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The indistinguishability of quantum particles is widely used as a resource for the generation of entanglement. Linear quantum networks (LQNs), in which identical particles linearly evolve to arrive at multimode detectors, exploit the…

Quantum Physics · Physics 2021-12-30 Seungbeom Chin , Yong-Su Kim , Sangmin Lee

Quantum communication relies on the existence of entanglement between two nodes of a network. However, due to its fragile nature, it is nearly impossible to establish entanglement at large distances through the direct transmission of…

Quantum Physics · Physics 2021-10-18 Sowmitra Das , Md. Saifur Rahman , Mahbub Majumdar

Quantum entanglement is a useful resource for implementing communication tasks. However, for the resource to be useful in practice, it needs to be accessible by parties with bounded computational resources. Computational entanglement…

Quantum Physics · Physics 2025-09-29 Ilia Ryzov , Faedi Loulidi , David Elkouss

We investigate entanglement sharing in a two-qubit sequential measurement scenario using three complementary classical correlation metrics: mutual information (I), sum of conditional probabilities (S), and the Pearson correlation…

Quantum Physics · Physics 2025-10-06 Zinuo Cai , Changliang Ren

In this paper we introduce a measure of genuine quantum incompatibility in the estimation task of multiple parameters, that has a geometric character and is backed by a clear operational interpretation. This measure is then applied to some…

Quantum Physics · Physics 2021-06-22 Federico Belliardo , Vittorio Giovannetti

Multi-task learning of dense prediction tasks, by sharing both the encoder and decoder, as opposed to sharing only the encoder, provides an attractive front to increase both accuracy and computational efficiency. When the tasks are similar,…

Computer Vision and Pattern Recognition · Computer Science 2022-08-22 Naresh Kumar Gurulingan , Elahe Arani , Bahram Zonooz

Quantum resource theories allow us to quantify a useful quantum phenomenon, to develop new protocols for its detection and determine the exact processes that maximize its use for practical tasks. These theories aim at transforming physical…

Quantum Physics · Physics 2022-11-16 Abdallah Slaoui

Quantum systems may contain underlying correlations which are inaccessible to computationally bounded observers. We capture this distinction through a framework that analyses bipartite states only using efficiently implementable quantum…

Quantum Physics · Physics 2026-04-20 Álvaro Yángüez , Noam Avidan , Jan Kochanowski , Thomas A. Hahn

Entanglement-based quantum networks exhibit a unique flexibility in the choice of entangled resource states that are then locally manipulated by the nodes to fulfill any request in the network. Furthermore, this manipulation is not uniquely…

Quantum Physics · Physics 2025-02-04 Maria Flors Mor-Ruiz , Julius Wallnöfer , Wolfgang Dür

Quantum-correlated networks distribute quantum resources such as squeezed and entangled states. These states are central to modern quantum technology, including photonic quantum computing, quantum communications, non-destructive biological…

Quantum Physics · Physics 2026-03-24 Stephan Grebien , Julian Gurs , Roman Schnabel , Mikhail Korobko

A future quantum network will consist of quantum processors that are connected by quantum channels, just like conventional computers are wired up to form the Internet. In contrast to classical devices, however, the entanglement and…

Quantum Physics · Physics 2022-12-28 Andreas Reiserer

This work addresses the complexities involved in designing distributed quantum algorithms, highlighting that quantum entanglement does not bypass the Fischer-Lynch-Paterson (FLP) impossibility theorem in asynchronous networks. Although…

Quantum Physics · Physics 2024-11-08 Chandrashekar Radhakrishnan , Yuhang Zheng , Olivier Marin

Entanglement is known to significantly improve the performance (separately) of communication and detection schemes that utilize quantum resources. This work explores the simultaneous utility of quantum entanglement for (joint) communication…

Quantum Physics · Physics 2025-10-22 Yuhang Yao , Syed A. Jafar

Connecting multiple smaller qubit modules by generating high-fidelity entangled states is a promising path for scaling quantum computing hardware. The performance of such a modular quantum computer is highly dependent on the quality and…

Multi-task learning (MTL) improves generalization and data efficiency by jointly learning related tasks through shared representations. In the widely used hard-parameter-sharing setting, a shared backbone is combined with task-specific…

Machine Learning · Computer Science 2026-04-16 Hevish Cowlessur , Chandra Thapa , Tansu Alpcan , Seyit Camtepe

The ability to generate bipartite entanglement in quantum computing technologies is widely regarded as pivotal. However, the role of genuinely multipartite entanglement is much less understood than bipartite entanglement, particularly in…

Quantum Physics · Physics 2025-02-24 Gopal Chandra Santra , Sudipto Singha Roy , Daniel J. Egger , Philipp Hauke

Measurement-Based Quantum Computing (MBQC) is an alternative to the quantum circuit model, whereby the computation proceeds via measurements on an entangled resource state. Noise processes are a major experimental challenge to the…

Quantum Physics · Physics 2017-04-25 Naïri Usher , Dan E. Browne

Quantum Local Area Networks (QLANs) represent a promising building block for larger scale quantum networks with the ambitious goal -- in a long time horizon -- of realizing a Quantum Internet. Surprisingly, the physical topology of a QLAN…

The development of quantum algorithms and protocols calls for adequate modelling and verification techniques, which requires abstracting and focusing on the basic features of quantum concurrent systems, like CCS and CSP have done for their…

Logic in Computer Science · Computer Science 2024-08-28 Lorenzo Ceragioli , Fabio Gadducci , Giuseppe Lomurno , Gabriele Tedeschi

Quantum neural networks combine quantum computing with advanced data-driven methods, offering promising applications in quantum machine learning. However, the optimal paradigm for balancing trainability and expressivity in QNNs remains an…

Quantum Physics · Physics 2025-08-05 Hongshun Yao , Xia Liu , Mingrui Jing , Guangxi Li , Xin Wang