Euler–Maclaurin formula
In mathematics, the Euler–Maclaurin formula is a formula for the difference between an integral and a closely related sum. It can be used to approximate integrals by finite sums, or conversely to evaluate finite sums and infinite series using integrals and the machinery of calculus. For example, many asymptotic expansions are derived from the formula, and Faulhaber's formula for the sum of powers is an immediate consequence. The formula was discovered independently by Leonhard Euler and Colin Maclaurin around 1735. Euler needed it to compute slowly converging infinite series while Maclaurin used it to calculate  integrals. It was later generalized to Darboux's formula. The formula. If and are natural numbers and is a real or complex valued continuous function for real numbers in the interval , then the integral formula_1 can be approximated by the sum (or vice versa) formula_2 (see rectangle method). The Euler–Maclaurin formula provides expressions for the difference between the sum and the integral in terms of the higher derivatives evaluated at the endpoints of the interval, that is to say and . Explicitly, for a positive integer and a function that is times continuously differentiable on the interval , we have formula_3  where is the th Bernoulli number (with ) and is an error term which depends on , , , and and is usually small for suitable values of . The formula is often written with the subscript taking only even values, since the odd Bernoulli numbers are zero except for . In this case we have formula_4 or alternatively formula_5 The remainder term. The remainder term arises because the integral is usually not exactly equal to the sum. The formula may be derived by applying repeated integration by parts to successive intervals for . The boundary terms in these integrations lead to the main terms of the  formula, and the leftover integrals form the remainder term. The remainder term has an exact expression in terms of the periodized Bernoulli functions . The Bernoulli polynomials may be defined recursively by and, for , formula_6 The periodized Bernoulli functions are defined as formula_7 where denotes the largest integer less than or equal to , so that always lies in the interval . With this notation, the remainder term equals formula_8 When , it can be shown that formula_9 where denotes the Riemann zeta function; one approach to prove this inequality is to obtain the Fourier series for the polynomials . The bound is achieved for  even when is zero. The term may be omitted for odd but the proof in this case is more complex (see Lehmer). Using this inequality, the size of the remainder term can be estimated as formula_10 Low-order cases. The Bernoulli numbers from to are . Therefore the low-order cases of the Euler–Maclaurin formula are: formula_11 Applications. The Basel problem. The Basel problem is to determine the sum formula_12 Euler computed this sum to 20 decimal places with only a few terms of the Euler–Maclaurin formula in 1735. This probably convinced him that the sum equals , which he  proved in the same year. Sums involving a polynomial. If is a polynomial and is big enough, then the remainder term vanishes. For instance, if , we can choose to obtain, after simplification, formula_13 Approximation of integrals. The formula provides a means of approximating a finite integral. Let be the endpoints of the interval of integration. Fix , the number of points to use in the approximation, and denote the corresponding step size by . Set , so that and . Then: formula_14 This may be viewed as an extension of the trapezoid rule by the inclusion of correction terms. Note that this asymptotic expansion  is usually not convergent; there is some , depending upon and , such that the terms past order increase rapidly. Thus, the remainder term generally demands close attention. The Euler–Maclaurin formula is also used for detailed error analysis in numerical quadrature. It explains the superior performance of the trapezoidal rule on smooth periodic functions and is used in certain extrapolation methods. Clenshaw–Curtis quadrature is essentially a change of variables to cast an arbitrary integral in terms of integrals of periodic functions where the Euler–Maclaurin approach is very accurate (in that particular case the Euler–Maclaurin formula takes the form  of a discrete cosine transform). This technique is known as a periodizing transformation. Asymptotic expansion of sums. In the context of computing asymptotic expansions of sums and series, usually the most useful form of the Euler–Maclaurin formula is formula_15 where and are integers. Often the expansion remains valid even after taking the limits or or both. In many cases the integral on the right-hand side can be evaluated in closed form in terms of elementary functions even though the sum on the left-hand side cannot. Then all the terms in the asymptotic series can be expressed  in terms of elementary functions. For example, formula_16 Here the left-hand side is equal to , namely the first-order polygamma function defined by the gamma function is equal to when is a positive integer. This results in an asymptotic expansion for . That expansion, in turn, serves as the starting point for one of the derivations of precise error estimates for Stirling's approximation of the factorial function. Examples. If is an integer greater than 1 we have: formula_18 Collecting the constants into a value of the Riemann zeta function, we can write an asymptotic expansion: formula_19 For equal to  2 this simplifies to formula_20 or formula_21 When , the corresponding technique gives an asymptotic expansion for the harmonic numbers: formula_22 where is the Euler–Mascheroni constant. Proofs. Derivation by mathematical induction. We outline the argument given in Apostol. The Bernoulli polynomials and the periodic Bernoulli functions for were introduced above. The first several Bernoulli polynomials are formula_23 The values are the Bernoulli numbers . Notice that for we have formula_24 and for , formula_25 The functions agree with the Bernoulli polynomials on the interval and are periodic with period 1. Furthermore, except when , they are also continuous. Thus, formula_26 Let be an  integer, and consider the integral formula_27 where formula_28 Integrating by parts, we get formula_29 Using , , and summing the above from to , we get formula_30 Adding to both sides and rearranging, we have formula_31 This is the case of the summation formula. To continue the induction, we apply integration by parts to the error term: formula_32 where formula_33 The result of integrating by parts is formula_34 Summing from to and substituting this for the lower order error term results in the case of the formula, formula_35 This process can be iterated. In this way we get a proof of the Euler –Maclaurin summation formula which can be formalized by mathematical induction, in which the induction step relies on integration by parts and on identities for periodic Bernoulli functions.