Glossary

AI for Quantum uses artificial intelligence and machine learning techniques to optimize quantum systems and operations, helping to improve quantum hardware performance, reduce errors, and automate quantum control processes.

Applied quantum computing involves using quantum computing technology to solve real-world problems across various industries. Promising applications include material sciences, drug discovery, financial modeling, AI, and cybersecurity.

An approach to realizing qubits based on defects in solid materials. The crystal defects (e.g. atomic replacement) have a unique electronic structure and can be used to realize “artificial atoms” in a solid. A common example is the “NV” or nitrogen vacancy center.

The quantum mechanical property by which two or more quantum systems can become linked such that they can only be described as a single composite system rather than multiple separable systems. Various experiments have demonstrated evidence that entanglement exists in real systems, countering claims of alternate theories to quantum physics such as “hidden variables” theories. Entanglement is a resource used to interact and process quantum information in quantum computers.

Error mitigation strategies are a class of NISQ-era postprocessing techniques designed to improve quantum algorithm performance with imperfect hardware. They broadly involve executing many slightly different versions of a target algorithm and then combining the results to somehow “extract the right answer through the errors”. The modifications applied to the circuit may be random or applied according to a fixed algorithm. The resulting outputs are then combined and postprocessed in order to provide improvement.  Such techniques incur exponentially large overhead in time and executions, limiting their relevance to certain problem classes

Error suppression (AKA deterministic error suppression or dynamic error suppression) comprises a set of techniques which reduce the likelihood of hardware error while quantum bits are being manipulated or used for memory storage. It uses the physics and techniques of the field of quantum control in order to build resilience against error into the operation of quantum hardware.

Grover's Algorithm is a quantum search algorithm that accelerates database searching, providing quadratic speedup over classical algorithms and impacting optimization and cryptography.

Magnetic map matching is a navigation technique that compares real-time magnetic field measurements against pre-recorded magnetic field maps to determine precise location, similar to how GPS compares satellite signals. This technology uses Earth's unique magnetic signatures in different locations as a natural positioning system, particularly valuable when traditional GPS signals are unavailable or unreliable.

NISQ stands for Noisy Intermediate-Scale Quantum. It refers to the current generation of quantum computers that have a moderate number of qubits but are susceptible to noise and errors. NISQ devices are essential for developing and testing quantum algorithms despite not yet being capable of full error correction.

See Color Centers.

An approach to realizing qubits using atoms as natural quantum coherent devices. The atoms are uncharged and held in arrays using laser light (AKA optical tweezers). Information can be encoded in the valence electron state of each atom.

QAOA stands for Quantum Approximate Optimization Algorithm. It is a quantum algorithm designed to solve combinatorial optimization problems by approximating the optimal solution. QAOA is particularly significant in the NISQ era as it can be run on near-term quantum computers and has applications in fields like machine learning and logistics.

An approach to improve the efficiency of machine learning or AI routines through the incorporation of quantum computing in model training of execution. Quantum AI is hoped to have immediate applications in optimization and machine learning, where quantum algorithms could accelerate tasks like training neural networks. This remains an open area of exploratory research, with provable benefits so far being limited to circumstances where data inputs are quantum coherent (an atypical situation).

A quantum accelerometer measures motion and acceleration using quantum effects like atom interferometry, achieving far greater precision than classical sensors by tracking the wave-like behavior of ultra-cold atoms. These devices provide exceptionally accurate measurements of movement and position without relying on external signals, making them valuable for navigation in GPS-denied environments.

Quantum algorithms are specialized sequences of quantum operations designed to solve specific problems by exploiting quantum mechanical properties like superposition and entanglement. These algorithms are designed to solve certain tasks exponentially faster than classical computers, particularly in areas like cryptography, searching large datasets, and simulating quantum systems.

Quantum computing is a field of technology that utilizes quantum mechanics to perform complex computations more efficiently than classical computers. Applications with mathematically provable advantages relate to factoring large numbers (see Shor’s algorithm).

Quantum computing is a field of technology that utilizes quantum mechanics to perform complex computations more efficiently than classical computers, especially for tasks like factoring large numbers.

Quantum development refers to the process of creating and optimizing software, algorithms, and control systems for quantum computers and quantum sensing devices. This includes building quantum circuits, error correction protocols, and applications that can harness quantum mechanical effects like superposition and entanglement to solve complex problems beyond classical computing capabilities.

Quantum error correction is a technique that protects quantum information from decoherence and computational errors by encoding quantum bits (qubits) across multiple physical qubits to create more stable logical qubits. This technology is foundational to quantum computer science but is currently not practical due to the extreme resource requirements in order to perform encoding and logical operations.

The lowest level of the quantum computing stack, focused on automation, error reduction, and characterization of quantum hardware. It is considered firmware in that it is generally invisible to the end user, but instrumental to hardware operation.

A Quantum gravimeter uses quantum systems to detect tiny variations in Earth's gravitational field, achieving unprecedented precision by exploiting the wave-like behavior of matter.

Quantum inertial navigation leverages quantum sensors to detect and measure motion with extreme precision by tracking changes in acceleration, rotation, and gravity using quantum mechanical properties. This technology enables highly accurate positioning and navigation independent of external signals like GPS, making it crucial for autonomous systems operating in challenging or denied environments.

Software technology designed to connect low-level hardware with high-level programming frameworks and applications. Quantum infrastructure software is responsible for improving the performance and utility of quantum hardware through abstraction, in analogy with virtualization in classical processors. Related tasks include hardware optimization, compilation, and quantum error correction.

See Quantum AI.

A quantum magnetometer uses quantum sensors to detect minute magnetic field variations with extreme precision by measuring the behavior of quantum systems like atomic spins. These devices achieve far greater sensitivity and stability than conventional magnetic sensors, enabling applications in navigation, medical imaging, and detection of subsurface structures.

Quantum mechanics is a fundamental theory in physics that describes behavior at the atomic and subatomic scale. It explains how energy and matter interact at the smallest levels, where particles can exist in multiple states simultaneously (superposition), influence each other instantly across distances (entanglement), and demonstrate both wave-like and particle-like properties.

Quantum Optimization involves leveraging quantum algorithms and quantum computers to solve complex optimization problems more efficiently than classical methods. It has significant applications in fields like logistics, finance, and machine learning, where finding optimal solutions is crucial.

Quantum Positioning Systems (QPS) use quantum sensors to provide precise navigation and positioning without relying on GPS or satellite signals. These systems utilize quantum sensing techniques, including quantum gravimetry and quantum accelerometry, to measure motion and position with extreme accuracy by detecting subtle variations in gravity and acceleration, making them particularly valuable for defense applications and navigation in GPS-denied environments.

Quantum Search refers to quantum algorithms that search through unsorted data faster than classical algorithms. Grover's Algorithm is a prime example, providing quadratic speedup and impacting fields like cryptography and optimization.

Quantum sensing is a revolutionary technology that uses quantum properties to create ultra-precise sensors for defense, scientific, and industrial applications. By harnessing quantum mechanical principles, these sensors can detect minuscule signals with unprecedented sensitivity, offering breakthrough capabilities in navigation, imaging, and threat detection.

The fundamental carrier of quantum information -- in analogy to the bit in classical computing -- whose physics translates directly from quantum-mechanical treatment of the “spin-½” problem.

RSA Encryption is a widely used encryption method based on the difficulty of factoring large numbers. Quantum factoring threatens its security by making factoring more feasible.

Shor's Algorithm is a quantum algorithm capable of factoring large integers exponentially faster than classical algorithms, posing significant implications for cryptography.

A type of qubit technology leveraging the spin degree of freedom of electrons trapped in a solid material. These devices are mooted to deliver scaling advantages through their leveraging of conventional semiconductor manufacturing.

A type of qubit where the two-level system is realized in the quantum mechanical properties of electrical currents in special superconducting materials. At low temperatures the electrons in these metals behave like composite quantum objects and enable various ways to generate a qubit. The flexibility of integrated circuit fabrication aids scaling and mass production.

The property by which waves can add coherently (i.e. preserving the phase or translation of the wave), as applied to the wave-like nature of matter in quantum mechanics.

An approach to realizing qubits using atoms as natural quantum coherent devices. The atoms are charged and held in place using electromagnetic fields. Due to the repulsion of like charges they form neatly ordered arrays. Information can be encoded in the valence electron state of each atom or the vibrational motion of the atoms in their trapping potentials.