Bulletin of the American Physical Society
APS March Meeting 2023
Volume 68, Number 3
Las Vegas, Nevada (March 5-10)
Virtual (March 20-22); Time Zone: Pacific Time
Session EE04: V: Variational Quantum Algorithms and Adiabatic Quantum Computing |
Hide Abstracts |
Sponsoring Units: DQI Chair: Oles Shtanko, IBM Quantum Room: Virtual Room 4 |
Monday, March 20, 2023 10:00AM - 10:12AM |
EE04.00001: Absence of barren plateaus and scaling of energy gradients in the optimization of isometric tensor network states Qiang Miao, Thomas Barthel Barren plateaus can pose substantial obstacles for high-dimensional optimization problems. Here we consider optimization problems for quantum many-body systems which can be studied on classical computers or in the form of variational quantum eigensolvers on quantum computers. Barren plateaus correspond to scenarios where the average amplitude of the cost function gradient decreases exponentially with increasing system size. This occurs, for example, for quantum neural networks. Here we show that variational optimization problems for matrix product states, tree tensor networks, and the multiscale entanglement renormalization ansatz are free of barren plateaus. The derived scaling properties for the average gradient variance provide an analytical guarantee for the trainability of randomly initialized tensor network states (TNS). In a suitable representation, unitary tensors that parametrize the TNS are sampled according to the uniform Haar measure. In contrast to other works, we employ a Riemannian formulation of the gradient based optimizations which makes the analytical evaluation rather simple and may be useful in other contexts. |
Monday, March 20, 2023 10:12AM - 10:24AM |
EE04.00002: Estimation of Ground State Energy of Small Molecules and Energy Profile of CO_{2} interaction with NH_{3} using the Variational Quantum Eigensolver Dominic Alfonso, Manh Tien Nguyen, Yueh-Lin Lee, Benjamin Avramidis, Hari P Paudel, Yuhua Duan We benchmark the Variational Quantum Eigensolver (VQE) for computing the ground state energy of small molecules and the reaction profile of CO_{2} interaction with NH_{3}. The Phyton-based Qiskit software package was implemented on the National Energy Technology Laboratory (NETL) Joule 2 supercomputer for the energetic calculations. With the minimal STO-3G basis set, we were able to push our hardware to use to up to 16 qubits on a quantum simulator. While it is possible to simulate H_{2}, LiH, BeH_{2}, H_{2}O and NH_{3} with the all-electron approach, the frozen-core approximation has to be used for the bigger CO, CH_{4}, F_{2} and HCl molecules in order to stay in the limit of 16 qubits. All the VQE predicted ground state energies compare well with the full-configuration interaction (FCI) reference values though generally not close to chemical accuracy. We benchmark the VQE-based Hartree Fock-Embedding algorithm to quantify the energy profile of CO_{2} + NH_{3} = NH_{2}COOH conversion, a simple CO_{2} capture reaction system. The embedding technique allows substantial reduction of classical resources, allowing this more challenging case to be done on classical quantum simulator. The generated reaction profile is found to be in good agreement with the classical high-level CCSD results. We also calculate the vibrational ground state energies of reactants and products along the CO_{2 }capture reaction pathway using VQE-based technique. The quantum computing algorithm helps enhance the calculation of vibrational ground state energy by considering the many-body vibrational coupling or anharmonicity effect. We describe the many-body potential energy with the expansion to the fourth order using Vibrational Self-Consistent Field method. We demonstrate that the quantum computed ground state energies have similar accuracy for CO_{2} and NH_{3 }molecules compared to classical computed results using the traditional diagonalization method. |
Monday, March 20, 2023 10:24AM - 10:36AM |
EE04.00003: An intrinsic reaction coordinate (IRC) driven VQE algorithm (IRC-VQE) to trace chemical reaction pathways accurately Shampa Sarkar, M R Nirmal, Manoj Nambiar, Sriram G Srinivasan The intrinsic reaction coordinate (IRC) of a molecule is defined as the minimum energy reaction pathway (MERP) on the BOPES in mass-weighted cartesian coordinates between the transition state of a reaction and its reactants and products. We report here an IRC-driven variational quantum eigensolver (IRC-VQE) algorithm to trace accurately chemical reaction pathways as a function of molecular bond stretching, bending or torsional degrees of freedom, where we estimate the ground state energy using VQE and trace the pathway in two different modes, viz., a perturbative-distortion based approach for traversing points along the IRC path, or a finite-difference based geometry optimization in eigenmode basis. We have applied IRC-VQE to simulate the umbrella inversion phenomenon of ammonia (NH_{3}) as a function of N-H bond stretching, which could resolve the tiny 8 mH barrier height between the planar (D_{3h}) and pyramidal (C_{3v}) configurations of NH_{3}. In another example, the experimentally observed tiny rotational energy barrier of 12 kJ/mol between staggered and eclipsed conformers of ethane (C_{2}H_{6}) has been traced accurately as a function of H-C-C-H torsional angle chosen as IRC. In future, we plan to improve the scalability of this framework to handle molecules of larger size and higher degrees of freedom. The incorporation of finite-difference based energy gradient could help the classical nonlinear optimizers to trace the reaction paths more accurately than force-field based methods which are approximate. |
Monday, March 20, 2023 10:36AM - 10:48AM |
EE04.00004: Determining Ground State Energies of Molecules Using a Quantum Variational Eigensolver Renuka Rajapakse, Timothy Powers Key properties of physical systems can be described by the eigenvalues of matrices that represent the system. Computational algorithms that determine the eigenvalues of these matrices exist, but they generally suffer from a loss of performance as the matrix grows in size. This process can be expanded to quantum computation to find the eigenvalues with better performance than the classical algorithms. One application of such an eigenvalue solver is to determine energy levels of a molecule given a matrix representation of its Hamiltonian using the variational principle. Using a quantum variational eigensolver, we determine the ground state energies of different molecules. |
Monday, March 20, 2023 10:48AM - 11:00AM |
EE04.00005: Limitations of Local Quantum Algorithms for Random Optimization Juspreet Singh Sandhu, Jonathan Shi, Peter J Love, Chris Jones, Kunal Marwaha, Chi-Ning Chou In a body of growing work, it is becoming increasingly clear that local quantum algorithms such as the Quantum Approximate Optimization Algorithm (QAOA) do not provide any computational advantage over classical algorithms for a large family of optimization problems. The results in the literature often come in two flavors: |
Monday, March 20, 2023 11:00AM - 11:12AM |
EE04.00006: Efficient Adiabatic Preparation of Tensor Network States Zhi-Yuan Wei, Daniel Malz, J. Ignacio Cirac Tensor network states play a fundamental role both in quantum information processing and many-body physics. In this talk, we propose and study a specific adiabatic path to prepare a family of tensor network states that are unique ground states of few-body parent Hamiltonians in finite lattices, which include normal tensor network states, as well as other relevant non-normal states. This path guarantees a gap and allows for efficient numerical simulation. In 1D we numerically investigate the preparation of a family of states with varying correlation lengths and the 1D AKLT state and show that adiabatic preparation can be much faster than standard methods based on sequential preparation. We also apply the method to the 2D AKLT state on the hexagonal lattice for which no method based on sequential preparation is known, and show that it can be prepared very efficiently for relatively large lattices. arXiv:2209.01230 |
Monday, March 20, 2023 11:12AM - 11:24AM |
EE04.00007: Efficient quantum correlated optimization of industrial planning Daniel Porat Optimization of NP-hard problems is a promising application of near-term quantum computers. Unfortunately, in spite of the huge efforts invested in the field, so far, quantum computers have not been able to demonstrate a commercial value in the solution of optimization problems. We attribute this failure to the lack of suitable models of real-life problems that can efficiently be run on quantum computers. We state 4 conditions that are needed to satisfy this requirement and identify a model of industrial planning that satisfies them. Even for this model, available quantum algorithms are outperformed by classical methods such as greedy approaches and linear programming. We show that Quantymize's proprietary approach, ``quantum correlated optimization'', is capable of obtaining the best solution in a broad range of parameters. We benchmark this approach both on a quantum simulator and on a Dwave quantum annealer, demonstrating a favorable scaling as a function of the number of variables. Our work paves the way for the use of quantum computers to solve real-life, large-scale problems. |
Monday, March 20, 2023 11:24AM - 11:36AM |
EE04.00008: Chromatin domains with quantum annealing Tobias Kempe, Mohammad H Ansari, Ali S Tabei Chromatin Domain Formation has recently become a topic of interest in biophys research due to its high relevance in understanding positioning of epigenic marks. Computational methods provide promising opportunities in sampling from the statistical pattern observed in nature to better understand and predict those chromatin domains. Binary quadratic models are used to model the state of nucleosome chains and find minimum energy combinations that represent possible chromatin domains. Interestingly, exactly this type of problem can not only be solved classically, but also fits into Quantum Annealing formulations and their recent hardware implementations. We investigate the Chromatin Domain Formation problem with respect to such implementations and use publicly available QA devices (by the DWave company) to solve them. We lay specific focus on the feasibility and usefulness of this approach considering scaling of devices and compare it to classical alternatives. |
Monday, March 20, 2023 11:36AM - 11:48AM |
EE04.00009: Navigating the noise-depth tradeoff in adiabatic quantum circuits Daniel Azses, Maxime Dupont, Bram Evert, Matthew J Reagor, Emanuele G Dalla Torre Adiabatic quantum algorithms solve computational problems by slowly evolving a trivial state to the desired solution. On an ideal quantum computer, the solution quality improves monotonically with increasing circuit depth. By contrast, increasing the depth in current noisy computers introduces more noise and eventually deteriorates any computational advantage. What is the optimal circuit depth that provides the best solution? Here, we address this question by investigating an adiabatic circuit that interpolates between the paramagnetic and ferromagnetic ground states of the one-dimensional quantum Ising model. We characterize the quality of the final output by the density of defects d, as a function of the circuit depth N and noise strength σ. We find that d is well-described by the simple form d_{ideal} + d_{noise}, where the ideal case d_{ideal} ∼ N^{-1/2} is controlled by the Kibble-Zurek mechanism, and the noise contribution scales as d_{noise} ∼ Nσ^{2}. It follows that the optimal number of steps minimizing the number of defects goes as ∼ σ^{-4/3}. We implement this algorithm on a noisy superconducting quantum processor and find that the dependence of the density of defects on the circuit depth follows the predicted non-monotonous behavior and agrees well with noisy simulations. Our work allows one to efficiently benchmark quantum devices and extract their effective noise strength σ. |
Monday, March 20, 2023 11:48AM - 12:00PM |
EE04.00010: Quantum Locally Testable Code with Exotic Parameters Zhiyang He, Anand Natarajan, Andrew Cross, Guanyu Zhu, Mario Szegedy In this paper, we present a few simple constructions of quantum locally testable codes that achieve interesting parameters which were previously unknown. We introduce an operation which we give the name check product, and show how this operation gives rise to quantum locally testable codes of constant soundness and linear rate, with varying distance and locality. |
Follow Us |
Engage
Become an APS Member |
My APS
Renew Membership |
Information for |
About APSThe American Physical Society (APS) is a non-profit membership organization working to advance the knowledge of physics. |
© 2024 American Physical Society
| All rights reserved | Terms of Use
| Contact Us
Headquarters
1 Physics Ellipse, College Park, MD 20740-3844
(301) 209-3200
Editorial Office
100 Motor Pkwy, Suite 110, Hauppauge, NY 11788
(631) 591-4000
Office of Public Affairs
529 14th St NW, Suite 1050, Washington, D.C. 20045-2001
(202) 662-8700