Talks

Directional dark matter detectors using diamond as a target material offer a novel solution to overcome solar neutrino backgrounds. Sub-micron damage tracks from nuclear recoils can be read out via advanced quantum sensing techniques with nitrogen-vacancy (NV) centers. I will discuss recent advancements in strain-sensitive quantum interferometry that enable precise strain imaging, paving the way for directional particle detection. These developments highlight the potential of diamond-based detectors for advancing dark matter and neutrino physics, as well as material science applications.

Emergent Modified Gravity (EMG) is a post-Einsteinian theory of canonical gravity. In this formulation, modified constraints are required to preserve an algebra of hypersurface deformation form and will in general imply modified structure functions. This procedure leads to the conclusion that spacetime is an emergent object with a nontrivial dependence on the gravitational phase space variables through the modified structure functions. Consistency conditions are imposed on the modified constraints and the emergent spacetime metric to ensure general covariance. The resulting modifications allowed by EMG go beyond those obtained from adding higher curvature terms and can result in nonpolynomial dependencies on extrinsic curvature components. In this talk, we discuss how a particular interpretation of such modifications as holonomy terms makes it possible to use EMG as a covariant framework for effective (loop) quantum gravity. We then focus on dynamical solutions of the spherically symmetric model which include nonsingular black holes, new effects to gravitational collapse, and MOND-like effects at intermediate scales.

The groundbreaking detection of gravitational waves from merging black holes has forever changed how we observe the Universe. Upcoming detectors, like the Laser Interferometer Space Antenna (LISA), will unlock new opportunities by allowing us to detect mergers between stellar-mass black holes (tens of solar masses) and supermassive black holes (SMBHs, millions to billions of solar masses). These fascinating events, known as extreme-mass-ratio inspirals (EMRIs), provide a wealth of information about the dynamics near SMBHs. A key formation channel for EMRIs involves weak gravitational interactions—two-body kicks—from surrounding stars and compact objects that gradually alter the small black hole's orbit, eventually driving it into the SMBH. However, the picture changes when we consider the presence of SMBH companions, which can induce high orbital eccentricities, further enhancing EMRI formation. In this talk, I will show that combining these two processes is crucial for understanding the progenitors of EMRIs. Moreover, I will demonstrate that SMBH binaries create EMRIs more efficiently than either process alone, making it truly rain black holes! This scenario results in a substantial stochastic gravitational wave background for future detectors like LISA. Finally, I will also discuss how this mechanism affects tidal disruption events and address the tantalizing question: Is it raining stars, too?

I'll discuss the representation theory of line operators in 3d holomorphic-topological theories, following recent work with Wenjun Niu and Victor Py. Examples of the line operators we have in mind include half-BPS lines in 3d N=2 supersymmetric theories (reinterpreted in a holomorphic twist). We compute the OPE of line operators, which endows the category with a meromorphic tensor product, and establish a perturbative nonrenormalization theorem for the OPE. Then, applying Koszul-duality methods of Costello and Costello-Paquette, we represent the category of lines as modules for a new sort of mathematical object, which we call a dg-shifted Yangian. This is an A-infinity algebra, with a chiral coproduct whose data includes a Maurer-Cartan element that behaves like an infinitesimal r-matrix. The structure is a cohomologically shifted version of the ordinary Yangians that represent lines in 4d holomorphic-topological theories.

Dark photons and axions are exciting candidates for dark matter, which may be observable through their couplings to electromagnetism or electrons. While many experimental programs have been developed to explore the wide range of parameter space over which these candidates may exist, the mass range corresponding to frequencies below a kHz has been seldom probed by laboratory experiments. In this talk, I will discuss two ongoing efforts to probe this region of parameter space. Both rely on the ability of dark-photon or axion dark matter to source an oscillating magnetic field signal inside an experimental apparatus. In the first case, this magnetic field signal is detected by observing its effect on magnetically levitated (Maglev) systems. The oscillating magnetic field signal sourced by dark matter can drive translational motion of a levitated superconductor or rotational motion of a levitated ferromagnet. As mechanical resonators, Maglev systems are naturally sensitive to lower frequencies, making them well-suited detectors for sub-kHz dark matter candidates. In the second case, we instead consider Earth as the experimental apparatus. That is, we search directly for the oscillating magnetic field signal using unshielded magnetometers located across the Earth's surface. Not only does the signal strength receive an enhancement from the large size of the Earth, but it is also correlated between independent measurements at different locations. I will discuss the search for this signal in existing publicly available magnetometer data maintained by the SuperMAG collaboration, as well as an independent experimental effort, known as SNIPE Hunt, to measure this signal in the field. I will show that both Maglev systems and unshielded magnetometers have the potential to set the leading laboratory constraints on dark-photon and axion dark matter in the sub-kHz regime.

Improving cosmological constraints from galaxy clustering presents several challenges, particularly in extracting information beyond the power spectrum due to the complexities involved in higher-order n-point function analysis. In this talk, I will introduce novel inference techniques that allow us to go beyond the state-of-the-art, not only by utilizing the galaxy trispectrum, a task that remains computationally infeasible with traditional methods, but also by accessing the full information encoded in the galaxy density field for the first time in cosmological analysis. I will present simulation-based inference (SBI), a powerful deep learning technique that enables cosmological inference directly from summary statistics in simulations, bypassing the need for explicit analytical likelihoods or covariance matrices. This is achieved using LEFTfield, a Lagrangian forward model based on the Effective Field Theory of Large Scale Structure (EFTofLSS) and the bias expansion, ensuring robustness on large scales. Furthermore, LEFTfield enables field-level Bayesian inference (FBI), where a field-level likelihood is used to directly analyze the full galaxy density field rather than relying on compressed statistics. I will conclude by exploring the question of how much cosmological information can be extracted at the field level through a comparison of σ8 constraints obtained from FBI, which directly uses the 3D galaxy density field, and those obtained from n-point functions via SBI.