Optimizing EPR pulses for broadband excitation and refocusing

TL;DR

This paper develops and compares numerical methods for optimizing broadband EPR pulses, achieving improved excitation and refocusing performance over traditional hyperbolic secant pulses, with flexible solutions suitable for future constraints.

Contribution

It introduces neural network, Fourier series, and discrete time series parameterizations for pulse optimization, demonstrating their effectiveness and flexibility over conventional methods.

Findings

NN, FS, and DT methods outperform HS pulses in simulations

Multiple equivalent optimal solutions exist, allowing customization

Optimized pulses are robust to realistic distortions

Abstract

In this paper, we numerically optimize broadband pulse shapes that maximize Hahn echo amplitudes. Pulses are parameterized as neural networks (NN), nonlinear amplitude limited Fourier series (FS), and discrete time series (DT). These are compared to an optimized choice of the conventional hyperbolic secant (HS) pulse shape. A power constraint is included, as are realistic shape distortions due to power amplifier nonlinearity and the transfer function of the microwave resonator. We find that the NN, FS, and DT parameterizations perform equivalently, offer improvements over the best HS pulses, and contain a large number of equivalent optimal solutions, implying the flexibility to include further constraints or optimization goals in future designs.