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The quantum adversary method is one of the most successful techniques for proving lower bounds on quantum query complexity. It gives optimal lower bounds for many problems, has application to classical complexity in formula size lower…

量子物理 · 物理学 2017-01-10 Peter Hoyer , Troy Lee , Robert Spalek

The quantum adversary method is a versatile method for proving lower bounds on quantum algorithms. It yields tight bounds for many computational problems, is robust in having many equivalent formulations, and has natural connections to…

量子物理 · 物理学 2007-05-23 Peter Hoyer , Troy Lee , Robert Spalek

In this paper, we study the following variant of the junta learning problem. We are given oracle access to a Boolean function $f$ on $n$ variables that only depends on $k$ variables, and, when restricted to them, equals some predefined…

量子物理 · 物理学 2014-10-29 Aleksandrs Belovs

We present a new variant of the quantum adversary method. All adversary methods give lower bounds on the quantum query complexity of a function by bounding the change of a progress function caused by one query. All previous variants…

量子物理 · 物理学 2007-05-23 Robert Spalek

The (negative-weighted) quantum adversary bound is a tight characterisation of the quantum query complexity for any partial function. We analyse the extent to which this bound can be generalised. Ambainis et al. [arXiv:1012.2112] and Lee et…

量子物理 · 物理学 2015-04-28 Aleksandrs Belovs

This note complements the paper "One-Way Ticket to Las Vegas and the Quantum Adversary" (arxiv:2301.02003). I develop the ideas behind the adversary bound - universal algorithm duality therein in a different form, using the same perspective…

量子物理 · 物理学 2023-02-23 Duyal Yolcu

The general adversary bound is a semi-definite program (SDP) that lower-bounds the quantum query complexity of a function. We turn this lower bound into an upper bound, by giving a quantum walk algorithm based on the dual SDP that has query…

量子物理 · 物理学 2016-11-17 Ben W. Reichardt

The general adversary dual is a powerful tool in quantum computing because it gives a query-optimal bounded-error quantum algorithm for deciding any Boolean function. Unfortunately, the algorithm uses linear qubits in the worst case, and…

量子物理 · 物理学 2023-06-28 Michael Czekanski , Shelby Kimmel , R. Teal Witter

Text classifiers are vulnerable to adversarial examples -- correctly-classified examples that are deliberately transformed to be misclassified while satisfying acceptability constraints. The conventional approach to finding adversarial…

计算与语言 · 计算机科学 2024-05-21 Tom Roth , Inigo Jauregi Unanue , Alsharif Abuadbba , Massimo Piccardi

We give a new version of the adversary method for proving lower bounds on quantum query algorithms. The new method is based on analyzing the eigenspace structure of the problem at hand. We use it to prove a new and optimal strong direct…

量子物理 · 物理学 2007-05-23 Andris Ambainis , Robert Spalek , Ronald de Wolf

We describe a method to upper bound the quantum query complexity of Boolean formula evaluation problems, using fundamental theorems about the general adversary bound. This nonconstructive method can give an upper bound on query complexity…

量子物理 · 物理学 2013-05-20 Shelby Kimmel

The Element Distinctness problem is to decide whether each character of an input string is unique. The quantum query complexity of Element Distinctness is known to be $\Theta(N^{2/3})$; the polynomial method gives a tight lower bound for…

量子物理 · 物理学 2014-08-04 Ansis Rosmanis

The approximate degree of a Boolean function f is the least degree of a real polynomial that approximates f pointwise to error at most 1/3. Approximate degree is known to be a lower bound on quantum query complexity. We resolve or nearly…

量子物理 · 物理学 2019-08-20 Mark Bun , Robin Kothari , Justin Thaler

The current paper studies the problem of agnostic $Q$-learning with function approximation in deterministic systems where the optimal $Q$-function is approximable by a function in the class $\mathcal{F}$ with approximation error $\delta \ge…

机器学习 · 计算机科学 2020-02-18 Simon S. Du , Jason D. Lee , Gaurav Mahajan , Ruosong Wang

Quantum state learning is a fundamental problem in physics and computer science. As near-term quantum devices are error-prone, it is important to design error-resistant algorithms. Apart from device errors, other unexpected factors could…

量子物理 · 物理学 2025-08-20 Maryam Aliakbarpour , Vladimir Braverman , Nai-Hui Chia , Yuhan Liu

We propose a new method for proving lower bounds on quantum query algorithms. Instead of a classical adversary that runs the algorithm with one input and then modifies the input, we use a quantum adversary that runs the algorithm with a…

量子物理 · 物理学 2007-05-23 Andris Ambainis

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 $\frac{1 - 2\sqrt{\epsilon}}{2} \rho_f N = \frac{1 - 2\sqrt{\epsilon}}{2} \bar{S}_f$…

量子物理 · 物理学 2007-05-23 Yaoyun Shi

In the thesis, we use a recently developed tight characterisation of quantum query complexity, the adversary bound, to develop new quantum algorithms and lower bounds. Our results are as follows: * We develop a new technique for the…

量子物理 · 物理学 2014-02-18 Aleksandrs Belovs

We investigate query-to-communication lifting theorems for models related to the quantum adversary bounds. Our results are as follows: 1. We show that the classical adversary bound lifts to a lower bound on randomized communication…

量子物理 · 物理学 2020-12-08 Anurag Anshu , Shalev Ben-David , Srijita Kundu

Quantum query complexity is known to be characterized by the so-called quantum adversary bound. While this result has been proved in the standard discrete-time model of quantum computation, it also holds for continuous-time (or…

量子物理 · 物理学 2015-07-01 Mathieu Brandeho , Jérémie Roland
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