A 10-qubit convolutional quantum graph neural network fed by autoencoder-compressed jet data achieves performance comparable to classical graph networks in distinguishing boosted Z jets from gluon jets.
Interplay of Direct and Indirect Searches for New Physics
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abstract
We report recent work on the interplay of collider and flavour physics regarding the search for physics beyond the Standard Model.
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hep-ph 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
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Quantum enhanced identification of boosted jets with quantum graph neural networks
A 10-qubit convolutional quantum graph neural network fed by autoencoder-compressed jet data achieves performance comparable to classical graph networks in distinguishing boosted Z jets from gluon jets.