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Architecture of a Quantum Multicomputer Optimized for Shor's Factoring Algorithm

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arxiv quant-ph/0607065 v1 pith:WJF2LXCE submitted 2006-07-11 quant-ph

classification quant-ph
keywords numberquantumfactoringmulticomputerarchitectureexponentiationmodularperformance
verification ladder T0 review T1 audit T2 compute T3 formal
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The quantum multicomputer consists of a large number of small nodes and a qubus interconnect for creating entangled state between the nodes. The primary metric chosen is the performance of such a system on Shor's algorithm for factoring large numbers: specifically, the quantum modular exponentiation step that is the computational bottleneck. This dissertation introduces a number of optimizations for the modular exponentiation. My algorithms reduce the latency, or circuit depth, to complete the modular exponentiation of an n-bit number from O(n^3) to O(n log^2 n) or O(n^2 log n), depending on architecture. Calculations show that these algorithms are one million times and thirteen thousand times faster, when factoring a 6,000-bit number, depending on architecture. Extending to the quantum multicomputer, five different qubus interconnect topologies are considered, and two forms of carry-ripple adder are found to be the fastest for a wide range of performance parameters. The links in the quantum multicomputer are serial; parallel links would provide only very modest improvements in system reliability and performance. Two levels of the Steane [[23,1,7]] error correction code will adequately protect our data for factoring a 1,024-bit number even when the qubit teleportation failure rate is one percent.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Fat-Tree QRAM: A High-Bandwidth Shared Quantum Random Access Memory for Parallel Queries

    quant-ph 2025-02 conditional novelty 7.0 of 10

    Fat-Tree QRAM pipelines up to log(N) simultaneous queries to a size-N memory in about log(N) time, using only about twice the hardware of a bucket-brigade QRAM.

  2. Optimizing Resource Allocation in a Distributed Quantum Computing Cloud: A Game-Theoretic Approach

    quant-ph 2025-04 unverdicted novelty 6.0 of 10

    Introduces QC-PRAGM and QC-PRAGM++ game models for partitioning quantum circuits in a distributed cloud, proving a 4/3 approximation on total client cost and reporting simulation gains over baselines in cost and commu...

  3. Performance Analysis of QAOA Across Distributed Quantum Network Topologies Using SwitchQNet

    quant-ph 2026-07 conditional novelty 3.5 of 10

    QAOA on SwitchQNet yields modest ~1.4–2.2× communication-latency reductions across QDC topologies and is useful mainly as a diagnostic benchmark for entanglement-aware scheduling.

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