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Quantum-enhanced metrology infers an unknown quantity with accuracy beyond the standard quantum limit (SQL). Feedback-based metrological techniques are promising for beating the SQL but devising the feedback procedures is difficult and…

Quantum Physics · Physics 2015-03-19 Alexander Hentschel , Barry C. Sanders

Quantum metrology leverages quantum resources such as entanglement and squeezing to enhance parameter estimation precision beyond classical limits. While optimal quantum control strategies can assist to reach or even surpass the Heisenberg…

Quantum Physics · Physics 2025-10-17 Qifei Wei , Shengshi Pang

Achieving ultimate bounds in estimation processes is the main objective of quantum metrology. In this context, several problems require measurement of multiple parameters by employing only a limited amount of resources. To this end,…

Estimation of the coin parameter(s) is an important part of the problem of implementing more robust schemes for quantum simulation using quantum walks. We present the estimation of the quantum coin parameter used for one-dimensional…

Quantum Physics · Physics 2020-07-10 Parth Rajauria , Prateek Chawla , C. M. Chandrashekar

We present a novel Adaptive Distribution Generator that leverages a quantum walks-based approach to generate high precision and efficiency of target probability distributions. Our method integrates variational quantum circuits with…

Quantum Physics · Physics 2026-04-10 Yen-Jui Chang , Wei-Ting Wang , Chen-Yu Liu , Yun-Yuan Wang , Ching-Ray Chang

Differential evolution (DE) is a population based evolutionary algorithm widely used for solving multidimensional global optimization problems over continuous spaces. However, the design of its operators makes it unsuitable for many…

Neural and Evolutionary Computing · Computer Science 2011-05-17 Ashish Ranjan Hota , Ankit Pat

Adaptive feedback schemes are promising for quantum-enhanced measurements yet are complicated to design. Machine learning can autonomously generate algorithms in a classical setting. Here we adapt machine learning for quantum information…

Quantum Physics · Physics 2010-02-25 Alexander Hentschel , Barry C. Sanders

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected Variational Quantum Dynamics (pVQD) algorithm, that performs a global optimization with linear…

Quantum Physics · Physics 2025-02-20 David Linteau , Stefano Barison , Netanel Lindner , Giuseppe Carleo

In this letter we revisit the problem of optimal design of quantum tomographic experiments. In contrast to previous approaches where an optimal set of measurements is decided in advance of the experiment, we allow for measurements to be…

Quantum Physics · Physics 2017-02-28 Ferenc Huszár , Neil M. T. Houlsby

Relevant metrological scenarios involve the simultaneous estimation of multiple parameters. The fundamental ingredient to achieve quantum-enhanced performances is based on the use of appropriately tailored quantum probes. However, reaching…

Quantum sensing harnesses the unique properties of quantum systems to enable precision measurements of physical quantities such as time, magnetic and electric fields, acceleration, and gravitational gradients well beyond the limits of…

Quantum Physics · Physics 2025-07-23 Ivana Nikoloska , Ruud Van Sloun , Osvaldo Simeone

Differentiable models of physical systems provide a powerful platform for gradient-based algorithms, with particular impact on parameter estimation and optimal control. Quantum systems present a particular challenge for such…

Quantum Physics · Physics 2025-09-09 David L. Craig , Natalia Ares , Erik M. Gauger

We investigate critical quantum metrology,that is the estimation of parameters in many-body systems close to a quantum critical point, through the lens of Bayesian inference theory. We first derive a no-go result stating that any…

Quantum Physics · Physics 2023-10-31 Raffaele Salvia , Mohammad Mehboudi , Martí Perarnau-Llobet

We present a quantum algorithm to estimate parameters at the quantum metrology limit using deterministic quantum computation with one bit. When the interactions occurring in a quantum system are described by a Hamiltonian $H= \theta H_0$,…

Quantum Physics · Physics 2008-07-03 Rolando D. Somma , Sergio Boixo

As Noisy Intermediate-Scale Quantum (NISQ) devices grow in number of qubits, determining good or even adequate parameter configurations for a given application, or for device calibration, becomes a cumbersome task. An evolutionary algorithm…

Quantum Physics · Physics 2021-07-15 Luke Mortimer , Marta P. Estarellas , Timothy P. Spiller , Irene D'Amico

Variational quantum metrology represents a powerful tool for optimizing generic estimation strategies, combining the principles of variational optimization with the techniques of quantum metrology. Such optimization procedures result…

Realisation of experiments even on small and medium-scale quantum computers requires an optimisation of several parameters to achieve high-fidelity operations. As the size of the quantum register increases, the characterisation of quantum…

Quantum Physics · Physics 2020-08-11 F. Martínez-García , D. Vodola , M. Müller

The Darwinian paradigm of biological evolution is based on the separability of the variation and selection processes. As a result, the population thinking had always been an integral part of the Darwinian approach. I propose an alternative…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Vasily Ogryzko

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

High precision measurements are essential to solve major scientific and technological challenges, from gravitational wave detection to healthcare diagnostics. Quantum sensing delivers greater precision, but an in-depth optimisation of…

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