Supersymmetric localization: ${\cal N}=(2,2)$ theories on S$^2$ and AdS$_2$

التفاصيل البيبلوغرافية
العنوان: Supersymmetric localization: ${\cal N}=(2,2)$ theories on S$^2$ and AdS$_2$
المؤلفون: Lezcano, Alfredo González, Jeon, Imtak, Ray, Augniva
سنة النشر: 2023
المجموعة: High Energy Physics - Theory
مصطلحات موضوعية: High Energy Physics - Theory
الوصف: Application of the supersymmetric localization method to theories on anti-de Sitter spacetime has received recent interest, yet still remains as a challenging problem. In this paper, we focus on (global) Euclidean AdS$_2$, on which we consider an Abelian ${\cal N}=(2,2)$ theory and implement localization computation to obtain the exact partition function. For comparison, we also revisit the theory on S$^2$ and perform a parallel computation. We refine the notion of equivariant supersymmetry and use appropriate functional integration measure. For AdS$_2$ we choose a supersymmetric boundary condition which is compatible with the principle of variation. To evaluate the 1-loop determinant about the localization saddle, we use index theory and fixed point formula, where we pay attention to the effect of zero modes and their superpartners. The existence of fermionic superpartner of 1-form boundary zero modes is proven. Obtaining the 1-loop determinant requires expansion of the index that presents an ambiguity, which we resolve using boundary condition. The resulting partition function reveals an overall dependence on the size of the background manifold, AdS$_2$ as well as S$^2$, as a sum of two types of contributions: a local one from local conformal anomaly through the index computation and a global one coming from zero modes. This overall size dependence is confirmed by the perturbative 1-loop evaluation using heat kernel method.
Comment: 63 pages + appendices, v2: references added, v3: typos corrected, matches with published version
نوع الوثيقة: Working Paper
DOI: 10.1007/JHEP07(2023)056
URL الوصول: http://arxiv.org/abs/2302.10370
رقم الأكسشن: edsarx.2302.10370
قاعدة البيانات: arXiv