Quantum computers are beginning to demonstrate interesting (albeit small) proof of principle calculations in optimization, machine learning, and quantum chemistry. These calculations are limited by both number of qubits and by the quality of the qubits. The information in the qubits decays away with a characteristic coherence time, limiting the total number of gate operations (and, therefor, complexity of algorithms) which can be run on the systems. I will describe different methods for dealing with this noise, beginning from standard quantum error correction techniques. I will also describe recent work I have been doing attempting to recover quantum information without an overhead in number of qubits, showing results in both simulation and on "Agave", Rigetti's 8 qubit quantum computer.
 

Bio:

Matthew Otten received his PhD from Cornell University in 2017, working with Cyrus Umrigar. While a graduate student, he worked at both Argonne National Laboratory (working with Misun Min of MCS and Stephen Gray of NST) and Lawrence Livermore National Laboratory, as a Livermore Graduate Scholar working with Miguel Morales.