Qulacs-Osaka is a python/C++ library for fast simulation of large, noisy, or parametric quantum circuits. This project is (implicitly) forked from Qulacs and developed at Osaka University.
Qulacs-Osaka is licensed under the MIT license.
Relation to Qulacs
The commits in Qulacs are merged into Qulacs-Osaka up to the pull request corresponding to the commit 987474b31a6e60eba116d2e40ab538dcf8086038
(link to the corresponding commit in Qulacs and in Qulacs-Osaka). After that commit, this project is developed independently from Qulacs and has many new features that have not been available in Qulacs.
- Fast quantum circuit simulation with parallelized C/C++ backend
- Noisy quantum gate for simulation of NISQ devices
- Parametric quantum gates for variational methods
- Circuit compression for fast simulation
- GPU support for fast simulation
- Many utility functions for research
- Compared following libraries on March, 2020
Package | Version |
---|---|
Qulacs GPU | 0.1.9 |
Cirq | 0.6.0 |
Qiskit Aer | 0.3.4 |
ProjectQ | 0.4.2 |
qHiPSTER | latest master branch |
Python interface of QuEST (PyQuest-cffi) | 3.0.0 |
qsim | latest master branch |
- Azure NC6s_v3 (6vcpu / Mem112GiB)
- Intel(R) Xeon(R) CPU E5-2690 v4 @ 2.60GHz
- Tesla V100 PCIE (driver 440.33.01)
for each qubit number N:
- Apply simultaneous random single-qubit Pauli-X rotation
and then repeat:
- Apply CNOT(i,(i+1)%N) for all i in [0..N-1]
- Apply simultaneous random single-qubit Pauli-X rotation
for N times.
- execution time include time for creating quantum circuit
- benchmark was done with float64 precision (qsim was done with float32)
This benchmark was done with majour quantum circuit simulators with python interface.
Yao is quantum circuit simulator using Julia that is as fast as Qulacs.
Benchmark inculde Yao can be found here.
- C++ compiler (gcc or VisualStudio)
- gcc/g++ >= 7.0.0 (checked in Linux, MacOS, cygwin, MinGW, and WSL)
- Microsoft VisualStudio C++ 2015 or later
- Boost >= 1.71.0 (Minimum version tested in CI)
- python 2.7 or 3.x
- cmake >= 3.0
- git
- (option) CUDA >= 8.0
- (option) AVX2 support
If your system supports AVX2 instructions, SIMD optimization is automatically enabled.
If you want to enable GPU simulator, install qulacs through qulacs-gpu
package or build from source.
Note that qulacs-gpu
includes CPU simulator. You don't need to install both.
Qulacs is tested on the following systems.
- Ubuntu 16.04 / 18.04
- MacOS X Sierra
- Windows 10
If you encounter some troubles, see troubleshooting.
Install (Multi-thread without GPU)
python setup.py install
Install (Multithread with GPU. CUDA is required)
python setup_gpu.py install
Install (Single-thread without GPU. For launching multiple qulacs processes.)
python setup_singlethread.py install
Uninstall
pip uninstall qulacs
git clone https://github.com/qulacs/qulacs.git
cd qulacs
./script/build_gcc.sh
When you want to build with GPU, use build_gcc_with_gpu.sh
.
git clone https://github.com/qulacs/qulacs.git
cd qulacs
script/build_msvc_2017.bat
When you want to build with GPU, use build_msvc_2017_with_gpu.bat
. If you use MSVC2015, replace "2017" in file names to "2015".
See the following documents for more detail.
from qulacs import Observable, QuantumCircuit, QuantumState
from qulacs.gate import Y,CNOT,merge
state = QuantumState(3)
state.set_Haar_random_state()
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)
If you want to run it on GPU, install GPU-enabled qulacs and replace QuantumState
in the above codes to QuantumStateGpu
.
#include <iostream>
#include <cppsim/state.hpp>
#include <cppsim/circuit.hpp>
#include <cppsim/observable.hpp>
#include <cppsim/gate_factory.hpp>
#include <cppsim/gate_merge.hpp>
int main(){
QuantumState state(3);
state.set_Haar_random_state();
QuantumCircuit circuit(3);
circuit.add_X_gate(0);
auto merged_gate = gate::merge(gate::CNOT(0,1),gate::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");
auto value = observable.get_expectation_value(&state);
std::cout << value << std::endl;
return 0;
}
Build command for g++:
g++ -O2 -I ./<qulacs_path>/include -L ./<qulacs_path>/lib <your_code>.cpp -fopenmp -lcppsim_static -lcsim_static
If you want to run it on GPU, include cppsim/state_gpu.hpp
and replace QuantumState
with QuantumStateGpu
.
Please cite this arXiv paper: Qulacs: a fast and versatile quantum circuit simulator for research purpose