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Common logarithm
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In mathematics, the common logarithm (aka "standard logarithm") is the logarithm with base 10.[1] It is also known as the decadic logarithm, the decimal logarithm and the Briggsian logarithm. The name "Briggsian logarithm" is in honor of the British mathematician Henry Briggs who conceived of and developed the values for the "common logarithm". Historically, the "common logarithm" was known by its Latin name logarithmus decimalis[2] or logarithmus decadis.[3]
The mathematical notation for using the common logarithm is log(x),[4] log10(x),[5] or sometimes Log(x) with a capital L;[a] on calculators, it is printed as "log",[6] but mathematicians usually mean natural logarithm (logarithm with base e ≈ 2.71828) rather than common logarithm when writing "log", since the natural logarithm is – contrary to what the name of the common logarithm implies – the most commonly used logarithm in pure math.[7]

Before the early 1970s, handheld electronic calculators were not available, and mechanical calculators capable of multiplication were bulky, expensive and not widely available. Instead, tables of base-10 logarithms were used in science, engineering and navigation—when calculations required greater accuracy than could be achieved with a slide rule. By turning multiplication and division to addition and subtraction, use of logarithms avoided laborious and error-prone paper-and-pencil multiplications and divisions.[1] Because logarithms were so useful, tables of base-10 logarithms were given in appendices of many textbooks. Mathematical and navigation handbooks included tables of the logarithms of trigonometric functions as well.[8] For the history of such tables, see log table.
Mantissa and characteristic
[edit]An important property of base-10 logarithms, which makes them so useful in calculations, is that the logarithm of numbers greater than 1 that differ by a factor of a power of 10 all have the same fractional part. The fractional part is known as the mantissa.[b] Thus, log tables need only show the fractional part. Tables of common logarithms typically listed the mantissa, to four or five decimal places or more, of each number in a range, e.g. 1000 to 9999.
The integer part, called the characteristic, can be computed by simply counting how many places the decimal point must be moved, so that it is just to the right of the first significant digit. For example, the logarithm of 120 is given by the following calculation:
The last number (0.07918)—the fractional part or the mantissa of the common logarithm of 120—can be found in the table shown. The location of the decimal point in 120 tells us that the integer part of the common logarithm of 120, the characteristic, is 2.
Negative logarithms
[edit]Positive numbers less than 1 have negative logarithms. For example,
To avoid the need for separate tables to convert positive and negative logarithms back to their original numbers, one can express a negative logarithm as a negative integer characteristic plus a positive mantissa. To facilitate this, a special notation, called bar notation, is used:
The bar over the characteristic indicates that it is negative, while the mantissa remains positive. When reading a number in bar notation out loud, the symbol is read as "bar n", so that is read as "bar 2 point 07918...". An alternative convention is to express the logarithm modulo 10, in which case
with the actual value of the result of a calculation determined by knowledge of the reasonable range of the result.[c]
The following example uses the bar notation to calculate 0.012 × 0.85 = 0.0102:
* This step makes the mantissa between 0 and 1, so that its antilog (10mantissa) can be looked up.
The following table shows how the same mantissa can be used for a range of numbers differing by powers of ten:
| Number | Logarithm | Characteristic | Mantissa | Combined form |
|---|---|---|---|---|
| n = 5 × 10i | log10(n) | i = floor(log10(n)) | log10(n) − i | |
| 5 000 000 | 6.698 970... | 6 | 0.698 970... | 6.698 970... |
| 50 | 1.698 970... | 1 | 0.698 970... | 1.698 970... |
| 5 | 0.698 970... | 0 | 0.698 970... | 0.698 970... |
| 0.5 | −0.301 029... | −1 | 0.698 970... | 1.698 970... |
| 0.000 005 | −5.301 029... | −6 | 0.698 970... | 6.698 970... |
Note that the mantissa is common to all of the 5 × 10i. This holds for any positive real number because
Since i is a constant, the mantissa comes from , which is constant for given . This allows a table of logarithms to include only one entry for each mantissa. In the example of 5 × 10i, 0.698 970 (004 336 018 ...) will be listed once indexed by 5 (or 0.5, or 500, etc.).
History
[edit]Common logarithms are sometimes also called "Briggsian logarithms" after Henry Briggs, a 17th century British mathematician. In 1616 and 1617, Briggs visited John Napier at Edinburgh, the inventor of what are now called natural (base-e) logarithms, in order to suggest a change to Napier's logarithms. During these conferences, the alteration proposed by Briggs was agreed upon; and after his return from his second visit, he published the first chiliad of his logarithms.
Because base-10 logarithms were most useful for computations, engineers generally simply wrote "log(x)" when they meant log10(x). Mathematicians, on the other hand, wrote "log(x)" when they meant loge(x) for the natural logarithm. Today, both notations are found. Since hand-held electronic calculators are designed by engineers rather than mathematicians, it became customary that they follow engineers' notation. So the notation, according to which one writes "ln(x)" when the natural logarithm is intended, may have been further popularized by the very invention that made the use of "common logarithms" far less common, electronic calculators.
To mitigate the ambiguity, the ISO 80000 specification recommends that loge(x) should be ln(x), while log10(x) should be written lg(x), which unfortunately is used for the base-2 logarithm by CLRS and Sedgwick and The Chicago Manual of Style.[10][11][12]
Numeric value
[edit]
The numerical value for logarithm to the base 10 can be calculated with the following identities:[5]
- or or
using logarithms of any available base
as procedures exist for determining the numerical value for logarithm base e (see Natural logarithm § Efficient computation) and logarithm base 2 (see Algorithms for computing binary logarithms).
Derivative
[edit]The derivative of a logarithm with a base b is such that[13]
, so .
See also
[edit]- Binary logarithm
- Cologarithm
- Decibel
- Logarithmic scale
- Napierian logarithm
- Significand (also commonly called mantissa)
Notes
[edit]- ^ The notation Log is ambiguous, as this can also mean the complex natural logarithmic multi-valued function.
- ^ This use of the word mantissa stems from an older, non-numerical, meaning: a minor addition or supplement, e.g., to a text.[citation needed] The word was introduced by Henry Briggs.[9] The word "mantissa" is often used to describe the part of a floating-point number that represents its significant digits, although "significand" was the term used for this by IEEE 754, and may be preferred to avoid confusion with logarithm mantissas.
- ^ For example, Bessel, F. W. (1825). "Über die Berechnung der geographischen Längen und Breiten aus geodätischen Vermessungen". Astronomische Nachrichten. 331 (8): 852–861. arXiv:0908.1823. Bibcode:1825AN......4..241B. doi:10.1002/asna.18260041601. S2CID 118630614. gives (beginning of section 8) , . From the context, it is understood that , the minor radius of the earth ellipsoid in toise (a large number), whereas , the eccentricity of the earth ellipsoid (a small number).
References
[edit]- ^ a b Hall, Arthur Graham; Frink, Fred Goodrich (1909). "Chapter IV. Logarithms [23] Common logarithms". Trigonometry. Vol. Part I: Plane Trigonometry. New York: Henry Holt and Company. p. 31.
- ^ Euler, Leonhard (1748). "Chapter 22: Solutio nonnullorum problematum ad Circulum pertinentium". Introductio in Analysin Infinitorum (Part 2) (in Latin). Lausanne: Marcum-Michaelem Bousquet. p. 304.
- ^ Scherffer, P. Carolo (1772). Institutionum Analyticarum Pars Secunda de Calculo Infinitesimali Liber Secundus de Calculo Integrali (in Latin). Vol. 2. Joannis Thomæ Nob. De Trattnern. p. 198.
- ^ "Introduction to Logarithms". www.mathsisfun.com. Retrieved 2020-08-29.
- ^ a b Weisstein, Eric W. "Common Logarithm". mathworld.wolfram.com. Retrieved 2020-08-29.
- ^ "Using a calculator - Laws of logarithms and exponents - Higher Maths Revision". BBC Bitesize. BBC. Retrieved 2025-07-08.
- ^ "Introduction to Logarithms". www.mathsisfun.com. Retrieved 2025-07-08.
- ^ Hedrick, Earle Raymond (1913). Logarithmic and Trigonometric Tables. New York, USA: Macmillan.
- ^ Schwartzman, Steven (1994-12-31). The Words of Mathematics: An Etymological Dictionary of Mathematical Terms in English. American Mathematical Soc. p. 131. ISBN 978-1-61444-501-2.
- ^ Cormen, Thomas H.; Leiserson, Charles E.; Rivest, Ronald L.; Stein, Clifford (2001) [1990], Introduction to Algorithms (2nd ed.), MIT Press and McGraw-Hill, pp. 34, 53–54, ISBN 0-262-03293-7
- ^ Sedgewick, Robert; Wayne, Kevin Daniel (2011), Algorithms, Addison-Wesley Professional, p. 185, ISBN 978-0-321-57351-3.
- ^ The Chicago Manual of Style (25th ed.), University of Chicago Press, 2003, p. 530
- ^ "Derivatives of Logarithmic Functions". Math24. 2021-04-14. Archived from the original on 2020-10-01.
Bibliography
[edit]- Abramowitz, Milton; Stegun, Irene Ann, eds. (1983) [June 1964]. Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables. Applied Mathematics Series. Vol. 55 (Ninth reprint with additional corrections of tenth original printing with corrections (December 1972); first ed.). Washington D.C.; New York: United States Department of Commerce, National Bureau of Standards; Dover Publications. ISBN 978-0-486-61272-0. LCCN 64-60036. MR 0167642. LCCN 65-12253.
- Möser, Michael (2009). Engineering Acoustics: An Introduction to Noise Control. Springer. p. 448. ISBN 978-3-540-92722-8.
- Poliyanin, Andrei Dmitrievich; Manzhirov, Alexander Vladimirovich (2007) [2006-11-27]. Handbook of mathematics for engineers and scientists. CRC Press. p. 9. ISBN 978-1-58488-502-3.
Common logarithm
View on GrokipediaDefinition and Fundamentals
Definition
The common logarithm of a positive real number , denoted as , is the exponent to which 10 must be raised to obtain , such that , where is a real number.[1][2] The domain of the common logarithm consists of all positive real numbers (), as the function is undefined for since no real exponent yields a non-positive result when raising 10 to that power.[1][2] Its range encompasses all real numbers, allowing to take any value on the real line depending on .[1][2] The common logarithm is the inverse function of the exponential function base 10, meaning that if , then , often referred to as the antilogarithm.[1][2] For example, because , and because .[1][2]Notation and Conventions
The common logarithm, defined as the logarithm with base 10, is denoted by in numerous mathematical, engineering, and physical contexts, where the base is conventionally understood to be 10 without explicit specification.[7] This shorthand arises from its frequent use in applied fields, but to prevent confusion—particularly since pure mathematicians often reserve for the natural logarithm (base )—the unambiguous form is recommended and widely employed in formal writing.[7][1] Historically, logarithmic notation has shifted from earlier conventions, such as the capitalized "Log" introduced by Gottfried Wilhelm Leibniz in 1675 to represent the logarithm of , to the modern lowercase popularized by Leonhard Euler in the mid-18th century as part of his treatment of logarithms as exponents of a base.[4] Euler's notation in works like his 1748 Introductio in analysin infinitorum established the subscript form for arbitrary bases, influencing contemporary standards. In practical tools, conventions vary by domain: scientific calculators, such as those from Casio and Texas Instruments commonly used in engineering, default the "log" button to base 10, reflecting its utility in measurements like decibels and Richter scales.[8] In contrast, many programming languages and mathematical software, including Python's math library and Wolfram Mathematica, treat "log" as the natural logarithm, necessitating "log10" or an equivalent for the common logarithm to maintain consistency with computational analysis. To resolve such ambiguities in international texts, especially in German and Russian literature, serves as an alternative symbol exclusively for the base-10 logarithm, as endorsed by standards like ISO 80000.[9] A prominent example of this notation in applied science is the pH scale in chemistry, where quantifies acidity using the base-10 logarithm of the hydrogen ion concentration in moles per liter, enabling intuitive scaling across orders of magnitude.[10]Properties and Operations
Algebraic Properties
The algebraic properties of the common logarithm, denoted or simply where the base 10 is implied, enable the simplification and manipulation of logarithmic expressions. These properties derive from the inverse relationship between logarithms and exponentiation, where if and only if for .[11] They hold for all positive real numbers and are fundamental to algebraic operations involving common logs.[12] The product rule states that . To see this, let and , so and . Then , which implies .[12] For example, , and indeed since .[11] The quotient rule is . This follows similarly: , so .[12] The power rule provides for real . Here, , yielding .[12] An illustration is .[11] Special cases include , since , and more generally for any integer , as directly by definition.[12] These properties collectively facilitate the transformation of products, quotients, and powers into sums, differences, and scalar multiples in logarithmic form.[11]Change of Base Formula
The change of base formula provides a method to express the common logarithm of a number in terms of logarithms using any other valid base. For any and base , , it states that This relation follows from the definition of logarithms as exponents and the consistency of logarithmic scales across bases.[13] A frequent practical application involves converting to natural logarithms (base ), yielding This form is advantageous in analytical work and programming, as natural logarithms are often the default in mathematical libraries and allow seamless integration with exponential functions based on .[14] The formula's primary significance is its role in facilitating computations of common logarithms by leveraging more accessible or efficient logarithmic evaluations, such as when base-10 tables are absent or when natural logs are preferred for their mathematical properties.[13] It historically supported manual calculations before electronic tools and remains essential for verifying results across bases.[14] For illustration, consider approximating : Here, and , with the result aligning closely to the known value of .[15][2][16] In numerical implementations, however, the change of base formula can encounter stability issues for very large or very small , where floating-point representations of the logarithms may introduce rounding errors that propagate through the division, potentially degrading accuracy.[17]Logarithmic Representation
Characteristic and Mantissa
In the context of common logarithms, which are base-10 logarithms, the value of for a positive real number is expressed as the sum of two parts: the characteristic, an integer , and the mantissa, a fractional part where . Thus, , which equivalently means . Here, represents the significand, a value between 1 and 10 that captures the scale-independent portion of .[18][2] The characteristic is determined by taking the floor of , effectively indicating the order of magnitude of . For instance, when lies in the interval $[1, 10)$, the characteristic is 0, as the logarithm ranges from 0 to just under 1. This integer part simplifies the handling of large or small numbers by shifting the focus to the normalized significand.[19][20] The mantissa provides the precise decimal adjustment to the characteristic, ensuring the full logarithmic value aligns with . Its significance lies in representing the relative precision of the number, independent of its magnitude. For example, consider ; this can be rewritten as , so , where 2 is the characteristic and 0.39794 is the mantissa.[21][22] This decomposition into characteristic and mantissa was essential for pre-digital computation, particularly in tools like slide rules, where the integer characteristic is managed through scale alignment and cursor positioning, while the mantissa is read directly from the logarithmic graduations for multiplication, division, and other operations.[23][24]Negative and Fractional Logarithms
For numbers where , the common logarithm is negative, reflecting that can be expressed as raised to a negative power. In this case, the logarithm takes the form , where is a positive integer (the negative of the characteristic) and is the mantissa, such that . The characteristic, which is the integer part of the logarithm, is negative, while the mantissa remains positive and represents the fractional part adjusted accordingly.[11] This representation leverages the property that for , allowing computation of logarithms for reciprocals by negating the log of the greater-than-1 value. For instance, , which decomposes as a characteristic of and a mantissa of , since . Similarly, exactly, with characteristic and mantissa , as . Another example is , yielding characteristic and mantissa .[11] Fractional logarithms arise naturally in these cases, as the result is generally non-integer for irrational or non-power-of-10 values less than 1. These fractional parts facilitate accurate representation and computation, especially in pre-calculator eras using logarithmic tables that listed only positive mantissas. Notably, is undefined, but as , , emphasizing the function's behavior near zero.[11]Historical Development
Origins and Early Concepts
The concept of logarithms has ancient roots in proportional scales and iterative calculations used by early civilizations to handle large numbers and astronomical computations. In ancient Babylonia, around 2000–1600 BC, clay tablets containing tables of successive powers of numbers demonstrated an early understanding of exponential growth, serving as a precursor to logarithmic thinking by facilitating multiplications through additions in related scales.[25] Similarly, Greek mathematicians employed proportional methods; Archimedes, in his third-century BC work The Sand Reckoner, developed a system to enumerate extraordinarily large numbers by iteratively multiplying by 10 and higher powers, effectively using exponential notation to bound the grains of sand in the universe, which foreshadowed the inverse relationship central to logarithms. During the medieval period, Islamic scholars advanced these ideas through refined trigonometric tables that relied on proportional interpolation. In the 15th century, Jamshīd al-Kāshī, working under Ulugh Beg, compiled highly precise sine tables in Zij-i Khāqānī, providing sine values to four sexagesimal places for each degree, accompanied by minute-by-minute differences for interpolation using proportional parts.[26] These proportional parts allowed astronomers to estimate intermediate values linearly, a technique that highlighted the need for more efficient ways to perform repeated multiplications and divisions in spherical trigonometry, laying groundwork for logarithmic simplification.[27] The formal invention of logarithms emerged in 1614 with John Napier's Mirifici logarithmorum canonis descriptio, where he introduced a function precursor to the natural logarithm to ease astronomical calculations. Motivated by the laborious multiplications required for trigonometric products in astronomy, Napier defined logarithms kinematically: the logarithm of a number decreases proportionally as the number itself decreases geometrically, such that the product of two numbers corresponds to the sum of their logarithms.[28] This innovation stemmed from earlier prosthaphaeresis formulas, which converted trigonometric multiplications into additions, but Napier's tables extended the approach to general arithmetic. A key insight in Napier's framework was the recognition that equal ratios between arguments produce equal differences in their logarithms, enabling the construction of arithmetic progressions from geometric sequences—a property that underscored logarithms' utility for computation before mechanical calculators.[28] Invented primarily to expedite trigonometric and multiplicative operations in astronomy and navigation, these early logarithms marked a pivotal shift toward systematic table-based arithmetic.Standardization and Key Contributors
The standardization of the common logarithm, defined as the logarithm to base 10, began in the early 17th century through modifications to John Napier's original concept of logarithms introduced in 1614. In 1615, English mathematician Henry Briggs, during his first visit to Napier in Edinburgh, proposed redefining the logarithm to base 10 such that log(1) = 0 and log(10) = 1, aligning it with the decimal system for computational simplicity and eliminating the cumbersome large numbers in Napier's tables.[29] This adjustment transformed Napier's logarithms into the more practical base-10 form, with log(1) = 0, facilitating easier arithmetic operations in scientific calculations. Briggs further refined this during subsequent visits in 1616, setting the stage for widespread adoption.[29] Briggs published the first table of common logarithms in Logarithmorum Chilias Prima in 1617, providing values for integers from 1 to 1,000 to 14 decimal places, dedicated to his audience at Gresham College.[30] He expanded this work in Arithmetica Logarithmica in 1624, offering comprehensive tables for numbers from 1 to 20,000 and 90,000 to 100,000, also to 14 decimal places, along with logarithmic values for trigonometric functions like sines and tangents. These publications marked the initial standardization of common logarithms, enabling their use in astronomy and geometry, as Briggs demonstrated in chapters on ellipses and polygons. Building on Briggs' foundation, Dutch mathematician Adriaan Vlacq extended the tables significantly in his 1628 Arithmetica Logarithmica, compiling logarithms for all integers from 1 to 100,000 to 10 decimal places, including the previously omitted range between 20,000 and 90,000. Assisted by Ezechiel de Decker, Vlacq's work filled critical gaps and incorporated trigonometric logarithms, making the tables more accessible for practical applications and serving as a reference for subsequent publications over centuries.[31] By 1628, these efforts had produced the first complete set of common logarithm tables, standardizing their format and precision for broader scientific use. Further refinements came through integration with computational tools, notably by English mathematician and clergyman William Oughtred, who in the 1620s and 1630s developed the slide rule based on common logarithmic scales. Oughtred's invention around 1622 placed two logarithmic scales side by side on sliding rods, allowing direct multiplication and division via addition of logs, with his 1633 gauging rod applying this to volume calculations for barrels and taxation.[32] This device, building on Napier's and Briggs' logarithmic principles, popularized common logarithms among practitioners by the 1630s, enhancing their utility in everyday computations without requiring full table lookups.[32] By the 19th century, common logarithms had become the standard in scientific texts and engineering, largely due to their inherent alignment with the decimal system, which mirrored the base-10 structure of emerging measurement standards like the metric system proposed in the 1790s.[33] This compatibility simplified logarithmic operations in fields requiring precise decimal handling, such as astronomy and surveying, where tables were routinely included in reference works. The adoption solidified their role as the default logarithm in education and research, supplanting other bases for most non-specialized applications.[34] A pivotal event underscoring the impact of standardized common logarithms was their application in verifying Kepler's third law of planetary motion and advancing navigation. Although Johannes Kepler initially used Napier's logarithms in his 1619 Harmonices Mundi to analyze orbital data and confirm the relation (where is the period and the semi-major axis) via log-log plots, the subsequent availability of Briggs' and Vlacq's base-10 tables enabled more efficient computations in celestial mechanics.[35] In navigation, common logarithms became indispensable from the 1620s onward, powering trigonometric calculations in almanacs and slide rules for determining positions at sea, as seen in works like Edmund Gunter's 1620 Canon Triangulorum, which tabulated base-10 logarithmic sines for mariners.[34] This standardization transformed logarithms from a novel aid into an essential tool for empirical sciences.Computation Methods
Traditional Table-Based Methods
Before the advent of electronic calculators, common logarithm tables were essential tools for performing arithmetic operations efficiently, particularly in fields like astronomy, navigation, and engineering. These tables, first systematically constructed by Henry Briggs in the early 17th century, listed the logarithms of numbers to facilitate computations by converting multiplication and division into addition and subtraction. Briggs' Arithmetica Logarithmica (1624) provided an initial table of common logarithms for numbers from 1 to 20,000 and 90,000 to 100,000, computed to 14 decimal places using manual iterative techniques.[36][37] The construction of these tables relied on painstaking numerical methods without digital aids. Briggs employed the "continued means" approach, involving repeated extraction of square roots to iteratively approximate logarithms of key values, such as log(2) ≈ 0.3010, which required up to 54 iterations for high precision.[38] Further entries were derived using difference methods and finite differences for interpolation between known points, allowing extension to larger ranges while minimizing redundant calculations; for instance, logarithms of primes were computed directly, then combined for composites.[38] Later tables, such as those by Adriaan Vlacq in 1628, expanded to 10 decimals and covered up to 100,000 numbers, building on Briggs' foundation through similar interpolation techniques.[36] In practice, these tables were used to simplify operations by leveraging logarithmic properties. For multiplication of two numbers and , one locates and in the table, adds them to get , and then finds the antilogarithm (number whose log is the sum) to obtain the product; division follows by subtraction of logs.[39] Powers and roots were handled by multiplying or dividing the log by the exponent or root index, respectively, before taking the antilog. Tables typically formatted the mantissa (fractional part) in columns for numbers from 1.000 to 9.999 (or scaled to 0.00 to 99.99), with 4 to 5 decimal places of precision, while the characteristic (integer part) was determined separately based on the number's magnitude—for example, numbers between 10 and 100 have a characteristic of 1.[18] A representative example illustrates the process: to compute , find (characteristic 1, mantissa 0.3617) and (characteristic 1, mantissa 0.6721), add to get , and take the antilog of 3.0338 (which is ).[39] This method reduced complex multiplications to table lookups and basic arithmetic. Despite their utility, traditional logarithm tables had inherent limitations. Interpolation between table entries introduced potential human error, as users manually estimated values for non-tabulated numbers, often leading to inaccuracies beyond 4-5 decimal places. Tables were generally restricted to 5-7 digits of overall precision due to printing constraints and computational labor, making them unsuitable for high-precision work without extensive manual adjustments.[36]Modern Numerical Algorithms
Modern numerical algorithms for computing the common logarithm, , leverage efficient iterative techniques and hardware optimizations, often reducing the problem to evaluating the natural logarithm via the change of base formula .[40] For , a preliminary step normalizes the input by determining the characteristic , expressing where , so . This reduces computation to the mantissa in . For example, with , and , yielding .[41] One foundational approach uses series expansions for the natural logarithm. The Taylor series for around , where , is . To compute , rewrite for suitable integer and , then , with precomputed. Dividing by the constant gives . This method converges with sufficient terms but requires careful range reduction for efficiency.[40] Iterative root-finding methods, such as the bisection algorithm, approximate by solving for over an initial interval containing the root, where and . The algorithm repeatedly bisects the interval, selecting the subinterval where the function changes sign, converging linearly to the root with error halving each step. For instance, starting with for , iterations narrow to . While simple and guaranteed to converge, bisection is slower than higher-order methods for high precision.[41] The CORDIC (COordinate Rotation DIgital Computer) algorithm provides a hardware-efficient alternative, particularly for embedded systems and calculators. In vectoring mode with hyperbolic rotations, it computes through iterative bit shifts and additions, avoiding multiplications. Extensions handle the base change to . Introduced for trigonometric functions, CORDIC's logarithmic variant achieves fixed-point precision iteratively, making it ideal for low-power devices.[42] In programming libraries like C++'s<cmath>, the log10() function implements high-precision computation using range reduction followed by minimax polynomials or the arithmetic-geometric mean (AGM). The AGM iterates arithmetic and geometric means starting from initial values related to , converging rapidly to values of elliptic integrals that can be used to compute after appropriate transformation and range reduction, such as via relations involving where is derived from . The result is then divided by for the common logarithm. Implementations in libraries such as glibc or LLVM libc ensure IEEE 754 compliance, delivering results accurate to the full precision of the input type. Double-precision floating-point arithmetic, with 53-bit mantissa, provides approximately 15 decimal digits of precision.[43][44][45]