Voynich Manuscript Decoder

A high-performance C++ application for systematic analysis of potential EVA-to-Hebrew alphabet translations of the Voynich Manuscript. This tool tests all possible permutations of the EVA alphabet mapped to Hebrew characters to discover meaningful linguistic patterns.

Project Purpose

The Voynich Manuscript is a mysterious 15th-century codex written in an unknown script. This project implements a brute-force computational approach to test the hypothesis that the manuscript might be written in Hebrew using a substitution cipher with the EVA (European Voynich Alphabet) transcription system.

Key Features

• Systematic Analysis: Tests all 27! (10,888,869,450,418,352,160) possible EVA-to-Hebrew alphabet mappings
• High Performance: Multi-threaded processing with optimized binary matrix operations
• Real-time Statistics: Live progress reporting with mappings/second and highest scores
• State Persistence: Automatic saving and resuming of progress for long-running analysis
• Hebrew Validation: Validates translated text against a comprehensive Hebrew lexicon (40,000+ words)
• Smart Result Filtering: Saves only high-scoring translations above configurable thresholds
• Graceful Shutdown: Ctrl+C handling with state preservation

How It Works

1. Input Processing: Loads Voynich words from EVA transcription and Hebrew lexicon
2. Mapping Generation: Systematically generates all possible EVA→Hebrew character mappings
3. Translation: Converts Voynich words to Hebrew using current mapping via binary matrix multiplication
4. Validation: Checks translated text against Hebrew dictionary for meaningful words
5. Scoring: Calculates percentage of valid Hebrew words in translation
6. Results: Saves high-scoring mappings with detailed analysis to output file

Requirements

• Compiler: Visual Studio 2022 (MSVC) with C++17 support
• Platform: Windows (x64)
• RAM: 8GB+ recommended for optimal performance
• Storage: Several GB for state files during long-running analysis

Required Files

The required data files are included in the resources/ folder:

• resources/Script_freq100.txt - Voynich manuscript words in EVA transcription
• resources/Tanah2.txt - Hebrew lexicon for word validation (~40,000 Hebrew words)

These files are automatically loaded using the default configuration paths.

Project Structure

VoynichDecoder/
├── resources/           # Data files
│   ├── Script_freq100.txt    # Voynich words (EVA transcription)
│   ├── Tanah2.txt           # Hebrew lexicon
│   └── README.md            # Resource documentation
├── *.cpp, *.h          # Source code files
├── VoynichDecoder.sln  # Visual Studio solution
├── VoynichDecoder.vcxproj   # Project file
└── README.md           # This file

Building the Project

Using Visual Studio 2022

1. Open VoynichDecoder.sln in Visual Studio 2022
2. Select configuration:
   • Debug: For development and testing
   • Release: For production runs (recommended for performance)
3. Select platform: x64
4. Build → Build Solution (Ctrl+Shift+B)

Using MSBuild Command Line

# Debug build
"C:\Program Files\Microsoft Visual Studio\2022\Community\MSBuild\Current\Bin\MSBuild.exe" VoynichDecoder.sln -p:Configuration=Debug -p:Platform=x64

# Release build  
"C:\Program Files\Microsoft Visual Studio\2022\Community\MSBuild\Current\Bin\MSBuild.exe" VoynichDecoder.sln -p:Configuration=Release -p:Platform=x64

Running the Decoder

Basic Usage

# Navigate to output directory
cd x64\Debug
# or for Release build:
cd x64\Release

# Run the decoder
VoynichDecoder.exe

Configuration

Edit main.cpp to modify analysis parameters:

VoynichDecoder::DecoderConfig config;
config.numThreads = 0;                    // 0 = auto-detect, or specify count
config.scoreThreshold = 45.0;             // Minimum % for saving results
config.statusUpdateIntervalMs = 5000;     // Progress update frequency
config.maxMappingsToProcess = 0;          // 0 = unlimited
config.mappingBlockSize = 100000;         // Mappings per processing block

Runtime Behavior

Voynich Manuscript Decoder
=========================
Systematic analysis of EVA-to-Hebrew translation mappings

Initializing Voynich Decoder...
Loaded 100 Voynich words
Generated block 0 with 100,000 mappings
Configured for 8 worker threads
Score threshold: 45.0
Max mappings to process: unlimited

[2.5min] Mappings: 245,892 (294.2/sec), Highest Score: 43.84
*** HIGH SCORE *** Thread 3: Score=47.12, Matches=47/100 (47.1%), Mapping=387291
Saved state: Block 3, Total generated: 300,000

Output Files

• voynich_analysis_results.txt: High-scoring translations with detailed mappings
• voynich_decoder_state.dat: Binary state file for resuming interrupted analysis

Sample Result Format

Date/Time: 2025-01-15 14:32:17
Score: 47.12% (47/100 matches)
EVA: a b c d e f g h i j k l m n o p q r s t u v w x y z  
HEB: א ב ג ד ה ו ז ח ט י כ ל מ נ ס ע פ צ ק ר ש ת ם ן ף ץ ך

Translated Hebrew words:
שלום, בית, איש, אשה, ילד...

Performance Expectations

• Processing Rate: ~25k mappings/second (varies by hardware)
• Memory Usage: ~2-4GB RAM during operation
• Total Runtime: Theoretical completion would take millions of years
• Practical Usage: Run until satisfactory results found or specific time limit

State Management

The decoder automatically saves progress every block completion:

• Resume: Restart the application to continue from last saved state
• Reset: Delete voynich_decoder_state.dat to start fresh
• Interrupt: Use Ctrl+C for graceful shutdown with state preservation

Architecture Overview

Core Components

• VoynichDecoder: Main orchestration and multi-threading
• MappingGenerator: Systematic permutation generation with state persistence
• Translator: EVA→Hebrew conversion using binary matrix operations
• HebrewValidator: Dictionary-based validation and scoring
• WordSet: Optimized word storage and manipulation

Key Algorithms

• Factorial Number System: Efficient permutation enumeration
• Binary Matrix Translation: O(1) character mapping operations
• Hash-based Validation: Fast Hebrew word lookup
• Thread-safe Block Processing: Concurrent analysis with progress tracking

Scientific Applications

This tool enables researchers to:

• Test computational linguistics hypotheses about the Voynich Manuscript
• Explore statistical patterns in potential Hebrew translations
• Identify promising character mapping candidates for further analysis
• Validate or refute Hebrew-language theories about the manuscript

Limitations

• Computational Scope: Complete analysis requires astronomical time
• Language Assumption: Only tests Hebrew translation hypothesis
• Dictionary Dependency: Limited to words in provided Hebrew lexicon
• Character Mapping: Assumes 1:1 EVA-to-Hebrew character correspondence

Contributing

This is a research tool for cryptographic and linguistic analysis. Contributions welcome for:

• Performance optimizations
• Additional language support
• Enhanced statistical analysis
• Improved result visualization

License

Research and educational use. Please cite appropriately in academic work.