Dynamic Fingerprint Research Articles

Scanning Acousto-Optoelectric Spectroscopy on a Transition Metal Dichalcogenide Monolayer.

The charge carrier dynamics are investigated by surface acoustic waves (SAWs) inside a WSe2 monolayer on LiNbO3 by scanning acousto-optoelectric spectroscopy. A strong enhancement of the PL emission intensity is observed almost over the entire area of the flake. This enhancement increases with increasing amplitude of the wave and is especially strong at or in the vicinity to defects. The latter is attributed to the SAW-driven Poole-Frenkel activation of trapped charge carriers bound to trapping sites at these defects. In addition, the PL intensity exhibit clear periodic modulations at the SAW's frequencyfSAW and at 2 fSAW. These modulations are clear and unambiguous fingerprints of spatio-temporal carrier dynamics driven by the SAW. These occur on sub-nanosecond timescales which are found in good agreement with calculated exciton dissociation times. Mapping and analyzing both effects, this study shows that scanning acousto-electric spectroscopy provides a highly sensitive and local contact-free probe which uncovers distinct local features not resolved by conventional quasi-static photoluminescence techniques. The method is ideally suited to study carrier transport in 2D and other types of nanoscale materials and to reveal dynamic exciton modulation, and carrier localization and activation dynamics in the technologically important megahertz to gigahertz frequency range.

Muon spin relaxation study of spin dynamics on a Kitaev honeycomb material H3LiIr2O6

The vacancy effect in quantum spin liquid (QSL) has been extensively studied. A finite density of random vacancies in the Kitaev model can lead to a pileup of low-energy density of states (DOS), which is generally experimentally determined by a scaling behavior of thermodynamic or magnetization quantities. Here, we report detailed muon spin relaxation (μSR) results of H3LiIr2O6, a Kitaev QSL candidate with vacancies. The absence of magnetic order is confirmed down to 80 mK, and the spin fluctuations are found to be persistent at low temperatures. Intriguingly, the time-field scaling law of longitudinal-field (LF)-μSR polarization is observed down to 0.1 K. This indicates a dynamical scaling, whose critical exponent of 0.46 is excellently consistent with the scaling behavior of specific heat and magnetization data. All the observations point to the finite DOS with the form N(E)∼E−ν\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$N(E)\\sim {E}^{-\ u }$$\\end{document}, which is expected for the Kitaev QSL in the presence of vacancies. Our μSR study provides a dynamical fingerprint of the power-law low-energy DOS and introduces a crucial new insight into the vacancy effect in QSL.

An experimental approach on dynamic occlusal fingerprint analysis to simulate use-wear localisation and development on stone tools

Information about the use of stone tools in the past is encoded in the wear patterns left on their surface; however, post-depositional processes can modify and obstruct these traces. One aim in the field of lithic functional analysis is to develop methods to detect and quantify these traces on stone tools. The occlusal fingerprint analysis (OFA) is a well-established method in dental wear studies to virtually simulate dental occlusal (contact between teeth) stroke movements and thus locate and quantify the sequential contact between opposing tooth crowns. Reaching across disciplines, we conducted controlled experiments to test the applicability of the OFA method on stone tools to address the challenge of use-wear quantification and localisation, and therefore the identification of post-depositional wear. Our findings reveal a clear overlap between zones of experimentally produced use-wear and OFA-calculated contact areas. We demonstrate OFA as a potential method to generate models of multiscale use-wear that can be used as references on experimental tools to identify post-depositional surface modifications on stone tool artefacts.

Single-Cell Fluidic Force Spectroscopy Reveals Dynamic Mechanical Fingerprints of Malignancy in Breast Cancer.

The interplay between cancer cell physical characteristics and metastatic potential highlights the significance of cancer cell mechanobiology. Using fluidic-based single-cell force spectroscopy (SCFS), quartz crystal microbalance with dissipation (QCM-D), and a model of cells with a spectrum of metastatic potential, we track the progression of biomechanics across the metastatic states by measuring cell-substrate and cell-to-cell adhesion forces, cell spring constant, cell height, and cell viscoelasticity. Compared to highly metastatic cells, cells in the lower spectrum of metastatic ability are found to be systematically stiffer, less viscoelastic, and larger. These mechanical transformations in cells within a cluster correlate with cells' metastatic potential but are significantly absent in single cells. Additionally, the response to chemotherapy is found to be highly dependent on cell viscoelastic properties in terms of both response time and magnitude. Shifts in cell softness and elasticity might serve as mechanoadaptive mechanisms during cancer cell metastasis, contributing to our understanding of metastasis and the effectiveness of potential therapeutic interventions.

Characterization of aroma dynamic changes during six developing stages of yellow cultivar Flammulina filiformis based on E-Nose, GC×GC-TOF MS, GC-IMS, and GC-O-MS

The aroma volatiles of Flammulina filiformis (F. filiformis) had notably dynamic changes during various developing stages. However, the dynamic fingerprints of the overall aroma volatiles during mushroom development remained largely unknown in F. filiformis. The purpose of this study was to characterize the dynamic changes in the aroma volatiles of yellow cultivar F. filiformis using E-Nose, GC-MS/O, GC-IMS, and GC × GC-TOF MS. A total of 140 volatiles were characterized (about 59% by GC × GC-TOF MS). Phenylacetaldehyde, 2-octenal, hexanal, nonanal, 2,4-decadienal, β-citronellol, 3-octanone, 1-octen-3-one, 2-methylpropyl butanoate, limonene, and 2-pentyl-furan were identified as key aroma compounds. The richness of odorants (numbers and concentrations) was most abundant during the initial stage of fruiting (with a fruity note). The concentrations of C8 volatiles and ketones gradually decreased before the mature stage, followed by a slight increase (with mushroom and sweet notes). An excellent correlation was observed between the changes in aroma attributes corresponding to odorants. Furthermore, the correlation between the volatile contents could be well explained by metabolic pathways (unsaturated fatty acids, β-oxidation of saturated fatty acids, and Ehrlich pathways for amino acids). Overall, this study provides insights into the metabolic pathways of volatiles potential for aroma quality enhancement in F. filiformis.

Autonomous and reliable fingerprint map maintenance for indoor positioning system

In WiFi-based crowdsourced fingerprinting indoor positioning systems (IPS), the signal space of WiFi APs changes over time. To autonomously maintain a highly reliable localization accuracy, the fingerprint database needs regular maintenance and updates. However, this process is labor-intensive and time-consuming due to the appearance of faulty access points (APs) in crowdsourced samples received from target clients, which are mainly used for autonomous maintenance and updates. Additionally, if some APs are relocated, removed, or replaced in the indoor environment after fingerprint map construction, it can severely impact IPS accuracy. In this paper, we present Dynamic Online Fingerprint Learning with Altered APs status-aware and updating (DOFLAAU) for IPS. Our systematic methodology involves several key steps. First, we employ the Modified Group Method of Data Handling (GMDH) neural network regression for autonomous AP status monitoring and alteration detection. Next, we perform autonomous APs subset sample selection using a modified Thomson model, followed by outlier feature detection and removal based on the weighted sample density rate. Thirdly, we propose a dynamic online fingerprint map updating model using the cosine similarity distance metric. Lastly, we adopted an effective signal distance-based weighted k-nearest neighbor algorithm to improve IPS accuracy. The experiment results validate the efficiency and effectiveness of our proposed algorithms in terms of better localization accuracy compared to peer algorithms.

Photo-induced collective charge-density-wave dynamics in bulk 1T-VSe2

We investigated temperature (T) and excitation density dependent ultrafast near-infrared (NIR) transient reflectivity dynamics in the charge density wave (CDW) phases of bulk layered 1T-VSe2 using NIR and visible excitations. The data reveal fingerprints of conventional non-adiabatic CDW collective dynamics with rather fast electronic order parameter dynamics showing sub-picosecond suppression and recovery. The slower T-dependent 100-ps dynamics indicates rather isotropic heat transport dominated by the lattice degrees of freedom.

Time-resolved photoelectron diffraction imaging of methanol photodissociation involving molecular hydrogen ejection.

Imaging ultrafast atomic and molecular hydrogen motion with femtosecond time resolution is a challenge for ultrafast spectroscopy due to the low mass and small scattering cross section of the moving neutral hydrogen atoms and molecules. Here, we propose time- and momentum-resolved photoelectron diffraction (TMR-PED) as a way to overcome limitations of existing methodologies and illustrate its performance using a prototype molecular dissociation process involving the sequential ejection of a neutral hydrogen molecule and a proton from the methanol dication. By combining state-of-the-art molecular dynamics and electron-scattering methods, we show that TMR-PED allows for direct imaging of hydrogen atoms in action. More specifically, the fingerprint of hydrogen dynamics reflects the time evolution of polarization-averaged molecular-frame photoelectron angular distributions (PA-MFPADs) as would be recorded in X-ray pump/X-ray probe experiments with few-femtosecond resolution. We present the results of two precursor experiments that support the feasibility of this approach.

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder.

The accurate representation of the structural and dynamical properties of water is essential for simulating the unique behavior of this ubiquitous solvent. Here we assess the current status of describing liquid water using ab initio molecular dynamics, with a special focus on the performance of all the later generation Minnesota functionals. Findings are contextualized within the current knowledge on DFT for describing bulk water under ambient conditions and compared to experimental data. We find that, contrary to the prevalent idea that local and semilocal functionals overstructure water and underestimate dynamical properties, M06-L, revM06-L, and M11-L understructure water, while MN12-L and MN15-L overdistance water molecules due to weak cohesive effects. This can be attributed to a weakening of the hydrogen bond network, which leads to dynamical fingerprints that are over fast. While most of the hybrid Minnesota functionals (M06, M08-HX, M08-SO, M11, MN12-SX, and MN15) also yield understructured water, their dynamical properties generally improve over their semilocal counterparts. It emerges that exact exchange is a crucial component for accurately describing hydrogen bonds, which ultimately leads to corrections in both the dynamical and structural properties. However, an excessive amount of exact exchange strengthens hydrogen bonds and causes overstructuring and slow dynamics (M06-HF). As a compromise, M06-2X is the best performing Minnesota functional for water, and its D3 corrected variant shows very good structural agreement. From previous studies considering nuclear quantum effects (NQEs), the hybrid revPBE0-D3, and the rung-5 RPA (RPA@PBE) have been identified as the only two approximations that closely agree with experiments. Our results suggest that the M06-2X(-D3) functionals have the potential to further improve the reproduction of experimental properties when incorporating NQEs through path integral approaches. This work provides further proof that accurate modeling of water interactions requires the inclusion of both exact exchange and balanced (non-local) correlation, highlighting the need for higher rungs on Jacob's ladder to achieve predictive simulations of complex biological systems in aqueous environments.

Exhaled VOC Biomarkers from Rats Injected with PMs from Thirty-One Major Cities in China.

Particulate matter (PMs) of different origins can cause diverse health effects. Here, a homemade box was used to facilitate real-time measurements of breath-borne volatile organic compounds (VOCs) by gas chromatography-ion mobility spectrometry. We have tracked exhaled VOC changes in 228 Wistar rats that were injected with water-soluble PM suspension filtrates (after 0.45 μm) from 31 China cities for 1 h to up to 1-6 days during the experiments. Rats exposed to the filtrates exhibited significant changes in breath-borne VOCs within hours, featuring dynamic fluctuations in the levels of acetone, butan-2-one, heptan-2-one-M, acetic acid-M, and ethanol. Subsequently, on the fifth to sixth day after the injection, there was a notable increase in the proportion of aldehydes (including hexanal-M, hexanal-D, pentanal, heptanal-M, and (E)-2-hexenal). The 10 dynamic VOC fingerprint patterns mentioned earlier showcased the capability to indirectly differentiate urban PM toxicity and categorize the 31 cities into four distinct groups based on their health effects. This study provides valuable insights into the mechanisms of exhaled VOCs and underscores their critical role as biomarkers for differentiating the toxicity of different PMs and detecting the early signs of potential diseases. The results from this work also provide a scientific basis for city-specific air pollution control and policy development.

Unusual Dynamics and Vibrational Fingerprints of van der Waals Dimers Formed by Linear Molecules and Rare-Gas Atoms.

Detailed structural, dynamical, and vibrational analyses have been performed for systems composed of linear triatomic molecules solvated by a single rare-gas atom, He, Ne, or Ar. Among the chromophores of these van der Waals (vdW) dimers, there are four neutral molecules (CO2, CS2, N2O, and OCS) and six molecular cations (HHe2+, HNe2+, HAr2+, HHeNe+, HHeAr+, and HNeAr+), both of apolar and polar nature. Following the exploration of bonding preferences, high-level four-dimensional (4D) potential energy surfaces (PESs) have been developed for 24 vdW dimers, keeping the two intramonomer bond lengths fixed. For these 24 complexes, over 1500 bound vibrational states have been obtained via quasi-variational nuclear-motion computations, employing exact kinetic-energy operators together with the accurate 4D PESs and their 2D/3D cuts. The reduced-dimensional (2D to 4D) dimer models have been compared with full-dimensional (6D) ones in the cases of the neutral CO2·Ar and charged HHe2+·He dimers, corroborating the high accuracy of the 2D to 4D vibrational energies. The reduced-dimensional models suggest that (a) while the equilibrium structures are T-shaped and planar, the effective ground-state structures are nonplanar, (b) certain bound states belong to collinear molecular structures, even when they are not minima, (c) the vdW vibrations are heavily mixed and many states have amplitudes corresponding to both the T-shaped and collinear structures, (d) there are a few dimers, for which even some of the vdW fundamentals lie above the first dissociation limit, and (e) the vdW vibrations are almost fully decoupled from the intramonomer bending motion.

Photoluminescence Mapping over Laser Pulse Fluence and Repetition Rate as a Fingerprint of Charge and Defect Dynamics in Perovskites

AbstractDefects in metal halide perovskites (MHP) are photosensitive, making the observer effect unavoidable when laser spectroscopy methods are applied. Photoluminescence (PL) bleaching and enhancement under light soaking and recovery in dark are examples of the transient phenomena that are consequent to the creation and healing of defects. Depending on the initial sample composition, environment, and other factors, the defect nature and evolution can strongly vary, making spectroscopic data analysis prone to misinterpretations. Herein, the use of an automatically acquired dependence of PL quantum yield (PLQY) on the laser pulse repetition rate and pulse fluence as a unique fingerprint of both charge carrier dynamics and defect evolution is demonstrated. A simple visual comparison of such fingerprints allows for assessment of similarities and differences between MHP samples. The study illustrates this by examining methylammonium lead triiodide (MAPbI3) films with altered stoichiometry that just after preparation showed very pronounced defect dynamics at time scale from milliseconds to seconds, clearly distorting the PLQY fingerprint. Upon weeks of storage, the sample fingerprints evolve toward the standard stoichiometric MAPbI3 in terms of both charge carrier dynamics and defect stability. Automatic PLQY mapping can be used as a universal method for assessment of perovskite sample quality.

An investigation on space debris of unknown origin using proper elements and neural networks

Proper elements represent a dynamical fingerprint of an object’s inherent state and have been used by small-body taxonomists in characterizing asteroid families. Being linked to the underlying dynamical structure of orbits, Celletti, Pucacco, and Vartolomei have recently adopted these innate orbital parameters for the association of debris from breakup or collision into its parent satellite. Building from this rich astronomical heritage and recent foundations, we introduce an unsupervised learning method—density-based spatial clustering of applications with noise (DBSCAN)—to determine clusters of orbital debris in the space of proper elements. Data is taken from the space-object catalog of trackable Earth-orbiting objects in the form of two-line element sets. Proper elements for debris fragments in low-Earth orbit are computed using an ad hoc numerical scheme, akin to the state-of-the-art Fourier-series-based synthetic method for the asteroid domain. Given the heuristic nature of classical DBSCAN, we investigate the use of neural networks, trained on known families, to augment DBSCAN into a classification problem and apply it to analyst objects of unknown origin.

Dynamic Magnetic Resonance Vascular Fingerprinting During Hypercapnia for Quantitative and Multiparametric Cerebrovascular Reactivity Measures.

Magnetic resonance fingerprinting (MRF) represents a potential paradigm shift in MR image acquisition, reconstruction, and analysis using computational biophysical modelling in parallel to image acquisition. Its flexibility allows for examination of cerebrovascular metrics through MR vascular fingerprinting (MRvF), and this has been extended even further to produce quantitative cerebral blood volume (CBV), microvascular vessel radius, and tissue oxygen saturation (SO2) maps of the whole brain simultaneously every few seconds. This allows for observation of rapid physiological changes like cerebrovascular reactivity (CVR), which is the ability of vessels to dilate in response to a vasoactive stimulus. Here we demonstrated a novel protocol in which a rapid, spin- and gradient-echo pulse sequence allowed for dynamic, and simultaneous acquisition of MRvF and blood oxygen level dependent (BOLD) measures. By combining this with a tailored hypercapnic (5% CO2) breathing paradigm we were able to show how these quantitative CBV, radius, and SO2 parameters changed in response to a stimulus and directly compare those to a colocalized, traditionally used BOLD CVR. We also compared these measures to another traditionally utilized technique in cerebral blood flow CVR from an arterial spin labelling sequence. These imaging, processing, and analysis techniques will allow for further investigation into the magnitude and rate of CVR based on BOLD and MRvF-based metrics and enable investigations to better understand vascular function in healthy aging and cerebrovascular diseases.Clinical Relevance- The development of dynamic magnetic resonance vascular fingerprinting has the potential to enable rapid, quantitative, and multiparametric functional imaging biomarkers of cerebrovascular diseases like vascular cognitive impairment, dementia, and Alzheimer's disease.

The dynamic functional connectivity fingerprint of high-grade gliomas

Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients’ cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.

Massive Galaxy Clusters Like El Gordo Hint at Primordial Quantum Diffusion

It is generally assumed within the standard cosmological model that initial density perturbations are Gaussian at all scales. However, primordial quantum diffusion unavoidably generates non-Gaussian, exponential tails in the distribution of inflationary perturbations. These exponential tails have direct consequences for the formation of collapsed structures in the Universe, as has been studied in the context of primordial black holes. We show that these tails also affect the very-large-scale structures, making heavy clusters like "El Gordo," or large voids like the one associated with the cosmic microwave background cold spot, more probable. We compute the halo mass function and cluster abundance as a function of redshift in the presence of exponential tails. We find that quantum diffusion generically enlarges the number of heavy clusters and depletes subhalos, an effect that cannot be captured by the famed f_{NL} corrections. These late-Universe signatures could, thus, be fingerprints of quantum dynamics during inflation that should be incorporated in N-body simulations and checked against astrophysical data.

Evolution of binary stars in the early evolutionary phases of ultra-faint dwarf galaxies

ABSTRACT The dynamics of binary stars provides a unique avenue to gather insight into the study of the structure and dynamics of star clusters and galaxies. In this paper, we present the results of a set of N-body simulations aimed at exploring the evolution of binary stars during the early evolutionary phases of ultra-faint dwarf galaxies (UFD). In our simulations, we assume that the stellar component of the UFD is initially dynamically cold and evolves towards its final equilibrium after undergoing the violent relaxation phase. We show that the early evolutionary phases of the UFD significantly enhance the disruption of wide binaries and leave their dynamical fingerprints on the semimajor axis distribution of the surviving binaries as compared to models initially in equilibrium. An initially thermal eccentricity distribution is preserved except for the widest binaries for which it evolves towards a superthermal distribution; for a binary population with an initially uniform eccentricity distribution, memory of this initial distribution is rapidly lost for most binaries as wider binaries evolve to approach a thermal/superthermal distribution. The evolution of binaries is driven both by tidal effects due to the potential of the UFD dark matter halo and collisional effects associated to binary–binary/single star encounters. Collisional effects are particularly important within the clumpy substructure characterizing the system during its early evolution; in addition to enhancing binary ionization and evolution of the binary orbital parameters, encounters may lead to exchanges of either of the primordial binary components with one of the interacting stars.

SoundID: Securing Mobile Two-Factor Authentication via Acoustic Signals

Mobile two-factor authentication (TFA), which uses mobile devices as a second security layer of protection to online accounts, has been widely applied with the proliferation of mobile phones. Currently, many studies propose to use acoustic fingerprints as the second factor. However, these solutions ignore the variations of the extracted static acoustic fingerprints incurred by the acoustic propagation process, which we show can be leveraged to develop an enhanced man-in-the-middle (MITM) attack to compromise the security strength of these systems, while hiding the traces of the attacking devices. To address this newly-uncovered vulnerability, we propose SoundID, a secure and novel authentication system that introduces a dual challenge-response design through the acoustic signals of the enrolled phone and the login device. Specifically, the enrolled phone first evaluates its proximity to the login device by the similarity of their audio recordings, and then the login authentication server compares the calculated dynamic acoustic fingerprint with the one received from the enrolled phone. To the best of our knowledge, SoundID is the first scheme that extracts dynamic acoustic fingerprints and can effectively defend against the enhanced MITM attack. SoundID combines the benefits of unpredictable influencing factors of acoustic propagation processes and the stable frequency response of the acoustic hardware, whose high complexity prevents attackers from predicting or impersonating them. We build a prototype of SoundID with off-the-shelf smartphones to validate its robustness and effectiveness. Our results show that SoundID is user-friendly and achieves over 96.62% accuracy with an equal error rate around 4.27%.

Resolving Complex Photoconductivity of Perovskite and Organic Semiconductor Films Using Phase-Sensitive Microwave Interferometry

Complex transient photoconductivity (Δσ) contains rich fingerprints of charge recombination dynamics in photoactive films. However, a direct measure of both real (Δσ′) and imaginary (Δσ″) components has proven difficult using conventional cavity-based time-resolved microwave conductivity approaches. Here, we present a novel approach to resolve Δσ′ and Δσ″ parts of Δσ by using a nonresonant coplanar transmission line and a microwave interferometric detection scheme. The use of a phase-sensitive microwave interferometer greatly increases the measurement sensitivity and eliminates the requirement of a resonant cavity. This broadband detection scheme allows for direct measurement of Δσ. The relationship between the experimental phase shift and Δσ′ and Δσ″ components is decoded through an in situ electron spin resonance (ESR) measurement. ESR line shape analysis is used to confirm the assignment of the transients to the Δσ′ and Δσ″ components. We demonstrate the utility of this technique on thin films of poly(3-hexylthiophene): [6,6]-phenylC61-butyric acid methyl ester (P3HT:PCBM) and perovskite MA0.85FA0.15PbI3 films on glass.

Pre-eruptive dynamics at the Campi Flegrei Caldera: from evidence of magma mixing to timescales estimates

We review pre-eruptive dynamics and evidence of open-system behavior in the volcanic plumbing system beneath Campi Flegrei Caldera, together with estimates of magma residence time, magma ascent, and mixing-to-eruption timescales. In detail, we compile pre- and syn-eruptive dynamics reported in the literature for (a) the Campanian Ignimbrite ~ 40 ka, (b) the Neapolitan Yellow Tuff (~ 15 ka), and (c) the recent activity within the Phlegrean area. We first summarize geochemical and textural evidence (e.g., magma mixing, crystal disequilibria, vertical zonings, and isotopic records) of open-system behavior for the pyroclasts erupted in the last 40 ky at Campi Flegrei Caldera. We show that the fingerprint of open-system dynamics is ubiquitous in the deposits associated with the volcanic activity at the Campi Flegrei Caldera in the last 40 ky. Then, we describe the results of geophysical and petrological investigations that allow us to hypothesize the structure of the magma feeding system. We point to a trans-crustal magmatic feeding system characterized by a main storage reservoir hosted at ~ 9 km that feeds and interacts with shallow reservoirs, mainly placed at 2–4 km. Finally, we define a scenario depicting pre-eruptive dynamics of a possible future eruption and provide new constraints on timescales of magma ascent with a physical model based on magma-driven ascending dyke theory. Results show that considerably fast ascent velocities (i.e., of the order of m/s) can be easily achieved for eruptions fed by both shallow (i.e., 3–4 km) and deep (i.e., ~ 9 km) reservoirs. Comparing the results from experimental and numerical methods, it emerges that mixing-to-eruption timescales occurring at shallow reservoirs could be on the order of minutes to hours. Finally, we highlight the volcanological implications of our timescale estimates for magma ascent and mixing to eruption. In particular, explosive eruptions could begin with little physical ‘warning’, of the order of days to months. In this case, the onset of volatile saturation might provide pre-eruptive indicators.Graphical