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A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

169,341 papers · 148 categories

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2457 · Jul 202619922001200920182026
48 results for flux vacua

We present a comprehensive classification of supersymmetric vacua of M-theory compactification on seven-dimensional manifolds with general four-form fluxes. We analyze the cases where the resulting four-dimensional vacua have N = 1,2,3,4 supersymmetry and the internal space allows for SU(2), SU(3) or G_2 structures. In…

2005-12-05abs ↗pdf ↗

Paper shows how Non-Abelian T-duality solves pure spinor equations in supersymmetric vacua.

problem Preserving N=1{\cal{N}} = 1 supersymmetry in Type II supergravity requires specific pure spinor equations.
method Demonstrates that Non-Abelian T-duality (NATD) is a solution generating transformation for these pure spinor equations, showing covariance under Pin(d,d)Pin(d,d) transformations.
result Non-Abelian T-duality (NATD) generates a flux that matches the geometric flux associated with the isometry group.

In this paper we study several issues related to the generation of superpotential induced by background Ramond-Ramond fluxes in compactification of Type IIA string theory on Calabi-Yau four-folds. Identifying BPS solitons with D-branes wrapped over calibrated submanifolds in a Calabi-Yau space, we propose a general for…

1999-11-03abs ↗pdf ↗

Bayesian analysis uncovers flux couplings in metabolic networks.

problem Uncertainty and unrealistic assumptions in traditional flux analysis methods.
method Introduces Bayesian metabolic flux analysis to model reactions probabilistically and infer flux distributions.
result Reveals informative flux couplings and more unobserved fluxes in metabolic networks.

Study 3d N=1 vacua from M-theory compactification on Spin(7) space.

problem Quantum corrections in 3d N=1 vacua from M-theory compactification.
method Use Higgs bundles to analyze 3d N=1 vacua and track corrections.
result Topological anomalies are robust and calculable in 3d effective field theory.

J.H.C. Whitehead defined a map Jr:πr(SO)πrsJ_r:π_r(SO)\rightarrow π_r^s from the homotopy of the special orthogonal group to the stable homotopy of spheres. Within a toy model we show how the known computation for kernel(J)(J) leads to nonlinear σσ-models with spherical source (space) and spherical target which admit false vacua…

2011-10-19abs ↗pdf ↗

Study introduces a probabilistic framework for air-sea fluxes using neural networks.

problem Accurately quantifying air-sea fluxes for understanding interactions and improving weather/climate models.
method Gaussian distributions conditioned on input variables, artificial neural networks, eddy-covariance data, minimizing negative log-likelihood loss.
result Trained neural networks provide alternative mean flux estimates and quantify uncertainty.

In this paper we address several aspects of flat Bogomolnyi-Prasad-Sommerfeld (BPS) domain walls together with their Lorentz invariant vacua of 4d N=1 supergravity coupled to a chiral multiplet. The scalar field spans a one-parameter family of 2d Kähler manifolds satisfying a Kähler-Ricci flow equation. We find that BP…

2009-01-05abs ↗pdf ↗

Derives fluxes in M-theory compactifications and connects them to threebrane sigma-models.

problem Deriving fluxes in M-theory compactifications and understanding their geometric and topological properties.
method Systematic derivation of fluxes from higher Courant brackets and generalized geometry, relating them to threebrane sigma-models.
result Fluxes in M-theory compactifications are understood as generalized Wess-Zumino terms in threebrane sigma-models, linking higher structure to Lie algebroid homotopy.

We study the flux homomorphism for closed forms of arbitrary degree, with special emphasis on volume forms and on symplectic forms. The volume flux group is an invariant of the underlying manifold, whose non-vanishing implies that the manifold resembles one with a circle action with homologically essential orbits.

2005-03-12abs ↗pdf ↗

Novel gravity theory on Poisson manifolds with R-flux.

problem Developing a gravity theory on Poisson manifolds with R-flux.
method Constructing a gravity theory based on Poisson Generalized Geometry, coupling R-fluxes with the theory.
result The Einstein-Hilbert action coupled with an R-flux is invariant under β-diffeomorphisms and β-gauge transformations.

Study on Euler class and flux homomorphisms for non-orientable surfaces.

problem Investigate Euler class and flux homomorphisms for non-orientable surfaces.
method Analyze Euler class and flux homomorphisms for non-orientable compact surfaces with one boundary component.
result Prove the simplicity of the kernel of the flux homomorphisms, implying the non-existence of invariants analogous to the Calabi invariant.

FLUXtrapolation benchmarks machine learning for extrapolating ecosystem fluxes under distribution shifts.

problem Machine learning challenges in extrapolating ecosystem fluxes under distribution shifts.
method Defined temporal, spatial, and temperature-based extrapolation scenarios; evaluated performance across domains, temporal aggregations, and tail errors.
result Baselines perform similarly under median hourly RMSE but differ under tail-focused and multi-scale evaluations.

Combines machine learning and convex limiting for accurate subgrid flux modeling in shallow-water equations.

problem Accurate subgrid flux modeling in shallow-water equations.
method Machine learning and flux limiting for property-preserving subgrid scale modeling.
result The proposed method produces meaningful closures even in untrained scenarios.

We characterize N=1 vacua of type II theories in terms of generalized complex structure on the internal manifold M. The structure group of T(M) + T*(M) being SU(3) x SU(3) implies the existence of two pure spinors Phi_1 and Phi_2. The conditions for preserving N=1 supersymmetry turn out to be simple generalizations of …

2005-05-24abs ↗pdf ↗

Machine learning and deep learning infer surface/groundwater exchange from temperature data.

problem Inferring surface/groundwater exchange from temperature data with high temporal resolution.
method Application of machine learning and deep learning algorithms to infer surface/groundwater exchange flux from subsurface temperature observations.
result DL methods outperform ML methods in interpreting noisy temperature data, especially with a smoothing filter.

Study on flux homomorphism and its extension in symplectic group of a disk.

problem Understanding the flux homomorphism and its extension in symplectic group.
method Defined and analyzed the flux homomorphism and its extension, determined the Euler class, and investigated its relation to group 2-cocycle and Calabi invariant.
result Determined the Euler class of the flux extension and investigated its relation to group 2-cocycle and Calabi invariant.