Project AETHERIS (v5.0)

Astrophysical Exoplanet Transit Heuristic Engine for Rapid Injection and Screening

Project AETHERIS is an automated, high-performance Python pipeline built to stream, clean, and analyze stellar light curves for exoplanetary transits using dynamic multi-threaded hardware acceleration. It is engineered specifically to eliminate sequential bottlenecks when processing massive amounts of raw stellar time-series data.

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🚀 Core Features

• Automated MAST Queries: Directly interfaces with the Mikulski Archive for Space Telescopes to safely fetch and stitch raw SPOC data sectors.
• Hardware-Aware Parallelism: Dynamically profiles host CPU capacity and scales background worker processes to maximize local or cloud hardware utilization.
• Content-Aware Noise Removal: Automatically calculates light curve variance metrics to intelligently compute optimal flattening windows, protecting shallow transits while removing stellar noise.
• Automated TOI Vetting System: Runs high-density Box Least Squares (BLS) periodogram arrays to extract transit periods, calculating Signal-to-Noise Ratios (SNR) and secondary depths to automatically isolate astronomical false positives.

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📊 Target Analysis Case Study: TIC 350618622

During pipeline validation testing on cloud server architectures, AETHERIS executed a comprehensive vetting run across a target array compiled from 62 raw historical sectors, utilizing a downsampled 3-sector baseline window.

🔍 System Metric Readings

• Recovered Signal Period: 28.46755 Days
• Signal-to-Noise Ratio (SNR): 15.01
• Derived Physical Radius: 3.75 R_Earth (Super-Earth / Sub-Neptune Profile)
• Odd/Even Depth Delta: 100.63%
• Final Preliminary Disposition: FALSE_POSITIVE

📝 Vetting Interpretation & Diagnostics

While a calculated radius of $3.75\ R_\oplus$ would initially suggest an exciting sub-Neptune candidate planet, the engine's automated phase-folding module identified a critical geometric indicator: an Odd/Even Depth Delta of 100.63%.

A depth mismatch of this magnitude reveals that alternating primary and secondary occultation depths are deeply uneven. This mathematically confirms that the transit profile is being generated by a grazing eclipsing binary star system rather than a genuine planetary body passing in front of a host star, showcasing the engine's ability to cleanly screen out false positives without manual intervention.

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💻 Sample Execution Log

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PROJECT AETHERIS V5 // FLAT DIRECTORY INJECTION ENGINE
Target Objective: TIC 350618622
[SYSTEM PROFILE] Host hardware detected: 4 Cores. Allocating 3 workers.
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[STAGE 1] Querying NASA MAST Archive for unrefined SPOC sectors...
[OPTIMIZE] Target has 62 sectors. Slicing most recent 3 baseline windows...
[STAGE 2] Streaming most recent target sectors (Max Timeout: 120s)...
[SUCCESS] Successfully secured and stitching 3 target data streams...
[STAGE 3] Computing variance metrics for content-aware flattening...
[SUCCESS] Cadence profiled at 2.00 mins. Tuning filter window length to: 1799
[STAGE 4] Launching multi-threaded BLS Comb Engine (10,000 Step Array)...
[PERFORMANCE LOG] Array processed via Parallel Acceleration [Active Workers: 3] in 9.82s.

[REPORT] --- AUTOMATED TOI VETTING ANALYSIS REPORT ---
-> Recovered Signal Period : 28.46755 Days
-> Signal-to-Noise (SNR)  : 15.01
-> Derived Physical Radius : 3.75 R_Earth
-> Odd/Even Depth Delta   : 100.63%
-> PRELIMINARY DISPOSITION : FALSE_POSITIVE
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[SUCCESS] Flat file compilation completed inside directory: System_TIC_350618622/
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Place your target files alongside the primary engine file and execute:

Bash
python3 ProjectAetheris.py