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Breakthrough Listen is the most comprehensive and sensitive search for extraterrestrial intelligence (SETI) to date, employing a collection of international observational facilities including both radio and optical telescopes. During the first three years of the Listen program, thousands of targets have been observed with the Green Bank Telescope (GBT), Parkes Telescope and Automated Planet Finder. At GBT and Parkes, observations have been performed ranging from 700 MHz to 26 GHz, with raw data volumes averaging over 1 PB day−1. A pseudo-real time software spectroscopy suite is used to produce multi-resolution spectrograms amounting to approximately 400 GB h−1 GHz−1 beam−1. For certain targets, raw baseband voltage data is also preserved. Observations with the Automated Planet Finder produce both two-dimensional and one-dimensional high-resolution (R ∼ 105) echelle spectral data. Although the primary purpose of Listen data acquisition is for SETI, a range of secondary science has also been performed with these data, including studies of fast radio bursts. Other current and potential research topics include spectral line studies, searches for certain kinds of dark matter, probes of interstellar scattering, pulsar searches, radio transient searches and investigations of stellar activity. Listen data are also being used in the development of algorithms, including machine-learning approaches to modulation scheme classification and outlier detection, that have wide applicability not just for astronomical research but for a broad range of science and engineering. In this paper, we describe the hardware and software pipeline used for collection, reduction, archival, and public dissemination of Listen data. We describe the data formats and tools, and present Breakthrough Listen Data Release 1.0 (BLDR 1.0), a defined set of publicly available raw and reduced data totaling 1 PB.

The Breakthrough Listen Initiative is undertaking a comprehensive search for radio and optical signatures from extraterrestrial civilizations. An integral component of the project is the design and implementation of wide-bandwidth data recorder and signal processing systems. The capabilities of these systems, particularly at radio frequencies, directly determine survey speed; further, given a fixed observing time and spectral coverage, they determine sensitivity as well. Here, we detail the Breakthrough Listen wide-bandwidth data recording system deployed at the 100 m aperture Robert C. Byrd Green Bank Telescope. The system digitizes up to 6 GHz of bandwidth at 8 bits for both polarizations, storing the resultant 24 GB s−1 of data to disk. This system is among the highest data rate baseband recording systems in use in radio astronomy. A future system expansion will double recording capacity, to achieve a total Nyquist bandwidth of 12 GHz in two polarizations. In this paper, we present details of the system architecture, along with salient configuration and disk-write optimizations used to achieve high-throughput data capture on commodity compute servers and consumer-class hard disk drives.

New radio telescope arrays offer unique opportunities for large-scale commensal SETI surveys. Ethernet-based architectures are allowing multiple users to access telescope data simultaneously by means of multicast Ethernet subscriptions. Breakthrough Listen will take advantage of this by conducting a commensal SETI survey on the MeerKAT radio telescope in South Africa. By subscribing to raw voltage data streams, Breakthrough Listen will be able to beamform commensally anywhere within the field of view during primary science observations. The survey will be conducted with unprecedented speed by forming and processing 64 coherent beams simultaneously, allowing the observation of several million objects within a few years. Both coherent and incoherent observing modes are planned. We present the list of desired sources for observation and explain how these sources were selected from the Gaia DR2 catalog. Given observations planned by MeerKAT’s primary telescope users, we discuss their effects on the commensal survey and propose a commensal observing strategy in response. Finally, we outline our proposed approach toward observing one million nearby stars and analyze expected observing progress in the coming years.

As it stands today, the search for extraterrestrial intelligence is highly dependent on our ability to detect interesting candidate signals, or technosignatures, in radio telescope observations and distinguish these from human radio frequency interference (RFI). Current signal search pipelines look for signals in spectrograms of intensity as a function of time and frequency (which can be thought of as images), but tend to do poorly in identifying multiple signals in a single data frame. This is especially apparent when there are dim signals in the same frame as bright, high signal-to-noise ratio (S/N) signals. In this work, we approach this problem using convolutional neural networks (CNN) as a computationally efficient method for localizing signals in synthetic observations resembling data collected by Breakthrough Listen using the Green Bank Telescope. We generate two synthetic data sets, the first with exactly one signal at various S/N levels and the second with exactly two signals, one of which represents RFI. We find that a residual CNN with strided convolutions and using multiple image normalizations as input outperforms a more basic CNN with max pooling trained on inputs with only one normalization. Training each model on a smaller subset of the training data at higher S/N levels results in a significant increase in model performance, reducing root mean square errors by at least a factor of 3 at an S/N of 25 dB. Although each model produces outliers with significant error, these results demonstrate that using CNNs to analyze signal location is promising, especially in image frames that are crowded with multiple signals.

The goal of the search for extraterrestrial intelligence (SETI) is to quantify the prevalence of technological life beyond Earth via their ‘technosignatures’. One theorized technosignature is narrowband Doppler drifting radio signals. The principal challenge in conducting SETI in the radio domain is developing a generalized technique to reject human radiofrequency interference. Here we present a comprehensive deep-learning-based technosignature search on 820 stellar targets from the Hipparcos catalogue, totalling over 480 h of on-sky data taken with the Robert C. Byrd Green Bank Telescope as part of the Breakthrough Listen initiative. We implement a novel β-convolutional variational autoencoder to identify technosignature candidates in a semi-unsupervised manner while keeping the false-positive rate manageably low, reducing the number of candidate signals by approximately two orders of magnitude compared with previous analyses on the same dataset. Our work also returned eight promising extraterrestrial intelligence signals of interest not previously identified. Re-observations on these targets have so far not resulted in re-detections of signals with similar morphology. This machine-learning approach presents itself as a leading solution in accelerating SETI and other transient research into the age of data-driven astronomy.A state-of-the-art machine-learning method combs a 480-h-long dataset of 820 nearby stars from the SETI Breakthrough Listen project, reducing the number of interesting signals by two orders of magnitude. Further visual inspection identifies eight promising signals of interest from different stars that warrant further observations.

The aim of the search for extraterrestrial intelligence (SETI) is to find technologically capable life beyond Earth through their technosignatures. On 2019 April 29, the Breakthrough Listen SETI project observed Proxima Centauri with the Parkes ‘Murriyang’ radio telescope. These data contained a narrowband signal with characteristics broadly consistent with a technosignature near 982 MHz (‘blc1’). Here we present a procedure for the analysis of potential technosignatures, in the context of the ubiquity of human-generated radio interference, which we apply to blc1. Using this procedure, we find that blc1 is not an extraterrestrial technosignature, but rather an electronically drifting intermodulation product of local, time-varying interferers aligned with the observing cadence. We find dozens of instances of radio interference with similar morphologies to blc1 at frequencies harmonically related to common clock oscillators. These complex intermodulation products highlight the necessity for detailed follow-up of any signal of interest using a procedure such as the one outlined in this work. A radio signal detected in the direction of Proxima Centauri in a Breakthrough Listen programme is analysed for signs that it was transmitted by extraterrestrial intelligent life, using a newly developed framework. However, the signal ‘blc1’ is likely to be terrestrial radio-frequency interference.

The detection of life beyond Earth is an ongoing scientific pursuit, with profound implications. One approach, known as the search for extraterrestrial intelligence (SETI), seeks to find engineered signals (‘technosignatures’) that indicate the existence of technologically capable life beyond Earth. Here, we report on the detection of a narrowband signal of interest at ~982 MHz, recorded during observations towards Proxima Centauri with the Parkes Murriyang radio telescope. This signal, BLC1, has characteristics broadly consistent with hypothesized technosignatures and is one of the most compelling candidates to date. Analysis of BLC1—which we ultimately attribute to being an unusual but locally generated form of interference—is provided in a companion paper. Nevertheless, our observations of Proxima Centauri are a particularly sensitive search for radio technosignatures towards a stellar target. A sensitive Breakthrough Listen search for technosignatures towards Proxima Centauri has resulted in a viable narrowband signal. The observational approach, using the Parkes Murriyang telescope, is described here, while the signal of interest is analysed in a companion paper by Sheikh et al.

We undertook observations with the Green Bank Telescope, simultaneously with the 300 m telescope in Arecibo, as a follow-up of a possible flare of radio emission from Ross 128. We report here the non-detections from the GBT observations in C band (4–8 GHz), as well as non-detections in archival data at L band (1.1–1.9 GHz). We suggest that a likely scenario is that the emission comes from one or more satellites passing through the same region of the sky.

Radio searches for extraterrestrial intelligence have mainly targeted the discovery of narrowband continuous-wave beacons and artificially dispersed broadband bursts. Periodic pulse trains, in comparison to the above technosignature morphologies, offer an energetically efficient means of interstellar transmission. A rotating beacon at the Galactic Center (GC), in particular, would be highly advantageous for galaxy-wide communications. Here, we present blipss, a CPU-based open-source software that uses a fast folding algorithm (FFA) to uncover channel-wide periodic signals in radio dynamic spectra. Running blipss on 4.5 hours of 4-8 GHz data gathered with the Robert C. Byrd Green Bank Telescope, we searched the central 6' of our Galaxy for kHz-wide signals with periods between 11-100 s and duty cycles (\\(\\delta\\)) between 10-50%. Our searches, to our knowledge, constitute the first FFA exploration for periodic alien technosignatures. We report a non-detection of channel-wide periodic signals in our data. Thus, we constrain the abundance of 4-8 GHz extraterrestrial transmitters of kHz-wide periodic pulsed signals to fewer than one in about 600,000 stars at the GC above a 7\\(\\sigma\\) equivalent isotropic radiated power of \\(\\approx 2 \\times 10^{18}\\) W at \\(\\delta \\simeq 10\\%\\). From an astrophysics standpoint, blipss, with its utilization of a per-channel FFA, can enable the discovery of signals with exotic radio frequency sweeps departing from the standard cold plasma dispersion law.

New radio telescope arrays offer unique opportunities for large-scale commensal SETI surveys. Ethernet-based architectures are allowing multiple users to access telescope data simultaneously by means of multicast Ethernet subscriptions. Breakthrough Listen will take advantage of this by conducting a commensal SETI survey on the MeerKAT radio telescope in South Africa. By subscribing to raw voltage data streams, Breakthrough Listen will be able to beamform commensally anywhere within the field of view during primary science observations. The survey will be conducted with unprecedented speed by forming and processing 64 coherent beams simultaneously, allowing the observation of several million objects within a few years. Both coherent and incoherent observing modes are planned. We present the list of desired sources for observation and explain how these sources were selected from the Gaia DR2 catalog. Given observations planned by MeerKAT’s primary telescope users, we discuss their effects on the commensal survey and propose a commensal observing strategy in response. Finally, we outline our proposed approach toward observing one million nearby stars and analyze expected observing progress in the coming years.