Detection of binary asteroids from sparse photometry Josef Durechˇ 1 Petr Scheirich Mikko Kaasalainen Tommy Grav Robert Jedicke Larry Denneau 1Astronomical Institute, Charles University in Prague Paris binary workshop, May 2008 Outline 1 Sparse photometry 2 Combined sparse + dense photometry 3 Asynchronous binaries 4 Fully synchronous binaries 5 Conclusions Sparse photometry contrary to standard dense lightcurves, sparse data consist of individual calibrated points – one or a few points per night tens to hundreds points from more apparitions all-sky surveys like Pan-STARRS, Gaia, LSST 100 points with < 5% error covering ∼ 5 years is sufficient for deriving a unique model sparse data from astrometry – noisy but sometimes useful Simulations So far, our results are based mainly on simulated data: Pan-STARRS cadences + artificial shapes + noise → inversion shape reconstruction based on a simulated Pan-STARRS cadence 10 years of observation, 3% noise Real data – combined datasets sparse photometry accurate (< 5%) sparse data are not yet available photometry obtained during astrometric observations is usually very noisy and spoiled by systematic errors US Naval Observatory, Flagstaff – data for ∼ 2000 asteroids, estimated accuracy 0.08–0.1 mag, typically 50–200 points from five years. standard lightcurves Uppsala Asteroid Photometric Catalogue archives of individual observers Combined datasets – (130) Elektra USNO sparse photometry of (130) Elektra 1994/2/15.7 2 1.2 1.5 1.1 1 1 0.9 0.5 0.8 Relative intensity 0.7 Reduced relative intensity 0 0.6 1996 1998 2000 2002 2004 2006 0 0.2 0.4 0.6 0.8 1 Epoch Phase of rotation ← full model based on 49 standard lightcurves from 9 apparitions periods are the same pole difference ∼ 7◦ of arc ← model based on 1 lightcurve and sparse data (113 points) Phase angle dependence – (130) Elektra observed versus modelled brightness phase angle dependence without shape effects 2 2 observation model 1.5 1.5 1 1 relative brightness relative brightness 0.5 0.5 0 5 10 15 20 25 0 5 10 15 20 25 phase angle [deg] phase angle [deg] rms = 0.08 mag Asynchronous binaries (NEAs) There are two periods in the data – rotation of the primary and orbital period of the secondary. Any single-body model cannot fit the data well – high O-C residuals. Can we somehow recognise it is a binary asteroid? If the secondary/primary size ratio is large enough and the geometry is suitable, mutual events are visible in the phase angle plot as decrease of brightness. Asynchronous binary NEAs – simulation simulated Pan-STARRS observations of binary NEAs 10 years, noise 3% 1991VH 1996FG3 1 1 0.5 0.5 intensity intensity 0 0 0 20 40 0 20 40 phase angle [deg] phase angle [deg] d1/d2 = 0.38 d1/d2 = 0.31 Our results are based on synthetic data, everything will depend on real errors, outliers, etc. Fully synchronous NEAs at high phase angles Synchronous binaries are detectable by high amplitudes at high phase angles. No modelling, just ’looking’ at data, then follow-up observations. Amplitude-phase relationship: amplitudes increase for higher phase angles. Also the probability of measuring large amplitudes from sparse sampling increases with phase angle. Lacerda (2008), ApJ 672,L57 Convex models of synchronous binaries From a lightcurve-inversion point of view, a fully synchronous binary behaves ¨H ¨¨ HH ¨¨ HH ¨ Hj like a single (nonconvex) convex model nonconvex model body – its lightcurves can be fitted by a convex model. The only indication that the original object is binary is the strange rectangular shape or α = 30 deg α = 60 deg pole-on silhouette of the −0.4 −0.4 −0.2 −0.2 model. 0 0 0.2 0.2 0.4 0.4 Relative brightness [mag] 0.6 Relative brightness [mag] 0.6 0 0.5 1 0 0.5 1 Rotational phase Rotational phase Synchronous binaries – synthetic Pan-STARRS sparse data original noise 3%, two solutions with λ ± 180◦ (1089) Tama – real data Behrend et al. (2006) USNO sparse photometry of (1089) Tama −1 −0.5 0 0.5 1 1.5 Reduced relative magnitude 2 1998 2000 2002 2004 2006 Epoch USNO sparse photometry of (1089) Tama Dense lightcurve of (1089) Tama −1 −0.03 −0.5 −0.02 0 −0.01 0.5 0 1 0.01 1.5 Relative magnitude 0.02 Reduced relative magnitude 2 0 10 20 30 40 0.03 Phase angle [deg] 0 0.2 0.4 0.6 0.8 1 Rotational phase (1089) Tama – shape model one of possible convex shape models period P and pole ecliptic latitude β are well determined, pole longitude λ is not well constrained (1313) Berna – real data Behrend et al. (2006) USNO sparse photometry of (1313) Berna −1 −0.5 0 0.5 1 Reduced relative magnitude 1.5 0 10 20 30 Phase angle [deg] (1313) Berna − O−C residuals USNO sparse photometry of (1313) Berna −1 −1 −0.5 −0.5 0 0 0.5 0.5 1 1 Reduced relative magnitude 1.5 Reduced relative magnitude 0 10 20 30 1.5 Phase angle [deg] 1998 2000 2002 2004 2006 Epoch (1313) Berna – shape model convex shape model Summary Asynchronous Data cannot be fitted with a single-body model. Mutual events might be visible in brightness vs. phase angle plot – only if the geometry is suitable and photometric errors are small Fully synchronous A convex model that fits the data well can be derived. Rectangular pole-on silhouette is strong indication that the object is binary (or bifurcated). Follow-up observations are necessary!.