qat.qpus.SimulatedAnnealing

class qat.qpus.SimulatedAnnealing(temp_t, n_steps, seed=None)

A Simulated Annealing solver interfaced as a Quantum Processing Unit (QPU)

Parameters:

• temp_t (ArithExpression) – temperature-time dependence. It needs to be specified using a variable t instantiated with the class Variable.

• n_steps (int) – number of annealing time steps in Temp(t) evolution.

• seed (int, optional) – Randomness seed.

submit(batch: Batch, meta_data: dict = None) → BatchResult

Executes a batch of jobs and returns the corresponding list of Results.

Parameters:

batch (Batch) – a batch of jobs. If a single job is provided, the job is embedded into a Batch, executed, and the first result is returned.

Returns:

a batch result

Return type:

(BatchResult)

qat.simulated_annealing.service.extract_j_and_h_from_obs(obs)

A function to extract the \(J\) coupling matrix, magnetic field \(h\) and Ising energy offset \(E_I\) from the Hamiltonian of an Ising problem. The Hamiltonian should be of the form

\[H = - \sum_{ij} J_{ij} s_i s_j - \sum_i h_i s_i - E_I\]

with \(s_i, s_j \in \{-1,1\}\).

Parameters:

obs (Observable) – an observable for an Ising problem

Returns:

3-element tuple containing

• J (2D numpy array) - an array with the coupling between each two spins - it represents the \(J\) matrix from the Hamiltonian of the problem

• h (1D numpy array) - an array with the magnetic field acting on each of the spins, coming from the Hamiltonian of the problem

• offset_i (double) - the value of the Ising offset energy in the respective Hamiltonian