Abstract
Tasks such as classification of data and determining the groundstate of a Hamiltonian cannot be carried out through purely unitary quantum evolution. Instead, the inherent non-unitarity of the measurement process must be harnessed. Post-selection and its extensions provide a way to do
this. However they make inefficient use of time resources — a typical computation might require O(2m) measurements over m qubits to reach a desired accuracy and cannot be done intermittently on current (superconducting-based) NISQ devices. We propose a method inspired by thermalisation
that harnesses insensitivity to the details of the bath. We find a greater robustness to gate noise by coupling to this bath, with a similar cost in time and more qubits compared to alternate methods for inducing non-linearity such as fixed-point quantum search for oblivious amplitude amplification. Post-selection on m ancillae qubits is replaced with tracing out O (log = log(1 p)) (where p is the probability of a successful measurement) to attain the same accuracy as the post-selection circuit. We demonstrate this scheme on the quantum perceptron, quantum gearbox and phase estimation algorithm. This method is particularly advantageous on current quantum computers involving superconducting circuits.
this. However they make inefficient use of time resources — a typical computation might require O(2m) measurements over m qubits to reach a desired accuracy and cannot be done intermittently on current (superconducting-based) NISQ devices. We propose a method inspired by thermalisation
that harnesses insensitivity to the details of the bath. We find a greater robustness to gate noise by coupling to this bath, with a similar cost in time and more qubits compared to alternate methods for inducing non-linearity such as fixed-point quantum search for oblivious amplitude amplification. Post-selection on m ancillae qubits is replaced with tracing out O (log = log(1 p)) (where p is the probability of a successful measurement) to attain the same accuracy as the post-selection circuit. We demonstrate this scheme on the quantum perceptron, quantum gearbox and phase estimation algorithm. This method is particularly advantageous on current quantum computers involving superconducting circuits.
Original language | English |
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Journal | Physical Review Research |
Publication status | Published - 28 May 2021 |