{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/optimized-compilation-of-aggregated","title":"Optimized Compilation of Aggregated Instructions for Realistic Quantum Computers","arxiv_id":"1902.01474","date":"2019-02-04","proceeding":null,"authors":["Yunong Shi","Nelson Leung","Pranav Gokhale","Zane Rossi","David I. Schuster","Henry Hoffman","Fred T. Chong"],"abstract":"Recent developments in engineering and algorithms have made real-world\napplications in quantum computing possible in the near future. Existing quantum\nprogramming languages and compilers use a quantum assembly language composed of\n1- and 2-qubit (quantum bit) gates. Quantum compiler frameworks translate this\nquantum assembly to electric signals (called control pulses) that implement the\nspecified computation on specific physical devices. However, there is a\nmismatch between the operations defined by the 1- and 2-qubit logical ISA and\ntheir underlying physical implementation, so the current practice of directly\ntranslating logical instructions into control pulses results in inefficient,\nhigh-latency programs. To address this inefficiency, we propose a universal\nquantum compilation methodology that aggregates multiple logical operations\ninto larger units that manipulate up to 10 qubits at a time. Our methodology\nthen optimizes these aggregates by (1) finding commutative intermediate\noperations that result in more efficient schedules and (2) creating custom\ncontrol pulses optimized for the aggregate (instead of individual 1- and\n2-qubit operations). Compared to the standard gate-based compilation, the\nproposed approach realizes a deeper vertical integration of high-level quantum\nsoftware and low-level, physical quantum hardware. We evaluate our approach on\nimportant near-term quantum applications on simulations of superconducting\nquantum architectures. Our proposed approach provides a mean speedup of\n$5\\times$, with a maximum of $10\\times$. Because latency directly affects the\nfeasibility of quantum computation, our results not only improve performance\nbut also have the potential to enable quantum computation sooner than otherwise\npossible.","url_abs":"http://arxiv.org/abs/1902.01474v2","url_pdf":"http://arxiv.org/pdf/1902.01474v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"optimized-compilation-of-aggregated","repo_url":"https://github.com/kashish0405/Gate-Optimisation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"optimized-compilation-of-aggregated","repo_url":"https://github.com/kashish0405/QuantumComputing_GateOptimisation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}