# Causal sets

The

**causal sets**programme is an approach toquantum gravity . Its founding principle is thatspacetime is fundamentally discrete and that the spacetime points are related by apartial order . This partial order has the physical meaning of thecausality relation s between spacetime points.Causal sets was initiated by

Rafael Sorkin who continues to be the main proponent of the programme. He has coined the slogan "Order + Number = Geometry" to characterise the above argument. The programme provides a theory in which spacetime is fundamentally discrete while retaining localLorentz invariance .**Definition**A

**causal set**(or**causet**) is a set $C$ with a partial order relation $prec$ which is

*Irreflexive : $x\; prec\; x$

*Transitive : $x\; prec\; y\; prec\; z$ implies $x\; prec\; z$

* Locally finite:**card**$(\{y\; in\; C\; |\; x\; prec\; y\; prec\; z\})\; <\; infty$for all $x,\; y,\; z\; in\; C$. Here**card**($A$) denotes thecardinality of a set $A$.Given a causal set we may ask whether it can be "embedded" into a

Lorentzian manifold . An embedding would be a map taking elements of the causal set into points in the manifold such that the order relation of the causal set matches the causal ordering of the manifold. A further criterion is needed however before the embedding is suitable. If, on average, the number of causal set elements mapped into a region of the manifold is proportional to the volume of the region then the embedding is said to be "faithful". In this case we can consider the causal set to be 'manifold-like'A central conjecture to the causal set programme is that the same causal set cannot be faithfully embedded into two spacetimes which are not similar on large scales. This is called the "hauptvermutung", meaning 'fundamental conjecture'. It is difficult to define this conjecture precisely because it is difficult to decide when two spacetimes are 'similar on large scales'.

Modelling spacetime as a causal set would require us to restrict attention to those causal sets which are 'manifold-like'. Given a causal set this is a difficult property to determine.

**Sprinkling**The difficulty of determining whether a causal set can be embedded into a manifold can be approached from the other direction. We can create a causal set by sprinkling points into a Lorentzian manifold. By sprinkling points in proportion to the volume of the spacetime regions and using the causal order relations in the manifold to induce order relations between the sprinkled points, we can produce a causal set which (by construction) can be faithfully embedded into the manifold.

To maintain Lorentz invariance this sprinkling of points must be done randomly using a

Poisson process . Thus the probability of sprinkling $n$ points into a region of volume $V$ is$P(n)\; =\; frac\{(\; ho\; V)^n\; e^\{-\; ho\; V\{n!\}$

where $ho$ is the density of the sprinkling.

Sprinkling points in on a regular lattice would not keep the number of points proportional to the region volume.

**Geometry**Some geometrical constructions in manifolds carry over to causal sets. When defining these we must remember to rely only on the causal set itself, not on any background spacetime into which it might be embedded. For an overview of these constructions, see G, Brightwell, R. Gregory, " [

*http://link.aps.org/abstract/PRL/v66/p260 Structure of random discrete spacetime*] ", Phys. Rev. Lett. 66, 260 - 263 (1991)] .**Geodesics**A "link" in a causal set is a pair of elements $x,\; y\; in\; C,!$ such that $x\; prec\; y$ but with no $z\; in\; C,!$ such that $x\; prec\; z\; prec\; y$.

A "chain" is a sequence of elements $x\_0,x\_1,ldots,x\_n$ such that $x\_i\; prec\; x\_\{i+1\}$ for $i=0,ldots,n-1$. The length of a chain is $n$, the number of relations used.

We can use this to define a

geodesic between two causal set elements. A geodesic between two elements $x,\; y\; in\; C$ is a chain consisting only of links such that

# $x\_0\; =\; x,!$ and $x\_n\; =\; y,!$

# The length of the chain, $n$, is maximal over all chains from $x,$ to $y,$.In general there will be more than one geodesic between two elements.**Dimension estimators**Much work has been done in estimating the manifold

dimension of a causal set. This involves algorithms using the causal set aiming to give the dimension of the manifold into which it can be faithfully embedded. The algorithms developed so far are based on finding the dimension of aMinkowski spacetime into which the causal set can be faithfully embedded.*

**Myrheim-Meyer dimension**This approach relies on estimating the number of $k$-length chains present in a sprinkling into $d$-dimensional Minkowski spacetime. Counting the number of $k$-length chains in the causal set then allows an estimate for $d$ to be made.*

**Midpoint-scaling dimension**This approach relies on the relationship between the proper time between two points in Minkowski spacetime and the volume of the spacetime interval between them. By computing the maximal chain length (to estimate the proper time) between two points $x,$ and $y,$ and counting the number of elements $z,$ such that $x\; prec\; z\; prec\; y$ (to estimate the volume of the spacetime interval) the dimension of the spacetime can be calculated.These estimators should give the correct dimension for causal sets generated by high-density sprinklings into $d$-dimensional Minkowski spacetime. Tests in conformally-flat spacetimesD.D. Reid, "Manifold dimension of a causal set: Tests in conformally flat spacetimes", Phys.Rev. D67 (2003) 024034, ] have shown these two methods to be accurate.

**Dynamics**An ongoing task is to develop the correct dynamics for causal sets. These would provide a set of rules that determine which causal sets correspond to physically realistic

spacetime s. The most popular approach to developing causal set dynamics is based on the "sum-over-histories " version ofquantum mechanics . This approach would perform a "sum-over-causal sets" by "growing" a causal set one element at a time. Elements would be added according to quantum mechanical rules andinterference would ensure a large manifold-like spacetime would dominate the contributions. The best model for dynamics at the moment is a classical model in which elements are added according to probabilities. This model, due to David Rideout andRafael Sorkin , is known as "classical sequential growth" (CSG) dynamics [*D.P. Rideout, R.D. Sorkin; "A classical sequential growth dynamics for causal sets", Phys. Rev D, 6, 024002 (2000)*] . The classical sequential growth model is a way to generate causal sets by adding new elements one after another. Rules for how new elements are added are specified and, depending on the parameters in the model, different causal sets result.**ee also***

Order theory

*General relativity

*Causal set theory bibliography **References****External links*** [

*http://arxiv.org/abs/gr-qc/0601121 The causal set approach to quantum gravity*] a review article by Joe Henson on causal sets* [

*http://link.aps.org/abstract/PRL/v59/p521 Space-time as a causal set*] - one of the first papers by Luca Bombelli, Joohan Lee, David Meyer, and Rafael D. Sorkin* [

*http://www.einstein-online.info/en/spotlights/causal_sets/index.html Geometry from order: causal sets*] - non-technical article by Rafael D. Sorkin on [*http://www.einstein-online.info/en Einstein Online*]

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