# About this Document¶

*Solvers*—compute resources to which you submit problems—accept
certain parameters that define the problem to be solved and parameters that
control how the problem is run. Solvers can be queried through SAPI for their
properties, which characterize their behaviors and supported features.

For an example of properties, D-Wave QPUs have a num_reads_range property that advertises the range you can set for the number of requested anneals on a problem:

```
>>> from dwave.system import DWaveSampler
>>> DWaveSampler().properties["num_reads_range"]
[1, 10000]
```

For an example of parameters, a Leap’s
hybrid solver might accept a
discrete binary model (DQM) and
Assign Problem Labels as its *problem parameters* and time_limit as
a *controlling parameter*, where the supported values of the latter are
specified by this solver’s minimum_time_limit property.

```
>>> from dwave.system import LeapHybridDQMSampler
>>> dqm = dimod.DiscreteQuadraticModel.from_file("my_dqm_problem")
>>> LeapHybridDQMSampler().sample_dqm(dqm, time_limit=10)
```

This document lists the supported problem parameters and the properties and parameters of the following solvers:

- QPU Solvers
- QPU-Like Solvers, including the VFYC solver, optimizing emulators, and sampling emulators
- Leap’s Hybrid Solvers
- Ising Heuristic Solvers

Note

Not all accounts have access to all solver types.