In this paper, we present a framework for the recursion method applied within the Liouvillian formalism, enabling the computation of response functions for a wide range of quantum operators. Indeed, unlike most previous literature on the Liouvillian recursion method, this framework readily computes electronic Green's function. We demonstrate the method by showcasing its application to a temperature dependence study of a $2\times2$ Hubbard model. Our results show that the recursion method accurately computes response functions and provides valuable insights into quantum many-body systems. While the method has already been successfully applied to study of condensed matter, further efforts are required to develop efficient algorithms for larger and more realistic systems. Tensor network methods and other variational techniques hold promise for tackling these challenges. Overall, the recursion method offers a flexible approach for investigating strongly correlated system.
In this paper, we present a framework for the recursion method applied within the Liouvillian formalism, enabling the computation of response functions for a wide range of quantum operators. Indeed, unlike most previous literature on the Liouvillian recursion method, this framework readily computes electronic Green's function. We demonstrate the method by showcasing its application to a temperature dependence study of a 2×2 Hubbard model. Our results show that the recursion method accurately computes response functions and provides valuable insights into quantum many-body systems. While the method has already been successfully applied to study of condensed matter, further efforts are required to develop efficient algorithms for larger and more realistic systems. Tensor network methods and other variational techniques hold promise for tackling these challenges. Overall, the recursion method offers a flexible approach for investigating strongly correlated system.
The Green's function method has applications in several fields in Physics, from classical differential equations to quantum many-body problems. In the quantum context, Green's functions are correlation functions, from which it is possible to extract information from the system under study, such as the density of states, relaxation times and response functions. Despite its power and versatility, it is known as a laborious and sometimes cumbersome method. Here we introduce the equilibrium Green's functions and the equation-of-motion technique, exemplifying the method in discrete lattices of non-interacting electrons. We start with simple models, such as the two-site molecule, the infinite and semi-infinite one-dimensional chains, and the two-dimensional ladder. Numerical implementations are developed via the recursive Green's function, implemented in Julia, an open-source, efficient and easy-to-learn scientific language. We also present a new variation of the surface recursive Green's function method, which can be of interest when simulating simultaneously the properties of surface and bulk.
The Green's function method has applications in several fields in Physics, from classical differential equations to quantum many-body problems. In the quantum context, Green's functions are correlation functions, from which it is possible to extract information from the system under study, such as the density of states, relaxation times and response functions. Despite its power and versatility, it is known as a laborious and sometimes cumbersome method. Here we introduce the equilibrium Green's functions and the equation-of-motion technique, exemplifying the method in discrete lattices of non-interacting electrons. We start with simple models, such as the two-site molecule, the infinite and semi-infinite one-dimensional chains, and the two-dimensional ladder. Numerical implementations are developed via the recursive Green's function, implemented in Julia, an open-source, efficient and easy-to-learn scientific language. We also present a new variation of the surface recursive Green's function method, which can be of interest when simulating simultaneously the properties of surface and bulk.
We present a quantum-classical hybrid implementation of the Liouvillian recursion method to compute many-body Green's functions using a quantum computer. From an approximate ground state preparation circuit, this algorithm produces the local (r=r′) and inter-site (r=r′) Green's functions Grr′(ω) by measuring observables generated recursively. We demonstrate the approach on a superconducting quantum processor for the open-boundary four-site Hubbard model. We then use the computed Green's functions as input to the Galitskii-Migdal formula to produce better ground state energy estimation than the expectation value of the Hamiltonian for the approximate circuit. Empirical results indicate exponential convergence in the number of iterations, yielding a computational complexity polynomial in the Green's-function accuracy, as measured with the Wasserstein distance. Our results also indicate significant robustness to noise and to inaccuracies of the ground state preparation, providing evidence that Liouvillian recursion is well adapted to the constraints of near-term quantum computing.
Description of electron correlation is crucial to chemical accuracy in quantum chemical calculations. However, the interaction of electrons in a system is an insoluble many-body problem. Constructing approximations to describe electron correlation is a challenging task, but there has been success in the quantum chemistry community using wavefunction methods and density functional theory. However, there are still challenges to be overcome in areas such as theoretical solid state chemistry, which requires description of large systems and the use of finite temperature. Large system sizes and finite temperature can be difficult to treat solely with the currently available methods. Therefore, a new class of methods, based on the temperature-dependent Green's function, is implemented and explored. This thesis is toward investigating the use of temperature-dependent Green's functions for ab-initio quantum chemistry. That is, we are treating a quantum chemical Hamiltonian with realistic electron interactions. While this formalism has been applied to model systems in the condensed matter community, its has been used much less by the quantum chemistry community. Therefore, the numerical behavior and accuracy of Green's function methods for quantum chemical calculations is relatively unknown. This work investigates the ability of the temperature-dependent Green's function, which is an ensemble formalism, to give access to temperature dependent thermodynamic quantities such as free energy and entropy when calculated in a second-order and perturbative manner (GF2). We find that this method is able to give good accuracy for lower temperatures and excellent accuracy for higher temperatures for a molecular case and is able to qualitatively describe a simple model of a solid. The results of this work are presented in chapter 3. Although Green's functions have a clear connection with spectra at zero temperature, it is not straight forward to obtain spectra from the finite temperature Green's function, which is calculated on the imaginary frequency axis. Therefore, we must investigate methods to obtain spectral quantities in a consistent and reliable manner from the imaginary axis. Chapter 4 investigates several methods to do so and we compare our results with experimental and highly accurate benchmark data. We find that it is possible to obtain spectral quantities that can differ by several electron volts, even if the same level of theory is used to obtain the Green's function. This reiterates that finding a spectrum from the imaginary axis is nontrivial and that one must exercise caution when comparing spectral quantities that were calculated using different techniques, even if they are treated with the same theoretical accuracy. Accessing larger systems with the Green's function requires the use of quantum embedding. Quantum embedding describes nontrivial electron interaction between a highly accurate ``active space'' or ``impurity'' and a larger, lower level ``environment''. It is challenging to construct an impurity solver that is reliable at low temperatures. In chapter 5 of this work, we implement and test a temperature dependent configuration interaction impurity solver for quantum embedding. This solver can be used in quantum embedding schemes such as dynamical mean field theory and self-energy embedding theory for larger systems. Overall, this thesis has made progress toward using Green's functions for ab-initio quantum chemistry at finite temperature. Groundwork has been laid for using this formalism to calculate thermodynamics and spectra using a Green's function with realistic electron interactions and to explore quantum embedding using an impurity solver at low temperatures.
Recent progress in materials synthesis combined with advances in computational science have opened up an opportunity to design new materials with specific properties. Semiconductors, heterostructures, and thin layered films are used for energy harvesting and solar cells. Transition metal oxides and metallic surfaces with deposited magnetic molecules are used for signal conversion, nonvolatile memory modules and spintronics. Due to growing complexity of the new materials the most efficient approach to their design requires combined experimental and theoretical effort. In order to advance our understanding of the complicated physics of the modern materials new theoretical methods based on controlled, reliable, computationally efficient and systematically improvable approximations describing correlation and finite-temperature effects are needed. Density functional theory (DFT) remains a method of choice for materials science calculations due to its low computational cost. However, despite all recent efforts, the majority DFT applications are limited to weakly correlated systems and zero temperature. The lack of systematic improvability, inaccurate treatment of strongly correlated systems will continue to restrict the domain of DFT applications. The multi-reference wave-function methods can provide an accurate description of the strongly correlated systems. Unfortunately, these methods are computationally expensive. In spite of recent improvement the computational complexity will likely to hinder the applications of wave-function based methods to materials science in foreseeable future. Finite-temperature Green's function methods offer several advantages such as systematic improvability, access to the excitation spectrum, thermodynamic properties and straightforward implementation of embedding frameworks. It has been realized long time ago and has been successfully used in condensed matter physics to study model systems. The applications of such methods to realistic systems are impeded due to lack of theoretical approaches providing chemical accuracy and efficient computational algorithms. In this dissertation, these shortcomings are addressed by developing self-energy embedding theory and its extensive comparison to established quantum chemistry methods. New numerical algorithms for efficient application of the finite-temperature Green's function methods to molecular and extended systems were developed. Properties of the second-order Green's function theory (GF2) in the context of quantum chemistry were investigated. Additionally, a new range-separated hybrid functional combining GF2 and DFT was developed and benchmarked.
Computation of the Green's function is crucial to study the properties of quantum many-body systems such as strongly correlated systems. Although the high-precision calculation of the Green's function is a notoriously challenging task on classical computers, the development of quantum computers may enable us to compute the Green's function with high accuracy even for classically-intractable large-scale systems. Here, we propose an efficient method to compute the real-time Green's function based on the local variational quantum compilation (LVQC) algorithm, which simulates the time evolution of a large-scale quantum system using a low-depth quantum circuit constructed through optimization on a smaller-size subsystem. Our method requires shallow quantum circuits to calculate the Green's function and can be utilized on both near-term noisy intermediate-scale and long-term fault-tolerant quantum computers depending on the computational resources we have. We perform a numerical simulation of the Green's function for the one- and two-dimensional Fermi-Hubbard model up to $4\ifmmode\times\else\texttimes\fi{}4$ sites lattice (32 qubits) and demonstrate the validity of our protocol compared to a standard method based on the Trotter decomposition. We finally present a detailed estimation of the gate count for the large-scale Fermi-Hubbard model, which also illustrates the advantage of our method over the Trotter decomposition.