ArXiv TLDR

An efficient Wavelet-Based Hamiltonian Formulation of Quantum Field Theories using Flow-Equations

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2604.14594

Mrinmoy Basak, Debsubhra Chakraborty, Nilmani Mathur

hep-lathep-phhep-th

TLDR

An efficient wavelet-based Hamiltonian formulation for quantum field theories uses flow-equations to reduce dimensionality and computational cost.

Key contributions

  • Proposes a wavelet-based Hamiltonian formulation for quantum field theories.
  • Combines with flow-equation methods (SRG) to decouple degrees of freedom across scales.
  • Reduces Hamiltonian dimensionality and computational cost for energy spectra calculations.
  • Successfully applied to calculate the low-energy spectrum of free scalar field theory.

Why it matters

This work offers a novel approach to simplify complex quantum field theory calculations. By efficiently decoupling resolution modes, it significantly reduces the computational burden, making QFT analysis more accessible and potentially advancing our understanding of fundamental particle interactions.

Original Abstract

We propose an effective Hamiltonian formulation of quantum field theories using a Daubechies wavelet basis in position space. Combined with flow-equation methods of the similarity renormalization group (SRG), this approach provides an efficient framework for analyzing quantum field theories by reducing the dimensionality of the Hamiltonian and systematically decoupling degrees of freedom across scales. As an application, the free scalar field theory has been reformulated within this framework to calculate the low-lying energy spectrum of the theory. These basis elements are known to transform the free scalar field theory into a theory of coupled localized oscillators, each of which is labeled by a location and a resolution index. In this representation, the Hamiltonian is naturally organized into fixed-resolution blocks, alongside blocks associated with the interactions between different resolutions. To decouple the different resolution modes and obtain a block diagonalized Hamiltonian with each block associated with a fixed resolution, the flow equation approach of SRG is applied. Finally, we demonstrate that with increasing resolution, the low-energy spectrum can be extracted from the effective lowest-resolution block of the Hamiltonian, leading to a significant reduction in computational cost.

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