# Background

I once implemented a datatype representing arbitrary real numbers in Haskell. It labels every real numbers by having a Cauchy sequence converging to it. That will let $$\mathbb{R}$$ be in the usual topology. I also implemented addition, subtraction, multiplication, and division.

But my teacher said, "This doesn't seem to be a good idea. Since comparison is undecidable here, this doesn't look very practical. In particular, letting division by 0 to fall in an infinite loop doesn't look good."

So I wanted my datatype to extend $$\mathbb{Q}$$. Since equality comparison of $$\mathbb{Q}$$ is decidable, $$\mathbb{Q}$$ is in discrete topology. That means a topology on $$\mathbb{R}$$ must be finer than the discrete topology on $$\mathbb{Q}$$.

But, I think I found that, even if I could implement such datatype, it will be impractical.

# Proof, step 1

Let $$\mathbb{R}$$ be finer than $$\mathbb{Q}$$ in discrete topology. Then $$\{0\}$$ is open in $$\mathbb{R}$$. Assume $$+ : \mathbb{R}^2 → \mathbb{R}$$ is continuous. Then $$\{(x,-x): x \in \mathbb{R}\}$$ is open in $$\mathbb{R}^2$$. Since $$\mathbb{R}^2$$ is in product topology, $$\{(x,-x)\}$$ is a basis element of $$\mathbb{R}^2$$ for every $$x \in \mathbb{R}$$. It follows that $$\{x\}$$ is a basis element of $$\mathbb{R}$$ for every $$x \in \mathbb{R}$$. That is, $$\mathbb{R}$$ is in discrete topology.

# Proof, step 2

Since $$\mathbb{R}$$ is in discrete topology, $$\mathbb{R}$$ is computably equality comparable. This is a contradiction, so $$+$$ is not continuous, and thus not computable.

# Question

What is bugging me is the bolded text. It is well-known that every computable function is continuous (Weihrauch 2000, p. 6). Though the analytic definition and the topological definition of continuity coincide in functions from and to Euclidean spaces, $$\mathbb{R}$$ above is not a Euclidean space. So I'm unsure whether my proof is correct. What is the definition of "continuity" in computable analysis?

• I don't follow your reasoning. Assuming by $\mathbb{R}$ you mean the set of real numbers, the topology on $\mathbb{R}$ is not a discrete topology. $\{0\}$ is not an open set in $\mathbb{R}$. It looks like you are starting by assuming "False" and then deriving all sorts of consequences from it. It's not clear to me what operations you want to support in your datatype, but the answer is probably that you can't support all of them.
– D.W.
Aug 23 '20 at 6:16
• @D.W. The keypoint is, $\mathbb{R}$ can be given a different topology, and I've tested what happens if I did so. Aug 23 '20 at 7:59
• I don't understand why "every computable function" should be continuous. Counterexamples: The functions floor(x) and sgn(x) are provided by all programming languages and they are not continuous. Aug 23 '20 at 13:31
• @MartinRosenau Your floor and sgn are computable because their domain is floating-point numbers. On all reals, they are not computable. Aug 23 '20 at 13:36
• @MartinRosenau No. The Heaviside step function $H$, where $H(0) = 1$, is right-continuous, but if it were computable, comparison would be decidable. This is a contradiction. Aug 23 '20 at 21:59

Different people have different views on what the definition of continuity should be, but the way I see it, we should define continuity to be computability relative to some oracle. For example:

Definition: A function $$f : \mathbf{X} \to \mathbf{Y}$$ is continuous, if there is a computable partial function $$F :\subseteq \mathbf{X} \times \mathbb{N}^\mathbb{N} \to \mathbf{Y}$$ and some $$p \in \mathbb{N}^\mathbb{N}$$ such that $$f(x) = F(x,p)$$.

So the most primitive concept in handling a space is what representation we are using for it, which then yields the notion of computability, and from that we get the notion of continuity.

So far, the definition of continuity seems rather unrelated to continuity from topology, and one may wonder why that term has been chosen. One reason is that we usually use admissible representations, which have the characterization that the functions between them which are continuous in the computable analysis definition are exactly the functions which are continuous in the topological sense.

If we have an admissible representation $$\delta : \subseteq \Sigma^\mathbb{N} \to \mathbf{X}$$, we get the topology on $$\mathbf{X}$$ as the final topology along $$\delta$$, i.e. a set $$U \subseteq \mathbf{X}$$ is open iff there is a set $$W$$ of finite words such that $$\delta^{-1}(U) = \operatorname{dom}(\delta) \cap \bigcup_{w \in W} w\Sigma^\mathbb{N}$$. Matthias Schröder has shown that the topological spaces which have admissible representations are exactly the $$T_0$$ quotients of countably-based spaces.

Now to slowly come back to the starting point of your question, what prevents us from using the discrete topology on the reals? The reason we cannot do that is that every countably-based space is separable, ie has a (countable) dense sequence. Taking quotients preserves being separable, so every topology associated to a representation is necessarily separable. A discrete space is separable iff it is countable, so we cannot get the discrete topology on the reals.

There is a way to get an admissible representation of $$\mathbb{R}$$ that makes $$\mathbb{Q}$$ a discrete subspace (essentially, treat $$\mathbb{R}$$ as $$\mathbb{N}^{*} \cup \mathbb{N}^\mathbb{N}$$), but as you have argued in the question, that makes addition uncomputable (and overall, has very little resemblance to the reals as we would want them).

On a side note, that we cannot avoid getting stuck without even recognising it when accidentally trying to divide by $$0$$ is a significant obstacle if we are trying to do linear algebra with real numbers.

References:

Pieter Collins: Computable analysis with applications to dynamic systems. Math. Struct. Comput. Sci. 30(2): 173-233 (2020)

Martín Hötzel Escardó: Synthetic Topology: of Data Types and Classical Spaces. Electron. Notes Theor. Comput. Sci. 87: 21-156 (2004)

Takayuki Kihara, Arno Pauly: Dividing by Zero - How Bad Is It, Really?. MFCS 2016: 58:1-58:14

Arno Pauly: On the topological aspects of the theory of represented spaces. Computability 5(2): 159-180 (2016) arXiv

Matthias Schröder: Extended admissibility. Theor. Comput. Sci. 284(2): 519-538 (2002)

Arno's answer provides some very useful background reading material, I would just like to address your specific question about $$\mathbb{R}$$.

Let us first recall a result by Peter Hertling, see Theorem 4.1 in A Real Number Structure that is Effectively Categorical (PDF here), about computable structure of the real numbers. Suppose we have a representation of $$\mathbb{R}$$, i.e., a data structure representing the reals, such that:

• $$0$$ and $$1$$ are computable elements of $$\mathbb{R}$$,
• the field operations $$+$$, $$-$$, $$\times$$ and $$/$$ are computable (where division by zero is of course undefined)
• the limit operator, taking a rapid Cauchy sequence to its limit, is computable (a sequence $$(x_n)_n$$ is rapid when $$|x_n - x_m| \leq 2^{-\min(m,n)}$$).
• the strict order $$<$$ is semidecidable

The above conditions simply state that the reals should be a computable Cauchy ordered field, which is pretty much the computable version of the usual chracterization of reals (the Archimedean axiom holds as well, as it turns out).

Then it follows that:

1. The topology of $$\mathbb{R}$$ is the standard Euclidean topology
2. Equality is undecidable, or equivalently, testng for zero is undecidable.
3. Any two such structures are computably isomorphic.

These are unavoidable facts. Your teacher may think that not having decidable equality is unfortunate, or that division by zero should report an error, but that is impossible to arrange if one wants to keep the computable structure of the reals.

Regarding your implementation: it is vital that you represent a real with a Cauchy sequence together with information on how fast it converges. I hope you did that.