Learning quantum circuits of some T gates

Ching Yi Lai, Hao Chung Cheng

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

In this paper, we study the problem of learning an unknown quantum circuit of a certain structure. If the unknown target is an n-qubit Clifford circuit, we devise an efficient algorithm to reconstruct its circuit representation by using O(n2) queries to it. For decades, it has been unknown how to handle circuits beyond the Clifford group since the stabilizer formalism cannot be applied in this case. Herein, we study quantum circuits of T-depth one on the computational basis. We show that the output state of a T-depth one circuit can be represented by a stabilizer pseudomixture with a specific algebraic structure. Using Pauli and Bell measurements on copies of the output states, we can generate a hypothesis circuit that is equivalent to the unknown target circuit on computational basis states as input. If the number of T gates of the target is of the order O(log n), our algorithm requires O(n2) queries to it and produces its equivalent circuit representation on the computational basis in time O(n3). Using further additional O(43n) classical computations, we can derive an exact description of the target for arbitrary input states. Our results greatly extend the previously known facts that stabilizer states can be efficiently identified based on the stabilizer formalism.

Original languageEnglish
JournalIEEE Transactions on Information Theory
DOIs
StateAccepted/In press - 2022

Keywords

  • Clifford circuits
  • Logic gates
  • Prediction algorithms
  • Quantum circuit
  • Quantum computing
  • Quantum state
  • Stabilizer formalism
  • stabilizer pseudomixture
  • T-depth
  • Task analysis
  • Tomography

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