A Case Study on Noise Resilient Operator Selection in Adaptive Variational Quantum Algorithms

Abstract

Hardware noise has been shown to significantly impact the accuracy of ADAPT-VQE, a ground state preparation algorithm. While previous work has studied the impact of noise on its parameter optimization step, its impact on the critical operator selection step remains comparatively unexplored. In this work, we examine the impact of a variety of noise channels on this step, using a linear H₃ molecule as a test case. We show that, despite the selection criterion's natural resilience to some noise, both coherent and incoherent noise can prevent convergence for sufficiently high noise rates. We employ quantum error mitigation techniques--dynamical decoupling, zero noise extrapolation, and Pauli twirling--and show that when combined appropriately, these techniques are capable of restoring a successful convergence profile. Our results highlight how error mitigation can improve the performance of ADAPT-VQE and enable convergence in the presence of hardware noise, offering valuable insights into the implementation of the algorithm on near-term quantum hardware.

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BibTeX RIS

BibTeX

@misc{haravu2026case,
  title = {{A Case Study on Noise Resilient Operator Selection in Adaptive Variational Quantum Algorithms}},
  author = {Soorya Haravu and Mafalda Ramôa and Bharath Sambasivam},
  howpublished = {arXiv},
  year = {2026},
  month = sep,
  doi = {10.48550/arxiv.2609.17501},
  eprint = {2609.17501},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2609.17501},
  note = {CC BY 4.0},
}

RIS

TY  - UNPB
TI  - A Case Study on Noise Resilient Operator Selection in Adaptive Variational Quantum Algorithms
AU  - Soorya Haravu
AU  - Mafalda Ramôa
AU  - Bharath Sambasivam
PY  - 2026
DA  - 2026/09/15
PB  - arXiv
DO  - 10.48550/arxiv.2609.17501
UR  - https://arxiv.org/abs/2609.17501
AB  - Hardware noise has been shown to significantly impact the accuracy of ADAPT-VQE, a ground state preparation algorithm. While previous work has studied the impact of noise on its parameter optimization step, its impact on the critical operator selection step remains comparatively unexplored. In this work, we examine the impact of a variety of noise channels on this step, using a linear H_3 molecule as a test case. We show that, despite the selection criterion's natural resilience to some noise, both coherent and incoherent noise can prevent convergence for sufficiently high noise rates. We employ quantum error mitigation techniques--dynamical decoupling, zero noise extrapolation, and Pauli twirling--and show that when combined appropriately, these techniques are capable of restoring a successful convergence profile. Our results highlight how error mitigation can improve the performance of ADAPT-VQE and enable convergence in the presence of hardware noise, offering valuable insights into the implementation of the algorithm on near-term quantum hardware.
ER  -

Abstract

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