We have developed a parameter optimization tool, Monte Carlo Josephson simulator (MJSIM), for rapid single flux quantum (RSFQ) digital circuits based on a Monte Carlo yield analysis. MJSIM can generate a number of net lists for the JSIM, where all parameter values are varied randomly according to the Gaussian distribution function, and calculate the circuit yields automatically. MJSIM can also produce an improved parameter set using the algorithm of the center-of-gravity method. In this algorithm, an improved parameter vector is derived by calculating the average of parameter vectors inside and outside the operating region. As a case study, we have optimized the circuit parameters of an RS flip-flop, and investigated the validity and efficiency of this optimization method by considering the convergency and initial condition dependence of the final results. We also proposed a method for accelerating the optimization speed by increasing 3σ spreads of the parameter distribution during the optimization.

We have designed rapid single-flux-quantum (RSFQ) adder circuits using two different architectures: one is the conventional architecture employing globally synchronous clocking and the other is the data-driven self-timed (DDST) architecture. It has been pointed out that the timing margin of the RSFQ logic is very sensitive to the circuit parameter variations which are induced by the fabrication process and the device parameter uncertainty. Considering the physical timing in the circuits, we have shown that the DDST architecture is advantageous for realizing RSFQ circuits operating at very high frequencies. We have also calculated the theoretical circuit yield of the DDST adders and shown that a four-bit system operating at 10 GHz is feasible with sufficient operating margin, considering the present 1 kA/cm2 Nb Josephson technology.