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quant-ph2025

Machine Learning for Arbitrary Single-Qubit Rotations on an Embedded Device

Madhav Narayan Bhat, Marco Russo, Luca P. Carloni +4

Here we present a technique for using machine learning (ML) for single-qubit gate synthesis on field programmable logic for a superconducting transmon-based quantum computer based…

quant-ph2025

Fast Machine Learning for Quantum Control of Microwave Qudits on Edge Hardware

Flor Sanders, Gaurav Agarwal, Luca Carloni +3

Quantum optimal control is a promising approach to improve the accuracy of quantum gates, but it relies on complex algorithms to determine the best control settings. CPU or GPU-bas…

quant-ph2025

Benchmarking the performance of a high-Q cavity qudit using random unitaries

Nicholas Bornman, Tanay Roy, Joshua A. Job +4

High-coherence cavity resonators are excellent resources for encoding quantum information in higher-dimensional Hilbert spaces, moving beyond traditional qubit-based platforms. A n…

quant-ph2025

End-to-end workflow for machine learning-based qubit readout with QICK and hls4ml

Giuseppe Di Guglielmo, Botao Du, Javier Campos +10

We present an end-to-end workflow for superconducting qubit readout that embeds co-designed Neural Networks (NNs) into the Quantum Instrumentation Control Kit (QICK). Capitalizing…

quant-ph2025

Inference of response functions with the help of machine learning algorithms

Doga Murat Kurkcuoglu, Alessandro Roggero, Gabriel N. Perdue +1

Response functions are a key quantity to describe the near-equilibrium dynamics of strongly-interacting many-body systems. Recent techniques that attempt to overcome the challenges…