Discover our quantum solutions, including the Quantum Innovative Computing Kit (QUICK) and Multiple Platform Quantum Programming (MPQP) language.
What is QUICK?
We believe that making quantum computing tools accessible to everyone can not only speed up scientific discovery, but to change the landscape of research and development as we know it.
New to quantum? No problem!
Basis of quantum computing
When it comes to quantum physics, quantum states can be in multiple states at the same time. In practical terms, this means that you could flip a coin and get heads and tails simultaneously. Or that your phone could be turned on and off at the same time. In simple terms, instead of option 0 and 1 as with the classical computer, now you have multiple simultaneous options at one time - including 0, 1 and everything in between. This is known as superposition.
Entanglement describes the relationship between a set of two or more particles that interact in a manner that makes it out of the question to describe each particle separately. Okay, this sounds quite complicated, so let's consider an analogy of such a situation.
Assume that you and your friend have two decks of cards. You randomly pick a card out of one of the decks, and your friend does the same with the other deck. Neither of you look at the card, but you put it in an envelope and take it with you.
When you arrive back at your house, and so does your friend, you both take a look at the cards at the same time. Under normal circumstances, the chances of you having a spade does not impact the probability of your friend having a spade. This is how our world normally works - two independent situations two not have an impact on each other probability-wise.
However, what if you decide to stamp the two envelopes before your departure? This is where the entanglement comes in - you have now entangled your envelopes. This implies that one card will give you information on the other card.
In other words, after you both go home, if you find a spade in your envelope, you know that your friend will too. These events are now entangled.
Superposition and entanglement open the door for many logical operations that a classical computer cannot fathom. This makes quantum computers more convenient to perform complex computations, simulations, and even cracking some of the most difficult mathematical problems. Better yet, it has the potential to completely transform the scientific research process as we know it today.
Our platform is...
Cost-efficient and sustainable
The Multi-Programming Quantum Platform (MPQP)
Multi-Programming Quantum Platform - Frequently Asked Questions
How does MPQP simplify the development of quantum applications?
What are the benefits of MPQP for the academic and education sector?
This early and practical exposure prepares the next generation of scientists and engineers to work effectively in the rapidly expanding field of quantum computing, thus stimulating innovation and research. On their end, researchers using MPQP can validate their work faster thanks to this easier access to quantum resources.
How can businesses benefit from MPQP?
Businesses looking for quantum solutions to complex problems will find MPQP a powerful tool. By lowering the friction between providers, MPQP allows companies’ developers to explore various quantum backends when validating their quantum algorithms. This opens opportunities for faster quantum program development iterations.
Where can I learn more about MPQP and start using it?
To learn more about MPQP and begin harnessing the power of quantum computing, visit our repository. There, you'll find detailed resources, including tutorials, technical documentation, and case studies. Developers, researchers, and organizations interested can get in touch with us through our website, if a new feature is desired.
What platforms and providers are currently accessible via MPQP?
In the current version of MPQP, we support three providers, all gate-based. For IBM Quantum, our user can call local simulators (Aer simulators), remote simulators, and remote QPUs. We also support all AWS Braket devices, the local simulator, the remote ones, and the various quantum computers available (IONQ, Rigetti, Oxford QC, etc.). Finally, we support Eviden’s simulators, both local (PyLinalg and CLinalg) and remote ones on the QLM. Our goal is to continue integrating diverse providers to offer our users the largest catalog of quantum devices on the market.
Does MPQP handle noise simulation and error mitigation?
This feature is upcoming in the next release. You can subscribe to our GitHub’s updates to be warned as soon as this update lands! If specific features or error mitigation techniques are important for you, feel free to get in touch with us to help us in their development.
Is MPQP open source?
MPQP is fully open source! Our project is under the GPLv3 license, so use it as your heart desires.
How can I contribute to the development of MPQP?
To contribute, you can fork the project on GitHub, perform your modifications on your fork of the project and then do what is called on GitHub a “Pull Request”.
How frequently is MPQP updated?
For now, we plan a bi-yearly update for MPQP, and of course, more if we can. To be notified of new releases, you can subscribe to our GitHub watchlist. If external contributions are important enough, they may trigger new updates out of the usual schedule.
Are there any licensing or usage fees associated with MPQP?
MPQP is free and will stay that way. Of course, as a company, we need to make money, but MPQP is a tool for us, so we do not plan to monetize it. This being said, to have access to our providers’ remote QPUs, you will need to pay for each of them individually. One of our goals is also to unify this subscription system, but for now, we do not support it. Local simulators are always free!
Does MPQP offer technical support or community animation (Discord, Slack, forum)?
Technical support is all handled through GitHub issues. Our team is very eager to hear from its users, so don’t be shy! Regarding community interactions, you can access our Discord server to chat with our team and other users.
How does MPQP ensure compatibility with different gate-based platforms?
MPQP relies heavily on OpenQASM. This standard originating from a collaboration between the academic world and IBM is now supported by all the main actors of the gate-based quantum ecosystem. It is currently version 3. Sadly, no provider properly supports it, so to allow a circuit to be deployed on any of our supported backends, we massage the OpenQASM-generated code into a version that the chosen provider supports.
Can MPQP be integrated into external quantum software or frameworks?
It sure can! See the GPLv3 complete license for more details on the matter.
What are the system requirements for using MPQP?
A full matrix of compatibility is available in our documentation. But a summary of it is that we support Python versions between 3.9 and 3.11.
Our team at ColibriTD is working hard to discover various advantages that quantum technology can provide. The key focus is not only on optimized time consumption, but on solution accuracy as well as energy consumption. We aim to provide environmentally friendly and sustainable solutions for complex problems.
We are here to democratize quantum computing, and provide our customers with advantages brought by quantum technology.
Your use case
Our goal is to bring quantum computing to everyone and make quantum technologies more accessible through our QUICK-platform, as well as our team of quantum researchers. Namely, we would be very excited to tackle any of the following use cases - and much more.If your use case is very different from the ones described below, we would still love to hear from you.
Cases modeled by the Navier–Stokes equations
The Navier–Stokes equations can be used to mathematically model fluid dynamics, climate science, macroeconomics, and has plenty of applications in engineering - thus, they play a crucial role in quantum computing.
It has been shown that quantum computers can bring remarkable advantage when solving linear differential equations. However, quantum solutions do not exist without some challenges - more specifically, here lies the issue: quantum mechanics are linear in nature. This makes nonlinear problems, such as the Navier–Stokes equations, difficult to solve.
However, there are several powerful quantum algorithms that can be implemented in order to efficiently solve partial differential equations (PDEs) on a quantum computer. Our solution can be systematically implemented to various use cases that can be modeled by PDEs - particularly ones modeled by the Navier–Stokes equations.
Fight cancer with quantum solutions
It has been estimated that about 50% of the entire world's population will receive a cancer diagnosis at some point in their lives. Additionally, cancer is currently the second leading cause of death worldwide. To battle this, scientists are continuously working on drug development and various treatment plans - and the process can be made much faster and more efficient by leveraging the power of quantum technology.
Quantum computers can simulate large molecules in precise detail – molecules that are impossible to simulate using a classical computer. This provides a path to safer and more efficient treatment plans.
Optimize your portfolio and get the best return on investment without time-consuming data analysis
A quantum approach can be particularly powerful when finding a company's portfolio which maximizes the return on investment - or one that minimizes risk. This is because quantum computers have been designed to try many possibilities simultaneously in order to find the optimal solution, making them a very powerful tool for these types of tasks.
Moreover, quantum annealers are known to be powerful for optimizing investment portfolios according to the risk margin, allowing for great annual return on investment.
Simulate complex systems in a fraction of the time
Climate modeling and weather forecasting are on the brink of a major quantum-breakthrough, as quantum computers enable researchers to make more accurate predictions with only a fraction of the time when compared to classical computers.
This is not only useful from the perspective of research in environmental and climate sciences, but it offers the potential to transform our battle with climate change by providing fewer technical challenges and a major acceleration of solutions.
The theoretical basis of climate modeling lies in ordinary and partial differential equations. Precisely, the motion of the atmosphere and our oceans can be considered with the application of Navier–Stokes equations, which our platform is designed to tackle.
Model your engineering problem using our quantum platform!
Our platform can be used to tackle various problems in engineering. Namely, QUICK offers quantum solutions that are closely tied to everyday tools used by engineers, which allows them to run top-quality simulations as fast as possible. Examples of such use cases can include, for example, computing various beam deflection scenarios.
With the help of QUICK, the user simply needs to characterize the problem by specifying the material, boundary conditions, and any potential constraints. This is then transferred to QUICK through a script that translates the given problem into the language of partial differential equations. Moreover, thanks to our collaboration with eleQtron, we can provide access to top quantum hardware, including eleQtron, an ion-based quantum computer for appropriate use cases.