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Setting Limits on Supersymmetry Using Simplified Models
Published on: November 15, 2013
Numerical renormalization group for bosonic systems and application to the sub-ohmic spin-boson model
Ralf Bulla1, Ning-Hua Tong, Matthias Vojta
1Theoretische Physik III, Elektronische Korrelationen und Magnetismus, Universität Augsburg, Augsburg, Germany.
Researchers generalized the numerical renormalization group method for quantum impurity models with bosonic baths. This approach reveals continuous quantum phase transitions in the spin-boson model for sub-Ohmic exponents.
Area of Science:
- Quantum Many-Body Physics
- Condensed Matter Theory
- Computational Physics
Background:
- Quantum impurity models are crucial for understanding complex quantum phenomena.
- Bosonic baths introduce unique challenges in theoretical modeling.
- Existing methods often struggle with nonperturbative regimes and low temperatures.
Purpose of the Study:
- To generalize Wilson's numerical renormalization group (NRG) method for quantum impurity models involving bosonic baths.
- To develop a general nonperturbative approach for studying bosonic impurity models.
- To investigate quantum phase transitions in the spin-boson model.
Main Methods:
- Generalization of Wilson's numerical renormalization group (NRG) method.
- Application to quantum impurity models with bosonic baths.
- Analysis of the spin-boson model with a power-law spectral density J(omega) proportional to omega(s).
Main Results:
- The developed NRG method provides access to exponentially small energies and temperatures.
- Clear evidence for a line of continuous quantum phase transitions was found for sub-Ohmic bath exponents (0
- This transition line terminates at the Kosterlitz-Thouless transition point (s=1).
Conclusions:
- The generalized NRG method offers a powerful nonperturbative tool for bosonic impurity models.
- The study elucidates the nature of quantum phase transitions in the spin-boson model.
- The findings establish a connection with perturbative renormalization group results and suggest broad applicability.
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