#### ETHOS

The Enabling Technologies for High-Order Simulations (ETHOS) project performs research of fundamental mathematical technologies for next-generation high-order simulations algorithms.

#### MFEM

The open-source MFEM library enables application scientists to quickly prototype parallel physics application codes based on PDEs discretized with high-order finite elements.

#### GOLLNLP

Responding to a DOE grid optimization challenge, an LLNL-led team developed the mathematical, computational, and software components needed to solve problems of the real-world power grid.

#### Tarik Dzanic

As Computing’s seventh Fernbach Fellow, postdoctoral researcher Tarik Dzanic will develop new algorithms and test them in computational physics simulations under the mentorship of Bob Anderson.

#### Andrew Gillette

CASC computational mathematician Andrew Gillette has always been drawn to mathematics and says it’s about more than just crunching numbers.

#### Brian Gunney

From wind tunnels and cardiovascular electrodes to the futuristic world of exascale computing, Brian Gunney has been finding solutions for unsolvable problems.

#### LLNL’s Yang honored among 2024 SIAM Class of Fellows

The Society for Industrial and Applied Mathematics (SIAM) announced the selection of Lawrence Livermore National Laboratory (LLNL) computational mathematician Ulrike Meier Yang as one of the 2024 Class of SIAM Fellows, the highest honor the organization bestows on its members.

#### Machine learning tool fills in the blanks for satellite light curves

MuyGPs helps complete and forecast the brightness data of objects viewed by Earth-based telescopes.

#### New research in time integration methods recognized at IEEE conference

Can novel mathematical algorithms help scientific simulations leverage hardware designed for machine learning? A team from LLNL’s Center for Applied Scientific Computing aimed to find out.