Quantum Zeno Monte Carlo for computing observables

• URL: http://arxiv.org/abs/2403.02763v3
• Date: Thu, 9 May 2024 04:06:27 GMT
• Title: Quantum Zeno Monte Carlo for computing observables
• Authors: Mancheon Han, Hyowon Park, Sangkook Choi,
• Abstract summary: We introduce a new classical-quantum hybrid algorithm termed Quantum Zeno Monte Carlo (QZMC) QZMC is capable of handling noises and Trotter errors while demonstrating computational cost. Compared to quantum phase estimation, QZMC offers a significantly reduced quantum circuit depth.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The recent development of logical quantum processors signifies a pivotal moment in the progression from the noisy intermediate-scale quantum (NISQ) era to the fault-tolerant quantum computing (FTQC) era. These advanced devices are poised to alter the approach to problems that challenge classical computation methods. By transforming such problems into Hamiltonian frameworks and exploiting quantum mechanical properties, these processors have the potential to address complex issues within a polynomial computational time. However, despite their advancements, these processors remain vulnerable to disruptive noise, highlighting the need for robust quantum algorithms designed to manage noise effectively. In response to this need, we introduce a new classical-quantum hybrid algorithm termed Quantum Zeno Monte Carlo (QZMC). QZMC is capable of handling device noises and Trotter errors while demonstrating polynomial computational cost. This algorithm combines the quantum Zeno effect with Monte Carlo integration techniques, facilitating multi-step transitions toward targeted eigenstates of the Hamiltonian problem. Notably, QZMC does not require overlap between the initial state and the target state, nor does it depend on variational parameters. It can compute static and dynamic properties of the targeted states, including ground state energy, excited state energies, and Green's functions. Compared to quantum phase estimation, QZMC offers a significantly reduced quantum circuit depth. These features make QZMC an important algorithm for navigating the current transitional phase in quantum computing and beyond.

Related papers

• State-Averaged Orbital-Optimized VQE: A quantum algorithm for the democratic description of ground and excited electronic states [0.0]
  The SA-OO-VQE package aims to answer both problems with its hybrid quantum-classical conception based on a typical Variational Quantum Eigensolver approach. The SA-OO-VQE has the ability to treat degenerate (or quasi-degenerate) states on the same footing, thus avoiding known numerical optimization problems around avoided crossings or conical intersections.
  arXiv  Detail & Related papers  (2024-01-22T12:16:37Z)
• QuantumSEA: In-Time Sparse Exploration for Noise Adaptive Quantum Circuits [82.50620782471485]
  QuantumSEA is an in-time sparse exploration for noise-adaptive quantum circuits. It aims to achieve two key objectives: (1) implicit circuits capacity during training and (2) noise robustness. Our method establishes state-of-the-art results with only half the number of quantum gates and 2x time saving of circuit executions.
  arXiv  Detail & Related papers  (2024-01-10T22:33:00Z)
• Fighting noise with noise: a stochastic projective quantum eigensolver [0.0]
  We present a novel approach to estimating physical observables which leads to a two order of magnitude reduction in the required sampling of the quantum state. The method can be applied to excited-state calculations and simulation for general chemistry on quantum devices.
  arXiv  Detail & Related papers  (2023-06-26T09:22:06Z)
• Synergy Between Quantum Circuits and Tensor Networks: Short-cutting the Race to Practical Quantum Advantage [43.3054117987806]
  We introduce a scalable procedure for harnessing classical computing resources to provide pre-optimized initializations for quantum circuits. We show this method significantly improves the trainability and performance of PQCs on a variety of problems. By demonstrating a means of boosting limited quantum resources using classical computers, our approach illustrates the promise of this synergy between quantum and quantum-inspired models in quantum computing.
  arXiv  Detail & Related papers  (2022-08-29T15:24:03Z)
• Simulating the Mott transition on a noisy digital quantum computer via Cartan-based fast-forwarding circuits [62.73367618671969]
  Dynamical mean-field theory (DMFT) maps the local Green's function of the Hubbard model to that of the Anderson impurity model. Quantum and hybrid quantum-classical algorithms have been proposed to efficiently solve impurity models. This work presents the first computation of the Mott phase transition using noisy digital quantum hardware.
  arXiv  Detail & Related papers  (2021-12-10T17:32:15Z)
• State preparation and evolution in quantum computing: a perspective from Hamiltonian moments [5.774827369850958]
  Recent efforts highlight the development of quantum algorithms based upon quantum computed Hamiltonian moments. This tutorial review focuses on the typical ways of computing Hamiltonian moments using quantum hardware and improving the accuracy of the estimated state energies.
  arXiv  Detail & Related papers  (2021-09-27T04:24:19Z)
• 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)
• An Algebraic Quantum Circuit Compression Algorithm for Hamiltonian Simulation [55.41644538483948]
  Current generation noisy intermediate-scale quantum (NISQ) computers are severely limited in chip size and error rates. We derive localized circuit transformations to efficiently compress quantum circuits for simulation of certain spin Hamiltonians known as free fermions. The proposed numerical circuit compression algorithm behaves backward stable and scales cubically in the number of spins enabling circuit synthesis beyond $mathcalO(103)$ spins.
  arXiv  Detail & Related papers  (2021-08-06T19:38:03Z)
• Towards a NISQ Algorithm to Simulate Hermitian Matrix Exponentiation [0.0]
  A practical fault-tolerant quantum computer is worth looking forward to as it provides applications that outperform their known classical counterparts. It would take decades to make it happen, exploiting the power of noisy intermediate-scale quantum(NISQ) devices, which already exist, is becoming one of current goals. In this article, a method is reported as simulating a hermitian matrix exponentiation using parametrized quantum circuit.
  arXiv  Detail & Related papers  (2021-05-28T06:37:12Z)
• Error mitigation and quantum-assisted simulation in the error corrected regime [77.34726150561087]
  A standard approach to quantum computing is based on the idea of promoting a classically simulable and fault-tolerant set of operations. We show how the addition of noisy magic resources allows one to boost classical quasiprobability simulations of a quantum circuit.
  arXiv  Detail & Related papers  (2021-03-12T20:58:41Z)
• Minimizing estimation runtime on noisy quantum computers [0.0]
  "engineered likelihood function" (ELF) is used for carrying out Bayesian inference. We show how the ELF formalism enhances the rate of information gain in sampling as the physical hardware transitions from the regime of noisy quantum computers. This technique speeds up a central component of many quantum algorithms, with applications including chemistry, materials, finance, and beyond.
  arXiv  Detail & Related papers  (2020-06-16T17:46:18Z)

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.