TilingComposite

Class

A dimod composite that tiles small problems multiple times to a Chimera-structured sampler.

The TilingComposite takes a problem that can fit on a small Chimera graph and replicates it across a larger Chimera graph to obtain samples from multiple areas of the solver in one call. For example, a 2x2 Chimera lattice could be tiled 64 times (8x8) on a fully-yielded D-Wave 2000Q system (16x16).

class TilingComposite(sampler, sub_m, sub_n, t=4)

Composite to tile a small problem across a Chimera-structured sampler.

Inherits from dimod.Sampler, dimod.Composite, and dimod.Structured.

Enables parallel sampling for small problems (problems that are minor-embeddable in a small part of a D-Wave solver’s Chimera graph).

The notation CN refers to a Chimera graph consisting of an NxN grid of unit cells. Each Chimera unit cell is itself a bipartite graph with shores of size t. The D-Wave 2000Q QPU supports a C16 Chimera graph: its 2048 qubits are logically mapped into a 16x16 matrix of unit cell of 8 qubits (t=4).

A problem that can be minor-embedded in a single unit cell, for example, can therefore be tiled across the unit cells of a D-Wave 2000Q as 16x16 duplicates. This enables sampling 256 solutions in a single call.

Parameters:

• sampler (dimod.Sampler) – Structured dimod sampler to be wrapped.
• sub_m (int) – Number of rows of Chimera unit cells for minor-embedding the problem once.
• sub_n (int) – Number of columns of Chimera unit cells for minor-embedding the problem once.
• t (int, optional, default=4) – Size of the shore within each Chimera unit cell.

Examples

This example instantiates a composed sampler using composite TilingComposite to tile a QUBO problem on a D-Wave solver, embedding it with composite EmbeddingComposite and selecting the D-Wave solver with the user’s default D-Wave Cloud Client configuration file. The two-variable QUBO represents a logical NOT gate (two nodes with biases of -1 that are coupled with strength 2) and is easily minor-embedded in a single Chimera cell (it needs only any two coupled qubits) and so can be tiled multiple times across a D-Wave solver for parallel solution (the two nodes should typically have opposite values).

>>> from dwave.system.samplers import DWaveSampler
>>> from dwave.system.composites import EmbeddingComposite
>>> from dwave.system.composites import TilingComposite
>>> sampler = EmbeddingComposite(TilingComposite(DWaveSampler(), 1, 1, 4))
>>> Q = {(1, 1): -1, (1, 2): 2, (2, 1): 0, (2, 2): -1}
>>> response = sampler.sample_qubo(Q)
>>> for sample in response.samples():    
...     print(sample)
...
{1: 0, 2: 1}
{1: 1, 2: 0}
{1: 1, 2: 0}
{1: 1, 2: 0}
{1: 0, 2: 1}
{1: 0, 2: 1}
{1: 1, 2: 0}
{1: 0, 2: 1}
{1: 1, 2: 0}
>>> # Snipped above response for brevity

Sampler Properties

TilingComposite.properties	dict – Properties in the form of a dict.
TilingComposite.parameters	dict[str, list] – Parameters in the form of a dict.

Composite Properties

TilingComposite.children	list – The single wrapped structured sampler.
TilingComposite.child	First child in children.

Structured Sampler Properties

TilingComposite.nodelist	list – List of active qubits for the structured solver.
TilingComposite.edgelist	list – List of active couplers for the D-Wave solver.
TilingComposite.adjacency	dict[variable, set] – Adjacency structure formatted as a dict, where keys are the nodes of the structured sampler and values are sets of all adjacent nodes for each key node.
TilingComposite.structure	Structure of the structured sampler formatted as a namedtuple Structure(nodelist, edgelist, adjacency), where the 3-tuple values are the nodelist and edgelist properties and adjacency() method.

Methods

TilingComposite.sample(bqm, **kwargs)	Sample from the provided binary quadratic model
TilingComposite.sample_ising(h, J, **parameters)	Samples from an Ising model using an implemented sample method.
TilingComposite.sample_qubo(Q, **parameters)	Samples from a QUBO using an implemented sample method.