12.3 Photonic Quantum Computing

Photonic quantum computing harnesses the quantum properties of light particles to process information. By encoding qubits in photon states like polarization or path, this approach offers advantages like low decoherence and room-temperature operation.

Despite challenges like weak photon interactions, researchers explore various techniques to realize photonic quantum computers. From linear optical quantum computing to integrated photonic circuits, these approaches aim to leverage light's unique properties for quantum information processing.

Fundamentals of Photonic Quantum Computing

Photons as quantum computing qubits

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• Photons serve as quantum information carriers exploiting wave-particle duality of light
• Quantum properties of photons enable superposition and entanglement for qubit operations
• Encoding quantum information in photons utilizes polarization states as qubit basis (horizontal/vertical)
• Path encoding leverages spatial modes for qubit representation (upper/lower path)
• Time-bin encoding uses temporal separation for qubit states (early/late arrival)
• Manipulation of photonic qubits employs single-qubit gates using wave plates and beam splitters
• Two-qubit gates implemented through nonlinear optical effects (parametric down-conversion)

Advantages of photonic quantum computing

• Low decoherence due to weak interaction with environment leads to long coherence times
• Room temperature operation eliminates need for cryogenic cooling systems
• Compatibility with existing optical technologies enables integration with fiber optic networks
• Leverages advancements in classical photonics for improved components (lasers, detectors)
• High-speed operations achieve light-speed information processing
• Potential for scalability through multiplexing techniques (wavelength division, spatial mode)

Challenges in photonic quantum computing

• Weak photon-photon interactions necessitate nonlinear media or ancillary systems for entangling operations
• Probabilistic nature of certain operations impacts scalability and increases error rates
• Photon loss and detection inefficiencies affect quantum circuit fidelity
• Precise control of photon states requires maintaining coherence during complex manipulations
• Integration of multiple components poses miniaturization and on-chip implementation difficulties

Approaches to photonic quantum computing

• Linear optical quantum computing (LOQC) utilizes Knill-Laflamme-Milburn (KLM) protocol
• Measurement-induced nonlinearities enable two-qubit gates in LOQC
• Cluster state model provides alternative approach to universal quantum computation
• Cavity-based systems exploit cavity quantum electrodynamics (CQED)
• Strong coupling between photons and atoms/quantum dots enhances photon-photon interactions
• Integrated photonic circuits leverage silicon photonics and lithium niobate platforms
• Hybrid approaches combine optomechanical systems with atomic ensembles for quantum memories
• Boson sampling demonstrates non-universal quantum computing model for quantum supremacy