Begin forwarded message: From: Jacques J Carolan &lt;carolanj(a)mit.edu <mailto:carolanj@mit.edu>> Subject: Fwd: [iQuISE] Prof. Steve Flammia & the Fault Tolerance Threshold Date: March 8, 2017 at 3:39:59 PM EST To: &quot;sflammia(a)gmail.com <mailto:sflammia@gmail.com>" &lt;sflammia(a)gmail.com <mailto:sflammia@gmail.com>> All the best, Jacques Begin forwarded message: > From: Sara &lt;smouradi(a)mit.edu <mailto:smouradi@mit.edu>> > Date: 8 March 2017 at 10:03:43 GMT-5 > To: &lt;iquise-associates(a)mit.edu <mailto:iquise-associates@mit.edu>> > Subject: [iQuISE] Prof. Steve Flammia & the Fault Tolerance Threshold > > Hello all, > > This week Professor Steve Flammia will give a talk on how experimentally measured error rates can be related to the worst-case error rates for fault-tolerant thresholding. > > The talk will be in Rm 26-214 tomorrow (Thursday March 9th) at 12:00, with pizza served at 11:45, as always! > > Thank you, > iQuISE Leadership > > > iQuISE Seminar Series > Comparing Experiments to the Fault-Tolerance Threshold > > > THURSDAY, March 9th, 2017 > 11:45 AM - 12:45 PM, ROOM 26-214 > > > Achieving error rates that meet or exceed the fault-tolerance threshold is a central goal for quantum computing experiments, and measuring these error rates using randomized benchmarking is now routine. However, direct comparison between measured error rates and thresholds is complicated by the fact that benchmarking estimates average error rates while thresholds reflect worst-case behavior. These two can differ by orders of magnitude in the regime of interest. I will discuss how to facilitate comparison between the experimentally accessible average error rates and the worst-case quantities that arise in current threshold theorems by describing relations between the two for a variety of physical noise sources, including dephasing, thermal relaxation, coherent and incoherent leakage, as well as coherent unitary over and under rotation. The results indicate that it is coherent errors that lead to an enormous mismatch between average and worst case, and we quantify how well these errors must be controlled to ensure fair comparison between average error probabilities and fault-tolerance thresholds. Finally, I will describe how a recently introduced measure of coherent errors called the unitarity can sometimes be used to directly quantify the distance to the threshold based on data collected from randomized benchmarking experiments.