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Topological Data Analysis of Monopole Current Networks in U(1) Lattice Gauge Theory (2024)
Journal Article
Crean, X., Giansiracusa, J., & Lucini, B. (2024). Topological Data Analysis of Monopole Current Networks in U(1) Lattice Gauge Theory. SciPost Physics, 17(4), Article 100. https://doi.org/10.21468/SciPostPhys.17.4.100

In 4-dimensional pure compact U(1) lattice gauge theory, we analyse topological aspects of the dynamics of monopoles across the deconfinement phase transition. We do this using tools from Topological Data Analysis (TDA). We demonstrate that observabl... Read More about Topological Data Analysis of Monopole Current Networks in U(1) Lattice Gauge Theory.

Anomalous mass diffusion in a binary mixture and Rayleigh-Bénard instability. (2024)
Journal Article
Barletta, A., & Straughan, B. (2024). Anomalous mass diffusion in a binary mixture and Rayleigh-Bénard instability. Physical Review E, 110(4), Article 045102. https://doi.org/10.1103/PhysRevE.110.045102

The onset of the Rayleigh-Bénard instability in a horizontal fluid layer is investigated by assuming the fluid as a binary mixture and the concentration buoyancy as the driving force. The focus of this study is on the anomalous diffusion phenomenolog... Read More about Anomalous mass diffusion in a binary mixture and Rayleigh-Bénard instability..

Exact approaches on the string worldsheet (2024)
Journal Article
Demulder, S., Driezen, S., Knighton, B., Oling, G., Retore, A. L., Seibold, F. K., Sfondrini, A., & Yan, Z. (2024). Exact approaches on the string worldsheet. Journal of Physics A: Mathematical and Theoretical, 57(42), Article 423001. https://doi.org/10.1088/1751-8121/ad72be

We review different exact approaches to string theory. In the context of the Green–Schwarz superstring, we discuss the action in curved backgrounds and its supercoset formulation, with particular attention to superstring backgrounds of the AdS3 type... Read More about Exact approaches on the string worldsheet.

Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient (2024)
Presentation / Conference Contribution
Dinh, V., Ho, L., & Nguyen, C. (2024, December). Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient. Presented at The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada

The Entropic journey of Kac's Model (2024)
Presentation / Conference Contribution
Einav, A. (2022, June). The Entropic journey of Kac's Model. Presented at PSPDE X: Particle Systems and Partial Differential Equations X, Braga, Portugal

The goal of this paper is to review the advances that were made during the last few decades in the study of the entropy, and in particular the entropy method, for Kac’s many particle system.

A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions (2024)
Journal Article
Einbeck, J., Coolen-Maturi, T., Uwimpuhwe, G., & Singh, A. (online). A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions. The Journal of Experimental Education, https://doi.org/10.1080/00220973.2024.2405738

The effectiveness of educational interventions has traditionally been evaluated using effect size measures which focus on a single feature of the distribution of the outcomes under intervention and control conditions: a (standardized) mean difference... Read More about A Comparison of Threshold-Free Measures for Assessing the Effectiveness of Educational Interventions.

Cosmological correlators for Bogoliubov initial states (2024)
Journal Article
Chopping, A. J., Sleight, C., & Taronna, M. (2024). Cosmological correlators for Bogoliubov initial states. Journal of High Energy Physics, 2024, Article 152. https://doi.org/10.1007/jhep09%282024%29152

We consider late-time correlators in de Sitter (dS) space for initial states related to the Bunch-Davies vacuum by a Bogoliubov transformation. We propose to study such late-time correlators by reformulating them in the familiar language of Witten di... Read More about Cosmological correlators for Bogoliubov initial states.

Bayesian Emulation for Computer Models with Multiple Partial Discontinuities (2024)
Journal Article
Vernon, I., Owen, J., & Carter, J. (online). Bayesian Emulation for Computer Models with Multiple Partial Discontinuities. Bayesian Analysis, https://doi.org/10.1214/24-BA1456

Computer models are widely used across a range of scientific disciplines to describe various complex physical systems, however to perform full uncertainty quantification we often need to employ emulators. An emulator is a fast statistical construct t... Read More about Bayesian Emulation for Computer Models with Multiple Partial Discontinuities.