Utilities#

Utility functions.

common_working_graph(graph0, graph1)

Creates a graph using the common nodes and edges of two given graphs.

coupling_groups(hardware_graph)

Generate groups of couplers for which a limit on total coupling applies for each group.

Temperature and Unit-Conversion Utilities#

The following effective temperature and bias estimators are provided:

  • Maximum pseudo-likelihood is an efficient estimator for the temperature describing a classical Boltzmann distribution P(x) = exp(-H(x)/T)/Z(T) given samples from that distribution, where H(x) is the classical energy function. The following links describe features of the estimator in application to equilibrium distribution drawn from binary quadratic models and non-equilibrium distributions generated by annealing: https://www.jstor.org/stable/25464568 https://doi.org/10.3389/fict.2016.00023

  • An effective temperature can be inferred assuming freeze-out during the anneal at s=t/t_a, an annealing schedule, and a device physical temperature. Necessary device-specific properties are published for online solvers: https://docs.dwavesys.com/docs/latest/doc_physical_properties.html

  • The biases (h) equivalent to application of flux bias, or vice-versa, can be inferred as a function of the anneal progress s=t/t_a by device-specific unit conversion. The necessary parameters for estimation [Mafm, B(s)] are published for online solvers: https://docs.dwavesys.com/docs/latest/doc_physical_properties.html

effective_field(bqm[, samples, ...])

Returns the effective field for all variables and all samples.

fast_effective_temperature([sampler, ...])

Provides an estimate to the effective temperature, \(T\), of a sampler.

fluxbias_to_h([fluxbias, Ip, B, MAFM, ...])

Convert flux biases to equivalent problem Hamiltonian bias h.

freezeout_effective_temperature(freezeout_B, ...)

Provides an effective temperature as a function of freezeout information.

h_to_fluxbias([h, Ip, B, MAFM, units_Ip, ...])

Convert problem Hamiltonian bias h to equivalent flux bias.

Ip_in_units_of_B([Ip, B, MAFM, units_Ip, ...])

Estimate qubit persistent current \(I_p(s)\) in schedule units.

maximum_pseudolikelihood_temperature([bqm, ...])

Returns a sampling-based temperature estimate.