Solar flare prediction using advanced feature extraction, machine learning and feature selection

YesNovel machine-learning and feature-selection algorithms have been developed to study: (i) the flare prediction capability of magnetic feature (MF) properties generated by the recently developed Solar Monitor Active Region Tracker (SMART); (ii) SMART's MF properties that are most significantly related to flare occurrence. Spatio-temporal association algorithms are developed to associate MFs with flares from April 1996 to December 2010 in order to differentiate flaring and non-flaring MFs and enable the application of machine learning and feature selection algorithms. A machine-learning algorithm is applied to the associated datasets to determine the flare prediction capability of all 21 SMART MF properties. The prediction performance is assessed using standard forecast verification measures and compared with the prediction measures of one of the industry's standard technologies for flare prediction that is also based on machine learning - Automated Solar Activity Prediction (ASAP). The comparison shows that the combination of SMART MFs with machine learning has the potential to achieve more accurate flare prediction than ASAP. Feature selection algorithms are then applied to determine the MF properties that are most related to flare occurrence. It is found that a reduced set of 6 MF properties can achieve a similar degree of prediction accuracy as the full set of 21 SMART MF properties

The White Dwarf Binary Pathways Survey. V. The Gaia White Dwarf Plus AFGK binary sample and the identification of 23 close binaries

Close white dwarf binaries consisting of a white dwarf and an A-, F-, G-, or K-type main-sequence star, henceforth close WD+AFGK binaries, are ideal systems to understand the nature of type Ia supernovae progenitors and to test binary evolution models. In this work we identify 775 WD+AFGK candidates from TGAS (The Tycho-Gaia Astrometric Solution) and Gaia Data Release 2 (DR2), a well-defined sample of stars with available parallaxes, and we measure radial velocities (RVs) for 275 of them with the aim of identifying close binaries. The RVs have been measured from high-resolution spectra obtained at the Xinglong 2.16 m Telescope and the San Pedro Mártir 2.12 m Telescope and/or from available LAMOST DR6 (low-resolution) and RAVE DR5 (medium-resolution) spectra. We identify 23 WD+AFGK systems displaying more than 3σ RV variation among 151 systems for which the measured values are obtained from different nights. Our WD+AFGK binary sample contains both AFGK dwarfs and giants, with a giant fraction ~43%. The close binary fractions we determine for the WD+AFGK dwarf and giant samples are sime24% and sime15%, respectively. We also determine the stellar parameters (i.e., effective temperature, surface gravity, metallicity, mass, and radius) of the AFGK companions with available high-resolution spectra. The stellar parameter distributions of the AFGK companions that are members of close and wide binary candidates do not show statistically significant differences

The polarized image of a synchrotron-emitting ring of gas orbiting a black hole

High Energy Astrophysic

Constraints on black-hole charges with the 2017 EHT observations of M87*

InstrumentationHigh Energy Astrophysic

The variability of the black hole image in M87 at the dynamical timescale

The black hole images obtained with the Event Horizon Telescope (EHT) are expected to be variable at the dynamical timescale near their horizons. For the black hole at the center of the M87 galaxy, this timescale (5–61 days) is comparable to the 6 day extent of the 2017 EHT observations. Closure phases along baseline triangles are robust interferometric observables that are sensitive to the expected structural changes of the images but are free of station-based atmospheric and instrumental errors. We explored the day-to-day variability in closure-phase measurements on all six linearly independent nontrivial baseline triangles that can be formed from the 2017 observations. We showed that three triangles exhibit very low day-to-day variability, with a dispersion of ∼3°–5°. The only triangles that exhibit substantially higher variability (∼90°–180°) are the ones with baselines that cross the visibility amplitude minima on the u–v plane, as expected from theoretical modeling. We used two sets of general relativistic magnetohydrodynamic simulations to explore the dependence of the predicted variability on various black hole and accretion-flow parameters. We found that changing the magnetic field configuration, electron temperature model, or black hole spin has a marginal effect on the model consistency with the observed level of variability. On the other hand, the most discriminating image characteristic of models is the fractional width of the bright ring of emission. Models that best reproduce the observed small level of variability are characterized by thin ring-like images with structures dominated by gravitational lensing effects and thus least affected by turbulence in the accreting plasmas.https://iopscience.iop.org/article/10.3847/1538-4357/ac332e/pdfPublished versio

Event Horizon Telescope observations of the jet launching and collimation in Centaurus A

InstrumentationLarge scale structure and cosmolog

First sagittarius A* Event Horizon Telescope results. VI. Testing the black hole metric

Galaxie

Resolving the inner parsec of the blazar J1924-2914 with the event horizon telescope

Galaxie

A universal power-law prescription for variability from synthetic images of black hole accretion flows

Instrumentatio

First sagittarius A* Event Horizon Telescope results. IV. Variability, morphology, and black hole mass

Galaxie