Stochastic Speckle Discrimination with Time-tagged Photon Lists: Digging below the Speckle Noise Floor

Abstract

We present an algorithm that uses the distribution of photon arrival times to distinguish speckles from incoherent sources, like planets and disks, in high-contrast images. Using simulated data, we show that our approach can overcome the noise limit from fluctuating speckle intensity. The algorithm is likely to be most advantageous when a coronagraph limits the coherent diffraction pattern in the image plane but the intensity is still strongly modulated by fast-timescale uncorrected stellar light, for example from atmospheric turbulence. These conditions are common at small inner working angles of highly corrected adaptive optics images and will allow probing of exoplanet populations at smaller angular separations. The technique requires a fast science camera that can temporally resolve the speckle fluctuations, and the detection of many photons per speckle decorrelation time. Because the algorithm directly extracts the incoherent light, standard differential imaging postprocessing techniques can be performed afterwards to further boost the signal.