86 citations · 558 across the 51 of their papers we have counts for
25 papers · 1 filter
LUCI on IBM Hardware: Error Suppression with Almost Half Syndrome Density
Younghun Kim, Spiro Gicev, Martin Sevior +1
Long-lived logical qubits are essential for fault-tolerant quantum computation. However, the practical performance of traditional error correction protocols relies on performing sp…
Fourier analysis of quantum neural network with non-linear data embedding
Haiyue Kang, Martin Sevior, Muhammad Usman
Fourier analysis has become a crucial tool for understanding the expressivity of Variational Quantum Circuit (VQC) models, as well as an important indicator of barren plateaus (BP)…
Crosstalk In Contemporary Quantum Devices
Spiro Gicev, Ben Harper, Haiyue Kang +2
Crosstalk noise derives from phenomena in quantum devices which inhibit individual addressability or cause unintended interactions among qubits. It is widely considered one of the…
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…
Feature-level analysis and adversarial transfer in rotationally equivariant quantum machine learning
Maureen Krumtünger, Martin Sevior, Muhammad Usman
Group-equivariant quantum models are designed to exploit symmetry and can improve trainability, but it remains unclear how symmetry constraints shape their adversarial robustness.…
Time-Dynamic Circuits for Fault-Tolerant Shift Automorphisms in Quantum LDPC Codes
Younghun Kim, Spiro Gicev, Martin Sevior +1
Quantum low-density parity-check (qLDPC) codes have emerged as a promising approach for realizing low-overhead logical quantum memories. Recent theoretical developments have establ…
Quantum Error Correction and Detection for Quantum Machine Learning
Eromanga Adermann, Haiyue Kang, Martin Sevior +1
At the intersection of quantum computing and machine learning, quantum machine learning (QML) is poised to revolutionize artificial intelligence. However, the vulnerability of the…
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…
Almost fault-tolerant quantum machine learning with drastic overhead reduction
Haiyue Kang, Younghun Kim, Eromanga Adermann +2
Errors in the current generation of quantum processors pose a significant challenge towards practical-scale implementations of quantum machine learning (QML) as they lead to traina…
A graph-theoretic approach to chaos and complexity in quantum systems
Maxwell West, Neil Dowling, Angus Southwell +4
There has recently been considerable interest in studying quantum systems via dynamical Lie algebras (DLAs) -- Lie algebras generated by the terms which appear in the Hamiltonian o…
Time-adaptive single-shot crosstalk detector on superconducting quantum computer
Haiyue Kang, Benjamin Harper, Muhammad Usman +1
Quantum crosstalk which stems from unwanted interference of quantum operations with nearby qubits is a major source of noise or errors in a quantum processor. In the context of sha…
Magic State Injection on IBM Quantum Processors Above the Distillation Threshold
Younghun Kim, Martin Sevior, Muhammad Usman
The surface code family is a promising approach to implementing fault-tolerant quantum computations. Universal fault-tolerance requires error-corrected non-Clifford operations, in…
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…
Transversal CNOT gate with multi-cycle error correction
Younghun Kim, Martin Sevior, Muhammad Usman
A scalable and programmable quantum computer holds the potential to solve computationally intensive tasks that classical computers cannot accomplish within a reasonable time frame,…
Non-Unitary Quantum Machine Learning
Jamie Heredge, Maxwell West, Lloyd Hollenberg +1
We introduce several probabilistic quantum algorithms that overcome the normal unitary restrictions in quantum machine learning by leveraging the Linear Combination of Unitaries (L…
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…
Crosstalk Attacks and Defence in a Shared Quantum Computing Environment
Benjamin Harper, Behnam Tonekaboni, Bahar Goldozian +2
Quantum computing has the potential to provide solutions to problems that are intractable on classical computers, but the accuracy of the current generation of quantum computers su…
Kernel Alignment for Quantum Support Vector Machines Using Genetic Algorithms
Floyd M. Creevey, Jamie A. Heredge, Martin E. Sevior +1
The data encoding circuits used in quantum support vector machine (QSVM) kernels play a crucial role in their classification accuracy. However, manually designing these circuits po…
Provably Trainable Rotationally Equivariant Quantum Machine Learning
Maxwell T. West, Jamie Heredge, Martin Sevior +1
Exploiting the power of quantum computation to realise superior machine learning algorithmshas been a major research focus of recent years, but the prospects of quantum machine lea…
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…
Boosted Ensembles of Qubit and Continuous Variable Quantum Support Vector Machines for B Meson Flavour Tagging
Maxwell T. West, Martin Sevior, Muhammad Usman
The recent physical realisation of quantum computers with dozens to hundreds of noisy qubits has given birth to an intense search for useful applications of their unique capabiliti…
Permutation Invariant Encodings for Quantum Machine Learning with Point Cloud Data
Jamie Heredge, Charles Hill, Lloyd Hollenberg +1
Quantum Computing offers a potentially powerful new method for performing Machine Learning. However, several Quantum Machine Learning techniques have been shown to exhibit poor gen…
Reflection Equivariant Quantum Neural Networks for Enhanced Image Classification
Maxwell T. West, Martin Sevior, Muhammad Usman
Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding…
Benchmarking Adversarially Robust Quantum Machine Learning at Scale
Maxwell T. West, Sarah M. Erfani, Christopher Leckie +3
Machine learning (ML) methods such as artificial neural networks are rapidly becoming ubiquitous in modern science, technology and industry. Despite their accuracy and sophisticati…