• DocumentCode
    834608
  • Title

    Complete Monte Carlo model description of lumped-element RSFQ logic circuits

  • Author

    Fourie, Coenrad Johann ; Perold, Willem Jakobus ; Gerber, Hendrik Retief

  • Author_Institution
    Dept. of Electr. & Electron. Eng., Univ. of Stellenbosch, Matieland, South Africa
  • Volume
    15
  • Issue
    2
  • fYear
    2005
  • fDate
    6/1/2005 12:00:00 AM
  • Firstpage
    384
  • Lastpage
    387
  • Abstract
    Over the last decade, Monte Carlo simulations have emerged as the most useful way of predicting the yield of RSFQ circuits, as they consider all manufacturing tolerance effects on a circuit, and are not restricted to bias current variations. Here we finally present a comprehensive definition of layout-extracted Monte Carlo model creation for lumped-element Spice simulations-from the local and global values for inductance, resistance and junction area from statistical models, to the inclusion of parasitics, layer-to-layer variations, variations in the penetration depth, and capacitance and mutual coupling. Finally, the addition of bias current trimming to the simulations to compensate for most global variations is described, and comparative yield results listed.
  • Keywords
    Monte Carlo methods; SPICE; circuit simulation; integrated circuit layout; integrated circuit modelling; superconducting logic circuits; Monte Carlo model description; Monte Carlo simulations; RSFQ circuit models; Spice models; bias current trimming; bias current variations; comparative yield results; junction area; layer-to-layer variations; layout extraction; lumped-element RSFQ logic circuits; lumped-element Spice simulations; manufacturing tolerance effects; mutual coupling; penetration depth; statistical models; yield prediction; Circuit optimization; Circuit simulation; Circuit testing; Inductance; Logic circuits; Manufacturing processes; Monte Carlo methods; Parasitic capacitance; Predictive models; Virtual manufacturing; Layout extraction; Monte Carlo models; RSFQ circuit models; Spice models; yield prediction;
  • fLanguage
    English
  • Journal_Title
    Applied Superconductivity, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1051-8223
  • Type

    jour

  • DOI
    10.1109/TASC.2005.849856
  • Filename
    1439656