Geometric Dynamics of Consumer Credit Cycles: A Multivector-based Linear-Attention Framework for Explanatory Economic Analysis
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Abstract (arXiv)
This study introduces geometric algebra to decompose credit system relationships into their projective (correlation-like) and rotational (feedback-spiral) components. We represent economic states as multi-vectors in Clifford algebra, where bivector elements capture the rotational coupling between unemployment, consumption, savings, and credit utilization. This mathematical framework reveals interaction patterns invisible to conventional analysis: when unemployment and credit contraction enter simultaneous feedback loops, their geometric relationship shifts from simple correlation to dangerous rotational dynamics that characterize systemic crises.
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References · 6
- 2017Attention Is All You Needcited by 60,361
- 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,548
- 2020Transformers are RNNs: Fast Autoregressive Transformers with Linear Attentioncited by 2,022
- 2020Rethinking Attention with Performerscited by 1,601
- 2016Geometric deep learning: going beyond Euclidean datacited by 1,048
- 2023Geometric Clifford Algebra Networkscited by 38
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