We introduce a field-theory framework in which fields transform under the little group, rather than the Lorentz group, specific to each particle type. By utilizing these fields, along with spinor products and the factor, we construct a field-theory action that naturally reproduces the vertices of the constructive standard model (CSM). This approach eliminates unphysical components, significantly reduces the degrees of freedom compared to traditional field theory, and offers deeper insights into the power of constructive amplitudes. Our action is momentum-conserving, Lorentz-invariant, Hermitian, and nonlocal. We also discuss this as a framework for developing new constructive field theories, discussing their essential properties and potential applicability in renormalization theory and nonperturbative calculations. Published by the American Physical Society2024
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Detecting and Attributing Change in Climate and Complex Systems: Foundations, Green’s Functions, and Nonlinear Fingerprints
Detection and attribution (DA) studies are cornerstones of climate science, providing crucial evidence for policy decisions. Their goal is to link observed climate change patterns to anthropogenic and natural drivers via the optimal fingerprinting method (OFM). We show that response theory for nonequilibrium systems offers the physical and dynamical basis for OFM, including the concept of causality used for attribution. Our framework clarifies the method’s assumptions, advantages, and potential weaknesses. We use our theory to perform DA for prototypical climate change experiments performed on an energy balance model and on a low-resolution coupled climate model. We also explain the underpinnings of degenerate fingerprinting, which offers early warning indicators for tipping points. Finally, we extend the OFM to the nonlinear response regime. Our analysis shows that OFM has broad applicability across diverse stochastic systems influenced by time-dependent forcings, with potential relevance to ecosystems, quantitative social sciences, and finance, among others. Published by the American Physical Society2024
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- Award ID(s):
- 2407484
- PAR ID:
- 10594770
- Publisher / Repository:
- American Physical Society
- Date Published:
- Journal Name:
- Physical Review Letters
- Volume:
- 133
- ISSN:
- 0031-9007
- Page Range / eLocation ID:
- 244201
- Subject(s) / Keyword(s):
- Linear Response Theory and Detection Attribution of Changes in Forced Complex Systems
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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