MAS-CCD: New technique for measuring low-level charge content based on the multiple amplifier architecture

TL;DR

This paper introduces a novel covariance-based technique for accurately and efficiently measuring spurious charge in MAS-CCD sensors, enhancing characterization of low-noise astronomical detectors.

Contribution

The work develops and validates a new method for estimating spurious charge using covariance analysis, improving measurement speed and precision over traditional approaches.

Findings

The method enables fast, precise spurious charge measurements under operational conditions.

Simulations confirm the theoretical model's validity and potential for large-scale sensor characterization.

The technique offers a practical alternative to empirical procedures for sensor optimization.

Abstract

Low-noise detectors are a key technology for the next generation of astronomical instruments aimed at spectroscopy of faint objects and the search for exoplanets. In this context, the multiple-amplifier sensing charge-coupled device (MAS-CCD) emerges as a promising technology for future scientific instruments. A critical parameter affecting the performance of these devices is spurious charge, produced by the clocking of the gates. Its measurement is typically challenging with existing methods. In practice, the optimization of this parameter often relies on empirical procedures that require significant time and careful consideration of the trade-off with full-well capacity. In this work, we present a new technique to estimate spurious charge based on covariance analysis of the output amplifiers of the MAS-CCD, which measures the same charge packet in different amplifiers at different times. The method enables fast and precise measurements of spurious charge under operating conditions where conventional approaches are difficult to apply. We develop the theoretical framework of the method and validate the model through simulations. The results demonstrate the feasibility of this approach and suggest that it could serve as a basis for reliable large-scale characterization of sensor performance.