Seminar

Lorentzian symmetry predicts universality beyond scaling laws

Speaker(s): 
Stephen J. Watson
Dates: 
Wednesday, August 15, 2018 - 11:00am to 12:00pm

We present a covariant theory for the ageing characteristics of phase-ordering systems that possess dynamical symmetries beyond mere scalings. A chiral spin dynamics which conserves the spin-up (+) and spin-down (−) fractions, $\mu_+$  and $\mu_-$ , serves as the emblematic paradigm of our theory. Beyond a parabolic spatio-temporal scaling, we discover a hidden Lorentzian dynamical symmetry therein, and thereby prove that the characteristic length L of spin domainsgrows in time t according to $L = \frac{\beta}{\sqrt{1 - \sigma^2}}t^{\frac{1}{2}}$ , where $\sigma:= \mu_+ - \mu_-$  (the invariant spin-excess) and βis a universal constant. Furthermore, the normalised length distributions of the spin-up and the spin-down domains each provably adopt a coincident universal (σ-independent) time-invariant form, and this supra-universal probability distribution is empirically verified to assume a form reminiscent of the Wigner surmise.

Orbital selective pairing in Fe-based superconductors

Speaker(s): 
Dr. Peter Hirschfeld
Dates: 
Thursday, October 18, 2018 - 4:00pm

Iron-based superconductors are unconventional superconductors with relatively high Tc that derive from metallic parent compounds with several Fe d-states dominant at the Fermi level. This gives rise to a number of novel effects based on differentiated degree of correlation of the different orbital states. I discuss the influence on spin-fluctuation pairing theory of orbital selective strong correlation effects in Fe-based superconductors, particularly Fe chalcogenide systems. This paradigm yields remarkably good agreement with the experimentally observed anisotropic gap structures in both...

Using the dynamics of nanodevices for artificial intelligence

Speaker(s): 
Alice Mizrahi
Dates: 
Tuesday, July 31, 2018 - 11:00am

Artificial neural networks are performing tasks, image recognition and natural language processing, for artificial intelligence. However, these algorithms run on traditional computers and consume orders of magnitude more energy more than the brain does at the same task. One promising path to reduce the energy consumption is to build dedicated hardware to perform artificial intelligence. Nanodevices are particularly interesting because they allow for complex functionality with low energy consumption and small size. I discuss two nanodevices. First, I focus on stochastic magnetic tunnel junctions, which can emulate the spike trains emitted by neurons with a switching rate that can be controlled by an input. junctions can be combined with CMOS circuitry to implement population coding to build low power computing systems capable of controlling output behavior. Second, I turn to different nanodevices, memristors, to implement a different type of computation occurring in nature: swarm intelligence. A broad class of algorithms inspired by the behavior of swarms have been proven successful at solving optimization problems (for example an ant colony can solve a maze). Networks of memristors can perform swarm intelligence and find the shortest paths in mazes, without any supervision or training. These results are striking illustrations of how matching the functionalities of nanodevices with relevant properties of natural systems open the way to low power hardware implementations of difficult computing problems.

Theory and Modeling of Excited State and Carrier Dynamics in Organic Functional Materials

Speaker(s): 
Zhigang Shuai
Dates: 
Monday, July 30, 2018 - 4:00pm to 5:00pm

We present our recent work on the computational investigations on the charge carrier transport and the excited state decay processes for organic energy materials. We developed a time-dependent vibration correlation function formalism for evaluating the molecular excited state non-radiative decay rate combining non-adiabatic coupling and spin-orbit coupling, to make quantitative prediction for light-emitting quantum efficiency. We proposed a nuclear tunneling enabled hopping model to describe the charge transport in organic semiconductors. An efficient time-dependent DMRG approach is proposed to calculate the optical spectra and carrier dynamics for molecular aggregates.

Variations on a theme of Aharonov and Bohm

Speaker(s): 
Sir Michael Victor Berry
Dates: 
Tuesday, September 25, 2018 - 4:30pm to 5:30pm

The Aharonov-Bohm effect (AB) concerns the role in quantum physics of the vector potential of an impenetrable line of magnetic flux. Its partial anticipation by Ehrenberg and Siday, in terms of interference, was an approximation whose wavefunction was not singlevalued, and whose connection with the singlevalued AB wave involves topology: waves winding round the flux (‘many-whirls representation’). AB is a fine illustration of idealization in physics. There are four AB effects, depending on whether the waves and the flux are classical or quantum. In the classical-classical case, many...

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