اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدStatistical Distribution of the Vacuum Energy Density in Racetrack Kahler Uplift Models in String Theory
158
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
We study a racetrack model in the presence of the leading alpha-correction in flux compactification in Type IIB string theory, for the purpose of getting conceivable de-Sitter vacua in the large compactified volume approximation. Unlike the Kahler Uplift model studied previously, the alpha-correction is more controllable for the meta-stable de-Sitter vacua in the racetrack case since the constraint on the compactified volume size is very much relaxed. We find that the vacuum energy density Lambda for de-Sitter vacua approaches zero exponentially as the volume grows. We also analyze properties of the probability distribution of Lambda in this class of models. As in other cases studied earlier, the probability distribution again peaks sharply at Lambda=0. We also study the Racetrack Kahler Uplift model in the Swiss-Cheese type model.
قيم البحث
اقرأ أيضاً
As the vacuum state of a quantum field is not an eigenstate of the Hamiltonian density, the vacuum energy density can be represented as a random variable. We present an analytical calculation of the probability distribution of the vacuum energy densi
ty for real and complex massless scalar fields in Minkowski space. The obtained probability distributions are broad and the vacuum expectation value of the Hamiltonian density is not fully representative of the vacuum energy density.
We perform an extensive analysis of the statistics of axion masses and interactions in compactifications of type IIB string theory, and we show that black hole superradiance excludes some regions of Calabi-Yau moduli space. Regardless of the cosmolog
ical model, a theory with an axion whose mass falls in a superradiant band can be probed by the measured properties of astrophysical black holes, unless the axion self-interaction is large enough to disrupt formation of a condensate. We study a large ensemble of compactifications on Calabi-Yau hypersurfaces, with $1 leq h^{1,1} leq 491$ closed string axions, and determine whether the superradiance conditions on the masses and self-interactions are fulfilled. The axion mass spectrum is largely determined by the Kahler parameters, for mild assumptions about the contributing instantons, and takes a nearly-universal form when $h^{1,1} gg 1$. When the Kahler moduli are taken at the tip of the stretched Kahler cone, the fraction of geometries excluded initially grows with $h^{1,1}$, to a maximum of $approx 0.5$ at $h^{1,1} approx 160$, and then falls for larger $h^{1,1}$. Further inside the Kahler cone, the superradiance constraints are far weaker, but for $h^{1,1} gg 100$ the decay constants are so small that these geometries may be in tension with astrophysical bounds, depending on the realization of the Standard Model.
It was shown in arXiv:1808.09428 that the modified 4d version of the KKLT model proposed in arXiv:1707.08678 is inconsistent for large values of the parameter $c$ advocated in arXiv:1707.08678, since there is a point in the moduli space where $|D_SW|
^2$ vanishes. The authors responded with yet another modification of the 4d KKLT model arXiv:1809.06618. However, for large $c$, this model suffers from an even worse problem: not only is there a point in the moduli space where $|D_SW|^2$ vanishes, there is also a region in the moduli space where $|D_SW|^2$ is negative. Meanwhile for small $c$ these models have dS vacua. We construct improved models, which are fully consistent for all values of parameters, just as the original version of the KKLT model using a nilpotent superfield. These models have a family of dS vacua for a broad range of parameter values. Thus, the results of the analysis of all presently available consistent generalizations of the 4d KKLT model, in the domain of their validity, confirm the existence of dS vacua in the KKLT scenario.
Generative models in deep learning allow for sampling probability distributions that approximate data distributions. We propose using generative models for making approximate statistical predictions in the string theory landscape. For vacua admitting
a Lagrangian description this can be thought of as learning random tensor approximations of couplings. As a concrete proof-of-principle, we demonstrate in a large ensemble of Calabi-Yau manifolds that Kahler metrics evaluated at points in Kahler moduli space are well-approximated by ensembles of matrices produced by a deep convolutional Wasserstein GAN. Accurate approximations of the Kahler metric eigenspectra are achieved with far fewer than $h^{11}$ Gaussian draws. Accurate extrapolation to values of $h^{11}$ outside the training set are achieved via a conditional GAN. Together, these results implicitly suggest the existence of strong correlations in the data, as might be expected if Reids fantasy is correct.
We construct a model of quintessence in string theory based on the idea of axion monodromy as discussed by McAllister, Silverstein and Westphal arXiv:0808.0706. In the model, the quintessence field is an axion whose shift symmetry is broken by the pr
esence of 5-branes which are placed in highly warped throats. This gives rise to a potential for the axion field which is slowly varying, even after incorporating the effects of moduli stabilization and supersymmetry breaking. We find that the resulting time dependence in the equation of state of Dark Energy is potentially detectable, depending on the initial conditions. The model has many very light extra particles which live in the highly warped throats, but these are hard to detect. A signal in the rotation of the CMB polarization can also possibly arise.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
