You can explore gravitational lenses without owning a telescope: start with the community catalog lenscat to locate known systems, then inspect public survey images from the DESI Legacy Surveys or selected Euclid previews. Treat an arc-like shape, catalog entry, or machine-ranked object as a lead—not automatic proof. Candidate status, data coverage, and survey release all matter when you decide what an image shows.
What a gravitational lens looks like
A gravitational lens forms when mass in the foreground bends light from a more distant object. The foreground mass is often a galaxy or a cluster of galaxies; the background source may be another galaxy or a quasar. In a strong lens, the deflection can produce visible arcs, a ring-like image, or several images of the same source. NASA describes a quasar appearing as four images around a foreground galaxy as one example.
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When examining an image, try to distinguish the likely lens from the likely source. The foreground galaxy or cluster is the mass doing the bending; the distorted light around or near it may come from farther away. An arc-like feature by itself is not enough to establish that interpretation. Interacting galaxies and image artifacts can look suggestive too, and a visual resemblance does not replace scientific vetting.
Strong lensing is the most immediately recognizable form for a visual search because the distortion can be apparent in an image. Weak lensing is a subtler effect: the shapes of many background galaxies are slightly distorted, so it is generally studied statistically across populations rather than identified as an obvious ring or set of multiple images. The routes below focus on finding known or candidate strong lenses, not measuring weak-lensing signals.
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Choose a route based on what you want to inspect
| Route | What you explore | Access and useful details | How to interpret a result |
|---|---|---|---|
| lenscat | A community-contributed catalog of known strong lenses | Web app, CSV, and Python package; supports searches by sky coordinates, lens redshift when available, lens type, and grading, as well as cross-matching and plotting | A convenient catalog record, not a definitive official census; check its grading and the cited source for the individual object |
| DESI Legacy Surveys imaging | Public wide-area survey images in optical and infrared bands | DESI describes roughly 14,000 square degrees of imaging, with optical g, r, z and four infrared bands | Use images to inspect candidate visual structure; an apparent arc still needs verification |
| DESI DR1 Strong Lensing Catalog | Spectroscopic records for strong-lens observations | FITS file desi-sl-vac-v1.fits, with a DESI_SL_CATALOG extension and documented observation and fit fields | It covers DR1 observations and is a subset of the DR2 sample, not a complete DESI or DR2 inventory |
| Euclid deep-field previews in ESASky | Selected Euclid deep-field preview images and a set of reported lens candidates | ESA’s 19 March 2025 release described previews of three deep fields as explorable in ESASky | Separate released previews and reported candidate records from images available only through a participation project |
| Euclid Space Warps | AI-preselected images offered for volunteer classification | ESA’s 2026 announcement described about 300,000 images selected from 72 million DR1 galaxies | The announced yield of more than 10,000 new lenses was an expectation, not a confirmed completed count; check the project for current access |
There is no established completeness or sensitivity comparison here that makes one survey a categorical winner. DESI and Euclid differ in survey coverage and imaging, while catalog and citizen-science routes expose different kinds of records. Choose by the question you have: locating a documented system, inspecting broad-area imaging, looking at spectroscopic observations, or helping classify selected images.
Start with lenscat when you want a known object
Search and inspect a record
- Open the lenscat web app, or download its plain CSV if you prefer to browse records in a spreadsheet or another data tool. The project also provides a Python package for people who want to work programmatically.
- Search using sky coordinates if you have a location to investigate. Other documented filters include lens redshift when available, lens type, and grading. A missing redshift should not be treated as evidence against a lens: the catalog only exposes that search value when it is available for a record.
- Open a promising object and examine its grading and attached references. The catalog is community-contributed, and individual entries can differ in grading and documentation. Follow the cited study for the object rather than treating inclusion alone as confirmation.
- Use the cross-matching and sky-map plotting features to relate catalog objects to other positions or records you are examining. Keep track of the coordinates and which catalog record you matched; a positional association is a useful navigation aid, not by itself a physical explanation of the image.
Lenscat is most useful as an entry point into existing knowledge. It helps you discover names and references, but it should not be described as an official, complete inventory of all strong lenses. For research or a claim about an individual system, the underlying publication is the stronger place to establish how the object was identified and graded.
Inspect public DESI Legacy Surveys images
Understand what the imaging covers
The Dark Energy Spectroscopic Instrument (DESI) describes the Legacy Surveys as public imaging over approximately 14,000 square degrees of extragalactic sky. The stated approximate footprint is -18° < δ < +84° and |b| > 15°, where δ is declination and b is Galactic latitude. These bounds describe a broad survey footprint, not a guarantee that every sky coordinate has identical coverage or image quality.
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1Fix the driver behind crashes, sound loss and screen glitches2Repair Windows errors before they cause bigger problems3Scan for outdated or missing drivers - takes under a minuteThe imaging combines optical g, r, and z bands with four infrared bands. Viewing the bands separately or in available combinations can help you notice structures that are less obvious in a single view. A colored feature should still be interpreted cautiously: the colors encode measurements in selected bands, not a direct label saying which object is in the foreground or whether a feature is lensed.
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Use candidate counts with their original scope
A 2022 study, New Strong Gravitational Lenses from the DESI Legacy Imaging Surveys Data Release 9, used neural-network ranking followed by visual inspection to search DESI Legacy Surveys DR9. The paper reported 1,895 candidates in that search, including 1,512 identified for the first time. Across that paper series’ first two papers and the DR9 paper, its authors reported 3,057 new candidates.
Those figures are publication-specific candidate totals, not the number of confirmed lenses in a live DESI inventory. They describe a particular search and sample, using a machine-ranking and human-inspection process. If you cite one, retain the words “candidates,” name the 2022 DR9 study, and do not present the totals as a current count of confirmed systems.
Turn an interesting image into a documented lead
- Choose a location within the survey’s broad footprint and open the corresponding public survey imaging through the available Legacy Surveys viewing route.
- Inspect the scene for a plausible foreground galaxy or cluster and possible distorted background light. Look for coherent arcs, ring-like structure, or multiple images rather than relying on color alone.
- Compare the appearance across the available bands and note the coordinate, image context, and data release you used. This makes the lead reproducible and helps distinguish what you actually observed from your interpretation.
- Search lenscat for a matching known system and consult candidate publications where relevant. A match may connect your image to an existing record; no match does not prove that the object is new or that it is a lens.
- Describe an unverified find as a possible lens or candidate. Confirmation requires evidence beyond visual plausibility, such as the expert vetting, modeling, or spectroscopic context documented for a particular system.
The available sources establish that candidate vetting is necessary, but do not provide a complete beginner’s catalog of every false-positive pattern. Do not treat the list of visual clues above as a classifier or as a substitute for the cited study of a candidate.
Read the DESI DR1 Strong Lensing Catalog within its limits
For spectroscopic records, DESI’s data documentation describes the FITS file desi-sl-vac-v1.fits and its DESI_SL_CATALOG extension. Listed fields include target ID, survey, program, HEALPix, redshift, redshift error, warning bits, fit statistic, coefficients, and pixel count. These fields can help you identify the target and understand what observations or fit information the record contains.
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The essential boundary is in the catalog’s release description: it comprises DR1 observations and is a subset of the DR2 sample. It is not a complete catalog of every DESI strong lens, and it should not be labeled a complete DR2 inventory. When recording a result, preserve the catalog name and release scope so that a reader can distinguish a DR1 observation from a broader survey claim.
A catalog record with a redshift or fit-related fields is not automatically equivalent to a published confirmation of lensing. Check the documentation and the relevant object study to understand the role of the recorded observation. In particular, distinguish evidence that a target was observed from a conclusion that the lens interpretation has been validated.
Explore Euclid previews and participation images carefully
Released deep-field previews
In a release dated 19 March 2025, the European Space Agency (ESA) described a first catalog of 500 galaxy-galaxy strong-lens candidates. ESA said the candidates were identified through AI screening followed by citizen-science inspection, expert vetting, and modeling, and that selected previews of three Euclid deep fields could be explored in ESASky. The number is a candidate count from that release, not a claim that all 500 are confirmed lenses.
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The same announcement said that, as of 19 March 2025, Euclid had observed about 2,000 square degrees—approximately 14% of its stated 14,000-square-degree survey area. Keep that date attached to the figure: it describes mission progress at the time of the announcement, not a current measurement of the survey’s completed coverage.
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Space Warps and the difference between announced and public data
ESA’s 2026 announcement described Euclid Space Warps as an early look at images associated with Euclid DR1. It said around 300,000 AI-preselected images would be shown, selected from 72 million DR1 galaxies classified by AI, and gave an expected yield of more than 10,000 new lenses. These were project expectations in the announcement, not a reported final yield.
ESA also said that the new images were not yet public outside the project at the time of that announcement. That statement is time-sensitive: do not assume it describes the project’s access today. Check the current Space Warps project and Euclid archive to determine whether participation or public access has changed. It is important to distinguish images available as public previews from images accessible through a volunteer classification workflow.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep candidate, catalog, and confirmation language separate
Several different stages can appear side by side in public astronomy resources. A machine score may rank an image for review; a visual search may produce a candidate; a community catalog may list a known system with a grade and references; spectroscopy may provide observations; and expert vetting or modeling may support a stronger conclusion. These are related, but they are not interchangeable labels.
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Outbyte PC Repair FREERepair Windows errors before they cause bigger problemsFix Now →Outbyte Driver Updater FREEScan for outdated or missing drivers - takes under a minuteDriver Scan →- Use “candidate” when describing the DESI DR9 search totals or the 500 Euclid candidates reported in March 2025.
- Call lenscat a community-contributed catalog of known strong lenses, and use the individual record’s grading and reference to explain the status of a particular object.
- Describe DESI DR1 catalog entries as DR1 observations and records, rather than as a complete lens census.
- For an individual scientific claim, follow the object’s cited study and its evidence. Do not turn an attractive image, machine score, or catalog match into a confirmation statement without support.
This language is useful even when you are browsing casually. It tells the next reader whether they are looking at a visual lead, a cataloged system, an observation, or a result supported by a study.
Make an exploration reproducible
Public data can change as releases and project access evolve. When saving an image or sharing a candidate, record enough context for another person to find the same material and understand what you saw.
- Write down the sky coordinates and the survey or catalog used.
- Record the data release or catalog version where one is stated; for DESI spectroscopy, distinguish DR1 from the wider DR2 sample.
- Note the access date, especially for Euclid previews and Space Warps, whose routes and availability may change.
- For a catalog match, preserve the object’s identifier, grading if provided, and the reference attached to the record.
- Keep observation separate from interpretation: describe the apparent arc or multiple images, then state whether the object is only a candidate or has a supporting study.
That small record-keeping step prevents a screenshot from losing its context and makes it easier to compare what a public interface showed with the published evidence.
Sources and scope to retain when citing results
The most useful source for a claim depends on what you are claiming. DESI’s imaging-surveys overview establishes the stated footprint and bands; its DR1 Strong Lensing Catalog documentation establishes the FITS file, fields, and release boundary. The 2022 DR9 paper is the source for its own candidate totals. ESA’s dated Euclid announcements establish what was reported about the 2025 candidate release and the 2026 Space Warps plans. A lenscat entry points toward object-specific references, which should be checked directly for a claim about a named lens.
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Do not collapse these into a single number called “lenses found.” The underlying sources describe different data products, selection methods, dates, and confidence stages. Preserve those distinctions in notes, captions, and any later analysis.
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