README: observables as in arXiv:2607.08505, autocorrelation table, citation
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by YangyangTan - opened
README.md
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Monte Carlo configurations of the scalar φ⁴ theory on periodic lattices of volume V = L^D with action
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$$S[\phi] = \sum_x \Big[-2\kappa \sum_{\mu=1}^{D} \phi_x \phi_{x+\hat\mu} +
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| D | κ | λ | κ_c | L | configurations per L | total size |
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|---|---|---|---|---|---|---|
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| 2 | 0.2705 | 0.022 | 0.27088 | 16, 32, 64, 128 | 10240 | 1.8 GB |
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| 3 | 0.1923 | 0.9 | 0.19225 | 16, 32, 64, 128 | 2560 | 49 GB |
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κ_c is the critical point estimated from the
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## Files
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Each array holds the float64 field values φ_x. Axis 0 runs over configurations in
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Monte Carlo order and the remaining axes are the periodic lattice directions. The
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configurations were generated with
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## Download
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f = hf_hub_download("phi4-generative/phi4-critical-configs",
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"3D/phi4_3D_L32_kappa0.1923_lambda0.9.npy", repo_type="dataset")
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phi = np.load(f, mmap_mode="r") # (2560, 32, 32, 32)
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```
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##
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2D, κ = 0.2705, λ = 0.022
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3D, κ = 0.1923, λ = 0.9
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Monte Carlo configurations of the scalar φ⁴ theory on periodic lattices of volume V = L^D with action
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$$S[\phi] = \sum_x \Big[-2\kappa \sum_{\mu=1}^{D} \phi_x \phi_{x+\hat\mu} + \phi_x^2 + \lambda\big(\phi_x^2-1\big)^2\Big]$$
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| D | κ | λ | κ_c | L | configurations per L | total size |
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| 2 | 0.2705 | 0.022 | 0.27088 | 16, 32, 64, 128 | 10240 | 1.8 GB |
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| 3 | 0.1923 | 0.9 | 0.19225 | 16, 32, 64, 128 | 2560 | 49 GB |
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κ_c is the critical point estimated from Binder-cumulant crossings in the reference below.
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## Files
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Each array holds the float64 field values φ_x. Axis 0 runs over configurations in
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Monte Carlo order and the remaining axes are the periodic lattice directions. The
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configurations were generated with Fourier-accelerated HMC combined with Wolff cluster
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updates. The 3D L = 128 file consists of ten independent chains of 256 configurations,
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concatenated along axis 0.
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## Download
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f = hf_hub_download("phi4-generative/phi4-critical-configs",
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"3D/phi4_3D_L32_kappa0.1923_lambda0.9.npy", repo_type="dataset")
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phi = np.load(f, mmap_mode="r") # (2560, 32, 32, 32)
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phibar = phi.mean(axis=(1, 2, 3)) # zero mode of each configuration
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```
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## Autocorrelation
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Every chain starts from a random field. One sampler iteration is one HMC trajectory
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followed by Wolff cluster flips. τ_int is the integrated autocorrelation time of the
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stored sequence in units of stored configurations, so 0.5 means consecutive
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configurations are uncorrelated.
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| D | L | chains × configurations | warm-up iterations | stored every | HMC acceptance | τ_int(\|φ̄\|) | τ_int(S) |
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| 2 | 16 | 1 × 10240 | 2000 | 5th iteration | 0.77 | 0.53 | 0.56 |
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| 2 | 32 | 1 × 10240 | 2000 | 5th iteration | 0.78 | 0.58 | 0.60 |
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| 2 | 64 | 1 × 10240 | 2000 | 5th iteration | 0.78 | 0.64 | 0.66 |
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| 2 | 128 | 1 × 10240 | 2000 | 5th iteration | 0.79 | 0.69 | 0.79 |
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| 3 | 16 | 1 × 2560 | 2000 | 10th iteration | 0.77 | 0.60 | 0.55 |
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| 3 | 32 | 1 × 2560 | 2000 | 10th iteration | 0.80 | 0.53 | 0.54 |
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| 3 | 64 | 1 × 2560 | 2000 | 10th iteration | 0.75 | 0.78 | 0.88 |
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| 3 | 128 | 10 × 256 | 2000 per chain | 10th iteration | 0.77 | 0.74 | 0.74 |
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## Observables
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With the zero mode φ̄ = V⁻¹ Σ_x φ_x of each configuration,
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$$\chi = V\big(\langle\bar\phi^2\rangle - \langle|\bar\phi|\rangle^2\big), \qquad U_L = 1 - \frac{\langle\bar\phi^4\rangle}{3\langle\bar\phi^2\rangle^2}, \qquad \kappa_2^{(\mathrm{site})} = \frac{1}{V}\sum_x\langle\phi_x^2\rangle .$$
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The action density ⟨S⟩/V omits the field-independent constant λ. Errors are jackknife
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over 64 blocks of consecutive configurations.
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2D, κ = 0.2705, λ = 0.022
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| L | ⟨\|φ̄\|⟩ | χ | U_L | κ₂^(site) | ⟨S⟩/V |
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| 16 | 0.8149(26) | 22.99(30) | 0.5524(18) | 1.5215(29) | 0.38758(49) |
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| 32 | 0.7147(25) | 64.28(83) | 0.5672(16) | 1.4698(19) | 0.39297(26) |
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| 64 | 0.6019(26) | 211.8(30) | 0.5551(20) | 1.4400(11) | 0.39619(18) |
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| 128 | 0.4446(23) | 771.6(69) | 0.4815(27) | 1.41936(61) | 0.398604(90) |
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3D, κ = 0.1923, λ = 0.9
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| L | ⟨\|φ̄\|⟩ | χ | U_L | κ₂^(site) | ⟨S⟩/V |
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| 16 | 0.2119(24) | 43.38(92) | 0.4681(65) | 0.62329(34) | −0.12466(49) |
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| 32 | 0.1497(14) | 171.7(36) | 0.4721(64) | 0.61929(11) | −0.11846(16) |
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| 64 | 0.1125(12) | 641(15) | 0.5032(48) | 0.617963(58) | −0.116385(81) |
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| 128 | 0.09725(87) | 2372(73) | 0.5658(35) | 0.617684(26) | −0.116003(38) |
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## Reference
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The ensembles follow the setup of
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```bibtex
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@article{Tan:2026ibs,
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author = "Tan, Yang-yang and Aarts, Gert and Habibi, Diaa E. and Lucini, Biagio and Wang, Lingxiao",
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title = "{Diffusion Models for Sampling Near Criticality in Lattice Field Theories}",
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eprint = "2607.08505",
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archivePrefix = "arXiv",
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primaryClass = "hep-lat",
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reportNumber = "RIKEN-iTHEMS-Report-26",
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month = "7",
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year = "2026"
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}
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```
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