Search Talks

Theories which spontaneously break spacetime parity can solve the strong CP problem. They usually have few free parameters and are therefore very predictive, but their landscape remains quite unexplored. I will present a construction based on a complete mirror copy of the standard model, linked to our world by colored portal fields. Those induce the partial spontaneous breaking of the color groups, yielding a vanishing theta angle at low energies. The lightest BSM fields could be found at colliders, and are either colored (pseudo-Goldstone or vector) bosons, or some of the vectorlike fermions predicted by parity. The lightest of the latter can actually play the role of thermal dark matter in our model, unlike what was previously found in similar constructions.

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This talk is virtual, but will also be broadcast in the Sky Room. 

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Determining the long-range phase of matter of a strongly coupled system from its microscopic description has long been one of the central topics in physics. Simple microscopic systems often become strongly coupled at long range where we usually rely on clever approximations. Bootstrap is an alternative approach that uses positivity and equations of motion to make predictions in quantum many-body systems without making approximations. In this talk, I will show my recent work on using bootstrap to compute the ground state energy, local observables and gaps of a quantum many-body system in the thermodynamic limit with rigorous error bars.

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A cosmological network of axion strings in our Universe today may leave its imprint on the polarization pattern of the cosmic microwave background radiation through the phenomenon of axion-string-induced birefringence. I will explain how this signal arises, discuss how it depends on the properties of the string network and the axion-photon coupling, describe how existing measurements of anisotropic birefringence place constraints on axion strings, and discuss how the non-Gaussian nature of this signal could be leveraged in searches with future data.

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