Search Talks

A remarkable aspect of 4-dimensional complexified General Relativity (GR) is that it can be non-trivially deformed: there exists an infinite-parameter set of modifications with the same degree of freedom count. It is trivial to impose reality conditions that lead to real theories with Euclidean or split signature, but the situation is more complicated and not yet fully understood in the Lorentzian case, which is the subject of this talk. I will first show that the choice of potentially consistent reality conditions is essentially unique and boils down to the reality of the underlying 3-metric at the canonical level, as in the case of GR. For simplicity, I will focus on a subset of modified theories that correspond to a natural extension of Ashtekar's Hamiltonian constraint, namely, a linear combination of EEE, EEB, EBB and BBB. Interestingly, the evolution equations for the 3-metric and its first time-derivative take the same form as in GR, but with an effective stress tensor source which cannot be expressed in terms of these two fields. Modified theories therefore appear as essentially "non-metric" in that they do not admit a closed geometrodynamics form. In particular, this obstructs the conservation of the reality conditions, because the effective source remains complex. Alternatively, if we insist on reality, we obtain extra reality conditions which then leave no room for degrees of freedom. I will finally argue that this should be a generic feature of the Lorenzian modified theories, in stark contrast to their Euclidean and split-signature counterparts.

Combining information from the first gravitational wave detected gamma-ray burst, GRB 170817 with observations of cosmological GRBs holds important lessons for understanding the structure of GRB jets and the required conditions at the emitting region. It also re-frames our understanding of more commonly observed phenomena in GRBs, such as X-ray plateaus, and sets our expectations for future observations. I will present different lines of argument suggesting that efficient gamma-ray emission in GRBs has to be restricted to material with Lorentz factor > 50 and is most likely confined to a narrow region around the core. GRB jets viewed slightly beyond their jet cores, result in X-ray plateaus that are consistent with observed light-curves and naturally reproduce correlations between plateau and prompt emission properties. For jets viewed further off-axis (that are expected to be detected as future GW triggered events) we provide new analytical modelling that reveals two different types of light-curves that could be observed (single or double peaked) and outlines how the underlying physical properties can be recovered from such observations.

To analyze the performance of adaptive measurement protocols for the detection and quantification 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 quantification. 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 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.

The understanding of strongly-correlated quantum matter has challenged physicists for decades. The discovery three years ago of correlated phases and superconductivity in magic angle twisted bilayer graphene led to the emergence of a new materials platform to investigate strongly correlated physics, namely moiré quantum matter. These systems exhibit a plethora of quantum phases, such as correlated insulators, superconductivity, magnetism, Chern insulators, and more. In this talk I will review some of the recent advances in the field, focusing on the newest generation of moiré quantum systems, where correlated physics, superconductivity, and other fascinating phases can be studied with unprecedented tunability. I will end the talk with an outlook of some exciting directions in this emerging field.

In recent years quantum error correction(QEC) has become an important part of AdS/CFT. Unfortunately, there are no field-theoretic arguments about why QEC holds in known holographic systems. The purpose of this paper is to fill this gap by studying the error-correcting properties of the fermionic sector of various large N theories. Specifically, we examine SU(N) matrix quantum mechanics and 3-rank tensor O(N)^3 theories. Both of these theories contain large gauge groups. We argue that gauge singlet states indeed form a quantum error-correcting code. Our considerations are based purely on large N analysis and do not appeal to a particular form of Hamiltonian or holography. Based on: arXiv: 2008.12869

Models of Dark Matter (DM) can leave unique imprints on the Universe's small scale structure by boosting density perturbations on small scales. We study the capability of Pulsar Timing Arrays to search for, and constrain, subhalos from such models. The models of DM we consider are ordinary adiabatic perturbations in ΛCDM, QCD axion miniclusters, models with early matter domination, and vector DM produced during inflation.

Recently, the notion of symmetry has been extended from 0-symmetry described by group to higher symmetry described by higher group. In this talk, we show that the notion of symmetry can be generalized even further to "algebraic higher symmetry". Then we will describe an even more general point of view of symmetry, which puts the (generalized) symmetry charges and topological excitations at equal footing: symmetry can be viewed gravitational anomaly, or symmetry can be viewed as shadow topological order in one higher dimension.

The predictions of quantum theory resist generalised noncontextual explanations. In addition to the foundational relevance of this fact, the particular extent to which quantum theory violates noncontextuality limits available quantum advantage in communication and information processing. In the first part of this work, we formally define contextuality scenarios via prepare-and-measure experiments, along with the polytope of general contextual behaviours containing the set of quantum contextual behaviours. This framework allows us to recover several properties of set of quantum behaviours in these scenarios . Most surprisingly, we discover contextuality scenarios and associated noncontextuality inequalities that require for their violation the individual quantum preparation and measurement procedures to be mixed states and unsharp measurements. With the framework in place, we formulate novel semidefinite programming relaxations for bounding these sets of quantum contextual behaviours. Most significantly, to circumvent the inadequacy of pure states and projective measurements in contextuality scenarios, we present a novel unitary operator based semidefinite relaxation technique. We demonstrate the efficacy of these relaxations by obtaining tight upper bounds on the quantum violation of several noncontextuality inequalities and identifying novel maximally contextual quantum strategies. To further illustrate the versatility of these relaxations we demonstrate the monogamy of preparation contextuality in a tripartite setting, and present a secure semi-device independent quantum key distribution scheme powered by quantum advantage in parity oblivious random access codes.

In the last two decades the field of nonequilibrium quantum many-body physics
has seen a rapid development driven, in particular, by the remarkable progress
in quantum simulators, which today provide access to dynamics in quantum
matter with an unprecedented control. However, the efficient numerical
simulation of nonequilibrium real-time evolution in isolated quantum matter
still remains a key challenge for current computational methods especially
beyond one spatial dimension. In this talk I will present a versatile and
efficient machine learning inspired approach. I will first introduce the
general idea of encoding quantum many-body wave functions into artificial
neural networks. I will then identify and resolve key challenges for the
simulation of real-time evolution, which previously imposed significant
limitations on the accurate description of large systems and long-time
dynamics. As a concrete example, I will consider the dynamics of the
paradigmatic two-dimensional transverse field Ising model, where we observe
collapse and revival oscillations of ferromagnetic order and demonstrate that
the reached time scales are comparable to or exceed the capabilities of state-
of-the-art tensor network methods.

I describe the non-relativistic c→∞ and ultra-relativistic c→0 limits of the kappa-deformed symmetries, with and without a cosmological constant.  The corresponding kappa-Newtonian and kappa-Carrollian noncommutative spacetimes are also obtained. These constructions show the non-trivial interplay between the quantum deformation parameter kappa, the curvature parameter Lambda and the speed of light parameter c.

Human contact patterns are highly heterogeneous in terms of the both the number and nature of interactions. To incorporate these heterogeneities into infectious disease models one naturally represents a population as a weighted network. While there is a large literature on the spread of diseases on networks, most techniques are highly computational in nature. In this talk I will talk about an analytical framework for modeling infectious diseases as a percolation process on weighted networks based on probability generating functions. 

In the context of vaccination, human contact heterogeneities become a resource: Vaccinating individuals with greater total exposure leads to a greater reduction in disease spread. We have proposed that exposure notification apps, such as COVID Alert, can be leveraged to improve vaccine uptake among high exposure individuals, thereby optimizing our limited COVID-19 vaccine supply. We demonstrate the efficiency of this proposal using our weighted percolation theory framework.