Variational Quantum Eigensolver Enables 27% Faster Molecular Energy Level Calculations with HiUCCSD

Determining the energy levels of molecules presents a significant challenge for quantum computing, yet solving this problem forms one of the most promising paths toward realising practical quantum advantage in the near future. Runhong He, Arapat Ablimit, and Xin Hong, alongside colleagues at their respective institutions, now present a new approach to this calculation, developing an advanced computational strategy called HiUCCSD. This method cleverly incorporates information directly from the Hamiltonian, the mathematical description of the molecule’s energy, to create a more efficient and robust solution, while respecting fundamental molecular symmetries. The team demonstrates that HiUCCSD performs comparably to existing methods for many molecules, but crucially avoids potential failures when applied to more complex systems, and significantly reduces the computational resources required for accurate results, paving the way for larger and more ambitious molecular simulations.

Solving molecular energy levels via the Variational Quantum Eigensolver (VQE) algorithm represents one of the most promising applications for demonstrating practically meaningful quantum advantage in the noisy intermediate-scale quantum (NISQ) era. To strike a balance between ansatz complexity and computational stability in VQE calculations, researchers propose HiUCCSD, a novel symmetry-respecting ansatz engineered from the intrinsic information of the Hamiltonian. They theoretically prove the effectiveness of HiUCCSD within the scope of Abelian point groups, and the team compares its performance with existing methods, establishing its potential for accurate and efficient quantum simulations of molecular systems.

Variational Quantum Eigensolver For Molecular Simulation

The text details research and development related to variational quantum algorithms (VQAs), specifically for solving problems in quantum computational chemistry. The primary goal is to find ways to simulate molecular energies and properties on quantum computers, overcoming the limitations of classical computational methods, with a significant focus on improving the efficiency and scalability of these algorithms. The core algorithm, Variational Quantum Eigensolver (VQE), is a hybrid quantum-classical approach used to find the ground state energy of a molecule. Unitary Coupled Cluster (UCC) is a common ansatz, and researchers are working to make it more efficient through techniques like Adaptive VQE (Adapt-VQE), which dynamically builds the quantum circuit during computation, adding only the most important quantum gates to reduce qubit count and circuit depth.

Qubit-Excitation-Based Adapt-VQE, a specific implementation, focuses on adding qubit excitation operators, while energy sorting prioritizes the most important excitations. Pruned Adapt-VQE further reduces circuit size by removing irrelevant operators, and the Bravyi-Kitaev Transformation maps fermionic problems to qubit problems, essential for quantum chemistry simulations. The research tackles challenges such as barren plateaus, where optimization becomes difficult, and the need to reduce circuit depth and qubit count, both critical for near-term quantum hardware. Adapt-VQE and pruning techniques address these issues, alongside leveraging molecular symmetry to simplify calculations and minimize resource requirements.

Researchers utilize PySCF, a Python-based framework for electronic structure calculations, and MindSpore Quantum, a quantum computing framework developed by Huawei, for implementing and testing the algorithms, alongside Scipy, a Python library for scientific computing. The text emphasizes the importance of point group symmetry in molecular systems, as exploiting symmetry can significantly reduce the computational cost of quantum simulations by reducing the number of parameters that need to be optimized. Optimization relies on methods like Quasi-Newton methods, such as Broyden. In essence, the text describes a cutting-edge area of research aimed at harnessing the power of quantum computers to solve complex problems in chemistry and materials science, focusing on making these computations practical and feasible on near-term quantum hardware.

HiUCCSD Improves Molecular Energy Calculations Significantly

Scientists have developed a new computational approach, HiUCCSD, to solve molecular energy levels using the Variational Quantum Eigensolver (VQE) algorithm, representing a significant advancement for near-term quantum computing. The work focuses on designing a more efficient quantum circuit, or ansatz, to accurately calculate the energy of molecules, a fundamental problem in chemistry and physics. Testing HiUCCSD and the established SymUCCSD ansatz on ten molecules, each possessing unique point group symmetries, using both VQE and Adaptive Derivative-Assembled Pseudo-Trotter (ADAPT)-VQE methods, revealed that HiUCCSD achieves performance equivalent to SymUCCSD for molecules with Abelian point group symmetries, avoiding potential failures observed with SymUCCSD in molecules with non-Abelian symmetries. Across all molecular systems studied, HiUCCSD reduces the number of parameters required for VQE calculations by 18% to 83% compared to the UCCSD ansatz, indicating a substantial decrease in computational demand.

Furthermore, the team measured a reduction in the excitation operator pool size by 27% to 84% when using ADAPT-VQE, streamlining the computational process and lowering resource requirements. These measurements confirm HiUCCSD’s enhanced robustness and broader applicability, offering a valuable new option for large-scale molecular VQE implementation. The breakthrough delivers a significant reduction in the computational resources needed to model molecular energies, paving the way for more complex simulations and potentially accelerating discoveries in materials science, drug design, and other fields reliant on accurate molecular modeling. The team’s work establishes a new benchmark for ansatz design, offering a pathway towards more efficient and scalable quantum simulations of molecular systems.

HiUCCSD Improves Molecular Energy Calculations

This research team has developed a new computational approach, HiUCCSD, to improve the accuracy and efficiency of Variational Quantum Eigensolver (VQE) calculations for determining molecular energy levels. Recognizing the limitations of existing methods in the emerging field of quantum computing, they engineered an ansatz, a carefully constructed trial solution, that incorporates molecular symmetry directly from the Hamiltonian. Theoretical analysis confirms the effectiveness of HiUCCSD for molecules possessing certain symmetry characteristics, specifically those belonging to Abelian point groups. Comparative numerical experiments, performed on ten molecules with diverse structures, demonstrate that HiUCCSD performs comparably to the established SymUCCSD method for these molecules, but crucially avoids potential failures when applied to molecules with more complex, non-Abelian symmetry. Importantly, HiUCCSD significantly reduces the number of parameters required for the VQE calculation, by as much as 83%, and minimizes the size of the excitation operator pool needed, thereby lessening the computational demands. This advancement provides a valuable new tool for progressing towards large-scale molecular simulations using quantum computers.