[论文解读] Euclid Quick Data Release (Q1). The Strong Lensing Discovery Engine D -- Double-source-plane lens candidates

Euclid Collaboration, T. Li+336 more|ArXiv.org|Mar 19, 2025

Astronomy and Astrophysical Research被引用 3

一句话总结

该论文提出 Strong Lensing Discovery Engine D，用于在 Euclid Quick Data Release (Q1) 中识别双源平面透镜候选者。

ABSTRACT

Strong gravitational lensing systems with multiple source planes are powerful tools for probing the density profiles and dark matter substructure of the galaxies. The ratio of Einstein radii is related to the dark energy equation of state through the cosmological scaling factor $β$. However, galaxy-scale double-source-plane lenses (DSPLs) are extremely rare. In this paper, we report the discovery of four new galaxy-scale double-source-plane lens candidates in the Euclid Quick Release 1 (Q1) data. These systems were initially identified through a combination of machine learning lens-finding models and subsequent visual inspection from citizens and experts. We apply the widely-used { t LensPop} lens forecasting model to predict that the full \Euclid survey will discover 1700 DSPLs, which scales to $6 \pm 3$ DSPLs in 63 deg$^2$, the area of Q1. The number of discoveries in this work is broadly consistent with this forecast. We present lens models for each DSPL and infer their $β$ values. Our initial Q1 sample demonstrates the promise of \Euclid to discover such rare objects.

研究动机与目标

• Motivate the use of Euclid Q1 data to discover strong lensing systems, specifically double-source-plane lenses.
• Describe the Strong Lensing Discovery Engine D and its role in candidate identification.
• Outline the workflow for selecting, validating, and prioritizing double-source-plane lens candidates.
• Integrate the discovery engine within the Euclid Quick Data Release framework to enable rapid follow-up and analysis.

提出的方法

• Introduce the Strong Lensing Discovery Engine D for double-source-plane lens candidates.
• Explain the methodological framework and criteria used to identify candidates.
• Describe integration with Euclid Q1 Quick Data Release data products.
• Outline validation and candidate prioritization steps for follow-up.
• Discuss the expected workflow and collaboration with the Euclid Collaboration.

实验结果

研究问题

• RQ1 How can double-source-plane lens candidates be robustly identified in Euclid Q1 data?
• RQ2 What selection criteria and validation steps define the Strong Lensing Discovery Engine D?
• RQ3 How does the discovery engine perform in identifying and prioritizing double-source-plane lens candidates?
• RQ4 What is the proposed workflow for integrating engine D within the Euclid Q1 data release pipeline?

主要发现

• Introduces the Strong Lensing Discovery Engine D for double-source-plane lens candidates.
• Describes the methodological framework for identifying and prioritizing candidates.
• Outlines the integration of engine D with the Euclid Q1 Quick Data Release data products.
• Discusses validation approaches and follow-up strategies for candidate confirmation.