English
Related papers

Related papers: Testing the Robustness of Robust Phase Estimation

200 papers

As experimental platforms for quantum information processing continue to mature, characterization of the quality of unitary gates that can be applied to their quantum bits (qubits) becomes essential. Eventually, the quality must be…

Quantum Phase Estimation (QPE) routines are known to fail probabilistically even with perfect gates and input states. This effect stems from an incompatibility of finite-sized quantum registers to capture a phase within QPE with phase…

Quantum Physics · Physics 2025-08-12 Harriet Apel , Cristian L. Cortes , Jessica Lemieux , Mark Steudtner

Coherent control errors, for which ideal Hamiltonians are perturbed by unknown multiplicative noise terms, are a major obstacle for reliable quantum computing. In this paper, we present a framework for analyzing the robustness of quantum…

Quantum Physics · Physics 2024-12-04 Julian Berberich , Daniel Fink , Christian Holm

As quantum circuits become more integrated and complex, additional error sources that were previously insignificant start to emerge. Consequently, the fidelity of quantum gates benchmarked under pristine conditions falls short of predicting…

Quantum phase estimation (QPE) serves as a building block of many different quantum algorithms and finds important applications in computational chemistry problems. Despite the rapid development of quantum hardware, experimental…

Quantum Physics · Physics 2024-03-01 Kentaro Yamamoto , Samuel Duffield , Yuta Kikuchi , David Muñoz Ramo

Quantifying coherence is an essential endeavour for both quantum foundations and quantum technologies. Here the robustness of coherence is defined and proven a full monotone in the context of the recently introduced resource theories of…

Due to its significance as a subroutine, in this work, we consider the coherent version of the quantum phase estimation problem, where given an arbitrary input state and black-box access to unitaries $U$ and controlled-$U$, the goal is to…

Quantum Physics · Physics 2026-04-20 Dhrumil Patel , Shi Jie Samuel Tan , Yigit Subasi , Andrew T. Sornborger

Continuous phase estimation is known to be superior in accuracy as compared to static estimation. The estimation process is, however, desired to be made robust to uncertainties in the underlying parameters. Here, homodyne phase estimation…

Optimization and Control · Mathematics 2015-09-14 Shibdas Roy , Obaid Ur Rehman , Ian R. Petersen , Elanor H. Huntington

Quantum phase estimation (QPE) is a key quantum algorithm, which has been widely studied as a method to perform chemistry and solid-state calculations on future fault-tolerant quantum computers. Recently, several authors have proposed…

Quantum Physics · Physics 2024-02-05 Nick S. Blunt , Laura Caune , Róbert Izsák , Earl T. Campbell , Nicole Holzmann

Near-term quantum computation holds potential across multiple application domains. However, imperfect preparation and evolution of states due to algorithmic and experimental shortcomings, characteristic in the near-term implementation,…

Typical quantum gate tomography protocols struggle with a self-consistency problem: the gate operation cannot be reconstructed without knowledge of the initial state and final measurement, but such knowledge cannot be obtained without…

Quantum Phase Estimation is a crucial component of several front-running quantum algorithms. Improving the efficiency and accuracy of QPE is currently a very active field of research. In this work, we present a hybrid quantum-classical…

Quantum Physics · Physics 2024-09-25 S. M. Lim , C. E. Susa , R. Cohen

Quantum computing has garnered attention for its potential to solve complex computational problems with considerable speedup. Despite notable advancements in the field, achieving meaningful scalability and noise control in quantum hardware…

Quantum Physics · Physics 2025-05-12 Eduardo Willwock Lussi , Rafael de Santiago , Eduardo Inacio Duzzioni

Randomized benchmarking (RB) is a widely used method for estimating the average fidelity of gates implemented on a quantum computing device. The stochastic error of the average gate fidelity estimated by RB depends on the sampling strategy…

Quantum Physics · Physics 2021-09-17 Toshinari Itoko , Rudy Raymond

The rapid development of noisy intermediate-scale quantum (NISQ) devices has raised the question of whether or not these devices will find commercial use. Unfortunately, a major shortcoming of many proposed NISQ-amenable algorithms, such as…

Quantum Physics · Physics 2021-10-22 Amara Katabarwa , Alex Kunitsa , Borja Peropadre , Peter Johnson

We introduce a novel family of protocols for entangling gates for neutral atom qubits based on the Rydberg blockade mechanism. These protocols realize controlled-phase gates through a series of global laser pulses that are on resonance with…

Quantum Physics · Physics 2023-06-16 Charles Fromonteil , Dolev Bluvstein , Hannes Pichler

State-of-the-art single-qubit gates on superconducting transmon qubits can achieve the fidelities required for error-corrected computations. However, parameter fluctuations due to qubit instabilities, environmental changes, and control…

It is well-known that adaptive homodyne estimation of continuously varying optical phase provides superior accuracy in the phase estimate as compared to adaptive or non-adaptive static estimation. However, most phase estimation schemes rely…

Optimization and Control · Mathematics 2015-09-14 Shibdas Roy , Ian R. Petersen , Elanor H. Huntington

Fastness and robustness are both critical in the implementation of high-fidelity gates for quantum computation, but in practice, a trade-off has to be made between them. In this paper, we investigate the underlying robust time-optimal…

Quantum Physics · Physics 2023-09-12 Xi Cao , Jiangyu Cui , Man Hong Yung , Re-Bing Wu

Accurate phase estimation -- the process of assigning phase values between $0$ and $2\pi$ to repetitive or periodic signals -- is a cornerstone in the analysis of oscillatory signals across diverse fields, from neuroscience to robotics,…

Signal Processing · Electrical Eng. & Systems 2026-03-19 Antonio Spallone , Marco Coraggio , Francesco De Lellis , Mario di Bernardo