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How to understand the compatibility of finite-dimensional distribution family of a stochastic process?
It can be understood as a so-called finite-dimensional distribution family with 1 symmetry and 2 compatibility, and describes two characteristics of stochastic processes:

1. The measurement of stochastic process has time traceability. If the measurement time changes in sequence, it will not change the measurement results, that is to say, what has happened has become an unchangeable history, even if the time goes back.

2. Compatibility means that once you start measuring a random process and get an implementation (or sample) of the random process, all your measurements will only observe this sample and not other samples, which means that all possible implementations (samples) of the random process are orthogonal to each other in measurement. Kind of like quantum mechanics.

Dimension, also called dimension, is the number of independent parameters in mathematics. In physics and philosophy, the number of independent space-time coordinates.

Dimension 0 is an infinitesimal point with no length. 1 dimension is an infinite straight line with only length. 2-D is a plane, which is an area composed of length and width (or partial curves).

Three dimensions are the volume formed by two dimensions plus height. Four dimensions are divided into four dimensions in time and space. People usually refer to the transfer of objects on the timeline.

There are exactly two kinds of four dimensions. 1. Four-dimensional space-time refers to three-dimensional space plus one-dimensional time. 2. Four-dimensional space only refers to four-dimensional space. Four-dimensional motion produces five dimensions.