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This research proposes a quantum framework for synchronizing finite state transition systems by leveraging superposition and amplitude amplification to achieve quadratic speedups over classical brute-force methods. By encoding states and inputs into quantum space, the model addresses NP-Hard and PSPACE-Complete complexity classes inherent in traditional resetting sequence problems. The work represents a theoretical advancement in applying quantum algorithms to control theory and system synchronization rather than offering immediate product applications.
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A quantum model for synchronizing finite state transition systems

arXiv3 min read

arXiv:2607.06953v2 Announce Type: replace Abstract: We propose a quantum model for finding a resetting input sequence (RS) which can take a finite state transition system (FA), to particular state independent of its current state. The complexity of finding such sequences for various types of FA can be NP-Hard or even PSPACE-Complete. To this end, we represent the FA states, inputs, and transition function in quantum space. Accordingly, we propose a model to represent the execution of an input sequence of a particular length $l$ starting form an initial FA state. The model is extended considering the application in superposition of all input sequences of length $l$ to an initial state of the FA. The model is further extended considering the application of all input sequences to all initial states of the FA capturing for every input sequence the collection (ordered list) of states reached by applying the sequence to all states of the FA. The amplitude amplification algorithm is then used as it combines similar collections of reached states while preserving all input sequences that reach these collections. A Grover search for a reached collection where its elements correspond to the same FA state provides a RS for the FA. Our approach offers a quadratic gain over the exponential complexity of traditional brute-force method, which is the only method that can be applied to a general FA class.

Abstract:We propose a quantum model for finding a resetting input sequence (RS) which can take a finite state transition system (FA), to particular state independent of its current state. The complexity of finding such sequences for various types of FA can be NP-Hard or even PSPACE-Complete. To this end, we represent the FA states, inputs, and transition function in quantum space. Accordingly, we propose a model to represent the execution of an input sequence of a particular length $l$ starting form an initial FA state. The model is extended considering the application in superposition of all input sequences of length $l$ to an initial state of the FA. The model is further extended considering the application of all input sequences to all initial states of the FA capturing for every input sequence the collection (ordered list) of states reached by applying the sequence to all states of the FA. The amplitude amplification algorithm is then used as it combines similar collections of reached states while preserving all input sequences that reach these collections. A Grover search for a reached collection where its elements correspond to the same FA state provides a RS for the FA. Our approach offers a quadratic gain over the exponential complexity of traditional brute-force method, which is the only method that can be applied to a general FA class.

Quantum Physics (quant-ph); Emerging Technologies (cs.ET)

D.2.5; F.1.1; F.2.1; I.1.2; J.6

arXiv:2607.06953 [quant-ph]

(or arXiv:2607.06953v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2607.06953 Focus to learn more arXiv-issued DOI via DataCite

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Full text under the publisher's open licence · 323 words

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