Highlights

If you would like to add your own highlights to this page, please read the instructions.

CompFUSE

• Quantifying entanglement in the solid state using neutrons
• Advanced Simulations Reveal Orbital Structure of Cooper Pairs in High-Temperature Superconductors
• Enabling Portability and GPU Direct on DCA++
• A coherent theoretical description of Kitaev-candidate material α-RuCl3
• AI accelerates lattice quantum Monte Carlo simulations
• Density Matrix Renormalization Group Method Enables Computing High-Resolution Magnetic Excitation Spectra
• Advancing Materials Simulations on Summit via RAPIDS
• Emerging hole band spurs unconventional superconductivity

NUCLEI

• PREX, CREX, and nuclear models: the plot thickens
• Alpha clusters in Carbon-12 from ab initio theory & statistical learning
• Tetraneutron discovery confirms prediction
• Neutrinoless double 𝛽-decay of 48Ca
• Caught in flight: fermion pair dynamics in open quantum systems
• Ab initio computation of the neutron skin in 208Pb
• Nuclei with up to A=6 nucleons with artificial neural network wave functions
• Variational Monte Carlo calculations with artificial neural-network correlators
• Supernovae Ignited by Nuclear Fission
• Benchmarking Optimization & Supervised Machine Learning Methods
• Machine Learning-Based Inversion of Nuclear Responses
• Spin Susceptibility in Neutron Matter from QMC Calculations
• Computing nuclei at lightning speed
• Accurate bulk properties of nuclei and nuclear matter from potentials with Δ isobars
• Multimessenger constraints on the neutron-star equation of state and the Hubble constant
• Excitation energies from effective field theory with quantified uncertainties
• Theory of nuclear radii challenges the magic character of neutron number N=32
• Odd–even staggering of charge radii of exotic copper isotopes
• Many-Body Factorization & Position-Momentum Equivalence of SRC
• How well do we know the matter that is inside of neutron stars?
• Efficient emulators for scattering using eigenvector continuation
• Ab initio calculation of neutrinoless double beta decay
• Benchmark calculations of pure neutron matter with realistic nucleon-nucleon interactions
• Inclusive neutrino scattering in 12C
• Nuclear and neutron-star matter from local chiral interactions
• Discovery of mirror symmetry violation in bound nuclear ground states
• Large Sound Speed in Dense Matter and the Deformability of Neutron Stars
• (e,e’p) study of momentum distribution ratios in A=3 nuclei
• Chiral Effective Field Theory for Nuclei Structure
• Computing Beta Decay Everywhere
• Nuclear Charge Radii of Boron 10 and 11
• Neutron superfluidity and kinks in charge radii at magic numbers
• 50-year-old puzzle about beta-decay rates resolved from first principles
• Nuclear Pasta: strongest material in the universe
• Neutron Drip Line in the Ca Region from Bayesian Model Averaging
• Deep Learning for Nuclear Binding Energy and Radius
• Confronting gravitational waves with modern nuclear physics constraints
• Exploring new small system geometries in heavy ion collisions
• Cluster radioactivity of 294Og
• Scientific discovery through statistics
• Quantum Computing of an Atomic Nucleus
• Ab initio short-range-correlation scaling factors in nuclei up to A=40
• Featherweight Oxygen Explained
• Puzzling Sizes of Extreme Calcium Isotopes
• Neutron-Rich Helium Isotopes: Complex Made Simple
• Bayesian approach to model-based extrapolation of nuclear observables
• Nucleon momentum distributions for local chiral interactions
• First Direct Evidence for the Fastest Neutrino Emission Mechanism in a Neutron Star
• Connecting Neutron Skins to Gravitational Waves
• Quantum Monte Carlo calculations of nuclei with local chiral interactions
• Oganesson is an oddball among atoms and nuclei
• Computing the structure of the lightest tin isotopes
• Computation of fragments in the spontaneous fission of 240Pu
• Theory errors for nuclear calculations using Bayesian statistics
• Quantified complex-energy shell model interaction for light nuclei
• Computer studies of colliding oxygen nuclei
• Variational calculation of closed-shell nuclei up to A = 40

RAPIDS

• Machine Learned Magnetohdrodynamic Reduced-Order Models
• Lagrangian Particle Tracing for Next Generation Architectures
• Verification of Structured Code Refactoring
• Parallel Data Aggregation for Neutrino Event Analysis
• Plasma-Material Coupling with ADIOS
• Surrogate Modeling for Spatio-Temporal Data from Earth System Models
• Accelerating Density Functional Theory Computations
• Accelerating Sparse Triangular Solves in Fusion Science Codes through One-Sided Communication
• Accelerating HEP Data Analysis on HPC Platforms
• Accelerating I/O for VPIC Simulations
• Galaxy-Scale Strong Gravitational Lens Detection
• Integrating Human Perception with Computational Power for Guided Exploratory Data Analysis
• Data Management and Visualization for Plasma Physics
• Automated Parallel Event Generation and Analysis
• Accelerating Event Reconstruction for Liquid Argon TPC Neutrino Detectors
• Enabling Global Adjoint Tomography at scale through next-generation I/O
• Graphical Model Structure Learning at Unprecedented Scale
• Global Particle-in-Cell Simulation of Fusion Plasmas
• Multivariate, Temporal Visual Analytics for Climate Model Analysis
• Accelerating Earthquake Detection
• Accelerating Weather Research Forecasting Simulations with Deep Neural Network Surrogates
• Accelerating Computational Kernels of Tokamak Simulations (with FASTMath)
• Performance Optimization for Multiscale Gyrokinetic Turbulence
• Accelerating HEP Event Generation and Analysis on HPC Systems
• Accelerating Fusion Fission Simulations
• In situ Viz Unlocks Unsteady Dynamics at Extreme Scale
• Roofline-Based Modeling in Intel Advisor
• Improving Network Throughput with Global Communication Reordering
• Improving Collective Reduction Performance On Manycore Architectures
• Deep Stack Program Optimization
• Autonomic Data Movement for Data Staging-based In-Situ Workflows
• Robust IO Performance Modeling in Leadership-Class Systems by Automated Change Detection
• In Situ Compression Artifact Removal in Scientific Data Using Deep Transfer Learning
• Error-controlled Reduction and Retrieval for Scientific Data
• FTK: A Spacetime Meshing Framework for Robust and Scalable Feature Tracking
• Analysis of GPU Data Access Patterns on Complex Geometries for D3Q19 Lattice Boltzmann Algorithm
• In Situ Compression Artifact Removal in Scientific Data Using Deep Transfer Learning and Experience Replay
• Machine learning-based application grouping and knowledge extraction for HPC I/O
• Fast neural Poincaré maps for toroidal magnetic fields
• Cosmic Inference: Constraining Parameters With Observations and Highly Limited Number of Simulations
• IExchange: Asynchronous Communication and Termination Detection for Iterative Algorithms
• Asynchronous and Load-Balanced Union-Find for Distributed and Parallel Scientific Data Visualization and Analysis
• RISE: Reducing I/O Contention in Staging-based Extreme-Scale In-situ Workflows
• Stabilized Neural Ordinary Differential Equations for Long-Time Forecasting of Dynamical Systems
• Porting and Tuning HBPS Applications with TAU and APEX
• MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs and GPUs
• Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data
• VDL-Surrogate: A View-Dependent Visualization Surrogate for Ensemble Simulations
• Near-Term Climate Prediction and Explanation
• Leveraging One-Sided Communication for GPU-accelerated Sparse Triangular Solvers
• FES-ASCR Partnership for Research on Superfacility Workflows
• Chemical reaction networks and opportunities for machine learning
• Learning differentiable solvers for systems with hard constraints
• An ecosystem for digital reticular chemistry
• Error Estimation for Random Fourier Features
• Steady-state collisional radiative closures using random forest regressors
• Understanding HPC I/O Performance Models
• NN-EFIT: Physics-constrained Plasma equilibrium reconstruction for magnetically confined Fusion
• Machine Learning Based Volumetric Compression
• Deep Bayesian Climate Emulator
• Adaptive Optimization of Model Training for Multiple GPUs
• How to Achieve High I/O Throughput on Perlmutter
• Understanding Data Access Patterns for Distributed Science Collaboration
• Intelligent Draining to Reduce I/O Contention in Staging-based Workflows
• Adaptive Elasticity for In Situ Analysis and Visualization
• Region-adaptive, Error-controlled Scientific Data Compression for Scientific Data
• Error-bounded compression with preservation of derived quantities
• Mitigate Data Management Challenges for the Exa.TrkX Workflow
• A Scalable Distributed Workflow for Quantum Chemical Prediction of UV/Vis Absorption Spectra for Organic Molecules
• Extreme-Scale Ensembles of Iterative Random Forests
• Scalable Training of Graph Convolutional Neural Networks using the ADIOS Scientific Data Management Library
• HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization
• Using Multi-Resolution Data to Accelerate Neural Network Training Time
• Fast Merge Tree Computation via SYCL
• Mesh repartitioning and flattening added to VisIt
• VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations
• GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations
• Neural Stream Functions
• Deep Hierarchical Super-Resolution for Scientific Data Reduction and Visualization
• IDLat: An Importance-Driven Latent Generation Method for Scientific Data
• Latent Representations for Particle Feature Exploration
• LANL used RAPIDS2 Production Visualization in Producing Science Video
• Improved Parallel Rendering Performance with GPU-Based Image Compression
• VTK-m Demonstrates Performance Portability
• Analyzing the Impact of Lossy Data Reduction on Volume Rendering of Cosmology Data
• Automating Optimization of Generator Tuning Parameters
• Machine Learning-Driven Adaptive OpenMP For Portable Performance on Heterogeneous Systems
• Porting and Tuning HBPS Applications with TAU and APEX
• Performance Portability of Sparse Computational Methods on GPU-Accelerated Architectures
• ML-based Performance Portability for Density Functional Theory in HPC Environments
• Optimized Preprocessing For Scientific Deep Learning Applications
• Multi-GPU Parallel Sparse Triangular Solver
• Leveraging One-Sided Communication for Sparse Triangular Solvers on traditional CPUs
• Critical Path Model for Sparse Triangular Solvers
• FES-ASCR Partnership for Research on Superfacility Workflows
• EFIT-AI: Performance Portable GPU-accelerated Reconstruction
• CCAMP: Integrated Translation and Optimization for OpenACC and OpenMP
• IRIS: A Portable Task Runtime System for Extremely Heterogeneous Computing
• Porting HEP Event Reconstruction to GPU-based Heterogeneous Systems
• MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs and GPUs
• Analysis of GPU Data Access Patterns on Complex Geometries for D3Q19 Lattice Boltzmann Algorithm
• Verifying Fortran Programs with CIVL
• Verification of Data Race Freedom for OpenMP Programs

TEAMS

• Core-Collapse Supernova Explosion Theory (2021)
• Supernova neutrino signals based on long-term axisymmetric simulations (2021)
• Equation of State from Multi-Messenger Observations
• Three-Dimensional CCSN Explosion Models using Fornax (2019)
• Neutron-Star Merger Simulations (2018)
• Gravitational Waves from 3D CCSN models
• Fornax (CCSN simulation capability) code paper
• MAESTROeX Low Mach Number Solver
• Microphysics Dependence of CCSN Explosions
• Explosions of Low-Mass Massive Stars
• Gravitational Waves from Core-Collapse Supernovae
• Exploding 3D CCSN Model
• 3D Fornax Supernova Simulation
• 3D Kilonova Model
• 3D CCSN Correlations
• Resolution Dependence of CCSN 3D Simulations
• The Overarching Framework of Core-Collapse Supernova Explosions as Revealed by 3D Fornax simulations
• Equation of State Distribution for Simulations
• A systematic study of proto-neutron star convection in three-dimensional core-collapse supernova simulations

Last updated: 27 February 2024