Academic Articles & Research Papers

Robot-Assisted Augmented Reality (AR)-Guided Surgical Navigation for Periacetabular Osteotomy

Periacetabular osteotomy (PAO) is an effective approach for the surgical treatment of developmental dysplasia of the hip (DDH). However, due to the complex anatomical structure around the hip joint and the limited field of view (FoV) during...

Digital Analysis Methods in Business-Processes and Projects in Digital Twins at Investment-Construction Companies

The article analyzes modeling of investment-construction company work from graph models to digital analogues. Such analysis is necessary in order to build economically grounded twin of the investment-construction company. The need to use ad...

A Two-Dimensional Sequential Packing Method for Lunar Regolith Particles Based on Random Polygons

To accurately characterize the effects of polydisperse particle sizes, multimineral composition, and angular morphology on the packing structure of lunar regolith, a two-dimensional sequential packing method based on random convex octagons ...

Developmental robotics: a survey

Developmental robotics is an emerging field located at the intersection of robotics, cognitive science and developmental sciences. This paper elucidates the main reasons and key motivations behind the convergence of fields with seemingly di...

QUANTUM DISCORD AND QUANTUM COMPUTING — AN APPRAISAL

We discuss models of computing that are beyond classical. The primary motivation is to unearth the cause of non-classical advantages in computation. Completeness results from computational complexity theory lead to the identification of ver...

Technological trajectories in quantum computing to design a quantum ecosystem for industrial change

This study develops a technology analysis to detect technological trajectories in quantum computing that can lay the foundation of a quantum industry. Study design considers data of 10,089 scientific products in ‘quantum computing’ over 198...

Recall Performance for Content-Addressable Memory Using Adiabatic Quantum Optimization

A content-addressable memory (CAM) stores key-value associations such that the key is recalled by providing its associated value. While CAM recall is traditionally performed using recurrent neural network models, we show how to solve this p...

Multimodal deep learning for automated atomic qubits fabrication in silicon

Donor-based spin qubits in silicon are a promising platform for scalable quantum computing due to their long coherence times and high-fidelity gate operations. A viable path for fabricating donor qubit arrays with atomic precision is scanni...

Optimization Strategies in Quantum Machine Learning: A Performance Analysis

This study presents a comprehensive comparison of multiple optimization algorithms applied to a quantum classification model, utilizing the Cleveland dataset. Specifically, the research focuses on three prominent optimizers—COBYLA, L-BFGS-B...

Nonnegative/Binary matrix factorization for image classification using quantum annealing

Abstract Classical computing has borne witness to the development of machine learning. The integration of quantum technology into this mix will lead to unimaginable benefits and be regarded as a giant leap forward in mankind’s ability to co...

Simulation-assisted learning of open quantum systems

Models for open quantum systems, which play important roles in electron transport problems and quantum computing, must take into account the interaction of the quantum system with the surrounding environment. Although such models can be der...

Numerical Study of the Turbulent Flow from a Steam Dumping Pressurizer Relief Tank

Due to the complex geometry and turbulent flow characteristics, it is hard to simulate the process of steam dumping of the pressurizer relief tank (PRT). In this study, we develop a compressible fluid solver PRTFOAM to numerically study the...

Experimental Quantum Computing without Entanglement

Deterministic quantum computation with one pure qubit (DQC1) is an efficient model of computation that uses highly mixed states. Unlike pure-state models, its power is not derived from the generation of a large amount of entanglement. Inste...

Recurrent quantum embedding neural network and its application in vulnerability detection

Abstract In recent years, deep learning has been widely used in vulnerability detection with remarkable results. These studies often apply natural language processing (NLP) technologies due to the natural similarity between code and languag...

Models in quantum computing: a systematic review

Modeling quantum computing in Haskell

The paper develops a model of quantum computing from the perspective of functional programming. The model explains the fundamental ideas of quantum computing at a level of abstraction that is familiar to functional programmers. The model al...

Interplay between charge-density-waves, disorder, and superconductivity in transition metal dichalcogenides

Transition metal dichalcogenides (TMDs) are a fascinating class of materials known for their various electronic properties and potential applications in nanoelectronics, quantum computing, and energy storage. This review explores the intric...

The Role and Application of Matrices in Artificial Intelligence: Foundations, Methods, and Advancements

Matrices are foundational to artificial intelligence (AI), serving as critical tools for data representation, manipulation, and transformation across various applications. From machine learning algorithms to neural network architectures, ma...

Quantum Computing for High-Energy Physics: State of the Art and Challenges

Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage—namely, a significant (in some cases exponential) speedup o...

Noise-augmented chaotic Ising machines for combinatorial optimization and sampling

Abstract Ising machines are hardware accelerators for combinatorial optimization and probabilistic sampling, using stochasticity to explore spin configurations and avoid local minima. We refine the previously proposed coupled chaotic bits (...