Note on Marsaglia's Xorshift Random Number Generators

Marsaglia (2003) has described a class of Xorshift random number generators (RNGs) with periods 2^n - 1 for n = 32, 64, etc. We show that the sequences generated by these RNGs are identical to the sequences generated by certain linear feedback shift register (LFSR) generators using "exclusive or" (xor) operations on n-bit words, with a recurrence defined by a primitive polynomial of degree n.

Note on Marsaglia's Xorshift Random Number Generators

Marsaglia (2003) has described a class of Xorshift random number generators (RNGs) with periods 2n - 1 for n = 32, 64, etc. We show that the sequences generated by these RNGs are identical to the sequences generated by certain linear feedback shift register (LFSR) generators using "exclusive or" (xor) operations on n-bit words, with a recurrence defined by a primitive polynomial of degree n

Revisiting LFSMs

Linear Finite State Machines (LFSMs) are particular primitives widely used in information theory, coding theory and cryptography. Among those linear automata, a particular case of study is Linear Feedback Shift Registers (LFSRs) used in many cryptographic applications such as design of stream ciphers or pseudo-random generation. LFSRs could be seen as particular LFSMs without inputs. In this paper, we first recall the description of LFSMs using traditional matrices representation. Then, we introduce a new matrices representation with polynomial fractional coefficients. This new representation leads to sparse representations and implementations. As direct applications, we focus our work on the Windmill LFSRs case, used for example in the E0 stream cipher and on other general applications that use this new representation. In a second part, a new design criterion called diffusion delay for LFSRs is introduced and well compared with existing related notions. This criterion represents the diffusion capacity of an LFSR. Thus, using the matrices representation, we present a new algorithm to randomly pick LFSRs with good properties (including the new one) and sparse descriptions dedicated to hardware and software designs. We present some examples of LFSRs generated using our algorithm to show the relevance of our approach.Comment: Submitted to IEEE-I

Some long-period random number generators using shifts and xors

Marsaglia recently introduced a class of `xorshift' random number generators with periods $2^n-1$ for $n = 32, 64,\ldots$. Here Marsaglia's xorshift generators are generalised to obtain fast and high quality random number generators with extremely long periods. Whereas random number generators based on primitive trinomials may be unsatisfactory, because a trinomial has very small weight, these new generators can be chosen so that their minimal polynomials have a large number of non-zero terms and, hence, a large weight. A computer search using Magma found good random number generators for$~n$ a power of two up to 4096. These random number generators are implemented in a free software package \texttt{xorgens}