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We are the Theory group of LPS!

If you are interested in doing an internship with us, or want to visit and discuss, please contact any of our members.

We are a very collaborative group which covers a wide range of topics from material sciences (functional materials, topological and relativistic matter, magnetism and superconductivity...) and quantum systems (in low dimensions, under magnetic fields, in and out-of equilibrium...) to soft and bio- matter (colloids, liquid crystals...).

Explore and enjoy our site!

  • Most recent peer-reviewed publications are below.

Recent Publications

Y. Kalcheim, Camjayi, A., del Valle, J., Salev, P., Rozenberg, M., and Schuller, I. K., “Non-thermal resistive switching in Mott insulator nanowires”, vol. 11, no. 1, p. 2985, 2020. WebsiteAbstract
Resistive switching can be achieved in a Mott insulator by applying current/voltage, which triggers an insulator-metal transition (IMT). This phenomenon is key for understanding IMT physics and developing novel memory elements and brain-inspired technology. Despite this, the roles of electric field and Joule heating in the switching process remain controversial. Using nanowires of two archetypal Mott insulators—VO2 and V2O3 we unequivocally show that a purely non-thermal electrical IMT can occur in both materials. The mechanism behind this effect is identified as field-assisted carrier generation leading to a doping driven IMT. This effect can be controlled by similar means in both VO2 and V2O3, suggesting that the proposed mechanism is generally applicable to Mott insulators. The energy consumption associated with the non-thermal IMT is extremely low, rivaling that of state-of-the-art electronics and biological neurons. These findings pave the way towards highly energy-efficient applications of Mott insulators.
P. Stoliar, Schneegans, O., and Rozenberg, M. J., “Biologically Relevant Dynamical Behaviors Realized in an Ultra-Compact Neuron Model”, Frontiers in Neuroscience, vol. 14, p. 421, 2020. WebsiteAbstract
We demonstrate a variety of biologically relevant dynamical behaviors building on a recently introduced ultra-compact neuron (UCN) model. We provide the detailed circuits which all share a common basic block that realizes the leaky-integrate-and-fire (LIF) spiking behavior. All circuits have a small number of active components and the basic block has only three, two transistors and a silicon controlled rectifier (SCR). We also demonstrate that numerical simulations can faithfully represent the variety of spiking behavior and can be used for further exploration of dynamical behaviors. Taking Izhikevich’s set of biologically relevant behaviors as a reference, our work demonstrates that a circuit of a LIF neuron model can be used as a basis to implement a large variety of relevant spiking patterns. These behaviors may be useful to construct neural networks that can capture complex brain dynamics or may also be useful for artificial intelligence applications. Our UCN model can therefore be considered the electronic circuit counterpart of Izhikevich’s (2003) mathematical neuron model, sharing its two seemingly contradicting features, extreme simplicity and rich dynamical behavior.
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