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

Physical Review Applied

Controlling Quantum Devices with Nonlinear Hardware

Ian Hincks, Christopher Granade, Troy W. Borneman, David G. Cory

Published Aug 20, 2015• 46 citations
Publisher

Abstract

To achieve high-fidelity, coherent control of quantum systems via imperfect classical hardware, the authors provide a general framework for designing control sequences that account for distortions---even those that are nonlinear and noninvertible. These sequences are robust to both a distribution of device Hamiltonians (such as for spatially varying fields) and uncertainties in the description of the control hardware itself, greatly extending the bounds of quantum device operation.

DOI
10.1103/physrevapplied.4.024012

Related papers

Accounting for Classical Hardware in the Control of Quantum Devices

Ian Hincks, Christopher Granade, Troy W. Borneman +1 more

High fidelity coherent control of quantum systems is critical to building quantum devices and quantum computers. We provide a general optimal control framework for designing control sequences that account for hardware control distortions while maintaining robustness to environmental noise. We demonstrate the utility of our algorithm by presenting examples of robust quantum gates optimized in the presence of nonlinear distortions. We show that nonlinear classical controllers do not necessarily incur additional computational cost to pulse optimization, enabling more powerful quantum devices.

arXiv:1409.8178•Sep 29, 2014•14 citations

Precision Quantum Control and Error-Suppressing Quantum Firmware for Robust Quantum Computing

Michael J. Biercuk, Lorenza Viola, Amir Yacoby

Abstract : This project aimed to address the most significant challenge facing the development of large-scale quantum computers: suppressing hardware error. Through this work we focused on the realization of a robust, high-fidelity Quantum Control Toolkit that is fully transportable between different quantum computing technology platforms. The techniques encapsulated herein were designed to provide qubit robustness to decoherence during memory (dynamical decoupling DD), and increase the fidelity of qubit operations undertaken in the presence of random environmental noise and control imperfections (dynamically corrected gates DCGs, and composite pulses CPs). This project has seen the demonstration of significant hardware-based improvements in quantum control fidelity along with the full experimental validation of an engineering-inspired filter-transfer function framework for quantum control.

•Sep 24, 2014•0 citations

Quantum gates robust to secular amplitude drifts

Qile David Su, Robijn Bruinsma, Wesley C. Campbell

The robustness of quantum gates in the presence of imperfections in the classical control fields that drive the gates is an important issue in quantum computation. The authors extend the technique of composite pulses and construct two pulse sequences that provide robustness against time-dependent drift in the amplitude of the control pulses.

arXiv:2108.04726•Physical Review A•Nov 30, 2021•6 citations

Compensating for Nonlinear Distortions in Controlled Quantum Systems

Juhi Singh, Robert Zeier, Tommaso Calarco +1 more

Predictive design and optimization methods for controlled quantum systems depend on the accuracy of the system model. Any distortion of the input fields in an experimental platform alters the model accuracy and eventually disturbs the predicted dynamics. These distortions can be nonlinear with a strong frequency dependence so that the field interacting with the microscopic quantum system has limited resemblance to the input signal. We present an effective method for estimating these distortions, which is suitable for nonlinear transfer functions of arbitrary lengths and magnitudes provided the available training data has enough spectral components. Using a quadratic estimation, we have successfully tested our approach for a numerical example of a single Rydberg atom system. The transfer function estimated from the presented method is incorporated into an open-loop control optimization algorithm allowing for high-fidelity operations in quantum experiments.

arXiv:2210.07833•Physical Review Applied•Jun 23, 2023•12 citations

Nonlinear Quantum System Modeling

Jincheng Zhang

This paper introduces a novel approach to quantum system modeling, designed to effectively simulate and predict the behavior of complex non-linear quantum systems. Traditional methods often struggle with the inherent intricacy of these systems, limiting their ability to provide accurate stability predictions. Our work centers on leveraging the inherent complexity of quantum states to construct a robust modeling framework. This framework promises to overcome limitations of existing techniques, offering a pathway to improved understanding and control of quantum phenomena.

•Sep 7, 2026•0 citations

Neural network approach to mitigating intra-gate crosstalk in superconducting CZ gates

Y. Yu, Yexiong Zeng, Ye‐Hong Chen +2 more

The potential of quantum computing is constrained by the susceptibility of qubits to noise and crosstalk during multi-qubit gate operations. Existing strategies, such as hardware isolation and dynamical decoupling, face limitations in scalability, feasibility, and robustness against complex noise sources. Here we show a physics-guided neural control framework that generates robust control pulses for superconducting transmon qubit systems, specifically targeting crosstalk mitigation. By combining a hardware-aware parameterization with a Hamiltonian-informed objective that accounts for condition-dependent crosstalk distortions, the framework steers the search toward smooth and physically realizable pulses while exploring high-dimensional control landscapes. Numerical simulations for the controlled-Z gate demonstrate superior fidelity and pulse smoothness compared to the Krotov and GRAPE baselines under matched constraints. The results show consistent and practically meaningful improvements in both nominal and perturbed conditions, with pronounced gains in worst-case fidelity, supporting physics-guided neural control as a route to robust control on near-term transmon devices. Quantum computers are highly sensitive to unwanted crosstalk between qubits, especially during multi-qubit gate operations. Here, the authors show that physics-guided neural control can generate smooth, hardware-compatible pulses that make two-qubit gates more robust against crosstalk.

Communications Physics•Jun 23, 2026•0 citations
To achieve high-fidelity, coherent control of quantum systems via imperfect classical hardware, the authors provide a general framework for designing control sequences that account for distortions---even those that are nonlinear and noninvertible. These sequences are robust to both a distribution of device Hamiltonians (such as for spatially varying fields) and uncertainties in the description of the control hardware itself, greatly extending the bounds of quantum device operation.
High fidelity coherent control of quantum systems is critical to building quantum devices and quantum computers. We provide a general optimal control framework for designing control sequences that account for hardware control distortions while maintaining robustness to environmental noise. We demonstrate the utility of our algorithm by presenting examples of robust quantum gates optimized in the presence of nonlinear distortions. We show that nonlinear classical controllers do not necessarily incur additional computational cost to pulse optimization, enabling more powerful quantum devices.
Abstract : This project aimed to address the most significant challenge facing the development of large-scale quantum computers: suppressing hardware error. Through this work we focused on the realization of a robust, high-fidelity Quantum Control Toolkit that is fully transportable between different quantum computing technology platforms. The techniques encapsulated herein were designed to provide qubit robustness to decoherence during memory (dynamical decoupling DD), and increase the fidelity of qubit operations undertaken in the presence of random environmental noise and control imperfections (dynamically corrected gates DCGs, and composite pulses CPs). This project has seen the demonstration of significant hardware-based improvements in quantum control fidelity along with the full experimental validation of an engineering-inspired filter-transfer function framework for quantum control.
Predictive design and optimization methods for controlled quantum systems depend on the accuracy of the system model. Any distortion of the input fields in an experimental platform alters the model accuracy and eventually disturbs the predicted dynamics. These distortions can be nonlinear with a strong frequency dependence so that the field interacting with the microscopic quantum system has limited resemblance to the input signal. We present an effective method for estimating these distortions, which is suitable for nonlinear transfer functions of arbitrary lengths and magnitudes provided the available training data has enough spectral components. Using a quadratic estimation, we have successfully tested our approach for a numerical example of a single Rydberg atom system. The transfer function estimated from the presented method is incorporated into an open-loop control optimization algorithm allowing for high-fidelity operations in quantum experiments.
This paper introduces a novel approach to quantum system modeling, designed to effectively simulate and predict the behavior of complex non-linear quantum systems. Traditional methods often struggle with the inherent intricacy of these systems, limiting their ability to provide accurate stability predictions. Our work centers on leveraging the inherent complexity of quantum states to construct a robust modeling framework. This framework promises to overcome limitations of existing techniques, offering a pathway to improved understanding and control of quantum phenomena.
The potential of quantum computing is constrained by the susceptibility of qubits to noise and crosstalk during multi-qubit gate operations. Existing strategies, such as hardware isolation and dynamical decoupling, face limitations in scalability, feasibility, and robustness against complex noise sources. Here we show a physics-guided neural control framework that generates robust control pulses for superconducting transmon qubit systems, specifically targeting crosstalk mitigation. By combining a hardware-aware parameterization with a Hamiltonian-informed objective that accounts for condition-dependent crosstalk distortions, the framework steers the search toward smooth and physically realizable pulses while exploring high-dimensional control landscapes. Numerical simulations for the controlled-Z gate demonstrate superior fidelity and pulse smoothness compared to the Krotov and GRAPE baselines under matched constraints. The results show consistent and practically meaningful improvements in both nominal and perturbed conditions, with pronounced gains in worst-case fidelity, supporting physics-guided neural control as a route to robust control on near-term transmon devices. Quantum computers are highly sensitive to unwanted crosstalk between qubits, especially during multi-qubit gate operations. Here, the authors show that physics-guided neural control can generate smooth, hardware-compatible pulses that make two-qubit gates more robust against crosstalk.