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thesis/presentations/progress.typ
Noa Aarts 858c352921
final fixes
2025-11-24 16:46:25 +01:00

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8.3 KiB
Typst
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#import "@preview/touying:0.6.1": *
#import "@preview/physica:0.9.5": *
#import "@preview/cetz:0.3.4"
#import "@preview/typsium:0.2.0": ce
#import "@preview/numbly:0.1.0": numbly
#import "./theme.typ": *
#set heading(numbering: numbly("{1}.", default: "1.1"))
#show ref: set text(size:0.5em, baseline: -0.75em)
#let cetz-canvas = touying-reducer.with(reduce: cetz.canvas, cover: cetz.draw.hide.with(bounds: true))
#show: university-theme.with(
config-info(
title: "Implementation Specific QAS", // Required
date: datetime.today().display(),
authors: ("Noa Aarts"),
// Optional Styling (for more / explanation see in the typst universe)
// ignore how bad the images look i'll adjust it until Monday
title-color: blue.darken(10%),
),
config-common(
// handout: true, // enable this for a version without animations
),
aspect-ratio: "16-9",
config-colors(
primary: rgb("#00a6d6"),
secondary: rgb("#00b3dc"),
tertiary: rgb("#b8cbde"),
neutral-lightest: rgb("#ffffff"),
neutral-darkest: rgb("#000000"),
),
)
#show outline.entry: it => link(
it.element.location(),
text(fill: rgb("#00b3dc"), size: 1.3em)[#it.indented(it.prefix(), it.body())],
)
= Week 3
== Outline
#align(horizon)[
Project plan
State of the Art
Planning
]
== The Plan
#slide[
#align(center + horizon)[
#cetz-canvas({
import cetz.draw: *
let left = -9
let mid = 0
let right = 7
let arr_col = rgb("#00a6d6").lighten(70%)
content((left, 6), [Inputs])
content((mid, 6), [Process])
content((right, 6), anchor: "west", [Outputs])
content((left, 3), [Qubits])
content((left, 2), [Gates])
content((left, 1), [Connections])
content((left, 0), text(fill: red)[Fidelities])
content((left, -1), [Expressibility])
content((left, -2), [Entanglement])
content((left, -3), text(fill: red)[Noise Treshold])
content((left, -4), text(fill: red)[Max Parameters])
line(
(-5.6, 0),
(-2.1, 0),
stroke: (
thickness: 8pt,
paint: arr_col,
cap: "round",
),
mark: (end: "stealth", scale: 8, fill: arr_col),
)
content((0,0), [test])
rect(cetz.vector.add((mid, 0), (-2, -2)), cetz.vector.add((mid, 0), (2, 2)), radius: (rest: .4), fill: rgb("#00b3dc"))
content((mid, 0), text(size: 4em)[?])
line(
(2.4, 0),
(6.0, 0),
stroke: (
thickness: 8pt,
paint: arr_col,
cap: "round",
),
mark: (end: "stealth", scale: 8, fill: arr_col),
)
content((right, 3), [QML Kernels], anchor: "west")
content(cetz.vector.add((right, 2), (1, 0)), anchor: "west", [Balanced])
content(cetz.vector.add((right, 1), (1, 0)), anchor: "west", text(fill: red)[Best Expressibility])
content(cetz.vector.add((right, 0), (1, 0)), anchor: "west", text(fill: red)[Best Entanglement])
content(cetz.vector.add((right, -1), (1, 0)), anchor: "west", text(fill: red)[Least Noise])
content(cetz.vector.add((right, -2), (1, 0)), anchor: "west", text(fill: red)[Fewer Parameters])
})
]
#text(fill: red)[red] text means it's a feature to focus on once the black points work
]
== The Process
- Cost function based on
- Expressibility
- Entanglement
- #text(fill: red)[Noise Treshold]
- #text(fill: red)[Max Parameters]
- Possible Methods (not complete)
- Monte-Carlo Tree-Search
- Machine Learning (many options)
- Bayesian Optimization
- Differentiable Optimization strategies
== State-of-the-art
#slide(composer: (auto, auto))[
#cetz-canvas({
import cetz.draw: *
line((0, 0.4), (0, 9), mark: (symbol: "stealth"))
content((-3, 4.5), anchor: "south", [Hardware], angle: 90deg)
content((-0.4, 1.0), anchor: "east", [agnostic])
content((-0.4, 8.0), anchor: "east", [specific])
line((0.4, 0), (9, 0), mark: (symbol: "stealth"))
content((5, -1.4), anchor: "north", [Task])
content((2, -0.4), anchor: "north", [agnostic])
content((8, -0.4), anchor: "north", [specific])
circle((1.3, 2), radius: 0.1, fill: black)
content((rel: (0.3, 0)), anchor: "west", text(size: 0.6em)[Hardware-Efficient Ansatz@expressibility-and-entanglement])
circle((1, 1), radius: 0.1, fill: black)
content((rel: (0.3, 0)), anchor: "west", text(size: 0.6em)[Random circuit])
circle((7, 1), radius: 0.1, fill: black)
content((rel: (0.3, 0)), anchor: "west", text(size: 0.6em)[Unitary Coupled-Cluster \ Singles and Doubles])
circle((9, 6), radius: 0.1, fill: black)
content((rel: (-0.3, -0.3)), anchor: "east", text(size: 0.6em)[Reinforcement-learning \ VQE@akash])
circle((7, 7), radius: 0.1, fill: black)
content((rel: (0.3, 0)), anchor: "west", text(size: 0.6em)[Hardware-aware Quantum \ Graph Neural Network@liu2025haqgnnhardwareawarequantumkernel])
circle((8, 5), radius: 0.1, fill: black)
content((rel: (0.3, 0)), anchor: "west", text(size: 0.6em)[Supernet@architecture-search])
circle((1.1, 7), radius: (1, 2.0), fill: rgb(0, 90, 180).lighten(40%))
content((1.1, 7), [Goal])
circle((1.3, 8), radius: 0.1, fill: black)
content((rel: (0.3, 0)), anchor: "west", text(size: 0.6em)[Training-Free Search@training-free])
})
][
#align(horizon)[
Reasons for research:
- Fast start on new problem
- Hardware update cycle
- Use as a starting point
]
]
== Comparing with training-free Search@training-free
Ways to improve:
- Smarter sampling
- Target expressibility instead of HAAR distribution
Parts to maybe re-use:
- Path-based proxy
- Very fast
- Approximates entanglement
- Filter out worst circuits
- Benchmarking
- allows for apples-to-apples
#let chev(start, len, f: none) = {
import cetz.draw: *
line(fill: f,
cetz.vector.add(start,(-1, -1))
, cetz.vector.add(start, (len - 1, -1))
, cetz.vector.add(start,(len, 0))
, cetz.vector.add(start, (len - 1, 1))
, cetz.vector.add(start,(-1,1))
, start
, cetz.vector.add(start,(-1,-1)))
}
#let lg(color1, color2) = gradient.linear(color2, color1, color2, angle: 90deg)
#let today-offset = (datetime.today() - datetime(day: 10, month: 11, year: 2025)).weeks()
== Planning
#slide[
#align(center + horizon)[
#cetz-canvas(length: 0.8cm, {
import cetz.draw: *
let lower = -10
content((today-offset, 0), anchor: "south", [today])
line((today-offset, -0.5), (today-offset, lower), stroke: (paint: rgb("#ff00cc")))
for x in (0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33) {
content((x, 0), text(size: 0.4em)[#(datetime(day: 10, month: 11, year: 2025) + duration(weeks: x)).display("[day]/[month]")], anchor: "north")
line(stroke: (paint: lime, dash: "dashed"), (x, -0.5), (x,lower))
}
line((3.6, -0.5), (3.6, lower), stroke: (paint: rgb("#0000dc")))
content((5, lower - 0.1), anchor: "north", [Literature review \ of methods])
line((6.3, -0.5), (6.3, lower), stroke: (paint: rgb("#0000dc")))
content((6.3, lower - 2.9), anchor: "north", [Methodology \ Decision])
line((15.2, -0.5), (15.2, lower), stroke: (paint: rgb("#ff0000")))
content((15.2, lower - 0.1) ,anchor: "north", [Midterm])
line((28.2, -0.5), (28.2, lower), stroke: (paint: rgb("#ff0000")))
content((28.2, lower - 0.1) ,anchor: "north", [Greenlight])
line((32.8, -0.5), (32.8, lower), stroke: (paint: rgb("#ff0000")))
content((32.0, lower - 2.1), anchor: "north", [Finalisation])
// line((14.5, -0.5), (14.5, lower), stroke: (paint: rgb("#ff00cc")))
// content((14, lower - 0.1), anchor: "north", "Midterm")
//
// chev((0.6,-2), 6.6, f: lg(yellow, yellow.darken(10%)))
// chev((6.2,-2), 1.0, f: gradient.linear(green, rgb(0,0,0,0), angle: 60deg).sharp(3).repeat(6))
// content((1.1,-2), anchor: "west", "Literature")
chev((7, -2), 2, f: lg(blue.lighten(20%), blue.lighten(5%)))
content((7.5, -3.5), anchor: "north", "Holiday")
//
// chev((9, -2), 6, f: lg(red, red.darken(10%)))
// content((10, -2), anchor: "west", "Make V1")
//
// chev((15.5, -2), 10.5, f: lg(red, red.darken(10%)))
// content((15.5, -1.5), anchor: "west", "Improvements")
// content((19.5, -2.5), anchor: "west", "Testing")
//
// chev((15.5 + 10.5, -2), 2, f: lg(purple, purple.darken(10%)))
// content((25.5, -3.5), anchor: "north", "Writing")
})
]
]
#slide[
== References <touying:unoutlined>
#bibliography("references.bib", title: [])
]
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