Open Source Quantum Computing Platform

Library for quantum computing applications and educations

Why Blueqat?

Blueqat is an open source platform to build quantum computing applications. It contains tools, libraries and community resources for researchers and developers can easily develop their applications. Blueqat has a very simple eco-system.

Easy coding

With method chain, decreasing the amount of coding. Easy for beginners.

Practical tutorials

Optimization, Chemistry, Machine Learning, there are a lot of tutorials.

Flexible Architecture

It is build on pure python. Easy to install and easy to expand tools for developers.


Install

Using python and pip, easily installed.

pip3 install blueqat

Quick Tutorial

from blueqat import Circuit
from blueqat import vqe
from blueqat.pauli import qubo_bit as q

#The entanglement of 2qubits
Circuit().h[0].cx[0,1].m[:].run(shots=100)

#The quantum-classical hybrid algorithm to find eigenvalue of matrix
hamiltonian = -3*q(0)-3*q(1)+2*q(0)*q(1)
result = vqe.Vqe(vqe.QaoaAnsatz(hamiltonian, step=2)).run()
print(result.most_common(12))


Tutorials

Step1.Logic Gate
001 1qubit Operation 208
002 2qubits Operation 93
003 Superposition 91
004 Entanglement 91
Step2.Advanced Logic Gate
005 Quantum Logic Gate 28
006 Single Fixed Rotation Gate 40
007 Single Arbitrary Rotation Gate 48
008 Controlled Gate 29
009 Controlled Rotation Gate 25
010 Swap Gate 74
011 Toffoli gate 74
012 Ising Gate 47
013 Time Evolution Operator 45
Step3.Universal Algorithms
100 Adder 79
101 Substractor 38
102 Multiplier 64
110 GHZ 112
111 Quantum Teleportation 89
112 Quantum Fourier Transform 78
113 Quantum Phase Estimation 68
114 Grover 71
116 Deutsch’s algorithm 13
117 Deutsch-Jozsa’s algorithm 13
118 Bernstein-Vazirani’s algorithm 2
119 Simon’s algorithm 2
120 Shor’s algorithm 2
121 HHL algorithm 2
122 Quantum Support Vector Machine 2
123 Modulus 30
Step4.NISQ Variational Algorithms
200 VQE 101
201 QAOA 110
Step5.NISQ Quantum Machine Learning
250 Quantum Machine Learning 0
251 Gradient 79
251 QCBM 28
252 TTN 37
253 MPS 33
Step6.Combinatorial Optimization
300 Combinatorial Optimization Problems 54
301 Maxcut 39
302 1+1 45
303 Number partitioning 38
304 BIL 38
305 Clique cover 38
306 cliques 39
307 exact cover 42
308 graph coloring 39
309 graph partitioning 41
310 Job sequence 44
311 Knapsack 40
312 Set cover 40
313 Set packing 34
314 Travelling Salesman 45
315 Vertex Cover 37
316 Traffic Flow Optimization 43
317 Boolean Reduction 42
318 Portfolio Optimization 43
319 Prime Factorization 37
320 Restricted Boltzmann machine 17
321 Weak Strong Cluster 39
322 Protein foldings 43
323 Clustering 35
Step7.Quantum Chemistry
400 Quantum Chemistry 41
Step8.Error Correction
500 Error Correction 2
Step9.Advanced Settings
600 Qgate 38
601 Classical Optimizer 41
602 Original backend 1 20
603 Original backend 2 2

Latest News & Community Support

Youtube

Let's watch movies on Youtube for lectures and latest topcis to understand how to use quantum computing.

Watch movies
Academy

Let's attend to the lecture, and study on Bluqat and quantum computing from the teachers and researchers.

See lectures
Blog

Let's read technical blogs to see the latest update and technical terms of blueqat team and parterns.

Read Blogs
Jupyter

Let's find the solution through the Blueqat python jupyter tutorial to solve your own problem from a lot of examples.

See tutorials
Slack

Let's join active online community to exchange knowledge and ask for question on quantum computing.

Join Slack
Twitter

Let's follow @blueqat_sdk on Twitter to get latest news and information about Blueqat team and users.

Follow Twitter

COMPANY

MDR Inc. (Machine Learning & Dynamics Research)
ABC Ground, 3-1-1-B2F, Marunouchi, Chiyoda, Tokyo, Japan
info@mdrft.com