A MERA-based autoencoder supplies a locality-aware hierarchical inductive bias that improves reconstruction-based anomaly detection for collider jets, with disentanglers providing benefit at strong compression bottlenecks.
Classical versus quantum: Comparing tensor-network-based quantum circuits on Large Hadron Collider data
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Quantum-Inspired Tensor Network Autoencoders for Anomaly Detection: A MERA-Based Approach
A MERA-based autoencoder supplies a locality-aware hierarchical inductive bias that improves reconstruction-based anomaly detection for collider jets, with disentanglers providing benefit at strong compression bottlenecks.