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Circuit-Based Quantum Random Access Memory for Classical Data.

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We developed a quantum random access memory (qRAM) for efficiently encoding classical data into quantum states. This qRAM system offers a flexible method for building quantum databases, crucial for advancing quantum information processing.

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Area of Science:

  • Quantum Information Science
  • Quantum Computing
  • Data Encoding

Background:

  • Efficiently encoding classical data into quantum superposition states is essential for quantum information processing.
  • Current methods may lack the systematic and flexible nature required for complex quantum tasks.

Purpose of the Study:

  • To present a novel circuit-based flip-flop quantum random access memory (qRAM).
  • To enable systematic and flexible construction of quantum databases from classical information.

Main Methods:

  • Utilized a circuit-based flip-flop design for the quantum random access memory.
  • Developed a method requiring O(n) qubits and O(Mn) steps to register or update M entries of n-bit classical data.
  • Incorporated post-selection for storing continuous data as probability amplitudes.

Main Results:

  • The proposed qRAM system efficiently encodes classical data into quantum superposition states.
  • The method allows for systematic and flexible construction of quantum databases.
  • Demonstrated conversion of classical training data for quantum supervised learning into a quantum state.

Conclusions:

  • The developed qRAM provides an efficient pathway for classical data encoding in quantum systems.
  • The method is scalable and adaptable for various quantum information processing applications.
  • Potential for further optimization through techniques like quantum forking to reduce state preparation queries.