Time complexity of a monitored quantum search with resetting

Fuente: arXiv
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Main Authors: King, Emma C., Roy, Sayan, Mattiotti, Francesco, Kiefer-Emmanouilidis, Maximilian, Bläser, Markus, Morigi, Giovanna
Format: Preprint
Published: 2026
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author King, Emma C.
Roy, Sayan
Mattiotti, Francesco
Kiefer-Emmanouilidis, Maximilian
Bläser, Markus
Morigi, Giovanna
author_facet King, Emma C.
Roy, Sayan
Mattiotti, Francesco
Kiefer-Emmanouilidis, Maximilian
Bläser, Markus
Morigi, Giovanna
contents Searching a database is a central task in computer science and is paradigmatic of transport and optimization problems in physics. For an unstructured search, Grover's algorithm predicts a quadratic speedup, with the search time $τ(N)=Θ(\sqrt{N})$ and $N$ the database size. Numerical studies suggest that the time complexity can change in the presence of feedback, injecting information during the search. Here, we determine the time complexity of the quantum analog of a randomized algorithm, which implements feedback in a simple form. The search is a continuous-time quantum walk on a complete graph, where the target is continuously monitored by a detector. Additionally, the quantum state is reset if the detector does not click within a specified time interval. This yields a non-unitary, non-Markovian dynamics. We optimize the search time as a function of the hopping amplitude, detection rate, and resetting rate, and identify the conditions under which time complexity could outperform Grover's scaling. The overall search time does not violate Grover's optimality bound when including the time budget of the physical implementation of the measurement. For databases of finite sizes monitoring can warrant rapid convergence and provides a promising avenue for fault-tolerant quantum searches.
format Preprint
id arxiv_https___arxiv_org_abs_2601_20560
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Time complexity of a monitored quantum search with resetting
King, Emma C.
Roy, Sayan
Mattiotti, Francesco
Kiefer-Emmanouilidis, Maximilian
Bläser, Markus
Morigi, Giovanna
Quantum Physics
Other Condensed Matter
Statistical Mechanics
Searching a database is a central task in computer science and is paradigmatic of transport and optimization problems in physics. For an unstructured search, Grover's algorithm predicts a quadratic speedup, with the search time $τ(N)=Θ(\sqrt{N})$ and $N$ the database size. Numerical studies suggest that the time complexity can change in the presence of feedback, injecting information during the search. Here, we determine the time complexity of the quantum analog of a randomized algorithm, which implements feedback in a simple form. The search is a continuous-time quantum walk on a complete graph, where the target is continuously monitored by a detector. Additionally, the quantum state is reset if the detector does not click within a specified time interval. This yields a non-unitary, non-Markovian dynamics. We optimize the search time as a function of the hopping amplitude, detection rate, and resetting rate, and identify the conditions under which time complexity could outperform Grover's scaling. The overall search time does not violate Grover's optimality bound when including the time budget of the physical implementation of the measurement. For databases of finite sizes monitoring can warrant rapid convergence and provides a promising avenue for fault-tolerant quantum searches.
title Time complexity of a monitored quantum search with resetting
topic Quantum Physics
Other Condensed Matter
Statistical Mechanics
url https://arxiv.org/abs/2601.20560