Quantinuum Announces λambeq Updates

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

λambeq update introduces many new important features to provide researchers and developers with more options and flexibility in turning sentences into quantum circuits.

The quantum natural language processing team at Quantinuum, the world’s leading integrated quantum computing company, has released a major update to its open-source Python library and toolkit, λambeq (pronounced “Lambek”).

λambeq converts any natural language sentence into a quantum circuit, ready to be realised on a quantum computer. The new release has been designed for a growing community of researchers, developers and users versed in quantum natural language processing (QNLP) and natural language processing (NLP). Natural language processing markets are projected to grow 27% annually over the next five years.

The update will support the growth of QNLP and potential future applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics.
Quantinuum’s Head of Applied Quantum NLP Research, Dr. Dimitrios Kartsaklis, said: “Since we launched λambeq, we have received valuable feedback from a rapidly growing community of users, and many of the new features available today reflect this. The new version of λambeq now comes, for example, with a native state-of-the-art parser that has been fully integrated with the toolkit. Additionally, the toolkit is now equipped with a training package that supports popular supervised learning libraries, such as PyTorch, to help users efficiently train NLP tasks using the quantum circuits and tensor networks that λambeq generates. This update is all about accessibility – and crucially, reducing the time it takes to achieve results.”

Additionally, and importantly, λambeq’s new neural-based CCG parser, Bobcat, is trained on a large human-annotated corpus of syntactic derivations. It is fully integrated with the toolkit, simplifying the installation process, and presents improved state-of-the-art parsing performance. The previous parser remains part of the toolkit, and for the benefit of the community, Bobcat will also be released as a separate stand-alone open-source tool in due course.

The new update is equipped with a command-line interface, making most of the toolkit’s functionality available to users with no programming knowledge. It also contains a new supervised training module designed to simplify the process of training parameterised quantum circuits and tensor networks in a machine learning setup.

λambeq is the first quantum NLP and computational linguistics toolkit. It can convert a sentence into a quantum circuit that inherits its entanglement structure from the sentence’s syntactic structure. This construction is motivated by formal mathematical correspondences between mathematical models of grammar and quantum protocols, as established by senior researchers at Quantinuum, Chief Scientist Prof. Bob Coecke and Head of AI Prof. Stephen Clark.

With this update, λambeq becomes more flexible in providing users with more options on the quantum circuits it can generate. It allows manipulation of syntax diagrams and makes it simpler to define the quantum circuits from the syntactic structure.The visualisation of λambeq’s output has also been improved, and documentation has been expanded with numerous examples to remove the barrier to entry for general users.

 

 

WHERE TO FIND LAMBEQ

λambeq has been released as a conventional Python repository on GitHub and is available here
https://github.com/CQCL/lambeq

More details about the new release can be found here
https://cqcl.github.io/lambeq/release_notes.html

The documentation and tutorials can be found here
https://cqcl.github.io/lambeq/index.html

 

FOR MORE INFORMATION

Peter Sigrist
peter.sigrist@cambridgequantum.com
+44(0)7720 056 981

 

QUANTINUUM

Quantinuum is the world’s largest integrated quantum computing company, formed by the combination of Honeywell Quantum Solutions’ world leading hardware and Cambridge Quantum’s class leading middleware and applications.

Quantinuum employs over 400 people including 300 scientists, at eight sites in the US, Europe, and Japan.
Science led and enterprise driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Quantinuum’s focus is to create scalable and commercial quantum solutions to solve the world’s most pressing problems, in fields such as energy, logistics, climate change, and health.

Quantinuum’s open-source developer toolkit TKET provides platform-inclusive access to the world’s leading quantum hardware and simulators and enhances the performance of every Quantinuum product, including cybersecurity key-generation platform Quantum Origin, quantum computational chemistry and materials science package EUMEN, and λambeq, Quantinuum’s quantum natural language processing and computational linguistics toolkit.

Quantinuum’s H1 generation quantum computer, Powered by Honeywell, is one of the most advanced in the world and was the first to pass the industry standard quantum volume 2048 benchmark. Quantinuum is committed to increasing the quantum volume of its commercial quantum computers by orders of magnitude each year for the next five years.

 

 

Modeling Carbon Capture with Quantum Computing

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

λambeq update introduces many new important features to provide researchers and developers with more options and flexibility in turning sentences into quantum circuits.

The quantum natural language processing team at Quantinuum, the world’s leading integrated quantum computing company, has released a major update to its open-source Python library and toolkit, λambeq (pronounced “Lambek”).

λambeq converts any natural language sentence into a quantum circuit, ready to be realised on a quantum computer. The new release has been designed for a growing community of researchers, developers and users versed in quantum natural language processing (QNLP) and natural language processing (NLP). Natural language processing markets are projected to grow 27% annually over the next five years.

The update will support the growth of QNLP and potential future applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics.
Quantinuum’s Head of Applied Quantum NLP Research, Dr. Dimitrios Kartsaklis, said: “Since we launched λambeq, we have received valuable feedback from a rapidly growing community of users, and many of the new features available today reflect this. The new version of λambeq now comes, for example, with a native state-of-the-art parser that has been fully integrated with the toolkit. Additionally, the toolkit is now equipped with a training package that supports popular supervised learning libraries, such as PyTorch, to help users efficiently train NLP tasks using the quantum circuits and tensor networks that λambeq generates. This update is all about accessibility – and crucially, reducing the time it takes to achieve results.”

Additionally, and importantly, λambeq’s new neural-based CCG parser, Bobcat, is trained on a large human-annotated corpus of syntactic derivations. It is fully integrated with the toolkit, simplifying the installation process, and presents improved state-of-the-art parsing performance. The previous parser remains part of the toolkit, and for the benefit of the community, Bobcat will also be released as a separate stand-alone open-source tool in due course.

The new update is equipped with a command-line interface, making most of the toolkit’s functionality available to users with no programming knowledge. It also contains a new supervised training module designed to simplify the process of training parameterised quantum circuits and tensor networks in a machine learning setup.

λambeq is the first quantum NLP and computational linguistics toolkit. It can convert a sentence into a quantum circuit that inherits its entanglement structure from the sentence’s syntactic structure. This construction is motivated by formal mathematical correspondences between mathematical models of grammar and quantum protocols, as established by senior researchers at Quantinuum, Chief Scientist Prof. Bob Coecke and Head of AI Prof. Stephen Clark.

With this update, λambeq becomes more flexible in providing users with more options on the quantum circuits it can generate. It allows manipulation of syntax diagrams and makes it simpler to define the quantum circuits from the syntactic structure.The visualisation of λambeq’s output has also been improved, and documentation has been expanded with numerous examples to remove the barrier to entry for general users.

 

 

WHERE TO FIND LAMBEQ

λambeq has been released as a conventional Python repository on GitHub and is available here
https://github.com/CQCL/lambeq

More details about the new release can be found here
https://cqcl.github.io/lambeq/release_notes.html

The documentation and tutorials can be found here
https://cqcl.github.io/lambeq/index.html

 

FOR MORE INFORMATION

Peter Sigrist
peter.sigrist@cambridgequantum.com
+44(0)7720 056 981

 

QUANTINUUM

Quantinuum is the world’s largest integrated quantum computing company, formed by the combination of Honeywell Quantum Solutions’ world leading hardware and Cambridge Quantum’s class leading middleware and applications.

Quantinuum employs over 400 people including 300 scientists, at eight sites in the US, Europe, and Japan.
Science led and enterprise driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Quantinuum’s focus is to create scalable and commercial quantum solutions to solve the world’s most pressing problems, in fields such as energy, logistics, climate change, and health.

Quantinuum’s open-source developer toolkit TKET provides platform-inclusive access to the world’s leading quantum hardware and simulators and enhances the performance of every Quantinuum product, including cybersecurity key-generation platform Quantum Origin, quantum computational chemistry and materials science package EUMEN, and λambeq, Quantinuum’s quantum natural language processing and computational linguistics toolkit.

Quantinuum’s H1 generation quantum computer, Powered by Honeywell, is one of the most advanced in the world and was the first to pass the industry standard quantum volume 2048 benchmark. Quantinuum is committed to increasing the quantum volume of its commercial quantum computers by orders of magnitude each year for the next five years.

 

 

Daniel Hussein Vice President Sales & Business Development

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

λambeq update introduces many new important features to provide researchers and developers with more options and flexibility in turning sentences into quantum circuits.

The quantum natural language processing team at Quantinuum, the world’s leading integrated quantum computing company, has released a major update to its open-source Python library and toolkit, λambeq (pronounced “Lambek”).

λambeq converts any natural language sentence into a quantum circuit, ready to be realised on a quantum computer. The new release has been designed for a growing community of researchers, developers and users versed in quantum natural language processing (QNLP) and natural language processing (NLP). Natural language processing markets are projected to grow 27% annually over the next five years.

The update will support the growth of QNLP and potential future applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics.
Quantinuum’s Head of Applied Quantum NLP Research, Dr. Dimitrios Kartsaklis, said: “Since we launched λambeq, we have received valuable feedback from a rapidly growing community of users, and many of the new features available today reflect this. The new version of λambeq now comes, for example, with a native state-of-the-art parser that has been fully integrated with the toolkit. Additionally, the toolkit is now equipped with a training package that supports popular supervised learning libraries, such as PyTorch, to help users efficiently train NLP tasks using the quantum circuits and tensor networks that λambeq generates. This update is all about accessibility – and crucially, reducing the time it takes to achieve results.”

Additionally, and importantly, λambeq’s new neural-based CCG parser, Bobcat, is trained on a large human-annotated corpus of syntactic derivations. It is fully integrated with the toolkit, simplifying the installation process, and presents improved state-of-the-art parsing performance. The previous parser remains part of the toolkit, and for the benefit of the community, Bobcat will also be released as a separate stand-alone open-source tool in due course.

The new update is equipped with a command-line interface, making most of the toolkit’s functionality available to users with no programming knowledge. It also contains a new supervised training module designed to simplify the process of training parameterised quantum circuits and tensor networks in a machine learning setup.

λambeq is the first quantum NLP and computational linguistics toolkit. It can convert a sentence into a quantum circuit that inherits its entanglement structure from the sentence’s syntactic structure. This construction is motivated by formal mathematical correspondences between mathematical models of grammar and quantum protocols, as established by senior researchers at Quantinuum, Chief Scientist Prof. Bob Coecke and Head of AI Prof. Stephen Clark.

With this update, λambeq becomes more flexible in providing users with more options on the quantum circuits it can generate. It allows manipulation of syntax diagrams and makes it simpler to define the quantum circuits from the syntactic structure.The visualisation of λambeq’s output has also been improved, and documentation has been expanded with numerous examples to remove the barrier to entry for general users.

 

 

WHERE TO FIND LAMBEQ

λambeq has been released as a conventional Python repository on GitHub and is available here
https://github.com/CQCL/lambeq

More details about the new release can be found here
https://cqcl.github.io/lambeq/release_notes.html

The documentation and tutorials can be found here
https://cqcl.github.io/lambeq/index.html

 

FOR MORE INFORMATION

Peter Sigrist
peter.sigrist@cambridgequantum.com
+44(0)7720 056 981

 

QUANTINUUM

Quantinuum is the world’s largest integrated quantum computing company, formed by the combination of Honeywell Quantum Solutions’ world leading hardware and Cambridge Quantum’s class leading middleware and applications.

Quantinuum employs over 400 people including 300 scientists, at eight sites in the US, Europe, and Japan.
Science led and enterprise driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Quantinuum’s focus is to create scalable and commercial quantum solutions to solve the world’s most pressing problems, in fields such as energy, logistics, climate change, and health.

Quantinuum’s open-source developer toolkit TKET provides platform-inclusive access to the world’s leading quantum hardware and simulators and enhances the performance of every Quantinuum product, including cybersecurity key-generation platform Quantum Origin, quantum computational chemistry and materials science package EUMEN, and λambeq, Quantinuum’s quantum natural language processing and computational linguistics toolkit.

Quantinuum’s H1 generation quantum computer, Powered by Honeywell, is one of the most advanced in the world and was the first to pass the industry standard quantum volume 2048 benchmark. Quantinuum is committed to increasing the quantum volume of its commercial quantum computers by orders of magnitude each year for the next five years.

 

 

Quantinuum

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

λambeq update introduces many new important features to provide researchers and developers with more options and flexibility in turning sentences into quantum circuits.

The quantum natural language processing team at Quantinuum, the world’s leading integrated quantum computing company, has released a major update to its open-source Python library and toolkit, λambeq (pronounced “Lambek”).

λambeq converts any natural language sentence into a quantum circuit, ready to be realised on a quantum computer. The new release has been designed for a growing community of researchers, developers and users versed in quantum natural language processing (QNLP) and natural language processing (NLP). Natural language processing markets are projected to grow 27% annually over the next five years.

The update will support the growth of QNLP and potential future applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics.
Quantinuum’s Head of Applied Quantum NLP Research, Dr. Dimitrios Kartsaklis, said: “Since we launched λambeq, we have received valuable feedback from a rapidly growing community of users, and many of the new features available today reflect this. The new version of λambeq now comes, for example, with a native state-of-the-art parser that has been fully integrated with the toolkit. Additionally, the toolkit is now equipped with a training package that supports popular supervised learning libraries, such as PyTorch, to help users efficiently train NLP tasks using the quantum circuits and tensor networks that λambeq generates. This update is all about accessibility – and crucially, reducing the time it takes to achieve results.”

Additionally, and importantly, λambeq’s new neural-based CCG parser, Bobcat, is trained on a large human-annotated corpus of syntactic derivations. It is fully integrated with the toolkit, simplifying the installation process, and presents improved state-of-the-art parsing performance. The previous parser remains part of the toolkit, and for the benefit of the community, Bobcat will also be released as a separate stand-alone open-source tool in due course.

The new update is equipped with a command-line interface, making most of the toolkit’s functionality available to users with no programming knowledge. It also contains a new supervised training module designed to simplify the process of training parameterised quantum circuits and tensor networks in a machine learning setup.

λambeq is the first quantum NLP and computational linguistics toolkit. It can convert a sentence into a quantum circuit that inherits its entanglement structure from the sentence’s syntactic structure. This construction is motivated by formal mathematical correspondences between mathematical models of grammar and quantum protocols, as established by senior researchers at Quantinuum, Chief Scientist Prof. Bob Coecke and Head of AI Prof. Stephen Clark.

With this update, λambeq becomes more flexible in providing users with more options on the quantum circuits it can generate. It allows manipulation of syntax diagrams and makes it simpler to define the quantum circuits from the syntactic structure.The visualisation of λambeq’s output has also been improved, and documentation has been expanded with numerous examples to remove the barrier to entry for general users.

 

 

WHERE TO FIND LAMBEQ

λambeq has been released as a conventional Python repository on GitHub and is available here
https://github.com/CQCL/lambeq

More details about the new release can be found here
https://cqcl.github.io/lambeq/release_notes.html

The documentation and tutorials can be found here
https://cqcl.github.io/lambeq/index.html

 

FOR MORE INFORMATION

Peter Sigrist
peter.sigrist@cambridgequantum.com
+44(0)7720 056 981

 

QUANTINUUM

Quantinuum is the world’s largest integrated quantum computing company, formed by the combination of Honeywell Quantum Solutions’ world leading hardware and Cambridge Quantum’s class leading middleware and applications.

Quantinuum employs over 400 people including 300 scientists, at eight sites in the US, Europe, and Japan.
Science led and enterprise driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Quantinuum’s focus is to create scalable and commercial quantum solutions to solve the world’s most pressing problems, in fields such as energy, logistics, climate change, and health.

Quantinuum’s open-source developer toolkit TKET provides platform-inclusive access to the world’s leading quantum hardware and simulators and enhances the performance of every Quantinuum product, including cybersecurity key-generation platform Quantum Origin, quantum computational chemistry and materials science package EUMEN, and λambeq, Quantinuum’s quantum natural language processing and computational linguistics toolkit.

Quantinuum’s H1 generation quantum computer, Powered by Honeywell, is one of the most advanced in the world and was the first to pass the industry standard quantum volume 2048 benchmark. Quantinuum is committed to increasing the quantum volume of its commercial quantum computers by orders of magnitude each year for the next five years.

 

 

lambeq: Cambridge Quantum Releases World’s First Quantum Natural Language Processing Toolkit and Library

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

λambeq update introduces many new important features to provide researchers and developers with more options and flexibility in turning sentences into quantum circuits.

The quantum natural language processing team at Quantinuum, the world’s leading integrated quantum computing company, has released a major update to its open-source Python library and toolkit, λambeq (pronounced “Lambek”).

λambeq converts any natural language sentence into a quantum circuit, ready to be realised on a quantum computer. The new release has been designed for a growing community of researchers, developers and users versed in quantum natural language processing (QNLP) and natural language processing (NLP). Natural language processing markets are projected to grow 27% annually over the next five years.

The update will support the growth of QNLP and potential future applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics.
Quantinuum’s Head of Applied Quantum NLP Research, Dr. Dimitrios Kartsaklis, said: “Since we launched λambeq, we have received valuable feedback from a rapidly growing community of users, and many of the new features available today reflect this. The new version of λambeq now comes, for example, with a native state-of-the-art parser that has been fully integrated with the toolkit. Additionally, the toolkit is now equipped with a training package that supports popular supervised learning libraries, such as PyTorch, to help users efficiently train NLP tasks using the quantum circuits and tensor networks that λambeq generates. This update is all about accessibility – and crucially, reducing the time it takes to achieve results.”

Additionally, and importantly, λambeq’s new neural-based CCG parser, Bobcat, is trained on a large human-annotated corpus of syntactic derivations. It is fully integrated with the toolkit, simplifying the installation process, and presents improved state-of-the-art parsing performance. The previous parser remains part of the toolkit, and for the benefit of the community, Bobcat will also be released as a separate stand-alone open-source tool in due course.

The new update is equipped with a command-line interface, making most of the toolkit’s functionality available to users with no programming knowledge. It also contains a new supervised training module designed to simplify the process of training parameterised quantum circuits and tensor networks in a machine learning setup.

λambeq is the first quantum NLP and computational linguistics toolkit. It can convert a sentence into a quantum circuit that inherits its entanglement structure from the sentence’s syntactic structure. This construction is motivated by formal mathematical correspondences between mathematical models of grammar and quantum protocols, as established by senior researchers at Quantinuum, Chief Scientist Prof. Bob Coecke and Head of AI Prof. Stephen Clark.

With this update, λambeq becomes more flexible in providing users with more options on the quantum circuits it can generate. It allows manipulation of syntax diagrams and makes it simpler to define the quantum circuits from the syntactic structure.The visualisation of λambeq’s output has also been improved, and documentation has been expanded with numerous examples to remove the barrier to entry for general users.

 

 

WHERE TO FIND LAMBEQ

λambeq has been released as a conventional Python repository on GitHub and is available here
https://github.com/CQCL/lambeq

More details about the new release can be found here
https://cqcl.github.io/lambeq/release_notes.html

The documentation and tutorials can be found here
https://cqcl.github.io/lambeq/index.html

 

FOR MORE INFORMATION

Peter Sigrist
peter.sigrist@cambridgequantum.com
+44(0)7720 056 981

 

QUANTINUUM

Quantinuum is the world’s largest integrated quantum computing company, formed by the combination of Honeywell Quantum Solutions’ world leading hardware and Cambridge Quantum’s class leading middleware and applications.

Quantinuum employs over 400 people including 300 scientists, at eight sites in the US, Europe, and Japan.
Science led and enterprise driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Quantinuum’s focus is to create scalable and commercial quantum solutions to solve the world’s most pressing problems, in fields such as energy, logistics, climate change, and health.

Quantinuum’s open-source developer toolkit TKET provides platform-inclusive access to the world’s leading quantum hardware and simulators and enhances the performance of every Quantinuum product, including cybersecurity key-generation platform Quantum Origin, quantum computational chemistry and materials science package EUMEN, and λambeq, Quantinuum’s quantum natural language processing and computational linguistics toolkit.

Quantinuum’s H1 generation quantum computer, Powered by Honeywell, is one of the most advanced in the world and was the first to pass the industry standard quantum volume 2048 benchmark. Quantinuum is committed to increasing the quantum volume of its commercial quantum computers by orders of magnitude each year for the next five years.

 

 

Cambridge Quantum Algorithm Solves Optimisation Problems Significantly Faster, Outperforming Existing Quantum Methods

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

λambeq update introduces many new important features to provide researchers and developers with more options and flexibility in turning sentences into quantum circuits.

The quantum natural language processing team at Quantinuum, the world’s leading integrated quantum computing company, has released a major update to its open-source Python library and toolkit, λambeq (pronounced “Lambek”).

λambeq converts any natural language sentence into a quantum circuit, ready to be realised on a quantum computer. The new release has been designed for a growing community of researchers, developers and users versed in quantum natural language processing (QNLP) and natural language processing (NLP). Natural language processing markets are projected to grow 27% annually over the next five years.

The update will support the growth of QNLP and potential future applications such as automated dialogue, text mining, language translation, text-to-speech, language generation and bioinformatics.
Quantinuum’s Head of Applied Quantum NLP Research, Dr. Dimitrios Kartsaklis, said: “Since we launched λambeq, we have received valuable feedback from a rapidly growing community of users, and many of the new features available today reflect this. The new version of λambeq now comes, for example, with a native state-of-the-art parser that has been fully integrated with the toolkit. Additionally, the toolkit is now equipped with a training package that supports popular supervised learning libraries, such as PyTorch, to help users efficiently train NLP tasks using the quantum circuits and tensor networks that λambeq generates. This update is all about accessibility – and crucially, reducing the time it takes to achieve results.”

Additionally, and importantly, λambeq’s new neural-based CCG parser, Bobcat, is trained on a large human-annotated corpus of syntactic derivations. It is fully integrated with the toolkit, simplifying the installation process, and presents improved state-of-the-art parsing performance. The previous parser remains part of the toolkit, and for the benefit of the community, Bobcat will also be released as a separate stand-alone open-source tool in due course.

The new update is equipped with a command-line interface, making most of the toolkit’s functionality available to users with no programming knowledge. It also contains a new supervised training module designed to simplify the process of training parameterised quantum circuits and tensor networks in a machine learning setup.

λambeq is the first quantum NLP and computational linguistics toolkit. It can convert a sentence into a quantum circuit that inherits its entanglement structure from the sentence’s syntactic structure. This construction is motivated by formal mathematical correspondences between mathematical models of grammar and quantum protocols, as established by senior researchers at Quantinuum, Chief Scientist Prof. Bob Coecke and Head of AI Prof. Stephen Clark.

With this update, λambeq becomes more flexible in providing users with more options on the quantum circuits it can generate. It allows manipulation of syntax diagrams and makes it simpler to define the quantum circuits from the syntactic structure.The visualisation of λambeq’s output has also been improved, and documentation has been expanded with numerous examples to remove the barrier to entry for general users.

 

 

WHERE TO FIND LAMBEQ

λambeq has been released as a conventional Python repository on GitHub and is available here
https://github.com/CQCL/lambeq

More details about the new release can be found here
https://cqcl.github.io/lambeq/release_notes.html

The documentation and tutorials can be found here
https://cqcl.github.io/lambeq/index.html

 

FOR MORE INFORMATION

Peter Sigrist
peter.sigrist@cambridgequantum.com
+44(0)7720 056 981

 

QUANTINUUM

Quantinuum is the world’s largest integrated quantum computing company, formed by the combination of Honeywell Quantum Solutions’ world leading hardware and Cambridge Quantum’s class leading middleware and applications.

Quantinuum employs over 400 people including 300 scientists, at eight sites in the US, Europe, and Japan.
Science led and enterprise driven, Quantinuum accelerates quantum computing and the development of applications across chemistry, cybersecurity, finance, and optimization. Quantinuum’s focus is to create scalable and commercial quantum solutions to solve the world’s most pressing problems, in fields such as energy, logistics, climate change, and health.

Quantinuum’s open-source developer toolkit TKET provides platform-inclusive access to the world’s leading quantum hardware and simulators and enhances the performance of every Quantinuum product, including cybersecurity key-generation platform Quantum Origin, quantum computational chemistry and materials science package EUMEN, and λambeq, Quantinuum’s quantum natural language processing and computational linguistics toolkit.

Quantinuum’s H1 generation quantum computer, Powered by Honeywell, is one of the most advanced in the world and was the first to pass the industry standard quantum volume 2048 benchmark. Quantinuum is committed to increasing the quantum volume of its commercial quantum computers by orders of magnitude each year for the next five years.

 

 

Cambridge Quantum and Honeywell Combine

Quantinuum Announces Updates To

Quantum Natural Language Processing Toolkit λambeq, Enhancing Accessibility

Honeywell Quantum Solutions, an investor and commercial partner with Cambridge Quantum since 2019, and Cambridge Quantum have combined, forming a new company that is extremely well-positioned to lead the quantum computing industry by offering both hardware and software solutions.

  • Cambridge Quantum, a global leader in quantum software and algorithms, today announced they have entered into a definitive agreement under which Cambridge Quantum will combine with Honeywell Quantum Solutions (HQS), a Honeywell business unit and maker of the highest performing quantum computer currently available. Honeywell has been an investor in and commercial partner with Cambridge Quantum since 2019.
  • The combination will form a new company that is extremely well-positioned to lead the quantum computing industry by offering advanced, fully integrated hardware and software solutions at an unprecedented pace, scale and level of performance to large high-growth markets worldwide.
  • The new company’s combined expertise will deliver solutions to customers globally as well as spur advances that will accelerate the adoption and impact of quantum technology worldwide.

“Joining together into an exciting newly combined enterprise, HQS and CQ will become a global powerhouse that will create and commercialize quantum solutions that address some of humanity’s greatest challenges, while driving the development of what will become a $1 trillion industry,” said Ilyas Khan, founder of CQ. “I am excited to lead a company that has the best people and technologies in the quantum computing industry and the best and boldest clients. Together we will lead the industry as it grows and matures, and create tangible, credible, provable and science-led advances.”

Honeywell’s Chairman and CEO Darius Adamczyk noted, “The new company will have the best talent in the industry, the world’s highest performing quantum computer, the first and most advanced quantum operating system, and comprehensive, hardware- agnostic software that will drive the future of the quantum computing industry. The new company will be extremely well positioned to create value in the near-term within the quantum computing industry by offering the critical global infrastructure needed to support the sector’s explosive growth.”

Adamczyk added, “Since we first announced Honeywell’s quantum business in 2018, we have heard from many investors who have been eager to invest directly in our leading technologies at the forefront of this exciting and dynamic industry – now, they will be able to do so. The new company will provide the best avenue for us to onboard new, diverse sources of capital at scale that will help drive rapid growth.”

“Since we first announced Honeywell’s quantum business in 2018, we have heard from many investors who have been eager to invest directly in our leading technologies at the forefront of this exciting and dynamic industry – now, they will be able to do so. The new company will provide the best avenue for us to onboard new, diverse sources of capital at scale that will help drive rapid growth.”

Dariuz Adamczyk

Founded in 2014, Cambridge Quantum has assembled the industry’s largest scientific team in quantum algorithms and software to achieve major advances in cybersecurity, finance, drug discovery, materials science, optimization, quantum machine learning, natural language processing and more. Cambridge Quantum will continue its presence and expand its software and algorithm development team in the UK, with offices in Cambridge, London and Oxford, and overseas in the USA (Washington), Germany and Japan. CQ will operate with no change to its globally recognized brand.

Honeywell began its quantum computer development program a decade ago and uses trapped-ion technology that uses charged atoms to hold quantum information. The Honeywell System Model H1 consistently achieves the highest quantum volume – a comprehensive performance measurement used widely by the industry – on a commercial quantum computer.

The new company, which will be formally named in due course, will have a long-term agreement with Honeywell to help manufacture the critical ion traps needed to power the quantum hardware. Honeywell will invest between US$270million to US$300 million in the new company.

 

 

ADDITIONAL DETAILS

Honeywell will be the majority shareholder of the new company, and CQ’s shareholders will own over 45% of the new company. The transaction has been unanimously approved by the Boards of Directors of both Cambridge Quantum and Honeywell. The deal is intended to close in Q3 this calendar year and is subject to the satisfaction of certain regulatory approvals, and other customary closing conditions.

Merrill Lynch International (“BofA Securities”) is acting as exclusive financial advisor to Cambridge Quantum, while Morrison & Foerster LLP is acting as its legal advisor. J.P. Morgan Securities LLC is acting as exclusive financial advisor to Honeywell, while Freshfields Bruckhaus Deringer LLP is acting as its legal advisor.

 

ABOUT HONEYWELL

Honeywell is a Fortune 100 technology company that delivers industry-specific solutions that include aerospace products and services; control technologies for buildings and industry; and performance materials globally. Our technologies help aircraft, buildings, manufacturing plants, supply chains, and workers become more connected to make our world smarter, safer, and more sustainable. For more news and information on Honeywell, please visit www.honeywell.com/newsroom.