While the accuracy of qubit operations has been greatly improved in the last decade, further development is demanded to achieve the ultimate goal: a fault-tolerant quantum computer that can solve real-world problems more efficiently than classical computers. With growing fidelities even subtle effects of environmental noise such as qubit–reservoir correlations and non-Markovian dynamics turn into the focus for both circuit design and control. To guide progress, we disclose, in a numerically rigorous manner, a comprehensive picture of the single-qubit dynamics in presence of a broad class of noise sources and for entire sequences of gate operations. Thermal reservoirs ranging from Ohmic to deep 1 / f ɛ -like sub-Ohmic behavior are considered to imitate realistic scenarios for superconducting qubits. Apart from dynamical features, fidelities of the qubit performance over entire sequences are analyzed as a figure of merit. The relevance of retarded feedback and long-range qubit–reservoir correlations is demonstrated on a quantitative level, thus, providing a deeper understanding of the limitations of performances for current devices and guiding the design of future ones. Published by the American Physical Society 2024
While the accuracy of qubit operations has been greatly improved in the last decade, further development is demanded to achieve the ultimate goal: a fault-tolerant quantum computer that can solve real-world problems more efficiently than classical computers. With growing fidelities even subtle effects of environmental noise such as qubit–reservoir correlations and non-Markovian dynamics turn into the focus for both circuit design and control. To guide progress, we disclose, in a numerically rigorous manner, a comprehensive picture of the single-qubit dynamics in presence of a broad class of noise sources and for entire sequences of gate operations. Thermal reservoirs ranging from Ohmic to deep 1 / f ɛ -like sub-Ohmic behavior are considered to imitate realistic scenarios for superconducting qubits. Apart from dynamical features, fidelities of the qubit performance over entire sequences are analyzed as a figure of merit. The relevance of retarded feedback and long-range qubit–reservoir correlations is demonstrated on a quantitative level, thus, providing a deeper understanding of the limitations of performances for current devices and guiding the design of future ones. Published by the American Physical Society 2024
Within a numerically exact simulation technique, the dissipative dynamics of a two-qubit architecture is considered in which each qubit couples to its individual noise source (reservoir). The goal is to reveal the role of subtle qubit-reservoir correlations including non-Markovian processes as a prerequisite to guide further improvements of quantum computing devices. This paper addresses the following three topics. First, we examine the validity of the rotating wave approximation imposed previously on the qubit-reservoir coupling with respect to the disentanglement dynamics. Second, generation of the entanglement as well as destruction are analyzed by monitoring the reduced dynamics during and after application of a iSWAP † gate, also focusing on memory effects caused by reservoirs. Finally, the performance of a Hadamard + CNOT sequence is analyzed for different gate decomposition schemes. In all three cases, various types of noise sources and qubit parameters are considered.
Abstract Superconducting qubits are currently a leading platform for developing a scalable quantum computer. However, random and uncontrollable noises from the environment during the design and measurement of qubits lead to limitations in qubit coherence time and gate fidelity, which is a major challenge in current state of the art for superconducting quantum computing. To advance superconducting qubits technologies, it is essential to understand and mitigate environmentally-induced errors. This requires modeling superconducting qubits as open quantum systems coupled to their surroundings. The present study aims to provide useful open quantum system approaches to analyze and quantify the interaction between superconducting qubits and their environments. We provide an accessible introduction to open quantum system formalism for newcomers to the field. For experts, we discuss recently developed methods for analyzing superconducting qubit dynamics under realistic noises. We outline how these techniques provide quantitative insights into decoherence mechanisms and how they can guide design improvements to enhance qubit coherence time. This self-contained review of open quantum system approaches can be used to model, understand, and improve superconducting qubit performance in the presence of unavoidable environmental noises.
Superconducting qubits are a leading platform for quantum computation, yet decoherence and scalability challenges continue to limit progress toward fault-tolerant systems. This review synthesizes research on architectures, noise sources, and error correction to clarify performance trade-offs and guide development. The transition from Transmon to Fluxonium has dramatically improved qubit performance, achieving millisecond-scale coherence times. However, this success reveals a fundamental limit of coherence now being primarily restricted by the physical properties of the materials, specifically dielectric losses occurring at the Josephson junction leads and within the surrounding materials. As overcoming these material limits becomes increasingly difficult, system-level engineering determines whether high-coherence qubits can scale.Scaling quantum systems is difficult because current cooling and control systems create too much heat and this forces a shift to integrated digital superconducting circuits and cryogenic light-based links. While these hardware challenges restrict scaling, experiments in error correction show that logical qubits can already outperform physical ones. For example, a distance-7 surface code improved logical qubit lifetime by 2.4×. Achieving practical fault tolerance, however, requires moving beyond simple error models. Future systems must combine techniques like Dynamical Decoupling and Machine Learning-based Optimal Control with dynamic classical control capable of handling complex, correlated faults such as Multi-Bit Burst Errors. Progress in materials, cryogenic system integration for control, and adaptive error management must advance together to realize scalable, high-fidelity quantum hardware.
Abstract In the scale-up of quantum computers, the framework underpinning fault-tolerance generally relies on the strong assumption that environmental noise affecting qubit logic is uncorrelated (Markovian). However, as physical devices progress well into the complex multi-qubit regime, attention is turning to understanding the appearance and mitigation of correlated — or non-Markovian — noise, which poses a serious challenge to the progression of quantum technology. This error type has previously remained elusive to characterisation techniques. Here, we develop a framework for characterising non-Markovian dynamics in quantum systems and experimentally test it on multi-qubit superconducting quantum devices. Where noisy processes cannot be accounted for using standard Markovian techniques, our reconstruction predicts the behaviour of the devices with an infidelity of 10 −3 . Our results show this characterisation technique leads to superior quantum control and extension of coherence time by effective decoupling from the non-Markovian environment. This framework, validated by our results, is applicable to any controlled quantum device and offers a significant step towards optimal device operation and noise reduction.
Superconducting quantum computers are yet to reach the fault-tolerant regime, and thus the tantalising promises behind quantum algorithms are laid barren. To cross this knowledge-concealing wasteland, one must first understand how both intrinsic and extrinsic noise hinders the reliability of quantum computing systems. Most recently, in fact, external impinging particle events have been discovered to be one of the causes behind sudden bursts of information loss in these devices. Modelling such events with standard methods is a masterfully complex endeavour, which is ultimately hampered by computational costs in terms of memory and time. There is a growing requirement for an accurate fault model able to characterise a qubit's interaction with impinging particles, and more generally, the performance of full algorithms on quantum computers in the presence of radiation. Such a fault model would be the first of many other steps, paving the way for research on new quantum error correction and mitigation algorithms, and ultimately giving scientists a new instrument for tackling and understanding this ever growing issue. Reaching such goal requires the efficient simulation of quantum systems, both at the algorithmic and device level, pushing against the known limitations and bottlenecks imposed by these methods. The first objective is to understand the feasibility of quantum circuit simulations with the available computational methods, underlining bounds and limitations. This paved the way to provide a physically accurate noise model for the interaction of impinging particles on superconducting qubits, the most widespread and scalable technology for building quantum computers. The model has been devised to be easy to interpret and simulate, whilst being highly expressive and tunable, in order to keep up with future technological advancements in the field. The following step has been to leverage the fault model to develop methods and techniques apt at testing the reliability of \gls{QEC} and quantum algorithms alike. This includes methods for detecting the presence of radiation-induced faults at runtime, and applying partial information reconstruction methods. A deeper understanding of the effects of radiation also prompted the modelling and study of hardware hardening techniques. At last, the interoperation of quantum and classical computing systems has been investigated in the context of the reliability of hybrid machine learning algorithms, which are going to play an ever important role in the high performance computing systems of the future. These contributions press on in the quest for knowledge, impacting the quantum computing stack, correlating logical and physical quantum circuit design, and widening the understanding of how to prevent faults in quantum computing systems, quickening the advent of fault-tolerant quantum computation.
Quantum computers are capable of carrying out calculations that are challenging or even impossible for classical computers. Quantum computers consist of quantum bits (qubits) which can exhibit a phenomenon called superposition where the qubit is in multiple states at the same time. Qubits can also be entangled with other qubits, which means that the states of the qubits are dependant on each other in a way that the state of a single qubit can not be expressed independently of the other qubits. These properties of qubits that enable quantum computing, are very sensitive to perturbations a ecting the system of qubits from the outside. A common choice for the physical architecture of a qubit is a superconducting qubit, which has its quantum properties implemented with a superconducting circuit. Realising a su ciently large qubit system has remained a challenge, since increasing the size of the system leads to more unwanted noise that interacts with the qubits. We have only just achieved systems that can outperform classical computers in speci c tasks. These devices do not o er signi cant advantages and the goal remains to grow the qubit systems, and overcoming the challenges caused by noise is of high importance. The e ect of noise can be reduced by designing hardware that has minimal sources of noise, or by creating qubits with error correction, meaning a way of undoing the e ect of noise on a qubit. Both of these approaches demand a way of recognising the noise mechanisms and their signi cance. Noise characterisation can be done with combining a theoretical model for the dynamics of a qubit with measurement data obtained from the qubit system in question. A su cient t of a theoretical model to noisy measurement data provides parametrisation of the noise, and a well designed model can link the noise to real physical phenomena. In this work, we introduce a noise model based on the Non-Markovian Quantum State Di usion equation. We present the physical processes the model describes and showcase its performance with noisy measurement data obtained with a real quantum processor consisting of superconducting qubits.