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Harmonic number

The nth harmonic number, denoted H_n, is defined as the partial sum of the first n terms of the harmonic series:
H_n = \sum_{k=1}^n \frac{1}{k} = 1 + \frac{1}{2} + \frac{1}{3} + \cdots + \frac{1}{n}. This sequence begins with H_1 = 1, H_2 = 1.5, H_3 \approx 1.833, and increases without bound as n grows, though the increments become progressively smaller.
Although the infinite harmonic series \sum_{k=1}^\infty \frac{1}{k} diverges to , the partial sums grow very slowly, approximately logarithmically—much more slowly than the linear divergence of the with ratio 1. A key asymptotic approximation for large n is H_n \approx \ln n + \gamma + \frac{1}{2n} - \frac{1}{12n^2} + \cdots, where \gamma \approx 0.57721 is the Euler-Mascheroni constant, defined as the limit \gamma = \lim_{n \to \infty} (H_n - \ln n). This approximation arises from comparisons, where H_n bounds the natural logarithm from above and below. The concept of harmonic numbers traces its origins to ancient mathematical traditions, including studies of harmonic proportions in and , with systematic development in the 17th and 18th centuries by figures like , who analyzed the series' divergence. They play a fundamental role in diverse areas of mathematics, including (e.g., connections to the prime harmonic series and functions), (e.g., in integral tests and for factorials), and (e.g., identities involving coefficients and permutations).

Definition and Fundamentals

Definition

The nth harmonic number, denoted H_n, is defined as the partial sum of the first n terms of the harmonic series: H_n = \sum_{k=1}^n \frac{1}{k} for each positive n. These numbers are named after the harmonic series, a concept rooted in the musical theory of , where the frequencies of sound waves form multiples of a fundamental tone, leading to the reciprocal proportions in the series. The explicit study of these partial sums as a distinct sequence traces back to , who in 1689 examined the harmonic series in his Tractatus de Seriebus Infinitis, later appended to his posthumously published (1713); there, Bernoulli provided a proof of the series' , highlighting the growth of the partial sums H_n. Unlike the infinite harmonic series \sum_{k=1}^\infty \frac{1}{k}, which diverges to , the harmonic numbers H_n remain finite for any finite n but increase without bound as n grows. For example, the first harmonic number is H_1 = 1, serving as the initial term from which subsequent values build additively.

Notation and Conventions

The nth harmonic number is conventionally denoted by H_n, where n is a non-negative integer, representing the partial sum \sum_{k=1}^n \frac{1}{k} of the harmonic series. This notation is standard in modern mathematical literature and emphasizes the cumulative nature of the sum up to the index n. By convention, the zeroth harmonic number is defined as H_0 = 0, corresponding to the before any terms are included. The indexing typically begins at n = [1](/page/1), where H_[1](/page/1) = [1](/page/1), and increases thereafter, with the partial explicitly written to clarify the range when necessary. Signed variants of numbers introduce alternating in the . The basic signed harmonic number is given by the partial \sum_{k=1}^n \frac{(-1)^{k+1}}{k}, which forms the alternating harmonic series and converges to \ln 2 in the limit. This form is often referred to simply as the alternating harmonic number in the literature, without a unique superscripted notation, though it relates to the for broader generalizations. For more general forms, the notation H_n^{(s)} is used to denote the generalized harmonic number \sum_{k=1}^n \frac{1}{k^s} for positive integers s \geq 1, extending the standard case where s = 1. In contemporary usage, and similar typesetting systems standardize H_n with subscript indexing, ensuring clarity and consistency across texts, while older literature occasionally employed varied symbols that have largely been supplanted by this convention.

Initial Values and Computation

The harmonic numbers for small indices can be obtained by direct summation of the reciprocals of the positive integers, providing concrete examples that illustrate their rational nature. For instance, H_1 = 1 = \frac{1}{1}, H_2 = 1 + \frac{1}{2} = \frac{3}{2}, H_3 = \frac{3}{2} + \frac{1}{3} = \frac{11}{6}, H_4 = \frac{11}{6} + \frac{1}{4} = \frac{25}{12}. The table below lists the first ten harmonic numbers in reduced fractional form, computed via successive addition:
nH_n
1$1/1
2$3/2
3$11/6
4$25/12
5$137/60
6$49/20
7$363/140
8$761/280
9 7129/2520
10 7381/2520
Each H_n is a rational number that can be represented exactly as the fraction p_n / q_n, where q_n is the of the integers \{1, 2, \dots, n\} in the unreduced form, and p_n = \sum_{k=1}^n q_n / k. This common denominator ensures precise addition of the unit fractions without loss of accuracy during . The standard recursive formula for computation is H_n = H_{n-1} + 1/n for n \geq 2, with base case H_1 = 1. This approach is efficient for sequential evaluation, but in software implementations, can introduce rounding errors for larger n due to the gradual increase in precision demands; using exact rational arithmetic libraries maintains fidelity by preserving the fractional representation.

Approximations and Asymptotics

Logarithmic Approximation

The nth harmonic number H_n admits a fundamental asymptotic approximation given by
H_n \approx \ln n + \gamma,
where \gamma \approx 0.5772156649 is the Euler-Mascheroni constant. This relation captures the leading-order growth of H_n, reflecting the divergent nature of the harmonic series in a . The constant \gamma is rigorously defined as
\gamma = \lim_{n \to \infty} (H_n - \ln n),
a limit first established by Leonhard Euler in his of harmonic progressions.
The approximation derives from integral comparisons that bound the discrete sum defining H_n. Consider the function f(x) = 1/x, which is decreasing for x > 0. By integral test remainder estimates, the sum satisfies
\int_1^{n+1} \frac{1}{x} \, dx < H_n < 1 + \int_1^n \frac{1}{x} \, dx,
or equivalently,
\ln(n+1) < H_n < 1 + \ln n.
These inequalities imply that H_n - \ln n is bounded between \ln(n+1) - \ln n = \ln(1 + 1/n) and 1, and monotonicity arguments show the difference converges to the finite limit \gamma as n \to \infty.
A straightforward error bound quantifies the accuracy of the leading approximation:
|H_n - \ln n - \gamma| < \frac{1}{2n}.
This estimate follows from the next-order term in the asymptotic expansion being approximately $1/(2n), with higher-order corrections ensuring the remainder is smaller in magnitude for sufficiently large n.

Euler-Maclaurin Expansion

The Euler-Maclaurin formula provides a systematic way to derive the asymptotic expansion of the harmonic number H_n = \sum_{k=1}^n \frac{1}{k} by approximating the sum with an integral and higher-order correction terms involving derivatives of the function f(x) = 1/x. The formula states that \sum_{k=a}^b f(k) = \int_a^b f(x) \, dx + \frac{f(a) + f(b)}{2} + \sum_{m=1}^p \frac{B_{2m}}{(2m)!} \left( f^{(2m-1)}(b) - f^{(2m-1)}(a) \right) + R_p, where B_{2m} are the , f^{(j)} denotes the j-th derivative, and R_p is the remainder term given by an integral involving the (2p)-th derivative and the B_{2p}(x). Applying this with a=1, b=n, and f(x) = 1/x, the integral yields \ln n, the endpoint correction gives \frac{1}{2} + \frac{1}{2n}, and the higher-order terms involve the derivatives f^{(2m-1)}(x) = (-1)^{2m-1} (2m-1)! \, x^{-2m}, leading to contributions proportional to B_{2m} / (2m \, n^{2m}) at the upper endpoint, while the lower endpoint and remainder contribute to the \gamma. The full asymptotic expansion is thus H_n = \ln n + \gamma + \frac{1}{2n} - \sum_{m=1}^p \frac{B_{2m}}{2m \, n^{2m}} + R_p, where the sum is over even-indexed B_2 = 1/6, B_4 = -1/30, B_6 = 1/42, and so on, and \gamma \approx 0.57721 is the . The first few terms of the expansion, up to order $1/n^2, are H_n = \ln n + \gamma + \frac{1}{2n} - \frac{1}{12 n^2} + O\left( \frac{1}{n^4} \right), since the m=1 term is -\frac{B_2}{2 n^2} = -\frac{1/6}{2 n^2} = -\frac{1}{12 n^2}. The next term for m=2 is +\frac{1}{120 n^4}, arising from B_4 < 0. The remainder R_p = O(1/n^{2p+1}) as n \to \infty for fixed p, ensuring the partial sum up to m=p approximates H_n with error decreasing as a power of $1/n; the series is asymptotic and diverges if summed to infinity, but truncation at optimal p \approx \log n yields high precision.

Error Bounds and Refinements

The harmonic number H_n satisfies the integral bounds \ln(n+1) < H_n < 1 + \ln n for all integers n > 1. These bounds arise from comparing the sum defining H_n to the areas of corresponding rectangles under the curve $1/x, providing a fundamental estimate of the slow divergence of the harmonic series. A refined approximation incorporates the Euler-Mascheroni constant \gamma \approx 0.57721, yielding H_n = \ln n + \gamma + \frac{1}{2n} - \epsilon_n, where $0 < \epsilon_n < \frac{1}{12n^2} for n \geq 1. This inequality follows from truncating the Euler-Maclaurin after the \frac{1}{2n} term, with the positive error \epsilon_n bounded above by the magnitude of the subsequent term -\frac{1}{12n^2}. Further precision can be achieved through continued fraction expansions of H_n - \ln n - \gamma. One such construction derives from the asymptotic series via a systematic transformation, yielding a continued fraction approximant like [0; 2n, -2n-1, 6n+3, \dots] that converges rapidly for large n. These expansions refine the remainder beyond polynomial terms, offering superior accuracy for intermediate n compared to partial sums of the series. Modern computational refinements often employ Stirling's series applied to the digamma function \psi(n+1) = H_n - \gamma, which provides an asymptotic expansion \psi(z) \sim \ln z - \frac{1}{2z} - \sum_{k=1}^\infty \frac{B_{2k}}{2k z^{2k}} for large |z| in |\arg z| < \pi. This series, with B_{2k}, enables high-precision bounds on the error in H_n approximations, particularly useful in numerical algorithms where truncating at a few terms suffices for machine accuracy.

Identities and Algebraic Relations

Basic Recurrence Relations

The harmonic numbers satisfy the defining recurrence relation H_n = H_{n-1} + \frac{1}{n} for integers n \geq 2, with the initial condition H_1 = 1. This relation follows immediately from the summation definition of H_n, as each successive term adds the next reciprocal to the partial sum. A key consequence of this recurrence is the difference formula H_n - H_m = \sum_{k=m+1}^n \frac{1}{k} for integers $0 \leq m < n. This identity arises by applying the basic recurrence telescopically from m+1 to n, effectively isolating the intermediate terms in the harmonic series. Setting m = 0 (where H_0 = 0 by convention) recovers the full sum representation of H_n. A related form expresses the harmonic number at a shifted index: H_{m+n} - H_m = \sum_{k=1}^n \frac{1}{m+k} for nonnegative integers m and positive integer n, which follows directly from the difference formula by substituting the appropriate bounds. These relations highlight the additive structure of harmonic numbers and facilitate computations for non-consecutive indices. Another fundamental identity involves the partial sum of the first n harmonic numbers: \sum_{k=1}^n H_k = (n+1) H_n - n. This can be verified by mathematical induction. For the base case n=1, the left side is H_1 = 1 and the right side is $2 \cdot 1 - 1 = 1. Assuming the identity holds for n, consider n+1: \sum_{k=1}^{n+1} H_k = \sum_{k=1}^n H_k + H_{n+1} = (n+1) H_n - n + H_n + \frac{1}{n+1} = (n+2) H_n - n + \frac{1}{n+1}, while the right side for n+1 is (n+2) H_{n+1} - (n+1) = (n+2) \left( H_n + \frac{1}{n+1} \right) - (n+1) = (n+2) H_n + \frac{n+2}{n+1} - n - 1 = (n+2) H_n - n + \frac{1}{n+1}, confirming equality. Alternatively, the identity can be derived using summation by parts, treating H_k as the cumulative sum and applying integration-like differencing to the reciprocals. These methods underscore the algebraic manipulability of harmonic numbers in summation contexts.

Connections to π and Other Constants

The alternating harmonic series establishes a direct connection between harmonic numbers and the constant \ln 2. The partial sum of the series \sum_{k=1}^{m} \frac{(-1)^{k+1}}{k} for m = 2n is precisely H_{2n} - H_n. As n \to \infty, this partial sum converges to \ln 2 \approx 0.693147. A significant link to \pi emerges from generalized harmonic numbers of order 2, defined as H_n^{(2)} = \sum_{k=1}^n \frac{1}{k^2}. In the limit as n \to \infty, H_n^{(2)} approaches the value of the Riemann zeta function at 2, \zeta(2) = \frac{\pi^2}{6} \approx 1.64493. This result, known as the solution to the Basel problem, was first established by Leonhard Euler in 1734 through a product expansion of the sine function and comparison with its Taylor series. The Leibniz formula for \pi further illustrates connections to harmonic numbers via series over odd denominators. The infinite series \sum_{k=1}^\infty \frac{(-1)^{k+1}}{2k-1} = \frac{\pi}{4} converges to approximately 0.785398. The corresponding positive sum over odd reciprocals up to n terms is [\sum_{k=1}^n \frac{1}{2k-1} = H_{2n} - \frac{1}{2} H_n](/page/K+S), which diverges logarithmically but provides the structural basis for the alternating version's convergence to \frac{\pi}{4}. These identities extend to polylogarithms and arctangent functions, where harmonic numbers appear in series expansions. For instance, the arctangent function \arctan x = \sum_{k=1}^\infty \frac{(-1)^{k+1} x^{2k-1}}{2k-1} at x=1 yields the Leibniz series, and finite truncations relate to incomplete harmonic sums. Such links underscore the role of harmonic numbers in bridging elementary series to transcendental constants like \pi and \ln 2.

Binomial and Integral Representations

The nth harmonic number admits the classical integral representation H_n = \int_0^1 \frac{1 - t^n}{1 - t} \, dt, originally discovered by Euler. This form arises from expressing each term 1/k as the integral \int_0^1 t^{k-1} \, dt for k = 1, 2, \dots, n, interchanging the sum and integral, and recognizing the finite geometric series \sum_{k=0}^{n-1} t^k = (1 - t^n)/(1 - t). The integral converges for all positive integers n and provides a useful tool for asymptotic analysis and connections to other special functions. An equivalent representation links H_n to the digamma function \psi(z) = \frac{d}{dz} \ln \Gamma(z), via H_n = \psi(n+1) + \gamma, where \gamma is the ; details on the digamma function appear elsewhere in this entry. The digamma function itself has integral representations, such as \psi(z+1) = -\gamma + \int_0^1 \frac{1 - t^z}{1 - t} \, dt, which directly recovers the form for H_n. A binomial coefficient representation is given by the alternating sum H_n = \sum_{k=1}^n (-1)^{k+1} \frac{1}{k} \binom{n}{k}. This identity can be derived by integrating the binomial expansion of (1 + x)^n, substituting x = -t, and relating to the geometric series underlying the integral form above. It highlights combinatorial interpretations, such as inclusion-exclusion principles in counting problems involving harmonic sums. Both the integral and binomial forms facilitate proofs of identities and approximations for H_n.

Generating Functions and Series

Ordinary Generating Functions

The ordinary generating function for the sequence of harmonic numbers \{H_n\}_{n=1}^\infty is G(x) = \sum_{n=1}^\infty H_n x^n = -\frac{\ln(1-x)}{1-x}, valid for |x| < 1. This closed form can be derived from the generating function for the reciprocal sequence, which is known to be \sum_{n=1}^\infty \frac{x^n}{n} = -\ln(1-x), \quad |x| < 1. Since each harmonic number satisfies H_n = \sum_{k=1}^n \frac{1}{k}, the generating function becomes G(x) = \sum_{n=1}^\infty \left( \sum_{k=1}^n \frac{1}{k} \right) x^n = \sum_{k=1}^\infty \frac{1}{k} \sum_{n=k}^\infty x^n. The inner sum is a geometric series: \sum_{n=k}^\infty x^n = \frac{x^k}{1-x} for |x| < 1. Substituting yields G(x) = \sum_{k=1}^\infty \frac{x^k}{k(1-x)} = \frac{1}{1-x} \sum_{k=1}^\infty \frac{x^k}{k} = \frac{-\ln(1-x)}{1-x}. The interchange of the double sum is justified by the absolute convergence of the series within the unit disk. The function G(x) is analytic throughout the open unit disk |x| < 1, where the power series converges, and the coefficient of x^n in its expansion is precisely H_n. At x = 1, G(x) exhibits a singularity arising from the logarithmic branch point of \ln(1-x) combined with the pole of $1/(1-x), leading to divergent behavior consistent with the growth of H_n \sim \ln n. Beyond the unit disk, G(x) admits analytic continuation to the Riemann surface of the logarithm, specifically to the complex plane minus the branch cut along the ray [1, \infty), preserving its multivalued nature due to the logarithm.

Exponential Generating Functions

The exponential generating function (EGF) for the harmonic numbers H_n is defined as E(x) = \sum_{n=1}^\infty H_n \frac{x^n}{n!}. A closed-form expression for this EGF is E(x) = e^x \left[ \gamma + \ln x + \Gamma(0, x) \right], where \gamma is the and \Gamma(0, x) is the upper incomplete gamma function evaluated at s=0, understood in the limiting sense as x \to 0^+. This form arises from umbral calculus techniques applied to the operational representation of harmonic numbers. An equivalent integral representation is E(x) = \int_0^1 \frac{e^x - e^{x t}}{1 - t} \, dt. This follows from the known integral representation of the harmonic numbers themselves, H_n = \int_0^1 \frac{1 - t^n}{1 - t} \, dt, by substituting into the EGF and interchanging the sum and integral (justified by uniform convergence for |x| < 1): E(x) = \sum_{n=1}^\infty \left( \int_0^1 \frac{1 - t^n}{1 - t} \, dt \right) \frac{x^n}{n!} = \int_0^1 \frac{1}{1 - t} \left( \sum_{n=1}^\infty \frac{x^n}{n!} - \sum_{n=1}^\infty \frac{(x t)^n}{n!} \right) dt = \int_0^1 \frac{e^x - e^{x t}}{1 - t} \, dt. The interchange leverages the geometric series expansion underlying the definition of H_n. Combinatorially, the coefficients H_n in the EGF relate to labeled structures, particularly through Stirling numbers of the first kind s(n,k), which count permutations of n elements with k cycles (up to sign). Specifically, H_n = \frac{1}{n!} \sum_{k=1}^n k \, |s(n,k)|, reflecting the total number of cycles across all permutations of n labeled elements divided by n!, or equivalently, the expected number of cycles in a random permutation. This connection highlights the role of the EGF in enumerative combinatorics for cycle decompositions in labeled objects, such as mappings or forests.

Integral and Series Expansions

The harmonic number H_n admits the infinite series representation H_n = \sum_{k=1}^\infty \left( \frac{1}{k} - \frac{1}{k + n} \right), which follows from the series expansion of the digamma function \psi(z + 1) = -\gamma + \sum_{k=1}^\infty \left( \frac{1}{k} - \frac{1}{k + z} \right), since H_n = \psi(n + 1) + \gamma. A well-known integral representation is Euler's formula H_n = \int_0^1 \frac{1 - t^n}{1 - t} \, dt. This arises from substituting the geometric series expansion \frac{1}{1 - t} = \sum_{k=0}^\infty t^k for |t| < 1 and integrating term by term up to the nth power. An equivalent probabilistic integral representation expresses H_n as n times the expected value of -\ln U, where U follows a (the distribution of the minimum of n i.i.d. uniform[0, 1] random variables): H_n = n \int_0^1 (-\ln u) (1 - u)^{n-1} \, du. This follows from differentiating the beta function and using the relation to the . In symmetric multiple integral form over the unit cube, it becomes H_n = \int_0^1 \cdots \int_0^1 \left( -\ln \left( \min(t_1, \dots, t_n) \right) \right) \, dt_1 \cdots dt_n, representing the expected value of -\ln (\min(T_1, \dots, T_n)) for i.i.d. uniform[0, 1] random variables T_i. The cotangent function provides a connection via its partial fraction (Fourier series) expansion \pi \cot(\pi z) = \frac{1}{z} + \sum_{k=1}^\infty \left( \frac{1}{z - k} + \frac{1}{z + k} \right), which underlies the series representation of \psi(z) and thus relates directly to harmonic numbers at positive integers. For generalized harmonic numbers H_n^{(s)} = \sum_{k=1}^n \frac{1}{k^s} with s > 1, a series expansion is H_n^{(s)} = [\zeta(s)](/page/Zeta) - \sum_{k=1}^\infty \frac{1}{(n + k)^s}, where [\zeta(s)](/page/Zeta) is the ; this follows from the tail of the zeta series. An form is H_n^{(s)} = \frac{1}{\Gamma(s)} \int_0^\infty \frac{t^{s-1} e^{-t}}{1 - e^{-t}} \left( 1 - e^{-n t} \right) \, dt. This representation generalizes the polylogarithm \mathrm{Li}_s(1) = \zeta(s) via the integral form of the Hurwitz zeta function \zeta(s, n+1) = \sum_{k=0}^\infty \frac{1}{(n + 1 + k)^s}.

Arithmetic and Analytic Properties

Growth and Monotonicity

The harmonic numbers H_n form a strictly increasing sequence, as H_{n+1} - H_n = \frac{1}{n+1} > 0 for all n \ge 1. This sequence diverges to , but its growth is logarithmic: H_n \sim \ln n + \gamma, where \gamma \approx 0.5772156649 is the Euler-Mascheroni constant; moreover, H_n = o(n^\epsilon) for any \epsilon > 0. The sequence is strictly concave down, since the second differences satisfy \Delta^2 H_n = -\frac{1}{n(n+1)} < 0 for n \ge 2. A useful set of bounds is given by \frac{1}{2(n+1)} < H_n - \ln n - \gamma < \frac{1}{2n} for n \ge 1, which sharpen the asymptotic approximation and confirm the slow, logarithmic growth.

Irrationality and Transcendence

The harmonic number H_n = \sum_{k=1}^n \frac{1}{k} is rational for every positive integer n, as it is a finite sum of rational numbers. In particular, H_1 = 1 is an integer, but H_n is not an integer for any integer n \geq 2. To see this, write H_n = \frac{a}{b} in lowest terms, where b > 1. The denominator b is the least common multiple of \{1, 2, \dots, n\} divided by the greatest common divisor of the numerator and that lcm after clearing denominators. By Bertrand's postulate, there exists a prime p with n/2 < p \leq n for n > 1. The p-adic valuation satisfies v_p(H_n) = -1, since the term $1/p contributes -1 to the valuation, while all other terms $1/k for k \neq p have v_p(1/k) \geq 0 (no higher multiples of p appear in the denominators up to n), and the numerator does not introduce a factor of p to cancel it. Thus, p divides the denominator but not the numerator, so H_n is not an integer. This result was first proved by Theisinger in 1915. Although each H_n is algebraic (being rational), questions of transcendence arise in connection with the asymptotic behavior H_n = \ln n + \gamma + O(1/n), where \gamma is the Euler-Mascheroni constant defined as \gamma = \lim_{n \to \infty} (H_n - \ln n). The of \gamma remains an ; if \gamma = p/q in lowest terms, then q > 10^{244663}. Various criteria for have been developed, often involving integrals or linear forms in \gamma, but none conclusively prove it. The transcendence of \gamma is also unresolved, but it is known that \gamma and e^\gamma cannot both be algebraic. By the Lindemann-Weierstrass theorem, if \gamma were algebraic and nonzero, then e^\gamma would be transcendental. Thus, assuming the open irrationality of \gamma, its would follow if e^\gamma were algebraic, but the status of e^\gamma itself is open: if rational, its denominator exceeds $10^{15000}. The quantity e^\gamma appears in , such as in the Mertens product theorem for primes, \prod_{p \leq x} (1 - 1/p)^{-1} \sim e^\gamma \ln x.

Finite Differences and Summation

The forward operator \Delta, defined by \Delta f(n) = f(n+1) - f(n), applied to the harmonic number H_n yields \Delta H_n = \frac{1}{n+1}. This follows from the defining recurrence H_{n+1} = H_n + \frac{1}{n+1}. Higher-order forward differences \Delta^k H_n can be computed recursively by repeated application of \Delta. The closed form for the k-th order is \Delta^k H_n = (-1)^{k-1} \frac{(k-1)!}{(n+1)(n+2)\cdots(n+k)}, which expresses the k-th difference in terms of the rising factorial (n+1)^{(k)}. This formula emerges from the role of H_n as the antidifference (discrete integral) of \frac{1}{n} in finite . Finite differences of harmonic numbers are connected to through combinatorial identities. In particular, the unsigned Stirling numbers of the first kind [n \ k], which count the number of permutations of n elements with k cycles, satisfy H_n = \frac{[n+1 \ 2]}{n!}, where [n+1 \ 2] is the Stirling number of the first kind for n+1 elements and 2 cycles. This relation provides a combinatorial of H_n as the average number of cycles in certain structures. identities involving harmonic numbers often arise from double summation or . A fundamental example is the sum of the first n harmonic numbers: \sum_{k=1}^n H_k = (n+1) H_n - n. This can be verified by induction or by expanding H_k = \sum_{j=1}^k \frac{1}{j}, interchanging the order of summation, and simplifying the resulting expression \sum_{j=1}^n \frac{n-j+1}{j} = (n+1) H_n - n . Telescoping sums using harmonic differences are useful for evaluating series. For instance, the difference H_{m+n} - H_m = \sum_{k=1}^n \frac{1}{m+k} allows summation over such terms to yield expressions like \sum_{m=1}^n (H_{m+n} - H_m) = \sum_{k=1}^n \frac{n-k+1}{k} H_n or related forms, though specific cases depend on the indices. These identities highlight the relational arithmetic properties of harmonic numbers in finite sums.

Applications

In Combinatorics and Number Theory

Harmonic numbers play a prominent role in , particularly in analyzing expected values for collection processes. In the , where one seeks to acquire all n distinct coupons through random draws with replacement, the expected number of draws required to complete the collection is exactly n H_n, where H_n is the nth harmonic number. This result arises from decomposing the process into stages, where the expected time to obtain a new coupon after having k distinct ones is n/(n-k), leading to the sum n ∑_{k=1}^n 1/k = n H_n. In , harmonic numbers connect to approximations of growth via 's formula. Specifically, the natural logarithm of n! admits the approximation ln(n!) ≈ n H_n - n + (1/2) ln(2πn), which refines the classical Stirling series by incorporating the harmonic sum's logarithmic behavior, H_n ≈ ln n + γ, where γ is the Euler-Mascheroni constant. This form highlights how harmonic numbers capture the cumulative reciprocal contributions in the product defining n!, aiding in asymptotic analyses of counts and related structures. In , differences of harmonic numbers provide expansions of certain rationals, as H_n - H_m = ∑{k=m+1}^n 1/k is a of distinct fractions representing the rational ∑{k=m+1}^n 1/k. The for the number of integer partitions into distinct parts is ∏_{k=1}^∞ (1 + x^k) = ∑ q(n) x^n, where q(n) counts such partitions.

In and Probability

In , the partial s of the harmonic series, denoted H_n = \sum_{k=1}^n \frac{1}{k}, play a key role in assessing the of infinite series through comparison and tests. The of the harmonic series itself is established via the test, where the \int_1^\infty \frac{1}{x} \, dx diverges logarithmically, implying that \sum_{k=1}^\infty \frac{1}{k} diverges, with H_n providing the partial s that grow without bound. This test extends to p-series \sum_{k=1}^\infty \frac{1}{k^p}, which converge for p > 1 and diverge for p \leq 1, as the \int_1^\infty \frac{1}{x^p} \, dx converges only when p > 1; the harmonic series corresponds to the boundary case p=1. Remainder estimates for convergent series often incorporate H_n to quantify errors. For the integral test applied to a decreasing positive f, the R_n = \sum_{k=n+1}^\infty f(k) satisfies \int_{n+1}^\infty f(x) \, dx \leq R_n \leq f(n+1) + \int_{n+1}^\infty f(x) \, dx, and for series like the p-series with p > 1, this yields R_n < \frac{1}{(p-1)n^{p-1}}. In the context of the alternating harmonic series, sharp bounds on the involve expressions related to H_n, such as |\sum_{k=n+1}^\infty \frac{(-1)^k}{k}| < \frac{1}{2(n+1)}, with more precise estimates linking to the digamma function but bounded using harmonic partial sums. Additionally, H_n aids in bounding the convergence of series like \sum_{k=2}^\infty \frac{1}{k \ln k}, which diverges by the integral test since \int_2^\infty \frac{1}{x \ln x} \, dx = \ln(\ln x) \big|_2^\infty = \infty, and comparisons show the partial sums grow like \ln(\ln n), analogous to the logarithmic growth of H_n. In Dirichlet series, harmonic numbers appear in the analytic continuation and evaluation of functions like the Dirichlet eta function, defined as \eta(s) = \sum_{k=1}^\infty \frac{(-1)^{k+1}}{k^s} = (1 - 2^{1-s}) \zeta(s) for \Re(s) > 0, where \zeta(s) is the . The partial sums of the alternating generalized harmonic series \sum_{k=1}^n \frac{(-1)^{k+1}}{k^s} approach \eta(s) as n \to \infty, providing a connection between finite harmonic sums and the eta function's role in . In , H_n arises as the in several stochastic processes, particularly uniform sampling problems. The yields E[T] = n H_n, reflecting the harmonic sum over the geometric waiting times for each new . This scales as n \ln n + \gamma n + O(1), highlighting the inherent to H_n. Similar applications occur in random walks on graphs, where the expected cover time or hitting times can involve harmonic sums for complete graphs or trees, though the coupon collector provides the canonical example.

In Computer Science and Algorithms

In , harmonic numbers often arise in the analysis of and tasks. A straightforward method for computing the nth harmonic number H_n involves precomputing a array, where an array H is initialized with H_0 = 0, and each subsequent entry is updated as H_i = H_{i-1} + \frac{1}{i} for i = 1 to n. This approach requires O(n) time and space for precomputation, enabling constant-time retrieval of any H_k for k \leq n thereafter, which is particularly useful in dynamic programming or iterative algorithms needing cumulative sums of reciprocals. For large n, direct summation can be inefficient or imprecise due to floating-point limitations, prompting the use of approximations derived from the Euler-Maclaurin formula. The leading-order approximation H_n \approx \ln n + \gamma, where \gamma \approx 0.57721 is the Euler-Mascheroni constant, provides O(1) evaluation with relative error O(1/n), sufficient for many analytical purposes; higher accuracy can be achieved by including terms like \frac{1}{2n} - \frac{1}{12n^2}. To mitigate accumulation of rounding errors in exact for moderate n, compensated algorithms such as Kahan summation are employed, which track and correct lost low-order bits, bounding the error by O(n u) where u is the unit roundoff, rather than the worse O(n^2 u) of naive —essential for numerical simulations or scientific computing involving harmonic series. Harmonic numbers feature prominently in the amortized analysis of classic data structures and sorting algorithms. In the union-find data structure with union-by-rank and path compression, the amortized time per operation is O(\alpha(n)), where \alpha(n) is the inverse Ackermann function; this bound emerges from potential functions incorporating sums over tree ranks and compression levels, ensuring near-constant performance despite worst-case paths up to \log n. Similarly, in randomized quicksort, the expected number of comparisons to sort n elements is exactly $2(n+1)H_n - 4n, which asymptotically simplifies to approximately $2n \ln n since H_n \sim \ln n + \gamma, highlighting the algorithm's average-case efficiency over O(n^2) worst-case behavior. In data science and machine learning, harmonic numbers support probabilistic modeling and optimization. For entropy estimation of discrete random variables from samples, an estimator leveraging the harmonic number function H_k for the k-th order statistic achieves asymptotic efficiency under tail conditions p_j = o(j^{-2}), offering strong mean squared error bounds and simplicity over plug-in or Miller-Madow methods, thus facilitating inference in high-cardinality settings like text analysis. In regularization for sparse models, harmonic regularization employs a penalty P(\beta_j) = \frac{|\beta_j|^a}{a} with $1 < a < 2 to approximate nonconvex \ell_q norms ($1/2 < q < 1), enhancing variable selection in Cox proportional hazards models for survival analysis on microarray data by promoting exact zeros while avoiding the bias of \ell_1 penalties like Lasso.

Generalizations

Generalized Harmonic Numbers

The generalized harmonic numbers of order s, denoted H_n^{(s)}, are defined for positive integer n and real s > 0 by the finite sum H_n^{(s)} = \sum_{k=1}^n k^{-s}. This generalizes the standard harmonic numbers, as H_n^{(1)} = H_n. The numbers satisfy the basic recurrence H_n^{(s)} = H_{n-1}^{(s)} + n^{-s}, with initial condition H_0^{(s)} = 0. For s > 1, the sequence H_n^{(s)} is strictly increasing in n and converges to the \zeta(s) = \sum_{k=1}^\infty k^{-s} as n \to \infty. For fixed n, H_n^{(s)} is monotonically decreasing in s, as each summand k^{-s} (for k \geq 2) decreases with increasing s, while the k=1 term remains constant at 1. A notable special case occurs for s = 2, where H_n^{(2)} is known as the quadratic harmonic numbers, and the infinite sum yields \zeta(2) = \pi^2 / 6, as established by Euler in his solution to the . These partial sums appear in various analytic contexts, including approximations to the and series evaluations in .

Hyperharmonic and Multiple Sums

Hyperharmonic numbers of order r, denoted H_n^{(r)}, extend the concept of ordinary harmonic numbers through iterated . They are defined recursively for positive integers n and r \geq 1 by H_n^{(1)} = H_n = \sum_{k=1}^n \frac{1}{k} and H_n^{(r)} = \sum_{k=1}^n H_k^{(r-1)} for r > 1. This construction yields a where each higher order represents the cumulative sum of the previous order, with the base case being the standard harmonic number. For example, the second-order hyperharmonic number is H_n^{(2)} = \sum_{k=1}^n H_k. The recursive nature allows for efficient computation via the relation H_n^{(r)} = H_{n-1}^{(r)} + H_n^{(r-1)} with initial conditions H_0^{(r)} = 0 for all r. An explicit closed-form expression, independent of recursion, expresses hyperharmonic numbers in terms of binomial coefficients and ordinary harmonics: H_n^{(r)} = \binom{n + r - 1}{r - 1} \left( H_{n + r - 1} - H_{r - 1} \right), where H_0 = 0. This formula facilitates direct evaluation and reveals connections to binomial expansions, originating from combinatorial interpretations of repeated summations. For large n and fixed r \geq 2, the asymptotic behavior of H_n^{(r)} is dominated by a logarithmic term scaled by a in n: H_n^{(r)} \sim \frac{n^{r-1} \ln n}{(r-1)!}. Higher-order terms in the expansion can be derived using Euler-Maclaurin summation, incorporating constants like the Euler-Mascheroni constant \gamma, but the leading term captures the growth rate, which is superlinear for r > 2 and reflects the iterated integration underlying the sums. Multiple sums generalize harmonic numbers further by considering products over strictly increasing indices. The k-fold multiple harmonic sum up to n is defined as S_{n,k} = \sum_{1 \leq i_1 < i_2 < \cdots < i_k \leq n} \frac{1}{i_1 i_2 \cdots i_k}. This represents the sum of reciprocals of all strictly ordered k-tuples within [1, n], and for k=1, it reduces to the ordinary harmonic number H_n. These sums form the finite analogs of multiple zeta values (MZVs), where the infinite limit n \to \infty yields \zeta(1,1,\dots,1) with k ones, though this diverges; regularized MZVs provide analytic continuations for deeper study. Hyperharmonic numbers relate to multiple sums via shuffling relations, as H_n^{(r)} can be expressed as a linear combination of S_{n,k} for weights summing to r, highlighting their role in evaluating Euler sums and polylogarithms.

Multiplication and Composition Formulas

Multiplication formulas for harmonic numbers arise from the multiplication theorems for the digamma function, leveraging the relation H_n = \psi(n+1) + \gamma, where \psi is the digamma function and \gamma is the Euler-Mascheroni constant. These formulas express harmonic numbers at multiples of the argument in terms of sums involving shifted harmonic numbers at fractional offsets. The duplication formula, corresponding to the case m = 2, states that H_{2n} = \frac{1}{2} \left( H_n + H_{n - \frac{1}{2}} \right) + \ln 2, where H_{n - 1/2} denotes the generalized harmonic number H_x = \psi(x+1) + \gamma evaluated at the half-integer x = n - 1/2. This relation connects the harmonic number at even indices to both an integer-indexed harmonic number and a half-integer counterpart, facilitating recursive computations and approximations for large n. For the general case with positive integer m, the multiplication theorem for the digamma function yields H_{mx} = \frac{1}{m} \sum_{k=0}^{m-1} H_{x + \frac{k}{m}} + \ln m, adjusted for the precise indexing via the digamma relation \psi(mz) = \ln m + \frac{1}{m} \sum_{k=0}^{m-1} \psi\left(z + \frac{k}{m}\right). When x = n is a positive integer, this expresses H_{mn} as an average of generalized harmonic numbers at fractional shifts plus a logarithmic term, providing a structured way to relate harmonic numbers at scaled indices. For example, with m=3, it involves terms like H_{n + 1/3} and H_{n + 2/3}, defined through the digamma extension. This theorem generalizes the duplication case and is fundamental for deriving identities in series expansions and asymptotic analyses. Composition formulas for harmonic numbers typically address linear scalings of the index, such as H_{an + b}, which can be decomposed using the multiplication theorem for suitable a. For integer shifts, a basic composition identity is H_{n+m} = H_n + \sum_{k=1}^m \frac{1}{n+k}, where the sum represents the incremental contribution from the additional terms; this sum equals H_{n+m} - H_n, offering a direct recursive structure for computation. More advanced compositions, like those for H_{mn}, reduce to sums of block contributions: H_{mn} = \sum_{j=0}^{m-1} \sum_{k=1}^n \frac{1}{jn + k} = \sum_{j=0}^{m-1} (H_{ (j+1)n } - H_{jn}), which telescopes but highlights the block-wise additive nature. These relations are essential in combinatorial enumerations and algorithmic efficiency analyses. For products of harmonic numbers, such as H_n H_m, explicit expansions involve double sums that can be reorganized using integral representations or higher-order harmonics. More generally, products like H_n^{(s)} H_m^{(t)} for generalized harmonics expand as \sum_{i=1}^n \sum_{j=1}^m \frac{1}{i^s j^t}. These expansions are crucial in evaluating multiple zeta values and polylogarithms.

Extensions to Real and Complex Domains

Digamma Function Representation

The digamma function, defined as the logarithmic derivative of the gamma function \psi(z) = \frac{d}{dz} \ln \Gamma(z) = \frac{\Gamma'(z)}{\Gamma(z)}, provides an analytic representation for the nth harmonic number H_n when evaluated at positive integers. Specifically, for positive integers n, H_n = \psi(n+1) + \gamma, where \gamma is the Euler-Mascheroni constant, approximately 0.57721. This relation equivalently expresses the digamma function at integers as \psi(n+1) = -\gamma + H_n.[62] This connection arises from the functional equation of the , \Gamma(z+1) = z \Gamma(z). Taking the logarithmic derivative of both sides yields the recurrence relation for the : \psi(z+1) = \psi(z) + \frac{1}{z}. Iterating this recurrence from z=1 to z=n gives \psi(n+1) = \psi(1) + \sum_{k=1}^n \frac{1}{k}. Since \psi(1) = -\gamma, substituting this value directly produces the representation \psi(n+1) = -\gamma + H_n. The link to the digamma function endows harmonic numbers with properties inherited from the analytic behavior of \psi(z). For instance, the increasing nature of \psi(z) for real z > 0, as its derivative (the ) is positive, implies that H_n is strictly increasing in n. This monotonicity aligns with the partial sums definition of H_n, reinforcing its role in extending harmonic sums to broader analytic contexts.

Asymptotic Behavior for Non-Integers

The generalized harmonic number H_x, defined for real x > 0 via the relation H_x = \psi(x+1) + \gamma where \psi is the and \gamma is the Euler-Mascheroni constant, possesses the H_x \sim \ln x + \gamma + \frac{1}{2x} - \frac{1}{12x^2} + \frac{1}{120x^4} - \cdots as x \to \infty. This series arises from the Euler-Maclaurin formula applied to the integral representation of H_x or, equivalently, from the asymptotic behavior of the digamma function. The digamma function admits the asymptotic expansion \psi(z) \sim \ln z - \frac{1}{2z} - \sum_{k=1}^\infty \frac{B_{2k}}{2k z^{2k}} as z \to \infty in the sector |\ph z| \leq \pi - \delta for any fixed \delta > 0, where B_{2k} are the numbers. Substituting z = x + 1 and expanding the leading terms in powers of $1/x produces the series for H_x. The expansion is divergent but yields accurate approximations when truncated appropriately, with the first few terms capturing the dominant logarithmic growth and subsequent power-law corrections. For complex x with \Re x > 0, the asymptotic expansion of H_x mirrors that for real arguments, holding uniformly in sectors where | \arg(x+1) | \leq \pi - \delta. The function's principal introduces a along (-\infty, 0], so the expansion applies away from regions where x + 1 approaches this cut, ensuring of H_x in the right half-plane. The remainder after m terms in the series is O(1/x^{2m+1}), with uniformity in the angular sectors excluding a fixed neighborhood of the negative real axis. This uniformity facilitates applications in and numerical computations for non-integer orders.

Special Values and Zeta Connections

The generalized harmonic number H_x, defined for non-integer x via the relation H_x = \psi(x+1) + \gamma where \psi is the digamma function and \gamma is the Euler-Mascheroni constant, admits closed-form expressions at certain rational points through known special values of \psi. For example, at x = 1/2, \psi(3/2) = \psi(1/2) + 2 = -\gamma - 2\ln 2 + 2, yielding H_{1/2} = 2 - 2\ln 2. Similarly, for negative half-integers, the reflection formula \psi(1 - z) - \psi(z) = \pi \cot(\pi z) facilitates computation; at x = -1/2, H_{-1/2} = \psi(1/2) + \gamma = -2\ln 2. These values highlight how harmonic numbers at fractional arguments connect elementary constants like \ln 2 and \gamma without requiring infinite series. A key link to the arises in the generalized setting, where the s-order harmonic number H_x^{(s)} = \sum_{k=1}^{\lfloor x \rfloor} k^{-s} + \frac{(\{x\})^{1-s}}{1-s} for non- x and \operatorname{Re}(s) > 1, but more precisely via the \zeta(s, a) = \sum_{k=0}^\infty (k + a)^{-s}, satisfying H_n^{(s)} = \zeta(s) - \zeta(s, n+1) for positive n. As n \to \infty with \operatorname{Re}(s) > 1, H_n^{(s)} \to \zeta(s), reflecting the partial sum approximation to the zeta series. For s = 1, the yields the defining relation H_x = \lim_{s \to 1^+} \left[ \zeta(s) - \zeta(s, x+1) \right], tying the divergent harmonic series to the pole of \zeta(s) at s=1. The Euler-Mascheroni constant \gamma emerges as a special case of this zeta connection: \gamma = \lim_{s \to 1^+} \left( \zeta(s) - \frac{1}{s-1} \right), which aligns with the digamma representation since \psi(1) = -\gamma and the Laurent expansion of \zeta(s, a) near s=1 involves -\psi(a). This limit underscores the harmonic number's role in regularizing the zeta function's singularity, with explicit ties to special values like H_{1/2} incorporating \gamma to balance logarithmic terms.

Fractional and Negative Arguments

The generalized harmonic number H_x for fractional x = m/n in lowest terms can be evaluated using the multiplication formula for the , which relates \psi(nz) to sums of digamma values at shifted arguments. Specifically, the formula states that \psi(nz) = \frac{1}{n} \sum_{k=0}^{n-1} \psi\left(z + \frac{k}{n}\right) + \ln n for positive integer n. This allows computation of \psi(m/n) by solving the resulting linear system, often incorporating known values such as \psi(1) = -\gamma. Since H_x = \psi(x+1) + \gamma, where \gamma is the Euler-Mascheroni constant, this yields explicit expressions for fractional harmonic numbers. For instance, the duplication formula (the case n=2) gives \psi(2z) = \frac{1}{2} \psi(z) + \frac{1}{2} \psi\left(z + \frac{1}{2}\right) + \ln 2, which can be rearranged to find values at half-integers. For negative arguments, H_x is defined via analytic continuation of the digamma representation, which is meromorphic with simple poles at non-positive integers. Thus, H_0 = \psi(1) + \gamma = 0, while H_{-n} for positive integers n \geq 1 is undefined due to poles in \psi(1 - n). For non-integer negative x, values are finite and computable using functional relations. The reflection formula for the , \psi(1 - x) - \psi(x) = \pi \cot(\pi x), facilitates evaluation near the negative real axis by reflecting to the positive domain. In terms of harmonic numbers, this implies H_{-x} = H_{x-1} + \pi \cot(\pi x) for non-integer x > 0, providing a direct relation between positive and negative arguments. Representative examples illustrate these evaluations. For the fractional case x = 1/2, H_{1/2} = 2 - 2 \ln 2, derived from \psi(3/2) = -\gamma + 2 - 2 \ln 2 using the duplication formula and known \psi(1/2) = -\gamma - 2 \ln 2. For the negative non-integer x = -1/2, H_{-1/2} = -2 \ln 2, obtained directly from \psi(1/2) + \gamma = -2 \ln 2. These values highlight the role of transcendental constants like \ln 2 in explicit forms. More generally, Gauss's digamma theorem provides closed forms for rational arguments: \psi\left(\frac{p}{q}\right) = -\gamma - \ln(2q) - \frac{\pi}{2} \cot\left(\frac{\pi p}{q}\right) + 2 \sum_{k=1}^{\lfloor (q-1)/2 \rfloor} \cos\left(\frac{2 \pi p k}{q}\right) \ln \sin\left(\frac{\pi k}{q}\right), enabling H_{p/q} for any rational fraction.

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