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Physical Review D

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J. High Energ. Phys. (1)Phys. Rev. D (1)

Articles Citing

Deep neural network driven simulation based inference method for pole position estimation under model misspecification

Daniel Sadasivan ^1,*, Isaac Cordero^1,†, Andrew Graham^1,‡, Cecilia Marsh ^1,§, Daniel Kupcho^1,∥, Melana Mourad^1,¶, and Maxim Mai ^2,3,**

¹Ave Maria University, Ave Maria, Florida 34142, USA
²Albert Einstein Center for Fundamental Physics, Institute for Theoretical Physics, University of Bern, Sidlerstrasse 5, Bern 3012, Switzerland
³Department of Physics, The George Washington University, 725 21st St, NW, Washington, DC 20052, USA

^*Contact author: daniel.sadasivan@avemaria.edu
^†Contact author: isaac.cordero@my.avemaria.edu
^‡Contact author: andrew.graham@my.avemaria.edu
^§Contact author: cecilia.marsh@my.avemaria.edu
^∥Contact author: daniel.kupcho@my.avemaria.edu
^¶Contact author: melana.mourad@my.avemaria.edu
^**Contact author: maxim.mai@faculty.unibe.ch

Deep learning topological inference-guided Tcc+ pole parameter extraction

Julius B. Pagayon, Klarence Tomas R. Cervantes, and Denny Lane B. Sombillo

Phys. Rev. D 114 014049 (2026)

The a1(1420) in a unitary coupled-channel three-body approach

Ajay S. Sakthivasan, Yuchuan Feng, Michael Döring, and Maxim Mai

J. High Energ. Phys. 2026 45 (2026)

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ISSN 2470-0029 (online), 2470-0010 (print).

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