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Quantum Control Optimization Methods

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0020618
Agency Tracking Number: 249682
Amount: $200,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 08c
Solicitation Number: DE-FOA-0002145
Timeline
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-02-18
Award End Date (Contract End Date): 2020-11-17
Small Business Information
1261 Oakmead Parkway
Sunnyvale, CA 94085-4040
United States
DUNS: 621683200
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Robert Kosut
 (415) 601-6287
 kosut@scsolutions.com
Business Contact
 Robert Kosut
Phone: (415) 601-6287
Email: kosut@scsolutions.com
Research Institution
 Princeton University
 Herschel Rabitz
 
87 Prospect Ave
Princeton, NJ 08544-2020
United States

 (609) 258-3917
 Nonprofit college or university
Abstract

Quantum information sciences started as a concept many years ago, transitioned to a subject of theoretical analysis, followed by experimental efforts mainly focused on controlling individual qubits Rather dramatically, the last couple of years have witnessed a significant milestone with the creation of nascent functioning quantum computers operating with tens of qubits Present quantum computers, referred to as noisy intermediate-scale quantum (NISQ) devices, operate under open-loop control without the benefit of error correction Thus, a critical need in the NISQ community is to obtain maximal performance from these early machines to enable them to function as a testbed for a host of potential applications The challenge addressed above translates to drawing on the best classical laboratory control resources, thereby assuring that gate operations are performed at the highest fidelity while simultaneously being robust to inevitable uncertainties in the device fabrication as well as noise from various sources The proposed university/industry STTR program will draw from the vast library of quantum control algorithms and software for control optimization developed in the university in order to create an integrated set of tools to meet the dual objectives of (a) computational design of reliable controls for NISQ devices, and (b) guiding their experimental implementation Thefocus of the Phase I effort is the creation of these individual software tools in a consistent format In doing so, the aim is to develop a software environment that can be interfaced in a synergistic fashion to guide each laboratory NISQ setup Such a tool will accelerate achieving optimal performance while drawing on the best features of computational control design and experimental implementation in a real time iterative fashion The synergistic capability of the software will take into account the particular characteristics of each device, including the presence of often unknown error sources in the laboratory setting

* Information listed above is at the time of submission. *

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