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Theoretical Physics Reference guide based on:
How to become a GOOD Theoretical Physicist by Gerard 't Hooft

Table of Contents

1. Languages

  1. The acquisition-learning hypothesis is a hypothesis that forms part of Stephen Krashen's

    theory of second language acquisition. It states that there are two independent ways in which we develop our linguistic skills: acquisition and learning. According to Krashen acquisition is more important than learning. `https://en.wikipedia.org/wiki/Input_hypothesis`

    1. Learn through audiobook:
    2. Learn reading:
  2. Learning:

1.1. English.

English is a prerequisite. All sciences nowadays are in English.

  1. Learning:

1.2. Some French, German, Spanish and Italian may be useful.

  1. Learning:

2. Primary mathematics

2.1. Natural numbers.

2.2. Integers.

2.3. Rational numbers.

2.4. Real numbers.

2.5. Complex numbers.

2.6. Set theory: open sets, compacts spaces. Topology.

2.7. Algebraic equations. Approximations techniques. Series expansions: Taylor series.

2.8. Solving equations with complex numbers. Trigonometry.

2.9. Infinitesimals. Differentiation. Differentiate basic functions.

2.10. Integration. Integrate basic functions. Differential equations. Linear equations.

2.11. Fourier transformation. The use of complex numbers. Convergence of series.

2.12. The complex plane. Cauchy theorems and contour integration.

2.13. The gamma function.

2.14. Gaussian integrals. Probability theory.

2.15. Partial differential equations. Dirichlet and Neumann boundary conditions.

3. Classical Mechanics

3.1. Static mechanics (force, tension). Hydrostatics. Newton's Laws.

3.2. The elliptical orbits of planets. The many body system.

3.3. The action principle. Hamilton’s equations. The Lagrangean.

3.4. The harmonic oscillator. The pendulum.

3.5. Poisson’s brackets.

A function \(f(p, q, t)\) of the phase space coordinates of the system and time as total time derivative

\[ \frac{d f}{d t}=\frac{\partial f}{\partial t}+\sum_{i}\left(\frac{\partial f}{\partial q_{i}} \dot{q}_{i}+\frac{\partial f}{\partial p_{i}} \dot{p}_{i}\right), \]

often written as

\[ \frac{d f}{d t}=\frac{\partial f}{\partial t} + \{H, f\}, \]

where \(\{H, f\}\) is the Poisson bracket. In canonical coordinates \((q_i, p_i)\) given (any) two functions \(f(p_i, q_i, t)\) and \(g(p_i, q_i, t)\) the Poisson bracket takes the form,

\[ \{f, g\}=\sum_{i=1}^{N}\left(\frac{\partial f}{\partial q_{i}} \frac{\partial g}{\partial p_{i}}-\frac{\partial f}{\partial p_{i}} \frac{\partial g}{\partial q_{i}}\right). \]

The canonical coordinates satisfy the fundamental Poisson bracket relations

  • \(\left\{q^{i}, q^{j}\right\}=0\)
  • \(\left\{p_{i}, p_{j}\right\}=0\)
  • \(\left\{q_{i}, p_{j}\right\}=\delta_{i j}\)

The Poisson bracket has the following properties:

  1. \(\{f, g\} = -\{g, f\}\),
  2. \(\{f, c\} = 0\),
  3. \(\{f, q_i\} = -\frac{\partial f}{\partial p_i}\),
  4. \(\{f, p_i\} = \frac{\partial f}{\partial q_i}\),
  5. \(\{f_1+f_2, g\} = \{f_1, g\} + \{f_2, g\}\),
  6. \(\{f_1f_2, g\} = f_1\{f_2, g\} + \{f_1, g\}f_2\),
  7. \(\frac{\partial}{\partial t}\{f, g\} = \left\{\frac{\partial f}{\partial t}, g\right\} + \left\{f, \frac{\partial g}{\partial t}\right\}\),

In case two, \(c\) is a constant of the motion, also called an integral of the motion.

An important identity satisfied by the Poisson brackets is the Jacob identity

\[ \{f,\{g, h\}\} + \{g,\{h, f\}\} + \{h,\{f, g\}\} = 0. \]

  1. Hamilton's equations are

    \[ \dot{q}=\frac{\partial H}{\partial p}\\ \dot{p}=-\frac{\partial H}{\partial q} \]

    with the Poisson bracket we have

    \[ \dot{q} =\{q, H(q, p)\} \\ \dot{p} =\{p, H(q, p)\} \]

3.6. Wave equations. Liquids and gases. The Navier-Stokes equations. Viscosity and friction.

4. Optics

4.1. Fraction and reflection.

4.2. Lenses and mirrors.

4.3. The telescope and the microscope.

4.4. Introduction to wave propagation.

4.5. Doppler effect.

4.6. Huijgens’ principle of wave superposition.

4.7. Wave fronts.

4.8. Caustics

5. Statistical Mechanics & Thermodynamics

5.1. The first, second and third laws of thermodynamics.

5.2. The Boltzmann distribution.

5.3. The Carnot cycle. Entropy. Heat engines.

5.4. Phase transitions. Thermodynamical models.

5.5. The Ising Model (postpone techniques to solve the 2-dimensional Ising Model to later).

5.6. Planck’s radiation law (as a prelude to Quantum Mechanics).

5.7. Homogeneous and inhomogeneous systems

5.7.1. Pair correlation function or the radial correlation function

In computational mechanics and statistics mechanics, a radial distribution function (RDF), \(g(r)\) describes how the density of surrounding matter varies as a function of the distance from a distinguished point. \(g(r)\) is of fundamental importance in thermodynamics for macroscopic thermodynamics quantities can be calculated using \(g(r)\).

  1. The virial equation for the pressure:

    \[ p = \rho k T-\frac{2\pi}{3kT}\rho^2\int r^3 u'(r)g(r, \rho,T) dr \]

  2. The energy equation:

    \[ \frac{E}{NkT} = \frac{3}{2} + \frac{\rho}{2kT}\int 4\pi r^2 u(r)g(r, \rho, T) dr \]

  3. The compressibility equation:

    \[ kT\left(\frac{\partial \rho}{\partial p}\right) = 1 + \rho \int[g(r) - 1] dr \]

6. Electronics

6.1. Ohm’s law, capacitors, inductors, using complex numbers to calculate their effects.

6.2. Transistors, diodes.

7. Electromagnetism

7.1. Maxwell’s Theory for electromagnetism: Homogeneous and inhomogeneous .

7.2. Maxwell’s laws in a medium. Boundaries. Solving the equations in: Vacumm and homogeneous medium (electromagnetic waves). In a box (wave guides). At boundaries (fraction and reflection).

7.3. The vector potential and gauge invariance (extremely important).

7.4. Emission and absorption on EM waves (antenna).

7.5. Light scattering against objects

8. Computational Physic

8.1. Numerical Integration and Differentiation

8.1.1. Derivative by:

  1. Finite difference `https://en.wikipedia.org/wiki/Finite_difference_method`

    The derivative of a function \(f(x)\) can be approximated by the forward difference based on the size \(h\)

    \[ f^{\prime}(x)=\lim _{h \rightarrow 0} \frac{f(x+h)-f(x)}{h} \approx \frac{f(x+h)-f(x)}{h} - \frac{h}{2}f^{\prime\prime}(\xi). \]

    First order of a Taylor expansion of \(f(x)\) with truncation error \(O(h) = hf(\xi)^{\prime\prime}/2\) linearly related to \(h\). The approximation is poor unless \(h\) is sufficient small. A final expression of this example and its order

    \[ \frac{f(x+h)-f(x)}{h} = f^{\prime}(x) + O(h). \]

    The derivative can be also approximated by the backward difference, replacing \(h\) by \(-h\) in the Taylor expansion,

    \[ f^{\prime}(x) \approx \frac{f(x)-f(x-h)}{h}. \]

    Subtracting the backward difference from the forward difference and dividing everything by \(2h\), we find the central difference

    \[ f^{\prime}(x) = \frac{f(x+h)-f(x-h)}{2 h}-\left(\frac{f^{\prime \prime \prime}(x)}{3 !} h^{2}+\frac{f^{(5)}(x)}{5 !} h^{4}+\cdots\right) \approx \frac{f(x+h)-f(x-h)}{2 h}, \]

    with the second order truncation error \(O(h)\). Adding the forward difference to the backward difference and solving for \(f(x)^{\prime\prime}\) we can get the approximation for the second order derivative

    \[ \boxed{f(x)^{\prime\prime} \approx \frac{f(x-h)-2 f(x)+f(x+h)}{h^{2}}} \]

  2. Interpolation

    `https://en.wikipedia.org/wiki/Interpolation` `https://en.wikipedia.org/wiki/Linear_interpolation`

    The derivative of a given function \(f(t)\) can be approximated by that of its polynomial interpolation based on a set of \(n+1\) points \(y_i = f(x_i), (i=0,\cdots, n)\), such as the Lagrange polynomial interpolation (`https://en.wikipedia.org/wiki/Polynomial_interpolation`)

    \[ f(x) \approx L_{n}(x)=\sum_{i=0}^{n} y_{i} l_{i}(x). \]

    Taking the derivative of \(f(x)\),

    \[ f^{\prime}(x) \approx L_{n}^{\prime}(x)=\sum_{i=0}^{n} y_{i} l_{i}^{\prime}(x)=\sum_{i=0}^{n} y_{i} d_{i}(x), \] where

    \[ d_{i}(x)=\frac{d}{d x} l_{i}(x)=\frac{d}{d x}\left(\prod_{j=0, j \neq i}^{n} \frac{x-x_{j}}{x_{i}-x_{j}}\right). \]

    The error is

    \[ E_{n}(x) = R_{n}^{\prime}(x) =\frac{1}{(n+1) !} \frac{d}{d x}\left(\left(f^{(n+1)}(\xi(x)) l(x)\right)\right.\\ = \frac{1}{(n+1) !}\left[l^{\prime}(x) f^{(n+1)}(\xi(x))+l(x) \frac{d}{d x} f^{(n+1)}(\xi(x))\right]. \]

    The error is unknown in general since \(\xi\) is not known explicit. But we can have for each node \(x_i\) where \(w(x_i)\),

    \[ E_{n}(x)=R_{n}^{\prime}(x)=l^{\prime}(x) \frac{f^{(n+1)}(\xi(x))}{(n+1) !}. \]

    1. Special cases:
      • \(n=1\), linear interpolation based on \(n+1 = 2\) points:

      \[ \begin{array}{l} d_{0}=l_{0}^{\prime}(x)=\frac{d}{d x}\left(\frac{x-x_{1}}{x_{0}-x_{1}}\right)=\frac{1}{x_{0}-x_{1}}, \\ d_{1}=l_{1}^{\prime}(x)=\frac{d}{d x}\left(\frac{x-x_{0}}{x_{1}-x_{0}}\right)=\frac{1}{x_{1}-x_{0}}, \end{array} \]

      and

      \[ f^{\prime}(x) \approx L_{1}^{\prime}(x)=y_{0} d_{0}(x)+y_{1} d_{1}(x)=\frac{y_{1}-y_{0}}{x_{1}-x_{0}}, \quad f^{\prime \prime}(x)=0. \]

      • \(n=2\), quadratic interpolation based on \(n+1 = 3\) points:

      \[ \begin{aligned} d_{0}(x) = l_{0}^{\prime}(x)=\frac{d}{d x}\left(\frac{\left(x-x_{1}\right)\left(x-x_{2}\right)}{\left(x_{0}-x_{1}\right)\left(x_{0}-x_{2}\right)}\right)=\frac{2 x-x_{1}-x_{2}}{\left(x_{0}-x_{1}\right)\left(x_{0}-x_{2}\right)}, \\ d_{1}(x) = l_{1}^{\prime}(x)=\frac{d}{d x}\left(\frac{(x-x_{0})(x-x_{2})}{\left(x_1-x_{0}\right)\left(x_1-x_{2}\right)}\right)=\frac{2 x-x_{0}-x_{2}}{\left(x_{1}-x_{0}\right)\left(x_{1}-x_{2}\right)}, \\ d_{2}(x) = l_{2}^{\prime}(x)=\frac{d}{d x}\left(\frac{\left(x-x_{0}\right)\left(x-x_{1}\right)}{\left(x_{2}-x_{0}\right)\left(x_{2}-x_{1}\right)}\right)=\frac{2 x-x_{0}-x_{1}}{\left(x_{2}-x_{0}\right)\left(x_{2}-x_{1}\right)}, \end{aligned} \]

      and

      \[ \begin{aligned} f^{\prime}(x) \approx L_{2}^{\prime}(x) = \sum_{i=1}^{2} d_{i} y_{i} = \frac{2 x-x_{1}-x_{2}}{\left(x_{0}-x_{1}\right)\left(x_{0}-x_{2}\right)} y_{0}+\frac{2 x-x_{0}-x_{2}}{\left(x_{1}-x_{0}\right)\left(x_{1}-x_{2}\right)} y_{1}+\frac{2 x-x_{0}-x_{1}}{\left(x_{2}-x_{0}\right)\left(x_{2}-x_{1}\right)} y_{2}. \end{aligned} \]

      If the 3 points are equally spaced with \(x_1=x, x_0 = x - h, x_2 = x + h\) one can have

      \[ f^{\prime}(x) \approx \frac{x-(x+h)}{2 h^{2}} y_{0}+\frac{2 x-(x-h)-(x+h)}{-h^{2}} y_{1}+\frac{x-(x-h)}{2 h^{2}}=\frac{1}{2 h}\left(y_{2}-y_{0}\right). \]

      with error \(O(h^2)\).

      The 2nd order derivative:

      \[ \begin{aligned} f^{\prime \prime}(x) \approx L_{2}^{\prime \prime}(x)=\frac{d}{d x} L_{2}^{\prime}(x) = \frac{d}{d x}\left[\frac{2 x-x_{1}-x_{2}}{\left(x_{0}-x_{1}\right)\left(x_{0}-x_{2}\right)} y_{0}+\frac{2 x-x_{0}-x_{2}}{\left(x_{1}-x_{0}\right)\left(x_{1}-x_{2}\right)} y_{1}+\frac{2 x-x_{0}-x_{1}}{\left(x_{2}-x_{0}\right)\left(x_{2}-x_{1}\right)} y_{2}\right] = 2\left[\frac{y_{0}}{\left(x_{0}-x_{1}\right)\left(x_{0}-x_{2}\right)}+\frac{y_{1}}{\left(x_{1}-x_{0}\right)\left(x_{1}-x_{2}\right)}+\frac{y_{2}}{\left(x_{2}-x_{0}\right)\left(x_{2}-x_{1}\right)}\right] \end{aligned} \]

      If the 3 points are equally spaced we have

      \[ f^{\prime}(x) \approx \frac{2 x-x_{1}-x_{2}}{2 h^{2}} y_{0}-\frac{2 x-x_{0}-x_{2}}{h^{2}} y_{1}+\frac{2 x-x_{0}-x_{1}}{2 h^{2}} y_{2}, \]

      and

      \[ f^{\prime}\left(x_{0}\right) = \frac{1}{2 h}\left(-3 y_{0}+4 y_{1}-y_{2}\right), \\ f^{\prime}\left(x_{1}\right) = \frac{1}{2 h}\left(-y_{0}+y_{2}\right), \\ f^{\prime}\left(x_{2}\right) = \frac{1}{2 h}\left(y_{0}-4 y_{1}+3 y_{2}\right). \]

      The second derivative is

      \[ f^{\prime \prime}(x) \approx \frac{d}{d x}\left[\frac{2 x-x_{1}-x_{2}}{2 h^{2}} y_{0}-\frac{2 x-x_{0}-x_{2}}{h^{2}} y_{1}+\frac{2 x-x_{0}-x_{1}}{2 h^{2}} y_{2}\right] \] \[ \boxed{f^{\prime \prime}(x) = \frac{1}{h^{2}}\left(y_{0}-2 y_{1}+y_{2}\right)}. \]

8.1.2. Boundary conditions:

  1. Dirichlet Boundary Conditions:

    The values at the edges are fixed at some constant values that we impose. In Finite Element Method, the Dirichlet boundary condition is defined by weighted-integral form of a differential equation. J. N. Reddy, SECOND-ORDER DIFFERENTIAL EQUATIONS IN ONE DIMENSION: FINITE ELEMENT MODELS, An Introduction to the Finite Element Method, 3rd Edition, pp. 110

  2. Neumann Boundary Conditions:

    The derivative (or discrete difference) at the edges are fixed at some constant values that we choose.

8.2. Programming languages

8.2.1. Julia

  1. Packages
    1. Latexify - `https://github.com/korsbo/Latexify.jl`

      This is a package for generating LaTeX maths from julia objects.

    2. SugarBLAS - `https://github.com/lopezm94/SugarBLAS.jl`

      This package provides macros for BLAS functions representing polynomials

    3. Flux - `https://fluxml.ai/Flux.jl`

      Flux is an elegant approach to machine learning.

    4. DifferentialEquations - `https://diffeq.sciml.ai`

      This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R.

    5. Knet - `https://denizyuret.github.io/Knet.jl`

      Knet (pronounced "kay-net") is the Koç University deep learning framework implemented in Julia by Deniz Yuret and collaborators. It supports GPU operation and automatic differentiation using dynamic computational graphs for models defined in plain Julia.

    6. Symbolics - `https://symbolics.juliasymbolics.org/dev

      Symbolics.jl is a fast and modern Computer Algebra System (CAS) for a fast and modern programming language (Julia)

    7. Pluto - `https://github.com/fonsp/Pluto.jl`

      Simple reactive notebooks for Julia

    8. Gadfly - `https://gadflyjl.org/stable/`

      Gadfly is a system for plotting and visualization written in Julia. It is based largely on Hadley Wickhams's ggplot2 for R and Leland Wilkinson's book The Grammar of Graphics. It was Daniel C. Jones' brainchild and is now maintained by the community.

    9. RCall - `https://juliainterop.github.io/RCall.jl/stable/`

      RCall, allows the user to call R packages from within Julia.

8.2.2. R

  1. ggplot2

    ggplot2 is a system for declaratively creating graphics, based on The Grammar of Graphics. You provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it takes care of the details.

    `https://ggplot2.tidyverse.org/`

8.3. Solvers

8.3.1. Fortran solvers

  1. VODE: stiff/nonstiff ODE systems, with direct linear solvers
  2. VODPK: with Krylov linear solvers (GMRES)
  3. NKSOL: Newton-Krylov solver - nonlinear algebraic systems
  4. DASPK: DAE system solver (from DASSL)

8.3.2. C - organized in a single suite, SUNDIALS (Suite of Nonlinear and Differential/Algebraic Equation Solvers

  1. CVODE
  2. PVODE
  3. KINSOL
  4. IDA: rewrite of DASPK

8.3.3. Julia Solvers

  1. DASSL

    Solves stiff differential algebraic equations (DAE) using variable stepsize backwards finite difference formula (BDF).

    `https://github.com/SciML/DASSL.jl`

  2. DASKR

    DASKR (FORTRAN solver) is a derivative of the DASSL solver with root finding.

    `https://github.com/SciML/DASKR.jl`

8.4. Simulações hidrodinâmicas

Tem desempenhado um papel central em astrofísica e astronomia desde os anos 50 com as simulações de interações de nuvens. Essas simulações são muito populares com ciências climáticas, modelagem de previsão do tempo, contudo a astrofísica representa um desafio para a dinâmica computacional de fluidos, já que possui alguns problemas específicos não comuns na dinâmica de fluidos, como efeitos de curvatura na atmosfera de uma estrela de nêutrons por exemplo. Técnicas numéricas foram desenvolvidas na década de 80 usando métodos de elementos finitos e suas extensões como o MUSCL (Monotonic Upstream-centered Scheme for Conservation Laws (van Leer, 1979)) e métodos parabólicos.

O ponto central das simulações hidrodinâmicas é descrito por meio das equações de Navier-Stokes, que expressa a conservação da massa, momento-energia em fluído. No contexto de astrofísica, a compressibilidade e efeitos relativísticos. Essas equações são equações diferenciais parciais. As equações de Navier-Stokes podem ser combinadas com as equações de Maxwell para simulações de magneto-hidrodinâmica.

Essas equações não procuram estabelecer uma relação entre as variáveis, mas sim entre as taxas de variação ou fluxos destas quantidades. A equação da continuidade, conservação da massa pode ser escrita como:

\[ \frac{\partial\rho}{\partial t} = \nabla\cdot(\rho \vec{v}) = 0;\]

onde \(\rho\) é a densidade do fluido e \(v\) sua velocidade. A equação de conservação de momento pode ser escrita como:

\[ \frac{\partial}{\partial t} (\rho v_i) + \nabla \cdot (\rho v_i \vec{v}) = \rho f_i \]

aqui \(\rho f_i\) é a i-ésima componente da força autuando sobre o fluído. Esta equação dá conta de mudanças no momento devido a forças externas que podem ser estendidas para levar em conta campos magnéticos (pela força de Lorentz), gravidade, gradientes de pressão. Esta equação também pode ser escrita como:

\[ \frac{\partial }{\partial t} (\rho \vec{v}) + \nabla \cdot (\rho\vec{v}\otimes v) = -\nabla p + \nabla\cdot \zeta + \rho f \]

com \(\zeta\) sendo viscosidade/tensor de stress

Há ainda a equação para troca de energia, em cenários astrofísicos isso pode ser bem complexo, requerendo termos adicionais ao considerar a primeira lei da termodinâmica \(Q = w + \delta U\); termos de convecção, difusão, dissipação, pressões realizado trabalho devem ser consideradas. Podemos escrever a equação para energia como:

\[ \frac{\partial E}{\partial t} + \nabla ((E + D) V) = \rho vg + Q + \nabla (k\nabla T)\]

onde \(E\) é a densidade de energia \(k\) a condutividade térmica, \(T\) temperatura, \(Q\) calor "viscoso".

Contudo estas equações estão de formas gerais, dependendo do sistema a ser modelado, equações adicionais são necessárias, como equações para processo radiativos, reações químicas, sistemas auto-gravitantes, etc.

As formulações das equações de hidrodinâmica podem ser Lagrangeanas (como as anteriores) se acompanham o movimento das partículas e se vê mudanças de grandezas nelas. Já o sistema euleriano, verifica-se um ponto no espaço e verifica mudanças neste ponto.

Métodos numéricos levam em conta essas formulações e podem fazer uso das duas por meio do teorema de Reynolds.

Para resolver as equações hidrodinâmicas diferentes métodos são empregados, os mais comuns são métodos de diferenças finitas, as derivadas são diferenças em um grid; métodos de volumes finitos, que considera a integração das equações em uma célula, as conservações são satisfeitas integrando fluxos. Método SPH (Smoothed-particle hydrodynamics) que é uma técnica para aproximar o continuum de fluídos por meio de partículas, cada partícula tem informação de massa, posição, velocidade e outras propriedades, as propriedades em qualquer ponto no espaço são dadas por interpolações dos pontos vizinhos; este método foi originalmente desenvolvido para astrofísica (Lucy, Gingold e Monaghan, 1977) e desde então tem sido aplicado em outras áreas das ciências.

A principal ideia do SPH é tratar a hidrodinâmica de uma maneira sem grides como no caso de elementos finitos. As equações são desenvolvidas levando em conta partículas, que deixa o sistema simples, com uma formulação de dinâmica de gás. Na representação SPH as quantidades conservadas são bem definidas. É uma formulação Lagrangeana, onde uma regiãolocal do SPH segue o fluxo de massa automaticamente, uma propriedade importante em sistemas astrofísicos com mudanças altas de densidade. Devido às suas particularidades e a facilidade de usar rotinas prontas para simulações cosmológicas em conjunto, este método se tornou popular em uma grande range de problemas em astrofísica, desde estruturas cosmológicas até estudos de colisões de protoplanetas. No coração do método SPH está a ideia de kernel interpolador, uma técnica para estimar o valor de uma função real como a média ponderada dos dados vizinhos à região. A extensões do SPH incluem modelaggem de campos magnéticos, fenômenos de transporte, processos radiastivos. O método também precisa ser extendido para considerar velocidades relativísticas. As aplicações do SPH incluem: formação de estruturas cosmológicas, estas simulações são usadas para o estudo de formação de galáxias em contexto cosmológico complexo, advindo de flutuações do cenário inflacionário; fusão de galáxias, a teoria hierárquica prediz a fusão constante de galáxias e a criação de grandes sistemas; em escalas mais baixas, muitas simulações SPH são feitas para estudar fragmentação de nuvens, formação de estrelas; formação de planetas e discos de acreção. O método tem sido aplicado com sucesso em formação gigantes e fragmentação de discos proto-planetários.

Agora o outro método popular é o refinamento por método adaptativo (AMR), é um método que usa a representação euleriana, este método é usado quando a dinâmica acontece em grandes ranges espaciais. Este método é um dos principais ingredientes em relatividade geral numérica. Em simulações numéricas de fusão de dois corpos, em geral

9. Quantum Mechanics (Non-relativistic).

9.1. Bohr’s atom

9.2. De Broglie’s relations (Energy-frequency, momentum-wave number).

9.3. Schrödinger’s equation (with electric potential and magnetic field).

9.3.1. Numerical solution of the Schrödinger equation

9.4. Ehrenfest’s theorem.

9.5. A particle in a box.

9.6. The hydrogen atom, solved systematically. The Zeeman effect. Stark effect.

9.7. The quantum harmonic oscillator.

9.8. Operators: energy, momentum, angular momentum, creation and annihilation operators.

9.9. Their commutation rules.

9.10. Introduction to quantum mechanical scattering. The S-matrix. Radio-active decay.

10. Atoms & Molecules

10.1. Chemical binding.

10.2. Orbitals.

10.3. Atomic and molecular spectra.

10.4. Emission and absorption of light.

10.5. Quantum selection rules.

10.6. Magnetic moments.

11. Solid State Physics

11.1. Crystal groups.

11.2. Bragg reflection.

11.3. Dielectric and diamagnetic constants.

11.4. Bloch spectra.

11.5. Fermi level.

11.6. Conductors, semiconductors and insulators.

11.7. Specific heat.

11.8. Electrons and holes.

11.9. The transistor.

11.10. Superconductivity.

11.11. Hall effect.

12. Nuclear Physics

12.1. Isotopes. Radio-activity. Fission and Fusion.

12.1.1. Geiger-Nuttall law

The Geinger-Nuttall relates the decay constant of a radioactive isotope with the energy of the alpha particles.

\[ \log _{10} \lambda=-a_{1} \frac{Z}{\sqrt{E}}+a_{2} \]

where \(\lambda\) is the decay constant, \(Z\) the atomic number, \(E\) the total kinetic energy and \(a_1\) and \(a_2\) are constants.

H. Geiger and J.M. Nuttall (1911) "The ranges of the α particles from various radioactive substances and a relation between range and period of transformation," Philosophical Magazine, Series 6, vol. 22, no. 130, pages 613-621. See also: H. Geiger and J.M. Nuttall (1912) "The ranges of α particles from uranium," Philosophical Magazine, Series 6, vol. 23, no. 135, pages 439-445.

G. Gamow (1928) "Zur Quantentheorie des Atomkernes" (On the quantum theory of the atomic nucleus), Zeitschrift für Physik, vol. 51, pages 204-212.

12.2. Droplet model.

12.3. Nuclear quantum numbers.

12.4. Magic nuclei.

12.5. Isospin.

12.6. Yukawa theory.

13. Plasma Physics

13.1. Magnetohydrodynamics.

13.2. Alfvén waves.

14. Advanced Mathematics

14.1. Group theory, and the linear representations of groups.

14.2. Lie group theory.

14.3. Vectors and tensors.

14.4. More techniques to solve (partial) differential and integral equations.

14.5. Extremum principle and approximation techniques based on that.

14.6. Difference equations.

14.7. Generating functions.

14.8. Hilbert space.

14.9. Introduction to the functional integral.

15. Special Relativity

These annotations are based on `http://jacobi.luc.edu/index.html` and `http://jacobi.luc.edu/Useful.html` i.e., the website of Prof. Robert A. McNees

Spacetime coordinates, 4-vectors, metric tensor \(g_{\mu\nu}\), etc:

Spacetime is any mathematical model which fuses the three dimensions of space and the one dimension of time into a single four-dimensional continuum, within of special relativity it relies on the Minkowski geometry.

15.1. 4-vectors.

In relativistic expressions four-vectors are written as

\[ A^{\mu} = (A_0, \vec{A}) = (A_0, A^1, A^2, A^3). \]

Four-vectors with superscript are called contravariant vectors (regarded as a column vector). Covariant vectors, denoted by subscript are defined as

\[ A_{\mu} = g_{\mu\nu}A^{\nu}, \]

with the metric tensor \(g_{\mu\nu}\) that reads in Cartesian coordinates in Minkowski space.

\[ \eta_{\mu \nu}=\eta^{\mu \nu} = {\rm diag}(1, -1, -1, -1); \qquad \eta^{\mu}{ }_{\nu}=\delta^{\mu}{ }_{\nu} = {\rm diag}(1, 1, 1, 1) \]

Raising and lowering indices:

\[ A^{\mu}=\eta^{\mu \nu} A_{\nu}; \qquad A_{\mu}=\eta_{\mu \nu} A^{\nu}; \]

Einstein summation convention:

\[ A^{\mu}B_{\mu} = A^0B_0 + A^{1}B_{1} + A^2B_2 + A^3B_3 = A^0B^0 - \vec{A}\cdot\vec{B}. \]

The inverse of the metric tensor is given by

\[ g^{\mu\nu} = g_{\mu\nu}. \]

A scalar product of two four-vectors is then defined by

\[ A \cdot B = A_{\mu}B^{\mu} = A^{\mu}B_{\mu} = A^0B^0 - \vec{A}\cdot\vec{B}. \]

The invariant square of the four-vector is thus

\[ A^2 = A_{\mu}A^{\mu} = A_0^2 - \vec{A}^2. \]

15.1.1. Spacetime coordinates:

\[x^{\mu} = (x^0, \vec{x}) = (ct, \vec{x}); \qquad x_{\mu} = (ct, -\vec{x}); \qquad \vec{x} = (x^1, x^2, x^3) = (x, y, z); \]

15.1.2. Four-momentum:

\[ p^{\mu} = (E/c, \vec{p}); \qquad p_{\mu} = (E/c, -\vec{p}); \qquad p^{\mu} = (p^1, p^2, p^3) = (p_x, p_y, p_z); \]

15.1.3. Derivatives:

\[ \partial_{\mu} \equiv \frac{\partial}{\partial x^{\mu}} = \left(\frac{1}{c} \frac{\partial}{\partial t}, \vec\nabla\right); \qquad \partial^{\mu} \equiv \frac{\partial}{\partial x_{\mu}} = \left(\frac{1}{c} \frac{\partial}{\partial t}, -\vec\nabla\right); \]

15.1.4. Four-momentum operator

\[ \hat{P}^{\mu} = i\partial^{\mu}. \]

15.1.5. Lorentz-invariant d'Alembert operator

\[ \partial^{\mu}\partial_{\mu} = \frac{\partial^2}{\partial t^2} - \vec\nabla^2 = \Box. \]

15.1.6. Four-current

\[ j^{\mu} = (\rho, \vec{j}). \]

15.1.7. Electromagnetic potential

\[ A^{\mu} = (\phi, \vec{A}). \]

15.2. The Lorentz transformation.

\[ A'_{\mu} = \Lambda_{\mu}{}^{\nu}A_{\nu}; \qquad A'^{\mu} = \Lambda^{\mu}{}_{\nu}A^{\nu}; \\ \eta^{\mu\nu} = \Lambda^{\mu}{}_{\alpha}\Lambda^{\nu}{}_{\beta}\,\eta^{\alpha\beta}; \qquad \eta_{\mu\nu} = \Lambda_{\mu}{}^{\alpha}\Lambda_{\nu}{}^{\beta}\,\eta_{\alpha\beta}. \]

  • Properties:
    1. \[\eta^{\mu \nu}=\Lambda_{\alpha}^{\mu} \Lambda_{\beta}^{\nu} \eta^{\alpha \beta}\]
    2. \[ \left|\operatorname{det} \Lambda_{\nu}^{\mu}\right|=1 \]
    3. \[ \left(\Lambda_{1}\right)^{\mu} \alpha\left(\Lambda_{2}\right)_{\nu}^{\alpha}=\left(\Lambda_{12}\right)_{\nu}^{\mu} \]
    4. \[ \left|\Lambda_{0}^{0}\right| \geq 1 \]

15.3. Lorentz contraction, time dilatation.

15.4. \(E=mc^2\).

15.5. Transformation rules for the Maxwell field.

15.6. Relativistic Doppler effect.

16. Advanced Quantum Mechanics

16.1. Hilbert space.

16.2. Atomic transitions.

16.3. Emission and absorption of light.

16.4. Stimulated emission.

16.5. Density matrix.

16.6. Interpretation of QM.

16.7. The Bell inequalities.

16.8. Towards relativistic QM: The Dirac equation, finestructure.

16.9. Electrons and positrons.

16.10. BCS theory for superconductivity.

16.11. Quantum Hall effect.

16.12. Advanced scattering theory.

16.13. Dispersion relations.

16.14. Perturbation expansion.

16.15. WKB approximation, Extremum principle.

The WKB approximation (named after Wentzel, Kramers and Brillouin) is a method for obtaining an approximate solution to a time-independent differential equation. Applications include: calculating bound-state energies and tunneling rates through potential barriers.

Solving the Schrödinger equation: It is a non-linear second order differential equation (ODE), in general, no analytic solution, an approximation method is usually applied to tackle the problem. The WKB approximation makes an assumptions of a slowly varying potential. See Boxi Li's note `https://www.thphys.uni-heidelberg.de/~wolschin/qms17_7s.pdf` if the link is broken, you can access the copy in `https://www.rvlobato.com/teaching/notes/pdfs/wkb.pdf`, more about WKB applied to tunneling `https://www.rvlobato.com/teaching/notes/pdfs/wkb_tunneling2.pdf`

16.16. Bose-Einstein condensation

16.17. Superliquid helium

16.18. Klein-Gordon equation

\[ \nabla^2\phi - m^2\phi = E^2\phi \]

Lagrangian Walecka model

\[ \mathcal{L} = \frac{1}{2}(\partial_{\mu}\sigma\partial^{\mu} - m_{\sigma}^2\phi^2) \]

17. Phenomenology/Astroparticles

17.1. Subatomic particles (mesons, baryons, photons, leptons, quarks) and cosmic rays

Particles classification

Particle Interaction
  Baryons Strong
Hadrons Mesons Electromagnetic
    Weak
  Electromagnetic
Leptons Weak
_ _
  • Baryons -> Fermions with half-integral spin (1/2, 3/2, …), Composed of 3 quarks. The lowest mass baryons are the proton and the neutron.
  • Meson -> Bosons with integral spin (0, 1, 2, 3, …). Composed of a quark + a anti-quarks.

17.1.1. QHD Quantum Hydrodynamics

  1. Modelo walecka

    \(\psi\) -> fermions -> p, n, hyperons (\(\Lambda, \Sigma, \Xi\)) (Dirac equations)

    \(\sigma\) -> meson, \(spin, S=0\),

18. General Relativity

18.1. 4-tensors

18.1.1. The metric tensor.

In local coordinates \(x^{\mu}\) the metric can be written in the form

\[ g=g_{\mu \nu} d x^{\mu} \otimes d x^{\nu}. \]

The factors \(dx^{\mu}\) are one-form gradient of the scalar fields \(x^{\mu}\). The coefficients \(g_{\mu\nu}\) are a set of 16 real-valued functions. The metric is symmetric

\[ g_{\mu \nu} = g_{\nu \mu}, \] giving 10 independents coefficients. Being \(dx^{\mu}\) the components of an infinitesimal displacement four-vector, the metric determines the invariant square of an infinitesimal line element, interval, denoted as

\[ d s^{2}=g_{\mu \nu} d x^{\mu} d x^{\nu}. \]

The interval \(ds^2\) imparts information about the causal structure of the spacetime.

  1. Timelike interval. If the spacetime interval is negative.
  2. Lightlike interval. If the spacetime interval is zero.
  3. Spacelike interval. If the spacetime interval is positive.

Under a change of coordinates \(x^{\mu} \rightarrow x^{\overline{\mu}}\), the components transform as

\[ g_{\bar{\mu} \bar\nu}=\frac{\partial x^{\rho}}{\partial x^{\bar{\mu}}} \frac{\partial x^{\sigma}}{\partial x^{\bar{\nu}}} g_{\rho \sigma}=\Lambda_{\bar{\mu}}^{\rho} \Lambda_{\bar{\nu}}^{\sigma} g_{\rho \sigma}. \]

  1. Flat spacetime

    The simplest of Lorentz manifold is flat spacetime which can be given as \(R^4\) with coordinates,

    \[ d s^{2}=-c^{2} d t^{2}+d x^{2}+d y^{2}+d z^{2}=\eta_{\mu \nu} d x^{\mu} d x^{\nu} \]

18.1.2. Space-time curvature.

The metric \(g\) completely determines the curvature of spacetime. On any semi-Riemannian manifold there is a unique connection \(\nabla\) that is compatible with the metric and torsion-free. The Levi-Civita connection. The Christoffel symbols of this connection are given in terms of partial derivatives of the metric in local coordinates

\[ \Gamma^{\lambda}_{}{\mu \nu}=\frac{1}{2} g^{\lambda \rho}\left(\frac{\partial g_{\rho \mu}}{\partial x^{\nu}}+\frac{\partial g_{\rho \nu}}{\partial x^{\mu}}-\frac{\partial g_{\mu \nu}}{\partial x^{\rho}}\right)=\frac{1}{2} g^{\lambda \rho}\left(g_{\rho \mu, \nu}+g_{\rho \nu, \mu}-g_{\mu \nu, \rho}\right), \]

the curvature of spacetime is then given by the Riemann curvature tensor which is defined in terms of the Levi-Civita connection \(\nabla\),

\[ R^{\rho}{}_{\sigma \mu \nu} = \partial_{\mu} \Gamma^{\rho}{}_{\nu \sigma}-\partial_{\nu} \Gamma^{\rho}{}_{\mu \sigma} + \Gamma^{\rho}{}_{\mu \lambda} \Gamma^{\lambda}{}_{\nu \sigma} - \Gamma^{\rho}{}_{\nu \lambda} \Gamma^{\lambda}{}_{\mu \sigma}. \]

  • Ricci tensor

\[ R_{\mu \nu}=\delta^{\sigma}{ }_{\rho} R^{\rho}{}_{\mu \sigma \nu}. \]

  • Scalar curvature

    \[ R = g^{\mu\nu}R_{\mu\nu}. \]

  • Schouten tensor

\[ S_{\mu \nu}=\frac{1}{d-1}\left(R_{\mu \nu}-\frac{1}{2 d} g_{\mu \nu} R\right); \qquad \nabla^{\nu} S_{\mu \nu}=\nabla_{\mu} S^{\nu}{}_{\nu}. \]

  • Weyl tensor

\[ C^{\lambda}{}_{\mu \sigma \nu} = R^{\lambda}{}_{\mu \sigma \nu} + g^{\lambda}{}_{\nu} S_{\mu \sigma} - g^{\lambda}{}_{\sigma} S_{\mu \nu} + g_{\mu \sigma} S^{\lambda}{}_{\nu} - g_{\mu \nu} S^{\lambda}{}_{\sigma}. \]

  • Commutators of Covariant Derivatives

\[ {\left[\nabla_{\mu}, \nabla_{\nu}\right] A_{\lambda} = R_{\lambda \sigma \mu \nu} A^{\sigma}}; \qquad {\left[\nabla_{\mu}, \nabla_{\nu}\right] A^{\lambda} = R^{\lambda}{}_{\sigma \mu \nu} A^{\sigma}}. \]

  • Bianchi Identity

\[ \nabla_{\kappa} R_{\lambda \mu \sigma \nu}-\nabla_{\lambda} R_{\kappa \mu \sigma \nu}+\nabla_{\mu} R_{\kappa \lambda \sigma \nu}=0; \qquad \nabla^{\nu} R_{\lambda \mu \sigma \nu}=\nabla_{\mu} R_{\lambda \sigma}-\nabla_{\lambda} R_{\mu\sigma}; \qquad \nabla^{\nu} R_{\mu \nu}=\frac{1}{2} \nabla_{\mu} R. \]

  • Bianchi identity for Weyl

\[ \nabla^{\nu} C_{\lambda \mu \sigma \nu}=(d-2) \left(\nabla_{\mu} S_{\lambda\sigma}-\nabla_{\lambda} S_{\mu \sigma}\right); \qquad \nabla^{\lambda} \nabla^{\sigma} C_{\lambda\mu \sigma \nu} = \frac{d-2}{d-1}\left[\nabla^{2} R_{\mu\nu}-\frac{1}{2 d} g_{\mu \nu} \nabla^{2} R-\frac{d-1}{2 d} \nabla_{\mu} \nabla_{\nu}R - \left(\frac{d+1}{d-1}\right) R_{\mu}{}^{\lambda} R_{\nu \lambda} + C_{\lambda \mu \sigma \nu} R^{\lambda \sigma}+\frac{(d+1)}{d(d-1)} R R_{\mu \nu}+\frac{1}{d-1} g_{\mu \nu}\left(R^{\lambda \sigma} R_{\lambda \sigma}-\frac{1}{d} R^{2}\right)\right] \]

  • Einstein tensor

    \[ G_{\mu\nu} = R_{\mu\nu} - \frac{1}{2}Rg_{\mu\nu} \]

which always obey \(\nabla^{\mu}G_{\mu\nu}=0\)

18.2. Einstein’s gravity equation.

From Einstein tensor, one can have

\[ G_{\mu\nu} = \kappa T_{\mu\nu} \] the field equation for the metric. The right-hand side is a covariant expression of the energy-momentum density (symmetric (0, 2) tensor). The left-had side is a symmetric conserved (0 , 2) tensor from the metric and its derivatives.

18.3. The Schwarzschild spacetime - black hole.

The standard Schwarzschild coordinates are introduced by a chart applied to the manifold \(\cal{M}\).

The metric tensor of the Lorentzian manifold \(\cal{M}\)

\[ g = \left( \frac{2 \, m}{r} - 1 \right) \mathrm{d} t\otimes \mathrm{d} t + \left( -\frac{1}{\frac{2 \, m}{r} - 1} \right) \mathrm{d} r\otimes \mathrm{d} r + r^{2} \mathrm{d} {\theta}\otimes \mathrm{d} {\theta} + r^{2} \sin\left({\theta}\right)^{2} \mathrm{d} {\phi}\otimes \mathrm{d} {\phi} \]

  • Christoffel symbols of \(g\) with respect to the Schwarzschild-Droste coordinates (the nonzero and nonredundant ones) are

    \begin{array}{lcl} \Gamma_{ \phantom{\, t} \, t \, r }^{ \, t \phantom{\, t} \phantom{\, r} } = -\frac{m}{2 \, m r - r^{2}} \\ \Gamma_{ \phantom{\, r} \, t \, t }^{ \, r \phantom{\, t} \phantom{\, t} } = -\frac{2 \, m^{2} - m r}{r^{3}} \\ \Gamma_{ \phantom{\, r} \, r \, r }^{ \, r \phantom{\, r} \phantom{\, r} } = \frac{m}{2 \, m r - r^{2}} \\ \Gamma_{ \phantom{\, r} \, {\theta} \, {\theta} }^{ \, r \phantom{\, {\theta}} \phantom{\, {\theta}} } = 2 \, m - r \\ \Gamma_{ \phantom{\, r} \, {\phi} \, {\phi} }^{ \, r \phantom{\, {\phi}} \phantom{\, {\phi}} } = {\left(2 \, m - r\right)} \sin\left({\theta}\right)^{2} \\ \Gamma_{ \phantom{\, {\theta}} \, r \, {\theta} }^{ \, {\theta} \phantom{\, r} \phantom{\, {\theta}} } = \frac{1}{r} \\ \Gamma_{ \phantom{\, {\theta}} \, {\phi} \, {\phi} }^{ \, {\theta} \phantom{\, {\phi}} \phantom{\, {\phi}} } = -\cos\left({\theta}\right) \sin\left({\theta}\right) \\ \Gamma_{ \phantom{\, {\phi}} \, r \, {\phi} }^{ \, {\phi} \phantom{\, r} \phantom{\, {\phi}} } = \frac{1}{r} \\ \Gamma_{ \phantom{\, {\phi}} \, {\theta} \, {\phi} }^{ \, {\phi} \phantom{\, {\theta}} \phantom{\, {\phi}} } = \frac{\cos\left({\theta}\right)}{\sin\left({\theta}\right)} \end{array}

18.4. Reissner-Nordström black hole.

18.5. Periastron shift

18.6. Gravitational lensing.

18.7. Cosmological models.

18.8. Gravitational radiation.

19. Cosmology

19.1. Big bang

19.1.1. Big Bang Nucleosynthesis

Primordial plasma reached \(\sim 1\ {\rm MeV}\) value and light nuclides such as \(^2{\rm H}\), \(^3{\rm He}\), \(^4{\rm He}\), \(^7{\rm Be}\) and \(^7{\rm Li}\) were produced.

  • One parameter controls the dynamics: Baryon to photon number density (standard cosmological scenario and framework of the electroweak standard model).
  • \(^7{\rm Li}\) Problem: theoretical prediction is a factor 2-3 higher than astrophysical measurements.

19.2. Books

  • Relativistic cosmology. George F.R. Ellis, Roy Maartens, Malcolm A.H. MacCallum
  • Cosmological Inflation and Large-Scale Structure. Liddle, A., & Lyth, D.
  • The Primordial Density Perturbation: Cosmology, Inflation and the Origin of Structure. David H. Lyth and Andrew R. Biddle
  • Exact Solutions of Einstein's Field Equations. Hans Stephani

20. Astrophysics

20.1. Compact stars

20.1.1. White dwarfs

20.1.2. Neutron stars

  • Reminiscent of stars with mass \(10\lesssim M/M_{\odot} \lesssim 25\).
  • In average the density is \(\rho\sim10^{14}\ {\rm g/cm^3}\). Denser than an atomic nucleus deeper inside.
  • One teaspoon of its material would have a mass over \(5.5\times10^{12}\) kg. It is about 6000 cargo ships.
  • The surface gravity is \(g\simeq10^{12}\ {\rm m/s^2}\). That is 1011 times the gravity on Earth.
  • The escape velocity on a NS \(100000 - 150000\ {\rm km/s}\), i.e., one third of the light speed.
  • Have magnetic field of \(10^8-10^{15}\ {\rm G}\) (Earth magnetic field 1 G, refrigerator magnet 100 G, sunspots \(3\times10^3\) G, magnetic resonance imaging \(7\times10^4\) G, LHC \(12\times10^4\) G)
  • Electric field \(10^{14}-10^{18}\ {\rm V/cm}\)
  • Temperature \(10^{6}-10^{11}\ {\rm K}\) (sun temperature 5778 \(\sim10^3\) K)
  • The rotation can reach 716 Hz (716 times per second), the linear speed is about 0.25c.
  1. Equation of state
    1. Nucleonic
      1. Non-relativistic
        1. APR

          Obtained from variational-method with modern nuclear potentials such as Argone (2-nucleon interaction) and Urbana (3-body interaction) potentials. Zero temperature and $β$-equilibrium \(npe\mu\) matter. (Akmal et al. (1998)).

        2. BBB

          Obtained from the Brueckner-Hartree-Fock (BHF) framework as approximation of the Brueckner-Bethe-Goldstone (BBG) theory. Uses two-three particle potentials. (Baldo et al (1997)).

        3. FPS

          Modern version of the EoS by Friedman and Pandharipande. It is a Skyrme type model with a energy density functional (EDF) that considers a nucleon-nucleon interaction by the Urbana potential and phenomenological three-nucleons interaction. (Lorenz et al (1993)).

      2. Relativistic
  2. Massive pulsars
    1. J1614-2230 (\(\approx2M_{\odot}\))
    2. J0348+0432 (\(\approx2M_{\odot}\))
    3. J0740+6620 (\(\approx2.14M_{\odot}\))
  3. Mass-radius measurements
    • {\it NICER}

      PSR J0030+0451

21. Quantum Field Theory

21.1. Classical fields: Scalar, Dirac-spinor, Yang-Mills vector fields.

21.2. Interactions, perturbation expansion. Spontaneous symmetry breaking, Goldstone mode, Higgs mechanism

21.3. Particles and fields: Fock space. Antiparticles. Feynman rules. The Gell-Mann-Lévy sigma model for pions and nuclei. Loop diagrams. Unitarity, Causality and dispersion relations. Renormalization (Pauli-Villars; dimensional ren.) Quantum gauge theory: Gauge fixing, Faddeev-Popov determinant, Slavnov identities, BRST symmetry. The renormalization group. Asymptotic freedom.

21.4. Solitons, Skyrmions. Magnetic monopoles and instantons. Permanent quark confinement mechanism. The 1/N expansion. Operator product expansion. Bethe-Salpeter equation. Construction of the Standard Model. P and CP violation. The CPT theorem. Spin and statistics connection. Supersymmetry.

22. Supersymmetry/Super gravity

Created by: Ronaldo V. Lobato on 2020-11-11. Last Updated: 2024-12-14 Sat 21:31