Alexander Condello

Currently this can be done with ```python sampleset = LeapHybridCQMSampler().sample_cqm(cqm) feasible_sampleset = sampleset.filter(lambda d: d.is_feasible) ``` see https://github.com/dwavesystems/dimod/blob/ec9c3b274ff4104c00fe702d680b320f0bffca25/dimod/sampleset.py#L1371 It would be relatively straightforward to add a `filter_feasible` (or similar) keyword...

DWaveSampler.get_samplers or similar

2

Analogous to [Client.get_solvers](https://docs.ocean.dwavesys.com/projects/cloud-client/en/stable/reference/generated/dwave.cloud.client.Client.get_solvers.html#dwave.cloud.client.Client.get_solvers) but at the `DWaveSampler` level. Something like ``` samplers = DWaveSampler(solver=dict(qpu=True)).get_samplers() ``` or possibly ``` sampler = DWaveSampler.get_samplers(qpu=True) ``` would only need to be a thin wrapper.

Warnings documentation and additional modes

1

The warnings submodule is not currently documented. It also has two more modes that need to be implemented, logging and raising.

Raise a more informative error message when passing BQM to DQM sampler

7

Currently `LeapHybridDQMSampler().sample_dqm(bqm)` raises `AttributeError: 'BinaryQuadraticModel' object has no attribute 'num_variable_interactions'`, this should be more informative.

Adapt TilingComposite to Pegasus architecture

2

Right now the `TilingComposite` is only defined for Chimera-structured hardware graphs. See also #294

Right now, setting [chain_break_fraction](https://github.com/dwavesystems/dwave-system/blob/ecbb0267a4d6a7a0f7b54620471a8fc09b016841/dwave/embedding/transforms.py#L545) to `True` returns the fraction of chains broken in each sample. Users are sometimes interested in knowing, across all samples, what fraction of times each qubit...

The information is in the solver properties and can be used to save time/internet bandwidth before submission.

Currently we only return the "problem id", not the id of the submitted bqm/dqm, called the "bqm id". This is a requirement for #397

Allow sampling by id from DWaveSampler, LeapHybridSampler, LeapHybridDQMSampler

9

We could either accept ids in the `.sample` method, ``` sampleset = LeapHybridSampler().sample(id_) ``` or be more explicit ``` sampleset = LeapHybridSampler().sample_id(id_) ``` My preference is for the latter, since...

Probably either generating random solutions or possibly converting to BQM and then solving in that domain.