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<p>The execution of large-scale quantum algorithms remains constrained by the limited number of available qubits, restricted qubit connectivity, and the intrinsic noise in current quantum processors. To address these challenges, Dynamic Quantum Circuits (DQC) have emerged as a promising design paradigm that leverages non-unitary operations–such as active reset, mid-circuit measurement, and classically controlled gates–to reduce qubit requirements during circuit realization. While DQC offers significant resource savings, it often incurs a trade-off in the form of increased circuit depth, making the assessment of circuit reliability a critical concern for near-term quantum hardware. In this work, we analyze the structure of oracle functions and observe that transforming their global mappings into vector-valued forms provides key benefits, including reduced circuit depth, improved parallelism, and minimal additional gate overhead. These properties make the proposed approach particularly effective for architectures with limited qubit connectivity and distributed quantum systems with communication constraints. Furthermore, we introduce a <i>DQC-based transformation scheme</i> and demonstrate its application to the Bernstein-Vazirani (BV) and Quantum Phase Estimation (QPE) algorithms across varying circuit sizes. Empirical results confirm that the proposed design methodology improves execution efficiency and reliability as a function of qubit count and circuit depth, paving the way for scalable DQC-based implementations in resource-constrained quantum architectures.</p>

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Dynamic Transformation of Quantum Algorithms for Resource-Constrained Architectures

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Abhoy Kole,
  • Louis Krüger,
  • Kamalika Datta,
  • Lennart Weingarten,
  • Indranil Sengupta,
  • Rolf Drechsler

摘要

The execution of large-scale quantum algorithms remains constrained by the limited number of available qubits, restricted qubit connectivity, and the intrinsic noise in current quantum processors. To address these challenges, Dynamic Quantum Circuits (DQC) have emerged as a promising design paradigm that leverages non-unitary operations–such as active reset, mid-circuit measurement, and classically controlled gates–to reduce qubit requirements during circuit realization. While DQC offers significant resource savings, it often incurs a trade-off in the form of increased circuit depth, making the assessment of circuit reliability a critical concern for near-term quantum hardware. In this work, we analyze the structure of oracle functions and observe that transforming their global mappings into vector-valued forms provides key benefits, including reduced circuit depth, improved parallelism, and minimal additional gate overhead. These properties make the proposed approach particularly effective for architectures with limited qubit connectivity and distributed quantum systems with communication constraints. Furthermore, we introduce a DQC-based transformation scheme and demonstrate its application to the Bernstein-Vazirani (BV) and Quantum Phase Estimation (QPE) algorithms across varying circuit sizes. Empirical results confirm that the proposed design methodology improves execution efficiency and reliability as a function of qubit count and circuit depth, paving the way for scalable DQC-based implementations in resource-constrained quantum architectures.