Quantum Complexity Measure Datasets

Quantum Complexity Measure Datasets<br>OverviewThis provides a description of the datasets used in the research paper "A Unified Quantum Complexity Measure for Addressing the P versus NP Problem".Dataset Descriptions<br>1. **Problem Instances (problem_instances.csv)** - Instance ID: Unique identifier for each problem instance. - Problem Type: Indicates whether the problem is in P or NP. - Size: The size of the problem instance. - Parameters: Additional parameters characterizing the problem instance.<br>2. **Classical Entropy (classical_entropy.csv)** - Instance ID: Unique identifier for each problem instance. - H(P): Calculated classical entropy for each problem instance.<br>3. **Quantum Entanglement Entropy (quantum_entropy.csv)** - Instance ID: Unique identifier for each problem instance. - E(P): Calculated quantum entanglement entropy for each problem instance.<br>4. **Unified Quantum Complexity Measure (complexity_measure.csv)** - Instance ID: Unique identifier for each problem instance. - H(P): Classical entropy. - E(P): Quantum entanglement entropy. - alpha: Weighting factor for H(P). - beta: Weighting factor for E(P). - C_P: Unified quantum complexity measure.<br>5. **Computational Experiment Results (experiment_results.csv)** - Instance ID: Unique identifier for each problem instance. - Algorithm Type: Indicates whether a classical or quantum algorithm was used. - Execution Time (s): Time taken to solve the problem instance. - Success Rate (%): Success rate of the algorithm in solving the problem instance.<br>6. **Potential Outcomes (potential_outcomes.csv)** - Instance ID: Unique identifier for each problem instance. - C_P: Unified quantum complexity measure. - Potential Outcome: Hypothesized outcome based on the value of C_P.<br>ContactFor any questions or further information, please contact Prof. Hector Ortiz II at [e-mail].<br>