A new quantum approach to solving the electronic structure of complex materials

(Nanowerk News) If you know the atoms that make up a given molecule or solid material, the interactions between those atoms can be determined computationally, by solving quantum mechanics equations — at least, if the molecules are small and simple. However, solving these equations, which are important for fields ranging from materials engineering to drug design, requires enormous computational time for complex molecules and materials.

Now, researchers 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 explored the possibility of solving these electronic structures using a quantum computer.

The research, which uses a new combination of computational approaches, is published online at Journal of Chemical and Computational Theory (“Fermionic Hamiltonian Quantum Simulation with Efficient Coding and Ansatz Schematics”). It is supported by Q-NEXT, the 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 towards using quantum computers to solve challenging problems in computational chemistry,” said Giulia Galli, who led the research with Marco Govoni, staff scientist at Argonne and member of the UChicago Consortium for Advanced Science and Engineering (CASE). Prof. Giulia Galli and co-researchers have explored the possibility of predicting the electronic structure of complex materials using quantum computers, an advance from materials engineering to drug design. (Image courtesy of Galli Group)

Computing challenges

Predicting the electronic structure of a material involves solving complex equations that determine how electrons interact, as well as modeling how the various possible structures compare to one another in their overall energy levels.

Unlike conventional computers which store information in binary bits, a quantum computer uses qubits that can exist in a superposition state, enabling it to solve certain problems more easily and quickly. Computational chemists have debated whether and when quantum computers will eventually be able to solve problems of the electronic structure of complex materials better than conventional computers. However, today’s quantum computers remain relatively small and produce noisy data.

Even with these drawbacks, Galli and his colleagues wondered if they could still make progress toward creating the basic quantum computing methods needed to solve the electronic structure problems of quantum computers.

“The question we really want to answer is what is possible with the current state of quantum computers,” said Govoni. “We asked the question: Despite the noisy results of quantum computers, could they still be useful for solving interesting problems in materials science?”

Iterative process

The researchers devised a hybrid simulation process, using an IBM quantum computer. In their approach, a small number of qubits — between four and six — do some of the computation, and the results are then further processed using a classical computer.

“We design an iterative computing process that harnesses the power of both quantum and conventional computers,” said Benchen Huang, a graduate student in the Galli Group and first author of the new paper.

After several iterations, the simulation process was able to provide the correct electronic structure of several spin defects in solid-state materials. In addition, the team developed a new error mitigation approach to help control the inherent noise generated by quantum computers and ensure the accuracy of the results.

Future hint

For now, electronic structures solved using new quantum computing approaches can already be solved using conventional computers. Therefore, the longstanding debate about whether quantum computers can be superior to classical computers in solving problems of electronic structure has not been resolved.

However, the results provided by the new method pave the way for quantum computers to deal with more complex chemical structures.

“When we scaled this down to 100 qubits instead of 4 or 6, we thought we might have an advantage over conventional computers,” said Huang. “But only time will tell.”

The research group plans to continuously improve and improve their approach, as well as use it to solve various types of electronic problems, such as molecules in the presence of a solvent, and molecules and materials in an excited state.