Peter Coveney

Last updated

Peter Coveney

FREng, MAE, FRSC, FInstP
PVC-2022.jpg
Coveney in April 2022
Born
Peter V. Coveney

Ealing, England
Nationality British
Alma mater University of Oxford
Scientific career
Fields
  • Computational Science
  • Physical Chemistry
  • Materials Science & Engineering
  • Computer Science
  • Life and Medical Sciences
  • High-Performance Computing
  • Validation, Verification and Uncertainty Quantification
  • Quantum Computing
Institutions University College London,
University of Amsterdam
Yale University
Thesis Semiclassical methods in scattering and spectroscopy  (1985)
Doctoral advisor Mark Child [1]
Website www.ucl.ac.uk/computational-science/advancing-science-through-computersthe-centre-computational-science

Peter V. Coveney is a British chemist who is Professor of Physical Chemistry, Honorary Professor of Computer Science, and the Director of the Centre for Computational Science (CCS) [2] and Associate Director of the Advanced Research Computing Centre at University College London (UCL). He is also a Professor of Applied High Performance Computing at University of Amsterdam (UvA) and Professor Adjunct at the Yale School of Medicine, Yale University. He is a Fellow of the Royal Academy of Engineering and Member of Academia Europaea. [3] Coveney is active in a broad area of interdisciplinary research including condensed matter physics and chemistry, materials science, as well as life and medical sciences in all of which high performance computing plays a major role. The citation about Coveney on his election as a FREng says: Coveney "has made outstanding contributions across a wide range of scientific and engineering fields, including physics, chemistry, chemical engineering, materials, computer science, high performance computing and biomedicine, much of it harnessing the power of supercomputing to conduct original research at unprecedented space and time scales. He has shown outstanding leadership across these fields, manifested through running multiple initiatives and multi-partner interdisciplinary grants, in the UK, Europe and the US. His achievements at national and international level in advocacy and enablement are exceptional". [4]

Contents

Education

Coveney was awarded a Doctor of Philosophy degree from the University of Oxford in 1985 for his work on Semiclassical methods in scattering and spectroscopy. [1]

Career

Coveney has held positions at University of Oxford, Princeton University, Schlumberger and QMUL, and currently holds positions at UCL [5] , UvA [6] and Yale, as well as acting as a Member of several academic councils in the UK [7] [8] and EU.

Research

Coveney worked with Ilya Prigogine at the Free University of Brussels (1985-87) and went on to publish work with the mathematician Oilver Penrose on rigorous foundations of irreversibility and the derivation of kinetic equations based on chaotic dynamical systems. [9] [10] [11] [12] He collaborated with Jonathan Wattis on extensions and generalisations of the Becker-Döring and Smoluchowski equations for the kinetics of aggregation-fragmentation processes which they applied to a wide range of phenomena, from self-reproducing micelles and vesicles to a scenario for the origin of the RNA world in which they showed that self-reproducing sequences of RNA can spontaneously arise from an aqueous mixture of the RNA nucleotide bases. [13] [14] [15] [16]

At Schlumberger Cambridge Research (SCR), Coveney initiated new lines of research in which advanced computational methods played a central role. Some parts of this work, to develop highly scalable lattice-gas and, later, lattice-Boltzmann models of complex fluids, was done in collaboration with Bruce M. Boghosian, following Schlumberger’s acquisition of a Connection Machine, the CM-5, from the company.[ citation needed ]

In a forerunner of many contemporary applications of machine learning, Coveney showed that one can use a combination of infrared spectroscopy and artificial neural networks to predict the setting properties of cement, without any need to dwell on the polemics of the chemical composition of cementitious materials and the concrete that forms when it hardens. [17] [18] At the same time, using methods from nonlinear dynamics, he was able to identify the rate-determining processes that enable one to design new compounds which inhibit the crystallisation of the mineral ettringite by molecular modelling. [19]

From 2006, Coveney moved away from studying oilfield fluids to investigate blood flow in the human body, including the brain. Working with a PhD student, Marco Mazzeo, he developed a new code, named HemeLB, which simulates blood flow in the complex geometries of the human vasculature, as derived from a variety of medical imaging modalities. [20] [21] [22] The algorithm, based on indirect addressing, scales to very large core counts on CPU-based supercomputers. Most recently, he and his team have developed a GPU-accelerated version of the code which scales to around 20,000 GPUs on the Summit supercomputer and will soon[ when? ] be deployed on the world’s first exascale machine, Frontier. [23]

Coveney works in the domain of multiscale modelling and simulation. Working initially with Eirik Flekkøy on foundations of the dissipative particle dynamics method and then with Rafael Delgado-Buscalioni, he was among the first to develop theoretical schemes which couple molecular dynamics and continuum fluid dynamics representations of fluids in a single simulation.[ citation needed ] His work covers numerous applications of these methods in advanced materials and biomedical domains. [24] [25] [26] [27] [28] [29]

Coveney’s recent work is on the rapid, accurate, precise and reliable prediction of free energies of binding of ligands to proteins, [30] a major topic in drug discovery. Coveney has noted that classical molecular dynamics is chaotic and to make robust predictions from it requires the use of ensembles at all times. [31] This is a practical manifestation of his earlier work on simpler dynamical systems, for which a thermodynamic description is possible using a probabilistic formulation. [32] It has only become possible in the era of petascale computing, when supercomputers have grown to sufficient size to make calculations of ensemble averages feasible.

Working with Bruce Boghosian and Hongyan Wang, Coveney showed that there are a variety of problems which arise when simulating even the simplest of all dynamical systems — the generalised Bernoulli map — on a computer. [33] The IEEE floating point numbers can produce errors which are extremely large as well others of more modest scale, but they are each wrong when compared with the known exact mathematical description of the dynamics.

In recent years, Coveney has been a leading player in the development and application of validation, verification and uncertainty quantification (VVUQ) to computer simulation codes across a wide range of domains. The VECAM Toolkit [34] [35] and later SEAVEA Toolkit [36] provide a set of open-source, open-development software components which can be used to instrument any code so as to study its VVUQ characteristics. The methods his team has developed [37] are aimed at the analysis of real-world codes of substantial complexity which run on high performance computers.

Coveney has become active in quantum computing, where he is specifically concerned with seeking to assess the feasibility of realising quantum advantage from its application to the solution of molecular electronic structure problems. He and his team are currently dealing with noise reduction and implementing error mitigation as extensively as possible on a range of quantum device architectures. [38] [39] [40] [41]

Coveney led the EPSRC RealityGrid e-Science Pilot Project [42] and its extension project, and the EU FP7 Virtual Physiological Human (VPH) Network of Excellent. [43] He is the Principal Investigator on the EU Horizon 2020 projects Verified Exascale Computing for Multiscale Applications, "VECMA" [44] and Centre of Excellence in Computational Biomedicine,"CompBioMed2". [45] The original CompBioMed initiative [46] was launched after Coveney and his team successfully challenged the EU [47] following a rejected grant proposal.

Coveney has been the recipient of US NSF and DoE, and European DEISA and PRACE [48] supercomputing awards.

Coveney has chaired the UK Collaborative Computational Projects Steering Panel [49] and served on the programme committee of the 2002 Nobel Symposium on self-organization. [50] He is a founding member of the UK Government's e-Infrastructure Leadership Council and a Medical Academy Nominated Expert to the UK Prime Minister's Council for Science and Technology [51] on Data, Algorithms and Modelling, which has led to the creation of the London-based Alan Turing Institute.

Books

Coveney has co-authored three popular science books with his long term friend and collaborator, Roger Highfield:

Related Research Articles

This is a timeline of quantum computing.

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Numerical relativity is one of the branches of general relativity that uses numerical methods and algorithms to solve and analyze problems. To this end, supercomputers are often employed to study black holes, gravitational waves, neutron stars and many other phenomena described by Einstein's theory of general relativity. A currently active field of research in numerical relativity is the simulation of relativistic binaries and their associated gravitational waves.

Quantum annealing (QA) is an optimization process for finding the global minimum of a given objective function over a given set of candidate solutions, by a process using quantum fluctuations. Quantum annealing is used mainly for problems where the search space is discrete with many local minima; such as finding the ground state of a spin glass or the traveling salesman problem. The term "quantum annealing" was first proposed in 1988 by B. Apolloni, N. Cesa Bianchi and D. De Falco as a quantum-inspired classical algorithm. It was formulated in its present form by T. Kadowaki and H. Nishimori in 1998 though an imaginary-time variant without quantum coherence had been discussed by A. B. Finnila, M. A. Gomez, C. Sebenik and J. D. Doll in 1994.

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<span class="mw-page-title-main">CP2K</span>

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References

  1. 1 2 Coveney, Peter V (1985). Semiclassical methods in scattering and spectroscopy (DPhil thesis). University of Oxford.
  2. ↑ ""The Centre for Computational Science"". 4 May 2021. Retrieved 29 December 2022.
  3. ↑ "Academy of Europe: Coveney Peter". Ae-info.org. Retrieved 13 February 2021.
  4. ↑ "Royal Academy of Engineering". raeng.org.uk. Retrieved 21 April 2024.
  5. ↑ "Peter Coveney, Professor of Physical Chemistry, Dept of Chemistry". profiles.ucl.ac.uk. Retrieved 21 April 2024.
  6. ↑ Amsterdam, Universiteit van (22 October 2023). "Prof. dr. P.V. (Peter Vivian) Coveney". University of Amsterdam. Retrieved 21 April 2024.
  7. ↑ University, Durham. "Institute of Advanced Study : Professor Peter Coveney - Durham University". www.durham.ac.uk. Retrieved 21 April 2024.
  8. ↑ "REF Case study search". impact.ref.ac.uk. Retrieved 21 April 2024.
  9. ↑ Coveney, P.V. (1987). "Statistical mechanics of a large dynamical system interacting with an external time-dependent field: generalised correlation subdynamics". Physica A: Statistical Mechanics and Its Applications. 143 (3): 507–534. Bibcode:1987PhyA..143..507C. doi:10.1016/0378-4371(87)90163-4.
  10. ↑ Coveney, P. V.; Penrose, O. (1992). "On the validity of the Brussels formalism in statistical mechanics". J. Phys. A: Math. Gen. 25 (19): 4947. Bibcode:1992JPhA...25.4947C. doi:10.1088/0305-4470/25/19/011.
  11. ↑ Evans, Allan K.; Coveney, Peter V. (1995). "On exponential long-time evolution in statistical mechanics". Proc. R. Soc. Lond. A. 448 (1933): 293–319. Bibcode:1995RSPSA.448..293E. doi:10.1098/rspa.1995.0018. S2CID   122838748.
  12. ↑ Evans, Allan K; Coveney, Peter V (1998). "On the long-time behaviour of ensembles in a model of deterministic diffusion". J. Phys. A: Math. Gen. 31 (28): 5887. Bibcode:1998JPhA...31.5887E. doi:10.1088/0305-4470/31/28/006.
  13. ↑ Coveney, Peter V.; Wattis, Jonathan A. D. (1996). "Analysis of a generalized Becker—Döring model of self-reproducing micelles". Proc. R. Soc. Lond. A. 452 (1952): 2079–2102. Bibcode:1996RSPSA.452.2079C. doi:10.1098/rspa.1996.0110. S2CID   95877636.
  14. ↑ Coveney, P. V.; Wattis, J. A. D. (1999). "Cluster renormalization in the Becker-Döring equations". J. Phys. A: Math. Gen. 32 (41): 7145. arXiv: cond-mat/9908402 . Bibcode:1999JPhA...32.7145C. doi:10.1088/0305-4470/32/41/308. S2CID   17019314.
  15. ↑ Wattis, J. A. D.; Coveney, P. V. (1999). "The origin of the RNA world: A kinetic model". J. Phys. Chem. B. 103 (21): 4231–4250. arXiv: adap-org/9903002 . doi:10.1021/jp983159v. S2CID   17792989.
  16. ↑ Wattis, J. A. D.; Coveney, P. V. (2005). "Symmetry-breaking in Chiral Polymerisation". Orig Life Evol Biosph. 35 (3): 243–273. arXiv: physics/0402091 . Bibcode:2005OLEB...35..243W. doi:10.1007/s11084-005-0658-7. PMID   16228641. S2CID   12451904.
  17. ↑ Coveney, P. V.; Fletcher, P.; Hughes, T. L. (1996). "Using Artificial Neural Networks to Predict the Quality and Performance of Oil-Field Cements". AI Magazine. 17 (4): 41. doi:10.1609/aimag.v17i4.1239.
  18. ↑ Scott, D. J.; Coveney, P. V.; Kilner, J. A.; Rossiny, J. C. H.; Alford, N. M. N. (2007). "Prediction of the functional properties of ceramic materials from composition using artificial neural networks". Journal of the European Ceramic Society. 27 (16): 4425–4435. arXiv: cond-mat/0703210 . doi:10.1016/j.jeurceramsoc.2007.02.212. S2CID   16162179.
  19. ↑ Bentz, D. P.; Coveney, P. V.; Garboczi, E. J.; Kleyn, M. F.; Stutzman, P. E. (1994). "Cellular automaton simulations of cement hydration and microstructure development". Modelling and Simulation in Materials Science and Engineering. 2 (4): 783. Bibcode:1994MSMSE...2..783B. doi:10.1088/0965-0393/2/4/001. S2CID   250845929.
  20. ↑ Mazzeo, M. D.; Coveney, P. V. (2008). "HemeLB: A high performance parallel lattice-Boltzmann code for large-scale fluid flow in complex geometries". Computer Physics Communications. 178 (12): 894–914. Bibcode:2008CoPhC.178..894M. doi:10.1016/j.cpc.2008.02.013.
  21. ↑ Franco, C. A.; Jones, M. L.; Bernabeu, M. O.; Geudens, I.; Mathivet, T.; Rosa, A. (2015). "Dynamic endothelial cell rearrangements drive developmental vessel regression". PLOS Biology. 13 (4): e1002125. doi: 10.1371/journal.pbio.1002125 . PMC   4401640 . PMID   25884288.
  22. ↑ Franco, C. A.; Jones, M. L.; Bernabeu, M. O.; Vion, A. C.; Barbacena, P.; Fan, J. (2016). "Non-canonical Wnt signalling modulates the endothelial shear stress flow sensor in vascular remodelling". eLife. 5: e07727. doi: 10.7554/eLife.07727 . PMC   4798962 . PMID   26845523.
  23. ↑ Zacharoudiou, I.; McCullough, J. W. S.; Coveney, P. V. (2023). "Development and performance of a HemeLB GPU code for human-scale blood flow simulation". Computer Physics Communications. 282: 108548. arXiv: 2202.11770 . Bibcode:2023CoPhC.28208548Z. doi:10.1016/j.cpc.2022.108548. S2CID   246457935.
  24. ↑ Flekkøy, E. G.; Coveney, P. V.; De Fabritiis, G. (2000). "Foundations of dissipative particle dynamics". Phys. Rev. E. 62 (2 Pt A): 2140–2157. arXiv: cond-mat/0002174 . Bibcode:2000PhRvE..62.2140F. doi:10.1103/PhysRevE.62.2140. PMID   11088680. S2CID   46132730.
  25. ↑ Flekkøy, E. G.; Coveney, P. V. (1999). "From molecular dynamics to dissipative particle dynamics". Phys. Rev. Lett. 83 (9): 1775. arXiv: cond-mat/9908334 . Bibcode:1999PhRvL..83.1775F. doi:10.1103/PhysRevLett.83.1775. S2CID   119456909.
  26. ↑ Delgado-Buscalioni, R.; Coveney, P. V. (2003). "Continuum-particle hybrid coupling for mass, momentum, and energy transfers in unsteady fluid flow". Phys. Rev. E. 67 (4 Pt 2): 046704. arXiv: cond-mat/0302519 . Bibcode:2003PhRvE..67d6704D. doi:10.1103/PhysRevE.67.046704. PMID   12786526. S2CID   22997525.
  27. ↑ Delgado-Buscalioni, R.; Coveney, P. V. (2003). "USHER: An algorithm for particle insertion in dense fluids". J. Chem. Phys. 119 (2): 978–987. arXiv: cond-mat/0303366 . Bibcode:2003JChPh.119..978D. doi:10.1063/1.1579475. S2CID   21241469.
  28. ↑ Suter, J.; Groen, D.; Coveney, P. V. (2015). "Chemically specific multiscale modeling of clay-polymer nanocomposites reveals intercalation dynamics, tactoid self-assembly and emergent materials properties". Advanced Materials. 27 (6): 966–984. Bibcode:2015AdM....27..966S. doi:10.1002/adma.201403361. PMC   4368376 . PMID   25488829.
  29. ↑ Suter, J. L.; Sinclair, R. C.; Coveney, P. V. (2020). "Principles Governing Control of Aggregation and Dispersion of Graphene and Graphene Oxide in Polymer Melts". Adv. Mater. 32 (36): 2003213. Bibcode:2020AdM....3203213S. doi:10.1002/adma.202003213. PMID   32720366. S2CID   220840677.
  30. ↑ Wright, D.; Hall, B.; Kenway, O.; Jha, S.; Coveney, P. V. (2014). "Computing Clinically Relevant Binding Free Energies of HIV-1 Protease Inhibitors". Journal of Chemical Theory and Computation. 10 (3): 1228–1241. doi:10.1021/ct4007037. PMC   3966525 . PMID   24683369.
  31. ↑ Coveney, P. V.; Wan, S. (2016). "On the calculation of equilibrium thermodynamic properties from molecular dynamics". Phys. Chem. Chem. Phys. 18 (44): 30236–30240. Bibcode:2016PCCP...1830236C. doi: 10.1039/C6CP02349E . PMID   27165501.
  32. ↑ Coveney, P. V.; Penrose, O. (1992). "On the validity of the Brussels formalism in statistical mechanics". J. Phys. A: Math. Gen. 25 (19): 4947-4966. Bibcode:1992JPhA...25.4947C. doi:10.1088/0305-4470/25/19/011.
  33. ↑ Boghosian, B. M.; Coveney, P. V.; Wang, H. (2019). "A New Pathology in the Simulation of Chaotic Dynamical Systems on Digital Computers". Advanced Theory and Simulations. 2 (12): 1900125. doi:10.1002/adts.201900125. PMC   8427473 . PMID   34527854.
  34. ↑ "VECMA".
  35. ↑ "VECMA Toolkit".
  36. ↑ "SEAVEA Toolkit".
  37. ↑ Coveney, P. V.; Groen, D.; Hoekstra, A. G. (2021). "Reliability and reproducibility in computational science: implementing validation, verification and uncertainty quantification in silico" (PDF). Phil. Trans. R. Soc. A. 379 (2197): 20200409. Bibcode:2021RSPTA.37900409C. doi:10.1098/rsta.2020.0409. PMID   33775138. S2CID   232387102.
  38. ↑ Tranter, A.; Sofia, S.; Seeley, J.; Kaicher, M.; McClean, J.; Babbush, R; Coveney, P. V.; Mintert, F.; Love, P. J. (2015). "The Bravyi-Kitaev Transformation". International Journal of Quantum Chemistry. 115: 1431–1441. doi:10.1002/qua.24969.
  39. ↑ Weaving, T.; Ralli, A.; Kirby, W. M.; Tranter, A.; Love, P. J.; Coveney, P. V. (2023). "A stabilizer framework for Contextual Subspace VQE and the noncontextual projection ansatz". Journal of Chemical Theory and Computation. 19 (3): 808–821. doi:10.1021/acs.jctc.2c00910. PMC   9933439 . PMID   36689668. S2CID   256192386.
  40. ↑ Ralli, A.; Love, P. J.; Tranter, A.; Coveney, P. V. (2021). "Implementation of Measurement Reduction for the Variational Quantum Eigensolver". Physical Review Research. 3 (3): 033195. arXiv: 2012.02765 . Bibcode:2021PhRvR...3c3195R. doi:10.1103/PhysRevResearch.3.033195. S2CID   227305826.
  41. ↑ O'Malley, P. J. J.; Babbush, R.; Kivlichan, I. D.; Romero, J.; McClean, J. R.; Barends, R.; Kelly, J.; Roushan, P.; Tranter, A.; Ding, N.; Campbell, B.; Chen, Y.; Chen, Z.; Chiaro, B.; Dunsworth, A.; Fowler, A. G.; Jeffrey, E.; Megrant, A.; Mutus, J. Y.; Neill, C.; Quintana, C.; Sank, D.; Vainsencher, A.; Wenner, J.; White, T. C.; Coveney, P. V.; Love, P. J.; Neven, H.; Aspuru-Guzik, A.; Martinis, J. M. (2016). "Scalable Quantum Simulation of Molecular Energies". Physical Review X. 6 (3): 031007. arXiv: 1512.06860 . Bibcode:2016PhRvX...6c1007O. doi:10.1103/PhysRevX.6.031007. S2CID   4884151.
  42. ↑ "Grants on the web". gow.epsrc.ukri.org.
  43. ↑ "CORDIS | European Commission".
  44. ↑ "CORDIS | European Commission".
  45. ↑ "CORDIS | European Commission".
  46. ↑ "CORDIS | European Commission".
  47. ↑ Callaway, Ewen (2016). "How one lab challenged a grant rejection and won €5 million". Nature. 532 (7598): 159–160. Bibcode:2016Natur.532..159C. doi: 10.1038/nature.2016.19714 . PMID   27075075.
  48. ↑ "Article" (PDF). prace-ri.eu. Retrieved 13 February 2021.
  49. ↑ "About the CCPs | UK Collaborative Computational Projects". Ccp.ac.uk. Retrieved 13 February 2021.
  50. ↑ Skår, J.; Coveney, P. V. (2003). "Self-organization: the quest for the origin and evolution of structure. Proceedings of the 2002 Nobel Symposium on self-organization". Proceedings of the 2002 Nobel Symposium on Self-organization.
  51. ↑ "Scientific Infrastructure" (PDF) (Press release). www.parliament.uk. Retrieved 13 February 2021.
  52. ↑ "The books to read in 2023". Financial Times. 9 January 2023.
  53. ↑ "Virtual You review: The quest to build your digital twin". NewScientist.
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