Reversible Logic Synthesis via Biconditional Binary Decision Diagrams

Chattopadhyay, Anupam; Littarru, Alessandro; Amarù, Luca; Gaillardon, Pierre-Emmanuel; Micheli, Giovanni De

doi:10.1109/ismvl.2015.21

Cited by 12 publications

(6 citation statements)

References 24 publications

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“…Instead, BBDDs are based on the biconditional expansion which natively models reversible XOR operations. In this way, BBDDs enable a more compact mapping into common reversible gates, such as Toffoli gates [134]. Fig.…”

Section: Resultsmentioning

confidence: 99%

New Logic Synthesis as Nanotechnology Enabler

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Section: Resultsmentioning

confidence: 99%

New Logic Synthesis as Nanotechnology Enabler

et al. 2015

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“…Kronecker 功能决策图(Kronecker FDD, KFDD) [10] 或双条件 BDD(biconditional BDD, BBDD) [11] 表示模型的可逆电路综合方法. 为降低量子成本和量子位数, 有在 KFDD 中使用补边并结合负控制线 Toffoli 门的方法 [12] , 以及对 FDD 或 KFDD 中的结点进行排序的方法 [9,13] .…”

Section: 计算机辅助设计与图形学学报unclassified

Reversible Circuit Synthesis Method by Combining Factoring and Boolean Expression Diagram

Bu¹

2021

J Comput-Aided Design Comput Graphics

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In order to reduce the cost of the resulting circuits, a reversible circuit synthesis method by combining factoring and Boolean expression diagram (BED) is proposed. For a given cover representing the exclusive-sum-of-products (ESOP) expansion of a Boolean function, cubes in the ESOP expansion represented by shared zero-suppressed multiple-output decision diagrams are first factored by leveraging algebraic division, then a BED is built from the factored ESOP cover and a reversible circuit is synthesized from the BED by mapping a BED node to a cascade of reversible gates. The proposed synthesis method is evaluated using benchmark functions. Experimental results show that the proposed synthesis method is time efficient. Compared to the existing reversible circuit synthesis methods using a directed acyclic graph as the representation model for Boolean functions, the proposed synthesis method can reduce the quantum cost and the number of qubits of the resulting reversible circuits in many cases. On average, compared to the synthesis method by combining variables grouping and BED, the proposed synthesis method can reduce the quantum cost and the number of qubits by 5.01% and 5.47%, respectively.

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“…The most effective methods use multi-level logic network representations such as BDDs [45], [61], [62], And-inverter graphs [63], [64], XOR-majority graphs [55], or LUT networks [65]. These methods are referred to as hierarchical reversible logic synthesis.…”

Section: Compiling Boolean Functionsmentioning

confidence: 99%

Programming quantum computers using design automation

Soeken

Haener

Roetteler

2018

2018 Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE)

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Recent developments in quantum hardware indicate that systems featuring more than 50 physical qubits are within reach. At this scale, classical simulation will no longer be feasible and there is a possibility that such quantum devices may outperform even classical supercomputers at certain tasks. With the rapid growth of qubit numbers and coherence times comes the increasingly difficult challenge of quantum program compilation. This entails the translation of a high-level description of a quantum algorithm to hardware-specific low-level operations which can be carried out by the quantum device. Some parts of the calculation may still be performed manually due to the lack of efficient methods. This, in turn, may lead to a design gap, which will prevent the programming of a quantum computer. In this paper, we discuss the challenges in fully-automatic quantum compilation. We motivate directions for future research to tackle these challenges. Yet, with the algorithms and approaches that exist today, we demonstrate how to automatically perform the quantum programming flow from algorithm to a physical quantum computer for a simple algorithmic benchmark, namely the hidden shift problem. We present and use two tool flows which invoke RevKit. One which is based on ProjectQ and which targets the IBM Quantum Experience or a local simulator, and one which is based on Microsoft's quantum programming language Q#.

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Reversible Logic Synthesis via Biconditional Binary Decision Diagrams

Cited by 12 publications

References 24 publications

New Logic Synthesis as Nanotechnology Enabler

New Logic Synthesis as Nanotechnology Enabler

Reversible Circuit Synthesis Method by Combining Factoring and Boolean Expression Diagram

Programming quantum computers using design automation

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