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Constant-Depth Quantum Circuits for Arbitrary Quantum State Preparation via Measurement and Feedback

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arxiv 2503.16208 v1 pith:W67K27VA submitted 2025-03-20 quant-ph

classification quant-ph
keywords quantumfeedbackmeasurementconstant-depthoperationsarbitrarycircuitcircuits
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The optimization of quantum circuit depth is crucial for practical quantum computing, as limited coherence times and error-prone operations constrain executable algorithms. Measurement and feedback operations are fundamental in quantum computing (e.g., quantum error correction); we develop a framework using them to achieve constant-depth implementations of essential quantum tasks. This includes preparing arbitrary quantum states with constant-depth circuits through measurement and feedback, breaking the linear-depth lower bound that is required without these operations. Our result paves the way for general quantum circuit compression using measurement and feedback.

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Forward citations

Cited by 5 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Optimal T Counts under Sparsity: from QROM to State Preparation and Block Encoding

    quant-ph 2026-07 accept novelty 7.0 of 10

    Sparse QROM has optimal Clifford+T cost Θ(√(sm)+√(sn)), yielding matching optimal T-counts for s-sparse state preparation and s-sparse block encoding.

  2. Efficient Depth--Ancilla Tradeoffs for Hamming Weight Computation and Symmetric Boolean Functions

    quant-ph 2026-08 conditional novelty 6.0 of 10

    New quantum circuits for Hamming weight and symmetric Boolean functions: O(log n) depth with sublinear ancillas (all-to-all), optimal Θ(√n) depth with O(log^2 n) ancillas (2D), and constant depth with O(n^{1+ε}) ancil...

  3. Optimizing sparse quantum state preparation with measurement and feedforward

    quant-ph 2025-08 conditional novelty 6.0 of 10

    Two new sparse quantum state preparation algorithms achieve O(n log d) and O(n) circuit depth with O(d) ancilla qubits and O(dn) size.

  4. Depth-Efficient Quantum Circuit Synthesis for Deterministic Dicke State Preparation

    quant-ph 2025-05 conditional novelty 6.0 of 10

    Deterministic quantum circuits prepare Dicke states in depth O(log k log(n/k)+k) with all-to-all connectivity and O(k log(n/k)+n_2) or O(n_2) on an n1 x n2 grid, with lower bounds showing near-optimality in several regimes.

  5. Reducing Circuit Depth in Quantum State Preparation for Quantum Simulation Using Measurements and Feedforward

    quant-ph 2025-01 conditional novelty 6.0 of 10

    Adaptive circuits with unary encoding prepare sparse states, Slater determinant sums, and Bethe wavefunctions in logarithmic or constant depth, trading circuit depth for extra width.

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