Applications In Nuclear Physics Research Articles

Water-based quantum dots liquid scintillator for particle physics

Liquid scintillators are typically composed from organic compounds dissolved in organic solvents. However, usage of such material is often restricted due to fire safety and environmental reasons. Because of this, R&D of water-based liquid scintillators is of extreme relevance; yet, no such scintillators have been made commercially available as yet. Here, we investigate an alternative, water-based quantum dots liquid scintillator. Pre-determined and controllable optical properties of the quantum dots, as well as the existence of large libraries of established protocols for their dispersion in aqueous solutions, make them an attractive option for nuclear and particle physics applications. We characterize the optical properties of water-based quantum dots liquid scintillator and find that most of its optical properties are preserved upon quantum dots' phase transfer into water, through the addition of an oleic acid hydrophilic layer. Using the developed scintillator, the time and charge responses from atmospheric muons are measured, highlighting the practical viability of water-based quantum dots liquid scintillators for nuclear and particle physics, special interest on neutrino physics.

Theories of Relativistic Dissipative Fluid Dynamics.

Relativistic dissipative fluid dynamics finds widespread applications in high-energy nuclear physics and astrophysics. However, formulating a causal and stable theory of relativistic dissipative fluid dynamics is far from trivial; efforts to accomplish this reach back more than 50 years. In this review, we give an overview of the field and attempt a comparative assessment of (at least most of) the theories for relativistic dissipative fluid dynamics proposed until today and used in applications.

Attosecond science the art of making electron movies

After 22 years since the first experimental demonstration of attosecond pulses, the attosecond science has become a very active field of research, with prominent applications in atomic, molecular and solid-state physics. Experimental advances, in terms of new sources, devices and techniques, are still required, together with new theoretical tools and approaches, but attosecond physics has firmly established as a mature research field.

Applications of nuclear physics to energy: the INFN-E project of the National Institute of Nuclear Physics (INFN)

In this talk, the main issues in radioactive waste management worldwide will be briefly introduced, as well as the world roadmap towards nuclear fusion. Then, an overview of the activities of the INFN-E (INFN Energia) strategic project will be given, showing how INFN's skills on basic theoretical aspects and on the design, construction and use of accelerators and radiation detectors can be applied to specific projects for the characterization and monitoring of radioactive waste as a means to increase nuclear safety and in the context of advanced plants for the study of nuclear fusion.

Electron plasma diagnostics in ELTRAP by electron cyclotron resonance heating method.

Electron cyclotron resonance heating method of Particle-in-Cell code was used to analyze heating phenomena, axial kinetic energy, and self-consistent electric field of confined electron plasma in ELTRAP device by hydrogen and helium background gases. The electromagnetic simulations were performed at a constant power of 3.8 V for different RF drives (0.5 GHz- 8 GHz), as well as for 1 GHz constant frequency at these varying amplitudes (1 V-3.8 V). The impacts of axial and radial temperatures were found maximum at 1.8 V and 5 GHz as compared to other amplitudes and frequencies for both background gases. These effects are higher at varying radio frequencies due to more ionization and secondary electrons production and maximum recorded radial temperature for hydrogen background gas was 170.41 eV. The axial kinetic energy impacts were found more effective in the outer radial part (between 0.03 and 0.04 meters) of the ELTRAP device due to applied VRF through C8 electrode. The self-consistent electric field was found higher for helium background gas at 5 GHz RF than other amplitudes and radio frequencies. The excitation and ionization rates were found to be higher along the radial direction (r-axis) than the axial direction (z-axis) in helium background gas as compared to hydrogen background gas. The current studies are advantageous for nuclear physics applications, beam physics, microelectronics, coherent radiation devices and also in magnetrons.

In‐Source High‐Resolution Spectroscopy Using an Integrated Tunable Raman Laser

AbstractTunable single‐frequency lasers are the most prominent tool for high‐resolution spectroscopy, allowing for the study and exploitation of the electronic structure of atoms. A significant milestone relies on the demonstration of integrated laser technology for performing such a task. The device presented here is composed of a compact Fabry–Perot monolithic resonator capable of producing tunable and Fourier‐limited nanosecond pulses with a MHz‐class frequency stability without active cavity stabilization elements. It also has the remarkable capability of exploiting the Raman effect to funnel efficiently the broad spectrum of an input laser to a spectrally‐bright Stokes pulse at hard‐to‐access wavelength ranges. The targeted atom for the demonstrations is 152Sm, released as an atomic vapor in a hot cavity environment. Here, the Stokes field is tuned to a wavelength of 433.9 nm, while a crossed‐beams spectroscopy setup is used to minimize the Doppler broadened spectral features of the atoms. With this work, the suitability of integrated diamond Raman lasers as a high‐resolution in‐source spectroscopy tool is demonstrated, enabling many applications in atomic and nuclear physics. The integrated form‐factor and inherent simplicity makes such a laser an interesting prospect for quantum‐technology based sensing systems and related applications.

Model Mixing Using Bayesian Additive Regression Trees

In modern computer experiment applications, one often encounters the situation where various models of a physical system are considered, each implemented as a simulator on a computer. An important question in such a setting is determining the best simulator, or the best combination of simulators, to use for prediction and inference. Bayesian model averaging (BMA) and stacking are two statistical approaches used to account for model uncertainty by aggregating a set of predictions through a simple linear combination or weighted average. Bayesian model mixing (BMM) extends these ideas to capture the localized behavior of each simulator by defining input-dependent weights. One possibility is to define the relationship between inputs and the weight functions using a flexible nonparametric model that learns the local strengths and weaknesses of each simulator. This article proposes a BMM model based on Bayesian Additive Regression Trees (BART). The proposed methodology is applied to combine predictions from Effective Field Theories (EFTs) associated with a motivating nuclear physics application. Supplementary materials for this article are available online. Source code is available at https://github.com/jcyannotty/OpenBT.

Accurate simultaneous lead stopping power and charge-state measurements in gases and solids: Benchmark data for basic atomic theory and nuclear applications

We have measured for the first time simultaneously both the mean charge states and stopping powers of (35–280) MeV/u 208Pb ions in gases and solids with an accuracy of 1%. The existence at lower energies and disappearance at higher of density effects in the charge-state distribution and the corresponding stopping power are directly confirmed and comparisons with widely used theories and simulations for heavy ions demonstrate strong deviations of up to 27%. However, an unprecedented prediction power of better than 3% has been achieved for the energy loss when the measured mean charge-states are implemented in the Lindhard-Sørensen theory. Our present benchmark data contribute to an improved understanding of the basic atomic collision processes and to numerous applications in nuclear physics. Extending the GANIL data [1] to higher accuracy and energies, we can now answer at which velocities the Bohr-Lindhard density effect in stopping will vanish.

Design and simulation of 4H-SiC low gain avalanche diode

In the applications of nuclear and high-energy physics, Silicon Low Gain Avalanche Diodes (Si LGAD) as particle detectors have been shown to perform well in time resolution. Compared with silicon, 4H Silicon Carbide (4H-SiC) has a wider band gap, better radiation resistance, higher saturated carrier velocity and lower temperature sensitivity. Therefore, 4H-SiC LGAD is suitable for the detection of Minimum Ionization Particles (MIPs) under extreme radiation and temperature. However, due to the complexity of SiC device design and production, high performance SiC LGAD devices have not yet been produced. In this work, we use TCAD tools to design and simulate two n-type 4H-SiC LGAD structures with different electric field profiles, I/V and C/V characteristics and gain efficiencies. Through the analysis of simulation results, the LGAD with a triangle electric field profile in the gain layer has a higher gain efficiency, while the design with a trapezoid electric field profile is less affected by the gain layer thickness and more stable at high temperature. Subsequently, we will develop a set of SiC production processes under the guidance of this work.

Determining neutron-induced reaction cross sections through surrogate reactions at storage rings

Determining the cross sections of neutron-induced reactions on short-lived nuclei is imperative to rate calculations in stellar nucleosynthesis and applications of nuclear physics. It is also an immense experimental challenge due to the radioactivity of the targets involved. Our goal is to circumvent this obstacle by using surrogate reactions in inverse kinematics at the heavy-ion storage rings of GSI/FAIR. We present here preliminary results from the first proof of principle experiment, where a beam of 208Pb impinged on a H2 gas jet target in the Experimental Storage Ring (ESR).

Unbinned deep learning jet substructure measurement in high Q2ep collisions at HERA

The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in high energy particle and nuclear physics. Looking at electron-proton collisions is of particular interest as many of the complications present at hadron colliders are absent. A detailed study of modern jet substructure observables, jet angularities, in electron-proton collisions is presented using data recorded using the H1 detector at HERA. The measurement is unbinned and multi-dimensional, using machine learning to correct for detector effects. All of the available reconstructed object information of the respective jets is interpreted by a graph neural network, achieving superior precision on a selected set of jet angularities. Training these networks was enabled by the use of a large number of GPUs in the Perlmutter supercomputer at Berkeley Lab. The particle jets are reconstructed in the laboratory frame, using the kT jet clustering algorithm. Results are reported at high transverse momentum transfer Q2>150GeV2, and inelasticity 0.2<y<0.7. The analysis is also performed in sub-regions of Q2, thus probing scale dependencies of the substructure variables. The data are compared with a variety of predictions and point towards possible improvements of such models.

Approximate analytical solutions and applications of pantograph-type equations with Caputo derivative and variable orders

This study presents an efficient method that is suitable for differential equations, both with integer-order and fractional derivatives. This study examines the construction of solutions of fractional differential equations that are associated with varying delay proportional to the independent variable using a hybrid of Sumudu transform method. This study considers differential equations with Caputo derivatives of fractional variable orders and their applications in Nuclear Physics. The application indicates that fractional differential equations that have varying delay proportional to the independent variable are useful as tools for the modelling of many anomalous phenomena in nature and in the theory of complex systems.

Melt Blending: A Tool to Simplify Plastic Scintillator Synthesis

Plastic scintillators are widely used as radiation detection media in homeland security and nuclear physics applications. Their attributes include low cost, scalability to large detector volumes, and additive compounding to enable additional material and detection features, such as pulse shape discrimination (PSD), gamma-ray spectroscopy, aging resistance and coincidence timing. However, traditional chemically cured plastic scintillators (CCS) require long reaction times, and hazardous wet chemical procedures performed by specially trained personnel, and can leave residual monomer, resulting in deleterious optical and material properties. Here, we synthesize melt blended scintillators (MBSs) in 2.5 days using easily accessible solid state compounding of commercially-available poly(styrene) with 30-60 wt. % fluorene-based compound ‘P2’ to create monolithic detectors with < 100 ppm residual monomer, in several form factors. The best scintillation performance was recorded for 60 % P2 in Styron 665, including gamma-ray light yield 139 % of EJ-200 commercial scintillator and PSD figure of merit (FOM) value of 2.65 at 478 keVee, approaching P2 OGS. The applicability of MBS to generate fog-resistant scintillators and PMMA-based scintillators for use in challenging environments is also demonstrated.

An active dose-measuring device for X-rays generated by ultra-short, ultra-intense laser pulses

Ultra-short, ultra-intense laser pulses can create extreme physical conditions for a wide range of applications in atomic and molecular physics, materials chemistry, and inertial-confinement fusion. However, laser-matter interactions can be accompanied by significant X-ray emission that introduces radiation risks to the nearby environment and personnel. It is usually to monitor the radiation dose during in high-intensity laser-target interactions with optically stimulated luminescence and thermo-luminescence devices. However, these passive methods cannot measure the radiation dose in real time, while most active dosimeters cannot accurately measure pulsed radiation doses. Here, transient pulse X-ray radiation doses are converted by CdWO4 crystals into slow signals. Because the crystals have a 14-μs luminescence decay time, they can absorb sub-nanosecond X-ray pulses and release the energy at a 100-μs rate, thus reducing the linear-response pressure of subsequent devices. A pulse detector based on a CdWO4 crystal, a phototube, and a custom signal-processing circuit was developed. Experiments were performed at the 45-TW femtosecond laser facility of the Laser Fusion Research Center. The detector deviation was less than ±20% relative to that of an ionization-chamber detector. This initially verified its feasibility for real-time pulsed X-ray radiation detection.

BUQEYE guide to projection-based emulators in nuclear physics

The BUQEYE collaboration (Bayesian Uncertainty Quantification: Errors in Your effective field theory) presents a pedagogical introduction to projection-based, reduced-order emulators for applications in low-energy nuclear physics. The term emulator refers here to a fast surrogate model capable of reliably approximating high-fidelity models. As the general tools employed by these emulators are not yet well-known in the nuclear physics community, we discuss variational and Galerkin projection methods, emphasize the benefits of offline-online decompositions, and explore how these concepts lead to emulators for bound and scattering systems that enable fast and accurate calculations using many different model parameter sets. We also point to future extensions and applications of these emulators for nuclear physics, guided by the mature field of model (order) reduction. All examples discussed here and more are available as interactive, open-source Python code so that practitioners can readily adapt projection-based emulators for their own work.

The ingredients of a successful atomic exhibition in Cold War Italy

ABSTRACT The organization of the mobile atomic exhibition, Mostra Atomica, designed by the United States Information Service to travel through Italy in 1954–55, had to meet technical, scientific, artistic, and political challenges. The head of the group in charge of the exhibition was architect Peter G. Harnden whose pedigree in the intelligence and training in architecture were an ideal match for leading the unit dedicated to exhibitions. The political sensitivity of the Mostra Atomica also required the intervention of the Italian Ministry of the Interior to guarantee safe mobility and secure shows. In every major town, American and British diplomats attended the local opening ceremony, while the very symbol of science diplomacy was Enrico Fermi, whose recorded message praised international cooperation. All in all, the USIS campaign promoting peaceful applications of nuclear physics was successful in reaching and involving Italian society. Visual and spatial aesthetics were particularly relevant: the geometrical design of the exposition rooms conveyed a strong sense of modernity that contrasted with the artistic heritage of Italian cities. The present article is based on archival files, newspaper reports, and photographs that document who was responsible for planning, setting up, and reporting this Cold War propaganda event.

The past and the future of the GAINS spectrometer @ GELINA

GAINS (Gamma Array for Inelastic Neutron Scattering), currently installed at the GELINA (Geel Electron Linear Accelerator) neutron source of the EC-JRC (European Commission-Joint Research Centre), is one of the best instruments available worldwide for measuring high resolution, low uncertainty neutron inelastic cross-section data relevant for both fundamental research and nuclear physics applications (like Generation IV facilities). It features 12 HPGe detectors coupled with a 235U fission chamber for neutron flux monitoring. The paper presents a short history of the GAINS development over the years and reviews some of the main experimental results together with plans for future experiments.

The process of molecular plating and the characteristics of the produced thin films – What we have learned in 60 years and what is still unknown

Molecular plating is a well-established and widely used method for producing thin films of various elements, which are used in variety of nuclear physics applications. Sixty years have passed since the method was established, and some insights into the chemical process underlying the method and the composition of the thin films have been gained. A brief overview of what has been learned about molecular plating since its introduction and the methods applied in the characterization of molecular plated thin films is given here. Through various spectroscopic and microscopic methods, the process of molecular plating and the chemical composition are gradually being elucidated, albeit we still do not understand all aspects.

Digital quantum simulation of an extended Agassi model: Using machine learning to disentangle its phase-diagram

A digital quantum simulation for the extended Agassi model is proposed using a quantum platform with eight trapped ions. The extended Agassi model is an analytically solvable model including both short range pairing and long range monopole-monopole interactions with applications in nuclear physics and in other many-body systems. In addition, it owns a rich phase diagram with different phases and the corresponding phase transition surfaces. The aim of this work is twofold: on one hand, to propose a quantum simulation of the model at the present limits of the trapped ions facilities and, on the other hand, to show how to use a machine learning algorithm on top of the quantum simulation to accurately determine the phase of the system. Concerning the quantum simulation, this proposal is scalable with polynomial resources to larger Agassi systems. Digital quantum simulations of nuclear physics models assisted by machine learning may enable one to outperform the fastest classical computers in determining fundamental aspects of nuclear matter.

A data-enabled physics-informed neural network with comprehensive numerical study on solving neutron diffusion eigenvalue problems

We put forward a data-enabled physics-informed neural network (DEPINN) with comprehensive numerical study for solving industrial scale neutron diffusion eigenvalue problems (NDEPs). In order to achieve an engineering acceptable accuracy for complex engineering problems, a very small amount of prior data from physical experiments are suggested to be used, to improve the accuracy and efficiency of training. We design an adaptive optimization procedure with Adam and LBFGS to accelerate the convergence in the training stage. We discuss the effect of different physical parameters, sampling techniques, loss function allocation and the generalization performance of the proposed DEPINN model for solving complex eigenvalue problems. The feasibility of proposed DEPINN model is verified on three typical benchmark problems, from simple geometry to complex geometry, and from mono-energetic equation to two-group equations. Numerous numerical results show that DEPINN can efficiently solve NDEPs with an appropriate optimization procedure. The proposed DEPINN can be generalized for other input parameter settings once its structure been trained. This work confirms the possibility of DEPINN for practical engineering applications in nuclear reactor physics.