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Unsupervised Particle Tracking with Neuromorphic Computing
A spiking neural network learns to identify charged-particle trajectories amid noise, supporting event-driven detector processing.
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TomOpt: differential optimisation for task- and constraint-aware design of particle detectors in the context of muon tomography
Task and cost constraints guide differentiable detector optimisation in muon tomography, illustrating application-aware instrument co-design.
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Artificial nanophotonic neuron with internal memory for biologically inspired and reservoir network computing
A nanophotonic neuron concept explores internal memory and dynamics relevant to biologically inspired and reservoir computing.
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Toward the end-to-end optimization of particle physics instruments with differentiable programming
Differentiable programming connects detector hardware, reconstruction and scientific objectives in a single optimisation problem.
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InP photonic integrated multi-layer neural networks: Architecture and performance analysis
A wavelength-multiplexed InP architecture shows how weighted optical connections and nonlinear elements can form multiple neural-network layers.
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Synaptic Delays for Insect-Inspired Temporal Feature Detection in Dynamic Neuromorphic Processors
Synaptic delays enable temporal feature detection in neuromorphic processors, providing background for processing time-structured sensor signals.
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Deep Neural Network Through an InP SOA-Based Photonic Integrated Cross-Connect
An InP semiconductor-optical-amplifier cross-connect provides background for integrated photonic neural-network architectures.
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