A new paper by UMBC researchers, led by physicist Sebastian Deffner, demonstrates quantum computing’s potential to optimize urban train scheduling, using Baltimore’s Light RailLink as a model. Their study, published with collaborators from the Polish Academy of Sciences, leverages quantum “noise” to model unpredictable train delays. Tested on IonQ and D-Wave quantum devices, the approach solves small-scale scheduling but highlights the need for advanced hardware for larger networks. This interdisciplinary work could revolutionize logistics, finance, and drug discovery by tackling complex systems affected by randomness.

The experiment, which will take place on 19 September, demonstrates the potential of high-performance computing infrastructures for emergency calculations, warning systems and urgent responses to extreme natural events.

Thanks to the exceptional allocation of supercomputing resources, unprecedented seismic simulation maps will be generated covering half of Mexico, one of the most seismically active areas on the planet.

In pancreatic cancer, knowing if there is metastasis is key to deciding whether to operate or not. Nowadays, a significant number of patients undergo unnecessary invasive surgeries because their metastasis was not detected in time.

"Our algorithm accurately predicts metastasis using images that are already routinely obtained," says Malats.

The article is published in the journal 'GUT'.

The algorithm will be tested in hospitals thanks to a project that has received nearly 800,000 euros in funding from the Spanish Department for Digital Transformation.