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.
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Outputing classification probability from the Qiskit VQC
I am new to Qiskit. For the last few days, I have been trying to train my first VQC to do some classification task. Now the VQC is successfully running but it could only output a label whenever I ask ...
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How to save a hybrid Tensorflow and Pennylane model?
I implemented a hybrid model with Keras and Pennylane that looks like this:
The quantum layer is basically a quantum circuit converted to a keras layer with the ...
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Error loading saved hybrid quantum (pennylane + tensorflow keras) model: Unknown layer: 'KerasLayer'
I'm creating a hybrid model consisting of classical convolutional layers and a quantum output using Tensorflow. I can save the model in either .h5 or .keras format, but when I load them with the code <...
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What's the case when parameter-shift rule does not hold?
When the parameterized unitary is of the form $e^{-i\theta V}$, where $V$ is a Hermitian operator of the unitary, we can use parameter shift rule to calculate the gradient.
In this paper, it says: &...
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Could kernels also be used for Reinforcement Learning?
In this paper Kernel-Based Reinforcement Learning (2002), a classical kernel-based method was demonstrated for Reinforcement Learning , which indicates that classical research in this direction is ...
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Tensorflow_quantum hybrid models tf-quantum
I am trying to QCNN for MNIST classification equivalent to that built in.
I’m having problems trying to pass my quantum circuit built with cirq as a Keras layer. Here’s what I have:
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Cannot import tensorflow_quantum module in Colab
I was trying to install the tensor flow quantum module using the one given in their official website but it is showing these errors while installing.
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What ways are there to use parallelisation in quantum machine learning?
In classical machine learning, GPUs have been used successfully to parallelise the training as well as the inference process. Does quantum machine learning have the same potential to operate with ...
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Qiskit Variational Quantum Regressor - Qiskit VQR
I am new to quantum machine learning and I am trying to build a VQR with Qiskit. The input and target data to my model both have shape (32,4), where 32 is the number of samples and 4 is the number of ...
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How to go from a classical LSTM cell to a quantum LSTM cell where the neural network parts in the LSTM cell's gates are replaced by quantum circuits?
The input data I have is a tensor with shape (num_samples, num_timesteps, num_features). A single datapoint in my problem case is a feature vector of dim = 4 which conceptually corresponds to an ...
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How to determine which embedding method to use for QML?
So there are a lot of feature mapping techniques out there for Quantum Machine Learning, but I'm not sure which one to use for my next VQC.
Can anyone explain when and why to use each of the following?...
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The possibility of an image classifier using quantum computer architecture?
Consider an exhaustive database of all contour images that can ever be created on a 16x16 grid. Out of the $2^{256}$ unique possibilities, could a quantum computer classify all the resulting images ...
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Quanvolutional NN vs Quantum Convolution NN
There are 2 primary approaches for Image recognition using Quantum Neural Networks: 1. Quanvolutional one and 2. Quantum Convolutional Neural Networks. The primary difference is that in 1 we don't ...
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The necessity of a qRAM-based state preparation in qSVT-type problems
I've been reading a couple of papers regarding qPCA and its dequantisation. In the course of my reading, it appears to me that one of the ingredients that makes this dequantisation meaningful is the ...
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Qiskit_machine_learning QNNEstimator 'Estimator job failed' when using CU-Gates
I'm trying to construct a QNN using controlled arbitrary unitary gates. While some simple code versions work perfectly for controlled single rotations, the moment I add CU gate with parameters, the ...
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Getting High cost function in code implementation of VQLS pennylane tutorial
I am currently trying to implement the tutorial in pennylane
https://pennylane.ai/qml/demos/tutorial_vqls.html
for very complex example in 3 Qubit and cost function is very high in spite of adding ...
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How can i get the superposition of 8 bits from 26 bits outputs in qiskit
the only idea i see is get state vector from density_matrix
for example, i have the circult:
...
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Detailed references on Quantum Principal Component Analysis
I am looking for review articles and other online resources on qPCA based on Lloyd's original proposal. I have found the original source to be slightly hand-wavy with the details so I am having ...
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RealAmplitudes ansatz
Does someone know why RealAmplitudes ansatz is made like this ? I can't find any research paper on it.
Why does it use 4 Ry Gate for one qubit ?
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Most promising QML algorithms in the NISQ era
This question was asked in the previous years, but how is 2023 state of the art Quantum Machine Learning ?
Things seem to go fast in this area, for instance I saw Thales used 4 qubits for quantum ...
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Python implementation of Matthew Hastings' Tensor PCA algorithm
Is there any publicly available implementation of the algorithm presented in the paper Classical and Quantum Algorithms for Tensor Principal
Component Analysis by Hastings?
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How to take gradient of the `tfq.layers.State` output?
I am using the following code for building a quantum circuit as a custom tf.keras.layers.Layer:
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Plotting an ROC Curve with Qiskit's VQC
I'm trying to compare VQC to another algorithm using the ROC curve. I thought of using sklearn, but I am having problem replicating a decision_function for the VQC. The sklearn.metrics.roc_curves ...
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Applications of Quantum Principal Component Analysis
I have been reading Seth Lloyd's paper on Quantum Principal Component Analysis and while there is a short discussion that points to possible applications, I am having a hard time seeing the advantage ...
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I am optimising a variational quantum circuit to learn a distribution $p(x)$, but it doesn't converge over a training set $\mathcal{X}$?
I am training a variational quantum circuit to learn distributions: given data $s(\vec{\lambda})$, what is the probability distribution for the parameterisation $\vec{\lambda}$, i.e. the posterior ...
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What are QML algorithms using less than 8 qubits and provide a quantum advantage?
So this is more of a soft question.
I've been trying to find some quantum machine learning algorithms can both be run with less than 8 qubits and provide a quantum advantage to classical machine ...
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What do arbitrary encoding circuits provide?
I'm about to implement my first VQC for image classification and I'm trying to figure out which data encoding method could fit better the problem. From what I've understood, there are three main ...
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Data input limitations (size) for QML
I have done quite a few Google/paper searches but did not found an answer.
I would like to test the possibility of speeding up/ improving the accuracy of an existing unsupervised machine learning (...
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How to convert classical machine learning dataset to quantum dataset?
I'm looking for a way to convert images dataset to quantum dataset format to apply some quantum machine learning algorithms.
Is it possible?
I have read about that and I found it is possible by using ...
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Advantage of density matrix over vector to form quantum kernel
In Maria Schuld, Supervised quantum machine learning models are kernel methods, Section III.A, on page 6, the third paragraph from the bottom states
While from a quantum physics perspective it seems ...
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133
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Pennylane: Pennylane can not train the parameters of the problem
I asked this question in the Pennylane forum, but there was no reply for a long time, the link is: https://discuss.pennylane.ai/t/why-does-the-embedding-metric-learning-case-not-work/2211?u=rx1
The ...
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Hilbert space vs RKHS
I believe in quantum machine learning, it is interesting to talk about RKHS(reproducing kernel Hilbert space) and Hilbert space where a quantum state lives in. How do we think of these two spaces? Are ...
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Inference on real hardware using a pre-trained quantum model on a simulator
Being Quantum Computers with more than 5-7 qubits quite expensive (especially IBM's) I was wondering if it makes sense to pre-train a quantum machine learning model on a noisy simulator, store the ...
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Method and Meaning of Quantum Encoding in Quantum Machine Learning
I'm now studying quantum machine learning. While studying papers about quantum machine learning, I have a question about quantum embedding.
To my knowledge, some general embedding algorithms, such as ...
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How to create a quantum circuit with 800+ features using PennyLane
I am new to Quantum ML, and I am currently using PennyLane to do the QML activity.
As per this article, total number of features is equal to the total number of qubits. (In the example, they have ...
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A path towards building quantum Computing graduation project for undergraduates
I need help. I'm a computer science student with a Data science major. I have a final graduation project this year. With that, I want to create a project in the Quantum computing field. I'm already ...
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What's new in Quantum Natural Language Processing (QNLP) w.r.t classical NLP?
I recently discovered Cambridge Quantum people have developed lambeq, a quantum natural language processing high-level library. Before diving into it, I'd like to understand more in detail what ...
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Quantum Kernel Method: If the input is the QK provided by the variable qiskit, is it still true?
The puzzle is from
Case 1: https://qiskit.org/documentation/machine-learning/tutorials/03_quantum_kernel.html
Case 2: https://qiskit.org/documentation/machine-learning/tutorials/...
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What are the practical advantages of quantum GANs with respect to classical ones?
I read some papers on Quantum GANs, for instance this one and this one. I also noticed all the main quantum computing frameworks have a tutorial on quantum GANs, e.g. qiskit.
However I don't really ...
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What is the relationship between the number of shots and the performance of a quantum agent?
What is the relationship between number of shots and the performance of quantum agent in Quantum neural network? and what is the limit of number of shoots in QASM simulator?
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How well different featuremap encode the data？
Recently, I was doing research on QML. Qiskit gave detailed steps on how to encode data into quantum states, but I was confused about one point: there are different feature mapping methods under ...
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Quantum Kernel Machine Learning loss function and the plot of kernel？
When I was doing quantum machine learning, after building the quantum kernel, I drew the graph of the loss function changing with the iteration function and the graph of the quantum kernel, but I ...
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keras agents fails in DQNAgent using PQC during clonation for target
I have some issues using keras-rl2 with tensorflow_quantum and VQC (using identical architecture as https://www.tensorflow.org/quantum/tutorials/quantum_reinforcement_learning)
After the creation of ...
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Tuning hyperparameters of QSVM
While implementing QSVM algorithm and I am facing some problems.
I followed this tutorial: https://qiskit.org/documentation/stable/0.24/tutorials/machine_learning/01_qsvm_classification.html
While ...
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Hybrid Quantum LSTM in Qiskit
I read this article on a Hybrid Quantum LSTM in Pennylane and I'm trying to replicate it in Qiskit. Nevertheless it doesn't seem to work very well.
Here's my code
...
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Game formulation of Quantum GAN
Quantum Generative Adversarial Network (QuGAN) generates a desired quantum state via a minimax game between generator and discriminator (equivalently, it's optimizing a trace distance between ...
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Calculating the Inner Product using Quantum Phase Estimation
I'm following the method laid out in https://arxiv.org/abs/2011.03429 (Page 23 Equations 13-23) to calculate the inner product of two amplitude embedded vectors using Quantum Phase Estimation. I'm ...
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How can I change the default mapping function in ZZ feature map?
I am working with QSVM and have been reading a few things about this. I tried QSVM from the qiskit documentation as well. I also went through the link Quantum circuit for the ZZ feature map which ...
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Methodology to select the optimum feature map?
I am trying to perform a classification task with qiskit's VQC. The dataset I am using has a large number of dimensions/features/columns. I am trying to figure out which feature map works best. Also, ...
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Implementing Logistic Regression on IBMQ Hardware
I'm trying to implement a logistic regression inference circuit on NISQ hardware by following some of the proposed approaches below,
[1] Hai-Ling Liu et al.Quantum algorithm for logistic regression. ...
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