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Qubit-Efficient Encoding Techniques for Solving QUBO Problems
- Classical algorithms are effective for optimization with low variable counts but struggle with larger problems due to combinatorial explosion.
- Quantum computing, utilizing superposition and entanglement, offers a parallel approach for large problems like QUBO.
- QAOA, a popular quantum algorithm for QUBO, requires 1 qubit per binary variable making it resource-intensive for large-scale problems.
- Qubit-efficient methods like PGE, ABE, and ACE offer alternatives suitable for NISQ devices and combinatorial optimization.
- These methods use fewer qubits and are scalable even on near-term quantum hardware.
- An image segmentation example is used to demonstrate the qubit-efficient techniques discussed.
- PGE encodes binary segmentation masks in rotation parameters of a diagonal gate requiring fewer qubits.
- The process involves quantum circuit initialization, encoding binary values, and cost function evaluation.
- A classic optimizer is used to optimize the result, mapping parameters to bits based on a threshold.
- The article references various quantum papers detailing the qubit-efficient encoding schemes used.
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