Atos Quantum Learning Machine


Aspen Systems, Inc. is proud to offer the Atos Quantum Learning Machine (QLM) to our customers. This is a fully supported quantum computing appliance that can simulate up to 41 qubits to help people experiment with a quantum computer. With the Atos QLM, you can learn how to develop your own algorithm on any existing or future quantum programming framework. The Atos QLM helps people learn and experiment with quantum computers without the need to wait for quantum machines to be physically available.

atos qlm and logo


A Global Strategy for Quantum Computing

1. Quantum Programming Platform

Complete programming and simulation environment for quantum software/hardware developers and for education/training

2. Quantum Expert Consulting Services

Assisting our customers in discovering Quantum Computing, detecting relevant use cases, assessing quantum implementation benefits on the QLM simulator

3. New Generatiuon Architectures

Designing the new quantum-powered accelerators for supercomputers or hybrid systems

4. Quantum Algorithms

Atos’ own research, focused on Quantum Machine Learning, one of the most promising application areas of QLM

5. Quantum Safe Cryptography

Preparing the cryptographices and hardware security modules, resistant to quantum computer attacks

Just Need a Basic Simulating Tool?

You can use the Atos myQLM freeware to do some basic programming. Link to their myQLM page for installing below.

Key Benefits of the Atos QLM

Hardware Agnostic

Offering an universal programming environment to avoid the vendor lock-in

Scalable & Futureproof

Simulating up to 41 qubits, on a simple business server physical dimensions

A User-Friendly Framework

Jupyter Notebooks library, and integrated Quantum Algorithms & QLIB.

Interoperability Kit

Use interoperability with proprietary frameworks and develop your own connectors.

Noisy Simulation

With QLM, you can evaluate the impact of quantum noise on your simulation’s results.

QLM for Combinatorial Optimization

First revealed in June 2020 and officially showcased at SC20, Atos’ QLM for Combinatorial Optimization environment will allow users to prepare codes to tackle combinatorial optimization problems using either quantum annealing or gate-based quantum computing.

As an additional feature of the Atos Quantum Learning Machine (QLM), Atos then allows users to simulate their code either on noisy or noiseless digital quantum simulators or using quantum-inspired modules like Simulated Quantum Annealing (SQA) or Simulated Bifurcation Algorithm (SBA).

Quantum Computing promises to solve larger optimization problems faster and more accurately, which will generate tangible benefits for industries, such as portfolio management, logistics, antenna location, chip design or clinical trial database search.

Key benefits of using both approaches in the Atos QLM

Better understand the specificities of quantum annealing and digital quantum computing
Compare the benefits and constraints of two quantum computing technological paths applied to combinatorial optimization problems
Prepare code to then run on NISQ accelerators or Quantum Annealing machines using the same programming environment

A highly scalable and modular simulator

Upgrade your Atos QLM to suit your simulation needs

Atos QLM, Atos QLM-E, myQLM

Feature Comparison

Features myQLM
Atos QLM
Atos QLM E(nhanced)
Custom Gates
QLIB Libraries
Interoperability Kit – Open Source
Gate Set Rewriter X
Topology Constraints Solver X
Circuit Optimizer X
DIGITAL QC SIMULATION Simulation Capabilities Up to 20 qubits Up to 40 qubits Up to 40 Qubits
Simulation Performances
PyLinalg – Open Source
Advanced Noiseless Simulators X
Noisy Simulators X
Acceleration up to 12x X X
QLM FOR COMBINATORIAL OPTIMIZATION Simulated Quantum Annealing X (default) up to 500 variables
(option) up to 2,000 variables
(option) up to 5,000 variables
(Soon) Acceleration for Simulated Bifurcation Algorithm X X
SERVICES Training Self-training Instructor-led Instructor-led
Support Community Subscription Subscription
Consulting On Demand On Demand On Demand