Bayesian macromodeling for circuit level QCA design

Srivastava, S. and Bhanja, S. (2006) Bayesian macromodeling for circuit level QCA design. In: Nanotechnology, 2006. IEEE-NANO 2006. Sixth IEEE Conference on, 17-20 June 2006.

Full content URL: http://dx.doi.org/10.1109/NANO.2006.247559

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Abstract

We present a probabilistic methodology to model and abstract the behavior of quantum-dot cellular automata circuit(QCA) at “ circuit level” above the current practice of layout level. These macromodels provide input-output relationship of components (a set of QCA cells emulating a logical function) that are faithful to the underlying quantum effects. We show the macromodeling of a few key circuit components in QCA circuit, such as majority logic, lines, wire-taps, cross-overs, inverters, and corners. In this work, we demostrate how we can make use of these macromodels to abstract the logical function of QCA circuits and to extract crucial device level characteristics such as polarization and low-energy error state configurations by circuit level Bayesian model, accurately accounting for temperature and other device level parameters. We also demonstrate how this macromodel based design can be used effectively in analysing and isolating the weak spots in the design at circuit level itself.

Keywords:Bayesian methods, Design methodology, Logic circuits, Logic devices, Polarization, Probability distribution, Pulse inverters, Quantum cellular automata, Quantum dots, Quantum mechanics
Subjects:H Engineering > H611 Microelectronic Engineering
H Engineering > H610 Electronic Engineering
H Engineering > H612 Integrated Circuit Design
Divisions:College of Science > School of Computer Science
College of Science > School of Engineering
ID Code:10742
Deposited On:26 Jul 2013 10:14

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