Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model

• URL: http://arxiv.org/abs/2408.12641v1
• Date: Thu, 22 Aug 2024 18:00:00 GMT
• Title: Surrogate Constructed Scalable Circuits ADAPT-VQE in the Schwinger model
• Authors: Erik Gustafson, Kyle Sherbert, Adrien Florio, Karunya Shirali, Yanzhu Chen, Henry Lamm, Semeon Valgushev, Andreas Weichselbaum, Sophia E. Economou, Robert D. Pisarski, Norm M. Tubman,
• Abstract summary: We develop a new approach, (SC)$2$-ADAPT-VQE, to further advance the simulation of periodic systems on quantum computers. Our approach builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable Surrogate Constructed'' method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Inspired by recent advancements of simulating periodic systems on quantum computers, we develop a new approach, (SC)$^2$-ADAPT-VQE, to further advance the simulation of these systems. Our approach extends the scalable circuits ADAPT-VQE framework, which builds an ansatz from a pool of coordinate-invariant operators defined for arbitrarily large, though not arbitrarily small, volumes. Our method uses a classically tractable ``Surrogate Constructed'' method to remove irrelevant operators from the pool, reducing the minimum size for which the scalable circuits are defined. Bringing together the scalable circuits and the surrogate constructed approaches forms the core of the (SC)$^2$ methodology. Our approach allows for a wider set of classical computations, on small volumes, which can be used for a more robust extrapolation protocol. While developed in the context of lattice models, the surrogate construction portion is applicable to a wide variety of problems where information about the relative importance of operators in the pool is available. As an example, we use it to compute properties of the Schwinger model - quantum electrodynamics for a single, massive fermion in $1+1$ dimensions - and show that our method can be used to accurately extrapolate to the continuum limit.

Related papers

• Scalable approach to monitored quantum dynamics and entanglement phase transitions [0.0]
  Measurement-induced entanglement phase transitions in monitored quantum circuits have stimulated activity in a diverse research community. We present a solution by introducing a scalable protocol in $U(1)$ symmetric circuits.
  arXiv  Detail & Related papers  (2024-06-27T09:59:58Z)
• Measurement-Based Quantum Approximate Optimization [0.24861619769660645]
  We focus on measurement-based quantum computing protocols for approximate optimization. We derive measurement patterns for applying QAOA to the broad and important class of QUBO problems. We discuss the resource requirements and tradeoffs of our approach to that of more traditional quantum circuits.
  arXiv  Detail & Related papers  (2024-03-18T06:59:23Z)
• Energy-Guided Continuous Entropic Barycenter Estimation for General Costs [95.33926437521046]
  We propose a novel algorithm for approximating the continuous Entropic OT (EOT) barycenter for arbitrary OT cost functions. Our approach is built upon the dual reformulation of the EOT problem based on weak OT.
  arXiv  Detail & Related papers  (2023-10-02T11:24:36Z)
• Adaptive Planning Search Algorithm for Analog Circuit Verification [53.97809573610992]
  We propose a machine learning (ML) approach, which uses less simulations. We show that the proposed approach is able to provide OCCs closer to the specifications for all circuits.
  arXiv  Detail & Related papers  (2023-06-23T12:57:46Z)
• Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection [88.23337313766353]
  This work first provides a comprehensive statistical theory for transformers to perform ICL. We show that transformers can implement a broad class of standard machine learning algorithms in context. A emphsingle transformer can adaptively select different base ICL algorithms.
  arXiv  Detail & Related papers  (2023-06-07T17:59:31Z)
• Robust nonadiabatic geometric quantum computation by dynamical correction [0.0]
  We propose a robust scheme for nonadiabatic geometric quantum computation (NGQC) combining with the dynamical correction technique. We numerically show that our scheme can greatly improve the gate robustness in previous protocols. Our scheme provides a promising alternation for the future scalable fault-tolerant quantum computation.
  arXiv  Detail & Related papers  (2022-08-02T14:09:48Z)
• Deep Equilibrium Optical Flow Estimation [80.80992684796566]
  Recent state-of-the-art (SOTA) optical flow models use finite-step recurrent update operations to emulate traditional algorithms. These RNNs impose large computation and memory overheads, and are not directly trained to model such stable estimation. We propose deep equilibrium (DEQ) flow estimators, an approach that directly solves for the flow as the infinite-level fixed point of an implicit layer.
  arXiv  Detail & Related papers  (2022-04-18T17:53:44Z)
• Adiabatic Quantum Computing for Multi Object Tracking [170.8716555363907]
  Multi-Object Tracking (MOT) is most often approached in the tracking-by-detection paradigm, where object detections are associated through time. As these optimization problems are often NP-hard, they can only be solved exactly for small instances on current hardware. We show that our approach is competitive compared with state-of-the-art optimization-based approaches, even when using of-the-shelf integer programming solvers.
  arXiv  Detail & Related papers  (2022-02-17T18:59:20Z)
• Unraveling correlated material properties with noisy quantum computers: Natural orbitalized variational quantum eigensolving of extended impurity models within a slave-boson approach [0.0]
  We propose a method for computing space-resolved correlation properties of the two-dimensional Hubbard model within a quantum-classical embedding strategy. We solve a two-impurity embedded model requiring eight qubits with an advanced hybrid scheme on top of the Variational Quantum Eigensolver algorithm. This paves the way to a controlled solution of the Hubbard model with larger and larger embedded problems solved by quantum computers.
  arXiv  Detail & Related papers  (2021-08-24T14:58:14Z)
• Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation [101.22379613810881]
  We consider data-driven optimization problems where one must maximize a function given only queries at a fixed set of points. This problem setting emerges in many domains where function evaluation is a complex and expensive process. We propose a tractable approximation that allows us to scale our method to high-capacity neural network models.
  arXiv  Detail & Related papers  (2021-02-16T06:04:27Z)
• Mutual information-assisted Adaptive Variational Quantum Eigensolver [2.565371913657446]
  We propose a way to construct entangler pools with reduced size by leveraging classical algorithms. Our method uses mutual information between the qubits in classically approximated ground state to rank and screen the entanglers. Our numerical experiments show that a reduced entangler pool with a small portion of the original entangler pool can achieve same numerical accuracy.
  arXiv  Detail & Related papers  (2020-08-17T18:01:11Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.