QwidgetCo specializes in quantum computing, quantum many-body systems, and quantum information processing. These large-scale numerical computations can be considered as two stages: model selection and parameter estimation.
We approach quantum machine learning from the perspective that probabilistic dynamical systems can be described by kinetic and potential energy terms. What this means is that machine learning is inherently quantum mechanical, and can be thought of as a dynamical quantum state.
Thus, the model selection stage consists of choosing the kinetic energy and potential energy terms appropriately. Parameter estimation is then acheived via learning rules and algorithms. QwidgetCo aims to develop and implement these novel quantum learning rules and strategies in a unique framework for designing quantum neural network models, and novel quantum machine learning software.
QwidgetCo offers the best in quantum machine-learning technology. We use our years of research to create the best in quantum programming, quantum optimization, quantum data compression, quantum automation, quantum hierarchical modeling, and device design We take pride in our work, offering the custom solutions you are looking for, all with a commitment to dedication for our clients and customers. We believe in a customer-centered approach, and use this philosophy as the backbone for our work and research in the quantum machine-learning and quantum technology fields.