Explicit gate construction of block-encoding for Hamiltonians needed for simulating partial differential equations
- URL: http://arxiv.org/abs/2405.12855v2
- Date: Wed, 09 Oct 2024 03:33:55 GMT
- Title: Explicit gate construction of block-encoding for Hamiltonians needed for simulating partial differential equations
- Authors: Nikita Guseynov, Xiajie Huang, Nana Liu,
- Abstract summary: This paper introduces an efficient quantum protocol for the explicit construction of block-encoding for an important class of Hamiltonians.
The proposed algorithm exhibits scaling with respect to the spatial size, suggesting an exponential speedup over classical finite-difference methods.
- Score: 0.6144680854063939
- License:
- Abstract: Quantum computation is an emerging technology with important potential for solving certain problems pivotal in various scientific and engineering disciplines. This paper introduces an efficient quantum protocol for the explicit construction of block-encoding for an important class of Hamiltonians. Using the Schrodingerisation technique -- which converts non-conservative PDEs into conservative ones -- this particular class of Hamiltonians is shown to be sufficient for simulating any linear partial differential equations that have coefficients which are polynomial functions. The class of Hamiltonians consist of discretisations of polynomial products and sums of position and momentum operators. This construction is explicit and leverages minimal one- and two-qubit operations. The explicit construction of this block-encoding forms a fundamental building block for constructing the unitary evolution operator for this Hamiltonian. The proposed algorithm exhibits polynomial scaling with respect to the spatial partitioning size, suggesting an exponential speedup over classical finite-difference methods. This work provides an important foundation for building explicit and efficient quantum circuits for solving partial differential equations.
Related papers
- Gate Efficient Composition of Hamiltonian Simulation and Block-Encoding with its Application on HUBO, Fermion Second-Quantization Operators and Finite Difference Method [0.0]
This article proposes a simple formalism which unifies Hamiltonian simulation techniques from different fields.
It leads to a gate decomposition and a scaling different from the usual strategy.
It can significantly reduce the quantum circuit number of rotational gates, multi-qubit gates, and the circuit depth.
arXiv Detail & Related papers (2024-10-24T12:26:50Z) - 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) - Scalable embedding of parity constraints in quantum annealing hardware [0.0]
We present fixed, modular and scalable embeddings that can be used to embed any optimization problem described as an Ising Hamiltonian.
These embeddings are the result of an extension of the well-known parity mapping.
We show how our new embeddings can be mapped to existing quantum annealers and that the embedded Hamiltonian physical properties match the original Hamiltonian properties.
arXiv Detail & Related papers (2024-05-23T16:14:33Z) - Hamiltonian simulation for hyperbolic partial differential equations by scalable quantum circuits [1.6268784011387605]
This paper presents a method that enables us to explicitly implement the quantum circuit for Hamiltonian simulation.
We show that the space and time complexities of the constructed circuit are exponentially smaller than those of conventional classical algorithms.
arXiv Detail & Related papers (2024-02-28T15:17:41Z) - Vectorization of the density matrix and quantum simulation of the von
Neumann equation of time-dependent Hamiltonians [65.268245109828]
We develop a general framework to linearize the von-Neumann equation rendering it in a suitable form for quantum simulations.
We show that one of these linearizations of the von-Neumann equation corresponds to the standard case in which the state vector becomes the column stacked elements of the density matrix.
A quantum algorithm to simulate the dynamics of the density matrix is proposed.
arXiv Detail & Related papers (2023-06-14T23:08:51Z) - Extension of exactly-solvable Hamiltonians using symmetries of Lie
algebras [0.0]
We show that a linear combination of operators forming a modest size Lie algebra can be substituted by determinants of the Lie algebra symmetries.
The new class of solvable Hamiltonians can be measured efficiently using quantum circuits with gates that depend on the result of a mid-circuit measurement of the symmetries.
arXiv Detail & Related papers (2023-05-29T17:19:56Z) - Variational Adiabatic Gauge Transformation on real quantum hardware for
effective low-energy Hamiltonians and accurate diagonalization [68.8204255655161]
We introduce the Variational Adiabatic Gauge Transformation (VAGT)
VAGT is a non-perturbative hybrid quantum algorithm that can use nowadays quantum computers to learn the variational parameters of the unitary circuit.
The accuracy of VAGT is tested trough numerical simulations, as well as simulations on Rigetti and IonQ quantum computers.
arXiv Detail & Related papers (2021-11-16T20:50:08Z) - Spectral density reconstruction with Chebyshev polynomials [77.34726150561087]
We show how to perform controllable reconstructions of a finite energy resolution with rigorous error estimates.
This paves the way for future applications in nuclear and condensed matter physics.
arXiv Detail & Related papers (2021-10-05T15:16:13Z) - Algebraic Compression of Quantum Circuits for Hamiltonian Evolution [52.77024349608834]
Unitary evolution under a time dependent Hamiltonian is a key component of simulation on quantum hardware.
We present an algorithm that compresses the Trotter steps into a single block of quantum gates.
This results in a fixed depth time evolution for certain classes of Hamiltonians.
arXiv Detail & Related papers (2021-08-06T19:38:01Z) - Fixed Depth Hamiltonian Simulation via Cartan Decomposition [59.20417091220753]
We present a constructive algorithm for generating quantum circuits with time-independent depth.
We highlight our algorithm for special classes of models, including Anderson localization in one dimensional transverse field XY model.
In addition to providing exact circuits for a broad set of spin and fermionic models, our algorithm provides broad analytic and numerical insight into optimal Hamiltonian simulations.
arXiv Detail & Related papers (2021-04-01T19:06:00Z) - A Hybrid Quantum-Classical Hamiltonian Learning Algorithm [6.90132007891849]
Hamiltonian learning is crucial to the certification of quantum devices and quantum simulators.
We propose a hybrid quantum-classical Hamiltonian learning algorithm to find the coefficients of the Pauli operator of the Hamiltonian.
arXiv Detail & Related papers (2021-03-01T15:15:58Z)
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.