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Lecture 5 6.Pdf
Lecture 6. Quantum operators and quantum states Physical meaning of operators, states, uncertainty relations, mean values. States: Fock, coherent, mixed states. Examples of such states. In quantum mechanics, physical observables (coordinate, momentum, angular momentum, energy,…) are described using operators, their eigenvalues and eigenstates. A physical system can be in one of possible quantum states. A state can be pure or mixed. We will start from the operators, but before we will introduce the so-called Dirac’s notation. 1. Dirac’s notation. A pure state is described by a state vector: . This is so-called Dirac’s notation (a ‘ket’ vector; there is also a ‘bra’ vector, the Hermitian conjugated one, ( ) ( * )T .) Originally, in quantum mechanics they spoke of wavefunctions, or probability amplitudes to have a certain observable x , (x) . But any function (x) can be viewed as a vector (Fig.1): (x) {(x1 );(x2 );....(xn )} This was a very smart idea by Paul Dirac, to represent x wavefunctions by vectors and to use operator algebra. Then, an operator acts on a state vector and a new vector emerges: Aˆ . Fig.1 An operator can be represented as a matrix if some basis of vectors is used. Two vectors can be multiplied in two different ways; inner product (scalar product) gives a number, K, 1 (state vectors are normalized), but outer product gives a matrix, or an operator: Oˆ, ˆ (a projector): ˆ K , ˆ 2 ˆ . The mean value of an operator is in quantum optics calculated by ‘sandwiching’ this operator between a state (ket) and its conjugate: A Aˆ . -
Arxiv:1809.04476V2 [Physics.Chem-Ph] 18 Oct 2018 (Sub)States
Quantum System Partitioning at the Single-Particle Level Quantum System Partitioning at the Single-Particle Level Adrian H. M¨uhlbach and Markus Reihera) ETH Z¨urich, Laboratorium f¨ur Physikalische Chemie, Vladimir-Prelog-Weg 2, CH-8093 Z¨urich,Switzerland (Dated: 17 October 2018) We discuss the partitioning of a quantum system by subsystem separation through unitary block- diagonalization (SSUB) applied to a Fock operator. For a one-particle Hilbert space, this separation can be formulated in a very general way. Therefore, it can be applied to very different partitionings ranging from those driven by features in the molecular structure (such as a solute surrounded by solvent molecules or an active site in an enzyme) to those that aim at an orbital separation (such as core-valence separation). Our framework embraces recent developments of Manby and Miller as well as older ones of Huzinaga and Cantu. Projector-based embedding is simplified and accelerated by SSUB. Moreover, it directly relates to decoupling approaches for relativistic four-component many-electron theory. For a Fock operator based on the Dirac one-electron Hamiltonian, one would like to separate the so-called positronic (negative-energy) states from the electronic bound and continuum states. The exact two-component (X2C) approach developed for this purpose becomes a special case of the general SSUB framework and may therefore be viewed as a system- environment decoupling approach. Moreover, for SSUB there exists no restriction with respect to the number of subsystems that are generated | in the limit, decoupling of all single-particle states is recovered, which represents exact diagonalization of the problem. -
A New Scalable Parallel Algorithm for Fock Matrix Construction
A New Scalable Parallel Algorithm for Fock Matrix Construction Xing Liu Aftab Patel Edmond Chow School of Computational Science and Engineering College of Computing, Georgia Institute of Technology Atlanta, Georgia, 30332, USA [email protected], [email protected], [email protected] Abstract—Hartree-Fock (HF) or self-consistent field (SCF) ber of independent tasks and using a centralized dynamic calculations are widely used in quantum chemistry, and are scheduler for scheduling them on the available processes. the starting point for accurate electronic correlation methods. Communication costs are reduced by defining tasks that Existing algorithms and software, however, may fail to scale for large numbers of cores of a distributed machine, particularly in increase data reuse, which reduces communication volume, the simulation of moderately-sized molecules. In existing codes, and consequently communication cost. This approach suffers HF calculations are divided into tasks. Fine-grained tasks are from a few problems. First, because scheduling is completely better for load balance, but coarse-grained tasks require less dynamic, the mapping of tasks to processes is not known communication. In this paper, we present a new parallelization in advance, and data reuse suffers. Second, the centralized of HF calculations that addresses this trade-off: we use fine- grained tasks to balance the computation among large numbers dynamic scheduler itself could become a bottleneck when of cores, but we also use a scheme to assign tasks to processes to scaling up to a large system [14]. Third, coarse tasks reduce communication. We specifically focus on the distributed which reduce communication volume may lead to poor load construction of the Fock matrix arising in the HF algorithm, balance when the ratio of tasks to processes is close to one. -
Domain Decomposition and Electronic Structure Computations: a Promising Approach
Domain Decomposition and Electronic Structure Computations: A Promising Approach G. Bencteux1,4, M. Barrault1, E. Canc`es2,4, W. W. Hager3, and C. Le Bris2,4 1 EDF R&D, 1 avenue du G´en´eral de Gaulle, 92141 Clamart Cedex, France {guy.bencteux,maxime.barrault}@edf.fr 2 CERMICS, Ecole´ Nationale des Ponts et Chauss´ees, 6 & 8, avenue Blaise Pascal, Cit´eDescartes, 77455 Marne-La-Vall´ee Cedex 2, France, {cances,lebris}@cermics.enpc.fr 3 Department of Mathematics, University of Florida, Gainesville, FL 32611-8105, USA, [email protected] 4 INRIA Rocquencourt, MICMAC project, Domaine de Voluceau, B.P. 105, 78153 Le Chesnay Cedex, FRANCE Summary. We describe a domain decomposition approach applied to the spe- cific context of electronic structure calculations. The approach has been introduced in [BCH06]. We survey here the computational context, and explain the peculiari- ties of the approach as compared to problems of seemingly the same type in other engineering sciences. Improvements of the original approach presented in [BCH06], including algorithmic refinements and effective parallel implementation, are included here. Test cases supporting the interest of the method are also reported. It is our pleasure and an honor to dedicate this contribution to Olivier Pironneau, on the occasion of his sixtieth birthday. With admiration, respect and friendship. 1 Introduction and Motivation 1.1 General Context Numerical simulation is nowadays an ubiquituous tool in materials science, chemistry and biology. Design of new materials, irradiation induced damage, drug design, protein folding are instances of applications of numerical sim- ulation. For convenience we now briefly present the context of the specific computational problem under consideration in the present article. -
Cavity State Manipulation Using Photon-Number Selective Phase Gates
week ending PRL 115, 137002 (2015) PHYSICAL REVIEW LETTERS 25 SEPTEMBER 2015 Cavity State Manipulation Using Photon-Number Selective Phase Gates Reinier W. Heeres, Brian Vlastakis, Eric Holland, Stefan Krastanov, Victor V. Albert, Luigi Frunzio, Liang Jiang, and Robert J. Schoelkopf Departments of Physics and Applied Physics, Yale University, New Haven, Connecticut 06520, USA (Received 27 February 2015; published 22 September 2015) The large available Hilbert space and high coherence of cavity resonators make these systems an interesting resource for storing encoded quantum bits. To perform a quantum gate on this encoded information, however, complex nonlinear operations must be applied to the many levels of the oscillator simultaneously. In this work, we introduce the selective number-dependent arbitrary phase (SNAP) gate, which imparts a different phase to each Fock-state component using an off-resonantly coupled qubit. We show that the SNAP gate allows control over the quantum phases by correcting the unwanted phase evolution due to the Kerr effect. Furthermore, by combining the SNAP gate with oscillator displacements, we create a one-photon Fock state with high fidelity. Using just these two controls, one can construct arbitrary unitary operations, offering a scalable route to performing logical manipulations on oscillator- encoded qubits. DOI: 10.1103/PhysRevLett.115.137002 PACS numbers: 85.25.Hv, 03.67.Ac, 85.25.Cp Traditional quantum information processing schemes It has been shown that universal control is possible using rely on coupling a large number of two-level systems a single nonlinear term in addition to linear controls [11], (qubits) to solve quantum problems [1]. -
4 Representations of the Electromagnetic Field
4 Representations of the Electromagnetic Field 4.1 Basics A quantum mechanical state is completely described by its density matrix ½. The density matrix ½ can be expanded in di®erent basises fjÃig: X ¯ ¯ ½ = Dij jÃii Ãj for a discrete set of basis states (158) i;j ¯ ® ¯ The c-number matrix Dij = hÃij ½ Ãj is a representation of the density operator. One example is the number state or Fock state representation of the density ma- trix. X ½nm = Pnm jni hmj (159) n;m The diagonal elements in the Fock representation give the probability to ¯nd exactly n photons in the ¯eld! A trivial example is the density matrix of a Fock State jki: ½ = jki hkj and ½nm = ±nk±km (160) Another example is the density matrix of a thermal state of a free single mode ¯eld: + exp[¡~!a a=kbT ] ½ = + (161) T rfexp[¡~!a a=kbT ]g In the Fock representation the matrix is: X ½ = exp[¡~!n=kbT ][1 ¡ exp(¡~!=kbT )] jni hnj (162) n X hnin = jni hnj (163) (1 + hni)n+1 n with + ¡1 hni = T r(a a½) = [exp(~!=kbT ) ¡ 1] (164) 37 This leads to the well-known Bose-Einstein distribution: hnin ½ = hnj ½ jni = P = (165) nn n (1 + hni)n+1 4.2 Glauber-Sudarshan or P-representation The P-representation is an expansion in a coherent state basis jf®gi: Z ½ = P (®; ®¤) j®i h®j d2® (166) A trivial example is again the P-representation of a coherent state j®i, which is simply the delta function ±(® ¡ a0). The P-representation of a thermal state is a Gaussian: 1 2 P (®) = e¡j®j =n (167) ¼n Again it follows: Z ¤ 2 2 Pn = hnj ½ jni = P (®; ® ) jhnj®ij d ® (168) Z 2n 1 2 j®j 2 = e¡j®j =n e¡j®j d2® (169) ¼n n! The last integral can be evaluated and gives again the thermal distribution: hnin P = (170) n (1 + hni)n+1 4.3 Optical Equivalence Theorem Why is the P-representation useful? ² j®i corresponds to a classical state. -
Matrix Algebra for Quantum Chemistry
Matrix Algebra for Quantum Chemistry EMANUEL H. RUBENSSON Doctoral Thesis in Theoretical Chemistry Stockholm, Sweden 2008 Matrix Algebra for Quantum Chemistry Doctoral Thesis c Emanuel Härold Rubensson, 2008 TRITA-BIO-Report 2008:23 ISBN 978-91-7415-160-2 ISSN 1654-2312 Printed by Universitetsservice US AB, Stockholm, Sweden 2008 Typeset in LATEX by the author. Abstract This thesis concerns methods of reduced complexity for electronic structure calculations. When quantum chemistry methods are applied to large systems, it is important to optimally use computer resources and only store data and perform operations that contribute to the overall accuracy. At the same time, precarious approximations could jeopardize the reliability of the whole calcu- lation. In this thesis, the selfconsistent eld method is seen as a sequence of rotations of the occupied subspace. Errors coming from computational ap- proximations are characterized as erroneous rotations of this subspace. This viewpoint is optimal in the sense that the occupied subspace uniquely denes the electron density. Errors should be measured by their impact on the over- all accuracy instead of by their constituent parts. With this point of view, a mathematical framework for control of errors in HartreeFock/KohnSham calculations is proposed. A unifying framework is of particular importance when computational approximations are introduced to eciently handle large systems. An important operation in HartreeFock/KohnSham calculations is the calculation of the density matrix for a given Fock/KohnSham matrix. In this thesis, density matrix purication is used to compute the density matrix with time and memory usage increasing only linearly with system size. The forward error of purication is analyzed and schemes to control the forward error are proposed. -
Problem Set #1 Solutions
PROBLEM SET #2 SOLUTIONS by Robert A. DiStasio Jr. Q1. 1-particle density matrices and idempotency. (a) A matrix M is said to be idempotent if M 2 = M . Show from the basic definition that the HF density matrix is idempotent when expressed in an orthonormal basis. An element of the HF density matrix is given as (neglecting the factor of two for the restricted closed-shell HF density matrix): * PCCμν = ∑ μi ν i . (1) i In matrix form, (1) is simply equivalent to † PCC= occ occ (2) where Cocc is the occupied block of the MO coefficient matrix. To reformulate the nonorthogonal Roothaan-Hall equations FC= SCε (3) into the preferred eigenvalue problem ~~ ~ FC= Cε (4) the AO basis must be orthogonalized. There are several ways to orthogonalize the AO basis, but I will only discuss symmetric orthogonalization, as this is arguably the most often used procedure in computational quantum chemistry. In the symmetric orthogonalization procedure, the MO coefficient matrix in (3) is recast as ~ + 1 − 1 ~ CSCCSC=2 ⇔ = 2 (5) which can be substituted into (3) yielding the eigenvalue form of the Roothaan-Hall equations in (4) after the following algebraic manipulation: FC = SCε − 1 ~ − 1 ~ FSCSSC( 2 )(= 2 )ε − 1 − 1 ~ −1 − 1 ~ SFSCSSSC2 ( 2 )(= 2 2 )ε . (6) −1 − 1 ~ −1 − 1 ~ ()S2 FS2 C= () S2 SS2 Cε ~~ ~ FC = Cε ~ ~ −1 − 1 −1 − 1 In (6), the dressed Fock matrix, F , was clearly defined as F≡ S2 FS 2 and S2 SS2 = S 0 =1 was used. In an orthonormal basis, therefore, the density matrix of (2) takes on the following form: ~ ~† PCC= occ occ . -
Generation and Detection of Fock-States of the Radiation Field
Generation and Detection of Fock-States of the Radiation Field Herbert Walther Max-Planck-Institut für Quantenoptik and Sektion Physik der Universität München, 85748 Garching, Germany Reprint requests to Prof. H. W.; Fax: +49/89-32905-710; E-mail: [email protected] Z. Naturforsch. 56 a, 117-123 (2001); received January 12, 2001 Presented at the 3rd Workshop on Mysteries, Puzzles and Paradoxes in Quantum Mechanics, Gargnano, Italy, September 1 7 -2 3 , 2000. In this paper we give a survey of our experiments performed with the micromaser on the generation of Fock states. Three methods can be used for this purpose: the trapping states leading to Fock states in a continuous wave operation, state reduction of a pulsed pumping beam, and finally using a pulsed pumping beam to produce Fock states on demand where trapping states stabilize the photon number. Key words: Quantum Optics; Cavity Quantum Electrodynamics; Nonclassical States; Fock States; One-Atom-Maser. I. Introduction highly excited Rydberg atoms interact with a single mode of a superconducting cavity which can have a The quantum treatment of the radiation field uses quality factor as high as 4 x 1010, leading to a photon the number of photons in a particular mode to char lifetime in the cavity of 0.3 s. The steady-state field acterize the quantum states. In the ideal case the generated in the cavity has already been the object modes are defined by the boundary conditions of a of detailed studies of the sub-Poissonian statistical cavity giving a discrete set of eigen-frequencies. -
Relativistic Cholesky-Decomposed Density Matrix
Relativistic Cholesky-decomposed density matrix MP2 Benjamin Helmich-Paris,1, 2, a) Michal Repisky,3 and Lucas Visscher2 1)Max-Planck-Institut f¨urKohlenforschung, Kaiser-Wilhelm-Platz 1, D-45470 M¨ulheiman der Ruhr 2)Section of Theoretical Chemistry, Vrije Universiteit Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands 3)Hylleraas Centre for Quantum Molecular Sciences, Department of Chemistry, UiT The Arctic University of Norway, N-9037 Tromø Norway (Dated: 15 October 2018) In the present article, we introduce the relativistic Cholesky-decomposed density (CDD) matrix second-order Møller–Plesset perturbation theory (MP2) energies. The working equations are formulated in terms of the usual intermediates of MP2 when employing the resolution-of-the-identity approximation (RI) for two-electron inte- grals. Those intermediates are obtained by substituting the occupied and vir- tual quaternion pseudo-density matrices of our previously proposed two-component atomic orbital-based MP2 (J. Chem. Phys. 145, 014107 (2016)) by the corresponding pivoted quaternion Cholesky factors. While working within the Kramers-restricted formalism, we obtain a formal spin-orbit overhead of 16 and 28 for the Coulomb and exchange contribution to the 2C MP2 correlation energy, respectively, compared to a non-relativistic (NR) spin-free CDD-MP2 implementation. This compact quaternion formulation could also be easily explored in any other algorithm to compute the 2C MP2 energy. The quaternion Cholesky factors become sparse for large molecules and, with a block-wise screening, block sparse-matrix multiplication algorithm, we observed an effective quadratic scaling of the total wall time for heavy-element con- taining linear molecules with increasing system size. -
Density Functional Theory
Density Functional Theory Fundamentals Video V.i Density Functional Theory: New Developments Donald G. Truhlar Department of Chemistry, University of Minnesota Support: AFOSR, NSF, EMSL Why is electronic structure theory important? Most of the information we want to know about chemistry is in the electron density and electronic energy. dipole moment, Born-Oppenheimer charge distribution, approximation 1927 ... potential energy surface molecular geometry barrier heights bond energies spectra How do we calculate the electronic structure? Example: electronic structure of benzene (42 electrons) Erwin Schrödinger 1925 — wave function theory All the information is contained in the wave function, an antisymmetric function of 126 coordinates and 42 electronic spin components. Theoretical Musings! ● Ψ is complicated. ● Difficult to interpret. ● Can we simplify things? 1/2 ● Ψ has strange units: (prob. density) , ● Can we not use a physical observable? ● What particular physical observable is useful? ● Physical observable that allows us to construct the Hamiltonian a priori. How do we calculate the electronic structure? Example: electronic structure of benzene (42 electrons) Erwin Schrödinger 1925 — wave function theory All the information is contained in the wave function, an antisymmetric function of 126 coordinates and 42 electronic spin components. Pierre Hohenberg and Walter Kohn 1964 — density functional theory All the information is contained in the density, a simple function of 3 coordinates. Electronic structure (continued) Erwin Schrödinger -
Chapter 18 the Single Slater Determinant Wavefunction (Properly Spin and Symmetry Adapted) Is the Starting Point of the Most Common Mean Field Potential
Chapter 18 The single Slater determinant wavefunction (properly spin and symmetry adapted) is the starting point of the most common mean field potential. It is also the origin of the molecular orbital concept. I. Optimization of the Energy for a Multiconfiguration Wavefunction A. The Energy Expression The most straightforward way to introduce the concept of optimal molecular orbitals is to consider a trial wavefunction of the form which was introduced earlier in Chapter 9.II. The expectation value of the Hamiltonian for a wavefunction of the multiconfigurational form Y = S I CIF I , where F I is a space- and spin-adapted CSF which consists of determinental wavefunctions |f I1f I2f I3...fIN| , can be written as: E =S I,J = 1, M CICJ < F I | H | F J > . The spin- and space-symmetry of the F I determine the symmetry of the state Y whose energy is to be optimized. In this form, it is clear that E is a quadratic function of the CI amplitudes CJ ; it is a quartic functional of the spin-orbitals because the Slater-Condon rules express each < F I | H | F J > CI matrix element in terms of one- and two-electron integrals < f i | f | f j > and < f if j | g | f kf l > over these spin-orbitals. B. Application of the Variational Method The variational method can be used to optimize the above expectation value expression for the electronic energy (i.e., to make the functional stationary) as a function of the CI coefficients CJ and the LCAO-MO coefficients {Cn,i} that characterize the spin- orbitals.