Ron Arad | Searcharxiv

arXiv2025

A search for minute-time-scale flares from the transient AT\,2024wpp

The AT 2018cow-like fast blue optical transient AT2022tsd showed a large number of few-minute-duration, high-luminosity (~10^43 erg/s) flares. We present an intensive search for such flares from another 18cow-like event, AT2024wpp. We have used the Large Array Survey Telescope (LAST) to observe this transient between 28 and 74 days after the approximate time of zero flux. The target was observed for about 23 hours to a sensitivity that allows one to detect 3x10^42 erg/s flares at S/N>5. No optical flares have been found, suggesting a one-sided 2-sigma confidence upper limit of <0.02 on the flare's duty cycle, and flare rate lower than about 0.11/hr. These limits suggest that not all 18cow-like objects display a high rate of minute-timescale luminous flares. This can be explained either by diversity in the 18cow-like population or by viewing angle effects (e.g., beaming), or rather that the optical depth towards the central emitting region did not fall below unity during the particular search window.

astro-ph.HE↗

arXiv2022

Probabilistic Approach for Detection of High-Frequency Periodic Signals using an Event Camera

Being inspired by the biological eye, event camera is a novel asynchronous technology that pose a paradigm shift in acquisition of visual information. This paradigm enables event cameras to capture pixel-size fast motions much more naturally compared to classical cameras. In this paper we present a new asynchronous event-driven algorithm for detection of high-frequency pixel-size periodic signals using an event camera. Development of such new algorithms, to efficiently process the asynchronous information of event cameras, is essential and being a main challenge in the research community, in order to utilize its special properties and potential. It turns out that this algorithm, that was developed in order to satisfy the new paradigm, is related to an untreated theoretical problem in probability: let $0\leq\tau_{1}\leq\tau_{2}\leq\cdots\leq\tau_{m}\leq1$, originated from an unknown distribution. Let also $\epsilon,\delta\in\mathbb{R}$, and $d\in\mathbb{N}$. What can be said about the probability $\Phi(m,d)$ of having more than $d$ adjacent $\tau_{i}$-s pairs that the distance between them is $\delta$, up to an error $\epsilon$ ? This problem, that reminds the area of order statistic, shows how the new visualization paradigm is also an opportunity to develop new areas and problems in mathematics.

cs.CV↗