QC Ware Forge

We conduct and implement cutting-edge research on artificial intelligence to create real advantage in financial investment. Illuminating the financial market with ground-breaking neuro-prediction. We combine novel deep reinforcement learning algorithms and graph-based learning with artificial neural networks for modeling and predicting time series. Neuri strives to generate synthetic data emulating the global financial markets, testing it with complex simulations of trading behavior. We bet on the future of quantum optimization in enabling our simulations to surpass the limits of classical supercomputing. Financial markets are highly fluid, with dynamics evolving over time. As such we build AI algorithms that adapt and learn continuously, in order to uncover the connections between different financial assets, classes and markets. The application of neuroscience-inspired models, quantum algorithms and machine learning to systematic trading at this point is underexplored.

The realization of large-scale physical quantum computers appears to be challenging, alongside the efforts to design quantum computers, significant efforts are focusing on the development of useful quantum algorithms. In the absence of a large physical quantum computer, an accurate software simulation of quantum computers on a classical computer is required to simulate the execution of those quantum algorithms and to study the behavior of a quantum computer and improve its design. Besides simulating error-free execution quantum circuits on a perfect quantum computer, the QX simulator can simulate realistic noisy execution using different error models such as the depolarizing noise. The user can activate the error model and define a physical error probability to simulate a specific target quantum computer. This error rate can be defined based on the gate fidelity and the qubit decoherence of the target platform.