More than 35,000 quantum developers now have access to BTQ Technologies’ MIMIQ emulator through qBraid’s managed API, expanding the reach of large-scale quantum simulation. MIMIQ bypasses the memory limitations of standard simulators by pairing optimized state-vector emulation with Matrix Product State techniques, allowing circuits with thousands of qubits and millions of gates to be modeled. “Quantum computing requires more than advances in hardware,” says Olivier Roussy Newton, CEO of BTQ Technologies. This integration supports the development of the broader quantum computing ecosystem by enabling validation and optimization before using quantum processing units.
MIMIQ Emulator Extends Simulation to Thousands of Qubits
The approach circumvents memory limitations inherent in traditional simulation by limiting the degree of entanglement within the simulated circuit. The integration of MIMIQ into qBraid’s managed API extends its reach to over 35,000 quantum developers, providing them with a platform to validate algorithms at scales approaching those of real quantum hardware.
Developers can now test and refine circuits before committing valuable quantum processing unit (QPU) time, and study the effects of noise and the performance of error-correction protocols at a larger scale than previously possible. The Provider Plugin facilitating this connection is available as open-source software under the Apache License 2.0, built upon QPerfect’s open-source mimiqcircuits-python library.
This expanded access to large-scale emulation addresses a critical need in quantum software development, as developers increasingly design circuits that exceed the capacity of exact simulation methods. “At QPerfect, we build the full software stack quantum teams need to get from algorithm to hardware, and emulation at scale is one essential step on that path,” said Philippe Blot, CEO of QPerfect. Ryan Hill, CTO of qBraid, added, “MIMIQ gives a place to run those circuits before they ever touch hardware, through the same SDK they already use for every other device on qBraid.”
Developers on qBraid are increasingly working at scales that exact simulation can’t reach, and many of them now build alongside AI agents that design, test, and iterate on circuits for them.
Ryan Hill, CTO, qBraid
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