I-Corps: Translation Potential of Technology Enabling Confidential Quantum Computing
- Institution
- Yale University, CT
- Principal investigator
- Mark B Gerstein
- Funding
- $50K
- Duration
- 2026–2027
Moonbase score
Still being scored
Abstract
This I-Corps project is based on the development of a technology to securely use remote quantum hardware without exposing sensitive data. As quantum computing is primarily accessed through cloud-based platforms, data privacy will be one gating factor for adoption because organizations cannot safely share proprietary, regulated, or sensitive information with external quantum infrastructure. This challenge affects a wide range of industries, including healthcare, life sciences, financial services, defense, and advanced manufacturing, which may limiting the deployment of quantum computing across many high-value, high-impact applications. This technology addresses this challenge by providing a privacy layer that enables secure delegated and collaborative quantum computation while preserving data confidentiality. This may accelerate adoption of quantum technologies, enable secure collaboration across organizations, and help unlock scientific discovery, economic growth, and innovation across many industries. This I-Corps project utilizes experiential learning coupled with first-hand investigation of the industry ecosystem to assess the translation potential of a quantum confidential computing framework for secure cloud-based quantum computing. This technology introduces a quantum-native data representation, termed quantum composite states, which captures the statistical structure of a data cohort in a single privacy-preserving quantum object while preventing reconstruction or inference of individual-level information. Currently, existing privacy-preserving approaches introduce significant computational overhead or constrain the underlying computation. Quantum composite states provide universal representations that preserve useful information for a broad range of downstream analyses while maintaining the native structure and scalability of quantum computation. This framework may support secure delegated quantum computation on remote quantum hardware and privacy-preserving collaborative quantum computation across multiple institutions without requiring disclosure of raw data. 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.
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