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A Compact and Power-Efficient Noise Generator for Stochastic Simulations.

Haixiang Zhao1, Rahul Sarpeshkar2, Soumyajit Mandal3

  • 1Dept. of Electrical & Computer Engineering, University of Florida, Gainesville, FL 32611, USA.

IEEE Transactions on Circuits and Systems. I, Regular Papers : a Publication of the IEEE Circuits and Systems Society
|August 19, 2024
PubMed
Summary
This summary is machine-generated.

This study presents an adaptive noise generator circuit for simulating stochastic chemical kinetics on-chip. The novel circuit efficiently emulates random telegraph signals, offering a compact and power-saving solution for complex simulations.

Keywords:
Analog computingcytomorphic processorsnoise generatorstochastic simulations

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Area of Science:

  • Microelectronic Engineering
  • Computational Chemistry
  • Biophysics

Background:

  • Stochastic chemical kinetics simulations are crucial for understanding biological systems.
  • Existing methods often require significant computational resources or complex hardware setups.
  • On-chip simulation offers a promising avenue for efficient and localized modeling.

Purpose of the Study:

  • To develop an adaptive noise generator circuit for on-chip simulation of stochastic chemical kinetics.
  • To emulate the characteristics of random telegraph signals (RTS) with Poisson-distributed level transitions.
  • To provide a compact, power-efficient, and capacitor-free hardware solution.

Main Methods:

  • Utilized amplified Bipolar Junction Transistor (BJT) white noise.
  • Implemented adaptive low-pass filtering to shape the noise spectrum.
  • Designed a current-mode circuit in a 0.35 μm BiCMOS process.
  • Validated against the Gillespie stochastic simulation algorithm.

Main Results:

  • The circuit accurately emulates the power spectrum and autocorrelation of RTS.
  • Demonstrated excellent agreement with theoretical results across a 60 dB dynamic range.
  • Achieved significant reductions in layout area (73%) and power consumption (50%) compared to prior work.
  • Verified experimental results from a board-level implementation.

Conclusions:

  • The developed adaptive noise generator circuit is a highly efficient and compact solution for on-chip stochastic simulations.
  • This hardware-based approach offers substantial improvements in area and power efficiency.
  • The circuit's performance validates its suitability for modeling complex chemical kinetics in integrated systems.