Electrons can be ‘kicked across’ solar materials at almost the fastest speed nature allows, scientists have discovered – challenging long-held theories about how solar energy systems work. The finding could help researchers design more efficient ways of harvesting sunlight and converting it into electricity.

In experiments capturing events lasting just 18 femtoseconds – less than 20 quadrillionths of a second – researchers at the University of Cambridge observed charge separation happening within a single molecular vibration.

“We deliberately designed a system that, according to conventional theory, should not have transferred charge this fast,” said Dr Pratyush Ghosh, Research Fellow, at St John’s College, Cambridge, and first author of the study. “By conventional design rules, this system should have been slow and that’s what makes the result so striking.

“Instead of drifting randomly, the electron is launched in one coherent burst. The vibration acts like a molecular catapult. The vibrations don’t just accompany the process, they actively drive it.”

A femtosecond is one quadrillionth of a second – one second holds about eight times more femtoseconds than all the hours that have passed since the universe began. At that scale, atoms inside molecules are physically vibrating. 

The research, published in Nature Communications, challenges decades of design rules in solar energy research.

Estimating things that exist is generally easy, but when it comes to estimating things that do not exist, it’s more difficult. This is something physicists from Poland and the UK are well aware of. To improve current simulations of high-energy particle collisions, they have developed a more accurate method for estimating the impact of calculations that are... not performed.

FAU has received a U.S. Air Force T-1A Jayhawk Mixed Reality and 3D Motion flight simulator through an in-kind grant from the U.S. Air Force Office of Scientific Research. The motion-enabled, open-architecture system replicates real flight conditions for high-risk, cost-effective experimentation. It will support cross-disciplinary work in neuroscience, biomedical engineering, cybersecurity, robotics and systems engineering. The simulator provides hands-on training opportunities for students and faculty, fosters collaboration with industry and federal partners, and establishes FAU as a hub for experimentation in next-generation autonomous and AI-enabled systems.

This article investigates Quantum Fisher Information (QFI) as a diagnostic tool for analyzing parameter sensitivity and entanglement in the Quantum Approximate Optimization Algorithm (QAOA).

Key Findings

Problem Analysis: The study examines Max-Cut problems on cyclic and complete graphs, plus random Ising model instances, comparing RX-only and hybrid RX-RY mixers up to depth p=9 .

QFI Insights: Complete-graph Max-Cut instances generate substantially larger QFI eigenvalues than cyclic ones, exceeding shot-noise scaling (4N) while remaining below the Heisenberg limit (4N2).

Entanglement Effects: The first entangling stage produces the dominant QFI increase, while additional stages yield diminishing returns. Entanglement primarily amplifies cross-parameter correlations rather than individual parameter sensitivity.

Practical Application: The authors propose QFI-Informed Mutation (QIm), a heuristic that adapts mutation probabilities using diagonal QFI entries. QIm outperforms uniform and random-restart baselines, especially for deeper circuits.

The work positions QFI as both a structural probe and practical optimization resource for NISQ-era quantum algorithms.