Other & Previous Research Interests
Machine learning has recently gained a lot of attention because of its practical utility. In particular, in the field of quantum technologies, where significant attention has been diverted to "quantum machine learning". But what exactly is it that adds the attribute "quantum" to machine learning? Is it the machine that operates based on quantum-mechanical principles? Or is it a "quantum" problem that a classical machine is applied to.
While both directions have their merit, here, we have been interested in the former: specifically, to understand in what sense reinforcement-learning agents could profit from having access to internal quantum-computing hardware, as is explained in more detail here. |
Scheme for a projective simulation agent that interacts with its environment via sensory input (percepts), and action on the environment that is conducted using a set of actuators.
The sensors and actuators are linked to the memory, which relates new perceptual input to the agent’s past experience. Figure from [Sriarunothai et al., Quant. Sci. Techn. 4, 015014 (2019)].
|
Fermions make up essentially all standard matter in the standard model of particle physics, but interestingly their role in quantum information and computation is sometimes regarded as marginal. Nonetheless, growing interest in fermions and their interesting properties is arising through applications in solid state physics. Many theoretical studies rely on mappings between fermions and qubits - the Pauli principle practically limits the occupation of a fermionic mode to at most one particle, effectively turning them into two-level systems. However, there is an interesting mismatch between fermions and qubits. My research interest is hence to study this difference, to learn in what sense "fermions are not qubits", and to study the quantum correlations in fermionic systems with no fixed particle number. Read about it in [Friis, Lee, Bruschi Phys. Rev. A 87, 022338 (2013)], and in [Friis, Reasonable fermionic quantum information theories require relativity, New J. Phys. 18, 033014 (2016)], or in our recent article on fermionic teleportation [Debarba, Iemini, Giedke, Friis, Phys. Rev. A 101, 052326 (2020)]. Download a presentation [pdf], or find out more on this website.
|
Over the past decade the discipline of relativistic quantum information (RQI) has received much attention. Its aim is the study of the resources and tasks of quantum information science in the context of relativity, i.e. by combining elements of quantum information theory, quantum optics and quantum field theory with special and general relativity. In particular attention has been focused on the mechanisms that degrade or generate entanglement, the main resource of quantum information tasks.
For reviews see, e.g., [Alsing and Fuentes, Class. Quantum Grav. 29, 224001 (2012)] or my Ph.D. thesis [Friis, Ph.D. thesis, University of Nottingham, 2013, arXiv:1311.3536]. More information can be found here. |
Can quantum effects in curved spacetimes be simulated in compact, laboratory-based experimental setups? Following the formal analogy between quantum field theory on curved spacetimes and classical fluid systems [Unruh, Phys. Rev. D 14, 870 (1976)], this question has captivated researchers for decades, see e.g. [Barceló, Liberati, and Visser, Living Rev. Relativity 8, 12 (2005)] for a recent review. A central aim in such studies is the observation of radiation that can be associated to quantum pair creation processes, e.g., to the Hawking-, Unruh- and the dynamical Casimir effect. All of these effects rely on similar mechanisms in quantum field theory, i.e., particle creation due to time-dependent gravitational fields and boundary conditions, or the presence of horizons.We investigate the possibility to generate quantum-correlated quasi-particles utilizing such analogue gravity systems. The quantumness of these correlations is a key aspect of analogue gravity effects and their presence allows for a clear separation between classical and quantum analogue gravity effects. Read more here.