Fast and inefficient star formation due to short-lived molecular clouds and rapid feedback

TL;DR

This study reveals that star formation in molecular clouds is rapid and inefficient, driven by stellar feedback that disperses clouds within about 10 million years, explaining the slow overall star formation rate in galaxies.

Contribution

It introduces a novel statistical method to quantify GMC evolution, demonstrating that feedback limits cloud lifetimes and star formation efficiency, advancing understanding of galaxy-scale star formation processes.

Findings

GMCs and star formation are spatially de-correlated on small scales.

Stellar feedback disperses GMCs within ~1.5 Myr.

Star formation efficiency in GMCs is only 2-3%.

Abstract

The physics of star formation and the deposition of mass, momentum, and energy into the interstellar medium by massive stars (`feedback') are the main uncertainties in modern cosmological simulations of galaxy formation and evolution. These processes determine the properties of galaxies, but are poorly understood on the $\lesssim$100 pc scale of individual giant molecular clouds (GMCs) resolved in modern galaxy formation simulations. The key question is why the timescale for depleting molecular gas through star formation in galaxies ($t_{\rm dep}\approx 2$ Gyr) exceeds the dynamical timescale of GMCs by two orders of magnitude. Either most of a GMC's mass is converted into stars over many dynamical times, or only a small fraction turns into stars before the GMC is dispersed on a dynamical timescale. Here we report our observation that molecular gas and star formation are spatially de-correlated on GMC scales in the nearby flocculent spiral galaxy NGC300, contrary to their tight correlation on galactic scales. We demonstrate that this de-correlation implies rapid evolutionary cycling between GMCs, star formation, and feedback. We apply a novel statistical method to quantify the evolutionary timeline and find that star formation is regulated by efficient stellar feedback, driving GMC dispersal on short timescales (~1.5 Myr) due to radiation and stellar winds, prior to supernova explosions. This feedback limits GMC lifetimes to about one dynamical timescale (~10 Myr), with integrated star formation efficiencies of only 2-3%. Our findings reveal that galaxies consist of building blocks undergoing vigorous, feedback-driven lifecycles, that vary with the galactic environment and collectively define how galaxies form stars. Systematic applications of this multi-scale analysis to large galaxy samples will provide key input for a predictive, bottom-up theory of galaxy formation and evolution.

Figures

Tables

Table 1. Table 1: Constrained quantities describing cloud-scale star formation and feedback. For various (independent and overlapping) intervals in galactocentric radius, the table lists the GMC lifetime ( t CO subscript 𝑡 CO t_{\rm CO} ), the feedback timescale ( t fb subscript 𝑡 fb t_{\rm fb} ), the region separation length ( λ 𝜆 \lambda ), the integrated SFE ( ϵ sf subscript italic-ϵ sf \epsilon_{\rm sf} ), the mass loading factor ( η fb subscript 𝜂 fb \eta_{\rm fb} ), the feedback outflow velocity ( v fb subscript 𝑣 fb v_{\rm fb} ), and the χ red 2 superscript subscript 𝜒 red 2 \chi_{\rm red}^{2} statistic of the model fit.

Radial interval	$t_{\mathrm{CO}}$	$t_{\mathrm{fb}}$	$\lambda$	${ϵ}_{\mathrm{sf}}$	${\eta }_{\mathrm{fb}}$	$v_{\mathrm{fb}}$	${\chi }_{\mathrm{red}}^2$
$\left[\mathrm{kpc}\right]$	$\left[\mathrm{Myr}\right]$	$\left[\mathrm{Myr}\right]$	$\left[\mathrm{pc}\right]$	$[\%]$	$[-]$	$\left[\mathrm{km}{s}^{-1}\right]$	$[-]$
$0.0$–$3.0$	${10.8}_{-1.7}^{+2.1}$	${1.5}_{-0.2}^{+0.2}$	${104}_{-18}^{+22}$	${2.5}_{-1.1}^{+1.9}$	${40}_{-18}^{+31}$	${9.4}_{-0.7}^{+0.8}$	$0.71$
$0.0$–$1.5$	${16.2}_{-3.9}^{+4.2}$	${1.8}_{-0.3}^{+0.3}$	${105}_{-22}^{+38}$	${2.6}_{-1.2}^{+2.1}$	${37}_{-17}^{+32}$	${8.1}_{-0.9}^{+1.3}$	$0.61$
$1.5$–$3.0$	${9.2}_{-1.6}^{+2.1}$	${1.4}_{-0.2}^{+0.1}$	${98}_{-21}^{+25}$	${2.3}_{-1.0}^{+1.8}$	${42}_{-19}^{+33}$	${9.8}_{-0.6}^{+1.2}$	$0.58$
$0.5$–$1.5$	${18.3}_{-4.4}^{+3.9}$	${1.6}_{-0.3}^{+0.4}$	${105}_{-28}^{+40}$	${2.8}_{-1.3}^{+2.1}$	${34}_{-15}^{+31}$	${9.0}_{-1.4}^{+1.2}$	$0.50$
$1.0$–$2.0$	${11.0}_{-2.0}^{+3.1}$	${1.7}_{-0.4}^{+0.3}$	${104}_{-23}^{+30}$	${2.2}_{-1.0}^{+1.9}$	${44}_{-20}^{+33}$	${8.8}_{-1.1}^{+1.8}$	$0.34$
$1.5$–$2.5$	${9.8}_{-1.8}^{+2.2}$	${1.5}_{-0.2}^{+0.1}$	${96}_{-20}^{+26}$	${2.6}_{-1.1}^{+2.0}$	${38}_{-17}^{+30}$	${9.3}_{-0.6}^{+1.0}$	$0.63$
$2.0$–$3.0$	${10.8}_{-2.2}^{+9.4}$	${1.4}_{-0.2}^{+1.7}$	${131}_{-45}^{+49}$	${2.7}_{-1.2}^{+3.7}$	${36}_{-22}^{+28}$	${10.5}_{-5.6}^{+1.5}$	$0.75$

Equations

$$\mathcal{B}(l_{\mathrm{ap}})=\frac{{\mathcal{F}}_{\mathrm{H}\alpha ,\mathrm{tot}}}{{\mathcal{F}}_{\mathrm{CO},\mathrm{tot}}}\frac{{\sum }_i{\mathcal{F}}_{\mathrm{CO},i}(l_{\mathrm{ap}})}{{\sum }_i{\mathcal{F}}_{\mathrm{H}\alpha ,i}(l_{\mathrm{ap}})},$$

$${\cal B}_{\rm H\alpha}(l_{\rm ap})=\frac{f_{\rm CO}\left[1+\beta_{\rm CO}^{-1}\left(\frac{t_{\rm CO}}{t_{\rm fb}}-1\right)\right]^{-1}+\frac{t_{\rm H\alpha}}{\mbox{$\tau$}}\left(\frac{l_{\rm ap}}{\mbox{$\lambda$}}\right)^{2}}{f_{\rm H\alpha}+\frac{t_{\rm H\alpha}}{\mbox{$\tau$}}\left(\frac{l_{\rm ap}}{\mbox{$\lambda$}}\right)^{2}},$$

$${\cal B}_{\rm CO}(l_{\rm ap})=\frac{f_{\rm CO}+\frac{t_{\rm CO}}{\mbox{$\tau$}}\left(\frac{l_{\rm ap}}{\mbox{$\lambda$}}\right)^{2}}{f_{\rm H\alpha}\left[1+\beta_{\rm H\alpha}^{-1}\left(\frac{t_{\rm H\alpha}}{t_{\rm fb}}-1\right)\right]^{-1}+\frac{t_{\rm CO}}{\mbox{$\tau$}}\left(\frac{l_{\rm ap}}{\mbox{$\lambda$}}\right)^{2}},$$

$$t_{\mathrm{H}\alpha ,\mathrm{ref}}=(4.32\pm 0.16\mathrm{Myr})\times (Z/{\mathrm{Z}}_{\odot }{)}^{-0.086\pm 0.017},$$

$${ϵ}_{\mathrm{sf}}=\frac{t_{\mathrm{CO}}}{t_{\mathrm{dep}}},$$

$${\eta }_{\mathrm{fb}}=\frac{1-{ϵ}_{\mathrm{sf}}}{{ϵ}_{\mathrm{sf}}},$$

$$v_{\mathrm{fb}}=\frac{r_{\mathrm{CO}}}{t_{\mathrm{fb}}}.$$

$$M_{\mathrm{ref}}=\pi {\left(\frac{\lambda }{2}\right)}^2\tau {\Sigma }_{\mathrm{SFR}},$$

$$\frac{\mathrm{d}p}{\mathrm{d}{r}_{\mathrm{n}}}=2\pi r_{\mathrm{n}}{\Sigma }_{\mathrm{reg},\mathrm{loc}}{\mathrm{e}}^{-\pi r_{\mathrm{n}}^2{\Sigma }_{\mathrm{reg},\mathrm{loc}}},$$

$$t_{\mathrm{phot}}=\frac{4}{7}{\left(\frac{3}{4}\right)}^{1/2}\frac{r_{\mathrm{S}}}{c_{\mathrm{s}}}\left[{\left(\frac{r_{\mathrm{stdev}}}{r_{\mathrm{S}}}\right)}^{7/4}-1\right],$$

$$r_{\mathrm{S}}={\left(\frac{3m_{\mathrm{H}}^2}{4\pi {\alpha }_B{X}_{\mathrm{H}}^2}\frac{{\dot{N}}_{\mathrm{LyC}}}{{\rho }_{\mathrm{GMC}}^2}\right)}^{1/3},$$

$$c_{\mathrm{s}}={\left(\frac{k_{\mathrm{B}}T}{\mu m_{\mathrm{H}}}\right)}^{1/2},$$

$$t_{\mathrm{wind}}={\left(\frac{154\pi }{125}\frac{{\rho }_{\mathrm{GMC}}}{L_{\mathrm{w}}}\right)}^{1/3}{r}_{\mathrm{stdev}}^{5/3},$$

$$\frac{t_{\rm cool}}{\mbox{${\rm Myr}$}}=2.9\left(\frac{Z}{{\rm 0.5Z}_{\odot}}\right)^{-35/22}\left(\frac{L_{\rm w}}{10^{30}~{}{\rm J}~{}{\rm s}^{-1}}\right)^{3/11}\left(\frac{\rho_{\rm GMC}}{20~{}\mbox{${\rm cm}^{-3}$}}\right)^{-8/11},$$

$$\tau_{\rm IR}=5.2\times 10^{-5}\left(\frac{\phi_{\rm tr}}{0.2}\right)\left(\frac{T_{\rm GMC}}{20~{}{\rm K}}\right)^{2}\left(\frac{\Sigma_{\rm GMC}}{13~{}\mbox{M${}_{\odot}$}~{}\mbox{${\rm pc}$}^{-2}}\right),$$

$$t_{\mathrm{rad}}={\left(\frac{2\pi c}{3}\frac{{\rho }_{\mathrm{GMC}}}{L_{\mathrm{bol}}}\right)}^{1/2}{r}_{\mathrm{stdev}}^2.$$

$$M_{\text{Hscii}}=\pi {\left(\frac{\lambda }{2}\right)}^2{ϵ}_{\mathrm{sf}}{\Sigma }_{\mathrm{gas}}.$$

$$l_{\mathrm{T}}=\frac{4{\pi }^{2}G{\Sigma }_{\mathrm{gas}}}{{\kappa }^2},$$

$$\kappa =\frac{v_{\mathrm{c}}}{R}{\left(1+\frac{\mathrm{d}\ln v_{\mathrm{c}}}{\mathrm{d}\ln R}\right)}^{1/2},$$

$$h_{\mathrm{gas}}=\frac{{\sigma }_{\mathrm{gas}}^2}{\pi G{\varphi }_P{\Sigma }_{\mathrm{gas}}},$$

$${\varphi }_P=1+\frac{{\Sigma }_{\star }}{{\Sigma }_{\mathrm{gas}}}\frac{{\sigma }_{\mathrm{gas}}}{{\sigma }_{\star }},$$

$${\sigma }_{\star }=2^{1/4}{\left(\pi G{h}_{\star }{\Sigma }_{\star }\right)}^{1/2}.$$

$$v_{\mathrm{shell}}=\frac{r_{\mathrm{stdev}}}{t_{\mathrm{shell}}},$$

Full text

†† {affiliations} Astronomisches Rechen-Institut, Zentrum für Astronomie der Universität Heidelberg, Mönchhofstraße 12-14, 69120 Heidelberg, Germany Max-Planck Institut für Astronomie, Königstuhl 17, 69117 Heidelberg, Germany Max-Planck Institut für Extraterrestrische Physik, Giessenbachstraße 1, 85748 Garching, Germany Astrophysics Research Institute, Liverpool John Moores University, IC2, Liverpool Science Park, 146 Brownlow Hill, Liverpool L3 5RF, United Kingdom Department of Astronomy, University of California Berkeley, Berkeley, CA 94720, USA Department of Physics & Astronomy, Texas Tech Univ., PO Box 41051, Lubbock, TX 79409, USA Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195, USA Leiden Observatory, Leiden University, P.O. Box 9513, NL-2300 RA, Leiden, the Netherlands

We carry out an empirical measurement to explain why t_{\rm dep}=t_{\rm sf}/\epsilon_{\rm sf}\approx 2~{}\mbox{{\rm Gyr}}, where $t_{\rm sf}$ and $\epsilon_{\rm sf}$ represent degenerate quantities: $t_{\rm sf}$ is the timescale over which gas is turned into stars and $\epsilon_{\rm sf}$ represents the fraction of mass converted into stars (the ‘star formation efficiency’ or SFE). If star formation within GMCs is slow and efficient (long $t_{\rm sf}$, high $\epsilon_{\rm sf}$), GMCs and young stars are co-spatial for many dynamical times. If star formation is fast and inefficient (short $t_{\rm sf}$, low $\epsilon_{\rm sf}$), they should rarely coincide. Therefore, measurements of the spatial correlation between gas and young stars discriminate between these two scenarios.

We characterise the lifecycle of GMCs and star-forming regions by applying a new statistical method[16] to maps of the molecular gas and emission from young massive stars in NGC300. This method requires observational data at high sensitivity and resolution over a large field-of-view, now available with the Atacama Large Millimeter/submillimeter Array (ALMA). NGC300 is the perfect target for the first application of this method, as it is the closest ($D=2$ Mpc), face-on, star-forming disc galaxy accessible from the southern hemisphere. Figure 1 (left) shows the molecular gas traced by our high-resolution (2^{\prime\prime}=20~{}\mbox{{\rm pc}}) ALMA map of CO(1-0). We combine this with a matched-resolution map of H$\alpha$-emitting Hii regions from the MPG/ESO 2.2-m telescope to trace recent star formation. The use of H$\alpha$ means that we define ‘star formation’ to refer to an unembedded stellar population, with a mass of at least 200~{}\mbox{M{}_{\odot}} and a normal stellar initial mass function (see Methods).

We characterise the correlation between GMCs and star formation by placing apertures on peaks of CO(1-0) or H$\alpha$ emission, and measuring how the enclosed CO-to-H$\alpha$ flux ratios are elevated or suppressed, respectively, relative to the galactic average as the aperture size is changed (Figure 1 and Supplementary Video 1)[17, 15]. The shorter-lived of these two tracers will be rare compared to the longer-lived, more common one. Only a small number of apertures are required to cover the complete sample of rare, short-lived emission peaks. These will encompass a relatively small part of the galaxy and contain few of the many long-lived emission peaks. This results in a CO-to-H$\alpha$ flux ratio that differs significantly from the galactic average. Conversely, covering the long-lived emission peaks requires numerous apertures that will also include many of the short-lived emission peaks, resulting in a modest deviation from the galactic CO-to-H$\alpha$ ratio.

We fit a model describing this statistical behaviour[16] (see Methods and Supplementary Video 2) to measure how long GMCs live and form stars ($t_{\rm CO}$), how long feedback takes to evacuate residual gas ($t_{\rm fb}$, the time for which GMCs and Hii regions coexist), and the mean separation length between independent star-forming regions ($\lambda$), below which the CO-to-H$\alpha$ ratio significantly deviates from the galactic average. These evolutionary time and length scales define the fraction of gas converted into stars (the cloud-scale integrated SFE), the time-averaged mass outflow rate per unit star formation rate (SFR) (the mass loading factor $\eta_{\rm fb}$), and the feedback outflow velocity ($v_{\rm fb}$). Extensive tests[16] show that these quantities are measured with an accuracy of better than $30\%$. The quantities $t_{\rm CO}$, $t_{\rm fb}$, $\lambda$, and $v_{\rm fb}$ are independent of the adopted CO-to-H2 and H$\alpha$-to-SFR conversion factors.

Figure 1 (left) demonstrates that CO(1-0) and H$\alpha$ emission are rarely co-spatial; they do not trace each other on the cloud scale. We quantify this in Figure 1 (right), which shows the CO-to-H$\alpha$ flux ratio as a function of the aperture size for apertures placed on either CO(1-0) or H$\alpha$ emission peaks (cf. Supplementary Video 1). We find a symmetric de-correlation between CO(1-0) and H$\alpha$ emission on small ({<}150~{}\mbox{{\rm pc}}) scales, implying that molecular gas and star formation are distinct, subsequent phases of the GMC and Hii region lifecycle with similar durations. The aperture size at which the two branches diverge shows that NGC300 consists of independent, cloud-scale building blocks separated by 100{-}150~{}\mbox{{\rm pc}} (cf. Figure 2) that exist in a state of vigorous evolutionary cycling. This empirical result implies that star formation is fast and inefficient; the long gas depletion times observed on galactic scales are not due to slow star formation on the cloud scale.

To infer which physics drive the observed evolutionary cycling, we fit the statistical model described in the Methods[16] to the data and summarise the constrained quantities in Table 1. We analyse both the entire field of view and several bins in galactic radius, visualised in Figure 2. We measure GMC lifetimes spanning t_{\rm CO}=9{-}18~{}\mbox{{\rm Myr}}, with a galactic average of t_{\rm CO}=10.8^{+2.1}_{-1.7}~{}\mbox{{\rm Myr}}. These lifetimes fall between the GMC crossing and gravitational free-fall times (see Methods) at all galactic radii. GMC lifetimes are the longest in the central region (R<1.5~{}\mbox{{\rm kpc}}), most likely caused by higher disc stability (see Extended Data Figure 1) and the correspondingly increased influence of galactic shear in supporting the GMCs against collapse[18, 19]. The GMCs live and form stars for a dynamical timescale, after which they are dispersed relative to the new-born stellar population. This implies that the global evolution of GMCs is not significantly slowed down by support from magnetic fields and that GMCs do not live long enough to be affected by spiral arm crossings[12] or cloud-cloud collisions[20] (see Methods).

GMC dispersal is likely feedback-driven in NGC300. By construction, our analysis measures the cumulative GMC lifetime up to (and including) the onset of massive star formation traced by H$\alpha$ emission, integrating over multiple cycles if these are unassociated with H$\alpha$. The GMCs in NGC300 have high virial ratios (see Methods) and have a cumulative lifetime of about one crossing time. This short timescale does not permit multiple GMC lifecycles during which GMCs disperse dynamically (which each would take a turbulent crossing time) prior to massive star formation. It is therefore most plausible that the GMC lifetime is limited by feedback from massive stars. GMCs and Hii regions coexist on average for t_{\rm fb}=1.5^{+0.2}_{-0.2}~{}\mbox{{\rm Myr}}, independently of galactic radius, implying that GMCs are dispersed before the first supernovae explode (\sim 3~{}\mbox{{\rm Myr}}, see Methods). Instead, early feedback by photoionisation, stellar winds, or radiation pressure is needed, none of which are currently included in large-scale cosmological simulations of galaxy formation[21, 22]. The quantitative comparison to predicted GMC dispersal timescales (Figure 2) shows that GMCs in NGC300 are primarily dispersed by photoionisation and stellar winds. The importance of stellar feedback in regulating the GMC lifecycle is further supported by the measured region separation lengths of \lambda=100{-}150~{}\mbox{{\rm pc}}. These closely match the disc scale height across the range of galactic radii, which is expected if the interstellar medium is structured by feedback-driven bubbles that depressurise when they break out of the disc[23, 24].

The short coexistence timescale of 1.5 Myr refers to that of unembedded, massive stars; low-mass stars or embedded massive stars could form and coexist with the parent GMC for longer. While we cannot trace low-mass stars in NGC300, we search for embedded massive star-forming regions using a Spitzer $24~{}\mu$m map, which does not suffer from extinction. We find only $4{-}7$ regions bright at $24~{}\mu$m that are not associated with H$\alpha$ emission, out of a total number of 224 identified H$\alpha$ peaks (or $\sim 3$%). This small number of embedded massive star-forming regions in NGC300 can be explained by the low GMC surface densities (\sim 20~{}\mbox{M{}_{\odot}}~{}\mbox{{\rm pc}}^{-2}, implying an H$\alpha$ extinction of only $\sim 0.5$ mag), and the observed spatial offset of $24~{}\mu$m emission and GMCs (consistent with observations of the Milky Way[25]). This means that our extinction-corrected H$\alpha$ map recovers most of the SFR, and rules out any significant impact of embedded massive stars on the conclusions of this work (also see Methods).

The GMCs in NGC300 achieve average integrated SFEs of only $\epsilon_{\rm sf}=2.5^{+1.9}_{-1.1}\%$. The SFE is constant with radius, indicating that local variations in $t_{\rm dep}=t_{\rm CO}/\epsilon_{\rm sf}$ reflect changes of the GMC lifetime. Feedback disperses the GMCs whenever the observed SFE reaches a few percent. Due to the low SFE, the mass loading factor on the cloud scale is high, with $\eta_{\rm fb}=40^{+31}_{-18}$. On galactic scales, $\eta_{\rm fb}$ is about an order of magnitude lower[26, 27], indicating that most of the expelled material will not escape NGC300, but will cool to form a new generation of GMCs. This is confirmed by the measured feedback velocities of v_{\rm fb}=8.1{-}10.5~{}\mbox{{\rm km}{}{\rm s}^{-1}}, which match the predicted photoionisation and stellar wind bubble velocities (including their increase with galactic radius) and fall well below the local escape velocities[28] of 50{-}120~{}\mbox{{\rm km}{}{\rm s}^{-1}}. The feedback velocity is derived from $t_{\rm fb}$ and the GMC radius and thus represents a prediction that can be verified independently with integral-field spectroscopy of the ionised gas kinematics.

Numerical simulations of galaxy formation and evolution often describe cloud-scale star formation with prescriptions based on the galactic-scale relation between the (molecular) gas mass and SFR[21, 22]. However, our results demonstrate that star-forming galaxies undergo rapid evolutionary cycling on spatial scales {<}150~{}\mbox{{\rm pc}}. Gas and young stars are not instantly related and the appearance of galaxies constantly changes. This fundamental behaviour of observed galaxies should be reproduced by simulations, rather than adopting the galactic-scale relationships to describe star formation on GMC scales. Our results show that GMC dynamics and pre-supernova feedback mechanisms need to be modelled to achieve this. Otherwise, galaxy simulations reproduce the macroscopic properties of galaxies for the wrong reasons. Initial steps towards including early feedback are promising in this regard[29, 8].

Figure 2 (top left) shows that the lifecycle of GMCs and Hii regions is not universal, but within NGC300 exhibits a factor-of-2 variation with galactic environment. GMC lifetimes may vary depending on the importance of galactic dynamics relative to cloud-scale dynamics[19], whereas the impact of stellar feedback is predicted to depend on the ambient gas density (see Methods). Future GMC-scale observations of large galaxy samples will reveal dynamical cycling processes similar to those identified here and in previous Galactic observations[5]. Our statistical method will facilitate the interpretation of these observations by constraining the physics setting the GMC lifecycle in galaxies as a function of their properties.

Figure 3 shows the performance of our method[16] as a function of spatial resolution (and thus galaxy distance). Owing to its statistical nature, this method does not require resolving individual GMCs or star-forming regions, but only their separation $\lambda$, offering a major benefit relative to previous methods for characterising evolutionary cycling on sub-galactic scales. Local galaxies like NGC300 require a resolution of $100{-}150$ pc, which Figure 2 shows corresponds to the disc scale height; the cloud-scale physics of star formation and feedback can therefore be characterised for hundreds of galaxies within tens of Mpc at $1^{\prime\prime}$ resolution with current observatories. At high redshift ($z>1$), the high gas content implies elevated scale heights and collapse length scales of[30] ${\sim}1$ kpc (below which fragmentation can still occur), implying that the dynamical cycling scale may be accessible by modern observatories (at $0.1^{\prime\prime}$) across cosmic time. This possibility is promising in view of the environmental dependences identified here. Mapping the GMC lifecycle across the Universe will eventually enable the representation of galaxies as ensembles of vigorously evolving building blocks and motivate a bottom-up theory of how galaxies grow and form stars, from high redshift to the present day.