The electron hopping between the two sites in a lattice is of fundamental importance in condensed matter physics. Precise control of the hopping strength allows for the prospect of manipulating the properties of electronic materials, such as topological properties, superconductivity, etc. In this framework, measuring the hopping strength of an electronic lattice with high precision is perhaps the most relevant step in controlling the properties of electronic materials. Here, we design a critical quantum metrological protocol to measure the hopping strength in a cavity electronic chain coupling system featuring a pseudo-superradiant phase transition. We show that the cavity ground state, which is initially a squeezed vacuum state, can be utilized as a quantum probe to achieve a high quantum precision of the hopping strength, which can be optimally saturated in either the loss or lossless case. Remarkably, in the presence of chain loss, we find that increasing the electron current in the chain is beneficial for enhancing precision, and the arbitrarily large precision could be obtained by increasing the chain size, in principle. Our results provide an effective method to measure the hopping strength in the electronic chain with high precision, so it has potential applications in critical quantum metrology, condensed matter physics, etc.
This note is a reproduction of the well known and historically significant series of notes called "The Edmonton Notes on Nilpotent Groups" based on lectures given by Philip Hall using the copy found in the Queen Mary College Mathematics Notes series. We use the original numbering of statements, definitions, footnotes, proofs, abstract, etc. to recover as much of the original document as possible.
In this work, we adopt the Gradient Projection Method (GPM) to problems of quantum control. For general $N$-level closed and open quantum systems, we derive the corresponding adjoint systems and gradients of the objective functionals, and provide the projection versions of the Pontryagin maximum principle and the GPM, all directly in terms of quantum objects such as evolution operator, Hamiltonians, density matrices, etc. Various forms of the GPM, including one- and two-step, are provided and compared. We formulate the GPM both for closed and open quantum systems, latter for the general case with simultaneous coherent and incoherent controls. The GPM is designed to perform local gradient based optimization in the case when bounds are imposed on the controls. The main advantage of the method is that it allows to exactly satisfy the bounds, in difference to other approaches such as adding constraints as weight to objective. We apply the GPM to several examples including generation of one- and two-qubit gates and two-qubit Bell and Werner states for models of superconducting qubits under the constraint when controls are zero at the initial and final times, and steering an open quantum system state to a target density matrix for simulating action of the Werner-Holevo channel, etc.
Ioannis Mademlis, Georgios Batsis, Adamantia Anna Rebolledo Chrysochoou
et al.
Automated detection of contraband items in X-ray images can significantly increase public safety, by enhancing the productivity and alleviating the mental load of security officers in airports, subways, customs/post offices, etc. The large volume and high throughput of passengers, mailed parcels, etc., during rush hours practically make it a Big Data problem. Modern computer vision algorithms relying on Deep Neural Networks (DNNs) have proven capable of undertaking this task even under resource-constrained and embedded execution scenarios, e.g., as is the case with fast, single-stage object detectors. However, no comparative experimental assessment of the various relevant DNN components/methods has been performed under a common evaluation protocol, which means that reliable cross-method comparisons are missing. This paper presents exactly such a comparative assessment, utilizing a public relevant dataset and a well-defined methodology for selecting the specific DNN components/modules that are being evaluated. The results indicate the superiority of Transformer detectors, the obsolete nature of auxiliary neural modules that have been developed in the past few years for security applications and the efficiency of the CSP-DarkNet backbone CNN.
Md. Mehedi Hasan, Md. Ali Hossain, Azmain Yakin Srizon
et al.
The application of the deep learning model in classification plays an important role in the accurate detection of the target objects. However, the accuracy is affected by the activation function in the hidden and output layer. In this paper, an activation function called TaLU, which is a combination of Tanh and Rectified Linear Units (ReLU), is used to improve the prediction. ReLU activation function is used by many deep learning researchers for its computational efficiency, ease of implementation, intuitive nature, etc. However, it suffers from a dying gradient problem. For instance, when the input is negative, its output is always zero because its gradient is zero. A number of researchers used different approaches to solve this issue. Some of the most notable are LeakyReLU, Softplus, Softsign, ELU, ThresholdedReLU, etc. This research developed TaLU, a modified activation function combining Tanh and ReLU, which mitigates the dying gradient problem of ReLU. The deep learning model with the proposed activation function was tested on MNIST and CIFAR-10, and it outperforms ReLU and some other studied activation functions in terms of accuracy(upto 6% in most cases, when used with Batch Normalization and a reasonable learning rate).
L’articolo discute la rappresentazione della Seconda Guerra Mondiale negli anni Duemila, e nello specifico il superamento sia del paradigma postmemoriale che dell’historiographic metafiction postmoderna, usando come case study La strada stretta verso il profondo Nord dell’australiano Richard Flanagan (The Narrow Road to the Deep North; 2013). In questo articolo intendo illustrare come La strada stretta verso il profondo Nord, recuperando e riaggiornando i modi del romanzo tradizionale, offra una rappresentazione problematica (anti-retorica e anti-nazionalistica) della Seconda Guerra Mondiale, e come, per farlo, si serva di forme d’arte (l’haiku, l’ensō) e di concetti del buddismo zen. Lungi dal rappresentare un’aggiunta ornamentale, i riferimenti al buddismo zen amplificano e approfondiscono le problematiche analizzate nel libro, dalla memoria della guerra in Australia e Giappone alle strutture di potere coloniali fino a una concezione della storia conoscibile ma non monolitica, bensì dinamica e plastica.
Language. Linguistic theory. Comparative grammar, Style. Composition. Rhetoric
Emanuele Lattanzi, Lorenzo Calisti, Valerio Freschi
Current guidelines from the World Health Organization indicate that the SARS-CoV-2 coronavirus, which results in the novel coronavirus disease (COVID-19), is transmitted through respiratory droplets or by contact. Contact transmission occurs when contaminated hands touch the mucous membrane of the mouth, nose, or eyes so hands hygiene is extremely important to prevent the spread of the SARSCoV-2 as well as of other pathogens. The vast proliferation of wearable devices, such as smartwatches, containing acceleration, rotation, magnetic field sensors, etc., together with the modern technologies of artificial intelligence, such as machine learning and more recently deep-learning, allow the development of accurate applications for recognition and classification of human activities such as: walking, climbing stairs, running, clapping, sitting, sleeping, etc. In this work, we evaluate the feasibility of a machine learning based system which, starting from inertial signals collected from wearable devices such as current smartwatches, recognizes when a subject is washing or rubbing its hands. Preliminary results, obtained over two different datasets, show a classification accuracy of about 95% and of about 94% for respectively deep and standard learning techniques.
Contextual Bandits find important use cases in various real-life scenarios such as online advertising, recommendation systems, healthcare, etc. However, most of the algorithms use flat feature vectors to represent context whereas, in the real world, there is a varying number of objects and relations among them to model in the context. For example, in a music recommendation system, the user context contains what music they listen to, which artists create this music, the artist albums, etc. Adding richer relational context representations also introduces a much larger context space making exploration-exploitation harder. To improve the efficiency of exploration-exploitation knowledge about the context can be infused to guide the exploration-exploitation strategy. Relational context representations allow a natural way for humans to specify knowledge owing to their descriptive nature. We propose an adaptation of Knowledge Infused Policy Gradients to the Contextual Bandit setting and a novel Knowledge Infused Policy Gradients Upper Confidence Bound algorithm and perform an experimental analysis of a simulated music recommendation dataset and various real-life datasets where expert knowledge can drastically reduce the total regret and where it cannot.
The paper describes an algorithm to compute a consensus sequence from a set of DNA sequences of approximatively identical length generated by 3rd sequencing generation technologies. Its purpose targets DNA storage and is guided by specific features that cannot be exhibited from biological data such as the exact length of the consensus sequences, the precise location of known patterns, the kmer composition, etc.
Ekraam Sabir, Ayush Jaiswal, Wael AbdAlmageed
et al.
Fake news often involves semantic manipulations across modalities such as image, text, location etc and requires the development of multimodal semantic forensics for its detection. Recent research has centered the problem around images, calling it image repurposing -- where a digitally unmanipulated image is semantically misrepresented by means of its accompanying multimodal metadata such as captions, location, etc. The image and metadata together comprise a multimedia package. The problem setup requires algorithms to perform multimodal semantic forensics to authenticate a query multimedia package using a reference dataset of potentially related packages as evidences. Existing methods are limited to using a single evidence (retrieved package), which ignores potential performance improvement from the use of multiple evidences. In this work, we introduce a novel graph neural network based model for multimodal semantic forensics, which effectively utilizes multiple retrieved packages as evidences and is scalable with the number of evidences. We compare the scalability and performance of our model against existing methods. Experimental results show that the proposed model outperforms existing state-of-the-art algorithms with an error reduction of up to 25%.
Alexandre Magueresse, Vincent Carles, Evan Heetderks
A current problem in NLP is massaging and processing low-resource languages which lack useful training attributes such as supervised data, number of native speakers or experts, etc. This review paper concisely summarizes previous groundbreaking achievements made towards resolving this problem, and analyzes potential improvements in the context of the overall future research direction.
Contrary to popular misconception, the question in the title is far from simple. It involves sets of numbers on the first level, sets of sets of numbers on the second level, and so on, endlessly. The infinite hierarchy of the levels involved distinguishes the concept of "definable number" from such notions as "natural number", "rational number", "algebraic number", "computable number" etc. (Explanatory essay for non-experts.)
We first briefly survey the value-distribution theory of L-functions of the Bohr-Jessen flavor (or the theory of "M-functions"). Limit formulas for the Riemann zeta-function, Dirichlet L-functions, automorphic L-functions etc. are discussed. Then we prove new results on the value-distribution of symmetric power L-functions, which are limit formulas involving associated M-functions.
The full story of the Stern-Gerlach experiment and its reception, interpretation and final understanding has many unexpected surprises. Here, we review the history and the context of the proposal, the experiment, and the subsequent story of the aftermath. We also discuss the story of the possible Stern-Gerlach experiment for free electrons etc. Finally, we comment on the remarkable career of Otto Stern.
Existing works for extracting navigation objects from webpages focus on navigation menus, so as to reveal the information architecture of the site. However, web 2.0 sites such as social networks, e-commerce portals etc. are making the understanding of the content structure in a web site increasingly difficult. Dynamic and personalized elements such as top stories, recommended list in a webpage are vital to the understanding of the dynamic nature of web 2.0 sites. To better understand the content structure in web 2.0 sites, in this paper we propose a new extraction method for navigation objects in a webpage. Our method will extract not only the static navigation menus, but also the dynamic and personalized page-specific navigation lists. Since the navigation objects in a webpage naturally come in blocks, we first cluster hyperlinks into different blocks by exploiting spatial locations of hyperlinks, the hierarchical structure of the DOM-tree and the hyperlink density. Then we identify navigation objects from those blocks using the SVM classifier with novel features such as anchor text lengths etc. Experiments on real-world data sets with webpages from various domains and styles verified the effectiveness of our method.
The aim of this article is to analyze the interpretation of Carlo Michelstaedter’s thought defined by Gianni Carchia. Discussing the Carchia’s approach to Michelstaedter’s philosophy, we will show up some problematic points, like the relation between language and rhetoric or that between life and being. Cloncluding, we will try to define the complex hermenutical relation which Gianni Carchia maintains with the Michelstaedter’s text.
Lo scopo del presente articolo è quello di analizzare l’interpretazione del pensiero di Carlo Michelsatedter offerta da Gianni Carchia. Discutendo l’approccio di carchia alla filosofia di Michelstaedter, sottolineeremo alcuni passaggi problematici, come la relazione fra lingua e retorica o quella fra vita ed essere. In conclusione, cercheremo di definire la complessa relazione ermeneutica che Gianni carchia intrattiene col testo di Michelstaedter
Language. Linguistic theory. Comparative grammar, Style. Composition. Rhetoric
Biswajit Saha, Amitabha Mandal, Soumendu Bikas Tripathy
et al.
This paper is an extensive survey of literature on complex network communities and clustering. Complex networks describe a widespread variety of systems in nature and society especially systems composed by a large number of highly interconnected dynamical entities. Complex networks like real networks can also have community structure. There are several types of methods and algorithms for detection and identification of communities in complex networks. Several complex networks have the property of clustering or network transitivity. Some of the important concepts in the field of complex networks are small-world and scale-robustness, degree distributions, clustering, network correlations, random graph models, models of network growth, dynamical processes on networks, etc. Some current areas of research on complex network communities are those on community evolution, overlapping communities, communities in directed networks, community characterization and interpretation, etc. Many of the algorithms or methods proposed for network community detection through clustering are modified versions of or inspired from the concepts of minimum-cut based algorithms, hierarchical connectivity based algorithms, the original GirvanNewman algorithm, concepts of modularity maximization, algorithms utilizing metrics from information and coding theory, and clique based algorithms.
We consider a quantitative form of the quasi-isometry problem. We discuss several arguments which lead us to different results and bounds of quasi-isometric distortion: comparison of volumes, connectivity etc. Then we study the transport of Poincaré constants by quasi-isometries and we give sharp lower and upper bounds for the homotopy distortion growth for an interesting class of hyperbolic metric spaces.