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We generalize the PAC (probably approximately correct) learning model to the quantum world by generalizing the concepts from classical functions to quantum processes, defining the problem of \emph{PAC learning quantum process}, and study…

Quantum Physics · Physics 2021-05-20 Kai-Min Chung , Han-Hsuan Lin

Shallow quantum circuits have attracted increasing attention in recent years, due to the fact that current noisy quantum hardware can only perform faithful quantum computation for a short amount of time. The constant-depth quantum circuits…

Quantum Physics · Physics 2025-11-11 Yangjing Dong , Fengning Ou , Penghui Yao

We show a simple reduction which demonstrates the cryptographic hardness of learning a single periodic neuron over isotropic Gaussian distributions in the presence of noise. More precisely, our reduction shows that any polynomial-time…

Machine Learning · Computer Science 2021-09-17 Min Jae Song , Ilias Zadik , Joan Bruna

It is becoming increasingly important to understand the vulnerability of machine learning models to adversarial attacks. In this paper we study the feasibility of robust learning from the perspective of computational learning theory,…

Machine Learning · Computer Science 2019-09-13 Pascale Gourdeau , Varun Kanade , Marta Kwiatkowska , James Worrell

While closed timelike curves (CTCs) are not known to exist, studying their consequences has led to nontrivial insights in general relativity, quantum information, and other areas. In this paper we show that if CTCs existed, then quantum…

Quantum Physics · Physics 2009-11-13 Scott Aaronson , John Watrous

Given a dataset of input states, measurements, and probabilities, is it possible to efficiently predict the measurement probabilities associated with a quantum circuit? Recent work of Caro and Datta (2020) studied the problem of PAC…

Quantum Physics · Physics 2023-06-07 Daniel Liang

The seminal work of Linial, Mansour, and Nisan gave a quasipolynomial-time algorithm for learning constant-depth circuits ($\mathsf{AC}^0$) with respect to the uniform distribution on the hypercube. Extending their algorithm to the setting…

Data Structures and Algorithms · Computer Science 2024-11-07 Adam R. Klivans , Konstantinos Stavropoulos , Arsen Vasilyan

The Fundamental Theorem of PAC Learning asserts that learnability of a concept class $H$ is equivalent to the $\textit{uniform convergence}$ of empirical error in $H$ to its mean, or equivalently, to the problem of $\textit{density…

Machine Learning · Computer Science 2025-03-04 Max Hopkins , Daniel M. Kane , Shachar Lovett , Gaurav Mahajan

We describe a quantum PAC learning algorithm for DNF formulae under the uniform distribution with a query complexity of $\tilde{O}(s^{3}/\epsilon + s^{2}/\epsilon^{2})$, where $s$ is the size of DNF formula and $\epsilon$ is the PAC error…

Quantum Physics · Physics 2011-10-11 Jeffrey C. Jackson , Christino Tamon , Tomoyuki Yamakami

Recent work by Bravyi et al. constructs a relation problem that a noisy constant-depth quantum circuit (QNC$^0$) can solve with near certainty (probability $1 - o(1)$), but that any bounded fan-in constant-depth classical circuit (NC$^0$)…

Quantum Physics · Physics 2021-09-29 Daniel Grier , Nathan Ju , Luke Schaeffer

The relevance of shallow-depth quantum circuits has recently increased, mainly due to their applicability to near-term devices. In this context, one of the main goals of quantum circuit complexity is to find problems that can be solved by…

Quantum Physics · Physics 2026-03-12 Alex Bredariol Grilo , Elham Kashefi , Damian Markham , Michael de Oliveira

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 advantages have been demonstrated in this setting, however, none…

Quantum Physics · Physics 2023-09-21 Wilfred Salmon , Sergii Strelchuk , Tom Gur

We give a polynomial time algorithm that, given copies of an unknown quantum state $\vert\psi\rangle=U\vert 0^n\rangle$ that is prepared by an unknown constant depth circuit $U$ on a finite-dimensional lattice, learns a constant depth…

Quantum Physics · Physics 2025-06-18 Zeph Landau , Yunchao Liu

Classical data encoding is usually treated as a black-box in the oracle-based quantum algorithms. On the other hand, their constructions are crucial for practical algorithm implementations. Here, we open the black-boxes of data encoding and…

Quantum Physics · Physics 2024-04-30 Xiao-Ming Zhang , Xiao Yuan

This paper surveys various results in the field of Quantum Learning theory, specifically focusing on learning quantum-encoded classical concepts in the Probably Approximately Correct (PAC) framework. The cornerstone of this work is the…

Quantum Physics · Physics 2026-02-03 Sagnik Chatterjee

The existence of one-way functions (OWFs) forms the minimal assumption in classical cryptography. However, this is not necessarily the case in quantum cryptography. One-way puzzles (OWPuzzs), introduced by Khurana and Tomer, provide a…

Quantum Physics · Physics 2025-07-03 Taiga Hiroka , Min-Hsiu Hsieh , Tomoyuki Morimae

The circuit class $\mathsf{QAC}^0$ was introduced by Moore (1999) as a model for constant depth quantum circuits where the gate set includes many-qubit Toffoli gates. Proving lower bounds against such circuits is a longstanding challenge in…

Quantum Physics · Physics 2024-07-19 Shivam Nadimpalli , Natalie Parham , Francisca Vasconcelos , Henry Yuen

One of the prominent current challenges in complexity theory is the attempt to prove lower bounds for $TC^0$, the class of constant-depth, polynomial-size circuits with majority gates. Relying on the results of Williams (2013), an appealing…

Computational Complexity · Computer Science 2017-11-07 Roei Tell

The Learning with Errors (\LWE) problem has been widely utilized as a foundation for numerous cryptographic tools over the years. In this study, we focus on an algebraic variant of the \LWE problem called \emph{Group ring} \LWE ($\GRLWE$).…

Cryptography and Security · Computer Science 2026-03-11 Jiaqi Liu , Fang-Wei Fu

Quantum magic is a necessary resource for quantum computers to be not efficiently simulable by classical computers. Previous results have linked the amount of quantum magic, characterized by the number of $T$ gates or stabilizer rank, to…

Quantum Physics · Physics 2025-02-07 Yifan Zhang , Yuxuan Zhang