On Lagrangian Formalism of Quantum Computation
- URL: http://arxiv.org/abs/2112.04892v1
- Date: Tue, 7 Dec 2021 12:24:04 GMT
- Title: On Lagrangian Formalism of Quantum Computation
- Authors: Jue Xu
- Abstract summary: We reformulate quantum computation in terms of Lagrangian (sum-over-path) formalism.
The meanings of Lagrangian (action) are interpreted in various contexts of quantum computation.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: We reformulate quantum computation in terms of Lagrangian (sum-over-path)
formalism, in contrast to the widely used Hamiltonian (unitary gate)
formulation. We exemplify this formalism with some widely-studied models,
including the standard quantum circuit model, quantum optimization heuristics,
and quantum random walks. The meanings of Lagrangian (action) are interpreted
in various contexts of quantum computation, such as complexity analysis.
Furthermore, an analog quantum simulation scheme is suggested where the
Lagrangian serves as the starting point and the sum-over-path method is
applied.
Related papers
- Lower bound for simulation cost of open quantum systems: Lipschitz continuity approach [5.193557673127421]
We present a general framework to calculate the lower bound for simulating a broad class of quantum Markov semigroups.
Our framework can be applied to both unital and non-unital quantum dynamics.
arXiv Detail & Related papers (2024-07-22T03:57:41Z) - Model Reduction for Quantum Systems: Discrete-time Quantum Walks and
Open Markov Dynamics [0.0]
A framework for exact model reduction of quantum systems is constructed leveraging on algebraic methods.
The proposed reduction algorithm is illustrated and tested on prototypical examples, including the quantum walk realizing Grover's algorithm.
arXiv Detail & Related papers (2023-07-12T17:30:12Z) - Lagrangian trajectories and closure models in mixed quantum-classical
dynamics [0.0]
We present a fully Hamiltonian theory of quantum-classical dynamics that appears to be the first to ensure a series of consistency properties.
Based on Lagrangian phase-space paths, the model possesses a quantum-classical Poincar'e integral invariant as well as infinite classes of Casimir functionals.
arXiv Detail & Related papers (2023-03-03T18:55:15Z) - The Quantum Path Kernel: a Generalized Quantum Neural Tangent Kernel for
Deep Quantum Machine Learning [52.77024349608834]
Building a quantum analog of classical deep neural networks represents a fundamental challenge in quantum computing.
Key issue is how to address the inherent non-linearity of classical deep learning.
We introduce the Quantum Path Kernel, a formulation of quantum machine learning capable of replicating those aspects of deep machine learning.
arXiv Detail & Related papers (2022-12-22T16:06:24Z) - Numerical Simulations of Noisy Quantum Circuits for Computational
Chemistry [51.827942608832025]
Near-term quantum computers can calculate the ground-state properties of small molecules.
We show how the structure of the computational ansatz as well as the errors induced by device noise affect the calculation.
arXiv Detail & Related papers (2021-12-31T16:33:10Z) - Efficient criteria of quantumness for a large system of qubits [58.720142291102135]
We discuss the dimensionless combinations of basic parameters of large, partially quantum coherent systems.
Based on analytical and numerical calculations, we suggest one such number for a system of qubits undergoing adiabatic evolution.
arXiv Detail & Related papers (2021-08-30T23:50:05Z) - 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) - The Hintons in your Neural Network: a Quantum Field Theory View of Deep
Learning [84.33745072274942]
We show how to represent linear and non-linear layers as unitary quantum gates, and interpret the fundamental excitations of the quantum model as particles.
On top of opening a new perspective and techniques for studying neural networks, the quantum formulation is well suited for optical quantum computing.
arXiv Detail & Related papers (2021-03-08T17:24:29Z) - Quantum simulation of quantum field theories as quantum chemistry [9.208624182273288]
Conformal truncation is a powerful numerical method for solving generic strongly-coupled quantum field theories.
We show that quantum computation could not only help us understand fundamental physics in the lattice approximation, but also simulate quantum field theory methods directly.
arXiv Detail & Related papers (2020-04-28T01:20:04Z) - Geometric viewpoint on the quantization of a fuzzy logic [0.0]
We give a description of quantum propositions in terms of fuzzy events in a complex projective space equipped with K"ahler structure (the quantum phase space)
We obtain a quantized version of a fuzzy logic by deformation of the product t-norm.
arXiv Detail & Related papers (2020-04-06T13:37:02Z) - Quantum Statistical Complexity Measure as a Signalling of Correlation
Transitions [55.41644538483948]
We introduce a quantum version for the statistical complexity measure, in the context of quantum information theory, and use it as a signalling function of quantum order-disorder transitions.
We apply our measure to two exactly solvable Hamiltonian models, namely: the $1D$-Quantum Ising Model and the Heisenberg XXZ spin-$1/2$ chain.
We also compute this measure for one-qubit and two-qubit reduced states for the considered models, and analyse its behaviour across its quantum phase transitions for finite system sizes as well as in the thermodynamic limit by using Bethe ansatz.
arXiv Detail & Related papers (2020-02-05T00:45:21Z)
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.