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What does Bidirectional LSTM Neural Networks has to do with Top Quarks?
Latest   Machine Learning

What does Bidirectional LSTM Neural Networks has to do with Top Quarks?

Last Updated on July 20, 2023 by Editorial Team

Author(s): Riccardo Di Sipio

Originally published on Towards AI.

And how it turned out that looking at a sequence of vectors in four dimensions from two opposite sides was the key to solve a decades-old problem

In a recent paper Bidirectional Long Short-Term Memory (BLSTM) neural networks for reconstruction of top-quark pair decay kinematics (preprint: arXiv:1909.01144), my summer student Fardin explored a number of techniques to reconstruct the decay chain of a fundamental particle called top quark that is abundantly produced at the LHC. This particle decays preferably into a W boson and a bottom quark (t→Wb). The W boson, in turn, can decay into a pair of quarks (W→qq’) in two-thirds of the cases or a charged lepton and a neutrino (W→lv) in the remaining one-third of the cases. The most common process leading to… Read the full blog for free on Medium.

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