Understanding the Moments of Tabulation Hashing via Chaoses
Jakob B{\ae}k Tejs Houen, Mikkel Thorup

TL;DR
This paper applies chaos theory from probability to analyze the moments of hash-based sums in simple tabulation hashing, providing tight bounds and extending results to mixed tabulation hashing.
Contribution
It introduces an analytical approach using chaos theory to analyze moments of hash-based sums, improving upon previous combinatorial methods.
Findings
Bounds for all moments of hash-based sums are tight up to constants.
Analysis applies to simple tabulation hashing and extends to mixed tabulation hashing.
Approach avoids intricate combinatorial arguments, simplifying the analysis.
Abstract
Simple tabulation hashing dates back to Zobrist in 1970 and is defined as follows: Each key is viewed as characters from some alphabet , we have fully random hash functions , and a key is hashed to where is the bitwise XOR operation. The previous results on tabulation hashing by P{\v a}tra{\c s}cu and Thorup~[J.ACM'11] and by Aamand et al.~[STOC'20] focused on proving Chernoff-style tail bounds on hash-based sums, e.g., the number keys hashing to a given value, for simple tabulation hashing, but their bounds do not cover the entire tail. Chaoses are random variables of the form where are independent random variables. Chaoses…
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