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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.

About Us

Brookhaven Lab's Computational Science Initiative, known as CSI, excels at integrating computer science, applied mathematics, and computational science with broad domain expertise to tackle problems and advance knowledge impacting scientific discovery.

CSI has long focused on timely analysis and interpretation of high-volume, high-velocity heterogeneous data, providing solutions for the national and international scientific community. These efforts now are being augmented by CSI's growing high-performance computing capabilities.


CSI takes a multidisciplinary, collaborative approach to its research, targeting challenges in cooperation with fellow researchers in science, national security, and industry—both at home and abroad.

We measure success by the transformational impacts we bring to how research is conducted and the advances we introduce to fundamental disciplines such as mathematics, data analysis, and computer science.

Computational Science News

  1. SEP



    NSLS-II Friday Lunchtime Seminar

    "Quantum Computing on crystalline beams of ions: the concept and proof-of-principle experiments"

    Presented by Timur Shaftan, NSLS-II

    12 pm, NSLS-II Bldg. 743 Room 156

    Friday, September 27, 2019, 12:00 pm

    Hosted by: Ignace Jarrige

    One of the promising directions in Quantum Computers (QC) is based on using ion traps. In a modern QC, several tens of ions are collected in an electromagnetic trap of a cm in size, with their motion cooled down to micro K temperature level, leading to entanglement of their quantum states, controlled by laser and RF fields. These ions = qubits then used to run quantum computations at unprecedent rate using specialized codes (check, for example, QuTip, Quantum Toolbox in Python). I will discuss a concept of a QC, which holds a promise to support 105 of qubits in contrast to the state-of-the-art devices. The idea is to use crystalline beams of ions in an accelerator as the medium for qubits. The crystalline beams were demonstrated in storage rings in 1980s when many protons, being cooled with electron beam formed a revolving ring with crystalline-like structure inside. Marrying this concept with that of the QC on a conventional ion trap, one might consider expansion of the QC to a large particle accelerator with high qubit capacity. The latter is important for expansion of QC capabilities, including the processing power and robustness against errors due to decoherence. In this presentation I will go over the concept and my analysis of a few challenges that require proof-of-principal experiments so that the some basic aspects of this interesting concept are validated.

  1. SEP



    GPU Hackathon 2019

    September 23-27, 2019

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