Quantum hidden Markov models are shown to be identifiable via a finite set of word probabilities, and the minimal quantum memory dimension is proved to be at least the square root of the minimal generalized hidden Markov model dimension.
Energetic advantages for quantum agents in online execution of complex strategies
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abstract
Agents often execute complex strategies -- adapting their response to each input stimulus depending on past observations and actions. Here, we derive the minimal energetic cost for classical agents to execute a given strategy, highlighting that they must dissipate a certain amount of heat with each decision beyond Landauer's limit. We then prove that quantum agents can reduce this dissipation below classical limits. We establish the necessary and sufficient conditions for a strategy to guarantee quantum agents have energetic advantage, and illustrate settings where this advantage grows without bound. Our results establish a fundamental energetic advantage for agents utilizing quantum processing to enact complex adaptive behaviour.
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quant-ph 1years
2025 1verdicts
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Identifiability and minimality bounds of quantum and post-quantum models of classical stochastic processes
Quantum hidden Markov models are shown to be identifiable via a finite set of word probabilities, and the minimal quantum memory dimension is proved to be at least the square root of the minimal generalized hidden Markov model dimension.