Why is the Integral of Dimensional Regularization Equal to 0?

In summary, the property of dimensional regularization states that for any value of ##\alpha##, the integral of ##\int d^dp \, (p^2)^\alpha## is equal to 0. This is achieved by defining integrals in a space-time dimension that exists and then using analytic continuation to evaluate integrals that are not defined. The usual regularization parameter is ##2 \epsilon = d-4## and Feynman diagrams are evaluated in a Laurent expansion in ##\epsilon##. This technique is used to renormalize 1PI truncated diagrams in perturbation theory. Collins' renormalization book is often cited as a source for the proof of this property.
  • #1
Luca_Mantani
36
1
Hi everyone,
I read this property of dimensional regularization, but i do not understand why it is so.

$$\int d^dp =0$$.

Actually looking for an answer i also saw that a general property of dim. reg. is

$$\int d^dp \, (p^2)^\alpha=0$$

for any value of ##\alpha##, so also for ##\alpha=0##. Do you have an explanation for this?
Thanks in advance.
 
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  • #2
Where is this from? It depends on how you define these integrals. Standing alone these integrals do not make sense since you can define only integrals which exist for some space-time dimensions and then use analytic continuation in ##d## to evaluate formally integrals that are not defined. The usual regularization parameter is ##2 \epsilon=d-4##, and Feynman diagrams are evaluated in form of a Laurent expansion in ##\epsilon## the poles in ##\epsilon##, which diverge for ##\epsilon \rightarrow 0## define the subtractions ("counter terms") to renormalize (order by order in perturbation theory) the proper vertex functions (aka 1PI truncated diagrams). For an introduction to the technique, see my QFT script:

http://th.physik.uni-frankfurt.de/~hees/publ/lect.pdf
 
  • #3
I read them in an Eft course, in the video the professor was citing the Collins renormalization book for the proof, but I do not have this book at my disposal now.
 

What is dimensional regularization?

Dimensional regularization is a mathematical technique used in theoretical physics to handle divergent integrals that arise in calculations involving quantum field theory. It involves analytically continuing the number of dimensions in spacetime from the usual four to a complex number, allowing for the cancellation of divergences.

Why is dimensional regularization used?

Dimensional regularization is used because it provides a systematic and consistent way to deal with divergences in quantum field theory calculations, which are essential for making predictions about the behavior of particles and forces at the subatomic level. It also preserves important symmetries and allows for the calculation of physical quantities that would be impossible to obtain using other methods.

How does dimensional regularization work?

Dimensional regularization works by treating dimensions as continuous variables rather than discrete integers. By performing calculations in a higher-dimensional space, the divergences can be regulated and then analytically continued back to the physical dimension of four, resulting in finite and well-defined results.

What are the limitations of dimensional regularization?

Although dimensional regularization is a powerful and widely used technique, it is not a universal solution for dealing with divergences in all quantum field theory calculations. It is most effective for calculations involving massless particles and can struggle with certain types of Feynman diagrams. In addition, the analytic continuation process can sometimes lead to non-physical results.

Are there any alternatives to dimensional regularization?

Yes, there are alternative regularization techniques such as cutoff regularization, which involves imposing a maximum value on the momentum of particles, and lattice regularization, which discretizes spacetime. However, each of these methods has its own limitations and drawbacks, and dimensional regularization remains a popular and useful approach in many areas of theoretical physics.

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