activity
20172026
most citedLearning hard quantum distributions with variational autoencoders

76 citations · 113 across the 11 of their papers we have counts for

collaborators

11 papers

quant-ph2026

Putting fermions onto a digital quantum computer

Riley W. Chien, Mitchell L. Chiew, Brent Harrison +8

Quantum computers are expected to become a powerful tool for studying physical quantum systems. Consequently, a number of quantum algorithms for studying the physical properties of…

quant-ph2025

Classical simulation of parity-preserving quantum circuits

Carolin Wille, Sergii Strelchuk

We present a classical simulation method for fermionic quantum systems which, without loss of generality, can be represented by parity-preserving circuits made of two-qubit gates i…

quant-ph2025★ 1 cited

Optimal fermion-qubit mappings via quadratic assignment

Mitchell Chiew, Cameron Ibrahim, Ilya Safro +1

Simulation of fermionic systems is one of the most promising applications of quantum computers. It spans problems in quantum chemistry, high-energy physics and condensed matter. Un…

quant-ph2024★ 1 cited

Ternary tree transformations are equivalent to linear encodings of the Fock basis

Mitchell Chiew, Brent Harrison, Sergii Strelchuk

We consider two approaches to designing fermion-qubit mappings: (1) ternary tree transformations, which use Pauli representations of the Majorana operators that correspond to root-…

quant-ph2024★ 2 cited

A Sierpinski Triangle Fermion-to-Qubit Transform

Brent Harrison, Mitchell Chiew, Jason Necaise +3

In order to simulate a system of fermions on a quantum computer, it is necessary to represent the fermionic states and operators on qubits. This can be accomplished in multiple way…

quant-ph2024

James-Stein Estimation in Quantum Gaussian Sensing

Wilfred Salmon, Sergii Strelchuk, David Arvidsson-Shukur

The James-Stein estimator is a biased estimator -- for a finite number of samples its expected value is not the true mean. The maximum-likelihood estimator (MLE), is unbiased and a…

quant-ph2023

Provable Advantage in Quantum PAC Learning

Wilfred Salmon, Sergii Strelchuk, Tom Gur

We revisit the problem of characterising the complexity of Quantum PAC learning, as introduced by Bshouty and Jackson [SIAM J. Comput. 1998, 28, 1136-1153]. Several quantum advanta…

quant-ph2022★ 8 cited

Ultrafast Hybrid Fermion-to-Qubit mapping

Oliver O'Brien, Sergii Strelchuk

Fermion-to-qubit mappings play a crucial role in representing fermionic interactions on a quantum computer. Efficient mappings translate fermionic modes of a system to qubit intera…

quant-ph2022★ 10 cited

Only Classical Parameterised States have Optimal Measurements under Least Squares Loss

Wilfred Salmon, Sergii Strelchuk, David Arvidsson-Shukur

Measurements of quantum states form a key component in quantum-information processing. It is therefore an important task to compare measurements and furthermore decide if a measure…

quant-ph2021★ 15 cited

Discovering optimal fermion-qubit mappings through algorithmic enumeration

Mitchell Chiew, Sergii Strelchuk

Simulating fermionic systems on a quantum computer requires a high-performing mapping of fermionic states to qubits. A characteristic of an efficient mapping is its ability to tran…

quant-ph2017★ 76 cited

Learning hard quantum distributions with variational autoencoders

Andrea Rocchetto, Edward Grant, Sergii Strelchuk +2

Studying general quantum many-body systems is one of the major challenges in modern physics because it requires an amount of computational resources that scales exponentially with…