ゼロギャップ半導体Ta2NiSe5における励起子絶縁体転移

学位の種別: 課程博士審査委員会委員 : (主査)東京大学教授 髙木 英典, 東京大学教授 廣井 善二, 東京大学教授 芝内 孝禎, 東京大学准教授 溝川 貴司, 東京大学准教授 山下 穣University of Tokyo(東京大学

From Ad-Hoc to Systematic: A Strategy for Imposing General Boundary Conditions in Discretized PDEs in variational quantum algorithm

We proposed a general quantum-computing-based algorithm that harnesses the exponential power of noisy intermediate-scale quantum (NISQ) devices in solving partial differential equations (PDE). This variational quantum eigensolver (VQE)-inspired approach transcends previous idealized model demonstrations constrained by strict and simplistic boundary conditions. It enables the imposition of arbitrary boundary conditions, significantly expanding its potential and adaptability for real-world applications, achieving this "from ad-hoc to systematic" concept. We have implemented this method using the fourth-order PDE (the Euler-Bernoulli beam) as example and showcased its effectiveness with four different boundary conditions. This framework enables expectation evaluations independent of problem size, harnessing the exponentially growing state space inherent in quantum computing, resulting in exceptional scalability. This method paves the way for applying quantum computing to practical engineering applications.Comment: 16 pages, 8 figure

Calculation of Sound Insulation for Hybrid CLT Fabricated with Lumber and LVL and comparison with experimental data.

The insulated predictions were carried out for LVL, CLT and HCLT in order to evaluate their sound properties, in which the theoretical value of sound insulation was predicted by regarding the substances in wood cell wall as equivalence to specific medium based on Biot model, and the wood anatomical characteristics, such as the length and diameter of tracheid, diameter of pit, and porosity, were taken into account for determining the equivalent density and bulk modulus of elasticity of wood cell wall. By comparing the tested and predicted values of sound insulation, the conclusion were drawn as follows: the predicted values of sound insulation were significantly correlated with the tested values for LVL, CLT and HCLT. As for Masson pine and Southern pine, the adjacent of earlywood and latewood was considered as sandwich structure for the calculation of sound insulation. Meanwhile, the bonding interface was creatively introduced to improve the accuracy of sound insulation prediction. The transfer function involved in sound insulation prediction provide an effective method to characterize the sound insulation volume of wood composite in construction and decoration areas

Suppression of <i>TREX1</i> deficiency-induced cellular senescence and interferonopathies by inhibition of DNA damage response

TREX1 encodes a major DNA exonuclease and mutations of this gene are associated with type I interferonopathies in human. Mice with Trex1 deletion or mutation have shortened life spans accompanied by a senescence-associated secretory phenotype. However, the contribution of cellular senescence in TREX1 deficiency-induced type I interferonopathies remains unknown. We found that features of cellular senescence present in Trex1−/− mice are induced by multiple factors, particularly DNA damage. The cGAS-STING and DNA damage response pathways are required for maintaining TREX1 deletion-induced cellular senescence. Inhibition of the DNA damage response, such as with Checkpoint kinase 2 (CHK2) inhibitor, partially alleviated progression of type I interferonopathies and lupus-like features in the mice. These data provide insights into the initiation and development of type I interferonopathies and lupus-like diseases, and may help inform the development of targeted therapeutics

WS-Snapshot: An effective algorithm for wide-field and large-scale imaging

The Square Kilometre Array (SKA) is the largest radio interferometer under construction in the world. The high accuracy, wide-field and large size imaging significantly challenge the construction of the Science Data Processor (SDP) of SKA. We propose a hybrid imaging method based on improved W-Stacking and snapshots. The w range is reduced by fitting the snapshot $uv$ plane, thus effectively enhancing the performance of the improved W-Stacking algorithm. We present a detailed implementation of WS-Snapshot. With full-scale SKA1-LOW simulations, we present the imaging performance and imaging quality results for different parameter cases. The results show that the WS-Snapshot method enables more efficient distributed processing and significantly reduces the computational time overhead within an acceptable accuracy range, which would be crucial for subsequent SKA science studies.Comment: 10 pages, 10 figures, 6 tables, accepted by MNRA

Statistical Parameterized Physics-Based Machine Learning Digital Twin Models for Laser Powder Bed Fusion Process

A digital twin (DT) is a virtual representation of physical process, products and/or systems that requires a high-fidelity computational model for continuous update through the integration of sensor data and user input. In the context of laser powder bed fusion (LPBF) additive manufacturing, a digital twin of the manufacturing process can offer predictions for the produced parts, diagnostics for manufacturing defects, as well as control capabilities. This paper introduces a parameterized physics-based digital twin (PPB-DT) for the statistical predictions of LPBF metal additive manufacturing process. We accomplish this by creating a high-fidelity computational model that accurately represents the melt pool phenomena and subsequently calibrating and validating it through controlled experiments. In PPB-DT, a mechanistic reduced-order method-driven stochastic calibration process is introduced, which enables the statistical predictions of the melt pool geometries and the identification of defects such as lack-of-fusion porosity and surface roughness, specifically for diagnostic applications. Leveraging data derived from this physics-based model and experiments, we have trained a machine learning-based digital twin (PPB-ML-DT) model for predicting, monitoring, and controlling melt pool geometries. These proposed digital twin models can be employed for predictions, control, optimization, and quality assurance within the LPBF process, ultimately expediting product development and certification in LPBF-based metal additive manufacturing.Comment: arXiv admin note: text overlap with arXiv:2208.0290