Dynamical Casimir effect entangles artificial atoms

We show that the physics underlying the dynamical Casimir effect may generate multipartite quantum correlations. To achieve it, we propose a circuit quantum electrodynamics (cQED) scenario involving superconducting quantum interference devices (SQUIDs), cavities, and superconducting qubits, also called artificial atoms. Our results predict the generation of highly entangled states for two and three superconducting qubits in different geometric configurations with realistic parameters. This proposal paves the way for a scalable method of multipartite entanglement generation in cavity networks through dynamical Casimir physics.Comment: Improved version and references added. Accepted for publication in Physical Review Letter

Disclosing hidden information in the quantum Zeno effect: Pulsed measurement of the quantum time of arrival

Repeated measurements of a quantum particle to check its presence in a region of space was proposed long ago [G. R. Allcock, Ann. Phys. {\bf 53}, 286 (1969)] as a natural way to determine the distribution of times of arrival at the orthogonal subspace, but the method was discarded because of the quantum Zeno effect: in the limit of very frequent measurements the wave function is reflected and remains in the original subspace. We show that by normalizing the small bits of arriving (removed) norm, an ideal time distribution emerges in correspondence with a classical local-kinetic-energy distribution.Comment: 5 pages, 4 figures, minor change

Entanglement Equivalence of NN-qubit Symmetric States

We study the interconversion of multipartite symmetric $N$-qubit states under stochastic local operations and classical communication (SLOCC). We demonstrate that if two symmetric states can be connected with a nonsymmetric invertible local operation (ILO), then they belong necessarily to the separable, W, or GHZ entanglement class, establishing a practical method of discriminating subsets of entanglement classes. Furthermore, we prove that there always exists a symmetric ILO connecting any pair of symmetric $N$-qubit states equivalent under SLOCC, simplifying the requirements for experimental implementations of local interconversion of those states.Comment: Minor correction

The circular economy and sustainability: a systematic literature review

The interest of this study lies in the fact that the transition from a linear to a circular economy is of key interest in relevant business and academic fields, although the circular economy is an emerging issue and theoretical and empirical research has been limited until recently. However, circular business models are receiving more and more attention, and it is therefore strategically necessary to develop tools that facilitate their implementation. Therefore, because of increasing interest amongst research in the circular economy and sustainability, the purpose of the present study and its strength lies in the systematic presentation of both of these specific academic streams. The approach was qualitative and based on a systematic literature review. We examined several areas in which the circular economy has a place. We highlight sustainability, consumer behaviour, innovation, remanufacturing, operations management, supply chains, intellectual capital, 3D printing, big data, and recycling. We also consider drivers, challenges, the relationship between circular economy and small to medium-sized enterprises, and the influence of circular economy in specific sectors such as textiles and food. It is hoped that the study will facilitate a possible sustainable solution that contrasts with the current linear model of production and resource management. The circular economy has the potential to create positive synergies in economic, social, and environmental areas, despite its recent origin © 2022, Cuadernos de Gestion.All Rights Reserve

Dynamics of momentum entanglement in lowest-order QED

We study the dynamics of momentum entanglement generated in the lowest-order QED interaction between two massive spin-1/2 charged particles, which grows in time as the two fermions exchange virtual photons. We observe that the degree of generated entanglement between interacting particles with initial well-defined momentum can be infinite. We explain this divergence in the context of entanglement theory for continuous variables, and show how to circumvent this apparent paradox. Finally, we discuss two different possibilities of transforming momentum into spin entanglement, through dynamical operations or through Lorentz boosts.Comment: 10 pages and 7 figures. Accepted in PR

Design considerations for engineering 3D models to study vascular pathologies in vitro

Many cardiovascular diseases (CVD) are driven by pathological remodelling of blood vessels, which can lead to aneurysms, myocardial infarction, ischaemia and strokes. Aberrant remodelling is driven by changes in vascular cell behaviours combined with degradation, modification, or abnormal deposition of extracellular matrix (ECM) proteins. The underlying mechanisms that drive the pathological remodelling of blood vessels are multifaceted and disease specific; however, unravelling them may be key to developing therapies. Reductionist models of blood vessels created in vitro that combine cells with biomaterial scaffolds may serve as useful analogues to study vascular disease progression in a controlled environment. This review presents the main considerations for developing such in vitro models. We discuss how the design of blood vessel models impacts experimental readouts, with a particular focus on the maintenance of normal cellular phenotypes, strategies that mimic normal cell-ECM interactions, and approaches that foster intercellular communication between vascular cell types. We also highlight how choice of biomaterials, cellular arrangements and the inclusion of mechanical stimulation using fluidic devices together impact the ability of blood vessel models to mimic in vivo conditions. In the future, by combining advances in materials science, cell biology, fluidics and modelling, it may be possible to create blood vessel models that are patient-specific and can be used to develop and test therapies

Digital quantum simulation of spin models with circuit quantum electrodynamics

Systems of interacting quantum spins show a rich spectrum of quantum phases and display interesting many-body dynamics. Computing characteristics of even small systems on conventional computers poses significant challenges. A quantum simulator has the potential to outperform standard computers in calculating the evolution of complex quantum systems. Here, we perform a digital quantum simulation of the paradigmatic Heisenberg and Ising interacting spin models using a two transmon-qubit circuit quantum electrodynamics setup. We make use of the exchange interaction naturally present in the simulator to construct a digital decomposition of the model-specific evolution and extract its full dynamics. This approach is universal and efficient, employing only resources which are polynomial in the number of spins and indicates a path towards the controlled simulation of general spin dynamics in superconducting qubit platforms.Comment: 12 pages, 9 figure

Real-time diameter of the fetal aorta from ultrasound

The automatic analysis of ultrasound sequences can substantially improve the efficiency of clinical diagnosis. This article presents an attempt to automate the challenging task of measuring the vascular diameter of the fetal abdominal aorta from ultrasound images. We propose a neural network architecture consisting of three blocks: a convolutional neural network (CNN) for the extraction of imaging features, a convolution gated recurrent unit (C-GRU) for exploiting the temporal redundancy of the signal, and a regularized loss function, called CyclicLoss, to impose our prior knowledge about the periodicity of the observed signal. The solution is investigated with a cohort of 25 ultrasound sequences acquired during the third-trimester pregnancy check, and with 1000 synthetic sequences. In the extraction of features, it is shown that a shallow CNN outperforms two other deep CNNs with both the real and synthetic cohorts, suggesting that echocardiographic features are optimally captured by a reduced number of CNN layers. The proposed architecture, working with the shallow CNN, reaches an accuracy substantially superior to previously reported methods, providing an average reduction of the mean squared error from 0.31 (state-of-the-art) to 0.09 $$ackslashmathrmmm^2$$mm2, and a relative error reduction from 8.1 to 5.3%. The mean execution speed of the proposed approach of 289 frames per second makes it suitable for real-time clinical use