A Polylogarithmic-Time Quantum Algorithm for the Laplace Transform
- URL: http://arxiv.org/abs/2512.17980v1
- Date: Fri, 19 Dec 2025 13:31:39 GMT
- Title: A Polylogarithmic-Time Quantum Algorithm for the Laplace Transform
- Authors: Akash Kumar Singh, Ashish Kumar Patra, Anurag K. S. V., Sai Shankar P., Ruchika Bhat, Jaiganesh G,
- Abstract summary: We introduce a quantum algorithm to perform the Laplace transform on quantum computers.<n>Our algorithm can implement $N times N$ discrete Laplace transform in gate complexity that grows as $O((log,N)3)$.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We introduce a quantum algorithm to perform the Laplace transform on quantum computers. Already, the quantum Fourier transform (QFT) is the cornerstone of many quantum algorithms, but the Laplace transform or its discrete version has not seen any efficient implementation on quantum computers due to its dissipative nature and hence non-unitary dynamics. However, a recent work has shown an efficient implementation for certain cases on quantum computers using the Taylor series. Unlike previous work, our work provides a completely different algorithm for doing Laplace Transform using Quantum Eigenvalue Transformation and Lap-LCHS, very efficiently at points which form an arithmetic progression. Our algorithm can implement $N \times N$ discrete Laplace transform in gate complexity that grows as $O((log\,N)^3)$, ignoring the state preparation cost, where $N=2^n$ and $n$ is the number of qubits, which is a superpolynomial speedup in number of gates over the best classical counterpart that has complexity $O(N\cdot log\,N)$ for the same cases. Also, the circuit width grows as $O(log\,N)$. Quantum Laplace Transform (QLT) may enable new Quantum algorithms for cases like solving differential equations in the Laplace domain, developing an inverse Laplace transform algorithm on quantum computers, imaginary time evolution in the resolvent domain for calculating ground state energy, and spectral estimation of non-Hermitian matrices.
Related papers
- Quantum-Inspired Algorithms beyond Unitary Circuits: the Laplace Transform [0.0]
Quantum-inspired algorithms can deliver substantial speedups over classical state-of-the-art methods.<n>We introduce a tensor-network approach to compute the discrete Laplace transform, a non-unitary, aperiodic transform.<n>We demonstrate simulations up to $N=230$ input data points, with up to $260$ output data points, and quantify how bond dimension controls runtime and accuracy.
arXiv Detail & Related papers (2026-01-25T07:19:56Z) - Efficient Quantum Circuits for the Hilbert Transform [0.0]
This letter presents a novel construction for a quantum Hilbert transform in polylogarithmic size and logarithmic depth for a signal of length $N$.<n>We generalize this algorithm to create any $d$-dimensional Hilbert transform in depth $O(dlog N)$.<n> Simulations demonstrate effectiveness for tasks such as power systems control and image processing, with exact agreement with classical results.
arXiv Detail & Related papers (2026-01-15T22:02:32Z) - Quantum Krylov Algorithm for Szegö Quadrature [0.8158532237212478]
We present a quantum algorithm to evaluate matrix elements of functions of unitary operators.<n>The method is based on calculating quadrature nodes and weights using data collected from a quantum processor.
arXiv Detail & Related papers (2025-09-23T16:13:08Z) - Optimization and Synthesis of Quantum Circuits with Global Gates [41.99844472131922]
We use global interactions, such as the Global Molmer-Sorensen gate present in ion trap hardware, to optimize and synthesize quantum circuits.<n>The algorithm is based on the ZX-calculus and uses a specialized circuit extraction routine that groups entangling gates into Global MolmerSorensen gates.<n>We benchmark the algorithm in a variety of circuits, and show how it improves their performance under state-of-the-art hardware considerations.
arXiv Detail & Related papers (2025-07-28T10:25:31Z) - Distributed quantum algorithm for divergence estimation and beyond [12.925989807145301]
We propose a distributed quantum algorithm framework to compute $rm Tr(f(A)g(B))$ within an additive error $varepsilon$.<n>This framework holds broad applicability across a range of distributed quantum computing tasks.
arXiv Detail & Related papers (2025-03-12T14:28:22Z) - Quantum simulation of Burgers turbulence: Nonlinear transformation and direct evaluation of statistical quantities [0.0]
It is still challenging to solve nonlinear equations in fluid dynamics, such as the Burgers equation, using quantum computers.<n>We propose a novel quantum algorithm to solve the Burgers equation.
arXiv Detail & Related papers (2024-12-23T01:17:26Z) - Quantum Algorithms for Stochastic Differential Equations: A Schrödingerisation Approach [29.662683446339194]
We propose quantum algorithms for linear differential equations.<n>The gate complexity of our algorithms exhibits an $mathcalO(dlog(Nd))$ dependence on the dimensions.<n>The algorithms are numerically verified for the Ornstein-Uhlenbeck processes, Brownian motions, and one-dimensional L'evy flights.
arXiv Detail & Related papers (2024-12-19T14:04:11Z) - Fast Laplace transforms on quantum computers [0.0]
We introduce the Quantum Laplace Transform (QLT), which enables the implementation of $Ntimes N$ discrete Laplace transforms on quantum states encoded in $lceil log_2(N)rceil$-qubits.<n>In many cases, the associated quantum circuits have a depth that scales with $N$ as $O(log(N))$ and a size that scales as $O(log(N))$, requiring exponentially fewer operations and double-exponentially less computational time than their classical counterparts.
arXiv Detail & Related papers (2024-12-06T16:44:00Z) - Q-Newton: Hybrid Quantum-Classical Scheduling for Accelerating Neural Network Training with Newton's Gradient Descent [37.59299233291882]
We propose Q-Newton, a hybrid quantum-classical scheduler for accelerating neural network training with Newton's GD.<n>Q-Newton utilizes a streamlined scheduling module that coordinates between quantum and classical linear solvers.<n>Our evaluation showcases the potential for Q-Newton to significantly reduce the total training time compared to commonly used quantum machines.
arXiv Detail & Related papers (2024-04-30T23:55:03Z) - Speeding up Learning Quantum States through Group Equivariant
Convolutional Quantum Ans\"atze [13.651587339535961]
We develop a framework for convolutional quantum circuits with SU$(d)$symmetry.
We prove Harrow's statement on equivalence between $nameSU(d)$ and $S_n$ irrep bases.
arXiv Detail & Related papers (2021-12-14T18:03:43Z) - Asymptotically Optimal Circuit Depth for Quantum State Preparation and
General Unitary Synthesis [24.555887999356646]
The problem is of fundamental importance in quantum algorithm design, Hamiltonian simulation and quantum machine learning, yet its circuit depth and size complexity remain open when ancillary qubits are available.
In this paper, we study efficient constructions of quantum circuits with $m$ ancillary qubits that can prepare $psi_vrangle$ in depth.
Our circuits are deterministic, prepare the state and carry out the unitary precisely, utilize the ancillary qubits tightly and the depths are optimal in a wide range of parameter regime.
arXiv Detail & Related papers (2021-08-13T09:47:11Z) - Synthesis of Quantum Circuits with an Island Genetic Algorithm [44.99833362998488]
Given a unitary matrix that performs certain operation, obtaining the equivalent quantum circuit is a non-trivial task.
Three problems are explored: the coin for the quantum walker, the Toffoli gate and the Fredkin gate.
The algorithm proposed proved to be efficient in decomposition of quantum circuits, and as a generic approach, it is limited only by the available computational power.
arXiv Detail & Related papers (2021-06-06T13:15:25Z) - Quantum Legendre-Fenchel Transform [6.643082745560234]
We present a quantum algorithm to compute the discrete Legendre-Fenchel transform.
We show that our quantum algorithm is optimal up to polylogarithmic factors.
arXiv Detail & Related papers (2020-06-08T18:00:05Z) - Quantum Gram-Schmidt Processes and Their Application to Efficient State
Read-out for Quantum Algorithms [87.04438831673063]
We present an efficient read-out protocol that yields the classical vector form of the generated state.
Our protocol suits the case that the output state lies in the row space of the input matrix.
One of our technical tools is an efficient quantum algorithm for performing the Gram-Schmidt orthonormal procedure.
arXiv Detail & Related papers (2020-04-14T11:05:26Z)
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.