Real-time error mitigation for variational optimization on quantum hardware
Year: 2026
Type: article
Abstract: In this work, we put forward the inclusion of error mitigation routines in the process of training variational quantum circuit (VQC) models. In detail, we define a real-time quantum error mitigation (RTQEM) algorithm to assist in fitting functions on quantum chips with VQCs. While state-of-the-art QEM methods cannot address the exponential loss concentration induced by noise in current devices, we demonstrate that our RTQEM routine can enhance VQCs’ trainability by reducing the corruption of the loss function. We tested the algorithm by simulating and deploying the fit of a monodimensional u -quark parton distribution function on a superconducting single-qubit device, and we further analyzed the scalability of the proposed technique by simulating a multidimensional fit with up to eight qubits.
Source: Physical Review Research
DOI: 10.1103/zyb2-zl2d
Institutions: University of Milan, European Organization for Nuclear Research, Consejo Superior de Investigaciones Científicas, Technology Innovation Institute, Instituto de Física Teórica, Universidad Autónoma de Madrid, Australian National University, Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Istituto Nazionale di Fisica Nucleare, Sezione di Milano Bicocca
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,625
OpenAlex ID: W4388650629
