A practically useful quantum computer will need many thousands of qubits – the fundamental building blocks of quantum computers. Due to imperfections in control instruments, fabrication and design, qubits have subtle variations requiring different sets of control parameters to render each one usable. An intricate process is required to be able to reach a practically useful quantum computer. As the number of qubits is increased, the challenge of tuning and characterizing them grows significantly. Successful tuning, optimizing, and stabilizing of many thousands of qubits, regardless of their variability, requires intelligent automation. A big parameter space must be explored efficiently, data interpreted, patterns recognized and decisions made in real-time. Current solutions that depend on human expertise are not good enough and will not scale. QuantrolOx is building automated machine learning-based control software for quantum technologies to tune, stabilize, and optimize qubits. QuantrolOx’s software is technology agnostic and applicable to all types of quantum technologies, however, initially, the company is targeting solid-state qubits where the team has already demonstrated substantial practical benefits.
B2B
1 to 25
N/A
N/A
Scaling Up
2021
Application Software
N/A
Increase Efficiency
Revenue Growth
Increase Productivity
Service
Yes
Active
Machine Learning
Software
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Machine Learning Engineer – Applied Research
Machine Learning Engineer – Customer Projects
Applied Researcher
Software Engineer – Customer Projects
Technical Team Lead
AI/ML Professionals
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1
$3.73M
Company was founded 2021 and it took almost 2 years (Mar 2023) to raise first external round
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Vishal Chatrath
Co-Founder & CEO
Dominic Lennon
Co-founder and Head of Quantum Technologies
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