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Questions tagged [tfq]

TensorFlow Quantum (TFQ) is a quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models. It integrates quantum computing algorithms and logic designed in Cirq and provides quantum computing primitives compatible with existing TensorFlow APIs and quantum circuit simulators.

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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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2 votes
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How to train the embedding of classical data as well as the classifier in TFQ?

I've got some classical training data, and, for the moment, each of these will have its own embedding parameters defining how it is inputted into a certain ansatz. What I'd like is a circuit in two ...
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Use parametrized quantum circuit output amplitudes for training in tensorflow

I am trying to train a quantum neural network in tensorflow_quantum (tfq). Using cirq.Circuit I have set up my circuit. I now need to wrap it in a keras model for ...
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Decomposition of the multi-controlled gate in tensorflow quantum

In TensorFlow Quantum 0.5.0, the support for Cirq gates that have arbitrary control via the gate.controlled_by function is added. I would like to know which kind of ...
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Does anyone know how to use TF Quantum with real hardware data?

I'm currently trying to embed a tensorflow model for denoising measurements as a tensorflow quantum model, and at some point I'd like for this to be able to run on hardware. After reading through all ...
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Quantum Circuits for Time-Series Data

I am currently working with a dataset with autocorrelated features, i.e, x(t) affects the value of x(t+1) which affects the value of x(t+2). Suppose this is the circuit representing x(t): Does ...
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2 votes
1 answer
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Encoding Numeric data as a quantum circuit in TFQ

I am working on a dataset where I have 6 input features that are numbers in the range of 1 - 1000 that need to be encoded as a quantum circuit. I am using TensorFlow Quantum for my research. While I ...
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3 votes
2 answers
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Sympy suddently does not work together with TFQ

I work with tensorflow-quantum and use sympy for parameter updating. Suddenly, without (manually) updating or changing anything this error comes up: ...
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How to convert a dataset of different values in [0,1000] to quantum data for training a model using Tensorflow QuantumHaving?

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How do you represent one-qubit rotations in two registers as a $4\times 4$ unitary matrix?

Let's say you have a circuit that performs a Z-rotation in the first register, and a Y-rotation in second register. How can we express this "moment" in terms of a 4x4 matrix, i.e. a two-...
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3 votes
1 answer
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Does TensorFlow Quantum tfq.convert_to_tensor work on custom gates?

I'm trying to use Cirq with TensorFlow Quantum to simulate a variational quantum classifier. There's a tutorial on the TFQ website on building a quantum neural network to classify a simplified version ...
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7 votes
3 answers
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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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1 answer
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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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