Lanczos algorithm

E697941

The Lanczos algorithm is an iterative numerical method used to approximate eigenvalues and eigenvectors of large sparse matrices, particularly in scientific computing and numerical linear algebra.

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Predicate Object
instanceOf Krylov subspace method
iterative method
numerical algorithm
application electronic structure calculations
graph partitioning
information retrieval
model reduction
principal component analysis
quantum many-body problems
structural engineering
vibration analysis
basedOn Krylov subspace NERFINISHED
computes orthonormal basis of Krylov subspace
field computational chemistry
computational physics
numerical linear algebra
scientific computing
hasVariant block Lanczos method NERFINISHED
implicitly restarted Lanczos method
thick-restart Lanczos method NERFINISHED
implementedIn ARPACK NERFINISHED
MATLAB eigs function
SLEPc NERFINISHED
SciPy sparse.linalg.eigsh NERFINISHED
inputType Hermitian matrix
large sparse matrix
symmetric matrix
namedAfter Cornelius Lanczos NERFINISHED
outputType Ritz values
Ritz vectors
tridiagonal matrix
property matrix-free
memory efficient for large sparse problems
sensitive to loss of orthogonality
short-term recurrence
well-suited for extreme eigenvalues
purpose approximation of eigenvalues of large sparse matrices
approximation of eigenvectors of large sparse matrices
reduction of large symmetric matrices to tridiagonal form
relatedTo Arnoldi iteration NERFINISHED
Rayleigh–Ritz method NERFINISHED
conjugate gradient method NERFINISHED
power method
requires initial starting vector
matrix-vector products
uses three-term recurrence
yearIntroduced 1950

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Jacobi matrix usedIn Lanczos algorithm