Phantom codes could help quantum computers avoid errors

Algorithms called ghost codes could help quantum computers run complex programs without errors, overcoming a major obstacle to making the technology more widely useful.

At first, some physicists doubted the usefulness of quantum computers because they expected the devices to be too prone to errors that are difficult to correct. Today, several types of quantum computers exist and have already been used for scientific discovery and exploration. Yet while progress has been made, researchers have not been able to completely eliminate the error problem.

Many popular error-correcting programs allow quantum computers to store information without errors, but face computational difficulties, says Shayan Majidy of Harvard University.

In search of a cure, he and his colleagues focused on calculations that include many calculation steps, making them time-consuming and inefficient to perform, and potentially leading to additional errors.

Quantum computers are made up of physical units called qubits, but these calculations involve logical qubits, or groups of qubits that share information to reduce error rates. To avoid computational errors, devices typically must manipulate logical qubits – for example, by firing lasers or microwaves at the physical qubits – in order to intrigue two or more of them or change their quantum properties.

Ghost codes allow many logical qubits to be entangled without any physical action being necessary – hence the name “ghost”. In practice, this means that the entire calculation would require fewer such actions, increasing its efficiency and reducing the number of possible errors.

Majidy and his colleagues used computer simulations to test ghost codes on two tasks: preparing a special qubit state often used in calculations and emulating a toy model of a quantum material. They found that, because it required less physical manipulation, their approach provided results up to 100 times more accurate than more conventional error correction programs.

Shadow codes can’t help with every quantum computing program, Majidy says, but they excel in situations where a calculation already requires a lot of entanglement. They don’t create entanglements out of thin air, he says, but rather take advantage of what already exists. “It’s not a free lunch. It’s just a lunch that was already there and we weren’t eating it,” he says.

Mark Howard, of the University of Galway in Ireland, says that choosing error-correcting code for a quantum computing task is like choosing armor: plate armor could offer more protection than chain mail, at the cost of being heavier and less flexible. Shadow codes offer flexibility, but just like chain mail, they also have drawbacks, such as requiring more qubits than some traditional approaches, Howard says. For this reason, they could be used for some targeted subroutines of quantum computing programs, but they are unlikely to be a complete solution to the error problems of quantum computers, he says.

Dominic Williamson, of the University of Sydney in Australia, says it remains an open question how competitive ghost codes can be with other error correction methods, some of which may depend on future developments in quantum computing hardware.

Majidy says his team is already working closely with colleagues who are building quantum computers from extremely cold atoms. He hopes that lessons learned from shadow codes, combined with insights into what a qubit can do in practice, will lead to a new strategy in which quantum computing programs are more specifically tailored to a particular task and implementation.