Related papers: Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry

Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry

URL: http://arxiv.org/abs/2004.04151v3
Date: Wed, 21 Jul 2021 15:29:08 GMT
Title: Resource-Optimized Fermionic Local-Hamiltonian Simulation on Quantum Computer for Quantum Chemistry
Authors: Qingfeng Wang, Ming Li, Christopher Monroe, Yunseong Nam
Abstract summary: We present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. We show that resource-requirement savings of up to more than $20%$, in small instances, is possible.
Score: 6.361119478712919
License: http://creativecommons.org/licenses/by/4.0/
Abstract: The ability to simulate a fermionic system on a quantum computer is expected to revolutionize chemical engineering, materials design, nuclear physics, to name a few. Thus, optimizing the simulation circuits is of significance in harnessing the power of quantum computers. Here, we address this problem in two aspects. In the fault-tolerant regime, we optimize the $\rzgate$ and $\tgate$ gate counts along with the ancilla qubit counts required, assuming the use of a product-formula algorithm for implementation. We obtain a savings ratio of two in the gate counts and a savings ratio of eleven in the number of ancilla qubits required over the state of the art. In the pre-fault tolerant regime, we optimize the two-qubit gate counts, assuming the use of the variational quantum eigensolver (VQE) approach. Specific to the latter, we present a framework that enables bootstrapping the VQE progression towards the convergence of the ground-state energy of the fermionic system. This framework, based on perturbation theory, is capable of improving the energy estimate at each cycle of the VQE progression, by about a factor of three closer to the known ground-state energy compared to the standard VQE approach in the test-bed, classically-accessible system of the water molecule. The improved energy estimate in turn results in a commensurate level of savings of quantum resources, such as the number of qubits and quantum gates, required to be within a pre-specified tolerance from the known ground-state energy. We also explore a suite of generalized transformations of fermion to qubit operators and show that resource-requirement savings of up to more than $20\%$, in small instances, is possible.

Related papers

Resource-Efficient Quantum Circuits for Molecular Simulations: A Case Study of Umbrella Inversion in Ammonia [1.439738350540859]
We develop a novel quantum circuit that reduces the required circuit depth and number of two-qubit entangling gates by about 60%. Even in the presence of device noise, these novel shallower circuits yielded substantially low error rates.
arXiv Detail & Related papers (2023-12-07T11:30:09Z)
Pre-optimizing variational quantum eigensolvers with tensor networks [1.4512477254432858]
We present and benchmark an approach where we find good starting parameters for parameterized quantum circuits by simulating VQE. We apply this approach to the 1D and 2D Fermi-Hubbard model with system sizes that use up to 32 qubits. In 2D, the parameters that VTNE finds have significantly lower energy than their starting configurations, and we show that starting VQE from these parameters requires non-trivially fewer operations to come down to a given energy.
arXiv Detail & Related papers (2023-10-19T17:57:58Z)
A self-consistent field approach for the variational quantum eigensolver: orbital optimization goes adaptive [52.77024349608834]
We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Assembled Ansatz Variational Eigensolver (ADAPTVQE) This framework is used for efficient quantum simulations of chemical systems on nearterm quantum computers.
arXiv Detail & Related papers (2022-12-21T23:15:17Z)
Phenomenological Theory of Variational Quantum Ground-State Preparation [0.0]
The variational quantum eigensolver (VQE) algorithm aims to prepare the ground state of a Hamiltonian exploiting parametrized quantum circuits. We show that the algorithm's success crucially depends on other parameters such as the learning rate. We propose a symmetry-enhanced simulation protocol that should be used if the gap closes.
arXiv Detail & Related papers (2022-05-12T18:00:04Z)
Quantum thermodynamic methods to purify a qubit on a quantum processing unit [68.8204255655161]
We report on a quantum thermodynamic method to purify a qubit on a quantum processing unit equipped with identical qubits. Our starting point is a three qubit design that emulates the well known two qubit swap engine. We implement it on a publicly available superconducting qubit based QPU, and observe a purification capability down to 200 mK.
arXiv Detail & Related papers (2022-01-31T16:13:57Z)
Realization of arbitrary doubly-controlled quantum phase gates [62.997667081978825]
We introduce a high-fidelity gate set inspired by a proposal for near-term quantum advantage in optimization problems. By orchestrating coherent, multi-level control over three transmon qutrits, we synthesize a family of deterministic, continuous-angle quantum phase gates acting in the natural three-qubit computational basis.
arXiv Detail & Related papers (2021-08-03T17:49:09Z)
Benchmarking adaptive variational quantum eigensolvers [63.277656713454284]
We benchmark the accuracy of VQE and ADAPT-VQE to calculate the electronic ground states and potential energy curves. We find both methods provide good estimates of the energy and ground state. gradient-based optimization is more economical and delivers superior performance than analogous simulations carried out with gradient-frees.
arXiv Detail & Related papers (2020-11-02T19:52:04Z)
Towards simulating 2D effects in lattice gauge theories on a quantum computer [1.327151508840301]
We propose an experimental quantum simulation scheme to study ground state properties in two-dimensional quantum electrodynamics (2D QED) using existing quantum technology. The proposal builds on a formulation of lattice gauge theories as effective spin models in arXiv:2006.14160. We present two Variational Quantum Eigensolver (VQE) based protocols for the study of magnetic field effects, and for taking an important first step towards computing the running coupling of QED.
arXiv Detail & Related papers (2020-08-21T01:20:55Z)
Gate-free state preparation for fast variational quantum eigensolver simulations: ctrl-VQE [0.0]
VQE is currently the flagship algorithm for solving electronic structure problems on near-term quantum computers. We propose an alternative algorithm where the quantum circuit used for state preparation is removed entirely and replaced by a quantum control routine. As with VQE, the objective function optimized is the expectation value of the qubit-mapped molecular Hamiltonian.
arXiv Detail & Related papers (2020-08-10T17:53:09Z)
Quantum-optimal-control-inspired ansatz for variational quantum algorithms [105.54048699217668]
A central component of variational quantum algorithms (VQA) is the state-preparation circuit, also known as ansatz or variational form. Here, we show that this approach is not always advantageous by introducing ans"atze that incorporate symmetry-breaking unitaries. This work constitutes a first step towards the development of a more general class of symmetry-breaking ans"atze with applications to physics and chemistry problems.
arXiv Detail & Related papers (2020-08-03T18:00:05Z)
QUANTIFY: A framework for resource analysis and design verification of quantum circuits [69.43216268165402]
QUANTIFY is an open-source framework for the quantitative analysis of quantum circuits. It is based on Google Cirq and is developed with Clifford+T circuits in mind. For benchmarking purposes QUANTIFY includes quantum memory and quantum arithmetic circuits.
arXiv Detail & Related papers (2020-07-21T15:36:25Z)

This list is automatically generated from the titles and abstracts of the papers in this site.