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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77 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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58 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 ...
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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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1answer
100 views

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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3answers
102 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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0answers
47 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
83 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
303 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
55 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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2answers
181 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
94 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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48 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
64 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
80 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
46 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
96 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
64 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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0answers
65 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
54 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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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
249 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
59 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
85 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
56 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
191 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
306 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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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
91 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
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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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49 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
200 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
106 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
309 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
282 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 ...
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1answer
389 views

Quantum speedup in Bayesian machine learning on NISQ computers

It is well known that in Bayesian learning, applying Bayes' theorem requires knowledge on how the data is distributed, and this usually requires either expensive integrals or some sampling mechanism, ...
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105 views

How to preprocess data to fit Qiskit QSVM

I want to start experimenting with quantum machine learning using Qiskit library, but I have come across an issue. All tutorials I have seen so far like this one import datasets using custom packages. ...
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3answers
664 views

Pennylane and Qiskit for quantum machine learning

I'm interested in quantum computing, specifically in “quantum machine learning” (QML). I'm going to start my masters program in computer science and have previous experience in classical machine ...
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1answer
63 views

Low-dimensional data and quantum machine learning

Ewin Tang says to not expect exponential speed-ups from quantum machine learning using low-dimensional data because, in such cases, quantum analogues of classical algorithms will not provide ...
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0answers
46 views

Transfer trained machine learning model

I know just the basics of quantum computer i.e. superposition, entanglement, gates and few other kinds of stuff. Now the question is it possible to transfer a trained machine learning model from IBM ...
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1answer
238 views

Can quantum computing contribute to the development of artificial intelligence?

I am interested how quantum computing can contribute to the development of artificial intelligence, I did some searching, but could not find much. Does somebody have an idea (or speculations)?
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Distance calcluation between two vectors

In Quantum Machine Learning for data scientists, Page 34 gives an algorithm to calculate the distance between two classifical vectors. As mentioned in this question, it is not clear how the SwapTest ...
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0answers
45 views

Encoding Binary Data into Quantum Basis

I am working on implementing a paper on QNNs. I have successfully been able to resize a MNIST digit to be able to meet the size of quantum circuit. But I am not clear of how to convert the resized ...
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0answers
132 views

Quantum Optimization via Quantum Label Classification in Quantum Circuits

I have been reading Farhi and Neven's paper on quantum neural networks on quantum circuits. I also found an example - albeit not ideal as pointed out by a couple of users - thank you - in here. ...
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866 views

How to run quantum SVM algorithm from Qiskit in real IBM Quantum Computer using IBMQ?

I'm trying to run QSVM algorithm in IBMQ experience, want to run in one of those real quantum computers. ...