Relationships between planetary positions and war incidence
The relationship between planetary positions across the ecliptic and armed conflict outbreaks: a retrospective analytical study of mundane astrology.
Jordi Bozzo-1*
1 Astronomical Association of Barcelona ASTER. Barcelona, Catalonia, Spain
*Correspondence to: aster.jbozzo@gmail.com
doi/10/70918.dfft0976
Abstract
According to natal chart-based astrology, the position of the celestial bodies at the time of birth can be used to determine a subject’s personality traits and their correspondence with terrestrial events. Although academic scientific studies have mostly ruled against these postulates, for completeness, in the present study it was hypothesized that human actions such as the decision to start a war (deemed a quantifiable, verifiable, and objective proxy for a state of global human affairs at certain points in time) could be influenced by the position of planets in specific areas of the background sky, regardless of birth date. This study compiled the starting dates of 204 war events throughout the twentieth century. The observed war counts when Mercury, Venus, Mars, Jupiter, Saturn, the Moon, and the Sun were transiting through each one of 12 sections of the ecliptic of 30º span each, with the East boundary of Aries starting at 23° from the vernal equinox (equivalent to the zodiac signs in Ptolemy’s time, when Western astrology foundations were settled) were statistically similar to the expected war counts under regular planetary dynamics (P-values from 0.089 to 0.822). Moreover, there was no clustering or anomalous distribution of war incidence when two planets were in conjunction or transiting the same zodiac sign. However, independently of geopolitical factors, war frequency slightly but significantly increased over the January to December period, and a reproducible but non-significant dip occurred mid-week.
Keywords: Astrology, zodiac sign, sidereal, constellation, ecliptic, planets, war
Plain language summary
Is it possible that planets in the sky could influence human affairs? Astrologers claim that planetary positions at the time of birth correlate with the individual life. But under controlled conditions such correlations disappear. They do not exist. Nevertheless, history tells us that the masses have been greatly influenced by comets and eclipses, to say nothing of moonlit nights for barbecues. Could planets still have an effect? It seems unlikely because planets are much less visible, and their calculated effects due to gravity and radiation effects are much too tiny to be plausible. But, for completeness, the idea of comparing planetary positions at the outbreak of 210 major wars 1901-2000 was here tested. Their frequency slightly but significantly increased over the January to December period, and a reproducible but non-significant dip occurred mid-week. However, no effect due to geography, zodiac starting point, or planetary positions, was detected.
Introduction
The earliest recorded use of an integrated astrological system is found in Mesopotamia about the 2nd millennium BC, where it spread to India and Europe, although there are signs of Babylonian inscriptions in cuneiform writing of remarkable facts related to the stars dating more than 4000 years ago (Bowen & Rochberg, 2020; Rochberg, 2010). Modern popular astrology comes directly from the Hellenistic period, particularly from the works of Ptolemy in the 2nd century CE. While his Almagest formed the basis of the sciences of the Cosmos until the end of the Renaissance, the Tetrabiblos is a true treatise on astrology whose postulates have remained almost unchanged throughout these more than 2000 years (Bowen, 1994; Bowen & Rochberg, 2020), and practically all its content has been accepted by western astrologers up to the present day.
According to natal astrology, the position of the Sun, Moon, and planets at birth can be used to determine a subject’s personality, temperament, and behavior (Zarka, 2009). The location of celestial bodies in predefined categories across the ecliptic (zodiac signs or houses) determines the natal chart, which constitutes the cornerstone of natal astrology. Despite the fact that there is a large primary literature on astrology, including empirical studies, it is highly scattered, and much of it is not online and difficult to retrieve. Helpfully, a comprehensive and up-to-date review by Dean G et al. is available (Dean, Mather, Nias, & Smit, 2022).
In studies published in academic journals, scientific tests aimed at verifying the claims of natal astrology have repeatedly failed (Dean & Kelly, 2003; Helgertz & Scott, 2020; Komath, 2009; Lower, 2007; McGrew & McFall, 1990; Narlikar, Kunte, Dabholkar, & Ghatpande, 2009; Silverman, 1971), with some showing positive results (Joswig, Stienen, Hock, Hildebrandt, & Surbeck, 2016; Peacock, Afzal, Asopa, Clement, & Sochart, 2023). But still, horoscopes, an astrologer’s interpretation of natal charts, are extremely popular. This holds even after the strongest evidence against natal astrology to date was provided in a double-blind study by Carlson in 1985 (Carlson, 1985). Not only were the professional astrologers actively involved in the design of Carlson’s study unable to describe the psychological profiles of participants based on their natal charts, but participants were also unable to recognize their own profiles at a level higher than chance. However, the results of Carlson’s study have been criticized for ambiguity, both from the point of view of methodology and astrology (Ertel, 2009).
It is generally accepted that environmental factors at birth can be associated with psychological and psychiatric phenomena and have an impact on personality. For instance, the season of birth can influence an individual’s early development (Lee, Lee, & Lee, 2021). In contrast, the inability of astrology to provide a consistent rationale for how planets and stars can imprint certain characteristics of individuals at birth is one of its main scientific criticisms (Kelly, 1997).
In addition to human personality traits, mundane astrology (also called political or world event astrology) is an ancient branch of astrology that focuses on the correspondence between celestial observations and terrestrial events, including politics, governments, disasters, and wars, with predictive aims. Mundane astrology is also based on the horoscopes of not only people but also cities and states (Bennett, Donahue, Schneider, & Voit, 2017; deGrasse Tyson & Lang, 2018).
Despite the inconsistencies of natal astrology, in this study it is hypothesized that, from a non-natal perspective, it could still be possible that the human brain and the consequent routine human behavior could somehow be influenced by the positions of planets as they appear in the background sky from the observer’s perspective on Earth. Hence, a reliable assessment of an astrological effect independent of the birth date would require a controlled study with a hypothesis formulated in advance on a well-defined and measurable parameter of human actions. With that aim in mind, the present study focused on war outbreaks.
Violence throughout human history, particularly its socially organized expression in the form of warfare, has been extensively addressed by scholars (Groebel & Hinde, 1989; Rifkin, 1963; Von Clausewitz, Howard, & Paret, 2008). War is typically considered a state of armed conflict between two or more countries or human groups within a country that begins as a sort of dispute that turns violent. There is a multitude of causes, mechanisms, and developments leading to war, including misdirected aggressive impulses (Schake, 2017; Waltz, 2001). Ultimately, in most cases, a war begins with a leader’s decision to act, consciously or unconsciously, driven by those circumstances (Levy, 1998). Importantly, recent armed conflicts are sufficiently documented events that could be used for mundane astrology tests. However, the astrological influence on war occurrence has only been addressed by tentative studies published in non-refereed media (Barbault, 1970; Doolaard, 1993a, 1993b).
With this background, for completeness, the present study explored the connection between the positions of the planets, the Moon, and the Sun across sections of the ecliptic corresponding to the signs of the astrological zodiac and a key aspect of human behavior such as violence, the latter represented by its manifestation in warfare.
Methods
Study design and objectives
The incidence of wars worldwide within a defined set of conditions was deemed a quantifiable, verifiable, and objective proxy for a global state of human affairs that resulted in the decision to start an act of violence such as war. In this study, some assumptions were made to support the existence of an astrological effect independent of birth date as much as possible while maintaining the scientific framework (see Supplementary Box S1).
The defined set of conditions was the location of the five planets relevant to astrology since antiquity (i.e., those that can be observed with the naked eye: Mercury, Venus, Mars, Jupiter, and Saturn), plus the Moon and the Sun, within 12 predefined sections of the ecliptic corresponding to the zodiac signs.
The primary objective of this study was to determine whether there is an association between the incidence of wars and the location of planets, the Moon, or the Sun within the zodiac signs. To achieve this objective, a database of war events was compiled. The number of wars that began when a planet, the Moon, or the Sun was transiting through each zodiac sign was compared with the number expected in the absence of any influence (i.e., by chance).
The possible higher-than-expected occurrence of wars when two of the studied celestial bodies were found concomitantly in the same section of the ecliptic, in sideral (Vedic) astrology meaning in conjunction within a specific zodiac sign (Shah, 2022), was also assessed as a secondary objective. A qualitative evaluation of war incidence when a conjunction was defined as two planets being close together on the ecliptic, according to tropical astrology, was also performed as an exploratory objective. To this aim, a conjunction was considered as the apparent angular distance between paired planets being 0º ± 5º, regardless of zodiac sign. Other astrologically relevant angular combinations such as semi-sextile (30º), sextile (60º), square (90º), trine (120º), quincunx (150º), and opposition (180º), known as “aspects” (Simon, 1979), were also assessed.
A series of controls were set up to evaluate the association of war incidence with other variables that could be determined from the collected data but were unrelated to the position of the celestial bodies with respect to the sky background. To this end, the distribution of wars was calculated: i) over the 12 months of the calendar; ii) over the seven days of the week; and iii) over the eight phases of the Moon. The distribution of wars worldwide according to socio-geographic factors was also considered.
War events data collection
A list of wars that occurred during the twentieth century (from January 1st, 1901, to December 31st, 2000) was prepared. This recent period of 100 years was deemed to contain a sufficient sample size of authenticated war events for the study analysis, while earlier conflicts were considered more poorly registered and documented.
Data on war events were collected from several online sources (Brunberg, 2013; Wikipedia, 2023a, 2023b, 2023c). To get a consistent list of events from the variety of armed conflicts included in the sources, only those that met the following inclusion criteria were gathered: i) events that were unequivocally defined as “war” or “invasion”; ii) events that were defined as “armed conflict” but the term was used interchangeably with “war” elsewhere; and iii) events with a known beginning date.
Planetary position calculations
The ecliptic coordinates of Mercury, Venus, Mars, Jupiter, and Saturn on the first day of eligible war events were obtained using Casio’s Keisan Online Calculator (https://keisan.casio.com/exec/system/1224748262). The Moon and the Sun ecliptic coordinates were obtained using Jens T. Satre’s online Sun & Moon Position Calculator (https://www.satellite-calculations.com/Satellite/suncalc.htm). For all calculations, the daytime was conveniently set to 12:00 UT. For the purpose of this study, only ecliptic longitude was relevant.
The values of ecliptic longitude in degrees were distributed across 12 sections of the ecliptic with a 30º span each with the limit between Aries and Pisces being located approximately 23° to 24° from the vernal equinox, concurring with the sign boundaries of the sidereal zodiac signs. In this study, the sidereal zodiac was preferred to the tropical zodiac because it takes the precession of the equinoxes into account (see Supplementary Box S2), and therefore its sign boundaries are closer to those of Ptolemy’s time.
War incidence measurement
The number of wars that commenced when Mercury, Venus, Mars, Jupiter, Saturn, the Moon, and the Sun were transiting through each of the 12 zodiac signs (in 30° sky sections defined in Supplementary Table S1), was counted.
To derive the number of war events expected in the absence of any potential astrological influence, it was determined that such a number should be proportional to the actual time that each planet remained in each zodiac sign during the 100-year period studied. However, because of the apparent retrograde motion of planets relative to the background stars (Supplementary Table S2), the time spent by a planet transiting through each of the 12 zodiac signs during its synodic period is not proportional to 1/12. This was not the case with the Moon and the Sun, in which time spent in each zodiac sign is very close to 1/12 proportion. To calculate these times, the daily ecliptic longitude values of each planet from January 1st, 1901, to December 31st, 2000 (36,525 days) were obtained using the NASA Horizons Web Application (https://ssd.jpl.nasa.gov/horizons/app.html#/). The ecliptic longitude values were distributed according to the ranges listed in Supplementary Table S1. To obtain the expected values, the proportion of each range with respect to the total number of observed war events was calculated and rounded to the nearest integer.
Procedures for control studies
Controls tests were designed to assess the potential influence of factors with astronomical and/or social nature, as detailed in Supplementary Table S3.
Wars were categorized according to their calendar month of beginning. The expected monthly war count was the total number of wars listed during the study period divided by 12 (monthly average). Similarly, wars were categorized according to the weekday of beginning. The expected war count per weekday was the total number of wars listed during the study period divided by 7 (daily average).
The moon phase of the day when a war broke out was obtained from Luca Cassioli’s Moon Local Time Calculator (https://win98.altervista.org/space/exploration/moon/moontime.html). For convenience, the daytime was set at 12:00 UT. Wars were classified within eight Moon phase categories: new, waxing-crescent, first quarter, waxing-gibbous, full, waning gibbous, last quarter, and waning crescent. Each category corresponded to 12.5% of the phase cycle (29.5 days). The expected war count per phase category was the total number of wars listed during the study period divided by 8.
To provide a socio-geographic contextualization, war events were classified, first, according to the geopolitical region where the countries or human groups involved were located: Western world, Eastern European, Latin American, and Caribbean, African, and Asia and the Pacific (Ruder, Nakano, & Aeschlimann, 2017); second, according to the Earth hemisphere: Northern vs. Southern; and third, according to the Earth climatic zone: tropical (i.e., between latitude 23º 27’ North and South) vs. non-tropical (subtropical and temperate: latitude higher than 23º 27’ North and South) (Kottek, Grieser, Beck, Rudolf, & Rubel, 2006).
Statistical analysis
The goodness of fit test was used to calculate the minimum sample size to gain a minimum power of 0.8 at a significance level α = 0.05, with a medium effect size (Cohen’s w = 0.3) for a chi-square comparison with 12 categories (Cohen, 1988). These baseline data determined the minimum sample size for N = 187 war events.
Contingency tables and graphs were prepared for the observed and expected numbers of wars that started when a planet, alone or in conjunction with another planet, the Moon, and the Sun were found transiting through each of the 12 zodiac signs. The observed and expected values were compared using chi-square tests. Statistical significance was set at P< 0.05, after applying the Benjamini-Hochberg procedure to correct the false discovery rate associated with multiple comparisons (Benjamini & Hochberg, 1995). Cramér's V was used to measure the effect size for the chi-square test. The effect size was considered small if V ≤ 0.3, medium if V ≤ 0.50, and large if V > 0.50.
Where deemed applicable, a linear regression model was used to conduct an additional trend analysis of the distribution of wars across the allocations. The regression curve with a 95% confidence interval (CI) and goodness of fit coefficient (r2) were calculated. The F-test was used to determine a non-zero slope at a significance level of P < 0.05. In addition, non-linear regression with the least square fitting to a polynomial curve was explored. To avoid overfitting, the lowest-order polynomial with a value of r2 > 0.35 was selected.
SPSS Statistics (IBM, Armonk, NY, U.S.), Microsoft Excel (Microsoft Corporation, Redmond, WA, U.S.), and GraphPad Prism (GraphPad Software Inc, San Diego, CA, U.S.) were used for the calculations and charting.
Results
A total of 210 war events were collected from the sources. The first war event started on November 1st, 1901 (Anglo-Aro War) and the last event started on June 5th, 2000 (Six-Day War between Uganda and Rwanda). In six cases the precise day of the month the war started was not documented. This left a total of 204 war events available for the primary analysis. This value was well above the minimum sample size required (N = 187). A complete list of wars and dates is provided in Supplementary Table S4.
War occurrence according to single planetary positions
The observed and expected war counts when planets, the Moon, and the Sun were transiting through each of the 12 zodiac signs (in 30° sky sections defined in Table S1) are represented as radar charts in Figure 1.
Saturn showed the most irregular graph shape due to its widest observed range of war counts (from 6 to 29), whereas Venus, the Moon, and the Sun had the narrowest ranges (from 11 to 23) with smoother graph shapes. For planets, the expected war count per zodiac sign was variable because of the retrogradation effects, ranging from between 15 and 19 in Mercury to between 13 and 22 in Saturn. For both the Moon and the Sun, the expected war count was 17 (204/12).
None of the observed war counts were statistically different from the expected counts: P = 0.432 for Mercury, P = 0.455 for Venus, P = 0.768 for Mars, P = 0.364 for Jupiter, P = 0.089 for Saturn, P = 0.658 for the Moon, and P = 0.822 for the Sun. The effect size was marginally moderate for Saturn (Cramér’s V = 0.343) and small for the other bodies (Cramér’s V ranging from 0.183 for the Sun to 0.281 for Jupiter).
Only the Sun’s curve seemed to follow a regular cyclic shape (Figure 1), with maximum war counts in signs located at opposite sides of the ecliptic (Pisces-Aries-Taurus and Virgo-Libra-Scorpius) and minimum counts in signs located perpendicularly to those (Capricornus-Sagittarius-Aquarius and Gemini-Cancer-Leo).
War occurrence according to planetary conjunctions
The percentage of wars that started during binary planetary conjunctions ranged from 20.6% in Mercury-Venus conjunctions to 7.4% in Mars-Jupiter conjunctions. Details of the war incidence for all the paired planet conjunctions, overall and per zodiac sign, are shown in Table 1. There were no statistically significant differences in the observed vs. expected counts of war occurrence, with P values ranging from P = 0.148 in Mercury-Mars and Mercury-Jupiter conjunctions to P = 0.998 in Jupiter-Saturn conjunctions (Table 1).
The ecliptic longitude plots for paired planets corresponding to their positions at the day of the beginning of each war are illustrated in Figure 2. It can be visually evidenced that there was no clustering or abnormal distribution of war occurrences when two planets were concomitantly transiting the same sign. A normal random or scattered pattern could also be observed in whichever sign or ecliptic longitude the planets were in (Figure 2).
The higher percentage of wars that happened in the Mercury-Venus conjunctions (Table 1) agreed with the natural positional concomitance of these planets, never being farther than two signs apart (Figure 2). This corresponds to their condition as inner planets (i.e., they orbit the Sun within Earth’s orbit), whose apparent distance as viewed from Earth never exceeds 75°. Mercury and Venus also showed a slight natural trend of positional concomitance with Mars. On the other hand, the linear pattern of war occurrence observed in the paired Jupiter-Saturn positions (Figure 2), corresponds to their condition as the farthest outer planets with long orbital periods and very similar synodic periods (Supplementary Table S2).
Results of war occurrence according to Moon-planets and Sun-planets conjunctions were comparable to those observed in the binary planetary conjunctions (See supplementary Figures S1 and S2). As expected, the plots showed a clear positional concomitance of the Sun with Mercury and Venus, the inner planets, and a slight concomitance with Mars.
Overall, the charted patterns of war occurrence during all conjunctions and no conjunctions were not qualitatively different from those expected from regular planetary movement dynamics.
War occurrence according to calendar months
The distribution of wars according to the month of outbreak showed a minimum count in January (n = 8) and a maximum of approximately three times that value in November and December (n = 24 and n = 23, respectively). Although there was no statistically significant difference in war count per month concerning average (17.5 wars per month), linear regression analysis demonstrated a statistically significant positive non-zero slope of 0.762 (95% CI: 0.128 to 1.397; P = 0.023) with a goodness of fit r2 = 0.418. Details are shown in Figure 4A. This pattern was proven reproducible since the plots of the first and second half of the analyzed war events (n = 105 each) showed the same slope (see Supplementary Figure S3A). In addition, the adjustment of the global trend to a third-order polynomial curve (r2 = 0.693) evidenced that the positive slope was concentrated in the first and fourth quarters of the year, being rather flat in between (Figure 4B).
Of note, if the Sun’s data in Figure 1 were plotted following the same approach, with the starting time point at Sagittarius (sidereal zodiac sign dates: December 16 to January 14), the shape of the resulting third-order polynomial curve was similar to the monthly curve (Figure 4C). However, the positive slope was not significant (P= 0.070) and replicability for the first and second half of the analyzed war events was weaker than in monthly distribution (Supplementary Figure S3B).
War occurrence according to weekday
War occurrence counts according to weekday did not show statistically significant differences when compared to the daily average (29.1 wars). However, a trend of minimal occurrence during mid-weekdays could be adjusted to a third-order polynomial curve (r2 = 0.691; Figure 5A). This pattern was also reproducible since the plots of the first and second half of the analyzed war events (n = 102 each) showed a similar line pattern (see Supplementary Figure S3C).
War occurrence according to Moon phases
War outbreaks showed no statistically significant count to happen more frequently than the average war count per Moon phase (22.5 wars). War counts ranged from n = 20 during the new moon to n = 31 during the first quarter, waning gibbous, and waning crescent. Detailed results are shown in Figure 5B. In addition, no apparent trend could be discerned.
War occurrence according to socio-geographic context
All geopolitical regions where wars occurred were well represented: 13.0% of wars involved the Western world, 18.8% involved Eastern Europe, 13.4% involved Latin America and the Caribbean, 21.3% involved Africa, and 33.5% involved Asia and the Pacific. Most wars occurred in the Northern Hemisphere: 84.8% vs. 15.5% in the Southern Hemisphere, which is in agreement with the emerged landmasses distribution. The percentage of wars occurring inside and outside the tropical belt was similar: 44.3% and 55.7%, respectively.
Discussion
The fact that natal astrology is unable to prove both descriptive and predictive power does not rule out the possibility that the positions of celestial bodies in specific parts of the background sky had an impact on human behavior unrelated to birth date. In this study, a non-natal approach was used to objectively examine the possible relationship between the movement of planets, the Moon, and the Sun across the ecliptic and human actions, namely activities related to violence and war, a topic addressed by mundane astrology. Results indicate that the null hypothesis (i.e., that there is no such a connection) should be accepted.
Symbolism is a core aspect of traditional astrology. Each planet is associated with certain meanings. Of relevance for this study, Mars, the symbol of war, and Saturn are the planets believed to possess the strongest “malefic” influence (Brennan, 2017). However, in this study, the pattern of war occurrence when Mars was transiting through zodiac signs was rather anodyne, whereas in Saturn the pattern was highly irregular. These facts are consistent with normal statistical fluctuations.
Planetary conjunctions are relevant events in astrology, since it is believed that the two bodies unite and blend their influences (Aston, 1970; Shah, 2022). Western astrologers argue that a conjunction occurs when the apparent angular distance between planets is 0º-10°, although Vedic astrology states that there is a conjunction when two planets link up in the same sign (Shah, 2022). The latter definition was preferred for the secondary objective of this study. Results showed that, when any pair of planets, including Mars and Saturn, being the carriers of evil, were simultaneously transiting specific zodiac signs, wars occurred in accordance with what would be expected from their regular orbital movements. The same interpretation could be drawn from the results obtained when a conjunction was defined as planets being within 10º of the apparent angular distance regardless of the zodiac sign they were in, as well as for the other combinations of angular distances. There is little chance that the outermost planets and minor objects of the Solar System not addressed in this study would behave otherwise.
A tentative study performed in 1993 analyzed the relationship between major wars and the sums of the angular separations between the outer five planets (Jupiter, Saturn, Uranus, Neptune, and Pluto), namely the Cyclical Index (Doolaard, 1993a). Results showed that more wars broke out during the downward phase of the waves than during the upward phase (Doolaard, 1993b). However, several methodological shortcomings, including a small sample size and no hypothesis formulated in advance, have been attributed to this study (Dean et al., 2022). It is also striking that three of the five outer planets (Uranus, Neptune, and Pluto) were discovered as recently as 1781, 1846, and 1930, respectively, which makes these bodies, particularly Pluto, ignored by astrology for most of its history. Moreover, since the discovery of Pluto’s companion, Charon, in 1978, Pluto-Charon has been considered a double system. Furthermore, with the discovery in 1992 of Albion, the first trans-Neptunian object after Pluto-Charon, and later of many remote bodies similar to Pluto (such as Eris, Haumea, Makemake, Gonggong, Quaoar, Sedna, Orcus, and other of the currently known as dwarf planets), Pluto became just one more forming part of the so-called Kuiper belt (International Astronomical Union, 2006). Interestingly, the existence of an Earth-like planet in the distant Kuiper belt has been postulated (Lykawka & Ito, 2023). Astrologers are still discussing how to tackle these new members of the Solar System (Park, 2004). For these reasons, the present study preferred considering the five planets known since ancient times only, in agreement with the foundations of astrology (Bowen, 1994; Bowen & Rochberg, 2020).
The only seemingly consistent study to date that found a purportedly astrological effect of Mars on human activities was described by Michel Gauquelin, in which sports champions were reported to be born when Mars had just risen or culminated (Gauquelin, 1988). However, there was controversy on whether the results were real (Ertel & Irving, 1997) or whether the original birth dates were biased (Kurtz, Nienhuys, & Sandhu, 1997). Curiously enough, this effect was unrelated to Mars’s position concerning the background sky, but to its position relative to the horizon, which depends on Earth’s rotation. Rather than bolstering astrology, Gauquelin’s findings highlight the inconsistency of astrology itself.
In contrast to the planets, the Sun and the Moon have a well-known influence on humans beyond astrological beliefs that can act as confounding factors. Thus, the Sun’s apparent yearly path across the ecliptic runs together with the course of the months and seasons. Accordingly, the first control of this study demonstrated that war occurrence correlated with the months of the calendar beyond planets’ positions and astrology beliefs. In any field that attempts to predict human behavior, such as psychology, a value of r2 > 0.35 is usually regarded as significant (Lewis-Beck & Skalaban, 1990). As the maximum variation was detected between January and December, two months with similar weather conditions, climatic influence is unlikely to have played a role. Furthermore, wars considered in this study took place in both the Northern and Southern Hemispheres, which have opposing hot-cold seasons that typically last three months, as well as wars in countries of the tropical belt, which have dry-rainy seasons that last six months (typically from December through June and June through November, respectively) (Kottek et al., 2006). Moreover, wars happened in all geopolitical regions and their associated cultural domains. All these factors point to the results being attributed to mind-rooted societal causes associated with end-of-year and new-year aims.
On the other hand, the results of this study indicated that the position of the Moon in the background sky of the ecliptic was not associated with changes in war incidence. Similarly, the Moon phase test acted as a negative control for war outbreaks. However, the Moon can indeed have an impact on mood and mental health (Cajochen et al., 2013; Wehr, 2018; Zimecki, 2006). With a synodic period of 29.5 days, lunar cycles have been linked to near-monthly periodicities, including violent behavior (Rotton & Kelly, 1985; Thakur & Sharma, 1984). Although it is known that high or low moon-depending night light is fully considered in conducting localized military actions, whether to prioritize visibility or occultation, respectively (US Marine Corps, 1998), neither Moon cycle nor moonlight seemed to play a role in the decision to start armed confrontations of higher magnitude, such as wars.
Finally, the weekday control test demonstrated a pattern of war outbreaks that was somehow comparable to the monthly pattern. However, unlike the yearly cycle, neither astronomical nor natural phenomena are associated with a 7-day cycle; therefore, the observed weekday pattern should be considered man-caused or artificial and unrelated to planetary influence. For instance, a relationship between day-of-week and violent crimes has been reported (Towers, Chen, Malik, & Ebert, 2018).
The limitations of this study include restrictions on the inclusion criteria for data homogeneity. Thus, only armed conflicts, defined as wars or invasions, were analyzed. Other violent events, such as single battles, uprisings, revolts, rebellions, insurrections, or coups d’état, were not considered. Important parameters that determine the impact of a war, such as duration (which varies from days to decades) and death toll (which varies from a few hundred to tens of millions), were not in the scope of this study. In addition, planetary positions were obtained using online calculators which do not provide the accuracy of the calculated values, and. there is no guarantee that the sources of information employed are complete or unbiased. Finally, other variables not addressed in this study, such as crime and delinquency, can also be used to analyze human violence and aggression. It should also be noted that this study operated with the sidereal zodiac. Other astrologies may use different zodiac signs (e.g., the Chinese Zodiac and its variations) or different boundaries (e.g., the tropical zodiac) (Gontier, 2016; Kassell, 2010).
Conclusions
This study avoided astrology’s reliance on natal charts, which is scientifically one of its weakest points, to give a chance of success to astrology’s potential strongest point: the possibility that celestial bodies such as planets, the Moon, and the Sun transiting through sections of the ecliptic equivalent to the zodiac signs could be somehow linked to human affairs globally. As an issue historically addressed by astrologers, the triggering of armed conflicts was taken as a documented, measurable, and reliable expression of human violent behavior susceptible to such an influence. However, no connection was observed.
Acknowledgments
Jordi Aloy at the Astronomical Association of Barcelona ASTER is acknowledged for his expert advice and critical revision of the manuscript. The author would like to thank the Referees for taking the time and effort necessary to evaluate and review the manuscript. The author sincerely appreciates the Referee's valuable comments and suggestions, which helped to improve the quality of the manuscript.
Author contributions
JB designed the study, collected, and interpreted the data, performed calculations, and wrote the manuscript.
Data availability
All data supporting the findings of this study are available in the article and/or supplementary material.
Competing interest
The author declares no competing interests.
Funding
This study received no funding.
Ethical compliance
Not applicable.
References
Aston, M. (1970). The Fiery Trigon Conjunction: An Elizabethan Astrological Prediction. Isis, 61(2), 159-187.
Barbault, A. (1970). Une recherche décevante. L'Astrologue, 11, 184-185.
Benjamini, Y., & Hochberg, Y. (1995). Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society: Series B (Methodological), 57(1), 289-300.
Bennett, J. O., Donahue, M. O., Schneider, N., & Voit, M. (2017). The cosmic perspective (8th ed.). San Francisco, CA: Pearson/Addison-Wesley.
Bowen, A. C. (1994). Ptolemy's Universe: The Natural Philosophical and Ethical Foundations of Ptolemy's Astronomy. Isis, 85(1), 140-141.
Bowen, A. C., & Rochberg, F. (2020). Hellenistic Astronomy: The Science in Its Contexts. Leiden: Brill Academic Pub.
Brennan, C. (2017). Benefic and Malefic Planets in Astrology. The Horoscopic Astrology Blog. https://horoscopicastrologyblog.com/2007/06/28/benefic-and-melefic-planets-in-astrology/. Accessed March 12, 2023.
Brunberg, J. (2013). The Polynational War Memorial. Wars since 1900. https://www.war-memorial.net/wars_all.asp. Accessed February 20, 2023.
Cajochen, C., Altanay-Ekici, S., Münch, M., Frey, S., Knoblauch, V., & Wirz-Justice, A. (2013). Evidence that the lunar cycle influences human sleep. Current Biology, 23(15), 1485-1488.
Carlson, S. (1985). A double-blind test of astrology. Nature, 318(6045), 419-425.
Cohen, J. (1988). Chi-Square Tests for Goodness of Fit and Contingency Tables. In: Statistical Power Analysis for the Behavioural Sciences. In (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
Dean, G., & Kelly, I. W. (2003). Is Astrology Relevant to Consciousness and Psi? Journal of Consciousness Studies, 10(6-7), 175-198.
Dean, G., Mather, A., Nias, D., & Smit, R. (2022). Understanding Astrology. A critical review of a thousand empirical studies 1900-2020. Amsterdam: AinO Publications.
deGrasse Tyson, N., & Lang, A. (2018). Accessory to War: The Unspoken Alliance Between Astrophysics and the Military: W. W. Norton & Company.
Doolaard, R. D. (1993a). The Pluto-Neptune Cycles. AinO, 8(1), 15-22.
Doolaard, R. D. (1993b). Waves of wars 1700-1992. AA Journal, 35(5), 268-279.
Ertel, S. (2009). Appraisal of Shawn Carlson’s Renowned Astrology Tests. Journal of Scientific Exploration, 23(2), 125-137.
Ertel, S., & Irving, K. (1997). Biased Data Selection in Mars Effect Research. Journal of Scientific Exploration, 11(1), 1-18.
Gauquelin, M. (1988). Is there a Mars effect? . Journal of Scientific Exploration, 2(1), 29-52.
Gontier, N. (2016). Time: The Biggest Pattern in Natural History Research. Evolutionary Biology, 4(43), 604-637.
Groebel, J., & Hinde, R. A. (1989). Aggression and war: Their biological and social bases. New York, NY, US: Cambridge University Press.
Helgertz, J., & Scott, K. (2020). The validity of astrological predictions on marriage and divorce: a longitudinal analysis of Swedish register data. Genus, 76(1), 34-34.
International Astronomical Union. (2006). Definition of a Planet in the Solar System: Resolutions 5 and 6. Available at https://www.iau.org/static/resolutions/Resolution_GA26-5-6.pdf. Retrieved September 30, 2023.
Joswig, H., Stienen, M. N., Hock, C., Hildebrandt, G., & Surbeck, W. (2016). The influence of lunar phases and zodiac sign 'Leo' on perioperative complications and outcome in elective spine surgery. Acta Neurochir (Wien), 158(6), 1095-1101.
Kassell, L. (2010). Stars, spirits, signs: towards a history of astrology 1100-1800. Studies in History and Philosophy of Biological and Biomedical Sciences, 41(2), 67-69.
Kelly, I. W. (1997). Modern Astrology: A Critique. Psychological Reports, 81(3), 1035-1066.
Komath, M. (2009). Testing astrology. Current Science, 96(12), 1568-1572.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., & Rubel, F. (2006). World Map of the Köppen-Geiger climate classification updated. Meteorologische Zeitschrift, 15(3), 259-263.
Kurtz, P., Nienhuys, W., & Sandhu, R. (1997). Is the "Mars Effect" Genuine?. Journal of Scientific Exploration, 11(1), 19-39.
Lee, H., Lee, H.-K., & Lee, K. (2021). Is personality linked to season of birth? PloS one, 16(6), e0253815-e0253815.
Levy, J. S. (1998). The causes of war and the conditions of peace. Annual Review of Political Science, 1(1), 139-165.
Lewis-Beck, M. S., & Skalaban, A. (1990). The R-Squared: Some Straight Talk. Political Analysis, 2, 153-171.
Lower, S. K. (2007). Treating astrology's claims with all due gravity. Nature, 447(7144), 528-528.
Lykawka, P. S., & Ito, T. (2023). Is There an Earth-like Planet in the Distant Kuiper Belt? The Astronomical Journal, 166(3), 118.
McGrew, J. H., & McFall, R. M. (1990). A Scientific Inquiry into the Validity of Astrology. Journal of Scientific Exploration, 4(1), 75-83.
Narlikar, J. V., Kunte, S., Dabholkar, N., & Ghatpande, P. (2009). A statistical test of astrology. Current Science, 96(5), 641-643.
Park, R. (2004). Sedna, a new power in astrology? MA thesis. Bath Spa University College. Mentioned by Dean, G., Mather, A., Nias, D., & Smit, R. (2022).
Peacock, C. J., Afzal, I., Asopa, V., Clement, N. D., & Sochart, D. H. (2023). Is success written in the stars? The effect of zodiac sign on the outcome of total knee arthroplasty. N Z Med J, 136(1572), 36-45.
Rifkin, A. H. (1963). Violence in Human Behavior. Science, 140(3569), 904-906.
Rochberg, F. (2010). The Heavenly Writing: Divination, Horoscopy, and Astronomy in Mesopotamian Culture: Cambridge University Press.
Rotton, J., & Kelly, I. W. (1985). Much ado about the full moon: a meta-analysis of lunar-lunacy research. Psychological Bulletin, 97(2), 286-306.
Ruder, N., Nakano, K., & Aeschlimann, J. (2017). The GA Handbook: A practical guide to the United Nations General Assembly: Permanent Mission of Switzerland to the United Nations.
Schake, K. (2017). What Causes War? Orbis, 61(4), 449-462.
Shah, S. (2022). Conjunctions: Vedic Astrology. In. Retrieved from https://books.google.es/books?id=PW_KDwAAQBAJ
Silverman, B. I. (1971). Studies of Astrology. The Journal of Psychology, 77(2), 141-149.
Simon, G. (1979). Kepler, astronome astrologue. Bibliothèque des Sciences Humaines. Paris: Gallimard.
Thakur, C. P., & Sharma, D. (1984). Full moon and crime. Br Med J (Clin Res Ed), 289(6460), 1789-1791.
Towers, S., Chen, S., Malik, A., & Ebert, D. (2018). Factors influencing temporal patterns in crime in a large American city: A predictive analytics perspective. PloS one, 13(10), e0205151.
US Marine Corps. (1998). Military Operations on Urbanized Terrain (MOUT). Available at: https://www.marines.mil/Portals/1/MCWP%203-35.3.pdf. Accessed October 30, 2023.
Von Clausewitz, C., Howard, M., & Paret, P. (2008). On war: Princeton University Press.
Waltz, K. (2001). Man, the state, and war: A theoretical analysis. New York: Columbia University Press.
Wehr, T. A. (2018). Bipolar mood cycles and lunar tidal cycles. Molecular Psychiatry, 23(4), 923-931.
Wikipedia. (2023a). List of wars: 1900–1944. https://en.wikipedia.org/wiki/List_of_wars:_1900%E2%80%931944. Accessed February 20, 2023.
Wikipedia. (2023b). List of wars: 1945–1989. https://en.wikipedia.org/wiki/List_of_wars:_1945%E2%80%931989. Accessed February 20, 2023.
Wikipedia. (2023c). List of wars: 1990–2002. https://en.wikipedia.org/wiki/List_of_wars:_1990%E2%80%932002. Accessed February 20, 2023.
Zarka, P. (2009). Astronomy and astrology. Proceedings of the International Astronomical Union, 5(S260), 420-425.
Zimecki, M. (2006). The lunar cycle: effects on human and animal behavior and physiology. Postepy Higieny i Medycyny Doswiadczalnej (Online), 60, 1-7.
Supplementary Materials
Table S1. Ranges of ecliptic longitude values for the distribution of the zodiac signs across the ecliptic as set in the study
Zodiac sign | Ecliptic longitude range (degree) |
Aries | ≥ 23° to < 53° |
Taurus | ≥ 53° to < 83° |
Gemini | ≥ 83° to < 113° |
Cancer | ≥ 113° to < 143° |
Leo | ≥ 143° to < 173° |
Virgo | ≥ 173° to < 203° |
Libra | ≥ 203° to < 233° |
Scorpius | ≥ 233° to < 263° |
Sagittarius | ≥ 263° to < 293° |
Capricornus | ≥ 293° to < 323° |
Aquarius | ≥ 323° to < 353° |
Pisces | ≥ 353° to < 360° ≥ 0° to < 23° |
Table S2. Orbital and synodic periods of planets, the Moon, and the Sun (apparent), and their retrogradation times
Celestial body | Orbital period (days) | Synodic period (days) | Days in retrogradation | % of days in retrogradation |
Mercury | 88 | 116 | 21* | 18.1%* |
225 | 584 | 41 | 7.0% | |
687 | 780 | 72 | 9.2% | |
4332 (≈12 years) | 399 | 121 | 30.3% | |
10759 (≈29 years) | 378 | 138 | 36.5% | |
Moon | 27.3 | 29.5 | No | No |
Sun | 365.3 | 365.3 | No | No |
* On average
Table S3. Nature of the potential influence assumed in the control studies
Nature of the influence | ||
Astronomical | Social | |
Moon phase* | Yes | No |
Weekday | No | Yes |
Calendar month | Yes | Yes |
* Depends on the angular distance of the Moon concerning the Sun for an Earth observer
Table S4. War events during the 20th Century (1901-2000)
Event# | Beginning date | Name |
1 | Nov-1-1901 | Anglo-Aro War |
2 | Feb-8-1904 | Russo-Japanese War |
3 | May-23-1906 | Ottoman invasion of Persia |
4 | Jun-11-1907 | War of 1907 |
5 | Apr-30-1909 | Russian invasion of Tabriz |
6 | Jul-15-1911 | Paraguayan Civil War |
7 | Sep-29-1911 | Italo-Turkish War |
8 | Oct-10-1911 | First Sino-Tibetan War |
9 | Dec-1911* | Dominican Civil War |
10 | Dec-28-1911 | War of the Generals, civil War in Ecuador |
11 | Aug-29-1912 | United States invasion of Nicaragua |
12 | Oct-8-1912 | First Balkan War |
13 | Oct-1912* | Contestado War |
14 | Feb-2-1913 | Sino–Mongolian War |
15 | Jun-29-1913 | Second Balkan War |
16 | Nov-1913* | Urtatagai conflict |
17 | Mar-1914* | Bluff War |
18 | Apr-21-1914 | United States invasion of Veracruz |
19 | May-31-1914 | Truku War |
20 | Jul-28-1914 | World War I |
21 | Jul-28-1915 | United States invasion of Haiti |
22 | Nov-19-1915 | Volta-Bani War |
23 | May-5-1916 | United States invasion of the Dominican Republic |
24 | Mar-8-1917 | Russian Civil War |
25 | Nov-8-1917 | Ukrainian–Soviet War |
26 | Jan-27-1918 | Finnish Civil War |
27 | Mar-30-1918 | Armenian–Azerbaijani War |
28 | Jun-15-1918 | Adubi War, between British Empire and rebels |
29 | Oct-25-1918 | Hungarian Civil War |
30 | Nov-1-1918 | Polish–Ukrainian War |
31 | Nov-23-1918 | Austro-Slovene conflict in Carinthia |
32 | Nov-28-1918 | Estonian War of Independence |
33 | Dec-5-1918 | Latvian War of Independence |
34 | Dec-7-1918 | Armeno-Georgian War |
35 | Dec-7-1918 | Franco-Turkish War |
36 | Dec-12-1918 | Lithuanian–Soviet War |
37 | Feb-14-1919 | Polish-Soviet War |
38 | Mar-28-1919 | Hungarian–Czechoslovak War |
39 | May-6-1919 | Third Anglo-Afghan War |
40 | May-15-1919 | Greco-Turkish War |
41 | May-19-1919 | Turkish War of Independence |
42 | Dec-13-1919 | Hungarian–Romanian War |
43 | Mar-8-1920 | Franco-Syrian War |
44 | Jun-4-1920 | Vlora War |
45 | Jul-14-1920 | Zhili–Anhui War |
46 | Sep-24-1920 | Turkish–Armenian War |
47 | Feb-15-1921 | Russian invasion of Georgia |
48 | Feb-21-1921 | Coto War |
49 | Nov-6-1921 | Soviet–Finnish conflict |
50 | May-27-1922 | Paraguayan Civil War |
51 | Jun-26-1922 | Irish Civil War |
52 | Mar-20-1923 | Posey War |
53 | Feb-2-1924 | Second Honduran Civil War |
54 | Sep-15-1924 | Second Zhili–Fengtian War |
55 | Mar-9-1925 | Pink's War |
56 | Nov-22-1925 | Anti-Fengtian War |
57 | Nov-27-1925 | Urtagai conflict |
58 | May-2-1926 | Nicaraguan Civil War |
59 | Aug-1-1927 | Chinese Civil War |
60 | Nov-14-1928 | Afghan Civil War |
61 | Mar-27-1929 | Chiang-Gui War |
62 | Jul-22-1929 | Sino-Soviet conflict |
63 | Mar-14-1930 | Central Plains War |
64 | Sep-18-1931 | Japan invades Manchuria |
65 | Mar-1-1932 | Soviet-Japanese Border War |
66 | Aug-28-1932 | Ecuadorian Civil War |
67 | Sep-9-1932 | Chaco War between Bolivia and Paraguay |
68 | Jan-16-1934 | Soviet invasion of Xinjiang |
69 | Feb-12-1934 | Austrian Civil War |
70 | Mar-22-1934 | Saudi–Yemeni War |
71 | Oct-3-1935 | Second Italo-Abyssinian War |
72 | Jul-18-1936 | Spanish Civil War |
73 | Jul-7-1937 | Beginning of World War II in the Far East |
74 | Mar-14-1939 | Hungary-Ukrainian War |
75 | Mar-23-1939 | Slovak–Hungarian War |
76 | Apr-7-1939 | Italian invasion of Albania |
77 | Sep-1-1939 | World War II in Europe |
78 | Dec-7-1941 | World War II in the Pacific |
79 | Sep-13-1945 | War in Vietnam |
80 | Mar-30-1946 | Greek Civil War |
81 | Dec-19-1946 | First Indochina War |
82 | Mar-7-1947 | Paraguayan Civil War |
83 | Aug-14-1947 | First Indo-Pakistani War |
84 | Nov-30-1947 | Civil War in Mandatory Palestine |
85 | Mar-12-1948 | Costa Rican Civil War |
86 | Apr-2-1948 | Civil War in Myanmar |
87 | May-15-1948 | Arab–Israeli War |
88 | Jun-25-1950 | Korean War |
89 | Aug-31-1952 | Invasion of Hamasa |
90 | Oct-10-1954 | Jebel Akhdar War in Oman |
91 | Nov-1-1954 | Algerian War |
92 | Aug-18-1955 | First Sudanese Civil War |
93 | Nov-1-1955 | Vietnam War |
94 | Oct-23-1957 | Ifni War |
95 | Dec-30-1958 | Mexico–Guatemala conflict |
96 | Apr-24-1959 | Cuban invasion of Panama |
97 | May-23-1959 | Laotian Civil War |
98 | Jun-14-1959 | Cuban invasion of Dominican Republic |
99 | Nov-13-1960 | Guatemalan Civil War |
100 | Feb-4-1961 | Angolan War of Independence |
101 | Apr-17-1961 | United States invasion of Bay of Pigs |
102 | Sep-1-1961 | Eritrean War of Independence |
103 | Sep-11-1961 | First Iraqi–Kurdish War |
104 | Sep-26-1962 | North Yemen Civil War |
105 | Oct-20-1962 | Sino-Indian War |
106 | Jan-23-1963 | Guinea-Bissau War of Independence |
107 | Sep-25-1963 | The Sand War |
108 | Nov-22-1963 | Shifta War |
109 | Dec-27-1963 | First Rwanda Civil War |
110 | Feb-6-1964 | Ethiopian–Somali Border War |
111 | Jul-4-1964 | Rhodesian Bush War |
112 | Sep-25-1964 | Mozambique War of Independence |
113 | Apr-24-1965 | Dominican Civil War |
114 | Aug-5-1965 | Second Indo-Pakistani War |
115 | Nov-1-1965 | Chadian Civil War |
116 | Aug-26-1966 | South African Border War |
117 | Oct-5-1966 | Second Korean War |
118 | Nov-3-1966 | Ñancahuazú Guerrilla War |
119 | Mar-11-1967 | Cambodian Civil War |
120 | May-8-1967 | Cuban invasion of Venezuela |
121 | Jun-5-1967 | Six-Day Arab-Israeli War |
122 | Jul-1-1967 | War of Attrition |
123 | Jul-6-1967 | Nigerian Civil War |
124 | Sep-11-1967 | Sino-Indian War |
125 | Aug-20-1968 | Warsaw Pact invasion of Czechoslovakia |
126 | Mar-2-1969 | Sino-Soviet border conflict |
127 | Jul-14-1969 | Football War |
128 | Nov-27-1969 | Al-Wadiah War |
129 | Mar-26-1971 | Bangladesh Liberation War |
130 | Dec-3-1971 | Third Indo-Pakistani War |
131 | Feb-1972* | First Eritrean Civil War |
132 | Sep-18-1972 | Invasion of Uganda |
133 | Oct-6-1973 | Yom Kippur War |
134 | Apr-1-1974 | Second Iraqi–Kurdish War |
135 | Jul-20-1974 | Turko Cypriot War |
136 | Sep-12-1974 | Ethiopian Civil War |
137 | Apr-13-1975 | Lebanese Civil War |
138 | Oct-30-1975 | Western Sahara War |
139 | Nov-8-1975 | Cabinda War |
140 | Nov-11-1975 | Angolan Civil War |
141 | Dec-7-1975 | Indonesian invasion of East Timor |
142 | Jul-13-1977 | Ethio-Somali War |
143 | Jul-21-1977 | Egyptian-Libyan War |
144 | Apr-27-1978 | War in Afghanistan |
145 | Oct-9-1978 | Uganda-Tanzania War |
146 | Dec-25-1978 | Cambodian-Vietnamese War |
147 | Feb-17-1979 | Sino-Vietnamese War |
148 | Feb-24-1979 | Second Yemenite War |
149 | Oct-15-1979 | Salvadoran Civil War |
150 | Dec-24-1979 | Soviet-Afghan War |
151 | Feb-1980* | Second Eritrean Civil War |
152 | Jul-29-1980 | Coconut War |
153 | Sep-22-1980 | Iran-Iraq War |
154 | Oct-8-1980 | Ugandan Bush War |
155 | Jan-25-1981 | Paquisha War |
156 | Apr-2-1982 | Falklands War |
157 | Jun-6-1982 | Lebanon War - Operation Peace for Galilee |
158 | Jun-30-1982 | Ethiopian-Somali Border War |
159 | Jun-5-1983 | Second Sudanese Civil War |
160 | Jul-23-1983 | Sri Lankan Civil War |
161 | Oct-25-1983 | Invasion of Grenada |
162 | Apr-13-1984 | Siachen War |
163 | Dec-25-1985 | Agacher Strip War |
164 | Jan-12-1986 | South Yemen Civil War |
165 | Nov-29-1986 | Surinamese Interior War |
166 | Feb-20-1988 | Nagorno-Karabakh War |
167 | Dec-1-1988 | Bougainville Civil War |
168 | Feb-15-1989 | Afghan Civil War |
169 | Apr-9-1989 | Mauritania–Senegal Border War |
170 | Dec-20-1989 | United States invasion of Panama |
171 | Dec-24-1989 | First Liberian Civil War |
172 | Aug-2-1990 | Gulf War |
173 | Oct-1-1990 | Rwanda Civil War |
174 | Nov-2-1990 | Transnistria War |
175 | Jan-5-1991 | South Ossetia War |
176 | Mar-23-1991 | Sierra Leone Civil War |
177 | Mar-31-1991 | Croatian War of Independence |
178 | Jun-27-1991 | Ten-Day War in Slovenia |
179 | Oct-31-1991 | Djiboutian Civil War |
180 | Nov-1-1991 | Chechen-Russian conflict |
181 | Dec-22-1991 | Georgian Civil War |
182 | Dec-26-1991 | Algerian Civil War |
183 | Apr-6-1992 | Bosnian War begins |
184 | Apr-28-1992 | Afghan Civil War |
185 | May-5-1992 | Tajikistani Civil War |
186 | Aug-14-1992 | War in Abkhazia |
187 | Oct-30-1992 | Ossetian-Ingush conflict |
188 | Oct-21-1993 | Burundian Civil War |
189 | May-1-1994 | Iraqi Kurdish Civil War |
190 | May-4-1994 | First Yemeni Civil War |
191 | Dec-11-1994 | First Chechen War |
192 | Jan-28-1995 | Cenepa War |
193 | Dec-15-1995 | Hanish Islands conflict |
194 | Feb-13-1996 | Nepalese Civil War |
195 | Sep-27-1996 | Afghan Civil War |
196 | Oct-24-1996 | First Congo War |
197 | Jan-16-1997 | Albanian Civil War |
198 | Jun-5-1997 | Republic of the Congo Civil War |
199 | Feb-28-1998 | Kosovo War |
200 | May-1-1998 | Saudi-Yemeni Border Conflict |
201 | May-6-1998 | Eritrean–Ethiopian War |
202 | May-18-1998 | War in Abkhazia |
203 | Jun-7-1998 | Guinea-Bissau Civil War |
204 | Aug-2-1998 | Second Congo War |
205 | Apr-21-1999 | Second Liberian Civil War |
206 | May-3-1999 | Fourth Indo-Pakistani War |
207 | Jul-3-1999 | Batken Conflict |
208 | Aug-7-1999 | War of Dagestan |
209 | Aug-26-1999 | Second Chechen War |
210 | Jun-5-2000 | Six-Day Uganda-Rwanda War |
* Undetermined beginning day
References for supplementary materials
Bowen, A. C. (1994). Ptolemy's Universe: The Natural Philosophical and Ethical Foundations of Ptolemy's Astronomy. Isis, 85(1), 140-141.
Bowen, A. C., & Rochberg, F. (2020). Hellenistic Astronomy: The Science in Its Contexts. Leiden: Brill Academic Pub.
Clifton, T. (2017). Gravity in the Solar System. In Gravity: A Very Short Introduction: Oxford University Press.
Feruglio, C., Fiore, F., França, F., Sacchi, N., Puccetti, S., Comastri, A., . . . Zamorani, G. (2008). The XMM-Newton survey of the ELAIS-S1 field II: optical identifications and multiwavelength catalogue of X-ray sources. Astronomy and Astrophysics.
Fornasa, M., & Sánchez-Conde, M. A. (2015). The nature of the Diffuse Gamma-Ray Background. Physics Reports, 598, 1-58.
Fraknoi, A. (2014). Light as a Cosmic Time Machine. Retrieved from Seeing in the Dark website: https://www.pbs.org/seeinginthedark/astronomy-topics/light-as-a-cosmic-time-machine.html
Gontier, N. (2016). Time: The Biggest Pattern in Natural History Research. Evolutionary Biology, 4(43), 604-637.
Hameroff, S., & Penrose, R. (2014). Consciousness in the universe: A review of the ‘Orch OR’ theory. Physics of Life Reviews, 11(1), 39-78.
Karttunen, H. (2007). Celestial Mechanics. In H. Karttunen, P. Kröger, H. Oja, M. Poutanen, & K. J. Donner (Eds.), Fundmental Astronomy (5th ed., pp. 113-130). Berlin Heidelberg: Springer-Verlag.
Kellermann, K. I. (1980). The Space Distribution of Radio Sources Based on Short Wavelength Surveys. Physica Scripta, 21(5), 664.
Lahav, N., & Neemeh, Z. A. (2022). A Relativistic Theory of Consciousness. Frontiers in Psychology, 12.
Schlickeiser, R., Oppotsch, J., Zhang, M., & Pogorelov, N. V. (2019). On the Anisotropy of Galactic Cosmic Rays. The Astrophysical Journal, 879(1), 29.