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Articles 1 - 21 of 21
Full-Text Articles in Plasma and Beam Physics
Effects Of Coulomb Collisions On The Structures Of Fast Magnetosonic Shocks, Bo Farnell
Effects Of Coulomb Collisions On The Structures Of Fast Magnetosonic Shocks, Bo Farnell
Physics and Astronomy Undergraduate Senior Theses
We present fully kinetic particle-in-cell simulations demonstrating qualitative effects of binary Coulomb collisions on fast magnetosonic shocks. We find that with a sufficiently high collisional frequency, shock rippling and reformation can be inhibited, creating stationary, laminar shocks. We see that collisions rapidly bring the reflected population into equilibrium with the upstream population, adding credibility to existing theories that the separation of these two populations create these dynamical behaviors around the shock transition region. We also see that Ohmic heating from Coulomb collisions can suppress instabilities.
Applying Machine Learning Methods To Laser Acceleration Of Protons: Synthetic Data For Exploring The High Repetition Rate Regime, John J. Felice, Ronak Desai, Nathaniel Tamminga, Joseph R. Smith, Alona Kryshchenko, Christopher M. Orban, Michael L. Dexter, Anil K. Patnaik
Applying Machine Learning Methods To Laser Acceleration Of Protons: Synthetic Data For Exploring The High Repetition Rate Regime, John J. Felice, Ronak Desai, Nathaniel Tamminga, Joseph R. Smith, Alona Kryshchenko, Christopher M. Orban, Michael L. Dexter, Anil K. Patnaik
Faculty Publications
Advances in ultra‐intense laser technology have increased repetition rates and average power for chirped‐pulse laser systems, which offer a promising solution for many applications including energetic proton sources. An important challenge is the need to optimize and control the proton source by varying some of the many degrees of freedom inherent to the laser‐plasma interactions. Machine learning can play an important role in this task, as our work examines. Building on our earlier work in Desai et al. 2024, we generate a large ∼1.5 million data point synthetic data set for proton acceleration using a physics‐informed analytic model that we …
Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud
Effects Of Plasma-Activated Water On Wheat: Germination And Seedling Development, Wafaa Abdulrazzaq Abdullah, Hadeel O. Ismael, Duaa A. Uamran, Hammad R. Humud
Karbala International Journal of Modern Science
The food sector must contend with issues such as pathogen resistance to some of the available chemical agents, environmental pollution, and climate change to provide healthy food for livestock and people. The application of atmospheric pressure plasma jets (APPJs) is one potential solution for such problems. Plasma is appropriate for effective surface decontamination regarding food products and seeds, surface decontamination, and achieving improved agricultural production yields. The impact of plasma-activated water (PAW) produced by plasma jet discharge (PJD) system on in vitro-cultivated wheat seeds is examined in this work. For this aim, a plasma jet system was constructed with a …
Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Kabe Aberle, Nadia Kako, Kateri Mcrae, Brooke Agulnek, Sky Palmon, Yasmine Ramirez, Francisca Aguirre Beltran, Ashley Juarez, Bridget Kim, Tessa Appel, Sterling Kerr, Spencer Ingley, Gabe Meyer, Robin Tinghitella, Dale Broder, Lily Baeza, Chloe Beers, Julia Coakley, Whitney Kelsey, Sydney Gainforth, Gabi Wing, Audrey Martin, Aaliyah Amore Berry, Brooke Watley, Kiruthika Venkatesan, Rachel Bienstock, Annabella Brotherston, Madison Bryant, Mia Burgener, Emma P. Lieb, Rachel A. Johnson, Jennifer L. Hoffman, Kania Campbell, Kiena Campbell, Courtney Cassidy, Sage Krzyzkowski, Maddox Jones, Skylar Abookire, Luke Hawkins, Sunnah Yoon, Andrea Chu, Yan Qin, Nyah Cubbison, Brian Gearity, Daniel Mcintosh, Mariely Cruz, Edward Garrido, Grady Dionne, Nicole Doris, Lyndsie Salvagio, Ann-Charlotte Granholm-Bentley, Anna Dymov, Hannah Eckert, Gabrielle Welsh, Erica Larson, Charlie Ernst, Anna Zhou, Sarah Watamura, Larissa Fedorovich-Klein, Georgie Fields, Kimberly A. Guevara, Aven Mccall, Ben Peltier, Feruz Yahia, Patrick Flores, Jadyn Floyd, Sophia Forcier, J. Von R. Monteza, Peter Sokol-Hessner, Gwendolyn Geiger, Scott Nichols, Camryn Gunter, Kendal Hengst, Charlie Bednarz, Issy Garside, Addison Baker, Rachel Mina, Brooke Hermanson, Amanda Klingler, William Highfill, Sydney Jaques, Kerstin Lewey, Allison Grossery, Daniel Linseman, Ethan Lim, Jagger Livengood, Owen Mantelli, Gabby Pappas, Abby Mcdonald, Madeleine Dierking, Eve Miller, Emma Loeber, Anna Marlow, Michael Kerwin, Ella Mathews, Hillary Hamann, Khadija Mohamed, Vivian Nguyen, Gabri Notov, Ifunayachi Ogbonna-Ukuku, Sunil Kumar, Charles Baysah, Sarah Olson, Don Sullivan, Anna Paradiso, Jay Parrish, Mira Pronobis, Alisha Pravasi, Kerstin Haring, Diego Ramirez, Christopher Reardon, Juliana Ramirez, Casey Doherty, Ella Kestner, Teagan Weindel, Cate Billings, Pablo Torre-Walter, Lucy Rand, Samantha Reynolds, Mark Siemens, Khadeeja Rashid, Laine Satterlee, Piper Heilbronner, Lily Pound, Ben Whitehurst, Anna Respet, Lizzie Lesoing, Sydney Hertel, Aya Saad-Masri, Brooke Ballenger, Max Proske, Hannah Rosenberg, Ellia Nakahara, Sophia Espinoza, Ivan Woolhouse, Simon Ruland, Gorkem Er, Timothy Sweeny, Melaku Saketa, Michela Schenk, Maren Lynch, Madi Hamm, Grace Schroeder, Michelle Rozenman, Rana Seif, Jackson Hall, Marisela Simental, Daniel Paredes, Aaron Mena, Preston Spaan, Evelyn Stovin, David Andrew Swartz, Anh Tran, Daniel Pittman, Luke Farchione, Emily Boyer, Ukari Verner, Lacey Conrad, Jonathan Velotta, James Weiner, Jagger Gossett, Noah Sherry, Sam Proud, Ben Block, Avi Narayana, Zoey Weiss, Alyssa Wilson, Gabrielle Walsh, David Zonana, Keely Wright, Kena Riveria, Lillybelle Deer, Jena Doom, Elysia Davis, Isabelle Yaremenko, Caitlyn Young
Du Undergraduate Showcase Abstracts: Research, Scholarship, And Creative Works, Kabe Aberle, Nadia Kako, Kateri Mcrae, Brooke Agulnek, Sky Palmon, Yasmine Ramirez, Francisca Aguirre Beltran, Ashley Juarez, Bridget Kim, Tessa Appel, Sterling Kerr, Spencer Ingley, Gabe Meyer, Robin Tinghitella, Dale Broder, Lily Baeza, Chloe Beers, Julia Coakley, Whitney Kelsey, Sydney Gainforth, Gabi Wing, Audrey Martin, Aaliyah Amore Berry, Brooke Watley, Kiruthika Venkatesan, Rachel Bienstock, Annabella Brotherston, Madison Bryant, Mia Burgener, Emma P. Lieb, Rachel A. Johnson, Jennifer L. Hoffman, Kania Campbell, Kiena Campbell, Courtney Cassidy, Sage Krzyzkowski, Maddox Jones, Skylar Abookire, Luke Hawkins, Sunnah Yoon, Andrea Chu, Yan Qin, Nyah Cubbison, Brian Gearity, Daniel Mcintosh, Mariely Cruz, Edward Garrido, Grady Dionne, Nicole Doris, Lyndsie Salvagio, Ann-Charlotte Granholm-Bentley, Anna Dymov, Hannah Eckert, Gabrielle Welsh, Erica Larson, Charlie Ernst, Anna Zhou, Sarah Watamura, Larissa Fedorovich-Klein, Georgie Fields, Kimberly A. Guevara, Aven Mccall, Ben Peltier, Feruz Yahia, Patrick Flores, Jadyn Floyd, Sophia Forcier, J. Von R. Monteza, Peter Sokol-Hessner, Gwendolyn Geiger, Scott Nichols, Camryn Gunter, Kendal Hengst, Charlie Bednarz, Issy Garside, Addison Baker, Rachel Mina, Brooke Hermanson, Amanda Klingler, William Highfill, Sydney Jaques, Kerstin Lewey, Allison Grossery, Daniel Linseman, Ethan Lim, Jagger Livengood, Owen Mantelli, Gabby Pappas, Abby Mcdonald, Madeleine Dierking, Eve Miller, Emma Loeber, Anna Marlow, Michael Kerwin, Ella Mathews, Hillary Hamann, Khadija Mohamed, Vivian Nguyen, Gabri Notov, Ifunayachi Ogbonna-Ukuku, Sunil Kumar, Charles Baysah, Sarah Olson, Don Sullivan, Anna Paradiso, Jay Parrish, Mira Pronobis, Alisha Pravasi, Kerstin Haring, Diego Ramirez, Christopher Reardon, Juliana Ramirez, Casey Doherty, Ella Kestner, Teagan Weindel, Cate Billings, Pablo Torre-Walter, Lucy Rand, Samantha Reynolds, Mark Siemens, Khadeeja Rashid, Laine Satterlee, Piper Heilbronner, Lily Pound, Ben Whitehurst, Anna Respet, Lizzie Lesoing, Sydney Hertel, Aya Saad-Masri, Brooke Ballenger, Max Proske, Hannah Rosenberg, Ellia Nakahara, Sophia Espinoza, Ivan Woolhouse, Simon Ruland, Gorkem Er, Timothy Sweeny, Melaku Saketa, Michela Schenk, Maren Lynch, Madi Hamm, Grace Schroeder, Michelle Rozenman, Rana Seif, Jackson Hall, Marisela Simental, Daniel Paredes, Aaron Mena, Preston Spaan, Evelyn Stovin, David Andrew Swartz, Anh Tran, Daniel Pittman, Luke Farchione, Emily Boyer, Ukari Verner, Lacey Conrad, Jonathan Velotta, James Weiner, Jagger Gossett, Noah Sherry, Sam Proud, Ben Block, Avi Narayana, Zoey Weiss, Alyssa Wilson, Gabrielle Walsh, David Zonana, Keely Wright, Kena Riveria, Lillybelle Deer, Jena Doom, Elysia Davis, Isabelle Yaremenko, Caitlyn Young
DU Undergraduate Research Journal Archive
Abstracts from the DU Undergraduate Research Showcase.
Applying Machine‐Learning Methods To Laser Acceleration Of Protons: Lessons Learned From Synthetic Data, Ronak Desai, Thomas Zhang, J. J. Felice, Ricky Oropeza, Joseph R. Smith, Alona Kryshchenko, Chris Orban, Michael L. Dexter, Anil K. Patnaik
Applying Machine‐Learning Methods To Laser Acceleration Of Protons: Lessons Learned From Synthetic Data, Ronak Desai, Thomas Zhang, J. J. Felice, Ricky Oropeza, Joseph R. Smith, Alona Kryshchenko, Chris Orban, Michael L. Dexter, Anil K. Patnaik
Faculty Publications
In this study, we consider three different machine-learning methods—a three-hidden-layer neural network, support vector regression, and Gaussian process regression—and compare how well they can learn from a synthetic data set for proton acceleration in the Target Normal Sheath Acceleration regime. The synthetic data set was generated from a previously published theoretical model by Fuchs et al. 2005 that we modified. Once trained, these machine-learning methods can assist with efforts to maximize the peak proton energy, or with the more general problem of configuring the laser system to produce a proton energy spectrum with desired characteristics. In our study, we focus …
Artificial Intelligence, Controls, And Sensor Fusion For Optimization And Modeling Of Space Missions And Particle Accelerators, Reza Pirayeshshirazinezhad
Artificial Intelligence, Controls, And Sensor Fusion For Optimization And Modeling Of Space Missions And Particle Accelerators, Reza Pirayeshshirazinezhad
Mechanical Engineering ETDs
This PhD dissertation is devoted to developing artificial intelligence (AI) applications for space missions and particle accelerators considering constraints on the computational resources. The space mission studied in this research, the Virtual Telescope for X-ray Observations (VTXO), is the mission exploiting 2 6U-CubeSats operating in a precision formation. The goal of the VTXO project is to develop a space-based, X-ray imaging telescope with high angular resolution precision. VTXO space mission is designed and the mission is optimized to increase the performance of the mission. Trajectory optimization with AI, hybrid control, control algorithms, and high performance computing are all used to …
Synthesis Of Cuo/Zno And Mgo/Zno Core/Shell Nanoparticles With Plasma Jets And Study Of Their Structural And Optical Properties, Raghad S. Mohammed, Kadhim A. Aadim, Khalid A. Ahmed
Synthesis Of Cuo/Zno And Mgo/Zno Core/Shell Nanoparticles With Plasma Jets And Study Of Their Structural And Optical Properties, Raghad S. Mohammed, Kadhim A. Aadim, Khalid A. Ahmed
Karbala International Journal of Modern Science
This paper reports the synthesis of CuO/ZnO and MgO/ZnO core/shell nanoparticles using atmospheric plasma jets. The characterization of the synthesized CuO/ZnO and MgO/ZnO core/shell nanoparticles were confirmed by a series of techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray dispersive spectroscopy (EDS), transmission electron microscopy (TEM), and UV–Vis spectroscopy. The XRD analysis confirmed no other peaks related to the secondary phases for CuO, MgO, or ZnO, indicating the purity of these nanoparticles. Additionally, EDX analysis confirmed the formation of high purity CuO/ZnO and MgO/ZnO core/shell nanoparticles. The surface morphology, which represented the high agglomeration rate, was investigated using …
Lattice Optics Optimization For Recirculatory Energy Recovery Linacs With Multi-Objective Optimization, Isurumali Neththikumara, Todd Satogata, Alex Bogacz, Ryan Bodenstein, Arthur Vandenhoeke
Lattice Optics Optimization For Recirculatory Energy Recovery Linacs With Multi-Objective Optimization, Isurumali Neththikumara, Todd Satogata, Alex Bogacz, Ryan Bodenstein, Arthur Vandenhoeke
College of Sciences Posters
Beamline optics design for recirculatory linear accelerators requires special attention to suppress beam instabilities arising due to collective effects. The impact of these collective effects becomes more pronounced with the addition of energy recovery (ER) capability. Jefferson Lab’s multi-pass, multi-GeV ER proposal for the CEBAF accelerator, ER@CEBAF, is a 10- pass ER demonstration with low beam current. Tighter control of the beam parameters at lower energies is necessary to avoid beam break-up (BBU) instabilities, even with a small beam current. Optics optimizations require balancing both beta excursions at high-energy passes and overfocusing at low-energy passes. Here, we discuss an optics …
Equations Of State For Warm Dense Carbon From Quantum Espresso, Derek J. Schauss
Equations Of State For Warm Dense Carbon From Quantum Espresso, Derek J. Schauss
Theses and Dissertations
Warm dense plasma is the matter that exists, roughly, in the range of 10,000 to 10,000,000 Kelvin and has solid-like densities, typically between 0.1 and 10 grams per centimeter. Warm dense fluids like hydrogen, helium, and carbon are believed to make up the interiors of many planets, white dwarfs, and other stars in our universe. The existence of warm dense matter (WDM) on Earth, however, is very rare, as it can only be created with high-energy sources like a nuclear explosion. In such an event, theoretical and computational models that accurately predict the response of certain materials are thus very …
Numerical Model Of A Radio Frequency Ion Source For Fusion Plasma Using Particle-In-Cell And Finite Difference Time Domain, Augustin L. Griswold
Numerical Model Of A Radio Frequency Ion Source For Fusion Plasma Using Particle-In-Cell And Finite Difference Time Domain, Augustin L. Griswold
University Honors Theses
Radio frequency (RF) plasma sources are common tool for application and study, and of particular interest for inertial electrostatic (IEC) fusion. Computational analysis is often carried out using particle in cell (PIC) methods or finite difference time domain (FDTD). However, a more holistic analysis is necessary as the particle distribution is highly dependant on the fields created by the plasma source. Herein, an analysis of a particular planar RF electrode with deuterium gas is provided which covers the fields and the particle behaviour using first FDTD then PIC. Further applications are discussed as well as further directions for this study.
Optimization And Control Of Production Of Graphene, Atharva Hans, Nimish M. Awalgaonkar, Majed Alrefae, Ilias Bilionis, Timothy S. Fisher
Optimization And Control Of Production Of Graphene, Atharva Hans, Nimish M. Awalgaonkar, Majed Alrefae, Ilias Bilionis, Timothy S. Fisher
The Summer Undergraduate Research Fellowship (SURF) Symposium
Graphene is a 2-dimensional element of high practical importance. Despite its exceptional properties, graphene’s real applications in industrial or commercial products have been limited. There are many methods to produce graphene, but none has been successful in commercializing its production. Roll-to-roll plasma chemical vapor deposition (CVD) is used to manufacture graphene at large scale. In this research, we present a Bayesian linear regression model to predict the roll-to-roll plasma system’s electrode voltage and current; given a particular set of inputs. The inputs of the plasma system are power, pressure and concentration of gases; hydrogen, methane, oxygen, nitrogen and argon. This …
Long-Term Simulations Of Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, R. Majeti, C. Cotnoir, M. Stefani, D. Ranjan, A. Godunov, V. Morozov, H. Zhang, F. Lin, Y. Roblin, E. Nissen, T. Satogata
Long-Term Simulations Of Beam-Beam Dynamics On Gpus, B. Terzić, K. Arumugam, R. Majeti, C. Cotnoir, M. Stefani, D. Ranjan, A. Godunov, V. Morozov, H. Zhang, F. Lin, Y. Roblin, E. Nissen, T. Satogata
Physics Faculty Publications
Future machines such as the electron-ion colliders (JLEIC), linac-ring machines (eRHIC) or LHeC are particularly sensitive to beam-beam effects. This is the limiting factor for long-term stability and high luminosity reach. The complexity of the non-linear dynamics makes it challenging to perform such simulations which require millions of turns. Until recently, most of the methods used linear approximations and/or tracking for a limited number of turns. We have developed a framework which exploits a massively parallel Graphical Processing Units (GPU) architecture to allow for tracking millions of turns in a sympletic way up to an arbitrary order and colliding them …
Simulations Of Coherent Synchrotron Radiation On Parallel Hybrid Gpu/Cpu Platform, B. Terzić, K. Arumugam, D. Duffin, A. Godunov, T. Islam, D. Ranjan, S. Sangam, Mohammad Zubair
Simulations Of Coherent Synchrotron Radiation On Parallel Hybrid Gpu/Cpu Platform, B. Terzić, K. Arumugam, D. Duffin, A. Godunov, T. Islam, D. Ranjan, S. Sangam, Mohammad Zubair
Physics Faculty Publications
Coherent synchrotron radiation (CSR) is an effect of self-interaction of an electron bunch as it traverses a curved path. It can cause a significant emittance degradation, as well as fragmentation and microbunching. Numerical simulations of the 2D/3D CSR effects have been extremely challenging due to computational bottlenecks associated with calculating retarded potentials via integrating over the history of the bunch. We present a new high-performance 2D, particle-in-cell code which uses massively parallel multicore GPU/GPU platforms to alleviate computational bottlenecks. The code formulates the CSR problem from first principles by using the retarded scalar and vector potentials to compute the self-interaction …
Exploring Mathematical Strategies For Finding Hidden Features In Multi-Dimensional Big Datasets, Tri Duong, Fang Ren, Apurva Mehta
Exploring Mathematical Strategies For Finding Hidden Features In Multi-Dimensional Big Datasets, Tri Duong, Fang Ren, Apurva Mehta
STAR Program Research Presentations
With advances in technology in brighter sources and larger and faster detectors, the amount of data generated at national user facilities such as SLAC is increasing exponentially. Humans have a superb ability to recognize patterns in complex and noisy data and therefore, data is still curated and analyzed by humans. However, a human brain is unable to keep up with the accelerated pace of data generation, and as a consequence, the rate of new discoveries hasn't kept pace with the rate of data creation. Therefore, new procedures to quickly assess and analyze the data are needed. Machine learning approaches are …
Optimization And Coding Of A Lcls Control Program, Tanner M. Worden
Optimization And Coding Of A Lcls Control Program, Tanner M. Worden
STAR Program Research Presentations
SLAS’s, Linac Coherent Light Source (LCLS) also known as X-ray free-electron laser (XFEL) is the first X-ray laser of its kind. It gave Scientist from around the world the unique ability to observe the world at a subatomic level. Allowing for major advancements in the field of biological chemistry, drug science, material science and many more. Since the LCLS is a fairly unique scientific instrument, the demand for its use by the scientific community has always been high since it turned on back in 2009. This means that any and all time that the laser is not being used for …
Simulation Of Nuclear Fusion Using A One Dimensional Particle In Cell Method, Steven T. Margell
Simulation Of Nuclear Fusion Using A One Dimensional Particle In Cell Method, Steven T. Margell
Cal Poly Humboldt theses and projects
In this thesis several novel techniques are developed to simulate fusion events in an isotropic, electrostatic three-dimensional Deuterium-Tritium plasma. These techniques allow us to accurately predict three-dimensional collision events with a one-dimensional model while simultaneously reducing compute time via a nearest neighbor algorithm. Furthermore, a fusion model based on first principles is developed that yields an average fusion reactivity which correlates well with empirical results.
Simulations Of Hl-Lhc Crab Cavity Noise Using Headtail, Stanley Steeper
Simulations Of Hl-Lhc Crab Cavity Noise Using Headtail, Stanley Steeper
Physics
The High Luminosity Large Hadron Collider (Hi-Lumi LHC) upgrade -- scheduled to be completed by 2025 -- will improve the existing LHC in many ways. One such upgrade is the addition of Crab Cavities (CCs). The CCs are resonant structures that provide strong transverse kicks to the circulating clouds of particles around each interaction region. As such, the CCs result in a head-on collision of the clouds and a large increase in event rate, leading to reduced statistical uncertainty and potentially faster discoveries. However, the CC field will be modulated by phase and amplitude noise which can have detrimental effects …
Preconditioning Visco-Resistive Mhd For Tokamak Plasmas, Daniel R. Reynolds, Ravi Samtaney, Hilari C. Tiedeman
Preconditioning Visco-Resistive Mhd For Tokamak Plasmas, Daniel R. Reynolds, Ravi Samtaney, Hilari C. Tiedeman
Mathematics Research
No abstract provided.
Reply To "Comment On ‘Atomic Spectral Line Free-Parameter Deconvolution Procedure’”, Vladimir Milosavljevic, Goran Poparic
Reply To "Comment On ‘Atomic Spectral Line Free-Parameter Deconvolution Procedure’”, Vladimir Milosavljevic, Goran Poparic
Articles
We do not agree with the authors of the preceding Comment [X. Nikolic, X. Ojurovic, and X. Mijatovic, Phys. Rev. E, 67, 058401, 2003]. Our numerical procedure for the deconvolution of the theoretical asymmetric convolution integral of a Gaussian and a plasma broadened spectral line profile jA,R(λ) for spectral lines enables the determination of all broadening parameters. All broadening parameters can be determined directly from the recorded line profile of a single line, with minimal assumptions or prior knowledge. Additional experimental diagnostics are not required.
Failure Mechanisms Of High Temperature Semiconductor Lasers, David H. Leicester
Failure Mechanisms Of High Temperature Semiconductor Lasers, David H. Leicester
Theses and Dissertations
The primary intent of this research was to determine the influence of three common degradation mechanisms, dark area defects, facet degradation, and contact degradation, on the operational lifetime of GaAs edge-emitting semiconductor lasers driven by continuous current at 100°C. Inherent to this work was the quantified characterization of the lasers during their operation. This characterization arose as the power output as a function of driving current at room temperature before and after laser exposure to 100°C ambient temperature. These power vs. current characterizations were conducted at room temperature on each laser before and after exposure to 100°C as well as …
Computer Model Of An Injection Locked Pulsed Co2 Laser, Allen M. Susie
Computer Model Of An Injection Locked Pulsed Co2 Laser, Allen M. Susie
Theses and Dissertations
With the discovery of the laser there have been continual attempts to increase the 'spectral brightness' of a laser for applications such as signal processing and lidar. To this end techniques using either passive or active cavity elements have been developed to isolate a single longitudinal mode in both continuous and pulsed laser systems. Although passive elements have useful applications in continuous systems their use in pulsed systems is difficult to control. The injection of an external signal has proved very successful.