Examples of M5-Brane Elliptic Genera

We determine the modified elliptic genus of an M5-brane wrapped on various one modulus Calabi-Yau spaces, using modular invariance together with some known Gopakumar-Vafa invariants of small degrees. As a bonus, we find nontrivial relations among Gopakumar-Vafa invariants of different degrees and genera from modular invariance.Comment: 13 page

Intrinsic Universal Measurements of Non-linear Embeddings

A basic problem in machine learning is to find a mapping $f$ from a low dimensional latent space to a high dimensional observation space. Equipped with the representation power of non-linearity, a learner can easily find a mapping which perfectly fits all the observations. However such a mapping is often not considered as good as it is not simple enough and over-fits. How to define simplicity? This paper tries to make such a formal definition of the amount of information imposed by a non-linear mapping. This definition is based on information geometry and is independent of observations, nor specific parametrizations. We prove these basic properties and discuss relationships with parametric and non-parametric embeddings.Comment: work in progres

Geometric free energy of toric AdS4/CFT3 models

We study the supersymmetric free energy of three dimensional Chern-Simons-matter theories holographically dual to AdS$_4$ times toric Sasaki-Einstein seven-manifolds. In the large $N$ limit, we argue that the square of the free energy can be written as a quartic polynomial of trial R-charges. The coefficients of the polynomial are determined geometrically from the toric diagrams. We present the coefficients of the quartic polynomial explicitly for generic toric diagrams with up to 6 vertices, and some particular diagrams with 8 vertices. Decomposing the trial R-charges into mesonic and baryonic variables, and eliminating the baryonic ones, we show that the quartic polynomial reproduces the inverse of the Martelli-Sparks-Yau volume function. On the gravity side, we explore the possibility of using the same quartic polynomial as the prepotential in the AdS gauged supergravity. Comparing Kaluza-Klein gravity and gauged supergravity descriptions, we find perfect agreement in the mesonic sector but some discrepancy in the baryonic sector.Comment: 39 pages, 21 figures; v2. references added, minor improvement

Power Spectrum Analysis of the 2dF QSO Sample Revisited

We revisit the power spectrum analysis of the complete sample of the two degree field (2dF) QSO redshift (2QZ) survey, as a complementary test of the work by Outram et al. (2003). A power spectrum consistent with that of the 2QZ group is obtained. Differently from their approach, fitting of the power spectrum is investigated incorporating the nonlinear effects, the geometric distortion and the light-cone effect. It is shown that the QSO power spectrum is consistent with the $\Lambda$ cold dark matter (CDM) model with the matter density parameter $\Omega_m=0.2\sim0.5$. Our constraint on the density parameter is rather weaker than that of the 2QZ group. We also show that the constraint slightly depends on the equation of state parameter $w$ of the dark energy. The constraint on $w$ from the QSO power spectrum is demonstrated, though it is not very tight.Comment: 15 pages, 5 figures, accepted for publication in the Astrophysical Journa

Subsampling in Smoothed Range Spaces

We consider smoothed versions of geometric range spaces, so an element of the ground set (e.g. a point) can be contained in a range with a non-binary value in $[0,1]$. Similar notions have been considered for kernels; we extend them to more general types of ranges. We then consider approximations of these range spaces through $\varepsilon$-nets and $\varepsilon$-samples (aka $\varepsilon$-approximations). We characterize when size bounds for $\varepsilon$-samples on kernels can be extended to these more general smoothed range spaces. We also describe new generalizations for $\varepsilon$-nets to these range spaces and show when results from binary range spaces can carry over to these smoothed ones.Comment: This is the full version of the paper which appeared in ALT 2015. 16 pages, 3 figures. In Algorithmic Learning Theory, pp. 224-238. Springer International Publishing, 201