RVSNUpy: A Python Package for Spectroscopic Redshift Measurement Based on Cross-Correlation

TL;DR

RVSNUpy is a Python package that accurately measures spectroscopic redshifts using cross-correlation with calibrated templates, demonstrating consistent results across different spectrographs in large surveys.

Contribution

The paper introduces RVSNUpy, a novel Python tool utilizing inverse-variance weighted cross-correlation with a universal set of calibrated templates for reliable redshift measurement.

Findings

RVSNUpy achieves homogeneous redshift results across different spectrographs.

Calibration of template spectra reduces systematic offsets.

The package is suitable for large-scale spectroscopic surveys.

Abstract

We introduce RVSNUpy, a new Python package designed to measure spectroscopic redshifts. Based on inverse-variance weighted cross-correlation, RVSNUpy determines the redshifts by comparing observed spectra with various rest-frame template spectra. We test the performance of RVSNUpy based on ~ 6000 objects in the HectoMAP redshift survey observed with both SDSS and MMT/Hectospec. We demonstrate that a slight redshift offset (~ 40 km/s) between SDSS and MMT/Hectospec measurements reported from previous studies results from the small offsets in the redshift template spectra used for SDSS and Hectospec reductions. We construct the universal set of template spectra, including empirical SDSS template spectra, carefully calibrated to the rest frame. Our test for the HectoMAP objects with duplicated observations shows that RVSNUpy with the universal template spectra yields the homogeneous redshift from the spectra obtained with different spectrographs. We highlight that RVSNUpy is a powerful redshift measurement tool for current and future large-scale spectroscopy surveys, including A-SPEC, DESI, 4MOST, and Subaru/PFS.