Chemistry & Vibration Modes
Working out why chemists like character tables, from first principles
When I first met finite groups and their representations in an undergraduate algebra class, they felt magical but esoteric. Differential equations felt connected to the real world; character tables did not. So it came as a genuine surprise when my chemist friends started casually using them — not as curiosities, but as working tools, on the same page as obviously practical concerns, like bond angles and vibrational spectra.
I never sat down to figure out what they were actually doing. I knew, vaguely, that the symmetry of a molecule controlled its behavior, and then that the character table was how this control was encoded. But how did symmetry affect behavior? This post is my attempt to work it out from first principles.
The goal is concrete: starting from Lagrangian mechanics of a molecule near an equilibrium, we will derive the procedure chemists use to read vibrational mode structure off a character table. Along the way the various ingredients — configuration space, the kinetic metric, the molecular point group, the isotypic decomposition — will show up in the order the physics needs them.
Because I’m a mathematician, I’m going to keep things needlessly general. Instead of narrowing our focus on the real world, we work on a general Riemannian manifold with isometry group . This way we can clearly see where the geometry, the analysis and the group theory interact.
The setup
We will work with the simplest classical toy model of a molecule: atoms are point masses in our ambient space , attracted to and repelled by one another through forces derivable from a potential energy. There is no electronic structure, no quantum mechanics — just classical particle dynamics on a Riemannian manifold. This is a less-than-honest model of real molecules, but it is enough to recover the chemists’ character-table procedure, which is what I am trying to understand.
A molecule, then, is a finite collection of point masses in , each atom labeled by a mass , with no two atoms ever occupying the same point. Ordered atom positions are tracked as a point in , but atoms of the same mass are physically indistinguishable, so swapping two of them gives the same molecule. The honest configuration space is the quotient
where is the diagonal (configurations with two atoms coincident) and is the group permuting atoms within each mass class. Motions of the molecule in space are curves in .
Two structures on drive everything that follows.
First, the kinetic metric. A moving molecule has kinetic energy , which is a quadratic form on . To unpack: a tangent vector at the configuration is a tuple with — one velocity vector per atom — and
the mass-weighted sum of the per-atom inner products. Written as a symmetric 2-tensor on , we’d say
Its - and -invariance are immediate: permuting equal-mass atoms leaves it alone, and moving the whole molecule by an isometry of leaves it alone.
Second, the potential . We require to be -invariant, where acts on by simultaneously moving every atom by the same isometry of (this is the diagonal action of on , which descends to since it commutes with ). Geometrically, the energy of a molecule does not depend on where in it sits or how it is oriented. In practice depends only on pairwise geodesic distances and bond angles, which are -invariant by construction.
The Lagrangian is , and the Euler–Lagrange equations take the coordinate-free form
where is the Levi–Civita connection of .
Everything in the rest of this post is a consequence of these few ingredients: the manifold , the kinetic metric , the -invariant potential , and the induced -action on .
Linearizing at an equilibrium
An equilibrium is a point with — a configuration at which no net force acts on any atom. We want to study small motions near such an equilibrium, and the natural first step is to linearize the Euler–Lagrange equation at .
Consider a one-parameter family of trajectories near the equalibrium . We might parameterize such a family in tersm of a variable , say with the equalibirum itself. Let be the small displacement at first order in . Since is the equalibirum, for all this vector based at , so is a curve in . This curve captures the infinitesimal behavior of our family of solutions near : since a vector at is really a collection of velocity vectors on each atom of our molecule, we can think of the path as an animation of changing velocity vectors on our equalibrium configuration, or an infinitesimal motion.
Our goal is to find the linearized equation that obeys. We get it by differentiating the Euler–Lagrange equation . Two vector fields on the image of organize the calculation. The first is which points along the solutions in our family — at each point it is the velocity of the trajectory passing through, obtained by moving in at fixed . The second is , which points across the family, from one solution to its neighbor — it is the displacement you see by moving in at fixed .
Thus, the fact that our family is a family of solutions, means that for each the Euler lagrangue equation is satisfied by
From this we want to extract an equation for . The idea is to covariantly differentiate both sides of the Euler–Lagrange equation along the variation direction , then evaluate at . Written out, we want to compute
and see what it says about . Each side turns out to be something we already care about. Two facts about this setup will do all of the work.
- Since and are derivatives of coordinate functions, .
- At the trajectory is constant in , so for all .
Left side
Rearranging the definition of the Riemann curvature tensor of ,
The bracket term vanishes, since . So
Next, we can swap the for . Precisely, the torsion free identity for the Levi Civita connection reads
The bracket term again vanishes, leaving . Substituting,
Now evaluate at . The curvature term vanishes because one of its arguments is (and its applied to !). What remains is . Along the constant curve , covariant differentiation reduces to ordinary differentiation in the vector space , and . So putting it all together
Right side
At , and , so applied to any vector field along the family reduces at to at . In particular,
The map is linear in (because the covariant derivative is linear in its lower index), so it is a linear operator on . We give it a name:
The right side of the Euler–Lagrange equation, linearized at the equilibrium, is .
Computing
We have named the operator, but at this point all we know about it is that it is linear. To get a formula — and to uncover whatever further structure has — we probe it by pairing against an arbitrary tangent vector via the kinetic metric. From the metric compatibility of the Levi–Civita connection,
Evaluating at does two things to this expression. The second term vanishes because . The first term simplifies via the defining property of the gradient, . Together,
The right-hand side has a hidden symmetry that we can extract by playing and off against each other. Using the bracket identity for vector fields acting on functions,
and the fact that , we conclude . But is exactly what our formula returns with the roles of and reversed: . Chaining these together,
where the last step uses symmetry of the metric. Comparing the first and last entries is exactly the statement that is self-adjoint with respect to the kinetic metric, a crucial property of for our future computational work.
To turn the implicit equation into an explicit formula for as a vector, we apply the musical isomorphism — the map that takes any 1-form to the unique vector with . The 1-form here is , and
This coordinate-free expression is somewhat abstract; the same defining relation also lets us compute in any basis we like. Pick a basis of and plug , into the formula. We get a number — call it — given by
If we use a coordinate basis, and , the right-hand side is a familiar second partial derivative
So is just the matrix of second partial derivatives of at the equilibrium.
But is not the matrix of our operator itself: sits inside a metric pairing on the left of the defining formula, so the kinetic metric is tangled with our operator. To peel off the metric and extract the matrix of alone, we use self-adjointness.
Treat , , and as ordinary matrices in our basis. For column vectors and ,
and self-adjointness of tells us . Setting the result equal to gives us the matrix identity
and demanding it hold for all and implies
The matrix of the operator in any basis is the inverse kinetic-metric matrix times the matrix of second partial derivatives of .
Putting it all together
We set out to study an infinitesimal deformation of the equilibrium solution — a curve describing the small motion away from rest. By covariantly differentiating both sides of the Euler–Lagrange equation along the variation direction and evaluating at , the relation
became a linear second-order ODE on the tangent space at the equilibrium,
where is the self-adjoint operator built directly from the two structures we started with — the (invese of the) kinetic metric and the (second derivatives of the) potential. Thus, the entire linear theory of molecular vibration is captured by the qualtiative behavior of ODE’s of this type.
A simplified derivation in
For comparison, here is the linearization in flat space, where the calculation is much shorter. Take , identify with an open subset of (where ) once we pick a basis, treat the kinetic metric as a constant symmetric positive-definite matrix , and let be the potential. The Lagrangian is
and the Euler–Lagrange equation reads
Linearize around an equilibrium (so ). Write and Taylor-expand the gradient,
where is the matrix of second partial derivatives at the equilibrium. Plug in, drop the terms, and multiply by :
Solving the linear theory
We are now ready to use the structure of to solve .
Modes by sign of eigenvalue
Because is self-adjoint with respect to the kinetic metric, the spectral theorem gives us a -orthonormal basis of consisting of eigenvectors of , with real eigenvalues.
Pick any eigenvector with eigenvalue , and look for solutions of the form where is a real-valued function of time. Plugging in,
so is a solution exactly when satisfies the scalar ODE
The behavior depends entirely on the sign of .
Positive eigenvalue (). The equation is a harmonic oscillator,
The mode wobbles back and forth in the direction with frequency — bounded oscillation. These are the normal modes of the molecule, and the corresponding are the normal frequencies.
Negative eigenvalue (). Writing with , the equation becomes , with general solution
For generic initial conditions the piece dominates: an arbitrarily small displacement in the direction grows exponentially in time. The equilibrium is unstable along — geometrically, is a saddle of in this direction, the potential going down rather than up.
Zero eigenvalue (). The equation reduces to , with general solution
The molecule drifts at constant velocity in the direction. There is no restoring force, no oscillation, no exponential growth — just uniform motion. These zero modes are neither oscillations nor instabilities; they are something else, and a structural part of the story.
Putting the modes together. Decomposing an arbitrary initial condition into the eigenbasis, the general solution to is
where each evolves independently according to its eigenvalue . The equilibrium is stable — every small perturbation stays small — exactly when every , i.e., when is positive definite. Equivalently, the matrix of second partials of at is positive definite, and is a local minimum of rather than a saddle or a maximum.
Real molecules sit at local minima of their potential, so we expect every nonzero to be positive — every nonzero mode an oscillation. But zero eigenvalues are not avoidable: there are always zero modes, forced by a structural feature of that we have so far ignored.
Where the zero modes come from
The structural feature we have so far ignored is that the equilibrium is never isolated. Equilibria of on always come in families, because is -invariant.
If for every , then carrying a critical point along the -action gives another critical point, and the full orbit
consists entirely of equilibria. This is not a pathology; it is the mathematical shadow of a fact we already accept — rigidly translating or rotating an equilibrium molecule gives another equilibrium molecule. The ambient isometry group acts trivially on the energy, so it acts non-trivially on the space of equilibria.
The tangent directions to this orbit at form a linear subspace
These are the infinitesimal rigid motions: velocities generated by a one-parameter subgroup of acting on the whole molecule at once.
Along any such direction the potential is constant — it has to be, because the orbit consists entirely of equilibria and they all share the same energy. So kills :
These are exactly the zero-eigenvalue modes from the previous section. We saw what they do under the linearized dynamics: they don’t oscillate, they drift. The molecule “oscillates” along these directions at zero frequency — which is to say, it just coasts off, rigidly translating or rotating through space.
These zero modes are not interesting as vibrations. They are the imprint on of the ambient isometry group, pure and simple. The genuine vibrational content of the molecule — the oscillatory modes we set out to compute — must live in the complementary directions.
The vibrational subspace
We need to separate the rigid-motion directions from the honest vibrations. The natural way is to take the orthogonal complement of in with respect to our kinetic metric — the only inner product on available to us. Define
so that the tangent space splits orthogonally as
The space is where the real vibrational dynamics lives. Before going further it is worth checking that the operator behaves nicely on the splitting — that it sends each summand into itself, and that the restriction is still self-adjoint.
That preserves is a consequence of self-adjointness. For any and any ,
since kills . So pairs trivially with every element of , which is to say . Self-adjointness of the restriction then comes for free: the restriction of a self-adjoint operator to an invariant subspace, together with the restricted inner product, is again self-adjoint. So is a self-adjoint operator on the inner product space .
Restricted to the operator is also non-degenerate (assuming is sufficiently generic — that we haven’t accidentally produced extra zero directions transverse to the orbit). The linearized Euler–Lagrange equation then decouples cleanly:
where with and . Zero modes drift; vibrational modes oscillate; the two never talk to each other.
So the problem reduces to a concrete finite-dimensional eigenvalue problem: diagonalize the self-adjoint operator on a vector space of dimension . For a molecule of atoms in three-space, is generically of dimension — which for even modestly sized molecules is already a substantial matrix.
Self-adjointness gives us a lot for free, even before we touch the matrix entries. The spectral theorem on yields an orthogonal direct sum
over the (real) eigenvalues of , where is the corresponding eigenspace. Each is a squared vibrational frequency , and the modes oscillating at frequency span . This is the most physical decomposition of available: split the modes by frequency.
Computing the eigenvalues and eigenvectors of explicitly requires the specific potential and a real diagonalization. But there are coarser questions about the spectrum that we might hope to answer without solving the eigenvalue problem at all:
- How many distinct vibrational frequencies are there?
- How many independent vibrational modes oscillate at each frequency?
Equivalently: how many distinct eigenvalues are there, and what are the dimensions ? This is coarse data about the eigendecomposition — the shape of the orthogonal direct sum, not the actual eigenvalues. And it is exactly the kind of information that symmetry alone can pin down, without reference to the specific .
This is where the group theory comes to save the day.
Symmetry and representation theory
Why symmetry?
We already know quite a bit about . It is a self-adjoint operator on a finite-dimensional inner product space, so the spectral theorem hands us an orthonormal basis of eigenvectors with real eigenvalues, and the small motions of the molecule decompose into independently oscillating modes accordingly. But this is a generic structure, available for any self-adjoint operator on any finite-dimensional inner product space. It tells us the modes exist; it tells us nothing about the organization of the spectrum — how many distinct frequencies, with what multiplicities, are forced.
If we want to say more about the spectrum without knowing the specifics of the potential , we need a structural input beyond ” is self-adjoint.” Symmetry is a natural candidate: a group acting on that commutes with would constrain its spectrum, in cases where the symmetry is rich enough. So our plan in this section is to identify a relevant group of symmetries of our linearized system, prove that it commutes with , and read off the consequences.
The symmetries of an equilibrium
The natural source of symmetries is the ambient isometry group , which we have already met as the group preserving everything we have built. We are not interested in all of , though, only the part that fixes our particular equilibrium . Set
What does an element of look like concretely? Pick a representative for the equivalence class . Then in exactly when the diagonally-moved tuple is -equivalent to . In other words: is a rigid motion of whose effect on the molecule’s atoms is the same as a permutation of equal-mass atom labels — there exists with for every .
So is the group of rigid motions of that send the molecular shape to itself. Each comes with a permutation , and is a group homomorphism .
In examples in :
- Water. has 4 elements: the molecular plane (containing all three atoms) is a mirror; the line through the oxygen perpendicular to the H–H line is a -rotation axis; and one further mirror containing that rotation axis is perpendicular to the molecular plane. The rotation and one mirror swap the two H’s; the molecular-plane mirror and the identity do not. Abstractly, is the Klein four-group .
- Ammonia. has 6 elements: two non-trivial rotations by about the nitrogen axis (cycling the three H’s), and three mirror planes containing that axis. Abstractly, is the dihedral group — the symmetry group of an equilateral triangle, or equivalently permutations of the three H atoms.
- Methane. has 24 elements — every symmetry of a regular tetrahedron, realized in as rotations and reflections that permute the four equivalent H atoms.
Action on the tangent space, and a classification
Each acts on the configuration space as a diffeomorphism
obtained by applying the isometry to every atom of the configuration. For , fixes the basepoint , so its differential at is a well-defined linear map of the tangent space. Collecting these differentials into a single homomorphism gives a representation of :
The representation has special structure built into how it was constructed: acts on by isometries of (since , and the descended action is isometric), and the differential of an isometry at a fixed point is itself a linear isometry of the tangent inner product space. So takes values in the orthogonal group of the kinetic-metric inner product:
We also note that preserves the splitting . The orbit is -invariant as a set, hence -invariant, so preserves ; preserving the metric, it then preserves as well. So restricts to an isometric representation on the vibrational subspace.
What kind of group is ? A priori sits inside the (large) orthogonal group . But the abstract group — sitting inside the much smaller Lie group — has a more constrained shape than that.
Warmup in . When this is easy to see directly. Place the origin at the (mass-weighted) center of mass of the molecule. Every permutes equal-mass atoms among themselves, so it preserves the center of mass and fixes the origin. The isometries of fixing the origin are exactly , so
For this is . The symmetry group of any molecular equilibrium in is a subgroup of .
This is a sharp constraint. Sometimes is infinite — a linear molecule like or has containing a continuous of rotations about the molecular axis. But if the molecule is not collinear, is finite. The finite subgroups of are completely classified. The finite subgroups of are the cyclic groups , the dihedral groups (of order ), and the three Platonic rotation groups (tetrahedral), (octahedral, equivalently the rotations of a cube), and (icosahedral, equivalently the rotations of a dodecahedron); the finite subgroups of are obtained from these by adjoining orientation-reversing elements like reflections.
So in we recover exactly the symmetry classification chemists already use: the molecular point groups. The same list in chemistry notation reads , , , , for the rotation-only groups, with their reflection-extended cousins , , , , , , , , .
The general case. The center-of-mass argument is genuinely Euclidean: in a curved Riemannian manifold the global Riemannian center of mass need not exist, and there is no canonical “origin” of to place. So we need a different route in the general setting — and fortunately the same kind of conclusion can be reached more abstractly, by identifying as a compact subgroup of and then applying a structural theorem about Lie groups.
That is compact follows from a standard fact in Riemannian geometry: the action of on is proper, meaning that the (setwise) stabilizer of any compact subset of is itself compact in . The atom positions form a compact (finite) subset of , and any permutes these atoms among themselves — so is contained in the setwise stabilizer of , which is compact by properness. Hence is compact.
(In typical cases is in fact finite. The precise condition is that the atoms are not all contained in a codimension-2 totally geodesic submanifold of — informally, that the molecule is “spread out enough” in that no continuous family of rotations preserves it. In this is the non-collinear case, since codimension 2 means a single geodesic line; a collinear molecule like has all its atoms on one line, and then contains a continuous of rotations about that line, giving or — still compact, just no longer finite. In higher-dimensional or differently shaped ambient spaces the condition adapts: in , a coplanar configuration similarly admits a continuous rotational stabilizer, and so on.)
Now apply a theorem of E. Cartan (the Cartan–Iwasawa–Mal’cev theorem): every compact subgroup of a Lie group is contained in some maximal compact subgroup of , and any two maximal compacts are conjugate. So embeds in a maximal compact of .
For Riemannian symmetric spaces this maximal compact has a clean identification, depending on type. For non-compact-type spaces (like ) and Euclidean-type spaces ( itself), the maximal compact of is exactly the point stabilizer at any chosen basepoint — so ends up inside that point stabilizer, which is in either case. For compact-type spaces (like ), is itself compact and serves as its own maximal compact; sits inside all of , which is a larger rotation group ( for ). Either way is a compact subgroup of a finite-dimensional rotation group.
In Thurston-geometry terms: and give ; gives ; the smaller geometries (, , , ) give correspondingly smaller maximal compacts inside . In every case is a compact subgroup of a familiar rotation group, and for sufficiently spread-out molecules — those whose atoms are not all on a codimension-2 totally geodesic submanifold of — it is in fact finite, falling into the classification we already wrote down.
For the rest of the post we assume our equilibrium satisfies this generic condition (in , that the molecule is non-collinear), so is a finite subgroup of — and the representation theory of is the classical theory of finite groups.
is -equivariant
Intuition. Think of as encoding the molecule’s linear restoring force: a small displacement from equilibrium produces a restoring force proportional to . Now suppose we displace not by but by its symmetry-image , for some . By symmetry of the molecule, the restoring force on this rotated/reflected displacement should be the same rotation/reflection of the original restoring force — that is, applied to . So
— the operator commutes with . Behind the scenes, this works because every ingredient of — the potential , the kinetic metric , and the equilibrium — is -invariant.
Proof. Recall how was defined: it is the unique linear operator on satisfying
— in other words, is built from the bilinear form via the kinetic metric. To show commutes with , it suffices to show that both sides of this defining relation transform compatibly under . The metric is -invariant by construction — is a linear isometry. The new fact we need is that the bilinear form is -invariant too. This follows from a single chain-rule fact:
Chain rule at a critical point. Let be smooth and a diffeomorphism with . If , then for any tangent vectors at ,
The slogan: at a critical point of , the second-derivative bilinear form of is ‘s second-derivative form with both inputs replaced by their pushforwards through .
We will apply the chain rule with , , , and . Combined with the metric invariance and the defining relation for , this gives the equivariance directly. Apply each fact in turn to the expression :
The first and last expressions are pairings against the same vector , and they agree for every . By non-degeneracy of the kinetic metric,
Conclusion.
The operator is -equivariant: for every .
This is the structural fact we will use everywhere from here on.
Rep theory to the rescue
Recall where we are. The spectral theorem gave us the orthogonal eigendecomposition from the self-adjointness of , and we posed two coarse questions about it: how many distinct eigenvalues are there, and what is the dimension of each eigenspace ? The new structural input we have is that carries a representation of , and the operator “plays well” with the -representation (they commute).
The first consequence of this commutation is that each eigenspace of is itself a representation of . Take an eigenvector with eigenvalue . For any ,
so is also an eigenvector of with the same eigenvalue . The eigenspace is therefore preserved by every , and so inherits the action and becomes a representation of in its own right.
To go further, we use a key fact from rep theory.
Building blocks: irreducible representations
The first thing rep theory tells us is that any representation of a finite group splits into “indivisible” pieces. An irreducible representation (or irrep) is one with no proper -invariant subspace — the smallest possible representation.
Maschke’s theorem. Every finite-dimensional representation of a finite group is completely reducible: it decomposes as a direct sum of irreps.
So our decomposes:
with each an irrep of .
What does this give us, qualitatively? Two things. First, is built out of simple ingredients — irreducible pieces that cannot be split further while respecting symmetry. Second, for any given finite group , there are only finitely many irreps up to equivalence. So the symmetry content of is a list of pieces drawn from a small finite menu.
The same theorem applies to every eigenspace separately, since each is itself a representation. So we now know each eigenspace is a sum of irreps drawn from the same finite menu — its symmetry content is also captured by a list.
Isotypic decomposition
Different copies of the same irrep can appear in , so it is clarifying to collect them. The isotypic decomposition groups equivalent irreps together:
The sum runs over irreps of that appear in , and the multiplicity space is a plain vector space (no -action of its own) whose dimension counts how many copies of appear. The notation encodes ” copies of ”: acts irreducibly on the factor, trivially on .
The two factors play different roles. The piece carries the symmetry content — how vectors there transform under . The multiplicity space carries the bookkeeping — how many copies of that symmetry type are present. The distinction matters in a moment.
Schur’s lemma constrains
Now we use ‘s equivariance. Each isotypic component is a -invariant subspace, so restricts to a -equivariant operator on each. The decisive question: what can such an operator look like?
Schur’s lemma. Any -equivariant linear map has the form for some endomorphism of the multiplicity space .
What does this tell us, qualitatively? has no power to distinguish vectors within a single copy of an irrep. The whole copy is forced to behave the same way: acts on it as the identity (times some scalar, set by where the copy sits in the multiplicity space). The only freedom has is in how it mixes the different copies of an irrep among themselves. That mixing is encoded by on .
The reason this is forced: irreps are by definition the smallest -invariant subspaces; a -equivariant map can rearrange copies of an irrep, but it cannot rearrange anything within a single copy without breaking equivariance.
Apply this to . On each isotypic component , acts as for some self-adjoint operator on (self-adjointness inherited from ). So is a direct sum of self-adjoint operators on the multiplicity spaces, one block per irrep:
Aligning the two decompositions
We now have two direct-sum decompositions of :
- The frequency decomposition from the spectral theorem — split by vibrational frequency.
- The isotypic decomposition from rep theory — split by symmetry type.
There is a clear always-true relationship between them, plus a sharper generic statement on top. Let’s separate the two.
Always true: each eigenspace splits into whole irreps. This is just Maschke, applied one more time. Each eigenspace is -invariant (we proved this), so it is itself a representation of . Apply Maschke directly to : it decomposes as a direct sum of irreps,
The output of Maschke is by construction a sum of complete irreps — there is no “partial copy” possibility. So every irrep appearing inside appears as a full copy, classified by its type , with such copies (possibly , if irrep does not appear at frequency ).
Comparing with the global isotypic decomposition : collecting the irrep- pieces from each eigenspace recovers the global -component, with . From the side, this is exactly the spectral decomposition of on — its -eigenspace is .
Generic: each eigenspace is one irrep. In general, an eigenspace can contain pieces of multiple irrep types — if and happen to share an eigenvalue , both contribute to . And itself can have repeated eigenvalues, putting multiple copies of into a single . Both are accidents: there is no symmetry reason for them, and a generic potential avoids them.
In the generic case — no accidents of either kind — the eigen decomposition coincides with the frequency decomposition itself, and each eigenspace is exactly one copy of one irrep . Each vibrational frequency has a single “symmetry type,” and its eigenspace is -dimensional.
What do we learn? Going back to the coarse questions we posed:
- How many distinct frequencies are there? Generically — one for each eigenvalue of each . The total is set by the irrep multiplicities .
- How many independent modes at each frequency? , where is the irrep that frequency is “stamped with.” A 2-dimensional irrep forces pairs of degenerate modes; a 3-dimensional irrep forces triples.
Two different numbers in this story, easy to conflate:
- The multiplicity — how many copies of appear in . This counts the number of independent frequencies of symmetry type .
- The forced degeneracy — how many independent modes share each of those frequencies.
The list of irreps appearing in , together with their multiplicities , is the symmetry-only data of the spectrum: which irreducible blocks appear, at what dimension, with how many independent frequencies each. This list depends on and on the representation — both depending on the molecule and its symmetry, but neither depending on the potential.
The actual frequencies need (we still have to diagonalize each ); the structural skeleton — the irrep at each frequency — does not.
Computing with characters
The decomposition exists abstractly, but to actually pin down the multiplicities we need a way to read them off the representation that doesn’t require us to explicitly diagonalize anything. Characters do this for us.
Given a finite-dimensional representation , its character is the function
The map seemingly throws almost all of our original representation away. is not a homomorphism — taking traces destroys multiplication — it is just a real-valued function on , an element of the function space . The matrices are gone; only their traces remain.
What we trade up for is enormous simplification. is a finite-dimensional vector space. The complicated category of representations gets replaced by a small linear-algebra problem.
For this trade to be worthwhile, the map had better be lossless — knowing should be enough to recover up to isomorphism. Amazingly, it is. This is the crucial theorem of character theory:
Characters determine representations. Two finite-dimensional representations of with the same character are isomorphic.
(There is no single agreed-upon name for this — Serre states it just as a corollary of the orthogonality relations below; it’s the load-bearing consequence of those relations.) Once we have this theorem, studying up to isomorphism is exactly the same as studying as an element of a small vector space. Everything we want to know — what irreps appear, with what multiplicities — is encoded in , and is to be extracted by linear algebra.
The rest of this subsection is the structural setup that makes the linear algebra work cleanly.
is a class function. Trace is conjugation-invariant: . So doesn’t really take values on individual group elements — it takes values on conjugacy classes. The function space it actually lives in is the space of class functions
whose dimension equals the number of conjugacy classes of . This is much smaller than — for (), .
has a natural inner product, and irreducible characters are an orthonormal basis. The inner product is the group average,
(the second sum runs over conjugacy classes, legitimately because depend only on the class). And:
Orthonormality of irreducible characters. The characters of the (finitely many) irreducible representations of form an orthonormal basis of .
This is what does the work behind the scenes: linear independence of the is what makes the multiplicities in uniquely determined — which is what makes “characters determine representations” true. Two consequences worth flagging: the number of irreps of equals the number of conjugacy classes of (both equal ), and every class function expands uniquely against the basis .
Apply that last point to itself. If , additivity of trace gives , and orthonormality reads off the coefficients:
So the entire categorical question “what is , up to isomorphism?” reduces to: compute the trace of on for one in each conjugacy class — that’s all of — and take the inner product against each .
Character tables
A character table packages the irreducible characters of a fixed group into a single grid: rows indexed by irreps , columns indexed by conjugacy classes , entries .
By the orthonormality theorem, this table records everything needed for representation arithmetic over . To find the multiplicities of irreps in any representation , you need only
- the character table of — a one-time lookup; and
- the character of your representation — one number per conjugacy class.
Then is a finite sum: pair the values with the -row of the table, weight each term by class size, sum, divide by .
A few features worth knowing for any character table. The first column (under ) is always the dimension of the irrep (). The first row is always the trivial representation (‘s everywhere — every element acts as the identity on ). The number of rows equals the number of columns (both equal the number of conjugacy classes of ). And the squared dimensions of the irreps sum to the order of the group:
a useful sanity check.
Let’s now build the character tables for the two groups we will need: water’s and ammonia’s.
Water
Place water in the plane with the oxygen at the origin and the -axis bisecting the H–H line. Then has four elements:
- the identity ;
- the rotation by about the -axis (sending each H to the other);
- the reflection in the molecular plane (fixing all three atoms);
- the reflection in the perpendicular plane (sending each H to the other).
These satisfy and ; any two generate the third. The group is abelian, and abstractly it’s — the Klein four-group.
In an abelian group every conjugacy class is a singleton, so there are classes and hence irreps. The dimensions satisfy , which forces for all — every irrep is -dimensional. A -dimensional rep of the Klein four-group is just a homomorphism into , so it amounts to picking signs for the two generators independently. Four sign-choice combinations, four irreps. Label them where records the chosen signs:
- : , (the trivial rep).
- : , .
- : , .
- : , .
Filling in the value at by multiplicativity (these are -dim reps, so ), the character table is:
The table is a matrix of ‘s — orthogonality of rows is visible by inspection: any two distinct rows have equal counts of and in their pointwise product, summing to . Each row’s squared norm is , normalizing to unit length under the inner product.
Ammonia
Place ammonia with the nitrogen on the -axis and the three H atoms forming an equilateral triangle in (a plane parallel to) the -plane. Then has six elements:
- the identity ;
- two rotations about the -axis by (cycling the three H atoms);
- three reflections , one in each vertical plane through the -axis and one of the H atoms.
These satisfy , , and (each reflection inverts the rotation). This is the dihedral group — the symmetry group of an equilateral triangle — equivalently , the symmetric group on the three H atoms (each is determined by the permutation it induces on the three H labels).
Conjugacy classes: the rotations and are conjugate to each other (any reflection conjugates one to the other), and the three reflections are all conjugate to each other (the rotations cycle them). So we get three classes:
- — element;
- — rotations;
- — reflections.
Three classes, hence three irreps. The dimensions satisfy , with at least one (the trivial rep), and the unique solution in positive integers is . So has two -dimensional irreps and one -dimensional irrep:
- The trivial rep : every element .
- The sign rep : rotations , reflections . Under the identification , this sends each permutation to its sign.
- The standard rep : the action of on as honest rotations and reflections of an equilateral triangle. (Equivalently: acts on by permuting coordinates; is the orthogonal complement of the diagonal .)
To fill in the table we need traces. For the -dim irreps the entries are just the sign assignments. For : the value at is (the dimension); a rotation by in has trace ; a reflection in has trace (one eigenvalue along the mirror, one perpendicular). So:
Orthogonality is again checkable by inspection, now with the class-size weights: e.g. , and .
The standard rep is the only -dimensional one in either of our tables — it is the source of the forced doublet degeneracies we’ll find in ammonia’s vibrational spectrum.
Computing
For our problem, . We get to by computing on the larger space and subtracting off the rigid-motion piece.
Total character on . Each is a block matrix in this decomposition. An atom that moves to a different atom contributes a zero diagonal block (its entries land in ). An atom that fixes contributes . So only fixed atoms contribute:
Rigid-motion character on , with acting by the descended adjoint action. For and a non-collinear molecule, and : three translations plus three rotations. acts on the translations by its inclusion (vector representation), and on the rotations by that same inclusion twisted by the determinant (axial-vector representation). So splits as
where is the trace of in the vector representation. This is on proper rotations and on improper ones.
Then
and .
Water
Coordinates as before — -axis along the rotation axis , molecule in the -plane, so is the molecular mirror and is perpendicular. For each class:
- fixes all atoms; , . So , .
- fixes only O (it swaps the H’s); (rotation by in has trace ), . So , .
- is the molecular plane and fixes all atoms; (trace of a reflection in ), . So , .
- fixes only O (swaps the H’s); , . So , .
Tabulating:
Inner-producting with each row of the character table (every class has size , ):
So
Total dimension , matching . ✓
What this tells us: water has vibrational modes, all stamped with -dimensional irreps, so no forced degeneracies. The two modes are invariant under all of (these are the symmetric stretch and the bend); the mode changes sign under both and (the antisymmetric stretch). The two modes form a -dimensional multiplicity space , on which is a self-adjoint operator — its two eigenvalues are the actual stretch and bend frequencies, set by the potential, with no symmetry obstruction to being whatever they are.
Ammonia
Three conjugacy classes — .
- : all atoms fixed; , . , .
- (rotation by ): only N fixed (the three H’s cycle); , . , .
- : N is fixed, plus the one H lying in this mirror plane; the other two H’s swap. So fixed atoms; , . , .
Inner-producting (class sizes ; ):
So
Total dimension , matching . ✓
Now we see the forced doublets explicitly: ammonia has vibrational modes, organized as singlets (copies of the trivial rep ) plus doublets (copies of ). The -block is on , contributing two singlet frequencies; the -block is on , and each of its eigenvalues comes with multiplicity in the full spectrum, because is -dimensional. So generically ammonia’s spectrum has distinct frequencies: two nondegenerate (the two trivial-rep copies) plus two doubly degenerate (the two standard-rep copies). Physically these are commonly described as a symmetric stretch and an “umbrella” inversion (the singlets) plus an asymmetric stretch pair and an asymmetric bend pair (the doublets).
What this computes — and what it doesn’t
What the character procedure gives us is the list , which by Schur tells us exactly how the spectrum decomposes by irrep — how many singlets, how many doublets, how many triplets, with all forced degeneracies accounted for. We learn the structural skeleton of the spectrum from and the molecule alone, before any eigenvalue problem is solved.
What we don’t get is the numerical values of the frequencies. Each is a small self-adjoint operator on the multiplicity space , and to compute its eigenvalues we need . Representation theory gives the structure; the dynamics gives the numbers.
This is the punchline. The character-table procedure that chemists use is doing exactly the symmetry-only part of the analysis — neither more nor less than what character orthogonality lets representation theory see. The remaining numerical eigenvalue problem inside each -block is a separate, smaller calculation, doable molecule-by-molecule once a potential is chosen.
Epilogue: What the generality bought us
Working with an abstract throughout, rather than narrowing to from the start, was free — the derivation never used anything about that wasn’t packaged into “Riemannian manifold with isometry group.” As a payoff, we get a few structural facts that aren’t obvious from the chemistry-textbook treatment.
Curvature is invisible to the harmonic machinery. The Riemann curvature of made a brief appearance in the linearization (in the term) and then vanished, because at the equilibrium. The whole construction — the operator , its self-adjointness, the rep-theoretic decomposition of its spectrum — went through without ever using the curvature of . Curvature first enters at cubic order, in the anharmonic corrections.
(The numerical eigenvalues of do still depend on the ambient space, since the potential is typically built from pairwise geodesic distances, which differ between , , , and so on. What’s curvature-independent is the form of the harmonic theory — same construction, same self-adjointness, same Schur structure — not the values of the frequencies.)
The vibrational dimension is . For a non-collinear molecule the dimension of the vibrational subspace is the total degrees of freedom minus the dimension of the ambient isometry group:
For a molecule of atoms in () this is the chemist’s familiar . On and it is also ( in both cases). On () it is , and on () it is — different ambient geometries support different numbers of “rigid motions” of a generic molecule, and the vibrational dimension absorbs the difference.
Mode organization is rep theory of on . The way the spectrum is organized into blocks — which irreps appear, with what multiplicities, with what forced degeneracies — is determined entirely by the representation of the symmetry group on the vibrational subspace. This depends on the molecule, but not on the potential, and not on whether the ambient space is curved or flat (but it does depend on the size of the isometry group). Same character tables, same forced degeneracies, regardless of .