Inverse Oscillations: Symbolic Regression Discovers a New Rhythm of the Early Universe ✛ ✎

Original: "Inverse-k Primordial Oscillations from a Symbolic Regression Search"
· Ze-Yu Peng, Qing-Yu Lan, Yun-Song Piao
arXiv:2607.04925v1 · 2026-07-06 · arXiv non-exclusive · independent analysis · 2 min
Symbolic regression has revealed inverse oscillations in the primordial power spectrum, hinting at a possible super-expansion phase after the Big Bang.

Context

Primordial oscillations are key to the physics right after the Big Bang. Georges Lemaître's theory of the expanding universe was confirmed by spectroscopy of the cosmic microwave background, predicted by Ralph Alpher. Deviations from a simple power-law spectrum could indicate exotic processes inaccessible to particle accelerators.

Methods

Instead of templates, the authors used symbolic regression—the PySR algorithm, which searches through analytic expressions, minimizing the discrepancy with cosmic microwave background data. Spectra were computed with the CLASS code at fixed cosmological parameters. Two datasets were used: Planck alone and the combination Planck+ACT+SPT-3G.

Results

Both datasets independently selected an oscillation of the form cos(B/k) with B≈4 Mpc⁻¹. For Planck, the amplitude was −0.03, and for SPA, −0.02. MCMC comparison showed that the inverse template gives a chi-squared improvement of ~12.6 versus ~7.7 for linear and ~5.8 for logarithmic. The amplitude of the inverse oscillation has weak nonzero significance: A = 0.0163+0.0099−0.0071, while the others are consistent with zero. The primordial origin of the signal is supported by polarization data on scales 800≲ℓ≲2000.

Implications

The inverse oscillation may point to a period of super-fast expansion with violation of the null energy condition (w < −1), proposed in some models. This links observational cosmology to quantum gravity and string theory, opening a window to the Planck era.

Future development

Future experiments like Simons Observatory and CMB-S4, with improved resolution on small scales, will confirm or refute the inverse oscillation. Moreover, the spectroscopic approach with symbolic regression will be increasingly applied to search for non-template signals.

Impact

The results touch upon early universe physics, modified gravity, and machine learning methods in astrophysics.

Next steps

Detailed theoretical elaboration of models that generate inverse oscillations is planned, along with their verification on new data.

Key open problems

The work aligns with the search for inflationary physics beyond the Standard Model, linking the problem of dark energy's nature and the initial singularity of the Big Bang.

The knowledge machine's view

This section is addressed to the author of the paper and their colleagues. Neighbouring works were found by meaning-based search across our archive, not by word overlap. We do not review: we show the field around the work.

What the work does

The study applies symbolic regression (PySR) to cosmic microwave background data (Planck and Planck+ACT+SPT-3G) to search for oscillations in the primordial power spectrum without predefined templates. The algorithm independently identified an inverse k-oscillation cos(B/k) with B≈4 Mpc⁻¹ in both datasets, which showed better agreement compared to linear and logarithmic oscillations. The amplitude of this oscillation has weak non-zero significance, and polarization data confirm its primordial origin.

Where its strength is

The strength of the work lies in the first application of symbolic regression for a model-independent search of oscillatory features in the power spectrum, which led to the discovery of a non-trivial form cos(B/k) not considered before. This opens the way to a systematic search for unknown structures in cosmological data without theoretical bias.

Where it could go next

Worth trying

  • Test the robustness of the found form cos(B/k) when varying cosmological parameters and including additional datasets, e.g., from future experiments.
  • Use symbolic regression to simultaneously search for multiple oscillatory components or more complex spectral features.
  • Assess how well the inverse oscillation agrees with specific early-universe models, such as a phase transition or a bounce, by comparing with theoretical predictions.

Why this may matter

If the inverse oscillation is confirmed, it would be the first observational hint of a violation of the null energy condition in the early universe, linking inflationary cosmology to quantum gravity and string theory. Furthermore, demonstrating the effectiveness of symbolic regression could change the approach to cosmological data analysis, making it more open to unexpected discoveries.

Symbolic regression allowed the algorithm to 'invent' the function cos(B/k) without clues — much like it previously rediscovered Kepler's laws from data.

Oscillations on cosmological scales echo the imagery of a pulsating universe in the works of Ursula Le Guin.

P_{\mathcal{R}}(k) = P_{\mathcal{R},0}(k)\,[1+f(k)]
The standard power-law spectrum P_{R,0} is multiplied by the modulation 1+f(k)
f(k) = A \cos\left(\frac{B}{k} + \phi\right)
Oscillations in inverse wavenumber with frequency B≈4 Mpc⁻¹

Key numbers

  • Frequency B (inverse oscillation): ≈ 4.1 Mpc⁻¹
  • Amplitude A (Planck): ≈ 0.03
  • Amplitude A (SPA): ≈ 0.02
  • Δχ² improvement (inverse vs linear): ~12.7
  • Δχ² improvement (inverse vs logarithmic): ~5.8
Scientists
Alan GuthAlexander FriedmannAndrei LindeGeorges LemaîtreJames PeeblesAdam Riess
Concepts
symbolic regression fundamental tone autoregressive model template first principles calculations