Linear subspace
Definition
Let be a field and let be a vector space over . A linear subspace of is a subset with these three properties:
- .
- If , then .
- If and , then .
Remarks
With the operations of , a subspace is itself a vector space over . The sets and are subspaces of . The lines through the origin are the one-dimensional subspaces of ; a line that misses the origin is not a subspace. The kernel and the image of a linear map are subspaces.
Explanations
L1 human
A subspace is a smaller vector space inside a bigger one. We cannot leave it by adding its vectors or by scaling them. In space, the subspaces are the origin, the lines and planes through the origin, and the whole space.
What this node needs for W2
- edge instance_of in: one example (0 of 1)
- edge not_instance_of in: one non-example that fails one clause (0 of 1)
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What this needs
To read this node, read these 2 nodes in this order. The foundations come first, and the list ends with this node.
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- Vector space definition
- Linear subspace definition
What depends on this
102 nodes use this node, directly or through other nodes.
- Dimension of the dual space 00889YD15K
- Linear map of a matrix 009892PZ30
- Nullity 00K4FK4NBH
- Every vector space has a basis 00MS9VMQ9Z
- Jordan–Chevalley decomposition 011K11VPJN
- Finite-dimensional vector space 018W3V3TCT
- Reflection 025158VEYZ
- Rank of a product of matrices 02FDWY55AS
- Determinant of a linear map 03F5KP94K0
- Direct sum of subspaces 041JTZCK9Q
- Parseval's identity 047RFCNVSK
- Complementary subspaces 04C3BAHV03
- Eigenvalues are the roots of the characteristic polynomial 053QVHF6N7
- A matrix is diagonalisable iff it has a basis of eigenvectors 056SW1E0AC
- Isomorphism with the coordinate space 059THXBRBB
- Dimension 05G2G0P224
- Matrix of a composition is the product of matrices 05Q1B7MH0M
- Dimension of a direct product 06HN47VPTH
- Grassmann's formula 06HTJNCMPA
- Spectral theorem 06J4PXRG22
- Every spanning set contains a basis 06MRNP4BNT
- Dimension of the annihilator 06Q1EFVH0Q
- Geometric multiplicity 06YSJVR356
- Orthogonal complement 079D68S3AW
- Third isomorphism theorem for vector spaces 07RB3EMBWW
- Existence of an eigenvalue over an algebraically closed field 08CJB2NQ92
- Steinitz exchange lemma 08ZDRN6H41
- An injective endomorphism of a finite-dimensional space is surjective 0912EEEVCT
- Linearly independent set of the right size is a basis 096V7H13H9
- Coordinates in an orthonormal basis 09DZ8CD1AK
- Second isomorphism theorem for vector spaces 0APN65D6Y6
- Spanning set 0BJKVF90Z6
- Coordinate vector 0BMVBHTWV2
- Least squares 0BYTQ4X1HC
- Characteristic polynomial of a linear map 0BZ81AJNWF
- Determinant is the product of the eigenvalues 0C2F40MEBC
- Classification of complex quadratic forms 0CEX9BRXRZ
- Matrix of the adjoint is the conjugate transpose 0DBTE6HVBD
- Spectral theorem for Hermitian matrices 0DGZBQWZWN
- Dimension of the orthogonal complement 0E2NYPVSP9
- Invariant subspace 0EP59ESQ94
- Row space 0EP73HK4C4
- QR decomposition 0ERWG4NXQ9
- Rank of a matrix 0EWQEYRVA8
- Column space 0F0RPPJ2TT
- Orthonormal basis 0FWJ0VW561
- Linear span 0HR573CHNM
- Rouché–Capelli theorem 0HV1SKWPMS
- Quotient map 0J0SK5FF4M
- Rank of a linear map 0JGB7A6GTS
- Determinant of a linear map is the determinant of its matrix 0KMN32XGPF
- Signature of a quadratic form 0KQZYGEJTF
- Change of basis matrix 0KWXYZPJKN
- Every linearly independent set extends to a basis 0M4SXE5WW3
- Orthogonal projection is the closest point 0MCDDSCB9Z
- Change of basis formula 0MQXVZEBMT
- First isomorphism theorem for linear maps 0MTBGVZ4XJ
- Trace is the sum of the eigenvalues 0NMXDCNNKR
- Matrix of a bilinear form 0P24YW565F
- Existence of a complementary subspace 0P9T8WHNMH
- Restriction of an endomorphism to an invariant subspace 0PFPWKBDTJ
- Principal axis theorem 0PR5P9Z4KM
- Orthogonal complement of the orthogonal complement 0PXN9G4MX1
- Orientation of a real vector space 0Q8BZXVT1Z
- Orthogonal projection 0Q8HZTJC7G
- Cayley–Hamilton theorem for linear maps 0QEM68Y0DE
- Dimension of the coordinate space 0QK7FPE6VE
- Semisimple endomorphism 0QS8P74F2Z
- Dimension of a subspace 0QW084460E
- Annihilator of a subspace 0R6M158SQ9
- Dimension of a tensor product 0R84PF4JV7
- A linear map is determined by its values on a basis 0R8X9XA83A
- Projection 0RH4E3CAV9
- Sum of subspaces 0RMKABS2S5
- Algebraic multiplicity 0S7A0EMPF4
- Basis of a tensor product 0SH5VT8QYA
- A space is the direct sum of a subspace and its orthogonal complement 0SP7P0G7KQ
- Change of basis for a bilinear form 0SPYAGE7T0
- Quotient space 0SVR29SV1V
- Dimension of a quotient space 0SXDQ6TN00
- Row rank equals column rank 0TZAG60ZYT
- Intersection of subspaces 0V33SPH7RR
- Determinant of a family of vectors in a basis 0V94H674MB
- Finite-dimensional spaces are isomorphic iff they have equal dimension 0VJBSK15SN
- Cartan–Dieudonné theorem 0VMWGYY35Q
- Gram–Schmidt process 0VT6P0GNQR
- Basis 0VTQTPQGAV
- Rank–nullity theorem 0W4FSW1TVB
- Dual basis 0W6M3PSD08
- Trace of a linear map is the trace of its matrix 0WCPH5Z7FA
- Sylvester's law of inertia 0WFED3K3DQ
- A subspace of full dimension is the whole space 0WGAXEK99E
- Dimension theorem for vector spaces 0WK0Y8RH1M
- Gram–Schmidt vectors are orthogonal 0WXBGBTA3D
- Existence of an orthonormal basis 0Y85GYEGSF
- Distinct eigenvalues imply diagonalisable 0Y95Z7MT02
- Matrix of a linear map 0YYMY95FWS
- Decomposition into generalised eigenspaces 0Z3GDY89T5
- Dimension of the space of linear maps 0Z9N1ER0W0
- Universal property of the quotient space 0ZERJX6PH6
- Canonical isomorphism with the double dual 0ZJM9D7NPS
- Matrix of the dual map is the transpose 0ZPB3180AY
Sources
What links here
Used by
- Orthogonal complement 079D68S3AW
- Invariant subspace 0EP59ESQ94
- Linear span 0HR573CHNM
- Dimension of a subspace 0QW084460E
- Annihilator of a subspace 0R6M158SQ9
- Sum of subspaces 0RMKABS2S5
- Quotient space 0SVR29SV1V
- Intersection of subspaces 0V33SPH7RR
- A subspace of full dimension is the whole space 0WGAXEK99E