Noise-to-Signal: Reimagining ultrafast optical spectroscopies to capture fluctuating dynamics in quantum materials
Supervisors: Dr. Raj Pandya (Chem.), Prof. James Lloyd-Hughes (Phys.), Prof. Animesh Datta (Phys)
Summary:
Optical pump-probe spectroscopy is the go-to method for capturing ultrafast (femtosecond) dynamics in solid-state materials and has been used to understand everything from magnetism to photosynthesis. The problem is that pump-probe methods can only capture the ‘average’ dynamics in a system. This means that rapid fluctuations in electronic excitations, critical to phenomena like superconductivity, ion transport or (quantum) phase transitions, remain inaccessible.
This project will revolutionise the information limits of pump-probe spectroscopy. We will build quantitative analytical/computational models of the experiment to derive new, universal, measurement and analysis protocols for capturing ultrafast nonequilibrium physics from pump-probe. We will then apply these methods to explore otherwise ‘hidden’ properties, e.g., quantum entanglement, in solid-state materials. The project is ideal for a student with interests in quantum dynamics, information theory/AI and stochastic physics, with close links to experimentalists.
Background:
Quantum materials (QMs) are ones whose properties are dominated by quantum mechanical effects. They include superconductors, superionic systems and topological insulators with applications in a range of fields from computing to energy storage [1]. A hallmark of quantum materials is the presence of femtosecond fluctuations in the electronic structure and atomic positions, caused by entanglement in the wavefunction. This ultimately gives rise to the fascinating functional properties of QMs.
Ultrafast optical pump-probe spectroscopy–where one laser pulse drives the system, and a second pulse follows the response–is the only tool we have available to capture femtosecond material dynamics [2]. Whilst pump-probe can capture short-lived excited states, it typically only gives a ‘time-averaged’ picture, when sufficient population of a state has built-up. As a result, we remain unable still to capture the key fluctuating, irreversible and randomly emerging ultrafast dynamics that lie at the crux of quantum materials.
What is needed is a way to link femtosecond pump-probe signals (observables) to quantum fluctuations [3], in the same way we do for classical fluctuations on millisecond timescales, e.g., Brownian motion. Luckily, recent developments in our ability to model complex light-matter interactions [4,5], and the theory of open quantum systems, means that tackling this problem is no-longer a pipedream. The aim of the Noise-to-Signal project is to unlock this new frontier in physics.
Project Objectives for the PhD project:
To push pump-probe spectroscopy into a regime where we can capture the key fluctuating dynamics of quantum materials, we will take several steps. First, we will develop a robust model of the pump-probe experiment, focussing on the information bounds in the experimental signals and how these depend on the nature of the light used (e.g., squeezed vs classical light). Secondly, we will derive analytical links between the measurable responses in pump-probe e.g., non-linear susceptibility or structure factor, and characteristics properties of the quantum system e.g., Fischer information. Here, there will be a close link to experimentalists such as to translate and test the theoretical models we derive into experimental protocols, for instance by varying the pulse sequence in pump-probe. From this we will develop software (useful to thousands of scientists) where one can ‘feed-in’ pump-probe data and then extract critical information on quantum dynamics. Finally, we will apply our resulting framework to explore entangled and metastable states in solid-oxide systems touted for material-based quantum computing.
The project is highly collaborative, with access to state-of-the art resources and opportunities for secondments to groups in Europe/USA as well as partners in the quantum-computing industry.
Relevant references:
[1] | Keimer et al. Nature Phys., 13, 1045–1055 (2017) |
[2] |
Pandya et al. Nat. Commun., 2, 6519 (2021) |
[3] | Hales et al. Nat. Commun. 14, 3512 (2023) |
[4] | Caprini et al. Nat. Commun., 15 94 (2024) |
[5] | Baykusheva et al. Phys. Rev. Lett. 130, 106902 (2023) |
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