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Questions tagged [variational-quantum-algorithms]

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motivation behind using PQCs in QML and Variational Algorithms

Parameterized quantum circuits (PQCs) are a key component in many quantum machine learning (QML) and variational quantum algorithms, such as the Variational Quantum Eigensolver (VQE) and quantum ...
Parmeet Singh EP 066's user avatar
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Implementing a Global Observable in Qiskit v1.1.0

In the following article the authors consider a quantum autoencoder in their numerical results, near to the equation (22). In more detail, the authors consider a bipartite quantum system $A B$ ...
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Error code 1217: "Session has been closed"

I am currently studying algorithms related to VQA. I have built a circuit to calculate the cost function and optimized it using a classical optimizer. During the initial optimization iterations, ...
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Error 400 on Variation Quantum Algorithm

As the title suggests, I am trying to optimize a cost function in a VQA (Variational Quantum Algorithm) code using a classical optimizer to obtain the best parameters. In my initial optimization ...
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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 ...
Moto's user avatar
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Gradient-free optimization in Qiskit without using pre-defined classes

Basically I want to build a gradient-free optimizer that classifies a very simple dataset (e.g. the sklearn make_moons) using scipy.optimize (Nelder-Mead or Powell ...
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VQLS behaves badly under simulation with noise

I was studying VQLS in https://qiskit.org/textbook/ch-paper-implementations/vqls.html and since I could not understand the circuit created by the new Hadamard test (...
MrEightL's user avatar
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How to combine a VQE circuit with normal qiskit quantum circuit without parameters and give the measured set of qubits to the estimator?

I want to use a parameterized quantum-circuit which is $\text{CNOT}$ with another quantum-circuit that has no parameters, then after a series of gates on the second quantum-circuit, I want to measure ...
Syed Shahmir Kazmi's user avatar
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Why are the variational parameters not changing in VarQRTE runs for TwoLocal ansatz?

Following the qiskit tutorial on Variational Time Evolution, I've changed the ansatz for VarQRTE from ansatz = EfficientSU2(hamiltonian.num_qubits, reps=1) to <...
squareroottwo's user avatar
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Qnode model gradient of inputs (not parameters!) question

I am trying to use qml to do physics informed quantum machine learning within Tensorflow. I know with TF, to get derivatives of the network's inputs (df/dx, for example), you can use with tf....
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Difference between PQCs and VQCs

I'm going through this TensorFlow tutorial on quantum machine learning. The code implements reinforcement learning algorithms based on parameterized/variational quantum circuits (PQCs or VQCs). What ...
Medulla Oblongata's user avatar
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Truncated Qumode States and Support

I am currently running numerical simulations of a single qumode state acted upon by a parameterised unitary. The qumode state is realised as a Fock state with a fixed cutoff dimension $(d)$ and is ...
Song of Physics's user avatar
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How can I get the structure of the variational ansatz for VQLS?

I have got a system of linear equations $$ A|x \rangle = |b\rangle \\ A = 0.45Z_3 + 0.55I \\ |b\rangle = H_1 H_2 H_3 $$ and I would like to solve it for $|x\rangle$. I am currently trying to ...
Matěj Šicner's user avatar
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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 ...
Zhelun Li's user avatar
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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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Obtain specific expectation value for a variational quantum circuit via optimization process

I have a quantum circuit built using CNOT gates and RY gates. I would like to obtain a specific expectation value for an observable (e.g. $\langle Z \rangle$ of the third qubit equal to a constant C). ...
stopper's user avatar
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Why is it hard to prove complexity bounds for variational algorithms?

I'm not very familiar with variational algorithms, but I've heard people say that they're "heuristic" and it's difficult to measure their performance via complexity analysis. Why is this the ...
confusion's user avatar
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Why EfficientSU2 in QGAN

In Qiskit's QGAN example, the parameterised quantum circuit to be trained is the EfficientSU2. I have not found any citation there on the choice of this circuit, and the only justification is that it ...
Wolfman Jack's user avatar
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1 answer
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Quantum computation of classical Fisher information

Consider a pure $n$-qubit quantum state $|\psi_\theta\rangle$ prepared by some parametrized quantum circuit. There exist well-known algorithms to efficiently estimate the quantum Fisher information ...
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Pennylane variational classifier demo - need for padding

In the variational classifier demo from Pennylane, the data loading is performed with ...
Sarvapriya Tripathi's user avatar
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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 ...
Jean-Gabriel Chenard's user avatar
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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 ...
Jean-Gabriel Chenard's user avatar
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What are the quantum algorithms available for Monte Carlo sampling?

What are the quantum algorithms available for performing Monte Carlo sampling. Is there any implementation of these algorithms. Any kind of resources would be helpful
Rag's user avatar
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1 answer
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Why is qiskit's VarQITE not estimating expectation correctly?

I am using Variational Quantum Imaginary Time Evolution to find the lowest eigenvalue and corresponding eigensatate of a Hamiltonian through Qiskit's VarQITE method. But, for a circuit of 4 qubits or ...
Cheshta Joshi's user avatar
4 votes
2 answers
149 views

Is there a way I can create an ansatz such that the number of 1 is same in all the superposition states? [duplicate]

So I am working with a variational quantum algorithm and I realised that it would be very beneficial if I could create an ansatz where all the states in the superposition have same numbers of 1s. For ...
Cheshta Joshi's user avatar
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1 answer
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Derivative of cost function with respect to the unitary matrix

Suppose I have a cost function $C = \langle \psi \rvert U^\dagger O U \rvert \psi \rangle$ for a fixed observable $O$ and a fixed state $\rvert \psi \rangle$. I know that usually people take the ...
userflux9674's user avatar
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1 answer
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Image classification using quantum variational circuit?

Image classification using variational quantum circuit is described in here. 3 image clusters having clearly separable 3 feature coordinates have been chosen to be: There are classical clustering ...
James's user avatar
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Subespace Search Variational Quantum Eigensolver (SSVQE) with contraints

I am trying to reproduce this paper: https://arxiv.org/pdf/2211.02302.pdf. However, I am having problems in getting the singlet first excited state (S1). The authors in the paper, they use the SSVQE ...
bjail66's user avatar
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an issue with the execution time of a VQC classifier on an IBM quantum machine

I tried to use the available open-source IBM quantum machines. I’m trying to do a classification using the VQC classifier to classify data, but I encountered a problem. The VQC keeps fitting on the ...
lynda lebdjiri's user avatar
5 votes
1 answer
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Recent experimental demonstrations of variational quantum algorithms?

I am interested in the recent experimental demonstrations of variational quantum algorithms. Can someone please provide me with a list of references of recent experimental demonstrations of ...
Soumik Adhikary's user avatar
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1 answer
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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 ...
Nithin Reddy Govindugari's user avatar
2 votes
2 answers
858 views

What exactly are "variational quantum algorithms"?

I constantly see papers on "variational quantum algorithms" but I don't really see any explanation of what they are that are clear to me. I found out about the variational method in quantum ...
Andrew Baker's user avatar
1 vote
2 answers
259 views

How are the parameters in a variational circuit optimized?

I'm quite new to QML and I don't understand how the parameters in a variational circuit are optimized. I read about the parameter shift rule but what happens after the gradient is calculated ? How do ...
Duen's user avatar
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