Namespaces
namespace	backends

Classes
struct	MetropolisStats
	Statistics returned by a single Metropolis sweep. More...

struct	UmbrellaStats
	Statistics returned by an umbrella sampling sweep. More...

struct	UmbrellaWindow
	Window constraint for umbrella sampling. More...

Functions
double	boltzmann_accept (double dE, double beta) noexcept
	Metropolis acceptance probability min(1, exp(-beta*dE)).

std::vector< double >	make_boltzmann_table (const std::vector< double > &dEs, double beta)

template<typename DeltaE , typename Apply , typename RNG >
MetropolisStats	metropolis_sweep (idx n_sites, DeltaE delta_energy, Apply apply_flip, real beta, RNG &rng)
	Single Metropolis sweep: n_sites random single-site updates.

template<typename ProbFn , typename Apply , typename RNG >
MetropolisStats	metropolis_sweep_prob (idx n_sites, ProbFn acceptance_prob, Apply apply_flip, RNG &rng)
	Metropolis sweep with caller-supplied acceptance probabilities.

template<typename DeltaE , typename Apply , typename Save , typename Restore , typename Measure , typename RNG >
UmbrellaStats	umbrella_sweep (idx n_sites, DeltaE delta_energy, Apply apply_flip, Save save_state, Restore restore_state, Measure measure_order, UmbrellaWindow window, real beta, RNG &rng)
	Umbrella-sampled Metropolis sweep (dE variant).

template<typename ProbFn , typename Apply , typename Save , typename Restore , typename Measure , typename RNG >
UmbrellaStats	umbrella_sweep_prob (idx n_sites, ProbFn acceptance_prob, Apply apply_flip, Save save_state, Restore restore_state, Measure measure_order, UmbrellaWindow window, RNG &rng)
	Umbrella-sampled Metropolis sweep (precomputed probability variant).

template<typename RNG = std::mt19937>
RNG	make_seeded_rng ()
	Construct an RNG seeded from hardware entropy.

template<typename RNG = std::mt19937>
RNG	make_rng (typename RNG::result_type seed)
	Construct an RNG from a fixed seed (for reproducible runs).

Function Documentation

◆ boltzmann_accept()

double num::markov::boltzmann_accept	(	double	dE,
		double	beta
	)

inlinenoexcept

Metropolis acceptance probability min(1, exp(-beta*dE)).

Definition at line 21 of file boltzmann_table.hpp.

References num::beta().

Referenced by make_boltzmann_table().

◆ make_boltzmann_table()

std::vector< double > num::markov::make_boltzmann_table	(	const std::vector< double > &	dEs,
		double	beta
	)

inline

Precompute a table of acceptance probabilities for a discrete set of dE values.

Definition at line 27 of file boltzmann_table.hpp.

References num::beta(), and boltzmann_accept().

◆ make_rng()

template<typename RNG = std::mt19937>

RNG num::markov::make_rng ( typename RNG::result_type seed )

Construct an RNG from a fixed seed (for reproducible runs).

Definition at line 23 of file rng.hpp.

◆ make_seeded_rng()

template<typename RNG = std::mt19937>

RNG num::markov::make_seeded_rng ( )

Construct an RNG seeded from hardware entropy.

Equivalent to RNG(std::random_device{}()). Use this at simulation startup for non-deterministic seeds.

Template Parameters

RNG	Any standard-library-compatible random number engine. Defaults to std::mt19937.

Definition at line 16 of file rng.hpp.

◆ metropolis_sweep()

template<typename DeltaE , typename Apply , typename RNG >

MetropolisStats num::markov::metropolis_sweep	(	idx	n_sites,
		DeltaE	delta_energy,
		Apply	apply_flip,
		real	beta,
		RNG &	rng
	)

Single Metropolis sweep: n_sites random single-site updates.

The acceptance probability is min(1, exp(-beta * dE)) computed from the value returned by delta_energy(i).

Template Parameters

DeltaE	Callable: idx -> real. Returns dE for proposing a flip at i.
Apply	Callable: idx -> void. Applies the flip at site i.
RNG	Random number generator (e.g., std::mt19937).

Definition at line 20 of file mcmc_impl.hpp.

References num::markov::MetropolisStats::accepted, num::beta(), and num::markov::MetropolisStats::total.

Referenced by umbrella_sweep().

◆ metropolis_sweep_prob()

template<typename ProbFn , typename Apply , typename RNG >

MetropolisStats num::markov::metropolis_sweep_prob	(	idx	n_sites,
		ProbFn	acceptance_prob,
		Apply	apply_flip,
		RNG &	rng
	)

Metropolis sweep with caller-supplied acceptance probabilities.

Use this variant when acceptance probabilities are precomputed (e.g. a Boltzmann table for a discrete-dE system like the Ising model), avoiding a runtime exp() call per proposed flip.

Template Parameters

ProbFn	Callable: idx -> real. Returns min(1, exp(-beta*dE)) for site i.
Apply	Callable: idx -> void. Applies the flip at site i.
RNG	Random number generator.

Definition at line 54 of file mcmc_impl.hpp.

References num::markov::MetropolisStats::accepted, and num::markov::MetropolisStats::total.

Referenced by num::solve(), and umbrella_sweep_prob().

◆ umbrella_sweep()

template<typename DeltaE , typename Apply , typename Save , typename Restore , typename Measure , typename RNG >

UmbrellaStats num::markov::umbrella_sweep	(	idx	n_sites,
		DeltaE	delta_energy,
		Apply	apply_flip,
		Save	save_state,
		Restore	restore_state,
		Measure	measure_order,
		UmbrellaWindow	window,
		real	beta,
		RNG &	rng
	)

Umbrella-sampled Metropolis sweep (dE variant).

Performs a sweep, measures the order parameter, then restores the saved state if the order parameter falls outside [window.lo, window.hi].

Template Parameters

DeltaE	Callable: idx -> real
Apply	Callable: idx -> void
Save	Callable: () -> void. Saves system state before the sweep.
Restore	Callable: () -> void. Restores saved state.
Measure	Callable: () -> idx. Returns the order parameter.
RNG	Random number generator.

Definition at line 92 of file mcmc_impl.hpp.

References num::beta(), num::markov::UmbrellaWindow::contains(), num::markov::UmbrellaStats::mc, metropolis_sweep(), num::markov::UmbrellaStats::order_param, and num::markov::UmbrellaStats::reverted.

◆ umbrella_sweep_prob()

template<typename ProbFn , typename Apply , typename Save , typename Restore , typename Measure , typename RNG >

UmbrellaStats num::markov::umbrella_sweep_prob	(	idx	n_sites,
		ProbFn	acceptance_prob,
		Apply	apply_flip,
		Save	save_state,
		Restore	restore_state,
		Measure	measure_order,
		UmbrellaWindow	window,
		RNG &	rng
	)

Umbrella-sampled Metropolis sweep (precomputed probability variant).

Same as umbrella_sweep but uses caller-supplied acceptance probabilities.

Template Parameters

ProbFn	Callable: idx -> real
Apply	Callable: idx -> void
Save	Callable: () -> void
Restore	Callable: () -> void
Measure	Callable: () -> idx
RNG	Random number generator.

Definition at line 134 of file mcmc_impl.hpp.

References num::markov::UmbrellaWindow::contains(), num::markov::UmbrellaStats::mc, metropolis_sweep_prob(), num::markov::UmbrellaStats::order_param, and num::markov::UmbrellaStats::reverted.

Namespaces

Classes

Functions

Function Documentation

◆ boltzmann_accept()

◆ make_boltzmann_table()

◆ make_rng()

◆ make_seeded_rng()

◆ metropolis_sweep()

◆ metropolis_sweep_prob()

◆ umbrella_sweep()

◆ umbrella_sweep_prob()