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The Quantum Bayesian, or QBist, interpretation regards the quantum formalism to be a tool that a single agent may adopt to help manage their expectations for the consequences of their actions. In other words, quantum theory is an addition to decision theory, and its shape, we hope, can teach us something about the nature of reality. Beyond simple consistency, an interpretation is judged by its capacity to point the way forward. In the first half of the talk, I will highlight several ways in which my collaborators and I have applied QBist intuitions to pose and solve technical questions regarding the informational structure and conceptual function of quantum theory. At the root of many of these developments is the notion of a reference measurement, the key to a probabilistic representation of quantum theory. In this setting, we can explore the boundary of the quantum reasoning structure from a uniquely QBist angle. Working with such representations grants a new perspective and inspires questions which wouldn't have occurred otherwise; as examples, we will meet downstream results concerning quantum channels, discrete quasiprobability representations, and a variant of the information-disturbance tradeoff. Most recently, I have pursued ways in which QBism could be applied to the construction of new tools and strategies for existing problems in quantum information and computation. In the second half of the talk, we will encounter the first of these, an agent-based modeling proposal where multiple, suitably interacting, QBist decision-makers might collectively work out the solution to a task of interest in the right circumstances. I will describe some initial explorations of modeling agent belief dynamics in two contexts: first, an expectation sampling interaction with an eye to agential agreement, and, second, a setting where agents are players of quantum games. In the future, we imagine it is possible that a sufficiently mature development of the agent-based program we have begun could suggest new approaches to quantum algorithm design.

Zoom Link: https://pitp.zoom.us/j/95668668835?pwd=MUJtRGMxbEFzSEdVVmZ3TkR3dVVVZz09

Several puzzles and issues in quantum gravity are related to the question of what type of high-energy information is actually available to low-energy observers. In this talk I will try to argue that the best description available to a low-energy observer is probably of a statistical nature. Such a statistical description naturally connects to e.g. the eigenstate thermalization hypothesis, and wormholes and the apparent lack of factorization. I will describe this statistical picture and the evidence we have for it, and what we could possibly learn from it. Partially based on work in progress.

Zoom Link: https://pitp.zoom.us/j/96646337719?pwd=UVRKN3Y4Q05xNXk1VExOenYwSFZvZz09

In the fuzzy dark matter model, dark matter consists of “axion-like” ultra-light scalar particles of mass around 10⁻²² eV. This candidate behaves similarly to cold dark matter on large scales, but exhibits different properties on smaller (galactic) scales due to macroscopic wave effects arising from the extremely light particles’ large de Broglie wavelengths. It has both particle physics motivations and a rich astrophysical phenomenology, giving rise to notable differences in the structures on highly non-linear scales due to the manifestation of wave effects, which can impact a number of contentious small-scale tensions in the standard cosmological model, ΛCDM. Some of the unique features include transient wave interference patterns and granules, the presence flat-density cores (solitons) at the centers of dark matter halos, and the formation of quantized vortices. I will present large numerical simulations of cosmic structure formation with this dark matter model – including the full non-linear wave dynamics – using a pseudo-spectral method to numerically solve the Schrödinger–Poisson equations, and the significant computational challenges associated with these equations. I will discuss several observables, such as the evolution of the matter power spectrum, the fuzzy dark matter halo mass function, dark matter halo density profiles, and the question of a fuzzy dark matter core–halo mass relation, using results obtained from these simulations, and contrast them with corresponding results for the cold dark matter model.

Aside from quantum mechanics, other areas in physics constrain information processing. From relativity, we know information cannot move faster than the speed of light. In quantum gravity, we expect but don't fully understand additional constraints, for instance on how densely information can be stored. Can we develop an understanding of information processing in the context of quantum gravity? Towards doing so, we consider quantum information within ``holographic'' spacetimes, which have an alternative, non-gravitational, description. In that context questions about information processing in the presence of gravity can be translated to different questions about quantum information without gravity. As a specific example, we study constraints on computation within a gravitating region, and use the holographic description to argue that gravity constrains the complexity of operations that can happen inside the region. Along the way, we are led to new connections relating quantum gravity, position-based cryptography, quantum secret sharing and complexity theory. 

Topological quantum codes illustrate a variety of concepts in quantum many-body physics. They also provide a realistic and resource-efficient approach to building scalable quantum computers. In this talk, I will focus on fault-tolerant quantum computing with a new topological code, the 3D subsystem toric code (STC). The 3D STC can be realized on the cubic lattice by measuring small-weight local parity checks. The 3D STC is capable of handling measurement errors while performing reliable quantum error correction and implementing logical gates in constant time. This dramatically reduces the computational time overhead and gives the 3D STC a resilience to time-correlated noise.