Quantum Characterization of Intermediate Scale Systems (QCISS)


Funding Opportunity ID: 323083
Opportunity Number: W911NF20S0004
Opportunity Title: Quantum Characterization of Intermediate Scale Systems (QCISS)
Opportunity Category: Discretionary
Opportunity Category Explanation:
Funding Instrument Type: Cooperative Agreement
Procurement Contract
Category of Funding Activity: Science and Technology and other Research and Development
Category Explanation:
CFDA Number(s): 12.431
Eligible Applicants: Public and State controlled institutions of higher education
Nonprofits having a 501(c)(3) status with the IRS, other than institutions of higher education
Nonprofits that do not have a 501(c)(3) status with the IRS, other than institutions of higher education
Private institutions of higher education
For profit organizations other than small businesses
Small businesses
Additional Information on Eligibility:
Agency Code: DOD-AMC
Agency Name: Department of Defense
Dept of the Army — Materiel Command
Posted Date: Dec 16, 2019
Close Date: Mar 17, 2020
Last Updated Date: Dec 16, 2019
Award Ceiling: $0
Award Floor: $0
Estimated Total Program Funding:
Expected Number of Awards:
Description: The U.S. Army Research Office (ARO) in partnership with the National Security Agency (NSA) is soliciting proposals for research in Quantum Characterization of Intermediate Scale Systems (QCISS). The goal of the BAA is to develop efficient and practical protocols and techniques that allow Quantum Characterization, Verification, and Validation (QCVV) of larger systems with direct relevance to Fault Tolerant Quantum Computing (FTQC), and to demonstrate these protocols on intermediate-scale systems. In this BAA, intermediate-scale refers to systems of size 10-20 qubits and larger systems greater than 20 qubits. Proposals are sought to develop reliable, efficient, and scalable protocols for evaluating intermediate-scale quantum systems and selectively characterizing only the subset of information relevant to FTQC. These new methods are sought as the next advances that will empower the quantum computing community to reliably interpret and evaluate emerging larger-scale quantum systems, and not merely a continuation of work applicable to one or two-qubit QCVV. The program success criterion is to identify the subset of information needed to characterize, verify, and validate a system’s behavior relevant for FTQC and create a suite of procedures for measuring that informationQuantum computing research has reached an exciting phase where controllable multi-qubit systems are becoming available across a number of venues, including academic laboratories, industry offerings, and even on the cloud. Demonstrations of progressively more sophisticated algorithms are occurring, and achieving ‘quantum advantage’ seems to be on the horizon. In order to evaluate and continue to improve quantum hardware, relevant protocols must be identified and used to characterize, verify, and validate the performance of these intermediate-scale quantum processing systems. However, QCVV of these increasingly complex quantum systems remains a challenge. The challenge being that as the number of qubits in a quantum system increases, the Hilbert space that defines the system grows exponentially, and the resources needed for complete characterization correspondingly grows exponentially. These resource limitations are already being encountered in small quantum systems of about 10 qubits. For continued progress, an additional challenge to overcome is to be able to identify a smaller subset of parameters that allow system performance to be predicted and understood for applications of interest without the need for full characterization.Two categories of proposals are sought for this BAA. The first category seeks proposals that integrate theoretical and experimental research to fully identify and address the challenges of QCVV for intermediate-scale quantum systems. The second category seeks theoretical research that may significantly advance QCVV for intermediate-scale quantum systems through novel approaches that retire a set of key challenges.
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