saving work in Shanks
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@ -1633,32 +1633,31 @@ that can be used to extract further information about the exact result.
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The Shanks transformation presents one approach for extracting this information
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and accelerating the rate of convergence of a sequence.\cite{Shanks_1955,BenderBook}
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\titou{T2: $N$ is defined as the number of electrons. Maybe we should use $n$ instead?}
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Consider the partial sums
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$S_N = \sum_{k=0}^{N} a_k$
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$S_n = \sum_{k=0}^{n} s_k$
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defined from the truncated summation of an infinite series
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$ S = \sum_{k=0}^{\infty} a_k$.
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$S = \sum_{k=0}^{\infty} s_k$.
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If the series converges, then the partial sums will tend to the exact result
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\begin{equation}
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\lim_{N\rightarrow \infty} S_N = S.
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\lim_{n \to \infty} S_n = S.
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\end{equation}
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The Shanks transformation attempts to generate increasingly accurate estimates of this
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limit by defining a new series as
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\begin{equation}
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T(S_N) = \frac{S_{N+1} S_{N-1} - S_{N}^2}{S_{N+1} + S_{N-1} - 2 S_{N}}.
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T(S_n) = \frac{S_{n+1} S_{n-1} - S_{n}^2}{S_{n+1} + S_{n-1} - 2 S_{n}}.
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\end{equation}
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This series can converge faster than the original partial sums and can thus provide greater
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accuracy using only the first few terms in the series.
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However, it is designed to accelerate exponentially converging partial sums with
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However, it is designed to accelerate \titou{exponentially?} converging partial sums with
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the approximate form
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\begin{equation}
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S_N \approx S + a\,b^N.
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S_n \approx S + \alpha\,\beta^n.
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\end{equation}
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Furthermore, while this transformation can accelerate the convergence of a series,
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there is no guarantee that this acceleration will be fast enough to significantly
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improve the accuracy of low-order approximations.
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\hugh{To the best of our knowledge, the Shanks transformation has never previously been applied
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To the best of our knowledge, the Shanks transformation has never previously been applied
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to the acceleration of the MP series.
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We have therefore applied it to the convergent Taylor series, Pad\'e approximants, and quadratic
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approximants for RMP and UMP in the symmetric Hubbard dimer.
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@ -1670,14 +1669,12 @@ can significantly improve the estimate of the energy using low-order perturbatio
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as shown in Table~\ref{tab:RMP_shank}.
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Even though the RMP series diverges at $U/t = 4.5$, the combination
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of diagonal Pad\'e approximants with the Shanks transformation reduces the absolute error of
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the best energy estimate to 0.002\,\%.}
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the best energy estimate to 0.002\,\%.
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\begin{table}[th]
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\caption{
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\hugh{%
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Acceleration of the diagonal Pad\'e approximant sequence for the RMP energy
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using the Shanks transformation.
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}
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\label{tab:RMP_shank}}
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\begin{ruledtabular}
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\begin{tabular}{lcccc}
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