arXiv subjects

Alon Levi

Publications and source records attributed to Alon Levi.

3 recordsLinked to original sources

arXiv2026

Initial Performance of the E320 Tracker

Our recent study discussed the prospects for measuring single positrons produced in electron-laser collisions via the nonlinear Breit-Wheeler deep-tunneling process in the SLAC Experiment 320 at the FACET-II RF LINAC. In this work, we demonstrate how a tracking detector, that is a scaled-down version of the one discussed in the prospective simulation study, enables the measurement. This prototype detector, installed in Aug 2024, is built out of five layers of single ALPIDE chips. The data are taken from several standalone runs completed in Nov 2024 and Feb 2025. We use positrons generated through conversion of Bremsstrahlung photons as a proxy to the nonlinear Breit-Wheeler process. These positrons are produced by the beam electrons in a thin Beryllium foil close to the experiment's interaction point. The tracking approach used in this initial work is based on a Hough-Transform seeding algorithm followed by a straight line fit confined to the detector volume. Even with this relatively simple approach, we are able to measure a signal rate of $(1.20\pm0.06_{stat.}\pm0.56_{syst.})\times10^{-1}$ positrons per shot. This signal rate is comparable to the nonlinear Breit-Wheeler rate expected in the main experiment. Notably, the measurement is achieved under an extreme, unprecedented background hit density of ~1.7/mm$^2$, unlike the main experiment, where at least a twice lower density is expected. This large background is mostly due to secondary particles produced when the large flux of Bremsstrahlung photons interacts with the material of the beamline elements. When the foil is retracted, the false-positive signal rate is shown to be four orders of magnitude smaller than the signal rate. We further show that the high spatial tracking resolution of ~5 micron allows to characterize the positrons' spectra. The results are compared to simulations, which are found to be compatible with the data.

hep-ex↗

arXiv2025

Optimal Quantum Likelihood Estimation

A hybrid quantum-classical algorithm is a computational scheme in which quantum circuits are used to extract information that is then processed by a classical routine to guide subsequent quantum operations. These algorithms are especially valuable in the noisy intermediate-scale quantum (NISQ) era, where quantum resources are constrained and classical optimization plays a central role. Here, we improve the performance of a hybrid algorithm through principled, information-theoretic optimization. We focus on Quantum Likelihood Estimation (QLE) - a hybrid algorithm designed to identify the Hamiltonian governing a quantum system by iteratively updating a weight distribution based on measurement outcomes and Bayesian inference. While QLE already achieves convergence using quantum measurements and Bayesian inference, its efficiency can vary greatly depending on the choice of parameters at each step. We propose an optimization strategy that dynamically selects the initial state, measurement basis, and evolution time in each iteration to maximize the mutual information between the measurement outcome and the true Hamiltonian. This approach builds upon the information-theoretic framework recently developed in [A. Te'eni et al. Oracle problems as communication tasks and optimization of quantum algorithms, arXiv:2409.15549], and leverages mutual information as a guiding cost function for parameter selection. Our implementation employs a simulated annealing routine to minimize the conditional von Neumann entropy, thereby maximizing information gain in each iteration. The results demonstrate that our optimized version significantly reduces the number of iterations required for convergence, thus proposing a practical method for accelerating Hamiltonian learning in quantum systems. Finally, we propose a general scheme that extends our approach to solve a broader family of quantum learning problems.

quant-ph↗

arXiv2025

Prospects for the production and detection of Breit-Wheeler tunneling positrons in Experiment 320 at the FACET-II accelerator

The SLAC Experiment 320 collides 10 TW-class laser pulses with the high-quality, 10 GeV electron beam from the FACET-II RF LINAC. This setup is expected to produce a sizable number of $e^+e^-$ pairs via nonlinear Breit-Wheeler mechanism in the strong-field tunneling regime, with an estimated yield of ~0.01-0.1 pairs per collision. This small signal rate typically comes along with large backgrounds originating, e.g., from dumping the high-charge primary beam, secondaries induced by the beam halo, as well as photons and low-energy electrons produced in the electron-laser collision itself. These backgrounds may reach densities of O(100) charged particles per cm^2 (and even more neutral particles) at the surface of the sensing elements, making it a tremendous challenge for an unambiguous detection of single particles. In this work, we demonstrate how detectors and methods adapted from high-energy physics experiments, can enable this measurement. The solution presented is based on a highly granular, multi-layer, radiation-hard pixel detector paired with powerful particle-tracking algorithms. Using a detailed simulation of the existing experimental setup, we show how the false-positive rate due to background processes can be reduced by more than an order of magnitude relative to the expected signal after full reconstruction. Furthermore, we show that the high spatial tracking resolution achievable (<10 microns) allows for positron momentum measurements with a resolution of <2%, enabling spectral characterization of the nonlinear Breit-Wheeler process. Based on our extensive simulation, with a conservatively large background assumption, we show that it is possible to measure single Breit-Wheeler positrons in the coming data taking campaign of E320. That would be the first statistically significant observation and characterization of this elusive process in the (deep) tunneling regime.

hep-ex↗