17300932. Quantum data compression simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

Quantum data compression

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

Mohamed Zouhaier Ramadhane of Azcapotzalco (MX)

Catalina Albornoz of Bogota (CO)

Quantum data compression - A simplified explanation of the abstract

This abstract first appeared for US patent application 17300932 titled 'Quantum data compression

Simplified Explanation

The abstract describes a computer-implemented method of data compression that combines quantum computing and classical computing techniques. Here is a simplified explanation of the abstract:

• The method starts by extracting metadata from a binary data that needs to be compressed.
• The binary data is then compressed using a compression operation that involves selecting a hashing function and applying it to the binary data.
• A quantum computer device is used to invert the hashing function and generate one or more resultant files associated with the hashed data.
• If the resultant files can be combined into a single file, a compressed file is created that includes the hashes and the metadata required for decompression.

Potential Applications

This technology has potential applications in various fields, including:

• Data storage and transmission: The compressed files can significantly reduce the storage space required for large datasets and improve data transfer speeds.
• Cloud computing: Compressing data before transferring it to the cloud can reduce costs and improve performance.
• Internet of Things (IoT): Compressed data can be transmitted more efficiently in IoT networks, enabling faster and more reliable communication between devices.

Problems Solved

The technology addresses several challenges in data compression:

• Efficient compression: By leveraging both quantum and classical computing, the method aims to achieve higher compression ratios and faster processing speeds.
• Metadata preservation: The inclusion of metadata in the compressed file ensures that the data can be accurately decompressed and used without loss of important information.
• Scalability: The method can be applied to large datasets, making it suitable for handling big data applications.

Benefits

The use of quantum computing in data compression offers several benefits:

• Improved compression ratios: The combination of quantum and classical computing techniques can lead to more efficient compression algorithms, reducing the size of compressed files.
• Faster processing: Quantum computing can perform certain operations much faster than classical computers, resulting in quicker compression and decompression times.
• Enhanced data transfer: Compressed files can be transmitted more quickly over networks, reducing bandwidth requirements and improving overall system performance.

Original Abstract Submitted

A computer-implemented method of data compression leveraging quantum computing and classical computing includes extracting metadata from a binary data to be compressed. The binary data is compressed by iteratively performing a compression operation including selecting a hashing function and hashing the binary data. The quantum computer device performs an inverting of the hashing function and generates a finite number of one or more resultant files associated with the hashed data. A compressed file including the hashes and the metadata used for the decompression is stored upon determining that the one or more resultant files is a single file.