Pseudorandom number generators (PRNG) are very complex beast.
There are no real "perfect" random number generators -- in fact the best that can be done from mathematical functions are pseudorandom -- they seem random enough for most intents and purposes.
In fact, performing any additional actions from a number returned by a PRNG doesn't really increase its randomness, and in fact, the number can become less random.
So, my best advice is, don't mess around with values returned from a PRNG. Use a PRNG that is good enough for the intended use, and if it isn't, then find a PRNG that can produce better results, if necessary.
And frankly, it appears that the mt_rand
function uses the Mersenne twister, which is a pretty good PRNG as it is, so it's probably going to be good enough for most casual use.
However, Mersenne Twister is not designed to be used in any security contexts. See this answer for a solution to use when you need randomness to ensure security.
Edit
There was a question in the comments why performing operations on a random number can make it less random. For example, some PRNGs can return more consistent, less random numbers in different parts of the bits -- the high-end can be more random than the low-end.
Therefore, in operations where the high-end is discarded, and the low end is returned, the value can become less random than the original value returned from the PRNG.
I can't find a good explanation at the moment, but I based that from the Java documentation for the Random.nextInt(int)
method, which is designed to create a fairly random value in a specified range. That method takes into account the difference in randomness of the parts of the value, so it can return a better random number compared to more naive implementations such as rand() % range
.
与恶龙缠斗过久,自身亦成为恶龙;凝视深渊过久,深渊将回以凝视…