Data clustering is a vital tool for data analysis. This work shows that some existing useful methods in data clustering are actually based on quantum mechanics and can be assembled into a powerful and accurate data clustering method where the efficie...
Nearest-neighbour clustering is a simple yet powerful machine learning algorithm that finds natural application in the decoding of signals in classical optical-fibre communication systems. Quantum k-means clustering promises a speed-up over the class...
Quantum computing is one of the most promising solutions for solving optimization problems in the healthcare world. Quantum computing development aims to light up the execution of a vast and complex set of algorithmic instructions. For its implementa...
In real-world scenarios, identifying the optimal number of clusters in a dataset is a difficult task due to insufficient knowledge. Therefore, the indispensability of sophisticated automatic clustering algorithms for this purpose has been contemplate...
Lead isotope ratios are frequently used in archaeometric provenance analysis; however, the overlap of isotopic fields within the Andean metallogenic belt complicates reliable provenance determination. This study presents a reproducible fidelity-based...
Advancements in communication technologies and the proliferation of smart devices have significantly increased the demand for wireless sensor networks (WSNs). These networks play an important role in the IoT environment. The wireless sensor network h...
Recently, the volume of the generated data has increased significantly, leading to the need for computational techniques capable of handling such data efficiently. As a result, many quantum algorithms have been developed, and the domain of quantum ma...
Clustering may uncover latent behavioral structure in Autism Spectrum Disorder (ASD) screening data without using outcome labels, but the resulting partitions depend strongly on data geometry and the adopted similarity measure. Quantum-hybrid cluster...
In the era of data-driven education, educational social networks generate large volumes of high-dimensional and complex-structured data through learner interactions, collaborative activities, and resource-sharing behaviors, posing significant challen...
Quantum computing requires large numbers of resources of entangled qubits, which cannot be satisfied using traditional methods of entanglement generation, such as optical systems. Therefore, we need more efficient ways of entanglement generation. It...
This paper proposes an energy-efficient cluster head selection method in the wireless ad hoc network by using a hybrid quantum-classical approach. The wireless ad hoc network is divided into several clusters via cluster head selection, and the perfor...
Clustering is an effective topology control approach that evenly distributes loads across sensor nodes, enhances network scalability, and increases the lifetime in wireless sensor networks. In this paper, we propose a novel energy-efficient weighted...
The blind quantum computation (BQC) protocol allows for privacy-preserving remote quantum computations. In this paper, we introduce a remote quantum error correction code preparation protocol for BQC using a cluster state and analyze its blindness in...
Many quantum algorithms for machine learning require access to classical data in superposition. However, for many natural data sets and algorithms, the overhead required to load the data set in superposition can erase any potential quantum speedup ov...
In this paper, we introduce a quantum private comparison (QPC) protocol designed for two players to securely and privately assess the equality of their private information. The protocol utilizes four-particle cluster states prepared by a semi-honest...
A widely used clustering algorithm, density peak clustering (DPC), assigns different attribute values to data points through the distance between data points, and then determines the number and range of clustering by attribute values. However, DPC is...
Nuclear quantum effects play a significant role in the dissociation dynamics of HCl ions during collisions with the (H2O)49 ice cluster. These effects become particularly important when analyzing proton transfer, tunneling, and zero-point energy cont...
The theoretical description of water properties continues to be a challenge. Using quantum cluster equilibrium (QCE) theory, we combine state-of-the-art quantum chemistry and statistical thermodynamic methods with the almost historical Clausius&ndash...
Cluster molecular magnets prove their potential for applications in quantum technologies, encouraging studies of quantum entanglement in spin systems. In the paper we discuss quantum entanglement properties of pentamer cluster composed of spins
Quantum computing leverages the principles of quantum mechanics in novel ways to tackle complex chemistry problems that cannot be accurately addressed using traditional quantum chemistry methods. However, the high computational cost and available num...
The satellite-mediated continuous-variable quantum key distribution (CV-QKD) protocol, which relies on off-the-shelf telecommunication components, has the potential for a global quantum communication network with all-day operation. However, the trans...
Great progress has been made in recent years towards understanding the properties of disordered electronic systems. In part, this is made possible by recent advances in quantum effective medium methods which enable the study of disorder and electron-...
A quantum private comparison (QPC) protocol enables two parties to securely compare their private data without disclosing the actual values to one another, utilizing quantum mechanics to maintain confidentiality. Many current QPC protocols mainly con...
Hydrogen-bond organization plays a central role in determining the structure and properties of water from molecular to macroscopic scales. In this study, we propose a geometry-based descriptor for small hydrogen-bonded water clusters, (H2O)n, with n...
Quantum private comparison (QPC) enables two users to securely conduct private comparisons in a network characterized by mutual distrust while guaranteeing the confidentiality of their private inputs. Most previous QPC protocols were primarily used t...
The variational quantum eigensolver is one of the most promising algorithms for near-term quantum computers. It has the potential to solve quantum chemistry problems involving strongly correlated electrons with relatively low-depth circuits, which ar...
The main limitation of wireless sensor networks (WSNs) lies in their reliance on battery power. Therefore, the primary focus of the current research is to determine how to transmit data in a rational and efficient way while simultaneously extending t...
In the present study, the predication of the binding affinity (log RBA) of estrogen receptor alpha with three categories of environmental endocrine disrupting chemicals (EDCs), namely, PCB, phenol, and DDT, is performed by the quantum chemical geneti...
In the present study, the interaction between organophosphorus pesticides and cholinesterase enzymes was investigated by quantum chemical cluster model and hard-soft acid-base (HSAB) approaches. The computational results of the equilibrium structure...
Recent advancements in experimental approaches have made it possible to synthesize silver (Ag5) atomic quantum clusters (AQCs), which have shown a great potential in photocatalysis. This study employs the generalized gradient approximation (GGA) dens...
Blockchain (BC) with a clustering scheme can be used to build secure and smart Vehicular Ad-Hoc Networks (VANETs), which provide improved data integrity, enhanced security, efficient resource allocation, and streamlined processes. This technology has...
Quantum entanglement plays a fundamental role in quantum mechanics, with applications in quantum computing. This study introduces a new approach that integrates quantum simulations, noise analysis, and fuzzy clustering to classify and evaluate the st...
Complex networks structures have been extensively used for describing complex natural and technological systems, like the Internet or social networks. More recently, complex network theory has been applied to quantum systems, where complex network to...
The Rio Santiago basin is one of the most environmentally stressed river systems in Mexico, with persistent organic, nutrient, microbial, surfactant, and metal contamination. This study develops a near-term quantum machine learning workflow for envir...
The chemistry community has long sought the exact relationship between the conventional and the unitary coupled cluster ansatz for a single-reference system, especially given the interest in performing quantum chemistry on quantum computers. In this...
Reducing the size from the bulk material to nanoparticles produces a scaling behavior in physical properties in the later ones, due to the large surface-to-volume fraction. By further size reduction, entering into the subnanometric cluster region, ph...
Sparse count data, such as patent document–keyword matrices, often contain excessive zeros and overdispersion, making conventional distance-based clustering methods less suitable. This study proposes a zero-inflated likelihood-based graph neura...
We analyze the many-body phases of an ensemble of particles interacting via a Lifshitz–Petrich–Gaussian pair potential in a harmonic confinement. We focus on specific parameter regimes where we expect decagonal quasiperiodic cluster arran...
Two-dimensional quantum billiards are one of the most important paradigms for exploring the connection between quantum and classical worlds. Researchers are mainly focused on nonintegrable and irregular shapes to understand the quantum characteristic...
Advances in quantum computing technology have been made in recent years due to the evolution of spin clusters. Recent studies have tended towards spin cluster subgeometries to understand more complex structures better. These molecular magnets provide...
Trust in embodied intelligence is dynamic, contextual, and interaction-dependent, but many existing computational approaches still model trust using static similarity structures. This study proposes and evaluates a compositional trust modeling approa...
This paper proposes a dynamic unmanned aerial vehicle (UAV) clustering model for multi-target localization in complex 3D environments, where mobility-aware cluster formation is integrated to enhance collaborative localization accuracy. We derive the...
By utilizing the non-maximally entangled four-qubit cluster states as the quantum channel, we first propose a hierarchical quantum information splitting scheme of arbitrary three-qubit states among three agents with a certain probability. Then we gen...
Multipartite Gaussian Einstein–Podolsky–Rosen (EPR) steering is a key resource for quantum networks, but in practice it is strongly degraded by channel loss and excess noise. This motivates the need to distill multipartite Gaussian EPR st...
Post-COVID-19 balance and postural control alterations have been reported after SARS-CoV-2 infection, but individual-level phenotyping remains challenging because post-acute sequelae are heterogeneous and often lack clear clinical ground truths. We a...
The double-cubane cluster (DCC) refers to an [Fe8S9] iron-sulfur complex that is otherwise only known to exist in nitrogenases. Containing a bridging µ2-S ligand, the DCC in the DCC-containing protein (DCCP) is covalently linked to the protein scaffo...
Quantum information splitting (QIS) provides an idea for transmitting the quantum state through a classical channel and a preshared quantum entanglement resource. This paper presents a new scheme for QIS based on a five-qubit cluster state and a Bell...
This paper is devoted to the foundational problems of dendrogramic holographic theory (DH theory). We used the ontic–epistemic (implicate–explicate order) methodology. The epistemic counterpart is based on the representation of data by dendrograms co...
The electronic structures and transition properties of three types of triangle MoS2 clusters, A (Mo edge passivated with two S atoms), B (Mo edge passivated with one S atom), and C (S edge) have been explored using quantum chemistry methods. The high...
Hyperspectral image (HSI) clustering has attracted significant attention due to its broad applications in agricultural monitoring, environmental protection, and other fields. However, the integration of high-dimensional spectral and spatial informati...
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