain very accurate curves. We degrade the resolution of spectra of these magnetic stars to lower spectral resolutions where the Zeeman splitting is undetectable. At these resolutions, the autocorrelation still gives good quality curves, thereby showing that it can be used to measure magnetic fields in spectra where the Zeeman splitting is significantly smaller than the width of the spectral line. This would therefore allow observing magnetic fields in very faint Ap stars with low-resolution spectrographs, thereby greatly increasing the number of known magnetic stars. It also demonstrates that the autocorrelation can measure magnetic fields in rapidly rotating stars as well as weak magnetic fields that give a Zeeman splitting smaller than the intrinsic width of the spectral lines. Finally, it shows that the autocorrelation can be used to find unknown magnetic stars in low resolution spectroscopic surveys.
We perform photometric (the Lomb-Scargle periodogram, autocorrelation, and wavelet) and asteroseismic analyses of 92 Kepler solar-like main-sequence stars to understand the reliability of the measured stellar rotation periods. We focus on the 70 stars without reported stellar companions, and classify them into four groups according to the quarter-to-quarter variance of the Lomb-Scargle period and the precision of the asteroseismic period. We present detailed individual comparison among photometric and asteroseismic constraints for these stars. We find that most of our targets exhibit significa…
Spinspotter is a robust and automated algorithm designed to extract stellar rotation periods from large photometric datasets with minimal supervision. Our approach uses the autocorrelation function (ACF) to identify stellar rotation periods up to one-third the observational baseline of the data. Our algorithm also provides a suite of diagnostics that describe the features in the ACF, which allows the user to fine-tune the tolerance with which to accept a period detection. We apply it to approximately 130,000 main-sequence stars observed by the Transiting Exoplanet Survey Satellite (TESS) at 2-…
Context: The study of stellar structure and evolution depends crucially on accurate stellar parameters. The photometry from space telescopes has provided superb data that allowed asteroseismic characterisation of thousands of stars. However, typical targets of space telescopes are rather faint and complementary measurements are difficult to obtain. On the other hand, the brightest, otherwise well-studied stars, are lacking seismic characterization. Aims: Our goal is to use the granulation and/or oscillation time scales measured from photometric time series of bright red giants (1.6$\leq$Vmag$\…
Rotational modulation of stellar light curves due to dark spots encloses information on spot properties and, thus, on magnetic activity. In particular, the decay of the autocorrelation function (ACF) of light curves is presumed to be linked to spot/active-region lifetimes, given that some coherence of the signal is expected throughout their lifetime. In the literature, an exponential decay has been adopted to describe the ACF. Here, we investigate the relation between the ACF and the active-region lifetimes. For this purpose, we produce artificial light curves of rotating spotted stars with di…
Measurements of microturbulence of Cepheids using the autocorrelation function
自相关函数（ACF）是一种简单而有用的工具，可以非常精确地测量光谱的平均线宽。与交叉关联函数（CCF）不同，可以使用ACF而不必依赖于加权二进制掩码。这使得ACF更容易使用。我们分析了7颗造父变星，并提出了一种新的方法来获得非常精确的湍流速度曲线，其中6个使用ACF。我们将我们的半峰全宽（FWHM）曲线作为脉动相位的函数与Nardetto等人（2006）的曲线进行了比较，后者仅使用Fe I 6056.005谱线。我们注意到一个显着的改善，所有造父变星的FWHM曲线的形状，通过使用ACF。从半高宽曲线，我们测量了6个造父变星的微湍流曲线，采用高斯近似。最后，我们人为地降低光谱的分辨率并添加噪声，以进一步评估和突出ACF的优点。用ACF获得的FWHM曲线几乎保持不变，直到退化10倍。由20倍的退化轻微影响的结果，但平均线宽的变化仍然很容易检测。
Asteroseismology of solar-like oscillators often relies on the comparisons between stellar models and stellar observations in order to determine the properties of stars. The values of the global seismic parameters, $ν_\mathrm{max}$ (the frequency where the smoothed amplitude of the oscillations peak) and $Δν$ (the large frequency separation), are frequently used in grid-based modeling searches. However, the methods by which $Δν$ is calculated from observed data and how $Δν$ is calculated from stellar models are not the same. Typically for observed stars, especially for those with low signal-to…
We have determined new statistical relations to estimate the fundamental atmospheric parameters of effective temperature and surface gravity, using MK spectral classification, and vice versa. The relations were constructed based on the published calibration tables (for main sequence stars) and observational data from stellar spectral atlases (for giants and supergiants). These new relations were applied to field giants with known atmospheric parameters, and the results of the comparison of our estimations with available spectral classification had been quite satisfactory.
Stellar activity mitigation is one of the major challenges for the detection of earth-like exoplanets in radial velocity (RV) measurements. Several promising techniques are now investigating the use of spectral time-series, to differentiate between stellar and planetary perturbations. In this paper, we present a new version of the Spot Oscillation And Planet (SOAP) 2.0 code that can model stellar activity at the spectral level using graphical processing units (GPUs). We take advantage of the computational power of GPUs to optimise the computationally expensive algorithms behind the original SO…
Stellar Spectral Signatures in High-Redshift Galaxies
恒星的发射线和吸收线通常在星系中用8- 10米级望远镜上的摄谱仪在红移高达5处观测到。虽然整体光谱是很好的理解，并已成功地使用经验和理论库建模，一些挑战仍然存在。讨论了三个问题：利用恒星和星际谱线确定丰度，了解强恒星He II 1640谱线的起源，并测量恒星Lyman-α对恒星+星云组合剖面的影响。所有这三个问题都可以通过最近建立的热恒星理论恒星库来解决，这些恒星库考虑到了恒星风的辐射流体动力学。
Stellar spectra encode detailed information about the stars. However, most machine learning approaches in stellar spectroscopy focus on supervised learning. We introduce Mendis, an unsupervised learning method, which adopts normalizing flows consisting of Neural Spline Flows and GLOW to describe the complex distribution of spectral space. A key advantage of Mendis is that we can describe the conditional distribution of spectra, conditioning on stellar parameters, to unveil the underlying structures of the spectra further. In particular, our study demonstrates that Mendis can robustly capture t…
Stellar population synthesis (SPS) models are invaluable to study star clusters and galaxies. They provide means to extract stellar masses, stellar ages, star formation histories, chemical enrichment and dust content of galaxies from their integrated spectral energy distributions, colours or spectra. As most models, they contain uncertainties which can hamper our ability to model and interpret observed spectra. This work aims at studying a specific source of model uncertainty: the choice of an empirical vs. a synthetic stellar spectral library. Empirical libraries suffer from limited coverage …
Due to the ever-expanding volume of observed spectroscopic data from surveys such as SDSS and LAMOST, it has become important to apply artificial intelligence (AI) techniques for analysing stellar spectra to solve spectral classification and regression problems like the determination of stellar atmospheric parameters Teff, log g, [Fe/H]. We propose an automated approach for the classification of stellar spectra in the optical region using Convolutional Neural Networks. Traditional machine learning (ML) methods with "shallow" architecture (usually up to 2 hidden layers) have been trained for th…
We present a new library of semi-empirical stellar spectra that is based on the empirical MILES library. A new, high resolution library of theoretical stellar spectra is generated that is specifically designed for use in stellar population studies. We test these models across their full wavelength range against other model libraries and find reasonable agreement in their predictions of spectral changes due to atmospheric $α$-element variations, known as differential corrections. We also test the models against the MILES and MaStar libraries of empirical stellar spectra and also find reasonable…
Theoretical stellar spectra rely on model stellar atmospheres computed based on our understanding of the physical laws at play in the stellar interiors. These models, coupled with atomic and molecular line databases, are used to generate theoretical stellar spectral libraries (SSLs) comprising of stellar spectra over a regular grid of atmospheric parameters (temperature, surface gravity, abundances) at any desired resolution. Another class of SSLs is referred to as empirical spectral libraries; these contain observed spectra at limited resolution. SSLs play an essential role in deriving the pr…
We use the first release of the SDSS/MaStar stellar library comprising ~9000, high S/N spectra, to calculate integrated spectra of stellar population models. The models extend over the wavelength range 0.36-1.03 micron and share the same spectral resolution (R~1800) and flux calibration as the SDSS-IV/MaNGA galaxy data. The parameter space covered by the stellar spectra collected thus far allows the calculation of models with ages and chemical composition in the range t>200 Myr, -2 <=[Z/H]<= + 0.35, which will be extended as MaStar proceeds. Notably, the models include spectra for dwarf Main S…
Interpreting the oscillations of massive and intermediate mass stars remains a challenging task. In fast rotators, the oscillation spectrum of p-modes is a superposition of sub-spectra which correspond to different types of modes, among which island modes and chaotic modes are expected to be the most visible. In the case of island modes, a semi-analytic formula describing the asymptotic behavior of island modes has been obtained previously. We study the properties of high frequency chaotic p-modes in a polytropic model. Unexpected peaks appear in the frequency autocorrelations of the spectra. …
Stellar spectra contain a large amount of information about the conditions in stellar atmospheres. However, extracting this information is challenging and demands comprehensive numerical modelling. Here, we present stellar spectra synthesized using the recently developed state-of-the-art MPS-ATLAS code on a fine grid of stellar fundamental parameters. These calculations have been extensively validated against solar and stellar observations and can be used for various astrophysical applications. The spectra are available at the Max Planck Digital Library (MPDL, https://edmond.mpdl.mpg.de/datase…
Uncertainties in stellar population models, both in terms of stellar evolution and stellar spectra, translate into uncertainties in our interpretation of stellar populations in galaxies, since stars are the source of most of the light we receive from them. Observations by JWST are revealing high-redshift galaxies in great detail, which must then be compared to models. One significant source of uncertainty is in the stellar spectra used to generate composite spectra of stellar populations, which are then compared to data. Confidence in theoretical models is important to enable reliable determin…
