Breakthrough in Quantum Computing for Chemically Accurate Simulations

Scientists have made a breakthrough in quantum computing, paving the way for more accurate and efficient simulations of chemical systems. Researchers Jean-Philip Piquemal and Diata Traore have developed a novel approach that combines density functional theory with quantum computing to obtain quantitative results on molecules that would otherwise require hundreds of logical qubits. This shortcut, published in Nature Communications Chemistry, enables chemically accurate quantum computations using fewer resources.

The team’s strategy involves coupling a quantum computing ansatz with density-based basis-set corrections and an on-the-fly generation of system-adapted basis sets. This approach allows for more efficient use of classical and quantum resources, making it possible to simulate complex chemical systems that were previously inaccessible. The researchers demonstrated the power of their method by computing chemically meaningful energies and properties on systems that would have required far more than 100 logical qubits.

This breakthrough has significant implications for the field of quantum chemistry, enabling researchers to study industrially relevant applications with unprecedented accuracy. Companies like IBM are already exploring the potential of quantum computing for drug discovery, and this new approach could accelerate progress in this area.

Quantum Computing for Chemically Accurate Results: A Shortcut via Density-Based Basis-Set Correction

Quantum computing has the potential to revolutionize the field of quantum chemistry by providing a more efficient and accurate approach to solving electronic-structure problems. However, one of the major challenges in achieving this goal is minimizing computing resources while maintaining chemical accuracy. Recently, researchers have proposed a novel strategy to address this challenge by coupling density-based basis-set corrections with any given variational ansatz.

The Need for Quantum Computing in Quantum Chemistry

Classical computational methods used in quantum chemistry often struggle to provide accurate results due to the exponential scaling of computational resources with system size. This limitation hinders the study of complex molecular systems, which are crucial for understanding various chemical and physical phenomena. Quantum computing offers a potential solution to this problem by exploiting the principles of quantum mechanics to perform calculations exponentially faster than classical computers.

Density-Based Basis-Set Correction: A Key to Efficient Quantum Computing

The density-based basis-set correction (DBBSC) strategy is based on the idea that density-functional approximation tends to have better convergence of the density with the basis-set size. This approach reduces the qubit requirements of a given ansatz, making it more feasible for implementation on current and near-term quantum hardware.

The researchers propose two DBBSC workflows: a self-consistent basis-set correction and an a posteriori correction. The first workflow iteratively updates the short-range electronic density using a functional of the density, while the second workflow allows for the addition of corrections to any type of computation on real hardware, as long as the electronic density is available at the Hartree-Fock level.

On-the-Fly Generation of System-Adapted Basis Sets

The DBBSC schemes are coupled with a modified pivoted-Cholesky strategy for an on-the-fly generation of basis sets based on the further exploitation of the Hartree-Fock computations. These system-adapted basis sets (SABS) are specifically tailored to a given molecular system, providing a reduced size compared to the original target basis set.

Applications and Results

The researchers apply their global strategy to ground-state energies, dipole moments, and dissociation curves, demonstrating a significant reduction in qubit requirements. Using GPU-accelerated state-vector emulation, they obtain quantitative quantum-chemistry results on molecules that would otherwise require brute-force quantum calculations using hundreds of logical qubits.

For example, the computation of the H2 total energy at the FCI/cc-pV5Z level, which would have required more than 220 logical qubits, can be achieved with only 24 qubits using their basis-set correction scheme and SABS technique. The researchers are also able to converge four systems to the FCI/CBS limit, including He, Be, H2, and LiH, and provide accurate dissociation curves for H2, LiH, and N2 (up to a triple zeta quality).

Implications and Future Directions

This research opens new possibilities for more affordable quantitative quantum-chemistry simulations of small molecules using QC algorithms. The proposed strategy has the potential to ease the applicability of quantum computing for quantum chemistry in industrially relevant applications.

In the long term, this work could lead to the development of novel strategies for better resource management and more efficient use of classical and quantum resources. As the field of quantum computing continues to evolve, research like this will be crucial in unlocking its full potential for revolutionizing various fields, including quantum chemistry.