There are numerous discussion about the Schrodinger’s cat thought experiment. Once the cat’s alive or dead is known or the Schrodinger’s box is open, then the quantum state of the particle will be fixed. In other words, the particle will no longer in its multiple states. In this author’s power point presentation, there is a quantum statistical linear regression model equation for the proposed particle’s multiple states, where on the upper part of the line, the data implies the cat’s alive and the lower part implies the cat’s dead. In such a case, we may get the quantum equation model and perform suitable quantum particle forecasting or prediction. The significant of the quantum equation model is that we may such quantum equation model as the basis for our practical commercial quantum computer. Certainly, there are still error(s) associated with the quantum equation model, but one may reduce the error by setting a small amount of acceptable delta value and apply the technique of reverse engineering to compute back the corresponding quantum gates probabilities. At the same time, in order to manipulate the quantum probabilities, we may need to add a damping coefficient to the Schrodinger Equation such that our researchers may control the expected and calculated those quantum probabilities required etc. At the same time, it is no doubt that, we may employ some error estimation or modeling method for the optimization to the aforementioned quantum equation model. These linear regression’s error optimization methods have been well applied in the U.S.A. commercial mathematical software such as the Matlab and Mathematica. One may further develop an essential and necessary algorithm for my proposed quantum model equation but this author believes that my method is much simpler and easier while the traditional error optimization algorithm may suffix to the defects that the squaring in the Mean Squared Error will induce a large penalized error. One may introduce a pattern recognization method to identify those relevant features as a remediation etc.

In a nutshell, both of the methods – Reverse Engineering and the (A.I.) error optimization method may be used for the quantum model equation while the focus of the present presentation is in the model equation but NOT in the error estimation.