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Fault-Resilience of Dissipative Processes for Quantum Computing

James Purcell, Abhishek Rajput, Toby Cubitt

TL;DR

This work proves that under circuit-level depolarizing noise, a version of the DQE algorithm applied to the geometrically local, stabilizer-encoded Hamiltonians that arise naturally when fermionic Hamiltonians are represented in qubits can suppress the additive error in the ground space overlap of the final output state exponentially in the code distance.

Abstract

Dissipative processes have long been proposed as a means of performing computational tasks on quantum computers that may be intrinsically more robust to noise. In this work, we prove two main results concerning the error-resilience capabilities of two types of dissipative algorithms: dissipative ground state preparation in the form of the dissipative quantum eigensolver (DQE), and dissipative quantum computation (DQC). The first result is that under circuit-level depolarizing noise, a version of the DQE algorithm applied to the geometrically local, stabilizer-encoded Hamiltonians that arise naturally when fermionic Hamiltonians are represented in qubits, can suppress the additive error in the ground space overlap of the final output state exponentially in the code distance. This enables us to get closer to fault-tolerance for this task without the associated overhead. In contrast, for computation as opposed to ground state preparation, the second result proves that DQC is no more robust to noise than the standard quantum circuit model.

Fault-Resilience of Dissipative Processes for Quantum Computing

TL;DR

This work proves that under circuit-level depolarizing noise, a version of the DQE algorithm applied to the geometrically local, stabilizer-encoded Hamiltonians that arise naturally when fermionic Hamiltonians are represented in qubits can suppress the additive error in the ground space overlap of the final output state exponentially in the code distance.

Abstract

Dissipative processes have long been proposed as a means of performing computational tasks on quantum computers that may be intrinsically more robust to noise. In this work, we prove two main results concerning the error-resilience capabilities of two types of dissipative algorithms: dissipative ground state preparation in the form of the dissipative quantum eigensolver (DQE), and dissipative quantum computation (DQC). The first result is that under circuit-level depolarizing noise, a version of the DQE algorithm applied to the geometrically local, stabilizer-encoded Hamiltonians that arise naturally when fermionic Hamiltonians are represented in qubits, can suppress the additive error in the ground space overlap of the final output state exponentially in the code distance. This enables us to get closer to fault-tolerance for this task without the associated overhead. In contrast, for computation as opposed to ground state preparation, the second result proves that DQC is no more robust to noise than the standard quantum circuit model.

Paper Structure

This paper contains 13 sections, 23 theorems, 102 equations.

Key Result

Lemma 1

If $H = \sum_i h_i$ is a Hamiltonian, then where is a $(\Delta, \Gamma, 0)$-AGSP for the projector $\Pi_0$ onto the ground space of $H$ with where $\lambda_0, \lambda_1$ are the minimum and next-lowest eigenvalues of $H$ (not counting degeneracies).

Theorems & Definitions (47)

  • Definition 1: Definition 6 of cubitt2023dissipative
  • Lemma 1: Lemma 12 of cubitt2023dissipative
  • Lemma 2: Lemma 11 of cubitt2023dissipative
  • Theorem 1
  • proof
  • Remark 1
  • Proposition 1
  • proof
  • Proposition 2
  • proof
  • ...and 37 more