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ADAPT-VQE is a leading variational quantum algorithm as it circumvents the choice-of-ansatz conundrum by iteratively growing compact and arbitrarily accurate problem-tailored ans\"atze.
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H. L. Tang, V. Shkolnikov, G. S. Barron, H. R. Grimsley, N. J. Mayhall, E. Barnes, and S. E. Economou, Qubit-adapt-vqe: An adaptive algorithm for constructing hardware-efficient ansätze on a quantum processor, PRX Quantum 2
2021
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L. Zhu, H. L. Tang, G. S. Barron, F. A. Calderon-Vargas, N. J. Mayhall, E. Barnes, and S. E. Economou, Adaptive quantum approximate optimization algorithm for solving combinatorial problems on a quantum computer, Phys. Rev. Res. 4
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H. R. Grimsley, G. S. Barron, E. Barnes, S. E. Economou, and N. J. Mayhall, Adaptive, problem-tailored variational quantum eigensolver mitigates rough parameter landscapes and barren plateaus, npj Quantum Information 9
2023
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V. O. Shkolnikov, N. J. Mayhall, S. E. Economou, and E. Barnes, Avoiding symmetry roadblocks and minimizing the measurement overhead of adaptive variational quantum eigensolvers, Quantum 7
2023
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Y. S. Yordanov, V. Armaos, C. H. W. Barnes, and D. R. M. Arvidsson-Shukur, Qubit-excitation-based adaptive variational quantum eigensolver, Communications Physics 4
2021
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J. Liu, Z. Li, and J. Yang, An efficient adaptive variational quantum solver of the Schrödinger equation based on reduced density matrices, The Journal of Chemical Physics 154
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Z. Holmes, K. Sharma, M. Cerezo, and P. J. Coles, Connecting ansatz expressibility to gradient magnitudes and barren plateaus, PRX Quantum 3
2022
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M. Majland, P. Ettenhuber, and N. T. Zinner, Fermionic adaptive sampling theory for variational quantum eigensolvers, Phys. Rev. A 108
2023
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J. D. Weidman, M. Sajjan, C. Mikolas, Z. J. Stewart, J. Pollanen, S. Kais, and A. K. Wilson, Quantum computing and chemistry, Cell Reports Physical Science 5
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A. Javadi-Abhari, M. Treinish, K. Krsulich, C. J. Wood, J. Lishman, J. Gacon, S. Martiel, P. D. Nation, L. S. Bishop, A. W. Cross, B. R. Johnson, and J. M. Gambetta, Quantum computing with Qiskit (2024),
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O. Oumarou, M. Scheurer, R. M. Parrish, E. G. Hohenstein, and C. Gogolin, Accelerating Quantum Computations of Chemistry Through Regularized Compressed Double Factorization, Quantum 8
2024
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K. Dalton, C. K. Long, Y. S. Yordanov, C. G. Smith, C. H. W. Barnes, N. Mertig, and D. R. M. Arvidsson-Shukur, Quantifying the effect of gate errors on variational quantum eigensolvers for quantum chemistry, npj Quantum Information 10
2024
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P. G. Anastasiou, Y. Chen, N. J. Mayhall, E. Barnes, and S. E. Economou, Tetris-adapt-vqe: An adaptive algorithm that yields shallower, denser circuit ansätze, Phys. Rev. Res. 6
2024
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M. Ramôa, P. G. Anastasiou, L. P. Santos, N. J. Mayhall, E. Barnes, and S. E. Economou, Reducing the resources required by adapt-vqe using coupled exchange operators and improved subroutines, npj Quantum Information 11
2025
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A. Nykänen, M. A. C. Rossi, E.-M. Borrelli, S. Maniscalco, G. García-Pérez, and A. Glos, Mitigating the measurement overhead of adapt-vqe with optimized informationally complete generalized measurements, Phys. Rev. Res. 7
2025
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2025
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R. Huang and A. F. Izmaylov, Quantum gambling: Best-arm strategies for generator selection in adaptive variational algorithms, Journal of Chemical Theory and Computation 10.1021/acs.jctc.6c00568 (2026)
2026
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