“Energy-Efficient Algorithms”, Erik D. Demaine, Jayson Lynch, Geronimo J. Mirano, Nirvan Tyagi2016-05-26 (information theory; similar)⁠:

We initiate the systematic study of the energy complexity of algorithms (in addition to time and space complexity) based on Landauer’s Principle in physics, which gives a lower bound on the amount of energy a system must dissipate if it destroys information.

We propose energy-aware variations of 3 standard models of computation: circuit RAM, word RAM, and transdichotomous RAM. On top of these models, we build familiar high-level primitives such as control logic, memory allocation, and garbage collection with zero energy complexity and only constant-factor overheads in space and time complexity, enabling simple expression of energy-efficient algorithms.

We analyze several classic algorithms in our models and develop low-energy variations: comparison sort, insertion sort, counting sort, breadth-first search, Bellman-Ford, Floyd-Warshall, matrix all-pairs shortest paths, AVL trees, binary heaps, and dynamic arrays. We explore the time/space/energy trade-off and develop several general techniques for analyzing algorithms and reducing their energy complexity.

These results lay a theoretical foundation for a new field of semi-reversible computing and provide a new framework for the investigation of algorithms.

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