Run Monte Carlo

Overview

runMC is a driver routine for a normal MCMC scheme having the following steps:

• Initialization
  • Initialize a model
• Thermalization
  • Update the spin configuration w/o measurement
• Measurement
  • Update the spin configuration w/ measurement

runMC takes a param :: Parameter and returns a MCMC result, jks ::JackknifeSet . param is a set of parameters. jks is a set of MCMC averaged quantities.

Input

param::Parameter is a mapping from keynames to values (Parameter is an alias of Dict{String, Any}). runMC requires the following parameters:

• "Model"
  • typename of a model (ex. Ising)
• "Lattice"
  • name of a lattice (ex. "square lattice")
• "Update Method"
  • function to update a model (ex. local_update!)

The following are optional:

• "MCS"
  • The number of Monte Carlo steps for measurement
  • default: 8192
• "Thermalization"
  • The number of Monte Carlo steps for thermalization
  • default: "MCS" >> 3
• "Seed"
  • The initial seed of the random number generator, Random.MersenneTwister
  • default: random (see the doc of Random.seed!)
• "Checkpoint Filename Prefix"
  • Suffix of filename of checkpoint file (see the "Restart" section)
  • default: "cp"
• "ID"
  • Job ID used for restarting
  • default: 0
• "Checkpoint Interval"
  • Time interval between saving a calculation state into the checkpoint file in units of second.
  • default: 0.0, this means NO checkpoint files will be loaded and saved.
• "Verbose"
  • print message with the parameter before and after calculation
  • default: false

Output

jks::JackknifeSet is a mapping from names to MCMC observables (JackknifeSet is an alias of Dict{String, Jackknife}). jk::Jackknife is a MCMC observable whose statistics are calculated by jack-knife method. Users can retrieve mean, variance, standard deviation, standard error, and $p \%$ confidence interval of jk by mean(jk), var(jk), stddev(jk), stderror(jk), and confidence_interval(jk, p/100), respectively.

The set of calculated quantities depends on the model (an estimator and a postproc). Please see the online document of specific functions (ex., simple_estimator(::Ising)).

Multiple simulations

runMC can take a list of parameters as an input instead of a single parameter and performs MCMC calculation for each parameter and returns a list of results. When a keyword arg parallel = true is passed, runMC performs MCMC calculations in parallel by using pmap function instead of map.

Restart

If param["Checkpoint Interval"] > 0.0, runMC saves the state of calculation (the state of the model and the random number generator) into a checkpoint file named "$(param["Checkpoint Filename Prefix"])_$(param["ID"]).dat" every param["Checkpoint Interval"] seconds.

If a checkpoint file exists and param["Checkpoint Interval"] > 0.0, runMC loads this file and restarts the pending simulation.

runMC(params::AbstractArray) has a keyword argument, autoID::Bool (default=true). If true, ["ID"] will be automatically set (overwritten) as params[i]["ID"] = i.

NOTE: Restart will fail if the version or the system image of julia changes (see the doc of Serialization.serialize).