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Resource-efficient inference for particle physics

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Selecting interesting proton–proton collisions from the millions taking place each second in the Large Hadron Collider is a challenging task. A neural network optimized for a field-programmable gate array hardware enables 60 ns inference and reduces power consumption by a factor of 50.

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Fig. 1: Display of the hundreds of particles recorded in one proton collision at the Large Hadron Collider.

References

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Correspondence to David Rousseau.

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Rousseau, D. Resource-efficient inference for particle physics. Nat Mach Intell 3, 656–657 (2021). https://doi.org/10.1038/s42256-021-00381-4

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