Scientific Series

Carrying the insights of conditional probability to the quantum realm is notoriously difficult due to the non-commutative nature of quantum observables. Nevertheless, conditional expectations on C* and von Neumann algebras have played a significant role in the development of quantum information theory, and especially the study of quantum error correction. In quantum gravity, it has been suggested that conditional expectations may be used to implement the holographic map algebraically, with quantum error correction underlying the emergence of spacetime through the generalized entropy formula. However, the requirements for exact error correction are almost certainly too strong for realistic theories of quantum gravity. In this talk, we provide an overview of the multifaceted nature of quantum conditional probability by exploring different non-commutative generalizations of conditional expectations which meet the demands of non-exact error correction. We then exemplify the utility of these tools through two examples. First, we demonstrate how operator valued weights can be used to classify the possible symmetries (including non-invertible symmetries) of a quantum system. Then, we introduce a generalization of Connes’ spatial theory leading to a fully non-commutative form of Bayes' law. This allows for an exact quantification of the information gap occurring in the data processing inequality for arbitrary quantum channels. When applied to algebraic inclusions, this further provides an approach to factorizing the entropy of states into a sum of terms including an emergent area operator that is fully non-commutative rather than central. 

Generative AI — a class of algorithms that learn complex probability distributions from data — is opening new avenues for discovery across fundamental physics. In this talk, I will highlight several recent applications. At the LHC, we are ushering in a new paradigm of model-agnostic searches for new physics, developing powerful anomaly detection methods using generative AI techniques such as normalizing flows. These same methods, applied to astronomical data, have enabled discovery of stellar streams and ultra-faint dwarf galaxies. Generative methods also accelerate simulation-based inference across many domains, including gravitational wave detection at pulsar timing arrays. When combined with physics-informed neural networks, generative AI enables an entirely new model-free measurement of the dark matter density in the local Galactic neighborhood. Finally, I will discuss how generative AI in the form of agentic LLMs is creating new modes of human-AI collaboration that promise to further accelerate research. Taken together, these advances signal that we have entered a new and exciting era — one where the oldest questions about our universe may very well be answered with the help of the newest AI tools.

Entanglement is usually discussed in the context of two subsystems at a fixed time. A natural question is whether this notion can be meaningfully extended to subsystems at different time slices. In this talk, I will present a family of entanglement measures defined for time-separated subsystems. A key property of these quantities is that they bound time-separated correlation functions, in close analogy with bounds on spatial correlators in terms of mutual information. For relativistic quantum field theories, our definition agrees with the analytic continuation from spacelike to timelike separated regions. I will discuss measurement protocols, computations for the Ising chain and holographic theories, and the relation of these constructions to the recently introduced timelike pseudoentropy. Based on https://arxiv.org/abs/2502.12240 .

The AdS/CFT correspondence makes it possible in principle to study explicit black hole microstates using field theory techniques. In practice, this is still difficult because the field theory is only dual to gravity when it is strongly coupled. A more modest goal is to focus on supersymmetric black holes which have the minimal energy allowed by their other charges. The superconformal index suggests that many of these are protected from quantum corrections and can therefore be constructed at weak coupling. I will explain how one can identify candidates for black holes by searching the Hilbert space of ABJM theory. On general grounds, these should depend sensitively on trace relations at finite N. This principle, known as fortuity, was first established in a similar study of maximally supersymmetric Yang-Mills theory. I will show that similarities between the two theories extend to the quantitative level thereby allowing additional progress to be made without a brute force search.

The interstellar medium (ISM) plays an important role in sculpting the structure of our Galaxy: in addition to being the birthplaces of stars, ISM substructures have the capacity to significantly perturb stellar orbits. However, conventional stellar-dynamical studies often rely on idealized toy models or omit these gas “fluctuations” entirely, leaving their impact on the evolution of stellar systems poorly understood. In this talk, I will present a model for ISM fluctuations that is both theoretically tractable and easily incorporated into traditional N-body simulations, while retaining the essential features of a realistic ISM. The model is derived from a characterization of the ISM in the state-of-the-art TIGRESS magnetohydrodynamics simulations, which include self-consistent, first-principles gas microphysics and resolve scales down to 2 parsecs. I will then highlight several key differences between the dynamical effects of these realistic fluctuations and those assumed in prevailing models, focusing on orbital heating and radial migration in galactic disks. Finally, I will discuss the importance of accounting for the ISM’s influence in drawing robust conclusions about the Milky Way’s dynamical history and dark matter substructure.

Spacetime fluctuations can invalidate usual notions of distance, time, and even what it means to perform an experiment. This raises a simple question: when spacetime fluctuates, how do we describe what happens? Few detailed ​answers exist, even in the low-energy effective field theory of quantum gravity. In this talk, we present a study of geometric and detector observables in perturbative quantum gravity. Geometric observables—elapsed proper time, proper distance, area, and Shapiro time delay—can be defined in relation to observer worldlines. Proper time observables capture quantum gravity effects in interferometers, leading to predictions for experiments that probe the interface between quantum mechanics and gravity. Several geometric observables display a quantum version of memory. Realistic detector observables—modelled by local operators inserted along worldlines—describe measurements more directly. We compute correlators of worldline-dressed scalars at tree level with an external on-shell graviton. The worldline dressing is hardly innocuous and can, in fact, induce enormous corrections. Gravitational effects can either open or close light cones, as captured by the commutator of dressed scalars. Finally, we discuss the broader landscape of observables now within closer reach in effective field theory and holography.

Gravitational waves (GW) offer a new and independent window onto the Universe. However, as they propagate across cosmological distances, they are inevitably affected by the intervening matter distribution. In this talk, I present a comprehensive overview of my work on the gravitational lensing of GWs, spanning weak lensing by the large-scale structure of the Universe, strong lensing by galaxies, and microlensing by stars and compact objects, and covering lensing effects from the geometric-optics to the wave-optics regimes. I highlight how gravitational lensing can serve not only as a systematic effect in GW observations, but also as a novel probe of cosmic structure and fundamental physics. Finally, I discuss future directions of GW lensing studies, inspired by advances in electromagnetic lensing.

Fault-tolerant logical entangling gates are essential for scalable quantum computing but are limited by the error rates and overheads of physical two-qubit gates and stabilizer measurements. We introduce phantom codes, a class of codes that attain the minimal possible cost: all in-block logical entangling operations reduce to qubit permutations that can be absorbed at the compilation stage, yielding zero physical-gate overhead and perfect logical fidelity. Our first main result is the discovery of such codes via four mechanisms. By exhaustively enumerating all 2.71x1010inequivalent CSS codes up to n=14 we find all codes to this scale and then identify additional instances up to n=21 using SAT methods. We then use quantum Reed-Muller constructions to find higher k instances and a "binzarization-and-concatenation" scheme to achieve higher d. Second, through end-to-end noisy simulations, we demonstrate scalable advantages of phantom codes over the surface code across multiple tasks. This includes a ~207x improvement in logical fidelity for Trotterized many-body quantum simulation at current physical error rates, with comparable qubit counts and a 22% preselection rate; the advantage persists from 8 to $64$ logical qubits. These results establish phantom codes as a viable architectural route to fault-tolerant quantum computation with scalable benefits for workloads with dense local entangling structure.