Abstract Quantum errors in noisy environments remain a major obstacle to advancing quantum information technology. Standard quantum error correction requires massive ancillary qubit overhead, motivating the need for hardware-efficient mitigation strategies. In this work, we propose a framework for dynamical quantum error correction at the circuit level, requiring no logical encoding or ancillary qubits. By extending a geometric framework-originally developed for creating dynamical error-correcting gates at the control pulse level—to the discrete dynamics of digital circuits, we map the accumulation of coherent errors to trajectories in a high-dimensional error space. We demonstrate that inserting deterministically optimized twirling gate sequences actively shapes these trajectories, utilizing destructive interference to keep the accumulated error bounded with error scaling O ( 1 ) . This deterministic path-shaping suppresses circuit errors fundamentally differently than the stochastic random-walk behavior of standard randomized compiling with error scaling O ( N ) . Furthermore, we show that this circuit-level dynamical correction synergizes with pulse-level robust control, providing an analytical bridge between continuous noise dynamics and discrete quantum compilation. This research illuminates pathways to achieving highly noise-resistant quantum circuits prior to the era of fault tolerance.
Abstract Quantum errors in noisy environments remain a major obstacle to advancing quantum information technology. Standard quantum error correction requires massive ancillary qubit overhead, motivating the need for hardware-efficient mitigation strategies. In this work, we propose a framework for dynamical quantum error correction at the circuit level, requiring no logical encoding or ancillary qubits. By extending a geometric framework-originally developed for creating dynamical error-correcting gates at the control pulse level—to the discrete dynamics of digital circuits, we map the accumulation of coherent errors to trajectories in a high-dimensional error space. We demonstrate that inserting deterministically optimized twirling gate sequences actively shapes these trajectories, utilizing destructive interference to keep the accumulated error bounded with error scaling O ( 1 ) . This deterministic path-shaping suppresses circuit errors fundamentally differently than the stochastic random-walk behavior of standard randomized compiling with error scaling O ( N ) . Furthermore, we show that this circuit-level dynamical correction synergizes with pulse-level robust control, providing an analytical bridge between continuous noise dynamics and discrete quantum compilation. This research illuminates pathways to achieving highly noise-resistant quantum circuits prior to the era of fault tolerance.
Quantum errors in noisy environments remain a major obstacle to advancing quantum information technology. In this work, we expand a recently developed geometric framework, originally utilized for analyzing noise accumulation and creating dynamical error-correcting gates at the control pulse level, to now study noise dynamics at the quantum circuit level. Through a geometric perspective, we demonstrate how circuit noise robustness can be enhanced using twirling techniques. Additionally, we show that circuits modified by random twirling correspond to random walk trajectories in this geometric framework, and provide a fresh perspective on randomized compiling by analytically deriving the perturbative expression for the resultant Pauli noise channel. We also illustrate that combining robustness optimization strategies at both the control pulse and circuit levels can significantly boost overall circuit fidelity even further through numerical examples. This research illuminates pathways to achieving noise-resistant quantum control beyond mere optimization of control pulses.
The rapid evolution of Noisy Intermediate-Scale Quantum (NISQ) devices has intensified the need for robust compilation strategies capable of mitigating hardware-induced errors while maximizing computational efficiency. Quantum compilers play a pivotal role in translating high-level quantum algorithms into hardware-executable instructions, yet they face significant challenges related to qubit connectivity constraints, limited coherence times, and stochastic noise. This paper examines error-resilient quantum compiler design for efficient qubit mapping, gate optimization, and noise mitigation in NISQ-era devices, proposing a framework that integrates topology-aware mapping, adaptive gate synthesis, and probabilistic error suppression techniques. By synthesizing advances in quantum circuit optimization, hardware-aware scheduling, and hybrid classical–quantum error correction strategies, the study evaluates how compiler-level innovations can substantially enhance execution fidelity and resource efficiency. The findings suggest that intelligent compiler architectures are critical enablers of practical quantum advantage during the transitional NISQ phase, bridging theoretical algorithm design with real-world hardware constraints.
Noise in current quantum hardware (NISQ devices) poses a major obstacle by degrading gate operations and overall circuit fidelity toward FTQC. Traditional quantum error correction (QEC) is effective but resource-intensive, requiring several extra qubits and operations beyond the reach of near-term devices. Quantum error mitigation (QEM) offers a complementary path by reducing the impact of error prior to full correction. We present an adaptive pulse-level QEM using genetic algorithms to dynamically adjust control pulses in real-time, improving algorithm fidelity without modifying the logic structure of a quantum circuit. By targeting pulse parameters directly, this method reduces the impact of various noise sources, improving algorithm resilience in quantum circuits. To demonstrate the effectiveness of our methodology, we apply our protocol to five key quantum algorithms, including Bernstein-Vazirani, DeutschJozsa, Grover's search, Quantum Fourier Transform (QFT), and its inverse (IQFT). Experimental results show that our pulse-level optimization strategy provides a flexible and efficient solution for increasing fidelity during the noisy execution of quantum circuits. Our work contributes to advance error mitigation techniques, essential for robust quantum computing, which will increasingly require HPC infrastructure as quantum systems scale.
Geometric quantum computation offers a potential route to fault-tolerant quantum information processing by exploiting the global nature of geometric phases. However, achieving controlled high-order suppression of multiple error sources remains a long-standing limitation, particularly in realistic large-scale circuits with complex noise environments. This limitation is largely due to the absence of a general framework that directly characterizes error accumulation and enables systematic improvement. Here we establish such a framework for universal doubly geometric gates by embedding target operations into a hierarchy of level-n identity constructions. This approach enables direct quantification of error accumulation while removing structural constraints inherent in previous schemes. We analytically show that the defining conditions lead to simultaneous fourth-order suppression of control errors, with a systematic extension to sixth-order suppression via higher-level constructions. Our results establish doubly geometric control as a general and scalable route toward high-order robust quantum gates, with potential implications for fault-tolerant quantum information processing.
Implementing high-fidelity quantum control and suppressing the unwanted environmental noise has been one of the essential challenges in developing quantum information technologies. In the past, driving pulse sequences based on Dirac delta functions or square wave functions, such as Hahn spin echo or CPMG, have been developed to dynamically correcting the noise effects. However, implementing these ideal pulses with high fidelity is a challenging task in real experiments. In this thesis, we provide a new and simple method to explore the entire solution space of driving pulse shapes that suppress environmental noise in the evolution of the system. In this method, any single-qubit phase gate that is first-order robust against quasi-static transversal noise corresponds to a closed curve on a two-dimensional plane, and more general first-order robust single-qubit gates correspond to closed three-dimensional space curves. Second-order robust gates correspond to closed curves having the property that their projection onto any two-dimensional planes shall enclose a zero net area. The driving pulse shapes that implement the gates can be determined by the curvature, torsion, and the length of the curve. By utilizing the framework it is possible to obtain globally optimal solutions in pulse shaping in respect of experimental constraints by mapping them into geometrical optimization problems. One such problem we solved is to prove that the fastest possible single-qubit phase gates that are second-order noise-resistant shall be implemented using sign-flipping square functions. Since square waves are not experimentally feasible, we provide a method to smooth these pulses with minimal loss in gate speed while maintaining the robustness, based on the geometrical framework. This framework can also be useful in diagnosing the noise-cancellation properties of pulse shapes generated from numerical methods such as GRAPE. We show that this method for pulse shaping can significantly improve the fidelity of single-qubit gates through numerical simulation.
Despite rapid advances in quantum hardware, noise remains a central obstacle to deploying quantum algorithms on near-term devices. In particular, random coherent errors that accumulate during circuit execution constitute a dominant and fundamentally challenging noise source. We introduce a noise-resilient framework for Quantum Signal Processing (QSP) that mitigates such coherent errors without increasing circuit depth or ancillary qubit requirements. Our approach uses ensembles of noisy QSP circuits combined with measurement-level averaging to suppress random phase errors in Z rotations. Building on this framework, we develop robust QSP algorithms for implementing polynomial functions of Hermitian matrices and for estimating observables, with applications to Hamiltonian simulation, quantum linear systems, and ground-state preparation. We analyze the trade-off between approximation error and hardware noise, which is essential for practical implementation under the stringent depth and coherence constraints of current quantum hardware. Our results establish a practical pathway for integrating error mitigation seamlessly into algorithmic design, advancing the development of robust quantum computing, and enabling the discovery of scientific applications with near- and mid-term quantum devices.