Documentation

Welcome to LARUN.SPACE documentation. This guide covers everything you need to know to discover exoplanets using our AI-powered detection system.

Quick Start

The fastest way to get started is through our chat interface. Simply navigate to the app and start asking questions.

Example: Search for Transits

Type in the chat:

Search for transits in TIC 307210830

LARUN will automatically fetch the light curve from NASA TESS, run TinyML detection, and present you with the results.

Authentication

Free tier users can analyze up to 10 targets per month without authentication. For unlimited access and API usage, create an account and subscribe to a paid plan.

API Authentication

For programmatic access, include your API key in the request header:

Authorization: Bearer YOUR_API_KEY

Chat Basics

The chat interface understands natural language queries about exoplanet detection. You can ask about specific targets, request analyses, or explore astronomical concepts.

Supported Query Types

Target Search: "Search for transits in TIC 123456789"
Analysis: "Run BLS periodogram on Kepler-11"
Habitability: "Is this planet in the habitable zone?"
Reports: "Generate a report for my candidate"

Example Queries

Finding Transits

Search for transits in TIC 307210830
Analyze light curve for TOI-700
Look for periodic dips in KIC 8462852

Parameter Fitting

Fit transit parameters for my candidate
What is the orbital period?
Estimate the planet radius

Habitable Zone Analysis

Is TOI-700 d in the habitable zone?
Check habitability for my candidate
What is the equilibrium temperature?

File Uploads

You can upload your own light curve data for analysis. Supported formats:

FITS: Standard astronomical data format
CSV: Comma-separated values with time and flux columns
TXT: Space-separated text files

CSV Format

time,flux,flux_err
0.0,1.0001,0.0001
0.1,0.9998,0.0001
0.2,1.0002,0.0001
...

API Overview

The LARUN API provides programmatic access to all detection and analysis features. Base URL: https://api.larun.space/v1

BLS Analysis

POST /analyze/bls

Run Box Least Squares periodogram analysis to detect transit signals.

Parameters

Name	Type	Description
tic_id required	string	TIC identifier (e.g., "307210830")
period_min	float	Minimum period to search (days). Default: 0.5
period_max	float	Maximum period to search (days). Default: 15.0

Example Request

curl -X POST https://api.larun.space/v1/analyze/bls \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "tic_id": "307210830",
    "period_min": 0.5,
    "period_max": 15.0
  }'

Response

{
  "status": "success",
  "period": 3.4254,
  "period_err": 0.0012,
  "t0": 2458765.432,
  "depth": 0.0023,
  "duration": 2.5,
  "snr": 12.4,
  "is_candidate": true
}

Transit Fitting

POST /analyze/fit

Fit transit model to derive planetary parameters.

Name	Type	Description
tic_id required	string	TIC identifier
period required	float	Orbital period in days
t0 required	float	Transit mid-time (BJD)

Star Classification

POST /stellar/classify

Classify the host star and retrieve stellar parameters.

Name	Type	Description
tic_id required	string	TIC identifier

Habitable Zone

POST /planet/hz

Check if a planet candidate is within the habitable zone.

Name	Type	Description
stellar_teff required	float	Stellar effective temperature (K)
stellar_luminosity required	float	Stellar luminosity (solar units)
semi_major_axis required	float	Planet semi-major axis (AU)

Full Pipeline

POST /pipeline

Run the complete exoplanet detection and characterization pipeline.

Name	Type	Description
tic_id required	string	TIC identifier
full_report	boolean	Generate full PDF report. Default: false

Data Sources

LARUN.SPACE uses data from the following NASA missions:

TESS: Transiting Exoplanet Survey Satellite
Kepler: Kepler Space Telescope (Scientist tier)
JWST: James Webb Space Telescope spectroscopy (Scientist tier)

Limitations

TinyML detection accuracy: 81.8% (may produce false positives)
Period search range: 0.5 - 15 days (configurable)
Minimum transit depth: ~0.1% (depends on stellar noise)
API rate limits apply based on subscription tier

FAQ

What is TinyML detection?

TinyML is a machine learning approach optimized for edge devices. Our neural network can identify transit signals in light curves with 81.8% accuracy while running efficiently in the browser.

Can I discover real exoplanets?

Yes! Many exoplanet candidates are discovered by citizen scientists. If LARUN identifies a promising candidate, you can submit it to professional follow-up programs like TFOP (TESS Follow-up Observing Program).

How do I report a bug?

Please open an issue on our GitHub repository or contact support at support@larun.space.