Quobly and Hon Hai Research Institute release an open-source toolbox to explore Quantum Phase Estimation for fault-tolerant quantum computing

Grenoble (France) and Taipei (Taiwan) – May, 12^th 2026 – Quobly, a French pioneer in silicon-based quantum computing, and Taiwan’s Hon Hai Research Institute, the R&D arm of Hon Hai Technology Group (Foxconn), today announced the release of an open-source numerical toolbox, jointly developed by the two partners, dedicated to the Quantum Phase Estimation (QPE) algorithm, a cornerstone of fault-tolerant quantum computing with major applications in quantum chemistry and materials science.

QPE is widely regarded as a key algorithm for computing ground-state energies of molecular systems on future fault-tolerant quantum computers. While its theoretical properties and asymptotic cost scalings are well understood, practical resource estimates and realistic performance trade-offs remain largely unexplored, due to the difficulty of simulating QPE beyond toy models.

The newly released toolbox aims to bridge this gap by providing researchers with a practical environment to explore QPE implementations and their resource implications, with a strong focus on understanding algorithmic building blocks and their practical implementation constraints.

 

From theory to practice: exploring the full QPE pipeline

 The QPE Toolbox is designed to give quantum algorithm practitioners a hands-on, numerical understanding of the full QPE workflow, from chemistry preprocessing to phase estimation, in a regime that challenges classical simulation while remaining computationally tractable.

Built on advanced tensor network techniques, the toolbox enables users to:

• Prepare physically motivated initial states using DMRG and matrix product states,
• Encode molecular Hamiltonians into quantum circuits via trotterization or block-encoding / qubitization methods,
• Compare textbook QPE with single-ancilla Robust Phase Estimation (RPE),
• Analyze circuit depth, gate counts, and error sources without necessarily executing the circuit.

The toolbox relies on the open-source quimb library and interfaces with standard quantum chemistry tools such as PySCF, ensuring compatibility with established workflows.

The first release is designed as an educational and exploratory framework, enabling researchers to build intuition around the practical implementation of QPE and its variants.

 

A modular tool for realistic numerical experiments

Rather than attempting to simulate early fault-tolerant quantum computers, which are by nature beyond classical reach, the QPE Toolbox focuses on practical, interpretable numerical experiments in regimes accessible to classical computation, where algorithmic choices, initialization fidelity, and Hamiltonian encoding strategies can be explored in detail.

 

Illustrative use cases enabled by the toolbox include (non-exhaustive):

• Full circuit executions for ~10–20 qubits and circuits ranging from <1,000 to ~100,000 gates,
• Ground state preparation for systems up to ~20–30 qubits,
• Hamiltonian encoding for systems up to ~20–30 qubits, typically within a few hours or less on a standard laptop.

 

These capabilities allow researchers to study trade-offs between precision, circuit depth, and resource requirements, and to build practical intuition about the behavior of QPE building blocks. The toolbox is therefore designed primarily as a pedagogical and exploratory platform, helping bridge the gap between theoretical proposals and their concrete implementation constraints.

 

Open, collaborative, and evolving

The QPE Toolbox is released as open source and is intended to evolve with the community. Future developments will include variational circuit synthesis, compressed fermionic encodings, and larger-scale tensor-network simulations.

 

The toolbox is available on GitHub: https://github.com/quobly-sw/qpe-toolbox

 

Documentation and example workflows are provided to help researchers explore the different components of the QPE pipeline.

 

“Our goal is to provide a practical, numerical playground for QPE, one that helps researchers move beyond purely theoretical cost models and develop realistic intuition for fault-tolerant quantum algorithms,” said Thibaud Louvet, Quantum Algorithms Scientist at Quobly.

 

“By combining state-of-the-art quantum algorithms with advanced tensor-network techniques, this toolbox offers researchers a structured environment to explore and better understand the practical requirements of future quantum applications,” said Min-Hsiu Hsieh, Director of the Quantum Computing Research Center at Hon Hai Research Institute.

 

The jointly developed software is free for use by academics and researchers. This collaboration reflects a shared commitment by Quobly and Hon Hai Research Institute to advancing algorithm-hardware co-design and accelerating progress toward practical fault-tolerant quantum computing.

About Quobly

Quobly is a pioneer in quantum microelectronics, developing silicon-based quantum chips using proven semiconductor manufacturing processes. Founded in 2022 in Grenoble, France, the company builds on over 15 years of collaborative research between world-class institutions CEA-Leti and CNRS, combining expertise in quantum physics and microelectronics. Co-founded by Maud Vinet, Ph.D. in quantum physics, author of 300+ papers and 70+ patents, and Tristan Meunier, a leading expert in semiconductor quantum engineering trained under Nobel laureate Serge Haroche, Quobly bridges science and industry to make quantum computing scalable and manufacturable.

The company has a strategic partnership with STMicroelectronics to accelerate the industrialization of its silicon quantum chips. In 2023, Quobly raised €19 million, a record European seed round for a quantum hardware startup, followed in 2025 by €21 million to advance its Q100T program, a key step toward fault-tolerant quantum computing. Quobly has offices in France, Singapore, and Canada.

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About Hon Hai Research Institute

The institute, founded in 2020 and part of Hon Hai Technology Group (Foxconn), has five research centers. Each center has an average of 40 high technology R&D professionals, all of whom are focused on the research and development of new technologies, the strengthening of Foxconn’s technology and product innovation pipeline, efforts to support the Group’s transformation from “brawn” to “brains”, and the enhancement of the competitiveness of Foxconn’s “3+3+3” strategy.

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