The method is to calculate the sum up to an integer \( q \) and estimate the tail using bounds on the function \( \theta \). I thus write \begin{equation*} S = \sum_{p =2 }^{\infty} f(p) =\sum_{p \le q } f(p) + \sum_{q < p }f(p) \end{equation*} Partial summation gives \begin{equation*} S = S_q + R_q \end{equation*} with \begin{equation*} S_q =\sum_{p \le q } f(p) - \frac{\theta(q) f(q)}{\log q} \quad\text{with}\quad R_q = - \int_q^{+\infty} \theta(x) \left( \frac{f(x)}{\log x} \right)^\prime\ dx \end{equation*}

__Application__

As a concrete example, take \begin{equation*} f(x) = \frac{1} { x \log x} \end{equation*} then \begin{equation*} \left( \frac{f(x)}{\log x} \right)^\prime = - \frac{\log x + 2}{x^2 \log^3 x} \end{equation*} thus \begin{equation*} R_q = \int_q^{+\infty} \theta(x) \frac{\log x + 2}{x^2 \log^3 x}\ dx \end{equation*} I now use the following lower and upper bound on \( \theta(x) \): for all real \( x \ge 1 \) \begin{equation*} \theta_1(x) \le \theta(x) \le \theta_2(x) \end{equation*} with \begin{align*} \theta_1(x) &= A x - 5 \log x - \frac{12}{5} A x^{1/2} - \frac{5}{2\log 6}\log^2 x \\ \theta_2(x) & = \frac{6}{5} A x + \frac{5}{\log 6} \log^2 x\\ A &= \frac{1}{2} \log 2 +\frac{1}{3} \log 3 + \frac{1}{5} \log 5 -\frac{1}{30} \log 30 \end{align*} These inequalities can be obtained using similar methods as in this blog post. Therefore \begin{equation*} \int_q^{+\infty} \theta_1(x) \frac{\log x + 2}{x^2 \log^3 x}\ dx \le R_q \le \int_q^{+\infty} \theta_2(x) \frac{\log x + 2}{x^2 \log^3 x}\ dx \end{equation*} For example, if \( q = 1000 \), then \( S_q = 1.472\) (3 decimal points). Numerical integration gives \( 0.148 \le R_q \le 0.187\). Thus \( 1.620 \le S \le 1.659\). This is consistent with the exact value \( S \approx 1.637\) which can be found on page 6 in the paper "High precision computation of Hardy-Littlewood constants" of Henri Cohen.

I illustrate the formulas in Mathematica.

The code to calculate \( S_q \) |

The code to bound the error \( R_q \) |

The blue area is the approximation; the red line is the exact value. |

__Other posts about Chebyshev's mémoire__

## No comments:

## Post a Comment