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Studies in computational intelligence

Quantum Computing: A Shift from Bits to Qubits

Rajiv Pandey, Nidhi Srivastava, Neeraj Kumar Singh, Kanishka Tyagi

Published Jan 1, 2023• 14 citations
Publisher
DOI
10.1007/978-981-19-9530-9

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A method of determining a pattern in a sequence of bits using a quantum computing system includes setting a first register of a quantum processor in a superposition of a plurality of string index states, encoding a bit string in a second register of the quantum processor, encoding a bit pattern in a third register of the quantum processor, circularly shifting qubits of the second register conditioned on the first register, amplifying an amplitude of a state combined with the first register in which the circularly shifted qubits of the second register matches qubits of the third register, measuring an amplitude of the first register and determining a string index state of the plurality of string index states associated with the amplified state, and outputting, by use of a classical computer, a string index associated with the first register in the measured state.
This book chapter explores the transition from classical to quantum computing, emphasizing the capabilities and challenges associated with quantum bits (qubits). Unlike classical computing, where the information is represented as binary digits, known as bits, quantum bits, or qubits, although they share similarities with classical bits, such as 0 and 1 states, they operate in superposition, simultaneously encompassing both 0 and 1 states. This unique property allows quantum computers to perform certain computations, traditionally done sequentially on classical computers, more efficiently, in a single operation with a qubit. Through comparative analysis, we investigate the feasibility and costs of integrating quantum computing into daily applications, examining the potential for personal quantum computing devices. Our findings highlight significant advancements in computational speed of routine mathematical operations, although not yet economically viable or competitive in the current market. Future directions question the market readiness for quantum computing, suggesting a pivotal shift towards cloud-based quantum computing resources.
Malnutrition is a concern in the current situation. This occurs due to issues in food security, which should be concentrated on to eradicate poverty. Though many techniques are evolving deep learning and machine learning that help the agriculture process to get a better yield, quantum computing is a trial run to test its achievability in increasing crop production. It is believed that quantum computing will help to resolve world hunger. The whirling qubits will help solve the problems in the crop production world. Can quantum computing end the difficulties faced in crop yield? if so, how? The other reason for writing this article is the urgency to implement quantum computing in agriculture. Quantum computing is the data processing of the future. In the world of agriculture, artificial intelligence with image processing is quite important. With colossal speedups and growth in the power savings of quantum computers and as the other research field is moving and focusing on the implementation of quantum computing, the idea of shifting quantum technique toward agriculture emerged. The qubit representation of bits in quantum computers as "0" and "1" simultaneously makes it different from classical computers where the bits are represented either as "0" or "1.” The conversion of qubits to bits will be applied through the qubit conversion method, to have more valid bit spacing for real-time evaluation and storing purposes.