research27 min studyLesson 768 in Physics

Fit a spectrum without mistaking a plateau for proof

Track source overlaps, temporal images, correlations, and excited states.

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What you’ll understand

  • Derive a spectral correlator and its effective mass.
  • Identify finite-time excited contamination and backward propagation.
  • Explain correlated-fit and uncertainty requirements.

A hadron correlator averages a product of composite quark and gluon operators with chosen quantum numbers. Its Euclidean decay contains the energies of states those operators can create. Extracting one mass requires separating that spectrum from finite-time contamination, temporal boundary effects, and noise. An effective-mass plot is a diagnostic, not an automatic estimator with a guaranteed plateau. Source and sink choices change overlaps, while a correct continuum energy requires additional lattice-spacing, mass-tuning, and volume analysis.

Project momentum and state the spectral sector

Construct an interpolating operator with the hadron’s desired quantum numbers and usually sum its sink over spatial sites to project zero momentum. In a positive transfer setting the vacuum-subtracted two-point function has a spectral sum with nonnegative squared overlaps for a matching Hermitian-conjugate pair. The lightest state with nonzero overlap dominates at sufficiently large Euclidean separation. If the operator misses a state by symmetry or poor overlap, a fitted energy need not be the globally lightest state of the theory.

On a lattice with temporal extent NT, backward propagation around the boundary matters. A stable bosonic one-state contribution is a sum of forward and backward exponentials, equivalently a cosh about the midpoint. Baryonic boundary structures, staggered oscillating contributions, thermal effects, or nonmatching source/sink bases require their own formulas. A simple single-exponential ratio should therefore be used only in the time range and operator setup where its assumptions are justified.

C(n)=∑k∣Zk∣2e−E^kn,E^k=aTEk,Cone(n)=A[e−m^n+e−m^(NT−n)]C(n)=\sum_k|Z_k|^2e^{-\hat E_kn},\qquad \hat E_k=a_TE_k,\qquad C_{\rm one}(n)=A[e^{-\hat m n}+e^{-\hat m(N_T-n)}]
n is an integer Euclidean time separation, not the Monte Carlo update count. Hats denote dimensionless energies. The first form neglects temporal images; the second retains the leading periodic bosonic image for one isolated state.↔ Scroll wide equations horizontally.

Use ratios with a contamination model

For an effectively infinite temporal direction, the logarithm of adjacent correlators is constant for one exponential. With a heavier positive contribution it typically approaches the ground energy from above, though more complicated operator or sign structures can invalidate that simple behavior. A plateau across a few noisy points can result from insufficient precision rather than negligible excited states. Varying fit windows, operators, and model complexity provides needed evidence for a stable extraction.

The cosh effective mass uses three adjacent times and exactly recovers one periodic-state mass when the formula applies. It is not a universal cure for multiple states, nor does it remove statistical correlations between those three estimates. At long time, signal-to-noise degradation can make the arithmetic ratio unstable or biased. Mass fitting should respect covariance across times and the nonlinear nature of the derived quantities.

m^log⁡(n)=log⁡C(n)C(n+1),m^cosh⁡(n)=arcosh⁡ ⁣[C(n−1)+C(n+1)2C(n)]\hat m_{\log}(n)=\log\frac{C(n)}{C(n+1)},\qquad \hat m_{\cosh}(n)=\operatorname{arcosh}\!\left[\frac{C(n-1)+C(n+1)}{2C(n)}\right]
The logarithmic formula assumes a positive correlator and negligible images for its one-state interpretation. The cosh formula assumes a compatible periodic single-state form; noisy arguments outside its real domain require analysis, not silent clipping.↔ Scroll wide equations horizontally.

Carry the ensemble uncertainty into the fit

The correlator at every time comes from the same gauge configurations, so its covariance is generally non-diagonal. Autocorrelation along the Markov chain further affects that covariance. Blocking and correlated resampling should preserve both structures. Covariance inversion can be unstable for too few independent samples or too many fitted times; any regularization and its effect on the result should be reported. A small fit residual alone cannot establish a correct spectral model.

The spectral lab illustrates a different identifiability issue. Reset and set mode count to 1 and decay exponent to 0; at reset time predict sum at x=π/2 equal to 1. Reset and set count to 2 and exponent to 0; predict the same readout 1 although an extra spatial mode is present. The smallest wavelength changes from 2π to π. This prescribed traveling sine sum has no exponential hadron spectrum, gauge ensemble, or statistical mass-fitting procedure.

C(n)=A0e−E^0n[1+re−ΔE^n+⋯ ],ΔE^=E^1−E^0>0C(n)=A_0e^{-\hat E_0n}\left[1+r e^{-\Delta\hat E n}+\cdots\right],\qquad \Delta\hat E=\hat E_1-\hat E_0>0
r=A₁/A₀ is an overlap ratio in the assumed positive two-state situation. Suppression depends on the gap and Euclidean time as well as overlap; it is not guaranteed by a visually smooth curve.↔ Scroll wide equations horizontally.

Watch an excited contribution decay

Let C(n)=2(1/2)ⁿ+(1/4)ⁿ on an effectively infinite temporal lattice. Compute the first two adjacent effective masses and identify the limiting ground energy.

  1. The first three values are C(0)=3, C(1)=5/4, and C(2)=9/16. The two terms have energies ln2 and ln4 in lattice units, with the first state lighter.

  2. The first log effective mass is ln[3/(5/4)]=ln(12/5)≈0.8755. The next is ln[(5/4)/(9/16)]=ln(20/9)≈0.7985.

  3. Both exceed ln2≈0.6931 and approach it as the heavier term is suppressed. A finite-time ratio therefore need not equal either energy exactly, even with noiseless correlator values.

The result

The first two effective masses are about 0.8755 and 0.7985, approaching the ground value ln2≈0.6931.

Explore the model

Interactive lab

Interactive lab · spectral

Expose an unchanged single readout

Reset and set N=1,p=0; at time 0 predict sum at x=π/2 equal to 1 and smallest wavelength 2π. Reset and set N=2,p=0; predict sum still 1 but smallest wavelength π.

Expose an unchanged single readoutA 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. Current readings: Sum at x = π/2: 0.867; Smallest wavelength: 2π / 5; Highest-mode coefficient: 0.2. All parameters are adjustable with the labeled controls below.01.573.144.716.28−2.56−1.2801.282.56x · radiansFinite sine sum
Finite sumHighest included mode
Sum at x = π/2
0.867
Smallest wavelength
2π / 5
Highest-mode coefficient
0.2
t = 0 s

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 forThe prescribed sine series shows that one scalar readout can miss an added mode. It contains no Euclidean hadron correlator, noise covariance, or spectrum fit.

Check your understanding

What does a stable-looking effective-mass plateau establish without further checks?

Try it yourself

A periodic single-state correlator has adjacent values C(n−1)=5,C(n)=4,C(n+1)=5 at its midpoint. Find the cosh effective mass and compare with the naive forward log ratio from n−1 to n.

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 cosh argument is 10/8=1.25; cosh(ln2)=1.25.

Compare with the solution

The cosh effective mass is ln2≈0.6931. The adjacent log ratio is ln(5/4)≈0.2231 and does not equal the mass because forward and backward contributions are comparable near the midpoint. The agreement of the cosh result relies on the stated one-state periodic model.

Take it with you

  • Euclidean correlators contain a state spectrum weighted by operator overlaps.
  • Temporal images and excited states change effective-mass diagnostics.
  • Correlated ensemble uncertainties and fit-model checks belong to the mass extraction.

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