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Related papers: Experimental Gaussian Boson Sampling

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Evaluating the Torontonian function is a central computational challenge in the simulation of Gaussian Boson Sampling (GBS) with threshold detection. In this work, we propose a recursive algorithm providing a polynomial speedup in the exact…

Quantum Physics · Physics 2022-11-16 Ágoston Kaposi , Zoltán Kolarovszki , Tamás Kozsik , Zoltán Zimborás , Péter Rakyta

Compressed sensing (CS) is a powerful method routinely employed to accelerate image acquisition. It is particularly suited to situations when the image under consideration is sparse but can be sampled in a basis where it is non-sparse. Here…

Image and Video Processing · Electrical Eng. & Systems 2022-07-18 Xudong Lv , Ashok Ajoy

Fast and precise characterization of Gaussian states is crucial for their effective use in quantum technologies. In this work, we apply a multi-parameter moment-based estimation method that enables rapid and accurate determination of…

Gaussian processes (GPs) are widely used in nonparametric regression, classification and spatio-temporal modeling, motivated in part by a rich literature on theoretical properties. However, a well known drawback of GPs that limits their use…

Methodology · Statistics 2011-06-29 Anjishnu Banerjee , David Dunson , Surya Tokdar

Boson sampling is a problem for which quantum devices could prove to go beyond classical computing using only linear optics and photon preparation and counting. While theoretically important, there is a lack of practical applications for…

Quantum Physics · Physics 2019-12-09 Juan Carlos Garcia-Escartin

Boson sampling is one of the leading protocols for demonstrating a quantum advantage, but the theory of how this protocol responds to noise is still incomplete. We extend the theory of classical simulation of boson sampling with partial…

Quantum Physics · Physics 2025-03-07 S. N. van den Hoven , E. Kanis , J. J. Renema

We present an experimental demonstration of boson sampling enhanced by optical feedback lines, a novel approach that introduces temporal correlations among photons to amplify computational complexity. We utilize a 25-mode femtosecond…

Spin-squeezed states constitute a valuable entanglement resource capable of surpassing the standard quantum limit (SQL). However, spin-squeezed states only enable sub-SQL uncertainty within a narrow parametric window near some specific…

Quantum Physics · Physics 2025-10-10 Jinye Wei , Jungeng Zhou , Yi Shen , Jiahao Huang , Chaohong Lee

We study the classical complexity of the exact Boson Sampling problem where the objective is to produce provably correct random samples from a particular quantum mechanical distribution. The computational framework was proposed by Aaronson…

Data Structures and Algorithms · Computer Science 2017-10-19 Peter Clifford , Raphaël Clifford

Probabilistic heralded Gaussification of quantum states of light is an important ingredient of protocols for distillation of continuous variable entanglement and squeezing. An elementary step of heralded Gaussification protocol consists of…

Quantum Physics · Physics 2024-12-17 Martin Dostál , Miroslav Ježek , Jaromír Fiurášek , Jan Bílek

The implementation of large-scale universal quantum computation represents a challenging and ambitious task on the road to quantum processing of information. In recent years, an intermediate approach has been pursued to demonstrate quantum…

Since its introduction Boson Sampling has been the subject of intense study in the world of quantum computing. The task is to sample independently from the set of all $n \times n$ submatrices built from possibly repeated rows of a larger $m…

Quantum Physics · Physics 2020-05-27 Peter Clifford , Raphaël Clifford

We introduce matrix quantum phase-space distributions. These extend the idea of a quantum phase-space representation via projections onto a density matrix of global symmetry variables. The method is applied to verification of low-loss…

Quantum Physics · Physics 2025-03-18 Peter D. Drummond , Alexander S. Dellios , Margaret D. Reid

We present an architecture for the generation of GKP states in which quadrature squeezing operations are used to control the average photon number statistics of probabilistic photon number measurements on Gaussian resource states.…

Quantum Physics · Physics 2025-12-03 Paul Renault , Patrick Yard , Raphael Pooser , Hussain Zaidi

Frequency-bin qudits constitute a promising tool for quantum information processing, but their high dimensionality can make for tedious characterization measurements. Here we introduce and compare compressive sensing and Bayesian mean…

Squeezed states of light constitute an important nonclassical resource in the field of high-precision measurements, e.g. gravitational wave detection, as well as in the field of quantum information, e.g. for teleportation, quantum…

Quantum Physics · Physics 2015-05-14 Moritz Mehmet , Henning Vahlbruch , Nico Lastzka , Karsten Danzmann , Roman Schnabel

Gibbs states (i.e., thermal states) can be used for several applications such as quantum simulation, quantum machine learning, quantum optimization, and the study of open quantum systems. Moreover, semi-definite programming, combinatorial…

Quantum Physics · Physics 2024-12-20 Norhan M. Eassa , Mahmoud M. Moustafa , Arnab Banerjee , Jeffrey Cohn

Analyzing the properties of complex quantum systems is crucial for further development of quantum devices, yet this task is typically challenging and demanding with respect to required amount of measurements. A special attention to this…

The implementation of cyber-physical systems in real-world applications is challenged by safety requirements in the presence of sensor threats. Most cyber-physical systems, especially multi-sensor systems, struggle to detect sensor attacks…

Systems and Control · Electrical Eng. & Systems 2025-08-26 Xingzhou Chen , Nachuan Yang , Peihu Duan , Shilei Li , Ling Shi

High-precision measurements require optimal setups and analysis tools to achieve continuous improvements. Systematic corrections need to be modeled with high accuracy and known uncertainty to reconstruct underlying physical phenomena. To…

Data Analysis, Statistics and Probability · Physics 2022-05-31 Max Lamparth , Mattis Bestehorn , Bastian Märkisch
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