Talks

Quantum biology explores how phenomena like superposition, tunneling, and entanglement influence biological systems, with growing experimental evidence supporting their role in processes such as photosynthesis, enzymatic reactions, DNA mutations, and animal navigation. These discoveries have profound implications for medicine, renewable energy, and our understanding of life. Quantum neurobiology applies this perspective to the brain, exploring how brain cells function beyond traditional models of electrical activity and chemical neurotransmission. Moving beyond classical models of chemical and electrical neuronal signaling, quantum approaches could revolutionize diagnostics and treatments for neurological disorders while offering deeper insights into cognition, behavior, and consciousness. Here will be presented an overview of quantum biology, examining the current state of quantum neurobiology, both theory and experiment, and exploring its potential applications in diagnosing and treating neuroinflammatory conditions such as Alzheimer’s and Parkinson’s disease.

In this talk, I will introduce our recent studies on the effect of decoherence on fractional quantum Hall fluids and their robustness as topological quantum memories. Specifically, we examine the behavior of Laughlin states and Moore-Read states under dephasing noise using the plasma analogy as well as the field theory description. Notably, we identify a critical filling (which is 1/4 for the Renyi-2 case and between 1/4 and 1/8 in the replica limit) separating two regimes of mixed-state phase transition. Below the critical filling, a Berezinskii-Kosterlitz-Thousless (BKT) transition occurs at finite noise strength, separating the topologically ordered phase from a critical phase. This transition is characterized by quantum-information quantities that are non-linear functions of the density matrix. On a torus, the BKT transition marks the critical decoherence above which the quantum memory encoded in the ground state manifold is degraded. In contrast, above the critical filling, the quantum memory is extremely resilient against dephasing noise, with the transition occurring only at infinite noise strength. For the Moore-Read state, we further show that the transition also characterizes whether different fusion outcomes of non-Abelian anyons remain distinguishable under decoherence.

In this talk, we will explore what low-energy experiments on gravitationally mediated entanglement (GME) can reveal about the quantum nature of gravity. We will analyze the key assumptions necessary to interpret GME experiments as evidence for quantum aspects of the gravitational interaction and examine how these assumptions influence our conclusions. Additionally, we will discuss possible modifications to experimental designs aimed at minimizing dependence on assumptions. Then we will discuss what these experiments in different regimes can and cannot probe about gravity’s quantum nature.

Motivated by the frame independence of the Bekenstein-Hawking black hole entropy, and the possibility of it being fundamentally entanglement entropy, I will present a spacetime definition for the entanglement entropy of free quantum fields. This definition is a spectral formulation, conducive to frame independent regularization. I will then go on to show an example calculation in Rindler spacetime, and comment on more general applications.

This study presents the modeling of the gravitational wave (GW) bias parameter by bridging a connection between simulated GW sources and galaxies in low redshift galaxy surveys 2MPZ and WISExSCOS (WISC). We study this connection by creating a mock GW catalog, populating galaxy surveys with binary black holes (BBHs) for different scenarios of the GW host-galaxy probability as a function of the galaxy stellar mass. We probe the observable consequences of this connection by exploring the spatial clustering of the GW sources in terms of the GW bias parameter. We consider a phenomenological broken power law model for the host-galaxy probability function, with a potential turnover M_K at high stellar mass (10^{11} solar mass in the fiducial model) where the star formation efficiency begins to drop. We vary the parameters of the GW host-galaxy probability function and find that generically the GW bias increases as M_K increases (and gets suppressed as M_K decreases). The change in the GW bias parameter shows a maximum change of about 30% for different scenarios explored in this work in comparison to the galaxy bias. Future measurements of the GW bias can help constrain M_K and the slopes of the host-galaxy probability function and thus offer insights into the underlying astrophysical processes.