Search Results (1,984)

We present a comprehensive computational study of UV/Vis absorption spectra of significant food colorants, specifically anthocyanins and curcumin tautomers, dissolved in polar protic solvents, namely water and ethanol. The absorption spectra are simulated using two fully polarizable quantum mechanical (QM)/molecular mechanics (MM) models based on the fluctuating charge (FQ) and fluctuating charge and dipoles (FQF$\mu$) force fields. To accurately capture the dynamical aspects of the solvation phenomenon, atomistic approaches are combined with configurational sampling obtained through classical molecular dynamics (MD) simulations. The calculated QM/FQ and QM/FQF$\mu$ spectra are then compared with experiments. Our findings demonstrate that a precise reproduction of the UV/Vis spectra of the studied pigments can be achieved by adequately accounting for configurational sampling, polarization effects, and hydrogen bonding interactions. Full article

This study demonstrates the existence of an evanescent electron wave outside both finite and infinite quantum wells by solving the Dirac equation and ensuring the continuity of the spinor wavefunction at the boundaries. We show that this evanescent wave shares the spin characteristics of the wave confined within the well, as indicated by analytical expressions for the current density across all regions. Our findings suggest that the electron cannot be confined to a mathematical singularity and that quantum information, or quantum entropy, can leak through any quantum confinement. These results emphasize that the electron wave, fully characterized by Lorentz-invariant charge and current densities, should be considered the true and sole entity of the electron. Full article

Earth data is essential for global environmental studies. Many Earth data types are naturally modeled by multidimensional arrays (tensors). Array (Tensor) DBMSs strive to be the best systems for tensor-related workloads and can be especially helpful for Earth data engineering, which takes up to 80% of Earth data science. We present a new quantum Array (Tensor) DBMS data model and new quantum approaches that rely on the upcoming quantum memory and demonstrate exponential speedups when applied to many toughest Array (Tensor) DBMS challenges stipulated by classical computing and real-world Earth data use-cases. We also propose new types of charts: Quantum Gantt (QGantt) Charts and Quantum Network Diagrams (QND). QGantt charts clearly illustrate how multiple operations occur simultaneously across different data items and what are the input/output data dependencies between these operations. Unlike traditional Gantt charts, which typically track project timelines and resources, QGantt charts integrate specific data items and operations over time. A Quantum Network Diagram combines several QGantt charts to show dependencies between multistage operations, including their inputs/outputs. By using a static format, QGantt charts and Quantum Network Diagrams allow users to explore complex processes at their own pace, which can be beneficial for educational and R&D purposes. Full article

The energy industry is experiencing a major change due to fast progress in artificial intelligence (AI). Startup companies in this revolution use AI technologies like Machine Learning (ML), predictive analytics, and optimization algorithms to improve energy efficiency, optimize grid management, and incorporate renewable energy sources. AI-powered solutions allow for a more accurate prediction of demand, immediate monitoring, and automated decision-making processes, significantly enhancing operational efficiency and sustainability. Through promoting a more effective energy system, these advancements play a vital role in the worldwide battle against climate change and carbon dioxide emissions. Adding to the progress of AI, quantum computing (QC) shows great potential despite being a nascent area. The collaboration of AI and QC is poised to transform the energy industry by offering unmatched computational capabilities. This blend of technologies can tackle intricate energy obstacles like enhancing power grids and enhancing battery storage, which traditional computers cannot currently handle. Combining QC with AI speeds up innovation, providing advanced solutions that improve the resilience and efficiency of energy networks. This paper discusses the latest advancements, possible effects, and upcoming paths of new companies leading in AI and QC innovations within the energy industry. Their joint responsibility is highlighted in advancing a sustainable and intelligent energy future, as well as tackling crucial environmental issues and lessening the impact of climate change. Full article

Here, we present a general framework for computing the infrared anharmonic vibrational spectra of polyatomic molecules using Born–Oppenheimer molecular dynamics (BOMD) with PyRAMD software. To account for nuclear quantum effects, we suggest using a simplified Wigner sampling (SWS) approach simultaneously coupled with Andersen and Berendsen thermostats. We propose a new criterion for selecting the parameter of the SWS based on the molecules’ harmonic vibrational frequencies and usage of the large-time-step blue shift correction, allowing for a decrease in computational expenses. For the Fourier transform of the dipole moment autocorrelation function, we propose using the regularized least-squares analysis, which allows us to obtain higher-frequency resolution than with the direct application of fast Fourier transform. Finally, we suggest the usage of the pre-parameterized scaling factors for the IR spectra from BOMD, also providing the scaling factors for the spectra at the BLYP-D3(BJ)/6-31G, PBE-D3(BJ)/6-31G, and PBEh-3c levels of theory. Full article

We investigate the implications of different quantization approaches in Loop Quantum Cosmology for the primordial power spectrum of tensor modes. Specifically, we consider the hybrid and dressed metric approaches to derive the effective mass that governs the evolution of the tensor modes. Our study comprehensively examines the two resulting effective masses and how to estimate them in order to obtain approximated analytic solutions to the tensor perturbation equations. Since Loop Quantum Cosmology incorporates preinflationary effects in the dynamics of the perturbations, we do not have at our disposal a standard choice of privileged vacuum, like the Bunch–Davies state in quasi-de Sitter inflation. We then select the vacuum state by a recently proposed criterion which removes unwanted oscillations in the power spectrum and guarantees an asymptotic diagonalization of the Hamiltonian in the ultraviolet. This vacuum is usually called the NO-AHD (from the initials of Non-Oscillating with Asymptotic Hamiltonian Diagonalization) vacuum. Consequently, we compute the power spectrum by using our analytic approximations and by introducing a suitable numerical procedure, adopting in both cases an NO-AHD vacuum. With this information, we compare the different spectra obtained from the hybrid and the dressed metric approaches, as well as from the analytic and numerical procedures. In particular, this proves the remarkable accuracy of our approximations. Full article

Quantum optimization is a significant area of quantum computing research with anticipated near-term quantum advantages. Current quantum optimization algorithms, most of which are hybrid variational-Hamiltonian-based algorithms, struggle to present quantum devices due to noise and decoherence. Existing techniques attempt to mitigate these issues through employing different Hamiltonian encodings or Hamiltonian clause pruning, but they often rely on optimistic assumptions rather than a deep analysis of the problem structure. We demonstrate how to formulate the problem Hamiltonian for a quantum approximate optimization algorithm that satisfies all the requirements to correctly describe the considered tactical aircraft deconfliction problem, achieving higher probabilities for finding solutions compared to previous works. Our results indicate that constructing Hamiltonians from an unconventional, quantum-specific perspective with a high degree of entanglement results in a linear instead of exponential number of entanglement gates instead and superior performance compared to standard formulations. Specifically, we achieve a higher probability of finding feasible solutions: finding solutions in nine out of nine instances compared to standard Hamiltonian formulations and quadratic programming formulations known from quantum annealers, which only found solutions in seven out of nine instances. These findings suggest that there is substantial potential for further research in quantum Hamiltonian design and that gate-based approaches may offer superior optimization performance over quantum annealers in the future. Full article

The effect of increased corrosion in re-enforcement structures has led to the need to identify and develop more inexpensive, non-toxic, eco-friendly and readily available inhibitors from natural resources. Extensive research and development have led to the discovery of new classes of green corrosion inhibitors. In this work, Tilapia fish scales (FSs) were used as a green corrosion inhibitor as they are abundant in both organic components, such as collagen (C₁₂H₁₉N₃O₅), and inorganic components, such as hydroxyapatite (Ca₁₀(PO₄)₆(OH)₂). The FSs were subjected to a maceration process to extract all the inorganic and organic compounds. The FS extract was then characterised using an X-ray diffractometer (XRD), a scanning electron microscope (SEM) and Fourier transform infra-red (FTIR). Quantum computational studies were conducted in order to determine parameters such as the energy of the highest occupied molecular orbital (EHOMO) and the energy of the lowest occupied molecular orbital (ELUMO). The Gaussian 09 program density functional theory at the 6-311++(d,p) basis set was used to investigate the interaction between the organic and inorganic molecules, therefore examining both interaction energies. The XRD results confirmed that a large amount of hydroxyapatite was present in the extract, with a high diffractive peak at 32θ and small amounts of collagen picked up between 13θ and 25θ. SEM results showed the percentage weight of atoms, such as carbon (19.8%), calcium (27%), oxygen (41.3%) and phosphate (11.9%), which were found to be present in both the organic and inorganic part of the FS sample. FTIR results confirmed the presence of hydroxyl (3200–3500 cm⁻¹), carbonate (1620–1700 cm⁻¹) and phosphate groups (1200–800 cm⁻¹). The computation studies showed that hydroxyapatite was the most reactive molecule, as it had the highest EHOMO of −0.2076 eV compared with that of collagen at −0.2470 eV. The interaction energy of the FS molecule was −615 kJ/mol. Full article

As the relationship between energy and information loss and reversible gates was revealed, much interest in reversible gate design arose, and as quantum-dot cellular automata (QCA) gained attention as a next-generation nano circuit design technology, various reversible gates based on QCA emerged. The proposed study optimizes the performance and design costs of existing QCA-based reversible gates including TR, RUG, PQR, and URG. According to most indicators, the proposed circuits showed significant improvement rates and outperformed existing studies. In particular, the proposed optimal TR, RUG, PQR, and URG showed performance improvements of 266%, 265%, 300%, and 144% in Cost_AD, respectively, compared with the best existing circuit. This shows outstanding improvement and superiority in terms of area and delay, which are the most important factors in the performance of nano-scale circuits that are becoming extremely miniaturized. Additionally, the exceptionally high-output polarization of the proposed circuits is an important indicator of the circuit’s expansion and connection and increases the circuit’s reliability. Full article

We demonstrate a Sn-doped monoclinic gallium oxide (β-Ga₂O₃)-based deep ultraviolet (DUV) phototransistor with high area coverage and manufacturing efficiency. The threshold voltage (V_T) switches between negative and positive depending on the β-Ga₂O₃ channel thickness and doping concentration. Channel depletion and Ga diffusion during manufacturing significantly influence device characteristics, as validated through computer-aided design (TCAD) simulations, which agree with the experimental results. We achieved enhancement-mode (e-mode) operation in <10 nm-thick channels, enabling a zero V_G to achieve a low dark current (1.84 pA) in a fully depleted equilibrium. Quantum confinement in thin β-Ga₂O₃ layers enhances UV detection (down to 210 nm) by widening the band gap. Compared with bulk materials, dimensionally constrained optical absorption reduces electron–phonon interactions and phonon scattering, leading to faster optical responses. Decreasing β-Ga₂O₃ channel thickness reduces V_T and V_G, enhancing power efficiency, dark current, and the photo-to-dark current ratio under dark and illuminated conditions. These results can guide the fabrication of tailored Ga₂O₃-based DUV phototransistors. Full article

Recent developments in the quantization of general relativity theory provide a new perspective on matter and even the whole universe. Already, in 1922, Eddington suggested that a future quantum gravity theory had to be linked to Planck length. This is today the main view among many working with quantum gravity. Recently, it has been demonstrated how Planck length, the Planck time, can be extracted from gravity observations with no knowledge of G, ℏ, or even c. Rooted in this, both general relativity theory and multiple other gravity theories can be quantized and linked to the Planck scale. A revelation from this is that matter seems to be ticking at the reduced Compton frequency, where each tick can be seen as one bit, and one bit corresponds to a Planck mass event. This new speculative way of looking at gravity can also potentially tell us considerably about what quantum gravity computers are and what they potentially can do. We will conjecture that that all quantum gravity and quantum gravity computers are directly linked to the Planck scale and the Compton frequency in matter, something we will discuss in this paper. Quantum gravity computers, we will see, in many ways, are nature’s own designed computers with enormous capacity to 3D “print” real time. So, somewhat speculatively, we suggest we live inside a gigantic quantum gravity computer known as the Hubble sphere, and we even are quantum gravity computers. The observable universe is based on this model, basically a quantum gravity computer that calculates approximately ${10}^{104}$ bits per second (bps). Full article

The security of traditional public key cryptography algorithms depends on the difficulty of the underlying mathematical problems. Asymmetric topological encryption is a graph-dependent encryption algorithm produced to resist attacks by quantum computers on these mathematical problems. The security of this encryption algorithm depends on two types of NP-complete problems: subgraph isomorphism and graph coloring. Topological coding technology refers to the technology of generating key strings or topology signature strings through topological coding graphs. We take odd-graceful labeling and set-ordered odd-graceful labeling as limiting functions, and propose two kinds of topological coding generation technique, which we call the random leaf-adding operation and randomly adding edge-removing operation. Through these two techniques, graphs of the same scale and larger scales can be generated with the same type of labeling so as to derive more number strings, expand the key space, and analyze the topology and property of the generated graphs. Full article

Background: In recent years, the advancement of computational chemistry has offered new insights into the rational design of molecularly imprinted polymers (MIPs). From this aspect, our study tried to give quantitative parameters for evaluating imprinting efficiency and exploring the formation mechanism of MIPs by combining simulation and experiments. Methods: The pre-polymerization system of sulfadimethoxine (SDM) was investigated using a combination of quantum chemical (QC) calculations and molecular dynamics (MD) simulations. MIPs were prepared on the surface of silica gel by a surface-initiated supplemental activator and reducing agent atom transfer radical polymerization (SI-SARA ATRP). Results: The results of the QC calculations showed that carboxylic monomers exhibited higher bonding energies with template molecules than carboxylic ester monomers. MD simulations confirmed the hydrogen bonding sites predicted by QC calculations. Furthermore, it was observed that only two molecules of monomers could bind up to one molecule of SDM, even when the functional monomer ratio was up to 10. Two quantitative parameters, namely, the effective binding number (EBN) and the maximum hydrogen bond number (HBN_Max), were defined. Higher values of EBN and HBN_Max indicated a higher effective binding efficiency. Hydrogen bond occupancies and RDF analysis were performed to analyze the hydrogen bond formation between the template and the monomer from different perspectives. Furthermore, under the influence of the EBN and collision probability of the template and the monomers, the experimental results show that the optimal molar ratio of template to monomer is 1:3. Conclusions: The method of monomer screening presented in this study can be extended to future investigations of pre-polymerization systems involving different templates and monomers. Full article

This review provides a summary of the existing literature on a crucial raw material for the production of isotopically pure semiconductors, which are essential for the development of second-generation quantum systems. Silicon-28-tetrafluoride (²⁸SiF₄) is used as an educt for several isotope-engineered chemicals, such as silane-28 (²⁸SiH₄) and silicon-28-trichloride (²⁸SiHCl₃), which are needed in the pursuit of various quantum technologies. We are exploring the entire chain from the synthesis of ²⁸SiF₄ to quantum applications. This includes the chemical properties of SiF₄, isotopic enrichment, conversion to silanes, conversion to bulk ²⁸Si and thin films, the physical properties of ²⁸Si (spin neutrality, thermal conductivity, optical properties), and the applications in quantum computing, photonics, and quantum sensing techniques. Full article

With quantum computers, the quantum resistance of cryptographic systems has gradually attracted attention. To overcome the shortcoming of existing identity-based encryption (IBE) schemes in resisting quantum attacks, we introduce an IBE scheme based on learning with errors (LWE). In addition, devices with limited computing power are becoming increasingly common in practice, making it increasingly important to improve the efficiency of online computation of encryption algorithms. The classic solution is to directly improve the efficiency of the Gaussian sampling algorithm, thereby increasing the overall efficiency of the scheme. However, our scheme combines the efficient Gaussian sampling algorithm, $\mathbf{G}$-trapdoor, with online/offline method to further improve the online encryption efficiency of the encryption algorithm. Our scheme completes partial computation before knowing the message and receiver’s identity, and once the message and receiver’s identity are obtained, the online part encryption can be efficiently completed. We construct an identity-based online/offline encryption (IBOOE) scheme from LWE with $\mathbf{G}$-trapdoor, improve the efficiency of online encryption while achieving quantum resistant security. We prove the scheme’s security under the standard model for chosen-plaintext attack (CPA). By comparing with relevant schemes in terms of experiments and analysis, our scheme has improved efficiency by 65% to 80% compared to the classical LWE IBE scheme (increasing with LWE security parameters), and by 60% to 70% compared to the recent IBE scheme from LWE. This greatly improves the efficiency of online computing for low-power encryption devices while ensuring security. Full article