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  ---
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  title: Cosmology Gravity Lab
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  emoji: 👀
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- colorFrom: green
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- colorTo: yellow
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  sdk: gradio
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  sdk_version: 6.1.0
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  app_file: app.py
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  pinned: false
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  license: other
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  short_description: 'Welcome to RFTs cosmology and gravity model '
 
 
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  title: Cosmology Gravity Lab
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  emoji: 👀
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+ colorFrom: indigo
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+ colorTo: purple
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  sdk: gradio
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  sdk_version: 6.1.0
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  app_file: app.py
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  pinned: false
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  license: other
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  short_description: 'Welcome to RFTs cosmology and gravity model '
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+ thumbnail: >-
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+ https://cdn-uploads.huggingface.co/production/uploads/685edcb04796127b024b4805/TOp7INVJ6aRZAKMDObeGn.png
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  ---
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+
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+ # Rendered Frame Theory — Cosmology & Gravity Lab
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+
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+ This space is the primary interactive lab for **Rendered Frame Theory (RFT)** in cosmology and gravity.
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+ Every module is driven by the same global coherence operator
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+
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+ \[
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+ U_{\rm RFT} = \Phi\,\Gamma\,\mathcal{R}\,(1 - \Xi)\,\Psi
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+ \]
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+
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+ and by the pair
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+
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+ \[
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+ \Phi\Gamma = \Phi \cdot \Gamma
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+ \]
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+
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+ which controls redshift mappings, lensing amplification and analytic rotation-curve scaling.
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+
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+ The point is simple: you see exactly how changing the **same five sliders** reshapes rotation curves, κ maps, BAO/CMB structure, black hole radii, and observer-driven collapse — in one coherent framework, not a zoo of unrelated “free parameters.”
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+
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+ ---
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+
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+ ## 🔧 Global controls — what the sliders actually do
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+
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+ These are the sliders at the top of the app. They feed every tab.
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+
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+ - **Φ (phase / amplification)**
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+ Overall strength of coherence amplification. Higher Φ makes RFT effects stronger across all modules (rotation curves, lensing, redshift, BH radius, collapse).
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+
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+ - **Γ (recursion scale)**
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+ Sets the microscopic recursion strength that builds BAO/CMB-like structure. Through
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+ \(\Gamma_{\rm eff} = \Gamma (1 + \Phi (1 - e^{-\Gamma}))\)
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+ it controls the effective BAO scale \(r_{\rm BAO}\) and the ℓ-peaks.
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+
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+ - **ℛ (curvature gain)**
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+ Large-scale curvature gain. Multiplies the entire coherence operator \(U_{\rm RFT}\). Increasing ℛ globally boosts cosmological deformations (expansion, BH radius, coherence crest strength).
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+
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+ - **Ξ (susceptibility)**
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+ How close the system is to collapse. As Ξ → 1, \(U_{\rm RFT}\) is suppressed and the system is driven towards measurement / collapse. In the observer tab we explicitly track when Ξ_total crosses 1.
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+
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+ - **Ψ (observer phase weight)**
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+ Strength of the observer’s coupling into the field. Higher Ψ tightens the link between coherence and what is actually rendered. It appears directly in \(U_{\rm RFT}\) and in the collapse drive \(\lambda_{\rm RFT}\).
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+
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+ Everything you see in the plots is just these five numbers being pushed through the same mathematics in different physical contexts.
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+
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+ ---
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+
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+ ## 🧩 Modules in this lab
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+
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+ Each module is a tab in the UI.
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+
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+ ### 1. Coherence dashboard
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+
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+ - Shows the derived quantities from your current global sliders:
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+ - \(U_{\rm RFT}\), \(\Phi\Gamma\), \(\Gamma_{\rm eff}\)
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+ - \(r_{\rm BAO}\) (coherence BAO scale)
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+ - Approximate CMB-like peaks \(\ell_1, \ell_2, \ell_3\)
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+ - Two redshift mappings: exponential and compression
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+ - Includes a BAO-scale vs \(\Gamma_{\rm eff}\) plot with your current point highlighted.
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+
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+ **What to look for:**
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+ Dial Φ and Γ and watch how \(\Gamma_{\rm eff}\) and \(r_{\rm BAO}\) move together. This is the “engine room” of the whole lab.
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+
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+ ---
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+
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+ ### 2. Rotation curves (analytic)
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+
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+ - Standard baryonic rotation curve \(v_{\rm bar}(r) = \sqrt{GM(r)/r}\) for a disk + bulge.
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+ - RFT curve:
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+ \[
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+ v_{\rm RFT}(r) = v_{\rm bar}(r)\,\sqrt{\max(\Phi\Gamma, 0)}.
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+ \]
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+ - You choose:
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+ - Disk mass, bulge mass, disk scale length.
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+ - The plot shows:
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+ - “Baryons only” vs “RFT amplified”.
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+ - A 220–240 km/s band for Milky Way-like flatness.
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+
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+ **What to look for:**
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+ How much of the “dark matter” effect can be mimicked purely by \(\Phi\Gamma\) without touching the baryonic profile.
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+
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+ ---
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+
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+ ### 3. RFT gravity disk sim (N-body toy)
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+
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+ - N-body toy galaxy disk with:
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+ - Central mass + particle disk.
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+ - Same initial conditions evolved with:
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+ - Newtonian gravity.
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+ - RFT-deformed gravity,
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+ \[
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+ g_{\rm RFT} = \tfrac{1}{2}\left(g_N + \sqrt{g_N^2 + 4 g_N a_0}\right),
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+ \]
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+ where \(a_0\) is tied to \(\Gamma_{\rm eff}\).
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+ - Outputs:
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+ - Rotation curves for Newton vs RFT.
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+ - Final spatial distribution plots for both runs.
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+
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+ **What to look for:**
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+ Whether the RFT run can sustain a flat, high-velocity outer disk without inserting a “dark halo,” purely by changing the gravitational law via \(\Gamma_{\rm eff}\).
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+
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+ ---
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+
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+ ### 4. Lensing κ maps
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+
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+ - Computes a κ map for a Gaussian or Plummer lens using:
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+ - Standard critical density:
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+ \[
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+ \Sigma_{\rm crit} = \frac{c^2}{4\pi G} \frac{D_s}{D_l D_{ls}}.
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+ \]
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+ - RFT convergence:
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+ \[
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+ \kappa_{\rm RFT} = \frac{\Sigma}{\Sigma_{\rm crit}} (\Phi\Gamma).
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+ \]
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+ - Uses `astropy` distances if available; falls back to a simple mapping otherwise.
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+
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+ **What to look for:**
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+ How κ_RFT scales with \(\Phi\Gamma\) at fixed baryonic mass profile. This is the transparent alternative to “dark lens” explanations.
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+
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+ ---
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+
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+ ### 5. BAO + CMB (toy recursion spectrum)
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+
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+ - Builds a toy recursion spectrum:
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+ \[
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+ P_{\rm RFT}(k) \propto k^{-1} \left[1 + \Phi\Gamma \cos\!\left(\frac{kD_A}{\sqrt{\Gamma_{\rm eff}}}\right)\right].
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+ \]
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+ - Reports:
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+ - \(\Gamma_{\rm eff}\)
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+ - \(r_{\rm BAO}\)
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+ - Approximate harmonic peaks \((\ell_1, \ell_2, \ell_3)\).
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+
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+ **What to look for:**
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+ How a single recursion parameter set (Φ, Γ, ℛ, Ξ, Ψ) maps to both the BAO scale and CMB-like peak spacing.
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+
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+ ---
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+
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+ ### 6. Redshift mapping
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+
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+ - Compares three curves:
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+ - FRW baseline: \(z_{\rm metric} = z_{\rm obs}\)
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+ - Exponential mapping:
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+ \[
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+ 1 + z_{\rm eff} = e^{\Phi\Gamma}
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+ \]
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+ - Compression mapping:
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+ \[
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+ 1 + z_{\rm RFT} = (1 + z_{\rm obs}) \frac{1}{1 + \Phi\Gamma}.
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+ \]
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+ - Plots \(z_{\rm rendered}\) vs \(z_{\rm obs}\) for your current ΦΓ.
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+
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+ **What to look for:**
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+ How much “redshift stretch” can be reinterpreted as coherence/observer effect instead of a hard-wired expansion history.
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+
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+ ---
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+
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+ ### 7. Black holes & LISA coherence crest (toy)
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+
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+ - Classical Schwarzschild radius:
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+ \[
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+ R_S = \frac{2GM}{c^2}.
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+ \]
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+ - RFT radius:
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+ \[
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+ R_{\rm RFT} = U_{\rm RFT} R_S.
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+ \]
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+ - Adds a **coherence crest** on top of a toy LISA-band chirp by making \(\Phi\Gamma(t)\) peak around merger and perturb the frequency.
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+
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+ **What to look for:**
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+ How a temporary spike in coherence would show up as a small, structured deviation from a GR chirp in the LISA band.
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+
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+ ---
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+
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+ ### 8. Observer field & collapse
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+
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+ - Effective susceptibility:
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+ \[
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+ \Xi_{\rm total} = \Xi_{\rm baseline} + \lambda_{\rm obs}\,\kappa_{\rm obs} + \Xi_{\rm slider}.
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+ \]
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+ - Collapse drive:
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+ \[
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+ \lambda_{\rm RFT} = \Phi\,\Gamma\,\Xi_{\rm total}\,\Psi.
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+ \]
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+ - The module:
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+ - Plots Ξ(t) and λ_RFT(t).
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+ - Flags whether Ξ_total ≥ 1 (“collapse triggered”) or not.
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+
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+ **What to look for:**
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+ How much observer coherence κ_obs you need, at your chosen Φ, Γ, Ψ, to push the system over the collapse threshold.
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+
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+ ---
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+
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+ ### 9. Math & case notes
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+
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+ Static summary of:
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+
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+ - The defining equations used in the lab.
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+ - How each module ties back to \(\Phi\Gamma\), \(U_{\rm RFT}\), and \(\Gamma_{\rm eff}\).
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+ - Enough detail for anyone to trace what the app is doing without guessing.
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+
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+ ---
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+
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+ ### 10. Provenance
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+
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+ - Every run of a module logs:
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+ - Module name
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+ - Timestamp (UTC)
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+ - Inputs (slider values, physical parameters)
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+ - Outputs (key scalars)
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+ - A **SHA-512 hash** over those fields
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+ - Records are stored in memory and (when allowed) appended to a `*.jsonl` file.
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+
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+ You can inspect the table in the **Provenance** tab.
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+
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+ ---
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+
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+ ## ⚙️ Running the lab
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+
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+ Locally:
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+
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+ ```bash
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+ pip install -r requirements.txt
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+ python app.py
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+ On Hugging Face Spaces, the app runs automatically with gradio as defined in app_file: app.py.
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+
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+ Basic usage pattern:
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+ 1. Set your global coherence field (Φ, Γ, ℛ, Ξ, Ψ) at the top.
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+ 2. Pick a tab (rotation curves, lensing, disk sim, etc.).
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+ 3. Adjust the physical parameters (masses, distances, timesteps).
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+ 4. Click the button in that tab to compute.
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+ 5. Interpret the plot using the descriptions above. All dependencies on Φ, Γ, ℛ, Ξ, Ψ are explicit.
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+
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+
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+
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+ 🔒 Legal position & allowed use
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+ • Authorship
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+ Rendered Frame Theory (RFT), its coherence operators, field equations and applied models are authored by Liam Grinstead.
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+ • Protection
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+ This work is protected under UK copyright law and the Berne Convention. All rights are reserved unless explicitly granted in writing.
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+ • You are allowed to
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+ • Use this lab to explore and understand RFT.
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+ • Make plots, screenshots, and share results for education, open research, and discussion, with proper attribution.
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+ • Cite RFT in scientific work, referencing the relevant Zenodo DOIs.
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+ • You are not allowed to
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+ • Use RFT, its equations, or this lab to design or optimise weapons or harmful systems.
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+ • Repackage the RFT framework, operators, or code, rebrand them, and claim ownership.
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+ • Commercially exploit RFT (products, services, proprietary models, or derivative frameworks) without explicit written permission from the author.
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+ • Intent
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+ RFT was built to crack open the gatekeeping around cosmology and consciousness, not to hoard knowledge.
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+ This lab is intentionally public and mathematically transparent.
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+ The line is clear: no weaponisation, no quiet commercial theft, no erasing authorship.
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+
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+
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+
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+ 📚 Citation
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+
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+ If you use this lab or RFT concepts in your work, cite at least:
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+
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+ Grinstead, L. (2025). Rendered Frame Theory’s Mathematical model. Zenodo.
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+ https://doi.org/10.5281/zenodo.17644885
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+
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+ (Include any additional RFT DOIs that match the specific equations or predictions you use.)
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+ ---
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference