Quantum Computers and their application to Chemistry Simulation

Quantum computers have the potential to gain a quantum advantage, allowing them to solve problems that classical computers have never been able to solve. A quantum computer’s computing capacity grows exponentially as the number of qubits it contains increases. With this, research on quantum applications has always been recognized. Now, scientists have executed the largest chemistry simulations involving quantum computers through the use of Google’s Sycamore quantum processor. They used a novel way to combat the noise that is common in quantum circuits.

 “we can sometimes get away with more noise, we’ve already blown past the largest VQE that folks have ever managed to perform, and we think that we can go significantly larger, even on the noisy quantum computers we have today.

William Huggins, a quantum physicist at Google Quantum AI in Mountain View, Calif.

Quantum computers may have a near-term application in chemistry, such as simulating molecular processes to provide insight into next-generation batteries or new pharmaceuticals. As molecules become larger, performing these kinds of simulations becomes progressively more complex, which can be an overwhelming barrier for traditional computing but one that quantum computers may be able to handle.

On Google’s 53-qubit quantum computer, scientists used up to 16 qubits to determine the ground state of molecules, the state in which they have the least amount of energy. The number of electrons in a molecule and the trajectories these electrons take as they orbit a nucleus determine the molecule’s ground state. The work was reported in Nature, but the work was nicely summarised in an article by the IEEE.

H4, molecular nitrogen, and solid diamond were all simulated by the researchers. There were as many as 120 orbitals involved, which are the patterns of electron density created by one or more electrons in atoms or molecules. These are the largest quantum computer-assisted chemistry simulations ever undertaken.

In fact, we provided evidence in the paper that, even for our largest experiments, the noise on the chip wasn’t the limiting factor, rather, we weren’t ambitious enough with the design of the circuits that approximated the ground state. This tells us that we have a good shot of scaling up our current approach further even without developing new theoretical tools, and that’s a real beacon of hope given how hard it can be to perform accurate calculations of quantum chemistry on a noisy device.

Joonho Lee, a quantum physicist at Columbia University, in New York City. 

The majority of this fermionic quantum Monte Carlo simulation is handled by a classical computer. The quantum computer enters the picture during the final, most computationally demanding step: calculating the discrepancies between the quantum computer’s and the classical computer’s estimates of the ground state.

We’ll make enough progress that attacking problems that pose a challenge for classical algorithms becomes practical,

Still, at the end of the day, we expect it to be extremely challenging to get a practical advantage for quantum chemistry using the noisy quantum computers that we have today, or even tomorrow.

William Huggins, a quantum physicist at Google Quantum AI in Mountain View, Calif.

The previous record for quantum computing chemical simulations used 12 qubits and a hybrid technique known as a variational quantum eigensolver (VQE), which has a variety of drawbacks and takes longer to execute and simulate measurements with a very precise answer when compared to this new hybrid technique. It also requires very little noise in quantum circuits in order to get very precise estimates of ground states, while the new hybrid technology does not.

The newly developed technique produced results that were nearly as accurate as of the best current classical method.

As we make progress on developing and understanding new algorithms, we’re also expecting that new advancements in the hardware, and the software that controls it, will keep making our job easier.

Joonho Lee, a quantum physicist at Columbia University, in New York City. 

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