Quasars are intensely bright galactic cores powered by supermassive black holes. Their luminosity can outshine the galaxy hosting them, making it difficult to measure the surrounding structure precisely. Gravitational lensing offers a workaround: the quasar’s mass bends and magnifies light from nearby sources, producing telltale distortions that reveal information about both the lens and the environment around it.

Because strong lensing by quasars is uncommon, the team faced a key problem—there are not enough real examples to train a traditional detection pipeline. Instead, they built a training strategy using a mixture of genuine quasar spectra and background galaxy spectra, then generated mock lens systems. A neural network learned the subtle spectral signatures that distinguish “normal” quasars from those with lensing-related features.

The researchers analyzed a catalog of 800,000 quasar candidates from DESI DR1. After applying the model, the list was narrowed to 200 objects, which were then hand-reviewed before selecting seven final candidates. The systems lie at least 5–6 billion light-years from Earth, meaning the observations probe a distant cosmic epoch while also helping astronomers refine models of quasar and galaxy growth.

The work underscores a broader scientific motivation: quasars may represent “missing links” in the early universe, connecting black hole formation to the evolution of galaxies. By studying the correlation between galaxies and their central black holes, researchers hope to better understand why galaxies—and the black holes inside them—develop along particular pathways, including why some black holes appear dormant.

Future confirmation will rely on powerful space-based observatories such as the Hubble Space Telescope. Once deeper follow-up validates these candidates, the same AI framework could be extended to hunt for other rare spectral anomalies across massive survey datasets.

The study was published July 22 in The Astrophysical Journal, and it was supported by the U.S. Department of Energy and the EU Horizon 2020 program—an early sign that “viral” breakthroughs in astronomy may increasingly come from machine learning applied to big data.

Subject of Research: Quasars acting as strong gravitational lenses detected in DESI DR1
Article Title: Quasars Acting as Strong Lenses Found in DESI DR1
News Publication Date: 22-Jul-2026
Web References: https://science.nasa.gov/missions/webb/nasas-webb-will-use-quasars-to-unlock-the-secrets-of-the-early-universe/ ; https://www.iopscience.iop.org/article/10.3847/1538-4357/ae8014 ; https://www.desi.lbl.gov/
References: 10.3847/1538-4357/ae8014
Image Credits:

Keywords

Quasar lenses, gravitational lensing, machine learning, neural networks, DESI, strong lenses, supermassive black holes, spectral analysis, early universe

For decades, the cosmic puzzle posed by dark matter—an invisible substance forming nearly five times the mass of all visible matter combined—has mystified scientists. Ordinary matter, the stuff that composes stars, planets, and humans, accounts for only roughly one-sixth of all matter in the cosmos. The rest, dark matter, interacts primarily through gravity, eluding direct detection through electromagnetic radiation. Its gravitational influence, however, sculpts the large-scale structure of the Universe, making gravitational lensing one of the few tools capable of probing its distribution.

The technique employed here, weak gravitational lensing, involves detecting tiny distortions in the shape of distant galaxies caused by the gravitational pull of matter lying along the line of sight. Unlike strong lensing, which bends light into easily recognizable arcs or multiple images, weak lensing’s subtlety demands exquisite precision in measuring galactic shapes over large areas of the sky. Achieving such precision has historically been challenging, limited by the resolution and sensitivity of previous space telescopes.

Enter JWST, whose cutting-edge instrumentation and infrared imaging capabilities, particularly through the COSMOS-Web survey, have revolutionized weak lensing studies. The new map covers an area of 0.77 by 0.70 degrees on the sky, a relatively small patch by cosmic standards but an enormous leap in detail. By leveraging the shapes of 129 galaxies per square arcminute—many surveyed independently in two infrared bands, F115W and F150W—the researchers attain an angular resolution finer than 1 arcminute. This resolution is more than twice that achieved by prior surveys using the Hubble Space Telescope, enabling astronomers to trace the intricate cosmic web with unprecedented clarity.

The resulting mass map reveals not only the distribution of dark matter but also its intimate interplay with luminous galaxies. Structures such as filaments, clusters, and vast underdense voids emerge vividly, illustrating how dark and ordinary matter co-evolve over cosmic time. Notably, this map extends its reach out to redshifts approaching z ≈ 2, capturing mass structures at a time when the Universe was less than half its current age. This high-redshift sensitivity is crucial for understanding the environments in which galaxies formed and evolved during the epoch of peak cosmic star formation.

Among the features highlighted by the map is a massive structure located at a redshift of approximately z ≈ 1.1, making it one of the most distant mass concentrations ever observed through weak lensing. By tracing such distant structures, the study offers insights into the underlying scaffolding that guided the formation of galaxies and large-scale structures billions of years ago. The clarity and detail of this new lensing map provide a vital benchmark for testing competing theories about the nature of dark matter, whether cold, warm, or self-interacting, as well as models of cosmic evolution.

The significance of this achievement extends beyond astrophysics; mapping dark matter to such precision holds profound implications for particle physics, cosmology, and our understanding of fundamental forces. As JWST’s deep, high-resolution observations continue, astronomers anticipate refining cosmological parameters with tighter constraints, potentially revealing deviations from the standard model of cosmology or uncovering new physics.

Technical experts emphasize that the methodology behind the map’s creation involved meticulous calibration and shape measurement algorithms capable of disentangling lensing signals from noise and systematic errors. The dual-band approach, utilizing both F115W and F150W infrared filters, mitigates biases linked to galaxy color and morphological evolution, ensuring robustness in the signals extracted. The combination of deep field coverage and high galaxy density yields a lensing signal of exceptional fidelity.

Moreover, this map sets a new standard for future surveys, such as those anticipated with the Nancy Grace Roman Space Telescope and the Euclid mission. These forthcoming programs aim to survey much larger areas but with resolutions that historically could not match JWST’s. Consequently, the COSMOS-Web map functions as a template to calibrate and validate larger-scale lensing analyses, particularly in regimes probing higher redshift structures.

The study also marks an important milestone in leveraging space-based infrared observations to complement optical data. Infrared imaging penetrates dust and extends surveys to more distant galaxies whose emitted light is redshifted beyond optical wavelengths. This feature is pivotal for unraveling the growth of structure during early cosmic epochs, where galaxy clusters form and evolve amidst a rapidly changing backdrop of star formation and dark matter accretion.

Intriguingly, the detailed mapping of dark matter filaments connecting galaxy clusters offers tantalizing perspectives on the mechanisms driving galaxy interactions, cluster mergers, and the flow of baryonic matter along these cosmic highways. By dissecting these connections at an angular scale below 1 arcminute, astronomers can probe environments where dark matter density gradients influence gas dynamics, star formation rates, and feedback from black holes.

Additionally, the data harnessed here provides fertile ground for machine learning and artificial intelligence applications, potentially accelerating the classification of cosmic structures and uncovering subtle lensing features overlooked by traditional analysis. The marriage of JWST’s unparalleled imagery with advanced computational techniques heralds a new era of dark matter science.

This pioneering work emphatically demonstrates that the quest to map the invisible Universe is accelerating at an extraordinary pace, fueled by technological innovation and collaborative scientific efforts. As researchers continue to analyze JWST’s treasure trove of data, we can expect transformative insights into the dark sector’s role in shaping cosmic history and the ultimate fate of the cosmos.

The authors of this study, led by D. Scognamiglio, G. Leroy, and D. Harvey among others, have not only produced a stunningly detailed map but have also laid the groundwork for future investigations coupling weak lensing with other cosmological probes. By integrating these findings with observations across the electromagnetic spectrum and particle detectors on Earth, the scientific community moves closer to unraveling the profound mysteries of dark matter.

In conclusion, this unprecedented weak lensing mass map embodies a monumental leap forward in cosmology, revealing the hidden structure of the Universe with unprecedented sharpness and depth. It challenges theorists to reconcile these empirical observations with existing models and ignites excitement for what future observations might reveal. In an era where the cosmic dark frontier remains largely uncharted, the James Webb Space Telescope has provided a beacon, illuminating the shadowy matter that orchestrates the grand cosmic dance.

Subject of Research: Mapping the distribution of dark matter in the Universe through weak gravitational lensing using high-resolution imaging from the James Webb Space Telescope.

Article Title: An ultra-high-resolution map of (dark) matter.

Article References:
Scognamiglio, D., Leroy, G., Harvey, D. et al. An ultra-high-resolution map of (dark) matter. Nat Astron (2026). https://doi.org/10.1038/s41550-025-02763-9

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41550-025-02763-9