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Geometric progression

A geometric progression, also known as a , is a sequence of non-zero numbers in which each after the first is obtained by multiplying the preceding by a fixed, non-zero called the . The general form of such a progression is a, ar, ar^2, ar^3, \dots , where a is the first and r is the . The nth is given by the formula a_n = a r^{n-1}. The sum of the first n terms of a finite geometric progression, denoted S_n, is calculated using the formula S_n = a \frac{1 - r^n}{1 - r} for r \neq 1. For an infinite geometric progression, the sum converges to S = \frac{a}{1 - r} the of the common ratio satisfies |r| < 1; otherwise, the series diverges. These summation formulas arise from algebraic manipulation of the series terms and are fundamental in analyzing convergence. Geometric progressions have been studied since ancient times, with Euclid describing them in Elements (Book V, Definitions 8–10) as continued proportions where the ratio between consecutive terms is constant, and exploring their properties in Books VIII and IX, including sums of such sequences. In modern mathematics and applications, they model exponential growth and decay, such as population dynamics, radioactive decay, and compound interest in finance, where the balance after each period multiplies by a fixed factor (1 + interest rate). They also appear in computer science for analyzing algorithm efficiency, like divide-and-conquer recurrences, and in physics for phenomena involving proportional scaling.

Definition and Fundamentals

Definition

A geometric progression, also known as a geometric sequence, is a sequence of non-zero numbers in which each term after the first is obtained by multiplying the preceding term by a fixed, non-zero constant known as the common ratio. The general form of such a sequence is \{a, ar, ar^2, ar^3, \dots, ar^{n-1}\}, where a \neq 0 represents the first term, or initial scale factor, and r \neq 0 denotes the common ratio. This structure ensures that the ratio between consecutive terms remains constant throughout the sequence. The stipulation of non-zero terms and ratio avoids trivial zero sequences and prevents division by zero when verifying the common ratio. Geometric progressions may be finite, with a predetermined number of terms, or infinite, extending without bound. In contrast to an arithmetic progression, which forms a linear sequence through constant addition, a geometric progression exhibits exponential growth or decay via multiplication.

Examples and Notation

A geometric progression is exemplified by the sequence 2, 4, 8, 16, \dots, where the first term is a = 2 and the common ratio is r = 2. Each subsequent term is formed by multiplying the previous term by r, resulting in terms that double progressively. Another illustrative example is the sequence 9, 3, 1, \frac{1}{3}, \dots, with first term a = 9 and common ratio r = \frac{1}{3}. In this case, the terms diminish because |r| < 1, leading to a reduction in magnitude with each step. Standard notation for the nth term of a geometric progression, where indexing begins at n = 1, is given by a_n = a r^{n-1}. This formula expresses any term directly in terms of the initial term a and the common ratio r. A special case occurs when r = 1, producing a constant sequence where every term equals a. Additionally, if |r| < 1 and a \neq 0, the absolute values of the terms decrease monotonically as n increases. The terms of a finite geometric progression can be compactly represented using sigma notation for the corresponding series, such as \sum_{k=0}^{n-1} a r^k, which sums the first n terms starting from index k = 0.

Properties of Geometric Progressions

General Term and Common Ratio

The general term of a geometric progression, starting with first term a and common ratio r, is given by the explicit formula a_n = a r^{n-1} for each positive integer n. This expression allows direct computation of any term without listing prior terms. The formula can be verified using mathematical induction. For the base case n=1, a_1 = a r^{1-1} = a \cdot 1 = a, which holds by definition of the first term. Assume the formula is true for some k \geq 1, so a_k = a r^{k-1}. For the inductive step, consider n = k+1: the next term is a_{k+1} = r \cdot a_k = r \cdot (a r^{k-1}) = a r^k = a r^{(k+1)-1}, confirming the formula holds for k+1. By the principle of , the formula is true for all positive integers n. The common ratio r governs the sequence's behavior. When |r| > 1, the absolute value of the terms increases exponentially without bound as n grows. Conversely, if |r| < 1 and r \neq 0, the terms diminish toward zero. If r < 0, the signs of the terms alternate between positive and negative while the magnitudes follow the exponential pattern dictated by |r|. The case r = 0 yields a degenerate geometric progression, where a_1 = a and a_n = 0 for all n \geq 2, effectively terminating after the initial term. For r > 0, the general term connects directly to exponential functions via the identity r^{n-1} = e^{(n-1) \ln r}, so a_n = a \, e^{(n-1) \ln r}, illustrating geometric progressions as discrete analogs of continuous exponential growth or decay.

Insertion of Terms

In a geometric progression, three consecutive terms a, b, and c satisfy the relation b^2 = ac, as this ensures the common ratio is constant: b/a = c/b. This property underscores the geometric harmony, where the middle term is the geometric mean of the adjacent terms. Consider inserting the arithmetic mean between two consecutive terms of a geometric progression, say a and ar, where r is the common ratio. The is \frac{a + ar}{2} = a \frac{1 + r}{2}. In contrast, the of these terms is \sqrt{a \cdot ar} = a \sqrt{r}, which corresponds exactly to the next term in the progression if positioned appropriately. This highlights that the arithmetic mean does not generally lie within the geometric progression unless r = 1. Similarly, the can be inserted between a and ar. The of two positive numbers x and y is \frac{2xy}{x + y}; applying this yields \frac{2 a \cdot ar}{a + ar} = \frac{2 a^2 r}{a(1 + r)} = a \frac{2 r}{1 + r}. Like the , this value typically does not form part of the original geometric progression, except in special cases such as r = 1. More generally, in a geometric progression, the of any two s equals the located midway between them in the sequence. For instance, the of the first and third s is the second itself.

Geometric Series

Finite Series Sum

The sum of the first n terms of a finite geometric progression, denoted S_n, with first a and common r \neq 1, is given by the formula S_n = a \frac{1 - r^n}{1 - r}. This expression provides a direct way to compute the partial sum without enumerating each term. An equivalent form, often preferred when r > 1 to ensure a positive denominator, is S_n = a \frac{r^n - 1}{r - 1}. For the special case where r = 1, the progression consists of identical terms a, a, \dots, a, and the sum simplifies to S_n = n a. A classic example is the series $1 + 2 + 4 + \dots + 2^{n-1}, where a = 1 and r = 2, yielding S_n = 2^n - 1. This illustrates how the formula captures in finite steps. When |r| < 1, the finite sum S_n increases toward the value a / (1 - r) as n grows larger, reflecting the progression's diminishing contributions from later terms./24:_The_Geometric_Series/24.01:_Finite_Geometric_Series)

Derivation of Finite Sum

The sum S_n of the first n terms of a with first term a and common ratio r (where r \neq 1) is given by S_n = a + ar + ar^2 + \dots + ar^{n-1}. To derive this formula, multiply both sides by r, yielding r S_n = ar + ar^2 + \dots + ar^{n-1} + ar^n. Subtracting the second equation from the first eliminates intermediate terms: S_n - r S_n = a - ar^n, which simplifies to S_n (1 - r) = a (1 - r^n), so S_n = \frac{a (1 - r^n)}{1 - r}. An alternative derivation uses mathematical induction. For the base case n = 1, S_1 = a, which holds trivially. Assume the formula is true for n = k, so S_k = \frac{a (1 - r^k)}{1 - r}. For n = k+1, add the next term: S_{k+1} = S_k + ar^k = \frac{a (1 - r^k)}{1 - r} + ar^k. Factoring gives S_{k+1} = \frac{a (1 - r^k) + ar^k (1 - r)}{1 - r} = \frac{a (1 - r^{k+1})}{1 - r}, completing the induction. When r = 1, the progression is constant, and the sum is simply S_n = na, obtained by direct addition since each of the n terms equals a. Geometrically, the formula can be interpreted through repeated scaling of similar figures, such as the total area formed by adding squares of side lengths in geometric ratio, where the sum represents the limiting enclosure under iterative subdivision.

Infinite Series and Convergence

An infinite geometric series is the sum of the terms of an infinite geometric progression, expressed as S_\infty = \sum_{k=0}^\infty a r^k, where a is the first term and r is the common ratio. This series converges to the finite value S_\infty = \frac{a}{1 - r} if and only if |r| < 1. The convergence of the infinite geometric series depends strictly on the magnitude of the common ratio r. Specifically, the series converges absolutely when |r| < 1, as the terms diminish geometrically toward zero, allowing the partial sums to approach a limit. Conversely, the series diverges when |r| \geq 1: if r = 1, the series becomes a constant sum a + a + a + \cdots, which grows without bound; if r = -1, the terms alternate but do not decrease in magnitude, leading to oscillation without convergence; and if |r| > 1, the terms increase exponentially, causing the partial sums to diverge to or negative depending on the sign of r./08%3A_Taylor_and_Laurent_Series/8.01%3A_Geometric_Series) The formula for the infinite sum arises as the of the partial sums of the finite geometric series. The partial sum up to n+1 terms is S_n = a \frac{1 - r^{n+1}}{1 - r} for r \neq 1; taking the as n \to \infty, when |r| < 1, the term r^{n+1} \to 0, yielding S_\infty = \frac{a}{1 - r}./11%3A_Sequences_Probability_and_Counting_Theory/11.05%3A_Series_and_Their_Notations) For example, the series $1 + \frac{1}{2} + \frac{1}{4} + \frac{1}{8} + \cdots has a = 1 and r = \frac{1}{2}, so |r| < 1 and it converges to \frac{1}{1 - 1/2} = 2. In contrast, the series $1 + 2 + 4 + 8 + \cdots with a = 1 and r = 2 has |r| > 1, so it diverges to .

Special Properties

Product of Terms

In a finite geometric progression (GP) with first term a, common ratio r, and n terms given by a, ar, ar^2, \dots, ar^{n-1}, a notable property concerns the product of terms that are equidistant from the beginning and the end. Specifically, the product of the first and last terms equals the product of the second and second-to-last terms, and so on, remaining constant throughout: a \cdot ar^{n-1} = ar \cdot ar^{n-2} = \dots = ar^{k-1} \cdot ar^{n-k} for k = 1, 2, \dots, \lfloor n/2 \rfloor. This constancy arises because each such pair simplifies to a^2 r^{n-1}, independent of the position k. The overall product P of all n terms in the GP is P = \prod_{k=1}^n ar^{k-1} = a^n r^{0 + 1 + \dots + (n-1)} = a^n r^{n(n-1)/2}. This formula can be derived by taking the logarithm: \log P = \sum_{k=1}^n \log(ar^{k-1}) = n \log a + (\log r) \sum_{k=0}^{n-1} k = n \log a + (\log r) \cdot \frac{(n-1)n}{2}. Exponentiating both sides yields P = a^n r^{n(n-1)/2}. For the special case where n is odd, say n = 2m + [1](/page/1), the terms are symmetric around the middle term ar^m. The product P simplifies to (ar^m)^{2m+[1](/page/1)} = (ar^m)^n, meaning the product of all terms equals the middle term raised to n. In this scenario, pairing terms equidistant from the middle gives products each equal to (ar^m)^2, and with the middle term itself, the overall product aligns with the powered middle term. For example, consider the GP $1, 2, 4 where a=[1](/page/1), r=2, n=3, and middle term $2: the pairs yield $1 \cdot 4 = 4 = 2^2, and including the middle term gives $1 \cdot 2 \cdot 4 = 8 = 2^3.

Relation to Geometric Mean

The geometric mean (GM) of the n terms in a geometric progression with first term a > 0 and common ratio r > 0 is the nth root of their product, which simplifies to a r^{(n-1)/2}. This expression arises directly from the product of the terms a, ar, ar^2, \dots, ar^{n-1}, given as a^n r^{n(n-1)/2} in the preceding section on properties. When n is odd, the geometric mean coincides precisely with the middle term of the progression. For even n, it equals the geometric mean of the two central terms. A fundamental property of geometric progressions is that each term serves as the of its adjacent terms, underscoring the multiplicative structure inherent to . This of the GM positions it as the "balancing" value in the progression, analogous to the in an . For positive terms in a geometric progression, the - (AM-GM) holds: the is at least as large as the , with all terms are (i.e., r = 1, reducing the progression to a constant sequence). In statistical contexts, geometric progressions relate to data with multiplicative dynamics, where taking logarithms transforms the terms into an . The then equals the of the of these logarithms, providing a measure of that stabilizes variance on the log scale for skewed, positive data distributions.

Applications

In Mathematics

Geometric progressions play a fundamental role in the theory of , where the \sum_{n=0}^{\infty} x^n = \frac{1}{1-x} for |x| < 1 serves as the prototypical example of a power series expansion, enabling the representation of rational functions and approximations of more complex analytic functions. This series arises directly from the infinite of a geometric progression with first term 1 and common ratio x, and its convergence within the unit disk provides the foundation for radius of convergence tests in general power series. While the Taylor series for the exponential function, e^x = \sum_{n=0}^{\infty} \frac{x^n}{n!}, is not itself a geometric progression due to the factorial denominators, partial sums of this series can approximate geometric progressions for small fixed ratios r by truncating higher-order terms, illustrating how power series generalize and refine geometric sums in analytic contexts. In linear algebra, geometric progressions appear in the context of eigenvalues and eigenvectors for certain matrices, particularly scaling or shift operators. For instance, consider the left shift operator \phi_{\text{left}} on sequences, defined by (\phi_{\text{left}} (a_0, a_1, a_2, \dots)) = (a_1, a_2, a_3, \dots); any geometric progression with common ratio r forms an eigenvector of this operator with corresponding eigenvalue r, as applying the shift scales the sequence by r while preserving its form. This connection extends to finite-dimensional approximations, such as companion matrices for linear recurrences, where eigenvalues determine the growth rates akin to geometric ratios, and diagonal scaling matrices with entries forming a geometric progression (e.g., diag(1, r, r^2, ..., r^{n-1})) have eigenvalues that are precisely the terms of that progression. Such structures are essential in understanding matrix powers and spectral decompositions, where repeated application yields scaled geometric sequences. Geometric progressions underpin the self-similar construction of fractals, exemplified by the , a generated iteratively starting from an . At each , every is replaced by four segments each scaled by a factor of $1/3 of the original length, resulting in the total perimeter forming a with first term equal to the initial perimeter P_0 and common $4/3: the perimeter after n iterations is P_n = P_0 \left(\frac{4}{3}\right)^n, which diverges to infinity as n \to \infty. This scaling reflects the fractal's dimension d = \frac{\log 4}{\log 3} \approx 1.2619, computed via the formula for self-similar sets, highlighting how geometric ratios quantify infinite complexity in finite constructions; the area, however, converges as a with $4/9, yielding a finite enclosed region. Arithmetic-geometric progressions (AGPs) combine elements of both arithmetic and geometric sequences, defined as a sequence where the nth term is the product of the nth term of an arithmetic progression and the nth term of a geometric progression, typically a_n = [b + (n-1)d] r^{n-1} for constants b, d, and r. The sum of the first n terms of an AGP can be derived by differentiating the geometric series sum formula with respect to the common ratio and solving the resulting expression, yielding S_n = b \frac{1 - r^n}{1 - r} + d r \frac{1 - n r^{n-1} + (n-1) r^n}{(1 - r)^2} for r \neq 1, which facilitates closed-form evaluations in summation problems involving linear trends modulated by exponential growth. AGPs arise naturally in applications like moment-generating functions or integral approximations, providing a bridge between polynomial and exponential behaviors in sequence analysis. A key application of geometric progressions lies in solving linear homogeneous recurrence relations with constant coefficients, where the general decomposes into a of geometric sequences corresponding to the of the . For a recurrence a_n = c_1 a_{n-1} + c_2 a_{n-2} + \dots + c_k a_{n-k}, assuming a of the form a_n = \rho^n leads to the \rho^k - c_1 \rho^{k-1} - \dots - c_k = 0; distinct \rho_i yield basis solutions \rho_i^n, while repeated incorporate polynomial factors like n^m \rho^n. This method reduces the recurrence to summing geometric progressions, with of infinite series solutions depending on the magnitude of the dominant |\rho| < 1.

In Real-World Scenarios

In , compound interest calculations model the growth of investments or loans where interest is added to periodically, forming a geometric progression. The amount A after t periods is given by A = P (1 + i)^t, where P is , i is the per period, and the common ratio is r = 1 + i. This progression allows for straightforward computation of future values, such as in savings accounts or annuities. In biology, geometric progressions describe or decay in discrete time steps, such as bacterial or . For population size, N_t = N_0 r^t, where N_0 is the initial population, t is time in generations or periods, and r is the ; for example, doubling each cycle uses r = 2. In , the amount remaining follows a similar form with r = 1/2 for each period, modeling the decline of isotopes like in dating applications. Asset depreciation in and often employs geometric progressions to estimate loss over time due to wear or . The after n periods is V_n = V_0 (1 - d)^n, where V_0 is the initial and d is the rate per period, yielding a common r = 1 - d < 1. This method, known as declining balance , is commonly used for machinery or vehicles in financial reporting. In , simplified models of virus spread, such as the early exponential phase of the (Susceptible-Infected-Recovered) model, approximate infections as a geometric progression in generations. Here, the number of infected individuals grows by a factor r (the effective reproduction number) each time step until saturation effects intervene. This formulation aids in forecasting outbreak trajectories, as seen in analyses of diseases like or COVID-19. A classic illustrative example of geometric progression's rapid escalation is the legend of wheat grains on a chessboard, where one grain is placed on the first square, two on the second, four on the third, and so on, doubling each of the 64 squares. The total grains form a finite summing to approximately $2^{64} - 1, or over 18 quintillion, highlighting the nature of such growth in problems. This , though apocryphal, demonstrates practical implications in and discussions.

Historical Development

Ancient and Classical Periods

Evidence of the use of proportions and ratios, foundational to geometric progressions, appears in around 2000 BC. Clay tablets from the Old Babylonian period (ca. 2000–1600 BC) include finite sequences based primarily on arithmetic and progressions, with applications in , resource division, and economic calculations, alongside some problems involving proportional reasoning. In , the , attributed to the scribe and dated to approximately 1650 BC, contains problems involving both and geometric progressions. For instance, Problem 79 requires summing a with a common of 7, showcasing early algebraic manipulation of such sequences. Additionally, the papyrus addresses geometric scaling in volume computations for granaries and pyramids, where proportional increases in dimensions lead to multiplicative changes in volumes, illustrating implicit geometric ratios. Greek mathematics formalized these concepts during classical antiquity, particularly in Euclid's Elements (c. 300 BC). In Book IX, Proposition 35, Euclid proves the sum of a finite geometric progression of numbers in continued proportion by subtracting the first term from the second and last, yielding a result equivalent to the modern formula for the sum S_n = a \frac{r^n - 1}{r - 1} where a is the first term and r the common ratio. This proposition applies proportional reasoning to establish the total, building on earlier Greek explorations of ratios in Books V and VIII. In ancient , the Sulba Sutras (c. 800–500 BC), appendices to the Vedic texts, employed geometric proportions and ratios for constructing fire altars of precise shapes, such as squares, , and isosceles trapezoids. These texts emphasize maintaining specific side ratios, like transforming a square into a or while preserving area, which relies on proportional adjustments akin to geometric scaling. Such constructions, attributed to sages like Baudhayana and Apastamba, highlight an early systematic use of ratios in geometric contexts.

Medieval and Early Modern Periods

During the , mathematicians made significant advances in understanding geometric progressions through algebraic and combinatorial contexts. Al-Karaji, around 1000 AD, contributed to the study of coefficients in his work Al-Fakhri fi'l-jabr wa'l-muqabala, where he formulated the coefficients and described a triangular array akin to , using inductive methods to expand expressions; these expansions implicitly relied on properties of geometric progressions for summing powers and coefficients, as seen in his proofs for series sums. , in the 11th century, further explored proportions in his commentary on Euclid's Elements, treating ratios as ideal numbers and emphasizing geometric proportionality, which underpinned applications of geometric progressions in solving equations and classifying conic intersections. In the European , geometric progressions gained practical importance in commercial and financial mathematics. Leonardo of Pisa, known as , in his 1202 , applied geometric progressions to model and , demonstrating how successive terms multiply by a constant to compute annuities and currency conversions, thereby introducing these concepts to for banking applications. The saw the formalization of terminology and connections to other algebraic operations. In 1544, Michael Stifel coined the term "geometric progression" in his Arithmetica Integra, illustrating it with the sequence 2, 4, 8, 16, 32, and linking it to while extending the progression to negative indices (e.g., 1/2, 1/4); he also connected these progressions to root extractions, using them to approximate irrational roots through iterative . Building on this, in 1614 introduced logarithms in Mirifici Logarithmorum Canonis Descriptio, conceptualizing them as a bridge between geometric progressions—where terms multiply by a constant ratio—and progressions, allowing of large numbers to be reduced to addition via logarithmic tables.

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