Adiabatic quantum computation

By J. Roland, N. J. Cerf. 2004

1,061 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/6ee9854a49e7a7e80bcf0b6103434644c52af971

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Citations in the corpus

Quantum simulation and computing with Rydberg-interacting qubits (2020, background): “It can also be thought of as a key step toward more general purpose adiabatic quantum computers, a promising alternative to digital circuit based approaches 272,273 .”
Quantum Technologies Need a Quantum Energy Initiative (2021, unknown): “Quantum annealing is a kind of adiabatic quantum computing [40], where the quantum data register is prepared in the ground state of a Hamiltonian, which is externally tuned via the control parameters.”
Challenges and opportunities in quantum optimization (2023, unknown): “The problems chosen should be sufficiently hard for state-of-the-art classical solvers to leave a margin for quantum methods, but”
Practical quantum advantage in quantum simulation (2022, methodology): “This approach is akin to the concept of an adiabatic quantum computer 58 , but in a restricted sense, as one typically cannot control all degrees of freedom of the system to realize a universal adiabatic quantum computer.”
Training Variational Quantum Algorithms Is NP-Hard. (2021, background): “QAOAs can be seen as certain types of VQAs, which are inspired by adiabatic computation, where a slow enough transition between two Hamiltonians Hb and Hc guarantees remaining in the ground state as long as the Hamiltonians are gapped and level crossings are avoided [21].”
Ising machines as hardware solvers of combinatorial optimization problems (2022, methodology): “Hybrid Quantum-Classical Algorithms The aim of variational quantum algorithms 158 is to solve classical and quantum optimization problems by combining a parametrized quantum circuit with a classical optimizer to obtain the variational parameters.”
Quantum annealing for industry applications: introduction and review (2021, unknown): “The hope that quantum mechanical effects lead to an advantage of QA over classical algorithms is related to the conjectured role of quantum superposition, tunneling, and entanglement [8].”