Hamiltonian Encoding for Quantum Approximate Time Evolution of Kinetic
Energy Operator
- URL: http://arxiv.org/abs/2310.03319v1
- Date: Thu, 5 Oct 2023 05:25:38 GMT
- Title: Hamiltonian Encoding for Quantum Approximate Time Evolution of Kinetic
Energy Operator
- Authors: Mostafizur Rahaman Laskar, Kalyan Dasgputa, Amit Kumar Dutta, Atanu
Bhattacharya
- Abstract summary: The time evolution operator plays a crucial role in the precise computation of chemical experiments on quantum computers.
We have proposed a new encoding method, namely quantum approximate time evolution (QATE) for the quantum implementation of the kinetic energy operator.
- Score: 2.184775414778289
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: The time evolution operator plays a crucial role in the precise computation
of chemical experiments on quantum computers and holds immense promise for
advancing the fields of physical and computer sciences, with applications
spanning quantum simulation and machine learning. However, the construction of
large-scale quantum computers poses significant challenges, prompting the need
for innovative and resource-efficient strategies. Traditional methods like
phase estimation or variational algorithms come with certain limitations such
as the use of classical optimization or complex quantum circuitry. One
successful method is the Trotterization technique used for quantum simulation,
specifically in atomic structure problems with a gate complexity of
approximately O(n^2) for an n-qubit realization. In this work, we have proposed
a new encoding method, namely quantum approximate time evolution (QATE) for the
quantum implementation of the kinetic energy operator as a diagonal unitary
operator considering the first quantization level. The theoretical foundations
of our approach are discussed, and experimental results are obtained on an IBM
quantum machine. Our proposed method offers gate complexity in sub-quadratic
polynomial with qubit size $n$ which is an improvement over previous work.
Further, the fidelity improvement for the time evolution of the Gaussian wave
packet has also been demonstrated.
Related papers
- Efficient Learning for Linear Properties of Bounded-Gate Quantum Circuits [63.733312560668274]
Given a quantum circuit containing d tunable RZ gates and G-d Clifford gates, can a learner perform purely classical inference to efficiently predict its linear properties?
We prove that the sample complexity scaling linearly in d is necessary and sufficient to achieve a small prediction error, while the corresponding computational complexity may scale exponentially in d.
We devise a kernel-based learning model capable of trading off prediction error and computational complexity, transitioning from exponential to scaling in many practical settings.
arXiv Detail & Related papers (2024-08-22T08:21:28Z) - Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
Quantum computing sets the foundation for new ways of designing algorithms.
New challenges arise concerning which field quantum speedup can be achieved.
Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
arXiv Detail & Related papers (2024-02-26T09:32:07Z) - Quantum Simulation of Dissipative Energy Transfer via Noisy Quantum
Computer [0.40964539027092917]
We propose a practical approach to simulate the dynamics of an open quantum system on a noisy computer.
Our method leverages gate noises on the IBM-Q real device, enabling us to perform calculations using only two qubits.
In the last, to deal with the increasing depth of quantum circuits when doing Trotter expansion, we introduced the transfer tensor method(TTM) to extend our short-term dynamics simulation.
arXiv Detail & Related papers (2023-12-03T13:56:41Z) - Efficient Quantum Modular Arithmetics for the ISQ Era [0.0]
This study presents an array of quantum circuits, each precision-engineered for modular arithmetic functions.
We provide a theoretical framework and practical implementations in the PennyLane quantum software.
arXiv Detail & Related papers (2023-11-14T21:34:39Z) - Expressive Quantum Supervised Machine Learning using Kerr-nonlinear
Parametric Oscillators [0.0]
Quantum machine learning with variational quantum algorithms (VQA) has been actively investigated as a practical algorithm in the noisy intermediate-scale quantum (NISQ) era.
Recent researches reveal that the data reuploading, which repeatedly encode classical data into quantum circuit, is necessary for obtaining the expressive quantum machine learning model.
We propose quantum machine learning with Kerrnon Parametric Hilberts (KPOs) as another promising quantum computing device.
arXiv Detail & Related papers (2023-05-01T07:01:45Z) - Quantum Annealing for Single Image Super-Resolution [86.69338893753886]
We propose a quantum computing-based algorithm to solve the single image super-resolution (SISR) problem.
The proposed AQC-based algorithm is demonstrated to achieve improved speed-up over a classical analog while maintaining comparable SISR accuracy.
arXiv Detail & Related papers (2023-04-18T11:57:15Z) - Quantum Phase Processing and its Applications in Estimating Phase and
Entropies [10.8525801756287]
"quantum phase processing" can directly apply arbitrary trigonometric transformations to eigenphases of a unitary operator.
Quantum phase processing can extract the eigen-information of quantum systems by simply measuring the ancilla qubit.
We propose a new quantum phase estimation algorithm without quantum Fourier transform, which requires the fewest ancilla qubits and matches the best performance so far.
arXiv Detail & Related papers (2022-09-28T17:41:19Z) - 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) - Imaginary Time Propagation on a Quantum Chip [50.591267188664666]
Evolution in imaginary time is a prominent technique for finding the ground state of quantum many-body systems.
We propose an algorithm to implement imaginary time propagation on a quantum computer.
arXiv Detail & Related papers (2021-02-24T12:48:00Z) - Electronic structure with direct diagonalization on a D-Wave quantum
annealer [62.997667081978825]
This work implements the general Quantum Annealer Eigensolver (QAE) algorithm to solve the molecular electronic Hamiltonian eigenvalue-eigenvector problem on a D-Wave 2000Q quantum annealer.
We demonstrate the use of D-Wave hardware for obtaining ground and electronically excited states across a variety of small molecular systems.
arXiv Detail & Related papers (2020-09-02T22:46:47Z) - Quantum Solver of Contracted Eigenvalue Equations for Scalable Molecular
Simulations on Quantum Computing Devices [0.0]
We introduce a quantum solver of contracted eigenvalue equations, the quantum analogue of classical methods for the energies.
We demonstrate the algorithm though computations on both a quantum simulator and two IBM quantum processing units.
arXiv Detail & Related papers (2020-04-23T18:35:26Z)
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.