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Quantum Computing: History, Uses, and Advantages

Quantum computing is an emerging field of study that has the potential to revolutionize the way we solve complex problems. By harnessing the principles of quantum mechanics, quantum computers operate on qubits (quantum bits) instead of classical bits, enabling them to perform calculations at speeds unimaginable with traditional computing systems. In this blog, we will…

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Understanding Qubits and Quantum Gates

Quantum computing is fundamentally different from classical computing due to its use of qubits and quantum gates. These two elements are essential to the power and potential of quantum computers, enabling them to solve problems that are practically impossible for classical computers to address. In this article, we will dive deeper into the concepts of…

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Quantum Mechanics, Physics, and Computers

Quantum mechanics, once a theoretical and mysterious branch of physics, has grown to become a revolutionary concept influencing the future of computers and technology. This rapidly advancing field of study holds the potential to solve problems that classical computers struggle with, such as optimizing complex systems, simulating molecular behavior, and even enhancing artificial intelligence. In…

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What is a transformer model?

A transformer model is a type of deep learning model that was introduced in 2017. These models have quickly become fundamental in natural language processing (NLP), and have been applied to a wide range of tasks in machine learning and artificial intelligence. The model was first described in a 2017 paper called “Attention is All You Need” by Ashish…

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Quantum Phase Estimation (QPE)

A Cornerstone of Quantum Computing Quantum Phase Estimation (QPE) stands as a fundamental algorithm in the realm of quantum computing, renowned for its efficiency in estimating the phase (eigenvalue) of a unitary operator. This capability is crucial for unveiling properties of quantum systems that remain inaccessible to classical computational approaches. The Emergence of QPE in…

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Assessing performance of a variational algorithm in presence of noise and quantum error mitigation

Variational algorithms are considered among the leading candidates for finding some of the first useful applications of quantum computing. However, noise in quantum hardware limits the number of operations we can run in a quantum circuit before errors accumulate and invalidate the result.Quantum error correction techniques will eventually resolve these errors in fault-tolerant quantum computers….

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