Sparse Linear System: Difference between revisions

From Algorithm Wiki
Jump to navigation Jump to search
No edit summary
No edit summary
 
Line 12: Line 12:
== Parameters ==  
== Parameters ==  


n: number of variables and number of equations
$n$: number of variables and number of equations


m: number of nonzero entries in matrix
$m$: number of nonzero entries in matrix


k: ratio between largest and smallest eigenvalues
$k$: ratio between largest and smallest eigenvalues


== Table of Algorithms ==  
== Table of Algorithms ==  
Line 26: Line 26:
|-
|-


| [[Harrow (Quantum) (Sparse Linear System Linear System)|Harrow (Quantum)]] || 2009 || $O(k^{2}*logn)$ || $O(log n)$ || Exact || Quantum || [https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.103.150502 Time] & [https://arxiv.org/pdf/0811.3171.pdf Space]
| [[Harrow (Quantum) (Sparse Linear System Linear System)|Harrow (Quantum)]] || 2009 || $O(k^{2}*\log n)$ || $O(\log n)$ || Exact || Quantum || [https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.103.150502 Time] & [https://arxiv.org/pdf/0811.3171.pdf Space]
|-
|-
|}
|}

Latest revision as of 09:18, 10 April 2023

Description

In this case, we restrict $A$ to be sparse (i.e. $A$ only has $O(n)$ nonzero entries).

Related Problems

Generalizations: General Linear System

Related: Positive Definite, Hermitian Matrix, Non-Definite, Symmetric Matrix, Toeplitz Matrix, Vandermonde Matrix

Parameters

$n$: number of variables and number of equations

$m$: number of nonzero entries in matrix

$k$: ratio between largest and smallest eigenvalues

Table of Algorithms

Name Year Time Space Approximation Factor Model Reference
Harrow (Quantum) 2009 $O(k^{2}*\log n)$ $O(\log n)$ Exact Quantum Time & Space

References/Citation

https://arxiv.org/abs/2007.10254