Plasma Wakefield Accelerator-Based Low Emittance Muon Source
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This project sets up a website to support the nascent Muon Catalyzed Fusion collaboration including development of particle accelerators and transport beamlines for muon beams. The website is envisioned as having the general public information pages and private pages for collaboration members. Multimedia elements like images, text animations, and video lectures, covering a broad spectrum of topics will populate the educational site, covering muon facilities, to comprehensive explorations and seminal documents that define the science of Muon Catalyzed Fusion, Acceleration, Applications, Instrumentation, Beamline Design, and beam dynamics design codes. Ensuring compatibility across devices and operating systems, it also features integration with Google Docs for collaboration, a code repository (GitHub), a blog platform with comments (WordPress), the potential for ChatGPT integration and interactive graph plotting with Python Plotty to enhance data visualization. This project will maintain public and protected private pages, due to the proprietary nature of the work or research in progress. The public sections will be built to foster dissemination of information and highlight recent work within the NK Labs collaboration, including lectures, published papers, and regular blog posts with open commenting. The private section will support unpublished or nonpublic research, by facilitating collaborative efforts through integrated Google Docs and Python Plotty for shared graphing work. Ultimately, this project strives to make complex scientific knowledge more accessible to the public, foster enhanced collaboration, and serve as a platform for sharing cutting-edge research in Muon Catalyzed Fusion and Accelerators.
When a cosmic ray particle collides with the upper atmosphere, it creates a shower of particles that transverse down to the Earth’s surface. These cosmogenic particles provide a challenging background in neutrino experiments. The Short Baseline Neutrino (SBN) Program is composed of three Liquid Argon Time Projection Chambers (LArTPCs) that will help us understand the elusive neutrino. Together with a Cosmic Ray Tagger (CRT) system, the ICARUS detector serves as the Far Detector in the SBN Program. The CRT surrounds the detector medium and tags incoming particles allowing us to combat the high flux of comic rays we experience at ICARUS. In this poster, I will show some of the first data analyses done with the fully commissioned CRT system, including studies using CRT timing information and CRT hit reconstruction.
The phenomenon of neutrino oscillations is the most significant evidence in experimental particle physics that points to the existence of Physics Beyond the Standard Model, and it opened a window for several and interesting new investigations in the field of neutrino physics. Among the possibilities, Non-Standard Interactions (NSI) are an extension of the neutrino matter effect leading to a rich phenomenology. These NSI are expected to modify the propagation of neutrinos through matter. The current open questions in the neutrino oscillation model rely heavily on how neutrinos interact with matter, and NSI could induce possible effects. This talk reports the preliminary search for CP-violating NSI of neutrinos with matter at the NOvA Experiment. Data from $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{\mu}(\bar{\nu}_{\mu})$ and $\nu_{\mu}(\bar{\nu}_{\mu})\rightarrow\nu_{e}(\bar{\nu}_{e})$ oscillation channels are used to measure the effect of the NSI parameters $\varepsilon_{e\mu}$ or $\v arepsilon_{e\tau}$ over the 810 km baseline of the experiment.
High-Entropy Alloys and Electrospun Nanofiber materials are two novel classes of materials that can offer improved resistance to beam-induced radiation damage and thermal shock. Research to develop these new materials specifically for multi-megawatt accelerator target applications, such as beam windows and particle-production targets, has recently begun. The research program will combine in-beam experiments with complementary simulations to tailor the microstructures of these novel materials for use in next-generation accelerator target facilities. Iterative simulations to optimize the material composition, physics performance and beam-induced thermomechanical response will guide the material design and fabrication processes based on established figures of merit. Ensuing material irradiation experiments using low-energy ions and prototypic high-energy protons, followed by extensive post-irradiation material characterization, will then assess and qualify the selected novel materials. This talk will provide an overview of the novel materials development research program initiated at Fermilab through my DOE Early Career Research Program award.
Description of GQuEST
High granularity silicon pixel sensors are at the heart of energy frontier particle physics collider experiments. At an collision rate of 40\,MHz, these detectors create massive amounts of data. Signal processing that handles data incoming at those rate and intelligently reduces the data within the pixelated region of the detector \textit{at rate} will enhance physics performance and enable physics analyses that are not currently possible. Using the shape of charge clusters deposited in an array of small pixels, the physical properties of the traversing particle can be extracted with locally customized neural networks. In this first work, we present a neural network that can be embedded into the on-sensor readout and filter out hits from low momentum tracks, reducing the detector's data volume by 54.4-75.4\%. The network is designed and simulated as a custom readout integrated circuit with 28\,nm CMOS technology and is expected to operate at less than 300\,$\mu W$ with an area of less than 0.2\,mm$^2$.
Optomechanical strain sensing provides attractive opportunities for novel particle detection schemes, as well as studying stress-induced (i.e. non-radiogenic) phonon bursts, which have been demonstrated to limit the coherence times of superconducting qubits and are a suspected culprit in the low energy excesses observed by many dark matter direct detection experiments. We are investigating SiN microring optical resonator strain sensors, developed at Purdue University, for applications in fundamental particle sensing and QIS. These sensors can be embedded in the substrate upon which superconducting qubits are patterned, providing a handle to distinguish decoherence events of radiogenic origin from those due to crystal stress. In a similar way, these sensors can be operated in conjunction with superconducting detectors (e.g., MKIDs, TES) to enable multi-channel readout of particle interactions in the device substrate or serve as anticoincidence detectors, which may be required to ident ify low-energy interactions from dark matter particles down to the fermionic thermal relic mass limit of a few keV. Such sensors can potentially be used to directly observe resonant scattering processes of gamma rays (and perhaps neutrinos) where no detectable quanta are produced in the target, via the microscopic stress induced by the momentum transfer to the (fixed-in-place) crystal lattice as a whole. These strain sensors have so far found application in photonics and communications, but have yet to be adopted for HEP uses, where they can provide unique capabilities in the search for dark matter as well as understanding and improving the coherence times of superconducting qubits.
The Superconducting Quantum Materials and Systems Center, led by Fermi National Accelerator Laboratory, is one of five research centers funded by the U.S. Department of Energy as part of a national initiative to develop and deploy the world’s most powerful quantum computers and sensors. The SQMS Center uses world-record quality-factor superconducting radio-frequency, or SRF, cavities as ultra-sensitive quantum probes. Cavities combined with superconducting transmon qubits can be the building block of a quantum computer, and they can also be employed for fundamental physics searches. Within the quantum sensing thrust, researchers are developing experiments based on cavities and novel quantum devices to search for particles beyond the Standard Model, dark matter candidates, gravitational waves and fundamental material properties. The seminar will present a brief overview of the center and focus on the physics and sensing work conducted at Fermilab.
CERN ABP Seminar talk,, Dec 14, 2023
In Fermilab's 2022-2023 proton complex run, Fermilab recovered from an unexpected failure in the neutrino focusing horn to achieve a record beam power of 960 kW. For Snowmass and P5, Fermilab recently proposed a new upgrade plan known as Accelerator Complex Evolution (ACE) to occur after PIP-II upgrade in tandem with DUNE/LBNF operation. The first phase of ACE, is the ACE Main Injector Ramp and Targetry upgrade, would raise the LBNF beam power from 1.2 MW to 2 MW by shortening the Main Injector cycle time to around 0.65s. The second phase of ACE, the ACE Booster Replacement, would replace the Booster with a new machine and achieve 2.4 MW for DUNE/LBNF. The core accelerator challenges, present and future, for operating intense neutrino beams at Fermilab will be highlighted.
Presents status of development of HTS-based rapid cycling accelerator magnet for muon acceleration and outlines required R&D
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Presentation at HTSHFF (https://www.htshff2023.org/)
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Though it may seem intuitive at times, the term 'complexity' is multifaceted, often encompassing various interacting aspects and components that follow local rules. This interaction leads to non-linearity, randomness, collective dynamics, hierarchy, and emergence. The phenomenological complexity found in large accelerators has recently been addressed by the Snowmass’21 Future Colliders Implementation Task Force (ITF). In this presentation, we will provide a concise overview of the mathematical constructs employed to assess hierarchical complexity, summarize the key findings from the ITF analysis, and offer a few examples demonstrating how this approach can be applied to analyze certain literaryclassics.
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