Numerical simulation workflows are hitting computational ceilings that classical infrastructure cannot raise on its own. ColibriTD was founded bring innovative solution to disrupt the domain of multiphysics simulation
Multi-physics simulation sits at the heart of aerospace, defense, energy, semiconductors, advanced manufacturing, and financial modelling. The equations governing these problems have not changed. The computational demands have grown beyond what classical infrastructure can comfortably handle. ColibriTD was built around this specific challenge leveraging quantum technologies in a unique way.
At ColibriTD, we develop quantum-driven multiphysics simulation tools for complex engineering systems. Our technology handles coupled physics problems with higher speed and improved accuracy. We target applications where classical methods reach their limits, from energy systems to advanced materials.
Leverage quantum algorithms within a production-ready software stack.
Run seamlessly across different quantum and classical infrastructures.
Model and simulate complex physical systems by solving advanced Partial Differential Equations.
A hybrid quantum-classical algorithm that integrates seamlessly into engineers' software or business applications
Different quantum technologies offer distinct advantages, our multi-hardware approach lets you leverage the most suitable platform for every multiphysics simulation.
Unlock the potential of quantum computing by seamlessly accessing various technologies in one place.
Optimize energy consumption and computational runtimes with our advanced quantum computing solution.
Our advanced technology analyzes your computational needs and selects the most efficient quantum hardware.
Improve computational performance and efficiency by leveraging the power of quantum computing.
Achieve precise results utilizing the most suitable quantum hardware for your specific use case.
QUICK is tailored to this landscape, designed to be hardware-agnostic, ensuring readiness for any qubit technology that may emerge as the standard, thus making it a low-risk and future-proof computational tool.
Meet us on 17-20 June 2026 at Vivatech in the Crédit Agricole stand.
ColibriTD is a deep tech company focused on quantum computing software for scientific and industrial applications. The company was founded in 2019 by Dr. Laurent Guiraud and Hacène Goudjil. They were joined by a team of researchers and engineers, including several PhD in quantum algorithms, quantum physics, condensed matter, and other diverse background.
ColibriTD develops software that connects advanced scientific simulations with quantum computing technologies. The objective is simple. Make quantum computing usable inside real engineering workflows. The platform is multi-hardware and can interact with different quantum computing infrastructures.
Many companies rely on large scale simulations to design products and systems. These simulations appear in fields such as computational fluid dynamics, electromagnetics, heat transfer, material deformation, and chemical reactions.
These models generate extremely large mathematical problems. Engineers often need to solve massive linear systems, differential equations, or complex combinatorial structures. The cost of these computations increases rapidly with model size and physical accuracy.
ColibriTD develops software tools that allow engineers and researchers to integrate quantum algorithms into these workflows. Instead of replacing existing simulation pipelines, the goal is to extend them with quantum capabilities.
The platform allows teams to:
This approach allows research teams and industrial engineers to evaluate quantum computing on practical problems such as multiphysics simulations, large scale numerical models, and advanced scientific computing tasks.
Quantum computing is a new type of computing based on the laws of quantum physics.
Classical computers use bits. A bit stores either 0 or 1. Quantum computers use qubits. A qubit can represent several states at the same time. This property comes from quantum phenomena such as superposition and entanglement.
Because of this behavior, quantum computers can explore many possible solutions at once. This approach differs from classical machines, which test possibilities one after another.
This capability is useful for problems that involve huge mathematical spaces.
Examples include:
Some quantum algorithms show strong theoretical performance for these tasks. This is why many researchers and companies study quantum computing for future scientific and industrial applications.
Quantum utility describes the moment when a quantum computer provides practical value for a real task.
Quantum advantage refers to a stronger condition. It occurs when a quantum computer solves a problem faster or more efficiently than the best known classical method.
This advantage can appear in several forms:
In practice, near term applications rely on hybrid approaches where classical computers and quantum processors work together.
Companies can start working with ColibriTD in several ways depending on their needs and maturity in quantum computing.
The fastest way is to experiment directly with our Qiskit function QUICK-PDE. This tool allows engineers and researchers to start testing quantum approaches for solving complex scientific equations, especially those appearing in physics based simulations.
For companies that want to explore deeper applications, we also work through project based collaborations.
The first phase usually lasts three months. During this phase we work with the partner team to:
At the end of this phase, a Go or No Go decision is taken.
If the results are promising, a second phase typically lasts six months. During this stage we:
ColibriTD also collaborates with partners through national and international research programs, including French and European innovation calls. This allows companies to explore quantum computing while sharing research efforts and funding.
Many physics simulations require solving large systems of equations or partial differential equations.
Examples include:
These simulations often generate matrices with millions or billions of variables.
Researchers explore quantum algorithms that can accelerate parts of these computations, such as:
Hybrid quantum classical workflows allow these algorithms to be tested within existing simulation pipelines.
Most current quantum applications rely on hybrid algorithms that combine classical and quantum computing.
In these approaches, a classical computer manages the overall workflow while a quantum processor evaluates specific mathematical operations. The classical part prepares the problem, updates parameters, and analyzes results. The quantum processor performs operations that are difficult to simulate efficiently with classical hardware.
This model is widely used today because current quantum processors still have limitations in terms of size and noise.
A common family of hybrid methods is called Variational Quantum Algorithms (VQA). In a VQA, a quantum circuit depends on adjustable parameters. A classical optimizer updates these parameters step by step in order to improve the result.
ColibriTD develops hybrid algorithms following this approach. One example is our Hybrid Differential Equation Sover (H-DES) algorithm, which belongs to the VQA family. It combines classical optimization with parameterized quantum circuits in order to explore complex mathematical structures.
This type of algorithm is particularly relevant for scientific computing problems where large numerical models and complex equations must be solved. Hybrid workflows allow researchers and engineers to experiment with quantum algorithms today while using classical computing resources to control the overall computation.
The quantum computing ecosystem includes various technology providers. Some design and build hardware, others provide cloud access, and specialized firms develop the software layers required for industrial applications.
Large international corporations play a major role by developing quantum processors and providing the infrastructure to run experiments.
Several companies are developing diverse physical architectures to power quantum computations.
The software layer is critical for translating complex industrial challenges into quantum instructions.
ColibriTD develops hybrid algorithms specifically for multiphysics simulations, including fluid dynamics, heat transfer, and material deformation. Because the company is hardware agnostic, its tools can interact with various quantum infrastructures. This approach allows industrial partners to integrate quantum acceleration into their engineering workflows while remaining independent from any specific hardware manufacturer.
Industrial applications of quantum computing usually start from a clear computational challenge. Many engineering and scientific workflows rely on heavy numerical calculations that require large amounts of computing power.
Quantum computing introduces new algorithmic approaches that can explore these problems differently from classical machines. When quantum advantage becomes practical, it could provide significant benefits for industry such as:
At ColibriTD, industrial collaborations typically follow two approaches.
The first approach is project based collaboration. In this model we work directly with industrial partners to identify a relevant computational challenge, analyze its mathematical structure, and develop quantum or hybrid prototypes adapted to the problem.
The second approach allows companies to start experimenting directly with our tools. Through our Qiskit function QUICK-PDE, engineers and researchers can begin testing quantum methods for solving complex equations used in scientific simulations. This allows teams to explore quantum computing in a practical way while keeping their existing simulation workflows.
Current research in quantum computing focuses on problems that require large computational resources and advanced numerical methods.
Examples include:
Many early applications rely on hybrid algorithms that combine classical computing with quantum processors.
At ColibriTD, the focus is on scientific computing and multiphysics simulations. These types of problems appear in many industrial sectors. The company works with partners across a wide range of industries including semiconductors, defense, finance, automotive, aerospace, and energy.
Companies usually begin with exploratory projects.
Typical steps include:
This allows R&D teams to build internal expertise while monitoring the maturity of quantum technologies.
Most quantum computing experiments today are performed through cloud platforms or simulators.
These tools allow researchers and engineers to:
Simulators run on classical hardware and allow teams to test algorithms before executing them on real quantum processors.
Because many different quantum hardware technologies exist today, experiments are often performed across multiple platforms and infrastructures.
ColibriTD provides a practical way for companies to begin these experiments. Its solutions are hardware agnostic and can interact with different quantum computing backends. This allows engineers and researchers to test the same algorithms on simulators and on several types of quantum hardware.
This approach makes ColibriTD a strong starting point for companies that want to explore quantum computing while remaining flexible in their choice of quantum infrastructure.
