Can the Sun be saved? Can the Sun's core be made smaller and its life extended through magnetism and fusion?

One of the greatest challenges in astrophysics lies in understanding how the Sun generates and cyclically modulates its global-scale magnetic field. For over 400 years solar observers have pondered the canonical marker of that magnetic field—the sunspot. It took more than 200 years after sunspot sketching and cataloging started before it was discovered that the number of sunspots waxes and wanes over an approximately 11 year period (Schwabe, 1849). A half century later, mapping the latitudinal variation of the spotted Sun yielded the “butterfly diagram,” a pattern progressing from ∼30◦ latitude to the equator over the ∼11 year period (Maunder, 1904). In the golden age of solar astronomy— soon to become solar physics—that followed, it was first suggested and then demonstrated that sunspots were sites of intense magnetism protruding through the Sun’s photosphere (Hale, 1908; Hale et al., 1919) and that the polarities of the butterfly’s wings alternated in sign with a period of about 22 years (Hale and Nicholson, 1925). The 11(-ish) year periodicity of sunspot number and the 22(-ish) year periodicity of magnetic polarization must therefore be inextricably linked (e.g., Hathaway, 2010), but how?

The extremely well-tended sunspot data catalog (e.g., Clette et al., 2015), including the limited representation shown in Fig. 1, has been scrutinized time and time again. Indeed, it has been, and will continue to be, exhaustively mined to reveal any hint of the underlying process or processes responsible for the enigmatic spots and their variation. At the largest scale, the modulation of sunspot number both in time and in time and space, have presented primary targets for the astrophysics community with an understanding of the Sun’s omnipotent magnetism as the goal. Further, the well correlated radiative analog of the Sun’s magnetic variability the disk-integrated calcium indices, observed for over a century (e.g., Schrijver et al., 1989; Bertello et al., 2016; Egeland et al., 2017), have created a means to standardize the approach of the astrophysical community to understanding solar and stellar activity en masse (e.g., Wilson, 1978; Baliunas et al., 1995; Egeland, 2017), as the ability to resolve spot activity on distant stars remains in its infancy (e.g., Berdyugina, 2005; Morris et al., 2017). Any theory designed to understand the origins of the Sun’s magnetism and its spotty conundrum, must replicate these measures to be plausible. When we reach our conclusion we will ask, was this dataset ever sufficient to answer the problem at hand? Comparing the 140 years of sunspot evolution as visualized by the Royal Observatory of Brussels, Solar Influences Data analysis Center (SIDC) and US Air Force (USAF). Panel A shows the daily sunspot number (fine dots) with a 50-day running average superposed in blue. Panel B shows the latitude-time distribution of sunspots over the same time frame, the size of the symbol plotted represents the relative size of the sunspot. In each panel the vertical dotted lines are the times of the magnetic (Hale) cycle terminations (McIntosh et al., 2019) while the horizontal dot-dashed lines signify 55◦ latitude. The universality of the 11-year solar activity “canon” cannot be ignored. Simply put, all investigations of the Sun’s influence on the Earth, the solar system and its other planetary bodies are intimately tied to the standard candles of “solar minimum” and “solar maximum”. These terms are used widely to describe magnetically quiet and active spells of solar activity that are tied to the dearth or glut of sunspot productivity. As we will see their use is conceptually limiting, but this is not a paper to go into the myriad of ways in which the magnetic evolution of our star is more devious than face value. As yet, no theory can claim to replicate the underlying physics of the problem from first principles (Parker, 1987) although many have tried, and some do better than others (e.g., Charbonneau, 2010). The class of theories that have developed to explain the gross magnetic variability over the 60 years since routine observations of the Sun’s global magnetism became possible (e.g., Hale, 1913; Babcock, 1961) are generally grouped by the term “dynamo theory.” A dynamo theory tries to capture the Sun’s ability to convert toroidal magnetic fields into poloidal magnetic fields and vice versa utilizing solar internal differential rotation, turbulent convection and circulatory patterns. Four principal forms of dynamo model are prevalent: the “Babcock-Leighton Dynamo;” the “Flux-Transport Dynamo”; the “dynamo wave;” and fully convective 3D magnetohydrodynamic (MHD) models. These concepts are beautifully and insightfully discussed in Charbonneau’s review (Charbonneau, 2010) although the interested reader should read about Parker’s dynamo dilemma (Parker, 1987) and the original literature (Parker, 1955; Leighton, 1964; Wang, Sheeley, and Nash, 1991). Of these dynamo concepts MHD simulations attempt to directly recover the plasma state of the Sun’s interior, while the first two are observation all ymotivated kinematic models, and the remaining concept tries to explain the magnetic progression in terms of global wave-like motions. Regardless of the a priori assumptions made in formulating the theory these models have the common goals of replicating the sunspot number modulation, the butterfly diagram progression, and the alternating polarity of the latter. Little attention has been paid to the situation where these variations place insufficient constraints on the physical problem at hand, however. There is an incredibly vast body of literature attempting to explain these phenomena (over 1,000 refereed articles with 30,000 citations with the phrase ‘solar dynamo’ in the title or abstract since 1970). The skeptical scientist may worry about the true size of the dynamo problem’s null space when so many researchers, wielding a vast array of models, can replicate these grand metrics, but lack success when used in any for ward looking way without constant ingestion of data or adjustment of the array of “free” parameters lurking in the background (Parker, 1993). We will return to the dynamo dilemma.