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.

Filter by
Sorted by
Tagged with
0
votes
1answer
27 views

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 ...
0
votes
0answers
35 views

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/...
1
vote
1answer
23 views

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 ...
2
votes
2answers
52 views

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 ...
1
vote
0answers
10 views

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 ...
4
votes
1answer
80 views

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 ...
3
votes
1answer
75 views

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 ...
1
vote
1answer
76 views

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 ...
4
votes
1answer
99 views

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 ...
0
votes
1answer
62 views

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 ...
0
votes
0answers
33 views

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 ...
0
votes
0answers
28 views

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 ...
1
vote
1answer
71 views

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 ...
1
vote
0answers
53 views

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 ...
1
vote
1answer
60 views

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 ...
2
votes
0answers
49 views

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 ...
4
votes
1answer
105 views

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{\...
0
votes
0answers
39 views

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 ...
3
votes
1answer
76 views

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 $U_W$...
1
vote
0answers
39 views

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 ...
2
votes
0answers
57 views

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(\...
2
votes
1answer
57 views

'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. ...
5
votes
0answers
119 views

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 ...
2
votes
1answer
361 views

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 \...
1
vote
0answers
44 views

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.
3
votes
2answers
167 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: ...
3
votes
1answer
105 views

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 ...
3
votes
1answer
63 views

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 ...
4
votes
1answer
57 views

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 ...
0
votes
0answers
36 views

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, ...
5
votes
1answer
190 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 ...
6
votes
2answers
440 views

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 ...
1
vote
1answer
73 views

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 ...
3
votes
1answer
75 views

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 ...
6
votes
1answer
138 views

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 ...
0
votes
0answers
66 views

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 ...
1
vote
2answers
83 views

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 ...
4
votes
1answer
149 views

SWAP Test as a Projective Measurement [closed]

In a much cited paper by Lloyd et al Quantum Algorithm for Supervised and Unsupervised Machine Learning, they proposed a rather cute quantum algorithm to evaluate the distance between an input feature ...
2
votes
2answers
135 views

Quantum Machine Learning in NISQ era

I know that quantum algorithms can be useful for machine learning ("ML") methods, and vice versa. For example if we use QAOA we can use for the optimization part different types of ML ...
0
votes
1answer
41 views

What's the point of the half coefficient in the max-cut cost Hamiltonian

Below is the cost Hamiltonian for an unweighted max-cut problem, I don't understand what the point of the half coefficient is. Why couldn't we omit it? $C_\alpha = \frac{1}{2}\left(1-\sigma_{z}^j\...
4
votes
2answers
252 views

Computing expectation value of product of observables in PennyLane

In PennyLane, the following circuit returns the expectation value of the PauliZ observable on qubit (wire) 1: ...
4
votes
2answers
165 views

What does the quantum part of the quantum support vector machine actually do?

I'm implementing a quantum support vector machine on qiskit and I was wondering what the quantum part of the algorithm actually does. I'm aware that it's a feature map that executes the kernel ...
8
votes
1answer
443 views

Comparing method of differentiation in variational quantum circuit

Training of variational circuits needs to calculate the derivative to be optimized. Several methods were proposed (1), the most famous ones being the finite difference and the parameter shift rule. ...
5
votes
1answer
87 views

Are there quantum algorithms demonstrating speedup computing classical neural networks (in 2021)?

It seems like there are a number of different speed-ups for different machine learning algorithms: But has anyone created an algorithm showing speed-up for neural networks? A similar question was ...
5
votes
4answers
196 views

Getting started with Quantum Machine Learning

I have some working knowledge in Machine Learning and Deep Learning. I am currently in the process of studying Quantum Computing fundamentals. I would like to know whether there are any Quantum ...
3
votes
1answer
124 views

Does TensorFlow Quantum tfq.convert_to_tensor work on custom gates?

I'm trying to use Cirq with TensorFlow Quantum to simulate a variational quantum classifier. There's a tutorial on the TFQ website on building a quantum neural network to classify a simplified version ...
2
votes
1answer
104 views

What is a "repeat until success quantum circuit" in quantum neural networks?

I am working now on a quantum neural network project and want a deep explanation on the Repeat Until Success circuit. What I know about this circuit is that it allows a nonlinear activation function ...
1
vote
2answers
267 views

Usage of Tensorflow/Keras to train Qiskit circuits

In order to explore whether it is possible to train a Qiskit Quantum circuit with tensorflow I built a small toy model. The purpose of this toy model is to find via tensorflow the correct angle to get ...
0
votes
1answer
154 views

Comparing QSVM & Classic SVM on BigData. Quantum Supremacy

I work on comparing QSVM and Classic SVM (SKlearnSVM) with using Qiskit. I have to show quantum supremacy at 400000-500000 samples but I don't get good results. I have problem with long time training ...
3
votes
1answer
259 views

What is the advantage of QSVM over the classical SVM?

I am mainly talking about QSVM from Qiskit (https://qiskit.org/documentation/stubs/qiskit.aqua.algorithms.QSVM.html#qiskit.aqua.algorithms.QSVM) versus a classical SVM. Is it just a time complexity ...