arXiv subjects

Chris Xu

Publications and source records attributed to Chris Xu.

8 recordsLinked to original sources

arXiv2026

Highly-efficient perturbative Raman shifting by engineering the nonlinear temporal response

Raman scattering underlies a broad range of spectroscopic and light-generation techniques, yet its conventional description, based on the Raman gain spectrum, accurately describes only long-pulse, steady-state dynamics. We present a time-domain theoretical approach that provides a unified and physically-transparent description of Raman interactions across all temporal regimes. It enables direct visualization of Raman temporal dynamics and accounts for spectrotemporal aspects of Raman phenomena, which cannot be addressed by prior theories. In particular, molecules with strong Raman responses do not produce an efficient soliton self-frequency shift in gas-filled hollow-core fibers. The time-domain analysis exposes temporal and spectral distortions from the Raman response that impact frequency-shifting detrimentally, and identifies how these distortions can be suppressed by reducing the Raman interaction to a perturbation on the electronic response. Experiments that employ gas mixtures with tunable Raman fractions of the nonlinear response demonstrate up to a four-fold increase in quantum efficiency (from 20 to 80%) compared to the pure molecular gas, and unity-efficiency Raman shifting will be possible. The new time-domain framework uncovers phenomena that are inaccessible through the decades-old frequency-domain treatment of Raman scattering, and it applies to Raman interactions in solids, liquids, and gases on various timescales.

physics.optics↗

arXiv2025

Determination of the fifth Busy Beaver value

The Busy Beaver value $S(n)$ is the maximum number of steps that an $n$-state 2-symbol Turing machine can perform from the all-zero tape before halting. $S$ was historically introduced by Tibor Rad\'o in 1962 as one of the simplest examples of an uncomputable function. We prove that $S(5) = 47,176,870$ using the Coq proof assistant. The proof enumerates $181,385,789$ Turing machines with 5 states and, for each machine, decides whether it halts or not. Our result marks the first determination of a new Busy Beaver value in over 40 years and the first Busy Beaver value ever to be formally verified, attesting to the effectiveness of massively collaborative online research (bbchallenge$.$org).

cs.LO↗

arXiv2025

Rigorous expansions of modular forms at CM points, I: Denominators

We describe an algorithm to rigorously compute the power series expansion at a CM point of a weight $2$ cusp form of level coprime to $6$. Our algorithm works by bounding the denominators that appear due to ramification, and without recourse to computing an explicit model of the corresponding modular curve. Our result is the first in a series of papers toward an eventual implementation of equationless Chabauty.

math.NT↗

arXiv2024

Efficient, broadly-tunable source of megawatt pulses for multiphoton microscopy based on self-phase modulation in argon-filled hollow-core fiber

An exciting recent development for deep-tissue imaging with cellular resolution is three-photon fluorescence microscopy (3PM) with excitation at long wavelengths (1300 and 1700 nm). In the last few years, long-wavelength 3PM has driven rapid progress in deep-tissue imaging beyond the depth limit of two-photon microscopy, with impacts in neuroscience, immunology, and cancer biology. However, wide adoption of 3PM faces challenges. Three-photon excitation (3PE) is naturally weaker than two-photon excitation, which places a premium on ultrashort pulses with high peak power. The inefficiency, complexity, and cost of current sources of these pulses present major barriers to the use of 3PM in typical biomedical research labs. Here, we describe a fiber-based source of femtosecond pulses with multi-megawatt peak power, tunable from 850 nm to 1700 nm. Compressed pulses from a fiber amplifier at 1030~nm are launched into an antiresonant hollow-core fiber filled with argon. By varying only the gas pressure, pulses with hundreds of nanojoules of energy and sub-100 fs duration are obtained at wavelengths between 850 and 1700 nm. This approach is a new route to an efficient, robust, and potentially low-cost source for multiphoton deep-tissue imaging. In particular, 960-nJ and 50-fs pulses are generated at 1300 nm with a conversion efficiency of 10\%. The nearly 20-MW peak power is an order of magnitude higher than the previous best from femtosecond fiber source at 1300~nm. As an example of the capabilities of the source, these pulses are used to image structure and neuronal activity in mouse brain as deep as 1.1 mm below the dura.

physics.optics↗

arXiv2024

Skelet #17 and the fifth Busy Beaver number

We prove nonhalting of the Turing machine dubbed "Skelet #17", known to be one of the toughest 5-state, 2-symbol Turing machines to analyze. Combined with the efforts of The Busy Beaver Challenge, we are therefore able to show that BB(5), the fifth Busy Beaver number, equals 47,176,870.

math.CO↗

arXiv2021

Roadmap on Wavefront Shaping and deep imaging in complex media

The last decade has seen the development of a wide set of tools, such as wavefront shaping, computational or fundamental methods, that allow to understand and control light propagation in a complex medium, such as biological tissues or multimode fibers. A vibrant and diverse community is now working on this field, that has revolutionized the prospect of diffraction-limited imaging at depth in tissues. This roadmap highlights several key aspects of this fast developing field, and some of the challenges and opportunities ahead.

physics.optics↗

arXiv2021

Joint Optimization of Hadamard Sensing and Reconstruction in Compressed Sensing Fluorescence Microscopy

Compressed sensing fluorescence microscopy (CS-FM) proposes a scheme whereby less measurements are collected during sensing and reconstruction is performed to recover the image. Much work has gone into optimizing the sensing and reconstruction portions separately. We propose a method of jointly optimizing both sensing and reconstruction end-to-end under a total measurement constraint, enabling learning of the optimal sensing scheme concurrently with the parameters of a neural network-based reconstruction network. We train our model on a rich dataset of confocal, two-photon, and wide-field microscopy images comprising of a variety of biological samples. We show that our method outperforms several baseline sensing schemes and a regularized regression reconstruction algorithm.

eess.IV↗

arXiv2003

Q factor in numerical simulations of DPSK with optical delay demodulation

A simple model is used to estimate the Q factor in numerical simulations of differential phase shift keying (DPSK) with optical delay demodulation and balanced detection. It is found that an alternative definition of Q is needed for DPSK in order to have a more accurate prediction of the bit error ratio (BER).

physics.optics↗