Incomplete port

.gitea/workflows/ci.yml

@@ -26,7 +26,7 @@ jobs:
 
       - name: "Download Typstyle"
         run: |
-          wget -q "https://github.com/Enter-tainer/typstyle/releases/download/v0.13.17/typstyle-x86_64-unknown-linux-musl"
+          wget -q "https://github.com/Enter-tainer/typstyle/releases/download/v0.12.14/typstyle-x86_64-unknown-linux-musl"
           chmod +x typstyle-x86_64-unknown-linux-musl
 
       - name: Check typst formatting
@@ -62,7 +62,7 @@ jobs:
       # more control anyway.
       - name: "Download Typst"
         run: |
-          wget -q "https://github.com/typst/typst/releases/download/v0.13.1/typst-x86_64-unknown-linux-musl.tar.xz"
+          wget -q "https://github.com/typst/typst/releases/download/v0.12.0/typst-x86_64-unknown-linux-musl.tar.xz"
           tar -xf "typst-x86_64-unknown-linux-musl.tar.xz"
           mv "typst-x86_64-unknown-linux-musl/typst" .
           rm "typst-x86_64-unknown-linux-musl.tar.xz"

lib/typst/local/handout/0.1.0/lib.typ

@@ -3,10 +3,13 @@
 // Re-exports
 // All functions that maybe used by client code are listed here
 #import "misc.typ": *
-#import "object.typ": definition, example, generic, problem, remark, theorem
+#import "object.typ": problem, definition, theorem, example, remark, generic
 #import "solution.typ": (
-  if_no_solutions, if_solutions, if_solutions_else, instructornote,
+  if_solutions,
-  sample_solution, solution,
+  if_no_solutions,
+  if_solutions_else,
+  solution,
+  instructornote,
 )
 
 
@@ -35,7 +38,10 @@
     margin: 20mm,
     width: 8.5in,
     height: 11in,
-    footer: align(center, context counter(page).display()),
+    footer: align(
+      center,
+      context counter(page).display(),
+    ),
     footer-descent: 5mm,
   )
 
@@ -96,8 +102,8 @@
 
   // Make handout title
   {
-    import "header.typ": make_header, short_solution_warning, solution_warning
+    import "header.typ": make_header, solution_warning, short_solution_warning
-    import "solution.typ": reset_solutions, solutions_state
+    import "solution.typ": solutions_state, reset_solutions
 
     reset_solutions()
 

lib/typst/local/handout/0.1.0/object.typ

@@ -29,7 +29,11 @@
   }
 
   // Render the object
-  block(above: 8mm, below: 2mm, text(weight: "bold", obj_content))
+  block(
+    above: 8mm,
+    below: 2mm,
+    text(weight: "bold", obj_content),
+  )
 
   // Generate labeled metadata for this object.
   //
@@ -53,7 +57,7 @@
   if not (
     it.element != none
       and it.element.has("value")
-      and type(it.element.value) == dictionary
+      and type(it.element.value) == "dictionary"
       and it.element.value.keys().contains(magic_key)
   ) {
     // This label is not attached to object metadata
@@ -96,5 +100,9 @@
 #let remark = _mkobj("Remark")
 
 #let generic(obj_content) = {
-  block(above: 8mm, below: 2mm, text(weight: "bold", obj_content))
+  block(
+    above: 8mm,
+    below: 2mm,
+    text(weight: "bold", obj_content),
+  )
 }

lib/typst/local/handout/0.1.0/solution.typ

@@ -1,4 +1,4 @@
-#import "misc.typ": oblue, ored
+#import "misc.typ": ored, oblue
 
 
 /// If false, hide instructor info.
@@ -61,7 +61,10 @@
 }
 
 #let solution(content) = {
-  if_solutions(align(center, stack(
+  if_solutions(
+    align(
+      center,
+      stack(
         block(
           width: 100%,
           breakable: false,
@@ -80,35 +83,16 @@
           inset: 3mm,
           align(left, content),
         ),
-  )))
-}
-
-#let sample_solution(content) = {
-  align(center, stack(
-    block(
-      width: 100%,
-      breakable: false,
-      fill: oblue,
-      stroke: oblue + 2pt,
-      inset: 1.5mm,
-      align(left, text(fill: white, weight: "bold", [Sample Solution:])),
       ),
-
-    block(
-      width: 100%,
-      height: auto,
-      breakable: false,
-      fill: oblue.lighten(80%).desaturate(10%),
-      stroke: oblue + 2pt,
-      inset: 3mm,
-      align(left, content),
     ),
-  ))
+  )
 }
 
-
 #let instructornote(content) = {
-  if_solutions(align(center, stack(
+  if_solutions(
+    align(
+      center,
+      stack(
         block(
           width: 100%,
           breakable: false,
@@ -127,5 +111,7 @@
           inset: 3mm,
           align(left, content),
         ),
-  )))
+      ),
+    ),
+  )
 }

src/Advanced/Fast Inverse Root/parts/02 float.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = Floats
 #definition()
@@ -33,7 +33,11 @@ Another way we can interpret a bit string is as a _signed floating-point decimal
 Floats represent a subset of the real numbers, and are interpreted as follows: \
 #note([The following only applies to floats that consist of 32 bits. We won't encounter any others today.])
 
-#align(center, box(inset: 2mm, cetz.canvas({
+#align(
+  center,
+  box(
+    inset: 2mm,
+    cetz.canvas({
       import cetz.draw: *
 
       let chars = (
@@ -92,7 +96,9 @@ Floats represent a subset of the real numbers, and are interpreted as follows: \
 
       line((3.10, y), (9.4, y))
       content((6.3, y - 0.2), [fraction])
-})))
+    }),
+  ),
+)
 
 - The first bit denotes the sign of the float's value
   We'll label it $s$. \

src/Advanced/Fast Inverse Root/parts/03 approx.typ

@@ -1,6 +1,6 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
-#import "@preview/cetz-plot:0.1.2": chart, plot
+#import "@preview/cetz-plot:0.1.0": plot, chart
 
 = Integers and Floats
 
@@ -44,11 +44,19 @@ This allows us to improve the average error of our linear approximation:
         {
           let domain = (0, 1)
 
-          plot.add(f1, domain: domain, label: $log(1+x)$, style: (
+          plot.add(
-            stroke: ogrape,
+            f1,
-          ))
+            domain: domain,
+            label: $log(1+x)$,
+            style: (stroke: ogrape),
+          )
 
-          plot.add(f2, domain: domain, label: $x$, style: (stroke: oblue))
+          plot.add(
+            f2,
+            domain: domain,
+            label: $x$,
+            style: (stroke: oblue),
+          )
         },
       )
     })
@@ -82,11 +90,19 @@ This allows us to improve the average error of our linear approximation:
         {
           let domain = (0, 1)
 
-          plot.add(f1, domain: domain, label: $log(1+x)$, style: (
+          plot.add(
-            stroke: ogrape,
+            f1,
-          ))
+            domain: domain,
+            label: $log(1+x)$,
+            style: (stroke: ogrape),
+          )
 
-          plot.add(f2, domain: domain, label: $x$, style: (stroke: oblue))
+          plot.add(
+            f2,
+            domain: domain,
+            label: $x$,
+            style: (stroke: oblue),
+          )
         },
       )
     })
@@ -104,13 +120,16 @@ We won't bother with this---we'll simply leave the correction term as an opaque
 
 #v(1fr)
 
-#note(type: "Note", [
+#note(
+  type: "Note",
+  [
     "Average error" above is simply the area of the region between the two graphs:
     $
-    integral_0^1 abs(#v(1mm) log(1+x)_2 - (x+epsilon) #v(1mm))
+      integral_0^1 abs( #v(1mm) log(1+x)_2 - (x+epsilon) #v(1mm))
     $
     Feel free to ignore this note, it isn't a critical part of this handout.
-])
+  ],
+)
 
 
 #pagebreak()
@@ -130,11 +149,12 @@ $
   Let $E$ and $F$ be the exponent and float bits of $x_f$. \
   We then have:
   $
-    log_2(x_f) & = log_2 ( 2^(E-127) times (1 + (F) / (2^23)) ) \
+    log_2(x_f)
-               & = E - 127 + log_2(1 + F / (2^23))              \
+    &= log_2 ( 2^(E-127) times (1 + (F) / (2^23)) ) \
+    &= E - 127 + log_2(1 + F / (2^23)) \
     & approx E-127 + F / (2^23) + epsilon \
-               & = 1 / (2^23)(2^23 E + F) - 127 + epsilon       \
+    &= 1 / (2^23)(2^23 E + F) - 127 + epsilon \
-               & = 1 / (2^23)(x_i) - 127 + epsilon
+    &= 1 / (2^23)(x_i) - 127 + epsilon
   $
 ])
 

src/Advanced/Introduction to Quantum/main.typ

@@ -0,0 +1,35 @@
+#import "@local/handout:0.1.0": *
+
+#show: handout.with(
+  title: [Intro to Quantum Computing],
+  by: "Mark",
+)
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+#include "src/parts/01 bits.typ"
+#pagebreak()
+
+#include "src/parts/02 qubit.typ"
+#pagebreak()
+
+#include "src/parts/03 two qubits.typ"
+#pagebreak()
+
+// DONE UNTIL HERE
+
+#include "src/parts/04 logic gates.typ"
+#pagebreak()
+
+#include "src/parts/05 quantum gates.typ"
+#pagebreak()
+
+#include "src/parts/06 hxh.typ"
+#pagebreak()
+
+#include "src/parts/07 superdense.typ"
+#pagebreak()
+
+#include "src/parts/08 teleport.typ"

src/Advanced/Introduction to Quantum/src/parts/01 bits.typ

@@ -0,0 +1,349 @@
+#import "@local/handout:0.1.0": *
+#import "@preview/cetz:0.4.2"
+
+= Probabilistic Bits
+
+#definition()
+As we already know, a _classical bit_ may take the values `0` and `1`.
+
+We can model this with a two-sided coin, one face of which is labeled `0`, and the other, `1`.
+
+#v(2mm)
+
+Of course, if we toss such a "bit-coin," we'll get either `0` or `1`.
+
+We'll denote the probability of getting `0` as $p_0$, and the probability of getting `1` as $p_1$.
+
+As with all probabilities, $p_0 + p_1$ must be equal to 1.
+
+#v(1fr)
+
+#definition()
+Say we toss a "bit-coin" and don't observe the result. We now have a _probabilistic bit_, with a probability $p_0$ of being `0`, and a probability $p_1$ of being `1`.
+
+#v(2mm)
+
+We'll represent this probabilistic bit's _state_ as a vector: $mat(p_0; p_1)$
+
+We do *not* assume this coin is fair, and thus $p_0$ might not equal $p_1$.
+
+#note[This may seem a bit redundant: since $p_0 + p_1 = 1$, we can always calculate one probability given the other. We'll still include both probabilities in the state vector, since this provides a clearer analogy to quantum bits.]
+
+#v(1fr)
+
+#definition()
+The simplest probabilistic bit states are of course $[0]$ and $[1]$, defined as follows:
+- $[0] = mat(1; 0)$
+- $[1] = mat(0; 1)$
+
+That is, $[0]$ represents a bit that we known to be `0`, and $[1]$ represents a bit we know to be `1`.
+
+#v(1fr)
+
+#definition()
+$[0]$ and $[1]$ form a _basis_ for all possible probabilistic bit states:
+
+Every other probabilistic bit can be written as a _linear combination_ of $[0]$ and $[1]$:
+
+$ mat(p_0; p_1) = p_0 mat(1; 0) + p_1 mat(0; 1) = p_0 [0] + p_1 [1] $
+
+#v(1fr)
+#pagebreak()
+
+#problem()
+Every possible state of a probabilistic bit is a two-dimensional vector.
+
+Draw all possible states on the axis below.
+
+#table(
+  columns: (1fr,),
+  align: center,
+  stroke: none,
+  align(center, cetz.canvas({
+    import cetz.draw: *
+
+    set-style(content: (frame: "rect", stroke: none, fill: none, padding: .25))
+    scale(200%)
+
+    line(
+      (0, 1.5),
+      (0, 0),
+      (1.5, 0),
+      stroke: black + 0.25mm,
+    )
+    mark((0, 1.5), (0, 2), symbol: ")>", fill: black)
+    mark((1.5, 0), (2, 0), symbol: ")>", fill: black)
+
+    content((0, 1.5), $p_1$, anchor: "south")
+    content((1.5, 0), $p_0$, anchor: "west")
+
+    circle((0, 0), radius: 0.6mm, fill: black, name: "00")
+    content("00.south", $mat(0; 0)$, anchor: "north")
+
+    circle((0, 1), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.west", $[1]$, anchor: "east")
+
+    circle((1, 0), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.south", $[0]$, anchor: "north")
+  })),
+)
+
+#solution[
+  #table(
+    columns: (1fr,),
+    align: center,
+    stroke: none,
+    align(center, cetz.canvas({
+      import cetz.draw: *
+
+      set-style(content: (
+        frame: "rect",
+        stroke: none,
+        fill: none,
+        padding: .25,
+      ))
+      scale(200%)
+
+      line(
+        (0, 1.5),
+        (0, 0),
+        (1.5, 0),
+        stroke: black + 0.25mm,
+      )
+      mark((0, 1.5), (0, 2), symbol: ")>", fill: black)
+      mark((1.5, 0), (2, 0), symbol: ")>", fill: black)
+
+      content((0, 1.5), $p_1$, anchor: "south")
+      content((1.5, 0), $p_0$, anchor: "west")
+
+
+      line(
+        (1, 0),
+        (0, 1),
+        stroke: ored + 1mm,
+      )
+
+      circle((0, 0), radius: 0.6mm, fill: black, name: "00")
+      content("00.south", $mat(0; 0)$, anchor: "north")
+
+      circle((0, 1), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+      content("00.west", $[1]$, anchor: "east")
+
+      circle((1, 0), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+      content("00.south", $[0]$, anchor: "north")
+    })),
+  )
+
+]
+
+
+#v(1fr)
+#pagebreak()
+
+= Measuring Probabilistic Bits
+
+#definition()
+As we noted before, a probabilistic bit represents a coin we've tossed but haven't looked at.
+
+We do not know whether the bit is `0` or `1`, but we do know the probability of both of these outcomes.
+
+#v(2mm)
+
+If we _measure_ (or _observe_) a probabilistic bit, we see either `0` or `1`—and thus our knowledge of its state is updated to either $[0]$ or $[1]$, since we now certainly know what face the coin landed on.
+
+#v(2mm)
+
+Since measurement changes what we know about a probabilistic bit, it changes the probabilistic bit's state. When we measure a bit, its state _collapses_ to either $[0]$ or $[1]$, and the original state of the bit vanishes. We _cannot_ recover the state $[x_0, x_1]$ from a measured probabilistic bit.
+
+#definition("Multiple bits")
+Say we have two probabilistic bits, $x$ and $y$, with states $[x] = [x_0, x_1]$ and $[y] = [y_0, y_1]$
+
+#v(2mm)
+
+The _compound state_ of $[x]$ and $[y]$ is exactly what it sounds like: It is the probabilistic two-bit state $|x y angle.r$, where the probabilities of the first bit are determined by $[x]$, and the probabilities of the second are determined by $[y]$.
+
+#problem(label: "firstcompoundstate")
+Say $[x] = [2/3, 1/3]$ and $[y] = [3/4, 1/4]$.
+
+- If we measure $x$ and $y$ simultaneously, what is the probability of getting each of `00`, `01`, `10`, and `11`?
+
+- If we measure $y$ first and observe `1`, what is the probability of getting each of `00`, `01`, `10`, and `11`?
+
+#note[*Note:* $[x]$ and $[y]$ are column vectors, but I've written them horizontally to save space.]
+
+#v(1fr)
+
+#problem()
+Say $[x] = [2/3, 1/3]$ and $[y] = [3/4, 1/4]$.
+
+What is the probability that $x$ and $y$ produce different outcomes?
+
+#v(1fr)
+#pagebreak()
+
+= Tensor Products
+
+#definition("Tensor Products")
+The _tensor product_ of two vectors is defined as follows:
+$
+  mat(x_1; x_2) times.circle mat(y_1; y_2) = mat(x_1 mat(y_1; y_2); x_2 mat(y_1; y_2)) = mat(x_1 y_1; x_1 y_2; x_2 y_1; x_2 y_2)
+$
+
+That is, we take our first vector, multiply the second vector by each of its components, and stack the result. You could think of this as a generalization of scalar multiplication, where scalar multiplication is a tensor product with a vector in $RR^1$:
+
+$
+  a mat(x_1; x_2) = mat(a_1) times.circle mat(y_1; y_2) = mat(a_1 mat(y_1; y_2)) = mat(a_1 y_1; a_1 y_2)
+$
+
+#problem()
+Say $x in RR^n$ and $y in RR^m$.
+
+What is the dimension of $x times.circle y$?
+
+#v(1fr)
+
+#problem(label: "basistp")
+What is the following pairwise tensor product?
+#v(4mm)
+$
+  {mat(1; 0; 0), mat(0; 1; 0), mat(0; 0; 1)}
+  times.circle
+  {mat(1; 0), mat(0; 1)}
+$
+#v(4mm)
+
+#hint[Distribute the tensor product between every pair of vectors.]
+
+#v(1fr)
+
+#problem()
+What is the _span_ of the vectors we found in @basistp?
+
+In other words, what is the set of vectors that can be written as linear combinations of the vectors above?
+
+#v(1fr)
+
+#pagebreak()
+
+#problem()
+Say $[x] = [2/3, 1/3]$ and $[y] = [3/4, 1/4]$.
+
+What is $[x] times.circle [y]$? How does this relate to @firstcompoundstate?
+
+#v(1fr)
+
+#problem()
+The compound state of two vector-form bits is their tensor product.
+
+Compute the following. Is the result what we'd expect?
+- $[0] times.circle [0]$
+- $[0] times.circle [1]$
+- $[1] times.circle [0]$
+- $[1] times.circle [1]$
+
+#hint[Remember that $[0] = mat(1; 0)$ and $[1] = mat(0; 1)$.]
+
+#v(1fr)
+
+#problem(label: "fivequant")
+Writing $[0] times.circle [1]$ is a bit tedious. We'll shorten this notation to $[01]$.
+
+In fact, we could go further: if we wanted to write the set of bits $[1] times.circle [1] times.circle [0] times.circle [1]$, \
+we could write $[1101]$—but a shorter alternative is $[13]$, since $13$ is `1101` in binary.
+
+#v(2mm)
+
+Write $[5]$ as a three-bit probabilistic state.
+
+#solution[
+  $[5] = [101] = [1] times.circle [0] times.circle [1] = [0,0,0,0,0,1,0,0]^T$ \
+
+  Notice how we're counting from the top, with $[000] = [1,0,...,0]$ and $[111] = [0, ..., 0, 1]$.
+]
+
+#v(1fr)
+
+#problem()
+Write the three-bit states $[0]$ through $[7]$ as column vectors.
+
+#hint[You do not need to compute every tensor product. Do a few and find the pattern.]
+
+#v(1fr)
+#pagebreak()
+
+
+
+= Operations on Probabilistic Bits
+
+Now that we can write probabilistic bits as vectors, we can represent operations on these bits with linear transformations—in other words, as matrices.
+
+#definition()
+Consider the NOT gate, which operates as follows:
+- $"NOT"[0] = [1]$
+- $"NOT"[1] = [0]$
+
+What should NOT do to a probabilistic bit $[x_0, x_1]$?
+
+If we return to our coin analogy, we can think of the NOT operation as flipping a coin we have already tossed, without looking at its state. Thus,
+$ "NOT" mat(x_0; x_1) = mat(x_1; x_0) $
+
+#review_box("Review: Multiplying vectors by matrices")[
+  #v(2mm)
+
+  $
+    A v = mat(1, 2; 3, 4) mat(v_0; v_1) = mat(1 v_0 + 2 v_1; 3 v_0 + 4 v_1)
+  $
+
+  #v(2mm)
+
+  Note that each element of $A v$ is the dot product of a row in $A$ and a column in $v$.
+]
+
+#problem()
+Compute the following product:
+$ mat(1, 0.5; 0, 1) mat(3; 2) $
+
+#v(1fr)
+
+#remark()
+Also, recall that every matrix is linear map, and that every linear map may be written as a matrix. We often use the terms _matrix_, _transformation_, and _linear map_ interchangeably.
+
+#pagebreak()
+
+#problem()
+Find the matrix that represents the NOT operation on one probabilistic bit.
+
+#solution[
+  $
+    mat(0, 1; 1, 0)
+  $
+]
+
+#v(1fr)
+
+#problem("Extension by linearity")
+Say we have an arbitrary operation $M$.
+
+If we know how $M$ acts on $[1]$ and $[0]$, can we compute $M[x]$ for an arbitrary state $[x]$?
+
+Say $[x] = [x_0, x_1]$.
+- What is the probability we observe $0$ when we measure $x$?
+- What is the probability that we observe $M[0]$ when we measure $M x$?
+
+#v(1fr)
+
+#problem(label: "linearextension")
+Write $M[x_0, x_1]$ in terms of $M[0]$, $M[1]$, $x_0$, and $x_1$.
+
+#solution[
+  $
+    M mat(x_0; x_1) = x_0 M mat(1; 0) + x_1 M mat(0; 1) = x_0 M[0] + x_1 M[1]
+  $
+]
+
+#v(1fr)
+
+#remark() Every matrix represents a _linear_ map, so the following is always true:
+$ A times (p x + q y) = p A x + q A y $
+
+@linearextension is just a special case of this fact.

src/Advanced/Introduction to Quantum/src/parts/02 qubit.typ

@@ -0,0 +1,514 @@
+#import "@local/handout:0.1.0": *
+#import "@preview/cetz:0.4.2"
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= One Qubit
+
+Quantum bits (or _qubits_) are very similar to probabilistic bits, but have one major difference: probabilities are replaced with _amplitudes_.
+
+#v(2mm)
+
+Of course, a qubit can take the values `0` and `1`, which are denoted $#ket("0")$ and $#ket("1")$.
+
+Like probabilistic bits, a quantum bit is written as a linear combination of $#ket("0")$ and $#ket("1")$:
+$ #ket([$psi$]) = psi_0 #ket("0") + psi_1 #ket("1") $
+
+Such linear combinations are called _superpositions_.
+
+#v(2mm)
+
+The $#ket("")$ you see in the expressions above is called a "ket," and denotes a column vector.
+
+$#ket("0")$ is pronounced "ket zero," and $#ket("1")$ is pronounced "ket one." This is called bra-ket notation.
+
+#note[*Note:* $#bra("0")$ is called a "bra," but we won't worry about that for now.]
+
+#v(2mm)
+
+This is very similar to the "box" $[#h(1.5mm)]$ notation we used for probabilistic bits.
+
+As before, we will write $#ket("0") = mat(1; 0)$ and $#ket("1") = mat(0; 1)$.
+
+#v(8mm)
+
+Recall that probabilistic bits are subject to the restriction that $p_0 + p_1 = 1$.
+
+Quantum bits have a similar condition: $psi_0^2 + psi_1^2 = 1$.
+
+Note that this implies that $psi_0$ and $psi_1$ are both in $[-1, 1]$.
+
+Quantum amplitudes may be negative, but probabilistic bit probabilities cannot.
+
+#v(2mm)
+
+If we plot the set of valid quantum states on our plane, we get a unit circle centered at the origin:
+
+#table(
+  columns: (1fr,),
+  align: center,
+  stroke: none,
+  align(center, cetz.canvas({
+    import cetz.draw: *
+
+    set-style(content: (frame: "rect", stroke: none, fill: none, padding: .25))
+    scale(150%)
+
+    line(
+      (0, 1.5),
+      (0, 0),
+      (1.5, 0),
+      stroke: black + 0.25mm,
+    )
+    mark((0, 1.5), (0, 2), symbol: ")>", fill: black)
+    mark((1.5, 0), (2, 0), symbol: ")>", fill: black)
+
+    circle((0, 0), radius: 1, stroke: (
+      paint: black,
+      thickness: 0.25mm,
+      dash: "dashed",
+    ))
+
+    content((0, 1.5), $p_1$, anchor: "south")
+    content((1.5, 0), $p_0$, anchor: "west")
+
+    circle((0, 1), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.west", $#ket("1")$, anchor: "east")
+
+    circle((1, 0), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.south", $#ket("0")$, anchor: "north")
+
+    circle((0.87, 0.5), radius: 0.6mm, fill: ored, stroke: ored, name: "00")
+    content("00.east", $#ket(math.psi)$, anchor: "west")
+  })),
+)
+
+
+Recall that the set of probabilistic bits forms a line instead:
+
+#table(
+  columns: (1fr,),
+  align: center,
+  stroke: none,
+  align(center, cetz.canvas({
+    import cetz.draw: *
+
+    set-style(content: (frame: "rect", stroke: none, fill: none, padding: .25))
+    scale(150%)
+
+    line(
+      (0, 1.5),
+      (0, 0),
+      (1.5, 0),
+      stroke: black + 0.25mm,
+    )
+    mark((0, 1.5), (0, 2), symbol: ")>", fill: black)
+    mark((1.5, 0), (2, 0), symbol: ")>", fill: black)
+
+
+    line(
+      (1, 0),
+      (0, 1),
+      stroke: ored + 1mm,
+    )
+
+    content((0, 1.5), $p_1$, anchor: "south")
+    content((1.5, 0), $p_0$, anchor: "west")
+
+    circle((0, 0), radius: 0.6mm, fill: black, name: "00")
+    content("00.south", $mat(0; 0)$, anchor: "north")
+
+    circle((0, 1), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.west", $[1]$, anchor: "east")
+
+    circle((1, 0), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.south", $[0]$, anchor: "north")
+  })),
+)
+
+
+#problem()
+In the above unit circle, the counterclockwise angle from $#ket("0")$ to $#ket([$psi$])$ is $30°$.
+
+Write $#ket([$psi$])$ as a linear combination of $#ket("0")$ and $#ket("1")$.
+
+#v(1fr)
+#pagebreak()
+
+#definition("Measurement I")
+Just like a probabilistic bit, we must observed $#ket("0")$ or $#ket("1")$ when we measure a qubit.
+
+If we were to measure $#ket([$psi$]) = psi_0 #ket("0") + psi_1 #ket("1")$, we'd observe either $#ket("0")$ or $#ket("1")$, with the following probabilities:
+- $cal(P)(#ket("1")) = psi_1^2$
+- $cal(P)(#ket("0")) = psi_0^2$
+
+#note[Note that $cal(P)(#ket("0")) + cal(P)(#ket("1")) = 1$.]
+
+#v(2mm)
+
+As before, $#ket([$psi$])$ _collapses_ when it is measured: its state becomes that which we observed in our measurement, leaving no trace of the previous superposition.
+
+#problem()
+- What is the probability we observe $#ket("0")$ when we measure $#ket([$psi$])$?
+- What can we observe if we measure $#ket([$psi$])$ a second time?
+- What are these probabilities for $#ket([$phi$])$?
+
+
+#table(
+  columns: (1fr,),
+  align: center,
+  stroke: none,
+  align(center, cetz.canvas({
+    import cetz.draw: *
+
+    set-style(content: (frame: "rect", stroke: none, fill: none, padding: .25))
+    scale(200%)
+
+    line(
+      (0, 1.5),
+      (0, 0),
+      (1.5, 0),
+      stroke: black + 0.25mm,
+    )
+    mark((0, 1.5), (0, 2), symbol: ")>", fill: black)
+    mark((1.5, 0), (2, 0), symbol: ")>", fill: black)
+
+    circle((0, 0), radius: 1, stroke: (
+      paint: black,
+      thickness: 0.25mm,
+      dash: "dashed",
+    ))
+
+    content((0, 1.5), $p_1$, anchor: "south")
+    content((1.5, 0), $p_0$, anchor: "west")
+
+    circle((0, 1), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.west", $#ket("1")$, anchor: "east")
+
+    circle((1, 0), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.south", $#ket("0")$, anchor: "north")
+
+    circle((0.87, 0.5), radius: 0.6mm, fill: ored, stroke: ored, name: "00")
+    content("00.east", $#ket(math.psi)$, anchor: "west")
+
+    arc(
+      (0, 0),
+      start: 0deg,
+      stop: -135deg,
+      anchor: "origin",
+      radius: 0.3,
+      name: "a135",
+      stroke: gray,
+    )
+    mark(
+      "a135.end",
+      135deg,
+      symbol: ")>",
+      fill: gray,
+      stroke: gray,
+    )
+    content("a135.center", text(fill: gray)[$135degree$], anchor: "north")
+
+
+    line((0, 0), (-0.607, -0.607), stroke: (
+      paint: gray,
+      thickness: 0.4mm,
+      dash: "dotted",
+    ))
+    mark(
+      (-0.627, -0.627),
+      (-0.708, -0.708),
+      symbol: ")>",
+      fill: gray,
+      stroke: gray,
+    )
+
+
+    arc(
+      (0, 0),
+      start: 0deg,
+      stop: 30deg,
+      anchor: "origin",
+      radius: 0.6,
+      name: "a30",
+      stroke: gray,
+    )
+    mark(
+      "a30.end",
+      120deg,
+      symbol: ")>",
+      fill: gray,
+      stroke: gray,
+    )
+    content("a30.end", text(fill: gray)[$30degree$], anchor: "south")
+
+
+    line((0, 0), (0.87, 0.5), stroke: (
+      paint: gray,
+      thickness: 0.4mm,
+      dash: "dotted",
+    ))
+    mark(
+      (0.80, 0.46),
+      (0.87, 0.5),
+      symbol: ")>",
+      fill: gray,
+      stroke: gray,
+    )
+
+    circle(
+      (-0.707, -0.707),
+      radius: 0.6mm,
+      fill: ored,
+      stroke: ored,
+      name: "00",
+    )
+    content("00.west", $#ket(math.phi)$, anchor: "east")
+  })),
+)
+
+
+
+#v(1fr)
+
+As you may have noticed, we don't need two coordinates to fully define a qubit's state. We can get by with one coordinate just as well.
+
+Instead of referring to each state using its cartesian coordinates $psi_0$ and $psi_1$, we can address it using its _polar angle_ $theta$, measured from $#ket("0")$ counterclockwise:
+
+#table(
+  columns: (1fr,),
+  align: center,
+  stroke: none,
+  align(center, cetz.canvas({
+    import cetz.draw: *
+
+    set-style(content: (frame: "rect", stroke: none, fill: none, padding: .25))
+    scale(180%)
+
+    line(
+      (0, 1.5),
+      (0, 0),
+      (1.5, 0),
+      stroke: black + 0.25mm,
+    )
+    mark((0, 1.5), (0, 2), symbol: ")>", fill: black)
+    mark((1.5, 0), (2, 0), symbol: ")>", fill: black)
+
+    circle((0, 0), radius: 1, stroke: (
+      paint: black,
+      thickness: 0.25mm,
+      dash: "dashed",
+    ))
+
+    content((0, 1.5), $p_1$, anchor: "south")
+    content((1.5, 0), $p_0$, anchor: "west")
+
+    circle((0, 1), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.west", $#ket("1")$, anchor: "east")
+
+    circle((1, 0), radius: 0.6mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.south", $#ket("0")$, anchor: "north")
+
+    circle((0.87, 0.5), radius: 0.6mm, fill: ored, stroke: ored, name: "00")
+    content("00.east", $#ket(math.psi)$, anchor: "west")
+
+
+    arc(
+      (0, 0),
+      start: 0deg,
+      stop: 30deg,
+      anchor: "origin",
+      radius: 0.6,
+      name: "a30",
+      stroke: gray,
+    )
+    mark(
+      "a30.end",
+      120deg,
+      symbol: ")>",
+      fill: gray,
+      stroke: gray,
+    )
+    content("a30.mid", text(fill: gray)[$theta$], anchor: "west")
+
+
+    line((0, 0), (0.87, 0.5), stroke: (
+      paint: gray,
+      thickness: 0.4mm,
+      dash: "dotted",
+    ))
+    mark(
+      (0.80, 0.46),
+      (0.87, 0.5),
+      symbol: ")>",
+      fill: gray,
+      stroke: gray,
+    )
+  })),
+)
+
+
+#problem()
+Find $psi_0$ and $psi_1$ in terms of $theta$ for an arbitrary qubit $psi$.
+
+#v(1fr)
+#pagebreak()
+
+#problem()
+Consider the following qubit states:
+
+#grid(
+  columns: (1fr, 1fr),
+  $ #ket("+") = (#ket("0") + #ket("1"))/sqrt(2) $,
+  $ #ket("-") = (#ket("0") - #ket("1"))/sqrt(2) $,
+)
+
+- Where are these on the unit circle?
+- What are their polar angles?
+- What are the probabilities of observing $#ket("0")$ and $#ket("1")$ when measuring $#ket("+")$ and $#ket("-")$?
+
+
+
+#table(
+  columns: (1fr,),
+  align: center,
+  stroke: none,
+  align(center, cetz.canvas({
+    import cetz.draw: *
+
+    set-style(content: (frame: "rect", stroke: none, fill: none, padding: .25))
+    scale(300%)
+
+    line(
+      (0, 1.3),
+      (0, 0),
+      (1.3, 0),
+      stroke: black + 0.25mm,
+    )
+    mark((0, 1.3), (0, 2), symbol: ")>", fill: black)
+    mark((1.3, 0), (2, 0), symbol: ")>", fill: black)
+
+    circle((0, 0), radius: 1, stroke: (
+      paint: black,
+      thickness: 0.25mm,
+      dash: "dashed",
+    ))
+
+    content((0, 1.3), $p_1$, anchor: "south")
+    content((1.3, 0), $p_0$, anchor: "west")
+
+    circle((0, 1), radius: 0.4mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.west", $#ket("1")$, anchor: "east")
+
+    circle((1, 0), radius: 0.4mm, fill: oblue, stroke: oblue, name: "00")
+    content("00.south", $#ket("0")$, anchor: "north")
+  })),
+)
+
+
+#v(1fr)
+
+#v(1fr)
+#v(1fr)
+#pagebreak()
+
+= Operations on One Qubit
+
+We may apply transformations to qubits just as we apply transformations to probabilistic bits. Again, we'll represent transformations as $2 times 2$ matrices, since we want to map one qubit state to another.
+
+#note[In other words, we want to map elements of $RR^2$ to elements of $RR^2$.]
+
+We will call such maps _quantum gates,_ since they are the quantum equivalent of classical logic gates.
+
+#v(2mm)
+
+There are two conditions a valid quantum gate $G$ must satisfy:
+- For any valid state $#ket([$psi$])$, $G #ket([$psi$])$ is a valid state. Namely, $G$ must preserve the length of any vector it is applied to. Recall that the set of valid quantum states is the set of unit vectors in $RR^2$
+
+- Any quantum gate must be _invertible_. We'll skip this condition for now, and return to it later.
+
+In short, a quantum gate is a linear map that maps the unit circle to itself. There are only two kinds of linear maps that do this: reflections and rotations.
+
+#problem()
+The $X$ gate is the quantum analog of the `not` gate, defined by the following table:
+- $X #ket("0") = #ket("1")$
+- $X #ket("1") = #ket("0")$
+
+Find the matrix $X$.
+
+#solution[
+  $
+    mat(0, 1; 1, 0)
+  $
+]
+
+#v(1fr)
+
+#problem()
+What is $X #ket("+")$ and $X #ket("-")$?
+
+#hint[Remember that all matrices are linear maps. What does this mean?]
+
+#solution[
+  $X #ket("+") = #ket("+")$ and $X #ket("-") = - #ket("-")$ (that is, a negative ket-minus). \
+  Most notably, rememver that $G(a#ket("0") + b #ket("1")) = a G #ket("0") + b G #ket("1")$.
+]
+
+#v(1fr)
+
+#problem()
+In terms of geometric transformations, what does $X$ do to the unit circle?
+
+#solution[
+  It is a reflection about the $45degree$ axis.
+]
+
+#v(1fr)
+#pagebreak()
+
+#problem()
+Let $Z$ be a quantum gate defined by the following table:
+- $Z #ket("0") = #ket("0")$,
+- $Z #ket("1") = -#ket("1")$.
+
+What is the matrix $Z$? What are $Z #ket("+")$ and $Z #ket("-")$?
+
+What is $Z$ as a geometric transformation?
+
+#v(1fr)
+
+#problem()
+Is the map $B$ defined by the table below a valid quantum gate?
+- $B #ket("0") = #ket("0")$
+- $B #ket("1") = #ket("+")$
+
+#hint[Find a $#ket([$psi$])$ so that $B #ket([$psi$])$ is not a valid qubit state]
+
+#solution[
+  $ B #ket("+") = (1 + sqrt(2))/(2) #ket("0") + 1/2 #ket("1") $
+
+  This has a non-unit length of
+  $
+    (sqrt(2) + 1)/(2)
+  $
+]
+
+#v(1fr)
+
+#problem("Rotation")
+As we noted earlier, any rotation about the center is a valid quantum gate. Let's derive all transformations of this form.
+
+- Let $U_theta$ be the matrix that represents a counterclockwise rotation of $theta$ degrees. What is $U #ket("0")$ and $U #ket("1")$?
+
+- Find the matrix $U_theta$ for an arbitrary $theta$.
+
+#v(1fr)
+
+#problem()
+Say we have a qubit that is either $#ket("+")$ or $#ket("-")$. We do not know which of the two states it is in.
+
+Using one operation and one measurement, how can we find out, for certain, which qubit we received?
+
+#v(1fr)

src/Advanced/Introduction to Quantum/src/parts/03 two qubits.typ

@@ -0,0 +1,126 @@
+#import "@local/handout:0.1.0": *
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= Two Qubits
+
+#definition()
+Just as before, we'll represent multi-qubit states as linear combinations of multi-qubit basis states.
+
+For example, a two-qubit state $#ket("ab")$ is the four-dimensional unit vector
+$ mat(a; b; c; d) = a #ket("00") + b #ket("01") + c #ket("10") + d #ket("11") $
+
+As always, multi-qubit states are unit vectors. Thus, $a^2 + b^2 + c^2 + d^2 = 1$ in the two-bit case above.
+
+#problem()
+Say we have two qubits $#ket([$psi$])$ and $#ket([$phi$])$.
+
+Show that $#ket([$psi$]) times.circle #ket([$phi$])$ is always a unit vector (and is thus a valid quantum state).
+
+#v(1fr)
+
+#definition("Measurement II")<measureii>
+Measurement of a two-qubit state works just like measurement of a one-qubit state:
+
+If we measure $a #ket("00") + b #ket("01") + c #ket("10") + d #ket("11")$, we get one of the four basis states with the following probabilities:
+
+- $cal(P)(#ket("00")) = a^2$
+- $cal(P)(#ket("01")) = b^2$
+- $cal(P)(#ket("10")) = c^2$
+- $cal(P)(#ket("11")) = d^2$
+
+As before, the sum of all the above probabilities is $1$.
+
+#problem()
+Consider the two-qubit state
+$#ket([$psi$]) = 1/sqrt(2) #ket("00") + 1/2 #ket("01") + sqrt(3)/4 #ket("10") + 1/4 #ket("11")$
+
+- If we measure both bits of $#ket([$psi$])$ simultaneously, what is the probability of getting each of $#ket("00")$, $#ket("01")$, $#ket("10")$, and $#ket("11")$?
+
+- If we measure the ONLY the first qubit, what is the probability we get $#ket("0")$? How about $#ket("1")$?
+
+  #hint[There are two basis states in which the first qubit is $#ket("0")$.]
+
+- Say we measured the second bit and read $#ket("1")$. If we now measure the first bit, what is the probability of getting $#ket("0")$?
+
+#v(1fr)
+#pagebreak()
+
+#problem()
+Again, consider the two-qubit state
+$#ket([$psi$]) = 1/sqrt(2) #ket("00") + 1/2 #ket("01") + sqrt(3)/4 #ket("10") + 1/4 #ket("11")$
+
+If we measure the first qubit of $#ket([$psi$])$ and get $#ket("0")$, what is the resulting state of $#ket([$psi$])$?
+
+What would the state be if we'd measured $#ket("1")$ instead?
+
+#v(1fr)
+
+#problem()
+Consider the three-qubit state $#ket([$psi$]) = c_0 #ket("000") + c_1 #ket("001") + ... + c_7 #ket("111")$.
+
+Say we measure the first two qubits and get $#ket("00")$. What is the resulting state of $#ket([$psi$])$?
+
+#solution[
+  We measure $#ket("00")$ with probability $c_0^2 + c_1^2$, and $#ket(math.psi)$ collapses to
+
+  #v(3mm)
+
+  $
+    (c_0 #ket("000") + c_1 #ket("001"))/(sqrt(c_0^2 + c_1^2))
+  $
+]
+
+
+#v(1fr)
+#pagebreak()
+
+#definition("Entanglement")
+Some product states can be factored into a tensor product of individual qubit states. For example,
+$
+  1/2 (#ket("00") + #ket("01") + #ket("10") + #ket("11")) = 1/sqrt(2) (#ket("0") + #ket("1")) times.circle 1/sqrt(2) (#ket("0") + #ket("1"))
+$
+
+Such states are called _product states._ States that aren't product states are called _entangled_ states.
+
+#problem()
+Factor the following product state:
+$
+  1/(2sqrt(2)) (sqrt(3) #ket("00") - sqrt(3) #ket("01") + #ket("10") - #ket("11"))
+$
+
+#solution[
+
+  $
+    (1)/(2 sqrt(2)) (sqrt(3) #ket("00") - sqrt(3) #ket("01") + #ket("10") - #ket("11"))
+    = (sqrt(3)/2 #ket("0") + 1/2 #ket("1") )
+    times.circle
+    ( 1/sqrt(2) #ket(0) - 1/sqrt(2) #ket("1"))
+  $
+]
+
+#v(1fr)
+
+#problem()
+Show that the following is an entangled state.
+$ 1/sqrt(2) #ket("00") + 1/sqrt(2) #ket("11") $
+
+#solution[
+  $
+    mat(a_0; a_1)
+    times.circle
+    mat(b_0; b_1)
+    =
+    a_0b_0 #ket(00) + a_0b_1 #ket(01) + a_1b_0 #ket(10) + a_1b_1 #ket(11)
+  $
+
+  #v(2mm)
+
+  So, we have that $a_1b_1 = a_0b_0 = sqrt(2)^(-1)$ \
+  But $a_0b_1 = a_1b_0 = 0$, so one of $a_0$ and $b_1$ must be zero. \
+  We thus have a contradiction.
+]
+
+#v(1fr)

src/Advanced/Introduction to Quantum/src/parts/04 logic gates.typ

@@ -0,0 +1,169 @@
+#import "@local/handout:0.1.0": *
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= Logic Gates
+
+#definition("Matrices")
+Throughout this handout, we've been using matrices. Again, recall that every linear map may be written as a matrix, and that every matrix represents a linear map. For example, if $f: RR^2 -> RR^2$ is a linear map, we can write it as follows:
+
+$
+  f(#ket("x")) = mat(m_1, m_2; m_3, m_4) mat(x_1; x_2) = mat(m_1 x_1 + m_2 x_2; m_3 x_1 + m_4 x_2)
+$
+
+#definition()
+Before we discussing multi-qubit quantum gates, we need to review to classical logic.
+
+Of course, a classical logic gate is a linear map from ${0,1}^m$ to ${0,1}^n$
+
+#problem()<notgatex>
+The `not` gate is a map defined by the following table:
+
+- $X #ket("0") = #ket("1")$
+- $X #ket("1") = #ket("0")$
+
+Write the `not` gate as a matrix that operates on single-bit vector states.
+
+That is, find a matrix $X$ so that $X mat(1; 0) = mat(0; 1)$ and $X mat(0; 1) = mat(1; 0)$
+
+#solution[
+  $
+    X = mat(0, 1; 1, 0)
+  $
+]
+
+#v(1fr)
+
+#problem()
+The `and` gate is a map $BB^2 -> BB$ defined by the following table:
+
+#align(center, table(
+  columns: 3,
+  stroke: none,
+  table.hline(),
+  [`a`], [`b`], [`a` and `b`],
+  table.hline(),
+  [0], [0], [0],
+  [0], [1], [0],
+  [1], [0], [0],
+  [1], [1], [1],
+  table.hline(),
+))
+
+Find a matrix $A$ so that $A #ket("ab")$ works as expected.
+
+#hint[Remember, we write bits as vectors.]
+
+#solution[
+  $
+    A = mat(1, 1, 1, 0; 0, 0, 0, 1)
+  $
+
+  #instructornote[
+    Because of the way we represent bits here, we also have the following property: \
+    The columns of $A$ correspond to the output for each input---i.e, $A$ is just a table of outputs. \
+
+    #v(2mm)
+
+    For example, if we look at the first column of $A$ (which is $[1, 0]$), we see: \
+    $A#ket(00) = A[1,0,0,0] = [1,0] = #ket(0)$
+
+    #v(2mm)
+
+    Also with the last column (which is $[0,1]$): \
+    $A#ket(00) = A[0,0,0,1] = [0,1] = #ket(1)$
+  ]
+]
+
+#v(1fr)
+#pagebreak()
+
+#remark()
+The way a quantum circuit handles information is a bit different than the way a classical circuit does. We usually think of logic gates as _functions_: they consume one set of bits, and return another/
+
+// TODO: and gate (input a, input b, output)
+
+#v(2mm)
+
+This model, however, won't work for quantum logic. If we want to understand quantum gates, we need to see them not as _functions_, but as _transformations_. This distinction is subtle, but significant:
+- functions _consume_ a set of inputs and _produce_ a set of outputs
+- transformations _change_ a set of objects, without adding or removing any elements
+
+#v(2mm)
+
+Our usual logic circuit notation models logic gates as functions—we thus can't use it. We'll need a different diagram to draw quantum circuits.
+
+#v(1fr)
+
+First, we'll need a set of bits. For this example, we'll use two, drawn in a vertical array. We'll also add a horizontal time axis, moving from left to right:
+
+#align(center)[
+  // Quantum circuit diagram showing two qubits over time
+  #box(width: 10cm, height: 4cm)[
+    _[Quantum circuit diagram with time axis would go here]_
+  ]
+]
+
+In the diagram above, we didn't change our bits—so the labels at the start match those at the end.
+
+#v(1fr)
+
+Thus, our circuit forms a grid, with bits ordered vertically and time horizontally. If we want to change our state, we draw transformations as vertical boxes. Every column represents a single transformation on the entire state:
+
+#align(center)[
+  // Quantum circuit with transformations
+  #box(width: 10cm, height: 4cm)[
+    _[Quantum circuit with transformations $T_1$, $T_2$, $T_3$ would go here]_
+  ]
+]
+
+Note that the transformations above span the whole state. This is important: we cannot apply transformations to individual bits—we always transform the _entire_ state.
+
+#v(1fr)
+#pagebreak()
+
+*Setup:* Say we want to invert the first bit of a two-bit state. That is, we want a transformation $T$ so that
+
+#align(center)[
+  // Circuit showing bit flip
+  #box(width: 8cm, height: 3cm)[
+    _[Circuit diagram showing first bit flip would go here]_
+  ]
+]
+
+In other words, we want a matrix $T$ satisfying the following equalities:
+- $T #ket("00") = #ket("10")$
+- $T #ket("01") = #ket("11")$
+- $T #ket("10") = #ket("00")$
+- $T #ket("11") = #ket("01")$
+
+#problem()
+Find the matrix that corresponds to the above transformation.
+
+#hint[Remember that $#ket("0") = mat(1; 0)$ and $#ket("1") = mat(0; 1)$. Also, we found earlier that $X = mat(0, 1; 1, 0)$, and of course $I = mat(1, 0; 0, 1)$.]
+
+#v(1fr)
+
+*Remark:* We could draw the above transformation as a combination $X$ and $I$ (identity) gate:
+
+#align(center)[
+  // Circuit with X and I gates
+  #box(width: 6cm, height: 3cm)[
+    _[Circuit diagram with X gate on first qubit, I gate on second would go here]_
+  ]
+]
+
+We can even omit the $I$ gate, since we now know that transformations affect the whole state:
+
+#align(center)[
+  // Simplified circuit with just X gate
+  #box(width: 6cm, height: 3cm)[
+    _[Simplified circuit diagram with just X gate on first qubit would go here]_
+  ]
+]
+
+We're now done: this is how we draw quantum circuits. Don't forget that transformations _always_ affect the whole state—even if our diagram doesn't explicitly state this.
+
+#pagebreak()

src/Advanced/Introduction to Quantum/src/parts/05 quantum gates.typ

@@ -0,0 +1,42 @@
+#import "@local/handout:0.1.0": *
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= Quantum Gates
+
+In the previous section, we stated that a quantum gate is a linear map. Let's complete that definition.
+
+#definition()
+A quantum gate is a _orthonormal matrix_, which means any gate $G$ satisfies $G G^T = I$.
+
+This implies the following:
+
+- $G$ is square. In other words, it has as many rows as it has columns.
+
+  #note[If we think of $G$ as a map, this means that $G$ has as many inputs as it has outputs. This is to be expected: we stated earlier that quantum gates do not destroy or create qubits.]
+
+- $G$ preserves lengths; i.e $|x| = |G x|$.
+
+  #note[This ensures that $G #ket([$psi$])$ is always a valid state.]
+
+(You will prove all these properties in any introductory linear algebra course. This isn't a lesson on linear algebra, so you may take them as given today.)
+
+*Remark:* Let $G$ be a quantum gate. Since quantum gates are, by definition, _linear_ maps, the following holds:
+
+$ G(a_0 #ket("0") + a_1 #ket("1")) = a_0 G #ket("0") + a_1 G #ket("1") $
+
+#problem()<cnot>
+Consider the _controlled not_ (or _cnot_) gate, defined by the following table:
+- $X_c #ket("00") = #ket("00")$
+- $X_c #ket("01") = #ket("01")$
+- $X_c #ket("10") = #ket("11")$
+- $X_c #ket("11") = #ket("10")$
+
+In other words, the cnot gate inverts its second bit if its first bit is $#ket("1")$.
+
+Find the matrix that applies the cnot gate.
+
+#v(1fr)
+#pagebreak()

src/Advanced/Introduction to Quantum/src/parts/06 hxh.typ

@@ -0,0 +1,53 @@
+#import "@local/handout:0.1.0": *
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= HXH
+
+Let's return to the quantum circuit diagrams we discussed a few pages ago. Keep in mind that we're working with quantum gates and proper qubits—not classical bits, as we were before.
+
+#definition("Controlled Inputs")
+A _control input_ or _inverted control input_ may be attached to any gate. These are drawn as filled and empty circles in our circuit diagrams:
+
+#align(center)[
+#grid(columns: (1fr, 1fr),
+[
+  // Non-inverted control circuit diagram would go here
+  #box(width: 6cm, height: 4cm)[
+    _[Non-inverted control input circuit would go here]_
+  ]
+],
+[
+  // Inverted control circuit diagram would go here
+  #box(width: 6cm, height: 4cm)[
+    _[Inverted control input circuit would go here]_
+  ]
+]
+)]
+
+#v(2mm)
+
+An $X$ gate with a (non-inverted) control input behaves like an $X$ gate if _all_ its control inputs are $#ket("1")$, and like $I$ otherwise. An $X$ gate with an inverted control inputs does the opposite, behaving like $I$ if its input is $#ket("1")$ and like $X$ otherwise. The two circuits above illustrate this fact—take a look at their inputs and outputs.
+
+#v(2mm)
+
+Of course, we can give a gate multiple controls. An $X$ gate with multiple controls behaves like an $X$ gate if...
+- all non-inverted controls are $#ket("1")$, and
+- all inverted controls are $#ket("0")$
+
+...and like $I$ otherwise.
+
+#problem()
+What are the final states of the qubits in the diagram below?
+
+#align(center)[
+  // Multi-control circuit diagram would go here
+  #box(width: 8cm, height: 6cm)[
+    _[Multi-control circuit diagram would go here]_
+  ]
+]
+
+#v(1fr)
+#pagebreak()

src/Advanced/Introduction to Quantum/src/parts/07 superdense.typ

@@ -0,0 +1,48 @@
+#import "@local/handout:0.1.0": *
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= Superdense Coding
+
+Consider the following entangled two-qubit states, called the _bell states_:
+- $#ket([$Phi^+$]) = 1/sqrt(2) #ket("00") + 1/sqrt(2) #ket("11")$
+- $#ket([$Phi^-$]) = 1/sqrt(2) #ket("00") - 1/sqrt(2) #ket("11")$
+- $#ket([$Psi^+$]) = 1/sqrt(2) #ket("01") + 1/sqrt(2) #ket("10")$
+- $#ket([$Psi^-$]) = 1/sqrt(2) #ket("01") - 1/sqrt(2) #ket("10")$
+
+#problem()
+The probabilistic bits we get when measuring any of the above may be called _anticorrelated bits_.
+
+If we measure the first bit of any of these states and observe $1$, what is the resulting compound state?
+
+What if we observe $0$ instead?
+
+Do you see why we can call these bits anticorrelated?
+
+#v(1fr)
+
+#problem()
+Show that the bell states are orthogonal
+
+#hint[Dot product]
+
+#v(1fr)
+
+#problem()<bellmeasure>
+Say we have a pair of qubits in one of the four bell states.
+
+How can we find out which of the four states we have, with certainty?
+
+#hint[$H #ket("+") = #ket("0")$, and $H #ket("-") = #ket("1")$]
+
+#v(1fr)
+#pagebreak()
+
+#definition()
+The $Z$ gate is defined as follows:
+$ Z mat(psi_0; psi_1) = mat(psi_0; -psi_1) $
+
+#v(1fr)
+#pagebreak()

src/Advanced/Introduction to Quantum/src/parts/08 teleport.typ

@@ -0,0 +1,31 @@
+#import "@local/handout:0.1.0": *
+
+// Define quantum notation macros
+#let ket(content) = $|#content angle.r$
+#let bra(content) = $angle.l #content|$
+
+= Quantum Teleportation
+
+Superdense coding lets us convert quantum bandwidth into classical bandwidth. Quantum teleportation does the opposite, using two classical bits and an entangled pair to transmit a quantum state.
+
+*Setup:* Again, suppose Alice and Bob each have half of a $#ket([$Phi^+$])$ state. We'll call the state Alice wants to teleport $#ket(math.psi) = psi_0 #ket("0") + psi_1 #ket("1")$.
+
+#problem()
+What is the three-qubit state $#ket(math.psi) #ket([$Phi^+$])$ in terms of $psi_0$ and $psi_1$?
+
+#v(1fr)
+
+#problem()
+To teleport $#ket(math.psi)$, Alice applies the following circuit to her two qubits, where $#ket([$Phi^+_"A"$])$ is her half of $#ket([$Phi^+$])$. She then measures both qubits and sends the result to Bob.
+
+#align(center)[
+  // Teleportation circuit diagram would go here
+  #box(width: 8cm, height: 4cm)[
+    _[Quantum teleportation circuit diagram would go here]_
+  ]
+]
+
+What should Bob do so that $#ket([$Phi^+_"B"$])$ takes the state $#ket(math.psi)$ had initially?
+
+#v(1fr)
+#pagebreak()

src/Advanced/Tropical Polynomials/macros.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 
 // Shorthand, we'll be using these a lot.
@@ -7,15 +7,17 @@
 #let tm = sym.times.circle
 
 #let graphgrid(inner_content) = {
-  align(center, box(inset: 3mm, cetz.canvas({
+  align(
+    center,
+    box(
+      inset: 3mm,
+      cetz.canvas({
         import cetz.draw: *
         let x = 5.25
 
         grid(
-      (0, 0),
+          (0, 0), (x, x), step: 0.75,
-      (x, x),
+          stroke: luma(100) + 0.3mm
-      step: 0.75,
-      stroke: luma(100) + 0.3mm,
         )
 
         if (inner_content != none) {
@@ -31,7 +33,9 @@
           (x + 0.25, 0),
           stroke: 0.75mm + black,
         )
-  })))
+      }),
+    ),
+  )
 }
 
 /// Adds extra padding to an equation.
@@ -44,16 +48,23 @@
 /// Note that there are newlines between the $ and content,
 /// this gives us display math (which is what we want when using this macro)
 #let eqnbox(eqn) = {
-  align(center, box(
+  align(
+    center,
+    box(
       inset: 3mm,
       eqn,
-  ))
+    ),
+  )
 }
 
 #let dotline(a, b) = {
-  cetz.draw.line(a, b, stroke: (
+  cetz.draw.line(
+    a,
+    b,
+    stroke: (
       dash: "dashed",
       thickness: 0.5mm,
       paint: ored,
-  ))
+    ),
+  )
 }

src/Advanced/Tropical Polynomials/parts/01 polynomials.typ

@@ -1,18 +1,21 @@
 #import "@local/handout:0.1.0": *
 #import "../macros.typ": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = Tropical Polynomials
 
 #definition()
 A _polynomial_ is an expression formed by adding and multiplying numbers and a variable $x$. \
 Every polynomial can be written as
-#align(center, box(
+#align(
+  center,
+  box(
     inset: 3mm,
     $
       c_0 + c_1 x + c_2 x^2 + ... + c_n x^n
     $,
-))
+  ),
+)
 for some nonnegative integer $n$ and coefficients $c_0, c_1, ..., c_n$. \
 The _degree_ of a polynomial is the largest $n$ for which $c_n$ is nonzero.
 
@@ -40,12 +43,15 @@ In this section, we will analyze tropical polynomials:
 #definition()
 A _tropical_ polynomial is a polynomial that uses tropical addition and multiplication. \
 In other words, it is an expression of the form
-#align(center, box(
+#align(
+  center,
+  box(
     inset: 3mm,
     $
       c_0 #tp (c_1 #tm x) #tp (c_2 #tm x^2) #tp ... #tp (c_n #tm x^n)
     $,
-))
+  ),
+)
 where all exponents represent repeated tropical multiplication.
 
 #pagebreak() // MARK: page
@@ -60,7 +66,7 @@ Draw a graph of the tropical polynomial $f(x) = x^2 #tp 1x #tp 4$. \
 #if_no_solutions(graphgrid(none))
 
 #solution([
-  $f(x) = min(2x, 1+x, 4)$, which looks like:
+  $f(x) = min(2x , 1+x, 4)$, which looks like:
 
   #graphgrid({
     import cetz.draw: *
@@ -84,12 +90,15 @@ Draw a graph of the tropical polynomial $f(x) = x^2 #tp 1x #tp 4$. \
 #problem()
 Now, factor $f(x) = x^2 #tp 1x #tp 4$ into two polynomials with degree 1. \
 In other words, find $r$ and $s$ so that
-#align(center, box(
+#align(
+  center,
+  box(
     inset: 3mm,
     $
       x^2 #tp 1x #tp 4 = (x #tp r)(x #tp s)
     $,
-))
+  ),
+)
 
 we will call $r$ and $s$ the _roots_ of $f$.
 
@@ -150,19 +159,15 @@ Find a factorization of $f$ in the form $a(x #tp r)(x#tp s)$.
 #solution([
   We (tropically) factor out $-2$ to get
 
-  #eqnbox(
+  #eqnbox($
-    $
     f(x) = -2(x^2 #tp 2x #tp 10)
-    $,
+  $)
-  )
 
 
   by the same process as the previous problem, we get
-  #eqnbox(
+  #eqnbox($
-    $
     f(x) = -2(x #tp 2)(x #tp 8)
-    $,
+  $)
-  )
 ])
 
 #v(1fr)
@@ -231,11 +236,11 @@ Graph $f(x) = 1x^2 #tp 3x #tp 5$.
 #problem()
 Find a factorization of $f$ in the form $a(x #tp r)(x#tp s)$.
 
-#solution(eqnbox(
+#solution(
-  $
+  eqnbox($
     f(x) = 1x^2 #tp 3 x #tp 5 = 1(x #tp 2)^2
-  $,
+  $),
-))
+)
 
 #v(1fr)
 
@@ -258,7 +263,8 @@ Graph $f(x) = 2x^2 #tp 4x #tp 4$.
 
 #if_no_solutions(graphgrid(none))
 
-#solution(graphgrid({
+#solution(
+  graphgrid({
     import cetz.draw: *
     let step = 0.75
 
@@ -272,7 +278,8 @@ Graph $f(x) = 2x^2 #tp 4x #tp 4$.
       (7.5 * step, 4 * step),
       stroke: 1mm + oblue,
     )
-}))
+  }),
+)
 
 
 #problem()
@@ -318,7 +325,7 @@ Find a formula for $B$ in terms of $a$, $b$, and $c$. \
 
 #solution([
   If we want to factor $a(x^2 #tp (b-a)x #tp (c-a))$, we need to find $r$ and $s$ so that
-  - $min(r, s) = b-a$, and
+  - $min(r,s) = b-a$, and
   - $r + s = c - a$
 
   #v(2mm)
@@ -334,8 +341,9 @@ Find a formula for $B$ in terms of $a$, $b$, and $c$. \
 
   *Case 2:* If $b > (a + c #sym.div) 2$, then
   $
-    accent(f, macron)(x) & = a x^2 #tp ((a+c)/2)x #tp c \
+    accent(f, macron)(x)
-                         & = a(x #tp (c-a)/2)^2
+    &= a x^2 #tp ((a+c)/2)x #tp c \
+    &= a(x #tp (c-a)/2)^2
   $
   has the same graph as $f$, and thus $B = (a+c) #sym.div 2$
 

src/Advanced/Tropical Polynomials/parts/02 cubic.typ

@@ -1,6 +1,6 @@
 #import "@local/handout:0.1.0": *
 #import "../macros.typ": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = Tropical Cubic Polynomials
 
@@ -131,12 +131,15 @@ Using the last three problems, find formulas for $B$ and $C$ in terms of $a$, $b
 #problem()
 What are the roots of the following polynomial?
 
-#align(center, box(
+#align(
+  center,
+  box(
     inset: 3mm,
     $
       3 x^6 #tp 4 x^5 #tp 2 x^4 #tp x^3 #tp x^2 #tp 4 x #tp 5
     $,
-))
+  ),
+)
 
 #solution([
   We have
@@ -166,8 +169,9 @@ Find a formula for each $C_i$ in terms of $c_0, c_1, ..., c_n$.
 
 #solution([
   $
-    A_j & = min_(l<=j<k)( (a_l - a_k) / (k-l) (k-j) + a_k )       \
+    A_j
-        & = min_(l<=j<k)( a_l (k-j) / (k-l) + a_k (j-l) / (k-l) )
+    &= min_(l<=j<k)( (a_l - a_k) / (k-l) (k-j) + a_k ) \
+    &= min_(l<=j<k)( a_l (k-j) / (k-l) + a_k (j-l) / (k-l) )
   $
 
   #v(2mm)

src/Advanced/Wallpaper/parts/00 intro.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = Wallpaper Symmetries
 

src/Advanced/Wallpaper/parts/01 reflect.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = Mirror Symmetry
 

src/Advanced/Wallpaper/parts/02 rotate.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = Rotational Symmetry
 

src/Advanced/Wallpaper/parts/03 problems.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 #let pat(img, sol) = {
   problem()

src/Advanced/Wallpaper/parts/04 theorem.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 = The Signature-Cost Theorem
 
@@ -7,7 +7,9 @@
 First, we'll associate a _cost_ to each type of symmetry in orbifold notation:
 
 #v(4mm)
-#align(center, table(
+#align(
+  center,
+  table(
     stroke: (1pt, 1pt),
     align: center,
     columns: (auto, auto, auto, auto),
@@ -20,7 +22,8 @@ First, we'll associate a _cost_ to each type of symmetry in orbifold notation:
     [$(n-1) / n$],
     [#sym.convolve`n`],
     [$(n-1) / (2n)$],
-))
+  ),
+)
 
 
 We then calculate the total "cost" of a signature by adding up the costs of each component.

src/Warm-Ups/Big-Tac-Toe/main.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 #show: handout.with(
   title: [Warm-Up: Big-Tac-Toe],
@@ -75,7 +75,9 @@ How does your strategy change? \
 #if extra_boards {
   pagebreak()
 
-  align(center, grid(
+  align(
+    center,
+    grid(
       stroke: none,
       align: center,
       columns: (1fr, 1fr),
@@ -83,5 +85,6 @@ How does your strategy change? \
       btt(0.35), btt(0.35),
       btt(0.35), btt(0.35),
       btt(0.35), btt(0.35),
-  ))
+    ),
+  )
 }

src/Warm-Ups/Odd Dice/main.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 
 #show: handout.with(
@@ -43,7 +43,10 @@ Now, consider the set of six-sided dice below:
 - Die $E$: $0, 5, 5, 5, 5, 5$
 On average, which die beats each of the others? Draw a diagram.
 
-#solution(align(center, cetz.canvas({
+#solution(
+  align(
+    center,
+    cetz.canvas({
       import cetz.draw: *
 
       let s = 0.8 // Scale
@@ -92,7 +95,9 @@ On average, which die beats each of the others? Draw a diagram.
       content(c, text(fill: white, size: t, [*C*]))
       content(d, text(fill: white, size: t, [*D*]))
       content(e, text(fill: white, size: t, [*E*]))
-})))
+    }),
+  ),
+)
 
 #v(1fr)
 

src/Warm-Ups/Painting/main.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 #show: handout.with(
   title: [Warm-Up: What's an AST?],
@@ -18,7 +18,9 @@ You may detach the string as you hang the painting, but it must be re-attached o
 
 #v(2mm)
 
-#align(center, cetz.canvas({
+#align(
+  center,
+  cetz.canvas({
     import cetz.draw: *
     let s = 2.5
 
@@ -67,7 +69,8 @@ You may detach the string as you hang the painting, but it must be re-attached o
     )
 
     circle((0.66 * s, 0.66 * s), radius: 0.07 * s, fill: white)
-}))
+  }),
+)
 
 #solution([
   Say we have a left nail and a right nail. The path of the string is as follows:

src/Warm-Ups/Passing Balls/main.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 #show: handout.with(
   title: [Warm-Up: Passing Balls],
@@ -78,7 +78,10 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
 
         let i = 1
         for p in pts {
-          circle(p, radius: radius * s, fill: if i == 1 {
+          circle(
+            p,
+            radius: radius * s,
+            fill: if i == 1 {
               ored
             } else if i == 2 {
               ogreen
@@ -86,9 +89,12 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
               oorange
             } else if i == 4 {
               oblue
-          } else { white })
+            } else { white },
+          )
 
-          content(p, text(
+          content(
+            p,
+            text(
               fill: if i <= 4 {
                 white
               } else {
@@ -96,7 +102,8 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
               },
               size: t,
               [*#i*],
-          ))
+            ),
+          )
           i = i + 1
         }
       }),
@@ -111,7 +118,10 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
           let l = calc.rem(((i - 1) * 5), 12) + 1
 
 
-          circle(p, radius: radius * s, fill: if l == 1 {
+          circle(
+            p,
+            radius: radius * s,
+            fill: if l == 1 {
               ored
             } else if l == 2 {
               ogreen
@@ -119,9 +129,12 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
               oorange
             } else if l == 4 {
               oblue
-          } else { white })
+            } else { white },
+          )
 
-          content(p, text(
+          content(
+            p,
+            text(
               fill: if l <= 4 {
                 white
               } else {
@@ -129,7 +142,8 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
               },
               size: t,
               [*#l*],
-          ))
+            ),
+          )
           i = i + 1
         }
       }),
@@ -144,7 +158,10 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
           let l = calc.rem(((i - 1) * 5), 12) + 1
 
 
-          circle(p, radius: radius * s, fill: if l == 1 {
+          circle(
+            p,
+            radius: radius * s,
+            fill: if l == 1 {
               oblue
             } else if l == 2 {
               oorange
@@ -152,9 +169,12 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
               ored
             } else if l == 4 {
               ogreen
-          } else { white })
+            } else { white },
+          )
 
-          content(p, text(
+          content(
+            p,
+            text(
               fill: if l <= 4 {
                 white
               } else {
@@ -162,7 +182,8 @@ Participant 1 has a black ball. Which balls are held by participants 2, 3, and 4
               },
               size: t,
               [*#l*],
-          ))
+            ),
+          )
           i = i + 1
         }
       }),

src/Warm-Ups/What's an AST/main.typ

@@ -1,5 +1,5 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 #show: handout.with(
   title: [Warm-Up: What's an AST?],
@@ -24,7 +24,9 @@ respecting the order of operations $[and, times, div, +, -]$.
 
 #v(2mm)
 
-#align(center, cetz.canvas({
+#align(
+  center,
+  cetz.canvas({
     import cetz.draw: *
 
     // spell:off
@@ -68,4 +70,5 @@ respecting the order of operations $[and, times, div, +, -]$.
     line("bb", "bba")
     line("bb", "bbb")
     // spell:on
-}))
+  }),
+)

src/Warm-Ups/Wild Tic-Tac-Toe/main.typ

@@ -1,12 +1,14 @@
 #import "@local/handout:0.1.0": *
-#import "@preview/cetz:0.4.2"
+#import "@preview/cetz:0.3.1"
 
 #show: handout.with(
   title: [Warm-Up: Wild Tic-Tac-Toe],
   by: "Mark",
 )
 
-#let ttt = align(center, cetz.canvas({
+#let ttt = align(
+  center,
+  cetz.canvas({
     import cetz.draw: *
     let s = 0.7 // scale
 
@@ -15,7 +17,8 @@
     line((1 * s, 3 * s), (1 * s, -3 * s))
     line((3 * s, -1 * s), (-3 * s, -1 * s))
     line((3 * s, 1 * s), (-3 * s, 1 * s))
-}))
+  }),
+)
 
 
 #problem()