A quantum computing view on unitary coupled cluster theory

Anand, Ankita; Schleich, Philipp; Alperin-Lea, Sumner; Jensen, Phillip W. K.; Sim, Sukin; Díaz–Tinoco, Manuel; Kottmann, Jakob S.; Degroote, Matthias; Izmaylov, Artur F.; Aspuru‐Guzik, Alán

doi:10.1039/d1cs00932j

Cited by 136 publications

(165 citation statements)

References 139 publications

(221 reference statements)

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“…For most applications, structure is configured previously, which depends on the tasks at hand. The widely used structures include quantum alternating operator ansatz, variational Hamiltonian ansatz and unitary coupled clustered ansatz [ 27 , 28 , 29 , 30 ]. In this study, according to hardware efficiency, we employed an

layered circuit for following n -qubit tasks.…”

Section: Resultsmentioning

confidence: 99%

A NISQ Method to Simulate Hermitian Matrix Evolution

Gao

2022

Entropy

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As a universal quantum computer requires millions of error-corrected qubits, one of the current goals is to exploit the power of noisy intermediate-scale quantum (NISQ) devices. Based on a NISQ module–layered circuit, we propose a heuristic protocol to simulate Hermitian matrix evolution, which is widely applied as the core for many quantum algorithms. The two embedded methods, with their own advantages, only require shallow circuits and basic quantum gates. Capable to being deployed in near future quantum devices, we hope it provides an experiment-friendly way, contributing to the exploitation of power of current devices.

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layered circuit for following n -qubit tasks.…”

Section: Resultsmentioning

confidence: 99%

A NISQ Method to Simulate Hermitian Matrix Evolution

Gao

2022

Entropy

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“…The number of CNOT counts can also be lower if one uses a different encoding than the Jordan-Wigner encoding [30]. We do not examine this strategy in detail here, primarily because such a decoding can be used for the different operators in the decomposition as well, and we anticipate similar gains in efficiency.…”

Section: Resultsmentioning

confidence: 99%

Decomposition of high-rank factorized unitary coupled-cluster operators using ancilla and multi-qubit controlled low-rank counterparts

Xu,

Lee,

Freericks

2021

Preprint

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The factorized form of the unitary coupled-cluster (UCC) approximation is one of the most promising methodologies to prepare trial states for strongly correlated systems within the variational quantum eigensolver (VQE) framework. The factorized form of the UCC ansatz can be systematically applied to a reference state to generate the desired entanglement. The difficulty associated with such an approach is the requirement of simultaneously entangling a growing number of qubits, which quickly exceeds the hardware limitations of today's quantum machines. In particular, while circuits for singles and double excitations can be performed on current hardware, higher-rank excitations require too many gate operations. In this work, we propose a set of new schemes that trade off using extra qubits for a reduced gate depth to decompose high-rank UCC excitation operators into significantly lower depth circuits. These results will remain useful even when fault-tolerant machines are available to reduce the overall state-preparation circuit depth.

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“…To do so, we use fragmentation strategies where the preferential adsorption site is solved by simulated quantum computation. In the latter, the adsorbing Al atom is treated with unitary coupled cluster truncated to singles and doubles excitations (UCCSD) 43 , an ansatz for the electronic wavefunction that can be variationally optimised by quantum computing techniques such as the variational quantum eigensolver (VQE) 44 .…”

Section: Main Textmentioning

confidence: 99%

Modelling Carbon Capture on Metal-Organic Frameworks with Quantum Computing

Greene‐Diniz¹,

Manrique²,

Wassil³

et al. 2022

Preprint

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Despite the recent progress in quantum computational algorithms for chemistry, there is a dearth of quantum computational simulations focused on material science applications, especially for the energy sector, where next generation sorbing materials are urgently needed to battle climate change. To drive their development, quantum computing is applied to the problem of CO 2 adsorption in Al-fumarate Metal-Organic Frameworks. Fragmentation strategies based on Density Matrix Embedding Theory are applied, using a variational quantum algorithm as a fragment solver, along with active space selection to minimise qubit number. By investigating different fragmentation strategies and solvers, we propose a methodology to apply quantum computing to Al-fumarate interacting with a CO 2 molecule, demonstrating the feasibility of treating a complex porous system as a concrete application of quantum computing. Our work paves the way for the use of quantum computing techniques in the quest of sorbents optimisation for more efficient carbon capture and conversion applications.

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A quantum computing view on unitary coupled cluster theory

Abstract: This review presents a comprehensive overview of the Unitary Coupled Cluster (UCC) ansatz and related ansätze which are used to solve the electronic structure problem on quantum computers.

Cited by 136 publications

References 139 publications

A NISQ Method to Simulate Hermitian Matrix Evolution

A NISQ Method to Simulate Hermitian Matrix Evolution

Decomposition of high-rank factorized unitary coupled-cluster operators using ancilla and multi-qubit controlled low-rank counterparts

Modelling Carbon Capture on Metal-Organic Frameworks with Quantum Computing

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