Quantum expectation value estimation by doubling the number of qubits
- URL: http://arxiv.org/abs/2412.14466v1
- Date: Thu, 19 Dec 2024 02:27:42 GMT
- Title: Quantum expectation value estimation by doubling the number of qubits
- Authors: Hiroshi Yano, Masaya Kohda, Shoichiro Tsutsui, Ryosuke Imai, Keita Kanno, Kosuke Mitarai, Yuya O. Nakagawa,
- Abstract summary: We investigate the efficiency of energy estimation for molecular Hamiltonians of up to 12 qubits.
We show that, when the target precision is no smaller than tens of milli-Hartree, this method requires fewer measurements than conventional sampling methods.
- Score: 0.0
- License:
- Abstract: Expectation value estimation is ubiquitous in quantum algorithms. The expectation value of a Hamiltonian, which is essential in various practical applications, is often estimated by measuring a large number of Pauli strings on quantum computers and performing classical post-processing. In the case of $n$-qubit molecular Hamiltonians in quantum chemistry calculations, it is necessary to evaluate $O(n^4)$ Pauli strings, requiring a large number of measurements for accurate estimation. To reduce the measurement cost, we assess an existing idea that uses two copies of an $n$-qubit quantum state of interest and coherently measures them in the Bell basis, which enables the simultaneous estimation of the absolute values of expectation values of all the $n$-qubit Pauli strings. We numerically investigate the efficiency of energy estimation for molecular Hamiltonians of up to 12 qubits. The results show that, when the target precision is no smaller than tens of milli-Hartree, this method requires fewer measurements than conventional sampling methods. This suggests that the method may be useful for many applications that rely on expectation value estimation of Hamiltonians and other observables as well when moderate precision is sufficient.
Related papers
- Reducing the sampling complexity of energy estimation in quantum many-body systems using empirical variance information [45.18582668677648]
We consider the problem of estimating the energy of a quantum state preparation for a given Hamiltonian in Pauli decomposition.
We construct an adaptive estimator using the state's actual variance.
arXiv Detail & Related papers (2025-02-03T19:00:01Z) - Heisenberg-limited adaptive gradient estimation for multiple observables [0.39102514525861415]
In quantum mechanics, measuring the expectation value of a general observable has an inherent statistical uncertainty.
We provide an adaptive quantum algorithm for estimating the expectation values of $M$ general observables within root mean squared error.
Our method paves a new way to precisely understand and predict various physical properties in complicated quantum systems using quantum computers.
arXiv Detail & Related papers (2024-06-05T14:16:47Z) - Calculating response functions of coupled oscillators using quantum phase estimation [40.31060267062305]
We study the problem of estimating frequency response functions of systems of coupled, classical harmonic oscillators using a quantum computer.
Our proposed quantum algorithm operates in the standard $s-sparse, oracle-based query access model.
We show that a simple adaptation of our algorithm solves the random glued-trees problem in time.
arXiv Detail & Related papers (2024-05-14T15:28:37Z) - Optimum phase estimation with two control qubits [0.0]
We show how to measure a phase with a minimum mean-square error using only two control qubits.
Our method corresponds to preparing the optimal control state one qubit at a time, while it is simultaneously consumed by the measurement procedure.
arXiv Detail & Related papers (2023-03-22T12:18:33Z) - Sparse random Hamiltonians are quantumly easy [105.6788971265845]
A candidate application for quantum computers is to simulate the low-temperature properties of quantum systems.
This paper shows that, for most random Hamiltonians, the maximally mixed state is a sufficiently good trial state.
Phase estimation efficiently prepares states with energy arbitrarily close to the ground energy.
arXiv Detail & Related papers (2023-02-07T10:57:36Z) - Almost optimal measurement scheduling of molecular Hamiltonian via finite projective plane [0.0]
We propose an efficient and almost optimal scheme for measuring molecular Hamiltonians in quantum chemistry on quantum computers.
It requires $2N2$ distinct measurements in the leading order with $N$ being the number of molecular orbitals.
Because evaluating expectation values of molecular Hamiltonians is one of the major bottlenecks in the applications of quantum devices to quantum chemistry, our finding is expected to accelerate such applications.
arXiv Detail & Related papers (2023-01-18T06:51:18Z) - Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping [49.36226952764697]
Estimation of the energy of quantum many-body systems is a paradigmatic task in various research fields.
We aim to find the optimal strategy with single-qubit measurements that yields the highest provable accuracy given a total measurement budget.
We develop a practical, efficient estimation strategy, which we call ShadowGrouping.
arXiv Detail & Related papers (2023-01-09T14:41:07Z) - Reducing the cost of energy estimation in the variational quantum
eigensolver algorithm with robust amplitude estimation [50.591267188664666]
Quantum chemistry and materials is one of the most promising applications of quantum computing.
Much work is still to be done in matching industry-relevant problems in these areas with quantum algorithms that can solve them.
arXiv Detail & Related papers (2022-03-14T16:51:36Z) - Quantum algorithms for estimating quantum entropies [6.211541620389987]
We propose quantum algorithms to estimate the von Neumann and quantum $alpha$-R'enyi entropies of an fundamental quantum state.
We also show how to efficiently construct the quantum entropy circuits for quantum entropy estimation using single copies of the input state.
arXiv Detail & Related papers (2022-03-04T15:44:24Z) - Quantum expectation-value estimation by computational basis sampling [0.0]
A practical obstacle is the necessity of a large number of measurements for statistical convergence.
We propose an algorithm to estimate the expectation value based on its approximate expression as a weighted sum of classically-tractable matrix elements.
arXiv Detail & Related papers (2021-12-14T14:08:56Z) - Communication Cost of Quantum Processes [49.281159740373326]
A common scenario in distributed computing involves a client who asks a server to perform a computation on a remote computer.
An important problem is to determine the minimum amount of communication needed to specify the desired computation.
We analyze the total amount of (classical and quantum) communication needed by a server in order to accurately execute a quantum process chosen by a client.
arXiv Detail & Related papers (2020-02-17T08:51:42Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.