Erik Schnetter

Erik Schnetter profile picture
Research Technologies Group Lead
Perimeter Institute for Theoretical Physics
Technology Services
Areas of research:
Strong Gravity
(519) 569-7600 x7032
http://www.perimeterinstitute.ca/personal/eschnetter/
I am a staff scientist at the Perimeter Institute for Theoretical Physics in Waterloo, Canada, where I lead the Research Technologies Group.
My research interests lie in computational science, in using computers as tools to solve scientific problems. This requires not only correctly and efficiently implementing physics models, but also requires tools to build complete applications around these models – such as: - Tools for communicating and collaborating, in particular for small, informal collaborations, including tools for software development, - Efficient computational infrastructure, supporting hardware ranging from laptops to large high-performance computing (HPC) installations, that allow people to easily build and publish their own applications, - Reducing the steep learning curve for high-performance computing, by making HPC calculations more transparent and more interactive.
  • Adjunct Faculty, Department of Physics & Astronomy, University of Waterloo, 2018-present
  • Adjunct Faculty, Department of Physics, University of Guelph, 2011-2018
  • Adjunct Faculty, Center for Computation & Technology, Louisiana State University, 2010-present
  • Postdoctoral Scholar, Max Planck Institute for Gravitational Physics, 2003-2005
  • Second IEEE International Scalable Computing Challenge, 1st place, SCALE, 2009
  • Shankar, S., Mösta, P., Brandt, S. R., Haas, R., Schnetter, E., & de Graaf, Y. (2023). GRaM-X: a new GPU-accelerated dynamical spacetime GRMHD code for Exascale computing with the Einstein Toolkit. Classical and Quantum Gravity, 40(20), 205009. doi:10.1088/1361-6382/acf2d9
  • Dailey, C., Afshordi, N., & Schnetter, E. (2023). Reflecting boundary conditions in numerical relativity as a model for black hole echoes. Classical and Quantum Gravity, 40(19), 195007. doi:10.1088/1361-6382/acde2f
  • Hammond, J., Dalcin, L., Schnetter, E., PéRache, M., Besnard, J. -B., Brown, J., . . . Zhou, H. (2023). MPI Application Binary Interface Standardization. In Proceedings of the 30th European MPI Users' Group Meeting. ACM. doi:10.1145/3615318.3615319
  • Khera, N., Metidieri, A. R., Bonga, B., Forteza, X. J., Krishnan, B., Poisson, E., . . . Yang, H. (2023). Nonlinearities at Black Hole Horizons. arxiv:2306.11142v2
  • Curtis, S., Bosch, P., Mösta, P., Radice, D., Bernuzzi, S., Perego, A., . . . Schnetter, E. (2023). Outflows from Short-Lived Neutron-Star Merger Remnants Can Produce a Blue Kilonova. arxiv:2305.07738v1
  • Dailey, C., Afshordi, N., & Schnetter, E. (2023). Reflecting boundary conditions in numerical relativity as a model for black hole echoes. arxiv:2301.05778v1
  • Schnetter, E. (2022). The Einstein Toolkit (Version ET_2022_11) [Computer Software]. doi:10.5281/zenodo.7245853
  • Churavy, V., Godoy, W. F., Bauer, C., Ranocha, H., Schlottke-Lakemper, M., Räss, L., . . . Edelman, A. (2022). Bridging HPC Communities through the Julia Programming Language. arxiv:2211.02740v2
  • Shankar, S., Mösta, P., Brandt, S. R., Haas, R., Schnetter, E., & Graaf, Y. D. (2022). GRaM-X: A new GPU-accelerated dynamical spacetime GRMHD code for Exascale computing with the Einstein Toolkit. arxiv:2210.17509v2
  • Peters, J. M., Coley, A., & Schnetter, E. (2022). Curvature invariants in a binary black hole merger. General Relativity and Gravitation, 54(7). doi:10.1007/s10714-022-02944-1
  • Coley, A., Peters, J. M., & Schnetter, E. (2021). Geometric horizons in binary black hole mergers. Classical and Quantum Gravity, 38(17), 17LT01. doi:10.1088/1361-6382/ac10ed
  • Mourier, P., Jiménez Forteza, X., Pook-Kolb, D., Krishnan, B., & Schnetter, E. (n.d.). Quasinormal modes and their overtones at the common horizon in a binary black hole merger. Physical Review D, 103(4). doi:10.1103/physrevd.103.044054
  • Peters, J. M., Coley, A., & Schnetter, E. (2021). Curvature Invariants and the Geometric Horizon Conjecture in a Binary Black Hole Merger. arxiv:2101.09615v2
  • Mösta, P., Radice, D., Haas, R., Schnetter, E., & Bernuzzi, S. (n.d.). A Magnetar Engine for Short GRBs and Kilonovae. The Astrophysical Journal, 901(2), L37. doi:10.3847/2041-8213/abb6ef
  • Prasad, V., Gupta, A., Bose, S., Krishnan, B., & Schnetter, E. (n.d.). News from Horizons in Binary Black Hole Mergers. Physical Review Letters, 125(12). doi:10.1103/physrevlett.125.121101
  • Pook-Kolb, D., Birnholtz, O., Jaramillo, J. L., Krishnan, B., & Schnetter, E. (2020). Horizons in a binary black hole merger I: Geometry and area increase. arxiv:2006.03939v1
  • Pook-Kolb, D., Birnholtz, O., Jaramillo, J. L., Krishnan, B., & Schnetter, E. (2020). Horizons in a binary black hole merger II: Fluxes, multipole moments and stability. arxiv:2006.03940v1
  • Numerical Methods Lecture - 230207, Numerical Methods (2022/2023), 2023/02/07, PIRSA:23020001
  • Numerical Methods Lecture - 230202, Numerical Methods (2022/2023), 2023/02/02, PIRSA:23020000
  • Numerical Methods Lecture - 230201, Numerical Methods (2022/2023), 2023/02/01, PIRSA:23020003
  • Numerical Methods Lecture - 230131, Numerical Methods (2022/2023), 2023/01/31, PIRSA:23010008
  • Numerical Methods Lecture - 230126, Numerical Methods (2022/2023), 2023/01/26, PIRSA:23010007
  • Numerical Methods Lecture - 230124, Numerical Methods (2022/2023), 2023/01/24, PIRSA:23010006
  • Numerical Methods Lecture - 230120, Numerical Methods (2022/2023), 2023/01/20, PIRSA:23010011
  • Numerical Methods Lecture - 230119, Numerical Methods (2022/2023), 2023/01/19, PIRSA:23010005
  • Numerical Methods Lecture - 230117, Numerical Methods (2022/2023), 2023/01/17, PIRSA:23010004
  • Numerical Methods Lecture - 230112, Numerical Methods (2022/2023), 2023/01/12, PIRSA:23010003
  • Numerical Methods Lecture - 230111, Numerical Methods (2022/2023), 2023/01/11, PIRSA:23010009
  • Numerical Methods Lecture - 230110, Numerical Methods (2022/2023), 2023/01/10, PIRSA:23010002