Quantum Discriminator for Binary Classification

09/02/2020
by   Prasanna Date, et al.
6

Quantum computers operate in the high-dimensional tensor product spaces and are known to outperform classical computers on many problems. They are poised to accelerate machine learning tasks in the future. In this work, we operate in the quantum machine learning (QML) regime where a QML model is trained using a quantum-classical hybrid algorithm and inferencing is performed using a quantum algorithm. We leverage the traditional two-step machine learning workflow, where features are extracted from the data in the first step and a discriminator acting on the extracted features is used to classify the data in the second step. Assuming that the binary features have been extracted from the data, we propose a quantum discriminator for binary classification. The quantum discriminator takes as input the binary features of a data point and a prediction qubit in the zero state, and outputs the correct class of the data point. The quantum discriminator is defined by a parameterized unitary matrix U_Θ containing 𝒪(N) parameters, where N is the number of data points in the training data set. Furthermore, we show that the quantum discriminator can be trained in 𝒪(N log N) time using 𝒪(N log N) classical bits and 𝒪(log N) qubits. We also show that inferencing for the quantum discriminator can be done in 𝒪(N) time using 𝒪(log N) qubits. Finally, we use the quantum discriminator to classify the XOR problem on the IBM Q universal quantum computer with 100% accuracy.

READ FULL TEXT
05/04/2019

Matrix Product State Based Quantum Classifier

In recent years, interest in expressing the success of neural networks t...
11/30/2020

Hybrid quantum-classical classifier based on tensor network and variational quantum circuit

One key step in performing quantum machine learning (QML) on noisy inter...
08/07/2022

An example of use of Variational Methods in Quantum Machine Learning

This paper introduces a deep learning system based on a quantum neural n...
10/14/2021

Hybrid Quantum-Classical Neural Network for Cloud-supported In-Vehicle Cyberattack Detection

A classical computer works with ones and zeros, whereas a quantum comput...
02/09/2022

Noise fingerprints in quantum computers: Machine learning software tools

In this paper we present the high-level functionalities of a quantum-cla...
08/04/2022

Scalable Quantum Neural Networks for Classification

Many recent machine learning tasks resort to quantum computing to improv...
12/03/2021

Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer

We present regression and compression algorithms for lattice QCD data ut...