Benjamin C. Travaglione

dblp:91/58 · also Ben Travaglione · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2003
—ORCID · none

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

Systems, architecture and hardware · 1 · 1 first-author

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.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Emerging computing paradigms · 100%
Theoretical computer science
1 paper
Quantum computing and quantum information · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Emerging computing paradigms › quantum computer architecture
quantum circuit implementation
0.012003
Designing and implementing small quantum circuits and algorithms · DAC 2003
Emerging computing paradigms
quantum computer architecture
0.012003
Designing and implementing small quantum circuits and algorithms · DAC 2003
Quantum computing and quantum information
quantum algorithms
0.012003
Designing and implementing small quantum circuits and algorithms · DAC 2003

Methods — techniques the papers use, named apart from their topics

reversible computation · 0.1read-only-memory computation model · 0.1
YearPublicationVenuePosition
2003 Designing and implementing small quantum circuits and algorithms
abstract
It appears, in principle, that the laws of quantum mechanics allow a quantum computer to solve certain mathematical problems more rapidly than can be done using a classical computer. However, in order to build such a quantum computer a number of technological problems need to be overcome. A stepping stone to this goal is the implementation of relatively simple quantum algorithms using current experimental techniques.This paper explores small scale quantum algorithms from two different perspectives. Firstly, it will be shown how small scale quantum algorithms can be tailored to fit current schemes for implementing a quantum computer. Secondly, I will review a simple model of computation, based on read-only-memory. This model allows the comparison of the space-efficiency of reversible error-free classical computation with reversible, error-free quantum computation. The quantum model has been shown to be more powerful than the classical model.
Benjamin C. Travaglione
DAC1