Simulations with a quantum computer show the current limits of the technology

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When it comes to simulating molecules, quantum circuits cannot yet surpass classical ones.

E.Lucero/Google

get real The Google-made Sycamore chip with 53 quantum bits was used to explore “quantum advantage”: a feat in quantum computation that surpasses anything possible on classical computers. But how well does this type of device perform on common problems of real-world interest, such as: B. Quantum simulations of molecules and materials?get real The Google-made Sycamore chip with 53 quantum bits was used to explore “quantum advantage”: a feat in quantum computation that surpasses anything possible on classical computers. But how well does this type of device work… show more

Quantum computers promise to directly simulate systems controlled by quantum principles, such as molecules or materials, since the quantum bits are themselves quantum objects. Recent experiments have demonstrated the power of these devices to perform carefully selected tasks. But a new study shows that for problems of real interest, such as calculating the energy states of an atom cluster, quantum simulations are no more accurate than those of classical computers [1]. The results provide a benchmark for assessing how close quantum computers are to becoming useful tools for chemists and materials scientists.

Richard Feynman proposed the idea of ​​quantum computers in 1982 and suggested that they could be used to calculate the properties of quantum matter. Today, quantum processors with several hundred quantum bits (qubits) are available, and some can, in principle, represent quantum states that cannot be encoded in any classical device. The 53-qubit Sycamore processor developed by Google has demonstrated the potential to perform calculations in a matter of days that would take many millennia on current classical computers [2]. However, this “quantum advantage” is only achieved for selected computing tasks that play to the strengths of these devices. How well do such quantum computers fare in the everyday challenges that molecular and materials researchers actually want to solve?

Garnet Chan of the California Institute of Technology and his collaborators set out to answer this question by running simulations of a molecule and a material using a 53-qubit Google Weber processor based on Sycamore. “We didn’t expect to learn anything new chemically, given how complex these systems are and how good classical algorithms are,” says Chan. “The goal was to understand how well the Sycamore hardware performs for a physically relevant class of circuits with a physically relevant success metric.”

The team selected two problems of current interest without considering how well suited they might be to a quantum circuit. The first involves calculating the energy states of an 8-atom iron (Fe) and sulfur (S) cluster located in the catalytic core of the enzyme nitrogenase. This enzyme breaks strong bonds in nitrogen molecules as the first step in an important biological process called nitrogen fixation. Understanding the chemistry of this process could be valuable for the development of artificial nitrogen-fixing catalysts for the chemical industry.

catalytic core. At the catalytic center of the nitrogenase enzyme, which is responsible for removing nitrogen from the atmosphere (nitrogen fixation), sits a collection of iron (red) and sulfur atoms (yellow) that catalyze the splitting of nitrogen molecules. Researchers want to simulate this process on a quantum computer to develop artificial nitrogen fixation catalysts.catalytic core. In the catalytic center of the nitrogenase enzyme, which is responsible for removing nitrogen from the atmosphere (nitrogen fixation), sits a collection of iron (red) and sulfur atoms (yellow) that catalyze the splitting of nitrogen molecules… show more

Second, the team attempted to study the collective behavior of magnetic spins in the crystalline material alpha-ruthenium trichloride (

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-RuCl3), which is thought to adopt an exotic quantum phase called the spin liquid at low temperatures [3]. Studying such states is part of the larger project to study quantum phenomena in materials.

The electronic ground states and the low-energy excitations of the two systems are determined by how the electron spins of the atoms interact with each other. These spins could be encoded into individual qubits and their interactions simulated by coupling the qubits in circuits that reflect the structures of the two systems.

One of the main obstacles to accurate quantum simulations is noise — random errors both in switching the “gates” that perform quantum logic operations and in reading their output states. These errors add up and limit the number of gate operations a calculation can perform before noise dominates. The researchers found that simulations with more than 300 gates were overwhelmed by noise. But the more complex the system, the more gates are needed. For example, the Fe-S cluster has long-range interactions between spins; Such interactions require many gates to be accurately represented.

Because of these challenges, the simulations on the Weber chip were rather limited. For example, the simulations provided predictions for the energy spectra of the Fe-S cluster and the heat capacity of

𝛼

-RuCl3 pretty good – but only if the simulated systems were not too big. To the

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-RuCl3 the team could only obtain meaningful results for a very small 6-atom break in the crystal lattice; When they increased the size to just 10 atoms, the noise overwhelmed the output. And the limitations of gate operations meant that only about a fifth of Weber’s quantum resources could be used for computation. However, Chan and colleagues were able to increase this usage to half the resources when they switched to simulating a model system better suited to Weber’s specific circuit architecture.

Chan says it’s hard to imagine quantum circuits doing much better at problems like this until there are better ways to reduce noise or correct errors. (The schemes developed so far do not allow full quantum error correction.)

“These results are state-of-the-art and show the challenges that need to be addressed in terms of future device performance,” says University of Toronto’s Alán Aspuru-Guzik, a specialist in the use of quantum computing in chemistry and materials . But the capabilities have grown steadily since the first quantum computers in the 2000s, as this new work shows, he says. Peter Love, a quantum simulation specialist at Tufts University, Massachusetts, is optimistic about the results. “These results are both exciting and frightening,” he says. “They are absolutely amazing compared to our expectations in 2005, but they also show how much work we still have to do.”

– Phillip Ball

Philip Ball is a freelance science writer based in London. His latest book is The modern myths (University of Chicago Press, 2021).

references

  1. RN Tashigulov et al.“Simulation of models of challenging correlated molecules and materials on the Sycamore quantum processor”, PRX Quantum 3040318 (2022).
  2. F. Arut et al.“Quantum supremacy with a programmable superconducting processor”, Nature 574505 (2019).
  3. H.Li et al.“Huge phonon anomalies in the neighboring Kitaev quantum spin liquid
    𝛼

    RuCl3

    nat. commune 123513 (2021).


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