myQLM - Quantum Computing Framework

Explore the capabilities of quantum programming on your laptop using the world’s first quantum simulator’s programming framework.

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You want to develop your next quantum algorithm!

Get access to essentials of myQLM:

- - basic functions
  - commands
  - syntaxes
  - modules…

This Cheat Sheet helps you to get direct access to the main keystrokes needed to perform your specific tasks.

Download the Cheat Sheet

myQLM benefits

Develop quantum algorithms on your laptop

myQLM allows quantum computing researchers, students and developers to test their ideas directly from their laptops. We made available the optimized code of the Atos Quantum Learning Machine (QLM) so you can efficiently simulate quantum circuits up to 20 qubits.

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Write your own quantum processing methods

Thanks to myQLM’s plugin architecture, you can create your own pre- and post-processing methods to optimize your quantum circuits vs. a specific target quantum technology for example.

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Finnet

Use it as a front-end to your Atos QLM

It is fully compatible with the Atos QLM: you can launch your myQLM programs on your organization’s Atos QLM to benefit from higher performances, larger simulation capabilities, and advanced features like quantum circuit optimizers and noisy simulators.

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Collaborate with any other framework’s user

myQLM is a python package that is provided with open source interoperability connectors with frameworks such as Qiskit, Cirq, ProjectQ or Forest™. Write your own connectors with any existing or future framework to expand you community.

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Try myQLM

Discover the community

Expand your quantum programming community with myQLM

myQLM is the best framework to help students, scientists and developers get acquainted with quantum computing and quantum programming.

Everyone’s myQLM ideas can be shared via a community GitHub repository.

It’s a tool to brainstorm, test and share ideas without being bothered by quantum noise.

You will have access to a broad user community as Atos also provides open source translators from myQLM to other main quantum programming environments.

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Testimonials

“We use myQLM in an introductory course on quantum computing. It is a great tool for learning. Students can experiment when and where they want. Select results can easily go to the large QLM for simulation.”

Jürgen Fuß / Dept. of Secure Information Systems, FH Upper Austria

“We are currently living the emergence of applied quantum computing with the first NISQ prototypes, although the best Q-hardware technology must still prove itself. In this regard, Atos Quantum Learning Machine (QLM) is the quality tool for learning, training, and algorithm development to ensure the foundation for further research on quantum simulations while remaining hardware-agnostic. Besides, the possibility of having myQLM as a personal desktop version of the quantum simulator makes this process of learning and training more flexible and efficient. The package is well-documented, providing access to different libraries and circuit examples, and making it available for both experienced users and newcomers in the domain.”

Elvira Shishenina, PhD – Quantum Computing Research Scientist @Total

”MyQLM allows the user to develop their own plugins, yielding an auxilary API for pre-processing quantum circuits before their execution. Thus circuits can be tailored to meet the hardware constraints of real QPU’s.”

Jami Rönkkö, Quantum Engineer, IQM

“Having access to myQLM, helps us to build a powerful quantum ecosystem, which enables the commercial use of quantum computers. With myQLM, it becomes much easier to integrate IQM hardware into the Atos environment."

Jan Goetz, CEO & Co-Founder, IQM

Step by step

Start building quantum programs on your laptop with myQLM

from qat.lang.AQASM import Program, H, CNOT
#Create a program
qprog = Program()
#Number of qubits
nbqubits = 2
#Allocate some qubits
qubits = qprog.qalloc(nbqubits)
#Apply some quantum gates
qprog.apply(H, qubits[0])
qprog.apply(CNOT, qubits[0], qubits[1])
#Export this program into a quantum circuit
circuit = qprog.to_circ()
#And display it!
%jsqatdisplay circuit