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proposal

qemcmc.sampler.proposal

Proposal 

Proposal(model)

Bases: ABC

Abstract base class for producing proposals for Markov Chain Monte Carlo algorithms.

Subclasses implement the proposal mechanism by defining an update(state) method that generates a candidate state from the current one (e.g. single-spin flips, block updates, or quantum proposals).

Parameters:

Name Type Description Default
model EnergyModel

Energy model defining the target distribution over spin configurations.

 required
Source code in src/qemcmc/sampler/proposal.py 
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def __init__(self, model: EnergyModel):
    self.model = model
    self.n_spins = model.n_spins

update abstractmethod 

update(state)

Generate a candidate state from the current state using the proposal mechanism.

This method should be implemented by subclasses to define the specific proposal strategy (e.g., single-spin flips, block updates, or quantum proposals).

Parameters:

Name Type Description Default
state MCMCState

The current state of the Markov chain.

 required

Returns:

Type Description
MCMCState

A new candidate state.
Source code in src/qemcmc/sampler/proposal.py 
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@abstractmethod
def update(self, state: MCMCState) -> MCMCState:
    """
    Generate a candidate state from the current state using the proposal mechanism.

    This method should be implemented by subclasses to define the specific proposal strategy
    (e.g., single-spin flips, block updates, or quantum proposals).

    Parameters
    ----------
    state : MCMCState
        The current state of the Markov chain.

    Returns
    -------
    MCMCState
        A new candidate state.
    """
    pass