Claude Code Finds a Planet Candidate in 7 Years of NASA TESS Data

An independent researcher says he used Claude Code to find a planet candidate that sat in NASA telescope data for about seven years. The claim spread fast on October 7 and 8, 2026. Read it carefully. A planet candidate is a signal that looks like a planet. It is not a confirmed planet. The author says so himself.

This post covers what Pavel Rabtsevich actually claims, the checks he reports, the main way the result could be wrong, and what builders can copy from his workflow.

TL;DR: the claim in one table

Update (October 9, 2026): a second user claims 10 more candidates

A second X account, @dysmemic, posted on October 7 that it used Opus 5.5 to scan 9,979 nearby red and orange dwarf stars and found 10 possible exoplanets "that aren't reported anywhere I could find." One of them, per the post as relayed by news aggregators, may be a third transiting planet around TOI-4342. Headlines have called this "10 more exoplanets."

Treat it as a claim, not a result. We found no preprint, data release or code behind the post, and no NASA or TESS page that mentions it. A "possible planet" from a search over nearly 10,000 stars is exactly where chance signals and instrument systematics show up, which is the post hoc selection risk described below. TOI-4342 is a known system: a 2023 Astronomical Journal paper reported two sub-Neptunes there (arXiv 2301.01370), so a third candidate would need its own vetting against that published work.

To judge claims like this, ask for the same things Rabtsevich published: the period and depth of each signal, injection and shuffled-data controls, and held-out predictions. Without them, it is a list of leads. We will update this section if the author publishes details. Source: @dysmemic on X.

What happened

On October 7, 2026, Rabtsevich posted on X: "I think I found a planet nobody knew existed. It's been hiding in NASA telescope data for seven years." The post had passed 740,000 views when we read it. He also posted in r/ClaudeAI on Reddit. HuggingNews and other outlets then repeated the story.

The primary document is the preprint. It is titled "Two Transit-like Signals in TESS Photometry of the Nearby K Dwarf TIC 4206066". It sits on Zenodo, dated September 25, 2026, and was modified on October 6. The author describes it as a preprint of a Research Note prepared for submission to the Research Notes of the AAS. It has not been peer reviewed.

The abstract says the signals were found in TESS Sector 98 and traced back to Sectors 6 and 32. The 3.18-day signal shows 23 transits at about 500 ppm. That corresponds to a planet of 1.4 plus or minus 0.1 Earth radii, if the signal comes from the target star.

HuggingNews adds that he wrote more than 1,000 scripts and used Claude Code with the Opus 5.5 and Fable 5.1 models. A summary of his post by a GitHub user says the analysis took two weeks. Treat the "1,000 scripts" and "two weeks" numbers as the author's reported figures, not as audited facts.

Why "candidate" is the right word

Astronomers use a ladder of words. Each rung needs more evidence.

1. Signal: a dip in brightness that repeats.
2. Candidate: the dip looks like a transit and survives basic checks.
3. Validated: a statistical argument says a planet is far more likely than any false positive.
4. Confirmed: independent measurements, often radial velocity or mass, show a real planet.

Rabtsevich sits between rungs 1 and 2. His preprint states that no statistical validation is claimed. His false-positive probability, from the TRICERATOPS tool, is 0.03 to 0.04. That number is low, but his own text says most of that probability comes from companion stars that his data disfavor. It does not close the case.

HuggingNews wrote that NASA "approved a formal request for telescope time." The more exact statement is this: the TESS mission lists a Director's Discretionary Time program for the star. The TESS DDT page shows Program 100, PI Pavel Rabtsevich, "Two-minute cadence for TIC 4206066, a nearby K-dwarf with a 1.4R planet candidate." Observation time is a test, not a verdict.

How the search worked

TESS, the Transiting Exoplanet Survey Satellite, watches large patches of sky and records stellar brightness. Public light curves live at NASA's MAST archive. A transit search looks for small, regular dips when a planet crosses its star.

A summary of Rabtsevich's workflow says Claude Code did much of the heavy lifting:

• downloading and parsing TESS data,
• writing transit-search code,
• fitting the dips,
• checking nearby stars for contamination,
• running false-positive checks,
• plotting and rerunning analyses.

Codex and separate clean agent sessions then reviewed the work. That matters. A single long session tends to defend its own earlier claims. A fresh session that only sees the result can attack it.

The same summary says the audit caught at least one overstrong statistical claim, and the author removed it. That is the right behavior. It is also a warning. If an audit caught one, an unaudited run would have shipped it.

The vetting checks he reports

The catalog search is the answer to "was this really unknown?" Per his post, he checked and found nothing matching. We have not independently re-run that search.

The main way this could be wrong

The preprint names it directly: a planet transiting an unresolved bound companion is the main alternative host scenario. In plain words, TIC 4206066 may be a pair of stars too close to separate. The planet could orbit the faint companion, not the target. Then the planet radius changes, and the claim "1.4 Earth radii" no longer holds for the target.

Other classic failure modes apply to any TESS candidate:

• Eclipsing binary in the background. A distant pair dims the pixels.
• Instrument systematics. Spacecraft pointing and scattered light make fake dips.
• Post hoc selection. Searching many stars and many periods produces chance signals. This is why the weak 11.13-day signal sits at only about 3 sigma in a post hoc test.

High-resolution imaging and radial velocities would help rule out the companion scenario. The summary of his work says the same.

The part worth copying: a preregistered test

The strongest idea is not the AI. It is the preregistration. TESS approved DDT Program 100 for two-minute cadence observations in Sector 110, from October 31 to November 26, 2026. Before that data exists, Rabtsevich published fixed predictions: nine expected transits for the main signal, three for the weaker one, expected depths, processing steps, and four outcome categories: recovered, inconsistent, excluded, or insufficient data. Frozen code and checksums are included.

This design stops goalpost moving. If the new data do not show the dips, he cannot adjust the period to rescue the claim. The supporting records are on Zenodo: the preprint at doi 10.5281/zenodo.22967456, the supporting code and data at doi 10.5281/zenodo.22967099, and the preregistered Sector 110 test at doi 10.5281/zenodo.23175179.

What developers are saying

The story reached Hacker News on October 8. The main thread, about 51 comments when we read it, is worth reading for its skepticism. These are reports of comment content, not verified facts.

• One commenter, soltanov, wrote that peer review must confirm it and called the risk "noise fitting noise."
• Another, wartywhoa23, wrote that they would wait until an astronomy community with more say than r/ClaudeAI acknowledges the planet.
• ContinuityLab asked about the false-positive rate when coding agents work on raw astronomical data, and warned about hallucinated data reduction.
• Commenter amirkhanian suggested controls that do not depend on the model's own report: inject fake planets into real data, run the same pipeline on shuffled data, and give a fresh session only the result and ask it to break it.

That last list is a good practice guide. Rabtsevich's own approach already includes several of those ideas. Read the full discussion on Hacker News.

Practical takeaways for builders

Use the case as a template for AI-assisted science, not as proof that agents "discover planets."

1. Separate generation from verification. Let the agent write search code. Use a different session or model for review. Give the reviewer only outputs.
2. Test the pipeline on known answers. Inject synthetic signals. Confirm the pipeline recovers them. Run it on shuffled data and count false alarms.
3. Hold data out. Predict what a held-out window will show, then check only that window.
4. Preregister the decisive test. Write predictions and outcome rules before new data arrive. Freeze code and publish checksums.
5. Use the right words. Call it a candidate until independent evidence says otherwise.
6. Log what the agent said it did. Scripts, versions and data hashes make the work reproducible. This is the core of good loop engineering with Claude Code.

What this means for AI-for-science work

Two things are true at once. First, a non-specialist with an agent can now run a pipeline that once needed a small team. That is real. Second, agents also make it easy to produce confident, wrong science. Models agree with their own earlier claims. They hide uncertainty. They fit noise.

This story is useful because it shows the second problem handled well. The author reported the alternative explanation, withheld a validation claim, and set up a test that can fail. That is the standard to hold other AI-for-science claims against.

For a wider view, read explainx.ai on Claude for Science, on why AI models hallucinate and how to catch it, and on whether AI flattens scientific discovery. We also covered an earlier case where a viral astronomy claim ran ahead of the evidence: the Harvard exoplanet radio signals story. For another Claude-assisted research harness, see BootLoops.

What to watch next

• Sector 110 data, observed from October 31 to November 26, 2026. If the predicted transits appear at the predicted times and depths, the candidate gains weight.
• Journal review. The preprint targets Research Notes of the AAS. Acceptance is not validation, but it adds expert eyes.
• Imaging and radial velocity follow-up. These would address the unresolved-companion risk.
• Independent reanalysis. The data and code are public. Another team can try to break the result.

If the new data fail to show the signal, the story still has value as a worked example of how to publish a falsifiable claim.

Sources

• Pavel Rabtsevich on X, October 7, 2026
• Preprint on Zenodo: Two Transit-like Signals in TESS Photometry of the Nearby K Dwarf TIC 4206066
• Supporting data and code on Zenodo
• TESS Director's Discretionary Time list, Program 100
• HuggingNews: Claude Code Finds Planet Candidate in 7 Years of NASA Data
• Summary of the work on GitHub Gist (third-party summary)
• Hacker News discussion

Facts reflect the preprint, the TESS DDT list and public reports as of October 9, 2026. The candidate is unconfirmed and may change after follow-up data. Figures such as script counts come from the author's reported account and were not independently audited.