Prof. Joseph Emerson has garnered an Early Researcher Award from the Ministry of Research and Innovation for his work on assessing and improving quantum information processing devices. Emerson is developing methods for assessing and improving the performance of quantum information devices in the presence of noise, a key step toward making large-scale quantum information processors viable. His work on randomized methods of noise estimation has shown great promise as a practical tool that experimentalists can use to diagnose and potentially correct sources of noise affecting the performance of quantum computers.
Achieving durable control of quantum systems is a prerequisite to achieving practically usable quantum computers. While prototype quantum computers have been realized, using laser-cooled atoms and superconducting circuits, for example, the systems are extremely sensitive to noise, or outside forces. At present, only a few simple operations can be performed before quantum coherence (and thus control) is lost to noise. In order to figure out how to achieve better control, it is crucial to pinpoint the source and nature of the noise, as first step to develop ways of preventing or minimizing it.
Quantum process tomography is a well-known method for full characterization of the noise, but is infeasible with large quantum systems, since it involves analysis of all the parameters of the system. In a 10 qubit system, for example, this would mean measuring 2 to the power of 40 parameters! It would be like taking every single part of your car apart down to the bolts and checking each piece to find out if there's any problem with the car, says Emerson. But what if there was a way to diagnose noise more efficiently? In a paper published in Science in 2003, Emerson and collaborators demonstrated that it was possible to efficiently generate random transformations of a quantum system.
In more recent work, also published in Science, Emerson and collaborators built on that earlier work and showed that by sampling from certain subsets of the possible random transformations, called asymmetry class, and then aggregating and averaging the results, an accurate picture of the dominant noise mechanisms affecting a system could be determined. In a 10 qubit system, for example, this method would reduce the size of the analysis to a few thousand tests, far less than the 2 to the power of 40 needed with quantum process tomography.
The tests generate a noise signature. that can function as a diagnostic tool. Emerson says, "Once you have this information, it tells the experimentalists that the system is failing in this way, so we need to focus on correcting this type of problem." Looking down the road, to when we have larger quantum information processors, this method will also indicate the best choices for error correction procedures. In the paper cited above, Raymond Laflamme's experimental group successfully implemented the theory in a three-qubit test system.
The real beauty of this approach is that it will be increasingly useful as quantum information processing systems get bigger. With his Early Researcher Award, Emerson will continue to develop the theory of symmetrized noise estimation. He is particularly interested in understanding how to obtain more information about memory effects in noise, the spatial distribution of error locations, and the presence and location of noiseless subsystems. Ultimately, these methods will help physicists and engineers develop robust quantum computing devices.