
I ran a full independent SETI pipeline over Breakthrough Listen's Proxima Centauri data - 6 epochs, 700 MHz, 4.9M raw hits, and what survived
SETI relevance up front (rule 7). This is a narrowband technosignature
search, an independent reanalysis of Breakthrough Listen's public Parkes
archive data for Proxima Centauri.
Not a detection. A clean null result, but the funnel that produced it and
the tooling might interest this sub.
I'm a hobbyist. Over the last few weeks I built an open-source pipeline +
dashboard that works end to end on Breakthrough Listen's public archive:
download (Parkes ON/OFF cadences and GBT ABACAD sessions), turboSETI scans
with configurable drift/SNR, ON/OFF RFI rejection, an automatic per-epoch
RFI zone mapper, barycentric correction, cross-epoch frequency matching,
and incoherent stacking.
The target was Proxima Centauri, six observation epochs from BL's 2017
Parkes campaign, fine-resolution data covering 2.7-3.4 GHz with 3x ON/OFF
cadences per epoch. Closest star, everyone's favorite candidate...
The funnel (all numbers from the final runs)
- Raw turboSETI hits: 4,909,152 (SNR 5+, drift to +/-5 Hz/s)
- ON/OFF rejection kills terrestrial signals present in both pointing
positions: 3,030,707 rejected (61.7%)
- Remaining unique ON frequencies at SNR 8+: 27,533
- Cross-epoch matching at 10 Hz barycentric tolerance, min 3 epochs:
0 frequencies repeat in 3+ epochs
- Final candidates: 0
- Robustness check: relaxing to 2-epoch coincidence at SNR 10 surfaces 7
frequency matches. All 7 fail the OFF veto or report drift rates equal
to the search grid's minimum step, the signature of stationary RFI
rather than a drifting transmitter.
Each epoch was also RFI-zone audited (sliding-window ON-OFF residual vs
the epoch's own noise floor; zones auto-excluded downstream), and the six
epochs were incoherently stacked for sensitivity below single-epoch
threshold. Zero candidates survived the full chain.
Why does a null result matter? It's a constraint, nothing narrowband above
SNR ~8-10 is leaking from Proxima's direction in this band during these six
epochs, verified by an independent implementation with different parameter
choices than BL's published searches. Replication with different tools is
how parameter-choice blind spots get caught. The barycentric matching
is the fun part. Without correction, Earth's orbital motion smears a real
transmitter across tens of kHz between epochs; RFI can't hold a barycentric
frequency across months, so it's the strongest automated filter there is.
The whole thing is open source (MIT, Python, Windows-tested):
https://github.com/w4gon79/backyard-seti
The README walks the full process. Clone to running dashboard to stacked
epochs, both telescopes' data conventions decoded. Work in progress,
but fully usable.
Happy to answer anything about the pipeline, the data handling, or the
funnel numbers.