Hardware and Simulators

Options for Execution: 

• Local Simulators which will be bundled with the software

• IBM cloud simulators

• IBM Quantum Hardware

Users will gain direct access to authentic quantum machine learning algorithms, facilitated by simulators. What sets us apart is that the application will come equipped with local device simulators, making the experience seamless and user-friendly. IBM's quantum simulators will also be at your disposal. Furthermore, we will introduce a feature that will enable users to seamlessly tap into IBM Quantum hardware by entering their API token. 

Datasets

Quant Pracar enables users to upload and train on datasets of their choice, fostering a hands-on learning experience. Additionally, users can conveniently access pre-loaded datasets, such as the Iris and the MNIST datasets, enhancing understanding of quantum machine learning.

Flexibility

Customizable Options: 

• Classical Optimizers: Select from a range of existing classical optimizers and there repetitions.

• Encoding Feature Maps: Select from a range of existing Encoding Feature Maps and their repetitions, 

• Number of iterations of the model.

• Datasets.

• Datasets Filtration within the software.

• Select Test/Train Split within the software

• Select a Random State to easily reproduce results.

The application offers unparalleled control over the learning journey. Users can tailor the training process by customising each and every aspect of the model to align with preferences. The ability to choose from a diverse range of classical optimisers, feature maps, iterations the application provides flexibility and full control to the user. 

Open-Source Commitment 

We will be fully committing to the open-source initiative by licensing this project under the MIT license