AI and machine learning

1. M. Natarajan, Xiaoye S. Li, Weiqun Zhang. AstraAI: LLMs, Retrieval, and AST-Guided Assistance for HPC Codebases. 2026. DOI: 10.48550/arXiv.2603.27423
2. Xiaoyu Zhang, Yuxiao Yi, Lile Wang, Zhi-Qin John Xu, Tianhan Zhang, Yao Zhou. Deep Neural Networks for Modeling Astrophysical Nuclear Reacting Flows. Astrophysical Journal, 2025. DOI: 10.3847/1538-4357/adf331  arXiv: 2504.14180
3. Vansh Sharma, Andreas H. Rauch, Venkatramanan Raman. Accelerating CFD Simulations With Super-Resolution Feedback-Informed Adaptive Mesh Refinement. AIAA SCITECH 2025 Forum, 2025. DOI: 10.2514/6.2025-1467
4. Duoming Fan, D. Willcox, Christopher J. DeGrendele, M. Zingale, A. Nonaka. Neural Networks for Nuclear Reactions in MAESTROeX. Astrophysical Journal, 2022. DOI: 10.3847/1538-4357/ac9a4b  arXiv: 2207.10628
5. Steven I. Reeves, Dongwoo Lee, A. Reyes, C. Graziani, P. Tzeferacos. An Application of Gaussian Process Modeling for High-order Accurate Adaptive Mesh Refinement Prolongation. Communications in Applied Mathematics and Computational Science, 2020. DOI: 10.2140/camcos.2022.17.1  arXiv: 2003.08508

Astrophysics and cosmology

1. Xiaoyu Zhang, Lile Wang, Yang Gao, Yao Zhou. Direct Numerical Simulations of Oxygen-flame-driven Deflagration-to-detonation Transition in Type Ia Supernovae. Astrophysical Journal, 2025. DOI: 10.3847/1538-4357/ae28ce  arXiv: 2510.26152
2. C. Palenzuela, Miguel Bezares, S. Liebling, et al.. MHDuet: a high-order general relativistic radiation MHD code for CPU and GPU architectures. Classical and quantum gravity, 2025. DOI: 10.1088/1361-6382/ae255e  arXiv: 2510.13965
3. M. Zingale, Khanak Bhargava, Ryan Brady, Zhi Chen, S. Guichandut, Eric T. Johnson, Max Katz, Alexander Smith Clark. The Challenges of Modeling Astrophysical Reacting Flows. Journal of Physics: Conference Series, 2024. DOI: 10.1088/1742-6596/2997/1/012007  arXiv: 2411.12491
4. S. Guichandut, M. Zingale, Andrew Cumming. Hydrodynamical Simulations of Proton Ingestion Flashes in Type I X-Ray Bursts. Astrophysical Journal, 2024. DOI: 10.3847/1538-4357/ad81f7  arXiv: 2405.08952
5. B. Boyd, A. Calder, D. Townsley, M. Zingale. 3D Convective Urca Process in a Simmering White Dwarf. Astrophysical Journal, 2024. DOI: 10.3847/1538-4357/ad9bb0  arXiv: 2412.07938
6. M. Zingale, Zhi Chen, Eric T. Johnson, Max Katz, Alexander Smith Clark. Strong Coupling of Hydrodynamics and Reactions in Nuclear Statistical Equilibrium for Modeling Convection in Massive Stars. Astrophysical Journal, 2024. DOI: 10.3847/1538-4357/ad8a66  arXiv: 2403.14786
7. M. Buschmann. Sledgehamr: Simulating Scalar Fields with Adaptive Mesh Refinement. Astrophysical Journal, 2024. DOI: 10.3847/1538-4357/ad9ea2  arXiv: 2404.02950
8. Zhi X. Chen, M. Zingale, K. Eiden. Sensitivity of He Flames in X-Ray Bursts to Nuclear Physics. Astrophysical Journal, 2023. DOI: 10.3847/1538-4357/acec72  arXiv: 2306.16320
9. Lisa Consortium Waveform Working Group, Niaesh Afshordi, Sarp Akccay, et al.. Waveform modelling for the Laser Interferometer Space Antenna. Living Reviews in Relativity, 2023. DOI: 10.1007/s41114-025-00056-1  arXiv: 2311.01300
10. M. Zingale, Zhi Chen, Melissa Rasmussen, A. Polin, Max Katz, Alexander Smith Clark, Eric T. Johnson. Sensitivity of Simulations of Double-detonation Type Ia Supernovae to Integration Methodology. Astrophysical Journal, 2023. DOI: 10.3847/1538-4357/ad3441  arXiv: 2309.01802
11. B. D. Wibking and M. R. Krumholz. Quokka: A code for two-moment AMR radiation hydrodynamics on GPUs. Monthly Notices of the Royal Astronomical Society, 512:1343, 2022. DOI: 10.1093/mnras/stac439  arXiv: 2110.01792
12. M. Zingale, M. Katz, A. Nonaka, M. Rasmussen. An Improved Method for Coupling Hydrodynamics with Astrophysical Reaction Networks. Astrophysical Journal, 2022. DOI: 10.3847/1538-4357/ac8478  arXiv: 2206.01285
13. S. Couch, Jared Carlson, M. Pajkos, Brian O'Shea, A. Dubey, T. Klosterman. Towards performance portability in the Spark astrophysical magnetohydrodynamics solver in the Flash-X simulation framework. Parallel Computing, 2021. DOI: 10.1016/j.parco.2021.102830
14. A. Harpole, N. Ford, K. Eiden, M. Zingale, D. Willcox, Y. Cavecchi, M. Katz. Dynamics of Laterally Propagating Flames in X-Ray Bursts. II. Realistic Burning and Rotation. Astrophysical Journal, 2021. DOI: 10.3847/1538-4357/abee87  arXiv: 2102.00051
15. M. Buschmann, J. Foster, A. Hook, A. Peterson, D. Willcox, et al.. Dark matter from axion strings with adaptive mesh refinement. Nature Communications, 2021. DOI: 10.1038/s41467-022-28669-y  arXiv: 2108.05368
16. M. Zingale, M. Katz, D. Willcox, A. Harpole. Practical Effects of Integrating Temperature with Strang Split Reactions. Research Notes of the AAS, 2021. DOI: 10.3847/2515-5172/ABF3CB  arXiv: 2103.13193
17. A. Almgren, M. B. Sazo, J. Bell, A. Harpole, M. Katz, Jean M. Sexton, D. Willcox, Weiqun Zhang, M. Zingale. CASTRO: A Massively Parallel Compressible Astrophysics Simulation Code. Journal of Open Source Software, 2020. DOI: 10.21105/joss.02513
18. M. Katz, A. Almgren, M. B. Sazo, K. Eiden, K. Gott, A. Harpole, Jean M. Sexton, D. Willcox, Weiqun Zhang, M. Zingale. Preparing Nuclear Astrophysics for Exascale. International Conference for High Performance Computing, Networking, Storage and Analysis, 2020. DOI: 10.1109/SC41405.2020.00095  arXiv: 2007.05218
19. Duoming Fan, Andrew Nonaka, A. Almgren, A. Harpole, M. Zingale. MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver. Journal of Open Source Software, 2019. DOI: 10.3847/1538-4357/ab4f75
20. A. Harpole, Duoming Fan, M. Katz, A. Nonaka, D. Willcox, M. Zingale. Modelling low Mach number stellar hydrodynamics with MAESTROeX. Journal of Physics: Conference Series, 2019. DOI: 10.1088/1742-6596/1623/1/012015  arXiv: 1910.12979
21. M. Zingale, A. Almgren, M. B. Sazo, John B. Bell, K. Eiden, A. Harpole, M. Katz, Andrew Nonaka, D. Willcox, Weiqun Zhang. The Castro AMR Simulation Code: Current and Future Developments. Journal of Physics: Conference Series, 2019. DOI: 10.1088/1742-6596/1623/1/012021  arXiv: 1910.12578
22. K. Eiden, M. Zingale, A. Harpole, D. Willcox, Y. Cavecchi, M. Katz. Dynamics of Laterally Propagating Flames in X-Ray Bursts. I. Burning Front Structure. Astrophysical Journal, 2019. DOI: 10.3847/1538-4357/ab80bc  arXiv: 1912.04956
23. M. Zingale, M. Katz, John B. Bell, M. Minion, Andrew Nonaka, et al.. Improved Coupling of Hydrodynamics and Nuclear Reactions via Spectral Deferred Corrections. Astrophysical Journal, 2019. DOI: 10.3847/1538-4357/ab4e1d  arXiv: 1908.03661

Biological systems

1. B. Palmer, A. Almgren, Connah G. M. Johnson, A. Myers, W. Cannon. BMX: Biological modelling and interface exchange. Scientific Reports, 2023. DOI: 10.1038/s41598-023-39150-1

Earth system modeling

1. Balaji Muralidharan, Alexander Boschitsch, Glen R. Whitehouse. A Mixed Formulation Vorticity-Velocity Formulation using AMReX Framework for Wind Farm Modeling. AIAA SCITECH 2026 Forum, 2026. DOI: 10.2514/6.2026-0861
2. Soonpil Kang, Ann S. Almgren, M. Natarajan, Aaron Lattanzi, J. Mirocha, et al.. An Embedded Boundary Scheme for Three-Dimensional Flow Over Terrain on a Staggered Mesh. 2026. DOI: 10.48550/arXiv.2604.11959
3. Michael B. Kuhn, Marc T. Henry de Frahan, Prakash Mohan, et al.. AMR‐Wind: A Performance‐Portable, High‐Fidelity Flow Solver for Wind Farm Simulations. Wind Energy, 2025. DOI: 10.1002/we.70010
4. Tim Dammann, Nirav Dangi, J. van Wingerden, Wei Yu. Benchmark Study on Rotor Performance, Wake Dynamics, and Atmospheric Boundary Layers using NREL SOWFA-6 and AMR-WIND. Journal of Physics: Conference Series, 2025. DOI: 10.1088/1742-6596/3016/1/012034
5. Hannah Klion, Robert D. Hetland, Jean M. Sexton, A. Almgren, I. Grindeanu, K. Hinson, V. Mahadevan. REMORA: Regional Modeling of Oceans Refined Adaptively (built on AMReX). Journal of Open Source Software, 2025. DOI: 10.21105/joss.07958
6. Aaron Lattanzi, A. Almgren, E. Quon, M. Natarajan, B. Kosović, J. Mirocha, Bruce Perry, David Wiersema, D. Willcox, Xingqiu Yuan, Weiqun Zhang. ERF: Energy Research and Forecasting Model. Journal of Advances in Modeling Earth Systems, 2024. DOI: 10.1029/2024MS004884  arXiv: 2412.04395
7. Daniel S. Abdi, Ann S. Almgren, Francis X. Giraldo, Isidora Jankov. Comparison of adaptive mesh refinement techniques for numerical weather prediction. arXiv.org, 2024. DOI: 10.48550/arXiv.2404.16648
8. A. Almgren, A. Lattanzi, R. Haque, P. Jha, B. Kosovic, J. Mirocha, B. Perry, E. Quon, M. Sanders, D. Wiersema, D. Willcox, X. Yuan, and W. Zhang. ERF: Energy Research and Forecasting. Journal of Open Source Software, 8(87):5202, 2023. DOI: 10.21105/joss.05202

Fluids and combustion

1. Jumeng Fan, Xiangyu Zhang, Huahua Xiao, Longhua Hu, Luqing Wang, Honghao Ma, Xinming Qin, Yundong Zhang, Chao Wu. Three- versus two-dimensional numerical simulation of distorted tulip flame in stoichiometric hydrogen-air mixture. Combustion and Flame, 2026. DOI: 10.1016/j.combustflame.2025.114733
2. Anthony Carreon, Shuzhi Zhang, Shivank Sharma, Jagmohan Singh, Venkatramanan Raman. GPU Performance Modeling and Assessment of High-Speed Combustion Simulations Using Adaptive Mesh Refinement. AIAA SCITECH 2025 Forum, 2025. DOI: 10.2514/6.2025-1168
3. Yuqi Wang, Yadong Zeng, R. Deiterding, Jianhan Liang. An efficient GPU-accelerated adaptive mesh refinement framework for high-fidelity compressible reactive flows modeling. Computer Physics Communications, 2025. DOI: 10.1016/j.cpc.2025.109870  arXiv: 2506.02602
4. Tin-Hang Un, S. Navarro-Martinez. Stochastic fields with adaptive mesh refinement for high-speed turbulent combustion. Combustion and Flame, 2025. DOI: 10.1016/j.combustflame.2024.113897
5. J. Salinas, H. Kolla, Martin Rieth, et al.. In situ multi-tier auto-ignition detection applied to dual-fuel combustion simulations. Combustion and Flame, 2025. DOI: 10.1016/j.combustflame.2025.114273
6. Tin-Hang Un, S. Navarro-Martinez. On the performance of the joint velocity-scalar PDF method near walls. Proceedings of the Combustion Institute, 2025. DOI: 10.1016/j.proci.2025.105838
7. Emma M. Boyd, Eric Sandall, Maycon Meier, J. M. Quinlan, Brandon Runnels. A diffuse boundary method for phase boundaries in viscous compressible flow. Journal of Computational Physics, 2025. DOI: 10.1016/j.jcp.2026.114898  arXiv: 2502.16053
8. Ishan Srivastava, Andrew Nonaka, Weiqun Zhang, Alejandro L. Garcia, J. Bell. Molecular fluctuations inhibit intermittency in compressible turbulence. Journal of Fluid Mechanics, 2025. DOI: 10.1017/jfm.2025.10796  arXiv: 2501.06396
9. Maycon Meier, E. Schmidt, P. Martinez, J. M. Quinlan, Brandon Runnels. Diffuse interface method for solid composite propellant ignition and regression. Combustion and Flame, 2024. DOI: 10.1016/j.combustflame.2023.113120
10. Shivank Sharma, Ral Bielawski, O. Gibson, Shuzhi Zhang, Vansh Sharma, Andreas H. Rauch, Jagmohan Singh, Sebastian S. Abisleiman, M. Ullman, Shivam Barwey, Venkat Raman. An AMReX-based Compressible Reacting Flow Solver for High-speed Reacting Flows relevant to Hypersonic Propulsion. arXiv preprint, 2024. DOI: 10.48550/arXiv.2412.00900
11. Kaiyan Jin, Xiaodong Cai, Rong Hong, Lin Zhang, Jianhan Liang. Numerical investigation on flow choking induced by local heat release and large-scale flow separation in a supersonic combustor. Combustion and Flame, 2024. DOI: 10.1016/j.combustflame.2024.113627
12. Michael A. Meehan, John C. Hewson, P. Hamlington. High resolution numerical simulations of methane pool fires using adaptive mesh refinement. Proceedings of the Combustion Institute, 2024. DOI: 10.1016/j.proci.2024.105768
13. L. Esclapez, Marc Day, John Bell, et al.. PeleLMeX: an AMR Low Mach Number Reactive Flow Simulation Code without level sub-cycling. Journal of Open Source Software, 2023. DOI: 10.21105/joss.05450
14. Suryanarayan Ramachandran, Navneeth Srinivasan, T. Taneja, Hongyuan Zhang, Suo Yang. Numerical study of turbulent non-premixed cool flames at high and supercritical pressures: Real gas effects and dual peak structure. Combustion and Flame, 2023. DOI: 10.1016/j.combustflame.2023.112626
15. Suryanarayan Ramachandran, Navneeth Srinivasan, Zhiyan Wang, Arsam Behkish, Suo Yang. A numerical investigation of deflagration propagation and transition to detonation in a microchannel with detailed chemistry: Effects of thermal boundary conditions and vitiation. The Physics of Fluids, 2023. DOI: 10.1063/5.0155645
16. M. T. Henry de Frahan, Jonathan S. Rood, M. Day, H. Sitaraman, S. Yellapantula, Bruce A. Perry, R. Grout, A. Almgren, Weiqun Zhang, J. Bell, Jacqueline H. Chen. PeleC: An adaptive mesh refinement solver for compressible reacting flows. The international journal of high performance computing applications, 2022. DOI: 10.1177/10943420221121151
17. Baburaj Kanagarajan, J. M. Quinlan, B. Runnels. A diffuse interface method for solid-phase modeling of regression behavior in solid composite propellants. Combustion and Flame, 2021. DOI: 10.31224/osf.io/etq5j
18. H. Sitaraman, S. Yellapantula, M. H. D. Frahan, Bruce A. Perry, Jonathan S. Rood, R. Grout, M. Day. Adaptive mesh based combustion simulations of direct fuel injection effects in a supersonic cavity flame-holder. Combustion and Flame, 2021. DOI: 10.1016/J.COMBUSTFLAME.2021.111531
19. N. Wimer, M. Day, C. Lapointe, Michael A. Meehan, Amanda S. Makowiecki, et al.. Numerical simulations of buoyancy-driven flows using adaptive mesh refinement: structure and dynamics of a large-scale helium plume. Theoretical and Computational Fluid Dynamics, 2020. DOI: 10.1007/s00162-020-00548-6

High-performance computing

1. Chris Egersdoerfer, P. Carns, Shane Snyder, Robert B. Ross, Dong Dai. STELLAR: Storage Tuning Engine Leveraging LLM Autonomous Reasoning for High Performance Parallel File Systems. International Conference on Software Composition, 2025. DOI: 10.1145/3712285.3759887  arXiv: 2602.23220
2. Dewen Liu, Shuai He, Haoran Cheng, Yadong Zeng. Investigate the efficiency of incompressible flow simulations on CPUs and GPUs with BSAMR. ArXiv, 2024. DOI: 10.48550/arXiv.2405.07148
3. Michael Beebe, Rahulkumar Gayatri, K. Gott, Adam Lavely, Muhammad Haseeb, et al.. A Performance Analysis of GPU-Aware MPI Implementations Over the Slingshot-11 Interconnect. IEEE Conference on High Performance Extreme Computing, 2024. DOI: 10.1109/HPEC62836.2024.10938430
4. Jakob Luettgau, Shane Snyder, Tyler Reddy, Nikolaus Awtrey, Kevin Harms, J. L. Bez, Rui Wang, Robert Latham, P. Carns. Enabling Agile Analysis of I/O Performance Data with PyDarshan. Proceedings of the SC '23 Workshops of the International Conference on High Performance Computing, Network, Storage, and Analysis, 2023. DOI: 10.1145/3624062.3624207
5. Junmin Gu, Philip E. Davis, Greg Eisenhauer, William F. Godoy, A. Huebl, et al.. Organizing Large Data Sets for Efficient Analyses on HPC Systems. Journal of Physics: Conference Series, 2022. DOI: 10.1088/1742-6596/2224/1/012042
6. Francis Alexander, A. Almgren, John Bell, A. Bhattacharjee, Jacqueline H. Chen, et al.. Exascale applications: skin in the game. Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2020. DOI: 10.1098/rsta.2019.0056

Materials and devices

1. A. Nonaka, Yingheng Tang, Julian C. LePelch, Prabhat Kumar, Weiqun Zhang, Jorge A. Muñoz, Christian Fernandez-Soria, C. Díaz, D. Gardner, Z. Yao. MagneX: A High-Performance, GPU-Enabled, Data-Driven Micromagnetics Solver for Spintronics. arXiv.org, 2026. DOI: 10.48550/arXiv.2602.12242
2. B. Runnels, V. Agrawal, Maycon Meier. The Alamo multiphysics solver for phase field simulations with strong-form mechanics and block structured adaptive mesh refinement. Journal of Open Source Software, 2025. DOI: 10.21105/joss.08581
3. Jiawei Lu, Nandan Gokhale, N. Nikiforakis. An immersed interface Adaptive Mesh Refinement algorithm for Li-ion battery simulations. I. Development of a fast P2D solver. Journal of Applied Physics, 2025. DOI: 10.1063/5.0281614
4. Jiawei Lu, Nandan Gokhale, N. Nikiforakis. An immersed interface Adaptive Mesh Refinement algorithm for Li-ion battery simulations. II. Multi-dimensional extension and separator modeling. Journal of Applied Physics, 2025. DOI: 10.1063/5.0281626
5. Tanmay Dutta, Dasari Mohan, Saurav Shenoy, et al.. MicroSim: A high-performance phase-field solver based on CPU and GPU implementations. Computational materials science, 2025. DOI: 10.1016/j.commatsci.2024.113438
6. B. Siddani, Weiqun Zhang, Andrew Nonaka, J. Bell, Ishan Srivastava. An adaptive, data-driven multiscale approach for dense granular flows. Computer Methods in Applied Mechanics and Engineering, 2025. DOI: 10.1016/j.cma.2025.118294  arXiv: 2505.13458
7. Maycon Meier, B. Runnels. Finite kinematics diffuse interface mechanics coupled to solid composite propellant deflagration. Computer Methods in Applied Mechanics and Engineering, 2024. DOI: 10.1016/j.cma.2024.117040
8. Saurabh S. Sawant, François Léonard, Zhi Yao, Andrew Nonaka. ELEQTRONeX: A GPU-accelerated exascale framework for non-equilibrium quantum transport in nanomaterials. npj Computational Materials, 2024. DOI: 10.1038/s41524-025-01604-7  arXiv: 2407.14633
9. R. Jambunathan, Zhi Yao, Richard Lombardini, Aaron Rodriguez, A. Nonaka. Two-fluid physical modeling of superconducting resonators in the ARTEMIS framework. Computer Physics Communications, 2023. DOI: 10.1016/j.cpc.2023.108836  arXiv: 2305.13419
10. Prabhat Kumar, A. Nonaka, R. Jambunathan, G. Pahwa, S. Salahuddin, Z. Yao. FerroX : A GPU-accelerated, 3D Phase-Field Simulation Framework for Modeling Ferroelectric Devices. Computer Physics Communications, 2022. DOI: 10.1016/j.cpc.2023.108757  arXiv: 2210.15668
11. E. Eren, Brandon Runnels, J. Mason. Comparison of evolving interfaces, triple points, and quadruple points for discrete and diffuse interface methods. Computational materials science, 2022. DOI: 10.1016/j.commatsci.2022.111632  arXiv: 2203.03167
12. V. Agrawal, B. Runnels. Robust, strong form mechanics on an adaptive structured grid: efficiently solving variable-geometry near-singular problems with diffuse interfaces. Computational Mechanics, 2022. DOI: 10.1007/s00466-023-02325-8  arXiv: 2212.02362
13. Tim Wallis, P. T. Barton, N. Nikiforakis. A unified diffuse interface method for the interaction of rigid bodies with elastoplastic solids and multi-phase mixtures. Journal of Applied Physics, 2021. DOI: 10.1063/5.0079970  arXiv: 2111.11806
14. Z. Yao, R. Jambunathan, Yadong Zeng, A. Nonaka. A massively parallel time-domain coupled electrodynamics–micromagnetics solver. The international journal of high performance computing applications, 2021. DOI: 10.1177/10943420211057906  arXiv: 2103.12819
15. V. Agrawal, B. Runnels. Block structured adaptive mesh refinement and strong form elasticity approach to phase field fracture with applications to delamination, crack branching and crack deflection. Computer Methods in Applied Mechanics and Engineering, 2021. DOI: 10.1016/j.cma.2021.114011  arXiv: 2102.10168
16. D. Ladiges, A. Nonaka, K. Klymko, G. C. Moore, J. Bell, et al.. Discrete ion stochastic continuum overdamped solvent algorithm for modeling electrolytes. Physical Review Fluids, 6:044309, 2021. DOI: 10.1103/PHYSREVFLUIDS.6.044309  arXiv: 2007.03036
17. B. Runnels, V. Agrawal, Weiqun Zhang, A. Almgren. Massively parallel finite difference elasticity using a block-structured adaptive mesh refinement with a geometric multigrid solver. Journal of Computational Physics, 2020. DOI: 10.1016/j.jcp.2020.110065  arXiv: 2001.04789
18. Tim Wallis, P. T. Barton, N. Nikiforakis. A Diffuse Interface Model of Reactive-fluids and Solid-dynamics. arXiv: Computational Physics, 2020. DOI: 10.1016/j.compstruc.2021.106578

Multiphase flow

1. Samarth C. Patel, Tyler Tryon, X. Yee, Brandon Runnels, Matt Quinlan. Diffuse Interface Model with Surface Tension for Modeling Wave–Droplet Interactions in Compressible Two-Phase Flows. AIAA SCITECH 2026 Forum, 2026. DOI: 10.2514/6.2026-2780
2. Chun Li, Xuzhu Li, Yiliang Wang, Dewen Liu, Shuai He, Bo Huang, Haoran Cheng, Xiaokai Li, Wenzhuo Li, Mingze Tang, Zheng-Yan Zhu, Yadong Zeng. IAMReX: an adaptive framework for the multiphase flow and fluid-particle interaction problems. Journal of Open Source Software, 2025. DOI: 10.21105/joss.08080
3. Ziyang Huang, William J. White, Eric Johnsen. Consistent and conservative Phase-Field method for compressible two- and N-phase flows with adaptive mesh refinement. Journal of Computational Physics, 2025. DOI: 10.1016/j.jcp.2025.114569
4. Alexander N. Barrett, P. Subbareddy, G. Candler. Development of a low-dissipation diffuse interface method for compressible multiphase flow. AIAA SCITECH 2024 Forum, 2024. DOI: 10.2514/6.2024-1756
5. Xuzhu Li, Chun Li, Xiaokai Li, Wenzhuo Li, Mingze Tang, Yadong Zeng, Zheng-Yan Zhu. An open-source, adaptive solver for particle-resolved simulations with both subcycling and non-subcycling methods. The Physics of Fluids, 2024. DOI: 10.1063/5.0236509  arXiv: 2408.14140
6. Nicholas Deak, H. Sitaraman, Yimin Lu, Nepu Saha, Jordan Klinger, et al.. A high-performance discrete-element framework for simulating flow and jamming of moisture bearing biomass feedstocks. Powder Technology, 2024. DOI: 10.1016/j.powtec.2024.120548
7. R. Porcù, Jordan Musser, A. Almgren, J. Bell, W. Fullmer, Deepak Rangarajan. MFIX-Exa: CFD-DEM simulations of thermodynamics and chemical reactions in multiphase flows. Chemical Engineering and Science, 2023. DOI: 10.1016/j.ces.2023.118614
8. A. Dhruv. Composable Design of Multiphase Fluid Dynamics Solvers in Flash-X. arXiv.org, 2023. DOI: 10.48550/arXiv.2312.11740
9. Yadong Zeng, Han Liu, Q. Gao, A. Almgren, A. Bhalla, Lian Shen. A consistent adaptive level set framework for incompressible two-phase flows with high density ratios and high Reynolds numbers. Journal of Computational Physics, 2023. DOI: 10.1016/j.jcp.2023.111971
10. Yadong Zeng, A. Xuan, Johannes Blaschke, Lian Shen. A parallel cell-centered adaptive level set framework for efficient simulation of two-phase flows with subcycling and non-subcycling. Journal of Computational Physics, 2022. DOI: 10.1016/j.jcp.2021.110740
11. Yadong Zeng, A. Bhalla, L. Shen. A subcycling/non-subcycling time advancement scheme-based DLM immersed boundary method framework for solving single and multiphase fluid–structure interaction problems on dynamically adaptive grids. Computers & Fluids, 2022. DOI: 10.1016/j.compfluid.2022.105358
12. Sobhan Hatami, S. Walsh. Using Adaptive Mesh Refinement strategies to investigate immiscible fluid flow in fractures. International Journal of Multiphase Flow, 2022. DOI: 10.1016/j.ijmultiphaseflow.2022.104274
13. Jordan Musser, A. Almgren, W. Fullmer, et al.. MFIX-Exa: A path toward exascale CFD-DEM simulations. The international journal of high performance computing applications, 2021. DOI: 10.1177/10943420211009293
14. S. Lao, Aaron Holt, Deepthi Vaidhynathan, H. Sitaraman, C. Hrenya, T. Hauser. Performance comparison of CFD-DEM solver MFiX-Exa, on GPUs and CPUs. arXiv.org, 2021. DOI: 10.48550/arXiv.2108.08821
15. Knut Sverdrup, A. Almgren, N. Nikiforakis. An embedded boundary approach for efficient simulations of viscoplastic fluids in three dimensions. The Physics of Fluids, 2019. DOI: 10.1063/1.5110654

Numerical methods

1. Bruce Ruishu Jin, P. Cook, Gerald G. Pereira. Improvement of spacer performance in membrane distillation via an adaptive mesh lattice Boltzmann model. International Journal of Heat and Fluid Flow, 2026. DOI: 10.1016/j.ijheatfluidflow.2026.110339
2. Yuqi Wang, Yadong Zeng, Jinhui Yang, Jianhan Liang. Low-dissipation high-order AMR schemes for robust shock-capturing. Journal of Computational Physics, 2026. DOI: 10.1016/j.jcp.2026.114929
3. Ruben M. Strässle, S. A. Hosseini, I. Karlin. A fully conservative discrete velocity Boltzmann solver with parallel adaptive mesh refinement for compressible flows. The Physics of Fluids, 2025. DOI: 10.1063/5.0263958  arXiv: 2502.04820
4. Yaning Wang, Yuchen Wu, Yadong Zeng, Maoqiang Jiang, Zhaohui Liu. An immersed boundary lattice Boltzmann method on block-structured adaptive grids for the simulation of particle-laden flows on CPUs/GPUs. Computer Physics Communications, 2025. DOI: 10.1016/j.cpc.2025.109674
5. A. A. Bay, O. Olkhovskaya, B. Chetverushkin. Characteristic Method for Modeling Radiation Transfer with Adaptive Mesh Refinement. Lobachevskii Journal of Mathematics, 2025. DOI: 10.1134/S1995080225609282
6. Alejandro L. Garcia, J. Bell, A. Nonaka, Ishan Srivastava, D. Ladiges, et al.. An Introduction to Computational Fluctuating Hydrodynamics. arXiv.org, 2024. DOI: 10.48550/arXiv.2406.12157
7. A. Djurdjevac, A. Almgren, John Bell. A Hybrid Algorithm for Systems of Non-interacting Particles. Communications in Applied Mathematics and Computational Science, 2024. DOI: 10.2140/camcos.2025.20.147  arXiv: 2409.00299
8. I. Sanchez, A. Almgren, John B. Bell, M. H. D. Frahan, Weiqun Zhang. A New Re-redistribution Scheme for Weighted State Redistribution with Adaptive Mesh Refinement. Journal of Computational Physics, 2023. DOI: 10.48550/arXiv.2309.06372
9. Justin Shafner, P. Martin. In-Situ Adaptive Mesh Refinement for High Fidelity Simulations of Compressible Turbulence. AIAA AVIATION 2023 Forum, 2023. DOI: 10.2514/6.2023-4331
10. Ishan Srivastava, D. Ladiges, A. Nonaka, Alejandro L. Garcia, J. Bell. Staggered scheme for the compressible fluctuating hydrodynamics of multispecies fluid mixtures. Physical Review E, 2022. DOI: 10.1103/PhysRevE.107.015305  arXiv: 2209.11292
11. J. Loffeld, A. Nonaka, Daniel R. Reynolds, D. Gardner, C. Woodward. Performance of explicit and IMEX MRI multirate methods on complex reactive flow problems within modern parallel adaptive structured grid frameworks. The international journal of high performance computing applications, 2022. DOI: 10.1177/10943420241227914  arXiv: 2211.03293
12. M. Natarajan, R. Grout, Weiqun Zhang, M. Day. A moving embedded boundary approach for the compressible Navier-Stokes equations in a block-structured adaptive refinement framework. Journal of Computational Physics, 2022. DOI: 10.1016/j.jcp.2022.111315  arXiv: 2108.00126
13. V. Gulizzi, A. Almgren, J. Bell. A coupled discontinuous Galerkin-Finite Volume framework for solving gas dynamics over embedded geometries. Journal of Computational Physics, 2021. DOI: 10.1016/j.jcp.2021.110861  arXiv: 2105.14353
14. Andrew Giuliani, A. Almgren, J. Bell, M. Berger, M. H. D. Frahan, et al.. A Weighted State Redistribution Algorithm for Embedded Boundary Grids. Journal of Computational Physics, 2021. DOI: 10.1016/j.jcp.2022.111305  arXiv: 2112.12360
15. Tim Wallis, P. T. Barton, N. Nikiforakis. A flux-enriched Godunov method for multi-material problems with interface slide and void opening. Journal of Computational Physics, 2020. DOI: 10.1016/j.jcp.2021.110499  arXiv: 2011.05569

Plasma and accelerators

1. Ashwyn Sam, S. Elschot. Self-consistent charging of complex objects in flowing plasma: Implementation and analysis in WarpX. Computer Physics Communications, 2025. DOI: 10.1016/j.cpc.2025.109680
2. A. Farmakalides, N. Nikiforakis, S. Millmore, M. Romanelli, P. Buxton. CRATOS-GS: A free-boundary, hierarchical adaptive mesh refinement Grad–Shafranov solver. AIP Advances, 2025. DOI: 10.1063/5.0285053
3. R. Jambunathan, Henry N Jones, L. Corrales, Hannah Klion, M. Rowan, Andrew Myers, Weiqun Zhang, J. Vay. Application of mesh refinement to relativistic magnetic reconnection. Physics of Plasmas, 2024. DOI: 10.1063/5.0233583  arXiv: 2408.08960
4. R. Sandberg, R. Lehe, Chad Mitchell, M. Garten, A. Myers, J. Qiang, J. Vay, A. Huebl. Synthesizing Particle-In-Cell Simulations through Learning and GPU Computing for Hybrid Particle Accelerator Beamlines. Platform for Advanced Scientific Computing Conference, 2024. DOI: 10.1145/3659914.3659937  arXiv: 2402.17248
5. Yuxi Chen, Gabor Toth, E. Powell, Talha Arshad, Ethan Bair, et al.. A Kinetic-magnetohydrodynamic Model with Adaptive Mesh Refinement for Modeling Heliosphere Neutral-plasma Interaction. Astrophysical Journal, 2024. DOI: 10.3847/1538-4357/ad6323  arXiv: 2403.12395
6. Hannah Klion, R. Jambunathan, M. Rowan, Eloïse Yang, D. Willcox, J. Vay, R. Lehe, A. Myers, A. Huebl, Weiqun Zhang. Particle-in-cell Simulations of Relativistic Magnetic Reconnection with Advanced Maxwell Solver Algorithms. Astrophysical Journal, 2023. DOI: 10.3847/1538-4357/acd75b  arXiv: 2304.10566
7. L. Fedeli, A. Huebl, F. Boillod-Cerneux, T. Clark, K. Gott, C. Hillairet, S. Jaure, A. Leblanc, R. Lehe, A. Myers, C. Piechurski, M. Sato, N. Zaim, Weiqun Zhang, J. Vay, H. Vincenti. Pushing the Frontier in the Design of Laser-Based Electron Accelerators with Groundbreaking Mesh-Refined Particle-In-Cell Simulations on Exascale-Class Supercomputers. International Conference for High Performance Computing, Networking, Storage and Analysis, 2022. DOI: 10.1109/sc41404.2022.00008
8. A. Huebl, R. Lehe, C. Mitchell, J. Qiang, R. Ryne, et al.. Next Generation Computational Tools for the Modeling and Design of Particle Accelerators at Exascale. arXiv.org, 2022. DOI: 10.18429/JACoW-NAPAC2022-TUYE2
9. S. Diederichs, C. Benedetti, A. Huebl, R. Lehe, A. Myers, A. Sinn, J.-L. Vay, W. Zhang, M. Th'evenet. HiPACE++: A portable, 3D quasi-static particle-in-cell code. Computer Physics Communications, 278:108421, 2022. DOI: 10.1016/j.cpc.2022.108421  arXiv: 2109.10277
10. K. Tapinou, V. Wheatley, D. Bond, I. Jahn. The Richtmyer–Meshkov instability of thermal, isotope and species interfaces in a five-moment multi-fluid plasma. Journal of Fluid Mechanics, 2022. DOI: 10.1017/jfm.2022.847
11. A. Myers, A. Almgren, L. Amorim, et al.. Porting WarpX to GPU-accelerated platforms. Parallel Computing, 2021. DOI: 10.1016/j.parco.2021.102833  arXiv: 2101.12149
12. J. Vay, A. Huebl, A. Almgren, et al.. Modeling of a chain of three plasma accelerator stages with the WarpX electromagnetic PIC code on GPUs. Physics of Plasmas, 2021. DOI: 10.1063/5.0028512
13. M. Rowan, A. Huebl, K. Gott, J. Deslippe, M. Th'evenet, R. Lehe, J. Vay. In-situ assessment of device-side compute work for dynamic load balancing in a GPU-accelerated PIC code. Platform for Advanced Scientific Computing Conference, 2021. DOI: 10.1145/3468267.3470614  arXiv: 2104.11385
14. L. Fedeli, N. Zaïm, A. Sainte-Marie, Maxence Th'evenet, A. Huebl, A. Myers, J. Vay, H. Vincenti. PICSAR-QED: a Monte Carlo module to simulate strong-field quantum electrodynamics in particle-in-cell codes for exascale architectures. New Journal of Physics, 2021. DOI: 10.1088/1367-2630/ac4ef1  arXiv: 2110.00256