Extracting vacuum expectation values from approximate vacuum prepared by
the adiabatic quantum computation
- URL: http://arxiv.org/abs/2308.15066v1
- Date: Tue, 29 Aug 2023 06:59:24 GMT
- Title: Extracting vacuum expectation values from approximate vacuum prepared by
the adiabatic quantum computation
- Authors: Kazuto Oshima
- Abstract summary: We use plural ancilla bits with hierarchical structure, intending to gradually put up approximate precision.
We exhibit simulation results for a typical one-qubit system and a two-qubits system based on the (1+1)-dimensional Schwinger model using classically emulated digital quantum simulator.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We propose a procedure to extract vacuum expectation values from approximate
vacuum prepared by the adiabatic quantum computation. We use plural ancilla
bits with hierarchical structure, intending to gradually put up approximate
precision. We exhibit simulation results for a typical one-qubit system and a
two-qubits system based on the (1+1)-dimensional Schwinger model using
classically emulated digital quantum simulator.
Related papers
- Photonic Simulation of Localization Phenomena Using Boson Sampling [0.0]
We propose boson sampling as an alternative compact synthetic platform performing at room temperature.
By mapping the time-evolution unitary of a Hamiltonian onto an interferometer via continuous-variable gate decompositions, we present proof-of-principle results of localization characteristics of a single particle.
arXiv Detail & Related papers (2024-10-17T18:00:05Z) - Digital Quantum Simulation for Spectroscopy of Schwinger Model [0.0]
This note discusses a method for computing the energy spectra of quantum field theory utilizing digital quantum simulation.
A quantum algorithm, called coherent imaging spectroscopy, quenches the vacuum with a time-oscillating perturbation.
As a practical demonstration, we apply this algorithm to the (1+1)-dimensional quantum electrodynamics with a topological term known as the Schwinger model.
arXiv Detail & Related papers (2024-04-23T06:54:41Z) - Simulations of quantum dynamics with fermionic phase-space
representations using numerical matrix factorizations as stochastic gauges [0.0]
We explore the use of dynamical diffusion gauges in quantum dynamics simulations.
For the physical systems with fermionic particles considered here, the numerical evaluation of the new diffusion gauges allows us to double the practical simulation time.
This development may have far reaching consequences for future quantum dynamical simulations of many-body systems.
arXiv Detail & Related papers (2023-04-11T11:33:55Z) - Pulse-controlled qubit in semiconductor double quantum dots [57.916342809977785]
We present a numerically-optimized multipulse framework for the quantum control of a single-electron charge qubit.
A novel control scheme manipulates the qubit adiabatically, while also retaining high speed and ability to perform a general single-qubit rotation.
arXiv Detail & Related papers (2023-03-08T19:00:02Z) - Importance sampling for stochastic quantum simulations [68.8204255655161]
We introduce the qDrift protocol, which builds random product formulas by sampling from the Hamiltonian according to the coefficients.
We show that the simulation cost can be reduced while achieving the same accuracy, by considering the individual simulation cost during the sampling stage.
Results are confirmed by numerical simulations performed on a lattice nuclear effective field theory.
arXiv Detail & Related papers (2022-12-12T15:06:32Z) - Calculating non-linear response functions for multi-dimensional
electronic spectroscopy using dyadic non-Markovian quantum state diffusion [68.8204255655161]
We present a methodology for simulating multi-dimensional electronic spectra of molecular aggregates with coupling electronic excitation to a structured environment.
A crucial aspect of our approach is that we propagate the NMQSD equation in a doubled system Hilbert space but with the same noise.
arXiv Detail & Related papers (2022-07-06T15:30:38Z) - Probing finite-temperature observables in quantum simulators of spin
systems with short-time dynamics [62.997667081978825]
We show how finite-temperature observables can be obtained with an algorithm motivated from the Jarzynski equality.
We show that a finite temperature phase transition in the long-range transverse field Ising model can be characterized in trapped ion quantum simulators.
arXiv Detail & Related papers (2022-06-03T18:00:02Z) - The vacuum provides quantum advantage to otherwise simulatable
architectures [49.1574468325115]
We consider a computational model composed of ideal Gottesman-Kitaev-Preskill stabilizer states.
We provide an algorithm to calculate the probability density function of the measurement outcomes.
arXiv Detail & Related papers (2022-05-19T18:03:17Z) - Improving approximate vacuum prepared by the adiabatic quantum
computation [0.0]
According to the quantum adiabatic theorem, we can in principle obtain a true vacuum of a quantum system starting from a trivial vacuum of a simple Hamiltonian.
In actual adiabatic digital quantum simulation with finite time length and non-infinitesimal time steps, we can only obtain an approximate vacuum that is supposed to be a superposition of a true vacuum and excited states.
arXiv Detail & Related papers (2022-04-08T06:11:36Z) - Taming numerical errors in simulations of continuous variable
non-Gaussian state preparation [1.2891210250935146]
A powerful instrument for such simulation is the numerical computation in the Fock state representation.
We analyze the accuracy of several currently available methods for computation of the truncated coherent displacement operator.
We then employ the method in analysis of non-Gaussian state preparation scheme based on coherent displacement of a two mode squeezed vacuum with subsequent photon counting measurement.
arXiv Detail & Related papers (2022-02-15T11:41:57Z) - Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable
Embeddings with Generative Priors [52.06292503723978]
Motivated by advances in compressive sensing with generative models, we study the problem of 1-bit compressive sensing with generative models.
We first consider noiseless 1-bit measurements, and provide sample complexity bounds for approximate recovery under i.i.d.Gaussian measurements.
We demonstrate that the Binary $epsilon$-Stable Embedding property, which characterizes the robustness of the reconstruction to measurement errors and noise, also holds for 1-bit compressive sensing with Lipschitz continuous generative models.
arXiv Detail & Related papers (2020-02-05T09:44:10Z)
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.