Contact us
Among many physical platforms, superconducting quantum hardware is well-suited for scaling the number of qubits and improving their fidelity while maintaining connectivity and thus becomes a preferred technology in the NISQ (Noisy Intermediate Scale Quantum) era with roadmaps towards fault tolerance. This is an easy and cost-effective way to establish a quantum program based on the existing expertise in microwave electronics.
As superconducting quantum hardware remains the leading platform for large industry vendors, this becomes a must-have experience for future quantum talent. The investment in the overall quantum computing market was $2.3 billion in 2022, this number is expected to grow at a compound annual growth rate of 11.5% from 2023 through 2027, reaching approximately $16.4 billion by the end of 2027.
Quantum computers are no longer just a theoretical concept. At IQM, we are already constructing these machines, and they are being used for research and education at institutions around the world. While quantum computers aren't yet ready to replace traditional computing, the technology is advancing rapidly, and industrial applications of quantum computing may be possible in the near future.
That's why we're also working with partners from industry and academia to unlock the algorithms for this era of quantum utility, which would mean we could solve some of these very hard problems faster, better, or with fewer resources than with traditional computing. And because quantum algorithms are so different from traditional algorithms, there are new skills to master. That is why we are committed to driving quantum education and creating the workforce needed to ensure that we all benefit from advances in quantum computing.
Quantum computing can revolutionize our ability to simulate the behavior of complex quantum systems, such as molecules and materials.
Quantum simulation has the potential to lead to breakthroughs in fields such as:
Quantum computing can also be used to solve optimization problems, which are problems that involve finding the best solution from a set of possible solutions.
Quantum optimization has the potential to improve a wide variety of algorithms and decision-making processes, including:
With our latest benchmarks measured on the 20-qubit quantum computer, we have demonstrated a median two-qubit (CZ) gate fidelity of 99.51% across 30 qubit pairs, with maximum fidelity over a single pair reaching as high as 99.8%.
Among the system-level benchmarks IQM obtained:
