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Implementation of quantum compression on IBM quantum computers.

Matej Pivoluska1,2, Martin Plesch3,4

  • 1Institute of Physics, Slovak Academy of Sciences, Dúbravská cesta 9, 841 04, Bratislava, Slovak Republic.

Scientific Reports
|April 8, 2022
PubMed
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We tested a quantum compression algorithm on IBM quantum processors, compressing three qubits into two. Results show transpilation significantly impacts performance, and current processors struggle with even simple compression/decompression tasks.

Area of Science:

  • Quantum Computing
  • Quantum Information Science

Background:

  • Quantum computing advancements enable practical testing of quantum algorithms.
  • Quantum information compression is a key area for developing quantum technologies.

Purpose of the Study:

  • To implement and evaluate a quantum compression algorithm for unknown quantum information.
  • To assess the performance of quantum compression on current quantum processors.

Main Methods:

  • Implementation of a quantum compression algorithm reducing three pure qubits to two.
  • Execution on IBM quantum processors with distinct topological layouts (fully connected vs. partially connected).
  • Analysis of the impact of processor connectivity and circuit transpilation on algorithm performance.

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Main Results:

  • Processor connectivity had minimal impact on compression performance.
  • Circuit transpilation critically influenced the compression algorithm's outcome.
  • Simultaneous compression and decompression of qubits is at the limit of current quantum processor capabilities.

Conclusions:

  • Current quantum processors face significant challenges in executing even basic quantum compression tasks.
  • Transpilation is a crucial factor to consider for optimizing quantum algorithm performance.
  • Further advancements in quantum hardware are needed for reliable quantum information compression.