[Resource Topic] 2022/1530: Multivariate lookups based on logarithmic derivatives

Welcome to the resource topic for 2022/1530

Title:
Multivariate lookups based on logarithmic derivatives

Authors: Ulrich Haböck

Abstract:

Logarithmic derivatives translate products of linear factors into sums of their reciprocals, turning zeroes into simple poles of same multiplicity. Based on this simple fact, we construct an interactive oracle proof for multi-column lookups over the boolean hypercube, which makes use of a single multiplicity function instead of working with a rearranged union of table and witnesses. For single-column lookups the performance is comparable to the well-known Plookup strategy used by Hyperplonk+. However, the real power of our argument unfolds in the case of batch lookups when multiple columns are subject to a single-table lookup: While the number of field operations is comparable to the Hyperplonk+ lookup (extended to multiple columns), the oracles provided by our prover are much less expensive. For example, for columns of length 2^12, paper-pencil operation counts indicate that the logarithmic derivative lookup is between 1.5 and 4 times faster, depending on the number of columns.

ePrint: https://eprint.iacr.org/2022/1530

See all topics related to this paper.

Feel free to post resources that are related to this paper below.

Example resources include: implementations, explanation materials, talks, slides, links to previous discussions on other websites.

For more information, see the rules for Resource Topics .