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A Fokker-Planck Solver to Model MTJ Stochasticity

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arxiv 2106.12304 v1 pith:ATZ7TMWB submitted 2021-06-23 cs.ET

Fernando García-Redondo , Pranay Prabhat , Mudit Bhargava This is my paper · ORCID
classification cs.ET
keywords modeldatafokker-planckswitchingworkaddressanalyticalbehavior
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Magnetic Tunnel Junctions (MTJs) constitute the novel memory element in STT-MRAM, which is ramping to production at major foundries as an eFlash replacement. MTJ switching exhibits a stochastic behavior due to thermal fluctuations, which is modeled by s-LLGS and Fokker-Planck (FP) equations. This work implements and benchmarks Finite Volume Method (FVM) and analytical solvers for the FP equation. To deploy an MTJ model for circuit design, it must be calibrated against silicon data. To address this challenge, this work presents a regression scheme to fit MTJ parameters to a given set of measured current, switching time and error rate data points, yielding a silicon-calibrated model suitable for MRAM macro transient simulation.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Magnetic Tunnel Junctions for Timekeeping in Intermittent Computing Systems

    cs.AR 2026-07 conditional novelty 7.0 of 10

    FLINT estimates power-off duration from the stochastic decay of MTJ arrays, reaching 15-minute range at ≤10% error with ~1 µJ per readout, constant across ranges.

  2. From sLLG to Fokker-Planck: Accurate WER Modeling for Non-Axisymmetric MRAM Devices

    cs.ET 2026-07 conditional novelty 6.0 of 10

    For non-axisymmetric STT/SOT MRAM devices, a 2D Fokker-Planck solver using central differencing matches 10^6-trajectory stochastic LLG write-error rates, while monotone schemes bias switching early.

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