At the Argonne National Laboratory, scientists explore the chances of resolving the electronic structures of complicated molecules with the help of a quantum computer.
Giulia Galli, Marco Govoni, and fellow researchers have explored the possibility of predicting the electronic structure of complex materials using a quantum computer, an advancement in fields from materials engineering to drug design. Image Credit: Galli Group
If one knows the atoms that form a specific molecule or solid material, the interactions between those atoms could be identified computationally by resolving quantum mechanical equations.
But solving such equations, crucial for fields from materials engineering to drug design, needs an exceedingly long computational time for complicated materials and molecules.
At present, scientists at the US Department of Energy’s (DOE) Argonne National Laboratory and the University of Chicago’s Pritzker School of Molecular Engineering (PME) and Department of Chemistry have used the chance to resolve such electronic structures by making use of a quantum computer.
The study makes use of a combination of new computational methods, which was reported online in the Journal of Chemical Theory and Computation. It was financially supported by Q-NEXT, a DOE National Quantum Information Science Research Center led by Argonne, and by the Midwest Integrated Center for Computational Materials (MICCoM).
“This is an exciting step toward using quantum computers to tackle challenging problems in computational chemistry,” stated Giulia Galli, who led the research with Marco Govoni, a staff scientist at Argonne and member of the UChicago Consortium for Advanced Science and Engineering (CASE).
A Computational Challenge
Forecasting the electronic structure of a material includes resolving complicated equations that identify the interaction of electrons, as well as modeling how several feasible structures compare to each other in their energy levels on the whole.
Contrary to traditional computers that have the potential to store information in binary bits, quantum computers make use of qubits that could exist in the superposition of states, thereby enabling them to resolve some issues in a more easy and rapid manner.
Ultimately, computational chemists have discussed if and when quantum computers might be able to handle the electronic structure issue of complicated materials better compared to conventional computers. But quantum computers available at present remain comparatively small and further produce noisy data.
Even with such weaknesses, Galli, along with her collaborators, wondered if they still could make advances in making the basic quantum computational techniques needed to resolve electronic structure issues on quantum computers.
The question we really wanted to address is what is possible to do with the current state of quantum computers. We asked the question: Even if the results of quantum computers are noisy, can they still be useful to solve interesting problems in materials science?
Marco Govoni, Staff Scientist and Member, UChicago Consortium for Advanced Science and Engineering, Argonne National Laboratory
An Iterative Process
A hybrid simulation process using IBM quantum computers was developed by the researchers. In their method, a small number of qubits—from four to six—execute part of the calculations, and the outcomes are then further processed with the help of a classical computer.
We designed an iterative computational process that takes advantages of the strengths of both quantum and conventional computers.
Benchen Huang, Study First Author and Graduate Student, Galli Group, Argonne National Laboratory
Following numerous iterations, the simulation process was capable of offering the proper electronic structures of various spin defects in solid-state materials. Besides, the team came up with a new error mitigation method to help control for the inherent noise produced by the quantum computer and guarantee the accuracy of the outcomes.
Hints at the Future
In the meantime, using a conventional computer, the electronic structures solved utilizing the new quantum computational approach could already be solved. Hence, the long-term debate of if a quantum computer could be superior to a classical one in resolving electronic structure issues that have not been settled yet.
The outcomes offered by the new method set the stage for quantum computers to fulfill highly complicated chemical structures.
When we scale this up to 100 qubits instead of 4 or 6, we think we might have an advantage over conventional computers. But only time will tell for sure.
Benchen Huang, Study First Author and Graduate Student, Galli Group, Argonne National Laboratory
The research team plans to keep enhancing and scaling up their method, as well as utilizing it to resolve different kinds of electronic issues, like molecules in the existence of solvents, materials, and molecules in excited states.
This study has been financially supported by the US Department of Energy National Quantum Information Science Research Centers as part of the Q-NEXT center and through the Midwest Integrated Center for Computational Materials (MICCoM). Headquartered at Argonne, MICCoM is funded by the DOE Office of Basic Energy Sciences.
Journal Reference
Huang, B., et al. (2023) Quantum Simulations of Fermionic Hamiltonians with Efficient Encoding and Ansatz Schemes. Journal of Chemical Theory and Computation. doi.org/10.1021/acs.jctc.2c01119.