Talks

We introduce a new class of first passage time optimization mediated by a threshold resetting (TR) mechanism. Inspired by many natural processes that operate under “safety covenant” or are governed by “threshold triggered events” wherein a system, structure, or process exceeds a predefined limit (threshold), causing failure, degradation, or a transition to a different state; we consider an arbitrary first passage process that is intermittently renewed when the search agents, looking for targets, are simultaneously reset upon reaching a certain threshold. Unlike the classical paradigm where the resetting events are externally modulated, here they are event driven and thus, strongly coupled to the system variables. Furthermore, the simultaneous resetting induces long-range interactions between the searchers. A unified theoretical framework is presented for computing the search time associated with this class of correlated stochastic processes, further showcasing a rich and diverse optimization phenomena.

In this talk, I will describe a method that rigorously transforms the toric code model into independent emergent qubits, which enables us to construct the toric code eigenstates exactly and devise precise quantum circuits for their implementation on quantum processors.

The Josephson diode effect (JDE), characterized by asymmetric critical currents in a Josephson junction, has drawn considerable attention in the field of condensed matter physics. We investigate the conditions under which JDE can manifest in a one-dimensional Josephson junction composed of a spin-orbit-coupled quantum wire with an applied Zeeman field, connected between two superconductors. Our study reveals that while spin-orbit coupling (SOC) and a Zeeman field in the quantum wire are not sufficient to induce JDE when the superconductors are purely singlet, the introduction of triplet pairing in the superconductors leads to the emergence of JDE. This finding highlights the potential of JDE as a probe for triplet superconductivity. We further demonstrate that even in absence of SOC in the quantum wire, JDE can arise when the directions of the triplet pairing and the Zeeman field are non-collinear, provided the superconductors exhibit mixed singlet-triplet pairing. Additionally, we identify specific conditions under which JDE is absent, namely, when the pairing is purely triplet and the directions of the SOC and the triplet pairing are perpendicular. Our results suggest that quantum wires in Josephson junctions could serve as effective platforms for probing triplet superconductivity through the observation of JDE.

Cosmology is undergoing a data revolution. Surveys such as the imminent Legacy Survey of Space and Time (LSST) to be conducted by the Vera C. Rubin Observatory will deliver huge galaxy catalogues that provide critical tools for understanding the nature of dark matter and dark energy. However, in order to obtain accurate cosmological constraints from these enormous datasets, we need reliable ways of estimating galaxy properties using only photometry. I will present pop-cosmos: a forward modelling framework for photometric galaxy survey data, where galaxies are modelled as draws from a population prior distribution over redshift, mass, dust properties, metallicity, and star formation history. These properties are mapped to photometry using an emulator for stellar population synthesis, followed by the application of a learned model for a survey's noise properties. Application of selection cuts enables the generation of mock galaxy catalogues. This enables us to use simulation-based inference to solve the inverse problem of calibrating the population-level prior on a deep multiwavelength catalogue, COSMOS2020. We use a diffusion model as a flexible population-level prior, and optimise its parameters by minimising the Wasserstein distance between forward-simulated photometry and the real COSMOS2020 survey data. The resulting model can then be used to derive accurate redshift distributions for upcoming photometric surveys, to facilitate weak lensing and clustering science. I will show applications of this framework, demonstrating how we are able to extract redshift distributions, and make inferences about galaxy evolution. I will also discuss the use of pop-cosmos as a prior for performing inference on individual galaxies in a highly scaleable manner, as well as ongoing work to analyse data from the Kilo-Degree Survey (KiDS) in preparation for LSST.