Our papers are the official record of our discoveries. They allow others to build on and apply our work. Each paper is the result of many months of research, so we make a special effort to make them clear, beautiful and inspirational, and publish them in leading journals.
The notion of quantum superposition speeds up the training process for binary neural networks and ensures that their parameters are optimal.
A solution to the information paradox uses standard quantum field theory to show that black holes can evaporate in a predictable way.
Machine learning techniques enhance the efficiency of energy harvesters by implementing reversible energy-conserving operations.
One-shot analogs of fluctuation-theorem results help unify these two approaches for small-scale, nonequilibrium statistical physics.
An explicit recipe for defining the Hamiltonian in general probabilistic theories, which have the potential to generalise quantum theory.
We generalise neural networks into a quantum framework, demonstrating the possibility of quantum auto-encoders and teleportation.
Spectroscopy experiments show that energy shifts due to photon emission from individual molecules satisfy a fundamental quantum relation.
A new equality which depends on the maximum entropy describes the worst-case amount of work done by finite-dimensional quantum systems.
Quantum tunnelling only occurs if either the Wigner function is negative, or the tunnelling rate operator has a negative Wigner function.
With inspiration from Maxwell’s classic thought experiment, it is possible to extract macroscopic work from microscopic measurements of photons.
Single-shot information theory inspires a new formulation of statistical mechanics which measures the optimal guaranteed work of a system.
A review of the achievements concerning typical bipartite entanglement for random quantum states involving a large number of particles.