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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

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Illustration accompanying Spectra confirm 70 gravitational lenses that a neural network flagged in DESI Legacy Surveys images
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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.

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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
Why these scores

Claim ledger

Ranked by verification strength, evidence, and original report placement.

  1. [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. [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. [3]

    The new lenses further expand one of the largest collections of confirmed lenses to date.

Sources

1 independent publisher whose own reporting we read for this story.

  1. phys.org

    1 article · October 8, 2026

    Largest 2D map of the universe helps scientists discover new gravitational lenses

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