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QLM - Quantum Learning Machine

Core benefits
The Eviden Quantum Learning Machine is a complete on-premises environnment with a powerfull dedicated hardware infrastucture that allows researchers, engineers and students to develop and experiment with quantum software.
It embeds a programming platforms, high-performance quantum simulators and optimizers. Applications developped on the Eviden QLM can be emulated or run on quantum accelerators without changing a single line of code.
  • Supports the mose widely used quantum programming paradigms
  • Interperability capabilities with proprietary frameworks
  • Enables the developpement of custom connectors
  • Enables the design of new quantum-powered accelerators for supercomputers and hybrid systems

QLM Enhanced

QLM Enhanced (QLM E) is a range of GPU-acceletated Quantum Learning Machine to simulate variational algorithms well-suited for NISQ (Noisy Intermediate Scale Quantum) devices which will be the first quantum accelerators to be commercialized in the next few years.
  • Quantum Approximate Optimization Algorithm
  • Variational Quantum Eigensolver
  • Variational Imaginary Time Evolution
  • Variation Quantum Factoring
  • Variation Quantum Classifier

myQLM

myQLM is a python package that is provided with open source interoperability connectors with frameworks such Qiskit, Cirq, ProjectQ or Forest. It is designed tp democratize quantum computing by allowing researchers, developpers and students to create and simulate quantum circuits on their laptops.

It is fully compatible with the Eviden QLM to benefit from larger simulation capabilities and advanced features.

 

 QLM 8U
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