Tootfinder

Experiences with Model Context Protocol Servers for Science and High Performance Computing
Haochen Pan, Ryan Chard, Reid Mello, Christopher Grams, Tanjin He, Alexander Brace, Owen Price Skelly, Will Engler, Hayden Holbrook, Song Young Oh, Maxime Gonthier, Michael Papka, Ben Blaiszik, Kyle Chard, Ian Foster
https://arxiv.org/abs/2508.18489

Experiences with Model Context Protocol Servers for Science and High Performance Computing
Large language model (LLM)-powered agents are increasingly used to plan and execute scientific workflows, yet most research cyberinfrastructure (CI) exposes heterogeneous APIs and implements security models that present barriers for use by agents. We report on our experience using the Model Context Protocol (MCP) as a unifying interface that makes research capabilities discoverable, invokable, and composable. Our approach is pragmatic: we implement thin MCP servers over mature services, includi…

Bidirectional anisotropic solar energetic particle events observed by Solar Orbiter
Zheyi Ding, Robert F. Wimmer-Schweingruber, Yu Chen, Lingling Zhao, Alexander Kollhoff, Patrick K\"uhl, Liu Yang, Lars Berger, Verena Heidrich-Meisner, Javier Rodriguez-Pacheco, George C. Ho, Glenn M. Mason, Gang Li, Tom\'a\v{s} Form\'anek, Christopher J. Owen
https…

Bidirectional anisotropic solar energetic particle events observed by Solar Orbiter
Solar Energetic Particle (SEP) events are critical for understanding particle acceleration and transport in the heliosphere. While most SEP events involve outward streaming particles along open magnetic field lines, bidirectional events characterized by simultaneous sunward and anti-sunward particle flows offer unique insights into magnetic field topology and the interplay of multiple acceleration sources. We aim to investigate the origin and transport of energetic particles in two rare bidirec…

JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
Zhiqiang Que, Chang Sun, Sudarshan Paramesvaran, Emyr Clement, Katerina Karakoulaki, Christopher Brown, Lauri Laatu, Arianna Cox, Alexander Tapper, Wayne Luk, Maria Spiropulu
https://arxiv.org/abs/2508.15468

JEDI-linear: Fast and Efficient Graph Neural Networks for Jet Tagging on FPGAs
Graph Neural Networks (GNNs), particularly Interaction Networks (INs), have shown exceptional performance for jet tagging at the CERN High-Luminosity Large Hadron Collider (HL-LHC). However, their computational complexity and irregular memory access patterns pose significant challenges for deployment on FPGAs in hardware trigger systems, where strict latency and resource constraints apply. In this work, we propose JEDI-linear, a novel GNN architecture with linear computational complexity that e…

Enhancement of Indistinguishable Photon Emission from a GaAs Quantum Dot via Charge Noise Suppression
Priyabrata Mudi, Avijit Barua, Kartik Gaur, Steffen Wilksen, Alexander Steinhoff, Setthanat Wijitpatima, Sarthak Tripathi, Julian Ritzmann, Andreas D. Wieck, Sven Rodt, Christopher Gies, Arne Ludwig, Stephan Reitzenstein
https://

Enhancement of Indistinguishable Photon Emission from a GaAs Quantum Dot via Charge Noise Suppression
The generation of indistinguishable single photons is a fundamental requirement for future quantum technologies, particularly in quantum repeater networks and for distributed quantum computing based on entanglement distribution. However, spectral jitter, often induced by charge noise in epitaxial quantum dots, leads to exciton dephasing, thereby limiting their practical usage in quantum applications. We present a straightforward approach to mitigate charge noise-induced decoherence in droplet-e…

SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction
Alexander Scarlatos, Nigel Fernandez, Christopher Ormerod, Susan Lottridge, Andrew Lan
https://arxiv.org/abs/2507.05129

SMART: Simulated Students Aligned with Item Response Theory for Question Difficulty Prediction
Item (question) difficulties play a crucial role in educational assessments, enabling accurate and efficient assessment of student abilities and personalization to maximize learning outcomes. Traditionally, estimating item difficulties can be costly, requiring real students to respond to items, followed by fitting an item response theory (IRT) model to get item difficulty estimates. This approach cannot be applied to the cold-start setting for previously unseen items either. In this work, we pr…

The relative index in coarse index theory and submanifold obstructions to uniform positive scalar curvature
Alexander Engel, Christopher Wulff
https://arxiv.org/abs/2506.14301

The relative index in coarse index theory and submanifold obstructions to uniform positive scalar curvature
We provide a coarse version of the relative index of Gromov and Lawson and thoroughly establish all of its basic properties. As an application, we discuss a general procedure to construct wrong way maps on the $K$-theory of the Roe algebra mapping the coarse index class of the Dirac operator of a manifold to the one of a suitably embedded submanifold of arbitrary codimension, thereby establishing an abstract machinery to find obstructions to uniform positive scalar curvature coming from these s…

Second public data release of the FIRE-2 cosmological zoom-in simulations of galaxy formation
Andrew Wetzel, Jenna Samuel, Pratik J. Gandhi, Sam B. Ponnada, Kung-Yi Su, Arpit Arora, Daniel Angles-Alcazar, Christopher C. Hayward, Robyn E. Sanderson, Robert Feldmann, Rachel Cochrane, Farnik Nikakhtar, Nondh Panithanpaisal, Jose A. Benavides, Viraj Pandya, Mike Grudic, Cameron Hummels, Alexander B. Gurvich, Zachary Hafen, Xiangcheng Ma, Shea Garrison-Kimmel, Omid Sameie, T. K Chan, Kareem…

Second public data release of the FIRE-2 cosmological zoom-in simulations of galaxy formation
We describe the second data release (DR2) of the FIRE-2 cosmological zoom-in simulations of galaxy formation, from the Feedback In Realistic Environments (FIRE) project, available at http://flathub.flatironinstitute.org/fire. DR2 includes all snapshots for most simulations, starting at z ~ 99, with all snapshot time spacings <~ 25 Myr. The Core suite -- comprising 14 Milky Way-mass galaxies, 5 SMC/LMC-mass galaxies, and 4 lower-mass galaxies -- includes 601 snapshots to z = 0. For the Core suit…

Reaching extreme fields in laser-electron beam collisions with XUV laser light
Brandon K. Russell, Christopher P. Ridgers, Stepan S. Bulanov, Kyle G. Miller, Christopher Arran, Thomas G. Blackburn, Sergei V. Bulanov, Gabriele M. Grittani, John P. Palastro, Qian Qian, Alexander G. R. Thomas
https://arxiv.org/abs/2506.01727…

Reaching extreme fields in laser-electron beam collisions with XUV laser light
Plasma-based particle accelerators promise to extend the revolutionary work performed with conventional particle accelerators to studies with smaller footprints, lower costs, and higher energies. Here, we propose a new approach to access an unexplored regime of strong-field quantum electrodynamics by plasma wakefield acceleration of both charged particles and photons. Instead of using increasingly powerful accelerators and lasers, we show that photon acceleration of optical pulses into the extr…

Parallel FFTW on RISC-V: A Comparative Study including OpenMP, MPI, and HPX
Alexander Strack, Christopher Taylor, Dirk Pfl\"uger
https://arxiv.org/abs/2506.08653

Parallel FFTW on RISC-V: A Comparative Study including OpenMP, MPI, and HPX
Rapid advancements in RISC-V hardware development shift the focus from low-level optimizations to higher-level parallelization. Recent RISC-V processors, such as the SOPHON SG2042, have 64 cores. RISC-V processors with core counts comparable to the SG2042, make efficient parallelization as crucial for RISC-V as the more established processors such as x86-64. In this work, we evaluate the parallel scaling of the widely used FFTW library on RISC-V for MPI and OpenMP. We compare it to a 64-core AM…

The Concordance of Weak Lensing and Escape Velocity Mass Estimates for Galaxy Clusters
Alexander Rodriguez, Christopher J. Miller
https://arxiv.org/abs/2507.20938 https://

The Concordance of Weak Lensing and Escape Velocity Mass Estimates for Galaxy Clusters
In the $Λ$CDM paradigm, the masses of the galaxy clusters inferred using background galaxies via weak-lensing shear should agree with the masses measured using the galaxy projected radius-velocity phase-space data via the escape velocity profile. However, prior work indicates that the correlation between caustic-inferred escape masses and weak lensing masses is statistically consistent with zero. Based on recent advancements in the measurement of the escape edge and its physical interpretation…

Managing, Analyzing and Sharing Research Data with Gen3 Data Commons
Craig Barnes, Kyle Burton, Michael S. Fitzsimons, Hara Prasad Juvvala, Brienna Larrick, Christopher Meyer, Pauline Ribeyre, Ao Liu, Clint Malson, Noah Metoki-Shlubsky, Andrii Prokhorenkov, Jawad Qureshi, Radhika Reddy, L. Philip Schumm, Mingfei Shao, Trevar Simmons, Alexander VanTol, Peter Vassilatos, Aarti Venkat, Robert L. Grossman

Managing, Analyzing and Sharing Research Data with Gen3 Data Commons
Gen3 is an open-source data platform for building data commons. A data commons is a cloud-based data platform for managing, analyzing, and sharing data with a research community. Gen3 has been used to build over a dozen data commons that in aggregate contain over 28 PB of data and 64 million FAIR data objects. To set up a Gen3 data commons, you first define a data model. Gen3 then autogenerates 1) a data portal for searching and exploring data in the commons; 2) a data portal for submitting dat…