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Radix-Agnostic Detection of Discrete Scale Invariance: A Certified Three-Stage Protocol and a Null Result from Planck 2018

DOI: 10.5281/zenodo.21902891
Published: 2026-08-12

Abstract

Discrete scale invariance (DSI) — invariance under a discrete set of

rescalings $x \to \lambda^n x$ — predicts log-periodic oscillations whose

angular frequency in the logarithmic coordinate $u = \ln x$ is

$\omega_0 = 2\pi/\ln\lambda$. When the scaling radix $\lambda$ is unknown,

a radix-locked search at assumed radices risks both false negatives (the

true radix was never probed) and multiplicity inflation (a continuum of

probed frequencies is scanned without correction). This work develops and

certifies a radix-agnostic detection protocol in three stages: (1) detrend

in log-space and locate the spectral peak by FFT or Lomb–Scargle

periodogram; (2) refine the peak with a bounded sinusoid fit on the

detrended residuals, yielding $\hat\lambda \pm \sigma_\lambda$; (3) test

candidate radices against the measured value. Certification is mandatory:

a max-statistic bootstrap null (already multiplicity-corrected), a

likelihood-ratio test ($\Delta\mathrm{BIC} > 10$), and three integrity

gates — resolvability ($\omega \ge 2\pi/u_{\rm span}$), amplitude

($\mathrm{SNR} \ge 1$), and radix precision

($\sigma_\lambda/\lambda < 10\%$). On synthetic data with a deliberately

non-prime radix $\lambda = 1.62$, the protocol recovers the radix to

$\le 0.02\%$ error and certifies the detection. Application to the Planck

2018 temperature power spectrum yields **no certified DSI at any

resolvable radix**, including the p-adic radices $\lambda \in \{2,3,5,7\}$

(probed at adequate resolution; fractional power $10^{-4}$–$10^{-3}$). A

model-subtraction variant is mandatory for non-power-law spectra: scanning

the $\Lambda$CDM-subtracted residuals yields a clean null

($p = 0.89$, $\Delta\mathrm{BIC} = -7.3$), consistent with the radix-locked

analyses. The protocol converts the p-adic radix hypothesis from an

assumption into a measurement.

Keywords: discrete scale invariance; log-periodic oscillations; radix;

p-adic; ultrametric; CMB


1. Introduction

Discrete scale invariance is the symmetry of a system under a discrete

set of rescalings $x \to \lambda^n x$, $n \in \mathbb{Z}$, rather than

under continuous dilations. Its observable fingerprint is a

log-periodic modulation: in the coordinate $u = \ln x$, a DSI quantity

oscillates with angular frequency

\[\omega_0 = \frac{2\pi}{\ln\lambda},\]

so that the radix $\lambda$ is encoded in the frequency of a

logarithmic-domain oscillation. Log-periodic structure has been

documented in growth models [@huang1997dsi], fracture and earthquake

processes [@sornette1995earthquakes], ice-quake precursors

[@faillettaz2008icequakes], financial markets [@drozdz1999stock;

@geraskin2011lppl; @filimonov2013lppl], and physical systems including

ultraquantum topological materials [@wang2018lpo; @wang2019dsi].

A central methodological question concerns the scaling radix $\lambda$.

If a theory predicts a specific radix — for example, the p-adic

hypothesis, under which spacetime structure is valued over $\mathbb{Q}_p$

and DSI inherits the prime radix $\lambda = p$ [@schikhof1984ultrametric;

@avetisov2002padic] — a radix-locked search fixes

$\omega_p = 2\pi/\ln p$ and scans only those frequencies. This is a

legitimate and low-multiplicity confirmation instrument: earlier

radix-locked searches of the cosmic microwave background temperature

spectrum found no detection at global $p = 0.38$ [@qunical03], and the

p-adic two-point and bispectrum searches found consistent nulls

[@quni2026cmb].

But when the radix is unknown — or should not be assumed — the search

must be radix-agnostic: estimate $\omega$ continuously and let

$\lambda$ emerge as a measured quantity. This is the discovery

instrument. It pays a multiplicity price: probing a continuum of

frequencies requires correction for the effective number of independent

bins. The log-periodic power-law literature has long warned that joint

fits are over-parameterized [@geraskin2011lppl]; a robust calibration

scheme requires care [@filimonov2013lppl]. This work formalizes the

radix-agnostic protocol, adds a mandatory certification layer, and

demonstrates both a synthetic recovery and a definitive null on real

cosmological data.

2. Methods

2.1 The three-stage protocol

Given data $(xi, yi)$ with $xi > 0$, set $ui = \ln x_i$ and

$fi = \ln yi$ (the protocol operates in log-space, where a DSI

modulation is sinusoidal).

Stage 1 — detrend and spectral peak. Subtract a smooth trend in

log-space (moving average or low-order polynomial), then compute the

power spectrum of the residuals. On uniformly sampled grids use the FFT;

on uneven grids use the Lomb–Scargle periodogram [@press1989lomb;

@zechmeister2009lomb; @vanderplas2018lomb]. The dominant non-DC peak at

$f0$ cycles per unit $u$ gives $\omega0 = 2\pi f_0$ and the coarse

estimate $\hat\lambda0 = e^{2\pi/\omega0}$.

Stage 2 — bounded sinusoid refinement. Fit

$r(u) = C\cos(\omega u + \phi)$ to the detrended residuals only, with

$\omega$ bounded to $\pm 5\%$ of the Stage-1 peak. The covariance of the

fit propagates to

\[\sigma_\lambda = \left|\frac{d\lambda}{d\omega}\right|\sigma_\omega = \left|\frac{\lambda\ln\lambda}{\omega}\right|\sigma_\omega.\]

Stage 3 — candidate-radix hypothesis test. With

$\hat\lambda \pm \sigma_\lambda$ in hand, test candidate radices:

integer primes (the p-adic hypothesis), rationals, 5-smooth numbers, or

other theory-specified values. A match found post hoc is

retrodiction; the candidate set must be pre-registered before Stage 1

for evidential weight.

2.2 Certification

A detection claim is certified only when all of the following hold:

  1. Bootstrap null (max-statistic). Shuffle the residuals and

recompute the maximum spectral peak statistic; compare the observed

maximum against the null distribution. The resulting $p$ is a

max-statistic $p$ — it is already corrected for multiplicity over

the probed frequency range. Applying a further Sidak correction

double-counts the look-elsewhere penalty and is incorrect.

  1. Likelihood ratio. Compare the pure baseline (in log-space, a

linear model) against baseline plus log-periodic term; require

$\Delta\mathrm{BIC} > 10$.

  1. Integrity gates. All three must pass:
  • G1 Resolvability: $\omega \ge 2\pi/u_{\rm span}$ — at least one

full log-periodic cycle must fit in the probed range; a peak below

this is a trend artifact, not an oscillation.

  • G2 Amplitude: residual sinusoid $\mathrm{SNR} \ge 1$.
  • G3 Radix precision: $\sigma_\lambda/\lambda < 10\%$.

2.3 Model-subtraction mode (G4)

For non-power-law data (e.g. a spectrum with physical structure such as

the $\Lambda$CDM acoustic peaks), the pure-noise bootstrap null is

mis-specified: shuffling destroys real, non-DSI structure and inflates

significance. The correct protocol subtracts the physical model first:

\[r(u) = \ln y_{\rm data} - \ln y_{\rm model},\]

then scans the residuals directly (the detrend step is bypassed; the

residuals are mean-zero by construction). The bootstrap null is valid

because the residuals are noise if the model fits.

2.4 Reproducibility

The protocol is implemented in a public script with a built-in

self-test; all numerical claims below were reproduced with fresh random

seeds in the same session.

3. Results

3.1 Synthetic recovery of a non-prime radix

A synthetic signal with radix $\lambda = 1.62$ — deliberately not an

integer prime — was generated with a power-law trend, a

$30\%$ log-periodic modulation, and multiplicative noise at

$\sigma = 2\%$. Stage 1 (FFT) recovered $\lambda = 1.601$

($1.2\%$ error); Lomb–Scargle on a $40\%$-subsampled uneven grid

recovered $\lambda = 1.649$ ($1.8\%$ error). Stage 2 recovered

$\lambda = 1.620$ with $\sigma_\lambda = 0.0002$

($0.01\%$ relative) — an error of $\le 0.02\%$ across three seeds.

Certification passed: bootstrap $p = 0.0033$,

$\Delta\mathrm{BIC} = 24{,}810$, $p_F \approx 0$, and all three

integrity gates.

A cautionary negative result. The full six-parameter log-periodic

power-law fit with free $\omega$, even initialized at the true spectral

peak, converged to a degenerate solution ($\lambda \sim 10^9$). This

empirically confirms the over-parameterization warning

[@geraskin2011lppl]: stage separation is not optional.

3.2 Null on the Planck 2018 temperature spectrum

The protocol was applied to the Planck 2018 unbinned TT power spectrum

(2507 rows, $\ell \in [2, 2508]$, $D_\ell$ in $\mu\mathrm{K}^2$),

restricted to $\ell \ge 30$ ($N = 2446$, $u_{\rm span} = 4.43$). The

naive raw-spectrum scan produced a low-frequency peak at

$\omega = 0.60$–$0.66$ rad — below the minimum resolvable frequency

$2\pi/u{\rm span} = 1.42$ rad — with $\sigma\lambda/\lambda$ of

$985$–$1762\%$ and $\mathrm{SNR} = 0.15$. All three integrity gates

rejected it as a trend artifact.

The p-adic radices $\lambda \in \{2,3,5,7\}$, corresponding to

$\omega \in \{9.07, 5.72, 3.90, 3.23\}$ rad, are all resolvable in the

probed range (2.3–6.4 cycles available) and were probed at adequate FFT

resolution ($0.078$ rad). Their fractional spectral power is

$2 \times 10^{-4}$ to $5 \times 10^{-4}$ — a genuine null, in agreement

with the radix-locked searches [@qunical03; @quni2026cmb].

3.3 Model-subtraction null

The binned TT spectrum was scanned against the embedded best-fit

$\Lambda$CDM column (83 points, same grid; log-residuals with mean

$-0.004$ and standard deviation $0.040$). The residual scan returned

bootstrap $p = 0.89$ (the observed peak lies below the null mean),

$\Delta\mathrm{BIC} = -7.3$ (the sinusoid model is worse than pure

noise), and zero of three gates. This is the definitive null: no

log-periodic structure survives $\Lambda$CDM subtraction at any

resolvable radix.

4. Discussion

The contrast between the raw-spectrum artifact and the model-subtraction

null is the central methodological lesson: on non-power-law data,

radix-agnostic scanning requires physical-model subtraction first and

resolvability enforcement. Without these, the detector flags its own

artifact — exactly the look-elsewhere failure mode the integrity layer is

designed to catch.

The multiplicity analysis quantifies the cost of the discovery

instrument: the radix-agnostic scan over the Planck multipole range

carries $N_{\rm eff} \approx 3000$ independent bins, so a nominal

single-bin $p = 10^{-4}$ becomes $p_{\rm global} = 0.26$ after Sidak

correction. The radix-locked search over four primes carries four

hypotheses ($p_{\rm global} \approx 4 \times 10^{-4}$). Radix-locked

confirmation and radix-agnostic discovery are complementary instruments;

the p-adic hypothesis is now constrained by the full continuous radix

coverage, not only by the four locked primes.

The null result is consistent with, and extends, the earlier

radix-locked analyses: no log-periodic signature is found in the Planck

2018 temperature spectrum beyond the $\Lambda$CDM expectation. This is

reported as a null, not as a disconfirmation of the p-adic framework;

the framework's falsifiable content is exactly the class of signature

this protocol is built to detect.

5. Conclusion

A certified radix-agnostic protocol for the detection of discrete scale

invariance has been developed, verified on synthetic data with a

non-prime radix, and applied to the Planck 2018 temperature spectrum.

The protocol's certification layer — max-statistic bootstrap null,

likelihood-ratio test, and resolvability/amplitude/precision gates —

distinguishes genuine log-periodic structure from trend artifacts and

model mis-specification. The empirical result is a null: no certified

DSI at any resolvable radix, including the p-adic radices. The method

turns the radix hypothesis from an assumption into a measurement, and is

ready for application to other complex systems where DSI may appear.

Declarations

Funding: No external funding.

Competing interests: The author declares no competing interests.

Data availability: Planck 2018 TT spectrum is public

(IRSA release 3 ancillary data). Synthetic data are reproducible from

the public implementation's self-test.

Code availability: The detector is implemented in a public

repository (see the project's artifact registry).

Pre-registration: The p-adic radix-locked search program was

pre-registered at OSF [@quni2026osf].

Use of artificial intelligence: The author used an AI assistant for

analysis, drafting, and verification. All numerical results were

independently reproduced with fresh random seeds.

References