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Related papers: Universalizing Analog Quantum Simulators

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Making quantum mechanical equations and concepts come to life through interactive simulation and visualization are commonplace for augmenting learning and teaching. However, graphical visualizations nearly always exhibit a set of hard-coded…

Quantum states are successfully reconstructed using the maximum likelihood estimation on the subspace where the measured projectors reproduce the identity operator. Reconstruction corresponds to normalization of incompatible observations.…

Quantum Physics · Physics 2008-11-26 Z. Hradil , J. Summhammer , H. Rauch

A quantum processor is a programmable quantum circuit in which both the data and the program, which specifies the operation that is carried out on the data, are quantum states. We study the situation in which we want to use such a processor…

Quantum Physics · Physics 2009-11-11 Mark Hillery , Mario Ziman , Vladimir Buzek

Modelling quantum devices is to find a model according to quantum theory that can explain the result of experiments in a quantum device. We find that usually we cannot correctly identify the model describing the actual physics of the device…

Quantum Physics · Physics 2019-10-08 Hang Ren , Ying Li

The standard uncertainty relations (UR) in quantum mechanics are typically used for unbounded operators (like the canonical pair). This implies the need for the control of the domain problems. On the other hand, the use of (possibly…

Mathematical Physics · Physics 2016-12-21 Andrzej Herdegen , Piotr Ziobro

Quantum process tomography is an experimental technique to fully characterize an unknown quantum process. Standard quantum process tomography suffers from exponentially scaling of the number of measurements with the increasing system size.…

Quantum Physics · Physics 2022-08-02 Shichuan Xue , Yong Liu , Yang Wang , Pingyu Zhu , Chu Guo , Junjie Wu

Simulating the stochastic evolution of real quantities on a digital computer requires a trade-off between the precision to which these quantities are approximated, and the memory required to store them. The statistical accuracy of the…

Quantum Physics · Physics 2017-10-16 Andrew J. P. Garner , Qing Liu , Jayne Thompson , Vlatko Vedral , Mile Gu

Some popular Machine Learning Uncertainty Quantification (ML-UQ) calibration statistics do not have predefined reference values and are mostly used in comparative studies. In consequence, calibration is almost never validated and the…

Machine Learning · Statistics 2024-06-25 Pascal Pernot

A quantum processor (the programmable gate array) is a quantum network with a fixed structure. A space of states is represented as tensor product of data and program registers. Different unitary operations with the data register correspond…

Quantum Physics · Physics 2007-05-23 Alexander Yu. Vlasov

Nuclear magnetic resonance techniques are used to realize a quantum algorithm experimentally. The algorithm allows a simple NMR quantum computer to determine global properties of an unknown function requiring fewer function ``calls'' than…

Quantum Physics · Physics 2009-10-31 Isaac L. Chuang , Lieven M. K. Vandersypen , Xinlan Zhou , Debbie W. Leung , Seth Lloyd

We investigate the tomography of unknown unitary quantum processes within the framework of a finite-dimensional Wigner-type representation. This representation provides a rich visualization of quantum operators by depicting them as shapes…

Quantum Physics · Physics 2024-12-19 Amit Devra , Léo Van Damme , Frederik vom Ende , Emanuel Malvetti , Steffen J. Glaser

Simulation models often have parameters as input and return outputs to understand the behavior of complex systems. Calibration is the process of estimating the values of the parameters in a simulation model in light of observed data from…

Methodology · Statistics 2024-11-15 Özge Sürer

The understanding of symmetry operations has brought enormous advancements in physics, ranging from elementary particle to condensed matter systems. In quantum mechanics, symmetry operations are described by either unitary or antiunitary…

Measuring expectation values of observables is an essential ingredient in variational quantum algorithms. A practical obstacle is the necessity of a large number of measurements for statistical convergence to meet requirements of precision,…

Quantum Physics · Physics 2022-09-07 Masaya Kohda , Ryosuke Imai , Keita Kanno , Kosuke Mitarai , Wataru Mizukami , Yuya O. Nakagawa

Analog quantum simulation is widely considered a step on the path to fault tolerant quantum computation. If based on current noisy hardware, the accuracy of an analog simulator will degrade after just a few time steps, especially when…

Quantum Physics · Physics 2020-07-01 Nathan K. Lysne , Kevin W. Kuper , Pablo M. Poggi , Ivan H. Deutsch , Poul S. Jessen

Quantum computing, with its potential to enhance various machine learning tasks, allows significant advancements in kernel calculation and model precision. Utilizing the one-class Support Vector Machine alongside a quantum kernel, known for…

We address the problem of estimating the expectation value <O> of an arbitrary operator O via a universal measuring apparatus that is independent of O, and for which the expectation values for different operators are obtained by changing…

Quantum Physics · Physics 2007-05-23 G. M. D'Ariano , P. Perinotti , M. F. Sacchi

Operating quantum sensors and quantum computers would make data in the form of quantum states available for purely quantum processing, opening new avenues for studying physical processes and certifying quantum technologies. In this…

Quantum embedding is an appealing route to fragment a large interacting quantum system into several smaller auxiliary `cluster' problems to exploit the locality of the correlated physics. In this work we critically review approaches to…

Strongly Correlated Electrons · Physics 2023-07-19 Max Nusspickel , Basil Ibrahim , George H. Booth

Atomistic simulations often rely on interatomic potentials to access greater time- and length- scales than those accessible to first principles methods such as density functional theory (DFT). However, since a parameterised potential…

Materials Science · Physics 2024-10-08 I. R. Best , T. J. Sullivan , J. R. Kermode