Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems

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Room-Temperature Quantum Optomechanics and Free-Electron Quantum Optics

Guanhao Huang

Quantum optics studies how photons interact with other forms of matter, the understanding of which was crucial for the development of quantum mechanics as a whole. Starting from the photoelectric effect, the quantum property of light has led to the develop ...

EPFL2024

Empirical Sample Complexity of Neural Network Mixed State Reconstruction

Giuseppe Carleo, Filippo Vicentini, Haimeng Zhao

Quantum state reconstruction using Neural Quantum States has been proposed as a viable tool to reduce quantum shot complexity in practical applications, and its advantage over competing techniques has been shown in numerical experiments focusing mainly on ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2024

Quantum Protocols for ML, Physics, and Finance

Grzegorz Adam Gluch

In this thesis, we give new protocols that offer a quantum advantage for problems in ML, Physics, and Finance. Quantum mechanics gives predictions that are inconsistent with local realism. The experiment proving this fact (Bell, 1964) gives a quantum proto ...

EPFL2024

Dual-frame optimization for informationally complete quantum measurements

Ivano Tavernelli

Randomized measurement protocols such as classical shadows represent powerful resources for quantum technologies, with applications ranging from quantum state characterization and process tomography to machine learning and error mitigation. Recently, the n ...

2024

Secure and Efficient Cryptographic Algorithms in a Quantum World

Loïs Evan Huguenin-Dumittan

Since the advent of internet and mass communication, two public-key cryptographic algorithms have shared the monopoly of data encryption and authentication: Diffie-Hellman and RSA. However, in the last few years, progress made in quantum physics -- and mo ...

EPFL2024

A graph convolutional autoencoder approach to model order reduction for parametrized PDEs

Jan Sickmann Hesthaven, Federico Pichi

The present work proposes a framework for nonlinear model order reduction based on a Graph Convolutional Autoencoder (GCA-ROM). In the reduced order modeling (ROM) context, one is interested in obtaining real -time and many-query evaluations of parametric ...

Academic Press Inc Elsevier Science2024

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Volkan Cevher, Grigorios Chrysos, Fanghui Liu

Despite the widespread empirical success of ResNet, the generalization properties of deep ResNet are rarely explored beyond the lazy training regime. In this work, we investigate scaled ResNet in the limit of infinitely deep and wide neural networks, of wh ...

2024

Room-temperature quantum optomechanics using an ultralow noise cavity

Tobias Kippenberg, Alberto Beccari, Nils Johan Engelsen, Guanhao Huang

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Nature Portfolio2024

Investigation of room-temperature single-photon emitters in GaN-based materials and GaN/AlN quantum dots

Johann Nicolaï Stachurski

Over the past decade, quantum photonics platforms aiming at harnessing the fundamental properties of single particles, such as quantum superposition and quantum entanglement, have flourished. In this context, single-photon emitters capable of operating at ...

EPFL2024

The complexity of quantum support vector machines

Gian Florin Gentinetta, Stefan Woerner

Quantum support vector machines employ quantum circuits to define the kernel function. It has been shown that this approach offers a provable exponential speedup compared to any known classical algorithm for certain data sets. The training of such models c ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2024

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