2025/07/22 by Yipei Zhang, Zhang, Yipei, Alain Sarlette +8 · 1 voice · 1 citation
Computer Science · Engineering · #Advanced Optical Network Technologies #Cloud Computing and Resource Management #Convergence (economics) #Observable #Optical Network Technologies #Optimal control #Quantum #Quantum Zeno effect #Schedule #Set (abstract data type) #Zeno's paradoxes
paper · pdf · doi:10.22331/q-2026-07-20-2167
published in Quantum 10, 2167 (Verein zur Förderung des Open Access Publizierens in den Quantenwissenschaften)
openalex created_date 2025/09/23 · openalex publication_date 2026/07/20 · rss pubdate 2026/07/20 · openalex updated_date 2026/08/05
Quantum 10, 2167 (2026). 10.22331/q-2026-07-20-2167 Quantum Zeno dragging enables the preparation of common eigenstates of a set of observables by frequent measurement and adiabatic-like modulation of the measurement basis. In this work, we present a deeper analysis of multi-channel Zeno dragging using generalized measurements, i.e. simultaneously measuring a set of non-commuting observables that vary slowly in time, to drag the state towards a target subspace. For concreteness, we will focus on a measurement-driven approach to solving k-SAT problems as examples. We first compute some analytical upper bounds on the convergence time, including the effect of finite measurement time resolution. We then apply optimal control theory to obtain the optimal dragging schedule that lower bounds the convergence time, for low-dimensional settings. This study provides a theoretical foundation for multi-channel Zeno dragging and its optimization, and also serves as a guide for designing optimal dragging schedules for quantum information tasks including measurement-driven quantum algorithms.