Questions tagged [quantum-neural-network]
A machine learning model or algorithm that combines concepts from quantum computing and artificial neural networks encompassing a variety of ideas, ranging from quantum computers emulating the exact computations of neural nets, to general trainable quantum circuits that bear only little resemblence with the multi-layer perceptron structure.
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Realizing as non-autonomous ODE as a quantum or hybrid circuit
Disclaimer: I am a mathematician/computer scientist interested in quantum computers.
Recently, I started reading about quantum computing, and I read that one uses unitary matrices since they ...
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What is the current equivalent of CircuitQNN?
I have a qiskit QNN code and I want to update some part of this code and use it in my project. In my project, I train and test a QNN that simply classifies images. However, I couldn't find what I ...
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Is there any QML algorithm that performs better than a classical one in practice?
As of today, is there any QML algorithm that performs better than a classical one in practice? I have been looking for quantum neural networks, quantum kernels and quantum CNN, but none so far have ...
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Implementation of identity block initialisation strategy for mitigating barren plateaus
I have been trying to implement this paper on identity block initialisation strategy for barren plateau mitigation but I don't really understand how one would apply it to a parameterised circuit with ...
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Is entanglement trainable?
There exists a famous result from Google that the gradients of the parameters of quantum neural networks (QNN) vanish exponentially with the number of qubits in the quantum circuit. Their result ...
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Quantum neural networks and quantum kernels deal with nonlinearities
I'm trying to understand quantum neural networks from reading Alchieri et al.'s review paper. The following paragraph describes the differences between classical and quantum neural networks:
Also, ...
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Measuring a single-qubit PauliZ using Qiskit's EstimatorQNN
I am currently working with the EstimatorQNN from Qiskit to construct a Quantum Neural Network using a custom Parametrized Quantum Circuit. But I want to change the ...
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What are necessary and sufficient conditions for the output of a parametrized unitary $U(\theta)$ to be smooth?
Let us consider a unitary $U$ parameterised by $\theta \in \mathbb{R}$, i.e, $U(\theta)$. What are the necessary and sufficient conditions for the output states of this unitary to be smooth? One ...
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How to add noise mode in Sampler (SamplerQNN) in qiskit for quantum neural network?
I would like to add a noise model to one of the tutorial examples of quantum machine learning in the Qiskit site (PyTorch QGAN implementation).
I used the following codes
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Quantum Generative Adversarial Network does not converge
I have built a quantum generative adversarial network model, in which the generator and the discriminator, both are quantum based model. The parametrized quantum circuit/ansatz of these two models are ...
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How can we compute the gradient in a Quantum RNN?
I was looking into implementing a quantum recurrent neural network (QRNN) for a project, but I have some doubts about the computation of the gradient. There are a few papers that have implemented a ...
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Categories and types of quantum inspired algorithms
I have a question concerning "quantum-inspired" algorithms. There seem to be several types of algorithms that fall into this category. Some examples are:
Ewin's dequantized algorithms
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How do I calculate the amount of qubits required for Image Classification with a Quantum Convolutional Neural Network?
I'm relatively new to the topic of QCNNs and I wanted to understand how the number of qubits is selected in the encoded quantum layer. Like is it based on the image we want to encode? What is the ...
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What are "unbounded loss functions" and "unbounded operators"?
I am reading this paper: Quantum Generative Training Using Rényi Divergences. In it, the authors mention the following multiple times:
"...an unbounded loss function can circumvent the existing ...
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Adding trainable weights to feature inputs for a CircuitQNN?
Currently I'm trying to get together a QNN that can be trained to classify the normalized (-1, 1) IRIS Dataset on all 3 classes. For this I am using Qiskit's ...
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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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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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Label function for a QNN designed to classify bit strings
The paper can be found https://arxiv.org/pdf/1802.06002.pdf here.
They say that for each binary label function $l(z)$ where $l(z)=−1$ or $l(z)=1$, there exists a unitary $U$ such that, for all input ...
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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 ...
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