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Following is a basic implementation of the Xorshift RNG (copied from the Wikipedia): uint32_t xor128(void) { static uint32_t x = 123456789; static uint32_t y = 362436069; static uint32_t z = 521288629; static uint32_t w = 88675123; uint32_t t; t = x ^ (x << 11); x = y; y = z; z = w; return w = w ^ (w >> 19) ^ (t ^ (t >> 8)); } I understand that w is the returned value and x , y and z are the state ("memory") variables. However, I can't understand the purpose of more than one memory variable. Can anyone explain me this point? Also, I tried to copy the above code to Python: class R2: def __init__(self): self.x = x = 123456789 self.y = 362436069 self.z = 521288629 self.w = 88675123 def __call__(self): t = self.x ^ (self.x<<11) self.x = self.y self.y = self.z self.z = self.w w = self.w self.w = w ^ (w >> 19) ^(t ^ (t >> 8)) return self.w Then, I have generated 100 numbers and plotted their log10 values: r2 = R2() x2 = [math.log10(r2()) for _ in range(100)] plot(x2, '.g') Here is the output of the plot: And this what happens when 10000 (and not 100) numbers are generated: The overall tendency is very clear. And don't forget that the Y axis is log10 of the actual value. Pretty strange behavior, don't you think?

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