Compilation of QCrank Encoding Algorithm for a Dynamically Programmable Qubit Array Processor
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arXiv
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| Main Authors: | , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866917136222388224 |
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| author | Balewski, Jan Lin, Wan-Hsuan Mitra, Anupam Kornjača, Milan Ostermann, Stefan Lopes, Pedro L. S. Tan, Daniel Bochen Cong, Jason |
| author_facet | Balewski, Jan Lin, Wan-Hsuan Mitra, Anupam Kornjača, Milan Ostermann, Stefan Lopes, Pedro L. S. Tan, Daniel Bochen Cong, Jason |
| contents | Algorithm and hardware-aware compilation co-design is essential for the efficient deployment of near-term quantum programs. We present a compilation case-study implementing QCrank -- an efficient encoding protocol for storing sequenced real-valued classical data in a quantum state -- targeting neutral atom-based Dynamically Programmable Qubit Arrays (DPQAs). We show how key features of neutral-atom arrays such as high qubits count, operation parallelism, multi-zone architecture, and natively reconfigurable connectivity can be used to inform effective algorithm deployment. We identify algorithmic and circuit features that signal opportunities to implement them in a hardware-efficient manner. To evaluate projected hardware performance, we define a realistic noise model for DPQAs using parameterized Pauli channels, implement it in Qiskit circuit simulators, and assess QCrank's accuracy for writing and reading back 24-320 real numbers into 6-20 qubits. We compare DPQA results with simulated performances of Quantinuum's H1-1E and with experimental results from IBM Fez, highlighting promising accuracy scaling for DPQAs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_10699 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Compilation of QCrank Encoding Algorithm for a Dynamically Programmable Qubit Array Processor Balewski, Jan Lin, Wan-Hsuan Mitra, Anupam Kornjača, Milan Ostermann, Stefan Lopes, Pedro L. S. Tan, Daniel Bochen Cong, Jason Quantum Physics Algorithm and hardware-aware compilation co-design is essential for the efficient deployment of near-term quantum programs. We present a compilation case-study implementing QCrank -- an efficient encoding protocol for storing sequenced real-valued classical data in a quantum state -- targeting neutral atom-based Dynamically Programmable Qubit Arrays (DPQAs). We show how key features of neutral-atom arrays such as high qubits count, operation parallelism, multi-zone architecture, and natively reconfigurable connectivity can be used to inform effective algorithm deployment. We identify algorithmic and circuit features that signal opportunities to implement them in a hardware-efficient manner. To evaluate projected hardware performance, we define a realistic noise model for DPQAs using parameterized Pauli channels, implement it in Qiskit circuit simulators, and assess QCrank's accuracy for writing and reading back 24-320 real numbers into 6-20 qubits. We compare DPQA results with simulated performances of Quantinuum's H1-1E and with experimental results from IBM Fez, highlighting promising accuracy scaling for DPQAs. |
| title | Compilation of QCrank Encoding Algorithm for a Dynamically Programmable Qubit Array Processor |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2507.10699 |