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QuantrolOx's raise is a funding story, but it points to a real bottleneck: manual calibration of physical qubits is a major operational cost as processors grow. Its machine-learning closed-loop approach to characterization and gate tuning is worth watching, though the article offers no performance benchmarks or independent validation. Readers should judge whether the hardware-agnostic claims hold up across real testbeds.
QuantrolOx Raises €12 Million ($13.36 Million USD) Series A2 to Scale Automated Quantum Control Software and U.S. Operations
QuantrolOx has secured €12 million ($13.36 million USD) in Series A2 funding, bringing its total funding to approximately €28 million. The company, which specializes in automated quantum control software, will use the investment to expand commercial deployments of its Quantum EDGE™ software, grow its educational offerings, and strengthen its North American presence. This funding will help QuantrolOx address the challenges of manual calibration in quantum systems by automating the process with machine-learning-driven solutions. The post QuantrolOx Raises €12 Million ($13.36 Million USD) Series A2 to Scale Automated Quantum Control Software and U.S. Operations appeared first on Quantum Computing Report.
Automated quantum control software developer QuantrolOx has raised €12 million (~$13.36 million USD) in a Series A2 funding round led by UK venture capital firm IW Capital alongside co-investment from the European Innovation Council (EIC) Fund. The financing round…
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