ITAIMar 28, 2023

An Optimal, Universal and Agnostic Decoding Method for Message Reconstruction, Bio and Technosignature Detection

arXiv:2303.16045v44 citationsh-index: 33
Originality Incremental advance
AI Analysis

This addresses the challenge of interpreting messages from unknown sources in fields like astrobiology and communication theory, though it appears incremental as it builds on existing reconstruction concepts with a focus on agnosticism.

The paper tackles the problem of reconstructing messages from unknown sources in zero-knowledge one-way communication channels, presenting an agnostic method that does not rely on prior knowledge of encoding schemes or observer-dependent characteristics, with applications demonstrated in image data for life and technosignature detection and coding theory.

We present an agnostic signal reconstruction method for zero-knowledge one-way communication channels in which a receiver aims to interpret a message sent by an unknown source about which no prior knowledge is available and to which no return message can be sent. Our reconstruction method is agnostic vis-à-vis the arbitrarily chosen encoding-decoding scheme and other observer-dependent characteristics, such as the arbitrarily chosen computational model, probability distributions, or underlying mathematical theory. We investigate how non-random messages encode information about their intended physical properties, such as dimension and length scales of the space in which a signal or message may have been originally encoded, embedded, or generated. We focus on image data as a first illustration of the capabilities of the new method. We argue that our results have applications to life and technosignature detection, and to coding theory in general.

Foundations

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