  Advancements in quantum computing underscore the critical need for
sophisticated qubit readout techniques to accurately discern quantum states.
This abstract presents our research intended for optimizing readout pulse
fidelity for 2D and 3D Quantum Processing Units (QPUs), the latter coupled with
Superconducting Radio Frequency (SRF) cavities. Focusing specifically on the
application of the Least Mean Squares (LMS) adaptive filtering algorithm, we
explore its integration into the FPGA-based control systems to enhance the
accuracy and efficiency of qubit state detection by improving Signal-to-Noise
Ratio (SNR). Implementing the LMS algorithm on the Zynq UltraScale+ RFSoC Gen 3
devices (RFSoC 4x2 FPGA and ZCU216 FPGA) using the Quantum Instrumentation
Control Kit (QICK) open-source platform, we aim to dynamically test and adjust
the filtering parameters in real-time to characterize and adapt to the noise
profile presented in quantum computing readout signals. Our preliminary results
demonstrate the LMS filter's capability to maintain high readout accuracy while
efficiently managing FPGA resources. These findings are expected to contribute
to developing more reliable and scalable quantum computing architectures,
highlighting the pivotal role of adaptive signal processing in quantum
technology advancements.
