- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
Negative-temperature-state relaxation and reservoir-assisted quantum entanglement in double-spin-domain systems
摘要： Spin collective phenomena including superradiance are even today being intensively investigated with experimental tests performed based on state-of-the-art quantum technologies. Such attempts are not only for the simple experimental verification of predictions from the last century, but also as a motivation to explore new applications of spin collective phenomena and the coherent control of the coupling between spin ensembles and reservoirs. In this paper, we investigate the open quantum dynamics of two spin ensembles (double-spin domains) coupled to a common bosonic reservoir. We analyze in detail the dynamics of our collective state and its structure by focusing on both the symmetry and asymmetry of this coupled spin system. We find that when the spin size of one of the double domains is larger than that of the other domain, at the steady state this system exhibits two unusual collective behaviors: the negative-temperature-state relaxation in the smaller spin domain and the reservoir-assisted quantum entanglement between the two domains. These results are the consequence of the asymmetry of this system and the decoherence driven by the common reservoir.
关键词： negative-temperature-state relaxation,spin collective phenomena,bosonic reservoir,superradiance,quantum entanglement,quantum dynamics
更新于2025-09-09 09:28:46
-
Unconditional preparation of nonclassical states via linear-and-quadratic optomechanics
摘要： Reservoir engineering enables the robust and unconditional preparation of pure quantum states in noisy environments. We show how a family of nonclassical states of a mechanical oscillator can be stabilized in a cavity that is parametrically coupled to both the mechanical displacement and the displacement squared. The cavity is driven with three tones, on the red sideband, on the cavity resonance, and on the second blue sideband. The states so stabilized are (squeezed and displaced) superpositions of a finite number of phonons. They show the unique feature of encompassing two prototypes of nonclassicality for bosonic systems: by adjusting the strength of the drives, one can in fact move from a single-phonon- to a Schr?dinger-cat-like state. The scheme is deterministic, supersedes the need for measurement-and-feedback loops, and does not require initialization of the oscillator to the ground state.
关键词： mechanical oscillator,quantum states,Reservoir engineering,nonclassical states,optomechanics
更新于2025-09-09 09:28:46
-
[IEEE 2018 24th International Conference on Pattern Recognition (ICPR) - Beijing, China (2018.8.20-2018.8.24)] 2018 24th International Conference on Pattern Recognition (ICPR) - Reservoir Computing with Untrained Convolutional Neural Networks for Image Recognition
摘要： Reservoir computing has attracted much attention for its easy training process as well as its ability to deal with temporal data. A reservoir computing system consists of a reservoir part represented as a sparsely connected recurrent neural network and a readout part represented as a simple regression model. In machine learning tasks, the reservoir part is fixed and only the readout part is trained. Although reservoir computing has been mainly applied to time series prediction and recognition, it can be applied to image recognition as well by considering an image data as a sequence of pixel values. However, to achieve a high performance in image recognition with raw image data, a large-scale reservoir including a large number of neurons is required. This is a bottleneck in terms of computer memory and computational cost. To overcome this bottleneck, we propose a new method which combines reservoir computing with untrained convolutional neural networks. We use an untrained convolutional neural network to transform raw image data into a set of smaller feature maps in a preprocessing step of the reservoir computing. We demonstrate that our method achieves a high classification accuracy in an image recognition task with a much smaller number of trainable parameters compared with a previous study.
关键词： Reservoir computing,Image recognition,Untrained networks,Convolutional neural networks
更新于2025-09-09 09:28:46
-
AIP Conference Proceedings [Author(s) PROCEEDINGS OF THE 3RD INTERNATIONAL SYMPOSIUM ON CURRENT PROGRESS IN MATHEMATICS AND SCIENCES 2017 (ISCPMS2017) - Bali, Indonesia (26–27 July 2017)] - Imaging structural control of geothermal reservoir using remote sensing and gravity data analysis in Blawan-Ijen, East Java, Indonesia
摘要： Ijen Volcanic Complex is part of the Quartenary volcanic front of the Sunda Arc. The arc is a subduction system as a result of the northward subduction of the Indo-Australian plate underneath the Eurasian plate. This paper presents remote sensing data analysis and gravity data interpretation to understand the geological structure and its correlation to the geothermal system. The remote sensing analysis is performed using morphostructure approach. Furthermore, the gravity survey also had been carried out in the Ijen Volcanic Complex in 2017. A total of 72 gravity stations were measured with station spacing about 1-1.5 km. The gravity anomaly was then separated into regional and residual anomaly using the first order of TSA method. A high bouguer anomaly found in the southwest area and then continued to the northeast area. The high bouguer anomaly in the southwest area is might be associated with the existence of several volcanoes such as Mt. Mlaten, Mt. Lingker, Mt. Anyar, and Mt. Pendil. Futhermore, the low bouguer anomaly that is seen in the southeast area is probably caused by the collapse of the Mt. Kukusan. Moreover, a high residual gravity anomaly in the center of the caldera is coincided with the geological structure intersection of Kawahwurung fault, Blawan fault and Kendeng-Merapi fault.
关键词： remote sensing,Structures,East Java,Blawan-Ijen,geothermal reservoir,gravity analysis
更新于2025-09-04 15:30:14