#include #include #include "randutils/randutils.hpp" #define WOLFF_USE_FINITE_STATES #include "wolff/lib/wolff_models/ising.hpp" using namespace wolff; class sample : public measurement> { private: typedef struct _dat { int e; int m; } dat; std::ofstream e_file; dat e; public: sample(const wolff::system>& s, unsigned D, unsigned L, double T, double H) { e_file.open("sample_" + std::to_string(D) + "_" + std::to_string(L) + "_" + std::to_string(T) + "_" + std::to_string(H) + ".bin", std::ios::out | std::ios::binary | std::ios::app); e.e = -s.ne; e.m = s.nv; } ~sample() { e_file.close(); } void ghost_bond_visited(const system>&, const typename graph<>::vertex&, const ising_t& s_old, const ising_t& s_new, double dE) override { e.m += s_new - s_old; } void plain_bond_visited(const wolff::system>& s, const typename graph<>::halfedge& ed, const ising_t& si_new, double dE) override { e.e -= 2 * (si_new * s.s[ed.neighbor.ind]); } void post_cluster(unsigned n, unsigned, const wolff::system>&) override { e_file.write((char*)&e, 2 * sizeof(int)); } }; int main(int argc, char* argv[]) { // set defaults unsigned N = (unsigned)1e4; unsigned D = 2; unsigned L = 128; double T = 2 / log(1 + sqrt(2)); double H = 0; int opt; // take command line arguments while ((opt = getopt(argc, argv, "N:D:L:T:H:")) != -1) { switch (opt) { case 'N': // number of steps N = (unsigned)atof(optarg); break; case 'D': // dimension D = atoi(optarg); break; case 'L': // linear size L = atoi(optarg); break; case 'T': // temperature T = atof(optarg); break; case 'H': // field H = atof(optarg); break; default: exit(EXIT_FAILURE); } } // define the spin-spin coupling std::function Z = [](const ising_t& s1, const ising_t& s2) -> double { return (double)(s1 * s2); }; // define the spin-field coupling std::function B = [=](const ising_t& s) -> double { return H * s; }; // initialize the lattice graph<> G(D, L); // initialize the system wolff::system> S(G, T, Z, B); // initialize the random number generator randutils::auto_seed_128 seeds; std::mt19937 rng{seeds}; // define function that generates self-inverse rotations std::function>&, const graph<>::vertex&)> gen_r = gen_ising>; // initailze the measurement object sample A(S, D, L, T, H); // run wolff N times S.run_wolff(N, gen_r, A, rng); // exit return 0; }