2025-12-05 14:06 |
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2025-12-05 04:52 |
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NNLO+NNLL Predictions for Heavy-Jet Mass and C-parameter in Higgs Decays to Quarks and Gluons
/ Fox, Elliot (Durham U., IPPP) ; Gehrmann-De Ridder, Aude (Zurich, ETH ; Zurich U.) ; Gehrmann, Thomas (Zurich U.) ; Glover, Nigel (Durham U., IPPP ; Zurich U. ; CERN) ; Marcoli, Matteo (Durham U., IPPP) ; Preuss, Christian T. (Gottingen U.)
We consider the resummation of large logarithmic corrections arising in the two-particle limit at next-to-next-to-leading logarithmic (NNLL) accuracy for the heavy-jet mass and $C$-parameter distributions in the decay of a Higgs boson to quarks and gluons: $H\to b\bar{b}$, $H\to c\bar{c}$, and $H\to gg$. [...]
IPPP/25/85 ; ZU-TH 82/25 ; MCNET-25-27 ; arXiv:2512.03263.
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2025-12-05 04:51 |
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2025-12-04 06:02 |
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2025-12-04 04:29 |
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High-Resolution Laser Spectroscopy on the Hyperfine Structure of $^{255}$Fm (Z=100)
/ Urquiza-González, M. (U. Gothenburg (main)) ; Stemmler, M. (Mainz U. ; Leibniz U., Hannover) ; Albrecht, T.E. (Florida State U., Tallahassee (main)) ; Bally, B. (Darmstadt, Tech. U.) ; Bender, M. (IP2I, Lyon) ; Berndt, S. (Mainz U.) ; Block, M. (Mainz U. ; Helmholtz Inst., Mainz ; Darmstadt, GSI) ; Brizard, A. (Darmstadt, GSI ; GANIL) ; Andrews, J.S. (Helmholtz Inst., Mainz ; Darmstadt, GSI) ; Bieron, J. (Jagiellonian U.) et al.
We report on high-resolution laser spectroscopy of $^{255}$Fm ($T_{1/2} = 20$h), one of the heaviest nuclides available from reactor breeding. [...]
arXiv:2511.20921.
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2025-12-04 04:26 |
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High Density Hybridisation Using ENIG Bumping and Anisotropic Conductive Films
/ Bangaru, Haripriya (CERN) ; Calderini, Giovanni (LPNHE, Paris) ; Dannheim, Dominik (CERN) ; De Oliveira, Rui (CERN) ; Lale, Ahmet (CERN) ; Lauser, Moritz (KIT, Karlsruhe) ; Pinto, Mateus Vicente Barreto (Geneva U.) ; Svihra, Peter (CERN ; LPNHE, Paris)
Fine-pitch hybridisation processes are essential for next-generation pixel detectors and high-density microelectronic assemblies. [...]
arXiv:2511.15562.
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2025-12-04 04:25 |
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hls4ml: A Flexible, Open-Source Platform for Deep Learning Acceleration on Reconfigurable Hardware
/ Schulte, Jan-Frederik (Purdue U.) ; Ramhorst, Benjamin (Zurich, ETH) ; Sun, Chang (Caltech) ; Mitrevski, Jovan (Fermilab) ; Ghielmetti, Nicolò (CERN) ; Lupi, Enrico (CERN) ; Danopoulos, Dimitrios (CERN) ; Lončar, Vladimir (Belgrade, Inst. Phys. ; CERN) ; Duarte, Javier (UC, San Diego (main)) ; Burnette, David (KETEK, Munich) et al.
We present hls4ml, a free and open-source platform that translates machine learning (ML) models from modern deep learning frameworks into high-level synthesis (HLS) code that can be integrated into full designs for field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs). [...]
arXiv:2512.01463.
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2025-12-03 20:22 |
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2025-12-03 04:49 |
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2025-12-02 07:34 |
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