07-10, 15:00–15:30 (US/Pacific), Room 315
Today’s quantum computers are far noisier than their classical counterparts. Unlike traditional computing errors, quantum noise is more complex, arising from decoherence, crosstalk, and gate imperfections that corrupt quantum states. Error mitigation has become a rapidly evolving field, offering ways to address these errors on existing devices. New techniques emerge regularly, requiring flexible tools for implementation and testing. This talk explores the challenges of mitigating noise and how researchers and engineers use Python to iterate quickly while maintaining reliable and reproducible workflows.
Quantum computing introduces a fundamentally different paradigm of computation, but just like classical computing, it is prone to errors. However, debugging quantum computations is far more challenging. In classical computing, when a program fails or returns incorrect results, we can inspect memory, log intermediate values, or rerun the program step by step to diagnose the issue. In contrast, quantum computations operate on delicate quantum states that collapse when measured, making it impossible to directly observe their evolution. This fundamental limitation means that traditional debugging techniques, like printing intermediate values or checking for errors after execution, do not translate directly to quantum systems.
This talk will explore the nature of quantum noise, why debugging quantum computers is fundamentally different from classical systems, and how Python has enabled researchers to develop techniques for mitigating errors. We will begin by breaking down the key sources of quantum noise, such as decoherence, crosstalk, and gate imperfections, and discuss how they corrupt computations in ways that are difficult to detect. Unlike classical errors, quantum errors can occur probabilistically and affect computations in subtle ways that make identifying and correcting them unique.
To address these issues, researchers have developed various error mitigation techniques that allow us to infer and reduce the impact of noise without direct observation. These include zero-noise extrapolation, which runs circuits at different noise levels and estimates an idealized result, and probabilistic error cancellation, which models and statistically corrects for noise effects. Other techniques, such as dynamical decoupling and noise-aware compilation, take a more proactive approach by structuring computations in ways that naturally reduce error rates.
While techniques were published in literature, the quantum software community was quick to catch up with implementation in Python. Enabling fast prototyping, simulation, and benchmarking, Python has become the de facto standard for error mitigation protocols, and even quantum computing at large. The flexibility and ease of use of the language has been crucial in a rapidly evolving field, where new error mitigation methods emerge more frequently and require testing and validation.
Attendees will gain insight into how debugging quantum computers differs from debugging classical systems, why noise is such a significant challenge, and how Python is enabling progress in error mitigation research. This talk is designed for researchers, engineers, and Python developers interested in quantum computing more broadly. No prior experience with quantum computing is required. By the end of the talk, attendees will have a deeper understanding of the complexities of quantum noise and a practical approaches for dealing with it, as well as how they can use Python to contribute to this growing field.
Nate has presented quantum computing to general science audiences at PyData (https://www.youtube.com/watch?v=8ZfyOUuBv3g) and the City University of Seattle (https://www.youtube.com/watch?v=9zB3aCDII7Q), and is the lead developer of the leading Python package for quantum error mitigation: mitiq (https://mitiq.readthedocs.io/, 210k+ downloads).
Nate is a Member of Technical Staff at Unitary Foundation working to make quantum computers useful, usable, and accessible. He mostly works on quantum error mitigation tooling, and is passionate about open source and the benefits it provides the scientific and technology ecosystem. In his spare time nate enjoys rock climbing, running, and building community.