Questions tagged [machine-learning]

For questions about how quantum computing could improve or affect machine learning i.e. quantum machine learning. Questions about classical machine learning belong on another site, such as Stack Overflow, Cross Validated or Artificial Intelligence SE.

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Is qiskit documentation about determining $|0\rangle$ and $|1\rangle$ incorrect?

I'm using pi-pulse pulses on qubit Armonk for determining 0 and 1 by Machine Learning. But when I run the code from https://qiskit.org/textbook/ch-quantum-hardware/calibrating-qubits-pulse.html.I get ...
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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?
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Random Circuit Generation in Cirq

I am trying to improve an optimization method as describe in this paper: enter link description here For that I need to create many random equivalent circuits. In my experiment I have 6 beam splitters ...
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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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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 ...
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2answers
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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 ...
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1answer
231 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. ...
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Calculating Dot Product of Two States

I've been reading Peter Wittek's Quantum Machine Learning. In chapter 10.2 of this book, the author explains how we can calculate the dot product of two states: To evaluate the dot product of two ...
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1answer
50 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 ...
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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 ...
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3answers
103 views

How to learn parameters in a quantum circuit, given an interference pattern?

Using cirq, I have the following quantum circuit, with three parameters: phi, alpha and beta: ...
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Quantum Boltzmann machine: How do you sample from the Boltzmann distribution on a quantum computer?

I am reading through the following article https://arxiv.org/abs/1601.02036. Eq. (22) describes one of the terms of the gradient of the log-likelihood cost function, which can be estimated using ...
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Quantum Circuit Optimization with Machine Learning [closed]

I read some paper about Quantum Circuit Optimization but I am on a low level. And have some experience in ML. But what I don't understand is it possible that ML can help to optimize Quantum Circuits ...
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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 ...
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What is the advantage of quantum machine learning over traditional machine learning?

Why exactly is machine learning on quantum computers different than classical machine learning? Is there a specific difference that allows quantum machine learning to outperform classical machine ...
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What are the benefits of using quantum machine learning?

I have been investigating uses for quantum machine learning, and have made a few working examples (variations of variational quantum classifiers using PennyLane). However, my issue now is its ...
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107 views

What are the differences between the IBM machines?

I'm quite new to this field, and have started sending jobs to IBM's quantum computers. I have access to around 11 locations. I can see that these have different numbers of qubits within them, and then ...
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120 views

Calculating gradient of a gate using Parameter shift rule

I've been following this website to check out how parameter-shift works for calculation of gradients for backpropagation in Variational Quantum Machine Learning Circuits Most of it made makes sense ...
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1answer
99 views

Quantum-Assisted Neural Network Training (Is my design reasonable?)

I'm a college student with a slight interest in quantum mechanics. I think I have a decent understanding of the Copenhagen and Many Worlds interpretations of quantum mechanics, and was considering how ...
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1answer
380 views

Quantum Circuit To Compute Any Inner Product

I'm currently reading the paper Classification with Quantum Neural Networks on Near Term Processors It shows a method to determine the following quantity: Where U is a unitary operator acting on $|z,...
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1answer
33 views

What's the relationship between output of qubit measurements and classification of data in Quantum Machine Learning?

I'm training a model in Q# which has more than 2 features. I have trouble understanding the following things: How is the data classified based on the qubit states? For example: If I have only 2 ...
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How do you decide which rotations to use in a Quantum Machine Learning model?

I am trying to design a model using Q#'s machine learning library that takes in two features (real numbers from 0 to 1) and classifies as 0 or 1. So how do I decide which Rotations and what seeds to ...
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1answer
78 views

How is back-propagation done in “Transfer learning in hybrid classical-quantum neural networks”

Just read this paper from Xanadu on Quantum Transfer Learning and a couple of things are unclear to me regarding the optimisation step. How is back-propagation done through the classical weights ...
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232 views

Q# Error: No namespace with the name “Microsoft.Quantum.MachineLearning” exists

I'm having trouble getting the namespace Microsoft.Quantum.MachineLearning. Here is an example Q# code: ...
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1answer
99 views

How many samples are required to estimate the probabilities of a state?

Suppose that we have a quantum state of the form: $$|\psi\rangle = \sqrt{p}|0\rangle + \sqrt{1-p}|1\rangle$$ In order to get an estimate of the probability of reading $|0\rangle$ or $|1\rangle$, we ...
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2answers
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Is there a “parameterized initialization” that I can apply to a QuantumRegister to re-use a circuit?

I'm working on a QuantumCircuit which measures the fidelity of one point (my "test vector") and two other points (my "data set", containing of states phi_1 and <...
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1answer
100 views

How to turn off multiprocessing in TensorFlow Quantum

Some background: I'm currently running the same training algorithm with a classical neural network and a quantum circuit, respectively. The NN is implemented in Keras with a TensorFlow backend, the ...
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1answer
68 views

IBM Q Experience - Can it be used draw out ML inferences? [closed]

Are there Quantum-enhanced Machine Learning algorithms that can be implemented via Qiskit in IBM Q Experience and obtain valuable inferences faster than their classical counterparts from datasets of ...
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1answer
83 views

Initial assumption of the unitary that allows us to estimate the label function

You can find the paper here , in which they describe the architecture of a QNN that can be used to learn binary functions and correctly classify unseen data. They say that for each binary label ...
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1answer
48 views

Question About Measuring an Operator For Quantum Neural Network Paper

I'm currently reading the paper: https://arxiv.org/pdf/1802.06002.pdf I'm a little bit stuck on the step of how to determine the following quantity: Where U is a unitary operator acting on $|z,1\...
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1answer
127 views

Why is Farhi and Neven's architecture described in “Classification with Quantum Neural Network on near term processors” called a Neural Network?

In regards to "Classification with Quantum Neural Networks on near term processors" (which you can find here) , there are still a few things that do not make entirely sense to me. First of all, why ...
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1answer
67 views

Quantum NN vs Quantum-Inspired NN

I can't find the true difference between Quantum Neural Network (QNN) and Quantum-Inspired Neural Network (QINN). I have multiple guesses: QINN and QNN are absolutely the same thing (all QNNs are ...
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1answer
127 views

New Hybrid-HHL algorithm vs VQLS

A team of researchers has realized hybrid quantum algorithm for solving a linear system of equations with exponential speedup that utilizes quantum phase estimation, the algorithm demonstrates quantum ...
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1answer
65 views

Will NISQ based algorithms be useful in fault-tolerant Quantum computers?

As a data scientist, I want to use the cutting edge algorithms of machine learning to build my models, I am interested in quantum machine learning, the recent research in QML is about variational ...
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29 views

Can We Currently Import Quantum Datasets (Datasets Containing Quantum Data) Onto NISQ-era Quantum Computers?

I'm still investigating the TFQ whitepaper. In one section of the paper, the authors say this with respect to Quantum Datasets In general, [a quantum dataset] might come from a given black-box ...
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1answer
259 views

How Mature is the Tensorflow Quantum Library [closed]

Where does The Tensorflow Quantum ( TFQ ) library fall on it's maturity curve. In other words can we currently leverage the TFQ ...
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0answers
66 views

What Are The Most Promising Real-World Applications For Quantum Machine Learning

I know this has been asked before in different ways, however, I am interested in something with a degree of clarity and focus not found in other questions. What I am looking to get is a list of the ...
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1answer
129 views

QML: “Quantum Data loader” instead of QRAM?

In last year‘s conference "Quantum For Business 2019" Iordanis Kerenidis gave a nice talk about quantum machine learning. At about time 27:10 he mentions a "Quantum Data loader" as an alternativ for ...
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1answer
65 views

What does the maximum of a Hamiltonian means (in a particular paper)?

In the paper Quantum Observables for continuous control of the Quantum Approximate Optimization Algorithm via Reinforcement Learning, an Hamiltonian is defined in order to solve the MAXCUT problem : $...
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1answer
321 views

How is data encoded in a quantum neural network?

I am a newbie to quantum machine learning. I am trying to build a quantum neural network (QNN). What I studied so far about QNN is that input would be qubits and hidden layer parameter can be set ...
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1answer
362 views

How to decompose a multi-target controlled gate?

I'm trying to replicate with qiskit the results of this paper in which basically they implement a quantum version of the Principal Component Analysis applying Quantum Phase Estimation algorithm in ...
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76 views

Understanding SGD on a Quantum Circuit

I implemented the following circuit, a very simple circuit: I applied the technique presented on Farhi's paper - which I am so happy people in here are talking about more and more ! - and applied to ...
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1answer
97 views

Is Industry or PhD programs best for someone wanting to go to quantum machine learning? [closed]

Is Industry and the companies including IBMa and D-wave etc or PhD research programs best for someone wanting to go to quantum statistical/mathematical machine learning in the United States? I mean ...
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1answer
41 views

Quantum Noise Dataset

Does anyone in here know of an open source source for finding noisy data from quantum gates. I am interested in playing around with in the same way people play around with MNIST. I know it's a long ...
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52 views

Software for implementing Quantum Machine Learning

I want to have a software product specifically suited for Quantum Machine Learning. Please help me with a list of software product which has been designed specifically for implementing Quantum Machine ...
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1answer
250 views

What are the mathematical prerequisites to study machine learning on quantum computers?

Besides machine learning, quantum info theory, optimization, and statistics knowledge, what are the prerequisites to implement existing ML techniques and create new ML techniques that would work on a ...
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2answers
120 views

Does anyone know how to get a list of all the Qiskit ML datasets, and if they can also be used for classical machine learning?

I am trying to create a Quantum Classifier and would like to try to test it out using a Qiskit ML dataset. However, I only know of the breast cancer dataset and I would like to try it on another ...
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Variances of the principal components in Ewin Tang's PCA algorithm

In Quantum-inspired classical algorithms for principal component analysis and supervised clustering, the PCA algorithm requires that the variances of the principal vectors differ by at least a ...
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1answer
372 views

Quantum PCA State Preparation

In Quantum Algorithm Implementations for Beginners is an example of the Quantum PCA with an given 2 x 2 covariance matrix $\sum$. The steps for state preparation are given in the paper. The steps are: ...
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1answer
365 views

Quantum Principal Component analysis by Seth Lloyd

I am currently reading the paper quantum principal component analysis from Seth Lloyd's article Quantum Principal Component Analysis There is the following equation stated. Suppose that on is ...