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Diffusion Monte Carlo (DMC) or diffusion quantum Monte Carlo is a
quantum Monte Carlo Quantum Monte Carlo encompasses a large family of computational methods whose common aim is the study of complex quantum systems. One of the major goals of these approaches is to provide a reliable solution (or an accurate approximation) of th ...
method that uses a
Green's function In mathematics, a Green's function is the impulse response of an inhomogeneous linear differential operator defined on a domain with specified initial conditions or boundary conditions. This means that if \operatorname is the linear differential ...
to solve the
Schrödinger equation The Schrödinger equation is a linear partial differential equation that governs the wave function of a quantum-mechanical system. It is a key result in quantum mechanics, and its discovery was a significant landmark in the development of the ...
. DMC is potentially numerically exact, meaning that it can find the exact ground state energy within a given error for any quantum system. When actually attempting the calculation, one finds that for
boson In particle physics, a boson ( ) is a subatomic particle whose spin quantum number has an integer value (0,1,2 ...). Bosons form one of the two fundamental classes of subatomic particle, the other being fermions, which have odd half-integer s ...
s, the algorithm scales as a polynomial with the system size, but for
fermion In particle physics, a fermion is a particle that follows Fermi–Dirac statistics. Generally, it has a half-odd-integer spin: spin , spin , etc. In addition, these particles obey the Pauli exclusion principle. Fermions include all quarks an ...
s, DMC scales exponentially with the system size. This makes exact large-scale DMC simulations for fermions impossible; however, DMC employing a clever approximation known as the fixed-node approximation can still yield very accurate results.


The projector method

To motivate the algorithm, let's look at the Schrödinger equation for a particle in some potential in one dimension: :i\frac=-\frac\frac + V(x)\Psi(x,t). We can condense the notation a bit by writing it in terms of an '' operator'' equation, with :H=-\frac\frac + V(x). So then we have :i\frac=H\Psi(x,t), where we have to keep in mind that H is an operator, not a simple number or function. There are special functions, called
eigenfunction In mathematics, an eigenfunction of a linear operator ''D'' defined on some function space is any non-zero function f in that space that, when acted upon by ''D'', is only multiplied by some scaling factor called an eigenvalue. As an equation, th ...
s, for which H\Psi(x)=E\Psi(x), where E is a number. These functions are special because no matter where we evaluate the action of the Hoperator on the
wave function A wave function in quantum physics is a mathematical description of the quantum state of an isolated quantum system. The wave function is a complex-valued probability amplitude, and the probabilities for the possible results of measurements mad ...
, we always get the same number E. These functions are called
stationary state A stationary state is a quantum state with all observables independent of time. It is an eigenvector of the energy operator (instead of a quantum superposition of different energies). It is also called energy eigenvector, energy eigenstate, ener ...
s, because the time derivative at any point x is always the same, so the amplitude of the wave function never changes in time. Since the overall phase of a wave function is not measurable, the system does not change in time. We are usually interested in the wave function with the lowest
energy In physics, energy (from Ancient Greek: ἐνέργεια, ''enérgeia'', “activity”) is the quantitative property that is transferred to a body or to a physical system, recognizable in the performance of work and in the form of heat a ...
eigenvalue In linear algebra, an eigenvector () or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted b ...
, the
ground state The ground state of a quantum-mechanical system is its stationary state of lowest energy; the energy of the ground state is known as the zero-point energy of the system. An excited state is any state with energy greater than the ground state. ...
. We're going to write a slightly different version of the Schrödinger equation that will have the same energy eigenvalue, but, instead of being oscillatory, it will be convergent. Here it is: :-\frac=(H-E_0)\Psi(x,t). We've removed the imaginary number from the time derivative and added in a constant offset of E_0, which is the ground state energy. We don't actually know the ground state energy, but there will be a way to determine it self-consistently which we'll introduce later. Our modified equation (some people call it the imaginary-time Schrödinger equation) has some nice properties. The first thing to notice is that if we happen to guess the ground state wave function, then H\Phi_0(x)=E_0\Phi_0(x) and the time derivative is zero. Now suppose that we start with another wave function(\Psi), which is not the ground state but is not orthogonal to it. Then we can write it as a linear sum of eigenfunctions: :\Psi=c_0\Phi_0+\sum_^\infty c_i\Phi_i Since this is a
linear differential equation In mathematics, a linear differential equation is a differential equation that is defined by a linear polynomial in the unknown function and its derivatives, that is an equation of the form :a_0(x)y + a_1(x)y' + a_2(x)y'' \cdots + a_n(x)y^ = b( ...
, we can look at the action of each part separately. We already determined that \Phi_0 is stationary. Suppose we take \Phi_1. Since \Phi_0 is the lowest-energy eigenfunction, the associate eigenvalue of \Phi_1 satisfies the property E_1 > E_0. Thus the time derivative of c_1 is negative, and will eventually go to zero, leaving us with only the ground state. This observation also gives us a way to determine E_0. We watch the amplitude of the wave function as we propagate through time. If it increases, then decrease the estimation of the offset energy. If the amplitude decreases, then increase the estimate of the offset energy.


Stochastic implementation

Now we have an equation that, as we propagate it forward in time and adjust E_0 appropriately, we find the ground state of any given
Hamiltonian Hamiltonian may refer to: * Hamiltonian mechanics, a function that represents the total energy of a system * Hamiltonian (quantum mechanics), an operator corresponding to the total energy of that system ** Dyall Hamiltonian, a modified Hamiltonian ...
. This is still a harder problem than
classical mechanics Classical mechanics is a physical theory describing the motion of macroscopic objects, from projectiles to parts of machinery, and astronomical objects, such as spacecraft, planets, stars, and galaxies. For objects governed by classical ...
, though, because instead of propagating single positions of particles, we must propagate entire functions. In classical mechanics, we could simulate the motion of the particles by setting x(t+\tau)=x(t)+\tau v(t)+0.5 F(t)\tau^2, if we assume that the force is constant over the time span of \tau. For the imaginary time Schrödinger equation, instead, we propagate forward in time using a
convolution In mathematics (in particular, functional analysis), convolution is a operation (mathematics), mathematical operation on two function (mathematics), functions ( and ) that produces a third function (f*g) that expresses how the shape of one is ...
integral with a special function called a
Green's function In mathematics, a Green's function is the impulse response of an inhomogeneous linear differential operator defined on a domain with specified initial conditions or boundary conditions. This means that if \operatorname is the linear differential ...
. So we get \Psi(x,t+\tau)=\int G(x,x',\tau) \Psi(x',t) dx' . Similarly to classical mechanics, we can only propagate for small slices of time; otherwise the Green's function is inaccurate. As the number of particles increases, the dimensionality of the integral increases as well, since we have to integrate over all coordinates of all particles. We can do these integrals by
Monte Carlo integration In mathematics, Monte Carlo integration is a technique for numerical integration using random numbers. It is a particular Monte Carlo method that numerically computes a definite integral. While other algorithms usually evaluate the integrand a ...
.


References

* * * {{Cite book, authors=B.L. Hammond, W.A Lester, Jr. & P.J. Reynolds, title=Monte Carlo Methods in Ab Initio Quantum Chemistry, series=World Scientific Lecture and Course Notes in Chemistry , publisher=World Scientific, doi=10.1142/1170, isbn=978-981-4317-24-5, date=1994, volume=1 Quantum chemistry Computational chemistry Quantum Monte Carlo