# Stochastic modeling of the time variability of ALMA calibrators

## TL;DR

This paper models the flux variability of ALMA calibrator quasars using stochastic processes, enabling better flux calibration and uncertainty estimation for millimeter/sub-millimeter observations.

## Contribution

It introduces a stochastic modeling approach with Ornstein-Uhlenbeck processes to characterize calibrator variability across multiple frequencies.

## Key findings

- Simple mixtures of Ornstein-Uhlenbeck processes effectively model flux variability.
- Calibrators exhibit negative spectral indices between -0.35 and -0.80.
- The model enables flux forecasts, interpolations, and uncertainty estimations.

## Abstract

Characterizing the variability of the extragalactic sources used for calibration in the Atacama Large Millimeter/Sub-millimeter Array (ALMA) is key to assess the flux scale uncertainty of science observations. To this end, we model the variability of 39 quasars which have been used by ALMA as secondary flux calibrators using continuous time stochastic processes. This formalism is specially adapted to the multi-frequency, quasi-periodic sampling which characterizes the calibration monitoring of ALMA. We find that simple mixtures of Ornstein-Uhlenbeck processes can describe well the flux and spectral index variability of these sources for Bands 3 and 7 (91.5 and 103.5, and 343.5 GHz, respectively). The spectral shape of the calibrators are characterized by negative spectral indices, mostly between $-0.35$ and $-0.80$, and with additional concavity. The model provides forecasts, interpolations, and uncertainty estimations for the observed fluxes that depend on the intrinsic variability of the source. These can be of practical use for the ALMA data calibrator survey and data quality assurance.