# **Provisional Patent Application Drafts** Below are two provisional patent application drafts based on the provided patent data. Each draft focuses on innovations that emphasize **probabilistic information units** or **classical systems** while challenging existing “quantum” claims that may overreach. These drafts are designed to position your inventions as novel and distinct from quantum mechanics-based patents. --- # **Provisional Patent Application #1: Probabilistic Information Unit for Data Encoding and Error Correction** ## **Title:** **Probabilistic Information Unit for Data Encoding and Error Correction** ## **Abstract:** This invention discloses a novel method and system for encoding and processing information using probabilistic states in classical systems. The system utilizes stochastic probability distributions and error-correcting codes to achieve high-fidelity information processing without relying on quantum superposition or entanglement. The invention is particularly useful for applications in data storage, communication, and machine learning. ## **Background:** Existing “quantum” patents often misapply the term to classical systems that use probabilistic methods but lack quantum mechanical foundations. For example, patents like **US-2022362450-A1** (Thoughtspot, Inc.) label data-sharing methods as “quantum” but rely on classical probabilistic protocols. Similarly, **US-10263967-B2** (Quantum Interface LLC) claims “quantum” identifiers but uses classical hashing algorithms. This invention clarifies the distinction between quantum and classical probabilistic systems. ## **Summary Of the Invention:** The invention comprises: 1. **Data Encoding Module**: A classical processor configured to encode data into probabilistic states using stochastic probability distributions. 2. **Memory Unit**: A memory array storing probabilistic information units, each unit encoded with redundancy for error correction. 3. **Controller**: A controller executing Monte Carlo sampling to validate results without relying on quantum superposition or entanglement. ## **Detailed Description:** ### **1. Data Encoding Module:** - **Stochastic Probability Distributions**: The system generates a stochastic probability distribution for input data, allowing for probabilistic encoding. - **Parallelized Matrix Operations**: The system applies parallelized matrix operations to encode the data into probabilistic states. ### **2. Memory Unit:** - **Redundancy Encoding**: Each probabilistic information unit is encoded with redundancy to enable classical error correction. - **Error-Correcting Codes**: The system uses classical error-correcting codes (e.g., Reed-Solomon, LDPC) to detect and correct errors. ### **3. Controller:** - **Monte Carlo Sampling**: The controller validates the encoded data via Monte Carlo sampling, ensuring high-fidelity results. - **Bayesian Inference**: The system uses Bayesian inference to refine probabilistic estimates and improve accuracy. ## **Claims:** **Claim 1:** A system for processing probabilistic information units, comprising: - A classical computing device configured to encode data into probabilistic states using stochastic probability distributions; - A memory unit storing said probabilistic information units, each unit encoded with redundancy for error correction; - A controller executing Monte Carlo sampling to validate results without relying on quantum superposition or entanglement. **Claim 2:** A method for encoding data into probabilistic information units, comprising the steps of: 1. Generating a stochastic probability distribution for input data; 2. Applying parallelized matrix operations to encode the data into probabilistic states; 3. Validating the encoded data via Bayesian inference without quantum hardware. **Claim 3:** A probabilistic information unit system that does not require: - Superconducting circuits (e.g., **US-10361353-B2**, Intel); - Photon entanglement (e.g., **JP-7254234-B2**, Cambridge Quantum Computing); - Topological qubits (e.g., **US-10346348-B2**, Microsoft). --- # **Provisional Patent Application #2: Classical Quantum-Inspired Algorithm for Optimization** ## **Title:** **Classical Quantum-Inspired Algorithm for Optimization** ## **Abstract:** This invention discloses a method and system for simulating quantum-inspired algorithms using classical computing resources. The system achieves performance comparable to quantum annealing for optimization tasks without requiring quantum hardware. The invention is particularly useful for applications in logistics, finance, and machine learning. ## **Background:** Many existing patents labeled as “quantum” overreach by claiming quantum-inspired algorithms that can be implemented using classical hardware. For example, **US-11316065-B2** (Artilux, Inc.) claims “quantum computing” but relies on classical lithography and materials (e.g., silicon). Similarly, **US-10686007-B2** (Intel) uses “quantum dot devices” but lacks quantum hardware. This invention positions classical quantum-inspired algorithms as a practical alternative to true quantum systems. ## **Summary Of the Invention:** The invention comprises: 1. **GPU-Accelerated Processor**: A GPU-accelerated processor executing variational optimization algorithms. 2. **Memory Array**: A memory array storing probabilistic information units encoded with error-correcting codes. 3. **Software Module**: A software module for interfacing with classical databases to process results. ## **Detailed Description:** ### **1. GPU-Accelerated Processor:** - **Variational Optimization Algorithms**: The system executes variational optimization algorithms to solve complex optimization problems. - **Parallelized Processing**: The system leverages GPU acceleration to parallelize matrix operations and achieve high-performance processing. ### **2. Memory Array:** - **Probabilistic Information Units**: The memory array stores probabilistic information units encoded with redundancy for error correction. - **Error-Correcting Codes**: The system uses classical error-correcting codes (e.g., LDPC, Reed-Solomon) to ensure data integrity. ### **3. Software Module:** - **Database Interface**: The software module interfaces with classical databases to retrieve and process data. - **Result Validation**: The system validates results using classical benchmarks to ensure accuracy. ## **Claims:** **Claim 1:** An apparatus for simulating quantum-inspired algorithms using classical computing resources, comprising: - A GPU-accelerated processor executing variational optimization algorithms; - A memory array storing probabilistic information units encoded with error-correcting codes; - A software module for interfacing with classical databases to process results. **Claim 2:** A method for simulating quantum-inspired algorithms using classical computing resources, comprising the steps of: 1. Executing variational optimization algorithms on a GPU-accelerated processor; 2. Storing probabilistic information units in a memory array encoded with error-correcting codes; 3. Validating results using classical benchmarks. **Claim 3:** A system for simulating quantum-inspired algorithms that does not require: - Superconducting circuits (e.g., **US-10361353-B2**, Intel); - Photon entanglement (e.g., **JP-7254234-B2**, Cambridge Quantum Computing); - Topological qubits (e.g., **US-10346348-B2**, Microsoft). --- # **Conclusion:** These provisional patent applications position your inventions as novel and distinct from existing “quantum” patents by emphasizing probabilistic information units and classical systems. By clearly defining the scope and avoiding quantum mechanics, these applications establish a strong foundation for protecting your innovations while challenging overbroad “quantum” claims.