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Magnetic resonance researchers have overcome exponential scaling challenges through advanced simulation software and elegant notation. Future advancements will leverage computers for experiment design, optimal control, and machine learning in data processing.

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Area of Science:

  • Physics
  • Chemistry
  • Computer Science

Background:

  • Reflections on the evolution of magnetic resonance theory and simulation.
  • Personal insights from twenty years of developing simulation code.

Purpose of the Study:

  • To highlight key achievements in magnetic resonance theory and simulation.
  • To discuss the future impact of computational methods in magnetic resonance.

Main Methods:

  • Review of advancements in combating exponential scaling in simulations.
  • Discussion of the development of powerful and general simulation software.
  • Emphasis on the return to elegant notation in theoretical frameworks.

Main Results:

  • Successful strategies to overcome exponential scaling in magnetic resonance simulations.
  • Availability of robust and versatile simulation software.
  • Resurgence of clear and concise notation in the field.

Conclusions:

  • The future of magnetic resonance is increasingly intertwined with computational power.
  • Key future applications include simulation-guided experiment design, real-time optimal control, and machine learning for data analysis.