Quantum algorithm for ground state energy estimation using circuit depth
with exponentially improved dependence on precision
- URL: http://arxiv.org/abs/2209.06811v3
- Date: Thu, 2 Nov 2023 12:58:18 GMT
- Title: Quantum algorithm for ground state energy estimation using circuit depth
with exponentially improved dependence on precision
- Authors: Guoming Wang, Daniel Stilck Fran\c{c}a, Ruizhe Zhang, Shuchen Zhu, and
Peter D. Johnson
- Abstract summary: A milestone in the field of quantum computing will be solving problems in quantum chemistry and materials faster than state-of-the-art classical methods.
We develop a ground state energy estimation algorithm for which this cost grows linearly in the number of bits of precision.
These features make our algorithm a promising candidate for realizing quantum advantage in the era of early fault-tolerant quantum computing.
- Score: 1.5831247735039677
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: A milestone in the field of quantum computing will be solving problems in
quantum chemistry and materials faster than state-of-the-art classical methods.
The current understanding is that achieving quantum advantage in this area will
require some degree of fault tolerance. While hardware is improving towards
this milestone, optimizing quantum algorithms also brings it closer to the
present. Existing methods for ground state energy estimation are costly in that
they require a number of gates per circuit that grows exponentially with the
desired number of bits in precision. We reduce this cost exponentially, by
developing a ground state energy estimation algorithm for which this cost grows
linearly in the number of bits of precision. Relative to recent resource
estimates of ground state energy estimation for the industrially-relevant
molecules of ethylene-carbonate and PF$_6^-$, the estimated gate count and
circuit depth is reduced by a factor of 43 and 78, respectively. Furthermore,
the algorithm can use additional circuit depth to reduce the total runtime.
These features make our algorithm a promising candidate for realizing quantum
advantage in the era of early fault-tolerant quantum computing.
Related papers
- T-Count Optimizing Genetic Algorithm for Quantum State Preparation [0.05999777817331316]
We present and utilize a genetic algorithm for state preparation circuits consisting of gates from the Clifford + T gate set.
Our algorithm does automatically generate fault tolerantly implementable solutions where the number of the most error prone components is reduced.
arXiv Detail & Related papers (2024-06-06T12:26:14Z) - Towards Efficient Quantum Computing for Quantum Chemistry: Reducing Circuit Complexity with Transcorrelated and Adaptive Ansatz Techniques [0.0]
This work demonstrates how to reduce circuit depth by combining the transcorrelated (TC) approach with adaptive quantum ans"atze.
Our study demonstrates that combining the TC method with adaptive ans"atze yields compact, noise-resilient, and easy-to-optimize quantum circuits.
arXiv Detail & Related papers (2024-02-26T15:31:56Z) - Near-Term Distributed Quantum Computation using Mean-Field Corrections
and Auxiliary Qubits [77.04894470683776]
We propose near-term distributed quantum computing that involve limited information transfer and conservative entanglement production.
We build upon these concepts to produce an approximate circuit-cutting technique for the fragmented pre-training of variational quantum algorithms.
arXiv Detail & Related papers (2023-09-11T18:00:00Z) - Exploring the role of parameters in variational quantum algorithms [59.20947681019466]
We introduce a quantum-control-inspired method for the characterization of variational quantum circuits using the rank of the dynamical Lie algebra.
A promising connection is found between the Lie rank, the accuracy of calculated energies, and the requisite depth to attain target states via a given circuit architecture.
arXiv Detail & Related papers (2022-09-28T20:24:53Z) - Quantum circuit debugging and sensitivity analysis via local inversions [62.997667081978825]
We present a technique that pinpoints the sections of a quantum circuit that affect the circuit output the most.
We demonstrate the practicality and efficacy of the proposed technique by applying it to example algorithmic circuits implemented on IBM quantum machines.
arXiv Detail & Related papers (2022-04-12T19:39:31Z) - 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) - Numerical Simulations of Noisy Quantum Circuits for Computational
Chemistry [51.827942608832025]
Near-term quantum computers can calculate the ground-state properties of small molecules.
We show how the structure of the computational ansatz as well as the errors induced by device noise affect the calculation.
arXiv Detail & Related papers (2021-12-31T16:33:10Z) - Reducing runtime and error in VQE using deeper and noisier quantum
circuits [0.0]
A core of many quantum algorithms including VQE, can be improved in terms of precision and accuracy by using a technique we call Robust Amplitude Estimation.
By using deeper, and therefore more error-prone, quantum circuits, we realize more accurate quantum computations in less time.
This technique may be used to speed up quantum computations into the regime of early fault-tolerant quantum computation.
arXiv Detail & Related papers (2021-10-20T17:11:29Z) - Mitigating algorithmic errors in quantum optimization through energy
extrapolation [4.426846282723645]
We present a scalable extrapolation approach to mitigating a non-negligible error in estimates of the ground state energy.
We have verified the validity of these approaches through both numerical simulation and experiments on an IBM quantum computer.
arXiv Detail & Related papers (2021-09-16T17:39:11Z) - Boundaries of quantum supremacy via random circuit sampling [69.16452769334367]
Google's recent quantum supremacy experiment heralded a transition point where quantum computing performed a computational task, random circuit sampling.
We examine the constraints of the observed quantum runtime advantage in a larger number of qubits and gates.
arXiv Detail & Related papers (2020-05-05T20:11:53Z)
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.