Quantum Transport in Oxides

QUANTUM WELLS

Over the recent years, we have investigated the properties of quantum wells (QWs) at the LaAlO₃/SrTiO₃ interface, including 2D superconductivity, Rashba spin-orbit fields and lattice vibrational modes [see References 1-3 below].

Among our recent discoveries there is the observation of polar lattice distortions in LaAlO3/SrTiO3 quantum wells due to extreme confinement of phonon modes [3]. We used advanced scanning transmission electron microscopy methods to visualize shifts in the atomic positions in the lattice and first-principles calculations to understand the physics behind these observations [3].

We are also interested in low-dimensional quantum transport, and in particular, with 2D superconductivity. Along these lines, we have recently observed for a first time a multi-condensate superconductor tuneable by electrostatic gating in LaAlO3/SrTiO3 quantum wells, published recently in Nature Materials [4].

More recently we have uncovered persistent photoconductance (PPC), whereby the system changes its conductance in a plastic way, retaining memory from its past history, as in the case of memristors, but using light instead of electric pulses. Our most recent discovery [5] is that light pulses can be used to replicate spike timing-dependent plasticity (STDP). STDP was proposed to emulate time causality of electro-chemical signals in biological neurons: pre-synaptic neurons spiking after post-synaptic neurons are “anti-causal” and learning is weakened; pre-synaptic neurons spiking before post-synaptic neurons are causal, reinforcing learning. STDP enables unsupervised learning, without need of labelling training data.

 

(Left) We can emulate STDP of biological neurons by illuminating the QWs with pairs of short-(violet)/long- (red) wavelength pulses of visible light. (Right) The reinforcement/depression of synaptic strength –represented by the photoconductance of the QW– might be exploited in artificial vision networks to replicate spatial and navigation maps built in biological brains.

[1] Pesquera et al., Physical Review Letters 2014. https://doi.org/10.1103/PhysRevLett.113.156802

[2] Herranz et al., Nature Communications 2015. https://doi.org/10.1038/ncomms7028

[3] Gazquez et al., Physical Review Letters 2017. https://doi.org/10.1103/PhysRevLett.119.106102

[4] G. Singh et al., Nature Materials 18, 948–954 (2019). https://doi.org/10.1038/s41563-019-0354-z

[5] Y. Chen et al. Physical Review Letters 124, 246804 (2020) https://doi.org/10.1103/PhysRevLett.124.246804

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