What Is the Renormalized Gluon Dressing Function?

In summary, the renormalized gluon dressing function is defined as the inverse of the renormalized gluon propagator and can be written in terms of the transverse and longitudinal tensors and the gauge parameter. The bare version of the function can be expressed in terms of the renormalization constant for the gluon field.
  • #1
RicardoMP
49
2
Consider, for example, the gluon propagator $$D^{\mu\nu}(q)=-\frac{i}{q^2+i\epsilon}[D(q^2)T^{\mu\nu}_q+\xi L^{\mu\nu}_q]$$

What exactly is the renormalized gluon dressing function ##D(q^2)## and what is its definition? My interest is in knowing if I can then write the bare version of this function simply as ##D_B(q^2)=Z_AD(q^2)##, where ##Z_A## is the renormalization constant for the gluon field (##A_B=Z_A^{\frac{1}{2}}A##).
 
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  • #2
The renormalized gluon dressing function ##D(q^2)## is defined as the inverse of the renormalized gluon propagator, which can be written as: $$D^{\mu\nu}(q)=-i[D(q^2)T^{\mu\nu}_q+\xi L^{\mu\nu}_q]$$where ##T^{\mu\nu}_q## and ##L^{\mu\nu}_q## are the transverse and longitudinal tensors, respectively, and ##\xi## is the gauge parameter. The renormalized gluon dressing function is then defined as$$D(q^2)=\frac{1}{-i(T^{\mu\nu}_q+\xi L^{\mu\nu}_q)D^{\mu\nu}(q)}$$Yes, you can write the bare version of the function as ##D_B(q^2)=Z_AD(q^2)##, where ##Z_A## is the renormalization constant for the gluon field (##A_B=Z_A^{\frac{1}{2}}A##).
 

Related to What Is the Renormalized Gluon Dressing Function?

1. What is a dressing function?

A dressing function is a mathematical concept used in statistics and probability theory. It is a function that assigns a probability to each possible outcome of a random variable, representing the likelihood of that outcome occurring.

2. How is a dressing function different from a probability distribution?

A dressing function is a specific type of probability distribution that is used to model the probability of a random variable. It differs from other probability distributions in that it is a continuous function, meaning that it can take on any value within a given range.

3. What is the purpose of a dressing function?

The main purpose of a dressing function is to provide a mathematical model for the probability of a random variable. This allows scientists and statisticians to make predictions and draw conclusions about the likelihood of certain events occurring.

4. How is a dressing function used in real-world applications?

Dressing functions are used in a variety of fields, including finance, engineering, and biology. They are commonly used in risk analysis, decision making, and data analysis to model uncertain events and make informed decisions.

5. What are some common types of dressing functions?

There are several types of dressing functions, including the normal distribution, the uniform distribution, and the exponential distribution. Each type has its own characteristics and is used for different purposes depending on the specific situation.

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