Damian Markham

dblp:14/8262 · DBLP profile ↗
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2ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0003-3111-7976ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 2 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Quantum computing and quantum information · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Quantum computing and quantum information
quantum metrology
0.612022
Robust Quantum Metrology With Explicit Symmetric States · IEEE Trans. Inf. Theory 2022
YearPublicationVenuePosition
2022 Robust Quantum Metrology With Explicit Symmetric States
abstract
12 pages, 2 figures, double column, (New: typos corrected, improved figures)
Yingkai Ouyang, Nathan Shettell, Damian Markham
IEEE Trans. Inf. Theory3
2013 Topological features of good resources for measurement-based quantum computation
abstract
We study how graph states on fractal lattices can be used to perform measurement-based quantum computation, and investigate which topological features allow this application. We find fractal lattices of arbitrary dimension greater than one that all act as good resources for measurement-based quantum computation, and sets of fractal lattices with dimension greater than one that do not. The difference is put down to other topological factors such as ramification and connectivity. This is in direct analogy to the tendency of lattices to observe criticality in spin systems. We also discuss the analogy between thermodynamics and one-way computation in this context. This work adds confidence to the analogy and highlights new features of what we require for universal resources for measurement-based quantum computation. This paper is an extended version of Markham et al. (2010), which appeared in the proceedings of DCM 2010.
Damian Markham, Janet Anders, Michal Hajdusek, Vlatko Vedral
Math. Struct. Comput. Sci.1