Quantum Circuit Sampling via Kraus Operator State Caching
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Solution Overview
Problem
Current quantum circuit simulators face challenges in sampling, particularly when a Kraus operator is involved, as they struggle with large quantum systems, leading to high memory usage and inefficiencies, such as requiring 16 terabytes of memory for a 20-qubit system.
Innovation Solution
A system that caches the probability distribution and quantum state of Kraus operators in a quantum circuit, allowing for the simulation of multiple shots based on these cached values, thereby reducing the number of shots executed in the simulation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a density matrix simulator is used to simulate quantum systems with a large number of qubits, then sampling capability is achieved, but memory usage increases substantially (e.g., 16 terabytes for a 20-qubit system)
Solution Approach 1:
The quantum circuit simulation is divided into multiple independent shots, where each shot processes a single quantum state evolution. The simulator caches intermediate results for each shot and reuses them across multiple executions, segmenting the overall simulation into manageable units that can be processed independently with reduced memory requirements.
Solution Approach 2:
The system performs preliminary caching of probability distributions and quantum states during the first shot execution. These cached results are then reused in subsequent shots, eliminating the need to recalculate the same quantum evolution multiple times and significantly reducing memory requirements for each individual shot.
2Measurement precision
If multiple shots are simulated to account for Kraus operator randomness, then accuracy is improved, but computational cost increases
Solution Approach 1:
The system creates cached copies of quantum state evolution results from the first shot and reuses these copies in subsequent shots. Instead of performing complete quantum simulations for each shot, the simulator copies and adapts previously computed probability distributions and state transformations, dramatically reducing computational cost while maintaining statistical accuracy across multiple shots.
Solution Approach 2:
The simulator changes the approach from computing full quantum states for each shot to using cached probability distributions and sampled outcomes. By transforming the computational parameters from exact quantum state evolution to statistical sampling of cached results, the system reduces computational complexity from exponential to polynomial scaling with the number of shots.
Data Source
AI summary
Systems, computer-implemented methods, and computer program products to facilitate sampling of an operator in a quantum system are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise a cache component that caches a probability distribution and a quantum state of one or more Kraus operators in a quantum circuit. The computer executable components can further comprise a simulator component that simulates one or more shots of the quantum circuit based on the probability distribution and the quantum state of the one or more Kraus operators. The one or more shots are indicative of one or more algorithm execution instances.