Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 1908.02600

Purifying electron spectra from noisy pulses with machine learning using synthetic Hamilton matrices

Sajal Kumar Giri·Ulf Saalmann·Jan M. Rost
View original source ↗Read source document ↗Export metadata ↓

Abstract

Photo-electron spectra obtained with intense pulses generated by free-electron lasers through self-amplified spontaneous emission are intrinsically noisy and vary from shot to shot. We extract the purified spectrum, corresponding to a Fourier-limited pulse, with the help of a deep neural network. It is trained on a huge number of spectra, which was made possible by an extremely efficient propagation of the Schrödinger equation with synthetic Hamilton matrices and random realizations of fluctuating pulses. We show that the trained network is sufficiently generic such that it can purify atomic or molecular spectra, dominated by resonant two- or three-photon ionization, non-linear processes which are particularly sensitive to pulse fluctuations. This is possible without training on those systems.

Explore related subjects

physics.atom-ph

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sajal Kumar Giri, Ulf Saalmann, Jan M. Rost. 2020-03-12. Purifying electron spectra from noisy pulses with machine learning using synthetic Hamilton matrices. https://doi.org/10.1103/physrevlett.124.113201

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Delay-engineered dynamical phases in a programmable non-Markovian spin oscillator

Non-Markovian dynamics offer a new route towards engineering non-equilibrium matter, where memory and feedback act as programmable resources for controlling order in time. Here we report the realization of a non-Markovian spin oscillator in a hot vapour $^{129}$Xe-Cs co-magnetometer with programmable feedback delay and gain. By tuning these parameters, we observe a hierarchy of dynamical phases, including time-crystalline response, nonlinear bifurcations, and frequency-comb formation. The measured spectra and phase boundaries are captured by linear stability analysis of delayed Bloch equations, revealing these phenomena as different manifestations of the same memory-induced instability structure. These results establish time-delayed feedback as a powerful strategy for controlling non-equilibrium phases, enabling quantum sensing, frequency referencing, and synchronization within a single spin-based platform.

physics.atom-ph↗
arXiv2026

Non-stick vacuum wall collisions with a laser-coolable molecule

Molecular species that are suitable for direct laser cooling are typically considered lost or destroyed if they collide with an ambient temperature vacuum wall. Here, we study surface collisions with aluminum monofluoride (AlF), a laser-coolable molecule that survives this process with unusually high probability. We detect the outgoing AlF molecules from a single wall collision via Doppler-sensitive laser-induced fluorescence spectroscopy, using incoming supersonic (pulsed) and thermochemical (continuous) molecular beams. The angular, velocity and rovibrational level distributions of the outgoing molecules show near-complete thermalisation to the wall in a single collision event. We determine an upper limit to the surface residence time of about 5$~\mu$s, and by monitoring the decay in density of pulses of molecules loaded into a small storage volume, we deduce the surface sticking probability for different materials. For a siloxane-coated metallic surface, the sticking probability of AlF is about 0.015, allowing us to accumulate molecules from the thermochemical source into an ambient temperature storage vessel at densities near $10^{8}~$cm$^{-3}$. This provides a route to compact, portable traps for neutral molecules.

physics.atom-ph↗
arXiv2026

Kinetic modeling of molecular beam formation in a cryogenic buffer-gas cell

Cryogenic buffer-gas cells are widely used to produce cold molecular beams, but the microscopic dynamics governing beam formation remain challenging to model. Here we present fully kinetic simulations of a cryogenic buffer-gas cell using the Direct Simulation Monte Carlo method implemented in the PICLas framework, treating the buffer gas and ablated molecules within a single unified model. We capture characteristic features of cryogenic buffer-gas sources, including plume cooling, directed transport toward the aperture, and the formation of a slow molecular beam, while also resolving energy transfer from the hot ablation plume to the helium buffer gas that is inaccessible to existing approaches relying on the background-gas approximation. Our results demonstrate that fully kinetic simulations can provide detailed insights into buffer-gas cell dynamics and open a route toward a systematic optimization of such sources.

physics.atom-ph↗