A Two-Branch Finite-Field Construction for Regular CSS LDPC Bases

• URL: http://arxiv.org/abs/2605.23894v1
• Date: Fri, 22 May 2026 17:56:26 GMT
• Title: A Two-Branch Finite-Field Construction for Regular CSS LDPC Bases
• Abstract summary: This paper develops a two-branch multiplicativecoset construction for regular CalderbankShorSteane (CSS) quantum lowdensity parity-check base matrices.<n>For decoding, we use joint logdomain belief propagation together with low-complexity post-processing rules for small residual syndromes.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper develops a two-branch multiplicative-coset construction for regular Calderbank-Shor-Steane (CSS) quantum low-density parity-check base matrices. For a target column weight \(J\) and an even row weight \(L\), the method reduces regularity, CSS orthogonality, and same-type 4-cycle exclusion to explicit quotient-coset conditions over a finite field. A normalized exhaustive search for these conditions produces base matrices for several \((J,L)\) pairs, so the construction is not tied to a single degree distribution. The construction separates the finite-length design into two stages: the base matrix fixes the degree distribution and the first girth constraints, and a cyclic lift randomizes edge connections subject to exact algebraic checks. As a detailed example, we carry one \((3,10)\)-regular base through the lift and decoding stages. For this example, the selected 64-fold lift gives a code whose same-type Tanner graphs have girth at least eight, and it also excludes a specified weight-16 nondegenerate logical-support orbit. The resulting instance is a \([[10240,4108,\,10\le d\le32]]\) CSS code. For decoding, we use joint log-domain belief propagation together with low-complexity deterministic post-processing rules for small residual syndromes, including repairs for residual patterns with two unsatisfied checks. The frame error rate (FER) measurements provide finite-length decoding data for this detailed example; at depolarizing probability \(p=0.058\), the post-processing FER is \(1.0\times10^{-7}\).

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