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Area of Science:

  • Quantum Information Science
  • Condensed Matter Physics
  • Quantum Computing

Background:

  • Simulating quantum systems with limited entanglement is computationally intensive.
  • Tensor-network states often possess spatial structures that are challenging to represent efficiently.
  • Quantum circuits offer a potential avenue for simulating these complex systems.

Purpose of the Study:

  • To demonstrate resource savings in quantum simulation by mapping tensor-network states to quantum circuits.
  • To experimentally extract the entanglement structure of infinite systems using a novel quantum circuit approach.
  • To quantitatively determine entanglement entropy and phase transitions in correlated spin chains.

Main Methods:

  • Utilizing selective midcircuit measurement and reset of qubits in a quantum circuit.
  • Encoding the entanglement structure of an infinite system into a small register of 'bond qubits'.
  • Employing Honeywell's model H0 quantum computer for experimental demonstration.

Main Results:

  • Achieved dramatic resource savings in quantum simulation by mapping spatial structures to circuit dynamics.
  • Successfully encoded and extracted the half-chain entanglement spectrum of an infinite system.
  • Quantitatively determined near-critical entanglement entropy of a correlated spin chain in the thermodynamic limit.

Conclusions:

  • Selective qubit operations in quantum circuits enable efficient simulation of tensor-network states.
  • The 'bond qubit' approach provides a powerful tool for extracting entanglement properties of extended quantum systems.
  • This method facilitates the resolution of phase transitions in the thermodynamic limit.