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Area of Science:

  • Spintronics
  • Nanomagnetism
  • Computational Science

Background:

  • Stochastic magnetic tunnel junctions (MTJs) are crucial for probabilistic computing.
  • Understanding the timescale of random telegraph noise (RTN) is key to optimizing MTJ performance.
  • Existing perpendicular easy-axis MTJs (p-MTJs) have slow RTN timescales, limiting their application.

Purpose of the Study:

  • To investigate the relaxation time of RTN in nanomagnets within stochastic MTJs.
  • To identify mechanisms governing RTN timescales in both p-MTJs and in-plane easy-axis MTJs (i-MTJs).
  • To demonstrate the potential for faster RTN in i-MTJs.

Main Methods:

  • Analytical and numerical calculations.
  • Utilizing the Landau-Lifshitz-Gilbert equation.
  • Applying the Fokker-Planck equation.

Main Results:

  • Revealed mechanisms governing RTN relaxation times in p-MTJs and i-MTJs.
  • Demonstrated that i-MTJs can achieve significantly faster RTN.
  • Achieved relaxation times as short as 8 nanoseconds in superparamagnetic i-MTJs with specific anisotropy properties.
  • This represents a speedup of over 5 orders of magnitude compared to typical p-MTJs.

Conclusions:

  • i-MTJs offer a pathway to substantially faster RTN.
  • The developed superparamagnetic i-MTJs are over 100 times faster than previously reported i-MTJs.
  • These findings provide a foundation for developing high-performance stochastic MTJs for probabilistic computers.