Kyulacs.jl

Unofficial Julia interface for qulacs.

Prerequisites

Install Python and qulacs >= 0.5.1, qulacsvis >= 0.3.2 via

$ pip3 install qulacs qulacsvis

Install Julia. If you're Julian, you can skip this step.

$ pip3 install jill # A cross-platform installer for Pythonista
$ jill install 1.8

After that you're supposed to add ${HOME}/.local/bin to your $PATH environment variable. You'll see the result below:

$ which julia
$ ~/.local/bin/julia
$ julia
               _
   _       _ _(_)_     |  Documentation: https://docs.julialang.org
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.8.3 (2022-11-14)
 _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
|__/                   |

julia> println("Hello")
Hello

julia> exit()

Install PyCall

$ julia
               _
   _       _ _(_)_     |  Documentation: https://docs.julialang.org
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.8.3 (2022-11-14)
 _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
|__/                   |

julia> ENV["PYTHON"] = Sys.which("python3")
julia> using Pkg; Pkg.add("PyCall")

Having trouble with the error messages ImportError: No module named site? Did you install Python via pyenv or asdf? Please re-install or install another Python again with CONFIGURE_OPTS="--enable-shared" option. Namely run one of the following:

$ CONFIGURE_OPTS="--enable-shared" pyenv 3.8.11
$ CONFIGURE_OPTS="--enable-shared" asdf install python 3.8.11

Install Kyulacs.jl

$ git clone https://github.com/AtelierArith/Kyulacs.jl.git
$ cd Kyulacs.jl
$ julia --project=@. -e 'using Pkg; Pkg.instantiate()'
$ julia --project=@. -e 'using Pkg; Pkg.test()'

How to use

Let's assume you've written a Python code which is similar to Python sample code given by qulacs.

# examples/readme_example.py
from qulacs import Observable, QuantumCircuit, QuantumState
from qulacs.gate import Y, CNOT, merge

state = QuantumState(3)
seed = 0  # set random seed
state.set_Haar_random_state(seed)

circuit = QuantumCircuit(3)
circuit.add_X_gate(0)
merged_gate = merge(CNOT(0, 1), Y(1))
circuit.add_gate(merged_gate)
circuit.add_RX_gate(1, 0.5)
circuit.update_quantum_state(state)

observable = Observable(3)
observable.add_operator(2.0, "X 2 Y 1 Z 0")
observable.add_operator(-3.0, "Z 2")
value = observable.get_expectation_value(state)
print(value)

You can try this code out of the box even if you are not familiar with quantum computing.

$ cd /path/to/this/repository
$ julia --project=@. examples/readme_example.jl

In Julia, we can achieve the same functionality with Kyulacs package.

# examples/readme_example.jl
using Kyulacs: Observable, QuantumCircuit, QuantumState
using Kyulacs.Gate: CNOT, Y, merge

state = QuantumState(3)
seed = 0  # set random seed
state.set_Haar_random_state(seed)

circuit = QuantumCircuit(3)
circuit.add_X_gate(0)
merged_gate = merge(CNOT(0, 1), Y(1))
circuit.add_gate(merged_gate)
circuit.add_RX_gate(1, 0.5)
circuit.update_quantum_state(state)

observable = Observable(3)
observable.add_operator(2.0, "X 2 Y 1 Z 0")
observable.add_operator(-3.0, "Z 2")
value = observable.get_expectation_value(state)
println(value)

Have a try!!!

$ cd /path/to/this/repository
$ julia -e "using InteractiveUtils; versioninfo()"
Julia Version 1.7.2
Commit bf53498635 (2022-02-06 15:21 UTC)
Platform Info:
  OS: macOS (x86_64-apple-darwin19.5.0)
  CPU: Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz
  WORD_SIZE: 64
  LIBM: libopenlibm
  LLVM: libLLVM-12.0.1 (ORCJIT, skylake)
$ julia --project=@. examples/readme_example.jl

These are pretty much the same thing. In fact, diff tells these are almost same.

$ diff readme_example.py readme_example.jl
1,3c1,3
< # readme_example.py
< from qulacs import Observable, QuantumCircuit, QuantumState
< from qulacs.gate import Y, CNOT, merge
---
> # readme_example.jl
> using Kyulacs: Observable, QuantumCircuit, QuantumState
> using Kyulacs.Gate: CNOT, Y, merge
21c21
< print(value)
---
> println(value)

Code Design

When you want migrate your code from Python to Julia, the following table may help you:

Python	Julia
`from qulacs import something`	`using Kyulacs: something`
`from qulacs.circuit import something`	`using Kyulacs.Gate: something`
`from qulacs.gate import something`	`using Kyulacs.Gate: something`
`from qulacs.observable import something`	`using Kyulacs.ObservableFunctions: something`
`from qulacs.quantum_operator import something`	`using Kyulacs.QuantumOperator: something`
`from qulacs.state import something`	`using Kyulacs.State: something`
`from qulacsvis.visualization import something`	`using Kyulacs.Vis: something`

If you feel using Kyulacs.ObservableFunctions is too exaggerated. Please send your feedback/idea to our issue tracker.

GPU API

using Kyulacs.GPU will export StateVectorGpu and QuantumStateGpu that wraps qulacs.StateVectorGpu and qulacs.QuantumStateGpu respectively.

Visualization

Kyulacs.jl also supports qulacsvis integration. The statement using Kyulacs.Vis allows us to use Python API under qulacsvis.visualization. Consider the following Julia code:

using Kyulacs: ParametricQuantumCircuit

# exports `circuit_drawer`
using Kyulacs.Vis

nqubits = 2
circuit = ParametricQuantumCircuit(nqubits)
circuit.add_parametric_RY_gate(0, 0.0)
circuit.add_parametric_RY_gate(1, 0.0)

circuit.add_parametric_RY_gate(0, 0.0)
circuit.add_CNOT_gate(0, 1)
circuit.add_parametric_RY_gate(0, 0.0)

circuit_drawer(circuit)

We'll get:

   ___     ___             ___
  |pRY|   |pRY|           |pRY|
--|   |---|   |-----●-----|   |--
  |___|   |___|     |     |___|
   ___             _|_
  |pRY|           |CX |
--|   |-----------|   |----------
  |___|           |___|

Docker

You can run Kyulacs.jl out of the box inside the official Julia Docker container:

$ docker run --rm -it julia:1.8.3
               _
   _       _ _(_)_     |  Documentation: https://docs.julialang.org
  (_)     | (_) (_)    |
   _ _   _| |_  __ _   |  Type "?" for help, "]?" for Pkg help.
  | | | | | | |/ _` |  |
  | | |_| | | | (_| |  |  Version 1.8.3 (2022-11-14)
 _/ |\__'_|_|_|\__'_|  |  Official https://julialang.org/ release
|__/                   |

julia> using Pkg
julia> pkg"registry add General https://github.com/AtelierArith/Gallery.git"
julia> Pkg.add("Conda") # Install Conda.jl
julia> using Conda
julia> Conda.pip_interop(true)
julia> Conda.pip("install", "qulacs")
julia> Conda.pip("install", "qulacsvis")
julia> using Kyulacs: Observable, QuantumCircuit, QuantumState
julia> using Kyulacs.Gate: CNOT, Y, merge
julia> state = QuantumState(3)
julia> seed = 0  # set random seed
julia> state.set_Haar_random_state(seed)
julia> circuit = QuantumCircuit(3)
julia> circuit.add_X_gate(0)
julia> merged_gate = merge(CNOT(0, 1), Y(1))
julia> circuit.add_gate(merged_gate)
julia> circuit.add_RX_gate(1, 0.5)
julia> circuit.update_quantum_state(state)
julia> observable = Observable(3)
julia> observable.add_operator(2.0, "X 2 Y 1 Z 0")
julia> observable.add_operator(-3.0, "Z 2")
julia> value = observable.get_expectation_value(state)

Appendix

Docker

$ git clone https://github.com/AtelierArith/Kyulacs.jl.git
$ cd Kyulacs.jl
$ make && make test
$ make build-gpu && make test-gpu # for gpu version

Blog post

Sponsorship

If you want to see more of our work, consider sponsoring us via Github sponsors.

Suggest Category

Kyulacs.jl

Prerequisites

How to use

Code Design

GPU API

Visualization

Docker

Appendix

Docker

Blog post

Sponsorship

Julia Packages