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

Discover the Atos Quantum ecosystem

• QLM
• QLaaS >
• myQLM >
• Quantum Services
• QLM User Club >

The Atos Quantum Learning Machine approach

• Help people learn and experiment with quantum computers
• Develop applications and algorithms
• Without the need to wait for quantum machines to be physically available

Atos QLM E

Atos Quantum Learning Machine Enhanced – Atos QLM E – is a new range of GPU-accelerated Atos Quantum Learning Machine. Atos QLM E offers an acceleration up to 12 times to simulate variational algorithms that a particularly well-suited for NISQ (Noisy Intermediate Scale Quantum) devices, which will be the first quantum accelerators to be commercialized in the next few years.

By promising to apply, in the near-term, computation capabilities that are beyond the reach of even the most powerful existing computers to solve complex, real-life problems, NISQ devices will play an important role in determining the commercial potential of quantum computing. Herein lies a double challenge for the industry: developing NISQ algorithms is as important as building the machines, since both are required to identify concrete applications. Atos QLM E has been optimized to drastically reduce the compilation time of hybrid quantum-classical algorithms simulations, leading to quicker advancement in application research.

Atos QLM E[nhanced] accelerating research in the NISQ era

• Accelerate your quantum simulations up to 12x
• Optimized for variational algorithms best suited for the NISQ* era (up to 30 qubits)
• Upgrade your QLM to a QLM E very easily to benefit from these enhanced features

Accelerate research on variational algorithms using Atos QLM E:

Quantum Approximate Optimization Algorithm

Variational Quantum Eigensolver / Variational Imaginary Time Evolution

Variational Quantum Factoring

Variational Quantum Classifier

             …

Atos Fast Start program with the Center of Excellence in Performance Programming

• Discover the Atos QLM
• Develop & Simulate your codes
• AQASM & pyAQASM
• Compile & Execute your algorithms…

• During two days
• On your premises

Center of Excellence in Performance programming

Related resources

Brochure

Atos Quantum Learning Machine
Getting ready for the Quantum Revolution

Statement of Direction

Atos has taken a hardware-agnostic approach, in crafting quantum-powered supercomputers and enabling end-user applications.

Recording talks

Recording Talk

Accelerating research in near-term quantum applications using GPU

Recording Talk

MyQLM Demo