scholarly journals Creation and control of high-dimensional multi-partite classically entangled light

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Yijie Shen ◽  
Isaac Nape ◽  
Xilin Yang ◽  
Xing Fu ◽  
Mali Gong ◽  
...  
Keyword(s):  
Degrees Of Freedom ◽  
State Of The Art ◽  
Structured Light ◽  
High Dimensional ◽  
Complete Set ◽  
Quantum Entangled States ◽  
Tomography Method ◽  
And Control ◽  
Light Beams ◽  
First Time

AbstractVector beams, non-separable in spatial mode and polarisation, have emerged as enabling tools in many diverse applications, from communication to imaging. This applicability has been achieved by sophisticated laser designs controlling the spin and orbital angular momentum, but so far is restricted to only two-dimensional states. Here we demonstrate the first vectorially structured light created and fully controlled in eight dimensions, a new state-of-the-art. We externally modulate our beam to control, for the first time, the complete set of classical Greenberger–Horne–Zeilinger (GHZ) states in paraxial structured light beams, in analogy with high-dimensional multi-partite quantum entangled states, and introduce a new tomography method to verify their fidelity. Our complete theoretical framework reveals a rich parameter space for further extending the dimensionality and degrees of freedom, opening new pathways for vectorially structured light in the classical and quantum regimes.

scholarly journals High-Dimensional Pixel Entanglement: Efficient Generation and Certification

Quantum ◽  
2020 ◽  
Vol 4 ◽  
pp. 376
Author(s):  
Natalia Herrera Valencia ◽  
Vatshal Srivastav ◽  
Matej Pivoluska ◽  
Marcus Huber ◽  
Nicolai Friis ◽  
...  
Keyword(s):  
Carrying Capacity ◽  
Communication Systems ◽  
Degrees Of Freedom ◽  
State Of The Art ◽  
Quality Measurement ◽  
High Dimensional ◽  
Single Photons ◽  
Spatial Mode ◽  
Classical Communication ◽  
Entanglement Of Formation

Photons offer the potential to carry large amounts of information in their spectral, spatial, and polarisation degrees of freedom. While state-of-the-art classical communication systems routinely aim to maximize this information-carrying capacity via wavelength and spatial-mode division multiplexing, quantum systems based on multi-mode entanglement usually suffer from low state quality, long measurement times, and limited encoding capacity. At the same time, entanglement certification methods often rely on assumptions that compromise security. Here we show the certification of photonic high-dimensional entanglement in the transverse position-momentum degree-of-freedom with a record quality, measurement speed, and entanglement dimensionality, without making any assumptions about the state or channels. Using a tailored macro-pixel basis, precise spatial-mode measurements, and a modified entanglement witness, we demonstrate state fidelities of up to 94.4% in a 19-dimensional state-space, entanglement in up to 55 local dimensions, and an entanglement-of-formation of up to 4 ebits. Furthermore, our measurement times show an improvement of more than two orders of magnitude over previous state-of-the-art demonstrations. Our results pave the way for noise-robust quantum networks that saturate the information-carrying capacity of single photons.

scholarly journals Subtitling 3D VR Content with Limited 6DoF: Presentation Modes and Guiding Methods

2021 ◽  
Vol 11 (16) ◽  
pp. 7472
Author(s):  
Mario Montagud ◽  
Cristian Hurtado ◽  
Juan Antonio De Rus ◽  
Sergi Fernández
Keyword(s):  
Degrees Of Freedom ◽  
State Of The Art ◽  
Presentation Mode ◽  
Multimedia Content ◽  
Video Content ◽  
Multimedia Services ◽  
Presentation Modes ◽  
6 Degrees Of Freedom ◽  
First Time ◽  
Access Services

All multimedia services must be accessible. Accessibility for multimedia content is typically provided by means of access services, of which subtitling is likely the most widespread approach. To date, numerous recommendations and solutions for subtitling classical 2D audiovisual services have been proposed. Similarly, recent efforts have been devoted to devising adequate subtitling solutions for VR360 video content. This paper, for the first time, extends the existing approaches to address the challenges remaining for efficiently subtitling 3D Virtual Reality (VR) content by exploring two key requirements: presentation modes and guiding methods. By leveraging insights from earlier work on VR360 content, this paper proposes novel presentation modes and guiding methods, to not only provide the freedom to explore omnidirectional scenes, but also to address the additional specificities of 3D VR compared to VR360 content: depth, 6 Degrees of Freedom (6DoF), and viewing perspectives. The obtained results prove that always-visible subtitles and a novel proposed comic-style presentation mode are significantly more appropriate than state-of-the-art fixed-positioned subtitles, particularly in terms of immersion, ease and comfort of reading, and identification of speakers, when applied to professional pieces of content with limited displacement of speakers and limited 6DoF (i.e., users are not expected to navigate around the virtual environment). Similarly, even in such limited movement scenarios, the results show that the use of indicators (arrows), as a guiding method, is well received. Overall, the paper provides relevant insights and paves the way for efficiently subtitling 3D VR content.

scholarly journals Soft Robotics: Biological Inspiration, State of the Art, and Future Research

2008 ◽  
Vol 5 (3) ◽  
pp. 99-117 ◽  
Author(s):  
Deepak Trivedi ◽  
Christopher D. Rahn ◽  
William M. Kier ◽  
Ian D. Walker
Keyword(s):  
Degrees Of Freedom ◽  
State Of The Art ◽  
Future Research ◽  
Robot Design ◽  
The Novel ◽  
Soft Robots ◽  
Biological Inspiration ◽  
End Effectors ◽  
And Control ◽  
Complex Movement

Traditional robots have rigid underlying structures that limit their ability to interact with their environment. For example, conventional robot manipulators have rigid links and can manipulate objects using only their specialised end effectors. These robots often encounter difficulties operating in unstructured and highly congested environments. A variety of animals and plants exhibit complex movement with soft structures devoid of rigid components. Muscular hydrostats (e.g. octopus arms and elephant trunks) are almost entirely composed of muscle and connective tissue and plant cells can change shape when pressurised by osmosis. Researchers have been inspired by biology to design and build soft robots. With a soft structure and redundant degrees of freedom, these robots can be used for delicate tasks in cluttered and/or unstructured environments. This paper discusses the novel capabilities of soft robots, describes examples from nature that provide biological inspiration, surveys the state of the art and outlines existing challenges in soft robot design, modelling, fabrication and control.

scholarly journals Entanglement goes classically high-dimensional

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Qiwen Zhan
Keyword(s):  
Structured Light ◽  
Laser Beams ◽  
High Dimensional ◽  
Entangled States ◽  
Light Fields ◽  
Quantum Entangled States

AbstractLaser beams from a customarily designed resonator can produce vectorial structured light fields as classical analogs to high-dimensional multipartite quantum entangled states.

scholarly journals Urdu Handwritten Characters Data Visualization and Recognition Using Distributed Stochastic Neighborhood Embedding and Deep Network

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Mujtaba Husnain ◽  
Malik Muhammad Saad Missen ◽  
Shahzad Mumtaz ◽  
Dost Muhammad Khan ◽  
Mickäel Coustaty ◽  
...  
Keyword(s):  
Data Visualization ◽  
State Of The Art ◽  
Computation Time ◽  
Principal Component ◽  
Multidimensional Data ◽  
High Dimensional ◽  
Deep Network ◽  
Reduced Dimensions ◽  
Handwritten Text ◽  
First Time

In this paper, we make use of the 2-dimensional data obtained through t-Stochastic Neighborhood Embedding (t-SNE) when applied on high-dimensional data of Urdu handwritten characters and numerals. The instances of the dataset used for experimental work are classified in multiple classes depending on the shape similarity. We performed three tasks in a disciplined order; namely, (i) we generated a state-of-the-art dataset of both the Urdu handwritten characters and numerals by inviting a number of native Urdu participants from different social and academic groups, since there is no publicly available dataset of such type till date, then (ii) applied classical approaches of dimensionality reduction and data visualization like Principal Component Analysis (PCA), Autoencoders (AE) in comparison with t-Stochastic Neighborhood Embedding (t-SNE), and (iii) used the reduced dimensions obtained through PCA, AE, and t-SNE for recognition of Urdu handwritten characters and numerals using a deep network like Convolution Neural Network (CNN). The accuracy achieved in recognition of Urdu characters and numerals among the approaches for the same task is found to be much better. The novelty lies in the fact that the resulting reduced dimensions are used for the first time for the recognition of Urdu handwritten text at the character level instead of using the whole multidimensional data. This results in consuming less computation time with the same accuracy when compared with processing time consumed by recognition approaches applied to other datasets for the same task using the whole data.

scholarly journals Novel Module-Based Membrane Reactor Design Approach for Improved Operability Performance

Membranes ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 157
Author(s):  
Brent A. Bishop ◽  
Fernando V. Lima
Keyword(s):  
Membrane Reactor ◽  
Degrees Of Freedom ◽  
Reactor Design ◽  
Membrane Reactors ◽  
Exchange Reactions ◽  
Potential Control ◽  
Novel Approach ◽  
In Series ◽  
And Control ◽  
First Time

This work aims to address the design and control challenges caused by the integration of phenomena and the loss of degrees of freedom (DOF) that occur in the intensification of membrane reactor units. First, a novel approach to designing membrane reactor units is proposed. This approach consists of designing smaller modules based on specific phenomena such as heat exchange, reactions, and mass transport and combining them in series to produce the final modular membrane-based unit. This approach to designing membrane reactors is then assessed using a process operability analysis for the first time to maximize the operability index, as a way of quantifying the operational performance of intensified processes. This work demonstrates that by designing membrane reactors in this way, the operability of the original membrane reactor design can be significantly improved, translating to an improvement in achievability for a potential control structure implementation.

scholarly journals Efficient PCA-Exploration of High-Dimensional Datasets

2020 ◽  
Author(s):  
Oxana Ye. Rodionova ◽  
Sergey Kucheryavskiy ◽  
Alexey L. Pomerantsev
Keyword(s):  
Degrees Of Freedom ◽  
Principal Component ◽  
Recent Decade ◽  
Model Complexity ◽  
High Dimensional ◽  
Exploratory Data ◽  
Classification Tasks ◽  
First Time ◽  
High Dimensional Datasets

<div><div><div><p>Basic tools for exploration and interpretation of Principal Component Analysis (PCA) results are well- known and thoroughly described in many comprehensive tutorials. However, in the recent decade, several new tools have been developed. Some of them were originally created for solving authentication and classification tasks. In this paper we demonstrate that they can also be useful for the exploratory data analysis.</p><p><br></p><p>We discuss several important aspects of the PCA exploration of high dimensional datasets, such as estimation of a proper complexity of PCA model, dependence on the data structure, presence of outliers, etc. We introduce new tools for the assessment of the PCA model complexity such as the plots of the degrees of freedom developed for the orthogonal and score distances, as well as the Extreme and Distance plots, which present a new look at the features of the training and test (new) data. These tools are simple and fast in computation. In some cases, they are more efficient than the conventional PCA tools. A simulated example provides an intuitive illustration of their application. Three real-world examples originated from various fields are employed to demonstrate capabilities of the new tools and ways they can be used. The first example considers the reproducibility of a handheld spectrometer using a dataset that is presented for the first time. The other two datasets, which describe the authentication of olives in brine and classification of wines by their geographical origin, are already known and are often used for the illustrative purposes.</p><p><br></p><p>The paper does not touch upon the well-known things, such as the algorithms for the PCA decomposition, or interpretation of scores and loadings. Instead, we pay attention primarily to more advanced topics, such as exploration of data homogeneity, understanding and evaluation of an optimal model complexity. The examples are accompanied by links to free software that implements the tools.</p></div></div></div>

scholarly journals Efficient PCA-Exploration of High-Dimensional Datasets

2020 ◽  
Author(s):  
Oxana Ye. Rodionova ◽  
Sergey Kucheryavskiy ◽  
Alexey L. Pomerantsev
Keyword(s):  
Degrees Of Freedom ◽  
Principal Component ◽  
Recent Decade ◽  
Model Complexity ◽  
High Dimensional ◽  
Exploratory Data ◽  
Classification Tasks ◽  
First Time ◽  
High Dimensional Datasets

<div><div><div><p>Basic tools for exploration and interpretation of Principal Component Analysis (PCA) results are well- known and thoroughly described in many comprehensive tutorials. However, in the recent decade, several new tools have been developed. Some of them were originally created for solving authentication and classification tasks. In this paper we demonstrate that they can also be useful for the exploratory data analysis.</p><p><br></p><p>We discuss several important aspects of the PCA exploration of high dimensional datasets, such as estimation of a proper complexity of PCA model, dependence on the data structure, presence of outliers, etc. We introduce new tools for the assessment of the PCA model complexity such as the plots of the degrees of freedom developed for the orthogonal and score distances, as well as the Extreme and Distance plots, which present a new look at the features of the training and test (new) data. These tools are simple and fast in computation. In some cases, they are more efficient than the conventional PCA tools. A simulated example provides an intuitive illustration of their application. Three real-world examples originated from various fields are employed to demonstrate capabilities of the new tools and ways they can be used. The first example considers the reproducibility of a handheld spectrometer using a dataset that is presented for the first time. The other two datasets, which describe the authentication of olives in brine and classification of wines by their geographical origin, are already known and are often used for the illustrative purposes.</p><p><br></p><p>The paper does not touch upon the well-known things, such as the algorithms for the PCA decomposition, or interpretation of scores and loadings. Instead, we pay attention primarily to more advanced topics, such as exploration of data homogeneity, understanding and evaluation of an optimal model complexity. The examples are accompanied by links to free software that implements the tools.</p></div></div></div>

scholarly journals Subtitling 3D VR Content with Limited 6DoF: Presentation Modes and Guiding Methods

2021 ◽  
Author(s):  
Mario Montagud Climent ◽  
Cristian Hurtado ◽  
Juan Antonio De Rus Arance ◽  
Sergi Fernández
Keyword(s):  
Degrees Of Freedom ◽  
State Of The Art ◽  
Presentation Mode ◽  
Multimedia Content ◽  
Service Needs ◽  
Video Content ◽  
Presentation Modes ◽  
6 Degrees Of Freedom ◽  
First Time ◽  
Access Services

Every (multimedia) service needs to be accessible. Accessibility for multimedia content is typically provided by means of access services, of which subtitling is likely the most widespread one. Up to date, many recommendations and solutions for subtitling classical 2D audiovisual services are available. Likewise, recent efforts have been devoted to devising adequate subtitling solutions for VR360 video content. This paper, for the first time, goes a step beyond, by exploring two key requirements to fulfill remaining challenges towards efficiently subtitling 3D Virtual Reality (VR) content: presentation modes, and guiding methods. By leveraging insights from earlier work on VR360 content, the paper proposes novel presentation modes and guiding methods to not only deal with the freedom to explore the omnidirectional scenes, but also with additional specificities of 3D VR compared to VR360 content: depth, 6 Degrees of Freedom (6DoF), and viewing perspectives. The obtained results prove that always-visible and a novel proposed comic-style presentation mode are far more appropriate than state-of-the-art fixed-positioned subtitles, mainly in terms of immersion, ease and comfort of reading, and identification of speakers, when applied to professional pieces of content with limited displacement of speakers and with limited 6DoF (i.e. users are not expected to largely navigate around the virtual environment). Likewise, even in such limited movement scenarios, the results show that the use of indicators (arrows), as guiding methods, is well received. Overall, the paper provides relevant insights and paves the way toward efficiently subtitling 3D VR content.

scholarly journals Theoretical study of deeply virtual Compton scattering off $^4$He

2020 ◽  
Author(s):  
Sara Fucini ◽  
Sergio Scopetta ◽  
Michele Viviani
Keyword(s):  
Compton Scattering ◽  
Degrees Of Freedom ◽  
Theoretical Study ◽  
State Of The Art ◽  
Impulse Approximation ◽  
Deeply Virtual Compton Scattering ◽  
Virtual Compton Scattering ◽  
Coordinate Space ◽  
Nuclear Systems ◽  
First Time

An interesting breakthrough in understanding the elusive inner content of nuclear systems in terms of partonic degrees of freedom is represented by deeply virtual Compton scattering processes. In such a way, tomographic view of nuclei and bound nucleons in coordinate space could be achieved for the first time. Moreover, nowadays experimental results for such a process considering ^44He targets recently released at Jefferson Lab are available. In this talk, the recent results of our rigorous Impulse Approximation for DVCS off ^44He, in terms of state-of-the-art models of the nuclear spectral function and of the parton structure of the bound proton, able to explain present data, has been shown.

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