Quantum Monte Carlo approaches for strongly correlated systems
The quantum many-body problem and Monte Carlo
Quantum Monte Carlo: sample properties without storing full wave functions
Exact simulations \(\rightarrow\) fermion sign problem (exponential decay of signal to noise ratio)
Lattice models:
Ab initio models:
Variational Monte Carlo
Stochastic multireference perturbation theory
Auxiliary field QMC
Outline
- Sampling and the sign problem in AFQMC
- Reducing noise using selected CI wave functions
- Benchmark results
- Jastrow symmetry projected states in VMC
- Auxiliary field QMC
- Variational MC
- Use in projection QMC
Projection QMC
- Free projection: try to manage sign problem, numerically exact and exponentially scaling
Noise in QMC sampling worsens exponentially with \(\tau\) and system size
Imaginary time propagation:
Two flavors:
- Constrained: use trial state to constrain projection, trial dependent bias but polynomially scaling
Sampling in Auxiliary Field QMC
- Exponentiating \(\hat{K}\):
- Exponentiating \(\hat{V}\): coupling to a scalar field
\(x_{\gamma}\): auxiliary field
(Thouless, 1960)
(Stratonovich, 1957)
Free projection:
Zhang, Krakauer, Reichman, Freisner, Rubenstein, ...
Phaseless:
CCSD as \(|\psi_r\rangle\) in free projection:
Benzene (30e, 102o)
The sign problem in free projection
Contour shift:
In AFQMC:
Baer, Head-Gordon, Neuhauser (1998)
Zero variance principle
If \(|\psi_l\rangle\) is the exact ground state, then \(N\) and \(D\) are perfectly correlated, \(\langle\psi_0|\hat{H}|\phi_i\rangle = E_0 \langle\psi_0|\phi_i\rangle\), and the energy estimator has zero variance. More accurate \(|\psi_l\rangle\ \rightarrow\ \) higher \(\text{Cov}(N, D)\).
Selected configuration interaction: put the most important configurations in the state using particle-hole excitations and diagonalize
Benzene (30e, 102o)
Selected CI local energy algorithm
Generalized Wick's theorem: consider \(|\psi_l\rangle = c_{ptqu}\hat{a}_t^{\dagger}\hat{a}_p\hat{a}_u^{\dagger}\hat{a}_q|\psi_0\rangle\)
Benzene (30e, 102o)
\([\text{Cu}_2\text{O}_2]^{2+}\) isomerization
\(\Delta E = E(\text{bis}) - E(\text{peroxo})\)
Method | |
DFT (UBLYP) | 36.0 |
DFT (UB3LYP) | 52.9 |
DFT (UMPW1K) | 74.0 |
CCSD(T) | 30.6 |
CR-CCSD(TQ) | 33.8 |
DMRG-CT | 27.1 |
ph-AFQMC (NOCI) | 32.1 |
fp-AFQMC | 24.1(6) |
kcal/mol
(32e, 108o)
\(\text{H}_{50}\) (50e, 50o)
Systematically improving phaseless AFQMC
Ni
Excited states in phaseless AFQMC
Butadiene: (22e, 142o)
Nickel porphyrin: (122e, 406o)
Method | ||
SC-NEVPT2 | 6.72 | 6.74 |
CCSD | 6.31 | 7.08 |
AFQMC | 6.46(5) | 6.67(5) |
TBE | 6.2 | 6.5 |
eV
Method | |
CASSCF (4e, 4o) | 3.8 |
CCSD | 2.55 |
AFQMC / sCI (50k) | 3.0(1) |
AFQMC / sCI (100k) | 2.8(1) |
Experiment | 2.3-2.4 |
eV
(4e, 8o) active space
Other properties
Species | Exact | CCSD | ph-AFQMC |
0.986 | 0.991 | 0.985(2) | |
0.990 | 0.992 | 0.986(2) | |
CO | 0.090 | 0.099 | 0.086(3) |
- Can be evaluated as derivatives of energy
- Derivatives can be calculated just as efficiently as energy (JAX implementation)
a.u.
Small molecule dipole moment calculations (6-31g basis):
NH\(_3\)
H\(_2\)O
Outline
- Sampling and the sign problem in AFQMC
- Reducing noise using selected CI wave functions
- Benchmark results
- Jastrow symmetry projected states in VMC
- Auxiliary field QMC
- Variational MC
- Use in projection QMC
Variational Monte Carlo (VMC)
Strategy:
- Parametrize the wave function: \(|\psi(\mathbf{p})\rangle\), choose initial \(\mathbf{p}\)
- Calculate energy and gradient: Markov chain Monte Carlo
- Optimize: smart gradient descent to change parameters
Ground state minimizes
McMillan (1965)
Symmetry projection in VMC
Symmetry breaking \(\rightarrow\) more variational freedom
Break the symmetry under a projector, to retain good quantum numbers
Projection in VMC by restricting random walk to the symmetry sector
Symmetries: spin, number, complex conjugation, ...
Example: complex conjugation in \(\text{H}_2\) near dissociation
Imada, Sorella, Neuscamman, ...
Jastrow factor
d (Bohr) | Exact (DMRG) | Jastrow-KSzPfaffian | Green's function MC |
1.6 | -0.5344 | -0.5337 | -0.5342 |
1.8 | -0.5408 | -0.5400 | -0.5406 |
2.5 | -0.5187 | -0.5180 | -0.5185 |
H\( _{50} \) linear chain (50e, 50o)
Hartree/particle
Correlates doublons and holons, can describe Mott insulating behavior
U | Benchmark energy | Jastrow- KSzGHF |
Green's function MC |
2 | -1.1962 | -1.1920 | -1.1939 |
4 | -0.8620 | -0.8566 | -0.8598 |
8 | -0.5237 | -0.5183 | -0.5221 |
2D Hubbard: 98 sites (half filling)
Density-density correlation function: 18 site 2D Hubbard model (\(U/t=4\))
Thank you!
afqmc_vmc_2
By Ankit Mahajan
afqmc_vmc_2
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