QAOA_maxcut

Matrix that specifies the edges between nodes. Rows are source nodes and columns are destination nodes. Value of 0 means no edge, value of 1 means edge. If edge is undirected, an edge should be specified going both directions.

connectionMatrix

Number of iterations that algorithm will run. Each iteration applies U(C,g) and U(B,b)

Angle for U(C,g), currently the same for all iterations. Should be between 0 and 2*pi

gamma

Angle for U(B,b), currently the same for all iterations. Should be between 0 and pi

beta

Boolean which specifies if progress should be shown. If TRUE, a bar plot is continually updated showing the amplitudes

displayProgress

Takes a connection matrix as input and converts it to a set of clauses, then runs the Quantum Approximation Optimization Algorithm (Farhi, Goldstone, and Gutmann 2014) &lt;arXiv:1411.4028&gt;.

Contains basic structures and operations used frequently in quantum computing. Intended to be a convenient tool to help learn quantum mechanics and algorithms. Can create arbitrarily sized kets and bras and implements quantum gates, inner products, and tensor products. Creates arbitrarily controlled versions of all gates and can simulate complete or partial measurements of kets. Has functionality to convert functions into equivalent quantum gates and model quantum noise. Includes larger applications, such as Steane error correction <DOI:10.1103/physrevlett.77.793>, Quantum Fourier Transform and Shor's algorithm (Shor 1999), Grover's algorithm (1996), Quantum Approximation Optimization Algorithm (QAOA) (Farhi, Goldstone, and Gutmann 2014) <arXiv:1411.4028>, and a variational quantum classifier (Schuld 2018) <arXiv:1804.00633>. Can be used with the gridsynth algorithm <arXiv:1212.6253> to perform decomposition into the Clifford+T set.

QAOA_maxcut: QAOA_maxcut

Description

Usage

Arguments

Value

Examples