Quantum Finance Library
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Updated
Oct 25, 2024 - Python
Quantum Finance Library
Fast and flexible nonadiabatic molecular dynamics in Julia!
GW-BSE for excited state Quantum Chemistry in a Gaussian Orbital basis, electronic spectroscopy with QM/MM, charge and energy dynamics in complex molecular systems
A dynamically executed quantum-classical hybrid runtime.
The official code repository for "Variational Quanvolutional Neural Networks with enhanced image encoding", https://arxiv.org/abs/2106.07327
A tutorial on classical to quantum transfer learning by Xanadu AI
A comparison analysis between classical and quantum-classical (or hybrid) neural network and the impact effectiveness of a compound adversarial attack.
DDQCL implementation using Qiskit. Variational quantum circuit that maps a randomly generated set of four 4-qubit input states to four 4-qubit output states. Circuit parameters are refined over time to get the lowest cost parameter set.
Hybrid neural network is protected against adversarial attacks using various defense techniques, including input transformation, randomization, and adversarial training.
A quantum-classical (or hybrid) neural network and the use of a adversarial attack mechanism. The core libraries employed are Quantinuum pytket and pytket-qiskit. torchattacks is used for the white-box, targetted, compounded adversarial attacks.
Hybrid neural network model is protected against adversarial attacks using either adversarial training or randomization defense techniques
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