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Quantum state discrimination is an important problem in many information processing tasks. In this work we are concerned with finding its best possible sample complexity when the states are preprocessed by a quantum channel that is required to be loc
Externí odkaz:
http://arxiv.org/abs/2406.18658
Quantum systems typically reach thermal equilibrium rather quickly when coupled to a thermal environment. The usual way of bounding the speed of this process is by estimating the spectral gap of the dissipative generator. However the gap, by itself,
Externí odkaz:
http://arxiv.org/abs/2404.16780
The preparation of thermal states of matter is a crucial task in quantum simulation. In this work, we prove that a recently introduced, efficiently implementable dissipative evolution thermalizes to the Gibbs state in time scaling polynomially with s
Externí odkaz:
http://arxiv.org/abs/2403.12691
We show that marginals of blocks of $t$ systems of any finitely correlated translation invariant state on a chain can be learned, in trace distance, with $O(t^2)$ copies -- with an explicit dependence on local dimension, memory dimension and spectral
Externí odkaz:
http://arxiv.org/abs/2312.07516
The combination of quantum many-body and machine learning techniques has recently proved to be a fertile ground for new developments in quantum computing. Several works have shown that it is possible to classically efficiently predict the expectation
Externí odkaz:
http://arxiv.org/abs/2311.07506
Autor:
Caro, Matthias, Gur, Tom, Rouzé, Cambyse, França, Daniel Stilck, Subramanian, Sathyawageeswar
Learning tasks play an increasingly prominent role in quantum information and computation. They range from fundamental problems such as state discrimination and metrology over the framework of quantum probably approximately correct (PAC) learning, to
Externí odkaz:
http://arxiv.org/abs/2311.05529
Autor:
König, Robert, Rouzé, Cambyse
Local update recovery seeks to maintain quantum information by applying local correction maps alternating with and compensating for the action of noise. Motivated by recent constructions based on quantum LDPC codes in the finite-dimensional setting,
Externí odkaz:
http://arxiv.org/abs/2309.16241
Reliable quantum technology requires knowledge of the dynamics governing the underlying system. This problem of characterizing and benchmarking quantum devices or experiments in continuous time is referred to as the Hamiltonian learning problem. In c
Externí odkaz:
http://arxiv.org/abs/2307.15026
The exponential convergence to invariant subspaces of quantum Markov semigroups plays a crucial role in quantum information theory. One such example is in bosonic error correction schemes, where dissipation is used to drive states back to the code-sp
Externí odkaz:
http://arxiv.org/abs/2307.13801
Autor:
Rouzé, Cambyse, França, Daniel Stilck
The unavoidable presence of noise is a crucial roadblock for the development of large-scale quantum computers and the ability to characterize quantum noise reliably and efficiently with high precision is essential to scale quantum technologies furthe
Externí odkaz:
http://arxiv.org/abs/2307.02959