Section:
Research Program
Research Program
Quantum Chemistry aims at understanding the properties of matter through
the modeling of its behavior at a subatomic scale, where matter is
described as an assembly of nuclei and electrons.
At this scale, the equation that rules the interactions between these
constitutive elements is the Schrödinger equation. It can be
considered (except in few special cases notably those involving
relativistic phenomena or nuclear reactions)
as a universal model for at least three reasons. First it contains all
the physical
information of the system under consideration so that any of the
properties of this system can in theory be deduced from the
Schrödinger
equation associated to it. Second, the Schrödinger equation does not
involve any
empirical parameters, except some fundamental constants of Physics (the
Planck constant, the mass and charge of the electron, ...); it
can thus be written for any kind of molecular system provided its
chemical
composition, in terms of natures of nuclei and number of electrons,
is known. Third, this model enjoys remarkable predictive
capabilities, as confirmed by comparisons with a large amount of
experimental data of various types.
On the other hand, using this high quality model requires working with
space and time scales which are both very
tiny: the typical size of the electronic cloud of an isolated atom is
the Angström ( meters), and the size of the nucleus embedded
in it is meters; the typical vibration period of a molecular
bond is the femtosecond ( seconds), and the characteristic
relaxation time for an electron is seconds. Consequently,
Quantum Chemistry calculations concern very short time (say
seconds)
behaviors of very small size (say m) systems. The
underlying
question is therefore whether information on phenomena at these
scales is useful in understanding or, better, predicting
macroscopic properties of matter.
It is certainly not true that all macroscopic properties can be
simply upscaled from the consideration of the short time behavior of a
tiny sample of matter. Many of them derive from ensemble or bulk
effects, that are far from being easy to understand and to model.
Striking examples are found in solid state materials or biological
systems. Cleavage, the ability of minerals to naturally split along
crystal surfaces (e.g. mica yields to thin flakes), is an ensemble
effect. Protein folding is
also an ensemble effect that originates from the presence of the
surrounding medium; it is responsible for peculiar properties
(e.g. unexpected acidity of some reactive site enhanced by special
interactions) upon which vital processes are based.
However, it is undoubtedly true that many macroscopic phenomena originate from
elementary processes which take place at the atomic scale. Let us
mention for instance the fact that
the elastic constants of a perfect crystal or the color of a chemical
compound (which is related to the wavelengths
absorbed or emitted during optic transitions between electronic
levels) can be evaluated by atomic scale calculations. In the same
fashion, the lubricative properties of graphite are essentially due to a
phenomenon which can be entirely modeled at the atomic scale.
It is therefore reasonable to simulate the behavior of matter at the
atomic scale in order to understand what is going on at the
macroscopic one.
The journey is however a long one. Starting from the basic
principles of Quantum Mechanics to model the matter at the subatomic
scale,
one finally uses statistical mechanics to reach the macroscopic
scale. It is often necessary to rely on intermediate steps to deal with
phenomena which take place on various mesoscales.
It may then be possible to couple one description of the system with some
others within the so-called multiscale models.
The sequel indicates how this journey can be completed
focusing on the first smallest scales (the subatomic one), rather than on the
larger ones.
It has already been mentioned that at the subatomic scale,
the behavior of nuclei and electrons is governed by the Schrödinger
equation, either in its time dependent form
or in its time independent form. Let us only mention at this point that
-
both equations involve the quantum Hamiltonian of the
molecular system under consideration; from a mathematical viewpoint,
it is a self-adjoint
operator on some Hilbert space; both the Hilbert
space and the Hamiltonian operator depend on the nature of the system;
-
also present into these equations is
the wavefunction of the system; it completely
describes its state; its norm is set to one.
The time dependent equation is a first order linear evolution
equation, whereas the time-independent equation is a linear eigenvalue
equation.
For the reader more familiar with numerical analysis
than with quantum mechanics, the linear nature of the problems stated
above may look auspicious. What makes the
numerical simulation of these equations
extremely difficult is essentially the huge size of the Hilbert
space: indeed, this space is roughly some
symmetry-constrained subspace of , with , and
respectively denoting the number of nuclei and the number of
electrons the system is made of. The parameter is already 39 for a
single water
molecule and rapidly reaches for polymers or biological
molecules. In addition, a consequence of the universality of the model
is
that one has to deal at the
same time with several energy scales. In molecular systems, the
basic elementary interaction between nuclei and electrons (the two-body
Coulomb interaction) appears in various complex physical and chemical phenomena whose
characteristic energies cover several orders of magnitude: the binding
energy of core electrons in heavy atoms is times as large as a
typical
covalent bond energy, which is itself around 20 times as large as the
energy of a
hydrogen bond. High precision or at least controlled error cancellations
are thus required to reach chemical accuracy when starting from the
Schrödinger equation.
Clever approximations of the Schrödinger problems
are therefore needed. The main two approximation
strategies, namely the Born-Oppenheimer-Hartree-Fock and the
Born-Oppenheimer-Kohn-Sham strategies, end up with
large systems of coupled nonlinear partial differential equations,
each
of these equations being posed on . The size of the
underlying functional
space is thus reduced at the cost of a dramatic increase of
the mathematical complexity of the problem: nonlinearity. The
mathematical and
numerical analysis of the resulting models has been the major concern
of the project-team for a long time. In the recent years, while part of the activity still
follows this path, the focus has progressively shifted to problems at other scales.
Such problems are described in the following sections.