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<p class="Abstract">We are developing a backward simulator, which determines the unknown system input from the system output by using a system model. However, its processing time would increase enormously if the simulation model requires the multiple case branching, which is typical for backward simulations. In some target applications, we can use forward simulation processing in the backward data flow with significant reduction of processing time. This paper shows an example of such application to determine system input of heater operation from measured data of room temperature. Although the resolution of measurement restricts the performance of the simulation result, we also used the model to improve the resolution of measured data and show its effect to simulation. Furthermore, we show the result of reduction of noise caused by quantizing LSB jitters.</p>

To verify the safety of a system, it is desirable to test all the situation, at least, by simulation. However, it is difficult to test the entire situation because the number of situations is almost uncountable. As a promising method, backward simulation which traces back from the undesirable result to causal input(s) is proposed. For such backward simulation, we have to transform the forward model into a backward model. This paper shows an example of transformation in the case of mathematical model of integer factorization, and shows the effectiveness of the backward simulation. Such backward simulation would require case branch processing. And the practicality of the simulation result will be influenced by the efficiency of the case division. We show an effective case branch processing by using stack and threaded actors which are promising schemes applicable to distributed processing.

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