Taming Quantum Chip Interactions

6 July 2026

Today’s quantum devices often look clean and well-controlled, but the physics inside is far richer and less forgiving. Researchers at Jülich, together with Nobel laureate John M. Martinis and collaborators at MIT, have developed a new framework to tame these hidden interactions.

A network of glowing, pyramid-shaped structures with colored tips in red, orange, blue, and purple against a dark background, with small silver spheres at the corners. (Mistral: Mistral Medium 3.5, 2026-07-06) — The landscape of large and previously hidden interactions among qubits in a quantum processor.

A superconducting quantum processor may look like a clean, well-ordered grid of qubits. Inside the chip, however, the physics is far more crowded. Each qubit can interact not only with its intended neighbours, but also with nearby –and even more distant—qubits through hidden stray couplings and many-body effects. These unwanted “conversations” can distort quantum states, degrade quantum-gate performance, and push the processor away from the behaviour assumed by an ideal quantum algorithm.

With the aim of improving quantum-gate performance, researchers at Quantum Device Theory (QDT) Group led by Dr. Mohammad Ansari at Forschungszentrum Jülich present a scalable theoretical framework for modelling large superconducting quantum processors with high physical fidelity. The findings were published in npj Quantum Information.

Modeling Google’s Sycamore processor with high fidelity

The new framework captures subtle circuit details that are usually simplified or ignored in simulations. With this precision hidden interaction landscapes becomes visible, showing researchers how stray couplings can be suppress or engineered and controlled.

The team tested its theory on Google’s Sycamore chip, the processor used in 2019 to demonstrate quantum supremacy over a classical computer for the first time. Despite that milestone, the microscopic reasons why gate performance can be so difficult to improve have remained partly hidden.

The new theory reveals strong, harmful interactions inside the Sycamore chip in the Processor Error Tomography, or namely PET scan. This helps to understand how previously overlooked couplings limit performance and how future processors can be designed to tame them.

New framework enables predictive design

The study reveals distinct operating regimes, ranging from computationally stable behaviour to highly complex dynamics dominated by many-body interactions. While the latter may be unsuitable for quantum computing, it offers a rich arena for exploring many-body physics. that is not suitable for computing yet interesting for many-body physics. Crucially, even small changes in device parameters can shift the processor into either one of these regimes, with immediate consequences for performance.

The message is clear: hidden interactions are not small correction: but a fundamental design constraint for scalable quantum hardware. The framework enables predictive modelling of quantum processors before they are built. By producing detailed interaction maps, researchers can test layouts, identify error sources, and optimize system parameters at the design stage, rather than relying on costly trial-and-error after fabrication.

International collaboration

The scientific work was carried out by Dr. Mohammad Ansari’s Quantum Device Theory (QDT) group at the Peter Grünberg Institute (PGI-12) of Forschungszentrum Jülich, in collaboration with Nobel Laureate Prof. John M. Martinis of the University of California, Santa Barbara, and Chloé Vignes, a QDT alumna now pursuing doctoral research at the Massachusetts Institute of Technology (MIT).