DETECT: Real-Time Identification of Transients with DESI Spectroscopic Redshift
Abstract
Wide-field surveys now report thousands of transients per month, while spectra are obtained for only a few per cent of them. We present DETECT (DESI--Transient Event Cross-matching Tool), a pipeline that turns each Transient Name Server (TNS) alert into a distance-informed candidate within an hour by placing it in the context of the Dark Energy Spectroscopic Instrument (DESI) archive. DETECT cross-matches every new report against the 22 million spectra of DESI EDR and DR1 through a HEALPix index, associates the transient with a host galaxy by a directional-light-radius rule whose morphology-dependent thresholds are calibrated on 4,474 supernovae with known redshifts (92.5% completeness, 0.4% wrong hosts), and passes ambiguous cases to a reviewer through a web interface. With a validated host redshift it derives the peak absolute magnitude, the projected offset and basic host properties of each event, and ranks it for spectroscopic follow-up. Applied retrospectively to ~1.2x10^5 TNS reports from 2020--2024, DETECT recovers a spectroscopic host for 15% of them, from these we build a Gold Sample of ~5,400 well-sampled light curves whose luminosity distributions by class reproduce those of untargeted surveys. Because the absolute magnitude is known at discovery, intrinsically overluminous events stand out immediately: in the prospective 2025 run this is how the lensed superluminous supernova SN~2025wny was flagged within hours of its report, and how faint, fast-declining kilonova candidates were screened against model grids and archival photometry. DETECT shows how an archival spectroscopic survey can make host redshifts a routine part of transient triage ahead of the Rubin Observatory's LSST.
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BibTeX
@misc{lee2026detect,
title = {{DETECT: Real-Time Identification of Transients with DESI Spectroscopic Redshift}},
author = {Yu-Hsing Lee and Ting-Wan Chen and Ze-Ning Wang and Sheng Yang and Limeng Deng and Chuan-Jui Li and K. C. Chambers and Thomas de Boer and Chien-Cheng Lin and Thomas B. Lowe and Paloma Mínguez and Gregory S. H. Paek and Richard Wainscoat},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.28951},
eprint = {2609.28951},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.28951},
}
RIS
TY - UNPB
TI - DETECT: Real-Time Identification of Transients with DESI Spectroscopic Redshift
AU - Yu-Hsing Lee
AU - Ting-Wan Chen
AU - Ze-Ning Wang
AU - Sheng Yang
AU - Limeng Deng
AU - Chuan-Jui Li
AU - K. C. Chambers
AU - Thomas de Boer
AU - Chien-Cheng Lin
AU - Thomas B. Lowe
AU - Paloma Mínguez
AU - Gregory S. H. Paek
AU - Richard Wainscoat
PY - 2026
DA - 2026/09/24
PB - arXiv
DO - 10.48550/arxiv.2609.28951
UR - https://arxiv.org/abs/2609.28951
AB - Wide-field surveys now report thousands of transients per month, while spectra are obtained for only a few per cent of them. We present DETECT (DESI--Transient Event Cross-matching Tool), a pipeline that turns each Transient Name Server (TNS) alert into a distance-informed candidate within an hour by placing it in the context of the Dark Energy Spectroscopic Instrument (DESI) archive. DETECT cross-matches every new report against the 22 million spectra of DESI EDR and DR1 through a HEALPix index, associates the transient with a host galaxy by a directional-light-radius rule whose morphology-dependent thresholds are calibrated on 4,474 supernovae with known redshifts (92.5% completeness, 0.4% wrong hosts), and passes ambiguous cases to a reviewer through a web interface. With a validated host redshift it derives the peak absolute magnitude, the projected offset and basic host properties of each event, and ranks it for spectroscopic follow-up. Applied retrospectively to ~1.2x10^5 TNS reports from 2020--2024, DETECT recovers a spectroscopic host for 15% of them, from these we build a Gold Sample of ~5,400 well-sampled light curves whose luminosity distributions by class reproduce those of untargeted surveys. Because the absolute magnitude is known at discovery, intrinsically overluminous events stand out immediately: in the prospective 2025 run this is how the lensed superluminous supernova SN~2025wny was flagged within hours of its report, and how faint, fast-declining kilonova candidates were screened against model grids and archival photometry. DETECT shows how an archival spectroscopic survey can make host redshifts a routine part of transient triage ahead of the Rubin Observatory's LSST.
ER -