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At least 325 records · Page 18

Measured Dynamic Aperture and Detuning of Nonlinear Integrable Optics

One of the most promising advantages of nonlinear integrable optics is strong amplitude dependent tune shift without degrading the dynamic aperture. The integrable optics test accelerator (IOTA) at Fermilab is constructed around nonlinear lattice elements of the elliptical type as described by Danilov and Nagaitsev. Detuning and dynamic aperture scans in IOTA were performed using a fast dipole kicker and a low emittance electron beam. The evolution of the dynamic aperture and detuning for different configurations of the integrable optics lattice are presented.

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Multiphysics Simulations of Thermal Shock Testing of Nanofibrous High Power Targets

Increase of primary beam power for neutrino beam-lines leads to a reduced lifespan for production targets. The field of High Power Targetry (HPT) is generating new concepts to meet the need for robust targets. One idea being investigated by the HPT Research and Development Group at Fermilab is an electrospun nanofiber target. As part of their evaluation, samples with different densities were sent to the HiRadMat facility at CERN for thermal shock tests. The samples with the higher density, irradiated under a high intensity beam pulse, exhibit major damages at the impact site whereas those with the lower density show no apparent damages. The exact cause of this failure was unclear at the time. In this paper, we present the results of multiphysics simulations of the thermal shock experienced by the nanofiber targets that suggest the failure originates from the reduced permeability of the high density sample to airflow. The air present in the porous target expands due to heating from the beam, but is unable to flow freely in the high density sample, resulting in a larger back pressure that blows apart the mat. We close with a discussion on how to further validate this hypothesis.

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Adaptation of the Fermilab Proton Source to Support New Muon Facilities

he PIP-II proton accelerator will provide the intensity sufficient to power a new generation of high energy facilities at Fermilab. Extension of that linac to higher energy with following acceleration and bunching rings could provide the intensity needed to feed a muon production target for a high-energy $\mu^{+} - \mu^{-}$ collider. Scenarios using a rapid-cycling synchrotron or an $\sim$8 GeV Linac are presented and discussed. Some near-term opportunities at Fermilab for muon collider R&D are introduced.

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Fermilab Booster Beam Emittances from Quadrupole Modes Measured BPMs

The measurement of beam emittances by extracting the quadrupole mode signal from a 4 plate beam position monitor (BPM) was published at least 40 years ago. Unfortunately, in practice, this method suffers from poor signal to noise ratio and requires a lot of tuning to extract out the emittances. In this paper, an improved method where multiple BPMs are used together with better mathematical analysis is described. The BPM derived emittances are then compared with those measured by the Ion Profile Monitor (IPM). Surprisingly, the BPM measured emittances behave very well and are more realistic than those measured by the IPM.

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Quantitative Description and Correction of Longitudinal Drifts in the Fermilab Linac

The Fermilab Linac accepts the 0.75 MeV H- ions from the front end and accelerates them to 400 MeV for injection into the Booster. Day-to-day drifts of the longitudinal trajectory in the Linac, reconstructed from phase readings of Beam Position Monitors, are at the level of several degrees. They are believed to cause additional losses both in the Linac and Booster, and are addressed by empirically adjusting the phases of Linac cavities. This work explores the option of expressing these drifts in terms of phase shifts in two cavities at the low-energy part of the Linac. Such description allows for a simplified visual representation of the drifts, suggest a clear algorithm for their compensation, and provides a tool for estimating efficiency of such compensation.

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Bayesian Optimization Scheme for the Design of a Nanofibrous High Power Target

High Power Targetry (HPT) R\&D is critical in the context of increasing beam intensity and energy for next generation accelerators. Many target concepts and novel materials are being developed and tested for their ability to withstand extreme beam environments; the HPT R\&D Group at Fermilab is developing an electrospun nanofiber material for this purpose. The performance of these nanofiber targets is sensitive to their construction parameters, such as the packing density of the fibers. Lowering the density improves the survival of the target, but reduces the secondary particle yield. Optimizing the lifetime and production efficiency of the target poses an interesting design problem, and in this paper we study the applicability of Bayesian optimization to its solution. We first describe how to encode the nanofiber target design problem as the optimization of an objective function, and how to evaluate that function with computer simulations. We then explain the optimization loop setup. Thereafter, we present the optimal design parameters suggested by the algorithm, and close with discussions of limitations and future refinements.

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Development and Test of a Large Aperture $Nb_3Sn$ Cos-Theta Dipole Coil with Stress Management

An innovative stress-management (SM) concept for cos-theta (CT) coils (SMCT coil concept) has been proposed at Fermilab. A large-aperture two-layer Nb3Sn SMCT dipole coil was designed and manufactured to validate and test the SM concept including coil design, fabrication technology, and performance. The first large-aperture SMCT coil (SMCT1) was fabricated and assembled with a small-aperture Nb3Sn coil inside a dipole mirror magnet. SMCT1 coil tests in a dipole mirror structure was performed in two configurations - SMCTM1a with only powered two-layer SMCT1 coil and SMCTM1b with the SMCT coil connected in series with an inner two-layer dipole coil. The test goals are to prove the SMCT coil concept in two-layer and four-layer mirror configurations; demonstrate that the magnet can reach the targeted quench current at the established preload; study magnet training, training memory after thermal cycle, ramp rate and temperature dependences of the magnet quench current; and test the SMCT1 coil quench protection parameters. This paper summarizes the SMCT1 coil design and parameters, the coil main fabrication steps, its assembly in the dipole mirror structure. The results of the SMCTM1a/b mirror test are presented and discussed.

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Optimization Studies of Radiation Shielding for PIP-II Project at Fermilab

The Proton Improvement Plan-II (PIP-II) at Fermilab represents a significant advancement in the quest to answer some of the most profound questions about our universe using the world's most intense high-energy neutrino beam. The project requires the construction of a new addition to the Fermilab accelerator complex – an 800-MeV high-intensity superconducting linear accelerator. Ensuring the safety and regulatory compliance of this ambitious project is paramount, necessitating thorough dose rate assessments under both normal operational and accidental scenarios to align with the Fermilab Radiological Control Manual (FRCM) standards. Our approach included a shielding optimization used for the simulations with the Monte Carlo code MARS [1,2,3] to incorporate new magnet and collimator designs, essential for reflecting the current state of PIP-II infrastructure. The implementation of high-resolution detector planes, despite their computational demands, enabled us to gather detailed radiation field data crucial for optimizing shielding configurations. To overcome the significant computational demands, we developed a branching code that drastically reduced simulation runtimes while maintaining statistical integrity. This was achieved through geometry splitting and the application of Russian Roulette techniques, tailored to prioritize regions of interest based on predefined importances and weight limits.

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Data vs. MC Comparison of Light Signal from Cosmic Rays in the ICARUS Detectors

Currently, the ICARUS-T600 liquid argon TPC is collecting data exposed to Booster Neutrino and Numi off-axis beams within the SBN program at Fermilab. A light detection system, based on PMTs deployed behind the TPC wire chambers, is in place to detect vacuum ultraviolet photons produced by ionizing particles in LAr. This system is fundamental for the detector operation, providing an efficient trigger and contributing to the 3D reconstruction of events. Moreover, since the TPC is exposed to a huge flux of cosmic rays due to its operations at shallow depths, the light detection system allows for the time reconstruction of events, contributing to the identification and to the selection of neutrino interactions within the beam spill gates. This contribution will primarily focus on the comparative study (data vs. MC) of light signal of cosmic muons to validate the light emulation.

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MLOps for Beam Controls

Machine learning operations (MLOps) is the standardization and streamlining of the ML development lifecycle to address the challenges associated with large-scale machine learning applications. The full MLOps pipeline consists of open-source tools: DataHub, MinIO and MLflow. It is being used for dataset management and model development to handle changing data dependencies, varying business needs, reproducibility, and diverse teams working with differing tools and skills. To demonstrate the completion of an MLOps pipeline for particle accelerator operations, we are deploying a simple script that computes settings for the Booster’s gradient magnet power supply. Once the demonstration is complete, we will develop and deploy ML-based optimization algorithms to improve Booster’s overall efficiency. This MLOps pipeline opens the gate to systematically develop and deploy ML applications for accelerator controls and diagnostics.

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TinyTPC: A Test Stand for LAr Doping

TinyTPC is a small scale liquid-argon time projection chamber (LArTPC) featuring a pixelated readout system (LArPix) designed to improve the detection of charged particles. To enhance energy measurements at MeV scales, TinyTPC will study the impact of isobutylene, a photosensitive dopant that converts light to charge, and xenon, a wavelength shifter. This presentation will detail TinyTPC's commissioning, operation, data collection methodologies, noise levels, and upcoming tests involving isobutylene, xenon, and radioactive sources.

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First search for an anomalous excess of charged-current $\nu_e$ interactions without visible pions using the full MicroBooNE dataset

This public note presents an investigation of low-energy electron-neutrino events in the Fermilab Booster Neutrino Beam by the MicroBooNE experiment. This search is motivated by the excess of low energy electromagnetic events observed by the MiniBooNE experiment and, more broadly, by the landscape of neutrino anomalies observed at short baselines. This is the first measurement to use all of the data collected by the MicroBooNE experiment, corresponding to $1.1\times 10^{21}$ protons on target. Two exclusive samples of electron neutrinos without visible pions are used, one with visible protons and one without any visible protons. MicroBooNE data is compared to two empirical models of the MiniBooNE low energy excess, one obtained by enhancing the electron-neutrino content as a function of the neutrino energy, and one representing the excess for the first time as a function of the kinematics of shower energy and angle. This measurement excludes an electron-like interpretation of the MiniBooNE excess based on these models at $\geq 99\%$ confidence level in all kinematic variables.

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Constructing Data-Driven Predictions at the Far Detector for NOvA's Neutrino Oscillation Analysis.

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 using $\nu_\mu \ (\bar{\nu}_\mu)$ disappearance and $\nu_e \ (\bar{\nu}_e)$ appearance data. The Neutrinos at Main Injector (NuMI) beamline at Fermilab provides a high purity 900 KW intense beam of neutrinos and anti-neutrinos to NOvA. The NOvA Near Detector, located 100m underground and 1km away from the beam source, observes the un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ and beam $\nu_e \ (\bar{\nu}_e)$ event spectrum. The Far Detector, located in Ash River, MN, USA, is 809 km from the ND and records the oscillated $\nu_e \ (\bar{\nu}_e)$ and the un-oscillated $\nu_\mu \ (\bar{\nu}_\mu)$ event spectrum. NOvA uses a data-driven technique called extrapolation to predict the expected number of $\nu_\mu \ (\bar{\nu}_\mu)$ and $\nu_e \ (\bar{\nu}_e)$ events at the Far Detector using the Near Detector data. The use of data from a functionally equivalent Near Detector provides a powerful constraint on the systematic uncertainties in NOvA neutrino oscillation analyses. As NOvA continues to add data statistics, a robust constraint on systematics becomes more crucial for neutrino oscillation analysis. The details of the NOvA neutrino oscillation analysis framework and how it constrains dominant systematic uncertainties using the Near Detector data will be discussed in this poster.

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Multi-Differential Charged Current $\nu_{\mu}$ - Argon Cross Section without Pions in the Final State Measurement in MicroBooNE

MicroBooNE, an 85-tonne liquid argon time projection chamber (LArTPC) detector is on-axis to the Booster Neutrino Beam (BNB) beamline facility at Fermi National Accelerator Laboratory. MicroBooNE is elucidating neutrino interactions with argon through cross-section measurements to refine interaction models and reduce uncertainties. In this poster, we present the status of the single and double multi-differential charged current (CC) cross section with zero pions in the final state (CC-0$\pi$) as a function of muon momentum ($0.1<p_\mu<2.0\,\mathrm{GeV/c}$) and the cosine of the muon angle ($-1<\cos\theta_\mu<1$). We present the details of the event selection and cross section extraction along with a set of tests using fake data to establish the robustness of the analysis methodology. We also discuss prospects for a future combined measurement with the Gd-H$_2$O target at the ANNIE experiment, to explore MicroBooNE’s proton multiplicity alongside ANNIE’s neutron multiplicity.

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Analysis of Superconducting Magnet Quench Antenna Data

Quenching poses a serious problem for superconducting magnets operating at high currents. It occurs when the material transitions from the superconducting to the normal state, which leads to heating and potential damage to the magnet. To understand and mitigate quenching, the Magnet Department at Fermilab is developing and testing superconducting magnet quench antenna arrays. This study delves into the anomalous events preceding the quench during magnet training by analyzing the collected data. With the moving average and Fast Fourier Transform techniques, we investigate the trends and frequency patterns of the data. Moreover, we introduce an unsupervised anomaly detection algorithm based on Principal Component Analysis and DBSCAN clustering. It can autonomously identify events within background noise, without relying on any predefined event features. Our analysis reveals that the spatio-temporal distribution of these anomalous events has little connection to the quench location, indicating that a majority of them bear no relation to the quenching process.

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Reconstruction and Selection of Neutrino Interactions in MicroBooNE using Deep Convolutional Neural Networks

In this document, we describe a new reconstruction workflow developed for the MicroBooNE experiment. It features the use of Deep Convolutional Neural Networks trained to recognize key structures within the data sufficient for the 3D reconstruction of neutrino interactions within the detector. As a test of the reconstruction utility, the products of the reconstruction workflow are used to select inclusive charged-current (CC) $\nu_e$ and $\nu_\mu$ interactions in both simulated and real MicroBooNE data. In simulation, our $\nu_e$ and $\nu_\mu$ selections achieve an efficiency of 57% and 68\%, respectively, with a purity of 91% and 96%, respectively. We find that these selections are competitive with the inclusive selections used for the most recent MicroBooNE LEE searches. In particular, the CC-$\nu_e$ inclusive selection efficiency improves by over 20% while also improving sample purity. As a first step in quantifying potential bias, the data and Monte Carlo expectati ons are compared for both selections using the MicroBooNE open data. Within statistical and systematic uncertainties, both the electron and muon CC-inclusive event samples agree. A comparison of the real data events chosen by our work and another reconstruction framework shows that the two analyses each identify a sizeable fraction of events the other does not. This suggests that future analyses integrating the strengths of each could lead to combined gains. This work demonstrates, for the first time on real LArTPC data, state-of-the-art neutrino interaction reconstruction centered around deep learning algorithms.

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