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At least 199 records · Page 11

Development of a Half-Meter Scale Traveling-Wave (TW) SRF Cavity

While a demonstration of TW resonance excitation in the 3-cell structure in 2K liquid helium had been prepared and carried out at Fermilab in collaboration with Euclid Techlabs, the RF design process of 0.5~1 meter scale TW cavity was begun at Fermilab as the next step of TW development towards an accelerator-scale one. Considering the physical dimensions of existing SRF facilities (for fabrication, processing, and cryogenic testing), Fermilab has proposed a half-meter scale TW RF design consisting of a 7-cell structure and a power feedback waveguide (WG) loop. The WG loop design includes the new RF configurations for TW resonance control during a high-power operation. 1-year US-Japan collaboration program focused on EBW optimization for the TW shape iris joint within the narrow gap was awarded and the efforts has been made by Fermilab, Jlab, and KEK. 1-year LDRD program of Fermilab is awarded recently to fabricate a low-cost mockup of the WG loop with new RF configurations and validate them. Here we will present a preliminary 7-cell TW RF design and will report the progress and challenges through the programs awarded.

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SBND Cryogenics Ignition Screenshots

The slides are screenshots of a project created with the Ignition software platform by Inductive Automation for the Short-Baseline Near Detector (SBND). They depict the human-machine interface (HMI) for the experiment’s cryogenic system. As the HMI itself is not of a format that may be converted to PDF or similar document, these slides present a comprehensive set of screenshots of all windows within the HMI that may be publicly presented.

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Smart Pixel Sensors for the HL-LHC

Large-scale particle physics experiments produce tens of terabytes of data every second. Innovative methods to manage the data rate at the HL-LHC, which expects to operate at 10x the luminosity of what the LHC was initially designed for, are needed. AI-on the chip provides a way to intelligently filter out low momentum clusters in the pixel detector. This will open up an opportunity to use the pixel detector for the first time in the CMS Level-1 trigger, and lead to increased sensitivity to new physics measurements and searches. We have taped out our first chip, which incorporates a $p_T$ filtering algorithm on an ASIC chip. Our initial $p_T$ filtering algorithm considers clusters that are tracked by CMS. We will report on ongoing studies seeking to enhance the performance of our filter by utilizing unsupervised learning on untracked clusters, thus increasing background rejection.

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Computational Exploration of High Entropy Alloys as Promising Materials for Future Beam Windows

With the ever-increasing demand for high beam power, the currently used beam-intercepting devices (BIDs) such as targets, and beam windows may not be able to handle the high power required for future accelerator complexes or the lifetime may be reduced drastically. As beam power increases, the damage incurred by BIDs, including thermal shock, fatigue, and irradiation damage, also rises. Therefore, it is imperative to design materials that can withstand high beam power for longer lifetimes. High entropy alloys (HEAs) have emerged as potential alternative materials for designing next-generation BIDs. In this study, we primarily focus on materials for developing beam windows for next-generation accelerator complexes. We propose an integrated approach that combines various computational techniques to study and design new materials. Specifically, we use CALPHAD, density functional theory (DFT), and molecular dynamics (MD) to comprehensively investigate the defect properties of suitable HEAs, offering potential alternatives for future beam windows. We begin by scanning the extensive phase space provided by Cr-Mn-V-Ti-Al-Co HEAs, selecting 8 compositions after evaluating approximately 120,000 unique compositions using CALPHAD. We, then employ DFT-informed machine learning techniques to develop force-field parameters. Finally, MD simulations using these developed force-field parameters will be used to study the effects of radiation damage on the defect and mechanical properties of the selected alloys. This research explains the use of the CALPHAD approach and shows how critical modeling (DFT and MD) is in developing novel material such as HEAs. It also highlights the promising role of machine learning in this field. The results from this study will greatly improve the novel materials development to be used in next-generation accelerator components, leading to higher beam power and longer operational times of BIDs.

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Three-Flavor Neutrino Oscillations at NOvA

NOvA, is a two-detector, long-baseline neutrino oscillation experiment located at Fermilab, Batavia, IL, USA. It is designed primarily to constrain neutrino oscillation parameters such as the atmospheric mass squared splitting, $\Delta m^2_{32}$, the mixing angle, $\theta_{23}$, neutrino mass hierachy, and the CP-violating phase, $\delta_{CP}$, using $\nu_\mu \ (\bar{\nu}_\mu)$ disappearance and $\nu_e \ (\bar{\nu}_e)$ appearance data. NOvA receives a high purity 900 KW instense beam of neutrinos and anti-neutrinos from Fermilab's Neutrinos at Main Injector (NuMI) beamline. NOvA used functionally identical finely granulated liquid scintillation detectors, both situated 14.6 mrad off-axis to the beam direction. The NOvA near detector observes un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and beam $\nu_e \ (\bar{\nu}_e)$ events, while the far detector, which is situated 809 km away from the near detector, records un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and oscillated $\nu_e \ (\bar{\nu}_e)$ events. We will discuss the neutrino oscillation analysis strategy at NOvA and the latest three-flavor oscillation results from 10 years of NOvA data in this talk.

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Real-Time Anomaly Detection for Charge-Based Triggering in LArTPCs

Modern particle detectors, including liquid argon time projection chambers (LArTPCs), collect a vast amount of data, making it impractical to save everything for offline analysis. As a result, these experiments need to employ different down-selection techniques during data acquisition, referred to as triggering. In this talk, I will present a framework that would enable real-time, data-driven triggering for LArTPCs, using anomaly detection algorithms implemented on Field-Programmable Gate Arrays (FPGAs). Drawing on a study that makes use of collected charge data from the MicroBooNE LArTPC Public Dataset, I will discuss the overall performance of such algorithms and potential applications for future neutrino experiments.

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ICARUS at the Short-Baseline Neutrino Program: First Results

First results from ICARUS experiment are presented at FNAL. The selection of nu_mu CC events with 1muon+ N Protons from BNB targeted at numu disappearance analysis is presented for a subset of the collected statistics, , compared with MC predictions. A similar selection of nu_mu CC events 1muon+ N Protons + 0 pions in the NuMI beam aiming at the neutrino-Argon cross section measurement is also presented, together with a control sideband requiring in addition at least a pion candidate. Finally the result of a BSM search for a new particle decaying into two muons is also presented, showing no evidence within the studied sample of new physics.

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Predicting Missing Regions in Charged Particle Tracks Using a Sparse 3D Convolutional Neural Network

The 2x2 Demonstrator is a prototype detector for the Deep Underground Neutrino Experiment (DUNE)'s Near Detector. Both the 2x2 Demonstrator and the Near Detector itself will have inactive regions wherein there is no sensitivity to charge deposition and light signals that arise from charged particle interactions with liquid argon. In the 2x2, these inactive regions are positioned in-between the active detector modules, which introduces the challenge of inferring what charge signals ought to look like in these regions. This study explores the use of a Sparse 3D Convolutional Neural Network (ConvNet) to infer missing regions in charged particle tracks. Hits corresponding to energy depositions are voxelized into a three-dimensional (3D) grid for each track. Inactive regions within the tracks are replaced with a dense, rectangular 3D grid of voxels, ensuring consistent step sizes in X, Y, and Z directions. Voxels in these dense regions are initialized with an energy value of -1, indicating nonphysical energy or charge. The model is trained to predict which voxels should activate as part of the track and which should not, with the goal of eventually inferring the missing charge or energy values in these voxels. Results indicate that the model accurately predicts track voxels within ±1 unit in X, Y, or Z directions and effectively identifies non-track voxels, despite some overprediction. The approach shows promise in prediction of missing track regions with some accuracy.

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The Icarus Experiment at Fermilab

In these slides I will present the ICARUS experiment at FNAL within the SBN program and I will briefly describe some of the most recent results.

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SBND Analysis using ML Reconstruction Chain

As part of the Short Baseline Neutrino (SBN) Program at Fermilab, the Short Baseline Near Detector (SBND) is positioned in the Booster Neutrino Beam (BNB) and explores neutrino-argon interactions with unprecedented statistics. SBND is a Liquid Argon Time Projection Chamber (LArTPC). Electrons produced through ionization drift toward three wire planes, providing signals that form 2D images of particle trajectories. I introduce the Scalable Particle Imaging using Neural Embeddings (SPINE) framework, which employs a Machine Learning (ML)-based 3D reconstruction using a series of neural networks. Here, we present SPINE’s reconstruction chain, analysis approaches, and results from our latest simulation samples.

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Optimal Transport for e/$\pi^0$ Particle Classification in LArTPC Neutrino Experiments

Separation of electron signals from $\pi^0$ backgrounds is crucial for neutrino oscillation measurements and searches for Beyond Standard Model (BSM) physics in current and future Liquid Argon Time Projection Chamber (LArTPC) experiments. e/$\pi^0$ separation has been a reconstruction challenge since both e and $\pi^0$ present as electromagnetic showers, and often only one out of the two showers produced by $\pi^0$ is reconstructed correctly. This research aims to improve the performance of e/$\pi^0$ separation using optimal transport (OT), by leveraging on the topological differences in the showers produced by the two particles. OT is a method which compares two distributions by finding the most efficient way to transform, or “move” from one to the other. This work uses the MicroBooNE open samples public dataset to test the e/$\pi^0$ separation performance of the method on events which incorporate realistic modeling of LArTPC detector response. Reconstructed 3D energy deposits are projected onto a plane perpendicular to the primary shower, allowing OT to better detect the topological differences between the two types of particles without the need to separately reconstruct all the showers in the events. Different distance metrics for OT are tested and preliminary results on e/$\pi^0$ separation are presented.

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SBND In 10 Minutes

The Short-Baseline Near Detector (SBND) is one of three Liquid Argon Time Projection Chamber (LArTPC) neutrino detectors positioned along the axis of the Booster Neutrino Beam (BNB) at Fermilab, as part of the Short-Baseline Neutrino (SBN) Program. The detector is currently being commissioned and is expected to take neutrino data this year. SBND is characterized by superb imaging capabilities and will record over a million neutrino interactions per year. Thanks to its unique combination of measurement resolution and statistics, SBND will carry out a rich program of neutrino interaction measurements and novel searches for physics beyond the Standard Model (BSM). It will enable the potential of the overall SBN sterile neutrino program by performing a precise characterization of the unoscillated event rate, and constraining BNB flux and neutrino-argon cross-section systematic uncertainties. In this talk, the physics reach, current status, and future prospects of SBND are discussed.

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Towards Field Emission Free Cavity Processing and String Assembly at Fermilab

Cavities and cryomodules assembled at Fermilab have demonstrated unprecedented field emission (FE) free gradients. However, consistent FE-free performance is not guaranteed. Many lessons were learned, and continued vigilance is a must. In addition, several improvements have been identified to further push the state-of-the-art low particulate cavity processing and assembly at Fermilab. Those included the optimization of nitrogen flow, robotic-assisted assembly, and low-particulate fasteners. We share our latest results and vision for the future clean assemblies of cavities and cryomodule strings.

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Rapid-cycling HTS magnet for muon acceleration

A very wide range of operational temperatures of the HTS (YBCO) superconductor makes it suitable for the construction of rapid-cycling magnets required for the muon acceleration. The measured [3] very low power loss of the 0.4 T magnet operating at 300 T/s suggested a realistic possibility of the HTS-based accelerator magnet with much higher magnetic field and ramp rate. The magnet core and the HTS cable designs for the 2 T field in the 30 mm beam gap are presented. The simulation of the HTS cable hysteresis power loss for the 1000 T/s ramp rate is discussed in terms of the operational temperatures and required cryogenic power.

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Fermilab Neutrino Program – Accelerators & Experiments

We provide an overview of the Fermilab neutrino program, including details for both the accelerator and experiment aspect of the program. On the accelerator side, the current operation of the proton complex is presented, alongside the status of the upcoming PIP-II upgrade and the newly proposed ACE-MIRT upgrade. On the detector side, the SBN and NOVA programs are presented, as well as the status of the upcoming DUNE/LBNF upgrade. The Fermilab neutrino program planning is contextualized in terms of the recent P5 report, as well as ongoing discussions on future flavor and collider programs.

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Calibration and Timing Performance of the Light Detection System in the ICARUS Detector

ICARUS is the largest Liquid Argon Time Projection Chamber (LArTPC) in operation and serves as the Far Detector of the Short Baseline Neutrino (SBN) program at Fermilab. It aims to investigate the possible existence of sterile neutrinos with $\Delta m^2 \approx \SI{1}{eV^2}$ using the Booster Neutrino Beam (BNB) and explore physics beyond the Standard Model with the Neutrinos at the Main Injector (NuMI) beam. The ICARUS light detection system, comprising 360 TPB-coated large-area Photo-Multiplier Tubes (PMTs), is crucial for triggering and event reconstruction. Due to its shallow installation, the detector is exposed to a high flux of cosmic rays, necessitating precise timing to reject background events and align neutrino interactions with the beam time profile. This talk will detail the timing inter-calibration procedures for the ICARUS light detection system, which achieve sub-nanosecond resolution. Additionally, the performance of the system in reconstructing the timing of neutrino interactions from the BNB and NuMI beams will be discussed. The results highlight the effectiveness of the ICARUS light detection system in enhancing the detector's capability for precise and reliable neutrino selection.

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Beam Optics Design of A Prototype 20 kW Conduction-Cooled SRF Accelerator for Medical Sterilization

Superconducting technology has significantly advanced the capabilities of particle accelerators, facilitating higher beam-power operations for fundamental research at a comparatively lower cost. However, the conventional implementation of superconducting technology introduces complexities in the form of cryogenic plants, cryogenic distribution systems and substantial construction and operational cost. In response to these challenges, recent research efforts at Fermilab have been dedicated to the development of a cryogen-free, conduction-cooled Nb3Sn-based superconducting technology. This paper outlines the beam optics design of a 20-kW conduction-cooled compact superconducting accelerator for medical sterilization. The paper reviews both the physics and practical constraints associated with high beam-power operation within the context of industrial applications. The focus is on providing insights into the potential of this innovative technology to overcome existing challenges and pave the way for more accessible and efficient industrial particle accelerators.

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On the Life Expectancy Ot High-power CW Magnetrons for Superconducting Accelrators

Modern CW or pulse Superconducting RF (SRF) accelerators require efficient RF sources controllable in phase and power with a reduced cost. Therefore, utilization of the high-power CW magnetrons as RF sources in SRF accelerator projects was proposed in a number of works, e.g., [1, 2]. But typically, the CW magnetrons are designed as RF sources for industrial heating, and the lifetime of the tubes is not the first priority as it is required for high-energy accelerators. The high-power industrial CW magnetrons use the cathodes made of pure tungsten. The emission properties of the tungsten cathodes are not deteriorated much by electron and ion bombardments, but the latter causes sputtering of the cathode in the magnetron crossed fields. The sputtered cathode material covers the magnetron interior. This leads to sparks and discharges that limit the life of the magnetrons. We considered an analysis of magnetron failure modes vs. output power [3]. We developed a model of ionization of the residual gas in the magnetrons interaction space and simulated the spattering of the cathode in 100 kW CW magnetrons to estimate the life expectancy. Basing on results we proposed ways to increase the CW magnetrons longevity for SRF accelerators.

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