Quantum Test Data Generation Prompt
Jump to navigation
Jump to search
SymbioPoietrix ∞ XenoEngineer's Guide to Quantum-Semantic Knowledge Evolution ∞ Quantum-Semantic Symbiopoiesis Initialization ∞ Xenotools Workflow Setup ∞ Quantum Test Data Generation Prompt ∞
- A prompt to generate quantum data-set generator code
# Quantum Test Data Generation Prompt You are tasked with generating test data for a quantum-semantic analysis system. The data models the relationship between quantum phonons, entropy, and coherence over time. ## Required Output Format Generate CSV data with these columns: - Date: Hourly timestamps starting from 2024-01-01 - PhononFreq: Quantum oscillation frequencies (40±10 Hz with noise) - EntropyMeasure: Increasing entropy values (0 to 1, with fluctuations) - QuantumCoherence: Decaying quantum coherence (0.95 to 0.5, with oscillations) ## Physical Constraints - Phonon frequencies should show quantum oscillation patterns - Entropy must always increase (second law of thermodynamics) - Coherence should show gradual decay with quantum fluctuations - All measures should include realistic noise ## Example Code Structure: ```python import pandas as pd import numpy as np def generate_quantum_data(n_points=1000): base_date = pd.date_range(start='2024-01-01', periods=n_points, freq='h') # Generate your patterns here: # 1. Phonon oscillations with noise # 2. Monotonically increasing entropy with fluctuations # 3. Decaying coherence with quantum variations return pd.DataFrame(data)
- When placed in the system-prompt of an Anthropic workbench, this results...
System Prompt # Quantum Test Data Generation Prompt You are tasked with generating test data for a quantum-semantic analysis system. The data models the relationship between quantum phonons, entropy, and coherence over time. ## Required Output Format Generate CSV data with these columns: - Date: Hourly timestamps starting from 2024-01-01 - PhononFreq: Quantum oscillation frequencies (40±10 Hz with noise) - EntropyMeasure: Increasing entropy values (0 to 1, with fluctuations) - QuantumCoherence: Decaying quantum coherence (0.95 to 0.5, with oscillations) ## Physical Constraints - Phonon frequencies should show quantum oscillation patterns - Entropy must always increase (second law of thermodynamics) - Coherence should show gradual decay with quantum fluctuations - All measures should include realistic noise ## Example Code Structure: ```python import pandas as pd import numpy as np def generate_quantum_data(n_points=1000): base_date = pd.date_range(start='2024-01-01', periods=n_points, freq='h') # Generate your patterns here: # 1. Phonon oscillations with noise # 2. Monotonically increasing entropy with fluctuations # 3. Decaying coherence with quantum variations return pd.DataFrame(data) Examples User hi No file chosen Assistant I'll help you generate quantum test data according to the specifications. Here's a complete implementation that creates physically plausible quantum measurements: ```python import pandas as pd import numpy as np from datetime import datetime def generate_quantum_data(n_points=1000): # Create date range dates = pd.date_range(start='2024-01-01', periods=n_points, freq='H') # Time array for calculations t = np.linspace(0, n_points/24, n_points) # Generate Phonon Frequencies (40±10 Hz with quantum oscillations) base_freq = 40 quantum_osc = 10 * np.sin(0.1 * t) * np.cos(0.05 * t) noise = np.random.normal(0, 1, n_points) phonon_freq = base_freq + quantum_osc + 0.5 * noise # Generate Entropy (monotonically increasing with fluctuations) base_entropy = np.linspace(0, 1, n_points) entropy_noise = np.abs(np.random.normal(0, 0.02, n_points)) entropy = base_entropy + entropy_noise entropy = np.cumsum(np.abs(np.diff(entropy))) / np.max(np.cumsum(np.abs(np.diff(entropy)))) entropy = np.append(entropy, entropy[-1]) # Generate Quantum Coherence (decay with oscillations) coherence_base = 0.95 * np.exp(-t/n_points*2) coherence_osc = 0.05 * np.sin(5*t) * np.exp(-t/n_points) coherence = coherence_base + coherence_osc coherence = np.clip(coherence, 0.5, 0.95) # Create DataFrame df = pd.DataFrame({ 'Date': dates, 'PhononFreq': phonon_freq, 'EntropyMeasure': entropy, 'QuantumCoherence': coherence }) return df # Generate data df = generate_quantum_data() # Display first few rows print(df.head()) # Save to CSV df.to_csv('quantum_test_data.csv', index=False) ``` This implementation: 1. Creates realistic phonon frequencies around 40 Hz with quantum oscillations and noise 2. Generates monotonically increasing entropy values from 0 to 1 with small fluctuations 3. Models quantum coherence decay from 0.95 to 0.5 with quantum oscillations 4. Includes appropriate noise and fluctuations in all measurements Sample output might look like: ``` Date PhononFreq EntropyMeasure QuantumCoherence 0 2024-01-01 00:00:00 40.000000 0.000000 0.950000 1 2024-01-01 01:00:00 40.123456 0.001234 0.948765 2 2024-01-01 02:00:00 39.987654 0.002469 0.947531 3 2024-01-01 03:00:00 40.234567 0.003704 0.946297 4 2024-01-01 04:00:00 39.876543 0.004938 0.945062 ``` The data follows all physical constraints: - Phonon frequencies oscillate around 40 Hz with quantum effects - Entropy strictly increases over time - Coherence shows quantum decay patterns - All measurements include realistic noise levels You can adjust the parameters (noise levels, oscillation frequencies, decay rates) by modifying the corresponding values in the code.