Time-reversible and norm-conserving high-order integrators for the nonlinear time-dependent Schrödinger equation: Application to local control theory

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We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potenti ...

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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 ...

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Parametric amplifiers play a crucial role in modern quantum technology by enabling the enhancement of weak signals with minimal added noise. Traditionally, Josephson junctions have been the primary choice for constructing parametric amplifiers. Nevertheles ...

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Time-domain solutions of Maxwell’s equations in homogeneous and isotropic media are paramount to studying transient or broadband phenomena. However, analytical solutions are generally unavailable for practical applications, while numerical solutions are co ...

Estimating the stress of reinforcing bars and its variations in service conditions can be useful to determine the reserve capacity of structures or to assess the risk of fatigue in the reinforcement. This paper investigates the use crack width measurements ...

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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 ...

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Driven by the need for more efficient and seamless integration of physical models and data, physics -informed neural networks (PINNs) have seen a surge of interest in recent years. However, ensuring the reliability of their convergence and accuracy remains ...

Much attention has been paid to dynamical simulation and quantum machine learning (QML) independently as applications for quantum advantage, while the possibility of using QML to enhance dynamical simulations has not been thoroughly investigated. Here we d ...

Time-reversible and norm-conserving high-order integrators for the nonlinear time-dependent Schrödinger equation: Application to local control theory

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Error estimates for SUPG-stabilised Dynamical Low Rank Approximations

High-order geometric integrators for the variational Gaussian wavepacket dynamics and application to vibronic spectra at finite temperature

From low-rank retractions to dynamical low-rank approximation and back

Adaptive projected variational quantum dynamics

Applications of the thawed Gaussian approximation to electronic spectroscopy

Quantum Error Correction and Simulation in Open Bosonic Systems

Ultra-high quantum coherent and scalable superconducting circuit optomechanics, from topological lattices to quantum storage

Room-temperature quantum optomechanics using an ultralow noise cavity

Scalable Quantum Algorithms for Noisy Quantum Computers

Three-wave-mixing quantum-limited kinetic inductance parametric amplifier operating at 6 T near 1 K

Electron-beam based nanoscale quantum controls

Quantum Protocols for ML, Physics, and Finance

The time-domain Cartesian multipole expansion of electromagnetic fields

Estimation of the bar stress based on crack width measurements in reinforced concrete structures

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

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Dual-frame optimization for informationally complete quantum measurements

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Residual-based attention in physics-informed neural networks

Dynamical simulation via quantum machine learning with provable generalization