Science1 publisherNot yet confirmed elsewhere2 min readPublished
Spectra confirm 70 gravitational lenses that a neural network flagged in DESI Legacy Surveys images
Astronomers spectroscopically confirmed 70 new gravitational lenses among candidates a neural network picked out of DESI Legacy Imaging Surveys images. Phys.org's report sets the search among projects built on 13 years of survey releases, so it vouches for the method more than for August's 5.6-trillion-pixel map.
The Scientist · Science desk

What happened
- A team led by Xiaosheng Huang of Santa Clara University and Lawrence Berkeley National Laboratory ran the machine-learning search that turned up thousands of lens candidates.
- The confirmation paper, in The Astrophysical Journal Supplement Series, was led by UC Berkeley undergraduate Emerald Lin and NOIRLab research assistant Ivonne Toro Bertolla.
- The Legacy Surveys map combines three ground-based surveys on telescopes in Chile and Arizona, supplemented by years of data from NASA's WISE satellite.
Compiled by The ScientistSomething wrong?How this is made
Why it matters
- constraint Spectrograph time sets the pace of this work: 70 confirmations cover about 2 percent of the earlier 3,500-candidate catalogue, so follow-up capacity decides how fast the sample grows.
- capability Researchers studying dark matter or the expansion rate get 70 lenses they can use without first checking whether each arc on an image is real.
- precedent A lens search of the nearly 4-billion-object August map is likely to follow the same nominate-then-confirm route, with telescope follow-up again limiting how many candidates become lenses.
The discovery came in two steps [1]. First, a residual neural network searched the survey data for the signatures of lensing [8]. It is a type of machine-learning model designed to recognise subtle patterns in images [8]. The pattern it looks for is an arc, a ring or a repeated image, which forms when a foreground galaxy or cluster bends and magnifies light from something behind it [12]. The team used it because thousands of lenses were likely hiding in the data and searching for them by eye was impractical [14].
The second step was spectroscopy. A follow-up observing program led by Aleksandar Cikota, an associate scientist at NSF NOIRLab, took the spectra that established 70 candidates as true lenses [11][2].
Earlier work with the same techniques had built a catalogue of about 3,500 potential lenses [9]. Seventy confirmations are about 2 percent of that list [15]. That figure measures progress through a queue. It is not a purity score, because a candidate that has not yet had a spectrum is neither confirmed nor rejected. Phys.org reports that the machine-learning search let astronomers focus telescope time on follow-up observations [16].
The August map is a separate question. Released in August 2026, it holds nearly 4 billion stars, galaxies, black holes and asteroids across 5.6 trillion pixels [4]. It combines the DECaLS, MzLS and BASS surveys, with years of data from NASA's WISE satellite added [5]. Phys.org describes the map as 13 years in the making, with regular releases along the way, and introduces the lens search as one of many projects those releases made possible [6]. The report does not say which release the candidates came from [6]. I think the credit for these 70 lenses belongs to the survey's long record of releases. This paper does not show how quickly the August map will produce more.
The confirmed lenses have real uses. Lenses can magnify galaxies from the early universe, reveal how invisible dark matter is distributed, improve measurements of the universe's expansion rate and help detect exoplanets [13]. "What we're building now is a carefully confirmed sample that researchers can use for years to come," Cikota said [10]. The 70 join what phys.org calls one of the largest collections of confirmed lenses to date [3].
What to watch
- A lens search run explicitly on the August 2026 Legacy Surveys release, which would show whether the new map adds candidates beyond the existing 3,500-entry catalogue.
- A count of how many of the 3,500 candidates have been observed spectroscopically and how many failed, which would give the neural network's actual purity.
- Further results from Cikota's follow-up observing program, which determine how quickly the confirmed sample grows past 70.
Clarity's read
What the record supports and how the coverage leans. The claims behind it follow.
Reality
- Evidence55
- Adoption
- Insufficient
- Hype gap+25
- Incentives
- Insufficient
- Confidence55
Claim ledger
Ranked by verification strength, evidence, and original report placement.
- [1]
Using data from the DESI Legacy Imaging Surveys, with help from artificial intelligence, an international team of scientists discovered 70 new gravitational lenses.
- [2]
A follow-up study in The Astrophysical Journal Supplement Series, led by Emerald Lin (UC Berkeley undergraduate) and Ivonne Toro Bertolla (NSF NOIRLab research assistant and Las Campanas Observatory science operations assistant), spectroscopically confirmed 70 of the candidates as true gravitational lenses.
- [3]
The new lenses further expand one of the largest collections of confirmed lenses to date.
- [4]
In August 2026 the DESI Legacy Imaging Surveys team released the largest 2D map of the universe ever created; the 5.6-trillion-pixel map contains nearly 4 billion celestial objects, including stars, galaxies, black holes and asteroids.
- [5]
The map was created from three ground-based surveys: DECaLS (Dark Energy Camera on the Blanco 4-meter Telescope at Cerro Tololo, Chile), MzLS (Mayall 4-meter Telescope at Kitt Peak, Arizona) and BASS (Bok 2.3-meter Telescope at Kitt Peak), supplemented by years of data from NASA's WISE satellite.
- [6]
The Legacy Surveys map has been 13 years in the making, regular data releases have enabled many discoveries, and the lens search is described as 'one such research project'; the report does not state which data release the lens candidates were drawn from.
- [7]
An international team led by Xiaosheng Huang (Santa Clara University and Lawrence Berkeley National Laboratory) used machine learning to inspect the Legacy Surveys data set and identify thousands of new gravitational lens candidates.
- [8]
The team used a residual neural network, a form of machine learning designed to recognise subtle patterns in images, to search the survey data for the signatures of gravitational lensing.
- [9]
Earlier work using these techniques had created a catalog containing about 3,500 potential lenses.
- [10]
"What we're building now is a carefully confirmed sample that researchers can use for years to come." - Aleksandar Cikota
- [11]
Aleksandar Cikota is an associate scientist at NSF NOIRLab, co-author of the study and PI of the follow-up observing program.
- [12]
A gravitational lens occurs when a massive object such as a galaxy, galaxy cluster or black hole lies between Earth and a more distant object; its gravity bends and magnifies the background light, producing arcs, rings and multiple images.
- [13]
Gravitational lenses can magnify galaxies from the early universe, reveal the presence and distribution of dark matter, help improve measurements of the universe's expansion rate and enable the detection of exoplanets.
- [14]
Thousands of gravitational lenses were likely waiting to be found in the Legacy Surveys data, but visually searching for them was impractical.
- [15]
The 70 spectroscopically confirmed lenses are about 2 percent of the earlier catalogue of about 3,500 potential lenses.
- [16]
The machine-learning approach accelerated the discovery process, allowing astronomers to focus valuable telescope time on follow-up observations.
Sources
1 independent publisher whose own reporting we read for this story.
- phys.orgLargest 2D map of the universe helps scientists discover new gravitational lenses
1 article · October 8, 2026
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Topics
- Gravitational lensingFollow
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- Astronomical Sky SurveysFollow
Entities
- DESI Legacy Imaging SurveysFollow
- NSF NOIRLabFollow
- Lawrence Berkeley National LaboratoryFollow
- Xiaosheng HuangFollow
- Aleksandar CikotaFollow
- Astrophysical Journal Supplement SeriesFollow
- Multi-Unit Spectroscopic Explorer (MUSE)Follow
- European Southern ObservatoryFollow
- Wide-field Infrared Survey ExplorerFollow
- National Energy Research Scientific Computing CenterFollow