Exemple #1
0
void Mocasinns::Metropolis<ConfigurationType,Step,RandomNumberGenerator,rejection_free>::do_metropolis_simulation(const TemperatureType& beta, Accumulator& measurement_accumulator)
{
  // Check the concept of the observator
  BOOST_CONCEPT_ASSERT((Concepts::ObservatorConcept<Observator,ConfigurationType>));
  // Check the concept of the observable
  BOOST_CONCEPT_ASSERT((Concepts::ObservableConcept<typename Observator::observable_type>));
  // Check the concept of the accumulator
  BOOST_CONCEPT_ASSERT((Concepts::AccumulatorConcept<Accumulator, typename Observator::observable_type>));

  // Log the start of the simulation
  this->simulation_start_log();

 // Perform the relaxation steps
  do_metropolis_steps(simulation_parameters.relaxation_steps, beta);
  
  // For each measurement, perform the steps, invoke the signal handler, take the measurement and check for posix signals
  for (unsigned int m = 0; m < simulation_parameters.measurement_number; ++m)
  {
    // Do the steps
    do_metropolis_steps(simulation_parameters.steps_between_measurement, beta);

    // Call the measurement signal handler
    signal_handler_measurement(this);

    // Observe and check for posix signals
    measurement_accumulator(Observator::observe(this->configuration_space));
    if (this->check_for_posix_signal()) return;
  }
}
Exemple #2
0
std::vector<typename Observator::observable_type> Metropolis<ConfigurationType, Step, RandomNumberGenerator>::autocorrelation_function(const TemperatureType& beta, unsigned int maximal_time, unsigned int simulation_time_factor)
{
  // Check the concept of the observator
  BOOST_CONCEPT_ASSERT((Concepts::ObservatorConcept<Observator,ConfigurationType>));
  // Check the concept of the observable
  BOOST_CONCEPT_ASSERT((Concepts::ObservableConcept<typename Observator::observable_type>));

  // Do the relaxation steps
  do_metropolis_steps(simulation_parameters.relaxation_steps, beta);

  // Define the vector with the results
  std::vector<typename Observator::observable_type> results;

  // Define the vector with the measurments of the observable and take the measurements
  std::vector<typename Observator::observable_type> observable_measurements;
  for (unsigned int i = 0; i <= maximal_time*simulation_time_factor; ++i)
  {
    do_metropolis_steps(this->get_config_space()->system_size(), beta);
    observable_measurements.push_back(Observator::observe(this->get_config_space()));
  }

  // Define an accumulator and calculate the mean value of the observable
  ba::accumulator_set<typename Observator::observable_type, ba::stats<ba::tag::mean> > acc_measured_mean(observable_measurements[0]);
  for (unsigned int i = 0; i <= maximal_time*simulation_time_factor; ++i)
  {
    acc_measured_mean(observable_measurements[i]);
  }
  typename Observator::observable_type measured_mean = ba::mean(acc_measured_mean);

  // Calculate the autocorrelation function using an accumulator
  for (unsigned int time = 0; time <= maximal_time; ++time)
  {
    // Calculate the mean autocorrelation function for time
    ba::accumulator_set<typename Observator::observable_type, ba::stats<ba::tag::mean> > acc_autocorrelation_function_time(observable_measurements[0]);
    for (unsigned int sweep = 0; sweep < simulation_time_factor; ++sweep)
    {
      unsigned int start_time = sweep*maximal_time;
      acc_autocorrelation_function_time(observable_measurements[start_time]*observable_measurements[start_time + time]);
    }
    
    // Add to the result vector
    results.push_back(ba::mean(acc_autocorrelation_function_time) - measured_mean*measured_mean);
  }

  // Return the result vector
  return results;
}