KMOS Data Flow: Reconstructing Data Cubes in One Step

TL;DR

The paper introduces a novel, modular data reduction pipeline for KMOS that reconstructs data cubes in a single step, improving efficiency and flexibility in processing complex near-infrared spectroscopic data.

Contribution

It presents a new one-step data cube reconstruction method within a modular pipeline architecture for KMOS, accommodating spectral/spatial flexure and background variations.

Findings

Single-step data cube reconstruction improves processing efficiency.

Modular pipeline allows flexible adaptation to various calibration needs.

Enhanced visualization with QFitsView supports data analysis.

Abstract

KMOS is a multi-object near-infrared integral field spectrometer with 24 deployable pick-off arms. Data processing is inevitably complex. We discuss specific issues and requirements that must be addressed in the data reduction pipeline, the calibration, the raw and processed data formats, and the simulated data. We discuss the pipeline architecture. We focus on its modular style and show how these modules can be used to build a classical pipeline, as well as a more advanced pipeline that can account for both spectral and spatial flexure as well as variations in the OH background. A novel aspect of the pipeline is that the raw data can be reconstructed into a cube in a single step. We discuss the advantages of this and outline the way in which we have implemented it. We finish by describing how the QFitsView tool can now be used to visualise KMOS data.