feat: Add quantum circuit visualization and 6 tutorial examples

[FlagQuantum]

🎯 Overview

This PR adds professional quantum circuit visualization capabilities to FlagQuantum,
along with 6 tutorial examples to help users get started quickly.

✨ New Features

Circuit Visualization

• OpHistoryVisualizer: Parse qdev.op_history to generate circuit diagrams
• Text Mode (draw_text): Unicode-based circuit representation (PennyLane style)
  • Supports ╭╰├│ grouping symbols for multi-qubit gates
  • Auto line-wrapping with max_length parameter
  • Configurable decimal precision for parameters
• MPL Mode (draw_mpl): Matplotlib-based publication-quality figures
  • Professional color scheme:
    • Fixed gates (H, X, Y, Z): soft blue #7B9EC2
    • Rotation gates (RX, RY, RZ): red #E15759
    • Phase gates (P): plum purple #DDA0DD
    • CPhase: teal #76B7B2
    • CRX/CRY/CRZ: orange #F28E2B
    • RXX/RYY/RZZ: light pink #FFB6C1 (box layout, no control points)
    • SWAP: teal #76B7B2
  • Layer-based layout algorithm (same-column gates share x-coordinate)
  • Supports Toffoli (CCX), Fredkin (CSWAP), multi-qubit gates
  • Initial state display (|0⟩) and measurement symbols

Tutorial Examples (6 notebooks)

1. 00_understanding_states.ipynb - Understanding quantum state representations
2. 01_basic_operations.ipynb - Basic single-qubit and two-qubit gates
3. 02_measurement.ipynb - Quantum measurement and expectation values
4. 03_parameterized_gates.ipynb - Parameterized gates (RX, RY, RZ, Phase, CPhase, CRX/CRY/CRZ)
5. 04_quantum_circuit_builder.ipynb - Building and visualizing circuits from op_history
6. 05_quantum_machine_learning.ipynb - End-to-end QML training with visualization

📁 File Changes

New Files

• flagquantum/drawer/__init__.py - Visualization submodule
• flagquantum/drawer/text_drawer.py - Text-based circuit drawer
• flagquantum/drawer/mpl_drawer.py - Matplotlib circuit drawer
• flagquantum/drawer/style.py - Plotting style management
• examples/tutorials/00_understanding_states.ipynb
• examples/tutorials/01_basic_operations.ipynb
• examples/tutorials/02_measurement.ipynb
• examples/tutorials/03_parameterized_gates.ipynb
• examples/tutorials/04_quantum_circuit_builder.ipynb
• examples/tutorials/05_quantum_machine_learning.ipynb

Modified Files

• flagquantum/__init__.py - Export visualization functions

🚀 Usage

import flagquantum as fq
import torch

# After running a circuit
qdev = fq.DistributedQuantumDevice(n_wires=4, bsz=1, record_op=True)
# ... apply gates ...

# Text visualization
print(fq.draw(qdev, format="text", decimals=3, show_all_wires=True, show_initial_state=True))

# MPL visualization
fig, ax = fq.draw(qdev, show_initial_state=True, format="mpl", style="flagquantum")