Data-Driven Approaches to Searches for the Technosignatures of Advanced Civilizations

Abstract

Humanity has wondered whether we are alone and about the existence of “others” for millennia. The discovery of life elsewhere in the Universe, particularly intelligent life, would have profound scientific, cultural, and societal effects, comparable to those of recognizing that the Earth is not the center of the Universe and that humans (Homo sapiens) evolved from previous species. The past two decades have witnessed rapid growths in both the fields of extrasolar planets and data-driven astronomy. In a relatively short interval, we have seen a change from knowing of no extrasolar planets to now knowing far more potentially habitable extrasolar planets than there are planets in the Solar System. In approximately the same interval, astronomy has transitioned from a relatively data-starved field into one in which extensive sky surveys can generate 1 quadrillion bytes (= 10¹⁵B = 1PB) or more of data. The Data-Driven Approaches to Searches for the Technosignatures of Advanced Civilizations study at the W. M. Keck Institute for Space Studies was intended to revisit searches for evidence of alien technologies in light of these two developments. Experts from around the world, in a variety of disciplines, gathered for a week to assess what new kinds of searches might be able to be undertaken. Of particular value for the search for technosignatures is that a data-driven approach may be able to mitigate biases, particularly unknown ones. Data-driven searches, being able to process volumes of data much greater than a human could, and in a reproducible manner, can identify anomalies—data that are inconsistent with a larger sample—that could be clues to the presence of technosignatures. While the focus of the study was identifying technosignatures from other civilizations, it was recognized that there are other intelligent species on this planet, even if they do not employ technologies capable of being detected over interstellar distances. Learning from how various species have interacted, or coopted interactions, may provide clues for how to search for extraterrestrial intelligent species. Even more tantalizing would be if universal rules for communication among terrestrial species were to be identified. A key outcome of this workshop was that technosignature searches should be conducted in a manner consistent with Freeman Dyson’s “First Law of SETI Investigations,” namely “every search for alien civilizations should be planned to give interesting results even when no aliens are discovered.” This approach to technosignature searches is commensurate with NASA’s approach to biosignatures in that no single observation or measurement can be taken as providing full certainty for the detection of life. There was broad agreement at the workshop that a variety of machine learning techniques could be of value in searching large data volumes. These techniques range from extensions to the classic matched filtering techniques to techniques in which the members of a data set can be organized into groups based solely on the characteristics of the individual members. These machine learning techniques already are being applied, with increasing success, to a variety of problems in astronomy and other fields. Consequently, machine learning techniques present powerful tools for identifying anomalies in data. Areas of particular promise identified during the workshop were the following: Data Mining of Large Sky Surveys Various large sky surveys are in the process of being conducted or will initiate in the next decade. Not only will these surveys be conducted at a variety of wavelengths, many of them are introducing a time domain aspect, enabling rich multi-parameter searches for anomalies to be conducted. All-Sky Survey at Far-Infrared Wavelengths No technology can be perfectly efficient, because of the Second Law of Thermodynamics. Any technology using substantial amounts of energy therefore will radiate some fraction of that energy as “waste heat,” likely to