Let the Great World Spin: Revealing the Stormy, Turbulent Nature of Young Giant Exoplanet Analogs with the Spitzer Space Telescope

We present a survey for photometric variability in young, low-mass brown dwarfs with the Spitzer Space Telescope. The 23 objects in our sample show robust signatures of youth and share properties with directly imaged exoplanets. We present three new young objects: 2MASS J03492367+0635078, 2MASS J09512690−8023553, and 2MASS J07180871−6415310. We detect variability in 13 young objects, and find that young brown dwarfs are highly likely to display variability across the L2–T4 spectral type range. In contrast, the field dwarf variability occurrence rate drops for spectral types >L9. We examine the variability amplitudes of young objects and find an enhancement in maximum amplitudes compared to field dwarfs. We speculate that the observed range of amplitudes within a spectral type may be influenced by secondary effects such as viewing inclination and/or rotation period. We combine our new rotation periods with the literature to investigate the effects of mass on angular momentum evolution. While high-mass brown dwarfs (>30M Jup) spin up over time, the same trend is not apparent for lower-mass objects (<30M Jup), likely due to the small number of measured periods for old, low-mass objects. The rotation periods of companion brown dwarfs and planetary-mass objects are consistent with those of isolated objects with similar ages and masses, suggesting similar angular momentum histories. Within the AB Doradus group, we find a high-variability occurrence rate and evidence for common angular momentum evolution. The results are encouraging for future variability searches in directly imaged exoplanets with facilities such as the James Webb Space Telescope and 30 m telescopes.

A New Method for Estimating Starspot Lifetimes Based on Autocorrelation Functions

We present a method that utilizes autocorrelation functions from long-term precision broadband differential light curves to estimate the average lifetimes of starspot groups for two large samples of Kepler stars: stars with and without previously known rotation periods. Our method is calibrated by comparing the strengths of the first few normalized autocorrelation peaks using ensembles of models that have various starspot lifetimes. We find that we must mix models of short and long lifetimes together (in heuristically determined ratios) to align the models with the Kepler data. Our fundamental result is that short starspot-group lifetimes (one to four rotations) are implied when the first normalized peak is weaker than about 0.4, long lifetimes (15 or greater) are implied when it is greater than about 0.7, and in between are the intermediate cases. Rotational lifetimes can be converted to physical lifetimes if the rotation period is known. Stars with shorter rotation periods tend to have longer rotational (but not physical) spot lifetimes, and cooler stars tend to have longer physical spot lifetimes than warmer stars with the same rotation period. The distributions of the physical lifetimes are log-normal for both samples and generally longer in the first sample. The shorter lifetimes in the stars without known periods probably explain why their periods are difficult to measure. Some stars exhibit longer than average physical starspot lifetimes; their percentage drops with increasing temperature from nearly half at 3000 K to nearly zero for hotter than 6000 K.

Superflares and Starspots: when size does not matter

Within the last decade, space missions have provided a wealth of information about stellar flares. Nevertheless, what triggers these superflares, and whether they are similar to the solar counterparts, remains a great mystery. How are flares connected to active regions and what are the main causes of their occurrence? Here we investigate the activity of two K-type stars, similar in every way from mass to rotation periods and planetary systems. Even if both stars exhibited hundreds of spots, Kepler-411 produced 65 superflares, while Kepler-210 presented none. The spots of both stars were characterised using the planetary transit mapping technique which yields the intensity, temperature, and radius of starspots. The only discrepant parameter was the size of the spots. While the average radius of spots on Kepler-411 was (17 ± 7) × 103 km, for Kepler-210 the mean radius was (39 ± 18) × 103 km. That is, the star with no superflare exhibited spots twice as large as the one with 65 superflares. Thus starspot area appears not to be the main culprit of superflare triggering, but rather the magnetic complexity seems more important, as in the case of the Sun. These are important clues to the magnetic dynamo acting on these solar-type stars.

Characterizing Sparse Asteroid Light Curves with Gaussian Processes

In the era of wide-field surveys like the Zwicky Transient Facility and the Rubin Observatory’s Legacy Survey of Space and Time, sparse photometric measurements constitute an increasing percentage of asteroid observations, particularly for asteroids newly discovered in these large surveys. Follow-up observations to supplement these sparse data may be prohibitively expensive in many cases, so to overcome these sampling limitations, we introduce a flexible model based on Gaussian processes to enable Bayesian parameter inference of asteroid time-series data. This model is designed to be flexible and extensible, and can model multiple asteroid properties such as the rotation period, light-curve amplitude, changing pulse profile, and magnitude changes due to the phase-angle evolution at the same time. Here, we focus on the inference of rotation periods. Based on both simulated light curves and real observations from the Zwicky Transient Facility, we show that the new model reliably infers rotational periods from sparsely sampled light curves and generally provides well-constrained posterior probability densities for the model parameters. We propose this framework as an intermediate method between fast but very limited-period detection algorithms and much more comprehensive but computationally expensive shape-modeling based on ray-tracing codes.

Rotation Period Detection for Earth-like Exoplanets

A terrestrial planet’s rotation period is one of the key parameters that determines its climate and habitability. Current methods for detecting the rotation period of exoplanets are not suitable for terrestrial exoplanets. Here we demonstrate that, under certain conditions, the rotation period of an Earth-like exoplanet will be detectable using direct-imaging techniques. We use a global climate model that includes clouds to simulate reflected starlight from an Earth-like exoplanet and explore how different parameters (e.g., orbital geometry, wavelength, time resolution) influence the detectability of the planet’s rotation period. We show that the rotation period of an Earth-like exoplanet is detectable using visible-wavelength channels with time-series monitoring at a signal-to-noise ratio (S/N) >20 with ∼5–15 rotation periods of data, while the rotation period of a planet with full ocean coverage is unlikely to be detectable. To better detect the rotation period, one needs to plan the observation so that each individual integration would yield a S/N >10, while keeping the integration time shorter than 1/6 to 1/4 of the rotation period of the planet. Our results provide important guidance for rotation period detection of Earth-like exoplanets in reflected light using future space telescopes.

General Circulation Model Errors Are Variable across Exoclimate Parameter Spaces

General circulation models (GCMs) are often used to explore exoclimate parameter spaces and classify atmospheric circulation regimes. Models are tuned to give reasonable climate states for standard test cases, such as the Held–Suarez test, and then used to simulate diverse exoclimates by varying input parameters such as rotation rates, instellation, atmospheric optical properties, frictional timescales, and so on. In such studies, there is an implicit assumption that the model works reasonably well for the standard test case will be credible at all points in an arbitrarily wide parameter space. Here, we test this assumption using the open-source GCM THOR to simulate atmospheric circulation on tidally locked Earth-like planets with rotation periods of 0.1–100 days. We find that the model error, as quantified by the ratio between physical and spurious numerical contributions to the angular momentum balance, is extremely variable across this range of rotation periods with some cases where numerical errors are the dominant component. Increasing model grid resolution does improve errors, but using a higher-order numerical diffusion scheme can sometimes magnify errors for finite-volume dynamical solvers. We further show that to minimize error and make the angular momentum balance more physical within our model, the surface friction timescale must be smaller than the rotational timescale.

Stellar Rotation in the Gaia Era: Revised Open Clusters’ Sequences

The period versus mass diagrams (i.e., rotational sequences) of open clusters provide crucial constraints for angular momentum evolution studies. However, their memberships are often heavily contaminated by field stars, which could potentially bias the interpretations. In this paper, we use data from Gaia DR2 to reassess the memberships of seven open clusters with ground- and space-based rotational data, and present an updated view of stellar rotation as a function of mass and age. We use the Gaia astrometry to identify the cluster members in phase space, and the photometry to derive revised ages and place the stars on a consistent mass scale. Applying our membership analysis to the rotational sequences reveals that: (1) the contamination in clusters observed from the ground can reach up to ∼35%; (2) the overall fraction of rotational outliers decreases substantially when the field contaminants are removed, but some outliers persist; (3) there is a sharp upper edge in the rotation periods at young ages; (4) at young ages, stars in the 1.0–0.6M ⊙ range inhabit a global maximum of rotation periods, potentially providing an optimal window for habitable planets. Additionally, we see clear evidence for a strongly mass-dependent spin-down process. In the regime where rapid rotators are leaving the saturated domain, the rotational distributions broaden (in contradiction with popular models), which we interpret as evidence that the torque must be lower for rapid rotators than for intermediate ones. The cleaned rotational sequences from ground-based observations can be as constraining as those obtained from space.

Studies of Magnetic Chemically Peculiar Stars Using the 6-m Telescope at SAO RAS

We present a survey of the most important results obtained in observations with the 6-m telescope in the studies of magnetic fields of chemically peculiar stars. It is shown that we have found more than 200 new magnetic chemically peculiar stars, which is more than 30% of their total known number. Observations of ultra-slow rotators (stars with rotation periods of years and decades) have shown that there are objects with strong fields among them, several kG in magnitude. In the association of young stars in Orion, it has been found that the occurrence and strength of magnetic fields of chemically peculiar stars decrease sharply with age in the interval from 2 to 10 Myr. These data indicate the fossil nature of magnetic fields of chemically peculiar stars. About 10 magnetic stars were found based on ultra-accurate photometry data obtained from the Kepler and TESS satellites. A new effective method of searching for magnetic stars was developed. In addition, the exact rotation periods make it possible to build reliable curves of the longitudinal field component variability with the phase of the star’s rotation period, and hence to create its magnetic model. The survey is dedicated to the memory of Prof. Yuri Nikolaevich Gnedin.

Three K2 Campaigns Yield Rotation Periods for 1013 Stars in Praesepe

We use three campaigns of K2 observations to complete the census of rotation in low-mass members of the benchmark, ≈670 Myr old open cluster Praesepe. We measure new rotation periods (P rot) for 220 ≲1.3 M ⊙ Praesepe members and recovery periods for 97% (793/812) of the stars with a P rot in the literature. Of the 19 stars for which we do not recover a P rot, 17 were not observed by K2. As K2’s three Praesepe campaigns took place over the course of 3 yr, we test the stability of our measured P rot for stars observed in more than one campaign. We measure P rot consistent to within 10% for >95% of the 331 likely single stars with ≥2 high-quality observations; the median difference in P rot is 0.3%, with a standard deviation of 2%. Nearly all of the exceptions are stars with discrepant P rot measurements in Campaign 18, K2’s last, which was significantly shorter than the earlier two (≈50 days rather than ≈75 days). This suggests that, despite the evident morphological evolution we observe in the light curves of 38% of the stars, P rot measurements for low-mass stars in Praesepe are stable on timescales of several years. A P rot can therefore be taken to be representative even if measured only once.

Estimating Gross Primary Productivity (GPP) over Rice–Wheat-Rotation Croplands by Using the Random Forest Model and Eddy Covariance Measurements: Upscaling and Comparison with the MODIS Product

Despite advances in remote sensing–based gross primary productivity (GPP) modeling, the calibration of the Moderate Resolution Imaging Spectroradiometer (MODIS) GPP product (GPPMOD) is less well understood over rice–wheat-rotation cropland. To improve the performance of GPPMOD, a random forest (RF) machine learning model was constructed and employed over the rice–wheat double-cropping fields of eastern China. The RF-derived GPP (GPPRF) agreed well with the eddy covariance (EC)-derived GPP (GPPEC), with a coefficient of determination of 0.99 and a root-mean-square error of 0.42 g C m−2 d−1. Therefore, it was deemed reliable to upscale GPPEC to regional scales through the RF model. The upscaled cumulative seasonal GPPRF was higher for rice (924 g C m−2) than that for wheat (532 g C m−2). By comparing GPPMOD and GPPEC, we found that GPPMOD performed well during the crop rotation periods but underestimated GPP during the rice/wheat active growth seasons. Furthermore, GPPMOD was calibrated by GPPRF, and the error range of GPP MOD (GPPRF minus GPPMOD) was found to be 2.5–3.25 g C m−2 d−1 for rice and 0.75–1.25 g C m−2 d−1 for wheat. Our findings suggest that RF-based GPP products have the potential to be applied in accurately evaluating MODIS-based agroecosystem carbon cycles at regional or even global scales.