Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification
We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to i...
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Abstract | We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to its parameters as is done in typical uncertainty quantification methods. We show that the functional sensitivity of the average potential energy and pressure in isothermal, isochoric MD simulations using Lennard-Jones two-body interactions can be used to accurately predict those properties for other interatomic potentials (with different functional forms) without re-running the simulations. This is demonstrated under three different thermodynamic conditions, namely a crystal at room temperature, a liquid at ambient pressure, and a high pressure liquid. The method provides accurate predictions as long as the change in potential can be reasonably described to first order and does not significantly affect the region in phase space explored by the simulation. The functional uncertainty quantification approach can be used to estimate the uncertainties associated with constitutive models used in the simulation and to correct predictions if a more accurate representation becomes available. |
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AbstractList | Journal of Computational Physics, 334, 207-220 (2017) We use functional, Fr\'echet, derivatives to quantify how thermodynamic
outputs of a molecular dynamics (MD) simulation depend on the potential used to
compute atomic interactions. Our approach quantifies the sensitivity of the
quantities of interest with respect to the input functions as opposed to its
parameters as is done in typical uncertainty quantification methods. We show
that the functional sensitivity of the average potential energy and pressure in
isothermal, isochoric MD simulations using Lennard-Jones two-body interactions
can be used to accurately predict those properties for other interatomic
potentials (with different functional forms) without re-running the
simulations. This is demonstrated under three different thermodynamic
conditions, namely a crystal at room temperature, a liquid at ambient pressure,
and a high pressure liquid. The method provides accurate predictions as long as
the change in potential can be reasonably described to first order and does not
significantly affect the region in phase space explored by the simulation. The
functional uncertainty quantification approach can be used to estimate the
uncertainties associated with constitutive models used in the simulation and to
correct predictions if a more accurate representation becomes available. We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute atomic interactions. Our approach quantifies the sensitivity of the quantities of interest with respect to the input functions as opposed to its parameters as is done in typical uncertainty quantification methods. We show that the functional sensitivity of the average potential energy and pressure in isothermal, isochoric MD simulations using Lennard-Jones two-body interactions can be used to accurately predict those properties for other interatomic potentials (with different functional forms) without re-running the simulations. This is demonstrated under three different thermodynamic conditions, namely a crystal at room temperature, a liquid at ambient pressure, and a high pressure liquid. The method provides accurate predictions as long as the change in potential can be reasonably described to first order and does not significantly affect the region in phase space explored by the simulation. The functional uncertainty quantification approach can be used to estimate the uncertainties associated with constitutive models used in the simulation and to correct predictions if a more accurate representation becomes available. |
Author | Samuel Temple Reeve Strachan, Alejandro |
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BackLink | https://doi.org/10.1016/j.jcp.2016.12.039$$DView published paper (Access to full text may be restricted) https://doi.org/10.48550/arXiv.1603.00599$$DView paper in arXiv |
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Snippet | We use functional, Fréchet, derivatives to quantify how thermodynamic outputs of a molecular dynamics (MD) simulation depend on the potential used to compute... Journal of Computational Physics, 334, 207-220 (2017) We use functional, Fr\'echet, derivatives to quantify how thermodynamic outputs of a molecular dynamics... |
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SubjectTerms | Atomic interactions Computer simulation Constitutive models Error correction Molecular dynamics Parameter uncertainty Physics - Computational Physics Potential energy Pressure Sensitivity Simulation |
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Title | Error correction in multi-fidelity molecular dynamics simulations using functional uncertainty quantification |
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