Key Concepts

  • Barren Plateaus

    Areas in the cost landscape where the gradient of a parameterized circuit disappears. The mortal enemy of many a variational algorithm, the variance of the gradient at these points is also close to zero in all directions.

  • Circuit Ansatz

    An ansatz is a basic architecture of a circuit, i.e., a set of gates that act on specific subsystems. The architecture defines which algorithms a variational circuit can implement by fixing the trainable parameters. A circuit ansatz is analogous to the architecture of a neural network.

  • Hybrid Computation

    A computation that includes classical and quantum subroutines, executed on different devices.

  • Parameter-shift Rule

    The parameter-shift rule is a recipe for how to estimate gradients of quantum circuits. See also quantum gradient.

  • Quantum Approximate Optimization Algorithm (QAOA)

    A hybrid variational algorithm that is used to find approximate solutions for combinatorial optimization problems. Characterized by a circuit ansatz featuring two alternating parameterized components.

  • Quantum Chemistry

    A research area focused on addressing classically intractable chemistry problems with quantum computing.

  • Quantum Computing

    A research area that extends the set of physical laws classical computers operate on by accessing quantum aspects of the physical world, opening up new ways of processing information.

  • Quantum Convolutional Neural Network

    A quantum neural network that mirrors the structure of a convolutional neural network. Characterized by alternating convolutional layers, and pooling layers which are effected by performing quantum measurements.

  • Quantum Datasets

    Collections of data for physical systems that exhibit quantum behavior.

  • Quantum Differentiable Programming

    The paradigm of making quantum algorithms differentiable, and thereby trainable. See also quantum gradient.

  • Quantum embedding

    Representation of classical data as a quantum state.

  • Quantum Feature Map

    The mathematical map that embeds classical data into a quantum state. Usually executed by a variational quantum circuit whose parameters depend on the input data. See also Quantum Embedding.

  • Quantum Generative Adversarial Network

    Quantum analog of Generative Adversarial Networks (GANs).

  • Quantum Gradient

    The derivative of a quantum computation with respect to the parameters of a circuit.

  • Quantum Machine Learning

    A research area that explores ideas at the intersection of machine learning and quantum computing.

  • Quantum Neural Network

    A term with many different meanings, usually referring to a generalization of artificial neural networks to quantum information processing. Also increasingly used to refer to variational circuits in the context of quantum machine learning.

  • Quantum Node

    A quantum computation executed as part of a larger hybrid computation.

  • Quanvolutional Neural Network

    A hybrid classical-quantum model in which classical CNNs are augmented by layers of variational quantum circuits.

  • Variational circuits

    Variational circuits are quantum algorithms that depend on tunable parameters, and can therefore be optimized.

  • Variational Quantum Classifier (VQC)

    A supervised learning algorithm in which variational circuits QNNs are trained to perform classification tasks.

  • Variational Quantum Eigensolver (VQE)

    A variational algorithm used for finding the ground-state energy of a quantum system. The VQE is a hybrid algorithm that involves incorporating measurement results obtained from a quantum computer running a series of variational circuits into a classical optimization routine in order to find a set of optimal variational parameters.

  • Variational Quantum Linear Solver (VQLS)

    An algorithm for solving systems of linear equations on quantum computers. Based on short variational circuits, it is amenable to running on near-term quantum hardware.

  • Variational Quantum Thermalizer (VQT)

    A generalization of the VQE to systems with non-zero temperatures. Uses QHBMs to generate thermal states of Hamiltonians at a given temperature.