Multi-fractional Brownian Motion Model Captures Long-Memory Effects in Charge Noise

Charge noise, a major obstacle to building stable quantum computers, limits how long quantum information persists in superconducting qubits. Mahboob Ul Haq from the Department of Physics, Govt Post Graduate College Timergara, and colleagues introduce a new model that captures the complex behaviour of this noise with unprecedented accuracy. Their approach utilises a mathematical framework called memory multi-fractional Brownian motion, allowing them to simulate noise that changes over time and retains ‘memory’ of past fluctuations. This innovative model successfully reproduces observed patterns of quantum decoherence and provides a deeper understanding of how environmental factors interact with delicate quantum systems, potentially paving the way for more robust and reliable quantum technologies.

Quantum computing has rapidly evolved from theoretical foundations to experimental demonstrations of quantum supremacy and industrial-scale hardware development. Among leading platforms, superconducting qubits have emerged as a promising building-block due to their scalability, compatibility with lithographic fabrication, and rapid gate operations. Particularly, the transmon qubit, a charge-insensitive variant of the superconducting charge qubit, offers enhanced coherence properties by optimising the ratio of Josephson energy to charging energy. Understanding and mitigating decoherence, however, remains a central challenge in realising practical quantum technologies and offers new insights into environmental interactions with superconducting quantum devices.

Superconducting Qubit Decoherence and Noise Mitigation

This research provides a detailed exploration of decoherence and noise in superconducting qubits, focusing on overcoming limitations imposed by these factors in early quantum devices. Researchers investigate charge noise as a dominant source of decoherence, employing multifractional Brownian motion to model its non-stationary and complex nature, a significant improvement over traditional models. The work relies on numerical simulations, validated by experimental observations, to understand and predict qubit behaviour. The research confirms that charge noise significantly contributes to decoherence in transmon qubits.

Simulations, using multifractional Brownian motion, accurately capture observed qubit behaviour, including coherence and energy relaxation times. The Lindblad master equation, incorporating these noise models, provides a realistic description of qubit dynamics, and experimental validation confirms the accuracy of the simulations. Designing qubits with inherent noise protection, through material choices or device geometry, is crucial for achieving longer coherence times. Simulations also demonstrate that charge noise can be managed to keep the excited state population low, maintaining qubit fidelity.

The research employs multifractional Brownian motion to model the time-dependent noise and uses the Lindblad master equation to describe qubit dynamics. Statistical analysis is used to compare simulation results to experimental data, and key quantum metrics quantify qubit performance. This work contributes to the fundamental understanding of noise and decoherence, essential for building practical quantum computers, and guides the design of more robust qubits with longer coherence times.

Charge Noise Exhibits Memory and Revival

Researchers have developed a new model to understand charge noise, a major source of errors in quantum computers using superconducting qubits. This model incorporates the idea that noise isn’t random but possesses a ‘memory’, influencing present fluctuations, and that these fluctuations occur over a wide range of timescales. The team employed multifractional Brownian motion to accurately capture these complex, long-lasting correlations. Simulations demonstrate that charge noise causes qubit fidelity to decay, but at a relatively slow rate of approximately 3 microseconds, and reveal a surprising degree of ‘revival’ in qubit coherence, indicating that the noise’s memory effect can partially restore lost information.

These findings align with experimental observations and suggest that charge noise doesn’t immediately destroy quantum information as quickly as previously thought. Refinement of the model incorporated realistic timescales for qubit behaviour, revealing that the impact of charge noise is limited by the qubit’s inherent properties, causing fidelity and coherence to plateau at a measurable level. This suggests that designing qubits with improved coherence and relaxation times is crucial for mitigating the effects of charge noise and building more robust quantum computers.

Bounded Decoherence via Stochastic Noise Modelling

This research introduces a new stochastic model for charge noise, employing multifractional Brownian motion, to better understand decoherence in quantum devices. The model successfully captures the non-stationary and long-memory characteristics of charge noise, mirroring key experimental observations and providing a more nuanced understanding of environmental interactions affecting qubits. Importantly, the findings suggest that while charge noise remains a source of decoherence, its practical impact is bounded by the inherent noise-protected properties of the qubits themselves. The developed framework is valuable for designing robust control protocols and optimising device parameters, potentially leading to more stable and reliable quantum systems. Further investigation is needed to fully characterise the complex interplay between different noise sources and their combined effect on qubit performance, contributing to the advancement of practical quantum technologies.