Publications

Goff, J.M., Sievers, C., Wood, M.A., Thompson, A.P., & Thompson, A.P. (2024). Permutation-adapted complete and independent basis for atomic cluster expansion descriptors. Journal of Computational Physics. https://doi.org/10.2172/1879613

Armstrong, E., Hansen, M.A., Knaus, R.C., Trask, N.A., Hewson, J.C., Sutherland, J.C., & Sutherland, J.C. (2024). Accurate Compression of Tabulated Chemistry Models with Partition of Unity Networks. Combustion Science and Technology, 196(6), pp. 850-867. https://doi.org/10.1080/00102202.2022.2102908

Grant, R.E., Hammond, S.D., Bachman, W.B., Levenhagen, M., Olivier, S.L., Bachman, W.B., Ward, L., Younge, A.J., & Younge, A.J. (2023). Enabling power measurement and control on Astra: The first petascale Arm supercomputer. Concurrency and Computation: Practice and Experience, 35(15). https://doi.org/10.1002/cpe.7303

D'Elia, M., Silling, S.A., You, H., Yu, Y., Fermen-Coker, M., & Fermen-Coker, M. (2023). Peridynamic Model for Single-Layer Graphene Obtained from Coarse-Grained Bond Forces. Journal of Peridynamics and Nonlocal Modeling. https://doi.org/10.2172/1819404

Mitchell, S.A., Knupp, P., MacKay, S., Deakin, M.F., & Deakin, M.F. (2023). Not so HOT Triangulations [Conference Presenation]. CAD Computer Aided Design. https://doi.org/10.2172/1873284

Naugle, A.B., Krofcheck, D.J., Warrender, C., Lakkaraju, K., Swiler, L.P., Verzi, S.J., Emery, B., Murdock, J., Bernard, M., Romero, V., & Romero, V. (2023). What can simulation test beds teach us about social science? Results of the ground truth program. Computational and Mathematical Organization Theory, 29(1), pp. 242-263. https://doi.org/10.1007/s10588-021-09349-6

Wendt, J.D., Field, R.V., Phillips, C.A., Prasadan, A., Wilson, T., Soundarajan, S., Bhowmick, S., & Bhowmick, S. (2023). Partitioning Communication Streams Into Graph Snapshots [Conference Presenation]. IEEE Transactions on Network Science and Engineering. https://doi.org/10.2172/1842249

Bachman, W.B., Maupin, K.A., Rodgers, T., & Rodgers, T. (2023). Monotonic Gaussian Process for Physics-Constrained Machine Learning With Materials Science Applications. Journal of Computing and Information Science in Engineering, 23(1). https://doi.org/10.1115/1.4055852

de Castro, A., Kuberry, P., Tezaur, I.K., Bochev, P., & Bochev, P. (2023). A Novel Partitioned Approach for Reduced Order Model - Finite Element Model (ROM-FEM) and ROM-ROM Coupling. Earth and Space 2022: Space Exploration, Utilization, Engineering, and Construction in Extreme Environments - Selected Papers from the 18th Biennial International Conference on Engineering, Science, Construction, and Operations in Challenging Environments. https://doi.org/10.1061/9780784484470.044

Demkowicz, L.F., Roberts, N.V., Munoz-Mutate, J., & Munoz-Mutate, J. (2023). The DPG Method for the Convection-Reaction Problem, Revisited. Computational Methods in Applied Mathematics, 23(1), pp. 93-125. https://doi.org/10.1515/cmam-2021-0149

Adler, J.H., He, Y., Hu, X., MacLachlan, S., Ohm, P., & Ohm, P. (2023). MONOLITHIC MULTIGRID FOR A REDUCED-QUADRATURE DISCRETIZATION OF POROELASTICITY. SIAM Journal on Scientific Computing, 45(3), pp. S54-S81. https://doi.org/10.1137/21m1429072

Naugle, A.B., Verzi, S.J., Lakkaraju, K., Swiler, L.P., Warrender, C., Bernard, M., Romero, V., & Romero, V. (2023). Feedback density and causal complexity of simulation model structure. Journal of Simulation, 17(3), pp. 229-239. https://doi.org/10.1080/17477778.2021.1982653

Wang, F., Teeter, C.M., & Teeter, C.M. (2022). Combining Spike Time Dependent Plasticity (STDP) and Backpropagation (BP) for Robust and Data Efficient Spiking Neural Networks (SNN). https://doi.org/10.2172/1902866

Roberts, N.V., Bond, S.D., Cyr, E.C., Miller, S.T., & Miller, S.T. (2022). Neural-network based collision operators for the Boltzmann equation. Journal of Computational Physics, 470. https://doi.org/10.1016/j.jcp.2022.111541

Bachman, W.B., Sun, J., Liu, D., Wang, Y., Wildey, T., & Wildey, T. (2022). A Stochastic Reduced-Order Model for Statistical Microstructure Descriptors Evolution. Journal of Computing and Information Science in Engineering, 22(6). https://doi.org/10.1115/1.4054237

Roberts, N.V., Munoz-Matute, J., Demkowicz, L., & Demkowicz, L. (2022). Combining DPG in space with DPG time-marching scheme for the transient advection–reaction equation. Computer Methods in Applied Mechanics and Engineering, 402. https://doi.org/10.1016/j.cma.2022.115471

Kononov, A., Lee, C.W., dos Santos, T.P., Robinson, B., Yao, Y., Yao, Y., Andrade, X., Baczewski, A.D., Constantinescu, E., Correa, A.A., Kanai, Y., Modine, N.A., Schleife, A., & Schleife, A. (2022). Electron dynamics in extended systems within real-time time-dependent density-functional theory. MRS Communications, 12(6), pp. 1002-1014. https://doi.org/10.1557/s43579-022-00273-7

Jock, R.M., Jacobson, N.T., Rudolph, M., Ward, D.R., Carroll, M.S., Luhman, D.R., & Luhman, D.R. (2022). A silicon singlet–triplet qubit driven by spin-valley coupling. Nature Communications, 13(1). https://doi.org/10.1038/s41467-022-28302-y

McGregor, D.A.O., Love, E., Sirajuddin, D., Swan, M.S., Collins, D., Pawlowski, R., Cartwright, K.L., Stafford, D., & Stafford, D. (2022). EMPIRE User Manual. https://doi.org/10.2172/1900358

D'Elia, M., Silling, S.A., Yu, Y., You, H., Gao, T., & Gao, T. (2022). Nonlocal kernel network (NKN): A stable and resolution-independent deep neural network. Journal of Computational Physics. https://doi.org/10.2172/1855045

Mounce, A.M., Wang, G., Schultz, P.A., Titze, M., de Campbell, A., Lu, P., Henshaw, J., & Henshaw, J. (2022). Development of Single Photon Sources in GaN. https://doi.org/10.2172/1898965

D'Elia, M., Glusa, C., & Glusa, C. (2022). A fractional model for anomalous diffusion with increased variability: Analysis, algorithms and applications to interface problems. Numerical Methods for Partial Differential Equations, 38(6), pp. 2084-2103. https://doi.org/10.1002/num.22865

Brooks, D.M., Swiler, L.P., Stein, E., Mariner, P.E., Basurto, E., Portone, T., Eckert, A., Leone, R.C., & Leone, R.C. (2022). Sensitivity analysis of generic deep geologic repository with focus on spatial heterogeneity induced by stochastic fracture network generation. Advances in Water Resources, 169. https://doi.org/10.1016/j.advwatres.2022.104310

Naugle, A.B., Rothganger, F., Verzi, S.J., Doyle, C.L., & Doyle, C.L. (2022). Conflicting Information and Compliance With COVID-19 Behavioral Recommendations. https://doi.org/10.2172/1894426

Fiedler, L., Modine, N.A., Schmerler, S., Vogel, D.J., Popoola, G.A., Thompson, A.P., Rajamanickam, S., Cangi, A., & Cangi, A. (2022). Predicting the Electronic Structure of Matter on Ultra-Large Scales. https://doi.org/10.2172/1895024

Eldred, C., Guba, O., Taylor, M.A., & Taylor, M.A. (2022). Thermodynamically consistent versions of approximations used in modelling moist air. Quarterly Journal of the Royal Meteorological Society, 148(748), pp. 3184-3210. https://doi.org/10.1002/qj.4353

Shadid, J.N. (2022). Embedded pairs for optimal explicit strong stability preserving Runge–Kutta methods. Journal of Computational and Applied Mathematics, 412. https://doi.org/10.1016/j.cam.2022.114325

Branch, B.A., Ruggles, T., Miers, J.C., Massey, C., Moore, D., Brown, N., Duwal, S., Silling, S.A., Mitchell, J.A., Specht, P.E., & Specht, P.E. (2022). Understanding Phase and Interfacial Effects of Spall Fracture in Additively Manufactured Ti-5Al-5V-5Mo-3Cr. https://doi.org/10.2172/1892129

Eldred, C., Brachet, M., Debreu, L., & Debreu, L. (2022). Comparison of exponential integrators and traditional time integration schemes for the shallow water equations. Applied Numerical Mathematics, 180, pp. 55-84. https://doi.org/10.1016/j.apnum.2022.05.006

Kononov, A., Olmstead, A., Baczewski, A.D., Schleife, A., & Schleife, A. (2022). First-principles simulation of light-ion microscopy of graphene. 2D Materials, 9(4). https://doi.org/10.1088/2053-1583/ac8e7e

Kordenbrock, T., Templet, G.J., Ulmer, C.D., Widener, P., & Widener, P. (2022). Viability of S3 Object Storage for the ASC Program at Sandia. https://doi.org/10.2172/1895203

Polonsky, A., Martinez, C., Appleby, C.A., Bernard, S.R., Griego, J.G., Noell, P., Pathare, P.R., & Pathare, P.R. (2022). Super-Resolution Approaches in Three-Dimensions for Classification and Screening of Commercial-Off-The-Shelf Components. https://doi.org/10.2172/1890107

Bidadi, S., Brazell, M., Brunhart-Lupo, N., Henry de Frahan, M.T., Lee, D.H., Hu, J.J., Melvin, J., Mullowney, P., Vijayakumar, G., Moser, R.D., Rood, J., Sakievich, P., Sharma, A., Williams, A.B., Sprague, M.A., & Sprague, M.A. (2022). Demonstrate multi-turbine simulation with hybrid-structured / unstructured-moving-grid software stack running primarily on GPUs and propose improvements for successful KPP-2. https://doi.org/10.2172/1891592

Cardwell, S.G., Plagge, M., Hughes, C., Rothganger, F., Agarwal, S., Feinberg, B., Awad, A., McFarland, J., Parker, L., & Parker, L. (2022). ATHENA: Analytical Tool for Heterogeneous Neuromorphic Architectures. https://doi.org/10.2172/1890038

Bachman, W.B., Wildey, T., Lim, H., & Lim, H. (2022). Microstructure-Sensitive Uncertainty Quantification for Crystal Plasticity Finite Element Constitutive Models Using Stochastic Collocation Methods. Frontiers in Materials, 9. https://doi.org/10.3389/fmats.2022.915254

Kelley, B., Rajamanickam, S., & Rajamanickam, S. (2022). Unified Language Frontend for Physic-Informed AI/ML. https://doi.org/10.2172/1888879

Chatterjee, E., Soh, D.B.S., Young, S.M., & Young, S.M. (2022). Lossless Quantum Hard-Drive Memory Using Parity-Time Symmetry. https://doi.org/10.2172/1888158

Wood, M.A., Nikolov, S.V., Rohskopf, A.D., Desjarlais, M.P., Cangi, A., Tranchida, J., & Tranchida, J. (2022). Quantum-Accurate Multiscale Modeling of Shock Hugoniots, Ramp Compression Paths, Structural and Magnetic Phase Transitions, and Transport Properties in Highly Compressed Metals. https://doi.org/10.2172/1898251

D'Elia, M., Bochev, P., Foster, J.T., Glusa, C., Gulian, M., Gunzburger, M., Trageser, J., Kuhlman, K.L., Martinez, M., Najm, H.N., Silling, S.A., Tupek, M., Xu, X., & Xu, X. (2022). Mathematical Foundations for Nonlocal Interface Problems: Multiscale Simulations of Heterogeneous Materials (Final LDRD Report). https://doi.org/10.2172/1888162

Moore, S.G. (2022). Large-Scale Atomistic Simulations [Slides]. https://doi.org/10.2172/1888083

Mariner, P.E., Debusschere, B.J., Fukuyama, D.E., Harvey, J.A., Laforce, T., Leone, R.C., Bachman, W.B., Swiler, L.P., Taconi, A., & Taconi, A. (2022). GDSA Framework Development and Process Model Integration FY2022. https://doi.org/10.2172/1893995

Mamaluy, D., Mendez Granado, J.P., & Mendez Granado, J.P. (2022). Revealing conductivity of p-type delta layer systems for novel computing applications. https://doi.org/10.2172/1887942

Tuminaro, R.S., Crockatt, M.M., Robinson, A.C., & Robinson, A.C. (2022). Composing preconditioners for multiphysics PDE systems with applications to Generalized MHD. https://doi.org/10.2172/1886757

Laforce, T., Basurto, E., Chang, K.W., Ebeida, M., Eymold, W., Faucett, C.A., Jayne, R., Kucinski, N., Leone, R.C., Mariner, P.E., Bachman, W.B., & Bachman, W.B. (2022). GDSA Repository Systems Analysis Investigations in FY2022. https://doi.org/10.2172/1898245

Mahadevan, V.S., Guerra, J.E., Jiao, X., Kuberry, P., Li, Y., Ullrich, P., Marsico, D., Jacob, R., Bochev, P., Jones, P., & Jones, P. (2022). Metrics for Intercomparison of Remapping Algorithms (MIRA) protocol applied to Earth system models. Geoscientific Model Development, 15(17), pp. 6601-6635. https://doi.org/10.5194/gmd-15-6601-2022

Robinson, A.C., Swan, M.S., Harvey, E.C., Klein, B., Lawson, G., Milewicz, R.M., Bachman, W.B., Schmitz, M.E., Warnock, S.A., & Warnock, S.A. (2022). An introduction to developing GitLab/Jacamar runner analyst centric workflows at Sandia. https://doi.org/10.2172/1885645

Feinberg, B., Agarwal, S., Plagge, M., Rothganger, F., Cardwell, S.G., Hughes, C., & Hughes, C. (2022). Modeling Analog Tile-Based Accelerators Using SST. https://doi.org/10.2172/1891950

Hansen, S.B., Baczewski, A.D., Gomez, T., Hentschel, T.W., Jennings, C.A., Kononov, A., Nagayama, T., Adler, K., Cangi, A., Cochrane, K.R., Bachman, W.B., Schleife, A., & Schleife, A. (2022). Improving Predictive Capability in REHEDS Simulations with Fast, Accurate, and Consistent Non-Equilibrium Material Properties. https://doi.org/10.2172/1890268

Dipietro, K.L., Ridzal, D., Morales, D., & Morales, D. (2022). Adaptive Space-Time Methods for Large Scale Optimal Design. https://doi.org/10.2172/1891589

Steyer, A. (2022). Computational Response Theory for Dynamics. https://doi.org/10.2172/1898244

Cartwright, K.L., Pointon, T.D., Powell, T.C., Grabowski, T.C., Shields, S., Sirajuddin, D., Jensen, D.S., Renk, T.J., Cyr, E.C., Stafford, D., Swan, M.S., Mitra, S.S., McDoniel, W., Moore, C.H., & Moore, C.H. (2022). Progress in Modeling the 2019 Extended Magnetically Insulated Transmission Line (MITL) and Courtyard Environment Trial at HERMES-III. https://doi.org/10.2172/1890050

Buczkowski, N.E., Foss, M.D., Parks, M.L., Radu, P., & Radu, P. (2022). Sensitivity Analysis for Solutions to Heterogeneous Nonlocal Systems. Theoretical and Numerical Studies. Journal of Peridynamics and Nonlocal Modeling, 4(3), pp. 367-397. https://doi.org/10.1007/s42102-022-00081-6

Modine, N.A., Stephens, J.A., Swiler, L.P., Thompson, A.P., Vogel, D.J., Cangi, A., Feilder, L., Rajamanickam, S., & Rajamanickam, S. (2022). Accelerating Multiscale Materials Modeling with Machine Learning. https://doi.org/10.2172/1889336

Lehoucq, R.B., Mayer, C.D., Tucker, J.D., & Tucker, J.D. (2022). Entropy and its Relationship with Statistics. https://doi.org/10.2172/1895025

Maupin, K.A., Bachman, W.B., Bachman, W.B., Knapp, P.F., Joseph, V.R., Wu, C.F.J., Glinsky, M.E., Valaitis, S.M., & Valaitis, S.M. (2022). Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework. https://doi.org/10.2172/1891191

Leonard, F., Fuller, E.J., Teeter, C.M., Vineyard, C.M., & Vineyard, C.M. (2022). Neuromorphic Information Processing by Optical Media. https://doi.org/10.2172/1887939

White, R.D., Alexanderian, A., Karbalaeisadegh, Y., Bekele-Maxwell, K., Banks, H.T., Talmant, M., Grimal, Q., Muller, M., & Muller, M. (2022). Using ultrasonic attenuation in cortical bone to infer distributions on pore size. Applied Mathematical Modelling, 109, pp. 819-832. https://doi.org/10.1016/j.apm.2022.05.024

Eldred, M., Adams, B.M., Geraci, G., Portone, T., Ridgway, E.M., Stephens, J.A., Wildey, T., & Wildey, T. (2022). Deployment of Multifidelity Uncertainty Quantification for Thermal Battery Assessment Part I: Algorithms and Single Cell Results. https://doi.org/10.2172/1885882

Eldred, C. (2022). Differential geometric approaches to momentum-based formulations for fluids [Slides]. https://doi.org/10.2172/1890065

Cardwell, S.G., Smith, J.D., Crowder, D.C., & Crowder, D.C. (2022). AI-enhanced Codesign for Next-Generation Neuromorphic Circuits and Systems. https://doi.org/10.2172/1889339

Roberts, N.V., Bond, S.D., Miller, S.T., Cyr, E.C., & Cyr, E.C. (2022). Fluid-Kinetic Coupling: Advanced Discretizations for Simulations on Emerging Heterogeneous Architectures (LDRD FY20-0643). https://doi.org/10.2172/1891588

Bond, S.D., Franke, B., Lehoucq, R.B., McKinley, S.A., & McKinley, S.A. (2022). Sensitivity Analyses for Monte Carlo Sampling-Based Particle Simulations. https://doi.org/10.2172/1889334

Bachman, W.B., Portone, T., Dandekar, R., Rackauckas, C., Bandy, R.J., Huerta, J.G., Dytzel, I., & Dytzel, I. (2022). Model-Form Epistemic Uncertainty Quantification for Modeling with Differential Equations: Application to Epidemiology. https://doi.org/10.2172/1888443

Rackers, J.A. (2022). Combining Physics and Machine Learning for the Next Generation of Molecular Simulation. https://doi.org/10.2172/1889331

Eydenberg, M.S., Batsch-Smith, L., Bice, C., Blakely, L., Bynum, M., Boukouvala, F., Castillo, A., Haddad, J., Hart, W.E., Jalving, J., Kilwein, Z., Laird, C., Skolfield, J.K., & Skolfield, J.K. (2022). Resilience Enhancements through Deep Learning Yields. https://doi.org/10.2172/1890044

Jakeman, J.D., Eldred, M., Geraci, G., Seidl, D.T., Smith, T.M., Gorodetsky, A.A., Pham, T., Narayan, A., Zeng, X., Ghanem, R., & Ghanem, R. (2022). Multi-fidelity information fusion and resource allocation. https://doi.org/10.2172/1888363

Arguello, B., Stewart, N.A., Hoffman, M.J., Nicholson, B.L., Garrett, R., Moog, E., & Moog, E. (2022). Dynamics Informed Optimization for Resilient Energy Systems. https://doi.org/10.2172/1893998

Swiler, L.P., Basurto, E., Brooks, D.M., Eckert, A., Leone, R.C., Mariner, P.E., Portone, T., Bachman, W.B., & Bachman, W.B. (2022). Uncertainty and Sensitivity Analysis Methods and Applications in the GDSA Framework (FY2022). https://doi.org/10.2172/1884909

Bradley, A.M., Bosler, P.A., Guba, O., & Guba, O. (2022). Islet: interpolation semi-Lagrangian element-based transport. Geoscientific Model Development, 15(16), pp. 6285-6310. https://doi.org/10.5194/gmd-15-6285-2022

Jakeman, J.D. (2022). PyApprox: Enabling efficient model analysis. https://doi.org/10.2172/1879614

Naugle, A.B., Swiler, L.P., Lakkaraju, K., Verzi, S.J., Warrender, C., Romero, V., & Romero, V. (2022). Graph-Based Similarity Metrics for Comparing Simulation Model Causal Structures. https://doi.org/10.2172/1884926

Roberds, N.A., Cartwright, K.L., Sandoval, A.J., Beckwith, K., Cyr, E.C., Bachman, W.B., & Bachman, W.B. (2022). Numerical simulation of a relativistic magnetron using a fluid electron model. Physics of Plasmas, 29(8). https://doi.org/10.1063/5.0090351

Tezaur, I.K., Peterson, K., Powell, A.J., Jakeman, J.D., Roesler, E.L., & Roesler, E.L. (2022). Global Sensitivity Analysis Using the Ultra-Low Resolution Energy Exascale Earth System Model. Journal of Advances in Modeling Earth Systems, 14(8). https://doi.org/10.1029/2021ms002831

Mendez Granado, J.P. (2022). Strain-tuning of transport gaps and semiconductor-to-conductor phase transition in twinned graphene. Acta Materialia, 234. https://doi.org/10.1016/j.actamat.2022.117987

Loe, J.A., Morgan, R.B., & Morgan, R.B. (2022). Toward efficient polynomial preconditioning for GMRES. Numerical Linear Algebra with Applications, 29(4). https://doi.org/10.1002/nla.2427

Turner, E.M., Campbell, Q.T., Avci, I., Weber, W.J., Lu, P., Wang, G.T., Jones, K.S., & Jones, K.S. (2022). Selective amorphization of SiGe in Si/SiGe nanostructures via high energy Si+ implant. Journal of Applied Physics, 132(3). https://doi.org/10.1063/5.0094185

Hamlin, N.D., Smith, T.M., Roberds, N.A., Bachman, W.B., Beckwith, K., & Beckwith, K. (2022). Electrostatic Relativistic Fluid Models of Electron Emission in a Warm Diode. IEEE International Conference on Plasma Science (ICOPS), 2022, pp. 1-26. https://doi.org/10.1109/icops45751.2022.9813152

Kolla, H., Phipps, E.T., Wolf, M., & Wolf, M. (2022). ExaLearn – GenTen Tensor Software ECP Milestone. https://doi.org/10.2172/1876624

Jakeman, J.D., Friedman, S., Eldred, M., Tamellini, L., Gorodetsky, A.A., Allaire, D., & Allaire, D. (2022). Adaptive experimental design for multi-fidelity surrogate modeling of multi-disciplinary systems. International Journal for Numerical Methods in Engineering, 123(12), pp. 2760-2790. https://doi.org/10.1002/nme.6958

Shukla, K., Xu, M., Trask, N.A., Karniadakis, G.E., & Karniadakis, G.E. (2022). Scalable algorithms for physics-informed neural and graph networks. Data-Centric Engineering, 3(6), pp. 1-26. https://doi.org/10.1017/dce.2022.24

Schultz, P.A., Hjalmarson, H.P., & Hjalmarson, H.P. (2022). Theory of the metastable injection-bleached E3c center in GaAs. Physical Review. B, 105(22). https://doi.org/10.1103/physrevb.105.224111

Guo, Z., Song, J.K., Barbastathis, G., Vaughan, C.T., Larson, K.W., Alpert, B.K., Levine, Z.H., Glinsky, M.E., & Glinsky, M.E. (2022). Physics-assisted generative adversarial network for X-ray tomography. Optics Express, 30(13), pp. 23238-23259. https://doi.org/10.1364/oe.460208

D'Elia, M., Glusa, C., Burkovska, O., & Burkovska, O. (2022). An optimization-based approach to parameter learning for fractional type nonlocal models. Computers and Mathematics with Applications, 116, pp. 229-244. https://doi.org/10.1016/j.camwa.2021.05.005

Edwards, A.H., Schultz, P.A., Dobzynski, R.M., & Dobzynski, R.M. (2022). Electronic structure of intrinsic defects in c-gallium nitride: Density functional theory study without the jellium approximation. Physical Review. B, 105(23). https://doi.org/10.1103/physrevb.105.235110

Schonbein, W., Barrett, B.W., Brightwell, R.B., Grant, R.E., Hemmert, K.S., Bachman, W.B., Underwood, K., Riesen, R., Hoefler, T., Barbe, M., Suraty Filho, L.H., Ratchov, A., MacCabe, A.B., & MacCabe, A.B. (2022). The Portals 4.3 Network Programming Interface. https://doi.org/10.2172/1875218

Tomas, I., Shadid, J.N., Maier, M., Salgado, A., & Salgado, A. (2022). Asymptotic preserving methods for fluid electron-fluid models in the large magnetic field limit with mathematically guaranteed properties (Final Report). https://doi.org/10.2172/1872178

Rezaul Karim, M., Narasimhachary, S., Radaelli, F., Amann, C., Dayal, K., Silling, S.A., Germann, T.C., & Germann, T.C. (2022). Crack nucleation at forging flaws studied by non-local peridynamics simulations. Mathematics and Mechanics of Solids, 27(6), pp. 1129-1149. https://doi.org/10.1177/10812865211057211

Clark, S.M., Norris, H., Landahl, A.J., Yale, C.G., Lobser, D., van der Wall, J.W., Revelle, M., & Revelle, M. (2022). QSCOUT Progress Report, June 2022 [Quantum Scientific Computing Open User Testbed]. https://doi.org/10.2172/1873977

Blume-Kohout, R.J., da Silva, M.P., Nielsen, E., Proctor, T.J., Rudinger, K.M., Sarovar, M., Young, K.C., & Young, K.C. (2022). A Taxonomy of Small Markovian Errors. PRX Quantum, 3(2). https://doi.org/10.1103/prxquantum.3.020335

Munoz-Matute, J., Demkowicz, L., Roberts, N.V., & Roberts, N.V. (2022). Combining DPG in space with DPG time-marching scheme for the transient advection-reaction equation. https://doi.org/10.2172/1869510

Ruzic, B., Barrick, T.A., Hunker, J.D., Law, R.J., McFarland, B., McGuinness, H.J.E., Parazzoli, L.P., Sterk, J.D., van der Wall, J.W., Stick, D., & Stick, D. (2022). Entangling-gate error from coherently displaced motional modes of trapped ions. Physical Review A, 105(5). https://doi.org/10.1103/physreva.105.052409

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