ExactSolver

```markdown
### D-Wave Training Project

#### Objective

The goal of this project was to solve a constraint satisfaction problem using D-Wave's quantum computing libraries.

#### Code Snippet

```python
import dimod
import dwavebinarycsp
# Define the graph
edges = [('0', '1'), ('0', '2'), ('0', '3'), ('1', '2'), ('1', '3'), ('2', '3')]
# Create a binary constraint satisfaction problem (CSP)
csp = dwavebinarycsp.ConstraintSatisfactionProblem(dwavebinarycsp.BINARY)
# Add constraints for equal-sized subsets
# Add objective function for minimizing the number of edges between subsets
# Convert the CSP to a binary quadratic model (BQM)
bqm = dwavebinarycsp.stitch(csp)
# Set up the solver and solve the problem
solver = dimod.ExactSolver()
solution = solver.sample(bqm)
# Print the solutions
for sample, energy in solution.data(['sample', 'energy']):
    print(sample, energy)
```

#### Mathematical Explanation

The graph edges are represented by the set \( \left\{ ('0', '1'), ('0', '2'), ('0', '3'), ('1', '2'), ('1', '3'), ('2', '3') \right\} \).

#### Resources

- [Gist for this project](https://gist.github.com/ec9b043b5ed5b1bc02a11198b4efb4a8)
- [Additional Information](https://davidmerwin.pieces.cloud/?p=071f45aa12)

## Contact

Feel free to reach out to me for collaborations, questions, or to chat about quantum computing!