NEASQC technology enablement activities aim to boost the research of NISQ applications in Europe by offering a complete and common toolset formed by three main components: a complete quantum programming environment, a set of open source application software libraries, and an application-focused benchmark suite

Quantum programming environment

This environment will be extended from the existing Atos freeware myQLM.

myQLM is a python-based quantum software stack which allows to write, simulate, optimise and execute quantum programmes.  myQLM is based on Atos Quantum Learning Machine (QLM).  

myQLM empowers researchers, students and developers seeking to experiment with quantum programming with tools able to simulate up to 20 qubits in a user’s own device and larger simulations in Atos QLM.

myQLM offers:

Open source application software libraries

NEASQC will provide up to eight industry-grade open source NISQ programming libraries extracted from the NEASQC use cases prototypes development.  These open source libraries aim at facilitating code-reusability, as well as, to enforce the availability of well-documented and high-quality exemplary industrial cases for newcomers to the quantum computing software community.  

Open source libraries made available in the initial release (30/09/2022):

Application-focused benchmark suite

NEASQC will design and test a series of application-focused benchmark to offer an application focused benchmark suite. This benchmark suite has the ambition to ease the cooperation among European QT Flagship hardware platform producers and end users by developing scalable and hardware-independent mechanisms to assess and compare quantum end-user applications behaviour in different hardware platforms.

Release 1.0 of the NEASQC Benchmark Suite was issued on 30 October 2023. The following benchmarks are included in the Suite:

  • T01: Benchmark for Probability Loading Algorithms (Annex C). This Benchmark addresses one of the current main problems of Quantum Computing: how to load classical data into the amplitudes. Extracted from the WP5, it is important for many different quantum algorithms.
  • T02: Benchmark for Amplitude Estimation Algorithms (Annex D). Amplitude Estimation algorithms are used as a technique to accelerate some results. It has been defined from the needs of WP5.
  • T03: Benchmark for Phase Estimation Algorithms (Annex E). Phase Estimation is a key algorithm in Quantum Computing that is used widely. Concretely, it is used in some possible solutions of the Use Case 5 from WP5.
  • T04: Benchmark for Parent Hamiltonian (Annex F). Variational algorithms, especially Variation Quantum Eigensolver, are proposed tools to get good results from the current noisy quantum computers. However, their results depend on the selected ansatz and used optimizer. This Benchmark tests the quality of the quantum computers and libraries to execute typical ansatzes used in WP4, without depending on the optimizer.
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