🤖 AI Summary
Existing methods for solving quadratic polynomial equations over binary extension fields rely on complex exponentiation or case-by-case analyses based on the parity or power structure of the field dimension \( m \), lacking both uniformity and efficiency. This work proposes a unified solution framework that leverages Reed–Muller matrices to represent function evaluations, thereby transforming the problem into a system of binary linear equations solvable using only XOR operations. For the first time, this approach yields a general formula applicable to any positive integer \( m \) without requiring case distinctions. The algorithm demands at most \( m^2 - 2m + 1 \) XOR operations and achieves a parallel time delay as low as \( \lceil \log_2 m \rceil \), significantly enhancing its generality, hardware friendliness, and suitability for low-power, low-latency applications.
📝 Abstract
Solving quadratic equations over finite fields is a fundamental task in algebraic coding theory and serves as a key subroutine for computing the roots of cubic and quartic polynomials. For the reduced quadratic polynomial $x^2+x+c\in \mathbb{F}_{2^m}[x]$, existing formula-based methods rely on heavy exponentiation or case distinctions on $m$ (odd/even or powers of two), which limits uniformity and efficiency. This paper presents a unified, formula-based solution for all positive integers $m$ that uses only exclusive-OR operations (XORs). The approach leverages a Reed-Muller matrix characterization of evaluations and reduces the problem to solving a binary linear system. The total cost is at most $m^2-2m+1$ XORs, and under parallelism, the latency is $\lceil \log_2 m\rceil$ XORs, making the method attractive for low-power, low-latency applications.