News Release

Is “Smoking Gun” evidence enough to prove scientific discovery?

When it comes to replication, sometimes the scientific process in the natural sciences also misfires

Peer-Reviewed Publication

University of Pittsburgh

Smoking gun or mundane fine-tuning?

image: 

Dramatic smoking gun patterns can signify important effects in topological condensed matter physics, but these originate from mundane fine-tuning in complex samples 

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Credit: Frolov Lab

Embargoed: Not for Release Until 2:00 pm U.S. Eastern Time Thursday, 08 January 2026.

A group of scientists, including Sergey Frolov, professor of physics at the University of Pittsburgh, and coauthors from Minnesota and Grenoble have undertaken several replication studies centered around topological effects in nanoscale superconducting or semiconducting devices. This field is important because it can bring about topological quantum computing, a hypothetical way of storing and manipulating quantum information while protecting it against errors. 

In all cases they found alternative explanations of similar data. While the original papers claimed advances for quantum computing and made their way into top scientific journals, the individual follow-ups could not make it past the editors at those same journals.  Reasons given for its rejection included that being a replication it was not novel; that after a couple of years the field has moved on. But replications take time and effort and the experiments are resource-intensive and cannot happen overnight. And important science does not become irrelevant on the scale of years. 

The scientists then united several replication attempts in the same field of topological quantum computing into a single paper. The aim was twofold: demonstrate that even very dramatic signatures that may appear consistent with major breakthroughs can have other explanations–especially when fuller datasets are considered, and outline changes to the research and peer review process that have the potential to increase the reliability of experimental results: sharing more data and openly discussing alternative explanations. 

It took significant time and argumentation for the rest of the community to accept this possibility: the paper spent a record two years under peer and editorial review. It was submitted in September 2023.  It will publish in the journal Science on January 8 2026.


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