362 citations · 378 across the 6 of their papers we have counts for
6 papers
Resource savings from fault-tolerant circuit design
Andrew K. Tan, Isaac L. Chuang
Using fault-tolerant constructions, computations performed with unreliable components can simulate their noiseless counterparts though the introduction of a modest amount of redund…
Reliable computation by large-alphabet formulas in the presence of noise
Andrew K. Tan, Matthew Ho, Isaac L. Chuang
We present two new positive results for reliable computation using formulas over physical alphabets of size . First, we show that for logical alphabets of size th…
Error Correction of Quantum Algorithms: Arbitrarily Accurate Recovery Of Noisy Quantum Signal Processing
Andrew K. Tan, Yuan Liu, Minh C. Tran +1
The intrinsic probabilistic nature of quantum systems makes error correction or mitigation indispensable for quantum computation. While current error-correcting strategies focus on…
Pareto-optimal clustering with the primal deterministic information bottleneck
Andrew K. Tan, Max Tegmark, Isaac L. Chuang
At the heart of both lossy compression and clustering is a trade-off between the fidelity and size of the learned representation. Our goal is to map out and study the Pareto fronti…
Fault-Tolerant Neural Networks from Biological Error Correction Codes
Alexander Zlokapa, Andrew K. Tan, John M. Martyn +3
It has been an open question in deep learning if fault-tolerant computation is possible: can arbitrarily reliable computation be achieved using only unreliable neurons? In the grid…
A Grand Unification of Quantum Algorithms
John M. Martyn, Zane M. Rossi, Andrew K. Tan +1
Quantum algorithms offer significant speedups over their classical counterparts for a variety of problems. The strongest arguments for this advantage are borne by algorithms for qu…