chore(docs): cut new docs version for tag v0.36.0

docs/versioned_docs/version-v0.36.0/explainers/cspell.json

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+{
+    "words": [
+        "Cryptdoku"
+    ]
+}

docs/versioned_docs/version-v0.36.0/explainers/explainer-oracle.md

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+---
+title: Oracles
+description: This guide provides an in-depth understanding of how Oracles work in Noir programming. Learn how to use outside calculations in your programs, constrain oracles, and understand their uses and limitations.
+keywords:
+  - Noir Programming
+  - Oracles
+  - JSON-RPC
+  - Foreign Call Handlers
+  - Constrained Functions
+  - Blockchain Programming
+sidebar_position: 1
+---
+
+If you've seen "The Matrix" you may recall "The Oracle" as Gloria Foster smoking cigarettes and baking cookies. While she appears to "know things", she is actually providing a calculation of a pre-determined future. Noir Oracles are similar, in a way. They don't calculate the future (yet), but they allow you to use outside calculations in your programs.
+
+![matrix oracle prediction](@site/static/img/memes/matrix_oracle.jpeg)
+
+A Noir program is usually self-contained. You can pass certain inputs to it, and it will generate a deterministic output for those inputs. But what if you wanted to defer some calculation to an outside process or source?
+
+Oracles are functions that provide this feature.
+
+## Use cases
+
+An example usage for Oracles is proving something on-chain. For example, proving that the ETH-USDC quote was below a certain target at a certain block time. Or even making more complex proofs like proving the ownership of an NFT as an anonymous login method.
+
+Another interesting use case is to defer expensive calculations to be made outside of the Noir program, and then constraining the result; similar to the use of [unconstrained functions](../noir/concepts//unconstrained.md).
+
+In short, anything that can be constrained in a Noir program but needs to be fetched from an external source is a great candidate to be used in oracles.
+
+## Constraining oracles
+
+Just like in The Matrix, Oracles are powerful. But with great power, comes great responsibility. Just because you're using them in a Noir program doesn't mean they're true. Noir has no superpowers. If you want to prove that Portugal won the Euro Cup 2016, you're still relying on potentially untrusted information.
+
+To give a concrete example, Alice wants to login to the [NounsDAO](https://nouns.wtf/) forum with her username "noir_nouner" by proving she owns a noun without revealing her ethereum address. Her Noir program could have an oracle call like this:
+
+```rust
+#[oracle(getNoun)]
+unconstrained fn get_noun(address: Field) -> Field
+```
+
+This oracle could naively resolve with the number of Nouns she possesses. However, it is useless as a trusted source, as the oracle could resolve to anything Alice wants. In order to make this oracle call actually useful, Alice would need to constrain the response from the oracle, by proving her address and the noun count belongs to the state tree of the contract.
+
+In short, **Oracles don't prove anything. Your Noir program does.**
+
+:::danger
+
+If you don't constrain the return of your oracle, you could be clearly opening an attack vector on your Noir program. Make double-triple sure that the return of an oracle call is constrained!
+
+:::
+
+## How to use Oracles
+
+On CLI, Nargo resolves oracles by making JSON RPC calls, which means it would require an RPC node to be running.
+
+In JavaScript, NoirJS accepts and resolves arbitrary call handlers (that is, not limited to JSON) as long as they match the expected types the developer defines. Refer to [Foreign Call Handler](../reference/NoirJS/noir_js/type-aliases/ForeignCallHandler.md) to learn more about NoirJS's call handling.
+
+If you want to build using oracles, follow through to the [oracle guide](../how_to/how-to-oracles.md) for a simple example on how to do that.

docs/versioned_docs/version-v0.36.0/explainers/explainer-recursion.md

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+---
+title: Recursive proofs
+description: Explore the concept of recursive proofs in Zero-Knowledge programming. Understand how recursion works in Noir, a language for writing smart contracts on the EVM blockchain. Learn through practical examples like Alice and Bob's guessing game, Charlie's recursive merkle tree, and Daniel's reusable components. Discover how to use recursive proofs to optimize computational resources and improve efficiency.
+
+keywords:
+  [
+    "Recursive Proofs",
+    "Zero-Knowledge Programming",
+    "Noir",
+    "EVM Blockchain",
+    "Smart Contracts",
+    "Recursion in Noir",
+    "Alice and Bob Guessing Game",
+    "Recursive Merkle Tree",
+    "Reusable Components",
+    "Optimizing Computational Resources",
+    "Improving Efficiency",
+    "Verification Key",
+    "Aggregation",
+    "Recursive zkSNARK schemes",
+    "PLONK",
+    "Proving and Verification Keys"
+  ]
+sidebar_position: 1
+pagination_next: how_to/how-to-recursion
+---
+
+In programming, we tend to think of recursion as something calling itself. A classic example would be the calculation of the factorial of a number:
+
+```js
+function factorial(n) {
+    if (n === 0 || n === 1) {
+        return 1;
+    } else {
+        return n * factorial(n - 1);
+    }
+}
+```
+
+In this case, while `n` is not `1`, this function will keep calling itself until it hits the base case, bubbling up the result on the call stack:
+
+```md
+        Is `n` 1?  <---------
+           /\               /
+          /  \         n = n -1 
+         /    \           /
+       Yes     No --------
+```
+
+In Zero-Knowledge, recursion has some similarities.
+
+It is not a Noir function calling itself, but a proof being used as an input to another circuit. In short, you verify one proof *inside* another proof, returning the proof that both proofs are valid.
+
+This means that, given enough computational resources, you can prove the correctness of any arbitrary number of proofs in a single proof. This could be useful to design state channels (for which a common example would be [Bitcoin's Lightning Network](https://en.wikipedia.org/wiki/Lightning_Network)), to save on gas costs by settling one proof on-chain, or simply to make business logic less dependent on a consensus mechanism.
+
+## Examples
+
+Let us look at some of these examples
+
+### Alice and Bob - Guessing game
+
+Alice and Bob are friends, and they like guessing games. They want to play a guessing game online, but for that, they need a trusted third-party that knows both of their secrets and finishes the game once someone wins.
+
+So, they use zero-knowledge proofs. Alice tries to guess Bob's number, and Bob will generate a ZK proof stating whether she succeeded or failed.
+
+This ZK proof can go on a smart contract, revealing the winner and even giving prizes. However, this means every turn needs to be verified on-chain. This incurs some cost and waiting time that may simply make the game too expensive or time-consuming to be worth it.
+
+As a solution, Alice proposes the following: "what if Bob generates his proof, and instead of sending it on-chain, I verify it *within* my own proof before playing my own turn?".
+
+She can then generate a proof that she verified his proof, and so on.
+
+```md
+      Did you fail?  <--------------------------
+           / \                                  /
+          /   \                             n = n -1 
+         /     \                              /
+       Yes      No                           /
+        |        |                          /
+        |        |                         /
+        |      You win                    /
+        |                                /
+        |                               /
+Generate proof of that                 /
+        +                             /
+    my own guess     ----------------
+```
+
+### Charlie - Recursive merkle tree
+
+Charlie is a concerned citizen, and wants to be sure his vote in an election is accounted for. He votes with a ZK proof, but he has no way of knowing that his ZK proof was included in the total vote count!
+
+If the vote collector puts all of the votes into a [Merkle tree](https://en.wikipedia.org/wiki/Merkle_tree), everyone can prove the verification of two proofs within one proof, as such:
+
+```md
+                    abcd
+           __________|______________
+          |                         |
+         ab                         cd 
+     _____|_____              ______|______
+    |           |            |             |              
+  alice        bob        charlie        daniel 
+```
+
+Doing this recursively allows us to arrive on a final proof `abcd` which if true, verifies the correctness of all the votes.
+
+### Daniel - Reusable components
+
+Daniel has a big circuit and a big headache. A part of his circuit is a setup phase that finishes with some assertions that need to be made. But that section alone takes most of the proving time, and is largely independent of the rest of the circuit.
+
+He might find it more efficient to generate a proof for that setup phase separately, and verify that proof recursively in the actual business logic section of his circuit. This will allow for parallelization of both proofs, which results in a considerable speedup.
+
+## What params do I need
+
+As you can see in the [recursion reference](noir/standard_library/recursion.mdx), a simple recursive proof requires:
+
+- The proof to verify
+- The Verification Key of the circuit that generated the proof
+- A hash of this verification key, as it's needed for some backends
+- The public inputs for the proof
+
+:::info
+
+Recursive zkSNARK schemes do not necessarily "verify a proof" in the sense that you expect a true or false to be spit out by the verifier. Rather an aggregation object is built over the public inputs.
+
+So, taking the example of Alice and Bob and their guessing game:
+
+- Alice makes her guess. Her proof is *not* recursive: it doesn't verify any proof within it! It's just a standard `assert(x != y)` circuit
+- Bob verifies Alice's proof and makes his own guess. In this circuit, he doesn't exactly *prove* the verification of Alice's proof. Instead, he *aggregates* his proof to Alice's proof. The actual verification is done when the full proof is verified, for example when using `nargo verify` or through the verifier smart contract.
+
+We can imagine recursive proofs a [relay race](https://en.wikipedia.org/wiki/Relay_race). The first runner doesn't have to receive the baton from anyone else, as he/she already starts with it. But when his/her turn is over, the next runner needs to receive it, run a bit more, and pass it along. Even though every runner could theoretically verify the baton mid-run (why not? 🏃🔍), only at the end of the race does the referee verify that the whole race is valid.
+
+:::
+
+## Some architecture
+
+As with everything in computer science, there's no one-size-fits all. But there are some patterns that could help understanding and implementing them. To give three examples:
+
+### Adding some logic to a proof verification
+
+This would be an approach for something like our guessing game, where proofs are sent back and forth and are verified by each opponent. This circuit would be divided in two sections:
+
+- A `recursive verification` section, which would be just the call to `std::verify_proof`, and that would be skipped on the first move (since there's no proof to verify)
+- A `guessing` section, which is basically the logic part where the actual guessing happens
+
+In such a situation, and assuming Alice is first, she would skip the first part and try to guess Bob's number. Bob would then verify her proof on the first section of his run, and try to guess Alice's number on the second part, and so on.
+
+### Aggregating proofs
+
+In some one-way interaction situations, recursion would allow for aggregation of simple proofs that don't need to be immediately verified on-chain or elsewhere.
+
+To give a practical example, a barman wouldn't need to verify a "proof-of-age" on-chain every time he serves alcohol to a customer. Instead, the architecture would comprise two circuits:
+
+- A `main`, non-recursive circuit with some logic
+- A `recursive` circuit meant to verify two proofs in one proof
+
+The customer's proofs would be intermediate, and made on their phones, and the barman could just verify them locally. He would then aggregate them into a final proof sent on-chain (or elsewhere) at the end of the day.
+
+### Recursively verifying different circuits
+
+Nothing prevents you from verifying different circuits in a recursive proof, for example:
+
+- A `circuit1` circuit
+- A `circuit2` circuit
+- A `recursive` circuit
+
+In this example, a regulator could verify that taxes were paid for a specific purchase by aggregating both a `payer` circuit (proving that a purchase was made and taxes were paid), and a `receipt` circuit (proving that the payment was received)
+
+## How fast is it
+
+At the time of writing, verifying recursive proofs is surprisingly fast. This is because most of the time is spent on generating the verification key that will be used to generate the next proof. So you are able to cache the verification key and reuse it later.
+
+Currently, Noir JS packages don't expose the functionality of loading proving and verification keys, but that feature exists in the underlying `bb.js` package.
+
+## How can I try it
+
+Learn more about using recursion in Nargo and NoirJS in the [how-to guide](../how_to/how-to-recursion.md) and see a full example in [noir-examples](https://github.com/noir-lang/noir-examples).