Quantum Errors and Benchmarking Quantum Computers

ai.bythebay.io Nov 2025, Oakland, full-stack AI conference We have two exciting talks – quantum errors and benchmarking quantum computers. Andrea Mari, Mitigating quantum errors with Mitiq This demo/talk introduces an open-source package for error-mitigation in quantum computation using zero-noise extrapolation. Error-mitigation techniques improve computational performance (with respect to noise) using minimal overhead in quantum resources by relying on a mixture of quantum sampling and classical post-processing techniques. Our error-mitigation package interfaces with multiple quantum computing software stacks, and we demonstrate improved performance on a variety of benchmarks performed on IBM and Rigetti quantum processors. We describe the library using code snippets to demonstrate usage and discuss features, support, and contribution guidelines. We’re looking forward to your feedback! Andrea Mari is a physicist, with experience in academic and industrial research. PhD in Physics. Interested in quantum technologies,machine learning, computer vision, internet-of-things. This is Mitiq recently uploaded white paper, https://arxiv.org/abs/2009.04417, and the package documentation can be found at https://mitiq.readthedocs.io/, including the full API documentation, hands-on tutorials and additional information on quantum error mitigation. Dan Mills, Benchmarking Near-Tern Quantum Computers One might imagine that verifying a quantum computation would take at least as much computing power as performing the computation itself. For example, in general it is thought that simul…