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#pragma once
#include <array>
#include <functional>
#include <list>
#include <queue>
#include <vector>
#include "randutils/randutils.hpp"
#include "euclidean.hpp"
#include "octree.hpp"
#include "quantity.hpp"
#include "spin.hpp"
template <class U, int D, class R, class S> class Model;
template <class U, int D, class R, class S> class measurement {
public:
virtual void pre_cluster(const Model<U, D, R, S>&, unsigned, const R&){};
virtual void plain_bond_visited(const Model<U, D, R, S>&, const Spin<U, D, S>*,
const Spin<U, D, S>*, const Spin<U, D, S>&, double){};
virtual void plain_site_transformed(const Model<U, D, R, S>&, const Spin<U, D, S>*,
const Spin<U, D, S>&){};
virtual void ghost_bond_visited(const Model<U, D, R, S>&, const Spin<U, D, S>&,
const Spin<U, D, S>&, double){};
virtual void ghost_site_transformed(const Model<U, D, R, S>&, const R&){};
virtual void post_cluster(const Model<U, D, R, S>&){};
};
template <class U, int D, class R, class S> using Gen = std::function<R(const Model<U, D, R, S>&, randutils::mt19937_rng&)>;
template <class U, int D, class R, class S> class Model;
template <class U, int D, class R, class S> class Transformation {
public:
virtual void ready() {};
virtual double p(const Transformation&) const { return 0; }
virtual void apply() {};
virtual std::set<Transformation*> to_consider() const {};
};
template <class U, int D, class R, class S> class SpinFlip : public Transformation<U, D, R, S> {
private:
Model<U, D, R, S>& M;
Spin<U, D, S>& s;
const R& r;
Spin<U, D, S> s_new;
public:
SpinFlip(Model<U, D, R, S>& M, Spin<U, D, S>& s, const R& r) : M(M), s(s), r(r) {}
void ready() override {
s_new = r.act(s);
};
double p(const SpinFlip& sf, double T) const override {
return 1.0 - exp(-(M.Z(s, sf.s) - M.Z(s_new, sf.s)) / T);
}
double p(const SpinFlip& sf, double T) const override {
return 1.0 - exp(-(M.Z(s, sf.s) - M.Z(s_new, sf.s)) / T);
}
};
template <class U, int D, class R, class S> class Model {
public:
U L;
R s0;
std::vector<Spin<U, D, S>> s;
Octree<U, D, S> dict;
std::function<double(const Spin<U, D, S>&, const Spin<U, D, S>&)> Z;
std::function<double(const Spin<U, D, S>&)> B;
randutils::mt19937_rng rng;
Model(U L, std::function<double(const Spin<U, D, S>&, const Spin<U, D, S>&)> Z,
std::function<double(const Spin<U, D, S>&)> B)
: L(L), s0(L), Z(Z), B(B), rng(), dict(L, std::floor(L)) {}
void step(double T, unsigned ind, R& r, measurement<U, D, R, S>& A) {
std::queue<Spin<U, D, S>*> queue;
queue.push(&(s[ind]));
std::set<Spin<U, D, S>*> visited;
while (!queue.empty()) {
Spin<U, D, S>* si = queue.front();
queue.pop();
if (!visited.contains(si)) {
visited.insert(si);
if (si == NULL) {
R s0_new = r.act(s0);
for (Spin<U, D, S>& ss : s) {
Spin<U, D, S> s0s_old = s0.inverse().act(ss);
Spin<U, D, S> s0s_new = s0_new.inverse().act(ss);
double p = 1.0 - exp(-(B(s0s_new) - B(s0s_old)) / T);
A.ghost_bond_visited(*this, s0s_old, s0s_new, p);
if (rng.uniform(0.0, 1.0) < p) {
queue.push(&ss);
}
}
A.ghost_site_transformed(*this, s0_new);
s0 = s0_new;
} else {
Spin<U, D, S> si_new = r.act(*si);
std::set<Spin<U, D, S>*> all_neighbors;
std::set<Spin<U, D, S>*> current_neighbors = dict.neighbors(si->x);
std::set<Spin<U, D, S>*> new_neighbors = dict.neighbors(si_new.x);
all_neighbors.insert(current_neighbors.begin(), current_neighbors.end());
all_neighbors.insert(new_neighbors.begin(), new_neighbors.end());
all_neighbors.insert(NULL);
for (Spin<U, D, S>* sj : all_neighbors) {
if (sj != si) {
double p;
if (sj == NULL) {
Spin<U, D, S> s0s_old = s0.inverse().act(*si);
Spin<U, D, S> s0s_new = s0.inverse().act(si_new);
p = 1.0 - exp(-(B(s0s_new) - B(s0s_old)) / T);
A.ghost_bond_visited(*this, s0s_old, s0s_new, p);
} else {
p = 1.0 - exp(-(Z(*si, *sj) - Z(si_new, *sj)) / T);
A.plain_bond_visited(*this, si, sj, si_new, p);
}
if (rng.uniform(0.0, 1.0) < p) {
queue.push(sj);
}
}
}
A.plain_site_transformed(*this, si, si_new);
dict.remove(si);
*si = si_new;
dict.insert(si);
}
}
}
}
void resize(double T, double P) {}
void wolff(double T, std::vector<Gen<U, D, R, S>> gs,
measurement<U, D, R, S>& A, unsigned N) {
for (unsigned i = 0; i < N; i++) {
Gen<U, D, R, S>& g = rng.pick(gs);
R r = g(*this, rng);
unsigned ind = rng.uniform((unsigned)0, (unsigned)(s.size() - 1));
A.pre_cluster(*this, ind, r);
this->step(T, ind, r, A);
A.post_cluster(*this);
}
}
};
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