Quantinuum announces InQuanto – an advanced computational chemistry platform for quantum computers

Quantinuum was created in 2021 by the merger of Honeywell Quantum Solutions (quantum hardware) and Cambridge Quantum Computing (quantum software). Quantinuum has launched InQuanto, a python-based quantum chemistry software platform that runs chemistry algorithms on current quantum hardware, following a series of previous announcements showcasing record quantum volume and an upgrade to QuantumNLP. InQuanto is based on TKET, Quantinuum’s open-source agnostic software development kit used to create and run programs.

InQuanto’s ongoing research began in 2019 and resulted in the publication of several articles under the EUMEN research name. InQuanto was developed and deployed by the Quantum Chemistry team to enable collaboration with global partners exploring quantum computing use cases suitable for their industries. Partners included BMW, Honeywell, JSR, Nippon Steel Corporation and TotalEnergies.

Dr. Jenni Strabley, Senior Director of Offer Management at Quantinuum, emphasized the importance of collaboration with customers.

“InQuanto offers its customers collaborative support no matter what stage of quantum research they are in,” she said. “If a customer is not ready to start a quantum program on their own, our quantum chemistry team will work side-by-side with their subject matter experts to investigate the problem, understand their capabilities, and help them develop a research. .”

Dr. Strabley explained that Quantinuum also offers a license for InQuanto, which includes access to the Honeywell System H1 trapped ion quantum computer. Customers may optionally use other quantum services with the license.

Algorithms and workflow

The latest and most essential quantum chemistry algorithms can be found in InQuanto. With the flexibility of the InQuanto platform and its tools, chemists can create a workflow for their specific use case.

InQuanto includes the Variational Quantum Eigensolver (VQE) algorithm, which is the most widely used variational algorithm for quantum chemical simulations on short-term quantum computers. VQE calculates the ground state energy of molecules using shallow quantum circuits in a classical-quantum hybrid loop arrangement.

Other algorithms such as ADAPT-VQE, Quantum Subspace Expansion and penalty-based VQE are also included in InQuanto for ground state and excited state calculations. It also allows users to choose from Quantinuum’s chemistry-specific noise mitigation methods.

For molecules too large to run on short-term quantum machines, InQuanto uses integration, a classic technique that has been adapted to quantum. Integration divides a wave function into fragments. Each fragment requires fewer qubits than the whole. Individual fragments are quantum-resolved and then all fragment solutions are recombined as the ground state of the entire molecule.

Dr. Simon McAdams, Product Manager for InQuanto, explained how fragmentation has been used recently.

“In our recent work with a large energy company, we modeled the absorption and interaction of a carbon dioxide molecule with an adsorbent known as an organometallic structure. This is the first time that this type of system has been modeled using quantum computing algorithms.”

If InQuanto has as widespread use as expected, it should lead to more user-generated research papers, which will benefit the entire ecosystem and advance chemical computational science.

The future of computational chemistry

Complete modeling of the simplest molecules is difficult for today’s supercomputers. As the number of electrons or atoms increases, the calculation becomes exponentially more difficult.

Calculating the quantum interaction between a few electrons in an atom may seem simple, but it is not. Even a supercomputer capable of performing over 500 trillion floating point operations per second will not compute an accurate solution. Unless some new classical computing technology emerges, only quantum computing has the potential to handle complex calculations like this. Here are some reasons:

  • There is no classical computational equivalent to the quantum combination of entanglement (a mysterious quantum force linking qubits together), superposition, and interference (a bias for the correct solution). Together, these properties of quantum mechanics allow quantum computers to process multiple logic states simultaneously.
  • Quantum computers are inherently powerful. A small quantum computer equipped with 30 qubits is comparable to a classical computer capable of performing 10,000 billion floating point operations per second. Future fault-tolerant quantum computers with millions of qubits will likely be able to simulate the largest of many-body systems.
  • Qubits can be used to represent electron spin orbits, and qubit entanglement can represent electron-electron interactions.
  • Quantum computers double in power every time a qubit is added. Every year, most quantum computing companies add several qubits to their systems. The number of qubits will start to increase exponentially in the future if physics allows.


Quantum computational chemistry has the potential to address some of the most complex and important applications in the world. These include climate change, new drugs, new materials, power grid optimization, efficient fertilizer manufacturing and more.

With InQuanto, computational chemists and quantum developers can explore the capabilities of today’s quantum computers to model industrially relevant molecules and materials.

Despite advances in error migration and qubit fidelity, more accurate calculations of large, complex systems are likely to experience their greatest breakthroughs with error-correcting quantum systems.

On the positive side, many experts believe that such a machine will be available within the decade. It is therefore essential for companies to start planning and training the workforce now.

From this point of view, in addition to being a research platform, InQuanto is also a training tool. It allows researchers to prepare for the possibility of working with fault-tolerant quantum computers capable of modeling large molecules.

Patrick Moorhead, CEO and Chief Analyst of Moor Insights and Strategy, has 25 years of experience in high-tech companies leading strategy, product management, product marketing and corporate marketing. He understands the value and importance of early training in emerging technologies.

“Quantum computing offers a pathway to the rapid and cost-effective development of new molecules and materials that could unlock new answers to some of the biggest challenges we face,” he said. “The way to ensure progress is to start prototyping now, using real use cases, so that methods are scaled to meet real industry needs. InQuanto is designed to do just that.

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Note: Moor Insights & Strategy writers and editors may have contributed to this article.

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