Why Do Random Numbers Repeat After Startup?

All the random number functions, rand, randn, randi, and randperm, draw values from a shared random number generator. Every time you start MATLAB^®, the generator resets itself to the same state using the default algorithm and seed. Therefore, a command such as rand(2,2) returns the same result any time you execute it immediately following startup in different MATLAB sessions that have the same settings for the random number generator. Also, any script or function that calls the random number functions returns the same result whenever you restart.

When you first start a MATLAB session or call rng("default"), MATLAB initializes the random number generator using the default algorithm and seed. You can set the default algorithm and seed in MATLAB settings (since R2023b). If you do not change these settings, then rng uses the factory value of "twister" for the Mersenne Twister generator with seed 0, as in previous releases. For more information, see Default Settings for Random Number Generator and Reproducibility for Random Number Generator.

• If you want to avoid repeating the same random number arrays when MATLAB restarts, then use rng("shuffle") before calling rand, randn, randi, or randperm. This command ensures that you do not repeat a result from a previous MATLAB session.

• If you want to repeat a result that you got at the start of a MATLAB session without restarting, you can reset the generator to the startup state using rng("default").

When you execute rng("default"), the ensuing random number commands return results that match the output of another MATLAB session that uses the same default algorithm and seed for the random number generator.

rng("default");
A = rand(2,2)

A =

    0.8147    0.1270
    0.9058    0.9134

The values in A match the output of rand(2,2) whenever you restart MATLAB using the same settings for the random number generator.

Alternatively, you can repeat a result by specifying the seed and algorithm used for the random number generator. For example, sets the seed to 1 and the generator algorithm to Mersenne Twister

rng(1,"twister");

Create an array of random numbers.

A = rand(2,2)

A =

    0.4170    0.0001
    0.7203    0.3023

Next, in a new MATLAB session, repeat the same commands to reproduce the array A.

rng(1,"twister");
A = rand(2,2)

A =

    0.4170    0.0001
    0.7203    0.3023