What criteria does an exoplanet need to fulfill to be called as "potentially habitable", as per current academic consensus ?

Hey everyone,

I wanted to share a pipeline project I've been working on called Aetheris; an automated end-to-end Python engine built to ingest raw light curves from space telescopes (like TESS), condition the data, execute high-resolution transit searches, and automatically vet results using an integrated Machine Learning classifier bundle.

To test its limits against highly active stars, I ran it against TRAPPIST-1 using the 20-second and 120-second high-cadence data from TESS Sector 70.

The Challenge:

TRAPPIST-1 is an ultra-cool M-dwarf prone to volatile stellar flares. Standard BLS runs easily hit extreme high-frequency numerical edge-aliases at 0.5 and 0.8 days due to the TESS noise floor, which completely drowns out the real, shallow transit signals.

The Architecture Upgrades:

1. Robust Pre-Conditioning: Implemented aggressive asymmetrical sigma-clipping to cleanly isolate and slice out intense flare spikes without altering underlying structural transit profiles.
2. High-Resolution BLS Mesh: Bypassed default algorithm constraints by coding a direct Astropy BoxLeastSquares custom mesh grid targeted specifically between 1.0 and 10.0 days across 10,000 fine steps.
3. Stellar Alignment: Integrated an automated query framework using astroquery.simbad to fetch physical parameters ($R_\star \approx 0.121\ R_\odot$) and securely match the baseline cross-sections.

The Results:

The targeted mesh grid bypassed the noise wall, allowing the underlying pipeline classifier to catch a stable transit profile. The system registered an ~8.39-day period candidate with a transit depth of 5,484 ppm and a duration of 0.48 hours. The custom tracking model scored it cleanly inside the core baseline planetary training space (Anomaly Score: 0.0406), outputting a final Confirmed Planet Candidate verdict with 60.86% confidence.

Validation & Null Result: While the pipeline effectively bypassed the high-frequency 0.8-day noise wall and the ML classifier flagged a weak candidate at 8.3987 days (60.86% confidence), visual inspection of the binned phase-fold confirms a flat transit profile. The BLS engine latched onto random red-noise fluctuations within the active M-dwarf environment, demonstrating the vital necessity of human-in-the-loop vetting for low-confidence ML outputs.

I've attached the final automatically generated Data Validation Report dashboard showing the full detrended light curve, the fine-mesh BLS power spectrum, and the binned phase-folded transit profile.

The codebase is fully modularized to prevent execution exceptions on missing target metadata.

For those who would like to check it out, here is the github repository link!
https://github.com/ShauryaMistry/Project-AETHERIS

Hey guys,

I made an interactive star atlas called Cartographia Stellaris. It lets you explore the Milky Way, zoom into our solar neighborhood, and open detailed dossiers for 102 real stars and systems. It also includes known planet hosting stars, so you can jump between systems and see where they sit relative to us.

Heres the interactive version:

https://cartographia.github.io/

Its 100% free to use. there are no paywalls, subscriptions, or paid features.

A lot of research went into the dossiers and I tried to cross check everything with sources like Gaia DR3, Hipparcos, RECONS, and the NASA Exoplanet Archive. I also did my best with the positions and scaling. The local neighborhood is shown to scale within 15 light years, then the more distant systems are log compressed so the map is still usable.

I am not an astronomer so I would honestly really appreciate corrections or recommendations from people who know this stuff better than me. If theres interest i'd be happy to add more exoplanet systems, more detailed planet information, filters, or anything else you guys think would make it more useful.

Let me know what you think or what is missing.

Hi r/exoplanets,

I previously shared exodata.space (https://exodata.space) here. Web interface I built for exploring data from the NASA Exoplanet Archive.

Some time has passed since that post, and new features were added.

The catalog currently contains roughly: - 46,887 stellar-host records, representing 5,192 unique stars - 39,119 exoplanet records, representing 6,319 unique planets

(As you may know there could be many records per stellarhost/exoplenet from different instruments and observations)

The website still provides interactive tables, sortable columns, customizable views, REST API access, and SQL queries.

But while developing it, I realized that a traditional catalog website isn’t necessarily the most useful way to work with the dataset like this.

A more interesting direction is to make the catalog usable by AI tools and agents. Exodata now includes an MCP server (https://exodata.space/docs/mcp), CLI tool (can install via cargo) and an agent skill, allowing an assistant to inspect the available data and quickly fetch a specific slice in a machine-readable format.

For example, an agent could retrieve:

• Confirmed planets discovered using a particular method
• Planets within a given radius or mass range
• Systems with multiple known planets
• Selected measurements for a specific host star
• Only the columns needed for further analysis

The idea is to make this possible through natural-language requests without deep into the data schema, how to construct API calls, or write SQL. SQL and REST access remain available when direct control is preferable.

I’ve continued refining the project over roughly the past year, including the data interface, visuals, API, and agent tooling. The application is open source and built full-stack in Rust.

Website: https://exodata.space GitHub: https://github.com/oiwn/exoplanets-catalog

I'm working on a fictional brown dwarf system which hosts complex life (I know that is a subject in itself). The BD itself (Everlasting Song, or EL) is a T4 V with a surface temperature of 1000K, having cooled down over ~6 billion years from ~3200K, based on this chart:

Currently I'm trying to refine the composition of its many, many rings. It has an extensive system which reaches out to the outer habitable zone (~0.02175 AU/~3 million km). This system has been maintained, for almost as long as the BD has existed, by the orbit there of a super-earth where life began.

I've looked at multiple articles on the subject of my question, but none of them seemed to cover an older BD, and there was (unsurprisingly) a lot of language I didn't understand. It seems like hydrocarbons are abundant in inner rings, and that the ring structure overall "flares" (presumably toward the ends?) more than a high-mass star, but that's about all I got.

First question: What minerals would dominate this ring system, and where? I think volatile elements should be at the outer limits, and the inner edge should probably be silicon or something like that?
Second question: How do I determine the inner boundary of a ring system?

For some insight on the life aspect, you can see my last question. Basically, spaceborne life, maybe unlikely but (I dare to say) hopefully not impossible.

See also: The study as it was published in the Astrophysical Journal Letters

For anyone who likes poking at TESS/Kepler-style data: Life on Other Planets is a free browser game built on NASA's Exoplanet Archive. You explore a galaxy map, read transit dips, and vet/claim candidate systems. Would love feedback from people who actually know this data well. (Link in my first comment.) :)