Abstract
We attempt to make superdeterminism more intuitive, notably by simulating a deterministic model system, a billiard game. In this system an initial ‘bang’ correlates all events, just as in the superdeterministic universe. We introduce the notions of ‘strong’ and ‘soft’ superdeterminism, in order to clarify debates in the literature. Based on the analogy with billiards, we show that superdeterministic correlations may exist as a matter of principle, but be undetectable for all practical purposes. Even if inaccessible, such strong-superdeterministic correlations can explain why soft-, or effective, superdeterministic theories can be built. We counter classic objections to superdeterminism such as the claim that it would be at odds with the scientific method, and with the construction of new theories. Finally, we show that probability theory, as a physical theory, indicates that superdeterminism has a greater explanatory power than its competitors: it can coherently answer questions from probability theory for which other positions remain powerless. Since probability theory is, in a sense, the most unifying physics theory (all physical systems comply with it), this argument confers considerable weight.
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Notes
Parts of this Section were elaborated in greater detail in [27].
Indeed, a relativistic version of Bohmian mechanics is lacking (see [29], § 14).
Equations (2–3) are probabilistic assumptions that are surely intuitive, but there is no proof within an accepted physics theory that they necessarily apply to a given physical system.
Hossenfelder and Palmer do not consider future input dependence and retrocausality as different from SD; they state in a ‘disambiguation’ section: “But some authors […] distinguish Superdeterminism from retrocausality (or Future Input Dependence, respectively)” [11]. Does this mean that retrocausality is (a form of) SD? Our main point is that relying on unusual types of causality (as mentioned in [12], p. 8) is not necessary: future input dependence, we believe, is nothing else than an effective type of SD, which can safely be justified by the classic SD relying on the classic causality and the usual causal arrow of time, as argued in the next section.
The model of [12] is in any case a soft-superdeterministic model in the sense that (a, b) refer to angles, not angle choices.
A possible reason why one can measure this quantum correlation, in contrast to many of the correlations between macroscopic variables, is that x and y refer to 1-particle variables of a fundamental theory, quantum mechanics. Usual classical systems have too many degrees of freedom and too many interactions between them, so they appear uncorrelated (unless a strong enough cause correlates them). This is a possible answer to questions asked in [19,20,21].
In quantum experiments decoherence is ubiquitous and one needs to fix not only a and b but a whole series of other variables; a specific well-controlled quantum set-up is needed to detect correlations.
Such a view immediately begs the question: what is the entity that materializes, or is responsible for, such an absolutely independent free will? An immaterial mind? A homunculus in the brain? There is no evidence for these in neuroscience.
This has non-trivial consequences also for deterministic theories: it implies for instance that two statistically independent stochastic variables x and y with an underlying deterministic (relativistic) dynamics must be functions x = fx(λx), y = fy(λy), where the sets of variables λx and λy share no variables.
If one finds our answer too speculative, note that to come to our final conclusion it is enough that the first two questions are answered.
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Acknowledgements
We would like to thank the participants to the conference “Superdeterminism and Retrocausality”, and especially the organizers, Sabine Hossenfelder, Huw Price and Tim Palmer, for helpful discussions.
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Appendix. Numerical Data for the Billiard Simulations
Appendix. Numerical Data for the Billiard Simulations
Here we provide the numerical data for the billiard simulations presented in Sect. 4. Figure 2 is an on-scale drawing of the billiard table at simulation time t = 0, containing 11 balls at rest with radius 20 (all parameters are in arbitrary units). Other parameters of the experiment:
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Dimensions of the table: 600 × 300
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Length of a time tick: 0.1 (experiments can run till t = 250, 500, 1000 etc., cf. text)
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Initial positions of the balls (given as (x, y) coordinates of the balls’ centers assuming that (0, 0) is the lower left corner of the table):
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green cue ball: (200, 155 ± ε), ε = 3 (uniform distribution, cf. text)
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other balls: (300, 150), (340, 120), (340, 180), (380, 210), (380, 150), (380, 90), (420, 240) [red ball], (420, 180), (420, 120), (420, 60)
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Initial velocity of the green ball: (vx, vy) = (20, 0)
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Positions of the test squares (given as (x1, y1) – upper left corner, and (x2, y2) – lower right corner):
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(150, 270), (240, 180)
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(430, 120), (520, 30)
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For the experiment of Fig. 4 (Brownian motion), all the positions of all balls are uniformly distributed with x ∈ [20, 580] and y ∈ [20, 280] (intersections of the balls are not allowed). The initial velocities are distributed uniformly such that vx ∈ [−20, 20] and vy ∈ [−20, 20].
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Nikolaev, V., Vervoort, L. Aspects of Superdeterminism Made Intuitive. Found Phys 53, 17 (2023). https://doi.org/10.1007/s10701-022-00648-9
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DOI: https://doi.org/10.1007/s10701-022-00648-9