The First Simulation Of Chemical Bonds On A Quantum Computer

  • Researchers used 4 qubits on a 20-qubit processor for simulating chemical bonds of molecular hydrogen and lithium hydride. 
  • This is the first-ever quantum simulation of energy bonds, performed on a system of trapped ions. 

Quantum simulator was first suggested by Richard Feynman. It aims to utilize controlled quantum evolutions to simulate other quantum systems that can solve tough problems in a variety of fields, including chemistry, physics and material science.

In order to enable quantum simulations with complexity level beyond the reach of traditional computers, different paths are being pursued to scale up universal quantum machine realized on platforms like superconducting qubits (spin orbitals) or trapped ions.

Recently, researchers at the University of Sydney and Institute for Quantum Optics and Quantum Information (Austria) explored a promising avenue to model chemical bonds and reactions using quantum computers. Let’s find out what exactly they did.

Simulating Energy Bonds

Even for advanced supercomputers, it’s very difficult to accurately model the basic chemistry. However, quantum machines could provide new ways to understand matter and solve complex problems in medicine, industrial chemistry and material science through simulations.

So far, ion-trap implementations of quantum simulations have been limited to working with single qubits only. Now, researchers have used 4 qubits on a 20-qubit processor to execute algorithms for simulating chemical bonds of molecular hydrogen and lithium hydride.

Why these molecules, you asked? Well, they are well-understood and could be simulated on a conventional computer. It enables researchers to verify the outcomes of quantum processors under development. They can look for errors, set benchmarks and plan key improvements.

In trapped ion qubit systems, each qubit can be arbitrarily entangled with others. Thus, part of the simulation can be obtained in a single operation instead of series of concatenated processes.

This could be a plus point for simulating chemical processes in multidimensional (over 100) space, which will be needed for simulating complex molecules, such as caffeine and ammonia.

Reference: Physical Review X | doi:10.1103/PhysRevX.8.031022 | University of Sydney 

In this research, rather than focusing on the largest or most precise simulation till date, they emphasized on what could possibly go unplanned in a variational quantum eigensolver (a quantum/classical hybrid algorithm for reducing the experimental overhead of phase estimation).

A quadrupole ion trap used in the experiment | Credit: IQOQI / M.R. Knabl

By using such efficient, ever-improving algorithms combined with error-mitigation methodologies, researchers could achieve reasonably accurate quantum simulations of chemical reactions with tens of qubits in the near future.

Future Applications

By observing multiple ways of encoding the chemistry problem, they are trying to minimize errors in quantum computers in order to develop a useful quantum machine that could be used in real-time applications.

Since quantum computing is in its early stage, it’s quite unclear what kind of problems they will solve efficiently in the future. Most experts believe that this emerging technology would have most beneficial applications in quantum chemistry.

By quantum chemistry, we mean complex energy bonds and reactions of molecules, which are beyond the limits of today’s fastest supercomputer. By modeling and analyzing these processes on quantum machines, researchers expect to uncover low-energy paths for chemical reactions, enabling designs of new catalysts.

Read: The First Simulation of Atomic Nucleus On a Quantum Computer

This could have a huge impact on chemical industries like fertilizer production. Other feasible applications include development of advanced batteries and organic solar cells via enhanced materials.

Written by
Varun Kumar

I am a professional technology and business research analyst with more than a decade of experience in the field. My main areas of expertise include software technologies, business strategies, competitive analysis, and staying up-to-date with market trends.

I hold a Master's degree in computer science from GGSIPU University. If you'd like to learn more about my latest projects and insights, please don't hesitate to reach out to me via email at [email protected].

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