Los Alamos National Labs with logo 2021

Computer, Computational, and Statistical Sciences

Computational physics, computer science, applied mathematics, statistics and the integration of large data streams are central to scientific discovery and innovation.
  • Deputy Division Leader
  • Aimee Hungerford
  • Email
  • Staff Operations Manager
  • Anita Castaneda
  • Email

Point of Contact  

Earth climate map

A single time step from an MPAS (Model for Prediction Across Scales) simulation, showing the temperature of the ocean. Building on research in human perception, our visualization researchers are exploring how to best emphasize features within extremely large simulations such as MPAS, so that important information is quickly and succinctly communicated to scientists. In this image, a blue/green colormap has been used to highlight the behavior of ocean eddies where the blue and green currents 'mix', and to emphasize the overall structure of features within the data.


The Computer, Computational, and Statistical Sciences (CCS) Division strengthens the visibility and impact of computer science and computational physics research for the strategic directions at the Laboratory.

Solving national problems through basic and applied research in key areas of

  • Climate and Energy programs
  • Basic science and technology research programs
  • Threat reduction and Department of Homeland Security programs
  • Nuclear weapons program
  • Information science and technology

Computational Physics and Methods

  • Performing innovative simulations of physics phenomena on tomorrow's scientific computing platforms
  • Conducting research in numerical methods and algorithms, physical model development, and software engineering
  • Creating numerical radiation transport methods to support the United States’ weapons program and produces packages for use in Advanced Strategic Computing codes

Information Sciences

  • Creating insight from heterogeneous data through advanced mathematics
  • Developing methods and tools for understanding complex interactions and extracting actionable information from massive data streams

Statistical Sciences

  • Providing statistical reasoning and rigor to multidisciplinary scientific investigations and the development, application, and communication of cutting-edge statistical sciences research

Applied Computer Science

  • Leading the way for scientific applications at extreme scale through co-design of algorithms, programming models, system software, and tools
  • Exploring new programming models, data-intensive computing, data science at extreme scales, and application and algorithm co-design 

Scientific activities are focused on:

  • Computational multiphysics and numerical modeling
  • Data-driven modeling and informatics
  • Computer and computational science
  • Computational co-design
  • Computational astrophysics
  • Comprehensible and incomprehensible fluids and hydrodynamics in complex flows
  • Data science at scale
  • Information science and technology
  • Computational biology and bioinformatics
  • Statistical sciences
  • Nuclear engineering and technology
  • High energy density plasmas and warm dense matter
  • Computational physics and applied math
  • Data analysis and uncertainty quantification
Programs Supported
  • Basic Science and Energy Research
  • DOE Defense Programs
  • DOE Nuclear Energy
  • DOE Office of Science
  • Homeland Security Programs
  • Advanced Simulation and Computing (ASC)
  • Nuclear Non-proliferation and Security
  • Laboratory Directed Research and Development (LDRD)
  • Defense Advanced Research Projects Agency (DARPA)
  • Defense Threat Reduction Agency (DTRA)

Applied Computer Science

  • Co-design
  • Data science at scale
  • Scientific visualization
  • Programming models

Computational Physics

  • High-fidelity techniques necessary to deliver verified and validated numerical solutions for important LANL programmatic simulation tools
  • Modern software practices, including formal verification and validation and the use of rapid prototyping tools
  • Numerical methods for advanced and emerging architecture
  • Molecular Dynamics and numerical kinetic theory of plasmas
  • Advanced multi-scale, multi-physics methods

Information Sciences

  • Computer science research in performance analysis and modeling of extreme-scale parallel systems and applications
  • Pattern recognition and machine learning
  • Knowledge systems and computational linguistics
  • Computational biology
  • Multilevel solvers
  • Quantum computing
  • Applied mathematics and computer science for scientific and engineering foundations of simulation for socio-technical systems

Statistical Sciences

  • Statistical reasoning
  • Multidisciplinary scientific investigations
  • Development, application, and communication of cutting-edge statistical sciences research