Locust: C++ software for simulation of RF detection

Esfahani, A. Ashtari; Böser, S.; Buzinsky, N.; Cervantes, R.; Claessens, C.; Viveiros, L. de; Fertl, M.; Formaggio, J. A.; Gladstone, L.; Guigue, M.; Heeger, K. M.; Johnston, J.; Jones, Andrew; Kazkaz, K.; LaRoque, B. H.; Lindman, A.; Machado, E.; Monreal, B.; Morrison, Erin C.; Nikkel, J.; Novitski, E.; Oblath, N. S.; Pettus, W.; Robertson, R. G. H.; Rybka, G.; Saldaña, L.; Sibille, V.; Schram, M.; Slocum, P. L.; Sun, Y. H.; Tedeschi, Jonathan R.; Thümmler, T.; VanDevender, B. A.; Wachtendonk, M.; Walter, Maximilian; Weiss, T. E.; Wendler, Tim; Zayas, E.

doi:10.1088/1367-2630/ab550d

Cited by 7 publications

(7 citation statements)

References 22 publications

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“…A significant advantage of using the simulated data described below for training and testing a model is the confident knowledge of ground truth properties. To avoid simulating CRES events with traditional particle-tracking calculations which demand great computational power and processing times, we developed a simpler and more efficient parametric-based Monte Carlo approach within the Locust software package [29]. The Locust software models the response of an antenna and receiver chain to time-varying electromagnetic fields with the use of internal classes called 'generators' .…”

Section: Simulation Of Cres Events For Optimizationmentioning

confidence: 99%

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

Ashtari Esfahani,

Böser,

Buzinsky

et al. 2024

Mach. Learn.: Sci. Technol.

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The general principle of Cyclotron Radiation Emission Spectroscopy (CRES) experiments is to build an energy spectrum by reconstructing the start frequencies of charged particle trajectories (called tracks) which leave quasilinear profiles in the time-frequency plane when exposed to a magnetic field. The Project 8 collaboration is developing the CRES technique in order to extract the unknown absolute neutrino mass value with a final sensitivity 0.04 eV/$c^2$ from the $\beta$-decay energy spectrum of tritium. Due to the small number of events in the spectrum's endpoint region and the need for excellent instrumental energy resolution, efficient and highly accurate reconstruction methods are desired. Deep learning convolutional neural networks (CNNs) - particularly suited to deal with information-sparse data and which offer precise foreground localization - may be utilized to extract track properties from basic CRES signals with relative computational ease. In this work, we develop a novel machine learning based model which operates a CNN and a support vector machine in tandem to reconstruct simulated CRES tracks and events. As applied to simulated CRES data, we show comparable performance in accuracy of track parameter reconstruction and a relative gain of 24.1\% in event reconstruction efficiency when compared to a traditional point-clustering based approach (baseline).

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Section: Simulation Of Cres Events For Optimizationmentioning

confidence: 99%

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

Ashtari Esfahani,

Böser,

Buzinsky

et al. 2024

Mach. Learn.: Sci. Technol.

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“…The Locust simulation package [10] can be used to directly simulate the EM fields generated by electrons performing cyclotron motion to validate the analytical calculations. Locust simulates the EM fields by first calculating the trajectory of the electrons in the magnetic trap using the Kassiopeia software package [13].…”

Section: Electric Fields Whose Phase Is Equal To the Azimuthal Angle ...mentioning

confidence: 99%

“…The motivation behind this antenna array design is to first develop an understanding of the antenna array approach to CRES with a small scale experiment before attempting to scale the technique to large volumes by using multiple antenna rings to construct the full cylindrical array. The development of the antenna array approach to CRES has largely proceeded through simulations using the Locust software package [10,11], which is used to model the fields emitted by CRES events and predict the signals received by the surrounding antenna array. To validate these simulations, a dedicated test stand is being constructed to perform characterization measurements of the prototype antenna array developed by Project 8 (see figure 2) and benchmark signal reconstruction methods using a specially designed transmitting calibration probe antenna.…”

Section: Introductionmentioning

confidence: 99%

SYNCA: A Synthetic Cyclotron Antenna for the Project 8 Collaboration

et al. 2023

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Cyclotron Radiation Emission Spectroscopy (CRES) is a technique for measuring the kinetic energy of charged particles through a precision measurement of the frequency of the cyclotron radiation generated by the particle's motion in a magnetic field. The Project 8 collaboration is developing a next-generation neutrino mass measurement experiment based on CRES. One approach is to use a phased antenna array, which surrounds a volume of tritium gas, to detect and measure the cyclotron radiation of the resulting β-decay electrons. To validate the feasibility of this method, Project 8 has designed a test stand to benchmark the performance of an antenna array at reconstructing signals that mimic those of genuine CRES events. To generate synthetic CRES events, a novel probe antenna has been developed, which emits radiation with characteristics similar to the cyclotron radiation produced by charged particles in magnetic fields. This paper outlines the design, construction, and characterization of this Synthetic Cyclotron Antenna (SYNCA). Furthermore, we perform a series of measurements that use the SYNCA to test the position reconstruction capabilities of the digital beamforming reconstruction technique. We find that the SYNCA produces radiation with characteristics closely matching those expected for cyclotron radiation and reproduces experimentally the phenomenology of digital beamforming simulations of true CRES signals.

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“…The data gathered from these measurement programs provide a detailed phenomenological under- standing of CRES in a waveguide environment [34]. CRES phenomenology is characterized by an original simulation package called Locust [37]. To simulate electron trajectories, Locust uses KATRIN's Kassiopeia package [38], which can model static fields and the motions of particles in them.…”

Section: Phenomenology and Simulationsmentioning

confidence: 99%

“…For 10% trapping efficiency, the ratio of fields is 99%, corresponding to a range of trapped pitch angles δθ max = ±5.7 • . Antenna-trap co-design is supported by Project 8's Locust simulation framework [37] that describes the response of antennas to electromagnetic radiation. Locust generates realistic simulated data sets on which analysis approaches can be tested.…”

Section: Free Space Cres Demonstratormentioning

confidence: 99%

The Project 8 Neutrino Mass Experiment

Collaboration¹,

Esfahani²,

Böser³

et al. 2022

Preprint

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Measurements of the β − spectrum of tritium give the most precise direct limits on neutrino mass. Project 8 will investigate neutrino mass using Cyclotron Radiation Emission Spectroscopy (CRES) with an atomic tritium source. CRES is a new experimental technique that has the potential to surmount the systematic and statistical limitations of current-generation direct measurement methods. Atomic tritium avoids an irreducible systematic uncertainty associated with the final states populated by the decay of molecular tritium. Project 8 will proceed in a phased approach toward a goal of 40 meV/c 2 neutrino-mass sensitivity.

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Locust: C++ software for simulation of RF detection

Cited by 7 publications

References 22 publications

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

Deep learning based event reconstruction for cyclotron radiation emission spectroscopy

SYNCA: A Synthetic Cyclotron Antenna for the Project 8 Collaboration

The Project 8 Neutrino Mass Experiment

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