A New Approach for Constraining Large-Scale Temperature Fluctuations in the Intergalactic Medium

The reionization of helium is thought to occur at $2.5\lesssim z\lesssim4$, marking the last phase transition and final global heating event of the intergalactic medium (IGM). Since it is driven by rare quasars, helium reionization should give rise to strong temperature fluctuations in the IGM between neutral and recently-ionized regions of order $σ(\ln T) \sim ΔT/T = 20-50\%$. We introduce a novel method to search for reionization-induced temperature fluctuations in the IGM by using the effective optical depths of the Lyman-$α$ forest towards a large number of background quasars. Higher IGM temperatures give rise to lower effective optical depths in the Lyman-$α$ forest, implying that temperature fluctuations will broaden the observed optical depth distribution. We measured the distributions of effective Lyman-$α$ forest optical depths across $71$ X-Shooter spectra from the XQ-100 survey in four redshift bins from $z=3.76$ to $z=4.19$ and compared them to a large-volume cosmological hydrodynamical simulation. A good agreement is found between the observations and the simulation, which does not include temperature fluctuations; therefore, we do not detect a signature of helium reionization. We then post-process the simulations to include an increasing amount of temperature fluctuations until the model becomes inconsistent with the observations. We obtain tight constraints on $σ(\ln T) < 0.29 \ (<0.40)$ at $2 σ (3 σ)$ at $z=3.76$ when averaging over scales of $100$ comoving Mpc, and weaker constraints for higher redshifts and smaller scales. Our constraints are the tightest to date, and imply that either the IGM temperature contrast caused by helium reionization is less than $\sim30\%$, or that the process has not yet significantly started at $z=3.76$.18 pages, 6+5 figures, 3 tables, submitted to Ap

A Mosquito-Inspired Theoretical Framework for Acoustic Signal Detection

Distortion products are tones produced through nonlinear effects of a system simultaneously detecting two or more frequencies. These combination tones are ubiquitous to vertebrate auditory systems and are generally regarded as byproducts of nonlinear signal amplification. It has previously been shown that several species of infectious-disease-carrying mosquitoes utilize these distortion products for detecting and locating potential mates. It has also been shown that their auditory systems contain multiple oscillatory components within the sensory structure, which respond at different frequency ranges. Using a generic theoretical model for acoustic detection, we show the signal-detection advantages that are implied by these two detection schemes: distortion product detection and cascading a signal through multiple layers of oscillator elements. Lastly, we show that the combination of these two schemes yields immense benefits for signal detection. These benefits could be essential for male mosquitoes to be able to identify and pursue a particular female within a noisy swarm environment

Lattice-guided growth of dense arrays of aligned transition metal dichalcogenide nanoribbons with high catalytic reactivity

Transition metal dichalcogenides (TMDs) exhibit unique properties and potential applications when reduced to one-dimensional (1D) nanoribbons (NRs), owing to quantum confinement and high edge densities. However, effective growth methods for self-aligned TMD NRs are still lacking. We demonstrate a versatile approach for lattice-guided growth of dense, aligned MoS2 NR arrays via chemical vapor deposition (CVD) on anisotropic sapphire substrates, without tailored surface steps. This method enables the synthesis of NRs with widths below 10 nm and longitudinal axis parallel to the zigzag direction, being also extensible to the growth of WS2 NRs and MoS2-WS2 hetero-nanoribbons. Growth is influenced by both substrate and CVD temperature, indicating the role of anisotropic precursor diffusion and substrate interaction. The 1D nature of the NRs was asserted by the observation of Coulomb blockade at low temperature. Pronounced catalytic activity was observed at the edges of the NRs, indicating their promise for efficient catalysis.41 pages, 27 figure

Plug-and-Play DISep: Separating Dense Instances for Scene-to-Pixel Weakly-Supervised Change Detection in High-Resolution Remote Sensing Images

Existing Weakly-Supervised Change Detection (WSCD) methods often encounter the problem of instance lumping under scene-level supervision, particularly in scenarios with a dense distribution of changed instances (i.e., changed objects). In these scenarios, unchanged pixels between changed instances are also mistakenly identified as changed, causing multiple changes to be mistakenly viewed as one. In practical applications, this issue prevents the accurate quantification of the number of changes. To address this issue, we propose a Dense Instance Separation (DISep) method as a plug-and-play solution, refining pixel features from a unified instance perspective under scene-level supervision. Specifically, our DISep comprises a three-step iterative training process: 1) Instance Localization: We locate instance candidate regions for changed pixels using high-pass class activation maps. 2) Instance Retrieval: We identify and group these changed pixels into different instance IDs through connectivity searching. Then, based on the assigned instance IDs, we extract corresponding pixel-level features on a per-instance basis. 3) Instance Separation: We introduce a separation loss to enforce intra-instance pixel consistency in the embedding space, thereby ensuring separable instance feature representations. The proposed DISep adds only minimal training cost and no inference cost. It can be seamlessly integrated to enhance existing WSCD methods. We achieve state-of-the-art performance by enhancing {three Transformer-based and four ConvNet-based methods} on the LEVIR-CD, WHU-CD, DSIFN-CD, SYSU-CD, and CDD datasets. Additionally, our DISep can be used to improve fully-supervised change detection methods. Code is available at https://github.com/zhenghuizhao/Plug-and-Play-DISep-for-Change-Detection.Accepted by ISPRS Journal of Photogrammetry and Remote Sensin

Electron-phonon coupling in lattice engineering of lithium niobate single crystal thin films

Lithium niobate (LN) single crystal thin films are a high-performance photonic platform with applications in electro-optic modulators, nonlinear optical devices, optical frequency combs, and acousto-optic modulators. LN\u27s significance in photonics parallels silicon\u27s in electronics, addressing challenges like high power consumption and slow communication speeds, and offering potential for broad applications in optical communications, quantum computing, and artificial intelligence. Despite progress in developing LN-based photonic structures, achieving low-loss, reconfigurable, and large-scale devices requires improved processing techniques. This work introduces a quantum design methodology based on LN\u27s crystal structure, utilizing electron-phonon coupling through external field perturbations. Multiscale structural analysis is performed with techniques such as time-of-flight secondary ion mass spectrometry, aberration-corrected transmission electron microscopy, and X-ray absorption spectra to identify and control defect structures. Angle-resolved Raman spectroscopy, femtosecond transient absorption spectroscopy, and Density Functional Theory further reveal the mechanisms of electron-phonon coupling. These findings establish a framework for designing LN-based quantum devices with enhanced performance and diverse functionalities

Subdivergence-free gluings of trees

A gluing of two rooted trees is an identification of their leaves and un-subdivision of the resulting 2-valent vertices. A gluing of two rooted trees is subdivergence free if it has no 2-edge cuts with both roots on the same side of the cut. The problem and language is motivated by quantum field theory. We enumerate subdivergence-free gluings for certain families of trees, showing a connection with connected permutations, and we give algorithms to compute subdivergence-free gluings.minor edits according to referee comments, 20 page

A Magneto-Optical Trap of Titanium Atoms

We realize laser cooling and trapping of titanium (Ti) atoms in a mangeto-optical trap (MOT). While Ti does not possess a transition suitable for laser cooling out of its $\mathrm{3d^24s^2}$ $\mathrm{a^3F}$ ground term, there is such a transition, at an optical wavelength of $λ=498\mathrm{nm}$, from the long-lived $\mathrm{3d^3(^4F)4s}$ $\mathrm{a^5F_5}$ metastable state to the $\mathrm{3d^3(^4F)4p}$ $\mathrm{y^5G^o_6}$ excited state. Without the addition of any repumping light, we observe MOTs of metastable $\mathrm{^{46}Ti}$, $\mathrm{^{48}Ti}$, and $\mathrm{^{50}Ti}$, the three stable nuclear-spin-zero bosonic isotopes of Ti. While MOTs can be observed when loaded directly from our Ti sublimation source, optical pumping of ground term atoms to the $\mathrm{a^5F_5}$ state increases the loading rate by a factor of 120, and the steady-state MOT atom number by a factor of 30. At steady state, the MOT of $\mathrm{^{48}Ti}$ holds up to $8.30(26)\times10^5$ atoms at a maximum density of $1.3(4)\times10^{11}\mathrm{cm}^{-3}$ and at a temperature of $90(15)\mathrm{μK}$. By measuring the decay of the MOT upon suddenly reducing the loading rate, we place upper bounds on the leakage branching ratio of the cooling transition $(\leq2.5\times 10^{-6})$ and the two-body loss coefficient $(\leq2\times10^{-10}\mathrm{cm}^3\mathrm{s}^{-1})$. Our approach to laser cooling Ti can be applied to other transition metals, enabling a significant expansion of the elements that can be laser cooled.6 pages, 4 figures, 1 tabl

Global Minimization of Electronic Hamiltonian 1-Norm via Linear Programming in the Block Invariant Symmetry Shift (BLISS) Method

The cost of encoding a system Hamiltonian in a digital quantum computer as a linear combination of unitaries (LCU) grows with the 1-norm of the LCU expansion. The Block Invariant Symmetry Shift (BLISS) technique reduces this 1-norm by modifying the Hamiltonian action on only the undesired electron-number subspaces. Previously, BLISS required a computationally expensive nonlinear optimization that was not guaranteed to find the global minimum. Here, we introduce various reformulations of this optimization as a linear programming problem, which guarantees optimality and significantly reduces the computational cost. We apply BLISS to industrially-relevant homogeneous catalysts in active spaces of up to 76 orbitals, finding substantial reductions in both the spectral range of the modified Hamiltonian and the 1-norms of Pauli and fermionic LCUs. Our linear programming techniques for obtaining the BLISS operator enable more efficient Hamiltonian simulation and, by reducing the Hamiltonian\u27s spectral range, offer opportunities for improved LCU groupings to further reduce the 1-norm

A Fréchet Lie group on distributions

Solving non-autonomous systems of ordinary differential equations leads to consider a new product of bivariate distributions called the $\star$~product in the literature. This product, distinct from the convolution product, has recently been used to establish structural results concerning non-autonomous differential systems, yet its formal underpinnings remain unclear. We demonstrate that it is well-defined on the weak closure of the space of smooth functions on a compact subset of $\mathbb{R}^2$. We establish that a subset of this weak closure has the structure of a Fréchet space $\mathcal{D}$. The $\star$~product arises from the composition of endomorphisms of that space. Invertible elements of $\mathcal{D}$ form a dense subset of it and a Fréchet Lie group for the operation $\star$. This product generalizes the convolution, Volterra compositions of first and second type and induces Schwartz\u27s bracket

Deriving Coding-Specific Sub-Models from LLMs using Resource-Efficient Pruning

Large Language Models (LLMs) have demonstrated their exceptional performance in various complex code generation tasks. However, their broader adoption is limited by significant computational demands and high resource requirements, particularly memory and processing power. To mitigate such requirements, model pruning techniques are used to create more compact models with significantly fewer parameters. However, current approaches do not focus on the efficient extraction of programming-language-specific sub-models. In this work, we explore the idea of efficiently deriving coding-specific sub-models through unstructured pruning (i.e., Wanda). We investigate the impact of different domain-specific calibration datasets on pruning outcomes across three distinct domains and extend our analysis to extracting four language-specific sub-models: Python, Java, C++, and JavaScript. We are the first to efficiently extract programming-language-specific sub-models using appropriate calibration datasets while maintaining acceptable accuracy w.r.t. full models. We are also the first to provide analytical evidence that domain-specific tasks activate distinct regions within LLMs, supporting the creation of specialized sub-models through unstructured pruning. We believe that this work has significant potential to enhance LLM accessibility for coding by reducing computational requirements to enable local execution on consumer-grade hardware, and supporting faster inference times critical for real-time development feedback