Euclid Quick Data Release (Q1). Refining the strong lens sample with Space Warps crowd-sourced science

@misc{collaboration2026euclid,
  title = {{Euclid Quick Data Release (Q1). Refining the strong lens sample with Space Warps crowd-sourced science}},
  author = {Euclid Collaboration and P. Holloway and A. Verma and T. E. Collett and N. E. P. Lines and T. Li and P. J. Marshall and A. More and M. Walmsley and K. Rojas and A. Manjón-García and C. Tortora and D. Sluse and J. A. Acevedo Barroso and L. R. Ecker and S. Schuldt and S. H. Vincken and J. Wilde and H. J. Dickinson and C. Scarlata and F. Courbin and G. Despali and R. B. Metcalf and R. Gavazzi and S. Serjeant and K. Jahnke and T. T. Thai and B. Altieri and L. Amendola and S. Andreon and N. Auricchio and C. Baccigalupi and M. Baldi and S. Bardelli and P. Battaglia and R. Bender and A. Biviano and M. Bolzonella and E. Branchini and M. Brescia and S. Camera and G. Cañas-Herrera and V. Capobianco and C. Carbone and J. Carretero and M. Castellano and G. Castignani and S. Cavuoti and A. Cimatti and C. Colodro-Conde and G. Congedo and C. J. Conselice and L. Conversi and Y. Copin and H. M. Courtois and M. Cropper and H. Degaudenzi and G. De Lucia and H. Dole and F. Dubath},
  howpublished = {arXiv},
  year = {2026},
  month = nov,
  doi = {10.48550/arxiv.2611.06667},
  eprint = {2611.06667},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2611.06667},
  note = {CC BY 4.0},
}

TY  - UNPB
TI  - Euclid Quick Data Release (Q1). Refining the strong lens sample with Space Warps crowd-sourced science
AU  - Euclid Collaboration
AU  - P. Holloway
AU  - A. Verma
AU  - T. E. Collett
AU  - N. E. P. Lines
AU  - T. Li
AU  - P. J. Marshall
AU  - A. More
AU  - M. Walmsley
AU  - K. Rojas
AU  - A. Manjón-García
AU  - C. Tortora
AU  - D. Sluse
AU  - J. A. Acevedo Barroso
AU  - L. R. Ecker
AU  - S. Schuldt
AU  - S. H. Vincken
AU  - J. Wilde
AU  - H. J. Dickinson
AU  - C. Scarlata
AU  - F. Courbin
AU  - G. Despali
AU  - R. B. Metcalf
AU  - R. Gavazzi
AU  - S. Serjeant
AU  - K. Jahnke
AU  - T. T. Thai
AU  - B. Altieri
AU  - L. Amendola
AU  - S. Andreon
AU  - N. Auricchio
AU  - C. Baccigalupi
AU  - M. Baldi
AU  - S. Bardelli
AU  - P. Battaglia
AU  - R. Bender
AU  - A. Biviano
AU  - M. Bolzonella
AU  - E. Branchini
AU  - M. Brescia
AU  - S. Camera
AU  - G. Cañas-Herrera
AU  - V. Capobianco
AU  - C. Carbone
AU  - J. Carretero
AU  - M. Castellano
AU  - G. Castignani
AU  - S. Cavuoti
AU  - A. Cimatti
AU  - C. Colodro-Conde
AU  - G. Congedo
AU  - C. J. Conselice
AU  - L. Conversi
AU  - Y. Copin
AU  - H. M. Courtois
AU  - M. Cropper
AU  - H. Degaudenzi
AU  - G. De Lucia
AU  - H. Dole
AU  - F. Dubath
PY  - 2026
DA  - 2026/11/04
PB  - arXiv
DO  - 10.48550/arxiv.2611.06667
UR  - https://arxiv.org/abs/2611.06667
AB  - We demonstrate the efficacy of crowd-sourced refinement of strong gravitational lens candidate samples by citizen scientists. Binary (lens/non-lens) classification by citizen scientists has been conducted previously, and here we extend such categorisation into `definite', `probable', `possible', and `non-lenses'. This grading is a required stage ahead of any strong lens sample publication and is usually carried out by (small) teams of researchers. We compare the responses of the volunteers to those of strong lens researchers and discuss the optimal strategy for lens classification and grading in future strong lens searches. Volunteers are found to be able to correctly identify systems of each grade, and their responses can be calibrated to be comparable to those of researchers. Grade posteriors, defined as the probability that a strong lens system classified by the volunteers is a certain grade, converge most rapidly for non-lens systems. We find that one researcher classification is equivalent to only 1.9 volunteer classifications when grading such systems. There is significant disagreement in the grading of intermediate-grade lens candidates amongst both volunteers and researchers. Moving towards calibrated lens probabilities for future lens searches would help to account for such subjectivity. If the Q1 lens search was rerun with volunteers performing lens grading (and corresponding calibration), a completeness of 79% for Grades A+B (corresponding to definite + probable lenses respectively) could be achieved with 41% purity prior to researcher inspection - this would correspond to an expected 12500 true lenses (i.e. excluding contaminants) in Euclid DR1.
ER  -