Quantum glossary

An integrated circuit designed to do one specific task very efficiently. Compared to general-purpose chips (like CPUs), ASICs present minimal programmability and are more resource-efficient, achieving high throughput levels with low power consumption.

The process of replenishing atoms in quantum computing systems, particularly in neutral atom qubit arrays. This process is crucial for maintaining the integrity and functionality of quantum systems, as atoms can be lost during operations.

A type of QEC code based on bivariate polynomials, with error checks defined by two binary matrices. The code is arranged in a cyclic (or “bicycle”) pattern, allowing for physical qubits to be mapped to a 2D grid.

Bit-flip errors (also known as X-errors) occur when the qubit state is flipped along the vertical axis, e.g., from a |0> to a |1> or vice versa. 

An error-correcting code where quantum information is stored in the state of continuous systems (such as the number of photons in a cavity), which naturally protects the qubit from certain types of noise.

Clifford gates are easy to simulate classically and to implement within a QEC code, whereas non-Clifford gates are costly to implement in a fault-tolerant way as well as hard to classically simulate. Non-Clifford gates are required for universal logic, so implementing them efficiently is a central challenge for fault-tolerant quantum computing.

A specialised program that translates source code written in a high-level programming language into a representation that can run on a specific system or architecture, such as a CPU or GPU.

Control systems are the hardware and software components that interact with quantum devices to manipulate their behaviour and achieve desired states. These systems use classical signals, such as precisely timed microwave or radio-frequency pulses, to control the qubits in a quantum computer. They are essential for operations such as gate calibration, qubit manipulation and QEC, forming the crucial bridge between abstract quantum algorithms and physical quantum hardware.

An integrated circuit that users can program to execute a given set of instructions, largely in sequence. See Compiler for how the program is generated.

Types of physical qubits used for encoding the state of a logical qubit in a QEC code. They are coupled with measurement qubits, which get measured to infer potential errors occurring in the data qubits. 

This refers to the process by which a quantum system loses its quantum properties (and thus any quantum information encoded within it), typically due to interactions with its environment. 

A quantum decoder is a classical algorithm used in quantum computing to infer and correct errors in a quantum computer's qubits. It functions by interpreting data from ‘syndrome measurements’, which are indirect checks on the qubits, to identify and fix errors that may have affected the encoded logical state. Decoders are a crucial part of the error-correction process, which groups physical qubits to create more stable ‘logical’ qubits, making quantum computations more reliable.  

The classical process used for inferring errors based on syndrome measurements and determining their effects on the logical state.

These classical algorithms interpret syndrome measurements from the QEC code to identify and correct errors. Minimum-weight perfect matching (MWPM) and belief propagation (BP) are two commonly used decoding algorithms. 

A bridge from NISQ computers to full FTQC, this involves developing and using quantum computers with limited error correction, requiring special algorithms that can tolerate some noise to enable practical applications during this intermediate period. The goal is to find a trade-off between hardware and algorithm capabilities that can tackle a limited set of useful problems before large-scale, fully robust systems are available. 

This is a fundamental feature of quantum mechanics where the quantum state of two or more particles can become so interconnected that one particle’s state cannot be described independently of the other(s), even when separated by large distances.

The ability to perform accurate quantum operations despite the presence of errors in the underlying physical qubits, achieved by encoding logical qubits on many physical qubits and continuously performing error correction. 

This measures the ‘closeness’ between an actual quantum state or operation and its ideal, intended state or effect. A fidelity of 100% represents an operation or state that perfectly matches the intended outcome.

This is semi-permanent software that acts to control how a specific piece of hardware operates. This code is normally responsible for booting a system or interfacing with external hardware rather than performing a device’s primary function. 

An integrated circuit that users can program or reconfigure after manufacture to perform specific tasks very quickly. It can be designed to achieve large parallelism and throughput levels.

Quantum gates are fundamental components in quantum computing, analogous to classical logic gates in traditional computing. They are unitary operations that manipulate qubits - the basic units of quantum information - to perform computations.

An integrated circuit that users can program to execute a given set of instructions, which are largely executed in parallel. See Compiler for how the program is generated. 

Computational methods that combine classical and quantum computing techniques to solve problems more efficiently than either approach alone. The main idea is to divide a problem into parts that are best handled by classical computers and parts that are better suited for quantum computers. This approach leverages the strengths of both types of computing to achieve results that might not be possible with classical computing alone.

This quantifies the exponential suppression of the logical error rate in a QEC code when more physical qubits are added. A higher Lambda-value means that the logical error rate decreases more quickly with increasing code size, indicating more effective error suppression. It is a key metric for evaluating a quantum system's performance - a Lambda-value of two implies that the logical error rate halves every time the distance of the code is increased by two.  

The amount of time between a request and a response, for example, how long it takes to perform an operation from the point it was first initiated.

A technique used in quantum computing for implementing fault-tolerant logic using the surface code. It is suitable for 2D-local architectures such as superconducting and solid-state qubit types. The method achieves logical operations by performing sequences of local gates and measurements on a lattice of physical qubits. 

A source of noise where qubits no longer occupy the computational basis states |0⟩ and |1⟩ and instead move into a higher excited state, such as the |2⟩-state, corrupting the quantum information.

Operations performed on logical qubits (as opposed to physical qubits). 

These are a fundamental concept in quantum computing, used to encode quantum information so that it is robust against errors. Logical qubits are protected against environmental noise by QEC techniques, which encode them into multiple physical qubits.

Magic state cultivation and distillation are both resource state generation techniques in fault-tolerant quantum computing that produce high-fidelity magic states, where magic states are essential for implementing certain quantum gates fault-tolerantly. They differ in their approach. While distillation uses many low-quality encoded states to produce fewer high-quality ones through measurements and post-selection, cultivation uses physical magic states to check the fidelity of an encoded state through multiple post-selected stages. Cultivation uses fewer resources than distillation but produces magic states with a higher overall error. Cultivated magic states can also be used as the input to distillation to create very low error magic states, with more efficiency than using distillation alone.

(also known as ancilla qubits). Used in QEC, these are physical qubits that are entangled with data qubits and get measured to infer possible errors on the data qubits.

This involves protecting a fixed quantum state over time, against the effects of decoherence and noise.

This refers to the quantum computing era in which devices have a limited number of qubits and are prone to errors due to noise. These devices are not yet capable of achieving utility-scale, i.e. the ability to solve problems faster or more efficiently than classical computers. However, they are valuable for learning about and experimenting with quantum computing concepts and algorithms. 

Establishing the parity of a set of bits involves counting whether there is an even or odd number of ‘1s’ in the set. Parity checks on measurement qubits make it possible to detect errors on data qubits without collapsing the protected logical information.

These are the actual qubits within a quantum computer, used to implement quantum operations.

QEC methods use multiple physical qubits to redundantly encode logical qubits. The logical state is protected from errors on the physical qubits (arising from various noise sources such as gate noise, measurement noise and relaxation processes), which can be detected and corrected by decoders.

A QPU is a central component of any quantum computer. It is responsible for executing quantum algorithms by manipulating qubits, which are the basic units of quantum information. QPUs are designed to perform computations that leverage the principles of quantum mechanics, such as superposition and entanglement, to solve certain problems more efficiently than classical computers.

A scheme that encodes quantum information into multiple noisy physical qubits, creating one or more logical qubits that are protected from errors at the physical level. Different QEC codes include the surface code, the colour code and the bivariate bicycle code.

The physical resources required to implement QEC, often referring to the ratio of physical qubits to logical qubits within a given QEC code.

The technologies required to run QEC, including orchestration (for hardware-aware compilation, processing and decoder coordination), classical decoding, data processing and routing (to manage and route syndrome data). 

A physical error rate below which it is possible to exponentially suppress logical errors in a QEC code by increasing the number of physical qubits used to encode the logical information.

Techniques used in near-term quantum computing (and NISQ) devices for improving the accuracy of quantum computations without leveraging QEC. QEM methods infer less noisy quantum computation outcomes rather than correct them, often by repeatedly running slightly different circuits and classically post-processing the results. QEM methods reduce noise and were useful in the NISQ era because constraints in quantum hardware can make full QEC less feasible on small-scale systems. However, QEM’s classical cost scales exponentially with the number of qubits, making this approach less effective than QEC on large-scale systems.

Quantum bits (qubits) are the fundamental units of quantum information, analogous to bits in classical computing. Qubits are two-level quantum systems exhibiting the hallmark characteristics of quantum mechanics such as superposition (in which a qubit can be in a coherent superposition of multiple states simultaneously) and entanglement (in which multiple qubits can exist in a highly correlated state that does not exist for classical information).

Specialised algorithms designed to run on quantum computers, expressed in terms of operations on qubits.

Multiple layers are essential for running algorithms on a quantum computer. These layers include quantum algorithms, the compilation stack, the QEC stack, the control system and the physical qubit hardware.

A different way of carrying and manipulating quantum information than qubits. Qumodes are based on continuous variable quantum systems (such as light) and are frequently used in photonic quantum computers.

QuOps are a proxy for a quantum algorithm’s complexity, defined for a quantum circuit with N logical qubits and D operations as ‘QuOps = ND’. The maximum error-free QuOp capacity is a useful measure to assess a quantum computer’s power, playing a similar role as floating-point operations per second (FLOPS), commonly used to rank supercomputers.

A binary vector extracted from qubit measurements, indicating the presence of error events. In QEC, the syndrome is passed to a decoder whose task is to infer the most likely error events that caused the syndrome.

A custom-designed hardware accelerator created by Google for machine learning and artificial intelligence workloads.

The number of operations done per unit of time.

Transversal gates are quantum gates that act independently on corresponding qubits across different blocks of a QEC code. They are particularly useful for performing fast fault-tolerant logical operations between logical qubits and are suitable for high-connectivity quantum hardware modalities such as neutral atoms.

A fundamental component in quantum computing used to perform operations on two qubits simultaneously. These gates are crucial for creating entanglement and performing complex quantum operations, forming the basis for universal quantum computation.

This typically refers to the capability of quantum computers to perform computations of practical value that offer a noticeable advantage over classical computers for certain applications. Achieving utility scale implies that quantum computers are not just theoretical or lab-bound curiosities but have reached a stage where their power and speed can solve real-world problems that are computationally complex or infeasible for classical machines. The Defense Advanced Research Projects Agency's (DARPA’s) Quantum Benchmarking Initiative (QBI) aims to accelerate this process by creating benchmarks and metrics to assess the performance and utility of quantum systems. Under DARPA’s initiative, the goal is to ensure that quantum technologies are progressing towards a level where they can be reliably used for strategic and practical applications, especially those critical to national security and advanced research. In this framework, the concept of utility-scale emphasises not only achieving technical milestones in quantum computing capabilities but also proving the utility and superiority of quantum systems in handling specific tasks better than classical counterparts.