Showing 1–22 of 22 results for author: Schulz, H

SimPoly: Simulation of Polymers with Machine Learning Force Fields Derived from First Principles

Authors: Gregor N. C. Simm, Jean Hélie, Hannes Schulz, Yicheng Chen, Guillem Simeon, Anna Kuzina, Ernesto Martinez-Baez, Piero Gasparotto, Gabriele Tocci, Chi Chen, Yatao Li, Lixue Cheng, Zun Wang, Bichlien H. Nguyen, Jake A. Smith, Lixin Sun

Abstract: Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses significant modeling challenges. Conventional force fields often lack the accuracy and transferability required to capture the intricate interactions governing polymer behavior. Conversely, quantum-chemical m… ▽ More Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses significant modeling challenges. Conventional force fields often lack the accuracy and transferability required to capture the intricate interactions governing polymer behavior. Conversely, quantum-chemical methods are computationally prohibitive for the large systems and long timescales required to simulate relevant polymer phenomena. Here, we overcome these limitations with a machine learning force field (MLFF) approach. We demonstrate that macroscopic properties for a broad range of polymers can be predicted ab initio, without fitting to experimental data. Specifically, we develop a fast and scalable MLFF to accurately predict polymer densities, outperforming established classical force fields. Our MLFF also captures second-order phase transitions, enabling the prediction of glass transition temperatures. To accelerate progress in this domain, we introduce a benchmark of experimental bulk properties for 130 polymers and an accompanying quantum-chemical dataset. This work lays the foundation for a fully in silico design pipeline for next-generation polymeric materials. △ Less

Submitted 15 October, 2025; originally announced October 2025.

DANRA: The Kilometer-Scale Danish Regional Atmospheric Reanalysis

Authors: Xiaohua Yang, Carlos Peralta, Bjarne Amstrup, Kasper Stener Hintz, Søren Borg Thorsen, Leif Denby, Simon Kamuk Christiansen, Hauke Schulz, Sebastian Pelt, Mathias Schreiner

Abstract: The DANish regional atmospheric ReAnalysis (DANRA) is a novel high-resolution (2.5 km) reanalysis dataset covering Denmark and its surrounding regions over a 34-year period (1990-2023). Denmark's complex coastline, with over 400 islands and an extensive 7,400 km coastline, means that most municipalities experience mixed land-sea variability. This complexity requires a regional climate reanalysis t… ▽ More The DANish regional atmospheric ReAnalysis (DANRA) is a novel high-resolution (2.5 km) reanalysis dataset covering Denmark and its surrounding regions over a 34-year period (1990-2023). Denmark's complex coastline, with over 400 islands and an extensive 7,400 km coastline, means that most municipalities experience mixed land-sea variability. This complexity requires a regional climate reanalysis that can resolve fine-scale coastal and inland features, as well as their impact on climate variability. DANRA is based on the HARMONIE-AROME Numerical Weather Prediction (NWP) model and assimilates a comprehensive set of observations, with a particular focus on Denmark. Compared to global reanalyses such as the ECMWF Reanalysis v5 (ERA5), DANRA demonstrates superior performance in representing essential climate variables, including near-surface weather parameters during both extreme and ordinary conditions. We illustrate these improvements in the representation of several extreme weather cases over Denmark, such as the December 1999 hurricane-force storm, the July 2022 national temperature record, and the August 2007 cloudburst in South Jutland. DANRA is made to support climate adaptation, impact modelling, and the training of next-generation data-driven atmospheric forecasting models. DANRA is distributed as Zarr dataset freely accessible from an object store, maximizing its usability for climate adaptation, impact modelling, and data-driven research. △ Less

Submitted 6 October, 2025; originally announced October 2025.

Understanding multi-fidelity training of machine-learned force-fields

Authors: John L. A. Gardner, Hannes Schulz, Jean Helie, Lixin Sun, Gregor N. C. Simm

Abstract: This study systematically investigates two multi-fidelity strategies used to train machine-learned force fields (MLFFs) -- pre-training/fine-tuning and multi-headed training -- and elucidates the mechanisms underpinning their success. For pre-training and fine-tuning, we uncover a log-log linear relationship between pre-trained and fine-tuned accuracies that holds across model architectures, model… ▽ More This study systematically investigates two multi-fidelity strategies used to train machine-learned force fields (MLFFs) -- pre-training/fine-tuning and multi-headed training -- and elucidates the mechanisms underpinning their success. For pre-training and fine-tuning, we uncover a log-log linear relationship between pre-trained and fine-tuned accuracies that holds across model architectures, model sizes, and quantum-chemical methods. The success of this approach hinges on the quantity and quality of available pre-training data, and, critically, the inclusion of force labels. We demonstrate that pre-trained representations are inherently method-specific, requiring adaptation of the model backbone during fine-tuning. In contrast, multi-headed models learn method-independent backbone representations, where again the heads' accuracies are log-log linearly related. Relative to pre-training and fine-tuning, these shared representations marginally reduce model performance in most cases. However, this trade-off is offset by practical advantages: multi-headed training extends naturally to multiple labelling methods and enables partial replacement of expensive labels with cheaper alternatives, paving the way towards cost-efficient universal MLFFs. △ Less

Submitted 2 April, 2026; v1 submitted 17 June, 2025; originally announced June 2025.

The QTF-Backbone: Proposal for a Nationwide Optical Fibre Backbone in Germany for Quantum Technology and Time and Frequency Metrology

Authors: Tara Cubel Liebisch, Peter Kaufmann, Harald Schnatz, Susanne Naegele-Jackson, Jochen Kronjäger, Klaus Blaum, Stefan Kück, Dieter Meschede, Stephan Schiller, Laura Agazzi, Soroosh Alighanbari, Joachim Ankerhold, Georgy V. Astakhov, Stefanie Barz, Ingo Baumann, Rainer Baumgart, Christoph Becher, Hendrik Bekker, Oliver Benson, Paolo Bianco, Ronald Bieber, Immanuel Bloch, Ulrike Blumröder, Rainer Bockholt, Johannes Bouman , et al. (144 additional authors not shown)

Abstract: The recent breakthroughs in the distribution of quantum information and high-precision time and frequency (T&F) signals over long-haul optical fibre networks have transformative potential for physically secure communications, resilience of timing infrastructure (such as that supporting Global Navigation Satellite Systems (GNSS)) and fundamental physics. To date, these capabilities remain confined… ▽ More The recent breakthroughs in the distribution of quantum information and high-precision time and frequency (T&F) signals over long-haul optical fibre networks have transformative potential for physically secure communications, resilience of timing infrastructure (such as that supporting Global Navigation Satellite Systems (GNSS)) and fundamental physics. To date, these capabilities remain confined to isolated testbeds, with quantum and T&F signals accessible, for example in Germany, to only a few institutions. In this white paper we propose the QTF Backbone: a dedicated national fibre-optic infrastructure in Germany for the networked distribution of Quantum and T&F signals using dark fibres and specialised hardware. The QTF Backbone is planned as a four-phase deployment over ten years to ensure scalable, sustainable access for research institutions and industry. The concept builds on successful demonstrations of time and frequency distribution at high Technology Readiness Levels (TRLs) across Europe, including PTB-MPQ links in Germany, REFIMEVE in France, and the Italian LIFT network. The QTF Backbone will enable transformative Research and Development (R&D), support a nationwide QTF ecosystem, and ensure the transition from innovation to deployment. As a national and European hub, it will position Germany and Europe at the forefront of quantum networking, as well as T&F transfer. △ Less

Submitted 16 August, 2026; v1 submitted 4 June, 2025; originally announced June 2025.

Comments: 60 pages, 7 figures This version of the article has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: https://doi.org/10.1140/epjs/s11734-026-02451-3

Journal ref: Liebisch, T.C., Kaufmann, P., Schnatz, H. et al. The QTF Backbone: proposal for a nationwide optical fibre backbone in Germany for quantum technology and time and frequency metrology. Eur. Phys. J. Spec. Top. 235, 3353-3387 (2026)

Path of a pair of deformable bubbles rising initially in line and close to a vertical wall

Authors: Haochen Huang, Pengyu Shi, Nina Elkina, Henrik Schulz, Jie Zhang

Abstract: It is known that in an unbounded fluid, the inline configuration of a freely rising bubble pair is often unstable with respect to lateral disturbances. This work numerically examines the stability of this configuration in the presence of a nearby vertical wall. The focus is on moderately inertial regimes, where two bubbles rising initially in line typically separate laterally from each other under… ▽ More It is known that in an unbounded fluid, the inline configuration of a freely rising bubble pair is often unstable with respect to lateral disturbances. This work numerically examines the stability of this configuration in the presence of a nearby vertical wall. The focus is on moderately inertial regimes, where two bubbles rising initially in line typically separate laterally from each other under unbounded conditions. In the presence of the wall, our results indicate that while the path of the bubble pair predominantly separates laterally, the plane of separation largely depends on the wall bubble interaction. This interaction involves a competition between two distinct effects, with the dominance determined by the ratios of buoyancy to viscous and buoyancy to capillary forces, which define the Galilei (Ga) and Bond (Bo) numbers, respectively. When Bo is below a critical Ga-dependent threshold, irrotational effects dominate, initially stabilizing both bubbles near the wall until horizontal separation among them occurs in the wall parallel plane. Conversely, at higher Bo, vortical effects dominate such that both bubbles migrate away from the wall. During the departure, asymmetric interactions cause the wall normal velocities of the two bubbles to differ, leading to horizontal separation in the wall-normal plane. These two separation motions, both newly identified in the present study, are found to result from two distinct mechanisms: one associated with the shear flow generated in the gap separating the wall and the leading bubble, which attracts the trailing bubble toward the wall, and the other linked to vortex shedding from the leading bubble, which promotes the trailing bubble's faster escape from the wall. △ Less

Submitted 10 January, 2025; v1 submitted 25 November, 2024; originally announced November 2024.

VERTECS: A COTS-based payload interface board to enable next generation astronomical imaging payloads

Authors: Ezra Fielding, Victor H. Schulz, Keenan A. A. Chatar, Kei Sano, Akitoshi Hanazawa

Abstract: Due to advances in observation and imaging technologies, modern astronomical satellites generate large volumes of data. This necessitates efficient onboard data processing and high-speed data downlink. Reflecting this trend is the VERTECS 6U Astronomical Nanosatellite. Designed for the observation of Extragalactic Background Light (EBL), this mission is expected to generate a substantial amount of… ▽ More Due to advances in observation and imaging technologies, modern astronomical satellites generate large volumes of data. This necessitates efficient onboard data processing and high-speed data downlink. Reflecting this trend is the VERTECS 6U Astronomical Nanosatellite. Designed for the observation of Extragalactic Background Light (EBL), this mission is expected to generate a substantial amount of image data, particularly within the confines of CubeSat capabilities. This paper introduces the VERTECS Camera Control Board (CCB), an open-source payload interface board leveraging Commercial Off-The-Shelf (COTS) components, with a Raspberry Pi Compute Module 4 at its core. The VERTECS CCB hardware and software have been designed from the ground up to serve as the sole interface between the VERTECS bus system and astronomical imaging payload, while providing compute capability not usually seen in nanosatellites of this class. Responsible for mission data processing, it will facilitate high-speed data transfer from the imaging payload via gigabit Ethernet, while also providing a high-bitrate serial connection to the payload X-band transmitter for mission data downlink. Additional interfaces for secondary payloads are provided via USB-C and standard 15-pin camera connectors. The Raspberry Pi embedded within the VERTECS CCB operates on a standard Linux distribution, streamlining the software development process. Beyond addressing the current mission's payload control and data handling requirements, the CCB sets the stage for future missions with heightened data demands. Furthermore, it supports the adoption of machine learning and other compute-intensive applications in orbit. This paper delves into the development of the VERTECS CCB, offering insights into the design and validation of this next-generation payload interface, to ensure that it can survive the rigors of space flight. △ Less

Submitted 2 June, 2024; originally announced June 2024.

Comments: 10 pages, to be presented at SPIE Software and Cyberinfrastructure for Astronomy VIII

Journal ref: Software and Cyberinfrastructure for Astronomy VIII 13101 (2024) 131010J

The Forward Physics Facility at the High-Luminosity LHC

Authors: Jonathan L. Feng, Felix Kling, Mary Hall Reno, Juan Rojo, Dennis Soldin, Luis A. Anchordoqui, Jamie Boyd, Ahmed Ismail, Lucian Harland-Lang, Kevin J. Kelly, Vishvas Pandey, Sebastian Trojanowski, Yu-Dai Tsai, Jean-Marco Alameddine, Takeshi Araki, Akitaka Ariga, Tomoko Ariga, Kento Asai, Alessandro Bacchetta, Kincso Balazs, Alan J. Barr, Michele Battistin, Jianming Bian, Caterina Bertone, Weidong Bai , et al. (211 additional authors not shown)

Abstract: High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe Standard Mod… ▽ More High energy collisions at the High-Luminosity Large Hadron Collider (LHC) produce a large number of particles along the beam collision axis, outside of the acceptance of existing LHC experiments. The proposed Forward Physics Facility (FPF), to be located several hundred meters from the ATLAS interaction point and shielded by concrete and rock, will host a suite of experiments to probe Standard Model (SM) processes and search for physics beyond the Standard Model (BSM). In this report, we review the status of the civil engineering plans and the experiments to explore the diverse physics signals that can be uniquely probed in the forward region. FPF experiments will be sensitive to a broad range of BSM physics through searches for new particle scattering or decay signatures and deviations from SM expectations in high statistics analyses with TeV neutrinos in this low-background environment. High statistics neutrino detection will also provide valuable data for fundamental topics in perturbative and non-perturbative QCD and in weak interactions. Experiments at the FPF will enable synergies between forward particle production at the LHC and astroparticle physics to be exploited. We report here on these physics topics, on infrastructure, detector, and simulation studies, and on future directions to realize the FPF's physics potential. △ Less

Submitted 9 March, 2022; originally announced March 2022.

Comments: 429 pages, contribution to Snowmass 2021

Report number: UCI-TR-2022-01, CERN-PBC-Notes-2022-001, FERMILAB-PUB-22-094-ND-SCD-T, INT-PUB-22-006, BONN-TH-2022-04

The Forward Physics Facility: Sites, Experiments, and Physics Potential

Authors: Luis A. Anchordoqui, Akitaka Ariga, Tomoko Ariga, Weidong Bai, Kincso Balazs, Brian Batell, Jamie Boyd, Joseph Bramante, Mario Campanelli, Adrian Carmona, Francesco G. Celiberto, Grigorios Chachamis, Matthew Citron, Giovanni De Lellis, Albert De Roeck, Hans Dembinski, Peter B. Denton, Antonia Di Crecsenzo, Milind V. Diwan, Liam Dougherty, Herbi K. Dreiner, Yong Du, Rikard Enberg, Yasaman Farzan, Jonathan L. Feng , et al. (56 additional authors not shown)

Abstract: The Forward Physics Facility (FPF) is a proposal to create a cavern with the space and infrastructure to support a suite of far-forward experiments at the Large Hadron Collider during the High Luminosity era. Located along the beam collision axis and shielded from the interaction point by at least 100 m of concrete and rock, the FPF will house experiments that will detect particles outside the acc… ▽ More The Forward Physics Facility (FPF) is a proposal to create a cavern with the space and infrastructure to support a suite of far-forward experiments at the Large Hadron Collider during the High Luminosity era. Located along the beam collision axis and shielded from the interaction point by at least 100 m of concrete and rock, the FPF will house experiments that will detect particles outside the acceptance of the existing large LHC experiments and will observe rare and exotic processes in an extremely low-background environment. In this work, we summarize the current status of plans for the FPF, including recent progress in civil engineering in identifying promising sites for the FPF and the experiments currently envisioned to realize the FPF's physics potential. We then review the many Standard Model and new physics topics that will be advanced by the FPF, including searches for long-lived particles, probes of dark matter and dark sectors, high-statistics studies of TeV neutrinos of all three flavors, aspects of perturbative and non-perturbative QCD, and high-energy astroparticle physics. △ Less

Submitted 25 May, 2022; v1 submitted 22 September, 2021; originally announced September 2021.

Comments: revised version, accepted by Physics Reports

Report number: BNL-222142-2021-FORE, CERN-PBC-Notes-2021-025, DESY-21-142, FERMILAB-CONF-21-452-AE-E-ND-PPD-T, KYUSHU-RCAPP-2021-01, LU TP 21-36, PITT-PACC-2118, SMU-HEP-21-10, UCI-TR-2021-22

Journal ref: Phys. Rept. 968 (2022), 1-50

BROOD: Bilevel and Robust Optimization and Outlier Detection for Efficient Tuning of High-Energy Physics Event Generators

Authors: Wenjing Wang, Mohan Krishnamoorthy, Juliane Muller, Stephen Mrenna, Holger Schulz, Xiangyang Ju, Sven Leyffer, Zachary Marshall

Abstract: The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time-consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new… ▽ More The parameters in Monte Carlo (MC) event generators are tuned on experimental measurements by evaluating the goodness of fit between the data and the MC predictions. The relative importance of each measurement is adjusted manually in an often time-consuming, iterative process to meet different experimental needs. In this work, we introduce several optimization formulations and algorithms with new decision criteria for streamlining and automating this process. These algorithms are designed for two formulations: bilevel optimization and robust optimization. Both formulations are applied to the datasets used in the ATLAS A14 tune and to the dedicated hadronization datasets generated by the sherpa generator, respectively. The corresponding tuned generator parameters are compared using three metrics. We compare the quality of our automatic tunes to the published ATLAS A14 tune. Moreover, we analyze the impact of a pre-processing step that excludes data that cannot be described by the physics models used in the MC event generators. △ Less

Submitted 11 March, 2021; v1 submitted 9 March, 2021; originally announced March 2021.

Comments: 87 pages, Submission to SciPost

Apprentice for Event Generator Tuning

Authors: Mohan Krishnamoorthy, Holger Schulz, Xiangyang Ju, Wenjing Wang, Sven Leyffer, Zachary Marshall, Stephen Mrenna, Juliane Muller, James B. Kowalkowski

Abstract: Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and… ▽ More Apprentice is a tool developed for event generator tuning. It contains a range of conceptual improvements and extensions over the tuning tool Professor. Its core functionality remains the construction of a multivariate analytic surrogate model to computationally expensive Monte-Carlo event generator predictions. The surrogate model is used for numerical optimization in chi-square minimization and likelihood evaluation. Apprentice also introduces algorithms to automate the selection of observable weights to minimize the effect of mis-modeling in the event generators. We illustrate our improvements for the task of MC-generator tuning and limit setting. △ Less

Submitted 9 March, 2021; originally announced March 2021.

Comments: 9 pages, 2 figures, submitted to the 25th International Conference on Computing in High-Energy and Nuclear Physics

HL-LHC Computing Review: Common Tools and Community Software

Authors: HEP Software Foundation, :, Thea Aarrestad, Simone Amoroso, Markus Julian Atkinson, Joshua Bendavid, Tommaso Boccali, Andrea Bocci, Andy Buckley, Matteo Cacciari, Paolo Calafiura, Philippe Canal, Federico Carminati, Taylor Childers, Vitaliano Ciulli, Gloria Corti, Davide Costanzo, Justin Gage Dezoort, Caterina Doglioni, Javier Mauricio Duarte, Agnieszka Dziurda, Peter Elmer, Markus Elsing, V. Daniel Elvira, Giulio Eulisse , et al. (85 additional authors not shown)

Abstract: Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHC's success so far and continued development and optimisation will be critical in the future. The challenges are driven by an ambitious physics programme, notably the LHC accelerator upgrade to high-luminosity, HL-LHC, and the corresponding detector upgrades of ATLAS and CMS. In this doc… ▽ More Common and community software packages, such as ROOT, Geant4 and event generators have been a key part of the LHC's success so far and continued development and optimisation will be critical in the future. The challenges are driven by an ambitious physics programme, notably the LHC accelerator upgrade to high-luminosity, HL-LHC, and the corresponding detector upgrades of ATLAS and CMS. In this document we address the issues for software that is used in multiple experiments (usually even more widely than ATLAS and CMS) and maintained by teams of developers who are either not linked to a particular experiment or who contribute to common software within the context of their experiment activity. We also give space to general considerations for future software and projects that tackle upcoming challenges, no matter who writes it, which is an area where community convergence on best practice is extremely useful. △ Less

Submitted 31 August, 2020; originally announced August 2020.

Comments: 40 pages contribution to Snowmass 2021

Report number: HSF-DOC-2020-01

Challenges in Monte Carlo event generator software for High-Luminosity LHC

Authors: The HSF Physics Event Generator WG, :, Andrea Valassi, Efe Yazgan, Josh McFayden, Simone Amoroso, Joshua Bendavid, Andy Buckley, Matteo Cacciari, Taylor Childers, Vitaliano Ciulli, Rikkert Frederix, Stefano Frixione, Francesco Giuli, Alexander Grohsjean, Christian Gütschow, Stefan Höche, Walter Hopkins, Philip Ilten, Dmitri Konstantinov, Frank Krauss, Qiang Li, Leif Lönnblad, Fabio Maltoni, Michelangelo Mangano , et al. (16 additional authors not shown)

Abstract: We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics programme. This paper has been prepared by the HEP Software Foundation (HSF) Physics Event Generator Working Group as an input to the LHCC review of HL-LHC computing, which has started in May 2020. We review the main software and computing challenges for the Monte Carlo physics event generators used by the LHC experiments, in view of the High-Luminosity LHC (HL-LHC) physics programme. This paper has been prepared by the HEP Software Foundation (HSF) Physics Event Generator Working Group as an input to the LHCC review of HL-LHC computing, which has started in May 2020. △ Less

Submitted 18 February, 2021; v1 submitted 28 April, 2020; originally announced April 2020.

Comments: 20 pages; editors Andrea Valassi, Efe Yazgan and Josh McFayden; addressed additional comments by journal reviewers

Report number: CERN-LPCC-2020-002; FERMILAB-PUB-20-183-SCD-T; MCNET-20-15

Journal ref: Comput Softw Big Sci 5, 12 (2021)

Grid-based minimization at scale: Feldman-Cousins corrections for SBN

Authors: Holger Schulz, Marianette Wospakrik, Mark Ross-Lonergan, Guanqun Ge, Saba Sehrish, Marc Paterno, Jim Kowalkowski, Wes Ketchum, Georgia Karagiorgi

Abstract: We present a computational model for the construction of Feldman-Cousins (FC) corrections frequently used in High Energy Physics (HEP) analysis. The program contains a grid-based minimization and is written in C++. Our algorithms exploit vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by using DIY. We de… ▽ More We present a computational model for the construction of Feldman-Cousins (FC) corrections frequently used in High Energy Physics (HEP) analysis. The program contains a grid-based minimization and is written in C++. Our algorithms exploit vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by using DIY. We demonstrate the application to scale very well at High Performance Computing (HPC) sites. We use HDF5 in conjunction with HighFive to write results of the calculation to file. △ Less

Submitted 18 February, 2020; originally announced February 2020.

Report number: FERMILAB-PUB-20-069-SCD

Technical Proposal: FASERnu

Authors: FASER Collaboration, Henso Abreu, Marco Andreini, Claire Antel, Akitaka Ariga, Tomoko Ariga, Caterina Bertone, Jamie Boyd, Andy Buckley, Franck Cadoux, David W. Casper, Francesco Cerutti, Xin Chen, Andrea Coccaro, Salvatore Danzeca, Liam Dougherty, Candan Dozen, Peter B. Denton, Yannick Favre, Deion Fellers, Jonathan L. Feng, Didier Ferrere, Jonathan Gall, Iftah Galon, Stephen Gibson , et al. (47 additional authors not shown)

Abstract: FASERnu is a proposed small and inexpensive emulsion detector designed to detect collider neutrinos for the first time and study their properties. FASERnu will be located directly in front of FASER, 480 m from the ATLAS interaction point along the beam collision axis in the unused service tunnel TI12. From 2021-23 during Run 3 of the 14 TeV LHC, roughly 1,300 electron neutrinos, 20,000 muon neutri… ▽ More FASERnu is a proposed small and inexpensive emulsion detector designed to detect collider neutrinos for the first time and study their properties. FASERnu will be located directly in front of FASER, 480 m from the ATLAS interaction point along the beam collision axis in the unused service tunnel TI12. From 2021-23 during Run 3 of the 14 TeV LHC, roughly 1,300 electron neutrinos, 20,000 muon neutrinos, and 20 tau neutrinos will interact in FASERnu with TeV-scale energies. With the ability to observe these interactions, reconstruct their energies, and distinguish flavors, FASERnu will probe the production, propagation, and interactions of neutrinos at the highest human-made energies ever recorded. The FASERnu detector will be composed of 1000 emulsion layers interleaved with tungsten plates. The total volume of the emulsion and tungsten is 25cm x 25cm x 1.35m, and the tungsten target mass is 1.2 tonnes. From 2021-23, 7 sets of emulsion layers will be installed, with replacement roughly every 20-50 1/fb in planned Technical Stops. In this document, we summarize FASERnu's physics goals and discuss the estimates of neutrino flux and interaction rates. We then describe the FASERnu detector in detail, including plans for assembly, transport, installation, and emulsion replacement, and procedures for emulsion readout and analyzing the data. We close with cost estimates for the detector components and infrastructure work and a timeline for the experiment. △ Less

Submitted 9 January, 2020; originally announced January 2020.

Comments: 49 pages, 25 figures; submitted to the CERN LHCC on 28 October 2019

Report number: CERN-LHCC-2019-017, LHCC-P-015, UCI-TR-2019-25

Multivariate Rational Approximation

Authors: Anthony P. Austin, Mohan Krishnamoorthy, Sven Leyffer, Stephen Mrenna, Juliane Muller, Holger Schulz

Abstract: We present two approaches for computing rational approximations to multivariate functions, motivated by their effectiveness as surrogate models for high-energy physics (HEP) applications. Our first approach builds on the Stieltjes process to efficiently and robustly compute the coefficients of the rational approximation. Our second approach is based on an optimization formulation that allows us to… ▽ More We present two approaches for computing rational approximations to multivariate functions, motivated by their effectiveness as surrogate models for high-energy physics (HEP) applications. Our first approach builds on the Stieltjes process to efficiently and robustly compute the coefficients of the rational approximation. Our second approach is based on an optimization formulation that allows us to include structural constraints on the rational approximation, resulting in a semi-infinite optimization problem that we solve using an outer approximation approach. We present results for synthetic and real-life HEP data, and we compare the approximation quality of our approaches with that of traditional polynomial approximations. △ Less

Submitted 2 December, 2019; originally announced December 2019.

MSC Class: 2010 MSC: 41A20; 41A63; 65D15

Combining crowd-sourcing and deep learning to explore the meso-scale organization of shallow convection

Authors: Stephan Rasp, Hauke Schulz, Sandrine Bony, Bjorn Stevens

Abstract: Humans excel at detecting interesting patterns in images, for example those taken from satellites. This kind of anecdotal evidence can lead to the discovery of new phenomena. However, it is often difficult to gather enough data of subjective features for significant analysis. This paper presents an example of how two tools that have recently become accessible to a wide range of researchers, crowd-… ▽ More Humans excel at detecting interesting patterns in images, for example those taken from satellites. This kind of anecdotal evidence can lead to the discovery of new phenomena. However, it is often difficult to gather enough data of subjective features for significant analysis. This paper presents an example of how two tools that have recently become accessible to a wide range of researchers, crowd-sourcing and deep learning, can be combined to explore satellite imagery at scale. In particular, the focus is on the organization of shallow cumulus convection in the trade wind regions. Shallow clouds play a large role in the Earth's radiation balance yet are poorly represented in climate models. For this project four subjective patterns of organization were defined: Sugar, Flower, Fish and Gravel. On cloud labeling days at two institutes, 67 scientists screened 10,000 satellite images on a crowd-sourcing platform and classified almost 50,000 mesoscale cloud clusters. This dataset is then used as a training dataset for deep learning algorithms that make it possible to automate the pattern detection and create global climatologies of the four patterns. Analysis of the geographical distribution and large-scale environmental conditions indicates that the four patterns have some overlap with established modes of organization, such as open and closed cellular convection, but also differ in important ways. The results and dataset from this project suggests promising research questions. Further, this study illustrates that crowd-sourcing and deep learning complement each other well for the exploration of image datasets. △ Less

Submitted 21 April, 2020; v1 submitted 5 June, 2019; originally announced June 2019.

Aging renewal theory and application to random walks

Authors: Johannes H. P. Schulz, Eli Barkai, Ralf Metzler

Abstract: The versatility of renewal theory is owed to its abstract formulation. Renewals can be interpreted as steps of a random walk, switching events in two-state models, domain crossings of a random motion, etc. We here discuss a renewal process in which successive events are separated by scale-free waiting time periods. Among other ubiquitous long time properties, this process exhibits aging: events co… ▽ More The versatility of renewal theory is owed to its abstract formulation. Renewals can be interpreted as steps of a random walk, switching events in two-state models, domain crossings of a random motion, etc. We here discuss a renewal process in which successive events are separated by scale-free waiting time periods. Among other ubiquitous long time properties, this process exhibits aging: events counted initially in a time interval [0,t] statistically strongly differ from those observed at later times [t_a,t_a+t]. In complex, disordered media, processes with scale-free waiting times play a particularly prominent role. We set up a unified analytical foundation for such anomalous dynamics by discussing in detail the distribution of the aging renewal process. We analyze its half-discrete, half-continuous nature and study its aging time evolution. These results are readily used to discuss a scale-free anomalous diffusion process, the continuous time random walk. By this we not only shed light on the profound origins of its characteristic features, such as weak ergodicity breaking. Along the way, we also add an extended discussion on aging effects. In particular, we find that the aging behavior of time and ensemble averages is conceptually very distinct, but their time scaling is identical at high ages. Finally, we show how more complex motion models are readily constructed on the basis of aging renewal dynamics. △ Less

Submitted 3 October, 2013; originally announced October 2013.

Comments: 21 pages, 7 figures, RevTeX

Journal ref: Phys. Rev. X 4, 011028 (2014)

Comparison of Different Parallel Implementations of the 2+1-Dimensional KPZ Model and the 3-Dimensional KMC Model

Authors: Jeffrey Kelling, Géza Ódor, Máté Ferenc Nagy, Henrik Schulz, Karl-Heinz Heinig

Abstract: We show that efficient simulations of the Kardar-Parisi-Zhang interface growth in 2 + 1 dimensions and of the 3-dimensional Kinetic Monte Carlo of thermally activated diffusion can be realized both on GPUs and modern CPUs. In this article we present results of different implementations on GPUs using CUDA and OpenCL and also on CPUs using OpenCL and MPI. We investigate the runtime and scaling behav… ▽ More We show that efficient simulations of the Kardar-Parisi-Zhang interface growth in 2 + 1 dimensions and of the 3-dimensional Kinetic Monte Carlo of thermally activated diffusion can be realized both on GPUs and modern CPUs. In this article we present results of different implementations on GPUs using CUDA and OpenCL and also on CPUs using OpenCL and MPI. We investigate the runtime and scaling behavior on different architectures to find optimal solutions for solving current simulation problems in the field of statistical physics and materials science. △ Less

Submitted 25 July, 2012; v1 submitted 23 April, 2012; originally announced April 2012.

Comments: 14 pages, 8 figures, to be published in a forthcoming EPJST special issue on "Computer simulations on GPU"

Journal ref: The European Physical Journal - Special Topics 210, Number 1 (2012), 175-187

Current reversal and exclusion processes with history-dependent random walks

Authors: Johannes H. P. Schulz, Anatoly B. Kolomeisky, Erwin Frey

Abstract: A class of exclusion processes in which particles perform history-dependent random walks is introduced, stimulated by dynamic phenomena in some biological and artificial systems. The particles locally interact with the underlying substrate by breaking and reforming lattice bonds. We determine the steady-state current on a ring, and find current-reversal as a function of particle density. This phen… ▽ More A class of exclusion processes in which particles perform history-dependent random walks is introduced, stimulated by dynamic phenomena in some biological and artificial systems. The particles locally interact with the underlying substrate by breaking and reforming lattice bonds. We determine the steady-state current on a ring, and find current-reversal as a function of particle density. This phenomenon is attributed to the non-local interaction between the walkers through their trails, which originates from strong correlations between the dynamics of the particles and the lattice. We rationalize our findings within an effective description in terms of quasi-particles which we call front barriers. Our analytical results are complemented by stochastic simulations. △ Less

Submitted 28 April, 2011; originally announced April 2011.

Comments: 5 pages, 6 figures

Journal ref: Europhys. Lett. 95, 30004 (2011)

Simulation of 1+1 dimensional surface growth and lattices gases using GPUs

Authors: Henrik Schulz, Géza Ódor, Gergely Ódor, Máté Ferenc Nagy

Abstract: Restricted solid on solid surface growth models can be mapped onto binary lattice gases. We show that efficient simulation algorithms can be realized on GPUs either by CUDA or by OpenCL programming. We consider a deposition/evaporation model following Kardar-Parisi-Zhang growth in 1+1 dimensions related to the Asymmetric Simple Exclusion Process and show that for sizes, that fit into the shared me… ▽ More Restricted solid on solid surface growth models can be mapped onto binary lattice gases. We show that efficient simulation algorithms can be realized on GPUs either by CUDA or by OpenCL programming. We consider a deposition/evaporation model following Kardar-Parisi-Zhang growth in 1+1 dimensions related to the Asymmetric Simple Exclusion Process and show that for sizes, that fit into the shared memory of GPUs one can achieve the maximum parallelization speedup ~ x100 for a Quadro FX 5800 graphics card with respect to a single CPU of 2.67 GHz). This permits us to study the effect of quenched columnar disorder, requiring extremely long simulation times. We compare the CUDA realization with an OpenCL implementation designed for processor clusters via MPI. A two-lane traffic model with randomized turning points is also realized and the dynamical behavior has been investigated. △ Less

Submitted 30 March, 2011; v1 submitted 2 December, 2010; originally announced December 2010.

Comments: 20 pages 12 figures, 1 table, to appear in Comp. Phys. Comm

Journal ref: Computer Physics Communications 182 (2011) 1467-1476

New developments in event generator tuning techniques

Authors: Andy Buckley, Hendrik Hoeth, Heiko Lacker, Holger Schulz, Jan Eike von Seggern

Abstract: Data analyses in hadron collider physics depend on background simulations performed by Monte Carlo (MC) event generators. However, calculational limitations and non-perturbative effects require approximate models with adjustable parameters. In fact, we need to simultaneously tune many phenomenological parameters in a high-dimensional parameter-space in order to make the MC generator predictions fi… ▽ More Data analyses in hadron collider physics depend on background simulations performed by Monte Carlo (MC) event generators. However, calculational limitations and non-perturbative effects require approximate models with adjustable parameters. In fact, we need to simultaneously tune many phenomenological parameters in a high-dimensional parameter-space in order to make the MC generator predictions fit the data. It is desirable to achieve this goal without spending too much time or computing resources iterating parameter settings and comparing the same set of plots over and over again. We present extensions and improvements to the MC tuning system, Professor, which addresses the aforementioned problems by constructing a fast analytic model of a MC generator which can then be easily fitted to data. Using this procedure it is for the first time possible to get a robust estimate of the uncertainty of generator tunings. Furthermore, we can use these uncertainty estimates to study the effect of new (pseudo-) data on the quality of tunings and therefore decide if a measurement is worthwhile in the prospect of generator tuning. The potential of the Professor method outside the MC tuning area is presented as well. △ Less

Submitted 28 May, 2010; originally announced May 2010.

Comments: To appear in the proceedings of the 13th International Workshop on Advanced Computing and Analysis Techniques in Physics Research, ACAT2010, Jaipur, India, February 22-27, 2010

Journal ref: PoS ACAT2010:079,2010

Systematic event generator tuning for the LHC

Authors: Andy Buckley, Hendrik Hoeth, Heiko Lacker, Holger Schulz, Jan Eike von Seggern

Abstract: In this article we describe Professor, a new program for tuning model parameters of Monte Carlo event generators to experimental data by parameterising the per-bin generator response to parameter variations and numerically optimising the parameterised behaviour. Simulated experimental analysis data is obtained using the Rivet analysis toolkit. This paper presents the Professor procedure and impl… ▽ More In this article we describe Professor, a new program for tuning model parameters of Monte Carlo event generators to experimental data by parameterising the per-bin generator response to parameter variations and numerically optimising the parameterised behaviour. Simulated experimental analysis data is obtained using the Rivet analysis toolkit. This paper presents the Professor procedure and implementation, illustrated with the application of the method to tunes of the Pythia 6 event generator to data from the LEP/SLD and Tevatron experiments. These tunes are substantial improvements on existing standard choices, and are recommended as base tunes for LHC experiments, to be themselves systematically improved upon when early LHC data is available. △ Less

Submitted 17 July, 2009; originally announced July 2009.

Comments: 28 pages. Submitted to European Physical Journal C. Program sources and extra information are available from http://projects.hepforge.org/professor/

Report number: IPPP/09/52, DCPT/104/22, LU TP 09-18, HU-EP-09/33, MCnet/09/14

Journal ref: Eur.Phys.J.C65:331-357,2010