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Protein–protein interaction (PPI) networks serve as invaluable repositories, shedding light on the intricate web of protein interactions within living organisms. Traditional methods for identifying essential proteins fail to capture the complex ...

Quantum computers have been called the Ultimate Computer a decisive leap in technology with profound implications for the entire world. Quantum computers might usher in an entirely new age for the economy, society, and our way of life. It is an ...

Quantum algorithms are often represented in terms of quantum circuits operating on ideal (logical) qubits. However, the practical implementation of these algorithms poses significant challenges. Many quantum algorithms require a substantial ...

• Quantum error correction adds significant qubit and runtime overhead.
• Our proposed framework compares classical and quantum algorithms effectively.
• The article focuses on quantum algorithms’ impact on cryptographic systems.
• ...

Quantum Computing (QC) offers significant potential to enhance scientific discovery in fields such as quantum chemistry, optimization, and artificial intelligence. Yet QC faces challenges due to the noisy intermediate-scale quantum era’s inherent ...

• Introduces a hardware-agnostic QC/HPC framework.
• Enhances HPC with QC for complex workflows.
• Integrates user interfaces for QC–HPC collaboration.
• Software tools for QC–HPC integration.

Quantum and quantum-inspired algorithms have not yet been systematically classified in the context of potential Operations Research (OR) applications. Our systematic mapping is designed for quick consultation and shows which algorithms have been ...

This article delves into the evolving landscape of pattern recognition, transitioning from classical methodologies to quantum-based techniques. It underscores how quantum algorithms offer a new paradigm with the potential to overcome the ...

• Comprehensive review of quantum computing to outline the current state of the art.
• Comprehensive review of recent advancements in quantum pattern recognition.
• Exploration of how quantum datasets can enhance the capabilities of ...

Quantum computing shows promise for solving problems that are intractable on classical computers. Devices that are available in the near-term will be noisy and limited in size. These type of devices have been termed: noisy intermediate-scale ...

• Evaluation of the impact trapped-ion architecture has on the performance of quantum algorithms.
• Quantitative methodology for evaluating quantum computing architectures based on algorithm benchmarking.
• Circuit implementations of ...

The essential protein identification on the protein–protein interaction (PPI) network can have crucial applications in cancer disease diagnosis and drug target cell identification. The study uses a graph-based approach to identify essential ...

Quantum computing (QC) has been viewed as a groundbreaking development in the modern technological landscape. The field of QC technology has made significant strides in various applications in recent years, making it one of the most researched ...

Despite fundamental interests in learning quantum circuits, the existence of a computationally efficient algorithm for learning shallow quantum circuits remains an open question. Because shallow quantum circuits can generate distributions that are ...

The semidirect discrete logarithm problem (SDLP) is the following analogue of the standard discrete logarithm problem in the semidirect product semigroup $G⋊\text{End}(G)$ for a finite semigroup G. Given $g\in G,\sigma \in \text{End}(G)$, and $h={\prod }_{i=0}^{t-1}{\sigma }^i(g)$ for some integer t, ...$$$$$$

Clustering is a well-established unsupervised machine-learning approach to classify data automatically. In large datasets, the classical version of such algorithms performs well only if significant computing resources are available (e.g., GPU). An ...

As bigger quantum processors with hundreds of qubits become increasingly available, the potential for quantum computing to solve problems intractable for classical computers is becoming more tangible. Designing efficient quantum algorithms and ...

The method of solving a polynomial system of equations plays a crucial role in various domains of cryptography. For instance, multivariate cryptography using public keys relies on the computational difficulty of solving a multivariate polynomial ...$\sqrt{}$$$

• Quantum computing is introduced, and differences with conventional computing are discussed.
• Other applications of Quantum technologies are included, with emphasis on AI and IoT.
• The expected applications and impact of Quantum ...

Agriculture has undergone progressive transformations using ever-evolving technologies to increase productivity and profitability. A new approach to agricultural management based on concepts from the fourth industrial revolution is being ...

Aaronson defined Forrelation (2010) as a measure of correlation between a Boolean function f and the Walsh–Hadamard transform  of another function $g$. In a recent work, we have studied different cryptographically important spectra of Boolean ...

Lattice reduction algorithms such as BKZ (Block-Korkine-Zolotarev) play a central role in estimating the security of lattice-based cryptography. The subroutine in BKZ which finds the shortest vector in a projected sublattice can be instantiated ...

Reference-guided DNA sequencing and alignment is an important process in computational molecular biology. The amount of DNA data grows very fast, and many new genomes are waiting to be sequenced while millions of private genomes need to be re-...

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• Quantum computers are expected to be involved in DNA sequencing acting as quantum accelerators.
• Novel quantum algorithm for reference-guided DNA sequence alignment modeled with gate-based quantum computing.
• The quantum algorithm ...

Lexicographically minimal string rotation (LMSR) is a problem to find the minimal one among all rotations of a string in the lexicographical order, which is widely used in equality checking of graphs, polygons, automata and chemical structures. In ...${}^{\mathrm{}\mathrm{}}$$\sqrt{}$$\mathrm{}\left(\sqrt{}\right)$

One of the challenges facing current noisy-intermediate-scale-quantum devices is achieving efficient quantum circuit measurement or readout. The process of extracting classical data from the quantum domain, termed in this work as quantum-to-...$\mathrm{}$