Brookhaven Lab is establishing itself as a global leader in tackling the challenges of Big Data, building on our existing expertise, capabilities, and investments in computational science and data management, and enabling scientific discovery in large-scale experimental environments.
Computer Science and Mathematics
Computing for National Security
Scientific Data and Computer Center
Center for Data-Driven Discovery
Computational Science LaboratoryAbout Us
Building on its capabilities in data-intensive computing and computational science, Brookhaven National Laboratory has embarked upon a major Computational Science Initiative.
Advances in computational science, data management and analysis have been a key factor in the success of Brookhaven Lab's scientific programs at the Relativistic Heavy Ion Collider (RHIC), the National Synchrotron Light Source (NSLS), the Center for Functional Nanomaterials (CFN), and in biological, atmospheric, and energy systems science, as well as our collaborative participation in international research endeavors, such as the ATLAS experiment at Europe's Large Hadron Collider.
The Computational Science Initiative (CSI) brings together under one umbrella the expertise that has driven this success to foster cross-disciplinary collaborations to address the next generation of scientific challenges posed by facilities such as the new National Synchrotron Light Source II (NSLS-II). A particular focus of CSI's work will be the research, development and deployment of novel methods and algorithms for the timely analysis and interpretation of high volume, high velocity, heterogeneous scientific data created by experimental, observational and computational facilities to accelerate and advance scientific discovery. CSI is hereby taking an integrated approach, providing capabilities from leading edge research to multi-disciplinary teams that deliver operational data analysis capabilities to the scientific user communities.
Enabling Capabilities
Computer Science and Mathematics—fundamental research into novel methods and algorithm in support of large-scale, multi-modal, and streaming data analysis. Novel solutions for long term data curation and active reuse. Approaches to enable energy efficient, extreme-scale numerical modeling specifically in computational materials science, chemistry, lattice quantum chromo dynamics and fusion.
The BNL Scientific Data and Computing Center, housing the latest systems in high-performance and data-intensive computing, data storage, and networking, offering everything from novel research platforms to highly reliable production services.
Translational Capabilities
The Computational Science Laboratory, a collaborative space for the development of advanced algorithms and their characterization and optimization, also brings together computer scientists, mathematicians, and leading computational scientists to develop next-generation numerical simulation models
The Center for Data Driven Discovery (C3D), a multi-disciplinary center for the development, deployment, and operation of data-intensive discovery services for science, national security, and industry
A Multi-disciplinary, Collaborative Approach
The CSI philosophy is a multi-disciplinary and collaborative approach to scientific research and development, with research targeted at and informed by the key challenges observed in close interactions with our clients in science, national security agencies, and industry. Our success is measured in equal parts by the advancement we can bring to computer science and mathematics, as well as by the transformational impact we have on our clients’ mission space.
The CSI brings together under one umbrella the expertise that fosters cross-disciplinary collaboration and makes optimal use of existing technologies, while also leading the development of new tools and methods that will benefit science both within and beyond the Laboratory. Key partners include nearby universities such as Columbia, Cornell, New York University, Stony Brook, and Yale, as well as IBM Research.
Strategic Partnerships
Brookhaven's computational scientists are looking to establish partnerships with key players in academia and industry (e.g. Stony Brook University’s Institute for Advanced Computational Science, Rensselaer Polytechnic Institute, Oak Ridge National Laboratory, IBM, and Intel). An example of a successful partnership is the collaboration of Brookhaven Lab’s high-energy and nuclear physics research groups with IBM that led to the development of the BlueGene supercomputing architecture now used on the world’s most powerful commercially available supercomputers.
More about strategic partnerships-
JAN
31
Thursday
CFN Colloquium
""Fermi systems and quantum computing""
Presented by Antonio Mezzacapo, Theory of Quantum Computing and Information, IBM T.J. Watson Research Center
4 pm, CFN, Bldg 735, Seminar Room 2nd Floor
Thursday, January 31, 2019, 4:00 pm
Hosted by: Deyu Lu (CFN) / Michael McGuigan (CSI)
Solving correlated Fermi systems is a problem of ubiquitous importance in the fields of chemistry, materials science and fundamental interactions. Quantum computers can help addressing this type of challenges, provided that descriptions of Fermi systems are loaded onto a set of qubits. In this talk I will review methods to represent Fermi quantum states and interactions onto a set of qubits, how to optimize mapping procedures, and how these methods are used to perform computations on quantum hardware. I will then introduce connections between such mappings and stabilizer codes, showing that adequate encodings can account for the correction of single-qubit errors. Finally, I will show how the tools presented can have an impact on classical numerical methods.
There are no conferences scheduled at this time.
