Showing 1–50 of 105 results for author: Maeno, T

Accuracy Improvement of Semi-Supervised Segmentation Using Supervised ClassMix and Sup-Unsup Feature Discriminator

Authors: Takahiro Mano, Reiji Saito, Kazuhiro Hotta

Abstract: In semantic segmentation, the creation of pixel-level labels for training data incurs significant costs. To address this problem, semi-supervised learning, which utilizes a small number of labeled images alongside unlabeled images to enhance the performance, has gained attention. A conventional semi-supervised learning method, ClassMix, pastes class labels predicted from unlabeled images onto othe… ▽ More In semantic segmentation, the creation of pixel-level labels for training data incurs significant costs. To address this problem, semi-supervised learning, which utilizes a small number of labeled images alongside unlabeled images to enhance the performance, has gained attention. A conventional semi-supervised learning method, ClassMix, pastes class labels predicted from unlabeled images onto other images. However, since ClassMix performs operations using pseudo-labels obtained from unlabeled images, there is a risk of handling inaccurate labels. Additionally, there is a gap in data quality between labeled and unlabeled images, which can impact the feature maps. This study addresses these two issues. First, we propose a method where class labels from labeled images, along with the corresponding image regions, are pasted onto unlabeled images and their pseudo-labeled images. Second, we introduce a method that trains the model to make predictions on unlabeled images more similar to those on labeled images. Experiments on the Chase and COVID-19 datasets demonstrated an average improvement of 2.07% in mIoU compared to conventional semi-supervised learning methods. △ Less

Submitted 8 April, 2026; originally announced April 2026.

Scalable AI-assisted Workflow Management for Detector Design Optimization Using Distributed Computing

Authors: Derek Anderson, Amit Bashyal, Markus Diefenthaler, Cristiano Fanelli, Wen Guan, Tanja Horn, Alex Jentsch Meifeng Lin, Tadashi Maeno, Kei Nagai, Hemalata Nayak, Connor Pecar, Karthik Suresh, Fang-Ying Tsai, Anselm Vossen, Tianle Wang, Torre Wenaus

Abstract: The Production and Distributed Analysis (PanDA) system, originally developed for the ATLAS experiment at the CERN Large Hadron Collider (LHC), has evolved into a robust platform for orchestrating large-scale workflows across distributed computing resources. Coupled with its intelligent Distributed Dispatch and Scheduling (iDDS) component, PanDA supports AI/ML-driven workflows through a scalable an… ▽ More The Production and Distributed Analysis (PanDA) system, originally developed for the ATLAS experiment at the CERN Large Hadron Collider (LHC), has evolved into a robust platform for orchestrating large-scale workflows across distributed computing resources. Coupled with its intelligent Distributed Dispatch and Scheduling (iDDS) component, PanDA supports AI/ML-driven workflows through a scalable and flexible workflow engine. We present an AI-assisted framework for detector design optimization that integrates multi-objective Bayesian optimization with the PanDA--iDDS workflow engine to coordinate iterative simulations across heterogeneous resources. The framework addresses the challenge of exploring high-dimensional parameter spaces inherent in modern detector design. We demonstrate the framework using benchmark problems and realistic studies of the ePIC and dRICH detectors for the Electron-Ion Collider (EIC). Results show improved automation, scalability, and efficiency in multi-objective optimization. This work establishes a flexible and extensible paradigm for AI-driven detector design and other computationally intensive scientific applications. △ Less

Submitted 31 March, 2026; originally announced March 2026.

Spatiotemporal imaging of gate-controlled multipath dynamics of fractional quantum Hall edge excitations

Authors: Yunhyeon Jeong, Akinori Kamiyama, John N. Moore, Takaaki Mano, Ken-ichi Sasaki, Yuuki Sugiyama, Tokiro Numasawa, Masahiro Hotta, Go Yusa

Abstract: Quantum Hall edge excitations, whose low-energy behavior admits a chiral conformal-field-theory description, are a promising platform for engineered dynamical experiments, including analog-spacetime proposals. However, establishing their edge dynamics in realistic electrostatic landscapes is essential for controlled dynamical experiments and has remained experimentally challenging. Here we report… ▽ More Quantum Hall edge excitations, whose low-energy behavior admits a chiral conformal-field-theory description, are a promising platform for engineered dynamical experiments, including analog-spacetime proposals. However, establishing their edge dynamics in realistic electrostatic landscapes is essential for controlled dynamical experiments and has remained experimentally challenging. Here we report spatiotemporal imaging of gate-controlled multipath dynamics of edge excitations in a $ν= 1/3$ fractional quantum Hall device using stroboscopic time-resolved photoluminescence microscopy and spectroscopy with $\sim$100-ps resolution. By tuning a control-gate-defined potential landscape, we observe switching between mesa-defined and gate-defined trajectories and identify an intermediate regime in which a single launched excitation accesses multiple pathways. Time-resolved measurements at downstream locations reveal gate-dependent arrival times and pronounced temporal broadening, showing that the propagation dynamics are strongly modified by the local confinement and become increasingly dispersive in a multipath landscape. We further observe a long-range transverse optical response extending tens of micrometers into the bulk and persisting over distances exceeding 200 $μ$m downstream, consistent with the near-field component of an edge magnetoplasmon. These results establish direct experimental access to controllable multipath edge dynamics in the fractional quantum Hall regime and suggest a platform for engineered nonequilibrium and interference-based experiments, as well as future analog-spacetime studies in quantum Hall edge systems. △ Less

Submitted 31 March, 2026; originally announced March 2026.

Leveraging Digital Twin Technologies: All-Photonics Networks-as-a-Service for Data Center Xchange in the Era of AI [Invited Tutorial]

Authors: Hideki Nishizawa, Kazuya Anazawa, Tetsuro Inui, Toru Mano, Takeo Sasai, Giacomo Borraccini, Tatsuya Matsumura, Hiroyuki Ishihara, Sae Kojima, Yoshiaki Sone, Koichi Takasugi

Abstract: This paper presents a data center exchange (Data Center Xchange, DCX) architecture for all-photonics networks-as-a-service in distributed data center infrastructures, enabling the creation of a virtual large-scale data center by directly interconnecting distributed data centers in metropolitan areas. Key requirements for such an architecture are identified: support for low-latency operations, scal… ▽ More This paper presents a data center exchange (Data Center Xchange, DCX) architecture for all-photonics networks-as-a-service in distributed data center infrastructures, enabling the creation of a virtual large-scale data center by directly interconnecting distributed data centers in metropolitan areas. Key requirements for such an architecture are identified: support for low-latency operations, scalability, reliability, and flexibility within a single network architecture; the ability to add new operator-driven automation functionalities based on an open networking approach; and the ability to control and manage remotely deployed transponders connected via access links with unknown physical parameters. We propose a set of technologies that enable digital twin operations for optical networks, including a cloud-native architecture for coherent transceivers, remote transponder control, fast end-to-end optical path provisioning, transceiver-based physical-parameter estimation incorporating digital longitudinal monitoring, and optical line system calibration, demonstrating their feasibility through field validations. △ Less

Submitted 15 January, 2026; originally announced January 2026.

Optical Network Digital Twin -- Commercialization Barriers, Value Proposition, Early Use Cases, and Challenges

Authors: Hideki Nishizawa, Toru Mano, Kazuya Anazawa, Tatsuya Matsumura, Takeo Sasai, Masatoshi Namiki, Dmitrii Briantcev, Renato Ambrosone, Esther Le Rouzic, Stefan Melin, Oscar Gonzalez-de-Dios, Juan Pedro Fernandez-Palacios, Xiaocheng Zhang, Keigo Akahoshi, Gert Grammel, Andrea D'Amico, Giacomo Borraccini, Marco Ruffini, Daniel Kilper, Vittorio Curri

Abstract: With the widespread adoption of AI, machine-to-machine communications are rapidly increasing, reshaping the requirements for optical networks. Recent advances in Gaussian noise modeling for digital coherent transmission have raised expectations for digital-twin-based operation. However, unlike digital twins in wireless communication, which are already well established, significant barriers remain… ▽ More With the widespread adoption of AI, machine-to-machine communications are rapidly increasing, reshaping the requirements for optical networks. Recent advances in Gaussian noise modeling for digital coherent transmission have raised expectations for digital-twin-based operation. However, unlike digital twins in wireless communication, which are already well established, significant barriers remain for commercialization in optical networks. This paper discusses the evolving requirements of optical networks in the AI era and proposes an Optical Network Digital Twin architecture that enables flexible end-to-end light path operation beyond conventional management. The value propositions of the proposed architecture, its evolutionary steps toward commercialization, and key research challenges for practical deployment are presented. △ Less

Submitted 9 November, 2025; originally announced November 2025.

Comments: 7 pages, 5 figures

iDDS: Intelligent Distributed Dispatch and Scheduling for Workflow Orchestration

Authors: Wen Guan, Tadashi Maeno, Aleksandr Alekseev, Fernando Harald Barreiro Megino, Kaushik De, Edward Karavakis, Alexei Klimentov, Tatiana Korchuganova, FaHui Lin, Paul Nilsson, Torre Wenaus, Zhaoyu Yang, Xin Zhao

Abstract: The intelligent Distributed Dispatch and Scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for… ▽ More The intelligent Distributed Dispatch and Scheduling (iDDS) service is a versatile workflow orchestration system designed for large-scale, distributed scientific computing. iDDS extends traditional workload and data management by integrating data-aware execution, conditional logic, and programmable workflows, enabling automation of complex and dynamic processing pipelines. Originally developed for the ATLAS experiment at the Large Hadron Collider, iDDS has evolved into an experiment-agnostic platform that supports both template-driven workflows and a Function-as-a-Task model for Python-based orchestration. This paper presents the architecture and core components of iDDS, highlighting its scalability, modular message-driven design, and integration with systems such as PanDA and Rucio. We demonstrate its versatility through real-world use cases: fine-grained tape resource optimization for ATLAS, orchestration of large Directed Acyclic Graph (DAG) workflows for the Rubin Observatory, distributed hyperparameter optimization for machine learning applications, active learning for physics analyses, and AI-assisted detector design at the Electron-Ion Collider. By unifying workload scheduling, data movement, and adaptive decision-making, iDDS reduces operational overhead and enables reproducible, high-throughput workflows across heterogeneous infrastructures. We conclude with current challenges and future directions, including interactive, cloud-native, and serverless workflow support. △ Less

Submitted 19 December, 2025; v1 submitted 3 October, 2025; originally announced October 2025.

Data Management System Analysis for Distributed Computing Workloads

Authors: Kuan-Chieh Hsu, Sairam Sri Vatsavai, Ozgur O. Kilic, Tatiana Korchuganova, Paul Nilsson, Sankha Dutta, Yihui Ren, David K. Park, Joseph Boudreau, Tasnuva Chowdhury, Shengyu Feng, Raees Khan, Jaehyung Kim, Scott Klasky, Tadashi Maeno, Verena Ingrid Martinez Outschoorn, Norbert Podhorszki, Frédéric Suter, Wei Yang, Yiming Yang, Shinjae Yoo, Alexei Klimentov, Adolfy Hoisie

Abstract: Large-scale international collaborations such as ATLAS rely on globally distributed workflows and data management to process, move, and store vast volumes of data. ATLAS's Production and Distributed Analysis (PanDA) workflow system and the Rucio data management system are each highly optimized for their respective design goals. However, operating them together at global scale exposes systemic inef… ▽ More Large-scale international collaborations such as ATLAS rely on globally distributed workflows and data management to process, move, and store vast volumes of data. ATLAS's Production and Distributed Analysis (PanDA) workflow system and the Rucio data management system are each highly optimized for their respective design goals. However, operating them together at global scale exposes systemic inefficiencies, including underutilized resources, redundant or unnecessary transfers, and altered error distributions. Moreover, PanDA and Rucio currently lack shared performance awareness and coordinated, adaptive strategies. This work charts a path toward co-optimizing the two systems by diagnosing data-management pitfalls and prioritizing end-to-end improvements. With the observation of spatially and temporally imbalanced transfer activities, we develop a metadata-matching algorithm that links PanDA jobs and Rucio datasets at the file level, yielding a complete, fine-grained view of data access and movement. Using this linkage, we identify anomalous transfer patterns that violate PanDA's data-centric job-allocation principle. We then outline mitigation strategies for these patterns and highlight opportunities for tighter PanDA-Rucio coordination to improve resource utilization, reduce unnecessary data movement, and enhance overall system resilience. △ Less

Submitted 1 October, 2025; originally announced October 2025.

Comments: 10 pages, 12 figures, to be presented in SC25 DRBSD Workshop

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Authors: Sairam Sri Vatsavai, Raees Khan, Kuan-Chieh Hsu, Ozgur O. Kilic, Paul Nilsson, Tatiana Korchuganova, David K. Park, Sankha Dutta, Yihui Ren, Joseph Boudreau, Tasnuva Chowdhury, Shengyu Feng, Jaehyung Kim, Scott Klasky, Tadashi Maeno, Verena Ingrid Martinez, Norbert Podhorszki, Frédéric Suter, Wei Yang, Yiming Yang, Shinjae Yoo, Alexei Klimentov, Adolfy Hoisie

Abstract: Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for mo… ▽ More Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim's capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6x better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware. △ Less

Submitted 1 October, 2025; originally announced October 2025.

Comments: The paper has been accepted at PMBS workshop SC25

Beyond Redundancy: Toward Agile Resilience in Optical Networks to Overcome Unpredictable Disasters

Authors: Toru Mano, Hideki Nishizawa, Takeo Sasai, Soichiroh Usui, Dmitrii Briantcev, Devika Dass, Brandt Bashaw, Eoin Kenny, Marco Ruffini, Yoshiaki Sone, Koichi Takasugi, Daniel Kilper

Abstract: Resilience in optical networks has traditionally relied on redundancy and pre-planned recovery strategies, both of which assume a certain level of disaster predictability. However, recent environmental changes such as climate shifts, the evolution of communication services, and rising geopolitical risks have increased the unpredictability of disasters, reducing the effectiveness of conventional re… ▽ More Resilience in optical networks has traditionally relied on redundancy and pre-planned recovery strategies, both of which assume a certain level of disaster predictability. However, recent environmental changes such as climate shifts, the evolution of communication services, and rising geopolitical risks have increased the unpredictability of disasters, reducing the effectiveness of conventional resilience approaches. To address this unpredictability, this paper introduces the concept of agile resilience, which emphasizes dynamic adaptability across multiple operators and layers. We identify key requirements and challenges, and present enabling technologies for the realization of agile resilience. Using a field-deployed transmission system, we demonstrate rapid system characterization, optical path provisioning, and database migration within six hours. These results validate the effectiveness of the proposed enabling technologies and confirm the feasibility of agile resilience. △ Less

Submitted 4 January, 2026; v1 submitted 28 September, 2025; originally announced September 2025.

Machine Learning-Driven Predictive Resource Management in Complex Science Workflows

Authors: Tasnuva Chowdhury, Tadashi Maeno, Fatih Furkan Akman, Joseph Boudreau, Sankha Dutta, Shengyu Feng, Adolfy Hoisie, Kuan-Chieh Hsu, Raees Khan, Jaehyung Kim, Ozgur O. Kilic, Scott Klasky, Alexei Klimentov, Tatiana Korchuganova, Verena Ingrid Martinez Outschoorn, Paul Nilsson, David K. Park, Norbert Podhorszki, Yihui Ren, John Rembrandt Steele, Frédéric Suter, Sairam Sri Vatsavai, Torre Wenaus, Wei Yang, Yiming Yang , et al. (1 additional authors not shown)

Abstract: The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource re… ▽ More The collaborative efforts of large communities in science experiments, often comprising thousands of global members, reflect a monumental commitment to exploration and discovery. Recently, advanced and complex data processing has gained increasing importance in science experiments. Data processing workflows typically consist of multiple intricate steps, and the precise specification of resource requirements is crucial for each step to allocate optimal resources for effective processing. Estimating resource requirements in advance is challenging due to a wide range of analysis scenarios, varying skill levels among community members, and the continuously increasing spectrum of computing options. One practical approach to mitigate these challenges involves initially processing a subset of each step to measure precise resource utilization from actual processing profiles before completing the entire step. While this two-staged approach enables processing on optimal resources for most of the workflow, it has drawbacks such as initial inaccuracies leading to potential failures and suboptimal resource usage, along with overhead from waiting for initial processing completion, which is critical for fast-turnaround analyses. In this context, our study introduces a novel pipeline of machine learning models within a comprehensive workflow management system, the Production and Distributed Analysis (PanDA) system. These models employ advanced machine learning techniques to predict key resource requirements, overcoming challenges posed by limited upfront knowledge of characteristics at each step. Accurate forecasts of resource requirements enable informed and proactive decision-making in workflow management, enhancing the efficiency of handling diverse, complex workflows across heterogeneous resources. △ Less

Submitted 19 December, 2025; v1 submitted 14 September, 2025; originally announced September 2025.

MSC Class: 68T05; 68M14; 68W10

Towards an Introspective Dynamic Model of Globally Distributed Computing Infrastructures

Authors: Ozgur O. Kilic, David K. Park, Yihui Ren, Tatiana Korchuganova, Sairam Sri Vatsavai, Joseph Boudreau, Tasnuva Chowdhury, Shengyu Feng, Raees Khan, Jaehyung Kim, Scott Klasky, Tadashi Maeno, Paul Nilsson, Verena Ingrid Martinez Outschoorn, Norbert Podhorszki, Frédéric Suter, Wei Yang, Yiming Yang, Shinjae Yoo, Alexei Klimentov, Adolfy Hoisie

Abstract: Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived… ▽ More Large-scale scientific collaborations like ATLAS, Belle II, CMS, DUNE, and others involve hundreds of research institutes and thousands of researchers spread across the globe. These experiments generate petabytes of data, with volumes soon expected to reach exabytes. Consequently, there is a growing need for computation, including structured data processing from raw data to consumer-ready derived data, extensive Monte Carlo simulation campaigns, and a wide range of end-user analysis. To manage these computational and storage demands, centralized workflow and data management systems are implemented. However, decisions regarding data placement and payload allocation are often made disjointly and via heuristic means. A significant obstacle in adopting more effective heuristic or AI-driven solutions is the absence of a quick and reliable introspective dynamic model to evaluate and refine alternative approaches. In this study, we aim to develop such an interactive system using real-world data. By examining job execution records from the PanDA workflow management system, we have pinpointed key performance indicators such as queuing time, error rate, and the extent of remote data access. The dataset includes five months of activity. Additionally, we are creating a generative AI model to simulate time series of payloads, which incorporate visible features like category, event count, and submitting group, as well as hidden features like the total computational load-derived from existing PanDA records and computing site capabilities. These hidden features, which are not visible to job allocators, whether heuristic or AI-driven, influence factors such as queuing times and data movement. △ Less

Submitted 24 June, 2025; originally announced June 2025.

Journal ref: CHEP 2024, EPJ Web of Conferences (EPJ WoC)

Electrically induced bulk and edge excitations in the fractional quantum Hall regime

Authors: Quentin France, Yunhyeon Jeong, Akinori Kamiyama, Takaaki Mano, Ken-ichi Sasaki, Masahiro Hotta, Go Yusa

Abstract: We apply a voltage pulse to electrically excite the incompressible region of a two-dimensional electron liquid in the $ν=2/3$ fractional quantum Hall state and investigate the collective excitations in both the edge and bulk via photoluminescence spectral energy shifts. Introducing an offset in the voltage pulse significantly enhances the excitation signal. Real-space and time-resolved measurement… ▽ More We apply a voltage pulse to electrically excite the incompressible region of a two-dimensional electron liquid in the $ν=2/3$ fractional quantum Hall state and investigate the collective excitations in both the edge and bulk via photoluminescence spectral energy shifts. Introducing an offset in the voltage pulse significantly enhances the excitation signal. Real-space and time-resolved measurements reveal the dynamics of the bulk excitations, with an estimated group velocity of approximately $3 \times 10^4$ m/s. These bulk excitations align well with the magneto-plasmon model. Our results highlight the topological link between edge and bulk states, providing a novel approach to exploring solid-state analogs of quantum gravity. △ Less

Submitted 2 February, 2025; originally announced February 2025.

Alternative Mixed Integer Linear Programming Optimization for Joint Job Scheduling and Data Allocation in Grid Computing

Authors: Shengyu Feng, Jaehyung Kim, Yiming Yang, Joseph Boudreau, Tasnuva Chowdhury, Adolfy Hoisie, Raees Khan, Ozgur O. Kilic, Scott Klasky, Tatiana Korchuganova, Paul Nilsson, Verena Ingrid Martinez Outschoorn, David K. Park, Norbert Podhorszki, Yihui Ren, Frederic Suter, Sairam Sri Vatsavai, Wei Yang, Shinjae Yoo, Tadashi Maeno, Alexei Klimentov

Abstract: This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (… ▽ More This paper presents a novel approach to the joint optimization of job scheduling and data allocation in grid computing environments. We formulate this joint optimization problem as a mixed integer quadratically constrained program. To tackle the nonlinearity in the constraint, we alternatively fix a subset of decision variables and optimize the remaining ones via Mixed Integer Linear Programming (MILP). We solve the MILP problem at each iteration via an off-the-shelf MILP solver. Our experimental results show that our method significantly outperforms existing heuristic methods, employing either independent optimization or joint optimization strategies. We have also verified the generalization ability of our method over grid environments with various sizes and its high robustness to the algorithm hyper-parameters. △ Less

Submitted 31 January, 2025; originally announced February 2025.

Experimental Evaluation of an SDN Controller for Open Optical-circuit-switched Networks

Authors: Kazuya Anazawa, Takeru Inoue, Toru Mano, Hiroshi Ou, Hirotaka Ujikawa, Dmitrii Briantcev, Sumaiya Binte Ali, Devika Dass, Hideki Nishizawa, Yoshiaki Sone, Eoin Kenny, Marco Ruffini, Daniel Kilper, Eiji Oki, Koichi Takasugi

Abstract: Open optical networks have been considered to be important for cost-effectively building and operating the networks. Recently, the optical-circuit-switches (OCSes) have attracted industry and academia because of their cost efficiency and higher capacity than traditional electrical packet switches (EPSes) and reconfigurable optical add drop multiplexers (ROADMs). Though the open interfaces and cont… ▽ More Open optical networks have been considered to be important for cost-effectively building and operating the networks. Recently, the optical-circuit-switches (OCSes) have attracted industry and academia because of their cost efficiency and higher capacity than traditional electrical packet switches (EPSes) and reconfigurable optical add drop multiplexers (ROADMs). Though the open interfaces and control planes for traditional ROADMs and transponders have been defined by several standard-defining organizations (SDOs), those of OCSes have not. Considering that several OCSes have already been installed in production datacenter networks (DCNs) and several OCS products are on the market, bringing the openness and interoperability into the OCS-based networks has become important. Motivated by this fact, this paper investigates a software-defined networking (SDN) controller for open optical-circuit-switched networks. To this end, we identified the use cases of OCSes and derived the controller requirements for supporting them. We then proposed a multi-vendor (MV) OCS controller framework that satisfies the derived requirements; it was designed to quickly and consistently operate fiber paths upon receiving the operation requests. We validated our controller by implementing it and evaluating its performance on actual MV-OCS networks. It satisfied all the requirements, and fiber paths could be configured within 1.0 second by using our controller. △ Less

Submitted 29 April, 2025; v1 submitted 28 January, 2025; originally announced January 2025.

Journal ref: IEEE/Optica Journal of Optical Communications and Networking 2025

Enhancing Spin Diffusion in GaAs Quantum Wells: The Role of Electron Density and Channel Width

Authors: B. W. Grobecker, A. V. Poshakinskiy, S. Anghel, T. Mano, G. Yusa, M. Betz

Abstract: This study explores the relationship between spin diffusion, spin lifetime, electron density and lateral spatial confinement in two-dimensional electron gases hosted in GaAs quantum wells. Using time-resolved magneto-optical Kerr effect microscopy, we analyze how Hall-bar channel width and back-gate voltage modulation influence spin dynamics. The results reveal that the spin diffusion coefficient… ▽ More This study explores the relationship between spin diffusion, spin lifetime, electron density and lateral spatial confinement in two-dimensional electron gases hosted in GaAs quantum wells. Using time-resolved magneto-optical Kerr effect microscopy, we analyze how Hall-bar channel width and back-gate voltage modulation influence spin dynamics. The results reveal that the spin diffusion coefficient increases with reduced channel widths, a trend further amplified at lower electron concentrations achieved via back-gate voltages, where it increases up to 150% for the narrowest channels. The developed theoretical model confirms the spatial inhomogeneities in the spin diffusion as arising from electron-density variations within the channels. The results underscore the importance of tuning electron density and spatial geometry to optimize spin transport and coherence, providing valuable design considerations for spintronic devices where efficient spin manipulation is crucial. △ Less

Submitted 14 January, 2025; originally announced January 2025.

Routing and Scheduling Optimization for Urban Air Mobility Fleet Management using Quantum Annealing

Authors: Renichiro Haba, Takuya Mano, Ryosuke Ueda, Genichiro Ebe, Kohei Takeda, Masayoshi Terabe, Masayuki Ohzeki

Abstract: The growing integration of urban air mobility (UAM) for urban transportation and delivery has accelerated due to increasing traffic congestion and its environmental and economic repercussions. Efficiently managing the anticipated high-density air traffic in cities is critical to ensure safe and effective operations. In this study, we propose a routing and scheduling framework to address the needs… ▽ More The growing integration of urban air mobility (UAM) for urban transportation and delivery has accelerated due to increasing traffic congestion and its environmental and economic repercussions. Efficiently managing the anticipated high-density air traffic in cities is critical to ensure safe and effective operations. In this study, we propose a routing and scheduling framework to address the needs of a large fleet of UAM vehicles operating in urban areas. Using mathematical optimization techniques, we plan efficient and deconflicted routes for a fleet of vehicles. Formulating route planning as a maximum weighted independent set problem enables us to utilize various algorithms and specialized optimization hardware, such as quantum annealers, which has seen substantial progress in recent years. Our method is validated using a traffic management simulator tailored for the airspace in Singapore. Our approach enhances airspace utilization by distributing traffic throughout a region. This study broadens the potential applications of optimization techniques in UAM traffic management. △ Less

Submitted 14 October, 2024; originally announced October 2024.

AI Surrogate Model for Distributed Computing Workloads

Authors: David K. Park, Yihui Ren, Ozgur O. Kilic, Tatiana Korchuganova, Sairam Sri Vatsavai, Joseph Boudreau, Tasnuva Chowdhury, Shengyu Feng, Raees Khan, Jaehyung Kim, Scott Klasky, Tadashi Maeno, Paul Nilsson, Verena Ingrid Martinez Outschoorn, Norbert Podhorszki, Frederic Suter, Wei Yang, Yiming Yang, Shinjae Yoo, Alexei Klimentov, Adolfy Hoisie

Abstract: Large-scale international scientific collaborations, such as ATLAS, Belle II, CMS, and DUNE, generate vast volumes of data. These experiments necessitate substantial computational power for varied tasks, including structured data processing, Monte Carlo simulations, and end-user analysis. Centralized workflow and data management systems are employed to handle these demands, but current decision-ma… ▽ More Large-scale international scientific collaborations, such as ATLAS, Belle II, CMS, and DUNE, generate vast volumes of data. These experiments necessitate substantial computational power for varied tasks, including structured data processing, Monte Carlo simulations, and end-user analysis. Centralized workflow and data management systems are employed to handle these demands, but current decision-making processes for data placement and payload allocation are often heuristic and disjointed. This optimization challenge potentially could be addressed using contemporary machine learning methods, such as reinforcement learning, which, in turn, require access to extensive data and an interactive environment. Instead, we propose a generative surrogate modeling approach to address the lack of training data and concerns about privacy preservation. We have collected and processed real-world job submission records, totaling more than two million jobs through 150 days, and applied four generative models for tabular data -- TVAE, CTAGGAN+, SMOTE, and TabDDPM -- to these datasets, thoroughly evaluating their performance. Along with measuring the discrepancy among feature-wise distributions separately, we also evaluate pair-wise feature correlations, distance to closest record, and responses to pre-trained models. Our experiments indicate that SMOTE and TabDDPM can generate similar tabular data, almost indistinguishable from the ground truth. Yet, as a non-learning method, SMOTE ranks the lowest in privacy preservation. As a result, we conclude that the probabilistic-diffusion-model-based TabDDPM is the most suitable generative model for managing job record data. △ Less

Submitted 10 October, 2024; originally announced October 2024.

Comments: 8 pages, 5 figures, to be presented in SC24 AI4S Workshop

Semi-Automatic Line-System Provisioning with Integrated Physical-Parameter-Aware Methodology: Field Verification and Operational Feasibility

Authors: Hideki Nishizawa, Giacomo Borraccini, Takeo Sasai, Yue-Kai Huang, Toru Mano, Kazuya Anazawa, Masatoshi Namiki, Soichiroh Usui, Tatsuya Matsumura, Yoshiaki Sone, Zehao Wang, Seiji Okamoto, Takeru Inoue, Ezra Ip, Andrea D'Amico, Tingjun Chen, Vittorio Curri, Ting Wang, Koji Asahi, Koichi Takasugi

Abstract: We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in r… ▽ More We propose methods and an architecture to conduct measurements and optimize newly installed optical fiber line systems semi-automatically using integrated physics-aware technologies in a data center interconnection (DCI) transmission scenario. We demonstrate, for the first time, digital longitudinal monitoring (DLM) and optical line system (OLS) physical parameter calibration working together in real-time to extract physical link parameters for transmission performance optimization. Our methodology has the following advantages over traditional design: a minimized footprint at user sites, accurate estimation of the necessary optical network characteristics via complementary telemetry technologies, and the capability to conduct all operation work remotely. The last feature is crucial, as it enables remote operation to implement network design settings for immediate response to quality of transmission (QoT) degradation and reversion in the case of unforeseen problems. We successfully performed semi-automatic line system provisioning over field fiber networks facilities at Duke University, Durham, NC. The tasks of parameter retrieval, equipment setting optimization, and system setup/provisioning were completed within 1 hour. The field operation was supervised by on-duty personnel who could access the system remotely from different time zones. By comparing Q-factor estimates calculated from the extracted link parameters with measured results from 400G transceivers, we confirmed that our methodology has a reduction in the QoT prediction errors (+-0.3 dB) over existing design (+-10.6 dB). △ Less

Submitted 24 March, 2024; originally announced March 2024.

Operational Experience and R&D results using the Google Cloud for High Energy Physics in the ATLAS experiment

Authors: Fernando Barreiro Megino, Kaushik De, Johannes Elmsheuser, Alexei Klimentov, Mario Lassnig, Miles Euell, Nikolai Hartmann, Tadashi Maeno, Verena Martinez Outschoorn, Jay Ajitbhai Sandesara, Dustin Sell

Abstract: The ATLAS experiment at CERN relies on a worldwide distributed computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure and conducted an R&D program on Google Cloud Platform. These initiatives leverage key features of commercial cloud providers: lightweight configuration and opera… ▽ More The ATLAS experiment at CERN relies on a worldwide distributed computing Grid infrastructure to support its physics program at the Large Hadron Collider. ATLAS has integrated cloud computing resources to complement its Grid infrastructure and conducted an R&D program on Google Cloud Platform. These initiatives leverage key features of commercial cloud providers: lightweight configuration and operation, elasticity and availability of diverse infrastructure. This paper examines the seamless integration of cloud computing services as a conventional Grid site within the ATLAS workflow management and data management systems, while also offering new setups for interactive, parallel analysis. It underscores pivotal results that enhance the on-site computing model and outlines several R&D projects that have benefited from large-scale, elastic resource provisioning models. Furthermore, this study discusses the impact of cloud-enabled R\&D projects in three domains: accelerators and AI/ML, ARM CPUs and columnar data analysis techniques. △ Less

Submitted 23 March, 2024; originally announced March 2024.

Comments: 21 pages, 8 figures

Integrating the PanDA Workload Management System with the Vera C. Rubin Observatory

Authors: Edward Karavakis, Wen Guan, Zhaoyu Yang, Tadashi Maeno, Torre Wenaus, Jennifer Adelman-McCarthy, Fernando Barreiro Megino, Kaushik De, Richard Dubois, Michelle Gower, Tim Jenness, Alexei Klimentov, Tatiana Korchuganova, Mikolaj Kowalik, Fa-Hui Lin, Paul Nilsson, Sergey Padolski, Wei Yang, Shuwei Ye

Abstract: The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of petabytes of raw image data and associated calibration data over the course of the experiment's run. More than 20 terabytes of data must be stored ev… ▽ More The Vera C. Rubin Observatory will produce an unprecedented astronomical data set for studies of the deep and dynamic universe. Its Legacy Survey of Space and Time (LSST) will image the entire southern sky every three to four days and produce tens of petabytes of raw image data and associated calibration data over the course of the experiment's run. More than 20 terabytes of data must be stored every night, and annual campaigns to reprocess the entire dataset since the beginning of the survey will be conducted over ten years. The Production and Distributed Analysis (PanDA) system was evaluated by the Rubin Observatory Data Management team and selected to serve the Observatory's needs due to its demonstrated scalability and flexibility over the years, for its Directed Acyclic Graph (DAG) support, its support for multi-site processing, and its highly scalable complex workflows via the intelligent Data Delivery Service (iDDS). PanDA is also being evaluated for prompt processing where data must be processed within 60 seconds after image capture. This paper will briefly describe the Rubin Data Management system and its Data Facilities (DFs). Finally, it will describe in depth the work performed in order to integrate the PanDA system with the Rubin Observatory to be able to run the Rubin Science Pipelines using PanDA. △ Less

Submitted 8 December, 2023; originally announced December 2023.

Comments: 8 pages, 3 figures, 26th International Conference on Computing in High Energy & Nuclear Physics

Fast WDM provisioning with minimal probing: the first field experiments for DC exchanges

Authors: Hideki Nishizawa, Toru Mano, Thomas Ferreira De Lima, Yue-Kai Huang, Zehao Wang, Wataru Ishida, Masahisa Kawashima, Ezra Ip, Andrea D'Amico, Seiji Okamoto, Takeru Inoue, Kazuya Anazawa, Vittorio Curri, Gil Zussman, Daniel Kilper, Tingjun Chen, Ting Wang, Koji Asahi, Koichi Takasugi

Abstract: We propose an approach to estimate the end-to-end GSNR accurately in a short time when a data center interconnect (DCI) network operator receives a service request from users, not by measuring the GSNR at the operational route and wavelength for the End-End optical path but by simply applying a QoT probe channel link by link, at a convenient wavelength/modulation-format for measurement. Assuming c… ▽ More We propose an approach to estimate the end-to-end GSNR accurately in a short time when a data center interconnect (DCI) network operator receives a service request from users, not by measuring the GSNR at the operational route and wavelength for the End-End optical path but by simply applying a QoT probe channel link by link, at a convenient wavelength/modulation-format for measurement. Assuming connections between coherent transceivers of various frequency ranges, modulators, and modulation formats, we propose a new device software architecture in which the DCI network operator optimizes the transmission mode between user transceivers with high accuracy using only standard parameters such as Bit Error Rate. In this paper, we first experimentally built three different routes of 32 km/72 km/122 km in the C-band to confirm the accuracy of this approach. For the operational end-to-end GSNR measurements, the accuracy estimated from the sum of the measurements for each link was 0.6 dB, and the wavelength-dependent error was about 0.2 dB. Then, using field fibers deployed in the NSF COSMOS testbed (deployed in an urban area), a Linux-based transmission device software architecture, and coherent transceivers with different optical frequency ranges, modulators, and modulation formats, the fast WDM provisioning of an optical path was completed within 6 minutes (with a Q-factor error of about 0.7 dB). △ Less

Submitted 6 April, 2024; v1 submitted 13 September, 2023; originally announced September 2023.

Comments: 10 pages, 11 figures, 3 tables

A presentation of the torus-equivariant quantum $K$-theory ring of flag manifolds of type $A$, Part II: quantum double Grothendieck polynomials

Authors: Toshiaki Maeno, Satoshi Naito, Daisuke Sagaki

Abstract: In our previous paper, we gave a presentation of the torus-equivariant quantum $K$-theory ring $QK_{H}(Fl_{n+1})$ of the (full) flag manifold $Fl_{n+1}$ of type $A_{n}$ as a quotient of a polynomial ring by an explicit ideal. In this paper, we prove that quantum double Grothendieck polynomials, introduced by Lenart-Maeno, represent the corresponding (opposite) Schubert classes in the quantum $K$-t… ▽ More In our previous paper, we gave a presentation of the torus-equivariant quantum $K$-theory ring $QK_{H}(Fl_{n+1})$ of the (full) flag manifold $Fl_{n+1}$ of type $A_{n}$ as a quotient of a polynomial ring by an explicit ideal. In this paper, we prove that quantum double Grothendieck polynomials, introduced by Lenart-Maeno, represent the corresponding (opposite) Schubert classes in the quantum $K$-theory ring $QK_{H}(Fl_{n+1})$ under this presentation. The main ingredient in our proof is an explicit formula expressing the semi-infinite Schubert class associated to the longest element of the finite Weyl group, which is proved by making use of the general Chevalley formula for the torus-equivariant $K$-group of the semi-infinite flag manifold associated to $SL_{n+1}(\mathbb{C})$. △ Less

Submitted 28 May, 2023; originally announced May 2023.

Comments: arXiv admin note: text overlap with arXiv:2302.09485

MSC Class: 2020 Mathematics Subject Classification: Primary 14N15; 14N35; Secondary 14M15; 05E14; 05E05

A presentation of the torus-equivariant quantum $K$-theory ring of flag manifolds of type $A$, Part I: the defining ideal

Authors: Toshiaki Maeno, Satoshi Naito, Daisuke Sagaki

Abstract: We give a presentation of the torus-equivariant quantum $K$-theory ring of flag manifolds of type $A$, as a quotient of a polynomial ring by an explicit ideal. This is the torus-equivariant version of our previous result, which gives a presentation of the non-equivariant quantum $K$-theory ring of flag manifolds of type $A$. However, the method of proof for the torus-equivariant one is completely… ▽ More We give a presentation of the torus-equivariant quantum $K$-theory ring of flag manifolds of type $A$, as a quotient of a polynomial ring by an explicit ideal. This is the torus-equivariant version of our previous result, which gives a presentation of the non-equivariant quantum $K$-theory ring of flag manifolds of type $A$. However, the method of proof for the torus-equivariant one is completely different from that for the non-equivariant one; our proof is based on the result in the $Q = 0$ limit, and uses Nakayama-type arguments to upgrade it to the quantum situation. Also, in contrast to the non-equivariant case in which we used the Chevalley formula, we make use of the inverse Chevalley formula for the torus-equivariant $K$-group of semi-infinite flag manifolds to obtain a relation which yields our presentation. △ Less

Submitted 13 November, 2023; v1 submitted 19 February, 2023; originally announced February 2023.

MSC Class: Primary 14M15; 14N35; Secondary 14N15; 05E10; 20C08

Thermal Transport Imaging in the Quantum Hall Edge Channel

Authors: J. N. Moore, A. Kamiyama, T. Mano, G. Yusa

Abstract: Research focused on heat transport in the quantum Hall (QH) edge channel has successfully addressed fundamental theoretical questions surrounding the QH physics. However, the picture of the edge channel is complicated by the phenomenon of energy dissipation out of the edge, and theories treating this dissipation are lacking. More experimental data is also needed to determine the coupling mechanism… ▽ More Research focused on heat transport in the quantum Hall (QH) edge channel has successfully addressed fundamental theoretical questions surrounding the QH physics. However, the picture of the edge channel is complicated by the phenomenon of energy dissipation out of the edge, and theories treating this dissipation are lacking. More experimental data is also needed to determine the coupling mechanism by which energy leaves the edge channel. We developed a method to map the heat transport in the QH edge to study the dissipation of heat. We locally heated the QH edge and locally detected the temperature increase while continuously varying the distance between heater and thermometer. We thereby obtained the thermal decay length of the edge state. △ Less

Submitted 15 April, 2023; v1 submitted 23 December, 2022; originally announced December 2022.

Dynamics of the fractional quantum Hall edge probed by stroboscope measurements of trions

Authors: Akinori Kamiyama, Masahiro Matsuura, John N. Moore, Takaaki Mano, Naokazu Shibata, Go Yusa

Abstract: By using observations from pump-probe stroboscopic confocal microscopy and spectroscopy, we demonstrate the dynamics of trions and the fractional quantum Hall edge on the order of $\sim1$ ps. The propagation of the quantum Hall edge state excited by a voltage pulse is detected as a temporal change in reflectance in the downstream edge probed by optical pulses synchronized with the voltage pulse. T… ▽ More By using observations from pump-probe stroboscopic confocal microscopy and spectroscopy, we demonstrate the dynamics of trions and the fractional quantum Hall edge on the order of $\sim1$ ps. The propagation of the quantum Hall edge state excited by a voltage pulse is detected as a temporal change in reflectance in the downstream edge probed by optical pulses synchronized with the voltage pulse. The temporal resolution of such stroboscopic pump-probe measurements is as fast as the duration time of the probe pulse ($\sim1$ ps). This ultra-fast stroboscope measurement enables us to distinguish between the normal mode of edge excitation, known as the edge magneto-plasmon or charge density wave, and other high-energy non-linear excitations. This is the only experimental method available to study the ultra-fast dynamics of quantum Hall edges, and makes it possible to derive the metric tensor $g_{μν}$ of the $(1+1)=2$-dimensional curved spacetime in quantum universe and black hole analogs implemented in the quantum Hall edge. △ Less

Submitted 11 December, 2022; originally announced December 2022.

Dynamic optical path provisioning for alien access links: architecture, demonstration, and challenges

Authors: Hideki Nishizawa, Takeo Sasai, Takeru Inoue, Kazuya Anazawa, Toru Mano, Kei Kitamura, Yoshiaki Sone, Tetsuro Inui, Koichi Takasugi

Abstract: With the spread of Data Center Interconnect (DCI) and local 5G, there is a growing need for dynamically established connections between customer locations through high-capacity optical links. However, link parameters such as signal power profile and amplifier gains are often unknown and have to be measured by experts, preventing dynamic path provisioning due to the time-consuming manual measuremen… ▽ More With the spread of Data Center Interconnect (DCI) and local 5G, there is a growing need for dynamically established connections between customer locations through high-capacity optical links. However, link parameters such as signal power profile and amplifier gains are often unknown and have to be measured by experts, preventing dynamic path provisioning due to the time-consuming manual measurements. Although several techniques for estimating the unknown parameters of such alien access links have been proposed, no work has presented architecture and protocol that drive the estimation techniques to establish an optical path between the customer locations. Our study aims to automatically connect customer-owned transceivers via alien access links with optimal quality of transmission (QoT). We first propose an architecture and protocol for cooperative optical path design between a customer and carrier, utilizing a state-of-the-art technique for estimating link parameters. We then implement the proposed protocol in a software-defined network (SDN) controller and white-box transponders using an open API. The experiments demonstrate that the optical path is dynamically established via alien access links in 137 seconds from the transceiver's cold start. Lastly, we discuss the QoT accuracy obtained with this method and the remaining issues. △ Less

Submitted 12 September, 2022; v1 submitted 6 September, 2022; originally announced September 2022.

Comments: 6 pages, 5 figures, 1 table

Spin helices in GaAs quantum wells: Interplay of electron density, spin diffusion, and spin lifetime

Authors: S. Anghel, A. V. Poshakinskiy, K. Schiller, G. Yusa, T. Mano, T. Noda, M. Betz

Abstract: To establish a correlation between the spin diffusion, the spin lifetime, and the electron density, we study, employing time-resolved magneto-optical Kerr effect microscopy, the spin polarization evolution in low-dimensional GaAs semiconductors hosting two-dimensional electron gases. It is shown that for the establishment of the longest spin-lifetime, the variation of scattering rate with the elec… ▽ More To establish a correlation between the spin diffusion, the spin lifetime, and the electron density, we study, employing time-resolved magneto-optical Kerr effect microscopy, the spin polarization evolution in low-dimensional GaAs semiconductors hosting two-dimensional electron gases. It is shown that for the establishment of the longest spin-lifetime, the variation of scattering rate with the electron density is of higher importance than the fulfilling of the persistent spin helix condition when the Rashba $α$ and Dresselhaus $β$ parameters are balanced. More specifically, regardless of the $α$ and $β$ linear dependencies on the electron density, the spin relaxation rate is determined by the spin diffusion coefficient that depends on electron density nonmonotonously. The longest experimental spin-lifetime occurs at an electron density, corresponding to the transition from Boltzmann to Fermi-Dirac statistics, which is several times higher than that when the persistent spin helix is expected. These facts highlight the role the electron density may play when considering applications for spintronic devices. △ Less

Submitted 8 June, 2022; originally announced June 2022.

Comments: 8 pages, 4 figures

Real-time and -space visualization of excitations of the ν= 1/3 fractional quantum Hall edge

Authors: Akinori Kamiyama, Masahiro Matsuura, John N. Moore, Takaaki Mano, Naokazu Shibata, Go Yusa

Abstract: We present scanning optical stroboscopic confocal microscopy and spectroscopy measurements wherein three degrees of freedom, namely energy, real-space, and real-time, are resolvable. The edge-state propagation is detected as a temporal change in the optical response in the downstream edge. We succeeded in visualizing the excited states of the most fundamental fractional quantum Hall (FQH) state an… ▽ More We present scanning optical stroboscopic confocal microscopy and spectroscopy measurements wherein three degrees of freedom, namely energy, real-space, and real-time, are resolvable. The edge-state propagation is detected as a temporal change in the optical response in the downstream edge. We succeeded in visualizing the excited states of the most fundamental fractional quantum Hall (FQH) state and the collective excitations near the edge. The results verify the current understanding of the edge excitation and also point toward further dynamics outside the edge channel. △ Less

Submitted 25 January, 2022; originally announced January 2022.

An intelligent Data Delivery Service for and beyond the ATLAS experiment

Authors: Wen Guan, Tadashi Maeno, Brian Paul Bockelman, Torre Wenaus, Fahui Lin, Siarhei Padolski, Rui Zhang, Aleksandr Alekseev

Abstract: The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and main processing in various workflows. It is an experiment-agnostic service around a workflow-orien… ▽ More The intelligent Data Delivery Service (iDDS) has been developed to cope with the huge increase of computing and storage resource usage in the coming LHC data taking. iDDS has been designed to intelligently orchestrate workflow and data management systems, decoupling data pre-processing, delivery, and main processing in various workflows. It is an experiment-agnostic service around a workflow-oriented structure to work with existing and emerging use cases in ATLAS and other experiments. Here we will present the motivation for iDDS, its design schema and architecture, use cases and current status, and plans for the future. △ Less

Submitted 28 February, 2021; originally announced March 2021.

Comments: 6 pages, 5 figures

Machine learning the dynamics of quantum kicked rotor

Authors: Tomohiro Mano, Tomi Ohtsuki

Abstract: Using the multilayer convolutional neural network (CNN), we can detect the quantum phases in random electron systems, and phase diagrams of two and higher dimensional Anderson transitions and quantum percolations as well as disordered topological systems have been obtained. Here, instead of using CNN to analyze the wave functions, we analyze the dynamics of wave packets via long short-term memory… ▽ More Using the multilayer convolutional neural network (CNN), we can detect the quantum phases in random electron systems, and phase diagrams of two and higher dimensional Anderson transitions and quantum percolations as well as disordered topological systems have been obtained. Here, instead of using CNN to analyze the wave functions, we analyze the dynamics of wave packets via long short-term memory network (LSTM). We adopt the quasi-periodic quantum kicked rotors, which simulate the three and four dimensional Anderson transitions. By supervised training, we let LSTM extract the features of the time series of wave packet displacements in localized and delocalized phases. We then simulate the wave packets in unknown phases and let LSTM classify the time series to localized and delocalized phases. We compare the phase diagrams obtained by LSTM and those obtained by CNN. △ Less

Submitted 7 May, 2021; v1 submitted 23 January, 2021; originally announced January 2021.

Comments: published version. Proceedings of Localisation 2020. Annals of Physics

Analysis of Kohn-Sham Eigenfunctions Using a Convolutional Neural Network in Simulations of the Metal-insulator Transition in Doped Semiconductors

Authors: Yosuke Harashima, Tomohiro Mano, Keith Slevin, Tomi Ohtsuki

Abstract: Machine learning has recently been applied to many problems in condensed matter physics. A common point of many proposals is to save computational cost by training the machine with data from a simple example and then using the machine to make predictions for a more complicated example. Convolutional neural networks (CNN), which are one of the tools of machine learning, have proved to work well for… ▽ More Machine learning has recently been applied to many problems in condensed matter physics. A common point of many proposals is to save computational cost by training the machine with data from a simple example and then using the machine to make predictions for a more complicated example. Convolutional neural networks (CNN), which are one of the tools of machine learning, have proved to work well for assessing eigenfunctions in disordered systems. Here we apply a CNN to assess Kohn-Sham eigenfunctions obtained in density functional theory (DFT) simulations of the metal-insulator transition of a doped semiconductor. We demonstrate that a CNN that has been trained using eigenfunctions from a simulation of a doped semiconductor that neglects electron spin successfully predicts the critical concentration when presented with eigenfunctions from simulations that include spin. △ Less

Submitted 13 July, 2021; v1 submitted 7 September, 2020; originally announced September 2020.

Comments: 7pages, 7 figures

Journal ref: J. Phys. Soc. Jpn. 90, 094001 (2021)

Towards an Intelligent Data Delivery Service

Authors: Wen Guan, Tadashi Maeno, Gancho Dimitrov, Brian Paul Bockelman, Torre Wenaus, Vakhtang Tsulaia, Nicolo Magini

Abstract: The ATLAS Event Streaming Service (ESS) at the LHC is an approach to preprocess and deliver data for Event Service (ES) that has implemented a fine-grained approach for ATLAS event processing. The ESS allows one to asynchronously deliver only the input events required by ES processing, with the aim to decrease data traffic over WAN and improve overall data processing throughput. A prototype of ESS… ▽ More The ATLAS Event Streaming Service (ESS) at the LHC is an approach to preprocess and deliver data for Event Service (ES) that has implemented a fine-grained approach for ATLAS event processing. The ESS allows one to asynchronously deliver only the input events required by ES processing, with the aim to decrease data traffic over WAN and improve overall data processing throughput. A prototype of ESS was developed to deliver streaming events to fine-grained ES jobs. Based on it, an intelligent Data Delivery Service (iDDS) is under development to decouple the "cold format" and the processing format of the data, which also opens the opportunity to include the production systems of other HEP experiments. Here we will at first present the ESS model view and its motivations for iDDS system. Then we will also present the iDDS schema, architecture and the applications of iDDS. △ Less

Submitted 3 July, 2020; originally announced July 2020.

Comments: 6 pages, 3 figures

Single photon emission from droplet epitaxial quantum dots in the standard telecom window around a wavelength of 1.55 $μ$m

Authors: N. Ha, T. Mano, S. Dubos, T. Kuroda, Y. Sakuma, K. Sakoda

Abstract: We study the luminescence dynamics of telecom wavelength InAs quantum dots grown on InP(111)A by droplet epitaxy. The use of the ternary alloy InAlGaAs as a barrier material leads to photon emission in the 1.55 $μ$m telecom C-band. The luminescence decay is well described in terms of the theoretical interband transition strength without the impact of nonradiative recombination. The intensity autoc… ▽ More We study the luminescence dynamics of telecom wavelength InAs quantum dots grown on InP(111)A by droplet epitaxy. The use of the ternary alloy InAlGaAs as a barrier material leads to photon emission in the 1.55 $μ$m telecom C-band. The luminescence decay is well described in terms of the theoretical interband transition strength without the impact of nonradiative recombination. The intensity autocorrelation function shows clear anti-bunching photon statistics. The results suggest that our quantum dots are useful for constructing a practical source of single photons and quantum entangled photon pairs. △ Less

Submitted 20 January, 2020; originally announced January 2020.

Comments: 4 pages

Journal ref: Appl. Phys. Express 13, 025002 (2020); open access

Application of Convolutional Neural Network to Quantum Percolation in Topological Insulators

Authors: Tomohiro Mano, Tomi Ohtsuki

Abstract: Quantum material phases such as the Anderson insulator, diffusive metal, and Weyl/Dirac semimetal as well as topological insulators show specific wave functions both in real and Fourier spaces. These features are well captured by convolutional neural networks, and the phase diagrams have been obtained, where standard methods are not applicable. One of these examples is the cases of random lattices… ▽ More Quantum material phases such as the Anderson insulator, diffusive metal, and Weyl/Dirac semimetal as well as topological insulators show specific wave functions both in real and Fourier spaces. These features are well captured by convolutional neural networks, and the phase diagrams have been obtained, where standard methods are not applicable. One of these examples is the cases of random lattices such as quantum percolation. Here, we study the topological insulators with random vacancies, namely, the quantum percolation in topological insulators, by analyzing the wave functions via a convolutional neural network. The vacancies in topological insulators are especially interesting since peculiar bound states are formed around the vacancies. We show that only a few percent of vacancies are required for a topological phase transition. The results are confirmed by independent calculations of localization length, density of states, and wave packet dynamics. △ Less

Submitted 18 November, 2019; v1 submitted 7 October, 2019; originally announced October 2019.

Comments: published version. Open access

Journal ref: Journal of the Physical Society of Japan vol. 88, 123704 (2019)

Drawing Phase Diagrams of Random Quantum Systems by Deep Learning the Wave Functions

Authors: Tomi Ohtsuki, Tomohiro Mano

Abstract: Applications of neural networks to condensed matter physics are becoming popular and beginning to be well accepted. Obtaining and representing the ground and excited state wave functions are examples of such applications. Another application is analyzing the wave functions and determining their quantum phases. Here, we review the recent progress of using the multilayer convolutional neural network… ▽ More Applications of neural networks to condensed matter physics are becoming popular and beginning to be well accepted. Obtaining and representing the ground and excited state wave functions are examples of such applications. Another application is analyzing the wave functions and determining their quantum phases. Here, we review the recent progress of using the multilayer convolutional neural network, so-called deep learning, to determine the quantum phases in random electron systems. After training the neural network by the supervised learning of wave functions in restricted parameter regions in known phases, the neural networks can determine the phases of the wave functions in wide parameter regions in unknown phases; hence, the phase diagrams are obtained. We demonstrate the validity and generality of this method by drawing the phase diagrams of two- and higher dimensional Anderson metal-insulator transitions and quantum percolations as well as disordered topological systems such as three-dimensional topological insulators and Weyl semimetals. Both real-space and Fourier space wave functions are analyzed. The advantages and disadvantages over conventional methods are discussed. △ Less

Submitted 25 December, 2019; v1 submitted 21 September, 2019; originally announced September 2019.

Comments: Journal of the Physical Society of Japan, invited review, open access

Journal ref: J. Phys. Soc. Jpn. 89, 022001 (2020)

Current-injection quantum-entangled-pair emitter using droplet epitaxial quantum dots on GaAs(111)A

Authors: Neul Ha, Takaaki Mano, Takashi Kuroda, Yoshiki Sakuma, Kazuaki Sakoda

Abstract: A source of single photons and quantum entangled photon pairs is a key element in quantum information networks. Here, we demonstrate the electrically driven generation of quantum entangled pairs using a naturally symmetric GaAs quantum dot grown by droplet epitaxy. Coincidence histograms obtained at a temperature of 10 K reveal the generation of quantum entangled pairs that have a fidelity to the… ▽ More A source of single photons and quantum entangled photon pairs is a key element in quantum information networks. Here, we demonstrate the electrically driven generation of quantum entangled pairs using a naturally symmetric GaAs quantum dot grown by droplet epitaxy. Coincidence histograms obtained at a temperature of 10 K reveal the generation of quantum entangled pairs that have a fidelity to the Bell pairs of 0.71 +- 0.015, much beyond the classical limit. The quantum nature of the emitted pairs is conserved at temperatures of up to ~65 K, and is essentially limited by the charge carrier confinement in the present dot system. Our study offers a guideline for the fabrication of quantum entangled pair sources suitable for practical use. △ Less

Submitted 20 June, 2019; originally announced June 2019.

Journal ref: Appl. Phys. Lett. 115, 083106 (2019)

Spontaneous Transition to a Correlated Phase of Skyrmions Observed in Real Space

Authors: John N. Moore, Hikaru Iwata, Junichiro Hayakawa, Takaaki Mano, Takeshi Noda, Naokazu Shibata, Go Yusa

Abstract: We conduct photoluminescence microscopy that is sensitive to both electron and nuclear spin polarization to investigate the changes that occur in the magnetic ordering in the vicinity of the first integer quantum Hall state in a GaAs 2D electron system (2DES). We observe a discontinuity in the electron spin polarization and nuclear spin longitudinal relaxation time which heralds a spontaneous tran… ▽ More We conduct photoluminescence microscopy that is sensitive to both electron and nuclear spin polarization to investigate the changes that occur in the magnetic ordering in the vicinity of the first integer quantum Hall state in a GaAs 2D electron system (2DES). We observe a discontinuity in the electron spin polarization and nuclear spin longitudinal relaxation time which heralds a spontaneous transition to a phase of magnetic skyrmions. We image in real space the spin phase domains that coexist at this transition, and observe hysteresis in their formation as a function of the 2DES's chemical potential. Based on measurements in a tilted magnetic field orientation, we found that the transition is protected by an energy gap containing the Zeeman energy, and conclude that the skyrmions here have formed as an ensemble. △ Less

Submitted 31 May, 2018; originally announced June 2018.

Comments: 4 figures

Journal ref: Phys. Rev. B 98, 161402 (2018)

Solomon-Terao algebra of hyperplane arrangements

Authors: Takuro Abe, Toshiaki Maeno, Satoshi Murai, Yasuhide Numata

Abstract: We introduce a new algebra associated with a hyperplane arrangement $\mathcal{A}$, called the Solomon-Terao algebra $\mbox{ST}(\mathcal{A},η)$, where $η$ is a homogeneous polynomial. It is shown by Solomon and Terao that $\mbox{ST}(\mathcal{A},η)$ is Artinian when $η$ is generic. This algebra can be considered as a generalization of coinvariant algebras in the setting of hyperplane arrangements. T… ▽ More We introduce a new algebra associated with a hyperplane arrangement $\mathcal{A}$, called the Solomon-Terao algebra $\mbox{ST}(\mathcal{A},η)$, where $η$ is a homogeneous polynomial. It is shown by Solomon and Terao that $\mbox{ST}(\mathcal{A},η)$ is Artinian when $η$ is generic. This algebra can be considered as a generalization of coinvariant algebras in the setting of hyperplane arrangements. The class of Solomon-Terao algebras contains cohomology rings of regular nilpotent Hessenberg varieties. We show that $\mbox{ST}(\mathcal{A},η)$ is a complete intersection if and only if $\mathcal{A}$ is free. We also give a factorization formula of the Hilbert polynomials when $\mathcal{A}$ is free, and pose several related questions, problems and conjectures. △ Less

Submitted 12 February, 2018; originally announced February 2018.

Comments: 24 pages

MSC Class: 32S22

Electrically tunable dynamic nuclear spin polarization in GaAs quantum dots at zero magnetic field

Authors: M. Manca, G. Wang, T. Kuroda, S. Shree, A. Balocchi, P. Renucci, X. Marie, M. V. Durnev, M. M. Glazov, K. Sakoda, T. Mano, T. Amand, B. Urbaszek

Abstract: In III-V semiconductor nano-structures the electron and nuclear spin dynamics are strongly coupled. Both spin systems can be controlled optically. The nuclear spin dynamics is widely studied, but little is known about the initialization mechanisms. Here we investigate optical pumping of carrier and nuclear spins in charge tunable GaAs dots grown on 111A substrates. We demonstrate dynamic nuclear p… ▽ More In III-V semiconductor nano-structures the electron and nuclear spin dynamics are strongly coupled. Both spin systems can be controlled optically. The nuclear spin dynamics is widely studied, but little is known about the initialization mechanisms. Here we investigate optical pumping of carrier and nuclear spins in charge tunable GaAs dots grown on 111A substrates. We demonstrate dynamic nuclear polarization (DNP) at zero magnetic field in a single quantum dot for the positively charged exciton X$^+$ state transition. We tune the DNP in both amplitude and sign by variation of an applied bias voltage V$_g$. Variation of $Δ$V$_g$ of the order of 100 mV changes the Overhauser splitting (nuclear spin polarization) from -30 $μ$eV (-22 %) to +10 $μ$eV (+7 %), although the X$^+$ photoluminescence polarization does not change sign over this voltage range. This indicates that absorption in the structure and energy relaxation towards the X$^+$ ground state might provide favourable scenarios for efficient electron-nuclear spin flip-flops, generating DNP during the first tens of ps of the X$^+$ lifetime which is of the order of hundreds of ps. Voltage control of DNP is further confirmed in Hanle experiments. △ Less

Submitted 27 March, 2018; v1 submitted 2 February, 2018; originally announced February 2018.

Comments: 5 pages, 2 figures

Journal ref: Appl. Phys. Lett. 112, 142103 (2018)

Transmission and reflection of charge density waves in a quantum Hall edge controlled by a metal gate

Authors: Masahiro Matsuura, Takaaki Mano, Takeshi Noda, Naokazu Shibata, Masahiro Hotta, Go Yusa

Abstract: Quantum energy teleportation (QET) is a proposed protocol related to the quantum vacuum. The edge channels in a quantum Hall system is well suited for the experimental verification of QET. For this purpose, we examine a charge density wave excited and detected by capacitively coupled front gate electrodes. We observe the waveform of the charge density wave, which is proportional to the time deriva… ▽ More Quantum energy teleportation (QET) is a proposed protocol related to the quantum vacuum. The edge channels in a quantum Hall system is well suited for the experimental verification of QET. For this purpose, we examine a charge density wave excited and detected by capacitively coupled front gate electrodes. We observe the waveform of the charge density wave, which is proportional to the time derivative of the applied square voltage wave. Further, we study the transmission and reflection behaviors of the charge density wave by applying a voltage to another front gate electrode to control the path of the edge state. We show that the threshold voltages where the dominant direction is switched in either transmission or reflection for dense and sparse waves are different from the threshold voltage where the current stops flowing in an equilibrium state. △ Less

Submitted 16 October, 2017; originally announced October 2017.

Comments: 4 pages, 4 figures

Phase Diagrams of Three-Dimensional Anderson and Quantum Percolation Models using Deep Three-Dimensional Convolutional Neural Network

Authors: Tomohiro Mano, Tomi Ohtsuki

Abstract: The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization--localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. {\bf 85}, 123706 (2016), {\bf 86}, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural networ… ▽ More The three-dimensional Anderson model is a well-studied model of disordered electron systems that shows the delocalization--localization transition. As in our previous papers on two- and three-dimensional (2D, 3D) quantum phase transitions [J. Phys. Soc. Jpn. {\bf 85}, 123706 (2016), {\bf 86}, 044708 (2017)], we used an image recognition algorithm based on a multilayered convolutional neural network. However, in contrast to previous papers in which 2D image recognition was used, we applied 3D image recognition to analyze entire 3D wave functions. We show that a full phase diagram of the disorder-energy plane is obtained once the 3D convolutional neural network has been trained at the band center. We further demonstrate that the full phase diagram for 3D quantum bond and site percolations can be drawn by training the 3D Anderson model at the band center. △ Less

Submitted 27 October, 2017; v1 submitted 4 September, 2017; originally announced September 2017.

Comments: 11 pages, 5 figures. Published version

Journal ref: J. Phys. Soc. Jpn. 86, 113704 (2017)

Gate-Control of Anisotropic Spin Transport and Spin Helix Dynamics in a Modulation-Doped GaAs Quantum Well

Authors: S. Anghel, F. Passmann, A. Singh, C. Ruppert, A. V. Poshakinskiy, S. A. Tarasenko, J. N. Moore, G. Yusa, T. Mano, T. Noda, X. Li, A. D. Bristow, M. Betz

Abstract: Electron spin transport and dynamics are investigated in a single, high-mobility, modulation-doped, GaAs quantum well using ultrafast two-color Kerr-rotation micro-spectroscopy, supported by qualitative kinetic theory simulations of spin diffusion and transport. Evolution of the spins is governed by the Dresselhaus bulk and Rashba structural inversion asymmetries, which manifest as an effective ma… ▽ More Electron spin transport and dynamics are investigated in a single, high-mobility, modulation-doped, GaAs quantum well using ultrafast two-color Kerr-rotation micro-spectroscopy, supported by qualitative kinetic theory simulations of spin diffusion and transport. Evolution of the spins is governed by the Dresselhaus bulk and Rashba structural inversion asymmetries, which manifest as an effective magnetic field that can be extracted directly from the experimental coherent spin precession. A spin precession length L-SOI is defined as one complete precession in the effective magnetic field. It is observed that application of (a) an out-of-plane electric field changes the spin decay time and L-SOI through the Rashba component of the spin-orbit coupling, (b) an in-plane magnetic field allows for extraction of the Dresselhaus and Rashba parameters, and (c) an in-plane electric field markedly modifies both the L-SOI and diffusion coefficient. While simulations reproduce the main features of the experiments, the latter results exceed the corresponding simulations and extend previous studies of drift-current-dependent spin-orbit interactions. △ Less

Submitted 15 December, 2017; v1 submitted 30 August, 2017; originally announced August 2017.

Comments: 11 pages, 7 figures

Journal ref: Phys. Rev. B 97, 125410 (2018)

Determinant structure for tau-function of holonomic deformation of linear differential equations

Authors: Masao Ishikawa, Toshiyuki Mano, Teruhisa Tsuda

Abstract: In our previous works, a relationship between Hermite's two approximation problems and Schlesinger transformations of linear differential equations has been clarified. In this paper, we study tau-functions associated with holonomic deformations of linear differential equations by using Hermite's two approximation problems. As a result, we present a determinant formula for the ratio of tau-function… ▽ More In our previous works, a relationship between Hermite's two approximation problems and Schlesinger transformations of linear differential equations has been clarified. In this paper, we study tau-functions associated with holonomic deformations of linear differential equations by using Hermite's two approximation problems. As a result, we present a determinant formula for the ratio of tau-functions (tau-quotient). △ Less

Submitted 19 June, 2018; v1 submitted 26 June, 2017; originally announced June 2017.

Comments: 24 pages

Freeness of multi-reflection arrangements via primitive vector fields

Authors: Torsten Hoge, Toshiyuki Mano, Gerhard Roehrle, Christian Stump

Abstract: In 2002, Terao showed that every reflection multi-arrangement of a real reflection group with constant multiplicity is free by providing a basis of the module of derivations. We first generalize Terao's result to multi-arrangements stemming from well-generated unitary reflection groups, where the multiplicity of a hyperplane depends on the order of its stabilizer. Here the exponents depend on the… ▽ More In 2002, Terao showed that every reflection multi-arrangement of a real reflection group with constant multiplicity is free by providing a basis of the module of derivations. We first generalize Terao's result to multi-arrangements stemming from well-generated unitary reflection groups, where the multiplicity of a hyperplane depends on the order of its stabilizer. Here the exponents depend on the exponents of the dual reflection representation. We then extend our results further to all imprimitive irreducible unitary reflection groups. In this case the exponents turn out to depend on the exponents of a certain Galois twist of the dual reflection representation that comes from a Beynon-Lusztig type semi-palindromicity of the fake degrees. △ Less

Submitted 17 April, 2019; v1 submitted 27 March, 2017; originally announced March 2017.

Comments: 26 pages; v2: an analogue of Saito's Hodge filtration is introduced and is used to show the universality of the vector field \nabla_D^{-m}(E) in Prop. 3.18; v3: minor changes; v4: reference [KMS18b] added; other minor changes; final version to appear in Advances in Math

MSC Class: 20F55; 52C35; 14N20; 32S25; 32S22; 05E15

Peterson Isomorphism in $K$-theory and Relativistic Toda Lattice

Authors: Takeshi Ikeda, Shinsuke Iwao, Toshiaki Maeno

Abstract: The $K$-homology ring of the affine Grassmannian of $SL_n(C)$ was studied by Lam, Schilling, and Shimozono. It is realized as a certain concrete Hopf subring of the ring of symmetric functions. On the other hand, for the quantum $K$-theory of the flag variety $Fl_n$, Kirillov and Maeno provided a conjectural presentation based on the results obtained by Givental and Lee. We construct an explicit b… ▽ More The $K$-homology ring of the affine Grassmannian of $SL_n(C)$ was studied by Lam, Schilling, and Shimozono. It is realized as a certain concrete Hopf subring of the ring of symmetric functions. On the other hand, for the quantum $K$-theory of the flag variety $Fl_n$, Kirillov and Maeno provided a conjectural presentation based on the results obtained by Givental and Lee. We construct an explicit birational morphism between the spectrums of these two rings. Our method relies on Ruijsenaars's relativistic Toda lattice with unipotent initial condition. From this result, we obtain a $K$-theory analogue of the so-called Peterson isomorphism for (co)homology. We provide a conjecture on the detailed relationship between the Schubert bases, and, in particular, we determine the image of Lenart--Maeno's quantum Grothendieck polynomial associated with a Grassmannian permutation. △ Less

Submitted 3 March, 2018; v1 submitted 25 March, 2017; originally announced March 2017.

Comments: added reference by Anderson-Chen-Tseng (arXiv: 1711.08414v1). minor changes

MSC Class: 14M15; 53D45; 17B67

Polynomial expressions of $p$-ary auction functions

Authors: Shizuo Kaji, Toshiaki Maeno, Koji Nuida, Yasuhide Numata

Abstract: Let $\mathbb{F}_p$ be the finite field of prime order $p$. For any function $f \colon \mathbb{F}_p{}^n \to \mathbb{F}_p$, there exists a unique polynomial over $\mathbb{F}_p$ having degree at most $p-1$ with respect to each variable which coincides with $f$. We call it the minimal polynomial of $f$. It is in general a non-trivial task to find a concrete expression of the minimal polynomial of a gi… ▽ More Let $\mathbb{F}_p$ be the finite field of prime order $p$. For any function $f \colon \mathbb{F}_p{}^n \to \mathbb{F}_p$, there exists a unique polynomial over $\mathbb{F}_p$ having degree at most $p-1$ with respect to each variable which coincides with $f$. We call it the minimal polynomial of $f$. It is in general a non-trivial task to find a concrete expression of the minimal polynomial of a given function, which has only been worked out for limited classes of functions in the literature. In this paper, we study minimal polynomial expressions of several functions that are closely related to some practically important procedures such as auction and voting. △ Less

Submitted 23 March, 2017; originally announced March 2017.

Comments: 11 pages

MSC Class: 68R05; 12Y05

Regular flat structure and generalized Okubo system

Authors: Hiroshi Kawakami, Toshiyuki Mano

Abstract: We study a relationship between regular flat structures and generalized Okubo systems. We show that the space of variables of isomonodromic deformations of a regular generalized Okubo system can be equipped with a flat structure. As its consequence, we introduce flat structures on the spaces of independent variables of generic solutions to (classical) Painlevé equations (except for PI). In our fra… ▽ More We study a relationship between regular flat structures and generalized Okubo systems. We show that the space of variables of isomonodromic deformations of a regular generalized Okubo system can be equipped with a flat structure. As its consequence, we introduce flat structures on the spaces of independent variables of generic solutions to (classical) Painlevé equations (except for PI). In our framework, the Painlevé equations PVI-PII can be treated uniformly as just one system of differential equations called the four-dimensional extended WDVV equation. Then the well-known coalescence cascade of the Painlevé equations corresponds to the degeneration scheme of the Jordan normal forms of a square matrix of rank four. △ Less

Submitted 19 June, 2018; v1 submitted 10 February, 2017; originally announced February 2017.

Comments: 33 pages. arXiv admin note: text overlap with arXiv:1511.01608

MSC Class: 34M55; 34M56; 33E17; 32S40

Optimal run-and-tumble based transportation of a Janus particle with active steering

Authors: Tomoyuki Mano, Jean-Baptiste Delfau, Masaki Sano

Abstract: Even though making artificial micrometric swimmers has been made possible by using various propulsion mechanisms, guiding their motion in the presence of thermal fluctuations still remains a great challenge. Such a task is essential in biological systems, which present a number of intriguing solutions that are robust against noisy environmental conditions as well as variability in individual genet… ▽ More Even though making artificial micrometric swimmers has been made possible by using various propulsion mechanisms, guiding their motion in the presence of thermal fluctuations still remains a great challenge. Such a task is essential in biological systems, which present a number of intriguing solutions that are robust against noisy environmental conditions as well as variability in individual genetic makeup. Using synthetic Janus particles driven by an electric field, we present a feedback-based particle guiding method, quite analogous to the "run-and-tumbling" behavior of Escherichia coli but with a deterministic steering in the tumbling phase: the particle is set to the "run" state when its orientation vector aligns with the target, while the transition to the "steering" state is triggered when it exceeds a tolerance angle α. The active and deterministic reorientation of the particle is achieved by a characteristic rotational motion that can be switched on and off by modulating the AC frequency of the electric field, first reported in this work. Relying on numerical simulations and analytical results, we show that this feedback algorithm can be optimized by tuning the tolerance angle α. The optimal resetting angle depends on signal to noise ratio in the steering state, and it is demonstrated in the experiment. Proposed method is simple and robust for targeting, despite variability in self-propelling speeds and angular velocities of individual particles. △ Less

Submitted 5 October, 2016; originally announced October 2016.

Hyperfine-controlled domain-wall motion observed in real space and time

Authors: John N. Moore, Junichiro Hayakawa, Takaaki Mano, Takeshi Noda, Go Yusa

Abstract: We perform real-space imaging of propagating magnetic domains in the fractional quantum Hall system using spin-sensitive photoluminescence microscopy. The propagation is continuous and proceeds in the direction of the conventional current, i.e. opposite to the electron flow direction. The mechanism of motion is shown to be connected to polarized nuclear spins around the domain walls. The propagati… ▽ More We perform real-space imaging of propagating magnetic domains in the fractional quantum Hall system using spin-sensitive photoluminescence microscopy. The propagation is continuous and proceeds in the direction of the conventional current, i.e. opposite to the electron flow direction. The mechanism of motion is shown to be connected to polarized nuclear spins around the domain walls. The propagation velocity increases when nuclei are depolarized, and decreases when the source-drain current generating this nuclear polarization is increased. We discuss how these phenomena may arise from spin interactions along the domain walls. △ Less

Submitted 16 October, 2016; v1 submitted 15 September, 2016; originally announced September 2016.

Comments: 5 figures

Wavelength extension beyond 1.5 micrometer in symmetric InAs quantum dots on InP(111)A using droplet epitaxy

Authors: N. Ha, T. Mano, Y. -N. Wu, Y. -W. Ou, S. -J. Cheng, Y. Sakuma, K. Sakoda, T. Kuroda

Abstract: By using a C3v symmetric (111) surface as a growth substrate, we are able to achieve high structural symmetry in self-assembled quantum dots, which are suitable for use as quantum-entangled photon emitters. Here we report on the wavelength controllability of InAs dots on InP(111)A, which we realized by tuning the ternary alloy composition of In(Al,Ga)As barriers that were lattice-matched to InP. W… ▽ More By using a C3v symmetric (111) surface as a growth substrate, we are able to achieve high structural symmetry in self-assembled quantum dots, which are suitable for use as quantum-entangled photon emitters. Here we report on the wavelength controllability of InAs dots on InP(111)A, which we realized by tuning the ternary alloy composition of In(Al,Ga)As barriers that were lattice-matched to InP. We changed the peak emission wavelength systematically from 1.3 to 1.7 micrometer by barrier band gap tuning. The observed spectral shift agreed with the result of numerical simulations that assumed a measured shape distribution independent of barrier choice. △ Less

Submitted 22 July, 2016; originally announced July 2016.

Journal ref: Appl. Phys. Express 9, 101201 (2016)