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Convolutional double copy in (anti) de Sitter space (2024)
Journal Article
Liang, Q., & Nagy, S. (2024). Convolutional double copy in (anti) de Sitter space. Journal of High Energy Physics, 2024(4), Article 139. https://doi.org/10.1007/jhep04%282024%29139

The double copy is a remarkable relationship between gauge theory and gravity that has been explored in a number of contexts, most notably scattering amplitudes and classical solutions. The convolutional double copy provides a straightforward method... Read More about Convolutional double copy in (anti) de Sitter space.

Gauge independent kinematic algebra of self-dual Yang-Mills theory (2023)
Journal Article
Bonezzi, R., Díaz-Jaramillo, F., & Nagy, S. (2023). Gauge independent kinematic algebra of self-dual Yang-Mills theory. Physical Review D, 108, Article 065007

The double-copy program relies crucially on the so-called color-kinematics duality which, in turn, is widely believed to descend from a kinematic algebra possessed by gauge theories. In this paper we construct the kinematic algebra of gauge-invariant... Read More about Gauge independent kinematic algebra of self-dual Yang-Mills theory.

Radiative phase space extensions at all orders in r for self-dual Yang-Mills and gravity (2023)
Journal Article
Nagy, S., & Peraza, J. (2023). Radiative phase space extensions at all orders in r for self-dual Yang-Mills and gravity. Journal of High Energy Physics, 2023(2), Article 202. https://doi.org/10.1007/jhep02%282023%29202

Working in the self-dual sector for Yang-Mills and gravity, we show how to construct an extended phase space at null infinity, to all orders in the radial expansion. This formalises the symmetry origin of the infrared behaviour of these theories to a... Read More about Radiative phase space extensions at all orders in r for self-dual Yang-Mills and gravity.

Penalized regression on principal manifolds with application to combustion modelling (2012)
Conference Proceeding
Einbeck, J., Isaac, B., Evers, L., & Parente, A. (2012). Penalized regression on principal manifolds with application to combustion modelling. In A. Komarek, & S. Nagy (Eds.), 27th International Workshop on Statistical Modelling, 16-20 July 2012, Prague, Czech Republic ; proceedings (117-122)

For multivariate regression problems featuring strong and non–linear dependency patterns between the involved predictors, it is attractive to reduce the dimension of the estimation problem by approximating the predictor space through a principal surf... Read More about Penalized regression on principal manifolds with application to combustion modelling.