2.1 Detailed Structure of the TFG Report

A thoroughly structured TFG report in Physics must contain:

Introduction

• Motivation and Context: Clearly present the scientific background, significance, and motivation of your study.
• Research Questions and Objectives: Explicitly state the research questions you seek to address and the specific objectives.
• Structure Overview: Briefly describe the organization of your document.

Theoretical Framework

• Literature Review: Critically analyze previous studies, highlighting contributions and limitations.
• Key Concepts and Theories: Clearly define and contextualize relevant physics theories, models, and equations.

Methodology

• Experimental Procedures: Provide detailed descriptions of experimental setups, instruments, and materials used.
• Computational Models: Clearly explain simulations, software (Python, MATLAB, R), algorithms, and mathematical formulations.
• Data Collection Methods: Describe the methods for data acquisition and management.

Results

• Presentation of Data: Utilize figures, tables, and graphs effectively to display your findings clearly.
• Analysis Techniques: Outline methods of analysis (statistical tests, computational methods).

Discussion and Analysis

• Interpretation: Relate your results to the original research questions, analyzing patterns, anomalies, and implications.
• Comparison: Critically compare your findings with previous research and theoretical predictions.

Conclusion

• Summary of Findings: Clearly summarize main outcomes and their relevance to the field of physics.
• Limitations and Future Work: Discuss methodological constraints and suggest areas for future exploration.

Bibliography

• IEEE Citation Standard: Consistently format all references according to IEEE guidelines, ensuring accuracy and completeness.

Appendices

• Supplementary Material: Include additional data, computational code scripts (clearly commented Python or R code), experimental procedures, and detailed mathematical derivations or proofs.

2.2 Academic Writing Best Practices

• Clarity and Precision: Maintain logical flow and consistency.
• Technical Writing: Clearly define all specialized terms upon first use; minimize ambiguity.
• Avoiding Plagiarism: Properly paraphrase and cite sources; use direct quotes sparingly.
• Proofreading and Editing: Regularly revise and seek peer feedback; consider grammar-check tools like Grammarly or LanguageTool.

2.3 Writing with an IDE

Visual Studio Code (VS Code)

• Setup: Install VS Code and essential plugins.
• Plugins for Productivity: Markdown All-in-One, GitLens, LaTeX Workshop, Code Spell Checker, Prettier for consistent formatting.
• Alternative IDEs: Brief introductions to RStudio, Positron, and their specific features for scientific writing.

2.4 Quarto Ecosystem

• Introduction to Quarto: Integrated tool for academic writing combining Markdown and executable code.
• Writing Reports: Step-by-step guidance on inserting and running Python or R code chunks.
• Export Formats: Create professional outputs in PDF (LaTeX templates), HTML, or interactive web formats.

2.5 Version Control

• Git Fundamentals: Step-by-step guide on setting up Git repositories, committing changes, creating branches, and merging.
• Collaborative Workflow: Best practices for using GitHub for peer collaboration and version backup.
• Integration with VS Code: Using built-in version control features within your IDE to manage your project’s revisions seamlessly.

2.6 Environments and Execution

• Virtual Environments: Instructions to create and manage Python (venv, conda) or R (renv) environments.
• Cross-Platform Reproducibility: Strategies for ensuring your project runs smoothly on Windows, macOS, and Linux.
• Dependency Management: Techniques to document (requirements.txt, environment.yml) and reproduce your computational environment accurately across different platforms.