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Start with lenscat to browse known strong-lens systems, then use public DESI Legacy Surveys images to explore the sky and compare visual clues with published candidates. For spectroscopic records, consult the DESI DR1 Strong Lensing Catalog; for selected Euclid deep-field images, use the previews ESA described as explorable in ESASky. These routes answer different questions: a catalog entry, a survey candidate, a spectroscopic observation, and a confirmed lens are not interchangeable.
A curved arc, ring, or group of repeated images can be a sign of gravitational lensing, but appearance alone does not establish that an object is a lens. The most reliable beginner workflow is to find a plausible feature, identify the dataset and its release, then follow the record’s references and status before treating it as confirmed.
What a gravitational lens looks like
Gravity from matter between an observer and a more distant source bends the source’s light. When the alignment and mass distribution are suitable, the background object can appear magnified, stretched into an arc, arranged into a ring, or split into multiple images. The foreground galaxy or cluster is the lens; the distorted or repeated light belongs to the more distant source. NASA’s overview of gravitational lenses illustrates a quasar appearing as four images around a foreground galaxy and explains how Hubble resolves faint lensed images.
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Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Strong lensing creates conspicuous distortions or multiple images. Weak lensing is generally detected through small, statistical distortions in the apparent shapes of many background galaxies rather than one dramatic ring or arc. This guide focuses on finding and exploring strong-lens systems, because the public catalog and candidate routes described below are centered on them.
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Do not identify a lens from color or shape alone. A blue arc-like feature may be a lens candidate, but interacting galaxies, other structures, and image artifacts can also look unusual. Treat visual appearance as a reason to investigate, not a verdict. A published record, the underlying study, and any stated vetting or modeling are important context.
Choose the route that matches your goal
| Route | What you explore | Useful for | Important limit |
|---|---|---|---|
| lenscat web app, CSV, or Python package | A community-contributed catalog of known strong lenses | Finding named systems, filtering records, and following references | It is a community catalog, not a definitive official census; grading and references vary by entry. |
| DESI Legacy Surveys imaging | Public wide-area optical and infrared survey images | Examining sky regions and visual features, and exploring the setting of reported candidates | Images and candidate lists do not by themselves confirm a lens; the stated footprint is approximate. |
| DESI DR1 Strong Lensing Catalog | Spectroscopic observations recorded in a FITS file | Inspecting listed observation and redshift-related fields | The documentation says it contains DR1 observations and is a subset of the DR2 sample, not a complete DESI or DR2 inventory. |
| Euclid deep-field previews in ESASky | Selected preview images from three deep fields | Exploring the images ESA highlighted alongside its first candidate catalog announcement | The cited release describes selected previews, not complete access to all Euclid survey images. |
| Euclid Space Warps | AI-preselected images for volunteer classification, as described by ESA | Participating in citizen-science classification when the project is accessible | ESA’s 2026 announcement said the images were not yet public outside the project at that time. The cited announcement does not establish present-day access or a completed yield. |
There is no supported, controlled comparison showing that one survey route is categorically more sensitive or complete than another. They differ in what they expose: catalog records, broad survey imaging, spectroscopic observations, selected space-based previews, or a volunteer classification workflow. Choose by the task you want to do, and record the data release and access date when you save or cite a result.
Browse known systems with lenscat
The lenscat project describes itself as a public, community-contributed catalog of known strong gravitational lenses. It offers a mobile-friendly web app, a plain CSV, and a Python package. Its documented search and exploration options include sky coordinates, lens redshift when available, lens type, grading, cross-matching, and plotting on a sky map.
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- Open the web app or download the CSV. Choose the browser route for an initial visual search, or the CSV if you want to work with records in a spreadsheet or another analysis environment. The project also provides a Python package for programmatic use.
- Filter by position or properties. Search by right ascension and declination, and narrow by lens redshift when recorded, lens type, or grading. A missing redshift is not evidence that a system is not a lens; it means that value is not available in that entry.
- Inspect the record rather than just its plotted point. Review the available grading and source references. A sky-map position helps locate the object, but does not tell you by itself how the system was established.
- Follow the cited study for scientific use. Check the underlying paper or source attached to an entry to understand its evidence and status. Community catalog entries may vary in grading and reference detail, so do not treat every row as having the same evidentiary standing.
- Record what you used. Note the catalog access date and the record or coordinates, especially if you later compare it with a survey image or another catalog. Public catalogs can change as records are added or revised.
lenscat is a convenient starting point when the question is “Has someone already cataloged a system in this part of the sky?” It is less suitable as a final authority on confirmation or as a complete count of all lenses. Use its references to establish what a particular record means.
Explore public DESI Legacy Surveys images
The Dark Energy Spectroscopic Instrument describes the Legacy Surveys as optical imaging in g, r, and z bands combined with four infrared bands, covering roughly 14,000 square degrees of extragalactic sky. Its imaging overview gives the approximate footprint as -18° < δ < +84° and |b| > 15°, and says the data are public. These are the survey’s stated approximate coverage figures, not a guarantee that every coordinate or object has identical data.
- Start from a position or a reported object. Use coordinates from a lenscat record or a published candidate when you have one. If you are browsing without a target, choose a region within the Legacy Surveys’ stated footprint.
- Open the public imaging products for that sky position. Inspect the available optical and infrared views. The band labels identify observations in different parts of the spectrum; a feature’s appearance can vary between bands, so compare them rather than relying on a single color composite.
- Separate the possible lens from the possible source. Look for a foreground galaxy or cluster and a candidate background feature such as a curved arc, ring, or multiple images. Keep the interpretation tentative: a plausible configuration is a visual clue, not proof that the foreground mass lensed the light.
- Compare against catalog and paper records. Search lenscat by coordinates or cross-match as appropriate, then follow the relevant candidate publication if one exists. A match is a lead to evidence, not confirmation on its own.
- Write down the release and coverage context. Include the survey data release, position, bands inspected, and access date in your notes. This matters when images or catalogs are updated and when another person needs to reproduce the lookup.
DESI Legacy Surveys imaging is useful for wide-area exploration, but a survey footprint is not the same as uniform depth, resolution, or completeness. The cited overview establishes the broad bands and approximate area; it does not provide a controlled comparison with Euclid imaging or a guarantee that every lens in the footprint will be detectable.
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Understand what DESI candidate counts mean
A 2022 paper, New Strong Gravitational Lenses from the DESI Legacy Imaging Surveys Data Release 9, described a search of DR9 images using a neural-network ranking followed by visual inspection. Its authors reported 1,895 candidates in that search, of which 1,512 were identified for the first time. Combining that paper with the first two papers in the series, the authors reported 3,057 new candidates across the series.
Those figures are publication-specific candidate counts, not a live inventory of confirmed lenses and not a count that should be applied to every DESI release. The method involved both machine ranking and human visual inspection; the word “candidate” remains important. If you cite these numbers, attribute them to the 2022 paper and its sample rather than presenting them as current totals.
Inspect the DESI DR1 Strong Lensing Catalog
For a catalog route focused on spectroscopic records, DESI’s official data documentation describes the FITS file desi-sl-vac-v1.fits and its DESI_SL_CATALOG extension. The listed fields include target ID, survey, program, HEALPix, redshift, redshift error, warning bits, fit statistic, coefficients, and pixel count. These are useful for understanding what an observation record contains; they are not interchangeable with a published confirmation label.
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- Open the official catalog documentation. Confirm the catalog name, file name, and extension before using a downloaded copy.
- Load the FITS catalog with software that reads FITS tables. Select the
DESI_SL_CATALOGextension and inspect its column names and metadata. The documentation identifies the fields above, but the precise analysis you can do depends on how you use the values and their definitions. - Use IDs and sky indexing to connect records carefully. Keep the target ID, survey, program, and HEALPix context with any redshift value you extract. Do not discard warning bits or fit information if you are evaluating a record.
- Check the catalog’s release boundary. DESI documentation says this catalog comprises DR1 observations and is a subset of the DR2 sample. It should not be described as a complete DR2 sample or a complete inventory of DESI strong lenses.
- Follow any relevant source material. If you intend to make a scientific claim about a system, use the documentation and applicable published work to establish what the spectrum and catalog entry demonstrate.
A redshift and its reported error are measurements recorded in a catalog field; they do not independently demonstrate that a particular image feature is a gravitational lens. Likewise, the existence of an observation record means there is a spectroscopic entry, not that every classification question about the target has been settled.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Explore Euclid images and citizen-science routes
Selected Euclid previews in ESASky
In a release dated 19 March 2025, the European Space Agency described a first catalog of 500 galaxy-galaxy strong-lens candidates found through AI screening, followed by citizen-science inspection, expert vetting, and modeling. ESA said selected preview images from three Euclid deep fields could be explored in ESASky. This is a route to those selected previews, not evidence that the entire Euclid image archive or every candidate is available there.
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The same announcement said that by 19 March 2025 Euclid had observed about 2,000 square degrees, approximately 14% of its stated 14,000-square-degree survey area. Keep the date and scope attached to those numbers: they describe progress reported in that release, not a current coverage total. Preview images can help you inspect striking examples, while the associated announcement and catalog context explain that the 500 objects were candidates.
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Space Warps and the status of access
ESA’s 2026 Space Warps announcement described a citizen-science effort using around 300,000 AI-preselected images selected from 72 million Euclid DR1 galaxies classified by AI. It presented more than 10,000 new lenses as an expected yield, not a completed result. ESA also said in that announcement that the images were not yet public outside the project at the time. That statement is time-bound: the announcement alone does not establish whether access or results have changed since it was made.
If you want to participate, check the project’s current access information before assuming you can browse the images independently. A volunteer classification interface and a public survey-image archive are different kinds of access. The announced scale and expected yield describe ESA’s plan, not the number of confirmed lenses already available to download.
A practical way to document a possible lens
Whether you begin with a catalog entry or spot an unusual shape in survey images, keep enough context for someone else to retrace the observation. This is especially important because catalogs and survey products have release boundaries, and a convincing image alone does not resolve candidate status.
- Position: retain the sky coordinates or catalog identifier used to locate the system.
- Dataset: name the survey or catalog and the release or file you inspected.
- Image context: record which available bands or preview product showed the feature.
- Record status: distinguish a cataloged known system, a published survey candidate, a spectroscopic observation, and an expert-vetted or modeled candidate where the source makes that distinction.
- Evidence trail: follow the record’s references and cite the underlying publication when making a scientific claim.
- Access date: note when you used the data, particularly for projects whose public status or released products can change.
For a first exploration, a sensible sequence is to locate a known object in lenscat, inspect its position in DESI imagery, and then consult the relevant record or study. If you instead begin with Euclid previews or a volunteer-classification project, keep the release date and access scope attached to what you saw. Either route can be useful without turning a visual impression into a claim of confirmation.
Common interpretation mistakes
- Calling every arc a lens. An arc-like form is a clue; visual resemblance does not rule out other structures or artifacts.
- Treating a machine score as a discovery verdict. The DESI DR9 work used machine ranking followed by visual inspection, while the Euclid release described additional citizen-science, expert, and modeling steps. Selection and vetting stages matter.
- Collapsing different records into one status. A community catalog record, a candidate list, and a spectroscopic observation tell you different things. Check the source for the status it actually assigns.
- Using a count without its date and sample. The DESI figures are from a 2022 DR9 paper and series; the Euclid first catalog was announced in March 2025. Neither figure is a current total of confirmed lenses.
- Overstating coverage. DESI’s approximate imaging footprint does not mean all sky is covered or all objects are equally detectable. The cited Euclid previews cover selected deep-field material, not the full survey.
- Assuming an announced project is an open archive. ESA’s Space Warps announcement explicitly described image access limits at announcement time. Check current project information rather than inferring present access from a dated notice.
Sources and release context
The routes and figures above are attributed to the lenscat project documentation; DESI’s Legacy Surveys imaging overview and Strong Lensing Catalog documentation; the 2022 paper New Strong Gravitational Lenses from the DESI Legacy Imaging Surveys Data Release 9; NASA’s gravitational-lensing overview; and ESA’s Euclid and Space Warps announcements. The ESA 500-candidate release is dated 19 March 2025. The DESI DR9 counts belong to the 2022 publication. The Space Warps figures are announcement-time plans and expectations, not confirmed completed outcomes.
For reproducible use, consult the relevant primary project page or paper directly and note the release and date you accessed. In particular, do not infer from an announcement that a later Euclid release occurred or that project access remains unchanged: the cited announcements establish what was described at their publication time, not every subsequent change.
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