Andrew J. Landahl

Brief announcement: the impact of classical electronics constraints on a solid-state logical qubit memory

We present and analyze an architecture for a logical qubit memory that is tolerant of faults in the processing of silicon double quantum dot (DQD) qubits. A highlight of our analysis is an in-depth consideration of the constraints faced when integrating DQDs with classical control electronics.

Implications of electronics constraints for solid-state quantum error correction and quantum circuit failure probability

In this paper we present the impact of classical electronics constraints on a solid-state quantum dot logical qubit architecture. Constraints due to routing density, bandwidth allocation, signal timing and thermally aware placement of classical supporting electronics significantly affect the quantum error correction circuits error rate (by a factor of ~3–4 in our specific analysis). We analyze one level of a quantum error correction circuit using nine data qubits in a Bacon–Shor code configured as a quantum memory. A hypothetical silicon double quantum dot quantum bit (qubit) is used as the fundamental element. A pessimistic estimate of the error probability of the quantum circuit is calculated using the total number of gates and idle time using a provably optimal schedule for the circuit operations obtained with an integer program methodology. The micro-architecture analysis provides insight about the different ways the electronics impact the circuit performance (e.g. extra idle time in the schedule), which can significantly limit the ultimate performance of any quantum circuit and therefore is a critical foundation for any future larger scale architecture analysis.

ASCR Workshop on Quantum Computing for Science

This report details the findings of the DOE ASCR Workshop on Quantum Computing for Science that was organized to assess the viability of quantum computing technologies to meet the computational requirements of the DOE’s science and energy mission, and to identify the potential impact of quantum technologies. The workshop was held on February 17-18, 2015, in Bethesda, MD, to solicit input from members of the quantum computing community. The workshop considered models of quantum computation and programming environments, physical science applications relevant to DOEs science mission as well as quantum simulation, and applied mathematics topics including potential quantum algorithms for linear algebra, graph theory, and machine learning. This report summarizes these perspectives into an outlook on the opportunities for quantum computing to impact problems relevant to the DOE’s mission as well as the additional research required to bring quantum computing to the point where it can have such impact.