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arXiv:2301.05752 · The Journal of Physical Chemistry Letters

Modeling Singlet Fission on a Quantum Computer

Daniel Claudino, Bo Peng, Karol Kowalski, Travis S. Humble

Published Jun 8, 2023• 11 citations
arXivHTMLPDF

Abstract

molecule as a simple model for singlet fission. We use the Peeters-Devreese-Soldatov energy functional to calculate the necessary energetics based on the moments of the Hamiltonian estimated on the quantum computer. To reduce the number of required measurements, we use several independent strategies: 1) reduction of the size of the relevant Hilbert space by tapering off qubits; 2) measurement optimization via rotations to eigenbases shared by groups of qubit-wise commuting Pauli strings; and 3) parallel execution of multiple state preparation and measurement operations using all 20 qubits available on the Quantinuum H1-1 quantum hardware. Our results meet the energetic requirements for singlet fission, are in excellent agreement with exact transition energies (for the chosen one-particle basis), and outperform classical methods considered computationally feasible for singlet fission candidates.

DOI
10.1021/acs.jpclett.3c01106

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molecule as a simple model for singlet fission. We use the Peeters-Devreese-Soldatov energy functional to calculate the necessary energetics based on the moments of the Hamiltonian estimated on the quantum computer. To reduce the number of required measurements, we use several independent strategies: 1) reduction of the size of the relevant Hilbert space by tapering off qubits; 2) measurement optimization via rotations to eigenbases shared by groups of qubit-wise commuting Pauli strings; and 3) parallel execution of multiple state preparation and measurement operations using all 20 qubits available on the Quantinuum H1-1 quantum hardware. Our results meet the energetic requirements for singlet fission, are in excellent agreement with exact transition energies (for the chosen one-particle basis), and outperform classical methods considered computationally feasible for singlet fission candidates.
Solar cell technology has reached a limiting efficiency, now known as the Shockley-Queisser efficiency limit, and researchers are investigating novel strategies like quantum mechanics to surpass this limit. Restriction is imposed by the fact that singlet fission singlet fission , a quantum process, doubles the number of charge carriers charge carriers per photon generated, which results in giving two low-energy excitons from one high-energy photon. But classical simulations would find it inherently difficult to avoid the cryptic nature of its underlying quantum structure, that is, based in coherence, spin states, and environmental influence. The principle of quantum mechanics enables the development of special quantum simulation quantum simulation as a revolutionary way of performing and improving singlet fission research. The material can be screened, the electrical structure studied, and the device or optoelectronic optimized while keeping the material quantum coherent. Hybrid quantum-classical approaches reduce the computational burdens of existing hardware, while sophisticated algorithms such as quantum phase estimation and variational quantum eigensolvers are used to accurately model molecular energetics. To efficiently simulate singlet fission in molecular systems (both simple models, such as linear H 4 molecules, as well as more complicated materials), this work relies on the PDS( K ) energy functional framework. Such a technique alleviates quantum resource limits by carrying out fewer Pauli string measurements, shorter qubits, and using commutativity principles to simplify calculation. Researchers thus find potential materials by modeling quantum states and excitonic transitions and improve device topologies to find the most efficient paths for converting that energy. But there are still distances to go, from producing stable, affordable materials to scaling up quantum technology. This, however, demonstrates that quantum simulation can propel solar cells to entirely novel heights, where they can be paired with existing science, such as perovskite solar cells. The potential for lower energy expenses and environmental gains are business implications. This is a revolutionary development in device engineering, quantum computing, and material discovery material discovery – the bellwether for the future of sustainable energy. Long-lasting solar cells result from quantum hardware and algorithms progressing alongside quantum theory and experimental testing, culminating in ultraefficient processes. So, quantum simulation represents an important breakthrough with respect to the efforts needed to solve the world’s energy problems and to promote an environmentally friendly and energy-secure future.
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 nnn-qubit molecular Hamiltonians in quantum chemistry calculations, it is necessary to evaluate O(n4)O(n^4)O(n4) 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 nnn-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 nnn-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.
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We propose an efficient algorithm for partitioning Pauli strings into subgroups, which can be simultaneously measured in a single quantum circuit. Our partitioning algorithm drastically reduces the total number of measurements in a variational quantum eigensolver for a quantum chemistry, one of the most promising applications of quantum computing. The algorithm is based on the Ising model optimization problem, which can be quickly solved using an Ising machine. We develop an algorithm that is applicable to problems with sizes larger than the maximum number of variables that an Ising machine can handle (nbitn_\text{bit}nbit​) through its iterative use. The algorithm has much better time complexity and solution optimality than other algorithms such as Boppana--Halldórsson algorithm and Bron--Kerbosch algorithm, making it useful for the quick and effective reduction of the number of quantum circuits required for measuring the expectation values of multiple Pauli strings. We investigate the performance of the algorithm using the second-generation Digital Annealer, a high-performance Ising hardware, for up to 65,53565,53565,535 Pauli strings using Hamiltonians of molecules and the full tomography of quantum states. We demonstrate that partitioning problems for quantum chemical calculations can be solved with a time complexity of O(N)O(N)O(N) for N≤nbitN\leq n_\text{bit}N≤nbit​ and O(N2)O(N^2)O(N2) for N>nbitN>n_\text{bit}N>nbit​ for the worst case, where NNN denotes the number of candidate Pauli strings and nbit=8,192n_\text{bit}=8,192nbit​=8,192 for the second-generation Digital Annealer used in this study. The reduction factor, which is the number of Pauli strings divided by the number of obtained partitions, can be 200200200 at maximum.
Quantum computing is being extensively used in quantum chemistry, especially in simulating simple molecules and evaluating properties like the ground state energy, dipole moment, etc. The transformation of a molecular Hamiltonian from the fermionic space to the qubit space provides us with a series of Pauli strings and the energy calculation involves the evaluation of the expectation values of all these individual strings. This introduces a major bottleneck for applications of VQEs in quantum chemistry. Unlike the fermionic Hamiltonian, the terms in a qubit Hamiltonian are additive and the present paper exploits this property to describe a new approach for extracting information from the partial qubit Hamiltonian of simple molecules to design more efficient variational quantum eigensolvers. In the partial (qubit) Hamiltonian approach (PHA), the qubit Hamiltonian is studied term-by-term to understand their relative contributions to the overall energy, and a partial Hamiltonian is constructed with fewer Pauli strings that can resolve the entire Hamiltonian. With PHA, we can simulate molecules at a much lower computational cost with a truncated Hamiltonian. Additionally, the outcomes of the measurements with PHA quench the error due to noise introduced by the quantum circuits. We have also demonstrated the application of PHA as an initialization technique, where the simple partial Hamiltonian can be used to find an optimal starting point for a more complex system.
Recently a new class of quantum algorithms that are based on the quantum computation of the connected moment expansion has been reported to find the ground and excited state energies. In particular, the Peeters-Devreese-Soldatov (PDS) formulation is found variational and bearing the potential for further combining with the existing variational quantum infrastructure. Here we find that the PDS formulation can be considered as a new energy functional of which the PDS energy gradient can be employed in a conventional variational quantum solver. In comparison with the usual variational quantum eigensolver (VQE) and the original static PDS approach, this new variational quantum solver offers an effective approach to navigate the dynamics to be free from getting trapped in the local minima that refer to different states, and achieve high accuracy at finding the ground state and its energy through the rotation of the trial wave function of modest quality, thus improves the accuracy and efficiency of the quantum simulation. We demonstrate the performance of the proposed variational quantum solver for toy models, H 2 molecule, and strongly correlated planar H 4 system in some challenging situations. In all the case studies, the proposed variational quantum approach outperforms the usual VQE and static PDS calculations even at the lowest order. We also discuss the limitations of the proposed approach and its preliminary execution for model Hamiltonian on the NISQ device.