While investigating non-periodic RNG's (random number generators) for irrational numbers, I came up with a version that actually produces pseudo-random words consisting of $N$ bits, where $N$ is typically a large prime number. Here I explain my RNG. My question is whether it suffers from the same problems as [Xorshift][1] RNG's or some other problems. As a starter, the version corresponding to $N=32$ is terrible: its period is $24$. But $N=31$ yields a good generator with a long period and nice statistical properties. In its basic version, it is defined as follows.

Start with a seed $S$. The first random word $B_0$ is $S$. In my case, I picked up the first $N$ binary digits of $\sqrt{2}/2$ for the seed.The $k$-th bit of $B_n$ is denoted as $B_n(k)$. Then $B_{n+1}$ is obtained recursively as follows. 

 - **Shifting step**: Create the word $C_{n}$ by shifting the bits of $B_{n}$
   by $L$ positions as follows: the $k$-th bit of $C_n$ is equal to  $C_n(k)=B_n(\bmod(k+L,N))$ for $k=0,\cdots, N-1$.
 - **Scrambling step**: $B_{n+1}(k)=\bmod(B_{n}(N-k-1)+C_{n}(k),2)$ for $k=0,\cdots, N-1$. In other words, $B_{n+1}(k)=\mbox{ XOR}(B_{n}(N-k-1),C_{n}(k))$. Thus the analogy with Xorshift generators.  

$L=2$ seems to work best in most cases. For $L=2$ and $N=7, 11$ or $17$, the period is $2^{N-3}-1$. More generally, if $N$ is prime, the period is of the order $2^N$. Of course, there is no way the period could be higher than $2^N$. So prime values of $N$ produce the best generators, though this might not be true for all primes. 

Also, the real number $X_n\in [0,1]$ is defined as follows:

$$X_n=\sum_{k=1}^{N} \frac{B_{n}(k-1)}{2^k}.$$

There is a one-to-one mapping between $B_n$ and $X_n$. I studied the patterns in the distribution of successive values of $X_n$ and haven't found any. For instance, unlike other RNG's (see [here][2] and follow-up discussion [here][3]), the triplets $(X_n,X_{n+1},X_{n+2})$ do not appear to lie in a small number of parallel planes. Successive values of $X_n$ are asymptotically un-correlated. For modern tests (George Marsaglia, 2020) to assess the quality of a RNG, see [here][4].

The underlying idea in the design of my generator is this: take a seed consisting of a large number of random bits, such as a the first $N$ binary digits of a [normal number][5] in base $2$. Then if you reverse these bits (the binary digits), the new number is a sequence of bits just as random as the previous one, and uncorrelated to the previous number. 

**Possible improvement**

Consider a $q$-order recursion $B_{n}=f(B_{n-1},\cdots,B_{n-q})$ instead of a first-order one as here. Then the period can be of the order $2^{Nq}$.

**Source code**

It also computes the period. Use for values of $N$ smaller than 45.

    #!/usr/bin/perl
    $N=31;  
    
    $L=2;
    $period=-1;
    $Niter=50000;
    
    %hash=();
    
    $seed=sqrt(2)/2;
    
    open(OUT,">randx.txt");
    print OUT "0\tB";
    $x=0;
    $word="B";
    $s=$seed;
    for ($k=0; $k<$N; $k++) {
      $a[$k]=int(2*$s);  # k-th digit of seed
      $s=2*$s-int(2*$s);  
      $b[$k]=$a[$k];
      $x+=$b[$k]/(2**($k+1));
      $word=$word."$b[$k]";
      $hash{$word}=0;
      print OUT "$b[$k]";
    }
    print OUT "\t$x\n";
    
    for ($iter=1; $iter<$Niter; $iter++) {
      print OUT "$iter\tB";
      $x=0;
      for ($k=0; $k<$N; $k++) { 
        $c[$k]=$b[($k+$L)%$N]; 
      }
      $word2="B";
      $nzero=0;
      for ($k=0; $k<$N; $k++) { 
        $b[$k]=($c[$k]+$b[$N-$k-1])%2;
        $word2=$word2."$b[$k]";
        $x+=$b[$k]/(2**($k+1));
        print OUT "$b[$k]";
      }
      print OUT "\t$x\n";
      if ($period==-1) { 
        if ($hash{$word2} eq "") { 
          $hash{$word2}=$iter; 
        } else {
          $period=$iter-$hash{$word2};
        }
      }
    }
    close(OUT);
    print "$N $L $period\n";


  [1]: https://en.wikipedia.org/wiki/Xorshift
  [2]: https://mathoverflow.net/questions/372103/recursive-random-number-generator-based-on-irrational-numbers
  [3]: https://mathoverflow.net/questions/372712/hybrid-numeration-system-on-0-12/372738
  [4]: https://www.researchgate.net/publication/5142801_Some_Difficult-to-Pass_Tests_of_Randomness
  [5]: https://en.wikipedia.org/wiki/Normal_number