Search Talks

Effective field theory is a computationally powerful and flexible theoretical framework, finding application in many areas of physics. In particle physics, Weinberg’s folk theorem also promises that any theory that reproduces the predictions of the Standard Model will, at low energies, look like an effective field theory. In one sense the power of this framework should be a cause for pride in the progress of physics and discovery of real structural features of the world. But given the inability to fully unite quantum theory and gravity into a consistent theoretical picture, there is also cause for pessimism: indirect tests of candidate theories of quantum gravity will ultimately reduce to something like an effective field theory, undermining efforts to find low-energy windows into new physics. One way around this pessimism is to look at where and why effective field theory breaks down in current physical theories. I will point to familiar breakdowns (the cosmological constant, inflation, the hierarchy problem), offering a take on what these breakdowns tell us about the shape of physics beyond the Standard Model. Cracks in the wall of effective field theory allow for a dim glimpse of what might lie beyond.

Polyaromatic hydrocarbons (PAHs) such as acenes have long been studied due to its interesting optical properties and low singlet triplet gaps. Earlier studies have already noticed that use of complete valence active space is imperative to the understanding of its qualitative and quantitative properties. Since complete active space based methods cannot be applied to such large active spaces, we have used density matrix renormalization group (DMRG) based approaches. Further small modification to the PAH topology shows interesting new phases of behaviour in its optical gaps. We have understood the effect of these effects based on spin frustration due to the presence of odd membered rings. In this talk, I will discuss these observations from molecular and model Hamiltonian perspectives.Further developments based on artificial neural network based configuration interaction for strongly correlated systems will also be discussed.5  The similarities between the ANNs and the MPS wavefunctions will be leveraged for 2D systems.

Zoom link:  https://pitp.zoom.us/j/92159136836?pwd=ZFJBcXZ3R3czSUcxcThOci9ueStBZz09