scholarly journals Spin precession and real-time dynamics in the Kondo model: Time-dependent numerical renormalization-group study

2006 ◽  
Vol 74 (24) ◽  
Author(s):  
Frithjof B. Anders ◽  
Avraham Schiller
Keyword(s):  
Renormalization Group ◽  
Real Time ◽  
Spin Precession ◽  
Time Dependent ◽  
Numerical Renormalization Group ◽  
Kondo Model ◽  
Time Dynamics

scholarly journals REAL-TIME NONEQUILIBRIUM DYNAMICS IN HOT QED PLASMAS

2001 ◽  
Vol 16 (supp01c) ◽  
pp. 1281-1283
Author(s):  
SHANG-YUNG WANG
Keyword(s):  
Renormalization Group ◽  
Real Time ◽  
Time Dependent ◽  
Nonequilibrium Dynamics ◽  
Group Method ◽  
Renormalization Group Method ◽  
Photon Distribution ◽  
Relaxation Time Approximation ◽  
Kinetics Of ◽  
Shell Energy

The quantum kinetics of photons in hot QED plasmas is studied directly in real time by implementing the dynamical renormalization group. In contrast to conventional approach, the dynamical renormalization group method consistently includes off-shell (energy non-conserving) effects and accounts for time-dependent collisional kernel. To lowest order we find that in the relaxation time approximation the semihard photon distribution function relaxes with a power law.

scholarly journals Estimation of Time-Dependent Reproduction Number for Global COVID-19 Outbreak

2020 ◽  
Author(s):  
Tatiana Petrova ◽  
Dmitry Soshnikov ◽  
Andrey Grunin
Keyword(s):  
Real Time ◽  
Disease Transmission ◽  
Reproduction Number ◽  
Time Window ◽  
Time Estimation ◽  
Time Dependent ◽  
Single Infection ◽  
Observation Data ◽  
Sir Epidemic Model ◽  
Time Dynamics

Real-time estimation of the parameters characterising infectious disease transmission is important for optimization quarantine interventions during outbreaks. One of the most significant parameters is the effective reproduction number - number of secondary cases produced by a single infection. The current study presents an approach for estimating the effective reproduction number and its application to COVID-19 outbreak. The method is based on fitting SIR epidemic model to observation data in a sliding time window and allows to show real-time dynamics of reproduction number at any phase of epidemic for countries globally. Online data on COVID-19 daily cases of infections, recoveries, deaths are used.Finally, time-dependent reproduction number is explored in connection with dynamics of peoples mobility. The method allows to assess the disease transmission potential and understand the effect of interventions on epidemics spread. It also can be easily adapted to future outbreaks of different pathogens. The tool is available online as Python code from the Github repository.

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