WebSnapse v4

A High-Performance Svelte 5 Visualization and Simulation Engine for Spiking Neural P Systems

WebSnapse v4 represents the next generation of Spiking Neural P (SN P) system simulators. Moving beyond the legacy Vue-based WebSnapse Reloaded, this version leverages the cutting-edge Svelte 5 framework and a high-performance FastAPI backend to provide a robust, reactive, and matrix-based simulation environment for theoretical computer science research.

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Abstract

Spiking Neural P systems are a class of distributed and parallel computing models inspired by the way biological neurons communicate through spikes. WebSnapse v4 transitions from traditional object-oriented simulation patterns to a reactive matrix-based architecture. By utilizing the Spiking Transition Matrix ($M_{\Pi}$), the engine achieves high-speed execution and deterministic/non-deterministic state exploration, all while maintaining a sleek, modern interface.

Core Functionalities

1. High-Speed Matrix Engine

At the heart of WebSnapse v4 is a NumPy-powered backend that simulates SN P systems using matrix multiplication. The firing of rules and spike distribution are calculated via the product of the Spiking Transition Matrix ($M_{\Pi}$) and the current configuration vector, ensuring O(1) or O(n) complexity relative to the system size.

2. Interactive Designer

A full-suite designer toolbar built on XYFlow (Svelte Flow) allows researchers to:

• Select: Inspect and modify neuron properties.
• Node: Add new neurons (Regular, Input, or Output).
• Edge: Establish synapses with weighted connections.
• Clear: Reset the workspace for new experiments.

3. Guided State Exploration

Handle non-determinism with ease. When multiple rule combinations are valid, the engine presents a Branch Modal, allowing the user to select the computation path or explore all possibilities in a guided manner.

4. Theoretical Judger

A batch-processing tool for formal language theory. The String Judge allows users to input a set of bitstrings and verify if the current SN P system accepts or rejects them based on defined halting conditions.

5. Research Templates

An integrated Gallery containing pre-built templates of famous SN P systems, such as:

• Binary Adders
• Bit Comparators
• Even Parity Checkers
• 2N Generators

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Tech Stack

• Frontend: Svelte 5 (Runes) for granular reactivity.
• Backend: FastAPI (Python) for asynchronous matrix computation.
• Graph Engine: XYFlow (Svelte Flow) for interactive canvas management.
• Mathematics: KaTeX for beautiful LaTeX rule rendering.
• Styling: Tailwind CSS for a modern, responsive UI.

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Getting Started

Prerequisites

• Python 3.10+
• Node.js 18+

Backend Setup

1. Navigate to the server directory: cd server
2. Create a virtual environment: python -m venv venv
3. Activate it: source venv/bin/activate (or venv\Scripts\activate on Windows)
4. Install dependencies: pip install fastapi uvicorn numpy
5. Start the engine: uvicorn main:app --reload

Frontend Setup

1. Navigate to the client directory: cd client
2. Install dependencies: npm install
3. Start the development server: npm run dev
4. Access the UI at http://localhost:5173

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Academic Attribution

This project is the terminal thesis work of Arturo Miguel V. Saquilayan in partial fulfillment of the requirements for the CS 199 (Special Problems II) course at the University of the Philippines Diliman.

Adviser: Francis George C. Cabarle Department: Department of Computer Science, College of Engineering.

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License

MIT