mindquantum.algorithm.qaia.LSB
- class mindquantum.algorithm.qaia.LSB(J, h=None, x=None, n_iter=1000, batch_size=1, backend='cpu-float32', dt=1, xi=None, threshold=8)[source]
Logarithmic Quantized Simulated Bifurcation.
Reference: Quantized Simulated Bifurcation for the Ising Model.
Note
For memory efficiency, the input array 'x' is not copied and will be modified in-place during optimization. If you need to preserve the original data, please pass a copy using x.copy().
- Parameters
J (Union[numpy.array, scipy.sparse.spmatrix]) – The coupling matrix with shape \((N x N)\).
h (numpy.array) – The external field with shape \((N, )\).
x (numpy.array) – The initialized spin value with shape \((N x batch_size)\). Default:
None.n_iter (int) – The number of iterations. Default:
1000.batch_size (int) – The number of sampling. Default:
1.backend (str) – Computation backend and precision to use: 'cpu-float32', 'gpu-float32'. Default:
'cpu-float32'.dt (float) – The step size. Default:
1.xi (float) – positive constant with the dimension of frequency. Default:
None.threshold (int) – dynamic threshold. Default:
8.