Search results for: quantum computation

Authors: Nilanjana Chanda, Rangeet Bhattacharyya

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Grover’s search algorithm is the fastest possible quantum mechanical algorithm to search a certain element from an unstructured set of data of N items. The algorithm can determine the desired result in only O(√N) steps. It has been demonstrated theoretically and experimentally on two-qubit systems long ago. In this work, we investigate the fidelity of Grover’s search algorithm by implementing it on an open quantum system. In particular, we study with what accuracy one can estimate that the algorithm would deliver the searched state. In reality, every system has some influence on its environment. We include the environmental effects on the system dynamics by using a recently reported fluctuation-regulated quantum master equation (FRQME). We consider that the environment experiences thermal fluctuations, which leave its signature in the second-order term of the master equation through its appearance as a regulator. The FRQME indicates that in addition to the regular relaxation due to system-environment coupling, the applied drive also causes dissipation in the system dynamics. As a result, the fidelity is found to depend on both the drive-induced dissipative terms and the relaxation terms, and we find that there exists a competition between them, leading to an optimum drive amplitude for which the fidelity becomes maximum. For efficient implementation of the search algorithm, precise knowledge of this optimum drive amplitude is essential.

Keywords: dissipation, fidelity, quantum master equation, relaxation, system-environment coupling

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Authors: Tory Erickson

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The "Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model introduces a framework aimed at unifying general relativity (GR) and quantum mechanics (QM). By proposing a concept of bidirectional spacetime, this model suggests that time can flow in more than one direction, thus offering a perspective on temporal dynamics. Integrated with spatial covariance and wave-particle duality in spacetime flow, the BST-SCWPDF Model resolves long-standing discrepancies between GR and QM. This unified theory has profound implications for quantum gravity, potentially offering insights into quantum entanglement, the collapse of the wave function, and the fabric of spacetime itself. The Bidirectional Spacetime with Spatial Covariance and Wave-Particle Duality in Spacetime Flow" (BST-SCWPDF) Model offers researchers a framework for a better understanding of theoretical physics.

Keywords: astrophysics, quantum mechanics, general relativity, unification theory, theoretical physics

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Authors: Hyunchul Oh

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One of the challenges in modern separation science and technology is the separation of hydrogen isotopes mixtures since D2 and H2 consist of almost identical size, shape and thermodynamic properties. Recently, quantum sieving of isotopes by confinement in narrow space has been proposed as an alternative technique. Despite many theoretical suggestions, however, it has been difficult to discover a feasible microporous material up to now. Among various porous materials, the novel class of microporous framework materials (COFs, ZIFs and MOFs) is considered as a promising material class for isotope sieving due to ultra-high porosity and uniform pore size which can be tailored. Hence, we investigate experimentally the fundamental correlation between D2/H2 molar ratio and pore size at optimized operating conditions by using different ultramicroporous frameworks. The D2/H2 molar ratio is strongly depending on pore size, pressure and temperature. An experimentally determined optimum pore diameter for quantum sieving lies between 3.0 and 3.4 Å which can be an important guideline for designing and developing feasible microporous frameworks for isotope separation. Afterwards, we report a novel strategy for efficient hydrogen isotope separation at technologically relevant operating pressure through the development of quantum sieving exploited by the pore aperture engineering. The strategy involves installation of flexible components in the pores of the framework to tune the pore surface.

Keywords: gas adsorption, hydrogen isotope, metal organic frameworks(MOFs), quantum sieving

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Authors: Wang Xingbo

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Computation of determinant in the form |I-X| is primary and fundamental because it can help to compute many other determinants. This article puts forward a time-reducible approach to compute determinant |I-X|. The approach is derived from the Newton’s identity and its time complexity is no more than that to compute the eigenvalues of the square matrix X. Mathematical deductions and numerical example are presented in detail for the approach. By comparison with classical approaches the new approach is proved to be superior to the classical ones and it can naturally reduce the computational time with the improvement of efficiency to compute eigenvalues of the square matrix.

Keywords: algorithm, determinant, computation, eigenvalue, time complexity

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Authors: Akhtar Rasool, Tasneem Zahra Rizvi

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In this study, a series of the cadmium sulphide quantum dots/polyaniline nanocomposites with varying compositions were prepared by in-situ polymerization technique and were characterized using X-ray diffraction and Fourier transform infrared spectroscopy. The surface morphology was studied by scanning electron microscopy. UV-Visible spectroscopy was used to find out the energy band gap of the nanoparticles and the nanocomposites. Temperature dependence of DC electrical conductivity and temperature and frequency dependence of AC conductivity were investigated to study the charge transport mechanism in the nanocomposites. DC conductivity was found to be a typical for a semiconducting behavior following Mott’s 1D variable range hoping model. The frequency dependent AC conductivity followed the universal power law.

Keywords: conducting polymers, nanocomposites, polyaniline composites, quantum dots

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Authors: Rajendra Kumar

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We study the Electronic spectral density of a double coupled quantum dots sandwich between superconducting leads, where one of the superconducting leads (QD1) are connected with left superconductor lead and (QD1) also connected right superconductor lead. (QD1) and (QD2) are coupling to each other. The electronic spectral density through a quantum dots between superconducting leads having s-wave symmetry of the superconducting order parameter. Such junction is called superconducting –quantum dot (S-QD-S) junction. For this purpose, we have considered a renormalized Anderson model that includes the double coupled of the superconducting leads with the quantum dots level and an attractive BCS-type effective interaction in superconducting leads. We employed the Green’s function technique to obtain superconducting order parameter with the BCS framework and Ambegaoker-Baratoff formalism to analyze the electronic spectral density through such (S-QD-S) junction. It has been pointed out that electronic spectral density through such a junction is dominated by the attractive the paring interaction in the leads, energy of the level on the dot with respect to Fermi energy and also on the coupling parameter of the two in an essential way. On the basis of numerical analysis we have compared the theoretical results of electronic spectral density with the recent transport existing theoretical analysis. QDs is the charging energy that may give rise to effects based on the interplay of Coulomb repulsion and superconducting correlations. It is, therefore, an interesting question to ask how the discrete level spectrum and the charging energy affect the DC and AC Josephson transport between two superconductors coupled via a QD. In the absence of a bias voltage, a finite DC current can be sustained in such an S-QD-S by the DC Josephson effect.

Keywords: quantum dots, S-QD-S junction, BCS superconductors, Anderson model

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Authors: Sourav Sarkar, Manashjit Gogoi

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In the evolving landscape of cancer diagnostics, optical biosensing has emerged as a promising tool due to its sensitivity and specificity. This study explores the potential of CdS/ZnS core-shell quantum dots (QDs) capped with 3-Mercaptopropionic acid (3-MPA), which aids in the linking chemistry of QDs to various cancer antibodies. The QDs, with their unique optical and electronic properties, have been integrated into the biosensor design. Their high quantum yield and size-dependent emission spectra have been exploited to improve the sensor’s detection capabilities. The study presents the design of this QD-enhanced optical biosensor. The use of these QDs can also aid multiplexed detection, enabling simultaneous monitoring of different cancer biomarkers. This innovative approach holds significant potential for advancing cancer diagnostics, contributing to timely and accurate detection. Future work will focus on optimizing the biosensor design for clinical applications and exploring the potential of QDs in other biosensing applications. This study underscores the potential of integrating nanotechnology and biosensing for cancer research, paving the way for next-generation diagnostic tools. It is a step forward in our quest for achieving precision oncology.

Keywords: quantum dots, biosensing, cancer, device

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Authors: Matthew Stephenson

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We study the electrical conductivity of strongly disordered, strongly coupled quantum field theories, holographically dual to non-perturbatively disordered uncharged black holes. The computation reduces to solving a diffusive hydrostatic equation for an emergent horizon fluid. We demonstrate that a large class of theories in two spatial dimensions have a universal conductivity independent of disorder strength, and rigorously rule out disorder-driven conductor-insulator transitions in many theories. We present a (fine-tuned) axion-dilaton bulk theory which realizes the conductor-insulator transition, interpreted as a classical percolation transition in the horizon fluid. We address aspects of strongly disordered holography that can and cannot be addressed via mean-field modeling, such as massive gravity.

Keywords: theoretical physics, black holes, holography, high energy

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Authors: A. Bouhmouche, I. Rhrissi, A. Jabar, R. Moubah

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Quantum spin liquids (QSLs), known for their competing interactions that prevent conventional ordering, exhibit emergent phenomena and exotic properties resulting from quantum correlations. Despite these recent advancements in QSLs, a significant portion of the optical and thermodynamic properties in the Kagome lattice remains unknown. In addition, the thermodynamic phenomenology of NaRuO₂ bears a resemblance to that of highly frustrated magnets. Here, we employed ab-initio calculations to explore the electronic, optical and thermodynamic properties of NaRuO₂, a new QSL candidate. NaRuO₂ was identified as a semiconductor with a small bandgap energy of 0.69 eV. Our results reveal huge anisotropic optical properties, in which a distinct refractive index within the ab-plane indicating an impressive birefringent character of the NaRuO₂ system and a significant enhancement of the optical absorption coefficient and optical conductivity in the in-plane with respect to the c-axis. The investigation also examines the electronic anisotropy of the gap energy; by applying strain, the gap energy displays significant variations in the ab-plane compared to the out-of-plane direction. Conversely, calculations of the thermodynamic properties reveal a low thermal conductivity (2.5-0.5 W.m-¹. K-¹) and specific heat, which suggests the existence of strong interactions among the NaRuO₂ quantum spins. The linear specific heat behavior observed in NaRuO₂ suggests the fractionalization of electrons and the presence of a spinons Fermi surface. These findings hold promising potential for future quantum applications.

Keywords: quantum spin liquids, anisotropy, hybrid-DFT, applied strain, optoelectronic and thermodynamic properties

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Authors: Rachid Fermous, Rima Mebrek

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Plasma expansion is an important physical process that takes place in laser interactions with solid targets. Within a self-similar model for the hydrodynamic multi-fluid equations, we investigated the expansion of dense plasma. The weakly relativistic electrons are produced by ultra-intense laser pulses, while ions are supposed to be in a non-relativistic regime. It is shown that dense plasma expansion is found to be governed mainly by quantum contributions in the fluid equations that originate from the degenerate pressure in addition to the nonlinear contributions from exchange and correlation potentials. The quantum degeneracy parameter profile provides clues to set the limit between under-dense and dense relativistic plasma expansions at a given density and temperature.

Keywords: plasma expansion, quantum degeneracy, weakly relativistic, under-dense plasma

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Authors: Mohamad Saab, Sidi Souvi

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In a major nuclear accident, the released fission products (FPs) and the structural materials are likely to influence the transport of iodine in the reactor coolant system (RCS) of a pressurized water reactor (PWR). So far, the thermodynamic data on cesium and silver species used to estimate the magnitude of FP release show some discrepancies, data are scarce and not reliable. For this reason, it is crucial to review the thermodynamic values related to cesium and silver materials. To this end, we have used state-of-the-art quantum chemical methods to compute the formation enthalpies and entropies of AgHMoO₄, CsHMoO₄, and AgCsMoO₄ in the gas phase. Different quantum chemical methods have been investigated (DFT and CCSD(T)) in order to predict the geometrical parameters and the energetics including the correlation energy. The geometries were optimized with TPSSh-5%HF method, followed by a single point calculation of the total electronic energies using the CCSD(T) wave function method. We thus propose with a final uncertainty of about 2 kJmol⁻¹ standard enthalpies of formation of AgHMoO₄, CsHMoO₄, and AgCsMoO₄.

Keywords: nuclear accident, ASTEC code, thermochemical database, quantum chemical methods

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Authors: Pavel Kotin, Sergey Dotofeev, Daniil Kozlov, Alexey Garshev

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We propose the investigation of CdSe quantum dots which were synthesized in the presence of silver halides. To understand a process of nanoparticle formation in more detail, we varied the silver halide amount in the synthesis and proposed a sampling during colloidal growth. The attempts were focused on the investigation of shape, structure and optical properties of nanoparticles. We used the colloidal method of synthesis. Cadmium oleate, tri-n-octylphosphine selenide (TOPSe) and AgHal in TOP were precursors of cadmium, selenium and silver halides correspondingly. The molar Ag/Cd ratio in synthesis was varied from 1/16 to 1/1. The sampling was basically realized in 20 sec, 5 min, and 30 min after the beginning of quantum dots nucleation. To investigate nanoparticles we used transmission electron microscopy (including high resolution one), X-ray diffraction, and optical spectroscopy. It was established that silver halides lead to obtaining tetrapods with different leg length and large ellipsoidal nanoparticles possessing an intensive near IR photoluminescence. The change of the amount of silver halide in synthesis and the selection of an optimal growth time allows controlling the shape and the share of tetrapods or ellipsoidal nanoparticles in the product. Our main attempts were focused on a detailed investigation of the quantum dots structure and shape evolution and, finally, on mechanisms of such nanoparticle formation.

Keywords: colloidal quantum dots, shape evolution, silver doping, tetrapods

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Authors: Sergio Tovar-Pérez, Sebastian Töpfer, Markus Gräfe

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The work proposes a technique that decreases the detection acquisition time of quantum holography schemes down to one-third; this allows the possibility to image moving objects. Since its invention, quantum holography with undetected photon schemes has gained interest in the scientific community. This is mainly due to its ability to tailor the detected wavelengths according to the needs of the scheme implementation. Yet this wavelength flexibility grants the scheme a wide range of possible applications; an important matter was yet to be addressed. Since the scheme uses digital phase-shifting techniques to retrieve the information of the object out of the interference pattern, it is necessary to acquire a set of at least four images of the interference pattern along with well-defined phase steps to recover the full object information. Hence, the imaging method requires larger acquisition times to produce well-resolved images. As a consequence, the measurement of moving objects remains out of the reach of the imaging scheme. This work presents the use and implementation of a spatial light modulator along with a digital holographic technique called quasi-parallel phase-shifting. This technique uses the spatial light modulator to build a structured phase image consisting of a chessboard pattern containing the different phase steps for digitally calculating the object information. Depending on the reduction in the number of needed frames, the acquisition time reduces by a significant factor. This technique opens the door to the implementation of the scheme for moving objects. In particular, the application of this scheme in imaging alive specimens comes one step closer.

Keywords: quasi-parallel phase shifting, quantum imaging, quantum holography, quantum metrology

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Erdem Elibol, Musa Cadırcı, Nedim Tutkun

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Recently, colloidal quantum dots (CQDs) have drawn increasing attention due to their unique size tunability, which makes them potential candidates for numerous applications including photovoltaic, LEDs, and imaging. However, the main challenge to exploit CQDs properly is that there has not been an effective method to produce them with highly crystalline form and narrow size dispersion. Hot injection method is one of the widely used techniques to produce high-quality nanoparticles. In this method, the key parameter is to reduce the time for injection of the precursors into each other, which yields fast and constant nucleation rate and hence to highly monodisperse QDs. In conventional hot injection method, the injection of precursors is carried out using standard lab syringes with long needles. However, this technique is relatively slow and thus will result in poor optical properties in QDs. In this work, highly luminescent CdTe QDs were synthesised by transferring hot precursors into each other using cannula method. Unlike regular syringe technique, with the help of high pressure difference between two precursors’ flasks and wide cross-section of cannula, the hot cannulation process is too short which yields narrow size distribution and high quantum yield of CdTe QDs. Here QDs with full width half maximum (FWHM) of 28 nm was achieved. In addition, the photoluminescence quantum yield of our samples was measured to be about 21 ± 0.9 which is at least twice the previous record values for CdTe QDs wherein syringe was used to transfer precursors.

Keywords: CdTe, hot injection method, luminescent, quantum dots

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Authors: John Pomerat, Aviv Segev

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Recently, deep learning has had many theoretical breakthroughs. For deep learning to be successful in the industry, however, there need to be practical algorithms capable of handling many real-world hiccups preventing the immediate application of a learning algorithm. Although AI promises to revolutionize the healthcare industry, getting access to patient data in order to train learning algorithms has not been easy. One proposed solution to this is data- sharing. In this paper, we propose an alternative protocol, based on multi-party computation, to train deep learning models while maintaining both the privacy and security of training data. We examine three methods of training neural networks in this way: Transfer learning, average ensemble learning, and series network learning. We compare these methods to the equivalent model obtained through data-sharing across two different experiments. Additionally, we address the security concerns of this protocol. While the motivating example is healthcare, our findings regarding multi-party computation of neural network training are purely theoretical and have use-cases outside the domain of healthcare.

Keywords: neural network aggregation, multi-party computation, transfer learning, average ensemble learning

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Authors: Erhan Zor, Funda Copur, Asli I. Dogan, Haluk Bingol

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Current trends in the wide-scale sensing technologies rely on the development of miniaturized, rapid and easy-to-use sensing platforms. Quantum dots (QDs) with strong and easily tunable luminescence and high emission quantum yields have become a well-established photoluminescent nanomaterials for sensor applications. Although the majority of the reports focused on the cadmium-based QDs which have toxic effect on biological systems and eventually would cause serious environmental problems, carbon-based quantum dots (CQDs) that do not contain any toxic class elements have attracted substantial research interest in recent years. CQDs are small carbon nanostructures (less than 10 nm in size) with various unique properties and are widely-used in different fields during the last few years. In this respect, chiral nanostructures have become a promising class of materials in various areas such as pharmacology, catalysis, bioanalysis and (bio)sensor technology due to the vital importance of chirality in living systems. We herein report the synthesis of chiral CQDs with D- or L-tartaric acid as precursor materials. The optimum experimental conditions were examined and the purification procedure was performed using ethanol/water by column chromatography. The purified chiral CQDs were characterized by UV-Vis, FT-IR, XPS, PL and TEM techniques. The resultants display different photoluminescent characteristics due to the size and conformational difference. Considering the results, it can be concluded that chiral CQDs is expected to be used as optical chiral sensor in different platforms.

Keywords: carbon quantum dots, chirality, sensor, tartaric acid

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Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

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Authors: H. Vargova, J. Strecka, N. Tomasovicova

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A rigorous analytical treatment, with the help of a concept of negativity, is used to study the quantum and thermal entanglement in an isotropic mixed spin-(1/2,S) Heisenberg dimer. The effect of the spin-S magnitude, as well as the effect of diversity between Landé g-factors of magnetic constituents on system entanglement, is exhaustively analyzed upon the variation of the external magnetic and electric field, respectively. It was identified that the increasing magnitude of the spin-S species in a mixed spin-(1/2,S) Heisenberg dimer with comparative Landé g-factors have always a reduction effect on a degree of the quantum entanglement, but it strikingly shifts the thermal entanglement to the higher temperatures. Surprisingly, out of the limit of identical Landé g-factors, the increasing magnitude of spin-S entities can enhance the system entanglement in both low and high magnetic fields. Besides this, we identify that the analyzed dimer with a high-enough magnitude of the spin-S entities at a sufficiently high magnetic field can exhibit unconventional thermally driven re-entrance between the entangled and unentangled mixed state. The importance of the electric-field stimuli is also discussed in detail.

Keywords: quantum and thermal entantanglement, mixed spin Heisenberg model, negativity, reentrant phase transition

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Authors: U. V. S. Seshavatharam, S. Lakshminarayana

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In a unified approach observed cosmic red shift can be re-interpreted as an index of cosmological galactic atomic light emission phenomenon. By increasing the applications of Hubble volume in cosmology as well as in quantum physics, concepts of ‘Black Hole Cosmology’ can be well-confirmed. Clearly speaking ‘quantum mechanics’ can be shown to be a branch of ‘black hole cosmology’. In Big Bang Model, confirmation of all the observations directly depend on the large scale galactic distances that are beyond human reach and raise ambiguity in all respects. The subject of modern black hole physics is absolutely theoretical. Advantage of Black hole cosmology lies in confirming its validity through the ground based atomic and nuclear experimental results.

Keywords: Hubble volume, black hole cosmology, CMBR energy density, Planck’s constant, fine structure ratio, cosmic time, nuclear charge radius, unification

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Authors: Sheng-Po Tseng, Che-Hua Yang

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Motivation and Objective: Ultrasonic guided waves become an important tool for nondestructive evaluation of structures and components. Guided waves are used for the purpose of identifying defects or evaluating material properties in a nondestructive way. While guided waves are applied for evaluating material properties, instead of knowing the properties directly, preliminary signals such as time domain signals or frequency domain spectra are first revealed. With the measured ultrasound data, inversion calculation can be further employed to obtain the desired mechanical properties. Methods: This research is development of high speed inversion calculation technique for obtaining full-field mechanical properties from the quantitative laser ultrasound visualization system (QLUVS). The quantitative laser ultrasound visualization system (QLUVS) employs a mirror-controlled scanning pulsed laser to generate guided acoustic waves traveling in a two-dimensional target. Guided waves are detected with a piezoelectric transducer located at a fixed location. With a gyro-scanning of the generation source, the QLUVS has the advantage of fast, full-field, and quantitative inspection. Results and Discussions: This research introduces two important tools to improve the computation efficiency. Firstly, graphic procession unit (GPU) with large amount of cores are introduced. Furthermore, combining the CPU and GPU cores, parallel procession scheme is developed for the inversion of full-field mechanical properties based on the QLUVS data. The newly developed inversion scheme is applied to investigate the computation efficiency for single-layered and double-layered plate-like samples. The computation efficiency is shown to be 80 times faster than unparalleled computation scheme. Conclusions: This research demonstrates a high-speed inversion technique for the characterization of full-field material properties based on quantitative laser ultrasound visualization system. Significant computation efficiency is shown, however not reaching the limit yet. Further improvement can be reached by improving the parallel computation. Utilizing the development of the full-field mechanical property inspection technology, full-field mechanical property measured by non-destructive, high-speed and high-precision measurements can be obtained in qualitative and quantitative results. The developed high speed computation scheme is ready for applications where full-field mechanical properties are needed in a nondestructive and nearly real-time way.

Keywords: guided waves, material characterization, nondestructive evaluation, parallel processing

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Authors: Vinai K. Singh

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For reducing impulsive noise without degrading image contours, median filtering is a powerful tool. In multiband images as for example colour images or vector fields obtained by optic flow computation, a vector median filter can be used. Vector median filters are defined on the basis of a suitable distance, the best performing distance being the Euclidean. Euclidean distance is evaluated by using the Euclidean norms which is quite demanding from the point of view of computation given that a square root is required. In this paper an optimal piece-wise linear approximation of the Euclidean norm is presented which is applied to vector median filtering.

Keywords: euclidean norm, quasi euclidean norm, vector median filtering, applied mathematics

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Authors: Ebrahim Alrashed, Yousef Rafique

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Mobile devices have drastically changed the way we do things on the move. They are being extremely relied on to perform tasks that are analogous to desktop computer capability. There has been a rapid increase of computational power on these devices; however, battery technology is still the bottleneck of evolution. The primary modern approach day approach to tackle this issue is offloading computation to the cloud, proving to be latency expensive and requiring high network bandwidth. In this paper, we explore efforts to perform barter-based mobile-to-mobile offloading. We present define a protocol and present an architecture to facilitate the development of such a system. We further highlight the deployment and security challenges.

Keywords: computational offloading, power conservation, cloud, sandboxing

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Authors: Peter M. Maurer Maurer

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DGL is a context free grammar-based tool for generating random data. Many types of simulator input data require some computation to be placed in the proper format. For example, it might be necessary to generate ordered triples in which the third element is the sum of the first two elements, or it might be necessary to generate random numbers in some sorted order. Although DGL is universal in computational power, generating these types of data is extremely difficult. To overcome this problem, we have enhanced DGL to include features that permit direct computation within the structure of a context free grammar. The features have been implemented as special types of productions, preserving the context free flavor of DGL specifications.

Keywords: DGL, Enhanced Context Free Grammars, Programming Constructs, Random Data Generation

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Authors: Damir Latypov

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A hybrid classical-quantum algorithm to solve boundary integral equations (BIE) arising in problems of electromagnetic and acoustic scattering is proposed. The quantum speed-up is due to a Quantum Linear System Algorithm (QLSA). The original QLSA of Harrow et al. provides an exponential speed-up over the best-known classical algorithms but only in the case of sparse systems. Due to the non-local nature of integral operators, matrices arising from discretization of BIEs, are, however, dense. A QLSA for dense matrices was introduced in 2017. Its runtime as function of the system's size N is bounded by O(√Npolylog(N)). The run time of the best-known classical algorithm for an arbitrary dense matrix scales as O(N².³⁷³). Instead of exponential as in case of sparse matrices, here we have only a polynomial speed-up. Nevertheless, sufficiently high power of this polynomial, ~4.7, should make QLSA an appealing alternative. Unfortunately for the QLSA, the asymptotic separability of the Green's function leads to high compressibility of the BIEs matrices. Classical fast algorithms such as Multilevel Fast Multipole Method (MLFMM) take advantage of this fact and reduce the runtime to O(Nlog(N)), i.e., the QLSA is only quadratically faster than the MLFMM. To be truly impactful for computational electromagnetics and acoustics engineers, QLSA must provide more substantial advantage than that. We propose a computational scheme which combines elements of the classical fast algorithms with the QLSA to achieve the required performance.

Keywords: quantum linear system algorithm, boundary integral equations, dense matrices, electromagnetic scattering theory

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Authors: S. M. Giripunje, Shikha Jindal

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Zinc sulphide (ZnS) quantum dots (QDs) were synthesized successfully via simple sonochemical method. X-ray diffraction (XRD), scanning electron microscopy (SEM) and high resolution transmission electron microscopy (HRTEM) analysis revealed the average size of QDs of the order of 3.7 nm. The band gap of the QDs was tuned to 5.2 eV by optimizing the synthesis parameters. UV-Vis absorption spectra of ZnS QD confirm the quantum confinement effect. Fourier transform infrared (FTIR) analysis confirmed the formation of single phase ZnS QDs. To fabricate the diode, blend of ZnS QDs and P3HT was prepared and the heterojunction of PEDOT:PSS and the blend was formed by spin coating on indium tin oxide (ITO) coated glass substrate. The diode behaviour of the heterojunction was analysed, wherein the ideality factor was found to be 2.53 with turn on voltage 0.75 V and the barrier height was found to be 1.429 eV. ZnS-Graphene QDs nanocomposite was characterised for the surface morphological study. It was found that the synthesized ZnS QDs appear as quasi spherical particles on the graphene sheets. The average particle size of ZnS-graphene nanocomposite QDs was found to be 8.4 nm. From voltage-current characteristics of ZnS-graphene nanocomposites, it is observed that the conductivity of the composite increases by 10⁴ times the conductivity of ZnS QDs. Thus the addition of graphene QDs in ZnS QDs enhances the mobility of the charge carriers in the composite material. Thus, the graphene QDs, with high specific area for a large interface, high mobility and tunable band gap, show a great potential as an electron-acceptors in photovoltaic devices.

Keywords: graphene, heterojunction, quantum confinement effect, quantum dots(QDs), zinc sulphide(ZnS)

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Authors: Sebastian Töpfer, Marta Gilaberte Basset, Jorge Fuenzalida, Fabian Steinlechner, Juan P. Torres, Markus Gräfe

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This work introduces a combination of digital phase-shifting holography with a non-linear interferometer using undetected photons. Non-linear interferometers can be used in combination with a measurement scheme called quantum imaging with undetected photons, which allows for the separation of the wavelengths used for sampling an object and detecting it in the imaging sensor. This method recently faced increasing attention, as it allows to use of exotic wavelengths (e.g., mid-infrared, ultraviolet) for object interaction while at the same time keeping the detection in spectral areas with highly developed, comparable low-cost imaging sensors. The object information, including its transmission and phase influence, is recorded in the form of an interferometric pattern. To collect these, this work combines the method of quantum imaging with undetected photons with digital phase-shifting holography with a minimal sampling of the interference. With this, the quantum imaging scheme gets extended in its measurement capabilities and brings it one step closer to application. Quantum imaging with undetected photons uses correlated photons generated by spontaneous parametric down-conversion in a non-linear interferometer to create indistinguishable photon pairs, which leads to an effect called induced coherence without induced emission. Placing an object inside changes the interferometric pattern depending on the object’s properties. Digital phase-shifting holography records multiple images of the interference with determined phase shifts to reconstruct the complete interference shape, which can afterward be used to analyze the changes introduced by the object and conclude its properties. An extensive characterization of this method was done using a proof-of-principle setup. The measured spatial resolution, phase accuracy, and transmission accuracy are compared for different combinations of camera exposure times and the number of interference sampling steps. The current limits of this method are shown to allow further improvements. To summarize, this work presents an alternative holographic measurement method using non-linear interferometers in combination with quantum imaging to enable new ways of measuring and motivating continuing research.

Keywords: digital holography, quantum imaging, quantum holography, quantum metrology

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Authors: Jing Zhang, Daniel Nikovski

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We propose an approximation algorithm called LINKUMP to compute the Pan Matrix Profile (PMP) under the unnormalized l∞ distance (useful for value-based similarity search) using double-ended queue and linear interpolation. The algorithm has comparable time/space complexities as the state-of-the-art algorithm for typical PMP computation under the normalized l₂ distance (useful for shape-based similarity search). We validate its efficiency and effectiveness through extensive numerical experiments and a real-world anomaly detection application.

Keywords: pan matrix profile, unnormalized euclidean distance, double-ended queue, discord discovery, anomaly detection

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Authors: Mahsa Fathollahzadeh

Abstract:

The quick advancement of nanotechnology necessitates the creation of innovative theoretical approaches to elucidate complex experimental findings and forecast novel capabilities of nanodevices. Therefore, over the past ten years, a difficult task in quantum chemistry has been comprehending electron and spin transport in molecular devices. This thorough evaluation presents a comprehensive overview of current research and its status in the field of molecular electronics, emphasizing the theoretical applications to various device types and including a brief introduction to theoretical methods and their practical implementation plan. The subject matter includes a variety of molecular mechanisms like molecular cables, diodes, transistors, electrical and visual switches, nano detectors, magnetic valve gadgets, inverse electrical resistance gadgets, and electron tunneling exploration. The text discusses both the constraints of the method presented and the potential strategies to address them, with a total of 183 references.

Keywords: chemistry, nanotechnology, quantum, molecule, spin

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Authors: Moustafa Osman Mohammed

Abstract:

The photocurrent generations are influencing ultra-high efficiency solar cells based on self-assembled quantum dot (QD) nanostructures. Nanocrystal quantum dots (QD) provide a great enhancement toward solar cell efficiencies through the use of quantum confinement to tune absorbance across the solar spectrum enabled multi-exciton generation. Based on theoretical predictions, QDs have potential to improve systems efficiency in approximate regular electrons excitation intensity greater than 50%. In solar cell devices, an intermediate band formed by the electron levels in quantum dot systems. The spatial architecture is exploring how can solar cell integrate and produce not only high open circuit voltage (> 1.7 eV) but also large short-circuit currents due to the efficient absorption of sub-bandgap photons. In the proposed QD system, the structure allows barrier material to absorb wavelengths below 700 nm while multi-photon processes in the used quantum dots to absorb wavelengths up to 2 µm. The assembly of the electronic model is flexible to demonstrate the atoms and molecules structure and material properties to tune control energy bandgap of the barrier quantum dot to their respective optimum values. In terms of energy virtual conversion, the efficiency and cost of the electronic structure are unified outperform a pair of multi-junction solar cell that obtained in the rigorous test to quantify the errors. The milestone toward achieving the claimed high-efficiency solar cell device is controlling the edge causes of energy bandgap between the barrier material and quantum dot systems according to the media design limits. Despite this remarkable potential for high photocurrent generation, the achievable open-circuit voltage (Voc) is fundamentally limited due to non-radiative recombination processes in QD solar cells. The orientation of voltage recovery system is compared theoretically with experimental Voc variation in mediation upper–limit obtained one diode modeling form at the cells with different bandgap (Eg) as classified in the proposed spatial architecture. The opportunity for improvement Voc is valued approximately greater than 1V by using smaller QDs through QD solar cell recovery systems as confined to other micro and nano operations states.

Keywords: nanotechnology, photovoltaic solar cell, quantum systems, renewable energy, environmental modeling

Procedia PDF Downloads 155