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Tailoring quantum architectures to implementation style: a quantum computer for mobile and persistent qubits
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International Symposium on Computer Architecture archive
Proceedings of the 34th annual international symposium on Computer architecture table of contents
San Diego, California, USA
SESSION: Core fusion and quantum table of contents
Pages: 198 - 209  
Year of Publication: 2007
ISBN:978-1-59593-706-3
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Authors
Eric Chi  Princeton University, Princeton, NJ
Stephen A. Lyon  Princeton University, Princeton, NJ
Margaret Martonosi  Princeton University, Princeton, NJ
Sponsors
SIGARCH: ACM Special Interest Group on Computer Architecture
IEEE-CS : Computer Society
Publisher
ACM  New York, NY, USA
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ABSTRACT

In recent years, quantum computing (QC) research has moved from the realm of theoretical physics and mathematics into real implementations. With many different potential hardware implementations, quantum computer architecture is a rich field with an opportunity to solve interesting new problems and to revisit old ones. This paper presents a QC architecture tailored to physical implementations with highly mobile and persistent quantum bits (qubits). Implementations with qubit coherency times that are much longer than operation times and qubit transportation times that are orders of magnitude faster than operation times lend greater flexibility to the architecture. This is particularly true in the placement and locality of individual qubits. For concreteness, we assume a physical device model based on electron-spin qubits on liquid helium (eSHe).

Like many conventional computer architectures, QCs focus on the efficient exposure of parallelism.We present here a QC microarchitecture that enjoys increasing computational parallelism with size and latency scaling only linearly with the number of operations. Although an efficient and high level of parallelism is admirable, quantum hardware is still expensive and difficult to build, so we demonstrate how the software may be optimized to reduce an application's hardware requirements by 25% with no performance loss. Because the majority of a QC's time and resources are devoted to quantum error correction, we also present noise modeling results that evaluate error correction procedures. These results demonstrate that idle qubits in memory need only be refreshedapproximately once every one hundred operation cycles.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Eric Chi: colleagues
Stephen A. Lyon: colleagues
Margaret Martonosi: colleagues