🤖 AI Summary
This work proposes a novel family of verifiable benchmarks based on the integer factorization problem to evaluate SAT solvers and Ising optimization algorithms. By encoding the arithmetic constraint of multiplying two primes into conjunctive normal form (CNF) formulas and mapping them to Ising models, the generated instances exhibit clear structure, single-parameter scalability, and built-in ground-truth solutions (p, q), facilitating straightforward verification. The approach integrates logical circuit modeling, efficient CNF encoding, carry compression, and Ising mapping techniques, addressing gaps in existing benchmarks regarding structural clarity and verifiability. Experimental results demonstrate that the median runtime of SAT solvers on these instances grows exponentially with the bit-length of the factors. An open-source instance generator accompanying this work has been publicly released.
📝 Abstract
We present a family of planted-solution benchmark instances for satisfiability (SAT) solvers and Ising optimization derived from integer factorization. Given two primes $p$ and $q$, the construction encodes the arithmetic constraints of $N = p \times q$ as a conjunctive normal form (CNF) formula whose satisfying assignments correspond to valid factorizations of~$N$. The known pair $(p,q)$ serves as a built-in ground truth, enabling unambiguous verification of solver output. We show that for two $d$-bit primes the total number of carry contractions is on the order of $d^4$. Empirical benchmarks with SAT solvers show that median runtime grows exponentially in the bit-length of the factors over the range tested. The construction provides a scalable, structured, and verifiable benchmark family controlled by a single parameter, accompanied by open-source generation software.