In the Shadow of the Hadamard Test: Using the Garbage State for Good and Further Modifications

The Hadamard test is one of the pillars on which quantum algorithm development rests and, at the same time, is naturally suited for the intermediate regime between the current era of noisy quantum devices and complete fault tolerance. Its applications use measurements of the auxiliary qubit to extract information but disregard the system register completely. Concomitantly, but independently of this development, advances in quantum learning theory have enabled the efficient representation of quantum states via classical shadows. This Letter shows that, strikingly, putting both lines of thought into a new context results in substantial improvements to the Hadamard test on a single auxiliary readout qubit, by suitably exploiting classical shadows on the remaining n-qubit work register. We argue that this combination inherits the best of both worlds and discuss statistical phase estimation as a vignette application. At the same time, the framework is more general and applicable to a wide range of other algorithms. There, we can use the Hadamard test to estimate energies on the auxiliary qubit, while classical shadows on the system register provide access to additional features such as (i) the fidelity of the initial state with certain pure quantum states, (ii) the initial state's energy, and (iii) how pure and how close the initial state is to an eigenstate of the Hamiltonian. Finally, we also discuss how anticontrolled unitaries can further augment this framework and explain how this Letter settles the exploitation of the Hadamard test for intermediate applications.

Authors

Institutions

Publication Details

Journal
Physical Review Letters
Published
2025-10-09
DOI
https://doi.org/10.1103/cqjw-kl8s
Citations
5
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
12.40

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

In the Shadow of the Hadamard Test: Using the Garbage State for Good and Further Modifications

Richard Kueng, Jens Eisert, Paul K. Faehrmann
5 citations
Physical Review Letters
Quantum Computing Algorithms and Architecture
12.40
article

In the Shadow of the Hadamard Test: Using the Garbage State for Good and Further Modifications

Richard Kueng, Jens Eisert, Paul K. Faehrmann
article en
5 citations

Abstract

The Hadamard test is one of the pillars on which quantum algorithm development rests and, at the same time, is naturally suited for the intermediate regime between the current era of noisy quantum devices and complete fault tolerance. Its applications use measurements of the auxiliary qubit to extract information but disregard the system register completely. Concomitantly, but independently of this development, advances in quantum learning theory have enabled the efficient representation of quantum states via classical shadows. This Letter shows that, strikingly, putting both lines of thought into a new context results in substantial improvements to the Hadamard test on a single auxiliary readout qubit, by suitably exploiting classical shadows on the remaining n-qubit work register. We argue that this combination inherits the best of both worlds and discuss statistical phase estimation as a vignette application. At the same time, the framework is more general and applicable to a wide range of other algorithms. There, we can use the Hadamard test to estimate energies on the auxiliary qubit, while classical shadows on the system register provide access to additional features such as (i) the fidelity of the initial state with certain pure quantum states, (ii) the initial state's energy, and (iii) how pure and how close the initial state is to an eigenstate of the Hamiltonian. Finally, we also discuss how anticontrolled unitaries can further augment this framework and explain how this Letter settles the exploitation of the Hadamard test for intermediate applications.

Physical Review LettersVol. 135(15)
Johannes Kepler University of Linz (AT), Helmholtz-Zentrum Berlin für Materialien und Energie (DE), Freie Universität Berlin (DE)
Deutsche Forschungsgemeinschaft, Bundesministerium für Bildung und Forschung, Austrian Science Fund, QuantERA
Openalex Percentile: Top 2%
Quantum Computing Algorithms and Architecture
12.40
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.