arXiv subjects

Robert B. Lowrie

Publications and source records attributed to Robert B. Lowrie.

3 recordsLinked to original sources

arXiv2026

Asymptotic constraints for 1D planar grey photon diffusion from linear transport with special-relativistic effects

We derive a grey linear diffusion equation for photons with respect to inertial (or lab-frame) space and time, using asymptotic analysis in 1D planar geometry. The solution of the equation is the comoving radiation energy density. Our analysis does not make use of assumptions about the magnitude of velocity; instead we derive an asymptotic scaling in the lab frame such that we avoid apparent non-physical pathologies that are encountered with the standard static-matter scaling. We permit the photon direction to be continuous (as opposed to constraining the analysis to discrete ordinates). The result is a drift-diffusion equation in the lab frame for comoving radiation energy density, with an adiabatic term that matches the standard semi-relativistic diffusion equation. Following a recent study for discrete directions, this equation reduces to a pure advection equation as the velocity approaches the speed of light. We perform preliminary numerical experiments comparing solutions to relativistic lab-frame Monte Carlo transport and to the well-known semi-relativistic diffusion equation.

astro-ph.HE↗

arXiv2024

The cost of solving linear differential equations on a quantum computer: fast-forwarding to explicit resource counts

How well can quantum computers simulate classical dynamical systems? There is increasing effort in developing quantum algorithms to efficiently simulate dynamics beyond Hamiltonian simulation, but so far exact resource estimates are not known. In this work, we provide two significant contributions. First, we give the first non-asymptotic computation of the cost of encoding the solution to general linear ordinary differential equations into quantum states -- either the solution at a final time, or an encoding of the whole history within a time interval. Second, we show that the stability properties of a large class of classical dynamics allow their fast-forwarding, making their quantum simulation much more time-efficient. From this point of view, quantum Hamiltonian dynamics is a boundary case that does not allow this form of stability-induced fast-forwarding. In particular, we find that the history state can always be output with complexity $O(T^{1/2})$ for any stable linear system. We present a range of asymptotic improvements over state-of-the-art in various regimes. We illustrate our results with a family of dynamics including linearized collisional plasma problems, coupled, damped, forced harmonic oscillators and dissipative nonlinear problems. In this case the scaling is quadratically improved, and leads to significant reductions in the query counts after inclusion of all relevant constant prefactors.

quant-ph↗

arXiv2024

Challenges for quantum computation of nonlinear dynamical systems using linear representations

A number of recent studies have proposed that linear representations are appropriate for solving nonlinear dynamical systems with quantum computers, which fundamentally act linearly on a wave function in a Hilbert space. Linear representations, such as the Koopman representation and Koopman von Neumann mechanics, have regained attention from the dynamical-systems research community. Here, we aim to present a unified theoretical framework, currently missing in the literature, with which one can compare and relate existing methods, their conceptual basis, and their representations. We also aim to show that, despite the fact that quantum simulation of nonlinear classical systems may be possible with such linear representations, a necessary projection into a feasible finite-dimensional space will in practice eventually induce numerical artifacts which can be hard to eliminate or even control. As a result, a practical, reliable and accurate way to use quantum computation for solving general nonlinear dynamical systems is still an open problem.

quant-ph↗