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Unbiasing time-dependent Variational Monte Carlo by projected quantum evolution

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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 protoco ...

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

Scalable Quantum Algorithms for Noisy Quantum Computers

Julien Sebastian Gacon

Quantum computing not only holds the potential to solve long-standing problems in quantum physics, but also to offer speed-ups across a broad spectrum of other fields. Access to a computational space that incorporates quantum effects, such as superposition ...

EPFL2024

Adaptive projected variational quantum dynamics

Giuseppe Carleo, Stefano Barison, David Linteau

We propose an adaptive quantum algorithm to prepare accurate variational time evolved wave functions. The method is based on the projected variational quantum dynamics (pVQD) algorithm, that performs a global optimization with linear scaling in the number ...

Amer Physical Soc2024

Quantum Error Correction and Simulation in Open Bosonic Systems

David Schlegel

Quantum computers have the potential to surpass conventional computing, but they are hindered by noise which induces errors that ultimately lead to the loss of quantum information. This necessitates the development of quantum error correction strategies fo ...

EPFL2024

Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...

Amer Physical Soc2024

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Simulating the dynamics of large quantum systems is a formidable yet vital pursuit for obtaining a deeper understanding of quantum mechanical phenomena. While quantum computers hold great promise for speeding up such simulations, their practical applicatio ...

Verein Forderung Open Access Publizierens Quantenwissenschaf2024

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 ...

Wien2024

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 process tomography with unsupervised learning and tensor networks

Giuseppe Carleo

The impressive pace of advance of quantum technology calls for robust and scalable techniques for the characterization and validation of quantum hardware. Quantum process tomography, the reconstruction of an unknown quantum channel from measurement data, r ...

NATURE PORTFOLIO2023