Sebastiano Vigna created RNG-123:
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             Summary: PCG generators may exhibit massive stream correlation
                 Key: RNG-123
                 URL: https://issues.apache.org/jira/browse/RNG-123
             Project: Commons RNG
          Issue Type: Bug
          Components: core
    Affects Versions: 1.3
            Reporter: Sebastiano Vigna


[This is based on an issue I posted on the Rust development mailing list.]

The documentation of the PCG generators does not state explicit that different 
seeds generate independent sequences, but the existence of a 128-bit seed 
implies somehow the idea that the whole seed is meaningful.

The user should be made aware that the second parameter (the constant of the 
underlying LCG) is almost useless from a mathematical and statistical viewpoint.

Changing constant to an LCG with power-of-two modulus and a constant like the 
one used in PCG simply adds a constant to the sequence (more precisely, there 
are two equivalence classes of constants, and in each equivalence class the 
sequences are identical, except for an additive constant).

The minimal scrambling done by the generator usually cannot cancel this fact, 
and as a result changing the constant is equivalent to changing the initial 
state (modulo an additive constant). You can try to run this program:

 
{noformat}
import org.apache.commons.rng.core.source32.PcgXshRr32;
import com.google.common.primitives.Ints;

public class TestPCG {
    public static void main(final String[] args) {
        final long state = Long.parseLong(args[0]);
        final long c = Long.parseLong(args[1]);
        final long d = Long.parseLong(args[2]);
        if (c % 2 != d % 2) throw new IllegalArgumentException();
        final long C = c << 1 | 1;
        final long D = d << 1 | 1;
        final long r = 1314878037273365987L * ((d - c) >>> 1);

        final PcgXshRr32 rng0 = new PcgXshRr32(new long[] { state, c });
        final PcgXshRr32 rng1 = new PcgXshRr32(new long[] {
            0xc097ef87329e28a5L  *(6364136223846793005L * (state + C) + C - r - 
D) - D, d });

        for(;;) {
            final int a = rng0.nextInt();
            System.out.write(Ints.toByteArray(a), 0, 4);
            final int b = rng1.nextInt();
            System.out.write(Ints.toByteArray(b), 0, 4);
        }
    }
}{noformat}
You can pass any state as first argument, and any two constants as the 
following two arguments, as long as they are either both even or both odd . The 
program will set up a second initial state so that the sequences generated by 
the PRNGs using the two constants as seed are based on almost identical 
underlying LCG sequences, in spite of having arbitrary, different constants and 
different initial states. The two streams should be independent, but if you 
pipe the output in PractRand you'll get immediately


{noformat}
rng=RNG_stdin32, seed=unknown
length= 4 megabytes (2^22 bytes), time= 2.1 seconds
  Test Name                         Raw       Processed     Evaluation
  BCFN(0+0,13-5,T)                  R=+263.2  p =  3.4e-103   FAIL !!!!!
  BCFN(0+1,13-5,T)                  R=+128.6  p =  1.5e-50    FAIL !!!!
  BCFN(0+2,13-6,T)                  R= +65.2  p =  9.2e-23    FAIL !!
  BCFN(0+3,13-6,T)                  R= +15.4  p =  1.0e-5   mildly suspicious
  DC6-9x1Bytes-1                    R= +59.1  p =  4.2e-33    FAIL !!!
  DC6-6x2Bytes-1                    R= +34.1  p =  9.0e-19    FAIL !
  DC6-5x4Bytes-1                    R= +15.2  p =  7.7e-8   very suspicious
  [Low4/16]BCFN(0+1,13-6,T)         R= +12.0  p =  1.5e-4   unusual
  [Low4/16]FPF-14+6/64:(4,14-8)     R=  +9.2  p =  1.1e-6   unusual
  [...]
  [Low8/32]FPF-14+6/4:(9,14-9)      R= +27.4  p =  1.6e-17    FAIL
  [Low8/32]FPF-14+6/4:(10,14-10)    R= +16.4  p =  2.5e-9   suspicious
  [Low8/32]FPF-14+6/4:all           R=+283.4  p =  8.4e-255   FAIL !!!!!!
  [Low8/32]Gap-16:A                 R=+414.8  p =  2.4e-336   FAIL !!!!!!!
  [Low8/32]Gap-16:B                 R= +1736  p =  5e-1320    FAIL 
!!!!!!!!{noformat}
You can also offset one of generator by hundred of iterations, but the 
sequences are so correlated that the result won't change. If you peek at the 
state of the two generators you'll see that their difference is constant.

I think the reader should be made aware of the danger. If you start several 
generators of this kind the state is too small to guarantee that there will be 
no overlap. Once you get overlap, since there are in practice just two 
sequences, you will get a lot of unwanted correlation.

There's a reason why nobody in the last decades ever considered creating 
"streams" using the constant part of an LCG, and it's that people realized very 
early that it doesn't work (see, e.g., 
[https://ieeexplore.ieee.org/document/718715]).

 



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