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Polar coordinate system: definition, properties, and applications

A two-dimensional coordinate system using a distance from a central point and an angle from a reference direction; covers definitions, conversions, common curves, uses, and key properties.

Author: Leandro Alegsa Creation date: November 13, 2022 Last updated: May 22, 2026

en.wikipedia.org · Public domain

The polar coordinate system is a method for locating points in a plane by specifying a distance and an angle rather than horizontal and vertical offsets. One coordinate (the radial coordinate) gives the distance from a fixed point called the pole, and the other (the angular coordinate) gives the direction of the point relative to a chosen reference ray. This representation is especially natural when problems involve rotational symmetry or radial distance, and it complements the more familiar Cartesian (rectangular) coordinates. For a concise introduction see overview.

Basic definitions and notation

A point in the plane is written as (r, θ), where r is the nonnegative or signed radial distance and θ is the angle measured from the polar axis. The pole corresponds to the origin in Cartesian geometry. Angles are usually measured in radians or degrees and are taken modulo full rotations, so θ and θ+2π represent the same direction. For precise coordinate rules and conventions consult conventions.

Conversion between polar and Cartesian coordinates

Polar coordinates relate to Cartesian coordinates (x,y) by simple trigonometric formulas. Given (r, θ):

x = r cos θ
y = r sin θ

Conversely, given (x,y):

r = sqrt(x² + y²)
θ = atan2(y, x), taking care with quadrant and branch choices

These conversions are used in analytic geometry and computer graphics; see conversion notes and numerical details at computation.

Properties and multiple representations

Polar coordinates are not unique. A single point can be represented by infinitely many pairs: (r, θ), (r, θ+2πn) for any integer n, and also by negative r together with θ shifted by π: (−r, θ) = (r, θ+π). The pole itself has r = 0 and any θ. These features are useful in solving equations but require care when interpreting graphs; more on branch choices is available at branching.

Common polar curves and graphing

Many classical plane curves have concise polar equations. Examples:

Circles not necessarily centered at the pole: r = a cos θ + b sin θ.
Spirals such as the Archimedean spiral: r = a + bθ.
Cardioid and limaçon families: r = a + b cos θ or r = a + b sin θ.
Rose curves: r = a cos(nθ) or r = a sin(nθ), producing petal shapes.

Polar graphing typically treats θ as the independent variable and plots r(θ) in the plane; specialized plotting software and analytic techniques are discussed at polar plotting.

Applications and connections

Polar coordinates appear across mathematics, physics and engineering. They simplify problems with circular symmetry such as fields around points, orbital motion, wavefronts, and boundary value problems in polar domains. In complex analysis the polar form z = r e^{iθ} links magnitude and argument directly, a central idea in representing complex numbers; see complex form. Polar methods also underpin polar integration in calculus and coordinate transforms used in partial differential equations and numerical simulation (see applications).

For historical context and further reading about development and standardization of polar methods, consult introductory histories and textbooks at history and references. $r$ $t$

A polar grid of different angles with degrees

History

The terms angle and radius were already used by the ancients in the first millennium BC. The Greek astronomer Hipparchus (190-120 BC) created a table of trigonometric chord functions to find the length of the chord for each angle. With this basis he was able to use polar coordinates to determine the position of certain stars. However, his work covered only a part of the coordinate system.

In his treatise On Spirals, Archimedes describes a spiral line with a function whose radius changes depending on its angle. However, the Greek's work did not yet include a full coordinate system.

There are different descriptions to define the polar coordinate system as part of a formal coordinate system. The whole history on this subject is summarized and explained in the book Origin of Polar Coordinates by the Harvard professor Julian Coolidge. According to it Grégoire de Saint-Vincent and Bonaventura Cavalieri introduced this conception independently of each other in the middle of the 17th century. Saint-Vincent wrote on the subject privately in 1625 and published his work in 1647, while Cavalieri published his elaboration in 1635, with a corrected version appearing in 1653. Cavalieri initially used polar coordinates to solve a problem concerning the area of the Archimedean spiral. Somewhat later, Blaise Pascal used polar coordinates to calculate the length of parabolic angles.

In the work Method of Fluxions (written 1671, published 1736), Sir Isaac Newton considers the transformation between polar coordinates, to which he referred as "Seventh Manner; For Spirals," and nine other coordinate systems.

He was followed by Jacob Bernoulli, who used a system consisting of a straight line and a point on this straight line, which he called polar axis or pole, in the technical journal Acta Eruditorum (1691). In it, the coordinates were defined by the distance from the pole and the angle to the polar axis. Bernoulli's work extended to the formulation of the circle of curvature of curves, which he expressed by the mentioned coordinates.

The term polar coordinates in use today was finally introduced by Gregorio Fontana and used in 18th century Italian writings. Subsequently, George Peacock adopted this term into the English language in 1816 when he translated the work of Sylvestre Lacroix Differential and Integral Calculus into his language.

Alexis-Claude Clairaut, on the other hand, was the first to think about polar coordinates in three dimensions, but it was the Swiss mathematician Leonhard Euler who succeeded in developing them.

Polar coordinates in the plane: circular coordinates

Definition

The polar coordinates of a point in the Euclidean plane (plane polar coordinates) are specified with respect to a coordinate origin (a point in the plane) and a direction (a ray starting at the coordinate origin).

The polar coordinate system is unambiguously defined by the fact that an excellent point, also called pole, forms the origin/zero point of the coordinate system. Furthermore, a ray emanating from it is distinguished as the so-called polar axis. Finally a direction (of two possible), which is perpendicular to this polar axis, must be defined as positive, in order to determine the sense of rotation / the direction of rotation / the orientation. Now an angle, the polar angle, can be defined between any ray passing through the pole and this distinguished polar axis. It is unique only up to integer revolutions around the pole, independently of what is chosen as angle measure for it. On the pole axis itself there is still an arbitrary but fixed scaling to define the radial unit length. Now each pair $(r,\phi )\in \mathbb {R} _{0}^{+}\times \mathbb {R}$ can be uniquely assigned to a point in the plane, where the first component is considered to be the radial length and the second the polar angle. Such a pair of numbers is called (not necessarily unique) polar coordinates of a point in this plane.

Plane polar coordinates (with angles in degrees) and their transformation into Cartesian coordinates

The coordinate , a length, is called radius (in practice also distance) and the coordinate ϕ $\phi$ (polar) angle or, in practice (occasionally) also azimuth.

In mathematics, the counterclockwise angle is usually defined as positive when looking vertically at the plane (clock) from above. So the direction of rotation goes from right to top (and further to the left). As angle measure the radian is preferred as angle unit, because it is then analytically most elegant to handle. The polar axis typically points to the right in graphical representations of the coordinate system.

Conversion between polar coordinates and Cartesian coordinates

Conversion from polar coordinates to Cartesian coordinates

If one chooses a Cartesian coordinate system with the same origin as the polar coordinate system, thereby the in the direction of the polar axis, and finally the positive -axis in the direction of the positive sense of rotation - as shown in the figure above on the right -, the result is for the Cartesian coordinates and a point:

$x=r\cos \varphi$

$y=r\sin \varphi$

Conversion from Cartesian coordinates to polar coordinates

The conversion of Cartesian coordinates into polar coordinates is somewhat more difficult, because mathematically one always depends on a trigonometric inverse function (which does not cover the entire range of values of the solid angle). First, however, the radius can be calculated simply with the Pythagorean theorem as follows:

$r=\sqrt{x^2 + y^2}$

When determining the angle φ two peculiarities of polar coordinates must be taken into account $\varphi$ :

For the angle φ is $\varphi$ not uniquely determined, but could take any real value. For a unique transformation rule, it is often defined to be 0. The following formulas are $r \ne 0$ given under the condition to simplify their derivation and presentation.
For $r \ne 0$ the angle φ is $2\pi$ determined $\varphi$ only to integer multiples of since the angles φ {\displaystyle $\varphi$ and φ $\varphi + 2\pi k$ (for $k \in \Z$ ) describe the same point. For the purpose of a simple and unambiguous transformation rule, the angle φ $\varphi$ is $2\pi$ restricted to a half-open interval of length Usually, depending on the application, the intervals $(-\pi ,\pi ]$ or $[0,2\pi)$ chosen.

For the calculation of φ $\varphi$ any of the equations

$\cos \varphi = \frac x r; \quad \sin \varphi = \frac y r; \quad \tan \varphi = \frac y x$

can be used. However, this does not uniquely determine the angle, even in the interval $(-\pi ,\pi ]$ or $[0,2\pi)$ , because none of the three functions $\sin$ , $\cos$ and $\tan$ is injective in these intervals. Moreover, the last equation is not defined for x=0 Therefore, a case distinction is necessary which depends on which quadrant the point (x,y) is located in, that is, on the signs of and .

Calculation of the angle in the interval [-π, π] or [-180°,180°].

Using the arc tangent, φ can be calculated $\varphi$ as follows in the interval $(-\pi ,\pi ]$ or $(-180^{\circ },180^{\circ }]$ can be determined:

$\varphi ={\begin{cases}\arctan {\frac {y}{x}}&\mathrm {f{\ddot {u}}r} \ x>0\\\left(\arctan {\frac {y}{x}}\right)+\pi &\mathrm {f{\ddot {u}}r} \ x<0,\ y\geq 0\\\left(\arctan {\frac {y}{x}}\right)-\pi &\mathrm {f{\ddot {u}}r} \ x<0,\ y<0\\+\pi /2&\mathrm {f{\ddot {u}}r} \ x=0,\ y>0\\-\pi /2&\mathrm {f{\ddot {u}}r} \ x=0,\ y<0\\\end{cases}}$

Some programming languages (such as Fortran 77) and application programs (such as Microsoft Excel) provide an $\operatorname {arctan2} (x,y)$ with two arguments, which internally accounts for the case distinctions presented and computes φ {\displaystyle $\varphi$ for arbitrary values of and

The same result is obtained if the point (x,y) in the Cartesian plane is considered as a complex number $z=x+\mathrm {i} y$ and the angle

$\varphi =\arg(z)$

$\arg$ calculated using the argument function

With the help of the arc cosine one gets along with only two case distinctions:

$\varphi = \begin{cases} +\arccos\frac{x}{r} & \mathrm{f\ddot ur}\ y\geq 0\\ -\arccos\frac{x}{r} & \mathrm{f\ddot ur}\ y<0 \end{cases}$

By taking advantage of the fact that in a circle a central angle is always twice as large as the corresponding circumferential angle, the argument φ can $\varphi$ also be calculated using the arctangent function with fewer case distinctions:

$\varphi ={\begin{cases}2\arctan {\frac {y}{r+x}}&{\mathrm {f{\ddot u}r}}\ r+x\neq 0\\\pi &{\mathrm {f{\ddot u}r}}\ r+x=0\end{cases}}$

Calculation of the angle in the interval [0, 2π) or [0, 360°)

The calculation of the angle φ $\varphi'$ the interval {\displaystyle $[0,2\pi)$ or $[0^\circ,360^\circ)$ can in principle be done in such a way that the angle is first calculated as described above in the interval $(-\pi ,\pi ]$ calculated and, only if it is negative, is $2\pi$ increased by

$\varphi' = \begin{cases} \varphi + 2\pi & \mathrm{falls}\ \varphi < 0\\ \varphi & \mathrm{sonst} \end{cases}$

By modifying the first formula above, φ $\varphi'$ $[0,2\pi)$ determined directly in the interval as follows:

$\varphi '={\begin{cases}\arctan {\frac {y}{x}}&\mathrm {f{\ddot {u}}r} \ x>0,\ y\geq 0\\\arctan {\frac {y}{x}}+2\pi &\mathrm {f{\ddot {u}}r} \ x>0,\ y<0\\\arctan {\frac {y}{x}}+\pi &\mathrm {f{\ddot {u}}r} \ x<0\\\pi /2&\mathrm {f{\ddot {u}}r} \ x=0,\ y>0\\3\pi /2&\mathrm {f{\ddot {u}}r} \ x=0,\ y<0\\\end{cases}}$

The formula with the arc cosine gets along with only two case distinctions also in this case:

$\varphi '={\begin{cases}\arccos {\frac {x}{r}}&\mathrm {f{\ddot {u}}r} \ y\geq 0\\2\pi -\arccos {\frac {x}{r}}&\mathrm {f{\ddot {u}}r} \ y<0\end{cases}}$

Shifting the angle

In geodetic or other calculations, azimuths φ may differ $\varphi$ with values outside the usual interval φ $\varphi _{\text{min}}\leq \varphi <\varphi _{\text{min}}+2\pi$ lower limit φ $\varphi _{\text{min}}=0$ (or else φ $\varphi _{\text{min}}=-\pi$ ) will result. The equation

$\phi =\varphi -2\pi \cdot {\bigl \lfloor }{\frac {\varphi -\varphi _{\text{min}}}{2\pi }}{\bigr \rfloor }$

shifts φ $\varphi$ to the desired interval, so that ϕ $\phi \in \left[\varphi _{\text{min}},\,\varphi _{\text{min}}+2\pi \right)$ holds. Here $x\mapsto \lfloor x\rfloor$ the floor function rounding to the nearest integer, ⌊ $\lfloor x\rfloor$ so for any real is the largest integer not greater than

Functional determinant

From the conversion formulas from polar coordinates to Cartesian coordinates one obtains for the functional determinant as determinant of the Jacobi matrix:

$\det J=\det {\frac {\partial (x,y)}{\partial (r,\varphi )}}={\begin{vmatrix}{\frac {\partial x}{\partial r}}&{\frac {\partial x}{\partial \varphi }}\\{\frac {\partial y}{\partial r}}&{\frac {\partial y}{\partial \varphi }}\end{vmatrix}}={\begin{vmatrix}\cos \varphi &-r\sin \varphi \\\sin \varphi &r\cos \varphi \end{vmatrix}}=r\cos ^{2}\varphi +r\sin ^{2}\varphi =r$

Area element

With the functional determinant, the result for the area element in polar coordinates is:

$\mathrm dA = \mathrm dx\,\mathrm dy=|J|\,\mathrm dr\,\mathrm d\varphi = r\,\mathrm dr\,\mathrm d\varphi$

As the accompanying figure shows, the area element can be interpreted as a differential rectangle with width $r\cdot \mathrm {d} \varphi$ and height $\mathrm {d} r$ .

Line element

From the above transformation equations

$x=r \cos\varphi$

$y=r \sin\varphi$

$\mathrm dx= \cos\varphi \, \mathrm dr - r \, \sin\varphi \, \mathrm d\varphi$

$\mathrm dy= \sin\varphi \, \mathrm dr + r \, \cos\varphi \, \mathrm d\varphi$

The following applies to the Cartesian line element

$\mathrm ds^2=\mathrm dx^2+\mathrm dy^2\,$

for which in polar coordinates follows:

$\mathrm ds^2=\mathrm dr^2+ r^2 \, \mathrm d\varphi^2$

Velocity and acceleration in polar coordinates

For this purpose, the motion is decomposed into a radial and a perpendicular "transversal" component. For the velocity vector $\dot {\vec r}$ following applies

$\dot{\vec r}=\dot{r}\,\vec e_r + r\dot{\varphi}\,\vec e_\varphi$

with unit vectors $\vec e_r=(\cos(\varphi),\sin(\varphi))$ and $\vec e_\varphi=({-\sin(\varphi)},\cos(\varphi))$ .

For the acceleration $\ddot {\vec r}$ is valid

$\ddot{\vec r}=(\ddot r - r\dot\varphi^2) \,\vec e_r+(2\dot r \dot \varphi + r \ddot \varphi) \,\vec e_{\varphi}.$

Spatial polar coordinates: Cylinder coordinates and spherical coordinates

Cylinder coordinates

Cylinder coordinates or cylindrical coordinates are essentially plane polar coordinates with a third coordinate added. This third coordinate describes the height of a point vertically above (or below) the plane of the polar coordinate system and is generally denoted by The coordinate ρ $\mathbf{\rho}$ now describes the distance of a point from the coordinate origin rather than from the -axis.

Conversion between cylindrical coordinates and Cartesian coordinates

If you align a Cartesian coordinate system so that the axes coincide, the $\varphi =0$ points in the direction φ and the angle φ $\varphi$ from the axis to the increases (is right-directed), then the following conversion formulas result:

$x=\rho\,\cos\varphi$

$y=\rho\,\sin\varphi$

$z=z$

For the conversion of Cartesian coordinates into cylindrical coordinates the same formulas result for ρ $\rho$ and φ $\varphi$ as for polar coordinates.

Basis vectors

$\vec e_\rho = \frac{\frac{\partial \vec r}{\partial \rho}}{\left|\frac{\partial \vec r}{\partial \rho}\right|} = \begin{pmatrix} \cos\varphi \\ \sin\varphi \\ 0 \end{pmatrix},\quad \vec e_\varphi = \frac{\frac{\partial \vec r}{\partial \varphi}}{\left|\frac{\partial \vec r}{\partial \varphi}\right|} = \begin{pmatrix} -\sin\varphi \\ \cos\varphi \\ 0 \end{pmatrix},\quad \vec e_z = \frac{\frac{\partial \vec r}{\partial z}}{\left|\frac{\partial \vec r}{\partial z}\right|} = \begin{pmatrix} 0 \\ 0 \\ 1 \end{pmatrix}.$

The basis vectors $\vec e_\rho$ , $\vec e_\varphi$ and ${\vec {e}}_{z}$ are orthonormal to each other and form a right system in this order.

Functional determinant

The addition of the rectilinear coordinates not affect the functional determinant:

$\det {\frac {\partial (x,y,z)}{\partial (\rho ,\varphi ,z)}}={\begin{vmatrix}\cos \varphi &-\rho \sin \varphi &0\\\sin \varphi &\rho \cos \varphi &0\\0&0&1\end{vmatrix}}=\rho$

Consequently, for the volume element $\mathrm {d} V$ :

$\mathrm{d}V=\rho \,\mathrm{d}\rho\, \mathrm{d}\varphi \, \mathrm{d}z$

This also corresponds to the square root of the amount of the determinant of the metric tensor, with the help of which the coordinate transformation can be calculated (see Laplace-Beltrami operator).

${\begin{pmatrix}\mathrm {d} x\\\mathrm {d} y\\\mathrm {d} z\end{pmatrix}}={\begin{pmatrix}\cos \varphi &-\rho \sin \varphi &0\\\sin \varphi &\rho \cos \varphi &0\\0&0&1\end{pmatrix}}\cdot {\begin{pmatrix}\mathrm {d} \rho \\\mathrm {d} \varphi \\\mathrm {d} z\end{pmatrix}}$

${\begin{pmatrix}\mathrm {d} \rho \\\mathrm {d} \varphi \\\mathrm {d} z\end{pmatrix}}={\begin{pmatrix}{\frac {x}{\sqrt {x^{2}+y^{2}}}}&{\frac {y}{\sqrt {x^{2}+y^{2}}}}&0\\{\frac {-y}{x^{2}+y^{2}}}&{\frac {x}{x^{2}+y^{2}}}&0\\0&0&1\end{pmatrix}}\cdot {\begin{pmatrix}\mathrm {d} x\\\mathrm {d} y\\\mathrm {d} z\end{pmatrix}}$

Vector Analysis

The following representations of the Nabla operator can be applied in the given form directly to scalar or vector-valued fields in cylindrical coordinates. The procedure is analogous to the vector analysis in Cartesian coordinates.

Gradient

The representation of the gradient transfers from Cartesian to cylindrical coordinates as follows:

$\nabla f={\frac {\partial f}{\partial \rho }}{\vec {e}}_{\rho }+{\frac {1}{\rho }}{\frac {\partial f}{\partial \varphi }}{\vec {e}}_{\varphi }+{\frac {\partial f}{\partial z}}{\vec {e}}_{z}$

Divergence

In the case of divergence, additional terms are added, resulting from the derivatives of the unit vectors depending on ρ $\rho$ , φ $\varphi$ and dependent unit vectors:

$\nabla \cdot {\vec {A}}={\frac {1}{\rho }}{\frac {\partial }{\partial \rho }}(\rho A_{\rho })+{\frac {1}{\rho }}{\frac {\partial A_{\varphi }}{\partial \varphi }}+{\frac {\partial A_{z}}{\partial z}}$

Rotation

The representation of the rotation is as follows:

$\nabla \times {\vec {A}}=\left({\frac {1}{\rho }}{\frac {\partial A_{z}}{\partial \varphi }}-{\frac {\partial A_{\varphi }}{\partial z}}\right){\vec {e}}_{\rho }+\left({\frac {\partial A_{\rho }}{\partial z}}-{\frac {\partial A_{z}}{\partial \rho }}\right){\vec {e}}_{\varphi }+{\frac {1}{\rho }}\left({\frac {\partial }{\partial \rho }}(\rho A_{\varphi })-{\frac {\partial A_{\rho }}{\partial \varphi }}\right){\vec {e}}_{z}$

Spherical coordinates

→ Main article: Spherical coordinates

Spherical coordinates are essentially plane polar coordinates with a third coordinate added. This is done by specifying an angle θ $\theta \in [0,\pi ]$ for the third axis. This third coordinate describes the angle between the vector ${\vec {r}}$ to the point and the -axis. θ $\theta$ is zero exactly when on the -axis.

n-dimensional polar coordinates

It is also possible to give a generalization of polar coordinates with $n \ge 3$ for an -dimensional space with Cartesian coordinates $x_{i}\in \mathbb {R}$ for $i=1,\dotsc ,n$ specify. For this purpose, one introduces for each new dimension (inductive construction over same) another angle $\vartheta_{n-2}\in [0,\pi]$ which is the angle between the vector $x\in \R^n$ and the new positive coordinate axis for $x_{n}$ . With the same procedure the angular coordinate of the 2-dimensional space can be constructed $\varphi =\vartheta _{0}\in [0,\pi ]$ inductively from the number line in a consistent way by means of φ provided that for the radial coordinate also negative values, thus whole $\mathbb {R}$ would be allowed.

Conversion to Cartesian coordinates

A conversion rule from these coordinates to Cartesian coordinates would then be:

${\begin{array}{lcr}x_{1}&=&r\ \cos \varphi \ \sin \vartheta _{1}\ \sin \vartheta _{2}\ \cdots \ \sin \vartheta _{n-3}\ \sin \vartheta _{n-2}\\x_{2}&=&r\ \sin \varphi \ \sin \vartheta _{1}\ \sin \vartheta _{2}\ \cdots \ \sin \vartheta _{n-3}\ \sin \vartheta _{n-2}\\x_{3}&=&r\ \cos \vartheta _{1}\ \sin \vartheta _{2}\ \cdots \ \sin \vartheta _{n-3}\ \sin \vartheta _{n-2}\\x_{4}&=&r\ \cos \vartheta _{2}\ \cdots \ \sin \vartheta _{n-3}\ \sin \vartheta _{n-2}\\\vdots &\vdots &\vdots \qquad \qquad \qquad \quad \\x_{n-1}&=&r\ \cos \vartheta _{n-3}\ \sin \vartheta _{n-2}\\x_{n}&=&r\ \cos \vartheta _{n-2}\end{array}}$

As can be shown, these polar coordinates change into the ordinary polar coordinates for the case n=2 and into the spherical coordinates for n=3

Functional determinant

The functional determinant of the transformation from spherical coordinates to Cartesian coordinates is:

$\det {\frac {\partial (x_{1},\dotsc ,x_{n})}{\partial (r,\vartheta _{1},\dotsc ,\vartheta _{n-2},\varphi )}}=r^{n-1}\sin \vartheta _{1}\left(\sin \vartheta _{2}\right)^{2}\dotsm \left(\sin \vartheta _{n-2}\right)^{n-2}$

Thus, the -dimensional volume element is:

${\begin{matrix}\mathrm {d} V&=&r^{n-1}\sin \vartheta _{1}\left(\sin \vartheta _{2}\right)^{2}\dotsm \left(\sin \vartheta _{n-2}\right)^{n-2}\mathrm {d} r\ \mathrm {d} \varphi \ \mathrm {d} \vartheta _{1}\dotsm \mathrm {d} \vartheta _{n-2}\\&=&r^{n-1}\ \mathrm {d} r\ \mathrm {d} \varphi \ \prod \limits _{j=1}^{n-2}(\sin \vartheta _{j})^{j}\ \mathrm {d} \vartheta _{j}\end{matrix}}.$

Note: -dimensional cylindrical coordinates are simply a product / composition -dimensional spherical coordinates and (n-k) -dimensional Cartesian coordinates with $k\geq 2$ and $n-k\geq 1$ .