Superdense Quantum Compression with Entangled Qubit Mapping
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Solution Overview
Problem
Current quantum computing devices face challenges in widespread adoption due to the need for isolation and extremely low operating temperatures to prevent quantum decoherence, limiting the use of superdense encoding for data compression.
Innovation Solution
The implementation of quantum communication driver (QCD) computing devices that perform superdense encoding of conventionally compressed files using entangled qubits, reducing storage requirements by half by encoding two classical bits into one qubit and storing it with a sequential qubit mapping.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If quantum computing devices are used for superdense encoding, then data compression ratio is improved (storage space reduced by half), but device complexity and operational requirements worsen (need for isolation and extremely low temperatures)
Solution Approach 1:
The system divides the quantum computing functionality into two separate devices: a first QCD computing device that performs the superdense encoding operation, and a second QCD computing device that stores the entangled qubits. This segmentation allows the complex quantum operations to be separated from the storage function, enabling conventional compression formats to be used while achieving quantum-level compression ratios.
Solution Approach 2:
The patent uses an intermediary classical computing device to convert data into compressed format before quantum encoding. This intermediary approach allows classical data processing to prepare the data for quantum superdense encoding, bridging the gap between conventional computing and quantum computing requirements.
2Ease of operation
If conventional compression formats are used, then ease of operation is improved, but compression ratio deteriorates compared to quantum superdense encoding
Solution Approach 1:
The system merges conventional compression techniques with quantum superdense encoding in a two-stage process. First, conventional compression algorithms reduce the data size to a compressed format that is easy to process. Then, quantum superdense encoding is applied to the compressed data, achieving an additional 50% space reduction. This combination allows the system to benefit from both the simplicity of classical compression and the efficiency of quantum encoding.
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 method enables efficient data compression and storage by leveraging entangled qubits, reducing storage needs and maintaining data integrity, while addressing the challenges of quantum decoherence and temperature requirements.
Implementation Method 1
a pair of qubits may also experience a physical phenomenon referred to as 'entanglement,' in which the quantum state of each qubit cannot be described independently of the state of the other qubit
Data Source
AI summary
Quantum compression using quantum communication driver (QCD) computing devices employing superdense encoding of conventionally compressed files is disclosed. In one example, a first QCD computing device receives a compressed file that was compressed using conventional compression formats by a computing device. The first QCD computing device performs superdense encoding of the compressed file using one or more first qubits that are each in an entangled state with a corresponding one or more second qubits of a second QCD computing device. The first qubit(s) are then sent to the second QCD computing device. In some examples, the second QCD computing device generates a sequential qubit mapping that represents a sequence in which the one or more first qubits encode the compressed file, and stores the first qubit(s) in association with the sequential qubit mapping.