Struct SparseMatrix 

pub struct SparseMatrix {
    pub shape: (usize, usize),
    pub inner: SciRSSparseMatrix<Complex64>,
    pub format: SparseFormat,
    pub simd_ops: Option<Arc<SimdOperations>>,
    pub metrics: SparseMatrixMetrics,
    pub buffer_pool: Arc<BufferPool<Complex64>>,
}

High-performance sparse matrix with SciRS2 integration

Fields

shape: (usize, usize)

Matrix dimensions (rows, cols)

inner: SciRSSparseMatrix<Complex64>

SciRS2 native sparse matrix backend

format: SparseFormat

Storage format optimized for quantum operations

simd_ops: Option<Arc<SimdOperations>>

SIMD operations handler

metrics: SparseMatrixMetrics

Performance metrics

buffer_pool: Arc<BufferPool<Complex64>>

Memory buffer pool for operations

Implementations

impl SparseMatrix

pub fn new(rows: usize, cols: usize, format: SparseFormat) -> Self

Create a new sparse matrix with SciRS2 backend

pub fn identity(size: usize) -> Self

Create identity matrix with SciRS2 optimization

pub fn zeros(rows: usize, cols: usize) -> Self

Create zero matrix

pub fn insert(&mut self, row: usize, col: usize, value: Complex64)

Add non-zero entry with SciRS2 optimization

pub fn nnz(&self) -> usize

Get number of non-zero entries

pub fn to_format(&self, new_format: SparseFormat) -> Self

Convert to different sparse format with SciRS2 optimization

pub fn matmul(&self, other: &Self) -> QuantRS2Result<Self>

High-performance matrix multiplication using SciRS2

pub fn kron(&self, other: &Self) -> Self

High-performance tensor product using SciRS2 parallel operations

pub fn transpose(&self) -> Self

High-performance transpose using SciRS2

pub fn dagger(&self) -> Self

High-performance Hermitian conjugate using SciRS2

pub fn is_unitary(&self, tolerance: f64) -> bool

Check if matrix is unitary using SciRS2’s numerical analysis

pub fn analyze_structure(&self) -> MatrixStructureAnalysis

Advanced matrix analysis using SciRS2 numerical routines

pub fn compress(&mut self, level: CompressionLevel) -> QuantRS2Result<f64>

Apply advanced compression using SciRS2

pub fn matrix_exp(&self, scale_factor: f64) -> QuantRS2Result<Self>

Matrix exponentiation using SciRS2’s advanced algorithms

pub const fn optimize_for_gpu(&mut self)

Optimize matrix for GPU computation

pub const fn optimize_for_simd(&mut self, simd_width: usize)

Optimize matrix for SIMD operations

Trait Implementations

impl Clone for SparseMatrix

fn clone(&self) -> SparseMatrix

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.