""" Getting Started Tab for QuantumArchitect-MCP """ import gradio as gr def add_getting_started_tab(): """Add the Getting Started tab to the Gradio interface.""" with gr.TabItem("🚀 Getting Started", id="getting-started"): gr.Markdown("""
# 🚀 Getting Started with Quantum Circuits Welcome to **QuantumArchitect-MCP**! This guide will help you understand quantum computing basics and how to use this tool effectively. --- ## 🎯 Quick Start (5 Minutes) ### Step 1: Understand What a Qubit Is A **qubit** (quantum bit) is the basic unit of quantum information. Unlike classical bits (0 or 1), qubits can exist in **superposition** - being both 0 and 1 simultaneously until measured. ``` Classical bit: 0 OR 1 Qubit: α|0⟩ + β|1⟩ (superposition of both states) ``` ### Step 2: Learn the Basic Gates | Gate | What it Does | Analogy | |------|--------------|---------| | **H** (Hadamard) | Creates superposition | Flipping a coin in the air | | **X** (NOT) | Flips 0↔1 | Light switch | | **CX** (CNOT) | Controlled NOT | "If A is 1, flip B" | | **Measure** | Collapses to 0 or 1 | Catching the coin | ### Step 3: Build Your First Circuit 1. Go to the **⚛️ Circuit Builder** tab 2. Set **Qubit 1** to `0` in the left panel 3. Click the **H** button to add a Hadamard gate 4. Click **▶️ Simulate** to see the results **Expected Result:** You'll see 50% probability for |0⟩ and 50% for |1⟩ (superposition!) --- ## 📚 Skill Levels
""") with gr.Tabs(): with gr.TabItem("🌱 Beginner"): gr.Markdown(""" ### Beginner Concepts **What You'll Learn:** - Qubits and superposition - Basic single-qubit gates (H, X, Y, Z) - Measurement - Simple 2-qubit entanglement (Bell State) **Recommended First Circuits:** | Circuit | Description | Try This | |---------|-------------|----------| | **Single Hadamard** | H gate on qubit 0 | Shows 50/50 superposition | | **Bell State** | H on q0, then CX on q0→q1 | Creates entanglement | | **NOT Gate** | X gate on qubit 0 | Flips |0⟩ to |1⟩ | **Key Concepts:** 🔹 **Superposition**: A qubit can be in multiple states at once 🔹 **Measurement**: Observing a qubit forces it to choose 0 or 1 🔹 **Entanglement**: Two qubits become correlated (Bell State) **Practice Exercise:** 1. Go to Circuit Builder 2. Add H gate to qubit 0 3. Add CX gate with control=0, target=1 4. Simulate and observe that |00⟩ and |11⟩ each have 50% probability """) with gr.TabItem("🔬 Intermediate"): gr.Markdown(""" ### Intermediate Concepts **What You'll Learn:** - Phase gates (S, T, Z) - Rotation gates (Rx, Ry, Rz) - Multi-qubit circuits - GHZ and W states - Quantum Fourier Transform basics **Phase Gates Explained:** | Gate | Matrix | Effect | |------|--------|--------| | **Z** | diag(1, -1) | Flips phase of |1⟩ | | **S** | diag(1, i) | 90° phase rotation | | **T** | diag(1, e^(iπ/4)) | 45° phase rotation | **Rotation Gates:** - **Rx(θ)**: Rotates around X-axis by angle θ - **Ry(θ)**: Rotates around Y-axis by angle θ - **Rz(θ)**: Rotates around Z-axis by angle θ **Try These Circuits:** 1. **GHZ State** (3 qubits): H(0), CX(0,1), CX(1,2) - Creates |000⟩ + |111⟩ superposition 2. **Phase Kickback**: H(0), H(1), CZ(0,1), H(0), H(1) - Demonstrates phase relationships 3. **Rotation Sequence**: Rx(π/2), Ry(π/2), Rz(π/2) - Explore the Bloch sphere """) with gr.TabItem("🎓 Advanced"): gr.Markdown(""" ### Advanced Concepts **What You'll Learn:** - Quantum Fourier Transform (QFT) - Grover's Search Algorithm - Variational Quantum Eigensolver (VQE) - QAOA for optimization - Error mitigation strategies - Hardware-aware circuit design **Quantum Fourier Transform:** ``` QFT transforms computational basis states to frequency domain: |j⟩ → (1/√N) Σₖ e^(2πijk/N) |k⟩ ``` **Grover's Algorithm:** - Searches unsorted database in O(√N) time - Uses oracle + diffusion operator - Optimal iterations: ≈ π/4 × √N **VQE (Variational Quantum Eigensolver):** - Hybrid classical-quantum algorithm - Finds ground state energy of molecules - Uses parameterized circuits (ansatz) **Hardware Considerations:** - Gate fidelity and error rates - Qubit connectivity constraints - T1/T2 coherence times - Circuit depth limitations **Use the Templates tab** to generate these circuits automatically! """) with gr.TabItem("🔧 Professional"): gr.Markdown(""" ### Professional & Research Topics **Topics Covered:** - Custom gate decomposition - Noise modeling and simulation - Quantum error correction codes - Transpilation strategies - Hardware backend optimization **Circuit Optimization Techniques:** | Technique | Description | Benefit | |-----------|-------------|---------| | Gate cancellation | Remove adjacent inverse gates | Reduces depth | | Commutation | Reorder commuting gates | Better scheduling | | Decomposition | Break complex gates into native set | Hardware compatibility | | Routing | Add SWAPs for connectivity | Executable circuits | **Using the MCP API:** This app exposes all functionality via MCP (Model Context Protocol) endpoints. AI agents can use these tools programmatically: ```python # Example MCP tool calls mcp_create_circuit("bell_state", 2, "{}") mcp_validate_circuit(qasm, "ibm_brisbane", True, True) mcp_simulate(qasm, 1024, True, "depolarizing") mcp_score_circuit(qasm, "ibm_brisbane") ``` **Research Applications:** - Quantum chemistry simulations - Optimization problems (MaxCut, TSP) - Quantum machine learning - Cryptographic protocols """)