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20192026
most citedTransversal Injection: A method for direct encoding of ancilla states for non-Clifford gates using stabiliser codes

2 citations · 6 across the 5 of their papers we have counts for

collaborators

6 papers

quant-ph2026

Optimal operating temperature for industry-compatible silicon spin quantum computing: colder is not necessarily better

Paul Steinacker, Amanda E. Seedhouse, Nard Dumoulin Stuyck +22

Silicon spin qubits are a leading candidate for large-scale quantum computing owing to their compatibility with semiconductor manufacturing. However, scaling to useful fault-tolera…

quant-ph2024

Transversal Injection: Using the Surface Code to Prepare Non-Pauli Eigenstates

Jason Gavriel, Daniel Herr, Alexis Shaw +3

The development of quantum computing systems for large scale algorithms requires targeted error rates unachievable through hardware advancements alone. Quantum Error Correction (QE…

quant-ph2022★ 2 cited

Quantum computation on a 19-qubit wide 2d nearest neighbour qubit array

Alexis T. E. Shaw, Michael J. Bremner, Alexandru Paler +2

In this paper, we explore the relationship between the width of a qubit lattice constrained in one dimension and physical thresholds for scalable, fault-tolerant quantum computatio…

quant-ph2022★ 2 cited

Transversal Injection: A method for direct encoding of ancilla states for non-Clifford gates using stabiliser codes

Jason Gavriel, Daniel Herr, Alexis Shaw +3

Fault-tolerant, error-corrected quantum computation is commonly acknowledged to be crucial to the realisation of large-scale quantum algorithms that could lead to extremely impactf…

quant-ph2022★ 1 cited

Quantum Parameterized Complexity

Michael J. Bremner, Zhengfeng Ji, Ryan L. Mann +3

Parameterized complexity theory was developed in the 1990s to enrich the complexity-theoretic analysis of problems that depend on a range of parameters. In this paper we establish…

cs.CC2019★ 1 cited

Cluster Editing with Vertex Splitting

Faisal N. Abu-Khzam, Emmanuel Arrighi, Matthias Bentert +7

Cluster Editing, also known as Correlation Clustering, is a well-studied graph modification problem. In this problem, one is given a graph and the task is to perform up to edge…