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Area of Science:

  • Materials Science
  • Condensed Matter Physics
  • Computer Engineering

Background:

  • Digital computers use pseudo-random number generators, which lack true randomness.
  • Existing true random number generators (TRNGs) often rely on hard-to-control phase transitions.
  • There is a need for efficient and reliable hardware-based TRNGs.

Purpose of the Study:

  • To develop a novel, efficient, and controllable hardware true random number generator (TRNG).
  • To leverage the spin crossover regime in LaCoO3 for stochasticity.
  • To demonstrate the superiority of spin crossover-based TRNGs over traditional phase transition methods.

Main Methods:

  • Developed a TRNG utilizing self-oscillations in LaCoO3 within its spin crossover regime.
  • Electrically biased the LaCoO3 material to control the spin crossover.
  • Employed phase field modeling to understand the stochasticity generation mechanism.
  • Validated the TRNG by probabilistically solving the NP-hard max-cut problem on a memristor crossbar array.

Main Results:

  • The LaCoO3-based TRNG passed all standard tests for true stochasticity.
  • The new TRNG requires fewer components compared to previous hardware TRNGs.
  • Spin crossovers were shown to be more effective for generating true stochasticity than traditional phase transitions.
  • The TRNG achieved superior solution quality for the max-cut problem compared to software-based randomness.

Conclusions:

  • LaCoO3's spin crossover regime provides a robust and efficient mechanism for hardware true random number generation.
  • This novel TRNG offers advantages in component count, efficiency, and controllability.
  • The demonstrated application in solving complex computational problems highlights the practical potential of this TRNG technology.