dimod.utilities.qubo_to_ising#
- qubo_to_ising(Q, offset=0.0)[source]#
Convert a QUBO problem to an Ising problem.
Map a quadratic unconstrained binary optimization (QUBO) problem \(x' Q x\) defined over binary variables (0 or 1 values), where the linear term is contained along the diagonal of Q, to an Ising model defined on spins (variables with {-1, +1} values). Return h and J that define the Ising model as well as the offset in energy between the two problem formulations:
\[x' Q x = offset + s' J s + h' s\]See
ising_to_qubo()for the inverse function.- Parameters:
Q (dict[(variable, variable), coefficient]) – QUBO coefficients in a dict of form {(u, v): coefficient, …}, where keys are 2-tuples of variables of the model and values are biases associated with the pair of variables. Tuples (u, v) represent interactions and (v, v) linear biases.
offset (numeric, optional, default=0) – Constant offset to be applied to the energy. Default 0.
- Returns:
A 3-tuple containing:
dict: Linear coefficients of the Ising problem.
dict: Quadratic coefficients of the Ising problem.
float: New energy offset.
- Return type:
Examples
This example converts a QUBO problem of two variables that have positive biases of value 1 and are positively coupled with an interaction of value 1 to an Ising problem, and shows the new energy offset.
>>> Q = {(1, 1): 1, (2, 2): 1, (1, 2): 1} >>> dimod.qubo_to_ising(Q, 0.5)[2] 1.75