uq
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uq [2018/11/30 17:01] – slongbottom | uq [2018/12/03 11:08] – [Hessian Bracketing Algorithm] slongbottom | ||
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where $\lambda_j$ are the hessian eigenvalues, | where $\lambda_j$ are the hessian eigenvalues, | ||
- | The MCMC algorithm samples potentials from the distribution at a temperature, | + | The MCMC algorithm samples potentials from the distribution at a temperature, |
+ | ===== Hessian Bracketing Algorithm ===== | ||
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+ | **Only use this if you know what you are doing! ** | ||
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+ | If '' | ||
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+ | If the landscape at this scale is not harmonic, the eigenvalues of the hessian will be negative. In this case a reduced sampling temperature may be required and the user should think about improving the reference data being fit to, as well as the suitability and possible limitations of the potential model being used. | ||
===== Parameters ===== | ===== Parameters ===== | ||
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^ **hess_pert** | float | 0.00001 | | ^ **hess_pert** | float | 0.00001 | | ||
- | | Percentage parameter perturbation in Hessian finite difference calculation. ||| | + | | Percentage parameter perturbation in Hessian finite difference calculation. |
|<100% 33% 33% 33%>| | |<100% 33% 33% 33%>| |