Bringing molecular simulations a step further

Visualization of molecular simulations
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What can we do with the near-term quantum devices that we currently have? What are the benefits that they bring, and what is their future potential? Is it possible for the actual NISQ (Noisy Intermediate-Scale Quantum) devices to further advance the fields of material and drug discovery through complex molecular simulations and modelling that are difficult to generate on a classical computer?

These are some of the main topics on quantum scientists’ research agenda and a strong point of interest for Sayonee Ray, a post-doctoral fellow at the Center for Quantum Information and Control in New Mexico. After finishing her Ph.D. in theoretical physics, she started working at the interface between quantum information, quantum optics, and many-body physics. In an attempt to deepen the understanding of quantum systems from a theoretical point of view, Ray develops simulations and models of quantum systems, comparing their performance to that of classical computers.

Molecular simulation allows researchers across various fields to understand complex processes and principles; interactions that take place at an atomic level that are not always accessible via experiments (e.g., how molecules bind to their receptors – very helpful in the drug development process, the protein folding process, etc.)

Despite note being very robust yet and being somewhat prone to errors, the current quantum devices can already model molecular configurations. After accurately simulating a molecule for the first time in 2016 [1], Google managed to simulate a chemical reaction in 2020 [2].

These operations can already be easily done on a classical computer. In fact, researchers currently use traditional devices to check the accuracy of quantum results. Applications on current quantum devices are still in their infancy, still trying to catch up with operations that are already possible on a traditional machine. However, due to their specific way of functioning, once they scale up, it is expected that quantum computers will surpass classical devices in certain industries and for specific problems.

“Quantum computers are not going to replace classical computers entirely. They will be used in certain industries, for specific tasks, such as determining the molecular structure of a very complicated drug, or testing the interaction between different molecules.” 

Ray sees quantum computers as having tremendous potential in a broad array of areas, from biochemistry, engineering and material science to finance, medicine and pharma. However, she considers the quantum simulation of complex chemical systems as one of the most promising applications of this technology.

Yet many milestones still need to be crossed before this application becomes a reality. Not only does the quality of qubits need to be enhanced and the errors and noise decreased, but also the quality and efficiency of algorithms and software need to be improved.

“It is for all of us a learning process. Everybody is trying at the same time, on different levels and in different areas, so something is definitely going to happen.” 

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References

[1]O’Malley, P., Babbush, R., Kivlichan, I. et al., 2016. Scalable Quantum Simulation of Molecular Energies. Physical Review X, [online] 6(3). Available at: <https://journals.aps.org/prx/abstract/10.1103/PhysRevX.6.031007> [Accessed 16 September 2020]. 

[2]Rubin, N. and Babbush, R., 2020. Hartree-Fock on a superconducting qubit quantum computer. Science, [online] (6507), pp.1084-1089. Available at: <https://science.sciencemag.org/content/369/6507/1084> [Accessed 16 September 2020]. 

Molecular Simulations, Quantum Computing, quantum systems

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