```
import numpy as np
import pandas as pd
import dimod
```

### Defining a sample QUBO 
\begin{equation}
H_{1}^{QUBO}=-4.4x_{1}^2+0.6x_{2}^2-2x_{3}^2+2.8x_{1}x_{2}-0.8x_{2}x_{3}+2.4
\end{equation}


```
linear = {0: -4.4, 1: 0.6, 2: -2}
quadratic = {(0,1): 2.8, (1,2):-0.8}
offset = 2.4

bqm_qubo = dimod.BinaryQuadraticModel(linear,quadratic,offset,dimod.Vartype.BINARY)
print(bqm_qubo)
print('\n',bqm_qubo.to_numpy_matrix().astype(float))
```

    BinaryQuadraticModel({0: -4.4, 1: 0.6, 2: -2.0}, {(0, 1): 2.8, (1, 2): -0.8}, 2.4, 'BINARY')
    
     [[-4.4  2.8  0. ]
     [ 0.   0.6 -0.8]
     [ 0.   0.  -2. ]]



```
from dwave.system import LeapHybridSampler
sampler = LeapHybridSampler() # 'hybrid_binary_quadratic_model_version2'
```


```
sampler.properties
```




    {'minimum_time_limit': [[1, 3.0],
      [1024, 3.0],
      [4096, 10.0],
      [10000, 40.0],
      [30000, 200.0],
      [100000, 600.0],
      [1000000, 600.0]],
     'maximum_time_limit_hrs': 24.0,
     'maximum_number_of_variables': 1000000,
     'maximum_number_of_biases': 200000000,
     'parameters': {'time_limit': None},
     'supported_problem_types': ['bqm'],
     'category': 'hybrid',
     'version': '2.0',
     'quota_conversion_rate': 20}




```
sampleset = sampler.sample(bqm_qubo)
print(sampleset)
```

       0  1  2 energy num_oc.
    0  1  0  1   -4.0       1
    ['BINARY', 1 rows, 1 samples, 3 variables]



```

```

68bb9d9f0b49680d489f1d1748f4b2f2dc35a7ae
ipynb
Jupyter Notebook
D'wave tutorials/7.D-wave Hybrid Solvers.ipynb
speQtrum/Ising_Annealing_Machines
f7da721c29314fc898436103a1501dcf6c05ce9c
MIT
2021-04-02T02:33:02.000Z
2021-04-03T02:08:14.000Z
D'wave tutorials/7.D-wave Hybrid Solvers.ipynb
speQtrum/Ising_Annealing_Machines
f7da721c29314fc898436103a1501dcf6c05ce9c
MIT
D'wave tutorials/7.D-wave Hybrid Solvers.ipynb
speQtrum/Ising_Annealing_Machines
f7da721c29314fc898436103a1501dcf6c05ce9c
MIT
2021-04-06T13:34:47.000Z
2022-03-17T00:45:08.000Z
Qwen/Qwen-72B
1. YES
2. YES