Digitized-Counterdiabatic Quantum Optimization

• URL: http://arxiv.org/abs/2201.00790v1
• Date: Mon, 3 Jan 2022 18:21:54 GMT
• Title: Digitized-Counterdiabatic Quantum Optimization
• Authors: Narendra N. Hegade, Xi Chen, Enrique Solano
• Abstract summary: We propose digitized-diabatic quantum optimization (DCQO) to achieve enhancement over adiabatic quantum optimization for the general Ising spin-glass model. This is accomplished via the digitization of adiabatic quantum algorithms that are catalysed by the addition of non-stoquastic counterdiabatic terms.
• Score: 4.336065967298193
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We propose digitized-counterdiabatic quantum optimization (DCQO) to achieve polynomial enhancement over adiabatic quantum optimization for the general Ising spin-glass model, which includes the whole class of combinatorial optimization problems. This is accomplished via the digitization of adiabatic quantum algorithms that are catalysed by the addition of non-stoquastic counterdiabatic terms. The latter are suitably chosen, not only for escaping classical simulability, but also for speeding up the performance. Finding the ground state of a general Ising spin-glass Hamiltonian is used to illustrate that the inclusion of k-local non-stoquastic counterdiabatic terms can always outperform the traditional adiabatic quantum optimization with stoquastic Hamiltonians. In particular, we show that a polynomial enhancement in the ground-state success probability can be achieved for a finite-time evolution, even with the simplest 2-local counterdiabatic terms. Furthermore, the considered digitization process, within the gate-based quantum computing paradigm, provides the flexibility to introduce arbitrary non-stoquastic interactions. Along these lines, using our proposed paradigm on current NISQ computers, quantum speed-up may be reached to find approximate solutions for NP-complete and NP-hard optimization problems. We expect DCQO to become a fast-lane paradigm towards quantum advantage in the NISQ era.

Related papers

• Optimizing random local Hamiltonians by dissipation [44.99833362998488]
  We prove that a simplified quantum Gibbs sampling algorithm achieves a $Omega(frac1k)$-fraction approximation of the optimum. Our results suggest that finding low-energy states for sparsified (quasi)local spin and fermionic models is quantumly easy but classically nontrivial.
  arXiv  Detail & Related papers  (2024-11-04T20:21:16Z)
• Optimizing Unitary Coupled Cluster Wave Functions on Quantum Hardware: Error Bound and Resource-Efficient Optimizer [0.0]
  We study the projective quantum eigensolver (PQE) approach to optimizing unitary coupled cluster wave functions on quantum hardware. The algorithm uses projections of the Schr"odinger equation to efficiently bring the trial state closer to an eigenstate of the Hamiltonian. We present numerical evidence of superiority over both the optimization introduced in arXiv:2102.00345 and VQE optimized using the Broyden Fletcher Goldfarb Shanno (BFGS) method.
  arXiv  Detail & Related papers  (2024-10-19T15:03:59Z)
• Application of Langevin Dynamics to Advance the Quantum Natural Gradient Optimization Algorithm [47.47843839099175]
  A Quantum Natural Gradient (QNG) algorithm for optimization of variational quantum circuits has been proposed recently. In this study, we employ the Langevin equation with a QNG force to demonstrate that its discrete-time solution gives a generalized form, which we call Momentum-QNG.
  arXiv  Detail & Related papers  (2024-09-03T15:21:16Z)
• Bias-field digitized counterdiabatic quantum optimization [39.58317527488534]
  We call this protocol bias-field digitizeddiabatic quantum optimization (BF-DCQO) Our purely quantum approach eliminates the dependency on classical variational quantum algorithms. It achieves scaling improvements in ground state success probabilities, increasing by up to two orders of magnitude.
  arXiv  Detail & Related papers  (2024-05-22T18:11:42Z)
• Challenges of variational quantum optimization with measurement shot noise [0.0]
  We study the scaling of the quantum resources to reach a fixed success probability as the problem size increases. Our results suggest that hybrid quantum-classical algorithms should possibly avoid a brute force classical outer loop.
  arXiv  Detail & Related papers  (2023-07-31T18:01:15Z)
• A self-consistent field approach for the variational quantum eigensolver: orbital optimization goes adaptive [52.77024349608834]
  We present a self consistent field approach (SCF) within the Adaptive Derivative-Assembled Problem-Assembled Ansatz Variational Eigensolver (ADAPTVQE) This framework is used for efficient quantum simulations of chemical systems on nearterm quantum computers.
  arXiv  Detail & Related papers  (2022-12-21T23:15:17Z)
• Accelerated Convergence of Contracted Quantum Eigensolvers through a Quasi-Second-Order, Locally Parameterized Optimization [0.0]
  A contracted quantum eigensolver (CQE) finds a solution to the many-electron Schr"odinger equation on a quantum computer. In this work, we accelerate the convergence of the CQE and its wavefunction ansatz via tools from classical optimization theory.
  arXiv  Detail & Related papers  (2022-05-03T18:48:04Z)
• 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)
• Quantum algorithms for quantum dynamics: A performance study on the spin-boson model [68.8204255655161]
  Quantum algorithms for quantum dynamics simulations are traditionally based on implementing a Trotter-approximation of the time-evolution operator. variational quantum algorithms have become an indispensable alternative, enabling small-scale simulations on present-day hardware. We show that, despite providing a clear reduction of quantum gate cost, the variational method in its current implementation is unlikely to lead to a quantum advantage.
  arXiv  Detail & Related papers  (2021-08-09T18:00:05Z)
• Digitized-counterdiabatic quantum approximate optimization algorithm [3.0638256603183054]
  We propose a digitized version of QAOA enhanced via the use of shortcuts to adiabaticity. We apply our digitized-counterdiabatic QAOA to Ising models, classical optimization problems, and the P-spin model, demonstrating that it outperforms standard QAOA in all cases.
  arXiv  Detail & Related papers  (2021-07-06T17:57:32Z)
• Variational Quantum Optimization with Multi-Basis Encodings [62.72309460291971]
  We introduce a new variational quantum algorithm that benefits from two innovations: multi-basis graph complexity and nonlinear activation functions. Our results in increased optimization performance, two increase in effective landscapes and a reduction in measurement progress.
  arXiv  Detail & Related papers  (2021-06-24T20:16:02Z)

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.