In September 2025, the focus was on reliability, documentation alignment, and strengthening test coverage to support stable, user-friendly simulations in Gkeyll. Key accomplishments centered on (1) regression test and documentation alignment for GEM reconnection and two-stream instability, ensuring input file structures and comments match the code and the updated Quick Start guide; this reduces user confusion and ensures consistency between documentation and code (commit 48ec880c9d3bc3c93c0bf5c59dc8ee31d5fbdb27). (2) GRMHD spatial metric derivative rank-3 transformation consistency for dynamic spacetimes, fixing source-term issues and aligning unit tests to verify the transformation under evolving geometries; commits include a0a6f91dfc437ad0c7dc48b1b53311940b7a8bc4 and ab1bd307a6d4be45442a0006b6b49d5802df93cc. (3) Broader consistency updates across GR equation systems with geometric source terms to reflect the new transformation, with corresponding unit test updates. (4) Overall impact and business value: improved simulation reliability, reduced onboarding friction, and stronger test coverage for dynamic spacetime coupling, enabling more accurate and reproducible research outcomes. (5) Technologies and skills demonstrated include regression testing across C and Lua, test-driven development, documentation sovereignty, GRMHD math transformations, unit testing, and maintainability enhancements.

August 2025 monthly highlights for ammarhakim/gkeyll: Delivered a mature set of GRMHD capabilities in the tetrad-basis framework, with dynamic spacetime integration and cross-language testing support. Substantial progress on divergence cleaning, spinning black hole accretion modeling, and gravitational collapse scenarios, underpinned by a strengthened test suite and build reliability.

July 2025: Strengthened reliability, broadened diffusion and advection capabilities, and advanced GRMHD foundations. Stabilized the build/test pipeline, introduced Lua-wrapped diffusion (constant coefficient) with full tensor support, standardized DG initialization, and prepared for cross-language diffusion wrapping. Enhanced testing infrastructure with preallocated NN data and test-rebuild rules, and made substantial progress on GRMHD components (flux, frame transforms, Newman–Hamlin reconstruction, HLL(E) solver, gauge fixing, curved spacetime source terms). Also fixed critical solver stability issues and memory leaks, improving robustness for higher-resolution runs.

June 2025 monthly summary for ammarhakim/gkeyll: Delivered a major overhaul of the 10-moment numeric pipeline, expanded test variants and NN-closure infrastructure, and improved cross-language test coverage and build reliability. The work focused on delivering tangible business value through correctness, stability, and broader capability for plasma simulations, including NN-based closures and GPU-enabled workflows.

Summary for 2025-05: The month focused on stabilizing and extending the GR hydrodynamics and spacetime coupling framework, expanding gauge control, and advancing neural-network-based closures. Delivered major features for dynamic spacetime coupling, static gauge reinitialization, and moment-EM-spacetime integration, while fixing key bugs to improve robustness. Built infrastructure for magnetosphere problems, two-fluid solvers, and NN training workflows. Tests and tolerances updated to reflect new architectures and CPU/GPU execution paths. The work lays groundwork for more accurate, scalable, and data-driven astrophysical simulations with cross-domain coupling between matter, EM fields, and spacetime.

April 2025 performance summary for ammarhakim/gkeyll. The month focused on delivering high-impact features, strengthening numerical robustness, and laying the groundwork for advanced relativistic hydrodynamics. The work improved simulation accuracy, reliability across CUDA/CPU boundaries, and prepared the codebase for more complex relativistic scenarios, while maintaining a clear path to future refinements.

Concise monthly summary for 2025-03 focused on delivering formally-verified solver components, expanding coverage across linear advection, Burgers, Maxwell, and isothermal Euler equations, and strengthening the GKYL CAS proof tooling. Improvements span core numerical solvers, proof efficiency, API stability, and regression coverage, with business value in safer, more maintainable code and reduced risk in production workflows.

February 2025 was marked by substantial progress in reliability, usability, and advanced verification across the two repositories. Key accomplishments include Lua integration with test coverage for the MHD solver (Lua support across builds, LuaJIT build, and Lua-based tests for Ryu-Jones and Orszag-Tang with necessary C refactors), and productization enhancements that simplify builds by making MPI and ADAS dependencies optional by default. The month also advanced formal verification and proof tooling for numerical solvers (flux limiters, hyperbolicity, and flux conservation), together with broad improvements to code generation, regression testing, and proof automation for gkylzero, Roe-type solvers, and Maxwell/vector PDE systems. These efforts deliver stronger correctness guarantees, easier onboarding for users, and a scalable path to more complex simulations.

January 2025: Delivered stability improvements, expanded test coverage, and HPC-ready infrastructure across Lua and C components of GKeyll. Parity and reliability improvements enable robust physics simulations and reproducible regression tests on HPC systems. Key outcomes include parity between Braginskii Lua wrappers and C; expanded Euler/5-moment fluid test suite; Lua GR interface enabling moment-spacetime coupling; Lua Vlasov app enhancements; major communicator infrastructure rewrite enabling MPI/CUDA across Vlasov, PKPM, and GK Lua apps; and broader GK non-uniform mappings/test coverage to support advanced plasma scenarios.

December 2024 monthly highlights for ammarhakim/gkeyll: robust cross-language parity, expanded test coverage, and mature general-relativistic capabilities, delivering measurable business value through reliability, reproducibility, and broader physics scope.

November 2024 monthly summary for ammarhakim/gkeyll: delivered major refactorings and Lua-driven solver integrations across GR, Vlasov, GK, and PKPM components to improve performance, stability, and scripting capability. The work emphasizes business value through cross-language parity with the C reference, reproducible results, and expanded physics coverage with external fields, non-uniform velocity spaces, and restartability across long-running simulations.

2024-10 monthly summary for ammarhakim/gkeyll: Delivered two major feature enhancements with validation groundwork and no recorded major bug fixes. 1) Moment time-stepper enhancements with Lua-configurable small time-step checks and post-simulation statistics, aligned with updates to the C input files. 2) Gradient-based closures support for the 10-moment equations, including Lua configuration refactor (hasGradClosure), updated C initializations, and new tests (LHDI with gradient closure). Overall impact includes improved diagnostic capabilities, enhanced modeling fidelity, and expanded test coverage. Technologies demonstrated: Lua-driven configuration, C input initializations, and drift-instability testing (LHDI).