Researchers at Harvard and Northwestern have developed a machine learning method that can design intrinsically disordered proteins with custom properties, addressing nearly 30% of all human proteins that are currently out of reach of AI tools like AlphaFold. The new approach uses automatic differentiation, traditionally a deep learning tool, to optimize protein sequences for desired properties.

In the era of instant data exchange and growing risks of cyberattacks, scientists are seeking secure methods of transmitting information. One promising solution is quantum cryptography – a quantum technology that uses single photons to establish encryption keys. A team from the Faculty of Physics at the University of Warsaw has developed and tested in urban infrastructure a novel system for quantum key distribution (QKD). The system employs so-called high-dimensional encoding. The proposed setup is simpler to build and scale than existing solutions, while being based on a phenomenon known to physicists for nearly two centuries – the Talbot effect. The research results have been published in prestigious journals: “Optica Quantum”, “Optica”, and “Physical Review Applied”.