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Noise driven emittance growth is modified by the presence of coherent forces. Closed form asymptotic growth rates are given for two frequency distributions. The analytic results are compared with tracking, showing good agreement. Purely numerical results for a parabolic frequency distribution are also presented. If a small antidamping force is present then additional, real frequency shifts increase growth rates.
In this paper, we consider a strongly convex stochastic optimization problem and propose three classes of variable sample-size stochastic first-order methods: (i) the standard stochastic gradient descent method, (ii) its accelerated variant, and (iii) the stochastic heavy-ball method. In each scheme, the exact gradients are approximated by averaging across an increasing batch size of sampled gradients. We prove that when the sample size increases at a geometric rate, the generated estimates converge in mean to the optimal solution at an analogous geometric rate for schemes (i)–(iii). Based on this result, we provide central limit statements, whereby it is shown that the rescaled estimation errors converge in distribution to a normal distribution with the associated covariance matrix dependent on the Hessian matrix, the covariance of the gradient noise, and the step length. If the sample size increases at a polynomial rate, we show that the estimation errors decay at a corresponding polynomial rate and establish the associated central limit theorems (CLTs). Under certain conditions, we discuss how both the algorithms and the associated limit theorems may be extended to constrained and nonsmooth regimes. As a result, we provide an avenue to construct confidence regions for the optimal solution based on the established CLTs and test the theoretical findings on a stochastic parameter estimation problem.
The Electron-Ion Collider Crab Cavity Low-Level Radio Frequency system will have to reduce the Crab Cavity impedance to prevent transverse instabilities, while regulating the crabbing voltage and minimizing the Radio Frequency noise levels injected to the beam. These are challenging and partly conflicting requirements. This works summarizes the specifications to achieve these requirements and investigates the possible trade-offs in the architecture.
We report on the operation of the first high peak and average power single-pass terahertz free-electron laser (THz FEL) based on a high-brightness photoinjector for developing a THz source for pump-probe experiments at advanced x-ray FELs (XFELs). Electron beams with 17 MeV/c momentum and charge up to 2.4 nC were used to generate narrow-band 3 THz radiation with pulse energies of more than 0.1 mJ. The novelty of the realized method is that the undulator radiation by electron beams is much longer than the radiation wavelength, with FEL starting from coherent beam contribution rather than shot noise. This proved to be not a simple scaling of the XFEL mechanism due to the significant role of the bunching factor in the considered case.
Modern Nuclear Physics experimental setups run experiments with higher beam intensity resulting in increased noise in detector components used for particle track reconstruction. Increased uncorrelated signals (noise) result in decreased particle reconstruction efficiency. In this paper, we investigate the usage of Machine Learning, specifically Convolutional Neural Network Auto-Encoders (CAE), for de-noising raw hits from drift chambers in the CLAS12 detector. To the best of our knowledge, this is the first time CAE is employed to perform such an operation in this field. During the de-noising phase, it is important to remove as much noise as possible while retaining the valid hits to avoid losing crucial information about the experiment. Here, we show that using CAE, it is possible to remove noise hits while retaining up to 94% of valid tracks for a beam current of 110nA while for lower beam currents (45-55nA), we get up to 98% efficiency. Studies on experimental conditions with increasing noise show that CAE performs better than conventional tracking algorithms in isolating hits belonging to tracks. Specifically, the de-noising algorithm results in tracking efficiency improvements greater than 15%, in real data production procedures with nominal conditions, and up to two times better efficiency in synthetically generated data with high luminosity conditions (90-110nA), indicating that machine learning can lead to significantly shorter times for conducting physics experiments.
We report flexible printed-circuit-board-based quench antenna arrays have been developed at FNAL since 2017. They proved to be low-noise, low-cost, sensitive, and non-invasive sensors for quench characterization in superconducting magnets, having the potential to extend even to quench detection. Starting with applications of small area sensors of this type, we have explored feasibility for operations at high pressure, and have invested in multi-channel quench antenna arrays covering the complete area of the innermost magnet layer of the conductor. We've also tested and optimized sensor geometry and relative orientations to increase sensitivity and spatial resolution. Beyond developments of warm and cold bore antennas, we've progressed to concepts which attach quench antennas to the conductor surfaces of accelerator magnets. Multiple programs and projects at FNAL and collaborating institutions benefited from this work already and our plans target further extensions of capabilities and applicability of these devices. In this paper we present the logic behind the development steps taken so far, status of our work and direction of near-term research on quench antennas at Fermilab.
The Relativistic Heavy Ion Collider (RHIC) at BNL are using the Low Energy RHIC Electron Cooling (LEReC) to conduct experiments that search for the quantum chromodynamic (QCD) critical point. The first ever electron cooling based on the RF acceleration of electron beams was experimentally demonstrated on April 5, 2019 at LEReC at BNL. The first critical step in obtaining successful 3D non-magnetized cooling of the Au ion bunches in the RHIC cooling section was matching the electron beam energy with a relative error less than 5*10 -4 to the ion beam energy. Part of the LEReC beamline is a dipole magnet that bends the electron beam 180 degree. One of the most outstanding measurement challenges is that the dipole field is so low (≈200 G). Most of the existing NMR probes can only measure fields >400 G. Lower signal-to-noise ratio at low fields is requires the use of larger sample volumes. Working with CAYLAR, a NMR probe has been redesigned and optimized for these low field measurements with high resolution. We report the methods, challenges, and results for extensive magnetic field mappings of the 180 dipole magnet. A combination of NMR and Hall sensors has been successfully implemented to measure uniform field regimes inside the magnet center area and non-uniform field regimes at the magnet ends. Detailed measurement and mapping have been performed at five radii and five heights along the beam trajectory. Meanwhile a finite element magnetic modeling simulation of the magnet using Opera software has been performed. The calculated and measured data are compared, and the calculated data is good reference for measured data over long length mapping from magnet edge to center. The measured magnetic measurement data is directly useful for beam instrumentation, diagnostics and operation.
Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, N-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-N-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations k 2 = 2k 1 = 0.2 h Mpc -1 by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the baryon acoustic oscillations (BAO) scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity (NG).
The EIC electron storage ring (ESR) has very tight tolerances for the beam position and size stability at the interaction point. The oscillations at the proton betatron frequency and its harmonics are the most dangerous because, for instance, they could lead to unacceptable proton emittance growth from the oscillating beam-beam kick from the electrons at the amplitude of the positional oscillations as low as 10 -4 of the beam size. Even at much lower frequencies, down to the single Hz range, the position oscillations at a few percent level of the nominal beam size were found to be dangerous. These oscillations could have different causes including magnet power supply ripple, mag net vibration, noise in the main and crab RF systems, and some collective instabilities. To specify the acceptable level of the current ripple and noise of the magnet power supplies we need to accurately account for the eddy current shielding by the vacuum chamber, as well as, potentially, by the laminated magnet yokes (considered elsewhere). With some ap proximations, the chamber shielding can be described analytically. The main objective of this note is to derive these analytical expressions and to document the resulting shielding performance of the ESR chamber.
We will present the first beam test results with centimeter-scale AC-LGAD strip sensors, using the Fermilab Test Beam Facility, and a study of the performance of AC-LGAD sensors as a function of their thickness. Sensors of this type are envisioned for applications that require large-area precision 4D tracking coverage with economical channel counts, including timing layers for the Electron Ion Collider (EIC), and space-based particle experiments. Long strip sensors with sparse readout offer better cost and performance for applications where channel count or electrical power density is a constraint. Thanks to the excellent signal to noise ratio in AC-LGADs, sparse readout can be exploited without significant degradation of spatial or time resolution, which is demonstrated in our studies. A survey of sensor designs is presented, with the aim of optimizing the electrode geometry for spatial resolution and timing performance. We will present our studies of the sensor geometry optimizatio n to maintain the desirable sensor performance characteristics with increasingly larger electrodes.
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.
Deep transfer learning has a great success story in computer vision (CV), natural language processing, and many other fields. In this communication, we are going to push forward the deep transfer learning to the hydraulic fracture imaging problem by proposing a two-step approach: 1) train a convolutional neural network (CNN) to reconstruct target geometries by a relatively large amount of approximated field patterns generated from a simplified model and 2) fine-tune the top layers of transferred CNN by a small amount of true field patterns generated through a full model. The advantages include the rapid generation of large amount of data through the simplified model and the high reconstruction accuracy through a careful design of the deep transfer learning. Here, the CNN trained through the deep transfer learning can accurately reconstruct the lateral extent and direction of fractures with unseen conductivity and white Gaussian noise, showing a notable acceleration/accuracy enhancement over the previous CNN trained by mixing a small number of true data into the approximated data as data augmentation.
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.
Wave or fuzzy dark matter produced with high momenta behaves in many ways like hot particle dark matter while also possessing seemingly different phenomenology due to wave interference. We develop wave perturbation theory to show that white noise density fluctuations generated by the interference of high-momenta waves are gravitationally unstable in the usual way during matter domination above the free-streaming scale and stabilize below the free-streaming scale, much like the analogous effects for massive neutrinos in hot dark matter. We verify and illustrate these effects in the density power spectra of Newtonian Schrödinger-Poisson simulations. In the cosmological context, this would cause a gradual suppression of the initial white noise isocurvature perturbations below the free-streaming scale at matter radiation equality, unlike cold dark matter isocurvature fluctuations, and virial stability of dark matter halos.
Here, we describe observations of low energy excess (LEE) events, background events observed in all light dark matter direct detection calorimeters, and noise in a transition edge sensor based two-channel silicon athermal phonon detector with 375 meV baseline energy resolution. We measure two distinct LEE populations: “shared” multichannel events with a pulse shape consistent with substrate athermal phonon events and sub-eV events that couple nearly exclusively to a single channel with a significantly faster pulse shape. These “singles” are consistent with events occurring within the aluminum athermal phonon collection fins. Similarly, our measured detector noise is higher than the theoretical expectation. Measured noise can be split into an uncorrelated component, consistent with shot noise from small energy depositions within the athermal phonon sensor itself, and a correlated component, consistent with shot noise from energy depositions within the silicon substrate's phonon system.
Gaussian boson sampling, a computational model that is widely believed to admit quantum supremacy, has already been experimentally demonstrated and is claimed to surpass the classical simulation capabilities of even the most powerful supercomputers today. However, whether the current approach limited by photon loss and noise in such experiments prescribes a scalable path to quantum advantage is an open question. Here, to understand the effect of photon loss on the scalability of Gaussian boson sampling, we analytically derive the asymptotic operator entanglement entropy scaling, which relates to the simulation complexity. As a result, we observe that efficient tensor network simulations are likely possible under the N out ∝ √N scaling of the number of surviving photons N out in the number of input photons N. We numerically verify this result using a tensor network algorithm with U(1) symmetry, and we overcome previous challenges due to the large local Hilbert-space dimensions in Gaussian boson sampling with hardware acceleration. Additionally, we observe that increasing the photon number through larger squeezing does not increase the entanglement entropy significantly. Finally, we numerically find the bond dimension necessary for fixed accuracy simulations, providing more direct evidence for the complexity of tensor networks.
The Multi-Probe 24A experiments took place on the Omega EP laser in November 2023. The experiments consisted of shots alternating between Omega EP’s two short-pulse laser beams to generate proton and deuteron ion beams from a range of film thicknesses, and x-ray sources from the established CPC+Ta wire targets. The backlighter was used for ion acceleration in the pitcher series, in which deuteron and proton beams characterized as a function of CD film thickness to develop a pitcher for a pitcher-catcher neutron radiographic source, while also characterizing electrons and x-rays emitted perpendicular to the target (i.e. Crosstalk for sidelighter-driven x-ray beams). The sidelighter was used for electron acceleration in the x-ray series, in which the electron acceleration and subsequent x-rays was characterized from the CPC+Ta wire targets and radiography was conducted with and without electro-magnetic electron defection. For the pitcher series, we found that at 500 J and 0.7 ps the 700-800 nm CD films yielded the greatest number and highest energy for both protons and deuterons. For the x-ray series, results demonstrated: a significant number of <100 keV x-rays are produced within the glue that fills the CPC cone, on-axis electron signal from the x-ray targets produce electrons resolvable up to ~10 MeV, and electron deflection (using MIFEDS) has a notable effect radiograph on noise reduction.
This article describes experimental evidence that the magnetic presheath is a fully three-dimensional structure modified by ion–neutral collisions. Velocity distributions of both ions and neutrals, obtained via laser-induced fluorescence, show that cross field ion drifts do not result from entrainment of ions in a flowing neutral background. Ion flows parallel to E x B arise and accelerate to as much as 0.2c s within several ion gyroradii of the boundary surface, where c s is the sound speed. Within measurement resolution, the onset of the E x B aligned flow occurs at the same distance to the surface that ions begin to deflect from travel along magnetic field lines. Collisional fluid and particle-in-cell simulations of the boundary region are compared to the experimental measurements. We find that, in contrast to the classical collisionless Chodura model, collisional effects between the ions and the non-flowing neutral population are essential to quantitatively predict the observed ion drift velocities. No momentum coupling between ions and neutrals, separable from noise and other effects, is observed in either signal. Here, we discuss several explanations and implications of this observation.