Vol. 1 · No. 001
|Analyze Quantum⟩
Technical notes on quantum computing, worked out from the math up.
Lead essay · Forecasting
Forecasting the arrival of useful quantum computers

Quantum computers have been promising to revolutionize computing for decades. But how close are we to seeing one solve a problem that actually matters? In this article, I use three complementary approaches to estimate when quantum computing might have its ChatGPT moment. I examine company roadmaps, historical trends in quantum hardware, and the technical challenges facing different hardware platforms. I then compare their predictions to arrive at a plausible timeline. I also include an interactive model that lets readers explore how different assumptions change the forecast.

Read the essay → By Abhinav Muraleedharan
The three forecasts
’31
ScienceFirst useful fault-tolerant science, around 2031 to 2033
’33
CryptoFirst machine that can break today's public-key cryptography, slowly, in the early-to-mid 2030s
’35
IndustryMachines that change an industry, mid-2030s
|analyze quantum⟩
Technical notes on quantum computing

Quantum computing, worked out from the math up.

Analysis of quantum algorithms, architectures and the full stack in between. Each essay starts from resource counts and complexity, then asks what that means for real machines.

SCIENCE · 2031–33First useful fault-tolerant science
CRYPTO · EARLY-TO-MID 2030sBreaking today's public-key cryptography, slowly
INDUSTRY · MID-2030sMachines that change an industry

Essays

Index · 1 essay
No. 001October 2026New

Forecasting the arrival of useful quantum computers

Quantum computers have been promising to revolutionize computing for decades. But how close are we to seeing one solve a problem that actually matters? In this article, I use three complementary approaches to estimate when quantum computing might have its ChatGPT moment. I examine company roadmaps, historical trends in quantum hardware, and the technical challenges facing different hardware platforms. I then compare their predictions to arrive at a plausible timeline. I also include an interactive model that lets readers explore how different assumptions change the forecast.

Algorithms · Error correction · HardwareAbhinav Muraleedharan
No. 002Up next

How to build a neutral-atom quantum computer

Coming soon. Get in touch to hear when it's out.

Topics

What I write about

Posts cover every layer of a quantum computer, from applications down to the physical qubits.

L5

Applications

Chemistry, materials, optimization, cryptography and machine learning, and how quantum methods compare with the best classical ones.

L4

Algorithms

Hamiltonian simulation, quantum linear algebra and quantum machine learning, and whether the speedups hold up in practice.

L3

Error correction

Surface codes, qLDPC codes and magic states, and how many physical qubits it takes to build one logical qubit.

L2

Architecture

How qubits are connected, controlled and cooled, and how fast errors can be decoded.

L1

Physical qubits

Superconducting, trapped-ion, neutral-atom and photonic qubits, and how their error rates and speeds compare.

About the author

Abhinav Muraleedharan

Abhinav is a PhD student at the University of Toronto, working with Nathan Wiebe on quantum algorithms. He has developed exponentially faster quantum algorithms for simulating physical systems, and is now working on quantum algorithms for machine learning. He holds a Master's from the University of Toronto and has worked at Pacific Northwest National Laboratory.

Contact

Questions, corrections, collaborations

If an essay gets a number wrong, or you are working on something related, write in. Research collaborations and speaking requests are welcome too.

abhinavmuraleedharan@gmail.com