Related papers: Controlling quantum effects in enhanced strong-fie…

We discuss quantum interference effects in a three-level atom in lambda-configuration, where both transitions from the upper state to the lower states are driven by a single monochromatic laser field. Although the system has two lower…

Landau-Zener-Stuckelberg interferometry has been extensively investigated in quantum two-level systems, with particular interests on artificial system such as superconducting flux qubits. With increasing the driving field amplitude, more…

The many-body state of carriers confined in a quantum dot is controlled by the balance between their kinetic energy and their Coulomb correlation. In coupled quantum dots, both can be tuned by varying the inter-dot tunneling and…

Quantum interference in coherent transport through single molecular rings may provide a mechanism to control current in molecular electronics. We investigate its applicability by using a single-particle Green function method combined with…

We investigate the time-evolution of quantum entanglement between an electron, liberated by a strong few-cycle laser pulse, and its parent ion-core. Since the standard procedure is numerically prohibitive in this case, we propose a novel…

Machine learning advances chemistry and materials science by enabling large-scale exploration of chemical space based on quantum chemical calculations. While these models supply fast and accurate predictions of atomistic chemical…

Bridging quantum optics and strong-field physics provides a pathway to explore how quantum light shapes extreme nonlinear light-matter interactions. However, direct characterization of non-classical light at damage-threshold intensities…

We investigate two classes of quantum control problems by using frequency-domain optimization algorithms in the context of ultrafast laser control of quantum systems. In the first class, the system model is known and a frequency-domain…

Quantum control is concerned with active manipulation of physical and chemical processes on the atomic and molecular scale. This work presents a perspective of progress in the field of control over quantum phenomena, tracing the evolution…

We perform a systematic analysis of quantum interference in nonsequential double ionization focusing on the recollision-excitation with subsequent ionization (RESI) mechanism, employing the strong-field approximation (SFA). We find that…

Frequency control in power systems is critical to maintaining stability and preventing blackouts. Traditional methods like meta-heuristic algorithms and machine learning face limitations in real-time applicability and scalability. This…

We employ a machine learning-enabled approach to quantum state engineering based on evolutionary algorithms. In particular, we focus on superconducting platforms and consider a network of qubits -- encoded in the states of artificial atoms…

As a general trend, nanoelectronics experiments are shifting toward frequencies so high that they become comparable to the device's internal characteristic time scales, resulting in new opportunities for studying the dynamical aspects of…

In laser-driven wakefield, ionization induced injection is an efficient way to inject electrons in the plasma wave. A detailed study on the beam dynamics under the influence of beam loading effects, which can be controlled by the…

Quantum states can in a sense be thought of as generalizations of classical probability distributions, but are more powerful than probability distributions when used for computation or communication. Quantum speedup therefore requires some…

Quantum machine learning has the potential for a transformative impact across industry sectors and in particular in finance. In our work we look at the problem of hedging where deep reinforcement learning offers a powerful framework for…

We investigate two-dimensional atomic arrays as a platform to modify the electromagnetic environment of individual quantum emitters. Specifically, we demonstrate that control over emission linewidths, resonant frequency shifts, and local…

We theoretically investigate transport signatures of quantum interference in highly symmetric double quantum dots in a parallel geometry and demonstrate that extremely weak symmetry-breaking effects can have a dramatic influence on the…

This paper provides an introduction to quantum machine learning, exploring the potential benefits of using quantum computing principles and algorithms that may improve upon classical machine learning approaches. Quantum computing utilizes…

Machine learning techniques have been shown to be effective to recognize different phases of matter and produce phase diagrams in the parameter space interested, while they usually require prior labeled data to perform well. Here, we…