QUTE: CTIC Quantum Testbed: quantum computing emulator

QUTE addresses a specific barrier in the quantum field: researchers and technologists who need to run experiments with quantum circuits and algorithms face serious limitations in accessing real quantum hardware. The platform provides a general-purpose simulation environment for designing, running, and validating those experiments without depending on that availability.

The objectives of QUTE are:

• To offer a general-purpose, high-performance quantum simulation capability that is accessible to the scientific community.
• To facilitate the design and validation of quantum algorithms in applications such as optimization problems and machine learning.
• To build a national and international community of users around the platform.

The areas on which QUTE is built are:

• Simulation platform: a general-purpose environment capable of emulating a quantum computer of 38 logical qubits, the largest quantum emulation capacity in Spain, deployed on the ISAAC supercomputing infrastructure.
• Specialized support service: answers to questions about quantum programming and accompaniment in designing algorithms and experiments for specific applications.
• User community: the platform is used by a dozen Spanish institutions (including the University of Oviedo, the CESGA Foundation, ICFO, UPV/EHU, and several CSIC institutes) and by international centers such as CERN openlab, the University of Toronto's Matterlab, Chalmers University's WACQT center, PSNC in Poznan, and HLRS in Stuttgart.

CTIC develops and operates the platform with its own funds, with the collaboration of the Quantum and High Performance Computing (QHPC) Group at the University of Oviedo. The development of QUTE relies on the ISAAC supercomputer, a quantum computing simulation infrastructure acquired by CTIC in 2019 with funding from the Asturias Program. In addition to technological development, CTIC directly provides the support service to user institutions, contributing its knowledge of quantum programming and algorithm design for specific use cases.