Data-driven synthesis of high-fidelity triaxial magnetic waveforms for quantum control

TL;DR

This paper introduces a data-driven method for synthesizing high-fidelity, arbitrary triaxial magnetic waveforms crucial for quantum control, using a FIR filter-based compensation model validated through experiments.

Contribution

It presents a novel, calibration-based approach to accurately generate complex magnetic waveforms by compensating amplifier-coil dynamics in the spectral range up to tens of kHz.

Findings

High waveform fidelity achieved in experiments

Effective compensation of amplifier-coil dynamics demonstrated

Capability to generate complex, sharp-transition magnetic sequences

Abstract

We present a system for generating arbitrary, triaxial magnetic waveforms with a spectral content spanning from DC to tens of kHz, a critical capability for quantum control and spin manipulation. To compensate for amplifier-coil dynamics, we implement a data-driven approach to identify a numerical compensation model. The method parametrizes the system response using a Finite Impulse Response (FIR) filter calibrated on the specific waveform to be generated. The application of a driving signal designed via frequency-domain inversion of the identified model enables the synthesis of complex field sequences with sharp transitions between static and single- or multi-frequency temporal segments. The work is validated with experimental results demonstrating waveform fidelity and transient performance, thereby showcasing the precision and feasibility of the method.