Precise determination of fundamental parameters of six exoplanet host stars and their planets

The aim of this paper is to determinate the fundamental parameters of six exoplanet host （EH） stars and their planets. Because techniques for detecting exo- planets yield properties of the planet only as a function of the properties of the host star, we must accurately determine the parameters of the EH stars first. For this rea- son, we constructed a grid of stellar models including diffusion and rotation-induced extra-mixing with given ranges of input parameters （i.e. mass, metallicity and initial rotation rate）. In addition to the commonly used observational constraints such as the effective temperature Tell, luminosity L and metallicity [Fe/H], we added two obser- vational constraints, the lithium abundance log N （Li） and the rotational period Prot. These two additional observed parameters can set further constraints on the model due to their correlations with mass, age and other stellar properties. Hence, our estimations of the fundamental parameters for these EH stars and their planets have a higher preci- sion than previous works. Therefore, the combination of rotational period and lithium helps us to obtain more accurate parameters for stars, leading to an improvement in knowledge about the physical state of EH stars and their planets.

Two-dimensional Parameter Relationships for W UMa-type Systems Revisited

Reviewing the empirical and theoretical parameter relationships between various parameters is a good way to understand more about contact binary systems.In this investigation,two-dimensional(2D)relationships for P–MV(system),P–L1,2,M1,2–L1,2,and q–Lratiowere revisited.The sample used is related to 118 contact binary systems with an orbital period shorter than 0.6 days whose absolute parameters were estimated based on the Gaia Data Release 3 parallax.We reviewed previous studies on 2D relationships and updated six parameter relationships.Therefore,Markov chain Monte Carlo and Machine Learning methods were used,and the outcomes were compared.We selected 22 contact binary systems from eight previous studies for comparison,which had light curve solutions using spectroscopic data.The results show that the systems are in good agreement with the results of this study.

Relations between SMBH Parameters and Jet Generation and Efficiency in Blazars

We analyzed the relationship between several basic parameters describing supermassive black holes such as jet power,black hole spin,accretion disk magnetic field,black hole mass,etc.We found that there is a general correlation between these parameters,such as jet power is significantly positively correlated with black hole spin,while black hole mass is significantly negatively correlated with black hole spin.To apprehend these relationships,we consider the Blandford–Znajek model to be superior to the Blandford–Payne model.It is also found that the intrinsic gamma luminosity of the FSRQs has a positive correlation with the accretion disk magnetic field,while the intrinsic gamma luminosity of the BL Lacs has a negative correlation with the accretion disk magnetic field.A feedback effect may exist between accretion disk accretion rate and magnetic field,which may be the key to the evolution between BL Lacs and FSRQs.There is no significant difference in the jet power and jet generation efficiency of FSRQs and BL Lacs,which suggests that the jets are generated by the same mechanism.The contribution rate of accretion rate to jet generation efficiency is high,while the contribution rate of accretion rate to jet power is very low.

Understanding the Predication Mechanism of Deep Learning through Error Propagation among Parameters in Strong Lensing Case

The error propagation among estimated parameters reflects the correlation among the parameters.We study the capability of machine learning of"learning"the correlation of estimated parameters.We show that machine learning can recover the relation between the uncertainties of different parameters,especially,as predicted by the error propagation formula.Gravitational lensing can be used to probe both astrophysics and cosmology.As a practical application,we show that the machine learning is able to intelligently find the error propagation among the gravitational lens parameters(effective lens mass ML and Einstein radiusθ_(E))in accordance with the theoretical formula for the singular isothermal ellipse(SIE)lens model.The relation of errors of lens mass and Einstein radius,(e.g.,the ratio of standard deviations F=σ_(ML)/σ_(θ_(E)))predicted by the deep convolution neural network are consistent with the error propagation formula of the SIE lens model.As a proof-of-principle test,a toy model of linear relation with Gaussian noise is presented.We found that the predictions obtained by machine learning indeed indicate the information about the law of error propagation and the distribution of noise.Error propagation plays a crucial role in identifying the physical relation among parameters,rather than a coincidence relation,therefore we anticipate our case study on the error propagation of machine learning predictions could extend to other physical systems on searching the correlation among parameters.

Correction Factors of the Measurement Errors of the LAMOST-LRS Stellar Parameters

We aim to investigate the propriety of stellar parameter errors of the official data release of the LAMOST lowresolution spectroscopy(LRS)survey.We diagnose the errors of radial velocity(RV),atmospheric parameters([Fe/H],Teff,logg)andα-enhancement([α/M])for the latest data release version of DR7,including 6,079,235effective spectra of 4,546,803 stars.Based on the duplicate observational sample and comparing the deviation of multiple measurements to their given errors,we find that,in general,the error of[α/M]is largely underestimated,and the error of RV is slightly overestimated.We define a correction factor k to quantify these misestimations and correct the errors to be expressed as proper internal uncertainties.Using this self-calibration technique,we find that the k-factors significantly vary with the stellar spectral types and the spectral signal-to-noise ratio(S/N).Particularly,we reveal a strange but evident trend between k-factors and error themselves for all five stellar parameters.Larger errors tend to have smaller k-factor values,i.e.,they were more overestimated.After the correction,we recreate and quantify the tight correlations between S/N and errors,for all five parameters,while these correlations have dependence on spectral types.It also suggests that the parameter errors from each spectrum should be corrected individually.Finally,we provide the error correction factors of each derived parameter of each spectrum for the entire LAMOST-LRS DR7 and plan to update them for the later data releases.

Long-term Speckle Interferometric Monitoring of Binary Systems:2007–2023Positional Measurements and Orbits of Seven Objects

The results of seventeen years of speckle interferometric monitoring of seven objects(Chara 122Aa,GJ 3010,HIP1987,GJ 3076,HIP 11253,HIP 11352,and HIP 14929)are presented.Observational data were obtained at the 6 m Big Telescope Alt-azimuthal Special Astrophysical Observatory of the Russian Academy of Science(BTA SAO RAS)from 2007 to the present.Analysis of previously published and new measurements made it possible to construct completely new orbits for Chara 122Aa,HIP 11253,and HIP 14929.The orbit of GJ 3076 cannot be constructed accurately due to the large influence of the weights assigned to the measurements.The resulting orbital solutions are classified based on a grading scheme suggested by W.I.Hartkopf,B.D.Mason and C.E.Worley;most orbits are“definitive”(Grade 1).The mass sums and masses of components calculated by two independent methods using Hipparcos and Gaia DR2 and DR3 parallaxes were compared for the objects under study.

BSEC Method for Unveiling Open Clusters and its Application to Gaia DR3:83 New Clusters

Open clusters(OCs) are common in the Milky Way, but most of them remain undiscovered. There are numerous techniques, including some machine-learning algorithms, available for the exploration of OCs. However, each method has its limitations and therefore, different approaches to discovering OCs hold significant values. We develop a comprehensive approach method to automatically explore the data space and identify potential OC candidates with relatively reliable membership determination. This approach combines the techniques of Hierarchical Density-Based Spatial Clustering of Applications with Noise, Gaussian mixture model, and a novel cluster member identification technique, color excess constraint. The new method exhibits efficiency in detecting OCs while ensuring precise determination of cluster memberships. Because the main feature of this technique is to add an extra constraint(EC) for the members of cluster candidates using the homogeneity of color excess,compared to typical blind search codes, it is called Blind Search-Extra Constraint(BSEC) method. It is successfully applied to the Gaia Data Release 3, and 83 new OCs are found, whose color–magnitude diagrams(CMDs) are fitted well to the isochrones. In addition, this study reports 621 new OC candidates with discernible main sequence or red giant branch. It is shown that BSEC technique can discard some false negatives of previous works, which takes about three percentage of known clusters. It shows that as an EC, the color excess(or twocolor) constraint is useful for removing fake cluster member stars from the clusters that are identified from the positions and proper motions of stars, and getting more precise CMDs, when differential reddening of member stars of a cluster is not large(e.g., ΔE(G_(BP)-G_(RP)) < 0.5 mag). It makes the CMDs of 15% clusters clearer(in particular for the region near turnoff) and therefore is helpful for CMD and stellar population studies. Our result suggests that the color excess constraint is more appropriate for clusters with small differential reddening, such as globular clusters or older OCs, and clusters that the distances of member stars cannot be determined accurately.

Study of 26 Galactic Open Clusters with Extended Main-sequence Turnoffs

Recent studies indicate that some Galactic open clusters(OCs)exhibit extended main-sequence turnoff(eMSTO)in their color–magnitude diagrams(CMDs).However,the number of Galactic OCs with eMSTO structures detected so far is limited,and the reasons for their formation are still unclear.This work identifies 26 Galactic OCs with undiscovered eMSTOs and investigates the causes of these features.Stellar population types and fundamental parameters of cluster samples are acquired using CMD fitting methods.Among them,the results of 11 OCs are reliable as the observed CMDs are well-reproduced.We propose the crucial role of stellar binarity and confirm the importance of stellar rotation in reproducing eMSTO morphologies.The results also show that the impact of age spread is important,as it can adequately explain the structure of young OCs and fit the observed CMDs of intermediate-age OCs better.

Physical and geometrical parameters of CVBS X:the spectroscopic binary Gliese 762.1

We present the physical and geometrical parameters of the individual components of the close visual double-lined spectroscopic binary system Gliese 762.1, which were estimated using Al-Wardat＇s complex method for analyzing close visual binary systems. The estimated parameters of the individual components of the system are as follows： radius RA= 0.845±0.09R⊙, RB= 0.795±0.10R⊙, effective temperature Teff^A = 5300luminosity±50 K, Teff^B= 5150 L±50 K, surface gravity log gA= 4.52±0.10, log gB=4.54±0.15 and A= 0.51 with a semi-major axis of 0.0865±0.08L⊙, LB= 0.40±0.07L⊙. New orbital elements are presented±0.010 arcsec using the Hippracos parallax π = 58.96 ndividual masses of the system are determined as M = 1.±0.65 mas, and an accurate total mass and i72±0.60 M⊙,MA= 0.89±0.08 M⊙and MB= 0.83 K0 V and±0.07 M⊙. Finally, the spectral types and luminosity classes of both components are assigned as K1.5V for the primary and secondary components respectively,and their positions on the H-R diagram and evolutionary tracks are given.

Physical and geometrical parameters of VCBS XIII: HIP 105947

The best physical and geometrical parameters of the main sequence close visual binary system(CVBS), HIP 105947, are presented. These parameters have been constructed conclusively using Al-Wardat’s complex method for analyzing CVBSs, which is a method for constructing a synthetic spectral energy distribution(SED) for the entire binary system using individual SEDs for each component star. The model atmospheres are in its turn built using the Kurucz(ATLAS9) line-blanketed plane-parallel models. At the same time, the orbital parameters for the system are calculated using Tokovinin’s dynamical method for constructing the best orbits of an interferometric binary system. Moreover, the mass-sum of the components, as well as the ?θ and ?ρ residuals for the system, is introduced. The combination of Al-Wardat’s and Tokovinin’s methods yields the best estimations of the physical and geometrical parameters. The positions of the components in the system on the evolutionary tracks and isochrones are plotted and the formation and evolution of the system are discussed.

Automatic determination of stellar atmospheric parameters and construction of stellar spectral templates of the Guoshoujing Telescope (LAMOST)

A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to- noise ratios （SNR） on the measurement of the stellar atmospheric parameters （effective temperature Teff, surface gravity log g, and metaUicity [Fe/H]）. We show that ULySS is reliable for determining these parameters with medium-resolution spectra （R ～2000）. Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope （LAMOST）. The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline （SSPP）, and we derived precisions of 167 K, 0.34dex, and 0.16dex for Teff, logg and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectral template library （Version 1.0） of LAMOST, and will be deployed as basic ingredients for the LAMOST automated parametrization pipeline.

Physical and geometrical parameters of CVBS Ⅺ: Cou 1511(HIP 12552)

Model atmospheres of the close visual binary star Cou 1511 （HIP 12552） are constructed using grids of Kuruz＇s blanketed models to build the individual synthetic spectral energy distributions （SEDs） for both components. These synthetic SEDs are combined together for the entire system and compared with the observational one following A1-Wardat＇s complex method for analyzing close visual binary stars. The entire observational SED of the system is used as a reference for comparison between the synthetic SED and the observed one. The parameters of both components are derived as： Teff = 6180 4- 50 K, Tebfr = 5865 ＋ 70 K, log 9a = 4.35 ± 0.12, log 9b = 4.45± 0.14, Ra = 1.262 ± 0.08 R⊙^eff, Rb = 1.006 ± 0.07 R⊙^ett, La = 2.09 -4- 0.10 L⊙ and Lb = 1.08 ± 0.12 L⊙, with spectral types F8V and G1.5V for components （a, b） respectively and age of 3.0 ± 0.9 Gyr. A modified orbit of the system is built and the masses of the two components are calculated as Ma = 1.17 ±0.11 Me and Mb = 1.06 ± 0.10 Me.

Stellar parameters of main sequence turn-off star candidates observed with LAMOST and Kepler

Main sequence turn-off （MSTO） stars since their ages can be robustly estimated from have advantages as indicators of Galactic evolution atmospheric parameters. Hundreds of thousands of MSTO stars have been selected from the LAMOST Galactic survey to study the evolution of the Galaxy, and it is vital to derive accurate stellar parameters. In this work, we select 150 MSTO star candidates from the MSTO star sample of Xiang that have asteroseismic parameters and determine accurate stellar parameters for these stars by combining asteroseismic parameters deduced from Kepler photometry and atmospheric parameters deduced from LAMOST spectra. With this sample, we examine the age determination as well as the contamination rate of the MSTO star sample. A comparison of age between this work and Xiang shows a mean difference of 0.53 Gyr （7%） and a dispersion of 2.71 Gyr （28%）. The results show that 79 of the candidates are MSTO stars, while the others are contaminations from either main sequence or sub-giant stars. The contamination rate for the oldest stars is much higher than that for younger stars. The main cause for the high contamination rate is found to be the relatively large systematic bias in the LAMOST surface gravity estimates.

Validation of LAMOST stellar parameters with the PASTEL catalog

The Large Sky Area Multi-Object Fiber Spectroscopic Telescope （LAMOST） published its first data release （DR1） in 2013, which is currently the largest dataset of stellar spectra in the world. We combine the PASTEL catalog and SIMBAD radial velocities as a testing standard to validate stellar parameters （effec- tive temperature Tefr, surface gravity log g, metallicity [Fe/H] and radial velocity Vr） derived from DR1. Through cross-identification of the DR1 catalogs and the PASTEL catalog, we obtain a preliminary sample of 422 stars. After removal of stellar param- eter measurements from problematic spectra and applying effective temperature con- straints to the sample, we compare the stellar parameters from DR1 with those from PASTEL and SIMBAD to demonstrate that the DR1 results are reliable in restricted ranges of Tefr. We derive standard deviations of 110 K, 0.19 dex and 0.11 dex for Tell, log 9 and [Fe/H] respectively when Teff〈 8000 K, and 4.91 km s-1 for Vr when Teff 〈 10 000 K. Systematic errors are negligible except for those of Vr. In addition, metallicities in DR1 are systematically higher than those in PASTEL, in the range of PASTEL [Fe/H] 〈 -1.5.

A comparison of stellar atmospheric parameters from the LAMOST and APOGEE datasets

We have compared stellar parameters, including temperature, gravity and metallicity, for common stars in the LAMOST DR2 and SDSS DR12/APOGEE datasets. It is found that the LAMOST dataset provides a more well-defined red clump feature than the APOGEE dataset in the Teff versus log g diagram. With this advantage, we have separated red clump stars from red giant stars, and attempt to establish calibrations between the two datasets for the two groups of stars. The results show that there is a good consistency in temperature with a calibration close to the one-to-one line, and we can establish a satisfactory metallicity calibration of[Fe/H]APOGEE= 1.18[Fe/H]LAMOST ＋ 0.11 with a scatter of ～ 0.08 dex for both the red clump and red giant branch samples. For gravity, there is no correlation for red clump stars between the two datasets, and scatters around the calibrations of red giant stars are substantial. We found two main sources of scatter in log g for red giant stars. One is a group of stars with 0.00253 × Teff- 8.67 〈 log g 〈 2.6 located in the forbidden region, and the other is the contaminated red clump stars, which could be picked out from the unmatched region where stellar metallicity is not consistent with position in the Teff versus log g diagram. After excluding stars in these two regions,we have established two calibrations for red giant stars, log g APOGEE = 0.000615 ×Teff,LAMOST＋ 0.697 × log g LAMOST- 2.208（σ = 0.150） for [Fe/H] 〉-1 and log gAPOGEE= 0.000874×Teff,LAMOST＋0.588×log g LAMOST-3.117（σ = 0.167）for [Fe/H] 〈-1. The calibrations are valid for stars with Teff = 3800- 5400 K and log g = 0- 3.8 dex, and are useful in work aiming to combine the LAMOST and APOGEE datasets in a future study. In addition, we find that an SVM method based on asteroseismic log g is a good way to greatly improve the accuracy of gravity for these two regions, at least in the LAMOST dataset.

Estimating stellar atmospheric parameters based on Lasso features

With the rapid development of large scale sky surveys like the Sloan Digital Sky Survey （SDSS）, GAIA and LAMOST （Guoshoujing telescope）, stellar spectra can be obtained on an ever-increasing scale. Therefore, it is necessary to estimate stel- lar atmospheric parameters such as Teff, log g and [Fe/H] automatically to achieve the scientific goals and make full use of the potential value of these observations. Feature selection plays a key role in the automatic measurement of atmospheric parameters. We propose to use the least absolute shrinkage selection operator （Lasso） algorithm to select features from stellar spectra. Feature selection can reduce redundancy in spectra, alleviate the influence of noise, improve calculation speed and enhance the robustness of the estimation system. Based on the extracted features, stellar atmospheric param- eters are estimated by the support vector regression model. Three typical schemes are evaluated on spectral data from both the ELODIE library and SDSS. Experimental results show the potential performance to a certain degree. In addition, results show that our method is stable when applied to different spectra.

Parameterizing Stellar Spectra Using Deep Neural Networks

Large-scale sky surveys are observing massive amounts of stellar spectra. The large number of stellar spectra makes it necessary to automatically parameterize spectral data, which in turn helps in statistically exploring properties related to the atmospheric parameters. This work focuses on designing an automatic scheme to estimate effective temperature （Tee）, surface gravity （log g） and metallicity [Fe/H] from stellar spectra. A scheme based on three deep neural networks （DNNs） is proposed. This scheme consists of the following three procedures： first, the configuration of a DNN is initialized using a series of autoencoder neural networks; second, the DNN is fine-tuned using a gradient descent scheme; third, three atmospheric parameters Tefr, log 9 and [Fe/H] are estimated using the computed DNNs. The constructed DNN is a neural network with six layers （one input layer, one output layer and four hidden layers）, for which the number of nodes in the six layers are 3821, 1000, 500, 100, 30 and 1, respectively. This proposed scheme was tested on both real spectra and theoretical spectra from Kurucz＇s new opacity distribution function models. Test errors are measured with mean absolute errors （MAEs）. The errors on real spectra from the Sloan Digital Sky Survey （SDSS） are 0.1477, 0.0048 and 0.1129 dex for log 9, log Tefr and [Fe/H] （64.85 K for Teff）, respectively. Regarding theoretical spectra from Kurucz＇s new opacity distribution function models, the MAE of the test errors are 0.0182, 0.0011 and 0.0112 dex for log 9, log Teff and [Fe/H] （14.90 K for Tdf）, respectively.

Absolute parameters of the three totally-eclipsing W UMa stars NSVS 2443858,NSVS 780649 and V1098 Her

We present the first photometric analysis of three totally-eclipsing W UMa binaries,NS VS2443858,NSVS 780649 and V1098 Her.The absolute astrophysical parameters of the stellar components were determined by means of Gaia distances and light curve solutions.The results show that:(ⅰ)Two of the systems,NSVS 2443858 and V1098 Her,are of A subtype while the obtained temperature of the secondary component of NSVS 780649 indicates that it is a W-subtype system;(ⅱ)The estimated mass ratios approach the lower limit of the mass ratio assumed by researchers in recent years so our targets could be classified as extreme mass ratio binary(EMRB)systems;(ⅲ)All the systems have deep contact configurations,so they also are deep low mass ratio(DLMR)systems;(ⅳ)The components of our systems are stars of F and G spectral type and undergo total eclipses;(ⅴ)The sum 0.871 M⊙of the component masses of NSVS 780649 is below the mass limit of 1.0-1.2 M⊙assumed for the known contact binary stars.

Three-dimensional orbit and physical parameters of HD 6840

HD 6840 is a double-lined visual binary with an orbital period of N7.5 years. By fitting the speckle interferometric measurements made by the 6 m BTA telescope and 3.5 m WIYN telescope, Balega et al. gave a preliminary astrometric orbital solution of the system in 2006. Recently, Griffin derived a precise spectroscopic orbital solution from radial velocities observed with OPH and Cambridge Coravel. However, due to the low precision of the determined orbital inclination, the derived component masses are not satisfying. By adding the newly collected astrometric data in the Fourth Catalog of Interferometric Measurements of Binary Stars, we give a three-dimensional orbit solution with high precision and derive the preliminary physical parameters of HD 6840 via a simultaneous fit including both astrometric and radial velocity measurements.

Irregular Spatial Distributions of Spectral Line Parameters in the Middle Solar Chromosphere Revealed from Analysis of Solar Flash MgⅠb_(2)Spectra

This paper presents the analytical results of solar MgⅠb_(2)flash spectra,obtained by the prototype Fiber Arrayed Solar Optic Telescope in process of the 2013 Gabon total solar eclipse.The analysis reveals irregular distributions of the spectral line parameters like ratio of line source function to continuum oneβ,ratio of line emissivity to continuum emissivityζ,ratio of the continuum opacity to the line opacity r_(0),line center optical depthτ_(0)、,the line widthΔλ_(D),and the line-of-sight velocity v_(los),while the approximately spherical symmetry can be found in the maps of integrated line intensity and continuum intensity.These irregular distributions originate from those of line profile features like the maximum intensity,the line width and line center wavelength.It is also found from the recovered line center optical depthτ_(0) that in the middle chromosphere,the optical depth is not small due to nonignorable absorption and the long light path along the line-of-sight.Finally,we show that the excessive broadening of spectral lines can be due to co-existence of multiple radiative sources with different line-of-sight velocities unresolved in one detector pixel.