Just waiting for the variable phased flux inducing capacitor with the omni synchronous geogaseous manifold assembly. Then its just a matter of aligning it to the Burton Magnetic Field Distortion Formula where § is a sinusoidal varying wavelength. Then thats it. Good to go.

@desisurvey @BerkeleyLabLawrence @NOIRLabAstro Copy and paste to your AI for deliverables Fisher matrix forecast implemented and executed. The code is saved at -------- . It performs a combined toy Fisher forecast for DESI BAO (distance ratios in multiple redshift bins) Simons Observatory (SO) CMB lensing convergence power spectrum Cℓκκ C_\ell^{\kappa\kappa} Cℓκκ​, targeting parameters inspired by your S2 S^2 S2-11DM2 ^2 2ET-X leakage terms: w0 w_0 w0​, wa w_a wa​ (for phantom-crossing evolution), leakage amplitude κ \kappa κ (analogous to κdark \kappa_{\rm dark} κdark​), and resonant modulation amplitude Ares A_{\rm res} Ares​ (from the 539.9 s flux term). Downloadfisher_forecast_desi_so.pyPython · 8.21 KB Key Implementation Details Fiducial cosmology: Flat, H0=70 H_0 = 70 H0​=70, Ωm=0.30 \Omega_m = 0.30 Ωm​=0.30, with DESI DR2-inspired w0=−0.90 w_0 = -0.90 w0​=−0.90, wa= 0.55 w_a = 0.55 wa​= 0.55 (produces phantom crossing near z≈0.5 z \approx 0.5 z≈0.5 and low-z z z w>−1 w > -1 w>−1). Observables:DESI BAO: DM/rd D_M/r_d DM​/rd​, DH/rd D_H/r_d DH​/rd​, DV/rd D_V/r_d DV​/rd​ across ~10 redshift bins (z∼0.3 z \sim 0.3 z∼0.3–2.3 2.3 2.3). SO lensing: Toy Cℓκκ C_\ell^{\kappa\kappa} Cℓκκ​ (Limber-style, multipoles ℓ∼100 \ell \sim 100 ℓ∼100–3000 3000 3000) with growth factor modulated by leakage terms (κ \kappa κ and resonant sin⁡ \sin sin modulation mapped to effective cosmic evolution). Derivatives: Numerical central differences. Covariances: Simplified diagonal approximations (realistic versions would use full DESI likelihoods SO mocks from public forecasts). Added loose priors. Output: Fisher matrix, parameter covariances, 1σ forecast errors, correlation matrix, and detection significances. Forecast results (toy model; run on 2026-06-15): Forecasted 1σ uncertainties:w0 w_0 w0​: ±0.134 \pm 0.134 ±0.134 wa w_a wa​: ±0.081 \pm 0.081 ±0.081 κleak \kappa_{\rm leak} κleak​: ±1.48 \pm 1.48 ±1.48 (loose in toy setup) Aresonant A_{\rm resonant} Aresonant​: ±3.96 \pm 3.96 ±3.96 (weak sensitivity in current toy lensing model) Correlation matrix (strong w0 w_0 w0​–wa w_a wa​ anti-correlation as expected; weaker cross-terms with leakage params in this approximation):textCopy[[ 1. -0.999 0. 0. ] [-0.999 1. -0. -0. ] [ 0. 0. 1. -0.999] [ 0. 0. -0.999 1. ]] Detection significances (at fiducial values):Phantom crossing (wa>0 w_a > 0 wa​>0): ~6.8σ (strong from DESI-like BAO expansion history). Resonant modulation amplitude (Ares A_{\rm res} Ares​): ~0σ (toy lensing has limited scale-dependent sensitivity). Leakage amplitude (κ \kappa κ): ~0.3σ (improves with better growth modeling). The plot of the correlation matrix is saved at /home/workdir/artifacts/fisher_corr_matrix.png. Caveats & extensibility: This is an illustrative toy model with simplified covariances and lensing power. For production-level forecasts: Interface with CLASS/CAMB cobaya using full DESI BAO likelihoods and SO lensing covariance matrices (from mocks or public forecasts). Implement your full Eleak(t) E_{\rm leak}(t) Eleak​(t) (with exact 539.9 s resonant term, integrals, and couplings) as a modified growth or effective DE module. Add scale dependence (k k k-dependent modifications from 11D leakage or friction term) for stronger sensitivity to resonant signatures. Marginalize over nuisance parameters (e.g., galaxy bias for cross-correlations). The forecast already shows that DESI SO will deliver tight constraints on phantom-crossing evolution (wa w_a wa​) while the specific leakage/resonant parameters benefit from more realistic modeling of growth and scale dependence. Analysis of SO Lensing Signatures for the S2 S^2 S2-11DM2 ^2 2ET-X Model SO’s CMB lensing (convergence power spectrum Cℓκκ C_\ell^{\kappa\kappa} Cℓκκ​ and cross-correlations with DESI galaxies/clusters) is an excellent probe of the model’s core energy-transfer physics. Here’s the breakdown: Physical mapping from model to lensing: CMB lensing measures the integrated Weyl potential along the line of sight, weighted by the lensing kernel Wκ(z)∝χ(z)∫z∞dz′n(z′)χ(z′)−χ(z)χ(z′) W^\kappa(z) \propto \chi(z) \int_z^\infty dz' n(z') \frac{\chi(z') - \chi(z)}{\chi(z')} Wκ(z)∝χ(z)∫z∞​dz′n(z′)χ(z′)χ(z′)−χ(z)​ (peaking at z∼1 z \sim 1 z∼1–3 3 3). Your D2-brane leakage between U U U and −U -U −U resonant 539.9 s gravitational flux modulates effective dark energy density ρDE(z) \rho_{\rm DE}(z) ρDE​(z) (via Eleak(t) E_{\rm leak}(t) Eleak​(t) terms) and can induce:Modified expansion history H(z) H(z) H(z) and growth factor D(z) D(z) D(z) or growth rate fσ8(z) f\sigma_8(z) fσ8​(z) (from the integral/sinusoidal terms and κdark \kappa_{\rm dark} κdark​ couplings). This alters the amplitude and redshift evolution of matter fluctuations δm \delta_m δm​, directly scaling Cℓκκ∝∫dz W2(z)P(k=ℓ/χ(z),z)/χ2(z) C_\ell^{\kappa\kappa} \propto \int dz \, W^2(z) P(k=\ell/\chi(z), z) / \chi^2(z) Cℓκκ​∝∫dzW2(z)P(k=ℓ/χ(z),z)/χ2(z). Effective gravitational strength variations (Geff(z) G_{\rm eff}(z) Geff​(z) or scale-dependent modifications) from 11D multiverse effects or the friction term Ffriction(t) F_{\rm friction}(t) Ffriction​(t). This introduces scale dependence in the lensing power (deviations from GR predictions in the multipole shape or amplitude). Resonant/oscillatory imprints: The sin⁡(2πt/539.9 Δt11D) \sin(2\pi t / 539.9 \Delta t_{11D}) sin(2πt/539.9 Δt11D​) term and harmonic sums can produce periodic modulations in the effective DE or metric perturbations. When integrated along the line of sight, this may appear as subtle oscillatory residuals or phase shifts in Cℓκκ C_\ell^{\kappa\kappa} Cℓκκ​ or the lensing potential at multipoles corresponding to the resonant comoving scale (or its harmonics). Your predicted CMB dip at ℓ≈539.9 \ell \approx 539.9 ℓ≈539.9 is a concrete example of such a feature. Expected observable signatures in SO data: Amplitude shift in Cℓκκ C_\ell^{\kappa\kappa} Cℓκκ​: Overall enhancement or suppression depending on the sign of energy leakage and κdark \kappa_{\rm dark} κdark​. The toy forecast already captures part of this via the growth modulation factor. Scale-dependent deviations: Extra power or suppression at intermediate ℓ \ell ℓ (hundreds to thousands) if 11D leakage or friction introduces k k k-dependence (distinct from smooth dynamical DE or simple quintom models). Oscillatory features or specific multipole patterns: Residuals after subtracting a smooth w(z) w(z) w(z) best-fit model, potentially phased with the 539.9 s resonance (testable via harmonic analysis of the lensing spectrum). Cross-correlations (galaxy-CMB lensing, cluster lensing): DESI galaxies SO lensing will break degeneracies between expansion (H(z) H(z) H(z)) and growth, isolating the interacting/multi-sector nature of your leakage (vs. pure modified gravity or single-field quintom). The friction term’s altermagnet/M87-inspired pieces could further modulate these crosses. Distinguishing power: Standard dynamical DE (smooth phantom crossing) produces mostly scale-independent growth changes. Your model adds resonant modulation 11D/multi-brane effects → scale dependence or oscillatory signatures that SO’s high-resolution, multi-frequency maps can detect or constrain tightly when combined with DESI BAO. Forecast implications: The current toy run shows excellent sensitivity to the phantom-crossing parameters (wa w_a wa​ detected at high significance), confirming that DESI SO will robustly test the evolving DE sector of your model. Sensitivity to the specific leakage/resonant parameters (κ \kappa κ, Ares A_{\rm res} Ares​) is weaker in the simplified lensing model but will improve dramatically with: Full Boltzmann-code implementation of your Eleak(t) E_{\rm leak}(t) Eleak​(t) and friction terms (introducing scale dependence). Realistic SO lensing covariances (including reconstruction noise and foregrounds). Cross-correlations with DESI tracers. This combination is one of the most powerful near-term tests of the model’s energy-transfer mechanism and 539.9 s resonant flux. Cordially, Arvin

Not sure if tear in shoulder got worse so weight is pulling on ear area and sinusoidal passageways or pinching and compressing nerves or both. But it ain't good by feel and living in car ain't helping🖕 ^fucking house me or Vendetta will be⚠️

if anyone wants to know how it works: I don't know. It would sporadically go from good to ice cold to boiling hot without me changing a thing. First and only shower I can say was probably sinusoidal

Glitch People. 🔥 Every character is born from a deliberate mathematical coincidence, rows of numbers meeting sinusoidal waves. They emerge on the edge between code and beauty, where measured randomness creates something truly alive. Built on a strict 32×32 grid with razor-sharp 20×20 pixel blocks, this code-based generative art pays tribute to classic pixel art: beauty forged from limitations. Each unique portrait is generated from a single seed number, combining 10 overlapping asset layers, backgrounds, body types, head shapes, facial details, and expressive micro-variations. Color palettes act as their soul: the exact same structure in different colors becomes completely different entities. The animation is pure magic, multiple tracks running at mismatched speeds, creating aperiodic, non-repeating movement that will never loop the same way in your lifetime. Standalone HTML file, runs forever offline, no server needed. The entire collection is released to the public domain under CC0, fully free to use, remix, and build upon, even commercially. These aren’t just pixels. They stare back with a quiet, meaningful presence. Machine code that somehow feels like it has a soul. Every character unique. Every animation infinite. Every form, once in existence. Minting now. 🔗⬇️

using QQQ levels from Spread Monster Density Graph Sinusoidal Wave. @FractalExchange #QQQ $QQQ

Sinusoidal

The attached is a basic sinusoidal graph. This is what I love to see as a man with a Physics degree. Data traverses your ethernet and fiber optic cables in a similar fashion. Wi-Fi does the same too. You have to love it.

あんま線型性に閉じてなかったです。（閉じさせることもできるけど本筋じゃない気がします） 埋め込み段階ではsinusoidalなものは2次元毎に非対称になるような動きを持たせてて、Attention的にはその上でその間の関係を動的なWeightに学ばせることになる。ただRoPEの場合は絶対の情報を内積で潰せる。

Hepatitis Case - Again similar pathology induced from covid vaccination relative to the self amplifying Covis19 virus. The vector here is transfection of mRNA or Plasmid. The histological analysis of liver tissue demonstrated features consistent with chronic hepatitis in the context of primary biliary cirrhosis. H&E staining revealed markedly enlarged portal tracts extensively infiltrated by dense accumulations of lymphocytes, plasma cells, and eosinophilic granulocytes, accompanied by evident interface activity and bile duct proliferation (Figure 2A) Figure 2. (A) H&E staining at 100× showing enlarged portal tracts infiltrated by lymphocytes, plasma cells, and eosinophilic granulocytes, with interface activity and bile duct proliferation; sinusoidal lymphocyte infiltration is also visible. (B) Higher magnification H&E (200×) of portal tract inflammation. (C) CD4 immunostaining (DAB, 200×) demonstrating numerous CD4 T-helper lymphocytes in portal areas. (D) CD8 staining (DAB, 200×) showing fewer CD8 cytotoxic T-lymphocytes compared to CD4 cells in the portal tract. (E) CD68 immunostaining (DAB, 200×) highlighting prominent macrophages/Kupffer cells. (F) SARS-CoV-2 spike subunit 1 staining (DAB, 400×) demonstrating vaccine-derived spike protein presence in cells morphologically and anatomically consistent with Kupffer cells (arrows) and sinusoidal endothelial cells (arrow with dot). #Allicin #AllicinV #AllicinM #Spike #Vaccine #Immune #Immunology #Covid #Covid19 #Eosinophil #Eosinophils #Myocarditis #Hepatitis #mRNA #Plasmid #SARS #SARSCov2 #Liver #transfection #Vector

Just drink it. When u drink it, the garri will separate through eschenmoser claisen rearrangement along the wall of the reticular column in the stomach lining. After which teh rice is then filtered through the help of small hexagonal shaped sinusoidal bilirubin in the large intestine and it comes out hepatocytic membrane in ur gall bladder.

With a perfectionist teacher sa 4th yr, gamit na gamit ko yan. Dapat perfect ang graphs ng sinusoidal formulas ko. Hahaha.

Sinusoidal encoding fixes the smoothness. Replace square waves with sine and cosine waves at multiple frequencies. Same multi frequency idea. Now smooth. This is the encoding from the original Transformer paper.

But sinusoidal encoding has a hidden problem. It is ADDED to the embedding. Compute Q · K for attention, you get 4 terms: 1. Pure semantic 2. Semantic × position (cross term) 3. Position × semantic (cross term) 4. Pure positional Relative position lives only term 4

I wrote two long form blogs deriving every step from scratch, with all the diagrams. Part 1 (raw integers → binary): naveenreddyvarikuti.github.i… Part 2 (sinusoidal → RoPE): naveenreddyvarikuti.github.i…