Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 2610.04449

The Robots are Coming: Artificial Intelligence Searching for Extraterrestrial Intelligence

Steve Croft
View original source ↗Read source document ↗Export metadata ↓

Abstract

Breakthrough Listen, humanity's most ambitious search for technosignatures, or evidence of extraterrestrial technology, is carrying out surveys across the sky and across the electromagnetic spectrum, in images, spectra, time series, catalogs, and alerts. Classical techniques still play a major role in the search, but the recent rapid growth in the capabilities of artificial intelligence is enabling new and more powerful algorithms and approaches to be deployed across enormous datasets. Surveys designed to look for technosignatures are still a major focus for the Breakthrough Listen program, but excitingly, the new strategies also enable comprehensive mining of archives and of general-purpose real-time data streams. We outline how artificial intelligence and machine learning are being used to scale up the search, including with the newly-commissioned Vera C. Rubin Observatory, in addition to radio telescopes around the planet. The chances of a detection have never been better.

Explore related subjects

astro-ph.IM

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Steve Croft. 2026-10-03. The Robots are Coming: Artificial Intelligence Searching for Extraterrestrial Intelligence. https://arxiv.org/abs/2610.04449

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

A Covariance-Aware Framework for Spatially Resolved Exoplanet Biosignature Inference with the Solar Gravitational Lens

Assessing possible life on an exoplanet requires spatial, spectral, temporal, and environmental context rather than a threshold detection of one molecule or surface feature. We develop a covariance-aware Solar Gravitational Lens (SGL) framework in which the data product is a time-tagged Stokes spectral cube reconstructed from wavelength-dependent Einstein-ring measurements. The demonstrated calculation is a 0.45-2.40 um Stokes-I reflected-light simulation of an Earth-radius planet at 30 pc, observed from 650 AU with a (128 x 128) raster, 128 simultaneous spectral channels, and $R\simeq70$. A separate 0.40-20 um architecture-level calculation tracks reflected and thermal planet photons, SGL gain, solar-corona noise, instrumental backgrounds, throughput, dwell time, and reconstruction covariance. In the controlled population audit, structural forward-model mismatch preserves the block ordering gas > surface > cloud/path > mineral > calibration/SGL while reducing the combined conditional information gain to 0.83 of the matched-model value. A reconstruction-covariance bracket reduces an (8 x 8) regional coadd gain from 7.77 to 3.00, implying a 6.7-fold dwell penalty. The feasibility results are design scalings, not a mission verdict: imaging and low-resolution mapping are earlier objectives, whereas full regional spectroscopy requires simultaneous acquisition, sub-ppm effective coronal calibration, measured reconstruction covariance, and branch-specific radiometric validation. We show that the SGL offers a uniquely powerful path to surface-resolved mapping, regional spectroscopy, thermal-climate diagnostics, and co-location tests, providing spatial, spectral, temporal, and environmental context that could strengthen assessments of habitability and possible biological activity beyond disk-integrated precursor observations.

astro-ph.IM↗
arXiv2026

Eclipses by Artificial Satellites to Measure the Angular Sizes of Stars

Direct measurements of the angular sizes of stars (other than our Sun) are inherently limited by telescopes' optical diffraction limit. The spatial diffraction limit can be overcome by using time-domain information when stars are `eclipsed' by anything moving in the foreground: artificial satellites or the Moon (known as `lunar occultation imaging'). Here we analyse the angular resolution achievable by high-speed photon counting devices, when stars are eclipsed for several microseconds by one of the thousands of satellites now in low or mid-Earth orbit. We also build a full Bayesian statistical treatment for analysing simulated observations. We show that eclipses by the moon and satellites deliver $<2$ milliarcsecond resolution for $\sim$$10^4$ stars every year, with the diameters of $\sim$$10^1 - 10^2$ stars constrained to better than $0.5$ milliarcseconds. The application of satellites requires an ultra-fast, photon-resolving detector, capable of continuous readout with inter-frame delay controlled within $\lesssim 1$ $μ$s. Such a fast rate can easily be handled by the SPINA instrument, which has demonstrated $8$ ns inter-frame delay, and potentially by the Cherenkov Telescope Array.

astro-ph.IM↗
arXiv2026

Constrained Diffusion for Data-Scarce Orbital Monte Carlo in Constellation Tasking

Constellation Monte Carlo results depend on the orbital population used to evaluate a tasking policy. With scarce reference trajectories, replay limits geometric diversity, while independent orbital-element jitter can violate physical constraints. We study constrained diffusion for orbital-population augmentation. A force-conditioned diffusion model learns a 13-dimensional orbital prior, recovering semimajor axis from perigee altitude and eccentricity; Basilisk propagates each sample under one of five force-model tiers. Using 800 reference trajectories, we compare diffusion with jittered bootstrap, per-tier Gaussian mixtures, and a conditional variational autoencoder, and evaluate distributional fidelity, support shift, classical astrodynamics diagnostics, and 4,000 paired GoDSAT-compatible campaigns. The largest diffusion model achieves held-out trajectory MMD of 0.0171 +/- 0.0239, similar to bootstrap (0.0170) and the mixture (0.0198), but samples farther from training priors (median nearest-training distance 2.7 versus 0.10 standardized units). All generators fail to match the shifted-blind population (classifier AUC 0.991-0.998). Endpoint-conditioned samples satisfy Lambert boundaries but have greater interior error than the matched Lambert reference (29.2 versus 5.7 km mean RMSE). Residual diffusion improves selected sparse forecasts and catalog-mode recall but does not outperform classical estimators on custody ranking. In a fixed 16-satellite configuration, diffusion yields similar mean custody to replay and bootstrap, while the force-tier mixture shifts custody by about 5.5 percentage points. Constrained diffusion supports local, in-support augmentation but cannot replace orbital dynamics or serve as an operational posterior. Orbital-population construction is a consequential source of uncertainty in constellation analysis.

astro-ph.IM↗