The Mission Accessible Near-Earth Objects Survey: Four years of photometry

Over 4.5 years, the Mission Accessible Near-Earth Object Survey (MANOS) assembled 228 Near-Earth Object (NEO) lightcurves. We report rotational lightcurves for 82 NEOs, constraints on amplitudes and periods for 21 NEOs, lightcurves with no detected variability within the image signal to noise and length of our observing block for 30 NEOs, and 10 tumblers. We uncovered 2 ultra-rapid rotators with periods below 20s; 2016MA with a potential rotational periodicity of 18.4s, and 2017QG$_{18}$ rotating in 11.9s, and estimate the fraction of fast/ultra-rapid rotators undetected in our project plus the percentage of NEOs with a moderate/long periodicity undetectable during our typical observing blocks. We summarize the findings of a simple model of synthetic NEOs to infer the object morphologies distribution using the measured distribution of lightcurve amplitudes. This model suggests a uniform distribution of axis ratio can reproduce the observed sample. This suggests that the quantity of spherical NEOs (e.g., Bennu) is almost equivalent to the quantity of highly elongated objects (e.g., Itokawa), a result that can be directly tested thanks to shape models from Doppler delay radar imaging analysis. Finally, we fully characterized 2 NEOs as appropriate targets for a potential robotic/human mission: 2013YS$_{2}$ and 2014FA$_{7}$ due to their moderate spin periods and low $\Delta v$.Comment: Accepted for Publication, The Astrophysical Journal Supplement Serie

Rapid variability in the synchrotron self Compton model for blazars

Blazars are characterized by large amplitude and fast variability, indicating that the electron distribution is rapidly changing, often on time scales shorter than the light crossing time. The emitting region is sufficiently compact to let radiative losses dominate the cooling of high energy electrons. We study the time dependent behaviour of the electron distribution after episodic electron injection phases, and calculate the observed synchrotron and self Compton radiation spectra. Since photons produced in different part of the source have different travel times, the observed spectrum is produced by the electron distribution at different stages of evolution. Even a homogeneous source then resembles an inhomogeneous one. Time delays between the light curves of fluxes at different frequencies are possible, as illustrated for the specific case of the BL Lac object Mkn 421.Comment: 11 pages, 11 figures, Submitted to MNRAS, revised version after referee's repor

The secular evolution of discrete quasi-Keplerian systems. I. Kinetic theory of stellar clusters near black holes

We derive the kinetic equation that describes the secular evolution of a large set of particles orbiting a dominant massive object, such as stars bound to a supermassive black hole or a proto-planetary debris disc encircling a star. Because the particles move in a quasi-Keplerian potential, their orbits can be approximated by ellipses whose orientations remain fixed over many dynamical times. The kinetic equation is obtained by simply averaging the BBGKY equations over the fast angle that describes motion along these ellipses. This so-called Balescu-Lenard equation describes self-consistently the long-term evolution of the distribution of quasi-Keplerian orbits around the central object: it models the diffusion and drift of their actions, induced through their mutual resonant interaction. Hence, it is the master equation that describes the secular effects of resonant relaxation. We show how it captures the phenonema of mass segregation and of the relativistic Schwarzschild barrier recently discovered in $N$-body simulations.Comment: 24 pages, 3 figure

Fast human detection for video event recognition

Human body detection, which has become a research hotspot during the last two years, can be used in many video content analysis applications. This paper investigates a fast human detection method for volume based video event detection. Compared with other object detection systems, human body detection brings more challenge due to threshold problems coming from a wide range of dynamic properties. Motivated by approaches successfully introduced in facial recognition applications, it adapts and adopts feature extraction and machine learning mechanism to classify certain areas from video frames. This method starts from the extraction of Haar-like features from large numbers of sample images for well-regulated feature distribution and is followed by AdaBoost learning and detection algorithm for pattern classification. Experiment on the classifier proves the Haar-like feature based machine learning mechanism can provide a fast and steady result for human body detection and can be further applied to reduce negative aspects in human modelling and analysis for volume based event detection