"A quantum computer is a computer that exploits quantum mechanical phenomena."
Overview of the principles and potential applications of quantum computing, including qubits and quantum algorithms.
Quantum States: The fundamental building blocks of quantum computing, quantum states represent the probability distribution of finding a particle in a certain state.
Quantum Gates: The basic operations of a quantum computer that manipulate quantum states.
Quantum Circuits: The combination of quantum gates that perform specific operations on quantum states.
Quantum Algorithms: The set of instructions used to manipulate quantum gates and states to perform a computational task.
Quantum Error Correction: Techniques used to mitigate the effects of noise and errors that arise due to the fundamental properties of quantum systems.
Quantum Cryptography: The use of quantum phenomena to create secure communication channels that can't be intercepted or decoded.
Quantum Entanglement: The phenomenon where two or more quantum systems become correlated in a way that violates classical physics.
Quantum Computing Architecture: The design of quantum computers, including the physical implementation of quantum gates and circuits.
Quantum Complexity Theory: The study of the computational complexity of quantum algorithms and the limitations of quantum computing.
Quantum Metrology: The use of quantum systems to increase the precision of measurement in various fields, such as astronomy and engineering.
Quantum Information Theory: The study of how quantum systems can process and store information, including concepts such as quantum entanglement and quantum teleportation.
Quantum Field Theory: The quantum mechanics of fields, which provides the theoretical framework for particle physics and quantum electrodynamics.
Quantum Cosmology: The application of quantum mechanics to the study of cosmology, with a focus on the early universe and the origins of space and time.
Quantum Gravity: The goal of developing a quantum theory of gravity, which would unify quantum mechanics and general relativity, the two most successful theories in physics.
Digital quantum computing: It is the most widely known type of quantum computing, which uses qubits (quantum bits) to represent information and follows the principles of digital computing, where the state of each qubit is encoded as 0 or 1. Digital quantum computing can perform complex computations faster than classical computing.
Analog quantum computing: It uses continuous variables such as the amplitude or phase of a wave to represent information rather than qubits. This type of quantum computing is promising for solving optimization problems.
Topological quantum computing: It is a type of quantum computing that relies on manipulating the topological properties of materials that host qubits. The concept behind topological quantum computing is to make qubits less sensitive to external noise, making them more stable compared to other types of qubits.
Adiabatic quantum computing: It aims to solve optimization problems by slowly changing the Hamiltonian of the system from the initial state to the final state. This approach ensures that the system remains in its fundamental state, and the computation is error-free.
Quantum annealing: It is a type of adiabatic quantum computing, which involves finding the global minimum of an energy function. Scientists are exploring many applications of quantum annealing, including optimization problems and the simulation of physical systems.
One-way quantum computing: In this type of quantum computing, entangled qubits are prepared in a particular way, and measurement is made to obtain the desired output state. The approach was invented in 2001 by a team of researchers at Caltech.
Photonic quantum computing: It uses photons to represent qubits, and quantum gates are realized by manipulating the polarization and phase of photons. Photonic quantum computing is considered a leading approach for quantum information processing.
Ion trap quantum computing: In this type of quantum computing, charged atoms or ions are used as qubits. The entanglement of the qubits is created through electromagnetic fields. Due to their long coherence times, Ion trap qubits are considered a promising platform for quantum computing.
Superconducting quantum computing: This type of quantum computing uses superconducting qubits, and it is considered a leading approach for creating a large-scale quantum computer. Superconducting qubits can operate at very low temperatures: Near absolute zero - and they can be manufactured using standard semiconductor technology.
Quantum simulations: Quantum simulation is a concept that is being used by quantum computers to simulate complex physical and chemical systems that are challenging to simulate on classical computers. This is achieved by representing the behavior of the system using qubits and quantum algorithms.
"At small scales, physical matter exhibits properties of both particles and waves, and quantum computing leverages this behavior, specifically quantum superposition and entanglement."
"Classical physics cannot explain the operation of these quantum devices, and a scalable quantum computer could perform some calculations exponentially faster than any modern 'classical' computer."
"A large-scale quantum computer could break widely used encryption schemes and aid physicists in performing physical simulations."
"The current state of the art is largely experimental and impractical, with several obstacles to useful applications."
"For many important tasks, quantum speedups are proven impossible."
"The basic unit of information in quantum computing is the qubit, similar to the bit in traditional digital electronics."
"A qubit can exist in a superposition of its two 'basis' states, which loosely means that it is in both states simultaneously. When measuring a qubit, the result is a probabilistic output of a classical bit."
"The design of quantum algorithms involves creating procedures that allow a quantum computer to perform calculations efficiently and quickly."
"If a physical qubit is not sufficiently isolated from its environment, it suffers from quantum decoherence, introducing noise into calculations."
"Two of the most promising technologies are superconductors and ion traps."
"In principle, a non-quantum (classical) computer can solve the same computational problems as a quantum computer, given enough time."
"Quantum advantage comes in the form of time complexity rather than computability, and quantum complexity theory shows that some quantum algorithms for carefully selected tasks require exponentially fewer computational steps than the best known non-quantum algorithms."
"Quantum speedup is not universal or even typical across computational tasks, since basic tasks such as sorting are proven to not allow any asymptotic quantum speedup."
"Claims of quantum supremacy have drawn significant attention to the discipline but are demonstrated on contrived tasks, while near-term practical use cases remain limited."
"Optimism about quantum computing is fueled by a broad range of new theoretical hardware possibilities facilitated by quantum physics."
"The improving understanding of quantum computing limitations counterbalances this optimism."
"The impact of noise and the use of quantum error-correction can undermine low-polynomial speedups."
"The current state of the art is largely experimental and impractical, with several obstacles to useful applications."
"Quantum speedups have been traditionally estimated for noiseless quantum computers, whereas the impact of noise and the use of quantum error-correction can undermine low-polynomial speedups."