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Ethan Davies

Publications and source records attributed to Ethan Davies.

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Modeling Optical Polarization Evolution in Myelinated Axon Waveguides with Realistic Imperfections

Biophotonic signaling via axons has been proposed as a potential mode of neural communication, where information might be encoded not only in photon number and wavelength but also in polarization. Although earlier computational studies have examined how structural imperfections influence optical transmission, their effects on polarization fidelity remain unexplored; previous modeling of polarization fidelity in myelinated axons has largely focused on idealized geometries. This study incorporates three structural imperfections characteristic of axons in vivo: variation in myelin thickness, non-circular cross-sectional geometry, and axonal bending, within a model that includes four nodes of Ranvier. We find that variation in myelin thickness alone has minimal impact on fidelity, while non-circular cross-sections show strong mode dependence. Axonal bending has the most significant influence, generating large fluctuations and deep fidelity dips. When all imperfections are combined in a single axon model, the simulations show substantial drops in fidelity, yet certain modes exhibit recovery, with repeated revivals reaching values of around 0.8, which exceeds the revivals observed in the single imperfection cases. Overall, the results indicate that although structural imperfections affect polarization, polarization-based biophotonic signals might remain recoverable even in realistic axons, lending support to the plausibility of polarization-based biophotonic signaling in the brain.

physics.bio-ph

Communication-Optimal Blind Quantum Protocols

A user, Alice, wants to get server Bob to implement a quantum computation for her. However, she wants to leave him blind to what she's doing. What are the minimal communication resources Alice must use in order to achieve information-theoretic security? In this paper, we consider a single step of the protocol, where Alice conveys to Bob whether or not he should implement a specific gate. We use an entropy-bounding technique to quantify the minimum number of qubits that Alice must send so that Bob cannot learn anything about the gate being implemented. We provide a protocol that saturates this bound. In this optimal protocol, the states that Alice sends may be entangled. For Clifford gates, we prove that it is sufficient for Alice to send separable states.

quant-ph

Quantum Algorithms for Drone Mission Planning

Mission planning often involves optimising the use of ISR (Intelligence, Surveillance and Reconnaissance) assets in order to achieve a set of mission objectives within allowed parameters subject to constraints. The missions of interest here, involve routing multiple UAVs visiting multiple targets, utilising sensors to capture data relating to each target. Finding such solutions is often an NP-Hard problem and cannot be solved efficiently on classical computers. Furthermore, during the mission new constraints and objectives may arise, requiring a new solution to be computed within a short time period. To achieve this we investigate near term quantum algorithms that have the potential to offer speed-ups against current classical methods. We demonstrate how a large family of these problems can be formulated as a Mixed Integer Linear Program (MILP) and then converted to a Quadratic Unconstrained Binary Optimisation (QUBO). The formulation provided is versatile and can be adapted for many different constraints with clear qubit scaling provided. We discuss the results of solving the QUBO formulation using commercial quantum annealers and compare the solutions to current edge classical solvers. We also analyse the results from solving the QUBO using Quantum Approximate Optimisation Algorithms (QAOA) and discuss their results. Finally, we also provide efficient methods to encode to the problem into the Variational Quantum Eigensolver (VQE) formalism, where we have tailored the ansatz to the problem making efficient use of the qubits available.

quant-ph

Efficient Post-Quantum Secured Blind Computation

In the medium term, quantum computing must tackle two key challenges: fault tolerance and security. Fault tolerance will be solved with sufficiently high quality experiments on large numbers of qubits, but the scale and complexity of these devices means that a cloud-based access model is likely to dominate. How can we risk evaluating valuable computations on an untrusted server? Here we detail a verifiable circuit-based model that only requires classical communication between parties. The server is blind to the details of the computation, which is computationally secure.

quant-ph

Optical Routing with Binary Optimisation and Quantum Annealing

A challenge for scalability of demand-responsive, elastic optical Dense Wavelength Division Multiplexing (DWDM) and Flexgrid networks is the computational complexity of allocating many optical routes on large networks. We demonstrate that demand satisfaction problems in communication networks can be formulated as quadratic unconstrained binary optimisation (QUBO) problems, and solved using a hybrid quantum annealer. Efficient encodings are developed which solve both unicast and multicast multicommodity-flow problems, while also adhering to individual requirements for maximum latency and resilience for each route. We present several QUBO formulations and analyse the qubit scaling. We demonstrate solutions using a hybrid solver, D-Wave Quantum Advantage QPU. Progress in generating optimal solutions with efficient use of computational resources will be beneficial to telecoms operators, enabling them to run dynamic optical network infrastructures which use resources efficiently, are resilient to local faults and cyber-attacks, and can be elastically responsive to demands.

cs.NI