Formalising the Pathways to Life Using Assembly Spaces.

Assembly theory (referred to in prior works as pathway assembly) has been developed to explore the extrinsic information required to distinguish a given object from a random ensemble. In prior work, we explored the key concepts relating to deconstructing an object into its irreducible parts and then evaluating the minimum number of steps required to rebuild it, allowing for the reuse of constructed sub-objects. We have also explored the application of this approach to molecules, as molecular assembly, and how molecular assembly can be inferred experimentally and used for life detection.

Identifying molecules as biosignatures with assembly theory and mass spectrometry.

The search for alien life is hard because we do not know what signatures are unique to life. We show why complex molecules found in high abundance are universal biosignatures and demonstrate the first intrinsic experimentally tractable measure of molecular complexity, called the molecular assembly index (MA). To do this we calculate the complexity of several million molecules and validate that their complexity can be experimentally determined by mass spectrometry.

Inform: Efficient Information-Theoretic Analysis of Collective Behaviors.

The study of collective behavior has traditionally relied on a variety of different methodological tools ranging from more theoretical methods such as population or game-theoretic models to empirical ones like Monte Carlo or multi-agent simulations. An approach that is increasingly being explored is the use of information theory as a methodological framework to study the flow of information and the statistical properties of collectives of interacting agents. While a few general purpose toolkits exist, most of the existing software for information theoretic analysis of collective systems is limited in scope.