DOE OSTI · 3391471
ML–Enabled FPGA Framework for Fast Quantum State Discrimination in Mid-Circuit Measurement Regimes
Abstract
Accurate and low-latency quantum state discrimination is essential for protocols involving mid-circuit measurement (MCM) and conditional feed-forward. In superconducting quantum systems, conventional readout pipelines transfer measurement data to host processors for post-processing, introducing millisecond-scale delays that far exceed qubit coherence times. To overcome this bottleneck, we present an in-situ machine learning (ML) inference engine implemented on an FPGA for real-time quantum state discrimination. Our design performs inference directly on digitized readout signals with 40 ns latency, supports both qubit and qutrit readout, and enables conditional operations without host-side intervention. This capability is critical for MCM and for feedback-driven protocols such as quantum error correction. We validate the system on superconducting transmon hardware, demonstrating robust discrimination fidelity across multiple qubit and qutrit channels. We further demonstrate conditional qutrit logic driven by FPGA-resident classification, highlighting the potential of low-latency ML-on-FPGA control for NISQ applications and scalable fault-tolerant quantum computing.
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Vora, Neel [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0009000204730150), Xu, Yilun [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:000000019284809X), Hashim, Akel [University of California, Berkeley, CA (United States)] (ORCID:0000000286110125), Fruitwala, Neelay [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000339004079), Nguyen, Nam [University of California, Berkeley, CA (United States)] (ORCID:0000000221892090), Goss, Noah [University of California, Berkeley, CA (United States)] (ORCID:0000000233779415), Balewski, Jan [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)] (ORCID:0000000218996526), Whaley, Birgitta [University of California, Berkeley, CA (United States)] (ORCID:0000000271644757), Siddiqi, Irfan [University of California, Berkeley, CA (United States)] (ORCID:0000000322001090), Nguyen, Vp [Univ. of Massachusetts, Amherst, MA (United States)] (ORCID:0000000180784463), Huang, Gang [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000232499315). 2026-06-22. ML–Enabled FPGA Framework for Fast Quantum State Discrimination in Mid-Circuit Measurement Regimes. https://doi.org/10.1145/3787109.3816383
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