Many quantum technologies rely on high-precision dynamics, which raises the question of how these are influenced by the experimental uncertainties that are always present in real-life settings. A standard approach in the literature to assess this is Monte Carlo sampling, which suffers from two major drawbacks. First, it is computationally expensive. Second, it does not reveal the effect that each individual uncertainty parameter has on the state of the system. In this Letter, we evade both these drawbacks by incorporating propagation of uncertainty directly into simulations of quantum dynamics, thereby obtaining a method that is orders of magnitude faster than Monte Carlo simulations and directly provides information on how each uncertainty...
The outcomes of quantum mechanical measurements are inherently random. It is therefore necessary to ...
Dissipative collective effects are ubiquitous in quantum physics and their relevance ranges from the...
We propose and analyze a sample-efficient protocol to estimate the fidelity between an experimentall...
We present a Bayesian quantum characterization framework that takes into account uncertainties from ...
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotte...
We present an exact path integral methodology for computing quantum dynamical information. This meth...
The stochastic-gauge representation is a method of mapping the equation of motion for the quantum me...
The stochastic-gauge representation is a method of mapping the equation of motion for the quantum me...
Heisenberg's uncertainty principle implies fundamental constraints on what properties of a quantum s...
This article deals with the problem of the uncertainty in rule-based systems (RBS), but from the per...
Deep learning (DL) models are extensively used to analyze small- and large-scale datasets due to the...
Dissertação de mestrado em Engenharia FísicaThe ability to efficiently determine the dynamics to whi...
© 2006 Dr. Jared Heath ColeThis thesis investigates several different aspects of the physics of few ...
Quantum computers have recently become available as noisy intermediate-scale quantum devices. Alread...
this paper, we show how the use of quantum computing can speed up some computations related to inter...
The outcomes of quantum mechanical measurements are inherently random. It is therefore necessary to ...
Dissipative collective effects are ubiquitous in quantum physics and their relevance ranges from the...
We propose and analyze a sample-efficient protocol to estimate the fidelity between an experimentall...
We present a Bayesian quantum characterization framework that takes into account uncertainties from ...
Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotte...
We present an exact path integral methodology for computing quantum dynamical information. This meth...
The stochastic-gauge representation is a method of mapping the equation of motion for the quantum me...
The stochastic-gauge representation is a method of mapping the equation of motion for the quantum me...
Heisenberg's uncertainty principle implies fundamental constraints on what properties of a quantum s...
This article deals with the problem of the uncertainty in rule-based systems (RBS), but from the per...
Deep learning (DL) models are extensively used to analyze small- and large-scale datasets due to the...
Dissertação de mestrado em Engenharia FísicaThe ability to efficiently determine the dynamics to whi...
© 2006 Dr. Jared Heath ColeThis thesis investigates several different aspects of the physics of few ...
Quantum computers have recently become available as noisy intermediate-scale quantum devices. Alread...
this paper, we show how the use of quantum computing can speed up some computations related to inter...
The outcomes of quantum mechanical measurements are inherently random. It is therefore necessary to ...
Dissipative collective effects are ubiquitous in quantum physics and their relevance ranges from the...
We propose and analyze a sample-efficient protocol to estimate the fidelity between an experimentall...