docs(readme): change Title; tiny polish

Author: PhysiMax

README.md

@@ -1,22 +1,22 @@
-# Software and Computing for Applied Physics Project
+# MCTRANSPORT Project
 ![License: MIT](https://img.shields.io/badge/license-MIT-green)
 ![Coverage](https://img.shields.io/badge/coverage-100%25-brightgreen)
 
 ## Installation
 It requires Python and git.  
-Tested on Python 3.10–3.12.
+Tested on Python 3.10-3.12.
 ```bash
-# (Optional) Create and activate a virtual environment
+# (Optional) Create and activate a virtual environment:
 python -m venv .venv
-# Windows (PowerShell)
+# Windows (PowerShell):
 . .\.venv\Scripts\Activate.ps1
-# macOS/Linux
+# macOS/Linux:
 # source .venv/bin/activate
 ```
 After cloning the repository:
 ```bash
 cd <project-directory>
-# Install the package and runtime dependencies
+# Install the package and runtime dependencies:
 pip install .
 # Or install the editable version (this is also optional):
 # pip install -e .[dev]
@@ -95,7 +95,6 @@ The free path **`L`** follows an exponential distribution with mean **`λ`**:
 </p>
 
 where the mean and the variance are <img src="https://latex.codecogs.com/png.latex?\bg_black\mathbb{E}[L]=\lambda" /> and <img src="https://latex.codecogs.com/png.latex?\bg_black\mathrm{Var}[L]=\lambda^2" />. 
-
 With the property:
 
 <p align="center">
@@ -245,7 +244,7 @@ mctransport absorption-only -N 50000 -d 1.5 -l 0.8 --seed 123 --terse --precisio
 # absorption-only,50000,1.5,0.8,123,0.15318
 ```
 
-Important: directories for --output must already exist; the program does not attempt to create missing directories and will exit with error 3 if they do not exist.
+Important: directories for **`--output`** must already exist; the program does not attempt to create missing directories and will exit with error 3 if they do not exist.
 
 ---
 
@@ -289,7 +288,7 @@ mctransport-graph
 # Example, all the parameters defined
 mctransport-graph --N 200000 --lam 1.5 --seed 7 --dmin 0 --dmax 6 --points 25 --outdir output_directory
 ```
-This method builds an equally spaced grid of distances and creates **`d_vals`** as **`linspace(dmin, dmax, points)`**.  
+This second method builds an equally spaced grid of distances and creates **`d_vals`** as **`np.linspace(dmin, dmax, points)`**.    
 
 The script produces two outputs:
   - CSV: **`results_absorption_sweep.csv`** with columns 'distance', 'T_mc', 'T_theory', 'SE';