Quantum Computing Problems & Solutions

These are my solutions to problems in the book Problems and solutions in quantum computing and quantum information^[1] using Julia with SymPy.jl within Pluto.jl notebooks.

The aim of this effort is to assist in improving ones mathematical rigor and know-how related to quantum computing using symbolic algebra and numerical computation.

It helps if you have access to the text by Nielsen & Chuang^[2] while working through these problems.

About this site

This site is intended to provide a static render of the various notebooks along with some minor background material. The end goal is to somehow turn the static renders into dynamic notebooks using something like binder.

begin
	using Pkg
	Pkg.activate(mktempdir())
	ENV["PYTHON"] = ""
	Pkg.add(["Conda", "PyCall"])
    Pkg.build()
    using Conda
    Conda.add("sympy")
	Pkg.add("SymPy")
end

Chapters

The site is broken down by chapter and within each chapter there are programming problems (i.e. solved using SymPy.jl) and those that are just solved by "hand".

• Ch. 1 Qubits

• Ch. 2 Product spaces

• Ch. 3 Matrices

• Ch. 4 Density Operators

• Ch. 5 Traces

• Ch. 7 Unitary Operators

• Ch. 8 Entropy

• Ch. 9 Measurement

• Ch. 10 Entanglement

• Ch. 11 Bell's Inequality

• Ch. 12 Quantum Information

• Ch. 13 Cloning

Using the notebooks files

Once the repo is locally cloned, the environment and pluto server can be instatiated from the Package.toml and dependencies from Manifest.toml from within the folder using the command line:

julia --project=@. -e "using Pluto; Pluto.run()"

or

julia> ]
(v1.5) pkg> activate .
(QuantumComputingProblemsSolutions) pkg> instantiate
julia> using Pluto
julia> Pluto.run()