SBIR/STTR Research Award

SBIR Phase II: A Cloud-Based Development Framework and Tool Suite for Quantum Computing

Award identifier 3c19df61826d4e8fb0b45c04050d76fba4cfabe04cd25d428cfeaca1f9ce4322Awarding agency National Science Foundation

Award amount

$747,122

Program and phase

SBIR · Phase II

Award year

2018

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Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
QC WARE CORP.
Proposal award date
2018-04-01
Contract end date
2020-03-31
UEI
R4UQNKMZKTB3
Solicitation number
Not reported
Topic code
IT

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will to enable inexpensive access to quantum computing (QC) and to take the complexity out of the programming and application hosting tasks, which currently pose a major barrier to entry for potential users. QC technology is expected to disrupt significant portions of the high-performance computing environment for optimization problems, which has previously been characterized by slow and incremental performance improvements. This project would yield a platform that both increases the efficiency and lowers the cost of analyzing complex optimization problems, which could spur fast-paced innovation in wide areas of the economy that tackle such issues. This Small Business Innovation Research (SBIR) Phase II project addresses the need for a cloud-based platform for using QC technology. Early-generation quantum computers have been introduced by multiple hardware vendors. Despite advances in performance of QC processors, little effort has been directed toward developing programming environments and applications that can provide simple and inexpensive access to QC capabilities and that can exploit the power that QC systems will have in the near future. This project will develop a suite of front-end and back-end tools that efficiently transform high-level computing problems into formulations for circuit-model QC systems, abstracting away the physical low-level details and domain knowledge currently necessary to build QC applications. The project will further develop a set of applications in optimization, search, and machine learning. The proposed research will explore the best software tools and platform methods for integrating emerging QC capabilities into enterprise and research workflows by streamlining and making affordable the decomposition and formulation of real-world problems into implementations that run on quantum processors. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

4 SBIR/STTR records share this UEI (2017–2020). Reported award amounts total $1,169,029. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Defense, National Science Foundation

Agency intelligence

National Science Foundation

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