QuantAlpsAn ecosystem for quantum science & technologies :
From the philosopher to the industrial

This is realized via the initialization, manipulation and reading of individual qubits according to quantum algorithms. The challenges are both experimental (e.g. the fabrication of qubit arrays coupled to driving electronics, the improvement of qubit figures of merit such as fidelity or coherence, the creation of quantum memories) and theoretical (the understanding of large-scale decoherence mechanisms, error mitigation and correction, the modeling of the quantum advantage, the definition of universal benchmarks).

Our research in quantum computing is being conducted on a wide range of solid state qubits: superconductors, molecular magnets, spins in silicon arrays, and single photon sources. In terms of technology, Grenoble has a continuum of manufacturing facilities on a single site, ranging from the most agile and research-based to the most reliable, pre-industrial, and industrial level. At the theoretical level, we have a recognized expertise in quantum information, quantum optics, quantum transport, and computational energy. This allows the development of hardware and software methods related to algorithms (computational models, formal methods, error correction codes...) and certification (entanglement fidelity measurements, correlation testing, quantum advantage modeling).



We would like to develop strong synergies in quantum computing within the Grenoble Ecosystem. To this end, we will

• Intensify connections between hardware and software: Test of algorithms on small systems (e.g. quantum error correction and quantum optimization), verification of Grenoble experimental qubit systems.
• Increase synergies between different hardware platforms: Realization of identical circuits and identification of noise specific to each experimental system, definition of figures of merit and comparison of different platforms (including energy)
• Mutualize the instrumentation developments and interfacing with a common software and cloud service.
• Identify use cases that can serve local and national industrial users of intensive computing.