Scaling Up Electronic Structure Calculations on Quantum Computers: The
Frozen Natural Orbital Based Method of Increments
- URL: http://arxiv.org/abs/2002.07901v2
- Date: Wed, 21 Apr 2021 03:10:21 GMT
- Title: Scaling Up Electronic Structure Calculations on Quantum Computers: The
Frozen Natural Orbital Based Method of Increments
- Authors: Prakash Verma, Lee Huntington, Marc Coons, Yukio Kawashima, Takeshi
Yamazaki, Arman Zaribafiyan
- Abstract summary: The MI-FNO framework provides a systematic reduction of the occupied and virtual orbital spaces for quantum chemistry simulations.
The correlation energies of the increments resulting from the MI-FNO reduction can then be solved by various algorithms.
We show that the MI-FNO approach provides a significant reduction in the qubit requirements relative to the full system simulations.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: The method of increments and frozen natural orbital (MI-FNO) framework is
introduced to help expedite the application of noisy, intermediate-scale
quantum~(NISQ) devices for quantum chemistry simulations. The MI-FNO framework
provides a systematic reduction of the occupied and virtual orbital spaces for
quantum chemistry simulations. The correlation energies of the resulting
increments from the MI-FNO reduction can then be solved by various algorithms,
including quantum algorithms such as the phase estimation algorithm and the
variational quantum eigensolver (VQE). The unitary coupled-cluster singles and
doubles VQE framework is used to obtain correlation energies for the case of
small molecules (i.e., BeH$_2$, CH$_4$, NH$_3$, H$_2$O, and HF) using the
cc-pVDZ basis set. The quantum resource requirements are estimated for a
constrained geometry complex (CGC) catalyst that is utilized in industrial
settings for the polymerization of $\alpha$-olefins. We show that the MI-FNO
approach provides a significant reduction in the qubit requirements relative to
the full system simulations. We propose that the MI-FNO framework can create
scalable examples of quantum chemistry problems that are appropriate for
assessing the progress of NISQ devices.
Related papers
- Reconfigurable Intelligent Surface (RIS)-Assisted Entanglement
Distribution in FSO Quantum Networks [62.87033427172205]
Quantum networks (QNs) relying on free-space optical (FSO) quantum channels can support quantum applications in environments where establishing an optical fiber infrastructure is challenging and costly.
A reconfigurable intelligent surface (RIS)-assisted FSO-based QN is proposed as a cost-efficient framework providing a virtual line-of-sight between users for entanglement distribution.
arXiv Detail & Related papers (2024-01-19T17:16:40Z) - Variational quantum eigensolver for closed-shell molecules with
non-bosonic corrections [6.3235499003745455]
We introduce a simple correction scheme in the electron correlation model approximated by the geometrical mean of the bosonic terms.
We find our non-bosonic correction method reaches reliable quantum chemistry simulations at least for the tested systems.
arXiv Detail & Related papers (2023-10-11T16:47:45Z) - Molecular Symmetry in VQE: A Dual Approach for Trapped-Ion Simulations
of Benzene [0.2624902795082451]
Near-term strategies hinge on the use of variational quantum eigensolver (VQE) algorithms combined with a suitable ansatz.
We employ several circuit optimization methods tailored for trapped-ion quantum devices to enhance the feasibility of intricate chemical simulations.
These methods, when applied to a benzene molecule simulation, enabled the construction of an 8-qubit circuit with 69 two-qubit entangling operations.
arXiv Detail & Related papers (2023-08-01T17:03:10Z) - 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) - Towards Neural Variational Monte Carlo That Scales Linearly with System
Size [67.09349921751341]
Quantum many-body problems are central to demystifying some exotic quantum phenomena, e.g., high-temperature superconductors.
The combination of neural networks (NN) for representing quantum states, and the Variational Monte Carlo (VMC) algorithm, has been shown to be a promising method for solving such problems.
We propose a NN architecture called Vector-Quantized Neural Quantum States (VQ-NQS) that utilizes vector-quantization techniques to leverage redundancies in the local-energy calculations of the VMC algorithm.
arXiv Detail & Related papers (2022-12-21T19:00:04Z) - Decomposition of Matrix Product States into Shallow Quantum Circuits [62.5210028594015]
tensor network (TN) algorithms can be mapped to parametrized quantum circuits (PQCs)
We propose a new protocol for approximating TN states using realistic quantum circuits.
Our results reveal one particular protocol, involving sequential growth and optimization of the quantum circuit, to outperform all other methods.
arXiv Detail & Related papers (2022-09-01T17:08:41Z) - Quantum-classical eigensolver using multiscale entanglement
renormalization [0.0]
We propose a variational quantum eigensolver (VQE) for the simulation of strongly-correlated quantum matter.
It can have substantially lower costs than corresponding classical algorithms.
It is particularly attractive for ion-trap devices with ion-shuttling capabilities.
arXiv Detail & Related papers (2021-08-30T17:46:35Z) - Error mitigation and quantum-assisted simulation in the error corrected
regime [77.34726150561087]
A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations.
We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
arXiv Detail & Related papers (2021-03-12T20:58:41Z) - 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) - Hybrid quantum variational algorithm for simulating open quantum systems
with near-term devices [0.0]
Hybrid quantum-classical (HQC) algorithms make it possible to use near-term quantum devices supported by classical computational resources.
We develop an HQC algorithm using an efficient variational optimization approach to simulate open system dynamics.
arXiv Detail & Related papers (2020-08-12T13:49:29Z)
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.