Simons Foundation

Research

Astronomical Data The Astronomical Data group solves hard problems in measurement and discovery. Depending on the context, the challenges in these problems can stem from the sheer size or complexity of the datasets, the precision requirements for measurements, or the subtlety or structure of the signals of interest.

Biophysical Modeling The Biophysical Modeling group focuses on the modeling and simulation of complex systems that arise in biology and soft condensed matter physics.

Compact Objects The Compact Objects group studies the astrophysics of neutron stars and black holes, using them as unique cosmic laboratories for exploring the physics of extreme gravitational and electromagnetic fields and of matter at extreme densities.

Computational Vision We are interested in the analysis and representation of visual information, including empirical study of the structure of visual scenes, construction of mathematical theories for representation and processing that structure.

Cosmology X Data Science The Cosmology X Data Science group develops novel algorithms and ways of thinking to apply to datasets to answer fundamental questions about the cosmos.

Developmental Dynamics The Developmental Dynamics group combines experiments, theory and computing to elucidate the contributions of encoded genomic instructions and self-organizing physical mechanisms to embryonic development.

Dynamics The Dynamics Group explores how collective dynamics driven by gravitational interactions shape structures — planets, stars and galaxies — in the universe. This topic sits at the crossroads between large observed and simulated datasets that describe these structures in the real and model universe.

Dynamics and Control At the Center for Computational Quantum Physics, we are developing the conceptual basis, theoretical formalism and computational tools needed to use the quantum nature of light to understand and control quantum phenomena in complex systems.

Galaxy Formation The Galaxy Formation group is developing the numerical tools and physical insights necessary to understand how galaxies form and evolve within a cosmological context.

Genomics An immensely complex molecular network of interactions forms the foundation of human biology and disease. Genomic approaches provide a particularly illuminating window to biological systems, and when combined with advanced analysis allow us to learn and model this complexity.

Gravitational Wave Astronomy The detection of gravitational waves from the merging binary black hole GW150914, followed by the (likely) binary black hole mergers LVT151012, GW151226, and GW170104, means the era of gravitational wave astronomy is upon us.

Image and Signal Processing At CCM, we develop new computational and statistical methods, and accompanying software, for the analysis of large, complex data sets, especially those that arise from high-throughput scientific experiments.

Machine Learning and Data Analysis One of the obstacles in scientific data analysis is that the fundamental processes lead to questions that are posed in high-dimensional spaces

Neural Circuits and Algorithms Our goal is to understand how the brain analyzes large and complex datasets streamed by sensory organs in order to aid efforts at building artificial neural systems and treating mental illness.

NeuroAI and Geometric Data Analysis Our group develops mathematical theories for understanding how neurons collectively give rise to behavior in biological and artificial neural networks. Our current focus is on addressing this question through two broad approaches at the intersection of computational neuroscience and deep learning:

Numerical Analysis The direct numerical simulation of many scientific processes remains impractical, even with modern supercomputers.

Planet Formation The Planet Formation group develops the theoretical framework and computational methods needed to understand the origin and evolution of planets and planetary systems.

Quantum Materials What arrangement produces a material with an optimal thermoelectric figure of merit, or a combination of magnetic and ferroelectric properties, or a high superconducting critical temperature?

Software Libraries A major effort of the CCQ is the development and support of high quality open-source software for quantum many-body physics research. Making software which is reliable, efficient, and productive accelerates discovery and fosters scientific consensus and reproducibility.

Statistical Analysis of Neural Data We develop statistical models and open-source computational tools to extract insights from neural data. We are particularly interested in characterizing flexibility and variability in neural circuits—e.g., how do the dynamics of large neural ensembles change over the course of learning a new skill, during periods of high attention or task engagement, or during development and aging.

Systems Biology At the Systems Biology group, we are developing new methods to learn the networks that run life’s program.

Theory and Methods The quantum many-body problem is one of the hard problems of complexity theory: A direct solution requires computational resources that grow exponentially with the size of the problem to be solved.