| qubit | |
|---|---|
| Name | Qubit |
| Caption | Bloch sphere representation of a qubit state |
| Type | Quantum information carrier |
| Invented | 1980s–1990s |
| Inventor | Paul Benioff; concept expanded by Richard Feynman and David Deutsch |
| Uses | Quantum computing, Quantum communication, Quantum cryptography |
qubit
A qubit is the fundamental unit of quantum information, analogous to the bit in Information theory but described by a two-level quantum mechanical system. Qubits exploit superposition and quantum entanglement to enable quantum computation and communication protocols that can outperform classical counterparts for certain tasks. Qubits underpin research in Quantum Physics fields including quantum information theory, quantum error correction, and experimental platforms such as superconducting qubits and trapped ions.
A qubit is any two-level quantum system whose state is a normalized vector in a two-dimensional complex Hilbert space, typically spanned by orthonormal basis states often denoted |0⟩ and |1⟩. Physically realizable qubits include the spin-1/2 of an electron (electron spin), the polarization states of a photon (photon polarization), energy levels of an atom (atomic physics), or discrete charge or flux states in superconducting circuits (Josephson junctions). The global phase of a qubit is physically irrelevant, so pure states are represented on the Bloch sphere as points parameterized by two real angles. Qubits are central to implementations of quantum teleportation, quantum key distribution (e.g., BB84 protocol), and tests of foundations such as violations of Bell's theorem in experiments by groups including those at IBM, Google Quantum AI, and academic labs at MIT, University of Oxford, and University of Innsbruck.
Mathematically a qubit state is expressed as α|0⟩ + β|1⟩ with complex amplitudes α and β satisfying |α|^2 + |β|^2 = 1. The state space is the projective Hilbert space CP^1; mixed states are represented by 2×2 density matrices ρ acting on the Hilbert space with ρ ≥ 0 and Tr(ρ)=1. Evolution of closed qubits follows unitary operators U ∈ U(2) generated by Hamiltonians via the Schrödinger equation; open-system dynamics are modeled by quantum channels and the Lindblad equation. Composite systems use the tensor product to form multi-qubit Hilbert spaces; correlations include classical and quantum correlations quantified by measures such as von Neumann entropy and concurrence. Mathematical frameworks relevant to qubits include linear algebra, operator theory, and quantum tomography techniques developed in works by researchers like John Preskill and Michael A. Nielsen & Isaac L. Chuang.
Experimental qubit realizations span multiple platforms. Superconducting qubits (e.g., transmon) implemented with Josephson junction circuits are pursued by IBM, Google, and Rigetti Computing. Trapped-ion qubits using Caesium or Ytterbium ions are developed by groups at University of Oxford, Honeywell Quantum Solutions (now Quantinuum), and University of Innsbruck. Semiconductor spin qubits in silicon and gallium arsenide quantum dots are advanced by Intel and academic groups. Photonic qubits use integrated optics and parametric down-conversion in experiments at University of Bristol and Photonics companies. Other platforms include neutral atom arrays (e.g., Cold atom tweezers by Pasqal), nitrogen-vacancy center qubits in diamond, and topological qubits proposed from Majorana fermion systems pursued by projects like Microsoft Quantum. Each technology balances coherence time, gate fidelity, scalability, and integration with cryogenic or room-temperature hardware.
Single-qubit operations are rotations on the Bloch sphere implemented by Hamiltonian control or resonant pulses; canonical gates include the Pauli operators X, Y, Z, the Hadamard gate H, and phase gates S and T. Two-qubit entangling gates such as CNOT gate, CZ gate, and the iSWAP are universal when combined with single-qubit gates. Control methodologies use quantum optimal control techniques, microwave pulses for superconducting qubits, laser-induced stimulated Raman transitions for trapped ions, and electrostatic gating for spin qubits. Fault-tolerant operation requires gate fidelities above error-correction thresholds determined by codes like the surface code and concatenated Calderbank–Shor–Steane (CSS) codes.
Entanglement between qubits is a resource for quantum protocols and is quantified by measures such as entanglement entropy and negativity. Decoherence arises from environmental coupling via dephasing (loss of phase coherence) and relaxation (energy decay, characterized by T2 and T1 times). Common noise sources include charge noise, flux noise, photon scattering, and spin-bath interactions; mitigation strategies include dynamical decoupling, material engineering, error-correcting codes, and cryogenic shielding. Landmark experimental demonstrations of multipartite entanglement and Bell inequality violations are reported by groups at Caltech, Harvard University, and national laboratories like NIST.
Qubits form the substrate for quantum algorithms such as Shor's algorithm for integer factorization, Grover's algorithm for unstructured search, and variational algorithms like the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA). Computational models include the circuit model, measurement-based quantum computation (cluster states), adiabatic quantum computing related to quantum annealing (e.g., D-Wave Systems), and topological quantum computation. Complexity classes such as BQP characterize decision problems efficiently solvable by quantum circuits acting on qubits, with implications for cryptography and computational complexity theory studied by researchers like Scott Aaronson.
Measurement of qubits projects states onto computational or other bases; projective (von Neumann) measurement and generalized positive operator-valued measures (POVMs) are standard. Readout techniques include dispersive readout in superconducting circuits, state-dependent fluorescence in trapped ions, charge sensing for spin qubits using quantum point contacts or single-electron transistors, and photon detectors for photonic qubits. Quantum state tomography reconstructs density matrices from measurement statistics, while randomized benchmarking and gate set tomography assess gate fidelities. Advances in high-fidelity, quantum nondemolition readout are critical for implementing quantum error correction and scalable quantum processors.