Tangent vector

In differential geometry, a tangent vector at a point p on a smooth manifold M is an element of the tangent space T_p M, which consists of all possible directions in which one can instantaneously move away from p while remaining on the manifold; it can be formally defined as a derivation on the space of smooth functions defined near p, or equivalently as the velocity vector of a smooth curve passing through p.^[1] This concept generalizes the notion of a tangent line to a curve or tangent plane to a surface in Euclidean space, providing a local linear approximation to the manifold at p.^[2] The tangent space T_p M forms a vector space of dimension equal to that of the manifold, with basis vectors corresponding to partial derivatives in local coordinates, allowing tangent vectors to be expressed as linear combinations v = \sum v^i \frac{\partial}{\partial x^i}.^[1] In the context of parametrized surfaces in \mathbb{R}^3, a tangent vector at p is any linear combination of the partial derivative vectors r_u(p) and r_v(p) from a parametrization r(u,v), spanning the tangent plane at p.^[3] These spaces assemble into the tangent bundle TM, a vector bundle over M whose sections are vector fields, which play a central role in describing flows, Lie derivatives, and the geometry of the manifold.^[1] Tangent vectors are foundational in applications ranging from general relativity, where they model worldlines and four-velocities, to computer graphics and robotics for path planning on curved spaces, and they enable the definition of Riemannian metrics that measure lengths and angles intrinsically on the manifold.^[2] In coordinate-free terms, the transformation law under change of charts ensures that tangent vectors are intrinsically defined, independent of the choice of local coordinates.^[4]

Motivation

From Calculus

In multivariable calculus, a tangent vector to a curve arises naturally as the derivative of a parametric representation of the curve in Euclidean space \mathbb{R}^n. Consider a smooth curve \gamma: I \to \mathbb{R}^n, where I is an interval, parameterized by a variable t that may represent time or arc length s. The tangent vector at a point \gamma(t_0) is defined as the limit of secant vectors approximating the curve's direction over small increments \Delta t = h:

\gamma'(t_0) = \lim_{h \to 0} \frac{\gamma(t_0 + h) - \gamma(t_0)}{h}.

This limit captures the instantaneous rate of change, with each component of \gamma'(t_0) being the derivative of the corresponding coordinate function.^[5] A concrete example illustrates this in \mathbb{R}^2. For the parabola \gamma(t) = (t, t^2), the tangent vector is \gamma'(t) = (1, 2t). At t = 1, \gamma'(1) = (1, 2), which points in the direction of the curve's instantaneous motion and has magnitude \sqrt{5}, reflecting the speed along the path. This vector represents the velocity of a particle traversing the curve, combining both directional and scalar information.^[6] Geometrically, the tangent vector provides the best linear approximation to the curve at \gamma(t_0), as the secant vectors converge to it, aligning with the curve's local direction; its magnitude |\gamma'(t_0)| quantifies the speed, equaling 1 if parameterized by arc length. The collection of all scalar multiples of such tangent vectors at a fixed point forms the tangent space there.^[5] The conceptual roots of tangent vectors trace to 19th-century developments in calculus by Carl Friedrich Gauss and Bernhard Riemann, who explored tangents to curves and surfaces in their foundational work on differential geometry. Gauss introduced key ideas like the tangent plane and metric elements for surfaces in his 1827 treatise, while Riemann extended these to abstract spaces in his 1854 lecture, laying groundwork for intrinsic geometry.^[7]

Contravariant Nature

Tangent vectors are contravariant objects, meaning their components transform under a change of coordinates according to the Jacobian matrix of the transformation, in contrast to covariant covectors, which transform according to the inverse Jacobian matrix. This transformation law ensures that the directional information encoded by the tangent vector remains consistent across different coordinate systems.^[8] For instance, consider \mathbb{R}^2 with a linear change of coordinates given by x' = A x, where A is an invertible matrix. A tangent vector v in the original coordinates transforms to v' = A v in the new coordinates. This preserves the invariance of the dot product with a covector \omega, where the covector transforms as \omega' = \omega A^{-1}, such that v \cdot \omega = v' \cdot \omega'.^[8] Conceptually, tangent vectors can be visualized as directed arrows that maintain their physical direction independent of the coordinate frame, whereas covectors, such as gradients, adjust to align with the changing basis to keep inner products invariant. This distinction arises naturally from the derivative of curves in calculus, which behaves as a simple contravariant object. The notion of contravariant vectors was introduced in the framework of tensor analysis by Gregorio Ricci-Curbastro and Tullio Levi-Civita around 1900 to systematically handle calculations in non-Cartesian coordinate systems.

Formal Definition

In Euclidean Space

In Euclidean space \mathbb{R}^n, a tangent vector at a point p \in \mathbb{R}^n is formally defined as an equivalence class of differentiable curves \gamma: (-\epsilon, \epsilon) \to \mathbb{R}^n for some \epsilon > 0 such that \gamma(0) = p, where two curves \gamma and \eta are equivalent if their derivatives agree at t = 0, that is, \gamma'(0) = \eta'(0).^[9] This equivalence class captures the notion of direction and speed at p without depending on the specific parametrization of the curve.^[10] An alternative and commonly used definition identifies the tangent vector with the velocity vector of the curve at t = 0, given by \frac{d\gamma}{dt}\big|_{t=0} \in \mathbb{R}^n.^[11] Explicitly, this velocity is computed as the limit v = \lim_{h \to 0} \frac{\gamma(h) - \gamma(0)}{h}, which yields an element v \in \mathbb{R}^n representing the tangent vector. Under this identification, each equivalence class corresponds uniquely to a vector in \mathbb{R}^n. The set of all tangent vectors at p forms a vector space that is isomorphic to \mathbb{R}^n and has dimension n.^[12] This structure arises naturally because the operations of addition and scalar multiplication on curves induce corresponding operations on their equivalence classes or velocity vectors, preserving the linear algebra of \mathbb{R}^n.^[9]

Tangent Space at a Point

In a differentiable manifold M, the tangent space at a point p \in M, denoted T_p M, is defined as the vector space consisting of all tangent vectors based at p. This space captures the directions in which one can "move" away from p while remaining tangent to M, providing a linear approximation to the manifold near that point. A standard abstract construction of T_p M identifies it with the space of derivations at p. A derivation is a \mathbb{R}-linear map v: C^\infty(M) \to \mathbb{R} from the algebra of smooth real-valued functions on M to the reals, satisfying the Leibniz product rule: for all f, g \in C^\infty(M),

v(fg) = v(f) g(p) + f(p) v(g).

The set of all such derivations forms a vector space under pointwise addition (v + w)(f) = v(f) + w(f) and scalar multiplication (\lambda v)(f) = \lambda v(f), which is precisely T_p M. This approach avoids reliance on embeddings or coordinates, making it intrinsic to the manifold structure. For any v \in T_p M and smooth function f \in C^\infty(M), the application v(f) yields the directional derivative of f at p in the direction specified by v. In the special case of Euclidean space, where M = \mathbb{R}^n, the tangent space satisfies T_p \mathbb{R}^n \cong \mathbb{R}^n via the natural identification with standard partial derivatives, and more generally, \dim(T_p M) = \dim(M) for any manifold M. This framework generalizes the curve-based view of tangent vectors in Euclidean space, where they arise as velocity vectors of smooth curves through p.

Properties

Vector Space Operations

Tangent vectors at a point p on a smooth manifold form a real vector space T_p M, equipped with operations of addition and scalar multiplication that are defined intrinsically using representatives from equivalence classes of smooth curves through p.^[13] To define addition, consider two tangent vectors v, w \in T_p M, each represented by smooth curves \gamma: (-\epsilon, \epsilon) \to M and \delta: (-\epsilon, \epsilon) \to M with \gamma(0) = \delta(0) = p. The sum v + w is the equivalence class of the curve \eta(t) = \gamma(t) + \delta(t), interpreted in a local coordinate chart around p where the addition of points makes sense via the chart map; the velocity \eta'(0) = \gamma'(0) + \delta'(0) ensures the operation is independent of curve representatives.^[13] This construction aligns with the geometric intuition that tangent vectors approximate linear directions, allowing their combination to yield a new direction at p.^[13] Scalar multiplication is similarly defined: for a real scalar c and tangent vector v represented by \gamma, the product c v is the equivalence class of the reparametrized curve \zeta(t) = \gamma(c t), with derivative \zeta'(0) = c \gamma'(0).^[13] This operation scales the "speed" of the curve while preserving the direction, confirming that scalar multiplication acts linearly on the velocities.^[13] The zero vector in T_p M is the equivalence class of the constant curve \gamma(t) = p for all t, whose derivative vanishes, \gamma'(0) = 0; this serves as the additive identity, as adding it to any tangent vector yields the original vector via the curve sum.^[13] These operations are well-defined on the equivalence classes of curves, meaning they do not depend on the choice of representatives, because if two curves define the same tangent vector (same velocity at p), their sums or scalar multiples will have matching velocities.^[13] Moreover, T_p M satisfies all vector space axioms: addition is associative and commutative, scalar multiplication distributes over vector addition and scalar addition, and every element has an additive inverse (defined via -v as the scalar multiple with c = -1).^[13] This structure is verified by showing an isomorphism between the space of tangent vectors and \mathbb{R}^n in local coordinates, where the operations reduce to standard vector addition and scaling.^[13]

Basis and Components

In local coordinates (x^1, \dots, x^n) defined around a point p on a manifold M, the tangent space T_p M admits a natural basis consisting of the partial derivative operators \partial / \partial x^i for i = 1, \dots, n. These basis vectors are defined by their action on smooth functions f: M \to \mathbb{R}, where \partial / \partial x^i (f) = \partial f / \partial x^i, the standard partial derivative in the coordinate chart. A key property is that \partial / \partial x^i (x^j) = \delta^i_j, where \delta^i_j is the Kronecker delta, ensuring the basis vectors distinguish the coordinate functions appropriately.^[14] Any tangent vector v \in T_p M can be uniquely expressed in this coordinate basis as v = v^i \partial / \partial x^i, where the v^i are the components of v and the Einstein summation convention is used over the repeated index i. The components v^i are real numbers determined by the action of v on the coordinate functions, specifically v^i = v(x^i). This representation highlights the vector space structure of T_p M, with the basis providing a linear isomorphism to \mathbb{R}^n.^[15] Under a change of coordinates from (x^1, \dots, x^n) to new coordinates (x'^1, \dots, x'^n), the basis vectors transform according to the inverse Jacobian matrix: \partial / \partial x'^i = (\partial x^j / \partial x'^i) \partial / \partial x^j, again using Einstein summation. Consequently, the components of the tangent vector transform contravariantly: v'^i = (\partial x'^i / \partial x^j) v^j. This ensures that the directional derivative action of v remains invariant under coordinate changes, preserving the intrinsic geometry of the tangent space.^[15]

Advanced Concepts

On Manifolds

In differential geometry, the concept of a tangent vector extends naturally to an n-dimensional smooth manifold M without relying on an embedding in a higher-dimensional Euclidean space. At a point p \in M, a tangent vector can be defined as the velocity vector of a smooth curve \gamma: (-\epsilon, \epsilon) \to M with \gamma(0) = p, where two such curves are equivalent if their velocities agree on all smooth functions, i.e., \frac{d}{dt}(f \circ \gamma)|_{t=0} is the same for every f \in C^\infty(M). Equivalently, a tangent vector v at p is a derivation: a linear map v: C^\infty(M) \to \mathbb{R} satisfying the Leibniz rule v(fg) = f(p) v(g) + g(p) v(f) for all f, g \in C^\infty(M). The set of all such derivations forms the tangent space T_p M, which is an n-dimensional real vector space.^[16] To express tangent vectors in coordinates, an atlas of charts (U, \phi) on M is used, where \phi: U \to \mathbb{R}^n is a diffeomorphism. In such a chart with p \in U, a tangent vector v \in T_p M is identified with an element of T_{\phi(p)} \mathbb{R}^n \cong \mathbb{R}^n via the differential d\phi_p: T_p M \to T_{\phi(p)} \mathbb{R}^n, allowing v to be written locally as v = \sum_{i=1}^n v^i \frac{\partial}{\partial x^i} \big|_p, where v^i are the components and \frac{\partial}{\partial x^i} form a basis. These local representations are glued together consistently across overlapping charts via the transition maps \psi \circ \phi^{-1}, whose Jacobians ensure the components transform contravariantly under coordinate changes. This construction is independent of the choice of atlas, as the smooth structure of M guarantees compatibility.^[16] A concrete example illustrates this intrinsic definition on the 2-sphere S^2, the set of points in \mathbb{R}^3 at distance 1 from the origin. At the north pole p = (0, 0, 1), tangent vectors in the ambient \mathbb{R}^3 appear as horizontal vectors orthogonal to p, such as those lying in the xy-plane. However, the manifold structure allows defining them intrinsically using charts, like stereographic projection from the north pole, where S^2 \setminus \{p\} is diffeomorphic to \mathbb{R}^2 via (x, y, z) \mapsto (x/(1-z), y/(1-z)), and tangent vectors at p are limits of velocities from curves on S^2 without reference to the embedding. This approach highlights how tangent vectors capture directions of motion along the surface itself.^[16] The collection of all tangent spaces T_p M over p \in M forms the tangent bundle TM = \bigcup_{p \in M} T_p M, which is itself a smooth manifold of dimension $2n equipped with a natural projection \pi: TM \to M sending (p, v) to p. Locally, TM is trivialized over chart domains, making it a vector bundle whose fibers are the tangent spaces.^[16]

Applications in Differential Geometry

In differential geometry, tangent vectors play a central role in the construction of vector fields on manifolds. A vector field X on a smooth manifold M assigns to each point p \in M a tangent vector X(p) \in T_p M, forming a smooth section X: M \to TM of the tangent bundle TM, where \pi \circ X = \mathrm{id}_M and \pi: TM \to M is the canonical projection.^[17] These vector fields generate local flows, which are one-parameter families of diffeomorphisms F_t: U_t \to M satisfying the flow property F_{t_1} \circ F_{t_2} = F_{t_1 + t_2} along integral curves \gamma(t) where \dot{\gamma}(t) = X(\gamma(t)), enabling the study of dynamical systems and symmetries on the manifold.^[17] A key operation on vector fields is the Lie bracket [X, Y], defined for smooth vector fields X, Y \in \mathcal{X}(M) by

[X, Y](f) = X(Y(f)) - Y(X(f))

for all smooth functions f \in C^\infty(M), yielding another vector field that quantifies the non-commutativity of their flows.^[18] The Lie bracket satisfies the properties of a Lie algebra structure on \mathcal{X}(M), including bilinearity, skew-symmetry [Y, X] = -[X, Y], and the Jacobi identity, making it essential for analyzing the algebraic structure underlying geometric transformations.^[18] Tangent vectors find significant applications in physics, where they represent velocities of particles constrained to move on a manifold, such as in phase space parameterized by positions and momenta, with the Hamiltonian vector field X_H generating trajectories via \iota_{X_H} \omega = -dH for the symplectic form \omega.^[15] In geometry, parallel transport of tangent vectors along a curve \gamma on M relies on a connection \nabla on the tangent bundle TM, which defines a vector field X along \gamma as parallel if its covariant derivative \nabla_{\dot{\gamma}} X = 0, preserving lengths and angles in the presence of a Riemannian metric and revealing curvature effects, such as rotation upon closing a loop on a sphere.^[19] A prominent example arises on Lie groups, where left-invariant vector fields are constructed by left-translating basis vectors from the tangent space at the identity T_e G; specifically, for V \in T_e G, the field satisfies d(l_g)_e (V) = V_g for all g \in G, with left translation l_g: G \to G, forming a Lie algebra isomorphic to T_e G under the Lie bracket and facilitating the study of group actions and infinitesimal symmetries.^[20]