Diagrammatic approach to non-Gaussianity from inflation

Byrnes C, Koyama K, Sasaki M, Wands D (2007)
JCAP 2007(11): 027.

Download
Es wurde kein Volltext hochgeladen. Nur Publikationsnachweis!
Zeitschriftenaufsatz | Veröffentlicht | Englisch
Autor
; ; ;
Abstract / Bemerkung
We present Feynman type diagrams for calculating the n-point function of theprimordial curvature perturbation in terms of scalar field perturbations duringinflation. The diagrams can be used to evaluate the corresponding terms in then-point function at tree level or any required loop level. Rules are presentedfor drawing the diagrams and writing down the corresponding terms in real spaceand Fourier space. We show that vertices can be renormalised to automaticallyaccount for diagrams with dressed vertices. We apply these rules to calculatethe primordial power spectrum up to two loops, the bispectrum including loopcorrections, and the trispectrum.
Erscheinungsjahr
Zeitschriftentitel
JCAP
Band
2007
Zeitschriftennummer
11
Seite
027
ISSN
PUB-ID

Zitieren

Byrnes C, Koyama K, Sasaki M, Wands D. Diagrammatic approach to non-Gaussianity from inflation. JCAP. 2007;2007(11):027.
Byrnes, C., Koyama, K., Sasaki, M., & Wands, D. (2007). Diagrammatic approach to non-Gaussianity from inflation. JCAP, 2007(11), 027. doi:10.1088/1475-7516/2007/11/027
Byrnes, C., Koyama, K., Sasaki, M., and Wands, D. (2007). Diagrammatic approach to non-Gaussianity from inflation. JCAP 2007, 027.
Byrnes, C., et al., 2007. Diagrammatic approach to non-Gaussianity from inflation. JCAP, 2007(11), p 027.
C. Byrnes, et al., “Diagrammatic approach to non-Gaussianity from inflation”, JCAP, vol. 2007, 2007, pp. 027.
Byrnes, C., Koyama, K., Sasaki, M., Wands, D.: Diagrammatic approach to non-Gaussianity from inflation. JCAP. 2007, 027 (2007).
Byrnes, Christian, Koyama, Kazuya, Sasaki, Misao, and Wands, David. “Diagrammatic approach to non-Gaussianity from inflation”. JCAP 2007.11 (2007): 027.

Export

Markieren/ Markierung löschen
Markierte Publikationen

Open Data PUB

Web of Science

Dieser Datensatz im Web of Science®

Quellen

arXiv: 0705.4096

Inspire: 751631

Suchen in

Google Scholar