To crack the most popular cryptocurrency, you need a quantum computer with a capacity of 13 to 317 million qubits
If you try to consider the essence of bitcoin in the most understandable way, then this crypto money can be described precisely as a variant of mathematical calculations.
In essence, a cryptocurrency is an algorithm that is continuously calculated. More precisely, calculations in the bitcoin variant are performed up to a given limit, and after that, users will only be able to exchange this cryptocurrency, but will not be able to create it. One way or another, we are talking about the fact that bitcoin is a kind of calculation. Accordingly, it is quite possible to assume that, given sufficient computer power, this calculation can be faked in some way.
Of course, the very algorithms that are used in the blockchain require that the data be distributed on all users’ computers, which makes counterfeiting an incredibly difficult option. However, modern scientists say that it is still possible to counterfeit cryptocurrencies using super-powerful quantum computers.
From the point of view of financial feasibility, this does not look particularly profitable, but the ability to fake bitcoins at all casts doubt on the stability of the crypto money system.
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WHAT ARE QUANTUM BIT COMPUTERS?
Quantum computing is a type of computation that harnesses the collective properties of quantum states, such as superposition, interference, and entanglement, to perform calculations. The devices that perform quantum computations are known as quantum computers.: I-5 Though current quantum computers are too small to outperform usual (classical) computers for practical applications, they are believed to be capable of solving certain computational problems, such as integer factorization (which underlies RSA encryption), substantially faster than classical computers. The study of quantum computing is a subfield of quantum information science.
Quantum computing began in 1980 when physicist Paul Benioff proposed a quantum mechanical model of the Turing machine. Richard Feynman and Yuri Manin later suggested that a quantum computer had the potential to simulate things a classical computer could not feasibly do. In 1994, Peter Shor developed a quantum algorithm for factoring integers with the potential to decrypt RSA-encrypted communications. In 1998 Isaac Chuang, Neil Gershenfeld and Mark Kubinec created the first two-qubit quantum computer that could perform computations. Despite ongoing experimental progress since the late 1990s, most researchers believe that “fault-tolerant quantum computing [is] still a rather distant dream.”
In recent years, investment in quantum computing research has increased in the public and private sectors. On 23 October 2019, Google AI, in partnership with the U.S. National Aeronautics and Space Administration (NASA), claimed to have performed a quantum computation that was infeasible on any classical computer, but whether this claim was or is still valid is a topic of active research.
There are several types of quantum computers (also known as quantum computing systems), including the quantum circuit model, quantum Turing machine, adiabatic quantum computer, one-way quantum computer, and various quantum cellular automata. The most widely used model is the quantum circuit, based on the quantum bit, or “qubit”, which is somewhat analogous to the bit in classical computation. A qubit can be in a 1 or 0 quantum state, or in a superposition of the 1 and 0 states. When it is measured, however, it is always 0 or 1; the probability of either outcome depends on the qubit’s quantum state immediately prior to measurement.
Efforts towards building a physical quantum computer focus on technologies such as transmons, ion traps and topological quantum computers, which aim to create high-quality qubits.: 2–13 These qubits may be designed differently, depending on the full quantum computer’s computing model, whether quantum logic gates, quantum annealing, or adiabatic quantum computation. There are currently a number of significant obstacles to constructing useful quantum computers. It is particularly difficult to maintain qubits’ quantum states, as they suffer from quantum decoherence and state fidelity. Quantum computers therefore require error correction.
Any computational problem that can be solved by a classical computer can also be solved by a quantum computer. Conversely, any problem that can be solved by a quantum computer can also be solved by a classical computer, at least in principle given enough time.
In other words, quantum computers obey the Church–Turing thesis. This means that while quantum computers provide no additional advantages over classical computers in terms of computability, quantum algorithms for certain problems have significantly lower time complexities than corresponding known classical algorithms. Notably, quantum computers are believed to be able to quickly solve certain problems that no classical computer could solve in any feasible amount of time—a feat known as “quantum supremacy.” The study of the computational complexity of problems with respect to quantum computers is known as quantum complexity theory.