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Related papers: Inference-Based Quantum Sensing

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Quantum Parameter Estimation (QPE) is important from the perspective of both fundamental quantum research and various practical applications of quantum technologies such as for developing optimal quantum control strategies. Standard and…

Quantum Physics · Physics 2024-07-18 Bijita Sarma , Junxin Chen , Sangkha Borah

Quantum sensing utilize quantum effects, such as entanglement and coherence, to measure physical signals. The performance of a sensing process is characterized by error which requires comparison to a true value. However, in practice, such a…

Quantum Physics · Physics 2024-10-29 Lian-Xiang Cui , Yi-Mu Du , C. P. Sun

We review and discuss the potential of using measurement-based elements in quantum communication schemes, where certain tasks are realized with the help of entangled resource states that are processed by measurements. We consider long-range…

Quantum Physics · Physics 2016-09-27 M. Zwerger , H. J. Briegel , W. Dür

The performance of a quantum sensor is fundamentally limited by noise. This noise is particularly damaging when it becomes correlated with the readout of a target signal, caused by fluctuations of the sensor's operating parameters. These…

Quantum-enhanced, idler-free sensing protocol to measure the response of a target object to the frequency of a probe in a noisy and lossy scenario is proposed. In this protocol, a target with frequency-dependent reflectivity embedded in a…

Quantum Physics · Physics 2022-11-15 Mateo Casariego , Yasser Omar , Mikel Sanz

Quantum metrology seeks to leverage the richness of quantum systems for making better measurements than are possible using only classical resources in order to gain a ``quantum advantage''. Quantum metrology schemes must also be resilient…

We use a meta-learning neural-network approach to analyse data from a measured quantum state. Once our neural network has been trained it can be used to efficiently sample measurements of the state in measurement bases not contained in the…

Quantum Physics · Physics 2021-07-01 Alistair W. R. Smith , Johnnie Gray , M. S. Kim

Starting from a simple estimation problem, here we propose a general approach for decoding quantum measurements from the perspective of information extraction. By virtue of the estimation fidelity only, we provide surprisingly simple…

Quantum Physics · Physics 2022-10-04 Huangjun Zhu

Quantum sensors typically translate external fields into a periodic response whose frequency is then determined by analyses performed in Fourier space. This allows for a linear inference of the parameters that characterize external signals.…

Quantum Physics · Physics 2021-08-27 R. Puebla , Y. Ban , J. F. Haase , M. B. Plenio , M. Paternostro , J. Casanova

In this work we introduce a general scheme for measurement based quantum computation in continuous variables. Our approach does not necessarily rely on the use of ancillary cluster states to achieve its aim, but rather on the detection of a…

Quantum Physics · Physics 2017-02-01 Giulia Ferrini , Jonathan Roslund , Francesco Arzani , Claude Fabre , Nicolas Treps

Quantum resources, such as entanglement, can decrease the uncertainty of a parameter-estimation procedure beyond what is classically possible. This phenomenon is well described for noiseless systems with asymptotically many measurement…

Quantum Physics · Physics 2021-08-09 Jason Saunders , Jean-Francois Van Huele

This paper proposes an intrinsic or background-independent quantum framework based on entangled state rather than absolute quantum state, it describes a quantum relative state between the under-study quantum system and the quantum measuring…

Quantum Physics · Physics 2026-03-13 M. J. Luo

Operator quantum error correction provides a unified framework for the known techniques of quantum error correction such as the standard error correction model, the method of decoherence-free subspaces, and the noiseless subsystem method.…

Quantum Physics · Physics 2014-04-25 Ri Qu , Bing-jian Shang , Yan-ru Bao , Yi-ping Ma

Quantum-enhanced metrology aims to estimate an unknown parameter such that the precision scales better than the shot-noise bound. Single-shot adaptive quantum-enhanced metrology (AQEM) is a promising approach that uses feedback to tweak the…

Quantum Physics · Physics 2016-10-17 Pantita Palittapongarnpim , Peter Wittek , Barry C. Sanders

Machine learning employs dynamical algorithms that mimic the human capacity to learn, where the reinforcement learning ones are among the most similar to humans in this respect. On the other hand, adaptability is an essential aspect to…

Quantum Physics · Physics 2018-10-15 F. Albarrán-Arriagada , J. C. Retamal , E. Solano , L. Lamata

Quantum coherence is a key resource in quantum information processing scenarios, and quantifying coherence is an important task for both quantum foundation and quantum technology. However, until now, all most of coherence measures are…

Quantum Physics · Physics 2017-10-24 Wei-Chen Wang , Mao-Fa Fang , Min Yu

Quantum sensing takes advantage of well controlled quantum systems for performing measurements with high sensitivity and precision. We have implemented a concept for quantum sensing with arbitrary frequency resolution, independent of the…

Quantum Physics · Physics 2017-06-07 J. M. Boss , K. S. Cujia , J. Zopes , C. L. Degen

Quantum sensing employs quantum resources of a sensor to attain a smaller estimation error of physical quantities than the limit constrained by classical physics. To measure a quantum reservoir, which is significant in decoherence control,…

Quantum Physics · Physics 2021-05-21 Wei Wu , Zhen Peng , Si-Yuan Bai , Jun-Hong An

We investigate in detail a recently introduced "coherent averaging scheme" in terms of its usefulness for achieving Heisenberg limited sensitivity in the measurement of different parameters. In the scheme, $N$ quantum probes in a product…

Quantum Physics · Physics 2023-07-19 Julien M. E. Fraïsse , Daniel Braun

We consider an unknown multivariate function representing a system-such as a complex numerical simulator-taking both deterministic and uncertain inputs. Our objective is to estimate the set of deterministic inputs leading to outputs whose…

Machine Learning · Statistics 2024-12-09 Romain Ait Abdelmalek-Lomenech , Julien Bect , Vincent Chabridon , Emmanuel Vazquez