An official website of the United States government
Precise and accurate atomic mass data provide crucial information for applications in a wide range of fields in physics and beyond, including astrophysics, nuclear structure, particle and neutrino physics, fundamental symmetries, chemistry, and metrology. The most precise atomic mass measurements are performed on charged particles confined in a Penning trap. Here, we describe the development, status, and outlook of CHIP-TRAP: the Central Michigan University high-precision Penning trap. CHIP-TRAP aims to perform ultra-high precision (∼1 part in 1011 fractional precision) mass measurements on stable and long-lived isotopes produced with external ion sources and transported to the Penning traps. Along the way, ions of a particular m/q are selected with a multi-reflection time-of-flight mass separator (MR-TOF-MS), with further filtering performed in a cylindrical capture trap before the ions are transported to a pair of hyperbolic measurement traps. In this paper, we report on the design and status of CHIP-TRAP and present results from the commissioning of the ion sources, MR-TOF-MS, and capture trap. We also provide an outlook on the continued development and commissioning of CHIP-TRAP.
more »
« less
Applications of Machine Learning and Neural Networks for FT-ICR Mass Measurements with SIPT
The single-ion Penning trap (SIPT) at the Low-Energy Beam Ion Trapping Facility has been developed to perform precision Penning trap mass measurements of single ions, ideal for the study of exotic nuclei available only at low rates at the Facility for Rare Isotope Beams (FRIB). Single-ion signals are very weak—especially if the ion is singly charged—and the few meaningful ion signals must be disentangled from an often larger noise background. A useful approach for simulating Fourier transform ion cyclotron resonance signals is outlined and shown to be equivalent to the established yet computationally intense method. Applications of supervised machine learning algorithms for classifying background signals are discussed, and their accuracies are shown to be ≈65% for the weakest signals of interest to SIPT. Additionally, a deep neural network capable of accurately predicting important characteristics of the ions observed by their image charge signal is discussed. Signal classification on an experimental noise dataset was shown to have a false-positive classification rate of 10.5%, and 3.5% following additional filtering. The application of the deep neural network to an experimental 85Rb+ dataset is presented, suggesting that SIPT is sensitive to single-ion signals. Lastly, the implications for future experiments are discussed.
more »
« less
- Award ID(s):
- 2111185
- PAR ID:
- 10521955
- Publisher / Repository:
- MDPI
- Date Published:
- Journal Name:
- Atoms
- Volume:
- 11
- Issue:
- 10
- ISSN:
- 2218-2004
- Page Range / eLocation ID:
- 126
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Penning-trap mass spectrometry in atomic and nuclear physics has become a well-established and reliable tool for the determination of atomic masses. In combination with short-lived radioactive nuclides it was first introduced at ISOLTRAP at the Isotope Mass Separator On-Line facility (ISOLDE) at CERN. Penning traps have found new applications in coupling to other production mechanisms, such as in-flight production and separation systems. The applications in atomic and nuclear physics range from nuclear structure studies and related precision tests of theoretical approaches to description of the strong interaction to tests of the electroweak Standard Model, quantum electrodynamics and neutrino physics, and applications in nuclear astrophysics. The success of Penning-trap mass spectrometry is due to its precision and accuracy, even for low ion intensities (i.e., low production yields), as well as its very fast measurement cycle, enabling access to short-lived isotopes. The current reach in relative mass precision goes beyond δ m/ m=10 −8 , the half-life limit is as low as a few milliseconds, and the sensitivity is on the order of one ion per minute in the trap. We provide a comprehensive overview of the techniques and applications of Penning-trap mass spectrometry in nuclear and atomic physics.more » « less
-
Markopoulos, Panos P.; Ouyang, Bing (Ed.)We consider the problem of unsupervised (blind) evaluation and assessment of the quality of data used for deep neural network (DNN) RF signal classification. When neural networks train on noisy or mislabeled data, they often (over-)fit to the noise measurements and faulty labels, which leads to significant performance degradation. Also, DNNs are vulnerable to adversarial attacks, which can considerably reduce their classification performance, with extremely small perturbations of their input. In this paper, we consider a new method based on L1-norm principal-component analysis (PCA) to improve the quality of labeled wireless data sets that are used for training a convolutional neural network (CNN), and a deep residual network (ResNet) for RF signal classification. Experiments with data generated for eleven classes of digital and analog modulated signals show that L1-norm tensor conformity curation of the data identifies and removes from the training data set inappropriate class instances that appear due to mislabeling and universal black-box adversarial attacks and drastically improves/restores the classification accuracy of the identified deep neural network architectures.more » « less
-
Abstract Name that Neutrinois a citizen science project where volunteers aid in classification of events for the IceCube Neutrino Observatory, an immense particle detector at the geographic South Pole. From March 2023 to September 2023, volunteers did classifications of videos produced from simulated data of both neutrino signal and background interactions.Name that Neutrinoobtained more than 128,000 classifications by over 1800 registered volunteers that were compared to results obtained by a deep neural network machine-learning algorithm. Possible improvements for bothName that Neutrinoand the deep neural network are discussed.more » « less
-
This paper considers a pure electron plasma, with a small admixture of negative ions, confined in a Penning–Malmberg trap. When a diocotron mode is excited on the plasma, the end sheaths of the plasma are azimuthally distorted. During reflection at a distorted end sheath, an ion steps off of the surface characterizing the drift motion in the plasma interior, and this step produces transport. The diocotron mode transfers canonical angular momentum to the ions, and in response damps. These transport mechanism and associated damping are called rotational pumping. It is particularly strong when the axial bounce motion and the rotational drift motion, in the rotating frame of the mode, satisfy a resonance condition. This paper calculates the transport flux of ions and the associated damping rate of the mode in the resonant regime. Previous papers have discussed the theory and the experimental observation of rotational pumping for the special case of a diocotron mode with azimuthal wave number l = 1, and this paper extends the theory to modes with l≠1, which may sound like a trivial extension, but in fact is not.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/atoms11100126
