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In function inversion, we are given a function $f: [N] \mapsto [N]$, and want to prepare some advice of size $S$, such that we can efficiently invert any image in time $T$. This is a well studied problem with profound connections to…

Quantum Physics · Physics 2020-11-24 Kai-Min Chung , Siyao Guo , Qipeng Liu , Luowen Qian

Given a random permutation $f: [N] \to [N]$ as a black box and $y \in [N]$, we want to output $x = f^{-1}(y)$. Supplementary to our input, we are given classical advice in the form of a pre-computed data structure; this advice can depend on…

Quantum Physics · Physics 2015-07-22 Aran Nayebi , Scott Aaronson , Aleksandrs Belovs , Luca Trevisan

In permutation inversion, we are given a permutation $\pi : [N] \rightarrow [N]$, and want to prepare some advice of size $S$, such that we can efficiently invert any image in time $T$. This is a fundamental cryptographic problem with…

Computational Complexity · Computer Science 2025-10-15 Akshima , Tyler Besselman , Kai-Min Chung , Siyao Guo , Tzu-Yi Yang

We study time/memory tradeoffs of function inversion: an algorithm, i.e., an inverter, equipped with an s-bit advice on a randomly chosen function $f : [n] -> [n]$ and using $q$ oracle queries to $f$, tries to invert a randomly chosen…

Computational Complexity · Computer Science 2021-05-11 Dror Chawin , Iftach Haitner , Noam Mazor

In the permutation inversion problem, the task is to find the preimage of some challenge value, given oracle access to the permutation. This is a fundamental problem in query complexity, and appears in many contexts, particularly…

Quantum Physics · Physics 2024-04-23 Gorjan Alagic , Chen Bai , Alexander Poremba , Kaiyan Shi

The problem of distinguishing between a random function and a random permutation on a domain of size $N$ is important in theoretical cryptography, where the security of many primitives depend on the problem's hardness. We study the quantum…

Computational Complexity · Computer Science 2013-12-23 Henry Yuen

We give a classical algorithm for linear regression analogous to the quantum matrix inversion algorithm [Harrow, Hassidim, and Lloyd, Physical Review Letters'09, arXiv:0811.3171] for low-rank matrices [Wossnig, Zhao, and Prakash, Physical…

Data Structures and Algorithms · Computer Science 2022-07-06 András Gilyén , Zhao Song , Ewin Tang

We show that Durr-Hoyer's quantum algorithm of searching for extreme point of integer function can not be sped up for functions chosen randomly. Any other algorithm acting in substantially shorter time $o(\sqrt{2^n})$ gives incorrect answer…

Quantum Physics · Physics 2009-10-31 Yuri Ozhigov

Access to the time-reverse $U^{-1}$ of an unknown quantum unitary process $U$ is widely assumed in quantum learning, metrology, and many-body physics. The fundamental task of unitary time-reversal dictates implementing $U^{-1}$ to within…

Quantum Physics · Physics 2026-02-24 Kean Chen , Nengkun Yu , Zhicheng Zhang

If a functional in an inverse problem can be estimated with parametric rate, then the minimax rate gives no information about the ill-posedness of the problem. To have a more precise lower bound, we study semiparametric efficiency in the…

Statistics Theory · Mathematics 2014-05-07 Mathias Trabs

We prove that, to compute a Boolean function $f$ on $N$ variables with error probability $\epsilon$, any quantum black-box algorithm has to query at least $\frac{1 - 2\sqrt{\epsilon}}{2} \rho_f N = \frac{1 - 2\sqrt{\epsilon}}{2} \bar{S}_f$…

Quantum Physics · Physics 2007-05-23 Yaoyun Shi

Lin and Lin have recently shown how starting with a classical query algorithm (decision tree) for a function, we may find upper bounds on its quantum query complexity. More precisely, they have shown that given a decision tree for a…

Quantum Physics · Physics 2020-03-04 Salman Beigi , Leila Taghavi

Low-rank pseudoinverses are widely used to approximate matrix inverses in scalable machine learning, optimization, and scientific computing. However, real-world matrices are often observed with noise, arising from sampling, sketching, and…

Machine Learning · Computer Science 2025-10-30 Phuc Tran , Nisheeth K. Vishnoi

We work out a theory of approximate quantum error correction that allows us to derive a general lower bound for the entanglement fidelity of a quantum code. The lower bound is given in terms of Kraus operators of the quantum noise. This…

Quantum Physics · Physics 2009-11-13 Rochus Klesse

Neural network systems describe complex mappings that can be very difficult to understand. In this paper, we study the inverse problem of determining the input images that get mapped to specific neural network classes. Ultimately, we expect…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Rebecca Pattichis , Sebastian Janampa , Constantinos S. Pattichis , Marios S. Pattichis

Approximate Counting refers to the problem where we are given query access to a function $f : [N] \to \{0,1\}$, and we wish to estimate $K = #\{x : f(x) = 1\}$ to within a factor of $1+\epsilon$ (with high probability), while minimizing the…

Quantum Physics · Physics 2020-10-12 Ramgopal Venkateswaran , Ryan O'Donnell

Quantum computing is a promising new area of computing with quantum algorithms offering a potential speedup over classical algorithms if fault tolerant quantum computers can be built. One of the first applications of the classical computer…

Quantum Physics · Physics 2023-03-09 Michael McGuigan

Quantum symmetrization is the task of transforming a non-strictly increasing list of $n$ integers into an equal superposition of all permutations of the list (or more generally, performing this operation coherently on a superposition of…

Quantum Physics · Physics 2025-05-06 Zhenning Liu , Andrew M. Childs , Daniel Gottesman

We prove lower bounds on the error probability of a quantum algorithm for searching through an unordered list of N items, as a function of the number T of queries it makes. In particular, if T=O(sqrt{N}) then the error is lower bounded by a…

Quantum Physics · Physics 2007-05-23 Harry Buhrman , Ronald de Wolf

In imaging inverse problems, we would like to know how close the recovered image is to the true image in terms of full-reference image quality (FRIQ) metrics like PSNR, SSIM, LPIPS, etc. This is especially important in safety-critical…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Jeffrey Wen , Rizwan Ahmad , Philip Schniter
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