On July 2, the Intelligence Advanced Research Projects Activity (IARPA) released the following funding opportunity for the Logical Qubits (LogiQ) Program (Solicitation Number: IARPA-BAA-15-10). Proposals for the initial round of selections are due no later than 5:00pm Eastern on September 1, 2015.
IARPA is seeking innovative solutions for the Logical Qubits (LogiQ) Program. LogiQ intends to build a logical qubit from a number of imperfect physical qubits by combining high-fidelity multi-qubit operations with extensible integration. The LogiQ Program is envisioned to begin 1 February 2016 and end by 31 January 2021.
Current quantum computing systems have important limitations that hinder their path to fault-tolerant quantum computation. First and foremost, the overall performance of multi-qubit systems is inferior to the performance of the individual qubits. These physical qubits are susceptible to system noise and losses induced by their environment, insufficient operation fidelity, lack of error correction, poor feedback and dynamical control, and inadequate multi-qubit control. Success in building practical quantum computers hinges on the ability to combat environment-induced decoherence and errors in quantum gates. This can be effectively and extensibly achieved by innovations that encode physical qubits into a logical qubit.
The Logical Qubits (LogiQ) Program seeks to overcome the limitations of current multi-qubit systems, described in the previous paragraph, by building a logical qubit from a number of imperfect physical qubits. LogiQ envisions that program success will require a multi-disciplinary approach that increases the fidelity of quantum gates, state preparation, and qubit readout; improves classical control; implements active quantum feedback; has the ability to reset and reuse qubits; and performs further system improvements.
Additionally, LogiQ seeks a modular architecture design of two coupled logical qubits that creates a flexible and feasible path to larger systems. Modular designs facilitate the incorporation of next-generation advances with minimal constraints, while maintaining or improving performance.
Full information is available here.