Lattice gauge equivariant convolutional neural networks M Favoni, A Ipp, DI Müller, D Schuh Physical Review Letters 128 (3), 032003, 2022 | 54 | 2022 |
Jet momentum broadening in the pre-equilibrium Glasma A Ipp, DI Müller, D Schuh Physics Letters B 810, 135810, 2020 | 40 | 2020 |
Anisotropic momentum broadening in the glasma: Analytic weak field approximation and lattice simulations A Ipp, DI Müller, D Schuh Physical Review D 102 (7), 074001, 2020 | 40 | 2020 |
Broken boost invariance in the Glasma via finite nuclei thickness A Ipp, D Müller Physics Letters B 771, 74-79, 2017 | 35 | 2017 |
Simulating collisions of thick nuclei in the color glass condensate framework D Gelfand, A Ipp, D Müller Physical Review D 94 (1), 014020, 2016 | 33 | 2016 |
Simulating jets and heavy quarks in the glasma using the colored particle-in-cell method D Avramescu, V Băran, V Greco, A Ipp, D Müller, M Ruggieri Physical Review D 107 (11), 114021, 2023 | 22 | 2023 |
Generalization capabilities of translationally equivariant neural networks S Bulusu, M Favoni, A Ipp, DI Müller, D Schuh Physical Review D 104 (7), 074504, 2021 | 22 | 2021 |
Tackling a VRP challenge to redistribute scarce equipment within time windows using metaheuristic algorithms A Kheiri, AG Dragomir, D Mueller, J Gromicho, C Jagtenberg, ... EURO Journal on Transportation and Logistics 8 (5), 561-595, 2019 | 19 | 2019 |
Progress on 3+1D Glasma simulations A Ipp, DI Müller The European Physical Journal A 56 (9), 1-9, 2020 | 18 | 2020 |
Implicit schemes for real-time lattice gauge theory A Ipp, D Müller The European Physical Journal C 78, 1-26, 2018 | 16 | 2018 |
Spacetime structure of color fields in high energy nuclear collisions A Ipp, DI Müller, S Schlichting, P Singh Physical Review D 104 (11), 114040, 2021 | 13 | 2021 |
Stabilizing complex Langevin for real-time gauge theories with an anisotropic kernel K Boguslavski, P Hotzy, DI Müller Journal of High Energy Physics 2023 (6), 1-42, 2023 | 10 | 2023 |
Simulations of the Glasma in 3+ 1D D Müller arXiv preprint arXiv:1904.04267, 2019 | 10 | 2019 |
Lattice gauge equivariant convolutional neural networks (2020) M Favoni, A Ipp, DI Müller, D Schuh arXiv preprint arXiv:2012.12901, 0 | 6 | |
Rapidity profiles from 3+1D glasma simulations with finite longitudinal thickness A Ipp, D Müller arXiv preprint arXiv:1710.01732, 2017 | 5 | 2017 |
A stabilizing kernel for complex Langevin simulations of real-time gauge theories K Boguslavski, P Hotzy, DI Müller arXiv preprint arXiv:2210.08020, 2022 | 4 | 2022 |
Generalization capabilities of translationally equivariant neural networks (2021) S Bulusu, M Favoni, A Ipp, DI Müller, D Schuh arXiv preprint arXiv:2103.14686, 0 | 4 | |
Applications of lattice gauge equivariant neural networks M Favoni, A Ipp, DI Müller EPJ Web of Conferences 274, 09001, 2022 | 3 | 2022 |
Energy-momentum tensor of the dilute (3+ 1) D Glasma A Ipp, M Leuthner, DI Müller, S Schlichting, K Schmidt, P Singh arXiv preprint arXiv:2401.10320, 2024 | 2 | 2024 |
Studying the 3+ 1D structure of the Glasma using the weak field approximation A Ipp, M Leuthner, DI Müller, S Schlichting, P Singh EPJ Web of Conferences 274, 05017, 2022 | 2 | 2022 |