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Quantum filtering is a signal processing technique that estimates the posterior state of a quantum system under continuous measurements and has become a standard tool in quantum information processing, with applications in quantum state…

Quantum Physics · Physics 2014-08-19 Mankei Tsang

A pair of conjugate observables, such as the quadrature amplitudes of harmonic motion, have fundamental fluctuations which are bound by the Heisenberg uncertainty relation. However, in a squeezed quantum state, fluctuations of a quantity…

Mesoscale and Nanoscale Physics · Physics 2015-12-16 J. -M. Pirkkalainen , E. Damskägg , M. Brandt , F. Massel , M. A. Sillanpää

Methods borrowed from the world of quantum information processing have lately been used to enhance the signal-to-noise ratio of quantum detectors. Here we analyze the use of stabilizer quantum error-correction codes for the purpose of…

Quantum Physics · Physics 2013-10-15 Roee Ozeri

We establish general limits on how precise a parameter, e.g. frequency or the strength of a magnetic field, can be estimated with the aid of full and fast quantum control. We consider uncorrelated noisy evolutions of N qubits and show that…

Quantum Physics · Physics 2017-09-07 Pavel Sekatski , Michalis Skotiniotis , Janek Kołodyński , Wolfgang Dür

The effective quantum field theory description of gravity, despite its non-renormalizability, allows for predictions beyond classical general relativity. As we enter the age of gravitational wave astronomy, an important and timely question…

General Relativity and Quantum Cosmology · Physics 2022-12-21 Thiago Guerreiro , Francesco Coradeschi , Antonia Micol Frassino , Jennifer Rittenhouse West , Enrico Junior Schioppa

In the last years several estimation strategies have been formulated to determine the value of an unknown parameter in the most precise way, taking into account the presence of noise. These strategies typically rely on the use of quantum…

Quantum Physics · Physics 2021-08-31 Andrea Smirne , Andreas Lemmer , Martin B. Plenio , Susana F. Huelga

The ultrahigh-frequency (above 10 kHz) gravitational waves (GW) window provides a unique opportunity to detect primordial GWs, free from astrophysical foregrounds that dominate lower frequencies. A stochastic GW background in this range is…

General Relativity and Quantum Cosmology · Physics 2026-02-27 Xinyao Guo , Haixing Miao , Zhi-Wei Wang , Huan Yang , Ye-Ling Zhou

The report presents a general approach for estimating quantum information technologies by means of fuzzy quantum measurements. The developed methods are used for precision reconstruction of quantum states under conditions of significant…

Quantum Physics · Physics 2022-01-11 Yu. I. Bogdanov

Extracting useful signals is key to both classical and quantum technologies. Conventional noise filtering methods rely on different patterns of signal and noise in frequency or time domains, thus limiting their scope of application,…

Quantum Physics · Physics 2023-02-28 Yang Shen , Ping Wang , Chun Tung Cheung , Joerg Wachtrup , Ren-Bao Liu , Sen Yang

We quantify how squeezed light can reduce quantum measurement noise to levels below the standard quantum limit in impulse measurements with mechanical detectors. The broadband nature of the signal implies that frequency-dependent squeezing…

Quantum Physics · Physics 2025-07-17 Tsai-Chen Lee , Jacob L. Beckey , Giacomo Marocco , Daniel Carney

It is often said that measuring a system's position must disturb the complementary property, momentum, by some minimum amount due to the Heisenberg uncertainty principle. Using a "weak-measurement", this disturbance can be reduced. One…

Quantum Physics · Physics 2018-11-26 G. S. Thekkadath , F. Hufnagel , J. S. Lundeen

Quantum computing and quantum sensing represent two distinct frontiers of quantum information science. In this work, we harness quantum computing to solve a fundamental and practically important sensing problem: the detection of weak…

Quantum Physics · Physics 2025-01-15 Richard R. Allen , Francisco Machado , Isaac L. Chuang , Hsin-Yuan Huang , Soonwon Choi

In an idealistic setting, quantum metrology protocols allow to sense physical parameters with mean squared error that scales as $1/N^2$ with the number of particles involved---substantially surpassing the $1/N$-scaling characteristic to…

Quantum Physics · Physics 2015-01-05 Jan Kolodynski

The quest for precision in parameter estimation is a fundamental task in different scientific areas. The relevance of this problem thus provided the motivation to develop methods for the application of quantum resources to estimation…

Quantum Physics · Physics 2024-06-18 Valeria Cimini , Emanuele Polino , Mauro Valeri , Nicolò Spagnolo , Fabio Sciarrino

Besides their stunning physical properties which are unmatched in a classical world, squeezed states of electromagnetic radiation bear advanced application potentials in quantum information systems and precision metrology, including…

In the present contribution we discuss the role of experimental limitations in the classical limit problem. We studied some simple models and found that Quantum Mechanics does not re-produce classical mechanical predictions, unless we…

Quantum Physics · Physics 2020-11-09 Adélcio C. Oliveira , Z. T. Oliveira Junior , N. S. Correia

Quantum fluctuations constitute the primary noise barrier limiting cavity-based axion dark matter searches. In an experiment designed to mimic a real axion search, we employ a quantum-enhanced sensing technique to detect a synthetic…

Modern precision experiments often probe unknown classical fields with bosonic sensors in quantum-noise-limited regimes where vacuum fluctuations limit conventional readout. We introduce Quantum Signal Learning (QSL), a sensing framework…

Quantum Physics · Physics 2026-02-24 Jordan Cotler , Daine L. Danielson , Ishaan Kannan

Quantum finite frequency noise is one of fundamental aspects in quantum measurements performed during quantum information processing where currently Majorana bound states offer an efficient way to implement fault-tolerant quantum…

Mesoscale and Nanoscale Physics · Physics 2019-04-30 Sergey Smirnov

One of the key obstacles in traditional deep learning is the reduction in model transparency caused by increasingly intricate model functions, which can lead to problems such as overfitting and excessive confidence in predictions. With the…

Machine Learning · Computer Science 2025-07-22 Maximilian Wendlinger , Kilian Tscharke , Pascal Debus
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