Smart Kanata: A Framework for Autonomous Decision Making in Rapid Follow-up Observations of Cataclysmic Variables

TL;DR

Smart Kanata is an autonomous framework that improves rapid follow-up observations of cataclysmic variables by estimating their types and selecting optimal observation modes, demonstrated through successful operation over 300 days.

Contribution

The paper introduces Smart Kanata, a novel autonomous decision-making system for prompt follow-up of CVs, integrating probabilistic classification and information-based mode selection.

Findings

Successfully operated for ~300 days with 21 samples

Automated observations of a nova and a microlensing event achieved

Detected rapid spectral changes in nova V4370 Oph

Abstract

Studying the early stages of transient events provides crucial information about the fundamental physical processes in cataclysmic variables (CVs). However, determining an appropriate observation mode immediately after the discovery of a new transient presents challenges due to significant uncertainties regarding its nature. We developed a framework designed for autonomous decision making in prompt follow-up observations of CVs using the Kanata 1.5-m telescope. The system, named Smart Kanata, first estimates the class probabilities of variable star types using a generative model. It then selects the optimal observation mode from three possible options based on the mutual information calculated from the class probabilities. We have operated the system for ~300 days and obtained 21 samples, among which automated observations were successfully performed for a nova and a microlensing event. In the time-series spectra of the nova V4370 Oph, we detected a rapid deepening of the absorption component of the H_alpha line. These initial results demonstrate the capability of Smart Kanata in facilitating rapid observations and improving our understanding of outbursts and eruptions of CVs and other galactic transients.