Questions tagged [quantum-enhanced-machine-learning]

For questions about quantum algorithms tackling machine learning tasks (e.g. the HHL algorithm or questions about quantum neural networks). For questions about applying classical machine learning to quantum-information-related problems, use machine-learning instead.

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The relationship between number of shots and performance of quantum agent

What is the relationship between number of shots and the performance of quantum agent in Quantum neural network? and what is the limit of number of shoots in QASM simulator?
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How well different featuremap encode the data?

Recently, I was doing research on QML. Qiskit gave detailed steps on how to encode data into quantum states, but I was confused about one point: there are different feature mapping methods under ...
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Quantum Kernel Machine Learning loss function and the plot of kernel?

When I was doing quantum machine learning, after building the quantum kernel, I drew the graph of the loss function changing with the iteration function and the graph of the quantum kernel, but I ...
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ValueError: setting an array element with a sequence for qiskit

I am trying to implement Quantum Kernel Ridge Regression (replacing the classical kernel with quantum kernel) in qiskit. The shape of my input x is (7165 x 529) and due to reshaping errors, I added an ...
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keras agents fails in DQNAgent using PQC during clonation for target

I have some issues using keras-rl2 with tensorflow_quantum and VQC (using identical architecture as https://www.tensorflow.org/quantum/tutorials/quantum_reinforcement_learning) After the creation of ...
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Tuning hyperparameters of QSVM

While implementing QSVM algorithm and I am facing some problems. I followed this tutorial: https://qiskit.org/documentation/stable/0.24/tutorials/machine_learning/01_qsvm_classification.html While ...
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Hybrid Quantum LSTM in Qiskit

I read this article on a Hybrid Quantum LSTM in Pennylane and I'm trying to replicate it in Qiskit. Nevertheless it doesn't seem to work very well. Here's my code ...
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Game formulation of Quantum GAN

Quantum Generative Adversarial Network (QuGAN) generates a desired quantum state via a minimax game between generator and discriminator (equivalently, it's optimizing a trace distance between ...
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Calculating the Inner Product using Quantum Phase Estimation

I'm following the method laid out in https://arxiv.org/abs/2011.03429 (Page 23 Equations 13-23) to calculate the inner product of two amplitude embedded vectors using Quantum Phase Estimation. I'm ...
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How can I change the default mapping function in ZZ feature map?

I am working with QSVM and have been reading a few things about this. I tried QSVM from the qiskit documentation as well. I also went through the link Quantum circuit for the ZZ feature map which ...
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186 views

Methodology to select the optimum feature map?

I am trying to perform a classification task with qiskit's VQC. The dataset I am using has a large number of dimensions/features/columns. I am trying to figure out which feature map works best. Also, ...
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Implementing Logistic Regression on IBMQ Hardware

I'm trying to implement a logistic regression inference circuit on NISQ hardware by following some of the proposed approaches below, [1] Hai-Ling Liu et al.Quantum algorithm for logistic regression. ...
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How to implement purification of the density matrix into a pure state of enlarged system in the quantum PCA algorithm?

I am trying to implement the quantum PCA algorithm to reduce the number of features (over 700 features) for a machine learning model. The original algorithm is proposed in this paper. I found a ...
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Parameterized swap test and perfect swap test

Suppose one has parameterized a swap test by using an ansatz $U(\theta) = \exp(-i\theta \text{ CSWAP})$, and one tries to find an angle $\theta$ such that one can distinguish given two quantum states ...
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Quantum GAN implementation

Can anyone provide a good link to understand how to implement qgan using pytorch in qiskit. Trying to understand this ( https://qiskit.org/documentation/machine-learning/tutorials/...
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Kernel ridge regression with qiskit's FeatureMap shows nonlinear patterns outside [0,1] range

I'm implementing a kernel ridge regressor using qiskit's FeatureMap and QuantumKernel to compute the alpha parameters of the solution. If I try to fit my model with non-normalized features I obtain ...
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Platform for mixed-state quantum machine learning?

I have been using PennyLane to run numerical QML simulations but it now seems to only support backprop on pure state simulations. Does anyone familiar with other packages know if there exists one that ...
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Implementation of Quantum PAC learning classifier

I am working on a project related to Boosting of Quantum Classifiers of PAC format. And I am a little confused about how do we go about implementing a PAC classifier. The basic idea is that we have to ...
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Why is sampling from probability distributions generated by specific quantum circuits classically intractable?

I was reading a paper by Benedetti et al. titled Parameterized quantum circuits as machine learning models. Its authors state the following: We also know that sampling from the probability ...
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Calculating the quantum euclidean distance between vectors

I am trying to get the distance using the swap test circuit. , With the help of the codes I shared, I can only estimate the distance between two vectors. Can it calculate the distances of many vectors ...
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How does the ZZ Feature Map influence the measurement?

I've been look at this Notebook from qiskit and trying to understand whats happening, but can't quite figure it out. From my understanding, rotations around the Z ...
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Understanding the Quantum Hebbian algorithm

I've been reading the paper from Lloyd and al. on Quantum Hopfield Networks, but I don't understand the quantum Hebbian algorithm (page 3). I am trying to understand the mathematical development on ...
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Is quantum machine learning faster than classical machine learning (at the moment)?

We all know that quantum computing is rapidly developing and somehow being used in the AI field. However, it seems like there's no specific comparison between quantum machine learning (could be deep ...
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How to perform multi-class classification with qiskit's VQC?

I am following the tutorial given in qiskit's website Neural Network Classifier and Regressor. In the first part, classification, the third section refers to qiskit's VQC library. Everything works ...
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How to train a Quantum Neural network for regression model in supervised learning

We want to train a parameterised circuit(which is our neural network - from this paper. Now our final circuit looks a little like Let's say there are n training cases. So I have n |gt> vectors ...
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1 answer
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How to set hyper parameters for a Variational Quantum Classifier (qiskit)?

I am trying to implement a Variational Quantum Classifier using qiskit's VQC. I have set the feature map to ZZFeatureMap and am using the ...
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1 answer
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Qiskit's classifier is not optimising the weights

I am using qiskit's VQC to build a classifier. Dimensionality of the data is 2 and number of classes are 4. The feature map I used is ZZFeatureMap and ansatz is the RealAplitudes. Then entanglement ...
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Is noise the only reason that makes the results of Quantum Support Vector Machine (QSVM) and Classical SVM differ, when we use a large dataset?

When I used and tested out the Quantum Support Vector Machine for just 120 samples of a large dataset (Training - 100 and Testing - 20). Its kernel classification results were quite close to the ...
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Does anyone know how to use TF Quantum with real hardware data?

I'm currently trying to embed a tensorflow model for denoising measurements as a tensorflow quantum model, and at some point I'd like for this to be able to run on hardware. After reading through all ...
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4 votes
1 answer
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Objective function of Quantum GAN in the paper "Quantum generative adversarial networks"

In this paper about Quantum GANs, the authors do not explain clearly how do they have the equation $$\newcommand{\tr}{\operatorname{Tr}}\newcommand{\Pr}{\operatorname{Pr}} V(\vec{\theta}_D, \vec{\...
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Quantum Boltzmann Machine and Gibbs state

I was looking into Quantum Boltzmann Machine and ran into Gibbs State as a part of training. Since new to this field, it would be good to have good intuitions why Gibbs state is related. Is Gibbs ...
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4 votes
1 answer
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Data encoding in the quantum perceptron model

In this paper, this figure shows the perceptron model used for quantum neural network. When realizing the inner product between weight vector and input vector, it defines a unitary transformation $U_W$...
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Quantum Machine Learning: how to get effective time of training/scoring

I am trying to examine the potential of Quantum Machine learning in terms of performance and time compared to classical algorithms. I am using both Qiskit's QSVM and scikit's SVM with Qiskit Quantum ...
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Reconstructing classical data from quantum feature maps

In the paper [Supervised learning with quantum enhanced feature spaces (Nature, arxiv) by Havlicek et al., a feature map is defined by $$| \Phi(\bar{x})\rangle=U_{\Phi(\bar x)}H^{\otimes n} U_{\Phi(\...
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1 answer
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'Geometric difference' in Google's 'Power of data in quantum machine learning' paper

Has anyone ever tried to implement the geometric difference metric introduced in the Google's power of data paper? It is defined in Eq. 5. My implementation of the metric is as follows. ...
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6 votes
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Is VQA quicker than classical machine learning?

Variational Quantum Algorithm (VQA) is a kind of quantum algorithm corresponding to classical machine learning. Unlike the square speed up of Grover's algorithm, the circuit in VQA does not seem to ...
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Quantum circuit for the ZZ feature map

Havlicek et al. propose a feature map for embedding $n$-dimensional classical data on $n$ qubits: $U_{\phi(x)}H^{\otimes n}$, where $$ U_{\phi(x)} = \exp (i \sum_{S \subseteq [n]} \phi_S(x) \prod_{i \...
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1 answer
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What is the kernel used in the IBM Qiskit's source code?

I want to redefine the QSVM code for a different kernel. But what is the kernel actually used in the IBM Qiskit's source code? And where is it defined, exactly. QSVM on Qiskit.
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2 answers
189 views

Sympy suddently does not work together with TFQ

I work with tensorflow-quantum and use sympy for parameter updating. Suddenly, without (manually) updating or changing anything this error comes up: ...
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4 votes
1 answer
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When and how do we use basis embedding?

It is suggested in various sources that a possible approach to representing classical data as a quantum state is simply to take the binary sequence $x$ and turn it to $|x\rangle$ (i.e., "basis ...
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3 votes
1 answer
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Why are 3, rather than 2 gates used in quantum variational circuits?

In the hello many worlds tensorflow tutorial and in the lockwood paper (2020) I have seen that often in QVC the following combination of gates is used: $R_z(\theta), R_y(\theta), R_x(\theta)$ I am ...
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5 votes
1 answer
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How is quantum machine learning reversible?

Say I have a binary classification network, which takes in inputs and classifies them. I can put in different inputs and get the same output, right? So does that not make QML non reversible, since ...
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Recommended resources for starter in quantum computing and its eventual applications on machine learning [duplicate]

A growing interest in Quantum Computing -particularly in its eventual applications on Machine Learning- has taken over me and I would like to follow that path. I have strong Maths (Calculus, ...
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6 votes
1 answer
261 views

Is a "kernel" just the quantum equivalent of classical SVMs?

I'm confused about the relationship between kernel methods and SVM methods used in quantum machine learning. Sometimes the two seem to be used interchangeably, but often I'll see them both in the same ...
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6 votes
2 answers
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Understanding the definition of quantum neural network of Abbas et al. 2020

My Question based on this Paper https://arxiv.org/pdf/2011.00027.pdf "Power of Quantum Neural Networks" - Section 2. So I know that there are different ways to implement Neural Networks into ...
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2 votes
2 answers
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Quantum SVM with large feature set

I am trying to practice QSVM from the following tutorial Introduction into Quantum Support Vector Machines The author has used 2 feature_dimension with 2 component PCA ...
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4 votes
1 answer
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How can I experimentally quantify the "speed up" of a quantum-enhanced machine learning?

I have essentially developed a Quantum Support Vector Machine to classify some data I have successfully. I wanted to know if it is possible to quantify the speed-up and time difference between this ...
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6 votes
1 answer
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Claimed "potential revenue" from machine learning in 2023?

In this plot: taken from here, IonQ is claiming to have a potential application in machine learning by 2023. What applications could they have in mind? From what I understand, modern error correction ...
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1 vote
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How do we implement QKNN algorithm on our dataset

What could be the steps to implement a distance based classifier (eg Qknn) on our dataset using quantum computing? I read a paper on "Distance based classifier using Iris dataset". I wanted ...
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2 answers
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What are the libararies for Machine Learning on NISQ Chip? And What are the roadmaps?

Nowadays quantum learning is hiring. And we can see mainly two different area. One of them is variational algorithms part. And the other one is classical learning for quantum systems like NISQ. (Some ...
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