So for quantum error correction, you must correct mistakes in bits that you aren’t allowed to copy or even look at too closely. It’s like proofreading while blindfolded. In the mid-1990s, researchers started proposing ways to do this using the subtleties of quantum mechanics, but quantum computers are just reaching the point where they can put the theories to the test.
The key idea is to make a logical qubit out of redundant physical qubits in a way that can check if the qubits agree on certain quantum mechanical facts without ever knowing the state of any of them individually.
Can’t Improve on the Atom
There are many proposed quantum error correction codes to choose from, and some are more natural fits for a particular approach to creating a quantum computer. Each way of making a quantum computer has its own types of errors as well as unique strengths. So building a practical quantum computer requires understanding and working with the particular errors and advantages that your approach brings to the table.
The ion trap-based quantum computer that Monroe and colleagues work with has the advantage that their individual qubits are identical and very stable. Since the qubits are electrically charged ions, each qubit can communicate with all the others in the line through electrical nudges, giving freedom compared to systems that need a solid connection to immediate neighbors.
“They’re atoms of a particular element and isotope so they're perfectly replicable,” says Monroe. “And when you store coherence in the qubits and you leave them alone, it exists essentially forever. So the qubit when left alone is perfect. To make use of that qubit, we have to poke it with lasers, we have to do things to it, we have to hold on to the atom with electrodes in a vacuum chamber, all of those technical things have noise on them, and they can affect the qubit.”
For Monroe’s system, the biggest source of errors is entangling operations—the creation of quantum links between two qubits with laser pulses. Entangling operations are necessary parts of operating a quantum computer and of combining qubits into logical qubits. So while the team can’t hope to make their logical qubits store information more stably than the individual ion qubits, correcting the errors that occur when entangling qubits is a vital improvement.
The researchers selected the Bacon-Shor code as a good match for the advantages and weaknesses of their system. For this project, they only needed 15 of the 32 ions that their system can support, and two of the ions were not used as qubits but were only needed to get an even spacing between the other ions. For the code, they used nine qubits to redundantly encode a single logical qubit and four additional qubits to pick out locations where potential errors occurred. With that information, the detected faulty qubits can, in theory, be corrected without the “quantum-ness” of the qubits being compromised by measuring the state of any individual qubit.
“The key part of quantum error correction is redundancy, which is why we needed nine qubits in order to get one logical qubit,” says JQI graduate student Laird Egan, who is the first author of the paper. “But that redundancy helps us look for errors and correct them, because an error on a single qubit can be protected by the other eight.”
The team successfully used the Bacon-Shor code with the ion-trap system. The resulting logical qubit required six entangling operations—each with an expected error rate between 0.7% and 1.5%. But thanks to the careful design of the code, these errors don't combine into an even higher error rate when the entanglement operations were used to prepare the logical qubit in its initial state.
The team only observed an error in the qubit's preparation and measurement 0.6% of the time—less than the lowest error expected for any of the individual entangling operations. The team was then able to move the logical qubit to a second state with an error of just 0.3%. The team also intentionally introduced errors and demonstrated that they could detect them.
“This is really a demonstration of quantum error correction improving performance of the underlying components for the first time,” says Egan. “And there's no reason that other platforms can't do the same thing as they scale up. It's really a proof of concept that quantum error correction works.”
As the team continues this line of work, they say they hope to achieve similar success in building even more challenging quantum logical gates out of their qubits, performing complete cycles of error correction where the detected errors are actively corrected, and entangling multiple logical qubits together.
“Up until this paper, everyone's been focused on making one logical qubit,” says Egan. “And now that we’ve made one, we're like, ‘Single logical qubits work, so what can you do with two?’”
Original story by Bailey Bedford
In addition to Monroe, Brown and Egan, the other coauthors of the paper are the following: JQI research scientist Marko Cetina; JQI graduate students Andrew Risinger, Daiwei Zhu and Debopriyo Biswas; Duke University physics graduate student Dripto M. Debroy; Duke University postdoctoral researchers Crystal Noel and Michael Newman; and Georgia Institute of Technology graduate student Muyuan Li.