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Quantum correlations are at the core of the power of quantum information and are necessary to reach a quantum computational advantage. In the context of continuous-variable quantum systems, another necessary ressource for quantum advantages…

Quantum Physics · Physics 2024-07-26 Carlos E. Lopetegui , Mathieu Isoard , Nicolas Treps , Mattia Walschaers

Despite their fundamental importance in dictating the quantum mechanical properties of a system, ground states of many-body local quantum Hamiltonians form a set of measure zero in the many-body Hilbert space. Hence determining whether a…

Disordered Systems and Neural Networks · Physics 2021-06-23 Michael Matty , Yi Zhang , T. Senthil , Eun-Ah Kim

We explore a supervised machine learning approach to estimate the entanglement entropy of multi-qubit systems from few experimental samples. We put a particular focus on estimating both aleatoric and epistemic uncertainty of the network's…

Quantum Physics · Physics 2024-01-04 Maximilian Rieger , Moritz Reh , Martin Gärttner

Quantum samplers are believed capable of sampling efficiently from distributions that are classically hard to sample from. We consider a sampler inspired by the classical Ising model. It is nonadaptive and therefore experimentally amenable.…

Quantum Physics · Physics 2019-07-17 Theodoros Kapourniotis , Animesh Datta

We propose two experimental schemes that can produce an arbitrary photon-number entangled state (PNES) in a finite dimension. This class of entangled states naturally includes non-Gaussian continuous-variable (CV) states that may provide…

Quantum Physics · Physics 2012-06-14 Su-Yong Lee , Jiyong Park , Hai-Woong Lee , Hyunchul Nha

Entanglement is one of the most fascinating features arising from quantum-mechanics and of great importance for quantum information science. Of particular interest are so-called hybrid-entangled states which have the intriguing property…

Entangled quantum states are essential ingredients for many quantum technologies, but they must be validated before they are used. As a full characterization is prohibitively resource-intensive, recent work has focused on developing methods…

Measurement of entanglement remains an important problem for quantum information. We present the design and simulation of an experimental method for entanglement estimation for a general multiqubit state. The system can be in a pure or a…

Quantum Physics · Physics 2012-11-09 E. C. Behrman , J. E. Steck

The continuous variable quantum computing platform constitutes a promising candidate for realizing quantum advantage, as exemplified in Gaussian Boson Sampling. While noise in the experiments makes the computation attainable for classical…

Quantum Physics · Physics 2025-08-11 Jonas Vinther , Michael James Kastoryano

In quantum metrology, measurements are usually treated as passive readout processes. Here we investigate whether post-selected von Neumann measurements (PVNMs) can be used as an active resource to reshape the nonclassical properties of a…

Quantum Physics · Physics 2026-04-21 Janarbek Yuanbek , Bruno Tenorio , Yusuf Turek

We investigate the quantum advantage that can arise in typical two-party communication scenarios, where the sender and the receiver are allowed to share prior correlations. Focusing on communication tasks constrained by the…

Quantum Physics · Physics 2026-03-20 Satyaki Manna , Ankush Pandit , Debashis Saha

In this paper, we present the first experimental demonstration on continuous variable quantum key distribution using determinant Einstein-Podolsky-Rosen entangled states of optical field. By means of the instantaneous measurements of the…

Quantum Physics · Physics 2015-05-30 Xiaolong Su , Wenzhe Wang , Yu Wang , Xiaojun Jia , Changde Xie , Kunchi Peng

We study the performance of an Ising spin network for quantum reservoir computing (QRC) in linear and non-linear memory tasks. We investigate the extent to which quantumness enhances performance by monitoring the behaviour of quantum…

Quantum Physics · Physics 2024-10-22 Youssef Kora , Hadi Zadeh-Haghighi , Terrence C Stewart , Khabat Heshami , Christoph Simon

Quantum machine learning is an approach that aims to improve the performance of machine learning methods by leveraging the properties of quantum computers. In quantum circuit learning (QCL), a supervised learning method that can be…

We present an optimal scheme to realize the transformations between single copies of two bipartite entangled states without classical communication between the sharing parties. The scheme achieves the upper bound for the success…

Quantum Physics · Physics 2008-12-17 Bing He , János A. Bergou

Recent advances in analog and digital quantum-simulation platforms have enabled exploration of the spectrum of entanglement Hamiltonians via variational algorithms. In this work we analyze the convergence properties of the variationally…

Quantum Physics · Physics 2025-05-16 Yanick S. Kind , Benedikt Fauseweh

Entanglement has been shown to be necessary for pure state quantum computation to have an advantage over classical computation. However, it remains open whether entanglement is necessary for quantum computers that use mixed states to also…

Quantum Physics · Physics 2019-07-22 Mithuna Yoganathan , Chris Cade

This Letter verifies the potential of several classes of entangled coherent state in well known quantum metrology which includes detection of classical external force, and shows that there is a class of entangled coherent state for the…

Quantum Physics · Physics 2012-01-10 Osamu Hirota , Kentaro Kato , Dan Murakami

These two accompanying papers treat two mode entanglement for systems of identical massive bosons and the relationship to spin squeezing and other quantum correlation effects. Entanglement is a key quantum feature of composite systems where…

Quantum Physics · Physics 2016-06-01 Bryan Dalton , John Goold , Barry Garraway , Margaret Reid

Statistical learning theory chiefly studies restricted hypothesis classes, particularly those with finite Vapnik-Chervonenkis (VC) dimension. The fundamental quantity of interest is the sample complexity: the number of samples required to…

Machine Learning · Computer Science 2008-07-10 David Soloveichik
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