Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session A01: Towards Discovery in Chemistry with Quantum Computers IFocus Recordings Available
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Sponsoring Units: DCP Chair: Bert de Jong, LBNL Room: McCormick Place W-175A |
Monday, March 14, 2022 8:00AM - 8:36AM |
A01.00001: The real cost of chemical simulation on quantum computers Invited Speaker: Nicholas C Rubin How long will it take future quantum computers to calculate energies of challenging molecular systems? We dissect this question through analysis of asymptotic bounds on quantum algorithms for Hamiltonian simulation, analysis of realistic systems, and describe a full cost estimation and run time analysis based on physical error rates within the surface code. We highlight how techniques from classical simulation of chemistry reduce resource costs by orders of magnitude to demonstrate the potential of discovery at the interface between molecular simulation science and quantum information. |
Monday, March 14, 2022 8:36AM - 8:48AM |
A01.00002: Making Small Quantum Computers do Big Things with the Quantum Many Body Expansion Katherine Klymko, Wayne Mullinax, Andres Montoya Castillo, Wibe A de Jong, Norm M Tubman We investigate the use of a quantum many body expansion method (qMBE) for use on quantum computers. qMBE is based on the classical many-body FCI method with generalizations that allow for efficient usage on quantum computers. In particular, we generalize the objects with respect to which the many-body expansion is performed. Whereas previous methods switched from electrons to (occupied and/or virtual) orbitals and (in more recent implementations) clusters of many-body states, here our generalization consists of using groups rather than individual orbitals as the fundamental expansion object, needing fewer calculations and in some cases leading to faster convergence. qMBE allows complicated molecular systems to be decomposed into smaller, manageable pieces, distributing the effort over near-term resources. We demonstrate our algorithm on a selection of molecular examples. |
Monday, March 14, 2022 8:48AM - 9:00AM |
A01.00003: Quantum Subspace Methods for Quantum chemistry Yu Zhang The Variational Quantum Eigensolver (VQE) is a method of choice to solve the electronic structure problem for molecules on near-term gate-based quantum computers. However, the circuit depth is expected to grow significantly with problem size. Increased depth can both degrade the accuracy of the results and reduce trainability due to the noises. Besides, near-term quantum devices have a limited number of qubits. This work proposes a novel approach to reduce ansatz circuit depth and the number of qubits by mutual-information-based permutation of qubits and iterative folding of ansatz into an effective Hamiltonian. This breaks the original VQE algorithm into a series of VQE simulations with shallower circuit depth and fewer qubits. Besides, to calculate excited states properties of molecules, we developed an efficient quantum Krylov subspace algorithm by leveraging the iterative growth of Krylov subspace. Such subspace methods remove the optimization problems suffered in the VQE-type of methods. The newly proposed quantum Krylov subspace algorithm is employed to study the excited-state properties of various systems on both simulators and quantum devices. The complexity of the quantum Krylov subspace method is also analyzed. We believe the newly developed quantum Krylov subspace algorithm provides a feasible tool for studying excited-state phenomena on quantum computers. |
Monday, March 14, 2022 9:00AM - 9:36AM |
A01.00004: Towards discovery in chemistry with quantum computers Invited Speaker: Sophia Economou Chemistry is one of the most interesting applications of quantum computers and a candidate for the first demonstration of a useful quantum advantage. Near term algorithms, including variational quantum eigensolvers, constitute a promising path toward that goal. I will give an overview of the elements that enter such algorithms and focus on state preparation, highlighting our work on problem-tailored ansatze. These include dynamical, adaptive, and symmetry-respecting ansatze. |
Monday, March 14, 2022 9:36AM - 9:48AM |
A01.00005: The role of symmetries in the ADAPT variational quantum eigensolver Luke W Bertels, Harper R Grimsley, Sophia E Economou, Edwin Barnes, Nicholas Mayhall Variational quantum eigensolvers (VQEs) are a class of hybrid classical-quantum computing methods which prepare and measure a parameterized state on quantum hardware and optimize the wavefunction parameters on classical hardware. While many VQEs begin with a predetermined wavefunction ansatz, ADAPT-VQE builds a problem-tailored ansatz starting from a reference state and adaptively adding operators to the ansatz from a pool of operators. This flexibility to choose shorter circuits is preferable in the current noisy intermediate-scale quantum regime of quantum computing for simulating molecular systems as it can lead to shorter circuits to initialize a state on the quantum device. In this work we investigate the role of different symmetries when constructing a reference and operator pool play in the convergence behavior of ADAPT-VQE. |
Monday, March 14, 2022 9:48AM - 10:00AM |
A01.00006: Details of Classical Optimization in ADAPT-VQE Harper R Grimsley, Edwin Barnes, Sophia Economou, Nicholas Mayhall Variational quantum eigensolvers (VQEs) have come to represent a diverse and powerful family of methods for computing chemical energies, where measurements of a quantum circuit are paired with classical parameter optimization to variationally minimize a cost function. Our team has recently introduced the concept of a dynamical ansatz in VQE (which we call ADAPT-VQE), which grows a unique circuit for each problem with the goal of minimizing the circuit depth. While ADAPT-VQE has been very successful at decreasing the circuit depth, the problem of classical parameter optimization persists. In general, VQEs appear to suffer from certain numerical difficulties during parameter optimization, such as exponential suppression of the gradient (barren plateaus) and large numbers of local minima. In this work, we discuss numerical problems in the context of ADAPT-VQE and how to modify the algorithm to avoid them. |
Monday, March 14, 2022 10:00AM - 10:36AM |
A01.00007: Emerging hybrid quantum-classical algorithms for quantum chemistry Invited Speaker: Mario Motta Digital quantum computers provide a computational framework for solving the Schrodinger equation for a variety of many-particle systems. |
Monday, March 14, 2022 10:36AM - 10:48AM |
A01.00008: Quantum Chemistry with Near-Clifford Circuits Philipp Schleich, Abhinav Anand, Joseph Boen, Lukasz Cincio, Jakob Kottmann, Pavel A Dub, Alan Aspuru-Guzik The variational quantum eigensolver is a near-term quantum algorithm for solving molecular electronic structure problems on quantum devices. However, current hardware is restricted by the availability of only few, noisy qubits. This limits the investigation of larger, more complex molecules. In this work, we investigate how far we can go with classical or close-to-classical treatment while staying within the framework of quantum circuits. To this end, we consider both a naive and a physically motivated product ansatz for the parametrized wavefunction in form of the separable pair ansatz, which is classically efficient; this is combined with classical post-treatment to account for interactions between subsystems originating from this ansatz. The classical treatment is given by another quantum circuit that has support between the enforced subsystems and is folded into the Hamiltonian. To avoid an exponential increase in the number of Hamiltonian terms, the entangling operations are constructed from purely Clifford or near-Clifford circuits. While purely Clifford circuits can be simulated efficiently classically, they are not universal; in order to account for the thus missing expressibility, near-Clifford circuits with only few, selected non-Clifford gates are employed. The exact circuit structure to do so is molecule-dependent and is constructed using simulated annealing and genetic algorithms. We demonstrate our approach on a set of molecules of interest and explore how far the methodology reaches. Empirical validation of our approach using numerical simulations shows up to a 50% qubit reduction for some molecules. |
Monday, March 14, 2022 10:48AM - 11:00AM |
A01.00009: Polynomial Depth Quantum Circuits for Time Evolution of Heisenberg Models Using the Yang-Baxter Equation Sahil Gulania, Bo Peng, Yuri Alexeev, Niranjan Govind Quantum time dynamics (QTD) is considered a promising problem to solve on near-term quantum computers. However, quantum circuits for QTD grow with increasing time simulation. This study focuses on simulating the time dynamics of 1-D integrable spin chains with nearest-neighbor interactions. We show how the Yang-Baxter equation can be exploited to compress a quantum circuit. With this compression scheme, the depth of the quantum circuit becomes independent of step size and only depends on the number of spins. The compressed circuit scales quadratically with system size, which allows for the simulations of time dynamics of very large 1-D spin chains. In addition, each time step of the simulation can run independently in parallel. We show the implementation of this scheme on an IBM quantum device and demonstrate the impact of our compression scheme on the fidelity of calculations. |
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