Variable Stars Research Articles

ASIVA – Platform for observational and computational analysis of stellar variables

The astronomical data analysis consists of two crucial process; data reduction of the captured images and data analysis of the derived magnitudes. We present the platform ASIVA, a data analysis platform which comes along with a data reduction pipeline. The data reduction pipeline gives flexibility to analyse the FITS images and also perform image alignment for detecting the correct image coordinates for required objects. It can be custom scheduled with cron jobs so that it picks the latest data and appends the results accordingly. The data analysis platform allows user to effectively analyse the ensemble data and perform accurate data processing and grouping with ease. It is integrated with a custom algorithm to detect the variable stars from an ensemble with its relative standard deviations. The statistical, spectral and non-linear dynamics features can be extracted from time series data which can be eventually used for in-depth analysis. To validate the capability, we have analysed 15 nights of Orion Nebula Cluster field in I filter which had 1585 images. ASIVA reduces manual effort to a great extent thus saves analysis time and excludes human errors.

Detection of Contact Binary Candidates Observed By TESS Using the Autoencoder Neural Network

A contact binary may be the progenitor of a red nova that eventually produces a merger event and have a cut-off period of around 0.2 days. Therefore, a large number of contact binaries is needed to search for the progenitor of red novae and to study the characteristics of short-period contact binaries. In this paper, we employ the Phoebe program to generate a large number of light curves based on the fundamental parameters of contact binaries. Using these light curves as samples, an autoencoder model is trained, which can reconstruct the light curves of contact binaries very well. When the error between the output light curve from the model and the input light curve is large, it may be due to other types of variable stars. The goodness of fit (R 2) between the output light curve from the model and the input light curve is calculated. Based on the thresholds for global goodness of fit (R 2), period, range magnitude, and local goodness of fit (R 2), a total of 1322 target candidates were obtained.

Gaia23ckh: Symbiotic outburst of the assumed Mira variable V390 Sco

AbstractThe poorly studied variable star V390 Sco, previously classified as a Mira pulsator, was detected in a brightening event by the ESA Gaia satellite in September 2023. This work presents an analysis of available archival multifrequency photometric data of this target, along with our spectroscopic observations. Our findings lead to the conclusion that V390 Sco is a new symbiotic star identified by Gaia, currently undergoing a classical symbiotic outburst. Additionally, we uncovered three prior outbursts of this system through archival photometry. The outbursts recur approximately every 2330–2400 days, and we hypothesize the periastron passage in an eccentric orbit may trigger them, similarly to the case of BX Mon, DD Mic, or MWC 560. A detailed investigation into the nature of the donor star suggested that V390 Sco is an S‐type symbiotic star, likely hosting a less evolved, semiregularly pulsating giant donor, but not a Mira variable.

FINKER: Frequency Identification through Nonparametric KErnel Regression in astronomical time series

Optimal frequency identification in astronomical datasets is crucial for variable star studies, exoplanet detection, and asteroseismology. Traditional period-finding methods often rely on specific parametric assumptions, employ binning procedures, or overlook the regression nature of the problem, limiting their applicability and precision. We introduce a universal, nonparametric kernel regression method for optimal frequency determination that is generalizable, efficient, and robust across various astronomical data types. FINKER uses nonparametric kernel regression on folded datasets at different frequencies, selecting the optimal frequency by minimising squared residuals. This technique inherently incorporates a weighting system that accounts for measurement uncertainties and facilitates multi-band data analysis. We evaluated our method's performance across a range of frequencies pertinent to diverse data types and compared it with an established period-finding algorithm, conditional entropy. The method demonstrates superior performance in accuracy and robustness compared to existing algorithms, requiring fewer observations to reliably identify significant frequencies. It exhibits resilience against noise and adapts well to datasets with varying complexity.

Machine learning approach to detect dynamical states from recurrence measures.

We integrate machine learning approaches with nonlinear time series analysis, specifically utilizing recurrence measures to classify various dynamical states emerging from time series. We implement three machine learning algorithms: Logistic Regression, Random Forest, and Support Vector Machine for this study. The input features are derived from the recurrence quantification of nonlinear time series and characteristic measures of the corresponding recurrence networks. For training and testing, we generate synthetic data from standard nonlinear dynamical systems and evaluate the efficiency and performance of the machine learning algorithms in classifying time series into periodic, chaotic, hyperchaotic, or noisy categories. Additionally, we explore the significance of input features in the classification scheme and find that the features quantifying the density of recurrence points are the most relevant. Furthermore, we illustrate how the trained algorithms can successfully predict the dynamical states of two variable stars, SX Her and AC Her, from the data of their light curves. We also indicate how the algorithms can be trained to classify data from discrete systems.

High speed stars

Context. The Gaia satellite has provided the community with three releases containing astrometrical and photometric data as well as by products, such as stellar parameters and variability indicators. Aims. By selecting in the Gaia database, one can select stars with the requested characteristics, such as high speed. At present any selection is based on available Gaia releases including a subset of the observations. This, for some stars, can show some limitations, for example there is still not a sufficient number of observations to detect binarity. Methods. We investigated a star selected in Gaia EDR3 for its high speed that appears unbound to the Galaxy. We requested high-quality spectra to derive more information on the star. Results. From the spectroscopic investigation we confirm the low metallicity content of the star, and we derive a detailed chemical composition. The star is poor in carbon and very rich in oxygen: [(C+N+O)/Fe] = +0.65. From the two spectra observed we conclude that the star is in a binary system and from the investigation of the ionisation balance we derive that the star is closer than implied by the Gaia DR3 parallax, and thus has a a lower intrinsic luminosity. Conclusions. The star is probably still unbound, but there is the possibility that it is bound to the Galaxy. Its low carbon abundance suggests that the star was formed in a dwarf galaxy.

Discovery of the Longest-period Classical Cepheid in the Milky Way

We report the discovery of the classical Cepheid OGLE-GD-CEP-1884 (= GDS_J1535467-555656) with the longest pulsation period known in our Galaxy. The period of 78.14 days is nearly 10 days longer than that of the previous record-holding Cepheid, S Vulpeculae, and thus, OGLE-GD-CEP-1884 can be categorized as the first ultra-long-period Cepheid in the Milky Way. This star is present in the ASAS-SN and Gaia DR3 catalogs of variable stars, but it has been classified as a long-period variable in those catalogs. Based on more than 10 yr of the photometric monitoring of this star carried out by the OGLE project in the I and V bands and a radial velocity curve from the Gaia Focused Product Release, we unequivocally demonstrate that this object is a fundamental-mode classical Cepheid. By employing the mid-infrared period–luminosity relation, we determine the distance to OGLE-GD-CEP-1884 (4.47 ± 0.34 kpc) and place it on the Milky Way map, along with about 2400 other classical Cepheids. We also discuss the potential of finding additional ultra-long-period Cepheids in our Galaxy.

Phenomenon of self-oscillation in bubble dynamics: Bouncing acoustic bubbles

Self-oscillations underlie many natural phenomena, such as heartbeat, ocean waves, and the pulsation of variable stars. From pendulum clocks to the behavior of animal groups, self-oscillation is one of the keys to the understanding of synchronization phenomena and hence to the collective behavior of interacting systems. In this study, we consider two closely spaced bubbles pulsating in the kHz range in response to ultrasonic excitation. A translational bouncing motion emerges from their interaction with a much lower frequency than the bubble pulsation frequency. Our analysis reveals that the observed bubble bouncing exhibits the main features of self-oscillation, such as negative damping and the emergence of a limit cycle. These results highlight unexpected nonlinear effects in the field of microbubbles and give insights into the understanding of synchronization in large bubble clouds.

Signs of magnetic star-planet interactions in HD 118203

Context. Planetary systems with close-in giant planets can experience magnetic star-planet interactions that modify the activity levels of their host stars. The induced activity is known to strongly depend on the magnetic moment of the interacting planet. Therefore, such planet-induced activity should be more readily observable in systems with close-in planets in eccentric orbits, since those planets are expected to rotate faster than in circular orbits. However, no evidence of magnetic interactions has been reported in eccentric planetary systems to date. Aims. We intend to unveil a possible planet-induced activity in the bright (V = 8.05 ± 0.03 mag) and slightly evolved star HD 118203, which is known to host an eccentric (e = 0.32 ± 0.02) and close-in (a = 0.0864 ± 0.0006 au) Jupiter-sized planet. Methods. We characterized the planetary system by jointly modelling 56 ELODIE radial velocities and four sectors of TESS photometry. We computed the generalized Lomb-Scargle periodogram of the TESS, ELODIE, and complementary ASAS-SN data to search for planet-induced and rotation-related activity signals. We studied the possible origins of the stellar variability found, analysed its persistence and evolution, and searched for possible links with the eccentric orbital motion of HD 118203 b. Results. We found evidence of an activity signal within the TESS photometry that matches the 6.1-day orbital period of its hosted planet HD 118203 b, which suggests the existence of magnetic star-planet interactions. We did not find, however, any additional activity signal that could be unambiguously interpreted as the rotation of the star, so we cannot discard stellar rotation as the actual source of the signal found. Nevertheless, both the evolved nature of the star and the significant orbital eccentricity make the synchronous stellar rotation with the planetary orbit very unlikely. Conclusions. The planetary system HD 118203 represents the best evidence that magnetic star–planet interactions can be found in eccentric planetary systems, and it opens the door to future dedicated searches in such systems that will allow us to better understand the interplay between close-in giant planets and their host stars.

Identifying Exoplanet Candidates Using WaveCeptionNet

In this study, we propose a wavelet-transform-based light curve representation method and a CNN model based on Inception-v3 for fast classification of light curves, enabling the quick discovery of potentially interesting targets from massive data. Experimental results on real observation data from the TESS showed that our wavelet processing method achieved about a 32-fold dimension reduction, while largely removing noise. We fed the wavelet-decomposed components of light curves into our improved Inception-v3 CNN model, achieving an accuracy of about 95%. Furthermore, our model achieves F1-scores of 95.63%, 95.93%, 95.65%, and 89.60% for eclipsing binaries, planet candidates, variable stars, and instrument noise, respectively. The precision rate of planet candidates identification reaches 96.49%, and the recall rate reaches 95.38% in the test set. The results demonstrate the effectiveness of our method for light curve.

A survey for variable young stars with small telescopes – IX. Evolution of spot properties on YSOs in IC 5070

ABSTRACT We present spot properties on 32 periodic young stellar objects in IC 5070. Long term, ∼5 yr, light curves in the V, R, and I-bands are obtained through the HOYS (Hunting Outbursting Young Stars) citizen science project. These are dissected into 6 months long slices, with 3 months oversampling, to measure 234 sets of amplitudes in all filters. We fit 180 of these with reliable spot solutions. Two thirds of spot solutions are cold spots, the lowest is 2150 K below the stellar temperature. One third are warm spots that are above the stellar temperature by less than ∼2000 K. Cold and warm spots have maximum surface coverage values of 40 per cent, although only 16 per cent of warm spots are above 20 per cent surface coverage as opposed to 60 per cent of the cold spots. Warm spots are most likely caused by a combination of plages and low-density accretion columns, most common on objects without inner disc excess emission in K − W2. Five small hot spot solutions have <3 per cent coverage and are 3000–5000 K above the stellar temperature. These are attributed to accretion, and four of them occur on the same object. The majority of our objects are likely to be accreting. However, we observe very few accretion hot spots as either the accretion is not stable on our time-scale or the photometry is dominated by other features. We do not identify cyclical spot behaviour on the targets. We additionally identify and discuss a number of objects that have interesting amplitudes, phase changes, or spot properties.

Nature of the diffuse emission sources in the H i supershell in the galaxy IC 1613

ABSTRACT We present a study of the nearby low-metallicity dwarf galaxy IC 1613, focusing on the search for massive stars and related feedback processes, as well as for faint supernova remnants (SNR) in late stages of evolution. We obtained the deepest images of IC 1613 in the narrow-band H α, He ii and [S ii] emission lines and new long-slit spectroscopy observations using several facilities (6-m BTA, 2.5m SAI MSU, and 150RTT telescopes), in combination with the multiwavelength archival data from MUSE/VLT, VLA, XMM–Newton, and Swift/XRT. Our deep narrow-band photometry identifies several faint shells in the galaxy, and we further investigate their physical characteristics with the new long-slit spectroscopy observations and the archival multiwavelength data. Based on energy balance calculations and assumptions about their possible nature, we propose that one of the shells is a possible remnant of a supernova explosion. We study five out of eight Wolf–Rayet (WR) star candidates previously published for this galaxy using the He ii emission line mapping, MUSE/VLT archival spectra, and new long-slit spectra. Our analysis discards the considered WR candidates and finds no new ones. We found P Cyg profiles in H α line in two stars, which we classify as Luminous Blue Variable (LBV) star candidates. Overall, the galaxy IC 1613 may have a lower rate of WR star formation than previously suggested.

Characterization of starspots on a young M-dwarf K2-25: multiband observations of stellar photometric variability and planetary transits

ABSTRACT Detailed atmospheric characterization of exoplanets by transmission spectroscopy requires careful consideration of stellar surface inhomogeneities induced by star-spots. This effect is particularly problematic for planetary systems around M-dwarfs, and their spot properties are not fully understood. We investigated the stellar activity of the young M-dwarf K2-25 and its effect on transit observations of the sub-Neptune K2-25 b. From multiband monitoring observations of stellar brightness variability using ground-based telescopes and Transiting Exoplanets Survey Satellite, we found that the temperature difference between the spots and photosphere is <190 K and the spot covering fraction is <61 per cent (2σ). We also investigated the effect of starspot activity using multiepoch, multiband transit observations. We rule out cases with extremely low spot temperatures and large spot covering fractions. The results suggest that spots could distort the transmission spectrum of K2-25 b by as much as ∼100 ppm amplitude, corresponding to the precision of JWST/NIRSPEC of the target. Our study demonstrates that simultaneous multiband observations with current instruments can constrain the spot properties of M-dwarfs with good enough precision to support atmospheric studies of young M-dwarf planets via transmission spectroscopy.

Superflare rate variability on M dwarfs

ABSTRACT M dwarfs are often highly flare productive, and changes in the rate of flaring can potentially affect the radiation and energetic particles an exoplanet is exposed to. Rate variability has been found to be rare on G-type stars, and there has been limited study of the variability of flaring on M dwarfs. Using data from the TESS mission up to Observation Sector 66, we analyse 658 stars ranging from K7 to M5 to test for superflare rate variability by calculating an optimal piecewise constant-rate model for flare occurrence using a Bayesian algorithm and identify 66 stars with rate changes, a larger proportion than our previous study into G-type stars (7 out of 270 stars). We find that rate variability does not depend on the stellar parameters for our sample. We investigate how the flare-frequency distribution for these stars varies and whether this variation affects exoplanet habitability. No stars in our sample provide sufficient UV flux to support prebiotic chemistry. We investigate the phase distributions on the rate variable stars, finding 11 cases of potential phase dependence in flaring across seven stars. We also compare the Bayesian method to another measure of activity, the fraction of flux emitted through flares, and do not observe a consistent relationship between this flaring activity metric and the optimal Bayesian model. We discuss the possible reasons for the discrepancy and identify a problem with the flaring activity metric due to the power-law distribution of the flare events.

Machine Learning-based Classification of Variable Stars

The classification of variable stars, essential for revealing information on stellar properties and cosmic distances, traditionally relied on statistical methods and limited data. With the emergence of transformative machine learning methodologies and large stellar surveys, we are able to perform more efficient, accurate, and robust handling of expansive databases. We deploy two different machine learning models—random forest and XGBoost—that effectively classify variable stars identified in the most recent phase of the Optical Gravitational Lensing Experiment using four features: (1) time of minimum brightness, (2) I-band amplitude, (3) mean or maximum I-band magnitude, and (4) period. The two models achieve a cross-correlation score of 99.00%, indicating largely shared classifications. The results produced by the models uncover new insights into the precision of supervised learning models in predicting variable stars with the aid of the most up-to-date survey data.

Variability Census of Legacy Catalogs. II. 6600+ New δ Scuti and γ Doradus Stars* *Dedicated to my wife Jingyun Zhang.

From Phase II of a variability vetting census in BD, HD, SAO and PPM catalogs, I have identified a total of new variables of over 5000 δ Scuti, 3500 γ Doradus, 1200 Maia variables, 4 RR Lyrae stars, 420 eclipsing binaries, 5500 rotating variables (220+ ellipsoidal variable stars, 550+ ACV and several other subtypes including solar-like oscillators), and other types. Notably, more than 66 eclipsing binary systems have been identified with pulsating primary components of either DSCT or GDOR type, while 10 more binaries feature overlapping Maia-type pulsation. Moreover, over 960 of these variables exhibit hybrid δ Sct-γ Dor pulsations.

Asteroseismic modelling of the chemically peculiar B-type pulsator with an asymptotic period spacing – a Cen

ABSTRACT A Cen is recognized as a magnetic variable star with peculiar helium abundance. The presence of large surface spots induces flux modulation, allowing for the derivation of the surface rotational period (∼8.8 d). TESS photometry has unveiled additional signals that we interpreted as SPB-type pulsation. Furthermore, we managed to find a regular period spacing pattern and hence identified pulsational modes. We performed an asteroseismic analysis that resulted in constraints for internal structure of the star. Taking into account the surface rotation period derived from spots and the internal rotation obtained from asteroseismology, we concluded that the gradient of the rotational velocity in the radial direction is very small, indicating nearly solid body rotation. We also constrained overshooting from the convective core, as well as the mass and metallicity of the star.

SAGUARO: Time-domain Infrastructure for the Fourth Gravitational-wave Observing Run and Beyond

We present upgraded infrastructure for Searches After Gravitational waves Using ARizona Observatories (SAGUARO) during LIGO, Virgo, and KAGRA’s fourth gravitational-wave (GW) observing run (O4). These upgrades implement many of the lessons we learned after a comprehensive analysis of potential electromagnetic counterparts to the GWs discovered during the previous observing run. We have developed a new web-based target and observation manager (TOM) that allows us to coordinate sky surveys, vet potential counterparts, and trigger follow-up observations from one centralized portal. The TOM includes software that aggregates all publicly available information on the light curves and possible host galaxies of targets, allowing us to rule out potential contaminants like active galactic nuclei, variable stars, solar system objects, and preexisting supernovae, as well as to assess the viability of any plausible counterparts. We have also upgraded our image-subtraction pipeline by assembling deeper reference images and training a new neural-network-based real–bogus classifier. These infrastructure upgrades will aid coordination by enabling the prompt reporting of observations, discoveries, and analysis to the GW follow-up community, and put SAGUARO in an advantageous position to discover kilonovae in the remainder of O4 and beyond. Many elements of our open-source software stack have broad utility beyond multimessenger astronomy, and will be particularly relevant in the “big data” era of transient discoveries by the Vera C. Rubin Observatory.

Observational Properties of 155 β Cephei Pulsating Variable Stars

β Cephei pulsating variable (BCEP) stars are the most massive pulsating variable stars in the main sequence, exhibiting both p- and g-mode pulsations. In this study, we identified 155 BCEP stars or candidates using data from TESS and Gaia, of which 83 were first confirmed as BCEP stars. They have visual magnitudes ranging from 8 to 12 mag and effective temperatures between approximately 20,000 and 30,000 K, while the parallaxes of most targets are between 0.2 and 0.6 mas. The study indicates that these BCEP stars have pulsation periods ranging from 0.06 to 0.31 days, with amplitudes ranging from 0.1 to 55.8 mmag in the TESS band. Additionally, the number of BCEP stars increases as the pulsation amplitude decreases. These targets align with the distribution region of BCEP stars in the luminosity–period (L–P) and temperature–period diagrams. We have updated the L–P relation of BCEP stars. The Hertzsprung–Russell diagram indicates that these targets are in the main-sequence evolutionary phase, with masses ranging from 7 to 20 M ⊙ and luminosities between 2800 and 71,000 L ⊙. They are almost in the theoretical instability region of BCEP stars but as previously reported, this region at the low-mass end (red) is not filled. The distribution of the pulsation constant indicates that the dominant pulsation periods of BCEP stars consist mainly of low-order p-mode pulsations with a high proportion of radial fundamental modes. These BCEP stars are excellent objects for enhancing our understanding of the structure and evolution of massive stars through asteroseismology.

The nature of medium-period variables on the extreme horizontal branch

A fraction of the extreme horizontal branch stars of globular clusters exhibit a periodic light variability that has been attributed to rotational modulation caused by surface spots. These spots are believed to be connected to inhomogeneous surface distribution of elements. However, the presence of such spots has not been tested against spectroscopic data. We analyzed the phase-resolved ESO X-shooter spectroscopy of three extreme horizontal branch stars that are members of the globular cluster ω Cen and also display periodic light variations. The aim of our study is to understand the nature of the light variability of these stars and to test whether the spots can reproduce the observed variability. Our spectroscopic analysis of these stars did not detect any phase-locked abundance variations that are able to reproduce the light variability. Instead, we revealed the phase variability of effective temperature and surface gravity. In particular, the stars show the highest temperature around the light maximum. This points to pulsations as a possible cause of the observed spectroscopic and photometric variations. However, such an interpretation is in a strong conflict with Ritter’s law, which relates the pulsational period to the mean stellar density. The location of the ω Cen variable extreme horizontal branch stars in HR diagram corresponds to an extension of PG 1716 stars toward lower temperatures or blue, low-gravity, large-amplitude pulsators toward lower luminosities, albeit with much longer periods. Other models of light variability, namely, related to temperature spots, should also be tested further. The estimated masses of these stars in the range of 0.2–0.3 M⊙ are too low for helium-burning objects.