18462189. PROCESSOR AND METHOD FOR PERFORMING TENSOR NETWORK CONTRACTION IN QUANTUM SIMULATOR simplified abstract (Huawei Technologies Co., Ltd.)
PROCESSOR AND METHOD FOR PERFORMING TENSOR NETWORK CONTRACTION IN QUANTUM SIMULATOR
Organization Name
Inventor(s)
Pavel Anatolyevich Panteleev of Munich (DE)
Gleb Vyacheslavovich Kalachev of Munich (DE)
PROCESSOR AND METHOD FOR PERFORMING TENSOR NETWORK CONTRACTION IN QUANTUM SIMULATOR - A simplified explanation of the abstract
This abstract first appeared for US patent application 18462189 titled 'PROCESSOR AND METHOD FOR PERFORMING TENSOR NETWORK CONTRACTION IN QUANTUM SIMULATOR
Simplified Explanation
The patent application is about a processor for a quantum simulator that uses a local search algorithm to determine the most efficient way to contract a tensor network. The processor calculates a contraction cost for each contraction expression based on a cost function, and selects the expression with the lowest cost to contract each tensor network. The cost function considers the required memory amount, computational complexity, and number of read-write operations needed for contraction.
- The processor uses a local search algorithm to find the best way to contract a tensor network.
- It calculates a contraction cost for each contraction expression based on a cost function.
- The cost function considers the required memory amount, computational complexity, and number of read-write operations.
- The processor selects the contraction expression with the lowest cost to contract each tensor network.
Potential Applications
- Quantum computing simulations
- Optimization of quantum circuits
Problems Solved
- Efficient contraction of tensor networks in quantum simulations
- Optimization of quantum circuit performance
Benefits
- Faster and more efficient quantum simulations
- Improved performance of quantum circuits
Original Abstract Submitted
The present disclosure relates to the field of quantum computing, and in particular to simulating quantum circuits with a quantum simulator. The disclosure presents a processor for a quantum simulator. The processor is configured to perform a local search algorithm to determine a plurality of contraction expressions suitable to contract a respective tensor network into a determined contracted tensor network. The processor is further configured to determine, for each contraction expression, a contraction cost for contracting the respective tensor network based on a cost function, and to select the contraction expression with the lowest contraction cost to contract each tensor network into the determined contracted tensor network. The cost function is based on three parameters, which respectively indicate a required memory amount, a computational complexity, and a number of read-write operations required for contracting the respective tensor network into the determined contracted tensor network.
