This talk reviews four different areas where adapting academic physics methods and knowledge proved to be very useful for developing better solar cells. (1) Our knowledge of strongly interacting electrons helped boosting the efficiency of energy conversion in quantum dot solar cells by “multiple electron generation”. (2) Work on the Metal-Insulator Transition was useful to improve charge extraction from quantum dot solar cells. (3) Ideas from quantum glassy dynamics helped mitigating the performance degradation of the next generation heterojunction silicon solar cells. In this study Machine Learning techniques were very helpful to model defect dynamics in silicon solar cells. (4) The theory of phase separation formed the basis for understanding how the next generation topcon solar cells degrade.

Website of the Szilárd Colloquium: https://physics.bme.hu/kollokvium?language=hu 

A long-standing problem in quantum information is: what are the resources that make quantum computers able to perform computational tasks in a way that outperforms any kind of classical Turing machine? The flip side of the same question is: what makes quantum mechanics so hard to simulate? These questions are at the core of the notion of quantum complexity. In this talk we will show that quantum advantage and quantum complexity arise from the conspiracy and interplay of two entropic resources, Entanglement Entropy and Stabilizer Entropy. In particular, quantum complex behavior arises when stabilizer entropy gets scrambled around, giving rise to Scrambling Entropy (SE). We will provide an introduction to the resource theory of SE and applications in quantum thermodynamics, quantum metrology, black-hole physics, and foundations of quantum mechanics.