Hubbry Logo
Analytic geometryAnalytic geometryMain
Open search
Analytic geometry
Community hub
Analytic geometry
logo
7 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Analytic geometry
Analytic geometry
from Wikipedia

In mathematics, analytic geometry, also known as coordinate geometry or Cartesian geometry, is the study of geometry using a coordinate system. This contrasts with synthetic geometry.

Analytic geometry is used in physics and engineering, and also in aviation, rocketry, space science, and spaceflight. It is the foundation of most modern fields of geometry, including algebraic, differential, discrete and computational geometry.

Usually the Cartesian coordinate system is applied to manipulate equations for planes, straight lines, and circles, often in two and sometimes three dimensions. Geometrically, one studies the Euclidean plane (two dimensions) and Euclidean space. As taught in school books, analytic geometry can be explained more simply: it is concerned with defining and representing geometric shapes in a numerical way and extracting numerical information from shapes' numerical definitions and representations. That the algebra of the real numbers can be employed to yield results about the linear continuum of geometry relies on the Cantor–Dedekind axiom.

History

[edit]

Ancient Greece

[edit]

The Greek mathematician Menaechmus solved problems and proved theorems by using a method that had a strong resemblance to the use of coordinates and it has sometimes been maintained that he had introduced analytic geometry.[1]

Apollonius of Perga, in On Determinate Section, dealt with problems in a manner that may be called an analytic geometry of one dimension; with the question of finding points on a line that were in a ratio to the others.[2] Apollonius in the Conics further developed a method that is so similar to analytic geometry that his work is sometimes thought to have anticipated the work of Descartes by some 1800 years. His application of reference lines, a diameter and a tangent is essentially no different from our modern use of a coordinate frame, where the distances measured along the diameter from the point of tangency are the abscissas, and the segments parallel to the tangent and intercepted between the axis and the curve are the ordinates. He further developed relations between the abscissas and the corresponding ordinates that are equivalent to rhetorical equations (expressed in words) of curves. However, although Apollonius came close to developing analytic geometry, he did not manage to do so since he did not take into account negative magnitudes and in every case the coordinate system was superimposed upon a given curve a posteriori instead of a priori. That is, equations were determined by curves, but curves were not determined by equations. Coordinates, variables, and equations were subsidiary notions applied to a specific geometric situation.[3]

Persia

[edit]

The 11th-century Persian mathematician Omar Khayyam saw a strong relationship between geometry and algebra and was moving in the right direction when he helped close the gap between numerical and geometric algebra[4] with his geometric solution of the general cubic equations,[5] but the decisive step came later with Descartes.[4] Omar Khayyam is credited with identifying the foundations of algebraic geometry, and his book Treatise on Demonstrations of Problems of Algebra (1070), which laid down the principles of analytic geometry, is part of the body of Persian mathematics that was eventually transmitted to Europe.[6] Because of his thoroughgoing geometrical approach to algebraic equations, Khayyam can be considered a precursor to Descartes in the invention of analytic geometry.[7]: 248 

Western Europe

[edit]

Analytic geometry was independently invented by René Descartes and Pierre de Fermat,[8][9] although Descartes is sometimes given sole credit.[10][11] Cartesian geometry, the alternative term used for analytic geometry, is named after Descartes.

Descartes made significant progress with the methods in an essay titled La Géométrie (Geometry), one of the three accompanying essays (appendices) published in 1637 together with his Discourse on the Method for Rightly Directing One's Reason and Searching for Truth in the Sciences, commonly referred to as Discourse on Method. La Geometrie, written in his native French tongue, and its philosophical principles, provided a foundation for calculus in Europe. Initially the work was not well received, due, in part, to the many gaps in arguments and complicated equations. Only after the translation into Latin and the addition of commentary by van Schooten in 1649 (and further work thereafter) did Descartes's masterpiece receive due recognition.[12]

Pierre de Fermat also pioneered the development of analytic geometry. Although not published in his lifetime, a manuscript form of Ad locos planos et solidos isagoge (Introduction to Plane and Solid Loci) was circulating in Paris in 1637, just prior to the publication of Descartes' Discourse.[13][14][15] Clearly written and well received, the Introduction also laid the groundwork for analytical geometry. The key difference between Fermat's and Descartes' treatments is a matter of viewpoint: Fermat always started with an algebraic equation and then described the geometric curve that satisfied it, whereas Descartes started with geometric curves and produced their equations as one of several properties of the curves.[12] As a consequence of this approach, Descartes had to deal with more complicated equations and he had to develop the methods to work with polynomial equations of higher degree. It was Leonhard Euler who first applied the coordinate method in a systematic study of space curves and surfaces.

Coordinates

[edit]
Illustration of a Cartesian coordinate plane. Four points are marked and labeled with their coordinates: (2,3) in green, (−3,1) in red, (−1.5,−2.5) in blue, and the origin (0,0) in purple.

In analytic geometry, the plane is given a coordinate system, by which every point has a pair of real number coordinates. Similarly, Euclidean space is given coordinates where every point has three coordinates. The value of the coordinates depends on the choice of the initial point of origin. There are a variety of coordinate systems used, but the most common are the following:[16]

Cartesian coordinates (in a plane or space)

[edit]

The most common coordinate system to use is the Cartesian coordinate system, where each point has an x-coordinate representing its horizontal position, and a y-coordinate representing its vertical position. These are typically written as an ordered pair (xy). This system can also be used for three-dimensional geometry, where every point in Euclidean space is represented by an ordered triple of coordinates (xyz).

Polar coordinates (in a plane)

[edit]

In polar coordinates, every point of the plane is represented by its distance r from the origin and its angle θ, with θ normally measured counterclockwise from the positive x-axis. Using this notation, points are typically written as an ordered pair (r, θ). One may transform back and forth between two-dimensional Cartesian and polar coordinates by using these formulae: This system may be generalized to three-dimensional space through the use of cylindrical or spherical coordinates.

Cylindrical coordinates (in a space)

[edit]

In cylindrical coordinates, every point of space is represented by its height z, its radius r from the z-axis and the angle θ its projection on the xy-plane makes with respect to the horizontal axis.

Spherical coordinates (in a space)

[edit]

In spherical coordinates, every point in space is represented by its distance ρ from the origin, the angle θ its projection on the xy-plane makes with respect to the horizontal axis, and the angle φ that it makes with respect to the z-axis. The names of the angles are often reversed in physics.[16]

Equations and curves

[edit]

In analytic geometry, any equation involving the coordinates specifies a subset of the plane, namely the solution set for the equation, or locus. For example, the equation y = x corresponds to the set of all the points on the plane whose x-coordinate and y-coordinate are equal. These points form a line, and y = x is said to be the equation for this line. In general, linear equations involving x and y specify lines, quadratic equations specify conic sections, and more complicated equations describe more complicated figures.[17]

Usually, a single equation corresponds to a curve on the plane. This is not always the case: the trivial equation x = x specifies the entire plane, and the equation x2 + y2 = 0 specifies only the single point (0, 0). In three dimensions, a single equation usually gives a surface, and a curve must be specified as the intersection of two surfaces (see below), or as a system of parametric equations.[18] The equation x2 + y2 = r2 is the equation for any circle centered at the origin (0, 0) with a radius of r.

Lines and planes

[edit]

Lines in a Cartesian plane, or more generally, in affine coordinates, can be described algebraically by linear equations. In two dimensions, the equation for non-vertical lines is often given in the slope-intercept form: where:

In a manner analogous to the way lines in a two-dimensional space are described using a point-slope form for their equations, planes in a three dimensional space have a natural description using a point in the plane and a vector orthogonal to it (the normal vector) to indicate its "inclination".

Specifically, let be the position vector of some point , and let be a nonzero vector. The plane determined by this point and vector consists of those points , with position vector , such that the vector drawn from to is perpendicular to . Recalling that two vectors are perpendicular if and only if their dot product is zero, it follows that the desired plane can be described as the set of all points such that (The dot here means a dot product, not scalar multiplication.) Expanded this becomes which is the point-normal form of the equation of a plane.[citation needed] This is just a linear equation: Conversely, it is easily shown that if a, b, c and d are constants and a, b, and c are not all zero, then the graph of the equation is a plane having the vector as a normal.[citation needed] This familiar equation for a plane is called the general form of the equation of the plane.[19]

In three dimensions, lines can not be described by a single linear equation, so they are frequently described by parametric equations: where:

  • x, y, and z are all functions of the independent variable t which ranges over the real numbers.
  • (x0, y0, z0) is any point on the line.
  • a, b, and c are related to the slope of the line, such that the vector (a, b, c) is parallel to the line.

Conic sections

[edit]
A hyperbola and its conjugate hyperbola

In the Cartesian coordinate system, the graph of a quadratic equation in two variables is always a conic section – though it may be degenerate, and all conic sections arise in this way. The equation will be of the form As scaling all six constants yields the same locus of zeros, one can consider conics as points in the five-dimensional projective space

The conic sections described by this equation can be classified using the discriminant[20]

If the conic is non-degenerate, then:

  • if , the equation represents an ellipse;
    • if and , the equation represents a circle, which is a special case of an ellipse;
  • if , the equation represents a parabola;
  • if , the equation represents a hyperbola;

Quadric surfaces

[edit]

A quadric, or quadric surface, is a 2-dimensional surface in 3-dimensional space defined as the locus of zeros of a quadratic polynomial. In coordinates x1, x2,x3, the general quadric is defined by the algebraic equation[21]

Quadric surfaces include ellipsoids (including the sphere), paraboloids, hyperboloids, cylinders, cones, and planes.

Distance and angle

[edit]
The distance formula on the plane follows from the Pythagorean theorem.

In analytic geometry, geometric notions such as distance and angle measure are defined using formulas. These definitions are designed to be consistent with the underlying Euclidean geometry. For example, using Cartesian coordinates on the plane, the distance between two points (x1y1) and (x2y2) is defined by the formula which can be viewed as a version of the Pythagorean theorem. Similarly, the angle that a line makes with the horizontal can be defined by the formula where m is the slope of the line.

In three dimensions, distance is given by the generalization of the Pythagorean theorem: while the angle between two vectors is given by the dot product. The dot product of two Euclidean vectors A and B is defined by[22] where θ is the angle between A and B.

Transformations

[edit]
a) y = f(x) = |x|       b) y = f(x+3)       c) y = f(x)-3       d) y = 1/2 f(x)

Transformations are applied to a parent function to turn it into a new function with similar characteristics.

The graph of is changed by standard transformations as follows:

  • Changing to moves the graph to the right units.
  • Changing to moves the graph up units.
  • Changing to stretches the graph horizontally by a factor of . (think of the as being dilated)
  • Changing to stretches the graph vertically.
  • Changing to and changing to rotates the graph by an angle .

There are other standard transformation not typically studied in elementary analytic geometry because the transformations change the shape of objects in ways not usually considered. Skewing is an example of a transformation not usually considered. For more information, consult the Wikipedia article on affine transformations.

For example, the parent function has a horizontal and a vertical asymptote, and occupies the first and third quadrant, and all of its transformed forms have one horizontal and vertical asymptote, and occupies either the 1st and 3rd or 2nd and 4th quadrant. In general, if , then it can be transformed into . In the new transformed function, is the factor that vertically stretches the function if it is greater than 1 or vertically compresses the function if it is less than 1, and for negative values, the function is reflected in the -axis. The value compresses the graph of the function horizontally if greater than 1 and stretches the function horizontally if less than 1, and like , reflects the function in the -axis when it is negative. The and values introduce translations, , vertical, and horizontal. Positive and values mean the function is translated to the positive end of its axis and negative meaning translation towards the negative end.

Transformations can be applied to any geometric equation whether or not the equation represents a function. Transformations can be considered as individual transactions or in combinations.

Suppose that is a relation in the plane. For example, is the relation that describes the unit circle.

Finding intersections of geometric objects

[edit]

For two geometric objects P and Q represented by the relations and the intersection is the collection of all points which are in both relations.[23]

For example, might be the circle with radius 1 and center : and might be the circle with radius 1 and center . The intersection of these two circles is the collection of points which make both equations true. Does the point make both equations true? Using for , the equation for becomes or which is true, so is in the relation . On the other hand, still using for the equation for becomes or which is false. is not in so it is not in the intersection.

The intersection of and can be found by solving the simultaneous equations:

Traditional methods for finding intersections include substitution and elimination.

Substitution: Solve the first equation for in terms of and then substitute the expression for into the second equation:

We then substitute this value for into the other equation and proceed to solve for :

Next, we place this value of in either of the original equations and solve for :

So our intersection has two points:

Elimination: Add (or subtract) a multiple of one equation to the other equation so that one of the variables is eliminated. For our current example, if we subtract the first equation from the second we get . The in the first equation is subtracted from the in the second equation leaving no term. The variable has been eliminated. We then solve the remaining equation for , in the same way as in the substitution method:

We then place this value of in either of the original equations and solve for :

So our intersection has two points:

For conic sections, as many as 4 points might be in the intersection.

Finding intercepts

[edit]

One type of intersection which is widely studied is the intersection of a geometric object with the and coordinate axes.

The intersection of a geometric object and the -axis is called the -intercept of the object. The intersection of a geometric object and the -axis is called the -intercept of the object.

For the line , the parameter specifies the point where the line crosses the axis. Depending on the context, either or the point is called the -intercept.

Geometric axis

[edit]

Axis in geometry is the perpendicular line to any line, object or a surface.

Also for this may be used the common language use as a: normal (perpendicular) line, otherwise in engineering as axial line.

In geometry, a normal is an object such as a line or vector that is perpendicular to a given object. For example, in the two-dimensional case, the normal line to a curve at a given point is the line perpendicular to the tangent line to the curve at the point.

In the three-dimensional case a surface normal, or simply normal, to a surface at a point P is a vector that is perpendicular to the tangent plane to that surface at P. The word "normal" is also used as an adjective: a line normal to a plane, the normal component of a force, the normal vector, etc. The concept of normality generalizes to orthogonality.

Spherical and nonlinear planes and their tangents

[edit]

Tangent is the linear approximation of a spherical or other curved or twisted line of a function.

Tangent lines and planes

[edit]

In geometry, the tangent line (or simply tangent) to a plane curve at a given point is the straight line that "just touches" the curve at that point. Informally, it is a line through a pair of infinitely close points on the curve. More precisely, a straight line is said to be a tangent of a curve y = f(x) at a point x = c on the curve if the line passes through the point (c, f(c)) on the curve and has slope f'(c) where f' is the derivative of f. A similar definition applies to space curves and curves in n-dimensional Euclidean space.

As it passes through the point where the tangent line and the curve meet, called the point of tangency, the tangent line is "going in the same direction" as the curve, and is thus the best straight-line approximation to the curve at that point.

Similarly, the tangent plane to a surface at a given point is the plane that "just touches" the surface at that point. The concept of a tangent is one of the most fundamental notions in differential geometry and has been extensively generalized; see Tangent space.

See also

[edit]

Notes

[edit]

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia
from Grokipedia
Analytic geometry, also known as coordinate geometry or Cartesian geometry, is a branch of that applies algebraic methods, particularly through coordinate systems, to analyze and describe geometric shapes and relationships in the plane and . It represents points, lines, curves, and surfaces using ordered pairs or triples of real numbers, enabling the translation of geometric problems into algebraic equations that can be solved using arithmetic operations. This approach contrasts with , which relies on axiomatic proofs without coordinates, by incorporating numerical measures and computational tools for precise analysis. The foundations of analytic geometry were laid in the early 17th century by French mathematicians (1596–1650) and (1607–1665), who independently developed methods to link algebra and geometry. Descartes formalized the system in his 1637 treatise , an appendix to Discours de la méthode, where he introduced the Cartesian coordinate plane with perpendicular axes intersecting at the origin, allowing points to be denoted as (x, y). Fermat, in unpublished manuscripts from around 1636 (published posthumously in 1679), contributed by using coordinates to study curves, tangents, and maxima/minima, laying groundwork for through algebraic optimization. Their innovations resolved ancient problems, such as Pappus's locus theorem, which had puzzled geometers for over 1,800 years, by algebraic means. Central to analytic geometry is the , which divides the plane into four quadrants and uses the distance formula—derived from the —√[(x₂ - x₁)² + (y₂ - y₁)²] to measure distances between points (x₁, y₁) and (x₂, y₂). Basic geometric objects are represented by equations: a straight line by Ax + By + C = 0 or y = mx + b (where m is the ), a by (x - h)² + (y - k)² = r², and conic sections like ellipses and parabolas through quadratic forms. This algebraic framework extends to three dimensions with (x, y, z) coordinates and supports vector operations, such as addition and , to quantify . Analytic geometry's significance lies in its unification of and , providing a quantitative basis for fields like , physics, and . It enabled advancements in studying curves, optimization, and motion, influencing the development of modern by making geometry computable and applicable to real-world problems, such as analysis and . Today, it remains essential in education and research, bridging with applied sciences.

History

Ancient and medieval developments

The foundations of analytic geometry trace back to ancient Greek mathematicians who developed synthetic geometric methods for constructions and the study of curves, laying essential groundwork without the use of coordinates. , in his seminal work Elements composed around 300 BCE, systematized plane geometry through axiomatic proofs and constructions, including theorems on lines, circles, and proportions that emphasized intersections and ratios as tools for solving geometric problems. Building on this, advanced the study of conic sections in his eight-book treatise Conics around 200 BCE, employing purely synthetic techniques to define ellipses, parabolas, and hyperbolas via their geometric properties, tangents, and diameters, which prefigured later analytic treatments of curves. During the medieval Islamic Golden Age, Persian scholars integrated algebra with geometry, creating proto-analytic approaches to solve equations representing spatial configurations. Muhammad ibn Musa al-Khwarizmi, in his Kitab al-Jabr wa'l-Muqabala around 820 CE, provided geometric proofs for quadratic equations, such as those modeling inheritance divisions or land measurements, by completing squares and using visual rearrangements to link algebraic operations to areas and lengths. Omar Khayyam extended this in his Treatise on Demonstration of Problems of Algebra circa 1070 CE, developing a geometric method to solve cubic equations by finding intersections of conic sections like parabolas and circles, classifying equation types and recognizing multiple positive roots through these constructions. These ancient and medieval innovations shifted from purely synthetic toward hybrid algebraic-geometric methods, using ratios and curve intersections to address problems that anticipated the explicit coordinate systems of analytic geometry in the early .

Early modern innovations

The marked the formal emergence of analytic geometry in , driven by advancements in algebra during the and the limitations of traditional , which relied on axiomatic proofs and constructions without algebraic tools. Synthetic methods, inherited from traditions, struggled with complex curves and lacked a systematic way to handle higher-degree equations, prompting mathematicians to seek algebraic integrations for greater precision and generality. This shift was influenced by the symbolic algebra developed by in the late , which provided a notation for unknowns and operations that could be applied to geometric forms. Pierre de Fermat independently pioneered coordinate-based methods around 1630, predating widespread publication but laying foundational work in analytic geometry. In manuscripts such as his Introduction to Plane and Solid Loci, Fermat used a system of coordinates—assigning numerical values to points along axes—to determine tangents to curves and find maxima and minima, effectively treating geometric problems as algebraic ones. He demonstrated this approach by linking algebraic equations directly to geometric loci, including early applications to conic sections, where equations described the paths of these curves reinterpret ancient Greek conics in a coordinate framework. Fermat's techniques, shared privately with contemporaries like , emphasized adequacy in algebraic manipulation over rigorous proof, reflecting the era's exploratory spirit. René Descartes formalized and publicized these ideas in his 1637 treatise , appended to Discours de la méthode, where he introduced what became known as Cartesian coordinates to solve geometric problems algebraically. Descartes proposed representing points in the plane by ordered pairs of numbers relative to fixed axes, allowing lines, circles, and other figures to be expressed as equations, thus unifying algebra and geometry under a single framework. This innovation enabled the classification of curves by their algebraic degrees and facilitated the of construction problems that with and deemed impossible, such as duplicating the or trisecting angles—ultimately aiding in the proof of their impossibility using those tools, while allowing more general constructions involving curves. Descartes' work built on Fermat's but emphasized a philosophical method of analysis, reducing complex figures to simpler ones through coordinates, and it spurred immediate applications in and during the .

19th and 20th century advancements

In the early 19th century, advanced analytic geometry by providing a geometric interpretation of complex numbers as points in the plane, enabling their use in solving geometric problems such as rotations and conformal mappings. This approach, detailed in his 1831 work Theoria residuorum biquadraticorum, transformed complex coordinates into a powerful tool for extending to non-real domains. Concurrently, contributed to by introducing barycentric coordinates in his 1827 book Der barycentrische Calcül, which employed to unify points at and facilitate transformations in . These innovations allowed analytic methods to handle perspective and incidence relations more elegantly, laying groundwork for modern projective techniques. Midway through the 19th century, William Rowan Hamilton introduced quaternions in 1843 as a four-dimensional extension of complex numbers, specifically designed to represent rotations in three-dimensional space. Hamilton's quaternions, motivated by the need for an algebraic structure beyond pairs for spatial geometry, provided a non-commutative multiplication that efficiently parameterized 3D orientations without singularities, as outlined in his 1844 paper to the Royal Irish Academy. Building on this, Josiah Willard Gibbs developed vector analysis in the 1880s, formalizing vectors as directed quantities in Euclidean space to simplify geometric computations like cross products and divergences. Gibbs's privately printed notes from 1881–1884, later expanded in the 1901 textbook Vector Analysis co-authored with Edwin Bidwell Wilson, integrated scalar and vector fields into analytic frameworks, enhancing the treatment of multidimensional geometry. Riemann's mid-19th-century work further bridged analytic geometry with through his 1854 lecture, "Über die Hypothesen, welche der Geometrie zu Grunde liegen," where he generalized coordinates to curved spaces via metrics, enabling the study of intrinsic geometry on manifolds. This Riemannian approach, which used analytic tools like tensor fields to describe curvature without embedding in higher dimensions, profoundly influenced 20th-century developments in and . In the 20th century, analytic geometry evolved computationally, particularly in , where algorithms for coordinate transformations and projections emerged in the . Pioneering efforts, such as Ivan Sutherland's 1963 system, applied analytic coordinate systems to interactive design, while subsequent advancements in the incorporated vector methods for rendering and hidden-surface removal, solidifying analytic geometry's role in digital visualization.

Coordinate Systems

Cartesian coordinates

Cartesian coordinates, also known as rectangular coordinates, form the foundational system in analytic geometry for specifying the position of points in Euclidean space using ordered numerical values relative to perpendicular axes. In two dimensions, each point in the plane is uniquely identified by an ordered pair (x,y)(x, y), where xx measures the signed distance from the origin along the horizontal x-axis, and yy measures the signed distance along the vertical y-axis. The origin, denoted (0,0)(0, 0), is the intersection point of the x-axis and y-axis, which are mutually perpendicular lines serving as reference directions. Unit vectors i^\hat{i} and j^\hat{j} define the positive directions along these axes, with i^\hat{i} pointing to the right and j^\hat{j} pointing upward, providing a basis for vector representations in the plane. In three dimensions, the system extends to ordered triples (x,y,z)(x, y, z), where zz represents the signed distance from the xy-plane along the z-axis, which is perpendicular to the plane formed by the x- and y-axes. The origin is (0,0,0)(0, 0, 0), and the unit vectors i^\hat{i}, j^\hat{j}, and k^\hat{k} correspond to the positive directions of the x-, y-, and z-axes, respectively, forming an for space. This coordinate framework, introduced by in his 1637 work , enables the precise algebraic description of spatial locations. Points in the Cartesian plane are plotted by moving horizontally from the origin by the x-value and then vertically by the y-value, allowing visualization of geometric figures through a grid of coordinates. Functions of the form y=f(x)y = f(x) are graphed by selecting values of xx and corresponding yy-values to plot points that connect into a , representing the relation between variables. The confirms whether such a graph defines yy as a single-valued function of xx: if any vertical line intersects the graph at most once, it passes the test and represents a function. Geometric elements like lines in the plane are expressed algebraically in the general form ax+by+c=0ax + by + c = 0, where aa, bb, and cc are real constants with aa and bb not both zero, encapsulating all points satisfying the equation. In three dimensions, planes are similarly represented by ax+by+cz+d=0ax + by + cz + d = 0, with constants aa, bb, cc, and dd where aa, bb, and cc are not all zero. These forms facilitate the and manipulation of shapes through linear equations. The core advantage of Cartesian coordinates lies in their ability to transform geometric problems into algebraic ones, as pioneered by Descartes, permitting solutions via substitution, elimination, or matrix operations that were previously intractable in pure . This algebraic-geometric synthesis revolutionized by enabling systematic of curves and surfaces through coordinate equations.

Curvilinear coordinates

Curvilinear coordinates offer parametrizations that align with the natural symmetries of curved or rotationally symmetric geometries, providing simpler equations compared to the rectilinear Cartesian system, which suits linear problems. These systems replace straight-line axes with radial, angular, or combined parameters, facilitating analysis in contexts like circles, cylinders, and spheres. In two dimensions, polar coordinates specify points using a radial r0r \geq 0 from the origin and an angular coordinate θ\theta, typically ranging from 0 to 2π2\pi. The relations to Cartesian coordinates are x=rcosθx = r \cos \theta and y=rsinθy = r \sin \theta, with the inverse given by r=x2+y2r = \sqrt{x^2 + y^2}
Add your contribution
Related Hubs
User Avatar
No comments yet.