Exact Reordering of Circuit Lines for Nearest Neighbor Quantum Architectures

Wille, Robert; Lye, Aaron; Drechsler, Rolf

doi:10.1109/tcad.2014.2356463

Cited by 84 publications

(43 citation statements)

References 46 publications

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“…While these approaches lead to heuristic solutions only, an exact approach guaranteeing the minimal number of SWAP insertions has recently been proposed in [8,9]. In [6] , another exact approach has been proposed which additionally allows for changing the order of the gates so that the results obtained there are not directly compara ble to the other solutions.…”

Section: A Related Work and Considered Problemmentioning

confidence: 99%

“…For 1D quantum circuits, this can been obtained in linear time using in version vectors [8,9] . For multi-dimensional circuits, this constitutes a more complex problem.…”

Section: B Costs Of Establishing An Arbitrary Permutationmentioning

confidence: 99%

“…More precisely, this con straint enumerates all possible adjacent positions for the 3Note that, in accordance to previous work (e.g. [5,7,8,9] ), we assume the primary input qubits can arbitrarily be permuted with no additional costs. 4 Adding the unit vector to a position, i.e.…”

Section: Optimal Swap Gate Insertionmentioning

confidence: 99%

“…Hence, be fore it comes to an actual SWAP gate insertion, the gen eral question is how costly (in terms of SWAP gates) is it to realize a certain permutation. While linear solutions 28-3 to this question exist for 1D circuits (due to the help of inversion vectors [8,9] ), the approach presented in Sec tion IV.B represents the first exact solution for multi dimensional circuits. This does not only provide the de signer with crucial information on the (exact) costs of es tablishing a certain operation, but also allows an analysis on the suitability of different configurations with respect to nearest neighbor constraints.…”

Section: A Costs Of Establishing An Arbitrary Permutationmentioning

confidence: 99%

“…In particular, reordering the qubit positions or considering SWAP gate insertion not only locally for each single gate but for the whole cascade may reduce the costs signifi cantly. Hence, several approaches on determining good SWAP gate insertions have been proposed in the past [4,5,6,7,8,9] .…”

Section: Introductionmentioning

confidence: 99%

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Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits

Lye

Wille

Drechsler

2015

The 20th Asia and South Pacific Design Automation Conference

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Motivated by the promises of significant speed-ups for certain problems, quantum computing received significant attention in the past. While much progress has been made in the development of synthesis methods for quantum cir cuits, new physical developments constantly lead to new constraints to be addressed. The limited interaction dis tance between the respective qubits (i.e. nearest neigh bor optimization) has already been considered intensely. But with the emerge of multi-dimensional quantum ar chitectures, new physical requirements came up for which only a few automatic synthesis solutions exist yet -all of them of heuristic nature. In this work, we propose an exact scheme for nearest neighbor optimization in multi dimensional quantum circuits. Although the complexity of the problem is a serious obstacle, our experimental eval uation shows that the proposed solution is sufficient to allow for a qualitative evaluation of the respective opti mization steps. Besides that, this enabled an exact com parison to heuristical results for the first time.978-1-4799-7792-5/15/$31.00 ©2015 IEEE

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Section: A Related Work and Considered Problemmentioning

confidence: 99%

“…For 1D quantum circuits, this can been obtained in linear time using in version vectors [8,9] . For multi-dimensional circuits, this constitutes a more complex problem.…”

Section: B Costs Of Establishing An Arbitrary Permutationmentioning

confidence: 99%

Section: Optimal Swap Gate Insertionmentioning

confidence: 99%

Section: A Costs Of Establishing An Arbitrary Permutationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Determining the minimal number of swap gates for multi-dimensional nearest neighbor quantum circuits

Lye

Wille

Drechsler

2015

The 20th Asia and South Pacific Design Automation Conference

Self Cite

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Deep Reinforcement Learning for Mapping Quantum Circuits to 2D Nearest‐Neighbor Architectures

Li,

Liu,

2024

Adv Quantum Tech

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Recently, quantum computing is considered as a promising future computing paradigm. However, when implementing quantum circuits on a quantum device, it is necessary to ensure that quantum circuits satisfy nearest‐neighbor architecture constraints. When performing nearest‐neighbor architecture mapping for quantum circuits, it is inevitable to introduce SWAP gates, which will increase the overhead and reduce the fidelity. Therefore, it is crucial to complete the mapping with the minimum SWAP. In this paper, a 2D nearest‐neighbor architecture mapping method for quantum circuits is proposed based on deep reinforcement learning. In the initial mapping, an isomorphic graph initial mapping search algorithm is designed to quickly find the isomorphic graph between quantum circuit and architecture constraint graph. For quantum circuits without isomorphic graph mapping, the reordering algorithm of qubit impact factors is designed to obtain the initial placement position of qubits. In the SWAP gate addition, a qubit local reordering algorithm based on dueling deep‐Q‐network is designed to reduce SWAP gates. Experiments on the benchmark set B131 and IBM Q20 Tokyo verify that the proposed method can add fewer SWAP gates. Compared with the state‐of‐the‐art method, the average running time is accelerated by 63.1%, and the average SWAP gates added are reduced by 24.7%.

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