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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Introductory material for quantum machine learning

In the past few days, I have been trying to collect material (mostly research papers) related to Quantum machine learning and its applications, for a summer project. Here are a few which I found ...
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Quantum machine learning after Ewin Tang

Recently, a series of research papers have been released (this, this and this, also this) that provide classical algorithms with the same runtime as quantum machine learning algorithms for the same ...
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Is there any potential application of quantum computers in machine learning or AI?

A lot of people believe that quantum computers can prove to be a pivotal step in creating new machine learning and AI algorithms that can give a huge boost to the field. There have even been studies ...
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Will deep learning neural networks run on quantum computers?

Deep Learning (multiple layers of artificial neural networks used in supervised and unsupervised machine learning tasks) is an incredibly powerful tool for many of the most difficult machine learning ...
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Are there any examples of anyone applying quantum algorithms to problems in computational biology?

As the title suggests, I'm searching for published examples of quantum algorithms being applied to problems in computational biology. Clearly the odds are high that practical examples don't exist (yet)...
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1answer
700 views

Embedding classical information into norm of a quantum state

According to An introduction to quantum machine learning (Schuld, Sinayskiy & Petruccione, 2014), Seth Lloyd et al. say in their paper: Quantum algorithms for supervised and unsupervised machine ...
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1answer
276 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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Where can I find example circuits to learn from?

I'm relatively new to quantum computing and my goal is to learn how to implement algorithms that I read in papers. While I have found many circuit snippets I have yet to find a repository of examples ...
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401 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. ...
8
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1answer
227 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 ...
8
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1answer
707 views

Can quantum computing speed up Bayesian learning?

One of the biggest drawbacks of Bayesian learning against deep learning is runtime: applying Bayes' theorem requires knowledge on how the data is distributed, and this usually requires either ...
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120 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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453 views

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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2answers
334 views

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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136 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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1answer
207 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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1answer
217 views

Gradient boosting akin to XGBoost using a quantum device

I am currently trying to implement a boosting algorithm akin to XGBoost with a quantum device. The reason is that I want to make use of a quantum device to train weak classifiers. However, as far as I ...
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1answer
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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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What do "$i$-th basic network", "quantum multiplexers" and "quantum parallelism" mean in this context? How are they beneficial?

I have been reading the paper A quantum-implementable neural network model (Chen et al., 2017) for a few days now, but failed to understand how exactly their algorithm offers a speedup over the ...
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182 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 ...
5
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1answer
156 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 ...
5
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3answers
1k 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 ...
5
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1answer
876 views

Is quantum backpropagation faster than classical backpropagation?

I recently stumbled upon a press release from Xanadu.ai stating that Under the hood, PennyLane's core feature is that it implements a version of the backpropagation algorithm - the workhorse for ...
5
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70 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
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1answer
378 views

How to encode MNIST data set on a quantum circuit to study supervised learning with QNN?

I am trying to implement arXiv:1802.06002†. I do not understand how to take the data set from MNIST and apply it to a quantum circuit. [†]: Classification with Quantum Neural Networks on Near Term ...
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1answer
121 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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163 views

What are some of the interesting problems whose solutions have been proposed using quantum neural networks?

I know there are some "quantum versions" of hand-writing recognition algorithms which have been proposed using quantum neural networks. Example: "Recognition of handwritten numerals by Quantum Neural ...
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95 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 ...
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351 views

How to build a quantum circuit representing the Ising Model?

Can someone explain to me how to build a quantum circuit representing the Ising Model? I just want to understand how to represent the Ising Model for the purposes of quantum state label classification....
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2answers
401 views

How to recognize if a paper is talking about quantum annealing or gate logic?

I am currently reading various survey papers in Quantum Machine Learning, such as "Quantum Machine Learning" by Biamonte, Wittek, Pancotti, Rebentrost, Wiebe, and Lloyd. To me, it is not clear when ...
4
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3answers
179 views

Software tools to train quantum circuits with parameters

I want to play with the following problem. Given a unitary $U$ with parameters $\theta$ I want to optimize these parameters to make $U$ match some target unitary $V$, i.e. to find $\operatorname{...
4
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1answer
334 views

What language is more suitable for quantum machine learning algorithms?

What language is more suitable for quantum machine learning algorithms? Is it right that it's Python + Pyquil? Or something else? And do you know the sources where you can see the sample codes of ...
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2answers
100 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 ...
4
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1answer
71 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{\...
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2answers
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Are all computational resources reducible to the time resource?

It's well known that in most (if not all?) computations you can trade time and space resources. An extreme example might be creating an infinitely large lookup table of all composites produced from ...
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1answer
53 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 ...
4
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1answer
947 views

How to study quantum machine learning?

I want to make my quantum machine learning algorithms. As far as I understand I must learn: basics of quantum physics, quantum computing (and algorithms), classical machine learning, quantum ...
4
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1answer
263 views

Differentiable Programming of Quantum Computers

Recently, I have tried PennyLane and TensorFlow Quantum. These platforms are said to provide differentiable programming of quantum computers but I can't understand it clearly though. I have searched ...
4
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1answer
77 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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1answer
81 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 ...
4
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1answer
506 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 ...
4
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1answer
462 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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0answers
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Why does $x\sqrt{1-x^2}$ enhance the ability to approximate analytical functions in quantum circuit learning?

In this paper Quantum Circuit Learning they say that the ability of a quantum circuit to approximate a function can be enhanced by terms like $x\sqrt{1-x^2}$ ($x\in[-1,1])$. Given inputs $\{x,f(x)\}$, ...
3
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1answer
628 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,...
3
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1answer
813 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 ...
3
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1answer
501 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, ...
3
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1answer
549 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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2answers
52 views

Normalize and encode real data in a way that encode collinear vectors with different values

Now, I am working on a quantum supervised learning problem and I have a problem with amplitude encoding. Before being encoded, a vector $(a_1, a_2,\dots,a_n)$ must be normalized in such a way that $\...
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2answers
75 views

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 <...
3
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1answer
71 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 ...