Quandela

Quantum computing offers a path forward to rapid and cost-effective development of new molecules and materials. InQuanto, a state-of-the-art quantum computational chemistry platform, represents a critical step toward this goal. Quantum chemistry aims to accurately describe and predict the fundamental properties of matter and hence is a powerful tool in the design and development of new molecules and materials. However, molecules and materials of industrial relevance are complex and not easy to accurately simulate. Today’s capabilities force a trade to either use highly accurate methods on the smallest-sized systems or use approximating techniques. InQuanto’s modular workflow enables both computational chemists and quantum algorithm developers to easily mix and match the latest quantum algorithms with advanced subroutines and error mitigation techniques to get the best out of today’s quantum platforms.

Bayesforge™ is a Linux machine image that curates the very best open source software for the data scientist who needs advanced analytical tools, as well as for quantum computing and computational mathematics practitioners who seek to work with one of the major QC frameworks. The image combines common machine learning frameworks, such as PyTorch and TensorFlow, with open source software from D-Wave, Rigetti as well as the IBM Quantum Experience and Google's new quantum computing language Cirq, as well as other advanced QC frameworks. For instance our quantum fog modeling framework, and our quantum compiler Qubiter which can cross-compile to all major architectures. All software is made accessible through the Jupyter WebUI which, due to its modular architecture, allows the user to code in Python, R, and Octave.