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Classical splitting of parametrized quantum circuits
Springer Science and Business Media LLC - Tập 5 - Trang 1-19 - 2023
Cenk Tüysüz, Giuseppe Clemente, Arianna Crippa, Tobias Hartung, Stefan Kühn, Karl Jansen
Barren plateaus appear to be a major obstacle for using variational quantum algorithms to simulate large-scale quantum systems or to replace traditional machine learning algorithms. They can be caused by multiple factors such as the expressivity of the ansatz, excessive entanglement, the locality of observables under consideration, or even hardware noise. We propose classical splitting of parametr...... hiện toàn bộ
Quantum convolutional neural networks with interaction layers for classification of classical data
Springer Science and Business Media LLC - - 2024
Jishnu Mahmud, Raisa Mashtura, Shaikh Anowarul Fattah, Mohammad Saquib
Quantum machine learning (QML) has come into the limelight due to the exceptional computational abilities of quantum computers. With the promises of near error-free quantum computers in the not-so-distant future, it is important that the effect of multi-qubit interactions on quantum neural networks is studied extensively. This paper introduces a quantum convolutional network with novel interaction...... hiện toàn bộ
Meta-variational quantum Monte Carlo
Springer Science and Business Media LLC - Tập 5 - Trang 1-9 - 2023
Tianchen Zhao, James Stokes, Shravan Veerapaneni
Motivated by close analogies between meta-reinforcement learning (Meta-RL) and variational quantum Monte Carlo with disorder, we propose a learning problem and an associated notion of generalization, with applications in ground state determination for quantum systems described by random Hamiltonians. Specifically, we elaborate on a proposal of (Zhao et al. 2020b) interpreting the Hamiltonian disor...... hiện toàn bộ
Quantum autoencoders for communication-efficient cloud computing
Springer Science and Business Media LLC - Tập 5 - Trang 1-15 - 2023
Yan Zhu, Ge Bai, Yuexuan Wang, Tongyang Li, Giulio Chiribella
In the model of quantum cloud computing, the server executes a computation on the quantum data provided by the client. In this scenario, it is important to reduce the amount of quantum communication between the client and the server. A possible approach is to transform the desired computation into a compressed version that acts on a smaller number of qubits, thereby reducing the amount of data exc...... hiện toàn bộ
Semi-supervised time series classification method for quantum computing
Springer Science and Business Media LLC - Tập 3 - Trang 1-11 - 2021
Sheir Yarkoni, Andrii Kleshchonok, Yury Dzerin, Florian Neukart, Marc Hilbert
In this paper we develop methods to solve two problems related to time series (TS) analysis using quantum computing: reconstruction and classification. We formulate the task of reconstructing a given TS from a training set of data as an unconstrained binary optimization (QUBO) problem, which can be solved by both quantum annealers and gate-model quantum processors. We accomplish this by discretizi...... hiện toàn bộ
Quantum algorithms for structured prediction
Springer Science and Business Media LLC - - 2022
Behrooz Sepehry, Ehsan Iranmanesh, Michael P. Friedlander, Pooya Ronagh
We introduce two quantum algorithms for solving structured prediction problems. We first show that a stochastic gradient descent that uses the quantum minimum finding algorithm and takes its probabilistic failure into account solves the structured prediction problem with a runtime that scales with the square root of the size of the label space, and in ...... hiện toàn bộ
Pseudo-dimension of quantum circuits
Springer Science and Business Media LLC - Tập 2 - Trang 1-14 - 2020
Matthias C. Caro, Ishaun Datta
We characterize the expressive power of quantum circuits with the pseudo-dimension, a measure of complexity for probabilistic concept classes. We prove pseudo-dimension bounds on the output probability distributions of quantum circuits; the upper bounds are polynomial in circuit depth and number of gates. Using these bounds, we exhibit a class of circuit output states out of which at least one has...... hiện toàn bộ
Robust implementation of generative modeling with parametrized quantum circuits
Springer Science and Business Media LLC - - 2021
Vicente Leyton-Ortega, Alejandro Perdomo-Ortiz, Óscar Perdomo
Behavior prediction of fiber optic temperature sensor based on hybrid classical quantum regression model
Springer Science and Business Media LLC - - 2024
T. Kanimozhi, S. Sridevi, M. Valliammai, J. Mohanraj, N. Vinodhkumar, Amirthalingam Sathasivam
In this research work, a quantum regression model (QRM) is proposed by combining an autoencoder and a dressed quantum circuit (DQC) to predict the behavior of fiber optic temperature sensors. As the experimental data gathered during our observations was limited to effectively train the proposed QRM model, we employed an autoencoder to expand the dataset. We examined the regression performance of t...... hiện toàn bộ
An evolutionary strategy for finding effective quantum 2-body Hamiltonians of p-body interacting systems
Springer Science and Business Media LLC - Tập 1 - Trang 113-122 - 2019
G. Acampora, V. Cataudella, P. R. Hegde, P. Lucignano, G. Passarelli, A. Vitiello
Embedding p-body interacting models onto the 2-body networks implemented on commercial quantum annealers is a relevant issue. For highly interacting models, requiring a number of ancilla qubits, that can be sizable and make unfeasible (if not impossible) to simulate such systems. In this manuscript, we propose an alternative to minor embedding, developing a new approximate procedure based on genet...... hiện toàn bộ
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