Time-reversal symmetry adaptation in relativistic density matrix renormalization group algorithm
Abstract
In the nonrelativistic Schrödinger equation, the total spin and spin projection are good quantum numbers. In contrast, spin symmetry is lost in the presence of spin-dependent interactions such as spin-orbit couplings in relativistic Hamiltonians. Previous implementations of relativistic density matrix renormalization group algorithm (R-DMRG) only employing particle number symmetry are much more expensive than nonrelativistic DMRG. Besides, artificial breaking of Kramers degeneracy can happen in the treatment of systems with odd number of electrons. To overcome these issues, we introduce time-reversal symmetry adaptation for R-DMRG. Since the time-reversal operator is antiunitary, this cannot be simply achieved in the usual way. We define a time-reversal symmetry-adapted renormalized basis and present strategies to maintain the structure of basis functions during the sweep optimization. With time-reversal symmetry adaptation, only half of the renormalized operators are needed and the computational costs of Hamiltonian-wavefunction multiplication and renormalization are reduced by half. The present construction of time-reversal symmetry-adapted basis also directly applies to other tensor network states without loops.
I Introduction
Relativistic quantum mechanics are more accurate description of the real world than the nonrelativistic quantum mechanics1. Phosphorescence, intersystem crossings, and zero-field splittings cannot be described by the Schrödinger equation due to the lack of spin-dependent interactions such as spin-orbit couplings (SOC) and spin-spin interactions. Unfortunately, it is known that relativistic calculations are much more expensive that nonrelativistic calculations either at the mean-field or correlated level. Depending on the level of theories, this can be attributed to several factors, such as the presence of negative energy states in the four-component Dirac equation, the loss of spin symmetry, and the use of complex algebra, etc. At the correlated level, adopting the no-pair approximation in four-component theories or using a two-component relativistic Hamiltonian such as the exact two-component (X2C) Hamiltonian2, 3, 4 from the start will make the dimension of the one-electron basis identical to that in the nonrelativistic unrestricted case5. The loss of spin symmetry is a more challenging issue. Since the time-reversal operator commutes with relativistic Hamiltonians in the absence of magnetic field, the time-reversal symmetry can be used to ameliorate the situation. However, its adaptation in correlated methods is nontrivial 6, 7, 8, 9, 10.
In this work, we consider the time-reversal symmetry adaptation in relativistic density matrix renormalization group (R-DMRG) algorithm. The DMRG algorithm11 has become a powerful tool for treating strongly correlated molecules12, 13, 14, 15, 16, 17, 18, 19, 20, 21. Thus, it will be of great interest to apply it to challenging systems involving heavy elements. In fact, including scalar relativistic effects into DMRG was carried out long time ago22, 23, and state interaction schemes for treating SOC based on matrix product states (MPS) obtained from spin-free DMRG calculations has been put forward24, 25, 26. However, including SOC variationally within DMRG27, 28, 29, 30 has only been achieved without time-reversal symmetry adaptation. Such R-DMRG implementation is much more expensive than nonrelativistic non-spin-adapted DMRG. While in the nonrelativistic case, a renormalized state can be labeled by (point group symmetry is not discussed here), where is the particle number and is the spin projection, only is a good quantum number in the relativistic case. Another problem for lacking time-reversal adaptation is that artificial breaking of Kramers degeneracy can happen in the treatment of systems with odd number of electrons. These drawbacks motivate us to introduce time-reversal symmetry adaptation for R-DMRG.
Conceptually, the fundamental difficulty of time-reversal symmetry adaptation is that the time-reversal operator is an anti-unitary operator31, unlike other symmetry operations employed in DMRG. In simple words, it cannot be simply achieved by associating a ’quantum number’ for an irreducible representation to renormalized states32, 33, 34, 35, 36, 37, 38, 39. In principle, one can add time-reversal operation into a symmetry group to form an enlarged group (called magnetic group40), and use Wigner’s corepresentation theory31, which is a generalization of the standard representation theory for groups of unitary operators to groups including anti-unitary elements. Without going into such mathematical complication, we will show that introducing a concept of time-reversal symmetry-adapted renormalized basis is already sufficient for our purpose. The proposed usage of time-reversal symmetry-adapted basis also directly applies to other tensor network states (TNS) without loops, such as the general tree TNS41, 42, 43, 44 or the simpler comb TNS45, 46.
The remainder of this paper is organized as follows. In Sec. II, we introduce the definition of time-reversal symmetry-adapted basis. In Sec. III, we present strategies to maintain such structure during the sweep optimization in DMRG, and demonstrate that a reduction of the computational costs of matrix-vector multiplication and renormalization by half can be achieved by using time-reversal symmetry. Conclusion and outlook is given in the last section.
II Time reversal symmetry-adapted basis
II.1 Definition
To utilize the time-reversal symmetry, we introduce the following time-reversal symmetry-adapted orthonormal basis for a subspace of the Fock space
(1) |
where the superscript/subscript e (or o) represents even (or odd) number of electrons. Here, the notation needs to be understood as , and we only show one of the basis functions for brevity. For later convenience, we will refer to the structure of basis for as time-reversal invariant, and that for as time-reversal paired. Note that the orthogonality between and its time-reversal partner is automatically guaranteed by the Kramers’ theorem. An arbitrary basis for does not necessarily takes this form (1). However, as long as is invariant under the action of , we can always construct basis functions with such structure based on the following observations:
(i) For the even-electron case, an arbitrary state and its time-reversal partner is not necessarily orthogonal, because the time-reversal operation does not impose any constraint on the overlap . Suppose is normalized, then by the Cauchy-Schwarz inequality. There can be two cases:
-
1.
If , which means that these two states are parallel and simply differ by a phase , then the new state will satisfy the condition in Eq. (1), i.e., . This derivation also shows that in this case the eigenvalue of is arbitrary, since for an arbitrary . Our choice will make the later discussion of matrix representation of operators very compact.
-
2.
If , then the linear combinations
(4) yield two linear independent functions satisfying Eq. (1). They are not orthonormal as the overlap metric depends on the overlap between and ,
(5) This real overlap matrix can be utilized to produce a time-reversal invariant orthonormal basis.
(ii) For the odd-electron case, an orthonormal set of will not be automatically orthogonal to , except for . This is different from the nonrelativistic or spin-free relativistic case with symmetry, where the two parts are of different spin projections and hence are orthogonal automatically. In general, the overlap metric for has a quaternion structure
(6) |
Diagonalizing it with an algorithm preserving the quaternion structure47, 48, 49, 50, 51, 52, 53 produce the following structured eigenvectors
(7) |
where is a positive semidefinite diagonal matrix. The matrix is also symplectic
(8) |
It can be used to construct a time-reversal paired orthonormal basis, e.g., using canonical orthonormalization54.
Therefore, we demonstrate that the basis with the structure (1) does exist for a time-reversal invariant subspace . In fact, Eq. (1) corresponds to the only two classes of irreducible projective representations of for systems with particle number and time-reversal symmetry 55. Here, represents a semidirect product, because for any element in with being the particle number operator, we have instead of a commuting relation. If is not invariant under the action of , we will refer it as time-reversal incomplete. Calculations performed within such space (e.g., configuration interaction) can be called Kramers symmetry contaminated, in analogy to spin contamination in the nonrelativistic case.
II.2 Direct product space
Having defined the time-reversal symmetry adapted basis, we consider its construction in a direct product space, which is relevant for constructing a configuration interaction space in DMRG. The direct product space of and another subspace with the structure (1) can be decomposed as
(9) | |||||
The pair structure for basis functions of is clear, following from the structures of and . For the even-electron subspace , by noting that
(10) |
we can define the following time-reversal invariant basis
(11) |
Consider the example that both and are one-electron spin states, then are triplets in a Cartesian representation1, while is singlet, viz.,
(16) |
Suppose a wavefunction is expanded in this direct product basis is , the coefficients of and its time-reversal partner are related by
(17) |
where the positive sign is for even-electron systems and the minus sign is for odd-electron systems as . We can write the wavefunction coefficient in the direct product space as a matrix
(18) |
such that for odd-electron systems
(19) |
and for even-electron systems
(20) |
Similar to Eq. (1), we can require the many-electron wavefunction of even electron system to be time-reversal invariant. Consequently, the wavefunction coefficient matrix is simplified as
(21) |
with the submatrix being real.
III Time reversal symmetry-adapted DMRG
We will show how the structure (1) can be maintained during the sweep optimization in DMRG, and used to reduce memory and computational cost. For this purpose, it suffices to discuss the local optimization problem in the sweep optimization, which amounts to first solve a configuration interaction problem in the direct product space ,
(22) |
and then produce an optimized basis for or (so-called decimation). We refer the readers to Refs. 13 for a detailed description of the entire sweep optimization.
III.0.1 Hamiltonian
We assume the one-electron basis has a Kramers paired structure , which can either be spin-orbitals or spinors computed from spin-restricted or Kramers-restricted self-consistent field calculations, respectively. The action of the time-reversal symmetry operator on spin-orbitals/spinors reads
(23) |
In the absence of magnetic field, commutes with the Hamiltonian , which is written in a second quantized form as
(24) |
To get the representation of in the direct product space , is usually rewritten as
(25) |
where , () represents the index of one-electron basis for the subspace (), and the introduced intermediates (normal and complementary operators56, 13) are
(26) |
The time-reversal invariance of the Hamiltonian is not obvious in this form. Since the integrals satisfy time-reversal symmetry, viz., and , we can rewrite Eq. (25) as
(34) |
using the derived time-reversal symmetry properties of intermediates such as
(35) | |||||
(36) |
The obtained ’skeleton’ operator is Hermitian but not time-reversal invariant, but the number of operators in is roughly half of that in . This form will be used later to reduce the computational cost of R-DMRG.
III.0.2 Diagonalization
To solve Eq. (22) in with in Eq. (34), we can use the iterative Davidson algorithm, where in each step the so-called vector needs to be formed . For the even-electron case, the coefficients of are
(37) | |||||
Since we require , it simply becomes
(38) |
with This shows that only needs to be constructed, whose computational cost is roughly half of that for constructing . Similarly, for odd-electron systems, we can find
(39) | |||||
(40) | |||||
Thus, it suffices to construct and , which reduces the computational cost for constructing and roughly by half.
In summary, the full can be recovered from the skeleton one by a ’time-reversal symmetrization’ in both even- and odd-electron cases. This is in a similar spirit to the construction of Fock matrix using the skeleton-matrix algorithm57, 58, 59. Expressions for in Eq. (34) immediately show that only half of the intermediate operators are necessary for constructing , which reduces the memory and computational cost for renormalized operators by half compared with an implementation without using time-reversal symmetry.
To use such reduction, we need to maintain the structure (1) for basis vectors of the subspace in Davidson algorithm. For the even-electron case, suppose the current subspace in Davidson algorithm is spanned by time-reversal invariant basis, then the representation of is a real matrix,
(41) |
Consequently, the eigenvectors of are real and the states are time-reversal invariant. It can be verified that the residual is also time-reversal invariant, so does the precondition residual as .
For the odd-electron case, suppose the current subspace is spanned by a Kramers paired basis, i.e., , then the representation of Hamiltonian has a quaternion structure (6). Diagonalizing it with a structure-preserving algorithm will produced Kramers paired eigenvectors . Similarly, one can show that the residuals also form a Kramers pair, . An important point for constructing new Kramers paired orthonormal basis is that if is already orthonormalized against , then will be automatically orthogonal to the basis vectors in , such that the pair can be added simultaneously. This property can be seen from
(42) | |||||
(43) |
and due to Kramers’ theorem. In this way, we can maintain the structure (1) for the basis vectors of the subspace in the Davidson diagonalization algorithm.
III.0.3 Decimation
Once the eigenvectors (18) of have been found in the direct product space , we need to perform decimation to obtain an optimized basis for or . This is done by diagonalizing the reduced density matrix or . In the sweep optimization of DMRG, (or ) is also a direct product space denoted by . It is formed by a direct product between the left environment and the left dot, referred as superblock. Simply diagonalizing the reduced density matrix will not yield a basis with the structure (1). We will show how to perform decimation in such space to produce time-reversal symmetry-adapted renormalized states.
For the even-electron subspace , we assume it is spanned by the following direct product basis
(44) |
with and . Here, represents the part of direct product basis which is already time-reversal invariant such as in Eq. (9). The pair and represent those parts which can be related by such as and . Suppose the reduced density matrix obtained from in is
(48) |
then that obtained from is
(52) |
The average is time-reversal invariant
(59) |
where , , and is real symmetric. However, simply diagonalizing it with a complex eigensolver will not produce time-reversal invariant basis function (1) due to the arbitrariness of the phase factor. To fix this problem, we can introduce a time-reversal invariant basis similar to Eq. (11),
(60) |
with being
(64) |
and transform into this basis, which leads to a real symmetric reduced density matrix
(68) |
where (or ) represents the real (or imaginary) part. Diagonalizing yields a set of real vectors in the time-reversal invariant basis, which can be back transformed to the original direct product basis (44) by
(78) |
with .
For the odd-electron subspace , we assume it is spanned by the following direct product basis
(79) |
which is already Kramers paired, see Eq. (9). The reduced density matrices are
(84) |
and the average has a quaternion structure
(89) |
Thus, diagonalizing it with a structural preserving algorithm47, 48, 49, 50, 51, 52, 53 will lead to a new set of Kramers paired renormalized states.
The above decimation procedure is quite general. We can even apply the decimation procedure for cases where is Kramers symmetry contaminated to produce a time-reversal symmetry-adapted basis. For instance, it can be applied to convert a Kramers symmetry contaminated selected configuration interaction wavefunctions to time-reversal symmetry-adapted MPS as the initial guess for R-DMRG46. Then, by iterating the above diagonalization and decimation procedure, the time-reversal symmetry structure of basis functions (1) can be maintained recursively during the sweep optimization in DMRG. For other tensor network states without loops41, 42, 43, 44, 45, 46, it is clear that the construction of time-reversal symmetry-adapted basis can be directly applied.
IV Conclusion
In this work, we propose the time-reversal symmetry adaption for R-DMRG by introducing a time-reversal symmetry-adapted basis (1) and strategies to maintaining this structure during the sweep optimization in DMRG. It overcomes the artificial symmetry breaking in conventional R-DMRG calculations and leads to a reduction of memory and computational cost. The construction of time-reversal symmetry-adapted basis also directly applies to other tensor network states without loops. This opens up new possibilities of applying R-DMRG for complex heavy-element compounds. Applications of the introduced time-reversal symmetry-adapted R-DMRG will be reported in due time.
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grants No. 21973003) and the Beijing Normal University Startup Package.
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