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SZ Sequences: Binary-Constructed $(0, 2^q)$-Sequences
DescriptionLow-discrepancy sequences have seen widespread adoption in computer graphics thanks to the superior rates of convergence that they provide.
Because rendering integrals often are comprised of products of lower-dimensional integrals, recent work has focused on developing sequences that are also well-distributed in lower-dimensional projections. To this end, we introduce a novel construction of binary-based $(0, 4)$-sequences; that is, progressive fully multi-stratified sequences of 4D points, and extend the idea to higher power-of-two dimensions. We further show that not only it is possible to nest lower-dimensional sequences in higher-dimensional ones---for example, embedding a $(0, 2)$-sequence within our $(0, 4)$-sequence---but that we can ensemble two $(0, 2)$-sequences into a $(0, 4)$-sequence, four $(0, 4)$-sequences into a $(0, 16)$-sequence, and so on. Such sequences can provide excellent rates of convergence when integrals include lower-dimensional integration problems in 2, 4, 16,$\ldots$ dimensions. Our construction is based on using 2$\times$2 block matrices as symbols to construct larger matrices that potentially generate a sequence with the target $(0, s)$-sequence in base $s$ property. We describe how to search for suitable alphabets and identify two distinct, cross-related alphabets of block symbols, which we call $s$ and $z$, hence \emph{SZ} for the resulting family of sequences.
Given the alphabets, we construct candidate generator matrices and search for valid sets of matrices. We then infer a simple recurrence formula to construct full-resolution (64-bit) matrices.
Because our generator matrices are binary, they allow highly-efficient implementation using bitwise operations and can be used as a drop-in replacement for Sobol matrices in existing applications.
We compare SZ sequences to state-of-the-art low discrepancy sequences, and demonstrate mean relative squared error improvements up to $1.93\times$ in common rendering applications.