To mitigate the computational burden, we imposed a two-hours upper bound time limit for each case and evaluated both the CP-exact, and SA-based enumeration algorithms on the benchmark dataset. The tolerant failure rate of the Ising-computing-based-enumeration algorithm was set to 0.01 to ensure a success probability greater than 0.99. Under the time limit, our SA-based enumeration algorithm successfully resolved 234 cases out of 241, whereas the CP-exact algorithm successfully resolved only 197 cases. We compared the maximum cliques generated by the SA-based method with those produced by the CP-exact algorithm for the 197 cases and found no discernible differences (i.e., all 10 instance runs of the SA-based method succeeded in finding the correct answer for each of the 197 cases). The computation times of both algorithms exhibited exponential increases with respect to the number of vertices in the modular product, denoted by N (see Figure ). In comparison, our SA-based enumeration algorithm demonstrated a flatter slope than the traditional CPexact algorithm and exhibited superior performance in cases with large N . Quantitatively, the computation time of the SA-based enumeration algorithm is approximately proportional to exp(0.011N ), while that of the CP algorithm is proportional to exp(0.051N ). This means that the former is expected to solve a problem with N = 1000 in 8.6 × 10 4 seconds, while the latter takes 1.2 × 10 19 seconds. Additionally, N correlates with the number of atoms involved in the chemical reaction, denoted by n. The relationship can be approximately expressed as N ≈ 0.21•n (see Figure in the Supporting Information). These approximation equations allows one to estimate the computation time required for the AAM of a chemical reaction and assess the applicability of our algorithm based on the number of atoms.