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Area of Science:

  • Quantum Information Science
  • Quantum Computing
  • Quantum Simulation

Background:

  • Gaussian Bosonic (GB) circuits are crucial for modeling various quantum systems.
  • Efficient simulation of GB circuits on large-scale quantum computers remains a challenge.
  • Existing methods struggle with the exponential scaling of modes in GB systems.

Purpose of the Study:

  • To develop a novel quantum computing framework for simulating GB circuits.
  • To encode bosonic states and GB operations into a qubit-based quantum computer.
  • To explore the computational power of simulating Gaussian states on quantum hardware.

Main Methods:

  • Encoding initial bosonic state expectation values and covariance matrix into qubit states.
  • Developing a quantum circuit to implement symplectic propagators of GB gates.
  • Mapping GB gates to qubit gates, distinguishing particle-preserving and non-particle-preserving operations.

Main Results:

  • Identified efficient quantum simulation strategies for specific GB circuits and initial states.
  • Established a dictionary for GB-to-qubit gate mapping, enabling real/imaginary time evolution simulation.
  • Demonstrated a Bounded-Error Quantum Polynomial time (BQP)-complete GB decision problem for particle-preserving circuits.
  • Showcased the framework's capability through numerical simulations of large-scale interferometers (∼8×10⁹ modes).

Conclusions:

  • The proposed framework enables efficient quantum simulation of Gaussian states and circuits.
  • Gaussian Bosonic evolutions on exponentially many modes are computationally equivalent to universal quantum computers.
  • The framework provides a powerful tool for exploring complex quantum systems and their dynamics.