Reviewerly/exHarmony huggingface dataset:
Completely positive quantum trajectories with applications to quantum state smoothing

Here, we are concerned with comparing estimation schemes for the quantum state under continuous measurement (quantum trajectories), namely quantum state filtering and, as introduced by us [Phys. Rev. Lett. 115, 180407 (2015)], quantum state smoothing. Unfortunately, the cumulative errors in the most typical simulations of quantum trajectories with a total time of simulation $T$ can reach orders of $T \Delta t$. Moreover, these errors may correspond to deviations from valid quantum evolution as described by a completely positive map. Here we introduce a higher-order method that reduces the cumulative errors in the complete positivity of the evolution to of order $T\Delta t^2$, whether for linear (unnormalised) or nonlinear (normalised) quantum trajectories. Our method also guarantees that the discrepancy in the average evolution between different detection methods (different `unravellings', such as quantum jumps or quantum diffusion) is similarly small. This equivalence is essential for comparing quantum state filtering to quantum state smoothing, as the latter assumes that all irreversible evolution is unravelled, although the estimator only has direct knowledge of some records. In particular, here we compare, for the first time, the average difference between filtering and smoothing conditioned on an event of which the estimator lacks direct knowledge: a photon detection within a certain time window. We find that the smoothed state is actually {\em less pure}, both before and after the time of the jump. Similarly, the fidelity of the smoothed state with the `true' (maximal knowledge) state is also lower than that of the filtered state before the jump. However, after the jump, the fidelity of the smoothed state is higher.
A Hierarchical Model with Recurrent Convolutional Neural Networks for Sequential Sentence Classification

Hierarchical neural networks approaches have achieved outstanding results in the latest sequential sentence classification research work. However, it is challenging for the model to consider both the local invariant features and word dependent information of the sentence. In this work, we concentrate on the sentence representation and context modeling components that influence the effects of the hierarchical architecture. We present a new approach called SR-RCNN to generate more precise sentence encoding which leverage complementary strength of bi-directional recurrent neural network and text convolutional neural network to capture contextual and literal relevance information. Afterwards, statement-level encoding vectors are modeled to capture the intrinsic relations within surrounding sentences. In addition, we explore the applicability of attention mechanisms and conditional random fields to the task. Our model advances sequential sentence classification in medical abstracts to new state-of-the-art performance.
Preliminary Poetics of Procedural Generation in Games

Procedural Content Generation (PCG) is deeply embedded in many games. While there are many taxonomies of the applications of PCG, less attention has been given to the poetics of PCG. In this paper we present a poetics for generative systems, including a descriptive framework that introduces terms for complex systems (Apollonian order and Dionysian chaos), the form that describes the shape of the generated output (formal gestalt, individual, and repetition), the locus of the generative process (structure, surface, or locus gestalt), the kind of variation the generator uses (style, multiplicity, and cohesion) and the relationship between coherence and the content used as input for the generator. Rather than being mutually exclusive categories, generators can be considered to exhibit aspects of all of these at once.
Search Method of disaster inspection coordinated by Multi-UAV

The use of unmanned aerial vehicle(UAV) for timely and efficient disaster inspection is an important measure to reduce earthquake losses. Aiming at the problem that complicated terrain of the disaster area and the urgent time of disaster relief, this paper puts forward a multi-UAV collaborative disaster inspection search method, gets the optimal scheme of inspection under the primary disaster and secondary disaster. Factors such as terrain, inspection time, search area coverage and number of drones are fully taken into account, and the multi-machine cooperative flight model under primary disaster and secondary disaster is established respectively. Combined with the fastest descent method and the A Star algorithm, a route plan is obtained to complete the maximum coverage search in a specified time with UAV. The whole area search route under secondary disaster is obtained by using taboo search algorithm. The simulation results show that the route is reasonable and the maneuverability is strong.
Approximate Uncertain Program

Chance constrained program where one seeks to minimize an objective over decisions which satisfy randomly disturbed constraints with a given probability is computationally intractable. This paper proposes an approximate approach to address chance constrained program. Firstly, a single layer neural-network is used to approximate the function from decision domain to violation probability domain. The algorithm for updating parameters in single layer neural-network adopts sequential extreme learning machine. Based on the neural violation probability approximate model, a randomized algorithm is then proposed to approach the optimizer in the probabilistic feasible domain of decision. In the randomized algorithm, samples are extracted from decision domain uniformly at first. Then, violation probabilities of all samples are calculated according to neural violation probability approximate model. The ones with violation probability higher than the required level are discarded. The minimizer in the remained feasible decision samples is used to update sampling policy. The policy converges to the optimal feasible decision. Numerical simulations are implemented to validate the proposed method for non-convex problems comparing with scenario approach and parallel randomized algorithm. The result shows that proposed method have improved performance.
The influences of the dispersion and impurity on the properties of the Gaussian confining potential qubit with magnetic field

The influences of the dispersion, the impurity and the electron–phonon coupling (EPC) on the properties of the Gaussian confining (GC) potential qubit with magnetic field were studied by Pekar-type variation method. Results show that the decoherence time will increase with increasing the dielectric constant (DC) ratio, the dispersion coefficient and the EPC strength, respectively. The phase rotation quality factor increases with increasing the dielectric constant ratio, the dispersion coefficient and EPC strength, respectively. The magnetic field has a regulatory effect on the decoherence time and the phase rotation quality factor.
A Tool for Transforming Semantic Web Rule Language to SPARQL Infererecing Notation

Semantic web rule language (SWRL) combines web ontology language (OWL) ontologies with horn logic rules of the rule markup language (RuleML) family. Being supported by ontology editors, rule engines and ontology reasoners, it has become a very popular choice for developing rule-based applications on top of ontologies. However, SWRL is probably not going to become a WWW Consortium standard, prohibiting industrial acceptance. On the other hand, SPARQL Inferencing Notation (SPIN) has become a de-facto industry standard to represent SPARQL rules and constraints on semantic web models, building on the widespread acceptance of SPARQL (SPARQL Protocol and RDF Query Language). In this article, we argue that the life of existing SWRL rule-based ontology applications can be prolonged by converting them to SPIN. To this end, we have developed the SWRL2SPIN tool in Prolog that transforms SWRL rules into SPIN rules, considering the object-orientation of SPIN, i.e. linking rules to the appropriate ontology classes and optimizing them, as derived by analysing the rule conditions.
New weak error bounds and expansions for optimal quantization

We propose new weak error bounds and expansion in dimension one for optimal quantization-based cubature formula for different classes of functions, such that piecewise affine functions, Lipschitz convex functions or differentiable function with piecewise-defined locally Lipschitz or $α$-Hölder derivatives. This new results rest on the local behaviors of optimal quantizers, the $L^r$-$L^s$ distribution mismatch problem and Zador's Theorem. This new expansion supports the definition of a Richardson-Romberg extrapolation yielding a better rate of convergence for the cubature formula. An extension of this expansion is then proposed in higher dimension for the first time. We then propose a novel variance reduction method for Monte Carlo estimators, based on one dimensional optimal quantizers.
Common Vulnerabilities Enumeration (CVE), Common Weakness Enumeration (CWE), and Common Quality Enumeration (CQE)

PDF of Powerpoint Slides
Key Recovery Attacks on Some Rank Metric Code-Based Signatures

Designing secure Code-based signature schemes remains an issue today. In this paper, we focus on schemes designed with the Fiat-Shamir transformations rationale (commit and challenge strategy). We propose two generic key recovery attacks on rank metric code-based signature schemes $$\mathsf{Veron}$$, $$\mathsf{TPL}$$ and $$\mathsf{RQCS}$$. More specifically, we exploit the weakness that a support basis or an extended support basis of the secret key could be recovered from the signatures generated in these schemes through different techniques. Furthermore, we are able to determine a support matrix or an extended support matrix for the secret key if the number of equations over the base field is greater than the number of unknown variables in the support matrix. We show that both the design of $$\mathsf{TPL}$$ and $$\mathsf{RQCS}$$ schemes contain these weaknesses, and no reparation of parameters for these schemes is possible to resist our two attacks. Moreover, we show that we can recover a support basis for the secret key used in $$\mathsf{Veron}$$ and that our first attack is successful due to the choice of its proposed parameters. We implement our attacks on $$\mathsf{Veron}$$, $$\mathsf{TPL}$$ and $$\mathsf{RQCS}$$ signature schemes and manage to recover the secret keys within seconds.
Two Families of Entanglement-Assisted Quantum MDS Codes from Constacyclic Codes

Entanglement-assisted quantum error correcting codes (EAQECCs) can be derived from arbitrary classical linear codes. However, it is a very difficult task to determine the number of entangled states required. In this work, using the method of the decomposition of the defining set of constacyclic codes, we construct two families of q-ary entanglement-assisted quantum MDS (EAQMDS) codes based on classical constacyclic MDS codes by exploiting less pre-shared maximally entangled states. We show that a class of q-ary EAQMDS have minimum distance upper bound greater than q. Some of them have much larger minimum distance than the known quantum MDS (QMDS) codes of the same length. Most of these q-ary EAQMDS codes are new in the sense that their parameters are not covered by the codes available in the literature.
Time-local optimal control for parameter estimation in the Gaussian regime

Information about a classical parameter encoded in a quantum state can only decrease if the state undergoes a non-unitary evolution, arising from the interaction with an environment. However, instantaneous control unitaries may be used to mitigate the decrease of information caused by an open dynamics. A possible, locally optimal (in time) choice for such controls is the one that maximises the time-derivative of the quantum Fisher information (QFI) associated with a parameter encoded in an initial state. In this study, we focus on a single bosonic mode subject to a Markovian, thermal master equation, and determine analytically the optimal time-local control of the QFI for its initial squeezing angle (optical phase) and strength. We show that a single initial control operation is already optimal for such cases and quantitatively investigate situations where the optimal control is applied after the open dynamical evolution has begun.
Optical-aberrations-corrected light field re-projection for high-quality plenoptic imaging

The singlet plenoptic camera, which consists of a single lens, microlens array (MLA) and image sensor, possesses the superiority that the imaging system is compact and lightweight, which is beneficial to miniaturization. However, such plenoptic cameras suffer from severe optical aberrations and their imaging quality is inferior for post-capture processing. Therefore, this paper proposes an optical-aberrations-corrected light field re-projection method to obtain high-quality singlet plenoptic imaging. First, optical aberrations are modeled by Seidel polynomials and included into point spread function (PSF) modeling. The modeled PSF is subsequently used to reconstruct imaging object information. Finally, the reconstructed imaging object information is re-projected back to the plenoptic imaging plane to obtain high-quality plenoptic images without optical aberrations. PSF modeling is validated by a self-built singlet plenoptic camera and the utility of the proposed optical-aberrations-corrected light field re-projection method is verified by numerical simulations and real imaging experiments.
The mean point of vergence is biased under projection

The point of interest in three-dimensional space in eye tracking is often computed based on intersecting the lines of sight with geometry, or finding the point closest to the two lines of sight. We first start by theoretical analysis with synthetic simulations. We show that the mean point of vergence is generally biased for centrally symmetric errors and that the bias depends on the horizontal vs. vertical noise distribution of the tracked eye positions. Our analysis continues with an evaluation on real experimental data. The estimated mean vergence points seem to contain different errors among individuals but they generally show the same bias towards the observer. And it tends to be larger with an increased viewing distance. We also provided a recipe to minimize the bias, which applies to general computations of gaze estimation under projection. These findings not only have implications for choosing the calibration method in eye tracking experiments and interpreting the observed eye movements data; but also suggest to us that we shall consider the mathematical models of calibration as part of the experiment.
A Symmetrical Encryption Technique for Text Encryption Using Randomized Matrix Based Key Generation

At present huge amount of data are moving through internet, this creates a huge concern for the security of the data while it is being moved through unsecured medium like wireless internet. Among all data most commonly used data format is text data which even though being highly vulnerable to security breaches is used in essential areas like banking and database management. There are many methodologies proposed to secure this data but the possibility of data being exploited remains. The proposed system presents a new symmetric encryption technique where complexities of calculating determinants and developing random matrices are used to generate keys. The system consists of three phases, key generation, encryption and decryption. In the first phase keys are generated which are computed by calculating the determinants of decomposed matrices, these decomposed matrices are generated from the multiplication of the original random matrices. In the second phase a key is randomly selected and is added with the ASCII value of the text message. The new generated value is then multiplied with the multiplication factor which is decomposition of selected key into the range of zero to nine. In the last phase the encrypted text is reverted back to its original text by performing reverse operations performed during encryption phase i.e. division of ASCII value of encrypted text by multiplication factor and then subtraction of the value of key from the computed result. The performance of the system is measured by calculating the total time taken to generate key with encryption and decryption of the input text message. The proposed system has been compared with various existing robust systems like AES, DES and BLOWFISH. And from the comparison it can be asserted that the proposed system is more efficient than the existing systems.
Recognizing New Classes with Synthetic Data in the Loop: Application to Traffic Sign Recognition

On-board vision systems may need to increase the number of classes that can be recognized in a relatively short period. For instance, a traffic sign recognition system may suddenly be required to recognize new signs. Since collecting and annotating samples of such new classes may need more time than we wish, especially for uncommon signs, we propose a method to generate these samples by combining synthetic images and Generative Adversarial Network (GAN) technology. In particular, the GAN is trained on synthetic and real-world samples from known classes to perform synthetic-to-real domain adaptation, but applied to synthetic samples of the new classes. Using the Tsinghua dataset with a synthetic counterpart, SYNTHIA-TS, we have run an extensive set of experiments. The results show that the proposed method is indeed effective, provided that we use a proper Convolutional Neural Network (CNN) to perform the traffic sign recognition (classification) task as well as a proper GAN to transform the synthetic images. Here, a ResNet101-based classifier and domain adaptation based on CycleGAN performed extremely well for a ratio ∼ 1 / 4 for new/known classes; even for more challenging ratios such as ∼ 4 / 1 , the results are also very positive.
Non-Abelian Aharonov-Bohm caging in photonic lattices

Aharonov-Bohm (AB) caging is the localization effect in translational-invariant lattices due to destructive interference induced by penetrated magnetic fields. Although current research focuses mainly on the case of Abelian AB caging, here, we go beyond and develop the non-Abelian AB caging concept by considering the particle localization in a one-dimensional multicomponent rhombic lattice with a non-Abelian background gauge field. In contrast to its Abelian counterpart, the non-Abelian AB cage depends on both the form of the nilpotent interference matrix and on the initial state of the lattice. This phenomena is the consequence of the non-Abelian nature of the gauge potential and, thus, has no Abelian analog. We further propose a circuit quantum electrodynamics realization of the proposed physics in which the required non-Abelian gauge field can be synthesized by the parametric conversion method, and the non-Abelian AB caging can be unambiguously demonstrated through the pumping and the steady-state measurements of only a few sites on the lattice. Requiring only currently available technique, our proposal can be readily tested in experiment and may pave a new route towards the investigation of exotic photonic quantum fluids.
Towards simultaneous observation of path and interference of a single photon in a modified Mach–Zehnder interferometer

Classical wisdom of wave–particle duality regulates that a quantum object shows either the particle or wave nature but never both. Consequently, it would be impossible to observe simultaneously the complete wave and particle nature of the quantum object. Mathematically the principle requests that the interference visibility <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m1"> <mml:mrow> <mml:mi>V</mml:mi> </mml:mrow> </mml:math> and which-path distinguishability <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m2"> <mml:mrow> <mml:mi>D</mml:mi> </mml:mrow> </mml:math> satisfy an orthodox limit of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m3"> <mml:mrow> <mml:msup> <mml:mi>V</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>+</mml:mo> <mml:msup> <mml:mi>D</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>≤</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:math> . The present work reports a new wave–particle duality test experiment using single photons in a modified Mach–Zehnder interferometer to demonstrate the possibility of breaking the limit. The key element of the interferometer is a weakly scattering total internal reflection prism surface, which exhibits a pronounced single-photon interference with a visibility of up to 0.97 and simultaneously provides a path distinguishability of 0.83. Apparently, the result of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m4"> <mml:mrow> <mml:msup> <mml:mi>V</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>+</mml:mo> <mml:msup> <mml:mi>D</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>≈</mml:mo> <mml:mn>1.63</mml:mn> </mml:mrow> </mml:math> exceeds the orthodox limit set by the classical principle of wave–particle duality for single photons. We expect that more delicate experiments in the future should be able to demonstrate the ultimate limit of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="m5"> <mml:mrow> <mml:msup> <mml:mi>V</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>+</mml:mo> <mml:msup> <mml:mi>D</mml:mi> <mml:mn>2</mml:mn> </mml:msup> <mml:mo>≈</mml:mo> <mml:mn>2</mml:mn> </mml:mrow> </mml:math> and shed new light on the foundations of contemporary quantum mechanics.
Automated Fake Access Point Attack Detection and Prevention System with IoT Devices

Wireless access points (APs), which allow many devices to be easily connected to the Internet, are widely used today because they offer the easiest way to connect to the Internet. With the development of the concept of Internet of Things (IoT), WiFi networks are widely used in our homes, workplaces, social areas, campus areas. With the increase of WiFi networks, attacks on these networks are constantly increasing. In this study, an IoT-based approach to detect and prevent Fake Access point attacks frequently seen in WiFi networks is proposed. A Single Board Computer (SBC) and a wireless antenna in the "Soft AP" feature are used for operation. Fake APs were detected by air scanning. In the first phase of the study, fake Access point broadcasts have been created which can create security weakness. In order to determine the fake Access points created in the second stage, SBC and wifi module were used to scan air. In the final stage, the mac address of the fake AP has been assigned to an unauthorized Virtual Local Area Network (vLAN) on the network to prevent detected fake AP broadcasts. The possible attack methods for the study were implemented and it was revealed that the proposed approach prevented the attack successfully in all scenarios. The study is seen as an effective, developed and economically useful IoT application for network administrators to prevent the attack using fake Access point.
Local-dimension-invariant qudit stabilizer codes

Protection of quantum information from noise is a massive challenge. One avenue people have begun to explore is reducing the number of particles needing to be protected from noise and instead use systems with more states, so-called qudit quantum computers. These systems will require codes which utilize the full computational space. Many prior qudit codes are very restrictive on relations between the parameters of number of qudits, number of logical qudits, distance of the code, and number of bases. In this paper we show that codes for these systems can be derived from already known codes, often relaxing the constraints somewhat, a result which could prove to be very useful for fault-tolerant qudit quantum computers.