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Calcolo quantistico basato su porte

Algoritmi di calcolo quantistico basati su porte
Da R2023a

Creare porte e circuiti quantistici, simulare circuiti sul computer locale ed eseguire circuiti su hardware remoto utilizzando Amazon^® Web Services (AWS^®) o IBM^® Qiskit^® Runtime Services.

Classi

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Circuiti e porte quantistici

`quantumCircuit`	Quantum computing circuit
`quantum.gate.SimpleGate`	Simple gate for quantum computing
`quantum.gate.CompositeGate`	Composite gate for quantum computing

Stati e misurazioni quantistici

`quantum.gate.QuantumState`	State of qubits in quantum circuit
`quantum.gate.QuantumMeasurement`	Measurement result of quantum circuit

Dispositivi e attività quantistici

`quantum.backend.QuantumDeviceAWS`	Quantum device available through AWS
`quantum.backend.QuantumTaskAWS`	Task sent to AWS for execution on quantum device
`quantum.backend.QuantumDeviceIBM`	Quantum device available through IBM (Da R2023b)
`quantum.backend.QuantumTaskIBM`	Task sent to IBM for execution on quantum device (Da R2023b)

Proprietà

QuantumCircuitChart Properties

Quantum circuit plot appearance and behavior (Da R2023b)

Funzioni

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Funzioni di creazione della porta

Porte su un qubit di destinazione

`hGate`	Hadamard gate
`idGate`	Identity gate
`xGate`	Pauli X gate
`yGate`	Pauli Y gate
`zGate`	Pauli Z gate

Porte di rotazione

`rxGate`	x-axis rotation gate
`ryGate`	y-axis rotation gate
`rzGate`	z-axis rotation gate
`r1Gate`	z-axis rotation gate with global phase
`sGate`	S gate
`siGate`	Inverse S gate
`tGate`	T gate
`tiGate`	Inverse T gate

Porte con un qubit di controllo e un qubit di destinazione

`chGate`	Controlled Hadamard gate
`cnotGate`	CNOT gate (controlled X gate)
`cxGate`	Controlled X gate (CNOT gate)
`cyGate`	Controlled Y gate
`czGate`	Controlled Z gate

Porta di scambio dello stato di due qubit

swapGate Swap gate

Porte di rotazione controllate

`crxGate`	Controlled x-axis rotation gate
`cryGate`	Controlled y-axis rotation gate
`crzGate`	Controlled z-axis rotation gate
`cr1Gate`	Controlled z-axis rotation gate with global phase

Porta X controllata

ccxGate Controlled controlled X gate (CCNOT or Toffoli gate)

Porte di accoppiamento Ising

`rxxGate`	Ising XX coupling gate
`ryyGate`	Ising YY coupling gate
`rzzGate`	Ising ZZ coupling gate

Porte composite e specializzate

`compositeGate`	Construct composite gate for quantum computing
`qftGate`	Quantum Fourier transform gate
`initGate`	Initialization gate with specified qubit states (Da R2023b)
`unitaryGate`	Unitary matrix gate (Da R2023b)
`mcxGate`	Multi-controlled X gate

Porte di rotazione controllate uniformemente

`ucrxGate`	Uniformly controlled x-axis rotation gate (Da R2023b)
`ucryGate`	Uniformly controlled y-axis rotation gate (Da R2023b)
`ucrzGate`	Uniformly controlled z-axis rotation gate (Da R2023b)

Argomenti

Nozioni di base e workflow

Introduction to Quantum Computing
This topic contains background information about qubits, quantum gates, and quantum circuits.
Types of Quantum Gates
This topic describes the different types of quantum gates to build quantum algorithms.
Local Quantum State Simulation
This topic describes how to simulate a quantum circuit locally and analyze the simulation results.
Run Quantum Circuit on Hardware Using AWS
This topic describes how to run quantum circuits on remote hardware using Amazon Web Services.
Run Quantum Circuit on Hardware Using IBM Qiskit Runtime Services
This topic describes how to run quantum circuits on remote hardware using IBM Qiskit Runtime Services.

Esempi in primo piano

Graph Coloring with Grover's Algorithm

Use Grover's algorithm on a quantum computer to solve graph coloring problems. Grover's algorithm, also called the quantum search algorithm, is a fast method to perform unstructured searches. This example applies the algorithm to a problem where a bit string of a given length is classified as valid or invalid, and the goal is to retrieve one of the valid bit strings. The algorithm uses a state oracle to determine whether a bit string is valid. Although this application of Grover's algorithm is not the most efficient method to solve the graph coloring problem in practice, it illustrates how a quantum algorithm can be applied to a well-known problem.

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Ground-State Protein Folding Using Variational Quantum Eigensolver (VQE)

An efficient method for using qubits to encode a protein fold on a 3-D tetrahedral lattice [1], [2]. The ground-state is found through a simulated variational quantum eigensolver (VQE) routine. The VQE algorithm uses classical optimization to improve the initial guess of the ground state, and then a quantum computer calculates the expectation value. The final circuit from the simulation is run on a real QPU for comparison.

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Solve XOR Problem Using Quantum Neural Network (QNN)

Solve the XOR problem using a trained quantum neural network (QNN). You use the network to classify the classical data of 2-D coordinates. A QNN is a machine learning model that combines quantum computing layers and classical layers. This example shows how to train such a hybrid network for a classification problem that is nonlinearly separable, such as the exclusive-OR (XOR) problem.

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Quantum Monte Carlo (QMC) Simulation

Use Quantum Monte Carlo (QMC) simulation in MATLAB® to compute the mean of a function of a random variable. There are a broad range of tasks in finance and economics that depend on Monte Carlo simulation, from option pricing to macroeconomic stress testing. While this example does not explore computational efficiency, research shows that QMC offers a quadratic speed-up compared to classic Monte Carlo methods.

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