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Interdisciplinary theory behind quantum computing From Wikipedia, the free encyclopedia
Quantum Information Science is a field that combines the principles of quantum mechanics with information theory to study the processing, analysis, and transmission of information. It covers both theoretical and experimental aspects of quantum physics, including the limits of what can be achieved with quantum information. The term quantum information theory is sometimes used, but it does not include experimental research and can be confused with a subfield of quantum information science that deals with the processing of quantum information.
Quantum teleportation, entanglement and the manufacturing of quantum computers depend on a comprehensive understanding of quantum physics and engineering. Google and IBM have invested significantly in quantum computer hardware research, leading to significant progress in manufacturing quantum computers since the 2010s. Currently, it is possible to create a quantum computer with over 100 qubits, but the error rate is high due to the lack of suitable materials for quantum computer manufacturing.[1] Majorana fermions may be a crucial missing material.[2]
Quantum cryptography devices are now available for commercial use. The one time pad, a cipher used by spies during the Cold War, uses a sequence of random keys for encryption. These keys can be securely exchanged using quantum entangled particle pairs, as the principles of the no-cloning theorem and wave function collapse ensure the secure exchange of the random keys. The development of devices that can transmit quantum entangled particles is a significant scientific and engineering goal.[citation needed]
Qiskit, Cirq and Q Sharp are popular quantum programming languages. Additional programming languages for quantum computers are needed, as well as a larger community of competent quantum programmers. To this end, additional learning resources are needed, since there are many fundamental differences in quantum programming which limits the number of skills that can be carried over from traditional programming.[citation needed]
Quantum algorithm and quantum complexity theory are two of the subjects in algorithms and computational complexity theory. In 1994, mathematician Peter Shor introduced a quantum algorithm for prime factorization that, with a quantum computer containing 4,000 logical qubits, could potentially break widely used ciphers like RSA and ECC, posing a major security threat. This led to increased investment in quantum computing research and the development of post-quantum cryptography to prepare for the fault-tolerant quantum computing (FTQC) era.[3]
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