Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE International Conference on Quantum Computing and Engineering (QCE)

Dynamic Circuit Compilation for Sparse Qubit Connectivity

Sumeet Shirgure, Siyuan Niu

Published Aug 30, 2025• 0 citations
Publisher

Abstract

In this work, we show how dynamic circuit compilation methods can transform a densely connected circuit into an ancilla-mediated, sparsely connected dynamic circuit that includes mid-circuit measurement and feedforward operations. This sparse connectivity is better suited to current quantum hardware, which often has limited qubit connectivity. Compared to compilation methods focused on unitary circuits, our method can reduce both circuit depth and the additional CNOTs required to execute non-adjacent qubit interactions.

DOI
10.1109/qce65121.2025.10360

Related papers

From Static to Dynamic: Implementation of Long-Range Entanglement GHZ States for Dynamic Circuit-Based Quantum Teleportation

Shisheer S Kaushik, Thirumalai M, Harsh Mehta

In many domains, quantum computing has demonstrated its superiority over classical computing, and it continues to expand. It has demonstrated exponential speedups compared to the classic approach in certain problems. Nevertheless, scalability and noisy environments remain challenges for quantum hardware. In contrast to the unitary dynamics that characterise quantum circuits, recent research has introduced dynamic circuits with non-unitary dynamics. Dynamic circuits include mid-circuit measurement and conditional feed-forward operations. Our proposal involves using dynamic circuits to achieve reduced circuit depth, which in turn significantly decreases error rates by integrating error-correcting feed-forward operations within the circuit. Long-Range Teleportation enables the expansion of teleportation protocols to accommodate intricate quantum states spanning multiple qubits. We have employed Dynamic circuits to ensure an optimal circuit depth and showcase the efficacy of dynamic circuits in facilitating reliable teleportation with an increasing number of qubits. Our findings highlight the benefits of using dynamic circuits to optimize the compilation time of the multi qubit quantum teleportation protocol.

IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)•Jul 12, 2024•1 citation

Dynamic Quantum Circuit Compilation

Kun Fang, Munan Zhang, Ruqi Shi +1 more

The practical applications of quantum computing is currently limited by the small number of available qubits. Recent advances in quantum hardware have introduced midcircuit measurements and resets, enabling the reuse of measured qubits and thus reducing the qubit requirements for executing quantum algorithms. In this work, we present a systematic study of dynamic quantum circuit compilation, a process that transforms static quantum circuits into their dynamic equivalents with fewer qubits through qubit reuse. We establish the first graph-based framework for optimizing qubit-reuse compilation. In particular, we characterize the task of finding the optimal compilation strategy for maximizing qubit reuse using binary integer programming and provide efficient heuristic algorithms for devising general compilation strategies. We conduct a thorough analysis of quantum circuits with practical relevance and offer their optimal qubit-reuse compilation strategies. We also perform a comparative analysis against state-of-the-art approaches, demonstrating the superior performance of our methods in both structured and random quantum circuits. Our framework lays a rigorous foundation for understanding dynamic quantum circuit compilation via qubit reuse, holding significant promise for the practical implementation of large-scale quantum algorithms on quantum computers with limited resources.

arXiv:2310.11021•IEEE Transactions on Computers•Dec 15, 2025•7 citations

Compile-Time Simplification of Classically Controlled Operations in Dynamic Circuits

Innocenzo Fulginiti, Yanbin Chen, Christian B. Mendl +1 more

Dynamic circuits use real-time outcomes of mid-circuit measurements, processed by a classical controller, to adapt subsequent operations during circuit execution. This additional flexibility over static circuits comes at a price. Mid-circuit measurements are typically slower and noisier than unitary gates. Furthermore, classical feedforward requires exchanging information between the quantum processor (QPU) and the classical controller, introducing latency that erodes the practical performance of dynamic circuits. We propose a compile-time optimization framework that reduces the use of classical controls in dynamic circuits while preserving their semantics. At its core, the framework uses a static analysis that symbolically executes the circuit by propagating classical information alongside the quantum state. By combining this classical-quantum information with the Probabilistic Circuit Model extended with probabilistic controls that emulate classical feedforward, we obtain an intermediate probabilistic representation of the dynamic circuit. In this representation, mid-circuit measurements and classically controlled operations can be removed or rewritten as purely unitary operations and probabilistic components. Compared to existing compile-time optimizations that target only mid-circuit measurements, our method applies to a broader class of dynamic circuits expressible in modern quantum programming languages. We evaluated our framework on randomly generated dynamic circuits, achieving about 50% classical feedforward reduction and even higher reductions in favorable settings.

quant-pharXiv:2605.28439•ISC High Performance (ISC)•May 28, 2026•1 citation

Optimizing sparse quantum state preparation with measurement and feedforward

Yuan Lü, Han-Hsuan Lin

Quantum state preparation (QSP) is a key component in many quantum algorithms. In particular, the problem of sparse QSP (SQSP) $\unicode{x2013}$ the task of preparing the states with only a small number of non-zero amplitudes $\unicode{x2013}$ has garnered significant attention in recent years. In this work, we focus on reducing the circuit depth of SQSP with limited number of ancilla qubits. We present two SQSP algorithms: one with depth $O(n\log d)$, and another that reduces depth to $O(n)$. The latter leverages mid-circuit measurement and feedforward, where intermediate measurement outcomes are used to control subsequent quantum operations. Both constructions have size $O(dn)$ and use $O(d)$ ancilla qubits. Compared to the state-of-the-art SQSP algorithm in arXiv:2108.06150, which allows an arbitrary number of ancilla qubits $m>0$, both of our algorithms achieve lower circuit depth when $m=d$.

arXiv:2508.21346•Aug 29, 2025•0 citations

Quantum Fourier Transform Using Dynamic Circuits

Elisa Bäumer, Vinay Tripathi, Alireza Seif +2 more

In dynamic quantum circuits, classical information from midcircuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers numerous advantages that can enable more efficient and powerful protocols by drastically reducing the resource requirements for certain core algorithmic primitives. In particular, in the case of the n-qubit quantum Fourier transform followed immediately by measurement, the scaling of resource requirements is reduced from O(n^{2}) two-qubit gates in an all-to-all connectivity in the standard unitary formulation to O(n) midcircuit measurements in its dynamic counterpart without any connectivity constraints. Here, we demonstrate the advantage of dynamic quantum circuits for the quantum Fourier transform on IBM's superconducting quantum hardware with certified process fidelities of >50% on up to 16 qubits and >1% on up to 37 qubits, exceeding previous reports across all quantum computing platforms. These results are enabled by our contribution of an efficient method for certifying the process fidelity, as well as of a dynamical decoupling protocol for error suppression during midcircuit measurements and feed forward within a dynamic quantum circuit that we call "feed-forward-compensated dynamical decoupling." Our results demonstrate the advantages of leveraging dynamic circuits in optimizing the compilation of quantum algorithms.

arXiv:2403.09514•Physical Review Letters•Oct 8, 2024•49 citations

Branch-Aware Quantum Constant Propagation for Dynamic Quantum Circuits

Innocenzo Fulginiti, Yanbin Chen

Compile-time optimization is important for improving the efficiency and reliability of quantum circuits on current noisy hardware. While many existing methods simplify circuits using structural patterns or quantum-state information, most of them target only unitary circuits and do not support dynamic circuits with mid-circuit measurements and classical feedforward. In this work, we present Branch-Aware Quantum Constant Propagation (BQCP), a compile-time analysis for dynamic circuits. BQCP extends Quantum Constant Propagation (QCP) by tracking the classical information produced by mid-circuit measurements together with the corresponding post-measurement quantum states across different execution branches. This enables path-sensitive reasoning inside conditional blocks and more precise information propagation than QCP. To keep the analysis scalable, we bound both the size of the quantum-state representation and the number of tracked branches. Using the information inferred by the analysis, we apply semantics-preserving simplifications to circuit operations. We prove the soundness of both the analysis and the simplifications. Experimental results on both application-driven and synthetic benchmarks show that, on dynamic circuits, our method consistently achieves larger reductions than other existing passes including QCP.

quant-pharXiv:2606.02018•IEEE International Conference on Quantum Software (QSW)•Jun 2, 2026•0 citations
In this work, we show how dynamic circuit compilation methods can transform a densely connected circuit into an ancilla-mediated, sparsely connected dynamic circuit that includes mid-circuit measurement and feedforward operations. This sparse connectivity is better suited to current quantum hardware, which often has limited qubit connectivity. Compared to compilation methods focused on unitary circuits, our method can reduce both circuit depth and the additional CNOTs required to execute non-adjacent qubit interactions.
In many domains, quantum computing has demonstrated its superiority over classical computing, and it continues to expand. It has demonstrated exponential speedups compared to the classic approach in certain problems. Nevertheless, scalability and noisy environments remain challenges for quantum hardware. In contrast to the unitary dynamics that characterise quantum circuits, recent research has introduced dynamic circuits with non-unitary dynamics. Dynamic circuits include mid-circuit measurement and conditional feed-forward operations. Our proposal involves using dynamic circuits to achieve reduced circuit depth, which in turn significantly decreases error rates by integrating error-correcting feed-forward operations within the circuit. Long-Range Teleportation enables the expansion of teleportation protocols to accommodate intricate quantum states spanning multiple qubits. We have employed Dynamic circuits to ensure an optimal circuit depth and showcase the efficacy of dynamic circuits in facilitating reliable teleportation with an increasing number of qubits. Our findings highlight the benefits of using dynamic circuits to optimize the compilation time of the multi qubit quantum teleportation protocol.
The practical applications of quantum computing is currently limited by the small number of available qubits. Recent advances in quantum hardware have introduced midcircuit measurements and resets, enabling the reuse of measured qubits and thus reducing the qubit requirements for executing quantum algorithms. In this work, we present a systematic study of dynamic quantum circuit compilation, a process that transforms static quantum circuits into their dynamic equivalents with fewer qubits through qubit reuse. We establish the first graph-based framework for optimizing qubit-reuse compilation. In particular, we characterize the task of finding the optimal compilation strategy for maximizing qubit reuse using binary integer programming and provide efficient heuristic algorithms for devising general compilation strategies. We conduct a thorough analysis of quantum circuits with practical relevance and offer their optimal qubit-reuse compilation strategies. We also perform a comparative analysis against state-of-the-art approaches, demonstrating the superior performance of our methods in both structured and random quantum circuits. Our framework lays a rigorous foundation for understanding dynamic quantum circuit compilation via qubit reuse, holding significant promise for the practical implementation of large-scale quantum algorithms on quantum computers with limited resources.
Dynamic circuits use real-time outcomes of mid-circuit measurements, processed by a classical controller, to adapt subsequent operations during circuit execution. This additional flexibility over static circuits comes at a price. Mid-circuit measurements are typically slower and noisier than unitary gates. Furthermore, classical feedforward requires exchanging information between the quantum processor (QPU) and the classical controller, introducing latency that erodes the practical performance of dynamic circuits. We propose a compile-time optimization framework that reduces the use of classical controls in dynamic circuits while preserving their semantics. At its core, the framework uses a static analysis that symbolically executes the circuit by propagating classical information alongside the quantum state. By combining this classical-quantum information with the Probabilistic Circuit Model extended with probabilistic controls that emulate classical feedforward, we obtain an intermediate probabilistic representation of the dynamic circuit. In this representation, mid-circuit measurements and classically controlled operations can be removed or rewritten as purely unitary operations and probabilistic components. Compared to existing compile-time optimizations that target only mid-circuit measurements, our method applies to a broader class of dynamic circuits expressible in modern quantum programming languages. We evaluated our framework on randomly generated dynamic circuits, achieving about 50% classical feedforward reduction and even higher reductions in favorable settings.
Quantum state preparation (QSP) is a key component in many quantum algorithms. In particular, the problem of sparse QSP (SQSP) $\unicode{x2013}$ the task of preparing the states with only a small number of non-zero amplitudes $\unicode{x2013}$ has garnered significant attention in recent years. In this work, we focus on reducing the circuit depth of SQSP with limited number of ancilla qubits. We present two SQSP algorithms: one with depth O(nlog⁡d)O(n\log d)O(nlogd), and another that reduces depth to O(n)O(n)O(n). The latter leverages mid-circuit measurement and feedforward, where intermediate measurement outcomes are used to control subsequent quantum operations. Both constructions have size O(dn)O(dn)O(dn) and use O(d)O(d)O(d) ancilla qubits. Compared to the state-of-the-art SQSP algorithm in arXiv:2108.06150, which allows an arbitrary number of ancilla qubits m>0m>0m>0, both of our algorithms achieve lower circuit depth when m=dm=dm=d.
In dynamic quantum circuits, classical information from midcircuit measurements is fed forward during circuit execution. This emerging capability of quantum computers confers numerous advantages that can enable more efficient and powerful protocols by drastically reducing the resource requirements for certain core algorithmic primitives. In particular, in the case of the n-qubit quantum Fourier transform followed immediately by measurement, the scaling of resource requirements is reduced from O(n^{2}) two-qubit gates in an all-to-all connectivity in the standard unitary formulation to O(n) midcircuit measurements in its dynamic counterpart without any connectivity constraints. Here, we demonstrate the advantage of dynamic quantum circuits for the quantum Fourier transform on IBM's superconducting quantum hardware with certified process fidelities of >50% on up to 16 qubits and >1% on up to 37 qubits, exceeding previous reports across all quantum computing platforms. These results are enabled by our contribution of an efficient method for certifying the process fidelity, as well as of a dynamical decoupling protocol for error suppression during midcircuit measurements and feed forward within a dynamic quantum circuit that we call "feed-forward-compensated dynamical decoupling." Our results demonstrate the advantages of leveraging dynamic circuits in optimizing the compilation of quantum algorithms.
Compile-time optimization is important for improving the efficiency and reliability of quantum circuits on current noisy hardware. While many existing methods simplify circuits using structural patterns or quantum-state information, most of them target only unitary circuits and do not support dynamic circuits with mid-circuit measurements and classical feedforward. In this work, we present Branch-Aware Quantum Constant Propagation (BQCP), a compile-time analysis for dynamic circuits. BQCP extends Quantum Constant Propagation (QCP) by tracking the classical information produced by mid-circuit measurements together with the corresponding post-measurement quantum states across different execution branches. This enables path-sensitive reasoning inside conditional blocks and more precise information propagation than QCP. To keep the analysis scalable, we bound both the size of the quantum-state representation and the number of tracked branches. Using the information inferred by the analysis, we apply semantics-preserving simplifications to circuit operations. We prove the soundness of both the analysis and the simplifications. Experimental results on both application-driven and synthetic benchmarks show that, on dynamic circuits, our method consistently achieves larger reductions than other existing passes including QCP.