Michael Pürrer

Biography

2022-present: Computational Scientist & Adjunct Assistant Professor, University of Rhode Island
2017 – 2022: Senior Scientist, Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Potsdam-Golm, Germany.
2015-2016: Postdoctoral Researcher, Max Planck Institute for Gravitational Physics (Albert Einstein Institute), Potsdam-Golm, Germany
2012-2015: Research Associate, Cardiff University, United Kingdom
2010-2012: Postdoctoral Researcher, University of Vienna, Austria
2009-2010: Technical Consultant for modeling and simulation of fuel injection systems, ECS GmbH & CoKG / MAGNA POWERTRAIN, Vienna, Austria
2007-2008: Postdoctoral Researcher, University of Vienna, Austria

Research

  • Gravitational wave data analysis
  • Compact binary source modeling & surrogate modeling
  • Scientific computing & high-performance computing
  • Data science and machine learning

Education

  • Ph.D. in Theoretical Physics, University of Vienna, Austria, 2007
  • Diploma in Theoretical Physics, University of Vienna, Austria, 2003

Selected Publications

  • M. Dax , S. Green, J. Gair, M. Pürrer, J. Wildberger, et al, “Neural Importance Sampling for Rapid and Reliable Gravitational-Wave Inference”, Phys. Rev. Lett. 130, 171403, https://doi.org/10.1103/PhysRevLett.130.171403
  • J. Wildberger, M. Dax, S. Green, J. Gair, M. Pürrer, et al, “Adapting to noise distribution shifts in flow-based gravitational-wave inference”, Phys. Rev. D 107, 084046, https://doi.org/10.1103/PhysRevD.107.084046
  • B. Gadre, M. Pürrer, S. Field, S. Ossokine, V. Varma, “A fully precessing higher-mode surrogate model of effective-one-body waveforms”, Preprint https://arxiv.org/abs/2203.00381.
  • V. Kalogera, et al, “The Next Generation Global Gravitational Wave Observatory: The Science Book”, Preprint https://arxiv.org/abs/2111.06990.
  • I. M. Romero-Shaw, et al, “Bayesian inference for compact binary coalescences with BILBY: validation and application to the first LIGO-Virgo gravitational-wave transient catalogue”, MNRAS 499, 3, 3295 (2020). doi: 10.1093/mnras/staa2850.
  • S. Ossokine, A. Buonanno, S. Marsat, R. Cotesta, S. Babak, T. Dietrich, R. Haas, I. Hinder, H. Pfeiffer, M. Pürrer, et al, “Multipolar effective-one-body waveforms for precessing binary black holes: Construction and validation”, Phys.Rev. D102, 044055 (2020), doi: 10.1103/PhysRevD.102.044055.
  • A. Matas, T. Dietrich, A. Buonanno, T. Hinderer, M. Pürrer, et al, “Aligned-spin neutron-star-black-hole waveform model based on the effective-one-body approach and numerical-relativity simulations”, Phys.Rev. D102, 043023 (2020), doi: 10.1103/PhysRevD.102.043023.
  • R. Cotesta, S. Marsat, M. Pürrer, “Frequency domain reduced order model of aligned-spin effective-one-body waveforms with higher-order modes”, Phys.Rev. D101, 124040 (2020), doi: 10.1103/PhysRevD.101.124040.
  • M. Pürrer, C.-J. Haster, “Ready for what lies ahead? – Gravitational waveform accuracy requirements for future ground based detectors”, Physical Review Research, 2, 023151 (2020), doi: 10.1103/PhysRevResearch.2.023151.
  • B. D. Lackey, M. Pürrer, A. Taracchini, S. Marsat, “Surrogate model for an aligned-spin effective one body waveform model of binary neutron star inspirals using Gaussian process regression”, Phys.Rev. D100, 024002 (2019), doi: 10.1103/PhysRevD.100.024002.
  • B.P.Abbott et al, “GWTC-1: A Gravitational-Wave Transient Catalog of Compact Binary Mergers Observed by LIGO and Virgo during the First and Second Observing Runs”, Phys. Rev. X 9, 031040, doi: 10.1103/PhysRevX.9.031040.
  • B.P.Abbott et al, “Effects of waveform model systematics on the interpretation of GW150914”, Class.Quant.Grav. 34 (2017) no.10, 104002, doi: 10.1088/1361-6382/aa6854.

An auto-generated list of Dr. Pürrer‘s publications can be found on the Astrophysics data system website

Awards and Honors

Recipient of 2016 Special Breakthrough Prize in Fundamental Physics (as part of the LSC).
Recipient of 2016 Gruber Cosmology Prize (as part of the LSC).
Recipient of Premio Princesa de Asturias de Investigación 2017 (as part of the LSC).
Recipient of 2017 RAS Group Achievement Award ‘A’ (as part of the LSC).