Backend for linear algebra operations on complex numbers using clojure.math.
This backend implements the BackendAdapter
, MatrixAlgebra
, MatrixDecompositions
,
MatrixFunctions
, and MatrixAnalysis
protocols from org.soulspace.qclojure.domain.math.protocols
using clojure.math.
The backend uses a Structure of Arrays (SoA) representation for complex numbers, where complex vectors and matrices are represented as maps with separate real and imaginary parts. This format is efficient for numerical computations and compatible with clojure.math operations.
Features:
Backend for linear algebra operations on complex numbers using clojure.math. This backend implements the `BackendAdapter`, `MatrixAlgebra`, `MatrixDecompositions`, `MatrixFunctions`, and `MatrixAnalysis` protocols from `org.soulspace.qclojure.domain.math.protocols` using clojure.math. The backend uses a Structure of Arrays (SoA) representation for complex numbers, where complex vectors and matrices are represented as maps with separate real and imaginary parts. This format is efficient for numerical computations and compatible with clojure.math operations. Features: - Conversion between various complex number representations - Basic and advanced matrix operations - Matrix decompositions (eigen, SVD, LU, QR, Cholesky) - Matrix functions (exponential, logarithm, square root) - Matrix analysis (spectral norm, condition number)
Linear algebra operations for complex numbers in Clojure.
This namespace provides implementations of common linear algebra operations for complex numbers represented in a structure-of-arrays (SoA) format. It includes matrix addition, multiplication, inversion, eigen-decomposition, and other utilities necessary for quantum computing applications.
Complex Number Representation:
Linear Algebra Operations:
Linear algebra operations for complex numbers in Clojure. This namespace provides implementations of common linear algebra operations for complex numbers represented in a structure-of-arrays (SoA) format. It includes matrix addition, multiplication, inversion, eigen-decomposition, and other utilities necessary for quantum computing applications. Complex Number Representation: - Complex numbers are represented as maps with :real and :imag keys. - Vectors and matrices of complex numbers are represented as maps with :real and :imag keys containing vectors or matrices of real numbers. Linear Algebra Operations: - Matrix addition, subtraction, scaling, multiplication - Matrix-vector products - Kronecker products - Transpose and conjugate transpose - Inner products - Hermitian checks - Solving linear systems - Matrix inversion - Spectral norm computation - Eigen-decomposition for Hermitian matrices
cljdoc builds & hosts documentation for Clojure/Script libraries
Ctrl+k | Jump to recent docs |
← | Move to previous article |
→ | Move to next article |
Ctrl+/ | Jump to the search field |