Magnetic Field Fingerprinting of Integrated-Circuit Activity with a Quantum Diamond Microscope
Abstract
Current density distributions in active integrated circuits result in patterns of magnetic fields that contain structural and functional information about the integrated circuit. Magnetic fields pass through standard materials used by the semiconductor industry and provide a powerful means to fingerprint integrated-circuit activity for security and failure analysis applications. Here, we demonstrate high spatial resolution, wide field-of-view, vector magnetic field imaging of static magnetic field emanations from an integrated circuit in different active states using a quantum diamond microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (N-V) quantum defects near the surface of a transparent diamond substrate placed on the integrated circuit to image magnetic fields. We show that QDM imaging achieves a resolution of approximately 10μm simultaneously for all three vector magnetic field components over the 3.7×3.7mm² field of view of the diamond. We study activity arising from spatially dependent current flow in both intact and decapsulated field-programmable gate arrays, and find that QDM images can determine preprogrammed integrated-circuit active states with high fidelity using machine learning classification methods.
Additional Information
© 2020 American Physical Society. Received 24 March 2020; revised 24 May 2020; accepted 11 June 2020; published 31 July 2020. We thank Ben Le for FPGA development; Adam Woodbury, Jeff Hamalainen, Maitreyi Ashok, Connor Hart, David Phillips, Greg Lin, CNS staff, Rebecca Cheng, and Amirhassan Shams-Ansari for helpful discussions and support; Raisa Trubko and Roger Fu for assistance on early measurements; Patrick Scheidegger and Raisa Trubko for work applying GPUfit to the analysis; Edward Soucy, Brett Graham, and the Harvard Center for Brain Science for technical support and fabrication assistance. This project was fully funded by the MITRE Corporation through the MITRE Innovation Program. R.L.W. acknowledges support from the Quantum Technology Center (QTC) at the University of Maryland. P.K. acknowledges support from the Sandia National Laboratories Truman Fellowship Program, which is funded by the Laboratory Directed Research and Development (LDRD) Program at Sandia National Laboratories. N-V diamond sensitivity optimization pertinent to this work was developed under the DARPA DRINQS program (Grant No. D18AC00033). This work was performed in part at the Center for Nanoscale Systems (CNS), a member of the National Nanotechnology Coordinated Infrastructure Network (NNCI), which is supported by the National Science Foundation under NSF Grant No. 1541959. CNS is part of Harvard University.Attached Files
Published - PhysRevApplied.14.014097.pdf
Accepted Version - 2004.03707.pdf
Supplemental Material - NVIC_Supplemental.pdf
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Additional details
- Eprint ID
- 105057
- Resolver ID
- CaltechAUTHORS:20200821-091832077
- MITRE Corporation
- University of Maryland
- Sandia National Laboratories
- Defense Advanced Research Projects Agency (DARPA)
- D18AC00033
- NSF
- ECCS-1541959
- Harvard University
- Created
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2020-08-21Created from EPrint's datestamp field
- Updated
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2021-11-16Created from EPrint's last_modified field