Zobrazeno 1 - 10
of 2 956
pro vyhledávání: '"Elfving, A."'
We develop an approach for building quantum models based on the exponentially growing orthonormal basis of Hartley kernel functions. First, we design a differentiable Hartley feature map parametrized by real-valued argument that enables quantum model
Externí odkaz:
http://arxiv.org/abs/2406.03856
Autor:
Sokolov, Igor O., Both, Gert-Jan, Bochevarov, Art D., Dub, Pavel A., Levine, Daniel S., Brown, Christopher T., Acheche, Shaheen, Barkoutsos, Panagiotis Kl., Elfving, Vincent E.
Kohn-Sham Density Functional Theory (KS-DFT) provides the exact ground state energy and electron density of a molecule, contingent on the as-yet-unknown universal exchange-correlation (XC) functional. Recent research has demonstrated that neural netw
Externí odkaz:
http://arxiv.org/abs/2404.14258
Autor:
Jaderberg, Ben, Gentile, Antonio A., Ghosh, Atiyo, Elfving, Vincent E., Jones, Caitlin, Vodola, Davide, Manobianco, John, Weiss, Horst
In this work we explore how quantum scientific machine learning can be used to tackle the challenge of weather modelling. Using parameterised quantum circuits as machine learning models, we consider two paradigms: supervised learning from weather dat
Externí odkaz:
http://arxiv.org/abs/2404.08737
Autor:
Williams, Chelsea A., Gentile, Antonio A., Elfving, Vincent E., Berger, Daniel, Kyriienko, Oleksandr
We propose quantum methods for solving differential equations that are based on a gradual improvement of the solution via an iterative process, and are targeted at applications in fluid dynamics. First, we implement the Jacobi iteration on a quantum
Externí odkaz:
http://arxiv.org/abs/2404.08605
Autor:
Dalyac, Constantin, Leclerc, Lucas, Vignoli, Louis, Djellabi, Mehdi, Coelho, Wesley da Silva, Ximenez, Bruno, Dareau, Alexandre, Dreon, Davide, Elfving, VIncent E., Signoles, Adrien, Henry, Louis-Paul, Henriet, Loïc
Neutral atom technology has steadily demonstrated significant theoretical and experimental advancements, positioning itself as a front-runner platform for running quantum algorithms. One unique advantage of this technology lies in the ability to reco
Externí odkaz:
http://arxiv.org/abs/2403.11931
Autor:
Chevallier, Claire, Vovrosh, Joseph, de Hond, Julius, Dagrada, Mario, Dauphin, Alexandre, Elfving, Vincent E.
We design variational pulse sequences tailored for neutral atom quantum simulators and show that we can engineer layers of single-qubit and multi-qubit gates. As an application, we discuss how the proposed method can be used to perform refocusing alg
Externí odkaz:
http://arxiv.org/abs/2402.07653
Geometric quantum machine learning (GQML) aims to embed problem symmetries for learning efficient solving protocols. However, the question remains if (G)QML can be routinely used for constructing protocols with an exponential separation from classica
Externí odkaz:
http://arxiv.org/abs/2402.03871
Autor:
Jaderberg, Ben, Gentile, Antonio A., Berrada, Youssef Achari, Shishenina, Elvira, Elfving, Vincent E.
Parameterized quantum circuits as machine learning models are typically well described by their representation as a partial Fourier series of the input features, with frequencies uniquely determined by the feature map's generator Hamiltonians. Ordina
Externí odkaz:
http://arxiv.org/abs/2309.03279
We can learn from analyzing quantum convolutional neural networks (QCNNs) that: 1) working with quantum data can be perceived as embedding physical system parameters through a hidden feature map; 2) their high performance for quantum phase recognitio
Externí odkaz:
http://arxiv.org/abs/2308.16664
We propose a physics-informed quantum algorithm to solve nonlinear and multidimensional differential equations (DEs) in a quantum latent space. We suggest a strategy for building quantum models as state overlaps, where exponentially large sets of ind
Externí odkaz:
http://arxiv.org/abs/2308.01827