QUANTUM NEXUS

Core Concept

Deconstruct complex quantum states step-by-step through reverse iteration analysis for deeper insights into quantum dynamics.

Key Features

• **Fuzzy Logic:** Implements a "Fuzzy Reverse-Stepping" algorithm to handle ambiguous or uncertain observational inputs.
• **Cost Calculation:** Quantifies the 'distance' or 'cost' between raw observations and defined target quantum realities (Red/Grey).
• **Comparative Analysis:** Determines the most probable target reality based on the lowest calculated cost.
• **Morse Code Input:** Utilizes a specialized 4-character Morse-like code (R/B/r/b) for raw data input.

Use Case

Ideal for interpreting subjective or probabilistic data, such as results from remote viewing experiments, by providing a quantitative framework for uncertainty.

Core Concept

Decodes and evaluates quantum signal predictions using Quantum Fidelity, offering a more accurate measure than simple geometric distance on the Bloch Sphere.

Key Features

• **Quantum Fidelity:** Grades predictions based on the true quantum mechanical similarity between states (inner product).
• **3D Bloch Sphere:** Visualizes target (Red/Grey) and predicted states in a 3D interactive sphere.
• **Signal Ledger:** Manages and tracks multiple signal predictions and their associated data (coordinates, grades, probabilities).
• **Probabilistic Grading:** Assigns grades (A+ to D) based on the calculated probability of the prediction matching the dominant target signal.
• **Data Analysis Tools:** Includes filtering, sorting, and quantitative analysis (vote counts, average grades) for specific data subsets (Theta/Phi ranges).

Use Case

Provides a robust platform for training and evaluating quantum state prediction accuracy, particularly useful in scenarios involving binary choices represented on a sphere.

Core Concept

Simulates Feynman's conceptual Billiard Ball Computer model for reversible computation, mapping the logic gates onto interactions represented on quantum Bloch Spheres.

Key Features

• **State Manipulation:** Allows control and visualization of up to 6 distinct quantum states (Ψ₁-Ψ₆) on a shared 3D Bloch Sphere.
• **Multiple Input Methods:** Define states using angles (θ, φ), density matrix components, or wave function coefficients.
• **Remote Viewer Integration:** Decodes specialized "RB Codes" to input and visualize external state predictions (RV_Ψ₁, RV_Ψ₂).
• **Collision Path Analysis:** Calculates fidelity between viewer predictions and output states (Ψ₃-Ψ₆) to infer collision outcomes based on the billiard ball model.
• **Randomization & Export:** Features state randomization based on model rules and data export capabilities.

Use Case

Explore concepts of reversible computation and quantum gate logic through interactive visualization. Analyze external predictions (like remote viewing data) within the framework of the model.

Core Concept

Performs a comparative audit of observational data (from ledgers) against predefined target quantum states, leveraging a Morse-code abstraction inspired by Billiard Ball Computing.

Key Features

• **Maximum Analytical Separation:** Generates optimally distinct comparison states (Ψ₅, Ψ₆) by inverting the Morse code (R↔B) of anchor states (Ψ₃, Ψ₄).
• **Morse Code Abstraction:** Converts quantum state angles (θ, φ) into 12-symbol Morse strings for rule-based comparison.
• **Ledger Comparison:** Audits two separate data ledgers (RV_Ψ₁ vs Ψ₄/Ψ₆ and RV_Ψ₂ vs Ψ₃/Ψ₅) row by row.
• **Cost-Based Scoring:** Calculates a "cost" representing the deviation between observed data (in 8-symbol Morse) and the target state rules (derived from 12-symbol Morse). Lower cost indicates better fit.
• **Detailed Drilldown:** Provides granular analysis showing row-by-row cost calculations and Morse code comparisons.

Use Case

Objectively determine which predefined quantum state (or its optimized inverse) best explains a set of observational data, designed for high-confidence results in comparative analysis scenarios.

Core Concept

Audits observational data against ideal quantum states using a Billiard Ball Computing model abstraction.

Key Features

• Maximum Analytical Separation
• Morse code inversion (R↔B)
• High-confidence audit system

Use Case

Compare ledgers of observational data (RV_Ψ₁/RV_Ψ₂) against four target states (Ψ₃-Ψ₆) to determine the best fit.

Core Concept

Automates the creation of nested directory structures for research trials or projects using a generated PowerShell script.

Key Features

• **Custom Structure:** Define complex, nested folder hierarchies using a simple editor.
• **Trial Range:** Specify start and end trial numbers for batch folder creation.
• **Placeholders:** Use `{TRIAL_NUM}` placeholder for automatic numbering (e.g., Trial_01, Trial_02).
• **Timestamp Option:** Optionally include date and time in the main trial folder names.
• **Preview:** Visualize the folder structure for the first trial before generating the script.
• **Script Generation:** Creates a ready-to-run `.ps1` PowerShell script.

Use Case

Streamline the setup process for experiments, simulations, or projects requiring consistent, numbered folder structures, saving time and reducing manual errors.