Surveying the Universe in 4D: Beating Cosmic Variance with Wide-Field Slitless Spectroscopy from HST, JWST, Euclid, Roman, and Beyond

@misc{petric2026surveying,
  title = {{Surveying the Universe in 4D: Beating Cosmic Variance with Wide-Field Slitless Spectroscopy from HST, JWST, Euclid, Roman, and Beyond}},
  author = {Andreea Petric and Gaël Noirot and Stacey Alberts and Russell Ryan and Louis-Gregory Strolger and Vicente Estrada-Carpenter and Mainak Singha and Adrian E. Bayer and Olivier Gilbert and Farhanul Hasan and Mason Huberty and Bingcheng Jin and Xiangyu Jin and Anika Kumar and Kasra Mokhtarpour and Preethi Nair and Eleni Tsiakaliari and Vivian U and Brittany N. Vanderhoof and Arshia Akhtarkavan and Natalia Alvarez-Ibanez and Roman Fernandez Aranda and Tri L. Astraatmadja and Clive Binu and Claire Bolda and Westley Brown and Guillermo Romero Cruz and Mohamed H. Abdullah and Jeremy Favaro and Mason Footh and Helen Fraser and Yuming Fu and Annie Giman and Nicolas Gomez and Massimo Griggio and Peter Gwartney and Aryana Haghjoo and Fabian Hervas-Peters and Jiamu Huang and Sandra Jaison and Jeyhan S. Kartaltepe and Sarah Kendrew and Ivan Kramarenko and Sahana Kumar and Zhaoran Liu and Arianna S. Long and Sangeeta Malhotra and Faezeh Manesh and Jasleen Matharu and Vihang Mehta and Edward M. Molter and Ivelina Momcheva and Zhiwei Pan and Yuxuan Pang and Pallavi Patil and Rachel Plesha and Marc Rafelski and Mitchell Revalski and Jyotika Roychowdhury and Gregory Rudnick},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.23148},
  eprint = {2609.23148},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.23148},
}

TY  - UNPB
TI  - Surveying the Universe in 4D: Beating Cosmic Variance with Wide-Field Slitless Spectroscopy from HST, JWST, Euclid, Roman, and Beyond
AU  - Andreea Petric
AU  - Gaël Noirot
AU  - Stacey Alberts
AU  - Russell Ryan
AU  - Louis-Gregory Strolger
AU  - Vicente Estrada-Carpenter
AU  - Mainak Singha
AU  - Adrian E. Bayer
AU  - Olivier Gilbert
AU  - Farhanul Hasan
AU  - Mason Huberty
AU  - Bingcheng Jin
AU  - Xiangyu Jin
AU  - Anika Kumar
AU  - Kasra Mokhtarpour
AU  - Preethi Nair
AU  - Eleni Tsiakaliari
AU  - Vivian U
AU  - Brittany N. Vanderhoof
AU  - Arshia Akhtarkavan
AU  - Natalia Alvarez-Ibanez
AU  - Roman Fernandez Aranda
AU  - Tri L. Astraatmadja
AU  - Clive Binu
AU  - Claire Bolda
AU  - Westley Brown
AU  - Guillermo Romero Cruz
AU  - Mohamed H. Abdullah
AU  - Jeremy Favaro
AU  - Mason Footh
AU  - Helen Fraser
AU  - Yuming Fu
AU  - Annie Giman
AU  - Nicolas Gomez
AU  - Massimo Griggio
AU  - Peter Gwartney
AU  - Aryana Haghjoo
AU  - Fabian Hervas-Peters
AU  - Jiamu Huang
AU  - Sandra Jaison
AU  - Jeyhan S. Kartaltepe
AU  - Sarah Kendrew
AU  - Ivan Kramarenko
AU  - Sahana Kumar
AU  - Zhaoran Liu
AU  - Arianna S. Long
AU  - Sangeeta Malhotra
AU  - Faezeh Manesh
AU  - Jasleen Matharu
AU  - Vihang Mehta
AU  - Edward M. Molter
AU  - Ivelina Momcheva
AU  - Zhiwei Pan
AU  - Yuxuan Pang
AU  - Pallavi Patil
AU  - Rachel Plesha
AU  - Marc Rafelski
AU  - Mitchell Revalski
AU  - Jyotika Roychowdhury
AU  - Gregory Rudnick
PY  - 2026
DA  - 2026/09/19
PB  - arXiv
DO  - 10.48550/arxiv.2609.23148
UR  - https://arxiv.org/abs/2609.23148
AB  - We summarize strategies, lessons learned, and future directions from the Space Telescope Science Institute workshop Surveying the Universe in 4D: Beating Cosmic Variance with Wide-Field Slitless Spectroscopy from HST, JWST, Euclid, Roman, and Beyond, held August 24--28, 2026. The workshop examined scientific results, observational and data analysis challenges, extraction tools, and future opportunities. Discussions highlighted (1) the transformative potential of WFSS for the study of transient phenomena, galaxy evolution --both spatially-resolved and within the broader context of the cosmic web--, and rare populations and (2) the synergies among Euclid and Roman surveys, Rubin-LSST monitoring, JWST WFSS, and high-resolution integral-field observations. Participants identified advances in forward modeling and physics-informed machine learning as essential for addressing spectral overlap, crowded fields, and upcoming, very large data volumes. Realizing WFSS's full potential will require community-wide infrastructure, science-ready data products, accessible cloud-based analysis tools, and robust benchmarking of reduction pipelines. Crucially, participants called for systemic changes to properly recognize early-career researchers who invest significant efforts in pipeline, code, and calibration developments that enable WFSS science, and stressed that progress requires collaborative, multidisciplinary practices that optimize the participation and benefits of the next generation.
ER  -