Theory of three-pulse photon echo spectroscopy with dual frequency combs

A theoretical analysis is carried out for the recently developed three-pulse photon echo spectroscopy employing dual frequency combs (DFC) as the light sources. In this method, the molecular sample interacts with three pulse trains derived from the DFC and the generated third-order signal is displayed as a two-dimensional (2D) spectrum that depends on the waiting time introduced by employing asynchronous optical sampling method. Through the analysis of the heterodyne-detected signal interferogram using a local oscillator derived from one of the optical frequency combs, we show that the 2D spectrum closely matches the spectrum expected from a conventional approach with four pulses derived from a single femtosecond laser pulse and the waiting time between the second and third field-matter interactions is given by the down-converted detection time of the interferogram. The theoretical result is applied to a two-level model system with solvation effect described by solvatochromic spectral density. The model 2D spectrum reproduces spectral features such as the loss of frequency correlation, dephasing, and spectral shift as a function of the population time. We anticipate that the present theory will be the general framework for quantitative descriptions of DFC-based nonlinear optical spectroscopy.Comment: 20 pages, 2 figures are included in the PDF fil

Rydberg-atom graphs for quadratic unconstrained binary optimization problems

There is a growing interest in harnessing the potential of the Rydberg-atom system to address complex combinatorial optimization challenges. Here we present an experimental demonstration of how the quadratic unconstrained binary optimization (QUBO) problem can be effectively addressed using Rydberg-atom graphs. The Rydberg-atom graphs are configurations of neutral atoms organized into mathematical graphs, facilitated by programmable optical tweezers, and designed to exhibit many-body ground states that correspond to the maximum independent set (MIS) of their respective graphs. We have developed four elementary Rydberg-atom subgraph components, not only to eliminate the need of local control but also to be robust against interatomic distance errors, while serving as the building blocks sufficient for formulating generic QUBO graphs. To validate the feasibility of our approach, we have conducted a series of Rydberg-atom experiments selected to demonstrate proof-of-concept operations of these building blocks. These experiments illustrate how these components can be used to programmatically encode the QUBO problems to Rydberg-atom graphs and, by measuring their many-body ground states, how their QUBO solutions are determined subsequently.Comment: 13 pages, 6 figure

Deep Imbalanced Time-series Forecasting via Local Discrepancy Density

Time-series forecasting models often encounter abrupt changes in a given period of time which generally occur due to unexpected or unknown events. Despite their scarce occurrences in the training set, abrupt changes incur loss that significantly contributes to the total loss. Therefore, they act as noisy training samples and prevent the model from learning generalizable patterns, namely the normal states. Based on our findings, we propose a reweighting framework that down-weights the losses incurred by abrupt changes and up-weights those by normal states. For the reweighting framework, we first define a measurement termed Local Discrepancy (LD) which measures the degree of abruptness of a change in a given period of time. Since a training set is mostly composed of normal states, we then consider how frequently the temporal changes appear in the training set based on LD. Our reweighting framework is applicable to existing time-series forecasting models regardless of the architectures. Through extensive experiments on 12 time-series forecasting models over eight datasets with various in-output sequence lengths, we demonstrate that applying our reweighting framework reduces MSE by 10.1% on average and by up to 18.6% in the state-of-the-art model.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD) 202

Diffusion-EDFs: Bi-equivariant Denoising Generative Modeling on SE(3) for Visual Robotic Manipulation

Diffusion generative modeling has become a promising approach for learning robotic manipulation tasks from stochastic human demonstrations. In this paper, we present Diffusion-EDFs, a novel SE(3)-equivariant diffusion-based approach for visual robotic manipulation tasks. We show that our proposed method achieves remarkable data efficiency, requiring only 5 to 10 human demonstrations for effective end-to-end training in less than an hour. Furthermore, our benchmark experiments demonstrate that our approach has superior generalizability and robustness compared to state-of-the-art methods. Lastly, we validate our methods with real hardware experiments. Project Website: https://sites.google.com/view/diffusion-edfs/homeComment: 31 pages, 13 figure

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As remote sensing and GIS have been considered to be essential technologies for disasters information production, researches on developing methods for analyzing spatial data, and developing new technologies for such purposes, have been actively conducted. Especially, it is assumed that the use of remote sensing and GIS for disaster management will continue to develop thanks to the launch of recent satellite constellations, the use of various remote sensing platforms, the improvement of acquired data processing and storage capacity, and the advancement of artificial intelligence technology. This spatial issue presents 10 research papers regarding ship detection, building information extraction, ocean environment monitoring, flood monitoring, forest fire detection, and decision making using remote sensing and GIS technologies, which can be applied at the disaster prediction, monitoring and response stages. It is anticipated that the papers published in this special issue could be a valuable reference for developing technologies for disaster management and academic advancement of related fields. ??????????????? GIS??? ????????? ???????????? ????????? ?????? ????????? ???????????? ????????? ?????? ????????? ???????????? ??????????????? ?????? ?????? ??? ?????? ????????? ?????? ????????? ????????? ???????????? ??????. ?????? ??????????????? ????????? ????????? ???????????????????????? ??????, ????????? ????????? ?????? ??? ?????? ????????? ??????, ???????????? ????????? ?????? ????????? ?????? ?????? ????????? ????????????????????? GIS ????????? ????????? ?????? ????????? ????????? ????????? ??????. ?????? ??????????????? ????????? ??????, ?????? ????????? ?????? ???????????? ????????????, ????????? ??????, ???????????? ??????, ????????????, ????????????, ????????? ?????? ????????? ??????????????????????????? ????????? ??????????????? GIS ????????? ????????? ????????? ????????? 10?????? ????????? ???????????????. ?????? ???????????? ????????????????????? ?????? ?????? ????????? ????????? ?????? ?????? ????????? ????????? ????????? ???????????? ??? ????????? ????????????

A Cyber Command and Control Framework for Psychological Operation Using Social Media

Global threats, international terrorist groups and North Korea, paralyze political decisions by attacking and neutralizing the credibility of the main policy makers in the state and simultaneously manipulate the public opinion, which results in distrust and disconnection between each other. These threats use social media as their biggest core routine to conduct such attacks. This paper presents a series of processes and frameworks on how a commander should make a decision when performing a cyber psychological operation using social media. Based on the Endsley model, which is a situational awareness model, the paper compares the strengths and weaknesses of the three social media operations (IGMO, DeSMO, OSMO) performed by the military and proposes a guideline for performing an operation

Controllable deposition of organic metal halide perovskite films with wafer-scale uniformity by single source flash evaporation

Conventional solution-processing techniques such as the spin-coating method have been used successfully to reveal excellent properties of organic-inorganic halide perovskites (OHPs) for optoelectronic devices such as solar cell and light-emitting diode, but it is essential to explore other deposition techniques compatible with large-scale production. Single-source flash evaporation technique, in which a single source of materials of interest is rapidly heated to be deposited in a few seconds, is one of the candidate techniques for large-scale thin film deposition of OHPs. In this work, we investigated the reliability and controllability of the single-source flash evaporation technique for methylammonium lead iodide (MAPbI(3)) perovskite. In-depth statistical analysis was employed to demonstrate that the MAPbI(3) films prepared via the flash evaporation have an ultrasmooth surface and uniform thickness throughout the 4-inch wafer scale. We also show that the thickness and grain size of the MAPbI(3) film can be controlled by adjusting the amount of the source and number of deposition steps. Finally, the excellent large-area uniformity of the physical properties of the deposited thin films can be transferred to the uniformity in the device performance of MAPbI(3) photodetectors prepared by flash evaporation which exhibited the responsivity of 0.2 A/W and detectivity of 3.82x10(11) Jones.

Blocking CHOP-dependent TXNIP shuttling to mitochondria attenuates albuminuria and mitigates kidney injury in nephrotic syndrome

Albuminuria is a hallmark of glomerular disease of various etiologies. It is not only a symptom of glomerular disease but also a cause leading to glomerulosclerosis, interstitial fibrosis, and eventually, a decline in kidney function. The molecular mechanism underlying albuminuria-induced kidney injury remains poorly defined. In our genetic model of nephrotic syndrome (NS), we have identified CHOP (C/EBP homologous protein)-TXNIP (thioredoxin-interacting protein) as critical molecular linkers between albuminuria-induced ER dysfunction and mitochondria dyshomeostasis. TXNIP is a ubiquitously expressed redox protein that binds to and inhibits antioxidant enzyme, cytosolic thioredoxin 1 (Trx1), and mitochondrial Trx2. However, very little is known about the regulation and function of TXNIP in NS. By utilizin

Investigation of the mechanism of the anomalous Hall effects in Cr2Te3/(BiSb)2(TeSe)3 heterostructure

The interplay between ferromagnetism and the non-trivial topology has unveiled intriguing phases in the transport of charges and spins. For example, it is consistently observed the so-called topological Hall effect (THE) featuring a hump structure in the curve of the Hall resistance (Rxy) vs. a magnetic field (H) of a heterostructure consisting of a ferromagnet (FM) and a topological insulator (TI). The origin of the hump structure is still controversial between the topological Hall effect model and the multi-component anomalous Hall effect (AHE) model. In this work, we have investigated a heterostructure consisting of BixSb2-xTeySe3-y (BSTS) and Cr2Te3 (CT), which are well-known TI and two-dimensional FM, respectively. By using the so-called minor-loop measurement, we have found that the hump structure observed in the CT/BSTS is more likely to originate from two AHE channels. Moreover, by analyzing the scaling behavior of each amplitude of two AHE with the longitudinal resistivities of CT and BSTS, we have found that one AHE is attributed to the extrinsic contribution of CT while the other is due to the intrinsic contribution of BSTS. It implies that the proximity-induced ferromagnetic layer inside BSTS serves as a source of the intrinsic AHE, resulting in the hump structure explained by the two AHE model