Talks

The idea that structure in the Universe was created from quantum mechanical vacuum fluctuations during inflation is very compelling, but unproven. Finding a test of this proposal has been challenging because the universe we observe is effectively classical. I will explain how quantum fluctuations can give rise to the density fluctuations we observe and will show that we can test this hypothesis using the statistical properties of maps of the universe.

Twisted bilayer graphene (tBLG) is a host to a variety of electronic phases, most notably superconductivity when doped away from putative correlated insulator phases. In order to understand the nature of those phases, numerical simulations such as Hartree-Fock calculation and density matrix renormalization group (DMRG) techniques are essential.

Due to the long-range Coulomb interaction and its fragile topology, however, tBLG is difficult to study with standard DMRG techniques.

In this work, we present how a recently developed MPO compression algorithm can be used to make the problem tractable, and how 1D Wannier localization can be used to circumvent the fragile topology.

As a test case, we apply this technique to the toy model of spinless/single-valley model of tBLG. We find that the ground state is essentially a k-space Slater determinant, confirming the validity of previous Hartree-Fock calculations. If time permits, I will also present our ongoing effort to apply this technique to spinful/valleyful model for tBLG.

 I will discuss how central extensions of charge algebras in gravitational theories with null boundaries arise from an anomalous transformation of the boundary term in the gravitational action. This parallels the way in which the holographic Weyl anomaly appears in AdS/CFT, with the ambiguity in the normalization of the null generator being the analogue of the choice of Weyl frame. I will discuss a way to define the gravitational charges unambiguously within the covariant phase space formalism. As an application, I will analyze the near-horizon Virasoro symmetries of black holes and give a systematic derivation of the central charges. I will show that the central extension computed by the charge algebra is directly related to the Bekenstein-Hawking entropy via the Cardy formula.

The potential for discovering new gauge fields of nature relies upon extending the collision energy of hadron colliding beams as far as possible beyond the present 14 TeV capability of LHC.  We must seek a balance of minimum cost/TeV for the ring of superconducting magnets, feasibility and cost of a tunnel to contain the ring, and balancing the luminosity against synchrotron radiation.  Balancing feasibility, technology, and cost is crucial if there is to be a high-energy frontier for discovery of new gauge fields. Three design cases exhibit the tricky balance among these parameters:

FCC-hh:                                100 TeV,              ~100 km tunnel around Geneva,               ~16 T magnets using Nb3Sn

SuperCIC:            100 TeV,              270 km tunnel around Dallas,                      4.5 T magnets using NbTi

Collider-in-the-Sea:         500 TeV,              1900 km pipeline in the Gulf of Mexico,  3.5 T magnets using REBCO

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.