A quantum computer is based on phenomena such as superposition and entanglement and uses such phenomena to perform operations on data. While binary digital electronic computers are based on transistors, quantum-mechanical phenomena form the basis of quantum computers.

Theoretically, large-scale quantum computers would be far more efficient and faster at solving certain problems than any classical computers. For example, Shor’s algorithm, a quantum algorithm for integer factorization running on a quantum computer would beat hands down the corresponding problem running on a classical computer. Another example where quantum computers would reign supreme is the simulation of quantum many-body systems. Quantum algorithms, such as Simon’s algorithm, run much faster compared to any possible probabilistic classical algorithm. It’s important to note that, in principle, a classical computer could simulate a quantum algorithm. This is because quantum computation does not violate the Church–Turing thesis. To perform this, however, a classical computer would require an inordinate amount of resources. Quantum computers, on the contrary, might efficiently solve problems that are too complex to be practically solved by classical computers.

A quantum computer uses quantum states to represent bits simultaneously to achieve an exponential increase in speed and power. Enormous, complex problems usually requiring massive amount of resources and time can be solved in a reasonable amount of time. This is highly beneficial for IoT data that requires a lot of computation power and other complex optimization functions. In drug discovery, for example, trillions of combinations of amino acids are examined to find a single elusive protein.

On the quantum level, you’re able to program the atoms to represent all possible input combinations simultaneously. That means when you run an algorithm, all possible input combinations are tested at once. With a regular computer, you’d have to serially cycle through every possible input combination to arrive at your solution. Interestingly, solving the most complex problems this way would take longer than the age of the universe.

For certain types of problems, quantum computers can provide an exponential speed boost. Quantum database search is the most well-known example of this.

Besides factorization and discrete logarithms, quantum algorithms offer more than polynomial speedup over the best-known classical algorithms. Simulation of quantum physical processes in solid state physics as well as chemistry, approximation of Jones polynomials, and solving Pell’s equation are some well-known examples.

A composite system is always expressible as a sum or superposition of products of states of local constituents.

#### Binary Bits vs. Quantum Qubits

With quantum computers, information is not held in individual units but rather in the system as a whole. The system can exist in two states at the same time. This is courtesy of the superposition principle of quantum mechanics. This “qubit” can store a “0” and “1” simultaneously. If you build a system comprising two qubits, it can hold four values at once — 00, 01, 10, and 11.

Quantum computers differ from digital computers, which use binary system and are based on transistors. Digital computing requires data encoded into bits, where a bit can be only in one exclusive state (0 or 1). Quantum computation, on the other hand, uses quantum bits (qubits), which need not be in an exclusive state; rather, the qubits can be in superpositions of states. A quantum Turing machine is a theoretical model of such a computer, also known as the universal quantum computer. The major groundwork in the field of quantum computing was done by Paul Benioff and Yuri Manin in 1980, Richard Feynman in 1982, and David Deutsch in 1985. In 1968, a quantum computer with spins as qubits was also formulated for use as a quantum space–time.

A classical computer has bits for memory, where each bit represents either a 0 or 1. A quantum computer, instead, has a sequence of qubits. A single qubit can represent 0, 1, or any quantum superposition of those two qubit states. Similarly, a pair of qubits can be in any quantum superposition of four states, and three qubits in any superposition of eight states. Generalizing, a quantum computer with n qubits can be in an arbitrary superposition of up to 2^{n} different states simultaneously. A classical computer, in contrast, can exclusively be in just one of these 2^{n} states at a time.

#### Implementing Qubits

A quantum computer operates on qubits. The qubits are set in a perfect drift, representing the specific problem at hand. Subsequently, a precise sequence of quantum logic gates is used to manipulate these qubits. The quantum algorithm is the sequence of gates to be applied to solve the problem. When a measurement is done, the qubit system collapses into a classical state, where each qubit is 0 or 1. Thus, the outcome can at most be n classical bits of information. An important aspect of quantum algorithms is their probabilistic nature. They associate a certain known probability with a correct solution.

A particle having spin states “up” and “down” (usually written | ↓ ⟩ and | ↑ ⟩ , or | 0 ⟩ and | 1 ⟩) can be considered an example of an implementation of qubits in a quantum computer. But in fact, any system possessing an observable quantity A, which is conserved under time evolution such that A has at least two discrete and sufficiently spaced consecutive eigenvalues, is a suitable candidate for implementing a qubit. This is true because any such system can be mapped onto an effective spin-1/2 system.

Qubits are not just the particles themselves. In addition to the controlled particles, qubits also have the means of control, such as the devices that trap particles and switch them between different states.

#### Research on Quantum Computers

As of 2017, the development of actual quantum computers is rapidly gaining pace. Advances are being made in both practical and theoretical research. National governments and military agencies are taking deep interest and funding in quantum computing research. Once developed, quantum computers can be employed in a variety of fields such as civilian, business, trade, environmental and national security purposes.

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