Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/139091
Title: | A template-based technique for efficient Clifford+T-based quantum circuit implementation | Authors: | Biswal, Laxmidhar Das, Rakesh Bandyopadhyay, Chandan Chattopadhyay, Anupam Rahaman, Hafizur |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2018 | Source: | Biswal, L., Das, R., Bandyopadhyay, C., Chattopadhyay, A., & Rahaman, H. (2018). A template-based technique for efficient Clifford+T-based quantum circuit implementation. Microelectronics Journal, 81, 58-68. doi:10.1016/j.mejo.2018.08.011 | Journal: | Microelectronics Journal | Abstract: | The near-future possibility of Quantum supremacy, which aspires to establish a set of algorithms running efficiently on a Quantum computer – have significantly fuelled the interest in design and automation of Quantum circuits. Multiple technologies such as Ion-Trap, Nuclear Magnetic Resonance (NMR), have made great progress in recent years towards a practical Quantum circuit implementation. For all these technologies, in order to suppress the inherent computation noise, fault-tolerance is a desirable feature. Fault tolerance is achieved by Quantum error correction codes, such as surface code. Due to the efficient realization of surface codes using Clifford + T gate library of Quantum logic gates, it is now becoming de facto gate library for Quantum circuit implementation. In this paper, we improve two key performance metrics, T − depth and T − count, for Quantum circuit realization using Clifford + T gates. In contrast with the previous approaches, we have incorporated two techniques - 1) restructuring of the gate positions in the designs to make it amenable towards a lower T − depth 2) using Binary Decision Diagrams (BDD) as an intermediate representation for achieving scalability. To validate our proposed optimizations, we have tested a wide spectrum of benchmarks, registering an average improvement of 74% and 21% on T − depth and T − count in compared works. | URI: | https://hdl.handle.net/10356/139091 | ISSN: | 0026-2692 | DOI: | 10.1016/j.mejo.2018.08.011 | Schools: | School of Computer Science and Engineering | Rights: | © 2018 Elsevier Ltd. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | SCSE Journal Articles |
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