1. Magnetic Field Fingerprinting of Integrated Circuit Activity with a Quantum Diamond Microscope
- Author
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Pauli Kehayias, Amir Yacoby, Srujan Meesala, Evelyn Hu, Edlyn V. Levine, Nicholas Langellier, Ronald L. Walsworth, Matthew Turner, Thomas M. Babinec, Rachel Bainbridge, Marko Loncar, and Dan Walters
- Subjects
Physics - Instrumentation and Detectors ,Microscope ,General Physics and Astronomy ,FOS: Physical sciences ,02 engineering and technology ,Integrated circuit ,Applied Physics (physics.app-ph) ,engineering.material ,01 natural sciences ,Molecular physics ,law.invention ,Magnetic field imaging ,law ,0103 physical sciences ,Mesoscale and Nanoscale Physics (cond-mat.mes-hall) ,010306 general physics ,Physics ,Quantum Physics ,Condensed Matter - Mesoscale and Nanoscale Physics ,Image (category theory) ,Diamond ,Physics - Applied Physics ,Instrumentation and Detectors (physics.ins-det) ,021001 nanoscience & nanotechnology ,Magnetostatics ,3. Good health ,Magnetic field ,engineering ,0210 nano-technology ,Quantum Physics (quant-ph) ,Current density - Abstract
Current density distributions in active integrated circuits (ICs) result in patterns of magnetic fields that contain structural and functional information about the IC. Magnetic fields pass through standard materials used by the semiconductor industry and provide a powerful means to fingerprint IC activity for security and failure analysis applications. Here, we demonstrate high spatial resolution, wide field-of-view, vector magnetic field imaging of static (DC) magnetic field emanations from an IC in different active states using a Quantum Diamond Microscope (QDM). The QDM employs a dense layer of fluorescent nitrogen-vacancy (NV) quantum defects near the surface of a transparent diamond substrate placed on the IC to image magnetic fields. We show that QDM imaging achieves simultaneous $\sim10$ $\mu$m resolution of all three vector magnetic field components over the 3.7 mm $\times$ 3.7 mm field-of-view of the diamond. We study activity arising from spatially-dependent current flow in both intact and decapsulated field-programmable gate arrays (FPGAs); and find that QDM images can determine pre-programmed IC active states with high fidelity using machine-learning classification methods., Comment: 12 pages, 5 figures, 1 table
- Published
- 2020
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