Researchers Develop Quantum Algorithm for Advanced Chemistry Calculations, Aiding Drug Design

A collaborative team of researchers from QC Ware Corporation, PsiQuantum, Boehringer Ingelheim Pharma GmbH & Co KG, University of Innsbruck, and Quantum Lab Boehringer Ingelheim have developed a fault-tolerant quantum algorithm for Symmetry-Adapted Perturbation Theory (SAPT). The algorithm efficiently computes observables beyond total energy, a key challenge in quantum chemistry. It estimates interaction energies at the first-order SAPT level using a high-order tensor factorization and block-encoding technique. The algorithm has practical applications in molecules and materials design, including polymers, catalysts, batteries, and drugs. Future work will focus on improving potential bottlenecks and further optimizing computational costs.

What is the Quantum Algorithm for Symmetry-Adapted Perturbation Theory?

A team of researchers from QC Ware Corporation, PsiQuantum, Boehringer Ingelheim Pharma GmbH & Co KG, Department of General Inorganic and Theoretical Chemistry University of Innsbruck, and Quantum Lab Boehringer Ingelheim have developed a fault-tolerant quantum algorithm for Symmetry-Adapted Perturbation Theory (SAPT). This algorithm is designed to efficiently compute observables beyond total energy, a key challenge in quantum chemistry. The team’s work focuses on the interaction energy components of SAPT as a prototypical example of such an observable.

The researchers have provided a guide for calculating this observable on a fault-tolerant quantum computer while optimizing the required computational resources. They present a quantum algorithm that estimates interaction energies at the first-order SAPT level with a Heisenberg-limited scaling. To achieve this, they exploit a high-order tensor factorization and block-encoding technique that efficiently represents each SAPT observable.

To quantify the computational cost of their methodology, the team provides resource estimates in terms of the required number of logical qubits and Toffoli gates to execute their algorithm for a range of benchmark molecules. They also take into account the cost of the eigenstate preparation and the cost of block encoding the SAPT observables.

How Does the Quantum Algorithm Work?

The quantum algorithm developed by the team estimates interaction energies at the first-order SAPT level with a Heisenberg-limited scaling. This is achieved by exploiting a high-order tensor factorization and block-encoding technique that efficiently represents each SAPT observable. The algorithm is designed to be executed on a fault-tolerant quantum computer, which is expected to provide speedups for systems where classical computers cannot find an accurate solution.

The algorithm calculates the interaction energy, defined as the energy difference between two weakly interacting systems (monomers A and B) and the system in which the monomers interact (referred to as the dimer AB). While the so-called supermolecular approach calculates the interaction energy by combining the results of three separate energy calculations, the team’s SAPT approach computes the interaction energy directly as an observable estimation task by decomposing the interaction energy in terms of physically interpretable quantities such as the electrostatic exchange and dispersion and induction energy contributions.

What are the Practical Applications of the Quantum Algorithm?

The quantum algorithm for SAPT has practical applications in molecules and materials design for polymers, catalysts, batteries, and drugs. The components of SAPT play a pivotal role in the characterization and featurization of intermolecular interactions between two weakly interacting subsystems.

The team performed the resource estimation for a heme and artemisinin complex as a representative large-scale system encountered in drug design. This highlighted the performance of their algorithm in this new benchmark study and discussed possible bottlenecks that may be improved in future work.

What are the Challenges and Future Work?

While the team’s quantum algorithm for SAPT presents a significant advancement in quantum chemistry, there are still challenges to be addressed. The scientific literature has been lacking an in-depth study of the computational cost of calculating the SAPT components on a fault-tolerant quantum computer.

The team’s future work will focus on improving possible bottlenecks in the algorithm’s performance. They also aim to further optimize the computational cost of their methodology, taking into account the cost of the eigenstate preparation and the cost of block encoding the SAPT observables.

What is the Significance of this Research?

This research represents a significant step forward in the field of quantum chemistry. The development of a fault-tolerant quantum algorithm for SAPT allows for the efficient computation of observables beyond total energy, a key challenge in the field.

The team’s work provides a guide for calculating this observable on a fault-tolerant quantum computer, presenting a methodology that optimizes the required computational resources. This research not only advances our understanding of quantum algorithms but also has practical applications in molecules and materials design, particularly in the field of drug design.