Quantum Machines Unveils Open-Source Qualibrate to Accelerate Quantum System Calibration

Quantum Machines, a leading provider of advanced hybrid quantum-classical control solutions, today announced the launch of Qualibrate (styled as QUAlibrate), an open-source framework designed to streamline quantum computer calibration. It significantly reduces calibration times from several hours to just minutes.
Tackling one of quantum computing's most significant scaling challenges, this new framework from Quantum Machines facilitates rapid, modular calibration while encouraging a worldwide ecosystem for developing and sharing calibration protocols.
The framework cuts calibration time substantially and delivers a complete solution for designing, running, and sharing calibration protocols across various quantum computing systems. Qualibrate’s open ecosystem allows global researchers and companies to collectively build on progress, speeding up the journey toward practical quantum computers.
Calibration is essential not only for initial setup but also for ongoing maintenance of quantum computer performance, as it compensates for system drift during operation.
As quantum systems expand, calibration complexity increases exponentially. For example, fully calibrating a 100-qubit superconducting quantum computer from scratch can require up to two days. Even recalibrating a precalibrated system can take over an hour. This inefficiency creates a major obstacle when scaling to future systems with hundreds of thousands of qubits.
“We focus on both calibration speed and quality—two factors that sometimes conflict—and this balance influences overall quantum computer performance,” stated Yonatan Cohen, CTO of Quantum Machines. “We developed an open-source solution because we believe the quantum community is best positioned to overcome this challenge together. Researchers in academia and industry are constantly designing innovative calibration algorithms and protocols. One day, a team in Boston might introduce a protocol that improves quantum operation fidelity; the next day, a European company could develop a method that accelerates calibration. Solving this foundational issue requires collaboration—letting teams instantly adopt and build on each other’s breakthroughs.”
To address this, Quantum Machines created Qualibrate, an open-source calibration framework that shifts quantum calibration from disconnected scripts to an integrated, modular system. Qualibrate empowers quantum researchers and engineers to develop reusable calibration components, assemble them into sophisticated workflows, and run calibrations through an intuitive user interface. By abstracting hardware complexity, the platform lets teams concentrate on quantum system logic instead of low-level implementation.
“Qualibrate has been a game-changer for our organization,” said John Martinis, CTO of Qolab. “Its automated calibration completes full calibrations in under 10 minutes—work that previously took up to two hours of manual effort. This saves valuable time, enabling our team to focus on accelerating QPU development.”
In a recent demonstration at the Israeli Quantum Computing Center (IQCC), Qualibrate performed a multi-qubit calibration of superconducting qubits in only 140 seconds, showcasing the system’s speed and effectiveness under real-world conditions.
Because Qualibrate is open source and modular, new calibration protocols developed by researchers can be quickly distributed, tested, and enhanced by the wider quantum computing community.
Companies can also build proprietary solutions using Qualibrate, integrating advanced techniques such as quantum system simulation and deep learning algorithms. This fosters an ecosystem where core calibration improvements are shared openly, while specialized tools drive performance forward.
Alongside the framework, Quantum Machines is releasing its first calibration graph for superconducting quantum computers—a ready-to-deploy, customizable calibration package.
This graph uses Qualibrate’s parallel calibration features to drastically shorten calibration times. Moving forward, Quantum Machines and NVIDIA are building software libraries that will integrate Qualibrate with systems like the NVIDIA DGX Quantum, enabling even quicker calibration runs and higher-fidelity results through machine learning models.
Quantum Machines was founded in early 2018 by Itamar Sivan (CEO), Yonatan Cohen (CTO), and Nissim Ofek (Chief Engineer). All three founders hold PhDs in physics and have extensive expertise in quantum computing and quantum electronics.
Since its inception, the company has secured $280 million in funding from top venture funds, including PSG Equity, Red Dot Capital Partners, Intel Capital, TLV Partners, and Battery Ventures. Quantum Machines employs roughly 170 people, with half based in Israel and the remainder spread across Europe, the U.S., and other regions.
Quantum computing researchers and engineers can start using QUAlibrate immediately by visiting the open-source repository at: https://github.com/qua-platform/qualibrate.
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Quantum Machines, a leading provider of advanced hybrid quantum-classical control solutions, today announced the launch of Qualibrate (styled as QUAlibrate), an open-source framework designed to streamline quantum computer calibration. It significantly reduces calibration times from several hours to just minutes.
Tackling one of quantum computing's most significant scaling challenges, this new framework from Quantum Machines facilitates rapid, modular calibration while encouraging a worldwide ecosystem for developing and sharing calibration protocols.
The framework cuts calibration time substantially and delivers a complete solution for designing, running, and sharing calibration protocols across various quantum computing systems. Qualibrate’s open ecosystem allows global researchers and companies to collectively build on progress, speeding up the journey toward practical quantum computers.
Calibration is essential not only for initial setup but also for ongoing maintenance of quantum computer performance, as it compensates for system drift during operation.
As quantum systems expand, calibration complexity increases exponentially. For example, fully calibrating a 100-qubit superconducting quantum computer from scratch can require up to two days. Even recalibrating a precalibrated system can take over an hour. This inefficiency creates a major obstacle when scaling to future systems with hundreds of thousands of qubits.
“We focus on both calibration speed and quality—two factors that sometimes conflict—and this balance influences overall quantum computer performance,” stated Yonatan Cohen, CTO of Quantum Machines. “We developed an open-source solution because we believe the quantum community is best positioned to overcome this challenge together. Researchers in academia and industry are constantly designing innovative calibration algorithms and protocols. One day, a team in Boston might introduce a protocol that improves quantum operation fidelity; the next day, a European company could develop a method that accelerates calibration. Solving this foundational issue requires collaboration—letting teams instantly adopt and build on each other’s breakthroughs.”
To address this, Quantum Machines created Qualibrate, an open-source calibration framework that shifts quantum calibration from disconnected scripts to an integrated, modular system. Qualibrate empowers quantum researchers and engineers to develop reusable calibration components, assemble them into sophisticated workflows, and run calibrations through an intuitive user interface. By abstracting hardware complexity, the platform lets teams concentrate on quantum system logic instead of low-level implementation.
“Qualibrate has been a game-changer for our organization,” said John Martinis, CTO of Qolab. “Its automated calibration completes full calibrations in under 10 minutes—work that previously took up to two hours of manual effort. This saves valuable time, enabling our team to focus on accelerating QPU development.”
In a recent demonstration at the Israeli Quantum Computing Center (IQCC), Qualibrate performed a multi-qubit calibration of superconducting qubits in only 140 seconds, showcasing the system’s speed and effectiveness under real-world conditions.
Because Qualibrate is open source and modular, new calibration protocols developed by researchers can be quickly distributed, tested, and enhanced by the wider quantum computing community.
Companies can also build proprietary solutions using Qualibrate, integrating advanced techniques such as quantum system simulation and deep learning algorithms. This fosters an ecosystem where core calibration improvements are shared openly, while specialized tools drive performance forward.
Alongside the framework, Quantum Machines is releasing its first calibration graph for superconducting quantum computers—a ready-to-deploy, customizable calibration package.
This graph uses Qualibrate’s parallel calibration features to drastically shorten calibration times. Moving forward, Quantum Machines and NVIDIA are building software libraries that will integrate Qualibrate with systems like the NVIDIA DGX Quantum, enabling even quicker calibration runs and higher-fidelity results through machine learning models.
Quantum Machines was founded in early 2018 by Itamar Sivan (CEO), Yonatan Cohen (CTO), and Nissim Ofek (Chief Engineer). All three founders hold PhDs in physics and have extensive expertise in quantum computing and quantum electronics.
Since its inception, the company has secured $280 million in funding from top venture funds, including PSG Equity, Red Dot Capital Partners, Intel Capital, TLV Partners, and Battery Ventures. Quantum Machines employs roughly 170 people, with half based in Israel and the remainder spread across Europe, the U.S., and other regions.
Quantum computing researchers and engineers can start using QUAlibrate immediately by visiting the open-source repository at: https://github.com/qua-platform/qualibrate.
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