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Outputs (222)

Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks (2022)
Journal Article
Hoffmann, S., Aiassa, E., Angrish, M., Beausoleil, C., Bois, F., Ciccolallo, L., Craig, P., de Vries, R., Dorne, J., Druwe, I., Edwards, S., Eskes, C., Georgiadis, M., Hartung, T., Kienzler, A., Kristjansson, E., Lam, J., Martino, L., Meek, B., Morgan, R., …Tsaioun, K. (2022). Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks. ALTEX - Alternatives to Animal Experimentation, 39(3), 499-518. https://doi.org/10.14573/altex.2202141

The workshop titled “Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks” was co-organized by the Evidence-based Toxicology Collaboration and the European Food Safety Authority (EFSA) and hosted by EFSA... Read More about Application of evidence-based methods to construct mechanism-driven chemical assessment frameworks.

Ice Model Calibration using Semi-continuous Spatial Data (2022)
Journal Article
Chang, W., Konomi, B., Karagiannis, G., Guan, Y., & Haran, M. (2022). Ice Model Calibration using Semi-continuous Spatial Data. Annals of Applied Statistics, 16(3), 1937-1961. https://doi.org/10.1214/21-aoas1577

Rapid changes in Earth’s cryosphere caused by human activity can lead to significant environmental impacts. Computer models provide a useful tool for understanding the behavior and projecting the future of Arctic and Antarctic ice sheets. However, th... Read More about Ice Model Calibration using Semi-continuous Spatial Data.

Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis (2022)
Journal Article
Raices Cruz, I., Lindström, J., Troffaes, M. C., & Sahlin, U. (2022). Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis. Computational Statistics & Data Analysis, 176, Article 107558. https://doi.org/10.1016/j.csda.2022.107558

Bayesian inference under a set of priors, called robust Bayesian analysis, allows for estimation of parameters within a model and quantification of epistemic uncertainty in quantities of interest by bounded (or imprecise) probability. Iterative impor... Read More about Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis.

Numerical simulation of self-dual U(1) lattice field theory with electric and magnetic matter (2022)
Presentation / Conference Contribution
Anosova, M., Gattringer, C., Iqbal, N., & Sulejmanpasic, T. (2022, December). Numerical simulation of self-dual U(1) lattice field theory with electric and magnetic matter. Presented at Proceedings of The 38th International Symposium on Lattice Field Theory — PoS(LATTICE2021)

We study a recently proposed formulation of U(1) lattice field theory with electric and magnetic matter based on the Villain formulation. This discretization allows for a duality that gives rise to relations between weak and strong gauge coupling. Th... Read More about Numerical simulation of self-dual U(1) lattice field theory with electric and magnetic matter.

Spin systems with hyperbolic symmetry: a survey (2022)
Presentation / Conference Contribution
Bauerschmidt, R., & Helmuth, T. (2022, July). Spin systems with hyperbolic symmetry: a survey. Paper presented at International Congress of Mathematicians, 2022

Cosmological scattering equations at tree-level and one-loop (2022)
Journal Article
Gomez, H., Jusinskas, R. L., & Lipstein, A. (2022). Cosmological scattering equations at tree-level and one-loop. Journal of High Energy Physics, 2022(7), Article 4. https://doi.org/10.1007/jhep07%282022%29004

We recently proposed a formula for tree-level n-point correlators of massive phi^4 theory in de Sitter momentum space which consists of an integral over n punctures on the Riemann sphere and differential operators in the future boundary dubbed the co... Read More about Cosmological scattering equations at tree-level and one-loop.

A characterisation of the continuum Gaussian free field in arbitrary dimensions (2022)
Journal Article
Aru, J., & Powell, E. (2022). A characterisation of the continuum Gaussian free field in arbitrary dimensions. Journal de l’École polytechnique — Mathématiques, 9, 1101-1120. https://doi.org/10.5802/jep.201

e prove that under certain mild moment and continuity assumptions, the d-dimensional continuum Gaussian free field is the only stochastic process satisfying the usual domain Markov property and a scaling assumption. Our proof is based on a decomposit... Read More about A characterisation of the continuum Gaussian free field in arbitrary dimensions.

G-invariant spin structures on spheres (2022)
Journal Article
Daura Serrano, J., Kohn, M., & Lawn, M.-A. (2022). G-invariant spin structures on spheres. Annals of Global Analysis and Geometry, 62(2), 437-455. https://doi.org/10.1007/s10455-022-09855-z

We examine which of the compact connected Lie groups that act transitively on spheres of different dimensions leave the unique spin structure of the sphere invariant. We study the notion of invariance of a spin structure and prove this classification... Read More about G-invariant spin structures on spheres.

On the critical-subcritical moments of moments of random characteristic polynomials: a GMC perspective (2022)
Journal Article
Keating, J. P., & Wong, M. D. (2022). On the critical-subcritical moments of moments of random characteristic polynomials: a GMC perspective. Communications in Mathematical Physics, 394(3), 1247-1301. https://doi.org/10.1007/s00220-022-04429-3

We study the ‘critical moments’ of subcritical Gaussian multiplicative chaos (GMCs) in dimensions d≤2. In particular, we establish a fully explicit formula for the leading order asymptotics, which is closely related to large deviation results for GMC... Read More about On the critical-subcritical moments of moments of random characteristic polynomials: a GMC perspective.