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Related papers: Watermarking of Quantum Circuits

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Despite the tremendous success, deep neural networks are exposed to serious IP infringement risks. Given a target deep model, if the attacker knows its full information, it can be easily stolen by fine-tuning. Even if only its output is…

Computer Vision and Pattern Recognition · Computer Science 2021-03-09 Jie Zhang , Dongdong Chen , Jing Liao , Weiming Zhang , Huamin Feng , Gang Hua , Nenghai Yu

As quantum technology matures, the efficient benchmarking of quantum devices remains a key challenge. Although sample-efficient, information-theoretic benchmarking techniques have recently been proposed, there is still a gap in adapting…

Quantum Physics · Physics 2025-10-22 Ana Silva , Eliska Greplova

Semiconductor intellectual property (IP) theft incurs hundreds of billions in annual losses, driven by advanced reverse engineering (RE) techniques. Traditional ``cryptic'' IC camouflaging methods typically focus on hiding localized gate…

Cryptography and Security · Computer Science 2026-03-30 Junling Fan , David Koblah , Domenic Forte

Ownership verification for neural networks is important for protecting these models from illegal copying, free-riding, re-distribution and other intellectual property misuse. We present a novel methodology for neural network ownership…

Cryptography and Security · Computer Science 2023-06-27 Feisi Fu , Wenchao Li

To guarantee the normal functioning of quantum devices in different scenarios, appropriate benchmarking tool kits are quite significant. Inspired by the recent progress on quantum state verification, here we establish a general framework of…

Quantum Physics · Physics 2020-07-01 Pei Zeng , You Zhou , Zhenhuan Liu

We initiate the systematic study of QMA algorithms in the setting of property testing, to which we refer as QMA proofs of proximity (QMAPs). These are quantum query algorithms that receive explicit access to a sublinear-size untrusted proof…

Quantum Physics · Physics 2022-10-17 Marcel Dall'Agnol , Tom Gur , Subhayan Roy Moulik , Justin Thaler

In quantum computation, series of quantum gates have to be arranged in a predefined sequence that led to a quantum circuit in order to solve a particular problem. What if the sequence of quantum gates is known but both the problem to be…

General Finance · Quantitative Finance 2015-07-13 Ovidiu Racorean

The efficient certification of classically intractable quantum devices has been a central research question for some time. However, to observe a "quantum advantage", it is believed that one does not need to build a large scale universal…

Quantum Physics · Physics 2018-03-05 Daniel Mills , Anna Pappa , Theodoros Kapourniotis , Elham Kashefi

Accurate and robust quantum process tomography (QPT) is crucial for verifying quantum gates and diagnosing implementation faults in experiments aimed at building universal quantum computers. However, the reliability of QPT protocols is…

The problem of simulatability of quantum processes using classical resources plays a cornerstone role for quantum computing. Quantum circuits can be simulated classically, e.g., using Monte Carlo sampling techniques applied to…

Quantum Physics · Physics 2024-02-09 Denis A. Kulikov , Vsevolod I. Yashin , Aleksey K. Fedorov , Evgeniy O. Kiktenko

A quantum encryption scheme (also called private quantum channel, or state randomization protocol) is a one-time pad for quantum messages. If two parties share a classical random string, one of them can transmit a quantum state to the other…

Quantum Physics · Physics 2007-05-23 Andris Ambainis , Adam Smith

The central challenge of quantum computing is implementing high-fidelity quantum gates at scale. However, many existing approaches to qubit control suffer from a scale-performance trade-off, impeding progress towards the creation of useful…

The recent explosion of high-quality language models has necessitated new methods for identifying AI-generated text. Watermarking is a leading solution and could prove to be an essential tool in the age of generative AI. Existing approaches…

Cryptography and Security · Computer Science 2024-10-25 Miranda Christ , Sam Gunn , Tal Malkin , Mariana Raykova

Deep neural networks have recently achieved significant progress. Sharing trained models of these deep neural networks is very important in the rapid progress of researching or developing deep neural network systems. At the same time, it is…

Computer Vision and Pattern Recognition · Computer Science 2018-02-07 Yusuke Uchida , Yuki Nagai , Shigeyuki Sakazawa , Shin'ichi Satoh

We introduce spectral quantum tomography, a simple method to extract the eigenvalues of a noisy few-qubit gate, represented by a trace-preserving superoperator, in a SPAM-resistant fashion, using low resources in terms of gate sequence…

Quantum Physics · Physics 2020-02-19 Jonas Helsen , Francesco Battistel , Barbara M. Terhal

Intellectual property (IP) piracy has become a non-negligible problem as the integrated circuit (IC) production supply chain is becoming increasingly globalized and separated that enables attacks by potentially untrusted attackers. Logic…

Graph-structured datasets are increasingly central to sensitive applications spanning social networks, biomedical research, and cryptographic systems. As organizations share these datasets with trusted parties for collaborative analysis,…

Cryptography and Security · Computer Science 2026-03-12 Alexander Nemecek , Emre Yilmaz , Erman Ayday

We present a so-called fuzzy watermarking scheme based on the relative frequency of error in observing qubits in a dissimilar basis from the one in which they were written. Then we discuss possible attacks on the system and speculate on how…

Quantum Physics · Physics 2007-05-23 G Gordon Worley

I've been building Powerpoint-based quantum computers with electron spins in silicon for 20 years. Unfortunately, real-life-based quantum dot quantum computers are harder to implement. Materials, fabrication, and control challenges still…

Mesoscale and Nanoscale Physics · Physics 2021-11-24 Charles Tahan

Although quantum circuit depth is commonly used to approximate circuit runtimes, it overlooks a prevailing trait of current hardware implementation: different gates have different execution times. Recognizing the potential for…

Quantum Physics · Physics 2025-09-17 Matthew Tremba , Paul Hovland , Ji Liu