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Length
Length
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Length
The metric length of one kilometre is equivalent to the imperial measurement of 0.62137 miles.
Common symbols
l
SI unitmetre (m)
Other units
see unit of length
Extensive?yes
Dimension

Length is a measure of distance. In the International System of Quantities, length is a quantity with dimension distance. In most systems of measurement a base unit for length is chosen, from which all other units are derived. In the International System of Units (SI) system, the base unit for length is the metre.[1]

Length is commonly understood to mean the most extended dimension of a fixed object.[1] However, this is not always the case and may depend on the position the object is in.

Various terms for the length of a fixed object are used, and these include height, which is vertical length or vertical extent, width, breadth, and depth. Height is used when there is a base from which vertical measurements can be taken. Width and breadth usually refer to a shorter dimension than length. Depth is used for the measure of a third dimension.[2]

Length is the measure of one spatial dimension, whereas area is a measure of two dimensions (length squared) and volume is a measure of three dimensions (length cubed).

History

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Measurement has been important ever since humans settled from nomadic lifestyles and started using building materials, occupying land and trading with neighbours. As trade between different places increased, the need for standard units of length increased. And later, as society has become more technologically oriented, much higher accuracy of measurement is required in an increasingly diverse set of fields, from micro-electronics to interplanetary ranging.[3]

Under Einstein's special relativity, length can no longer be thought of as being constant in all reference frames. Thus a ruler that is one metre long in one frame of reference will not be one metre long in a reference frame that is moving relative to the first frame. This means the length of an object varies depending on the speed of the observer.

Use in mathematics

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Euclidean geometry

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In Euclidean geometry, length is measured along straight lines unless otherwise specified and refers to segments on them. Pythagoras's theorem relating the length of the sides of a right triangle is one of many applications in Euclidean geometry. Length may also be measured along other types of curves and is referred to as arclength.

In a triangle, the length of an altitude, a line segment drawn from a vertex perpendicular to the side not passing through the vertex (referred to as a base of the triangle), is called the height of the triangle.

The area of a rectangle is defined to be length × width of the rectangle. If a long thin rectangle is stood up on its short side then its area could also be described as its height × width.

The volume of a solid rectangular box (such as a plank of wood) is often described as length × height × depth.

The perimeter of a polygon is the sum of the lengths of its sides.

The circumference of a circular disk is the length of the boundary (a circle) of that disk.

Other geometries

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In other geometries, length may be measured along possibly curved paths, called geodesics. The Riemannian geometry used in general relativity is an example of such a geometry. In spherical geometry, length is measured along the great circles on the sphere and the distance between two points on the sphere is the shorter of the two lengths on the great circle, which is determined by the plane through the two points and the center of the sphere.

Graph theory

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In an unweighted graph, the length of a cycle, path, or walk is the number of edges it uses.[4] In a weighted graph, it may instead be the sum of the weights of the edges that it uses.[5]

Length is used to define the shortest path, girth (shortest cycle length), and longest path between two vertices in a graph.

Measure theory

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In measure theory, length is most often generalized to general sets of via the Lebesgue measure. In the one-dimensional case, the Lebesgue outer measure of a set is defined in terms of the lengths of open intervals. Concretely, the length of an open interval is first defined as

so that the Lebesgue outer measure of a general set may then be defined as[6]

Computer science

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In computer science, the length of a string is the number of characters that comprise the string. For example, the bit string has length 11.[7]

Many programming languages have a string data type with a method for length to retrieve the length of a string.

String s = "Hello, world!";
int len = s.length(); // len = 13

The "length" of a sequential data structure, such as a dynamic array, can be described as the number of elements contained in it.

import java.util.List;

int[] a = {1, 2, 3, 4, 5};
int len = a.length; // len = 5

List<Integer> list = List.of(1, 2, 3, 4, 5, 6, 7, 8);
int len = list.size(); // len = 8

Units

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In the physical sciences and engineering, when one speaks of units of length, the word length is synonymous with distance. There are several units that are used to measure length. Historically, units of length may have been derived from the lengths of human body parts, the distance travelled in a number of paces, the distance between landmarks or places on the Earth, or arbitrarily on the length of some common object.

In the International System of Units (SI), the base unit of length is the metre (symbol, m), now defined in terms of the speed of light (about 300 million metres per second). The millimetre (mm), centimetre (cm) and the kilometre (km), derived from the metre, are also commonly used units. In U.S. customary units, English or imperial system of units, commonly used units of length are the inch (in), the foot (ft), the yard (yd), and the mile (mi). A unit of length used in navigation is the nautical mile (nmi).[8]

1.609344 km = 1 miles

Units used to denote distances in the vastness of space, as in astronomy, are much longer than those typically used on Earth (metre or kilometre) and include the astronomical unit (au), the light-year, and the parsec (pc).

Units used to denote sub-atomic distances, as in nuclear physics, are much smaller than the millimetre. Examples include the fermi (fm).

See also

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References

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Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Length is a fundamental that measures the between two points or the extent of an object along a single dimension. In the (SI), length is one of the seven base quantities, with the (symbol: m) defined as the length of the path travelled by in during a time interval of 1/299,792,458 of a second. This definition, adopted in 1983, ties length to the universal constant of the , ensuring precision and invariance across reference frames. Historically, length measurements originated from human body parts and natural objects, such as the (approximately the length of a ) used in around 3000 BCE or the foot derived from an average human foot in early Saxon times. Standardization efforts culminated in the during the in 1791, establishing the based on one ten-millionth of the distance from the to the , later refined through prototypes and now the light-based definition. In everyday applications, length underpins , , and , while in physics, it is essential for describing motion, forces, and in relativity, where occurs at high velocities relative to the observer. In , length extends beyond physical distance to include the magnitude of vectors—calculated as the of the with itself—and the of curves, approximated by integrals for precise computation. These concepts form the basis for , where defined a line as "breadthless length" in Elements (c. 300 BCE), emphasizing its one-dimensional nature without width. Across disciplines, length scales range from the Planck length (about 1.6 × 10⁻³⁵ m), the smallest meaningful distance in , to cosmic distances like the universe's diameter (approximately 8.8 × 10²⁶ m).

Fundamentals

Definition and Concept

Length is a fundamental quantity that measures the one-dimensional extent between two points or along a continuous path in space. Intuitively, it represents the separation between objects, such as the across a or the of a building, providing a basic sense of in everyday observations. In physical contexts, length is defined as a basic independent of other quantities, capturing the spatial interval without inherent direction. Formally, in mathematical terms, length corresponds to the separation between elements in a , where a function d(x,y)d(x, y) quantifies the "length" between points xx and yy, adhering to axioms such as non-negativity (d(x,y)0d(x, y) \geq 0), (d(x,y)=0d(x, y) = 0 x=yx = y), , and the . This concept extends to higher dimensions while remaining one-dimensional in nature, as it evaluates extent along a single axis or direction within the space. Length thus operates as a scalar value, yielding a non-negative that describes magnitude without vectorial components. While related, length differs from in that the latter typically denotes the shortest straight-line separation ( distance) between points, whereas length can refer to the total extent along any specified path, such as a . It also contrasts with broader notions of , which encompass multi-dimensional measures like area or , focusing instead on . In vector spaces, length manifests as the norm of a vector, a scalar that quantifies its magnitude, reinforcing its role in abstract geometric structures.

Basic Properties

In , the length of a is characterized by several fundamental properties that ensure its consistency and utility as a measure of extent. These properties include additivity for collinear segments, invariance under rigid transformations, positivity, homogeneity under scaling, and the . They form the basis for defining length as a metric function on the , applicable prior to more advanced geometric constructions. Additivity states that for any three collinear points A, B, and C, with B between A and C, the length of segment AC equals the sum of the lengths of AB and BC, expressed as \length(AC)=\length(AB)+\length(BC)\length(AC) = \length(AB) + \length(BC). This property arises from the order axioms in foundational systems, allowing the continuous extension of segments along a line. It ensures that length behaves like a one-dimensional measure along straight paths. Length is invariant under rigid transformations, such as translations and rotations, in . Specifically, if T is a rigid motion (), then for any points A and B, \length(T(A)T(B))=\length(AB)\length(T(A)T(B)) = \length(AB). This preservation follows from the congruence axioms, which equate segments that can be superimposed by such motions without . Positivity requires that the length of any segment is non-negative, with \length(AB)>0\length(AB) > 0 for distinct points A and B, and \length(AB)=0\length(AB) = 0 only if A coincides with B. This establishes length as a strict measure of separation, excluding negative or zero values for non-degenerate segments. Homogeneity implies that scaling a figure by a positive factor k proportionally affects its lengths, so \length(kAB)=k\length(AB)\length(k \cdot AB) = k \cdot \length(AB). Derived from the correspondence between geometric segments and real numbers in axiomatic frameworks, this property supports similarity transformations and . The triangle inequality provides that for any points A, B, and C, \length(AC)\length(AB)+\length(BC)\length(AC) \leq \length(AB) + \length(BC), with equality holding B lies on the segment AC. As a derived from the metric properties and order axioms, it bounds the direct extent between points by indirect paths, foundational for path minimization in .

Historical Development

Ancient and Pre-Modern Measures

In ancient Mesopotamia, length measurements were primarily empirical and derived from body parts, with the cubit (known as kush) serving as a fundamental unit equivalent to approximately 0.5 meters, based on the length of the forearm from elbow to fingertip. This unit was subdivided into smaller components, such as the shu-si (finger, about 1.67 cm) and she (barleycorn, roughly 0.28 cm), and scaled up to larger measures like the nindan (rod, about 6 meters), facilitating applications in construction, agriculture, and land surveying. Similarly, in ancient Egypt, the cubit was a core unit, with the royal cubit standardized at around 52.3 cm—slightly longer than the common cubit to account for the pharaoh's forearm plus a hand span—and used extensively for building monuments and surveying Nile floodplains. Variations in the royal cubit appeared in practical artifacts, such as New Kingdom jars with circumferences ranging from 48.6 to 59.8 cm, reflecting regional adaptations while maintaining a base of 28 fingers (each about 1.87 cm). Greek metrology built on these traditions, introducing units tied to athletics and architecture, notably the stadion—a track length of approximately 185 meters, or 600 Greek feet (each foot around 0.308 meters)—which defined the shortest sprint race at events like the Olympics and Pythian Games. This measure varied slightly by locale, with the Olympic stadion measured at 192.27 meters and the Delphic at about 177.65 meters, underscoring early inconsistencies in foot lengths across city-states. Hero of Alexandria advanced metrology in the first century CE through his work Metrica and Dioptra, describing anthropometric systems that proportioned units like the finger (daktylos, ~1.9 cm), palm (4 fingers), and foot (16 fingers, ~30.8 cm) to the human body, while devising instruments for precise surveying of lengths in engineering and astronomy. These contributions emphasized proportional relationships, such as the cubit as 18 inches or 24 fingers, aiding in the measurement of distances for trade routes and public works. The Romans adapted Greek and earlier systems into a more militaristic framework, with the pes (foot) standardized at about 29.6 cm—derived from an average adult foot—and serving as the base for engineering feats like roads and aqueducts. Larger distances were reckoned in paces (passus, two steps or 1.48 meters) and miles (mille passus, 1,000 paces or roughly 1,480 meters), enabling efficient legionary marches and territorial mapping. Into the medieval period, these body-based units persisted across Europe but with growing inconsistencies; the foot varied from 25 to 35 cm by region (e.g., shorter in England at ~30.5 cm post-Norman Conquest, longer in parts of Germany), the hand (palm width, 7-10 cm) differed by occupation, and the pace (step length, 70-80 cm) fluctuated with terrain and individual gait, complicating trade and leading to disputes among merchants. Such variability arose from local customs and the absence of durable standards, as measures were often calibrated against rulers' bodies or common tools rather than fixed artifacts. Efforts toward standardization emerged in ancient trade contexts, particularly in , where the Attic foot (approximately 29.5 cm) was promoted for consistency in commerce and , as evidenced by its use in Athenian markets and temples to align measurements with imported goods from across the Mediterranean. This unit, described by as derived from proportional divisions of the human form, helped mitigate discrepancies in exchanges but remained one of many local variants until later reforms.

Modern Standardization

The modern standardization of length measurement began during the , when the proposed a universal unit based on natural phenomena to replace disparate local standards. On March 26, 1791, the French National Assembly adopted the as one ten-millionth of the distance from the to the along the meridian passing through , a definition intended to be both rational and invariant. This initial prototype, known as the Mètre des Archives, was crafted from brass in 1799, but its reliance on a specific survey introduced inaccuracies due to measurement errors in the . To achieve international consensus and reproducibility, the was signed on May 20, 1875, by representatives of 17 nations in , establishing the International Bureau of Weights and Measures (BIPM) in , , as the custodian of metric standards. The 1st General on Weights and Measures (CGPM) in 1889 formalized the as the distance between two engraved lines on a platinum-iridium bar (the International Prototype Metre) maintained at 0°C, marking a shift to a durable artifact standard while preserving the original intent. However, this artifact-based definition faced challenges, including gradual instability from surface wear, contamination, and variations, which complicated precise replication across laboratories without direct access to the prototype. Advancements in spectroscopy prompted further refinements for greater universality. At the 11th CGPM in 1960, the metre was redefined as exactly 1,650,763.73 wavelengths in vacuum of the orange-red radiation from the transition between the 2p₁₀ and 5d₅ energy levels of krypton-86 atoms, enabling atomic-scale reproducibility independent of physical artifacts. This spectral standard was superseded in 1983 by the 17th CGPM, which defined the metre as the distance light travels in vacuum in 1/299,792,458 of a second, tying length directly to the speed of light (c) and the second, thus addressing prior reproducibility issues by leveraging fundamental constants. The 26th CGPM in 2019 completed this evolution through the SI redefinition, fixing c at exactly 299,792,458 m/s alongside other constants like the caesium hyperfine frequency for the second, ensuring the metre's definition remains stable and universally accessible via advanced interferometry without reliance on variable measurements.

Mathematical Applications

Euclidean Geometry

In , length is treated as a primitive concept through the framework of , as established in 's Elements. A straight line is defined as a breadthless length, and a is the finite portion between two points on that line. Equality of lengths, equivalent to modern congruence, is assumed in the common notions, such as "things which coincide with one another are equal to one another," allowing segments to be compared by superposition. These foundations enable the rigorous treatment of lengths without numerical measurement, emphasizing geometric equality. The exemplifies the role of length in right triangles, stating that if a is formed by sides of lengths aa and bb, then the cc satisfies a2+b2=c2a^2 + b^2 = c^2. proves this in Book I, Proposition 47, by constructing squares on each side and showing via area rearrangements (using prior propositions on parallelograms) that the area on the equals the sum of the areas on the legs. An outline of an alternative proof using similar triangles proceeds by drawing the altitude from the to the , dividing the original into two smaller right triangles; each is similar to the original by AA criterion (sharing angles), yielding proportions ac=pa\frac{a}{c} = \frac{p}{a} and bc=qb\frac{b}{c} = \frac{q}{b}, where p+q=cp + q = c, which multiply to a2+b2=c2a^2 + b^2 = c^2. Circle properties further illustrate length applications, where the CC is given by C=2πrC = 2\pi r, with π\pi as the fixed ratio of circumference to diameter, approximately 3.14159. does not compute π\pi explicitly but demonstrates in Book III, Propositions 26–28, that in equal circles, equal s subtend equal arcs, and arc lengths are proportional to the central angles via inscribed angles and sector divisions. This proportion underpins the formula s=rθs = r \theta, where θ\theta is the central angle in radians (defined such that a full circle is 2π2\pi), derived by limiting polygonal approximations. Geometric constructions with and , as per Euclid's first three postulates, allow precise manipulation of lengths without scales. For instance, Proposition I.3 enables copying a given segment to subtract equal lengths from a longer one, while Proposition I.10 bisects a segment by constructing perpendiculars and equal circles to find the . Proposition I.1 constructs an on a given segment, ensuring all sides equal the base length through circle intersections. These methods preserve length equality, forming the basis for all Euclidean constructions. Congruence and similarity criteria rely heavily on length equalities or proportions. For congruence, the side-angle-side (SAS) criterion (Book I, Proposition 4) states that if two sides and the included angle of one triangle equal those of another, the triangles are congruent, implying equal third sides and angles. The side-side-side (SSS) criterion (Book I, Proposition 8) follows: if all three sides of one triangle equal those of another, the triangles are congruent. For similarity, proportional lengths under equal angles (Book VI) extend these, such as SSS similarity where corresponding sides are proportional.

Non-Euclidean Geometries

In non-Euclidean geometries, the concept of length deviates from the Euclidean framework due to constant nonzero , leading to modified measurements along geodesics, the shortest paths between points. , characterized by negative , exhibits in lengths along geodesics; for instance, the of a of rr is 2πsinhr2\pi \sinh r, which expands exponentially with increasing rr, contrasting the linear growth 2πr2\pi r in . This property arises because parallel geodesics diverge, causing s between them to increase exponentially, as seen in models like the upper half-plane where the between two vertical geodesics separated by a fixed horizontal grows with . Elliptic geometry, with positive , features finite spaces where all s intersect, and lengths are measured along elliptic lines, modeled by great circles on a with antipodal points identified (). The shortest path between two points is the minor arc of the elliptic line connecting them, with distances bounded— in this model from the unit , the maximum distance is π/2\pi/2, corresponding to a quarter of the great circle of 2π2\pi. These paths are longer than the straight-line distances in the embedding , reflecting the geometry's and . The Gauss-Bonnet connects this to boundary lengths: for a region with boundary, the integral of over the area equals 2π2\pi times the minus the sum of interior angles and the integral of geodesic along the boundary, where the latter term involves the total length scaled by . In hyperbolic settings with constant negative K=1K = -1, this implies defect angles in polygons relate directly to areas, indirectly influencing perimeter lengths through geodesic properties. Metric tensors formalize these length elements. In , the line element is ds2=dx2+dy2ds^2 = dx^2 + dy^2, yielding straight-line distances. In the of , it becomes ds2=dx2+dy2(1x2y2)2ds^2 = \frac{dx^2 + dy^2}{(1 - x^2 - y^2)^2}, distorting lengths such that points near the boundary appear farther apart, with geodesics as circular arcs orthogonal to the unit circle. For on the unit (before quotient), the metric is ds2=dθ2+sin2θdϕ2ds^2 = d\theta^2 + \sin^2 \theta \, d\phi^2, where great-circle distances are given by d=arccos(cosθ1cosθ2+sinθ1sinθ2cos(ϕ2ϕ1))d = \arccos(\cos \theta_1 \cos \theta_2 + \sin \theta_1 \sin \theta_2 \cos(\phi_2 - \phi_1)). The ratio of a circle's to its varies with in both geometries, unlike the constant π\pi in ; in , it exceeds π\pi and grows without bound, while in , the analogue πsinrr\pi \frac{\sin r}{r} is less than π\pi and decreases toward 2 as radius approaches π/2\pi/2. The foundations of non-Euclidean geometries were established independently by , who published his work on in 1829, and János Bolyai, who developed similar ideas around 1832 without prior knowledge of Lobachevsky's results. These discoveries challenged Euclid's parallel postulate and paved the way for modern .

Graph Theory and Discrete Structures

In , the concept of length manifests in discrete structures through path metrics, where paths consist of edges connecting vertices. In unweighted graphs, the between two vertices is defined as the minimum number of edges in any path connecting them, providing a combinatorial measure of separation. The graph diameter extends this notion as the maximum such over all pairs of vertices, quantifying the overall "spread" or worst-case connectivity in the structure. These definitions, foundational to , enable analysis of network efficiency and without invoking continuous measures. Weighted graphs introduce edge lengths as non-negative real numbers assigned to edges, representing costs such as time, capacity, or resources. The length of a path in such a graph is the sum of its edge weights, and the shortest path between vertices is the one with minimal total length. This framework generalizes unweighted distances, where each edge implicitly has weight 1, and supports optimization in combinatorial problems. Seminal work established efficient computation of these lengths, emphasizing their role in modeling real-world discrete systems. Dijkstra's algorithm computes shortest paths from a source vertex to all others in weighted graphs with non-negative edge weights. It operates by maintaining a of tentative , initializing the source with distance zero and others with . Iteratively, it extracts the vertex with the smallest tentative distance, marks it as permanently settled, and relaxes the distances to its adjacent vertices by checking if routing through the settled vertex yields a shorter path. This greedy process continues until all vertices are settled, yielding exact shortest lengths in O((V + E) log V) time with efficient priority queues, where V is the number of vertices and E the number of edges. The algorithm's correctness relies on the non-negativity of weights, ensuring no shorter paths are missed after settlement. In computer networks, graph lengths model efficiency, with vertices as routers and edges weighted by (edge count) or latency ( delay). Protocols like RIP use hop counts as lengths to find minimal-hop paths via distance-vector methods, limiting diameters to 15 to prevent infinite loops. More advanced link-state protocols, such as OSPF, employ on latency-weighted graphs to compute global shortest paths, adapting to changes for low-latency . These applications demonstrate how discrete length optimization minimizes data transmission delays in large-scale networks. Hamiltonian paths, which visit each vertex exactly once, relate to length optimization in the traveling salesman problem (TSP), where the goal is to find the minimal total edge weight of such a path forming a cycle. TSP, NP-hard in general, models discrete routing challenges like , with edge lengths as distances or costs. Early exact methods used cutting-plane techniques on integer programs to solve large instances, establishing benchmarks for approximation and heuristic approaches in .

Measure Theory

In measure theory, the concept of length is rigorously formalized through the Lebesgue measure on the real line R\mathbb{R}, providing a foundation for measuring subsets in a way that extends classical notions while handling more general sets. The Lebesgue outer measure mm^*, introduced by Henri Lebesgue, assigns to any subset ERE \subseteq \mathbb{R} the value m(E)=inf{n=1(In)  |  En=1In,  In open intervals},m^*(E) = \inf\left\{ \sum_{n=1}^\infty \ell(I_n) \;\middle|\; E \subseteq \bigcup_{n=1}^\infty I_n, \; I_n \text{ open intervals} \right\},
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