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Abstract and

Zoom Link: https://pitp.zoom.us/j/91762985902?pwd=djhwYVdsQ25GVVBRVTlwSkQvaDJ4Zz09

Cosmology and astrophysics with the extragalactic light: background and fluctuations

Abstract: The aggregate light emitted by all extragalactic sources can be measured either as an absolute intensity or through its spatial fluctuations; these are known as line-intensity mapping (LIM) when a particular line transition is targeted. I will discuss how these measurements can be used both to learn about galaxy evolution and to investigate the presence of more speculative sources of radiation, such as decaying dark matter. I will then discuss the prospects of LIM to probe the interstellar and intergalactic medium, as well as structure on large scales. In particular, I will focus on the joint information across different line transitions and across different tracers, such as galaxies and extragalactic CMB foregrounds.

Zoom Link: https://pitp.zoom.us/j/94959896129?pwd=QjhzWS9rczdBNGFndUhhNDZ1K1FLQT09

Variational methods have proven to be excellent tools to approximate the ground states of complex many-body Hamiltonians. Generic tools such as neural networks are extremely powerful, but their parameters are not necessarily physically motivated. Thus, an efficient parametrization of the wave function can become challenging. In this talk I will introduce a neural-network-based variational ansatz that retains the flexibility of these generic methods while allowing for a tunability with respect to the relevant correlations governing the physics of the system. I will illustrate the ansatz on a model exhibiting topological phase transitions: The toric code in the presence of magnetic fields. Additionally, I will talk about the use of variational wave functions to gain physical insights beyond lattice models, in particular for the real use-case of two-dimensional materials.

Information is physical, and for a physical theory to be universal, it
should model observers as physical systems, with concrete memories where
they store the information acquired through experiments and reasoning.
Here we address these issues in Spekkens' toy theory, a non-contextual
epistemically restricted model that partially mimics the behaviour of
quantum mechanics. We propose a way to model physical implementations of
agents, memories, measurements, conditional actions and information
processing. We find that the actions of toy agents are severely limited:
although there are non-orthogonal states in the theory, there is no way
for physical agents to consciously prepare them. Their memories are also
constrained: agents cannot forget in which of two arbitrary states a
system is. Finally, we formalize the process of making inferences about
other agents' experiments and model multi-agent experiments like
Wigner's friend. Unlike quantum theory or box world, in the toy theory
there are no inconsistencies when physical agents reason about each
other's knowledge.

Zoom Link: TBD