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To take quantum advantage of collective effects in many-body system, we design an elementary block for building multipartite quantum battery, which enables charging an atomic ensemble with optimal numbers in a common thermal bath. One achieves maximum free energy as the stored energy in the steady state, which is prior to each atom parallel charging independently. It ascribes to quantum collective effects in the ensemble of atoms induced by the competition between the coherent driving and decoherent dissipation. The corresponding thermodynamic efficiency of the energy storage is analyzed. The existence of the optimal elementary units of multipartite quantum battery provide a guideline for designing a realizable charging scheme.
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Quantum batteries are miniature energy storage devices and play a very important role in quantum thermodynamics. In recent years, quantum batteries have been extensively studied, but limited in theoretical level. Here we report the experimental realization of a quantum battery based on superconducting qubits. Our model explores dark and bright states to achieve stable and powerful charging processes, respectively. Our scheme makes use of the quantum adiabatic brachistochrone, which allows us to speed up the {battery ergotropy injection. Due to the inherent interaction of the system with its surrounding, the battery exhibits a self-discharge, which is shown to be described by a supercapacitor-like self-discharging mechanism. Our results paves the way for proposals of new superconducting circuits able to store extractable work for further usage.
Even the most sophisticated artificial neural networks are built by aggregating substantially identical units called neurons. A neuron receives multiple signals, internally combines them, and applies a non-linear function to the resulting weighted sum. Several attempts to generalize neurons to the quantum regime have been proposed, but all proposals collided with the difficulty of implementing non-linear activation functions, which is essential for classical neurons, due to the linear nature of quantum mechanics. Here we propose a solution to this roadblock in the form of a small quantum circuit that naturally simulates neurons with threshold activation. Our quantum circuit defines a building block, the quantum neuron, that can reproduce a variety of classical neural network constructions while maintaining the ability to process superpositions of inputs and preserve quantum coherence and entanglement. In the construction of feedforward networks of quantum neurons, we provide numerical evidence that the network not only can learn a function when trained with superposition of inputs and the corresponding output, but that this training suffices to learn the function on all individual inputs separately. When arranged to mimic Hopfield networks, quantum neural networks exhibit properties of associative memory. Patterns are encoded using the simple Hebbian rule for the weights and we demonstrate attractor dynamics from corrupted inputs. Finally, the fact that our quantum model closely captures (traditional) neural network dynamics implies that the vast body of literature and results on neural networks becomes directly relevant in the context of quantum machine learning.
In this paper, we investigate the effect of different optical field initial states on the performance of Tavis-Cummings(T-C) quantum battery. In solving the dynamical evolution of the system, we found a fast way to solve the Bethe ansatz equation. We find that the stored energy and the average charging power of the T-C quantum battery are closely related to the probability distribution of the optical field initial state in the number states. We define a quantity called the number state stored energy. With this prescribed quantity, we only need to know the probability distribution of the optical field initial state in the number states to obtain the stored energy and the average charging power of the T-C quantum battery at any moment. We propose an equal probability and equal expected value allocation method by which we can obtain two inequalities, and the two inequalities can be reduced to Jensens inequalities. By this method, we found the optimal initial state of the optical field. We found that the maximum stored energy and the maximum average charging power of the T-C quantum battery are proportional to the initial average photon number. The quantum battery can be fully charged when the initial average photon number is large enough. We found two novel phenomena, which can be described by two empirical inequalities. These two novel phenomena reflect the hypersensitivity of the stored energy of the T-C quantum battery to the number-state cavity field.
Large scale quantum computers will consist of many interacting qubits. In this paper we expand the two flux qubit coupling scheme first devised in [Phys. Rev. B {bf 70}, 140501 (2004)] and realized in [Science {bf 314}, 1427 (2006)] to a three-qubit, two-coupler scenario. We study L-shaped and line-shaped coupler geometries, and show how the interaction strength between qubits changes in terms of the couplers dimensions. We explore two cases: the on-state where the interaction energy between two nearest-neighbor qubits is high, and the off-state where it is turned off. In both situations we study the undesirable crosstalk with the third qubit. Finally, we use the GRAPE algorithm to find efficient pulse sequences for two-qubit gates subject to our calculated physical constraints on the coupling strength.
We study the dynamical entanglement distribution in a multipartite system. The initial state is a maximally entangled two level atom with a single photon field. Next a sequence of atoms are sent, one at the time, and interact with the field. We show that the which way information initially stored only in the field is now distributed among the parties of the global system. We obtain the corresponding complementarity relations in analytical form. We show that this dynamics may lead to a quantum eraser phenomenon provided that measurements of the probe atoms are performed in a basis which maximizes the visibility. The process may be realized in microwave cavities with present technology.
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