26 citations · 71 across the 6 of their papers we have counts for
7 papers
Quantum quenches of scar states in the Affleck-Kennedy-Lieb-Tasaki model via Clifford augmented tensor network simulation
Azar C. Nakhl, Ben Harper, Muhammad Usman +1
Clifford augmented methods have emerged as a powerful technique to simulate quantum circuits and many-body systems by exploiting the stabiliser structure found in said systems, whi…
Non-Clifford Crosstalk Noise in Surface Codes Using Hybrid Stabilizer-Tensor Network Methods
Ben Harper, Azar C. Nakhl, Martin Sevior +1
Scalable realisation of quantum computing is reliant on the development of fault tolerant devices. Analysis of quantum error correction protocols typically considers incoherent noi…
GCAMPS: A Scalable Classical Simulator for Qudit Systems
Ben Harper, Azar C. Nakhl, Thomas Quella +2
Classical simulations of quantum systems are notoriously difficult computational problems, with conventional state vector and tensor network methods restricted to quantum systems t…
Stabilizer Tensor Networks with Magic State Injection
Azar C. Nakhl, Ben Harper, Maxwell West +4
This work augments the recently introduced Stabilizer Tensor Network (STN) protocol with magic state injection, reporting a new framework with significantly enhanced ability to sim…
Adversarial Robustness Guarantees for Quantum Classifiers
Neil Dowling, Maxwell T. West, Angus Southwell +4
Despite their ever more widespread deployment throughout society, machine learning algorithms remain critically vulnerable to being spoofed by subtle adversarial tampering with the…
Calibrating the role of entanglement in variational quantum circuits
Azar C. Nakhl, Thomas Quella, Muhammad Usman
Entanglement is a key property of quantum computing that separates it from its classical counterpart, however, its exact role in the performance of quantum algorithms, especially v…
Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning
Maxwell T. West, Azar C. Nakhl, Jamie Heredge +4
Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realisation for practical applications re…