Search Talks

Studying the smallest self-bound dark matter structure in our Universe can yield important clues about the fundamental particle nature of dark matter, and galaxy-scale strong gravitational lensing provides a unique way to detect and characterize dark matter on small scales at cosmological distances from the Milky Way. Research in this field can be broadly separated into works that aim to directly detect individual perturbers and works that aim to statistically constrain the matter distribution by looking at collective perturbations caused by an unresolved population of perturbers. We present recent advances in both of these approaches. With respect to the former, we present advances in the analysis of gravitational lenses and identification of small-scale clumps using machine learning. With respect to the latter, we introduce the convergence power spectrum as a promising statistical observable that can be extracted from strong lens images and used to distinguish between different dark matter scenarios, showing how different properties of the dark matter get imprinted on different scales. We include a discussion on the different contribution of substructure and line-of-sight structure to perturbations in strong lens images.

To analyze the performance of adaptive measurement protocols for the detection and quanti cation of state resources, we introduce the framework of quantum preparation games. A preparation game is a task whereby a player sequentially sends a number of quantum states to a referee, who probes each of them and announces the measurement result. The measurement setting at each round, as well as the final score of the game, are decided by the referee based on the past history of settings and measurement outcomes. We show how to compute the maximum average score that a player can achieve under very general constraints on their preparation devices and provide practical methods to carry out optimizations over n-round preparation games. We apply our general results to devise new adaptive protocols for entanglement detection and quanti cation. Given a set of experimentally available local measurement settings, we provide an algorithm to derive, via convex optimization, optimal n-shot protocols for entanglement detection using these settings. We also present families of non-trivial adaptive protocols for multiple-target entanglement detection with arbitrarily many rounds. Surprisingly, we find that there exist instances of entanglement detection problems with just one target entangled state where the optimal adaptive protocol supersedes all non-adaptive alternatives.

I discuss general argument to show that if a physical system can mediate locally the generation of entanglement between two quantum systems, then it itself must be non-classical. Remarkably, the argument does not assume any classical or quantum formalism to describe the mediating physical system: the result follows from general information-theoretic principles. This argument provides a robust and general theoretical basis for recently proposed tests of non-classicality in gravity, based on witnessing gravitationally-induced entanglement in quantum probes.

The theory of quasimaps to Nakajima quiver varieties X has recently been used very effectively by Aganagic, Okounkov and others to study symplectic duality. For certain X, namely Hilbert schemes of ADE surfaces, it turns out quasimap theory is equivalent to a particular flavor of Donaldson-Thomas theory on a related threefold Y. I will explain this equivalence and how it intertwines concepts and tools from the two sides. For example, symplectic duality has something to say about the crepant resolution conjecture for Y.

The astrophysical background of gravitational waves (AGWB) is composed by the incoherent superposition of gravitational wave signals emitted by resolved and unresolved astrophysical sources from the onset of stellar activity until today. In this talk, I  will present a theoretical framework  to characterize the AGWB in terms of energy density and polarization and  I will show predictions for the angular power spectra of the background anisotropy and for its cross-correlations with electromagnetic observables, in the frequency bands accessible by  LIGO/Virgo and  LISA.  I will then discuss the astrophysical content of these observables, give an overview of the state of the art of observations, and highlight future observational challenges.

What do data science and the foundations of quantum theory have to do with one another?

A great deal, it turns out. The particular branch of data science known as causal inference focuses on a problem which is central to disciplines ranging from epidemiology to economics: that of disentangling correlation and causation in statistical data.

Meanwhile, in a slightly different guise, this same problem has been pondered by quantum physicists as part of a continuing effort to make sense of various puzzling quantum phenomena. On top of that, the most celebrated result concerning quantum theory’s meaning for the nature of reality – Bell’s theorem – can be seen in retrospect to be built on the solution to a particularly challenging problem in causal inference.

Recent efforts to elaborate upon these connections have led to an exciting flow of techniques and insights across the disciplinary divide.

Perimeter researchers Robert Spekkens and Elie Wolfe have done pioneering work studying relations of cause and effect through a quantum foundational lens, and can be counted among a small number of physicists worldwide with expertise in this field.

In their joint webcast from Perimeter on October 7, Spekkens and Wolfe will explore what is happening at the intersection of these two fields and how thinking like a quantum physicist leads to new ways of sussing out cause and effect from correlation patterns in statistical data.

Watch live online at insidetheperimeter.ca.

The Petz recovery channel plays an important role in quantum information science as an operation that approximately reverses the effect of a quantum channel. The pretty good measurement is a special case of the Petz recovery channel, and it allows for near-optimal state discrimination. A hurdle to the experimental realization of these vaunted theoretical tools is the lack of a systematic and efficient method to implement them. We rectify this lack using the recently developed tools of quantum singular value transformation and oblivious amplitude amplification, providing a quantum algorithm to implement the Petz recovery channel. Our quantum algorithm also provides a procedure to perform pretty good measurements when given multiple copies of the states that one is trying to distinguish.

Using the same toolbox, we also develop a quantum algorithm for enacting the polar decomposition, a workhorse in linear algebra. This provides an alternative route to implementing a pretty-good measurements for the special case of pure states, which speeds up the general-purpose algorithm developed above.

We show that a naïve application of the quantum extremal surface (QES) prescription can lead to paradoxical results and must be corrected at leading order. The corrections arise when there is a second QES (with strictly larger generalized entropy at leading order than the minimal QES), together with a large amount of highly incompressible bulk entropy between the two surfaces. We trace the source of the corrections to a failure of the assumptions used in the replica trick derivation of the QES prescription, and show that a more careful derivation correctly computes the corrections. Using tools from one-shot quantum Shannon theory (smooth min- and max-entropies), we generalize these results to a set of refined conditions that determine whether the QES prescription holds. We find similar refinements to the conditions needed for entanglement wedge reconstruction (EWR), and show how EWR can be reinterpreted as the task of one-shot quantum state merging (using zero-bits rather than classical bits), a task gravity is able to achieve optimally efficiently.

Mapping of galaxy density fluctuations on large scales is one of the most important goals of observational cosmology in this decade. These observations can significantly improve our knowledge of the universe, its origins and composition. In this talk I will review some of the science goals of the ongoing and future spectroscopic galaxy surveys and explain how these goals can be met. In particular, I will focus on some recent progress in theoretical modelling of the nonlinear structure formation and show how it can be used to extract cosmology from observations of the cosmic web. As an example I will present several analyses from the publicly available Baryon Oscillation Spectroscopic Survey (BOSS) data and results for the standard LCDM model as well as several relevant extensions.

Hoop conjecture suggests that microscopic black holes can be produced in collisions of high energy particles if the fundamental gravity scale is lowered to the electroweak scale in extra dimension models. This opens up the possibility of studying extra dimensions in collliders and neutrino telescopes. In this talk, I will introduce the unique signatures associated with black holes from cosmic neutrino-nucleon scattering in IceCube-Gen2. These signatures include new topologies, distinct energy distributions and unusual ratios of hadronic-to-electronic energy deposition. I will also discuss the study of dark sector in future colliders through the investigation of the production and decay of microscopic black holes and the implications of these black holes for the early universe.