ommx_openjij_adapter

Functions

response_to_samples(→ ommx.v1.Samples)

Convert OpenJij's Response to ommx.v1.Samples

sample_qubo_sa(→ ommx.v1.Samples)

Sampling QUBO with Simulated Annealing (SA) by [openjij.SASampler](https://openjij.github.io/OpenJij/reference/openjij/index.html#openjij.SASampler)

Package Contents

ommx_openjij_adapter.response_to_samples(response: openjij.Response) → ommx.v1.Samples

Convert OpenJij’s Response to ommx.v1.Samples

ommx_openjij_adapter.sample_qubo_sa(instance: ommx.v1.Instance, *, beta_min: float | None = None, beta_max: float | None = None, num_sweeps: int | None = None, num_reads: int | None = None, schedule: list | None = None, initial_state: list | dict | None = None, updater: str | None = None, sparse: bool | None = None, reinitialize_state: bool | None = None, seed: int | None = None) → ommx.v1.Samples

Sampling QUBO with Simulated Annealing (SA) by [openjij.SASampler](https://openjij.github.io/OpenJij/reference/openjij/index.html#openjij.SASampler)

The input instance must be a QUBO (Quadratic Unconstrained Binary Optimization) problem, i.e.

  • Every decision variables are binary

  • No constraint

  • Objective function is quadratic

  • Minimization problem

You can convert a problem to QUBO via [ommx.v1.Instance.penalty_method](https://jij-inc.github.io/ommx/python/ommx/autoapi/ommx/v1/index.html#ommx.v1.Instance.penalty_method) or other corresponding method.

Parameters:

  • instance – ommx.v1.Instance representing a QUBO problem

  • beta_min – minimal value of inverse temperature

  • beta_max – maximum value of inverse temperature

  • num_sweeps – number of sweeps

  • num_reads – number of reads

  • schedule – list of inverse temperature

  • initial_state – initial state

  • updater – updater algorithm

  • sparse – use sparse matrix or not.

  • reinitialize_state – if true reinitialize state for each run

  • seed – seed for Monte Carlo algorithm

Note that this is a simple wrapper function for openjij.SASampler.sample_qubo method. For more advanced usage, you can use ommx.v1.Instance.as_qubo_format to get QUBO matrix, and use OpenJij manually, and convert the openjij.Response via response_to_samples function.