# Kullervo Rainio

## Discrete Process Model for Quantum and Mind Systems

### Abstract

The fundamental principle on which the discrete process model (DPM) is based
is the assumption that all quantum mechanical processes occur not only in discrete
space but also in discrete time. Thus, a process is seen as a transition from
one state to another at every step in the (discontinuous) time. These transitions
are controlled by the probabilities of moving from one state to another during
a step in time. Those probabilities constitute a Markov-matrix, called transition
probability matrix.

The process advances in one step in time in the following way: the product
of the state vector and the transition probability matrix is calculated, the
result being a new state vector (a Markov-vector) for the following point in
time. According to this stochastic state vector, "a lot is drawn by nature"
to determine which one of the possible states will be actualized to be the next
transitional state. The process continues in this way until the system remains
in a stable state - and the realization of that state occurs. This stability
enables the actualized state to be perceived, in principle. Thus, being observable
is defined in DPM as being a stable state of the transitional system.

The model is applied to physical - quantum-mechanical - processes as well as
to those of consciousness (mind). In the earlier case, the transition probability
matrix remains unchanged during the process, while in the latter it may change
in many way.

Two systems interact if some probabilities in their transition matrices are
conditional to each other. In this case, both vectors - or their parts - change
according to vector-interference.

The vector-interference between the physical and mind systems explains perception
as well as psychomotorics. It is shown that, using DPM, there exists no way
to reduce conscious phenomena to physical - and vice versa.

**Keywords**: cognitive, cognition, consciousness, covering, detector, discrete,
Eccles, entangle, exocytosis, interference, learning, Markov-matrix, mind, quantum
mechanics, perception, psychophysical, synapsis, transition probability.