Distributed Quantum Computing System Using Entangled Qubits
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Solution Overview
Problem
Traditional distributed computing systems face challenges in efficiently processing and joining large datasets, particularly in multi-omics scenarios, due to the need for significant data movement and resource-intensive operations, which are costly and time-consuming, especially in handling large genomic data sets.
Innovation Solution
A distributed quantum computing system utilizes entangled qubits to facilitate data transfer and processing across nodes, enabling instantaneous transformations and reducing the need for classical data movement by using quantum entanglement and quantum algorithms like Grover's algorithm for efficient dataset joining.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If classical distributed computing systems are used to process and join large datasets, then data processing can be performed using conventional methods, but significant data movement between nodes is required which is costly and time-consuming
Solution Approach 1:
The patent replaces the mechanical data movement process in classical distributed systems with quantum teleportation. Instead of physically transmitting large volumes of data between classical computing nodes, the system uses entangled qubits to transfer quantum states that represent dataset information, eliminating the need for traditional data transmission infrastructure and significantly reducing data movement time.
Solution Approach 2:
The system transforms data from classical binary format to quantum state representation using entangled qubits. By changing the fundamental parameter of data representation from classical bits to quantum states, the system enables instantaneous transformation and processing across distributed nodes without the constraints of classical data transmission speeds.
2Adaptability or versatility
If large volumes of data are transmitted between nodes of a distributed system, then datasets can be joined and processed, but the operation becomes expensive and time-consuming
Solution Approach 1:
The patent replaces energy-intensive classical data transmission with quantum teleportation using entangled qubits. The system maps entanglements between qubit sets at different nodes, allowing dataset information to be transferred through quantum state transformation rather than physical data transmission, thereby reducing computational energy consumption while maintaining dataset joining capability.
Solution Approach 2:
The system performs preliminary entanglement establishment between qubit sets at distributed nodes before data processing is needed. By pre-configuring the quantum communication channels through entanglement mapping, the system eliminates the need for expensive real-time data transmission when joining datasets, as the quantum pathways are already in place.
3Speed
If quantum entanglement is used for data transfer between distributed nodes, then data movement is reduced and processing speed is enhanced, but system complexity increases
Solution Approach 1:
The patent divides the quantum computing system into distinct operational nodes, each with its own qubit sets that are locally managed. The entanglement mapping is segmented and stored in a repository, allowing each node to independently handle quantum operations while maintaining coordinated communication through the mapped entanglements, thereby managing system complexity through modular architecture.
Solution Approach 2:
The system introduces a classical-quantum intermediary layer that manages the mapping between entangled qubit sets. This intermediary repository stores the entanglement mappings and coordinates the quantum operations across nodes, acting as a mediator that simplifies the complexity of direct quantum-quantum communication while maintaining the high-speed data transfer capabilities of quantum entanglement.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach significantly enhances the speed and efficiency of data processing and joining operations, reducing the computational burden and costs associated with handling large genomic datasets, thereby improving the performance of multi-omics analyses.
Implementation Method 1
transformation of the state of the entangled set of qubits at the second node effectuates a corresponding transformation of an entangled set of qubits at the first node that provides an indication of the dataset
Data Source
AI summary
A method for executing a query, the method comprising: obtaining, by a central node, a data request, wherein a first operational node stores a first dataset and the data request indicates that the first operational node needs a second dataset to finish an operation that involves generating a joined dataset based on the first dataset and the second data; and based on the data request, sending, by the central node, a data load request to a second operational node, wherein: the second operational node stores the second dataset, a first entangled qubit set at the first operational node includes qubits that are entangled with qubits in a second entangled qubit set at the second operational node, and the data load request instructs the second operational node to use the second entangled qubit set to transfer a quantum state based on the second dataset to the first entangled qubit set.