Tootfinder

A Gross-Pitaevskii theory for an excitonic incompressible Bose solid
Sara Conti, Andrey Chaves, Alexander R. Hamilton, Jacques Tempere, Milorad V. Milosevic, David Neilson
https://arxiv.org/abs/2507.20236

A Gross-Pitaevskii theory for an excitonic incompressible Bose solid
We show that interlayer excitons in double-layer semiconductor heterostructures can form a Bose solid, which is an incompressible supersolid characterized by exactly one boson per lattice site. This exciton Bose solid would be the first realization of an incompressible supersolid, unlike the generally compressible cluster supersolids seen in dipolar quantum gases. Capturing its characteristics and associated emergent phenomena requires extending the Gross-Pitaevskii formalism to include strong …

Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
Jacek Karwowski, Frank Nielsen
https://arxiv.org/abs/2508.14369

Hilbert geometry of the symmetric positive-definite bicone: Application to the geometry of the extended Gaussian family
The extended Gaussian family is the closure of the Gaussian family obtained by completing the Gaussian family with the counterpart elements induced by degenerate covariance or degenerate precision matrices, or a mix of both degeneracies. The parameter space of the extended Gaussian family forms a symmetric positive semi-definite matrix bicone, i.e. two partial symmetric positive semi-definite matrix cones joined at their bases. In this paper, we study the Hilbert geometry of such an open bounde…

Forecasting Labor Markets with LSTNet: A Multi-Scale Deep Learning Approach
Adam Nelson-Archer, Aleia Sen, Meena Al Hasani, Sofia Davila, Jessica Le, Omar Abbouchi
https://arxiv.org/abs/2507.01979

Forecasting Labor Markets with LSTNet: A Multi-Scale Deep Learning Approach
We present a deep learning approach for forecasting short-term employment changes and assessing long-term industry health using labor market data from the U.S. Bureau of Labor Statistics. Our system leverages a Long- and Short-Term Time-series Network (LSTNet) to process multivariate time series data, including employment levels, wages, turnover rates, and job openings. The model outputs both 7-day employment forecasts and an interpretable Industry Employment Health Index (IEHI). Our approach o…