Our platform is...
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Hardware-Agnostic and Future-Proof

The variety of Software Development Kits (SDKs) can overcomplicate the adoption of quantum computing. Well known SDKs include, for instance, IBM's Qiskit and AWS's Braket quantum computing service. To tackle the abundance of existing SDKs, our platform is deployable on any available Quantum Processing Unit (QPU) by efficient translation between various SDK commands. This offers a single convenient platform for all QPUs and SDKs.

The hardware-agnostic nature of our platform makes it future-proof, as in our era of quantum computing it is still not clear which quantum tools and technologies will attain a large-scale quantum fault-tolerance, i.e., be able to avoid errors caused by the interaction of qubits.

Cost-Efficient

The computational runtimes may be too long to be viable if you are looking to simulate or model complex systems. These runtimes can be drastically reduced by our solution; QUICK takes the given parameters and translates the simulation into a problem that can be solved in an efficient manner - reducing time and energy costs.

Convenient and
‍User-Friendly

QUICK unifies access to multiple available quantum devices. In addition, it does not require any knowledge of quantum computing from the customer's side, saving you plenty of time in the process.

Our Vision

Our aim is to cover various use cases, such as material deformation or climate simulations. The workflow of our program can be simply described in the following manner:

The user inputs their problem parameters and meta-parameters. These can determine, for example, the maximum length or budget - or even the minimal precision of the required solution.

The input parameters are then used in our platform to choose an optimal algorithm, computational time as well as the ideal device.

After the initialization of the parameters and meta-parameters, specialized modules are called on our servers. This includes our quantum advantage module. While other modules prepare the data for the optimal algorithm, the quantum advantage module is one that decides the ideal quantum algorithm along with the choice of parameters (e.g., number of iterations, qubits, etc).

The chosen quantum algorithm is run in our abstract language library, and executed on our partner's hardware. Following the execution of the quantum algorithm, our platform interprets the results in a presentable and familiar format for the customer.

Our Future

Our team at ColibriTD is working hard to discover various advantages that quantum technology can provide. Our focus is not only on optimized time consumption, but on solution accuracy as well as energy consumption.

We are here to democratize quantum computing, and provide our customers with advantages brought by quantum technology as soon as possible.

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, our team is specialized in providing quantum solutions for any of the potential use cases described below.
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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.
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Cancer Treatment

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.

The spatial modeling of cancer growth and treatment can be done using ordinary differential equations or partial differential equations. Moreover, quantum computers can simulate large molecules in precise detail – molecules which are impossible to simulate using a classical computer. This provides a path to safer and more efficient treatment plans.
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Portfolio Optimization

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.
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Climate Modeling

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 - you guessed it - ordinary and partial differential equations. Precisely, the motion of the atmosphere and our oceans can be considered with the application of Navier–Stokes equations.