Feedforward Quantum Singular Value Transformation

Dong An; Murphy Yuezhen Niu; Yulong Dong

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Feedforward Quantum Singular Value Transformation

Yulong Dong, Dong An, Murphy Yuezhen Niu

Quantum Physics · Submitted 14 Aug 2024

abstract compiled · 2026-09-23 · no language-model review

The authors' main claim Our results show that FQSVTs can exponentially accelerate the projection of quantum states onto energy subspaces, outperforming probabilistic projection and adiabatic algorithms with superior efficiency and a drastic reduction in query complexity.

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Compiled by classifier-1.13.0 via TypeSafe API, question bank abstract-p1-20260923, 2026-09-23: 1 request, 3,712 input tokens.

What the abstract itself states, as probabilities: claims first 0.10 · states limitation 0.06 · human participants 0.02 · controlled comparison 0.62 · randomized assignment 0.01 · states quantitative result 0.12 · compares with prior results 0.96 · mentions code or data availability 0.03.

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arXiv listing abstract v1. Results and the main claim are underlined; show every role.

In this paper, we introduce a major advancement in Quantum Singular Value Transformation (QSVT) through the development of Feedforward QSVT (FQSVT), a framework that significantly enhances the efficiency and robustness of quantum algorithm design. By leveraging intermediate measurements and feedforward operations, FQSVTs reclaim quantum information typically discarded in conventional QSVT, enabling more efficient transformations. Our results show that FQSVTs can exponentially accelerate the projection of quantum states onto energy subspaces, outperforming probabilistic projection and adiabatic algorithms with superior efficiency and a drastic reduction in query complexity. In the context of superconducting qubits, FQSVTs offer a powerful tool for managing energy subspaces, improving efficiency for state preparation and leakage detection.

background contribution method result interpretation main claim

What the classifier reports for each sentence. The number is the probability it gave the label.
#	sentence	role	the authors' own work	states the main conclusion	strength
s0	In this paper, we introduce a major advancement in Quantum Singular Value Transformation (QSVT) through the development of Feedforward QSVT (FQSVT), a framework that significantly enhances the efficiency and robustness of quantum algorithm design.	contribution 1.00	0.87	0.34	asserted 1.00
s1	By leveraging intermediate measurements and feedforward operations, FQSVTs reclaim quantum information typically discarded in conventional QSVT, enabling more efficient transformations.	method 0.92	0.48	0.11	asserted 1.00
s2	Our results show that FQSVTs can exponentially accelerate the projection of quantum states onto energy subspaces, outperforming probabilistic projection and adiabatic algorithms with superior efficiency and a drastic reduction in query complexity.	result 1.00	0.90	0.59	asserted 1.00
s3	In the context of superconducting qubits, FQSVTs offer a powerful tool for managing energy subspaces, improving efficiency for state preparation and leakage detection.	interpretation 0.83	0.41	0.08	asserted 0.95

What kind of paper the classifier reports this is: method or tool 1.00 · evidence from proof or derivation 0.80.

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The paper

Original abstract

In this paper, we introduce a major advancement in Quantum Singular Value Transformation (QSVT) through the development of Feedforward QSVT (FQSVT), a framework that significantly enhances the efficiency and robustness of quantum algorithm design. By leveraging intermediate measurements and feedforward operations, FQSVTs reclaim quantum information typically discarded in conventional QSVT, enabling more efficient transformations. Our results show that FQSVTs can exponentially accelerate the projection of quantum states onto energy subspaces, outperforming probabilistic projection and adiabatic algorithms with superior efficiency and a drastic reduction in query complexity. In the context of superconducting qubits, FQSVTs offer a powerful tool for managing energy subspaces, improving efficiency for state preparation and leakage detection.

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References

Forward citations

Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

Solving wave propagation problems via geometric quantum state preparation on dispersion manifolds
quant-ph 2026-09 accept novelty 8.0 of 10

A quantum algorithm for the Helmholtz equation that prepares the resonant manifold directly, achieving polylogarithmic gate complexity independent of domain size for a fixed number of sources.
Measurement-Based Uncomputation from an Error Correction Perspective
quant-ph 2026-09 conditional novelty 6.0 of 10

The success probability of post-selected measurement-based uncomputation equals two to the power of minus the affine rank of the populated garbage support, unifying modular-arithmetic, QROM, and QRAM constructions und...

How the literature uses it

1 arXiv paper cite this in 1 sentence

Each citing sentence is taken from the citing paper's LaTeX source and typed by Pith's classifier. A label appears at probability 0.8 or more (0.95 for support), a contest at 0.7 or more; the quoted words are the citing authors'. How each label was checked · JSON

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Uses the method or tool of 1 paper

To construct a digital quantum algorithm, we can apply the truncated Dyson series method [ref] to solve the Hamiltonian simulation problem in <ref>.

Hamiltonian Simulation in the Interaction Picture · Adiabatic state preparation · 1.00

Cites as background 3 papers

To accommodate the unitary nature of quantum operations, the relevant matrix $H$ is accessed through an input model called block encoding, which is a unitary $U_H$ whose upper-left submatrix is equal to $H$ (up to rescaling) [ref] .

The power of block-encoded matrix powers: improved regression techniques via faster Hamiltonian simulation · Quantum singular value transformations with feedforward operations · 0.86
Efficient quantum algorithms have been demonstrated through QSVT for a variety of problems, including quantum Hamiltonian simulation [ref] , ground state preparation [ref] , quantum linear system problems [ref] , and quantum benchmarking [ref] .

Ground state preparation and energy estimation on early fault-tolerant quantum computers via quantum eigenvalue transformation of unitary matrices · Introduction · 0.88
Efficient quantum algorithms have been demonstrated through QSVT for a variety of problems, including quantum Hamiltonian simulation [ref] , ground state preparation [ref] , quantum linear system problems [ref] , and quantum benchmarking [ref] .

Multi-level quantum signal processing with applications to ground state preparation using fast-forwarded Hamiltonian evolution · Introduction · 0.88

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