(HPC.Wire) A team of experimental physicists at the Advanced Quantum Testbed (AQT) at Lawrence Berkeley National Laboratory (Berkeley Lab) demonstrated an error characterization method—randomized benchmarking (RB)—on a superconducting qutrit quantum processor. Scientists have now tested this widely used error characterization method with qutrits. Their results were published at Physical Review Letters earlier this year, marking a significant milestone towards benchmarking the accuracy of qutrit-based quantum devices and identifying the barriers to overcome in future research.
Quantum processors usually operate on qubits – the quantum version of the classical bit of information with two states, usually labeled “0” and “1.” Qutrit makes use of an extra quantum state, “2,” increasing the quantity of information stored. Qutrit-based processors promise advantages over qubits at implementing specific algorithms due to increased storage and processing capacity. However, this extra quantum level increases complexity and makes the existing error-characterization methods unusable.
Error rates are currently a considerable problem for quantum computers, causing decoherence (loss of information) and, therefore, problems with the execution of quantum logic gates, which corrupt the results. A growing number of qubits or qutrits increases the propensity for errors, so finely describing these errors—error characterization—allows researchers to overcome them and design better algorithms and processors.
“We knew crosstalk was an issue for our qutrit processor, but now with RB, we can quantify its impact on our qutrit device. This allows us to compare it to a qubit-based architecture and try to find new ideas to minimize these effects and come up with better qutrit processors in the future,” noted Alexis Morvan, a postdoctoral researcher at AQT.
According to Morvan, this experimental demonstration leveraged key expertise from Berkeley Lab and UC Berkeley and built on previous multidisciplinary research at AQT on superconducting qutrits, enabling them to further explore a qutrit-based architecture and adapt the RB method to characterize the qutrit processor properly.