DOCSLIB.ORG

Semiclassical Modeling of Multiparticle Quantum Mechanics

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Semiclassical Modeling of Multiparticle Quantum Mechanics UNIVERSITY OF CALIFORNIA Los Angeles Semiclassical Modeling of Quantum-Mechanical Multiparticle Systems using Parallel Particle-In-Cell Methods A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Physics by Dean Edward Dauger 2001 © Copyright by Dean Edward Dauger 2001 To my parents, Alan and Marlene, who were always fully supportive of my work and my endeavors. And Charlie and Allegra, my cats. And to all those who have a vision, a dream of something new and inspiring, to express that Idea, limited only by its own conclusion if it has one. iii Contents I. Introduction A. Motivation ···················································································1 B. Existing Methods ···················································································6 C. Outline ···················································································8 D. Conventions ···················································································9 II. Theory A. The Approach ·················································································11 B. Feynman Path Integrals···············································································13 C. The Semiclassical Approximation·······························································18 D. Initial Position and Final Momentum·························································21 E. The Matrix ··················································································23 F. The Determinant ··················································································26 G. Summary ··················································································30 III. Implementation A. The Numbers ··················································································32 B. The Plasma PIC Code ··················································································36 C. The Quantum PIC Code ··············································································42 iv D. Boundary Conditions ··················································································53 E. Simulation Parameters·················································································56 F. Alternative Implementations······································································60 IV. Validation A. Output ··················································································61 B. Free-Space Gaussian ··················································································62 C. Simple Harmonic Oscillator·········································································67 D. Infinite Square Well ··················································································74 E. Barriers ··················································································80 F. Fermion Statistics ··················································································83 V. The One-Dimensional Atom A. The Problem ··················································································92 B. The One-Electron Case·················································································93 C. The Two-Electron Case················································································97 D. Eigenstate Extraction ················································································100 E. Conclusion ················································································106 VI. Energy Fluctuations in a Plasma A. The Problem ················································································107 v B. The Model and the Analysis······································································111 C. Implementation ················································································112 D. Proper Comparison ················································································114 E. Quantum Theory and Simulation ····························································122 F. Conclusion ················································································131 VII. Future Work A. The Future ················································································137 B. One Dimension ················································································138 C. Higher Dimensions ················································································141 D. Evolution of the Implementation·····························································146 E. Evolution of the Methods··········································································150 F. Conclusion ················································································159 VIII. Appendix A - Development of a New Code A. Experimentation ················································································160 B. Virtual Particle Distribution·······································································161 C. Alternative Depositing···············································································163 vi IX. Appendix B - The Quantum PIC Source Code A. Source Code ················································································170 B. Main Program ················································································170 C. External Potential ················································································188 D. Particle Preparation ················································································190 E. Particle Push ················································································197 F. Wavefunction Reconstruction/Particle Deposit·····································200 X. Appendix C - Source Code for Visualization and Data Formats A. Visualization ················································································213 B. Quantum Correlation Analysis, Eigenstate Extraction, and Data Reader ················································································216 XI. References ················································································260 vii List of Figures Figure Page 1 An arbitrary path from x0 to xN . 17 2 A classical path is shown, accompanied by variations on that path. 20 3 Particles in space overlaid with a grid in one dimension. 38 4 Simplified flow chart for the plasma PIC code. 39 5 Particles in space partitioned into four cells. 41 6 Simplified flow chart for the quantum PIC code. 44 7 A virtual classical particle reflecting at one-half grid point behind the l (x = 0) = 0 boundary of the well. 55 8 Four frames of the evolution of a stationary Gaussian in free space. 64 9 Four frames of the evolution of the ground state of the simple harmonic oscillator. 69 10 Frames from simulations of the n =1 , n = 5 , and n = 7 eigenstates of the simple harmonic oscillator. 70 11 Three frames from the evolution of an arbitrarily chosen superposition of the n = 0 , n =1 , n = 5 , and n = 7 eigenstates of the simple harmonic oscillator. 72 12 Energy spectrum of the simulation shown in Figure 11. 73 13 A moving Gaussian bouncing off a wall of the infinite square well. 75 viii 14 Example eigenstates of the infinite square well. 78 15 Evolution of a Gaussian wavefunction colliding with a square barrier. 82 16 A pair of frames each from a pair of wavefunctions in an infinite square well. 85 17 Energy spectrum from the evolution of a fermion pair initialized using the five lowest energy eigenstates of the infinite square well. 88 18 Energy spectrum from the evolution of a fermion pair initialized using arbitrarily chosen Gaussians. 90 19 Frames from the evolution of an electron bound to a one-dimensional atom. 95 20 Energy spectrum of a simulation shown in Figure 19. 96 21 Four frames from two-electrons bound to a one-dimensional atom. 98 22 Energy spectrum of the fermionic two-electron simulation shown in Figure 21. 99 23 Five energy eigenstates extracted from the one-electron one-dimensional atom simulation seen in Figure 19. 102 24 Five two-electron fermionic eigenstates of the one-dimensional atom. 104 25 Placement of initial positions of the particles for the hot plasma. 113 26 Energy spectra of the longitudinal electric field in a hot plasma assuming classical theory. 116 ix 27 Energy spectra of the longitudinal electric field in a hot plasma using a 128-particle plasma simulation that assumes classical theory. 118 28 Energy spectra of the longitudinal electric field in a hot plasma using a 12,800-particle plasma simulation that assumes classical theory. 119 29 Energy spectra of the longitudinal electric field in a hot plasma using a 1,024,000-particle plasma simulation that assumes classical theory. 121 30 Energy spectra of the longitudinal electric field in a hot plasma using quantum theory and classical theory. 124 31 Three frames from the evolution of a set of Gaussians representing a hot plasma. 126 32 Energy spectra of the longitudinal electric field in a hot plasma, shown in Figure 31, while including quantum-mechanical effects. 128 33 A comparison against a classical simulation of the energy spectra of the longitudinal electric field in a hot plasma, shown in Figure 31, while accounting for quantum-mechanical effects. 129 34 Energy spectra of the longitudinal electric field in a hot plasma at low k while accounting for quantum-mechanical effects. 133 35 A comparison of runs using randomly
Load more

Recommended publications
  • Verification of Gyrokinetic Codes: Theoretical Background & Numerical Implementations
    N.Tronko 1, T.Goerler 2 , A.Bottino 2 , B.D.Scott 2, E.Sonnendrücker 1 Verification of Gyrokinetic codes: Theoretical background & Numerical implementations NumKin 2016, IRMA, Strasbourg, France 1 NMPP, Max Planck Institute für Plasmaphysik 2 TOK, Max Planck Institute für Plasmaphysik VeriGyro Project Participants Enabling Research Project on Verification of Gyrokinetic codes • Germany! Max Planck Insitute for Plasma Physics (Garching and Greifswald) • Switzerland SPC-EPFL, Lausanne • Finland! Aalto Univeristy • Great Britain University of Warwick • France CEA Cadarache, Université Paris IV, Rennes, Toulouse, Lorraine, Bretagne IRMA, Maison de la Simulation (Saclay) • USA Saint Michel’s College, VT NumKin 2016 VeriGyro Project @ IPP Garching Interdisciplinary Project in IPP Max Planck (Garching) NMPP Division (Numerical Methods for Plasma Physics) • Development and implementation of new algorithms for fusion and astrophysical plasma modeling • Development of libraries (i.e. Selalib) • Verification of existing codes • Participants: N. Tronko, E. Sonnendrücker Enabling Research Project VeriGyro TOK (Tokamak Theory) • Development of major codes • Plasma modeling and comparison with experimental results (ASDEX Upgrade) • Participants: T. Görler, A. Bottino, B. D. Scott NumKin 2016 VeriGyro Project: Motivation • Verification of Global (Electromagnetic) Gyrokinetic codes: Why? • Most popular tools for magnetised plasmas simulations: • Significant Development since last 10 years • Electrostatic gyrokinetic implementations : well established ! [Dimits
    [Show full text]
  • Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
    processes Review Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development Outi M. H. Salo-Ahen 1,2,* , Ida Alanko 1,2, Rajendra Bhadane 1,2 , Alexandre M. J. J. Bonvin 3,* , Rodrigo Vargas Honorato 3, Shakhawath Hossain 4 , André H. Juffer 5 , Aleksei Kabedev 4, Maija Lahtela-Kakkonen 6, Anders Støttrup Larsen 7, Eveline Lescrinier 8 , Parthiban Marimuthu 1,2 , Muhammad Usman Mirza 8 , Ghulam Mustafa 9, Ariane Nunes-Alves 10,11,* , Tatu Pantsar 6,12, Atefeh Saadabadi 1,2 , Kalaimathy Singaravelu 13 and Michiel Vanmeert 8 1 Pharmaceutical Sciences Laboratory (Pharmacy), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland; ida.alanko@abo.fi (I.A.); rajendra.bhadane@abo.fi (R.B.); parthiban.marimuthu@abo.fi (P.M.); atefeh.saadabadi@abo.fi (A.S.) 2 Structural Bioinformatics Laboratory (Biochemistry), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland 3 Faculty of Science-Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, 3584 CH Utrecht, The Netherlands; [email protected] 4 Swedish Drug Delivery Forum (SDDF), Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden; [email protected] (S.H.); [email protected] (A.K.) 5 Biocenter Oulu & Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7 A, FI-90014 Oulu, Finland; andre.juffer@oulu.fi 6 School of Pharmacy, University of Eastern Finland, FI-70210 Kuopio, Finland; maija.lahtela-kakkonen@uef.fi (M.L.-K.); tatu.pantsar@uef.fi
    [Show full text]
  • Department of Physics Scheme of Instruction
    Department Of Physics OsmaniaUniversity Scheme of Instruction and Syllabus B.Sc Physics (I – VI Semesters) Under CBCS scheme (from the academic year 2016-2017) 1 B.Sc. PHYSICS SYLLABUS UNDER CBCS SCHEME SCHEME OF INSTRUCTION Semester Paper [ Theory and Practical ] Instructions Marks Credits Hrs/week I sem Paper – I : Mechanics 100 4 4 Practicals – I : Mechanics 3 50 1 II sem Paper – II: Waves and Oscillations 100 4 4 Practicals – II : Waves and Oscillations 3 50 1 III sem Paper – III : Thermodynamics 100 4 4 Practicals – III : Thermodynamics 3 50 1 IV sem Paper – IV : Optics 4 100 4 Practicals – IV :Optics 3 50 1 Paper –V : Electromagnetism 3 100 3 Practicals – V: Electromagnetism 3 50 1 V sem Paper – VI : Elective – I 100 3 Solid state physics/ 3 Quantum Mechanics and Applications Practicals – VI : Elective – I Practical 50 1 Solid state physics/ 3 Quantum Mechanics and Applications Paper – VII : Modern Physics 3 100 3 Practical – VII : Modern Physics Lab 3 50 1 VI sem Paper – VIII : Elective – II 100 3 Basic Electronics/ 3 Physics of Semiconductor Devices Practicals – VIII : Elective – II Practical 50 1 Basic Electronics/ 3 Physics of Semiconductor Devices Total Credits 36 2 B.Sc. (Physics)Semester I-Theory Syllabus 56hrs Paper – I:Mechanics (W.E.F the academic year 2016-2017) (CBCS) Unit – I 1. Vector Analysis (14) Scalar and vector fields, gradient of a scalar field and its physical significance.Divergence and curl of a vector field and related problems.Vector integration, line, surface and volume integrals.Stokes, Gauss and Greens theorems- simple applications. Unit – II 2.
    [Show full text]
  • 1 the Derivation of Particle Monte Carlo Methods for Plasma Modeling
    The derivation of Particle Monte Carlo methods for plasma modeling from transport equations. Savino Longo Dipartimento di Chimica dell'Università and CNR/IMIP, Via Orabona 4, 70126 Bari, Italy. e-mail: [email protected] Abstract: We analyze here in some detail, the derivation of the Particle and Monte Carlo methods of plasma simulation, such as Particle in Cell (PIC), Monte Carlo (MC) and Particle in Cell / Monte Carlo (PIC/MC) from formal manipulation of transport equations. Keywords: Charged Particle Transport, Boltzmann Equation, Monte Carlo Methods, Particle-in-Cell, Vlasov/Boltzmann equation 1 1.Introduction An accurate calculation of the velocity distribution of charged particles in non equilibrium plasmas is necessary in order to evaluate the rate at which collisional elementary processes take place in these media as well as their transport properties [1]. In doing so, one has to take into account the effect of inertia, scattering, externally applied and self-coherent fields, all affecting the particle transport. To this aim, different particle simulation techniques have been used extensively, as an alternative to the grid-based solution of transport equations [1] by finite differences or finite element techniques. To these belong the very well-know Test Particle Monte Carlo (TPMC, or simply Monte Carlo, MC [1]), the Particle in Cell (PIC [2,3]) and Particle in Cell / Monte Carlo methods (PIC/MC [4]). No explicit description of the methods will be given here because of their widespread application within the plasma modelling community, and we assume in the following that they are already known to the reader.
    [Show full text]
  • Determining Equilibrium Structures and Potential Energy Functions for Diatomic Molecules Robert J
    Chapter 6 Determining Equilibrium Structures and Potential Energy Functions for Diatomic Molecules Robert J. Le Roy CONTENTS 1 6.0 Introduction 6.1 Quantum Mechanics of Vibration and Rotation 6.2 Semiclassical Methods 6.2.1 The semiclassical quantization condition 6.2.2 The Rydberg-Klein-Rees (RKR) inversion procedure 6.2.3 Near-dissociation theory (NDT) 6.2.4 Conclusions regarding semiclassical methods 6.3 Quantum-Mechanical Direct-Potential-Fit Methods 6.3.1 Overview and background 6.3.2 Potential function forms 6.3.2 A Polynomial Potential Function Forms 6.3.2 B The Expanded Morse Oscillator (EMO) Potential Form and the Importance of the Definition of the Expansion Variable 6.3.2 C The Morse/Long-Range (MLR) Potential Form 6.3.2 D The Spline-Pointwise Potential Form 6.3.3 Initial trial parameters for direct potential fits 6.4 Born-Oppenheimer Breakdown Effects 6.5 Concluding Remarks Appendix: What terms contribute to a long-range potential? Exercises References Because the Hamiltonian governing the vibration-rotation motion of diatomic molecules is essen- tially one dimensional, the theory is relatively tractable, and analyses of experimental data can be much more sophisticated than is possible for polyatomics. It is therefore possible to deter- mine equilibrium structures to very high precision – up to 10−6 A˚ – and often also to determine accurate potential energy functions spanning the whole potential energy well. The traditional way of doing this involves first determining the v-dependence of the vibrational level energies Gv and inertial rotational constants Bv, and then using a semiclassical inversion procedure to 1 Chapter 6, pp.
    [Show full text]
  • Computational Plasma Physics
    Computational plasma physics S. Possanner and E. Sonnendr¨ucker Max-Planck-Institut f¨urPlasmaphysik und Zentrum Mathematik, TU M¨unchen Lecture notes Sommersemester 2019 April 26, 2019 Contents 1 Introduction2 1.1 Scientific computing..........................2 1.2 Plasmas.................................4 1.3 Model equations.............................4 1.3.1 The N-body model.......................6 1.3.2 Kinetic models.........................7 1.3.3 Fluid models..........................9 1 Chapter 1 Introduction 1.1 Scientific computing Understanding an experiment in physics relies on a model which is generally a differential equation or a partial differential equation or a system involving many of these. In sufficiently simple cases analytical solutions of these models exist and then this can be used to predict the behaviour of a similar experiment. However in many cases, especially when the model is based on first principles, it is so complex that there is no analytical solution available. Then there are two options: the first is to simplify the model until it can be analytically solved, the second is to compute an approximate solution using a computer. In practice both are usually done, the simplified models being used to verify that the code is working properly. Due to the enormous development of computer resources in the last 50 years, quite realistic simulations of physical problems become now possible. A large amount of theoretical work in physics and related disciplines, in particular in plasma physics, now relies quite heavily on numerical simulation. Computational sciences have emerged next to theory and experiments as a third pillar in physics and engineering. Designing efficient, robust and accurate simulation codes is a challenging task that is at the interface of the application domain, plasma physics in our case, applied mathematics and computer science.
    [Show full text]
  • Computational Modeling of Fully Ionized Magnetized Plasmas Using the fluid Approximationa…
    PHYSICS OF PLASMAS 13, 058103 ͑2006͒ Computational modeling of fully ionized magnetized plasmas using the fluid approximationa… ͒ D. D. Schnackb Center for Energy and Space Science, Science Applications International Corporation, 10260 Campus Point Drive, San Diego, California 92121 D. C. Barnes Center for Integrated Plasma Studies, University of Colorado, 2000 Colorado Avenue, Boulder, Colorado 80309 D. P. Brennan General Atomics, P.O. Box 85608, San Diego, California 92186 C. C. Hegna Department of Engineering Physics, University of Wisconsin, 1500 Engineering Drive, Madison, Wisconsin 53706 E. Held Department of Physics, Utah State University, Logan, Utah 84322 C. C. Kim Department of Engineering Physics, University of Wisconsin, 1500 Engineering Drive, Madison, Wisconsin 53706 and Plasma Science and Innovation Center, University of Washington, P.O. Box 352250, Seattle, Washington 98195 S. E. Kruger TechX Corporation, 5621 Arapahoe Avenue, Suite A, Boulder, Colorado 80303 A. Y. Pankin Center for Energy and Space Science, Science Applications International Corporation, 10260 Campus Point Drive, San Diego, California 92121 C. R. Sovinec Department of Engineering Physics, University of Wisconsin, 1500 Engineering Drive, Madison, Wisconsin 53706 ͑Received 20 October 2005; accepted 6 January 2006; published online 11 May 2006͒ Strongly magnetized plasmas are rich in spatial and temporal scales, making a computational approach useful for studying these systems. The most accurate model of a magnetized plasma is based on a kinetic equation that describes the evolution of the distribution function for each species in six-dimensional phase space. High dimensionality renders this approach impractical for computations for long time scales. Fluid models are an approximation to the kinetic model.
    [Show full text]
  • Classical Chaos Described by a Density Matrix
    Article Classical Chaos Described by a Density Matrix Andres Mauricio Kowalski , Angelo Plastino * and Gaspar Gonzalez IFLP, Universidad Nacional de La Plata, La Plata 1900, Argentina; kowalski@fisica.unlp.edu.ar (A.M.K.); [email protected] (G.G.) * Correspondence: plastino@fisica.unlp.edu.ar Abstract: In this paper, a reference to the semiclassical model, in which quantum degrees of freedom interact with classical ones, is considered. The classical limit of a maximum-entropy density matrix that describes the temporal evolution of such a system is analyzed. Here, it is analytically shown that, in the classical limit, it is possible to reproduce classical results. An example is classical chaos. This is done by means a pure-state density matrix, a rather unexpected result. It is shown that this is possible only if the quantum part of the system is in a special class of states. Keywords: classical limit; semiclassical system; semiclassical chaos; clasiccal chaos; maximum entropy density matrix 1. Introduction The quantum–classical transition is a frontier issue, a rather transcendental physics topic [1–5]. The use of semi-classical systems to describe problems in physics has a long history; see, e.g., [6–12]. A particularly important case to be highlighted is the one, in which the quantum features of one of the two components of a composite system are negligible in comparison with those of the other. Regarding the first component as a classical one simplifies the description and provides deep insight into the combined system Citation: Kowalski, A.M.; Plastino, dynamics [13]. This methodology is used for the interaction of matter with a field.
    [Show full text]
  • Quantum Monte Carlo for Vibrating Molecules
    LBNL-39574 UC-401 ERNEST DRLANDD LAWRENCE BERKELEY NATIDNAL LABDRATDRY 'ERKELEY LAB I Quantum Monte Carlo for Vibrating Molecules W.R. Brown DEC 1 6 Chemical Sciences Division August 1996 Ph.D. Thesis OF THIS DocuMsvr 8 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by its trade name, trademark, manufacturer, or otherwise, does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or The Regents of the University of California. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof, or The Regents of the University of California. Ernest Orlando Lawrence Berkeley National Laboratory is an equal opportunity employer. LBjL-39574 ^UC-401 Quantum Monte Carlo for Vibrating Molecules Willard Roger Brown Ph.D. Thesis Chemistry Department University of California, Berkeley and Chemical Sciences Division Ernest Orlando Lawrence Berkeley National Laboratory University of California Berkeley, CA 94720 August 1996 This work was supported by the Director, Office of Energy Research, Office of Basic Energy Sciences, Chemical Sciences Division, of the U.S.
    [Show full text]
  • Particle-In-Cell Simulations of Highly Collisional Plasmas on the GPU in 1 and 2 Dimensions
    Particle-In-Cell Simulations Of Highly Collisional Plasmas On The GPU In 1 And 2 Dimensions A thesis for the degree of PHILOSOPHIAE DOCTOR Presented to DUBLIN CITY UNIVERSITY By Nina Hanzlikova B.Sc. School of Physical Sciences Dublin City University Research Supervisor: Prof. Miles M. Turner March 2015 Declaration I hereby certify that this material, which I now submit for assessment on the programme of study leading to the award of Philosophiae Doctor is entirely my own work, and that I have exercised reasonable care to ensure that the work is original, and does not to the best of my knowledge breach any law of copyright, and has not been taken from the work of others save and to the extent that such work has been cited and acknowledged within the text of my work. Signed: ........................................................ Nina Hanzlikova ID No.: 56459501 Date: 27th December 2014 Contents List of Figures xii List of Symbols xiii 1 Introduction 1 1.1 Overview . 2 1.2 Plasma Fundamentals . 4 1.2.1 Debye Length . 4 1.2.2 Plasma Frequency . 5 1.2.3 Collisions . 7 1.2.4 Diffusion . 9 1.2.5 Plasma Sheath . 11 1.2.6 Driving Potential and Heating . 14 1.3 Atmospheric Pressure Plasmas . 15 1.3.1 Atmospheric Plasma Sources . 15 1.3.2 Atmospheric Plasma Characteristics . 16 ii CONTENTS 1.4 Plasma Modelling . 21 1.4.1 Particle Modelling . 22 1.4.2 Atmospheric Plasma Modelling . 23 1.5 Chapter Summary . 25 2 Introduction To High Performance Computing 27 2.1 Graphical Processing Unit (GPU) .
    [Show full text]
  • Fact and Folklore in Quantum Gravity∗
    Draft. Do not quote or distribute. Final version forthcoming in Philosophy of Science To Quantize or Not to Quantize: Fact and Folklore in Quantum Gravity∗ Christian W¨uthrich University of Pittsburgh 30 September 2004 Abstract Does the need to find a quantum theory of gravity imply that the gravitational field must be quantized? Physicists working in quantum gravity routinely assume an affirmative answer, often without being aware of the metaphysical commitments that tend to underlie this assumption. The ambition of this article is to probe these commitments and to analyze some recently adduced arguments pertinent to the issue of quantization. While there exist good reasons to quantize gravity, as this analysis will show, alternative approaches to gravity challenge the received wisdom. These renegade approaches do not regard gravity as a fundamental force, but rather as effective, i.e. as merely supervening on fundamental physics. I will urge that these alternative accounts at least prove the tenability of an opposition to quantization. 1 Introduction All major approaches to quantum gravity endorse, implicitly or explicitly, the view that gravity must be “quantized” in order to be amenable to a description at the fundamental level. To be sure, different approaches pro- pose to execute this task in radically different manners. But they agree ∗I wish to thank John Earman, Florian Girelli, John Moffat, Carlo Rovelli and Danny Terno for discussions. This work is supported by the Swiss National Science Foundation (grant PBSK1–102693). 1 in that without a quantization of gravity no consistent quantum theory of gravity will be forthcoming. What such a quantization involves will vary with the approach taken.
    [Show full text]
  • TUOMO NIEMINEN a STUDY of RHODOPSIN AS a POTENTIAL PHOSPHOLIPID SCRAMBLASE Master of Science Thesis
    TUOMO NIEMINEN A STUDY OF RHODOPSIN AS A POTENTIAL PHOSPHOLIPID SCRAMBLASE Master of Science Thesis Examiner: Ilpo Vattulainen Examiner and topic approved in the Faculty of Science and Environmental Engineering council meeting on 5 September 2012 II TIIVISTELMA¨ TAMPEREEN TEKNILLINEN YLIOPISTO Teknis-luonnontieteellinen koulutusohjelma NIEMINEN, TUOMO: Tutkimus rodopsiinista potentiaalisena scramblaasipro- teiinina Diplomity¨o, 73 sivua Joulukuu 2012 P¨a¨aaine: Teknillinen fysiikka Tarkastaja: Professori Ilpo Vattulainen Ohjaaja: DI Matti Javanainen Avainsanat: Apoptoosi, biologinen fysiikka, flip{flop, flippaasi, molekyylidynamiikkasi- mulaatiot, rodopsiini, scramblaasi, umbrella sampling Solukalvon lipidien siirtyminen kalvon yhdelt¨a puolelta toiselle (flip{flop) on solu- el¨am¨an kannalta elint¨arke¨a prosessi. T¨am¨an hitaan prosessin kulkua nopeuttavat tietyt integraaliset kalvoproteiinit, joita kutsutaan flippaaseiksi ja scramblaaseiksi. N¨am¨a kalvoproteiinit n¨aht¨av¨asti alentavat solukalvon keskell¨a olevaa vapaaenergia- kynnyst¨a sellaiselle tasolle, ett¨a fosfolipidien flip{flop-ilmi¨o tapahtuu huomattavasti nopeammin joko ulkoisten energial¨ahteiden kuten ATP:n avulla, tai vaihtoehtoisesti pelk¨ast¨a¨an kalvon l¨amp¨ov¨ar¨ahtelyn vaikutuksesta. Flippaasien olemassaolosta on tiedetty jo pitk¨a¨an, mutta niiden nopeuttaman flip–flop-ilmi¨on tapahtumaketjusta ei ole viel¨a selkeytt¨a eik¨a kyseisi¨a proteiineja ole viel¨a kyetty yksil¨oim¨a¨an. Scramblaa- sien olemassaolosta on k¨ayty kiihke¨at¨a keskustelua, sill¨a ainoastaan niihin liittyvi¨a geenisekvenssej¨a on pystytty tunnistamaan. Scramblaasiproteiinien toimintamekanismien laajempi ymm¨art¨aminen voisi olla hy¨odyllist¨a monien solutasolla alkavien sairauksien ymm¨art¨amisess¨a. Esimerkiksi ohjattu solukuolema ilmeisesti l¨ahtee k¨ayntiin tietyn scramblaasiproteiinin aktivoi- tuessa, jolloin fosfatidyyliseriini-lipidit siirtyv¨at nopeasti solun pinnalle.
    [Show full text]