Results 41 to 50 of about 1,791 (221)
Renormalization Using Domain Wall Regularization [PDF]
We formulate the renormalization procedure using the domain wall regularization that is based on the heat-kernel method. The quantum effects of both fermions and bosons (gauge fields) are taken into account. The background field method is quite naturally introduced.
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Many numerical predictions of experimental phenomena in particle physics are made possible by exploiting the discovery that simplifications can happen when phenomena are investigated on short distance and time scales.
Collins, John C.
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At the three-loop level we analyze, how the NSVZ relation appears for N=1 SQED regularized by the dimensional reduction. This is done by the method analogous to the one which was earlier used for the theories regularized by higher derivatives. Within the
S.S. Aleshin +3 more
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Scalar-fermion fixed points in the ε expansion
The one-loop beta functions for systems of N s scalars and N f fermions interacting via a general potential are analysed as tensorial equations in 4 − ε dimensions.
William H. Pannell, Andreas Stergiou
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Reduction with degenerate Gram matrix for one-loop integrals
An improved PV-reduction (Passarino-Veltman) method for one-loop integrals with auxiliary vector R has been proposed in [1, 2]. It has also been shown that the new method is a self-completed method in [3].
Bo Feng +3 more
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Nontrivial one-loop recursive reduction relation
In [1], we proposed a universal method to reduce one-loop integrals with both tensor structure and higher-power propagators. But the method is quite redundant as it does not utilize the results of lower rank cases when addressing certain tensor integrals.
Tingfei Li
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Renormalization of the Regularized Relativistic Electron-Positron Field [PDF]
11 pages ...
Lieb, Elliott H., Siedentop, Heinz
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Exact Schwinger Proper Time Renormalisation
We derive an exact version of the Schwinger Proper Time Renormalisation Group flow equation from first principles from the complete path integral, without using any perturbative expansion.
Steven Abel, Lucien Heurtier
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Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
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We present the dimensional regularization approach to the renormalization group theory of the generalized sine-Gordon model. The generalized sine-Gordon model means the sine-Gordon model with high frequency cosine modes.
Takashi Yanagisawa
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