Quantum Computed Simulations Show the Frontier of Technology

Quantum Computed Simulations Show Technology's Limits
Quantum Computing Simulations Show Technology's Frontier - 53 quantum bits make up Google's Sycamore chip, which is used to study "quantum advantage" - a quantum computing performance superior to classical computers. But how effective is such an apparatus at solving typical problems of practical importance, such as quantum simulations of molecules and materials?

When modeling molecules, quantum circuits still cannot beat classical circuits. Quantum bits are themselves quantum objects. Quantum computers promise to directly emulate systems governed by quantum laws, such as molecules or materials.

Recent tests have shown how effective these devices are at performing certain activities. But a recent study reveals that quantum simulations are no more precise than traditional computers in matters that raise practical concerns, such as determining the energy states of a cluster of atoms. The findings provide a benchmark for estimating how soon chemists and materials scientists can use quantum computers as tools.

In 1982, Richard Feynman proposed that quantum computers could be used to calculate properties of quantum matter. Currently, several hundred quantum bits (qubits) are available in quantum processors, and some of these could theoretically represent quantum states that cannot be encoded in any conventional device.

Google's 53-qubit Sycamore processor has demonstrated its ability to complete calculations in a matter of days that would take several centuries in conventional computers today. However, this "quantum advantage" can only be achieved for certain computational tasks that take advantage of these devices.

How effective are these quantum computers at solving the kinds of problems that scientists studying chemicals and materials face on a daily basis?

To answer this question, Garnet Chan of the California Institute of Technology and his team used simulations of a molecule and a material on a 53-qubit Google processor named Sycamore-based Weber. "We didn't expect to learn anything new chemically," says Chan, given how complex these systems are and how well traditional algorithms work.

The goal was to understand how well Sycamore hardware performs for a physically related class of circuits and a physically related success metric.

Without considering how well suited they would be to a quantum circuit, the team chose two hot topics.

In the first, the octatomic iron (Fe) and sulfur (S) clusters, which form the catalytic center of the nitrogenase enzyme, were calculated in terms of their energy states.

The first step in an important biological process known as nitrogen fixation, this enzyme breaks the strong bonds in nitrogen molecules. For the chemical industry, understanding the chemistry of this process can be useful in creating synthetic nitrogen-fixing catalysts.

The scientists also sought to determine the collective behavior of magnetic spins in alpha-ruthenium trichloride (α-RuCl3), a crystalline substance thought to transition into an unusual quantum phase known as spin fluid at low temperatures. The larger project investigating quantum phenomena in materials involves studying such states.

The interaction between the electron spins of atoms determines the fundamental electronic states and low-energy excitations of the two systems. By connecting qubits in circuits that mirror the architecture of the two systems, these spins can be recorded in a single qubit and their interactions recreated.

Noise is one of the main challenges to reliable quantum simulations. For example, random errors in switching "gates" that perform quantum logic operations and reading output states.

The number of port operations a computer can perform before noise takes control is limited by the accumulation of these errors.

The scientists discovered that noise was dominant in simulations with more than 300 gates. However, as the system becomes more complex, additional gates are required. For example, there are long-range interactions between spins in the Fe-S cluster; several gates are needed to adequately describe such interactions.

Simulations using the Weber chip were relatively limited as a result of these difficulties. For example, the simulations predicted the heat capacity of RuCl3 and the energy spectrum of the Fe-S cluster fairly accurately - but only if the simulated systems were not excessively large.

For α-RuCl3, the scientists found that they were able to obtain useful data for only a small 6-atom fraction of the crystal lattice; when they expanded the size to only 10 atoms, the output was drowned out by noise. Also, only one-fifth of Weber's quantum resources could be used for computation due to restrictions on gate operations.

When Chan and colleagues moved on to simulate a model system better suited to Weber's custom circuit layout, they were able to increase this utilization to use half the resources.

Chan claims it's hard to predict that quantum circuits will perform much better in such matters until better ways are found to reduce noise or correct errors. (Current techniques do not allow for comprehensive quantum error correction).

Alán Aspuru-Guzik of the University of Toronto, who specializes in applying quantum computing to chemistry and materials, believes these results represent cutting-edge technology and highlight the challenges that must be overcome for future devices to work as intended. But as this latest study shows, capabilities have evolved since the first quantum computers in the 2000s.

The results excite Peter Love, a quantum simulation expert at Tufts University in Massachusetts. Love says these discoveries are "both exciting and frightening." These are truly extraordinary compared to what we envisioned in 2005, but they also highlight how much more work remains.

Source: physics.aps.org/articles/v15/175

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