Wilsonian matching and power counting
Integrate out a Gaussian heavy scalar, determine the effective interaction's sign, and measure the accuracy of its derivative expansion.
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The question for today
What you’ll understand
- Eliminate a heavy field by completing a Euclidean square and identify its nonlocal kernel.
- Expand that kernel in external momentum and check operator dimensions.
- Keep derivative truncation, loop corrections, and infrared matching distinct in an error budget.
A low-energy theory earns predictive power by reproducing specified measurements. Matching determines coefficients by comparing a more resolved description with its effective replacement. We will use a Gaussian heavy scalar, where completing a square exposes both the sign and the derivative expansion before any loop calculation is needed.
Integrate out a field with the sign visible
Work in four-dimensional Euclidean spacetime with a real light field , a heavy field , and interaction . Both fields have mass dimension one, so has dimension one. The heavy quadratic operator is , whose momentum eigenvalue is positive . Complete the square in with source . Gaussian integration produces a light-field term with a minus sign, because the completed square subtracts half of .
The determinant is independent of in this deliberately simple Gaussian model and only changes the vacuum normalization. Extra interactions involving would make further terms possible. The negative quartic contribution here does not assert that an isolated light potential is globally stable: the full model must contain appropriate stabilizing interactions and be used around its stated vacuum. Euclidean action coefficients also should not be copied into Minkowski scattering rules without translating conventions.
A local series needs a small kinematic ratio
In a channel with Euclidean transfer , expand the positive kernel as a geometric series. This isolates a dimensionless coefficient followed by corrections in . In position space the first term multiplies , a dimension-four operator. The next can be written using derivatives on and has dimension six, so its coefficient has mass dimension minus two. Integration by parts can change its appearance but cannot change a matched observable.
Every relevant external invariant must be small compared with the heavy scale. Low total energy alone is insufficient if a different channel carries a large transfer or if another nearby threshold was omitted. A geometric expansion at small spacelike momentum has an explicitly calculable remainder in this example. More general effective theories estimate the next allowed order using power counting, symmetries, and coefficient sizes. An unexpectedly enhanced coefficient is information to investigate, rather than permission to claim a universal tiny error.
Matching is not the same operation as running
Matching fixes coefficients at a chosen scale by equating the same low-energy quantities in two descriptions. Renormalization-group running then transports those coefficients between scales within the effective theory. When light loops occur on both sides, common infrared contributions must cancel in the matching difference; otherwise long-distance physics would be incorrectly counted as a new short-distance coefficient. Operators related by field redefinitions can trade coefficients, so the chosen basis and renormalization prescription belong in a reproducible result.
Our Gaussian elimination is exact for the heavy field in the stated action, but evaluating the remaining light-field theory at tree level is an additional approximation. Report separately which derivative terms are retained, which loop orders are evaluated, and how measured inputs were fixed. This bookkeeping makes the effective theory useful for precision work: increasing one order has a stated purpose and test. It also exposes the boundary where a heavy degree of freedom must be restored rather than approximated by more local terms.
Work it through
Compare two local approximations with the exact kernel
Use M = 10, g = 2, and Euclidean Q = 1 in consistent mass units. Compare the constant and two-term approximations to K.
The exact positive kernel is 4/(100 + 1) = 4/101, approximately 0.03960396. This is a kernel value, not the signed quartic coefficient of the action.
The constant approximation is 4/100 = 0.04. Its difference from the exact value divided by the exact value is 0.01, or 1%.
Retain the first derivative correction: 0.04 times (1 − 0.01) = 0.0396. The relative error is 0.0001, or 0.01%, as predicted by the next power of the small ratio.
A channel ratio of Q squared/M squared = 0.01 controls the local expansion here. The known remainder checks the power counting, while the Euclidean action still carries its derived negative coefficient.
The living notebook
Explore the model
Interactive lab · spectral
Compare resolved detail with a truncated representation
Increase or decrease N in the finite sine sum Σ sin(nx−t)/nᵖ while holding p fixed. It provides an inspectable example of retaining a limited set of spatial scales. Removing Fourier terms is not the same calculation as integrating out H, and this lab neither matches Wilson coefficients nor estimates an effective-theory loop error.
- Sum at x = π/2
- 0.867
- Smallest wavelength
- 2π / 5
- Highest-mode coefficient
- 0.2
A finite sum of sin(nx − t)/nᵖ. Playback changes t; increasing the cutoff includes finer spatial scales. This is not a proof about a continuum limit or renormalization. Parameter changes pause playback and recompute the model at the current elapsed time. Reset restores both parameters and returns time to zero. Playback starts paused. Adjust either parameter, then choose Play or Step.
Look forA truncated representation needs a stated domain. Effective matching additionally determines the interactions that replace the omitted degrees of freedom.
Pause & reason
Check your understanding
Your turn
Try it yourself
Keep M = 10 and g = 2 but raise Q to 5. Compute the constant and two-term kernels and compare their relative errors with the exact value.
Take a moment to make a prediction or work it out on paper. Open a hint when you need one.
Give me a hint
The expansion parameter is now 25/100. Evaluate the denominator before computing percentage differences.
Compare with the solution
The exact kernel is 4/125 = 0.032. The constant approximation 0.04 is 25% too large. The two-term value is 0.04 times 0.75 = 0.03, which is 6.25% too small. The errors follow the first and second powers of 0.25 in this geometric example; they do not justify using the same local expansion through a heavy-particle threshold.
Keep the idea
Take it with you
- Completing the heavy-field square fixes a sign that guessing local operators cannot determine.
- Power counting requires operator dimensions, coefficient sizes, and all relevant small kinematic ratios.
- Matching, running, derivative truncation, and loop truncation solve distinct parts of the prediction problem.
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