41 citations · 165 across the 14 of their papers we have counts for
18 papers
Gibbs state preparation through quantum decoding
Christophe Piveteau, Yihui Quek, M. Isabel Franco Garrido
We propose a Gibbs state preparation algorithm that exploits algebraic structure in the Hamiltonian. Our starting point is Hamiltonian Decoded Quantum Interferometry (HDQI), a rece…
Predicting properties of Scrooge ensembles with high accuracy and low sample complexity
Yue Wu, Yuzhi Tong, Helen Propson +2
The Scrooge ensemble associated with a density matrix is the maximally random ensemble whose average density matrix is . It has attracted growing interest for its applicatio…
Post-Quantum Cryptography from Quantum Stabilizer Decoding
Jonathan Z. Lu, Alexander Poremba, Yihui Quek +1
Post-quantum cryptography currently rests on a small number of hardness assumptions, posing significant risks should any one of them be compromised. This vulnerability motivates th…
Deep thermalization with and without quantum chaos
Soumik Ghosh, Arjun Mirani, Yihui Quek +1
Can measuring part of a quantum system make the remainder more random than the whole? Deep thermalization is a phenomenon in which measurement on part of a thermalizing quantum man…
Hamiltonian Decoded Quantum Interferometry
Alexander Schmidhuber, Jonathan Z. Lu, Noah Shutty +3
We introduce Hamiltonian Decoded Quantum Interferometry (HDQI), a quantum algorithm that utilizes coherent Bell measurements and the symplectic representation of the Pauli group to…
Quantum advantage from random geometrically-two-local Hamiltonian dynamics
Yihui Quek
Classical hardness-of-sampling results are largely established for random quantum circuits, whereas analog simulators natively realize time evolutions under geometrically local Ham…
Information-Computation Gaps in Quantum Learning via Low-Degree Likelihood
Sitan Chen, Weiyuan Gong, Jonas Haferkamp +1
In a variety of physically relevant settings for learning from quantum data, designing protocols that can computationally efficiently extract information remains largely an art, an…
Simulating quantum chaos without chaos
Andi Gu, Yihui Quek, Susanne Yelin +2
Quantum chaos is a quantum many-body phenomenon that is associated with a number of intricate properties, such as level repulsion in energy spectra or distinct scalings of out-of-t…
The Learning Stabilizers with Noise problem
Alexander Poremba, Yihui Quek, Peter Shor
Random classical codes have good error correcting properties, and yet they are notoriously hard to decode in practice. Despite many decades of extensive study, the fastest known al…
Noise-induced shallow circuits and absence of barren plateaus
Antonio Anna Mele, Armando Angrisani, Soumik Ghosh +4
Motivated by realistic hardware considerations of the pre-fault-tolerant era, we comprehensively study the impact of uncorrected noise on quantum circuits. We first show that in th…
Learning quantum states and unitaries of bounded gate complexity
Haimeng Zhao, Laura Lewis, Ishaan Kannan +3
While quantum state tomography is notoriously hard, most states hold little interest to practically-minded tomographers. Given that states and unitaries appearing in Nature are of…
Pseudomagic Quantum States
Andi Gu, Lorenzo Leone, Soumik Ghosh +3
Notions of nonstabilizerness, or "magic", quantify how non-classical quantum states are in a precise sense: states exhibiting low nonstabilizerness preclude quantum advantage. We i…
Learning quantum processes without input control
Marco Fanizza, Yihui Quek, Matteo Rosati
We introduce a general statistical learning theory for processes that take as input a classical random variable and output a quantum state. Our setting is motivated by the practica…
Exponentially tighter bounds on limitations of quantum error mitigation
Yihui Quek, Daniel Stilck França, Sumeet Khatri +2
Quantum error mitigation has been proposed as a means to combat unwanted and unavoidable errors in near-term quantum computing without the heavy resource overheads required by faul…
Multivariate trace estimation in constant quantum depth
Yihui Quek, Eneet Kaur, Mark M. Wilde
There is a folkloric belief that a depth- quantum circuit is needed to estimate the trace of the product of density matrices (i.e., a multivariate trace), a subroutine cr…
Learnability of the output distributions of local quantum circuits
Marcel Hinsche, Marios Ioannou, Alexander Nietner +6
There is currently a large interest in understanding the potential advantages quantum devices can offer for probabilistic modelling. In this work we investigate, within two differe…
Private learning implies quantum stability
Srinivasan Arunachalam, Yihui Quek, John Smolin
Learning an unknown -qubit quantum state is a fundamental challenge in quantum computing. Information-theoretically, it is known that tomography requires exponential in …
Bounding the forward classical capacity of bipartite quantum channels
Dawei Ding, Sumeet Khatri, Yihui Quek +3
We introduce various measures of forward classical communication for bipartite quantum channels. Since a point-to-point channel is a special case of a bipartite channel, the measur…