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

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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.

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