Adiabatic dynamics of entanglement
Open Access
- 7 October 2025
- journal article
- Published by IOP Publishing in Quantum Science and Technology
- Vol. 10 (4) , 045054
Abstract
We show that, during adiabatic evolution, any changes in entanglement can be attributed to a succession of avoided energy level crossings at which eigenvalues swap their eigenvectors. These swaps mediate the generation and redistribution of entanglement in multipartite systems. The efficiency of this redistribution depends on the narrowness of the avoided level crossings and thus constrains the speed of adiabatic evolution. Moreover, we relate the amount of entanglement involved to the ruggedness of the energy landscape, which directly affects the hardness of a computational problem. This enables an analysis of computational complexity and quantum advantage from the point of view of entanglement requirements. Applied to adiabatic quantum computation, our findings directly relate the computation’s speed to its utilization of entanglement as a resource. The same principles extend to gate-based discretized adiabatic quantum algorithms, including those for Hamiltonian simulation and combinatorial optimization.Keywords
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Funding Information
- Australian Research Council
- National Research Council of Canada
- NSERC
- National Science and Engineering Council of Canada
This publication has 48 references indexed in Scilit:
- Hamiltonian dynamics on digital quantum computers without discretization errornpj Quantum Information, 2024
- Optimisation of spatiotemporal context-constrained full-view area coverage deployment in camera sensor networks via quantum annealingInternational Journal of Geographical Information Science, 2024
- Negativity vs. purity and entropy in witnessing entanglementScientific Reports, 2023
- Prospects for quantum enhancement with diabatic quantum annealingNature Reviews Physics, 2021
- Error suppression in adiabatic quantum computing with qubit ensemblesnpj Quantum Information, 2021
- Traffic signal optimization on a square lattice with quantum annealingScientific Reports, 2021
- Quantum control based on machine learning in an open quantum systemPhysics Letters A, 2020
- Approaching the adiabatic timescale with machine learningProceedings of the National Academy of Sciences, 2018
- Rank-one modification of the symmetric eigenproblemNumerische Mathematik, 1978
- Beweis des AdiabatensatzesThe European Physical Journal A, 1928