Researchers at the Pritzker School of Molecular Engineering (PME) and the Department of Chemistry at the University of Chicago are investigating the prospect of employing a quantum computer to solve atomic calculations in electronic structures with a complex molecule.
If the molecule is tiny and straightforward, quantum mechanical equations can be used to calculate the interactions between the atoms that make up the molecule or solid materials. However, the computational time required to solve these equations is prohibitive for complex molecules and materials, despite their crucial importance in fields such as materials engineering and drug creation. Quantum computers, then, can play a part in speeding up the calculation.
Co-author Giulia Galli called it “an exciting step towards using quantum computers to tackle challenging problems in computational chemistry.” The project was conducted by Marco Govoni, a Staff Scientist at Argonne and a Member of the UChicago Consortium for Advanced Science and Engineering (CASE).
Solving complex equations that determine how electrons interact and modelling how several probable structures compare to each other in terms of their total energy level are required to predict a material’s electronic structure.
Quantum computers can tackle some problems more rapidly and readily than traditional computers because they store information in qubits that can exist in the superposition of states. Whether quantum computers can solve the electronic structure problem of complex materials has been a heated dispute among computational chemists. However, current-day quantum computers are still somewhat small and yield noisy results.
Galli and her co-workers questioned if they could make any headway in developing the fundamental quantum computing methods needed to solve electrical structure issues on quantum computers despite these limitations.
“The question we wanted to address is what is possible to do with the current state of quantum computers,” said Govoni. We wondered if quantum computers may help solve fascinating problems in materials science, even if their answers were incoherent.
The team used U.S. tech company quantum computers in a hybrid simulation approach they developed. Their method involves performing some calculations with a small number of qubits (between four and six) and then running those results via a classical computer for further processing.
Benchen Huang, a graduate student at the Galli Group and the paper’s first author, explained: “We designed an iterative computational process that takes advantage of the strengths of both quantum and conventional computers.”
Many simulations run yielded accurate electronic structures for many spin defects in solid-state materials. In addition, the group developed a novel error mitigation strategy to deal with the quantum computer’s natural noise and guarantee the precision of the outputs.
For now, conventional computers can already solve the electrical structures that were solved using the novel quantum computational technique. Thus, whether a quantum computer can outperform a traditional one at solving electrical structure issues is still being determined. The findings from the new approach open the door for quantum computers to tackle more intricate chemical structures.
Compared to traditional computers, “we think we might have an advantage when we scale this up to 100 qubits,” Huang added. But as they say, “Only time will tell.”
The team hopes to expand on their current work by applying it to a broader range of electrical challenges, including molecules in the presence of solvents and materials in excited states.
The study used new computational methods published in the online version of the Journal of Chemical Theory and Computation. The Midwest Integrated Centre for Computational Materials (MICCoM) and the Department of Energy’s (DOE) Centre for Quantum Information Science Research at Argonne (Q-NEXT) funded the effort.
