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https://github.com/apkille/gabs.jl
A library for fast simulations of Gaussian quantum information.
https://github.com/apkille/gabs.jl
continuous-variables gaussian-quantum-information harmonic-oscillator julia phase-space photonics quantum-computing quantum-information quantum-network symplectic
Last synced: 10 days ago
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A library for fast simulations of Gaussian quantum information.
- Host: GitHub
- URL: https://github.com/apkille/gabs.jl
- Owner: apkille
- License: mit
- Created: 2024-09-02T00:17:36.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-20T00:12:55.000Z (15 days ago)
- Last Synced: 2025-01-20T01:19:26.174Z (15 days ago)
- Topics: continuous-variables, gaussian-quantum-information, harmonic-oscillator, julia, phase-space, photonics, quantum-computing, quantum-information, quantum-network, symplectic
- Language: Julia
- Homepage: https://apkille.github.io/Gabs.jl/
- Size: 750 KB
- Stars: 8
- Watchers: 2
- Forks: 1
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# Gabs.jl
[](https://apkille.github.io/Gabs.jl/stable)
[](https://apkille.github.io/Gabs.jl/dev)
[](https://github.com/apkille/Gabs.jl/actions)
[](https://codecov.io/github/apkille/Gabs.jl)
[](https://github.com/aviatesk/JET.jl)
[](https://github.com/JuliaTesting/Aqua.jl)
Gabs.jl is a numerical tooling package for simulating **Gaussian quantum information**.
Gaussian states and operators have the convenient property that they can be
characterized by low-dimensional matrices in the phase space representation.
Thus, a large class of continuous variable quantum information can be efficiently
simulated on a classical computer. Gabs.jl provides a high-level [Julia](https://julialang.org) interface for straightforward and high performance implementations of Gaussian quantum systems.
See the detailed [suggested readings & references page](https://apkille.github.io/Gabs.jl/dev/bibliography/) for a background on quantum information with Gaussian states.
## Installation
To install Gabs.jl, start Julia and run the following command:
```julia
using Pkg
Pkg.add("Gabs")
```
To use the package, run the command
```julia
using Gabs
```
Now, the entire library is loaded into the current workspace, with access to its
high-level interface and predefined objects.
## Example Usage
```julia
julia> basis = QuadPairBasis(1)
QuadPairBasis(1)
julia> state = vacuumstate(basis) ⊗ coherentstate(basis, 1.0-im)
GaussianState for 2 modes.
symplectic basis: QuadPairBasis
mean: 4-element Vector{Float64}:
0.0
0.0
1.4142135623730951
-1.4142135623730951
covariance: 4×4 Matrix{Float64}:
1.0 0.0 0.0 0.0
0.0 1.0 0.0 0.0
0.0 0.0 1.0 0.0
0.0 0.0 0.0 1.0
julia> op = beamsplitter(basis ⊕ basis, 0.75)
GaussianUnitary for 2 modes.
symplectic basis: QuadPairBasis
displacement: 4-element Vector{Float64}:
0.0
0.0
0.0
0.0
symplectic: 4×4 Matrix{Float64}:
0.5 0.0 0.866025 0.0
0.0 0.5 0.0 0.866025
-0.866025 0.0 0.5 0.0
0.0 -0.866025 0.0 0.5
julia> apply!(state, op)
GaussianState for 2 modes.
symplectic basis: QuadPairBasis
mean: 4-element Vector{Float64}:
1.2247448713915892
-1.2247448713915892
0.7071067811865476
-0.7071067811865476
covariance: 4×4 Matrix{Float64}:
1.0 0.0 0.0 0.0
0.0 1.0 0.0 0.0
0.0 0.0 1.0 0.0
0.0 0.0 0.0 1.0
julia> ptrace(state, 1)
GaussianState for 1 mode.
symplectic basis: QuadPairBasis
mean: 2-element Vector{Float64}:
1.2247448713915892
-1.2247448713915892
covariance: 2×2 Matrix{Float64}:
1.0 0.0
0.0 1.0
```