Distributed Quantum Computing With Resource Allocation and QPU Synchronization
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Solution Overview
Problem
Current quantum computers face challenges in scaling up due to hardware limitations, particularly with qubit count, and there is a need for efficient resource allocation and synchronization in distributed quantum computing systems to enable simultaneous access by multiple users.
Innovation Solution
A system and method for distributed quantum computing that includes a processor and memory configured to manage quantum programs, discover nodes, allocate resources, and convert programs into machine-level instructions for execution across a distributed quantum computer network, utilizing high-level and low-level compilers to optimize resource utilization and synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If quantum computers are scaled up by building single systems with more qubits, then computing power increases, but hardware complexity and difficulty of manufacture increase significantly
Solution Approach 1:
The patent divides a large-scale quantum computing system into multiple smaller quantum processing units (QPUs), each with a manageable number of qubits (e.g., 50-500 qubits per node). These modular QPUs are connected through quantum communication channels to form a distributed quantum computer, avoiding the need to manufacture single complex systems with thousands of qubits while achieving equivalent or greater computational power.
2Ease of manufacture
If distributed quantum computing is implemented, then hardware complexity is reduced, but coordination and synchronization complexity increases
Solution Approach 1:
The patent introduces a quantum compiler as an intermediary component that automatically handles the coordination and synchronization between distributed QPUs. The compiler translates high-level quantum algorithms into low-level instructions that account for quantum communication delays, entanglement distribution, and node synchronization, thereby shielding users from the underlying coordination complexity.
Solution Approach 2:
The system dynamically adjusts operational parameters such as quantum communication channel selection, entanglement distribution timing, and instruction scheduling based on real-time system state. This allows the distributed quantum computer to optimize performance and handle synchronization automatically without requiring manual intervention.
3Productivity
If quantum algorithms are executed on distributed systems, then resource utilization improves, but additional operations and coordination steps increase execution time
Solution Approach 1:
The quantum compiler performs preliminary actions by pre-compiling quantum algorithms into distributed instruction sets that optimize resource utilization before execution. It prepares entanglement distribution schedules, allocates quantum resources across nodes, and sequences operations to minimize communication overhead, thereby reducing execution time despite the distributed architecture.
Solution Approach 2:
The system maintains continuous useful action by overlapping quantum operations across multiple QPUs and utilizing quantum parallelism. While some QPUs are executing computational operations, others are simultaneously establishing entanglement or preparing quantum states, ensuring that resources remain actively utilized without idle periods that would increase overall execution time.
4Productivity
If multiple users access quantum computing resources simultaneously, then system utilization increases, but resource allocation and security management complexity increases
Solution Approach 1:
The patent implements a universal quantum operating system and resource management platform that handles multiple user requests, security authentication, resource allocation, and job scheduling through a single integrated system. This multi-functional platform abstracts the complexity of managing distributed quantum resources, allowing multiple users to access the system simultaneously while maintaining security and optimal resource utilization.
Data Source
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AI summary
A system for distributed quantum computing execution is provided. The system comprises a processor configured to receive at least one user instruction set, process user data to output a flow of quantum programs, determine allocation of available quantum resources need for the flow of quantum programs, remap the flow of programs to the allocation of available quantum resources produce distributed machine level instructions, serialize said distributed machine level instructions, and send the distributed machine level instructions to a distributed quantum computing system. The system further includes a distributed quantum computing system comprising, at least one quantum processing unit configured to receive at least one set of machine level instructions, communicate with a central controller, and send measurement results back to the processor.