New directions in dynamical expectation estimation
Abstract
Computing dynamical expectation values typically relies on approximations optimized for the state or observable separately, without accounting for how their errors combine in the final expression. This work explores an alternative approach in which each approximation is guided by both the state and the observable, accounting for how they jointly determine the target expectation value. This idea is implemented through a sweep algorithm with coupled loss functions for forward state and backward observable updates. Exact error relations provide an analytical rationale for how the proposed losses can improve the accuracy. Numerical tests on 30-qubit random circuits show errors two to three orders of magnitude smaller than those of variational state compression at equal bond dimensions. These results motivate further exploration of joint state and observable approximation for dynamical expectation value estimation.
Related
- Efficient expectation value estimation for quantum circuits via extended stabilizer frameworks and adaptive variance estimation
- Hardware-Friendly Estimation of LCU-Based Expectation Values via Quantum-to-Classical Workload Shifting
- Squeezed light and coherent feedback enhanced multiparameter quantum estimation in a double-cavity optomechanics: steady and dynamical states
- Alignment-Free Optical Combining with Scalar-Message Expectation Propagation Detection for Distributed Multi-Aperture Coherent Reception
- Constraints from big bang nucleosynthesis and cosmological observations on varying Higgs vacuum expectation value
BibTeX
@misc{kim2026directions,
title = {{New directions in dynamical expectation estimation}},
author = {Panjin Kim and Kyung Chul Jeong and Yun-Tak Oh},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.18246},
eprint = {2609.18246},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.18246},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - New directions in dynamical expectation estimation
AU - Panjin Kim
AU - Kyung Chul Jeong
AU - Yun-Tak Oh
PY - 2026
DA - 2026/09/17
PB - arXiv
DO - 10.48550/arxiv.2609.18246
UR - https://arxiv.org/abs/2609.18246
AB - Computing dynamical expectation values typically relies on approximations optimized for the state or observable separately, without accounting for how their errors combine in the final expression. This work explores an alternative approach in which each approximation is guided by both the state and the observable, accounting for how they jointly determine the target expectation value. This idea is implemented through a sweep algorithm with coupled loss functions for forward state and backward observable updates. Exact error relations provide an analytical rationale for how the proposed losses can improve the accuracy. Numerical tests on 30-qubit random circuits show errors two to three orders of magnitude smaller than those of variational state compression at equal bond dimensions. These results motivate further exploration of joint state and observable approximation for dynamical expectation value estimation.
ER -