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Exploiting dynamic quantum circuits in a quantum algorithm with superconducting qubits

1 Pith paper cite this work. Polarity classification is still indexing.

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abstract

The execution of quantum circuits on real systems has largely been limited to those which are simply time-ordered sequences of unitary operations followed by a projective measurement. As hardware platforms for quantum computing continue to mature in size and capability, it is imperative to enable quantum circuits beyond their conventional construction. Here we break into the realm of dynamic quantum circuits on a superconducting-based quantum system. Dynamic quantum circuits involve not only the evolution of the quantum state throughout the computation, but also periodic measurements of a subset of qubits mid-circuit and concurrent processing of the resulting classical information within timescales shorter than the execution times of the circuits. Using noisy quantum hardware, we explore one of the most fundamental quantum algorithms, quantum phase estimation, in its adaptive version, which exploits dynamic circuits, and compare the results to a non-adaptive implementation of the same algorithm. We demonstrate that the version of real-time quantum computing with dynamic circuits can offer a substantial and tangible advantage when noise and latency are sufficiently low in the system, opening the door to a new realm of available algorithms on real quantum systems.

fields

quant-ph 1

years

2025 1

verdicts

CONDITIONAL 1

representative citing papers

Mid-circuit measurement as an algorithmic primitive

quant-ph · 2025-05-30 · conditional · novelty 4.0

A single-ancilla Hadamard test post-selects a QAOA state toward low-energy answers, but the implementation sets its parameters from the exact ground energy, making the convergence demonstration self-referential.

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  • Mid-circuit measurement as an algorithmic primitive quant-ph · 2025-05-30 · conditional · none · ref 10 · internal anchor

    A single-ancilla Hadamard test post-selects a QAOA state toward low-energy answers, but the implementation sets its parameters from the exact ground energy, making the convergence demonstration self-referential.