Some Properties of the Calogero-Sutherland Model with Reflections

We prove that the Calogero-Sutherland Model with reflections (the BC_N model) possesses a property of duality relating the eigenfunctions of two Hamiltonians with different coupling constants. We obtain a generating function for their polynomial eigenfunctions, the generalized Jacobi polynomials. The symmetry of the wave-functions for certain particular cases (associated to the root systems of the classical Lie groups B_N, C_N and D_N) is also discussed.Comment: 16 pages, harvmac.te

Explicit formulas for the generalized Hermite polynomials in superspace

We provide explicit formulas for the orthogonal eigenfunctions of the supersymmetric extension of the rational Calogero-Moser-Sutherland model with harmonic confinement, i.e., the generalized Hermite (or Hi-Jack) polynomials in superspace. The construction relies on the triangular action of the Hamiltonian on the supermonomial basis. This translates into determinantal expressions for the Hamiltonian's eigenfunctions.Comment: 19 pages. This is a recasting of the second part of the first version of hep-th/0305038 which has been splitted in two articles. In this revised version, the introduction has been rewritten and a new appendix has been added. To appear in JP

BULLDOZER, A FREE OPEN SOURCE SCALABLE SOFTWARE FOR DTM EXTRACTION

The paper introduces a software called Bulldozer, designed to extract a Digital Terrain Model (DTM) from a Digital Surface Model (DSM) obtained from various sensors. The software is based on a modified version of the multi-scale Drap Cloth principle to process noisy DSMs of any size, employing a tiling strategy and a stability margin to ensure consistent results. A parameter called max object size is introduced to differentiate objects from the ground during the drap cloth process. Gravity steps and ground distance sampling resolution are adjusted based on the input DSM. No-data and noisy values present in the DSM are detected and converted into no-data values to improve the quality of the Cloth simulation. The paper describes a memory-aware parallel execution strategy using both the multiprocessing and the shared memory Python modules. A benchmark dataset has been created to analyze the results and compare them with alternative approaches and reference datasets. Bulldozer offers an extensive Python API. It is open-source and available on PyPi and GitHub. Additionally, a QGIS plugin has been developed

Intersecting where? The multi-scalar contextual embeddedness of intersectional entrepreneurs

We explore the experiences of LGBT* ethnic minority entrepreneurs, their changing locations and their entrepreneurial activities. Using a unique mixed-method approach which collected empirical data from Germany and the Netherlands, the paper combines an ethnographic fieldwork of intersectional entrepreneurs, community activists and policy-makers with an original survey with LGBT* customers. Our findings contribute to understanding of intersectionality by revealing the role played by the contextualized embeddedness of intersectional entrepreneurs at the different geographic scales of supranational, national, regional and inter and intra-urban. While such embeddedness frames the challenges they face, it also provides opportunities for intersectional entrepreneurs. Using a multi-scalar perspective, this paper delivers a spatially contextual perspective of entrepreneurial diversity and provides a framework to analyse the complex issues and contexts with which intersectional entrepreneurs are both confronted and embedded within. This paper contributes to refining the spatial context of entrepreneurship which has gained attention in recent studies of entrepreneurship and regional development. The paper responds to a call for gender entrepreneurship scholars to contribute to understanding of intersectional entrepreneurship. Finally, this study goes beyond the binary view of female migrant entrepreneurship by adopting a more gender diverse lens which considers the experiences of LGBT* entrepreneurs from ethnic minorities