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A substance that reaches superconductivity, a state in which magnetic fields cannot penetrate, and there is no electrical resistance, is referred to as a superconductor. In 1911, Heike Kamerlingh Onnes of Leiden University, a Dutch physicist, observed a relation between the temperature and the resistance of the element mercury. The mercury sample was then cooled in liquid helium to study the linear dependence of resistance on temperature. It was observed that, as the temperature decreased, the...
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Digitized adiabatic quantum computing with a superconducting circuit.

R Barends1, A Shabani2, L Lamata3

  • 1Google Inc., Santa Barbara, California 93117, USA.

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This summary is machine-generated.

Researchers developed digitized adiabatic quantum computing on superconducting systems. This hybrid approach combines the strengths of adiabatic and digital quantum computing for solving complex physics and chemistry problems.

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Area of Science:

  • Quantum Computing
  • Solid-State Physics
  • Computational Chemistry

Background:

  • Adiabatic quantum computing offers general problem-solving but faces hardware limitations like noise and connectivity.
  • Digital quantum computing provides flexibility and error correction but uses problem-specific algorithms.

Purpose of the Study:

  • To combine the advantages of adiabatic and digital quantum computing.
  • To implement a hybrid approach called digitized adiabatic quantum computing.
  • To demonstrate its capabilities on a superconducting system.

Main Methods:

  • Implemented digitized adiabatic quantum computing on a superconducting platform.
  • Utilized up to nine qubits and 1,000 quantum logic gates.
  • Performed tomographic probing during digitized evolution and analyzed error scaling.

Main Results:

  • Successfully simulated the adiabatic algorithm using a digital approach.
  • Solved instances of the one-dimensional Ising problem and complex interaction Hamiltonians.
  • Demonstrated the feasibility of digitized adiabatic quantum computing in a solid-state system.

Conclusions:

  • Digitized adiabatic quantum computing bridges the gap between general applicability and hardware constraints.
  • This approach enables the synthesis of long-range correlations and the solution of complex computational problems.
  • Integration with fault-tolerance promises a scalable, general-purpose quantum algorithm.